Coronavirus disease 2019 (COVID-19) is often associated with thrombosis. Elevated levels of soluble C-type lectin-like receptor 2 (sCLEC-2), a biomarker for platelet activation, have been reported in COVID-19. Therefore, we examined the behavior of sCLEC-2 levels and their relationship with thrombosis.The clinical course of inflammatory and thrombotic biomarkers was assessed in 271 patients with COVID-19.Inflammatory biomarkers such as C-reactive protein, procalcitonin, and presepsin levels were significantly increased in patients with COVID-19, and these behaviors differed among the clinical course or stages. The plasma D-dimer levels increased slightly and gradually. Platelet counts were within the normal range, and plasma sCLEC-2 levels were markedly increased in most patients with COVID-19. There were 17 patients with thrombosis in this study. Although there was no significant difference in various biomarkers between COVID-19 patients with and without thrombosis, the super formula of sCLEC-2xD-dimer/platelet count in patients with thrombosis was significantly higher than in those without thrombosis. Furthermore, this super formula was significantly higher in COVID-19 patients with severe or critical illness than in those with mild or moderate illness.Elevation of the super formula of sCLEC-2xD-dimer/platelet count was associated with the thrombosis in patients with COVID-19 suggesting the thrombosis in COVID-19 may be caused by the development of microthrombosis.

The COVID-19 pandemic began in March 2020 and has affected many countries and infected over a million people. It has had a serious impact on people's physical and mental health, daily life and the global economy. Today, many drugs show limited efficacy in the treatment of COVID-19 and studies to develop effective drugs continue. Here, we aim to the synthesise and characterise of the flavonol-3-O-glycoside derivatives, the following and evaluated molecular docking studies with antimicrobial activity, inhibition of SARS-CoV-2 main protease enzyme (3CLpro) and nuclease activity. Molecular docking simulations of the synthesized flavonol-3-O-glycoside derivatives, especially compounds 5a, 5d, 5h, 5i and 5m, showed a stronger interaction with SARS-CoV-2 3CLpro in the active site. Two compounds from the target compounds, 5h and 5m, were found to be specifically effective against M. smegmatis and yeasts. In particular, compounds 5a, 5d, 5h, 5i and 5m, which exhibited high activity against the SARS-CoV-2 main protease enzyme, were found to be effective at low concentrations. We determined the IC50 values for the compounds that showed an inhibitory effect as well as their nuclease activities, which further emphasising the potential of our results. Among these, compound 5d showed a significant competitive inhibitor of 3CLpro. Furthermore, nuclease activity studies identified compound 5d as the most potent. The above results suggest that the flavonol-3-O-glycoside derivatives could be promising new antiviral agents for the development of 3CLpro inhibitors to combat COVID-19.

Early prognostic prediction is crucial for determining appropriate clinical interventions. Previous single-omics models had limitations, such as high contingency and overlooking complex physical conditions. In this paper, we introduced multi-omics graph knowledge representation to predict in-hospital outcomes for pneumonia patients. This method utilizes CT imaging and three non-imaging omics information, and explores a knowledge graph for modeling multi-omics relations to enhance the overall information representation. For imaging omics, a multichannel pyramidal recursive MLP and Longformer-based 3D deep learning module was developed to extract depth features in lung window, while radiomics features were simultaneously extracted in both lung and mediastinal windows. Non-imaging omics involved the adoption of laboratory, microbial, and clinical indices to complement the patient's physical condition. Following feature screening, the similarity fusion network and graph convolutional network (GCN) were employed to determine omics similarity and provide prognostic prediction. The results of comparative experiments and generalization validation demonstrat that the proposed multi-omics GCN-based prediction model has good robustness and outperformed previous single-type omics, classical machine learning, and previous deep learning methods. Thus, the proposed multi-omics graph knowledge representation model enhances early prognostic prediction performance in pneumonia, facilitating a comprehensive assessment of disease severity and timely intervention for high-risk patients.

Background: Epilepsy is a common neurological disorder in children, associated with significant morbidity and socioeconomic burden. The coronavirus disease 2019 (COVID-19) pandemic disrupted healthcare delivery, potentially exacerbating seizure control among pediatric epilepsy patients. This study aimed to evaluate the pandemic's impact on seizure characteristics and identify risk factors contributing to seizure exacerbation in children with epilepsy. Methods: A retrospective cohort study was conducted using medical records of 84 pediatric epilepsy patients at The Catholic University of Korea Yeouido St. Mary's Hospital from July 2019 to July 2022. Data were collected on demographics, epilepsy characteristics, and healthcare accessibility. Changes in seizure outcomes were analyzed alongside potential risk factors, including infections and socioeconomic variables. Statistical analyses assessed correlations between these factors and seizure exacerbations. Results: Among the 84 pediatric epilepsy patients, 25% experienced significant seizure exacerbations during the COVID-19 pandemic. These included increased seizure frequency (18%), prolonged duration (13%), emergence of new seizure types (4%), and status epilepticus requiring hospitalization (5%). Multivariate analysis identified recent epilepsy diagnosis (<1 year) and low socioeconomic status as independent predictors of seizure worsening (p < 0.05). Infections with non-COVID-19 respiratory viruses, such as RSV and influenza, were strongly associated with exacerbated seizure activity (p < 0.001). Dissatisfaction with access to epilepsy care further increased the risk of poor seizure control, reflecting the challenges posed by disrupted healthcare systems. Notably, no significant relationship was observed between SARS-CoV-2 infection and seizure outcomes, suggesting that indirect factors, rather than direct viral effects, were primary contributors to seizure exacerbation. Conclusions: This study highlights the compounded impact of disrupted healthcare access, socioeconomic challenges, and respiratory viral infections on seizure control during the COVID-19 pandemic. Strategies such as telehealth expansion, regular monitoring, and vaccination against respiratory pathogens are essential to optimize seizure management in future health crises.

Acute respiratory distress syndrome (ARDS) is a life-threatening type of acute lung injury (ALI) characterized by elevated mortality rates and long-term effects. To date, no pharmacological treatment has proven effective for ARDS. Mesenchymal stem cell-derived apoptotic vesicles (apoVs) were recently found to have excellent therapeutic potential for inflammatory diseases. In this study, our aim was to investigate the therapeutic effects and underlying mechanisms of apoVs in ALI.

ALI was induced in mice through intratracheal instillation of lipopolysaccharide (LPS). ApoVs were then administered two hours post-induction, and their impacts on platelet activation, neutrophil infiltration, and NETosis were assessed. Additionally, the role of CD73 in mediating these effects was thoroughly investigated.

ApoVs inhibit platelet activation, thereby impeding the infiltration of neutrophils into the lung and the initiation of NETosis, ultimately alleviating ALI. Remarkably, apoVs were enriched with CD73, which was critical for apoV-mediated repression of platelet activation and neutrophil NETosis, as well as the therapeutic effects observed in lung injury.

This study reveals that apoVs inhibit platelet activity and neutrophil NETosis via CD73, offering an innovative and effective cell-free therapeutic strategy for ALI/ARDS.

Current clinical care relies heavily on complex, rule-based systems for tasks like diagnosis and treatment. However, these systems can be cumbersome and require constant updates. This study explores the potential of the large language model (LLM), LLaMA 2, to address these limitations. We tested LLaMA 2's performance in interpreting complex clinical process models, such as Mayo Clinic Care Pathway Models (CPMs), and providing accurate clinical recommendations. LLM was trained on encoded pathways versions using DOT language, embedding them with SentenceTransformer, and then presented with hypothetical patient cases. We compared the token-level accuracy between LLM output and the ground truth by measuring both node and edge accuracy. LLaMA 2 accurately retrieved the diagnosis, suggested further evaluation, and delivered appropriate management steps, all based on the pathways. The average node accuracy across the different pathways was 0.91 (SD ± 0.045), while the average edge accuracy was 0.92 (SD ± 0.122). This study highlights the potential of LLMs for healthcare information retrieval, especially when relevant data are provided. Future research should focus on improving these models' interpretability and their integration into existing clinical workflows.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and first identified in Wuhan, China, in December 2019, has led to global efforts in vaccination to mitigate rising morbidity and mortality, with vaccines proving crucial in controlling the pandemic. This study evaluated the humoral responses to the inactivated virus vaccine Sinopharm or Koxing Kerlafor, the protein subunit vaccine ZF001, and the adenoviral vector vaccine Convidecia after 18 months of inactivated virus vaccination by heterologous and homologous booster vaccination in patients with previous SARS-CoV-2 infection and healthy individuals. We discovered that patients who had recovered from the infection and then received a third vaccine dose (booster) exhibited durable immunity. Furthermore, the heterologous booster vaccine induced higher neutralizing antibody responses compared with the homologous booster. These findings offer valuable insights into the efficacy of different COVID-19 vaccine strategies following booster immunization.

The reverse transcription-polymerase chain reaction (RT-PCR) test to detect SARS-CoV-2, the virus causing COVID-19, has been regarded as the diagnostic gold standard. However, the excessive sensitivity of RT-PCR may cause false-positive outcomes from contamination. Again, its technical complexity increases the chances of false-negatives due to pre-analytical and analytical errors. This narrative review explores the elements contributing to inaccurate results during the COVID-19 pandemic and offers strategies to minimize these errors. False-positive results may occur due to specimen contamination, non-specific primer binding, residual viral RNA, and false-negatives, which may arise from improper sampling, timing, labeling, storage, low viral loads, mutations, and faulty test kits. Proposed mitigation strategies to enhance the accuracy of RT-PCR testing include comprehensive staff training in specimen collection, optimizing the timing of tests, analyzing multiple gene targets, incorporating clinical findings, workflow automation, and implementing stringent contamination control measures. Identifying and rectifying sources of error in RT-PCR diagnosis through quality control and standardized protocols is imperative for ensuring quality patient care and effective epidemic control.

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, is a severe disease in older adults and in individuals with associated comorbidities such as diabetes mellitus. Patients with diabetes infected with SARS-CoV-2 are more likely to develop severe pneumonia, hospitalization, and mortality compared with infected non-diabetic patients. During diabetes, hyperglycemia contributes to the maintenance of a low-grade inflammatory state which has been implicated in the microvascular and macrovascular complications associated with this pathology. The receptor for advanced glycation end products (RAGE) is a multi-ligand pattern recognition receptor, expressed on a wide variety of cells, which participates as an important mediator of inflammatory responses in many diseases, including lung diseases. This review highlights the role of RAGE in the pathophysiology of COVID-19 with special emphasis on diabetic patients. These data could explain the severity of the disease, positioning it as a key therapeutic target in the clinical management of this infection.

This study explores the association of vitamin D-binding protein (VDBP) gene polymorphisms, vitamin D levels, and the severity of COVID-19, including the need for intensive care unit (ICU) hospitalization. We analyzed a cohort of 56 consecutive age- and gender-matched adult COVID-19-positive patients and categorized them into three groups: outpatients with mild illness, inpatients with moderate disease, and ICU patients. We measured levels of free, total, and bioavailable 25-hydroxyvitamin D [25(OH)D], VDBP, and albumin. VDBP polymorphisms rs5488 and rs7041 were identified using real-time PCR. A significant proportion of ICU patients were vitamin D-deficient (56.25%) compared to outpatients (10%) and inpatients (5%) (p = 0.0003). ICU patients also had notably lower levels of VDBP (median: 222 mg/L) and total 25(OH)D (median: 18.8 ng/mL). Most patients carried heterozygous rs7041 (60.7%) and wild-type rs4588 (58.9%) genotypes. The distribution of rs7041 SNP varied significantly among groups (p = 0.0301), while rs4588 SNP distribution did not (p = 0.424). Heterozygous rs4588 patients had significantly lower VDBP levels (p = 0.029) and reduced bioavailable 25(OH)D compared to those with wild-type rs4588 (p = 0.020). Our findings indicate that VDBP gene polymorphisms, particularly rs7041 and rs4588, are associated with vitamin D status and the severity of COVID-19. The lower VDBP levels and bioavailable vitamin D in ICU patients suggest that these genetic variants may influence disease severity and hospitalization needs. These results highlight the potential role of VDBP polymorphisms in COVID-19 severity, suggesting that genetic screening could be valuable in assessing the risk of severe outcomes and guiding personalized treatment strategies.

People experiencing homelessness are at greater risk of exposure and poor health outcomes from COVID-19. However, little data exist on the prevalence and correlates of COVID-19 among homeless populations. To mitigate the spread and severity, uptake of the COVID-19 vaccine is needed. This can be challenging among youth experiencing homelessness who are more likely to be unvaccinated when compared to stably housed youth.

We conducted this study to determine the prevalence and correlates of COVID-19 among youth experiencing homelessness.

We examined experiences of COVID-19 symptoms, self-report of infection, and rates of COVID-19 antibodies and distinguished between natural and vaccinated immunity among youth experiencing homelessness ( N = 265) recruited in one large metropolitan area in the south.

Based on self-report, very few participants experienced any symptoms, and 80% had never been diagnosed with COVID-19. Of those with COVID-19 antibodies (68%), the proportion with antibodies resulting from natural infection was 44%. The vaccination rate was 42%. Younger and vaccinated participants and those in shelters were likelier to have COVID-19 antibodies. Black and Hispanic youth were more likely than White youth to have had COVID-19. Those who adopted only one or two prevention behaviors were more likely to acquire a natural infection than those who adopted three or more prevention behaviors.

Youth experiencing homelessness report low vaccination rates, disrupted access to healthcare and social supports, and underlying chronic conditions, which may explain why they face poorer outcomes when infected with COVID-19. Vaccination and risk mitigation strategies to combat the high prevalence of COVID-19 are especially needed for sheltered youth who are at high risk yet are often asymptomatic.

Wearing a mask was a crucial component in slowing the COVID-19 pandemic. However, little is known about the intersectionality between mask usage, risk perception, and infection. The purpose of this study was to investigate whether risk perceptions and masking behaviors are associated with contracting SARS-CoV-2 and how contracting SARS-CoV-2 subsequently changes masking behaviors in specific situations.

This cohort study utilized survey data from the UC San Diego ZAP COVID-19 study (n = 1,230) to evaluate the risk of contracting SARS-CoV-2 in relation to baseline risk perceptions and masking behaviors in various situations and how contracting SARS-CoV-2 affects subsequent masking behavior.

We found that more consistent self-reported mask use in indoor public spaces (p = 0.03) and in other people's houses (p = 0.002) was associated with remaining free of SARS-CoV-2 infection. We also found that contracting SARS-CoV-2 was associated with a subsequent increase in mask use in other people's houses (p = 0.01).

Our findings suggest that consistent mask use is correlated with decreased infection and that contracting SARS-CoV-2 may modify mask use behaviors in high-risk situations. These findings may help inform future public health messaging for infectious disease prevention.

This study has not been previously registered as it is an observational study. There was no pre-registration of the analytic plan for the present study.

In this study, a deep quantum neural network (DQNN) based on the Lion-based Coot algorithm (LBCA-based Deep QNN) is employed to predict COVID-19. Here, the genome sequences are subjected to feature extraction. The fusion of features is performed using the Bray-Curtis distance and the deep belief network (DBN). Lastly, a deep quantum neural network (Deep QNN) is used to predict COVID-19. The LBCA is obtained by integrating Coot algorithm and LOA. The COVID-19 predictions are done with mutation points. The LBCA-based Deep QNN outperformed with testing accuracy of 0.941, true positive rate of 0.931, and false positive rate of 0.869.

At present, COVID-19 remains a public health concern due to the ongoing evolution of SARS-CoV-2 and its prevalence in particular countries. This paper provides an updated overview of the epidemiology and pathogenesis of COVID-19, with a focus on the emergence of SARS-CoV-2 variants and the phenomenon known as 'long COVID'. Meanwhile, diagnostic and detection advances will be mentioned. Though many inventions have been made to combat the COVID-19 pandemic, some outstanding ones include multiplex RT-PCR, which can be used for accurate diagnosis of SARS-CoV-2 infection. ELISA-based antigen tests also appear to be potential diagnostic tools to be available in the future. This paper also discusses current treatments, vaccination strategies, as well as emerging cell-based therapies for SARS-CoV-2 infection. The ongoing evolution of SARS-CoV-2 underscores the necessity for us to continuously update scientific understanding and treatments for it.

A focus on water quality has intensified globally, considering its critical role in sustaining life and ecosystems. Wastewater, reflecting societal development, profoundly impacts public health. Wastewater-based epidemiology (WBE) has emerged as a surveillance tool for detecting outbreaks early, monitoring infectious disease trends, and providing real-time insights, particularly in vulnerable communities. WBE aids in tracking pathogens, including viruses, in sewage, offering a comprehensive understanding of community health and lifestyle habits. With the rise in global COVID-19 cases, WBE has gained prominence, aiding in monitoring SARS-CoV-2 levels worldwide. Despite advancements in water treatment, poorly treated wastewater discharge remains a threat, amplifying the spread of water-, sanitation-, and hygiene (WaSH)-related diseases. WBE, serving as complementary surveillance, is pivotal for monitoring community-level viral infections. However, there is untapped potential for WBE to expand its role in public health surveillance. This review emphasizes the importance of WBE in understanding the link between viral surveillance in wastewater and public health, highlighting the need for its further integration into public health management.

There are limited studies comparing the health utility values of EQ-5D-5L and SF-6Dv2 within the same patient cohorts. The widespread transmission and recurring infections associated with Omicron variants amid the COVID-19 pandemic have resulted in substantial health detriments and increased utilisation of health care resources. This highlights the crucial need to assess the loss in quality-adjusted life years (QALYs). Therefore, this study aims to compare the ceiling and floor effects, agreement, correlation and responsiveness between EQ-5D-5L and SF-6Dv2 based on COVID-19 patients during the Omicron outbreak in China.

We recruited 694 COVID-19 patients across mainland China to participant in an online questionnaire survey from January to February 2023. The questionnaire encompassed queries concerning the sociodemographic and health details of the participants, who were requested to recollect their health status during and after experiencing COVID-19 using the EQ-5D-5L and SF-6Dv2 questionnaires. Epanechnikov kernel density plots were used to visualise the ceiling and floor effects for both instruments. Agreement was assessed by Bland-Altman graph and intraclass correlation coefficient (ICC). Correlation was evaluated using linear regression, Pearson's correlation and Spearman's correlation. The standardised response mean (SRM) and relative efficiency (RE) were used to examine the responsiveness of EQ-5D-5L and SF-6Dv2 at detecting the health improvement after COVID-19 infection and the difference in dichotomous health indicators.

In total, 648 valid responses from patients aged 35.6 ± 15.0 years were involved in analysis. The EQ-5D-5L utility indices were 0.58 ± 0.33 and 0.92 ± 0.14 during and after COVID-19 infection, respectively, which were significantly higher than indices of the SF-6Dv2 utility (0.43 ± 0.31 and 0.81 ± 0.19, p < 0.001). A ceiling effect of EQ-5D-5L larger than that of SF-6Dv2 was observed during COVID-19 infection (49.5% vs 21.6%). Intraclass correlation coefficients between EQ-5D-5L and SF-6Dv2 during and after COVID-19 infection were 0.69 and 0.55, respectively. The utility indices of EQ-5D-5L and SF-6Dv2 were highly correlated, with Pearson's correlation coefficients of 0.76 and 0.70 (p < 0.001) during and after COVID-19 infection, respectively. The spearman's correlations were moderate to high between dimensions of EQ-5D-5L and SF-6Dv2 (p < 0.01). Both EQ-5D-5L and SF-6Dv2 were responsive to detect health improvement after COVID-19 and the differences in dichotomous health indicators.

The utility indices generated by EQ-5D-5L and SF-6Dv2 in COVID-19 patients demonstrate strong correlation and responsiveness. However, the agreement between these two instruments does not reach a satisfactory level. Consequently, these two measures cannot be used interchangeably. In situations where apprehensions about ceiling effects affecting outcome measurement arise, it is advisable to consider SF-6Dv2 as a preferable outcome measure for studies on patients with COVID-19.

Background and purpose. Coronavirus (COVID-19) is a contagious disease causing severe acute respiratory syndrome which had a catastrophic effect on the world population and resulted in more than 2.9 million deaths worldwide. Epidemiological investigations have recently announced blood type has an association with the incidence of COVID-19 infection. Consequently, research in this regard can be effective in determining a person's susceptibility to a viral infection. Therefore, we investigated the relationship between blood types and the risk of COVID-19 in patients admitted to Khorshid laboratory, Tehran, Iran. Materials and methods. From January to March 2020, 50 nasal and throat swapb samples of patients' secretions were obtained from patients who were admitted to Khorshid laboratory. They were confirmed to have COVID-19 virus RNA and real-time polymerase chain reaction (PCR)-ABI, and their blood type was determined simultaneously. After collecting data to determine the relationship between COVID-19 infection and blood type, a confidence interval of 90 % was considered using SPSS 16. Results. The mean age of the patients was measured at 38.4±6.3 years. According to PCR results, 100 % of the subjects with COVID-19 showed blood type A. In addition, the ratio of blood type A to the percentage of reference type O was higher (P=0.009). Conclusion. There was a significant relationship between ABO blood type and susceptibility to COVID-19. As the current study suggests, those with blood type A are at a higher COVID-19 infection risk than those with blood type O.

Zinc is an important trace element for growth and health at pediatric ages. Zinc is fundamental in inflammatory pathways, oxidative balance, and immune function. Zinc exhibits anti-inflammatory properties by modulating Nuclear Factor-kappa (NF-κB) activity and reducing histamine release from basophils, leukocytes, and mast cells. Furthermore, its antioxidant activity protects against oxidative damage and chronic diseases. Finally, zinc improves the ability to trigger effective immune responses against pathogens by contributing to the maturation of lymphocytes, the production of cytokines, and the regulation of apoptosis. Given these properties, zinc can be considered an adjunctive therapy in treating and preventing respiratory, nephrological, and gastrointestinal diseases, both acute and chronic. This review aims to deepen the role and metabolism of zinc, focusing on the role of supplementation in developed countries in pediatric diseases.

Tuberculosis (TB) control has been a challenge in the country and its overall health impact remains significant. COVID-19 has caused significant morbidity and mortality especially among hospitalized patients. TB and COVID-19 co-infection (COVID-TB) may cause more catastrophic consequences and outcomes among afflicted individuals and management may be daunting. There is limited local data on COVID-TB.

The clinical profile of COVID-TB patients who were admitted were described. Comparison of the clinical outcomes was also done versus the general admitted COVID-19 patients without concomitant TB in the same institution. Relevant patient outcomes were reported which included admission to an intensive care unit (ICU), length of hospital stay, and mortality rate.

This is a descriptive study on the demographics and clinical outcomes of patients admitted in the Philippine General Hospital (PGH) for COVID-19 with TB co-infection from March 2020 to September 2020. We aimed to characterize patients with COVID-TB and analyzed their outcomes.

There was a total of 79 patients who were admitted for COVID-19 (confirmed with RT-PCR) with TB co-infection during the study period. Majority of them were males (70.9%) with a median age of 54 (IQR 42 to 64) years. In terms of TB affliction, 75 (94.9%) patients were identified to have pulmonary tuberculosis. Majority of patients had at least one co-morbid illness with hypertension (16.5%), diabetes mellitus (13.9%), and heart failure (11.4%) as the most common. Respiratory symptoms (dyspnea and cough) were the predominant presenting complaint during hospital admission. Majority of the patients were classified as severe (8 or 10.1%) and critical (36 or 45.57%) COVID-19 disease. Fifty-six (70.9%) were bacteriologically confirmed tuberculosis. Radiologic imaging studies revealed findings consistent with pulmonary tuberculosis in 70 (88.61%) through plain radiograph. Forty-seven underwent HRCT and 46 of these (97.8%) had findings suggestive of PTB. Overall, 61 patients (77%) subsequently required oxygen supplementation. The in-hospital mortality within the study population was 36.7% (29/79) in contrast to the general COVID patients admitted in the same period which revealed significantly less fatality at 17.5% (35/200). The length of hospital stay was found to be 21.1 days ± 14.75 days across all study patients, and with median of 20 days for surviving patients. TB treatment outcomes were tracked in the 50 surviving COVID-19 patients where cure was declared in 8/50 (16%) while 22/50 (44%) successfully completed their six-month treatment regimen.

This study of COVID-TB provides an initial evaluation of the potential association between active TB infection and COVID-19 severity and mortality. The data generated from this study may be a starting point to assess the interaction of these two diseases. Furthermore, bidirectional screening may be recommended even at hospitals' triage areas since both diseases may have similar presentations.

Background: This study aimed to evaluate the clinical characteristics, patient's management approaches, and outcomes of the COVID-19 patients in Phu Tho Province, Vietnam. Methods: A retrospective, multicenter study of 2166 COVID-19 patients in 13 hospitals in Phutho Province, Vietnam. The subjects were divided into 3 groups based on vaccination status: unvaccinated group, 1st dose of vaccine group, 2nd dose of vaccine group. The clinical characteristics, management approaches, and outcomes were collected and compared between the 3 groups. Results: The hospitalization rate of the 3 groups decreased from the unvaccinated group, the 1st dose of vaccinated group, to the 2nd dose of vaccinated group, 42.61%; 30,24% and 27,15% respectively. The 19-40 years old group had the highest hospitalization rate (38,1%) together with the group that had not accepted the full COVID 19 vaccination dose (57,64%). The 2nd dose of vaccinated group had the lowest percentages of high temperature, cough, dyspnea, chest pain and sore throat. The unvaccinated group had the highest heart rate, respiratory rate and SpO2 compared to the two other groups. The percentage needing Immunomodulation and Anticoagulant Therapy was highest (6.8% and 1.4 % respectively) in the unvaccinated group. The percentage receiving Antiviral Therapy was highest (42,5%) in those who had received the 2nd dose of vaccine. Conclusions: COVID-19 vaccination improved the symptoms of the patients and should be accepted in all ages.

Coronavirus disease 2019 (COVID-19) was considered a major public health burden worldwide. Multiple studies have shown that susceptibility to severe infections and the development of long-term symptoms is significantly influenced by viral and host factors. These findings have highlighted the potential of host genetic markers to identify high-risk individuals and develop target interventions to reduce morbimortality. Despite its importance, genetic host factors remain largely understudied in Latin-American populations. Using a case-control design and a custom next-generation sequencing (NGS) panel encompassing 81 genetic variants and 74 genes previously associated with COVID-19 severity and long-COVID, we analyzed 56 individuals with asymptomatic or mild COVID-19 and 56 severe and critical cases. In agreement with previous studies, our results support the association between several clinical variables, including male sex, obesity and common symptoms like cough and dyspnea, and severe COVID-19. Remarkably, thirteen genetic variants showed an association with COVID-19 severity. Among these variants, rs11385942 (p < 0.01; OR = 10.88; 95% CI = 1.36-86.51) located in the LZTFL1 gene, and rs35775079 (p = 0.02; OR = 8.53; 95% CI = 1.05-69.45) located in CCR3 showed the strongest associations. Various respiratory and systemic symptoms, along with the rs8178521 variant (p < 0.01; OR = 2.51; 95% CI = 1.27-4.94) in the IL10RB gene, were significantly associated with the presence of long-COVID. The results of the predictive model comparison showed that the mixed model, which incorporates genetic and non-genetic variables, outperforms clinical and genetic models. To our knowledge, this is the first study in Colombia and Latin-America proposing a predictive model for COVID-19 severity and long-COVID based on genomic analysis. Our study highlights the usefulness of genomic approaches to studying host genetic risk factors in specific populations. The methodology used allowed us to validate several genetic variants previously associated with COVID-19 severity and long-COVID. Finally, the integrated model illustrates the importance of considering genetic factors in precision medicine of infectious diseases.

COVID-19 may be associated with orthopedic symptoms, including myalgia and joint pain. There are reports of reactive arthritis and acute arthritis diagnosed after COVID-19; however, COVID-19-associated pyogenic arthritis has not been reported.

We treated a young woman with secondary pyogenic hip arthritis that started after COVID-19. The patient was a 23-year-old woman who developed acute pain in the right hip 9 days after being diagnosed with COVID-19. Blood cultures revealed methicillin-sensitive Staphylococcus aureus and contrast-enhanced computed tomography revealed joint effusion in the right hip. Although the joint fluid culture results were negative, we suspected pyogenic arthritis of the hip joint and performed curettage and continuous irrigation of the right hip joint. Intraoperative histopathological examination of the synovial membrane revealed numerous neutrophils with segmental nuclei, consistent with a diagnosis of pyogenic arthritis.

To the best of our knowledge, this is the first report of probable secondary pyogenic hip arthritis in a patient with COVID-19.

The cutting-edge combination of fluvoxamine (FVM) and ivermectin (IVM) has been presented as a proposed dosage form for the treatment of COVID-19 infections in early diagnosed patients. The main objective of this work is to develop simple, sensitive, and efficient methods for the synchronous quantification of FVM and IVM without any prior separation. Four green UV-methods were employed for the synchronous quantification, namely: Fourier functions convolution of absorption spectra, FFAS, Fourier functions convolution of derivative spectra of absorption curves, FFDS, Fourier function convolution of ratio spectra of absorption curves, FFRS and the dual-wavelength method, DWM. FFRS and DWM approaches can be able to reconcile the two components' significantly interfering spectrum presented in this commixture. Good linearity was checked in the range of 5-40, and 2.5-25 μg/mL for the FVM, and IVM, respectively. All approaches developed have been recommended in compliance with ICH principles. Furthermore, the approaches' greenness was predestined by "National Environmental Method Index" (NEMI), "Analytical GREEnness metric (AGREE)", the "Analytical Eco-Scale", and the "Green Analytical Procedure Index" (GAPI). In addition, spider diagram was utilized for the assessment of the greenness index of the solvent used. Beside greenness, the sustainability of our methods was investigated using the HEXAGON tool. Continuing the constant pursuit of greenness, drug-drug interactions (DDIs) between FVM & IVM were predicted by insilico tools to ensure the safety of the suggested mixture as a preliminary step before invitro and in vivo studies. Because they were deemed sustainable, affordable, and successful, the suggested UV-methods may be used for routine quality control investigations of the indicated formulations FVM & IVM.

SARS-CoV-2 has the ability to form large multi-nucleated cells known as syncytia. Little is known about how syncytia affect the dynamics of the infection or severity of the disease. In this manuscript, we extend a mathematical model of cell-cell fusion assays to estimate both the syncytia formation rate and the average duration of the fusion phase for five strains of SARS-CoV-2. We find that the original Wuhan strain has the slowest rate of syncytia formation (6.4×10-4/h), but takes only 4.0 h to complete the fusion process, while the Alpha strain has the fastest rate of syncytia formation (0.36 /h), but takes 7.6 h to complete the fusion process. The Beta strain also has a fairly fast syncytia formation rate (9.7×10-2/h), and takes the longest to complete fusion (8.4 h). The D614G strain has a fairly slow syncytia formation rate (2.8×10-3/h), but completes fusion in 4.0 h. Finally, the Delta strain is in the middle with a syncytia formation rate of 3.2×10-2/h and a fusing time of 6.1 h. We note that for these SARS-CoV-2 strains, there appears to be a tradeoff between the ease of forming syncytia and the speed at which they complete the fusion process.

Recent evidence reported that some dietary compounds like quercetin and apigenin as the most well-known flavonoids with anti-inflammatory effects may inhibit SARS-CoV-2 main protease. The hypothesis of the promising effects and possible mechanisms of action of quercetin against COVID-19 were assessed in this article.

Related papers on the inhibitory effects of quercetin against COVID-19 were collected using the following search strategy: "corona or coronavirus or COVID or COVID-19 or viral or virus" AND "nutrient or flavonoid or Quercetin".

The findings indicated that quercetin can be considered an effective agent against COVID-19 because of its SARS-CoV-2 main protease and RNA-dependent RNA polymerase inhibitory effects. In addition, quercetin may attenuate angiotensin-converting enzyme-2 (ACE-2) receptors leading to a reduction of SARS-CoV-2 ability to enter host cells. Moreover, the antiviral, anti-inflammatory, and immunomodulatory activities of quercetin have been frequently reported.

Quercetin may be an effective agent for managing the complications of COVID-19. Further longitudinal human studies are warranted.

The aim of the study was to investigate the level of fear of the COVID-19 pandemic and to detect a possible correlation between the autistic traits and the level of fear and to learn about other factors that may affect the level of fear.

The study utilised a questionnaire and was conducted online in the period from 16.02.2021 to 11.06.2021. The test group consisted of 214 respondents with an average age of 23.78 years (95%CI: 22.48 - 25.08; max: 61, min: 14) from the general population. The study used The Autism-Spectrum Quotient (AQ) questionnaire to assess the degree of autistic traits in the general population and The Fear of COVID-19 Scale, which was used to assess the level of fear of COVID-19.

Among the respondents, 9 people scored ≥32 on the AQ test and were considered to have a high degree of autistic traits. In multiple regression (R2 = 0.1, p<0.0001), a positive relationship between the severity of fear of COVID-19 and the autistic traits (p=0.01) and age (p<0.001) was obtained. Additionally, a second multiple regression (R2 = 0.1, p<0.000001) including the subscales of AQ was performed and a positive relationship between the severity of fear of COVID-19 and the difficulties in attention switching (p=0.0004) and age (p=0.00001) was obtained.

People with higher autistic traits present greater fear of the COVID-19 pandemic. We suggest that it might be caused by cognitive stiffness and disorders in emotions regulation, according to the literature. The elderly also present higher levels of fear. The other variables did not affect the level of fear of the COVID-19 pandemic.

Telemedicine technologies allow distribution of health-related services and information and can include electronic and telecommunication technologies, remote patient and clinician contact, referral and prescribing, patient education, and monitoring. This systematic review aimed to evaluate publications on the perceptions and management of chronic medical conditions using telehealth remote consultations by primary healthcare professionals between April 2020 and December 2021 during the COVID-19 pandemic. Electronic databases, including Cinhal, PubMed, Science Direct, and ProQuest were searched to extract qualitative studies relevant to the topic. Inclusion criteria were developed based on the Population, Exposure, and Outcomes scoping framework. The target population was healthcare professionals working in primary care settings. Included studies encompassed various types of telemedicine, such as synchronous telemedicine, video conferencing, telephone conversations, and smart devices. Eight studies were included. Synchronous telemedicine was highly effective in ensuring the continuity of care and treatment, providing patients with convenience, improved access to treatment, and earlier disease management. Video conferencing and telephone consultations were the most common methods used. Challenges included concerns about patient privacy, technology literacy, and acceptance. Telemedicine was commended for its ability to provide access to immediate expert medical advice and eliminate the need for long-distance travel, contributing to increased patient compliance. Synchronous telemedicine is a promising solution for managing chronic conditions during and after the COVID-19 pandemic, offering benefits to patients and healthcare professionals. To maximize its potential, concerns regarding patient privacy, confidentiality, and technology literacy need to be addressed. Proper legislation and regulations are required for long-term success of telemedicine, making it a valuable component of healthcare systems.

In recent years, healthcare systems worldwide have faced the challenge of the severe COVID-19 pandemic. However, cases of severe rhabdomyolysis, acute myocardial damage, and multiple organ dysfunction syndrome (MODS) caused by COVID-19 are currently rare. This report presents a case of severe rhabdomyolysis, acute myocardial damage, and MODS caused by COVID-19. The patient was treated at The University of Hong Kong-Shenzhen Hospital. The purpose of this report is to aid clinicians in quickly identifying and treating similar cases, ultimately improving patient outcomes.

Coronavirus disease-19 (COVID-19), a serious pandemic due to the SARS-CoV-2 virus infection, caused significant lockdowns, healthcare shortages, and deaths worldwide. The infection leads to an uncontrolled systemic inflammatory response causing severe respiratory distress and multiple-organ failure. Quick development of several vaccines efficiently controlled the spread of COVID-19. However, the rise of various new subvariants of COVID-19 demonstrated some concerns over the efficacy of existing vaccines. Currently, better vaccines to control these variants are still under development as several new subvariants of COVID-19, such as omicron BA-4, BA-5, and BF-7 are still impacting the world. Few antiviral treatments have been shown to control COVID-19 symptoms. Further, control of COVID-19 symptoms has been explored with many natural and synthetic adjuvant compounds in hopes of treating the deadly and contagious disease. Vitamins have been shown to modulate the immune system, function as antioxidants, and reduce the inflammatory response. Recent studies have investigated the potential role of vitamins, specifically vitamins A, B, C, D, and E, in reducing the immune and inflammatory responses and severity of the complication. In this brief article, we discussed our current understanding of the role of vitamins in controlling COVID-19 symptoms and their potential use as adjuvant therapy.

Worldwide, over 694 million people have been infected with SARS-CoV-2, with an estimated 55-60% of those infected developing COVID-19. Since the beginning of the pandemic in December 2019, different variants of concern have appeared and continue to occur. With the emergence of different variants, an increasing rate of vaccination and previous infections, the acute neurological symptomatology of COVID-19 changed. Moreover, 10-45% of individuals with a history of SARS-CoV-2 infection experience symptoms even 3 months after disease onset, a condition that has been defined as 'post-COVID-19' by the World Health Organization and that occurs independently of the virus variant. The pathomechanisms of COVID-19-related neurological complaints have become clearer during the past 3 years. To date, there is no overt - that is, truly convincing - evidence for SARS-CoV-2 particles in the brain. In this Review, we put special emphasis on discussing the  methodological difficulties of viral detection in CNS tissue and discuss immune-based (systemic and central) effects contributing to COVID-19-related CNS affection. We sequentially review the reported changes to CNS cells in COVID-19, starting with the blood-brain barrier and blood-cerebrospinal fluid barrier - as systemic factors from the periphery appear to primarily influence barriers and conduits - before we describe changes in brain parenchymal cells, including microglia, astrocytes, neurons and oligodendrocytes as well as cerebral lymphocytes. These findings are critical to understanding CNS affection in acute COVID-19 and post-COVID-19 in order to translate these findings into treatment options, which are still very limited.

Developmental coordination disorder (DCD) is a neurodevelopmental disorder that affects children's occupational performance and participation. It is known that the Covid pandemic has adversely affected the whole world in many areas. We aim to investigate the occupational performance and participation of children with DCD before and during the COVID-19.

Sixty-five children aged 5-12 years included in the study were assessed by the Canadian Measure of Occupational Performance and the Participation and Environment Measure for Children and Youth.

Statistically significant differences were detected in occupational performance and satisfaction scores (p < 0.01). Additionally, except for 'involvement in the home environment' (p > 0.05), there were statistically significant differences in all other areas of participation (p < 0.01).

The occupational performance and participation of children with DCD are impacted during COVID-19. In addition, it is seen that the desire of families to change regarding participation has increased due to COVID-19. It would be beneficial to include strategies to improve these areas in the rehabilitation processes.

Monkeypox (Mpox) is a zoonotic disease caused by a virus (monkeypox virus-MPV) belonging to the Poxviridae family. In humans, the disease has an incubation period of 5-21 days and then progresses in two phases, the prodromal phase and the rash phase. The prodromal phase is characterized by non-specific symptoms such as fever, muscle pain, malaise, lymphadenopathy, headache, and chills. Skin lesions appear in the rash phase of the disease. These lesions progress through different stages (macules, papules, vesicles, and pustules). In May 2022, WHO reported an outbreak of human Mpox in several countries which were previously Mpox-free. As per the CDC report of March 01, 2023, a total of 86,231 confirmed cases of Mpox and 105 deaths have been reported from 110 countries and territories across the globe. Notably, more than 90% of these countries were reporting Mpox for the first time. The phylogenetic analysis revealed that this outbreak was associated with the virus from the West African clade. However, most of the cases in this outbreak had no evidence of travel histories to MPV-endemic countries in Central or West Africa. This outbreak was primarily driven by the transmission of the virus via intimate contact in men who have sex with men (MSM). The changing epidemiology of Mpox raised concerns about the increasing spread of the disease in non-endemic countries and the urgent need to control and prevent it. In this chapter, we present all the documented cases of Mpox from 1970 to 2023 and discuss the past, present, and future of MPV.

The conditions in the workplace have a critical influence on the mental health of nurses and their attitudes toward their job, which may impact patient care.

This cross-sectional study aimed to investigate the association between perceptions of the work environment and fear of COVID-19 experienced by nurses.

The data were collected using a demographic data form, the Work Environment Scale (WES), and the Fear of COVID-19 Scale. The study was completed with 183 nurses who provide care to COVID-19 patients.

The mean scores for the WES and Fear of COVID-19 Scale were 63.59±12.35 and 21.98±8.36, respectively. There was a positive correlation between the points acquired from the "employee fears" section of the WES and the Fear of COVID-19 Scale mean ranks (r = 0.22). There was a weak negative correlation between the Fear of COVID-19 score and the WES "job satisfaction" score (r = -0.214). There was a weak negative correlation between the scores of the Fear of COVID-19 Scale and perceived support at work (r = -0.33) and between the WES scores and weekly working hours (r = -0.27). However, there was a weak to moderate positive correlation between the WES scores and number of days off per week (r = 0.45).

Nurses experience a high fear of COVID-19, and a decrease in their attitudes of the work environment was associated with an increased fear of COVID-19. The fear of COVID-19 may be reduced by various interventions to provide support at work and increase nurses' job satisfaction.

Coronavirus Disease 2019 (COVID-19) is a viral infection caused by SARS-CoV-2, which can trigger autoimmune diseases such as antineutrophilic cytoplasmic antibody (ANCA) associated vasculitis (AAV) that affect small and medium-sized blood vessels in multiple organs. This study discusses a case with neuropathy and positive ANCA after COVID-19 infection and reviews the literature on AAV following COVID-19 infection. A 59-year-old man is presented that was referred to Shariati Hospital for evaluation of neurologic problems after a COVID-19 infection. Initially, he had flu-like symptoms. A few days later, he developed right distal upper and lower limb paresthesia. His electromyography (EMG) and nerve conduction velocity (NCV) results were consistent with polyneuropathy. Lumbar puncture (LP) was normal except for positive COVID-19 polymerase chain reaction (PCR). The patient's paresthesia worsened. Laboratory data showed leukocytosis, anemia, thrombocytosis, high erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP). Perinuclear anti-neutrophil cytoplasmic antibody (MPO-ANCA) was positive. According to the results, vasculitis was the main differential diagnosis. The sural nerve biopsy was performed, and the result was consistent with small to medium-sized vessel vasculitis. The patient was diagnosed with COVID-induced AAV. He was prescribed methylprednisolone and cyclophosphamide and was discharged with prednisolone and cotrimoxazole. In this study, a unique case of AAV induced by COVID-19 infection confirmed by nerve biopsy is presented. A review of the literature found 48 cases of new-onset AAV in adults and pediatrics after COVID-19 infection. Further research is needed to completely understand the relationship between COVID-19.

The COVID-19 pandemic has progressed rapidly, with the emergence of new virus variants that pose challenges in treating infected individuals. In Mexico, four epidemic waves have been recorded with varying disease severity. To understand the heterogeneity in clinical presentation over time and the sensitivity and specificity of signs and symptoms in identifying COVID-19 cases, an analysis of the changes in the clinical presentation of the disease was conducted.

To analyze the changes in the clinical presentation of COVID-19 among 3.38 million individuals tested for SARS-CoV-2 at the Mexican Social Security Institute (IMSS) from March 2020 to October 2021 and evaluate the predictivity of signs and symptoms in identifying COVID-19 cases.

A retrospective analysis of clinical presentation patterns of COVID-19 among individuals treated at IMSS was performed, contrasting the signs and symptoms among SARS-CoV-2-positive individuals with those who tested negative for the virus but had respiratory infection symptoms. The sensitivity and specificity of each sign and symptom in identifying SARS-CoV-2 infection were estimated.

The set of signs and symptoms reported for COVID-19-suspected patients treated at IMSS were not highly specific for SARS-CoV-2 positivity. The signs and symptoms exhibited variability based on age and epidemic wave. The area under the receiver operating characteristic (ROC) curve was 0.62 when grouping the five main symptoms (headache, dyspnea, fever, arthralgia, and cough). Most of the individual symptoms had ROC values close to 0.5 (16 out of 22 between 0.48 and 0.52), indicating non-specificity.

The results highlight the difficulty in making a clinical diagnosis of COVID-19 due to the lack of specificity of signs and symptoms. The variability of clinical presentation over time and among age groups highlights the need for further research to differentiate whether the changes are due to changes in the virus, who is becoming infected, or the population, particularly with respect to prior infection and vaccination status.

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has necessitated reliable and authoritative information for public guidance. The World Health Organization (WHO) has been a primary source of such information, disseminating it through a question and answer format on its official website. Concurrently, ChatGPT 3.5 and 4.0, a deep learning-based natural language generation system, has shown potential in generating diverse text types based on user input.

This study evaluates the accuracy of COVID-19 information generated by ChatGPT 3.5 and 4.0, assessing its potential as a supplementary public information source during the pandemic.

We extracted 487 COVID-19-related questions from the WHO's official website and used ChatGPT 3.5 and 4.0 to generate corresponding answers. These generated answers were then compared against the official WHO responses for evaluation. Two clinical experts scored the generated answers on a scale of 0-5 across 4 dimensions-accuracy, comprehensiveness, relevance, and clarity-with higher scores indicating better performance in each dimension. The WHO responses served as the reference for this assessment. Additionally, we used the BERT (Bidirectional Encoder Representations from Transformers) model to generate similarity scores (0-1) between the generated and official answers, providing a dual validation mechanism.

The mean (SD) scores for ChatGPT 3.5-generated answers were 3.47 (0.725) for accuracy, 3.89 (0.719) for comprehensiveness, 4.09 (0.787) for relevance, and 3.49 (0.809) for clarity. For ChatGPT 4.0, the mean (SD) scores were 4.15 (0.780), 4.47 (0.641), 4.56 (0.600), and 4.09 (0.698), respectively. All differences were statistically significant (P<.001), with ChatGPT 4.0 outperforming ChatGPT 3.5. The BERT model verification showed mean (SD) similarity scores of 0.83 (0.07) for ChatGPT 3.5 and 0.85 (0.07) for ChatGPT 4.0 compared with the official WHO answers.

ChatGPT 3.5 and 4.0 can generate accurate and relevant COVID-19 information to a certain extent. However, compared with official WHO responses, gaps and deficiencies exist. Thus, users of ChatGPT 3.5 and 4.0 should also reference other reliable information sources to mitigate potential misinformation risks. Notably, ChatGPT 4.0 outperformed ChatGPT 3.5 across all evaluated dimensions, a finding corroborated by BERT model validation.

The current understanding of long COVID (LC) is still limited. This review highlights key findings regarding the role of gut microbiota, mitochondria, and the main pathophysiological aspects of LC revealed by clinical studies, related to the complex interplay between infection, intestinal dysbiosis, dysfunctional mitochondria, and systemic inflammation generated in a vicious circle, reflecting the molecular and cellular processes from the "leaky gut" to the "leaky electron transport chain (ETC)" into a quantum leap. The heterogeneity of LC has hindered progress in deciphering all the pathophysiological mechanisms, and therefore, the approach must be multidisciplinary, with a special focus not only on symptomatic management but also on addressing the underlying health problems of the patients. It is imperative to further assess and validate the effects of COVID-19 and LC on the gut microbiome and their relationship to infections with other viral agents or pathogens. Further studies are needed to better understand LC and expand the interdisciplinary points of view that are required to accurately diagnose and effectively treat this heterogeneous condition. Given the ability of SARS-CoV-2 to induce autoimmunity in susceptible patients, they should be monitored for symptoms of autoimmune disease after contracting the viral infection. One question remains open, namely, whether the various vaccines developed to end the pandemic will also induce autoimmunity. Recent data highlighted in this review have revealed that the persistence of SARS-CoV-2 and dysfunctional mitochondria in organs such as the heart and, to a lesser extent, the kidneys, liver, and lymph nodes, long after the organism has been able to clear the virus from the lungs, could be an explanation for LC.

Coronavirus disease 2019 (COVID-19) is an acute infectious disease caused by a novel coronavirus. Traditional Chinese medicine (TCM) has been proven to have a potential curative effect on COVID-19. This study preliminarily analyzed the existing TCM prescription's key components and action mechanisms for preventing and treating COVID-19 using bioinformatic and experimental methods. Association and clustering analysis reveals that the "HQ + FF + BZ" drug combination had a strong correlation and confidence in 93 TCM prescriptions and may affect the progression of COVID-19 through inflammatory pathways such as the TNF signaling pathway. Further molecular docking revealed that quercetin has a higher affinity for IL6 and IL10 in the TNF signaling pathway associated with COVID-19. In vitro experiments demonstrated that quercetin could effectively reduce the levels of the inflammatory factor IL-6 and increase the anti-inflammatory factor IL-10, alleviating inflammation impact on cells. Our results provide a new understanding of the molecular mechanism of TCM prevention and treatment of COVID-19, which is helpful to the development of new diagnosis and treatment schemes for COVID-19.

Since the first case of severe COVID-19, its effect on patients with previous interstitial lung disease (ILD) has been uncertain. We aimed to describe baseline clinical characteristics in ILD patients hospitalized by critical COVID and compare mortality during hospitalization.

We studied patients with ILD with COVID-19 and a control group matched by age, 1:2 ratio with COVID-19 without previous lung disease. On admission, laboratory tests and sociodemographic variables were evaluated. We evaluated patients critically ill and compared baseline characteristics and mortality in each group. Additionally, we performed a sub-analysis of ILD patients who died versus survivors.

Forty-one patients and 82 controls were analyzed. In the group of ILD with COVID-19 there was a predominance of women (65 versus 33%: p < 0.001); lower leukocytes (9 ± 6 versus 11 ± 7, p = 0.01) and neutrophils (8 ± 5 versus 10 ± 6, p = 0.02). The most common ILD was secondary to autoimmune diseases. Patients with ILD and critical COVID-19 showed a significantly higher mortality compared with those without previous ILD (63 versus 33%, p = 0.007). Patients who died in this group had higher BMI (28 ± 6 versus 25 ± 4 kg/m2, p = 0.05), less extended hospital stay (20 ± 17 versus 36 ± 27 days, p = 0.01), and fewer days of evolution (9 ± 7 versus 16 ± 16, p = 0.05).

We found higher mortality in patients with ILD with critical COVID-19. Higher BMI and comorbidities were present in the non-survivors.

COVID-19 (Coronavirus Disease 2019) is an infectious disease caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and has globally infected 768 million people and caused over 6 million deaths. COVID-19 primarily affects the respiratory system but increasing reports of neurologic symptoms associated with COVID-19 have been reported in the literature. The exact mechanism behind COVID-19 neurologic pathophysiology remains poorly understood due to difficulty quantifying clinical neurologic symptoms in humans and correlating them to findings in human post-mortem samples and animal models. Thus, robust preclinical experimental models for COVID-19 neurologic manifestations are urgently needed. Here, we review recent advances in in vitro, in vivo, and other models and technologies for studying COVID-19 including primary cell cultures, pluripotent stem cell-derived neurons and organoids, rodents, nonhuman primates, 3D bioprinting, artificial intelligence, and multiomics. We specifically focus our discussion on the contribution, recent advancements, and limitations these preclinical models have on furthering our understanding of COVID-19's neuropathic physiology. We also discuss these models' roles in the screening and development of therapeutics, vaccines, antiviral drugs, and herbal medicine, and on future opportunities for COVID-19 neurologic research and clinical management.

Observational studies have suggested that COVID-19 increases the prevalence of psychiatric disorders, but the results of such studies are inconsistent. This study aims to investigate the association between COVID-19 and the risk of psychiatric disorders using Mendelian randomization (MR) analysis.

We used summary statistics from COVID-19 Host Genetics Initiative genome-wide association study (GWAS) of COVID-19 involving 2,586,691 participants from European ancestry. Genetic variations of five psychiatric disorders including autism spectrum disorder (ASD) (N = 46,351), bipolar disorder (BID) (N = 51,710), major depressive disorder (MDD) (N = 480,359), anxiety disorder (N = 83,566), and schizophrenia (SCZ) (N = 77,096) were extracted from several GWAS of European ancestry. The inverse-variance weighted (IVW) method as the main MR analysis conducted. We further performed sensitivity analyzes and heterogeneity analyzes as validation of primary MR results.

The IVW analysis found that COVID-19 hospitalization phenotype was the risk factor for BID (OR = 1.320, 95% CI = 1.106-1.576, p = 0.002) and SCZ (OR = 1.096, 95% CI = 1.031-1.164, p = 0.002). Moreover, we detected a significant positive genetic correlation between COVID-19 severity and two psychiatric traits, BID (OR = 1.139, 95% CI = 1.033-1.256, p = 0.008) and SCZ (OR = 1.043, 95% CI = 1.005-1.082, p = 0.024). There was no evidence supporting the causal relationship between COVID-19 susceptibility and psychiatric disorders.

Our results found that the COVID-19 hospitalization phenotype and COVID-19 severity phenotype might be the potential risks of BID and SCZ in European populations. Therefore, patients infected with SARS-CoV-2 should have enhanced monitoring of their mental status.

The coronavirus disease 2019 (COVID-19) pandemic is a rapidly evolving global emergency and continuously poses a serious threat to public health, highlighting the urgent need of identifying biomarkers for disease severity and progression. In order to early identify severe and critical patients, we retrospectively analyze the clinical characteristics and risk indicators of severe disease in patients with corona virus disease 2019 (COVID-19).

A total of 420 confirmed COVID-19 patients were included in the study. According to the "Diagnosis and Treatment of novel coronavirus Pneumonia (10th Edition)", the cases were divided into mild group (n = 243) and severe group (n =177). Laboratory parameters were analyzed in combination with clinical data.

Male patients over 46 years who have smoking habits were more likely to suffer from severe COVID-19. Critically ill patients had lower lymphocyte counts and red blood cell counts, and higher white blood cell counts (P<0.05). Expectedly, serum inflammatory factors (NLR, PLR, LMR, CLR, PCT, CRP), coagulation markers (APTT, PT, TT, FIB, D-Dimer), Myocardial damage markers (hs-TNT, LDH) were significantly increased (P<0.05) in severe COVID-19 patients. Surprisedly, those patients showed obviously elevated levels of common tumor markers (ProGRP, CYFRA21-1, SCC, NSE) (P<0.05). In this case, the levels of tumor marker reflected more the condition of inflammation than the growth of tumor. More importantly, HA and PIIIN-P were highly associated with COVID-19 severity. The AUC of the ROC curve for the diagnosis of severe COVID-19 by HA and PIIIN-P was 0.826. Meanwhile, HA was positively correlated with myocardial damage markers (hs-TNT, LDH). PIIIN-P was positively correlated with myocardial damage markers (hs-TNT, LDH) and inflammatory factors (NLR, PLR, LMR, CLR, ProGRP, SCC, PCT, CRP). On the contrary, PIIIN-P was negatively correlated with pulmonary function indexes (oxygenation index and oxygen saturation of hemoglobin).

HA and PIIIN-P are highly associated with disease severity and progression of COVID-19 and can be used as new markers for the prediction of severe COVID-19.

During the Coronavirus disease 2019 (COVID-19) pandemic, there was always concern about damage to different organs of the body. In this study, we aimed to determine if coronavirus 2 (SARS-CoV-2) could influence the sperm parameters in inpatient adult men with COVID-19.

In this prospective study during 2021, 22 patients with COVID-19 diagnosed with polymerase chain reaction (PCR) test and clinical symptoms and history of admission and 19 volunteer healthy men as the control group participated. They were asked to provide semen samples at 2 and 6 months after hospital discharge and the same time for the control group. The following parameters were measured in all semen samples and beside the demographic data, they compared between the two groups: volume (mL), sperm concentration (106/mL), total motile sperm percentage, progressive percentage, normal morphology percentage, and DNA fragmentation index (DFI).

The mean ± SD age of the participants in the COVID and control groups was 46.36 ± 9.94 and 45.84 ± 10.21 years, respectively (P=0.869). The mean ± SD body mass index (BMIs) of the participants in the COVID and control groups were 28.6 ± 5.460 and 29.6 ± 6.092, respectively (P=0.579). The mean ± SD number of children was 1.41 ± 1.054 in the COVID group and 1.47 ± 1.073 in the control group (P=0.847). All the sperm parameters were significantly impaired after 2 months in the COVID group in comparison with the control group (P<0.05). After 4 months from first sampling, all the parameters were improved significantly (except normal morphology) but had not yet reached the level of the control group.

SARS-CoV-2 affected semen parameters in patients admitted because of COVID-19, in the short term. It is expected that this will improve with time.

Despite the declining COVID-19 cases, global healthcare systems still face significant challenges due to ongoing infections, especially among fully vaccinated individuals, including adolescents and young adults (AYA). To tackle this issue, cost-effective alternatives utilizing technologies like Artificial Intelligence (AI) and wearable devices have emerged for disease screening, diagnosis, and monitoring. However, many AI solutions in this context heavily rely on supervised learning techniques, which pose challenges such as human labeling reliability and time-consuming data annotation. In this study, we propose an innovative unsupervised framework that leverages smartwatch data to detect and monitor COVID-19 infections. We utilize longitudinal data, including heart rate (HR), heart rate variability (HRV), and physical activity measured via step count, collected through the continuous monitoring of volunteers. Our goal is to offer effective and affordable solutions for COVID-19 detection and monitoring. Our unsupervised framework employs interpretable clusters of normal and abnormal measures, facilitating disease progression detection. Additionally, we enhance result interpretation by leveraging the language model Davinci GPT-3 to gain deeper insights into the underlying data patterns and relationships. Our results demonstrate the effectiveness of unsupervised learning, achieving a Silhouette score of 0.55. Furthermore, validation using supervised learning techniques yields high accuracy (0.884 ± 0.005), precision (0.80 ± 0.112), and recall (0.817 ± 0.037). These promising findings indicate the potential of unsupervised techniques for identifying inflammatory markers, contributing to the development of efficient and reliable COVID-19 detection and monitoring methods. Our study shows the capabilities of AI and wearables, reflecting the pursuit of low-cost, accessible solutions for addressing health challenges related to inflammatory diseases, thereby opening new avenues for scalable and widely applicable health monitoring solutions.