Near coding-complete genome sequence of 12 dengue serotype 2 viruses from the 2023 outbreak in Bangladesh.

We report the near coding-complete genomes of 12 DENV serotype 2 strains collected during the 2023 dengue outbreak in Bangladesh. Analyses showed that all 12 strains were closely related and belonged to genotype II-Cosmopolitan.

Emergence of SARS-CoV-2 Omicron sub-lineage JN.1 in Bangladesh.

We report complete genome sequences of 14 severe acute respiratory syndrome coronavirus 2 Omicron sub-lineage JN.1 obtained from Bangladeshi individuals between 19 December 2023 and 21 January 2024. All sequence data were generated by Oxford Nanopore Sequencing Technology using the amplicon sequencing approach developed by the ARTIC network.

Reduced control of SARS-CoV-2 infection associates with lower mucosal antibody responses in pregnancy.

Pregnant patients are at greater risk of hospitalization with severe COVID-19 than non-pregnant people. This was a retrospective observational cohort study of remnant clinical specimens from patients who visited acute care hospitals within the Johns Hopkins Health System in the Baltimore, MD-Washington DC, area between October 2020 and May 2022. Participants included confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected pregnant people and matched non-pregnant people (the matching criteria included age, race/ethnicity, area deprivation index, insurance status, and vaccination status to ensure matched demographics). The primary dependent measures were clinical COVID-19 outcomes, infectious virus recovery, viral RNA levels, and mucosal anti-spike (S) IgG titers from upper respiratory tract samples. A total of 452 individuals (117 pregnant and 335 non-pregnant) were included in the study, with both vaccinated and unvaccinated individuals represented. Pregnant patients were at increased risk of hospitalization (odds ratio [OR] = 4.2; confidence interval [CI] = 2.0-8.6), intensive care unit admittance (OR = 4.5; CI = 1.2-14.2), and being placed on supplemental oxygen therapy (OR = 3.1; CI = 1.3-6.9). Individuals infected during their third trimester had higher mucosal anti-S IgG titers and lower viral RNA levels (P < 0.05) than those infected during their first or second trimesters. Pregnant individuals experiencing breakthrough infections due to the Omicron variant had reduced anti-S IgG compared to non-pregnant patients (P < 0.05). The observed increased severity of COVID-19 and reduced mucosal antibody responses particularly among pregnant participants infected with the Omicron variant suggest that maintaining high levels of SARS-CoV-2 immunity through booster vaccines may be important for the protection of this at-risk population.IMPORTANCEIn this retrospective observational cohort study, we analyzed remnant clinical samples from non-pregnant and pregnant individuals with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections who visited the Johns Hopkins Hospital System between October 2020 and May 2022. Disease severity, including intensive care unit admission, was greater among pregnant than non-pregnant patients. Vaccination reduced recovery of infectious virus and viral RNA levels in non-pregnant patients, but not in pregnant patients. In pregnant patients, increased nasopharyngeal viral RNA levels and recovery of infectious virus were associated with reduced mucosal IgG antibody responses, especially among women in their first trimester of pregnancy or experiencing breakthrough infections from Omicron variants. Taken together, this study provides insights into how pregnant patients are at greater risk of severe COVID-19. The novelty of this study is that it focuses on the relationship between the mucosal antibody response and its association with virus load and disease outcomes in pregnant people, whereas previous studies have focused on serological immunity. Vaccination status, gestational age, and SARS-CoV-2 omicron variant impact mucosal antibody responses and recovery of infectious virus from pregnant patients.

Quality of Life Assessment in Women With Breast Cancer in Nineveh, Iraq.

Background Due to earlier detection and improved treatment and examinations, there has been a rise in the survival rate of patients with breast cancer (BC). It is imperative to examine the health-related quality of life (QoL) of these patients, as it can aid healthcare professionals and authorities in comprehending the variables that influence quality of life. Unfortunately, there is a dearth of information on the subject of women in Nineveh. In Nineveh, a study sought to delve into the quality of life experienced by women undergoing treatment or on follow-up for breast cancer at Mosul Oncology and Nuclear Medicine Hospital. Specifically, researchers wanted to see how age and treatment impacted the QoL of these women. Methods A cross-sectional study was conducted on 212 women with BC. Clinico-pathological-, social-, disease-, and treatment-related characteristics were reviewed. The Functional Assessment of Cancer Therapy-Breast (FACT-B) questionnaire was used for assessing QoL in this study. Results The overall FACT-B score was 75.7 (SD=19.99). Around 36.3% (n=77) of women with BC suffered from a lack of energy, and 39% (n=83) could not meet the needs of their families. The mean score of emotional well-being was the lowest among the FACT-B subscales. Patients aged 60 years and older had significantly worse QoL than younger patients (less than 60 years), and patients receiving chemotherapy had poor QoL. During the chemotherapy period, 51.4% (n=77) of patients were bothered by the side effects of treatment; 43.8% (n=65) suffered from pain; 35.3% (n=53) had nausea; and 39.1% (n=58) felt ill. Conclusions Patients with breast carcinoma who are older tend to experience a lower quality of life, according to the findings of a recent study. Interestingly, those who undergo systemic chemotherapy have a worse QoL than their counterparts who complete their chemotherapy cycles. As a result, healthcare providers must offer targeted interventions to improve quality of life, particularly for those who fall into the older age group and those receiving chemotherapy.

An artificial intelligence approach to predict infants' health status at birth.

BACKGROUND: Machine learning could be used for prognosis/diagnosis of maternal and neonates' diseases by analyzing the data sets and profiles obtained from a pregnant mother. PURPOSE: We aimed to develop a prediction model based on machine learning algorithms to determine important maternal characteristics and neonates' anthropometric profiles as the predictors of neonates' health status. METHODS: This study was conducted among 1280 pregnant women referred to healthcare centers to receive antenatal care. We evaluated several machine learning methods, including support vector machine (SVM), Ensemble, K-Nearest Neighbor (KNN), Naïve Bayes (NB), and Decision tree classifiers, to predict newborn health state. RESULTS: The minimum redundancy-maximum relevance (MRMR) algorithm revealed that variables, including head circumference of neonates, pregnancy intention, and drug consumption history during pregnancy, were top-scored features for classifying normal and unhealthy infants. Among the different classification methods, the SVM classifier had the best performance. The average values of accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC) in the test group were 75%, 75%, 76%, 76%, and 65%, respectively, for SVM model. CONCLUSION: Machine learning methods can efficiently forecast the neonate's health status among pregnant women. This study proposed a new approach toward the integration of maternal data and neonate profiles to facilitate the prediction of neonates' health status.

Increased circulation of human adenovirus in 2023: an investigation of the circulating genotypes, upper respiratory viral loads, and hospital admissions in a large academic medical center.

IMPORTANCE: The circulation of human adenoviruses (HAdV) increased in 2023. In this manuscript, we show that HAdV-B3 was predominant in 2023 in a cohort characterized by the Johns Hopkins Hospital System. We also show that HAdV-B3 was associated with an increase in viral loads in respiratory samples and provide a correlation with the clinical presentations and outcomes.

Evolution of Influenza A(H3N2) Viruses in 2 Consecutive Seasons of Genomic Surveillance, 2021-2023.

Background: The circulation and the genomic evolution of influenza A(H3N2) viruses during the 2021/2022 and 2022/2023 seasons were studied and associated with infection outcomes. Methods: Remnant influenza A-positive samples following standard-of-care testing from patients across the Johns Hopkins Health System (JHHS) were used for the study. Samples were randomly selected for whole viral genome sequencing. The sequence-based pEpitope model was used to estimate the predicted vaccine efficacy (pVE) for circulating H3N2 viruses. Clinical data were collected and associated with viral genomic data. Results: A total of 121 683 respiratory specimens were tested for influenza at JHHS between 1 September 2021 and 31 December 2022. Among them, 6071 (4.99%) tested positive for influenza A. Of these, 805 samples were randomly selected for sequencing, with hemagglutinin (HA) segments characterized for 610 samples. Among the characterized samples, 581 were H3N2 (95.2%). Phylogenetic analysis of HA segments revealed the exclusive circulation of H3N2 viruses with HA segments of the 3C.2a1b.2a.2 clade. Analysis of a total of 445 complete H3N2 genomes revealed reassortments; 200 of 227 of the 2022/2023 season genomes (88.1%) were found to have reassorted with clade 3C.2a1b.1a. The pVE was estimated to be -42.53% for the 2021/2022 season and 30.27% for the 2022/2023 season. No differences in clinical presentations or admissions were observed between the 2 seasons. Conclusions: The increased numbers of cases and genomic diversity of influenza A(H3N2) during the 2022/2023 season were not associated with a change in disease severity compared to the previous influenza season.

A misdiagnosed aneurysm of the petrous internal carotid artery: A case report.

INTRODUCTION: An aneurysm is characterized by the weakening of the arterial wall, which leads to a bulge that can be filled with blood. Aneurysms of the petrous portion of the internal carotid artery are rare and predominantly detected incidentally. This is a report of multiple misdiagnoses of an aneurysm of the petrous segment of the internal carotid artery (ICA) that highlights its imaging-based diagnosis and risk of mortality. PRESENTATION OF CASE: A 60-year-old woman with chronic kidney disease and a history of stroke presented with left ear discharge, decreased hearing, and non-pulsatile tinnitus that had persisted for four months. Clinical examination showed wet tympanic membrane perforation, and imaging revealed an ill-defined infiltrative mass involving the left petrous apex initially misdiagnosed as glomus jugulare. Diagnostic computed tomography (CT) angiography revealed a left aneurysm in the petrous part of the ICA, which was successfully treated with interventional radiology. Follow-up was planned for infectious diseases and internal medicine, but she was lost to follow-up by the otolaryngology department. DISCUSSION: Aneurysms in the petrous portion of the ICA are rare and usually asymptomatic. However, their clinical manifestations vary, and they have various differential diagnoses. CT and magnetic resonance imaging are essential for diagnosis, and CT angiography is the gold standard. CONCLUSION: Diagnosing petrous ICA aneurysms requires a high level of suspicion and CT angiography. Their clinical presentations vary from asymptomatic to severe. Case-specific management and endovascular treatment yield positive neurological outcomes.

Accuracy of Expired BinaxNOW Rapid Antigen Tests.

The widespread existence of expired antigen testing kits in households and potential coronavirus outbreaks necessitates evaluating the reliability of these expired kits. Our study examined BinaxNOW COVID-19 rapid antigen tests 27 months postmanufacture and 5 months past their FDA extended expiration dates, using SARS-CoV-2 variant XBB.1.5 viral stock. We conducted testing at two concentrations, the limit of detection (LOD) and 10 times the LOD. One hundred expired and unexpired kits were tested at each concentration for a total of 400 antigen tests. At the LOD (2.32 × 102 50% tissue culture infective dose/mL [TCID50/mL]), both expired and unexpired tests displayed 100% sensitivity (95% confidence interval [CI], 96.38% to 100%), with no statistical difference (95% CI, -3.92% to 3.92%). Similarly, at 10 times the LOD, unexpired tests retained 100% sensitivity (95% CI, 96.38% to 100%), while expired tests exhibited 99% sensitivity (95% CI, 94.61% to 99.99%), demonstrating a statistically insignificant 1% difference (95% CI, -2.49% to 4.49%; P = 0.56). Expired rapid antigen tests had fainter lines than the unexpired tests at each viral concentration. The expired rapid antigen tests at the LOD were only just visible. These findings carry significant implications for waste management, cost efficiency, and supply chain resilience in pandemic readiness efforts. They also provide critical insights for formulating clinical guidelines for interpreting results from expired kits. In light of expert warnings of a potential outbreak of a severity rivaling the Omicron variant, our study underscores the importance of maximizing the utility of expired antigen testing kits in managing future health emergencies. IMPORTANCE The study examining the reliability of expired antigen testing kits in the context of COVID-19 has significant real-world implications. By demonstrating that these expired kits retain their sensitivity in detecting the virus, this work provides evidence that expired kits can still be utilized, reducing waste and optimizing resources in health care systems. These findings are especially crucial in light of potential future coronavirus outbreaks and the need to be prepared. The study's outcomes have the potential to contribute to waste management efforts, cost efficiency, and supply chain resilience, ensuring that diagnostic tests remain readily available for effective public health interventions. Furthermore, it provides critical insights for formulating clinical guidelines on interpreting results from expired kits, enhancing the accuracy of testing outcomes, and supporting informed decision-making. Ultimately, this work holds great importance in maximizing the utility of expired antigen testing kits, safeguarding public health, and enhancing pandemic readiness on a global scale.

Severity outcomes associated with SARS-CoV-2 XBB variants, an observational analysis.

The rapidity with which SARS-CoV-2 XBB variants rose to predominance has been alarming. We used a large cohort of patients diagnosed with Omicron infections between September 2022 and mid-February 2023 to evaluate the likelihood of admission or need for supplemental oxygen in patients infected with XBB variants. Our data showed no significant association between XBB or XBB.1.5 infections and admissions. Older age groups, lack of vaccination, immunosuppression and underlying heart, kidney, and lung disease showed significant associations with hospitalization.

Respiratory Adenovirus Quantification with a Droplet Digital Polymerase Chain Reaction (ddPCR) Assay.

Human adenoviruses (HAdVs) are double-stranded DNA viruses that can cause a wide spectrum of disease, including respiratory infections. Little is known about the value of respiratory HAdV quantification and its correlation with disease severity. In this study, we developed a quantitative HAdV droplet digital PCR (ddPCR) assay to study the association between viral loads, circulating types, and clinical outcomes. Remnant respiratory specimens positive for HAdV after the standard of care testing were collected from December 2020 to April 2022. A total of 129 samples were tested by a ddPCR method. Typing was performed using Nanopore sequencing of the hexon gene hypervariable region. Clinical chart reviews were performed to correlate the viral loads with the disease severity. The ddPCR assay showed an analytical sensitivity and a lower limit of quantification below 100 copies/mL. Of 129 positive clinical samples, 100 were quantified by ddPCR, 7 were too concentrated to be quantified, and 22 were negative. Of the 22 false negatives, only 3 were successfully typed; however, 99 of the 107 positive samples had a characterized genotype. The main HAdV types identified in this cohort were C1 (49.5%) followed by C2 (34.3%). No significant difference in HAdV loads was noted between patients who were admitted, those who required supplemental oxygen, and outpatients or between different HAdV types. HAdV ddPCR is a reliable absolute quantification approach for HAdV from respiratory samples. HAdV loads at initial presentation does not appear to differ between patients who require hospitalization versus outpatients. IMPORTANCE Measuring viral load using droplet digital PCR (ddPCR) is an absolute quantification approach that can facilitate comparability between different laboratories. This approach could prove valuable in studies that focus on the clinical utility of quantification. In this study, we evaluate a human adenovirus (HAdV) ddPCR assay and study the relationship between viral loads and outcomes after HAdV respiratory infections.

Reduced control of SARS-CoV-2 infection is associated with lower mucosal antibody responses in pregnant women.

Importance: Pregnant women are at increased risk of severe COVID-19, but the contribution of viral RNA load, the presence of infectious virus, and mucosal antibody responses remain understudied. Objective: To evaluate the association of COVID-19 outcomes following confirmed infection with vaccination status, mucosal antibody responses, infectious virus recovery and viral RNA levels in pregnant compared with non-pregnant women. Design: A retrospective observational cohort study of remnant clinical specimens from SARS-CoV-2 infected patients between October 2020-May 2022. Setting: Five acute care hospitals within the Johns Hopkins Health System (JHHS) in the Baltimore, MD-Washington, DC area. Participants: Participants included confirmed SARS-CoV-2 infected pregnant women and matched non-pregnant women (matching criteria included age, race/ethnicity, and vaccination status). Exposure: SARS-CoV-2 infection, with documentation of SARS-CoV-2 mRNA vaccination. Main Outcomes: The primary dependent measures were clinical COVID-19 outcomes, infectious virus recovery, viral RNA levels, and mucosal anti-spike (S) IgG titers from upper respiratory tract samples. Clinical outcomes were compared using odds ratios (OR), and measures of virus and antibody were compared using either Fisher's exact test, two-way ANOVA, or regression analyses. Results were stratified according to pregnancy, vaccination status, maternal age, trimester of pregnancy, and infecting SARS-CoV-2 variant. Resultss: A total of 452 individuals (117 pregnant and 335 non-pregnant) were included in the study, with both vaccinated and unvaccinated individuals represented. Pregnant women were at increased risk of hospitalization (OR = 4.2; CI = 2.0-8.6), ICU admittance, (OR = 4.5; CI = 1.2-14.2), and of being placed on supplemental oxygen therapy (OR = 3.1; CI =13-6.9). An age-associated decrease in anti-S IgG titer and corresponding increase in viral RNA levels (P< 0.001) was observed in vaccinated pregnant, but not non-pregnant, women. Individuals in their 3rd trimester had higher anti-S IgG titers and lower viral RNA levels (P< 0.05) than those in their 1st or 2nd trimesters. Pregnant individuals experiencing breakthrough infections due to the omicron variant had reduced anti-S IgG compared to non-pregnant women (P< 0.05). Conclusions and Relevance: In this cohort study, vaccination status, maternal age, trimester of pregnancy, and infecting SARS-CoV-2 variant were each identified as drivers of differences in mucosal anti-S IgG responses in pregnant compared with non-pregnant women. Observed increased severity of COVID-19 and reduced mucosal antibody responses particularly among pregnant participants infected with the Omicron variant suggest that maintaining high levels of SARS-CoV-2 immunity may be important for protection of this at-risk population.

Diagnostic Yield of Neuroimaging for Headache in a Pediatric Emergency Department: A Single Tertiary Centre Experience.

OBJECTIVES: This study aimed to examine headache neuroimaging findings among the pediatric population visiting the emergency department in Saudi Arabia. METHODS: This was a cross-sectional retrospective study of pediatric patients who presented to the emergency department with a headache as their primary complaint. Data were extracted from the electronic medical files of the patients at King Abdullah Specialized Children Hospital (KASCH) between 2015 and 2020. The diagnosis of headache was confirmed using a computerized tomography (CT) scan or magnetic resonance imaging (MRI) upon the patients' presentation. RESULTS: A total of 263 patients met the inclusion criteria, and their data were extracted. The CT scans were abnormal in 50% of the patients. The MRI showed abnormal findings for 26% of the patients. CT scans and MRI identified that abnormalities were predominantly among patients with the secondary type of headache. The most common abnormal findings on CT were sinusitis (16%), masses (7%), and hydrocephalus (7%). The most common abnormal findings on MRI were masses (8%), cysts (5%), and hydrocephalus (3%). Of all patients with headaches, 10% had a prior diagnosis of headache, and 12% had a family history of headache. A significantly higher percentage of patients with secondary headache were prescribed NSAID and required admission compared to patients with primary headache (p ≤ 0.05). There was no statistically significant differences in the proportion of patients diagnosed with primary and secondary headache in terms of their neurological examination and headache types (p = 0.43). CONCLUSIONS: Neuroimaging is essential for diagnosing headaches in children. Headaches were associated with sinusitis in children. The secondary type was more likely to have abnormal CT and MRI results. Primary type headaches were more common in those with a family history. CT scans and MRIs are needed when a headache is accompanied by an abnormal clinical evaluation. Neuroimaging and mild CT usage may be explored if there are clinical abnormalities or family history.

An increase in enterovirus D68 circulation and viral evolution during a period of increased influenza like illness, The Johns Hopkins Health System, USA, 2022.

BACKGROUND: An increase in influenza like illness in children and adolescents at the Johns Hopkins Health system during summer 2022 was associated with increased positivity for enterovirus/ rhinovirus. We sought to characterize the epidemiology and viral evolution of enterovirus D68 (EV-D68). METHODS: A cohort of remnant respiratory samples tested at the Johns Hopkins Microbiology Laboratory was screened for EV-D68. EV-D68 positives were characterized by whole genome sequencing and viral loads were assessed by droplet digital PCR (ddPCR). Genomic changes and viral loads were analyzed along with patients' clinical presentations. RESULTS: Of 566 screened samples, 126 were EV-D68 (22.3%). The median age of EV-D68 infected patients was four years, a total of 52 required supplemental oxygen (41.3%), and 35 (27.8%) were admitted. Lung disease was the most frequent comorbidity that was associated with hospitalization. A total of 75 complete and 32 partial genomes were characterized that made a new cluster within the B3 subclade that was closest to US genomes from 2018. Amino acid changes within the BC and DE loops were identified from 31 genomes (29%) which correlated with an increase in average viral load in respiratory specimens and the need for supplemental oxygen. CONCLUSIONS: EV-D68 outbreaks continue to cause influenza like illness that could be overwhelming for the health system due to a significant demand for high flow oxygen. Viral evolution and an increase in the susceptible population are likely driving the trends of the increased EV-D68 infections.

Omicron Subvariants: Clinical, Laboratory, and Cell Culture Characterization.

BACKGROUND: The variant of concern Omicron has become the sole circulating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant for the past several months. Omicron subvariants BA.1, BA.2, BA.3, BA.4, and BA.5 evolved over the time, with BA.1 causing the largest wave of infections globally in December 2021-January 2022. This study compared the clinical outcomes in patients infected with different Omicron subvariants and the relative viral loads and recovery of infectious virus from upper respiratory specimens. METHODS: SARS-CoV-2-positive remnant clinical specimens, diagnosed at the Johns Hopkins Microbiology Laboratory between December 2021 and July 2022, were used for whole-genome sequencing. The clinical outcomes of infections with Omicron subvariants were compared with infections with BA.1. Cycle threshold (Ct) values and the recovery of infectious virus on the VeroTMPRSS2 cell line from clinical specimens were compared. RESULTS: BA.1 was associated with the largest increase in SARS-CoV-2 positivity rate and coronavirus disease 2019 (COVID-19)-related hospitalizations at the Johns Hopkins system. After a peak in January, cases decreased in the spring, but the emergence of BA.2.12.1 followed by BA.5 in May 2022 led to an increase in case positivity and admissions. BA.1 infections had a lower mean Ct value when compared with other Omicron subvariants. BA.5 samples had a greater likelihood of having infectious virus at Ct values <20. CONCLUSIONS: Omicron subvariants continue to be associated with a relatively high rate of polymerase chain reaction (PCR) positivity and hospital admissions. The BA.5 infections are more while BA.2 infections are less likely to have infectious virus, suggesting potential differences in infectibility during the Omicron waves.

Efficacy and Safety of Temporary in situ Stenting of Ahmed Glaucoma Valve in Eyes with High Risk of Hypotony.

Introduction and Objective: To describe a novel technique for providing external ligation of the Ahmed glaucoma valve (AGV) to prevent hypotony in eyes at high risk with a 4/0 nylon stent suture and report outcomes compared to ligation with an absorbable vicryl suture and no ligation in terms of efficacy and safety. Methods: This was a retrospective cohort study investigating the efficacy and safety of in situ stenting compared to an absorbable ligature and the standard care, in high risk eyes, of hypotony. It included 116 patients; 34 in Group A (ligation + stent), 27 in Group B (ligation - stent), and 55 in Group C (no ligation). Results: The mean age (in years) of the participants was 53.94±19.01 in Group A, 44.85±29.92 in Group B and 52.62±24.47 in Group C, 59% (n = 20), 63% (n = 17) and 60% (n = 33) were males, respectively. The follow-up period was at least 6 months (Group A: 9.1±4.2 months, Group B: 9.6±3.4 months and Group C: 10.2±6.4 months). The mean baseline Snellen VA (LogMAR) was 1.82±1.34, 1.30±0.98 and 1.34±1.07 and the mean baseline IOP was 32.50±9.48, 28.22±7.12 and 28.33±10.63 mmHg, in Groups A, B and C, respectively. The failure rates, by the Kaplan Meier Survival curve, were higher 27.3% in Group C (no ligation) compared to 20.6% in Group A (ligation + stent) and 18.5% in Group B (ligation - stent) yet not found to be statistically significant (p = 0.4; log rank test). There was lower hypotony 2.9% in Group A and lower complications 25.9% in Group B but no statistical significance was found amongst the groups. Conclusion: In conclusion, temporary nylon in situ stenting of AGV had lower rates of hypotony. Furthermore, lower failure and complication rates were observed in vicryl only ligated AGV, then nylon in situ stented AGV and lastly in standard AGV controls.

SARS-CoV-2 reinfections during the Delta and Omicron waves.

BACKGROUNDIncreased SARS-CoV-2 reinfection rates have been reported recently, with some locations basing reinfection on a second positive PCR test at least 90 days after initial infection. In this study, we used Johns Hopkins SARS-CoV-2 genomic surveillance data to evaluate the frequency of sequencing-validated, confirmed, and inferred reinfections between March 2020 and July 2022.METHODSPatients who had 2 or more positive SARS-CoV-2 tests in our system, with samples sequenced as a part of our surveillance efforts, were identified as the cohort for our study. SARS-CoV-2 genomes of patients' initial and later samples were compared.RESULTSA total of 755 patients (920 samples) had a positive test at least 90 days after the initial test, with a median time between tests of 377 days. Sequencing was attempted on 231 samples and was successful in 127. Rates of successful sequencing spiked during the Omicron surge; there was a higher median number of days from initial infection in these cases compared with those with failed sequences. A total of 122 (98%) patients showed evidence of reinfection; 45 of these patients had sequence-validated reinfection and 77 had inferred reinfections (later sequencing showed a clade that was not circulating when the patient was initially infected). Of the 45 patients with sequence-validated reinfections, 43 (96%) had reinfections that were caused by the Omicron variant, 41 (91%) were symptomatic, 32 (71%) were vaccinated prior to the second infection, 6 (13%) were immunosuppressed, and only 2 (4%) were hospitalized.CONCLUSIONSequence-validated reinfections increased with the Omicron surge but were generally associated with mild infections.FUNDINGFunding was provided by the Johns Hopkins Center of Excellence in Influenza Research and Surveillance (HHSN272201400007C), CDC (75D30121C11061), Johns Hopkins University President's Fund Research Response, Johns Hopkins Department of Pathology, and the Maryland Department of Health.

The Effect of Short Treatment with Nigella Sativa on Symptoms, the Cluster of Differentiation (CD) Profile, and Inflammatory Markers in Mild COVID-19 Patients: A Randomized, Double-Blind Controlled Trial.

The current study investigated the impact of different doses of Nigella sativa seeds on the symptoms, the cluster of differentiation profile group, and inflammatory markers of mild COVID-19 cases. METHODS: The study was a double-blind placebo-controlled clinical trial. Patients with mild and asymptomatic SARS-CoV-2 infection patients were randomly subdivided into seven subgroups: Group (GP) 1: received charcoal capsules as a control group, and GP 2: received three capsules of whole Nigella sativa seeds daily, two capsules in the morning and one in the evening; GP 3: received three capsules of whole Nigella sativa seeds every 12 h, GP 4: received five capsules in the morning and four capsules of whole Nigella sativa seeds in the evening, GP 5: received one capsule of Nigella sativa powder every 12 h; GP 6: received two capsules of Nigella sativa powder every 12 h; GP 7: received three capsules of Nigella sativa powder every 12 h; all treatment course was for ten days. Inflammatory parameters were assessed before and after interventions. RESULTS: 262 subjects were included in the final analysis. No significant difference was detected regarding age, gender, and nationality. No significant differences were detected between the inflammatory marker in all groups. The WBCs showed a significant difference between before and after the intervention. While for procalcitonin, a significant difference was demonstrated in groups 1,4, and 6. CONCLUSIONS: The current randomized clinical trial did not reveal a significant effect of ten days of treatment with various doses of Nigella sativa on symptoms, differentiation profile, and inflammatory markers of patients with COVID-19. As a natural product, the effect of Nigella sativa on disease requires weeks to manifest itself.

Omicron Subvariants: Clinical, Laboratory, and Cell Culture Characterization.

Background: The variant of concern, Omicron, has become the sole circulating SARS-CoV-2 variant for the past several months. Omicron subvariants BA.1, BA.2, BA.3, BA.4, and BA.5 evolved over the time, with BA.1 causing the largest wave of infections globally in December 2021- January 2022. In this study, we compare the clinical outcomes in patients infected with different Omicron subvariants and compare the relative viral loads, and recovery of infectious virus from upper respiratory specimens. Methods: SARS-CoV-2 positive remnant clinical specimens, diagnosed at the Johns Hopkins Microbiology Laboratory between December 2021 and July 2022, were used for whole genome sequencing. The clinical outcomes of infections with Omicron subvariants were compared to infections with BA.1. Cycle threshold values (Ct) and the recovery of infectious virus on VeroTMPRSS2 cell line from clinical specimens were compared. Results: The BA.1 was associated with the largest increase in SARS-CoV-2 positivity rate and COVID-19 related hospitalizations at the Johns Hopkins system. After a peak in January cases fell in the spring, but the emergence of BA.2.12.1 followed by BA.5 in May 2022 led to an increase in case positivity and admissions. BA.1 infections had a lower mean Ct when compared to other Omicron subvariants. BA.5 samples had a greater likelihood of having infectious virus at Ct values less than 20. Conclusions: Omicron subvariants continue to associate with a relatively high positivity and admissions. The BA.5 infections are more while BA.2 infections are less likely to have infectious virus, suggesting potential differences in infectibility during the Omicron waves. Funding: Centers for Disease Control and Prevention contract 75D30121C11061, NIH/NIAID Center of Excellence in Influenza Research and Surveillance contract HHS N2772201400007C, Johns Hopkins University, Maryland department of health, and The Modeling Infectious Diseases in Healthcare Network (MInD) under awards U01CK000589.

A Review on Machine Learning Approaches in Identification of Pediatric Epilepsy.

Epilepsy is the second most common neurological disease after Alzheimer. It is a disorder of the brain which results in recurrent seizures. Though the epilepsy in general is considered as a serious disorder, its effects in children are rather dangerous. It is mainly because it reasons a slower rate of development and a failure to improve certain skills among such children. Seizures are the most common symptom of epilepsy. As a regular medical procedure, the specialists record brain activity using an electroencephalogram (EEG) to observe epileptic seizures. The detection of these seizures is performed by specialists, but the results might not be accurate and depend on the specialist's experience; therefore, automated detection of epileptic pediatric seizures might be an optimal solution. In this regard, several techniques have been investigated in the literature. This research aims to review the approaches to pediatric epilepsy seizures' identification especially those based on machine learning, in addition to the techniques applied on the CHB-MIT scalp EEG database of epileptic pediatric signals.