Towards achieving a vaccine-derived herd immunity threshold for COVID-19 in the U.S. A novel coronavirus emerged in December of 2019 (COVID-19), causing a pandemic that continues to inflict unprecedented public health and economic burden in all nooks and corners of the world. Although the control of COVID-19 has largely focused on the use of basic public health measures (primarily based on using non-pharmaceutical interventions, such as quarantine, isolation, social-distancing, face mask usage and community lockdowns), three safe and highly-effective vaccines (by AstraZeneca Inc., Moderna Inc. and Pfizer Inc., with protective efficacy of 70%, 94.1% and 95%, respectively) have been approved for use in humans since December 2020. We present a new mathematical model for assessing the population-level impact of the three currently-available anti-COVID vaccines that are administered in humans. The model stratifies the total population into two subgroups, based on whether or not they habitually wear face mask in public. The resulting multigroup model, which takes the form of a deterministic system of nonlinear differential equations, is fitted and parametrized using COVID-19 cumulative mortality data for the third wave of the COVID-19 pandemic in the U.S. Conditions for the asymptotic stability of the associated disease-free equilibrium, as well as expression for the vaccine-derived herd immunity threshold, are rigorously derived. Numerical simulations of the model show that the size of the initial proportion of individuals in the masks-wearing group, together with positive change in behaviour from the non-masks wearing group (as well as those in masks-wearing group do not abandon their masks-wearing habit) play a crucial role in effectively curtailing the COVID-19 pandemic in the U.S. This study further shows that the prospect of achieving herd immunity (required for COVID-19 elimination) in the U.S., using any of the three currently-available vaccines, is quite promising. In particular, while the use of the AstraZeneca vaccine will lead to herd immunity in the U.S. if at least 80% of the populace is vaccinated, such herd immunity can be achieved using either the Moderna or Pfizer vaccine if about 60% of the U.S. population is vaccinated. Furthermore, the prospect of eliminating the pandemic in the US in the year 2021 is significantly enhanced if the vaccination program is complemented with nonpharmaceutical interventions at moderate increased levels of compliance (in relation to their baseline compliance). The study further suggests that, while the waning of natural and vaccine-derived immunity against COVID-19 induces only a marginal increase in the burden and projected time-to-elimination of the pandemic, adding the impacts of the therapeutic benefits of the vaccines into the model resulted in a dramatic reduction in the burden and time-to-elimination of the pandemic.
How radical is radical cure? Site-specific biases in phase-III clinical trials underestimate the effect of radical cure against Plasmodium vivax hypnozoites Plasmodium vivax relapses caused by reactivating hypnozoites are a major barrier for elimination and control of this form of malaria. Radical cure is a form of therapy capable of addressing this problem. Recent clinical trials of radical cure have yielded efficacy estimates ranging from 65% to 94%, with substantial variation across trial sites. We performed an analysis of simulated trial data using a transmission model to demonstrate that variation in efficacy estimates across trial sites can arise from differences in the conditions under which trials are conducted. Our analysis revealed that differences in transmission intensity, heterogeneous exposure, and relapse rate can yield efficacy estimates ranging as wide as 12-78%, despite simulating trial data under the uniform assumption that treatment had a 75% chance of clearing hypnozoites. A longer duration of prophylaxis leads to a greater measured efficacy, particularly at higher transmission intensities, making the comparison of the protection of different radical cure treatment regimens against relapse more challenging. We show that vector control and parasite genotyping offer two potential means to yield more standardized efficacy estimates that better reflect protection against relapse. We predict that site-specific biases are likely to contribute to variation in efficacy estimates both within and across phase-III clinical trials. Future clinical trials can reduce site-specific biases by conducting trials in low-transmission settings where reinfections from mosquito biting are less common, by preventing reinfections using vector control measures, or by identifying and excluding likely reinfections that occur during follow-up using parasite genotyping methods.

AUTHOR SUMMARYRadical cure holds promise as a strategy for Plasmodium vivax malaria control by clearing the parasites known as hypnozoites that latently infect the liver and cause relapsing infections. The efficacy of radical cure treatment regimens is evaluated in phase-III clinical trials. Recent trial results have noted substantial variation in efficacy estimates across trial sites, complicating the interpretation of the benefit of radical cure. However, P. vivax infections identified during the course of the clinical trial could include reinfections from mosquito biting that do not directly reflect the effect of the therapeutic being trialed, potentially biasing efficacy estimates. In this study, we simulated clinical trials to identify the causes and solutions of these site-specific biases. We found that features of both the trial location, such as the transmission intensity, and the trial design, such as the duration of follow-up, lead to an underestimate of the effect of radical cure against hypnozoites. We then demonstrated that vector control and parasite genotyping are two possible strategies to reduce these biases. These insights can be leveraged to aid in the interpretation of past trial results and to help design future clinical trials that minimize site-specific biases.
Longitudinal determination of mRNA-vaccination induced strongly binding SARS-CoV-2 IgG antibodies in a cohort of Romanian healthcare workers Mass vaccination against the disease caused by the novel coronavirus (COVID-19) was a crucial step in slowing the spread of SARS-CoV-2 in 2021. Even in the face of new variants, it still remains extremely important for reducing hospitalizations and COVID-19 deaths. Only limited data exists about the short- and long-term dynamics of humoral immune response. We present a longitudinal analysis of post-vaccination IgG levels in a cohort of 166 healthcare workers vaccinated with BNT162b2 with weekly follow-up until 35 days past the first dose and monthly follow-up up to 6 months post-vaccination. A subset of the patients continued with follow-up after 6 months and either received a booster dose or got infected during the Delta wave in Romania. Tests were carried out on 1697 samples using a CE-marked IgG ELISA assay developed in-house, containing S1 and N antigens of the wild type virus.

Participants infected with SARS-CoV-2 before vaccination mount a quick immune response, reaching peak IgG levels two weeks after the first dose, while IgG levels of previously uninfected participants mount gradually, increasing abruptly after the second dose. Overall higher IgG levels are maintained for the previously infected group 35-70 days after vaccination. The decrease of IgG levels is gradual, with lower overall values in the infection naive cohort even 7-8 months after vaccination, compared to the previously infected cohort. Administration of a booster dose yielded higher average IgG antibody levels than post second dose in the infection naive group and comparable levels in the previously infected group. Machine Learning Approaches for Binary Classification to Discover Liver Diseases using Clinical Data For a medical diagnosis, health professionals use different kinds of pathological ways to make a decision for medical reports in terms of patients medical condition. In the modern era, because of the advantage of computers and technologies, one can collect data and visualize many hidden outcomes from them. Statistical machine learning algorithms based on specific problems can assist one to make decisions. Machine learning data driven algorithms can be used to validate existing methods and help researchers to suggest potential new decisions. In this paper, Multiple Imputation by Chained Equations was applied to deal with missing data, and Principal Component Analysis to reduce the dimensionality. To reveal significant findings, data visualizations were implemented. We presented and compared many binary classifier machine learning algorithms (Artificial Neural Network, Random Forest, Support Vector Machine) which were used to classify blood donors and non-blood donors with hepatitis, fibrosis and cirrhosis diseases. From the data published in UCI-MLR, all mentioned techniques were applied to find one better method to classify blood donors and non-blood donors (hepatitis, fibrosis, and cirrhosis) that can help health professionals in a laboratory to make better decisions. Our proposed ML-method showed a better accuracy score (e.g. 98.23% for SVM). Thus, it improved the quality of classification. Gamma Frequency Sensory Stimulation in Probable Mild Alzheimer's Dementia Patients: Results of a Preliminary Clinical Trial Non-invasive Gamma ENtrainment Using Sensory stimuli (GENUS) at 40Hz reduced Alzheimers disease (AD) pathology, prevented cerebral atrophy and improved performance during behavioral testing in mouse models of AD. We report data from a safety study (NCT04042922) and a randomized, placebo-controlled trial in participants with probable mild AD dementia after 3 months of one-hour daily 40Hz light and sound GENUS (NCT04055376) to assess safety, compliance, entrainment and possible effects on brain structure, function, sleep and cognitive function. GENUS was well-tolerated and compliance was high in both groups. Electroencephalography recordings show that our GENUS device safely and effectively induced 40Hz entrainment in cognitively normal subjects and participants with mild AD. After 3 months of daily stimulation, participants with mild AD in the 40Hz GENUS group showed less ventricular enlargement and stabilization of the hippocampal size compared to the control group. Functional connectivity increased in both the default mode network and the medial visual network after 3 months of stimulation. Circadian rhythmicity also improved with GENUS. Compared to controls, the active group performed better on the face-name association delayed recall test. These results suggest that 40Hz GENUS can be used safely at home daily and shows favorable outcomes on cognitive function, daily rhythms, and structural and functional MRI biomarkers of AD-related degeneration. These results support further evaluation of GENUS in larger and longer clinical trials to evaluate its potential as a disease modifying therapeutic for Alzheimers disease. Macronutrient mass intake explains deferential weight and fat loss in isocaloric diets Differential weight and fat losses under isocaloric diets of distinct macronutrient composition are well-documented findings in obesity research.1-6 Such data are considered a result of inadequate methodology as it disagree with the energy balance theory.7 A recent mathematical analysis of this paradigm has found, however, serious analytical contradictions in its foundations.8 As an alternative, a mass balance model was proposed to explain the aforesaid body composition alterations. Here, we expand on this observation by contrasting both models. We show that mass balance explains a wide range of fending experiments including those concurring with the energy balance principle. The latter, however, is less flexible and results in poor forecasts in settings consistent with mass balance. The energy balance theory is thus an unsatisfactory model of body composition changes. Consequently, by shifting to a mass balance paradigm of obesity a much deeper understanding of this disease may follow in the near future. Clinical observation of high-flow nasal cannula with non-rebreather mask use on severe or critically ill COVID-19 diabetic patients Background and aimsPrevalence of diabetes is a vital factor in COVID-19s clinical prognosis. This study aimed to investigate and compare the efficacy of High-flow Nasal Cannula (HFNC) with/without non-rebreather mask (NRM) use on critical COVID-19 patients with/without diabetes.

MethodsFor analysis and comparison, epidemiological, biochemical, and clinical data were collected from 240 HFNC ({+/-}NRM) treated severe and critical COVID-19 patients (diabetic = 136; non-diabetic = 104) admitted into ICUs of five hospitals in Chattogram, Bangladesh.

Results59.1% of patients with fever had diabetes (p=0.012). ICU stay was longer for diabetic patients (9.06{+/-}5.70) than non-diabetic patients (7.41{+/-}5.11) (p=0.020). Majority of the hypertensive patients were diabetic (68.3%; p<0.001). Majority of diabetic patients (70.4%; p<0.005) had elevated creatinine levels. Partial pressure of oxygen (mmHg) after HFNC (only) administration was significantly (p=0.031) higher in non-diabetic patients (69.30{+/-}23.56) than in diabetic patients (61.50{+/-}14.49). Diabetic (62.64{+/-}13.05) and non-diabetic patients (59.40{+/-}13.22) had almost similar partial pressure of oxygen (mmHg) from HFNC with NRM. Patients with elevated RBS required NRM with HFNC five times (AOR=5.1, 1.2-20.8) higher than others. Besides age, and hypertension were significantly associated with the HFNC+NRM treated diabetic patients. Factors those affected the HFNC only treated patients were fever and impaired glucose tolerance.

ConclusionsThe results of this study imply that oxygen supply with HFNC and NRM may be beneficial for the elderly/hypertensive diabetic patients with COVID-19 associated AHRF; and that increased blood glucose level could be a determinant for the need of HFNC + NRM treatment.

HighlightsO_LIElderly diabetic patients required both HFNC and NRM to increase oxygen saturation.
C_LIO_LIHypertension may be a factor for diabetic patients with COVID-19 requiring HFNC and NRM together.
C_LIO_LI HFNC + NRM-combination therapy might be needed when blood glucose levels rise.
C_LI Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis Fecal microbiota transplant is a promising therapy for ulcerative colitis. Parameters maximizing effectiveness and tolerability are not yet clear, and it is not known how import the transmission of donor microbes to patients is. Here (clinicaltrails.gov: NCT03006809) we have tested the effects of antibiotic pretreatment and compared two modes of maintenance dose delivery, capsules versus enema, in a randomized, pilot, open-label, 2x2 factorial design with 22 patients analyzed with mild to moderate UC. Clinically, the treatment was well-tolerated with favorable safety profile. Of patients who received antibiotic pretreatment, 6 of 11 experienced remission after six weeks of treatment, versus 2 of 11 non-pretreated patients (odds ratio: 1.69, 95% confidence interval: -0.25 to 3.62). No significant differences were found between maintenance dosing via capsules versus enema. In exploratory analyses, microbiome turnover at both the species and strain levels was extensive and significantly more pronounced in the pretreated patients. Associations were also revealed between taxonomic turnover and changes in the composition of primary and secondary bile acids. Together these findings suggest that antibiotic pretreatment contributes to microbiome engraftment and possibly clinical effectiveness, and validate longitudinal strain tracking as a powerful way to monitor the dynamics and impact of microbiota transfer. What We Learned from COVID-19: From endotheliitis to treatment ObjectiveCOVID-19 may yield a variety of clinical pictures, differing from pneumonitis to Acute Respiratory Distress Syndrome (ARDS) along with vascular damage in the lung tissue, named as endotheliitis. To date, no specific treatment strategy was approved by any authority for the prevention or treatment of COVID-19 in terms of endotheliitis-related comorbidities. Here, we present our experience of COVID-19 by evaluating 11,190 COVID-19 patients with the manifestations of endotheliitis in skin, lung, and brain tissues according to the different phases of COVID-19.

MethodsAfter a retrospective examination, patients were divided into three groups according to their repercussions of vascular distress, which were represented by radiological, histopathological, and clinical findings. (Group A: no or mild pulmonary involvement, Group B: moderate pulmonary involvement with clinical risk of deterioration, Group C: severe pulmonary involvement and respiratory failure). We presented the characteristics and disease course of seven representative and complicated cases which represents the different phases of the disease, and discussed the treatment strategies in each group. The current pathophysiological mechanisms responsible from SARS-CoV-2 infection, COVID-19 related respiratory failure and current treatment strategies were reviewed and discussed in detail.

ResultsAmong 11.190 patients, 9294 patients met the criteria for Group A, and 1376 patients were presented to our clinics with Group B characteristics. Among these patients, 1896 individuals(Group B and Group C) were hospitalized. While 1220 inpatients were hospitalized within the first 10 days after the diagnosis, 676 of them were worsened and hospitalized 10 days after their diagnosis. Among hospitalized patients, 520 of them did not respond to group A and B treatments and developed hypoxemic respiratory failure (Group C) and 146 individuals needed ventilator support and were followed in the intensive care unit, and 43 (2.2%) patients died.

ConclusionDistinctive manifestations in each COVID-19 patient, including non-respiratory conditions in the acute phase and the emerging risk of long-lasting complications, suggest that COVID-19 has an endotheliitis-centred thrombo-inflammatory pathophysiology. Endotheliitis can also explain the mechanism behind the respiratory failure in COVID-19, and the difference of COVID-19 related ARDS from ARDS seen in other critical conditions. In addition, use of early corticosteroid in patients with early symptoms and early tocilizumab in ICU helps to reduce mortality and progression of the disease. Endotheliitis-based pathophysiological mechanisms are known to be momentarily changing and difficut to manage due to their risk of sudden aggrevation. Hence, daily evaluation of clinical, laboratory and radiological findings of patients and deciding appropriate pathophysiological treatment would help to reduce the mortality rate of COVID-19. Effects of Glucagon-like Peptide-1 Receptor Agonists on Cardiovascular and Renal Outcomes: A Meta-analysis and Meta-regression Analysis AimsCardiovascular and renal effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) have been inconsistent in cardiovascular outcome trials, and factors associated with the efficacy of GLP-1RAs remain to be clarified. Here, we evaluate the cardiovascular and renal outcomes with GLP-1RAs and associations between these outcomes and HbA1c or weight reduction.

Materials and MethodsWe searched PubMed/MEDLINE, EMBASE, and CENTRAL for randomized, placebo-controlled trials of GLP1-RAs reporting major adverse cardiovascular events (MACE; a composite of cardiovascular mortality, stroke, and myocardial infarction) as the primary outcome. We conducted a meta-regression analysis of primary and secondary outcomes with HbA1c or weight reduction following a meta-analysis with a random-effects model for these outcomes.

ResultsWe extracted data of 60,800 individuals from eight eligible studies (ELIXA, LEADER, SUSTAIN-6, EXSCEL, HARMONY, PIONEER 6, REWIND, and AMPLITUDE-O). GLP-1RAs reduced MACE (hazard ratio [HR] 0.86; 95% CI: 0.80-0.93; P < 0.001) and secondary outcomes including the composite renal outcome (0.80; 0.73-0.87; P < 0.001). In meta-regression analysis, every 1% reduction in HbA1c was associated with 26% and 35% decreases in the logarithm of HR of MACE (P = 0.044; R2 = 0.65) and the composite renal outcome (P = 0.040; R2 = 0.85), respectively. On the contrary, weight reduction was not associated with any outcome, including MACE (P = 0.390).

ConclusionsThe reduction in HbA1c, but not body weight, is associated with cardiovascular and renal outcomes. The magnitude of HbA1c reduction can be a surrogate for cardiovascular and renal benefits of treatment with GLP-1RAs. Deaths from cardiovascular disease involving anticoagulants: a systematic synthesis of coroners' case reports BackgroundThe global burden of cardiovascular disease (CVD) is forecast to increase, and anticoagulants will remain important medicines for its management. Coroners Prevention of Future Death reports (PFDs) provide valuable insights that may enable safer and more effective use of these agents.

AimTo identify CVD-related PFDs involving anticoagulants.

Design and SettingRetrospective observational study of coronial case reports in England and Wales between 2013 and 2019.

MethodWe screened 3037 PFDs for eligibility and included PFDs where CVD and an anticoagulant caused or contributed to the death. We descriptively analysed included cases and used content analysis to assess concerns raised by coroners and who responded to them.

ResultsWe identified 113 cardiovascular disease-related PFDs involving anticoagulants. Warfarin (36%), enoxaparin (11%), and rivaroxaban (11%) were the most common anticoagulants reported. Concerns most frequently raised by coroners included poor systems (31%), poor communication (25%), and failures to keep accurate medical records (25%). These concerns were most often directed to NHS trusts (29%), hospitals (10%), and general practices (8%). Nearly two-thirds (60%) of PFDs had not received responses from such organisations, which are mandatory under regulation 28 of the Coroners (Investigations) Regulations 2013. We created a publicly available tool, https://preventabledeathstracker.net/, which displays coroners reports in England and Wales to streamline access and identify important lessons to prevent future deaths.

ConclusionNational organisations, healthcare professionals, and prescribers should take actions to address the concerns of coroners in PFDs to improve the safe use of anticoagulants in patients with cardiovascular disease.

How this fits inA previous assessment of 500 PFDs identified anticoagulants as the class of drugs most often involved in fatal medication errors. This study uses innovative methods to automatically collect all available PFDs between 2013 and 2019 to identify deaths from cardiovascular disease when the use of or lack of anticoagulants caused or contributed to the death. Coroners raised hundreds of coroners in their reports, including issues with communication, following protocols, education and training, access to resources, and safety. Despite repeat concerns with national relevance being identified, most CVD-anticoagulant PFDs were sent locally to NHS Trusts, hospitals, and general practices, limiting their ability to reduce harms and prevent premature deaths. The Preventive Treatment of Migraine with Low-Dose Naltrexone/Acetaminophen Combination: Findings of a Small, Randomized, Double-Blind, and Placebo-Controlled Clinical Trial with an Open-Label Extension for None-Responders We tested a low-dose naltrexone and acetaminophen combination for episodic migraine prevention. We randomly assigned patients to naltrexone and acetaminophen combination (n=6) or placebo (n=6) for a 12-week double-blind treatment. Non-responders continued into open-label treatment with naltrexone and acetaminophen combination (n=5) for additional 12 weeks. Patients were adults who experienced 5 to 17 (average 9.7) migraine days at baseline. The primary endpoint was the mean change in the monthly migraine days during the last 4 weeks of the double-blind treatment period. The key secondary endpoint was the mean change in the monthly migraine days from the 4-week double-blind follow-up (2nd baseline) to the last 4 weeks of the open-label treatment period.

The magnitude of the treatment effect for the naltrexone and acetaminophen combination observed in the double-blind period was 2.2 fewer monthly migraine days than placebo (p=0.43). Four out of 6 (66.7%) naltrexone and acetaminophen-treated patients experienced 75% reduction in migraine days compared to 1 out of 6 (16.7%) placebo-treated patients (p=0.09).

In the open-label phase, treatment with the naltrexone and acetaminophen combination (n=5) led to 8.2 fewer mean monthly migraine days (from 11.8 to 3.6), representing 69.5% improvement (p=0.03), and 100% of the patients experienced a 50% reduction in monthly migraine days. Adverse events were mild to moderate and transient, included dry mouth, fatigue, sedation, nausea, and feeling jittery.

We postulate that naltrexones toll-like receptor (TLR4) antagonism properties prevent pro-inflammatory cytokines production in the trigeminal ganglion averting "overactive nerves" (laymans term) and migraine. Although this trial used low-dose naltrexone (defined as 1 - 5 mg/day), in future phase 3 studies we will test a range of naltrexone and acetaminophen combination doses. Estimating the impact of Angelman syndrome on parental productivity in Australia using productivity-adjusted life years Angelman syndrome (AS) is a severe neurodevelopmental condition associated with a significant socioeconomic impact. This is the first study to estimate the impact of AS on parental productivity in Australia using cost-of-illness modelling with simulated follow-up over a 10-year period using 2019 as the baseline year. Key data were obtained from a prospective cohort of AS families, peer-reviewed literature, and publicly-available sources. The base-case productivity burden borne by the estimated 330 living parents of the 428 prevalent-persons with AS totalled AUD$1.25 million, corresponding to a loss of 38.42% of PALYs per-parent. This shows that caring for a child with AS has a significant impact on the productivity of affected parents, with a large associated impact on the broader Australian economy. Substance Use Onset in High-Risk 9-13 Year-Olds in the ABCD Study AimA key aim of the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting obscures accurate drug use characterization. Hair toxicology tests provide objective historical substance use data, but are rarely investigated in youth. Here, we compare objective hair toxicology results with self-reported substance use in youth.

MethodsA literature-based substance use risk algorithm identified 696 ABCD Study(R) participants for hair sample collections between baseline and 2-year follow-up (spanning ages 9-13) for laboratory analysis. Chi-square and t-tests assessed differences between participants demographics, positive and negative hair tests, risk algorithm scores, and self-reported substance use.

ResultsHair testing confirmed that 17% of at-risk 9-13 year-olds had evidence of past 3-month use of one (n=99), two (n=17), three (n=3), or four (n=2) drug classes. After considering prescribed medication use, 11% had a positive test incongruent with self- or parent-report. No participant with a positive result self-reported substance use consistent with their toxicology results. Participants with positive tests under-reported use (p<.001), reported less sipping of alcohol (p<.001), and scored higher on the risk algorithm (p<.001) than those with negative hair toxicology.

ConclusionsAn alarming 11% of tested samples in at-risk 9-13 year-olds were positive for at least one unreported substance, suggesting underreporting in this population when participating in a national healthy development study. The degree of underreporting cannot yet be calculated, as at-risk samples were prioritized for assays. Expanded toxicology testing is key to characterize substance use in youth. Deep learning for caries detection using optical coherence tomography Early detection of dental caries has been one of the most predominant topics studied over the last few decades. Conventional examination through visual-tactile inspection and radiography can be inaccurate and destructive to the tooth structure. The development of optical coherence tomography (OCT) has given dentistry an alternative diagnostic technique, which has been proven by numerous studies, that it has better sensitivity, specificity, and non-invasive characteristics. The growing popularity of artificial intelligence (AI) also contributes to a more efficient and effective way of image-based detection and decision-making. However, previous studies, which have attempted to employ AI for caries assessment, did not incorporate high-quality ground truth data. Therefore, this study aims to bypass this issue and highlights the importance of high-quality data. A two-phase study was carried out to explore different methods for caries detection. Initially, the comparison of caries detection based on OCT and apical radiography by 5 experienced clinicians was conducted. Then, five convolutional neural networks (CNNs), including AlexNet, VGG-16, ResNet-152, Xception, and ResNext-101, in the scope of AI were employed to detect caries and compared with the findings of the 5 clinicians. The data was preprocessed and labeled with the ground truth corresponding to microcomputed tomography (micro-CT) with rigorous definition. The weighted Kappa statistics suggested that OCT ({varkappa}= .699, SD = .090) showed a higher accuracy rate than radiography ({varkappa}= .407, SD = .049), and CNNs ({varkappa}= .860, SD = .049) were rated higher than clinicians ({varkappa}= .679, SD = .113), both at a .05 significance level. The best result was carried out by ResNet-152, which demonstrated a high accuracy rate of 95.21% and a sensitivity of 98.85%. These findings illustrate the importance of ground truth data for AI training and the potential of deep CNN algorithms combined with OCT for diagnosing dental caries. Impact of tozinameran (BNT162b2) mRNA vaccine on kidney transplant and chronic dialysis patients: 3-5 months followup BackgroundDetermining the humoral immunogenicity of tozinameran (BNT162b2) vaccine in patients requiring chronic renal replacement therapy, and its impact on COVID-19 morbidity several months after vaccination, will guide risk assessment and subsequent changes in vaccination policy.

MethodsIn a prospective post-vaccination cohort study with up to 5 months follow-up we studied outpatient dialysis and kidney transplant patients and respective healthcare teams. Outcomes were anti S1/S2 antibody response to vaccine or infection and infection rate during followup.

Results175 dialysis patients (40% women, 65{+/-}15 years), 252 kidney transplant patients (33% women, 54{+/-}14 years) and 71 controls (65% women, 44{+/-}14 years) were followed. Three months or longer after vaccination we detected anti S1/S2 IgG antibodies in 80% of dialysis patients, 44% of transplant recipients and 100% of controls, whereas respective rates after infection were 94%, 75% and 100%. Predictors of non-response were older age, diabetes, history of cancer, lower lymphocyte count and lower vitamin-D levels. Factors associated with lower titers in dialysis patients were modality (hemodialysis vs peritoneal) and high serum ferritin levels. In transplant patients, hypertension and higher calcineurin or mTOR inhibitor drug levels were linked with diminished antibody response. Vaccination associated with fewer subsequent infections (HR=0.23, p<0.05). Moreover, higher antibody titers associated with fewer events, HR 0.41 for each unit increased in log10titer (p<0.05).

ConclusionsDialysis patients, and more so kidney transplant recipients, mounted reduced antibody response to COVID-19 mRNA vaccination, and lesser humoral response associated with more infections. Measures to identify and protect non-responsive patients are urgently required.

SignificanceReports on the humoral immunogenicity of SARS-CoV-2 mRNA vaccines in patients with end stage renal disease are scarce, and association with subsequent COVID-19 morbidity is unknown. In this cohort study that included 175 patients treated with dialysis, 252 kidney transplant recipients and 71 control volunteers, the proportion achieving an antibody response was time- and group-dependent, reaching 80%, 44% and 100% at 3 months post prime inoculation. Personal history of vaccination, positive antibody responses and antibody titers associated with significantly lower risk of COVID-19 infection. Thus, in patients with end stage renal disease, SARS-CoV-2 antibody testing may be warranted after vaccination, to identify non-responders at higher risk for disease. Covid-19 Associated Hepatitis in children (CAH-C) during the second wave of SARS-CoV-2 infections in Central India: Is it a complication or transient phenomenon. Objective: While pediatric population has largely remained free of severe COVID-19, in some cases SARS-CoV-2 infection has been associated with complications like Multiple Inflammatory Syndrome in children (MIS-C). We mention another unique presentation subsequent to asymptomatic infection of SARS-CoV-2, a unique form of hepatitis designated by us as COVID-19 Associated Hepatitis in Children (CAH-C). The contrasting clinical presentations, temporal association and viral parameters of CAH-C cases, to the MIS-C cases are presented here. Methods: As a retrospective and follow-up observational study we reviewed all children testing positive for SARS-CoV-2 during study period. Children presenting with sudden onset of hepatitis, elevated transaminases, non-obstructive jaundice, lacking marked inflammatory responses and without evidence of (a) other known causes of acute hepatitis or previous underlying liver disease (b) multi-system involvement were classified as CAH-C, are described here. Results: Among 475 children who tested positive, 47 patients presented with hepatitis, 37 patients who had features of CAH-C, having symptoms of hepatitis only, with un-elevated inflammatory markers and uneventful recovery following supportive treatment. Whereas remaining 10 MIS-C hepatitis had protracted illness, multiple system involvement, required admission to critical care, and had mortality of 30%. Conclusion: With the emergence of newer variants of concern (VOC) including the Delta variant which predominated the second wave of infections in India and has now spread to more than 142 countries with changing presentations, CAH-C might be one of them. Cases of such new entities need to be identified early and differentiated from other emerging syndromes in children during the ongoing pandemic for preventing adversities by timely intervention. Evaluating the Risk of Psilocybin for the Treatment of Bipolar Depression: A Review of the Research Literature and Published Case Studies Growing evidence suggests that psilocybin, the active ingredient in hallucinogenic mushrooms, can rapidly and durably improve symptoms of depression, leading to recent breakthrough status designation by the FDA and legalization for mental health treatment in some jurisdictions. Depression in bipolar disorder is associated with significant morbidity and has few effective treatments. However, there is little available scientific data on the risk of psilocybin use in people with bipolar disorder. Individuals with bipolar disorder have been excluded from modern clinical trials, out of understandable concerns of activating mania or worsening the illness course. As psilocybin becomes more available, people with these disorders will likely seek psilocybin treatment for depression and have likely already been doing so in unregulated settings. Our goal here is to summarize the known risks of psilocybin use (and similar substances) in bipolar disorder and to systematically evaluate examples of published case history data, in order to critically evaluate the relative risk of psilocybin as a treatment for bipolar depression. We found 17 cases suggesting that there is potential risk for activating a manic episode, thereby warranting caution. Nonetheless, the relative lack of systematic data or common case examples indicating risk appears to show that a cautious trial, using modern trial methods focusing on appropriate  set and  setting, targeted at those lowest at risk for mania in the bipolar spectrum (e.g., bipolar 2 disorder), is very much needed, especially given the degree to which depression impacts this population. Dental biofilm microbiota dysbiosis is associated with the risk of acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation Acute graft-versus-host disease (aGVHD) is one of the major causes of death after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Recently, aGVHD onset was linked to intestinal microbiota (IM) dysbiosis. However, other bacterial-rich gastrointestinal sites, such as the mouth, which hosts several distinctive microbiotas, may also impact the risk of GVHD. The dental biofilm microbiota (DBM) is highly diverse and, like the IM, interacts with host cells and modulates immune homeostasis. We characterized changes in the DBM of patients during allo-HSCT and evaluated whether the DBM could be associated with the risk of aGVHD. DBM dysbiosis during allo-HSCT was marked by a gradual loss of bacterial diversity and changes in DBM genera composition, with commensal genera reductions and potentially pathogenic bacteria overgrowths. High Streptococcus and high Corynebacterium relative abundance at preconditioning were associated with a higher risk of aGVHD (67% vs. 33%; HR = 2.89, P = 0.04 and 73% vs. 37%; HR = 2.74, P = 0.04, respectively), while high Veillonella relative abundance was associated with a lower risk of aGVHD (27% vs. 73%; HR = 0.24, P < 0.01). Enterococcus faecalis bloom during allo-HSCT was observed in 20% of allo-HSCT recipients and was associated with a higher risk of aGVHD (100% vs. 40%; HR = 4.07, P < 0.001) and severe aGVHD (60% vs. 12%; HR = 6.82, P = 0.01). To the best of our knowledge, this is the first study demonstrating that DBM dysbiosis is associated with the aGVHD risk after allo-HSCT. A Randomised Trial of a Wearable UV dosimeter for Skin Cancer Prevention BackgroundNon-melanoma skin cancer (NMSC) is the most prevalent cancer in the United States, affecting 5 million people and costing $8.1 billion per year. Despite well-defined guidelines on ultraviolet radiation (UVR) avoidance, it remains difficult for people to assess their individual exposure, as UVR is invisible and the onset of symptoms due to UVR damage are delayed.

MethodsIn a prospective, randomized-controlled trial, 97 patients with a history of actinic keratoses were enrolled from March 2018 to July 2018 and followed over 6 months. 50 patients were given a wearable device that measured UV exposure and a smartphone application that provided both real-time and cumulative UV exposure information, and 47 patients were provided with UV protection counseling by a dermatologist.

ResultsWe observed a significant decrease in the incidence rate of NMSC in the intervention group compared to the control group over 3 months (p = 0.02). We did not observe a significant decrease in the incidence rate of actinic keratoses (AK) in the intervention group compared to the control group. The observed clinical benefit was not accompanied by psychological side effects such as anxiety and depression.

ConclusionsThis study suggests that providing real-time UV exposure data using a wearable UV dosimeter is a safe and effective behavioral change strategy to prevent NMSC. (Funded by the National Cancer Institute, contract HHSN261201700005C; ClinicalTrials.gov number NCT03315286.) Predictors of bovine Schistosoma japonicum infection in rural China In China, bovines are believed to be the most common animal source of human schistosomiasis infections, though little is known about what factors promote bovine infections. The current body of literature features inconsistent, and sometimes contradictory results, and to date, few studies have looked beyond physical characteristics to identify the broader environmental conditions that predict bovine schistosomiasis. Because schistosomiasis is a sanitation-related, water-borne disease transmitted by many animals, we hypothesized that several environmental factors - such as the lack of improved sanitation systems, or participation in agricultural production that is water-intensive - could promote schistosomiasis infection in bovines. Using data collected as a part of a repeat cross-sectional study conducted in rural villages in Sichuan, China from 2007 to 2016, we used a Random Forests, machine learning approach to identify the best physical and environmental predictors of bovine S. japonicum infection. Candidate predictors included: 1) physical/biological characteristics of bovines, 2) human sources of environmental schistosomes, 3) socio-economic indicators, 4) animal reservoirs, and 5) agricultural practices. The density of bovines in a village and agricultural practices such as the area of rice and dry summer crops planted and the use of night soil as an agricultural fertilizer, were among the top predictors of bovine S. japonicum infection in all collection years. Additionally, human infection prevalence, pig ownership and bovine age were found to be strong predictors of bovine infection in at least one year. Our findings highlight that presumptively treating bovines in villages with high bovine density or human infection prevalence may help to interrupt transmission. Furthermore, village-level predictors were stronger predictors of bovine infection than household-level predictors, suggesting future investigations may need to apply a broad ecological lens to identify potential underlying sources of persistent transmission. Mutation burden-orthogonal tumor genomic subtypes delineate responses to immune checkpoint therapy Higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types. Systematic mutational signature analysis on all solid tumors in The Cancer Genome Atlas yielded eight distinct tumor genomic subtypes, which were characterized by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were construed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. Under this hypothesis, we developed a software to classify new tumors submitted to whole-exome sequencing. A pan-cancer dataset containing 973 cases treated with ICIs and clinical response was used for validation, where the classified tumor subtypes were significantly associated with ICI response, independent of cancer type and tumor mutational burden high or low status. The new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

Structured abstractO_ST_ABSBackgroundC_ST_ABSIn cancer therapy, higher-resolution tumor-agnostic biomarkers that predict response to immune checkpoint inhibitor (ICI) therapy are needed. Mutation signatures reflect underlying oncogenic processes that can affect tumor immunogenicity, and thus potentially delineate ICI treatment response among tumor types.

MethodsBased on mutational signature analysis, we developed a stratification for all solid tumors in The Cancer Genome Atlas (TCGA). Subsequently, we developed a new software (GS-PRACTICE) to classify new tumors submitted to whole-exome sequencing. Using existing data from 973 pan-cancer ICI-treated cases with outcomes, we evaluated the subtype-response predictive performance.

ResultsSystematic analysis on TCGA samples identified eight tumor genomic subtypes, which were characterized by features represented by smoking exposure, ultraviolet light exposure, APOBEC enzyme activity, POLE mutation, mismatch repair deficiency, homologous recombination deficiency, genomic stability, and aging. The former five subtypes were presumed to form an immune-responsive group acting as candidates for ICI therapy because of their high expression of immune-related genes and enrichment in cancer types with FDA approval for ICI monotherapy. In the validation cohort, the samples assigned by GS-PRACTICE to the immune-reactive subtypes were significantly associated with ICI response independent of cancer type and TMB high or low status.

ConclusionsThe new tumor subtyping method can serve as a tumor-agnostic biomarker for ICI response prediction and will improve decision making in cancer treatment.

One Sentence SummaryA novel tumor genome subtyping method based on mutation signature analysis can predict response to immune checkpoint therapy orthogonally to tumor mutational burden. Prediction of Subsequent Need for Intensive Oxygen Supplementation in Galveston, Texas: A Retrospective Cohort Study and Multivariable Regression Model of Unvaccinated COVID-19 Patients ObjectiveThe severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) has caused a pandemic claiming more than 4 million lives worldwide. Overwhelming Coronavirus-Disease-2019 (COVID-19) respiratory failure placed tremendous demands on healthcare systems increasing the death toll. Cost-effective prognostic tools to characterize COVID-19 patients likely to progress to severe hypoxemic respiratory failure are still needed.

DesignWe conducted a retrospective cohort study to develop a model utilizing demographic and clinical data collected in the first 12-hours admission to explore associations with severe hypoxemic respiratory failure in unvaccinated and hospitalized COVID-19 patients.

SettingUniversity based healthcare system including 6 hospitals located in the Galveston, Brazoria and Harris counties of Texas.

ParticipantsAdult patients diagnosed with COVID-19 and admitted to one of six hospitals between March 19th and June 31st, 2020.

Primary outcomeThe primary outcome was defined as reaching a WHO ordinal scale between 6-9 at any time during admission, which corresponded to severe hypoxemic respiratory failure requiring high-flow oxygen supplementation or mechanical ventilation.

ResultsWe included 329 participants in the model cohort and 62 (18.8%) met the primary outcome. Our multivariable regression model found that lactate dehydrogenase (OR 2.36), qSOFA score (OR: 2.26), and neutrophil to lymphocyte ratio (OR:1.15) were significant predictors of severe disease. The final model showed an area under curve (AUC) of 0.84. The sensitivity analysis and point of influence analysis did not reveal inconsistencies.

ConclusionsOur study suggests that a combination of accessible demographic and clinical information collected on admission may predict the progression to severe COVID-19 among adult patients with mild and moderate disease. This model requires external validation prior to its use.

STRENGTHS AND LIMITATIONS OF THIS STUDY Our study utilized objective and measurable demographic and clinical information regularly available in healthcare settings even among patients unable to communicate.
 Our primary outcome corresponds to WHO ordinal score which would allow compare our results to other studies and in other settings.
 Our model could serve as an effective point of service tool during early admission to assist in clinical management and allocation of resources to unvaccinated patients.
 Our study is a retrospective study of unvaccinated COVID19 patients, and validation of our prediction model in the rest of our study population is still needed.
 In addition, testing our model in a more recent cohort after emergence of new SARS-CoV-2 variants will be needed to assess its robustness. Simple risk scores to predict hospitalization or death in outpatients with COVID-19 including the Omicron variant ImportanceOutpatient physicians need guidance to support their clinical decisions regarding management of patients with COVID-19, in particular whether to hospitalize a patient and if managed as an outpatient, how closely to follow them.

ObjectiveTo develop and prospectively validate a clinical prediction rule to predict the likelihood of hospitalization for outpatients with COVID-19 that does not require laboratory testing or imaging.

DesignDerivation and temporal validation of a clinical prediction rule, and prospective validation of two externally derived clinical prediction rules.

SettingPrimary and Express care clinics in a Pennsylvania health system.

ParticipantsPatients 12 years and older presenting to outpatient clinics who had a positive polymerase chain reaction test for COVID-19.

Main outcomes and measuresClassification accuracy (percentage in each risk group hospitalized) and area under the receiver operating characteristic curve (AUC).

ResultsOverall, 7.4% of outpatients in the early derivation cohort (5843 patients presenting before 3/1/21) and 5.5% in the late validation cohort (3806 patients presenting 3/1/21 or later) were ultimately hospitalized. We developed and temporally validated three risk scores that all included age, dyspnea, and the presence of comorbidities, adding respiratory rate for the second score and oxygen saturation for the third. All had very good overall accuracy (AUC 0.77 to 0.78) and classified over half of patients in the validation cohort as very low risk with a 1.7% or lower likelihood of hospitalization. Two externally derived risk scores identified more low risk patients, but with a higher overall risk of hospitalization (2.8%).

Conclusions and relevanceSimple risk scores applicable to outpatient and telehealth settings can identify patients with very low (1.6% to 1.7%), low (5.2% to 5.9%), moderate (14.7% to 15.6%), and high risk (32.0% to 34.2%) of hospitalization. The Lehigh Outpatient COVID Hospitalization (LOCH) risk score is available online as a free app: https://ebell-projects.shinyapps.io/LehighRiskScore/.