The sensitivity improved two-test algorithm "SIT2": a universal optimization strategy for SARS-CoV-2 serology BackgroundSerological tests are widely used in various medical disciplines for diagnostic and monitoring purposes. Unfortunately, the sensitivity and specificity of test systems is often poor, leaving room for false positive and false negative results. However, conventional methods used to increase specificity decrease sensitivity and vice versa. Using SARS-CoV-2 serology as an example, we propose here a novel testing strategy: the "Sensitivity Improved Two-Test" or " SIT2" algorithm.

MethodsSIT2 involves confirmatory re-testing of samples with results falling in a predefined retesting-zone of an initial screening test, with adjusted cut-offs to increase sensitivity. We verified and compared the performance of SIT2 to single tests and orthogonal testing (OTA) in an Austrian cohort (1,117 negative, 64 post-COVID positive samples) and validated the algorithm in an independent British cohort (976 negatives, 536 positives).

ResultsThe specificity of SIT2 was superior to single tests and non-inferior to OTA. The sensitivity was maintained or even improved using SIT2 when compared to single tests or OTA. SIT2 allowed correct identification of infected individuals even when a live virus neutralization assay could not detect antibodies. Compared to single testing or OTA, SIT2 significantly reduced total test errors to 0.46% (0.24-0.65) or 1.60% (0.94-2.38) at both 5% or 20% seroprevalence.

ConclusionFor SARS-CoV-2 serology, SIT2 proved to be the best diagnostic choice at both 5% and 20% seroprevalence in all tested scenarios. It is an easy to apply algorithm and can potentially be helpful for the serology of other infectious diseases.
SARS-CoV-2 Transmission and Impacts of Unvaccinated-Only Testing in Populations of Mixed Vaccination Status Community testing programs focused on the unvaccinated population are being enacted in populations with mixed vaccination status to mitigate SARS-CoV-2 spread. Presumably, these policies assume that the unvaccinated are driving transmission, though it is not well understood how viral spread occurs in mixed-status populations. Here, we analyze a model of transmission in which a variable fraction of the population is vaccinated, with unvaccinated individuals proactively screened for infection. By exploring a range of transmission rates, vaccine effectiveness (VE) scenarios, and rates of prior infection, this analysis reveals principles of viral spread in communities of mixed vaccination status, with implications for screening policies. As vaccination rates increase, the proportion of transmission driven by the unvaccinated population decreases, such that most community spread is driven by breakthrough infections once vaccine coverage exceeds 55% (omicron) or 80% (delta), with additional variation dependent on waning or boosted VE. More broadly, the potential impacts of unvaccinated-only screening fall into three distinct parameter regions: (I) "flattening the curve" with little impact on cumulative infections, (II) effectively suppressing transmission, and (III) negligible impact because herd immunity is reached without screening. By evaluating a wide range of scenarios, this work finds broadly that effective mitigation of SARS-CoV-2 transmission by unvaccinated-only screening is highly dependent on vaccination rate, population-level immunity, screening compliance, and vaccine effectiveness against the current variant.
Decoding hand and wrist movement intention from chronic stroke survivors with hemiparesis using a user-friendly, wearable EMG-based neural interface Prosthetics and orthotics have been recognized for decades as a potential means to restore hand function and independence to individuals living with impairment due to stroke. However, 75% of stroke survivors, caregivers, and health care professionals (HCP) believe current practices are insufficient, specifically calling out the upper extremity as an area where innovation is needed to develop highly usable prosthetics/orthotics for the stroke population. A promising method for controlling upper limb technologies is to infer movement intent non-invasively from surface electromyography (EMG) activity. While this approach has garnered significant attention in the literature, existing technologies are often limited to research settings and struggle to meet stated user needs. To address these limitations, we have developed the NeuroLife(R) EMG System, which consists of a wearable forearm sleeve with 150 embedded electrodes and associated hardware and software to record and decode surface EMG. Here, we demonstrate accurate decoding of 12 functional hand, wrist, and forearm movements, including multiple types of grasps from participants with varying levels of chronic impairment from stroke, with an overall accuracy of 77.1{+/-}5.6%. Importantly, we demonstrate the ability to decode a subset of 3 fundamental movements in individuals with severe hand impairment at 85.4{+/-}6.4% accuracy, highlighting the potential as a control mechanism for assistive technologies. Feedback from stroke survivors who tested the system indicates that the sleeves design meets various user needs, including being comfortable, portable, and lightweight. The sleeve is in a form factor such that it can be used at home without an expert technician and can be worn for multiple hours without discomfort. Taken together, the NeuroLife EMG System represents a platform technology to record and decode high-definition EMG for the eventual real-time control of assistive devices in a form factor designed to meet user needs. Prime hAd5 Spike plus Nucleocapsid Vaccination Induces Ten-Fold Increases in Mean T-Cell Responses in Phase 1 Subjects that are Sustained Against Spike Variants In response to the need for a safe, efficacious vaccine that elicits vigorous T cell as well as humoral protection against SARS-CoV-2 infection, we have developed a dual-antigen COVID-19 vaccine comprising both the viral spike (S) protein modified to increase cell-surface expression (S-Fusion) and nucleocapsid (N) protein with an Enhanced T-cell Stimulation Domain (N-ETSD) to enhance MHC class I and II presentation and T-cell responses. The antigens are delivered using a human adenovirus serotype 5 (hAd5) platform with E1, E2b, and E3 regions deleted that has been shown previously in cancer vaccine studies to be safe and effective in the presence of pre-existing hAd5 immunity. The findings reported here are focused on human T-cell responses due to the likelihood that such responses will sustain efficacy against emerging variants, a hypothesis supported by our in silico prediction of T-cell epitope HLA binding for both the first-wave SARS-CoV-2  A strain and the B.1.351 strain K417N, E484K, and N501Y spike and T201I N variants. We demonstrate the hAd5 S-Fusion + N-ETSD vaccine antigens expressed by previously SARS-CoV-2-infected patient dendritic cells elicit Th1 dominant activation of autologous patient T cells, indicating the vaccine antigens have the potential to elicit immune responses in previously infected patients. For participants in our open-label Phase 1b study of the vaccine (NCT04591717; https://clinicaltrials.gov/ct2/show/NCT04591717), the magnitude of Th-1 dominant S- and N-specific T-cell responses after a single prime subcutaneous injection were comparable to T-cell responses from previously infected patients. Furthermore, vaccinated participant T-cell responses to S were similar for A strain S and a series of spike variant peptides, including S variants in the B.1.1.7 and B.1.351 strains. The findings that this dual-antigen vaccine elicits SARS-CoV-2-relevant T-cell responses and that such cell-mediated protection is likely to be sustained against emerging variants supports the testing of this vaccine as a universal booster that would enhance and broaden existing immune protection conferred by currently approved S-based vaccines. Macular vascular complexity analysis of diabetes mellitus by swept-source optical coherence tomographic angiography PurposeTo evaluate the associations of retinal vascular complexity features, including fractal dimension (FD) and blood vessel tortuosity (BVT), with the severity of diabetic retinopathy (DR) by using noninvasive optical coherence tomographic angiography (OCTA).

MethodsThis prospective cross-sectional study recruited ocular-treatment-naive patients with type 2 diabetes mellitus (DM) registered in the community of Guangzhou, China. OCTA was used to obtain the measurements of FD and BVT in the superficial capillary plexus (SCP) and the deep capillary plexus (DCP). Univariate and multivariate linear regression was used to analyse the correlation of FD and BVT in different layers with DR severity.

ResultsA total of 1282 patients with DM (1282 eyes), with a mean age of 64.2{+/-}7.8 years, were included. FD in the DCP decreased and BVT in the DCP increased in DR patients compared to non-DR patients, even after adjusting for confounding factors (P< 0.05). Trend analysis showed a significant decrease in the FD values as the DR progressed, while the BVT progressively increased with worsening DR severity (P< 0.01). The FD in DCP had a statistically significant positive correlation with FD in SCP and a negative correlation with BVT in SCP and BVT in DCP in all of the participants, including the non-DR group, moderate DR group and severe DR group (P< 0.01).

ConclusionFD and BVT determined using OCTA might be useful parameters for objectively distinguishing DR from non-DR and indicating DR progression. Virtual Trials: Causally-validated treatment effects efficiently learned from an observational cancer registry Randomized controlled trials (RCTs) offer a clear causal interpretation of treatment effects, but are inefficient in terms of information gain per patient. Moreover, because they are intended to test cohort-level effects, RCTs rarely provide information to support precision medicine, which strives to choose the best treatment for an individual patient. If causal information could be efficiently extracted from widely available real-world data, the rapidity of treatment validation could be increased, and its costs reduced. Moreover, inferences could be made across larger, more diverse patient populations. We created a "virtual trial" by fitting a multilevel Bayesian survival model to treatment and outcome records self-reported by 451 brain cancer patients. The model recovers group-level treatment effects comparable to RCTs representing over 3200 patients. The model additionally discovers the feature-treatment interactions needed to make individual-level predictions for precision medicine. By learning from heterogeneous real-world data, virtual trials can generate more causal estimates with fewer patients than RCTs, and they can do so without artificially limiting the patient population. This demonstrates the value of virtual trials as a complement to large randomized controlled trials, especially in highly heterogeneous or rare diseases. The ANTsX ecosystem for quantitative biological and medical imaging The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis. Diagnostic Model of in-Hospital Mortality in Patients with Acute ST-Segment Elevation Myocardial Infarction Used Artificial Intelligence Methods BackgroundPreventing in-hospital mortality in Patients with ST-segment elevation myocardial infarction (STEMI) is a crucial step.

ObjectivesThe objective of our research was to to develop and externally validate the diagnostic model of in-hospital mortality in acute STEMI patients used artificial intelligence methods.

MethodsWe divide non-randomly the American population with acute STEMI into a training set, a test set,and a validation set. We converted the unbalanced data into balanc ed data. We used artificial intelligence methods to develop and externally validate the dia gnostic model of in-hospital mortality in acute STEMI patients. We used confusion matrix combined with the area under the receiver operating characteristic curve (AUC) to evaluat e the pros and cons of the above models.

ResultsThe strongest predictors of in-hospital mortality were age, gender, cardiogenic shock, atrial fibrillation(AF), ventricular fibrillation(VF),third degree atrioventricular block,in-hospital bleeding, underwent percutaneous coronary intervention(PCI) during hospitalization, underwent coronary artery bypass grafting (CABG) during hospitalization, hypertension history, diabetes history, and myocardial infarction history.The F2 score of logistic regression in the training set, the test set, and the validation data set were 0.81, 0.6, and 0.59 respectively.The AUC of logistic regression in the training set, the test set, and the validation data set were 0.77, 0.78, and 0.8 respectively. The diagnostic model built by logistic regression was the best.

ConclusionWe had used artificial intelligence methods developed and externally validated the diagnostic model of in-hospital mortality in acute STEMI patients.

We registered this study with WHO International Clinical Trials Registry Platform (ICTRP) (registration number: ChiCTR1900027129; registered date: 1 November 2019). A general computational framework for COVID-19 modelling with applications to testing varied interventions in education environments We construct a spatially-compartmental individual-based model of the spread of Covid-19 in indoor spaces. The model can be used to predict the infection rates in a variety of locations when various non-pharmaceutical interventions (NPIs) are introduced. Tasked by the Welsh Government, we apply the model to secondary schools and Further and Higher Education environments. Specifically, we consider student populations mixing in a classroom and in halls of residence. We focus on assessing the potential efficacy of Lateral Flow Devices (LFDs) when used in broad-based screens for asymptomatic infection or in  test-to-release scenarios in which individuals who have been exposed to infection are released from isolation given a negative result. LFDs are also compared to other NPIs; we find that, although LFD testing can be used to mitigate the spread of Covid-19, it is more effective to invest in personal protective equipment, e.g. masks, and in increasing ventilation quality. In addition, we provide an open-access and user-friendly online applet that simulates the individual-based model, complete with user tutorials to encourage the use of the model to aid educational policy decisions as input infection data evolves (https://bit.ly/CV19_INTER_IBM). 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. The effects of modifiable maternal pregnancy exposures on offspring molar-incisor hypomineralisation: A negative control study ObjectivesO_LITo explore the associations between modifiable maternal pregnancy exposures: pre-pregnancy body mass index (BMI), pregnancy smoking and alcohol consumption with offspring molar-incisor hypomineralisation (MIH).
C_LIO_LITo explore for the presence of residual confounding using negative control analyses.
C_LI

MethodsThis study used data from Avon Longitudinal Study of Parents and Children (ALSPAC), a UK prospective birth cohort. We defined offspring MIH using prospectively collected questionnaire data. We used logistic regression to explore confounder adjusted associations between maternal pre-pregnancy BMI and smoking and alcohol consumption during pregnancy with MIH. We included negative control exposure (paternal BMI, smoking and alcohol around the time of pregnancy) and outcome (offspring dental trauma) analyses to explore for the presence of residual confounding.

Results5536 mother/offspring pairs were included (297 MIH cases [5.4%]). We found a positive association between maternal mean BMI and offspring MIH (OR per 1-kg/m2 difference in maternal BMI: 1.04, 95% CI: 1.00, 1.08). In subsequent analyses, we found evidence that this effect was non-linear and being driven by women in the highest BMI quintiles. In negative control analyses, we found no evidence of association between paternal BMI and offspring MIH (OR: 0.94, 95% CI: 0.89, 1.00) and maternal BMI and offspring dental trauma (OR: 0.99, 95% CI: 0.96, 1.02). There was no clear evidence of an association for maternal pregnancy smoking (OR: 0.76, 95%CI: 0.46, 1.22) and alcohol consumption (OR: 0.79, 95% CI: 0.56, 1.21) with offspring MIH with results imprecisely estimated.

ConclusionIn summary we found evidence of a possible intrauterine effect of high maternal pre-pregnancy BMI on offspring MIH. We did not find robust evidence for an intrauterine effect of maternal pregnancy smoking or alcohol consumption on offspring MIH. Our findings provide further support for women of reproductive age to maintain a healthy weight. Future studies are warranted to explore possible mechanisms on how the pregnancy environment may relate to offspring MIH. Risk of sustained SARS-CoV-2 transmission in Queensland, Australia We used an agent-based model Covasim to assess the risk of sustained community transmission of SARS-CoV-2/COVID-19 in Queensland (Australia) in the presence of high-transmission variants of the virus. The model was calibrated using the demographics, policies, and interventions implemented in the state. Then, using the calibrated model, we simulated possible epidemic trajectories that could eventuate due to leakage of infected cases with high-transmission variants, during a period without recorded cases of locally acquired infections, known in Australian settings as "zero community transmission". We also examined how the threat of new variants reduces given a range of vaccination levels. Specifically, the model calibration covered the first-wave period from early March 2020 to May 2020. Predicted epidemic trajectories were simulated from early February 2021 to late March 2021. Our simulations showed that one infected agent with the ancestral (A.2.2) variant has a 14% chance of crossing a threshold of sustained community transmission (SCT) (i.e., > 5 infections per day, more than 3 days in a row), assuming no change in the prevailing preventative and counteracting policies. However, one agent carrying the alpha (B.1.1.7) variant has a 43% chance of crossing the same threshold; a threefold increase with respect to the ancestral strain; while, one agent carrying the delta (B.1.617.2) variant has a 60% chance of the same threshold, a fourfold increase with respect to the ancestral strain. The delta variant is 50% more likely to trigger SCT than the alpha variant. Doubling the average number of daily tests from [~] 6,000 to 12,000 results in a decrease of this SCT probability from 43% to 33% for the alpha variant. However, if the delta variant is circulating we would need an average of 100,000 daily tests to achieve a similar decrease in SCT risk. Further, achieving a full-vaccination coverage of 70% of the adult population, with a vaccine with 70% effectiveness against infection, would decrease the probability of SCT from a single seed of alpha from 43% to 20%, on par with the ancestral strain in a naive population. In contrast, for the same vaccine coverage and same effectiveness, the probability of SCT from a single seed of delta would decrease from 62% to 48%, a risk slightly above the alpha variant in a naive population. Our results demonstrate that the introduction of even a small number of people infected with high-transmission variants dramatically increases the probability of sustained community transmission in Queensland. Until very high vaccine coverage is achieved, a swift implementation of policies and interventions, together with high quarantine adherence rates, will be required to minimise the probability of sustained community transmission. "What do you mean I can't have a doctor? This is Canada!" - A Qualitative Study of the Myriad Consequences for Unattached Patients Awaiting Primary Care Attachment BackgroundPatient access to primary healthcare (PHC) is the foundation of a strong healthcare system and healthy populations. Attachment to a regular PHC provider, a key to healthcare access, has seen a decline in some jurisdictions. This study explored the consequences of unattachment from a patient perspective, an under-studied phenomenon to date.

MethodsA realist-informed qualitative study was conducted with unattached patients in Nova Scotia, Canada. Semi-structured interviews with nine participants were conducted and transcribed for analysis. The framework method was used to carry out analysis, which was guided by Donabedians model of assessing healthcare access and quality.

ResultsFive key findings were noted in this study: 1) Participants experienced a range of consequences from not having a regular PHC provider. Participants used creative strategies to 2) attempt to gain attachment to a regular PHC provider, and, to 3) address their health needs in the absence of a regular PHC provider. 4) Participants experienced negative feelings about themselves and the healthcare system, and 5) stress related to the consequences and added work of being unattached and lost care.

ConclusionsUnattached patients experienced a burden of care related to lost care and managing their own health and related information, due to the download of medical record management and system navigation to them. These findings may underestimate the consequences for further at-risk populations who would not have been included in our recruitment. This may result in poorer health outcomes, which could be mitigated by interventions at the structural level, such as enhanced centralized waitlists to promote attachment. Such waitlists may benefit from a triage approach to appropriately attach patients based on need. The effect of D-cycloserine on brain processing of breathlessness over pulmonary rehabilitation - an experimental medicine study BackgroundPulmonary rehabilitation is the best treatment for chronic breathlessness in COPD but there remains an unmet need to improve efficacy. Pulmonary rehabilitation has strong parallels with exposure-based cognitive behavioural therapies (CBT), both clinically and in terms of brain activity patterns. The partial NMDA-receptor agonist, D-cycloserine has shown promising results in enhancing efficacy of CBT, thus we hypothesised that it would similarly augment the effects of pulmonary rehabilitation in the brain. Positive findings would support further development in phase 3 clinical trials.

Methods72 participants with mild-to-moderate COPD were recruited to a double-blind pre-registered (ID: NCT01985750) experimental medicine study running parallel to a pulmonary rehabilitation course. Participants were randomised to 250mg D-cycloserine or placebo, administered immediately prior to the first four sessions of pulmonary rehabilitation. Primary outcome measures were differences between D-cycloserine and placebo in brain activity in the anterior insula, posterior insula, anterior cingulate cortices, amygdala and hippocampus following completion of pulmonary rehabilitation. Secondary outcomes included the same measures at an intermediate time point and voxel-wise difference across wider brain regions.

ResultsNo difference between D-cycloserine and placebo groups was observed across the primary or secondary outcome measures. Questionnaire and measures of respiratory function showed no group difference.

ConclusionsThis is the first study testing brain-active drugs in pulmonary rehabilitation. Rigorous trial methodology and validated surrogate end-points maximised statistical power. Although increasing evidence supports therapeutic modulation of NMDA pathways to treat symptoms, we conclude that a phase 3 clinical trial of D-cycloserine would not be worthwhile.

Key MessagesO_ST_ABSWhat is the key question?C_ST_ABSDoes the partial NMDA-receptor agonist, D-cycloserine, augment the effects of pulmonary rehabilitation on breathlessness related brain activity?

What is the bottom line?Rigorous trial methodology and validated surrogate end-points revealed no effect of D-cycloserine on breathlessness related brain activity across pulmonary rehabilitation.

Why read on?This study highlights both the value of functional magnetic resonance imaging in "de-risking" expensive clinical trials and provides detailed investigation of brain-targeted points for pharmacological treatments of breathlessness. Estimating real-world COVID-19 vaccine effectiveness in Israel using aggregated counts The vaccination roll-out of the COVID-19 vaccines in Israel has been highly successful. By February 22th, approximately 47% of the population has already been administered at least one dose of the BNT162b2 vaccine. Efforts to estimate the true real-world effectiveness of the vaccine have been hampered by disease dynamics and social-economic discrepancies. Here, using counts of positive and hospitalized cases of vaccinated individuals, we conduct a sensitivity analysis of the vaccine effectiveness. Under an assumption of no effectiveness on the first two weeks after the 1st dose, we observe very low effectiveness on the third week. After the 2nd dose, on weeks 1 and 2 we find 73-85% effectiveness in reducing positive cases, hospitalizations, and severe cases, which increase to 89-97% effectiveness 14 days after the 2nd dose. As more granular data will be available, it will be possible to extract more exact estimates; however, the emerging evidence suggests that the vaccine is highly effective. Prospectively validated augmented intelligence for disease-agnostic predictions of clinical success for novel therapeutics Despite numerous superhuman achievements in complex challenges1,2, standalone AI does not free life science from the long-term bottleneck of linearly extracting new knowledge from exponentially growing new data3, severely limiting the success rate of drug discovery4. Inspired by the state-of-the-art AI training methods, we trained a human-centric hybrid augmented intelligence5 (HAI) to learn a foundation model6 that extracts all-encompassing knowledge of human physiology and diseases. To evaluate the quality of HAIs extracted knowledge, we designed the public, prospective prediction of pivotal ongoing clinical trial outcomes at large scale (PROTOCOLS) challenge to benchmark HAIs real-world performance of predicting drug clinical efficacy without access to human data. HAI achieved a 10.5-fold improvement from the baseline with 99% confidence7 in the PROTOCOLS validation, readily increasing the average clinical success rate of investigational new drugs from 7.9%8 to 90% for almost any human diseases9,10. The validated HAI confirms that exponentially extracted knowledge alone is sufficient for accurately predicting drug clinical efficacy, effecting a total reversal of Erooms law4. HAI is also the worlds first clinically validated model of human aging that could substantially speed up the discovery of preventive medicine for all age-related diseases11. Our results demonstrate that disruptive breakthroughs necessitate the smallest team size to attain the largest HAI for optimal knowledge extraction from high-dimensional low-quality data space, thus establishing the first prospective proof of the previous discovery that small teams disrupt12. The global adoption of training HAI provides a well-beaten economic path to mass-produce scientific and technological breakthroughs via exponential knowledge extraction and better designs of data labels for training better-performing AI13. Spatial Allocation of Scarce COVID-19 Vaccines The COVID-19 Vaccines Global Access (COVAX) is an initiative led by the World Health Organization (WHO) and other partners that aims for an equitable access of COVID-19 vaccines. Despite a potential heterogeneous disease burden across space, countries receiving allotments of vaccines via COVAX may want to follow WHOs allocation rule and distribute vaccines to their jurisdictions based on the jurisdictions relative population size. Utilizing economic-epidemiological modeling, we benchmark the performance of this ad hoc allocation rule by comparing it to the rule that minimizes the economic damages and expenditures over time, including a penalty cost representing the social costs of deviating from the ad hoc allocation. Under different levels of vaccine scarcity and different demographic characteristics, we consider scenarios where length of immunity and compliance to travel restrictions vary, and consider the robustness of the rules when assumptions regarding these factors are incorrect. The benefits from deviating are especially high when immunity is permanent, when there is compliance to travel restrictions, when the supply of vaccine is low, and when there is heterogeneity in demographic characteristics. Interestingly, a lack of compliance to travel restrictions pushes the optimal allocations of vaccine towards the ad hoc and improves the relative robustness of the ad hoc rule, as the mixing of the populations reduces the spatial heterogeneity in disease burden.

JEL ClassificationC61, H12, H84, I18, Q54 The effect of hypersensitivity pneumonitis guideline on pathologic diagnosis of interstitial pneumonia Hypersensitivity pneumonitis (HP) and interstitial pneumonia (IP) have several overlapping characteristics, and a high diagnostic concordance rate of HP is rarely obtained. New guideline, highly influenced by pathology, were devised for its diagnosis. We recently reported that the 2020 HP guideline may result in a possible overdiagnosis of fibrotic HP (fHP) through multidisciplinary discussion. Here, we attempted to investigate the impact of the 2020 HP guideline on the pathological diagnosis of cases previously diagnosed as IP. We classified 247 cases with fibrotic IP diagnoses sourced from 2014-2019 into three categories according to the 2020 HP guideline: typical, probable, and indeterminate HP. The original pathological diagnosis and categorization based on the 2020 HP guideline were compared. The clinical data including serum data and pulmonary function tests were compared among groups. The number of cases that changed to HP from an original diagnosis other than HP based on the guideline was 56 (23%). The clinical data of these cases bore a greater resemblance to cases diagnosed as indeterminate for HP than those diagnosed as typical or probable. The ratio of typical and probable HP to the total cases was significantly lower when using a transbronchial lung cryobiopsy (TBLC). Based on the new guideline, the pathological diagnosis of HP efficiently excluded HP cases but increased the rate of HP diagnosis for cases with fibrotic IP that may not suit an HP diagnosis. Thus, a TBLC may not be useful when imparting findings for fibrotic HP diagnosis using the new criteria.

Key messagesO_LIWhat is the key question? >
Does the 2020 HP Guideline improve pathological diagnosis?
C_LIO_LIWhat is the bottom line? >
By applying the new guideline, about 1/4 of the pathological diagnoses were changed from not chronic HP to probable or typical fHP, but most of the changed cases showed a clinical picture closer to not chronic HP.
C_LIO_LIWhy read on? >
To understand that simple application of the pathological criteria of the HP guideline may cause a misleading diagnosis.
C_LI Heading for personalized rTMS in tinnitus: reliability of individualized stimulation protocols in behavioral and electrophysiological responses BackgroundRepetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation tool potentially modulating pathological brain activity. Its clinical effectiveness is hampered by varying results and characterized by inter-individual variability in treatment responses. RTMS individualization might constitute a useful strategy to overcome this variability. A precondition for this approach would be that repeatedly applied protocols result in reliable effects. The condition tinnitus provides the advantage of immediate behavioral consequences (tinnitus loudness changes) after interventions and thus offers an excellent model to exemplify TMS personalization.

ObjectiveThe aim was to investigate the test-retest reliability of short rTMS stimulations in modifying tinnitus loudness and oscillatory brain activity as well as to examine the feasibility of rTMS individualization in tinnitus.

MethodsThree short verum (1Hz, 10Hz, 20Hz; 200 pulses) and one sham (0.1Hz; 20 pulses) rTMS protocol were administered on two different days in 22 tinnitus patients. Before and after each protocol, oscillatory brain activity was recorded with electroencephalography (EEG) together with behavioral tinnitus loudness ratings. RTMS individualization was executed by dint of behavioral and electrophysiological responses. Stimulation responders were identified via consistent sham-superior increases in tinnitus loudness (behavioral responders) and alpha power increases or gamma power decreases (alpha responders/ gamma responders) in accordance to the prevalent neurophysiological models for tinnitus.

ResultsIt was feasible to identify individualized rTMS protocols featuring reliable tinnitus loudness changes (55% behavioral responder), alpha increases (91% alpha responder) and gamma decreases (100% gamma responder) respectively. Alpha responses primary occurred over parieto-occipital areas, whereas gamma responses mainly appeared over frontal regions. Contrary, test-retest correlation analyses per protocol on a group-level were not significant neither for behavioral nor for electrophysiological effects. No associations between behavioral and EEG responses were given.

ConclusionRTMS individualization via behavioral and electrophysiological data in tinnitus can be considered as a feasible approach to overcome low reliability on group-level. The present results open the discussion favoring personalization utilizing neurophysiological markers rather than behavioral responses. These insights are not only useful for the rTMS treatment of tinnitus but also for neuromodulation interventions in other pathologies as our results suggest that the individualization of stimulation protocols is feasible despite absent group-level reliability. 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.) Effectiveness of mRNA and ChAdOx1 COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe outcomes with variants of concern in Ontario SARS-CoV-2 variants of concern (VOC) are more transmissible and have the potential for increased disease severity and decreased vaccine effectiveness. We estimated the effectiveness of BNT162b2 (Pfizer-BioNTech Comirnaty), mRNA-1273 (Moderna Spikevax), and ChAdOx1 (AstraZeneca Vaxzevria) vaccines against symptomatic SARS-CoV-2 infection and COVID-19 hospitalization or death caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2) VOCs in Ontario, Canada using a test-negative design study. Effectiveness against symptomatic infection [&ge;]7 days after two doses was 89-92% against Alpha, 87% against Beta, 88% against Gamma, 82-89% against Beta/Gamma, and 87-95% against Delta across vaccine products. The corresponding estimates [&ge;]14 days after one dose were lower. Effectiveness estimates against hospitalization or death were similar to, or higher than, against symptomatic infection. Effectiveness against symptomatic infection is generally lower for older adults ([&ge;]60 years) compared to younger adults (<60 years) for most of the VOC-vaccine combinations. Serum proteome analysis of systemic JIA and related pulmonary alveolar proteinosis identifies distinct inflammatory programs and biomarkers ObjectivesRecent observations in systemic Juvenile Idiopathic Arthritis (sJIA) suggest an increasing incidence of high-mortality interstitial lung disease, characterized by a variant of pulmonary alveolar proteinosis (PAP). Co-occurrence of macrophage activation syndrome (MAS) and PAP in sJIA suggested a shared pathology, but sJIA-PAP patients also commonly experience features of drug reaction such as atypical rashes and eosinophilia. We sought to investigate immunopathology and identify biomarkers in sJIA, MAS, and sJIA-PAP.

MethodsWe used SOMAscan to measure >1300 analytes in sera from healthy controls and patients with sJIA, MAS, sJIA-PAP and other related diseases. We verified selected findings by ELISA and lung immunostaining. Because the proteome of a sample may reflect multiple states (sJIA, MAS, sJIA-PAP), we used regression modeling to identify subsets of altered proteins associated with each state. We tested key findings in a validation cohort.

ResultsProteome alterations in active sJIA and MAS overlapped substantially, including known sJIA biomarkers like SAA and S100A9, and novel elevations of heat shock proteins and glycolytic enzymes. IL-18 was elevated in all sJIA groups, particularly MAS and sJIA-PAP. We also identified an MAS-independent sJIA-PAP signature notable for elevated ICAM5, MMP7, and allergic/eosinophilic chemokines, which were all previously associated with lung damage. Immunohistochemistry localized ICAM5 and MMP7 in sJIA-PAP lung. ICAM5s ability to distinguish sJIA-PAP from sJIA/MAS was independently validated.

ConclusionsSerum proteins support an sJIA-to-MAS continuum, help distinguish sJIA, sJIA/MAS, and sJIA-PAP, and suggest etiologic hypotheses. Select biomarkers, such as ICAM5, could aid in early detection and management of sJIA-PAP. Genetic factors affecting immune phenotypes in type 1 diabetes Large inter-individual variability in immunological cell composition and function determines immune responses in general and susceptibility to immune-mediated diseases in particular. While much has been learned about the genetic variants relevant for type 1 diabetes, the pathophysiological mechanisms through which these variations exert their effects are unknown. In this study, we characterize the genetic factors influencing immune responses in patients with type 1 diabetes. Genetic variants that determine susceptibility to T1D significantly affect T cell composition. Specifically, the CCR5+ regulatory T cells associate with T1D through the CCR region, suggesting a shared genetic regulation. Genome-wide quantitative trait loci (QTL) mapping analysis of immune traits revealed 15 genetic loci that influence immune responses in T1D. Among them, 12 have never been reported in healthy population studies, implying a disease-specific genetic regulation. Altogether this study provides new insights into the genetic factors that affect immunological responses in T1D. RELATIONSHIP BETWEEN ADVERSE EVENTS PREVALENCE, PATIENT SAFETY CULTURE AND PATIENT SAFETY PERCEPTION IN A SINGLE SAMPLE OF PATIENTS: A CROSS-SECTIONAL AND CORRELATIONAL STUDY ObjectiveTo assess the relationship between Adverse Events Prevalence, Patient Safety Culture and Patient Safety Perception.

DesignCross-sectional, ex post facto comparative study on a single sample of patients.

SettingFour medium-high-level hospitals were included in the study -- two public and two private from Zulia State in Venezuela.

Participants556 medical records and patients were studied for the prevalence and patient safety perception study, and 397 of the healthcare providers involved in the care of these patients were surveyed for the patient safety culture study, at two public and two private hospitals.

Outcome measurementThe primary outcome of this study was the Association between Adverse Events Prevalence, Patient Safety Culture and Patient Safety Perception, and according to hospital funding type, private and public.

ResultsAn inverse association was observed between Adverse Events Prevalence and its severity and Patient Safety Culture Index (PSCI: rho=-0.8 p=0.5) (95% CI=0.26-0.10) and Patient Safety Perception Index (PSPI: rho=-0.6 p=0.18) (95% CI=0.10-0.28), which were protective factors for patient safety. No association was identified between Patient Safety Culture and Patient Safety Perception (rho=0.0001). No statistical differences were identified by hospital type (p=0.93) (95% CI=0.70-1.2).

ConclusionsThe analysis of the variable correlations studied (AEP, PSC and PSP) within the same sample offers an interesting and useful perspective. In this sample, although no correlation was observed between the three variables as an interacting set, some correlation patterns were observed between pairs of variables that could guide further studies.

Strengths and limitations of this studyO_LIThe association analysis of the three main variables (adverse events prevalence, patient safety culture and patient safety perception) in the same sample of patients and health professionals and over the same time period during which the care process and, consequently, the adverse events took place is an unprecedented and innovative approach, which contributes to the body of knowledge on this field of study.
C_LIO_LIThe relational theoretical framework produced provides a "map" that can facilitate decision-taking and which establishes the variables that should be considered a priority. As a result, it is highly likely to have an impact on the clinical efficiency and safety of healthcare institutions and services.
C_LIO_LIThe study was carried out at both private and public hospitals, enabling the behaviour of the aforementioned variables to be compared and analysed at each type of institution. The literature to date on this approach is scarce and offers little information.
C_LIO_LIAlthough the sample of hospitals selected is not representative of Venezuela, it is representative of the hospitals of one of the most productive and populated states in the country.
C_LIO_LIDuring stages 1 and 2, some resistance to collaborating with and completing the evaluation instruments was identified among the health professionals.
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