Benchmarking saliency methods for chest X-ray interpretation Saliency methods, which "explain" deep neural networks by producing heat maps that highlight the areas of the medical image that influence model prediction, are often presented to clinicians as an aid in diagnostic decision-making. Although many saliency methods have been proposed for medical imaging interpretation, rigorous investigation of the accuracy and reliability of these strategies is necessary before they are integrated into the clinical setting. In this work, we quantitatively evaluate three saliency methods (Grad-CAM, Grad-CAM++, and Integrated Gradients) across multiple neural network architectures using two evaluation metrics. We establish the first human benchmark for chest X-ray interpretation in a multilabel classification set up, and examine under what clinical conditions saliency maps might be more prone to failure in localizing important pathologies compared to a human expert benchmark. We find that (i) while Grad-CAM generally localized pathologies better than the two other saliency methods, all three performed significantly worse compared with the human benchmark; (ii) the gap in localization performance between Grad-CAM and the human benchmark was largest for pathologies that had multiple instances, were smaller in size, and had shapes that were more complex; (iii) model confidence was positively correlated with Grad-CAM localization performance. Our work demonstrates that several important limitations of saliency methods must be addressed before we can rely on them for deep learning explainability in medical imaging.
Adaptation of HL7 FHIR for the exchange of patients' gene expression profiles High-throughput technologies, especially gene expression analyses can accurately capture the molecular state in patients under different conditions. Thus, their application in clinical routine gains increasing relevance and fosters patient stratification towards individualized treatment decisions. Electronic health records already evolved to capture genomic data within clinical systems and standards like FHIR enable sharing within, and even between institutions. However, FHIR only provides profiles tailored to variations in the molecular sequence, while expression patterns are neglected although being equally important for decision making. Here we provide an exemplary implementation of gene expression profiles of a microarray analysis of patients with acute myeloid leukemia using an adaptation of the FHIR genomics extension. Our results demonstrate how FHIR resources can be facilitated in clinical systems and thereby pave the way for usage for the aggregation and exchange of transcriptomic data in multi-center studies.
Inflammasome-related markers at the ICU admission are not associated with outcome in the critically ill COVID-19 patients. PurposeDevelopment of targeted biological therapies for COVID-19 requires reliable biomarkers that could help indicate the responding patients. Hyperactivation of the inflammasome by SARS-CoV2 virus is hypothesized to contribute to severe course of the COVID-19 disease. Therefore, we aimed to evaluate the prognostic value of several inflammasome-related cytokines and proteins at the admission to the intensive care unit (ICU).

Patients and methodsPlasma samples were obtained from 45 critically ill COVID-19 patients and from 10 patients any without any signs of infection (TBI, traumatic brain injury) on admission to the ICU. The concentration of IL-1, IL-1{beta}, IL-18, IL-1RA, galectin-1, ASC, LDH, ferritin, and gasdermin D were analyzed. A novel cell-free caspase-1 plasma assay was developed by inhibitor-based immunoprecipitation followed by Western Blot. Demographic and clinical characteristics were recorded.

ResultsIn-hospital mortality in COVID-19 patients reached 62%. Galectin-1 was 1.8-fold lower in COVID-19 than in TBI patients (17101.84 vs. 30764.20 pg/ml, p=0.007), but other inflammasome-related biomarkers were at similar concentrations. Patients with SOFA score of >9 on admission who were at high risk of death had significantly higher galectin-1 but lower IL-1RA in comparison to low-risk patients (25551.3 pg/ml vs 16302.7 pg/ml, p=0.014; 14.5 pg/ml vs 39.4 pg/ml, p=0.04, respectively). Statistically significant correlations were observed between: IL-1 and platelets (r=-0.37), IL-1{beta} and platelets (r=-0.36), ferritin and INR (r=0.39). Activated caspase-1 p35 was detectable in 12/22 COVID-19 patients but in none of the TBI patients. Its presence was related with higher fibrinogen and lower D-dimers. Moreover, the densitometric analysis showed a significantly higher amount of p35 in patients with SOFA> 9.

ConclusionOur results indicate that the systemic markers of activation of the inflammasome in critically ill COVID-19 patients is not directly related with outcome. Therefore, potential interventions aimed at the inflammasome pathway in this group of patients may be of limited effectiveness and should be biomarker-guided. Factors affecting first return to work following arthroscopic rotator cuff repair: A retrospective observational study in an occupational medicine clinic and single-surgeon practice BackgroundReturn to work (RTW) following arthroscopic rotator cuff repair (aRCR) within New South Wales (NSW), Australia, under compensable schemes has not been reported.

AimsDetermine factors affecting RTW status and time in patients treated with aRCR under state-based compensation schemes, compared to those outside such schemes.

MethodsPatients undergoing aRCR by one surgeon with minimum 1-year follow-up were grouped into those under (CP) or outside (non-CP) workers or vehicle accident compensation schemes, matched by age and gender. RTW status and time were assessed using chi-square analysis and multivariable linear regression.

ResultsOf 1054 available patients, 90 CP patients were identified with 29 consented and matched to non-CP (N=29). A higher proportion of CP patients (17.2 vs 0%, P<0.001) never returned to work and a lower proportion resumed pre-injury duties at first RTW (3 vs 52%, P<0.01). Median time to first RTW did not differ between CP and non-CP groups (5.1 vs 4.4, P=0.86). Smoking (P=0.007) and post-injury activity level (P=0.004) were significantly associated with longer time to first RTW, whereas compensation status was not.

ConclusionsCP patients undergoing aRCR in NSW are at risk of not returning to work. For those that return, there is no significant difference compared to non-CP in time to first RTW. Particularly, patient and management factors associated with extended time to first RTW have been identified. Interventions aimed at modifiable factors such as smoking cessation and increasing preoperative activity may improve future outcomes.

What is already known about this subjectO_LIWork-related injury and disease present a significant financial burden to the Australian economy ($AUD61.8billion per annum), with shoulder conditions due to body stressing accounting for 7% of this total cost (>$AUD4.2billion)
C_LIO_LIPatients receiving compensation appear to have poorer outcomes and take longer to return to work than their non-compensated counterparts, but the degree to which this occurs is variably reported in the literature
C_LIO_LIThe effect of modifiable factors on return to work status and time remain unclear, and have not previously been reported for the Australian population under the New South Wales workers compensation scheme
C_LI

What this study addsO_LIPatients receiving arthroscopic rotator cuff repair under a compensable scheme in New South Wales are at increased risk of not returning to work compared to patients presenting outside of a compensable scheme and patients in equivalent schemes internationally
C_LIO_LIPatients reporting a longer duration of symptoms and smokers are at increased risk of extended time to first return to work
C_LI

What impact this may have on practice or policyO_LIThe study has identified smoking and pre-surgery activity levels as key targets for intervention in patients receiving arthroscopic rotator cuff repair under a workers compensation scheme in New South Wales
C_LIO_LIBy further investigating whether interventions designed to modify these factors are able to favourably affect patient outcomes, there is potential to return patients to their preoperative level of work sooner
C_LI Decreased Diastolic Hydraulic Forces Incrementally Associate With Survival Beyond Conventional Measures of Diastolic Dysfunction AIMSDecreased hydraulic forces during diastole contribute to reduced left ventricular (LV) filling and heart failure with preserved ejection fraction. However, their association with diastolic function and patient outcomes are unknown. The aim of this study was to determine the association between diastolic hydraulic forces, estimated by echocardiography as the atrioventricular area difference (AVAD), and both diastolic function and survival.

METHODS AND RESULTSPatients (n=11,734, median [interquartile range] 3.9 [2.4-5.0] years follow-up, 1,213 events) were selected from the National Echo Database Australia based on the presence of relevant transthoracic echocardiographic measures, LV ejection fraction (LVEF) [&ge;]50%, heart rate 50-100 beats/minute, the absence of moderate or severe valvular disease, and no prior cardiac surgery. AVAD was calculated as the cross-sectional area difference between the LV and left atrium. LV diastolic dysfunction was graded according to 2016 guidelines. AVAD was weakly associated with E/e, left atrial volume index, and LVEF (multivariable global R2=0.15, p<0.001), and not associated with e and peak tricuspid regurgitation velocity. Decreased AVAD was independently associated with poorer survival, and demonstrated improved model discrimination after adjustment for diastolic function grading (C-statistic [95% confidence interval] 0.645 [0.629-0.662] vs 0.607 [0.592-0.623], p<0.001) and E/e (0.639 [0.623-0.655] vs 0.621 [0.604-0.637], p<0.001), respectively.

CONCLUSIONDecreased hydraulic forces, estimated by AVAD, are weakly associated with diastolic dysfunction and demonstrate an incremental prognostic association with survival beyond conventional measures used to grade diastolic dysfunction. Complementary frailty and mortality prediction models on older patients as a tool for assessing palliative care needs BackgroundPalliative care (PC) has demonstrated benefits for life-limiting illnesses. Cancer patients have mainly accessed these services, but there is growing consensus about the importance of promoting access for patients with non-malignant disease. Bad survival prognosis and patients frailty are usual dimensions to decide PC inclusion.

ObjectivesThe main aim of this work is to design and evaluate three quantitative models based on machine learning approaches to predict frailty and mortality on older patients in the context of supporting PC decision making: one-year mortality, survival regression and one-year frailty classification.

MethodsThe dataset used in this study is composed of 39,310 hospital admissions for 19,753 older patients (age >= 65) from January 1st, 2011 to December 30th, 2018. All prediction models were based on Gradient Boosting Machines. From the initial pool of variables at hospital admission, 20 were selected by a recursive feature elimination algorithm based on the random forests GINI importance criterion. Besides, we run an independent grid search to find the best hyperparameters in each model. The evaluation was performed by 10-fold cross-validation and area under the receiver operating characteristic curve and mean absolute error were reported. The Cox proportional-hazards model was used to compare our proposed approach with classical survival methods.

ResultsThe one-year mortality model achieved an AUC ROC of 0.87 {+/-} 0.01; the mortality regression model achieved an MAE of 329.97 {+/-} 5.24 days. The one-year frailty classification reported an AUC ROC of 0.9 {+/-} 0.01. The Spearmans correlation between the admission frailty index and the survival time was -0.1, while the point-biserial correlation between one-year frailty index and survival time was -0.16.

ConclusionsOne-year mortality model performance is at a state-of-the-art level. Frailty Index used in this study behaves coherently with other works in the literature. One-year frailty classifier demonstrated that frailty status within the year could be predicted accurately. To our knowledge, this is the first study predicting one-year frailty status based on a frailty index. We found mortality and frailty as two weakly correlated and complementary PC needs assessment criteria. Predictive models are available online at http://demoiapc.upv.es. Elevated Levels of IL-6 in IgA Nephropathy patients are induced by an Epigenetically Driven Mechanism Triggered by Viral and Bacterial RNA Recently, a several models has been proposed to describe the pathogenesis of Immunoglobulin A nephropathy (IgAN), and among them the multihit and the gut-microbiota. These models explain the pathogenesis of IgAN caused by the production of aberrant IgA, but it is believed further predisposing factors are present, including immunological, genetic, environmental, or nutritional factors that can influence the pathogenesis and that could be useful for development of precision nephrology and personalized therapy.

Newly, the role of IL-6 in pathogenesis is becoming increasingly important. It is essential for glomerular immunoglobulin A deposition and the development of renal pathology in Cd37-deficient mice, even if the reason why levels of IL-6 are elevated in IgAN patients is not well understood. One attainable hypothesis on high levels of IL-6 in IgAN comes out from our recent whole genome DNA methylation screening in IgAN patients, that identified, among others, a hypermethylated region comprising Vault RNA 2-1 (VTRNA2-1), a non-coding RNA also known as precursor of miR-886 (pre-mi-RNA). Consistently, the VTRNA2-1 expression was found down-regulated in IgAN patients.

Here we confirm that VTRNA2-1 is low expressed in IgAN subjects compared to HS and we found that also in transplanted IgAN patients (TP-IgAN), compared to non IgAN transplanted patients (TP), the VTRNA2-1 transcript was expressed at level very low. We found that in IgAN patients with downregulated VTRNA2-1, PKR is overactivated, coherently with the role of the VTRNA2-1 that binds to PKR and inhibits its phosphorylation. The loss of the VTRNA2-1 natural restrain causes, in turn, the activation of CREB by PKR. We found CREB, a classical cAMP-inducible CRE-binding factor interacting with a region of the IL-6 promoter and leading to IL-6 production, overactivated both in IgAN and in TP-IgAN patients. Effectively, in the same patients, we found elevated levels of IL-6 correlating with CREB and PKR phosphorylation.

Since PKR is normally activated by bacterial and viral RNA we hypothesized that these microrganisms can further activate the PKR/CREB/IL-6 pathway leading to an excess of IL-6 production, explaining both the high levels of IL-6, both infection involvement in the disease, both cases of IgAN associated with COVID-19 infection and with COVID-19 RNA-vaccination, and recent data showing microbiota involvment in IgAN.

Effectively, we found that Effectively, we sfound that both the RNA poly(I:C) and the COVID-19 RNA-vaccine stimulation significantly increase the IL-6 levels in IgAN patient PBMCs.

The PKR/CREB/IL-6 pathway may be very important also in the setting of renal transplantation. We found that this pathway is upregulated also in IgAN transplanted patients. Recent studies showed that the cumulative risk of IgA nephropathy recurrence increases after transplant and is associated with a 3.7-fold greater risk of graft loss. Finally, we showed that the IL-6 secretion can be reduced by the PKR inhibitor imoxin.

In conclusion, the discovery of the upregulated VTRNA2-1/PKR/CREB/IL-6 pathway in IgAN patients may provide novel approach to treat the disease and may be useful for development of precision nephrology and personalized therapy, possibly by checking the VTRNA2-1 methylation level in IgAN patients. Relationship Between Patient Sex and Serum Tumor Necrosis Factor Antagonist Drug and Anti-Drug Antibody Concentrations in Inflammatory Bowel Disease; A Nationwide Cohort Study BackgroundAnti-drug antibodies to infliximab (ATI) and adalimumab (ATA) are associated with loss of response to tumor necrosis factor antagonist (anti-TNF) therapy in inflammatory bowel disease (IBD). We evaluated the relationship between patient sex and serum TNF antagonist drug and antibody concentrations in inflammatory bowel disease

MethodsA nationwide multicenter retrospective cohort study was conducted by evaluating patients charts from July 2018 until September 2021. The effect of patient sex on anti-drug antibodies and serum drug concentration in patients with IBD across 7 hospitals was investigated. A subgroup analysis also investigated the effect of anti-TNF combination therapy. Geometric means were calculated, and multiple linear regression was used to estimate the adjusted ratio of geometric means (RoGM) and their 95% confidence intervals (CI).

ResultsIn the total study sample (n = 1093), males receiving infliximab had higher anti-drug antibody concentrations (38.3 vs. 22.3 AU/ml; aRoGM = 1.72, 95% CI: 1.30-2.27, p-value <0.001) compared to females. Additionally, infliximab serum drug concentrations among males were lower compared to females (2.6 vs. 4.1 ug/ml; aRoGM = 0.62, 95% CI: 0.44-0.88, p-value = 0.007). In the subgroup analysis (n = 359), male compared to female patients on combination therapy with infliximab and immunomodulators had similar anti-drug antibody concentrations (30.2 vs. 21.9 AU/ml; aRoGM = 1.38, 95% CI: 0.79-2.40, p-value = 0.254). There was no difference in the anti-drug antibody and serum drug concentrations among males and females on adalimumab.

ConclusionIn patients receiving infliximab, anti-drug antibodies were higher in males than females. Consistent with this, serum drug concentrations were lower in males than females on infliximab. There was no difference in anti-drug antibody and serum drug concentrations among males and females on adalimumab. In addition, no difference in anti-drug antibodies between males and females receiving anti-TNF combination therapy was observed. Comparative profiles of SARS-CoV-2 Spike-specific human milk antibodies elicited by mRNA- and adenovirus-based COVID-19 vaccines Numerous COVID-19 vaccines are authorized globally. To date, [~]71% of doses are comprised of the Pfizer/BioNTech vaccine, and [~]17% the Moderna/NIH vaccine, both of which are mRNA-based. The chimpanzee Ad-based Oxford/AstraZeneca (AZ) vaccine comprises [~]9%, while the Johnson & Johnson/Janssen (J&J) human adenovirus (Ad26) vaccine ranks 4th at [~]2% [1]. No COVID-19 vaccines are yet available for children 0-4. One method to protect this population may be passive immunization via antibodies (Abs) provided in the milk of a lactating vaccinated person. Our early work [2] and other reports [3-5] have demonstrated that unlike the post-SARS-CoV-2 infection milk Ab profile, which is rich in specific secretory (s)IgA, the vaccine response is highly IgG-dominant. In this report, we present a comparative assessment of the milk Ab response elicited by Pfizer, Moderna, J&J, and AZ vaccines. This analysis revealed 86% -100% of mRNA vaccine recipient milk exhibited Spike-specific IgG endpoint titers, which were 12 - 28-fold higher than those measured for Ad vaccine recipient milk. Ad-based vaccines elicited Spike-specific milk IgG in only 33%-38% of recipients. Specific IgA was measured in 52%-71% of mRNA vaccine recipient milk and 17%-23% of Ad vaccine recipient milk. J&J recipient milk exhibited significantly lower IgA than Moderna recipients, and AZ recipients exhibited significantly lower IgA titers than Moderna and Pfizer. <50% of milk of any group exhibited specific secretory Ab, with Moderna recipient IgA titers measuring significantly higher than AZ. Moderna appeared to most frequently elicit >2-fold increases in specific secretory Ab titer relative to pre-vaccine sample. These data indicate that current Ad-based COVID-19 vaccines poorly elicit Spike-specific Ab in milk compared to mRNA-based vaccines and that mRNA vaccines are preferred for immunizing the lactating population. This study highlights the need to design vaccines better aimed at eliciting an optimal milk Ab response. Hyperreflective foci, OCT progression indicators in age-related macular degeneration, include transdifferentiated retinal pigment epithelium PurposeBy optical coherence tomography (OCT) imaging, hyperreflective foci (HRF) indicate progression risk for advanced age-related macular degeneration (AMD) and are in part attributable to ectopic retinal pigment epithelium (RPE). We hypothesized that ectopic RPE are molecularly distinct from in-layer cells and that their cross-retinal course follows Muller glia.

MethodIn clinical OCT (61 eyes, 44 AMD patients, 79.4 {+/-} 7.7 years; 29 female; follow-up = 4.7 {+/-} 0.9 years) one HRF type, RPE plume, was reviewed. Twenty eyes of 20 donors characterized by ex vivo OCT were analyzed by histology (normal, 4; early/intermediate AMD, 7; geographic atrophy (GA), 6; 3 neovascular AMD (nvAMD). Cryosections were stained with antibodies to retinoid (RPE65, CRALPB) and immune (CD68, CD163) markers. In published RPE cellular phenotypes, red immunoreactivity was assessed semi-quantitatively by one observer (none, some cells, all cells).

ResultsTrajectories of RPE plume and cellular debris paralleled Muller glia, whether ordered or subsident, near atrophy borders. RPE corresponding to HRF lost immunoreactivity for retinoid markers and gained immunoreactivity for immune markers. Aberrant immunoreactivity appeared in individual in-layer RPE cells and extended to all abnormal phenotypes. Muller glia remained CRALBP-positive. Plume cells approached and contacted retinal capillaries.

ConclusionGain- and loss-of-function starts with individual in-layer RPE cells and extends to all abnormal phenotypes. Down-regulated RPE retinoid handling may impair rod vision while Muller glia sustain cone vision. Evidence for RPE transdifferentiation, possibly due to ischemia, supports a proposed process of epithelial-mesenchyme transition. Data can propel new biomarkers and therapeutic strategies for AMD.

PrecisHyperreflective foci (HRF) are OCT progression risk indicators in age-related macular degeneration. Abnormal RPE cells including some that correspond to HRF lose immunoreactivity for retinoid markers and gain immunoreactivity for immune markers, indicating molecular transdifferentiation. Knee-extensor strength, symptoms, and need for surgery after two, four, or six exercise sessions/week using a home-based one-exercise program: A randomized dose-response trial of knee-extensor resistance exercise in patients eligible for knee replacement (the QUADX-1 trial). ObjectiveTo investigate firstly the efficacy of three different dosages of one home-based, knee-extensor resistance exercise on knee-extensor strength in patients eligible for knee replacement, and secondly, the influence of exercise on symptoms, physical function and decision on surgery.

MethodOne-hundred and forty patients eligible for knee replacement were randomized to three groups: 2, 4 or 6 home-based knee-extensor resistance exercise-sessions per week (group 2, 4 and 6 respectively) for 12 weeks. Primary outcome: isometric knee-extensor strength. Secondary outcomes: Oxford Knee Score, Knee injury and Osteoarthritis Outcome Score, average knee pain last week (0-10 numeric rating scale), 6-minute walk test, stair climbing test, exercise adherence and "need for surgery".

ResultsPrimary analysis: Intention-to-treat analysis of 140 patients did not find statistically significant differences between the groups from baseline to after 12 weeks of exercise in isometric knee-extensor strength: Group 2 vs. 4 (0.003 Nm/kg (0.2%) [95% CI -0.15 to 0.15], P=0.965) and group 4 vs. 6 (-0.04 Nm/kg (-2.7%) [95% CI -0.15 to 0.12], P=0.628). Secondary analysis: Intention-to-treat analyses showed statistically significant differences between the two and six sessions/week groups in favor of the two sessions/week group for Oxford Knee Score: 4.8 OKS points (15.2%) [1.3 to 8.3], P=0.008) and avg. knee pain last week (NRS 0-10): - 1.3 NRS points (-19.5%) [-2.3 to -0.2], P=0.018. After the 12-week exercise intervention, data were available for 117 patients (N=39/group): 38 (32.5%) patients wanted surgery and 79 (67.5%) postponed surgery. This was independent of exercise dosage.

ConclusionIn patients eligible for knee-replacement we found no between-group differences in isometric knee extensor strength after 2, 4 and 6 knee-extensor resistance exercise sessions per week. We saw no indication of an exercise dose-response relationship for isometric knee-extensor strength and only clinically irrelevant within group changes. For some secondary outcome (e.g. KOOS subscales) we found clinically relevant within group changes, which could help explain why only one in three patients decided to have surgery after the simple home-based exercise intervention.

Trial registrationClinicalTrials.gov identifier: NCT02931058. Preprint: https://doi.org/10.1101/2021.04.07.21254965. 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. 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.) Long-term ozone exposure associated cause-specific mortality risks with adjusted metrics by cohort studies: A systematic review and meta-analysis BACKGROUNDLong-term ozone (O3) exposure could lead to a series of non-communicable diseases and increase the mortality risks. However, cohort-based studies were still rather rare, and inconsistent exposure metrics might impair the credibility of epidemiological evidence synthetisation. To provide more accurate meta-estimation, this review updated the systematic review with inclusion of recent studies and summarised the quantitative associations between O3 exposure and cause-specific mortality risks based on unified exposure metrics.

METHODSResearch articles reporting relative risks between incremental long-term O3 exposure and causes of mortality covering all-cause, cardiovascular diseases, respiratory diseases, chronic obstructive pulmonary disease, pneumonia, ischaemic heart diseases, ischaemic stroke, congestive heart failure, cerebrovascular diseases, and lung cancer, estimated from cohort studies were identified through systematic searches in MEDLINE, Embase and Web of Science. Cross-metric conversion factors were estimated linearly by decadal of observations during 1990-2019. The Hunter-Schmidt random effect estimator was applied to pool the relative risks.

RESULTSA total of 25 studies involving 226,453,067 participants (14 unique cohorts covering 99,855,611 participants) were included in the systematic review. After linearly adjusting the inconsistent O3 exposure metrics into congruity, the pooled relative risks (RR) associated with every 10 nmol mol-1 (ppbV) incremental O3 exposure, by mean of warm-season daily maximum 8-hour average metric, was: 1.014 with 95% confidence interval (CI) ranging 1.009-1.019 for all-cause mortality; 1.025 (95% CI: 1.010-1.040) for respiratory mortality; 1.056 (95% CI: 1.029-1.084) for COPD mortality; 1.019 (95% CI: 1.004-1.035) for cardiovascular mortality; and 1.096 (95% CI: 1.065-1.129) for congestive heart failure mortality. Insignificant mortality risk associations were found for ischaemic heart disease, cerebrovascular diseases and lung cancer.

DISCUSSIONThis review covered up-to-date studies, expanded the O3-exposure associated mortality causes into wider range of categories, and firstly highlighted the issue of inconsistency in O3 exposure metrics. Non-intercept linear regression-based cross-metric RR conversion was another innovation, but limitation lay in the observation reliance, indicating further calibration with more credible observations available. Large uncertainties in the multi-study pooled RRs would inspire more future studies to corroborate or contradict the results from this review.

CONCLUSIONAdjustment for exposure metrics laid more solid foundation for multi-study meta-analysis, and wider coverage of surface O3 observations are anticipated to strengthen the cross-metric conversion in the future. Ever-growing numbers of epidemiological studies supported unneglectable cardiopulmonary hazards and all-cause mortality risks from long-term O3 exposure. However, evidences on long-term O3 exposure associated health effects were still scarce, and hence more relevant studies are encouraged to cover more population with regional diversity.

REGISTRATIONThe review was registered in PROSPERO (CRD42021270637).

FUNDINGThis study is mainly funded by UK Natural Environment Research Council, UK National Centre for Atmospheric Science, Australian Research Council and Australian National Health and Medical Research Council.

HighlightsO_LIUpdated evidence for O3-mortality associations from 25 cohorts has been provided.
C_LIO_LIAdjusting various O3 exposure metrics can provide more accurate risk estimations.
C_LIO_LILong-term O3-exposure was associated with increased mortality from all-causes, respiratory disease, COPD, cardiovascular disease and congestive heart failure.
C_LI A cross-sectional study of infection control measures against COVID-19 and psychological distress among Japanese workers ObjectivesThis study examined the relationship between the status of infection control efforts against COVID-19 in the workplace and workers mental health using a large-scale Internet-based study.

MethodsThis cross-sectional study was based on an Internet monitoring survey conducted during the third wave of the COVID-19 epidemic in Japan. Of the 33,302 people who participated in the survey, 27,036 were included in the analyses. Participants answered whether or not each of 10 different infection control measures were in place at their workplace (e.g. wearing masks at all times during working hours). A Kessler 6 (K6) score of [&ge;]13 was defined as mild psychological distress. The odds ratios (ORs) of psychological distress associated with infection control measures at the workplace were estimated using a multilevel logistic model nested in the prefectures of residence.

ResultsThe OR of subjects working at facilities with 4 or 5 infection control measures for psychological distress was 1.19 (95% confidence interval [CI]: 1.05-1.34, p=0.010), that in facilities with 2 or 3 infection control measures was 1.43 (95% CI: 1.25-1.64, p<0.001), and that in facilities with 1 or no infection control measures was 1.87 (95% CI: 1.63-2.14, p<0.001) compared to subjects whose workplaces had [&ge;]6 infection control measures.

ConclusionOur findings suggest that proactive COVID-19 infection control measures can influence the mental health of workers. Prospectively validated disease-agnostic predictive medicine with augmented intelligence 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. 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. 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 Serological surveys to estimate cumulative incidence of SARS-CoV-2 infection in adults (Sero-MAss study), Massachusetts, July-August 2020- a mail-based cross-sectional study BackgroundThe SARS-CoV-2 pandemic is an unprecedented global health crisis. The state of Massachusetts was especially impacted during the initial stages; however, the extent of asymptomatic transmission remains poorly understood due to limited asymptomatic testing in the "first wave." To address this gap, a geographically representative and contact-free seroprevalence survey was conducted in July-August 2020, to estimate prior undetected SARS-CoV-2 infections.

MethodsStudents, faculty, librarians and staff members at the University of Massachusetts, Amherst without a previous COVID-19 diagnosis were invited to participate in this study along with one member of their household in June 2020. Two separate sampling frames were generated from administrative lists: all undergraduates and their household members (primary sampling group) were randomly selected with probability proportional to population size. All staff, faculty, graduate students and librarians (secondary sampling group) were selected as a simple random sample. After informed consent and a socio-behavioral survey, participants were mailed test kits and asked to return self-collected dried blood spot (DBS) samples. Samples were analyzed via ELISA for anti-SARS-CoV-2 IgG antibodies, and then IgM antibodies if IgG-positive. Seroprevalence estimates were adjusted for survey non-response. Binomial models were used to assess factors associated with seropositivity in both sample groups separately.

ResultsApproximately 27,000 persons were invited via email to assess eligibility. Of the 1,001 individuals invited to participate in the study, 762 (76%) returned blood samples for analysis. In the primary sampling group 548 returned samples, of which 230 enrolled a household member. Within the secondary sampling group of 214 individuals, 79 enrolled a household member. In the primary sample group, 36 (4.6%) had IgG antibodies detected for an estimated weighed prevalence for this population of 5.3% (95% CI: 3.5 to 8.0). In the secondary sampling group, 10 (3.4%) of 292 individuals had IgG antibodies detected for an estimated adjusted prevalence of 4.0% (95% CI: 2.2 to 7.4). No samples were IgM positive. No association was found in either sample group between seropositivity and self-reported work duties or customer-facing hours. In the primary sampling group, self-reported febrile illness since Feb 2020, male sex, and minority race (Black or American Indian/Alaskan Native) were associated with seropositivity. No factors except geographic regions within the state were associated with evidence of prior SARS-CoV-2 infection in the secondary sampling group.

InterpretationThis study provides insight into the seroprevalence of university-related populations and their household members across the state of Massachusetts during the summer of 2020 of the pandemic and helps to fill a critical gap in estimating the levels of sub-clinical and asymptomatic infection. Estimates like these can be used to calibrate models that estimate levels of population immunity over time to inform public health interventions and policy.

FundingUMass Faculty Fund (A Lover); UMass Faculty Discretionary Funds (N Reich); UMass Institute for Applied Life Science "Midigrant" (#169076; A. Lover); and D. Alfandari was supported by grants from the USPHS (R24OD021485). 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. Pre-pandemic mental health and disruptions to healthcare, economic, and housing outcomes during COVID-19: evidence from 12 UK longitudinal studies BackgroundThe COVID-19 pandemic and associated virus suppression measures have disrupted lives and livelihoods and people already experiencing mental ill-health may have been especially vulnerable.

AimTo quantify mental health inequalities in disruptions to healthcare, economic activity and housing.

Method59,482 participants in 12 UK longitudinal adult population studies with data collected prior to and during the COVID-19 pandemic. Within each study we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to three domains: healthcare (medication access, procedures, or appointments); economic activity (employment, income, or working hours); and housing (change of address or household composition). Meta-analyses were used to pool estimates across studies.

ResultsAcross the analysed datasets, one to two-thirds of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. One standard deviation higher pre-pandemic psychological distress was associated with: (i) increased odds of any healthcare disruptions (OR=1.30; [95% CI:1.20-1.40]) with fully adjusted ORs ranging from 1.24 [1.09-1.41] for disruption to procedures and 1.33 [1.20- 1.49] for disruptions to prescriptions or medication access; (ii) loss of employment (OR=1.13 [1.06-1.21]) and income (OR=1.12 [1.06 -1.19]) and reductions in working hours/furlough (OR=1.05 [1.00-1.09]); (iii) no associations with housing disruptions (OR=1.00 [0.97-1.03]); and (iv) increased likelihood of experiencing a disruption in at least two domains (OR=1.25 [1.18-1.32]) or in one domain (OR=1.11 [1.07-1.16]) relative to no disruption.

ConclusionPeople experiencing psychological distress pre-pandemic have been more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening the existing inequalities in mental health. 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. 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. 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.