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Abstract Despite progress in smoking reduction in the past several decades, cigarette smoking remains a significant public health concern world-wide, with many smokers attempting but ultimately failing to maintain abstinence. However, little is known about how decision-making evolves in quitting smokers. Based on preregistered hypotheses and analysis plan ( https://osf.io/yq5th ), we examined the evolution of reinforcement learning (RL), a key component of decision-making, in smokers during acute and extended nicotine abstinence. In a longitudinal, within-subject design, we used a probabilistic reward task (PRT) to assess RL in twenty smokers who successfully refrained from smoking for at least 30 days. We evaluated changes in reward-based decision-making using signal-detection analysis and five RL models across three sessions during 30 days of nicotine abstinence. Contrary to our preregistered hypothesis, punishment sensitivity emerged as the only parameter that changed during smoking cessation. While it is plausible that some changes in task performance could be attributed to task repetition effects, we observed a clear impact of the Nicotine Withdrawal Syndrome (NWS) on RL, and a dynamic relationship between craving and reward and punishment sensitivity over time, suggesting a significant recalibration of cognitive processes during abstinence. In this context, the heightened sensitivity to negative outcomes observed at the last session (30 days after quitting) compared to the previous sessions, may be interpreted as a cognitive adaptation aimed at fostering long-term abstinence. While further studies are needed to clarify the mechanisms underlying punishment sensitivity during nicotine abstinence, these results highlight the need for personalized treatment approaches tailored to individual needs.

Anthropogenic activities have contributed significantly to the erratic supply of potable drinking water to various parts of Ghana posing significant health risks, water scarcity, and security issues for consumers and the environment. This study aimed to assess the physicochemical, microbiological, and toxic element concentrations, determine the Water Quality Index (WQI), estimate potential human health risks, characterize the pollution potential and ecological risks, and identify pollution sources in the Bonsa River using multivariate statistical analyses. The findings indicated that the river water was acidic and the turbidity, Ca2+, Mg2+, DO, Fe, Pb, Hg, Cr, As, aerobic plate count, Escherichia, total, and fecal coliforms were higher than their respective maximum recommended limits. The multivariate analysis indicated illegal mining, geological influences, open defecation and sewerage runoff from waste dumps strongly influenced contaminant sources, transport, and enrichment. The WQI status ranged from 3484 % to 10,525 %, indicating an unsuitable water source for domestic, irrigation, and industrial applications. Children have higher chronic daily exposure to potentially toxic elements compared to adults, and oral exposure to toxic elements was significantly higher than dermal exposure. The cumulative carcinogenic risk exceeded 10−4 and the total non-carcinogenic risk exceeded 1, indicating a high potential for cancer, adverse health risks, and water-related diseases. The pollution and ecological indices indicate a severe contamination water status associated with high ecological sensitivity. This study provides benchmark data for monitoring Bonsa River's water quality and identifying areas for interventions to enhance water quality and safeguard the river's ecosystem.

Background: Viral infections (VIs) have been linked to T-cell exhaustion, a state that impacts the immune system's ability to mount an effective anti-tumor response. This immunosuppressive effect may potentially worsen outcomes in melanoma patients. This study investigates the relationship between a history of VIs and melanoma-specific mortality, with the goal of understanding whether prior history of Vis contribute to an increased risk of mortality in melanoma patients. Materials and methods: A retrospective review of patients in the Utah Population Database (1997–2020) was done. There were 17,754 eligible melanoma patients, with 2286 also having a history of viral infections. Multivariable Cox proportional hazard models were used to assess the effect of VI on melanoma-specific mortality. Results: History of VI was associated with a higher risk of melanoma-specific mortality (HR = 1.33, 95 % CI: 1.07–1.65, P = 0.01). No differences were observed in mortality among patients undergoing surgery and adjuvant immunotherapy. Conclusions: A history of viral infections was associated with higher melanoma-specific mortality. The mechanism of this association and relationship with different types of viral infections and duration of infections remain to be elucidated.

Constructed wetlands are standard conservation practices used to reduce nitrate loads in agricultural watersheds. Many studies have examined the efficiency of denitrification in wetlands under various scenarios, but quantifying the watershed-scale impact of wetlands on downstream nitrate levels is rarely done using field observations. In this study, we estimated nitrate removal in a constructed wetland in the headwaters of Mud Creek, a HUC12 watershed in eastern Iowa, from May–September 2022 and May–September 2023 (a ten-month period). We also measured nitrate loads at four successive downstream sites, three along Mud Creek and one below its confluence with the larger Cedar River. The wetland removed 6,200 kg of nitrate (74% of total inputs). At the three downstream locations in Mud Creek, the percentage of each site’s total nitrate load removed by the wetland decreased to 19, 8.6, and 4.1%—this latter value represents the wetland’s influence on nitrate removal in the entire Mud Creek basin. The wetland’s impact of nitrate loads in the Cedar River was negligible (reduction of 0.02%). The percentage of a site’s drainage area treated by the wetland approximately followed a 1:1 relationship to that site’s percent reduction in nitrate. Profiles of nitrate concentrations in Mud Creek notably varied pre- and post-wetland. Concentrations before the installation steadily decreased along the waterway, while post-wetland concentrations rapidly decreased directly downstream of the wetland and steadily increased at each succeeding site. Our results demonstrate that while the wetland successfully lowered local nitrate levels, its effect on the basin’s overall nitrate loads was minimal. Achieving nutrient reduction goals at the watershed scale solely using constructed wetlands appears infeasible given that the required number of practices greatly exceeds current efforts.

Abstract BackgroundElectronic medical records (EMRs) contain large amounts of detailed clinical information. Using medical record review to identify conditions within large quantities of EMRs can be time-consuming and inefficient. EMR-based phenotyping using machine learning and natural language processing algorithms is a continually developing area of study that holds potential for numerous mental health disorders. ObjectiveThis review evaluates the current state of EMR-based case identification for depression and provides guidance on using current algorithms and constructing new ones. MethodsA scoping review of EMR-based algorithms for phenotyping depression was completed. This research encompassed studies published from January 2000 to May 2023. The search involved 3 databases: Embase, MEDLINE, and APA PsycInfo. This was carried out using selected keywords that fell into 3 categories: terms connected with EMRs, terms connected to case identification, and terms pertaining to depression. This study adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. ResultsA total of 20 papers were assessed and summarized in the review. Most of these studies were undertaken in the United States, accounting for 75% (15/20). The United Kingdom and Spain followed this, accounting for 15% (3/20) and 10% (2/20) of the studies, respectively. Both data-driven and clinical rule-based methodologies were identified. The development of EMR-based phenotypes and algorithms indicates the data accessibility permitted by each health system, which led to varying performance levels among different algorithms. ConclusionsBetter use of structured and unstructured EMR components through techniques such as machine learning and natural language processing has the potential to improve depression phenotyping. However, more validation must be carried out to have confidence in depression case identification algorithms in general.

Within host environments, iron availability is limited, which instigates competition for this essential trace element. In response, bacteria produce siderophores, secondary metabolites that scavenge iron and deliver it to bacterial cells via specific receptors. This role in iron acquisition contributes significantly to bacterial pathogenesis, thereby designating siderophores as virulence factors. While prior research has primarily focused on unravelling the molecular mechanisms underlying siderophore biosynthesis, uptake, and iron sequestration, recent investigations have unveiled additional non-iron chelating functions of siderophores. These emerging roles are being consistently shown to support bacterial pathogenesis. In this review, we present the current understanding of siderophores in various roles: acquiring non-iron metal ions, supporting tolerance to metal-induced and reactive oxygen species (ROS)-induced stresses, mediating siderophore signalling, inducing ROS formation, and functioning in class IIb microcins. By integrating recent findings, this review aims to provide an overview of the diverse roles of siderophores in bacterial pathogenesis.

Objective Cardiovascular diseases (CVD) are the leading cause of mortality and morbidity worldwide. Traditionally, disease surveillance relies on data from surveys, registries, and administrative databases. As medical records undergo global digitization, electronic medical records (EMRs) are emerging as a crucial reservoir of real-world data. However, the extent EMRs are used in CVD surveillance is unknown. We are conducting a scoping review to assess the current state and effectiveness of EMR-based CVD surveillance worldwide. Approach Following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews, we searched MEDLINE and EMBASE bibliographic databases to capture studies on prevalence, incidence, and trend measurements of CVDs using EMRs. Assessed factors include CVD types, modelling methodologies, data linkages, advantages, disadvantages, challenges, and solutions. Due to the qualitative nature of the review, collected data will be narratively synthesized to present overall perspectives. Results Our search algorithm yielded 11,979 citations, of which 5,886 abstracts were selected for screening, in progress at the time of this submission. The interim results indicate that most eligible reports came from the USA (49%), followed by the UK (13%), China (6%), Spain (4%) and Canada (3%). The most common diseases were coronary artery diseases (29%), followed by hypertension (26%), stroke (21%), and heart failure (15%). Conclusions Surveillance of CVD is crucial for prevention and health policy development. While EMRs can be a data source for surveillance, such potential has yet to be fully realized. Implications This study will inform existing research challenges and future opportunities of EMR-based CVD surveillance.

Abstract Aircraft observations of the four chloromethanes: carbon tetrachloride (CCl4), methyl chloride (CH3Cl), dichloromethane (CH2Cl2), and chloroform (CHCl3), collected over North America between 2000 and 2022, were used to evaluate their vertical distributions and temporal trends in the atmosphere. We examine the vertical profiles, from the surface to the lower stratosphere (LS), of these increasingly important contributors to ozone‐depleting chlorine in both altitude and potential temperature space. Airborne chloromethane trends were compared with those measured at long‐term, ground‐based monitoring stations. Below 20 km altitude, CCl4 trends were decreasing at all levels studied in the North American atmosphere (−1.1 ppt yr−1). CHCl3 and CH2Cl2 airborne observations were comparable to ground network measurements: CHCl3 increased between 2000 and 2018 and then decreased leading to a negligible trend over the 22 years studied and CH2Cl2 has been increasing at all levels in the troposphere (+2.41 ppt yr−1, 2000–2022,

We report a case of a new-onset, persistent tremor that developed during a clinical trial (NCT02927236) of intermittent theta burst stimulation [iTBS, a form of repetitive magnetic transcranial magnetic stimulation (rTMS)] for cocaine use disorder. Although the participant exhibited an exceptionally strong clinical response, subsequent unblinding revealed that they received sham iTBS. This case highlights the potential for strong functional neurological placebo responses in rTMS trials, and functional disorders might be a marker of a placebo response. Additionally, we note the possibility that the weak e-fields produced by some sham rTMS systems may induce clinically relevant effects.

Phosphorus (P) plays an integral part in Iowa’s economic and environmental activities through its role as an essential nutrient and waterborne pollutant. However, the amount of phosphorus transported through these activities has not been well quantified. This study estimates the annual mass of P entering and exiting Iowa’s landscape from 1998 to 2022 through seven transport pathways. Four input pathways (fertilizer application, manure production, industrial sources, and human sources) and three output pathways (harvesting, livestock grazing, and stream export) were quantified using various agricultural, economic, and water quality datasets. We also estimated the total mass of P present in the top 0.61 m layer of Iowa’s landscape using results from a statewide soil sampling survey. The harvest component was the largest, with annual values consistently above 200 million kg. This was followed by the fertilizer and manure components, with annual values near 100 million kg. The other components were much smaller; the mean grazing and stream export values were 15 and 19 million kg, respectively, and human and industrial sources were less than 4 million kg. Stream export was the most dynamic pathway, with the largest coefficient of variation (0.59). The net P budget (inputs–outputs) was negative in 20 of the 25 years assessed, indicating that Iowa typically runs a P deficit. A trend analysis revealed that the manure, human, industry, and harvesting components increased across the 1998–2022 period while the grazing component decreased. The mass of P in Iowa’s top layer of soil was 81.5 billion kg—orders of magnitude larger than any individual budget component. This analysis provides a new perspective on P transport pathways in Iowa and may help inform policymakers as they make decisions on the many activities involving P.

Abstract Background Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection. Methods This retrospective cohort study included adult patients (age ≥ 18 years) admitted to Calgary, Canada acute care hospitals who underwent primary total elective hip (THA) or knee (TKA) arthroplasty between Jan 1st, 2013 and Aug 31st, 2020. True SSI conditions were judged by the Alberta Health Services Infection Prevention and Control (IPC) program staff. Using the IPC cases as labels, we developed and validated nine XGBoost models to identify deep incisional SSIs, organ space SSIs and complex SSIs using administrative data, electronic medical records (EMR) free text data, and both. The performance of machine learning models was assessed by sensitivity, specificity, positive predictive value, negative predictive value, F1 score, the area under the receiver operating characteristic curve (ROC AUC) and the area under the precision–recall curve (PR AUC). In addition, a bootstrap 95% confidence interval (95% CI) was calculated. Results There were 22,059 unique patients with 27,360 hospital admissions resulting in 88,351 days of hospital stay. This included 16,561 (60.5%) TKA and 10,799 (39.5%) THA procedures. There were 235 ascertained SSIs. Of them, 77 (32.8%) were superficial incisional SSIs, 57 (24.3%) were deep incisional SSIs, and 101 (42.9%) were organ space SSIs. The incidence rates were 0.37 for superficial incisional SSIs, 0.21 for deep incisional SSIs, 0.37 for organ space and 0.58 for complex SSIs per 100 surgical procedures, respectively. The optimal XGBoost models using administrative data and text data combined achieved a ROC AUC of 0.906 (95% CI 0.835–0.978), PR AUC of 0.637 (95% CI 0.528–0.746), and F1 score of 0.79 (0.67–0.90). Conclusions Our findings suggest machine learning models derived from administrative data and EMR text data achieved high performance and can be used to automate the detection of complex SSIs.

Abstract Background Abstracting cerebrovascular disease (CeVD) from inpatient electronic medical records (EMRs) through natural language processing (NLP) is pivotal for automated disease surveillance and improving patient outcomes. Existing methods rely on coders’ abstraction, which has time delays and under-coding issues. This study sought to develop an NLP-based method to detect CeVD using EMR clinical notes. Methods CeVD status was confirmed through a chart review on randomly selected hospitalized patients who were 18 years or older and discharged from 3 hospitals in Calgary, Alberta, Canada, between January 1 and June 30, 2015. These patients’ chart data were linked to administrative discharge abstract database (DAD) and Sunrise™ Clinical Manager (SCM) EMR database records by Personal Health Number (a unique lifetime identifier) and admission date. We trained multiple natural language processing (NLP) predictive models by combining two clinical concept extraction methods and two supervised machine learning (ML) methods: random forest and XGBoost. Using chart review as the reference standard, we compared the model performances with those of the commonly applied International Classification of Diseases (ICD-10-CA) codes, on the metrics of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Result Of the study sample (n = 3036), the prevalence of CeVD was 11.8% (n = 360); the median patient age was 63; and females accounted for 50.3% (n = 1528) based on chart data. Among 49 extracted clinical documents from the EMR, four document types were identified as the most influential text sources for identifying CeVD disease (“nursing transfer report,” “discharge summary,” “nursing notes,” and “inpatient consultation.”). The best performing NLP model was XGBoost, combining the Unified Medical Language System concepts extracted by cTAKES (e.g., top-ranked concepts, “Cerebrovascular accident” and “Transient ischemic attack”), and the term frequency-inverse document frequency vectorizer. Compared with ICD codes, the model achieved higher validity overall, such as sensitivity (25.0% vs 70.0%), specificity (99.3% vs 99.1%), PPV (82.6 vs. 87.8%), and NPV (90.8% vs 97.1%). Conclusion The NLP algorithm developed in this study performed better than the ICD code algorithm in detecting CeVD. The NLP models could result in an automated EMR tool for identifying CeVD cases and be applied for future studies such as surveillance, and longitudinal studies.

Bone cortical tissues reorganize and remodel in response to tensile forces acting on them, while compressive forces cause atrophy. However, implants support most of the payload. Bones do not regenerate, and stress shielding occurs. The aim is to analyze the biomechanical behavior of a lumbar cage to study the implant’s stress shielding. The ASTM E-9 standard was used with the necessary adjustments to perform compression tests on lumbar and thoracic porcine spinal vertebrae. Twelve cases were analyzed: six with the metal prosthesis and six with the PEEK implant. A mathematical model based on the Hertz contact theory is proposed to assess the stress shielding for endoprosthesis used in spine pathologies. The lumbar spacer (screw) helps to reduce the stress shielding effect due to the ACME thread. The best interspinous spacer is the PEEK screw. It does not embed in bone. The deformation capability increases by 11.5% and supports 78.6 kg more than a system without any interspinous spacer.

This study examined injuries sustained by a six-year-old child dummy in a numerical dolly rollover crash using a Toyota Yaris 2010. A harmonic dynamic system (HDS) composed of spring, dampers, and masses with a Low Back Booster (LBB) is denominated as HDS-LBB model. The HDS-LBB was designed to allow damping movements along three Cartesian axes (X, Y, Z) to reduce the energy transferred to the child by a motor vehicle accident and avoid a high injury risk. The HDS-LBB incorporates springs into the vertical axis to decrease the vertical movement during the rollover. The numerical analysis was conducted using LS-Dyna® R12.1 version during an interval of 1 s, and the boundary conditions were set by the Federal Motor Vehicle Safety Standard (FMVSS) 213 for child restraint recommendations and the FMVSS 208 for a dolly rollover procedure. Data on head and thorax decelerations, neck flexion-extension, and thoracic deflection were acquired at a rate of 1 ms. The injury values obtained by the HDS-LBB were compared with the injury values by another configuration denominated LBB-ISOFIX to assess the effectiveness of the model proposed. The results show a higher peak injury value in the neck and thorax because of seatbelt displacement across the child’s shoulder. Nevertheless, despite this seatbelt behavior, the injuries sustained remained below the Injury Assessment Reference Values (IARVS).

Abstract Objective Coding of obesity using the International Classification of Diseases (ICD) in healthcare administrative databases is under‐reported and thus unreliable for measuring prevalence or incidence. This study aimed to develop and test a rule‐based algorithm for automating the detection and severity of obesity using height and weight collected in several sections of the Electronic Medical Records (EMRs). Methods In this cross‐sectional study, 1904 inpatient charts randomly selected in three hospitals in Calgary, Canada between January and June 2015 were reviewed and linked with AllScripts Sunrise Clinical Manager EMRs. A rule‐based algorithm was created which looks for patients' height and weight values recorded in EMRs. Clinical notes were split into sentences and searched for height and weight, and BMI was computed. Results The study cohort consisted of 1904 patients with 50.8% females and 43.3% > 64 years of age. The final model to identify obesity within EMRs resulted in a sensitivity of 92.9%, specificity of 98.4%, positive predictive value of 96.7%, negative predictive value of 96.6%, and F1 score of 94.8%. Conclusions This study developed a highly valid rule‐based EMR algorithm that detects height and weight. This could allow large‐scale analyses using obesity that were previously not possible.

IntroductionThere are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance.MethodsWe estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method.ResultsThe results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = −0.27, p < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments.DiscussionOur findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.

Abstract We present JBrowse 2, a general-purpose genome annotation browser offering enhanced visualization of complex structural variation and evolutionary relationships. It retains core features of JBrowse while adding new views for synteny, dotplots, breakpoints, gene fusions, and whole-genome overviews. It allows users to share sessions, open multiple genomes, and navigate between views. It can be embedded in a web page, used as a standalone application, or run from Jupyter notebooks or R sessions. These improvements are enabled by a ground-up redesign using modern web technology. We describe application functionality, use cases, performance benchmarks, and implementation notes for web administrators and developers.

Background: This study assessed the potential cost-effectiveness of high (80–100%) vs low (21–35%) fraction of inspired oxygen (FiO2) at preventing surgical site infections (SSIs) after abdominal surgery in Nigeria, India, and South Africa. Methods: Decision-analytic models were constructed using best available evidence sourced from unbundled data of an ongoing pilot trial assessing the effectiveness of high FiO2, published literature, and a cost survey in Nigeria, India, and South Africa. Effectiveness was measured as percentage of SSIs at 30 days after surgery, a healthcare perspective was adopted, and costs were reported in US dollars ($). Results: High FiO2 may be cost-effective (cheaper and effective). In Nigeria, the average cost for high FiO2 was $216 compared with $222 for low FiO2 leading to a −$6 (95% confidence interval [CI]: −$13 to −$1) difference in costs. In India, the average cost for high FiO2 was $184 compared with $195 for low FiO2 leading to a −$11 (95% CI: −$15 to −$6) difference in costs. In South Africa, the average cost for high FiO2 was $1164 compared with $1257 for low FiO2 leading to a −$93 (95% CI: −$132 to −$65) difference in costs. The high FiO2 arm had few SSIs, 7.33% compared with 8.38% for low FiO2, leading to a −1.05 (95% CI: −1.14 to −0.90) percentage point reduction in SSIs. Conclusion: High FiO2 could be cost-effective at preventing SSIs in the three countries but further data from large clinical trials are required to confirm this.

The COVID-19 pandemic, and the subsequent lockdown, had a significant and disproportionate impact on subjects that required the development of clinical technical skills due to the lack of access to simulation classrooms and patients. To directly address this impact, we developed a conceptual framework for the design and implementation of a progressive simulation approach from the perspective of a teacher. This conceptual framework integrates and draws from key theories of simulation design, curriculum integration, learner motivation, and considerations of the facets of good assessment, including modern approach validity. We used the conceptual framework to inform and develop a progressive simulation design to support the development of essential intra-oral suturing skills outside of the classroom, at home, while still being able to provide external feedback as if learners were in the classroom or clinic. Moreover, the approach described significantly extended the available opportunities for deliberate practice, assisting with the automation of essential skills and aiming to better support learner development during face-to-face patient opportunities. Although further work is needed, we believe that our conceptual framework could be applied to any situation where progressive simulation is seen as beneficial, especially if there are elements of key skills that could initially be developed using a simple take-home simulator.

Introduction Accurate identification of medical conditions within a real-time inpatient setting is crucial for health systems. Current inpatient comorbidity algorithms rely on integrating various sources of administrative data, but at times, there is a considerable lag in obtaining and linking these data. Our study objective was to develop electronic medical records (EMR) data-based inpatient diabetes phenotyping algorithms.Materials and methods A chart review on 3040 individuals was completed, and 583 had diabetes. We linked EMR data on these individuals to the International Classification of Disease (ICD) administrative databases. The following EMR-data-based diabetes algorithms were developed: (1) laboratory data, (2) medication data, (3) laboratory and medications data, (4) diabetes concept keywords and (5) diabetes free-text algorithm. Combined algorithms used or statements between the above algorithms. Algorithm performances were measured using chart review as a gold standard. We determined the best-performing algorithm as the one that showed the high performance of sensitivity (SN), and positive predictive value (PPV).Results The algorithms tested generally performed well: ICD-coded data, SN 0.84, specificity (SP) 0.98, PPV 0.93 and negative predictive value (NPV) 0.96; medication and laboratory algorithm, SN 0.90, SP 0.95, PPV 0.80 and NPV 0.97; all document types algorithm, SN 0.95, SP 0.98, PPV 0.94 and NPV 0.99.Discussion Free-text data-based diabetes algorithm can yield comparable or superior performance to a commonly used ICD-coded algorithm and could supplement existing methods. These types of inpatient EMR-based algorithms for case identification may become a key method for timely resource planning and care delivery.

About 40 trans-Neptunian binaries (TNBs) have fully determined orbits with about 10 others being solved except for breaking the mirror ambiguity. Despite decades of study, almost all TNBs have only ever been analyzed with a model that assumes perfect Keplerian motion (e.g., two point masses). In reality, all TNB systems are non-Keplerian due to nonspherical shapes, possible presence of undetected system components, and/or solar perturbations. In this work, we focus on identifying candidates for detectable non-Keplerian motion based on sample of 45 well-characterized binaries. We use MultiMoon , a non-Keplerian Bayesian inference tool, to analyze published relative astrometry allowing for nonspherical shapes of each TNB system’s primary. We first reproduce the results of previous Keplerian fitting efforts with MultiMoon , which serves as a comparison for the non-Keplerian fits and confirms that these fits are not biased by the assumption of a Keplerian orbit. We unambiguously detect non-Keplerian motion in eight TNB systems across a range of primary radii, mutual orbit separations, and system masses. As a proof of concept for non-Keplerian fitting, we perform detailed fits for (66652) Borasisi-Pabu, possibly revealing a J _2 ≈ 0.44, implying Borasisi (and/or Pabu) may be a contact binary or an unresolved compact binary. However, full confirmation of this result will require new observations. This work begins the next generation of TNB analyses that go beyond the point mass assumption to provide unique and valuable information on the physical properties of TNBs with implications for their formation and evolution.

BackgroundCongenital heart defects (CHD) and congenital anomalies of the kidney and urinary tract (CAKUT) account for significant morbidity and mortality in childhood. Dozens of monogenic causes of anomalies in each organ system have been identified. However, even though 30% of CHD patients also have a CAKUT and both organs arise from the lateral mesoderm, there is sparse overlap of the genes implicated in the congenital anomalies for these organ systems. We sought to determine whether patients with both CAKUT and CHD have a monogenic etiology, with the long-term goal of guiding future diagnostic work up and improving outcomes.MethodsRetrospective review of electronic medical records (EMR), identifying patients admitted to Rady Children's Hospital between January 2015 and July 2020 with both CAKUT and CHD who underwent either whole exome sequencing (WES) or whole genome sequencing (WGS). Data collected included demographics, presenting phenotype, genetic results, and mother's pregnancy history. WGS data was reanalyzed with a specific focus on the CAKUT and CHD phenotype. Genetic results were reviewed to identify causative, candidate, and novel genes for the CAKUT and CHD phenotype. Associated additional structural malformations were identified and categorized.ResultsThirty-two patients were identified. Eight patients had causative variants for the CAKUT/CHD phenotype, three patients had candidate variants, and three patients had potential novel variants. Five patients had variants in genes not associated with the CAKUT/CHD phenotype, and 13 patients had no variant identified. Of these, eight patients were identified as having possible alternative causes for their CHD/CAKUT phenotype. Eighty-eight percent of all CAKUT/CHD patients had at least one additional organ system with a structural malformation.ConclusionsOverall, our study demonstrated a high rate of monogenic etiologies in hospitalized patients with both CHD and CAKUT, with a diagnostic rate of 44%. Thus, physicians should have a high suspicion for genetic disease in this population. Together, these data provide valuable information on how to approach acutely ill patients with CAKUT and CHD, including guiding diagnostic work up for associated phenotypes, as well as novel insights into the genetics of CAKUT and CHD overlap syndromes in hospitalized children.

BackgroundSurveillance of hospital-acquired pressure injuries (HAPI) is often suboptimal when relying on administrative health data, as International Classification of Diseases (ICD) codes are known to have long delays and are undercoded. We leveraged natural language processing (NLP) applications on free-text notes, particularly the inpatient nursing notes, from electronic medical records (EMRs), to more accurately and timely identify HAPIs. ObjectiveThis study aimed to show that EMR-based phenotyping algorithms are more fitted to detect HAPIs than ICD-10-CA algorithms alone, while the clinical logs are recorded with higher accuracy via NLP using nursing notes. MethodsPatients with HAPIs were identified from head-to-toe skin assessments in a local tertiary acute care hospital during a clinical trial that took place from 2015 to 2018 in Calgary, Alberta, Canada. Clinical notes documented during the trial were extracted from the EMR database after the linkage with the discharge abstract database. Different combinations of several types of clinical notes were processed by sequential forward selection during the model development. Text classification algorithms for HAPI detection were developed using random forest (RF), extreme gradient boosting (XGBoost), and deep learning models. The classification threshold was tuned to enable the model to achieve similar specificity to an ICD-based phenotyping study. Each model’s performance was assessed, and comparisons were made between the metrics, including sensitivity, positive predictive value, negative predictive value, and F1-score. ResultsData from 280 eligible patients were used in this study, among whom 97 patients had HAPIs during the trial. RF was the optimal performing model with a sensitivity of 0.464 (95% CI 0.365-0.563), specificity of 0.984 (95% CI 0.965-1.000), and F1-score of 0.612 (95% CI of 0.473-0.751). The machine learning (ML) model reached higher sensitivity without sacrificing much specificity compared to the previously reported performance of ICD-based algorithms. ConclusionsThe EMR-based NLP phenotyping algorithms demonstrated improved performance in HAPI case detection over ICD-10-CA codes alone. Daily generated nursing notes in EMRs are a valuable data resource for ML models to accurately detect adverse events. The study contributes to enhancing automated health care quality and safety surveillance.

According to the World Health Organization (WHO), approximately 1.3 billion people experience visual impairments. Daily exposure to various levels of luminous beams directly impacts the front layer of the visible structure, leading to corneal injuries. To comprehensively understand this, we reconstructed a three-dimensional model utilizing the PENTACAM® system. This enabled us to accurately determine the 50th percentile dimensions of the fibrous layer of the eyeball. Using the Ogden mathematical model, we developed a 3D cornea model, treating it as a soft tissue with predictable behavior, considering mechanical properties such as viscoelasticity, anisotropy, and nonlinearity. Employing the Finite Element Method (FEM), we analyzed five distinct test scenarios to explore the structural response of the cornea. Luminous beam properties were instrumental in establishing varying mechanical loads, leading to structural deformations on the corneal surface. Our findings reveal that when a smartphone’s screen emits light at a frequency of 651.72 THz from 200 mm, displacements in the corneal layer can reach up to 9.07 µm. The total load, computed by the number of photons, amounts to 7172.637 Pa.

This article offers a semester-long approach to using generative AI in the public-speaking course. Using critical communication pedagogy, the authors provide practices to navigate the turbulence that has followed the emergence of publicly available generative AI tools. These tools have received negative attention because of their potential to facilitate academic dishonesty and undermine the learning process. Despite this concern, we've chosen to embrace these tools and the transformative power they have for public-speaking curricula. Course: Public Speaking. Objectives: Create an environment of co-learning with students; formulate expectations for student use of AI; develop a reflective process for students to critically evaluate AI material; and design assignments to encourage critical thinking skills.

Helix-destabilizing DNA lesions induced by environmental mutagens such as UV light cause genomic instability by strongly blocking the progression of DNA replication forks (RFs). At blocked RF, single-stranded DNA (ssDNA) accumulates and is rapidly bound by Replication Protein A (RPA) complexes. Such stretches of RPA-ssDNA constitute platforms for recruitment/activation of critical factors that promote DNA synthesis restart. However, during periods of severe replicative stress, RPA availability may become limiting due to inordinate sequestration of this multifunctional complex on ssDNA, thereby negatively impacting multiple vital RPA-dependent processes. Here, we performed a genome-wide screen to identify factors that restrict the accumulation of RPA-ssDNA during UV-induced replicative stress. While this approach revealed some expected "hits" acting in pathways such as nucleotide excision repair, translesion DNA synthesis, and the intra-S phase checkpoint, it also identified SCAI, whose role in the replicative stress response was previously unappreciated. Upon UV exposure, SCAI knock-down caused elevated accumulation of RPA-ssDNA during S phase, accompanied by reduced cell survival and compromised RF progression. These effects were independent of the previously reported role of SCAI in 53BP1-dependent DNA double-strand break repair. We also found that SCAI is recruited to UV-damaged chromatin and that its depletion promotes nascent DNA degradation at stalled RF. Finally, we (i) provide evidence that EXO1 is the major nuclease underlying ssDNA formation and DNA replication defects in SCAI knockout cells and, consistent with this, (ii) demonstrate that SCAI inhibits EXO1 activity on a ssDNA gap in vitro. Taken together, our data establish SCAI as a novel regulator of the UV-induced replicative stress response in human cells.

This systematic meta-analytic review investigated the relations between achievement goals and internalizing symptoms and disorders, namely, anxiety and depression. The number of samples for each focal relationship ranged from 3 to 36. The results indicated significant effect sizes for the relations between mastery-approach goals and anxiety (r = - 0.10) and depression (r = - 0.18), as well as performance-avoidance goals and anxiety (r = 0.25) and depression (r = 0.16). A significant effect size was also found for the relation between performance-approach goals and anxiety (r = 0.15), and a non-significant effect size was observed for the relation between performance-approach goals and depression (r = 0.05). Mastery-avoidance goals were not significantly related to either anxiety (r = 0.08) or depression (r = - 0.13). Several moderators representing the conceptualization of achievement goals (e.g., theoretical model), sample characteristics (e.g., education level), and methodology- and publication-based characteristics (e.g., year of publication) were significant, and suggested avenues for future research. These findings herein have implications for intervention programs that could focus on reducing the links between achievement goals and internalizing problems.

Abstract Introduction Classical teaching of a 2 cm macroscopic surgical margin for surgical treatment of primary penile cancer is overly aggressive. Contemporary evidence suggests narrow but clear margins have similar survival outcomes for localized disease. This study aims to determine the oncological outcome of using a risk‐adapted algorithm to selection of macroscopic surgical margin based on biopsy grade of disease: 5 mm margin for grade 1, 10 mm margin for grade 2, and 20 mm margin for grade 3. Methods This is a retrospective case series of patients who underwent penile‐sparing surgery for biopsy‐proven penile SCC by a single surgeon from May 2010 through to January 2019. Clinicopathological data were extracted from medical records. Primary outcome was the positive margin rate. Secondary outcomes were overall survival (OS), cancer‐specific survival (CSS), metastasis‐free survival (MFS), and local recurrence‐free survival (RFS). Kaplan‐Meier survival analysis was used to determine survival outcomes. Results A total of 21 patients were included in this study. The median age was 65. Pre‐operative biopsy grade was grade 1 in 19.1% of patients, grade 2 in 47.6%, and grade 3 in 33.3%. The median size of tumor on examination was 20 mm. Using a grade‐stratified algorithm for macroscopic surgical margin, only one patient (4.8%) had a positive margin. This patient had G1T3 disease and proceeded to have a total penectomy for oncological clearance. The median margin clearance was 7 mm. The 12‐month OS, CSS, MFS, and local RFS were 94.6%, 94.6%, 81.0%, and 92.3%, respectively. Conclusion This study suggests that using a grade‐stratified approach to aim for a narrower macroscopic surgical margin does not appear to significantly alter the oncological outcome, with a negative margin rate of 95.2% in our this series. This enables more men to be eligible for organ preserving surgery and thereby improve their quality of life in the urinary function and sexual function domain. Larger prospective studies are warranted to confirm these findings.

Background: The initiatives of precision medicine and learning health systems require databases with rich and accurately captured data on patient characteristics. We introduce the Clinical Registry, AdminisTrative Data and Electronic Medical Records (CREATE) database, which includes linked data from 4 population databases: Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease (APPROACH; a national clinical registry), Sunrise Clinical Manager (SCM) electronic medical record (city-wide), the Discharge Abstract Database (DAD), and the National Ambulatory Care Reporting System (NACRS). The intent of this work is to introduce a cardiovascular-specific database for pursuing precision health activities using big data analytics. Methods: We used deterministic data linkage to link SCM electronic medical record data to APPROACH clinical registry data using patient identifier variables. The APPROACH-SCM data set was subsequently linked to DAD and NACRS to obtain inpatient and outpatient cohort data. We further validated the quality of the linkage, where applicable, in these databases by comparing against the Alberta Health Insurance Care Plan registry database. Results: We achieved 99.96% linkage across these 4 databases. Currently, there are 30,984 patients with 35,753 catheterizations in the CREATE database. The inpatient cohort contained 65.75% (20,373/30,984) of the patient sample, whereas the outpatient cohort contained 29.78% (9226/30,984). The infrastructure and the process to update and expand the database has been established. Conclusions: CREATE is intended to serve as a database for supporting big data analytics activities surrounding cardiac precision health. The CREATE database will be managed by the Centre for Health Informatics at the University of Calgary, and housed in a secure high-performance computing environment. Résumé: Contexte: Les initiatives en matière de médecine de précision et les systèmes de santé apprenants ont besoin de bases de données riches et exactes sur les caractéristiques des patients. Nous présentons ici la base de données CREATE (Clinical Registry, Administrative Data and Electronic Medical Records), qui regroupe les données couplées de quatre bases de données populationnelles : le registre clinique national APPROACH (Alberta Provincial Project for Outcome Assessment in Coronary Heart Disease), le système de gestion des dossiers médicaux électroniques SCM (Sunrise Clinical Manager, utilisé à l’échelle municipale), la Base de données sur les congés des patients (BDCP), et le Système national d’information sur les soins ambulatoires (SNISA). Notre objectif est d’offrir une base de données portant précisément sur les maladies cardiovasculaires, afin de soutenir les activités en santé de précision nécessitant l’analyse de mégadonnées. Méthodologie: Nous avons utilisé une méthode de couplage déterministe pour apparier les données du système SCM à celles du registre APPROACH à l’aide de variables d’identification des patients. L’ensemble de données SCM-APPROACH a ensuite été couplé aux données de la BDCP et du SNISA, afin d’obtenir les données des cohortes des patients hospitalisés et des patients ambulatoires. Lorsque c’était possible, nous avons en outre validé la qualité du couplage en comparant les données à celles de la base de données du Régime d’assurance maladie de l’Alberta. Résultats: Nous avons obtenu un taux de couplage de 99,96 % pour les quatre bases de données. À l’heure actuelle, la base de données CREATE compte 30 984 patients ayant subi 35 753 cathétérismes. La cohorte des patients hospitalisés représente 65,75 % (20 373/30 984) de l’échantillon, tandis que la cohorte des patients ambulatoires représente 29,78 % (9226/30 984). L’infrastructure et le processus de mise à jour et d’expansion de la base de données ont été définis. Conclusions: La base de données CREATE est destinée à soutenir les activités d’analyse de mégadonnées nécessaires à la santé cardiaque de précision. Elle sera gérée par le Centre for Health Informatics de l’Université de Calgary et hébergée dans un environnement informatique à haut rendement sécurisé.

BACKGROUND: Hip abductor tendon tears have been identified as a common cause of greater trochanteric pain syndrome. While abductor tendon tears are often managed surgically, the optimal tendon attachment technique remains controversial. PURPOSE: To compare the outcomes of hip abductor tendon repair between the suture anchor (SA) and transosseous suture (TS) techniques. STUDY DESIGN: Systematic review; Level of evidence, 4. METHODS: A literature search was performed in June 2023 in Embase, PubMed, and Web of Science databases. Studies reporting pre- and postoperative clinical outcomes of hip abductor repairs using SA or TS fixation with a minimum follow-up of 12 months were included in our analysis. From 608 studies initially identified, 21 studies (14 SA and 7 TS) with a total of 680 patients met the inclusion criteria. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist guided the reporting and data abstraction, and the quality of the studies was assessed using the methodological index for non-randomized studies checklist. The results were presented as a narrative summary using descriptive statistics such as ranges and agreement statistics. RESULTS: Significant pre- to postoperative improvement in pain scores and functional outcomes were reported on all included studies. The mean improvement on the Harris Hip Score/modified Harris Hip Score was 32.5 (95% CI, 28.4-36.7) for the SA technique versus 21.9 (95% CI, 6.7-37.0) for the TS technique, while mean improvement in pain according to the visual analog scale was 5.1 ± 2.3 for SA and 4.8 ± 2.2 for TS (P = .9). There was a trend toward statistical significance regarding retear rates, with higher rates for SA (6.7% ± 7.6%) versus TS (1.3% ± 4.7%) (t[13.9] = 2.0; P = .06). CONCLUSION: We observed no significant difference between SA and TS regarding improvements in patient-reported hip outcome and pain scores. However, SA trended toward a higher retear rate. Future research should propose a classification scheme that considers tear size and morphology, the extent of associated muscle degeneration, and the distance of tendon retraction to provide more context for the understanding of expected functional outcomes.

Delivering ribonucleoproteins (RNPs) for in vivo genome editing is safer than using viruses encoding for Cas9 and its respective guide RNA. However, transient RNP activity does not typically lead to optimal editing outcomes. Here we show that the efficiency of delivering RNPs can be enhanced by cell-penetrating peptides (covalently fused to the protein or as excipients) and that lipid nanoparticles (LNPs) encapsulating RNPs can be optimized for enhanced RNP stability, delivery efficiency and editing potency. Specifically, after screening for suitable ionizable cationic lipids and by optimizing the concentration of the synthetic lipid DMG-PEG 2000, we show that the encapsulation, via microfluidic mixing, of adenine base editor and prime editor RNPs within LNPs using the ionizable lipid SM102 can result in in vivo editing-efficiency enhancements larger than 300-fold (with respect to the delivery of the naked RNP) without detectable off-target edits. We believe that chemically defined LNP formulations optimized for RNP-encapsulation stability and delivery efficiency will lead to safer genome editing.

PURPOSE: With the growing popularity of badminton worldwide, the incidence of badminton-related ocular injuries is expected to rise. The high velocity of shuttlecocks renders ocular traumas particularly devastating, especially with the possibility of permanent vision loss. This study investigated the mechanism behind ocular complications through simulation analyses of mechanical stresses and pressures upon shuttlecock impact. DESIGN: Computational simulation study. PARTICIPANTS: None. METHODS: A 3-dimensional human eye model was reconstructed based on the physiological and biomechanical properties of various ocular tissues. Finite element analysis simulations involved a frontal collision with a shuttlecock projectile at 128.7 km/hour (80 mph). Intraocular pressure (IOP) changes and tissue stress were mapped and quantified in the following ocular structures: the limbus, ciliary body, zonular fibers, ora serrata, retina, and optic nerve head. MAIN OUTCOME MEASURES: Intraocular pressure and tissue stress. RESULTS: Upon shuttlecock impact, compressive force was transferred to the anterior pole of the cornea, propagating posteriorly to the optic nerve head. Deflection of forces anteriorly contributed to refractory oscillations of compressive and tensile stress of ocular tissue. Initial impact led to a momentary (