High-Throughput Compound Quality Assessment with High-Mass-Resolution Acoustic Ejection Mass Spectrometry: An Automatic Data Processing Toolkit.

Pharmacological screening heavily relies on the reliability of compound libraries. To ensure the accuracy of screening results, fast and reliable quality control (QC) of these libraries is essential. While liquid chromatography (LC) with ultraviolet (UV) or mass spectrometry (MS) detection has been employed for molecule QC on small sample sets, the analytical throughput becomes a bottleneck when dealing with large libraries. Acoustic ejection mass spectrometry (AEMS) is a high-throughput analytical platform that covers a broad range of chemical structural space. In this study, we present the utilization of an AEMS system equipped with a high-resolution MS analyzer for high-throughput compound QC. To facilitate efficient data processing, which is a key challenge for such a high-throughput application, we introduce an automatic data processing toolkit that allows for the high-throughput assessment of the sample standards' quantitative and qualitative characteristics, including purity calculation with the background processing option. Moreover, the toolkit includes a module for quantitatively comparing spectral similarity with the reference library. Integrating the described high-resolution AEMS system with the data processing toolkit effectively eliminates the analytical bottleneck, enabling a rapid and reliable compound quality assessment of large-scale compound libraries.

Assessing teachers' intervention-related expectations and self-efficacy: An examination of the factor structure of the implementation beliefs assessment.

Individual-level determinants are hypothesized to enable or prevent successful implementation of evidence-based practices, yet there are limited options for measuring theory-informed, individual-level determinants that influence teachers' and other implementers' delivery of school-based interventions. The goal of this study was to develop a self-report scale that measures variables that have been associated with initial and sustained behavior change related to school-based intervention implementation according to the health action process approach (HAPA). Participants were a nationally representative sample of kindergarten through Grade 12 public school teachers, stratified by grade level and geographical region. Item generation was based on a systematic review of the literature on outcome expectations and self-efficacy, the core constructs related to initiating and sustaining behavior change from the HAPA and in consultation with the theory developer. The sample was randomly split; half of the sample was used for exploratory factor analysis (EFA), and the other half was used for confirmatory factor analysis (CFA). The EFA resulted in a final factor structure of three dimensions of the Implementation Beliefs Assessment (IBA): (a) implementation self-efficacy, (b) positive outcome expectations, and (c) negative outcome expectations. This structure was supported in the other half of the sample using CFA. Additional analyses supported the reliability of IBA data. The IBA represents a step forward toward psychometrically sound measurement of factors associated with initial and sustained behavior change. Implications for future research are discussed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Antegrade ejaculation preservation in surgical treatment for benign prostatic hyperplasia: quest for balance between voiding and sexual function.

PURPOSE OF REVIEW: Surgical treatment of benign prostatic hyperplasia (BPH) carries a significant risk of ejaculation dysfunction. Preservation of antegrade ejaculation while providing effective, well tolerated, and durable treatment of BPH is a paramount component of physical and sexual well being for significant number of men. We reviewed available literature with an aim of providing status on antegrade ejaculation preserving BPH surgical therapies. RECENT FINDINGS: Minimally invasive surgical therapies for BPH have been developed over the last decade, with significant marketing emphasis on their potential for preservation of antegrade ejaculation. However, the question about durability of relief of bladder outlet obstruction remains. Parallel to this technological development, the understanding of anatomical structures involved in ejaculation have resulted in technical modifications of well established surgical treatments modalities like transurethral resection of prostate, endoscopic enucleation of prostate and simple prostatectomy, thereby providing safe and durable relief of bladder outlet obstruction secondary to BPH with a satisfactory preservation of antegrade ejaculation. SUMMARY: Preservation of antegrade ejaculation is an important goal for significant number of men needing BPH surgery. Novel minimally invasive surgical technologies have been developed for this purpose; but understanding of the anatomical structures essential for antegrade ejaculation have allowed technical modification of existing surgical techniques with excellent preservation of antegrade ejaculation.

Community-Directed Vector Control to Accelerate Onchocerciasis Elimination.

Onchocerciasis, or river blindness, has historically been one of the most important causes of blindness worldwide, and a major cause of socio-economic disruption, particularly in sub-Saharan Africa. Its importance as a cause of morbidity and an impediment to economic development in some of the poorest countries in the world motivated the international community to implement several programs to control or eliminate this scourge. Initially, these involved reducing transmission of the causative agent Onchocerca volvulus through controlling the vector population. When ivermectin was found to be a very effective drug for treating onchocerciasis, the strategy shifted to mass drug administration (MDA) of endemic communities. In some countries, both vector control and ivermectin MDA have been used together. However, traditional vector control methods involve treating rivers in which the black fly vectors breed with insecticides, a process which is expensive, requires trained personnel to administer, and can be ecologically harmful. In this review, we discuss recent research into alternatives to riverine insecticide treatment, which are inexpensive, ecologically less harmful, and can be implemented by the affected communities themselves. These can dramatically reduce vector densities and, when combined with ivermectin MDA, can accelerate the time to elimination when compared to MDA alone.

Use of The Risk Assessment and Prediction Tool to Predict Same-day Discharge After Primary Hip and Knee Arthroplasty.

INTRODUCTION: The Risk Assessment and Prediction Tool (RAPT) is a preoperative screening tool developed to predict discharge disposition after total hip arthroplasty (THA) and total knee arthroplasty (TKA), but its predictive value for same-day discharge (SDD) has not been investigated. The aims of this study were (1) to assess RAPT's ability to predict SDD after primary THA and TKA and (2) to determine a cutoff RAPT score that may recognize patients appropriate for SDD. METHODS: Data were retrospectively collected from patients undergoing primary THA and TKA at a single tertiary care center between February 2020 and May 2021. A receiver operating characteristic curve was generated to choose a cutoff value to screen for SDD. Logistic regression analysis was done to identify factors including age, BMI, or RAPT score that may be associated with SDD. RESULTS: Three hundred sixty-one patients with preoperative RAPT scores were included in the analysis of whom 147 (42.6%) underwent SDD. A cutoff of ≥9 was identified for TKA and ≥11 for THA. RAPT had a predictive accuracy of only 66.7% for SDD, whereas the discharge plan documented in the preoperative note was 91.7% accurate. DISCUSSION: Although there is a positive association between RAPT and SDD, it is not a useful screening tool given its low predictive accuracy.

Deep Learning for Face Detection and Pain Assessment in Japanese macaques (Macaca fuscata).

Facial expressions have increasingly been used to assess emotional states in mammals. The recognition of pain in research animals is essential for their well-being and leads to more reliable research outcomes. Automating this process could contribute to early pain diagnosis and treatment. Artificial neural networks have become a popular option for image classification tasks in recent years due to the development of deep learning. In this study, we investigated the ability of a deep learning model to detect pain in Japanese macaques based on their facial expression. Thirty to 60 min of video footage from Japanese macaques undergoing laparotomy was used in the study. Macaques were recorded undisturbed in their cages before surgery (No Pain) and one day after the surgery before scheduled analgesia (Pain). Videos were processed for facial detection and image extraction with the algorithms RetinaFace (adding a bounding box around the face for image extraction) or Mask R-CNN (contouring the face for extraction). ResNet50 used 75% of the images to train systems; the other 25% were used for testing. Test accuracy varied from 48 to 54% after box extraction. The low accuracy of classification after box extraction was likely due to the incorporation of features that were not relevant for pain (for example, background, illumination, skin color, or objects in the enclosure). However, using contour extraction, preprocessing the images, and fine-tuning, the network resulted in 64% appropriate generalization. These results suggest that Mask R-CNN can be used for facial feature extractions and that the performance of the classifying model is relatively accurate for nonannotated single-frame images.

Racial and Ethnic Disparities in Receipt of Pediatric Mental Health Care.

BACKGROUND: Studies suggest increasing mental health care needs among children but limited capacity to meet those needs, potentially leaving some needs unmet. There are no recent national studies examining the receipt of mental health treatment among children. We sought to identify the correlates of treatment receipt in a nationally representative sample of children in the United States. METHODS: We conducted a cross-sectional analysis of the 2019 National Health Interview Survey. Parents reported on their child's sociodemographic characteristics, general health care engagement, mental health using the Strengths and Difficulties Questionnaire, and whether their child received therapy or medication in the prior year. Weighted logistic regressions tested associations among child characteristics and receipt of mental health treatment while controlling for parental report of child mental health symptoms. RESULTS: Among 7168 children surveyed, 1044 (15%) received mental health treatment, equating to over 7 million US children. Hispanic children (adjusted odds ratio [AOR]: 0.46 [95% confidence interval (CI): 0.34-0.62]) and non-Hispanic Black children (AOR: 0.35 [95% CI: 0.23-0.54]) had lower odds of receiving treatment compared to non-Hispanic White children, controlling for mental health symptoms. Children with a well-child visit in the last year (AOR: 2.05 [95% CI: 1.20-3.52]) and whose usual place of care was a doctor's office (AOR 2.10 [95% CI: 1.33-3.34]) had higher odds of treatment receipt. CONCLUSIONS: Racially and ethnically minoritized children and those without primary care access have disproportionately low levels of receipt of mental health treatment. Interventions to meet the needs of these groups should be prioritized to reduce mental health disparities.

DeepBiomarker2: Prediction of Alcohol and Substance Use Disorder Risk in Post-Traumatic Stress Disorder Patients Using Electronic Medical Records and Multiple Social Determinants of Health.

Prediction of high-risk events amongst patients with mental disorders is critical for personalized interventions. We developed DeepBiomarker2 by leveraging deep learning and natural language processing to analyze lab tests, medication use, diagnosis, social determinants of health (SDoH) parameters, and psychotherapy for outcome prediction. To increase the model's interpretability, we further refined our contribution analysis to identify key features by scaling with a factor from a reference feature. We applied DeepBiomarker2 to analyze the EMR data of 38,807 patients from the University of Pittsburgh Medical Center diagnosed with post-traumatic stress disorder (PTSD) to determine their risk of developing alcohol and substance use disorder (ASUD). DeepBiomarker2 predicted whether a PTSD patient would have a diagnosis of ASUD within the following 3 months with an average c-statistic (receiver operating characteristic AUC) of 0.93 and average F1 score, precision, and recall of 0.880, 0.895, and 0.866 in the test sets, respectively. Our study found that the medications clindamycin, enalapril, penicillin, valacyclovir, Xarelto/rivaroxaban, moxifloxacin, and atropine and the SDoH parameters access to psychotherapy, living in zip codes with a high normalized vegetative index, Gini index, and low-income segregation may have potential to reduce the risk of ASUDs in PTSD. In conclusion, the integration of SDoH information, coupled with the refined feature contribution analysis, empowers DeepBiomarker2 to accurately predict ASUD risk. Moreover, the model can further identify potential indicators of increased risk along with medications with beneficial effects.

Development of a serious gaming approach for cyber aptitude assessment.

Numerous traditional assessments have been developed to determine suitability of US military recruits for cyber careers. Cyber career field managers expressed a concern there may be well-qualified candidates that lack cyber knowledge, and therefore are not identified with knowledge-based tests. Technological advances such as serious gaming may provide opportunities to assess constructs traditional methods do not effectively measure. The purpose of this effort was to identify potential gains in validity that could be achieved beyond traditional methods through the use of serious games for several cyber jobs (both for enlisted and officer positions). Throughout this phase of research, an extensive literature review of military and civilian assessments targeted cyber occupations. Then, military subject matter experts in these career fields provided input and guidance (e.g., focus on aptitudes and traits as knowledge and skill are rapidly outdated). A gap analysis between all measures of such constructs identified a short list of candidates for measurement in a serious game. A survey of 800 airmen in the 1N4X1A, 3D1X2 and 17DEX/SX career fields was conducted; 290 respondents identified six constructs to be the focus for serious game assessment. The game was developed, and constructs validated on a sample chosen to model Air Force enlisted recruits. Additional psychometric data from enlistees and cyber trainees will be gathered once COVID-19 restrictions are lifted.

Folding-upon-binding pathways of an intrinsically disordered protein from a deep Markov state model.

A central challenge in the study of intrinsically disordered proteins is the characterization of the mechanisms by which they bind their physiological interaction partners. Here, we utilize a deep learning-based Markov state modeling approach to characterize the folding-upon-binding pathways observed in a long timescale molecular dynamics simulation of a disordered region of the measles virus nucleoprotein NTAIL reversibly binding the X domain of the measles virus phosphoprotein complex. We find that folding-upon-binding predominantly occurs via two distinct encounter complexes that are differentiated by the binding orientation, helical content, and conformational heterogeneity of NTAIL. We observe that folding-upon-binding predominantly proceeds through a multi-step induced fit mechanism with several intermediates and do not find evidence for the existence of canonical conformational selection pathways. We observe four kinetically separated native-like bound states that interconvert on timescales of eighty to five hundred nanoseconds. These bound states share a core set of native intermolecular contacts and stable NTAIL helices and are differentiated by a sequential formation of native and non-native contacts and additional helical turns. Our analyses provide an atomic resolution structural description of intermediate states in a folding-upon-binding pathway and elucidate the nature of the kinetic barriers between metastable states in a dynamic and heterogenous, or "fuzzy", protein complex.

Social Determinants of Health and Preoperative Care.

Preoperative care exists as part of perioperative continuum during which anesthesiologists and surgeons optimize patients for surgery. These multispecialty efforts are important, particularly for patients with complex medical histories and those requiring major surgery. Preoperative care improves planning and determines the clinical pathway and discharge disposition. The role of nonmedical social factors in the preoperative planning is not well described in anesthesiology. Research to improve outcomes based on social factors is not well described for anesthesiologists but could be instrumental in decreasing disparities and advancing health equity in surgical patients.

Is There an Implicit Racial Bias in the Case Order of Elective Total Joint Arthroplasty?

INTRODUCTION: Identifying ways to improve equitable access to healthcare is of the utmost important. In this study, we analyzed whether patient race was negatively associated with surgical start times for total joint arthroplasties (TJA). METHODS: The surgical case order and start times of all primary TJAs performed at a large academic medical center between May 2014 and May 2018 were retrospectively reviewed. Patients were included if > 21, had a documented self-reported race, and were operated on by an arthroplasty fellowship-trained surgeon. Operations were categorized as first-start, early (7:00 AM-11:00 AM), mid-day (11:00 AM-3:00 PM), or late (after 3:00 PM). Multivariable logistic regression (MLR) was performed, and odds ratios (OR) were calculated. RESULTS: This study identified 1663 TJAs-871 total knee (TKA) and 792 total hip arthroplasties (THA) who met inclusion criteria. Overall, there was no association between race and surgical start time. Upon sub-analysis by surgical type, this held true for TKA patients, but self-identifying Hispanic and non-Hispanic Black patients undergoing THA were more likely to have later surgical start times (ORs: 2.08 and 1.88; p < 0.05). DISCUSSION: Although there was no association between race and overall TJA surgical start times, patients with marginalized racial and ethnic identities were more likely to undergo elective THA later in the surgical day. Surgeons should be aware of potential implicit bias when determining case order to potentially prevent adverse outcomes due to staff fatigue or lack of proper resources later in the day.

Moving Beyond Simulation: Data-Driven Quantitative Photoacoustic Imaging Using Tissue-Mimicking Phantoms.

Accurate measurement of optical absorption coefficients from photoacoustic imaging (PAI) data would enable direct mapping of molecular concentrations, providing vital clinical insight. The ill-posed nature of the problem of absorption coefficient recovery has prohibited PAI from achieving this goal in living systems due to the domain gap between simulation and experiment. To bridge this gap, we introduce a collection of experimentally well-characterised imaging phantoms and their digital twins. This first-of-a-kind phantom data set enables supervised training of a U-Net on experimental data for pixel-wise estimation of absorption coefficients. We show that training on simulated data results in artefacts and biases in the estimates, reinforcing the existence of a domain gap between simulation and experiment. Training on experimentally acquired data, however, yielded more accurate and robust estimates of optical absorption coefficients. We compare the results to fluence correction with a Monte Carlo model from reference optical properties of the materials, which yields a quantification error of approximately 20%. Application of the trained U-Nets to a blood flow phantom demonstrated spectral biases when training on simulated data, while application to a mouse model highlighted the ability of both learning-based approaches to recover the depth-dependent loss of signal intensity. We demonstrate that training on experimental phantoms can restore the correlation of signal amplitudes measured in depth. While the absolute quantification error remains high and further improvements are needed, our results highlight the promise of deep learning to advance quantitative PAI.

Simulation study of a novel small animal FLASH irradiator (SAFI) with integrated inverse-geometry CT based on circularly distributed kV X-ray sources.

Ultra-high dose rate (UHDR) radiotherapy (RT) or FLASH-RT can potentially reduce normal tissue toxicity. A small animal irradiator that can deliver FLASH-RT treatments similar to clinical RT treatments is needed for pre-clinical studies of FLASH-RT. We designed and simulated a novel small animal FLASH irradiator (SAFI) based on distributed x-ray source technology. The SAFI system comprises a distributed x-ray source with 51 focal spots equally distributed on a 20 cm diameter ring, which are used for both FLASH-RT and onboard micro-CT imaging. Monte Carlo simulation was performed to estimate the dosimetric characteristics of the SAFI treatment beams. The maximum dose rate, which is limited by the power density of the tungsten target, was estimated based on finite-element analysis (FEA). The maximum DC electron beam current density is 2.6 mA/mm2, limited by the tungsten target's linear focal spot power density. At 160 kVp, 51 focal spots, each with a dimension of [Formula: see text] mm2 and 10° anode angle, can produce up to 120 Gy/s maximum DC irradiation at the center of a cylindrical water phantom. We further demonstrate forward and inverse FLASH-RT planning, as well as inverse-geometry micro-CT with circular source array imaging via numerical simulations.

SPINE20 recommendations 2023: One Earth, one family, one future WITHOUT spine DISABILITY.

Introduction: The purpose is to report on the fourth set of recommendations developed by SPINE20 to advocate for evidence-based spine care globally under the theme of "One Earth, One Family, One Future WITHOUT Spine DISABILITY". Research question: Not applicable. Material and methods: Recommendations were developed and refined through two modified Delphi processes with international, multi-professional panels. Results: Seven recommendations were delivered to the G20 countries calling them to:-establish, prioritize and implement accessible National Spine Care Programs to improve spine care and health outcomes.-eliminate structural barriers to accessing timely rehabilitation for spinal disorders to reduce poverty.-implement cost-effective, evidence-based practice for digital transformation in spine care, to deliver self-management and prevention, evaluate practice and measure outcomes.-monitor and reduce safety lapses in primary care including missed diagnoses of serious spine pathologies and risk factors for spinal disability and chronicity.-develop, implement and evaluate standardization processes for spine care delivery systems tailored to individual and population health needs.-ensure accessible and affordable quality care to persons with spine disorders, injuries and related disabilities throughout the lifespan.-promote and facilitate healthy lifestyle choices (including physical activity, nutrition, smoking cessation) to improve spine wellness and health. Discussion and conclusion: SPINE20 proposes that focusing on the recommendations would facilitate equitable access to health systems, affordable spine care delivered by a competent healthcare workforce, and education of persons with spine disorders, which will contribute to reducing spine disability, associated poverty, and increase productivity of the G20 nations.

Intracardiac shunt assessment using CT coronary angiography.

BACKGROUND: Detection of intracardiac shunts using CT Coronary Angiography (CTCA) is currently based on anatomical demonstration of defects. We assessed a novel technique using a standard CTCA test bolus in detecting shunts independent of anatomical assessment and to provide an estimate of Qp/Qs. METHODS: We retrospectively reviewed 51 CTCAs: twenty-one from patients with known simple left to right intracardiac shunts with contemporaneous functional assessment (using CMR) within 6 months, 20 controls with structurally normal hearts, and 10 patients with shunt repairs. From the dynamic acquisition of a test bolus, we measured mean Hounsfield Units (HU) in various anatomical structures. We created time/density curves from the test bolus data, and calculated disappearance time (DT) from the ascending aorta (deriving a Qp/Qs), peak ascending aortic HU, and mean coefficient of variation of the arterial curves, and compared these with the Qp/Qs from the respective CMR. RESULTS: Patients with intracardiac shunts had significantly higher test bolus derived Qp/Qs compared with both the controls, and the repaired shunt comparator group. There was a very strong agreement between the test bolus derived Qp/Qs, and Qp/Qs as measured by CMR (Intraclass correlation 0.89). Mean bias was 0.032 â€‹± â€‹0.341 (95% limits of agreement -0.64 to 0.70). Interobserver, and intraobserver agreement of the disappearance time was excellent (0.99, 0.99 (reader 1) and 1.00 (reader 2) respectively). CONCLUSION: In this proof-of-concept study, we demonstrate a novel technique to detect, and to estimate severity of left to right intracardiac shunts on routine Cardiac CT.