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Abstract Background The clinical translation of positron emission tomography (PET) radiotracers for cancer management presents complex challenges. We have developed consensus-based recommendations for preclinical and clinical assessment of novel and established radiotracers, applied to image different cancer types, to improve the standardisation of translational methodologies and accelerate clinical implementation. Methods A consensus process was developed using the RAND/UCLA Appropriateness Method (RAM) to gather insights from a multidisciplinary panel of 38 key stakeholders on the appropriateness of preclinical and clinical methodologies and stakeholder engagement for PET radiotracer translation. Panellists independently completed a consensus survey of 57 questions, rating each on a 9-point Likert scale. Subsequently, panellists attended a consensus meeting to discuss survey outcomes and readjust scores independently if desired. Survey items with median scores ≥ 7 were considered ‘required/appropriate’, ≤ 3 ‘not required/inappropriate’, and 4–6 indicated ‘uncertainty remained’. Consensus was determined as ~ 70% participant agreement on whether the item was ‘required/appropriate’ or ‘not required/not appropriate’. Results Consensus was achieved for 38 of 57 (67%) survey questions related to preclinical and clinical methodologies, and stakeholder engagement. For evaluating established radiotracers in new cancer types, in vitro and preclinical studies were considered unnecessary, clinical pharmacokinetic studies were considered appropriate, and clinical dosimetry and biodistribution studies were considered unnecessary, if sufficient previous data existed. There was ‘agreement without consensus’ that clinical repeatability and reproducibility studies are required while ‘uncertainty remained’ regarding the need for comparison studies. For novel radiotracers, in vitro and preclinical studies, such as dosimetry and/or biodistribution studies and tumour histological assessment were considered appropriate, as well as comprehensive clinical validation. Conversely, preclinical reproducibility studies were considered unnecessary and ‘uncertainties remained’ regarding preclinical pharmacokinetic and repeatability evaluation. Other consensus areas included standardisation of clinical study protocols, streamlined regulatory frameworks and patient and public involvement. While a centralised UK clinical imaging research infrastructure and open access federated data repository were considered necessary, there was ‘agreement without consensus’ regarding the requirement for a centralised UK preclinical imaging infrastructure. Conclusions We provide consensus-based recommendations, emphasising streamlined methodologies and regulatory frameworks, together with active stakeholder engagement, for improving PET radiotracer standardisation, reproducibility and clinical implementation in oncology.

Abstract Background The field of single cell technologies has rapidly advanced our comprehension of the human immune system, offering unprecedented insights into cellular heterogeneity and immune function. While cryopreserved peripheral blood mononuclear cell (PBMC) samples enable deep characterization of immune cells, challenges in clinical isolation and preservation limit their application in underserved communities with limited access to research facilities. We present CryoSCAPE (Cryopreservation for Scalable Cellular And Proteomic Exploration), a scalable method for immune studies of human PBMC with multi-omic single cell assays using direct cryopreservation of whole blood. Results Comparative analyses of matched human PBMC from cryopreserved whole blood and density gradient isolation demonstrate the efficacy of this methodology in capturing cell proportions and molecular features. The method was then optimized and verified for high sample throughput using fixed single cell RNA sequencing and liquid handling automation with a single batch of 60 cryopreserved whole blood samples. Additionally, cryopreserved whole blood was demonstrated to be compatible with functional assays, enabling this sample preservation method for clinical research. Conclusions The CryoSCAPE method, optimized for scalability and cost-effectiveness, allows for high-throughput single cell RNA sequencing and functional assays while minimizing sample handling challenges. Utilization of this method in the clinic has the potential to democratize access to single-cell assays and enhance our understanding of immune function across diverse populations.

Abstract Small microphone arrays and sound‐source localisation algorithms are increasingly prevalent in the passive acoustic monitoring (PAM) of ecosystems. These technologies enable analysis of natural soundscapes' spatial features, yielding additional insights into biodiversity and ecosystem health. While many of these technologies have been evaluated in the field, there is a lack of controlled, repeatable methods to test them. We developed an ambisonic virtual sound environment (VSE) for simulating real natural soundscapes to evaluate spatial PAM technologies. We validated this novel approach using a PAM recorder with a six‐microphone array, from which we extracted a typical suite of ecoacoustic metrics, including acoustic indices and avian species predictions and localisations from the software BirdNET and HARKBird, respectively. We first verified whether the VSE could replicate natural soundscapes well enough to test PAM technologies by comparing these metrics between field and VSE‐based recordings. To pilot the VSE as an environment for testing PAM hardware, we assessed how orientation impacts the six‐microphone array's performance by using the same suite of metrics to compare VSE recordings made with the array at various pitch angles. Finally, we piloted the VSE as a test platform for PAM software by investigating how BirdNET and HARKBird perform on bird calls added to the VSE‐replicated soundscapes. While the VSE and field recordings had similarities in some metrics, including spectral composition and BirdNET predictions, ambisonics' perceptual bias and susceptibility to spatial aliasing limited the spatial analyses that could be undertaken. Our trials nonetheless revealed that device orientation impacts the performance of HARKBird and certain ecoacoustic indices, and that BirdNET and HARKBird perform best on louder, more directional bird calls. Our results demonstrate the potential for this approach, but highlight limitations to using an ambisonics‐based VSE. We thus provide guidelines for the use and refinement of such systems towards more standardised, controlled benchmarking of PAM technologies, empowering practitioners to make more informed decisions on using these vital tools.

Abstract Extensive neovascularization is a hallmark of glioblastoma (GBM). In addition to supplying oxygen and nutrients, vascular endothelial cells provide trophic support to GBM cells via paracrine signaling. Here we report that Endocan (ESM1), an endothelial-secreted proteoglycan, confers enhanced proliferative, migratory, and angiogenic properties to GBM cells and regulates their spatial identity. Mechanistically, Endocan exerts at least part of its functions via direct binding and activation of the PDGFRA receptor. Subsequent downstream signaling enhances chromatin accessibility of the Myc promoter and upregulates Myc expression inducing stable phenotypic changes in GBM cells. Furthermore, Endocan confers radioprotection on GBM cells in vitro and in vivo. Inhibition of Endocan-PDGFRA signaling with ponatinib increases survival in the Esm1 wild-type but not in the Esm1 knock-out mouse GBM model. Our findings identify Endocan and its downstream signaling axis as a potential target to subdue GBM recurrence and highlight the importance of vascular-tumor interactions for GBM development.

Abstract Quantum key distribution (QKD) is one of the major applications of quantum information technology. It can provide ultra‐secure key distribution with security guaranteed by the laws of quantum physics. Quantum key distribution is necessary to protect data transmission from quantum computing attacks in future communication networks. The laws of quantum mechanics dictate that as opposed to microwave frequencies, quantum coherence is preserved at room temperatures for terahertz (THz) frequencies. This makes the THz band a promising solution for room‐temperature QKD implementation in future wireless communication networks. The authors present the principles of continuous variable QKD (CV‐QKD) systems and review the latest developments in the design and analysis of CV‐QKD systems operating at microwave and THz frequencies. The authors also discuss how multiple‐input multiple‐output transmission can be incorporated into the quantum communications framework to improve the secret key rates and increase the coverage distances of the THz CV‐QKD system. Furthermore, major hardware challenges that must be surmounted to practically realise THz CV‐QKD systems are highlighted.

Abstract Designing optimal measurement operators for quantum state discrimination (QSD) is an important problem in quantum communications and cryptography applications. Prior works have demonstrated that optimal quantum measurement operators can be obtained by solving a convex semidefinite program (SDP). However, solving the SDP can represent a high computational burden for many real‐time quantum communication systems. To address this issue, a majorisation‐minimisation (MM)‐based algorithm, called Quantum Majorisation‐Minimisation (QMM) is proposed for solving the QSD problem. In QMM, the authors reparametrise the original objective, then tightly upper‐bound it at any given iterate, and obtain the next iterate as a closed‐form solution to the upper‐bound minimisation problem. Our numerical simulations demonstrate that the proposed QMM algorithm significantly outperforms the state‐of‐the‐art SDP algorithm in terms of speed, while maintaining comparable performance for solving QSD problems in quantum communication applications.

Abstract Purpose [99mTc]Tc-HYNIC-iPSMA is a novel technetium-99m-labelled small molecule inhibitor of the prostate-specific membrane antigen (PSMA) for detecting prostate cancer (PC). The objective of this registry was to collect and evaluate [99mTc]Tc-HYNIC-iPSMA patient data and images to establish the safety and tolerability, and clinical utility of this agent in imaging at different stages of PC. Methods Patients 18 to 80 years old with primary staging and metastatic PC were eligible. Patients unable to perform prescribed examinations, undergo a [99mTc]Tc-HYNIC-iPSMA planar and SPECT or SPECT/CT (when available), or sign a patient informed consent form were excluded from the registry. All eligible patients underwent a screening and baseline visit before imaging with [99mTc]Tc-HYNIC-iPSMA. The primary safety endpoint was assessed by collecting and grading all treatment-related adverse events using the Common Terminology Criteria for Adverse Events. Patients were followed until disease progression, death, serious or intolerable adverse events, registry termination by the sponsor, patient withdrawal, or lost to follow-up. Analysis was planned for when data was available from 40 enrolled patients. Results 40 patients enrolled in 6 countries and received [99mTc]Tc-HYNIC-iPSMA tracer administration followed by planar and SPECT imaging. Of the 40 patients included, investigators reported a change in management due to the [99mTc]Tc-HYNIC-iPSMA imaging in 17/40 of patients (42.5%). No adverse events were reported. Conclusions [99mTc]Tc-HYNIC-iPSMA is a promising option to identify PSMA-positive prostate cancer on SPECT and could improve patient access to PSMA imaging worldwide.

Abstract Developing collaborative research platforms for quantum bit control is crucial for driving innovation in the field, as they enable the exchange of ideas, data, and implementation to achieve more impactful outcomes. Furthermore, considering the high costs associated with quantum experimental setups, collaborative environments are vital for maximizing resource utilization efficiently. However, the lack of dedicated data management platforms presents a significant obstacle to progress, highlighting the necessity for essential assistive tools tailored for this purpose. Current qubit control systems are unable to handle complicated management of extensive calibration data and do not support effectively visualizing intricate quantum experiment outcomes. In this paper, we introduce Qubit Control Storage and Visualization (QubiCSV), a platform specifically designed to meet the demands of quantum computing research, focusing on the storage and analysis of calibration and characterization data in qubit control systems. As an open-source tool, QubiCSV facilitates efficient data management of quantum computing, providing data versioning capabilities for data storage and allowing researchers and programmers to interact with qubits in real time. The insightful visualization are developed to interpret complex quantum experiments and optimize qubit performance. QubiCSV not only streamlines the handling of qubit control system data but also improves the user experience with intuitive visualization features, making it a valuable asset for researchers in the quantum computing domain.

Coffee has long been popular worldwide. The rise in lifestyle-related diseases such as cardiovascular disease, diabetes, stroke, dementia, and others has motivated coffee usage and illness prevalence studies. Some studies show coffee consumers are at risk for such diseases, whereas others show its active components protect them. Policymakers and the public need a comprehensive umbrella review to make healthy choices and enjoy coffee. Coffee consumption and stroke, CHD, and dementia outcomes have been distinguished using the PICO search strategy in PubMed with a filter for meta-analysis. We included 10 years of investigations until October 2023. MeSH terms “coffee intake,” “stroke, dementia,” and “transient ischemic attack,” comparing stroke risk with coffee consumption were used. The study excluded case reports and non-human, non-English observational research. The stroke risk of coffee was examined using RevMan software. Coffee consumption’s stroke risk ratio (RR), 95% CI, and I2 were estimated. Forest plots with P values ≤ 0.05 are significant. The umbrella review includes 11 meta-analyses from 457052 papers, totalling 11.96 million individuals. Drinking up to 4 cups of coffee daily reduced stroke risk by 12% compared with not drinking any coffee (0.88 (CI of 0.84-0.92, I2 of 13%, P < 0.00001)). Coffee drinkers had a 1.19 risk ratio for cardiovascular diseases compared to non-coffee drinkers (CI: 0.99–1.38, I2 = 84%, P < 0.00001). The dementia risk ratio for caffeine users was 0.90 (95% CI: 0.82-0.97, I2 = 46%, P < 0.00001) compared with non-consumers. Our analysis covering 5.42 million individuals found that 4 cups of coffee consumed a day reduced stroke risk by 12%. Coffee may reduce ischemic and haemorrhagic strokes by preserving endothelium and antioxidants. Coffee may lessen dementia risk, according to our study’s 0.94 pooled risk ratio after sensitivity analysis. Heavy coffee drinkers had a greater CHD risk, as per our findings. Heavy coffee drinkers were more at risk.

Abstract Advanced design strategies are essential to realize the full potential of engineered living materials, including their biodegradability, manufacturability, sustainability, and ability to tailor functional properties. Toward these goals, we present mechanically engineered living material with compostability, healability, and scalability – a material that integrates these features in the form of a stretchable plastic that is simultaneously flushable, compostable, and exhibits the characteristics of paper. This plastic/paper-like material is produced in scalable quantities (0.5–1 g L−1), directly from cultured bacterial biomass (40%) containing engineered curli protein nanofibers. The elongation at break (1–160%) and Young’s modulus (6-450 MPa) is tuned to more than two orders of magnitude. By genetically encoded covalent crosslinking of curli nanofibers, we increase the Young’s modulus by two times. The designed engineered living materials biodegrade completely in 15–75 days, while its mechanical properties are comparable to petrochemical plastics and thus may find use as compostable materials for primary packaging.

Abstract Biopolymer research has led to the development of novel products through innovative strategies. Their functionalization is typically achieved by physical/chemical methods that require harsh chemicals or mechanical treatments. These functionalities could be alternatively achieved by employing bioengineering design methods. We demonstrate, a bioengineered dual-microbial approach to create functional bacterial cellulose from microbial workhorses. Komagataeibacter hansenii ATCC 53582 is used to produce bacterial cellulose and engineered E. coli is used to functionalize the matrix with a recombinant fibrous protein. The E. coli harbours synthetic genes for the secretion of amyloid curli protein subunit (CsgA) tagged with short functional M6A peptide domains. The incorporation of M6A-functionalized amyloid proteins into bacterial cellulose facilitates magnetite nanoparticle nucleation. We achieved a saturation magnetization of 40 emu g−1, a three-fold increase compared to existing strategies. The magnetic bacterial cellulose films demonstrate cytocompatibility and accelerate cell migration in the presence of magnetic field.

Abstract Background Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue processing procedures result in the introduction of artifacts, which are ultimately transferred to the digitized version of glass slides, known as whole slide images (WSIs). Artifacts are diagnostically irrelevant areas and may result in wrong predictions from deep learning (DL) algorithms. Therefore, detecting and excluding artifacts in the computational pathology (CPATH) system is essential for reliable automated diagnosis. Methods In this paper, we propose a mixture of experts (MoE) scheme for detecting five notable artifacts, including damaged tissue, blur, folded tissue, air bubbles, and histologically irrelevant blood from WSIs. First, we train independent binary DL models as experts to capture particular artifact morphology. Then, we ensemble their predictions using a fusion mechanism. We apply probabilistic thresholding over the final probability distribution to improve the sensitivity of the MoE. We developed four DL pipelines to evaluate computational and performance trade-offs. These include two MoEs and two multiclass models of state-of-the-art deep convolutional neural networks (DCNNs) and vision transformers (ViTs). These DL pipelines are quantitatively and qualitatively evaluated on external and out-of-distribution (OoD) data to assess generalizability and robustness for artifact detection application. Results We extensively evaluated the proposed MoE and multiclass models. DCNNs-based MoE and ViTs-based MoE schemes outperformed simpler multiclass models and were tested on datasets from different hospitals and cancer types, where MoE using (MobileNet) DCNNs yielded the best results. The proposed MoE yields 86.15 % F1 and 97.93% sensitivity scores on unseen data, retaining less computational cost for inference than MoE using ViTs. This best performance of MoEs comes with relatively higher computational trade-offs than multiclass models. Furthermore, we apply post-processing to create an artifact segmentation mask, a potential artifact-free RoI map, a quality report, and an artifact-refined WSI for further computational analysis. During the qualitative evaluation, field experts assessed the predictive performance of MoEs over OoD WSIs. They rated artifact detection and artifact-free area preservation, where the highest agreement translated to a Cohen Kappa of 0.82, indicating substantial agreement for the overall diagnostic usability of the DCNN-based MoE scheme. Conclusions The proposed artifact detection pipeline will not only ensure reliable CPATH predictions but may also provide quality control. In this work, the best-performing pipeline for artifact detection is MoE with DCNNs. Our detailed experiments show that there is always a trade-off between performance and computational complexity, and no straightforward DL solution equally suits all types of data and applications. The code and HistoArtifacts dataset can be found online at Github and Zenodo , respectively.

Abstract Hanging drop cultures provide a favorable environment for the gentle, gel-free formation of highly uniform three-dimensional cell cultures often used in drug screening applications. Initial cell numbers can be limited, as with primary cells provided by minimally invasive biopsies. Therefore, it can be beneficial to divide cells into miniaturized arrays of hanging drops to supply a larger number of samples. Here, we present a framework for the miniaturization of hanging drop networks to nanoliter volumes. The principles of a single hanging drop are described and used to construct the fundamental equations for a microfluidic system composed of multiple connected drops. Constitutive equations for the hanging drop as a nonlinear capacitive element are derived for application in the electronic-hydraulic analogy, forming the basis for more complex, time-dependent numerical modeling of hanging drop networks. This is supplemented by traditional computational fluid dynamics simulation to provide further information about flow conditions within the wells. A fabrication protocol is presented and demonstrated for creating transparent, microscale arrays of pinned hanging drops. A custom interface, pressure-based fluidic system, and environmental chamber have been developed to support the device. Finally, fluid flow on the chip is demonstrated to align with expected behavior based on the principles derived for hanging drop networks. Challenges with the system and potential areas for improvement are discussed. This paper expands on the limited body of hanging drop network literature and provides a framework for designing, fabricating, and operating these systems at the microscale.

Background Medical education was affected worldwide by the coronavirus disease 2019 (COVID-19) pandemic. The sudden announcement of the lockdown resulted in a sudden, unplanned shift to online education. The study aimed to explore the perceptions of the faculty and medical students regarding the experience of utilizing online education at the College of Medicine (CoM), King Saud University, Saudi Arabia. Methods A cross-sectional study was conducted in 2022 with the faculty and medical students in the CoM, King Saud University. The students’ survey was distributed using Google Forms. The questionnaire consisted of six sections with a total of 28 questions that included closed-ended, 5-point Likert scale, and binary “yes” and “no” questions: (1) demographic data, (2) using online education before COVID-19, (3) using of online education during COVID-19, (4) student perceptions of E-learning during COVID-19 pandemic, (5) impact of online education on clinical teaching, and (6) preference in future. The faculty survey was distributed electronically by E-mail through the university’s official E-mail. The faculty survey consisted of 17 questions divided into “Demographic Information” and “Experience with E-Learning before and after COVID-19.” Results A total of 302 students responded to the survey, with most being from year 4 (30%). Students spent more than 10 h using online learning platforms during the pandemic, compared with 1–3 h before the pandemic. The most used online learning resource indicated by students was YouTube (75%), with Zoom being the most preferred platform (48%). The main benefit of online teaching based on students’ responses was that it saves students’ time (88%), while lack of contact with teachers (43%) was a barrier. 76.2% of students indicated satisfaction with the online learning experience during COVID-19. Male students showed more satisfaction than females with the learning experience during COVID-19 (P = 0.029). Almost all students (90%) wanted to continue with online learning post-COVID-19. For the faculty survey, 61 faculty members completed the survey. Overall, the faculty positively viewed online teaching and e-learning interactions. About 39.4% identified giving both live and recorded sessions during COVID-19. About 65.57% of faculty used Zoom to conduct sessions. Regarding preference, 34% preferred e-learning compared to an actual classroom setup for theoretical lectures, and 33% preferred e-learning for problem-based learning lectures. Almost half of the faculty rated their experience as poor for clinical and practical sessions. For problem-based lectures, 34% of faculty rated their interaction with students as poor during online learning compared to the actual classroom. Conclusions Despite the challenges, medical students and faculty perceived the sudden shift to online education due to COVID-19 as satisfactory. However, further efforts are needed to improve the utilization and implementation of online education in medical education and regularly monitor its effectiveness.

Abstract Multi‐microphone recording adds spatial information to recorded audio with emerging applications in ecosystem monitoring. Specifically placing sounds in space can improve animal count accuracy, locate illegal activity like logging and poaching, track animals to monitor behaviour and habitat use and allow for ‘beamforming’ to amplify sounds from target directions for downstream classification. Studies have shown many advantages of spatial acoustics, but uptake remains limited as the equipment is often expensive, complicated, inaccessible or only suitable for short‐term deployments. With an emphasis on enhanced uptake and usability, we present a low‐cost, open‐source, six‐channel recorder built entirely from commercially available components which can be integrated into a solar‐powered, online system. The MAARU (Multichannel Acoustic Autonomous Recording Unit) works as an independent node in long‐term autonomous, passive and/or short‐term deployments. Here, we introduce MAARU's hardware and software and present the results of lab and field tests investigating the device's durability and usability. MAARU records multichannel audio with similar costs and power demands to equivalent omnidirectional recorders. MAARU devices have been deployed in the United Kingdom and Brazil, where we have shown MAARUs can accurately localise pure tones up to 6 kHz and bird calls as far as 8 m away (±10° range, 100% and >60% of signals, respectively). Louder calls may have even further detection radii. We also show how beamforming can be used with MAARUs to improve species ID confidence scores. MAARU is an accessible, low‐cost option for those looking to explore spatial acoustics accurately and easily with a single device, and without the formidable expenses and processing complications associated with establishing arrays. Ultimately, the added directional element of the multichannel recording provided by MAARU allows for enhanced recording of sonic environments, further enabling a potential step change in the uptake of spatial acoustics in the wider field.

Abstract While ventricular shunts are the main treatment for adult hydrocephalus, shunt malfunction remains a common problem that can be challenging to diagnose. Computer vision-derived algorithms present a potential solution. We designed a feasibility study to see if such an algorithm could automatically predict ventriculomegaly indicative of shunt failure in a real-life adult hydrocephalus population. We retrospectively identified a consecutive series of adult shunted hydrocephalus patients over an eight-year period. Associated computed tomography scans were extracted and each scan was reviewed by two investigators. A machine learning algorithm was trained to identify the lateral and third ventricles, and then applied to test scans. Results were compared to human performance using Sørensen–Dice coefficients, calculated total ventricular volumes, and ventriculomegaly as documented in the electronic medical record. 5610 axial images from 191 patients were included for final analysis, with 52 segments (13.6% of total data) reserved for testing. Algorithmic performance on the test group averaged a Dice score of 0.809 ± 0.094. Calculated total ventricular volumes did not differ significantly between computer-derived volumes and volumes marked by either the first reviewer or second reviewer (p > 0.05). Algorithm detection of ventriculomegaly was correct in all test cases and this correlated with correct prediction of need for shunt revision in 92.3% of test cases. Though development challenges remain, it is feasible to create automated algorithms that detect ventriculomegaly in adult hydrocephalus shunt malfunction with high reliability and accuracy.

Background and Aim: Haemolysis due to dapsone as a part of MDT in leprosy patients has been long recognized. However, the frequency and severity of this side effect and factors associated with it have not been well documented. We planned to determine the frequency of dapsone-induced haemolysis in leprosy patients on MDT and various risk factors associated with it. MATERIALS AND METHODS: This was a hospital-based retrospective analysis, conducted on 36 treatment completed or partially treated or on treatment leprosy patients in a tertiary care centre in Chhattisgarh. Results: Out of 36 patients, 83.3% showed a fall in haemoglobin from the baseline value (pre-treatment values). Dapsone was stopped in 33.3% of patients with a significant fall in haemoglobin. We found that the mean haemoglobin concentration for all patients fell from 13.05(+/−1.8) g/dl to 11.8(+/−1.9) g/dl (P < 0.05) which was statistically significant. A total of 25% of patients were labelled as confirmed cases of dapsone-induced haemolysis as per our definition. Conclusion: Our results underline the need to incorporate haematological investigations in leprosy management protocol, especially in primary care settings where the majority of leprosy patients are managed.

IntroductionPharmacotherapy during lactation often lacks reliable drug safety data, resulting in delayed treatment or early cessation of breastfeeding. In silico tools, such as physiologically-based pharmacokinetic (PBPK) models, can help to bridge this knowledge gap. To increase the accuracy of these models, it is essential to account for the physiological changes that occur throughout the postpartum period.MethodsThis study aimed to collect and analyze data on the longitudinal changes in various physiological parameters that can affect drug distribution into breast milk during lactation. Following meta-analysis of the collated data, mathematical functions were fitted to the available data for each parameter. The best-performing functions were selected through numerical and visual diagnostics.Results and DiscussionThe literature search identified 230 studies, yielding a dataset of 36,689 data points from 20,801 postpartum women, covering data from immediately after childbirth to 12 months postpartum. Sufficient data were obtained to describe postpartum changes in maternal plasma volume, breast volume, cardiac output, glomerular filtration rate, haematocrit, human serum albumin, alpha-1-acid glycoprotein, milk pH, milk volume, milk fat, milk protein, milk water content, and daily infant milk intake. Although data beyond 7 months postpartum were limited for some parameters, mathematical functions were generated for all parameters. These functions can be integrated into lactation PBPK models to increase their predictive power and better inform medication efficacy and safety for breastfeeding women.

Introduction: Chemoradiation followed by durvalumab is considered a standard approach for patients with locally advanced NSCLC. With improvements in perioperative and neoadjuvant approaches, there is renewed interest in offering surgery to carefully selected patients with cT3/4N2 stage IIIB cancer. We sought to assess survival outcomes after surgery as part of a multimodality treatment regimen for these patients. Methods: Patients with cT3/T4N2M0 NSCLC who received surgery (S) as part of a multimodality approach and patients receiving multimodality treatment without surgery (chemoradiation [CRT] or systemic therapy only) were identified in the National Cancer Database (2010–2019). We evaluated factors associated with the receipt of S (logistic regression). After propensity matching, we estimated the overall survival (OS) of patients who received S and compared with those who received CRT (Kaplan-Meier and Cox regression). Results: A total of 44,756 patients were identified, of whom 3928 (8.8%) underwent S, 29,798 (66.6%) CRT, and 11,030 (24.6%) systemic therapy only. Fewer comorbidities (Charlson-Deyo index 0 or 1, adjusted OR [aOR]: 1.22, 95% confidence interval [CI]: 1.05–1.42), treatment at an academic facility (aOR: 1.70, 95% CI: 1.52–1.89), private insurance (aOR: 2.44, 95% CI: 1.61–3.69), adenocarcinoma histology (aOR: 1.48, 95% CI: 1.22–1.79), and clinical T3 stage (

Objective: Intracranial hemorrhage (ICH) after durotomy in elective spine surgery, though rare, can pose a significant risk to patient outcomes. Spine surgeries bear a risk of dural tears (DT) with potential of postoperative cerebrospinal fluid leakage (PCSFL). Excessive PCSFL can precipitate a decrease in intracranial pressure, potentially leading to ICH. Literature on ICH as a postoperative complication is scarce. The aim was to assess the incidence and risk factors of ICH in patients undergoing elective spine surgery. Methods: Utilizing the 2020 National Impatient Sample (NIS) adults (>18 years) were selected by primary procedure category codes for spine fusion, discectomy, spinal cord decompression and cervicothoracic/lumbosacral nerve decompression. Exclusion criteria were trauma and malignancy. The primary outcome was occurrence of ICH. Comparative analysis and a multivariable logistic regression were used to identify independent risk. Results: In total, 40,990 patients met our criteria with an incidence of ICH at 0.08%. The ICH-group showed an increased length of stay and higher mortality compared to the control group. Spinal cord decompression, DT and PCSFL were significantly more frequent in patients with ICH. Alcohol, drug abuse and hypertension were significantly more prevalent in patients with ICH. DT, alcohol abuse and hypertension were independent risk factors for ICH. Conclusions: This study underscores the rarity and severity of ICHs following elective spine surgery, emphasizing awareness and looking for possible preventive measures. Our finding suggests that DT, as a complication of surgical techniques, as well as alcohol abuse and hypertension are significant predictors of ICH.

Repurposing of pleiotropic factors during execution of diverse cellular processes has emerged as a regulatory paradigm. Embryonic development in metazoans is controlled by maternal factors deposited in the egg during oogenesis. Here, we explore maternal role(s) of Caspar (Casp), the Drosophila orthologue of human Fas-associated factor-1 (FAF1) originally implicated in host-defense as a negative regulator of NF-κB signaling. Maternal loss of either Casp or it’s protein partner, transitional endoplasmic reticulum 94 (TER94) leads to partial embryonic lethality correlated with aberrant centrosome behavior, cytoskeletal abnormalities, and defective gastrulation. Although ubiquitously distributed, both proteins are enriched in the primordial germ cells (PGCs), and in keeping with the centrosome problems, mutant embryos display a significant reduction in the PGC count. Moreover, the total number of pole buds is directly proportional to the level of Casp. Consistently, it’s ‘loss’ and ‘gain’ results in respective reduction and increase in the Oskar protein levels, the master determinant of PGC fate. To elucidate this regulatory loop, we analyzed several known components of mid-blastula transition and identify the translational repressor Smaug, a zygotic regulator of germ cell specification, as a potential critical target. We present a detailed structure-function analysis of Casp aimed at understanding its novel involvement during PGC development.

Background: Fiji is a Pacific Island nation with the predominant ethnic groups indigenous Fijians (iTaukei) (62 %) and Fijians of Indian descent (31 %). This study reports on the effect of a Parental Assistance Payment Program (PAPP) tied to on-time birth registration, available in Fiji from August 2018 to July 2020. Methods: Unit record birth registration data (n = 117,829) for children born during 2016–22 were used to calculate mean birth-to-registration intervals and the likelihood of on-time birth registration (within 365 days) before the PAPP (January 2016–July 2018) compared to during the PAPP (August 2018–July 2020), by population disaggregations (sex, ethnicity, age, marital status). Results: During the PAPP, mean birth-to-registration intervals declined sharply by 81 %, from 665 days (95 %CI: 658–671) to 124 days (121–127). The largest declines were among i-Taukei children (803 to 139 days, 83 %) compared to non-iTaukei (283 to 76 days, 73 %); mothers aged 10–19 years (880 to 134 days, 85 %) compared to ≥20 years (653 to 123 days, 81 %); and single mothers (983 to 145 days, 85 %) compared to married mothers (570 to 115 days, 80 %). On-time birth registration increased from 57 % to 93 %, and the adjusted hazard ratio showed children born during the PAPP were 2.3 times more likely (95 %CI: 2.2–2.4) to have their birth registered on-time compared to children born before the PAPP. When the PAPP was discontinued in August 2020, the birth-to-registration interval increased sharply in all population groups. Conclusions: During the two-year period the PAPP was available, it was highly effective at improving the timeliness of birth registration, particularly among iTaukei children, young mothers, and single mothers. After the PAPP was discontinued, the timeliness of birth registration deteriorated sharply. Longer post-PAPP follow-up time (≠5 years) is required to determine whether the timeliness of birth registration has deteriorated to levels similar to those during the pre-PAPP period.

ABSTRACT: Background: Mind-body treatments have the potential to manage pain, yet their effectiveness when delivered online for the treatment of low back pain (LBP) is unknown. We sought to evaluate whether a virtually delivered mind-body program integrating tai chi, qigong, and meditation (VDTQM) is effective for treating LBP. Methods: This randomized controlled trial compared VDTQM (n=175) to waitlist control (n=175). Eligible participants were at least 18 years old, had LBP for at least 6 weeks, were not pregnant, had not previously taken tai chi classes, and had not undergone spine surgery within 6 months. The treatment group received a 12-week VDTQM program in live online 60-minute twice-weekly group classes from September 2022 to December 2022. All participants continued their usual activities and care. Primary outcome was pain-related disability assessed by the Oswestry Disability Index (ODI) score. Secondary outcomes included pain intensity, sleep quality, and quality of life (QOL). Intent-to-treat analyses were conducted. Results: Of the 350 participants 278 (79%) were female, mean age was 58.8 years (range: 21–92), 244 (69.7%) completed the 8-week survey, 248 (70.9%) the 12-week, and 238 (68%) the 16 -week. No participants withdrew due to adverse treatment effects. Compared with control group, treatment group experienced statistically and clinically significant improvement in ODI score by −4.7 (95% CI: −6.24 to −3.16, p

Background There is a paucity of patient-reported outcomes (PROs) data in lower extremity salvage. Limb salvage can often be achieved with the use of local muscle flaps or fasciocutaneous flaps. The purpose of this study was to compare PROs of patients who underwent lower extremity salvage using local fasciocutaneous flaps or muscle flaps to lower extremity amputation.

Abstract Methane emissions from the oil and gas sector are a large contributor to climate change. Robust emission quantification and source attribution are needed for mitigating methane emissions, requiring a transparent, comprehensive, and accurate geospatial database of oil and gas infrastructure. Realizing such a database is hindered by data gaps nationally and globally. To fill these gaps, we present a deep learning approach on freely available, high-resolution satellite imagery for automatically mapping well pads and storage tanks. We validate the results in the Permian and Denver-Julesburg basins, two high-producing basins in the United States. Our approach achieves high performance on expert-curated datasets of well pads (Precision = 0.955, Recall = 0.904) and storage tanks (Precision = 0.962, Recall = 0.968). When deployed across the entire basins, the approach captures a majority of well pads in existing datasets (79.5%) and detects a substantial number (>70,000) of well pads not present in those datasets. Furthermore, we detect storage tanks (>169,000) on well pads, which were not mapped in existing datasets. We identify remaining challenges with the approach, which, when solved, should enable a globally scalable and public framework for mapping well pads, storage tanks, and other oil and gas infrastructure.

Introduction: Subcutaneous implantable cardioverter-defibrillator (S-ICD) differs from the transvenous ICD (TV-ICD) system in its extrathoracic and extravascular localization, eliminating the risks arising from vascular access and leading to fewer complications. The objective was to describe the functionality and postoperative complications associated with SICD implants in patients with cardiac dysfunctions. Methods: We enrolled six patients eligible for SICD due to either anterior wall myocardial infarction or left ventricular dysfunction, who reported to our tertiary cardiac care center from June 2020 to March 2022. Preprocedural evaluation for various cardiac parameters was carried out. The procedure was performed under antibiotic prophylaxis. Two incision techniques were used for the SICD placement. The primary and secondary endpoints for the cases were set to evaluate device-related complications and predictive outcomes, respectively. Results: Subcutaneous implantable defibrillator was placed in six male patients aged 36−51 years. The procedure demonstrated an efficient, reliable, and well-accepted modality in eliminating ventricular tachycardia, ventricular fibrillation, and sudden cardiac death. In addition, postoperative complications, such as device infection, pocket hematoma, blood transfusion, prolonged hospitalization, cardiac perforation or tamponade, lead repositioning, or inappropriate shocks, were not reported in the 2 years of follow-up. Conclusion: Subcutaneous implantable defibrillator promises to offer a suitable and safer option for TV-ICD, especially in young patients. It circumvents the need to enter the vasculature or cardiac chambers. As a result, fewer reported lead-related complications, better cosmetic appearance, and greater immediate postoperative comfort as it permits free shoulder movement.

Abstract Background As U.S. legislators are urged to combat ghost networks in behavioral health and address the provider data quality issue, it becomes important to better characterize the variation in data quality of provider directories to understand root causes and devise solutions. Therefore, this manuscript examines consistency of address, phone number, and specialty information for physician entries from 5 national health plan provider directories by insurer, physician specialty, and state. Methods We included all physicians in the Medicare Provider Enrollment, Chain, and Ownership System (PECOS) found in ≥ 2 health insurer physician directories across 5 large national U.S. health insurers. We examined variation in consistency of address, phone number, and specialty information among physicians by insurer, physician specialty, and state. Results Of 634,914 unique physicians in the PECOS database, 449,282 were found in ≥ 2 directories and included in our sample. Across insurers, consistency of address information varied from 16.5 to 27.9%, consistency of phone number information varied from 16.0 to 27.4%, and consistency of specialty information varied from 64.2 to 68.0%. General practice, family medicine, plastic surgery, and dermatology physicians had the highest consistency of addresses (37-42%) and phone numbers (37-43%), whereas anesthesiology, nuclear medicine, radiology, and emergency medicine had the lowest consistency of addresses (11-21%) and phone numbers (9-14%) across health insurer directories. There was marked variation in consistency of address, phone number, and specialty information by state. Conclusions In evaluating a large national sample of U.S. physicians, we found minimal variation in provider directory consistency by insurer, suggesting that this is a systemic problem that insurers have not solved, and considerable variation by physician specialty with higher quality data among more patient-facing specialties, suggesting that physicians may respond to incentives to improve data quality. These data highlight the importance of novel policy solutions that leverage technology targeting data quality to centralize provider directories so as not to not reinforce existing data quality issues or policy solutions to create national and state-level standards that target both insurers and physician groups to maximize quality of provider information.

Background: To assess the effects of combining Tramadol and Dexamethasone with Bupivacaine in supraclavicular brachial plexus block for upper limb surgeries. Material and Methods: A clinical research was performed with sixty patients who received upper limb surgery with a supraclavicular brachial plexus block. The study encompassed a total of 60 patients who were divided into two groups, with 30 patients in each group. Group D was administered a blend of Bupivacaine and Dexamethasone, whilst Group T was given a mixture of Bupivacaine and Tramadol, resulting in a combined amount of 25 ml. The study recorded the beginning and length of the sensory and motor block. We meticulously observed the hemodynamic variables throughout the research, until the administration of the first rescue analgesic. Results: In group D, the mean time for motor block to occur was 5.10±0.92 minutes, whereas in group T, it took 7.93±0.98 minutes. Group D had an average sensory block onset time of 8.23±1.22 minutes, whereas Group T had a slightly longer average onset time of 10.97±1.22 minutes. Group D had an average motor block duration of 560.53±24.46 minutes, whereas group T had a duration of 358.93±20.85 minutes. Group D had a mean duration of sensory block of 745.17±32.81 minutes, whereas group T had a slightly shorter duration of 457.07±16.36 minutes. In group D, the average time for the first rescue analgesia was 961.50±32.94 minutes, whereas in group T, it was 524.17±16.46 minutes. Conclusion: Inclusion of Dexamethasone led to a noticeably quicker onset of motor and sensory block in comparison to Tramadol. In a recent study, researchers discovered that when Dexamethasone was added to the mix, it had a notable impact on the duration of both motor and sensory block. The effects were significant and promising. When Dexamethasone was added, it noticeably increased the duration until the first rescue analgesia, in comparison to Tramadol.

Background:. There is limited consensus regarding the economic value of prosthetic devices with advancing age. We aimed to meet this knowledge gap by studying the cost-effectiveness of lower limb prostheses (LLPs) for older adults with dysvascular amputations. Methods Design:. We constructed a decision analytic model nested with Markov models with a lifetime horizon to compare LLP recipients (LLP) with non-recipients (no-LLP) from a health care sector perspective. A 3% annual rate was applied to obtain the present value of the main outcome measures. One-way sensitivity analyses that modeled clinically extreme scenarios were conducted on LLP cost, change, abandonment rate, fall rate, mortality, and utility. Data sources:. Model parameters were obtained from literature, with many source studies utilizing Medicare data and focusing on dysvascular amputations. Parameters included the “annual probability” of fall, LLP abandonment and mortality, costs associated with decreased physical inactivity or deconditioning, falls (rate and cost), abandonment (rate), mortality, and “utilities associated” with Markov model health states. All costs were adjusted to 2022 price levels. Intervention:. Lower limb prosthesis. Main Outcome Measures:. Lifetime cost, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratio (ICER). Results:. The LLP group incurred a lifetime cost of $36,789 and yielded 4.54 QALYs. The no-LLP group incurred a lifetime cost of $23,909 and yielded 2.58 QALYs. The ICER was $6588/QALY, which is below the most conservative willingness-to-pay threshold of $50,000/QALY and indicated that LLP was cost-effective compared with no-LLP. Sensitivity analyses for increasing LLP replacement to annual (ICER = $33,477/QALY), abandonment rate to 22% (ICER=$6367), fall rate to 70% (ICER = $7140/QALY), and increasing No-LLP EuroQol–five-dimension to 0.71 (ICER = $10,819/QALY) were all below the willingness-to-pay as well. Conclusions:. LLP for older adults with dysvascular amputations was cost-effective for most clinically realistic scenarios.

Abstract Background Sport-related injuries and illnesses can negatively impact athlete welfare at all standards of participation in team sports. Injury and illness surveillance (IIS), and the development of monitoring systems, initiates the sequence of injury and illness prevention. Operational IIS monitoring systems help to appraise epidemiological estimates of injury and illness incidence and burden in various athlete populations. However, the methodological underpinnings of various monitoring systems are not harmonized or widely documented, with the presence of efficient and successful programmes rarely showcased at non-elite levels. The aim is to provide a framework that guides the development of IIS, which will enhance overall surveillance, to indirectly inform injury prevention strategies. Methods The process involved all members of the research group initially discussing the research gaps, scope of the project, and the aims of the article. Unique experiences were shared, and specific and global challenges and barriers to IIS at all standards of team sport participation were identified. A tiered system of data collection with corresponding content were produced, with experiences and guidance provided throughout the article. Results The literature has been reviewed and using first-hand experience in conducting IIS programmes in complex and diverse sport settings, the authors have identified key enablers and barriers for best practise as time, technological and human resources, reporter/practitioner training, and medical expertise. Areas of greatest importance regarding the conducting of IIS have been outlined, providing guidance and recommendations across all levels of team sport participation. These areas include definitions, data context, collection procedures, handling, security, ethics, storage, dissemination, quality, compliance, and analysis. Given the barriers to IIS, 3-tiered levels of data collection and content have been proposed. The levels indicate data collection variables, with a focus on sufficiency and achievability, aiming to support the successful conducting of IIS in team sports across all standards of participation. Future opportunities in IIS have been discussed, with several predictive measures and analytical techniques expanded upon. Conclusions The framework provides universal guidance for implementing IIS monitoring systems, facilitating athletes, coaches, parents/guardians, governing bodies and practitioners to implement IIS processes, identify challenges, complete analysis, and interpret outcomes at all standards of participation.

Abstract L1CAM-positive extracellular vesicles (L1EV) are an emerging biomarker that may better reflect ongoing neuronal damage than other blood-based biomarkers. The physiological roles and regulation of L1EVs and their small RNA cargoes following stroke is unknown. We sought to characterize L1EV small RNAs following stroke and assess L1EV RNA signatures for diagnosing stroke using weighted gene co-expression network analysis and random forest (RF) machine learning algorithms. Interestingly, small RNA sequencing of plasma L1EVs from patients with stroke and control patients (n = 28) identified micro(mi)RNAs known to be enriched in the brain. Weighted gene co-expression network analysis (WGCNA) revealed small RNA transcript modules correlated to diagnosis, initial NIH stroke scale, and age. L1EV RNA signatures associated with the diagnosis of AIS were derived from WGCNA and RF classification. These small RNA signatures demonstrated a high degree of accuracy in the diagnosis of AIS with an area under the curve (AUC) of the signatures ranging from 0.833 to 0.932. Further work is necessary to understand the role of small RNA L1EV cargoes in the response to brain injury, however, this study supports the utility of L1EV small RNA signatures as a biomarker of stroke.

Microscopic and digital whole-slide images (WSIs) often suffer from limited spatial resolution, hindering accurate pathological analysis and cancer diagnosis. Improving the spatial resolution of these pathology images is crucial, as it can enhance the visualization of fine cellular and tissue structures, leading to more reliable and precise cancer detection and diagnosis. This paper presents a comprehensive comparative study on super-resolution (SR) reconstruction techniques for prostate WSI, exploring a range of machine learning, deep learning, and generative adversarial network (GAN) algorithms. The algorithms investigated include regression, sparse learning, principal component analysis, bicubic interpolation, multi-support vector neural networks, an SR convolutional neural network, and an autoencoder, along with advanced SRGAN-based methods. The performance of these algorithms was meticulously evaluated using a suite of metrics, such as the peak signal-to-noise ratio (PSNR), structural similarity index metrics (SSIMs), root-mean-squared error, mean absolute error and mean structural similarity index metrics (MSSIMs). The comprehensive study was conducted on the SICAPv2 prostate WSI dataset. The results demonstrated that the SRGAN algorithm outperformed other algorithms by achieving the highest PSNR value of 26.47, an SSIM of 0.85, and an MSSIM of 0.92, by 4× magnification of the input LR image, preserving the image quality and fine details. Therefore, the application of SRGAN offers a budget-friendly counter to the high-cost challenge of acquiring high-resolution pathology images, enhancing cancer diagnosis accuracy.

Despite the prevalence of mesenteric artery occlusive disease in the elderly population, revascularization for chronic mesenteric ischemia (CMI) accounts for

Mental health problems have become one of the major issues worldwide. People of every age group and gender are facing psychological issues. Conventional medicines are not reliable due to their adverse effects like altered sleeping pattern, addiction and health problems throughout the entire body. Psychobiotics is a new class of probiotics that is serving a wide range of applications in psychological health. Psychobiotic refers to the biological formulation which when consumed in right amount, confers psychological benefits. A lot of studies have supported the function of gut microbiota in mood cognition and controlling anxiety. The mechanism of action of psychobiotics has not been completely investigated. However, it may confer benefits by modulating hypothalamic-pituitary-adrenal (HPA) axis, by directly influencing immune system and through production of various neurotransmitters and neurohormones like proteins and short fatty acids chains. This review highlights the potential of different bacterial strains in human and animal trials. It latter also covers various psychobiotics formulations marketed by different companies. In addition to this, we also tried to cover the various hurdles in psychobiotic research that need to be addressed in the future to build a prosperous society.

Undoubtedly, urbanization has improved human living conditions. However, it has also altered the natural landscape, leading to negative consequences such as increased Land Surface Temperature (LST) and Urban Heat Island (UHI) due to the expansion of Impervious Surface (IS). Much research has been conducted in other countries on the effects of changing urban landscape structures on LST and UHI formation. However, in Sri Lanka, only a few studies have been available on this topic, primarily concentrating on major cities like Colombo. Impervious Surface is absorbing high amounts of solar energy as well, which accelerates the magnitude of UHI in urbanized areas. Remote Sensing indices such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Buildup Index (NDBI), UHI, and Environmental Criticality Index (ECI) can effectively be used to quantify the intensity of the UHI phenomenon. This study aimed to investigate the effect of spatiotemporal variations in IS and Green Surface (GS) on UHI, LST, and the environmental criticality in Galle Municipal Council (MC), Sri Lanka employing multi-temporal Landsat-5 and 8 data from four different periods: 1996, 2005, 2014, and 2022. Different geospatial techniques including supervised image classification, Urban-Rural Gradient Zone (URGZ) analysis, grid-based analysis, UHI profiles, and regression analysis were used in the study. The findings revealed that Impervious Surface increased by 42.3% (7.34 km2) while Green Surface had a decline of 22.5% (3.91 km2) during the concerned period. This landscape transition led to a 2.74 C increase in mean surface temperature in the study area, along with a 9.5 C increase in the UHI index during 26 years. The results further revealed that Impervious Surface rapidly developed within 4 km (URGZ1-19) from city center, while Green Surface decreased. Newly built-up areas within the 1.5 km gradient (URGZ1-URGZ8) were more affected by increased LST. A positive correlation was identified between NDBI and LST, especially in the year 2022, with an R2 of 0.457, while NDVI and LST reported a negative R2 of 0.257. The grid-based analysis demonstrated an increasingly positive relationship between mean LST and the fraction of Impervious Surface, highlighting the role of built-up areas in raising LST and UHI in the MC. As a result, very high environmental critical areas have been concentrated in and around high-density Impervious Surface. Thus, it can be predicted that the UHI effect and Environmental Criticality (EC) may increase further in the future. In this context, planning agencies should prioritize green urban planning strategies, such as implementing green belts and urban agriculture in the study area, particularly in and around areas with high LST and high environmental criticality. This approach may help protect the natural environment and sustainably ensure the health of the urban community.

BackgroundOn average, people in the United States visit a doctor 4 times a year, and many of them have chronic illnesses. Because of the increased use of technology, people frequently rely on the internet to access health information and statistics. People use health care information to make better-educated decisions for themselves and others. Health care dashboards should provide pertinent and easily understood data, such as information on timely cancer screenings, so the public can make better-informed decisions. In order to enhance health outcomes, effective dashboards should provide precise data in an accessible and easily digestible manner. ObjectiveThis study identifies the top 15 attributes of a health care dashboard. The objective of this research is to enhance health care dashboards to benefit the public by making better health care information available for more informed decisions by the public and to improve population-level health care outcomes. MethodsThe authors conducted a survey of health care dashboards with 218 individuals identifying the best practices to consider when creating a public health care dashboard. The data collection was conducted from June 2023 to August 2023. The analyses performed were descriptive statistics, frequencies, and a comparison to a prior study. ResultsFrom May 2023 to June 2023, we collected 3259 responses in multiple different states around the United States from 218 people aged 18 years or older. The features ranking in descending order of importance are as follows: (1) easy navigation, (2) historical data, (3) simplicity of design, (4) high usability, (5) use of clear descriptions, (6) consistency of data, (7) use of diverse chart types, (8) compliance with the Americans with Disabilities Act, (9) incorporated user feedback, (10) mobile compatibility, (11) comparison data with other entities, (12) storytelling, (13) predictive analytics with artificial intelligence, (14) adjustable thresholds, and (15) charts with tabulated data. ConclusionsFuture studies can extend the research to other types of dashboards such as bioinformatics, financial, and managerial dashboards as well as confirm these top 15 best practices for medical dashboards with further evidentiary support. The medical informatics community may benefit from standardization to improve efficiency and effectiveness as dashboards can communicate vital information to patients worldwide on critically prominent issues. Furthermore, health care professionals should use these best practices to help increase population health care outcomes by informing health care consumers to make better decisions with better data.

Background: The American Thoracic Society has published general guidelines for sterility when testing for bronchodilator responsiveness. However, the extent to which practicing allergists implement sterility measures is currently unknown. Objective: This study aims to understand the adherence to the American Thoracic Society guidelines for sterility among practicing allergists. Methods: In 2015, a questionnaire was approved and distributed by the American Academy of Allergy, Asthma & Immunology to all its members. The anonymous responses were recorded and tabulated after a 3-week period. Results: Of the 6800 allergists who received surveys from the American Academy of Allergy, Asthma & Immunology members, 496 participated in the survey (response rate 7.3%). Using metered dose inhalers with a spacer and nebulizers were the most common bronchodilator administration techniques, as indicated by 59.35% and 58.52% of responses, respectively. Whereas 69.25% of the allergists considered their bronchodilator administration techniques to be sterile, 14.05% did not consider their administration technique to be sterile and 16.70% were unsure. For maintaining sterility, 38.75% of the respondents indicated using a new disposable attachment for reused inhalers, 18.71% indicated using a new inhaler for each patient, and 9.13% reported wiping inhalers with a cleaning agent. Conclusions: When asked about the sterility of the techniques used by them, nearly one-third of the allergists either stated that the measures used by them were unsterile or stated that they were were unsure. To increase adherence to sterility measures among North American allergists, promoting guideline awareness and proposing updated guidelines focused on the most common bronchodilator administration techniques is essential.

Abstract BackgroundRecent studies, including those by the National Board of Medical Examiners, have highlighted the remarkable capabilities of recent large language models (LLMs) such as ChatGPT in passing the United States Medical Licensing Examination (USMLE). However, there is a gap in detailed analysis of LLM performance in specific medical content areas, thus limiting an assessment of their potential utility in medical education. ObjectiveThis study aimed to assess and compare the accuracy of successive ChatGPT versions (GPT-3.5, GPT-4, and GPT-4 Omni) in USMLE disciplines, clinical clerkships, and the clinical skills of diagnostics and management. MethodsThis study used 750 clinical vignette-based multiple-choice questions to characterize the performance of successive ChatGPT versions (ChatGPT 3.5 [GPT-3.5], ChatGPT 4 [GPT-4], and ChatGPT 4 Omni [GPT-4o]) across USMLE disciplines, clinical clerkships, and in clinical skills (diagnostics and management). Accuracy was assessed using a standardized protocol, with statistical analyses conducted to compare the models’ performances. ResultsGPT-4o achieved the highest accuracy across 750 multiple-choice questions at 90.4%, outperforming GPT-4 and GPT-3.5, which scored 81.1% and 60.0%, respectively. GPT-4o’s highest performances were in social sciences (95.5%), behavioral and neuroscience (94.2%), and pharmacology (93.2%). In clinical skills, GPT-4o’s diagnostic accuracy was 92.7% and management accuracy was 88.8%, significantly higher than its predecessors. Notably, both GPT-4o and GPT-4 significantly outperformed the medical student average accuracy of 59.3% (95% CI 58.3‐60.3). ConclusionsGPT-4o’s performance in USMLE disciplines, clinical clerkships, and clinical skills indicates substantial improvements over its predecessors, suggesting significant potential for the use of this technology as an educational aid for medical students. These findings underscore the need for careful consideration when integrating LLMs into medical education, emphasizing the importance of structured curricula to guide their appropriate use and the need for ongoing critical analyses to ensure their reliability and effectiveness.

Summary: Background: There have been no detailed descriptions of infants born to mothers treated for drug resistant TB in pregnancy. Critical case history assessment is important to identify risks and guide clinical practice. Methods: In a cohort of pregnant women with multidrug or rifampicin resistant (MDR/RR)-TB enrolled between 1 January 2013 and 31 December 2022, we followed mother-infant pairs until the infant was 12 months old. We performed critical case history assessments to explore potential mechanisms of Mycobacterium tuberculosis transmission to the infant, and to describe the clinical presentation and disease trajectories observed in infants diagnosed with TB. Findings: Among 101 mother-infant pairs, 23 (23%) included infants diagnosed with TB disease; 16 were clinically diagnosed and seven had microbiological confirmation (five MDR/RR-TB, two drug-susceptible TB). A positive maternal sputum culture at the time of delivery was significantly associated with infant TB risk (p = 0.023). Of the 12 infants diagnosed with TB in the first three months of life, seven (58%) of the mothers were culture positive at delivery; of whom four reported poor TB treatment adherence. However, health system failures, including failing to diagnose and treat maternal MDR/RR-TB, inadequate screening of newborns at birth, not providing appropriate TB preventive therapy (TPT), and M. tuberculosis transmission from non-maternal sources also contributed to TB development in infants. Interpretation: Infants born to mothers with MDR/RR-TB are at greatest risk if maternal adherence to MDR/RR-TB treatment or antiretroviral therapy (ART) is sub-optimal. In a high TB incidence setting, infants are also at risk of non-maternal household and community transmission. Ensuring maternal TB diagnosis and appropriate treatment, together with adequate TB screening and prevention in all babies born to mothers or households with TB will minimise the risk of infant TB disease development. Funding: South African Medical Research Council.

Abstract BackgroundAdmission to the neonatal intensive care unit (NICU) is costly and has been associated with financial and emotional stress among families. Digital health may be well equipped to impact modifiable health factors that contribute to NICU admission rates. ObjectiveThe aim of the study is to investigate how the use of a comprehensive prenatal digital health platform is associated with gestational age at birth and mechanisms to reduce the risk of admission to the NICU. MethodsData were extracted from 3326 users who enrolled in a comprehensive digital health platform between January 2020 and May 2022. Multivariable linear and logistic regression models were used to estimate the associations between hours of digital health use and (1) gestational age at birth and (2) mechanisms to reduce the risk of a NICU admission. Multivariable logistic regression models estimated the associations between (1) gestational age at birth and (2) mechanisms to reduce the risk of a NICU admission and the likelihood of a NICU admission. All analyses were stratified by the presence of any gestational conditions during pregnancy. ResultsFor users both with and without gestational conditions, hours of digital health use were positively associated with gestational age at birth (in weeks; with gestational conditions: β=.01; 95% CI 0.0006-0.02; PPPPPPPPPPP ConclusionsDigital health use may aid in extending gestational age at birth and reduce the risk of NICU admission.

Recent research has shown that droughts have intensified in South Asia over the past two decades. As a natural disaster, this has severely impacted people’s livelihoods, especially in the dry zones of Sri Lanka. Thus, to ensure human well-being, security of water resources, and ecosystem health, it is essential to minimize the impacts of droughts using reliable information. Remote sensing (RS) data and techniques help bridge the gap by enabling the analysis of drought phenomena through a diverse array of indices developed in the fields. However, until now, there has been a lack of systematic monitoring and reliable data for accurately characterizing droughts in the study area. As the first comprehensive analysis, we tried to evaluate the spatial–temporal dynamics of drought conditions in two Divisional Secretariat Divisions of the Anuradhapura district, Sri Lanka using eight standardized remote sensing-derived indices over a decade (2013–2023) including the Standardized Precipitation Index (SPI). SPI values indicated that the region has experienced notably below-average precipitation. According to SPI results, a significant portion of the Medawchchiya area experienced arid conditions in 2023. All other indices proved that 2018 was the driest year and 2013 was the wettest year among the three time points, as reflected by their low and high index values. However, according to NVSMI and LST, the wettest year is 2023, with only 1.78 % of areas experiencing severe drought and a maximum LST of 31.4 °C. LULC change detection revealed that 14.3 % of agricultural lands and 5.1 % of forest areas were converted into barren lands over a decade. Overall, this conversion may be another leading factor contributing to increased LST and dryness in the area during the concerned period while increasing the mean LST of barren land by around 4.7 °C per decade. Land surface-related and vegetation-related indices, such as NDWI, NDMI, LST, and NDVI, exhibited a more pronounced impact on short-term drought occurrences. The findings revealed that average precipitation coincides with short-term drought episodes in the area, with 2018 standing out as having the least rainfall and the driest year. The study’s findings may provide additional insights for planning authorities, supporting environmental protection and enhancing agricultural production by mitigating droughts’ impacts through short- and long-term strategies. Although, the study focused on a small area, a similar approach could be extended to other areas by incorporating advanced machine learning techniques and additional drought indices in the future.

Objective Given the complex nature of preterm birth, interventions to reduce rates of preterm birth should be multifaceted. This analysis aimed to explore the association between the duration of using Maven, a digital health platform for women's and family health, and the odds of preterm birth. Methods Data came from 3326 pregnant, nulliparous Maven users who enrolled in Maven during their pregnancy between January 2020 and September 2022. Chi-square and Fisher's exact tests compared characteristics between users who developed gestational conditions and users who did not. This retrospective cohort study used logistic regression models to estimate the association between the duration of Maven use and odds of preterm birth, stratified by the presence of gestational conditions. Results Compared to those without gestational conditions, individuals who developed gestational conditions were more likely to have a preterm birth (8.7% vs. 3.4%; p

Reliable information plays a pivotal role in sustainable urban planning. With advancements in computer technology, geoinformatics tools enable accurate identification of land use and land cover (LULC) in both spatial and temporal dimensions. Given the need for precise information to enhance decision-making, it is imperative to assess the performance and reliability of classification algorithms in detecting LULC changes. While research on the application of machine learning algorithms in LULC evaluation is widespread in many countries, it remains limited in Zambia and Sri Lanka. Hence, we aimed to assess the reliability and performance of support vector machine (SVM), random forest (RF), and artificial neural network (ANN) algorithms for detecting changes in land use and land cover taking Lusaka and Colombo City as the study area from 1995 to 2023 using Landsat Thematic Mapper (TM), and Operational Land Imager (OLI). The results reveal that the RF and ANN models exhibited superior performance, both achieving Mean Overall Accuracy (MOA) of 96% for Colombo and 96% and 94% for Lusaka, respectively. Meanwhile, the SVM model yielded Overall Accuracy (OA) ranging between 77% and 94% for the years 1995 and 2023. Further, RF algorithm notably produced slightly higher OA and kappa coefficients, ranging between 0.92 and 0.97, when compared to both the ANN and SVM models, across both study areas. A predominant land use change was observed as the expansion of vegetation by 11,990 ha (60.4%), primarily through the conversion of 1,926 ha of bare lands into vegetation in Lusaka during 1995–2005. However, a noteworthy shift was observed as built-up areas experienced significant growth from 2005 to 2023, with a total increase of 25,110 ha (71%). However, despite the conversion of vegetation to built-up areas during the entire period from 1995 to 2023, there was still a net gain of over 11,000 ha (53.4%) in vegetation cover. In case of Colombo, built-up areas expanded by 1,779 ha (81.5%), while vegetation land decreased by 1,519 ha (62.3%) during concerned period. LULC simulation also indicated a 160-ha expansion of built-up areas during the 2023–2035 period in Lusaka. Likewise, Colombo saw a rise in built-up areas by 337 ha within the same period. Overall, the RF algorithm outperformed the ANN and SVM algorithms. Additionally, the prediction and simulation results indicate an upward trend in built-up areas in both scenarios. The resultant land cover maps provide a crucial baseline that will be invaluable for urban planning and policy development agencies in both countries.

Abstract The gold standard for enrollment and endpoint assessment in metabolic dysfunction‐associated steatosis clinical trials is histologic assessment of a liver biopsy performed on glass slides. However, obtaining the evaluations from several expert pathologists on glass is challenging, as shipping the slides around the country or around the world is time‐consuming and comes with the hazards of slide breakage. This study demonstrated that pathologic assessment of disease activity in steatohepatitis, performed using digital images on the AISight whole slide image management system, yields results that are comparable to those obtained using glass slides. The accuracy of scoring for steatohepatitis (nonalcoholic fatty liver disease activity score ≥4 with ≥1 for each feature and absence of atypical features suggestive of other liver disease) performed on the system was evaluated against scoring conducted on glass slides. Both methods were assessed for overall percent agreement with a consensus “ground truth” score (defined as the median score of a panel of three pathologists’ glass slides). Each case was also read by three different pathologists, once on glass and once digitally with a minimum 2‐week washout period between the modalities. It was demonstrated that the average agreement across three pathologists of digital scoring with ground truth was noninferior to the average agreement of glass scoring with ground truth [noninferiority margin: −0.05; difference: −0.001; 95% CI: (−0.027, 0.026); and p

Interactions between cancer cells and immune cells in the tumor microenvironment influence tumor growth and can contribute to the response to cancer immunotherapies. It is difficult to gain mechanistic insights into the effects of cell–cell interactions in tumors using a purely experimental approach. However, computational modeling enables quantitative investigation of the tumor microenvironment, and agent-based modeling, in particular, provides relevant biological insights into the spatial and temporal evolution of tumors. Here, we develop a novel agent-based model (ABM) to predict the consequences of intercellular interactions. Furthermore, we leverage our prior work that predicts the transitions of CD8+ T cells from a naïve state to a terminally differentiated state using Boolean modeling. Given the details incorporated to predict T cell state, we apply the integrated Boolean–ABM framework to study how the properties of CD8+ T cells influence the composition and spatial organization of tumors and the efficacy of an immune checkpoint blockade. Overall, we present a mechanistic understanding of tumor evolution that can be leveraged to study targeted immunotherapeutic strategies.

Abstract The study aimed to determine the accuracy of diagnosing periodontal conditions using the developed web-based PocketPerio application and evaluate the user’s perspective on the use of PocketPerio. First, 22 third-year dental students (DS3) diagnosed ten cases without PocketPerio (control) and with PocketPerio (test) during a mock examination. Then, 105 DS3, 13 fourth-year dental students (DS4), and 32 senior second-year International Standing Program students (ISP2) used PocketPerio chairside. Statistical analysis was performed using a non-parametric paired two-tailed test of significance with the Wilcoxon matched-pairs signed rank test. The null hypothesis that PocketPerio did not increase the accuracy of periodontal diagnoses was rejected at α

Introduction: Volume Controlled Ventilation (VCV) is traditionally used during One Lung Ventilation (OLV); however, it is associated with complications such as volutrauma and barotrauma. On the other hand, Pressure Controlled Ventilation (PCV) allows the delivery of a required tidal volume at lower airway pressures, leading to enhanced oxygenation and ventilation. Aim: To compare VCV and PCV modes for OLV in patients undergoing surgery for empyema thoracis. Materials and Methods: A randomised controlled trial was conducted among 50 patients requiring OLV. The participants were divided into two groups, namely Group-V and Group-P, with each group receiving VCV and PCV, respectively. The two groups were compared based on the partial pressure of oxygen (during the intraoperative and post-operative period), peak and plateau airway pressures, lung compliance, and complications. The groups were analysed using the Chi-square test, and the threshold of statistical significance was set at a p-value

Abstract Background Reduced clearance of cerebrospinal fluid (CSF) has been suggested as a pathological feature of Alzheimer’s disease (AD). With extensive documentation in non-human mammals and contradictory human neuroimaging data it remains unknown whether the nasal mucosa is a CSF drainage site in humans. Here, we used dynamic PET with [1-11C]-Butanol, a highly permeable radiotracer with no appreciable brain binding, to test the hypothesis that tracer drainage from the nasal pathway reflects CSF drainage from brain. As a test of the hypothesis, we examined whether brain and nasal fluid drainage times were correlated and affected by brain amyloid. Methods 24 cognitively normal subjects (≥ 65 years) were dynamically PET imaged for 60 min. using [1-11C]-Butanol. Imaging with either [11C]-PiB or [18F]-FBB identified 8 amyloid PET positive (Aβ+) and 16 Aβ- subjects. MRI-determined regions of interest (ROI) included: the carotid artery, the lateral orbitofrontal (LOF) brain, the cribriform plate, and an All-turbinate region comprised of the superior, middle, and inferior turbinates. The bilateral temporalis muscle and jugular veins served as control regions. Regional time-activity were used to model tracer influx, egress, and AUC. Results LOF and All-turbinate 60 min AUC were positively associated, thus suggesting a connection between the brain and the nose. Further, the Aβ+ subgroup demonstrated impaired tracer kinetics, marked by reduced tracer influx and slower egress. Conclusion The data show that tracer kinetics for brain and nasal turbinates are related to each other and both reflect the amyloid status of the brain. As such, these data add to evidence that the nasal pathway is a potential CSF drainage site in humans. These data warrant further investigation of brain and nasal contributions to protein clearance in neurodegenerative disease.

Abstract The present study examined the role of age and sex in the outcomes of non-surgical periodontal therapy (NSPT). De-identified demographic and periodontal characteristics of patients who presented for baseline periodontal evaluation, NSPT, and periodontal re-evaluation were abstracted from electronic health records. Independent associations of age and sex with severe periodontitis defined as ≥ 5 mm clinical attachment loss (CAL) and ≥ 6 mm probing depth (PD) were determined using multinomial logistic regression. The null hypothesis was rejected at α