Browse Articles

Pure data correction enhancing remote sensing image classification with a lightweight ensemble model

A randomized trial comparing medium cut-off membrane dialyzers with online hemodiafiltration for uremic toxins clearance in hemodialysis patients

Accelerating inverse Kohn–Sham calculations using reduced density matrices

The Ryabinkin–Kohut–Staroverov (RKS) and Kanungo–Zimmerman–Gavini (KZG) methods offer two approaches to find exchange-correlation (XC) potentials from ground state densities. The RKS method utilizes the one- and two-particle reduced density matrices to alleviate any numerical artifacts stemming from a finite basis (e.g., Gaussian- or Slater-type orbitals). The KZG approach relies solely on the density to find the XC potential by combining a systematically convergent finite-element basis with appropriate asymptotic correction on the target density. The RKS method, being designed for a finite basis, offers computational efficiency. The KZG method, using a complete basis, provides higher accuracy. In this work, we combine both methods to simultaneously afford accuracy and efficiency. In particular, we use the RKS solution as an initial guess for the KZG method to attain a significant 3–11× speedup. This work also presents a direct comparison of the XC potentials from the RKS and the KZG method and their relative accuracy on various weakly and strongly correlated molecules, using their ground state solutions from accurate configuration interaction calculations solved in a Slater orbital basis.

A parallel texture-based region-growing algorithm implemented in OpenMP

Three-dimensional memory of nuclear organization through cell cycles

The genome in the cell nucleus is organized by a dynamic process influenced by structural memory from mitosis. In this study, we develop a model of human genome dynamics through cell cycles by extending the previously developed whole-genome model to cover the mitotic phase. With this extension, we focus on the role of mitotic and cell cycle memory in genome organization. The simulation progresses from mitosis to interphase and the subsequent mitosis, leading to successive cell cycles. During mitosis, our model describes microtubule dynamics, showing how forces orchestrate the assembly of chromosomes into a rosette ring structure at metaphase. The model explains how the positioning of chromosomes depends on their size in metaphase. The memory of the metaphase configuration persists through mitosis and into interphase in dimensions perpendicular to the cell division axis, effectively guiding the distribution of chromosome territories over multiple cell cycles. At the onset of each G1 phase, phase separation of active and inactive chromatin domains occurs, leading to A/B compartmentalization. Our cycling simulations show that the compartments are unaffected by structural memory from previous cycles and are consistently established in each cell cycle. The genome model developed in this study highlights the interplay between chromosome dynamics and structural memory across cell cycles, providing insights for the analyses of cellular processes.

Saturation genome editing-based clinical classification of BRCA2 variants

Deep learning based screening model for hip diseases on plain radiographs

Introduction The interpretation of plain hip radiographs can vary widely among physicians. This study aimed to develop and validate a deep learning-based screening model for distinguishing normal hips from severe hip diseases on plain radiographs. Methods Electronic medical records and plain radiograph from 2004 to 2012 were used to construct two patient groups: the hip disease group (those who underwent total hip arthroplasty) and normal group. A total of 1,726 radiographs (500 normal hip radiographs and 1,226 radiographs with hip diseases, respectively) were included and were allocated for training (320 and 783), validation (80 and 196), and test (100 and 247) groups. Four different models were designed–raw image for both training and test set, preprocessed image for training but raw image for the test set, preprocessed images for both sets, and change of backbone algorithm from DenseNet to EfficientNet. The deep learning models were compared in terms of accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1-score, and area under the receiver operating characteristic curve (AUROC). Results The mean age of the patients was 54.0 ± 14.8 years in the hip disease group and 49.8 ± 14.9 years in the normal group. The final model showed highest performance in both the internal test set (accuracy 0.96, sensitivity 0.96, specificity 0.97, PPV 0.99, NPV 0.99, F1-score 0.97, and AUROC 0.99) and the external validation set (accuracy 0.94, sensitivity 0.93, specificity 0.96, PPV 0.95, NPV 0.93, F1-score 0.94, and AUROC 0.98). In the gradcam image, while the first model depended on unrelated marks of radiograph, the second and third model mainly focused on the femur shaft and sciatic notch, respectively. Conclusion The deep learning-based model showed high accuracy and reliability in screening hip diseases on plain radiographs, potentially aiding physicians in more accurately diagnosing hip conditions.

Timing the Taming of Vascular Inflammation

Human responses to the DNA prime/chimpanzee adenovirus (ChAd63) boost vaccine identify CSP, AMA1 and TRAP MHC Class I-restricted epitopes

Background A three-antigen DNA-prime/chimpanzee adenovirus 63 (ChAd63) boost vaccine containing pre-erythrocytic Plasmodium falciparum (Pf) circumsporozoite protein (CSP), Pf apical membrane antigen-1 (AMA1) and malaria multiple epitopes (ME) fused to Pf thrombospondin-related adhesion protein (ME-TRAP) elicited higher vaccine efficacy (VE) in an open label, randomized Phase 1 trial against controlled human malaria infection (CHMI) than the two-antigen vaccine DNA/Human Adenovirus 5 (HuAd5) containing CSP and AMA1. The objective of this follow-up study was to determine whether responses to CSP, AMA1 or TRAP MHC Class I-restricted epitopes were associated with VE. Methodology Protected (n = 6) and non-protected participants (n = 26) were screened in FluoroSpot interferon gamma (IFN-γ) and Granzyme B (GzB) assays using antigen-specific 15mer peptide subpools spanning CSP (n = 9 subpools), AMA1 (n = 12 subpools), and TRAP (n = 11 subpools). Individual antigen-specific 15mers in the subpools with strong responses were then deconvoluted, evaluated for activities, and MHC Class I-restricted epitopes within the active 15mers were predicted using NetMHCpan algorithms. The predicted epitopes were synthesized and evaluated in the FluoroSpot IFN-γ and GzB assays. Results Protected and some non-protected participants had similar responses to individual antigen-specific peptide subpools, which did not distinguish only protected participants. However, deconvoluted antigen-specific positive subpools with high magnitudes of responses revealed individual 15mer peptides containing specific and/or predicted MHC Class I (HLA) epitopes. Responses to epitopes were either IFN-γ-only, IFN-γ and GzB, or GzB-only. Due to limitation of cells, most of the analysis concentrated on the identification of protection associated AMA1 epitopes, since most of the predominant pool specific responses were generated against AMA1 15mer subpools. Furthermore, we previously identified protection associated HLA class I-restricted epitopes in a previous gene-based vaccine trial. Seven predicted minimal epitopes in AMA1 were synthesized and upon testing, five recalled responses from protected participants confirming their possible contribution and association with protection, and two recalled responses from non-protected participants. Two protection-associated epitopes were promiscuous and may have also contributed to protection by recognition of different HLA alleles. In addition, strongly positive antigen-specific 15mers identified within active antigen-specific subpools contained 39 predicted but not tested epitopes were identified in CSP, AMA1 and TRAP. Finally, some non-protected individuals recognized HLA-matched protection-associated minimal epitopes and we discuss possible reasons. Other factors such as HLA allele fine specificity or interaction between other HLA alleles in same individual may also influence protective efficacy. Conclusions This integrated approach using immunoassays and bioinformatics identified and confirmed AMA1-MHC Class I-restricted epitopes and a list of predicted additional epitopes which could be evaluated in future studies to assess possible association with protection against CHMI in the Phase 1 trial participants. The results suggest that identification of protection-associated epitopes within malaria antigens is feasible and can help design potent next generation multi-antigen, multi-epitope malaria vaccines for a genetically diverse population and to develop robust assays to measure protective cellular immunity against pre-erythrocytic stages of malaria. This approach can be used to develop vaccines for other novel emerging infectious disease pathogens.

Reviewers for the <i>Journal</i> , July–December 2024

Correction: Using moss as a bio-indicator to evaluate soil quality in litchi orchard

Radiographic characteristics of impacted teeth: A retrospective study of 2199 radiograph

Objective To analyze the radiological characteristics of impacted teeth in the population of Makkah in Saudi Arabia. Methods A retrospective analysis was conducted on 2199 digital panoramic radiograph (OPG) scans collected from the database of the dental teaching hospital at Umm Al-Qura University, Makkah, KSA. Out of these, 1503 OPGs (749 males and 754 females) met the inclusion criteria, which required clear OPGs with high quality and good visibility of anatomic structures. The study included patients of both genders, aged between 13 and 70, with complete root formation of impacted teeth. Results The analysis of 1,503 patients’ radiographs revealed that 27.70% had impacted third molars, with mandibular molars being more commonly affected than maxillary molars. Additionally, other impacted teeth were observed, including maxillary canines, second premolars, second molars, and supernumerary teeth. Male patients had a slightly higher prevalence of impaction. The majority of impacted third molars were found in the age group of 18-30. The angulation and depth of impacted teeth differed between maxillary and mandibular arches. Most impacted mandibular third molars had a class I relation with the ramus. Conclusion The study provides valuable insights into impacted teeth in Makkah, Saudi Arabia. It highlights a significant occurrence of impacted third molars, as well as other teeth. These findings contribute to a better understanding of impacted teeth and provide important support for dental professionals in their efforts to improve patient outcomes.

Adjusted trajectory of medication exposure taking into account the periodicity of dispensations and the number of dispensed packs and comparative analysis on EFEMERIS database

We presented an adjustment method for the calculation of medication exposure trajectories based on the number of dispensed packs and the type of dispensations (occasional or regular). A comparative study based on the EFEMERIS data was carried out using three different scenarios of trajectory calculation depending on whether or not the number of packs and the periodicity of medication dispensations were taken into account. The impact of the scenario was highlighted using global indicators on the number of Define-Daily Dose (DDD) on all women exposed; the study of changes in individual trajectories from one scenario to another was carried out; we also compared the results of a clustering into four groups. If 65% of the trajectories remained unchanged, we could observe on the rest significant changes in number of DDD and/or on individual exposure profile. We observed 4% of trajectories that were attributed to a different cluster, and the clustering was of better quality with the adjustment method. Depending on the study context, an impact on cluster distribution could be observed for some maternal characteristics and neonatal outcomes. This was the case for a higher occurrence of neonatal pathology for neonates from mothers belonging to the cluster with high doses of psychotropics, thus reinforcing the conclusions of previous studies of a link between high exposure to psychotropic medications and presence of pathology for the newborn.

Is the relative age effect just a European problem? A comprehensive analysis of birth date distribution and its impact on player selection at the 2023 FIFA Women’s World Cup

This study examines the presence and implications of the Relative Age Effect (RAE) in the 2023 FIFA Women’s World Cup, focusing on the distribution of players’ birth dates across continents and professional levels. Utilizing a sample of 735 players, a Poisson regression was conducted on the weekly birth frequency to determine the significance of the fit to a Poisson regression curve. Despite the lack of a significant RAE across the overall player population, our findings reveal notable geographical and positional variations. Specifically, European players, particularly goalkeepers and defenders, alongside the top 4 classified teams and nations with a substantial number of federation licenses, exhibit a significant RAE, suggesting a substantial impact on player selection favouring those born earlier in the year. Conversely, players from Africa, America, Asia, and Oceania do not show a significant RAE, indicating variability in its manifestation across different football environments.

Identification of early predictors and model for bacterial infection in diabetic ketoacidosis patients: A retrospective study

Purpose The purpose of this report was to identify effective indicators capable of predicting bacterial infection during the early stages of diabetic ketoacidosis (DKA) and to establish a diagnostic model suitable for clinical application. Methods This was a retrospective cross-sectional study. Between February 2018 and May 2023, Yuhuangding Hospital admitted 101 DKA patients, of whom 45 were diagnosed with bacterial infections. A confirmed bacterial infection was defined as documented bacteriological evidence in any bacterial sample. Clinical parameters and biological markers (including cortisol, C-reactive protein (CRP), procalcitonin, etc.) were recorded during the initial DKA phase. Multivariate regression analysis was employed to construct a diagnostic model. Results CRP (OR = 1.014, 95% CI: 1.002–1.026, p = 0.017) and cortisol (OR = 1.007, 95% CI: 1.002–1.012, p = 0.003) were found to have an independent association with bacterial infection in DKA patients. The area under the receiver operating characteristic curve (AUC) for CRP in identifying bacterial infection was 0.855 (95% CI, 0.771–0.917), with a sensitivity of 76.1% and a specificity of 83.6%. The AUC for cortisol in identifying bacterial infection was 0.847 (95% CI, 0.761–0.911), with a sensitivity of 71.7% and a specificity of 89.1%. A joint diagnostic model based on cortisol and CRP was developed through multifactor regression analysis. The AUC of this diagnostic model was 0.930 (95% CI, 0.862–0.972), resulting in a sensitivity of 93.5% and a specificity of 80.0%. Conclusion CRP and cortisol are early indicators of bacterial infection in DKA patients. Furthermore, based on their combination, the regression diagnostic model exhibits enhanced diagnostic performance.

The effect of a cognitive dual-task on the control of wheelchair propulsion

Movement analyses of wheelchair users are rarely integrated into clinical operations, although these are recommended to prevent pain and injury in the upper extremity. In addition, previous movement analyses in the laboratory do not include the possible influences of distractions that occur in everyday wheelchair use. We therefore transferred the dual-task method known from the motion analysis of walkers to the analysis of the propulsion behavior of wheelchair users and examined whether the changes resulting from the additional cognitive task also show up here. The 52 participants consisted of 38 manual wheelchair users (age = 43.8 ± 14.2 years; sex = 11/27 f/m) and 14 novices (age = 39.2 ±  15.4 years; sex = 8/6 f/m). The participants propelled their wheelchairs on a test stand and movements of hand and wheel were recorded with a marker-based 3D motion-capturing system. The measurements were performed at preferred speed under single- and dual-task conditions. The Paced Auditory Serial Addition Test (PASAT) was used for the additional cognitive task. The participants propelled with a significantly higher frequency (p = 0.001), had a shorter cycle- (p = 0.001) and recovery time (p = 0.001) and propelled with a lower push angle (p = 0.045) under dual-task conditions. The distance between the hand and the pushrim was shorter (p = 0.008) and the distance between the hand and the axis was significantly longer (p = 0.004). The differences occurred predominantly in the group of manual wheelchair users. Significant differences in propulsion behavior were also found between the two groups under both single-task and dual-task conditions. The results indicate that dual-task conditions during wheelchair propulsion have an influence on spatiotemporal parameters similar to walking. Future movement analyses of wheelchair users should therefore consider the additional measurement under dual-task conditions in order to obtain more realistic results.

Comparative SIR/SEIR modeling of the Antonine Plague in Rome

Some scholars consider the Antonine Plague to have been a major disease outbreak in the 2nd century CE that caused a significant decline in the population of the Roman Empire. Although there is currently no molecular evidence of the specific pathogen, literary evidence indicates the parameters of the disease that it caused and how significant the impact on Roman society was. One way to advance the current discussion concerning the Antonine Plague’s impact on the Roman Empire’s population is to examine the currently available sources and comparatively model the spread of different pathogens in a specific location with known demographic data for the relevant period. To accomplish this, we developed a series of dynamic ordinary differential equation models of the spread of disease in Rome between 165 and 189 CE for several pathogens. We found that daily disease deaths in the final years of the pandemic were inconsistent with estimates reported in primary sources, suggesting that either (a) the impact of the Antonine Plague may have been exaggerated in the descriptions of ancient authors, or (b) the daily deaths in ca. 189 CE were caused by a different disease event than the Antonine Plague, or (c) seasonality might have been a significant factor changing the intensity of disease spread, with the population more severely affected during the winter months. Although none of the pathogens we analyzed emerged as the likely causative agent of the Antonine Plague, the models show that the overall mortality rate would have increased maximally by 7%. This result contradicts the mortality rate accepted by historians who defend the thesis of the significant impact of this epidemic on the demography of the Roman Empire.

Author Correction: Lithocholic acid phenocopies anti-ageing effects of calorie restriction

Estimating an affine term structure model of interest rates with correlated noise

Kalman filtering for the affine term structure model of interest rates is typically applied under the assumption of white noise. However, correlated noise frequently occurs during actual data processing. The accuracy and reliability of the filter are compromised if the correlated noise is assumed to be white noise. This paper develops a measurement expansion scheme for the affine term structure model based on the whitening properties of the Kalman filter, enabling latent factor estimation under the general assumption of correlated noise. The simulation results indicate that the estimation based on the measurement expansion scheme achieves higher accuracy compared to the traditional method.

Author Correction: An RNA-dependent RNA polymerase formed by TERT and the RMRP RNA