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Comparison of intrinsic foot muscle function in patients with different lower extremity conditions
Background The intrinsic foot muscles (IFM), or foot core, provides stability to the foot skeleton. IFM dysfunction has been linked to foot and ankle injuries; however, the functional assessment of IFM in lower extremity conditions remains a clinical conundrum. We undertook a large study to understand the differences in muscle size and quality of IFM across a spectrum of conditions including Chronic Ankle Instability (CAI), Patellofemoral Pain (PFP), 1st Metatarsophalangeal Joint (1st MTPJ) arthrodesis and in patients with diabetes. This study compares IFM morphology and tissue quality in patients across these conditions and healthy control group individuals. Methods This study included 119 participants: 35 PFP, 29 CAI, 8 with 1st MTPJ arthrodesis, 9 with Diabetes, and 38 healthy controls. Ultrasound imaging (USI) assessed cross-sectional area (CSA) for muscle size and echogenicity for muscle quality in the Abductor Hallucis (AbH) and Flexor Digitorum Brevis (FDB). All size measures were normalized to body mass. Analysis of Coavariance (ANCOVA) was performed between groups, controlling for age and sex, to identify differences. Results Significant differences (P < 0.05) in the CSA of the AbH were found between all pathology groups and healthy control group, except for the 1st MTPJ group. CSA of FDB showed significant differences (P < 0.01) in all groups except the PFP and 1st MTPJ groups. For echogenicity, significant differences (P < 0.05) were found between groups for both AbH and FDB, while CAI, 1st MTPJ, and PFP groups showed higher FDB echogenicity. Large effect sizes were found for CSA and echogenicity in all groups except PFP. Conclusion This is the first study to our knowledge to collectively analyze multiple clinical groups with suspected IFM weakness in functional position for both muscle size and quality. Significant changes in muscle size and quality were observed, suggesting that clinicians should assess and target IFM rehabilitation to improve foot and ankle function in these populations.
The role of effective mass on semiconductor charge carrier localization as revealed by the split operator method
Charge carriers in a solid-state material are modeled as free particles with a variable “effective” mass that is derived from the curvature of the conduction/valence band. These effective masses of electrons and holes are unique to each material and are dependent on the internal band structure (e.g., heavy vs light holes). Quantum mechanical characterizations of nanomaterials employ effective mass theory using particle-in-a-box paradigms to calculate quantum confinement (i.e., localization) energies. However, semiconductor heterostructures, such as core/shell quantum dots, have spatially variant masses, and as a result, the Schrodinger equation must be solved via a numerical approach incorporating the Hermitian kinetic energy operator T̂∼∇m−1x∇. To this end, the split operator “spectral” method was modified with the variable mass kinetic energy operator to study a variety of core/shell quantum dots. The results reveal a preferential localization of charge carriers into regions of high effective mass, which has a non-negligible effect on structure/property relationships that are increasingly being used to guide the synthesis of semiconductor heterostructures, such as “giant” type II quantum dots.
Vaccine hesitancy and decision regret among nurses in oncology settings in Italy: a cluster-based profile analysis
A recipe for systems change: Predictive modeling and street-level bureaucracy among homeless services
Selective remodelling of the adipose niche in obesity and weight loss
Abstract Weight loss significantly improves metabolic and cardiovascular health in people with obesity1–3. The remodelling of adipose tissue (AT) is central to these varied and important clinical effects4. However, surprisingly little is known about the underlying mechanisms, presenting a barrier to treatment advances. Here we report a spatially resolved single-nucleus atlas (comprising 171,247 cells from 70 people) investigating the cell types, molecular events and regulatory factors that reshape human AT, and thus metabolic health, in obesity and therapeutic weight loss. We discover selective vulnerability to senescence in metabolic, precursor and vascular cells and reveal that senescence is potently reversed by weight loss. We define gene regulatory mechanisms and tissue signals that may drive a degenerative cycle of senescence, tissue injury and metabolic dysfunction. We find that weight loss reduces adipocyte hypertrophy and biomechanical constraint pathways, activating global metabolic flux and bioenergetic substrate cycles that may mediate systemic improvements in metabolic health. In the immune compartment, we demonstrate that weight loss represses obesity-induced macrophage infiltration but does not completely reverse activation, leaving these cells primed to trigger potential weight regain and worsen metabolic dysfunction. Throughout, we map cells to tissue niches to understand the collective determinants of tissue injury and recovery. Overall, our complementary single-nucleus and spatial datasets offer unprecedented insights into the basis of obese AT dysfunction and its reversal by weight loss and are a key resource for mechanistic and therapeutic exploration.
Discriminant analysis optimizes progress coordinate in weighted ensemble simulations of rare event kinetics
Calculating the kinetics of rare-but-important conformational transitions in complex biomolecules is a significant challenge in computational biophysics. Because of the long timescales needed to observe such processes, regular molecular dynamics simulations are too slow to sample these events by direct integration of the equations of motion. Recently, the weighted ensemble method has gained significant popularity for its ability to compute the rates of conformational transitions in biomolecular systems using unbiased simulations. However, the progress coordinate(s) of the weighted ensemble simulation should be carefully designed to capture the slow degrees of freedom of the system. Here, we demonstrate the application of a machine learning approach, harmonic linear discriminant analysis, which builds a predictive model for class membership, to design progress coordinates for weighted ensemble simulations. We test the accuracy and efficiency of this technique for computing the kinetics of the conformational transition of alanine dipeptide and the unfolding of a small protein. The key advantage of our data-driven approach is its minimal system knowledge requirement, which potentially extends its applicability to more complex and physiologically relevant systems.
The effect of age-related sensorimotor changes on step-down strategy: a predictive simulation study
Abstract Humans adjust neuromuscular control in anticipation of a step-down during walking. Due to age-related sensorimotor changes, older adults may require adaptation of this control to step-down safely. We used predictive simulations to investigate how muscle weakness and delayed neural transmission affect anticipatory control during step-down. Five model variants were developed: a default model, two with muscle strength reduced to 80% and 60%, and two with neural delays increased by 20% and 40%. For each model, we tested two strategies in the trailing leg during the last contact before step-down: reduced soleus activity (SOL strategy) and increased hamstring activity (HAM strategy). We systematically varied step-down height and anticipatory control levels. For the SOL strategy, both muscle weakness and neural delay reduced the maximum feasible step-down height, with muscle weakness requiring more precise adjustments. The HAM strategy was mainly affected by neural delay and showed less sensitivity to control precision. While the SOL strategy generally performed better, the HAM strategy was more robust under severe weakness. These results suggest that the HAM strategy may benefit individuals with progressive sensorimotor decline, while maintaining SOL strategy applicability—e.g., through strength training—could help maintain its benefits. Further investigations are needed to confirm this.
Olfactory dysfunction and amyloid-positivity in Parkinson’s disease—longitudinal analysis of cognitive decline and cerebrospinal fluid markers
Background Olfactory dysfunction is a common non-motor symptom in Parkinson’s disease (PD). The objective was to evaluate the association between olfaction in PD with cross-sectional and longitudinal assessments of clinical variables and novel cerebrospinal fluid (CSF) markers. Methods Patients with PD and baseline olfactory function assessed using the Brief Smell Identification Test (B-SIT) were included from the BioFINDER-1 cohort. Clinical variables, CSF measures and disease status were assessed longitudinally for up to 11 years. CSF was analyzed using Roche Elecsys® NeuroToolKit, including biomarkers of neurodegeneration, glial activation, neuroinflammation and the core Alzheimer disease biomarkers. Results A total of 172 patients with PD were included, 63 with normal olfactory function and 109 with hyposmia. No differences were seen in clinical variables at baseline. Glial fibrillary acidic protein was the only CSF marker differing at baseline, being elevated in hyposmic patients with PD (12.25 ± 3.87 vs 10.46 ± 3.68, p = 0.001). At follow-up, olfactory function declined predominantly in patients with normal olfaction at baseline (β = −0.25 [−0.40 to −0.12], p = 0.001). Patients with PD with both olfactory dysfunction and amyloid-positivity (defined by the CSF Aβ42/Aβ40 ratio) declined faster in several cognitive and motor measures. Olfaction and amyloid-status were independently associated with increased risk of progressing to dementia (B-SIT score, HR = 0.77 [0.67–0.88] and amyloid-positivity, HR = 4.47 [2.30–8.67]). Conclusions Olfactory dysfunction and amyloid-positivity are independently associated with a higher rate of cognitive decline and progression to dementia in patients with PD. Novel CSF markers of neurodegeneration and glial-activity do not differ depending on olfactory status in PD.
Simulation of coupled fluid–ion transport through a biological nanopore on graphics processing units
Nanoscale fluid–ion transport is investigated in biophysical chemistry, drug delivery, protein sequencing, etc. Currently, fast three-dimensional models for fluid–ion transport through biological nanopores are unavailable. This study, therefore, focuses on the simulation and parallelization of nanoscale fluid–ion transport on multiple graphics processing units (GPUs). Nanoscale fluid–ion transport is described through the fourth-order Poisson–Nernst–Planck–Bikerman model coupled with the Navier–Stokes equations. The model incorporates the effect of ionic and non-ionic interactions, ion solvation, nonlocal electrostatics, and the finite size of particles. Governing equations are discretized using the lattice Boltzmann method (LBM). For complex geometries, the immersed boundary method has been incorporated with the LBM. To demonstrate the applicability of the developed model, electro-osmotic flow through a relatively large biological nanopore has been simulated. Parallelization on multiple GPUs has enabled us to perform simulations for a full three-dimensional channel geometry. Results showed a good match with the published data. We captured local variations in concentration and fluid flow in both axial and radial directions. Furthermore, flow circulation around the channel was also observed. The impact of external potential difference and the finite size of the particles on the flow has also been assessed. Using our in-house code, we achieved a performance of 1982 × 106 lattice updates per second on 8 A100 80 gigabyte GPUs. The methodology presented here provides an accurate and fast simulation methodology for characterizing symmetric/asymmetric nanopore properties. This model can help in enhancing the fundamental understanding of nanofluidics and characterization of the nanopores.
Common garden experiments suggest terpene-mediated associations between phyllosphere microbes and Japanese cedar
Association of lifestyle and behavioral factors with self-reported visual problems among schoolchildren in rural Bangladesh
Background Lifestyle, environmental, and genetic factors influence visual impairment. The current study aims to report the sociodemographic, lifestyle, and behavioral factors associated with self-reported ocular conditions among children. Materials and methods Data were collected from 13341 children aged 7–14 from 176 primary schools and 16 madrasas (Islamic educational institutes) of Narail Upazila from 30 November 2022 to 20 August 2023. Data on sociodemographic factors, including living conditions and parents’ education; lifestyle and behavioral characteristics, including vitamin A consumption, watching TV or mobile; and self-reported ocular conditions, including seeing the blackboard or distant people, were collected. Chi-square tests and logistic regression analyses reported the association between sociodemographic characteristics with lifestyle and behavioral characteristics, and self-reported ocular conditions. The statistical software SPSS was used for data analysis. Results Of the total children, 52.5% were girls. Almost 99% had taken Vitamin A, 59% watched TV or mobile screens regularly, 99 (0.7%) children reported that they had problems seeing the blackboard or distant people, only 59 (0.4%) children had eye examinations previously, and 32 (0.2%) children used spectacles even if they had experienced any adverse ocular conditions. The proportion of children watching TV (67% vs. 58%) or mobile screens (69.6% vs. 57.6%) was higher in urban than rural areas. The proportion of children who had problems seeing blackboard was higher in urban areas (2.2% vs. 0.6) than in rural areas and among mothers with higher education (3.1% among graduate mothers vs. 0.3% among mothers without schooling). More than 99% of children had no eye examination before this screening program. Watching TV one-hour relative risk 4.16, (95% confidence interval (CI): 2.15–8.07 or more than one hour RR 5.33, 95% CI: 2.62–10.8 was associated with a higher proportion of seeing problems than those who did not watch TV. Those who used mobile for one hour, 4.82, (95% confidence interval (CI): 2.17–10.7 or more than one hour RR 7.30, 95% CI: 3.06–17.4 was associated with a higher proportion of reporting any ocular trauma than who did not use mobile phone. Conclusion Vitamin A taken among schoolchildren is very high, and self-reported ocular problems are minimal. Children living in urban areas are more prone to behavioral risk factors for visual impairment and have a higher proportion of ocular trauma. Increased awareness of vision impairment and its risk factors by schoolteachers can be a feasible and cost-effective approach to improving eye health in schoolchildren, especially in resource-poor setting.
Interaction strength of carbon dioxide on graphene from periodic quantum diffusion Monte Carlo
Despite the importance of graphene based carbon capture devices, an accurate estimate of the interaction strength of a carbon dioxide molecule with graphene from periodic calculations is lacking. In this work, we compute a fixed node quantum diffusion Monte Carlo reference value for the interaction energy of a carbon dioxide molecule with a periodic free-standing graphene sheet, obtaining a value of −152 ± 15 meV. In addition, we evaluate the performance of several widely used density functional theory approximations and foundation machine learning interatomic potentials, for both carbon dioxide and water adsorption on graphene, competitive processes that play an important role in carbon capture technologies. Among the approaches tested, the B86bPBE-XDM, PBE-D3, revPBE-D3, rev-vdW-DF2, SCAN+rVV10, and PBE0-D3-ATM functionals achieve the closest agreement with DMC for the carbon dioxide–graphene interaction. The vdW-DF2, rev-vdW-DF2, and PBE0-D4-ATM functionals perform better for the competitive adsorption of water and carbon dioxide.
Development and validation of a nomogram to predict failure of initial radioactive iodine therapy in differentiated thyroid cancer: a retrospective cohort study
Improvement in risk prediction for patients with atrial fibrillation and intermediate-risk CHA2DS2-VASc score utilizing highly sensitive cardiac troponin T
Background Guidelines of the European Society of Cardiology recommend a clinical risk assessment for patients with atrial fibrillation (AF). However, scores such as the CHA2DS2-VASc score show only a modest performance for prediction of adverse endpoints. Methods This retrospective single-center all-comer study uses data from the Heidelberg Registry of Atrial Fibrillation of 9,995 patients with non-valvular AF presenting to the emergency department (ED) of the University Hospital of Heidelberg from June 2009 until March 2020. Per CHA2DS2-VASc, risk was classified as low (0 point in men, ≤ 1 point in females), intermediate, or high (≥2 points in men and ≥3 points in females). The predictive performance of the CHA2DS2-VASc score, with and without highly sensitive cardiac troponin T (hs-cTnT), was evaluated for a composite endpoint comprising stroke, myocardial infarction (MI) or all-cause mortality. Results Performance of the CHA2DS2-VASc score for the prediction of the composite endpoint was poor Area under the curve (AUC): 0.648 (95%CI: 0.638–0.657) particularly in patients at intermediate-risk AUC: 0.542 (95%CI: 0.508–0.575). Adding hs-cTnT improved discrimination substantially in intermediate-risk patients (AUC: 0.778, 95% CI: 0.748–0.805). Notably, no events occurred in intermediate-risk patients with undetectable hs-cTnT (<5 ng/L). Conclusion In patients with AF at intermediate thromboembolic risk, the addition of hs-cTnT to the CHA₂DS₂-VASc score enhances prediction of adverse cardiovascular outcomes. Hs-cTnT may help identify patients who could benefit from anticoagulation, while also identifying a low-risk subgroup unlikely to experience events.
Taylor-mode automatic differentiation for constructing molecular rovibrational Hamiltonian operators
We present an automated framework for constructing Taylor series expansions of rovibrational kinetic and potential energy operators for arbitrary molecules, internal coordinate systems, and molecular frame embedding conditions. Expressing operators in a sum-of-products form allows for computationally efficient evaluations of matrix elements in product basis sets. Our approach uses automatic differentiation tools from the Python machine learning ecosystem, particularly the JAX library, to efficiently and accurately generate high-order Taylor expansions of rovibrational operators. The implementation is available at https://github.com/robochimps/vibrojet.
miRNA biomarkers for prognosis and therapy monitoring in a multi-ethnic cohort with SARS-CoV-2 infection
HEroBM: A deep equivariant graph neural network for high-fidelity backmapping from coarse-grained to all-atom structures
Molecular simulations play a pivotal role in chemistry, biology, and material sciences, enabling the study of complex dynamic properties within systems. Coarse-grained (CG) techniques have emerged as indispensable tools in this domain, facilitating the sampling of large-scale systems and extending simulation timescales by simplifying system representation. However, CG approaches involve a trade-off: they sacrifice atomistic details that may be crucial for understanding the underlying processes. To address this challenge, a recommended strategy is to identify key CG conformations and employ backmapping methods to retrieve atomistic coordinates. Currently, rule-based methods often yield suboptimal geometries and rely on energy relaxation, resulting in less-than-optimal outcomes. In contrast, machine learning techniques offer higher accuracy but may lack transferability between systems or be tied to specific CG mappings. In this study, we present HEroBM, a dynamic and scalable method that utilizes deep equivariant graph neural networks and a hierarchical approach to achieve high-resolution backmapping. HEroBM is capable of handling any type of CG mapping, providing a versatile and efficient protocol for reconstructing atomistic structures with high accuracy. Grounded in local principles, HEroBM spans the entire chemical space and can be applied across systems of varying composition and sizes. We demonstrate the versatility of our framework through a range of biological systems, including a complex real-case scenario. Here, our end-to-end backmapping approach accurately generates atomistic coordinates for a G protein-coupled receptor bound to an organic small molecule within a cholesterol/phospholipid bilayer. The high-fidelity HEroBM backmapping enables researchers to effortlessly transition between CG and all-atom simulations, opening unprecedented avenues for molecular investigations.
Practical implementation of m-Plane GaN resonant-phonon Terahertz quantum cascade laser
Minimized reaction network method for the construction of combustion reaction mechanism: NH3/DME mixed combustion
In view of the shortcomings of the previous NH3/DME reaction mechanism, combustion reaction mechanisms of NH3, DME, and NH3/DME were constructed by using the minimized reaction network method under the condition of determining the number of chemical species. The mechanism of the construction had a simple reaction network using reversible reaction form, and the reaction direction was unified in form. The mechanism construction process of NH3, DME, and NH3/DME avoided the mechanism simplification step, which can greatly reduce the number of species and reactions. Finally, the NH3 chemical reaction mechanism containing 18 species and 43 reactions, the DME chemical reaction mechanism containing 34 species and 51 reactions, and the NH3/DME chemical reaction mechanism containing 44 species and 93 reactions were developed. The laminar burning velocity and ignition delay time of NH3, NH3/H2, DME, DME/H2, and NH3/DME combustion under a wide range of initial conditions were validated. The results showed that the errors of laminar burning velocity and ignition delay time compared with the experimental values were within 10% under most initial conditions, which verifies the reliability and practicability of each combustion reaction mechanism.