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Health Care Delivery and Financial Considerations in Amyotrophic Lateral Sclerosis Clinics: A Survey of Clinic Directors.

Neurology

February 2025

From the Temple University College of Public Health (I.L.H.); Thomas Jefferson University (G.G.); and Department of Neurology (T.D.H.-P.), Lewis Katz School of Medicine at Temple University, Philadelphia, PA.

Background And Objectives: Clinical care for people living with amyotrophic lateral sclerosis (PLWALS) is directed at slowing disease progression and symptom management. The American Academy of Neurology recommends a multidisciplinary approach to providing ALS health care because observational studies show that multidisciplinary clinics (MDCs) extend survival and improve quality of life. However, providing multidisciplinary care is a challenging financial proposition.

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The impact of cognitive decline in older adults can be evaluated with dual-task gait (DTG) testing in which a cognitive task is performed during walking, leading to increased costs of gait. Previous research demonstrated that higher DTG costs correlate with increasing cognitive deficits and with age. The present study was conducted to explore whether the relationship between the DTG costs and cognitive abilities in older individuals is influenced by sex differences.

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Background: Sensitive diagnostic tools that signal lymphatic filariasis (LF) transmission are needed to monitor the progress of LF elimination programs. Anti-filarial antibody (Ab) markers could be more sensitive than antigen (Ag) point-of-care tests for monitoring LF transmission in some settings. This study aimed to investigate the sensitivity of anti-filarial Abs for detecting signals of LF transmission in Samoa by i) investigating the sensitivity and specificity of Ab to identify Ag-positives; ii) estimating the average number needed to test (NNTestav) to identify LF-seropositives (seropositive for Ag and/or any Ab), and iii) compare the efficiency of the different serological indicators by target age group and sampling design.

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ISLRWR: A network diffusion algorithm for drug-target interactions prediction.

PLoS One

January 2025

Shanghai Xinhao Information Technology Co., Ltd., Shanghai, China.

Machine learning techniques and computer-aided methods are now widely used in the pre-discovery tasks of drug discovery, effectively improving the efficiency of drug development and reducing the workload and cost. In this study, we used multi-source heterogeneous network information to build a network model, learn the network topology through multiple network diffusion algorithms, and obtain compressed low-dimensional feature vectors for predicting drug-target interactions (DTIs). We applied the metropolis-hasting random walk (MHRW) algorithm to improve the performance of the random walk with restart (RWR) algorithm, forming the basis by which the self-loop probability of the current node is removed.

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Article Synopsis
  • The study investigates the temperature sensitivity of runways in permafrost regions and proposes a parallel perforated ventilation subgrade to improve cooling.
  • The finite element model used was validated against previous research, demonstrating the cooling effectiveness of the new subgrade design.
  • Results indicate significant cooling effects on pavement temperatures over time, while air velocity and working time primarily impact the crushed rock layer and subgrade temperature rather than the surface layer.
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