Nevin Manimala

J Psychosoc Nurs Ment Health Serv. 2024 Jul;62(7):11-15. doi: 10.3928/02793695-20240620-01. Epub 2024 Jul 1.

ABSTRACT

The mental health needs of Asian American older adults are complex and multifaceted. Despite their rich diversity, Asian American older adults face significant challenges, including mental health stigma, cultural stress, limited English proficiency, and historical trauma. In addition, the coronavirus disease 2019 pandemic reignited preexisting anti-Asian attitudes of hostility, discrimination, blame, and scapegoating. The historical context of Asian immigration to the United States, impact of race-based discrimination, and recent resurgence of anti-Asian hate crimes impact mental health in Asian American older adults. Thus, there is a need for a culturally sensitive and competent mental health care workforce, culturally tailored interventions, and family involvement. In the context of research and policy, it is critical to prioritize increased funding and research focus on culturally tailored instrument development, interventions, and policy initiatives informed by recent findings to safeguard this population from hate crimes and discrimination. [Journal of Psychosocial Nursing and Mental Health Services, 62(7), 11-15.].

PMID:38976856 | DOI:10.3928/02793695-20240620-01

Orthopedics. 2024 Jul 10:1-5. doi: 10.3928/01477447-20240702-02. Online ahead of print.

ABSTRACT

BACKGROUND: Displaced diaphyseal fractures can be reduced using the push-pull technique, wherein a plate is affixed to the distal fragment of the fracture, a post screw is placed proximal to the plate, and a lamina spreader creates distraction. This study evaluated the load to failure and mechanism of failure of bicortical and unicortical post screws during reduction.

MATERIALS AND METHODS: Four matched pairs of cadaver legs were subjected to a 2-cm oblique osteotomy simulating a displaced, oblique diaphyseal fracture. A 6-hole compression plate was affixed to the distal fragment with 2 unicortical locking screws, and a 12-mm uni-cortical or 20-mm bicortical screw was inserted as a post screw proximal to the plate. A lamina bone spreader was used to exert a distraction force between the plate and the post screw. A mechanical actuator simulated the distraction procedure until failure. Maximum applied load, displacement, and absorbed energy were recorded and compared across unicortical and bicortical groups by paired t tests.

RESULTS: At maximum load, we found statistically significant differences in displacement (P=.003) and energy absorbed (P=.022) between the two groups. All unicortical screws failed through screw toggle and bone cut-out. Bicortical screws failed through bending, with no visible damage to the bone at the screw site.

CONCLUSION: When diaphyseal fractures are significantly shortened and require a greater distraction force to achieve reduction, bicortical screws demonstrate a higher mechanical load to failure and increased bone loss from the screw-removal site. A unicortical post screw may be used if minimal distraction is needed. [Orthopedics. 202x;4x(x):xx-xx.].

PMID:38976846 | DOI:10.3928/01477447-20240702-02

JCO Precis Oncol. 2024 Jun;8:e2300718. doi: 10.1200/PO.23.00718.

ABSTRACT

PURPOSE: To use modern machine learning approaches to enhance and automate the feature extraction from the longitudinal circulating tumor DNA (ctDNA) data and to improve the prediction of survival and disease progression, risk stratification, and treatment strategies for patients with 1L non-small cell lung cancer (NSCLC).

MATERIALS AND METHODS: Using IMpower150 trial data on patients with untreated metastatic NSCLC treated with atezolizumab and chemotherapies, we developed a machine learning algorithm to extract predictive features from ctDNA kinetics, improving survival and progression prediction. We analyzed kinetic data from 17 ctDNA summary markers, including cell-free DNA concentration, allele frequency, tumor molecules in plasma, and mutation counts.

RESULTS: Three hundred and ninety-eight patients with ctDNA data (206 in training and 192 in validation) were analyzed. Our models outperformed existing workflow using conventional temporal ctDNA features, raising overall survival (OS) concordance index to 0.72 and 0.71 from 0.67 and 0.63 for C3D1 and C4D1, respectively, and substantially improving progression-free survival (PFS) to approximately 0.65 from the previous 0.54-0.58, a 12%-20% increase. Additionally, they enhanced risk stratification for patients with NSCLC, achieving clear OS and PFS separation. Distinct patterns of ctDNA kinetic characteristics (eg, baseline ctDNA markers, depth of ctDNA responses, and timing of ctDNA clearance, etc) were revealed across the risk groups. Rapid and complete ctDNA clearance appears essential for long-term clinical benefit.

CONCLUSION: Our machine learning approach offers a novel tool for analyzing ctDNA kinetics, extracting critical features from longitudinal data, improving our understanding of the link between ctDNA kinetics and progression/mortality risks, and optimizing personalized immunotherapies for 1L NSCLC.

PMID:38976829 | DOI:10.1200/PO.23.00718

J Chem Theory Comput. 2024 Jul 8. doi: 10.1021/acs.jctc.4c00514. Online ahead of print.

ABSTRACT

Alchemical free energy methods are useful in computer-aided drug design and computational protein design because they provide rigorous statistical mechanics-based estimates of free energy differences from molecular dynamics simulations. λ dynamics is a free energy method with the ability to characterize combinatorial chemical spaces spanning thousands of related systems within a single simulation, which gives it a distinct advantage over other alchemical free energy methods that are mostly limited to pairwise comparisons. Recently developed methods have improved the scalability of λ dynamics to perturbations at many sites; however, the size of chemical space that can be explored at each individual site has previously been limited to fewer than ten substituents. As the number of substituents increases, the volume of alchemical space corresponding to nonphysical alchemical intermediates grows exponentially relative to the size corresponding to the physical states of interest. Beyond nine substituents, λ dynamics simulations become lost in an alchemical morass of intermediate states. In this work, we introduce new biasing potentials that circumvent excessive sampling of intermediate states by favoring sampling of physical end points relative to alchemical intermediates. Additionally, we present a more scalable adaptive landscape flattening algorithm for these larger alchemical spaces. Finally, we show that this potential enables more efficient sampling in both protein and drug design test systems with up to 24 substituents per site, enabling, for the first time, simultaneous simulation of all 20 amino acids.

PMID:38976796 | DOI:10.1021/acs.jctc.4c00514

J Healthc Manag. 2024 Jul-Aug 01;69(4):280-295. doi: 10.1097/JHM-D-23-00137. Epub 2024 Jul 4.

ABSTRACT

GOAL: We sought to build upon previous studies that have demonstrated how healthcare workers’ ratings of their immediate supervisor’s leadership capabilities relate to their well-being and job satisfaction.

METHODS: In 2022, we analyzed cross-sectional data from 1,780 physicians and 39,896 allied health professionals (collected in 2017) and 729 residents (collected in 2019), as well as longitudinal data from 1,632 physicians (collected from 2015 to 2017), to identify a psychometrically strong, broadly applicable, actionable, and low-burden approach to assessing supervisor leadership capability to support healthcare worker well-being.

PRINCIPAL FINDINGS: The magnitude of association between our 1-, 2-, 3-, and 9-item leadership indexes and burnout, and between our 1-, 2-, 3-, and 9-item leadership indexes and satisfaction with the organization were similar to each other in the cross-sectional and longitudinal cohorts and across diverse groups of healthcare workers, including physicians, residents, and allied health professionals. The likelihood ratio for a high leadership score increased with an increasing score for each leadership measure. The area under the receiver operating characteristic curve for the 1-, 2-, and 3-item measures for a high leadership score was 0.9349, 0.9672, and 0.9819, respectively.

PRACTICAL APPLICATIONS: A single item assessing perceptions of leadership capability efficiently provides useful information about leadership qualities of healthcare workers’ immediate supervisors. The inclusion of this item in healthcare worker surveys may be useful for evaluating interventions and galvanizing organizational action to support healthcare worker well-being.

PMID:38976788 | DOI:10.1097/JHM-D-23-00137

PLoS Comput Biol. 2024 Jul 8;20(7):e1012287. doi: 10.1371/journal.pcbi.1012287. Online ahead of print.

ABSTRACT

Identifying the association and corresponding types of miRNAs and diseases is crucial for studying the molecular mechanisms of disease-related miRNAs. Compared to traditional biological experiments, computational models can not only save time and reduce costs, but also discover potential associations on a large scale. Although some computational models based on tensor decomposition have been proposed, these models usually require manual specification of numerous hyperparameters, leading to a decrease in computational efficiency and generalization ability. Additionally, these linear models struggle to analyze complex, higher-order nonlinear relationships. Based on this, we propose a novel framework, KBLTDARD, to identify potential multiple types of miRNA-disease associations. Firstly, KBLTDARD extracts information from biological networks and high-order association network, and then fuses them to obtain more precise similarities of miRNAs (diseases). Secondly, we combine logistic tensor decomposition and Bayesian methods to achieve automatic hyperparameter search by introducing sparse-induced priors of multiple latent variables, and incorporate auxiliary information to improve prediction capabilities. Finally, an efficient deterministic Bayesian inference algorithm is developed to ensure computational efficiency. Experimental results on two benchmark datasets show that KBLTDARD has better Top-1 precision, Top-1 recall, and Top-1 F1 for new type predictions, and higher AUPR, AUC, and F1 values for new triplet predictions, compared to other state-of-the-art methods. Furthermore, case studies demonstrate the efficiency of KBLTDARD in predicting multiple types of miRNA-disease associations.

PMID:38976761 | DOI:10.1371/journal.pcbi.1012287

Gynecol Endocrinol. 2024 Dec;40(1):2375568. doi: 10.1080/09513590.2024.2375568. Epub 2024 Jul 8.

ABSTRACT

BACKGROUND: Iron metabolism plays a significant role in the development of metabolic disorders in women with polycystic ovary syndrome (PCOS). Despite the importance of hepcidin, a key iron regulator, current research on serum hepcidin levels in PCOS patients shows conflicting results.

METHODS: PubMed, Embase, Web of Science, Cochrane Library and the China National Knowledge Infrastructure (CNKI) database were systematically searched from their inception to 9 September 2023. The search aimed to identify studies in English and Chinese that examined hepcidin levels in women with PCOS compared to healthy control subjects. Standardized mean differences (SMDs) with corresponding 95% confidence intervals (95% CIs) were calculated to evaluate the difference in serum hepcidin levels between women with and without PCOS.

RESULTS: The meta-analysis included a total of 10 eligible studies, which encompassed 499 PCOS patients and 391 control subjects. The pooled analysis revealed a significant reduction in serum hepcidin levels among the PCOS patients compared to the healthy controls (SMD = -3.49, 95% CI: -4.68 to -2.30, p < .05). There was no statistically significant difference in serum hepcidin levels between PCOS patients with a body mass index (BMI) < 25 and those with a BMI ≥ 25 (p > .05).

CONCLUSION: The serum hepcidin levels of women with PCOS were significantly lower than those of healthy controls, which suggests that serum hepcidin could be a potential biomarker for PCOS.

PMID:38976752 | DOI:10.1080/09513590.2024.2375568

PLoS Comput Biol. 2024 Jul 8;20(7):e1011620. doi: 10.1371/journal.pcbi.1011620. Online ahead of print.

ABSTRACT

Boolean networks are largely employed to model the qualitative dynamics of cell fate processes by describing the change of binary activation states of genes and transcription factors with time. Being able to bridge such qualitative states with quantitative measurements of gene expressions in cells, as scRNA-seq, is a cornerstone for data-driven model construction and validation. On one hand, scRNA-seq binarisation is a key step for inferring and validating Boolean models. On the other hand, the generation of synthetic scRNA-seq data from baseline Boolean models provides an important asset to benchmark inference methods. However, linking characteristics of scRNA-seq datasets, including dropout events, with Boolean states is a challenging task. We present scBoolSeq, a method for the bidirectional linking of scRNA-seq data and Boolean activation state of genes. Given a reference scRNA-seq dataset, scBoolSeq computes statistical criteria to classify the empirical gene pseudocount distributions as either unimodal, bimodal, or zero-inflated, and fit a probabilistic model of dropouts, with gene-dependent parameters. From these learnt distributions, scBoolSeq can perform both binarisation of scRNA-seq datasets, and generate synthetic scRNA-seq datasets from Boolean traces, as issued from Boolean networks, using biased sampling and dropout simulation. We present a case study demonstrating the application of scBoolSeq’s binarisation scheme in data-driven model inference. Furthermore, we compare synthetic scRNA-seq data generated by scBoolSeq with BoolODE’s, data for the same Boolean Network model. The comparison shows that our method better reproduces the statistics of real scRNA-seq datasets, such as the mean-variance and mean-dropout relationships while exhibiting clearly defined trajectories in two-dimensional projections of the data.

PMID:38976751 | DOI:10.1371/journal.pcbi.1011620

Proc Natl Acad Sci U S A. 2024 Jul 16;121(29):e2409344121. doi: 10.1073/pnas.2409344121. Epub 2024 Jul 8.

NO ABSTRACT

PMID:38976742 | DOI:10.1073/pnas.2409344121

PLoS Negl Trop Dis. 2024 Jul 8;18(7):e0011942. doi: 10.1371/journal.pntd.0011942. Online ahead of print.

ABSTRACT

The World Health Organization (WHO) endorsed the use of triple-drug mass drug administration (MDA) regimen with ivermectin, diethylcarbamazine (DEC) and albendazole (commonly abbreviated as IDA) to accelerate the elimination of lymphatic filariasis (LF) as a public health problem in settings where onchocerciasis is not co-endemic. The National Programme for Elimination of LF (NPELF) in Kenya was among the first adopters of the IDA-MDA and two annual rounds were provided in 2018 and 2019 to the residents of Lamu County and Jomvu sub-County in the coast region. This study documented the feasibility of successfully delivering the two rounds of IDA-MDA. An operational research study was undertaken to determine efficient sampling strategies, indicators, and the appropriate population groups that could be used for the monitoring and evaluation of LF programs using IDA-MDA for the elimination of the disease as a public health problem. Two cross-sectional surveys were conducted at baseline in 2018 before IDA-MDA and an impact assessment 17 months after the second round of IDA-MDA. The reported epidemiological treatment coverage was at least 80% in all implementation units during each round of IDA-MDA. Blood samples were tested for filarial antigenemia using commercial Filariasis Test Strips (FTS) and any individual found to be positive was tested again at night for the presence of microfilariae in finger prick blood smears using microscopy. The overall prevalence of circulating filarial antigen (CFA) was relatively low at the baseline survey with Jomvu having 1.39% (95% CI: 0.91, 2.11) and Lamu having 0.48% (95% CI: 0.21, 1.13). Significant reduction in CFA prevalence was observed during the impact assessment after two annual rounds of treatment. The overall relative reduction (%) in CFA prevalence following the two rounds of MDA with IDA was significant in both Jomvu (52.45%, Z = -2.46, P < 0.02) and Lamu (52.71%, Z = -1.97, P < 0.05). Heterogeneity, however, was observed in the CFA prevalence reduction between random and purposive clusters, as well as between adult and child populations. The results of the impact assessment survey offered strong evidence that it was safe to stop the IDA-MDA in the two EUs because transmission appears to have been interrupted. It is also important to implement a post-treatment surveillance system which would enable efficient detection of any recrudescence of LF transmission at a sub-evaluation unit level. Our findings show that IDA-MDA may be considered for acceleration of LF elimination in other settings where onchocerciasis is not co-endemic.

PMID:38976718 | DOI:10.1371/journal.pntd.0011942