Category: Nevin Manimala

Mov Ecol. 2024 Dec 3;12(1):75. doi: 10.1186/s40462-024-00519-0.

ABSTRACT

BACKGROUND: Wildfires can have complex effects on wildlife populations. Understanding how post-fire conditions affect the movement ecology of threatened species can assist in better conservation and management, including informing the release of rescued and rehabilitated animals. The 2019-2020 megafires in Australia resulted in thousands of animals coming into care due to injury or concerns over habitat degradation. This included hundreds of koalas (Phascolarctos cinereus), for which relatively little was known about how fire affected habitat suitability, or when rehabilitated animals could be returned to burnt areas.

METHODS: We compared the movements of koalas across three experimental groups-non-rehabilitated koalas in burnt habitat, non-rehabilitated koalas in nearby unburnt habitat, and rehabilitated koalas returned to their rescue location in burnt habitat in New South Wales, Australia. We GPS-tracked 32 koalas for up to nine months and compared, across treatment groups, home ranges, mean nightly distance moved, the farthest distance moved from their release site and total displacement distance.

RESULTS: We found no differences in koala movements and home range size between non-rehabilitated koalas in burnt and unburnt habitat. However, rehabilitated koalas moved farther from their release site, had larger displacement distances, and larger home ranges than non-rehabilitated individuals. Regardless of their experimental group, we also found that males moved further than females each night. Additionally, our resource selection analysis showed that, koalas preferred low and moderately burnt habitats over all other fire severity classes.

CONCLUSIONS: Experimental frameworks that incorporate “treatment” and “control” groups can help isolate disturbance effects on animal movements. Encouragingly, despite catastrophic wildfires, burnt woodlands provided adequate resources for koalas to persist and recover. Furthermore, rehabilitated koalas re-integrated into the burnt landscape despite moving farther from their release sites than non-rehabilitated individuals. Studies like this improve our understanding of the ecological impacts of fire on species and their habitats, and will be instrumental in informing wildlife management and conservation efforts as wildfires increase in frequency and severity worldwide in response to climate change.

PMID:39627876 | DOI:10.1186/s40462-024-00519-0

Mol Autism. 2024 Dec 3;15(1):51. doi: 10.1186/s13229-024-00630-4.

ABSTRACT

BACKGROUND: Very large sample sizes are often needed to capture heterogeneity in autism, necessitating data sharing across multiple studies with diverse assessment instruments. In these cases, data harmonization can be a critical tool for deriving a single dataset for analysis. This can be done through computational approaches that enable the conversion of scores across various instruments. To this end, our study examined the use of analytical approaches for mapping scores on two measures of adaptive functioning, namely predicting the scores on the vineland adaptive behavior scales II (VABS) from the scores on the adaptive behavior assessment system II (ABAS).

METHODS: Data from the province of Ontario neurodevelopmental disorders network were used. The dataset included scores VABS and the ABAS for 720 participants (autism n = 547, 433 male, age: 11.31 ± 3.63 years; neurotypical n = 173, 95 male, age: 12.53 ± 4.05 years). Six regression approaches (ordinary least squares (OLS) linear regression, ridge regression, ElasticNet, LASSO, AdaBoost, random forest) were used to predict VABS total scores from the ABAS scores, demographic variables (age, sex), and phenotypic measures (diagnosis; core and co-occurring features; IQ; internalizing and externalizing symptoms).

RESULTS: The VABS scores were significantly higher than the ABAS scores in the autism group, but not the neurotypical group (median difference: 8, 95% CI = (7,9)). The difference was negatively associated with age (beta = -1.2 ± 0.12, t = -10.6, p < 0.0001). All estimators demonstrated similar performance, with no statistically significant differences in mean absolute error (MAE) values across estimators (MAE range: 4.96-6.91). The highest contributing features to the prediction model were ABAS composite score, diagnosis, and age.

LIMITATIONS: This study has several strengths, including the large sample. We did not examine the conversion of domain scores across the two measures of adaptive functioning and suggest this as a future area of investigation.

CONCLUSION: Overall, our results supported the feasibility of harmonization. Our results suggest that a linear regression model trained on the ABAS composite score, the ABAS raw domain scores, and age, sex, and diagnosis would provide an acceptable trade-off between accuracy, parsimony, and data collection and processing complexity.

PMID:39627866 | DOI:10.1186/s13229-024-00630-4

Genome Med. 2024 Dec 3;16(1):143. doi: 10.1186/s13073-024-01392-7.

ABSTRACT

BACKGROUND: Multiplexed Assays of Variant Effects (MAVEs) can test all possible single variants in a gene of interest. The resulting saturation-style functional data may help resolve variant classification disparities between populations, especially for Variants of Uncertain Significance (VUS).

METHODS: We analyzed clinical significance classifications in 213,663 individuals of European-like genetic ancestry versus 206,975 individuals of non-European-like genetic ancestry from All of Us and the Genome Aggregation Database. Then, we incorporated clinically calibrated MAVE data into the Clinical Genome Resource’s Variant Curation Expert Panel rules to automate VUS reclassification for BRCA1, TP53, and PTEN.

RESULTS: Using two orthogonal statistical approaches, we show a higher prevalence (p ≤ 5.95e – 06) of VUS in individuals of non-European-like genetic ancestry across all medical specialties assessed in all three databases. Further, in the non-European-like genetic ancestry group, higher rates of Benign or Likely Benign and variants with no clinical designation (p ≤ 2.5e – 05) were found across many medical specialties, whereas Pathogenic or Likely Pathogenic assignments were increased in individuals of European-like genetic ancestry (p ≤ 2.5e – 05). Using MAVE data, we reclassified VUS in individuals of non-European-like genetic ancestry at a significantly higher rate in comparison to reclassified VUS from European-like genetic ancestry (p = 9.1e – 03) effectively compensating for the VUS disparity. Further, essential code analysis showed equitable impact of MAVE evidence codes but inequitable impact of allele frequency (p = 7.47e – 06) and computational predictor (p = 6.92e – 05) evidence codes for individuals of non-European-like genetic ancestry.

CONCLUSIONS: Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.

PMID:39627863 | DOI:10.1186/s13073-024-01392-7

J Cheminform. 2024 Dec 3;16(1):135. doi: 10.1186/s13321-024-00932-y.

ABSTRACT

Extended-connectivity fingerprints (ECFPs) are a ubiquitous tool in current cheminformatics and molecular machine learning, and one of the most prevalent molecular feature extraction techniques used for chemical prediction. Atom features learned by graph neural networks can be aggregated to compound-level representations using a large spectrum of graph pooling methods. In contrast, sets of detected ECFP substructures are by default transformed into bit vectors using only a simple hash-based folding procedure. We introduce a general mathematical framework for the vectorisation of structural fingerprints via a formal operation called substructure pooling that encompasses hash-based folding, algorithmic substructure selection, and a wide variety of other potential techniques. We go on to describe Sort & Slice, an easy-to-implement and bit-collision-free alternative to hash-based folding for the pooling of ECFP substructures. Sort & Slice first sorts ECFP substructures according to their relative prevalence in a given set of training compounds and then slices away all but the L most frequent substructures which are subsequently used to generate a binary fingerprint of desired length, L. We computationally compare the performance of hash-based folding, Sort & Slice, and two advanced supervised substructure-selection schemes (filtering and mutual-information maximisation) for ECFP-based molecular property prediction. Our results indicate that, despite its technical simplicity, Sort & Slice robustly (and at times substantially) outperforms traditional hash-based folding as well as the other investigated substructure-pooling methods across distinct prediction tasks, data splitting techniques, machine-learning models and ECFP hyperparameters. We thus recommend that Sort & Slice canonically replace hash-based folding as the default substructure-pooling technique to vectorise ECFPs for supervised molecular machine learning. Scientific contribution A general mathematical framework for the vectorisation of structural fingerprints called substructure pooling; and the technical description and computational evaluation of Sort & Slice, a conceptually simple and bit-collision-free method for the pooling of ECFP substructures that robustly and markedly outperforms classical hash-based folding at molecular property prediction.

PMID:39627861 | DOI:10.1186/s13321-024-00932-y

BMC Health Serv Res. 2024 Dec 3;24(1):1533. doi: 10.1186/s12913-024-12014-8.

ABSTRACT

BACKGROUND: There are more than 4 million breast cancer survivors in the United States. With continuing improvements in early detection and treatment, the number of breast cancer survivors will only continue to increase. Breast cancer survivors face a lifetime risk of long-term or late-effects from cancer treatments, thus post-cancer treatment care, referred to as survivorship care, is critical. Social determinants of health, including where a breast cancer survivor lives, may impact cancer survivorship care. Our purpose was to evaluate the relationship between rural/urban status and receipt of cancer survivorship care and instructions for Missouri breast cancer survivors using state-level data from a nationwide telephone survey-the Behavioral Risk Factor Surveillance System (BRFSS).

METHODS: Missouri included the BRFSS Cancer Survivorship Module in 2014, 2016, 2018, and 2020. Module items ask cancer survivors about receipt of a “post-cancer-treatment summary” and “follow-up instructions.” We hypothesized chances of receipt of both components would differ among four level Rural-Urban Commuting Area (RUCA) Code groups (Rural, Small-Town, Micropolitan, Metropolitan). Data from 430 breast cancer survivors over four survey years were combined and grouped according to RUCA status. Using a logistic model with a multilevel approach (after sampling weights calibration), the relationship between receipt of survivorship instructions and RUCA group was examined.

RESULTS: 46% of Missouri breast cancer survivors reported receipt of complete survivorship instructions. Compared to rural breast cancer survivors, micropolitan breast cancer survivors had 5.9 times higher odds of receiving survivorship instructions (p < 0.0001).

CONCLUSIONS: Less than half of respondents reported receiving complete post-cancer treatment instructions. More urban respondents were more likely to receive instructions than their rural counterparts which raises questions about the quality of post-treatment care between rural and urban survivors. A sophisticated and purposeful approach to mitigating potential disparities is warranted. Receipt of cancer survivorship care plans may be impacted by rurality/urbanicity. Clinicians caring for cancer survivors living in rural or urban settings must continue to be diligent with providing personalized survivorship care.

PMID:39627855 | DOI:10.1186/s12913-024-12014-8

BMC Nurs. 2024 Dec 3;23(1):880. doi: 10.1186/s12912-024-02535-2.

ABSTRACT

OBJECTIVE: To develop an empathy scale to measure the empathy in nurses.

MATERIALS AND METHODS: The sample of the study were collected between March and May in 2023 from 720 nurses working in private and state hospitals in İstanbul. Both exploratory factor analysis and confirmatory factor analysis were carried out. IBM SPSS and AMOS were utilized for statistical analyses.

RESULTS: KMO and Bartlett’s test values of scale showed that the dataset was convenient for factor analyses (KMO = 0.94, Chi-Square = 9683.89, df = 595). In exploratory factor analysis, the 16 items comprising scale were distributed in three subscales. The confirmatory factor analysis revealed that the scale was in sufficient model fit. Cronbach’s alpha of the total scale was 0.91.

CONCLUSION: Empathy scale is a valid and reliable measurement tool to evaluate the empathy levels of nurses in three subscales: Emotional Empathy, Cognitive Empathy and Compassionate Empathy. The scale is a valuable tool for quality nursing care and contributes to the definition of strategies that advance the quality of nursing care.

PMID:39627839 | DOI:10.1186/s12912-024-02535-2

Trials. 2024 Dec 4;25(1):809. doi: 10.1186/s13063-024-08651-3.

ABSTRACT

BACKGROUND: The number of non-inferiority (NI) trials, those aiming to show a new treatment is no worse than a comparator, is increasing. However, their added complexity over superiority trials can create confusion. Most guidance and reviews to date have an industry focus with research suggesting these trials may differ from publicly funded NI trials. The aim of this work is to review the design and reporting characteristics of UK publicly funded NI trials. This assessment will show how well recommendations from industry are translating to publicly funded trials.

METHODS: The International Standard Randomised Controlled Trial Number web registry and the National Institute for Health and Care Research’s Funding and Awards Library and Journals Library were searched using the term non-inferiority and logical synonyms. Inclusion requirements were a UK publicly funded NI randomised controlled trial. Characteristics of the design, analyses and results as available were recorded on a dedicated data extraction spreadsheet. Appropriate summary statistics were used to present the results.

RESULTS: Searches completed on the 14th of January 2022 identified 477 potential trials which after exclusions resulted in a database of 114 NI trials to be summarised. Non-inferiority margins were defined for most trials with a median of 8% (IQR: 3-10%) used for risk differences (n = 58) and 0.35 (IQR: 0.26-0.43) standardised mean difference for continuous outcomes (n = 30). Justifications for the margin chosen (n = 62) were more commonly based on the clinical importance (49/62) and less commonly using statistical considerations (13/62). The most prevalent primary analysis population was solely on an intention-to-treat basis (49/114). The superiority of the treatment was well described but not always included as an outcome and only powered for in about a third of cases.

CONCLUSIONS: Aspects of NI trial design are well described but not always in line with current recommendations. Of particular note, is the absence of statistical considerations when setting the non-inferiority margin, which eliminates the ability to confirm indirect superiority over placebo for the new treatment. Additionally, despite suggestions that it can increase the type 1 error in NI trials, the use of the intention-to-treat alone is the most common analysis population.

TRIAL REGISTRATION: Research on Research ID: 3171 (registration date: 31st May 2023).

PMID:39627838 | DOI:10.1186/s13063-024-08651-3

BMC Health Serv Res. 2024 Dec 3;24(1):1534. doi: 10.1186/s12913-024-12025-5.

ABSTRACT

BACKGROUND: Healthcare transformation is a multifaceted process that hinges on the collaborative efforts of various stakeholders. The success of a significant transformational project is contingent upon the readiness and acceptance among the healthcare workers.

AIMS: This study aims to assess the level of understanding and awareness of healthcare workers regarding healthcare transformation, with a specific focus on Vision 2030.

METHODS: A cross-sectional quantitative study was undertaken involving Saudi healthcare workers. The research employed bivariate correlations and multivariate linear regressions for statistical analysis. Survey data were collected from 456 healthcare workers to gauge their perspectives on healthcare transformation.

RESULTS: The findings reveal a robust correlation between awareness of healthcare transformation and the perceived significance of the transformation. Notably, participation in the planning and execution stages significantly enhances awareness levels. Conversely, a negative correlation is observed between awareness levels and concerns related to job security and other challenges faced by healthcare workers.

CONCLUSION: To ensure the success of the national transformation program, decision-makers should actively involve all potential stakeholders, particularly during the planning and execution stages. Reassuring healthcare workers about job security and addressing their concerns are crucial steps in overcoming resistance and fostering the necessary support for healthcare transformation initiatives.

PMID:39627826 | DOI:10.1186/s12913-024-12025-5

BMC Nurs. 2024 Dec 3;23(1):881. doi: 10.1186/s12912-024-02554-z.

ABSTRACT

BACKGROUND: Clinical nurses play a vital role in healthcare. Their innovative behavior is crucial for improving patient care, advancing the profession, and ensuring the healthcare industry’s continued success. Many studies have highlighted the importance of nurse innovative behavior, but the link between their innovative behavior, structural empowerment, and decent work perception remains unclear.

OBJECTIVES: This study aimed to investigate the relationship between innovative behavior, structural empowerment, and decent work perception among the Chinese clinical nurses and identify the mediating role of decent work perception.

METHODS: A cross-sectional correlational design was employed, and from July 2023 to April 2024, 1,513 clinical nurses were recruited from 8 tertiary grade-A hospitals across three cities in China. Data from the Demographic Characteristics Questionnaire, the Nurse Innovation Behavior Scale, the Conditions of Work Effectiveness Questionnaire-II, and the Decent Work Perception Scale were collected through convenience sampling and analyzed using descriptive statistics, univariate correlation, and process plug-in mediation effect analyses.

RESULTS: The total scores of innovative behavior, structural empowerment, and decent work perception were 28.36 ± 6.25, 51.15 ± 12.63, and 42.97 ± 9.25, respectively. Innovative behavior was significantly, moderately and positively correlated with structural empowerment (r = 0.657, p < 0.01) and decent work perception (r = 0.618, p < 0.01); decent work perception played a partial mediating role between innovative behavior and structural empowerment (52.5%).

CONCLUSION: The innovative behavior, structural empowerment, and decent work perception among the Chinese clinical nurses were relatively moderate, indicating a need for improvement. Structural empowerment perception can, directly and indirectly, impact innovative behavior through decent work perception among Chinese clinical nurses. Nursing managers should promote innovative behavior of clinical nurses by raising structural empowerment and decent work perception to improve the quality of clinical nursing. Thus, it can be improved by creating a positive empowerment climate for clinical nurses and providing them with the information, resources, support, and opportunities for their jobs and improving their level of structural empowerment and decent work perception.

PMID:39627823 | DOI:10.1186/s12912-024-02554-z

J Transl Med. 2024 Dec 4;22(1):1100. doi: 10.1186/s12967-024-05851-y.

ABSTRACT

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide, with highly variable prognosis and response to treatment. A large subset of patients does not respond to standard treatments or develops resistance. As an alternative, adoptive immunotherapy based on chimeric antigen receptor (CAR)-transduced immune cells has been proposed, however with significant adverse events. We therefore evaluated alternative CAR targets already tested in other tumour types and employed the natural killer cell line NK-92 for CAR transduction because of its more favourable toxicity profile.

METHODS: As an alternative antigen, we considered mesothelin (MSLN), the most represented target in CAR-based clinical studies for solid tumours. MSLN RNA expression was analysed in large series of CRC tumours (n = 640) and cell lines (n = 150), to evaluate its distribution and to identify MSLN-overexpressing models. NK-92 cells were transduced with anti-MSLN CAR, and subsequently sorted and cloned. Activity of CAR-NK-92 cells against target-expressing ovarian and CRC cells was assessed in vitro and in vivo. Statistical significance of efficacy was evaluated by t-test and log-rank test.

RESULTS: Large-scale expression analysis highlighted that about 10% of CRCs overexpress MSLN at levels comparable to those of ovarian cancer, a typical target of MSLN-CAR-based therapy. Intriguingly, MSLN overexpression is more frequent in poor prognosis and KRAS/BRAF-mutant CRC. Lentiviral transduction of NK-92 cells with the MSLN-CAR, followed by sorting and cloning, led to the identification of one clone, MSLN.CAR.NK-92.cl45, stably expressing the CAR and retaining the NK phenotype. As expected, the clone demonstrated significant in vitro and in vivo activity against ovarian cancer cells. When repurposed against models of CRC expressing high MSLN levels, it displayed comparable efficacy, both in vitro and in vivo. Specificity of the clone was confirmed by the absence of activity on control models with low or absent MSLN.

CONCLUSIONS: Our results provide preclinical evidence that a subset of colorectal cancers expressing high mesothelin levels can be effectively targeted by MSLN-CAR-based immunotherapy. The potential therapeutic impact of these findings is enhanced by the fact that frequently MSLN-overexpressing CRCs display worse prognosis and resistance to standard care.

PMID:39627822 | DOI:10.1186/s12967-024-05851-y