bluuebunny/crossref_metadata_2025_split huggingface dataset:
California Mortality and the Healthy Places Index
Authors: Maizlish Neil , Damicis Adrienne 
Published: November 2024

Abstract
We investigated California mortality and social determinants of health, as measured by the Healthy Places Index (HPI), which is a composite measure of 23 indicators of neighborhood (census tract) economic conditions, education, transportation, housing, social capital, environmental pollution, built-environment, and access to health care. We aggregated deaths to 2010 census tract boundaries for leading causes, 2015 to 2019, and COVID-19, 2020-2021, from death certificates and populations from the American Community Survey, 2015 to 2019. We age-adjusted and stratified death rates by HPI deciles, age, gender, and race/ethnicity, and examined HPI dose-response with segmental regression. For all causes, cancer, cardiovascular disease, COVID-19, diabetes, cirrhosis of the liver, injuries, and Alzheimer’s disease (ages 65-74 years), mortality rates were inversely related to HPI decile. For all causes mortality, the rate ratio between the 1st and 10th decile (reference) was 1.63 (CI95%: 1.60–1.66), and, for COVID-19, the rate ratio was 7.61 (CI95%: 7.14–8.12). The population attributable fraction was 24% for all causes and 72% for COVID-19. Age, gender, race/ethnicity modified the steepness and shape of dose-response curves. The findings illustrate opportunities to incorporate area-based socioeconomic measures in routine public health surveillance, and to reinforce policies and programs that reduce health inequities.
Impact of using dosing criteria to refine pharmacogenomic clinical decision support for tricyclic antidepressants
Authors: Massmann Amanda , Petry Natasha , Mills Sarah , Adjekum Adwoa , Van Heukelom Joel 
Published: November 2024

Abstract

Purpose
To evaluate the impact of dose-specific logic for tricyclic antidepressant (TCA) pharmacogenomics (PGx) clinical decision support (CDS). We aimed to provide guidance in an area with limited supporting literature, ensure optimal dosing through CDS, and limit alert fatigue. The primary outcome was the reduction in alerts prescribers encountered, while the secondary outcome included an analysis across specialties.

Methods
A retrospective chart review was conducted to examine TCA PGx CDS before and after implementation of dosing criteria for alerts. Data were abstracted from the electronic medical record. A χ2 test was performed to analyze the frequency of alerts in behavioral health and other specialties.

Results
In the cohort lacking dose criteria, most TCA orders were for indications other than depression (76%) and guidelines would not apply to the majority of these orders. Using dosing criteria to refine CDS reduced the volume of TCA alerts by 74.8%. Alert volume decreased the most in specialties other than behavioral health due to prescriptions for indications other than anxiety or depression (P = 0.035).

Conclusion
Dose-centric alerts may be used as a strategy to achieve optimal dosing. Alerting clinicians when dose modifications should occur contributes to getting the right dose to the right patient. Future efforts should focus on optimal dosing of medication through CDS enhancements.
AIGen: an artificial intelligence software for complex genetic data analysis
Authors: Hou Tingting , Shen Xiaoxi , Zhang Shan , Liang Muxuan , Chen Li , Lu Qing 
Published: November 2024

Abstract
The recent development of artificial intelligence (AI) technology, especially the advance of deep neural network (DNN) technology, has revolutionized many fields. While DNN plays a central role in modern AI technology, it has rarely been used in genetic data analysis due to analytical and computational challenges brought by high-dimensional genetic data and an increasing number of samples. To facilitate the use of AI in genetic data analysis, we developed a C++ package, AIGen, based on two newly developed neural networks (i.e. kernel neural networks and functional neural networks) that are capable of modeling complex genotype-phenotype relationships (e.g. interactions) while providing robust performance against high-dimensional genetic data. Moreover, computationally efficient algorithms (e.g. a minimum norm quadratic unbiased estimation approach and batch training) are implemented in the package to accelerate the computation, making them computationally efficient for analyzing large-scale datasets with thousands or even millions of samples. By applying AIGen to the UK Biobank dataset, we demonstrate that it can efficiently analyze large-scale genetic data, attain improved accuracy, and maintain robust performance. Availability: AIGen is developed in C++ and its source code, along with reference libraries, is publicly accessible on GitHub at https://github.com/TingtHou/AIGen.
MPA-MutPred: a novel strategy for accurately predicting the binding affinity change upon mutation in membrane protein complexes
Authors: Ridha Fathima , Gromiha M Michael 
Published: November 2024

Abstract
Mutations in the interface of membrane protein (MP) complexes are key contributors to a broad spectrum of human diseases, primarily due to changes in their binding affinities. While various methods exist for predicting the mutation-induced changes in binding affinity (ΔΔG) in protein–protein complexes, none are specific to MP complexes. This study proposes a novel strategy for ΔΔG prediction in MP complexes, which combines linear and nonlinear models, to obtain a more robust model with improved prediction accuracy. We used multiple linear regression to extract informative features that influence the binding affinity in MP complexes, which included changes in the stability of the complex, conservation score, electrostatic interaction, relatively accessible surface area, and interface contacts. Further, using gradient boosting regressor on the selected features, we developed MPA-MutPred, a novel method specific for predicting the ΔΔG of membrane protein–protein complexes, and it is freely accessible at https://web.iitm.ac.in/bioinfo2/MPA-MutPred/. Our method achieved a correlation of 0.75 and a mean absolute error (MAE) of 0.73 kcal/mol in the jack-knife test conducted on a dataset of 770 mutants. We further validated the method using a blind test set of 86 mutations, obtaining a correlation of 0.85 and an MAE of 0.77 kcal/mol. We anticipate that this method can be used for large-scale studies to understand the influence of binding affinity change on disease-causing mutations in MP complexes, thereby aiding in the understanding of disease mechanisms and the identification of potential therapeutic targets.
Plio/Pleistocene-induced climatic oscillations drive cladogenesis in a high-altitude freshwater crab, Potamonautes mariepskoppie (Decapoda: Potamonautidae), in South Africa
Authors: Gunkel Kallyn G R , Daniels Savel R 
Published: November 2024

Abstract
In this study, we explored the phylogeographical history of the mountain-dwelling freshwater crab Potamonautes mariepskoppie to understand evolutionary processes and identify possible hidden lineages. DNA sequence data from mitochondrial loci (COI, 12S rRNA, and 16S rRNA) and a nuclear locus (histone 3) were analysed using both maximum likelihood and Bayesian inference. Species delimitation was tested with four methods: ASAP, bPTP, bGMYC, and STACEY. Divergence time estimation and ecological niche modelling with ENMEval and Maxent were used to study species distribution and elucidate abiotic factors affecting evolution. Phylogenetic analyses showed three distinct clades, corresponding to geographical regions: Limpopo, Mpumalanga, and Mount Sheba. These clades had no shared haplotypes and exhibited moderate genetic differentiation. Divergence time estimates indicated that these clades diverged during the Plio/Pleistocene, a period of significant climatic shifts in southern Africa. All four species delimitation methods consistently supported the recognition of these clades as distinct species; however, discriminant function analyses of carapace characteristics showed significant overlap between the three clades. Ecological niche modelling indicated that rainfall is a key factor in the species distribution. The present study highlights the need for further investigation of the high-elevation plateaus throughout Limpopo and Mpumalanga, because fine-scale sampling might unmask considerable hitherto-undocumented biodiversity.
A cross-sectional evaluation of knowledge and attitudes of medical interns regarding social service practices in healthcare institutions
Authors: Şevik İrem , Kuyucu Simge , Torcu Özgün , Çiçeklioğlu Meltem 
Published: November 2024

Abstract
Interprofessional collaboration is essential for holistic healthcare, yet social work remains under-integrated in medical curricula, particularly in Türkiye. Neoliberal policies have weakened community-based services, increasing the need to address gaps in medical education regarding social work’s role in addressing social determinants of health. This is especially critical given Türkiye’s demographic shifts, such as an aging population and rising social inequalities. This study aimed to assess the knowledge and attitudes of intern doctors at a university in Izmir, Türkiye, regarding social work practices in healthcare and to identify associated factors. A sample of 181 was selected through simple random sampling. Data analysis included descriptive statistics, t-test, Spearman correlation, and factor analyses. The Cronbach’s alpha for the attitude scale was 0.87. A significant portion (34.8 percent) had not heard of the social work profession, and 56.4 percent were unaware of social workers in their institution. Female students and those encountering underserved patients showed higher knowledge scores. There was a weak positive correlation between knowledge and attitudes. Factors influencing attitudes included gender, familiarity with social work, encountering underserved patients and financial status. Changes in medical education are needed to enhance interprofessional collaboration, with further research recommended on gender roles and attitudes towards social work.
Loss of tissue-type plasminogen activator causes multiple developmental anomalies
Authors: Uguen Kevin , Frey Tanja , Muthaffar Osama , Décarie Jean-Claude , Ameziane Najim , Boissel Sarah , Baradaran-Heravi Yalda , Rauch Anita , Oprea Gabriela , Rad Aboulfazl , Steindl Katharina , Michaud Jacques L 
Published: November 2024

Abstract
Hydrocephalus and Dandy–Walker malformation are amongst the most common congenital brain anomalies. We identified three consanguineous families with both obstructive hydrocephalus and Dandy–Walker malformation. To understand the molecular basis of these anomalies, we conducted genome-wide sequencing in these families. We identified three homozygous truncating variants in the PLAT gene in the four affected family members. All of them showed tetraventricular hydrocephalus. In two individuals, a membrane at the inferior aspect of the fourth ventricle was likely the cause of their hydrocephalus. Three cases exhibited Dandy–Walker malformation, whereas the two oldest individuals displayed intellectual disability. PLAT encodes the tissue-type plasminogen activator, a serine protease whose main function is to cleave the proenzyme plasminogen to produce active plasmin. Interestingly, plasminogen deficiency has also been shown to cause obstructive hydrocephalus and Dandy–Walker malformation, suggesting that loss of PLAT causes these defects by disrupting plasmin production. In summary, we describe a recessive disorder characterized by obstructive hydrocephalus, Dandy–Walker malformation and intellectual disability in individuals with loss-of-function variants in PLAT. This discovery further strengthens the involvement of the plasminogen pathway in the pathogenesis of these developmental disorders.
Cerebral white matter myelination is associated with longitudinal changes in processing speed across the adult lifespan
Authors: Gong Zhaoyuan , Bilgel Murat , An Yang , Bergeron Christopher M , Bergeron Jan , Zukley Linda , Ferrucci Luigi , Resnick Susan M , Bouhrara Mustapha 
Published: November 2024

Abstract
Myelin’s role in processing speed is pivotal, as it facilitates efficient neural conduction. Its decline could significantly affect cognitive efficiency during ageing. In this work, myelin content was quantified using our advanced MRI method of myelin water fraction mapping. We examined the relationship between myelin water fraction at the time of MRI and retrospective longitudinal change in processing speed among 121 cognitively unimpaired participants, aged 22–94 years, from the Baltimore Longitudinal Study of Aging and the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (a mean follow-up duration of 4.3 ± 6.3 years) using linear mixed-effects models, adjusting for demographics. We found that higher myelin water fraction values correlated with longitudinally better-maintained processing speed, with particularly significant associations in several white matter regions. Detailed voxel-wise analysis provided further insight into the specific white matter tracts involved. This research underscores the essential role of myelin in preserving processing speed and highlights its potential as a sensitive biomarker for interventions targeting age-related cognitive decline, thereby offering a foundation for preventative strategies in neurological health.
Excessive Data Collection and (Mis)use of Data: A Comparative Law and Economics Study on the Chinese Didi Case and the German Facebook Case
Authors: Li Qian 
Published: November 2024

Abstract
The excessive data collection and (mis)use of data can result in the coexistence of two market failures—namely, market dominance and information asymmetry—which in turn interact with each other in digital markets and trigger simultaneous concerns about competition law and data protection law. This article establishes a law and economics framework to study the divergence in response to the concerns caused by excessive data collection and (mis)use of data by dominant technology undertakings in the European Union and China. The German competition authority, the Bundeskartellamt, found that Facebook, a dominant social network platform, abused its dominant position by excessively collecting and misusing user data without consent, whereas the Cyberspace Administration of China addressed similar concerns caused by Didi, a dominant ride-hailing undertaking, via data protection law. Based on the comparative analysis of the German Facebook case and the Chinese Didi case, a competition law approach to deal with excessive data collection and the (mis)use of data by a dominant technology undertaking results in high enforcement costs due to the prerequisites of market definition and dominance determination under abuse of dominance, while contributing to minimizing error costs, especially false negatives in the absence of data protection enforcement. In contrast, a data protection approach would be a cost-effective way to intervene in the market ex-ante by decreasing the likelihood of excessive collection and misuse of data, reducing the exclusionary and/or exploitative effects of competition and lowering the market entry barrier that benefits from the collection and processing of significant amounts of data.
Acute kidney injury following CAR-T cell therapy: a nephrologist’s perspective
Authors: Kanbay Mehmet , Mizrak Berk , Alper Ezgi N , Copur Sidar , Ortiz Alberto 
Published: November 2024

ABSTRACT
Chimeric antigen receptor T (CAR-T) cell therapy, an emerging personalized immunotherapy for various haematologic malignancies, autoimmune diseases and other conditions, involves the modification of patients’ T cells to express a chimeric antigen receptor that recognizes tumour or autoimmune cell antigens, allowing CAR-T cells to destroy cancerous and other target cells selectively. Despite remarkable clinical improvements in patients, multiple adverse effects have been associated with CAR-T cell therapy. Among the most recognized adverse effects are cytokine release syndrome, immune effector cell–associated neurotoxicity syndrome and tumour lysis syndrome. Even though less recognized, the incidence of acute kidney injury (AKI) ranges from 5 to 33%. The wide range of reported AKI incidence rates might depend on patient population characteristics and comorbidities and specific CAR-T cell therapy features. Even though the exact pathophysiology remains unknown, several key mechanisms, including cytokine release syndrome, tumour lysis syndrome and other factors such as direct renal toxicity of CAR-T cell therapy, conditioning regimens or other medications (e.g. antibiotics), and infectious complications (e.g. sepsis) have been proposed. Risk factors for CAR-T-related AKI include lower baseline glomerular filtration rate, higher rates of allopurinol or rasburicase use, intravenous contrast material exposure, elevated baseline lactate dehydrogenase and grade 3 or higher cytokine release syndrome. Future prospective studies with larger patient populations are needed to gain insights into the pathophysiology of CAR-T-related AKI and, more importantly, to be able to prevent as well as to develop novel and more efficient treatment modalities. In this narrative review, we discuss the underlying pathophysiology, risk factors, potential interventions and future directions related to AKI following CAR-T cell therapy.
Complications on the feeding artery after an arterio-venous fistula closure in patients after kidney transplantation – a national cohort study
Authors: Zrimšek Matej , Vajdič-Trampuž Barbara , Jelenc Matija , Kšela Juš , Gubenšek Jakob 
Published: November 2024

ABSTRACT

Background
Arteriovenous fistulas (AVFs) in kidney transplant recipients are sometimes closed, either as a policy or due to complications. We collected data on the incidence of complications after AVF closure in a national cohort of transplanted patients.

Methods
Patients who received a kidney transplant between 2000 and 2015 and had a functional AVF that was later ligated or extirpated were included. Medical records were searched for arterial complications on the arm with the closed AVF. Furthermore, all patients who were still alive in January 2023 were invited for a follow-up arterial ultrasound exam.

Results
Sixty patients were included; mean follow-up was 9.3 ± 3.8 years. There were five (8% cumulative incidence) patients with symptomatic arterial thrombosis and three (5% incidence) with a symptomatic feeding artery aneurysm. Prospective ultrasound exams were performed in 50 patients; the mean diameter of the brachial artery was almost doubled on the arm with the closed AVF (8.1 ± 3.2 versus 4.7 ± 0.7 mm; P &lt; .001). Additional asymptomatic complications were found in nine patients (18% incidence): seven cases (14% incidence) of arterial thrombosis, some extending up to the axillary artery, and three (6% incidence) brachial artery aneurysms. All patients in whom the thrombosis spread to the brachial artery had large brachial arteries (&gt;10 mm) or an aneurysm.

Conclusion
We observed a high cumulative incidence of arterial thrombosis (20%) and brachial artery aneurysms (10%), sometimes developing several years after AVF closure. These complications should be taken into account when contemplating closure of a well-developed AVF and an AVF-preserving approach with flow reduction surgery might be preferred in some cases.
A comparison of artificial intelligence–enhanced electrocardiography approaches for the prediction of time to mortality using electrocardiogram images
Authors: Sau Arunashis , Zeidaabadi Boroumand , Patlatzoglou Konstantinos , Pastika Libor , Ribeiro Antônio H , Sabino Ester , Peters Nicholas S , Ribeiro Antonio Luiz P , Kramer Daniel B , Waks Jonathan W , Ng Fu Siong 
Published: November 2024

Abstract

Aims
Most artificial intelligence-enhanced electrocardiogram (AI-ECG) models used to predict adverse events including death require that the ECGs be stored digitally. However, the majority of clinical facilities worldwide store ECGs as images.

Methods and results
A total of 1 163 401 ECGs (189 539 patients) from a secondary care data set were available as both natively digital traces and PDF images. A digitization pipeline extracted signals from PDFs. Separate 1D convolutional neural network (CNN) models were trained on natively digital or digitized ECGs, with a discrete-time survival loss function to predict time to mortality. A 2D CNN model was trained on 310 × 868 px ECG images. External validation was performed in 958 954 ECGs (645 373 patients) from a Brazilian primary care cohort and 1022 ECGs (1022 patients) from a Chagas disease cohort. The image 2D CNN model and digitized 1D CNN model performed comparably to natively digital 1D CNN model in internal [C-index 0.780 (0.779–0.781), 0.772 (0.771–0.774), and 0.775 (0.774–0.776), respectively] and external validation. Models trained on natively digital 1D ECGs had comparable performance when applied to digitized 1D ECGs [C-index 0.773 (0.771–0.774)].

Conclusion
Both the image 2D CNN and digitized 1D CNN enable mortality prediction from ECG images, with comparable performance to natively digital 1D CNN. Models trained on natively digital 1D ECGs can also be applied to digitized 1D ECGs, without any significant loss in performance. This work allows AI-ECG mortality prediction to be applied in diverse global settings lacking digital ECG infrastructure.
Whole-genome sequencing confirms multiple species of Galapagos giant tortoises
Authors: Gaughran Stephen J , Gray Rachel , Ochoa Alexander , Jones Menna , Fusco Nicole , Miller Joshua M , Poulakakis Nikos , de Queiroz Kevin , Caccone Adalgisa , Jensen Evelyn L 
Published: November 2024

Abstract
Galapagos giant tortoises are endemic to the Galapagos Archipelago, where they are found in isolated populations. While these populations are widely considered distinguishable in morphology, behavior, and genetics, the recent divergence of these taxa has made their status as species controversial. Here, we apply multispecies coalescent methods for species delimitation to whole-genome resequencing data from 38 tortoises across all 13 extant taxa to assess support for delimiting these taxa as species. In contrast to previous studies based solely on divergence time, we find strong evidence to reject the hypothesis that all Galapagos giant tortoises belong to a single species. Instead, a conservative interpretation of model-based and divergence-based results indicates that these taxa form a species complex consisting of a minimum of 9 species, with most analyses supporting 13 species. There is mixed support for the species status of taxa living on the same island, with some methods suggesting multiple populations of a single species per island. These results make clear that Galapagos giant tortoise taxa represent different stages in the process of speciation, with some taxa further along in that evolutionary process than others. Our study provides insight into the complex process of speciation on islands, which is urgently needed given the threatened status of island species around the world.