bluuebunny/crossref_metadata_2025_split huggingface dataset:
Harris' Developmental Neuropsychiatry: The Interface with Cognitive and Social Neuroscience
Authors: Harris James C. , Coyle Joseph T. 
Published: August 2024

Abstract
Harris' Developmental Neuropsychiatry is an update of the First Edition, which introduced the integration of developmental neuroscience into the understanding of the pathophysiology and treatment of children with neuropsychiatric conditions. It opens with a comprehensive review of methods of assessment including behavior rating scales and neuropsychological testing moving from the scientific underpinnings to clinical application. The developmental aspects of components of cognition including attention, emotion, language, memory and consciousness are reviewed. It addresses how current brain imaging techniques have transformed our ability to link specific cognitive/emotional states to brain structure and function in health and disease. Historically, discussion of social and emotional development did not generally include the role of the brain. The Harris textbook commits significant space to connecting attachment, social development and temperament to normal brain maturation and pathologies associated with genetic disorders and environmental risk factors. The textbook closes by reviewing the diagnosis and treatment of several childhood neuropsychiatric disorders that can now be viewed through a lens informed by the prior basic chapters. The late James Harris, MD was a pioneer in bringing the brain into Child and Adolescent Psychiatry, and this textbook demonstrates how radically the advances in neuroscience and genetics have transformed the field and improved the care of this vulnerable population.
Deep learning and direct sequencing of labeled RNA captures transcriptome dynamics
Authors: Martinek Vlastimil , Martin Jessica , Belair Cedric , Payea Matthew J , Malla Sulochan , Alexiou Panagiotis , Maragkakis Manolis 
Published: August 2024

Abstract
In eukaryotes, genes produce a variety of distinct RNA isoforms, each with potentially unique protein products, coding potential or regulatory signals such as poly(A) tail and nucleotide modifications. Assessing the kinetics of RNA isoform metabolism, such as transcription and decay rates, is essential for unraveling gene regulation. However, it is currently impeded by lack of methods that can differentiate between individual isoforms. Here, we introduce RNAkinet, a deep convolutional and recurrent neural network, to detect nascent RNA molecules following metabolic labeling with the nucleoside analog 5-ethynyl uridine and long-read, direct RNA sequencing with nanopores. RNAkinet processes electrical signals from nanopore sequencing directly and distinguishes nascent from pre-existing RNA molecules. Our results show that RNAkinet prediction performance generalizes in various cell types and organisms and can be used to quantify RNA isoform half-lives. RNAkinet is expected to enable the identification of the kinetic parameters of RNA isoforms and to facilitate studies of RNA metabolism and the regulatory elements that influence it.
Interference detection in radio astronomy: applying Shapiro–Wilks normality test, spectral entropy, and spectral relative entropy
Authors: Cao Zhicheng , Schmid Natalia A , Bandura Kevin , Lorimer Duncan R , Dameron Morgan , Crockett Katelyn , Grubick Clayton , Schmid Andreas , Zheng Shaonan 
Published: August 2024

Abstract
Radio-frequency interference (RFI) is becoming an increasingly significant problem for most radio telescopes. Working with Green Bank Telescope data from PSR J1730+0747 in the form of complex-valued channelized voltages and their respective high-resolution power spectral densities, we evaluate a variety of statistical measures to characterize RFI. As a baseline for performance comparison, we use median absolute deviation (MAD) in complex channelized voltage data and spectral kurtosis (SK) in power spectral density data to characterize and filter out RFI. From a new perspective, we implement the Shapiro–Wilks (SW) test for normality and two information theoretical measures, spectral entropy (SE) and spectral relative entropy (SRE), and apply them to mitigate RFI. The baseline RFI mitigation algorithms are compared against our novel RFI detection algorithms to determine how effective and robust the performance is. Except for MAD, we find significant improvements in signal-to-noise ratio through the application of SE, symmetrical SRE, asymmetrical SRE, SK, and SW. These algorithms also do a good job of characterizing broad-band RFI. Time- and frequency-variable RFI signals are best detected by SK and SW tests.
Evaluating the Severity Spectrum: A Hierarchical Analysis of Complications During Hip Fracture Admission Associated With Mortality
Authors: Pettit Christopher J. , Herbosa Carolyn F. , Ganta Abhishek , Rivero Steven , Tejwani Nirmal , Leucht Philipp , Konda Sanjit R. , Egol Kenneth A. 
Published: August 2024

OBJECTIVES:
To determine which in-hospital complications after the operative treatment of hip fractures are associated with increased in-patient, 30-day, and 1-year mortality.

METHODS:

Design:
Retrospective study.

Setting:
A single academic medical center and a Level 1 Trauma Center.

Patient Selection Criteria:
All patients who were operatively treated for hip fractures (Orthopaedic Trauma Association/AO 31A, 31B and Vancouver A, B, and C periprosthetic fractures) at a single center between October, 2014, and June, 2023.

Outcome Measures and Comparisons:
Occurrence of an in-hospital complication was recorded. Cohorts were based on mortality time points (during admission, 30 days, and 1 year) and compared with patients who were alive at those time points to determine which in-hospital complications were most associated with mortality. Correlation analysis was performed between patients who died and those who were alive at each time point.

RESULTS:
A total of 3134 patients (average age of 79.6 years, range 18–104 years and 66.6% women) met inclusion for this study. The overall mortality rate during admission, 30 days, and 1 year was found to be 1.6%, 3.9%, and 11.1%, respectively. Sepsis was the complication most associated with increased in-hospital mortality (odds ratio [OR] 7.79, 95% confidence interval [CI], 3.22–18.82, P < 0.001) compared with other in-hospital complications. Compared with other in-hospital complications, stroke was the complication most associated with 30-day mortality (OR 7.95, 95% CI, 1.82–34.68, P < 0.001). Myocardial infarction was the complication most associated with 1-year mortality (OR 2.86, 95% CI, 1.21–6.77, P = 0.017) compared with other in-hospital complications.

CONCLUSIONS:
Postoperative sepsis, stroke, and myocardial infraction were the 3 complications most associated with mortality during admission, 30-day mortality, and 1-year mortality, respectively, during the operative treatment of hip fractures.

LEVEL OF EVIDENCE:
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Analyzing leukemia content on social media: a comprehensive cross-sectional examination of Instagram and YouTube
Authors: Varma Meghal , Syed Aina M. , Patel Visarg J. , Mediboina Anjali 
Published: August 2024

Introduction:
Leukemia is a hematologic malignancy characterized by the uncontrolled proliferation of abnormal white blood cells. Patients with childhood leukemia may turn to social media for emotional support and information. This study aimed to identify the quality, reliability, understandability, and actionability of posts related to leukemia on YouTube and Instagram.

Methods:
Apify, a web scraping tool was used to gather relevant posts. The top 100 posts in each hashtag “leukemia,” “childhoodcancer,” “childhoodcancerawareness,” “leukemiaawareness” on Instagram, and the top 60 videos on YouTube for the term “leukemia” were scraped on 24 September 2023, resulting in the collection of 361 Instagram and 58 YouTube videos. All posts and videos in English and related to leukemia were included in the analysis, and thus, a total of 231 Instagram posts and 56 YouTube videos were evaluated, guided by the strengthening the reporting of cohort studies in surgery guidelines and utilized standardized tools [Global Quality Scale (GQS), modified DISCERN, and Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V)]. Data analysis was done in R Studio (4.3.1.); Kruskal–Wallis test was used to determine statistical significance.

Results:
YouTube videos demonstrated commendable standards with moderate quality and reliability (GQS 3.1, modified DISCERN 2.9, PEMAT-A/V understandability averaged 89%, and actionability averaged 50%). The impact of the uploader type on content quality and reliability was insignificant on both platforms. However, a notable correlation between YouTube video duration and quality scores underscored the potential influence of content length on information presentation. Instagram posts exhibited comparatively lower scores (GQS 2, modified DISCERN 1.8, PEMAT-A/V understandability averaged 56%, and actionability averaged 15%), indicating a need for enhanced content quality. Personal narratives emphasized the significant role of lived experiences in shaping content.

Conclusion:
Despite high understandability, actionable content, particularly on Instagram, necessitated improvement, revealing a potential gap in disseminating practical information. While personal narratives contributed significantly, lower reliability scores highlighted inherent challenges, underscoring the pivotal role of healthcare provider engagement and content validation.
Evaluating cancer rehabilitation services: Insight from Australia and New Zealand
Authors: Song Krystal , Jena Swatee , Alexander Tara , Lee Su Yi , Amatya Bhasker , Faux Steven G. , Khan Fary 
Published: August 2024

Background:
Despite evidence supporting the benefits of rehabilitation for cancer survivors, the nature of cancer rehabilitation programs is inadequately described in Australia and New Zealand. This study provides insight into current service delivery and challenges for healthcare systems in implementation of cancer rehabilitation programs.

Methods:
A cross-sectional survey of directors of public and private rehabilitation services in hospital and ambulatory settings across Australia and New Zealand using the Australasian Rehabilitation Outcomes Centre (AROC) registry evaluated the current delivery of cancer rehabilitation programs, health professional workforce, core care components delivered, barriers and facilitators to service delivery, and unit/organisation-wide cancer rehabilitation activities. Descriptive statistics analyzed quantitative data, and qualitative analyses interpreted item responses.

Results:
Of the 300 services, 102 (34%) participants completed the survey. Most services provide non-dedicated cancer rehabilitation programs (n=63), led by rehabilitation physicians, followed by allied health. The common tumour streams referred included central nervous system (67%, n=56), haematological (59%, n=49), prostate (58%, n=48), and lung cancers (58%, n=48). Patients were frequently referred during post-treatment (87%, n=72) and treatment phases (66%, n=55). Core program components were multimodal exercises, fatigue management strategies, and management of medical complications and medications. The main barriers and facilitators toward the uptake of cancer rehabilitation programs were identified. Key activities in education, research, advocacy, and clinical practice improvement were also highlighted.

Conclusions:
The survey identified key barriers and facilitators for the implementation of cancer rehabilitation programs. Collaborative efforts of relevant stakeholders, clinicians, consumers, and policymakers need to address barriers to broader implementation of cancer rehabilitation services.
Association between HIV and cytomegalovirus and neurocognitive outcomes among children with HIV
Authors: Neary Jillian , Chebet Daisy , Benki-Nugent Sarah , Moraa Hellen , Richardson Barbra A. , Njuguna Irene , Langat Agnes , Ngugi Evelyn , Lehman Dara A. , Slyker Jennifer , Wamalwa Dalton , John-Stewart Grace 
Published: August 2024

Objectives:
Children with HIV may experience adverse neurocognitive outcomes despite antiretroviral therapy (ART). Cytomegalovirus (CMV) is common in children with HIV. Among children on ART, we examined the influences of early HIV viral load and CMV DNA on neurocognition.

Design:
We determined the association between pre-ART viral load, cumulative viral load, and CMV viremia and neurocognition using data from a cohort study.

Methods:
Children who initiated ART before 12 months of age were enrolled from 2007 to 2010 in Nairobi, Kenya. Blood was collected at enrollment and every 6 months thereafter. Four neurocognitive assessments with 12 domains were conducted when children were a median age of 7 years. Primary outcomes included cognitive ability, executive function, attention, and motor z scores. Generalized linear models were used to determine associations between HIV viral load (pre-ART and cumulative; N = 38) and peak CMV DNA (by 24 months of age; N = 20) and neurocognitive outcomes.

Results:
In adjusted models, higher peak CMV viremia by 24 months of age was associated with lower cognitive ability and motor z scores. Higher pre-ART HIV viral load was associated with lower executive function z scores. Among secondary outcomes, higher pre-ART viral load was associated with lower mean nonverbal and metacognition z scores.

Conclusion:
Higher pre-ART viral load and CMV DNA in infancy were associated with lower executive function, nonverbal and metacognition scores and cognitive ability and motor scores in childhood, respectively. These findings suggest long-term benefits of early HIV viral suppression and CMV control on neurocognition.
BioLP-bench: Measuring understanding of biological lab protocols by large language models
Authors: Ivanov Igor 
Published: August 2024

AbstractLanguage models rapidly become more capable in many domains, including biology. Both AI developers and policy makers [1] [2] [3] are in need of benchmarks that evaluate their proficiency in conducting biological research. However, there are only a handful of such benchmarks[4, 5], and all of them have their limitations. This paper introduces the Biological Lab Protocol benchmark (BioLP-bench) that evaluates the ability of language models to find and correct mistakes in a diverse set of laboratory protocols commonly used in biological research.To evaluate understanding of the protocols by AI models, we introduced in these protocols numerous mistakes that would still allow them to function correctly. After that we introduced in each protocol a single mistake that would cause it to fail. We then presented these modified protocols to an LLM, prompting it to identify the mistake that would cause it to fail, and measured the accuracy of a model in identifying such mistakes across many test cases. Only OpenAI o1-preview scored similarly to the performance of human experts, while other language models demonstrated substantially worse performance, and in most cases couldn’t correctly identify the mistake.Code and dataset are published athttps://github.com/baceolus/BioLP-bench
GENETIC VARIABILITY AND ASSOCIATION OF TRAITS IN COMMON BEAN (Phaseolus vulgarisL.)GENOTYPES IN SEKOTA, NORTH WESTERN ETHIOPIA
Authors: Assefa Abebe , Worku Dereje , Bantayhu Muluken , Asres Fentaw 
Published: August 2024

ABSTRACTCommon bean (Phaseolus vulgaris L.) is one of the most important pulse crops in Ethiopia, contributing to income generation and food security. Information on the genetic variability and trait associations of common bean in the Sekota district of north Western Ethiopia is inadequate. This study was initiated with the objective to assess variability, heritability and trait association among 64 common bean genotypes for quantitative traits using 8x8 simple lattice design at Aybra main research site 2023 under rain fed conditions. Analysis of variance was performed using SAS software and the ANOVA revealed highly significant variations among genotypes for all the traits considered in the study. The yield ranged from 1633.1 to 3702.10 kg ha-1with a mean of 2542.53 kg ha-1. There was a yield advantage of 24.56 to 55.89% over the checks. A moderate genotypic coefficient of variation coupled with high heritability and high genetic advance as a percentage of the mean was obtained for plant height, branches per plant, hundred seed weight, seed yield, and harvest index. Branches per plant, aboveground biomass and harvest index had significant positive correlations and direct effects on seed yield at the genotypic and phenotypic levels while days to maturity had a significant negative correlation and indirect effect with seed yield at the genotypic. The maximum inter cluster distance was found between clusters VII and 8 (D2=351.39), followed by clusters V and VIII (D2=331.23). The first five principal component axes accounted for 74.3% of the total variation, with eigenvalues greater than unity. The number of days to maturity, plant height, number of pods per plant, number seeds per pod, seed yield, and harvest index were the traits that contributed most of the variation in the first PCs. Generally, the presence of variability, and strong positive association of traits among the genotypes were observed in the traits under study. Therefore, selection based on agronomic performance and hybridization based on cluster distance could be possible for the improvement of common bean in the study area.
An Affordable and Customizable Arduino-based Thermo-controller for Thermal Ecology Experiments
Authors: Hawk Cassidy , Iverson Erik , Havird Justin 
Published: August 2024

AbstractInsight into organismal physiology, evolutionary ecology, and climate change susceptibility all rely on high-quality and easily-obtainable thermal tolerance information. A variety of methods exist for measuring thermal tolerance, and thermal tolerance metrics are highly influenced by small differences in methodology. To promote consistency, reproducibility, and accessibility, we present here instructions for building an Arduino-based thermo-controller for raising, lowering, and holding temperature in a variety of experimental conditions. The setup is affordable (∼$100), highly customizable, and highly consistent in the outcomes it produces. We include data from real thermal trials demonstrating the ability of the system to meet, hold, and reproduce desired ramping rates and hold temperatures.
Pipeline for Assessing Tumor Immune Status Using Superplex Immunostaining and Spatial Immune Interaction Analysis
Authors: Xiao Chaoxin , Zhou Ruihan , Chen Qin , Hou Wanting , Li Xiaoying , Wang Yulin , Liu Lu , Wang Huanhuan , Yao Xiaohong , Xu Tongtong , Cao Fujun , Yin Banglei , Yan Ouying , Jiang Lili , Wang Wei , Cao Dan , Zhao Chengjian 
Published: August 2024

ABSTRACTThe characteristics of the tumor microenvironment (TME) are closely linked to tumor progression and treatment response. The TME comprises various cell types, their spatial distribution, cell-cell interactions, and their organization into cellular niches or neighborhoods. To capture this complexity, several spatial profiling technologies have been developed. However, challenges such as low throughput, high costs, and complicated data analysis have limited their widespread use in immune research. In this study, we introduce the Cyclic-multiplex TSA (CmTSA) staining platform, a high-throughput superplex staining technology based on tyramide signal amplification (TSA) immunostaining combined with an efficient fluorophore recycling method. The CmTSA platform allows for the labeling of 30-60 antigens across multiple parallel formalin-fixed paraffin-embedded (FFPE) slides. Furthermore, the automated CmTSA workflow requires only standard histological equipment and conventional immunohistochemistry (IHC) primary antibodies (Abs), significantly reducing costs. While the superplex images produced contain extensive multidimensional information, extracting the spatial features of the TME from raw pixel data can be challenging. To address this, we present a computer vision-based analysis pipeline, which begins with deep learning-based algorithms to segment individual cells and identify cell types based on defined annotation rules. It then evaluates the spatial distribution tendencies of each cell type, the interaction intensity between paired cells, and the multicellular functional niches. This comprehensive approach enables researchers to visualize and quantify the types, states, and levels of immune activities within the TME effectively, advancing tumor immunology research and precision immune medicine.
Developing and characterising decellularized extracellular matrix hydrogels to bio-fabricate female reproductive tissues
Authors: Ribes Martinez E. , Franko Y. , Franko R. , Ferronato G.A. , Viana A.E.S. , Windenbach E , Stoeckl J. B. , Frohlich T. , Ferraz M.A.M.M. 
Published: August 2024

AbstractThis study investigated the development and characterization of decellularized extracellular matrix (dECM) hydrogels tailored for the bio-fabrication of female reproductive tissues, specifically targeting cortex, endometrium, medulla, and oviduct tissues. We aimed to evaluate the cytocompatibility, biomechanical properties, and overall efficacy of these dECMs in promoting cell viability, proliferation, and differentiation. Our findings revealed that these dECMs exhibited high biocompatibility with embryo development and cell viability, supporting micro vascularization and cellular differentiation without the need for external growth factors. These hydrogels displayed biomechanical properties that closely mimicked native tissues, which was vital for maintaining their functional integrity and supporting cellular activities. The printability assessments showed that dECMs, particularly those from cortex tissues, achieved high precision in replicating the intended structures, though challenges such as low porosity remained. The bioprinted constructs demonstrated robust cell growth, with over 97% viability observed by day 7, indicating their suitability for cell culture. This work represented a significant advancement in reproductive tissue bio-fabrication, demonstrating the potential of dECM-based hydrogels in creating structurally and functionally viable tissue constructs. By tailoring each dECM to match the unique biomechanical properties of different tissues, we paved the way for more effective and reliable applications in reproductive medicine and tissue engineering.HighlightsDeveloped decellularized extracellular matrix (dECM) bio-inks for bio-fabrication of female reproductive tissues.Demonstrated high biocompatibility with embryo development and cell viability.Achieved accurate bioprinting, maintaining structural integrity.Promoted micro vascularization and cell differentiation without added growth factors.