bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning-based design and experimental validation of a medicine-like human antibody library
Authors: Rajagopal Nandhini , Choudhary Udit , Tsang Kenny , Martin Kyle P , Karadag Murat , Chen Hsin-Ting , Kwon Na-Young , Mozdzierz Joseph , Horspool Alexander M , Li Li , Tessier Peter M , Marlow Michael S , Nixon Andrew E , Kumar Sandeep 
Published: January 2025

Abstract
Antibody generation requires the use of one or more time-consuming methods, namely animal immunization, and in vitro display technologies. However, the recent availability of large amounts of antibody sequence and structural data in the public domain along with the advent of generative deep learning algorithms raises the possibility of computationally generating novel antibody sequences with desirable developability attributes. Here, we describe a deep learning model for computationally generating libraries of highly human antibody variable regions whose intrinsic physicochemical properties resemble those of the variable regions of the marketed antibody-based biotherapeutics (medicine-likeness). We generated 100000 variable region sequences of antigen-agnostic human antibodies belonging to the IGHV3-IGKV1 germline pair using a training dataset of 31416 human antibodies that satisfied our computational developability criteria. The in-silico generated antibodies recapitulate intrinsic sequence, structural, and physicochemical properties of the training antibodies, and compare favorably with the experimentally measured biophysical attributes of 100 variable regions of marketed and clinical stage antibody-based biotherapeutics. A sample of 51 highly diverse in-silico generated antibodies with &gt;90th percentile medicine-likeness and &gt; 90% humanness was evaluated by two independent experimental laboratories. Our data show the in-silico generated sequences exhibit high expression, monomer content, and thermal stability along with low hydrophobicity, self-association, and non-specific binding when produced as full-length monoclonal antibodies. The ability to computationally generate developable human antibody libraries is a first step towards enabling in-silico discovery of antibody-based biotherapeutics. These findings are expected to accelerate in-silico discovery of antibody-based biotherapeutics and expand the druggable antigen space to include targets refractory to conventional antibody discovery methods requiring in vitro antigen production.
Birds, stars, and mousikē: visions of escape in Euripidean choral odes
Authors: Reitzammer Laurialan 
Published: January 2025

ABSTRACT
In this essay, I discuss, as a group, moments when a Euripidean female chorus express a wish for winged travel elsewhere—the second stasimon of Iphigenia among the Taurians (1089–1152),the third stasimon of Helen (1451–1511), the second stasimon of Hippolytus (732–75), and the first stasimon of Bacchae (370–431). These choral passages offer lengthy and elaborate escape prayers that embellish the conventional wish to take wing or disappear, focusing on the idea of wings and travel as opposed to the idea of disappearing, and offering a bird’s-eye view of imagined expanses of land and sea. In Euripides’ plays, as I argue, female choruses who wish for release from their impossible circumstances offer surprisingly similar visions of escape. Again and again, they wish to return home (to an actual home or to a notional homeland) and they yearn for winged travel to places characterized by bands of maidens and female mousikê (song, dance, and music).
Reconsidering the computer’s role in literary studies through Levison 1964
Authors: Rodda Martina Astrid 
Published: January 2025

ABSTRACT
This article takes as its starting point a 1964 BICS article by Michael Levison and its scholarly context. From this piece, it traces the history of some key themes in Digital Humanities and computational approaches to classical texts: the availability of data and tools; the potential of different methods, from authorship attribution to textual reconstruction; and what questions they raise for the ethics of the field.
Functional profiling of the sequence stockpile: a protein pair-based assessment of in silico prediction tools
Authors: Prabakaran R , Bromberg Yana 
Published: January 2025

Abstract

Motivation
In silico functional annotation of proteins is crucial to narrowing the sequencing-accelerated gap in our understanding of protein activities. Numerous function annotation methods exist, and their ranks have been growing, particularly so with the recent deep learning-based developments. However, it is unclear if these tools are truly predictive. As we are not aware of any methods that can identify new terms in functional ontologies, we ask if they can, at least, identify molecular functions of proteins that are non-homologous to or far-removed from known protein families.

Results
Here, we explore the potential and limitations of the existing methods in predicting the molecular functions of thousands of such proteins. Lacking the “ground truth” functional annotations, we transformed the assessment of function prediction into evaluation of functional similarity of protein pairs that likely share function but are unlike any of the currently functionally annotated sequences. Notably, our approach transcends the limitations of functional annotation vocabularies, providing a means to assess different-ontology annotation methods. We find that most existing methods are limited to identifying functional similarity of homologous sequences and fail to predict the function of proteins lacking reference. Curiously, despite their seemingly unlimited by-homology scope, deep learning methods also have trouble capturing the functional signal encoded in protein sequence. We believe that our work will inspire the development of a new generation of methods that push boundaries and promote exploration and discovery in the molecular function domain.

Availability and implementation
The data underlying this article are available at https://doi.org/10.6084/m9.figshare.c.6737127.v3. The code used to compute siblings is available openly at https://bitbucket.org/bromberglab/siblings-detector/.
Semiparametric Sieve Estimation for Survival Data with Two-layer Censoring
Authors: Wang Yudong , Tong Jiayi , Hu Xiangbin , Ye Zhi-Sheng , Tang Cheng Yong , Chen Yong 
Published: January 2025

Abstract
Disease registry data provide important information on the progression of disease conditions. However, reports of death or dropout of patients enrolled in the registry are always subject to a noticeable delay. Reporting delays, together with the administrative censoring that arises from a freeze date in data collection, lead to two layers of right censoring in the data. The first layer results from random dropout and acts on the survival time. The second layer is the administrative censoring, which acts on the summation of the reporting delay and the minimum of the survival time and random dropout time. The heterogeneities among patients further complicate data analysis. This paper proposes a novel semiparametric sieve method based on phase-type distributions, in which covariates can be readily accommodated by the accelerated failure time model. A well-orchestrated EM algorithm is developed to compute the sieve maximum likelihood estimator. We establish the consistency and rate of convergence of the proposed sieve estimators, as well as the asymptotic normality and semiparametric efficiency of the estimators for the regression parameters. Comprehensive simulations and a real example of lung cancer registry data are used to demonstrate the proposed method. The results reveal substantial biases if reporting delays are overlooked.
An improved cell nuclear isolation method
Authors: Li Pengfei , Zhang Jingyao , Liu Xiaojuan , Wu Zhijuan , Kang Y James , Zhang Wenjing 
Published: January 2025

Abstract
Nuclear isolation is crucial for studying gene expression and regulatory mechanisms in eukaryotic cells. This study aimed to improve nuclear isolation and compare the yield, purity, and efficiency of several methods. Human umbilical vein endothelial cells were used to evaluate four different techniques: sucrose centrifugation, a simplified method, homogenization, and the NE-PER kit. For sucrose centrifugation, cells were scraped in Tween buffer, washed with sucrose buffer, and homogenized in a Dounce homogenizer. The pellet was washed with glycerol buffer to isolate the nuclei. In the simplified method, cells were scraped in scraping buffer, washed with sucrose buffer, and the pellet was washed with glycerol buffer to isolate the nuclei. For homogenization, cells were washed with phosphate buffered saline, followed by two washes in extract buffer and lysed with 10 strokes in a Kontes Dounce homogenizer. The NE-PER kit was used according to the manufacturer’s protocol. Nuclei isolated by each method were tested by immunoblotting, co-immunoprecipitation (Co-IP), and chromatin immunoprecipitation (Ch-IP) assays. The simplified method produced nuclei with fewer organelles and less cytoplasm than those isolated by homogenization or the NE-PER kit. It was similarly effective as sucrose centrifugation but faster. Co-IP and Ch-IP assays confirmed that the simplified method enriched target proteins and DNA fragments. Overall, the simplified method provides a highly pure nuclear sample optimal for downstream applications requiring purified nuclei.
Distributed lag models for retrospective cohort data with application to a study of built environment and body weight
Authors: Bobb Jennifer F , Mooney Stephen J , Cruz Maricela , Vernez Moudon Anne , Drewnowski Adam , Arterburn David , Cook Andrea J 
Published: January 2025

ABSTRACT
Distributed lag models (DLMs) estimate the health effects of exposure over multiple time lags prior to the outcome and are widely used in time series studies. Applying DLMs to retrospective cohort studies is challenging due to inconsistent lengths of exposure history across participants, which is common when using electronic health record databases. A standard approach is to define subcohorts of individuals with some minimum exposure history, but this limits power and may amplify selection bias. We propose alternative full-cohort methods that use all available data while simultaneously enabling examination of the longest time lag estimable in the cohort. Through simulation studies, we find that restricting to a subcohort can lead to biased estimates of exposure effects due to confounding by correlated exposures at more distant lags. By contrast, full-cohort methods that incorporate multiple imputation of complete exposure histories can avoid this bias to efficiently estimate lagged and cumulative effects. Applying full-cohort DLMs to a study examining the association between residential density (a proxy for walkability) over 12 years and body weight, we find evidence of an immediate effect in the prior 1-2 years. We also observed an association at the maximal lag considered (12 years prior), which we posit reflects an earlier ($\ge$12 years) or incrementally increasing prior effect over time. DLMs can be efficiently incorporated within retrospective cohort studies to identify critical windows of exposure.
Beyond crisis and grief: Rethinking conservation narratives
Authors: Malavasi Marco 
Published: January 2025

Abstract
Since 1985, conservation science has been unquestioningly described as a crisis discipline. This narrative entails prioritizing immediate responses to threats despite limited knowledge. Although crisis interventions have grown significantly, biodiversity loss has continued unabated, and those working or living alongside declining ecosystems report increasing levels of emotional distress. Ecological grief is particularly on the rise and is claimed by some as a necessary process to fuel the urgent lifesaving changes. However, I argue that both narratives—the emerging ecological grief and the established crisis approach—can synergically reinforce a loop of resignation, where ecological decline is either passively accepted or inadvertently perpetuated. Such resignation ultimately leads to harmful adaptation to ongoing ecological degradation. Finally, I propose a shift toward a transformative conservation narrative, moving away from the primary focus on crisis thinking to embrace proactive futures. Reframing the underlying narratives is essential, because they can influence the broader conservation agenda.
The value of ultrasound measured rectus femoris thickness, cross-sectional area and shear wave velocity in assessment of muscle in postmenopausal women with osteosarcopenia
Authors: Chen Zi-Tong , Ge Jia-Ying , Jin Feng-Shan , Guo Le-Hang , Wang Qiao , Zhao Hui , Sun Li-Ping , Xu Hui-Xiong , Sheng Hui , Li Xiao-Long ,   China Alliance of Multi-Center Clinical Study for Ultrasound (Ultra-Chance)
Published: January 2025

Abstract

Objectives
To evaluate the value of ultrasound (US) and shear wave velocity (SWV) to assess muscle in postmenopausal women with osteosarcopenia (OSP).

Methods
This study included 145 postmenopausal women, comprising 115 osteopenia/osteoporosis participants without sarcopenia (OP alone) and 30 OSP participants. All received the evaluation of bone mineral density (BMD), appendicular skeletal muscle mass index (ASMI), handgrip strength, calf circumference, 6-meter walking speed, and 5-time chair stand test. The cross-sectional area (RFcsa), thickness (RFthickness), and mean SWV of rectus femoris (RF) were measured by US and shear wave elastography. The clinical characteristics, RFcsa, RFthickness, and SWV, were compared between OP alone and OSP to determine the independent predictors of OSP. Receiver operating characteristic (ROC) curve analysis was used to evaluate the value of US and SWV for assessment of OSP.

Results
The RFcsa, RFthickness, SWV, and BMD of OSP were lower than those of OP alone (all P &lt; 0.05). Through multivariate analysis, the diagnostic performance of the prediction model (area under the ROC curve, AUC, 0.917) composed of RFcsa and SWV was superior to RFcsa (AUC, 0.847), RFthickness (AUC, 0.797), and SWV (AUC, 0.740) alone. Moreover, the prediction model achieved 70.0% sensitivity, 93.0% specificity, and 88.3% accuracy.

Conclusions
The RFcsa, RFthickness, and SWV have potential value in assessing muscle in OSP and can be applied to routine clinical management of postmenopausal women.

Advances in knowledge
US measured RF thickness, CSA and SWV could assist detection and clinical management of OSP in postmenopausal women.
The impact of resective epilepsy surgery on the brain network: evidence from post-surgical imaging
Authors: Sainburg Lucas E , Englot Dario J , Morgan Victoria L 
Published: January 2025

Abstract
Resective epilepsy surgery can be an effective treatment for patients with medication-resistant focal epilepsy. Epilepsy resection consists of the surgical removal of an epileptic focus to stop seizure generation and disrupt the epileptic network. However, even focal surgical resections for epilepsy lead to widespread brain network changes. Understanding the impact of epilepsy surgery on the brain is crucial to improve surgical outcomes for patients. Here we provide a summary of studies imaging the postsurgical effects of epilepsy resection on the brain. We focus on MRI and PET studies of temporal lobe and pediatric epilepsy, reflecting the current literature. We discuss three potential mechanisms for surgery-induced brain changes: damage and degeneration, recovery, and reorganization. We additionally review the postsurgical brain correlates of surgical outcomes as well as the potential to predict the impact of surgery on an individual patient’s brain. A comprehensive characterization of the impact of surgery on the brain and precise methods to predict these brain network changes could lead to more personalized surgeries that improve seizure outcomes and reduce neuropsychological deficits after surgery.
Enhancing diabetic muscle repair through W-GA nanodots: a nanomedicinal approach to ameliorate myopathy in type 2 diabetes
Authors: Liu Shan , Wan Renwen , Li QingRong , Chen Yisheng , He Yanwei , Feng Xingting , Yung Patrick Shu-Hang , Luo Zhiwen , Wang Xianwen , Chen Chen 
Published: January 2025

Abstract

Objective
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disorder that significantly impairs muscle regeneration following injuries, contributing to numerous complications and reduced quality of life. There is an urgent need for therapeutic strategies that can enhance muscle regeneration and alleviate these pathological mechanisms. In this study, we evaluate the therapeutic efficacy of W-GA nanodots, which are composed of gallic acid (GA) and tungstate (W6+), on muscle regeneration in type 2 diabetes mellitus (T2D)-induced muscle injury, with a focus on their anti-inflammatory and antioxidative effects.

Methods
This study synthesized ultrasmall W-GA nanodots that were optimized for improved stability and bioactivity under physiological conditions. In vitro assessments included cell viability, apoptosis, reactive oxygen species (ROS) generation, and myotube differentiation in C2C12 myoblasts under hyperglycemic conditions. In vivo, T2D was induced in C57BL/6 mice, followed by muscle injury and treatment with W-GA. Muscle repair, fibrosis, and functional recovery were assessed through histological analysis and gait analysis using the CatWalk system.

Results
The W-GA nanodots significantly enhanced muscle cell proliferation, decreased ROS, and reduced apoptosis in vitro. In vivo, compared with the control group, the W-GA-treated group exhibited notably improved muscle regeneration, decreased fibrosis, and enhanced functional recovery. The treatment notably modulated the inflammatory response and oxidative stress in diabetic muscle tissues, facilitating improved regenerative dynamics and muscle function.

Conclusions
W-GA nanodots effectively counter the pathological mechanisms of diabetic myopathy by enhancing regenerative capacity and reducing oxidative stress and inflammation. This nanomedicine approach offers a promising therapeutic avenue for improving muscle health and overall quality of life in individuals suffering from T2D. However, further studies are needed to explore the clinical applications and long-term efficacy of these nanodots in preventing diabetic complications.
New Insights into the Quality Control Strategies of Inula racemosa Hook. F. (Pushkarmula) and Saussurea lappa Decne. (Kuth): Medicinal Crops of Alpine Himalaya
Authors: Kumar Manish , Bhardwaj Rishabh , Kumar Anil , Kumar Dinesh 
Published: January 2025

Abstract
Adulteration and illegal trade of Saussurea lappa in the name of Inula racemosa is a major issue. Therefore, accurate and easy methods are required to control malpractice and define authenticity. The current study is focused on authenticating and defining quality control methods for I. racemosa and S. lappa. Reference and market samples of S. lappa and I. racemosa were used to develop methods, including high-performance thin layer chromatography (HPTLC), Gas chromatography–mass spectrometry (GC-MS) and (Ultra Performance Liquid Chromatography-Photo Diode Array (UPLC-PDA). Multivariate analysis was used to define variations among samples. Costunolide, dehydrocostus lactone, isoalantolactone and alantolactone were used to develop and validate the quality control method. Phytochemical investigations and filter paper reagent tests clearly differentiate between Saussurea and Inula. HPTLC and GC–MS fingerprints were found significant to certify both species. From a quality control perspective, the UPLC-PDA method was found significant for the separation of targeted molecules. Altantolactones were found higher in I. racemosa while costunolides in S. lappa, whereas market samples closely resembled with Inula species and confirmed as I. racemosa. The current findings suggested that filter paper tests could be useful for farmers, traders and industries to check the authenticity of S. lappa and I. racemosa. Chemical fingerprints and UPLC-PDA method were found sufficient to define quality of both the species.
Transition dynamics of hybrid farmers: a survival analysis of exits and entries into full-time farming
Authors: Johansson Eleanor , Nilsson Pia , Hansson Helena 
Published: January 2025

Abstract
Using Swedish-matched employer–employee data from 2001 to 2018 and parametric survival analysis, we examine how the share of off-farm wage income affects survival time in the state of hybrid farming. We find a non-linear relationship between the share of off-farm wage income and the risk of exit; at lower levels, the share of off-farm wage income increases the risk of exiting agriculture completely and exiting from hybrid farming into full-time farming, while at higher levels it decreases the risk of exiting the hybrid state. This indicates that at higher levels of off-farm income, hybrid farming can be a stable state.
The interplay between scion genotype, root microbiome, and Neonectria ditissima apple canker
Authors: McLean Hamish , Mikaberidze Alexey , Deakin Greg , Xu Xiangming , Papp-Rupar Matevz 
Published: January 2025

Abstract
Severity of European apple canker caused by Neonectria ditissima can vary between locations and apple genotypes. We investigated how location, cold storage/planting season, and apple scion genotype affect root-associated microbial communities. Additionally, we investigated whether differences in abundance of specific taxa could be associated with canker lesion counts. Seven scion cultivars grafted onto M9 rootstocks were inoculated with N. ditissima in the nursery and then planted in December 2018 or stored at 2 °C until planting in April 2019 at three sites in Kent, UK. We assessed canker lesions and collected root samples in June 2021. Quantitative PCR and 16S/ITS amplicon sequencing was used to analyse microbial communities. Site was the primary factor affecting microbiome size, diversity, and composition. Cold storage/planting season had small but significant effects, indicating that differences in the microbiome at planting can persist long-term. Scion genotype had a limited effect on diversity but did influence the abundance of specific root associated taxa. Bacterial α-diversity was associated with canker count in a site-dependent manner. Increased abundances of particular fungal (Rhizophagus irregularis and Epicoccum nigrum) and bacterial (Amycolatopsis and Bradyrhizobium) root associated taxa were associated with fewer cankers.