bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing roadway scenario classification through vision transformer features and decision tree algorithms
Authors: P P Anoop , R Deivanathan
Published: January 2025

Drivers face significant visibility challenges throughout the day and night due to varying environmental and lighting conditions. During the day, heavy rain and dense fog can severely reduce visibility, making it difficult to identify road markings and navigate safely. At night, the absence of natural light exacerbates visibility issues, and the intense glare from high-beam headlights further impairs focus of the driver which affects his reaction times. These challenges significantly increase the risk of accidents. To address these issues, modern vehicles are equipped with advanced systems such as front-mounted cameras and displays to improve road visibility. However, maintaining display clarity under adverse conditions remains a challenge for them. This study proposes a novel method for classifying roadway scenarios using Vision Transformer (ViT) features combined with decision-tree-based classifiers and applying tailored image enhancement algorithms for each scenario. The method effectively distinguishes between six road scenarios, including adverse weather and low-light conditions. Using Random Forest as the classification model, the proposed approach achieved a maximum accuracy of 96.60%, outperforming state-of-the-art methods. By accurately classifying scenarios and applying appropriate enhancement techniques, this approach improves road visibility and enhances driver safety.
Performance of heat transfer in Al2O3/MWCNT hybrid nanofluid flow using machine learning models
Authors: Tota Rakesh Kumar , Nagaraju Dora , Syed Javed , Mohammad Abdul Razack
Published: January 2025

This investigation diverges from traditional studies concentrating on single-component nanofluids, instead examining the thermophysical benefits of hybrid nanofluids, like Al2O3/MWCNT, aimed at improving thermal conductivity and heat transfer efficiency in passive systems. Machine learning is a promising solution for designing efficient heat exchangers by understanding intricate relationships and utilizing suitable modelling techniques. Numerical simulations were conducted to validate the benchmark results; later, passive techniques were incorporated into the numerical model to predict the heat transfer characteristics. The dataset derived from numerical simulation results is employed to train contemporary machine learning methodologies, including support vector regression (SVR), decision tree (DT), and random forest (RF). Data from experiments and CFD analysis were gathered for preprocessing and machine learning (ML) analysis. The preprocessing phase involved the application of a standard scaler operation to enhance accuracy levels. The models underwent validation using ten experimental data samples to assess their performance against statistical tool metrics. A higher thermal performance factor (ThPF) is observed with the divergent nozzle insert in the plain tube at 0.028 vol% of MWCNT/Al2O3 (HNF3) at Reynolds number 3093. R2 values of SVR, DT and RF are predicted as 0.95, 0.98 and 0.99, respectively, for the case of HNF3 fluid flowing through the divergent nozzle insert. The investigation broadens its conclusions to include improvements in passive heat transfer, encompassing extended surfaces and geometric alterations, offering practical guidance for developing advanced heat exchanger designs.
Solar parking lot capacity: an abundant dual-use alternative to meet demand for the renewable energy transition
Authors: Markwith Scott
Published: January 2025

Most utility-scale solar facilities (USSFs) in the United States (US) are planned or installed in grasslands, pastures, agriculture land, and timberland, with aggressive future expansion plans. Investor-owned electricity providers have lobbied aggressively to remove obstacles to approval of USSFs on agricultural lands and for limits on regulations that support distributed solar installation. Rural USSF expansion may have potentially significant local, state, and regional impacts on agricultural production and the economy, property values and affordability, and conservation of habitats, connectivity, and endangered species. The potential use of parking lots in urban and suburban areas for solar development to meet demands is poorly studied and parking lot solar has not gained much traction in the US. The objective of this research was to estimate whether solar photovoltaic (PV) systems installed in parking lots can meet electricity demands across multiple urban and suburban metropolitan areas within the US. Parking lot data across four municipalities with variation in latitude, solar radiation, and population density was obtained, along with modeled annual electricity demand by sector. Parking lot area and potential generating capacity was calculated for canopy and carport designs using standard and premium efficiency panels, and annual electricity production was estimated using the National Renewable Energy Laboratory’s PVWatts Calculator. Premium efficiency canopy designs can meet ∼100% of demand in some large car dependent low to medium density municipalities. High density urban areas may receive marginal direct benefit from parking lot solar development within their boundaries. Dual-use of lands without any ecosystem or productive value can substantially contribute to renewable energy mixes to meet demands.
Dispersion relations for rotational flows with exponential vorticity
Authors: Cao Feng , Yu Na , Zhang Jiachao
Published: January 2025

The aim of this short paper is to study the dispersion relations for two-dimensional steady gravity water waves with piecewise exponential vorticity distributions, by assuming that the waves propagate over a flat bed and without stagnation points.
Bernstein-Sato polynomial and related invariants for meromorphic functions
Authors: Àlvarez Montaner Josep , González Villa Manuel , León-Cardenal Edwin , Núñez-Betancourt Luis
Published: January 2025

We develop a theory of Bernstein-Sato polynomials for meromorphic functions. As a first application we study the poles of Archimedian local zeta functions for meromorphic germs. We also present a theory of multiplier ideals for meromorphic functions from the analytic and algebraic point of view. It is also shown that the jumping numbers of these multiplier ideals are related with the roots of the Bernstein-Sato polynomials.
From fragmentation to negotiation, 1851–1875
Authors: 6 Perri , Heims Eva
Published: January 2025

Following the neo-Durkheimian explanation’s structure, this chapter first analyses formal and informal social organization in government. It then shows how social organization shaped British policymaking on international telegraphy from the early 1850s to 1875. The chapter argues that in this period, fragmented buffering was slowly modified to allow more negotiated ordering of buffering between civilian commercial considerations in international telegraphy and security, naval, and military ones. Both forms of buffering help us to understand Britain’s decision to join the International Telegraph Union and how grudging commitment to the international regime emerged in British government. The chapter highlights the initial lack of capacity of the General Post Office (GPO) to handle international matters of telegraphy.
The zenith of parallel integration, 1903–1914
Authors: 6 Perri , Heims Eva
Published: January 2025

The zenith of parallel integrated buffering was achieved under the Liberal administration after 1905. Social organization among ministers was highly individualistically negotiated but within the machinery of government it was increasingly integrated and rule-based. The chapter shows how this shaped development in the highly complex plan for wartime cable-cutting in which the General Post Office (GPO) played a key role. The same GPO officials were also engaging closely with the International Telegraph Union (ITU) and intimately deepening cooperation with the German telegraph administration and working closely with their German counterparts in the 1913 submarine cable conference.
Trade Agreements Can Empower Women
Authors: Bahri Amrita
Published: January 2025

This chapter explores how trade agreements have addressed women’s concerns by analysing ten different approaches that are employed by countries to add women’s perspective in existing trade agreements. With the help of multiple practice examples from different regions, this chapter prepares a detailed menu of negotiating options for trade negotiators from across the globe. These approaches range from negotiating a stand-alone chapter on trade and women, legally binding provisions, and general affirmations to cooperative actions and policy carve-outs. The chapter also delves into the challenges and benefits of these approaches, highlighting the nuanced ways in which women’s participation in trade may be facilitated or hindered by these inclusions.
Revealing the Active Components and Therapeutic Targets of Sanao Decoction against Chronic Obstructive Pulmonary Disease Using Quantitative Analysis of Multi-Components by Single Marker and Network Pharmacology
Authors: Ji Wanli , Wang Jiahong , Huo Yan , Hu Cheng , Zhang Yifan
Published: January 2025

As a traditional Chinese medicine, Sanao decoction (SAD) has been used to treat chronic obstructive pulmonary disease (COPD) for multi-years. However, the potential mechanism and targets for its effects of SAD remain unknown. The 94 components of SAD were identified by UPLC–LTQ–Orbitrap MS. Meanwhile, the quantitative analysis of multi-components by single marker (QAMS) method was used to control the quality of SAD, including ephedrine hydrochloride, amygdalin, liquiritin, liquiritigenin, glycyrrhizic acid and glycyrrhetinic acid. The method was strictly validated with recovery (90.0–110.0%), precision [relative standard deviation (RSD), 0.79–2.01%], stability (RSD, 1.84–2.64%), repeatability (RSD, 0.45–3.03%) and relative correction factors (RSD, 0.28–2.67%), respectively. All the compounds showed good linearities (R2 > 0.999). Subsequently, 37 target proteins of SAD in the treatment of COPD were screened. The “Compounds-Targets” interaction and protein–protein interaction network found that TNF-α, IL-6 and VEGFA may act a crucial role in the treatment of COPD by SAD. Molecular docking demonstrated that TNF-α had good affinity with the main components of SAD. A strategy of QAMS and network pharmacology was a novel method to assess the quality control of SAD and uncover the targets and potential mechanism of SAD in the treatment of COPD.
Risk stratification for cardiovascular disease: a comparative analysis of cluster analysis and traditional prediction models
Authors: Yacaman Mendez Diego , Zhou Minhao , Brynedal Boel , Gudjonsdottir Hrafnhildur , Tynelius Per , Trolle Lagerros Ylva , Lager Anton
Published: January 2025

Aims

Primary prevention of cardiovascular disease (CVD) relies on effective risk stratification to guide interventions. Current models, primarily developed using regression analysis, can lead to inaccurate estimates when applied to external populations. This study evaluates the utility of cluster analysis as an alternative method for developing CVD risk stratification models, comparing its performance with established CVD risk prediction models.

Methods and results

Using data from 3416 individuals (mean age of 66 years and no prior CVD) followed for an average of 5.2 years for incidence of CVD, we developed a risk stratification model using cluster analysis based on established CVD risk factors. We compared our model to the Systematic COronary Risk Evaluation (SCORE2), the Pooled Cohort Equations (PCE), and the Predicting Risk of Cardiovascular Disease Events (PREVENT) models. We used Poisson and Cox regression to compare CVD risk between risk categories in each model. Predictive accuracy of the models was evaluated using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and C-statistic. During the study, 161 CVD events were detected. The high-risk cluster had a sensitivity of 59.0%, a PPV of 7.5%, a specificity of 64.2%, and NPV of 96.9% to predict CVD. Compared to the high-risk groups of the SCORE2, PCE, and PREVENT, the high-risk cluster had a high sensitivity and NPV, but a low specificity and PPV. No statistically significant differences were found in C-statistic between models.

Conclusion

Cluster analysis performed comparably to existing models and identified a larger high-risk group that included more individuals who developed CVD, although with more false positives. Further studies in larger, diverse cohorts are needed to validate the clinical utility of cluster analysis in CVD risk stratification.
Longitudinal Associations Between Neighborhood Environments and Functional Disabilities Among Community-Dwelling Older Adults in China
Authors: Zhou Jia-Jia , Zhou Shuai , Cai Xinxin , Luo Jiemei
Published: January 2025

Objectives

This study aims to investigate the longitudinal associations between neighborhood environments and functional disabilities over time among older adults in China. Urban–rural disparities in these associations were examined in this study.

Methods

Data from 4 waves of the China Health and Retirement Longitudinal Study (2011–2018) were analyzed, including a sample of 5,379 older adults aged 60 and over. Multilevel linear probability modeling was fitted to estimate the effects of neighborhood environments on functional disabilities, encompassing both incidence and rate of change over a 7-year period.

Results

Older adults residing in neighborhoods with superior infrastructure experienced a lower incidence of functional disabilities in both rural and urban areas. In urban communities, increased handicapped access was associated with a reduced risk of IADL disability onset among older adults (B = −0.013, SE = 0.006, p < .05). In rural villages, the presence of 2 or more bus lines was associated with a slower rate of IADL disablement over the 7-year period (B = −0.019, SE = 0.009, p < .05).

Discussion

This research reveals the prominent roles of neighborhood environments in protecting functional abilities among older adults. The findings highlight the importance of incorporating community policies and infrastructure development into public health considerations. Empirical evidence is provided for policymakers and urban planners aimed at enhancing functional abilities in older adults and mitigating urban–rural disparities in health outcomes.
Comparison of Referral Rates and Costs Using Fibrosis-4 and Enhanced Liver Fibrosis (ELF) Testing Strategies for Initial Evaluation of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) in a Veteran Population
Authors: Yeramaneni Samrat , Chang Stephanie T , Cheung Ramsey C , Chalfin Donald B , Sangha Kinpritma , Levy H Roma , Boltyenkov Artem T
Published: January 2025

Background

Global metabolic dysfunction-associated steatotic liver disease (MASLD) prevalence is estimated at 30% and projected to reach 55.7% by 2040. In the Veterans Affairs (VA) healthcare system, an estimated 1.8 million veterans have metabolic dysfunction-associated steatohepatitis (MASH).

Methods

Adult patients at risk for MASLD in a VA healthcare system underwent Fibrosis-4 (FIB-4) and Enhanced Liver Fibrosis (ELF®) testing. Referral rates and cost savings were compared among 6 noninvasive testing (NIT) strategies using these 2 tests independently or sequentially at various cutoffs.

Results

Enrolled patients (N = 254) had a mean age of 65.3 ± 9.3 years and mean body mass index (BMI) of 31.7 ± 6, 87.4% male: 78.3% were non-Hispanic/Latino, and 96.5% had type 2 diabetes mellitus (T2DM). Among the 6 evaluated strategies, using FIB-4 followed by ELF at a 9.8 cutoff yielded the highest proportion of patients retained in primary care without need of referral to hepatology clinic (165/227; 72.7%), and was associated with the lowest costs ($407.62). Compared to the FIB-4 only strategy, FIB-4/ELF with a 9.8 cutoff strategy resulted in 26% fewer referrals and 8.47% lower costs. In the subgroup of patients with BMI >32, there were 25.17% fewer referrals and costs were 8.31% lower.

Conclusions

Our study suggests that sequential use of ELF with a 9.8 cutoff following indeterminate FIB-4 tests results in lower referral rates and lower care costs in a veteran population at risk of MASLD. Adding ELF as a sequential test after indeterminate FIB-4 might help reduce the number of referrals and overall cost of care.
Time-lapse HR-pQCT reliably assesses and monitors local bone turnover in patients with chronic kidney disease
Authors: Zhou Minhao , Sadoughi Saghi , Go Lauren , Ramil Gabriella , Yu Isabel , Saeed Isra , Fan Bo , Wu Po-Hung , Salusky Isidro B , Nickolas Thomas L , Ix Joachim H , Kazakia Galateia J
Published: January 2025

Bone turnover assessment and monitoring are essential for chronic kidney disease (CKD)-associated bone care. Patients with CKD suffer from significantly elevated fracture risk due to abnormally high or low bone turnover, which benefits from diametrically opposite treatments informed by patient-specific bone turnover data. However, a reliable, accessible, noninvasive bone turnover assessment and monitoring tool remains an unmet clinical need. Combining time-lapse (TL) analysis with high-resolution peripheral quantitative computed tomography (HR-pQCT) scans obtained over time allows for in vivo temporospatial bone remodeling assessment. This study aimed to evaluate the feasibility of applying TL HR-pQCT to assess and monitor local bone formation and resorption in patients with CKD. A customized TL HR-pQCT pipeline was developed on a second-generation HR-pQCT platform and optimized using both ex vivo cadaveric phantom and in vivo scan-rescan HR-pQCT images. The annualized least significant changes in bone formation and resorption were evaluated using in vivo longitudinal reproducibility images. Finally, the feasibility of the TL HR-pQCT pipeline in assessing and monitoring bone turnover was evaluated in patients with end-stage kidney disease (ESKD; n = 9). We found that a 2-month TL period was sufficient for the TL HR-pQCT pipeline to reliably assess and monitor local bone turnover in a cohort of patients with ESKD. We also demonstrated the importance of characterizing TL HR-pQCT precision metrics using longitudinal baseline/follow-up rather than short-term scan-rescan datasets. The TL HR-pQCT pipeline assessed a range of bone formation metrics agreeing with the gold-standard histomorphometry bone formation reported in the literature for patients with CKD and ESKD. Our findings highlight that TL HR-pQCT holds promise as a “virtual bone biopsy” that reliably assesses and monitors local bone turnover for CKD bone care. Subsequent work will focus on validating this TL HR-pQCT pipeline against the gold-standard bone biopsy with quantitative histomorphometry.
The Y dwarf population with HST: unlocking the secrets of our coolest neighbours – II. Parallaxes and proper motions
Authors: Fontanive Clémence , Bedin Luigi R , Albert Loïc , Bardalez Gagliuffi Daniella C
Published: January 2025

We present astrometric results from a Hubble Space Telescope (HST) campaign aimed at determining precise distances for cold Y-type brown dwarfs. Combining observations from a dedicated HST/WFC3 programme with archival data, we derive astrometric solutions for 15 nearby Y dwarfs, by linking the high-precision relative astrometry from Hubble to the high-accuracy Gaia DR3 absolute reference system, using stars present in both to anchor the two frames of reference. We reach uncertainties on parallaxes below the 1-mas level for half of the sample, and down to 3 mas for two-thirds of the targets, or relative precisions <1  per cent in most cases and 2–5$\times$ improvements over previous measurements. For the remaining targets, we achieved slightly lower precisions on parallaxes (5–12 mas, 5–10  per cent), correlated with the lower signal-to-noise of the faintest targets. The precision reached in our derived proper motions is around 0.1–0.4 mas yr−1 for most targets, and up to 1–2 mas yr−1 for less precise cases. Our estimated parallaxes and proper motions are generally in good agreement with literature values, and consistent to 1–2$\sigma$ with recent Spitzer-derived parallaxes in most cases. These new astrometric solutions provide important validation of these objects’ distances and sky motions, especially given the large disparities seen in previous estimates. Our results demonstrate the power of HST combined with Gaia to measure highly precise absolute astrometry for faint brown dwarfs, and highlights the limitations reached for the reddest and coldest objects, for which JWST will certainly provide a favourable platform to improve these results.
Smuggling unnoticed: towards a 2D view of water and dust delivery to the inner regions of protoplanetary discs
Authors: Houge Adrien , Krijt Sebastiaan , Banzatti Andrea , Blake Geoffrey A , Pinilla Paola , Pontoppidan Klaus M , Trapman Leon , Williams Joe , Zhang Ke
Published: January 2025

Infrared spectroscopy, e.g. with JWST, provides a glimpse into the chemical inventory of the innermost region of protoplanetary discs, where terrestrial planets eventually form. The chemical make-up of regions inside snowlines is connected to the material drifting from the outer regions, which can be modelled with dust evolution models. However, infrared observations are limited by the high dust extinction in the inner disc, and only probes the abundances of gaseous species in the disc surface layers. As a result, the bulk mass of delivered volatiles is not directly relatable to what is measured through infrared spectra. In this paper, we investigate how the delivery of dust and ice after prolonged pebble drift affects the observable reservoir of water vapour in the inner disc. We develop a 1 + 1D approach based on dust evolution models to determine the delivery and distribution of vapour compared to the height of the $\tau = 1$ surface in the dust continuum. We find that the observable column density of water vapour at wavelengths probed by JWST spans many orders of magnitude over time, exhibiting different radial profiles depending on dust properties, drift rate, and local processing. In the presence of a traffic-jam effect inside the snowline, the observable vapour reservoir appears constant in time despite the ongoing delivery by pebble drift, such that water is effectively smuggled unnoticed. Differences in measured column densities then originate not only from variations in bulk vapour content, but also from differences in the properties and distribution of dust particles.
GENA-LM: a family of open-source foundational DNA language models for long sequences
Authors: Fishman Veniamin , Kuratov Yuri , Shmelev Aleksei , Petrov Maxim , Penzar Dmitry , Shepelin Denis , Chekanov Nikolay , Kardymon Olga , Burtsev Mikhail
Published: January 2025

Recent advancements in genomics, propelled by artificial intelligence, have unlocked unprecedented capabilities in interpreting genomic sequences, mitigating the need for exhaustive experimental analysis of complex, intertwined molecular processes inherent in DNA function. A significant challenge, however, resides in accurately decoding genomic sequences, which inherently involves comprehending rich contextual information dispersed across thousands of nucleotides. To address this need, we introduce GENA language model (GENA-LM), a suite of transformer-based foundational DNA language models capable of handling input lengths up to 36 000 base pairs. Notably, integrating the newly developed recurrent memory mechanism allows these models to process even larger DNA segments. We provide pre-trained versions of GENA-LM, including multispecies and taxon-specific models, demonstrating their capability for fine-tuning and addressing a spectrum of complex biological tasks with modest computational demands. While language models have already achieved significant breakthroughs in protein biology, GENA-LM showcases a similarly promising potential for reshaping the landscape of genomics and multi-omics data analysis. All models are publicly available on GitHub (https://github.com/AIRI-Institute/GENA_LM) and on HuggingFace (https://huggingface.co/AIRI-Institute). In addition, we provide a web service (https://dnalm.airi.net/) allowing user-friendly DNA annotation with GENA-LM models.
Communists and Black liberation movements: divergent trajectories in the United States and South Africa, 1939–1969
Authors: Paret Marcel , Levenson Zachary
Published: January 2025

In the 1920s, the Moscow-based Comintern began to promote a Black Communist movement, with specific emphasis on the United States and South Africa. Despite this common point of departure, the United States and South African Communist parties followed opposite trajectories. By the mid-20th century, the former dwindled as it grew increasingly detached from Black movements, while the latter developed a close relationship with the African National Congress, setting the stage for the party’s explosive growth in the post-apartheid period. To explain this divergence, we focus on what we call movement politics: the dynamic interaction among movements as they pursue particular political orientations and strategies. In the instances examined here, movement politics takes the form of a triangular relationship among three sets of actors: the international Communist movement, Black movements, and national Communist parties. We examine this dynamic interaction in two key conjunctures: first, during World War II, when loyalty to the Soviet Union proved to be an asset for the CPSA and a liability for the CPUSA; and second, during the Cold War, when South African Communists and Black movements converged on a politics of national liberation, while in the United States, Black movements turned to Third World liberation or anti-Communism as two alternatives to the CPUSA. These divergent trajectories reveal the period considered here, 1939 to 1969, as a critical juncture when American Communists became alienated from Black movements, while their counterparts in South Africa developed a lasting alliance with Black movements that persists to this day.
From Lesions to Lessons: Two Decades of Filamentous Plant Pathogen Genomics
Authors: Fagundes Wagner C. , Huang Yu-Seng , Häußler Sophia , Langner Thorsten
Published: January 2025

Filamentous plant pathogens pose a severe threat to food security. Current estimates suggest up to 23% yield losses to pre- and post-harvest diseases and these losses are projected to increase due to climate change (Singh et al. 2023; Chaloner et al. 2021; Stukenbrock and Gurr 2023; Fisher et al. 2012; Steinberg and Gurr 2020). Understanding how filamentous plant pathogens emerge, spread and adapt to their hosts and new environmental niches is crucial to address their devastating impact on global agriculture. Over the past two decades, genomics has emerged as a central technology to advance our understanding of the population dynamics and coevolution of filamentous plant pathogens. The first genome of a filamentous plant pathogen, the blast fungus Magnaporthe oryzae, was sequenced 20 years ago. Since then, plant pathogen genomics has not only provided a deep understanding of the genomic makeup of plant pathogen populations, but has emerged as a fundamental technology for gene discovery, disease diagnostics, and has accelerated molecular biology. In merely two decades, we have witnessed several revolutions in the field, including the first reference genomes of many filamentous plant pathogens, population scale genomics of thousands of individuals, long-read and chromosome conformation sequencing for highly continuous assemblies and recent intersections of genomics and structural biology. Here, we commemorate the 20th anniversary by presenting important technological advances (Fig. 1) and lessons we learned from the past two decades of filamentous plant pathogen genomics, with a focus on cereal diseases.
Apelin‐13 inhibits ischemia–reperfusion mediated podocyte apoptosis by reducing m‐TOR phosphorylation to enhance autophagy
Authors: Zheng Xiang , Chen Dongshan , Wu Jiyue , Gao Zihao , Huang Mingcong , Fan Chunmeng , Chang Jing , Liu Yu , Zeng Xiangjun , Wang Wei
Published: January 2025

Podocytes are essential to maintain the normal filtration function of glomerular basement membrane, which could be injured by ischemia–reperfusion. As complicated function of autophagy in terminal differentiated podocytes, autophagy dysfunction might contribute to I/R induced renal dysfunction following glomerular filtration membrane (GFM) injuries. Meanwhile, apelin‐13, an endogenous polypeptide, has been proved to be effective in regulating autophagy and apoptosis in podocytes. Therefore, it is hypothesized that apelin‐13 may protect podocytes from IRI by inhibiting podocyte apoptosis through regulation of podocyte autophagy. Our study demonstrates for that podocytes are also involved in renal ischemia–reperfusion (I/R) injury and shows in detail the morphological and functional changes in podocytes during renal I/R. Because podocytes are terminally differentiated cells whose homeostasis require high levels of autophagy, we investigate the cellular mechanisms underlying the effects of apelin‐13 on I/R‐mediated podocyte injury in terms of autophagy. In addition, our study demonstrates that apelin‐13 ameliorates renal I/R injury in podocyte injury, by increasing podocyte autophagy through inhibition of m‐TOR phosphorylation, which in turn inhibits apoptosis.
Consideration of the sensitivity of oral bacteria to ozone oxidation in the context of oral bacteria-related systemic diseases
Authors: Horiuchi Yasuhiro
Published: January 2025

Despite the abundance of oral care measures, periodontal disease, such as periodontitis, still cannot be overcome. It can sometimes progress to alveolar pyorrhea and even lead to tooth loss, and it is a problem that cannot be solved together with its oral bacteria. Recently, periodontal bacteria have attracted great interest because they can cause some systemic diseases, such as Alzheimer's disease. Nano-ozone water, which dissolved ozone nanobubble particles in water/saline, is also attracting attention as an adjunct therapeutic sterilizing agent for periodontal disease, but this does not completely cure periodontal disease. This indicates that some bacterial species are resistant to the mechanical sterilization effects of ozone oxidation. There is a demand for species classification based on susceptibility to ozone oxidation to identify causative bacteria. The morphology and cytoskeleton of oral bacteria, attachment system of pili and flagella, and susceptibility to ozone oxidation of cell wall components, such as peptidoglycans, as reported in the literature are discussed. The need to analyze the structural components of bacterial cell walls and appendages, and particularly their sensitivity to ozone oxidization, is increasing. If bacteria can be classified according to their sensitivity to ozone oxidation, it will be possible to identify strategies for treating periodontal diseases.
Does Parathyroid Autotransplantation Prevent Hypoparathyroidism after Thyroid Surgery?
Authors: Kasmirski Julia Adriana , Allahwasaya Ashba , Wu Christopher , Song Zhixing , Akhund Ramsha , Balachandra Sanjana , McLeod M Chandler , Gillis Andrea , Fazendin Jessica , Lindeman Brenessa , Chen Herbert
Published: January 2025

Objective:

To assess the impact of parathyroid gland autotransplantation on the restoration of parathyroid function in patients who are hypoparathyroid after thyroidectomy.

Background Data:

Hypoparathyroidism post-thyroidectomy arises when all parathyroid glands are devascularized or injured. Autotransplantation of compromised parathyroids aims to preserve their function and prevent permanent hypoparathyroidism. Despite routine use, comprehensive evidence on the efficacy of parathyroid autotransplantation remains limited.

Methods:

A retrospective analysis was conducted on 549 patients who underwent total or completion thyroidectomy from December 2015 to June 2023. Surgical outcomes of patients with and without parathyroid autotransplantation were compared. A subgroup analysis included patients with post-anesthesia care unit (PACU) parathyroid hormone (PTH) levels below 10 units. Statistical analyses included the Chi-squared test and multivariable analysis.

Results:

Of the 549 patients, 152 (27.7%) had parathyroid autotransplantation and 397 (72.3%) did not. The groups were similar in demographics and underlying thyroid etiologies. No significant difference was found in intraoperative parathyroid identification rates (P=0.25). Postoperatively, autotransplanted patients had a higher incidence of transient symptomatic hypocalcemia at 2 weeks (38.0% vs. 19.3%, P<0.001). Multivariable regression showed a higher frequency of postoperative transient hypocalcemia with autotransplantation (IRR=1.90, 95% CI: 1.42-2.54, P<0.001). Among patients with PACU PTH<10 units, recovery rates of parathyroid function were similar between treatment groups (82.2% vs. 82.5%, P=0.46). Long-term follow-up showed comparable low incidence of parathyroid insufficiency in both groups (5.3% vs. 3.8%, P=0.46).

Conclusions:

Parathyroid autotransplantation does not enhance recovery in hypoparathyroid patient’s post-thyroidectomy and does not significantly alter outcomes among patients with PACU PTH<10 .
Adherence to Recommendations and Yield of Critical Care EEG Monitoring: A Prospective Multicentric Study
Authors: Bellante Flavio , Santos Susana Ferrao , Gérard Ludovic , Jacquet Luc-Marie , Piagnerelli Michaël , Taccone Fabio , Thooft Aurélie , Wittebole Xavier , Legros Benjamin , Gaspard Nicolas
Published: January 2025

Purpose:

The American Clinical Neurophysiology Society has provided a set of recommendations on the use of critical care EEG monitoring (CEEG). However, these recommendations have not been prospectively validated. We aimed to assess the adherence to the American Clinical Neurophysiology Society recommendations for obtaining CEEG for different indications and the yield of obtained CEEG according to these different indications.

Methods:

This was a multicenter prospective observational study of critically ill adult patients between April 01, 2022, and June 22, 2022, in two academic medical centers and a large teaching hospital. Indications for CEEG, according to the American Clinical Neurophysiology Society recommendations, were determined based on clinical data at the time of discharge from the intensive care unit. The use of CEEG and detection of electrographic seizures were retrieved from the EEG databases.

Results:

A total of 600 patients were enrolled in this study. The primary admission diagnoses were medical (49%), surgical (30%), or neurologic/neurosurgical (21%). Approximately 60% of patients had an altered mental status. A few (6%) patients had a preceding clinical seizure, and 1% had generalized convulsive status epilepticus. Indications were identified in 226 admissions. Of these patients, 88 (39%) underwent CEEG. In addition, 12 patients underwent CEEG without clear indications. Of the 100 patients, 33 (33%) had electrographic seizures. Adherence to recommendations and yields was highest for refractory status epilepticus, altered mental status after any clinical seizure, and acute brain injury. Adherence and yield varied the most and were inversely correlated in the group of patients without acute brain injury, suggesting that additional clinical factors may have contributed to patient selection.

Conclusions:

Patients meeting American Clinical Neurophysiology Society indications and receiving CEEG had a high seizure risk. Emerging CEEG programs should focus on epilepsy-related and neurologic diagnosis. Although recommendations effectively identify groups of patients with a high seizure risk, additional clinical factors might further help select candidates in the low-risk group.
Active invisible metamaterial of elastic waves with double targets in a thick plate
Authors: Jiang Jing-Wei , Wang Yi-Ze
Published: January 2025

Wave invisibility has received increasing attention due to its great theoretical value and application to aerospace, military and other fields. In this work, the invisible flexural cloak for double hole targets in an elastic thick plate is proposed and proportional integral derivative (PID) active control is applied. Based on Mindlin thick plate theory and wave function expansion method, the wave equation for the thick plate is derived and scattering mode coefficients are obtained. The influences of structural and material parameters on dynamic stress concentration, scattering amplitude and scattering cross section (SCS) for double targets are investigated. With the consideration of specific hole targets, the cloaking configuration includes cloaks 1 and 2 and consists of periodically arranged piezoelectric (PZT) patches. Every PZT patch is attached to the active circuit with PID control function. The theoretical and experimental results illustrate that the cloak can achieve an invisible function for double targets within multiple frequency regions. On the other hand, the cloak can reduce the dynamic stress concentration, scattering amplitude and SCS of the thick plate. Different from the original structure without control, the effective frequency range of the PID active cloak can be widely extended.
An integrated systems biology approach establishes arginine biosynthesis as a metabolic weakness inCandida albicansduring host infection
Authors: Chakraborty Shuvechha , Palanikumar Indumathi , Gune Yash , Venkatesh K.V. , Raman Karthik , Idicula-Thomas Susan
Published: January 2025

Candida albicans(CAL), one of the leading causes of fungal infections affecting nearly 70% of the population, poses a significant global health threat. With the emergence of drug-resistant strains, mortality rates have reached a staggering 63.6% in severe cases, complicating treatment options and demanding the discovery of novel therapeutic targets. To address this pressing need, we employed a unique multidisciplinary approach to elucidate the metabolic pathways that enable CAL to switch from a commensal to a virulent state. Condition-specific genome-scale metabolic models (GSMMs), along with a novel integrated host-CAL model developed in this study, highlighted the central role of arginine (Arg) metabolism and uncoveredALT1, an arginine biosynthesis enzyme, as a critical metabolic vulnerability in CAL virulence. Heightened expression of arginine biosynthesis genes indicated that increased arginine synthesis mainly occurs through proline intermediates during host interaction. Significantly impaired virulence andin vivopathogenicity ofALT1-deleted CAL highlighted the potential of targeting arginine metabolism as a novel strategy to combat antifungal resistance and underscored the power of integrating systems biology with experimental approaches in identifying new therapeutic targets.

Graphical abstract
Autoimmune regulator deficiency causes sterile epididymitis and impacts male fertility through disruption of inorganic physiology
Authors: Ahn Soo Hyun , Halgren Katrina , Grzesiak Geoffrey , MacRenaris Keith W. , Sue Aaron , Xie Huirong , Demireva Elena , O’Halloran Thomas V. , Petroff Margaret G.
Published: January 2025

Autoimmune regulator (AIRE), a transcription factor expressed by medullary thymic epithelial cells, is required for shaping the self-antigen tolerant T cell receptor repertoire. Humans with mutations inAIREsuffer from Autoimmune Polyglandular Syndrome Type 1 (APS-1). Among many symptoms, men with APS-1 commonly experience testicular insufficiency and infertility, but the mechanisms causing infertility are unknown. Using anAire-deficient mouse model, we demonstrate that male subfertility is caused by sterile epididymitis characterized by immune cell infiltration and extensive fibrosis. In addition, we reveal that the presence of autoreactive immune cells and inflammation in epididymides ofAire-deficient mice are required for iron (Fe) deposition in the interstitium, which is brought on by macrophages. We further demonstrate that male subfertility is associated with a decrease in metals zinc (Zn), copper (Cu), and selenium (Se) which serve as cofactors in several antioxidant enzymes. We also show increase in DNA damage of epididymal sperm ofAire-/-animals as a key contributing factor to subfertility. The absence ofAireresults in autoimmune attack of the epididymis leading to fibrosis, Fe deposition, and Cu, Zn and Se imbalance, ultimately resulting in sperm DNA damage and subfertility. These results highlight the requirement ofAireto promote immune tolerance throughout the epididymis, disruption of which causes an imbalance of inorganic elements with resulting consequence on male fertility.

Key points

Breakdown of epididymal self-tolerance promotes disruption of inorganic elements. Autoimmunity causes interstitial fibrosis resulting in sperm DNA damage and subfertility. Elevated interstitial iron and macrophages contribute to fibrosis.
Predicting Car Accident Severity in Northwest Ethiopia: A Machine Learning Approach Leveraging Driver, Environmental, and Road Conditions
Authors: Mengistu Abraham Keffale , Gedefaw Andualem Enyew , Baykemagn Nebebe Demis , Walle Agmasie Damtew , Yehuala Tirualem Zeleke , Alemayehu Meron Asmamaw , Messelu Mengistu Abebe , Assaye Bayou Tilahun
Published: January 2025

Background

Car accidents in Northwest Ethiopia have significantly increased in severity, with increasing impacts on public safety. This study aims to predict car accident severity in the region by considering driver behavior, environmental conditions, and road characteristics, utilizing machine learning models to enhance traffic safety measures.

Methods

This study used a dataset comprising accident records, weather conditions, road types, traffic volume, and driver characteristics. Various machine learning models, including logistic regression, decision trees, random forests, gradient boosting, XGBoost, LightGBM, support vector machines, K-nearest neighbors, multilayer perceptron (neural networks), and naive Bayes, have been employed to predict accident severity. Model performance was assessed in terms of accuracy, precision, recall, and the F1 score.

Results

Driver-related factors, including age and behavior, were found to significantly influence accident severity. Environmental factors, such as weather and road type, also play crucial roles in determining outcomes. Among the evaluated models, the random forest classifier demonstrated superior performance, achieving an initial accuracy of 78% in predicting fatal accidents. Its performance was improved to 82% through hyperparameter tuning, highlighting its strong predictive ability.

Conclusions

This research highlights the importance of environmental and driver-related factors in predicting accident severity in Northwest Ethiopia. The random forest model proves to be an effective tool for forecasting accident severity, which could inform policies and interventions to improve road safety in the region. Future work should focus on expanding the dataset and exploring additional models for better prediction accuracy.
Contrastive Learning for Omics-guided Whole-slide Visual Embedding Representation
Authors: Yu Suwan , Kim Yooeun , Kim Hoeyoung , Lee Sangseon , Kim Kwangsoo
Published: January 2025

While computational pathology has transformed cancer diagnosis and prognosis prediction, existing computational methods remain limited in their ability to decipher the complex molecular characteristics within tumors. We present CLOVER (Contrastive Learning for Omics-guided whole-slide Visual Embedding Representation), a novel deep learning framework that leverages self-supervised contrastive learning to integrate multi-omics data (genomics, epigenomics, and transcriptomics) with slide representations, connecting the morphological and molecular features of tumors. Using the breast cancer cohorts comprising diagnostic slides and multi-omics paired data from 610 breast cancer patients, we validated CLOVER’s excellence by demonstrating its ability to generate effective slide-level representations that consider molecular states of cancer. CLOVER outperforms existing methods in few-shot learning scenarios, particularly in cancer subtype classification and clinical biomarker prediction tasks (ER, PR, and HER2 status). Through comprehensive interpretability analysis, we identified tumor microenvironment components within slides and revealed molecular features associated with breast cancer. Our results demonstrate that CLOVER enables detailed molecular characterization from single slide analysis, suggesting its potential for effective utilization in future cancer diagnosis and prognosis prediction studies.
Atlas of the Bacterial Serine-Threonine Kinases expands the functional diversity of the kinome
Authors: O’Boyle Brady , Yeung Wayland , Lu Jason D. , Katiyar Samiksha , Yaron-Barir Tomer M. , Johnson Jared L. , Cantley Lewis C. , Kannan Natarajan
Published: January 2025

Bacterial serine-threonine protein kinases (STKs) regulate diverse cellular processes associated with cell growth, virulence, and pathogenicity. They are evolutionarily related to the druggable eukaryotic STKs. However, an incomplete knowledge of how bacterial STKs differ from their eukaryotic counterparts and how they have diverged to regulate diverse bacterial signaling functions presents a bottleneck in targeting them for drug discovery efforts. Here, we classified over 300,000 bacterial STK sequences from the NCBI RefSeq non-redundant and UniProt protein databases into 35 canonical and seven non-canonical (pseudokinase) families based on the patterns of evolutionary constraints in the conserved catalytic domain and flanking regulatory domains. Through statistical comparisons, we identified distinguishing features of bacterial STKs, including a distinctive arginine residue in a regulatory helix (C-Helix) that dynamically couples ATP and substrate binding lobes of the kinase domain. Biochemical and peptide-library screens demonstrated that constrained residues contribute to substrate specificity and kinase activation in theMycobacterium tuberculosiskinase PknB. Collectively, these findings open new avenues for investigating bacterial STK functions in cellular signaling and for the development of selective bacterial STK inhibitors.
Percolation and lifestyle transition in microbial metabolism
Authors: Supo-Escalante Rydberg , Plata Germán , Usmanova Dinara R. , Vitkup Dennis
Published: January 2025

Microbial species exhibit a remarkable diversity in their metabolic properties, genome composition, and ecological distribution. A central challenge of systems biology is to understand the relationships between genomic, metabolic, and phenotypic properties of bacteria. However, it is currently not well understood how the structure of metabolic network defines and reflects the lifestyle of diverse bacterial species across the tree of life. By analyzing thousands of genome-scale metabolic models of bacteria, we found a percolation-like transition in their ability to grow on independent carbon sources at around 800 metabolic reactions or about 2000 protein-coding genes. The observed transition is characterized by significant changes in metabolic network functional connectivity primarily associated with the completion of central carbon metabolism and the TCA cycle. Strikingly, experimentally observed phenotypic properties of bacteria also exhibit two markedly different regimes below and above the transition. Species with metabolic network sizes below the transition are typically obligate symbionts and require complex minimal media for their growth. In contrast, species with networks above the transition are primarily free- living generalists. The observed percolation transition is also reflected in multiple other genomic properties, such as a substantial decrease in the fraction of regulatory genes below the transition and higher evolvability for new metabolic phenotypes above the transition. Furthermore, we find that the distribution of bacterial genome sizes from unbiased environmental metagenomic sequencing also reflects genomic clusters corresponding to the observed transition. Overall, our work identifies two qualitatively different regimes in microbial metabolism and lifestyles characterized by distinct structural and functional properties of their metabolic networks.