bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adipokine secretion and lipolysis following gender-affirming treatment in transgender individuals
Authors: Subramanian N. , Wiik A. , Rullman E. , Melin M. , Lundberg T. R. , Flanagan J. , Holmberg M. , Dekanski A. , Dhejne C. , Arver S. , Gustafsson T. , Laurencikiene J. , Andersson D. P. 
Published: March 2024

Abstract
Background
The organ-specific effects of gender-affirming sex hormone treatment (GAHT) in transgender women (TW) and transgender men (TM) are insufficiently explored. This study investigated the effects of GAHT on adipose tissue function.

Methods
In a single-center interventional prospective study, 32 adults undergoing GAHT, 15 TW and 17 TM, were examined with anthropometry and abdominal subcutaneous adipose tissue biopsies obtained before initiation of treatment, 1 month after endogenous sex hormone inhibition and three and 11 months after initiated GAHT. Fat cell size, basal/stimulated lipolysis and cytokine secretion in adipose tissue were analyzed.

Results
TW displayed an increase in complement component 3a and retinol-binding protein 4 (RBP4) secretion after sex hormone inhibition, which returned to baseline following estradiol treatment. No changes in lipolysis were seen in TW. TM showed downregulation of RBP4 after treatment, but no changes in basal lipolysis. In TM, the estrogen suppression led to higher noradrenaline stimulated (NA) lipolysis that was normalized following testosterone treatment. At 11 months, the ratio of NA/basal lipolysis was lower compared to baseline. There were no significant changes in fat cell size in either TW or TM.

Conclusion
In TW, gonadal hormone suppression results in transient changes in cytokines and in TM there are some changes in NA-stimulated lipolysis following testosterone treatment. However, despite the known metabolic effects of sex hormones, the overall effects of GAHT on adipose tissue function are small and likely have limited clinical relevance, but larger studies with longer follow-up are needed to confirm these findings.

Trial registration
ClinicalTrials.gov Identifier: NCT02518009, Retrospectively registered 7 August 2015.
Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach
Authors: Xing J. , Dong K. , Liu X. , Ma J. , Yuan E. , Zhang L. , Fang Y. 
Published: March 2024

Abstract
Background
Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can enhance these outcomes.

Methods
We conducted a study on a cohort of 3467 pregnant women during their pregnancy, with a total of 5649 clinical and biochemical records collected. We utilized this dataset as our training dataset to develop a web server called GDMPredictor. The GDMPredictor utilizes advanced machine learning techniques to predict the risk of GDM in pregnant women. We also personalize treatment recommendations based on essential biochemical indicators, such as A1MG, BMG, CysC, CO2, TBA, FPG, and CREA. Our assessment of GDMPredictor's effectiveness involved training it on the dataset of 3467 pregnant women and measuring its ability to predict GDM risk using an AUC and auPRC.

Results
GDMPredictor demonstrated an impressive level of precision by achieving an AUC score of 0.967. To tailor our treatment recommendations, we use the GDM risk level to identify higher risk candidates who require more intensive care. The GDMPredictor can accept biochemical indicators for predicting the risk of GDM at any period from 1 to 24 weeks, providing healthcare professionals with an intuitive interface to identify high-risk patients and give optimal treatment recommendations.

Conclusions
The GDMPredictor presents a valuable asset for clinical practice, with the potential to change the management of GDM in pregnant women. Its high accuracy and efficiency make it a reliable tool for doctors to improve patient outcomes. Early identification of high-risk individuals and tailored treatment can improve maternal and fetal health outcomes http://www.bioinfogenetics.info/GDM/.
Lightweight camouflaged object detection model based on multilevel feature fusion
Authors: Li Qiaoyi , Wang Zhengjie , Zhang Xiaoning , Du Hongbao 
Published: March 2024

AbstractThe intrinsic similarity between camouflaged objects and background environment impedes the automatic detection/segmentation of camouflaged objects, and novel network architectures for deep learning are promising to overcome this challenge and improve detection accuracy. However, these existing network architectures for distinguishing between camouflaged objects and their backgrounds do not account for the constraint of detection speed, which results in high computational complexity and the inability to meet the requirements of rapid detection. Therefore, based on the human visual system, this study proposes a single-stage lightweight camouflage object detection network using multilevel feature fusion, integrating features of various feature layers and receptive field sizes. Using three benchmark datasets for normal camouflaged objects, the lightweight network (LINet) model demonstrated an accuracy superior to those of six existing mainstream camouflaged object detection methods. Its detection speed, 126.3 frames per second, is significantly higher than those of the existing mainstream methods, enabling rapid detection with a maximum increase of 187.62%. The accuracy of LINet is the minimum and maximum for Resnet101 and Resnet152, respectively. These findings pave the way for diverse applications of camouflaged target detection algorithms.
New fungicides for managing Phytophthora diseases of tree crops with foliar and soil applications
Authors: Adaskaveg James E. , Förster Helga , O’Fallon Chaydon 
Published: March 2024

AbstractFour new modes of action, oxathiapiprolin, fluopicolide, mandipropamid, and ethaboxam, have or are pending registrations on multiple tree crops in the USA including avocado, citrus, almond (and other tree nuts), and stone fruits to be used in sustainable anti-resistance rotation and mixture programs for managing Phytophthora diseases. All four fungicides are highly toxic in vitro against species of Phytophthora from different tree crops. Efficacy of foliar applications of oxathiapiprolin and mandipropamid for the management of citrus brown rot persisted for over 10 weeks. Still, residues could be removed to non-detectable levels by postharvest washing and brushing of fresh-market fruit. The four fungicides were highly effective in reducing root rot and crown/trunk cankers on tree crops and demonstrated acropetal systemic movement through the xylem after soil application and absorption by almond, citrus, and cherry roots. This was substantiated by reduced lesion size in stem inoculations of potted trees that were treated by soil applications or by in vitro bioassays and HPLC–MS–MS analyses of root, stem, and leaf extracts. Using an adapted Bromilow model that is based on the partition coefficient logP that indicates the lipo- or hydrophilicity and the acid dissociation constant pKa, mobility of ethaboxam, fluopicolide, mandipropamid, and oxathiapiprolin in plants was predicted, and this was supported by our studies. Mandipropamid and a mandipropamid–oxathiapiprolin pre-mixture are now registered as foliar applications for managing citrus brown rot, whereas oxathiapiprolin and fluopicolide are registered, and ethaboxam is pending registration as soil applications to control citrus root rot. Oxathiapiprolin has also been registered for soil use on almond and other nut crops, as well as avocado, and soil applications of mandipropamid are planned to be restricted to nursery use of multiple crops.
“Just Did The Best That I Could Do”: CPS Social Workers’ Perceptions of Self-Efficacy in Legal Aspects
Authors: Bates Michelle E. , Campbell Erica , Lewinson Terri 
Published: March 2024

AbstractChild protective services (CPS) social workers assess safety and risk needs during abuse and neglect investigations to determine if legal interventions are needed. However, only 60% of abuse and neglect cases have safety and risk assessed during the investigatory process in North Carolina. This study aimed to explore the perceptions of self-efficacy among rural North Carolina CPS social workers in child abuse and neglect investigations. Understanding CPS social workers’ perceptions of self-efficacy and factors that may influence their self-efficacy is vital to improving job satisfaction, retention, and the legal and investigative processes relating to child abuse and neglect. A purposive sampling approach was used to recruit nine CPS social workers in rural counties in North Carolina. Through a process of open, axial, and selective coding, we conclude that a CPS social worker’s self-efficacy is impacted by factors relating to leadership and legal teams, longevity, previous social work experience, and paperwork and caseload demands.
Using Yield and Entropy-Based Characteristics for Circular Economy
Authors: Compart Fred , Gräbner Martin 
Published: March 2024

AbstractEnvironmental impacts of the extant linear carbon economy and aspects of conservation of resources demand a transformation to a circular carbon economy (CCE). In view of this transformation, carbon-containing plastic products should be reused and recycled to prevent or minimize the release of their carbon content into the environment. Different plastic waste feedstock recycling strategies are applicable, with different degrees of feedstock destruction, depending on the degree of degradation and contamination of the intended recycle fractions. The evaluation of the effectiveness of recycling processes by substance and carbon-based yield and entropic characteristics could be a part of the overall evaluation strategy for recycling processes. Possible principles and base equations of such substance and carbon-based yield and entropic characteristics, extracted from the literature and adapted, are delineated in this article. Substance-based characteristics could be applied for physical recycling processes in which the aspired recovery substances remain preserved and are physically separated. A resort to carbon-based characteristics could be practiced for recycling and combustion processes, in which the feedstock is chemically destroyed, and new substances are possibly synthesized. Stylized process examples depict the way of a joint usage of yield and entropic characteristics.
Uncovering Current and Future Variations of Irrigation Water Use Across China Using Machine Learning
Authors: Liu Kai , Bo Yong , Li Xueke , Wang Shudong , Zhou Guangsheng 
Published: March 2024

AbstractAccurately characterizing changes in irrigation water use (IWU) is crucial for formulating optimal water resource allocation policies, particularly in the context of climate change. However, existing IWU estimation methods suffer from uncertainties due to limited data availability and model constraints, restricting their applicability on a national scale and under future climate change scenarios. We present a robust framework leveraging machine learning and multiple data sets to estimate IWU across China. Forced with an ensemble of climate and socio‐economic projections, we appraise future trends and additional costs of IWU. Our model shows high accuracy in reproducing IWU, with coefficient of determination (R2) ranging from 0.86 to 0.91 and root mean square error from 0.261 to 0.361 km3/yr when compared to reported values in Chinese prefectures. Independent validation at 11 cropland sites further confirms the model's predictive power (R2 = 0.67). Under different emissions scenarios, China's IWU is projected to increase by 8.5%–17.1% (6.8%–34.8%) by 2050s (2100s) compared to the historical period (1981–2010), with higher emissions leading to more significant increases. This rise in IWU by 2050s (2100s) comes with an estimated additional cost of US $1.65–3.91 ($2.28–6.5) billion/year, highlighting the urgency for sustainable water management. Our study provides an effective approach for estimating current and future IWU using machine learning techniques, transferable to other countries facing increasing irrigation demands.
Integrating Trait‐Based Stoichiometry in a Biogeochemical Inverse Model Reveals Links Between Phytoplankton Physiology and Global Carbon Export
Authors: Sullivan Megan R. , Primeau François W. , Hagstrom George I. , Wang Wei‐Lei , Martiny Adam C. 
Published: March 2024

AbstractThe elemental ratios of carbon, nitrogen, and phosphorus (C:N:P) within organic matter play a key role in coupling biogeochemical cycles in the global ocean. At the cellular level, these ratios are controlled by physiological responses to the environment. But linking these cellular‐level processes to global biogeochemical cycles remains challenging. We present a novel model framework that combines knowledge of phytoplankton cellular functioning with global scale hydrographic data, to assess the role of variable carbon‐to‐phosphorus ratios (RC:P) on the distribution of export production. We implement a trait‐based mechanistic model of phytoplankton growth into a global biogeochemical inverse model to predict global patterns of phytoplankton physiology and stoichiometry that are consistent with both biological growth mechanisms and hydrographic carbon and nutrient observations. We compare this model to empirical parameterizations relating RC:P to temperature or phosphate concentration. We find that the way the model represents variable stoichiometry affects the magnitude and spatial pattern of carbon export, with globally integrated fluxes varying by up to 10% (1.3 Pg C yr−1) across models. Despite these differences, all models exhibit strong consistency with observed dissolved inorganic carbon and phosphate concentrations (R2 > 0.9), underscoring the challenge of selecting the most accurate model structure. We also find that the choice of parameterization impacts the capacity of changing RC:P to buffer predicted export declines. Our novel framework offers a pathway by which additional biological information might be used to reduce the structural uncertainty in model representations of phytoplankton stoichiometry, potentially improving our capacity to project future changes.
Modeling the Contribution of Precipitation Loss to a Radiation Belt Electron Dropout Observed by Van Allen Probes
Authors: Li Zhi‐Gu , Tu Weichao , Selesnick Richard , Huang Jinbei 
Published: March 2024

AbstractA drift‐diffusion model is used to simulate the low‐altitude electron distribution, accounting for azimuthal drift, pitch angle diffusion, and atmospheric backscattering effects during a rapid electron dropout event on 21st August 2013, at L = 4.5. Additional external loss effects are introduced during times when the low‐altitude electron distribution cannot be reproduced by diffusion alone. The model utilizes low‐altitude electron count rate data from five POES/MetOp satellites to quantify pitch angle diffusion rates. Low‐altitude data provides critical constraint on the model because it includes the drift loss cone region where the electron distribution in longitude is highly dependent on the balance between azimuthal drift and pitch angle diffusion. Furthermore, a newly derived angular response function for the detectors onboard POES/MetOp is employed to accurately incorporate the bounce loss cone measurements, which have been previously contaminated by electrons from outside the nominal field‐of‐view. While constrained by low‐altitude data, the model also shows reasonable agreement with high‐altitude data. Pitch angle diffusion rates during the event are quantified and are faster at lower energies. Precipitation is determined to account for all of the total loss observed for 450 keV electrons, 88% for 600 keV and 38% for 900 keV. Predictions made in the MeV range are deemed unreliable as the integral energy channels E3 and P6 fail to provide the necessary constraint at relativistic energies.
Signature of Mesoscale Eddies on Air‐Sea Heat Fluxes in the North Indian Ocean
Authors: Chen Yanxu , Yu Lisan 
Published: March 2024

AbstractUsing a combination of 20‐year (1999–2018) remotely‐sensed air‐sea heat flux products and altimeter‐based eddy atlas, we investigate the signature of mesoscale eddies on sea surface temperature (SST) and air‐sea turbulent latent and sensible fluxes, or simply, turbulent heat fluxes (THFs), in the North Indian Ocean. On average, eddy‐induced THF feedback can approach ∼40 W m−2 k−1 for warm‐core anticyclones (AEs) and ∼28 W m−2 k−1 for cold‐core cyclones (CEs) at their extreme values. In addition to these conventional SSH‐SST coherent eddies and their imprints as monopoles in heat fluxes, a comparable proportion of SSH‐SST incoherent eddies (cold‐AEs and warm‐CEs) are surprisingly active in this region, which offset the monopolar paradigm of coherent eddy‐induced THF anomalies or develop a dipole structure when combined with these conventional eddies. In terms of seasonality, the aggregation of SSH‐SST coherent and incoherent eddies in the Arabian Sea develops concentrated monopoles within eddy contours in both summer and winter, with a damped THF located farther away from the eddy core in winter. In the Bay of Bengal, a strong compensation between SSH‐SST coherent and incoherent eddies is observed in summer that leads to null net fluxes, while the winter‐time THF composite of these two eddy types displays a dipolar structure which was described as eddy‐stirring effect in the literature.
Integration of whole-exome sequencing and structural neuroimaging analysis in major depressive disorder: a joint study
Authors: Oh Eun-Young , Han Kyu-Man , Kim Aram , Kang Youbin , Tae Woo-Suk , Han Mi-Ryung , Ham Byung-Joo 
Published: March 2024

AbstractMajor depressive disorder (MDD) is a common mental illness worldwide and is triggered by an intricate interplay between environmental and genetic factors. Although there are several studies on common variants in MDD, studies on rare variants are relatively limited. In addition, few studies have examined the genetic contributions to neurostructural alterations in MDD using whole-exome sequencing (WES). We performed WES in 367 patients with MDD and 161 healthy controls (HCs) to detect germline and copy number variations in the Korean population. Gene-based rare variants were analyzed to investigate the association between the genes and individuals, followed by neuroimaging-genetic analysis to explore the neural mechanisms underlying the genetic impact in 234 patients with MDD and 135 HCs using diffusion tensor imaging data. We identified 40 MDD-related genes and observed 95 recurrent regions of copy number variations. We also discovered a novel gene, FRMPD3, carrying rare variants that influence MDD. In addition, the single nucleotide polymorphism rs771995197 in the MUC6 gene was significantly associated with the integrity of widespread white matter tracts. Moreover, we identified 918 rare exonic missense variants in genes associated with MDD susceptibility. We postulate that rare variants of FRMPD3 may contribute significantly to MDD, with a mild penetration effect.
SLC26A9 promotes colorectal tumorigenesis by modulating Wnt/β-catenin signaling
Authors: Zhang Minglin , Ma Zhiyuan , Yi Zhiqiang , Wang Hu , Zhu Jiaxing , Wen Guorong , Jin Hai , An Jiaxing , Deng Zilin , Tuo Biguang , Li Taolang , Liu Xuemei 
Published: March 2024

AbstractSolute carrier family 26 member 9 (SLC26A9) is a member of the Slc26a family of multifunctional anion transporters that functions as a Cl- channel in parietal cells during acid secretion. We explored the role of SLC26A9 in colorectal cancer (CRC) and its related mechanisms through clinical samples from CRC patients, CRC cell lines and mouse models. We observed that SLC26A9 was expressed at low levels in the cytoplasm of adjacent tissues, polyps and adenomas but was significantly increased in colorectal adenocarcinoma. Moreover, increased levels of SLC26A9 were associated with a high risk of disease and poor prognosis. In addition, downregulation of SLC26A9 in CRC cells induced cell cycle arrest and apoptosis but inhibited cell proliferation and xenograft tumor growth both in vitro and in vivo. Mechanistic analysis revealed that SLC26A9 was colocalized with β-catenin in the nucleus of CRC cells. The translocation of these two proteins from the cytoplasm to the nucleus reflected the activation of Wnt/β-catenin signaling, and promoted the transcription of downstream target proteins, including CyclinD1, c-Myc and Snail, but inhibited the expression of cytochrome C (Cyt-c), cleaved Caspase9, cleaved Caspase3 and apoptosis-inducing factor (AIF). CRC is accompanied by alteration of epithelial mesenchymal transition (EMT) markers. Meanwhile, further studies showed that in SW48 cells, overexpressing SLC26A9 was cocultured with the β-catenin inhibitor XAV-939, β-catenin was downregulated, and EMT was reversed. Our study demonstrated SLC26A9 may be responsible for alterations in the proliferative ability and aggressive potential of CRC by regulating the Wnt/β-catenin signaling pathway.
Uric acid–driven NLRP3 inflammasome activation triggers lens epithelial cell senescence and cataract formation
Authors: Lin Hong Liang , Wang Sheng , Sato Kota , Zhang Yu Qiao , He Bei Ting , Xu Jing , Nakazawa Toru , Qin Yong Jie , Zhang Hong Yang 
Published: March 2024

AbstractExcessive uric acid (UA) is associated with age-related cataract. A previous study showed that a high UA level in the aqueous humor stimulated the senescence of lens epithelial cells (LECs), leading to cataract progression. To better understand the underlying mechanisms, we investigated UA-driven senescence in human lens tissue samples obtained during surgery, rat lens organ cultures, and in vivo experiments, using senescence-associated β-galactosidase (SA-β-gal) staining, electronic microscopy, Western blotting, and histological analyses. Initially, we identified markedly higher expressions of NLRP3 and caspase-1 in the lens capsules of hyper-uricemic patients compared to normo-uricemic patients. This increase was accompanied by a significant rise in the SA-β-gal positive rate. We next built a cataract model in which rat lenses in an organ culture system were treated with an increasing dosage of UA. Notably, opacification was apparent in the lenses treated with 800 μM of UA starting on the fifth day. Mechanistically, UA treatment not only significantly induced the expression of NLRP3, caspase-1, and IL-1β, but also upregulated the levels of SA-β-gal and the senescence regulators p53 and p21. These effects were fully reversed, and lens opacification was ameliorated by the addition of MCC950, a selective NLRP3 antagonist. Moreover, an in vivo model showed that intravitreal UA injection rapidly induced cataract phenotypes within 21 days, an effect significantly mitigated by co-injection with MCC950. Together, our findings suggest that targeting the UA-induced NLRP3 inflammasome with MCC950 could be a promising strategy for preventing cataract formation associated with inflammageing.