bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association of genetic variations in FoxP3 gene with Graves' disease in a Southwest Chinese Han population
Authors: Tan Guiqin , Zheng Guangbing , Li Jiang , Zhu Yingping , Liang Zhongzhi , Li Hua , Yu Hongsong , Wang Xin 
Published: October 2023

AbstractBackgroundGraves' disease (GD) is a T cell‐mediated organ‐specific autoimmune disease. Forkhead box P3 (FoxP3) is an excellent marker for the induction and development of regulatory T cells (Tregs). Recent studies showed that single‐nucleotide polymorphisms (SNPs) in the FoxP3 gene were associated with the increased susceptibility to several autoimmune diseases. In the present study, we investigated the association of FoxP3 gene polymorphisms with GD in a Southwest Chinese Han population.MethodsA two‐stage case‐control study was performed in 890 healthy controls (male, 282; female, 608) and 503 patients with GD (male, 138; female, 365). Four SNPs (rs3761548, rs3761549, rs3761547, and rs2280883) were genotyped by the polymerase chain reaction‐restriction fragment length polymorphism assay. The χ2 test was used to compare the genotype distributions and allele frequencies between GD patients and healthy controls.ResultsIn the first stage, the significantly increased frequencies of the A allele (p = .031, odds ratio [OR] = 1.635) and AA genotype (p = .023, OR = 3.257), together with a significantly decreased frequency of the C allele (p = .031, OR = 0.611) of FoxP3/rs3761548 were found in female patients with GD. None of the other FoxP3 SNPs was associated with GD susceptibility. Subsequent validation and combination of data confirmed the association between FoxP3/rs3761548 and the female patients with GD (A allele: p < .001, OR = 1.672; AA genotype: p = .005, OR = 2.488; CC genotype: p = .001, OR = 0.622; C allele: p < .001, OR = 0.615, respectively).ConclusionOur findings suggest that FoxP3/rs3761548 is significantly associated with female GD patients in a Southwest Chinese Han population.
Real‐world treatment patterns for palbociclib plus an aromatase inhibitor, or an aromatase inhibitor alone, for patients with metastatic breast cancer in the Flatiron Database
Authors: Rugo Hope S. , Liu Xianchen , Li Benjamin , McRoy Lynn , Chen Connie , Layman Rachel M. , Brufsky Adam 
Published: October 2023

AbstractThere are limited real‐world comparative effectiveness data for palbociclib plus an aromatase inhibitor (AI) as a first‐line (1L) treatment examining endpoints that require long term follow‐up and post 1L progression. The Flatiron Health Analytic Database was used to characterize treatment and dosing patterns in patients with hormone receptor‐positive/human epidermal growth factor 2‐negative (HR+/HER2−) metastatic breast cancer (mBC) receiving palbociclib plus an AI vs an AI alone in routine US clinical practice. In addition, time to chemotherapy (TTC) and real‐world progression‐free survival (rwPFS) when combining 1L and second‐line of therapy (rwPFS2) were assessed. Of 1324 patients who received palbociclib plus an AI between February 3, 2015 and March 31, 2020, 1110 (83.8%) started palbociclib at the recommended 125 mg/day dose. After stabilized inverse probability treatment‐weighting (sIPTW), median TTC in patients treated with palbociclib plus an AI and AI alone was 37.4 months (95% confidence interval [CI], 33.7‐40.7) and 29.2 months (95% CI, 26.8‐33.5), respectively (hazard ratio [HR] = 0.77 [95% CI, 0.69‐0.86], P < .0001); median rwPFS2 was 32.6 months (95% CI, 29.4‐35.2) and 20.7 months (95% CI, 18.9‐22.6), respectively (HR = 0.62 [95% CI, 0.54‐0.70], P < .0001). Sensitivity analyses with propensity score matching showed similar results to sIPTW analyses. Results from this large real‐world study examining additional effectiveness outcomes beyond 1L rwPFS and overall survival support the use of palbociclib plus an AI as a 1L treatment for patients with HR+/HER2− mBC.
Influence of pelvic floor disorders on sexuality in women
Authors: Martínez‐Galiano Juan Miguel , Peinado‐Molina Rocío Adriana , Martínez‐Vazquez Sergio , Hita‐Contreras Fidel , Delgado‐Rodríguez Miguel , Hernández‐Martínez Antonio 
Published: October 2023

AbstractObjectiveTo determine the association between different pelvic floor disorders and the presence of sexual dysfunction in women.MethodAn observational study of non‐pregnant women was carried out in Spain in 2021 and 2022. To assess the presence of pelvic floor problems, the Pelvic Floor Distress Inventory (PFDI‐20) was used, consisting of the subscales Pelvic Organ Prolapse Distress Inventory‐6 (POPDI‐6; prolapse symptoms), Colorectal‐Anal Distress Inventory (CRADI‐8; colorectal symptoms), and Urinary Distress Inventory‐6 (UDI‐6; urinary symptoms). The validated tool, Female Sexual Function (FSF), was used to evaluate female sexual function.ResultsIn total, 1008 women participated. Of these, 288 (28.6%) had some type of sexual dysfunction. Regarding symptoms, 52 (5.2%) stated that they do not reach orgasm and 172 (17.1%) said they had never or occasionally felt sexual desire in the last month. Women with sexual dysfunctions had higher mean scores on the POPDI‐6, CRADI‐8, and UDI‐6 subscales than those who did not have sexual dysfunction (P ≤ 0.005). Risk factors identified included being postmenopausal, with an adjusted odds ratio (aOR) of 2.98 (95% confidence interval [CI] 2.12–4.18), and a greater impact of the symptoms of pelvic floor problems as assessed by the PFDI‐20 scale, in such a way that for each point increase the probability of sexual dysfunction increases with an aOR of 1.008 (95% CI 1.005–1.011).ConclusionWomen with pelvic floor disorders and postmenopausal women present sexual dysfunction more frequently.
Gold–graphitic carbon nitride composite electrode for pimobendan detection
Authors: Luk Hsiang‐Ning , Chang Xu‐Jia , Wu Ren‐Jang , Yuan Shuo‐Huang 
Published: October 2023

AbstractIntroductionHeart failure can lead to death and hospitalization, especially among older adults, and pimobendan is used with human patients. We investigated the electrochemical behavior of Au/g‐C3N4 electrochemical sensors to detect the concentration of pimobendan.ExperimentalCharacterization of the materials was conducted using XRD, TEM, SEM, EDS and FTIR. Cyclic voltammetry (CV) was used to measure the concentration and redox properties of pimobendan.Result and DiscussionsAt a voltage of 0.05 V, a reduction peak appeared, indicating an association between pimobendan concentration (ranging from 0 to 55 μM) and reductive current. At low concentrations of pimobendan concentration from 0.0 to 1.3 μM, the linearity R2 = 0.9149 with a detection limit of 0.29 μM. Dopamine, epinephrine, and uric acid did not interfere with the detection of pimobendan.ConclusionsA composite sensing electrode consisting of 3% Au/g‐C3N4 was fabricated for the detection of pimobendan. A potential pimobendan sensing mechanism on 3% Au/g‐C3N4 was proposed on the basis of these findings.
Prognostic Impact of Early Administration of β‐Blockers in Critically Ill Patients with Acute Myocardial Infarction
Authors: Zhang Chong , Wang Fei , Hao Cuijun , Liang Weiru , Hou Tianhua , Xin Jiayan , Su Bin , Ning Meng , Liu Yingwu 
Published: October 2023

AbstractIn critically ill patients with acute myocardial infarction (AMI), the relationship between the early administration of β‐blockers and the risks of in‐hospital and long‐term mortality remains controversial. Furthermore, there are conflicting evidences for the efficacy of the early administration of intravenous followed by oral β‐blockers in AMI. We conducted a retrospective analysis of critically ill patients with AMI who received the early administration of β‐blockers within 24 hours of admission. The data were extracted from the Medical Information Mart for Intensive Care IV database. We enrolled 2467 critically ill patients with AMI in the study, with 1355 patients who received the early administration of β‐blockers and 1112 patients who were non‐users. Kaplan‐Meier survival analysis and Cox proportional hazards models showed that the early administration of β‐blockers was associated with a lower risk of in‐hospital mortality (adjusted hazard ratio [aHR] 0.52; 95% confidence interval [95%CI] 0.42‐0.64), 1‐year mortality (aHR 0.54, 95%CI 0.47‐0.63), and 5‐year mortality (aHR 0.60, 95%CI 0.52‐0.69). Furthermore, the early administration of both oral β‐blockers and intravenous β‐blockers followed by oral β‐blockers may reduce the mortality risk, compared with non‐users. The risks of in‐hospital and long‐term mortality were significantly decreased in patients who underwent revascularization with the early administration of β‐blockers. We found that the early administration of β‐blockers could lower the risks of in‐hospital and long‐term mortality. Furthermore, the early administration of both oral β‐blockers and intravenous β‐blockers followed by oral β‐blockers may reduce the mortality risk, compared with non‐users. Notably, patients who underwent revascularization with the early administration of β‐blockers showed the lowest risks of in‐hospital and long‐term mortality.
Modelling selenite and chemical oxygen demand removal in an inverse fluidized bed bioreactor using genetic algorithm optimized artificial neural network
Authors: Sinharoy Arindam , Mahanty Biswanath , Behera Shishir Kumar , Mehta Manan , Mantri Shalini , Das Raja , Saikia Sudeshna , Rene Eldon R. , Pakshirajan Kanan 
Published: October 2023

AbstractBACKGROUNDA genetic algorithm (GA) optimized artificial neural network (ANN) model was developed to simulate selenite removal efficiency (SRe) and chemical oxygen demand (COD) removal efficiency (CRe) in a single‐stage inverse fluidized bed reactor (IFBR) operated under different hydraulic retention time (HRT) (12–48 h), and inlet selenite concentration (12.7–635 mg L−1). Multi‐objective optimization for SRe and CRe with the ANN model was adopted to estimate the pareto optimal solutions in the bioreactor system.RESULTSGA optimized ANN topology suggested five neurons in the hidden layer, and the optimal data partitioning between training, test, and validation subsets (in 70:15:15 ratio) using cross‐validation. The average fitness for SRe and CRe of the resulting ANN model over training (R2 = 0.885), test (R2 = 0.967) and validation (R2 = 0.972) subsets were reasonably good. Sensitivity analysis suggested an increase in SRe and CRe with HRT, while an increase in inlet selenite concentration had a negative effect on SRe. Local interpretable model‐agnostic explanations and SHapley Additive exPlanations for the developed model suggested a positive coefficient of the predictors on CRe. Pareto optimal solution for SRe (92.87%–95.26%), and CRe (91.33%–99.35%) were suggested for HRT and inlet selenite concentration varying between 35.67 h and 36 h, and 0.1 g L−1 and 0.884 g L−1, respectively.CONCLUSIONSThe GA optimized ANN model could be exploited for the prediction of contaminant removal efficiencies in the bioreactor system with a fair degree of complexity (i.e., IFBR). Multiple objective pareto optimal solutions can identify the best operating conditions relevant for wastewater treatment. © 2023 Society of Chemical Industry (SCI).
Crosstalk between tumour and stroma modifies CLIC4 cargo in extracellular vesicles
Authors: Sanchez Vanesa C. , Craig‐Lucas Alayna , Cataisson Christophe , Carofino Brandi L. , Yuspa Stuart H. 
Published: October 2023

AbstractMouse models of breast cancer have revealed that tumour‐bearing hosts must express the oxidoreductase CLIC4 to develop lung metastases. In the absence of host CLIC4, primary tumours grow but the lung premetastatic niche is defective for metastatic seeding. Primary breast cancer cells release EVs that incorporate CLIC4 as cargo and circulate in plasma of wildtype tumour‐bearing hosts. CLIC4‐deficient breast cancer cells also form tumours in wildtype hosts and release EVs in plasma, but these EVs lack CLIC4, suggesting that the tumour is the source of the plasma‐derived EVs that carry CLIC4 as cargo. Paradoxically, circulating EVs are also devoid of CLIC4 when CLIC4‐expressing primary tumours are grown in CLIC4 knockout hosts. Thus, the incorporation of CLIC4 (and perhaps other factors) as EV cargo released from tumours involve specific signals from the surrounding stroma determined by its genetic composition. Since CLIC4 is also detected in circulating EVs from human breast cancer patients, future studies will address its association with disease.
A decade of hibernating bat communities along the periphery of a region of white‐nose syndrome
Authors: Perea Santiago , Ferrall Emily A. , Morris Katrina M. , Pattavina Pete E. , Sharp Nicholas , Castleberry Steven B. 
Published: October 2023

AbstractLong‐term monitoring programs are necessary to assess populations for conservation planning and management decisions. Hibernating bats in North America have declined because of numerous natural and human‐induced disturbances. White‐nose syndrome (WNS) has become the most serious threat to North American cave‐dwelling bats, leading to significant population declines in several species. We examined trends in hibernating bat populations at 11 hibernacula in northern Georgia and Alabama, USA, from 2013–2022, beginning when WNS was first detected in the region. Although we observed interannual variation in numbers of the federally endangered gray bat (Myotis grisescens), mean counts remained stable over time. In contrast, the tricolored bat (Perimyotis subflavus) and the federally endangered northern long‐eared bat (M. septentrionalis) declined by >90% in the first 5 years after WNS detection in the region. Although no northern long‐eared bats have been reported since 2019, tricolored bat counts stabilized following initial declines. Understanding changes in bat populations as WNS continues to spread, and determining the extent of population declines, is necessary for making appropriate management decisions. Our findings elucidate the status of cave‐dwelling bat species along the periphery of the white‐nose syndrome endemic region and highlight the importance of monitoring bat communities on a regional scale to develop effective conservation strategies.
Understanding implications of detection heterogeneity in wildlife abundance estimation
Authors: Laake Jeffrey L. , Collier Bret A. 
Published: October 2023

AbstractNegative bias in mark‐recapture abundance estimators due to heterogeneity in detection (capture) probability is a well‐known problem, but we believe most biologists do not understand why heterogeneity causes bias and how bias can be reduced. We demonstrate how heterogeneity creates dependence and bias in mark‐recapture approaches to abundance estimation. In comparison, heterogeneity, and hence estimator bias, is not as problematic for distance sampling and mark‐resight methods because both techniques estimate detection probabilities based on a known quantity. We show how the introduction of a known number of individuals planted into a study population prior to a mark‐recapture survey can reduce bias from heterogeneity in detection probability. We provide examples with simulation and an analysis of motion‐sensitive camera data from a study population of introduced eastern wild turkeys (Meleagris gallopavo silvestris) of known size with a subset of telemetered birds. In choosing a method for abundance estimation, careful consideration should be given to assumptions and how heterogeneity in detection probability can be accommodated for each application.
Changes in the biological “regulators” of organic carbon mineralization in silted soils of check dams as a result of wet‐dry cycles
Authors: Liu Xiaojun , Zhang Yi , Li Peng , Xiao Lie 
Published: October 2023

AbstractClimate change is increasing the frequency of prolonged droughts and extreme rainfall events, with implications for ecosystem carbon (C) cycling and efforts to mitigate climate change. Exploring how wet and dry cycling events affect microbially mediated soil organic carbon (SOC) mineralization processes is critical for achieving global C neutrality targets. This study examines how drought, water stress, and wet‐dry cycles influence microorganisms and the SOC mineralization process. We found that wet‐dry cycles initially excited mineralization of SOC, but that soil mineralization gradually decreased as wet‐dry cycling continued. At the same time, the utilization of C sources by different microbial communities tended to change, from primarily carbohydrate, amines and acids to a single acid, esters, or alcohols. The limiting factors for SOC mineralization also varied when soils were exposed to drought, water stress, and wet‐dry cycles, and we quantified the direct and interactive contributions of each factor to SOC mineralization. The direct effects of the factors under drought and water stress were 0.70 and 0.74, while the interaction of the elements was only 0.29 and 0.24. The direct effects of the factors were only 0.30 under wet‐dry cycling conditions. Based on the results of this study, we propose a pathway for soil biological regulation of SOC mineralization during drought, water stress and wet‐dry cycles, in order to further clarify the microbial regulation mechanism related to SOC mineralization.
Out‐of‐distribution detection with in‐distribution voting using the medical example of chest x‐ray classification
Authors: Wollek Alessandro , Willem Theresa , Ingrisch Michael , Sabel Bastian , Lasser Tobias 
Published: October 2023

AbstractBackgroundDeep learning models are being applied to more and more use cases with astonishing success stories, but how do they perform in the real world? Models are typically tested on specific cleaned data sets, but when deployed in the real world, the model will encounter unexpected, out‐of‐distribution (OOD) data.PurposeTo investigate the impact of OOD radiographs on existing chest x‐ray classification models and to increase their robustness against OOD data.MethodsThe study employed the commonly used chest x‐ray classification model, CheXnet, trained on the chest x‐ray 14 data set, and tested its robustness against OOD data using three public radiography data sets: IRMA, Bone Age, and MURA, and the ImageNet data set. To detect OOD data for multi‐label classification, we proposed in‐distribution voting (IDV). The OOD detection performance is measured across data sets using the area under the receiver operating characteristic curve (AUC) analysis and compared with Mahalanobis‐based OOD detection, MaxLogit, MaxEnergy, self‐supervised OOD detection (SS OOD), and CutMix.ResultsWithout additional OOD detection, the chest x‐ray classifier failed to discard any OOD images, with an AUC of 0.5. The proposed IDV approach trained on ID (chest x‐ray 14) and OOD data (IRMA and ImageNet) achieved, on average, 0.999 OOD AUC across the three data sets, surpassing all other OOD detection methods. Mahalanobis‐based OOD detection achieved an average OOD detection AUC of 0.982. IDV trained solely with a few thousand ImageNet images had an AUC 0.913, which was considerably higher than MaxLogit (0.726), MaxEnergy (0.724), SS OOD (0.476), and CutMix (0.376).ConclusionsThe performance of all tested OOD detection methods did not translate well to radiography data sets, except Mahalanobis‐based OOD detection and the proposed IDV method. Consequently, training solely on ID data led to incorrect classification of OOD images as ID, resulting in increased false positive rates. IDV substantially improved the model's ID classification performance, even when trained with data that will not occur in the intended use case or test set (ImageNet), without additional inference overhead or performance decrease in the target classification. The corresponding code is available at https://gitlab.lrz.de/IP/a‐knee‐cannot‐have‐lung‐disease.
Comparison of distortion correction preprocessing pipelines for DTI in the upper limb
Authors: Wade Ryckie G. , Tam Winnie , Perumal Antonia , Pepple Sophanit , Griffiths Timothy T. , Flather Robert , Haroon Hamied A. , Shelley David , Plein Sven , Bourke Grainne , Teh Irvin 
Published: October 2023

AbstractPurposeDTI characterizes tissue microstructure and provides proxy measures of nerve health. Echo‐planar imaging is a popular method of acquiring DTI but is susceptible to various artifacts (e.g., susceptibility, motion, and eddy currents), which may be ameliorated via preprocessing. There are many pipelines available but limited data comparing their performance, which provides the rationale for this study.MethodsDTI was acquired from the upper limb of heathy volunteers at 3T in blip‐up and blip‐down directions. Data were independently corrected using (i) FSL's TOPUP & eddy, (ii) FSL's TOPUP, (iii) DSI Studio, and (iv) TORTOISE. DTI metrics were extracted from the median, radial, and ulnar nerves and compared (between pipelines) using mixed‐effects linear regression. The geometric similarity of corrected b = 0 images and the slice matched T1‐weighted (T1w) images were computed using the Sörenson‐Dice coefficient.ResultsWithout preprocessing, the similarity coefficient of the blip‐up and blip‐down datasets to the T1w was 0·80 and 0·79, respectively. Preprocessing improved the geometric similarity by 1% with no difference between pipelines. Compared to TOPUP & eddy, DSI Studio and TORTOISE generated 2% and 6% lower estimates of fractional anisotropy, and 6% and 13% higher estimates of radial diffusivity, respectively. Estimates of anisotropy from TOPUP & eddy versus TOPUP were not different but TOPUP reduced radial diffusivity by 3%. The agreement of DTI metrics between pipelines was poor.ConclusionsPreprocessing DTI from the upper limb improves geometric similarity but the choice of the pipeline introduces clinically important variability in diffusion parameter estimates from peripheral nerves.