bluuebunny/crossref_metadata_2025_split huggingface dataset:
Brief, cognitive‐behavioral intervention to promote treatment seeking in adults with severe alcohol use disorder: A randomized controlled trial
Authors: Conner Kenneth R. , Maisto Stephen A. , Abar Beau , Szafranski Sarah , Chiang Andrew , Hutchison Morica , Aldalur Aileen , Stecker Tracy 
Published: July 2023

AbstractBackground and AimsThere is little RCT evidence that brief interventions improve treatment seeking in individuals with severe alcohol use disorder (AUD) or treatment seeking reduces alcohol use. The aim was to test the efficacy of a brief intervention to increase treatment seeking in treatment naïve adults with severe AUD and measure its effects on alcohol use.DesignParallel group, non‐pharmacologic RCT with intervention (n = 197) and active control (n = 203) conditions, with blinded assessors conducting follow‐ups at 1, 3 and 6 months.SettingOnline recruitment in a 17‐county region of upstate New York, USA.ParticipantsInclusion criteria consisted of ages ≥18 years, Alcohol Use Disorders Identification Test score ≥16, exceeds recommended limits for alcohol use and no history of AUD treatment. n = 400; 50% female; 79% white; mean age, 40.7; mean education, 14.6 years.Intervention and comparatorOne‐session telephone‐delivered interventions: Cognitive‐Behavioral Therapy for Treatment Seeking (CBT‐TS; intervention), review of a National Institute on Alcohol Abuse and Alcoholism pamphlet on AUD treatment (control).MeasurementsSelf‐report of any AUD treatment use over 3 months (primary outcome) and two standard measures of alcohol use over 6 months (secondary outcomes).FindingsIntent‐to‐treat analyses were used. Assessment follow‐up rates were ≥93%. Any alcohol‐related treatment use over 3‐month follow‐up was obtained by 38 (19%) intervention participants and 36 (18%) control participants, a non‐significant difference, χ2 [1] = 0.16, P = 0.689. Secondary analysis showed a significant interaction term between sex and intervention assignment (β = −1.197, P = 0.027). The interaction suggested CBT‐TS was effective in men (22% vs 13%), although the evidence was somewhat weak (P = 0.071), and it was not effective in women (17% vs 24%).ConclusionsA one‐session cognitive‐behavioral therapy intervention to increase treatment seeking in treatment naïve adults with severe alcohol use disorder did not increase treatment seeking.
Anthropometrics of neonates born to mothers with PCOS with metformin or placebo exposure in utero
Authors: Nilsen Guro Ørndal , Simpson Melanie Rae , Hanem Liv Guro Engen , Løvvik Tone Shetelig , Ødegård Rønnaug , Stokkeland Live Marie T. , Andersen Marianne Skovsager , Juliusson Petur Benedikt , Vanky Eszter 
Published: July 2023

AbstractIntroductionFetal growth may be affected by both maternal polycystic ovary syndrome (PCOS) and metformin therapy. Here, we explore the effect of intrauterine metformin exposure on birth anthropometrics of infants born to women with PCOS. We also investigated whether the effect of metformin on birth anthropometrics is modified by maternal pre‐pregnancy body mass index, PCOS hyperandrogenic phenotype, serum androgen levels, preconception use of metformin and offspring sex. Additionally, we assessed newborn anthropometrics in relation to a national reference population.Material and methodsIndividual data from three randomized controlled triasl were pooled. The randomized controlled trials investigated the effects of metformin in pregnant women with PCOS. In all, 397 and 403 were randomized to the metformin and placebo groups, respectively. A Scandinavian growth reference was used to calculate sex and gestational age adjusted z‐scores. Linear regression models were used to estimate the effect of metformin on offspring z‐scores of head circumference, birth length, birthweight, placental weight, body mass index, ponderal index and birthweight:placental weight ratio. S‐testosterone, s‐androstenedione, and s‐sex‐hormone binding globulin from four timepoints in pregnancy were analyzed.ResultsCompared with the PCOS‐placebo group, newborns in the PCOS‐metformin group had larger head circumference (head circumference z‐score: mean difference = 0.25, 95% CI = 0.11– 0.40). This effect of metformin on head circumference z‐score was particularly observed among offspring of overweight/obese mothers and mothers with hyperandrogenic PCOS‐phenotype. We observed no difference in other anthropometric measures between the metformin and placebo groups or any clear interaction between maternal androgen levels and metformin. Newborns in the PCOS‐placebo group were shorter than in the reference population (birth length z‐score: mean = −0.04, 95% CI = –0.05 to −0.03), but head circumference and birthweight were similar.ConclusionsLarger head circumference was observed at birth in metformin‐exposed offspring of mothers with PCOS. PCOS‐offspring were also shorter, with a similar birthweight to the reference population, indirectly indicating higher weight‐to‐height ratio at birth.
Converging old and new carbon frontiers in northern Australia
Authors: Neale Timothy , Dahlgren Kari , Howey Kirsty , Kearnes Matthew 
Published: July 2023

AbstractOver the past 15 years, international climate policy and governance practice have shifted from a linear model of carbon emissions management to a circular model. Whereas the former primarily focused on reducing absolute emissions, the latter focuses on balancing emissions sources and sinks. Australia, a major global exporter of ‘old’ carbon resources such as coal, has actively embraced circular carbon policies and their related ‘new’ carbon resources such as carbon credits. Focusing on Australia's Northern Territory as a site of old and new carbon economies, where government administrators have actively sought to host carbon circulations and loops, this paper examines three interlinked cases to illustrate the interdependencies generated through circular carbon policies. Identifying how sources, sinks, and the mediation of relations between them all constitute key contemporary carbon frontiers, we conclude by calling for a research agenda that analyses ‘old’ and ‘new’ carbon economies as a co‐produced assemblage rather than as isolated zones.
A Self-Censoring Model for Multivariate Nonignorable Nonmonotone Missing Data
Authors: Li Yilin , Miao Wang , Shpitser Ilya , Tchetgen Tchetgen Eric J. 
Published: July 2023

Abstract
We introduce an itemwise modeling approach called “self-censoring” for multivariate nonignorable nonmonotone missing data, where the missingness process of each outcome can be affected by its own value and associated with missingness indicators of other outcomes, while conditionally independent of the other outcomes. The self-censoring model complements previous graphical approaches for the analysis of multivariate nonignorable missing data. It is identified under a completeness condition stating that any variability in one outcome can be captured by variability in the other outcomes among complete cases. For estimation, we propose a suite of semiparametric estimators including doubly robust estimators that deliver valid inferences under partial misspecification of the full-data distribution. We also provide a novel and flexible global sensitivity analysis procedure anchored at the self-censoring. We evaluate the performance of the proposed methods with simulations and apply them to analyze a study about the effect of highly active antiretroviral therapy on preterm delivery of HIV-positive mothers.
Obesity is associated with poor outcomes of corticosteroid treatment in patients with primary immune thrombocytopenia
Authors: Zhang Xiaoyu , Liu Qiang , Liu Anli , Leng Shaoqiu , Wang Xiaolin , Zhao Ruxia , Sheng Zi , Feng Qi , Yang Xiaorong , Wang Shuwen , Hou Ming , Peng Jun , Feng Gege 
Published: July 2023

SummaryEmerging evidence has demonstrated that obesity impacts multiple immune‐related diseases. It remains unclear whether and how obesity alters treatment outcomes in patients with primary immune thrombocytopenia (ITP). Thus, we retrospectively investigated 214 treatment‐naïve patients who received standard high‐dose dexamethasone therapy in Qilu Hospital. Patients with obesity showed significantly lower overall initial response (underweight vs. normal vs. overweight vs. obese: 85.7% vs. 85.2% vs. 72.0% vs. 52.3%, p = 0.001) and initial complete response ([CR], 71.4% vs. 70.4% vs. 53.3% vs. 27.3%, p < 0.001) rates. The same trend was observed in the 6‐month sustained response (63.6% vs. 52.3% vs. 35.6% vs. 22.7%, p = 0.03) and sustained CR (36.4% vs. 44.6% vs. 24.4% vs. 9.1%, p = 0.01). The Kaplan–Meier analysis revealed a shortened duration of remission in the obese group (median duration of remission, not reached vs. 16 months vs. 2 months vs. 1 month, p = 0.002). In multivariate regression analysis, obesity was independently associated with poor initial and sustained responses, and an increased risk for relapse. In conclusion, obesity is a negative predictor for outcomes of corticosteroid treatment. A stratified strategy according to body mass index status may facilitate the precision management of ITP.
Machine learning approaches for predicting 5‐year breast cancer survival: A multicenter study
Authors: Nguyen Quynh Thi Nhu , Nguyen Phung‐Anh , Wang Chun‐Jung , Phuc Phan Thanh , Lin Ruo‐Kai , Hung Chin‐Sheng , Kuo Nei‐Hui , Cheng Yu‐Wen , Lin Shwu‐Jiuan , Hsieh Zong‐You , Cheng Chi‐Tsun , Hsu Min‐Huei , Hsu Jason C. 
Published: July 2023

AbstractThe study used clinical data to develop a prediction model for breast cancer survival. Breast cancer prognostic factors were explored using machine learning techniques. We conducted a retrospective study using data from the Taipei Medical University Clinical Research Database, which contains electronic medical records from three affiliated hospitals in Taiwan. The study included female patients aged over 20 years who were diagnosed with primary breast cancer and had medical records in hospitals between January 1, 2009 and December 31, 2020. The data were divided into training and external testing datasets. Nine different machine learning algorithms were applied to develop the models. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and F1‐score. A total of 3914 patients were included in the study. The highest AUC of 0.95 was observed with the artificial neural network model (accuracy, 0.90; sensitivity, 0.71; specificity, 0.73; PPV, 0.28; NPV, 0.94; and F1‐score, 0.37). Other models showed relatively high AUC, ranging from 0.75 to 0.83. According to the optimal model results, cancer stage, tumor size, diagnosis age, surgery, and body mass index were the most critical factors for predicting breast cancer survival. The study successfully established accurate 5‐year survival predictive models for breast cancer. Furthermore, the study found key factors that could affect breast cancer survival in Taiwanese women. Its results might be used as a reference for the clinical practice of breast cancer treatment.
Discovery of novel TRPV1 modulators through machine learning‐based molecular docking and molecular similarity searching
Authors: Wei Xinmiao , Yang Qifan , Yang Zhijiang , Huang Tengxin , Yang Hang , Wang Liangliang , Pan Li , Ding Junjie 
Published: July 2023

AbstractThe transient receptor potential vanilloid 1 (TRPV1) channel belongs to the transient receptor potential channel superfamily and participates in many physiological processes. TRPV1 modulators (both agonists and antagonists) can effectively inhibit pain caused by various factors and have curative effects in various diseases, such as itch, cancer, and cardiovascular diseases. Therefore, the development of TRPV1 channel modulators is of great importance. In this study, the structure‐based virtual screening and ligand‐based virtual screening methods were used to screen compound databases respectively. In the structure‐based virtual screening route, a full‐length human TRPV1 protein was first constructed, three molecular docking methods with different precisions were performed based on the hTRPV1 structure, and a machine learning‐based rescoring model by the XGBoost algorithm was constructed to enrich active compounds. In the ligand‐based virtual screening route, the ROCS program was used for 3D shape similarity searching and the EON program was used for electrostatic similarity searching. Final 77 compounds were selected from two routes for in vitro assays. The results showed that 8 of them were identified as active compounds, including three hits with IC50 values close to capsazepine. In addition, one hit is a partial agonist with both agonistic and antagonistic activity. The mechanisms of some active compounds were investigated by molecular dynamics simulation, which explained their agonism or antagonism.
Beyond ARIA: Will e‐diaries replace retrospective questionnaires in measuring the severity of allergic rhinitis in clinical research and daily practice?
Authors: Matricardi Paolo M. , Sousa‐Pinto Bernardo , Dramburg Stephanie , Bousquet Jean 
Published: July 2023

AbstractRetrospective questionnaires are used since decades to assess the severity and/or control of allergic diseases. Applications on smartphones have recently facilitated the use of prospective clinical diaries, based on questionnaires filled every day by the patient. Once limited to clinical trials, these e‐diaries, based on validated disease control scores and visual analogue scales, permit a quantitative day‐by‐day measure free of recall bias. Given the advantages of this procedure, its use could be extended to the daily clinical practice. E‐diaries may facilitate (1) a more precise identification of the culprit allergen in the diagnostic work‐up of poly‐sensitized patients, (2) the stratification of patients for treatment, (3) the follow‐up of the patients under treatment for optimized shared decision‐making, and (4) a careful assessment of preventive therapies. While a few apps are being used in scientific studies, consensus on their use in daily practice should be reached and guidelines for specialists should be elaborated by scientific associations.
The importance of expert selection when identifying threatened ecosystems
Authors: Travers Samantha K. , Dorrough Josh , Shannon Ian , Val James , Scott Mitchell L. , Moutou Claudine J. , Oliver Ian 
Published: July 2023

AbstractIdentifying threatened ecosystem types is fundamental to conservation and management decision‐making. When identification relies on expert judgment, decisions are vulnerable to inconsistent outcomes and can lack transparency. We elicited judgements of the occurrence of a widespread, critically endangered Australian ecosystem from a diverse pool of 83 experts. We asked 4 questions. First, how many experts are required to reliably conclude that the ecosystem is present? Second, how many experts are required to build a reliable model for predicting ecosystem presence? Third, given expert selection can narrow the range opinions, if enough experts are selected, do selection strategies affect model predictions? Finally, does a diverse selection of experts provide better model predictions? We used power and sample size calculations with a finite population of 200 experts to calculate the number of experts required to reliably assess ecosystem presence in a theoretical scenario. We then used boosted regression trees to model expert elicitation of 122 plots based on real‐world data. For a reliable consensus (90% probability of correctly identifying presence and absence) in a relatively certain scenario (85% probability of occurrence), at least 17 experts were required. More experts were required when occurrence was less certain, and fewer were needed if permissible error rates were relaxed. In comparison, only ∼20 experts were required for a reliable model that could predict for a range of scenarios. Expert selection strategies changed modeled outcomes, often overpredicting presence and underestimating uncertainty. However, smaller but diverse pools of experts produced outcomes similar to a model built from all contributing experts. Combining elicited judgements from a diverse pool of experts in a model‐based decision support tool provided an efficient aggregation of a broad range of expertise. Such models can improve the transparency and consistency of conservation and management decision‐making, especially when ecosystems are defined based on complex criteria.
Construction and evaluation of a risk prediction model for pulmonary infection‐associated acute kidney injury in intensive care units
Authors: Cao Xinyi , Liang Yongzhi , Feng Honglin , Chen Li , Liu Shengming 
Published: July 2023

AbstractAcute kidney injury (AKI) is one of the common complications of pulmonary infections. However, nomograms predicting the risk of early‐onset AKI in patients with pulmonary infections have not been comprehensively researched. In this study, 3278 patients with pulmonary infection were extracted from the Medical Information Mart for Intensive Care III (MIMIC‐III) database. These patients were randomly divided into training and validation cohorts, with the training cohort used for model building and the validation cohort used for validation. Independent risk factors for patients with pulmonary infection were determined using the least absolute shrinkage and selection operator (LASSO) method and forward stepwise logistic regression, which revealed that 11 independent risk factors for AKI in patients with pulmonary infections were congestive heart failure (CHF), hypertension, diabetes, transcutaneous oxygen saturation (SpO2), 24‐h urine output, white blood cells (WBC), serum creatinine (Scr), prothrombin time (PT), potential of hydrogen (PH), vasopressor use, and mechanical ventilation (MV) use. The nomogram was then constructed and validated. The area under the receiver operating characteristic curve (AUC) values of the nomogram were 0.770 (95% CI = 0.789–0.807) in the training cohort and 0.724 (95% CI = 0.754–0.784) in the validation cohort. High AUC values indicated the good discriminative ability of the nomogram, while the calibration curves and Hosmer–Lemeshow test results indicated that the nomogram was well‐calibrated. Improvements in net reclassification index (NRI) and integrated discrimination improvement (IDI) values indicate that our nomogram was superior to the Simplified Acute Physiology Score (SAPS) II scoring system, and the decision–curve analysis (DCA) curves indicate that the nomogram has good clinical application. We established a risk‐prediction model for AKI in patients with pulmonary infection, which has good discriminative power and is superior to the SAPS II scoring system. This model can provide clinical reference information for patients with this type of disease in the intensive care unit.
Conductivity and water level modulate developmental plasticity and explain distribution patterns in a diverse neotropical Odonata assemblage
Authors: Aristizábal‐Botero Ángela , Snoeks Joren M. , Realpe Emilio , Vanschoenwinkel Bram 
Published: July 2023

Abstract

Developmental plasticity can help organisms to survive in temporally variable environments. However, it is not well understood how variation in life history plasticity helps species coexist in heterogeneous environments. Here, we investigate the extent to which life‐history plasticity explains species distributions in a diverse assemblage of odonates in a tropical freshwater rock pool system characterized by substantial variation in pond permanence. Some dragonflies and damselflies (Odonata) can accelerate their development to leave the water before their habitat dries. However, how they sense habitat drying is poorly understood.

Here, we experimentally tested the extent to which elevated concentrations of salts in water or reductions in water level can be used as cues for developmental acceleration in a neotropical Odonata assemblage from granite rock pools.

Libellulidae dragonflies were found along the permanence gradient and accelerated their growth in response to elevated dissolved salts (measured as conductivity). Anax amazili (Aeshnidae) was also found in all environments and did the same in response to lower water levels. In turn, larvae of the damselfly Telebasis simulata (Coenagrionidae) were restricted to deeper long‐lived pools and did not respond to the tested cues.

Differentiation in life‐history strategies can contribute to niche differentiation in this diverse predator assemblage. Developmental plasticity triggered by different cues helps odonates avoid mortality and exploit short‐lived habitats. The global acceleration of freshwater salinisation due to human activities might disrupt the delicate links between low levels of dissolved salts and life‐history responses and represent a significant threat to these ecosystems and their biodiversity.
The impact of SETBP1 mutations in neurological diseases and cancer
Authors: Kohyanagi Naoki , Ohama Takashi 
Published: July 2023

AbstractSE translocation (SET) is a cancer‐promoting factor whose expression is upregulated in many cancers. High SET expression positively correlates with a poor cancer prognosis. SETBP1 (SET‐binding protein 1/SEB/MRD29), identified as SET‐binding protein, is the causative gene of Schinzel–Giedion syndrome, which is characterized by severe intellectual disability and a distorted facial appearance. Mutations in these genetic regions are also observed in some blood cancers, such as myelodysplastic syndromes, and are associated with a poor prognosis. However, the physiological role of SETBP1 and the molecular mechanisms by which the mutations lead to disease progression have not yet been fully elucidated. In this review, we will describe the current epidemiological data on SETBP1 mutations and shed light on the current knowledge about the SET‐dependent and ‐independent functions of SETBP1.
Path dependence and jumping tracks: Investigating institutional continuity and change across the Tasmanian convict and pauper systems
Authors: Watkins Emma 
Published: July 2023

AbstractThis article uses a historical case study to significantly advance theoretical debates on path dependence in institutional change and continuity. In particular, it argues that the heuristic of ‘jumping tracks’ can be productively developed to explain how institutional arrangements can shift into different policy arenas. The historical criminological case study examines welfare provision and penalties in colonial Australia. Substantively, the case study provides historical support to current claims that the boundaries between crime, poverty and welfare are fluid. Just as the shadow of the contemporary carceral state is enlarging non‐criminal pathways to punishment, it will be shown that in 19th‐century Tasmania the shadow of the penal colony acted to control paupers. When the Tasmanian penal system began to be dismantled, the institutional arrangements that had developed within it jumped tracks to the pauper system. Fundamentally, the key theoretical proposition is that path dependence can work across institutions by jumping tracks.