bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real‐Time, AI‐Guided Photodynamic Laparoscopy Enhances Detection in a Rabbit Model of Peritoneal Cancer Metastasis
Authors: Rivera‐Piza Adriana , Lee Sung‐Ho , Lee Hannah HeeJung , Lee Seungho , Shin Su‐Jin , Kim Jaehyuk , Park Jong‐Hyun , Yu Jae Eun , Lee Sang Won , Park Gyuri , Wilson Brian C. , Kim Hyoung‐Il 
Published: February 2025

ABSTRACTAccurate diagnosis is essential for effective cancer treatment, particularly in peritoneal surface malignancies, where failure to detect metastatic lesions can mislead the treatment plan. This study assessed the diagnostic accuracy of staging laparoscopy using the integration of artificial intelligence (AI)‐guided photodynamic diagnosis (PDD) with the photosensitizer Phonozen, activated at 405 nm in a rabbit model. To create peritoneal carcinomatosis, VX2 cells were inoculated laparoscopically into the peritoneum of female white New Zealand rabbits. Conventional and PDD‐guided laparoscopy utilized a customized light source that emitted broad‐spectrum white light or 405‐nm blue light, respectively. The surgical procedure comprised a tripartite approach: exploration and labeling of suspected nodules under white‐light visualization, identification of additional metastatic tumors under blue‐excitation fluorescent light, and confirmatory open laparotomy to locate overlooked nodules by palpation. Our results showed that the initial experimental data from 371 nodules in 14 rabbits, comparing conventional diagnostic laparoscopy and PDD, showed increased detection sensitivity from 67% ± 1.9% (conventional) to 98% ± 0.7% (PDD) in the small‐size nodule. In the second experimental data set from 265 nodules in 10 rabbits, the addition of a real‐time AI algorithm further increased the sensitivity to 100% ± 0.0%. Combining PDD with AI enhances the detection of peritoneal cancer metastasis in staging laparoscopy.
Detecting Glaucoma in Highly Myopic Eyes From Fundus Photographs Using Deep Convolutional Neural Networks
Authors: Chen Xiaohong , Zhou Chen , Zhu Yingting , Luo Man , Hu Lingjing , Han Wenjing , Zuo Chengguo , Li Zhidong , Xiao Hui , Huang Shaofen , Chen Xuhao , Zhao Xiujuan , Lu Lin , Wang Yizhou , Zhuo Yehong 
Published: February 2025

ABSTRACTBackgroundHigh myopia (HM) is a major risk factor for glaucoma. However, glaucomatous optic neuropathy is often undiagnosed owing to atypical structural alterations with axial elongation. Moreover, an algorithm to detect glaucoma in highly myopic eyes has not yet been reported.MethodsWe recruited 2643 colour fundus photographs to train a ResNet‐50 network for discriminating eyes with highly myopic glaucoma (HMG) from HM or glaucoma alone. We employed a 10‐fold cross‐validation strategy to evaluate the model's performance and applicability across diverse patient groups. Multiple metrics were computed to gauge the model's diagnostic process. The diagnostic ability of the model was then juxtaposed with those made by ophthalmologists to determine concordance. The gradient‐weighted class activation maps were used for visual explanations.ResultsOur model demonstrated an overall accuracy of 97.7% with an area under the curve of 98.6% (sensitivity, 91.2%; specificity, 98.0%) for the differential diagnosis among HM, glaucoma, HMG and normal controls. These metrics notably outperformed the diagnostic performances of two attending ophthalmologists, who achieved accuracies of 64.7% and 69.9%. The activation maps derived from the model suggested that the most discriminative lesions for diagnosing HMG were predominantly in the disc, peripapillary area and inferior region of the disc, which are often displayed with a tessellated fundus. These results were slightly different from the understanding of the attending ophthalmologists.ConclusionsOur proposed model demonstrates high efficacy and suggests specific features for distinguishing eyes with HMG, enabling potential clinical value in assisting the intricate diagnosis of this vision‐threatening disease.
Neural Activity Alterations and Their Association With Neurotransmitter and Genetic Profiles in Schizophrenia: Evidence From Clinical Patients and Unaffected Relatives
Authors: Guo Zixuan , Xiao Shu , Sun Shilin , Su Ting , Tang Xinyue , Chen Guanmao , Chen Pan , Chen Ruoyi , Chen Chao , Gong Jiaying , Yang Zibin , Huang Li , Jia Yanbin , Wang Ying 
Published: February 2025

ABSTRACTBackgroundThe pattern of abnormal resting‐state brain function has been documented in schizophrenia (SCZ). However, as of yet, it remains unclear whether this pattern is of genetic predisposition or related to the illness itself.MethodsA systematical meta‐analysis was performed to identify resting‐state functional differences in probands and their high‐risk first‐degree relatives of schizophrenia (FDRs‐SCZ) using Seed‐based d Mapping software. Subsequently, spatial associations between postmortem gene expression and neurotransmitters distribution data and neural activity alterations were conducted to uncover neural mechanisms underlaying FDRs‐SCZ and SCZ from a multidimensional perspective.ResultsA total of 13 studies comprising 503 FDRs‐SCZ and 605 healthy controls (HCs) and 129 studies comprising 6506 patients with SCZ and 6982 HCs were included. Compared to HCs, FDRs‐SCZ displayed increased spontaneous functional activity in the bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC); patients with SCZ showed decreased spontaneous functional activity in the bilateral ACC/mPFC, bilateral postcentral gyrus, and right middle temporal gyrus as well as increased spontaneous functional activity in the bilateral striatum. The altered functional activity in FDRs‐SCZ and SCZ shared similar spatial associations with genes enriched in potassium ion transmembrane transport, channel activity, and complex. The FDRs‐SCZ and SCZ‐related brain functional patterns were additionally associated with dopaminergic, serotonergic, and cholinergic neurotransmitter distribution.ConclusionsSCZ‐related resting‐state functional, neuroimaging transcriptomes, and neurotransmitters abnormalities may exist in high‐risk unaffected FDRs‐SCZ, rather than just in overt SCZ. The study extended the evidence that altered brain function, along with their spatial correlations to genetics and neurotransmitter systems, may associate with genetic vulnerability for SCZ.
Discovery of Novel Pain Regulators Through Integration of Cross‐Species High‐Throughput Data
Authors: Chen Ying , Bajpai Akhilesh K. , Li Nan , Xiang Jiahui , Wang Angelina , Gu Qingqing , Ruan Junpu , Zhang Ran , Chen Gang , Lu Lu 
Published: February 2025

ABSTRACTAimsChronic pain is an impeding condition that affects day‐to‐day life and poses a substantial economic burden, surpassing many other health conditions. This study employs a cross‐species integrated approach to uncover novel pain mediators/regulators.MethodsWe used weighted gene coexpression network analysis to identify pain‐enriched gene module. Functional analysis and protein‐protein interaction (PPI) network analysis of the module genes were conducted. RNA sequencing compared pain model and control mice. PheWAS was performed to link genes to pain‐related GWAS traits. Finally, candidates were prioritized based on node degree, differential expression, GWAS associations, and phenotype correlations.ResultsA gene module significantly over‐enriched with the pain reference set was identified (referred to as “pain module”). Analysis revealed 141 pain module genes interacting with 46 pain reference genes in the PPI network, which included 88 differentially expressed genes. PheWAS analysis linked 53 of these genes to pain‐related GWAS traits. Expression correlation analysis identified Vdac1, Add2, Syt2, and Syt4 as significantly correlated with pain phenotypes across eight brain regions. NCAM1, VAMP2, SYT2, ADD2, and KCND3 were identified as top pain response/regulator genes.ConclusionThe identified genes and molecular mechanisms may enhance understanding of pain pathways and contribute to better drug target identification.
Impact of CEO's IT Background on Green Technology Innovation: Evidence From China
Authors: Zhang Xue , Zhang Wensong , Wang Jiayuan , Chen Baolian 
Published: February 2025

ABSTRACTResearch Question/IssueConsidering the important role of CEO's background characteristics in formulating firms' innovation strategy decisions, we investigate the relationship between the CEO's information technology (IT) background and corporate green technology innovation.Research Findings/InsightsWe find that the CEO with an IT background results in an addition of 19.6% in corporate green technology innovation outputs. The result is robust to identification tests, including 2SLS, PSM, DID, and system GMM. The channel test shows that the CEO's IT background positively affects green technology innovation by promoting firms' digital transformation. And the financial‐industrial integration strengthens the positive relationship between the CEO's IT background and corporate green technology innovation. Heterogeneity analysis indicates that the relationship is pronounced in state‐owned enterprises, mature enterprises, and non‐high‐tech enterprises.Theoretical/Academic ImplicationsThe findings of this paper not only enrich the research literature on antecedent variables of green technology innovation but also provide theoretical support for listed companies to improve the background configuration of the executive team.Practitioner/Policy ImplicationsAgainst the backdrop of China's booming digital economy, our results provide important insights for practitioners, suggesting that they should employ more IT professionals to improve their green technology innovation capabilities and gain a sustainable competitive advantage.
Inhibition of Tacrolimus Metabolism by Cannabidiol and Its Metabolites In Vitro
Authors: So Gerald C. , Lu Jessica Bo Li , Cheng Ying‐Hua , Gisch Debora L. , Koyama Sachiko , Melo Ferreira Ricardo , Beamon Travis R. , Desta Zeruesenay , Eadon Michael T. 
Published: February 2025

ABSTRACTDrug interactions are major causes of interindividual variability in tacrolimus exposure and effect. Tacrolimus, a widely used drug in transplant patients, is metabolized by CYP3A4 and CYP3A5. Cannabidiol (CBD) use after transplant is common. Clinical cases suggest CBD may alter tacrolimus exposure, but the mechanism of this interaction is unknown. We hypothesize that cannabidiol will inhibit tacrolimus metabolism in vitro mainly through CYP3A5 inhibition. In pooled human liver microsomes (HLMs) and recombinant (r) CYP3A4 and CYP3A5 enzymes, tacrolimus (1 μM) metabolism was determined using substrate depletion method in the absence (control) and the presence of 10 μM CBD, 7‐hydroxyCBD, and 7‐carboxyCBD. Ketoconazole (1 μM) served as a positive control for the inhibition of CYP3A. Linear regression analyses were performed to obtain kinetic parameters of the depletion. Tacrolimus depletion half‐life was 2.54, 0.922, and 0.351 min with pooled HLMs, rCYP3A4, and rCYP3A5, respectively. In pooled HLMs, CBD and 7‐hydroxyCBD increased tacrolimus half‐life by 0.8‐ and 2.3‐fold (both p < 0.0001), respectively. In rCYP3A4, CBD, 7‐hydroxyCBD, and ketoconazole prolonged tacrolimus half‐life by 5.8‐, 14‐, and 7.7‐fold, respectively. In rCYP3A5, CBD, 7‐hydroxyCBD, and ketoconazole prolonged half‐life by 29.3‐, 19.7‐, and 0.1‐fold, respectively. In all experiments, 7‐carboxyCBD had minimal effect on tacrolimus depletion. CBD and 7‐hydroxyCBD inhibited tacrolimus metabolism in vitro. CBD showed stronger inhibition in rCYP3A5 than rCYP3A4. The demonstrated CYP3A5 selectivity of cannabidiol may contribute to the in vitro identification of CYP3A5 substrates in new drug development. Our results support the potential of a clinical drug–drug interaction between CBD and tacrolimus.
A mixed‐methods study of staff perspectives on the barriers and facilitators to the implementation of patient‐reported routine outcome measures and feedback in alcohol and other drug treatment
Authors: Pocuca Nina , Campbell Gabrielle , Barnett Anthony , Beck Alison K. , Ellem Rhiannon , Quinn Catherine A. , Kelly Peter J. , Larance Briony , Baker Amanda L. , Connor Jason P. , Marsden John , Chan Gary C. K. , Connelly Luke , Lenzen Sabrina , Farrell Michael , Stirling Robert , Hudson Suzie , Hides Leanne 
Published: February 2025

AbstractIntroductionPreliminary evidence supports the use of patient‐reported outcome measures (PROM) and feedback for enhancing client outcomes in alcohol and other drug (AOD) treatment. However, successful implementation remains challenging. This mixed‐methods study applied the Consolidated Framework for Implementation Research (CFIR) framework to examine inner setting and staff characteristics that act as barriers and facilitators to the implementation of PROMs in AOD treatment.MethodsTo understand CFIR‐informed barriers and facilitators to implement PROMs in AOD treatment, qualitative interviews were conducted with N = 23 AOD counsellors. A separate quantitative survey was conducted with N = 108 AOD counsellors.ResultsFour qualitative themes emerged: (i) PROMs and feedback are valuable to AOD treatment; (ii) counsellor resistance towards PROMs and feedback is a barrier to successful implementation; (iii) competing interests and logistical issues are barriers to the implementation of PROMs and feedback; and (iv) PROMs are a burden to clients that may serve to disengage them from treatment. Survey results indicated a positive association between leadership support (CFIR inner setting construct) and counsellor knowledge and beliefs regarding PROMs and feedback (CFIR staff characteristics construct; β = 0.35, 95% CI [0.13, 0.60]). Findings demonstrated a positive association between available PROMs resources (CFIR inner setting construct) and both knowledge and beliefs regarding PROMs and feedback (β = 0.31, 95% CI [0.14, 0.48]) and self‐efficacy to implement PROMs and feedback (CFIR staff characteristics construct; β = 0.18, 95% CI [0.04, 0.32]).Discussion and ConclusionsFindings point to the critical need to adopt a whole‐of‐organisation approach to foster buy‐in for PROMs and feedback to support successful implementation.
Development, dissemination and community response towards the first community notice regarding misrepresented illicit anabolic‐androgenic steroids in circulation in Australia
Authors: Piatkowski Timothy , Volpe Isabelle , Brien Rita , Coomber Ross , Barratt Monica , Kill Emma , Davey Geoff , Francis Cameron , Cresswell Sarah , White Alan , Harding Madeline , Blakey Karen , Reeve Steph , Walters Brooke , Ferris Jason , Puljević Cheneal 
Published: February 2025

AbstractIntroductionDrug alerts aimed at both people who use drugs and health workers help to prevent acute harms from unpredictable illicit drug markets and by equipping health workers to handle unusual drug events and share vital information with service users. However, there has never been an alert produced for anabolic‐androgenic steroids (AAS), an important class of illicit drugs. We report on the development, implementation and community receptivity of the first‐ever AAS community drug alert.MethodsBased on findings from samples collected during the first month of an AAS checking trial conducted by drug checking service CheQpoint, we identified contamination in two oxandrolone samples, which prompted issuing of the first‐ever AAS community notice. Drawing on digital ethnographic techniques, we collected and analysed social media comments on the notice to assess AAS community perceptions and the broader impact of this harm reduction initiative.ResultsThe Instagram post by CheQpoint reached 1376 users, with 3429 impressions and 87 interactions. Community feedback indicated receptivity to the notice, with several people in the community recognising the prevalence of AAS adulteration. Responses highlighted the need for more thorough testing and indication of sample content, given the perception of a growing number of new people using AAS.Discussion and ConclusionsThis study, the first to describe a community notice for illicit market AAS, reveals a strong demand for harm reduction interventions. We call for the urgent expansion of drug‐checking services to provision for AAS and, thus, provide equitable health support to address systemic gaps for this group.
Mapping Butterfly Species Richness and Abundance in Mountain Grasslands—Spatial Application of a Biodiversity Indicator
Authors: Barkmann Friederike , Tasser Erich , Tappeiner Ulrike , Huemer Peter , Schattanek‐Wiesmair Benjamin , Lechner Kurt , Ortner Alois , Rüdisser Johannes 
Published: February 2025

ABSTRACTAimThe integration of high‐quality field data with high‐resolution remote sensing data can give detailed insights into the spatial distribution of biodiversity and provide valuable information for biodiversity conservation at a scale relevant for management action. We developed a framework based on remote sensing data and field surveys for modelling species richness and abundance of butterflies at high spatial resolution to inform about the spatial distribution of butterfly species richness and abundance and analyse their drivers and the scale of effect of landscape factors.LocationWestern Austria.MethodsWe combined structured butterfly surveys at 175 grassland sites in western Austria with remote sensing variables describing topography, grassland characteristics, and the landscape composition and configuration at different radii around a site. For spatial predictions of butterfly species richness and abundance, generalised linear models with elastic net regularisation were used and compared with stepwise variable selection. To analyse the influence of selected variables and their scale of effect, models with landscape variables in different radii around the sites and variables describing topography were applied.ResultsFor species richness, the Spearman rank correlation between predicted and measured values was 0.62. For abundance, predictive power was lower with a correlation of 0.52. Models with variables from smaller radii (125 and 250 m) generally showed better predictive performance than those at larger radii (500 and 1000 m). We found an effect of elevation, maximum grassland productivity, northness, and forest ecotone density in most models.Main ConclusionsIntegrating remote sensing data with spatial modelling techniques substantially enhances our ability to understand patterns and identify key drivers of butterfly species richness at high spatial resolution. Our study highlights the positive influence of forest edges, small woody features, and moderate grassland productivity on butterfly species richness and abundance.
Heat shock‐pretreated bone marrow mesenchymal stem cells accelerate wound healing in a diabetic foot ulcer rat model
Authors: Lin Xi , Lin Qi 
Published: February 2025

AbstractBackgroundDiabetic foot ulcers (DFUs) are the severe chronic complications of diabetes, amputation is required when ulcers cause severe loss of tissue or evoke a life‐threatening infection. Mesenchymal stem cells (MSCs) have shown a good effect in helping DFU healing, though the efficiency needs to be improved. This study aimed to investigate the effects of heat shock pretreatment on the improvement of the therapeutic effects of MSCs.MethodsPrimary rat bone marrow MSCs (BMSCs) were isolated and stimulated with heat shock pretreatment and then tested on a DFU rat model. Alkaline phosphatase, Alizarin Red S, and Oil Red O were stained to check the osteogenic differentiation ability of heat shock‐pretreated BMSCs. The effect of heat shock pretreatment on the inflammatory response of macrophages was studied with the lipopolysaccharides stimulation model on a mouse macrophage cell line RAW264.7. The impact of heat shock‐pretreated BMSCs on dermal fibroblasts was also checked. Last, heat shock‐pretreated BMSCs were tested on a DFU rat model.ResultsHeat shock‐pretreated BMSCs were characterized by the expression of CD105 and CD44. Heat shock pre‐stimulation did not affect cell viability when cultured up to 96 h. Heat shock pre‐stimulated BMSCs inhibited the inflammatory response by reducing the pro‐inflammatory cytokine production (IL‐1β, IL‐6, and TNF‐α) and enhancing the anti‐inflammatory cytokine production (IL‐10) (at least all p < 0.01), as well as increasing the ratio of M2 polarization macrophages to M1 polarization in vitro (p < 0.001). Heat shock pre‐stimulated BMSCs enhanced the growth and migration of dermal fibroblasts in vitro (p < 0.001). Heat shock‐BMSCs promoted the M2 polarization level of macrophages in wound tissues in a DFU rat model.ConclusionHeat shock pretreatment could enhance the therapeutic effect of BMSCs on wound healing in a DFU rat model.
Adding social determinants of health to the equation: Development of a cardiometabolic disease staging model using clinical and social determinants of health to predict type 2 diabetes
Authors: Howell Carrie R. , Tanaka Shiori , Zhang Li , Carson April P. , Yi Nengjun , Shikany James M. , Garvey W. Timothy , Cherrington Andrea L. 
Published: February 2025

AbstractAimsIdentifying individuals at the highest risk of progression to type 2 diabetes (T2D) using clinical and social determinants of health (SDoH) measures will help prioritize prevention efforts. We aimed to investigate model performance after adding SDoH to a previously validated cardiometabolic disease staging diabetes risk prediction model.Materials and MethodsWe developed a Bayesian predictive model using data [clinical factors: fasting glucose, blood pressure, body mass index, high‐density lipoprotein cholesterol, triglycerides; individual SDoH: income, education, health insurance status, relationship status, self‐reported stress and neighbourhood SDoH: census‐tract level social vulnerability index] from the REasons for Geographic And Racial Differences in Stroke (REGARDS) study to predict T2D with external validation using the Coronary Artery Risk Development in Young Adults (CARDIA) study.ResultsThe analysis included 9907 REGARDS participants without T2D at baseline [mean age 63 years (SD 8.5), 54% female, 33% non‐Hispanic Black] who completed a follow‐up visit 10 years later. N = 1268 (12.8%) developed T2D. Adding SDoH to the clinical model modestly improved performance [Area Under the Curve: 0.802 vs. 0.804, p = 0.01]. Calibration plots indicated that the clinical model underpredicted risk in disadvantaged SDoH subgroups, whereas the clinical plus SDoH model improved prediction accuracy in subgroups. Classification tables revealed that the clinical plus SDoH model accurately reclassified individuals categorized as borderline risk in a clinical‐only model.ConclusionIncluding SDoH in T2D risk prediction and stratification at the population level may aid in better classifying T2D risk among vulnerable populations, which has important implications for screening strategies.