bluuebunny/crossref_metadata_2025_split huggingface dataset:
Validation of an ICD-code-based case definition for psychotic illness across three health systems
Authors: Deo Anthony J. , Castro Victor M. , Baker Ashley , Carroll Devon , Gonzalez-Heydrich Joseph , Henderson David C. , Holt Daphne J. , Hook Kimberly , Karmacharya Rakesh , Roffman Joshua L. , Madsen Emily M. , Song Eugene , Adams William G. , Camacho Luisa , Gasman Sarah , Gibbs Jada S. , Fortgang Rebecca G. , Kennedy Chris J. , Lozinski Galina , Perez Daisy C. , Wilson Marina , Reis Ben Y. , Smoller Jordan W. 
Published: February 2024

AbstractBackground and HypothesisEarly detection of psychosis is critical for improving outcomes. Algorithms to predict or detect psychosis using electronic health record (EHR) data depend on the validity of the case definitions used, typically based on diagnostic codes. Data on the validity of psychosis-related diagnostic codes is limited. We evaluated the positive predictive value (PPV) of International Classification of Diseases (ICD) codes for psychosis.Study DesignUsing EHRs at three health systems, ICD codes comprising primary psychotic disorders and mood disorders with psychosis were grouped into five higher-order groups. 1,133 records were sampled for chart review using the full EHR. PPVs (the probability of chart-confirmed psychosis given ICD psychosis codes) were calculated across multiple treatment settings.Study ResultsPPVs across all diagnostic groups and hospital systems exceeded 70%: Massachusetts General Brigham 0.72 [95% CI 0.68-0.77], Boston Children’s Hospital 0.80 [0.75-0.84], and Boston Medical Center 0.83 [0.79-0.86]. Schizoaffective disorder PPVs were consistently the highest across sites (0.80-0.92) and major depressive disorder with psychosis were the most variable (0.57-0.79). To determine if the first documented code captured first-episode psychosis (FEP), we excluded cases with prior chart evidence of a diagnosis of or treatment for a psychotic illness, yielding substantially lower PPVs (0.08–0.62).ConclusionsWe found that the first documented psychosis diagnostic code accurately captured true episodes of psychosis but was a poor index of FEP. These data have important implications for the development of risk prediction models designed to predict or detect undiagnosed psychosis.
Artificial Intelligence in Healthcare: 2023 Year in Review
Authors: Awasthi Raghav , Mishra Shreya , Grasfield Rachel , Maslinski Julia , Mahapatra Dwarikanath , Cywinski Jacek B. , Khanna Ashish K. , Maheshwari Kamal , Dave Chintan , Khare Avneesh , Papay Francis A. , Mathur Piyush 
Published: February 2024

ABSTRACTBackgroundThe infodemic we are experiencing with AI related publications in healthcare is unparalleled. The excitement and fear surrounding the adoption of rapidly evolving AI in healthcare applications pose a real challenge. Collaborative learning from published research is one of the best ways to understand the associated opportunities and challenges in the field. To gain a deep understanding of recent developments in this field, we have conducted a quantitative and qualitative review of AI in healthcare research articles published in 2023.MethodsWe performed a PubMed search using the terms, “machine learning” or “artificial intelligence” and “2023”, restricted to English language and human subject research as of December 31, 2023 on January 1, 2024. Utilizing a Deep Learning-based approach, we assessed the maturity of publications. Following this, we manually annotated the healthcare specialty, data utilized, and models employed for the identified mature articles. Subsequently, empirical data analysis was performed to elucidate trends and statistics.Similarly, we performed a search for Large Language Model(LLM) based publications for the year 2023.ResultsOur PubMed search yielded 23,306 articles, of which 1,612 were classified as mature. Following exclusions, 1,226 articles were selected for final analysis. Among these, the highest number of articles originated from the Imaging specialty (483), followed by Gastroenterology (86), and Ophthalmology (78). Analysis of data types revealed that image data was predominant, utilized in 75.2% of publications, followed by tabular data (12.9%) and text data (11.6%). Deep Learning models were extensively employed, constituting 59.8% of the models used. For the LLM related publications,after exclusions, 584 publications were finally classified into the 26 different healthcare specialties and used for further analysis. The utilization of Large Language Models (LLMs), is highest in general healthcare specialties, at 20.1%, followed by surgery at 8.5%.ConclusionImage based healthcare specialities such as Radiology, Gastroenterology and Cardiology have dominated the landscape of AI in healthcare research for years. In the future, we are likely to see other healthcare specialties including the education and administrative areas of healthcare be driven by the LLMs and possibly multimodal models in the next era of AI in healthcare research and publications.
Tissue-specific and endogenous protein labeling with split fluorescent proteins
Authors: Ligunas Gloria D. , Paniagua German , LaBelle Jesselynn , Ramos-Martinez Adela , Shen Kyle , Gerlt Emma H. , Aguilar Kaddy , Nguyen Alice , Materna Stefan C. , Woo Stephanie 
Published: February 2024

AbstractThe ability to label proteins by fusion with genetically encoded fluorescent proteins is a powerful tool for understanding dynamic biological processes. However, current approaches for expressing fluorescent protein fusions possess drawbacks, especially at the whole organism level. Expression by transgenesis risks potential overexpression artifacts while fluorescent protein insertion at endogenous loci is technically difficult and, more importantly, does not allow for tissue-specific study of broadly expressed proteins. To overcome these limitations, we have adopted the split fluorescent protein system mNeonGreen21-10/11(split-mNG2) to achieve tissue-specific and endogenous protein labeling in zebrafish. In our approach, mNG21-10is expressed under a tissue-specific promoter using standard transgenesis while mNG211is inserted into protein-coding genes of interest using CRISPR/Cas-directed gene editing. Each mNG2 fragment on its own is not fluorescent, but when co-expressed the fragments self-assemble into a fluorescent complex. Here, we report successful use of split-mNG2 to achieve differential labeling of the cytoskeleton genestubb4bandkrt8in various tissues. We also demonstrate that by anchoring the mNG21-10component to specific cellular compartments, the split-mNG2 system can be used to manipulate protein function. Our approach should be broadly useful for a wide range of applications.
Drug inhibition and substrate alternating flipping mechanisms of human VMAT2
Authors: Wei Feiwen , Liu Huihui , Zhang Wei , Wang Jufang , Zhang Yanqing 
Published: February 2024

AbstractVesicular monoamine transporters (VMAT1/2) are responsible for loading and packaging monoamine neurotransmitters into synaptic vesicles, including serotonin (5-HT), dopamine (DA), norepinephrine, and histamine. Dysregulation of VMAT2 within the central nervous system can lead to schizophrenia, mood disorders, and Parkinson’s disease, due to the imbalances of these monoamine neurotransmitters. Medications such as tetrabenazine (TBZ) and valbenazine (VBZ) targetting VMAT2 are approved for treating chorea associated with Huntington’s disease and Tardive Dyskinesia. Our cryo-EM studies and molecular dynamics (MD) simulations on VMAT2 bound to drug inhibitors (TBZ and VBZ) and substrates (5-HT and DA), unveil the inhibition mechanism of VMAT2, alternating flipping mechanism of substrates during loading, translocation, and release, as well as the interplay between protonation of crucial acidic residues and substrate release. These findings enhance the understanding of VMAT-mediated monoamine neurotransmitter transport, fostering drug development for neurological and neuropsychiatric disorders, with a specific emphasis on VMATs.
DVL1variants and C-terminal deletions have differential effects on craniofacial development and WNT signaling
Authors: Tophkhane Shruti S. , Gignac Sarah J. , Fu Katherine , Verheyen Esther M. , Richman Joy M. 
Published: February 2024

AbstractRobinow Syndrome (RS) is a rare disease characterized by craniofacial malformations and limb shortening linked with mutations in seven WNT pathway genes. Our objective was to investigate the functional effects of frameshift mutations the intracellular adaptor protein, Dishevelled (DVL1;c.1519ΔT, p.Trp507Glyfs*142) on chicken craniofacial development. Misexpression of wt (wt) or mutant hDVL1variants in vivo caused upper beak shortening (wtDVL1n=8/14;DVL11519ΔT12/13). At early stages of development, theDVL11519ΔTinhibited frontonasal mass narrowing, chondrogenesis, and proliferation. To test whether the phenotypes were caused due to the abnormal C-terminal peptide inDVL11519ΔT, we designed two additional constructs. TheDVL11519*(DVL1507*) retains first 30 amino acids of the C-terminus whileDVL11431*(DVL1477*) removes the entire C-terminus.DVL11519*injected embryos had normal beaks whileDVL11431*caused high mortality and the phenotypes were like theDVL11519ΔT. In frontonasal micromass cultures, bothDVL11519ΔTandDVL11431*inhibited skeletogenesis while theDVL11519*resembled wtDVL1andGFPcultures. In luciferase assaysDVL11519ΔT,DVL11519*andDVL11431*weakly activated the WNT canonical and non-canonical JNK-PCP pathways compared to wtDVL1. Furthermore, we observed that variant DVL1507*fsis stalled in the nucleus similar to hDVL1477*, possibly due to the abnormal C-terminus interfering with the nuclear export sequence. wtDVL1 and DVL1507*were distributed in nucleus and the cytoplasm. Our RS-DVL11519ΔTavian model recapitulates the broad face and jaw hypoplasia and demonstrates defects in both branches of WNT signaling. This is the first study to clarify the role of abnormal C-terminus in ADRS and to recognize the importance of an uncharacterized C-terminal sequence.Summary StatementFunctional and biochemical studies on chicken embryos with the Robinow syndrome (RS)DVL1variant demonstrate defects in skeletogenesis and both branches of WNT signaling. This is the first study to establish a link between the RS facial defects and the mutated C-terminal sequence. We identified first 30 amino acids of theDVL1C-terminus are sufficient for normal development.
Collective polaritonic effects on chemical dynamics suppressed by disorder
Authors: Pérez-Sánchez Juan B. , Mellini Federico , Giebink Noel C. , Yuen-Zhou Joel 
Published: February 2024

We present a powerful formalism, disordered collective dynamics using truncated equations (d-CUT-E), to simulate the ultrafast quantum dynamics of molecular polaritons in the collective strong coupling regime, where a disordered ensemble of N≫106 molecules couples to a cavity mode. Notably, we can capture this dynamics with a cavity hosting a single molecule with ∼Nbins electronic states, where Nbins≪N is the number of bins discretizing the disorder distribution. Using d-CUT-E we conclude that strong coupling, as evaluated from linear optical spectra, can be a poor proxy for polariton chemistry. For highly disordered ensembles, total reaction yield upon broadband excitation is identical to that outside of the cavity, while narrowband excitation produces distinct reaction yields solely due to differences in the initial states prepared prior to the reaction.

Published by the American Physical Society
2024
Emergent leadership in agile software development teams: leader identification through network analysis and aggregation approaches
Authors: Tabassum Marya , Raziq Muhammad Mustafa , Sarwar Naukhez 
Published: February 2024

PurposeAgile project teams are self-managing and self-organizing teams, and these two characteristics are pivotal attributes of emergent leadership. Emergent leadership is thus common in agile teams – however, how these (informal) emergent leaders can be identified in teams remains far from understood. The purpose of this research is to uncover techniques that enable top management to identify emergent agile leaders.Methodology/designWe approached six agile teams from four organizations. We employ social network analysis (SNA) and aggregation approaches to identify emergent agile leaders.Design/methodology/approachWe approached six agile teams from four organizations. We employ SNA and aggregation approaches to identify emergent agile leaders.FindingsSeven emergent leaders are identified using the SNA and aggregation approaches. The same leaders are also identified using the KeyPlayer algorithms. One emergent leader is identified from each of the five teams, for a total of five emergent leaders from the five teams. However, two emergent leaders are identified for the remaining sixth team.Originality/valueEmergent leadership is a relatively new phenomenon where leaders emerge from within teams without having a formal leadership assigned role. A challenge remains as to how such leaders can be identified without any formal leadership status. We contribute by showing how network analysis and aggregation approaches are suitable for the identification of emergent leadership talent within teams. In addition, we help advance leadership research by describing the network behaviors of emergent leaders and offering a way forward to identify more than one emergent leader in a team. We also show some limitations of the approaches used and offer some useful insights.
Clothing image attribute editing based on generative adversarial network, with reference to an upper garment
Authors: Wang Wei-Zhen , Xiao Hong-Mei , Fang Yuan 
Published: February 2024

PurposeNowadays, artificial intelligence (AI) technology has demonstrated extensive applications in the field of art design. Attribute editing is an important means to realize clothing style and color design via computer language, which aims to edit and control the garment image based on the specified target attributes while preserving other details from the original image. The current image attribute editing model often generates images containing missing or redundant attributes. To address the problem, this paper aims for a novel design method utilizing the Fashion-attribute generative adversarial network (AttGAN) model was proposed for image attribute editing specifically tailored to women’s blouses.Design/methodology/approachThe proposed design method primarily focuses on optimizing the feature extraction network and loss function. To enhance the feature extraction capability of the model, an increase in the number of layers in the feature extraction network was implemented, and the structure similarity index measure (SSIM) loss function was employed to ensure the independent attributes of the original image were consistent. The characteristic-preserving virtual try-on network (CP_VTON) dataset was used for train-ing to enable the editing of sleeve length and color specifically for women’s blouse.FindingsThe experimental results demonstrate that the optimization model’s generated outputs have significantly reduced problems related to missing attributes or visual redundancy. Through a comparative analysis of the numerical changes in the SSIM and peak signal-to-noise ratio (PSNR) before and after the model refinement, it was observed that the improved SSIM increased substantially by 27.4%, and the PSNR increased by 2.8%, serving as empirical evidence of the effectiveness of incorporating the SSIM loss function.Originality/valueThe proposed algorithm provides a promising tool for precise image editing of women’s blouses based on the GAN. This introduces a new approach to eliminate semantic expression errors in image editing, thereby contributing to the development of AI in clothing design.
Nexus among green intellectual capital, green information systems, green management initiatives and sustainable performance: a mediated-moderated perspective
Authors: Riaz Adil , Cepel Martin , Ferraris Alberto , Ashfaq Khurram , Rehman Shafique Ur 
Published: February 2024

PurposeSustainability issues are crucial in today’s competitive environment. The integration of technology plays a vital role in the attainment of sustainability objectives. The study aims to investigate the relationship between green intellectual capital (IC), green information systems (IS), green management initiatives (GMI) and green technology adoption in light of natural resource-orchestration theory (ROT). Moreover, digital technology adoption mediates between green IC, green IS, GMI and sustainable performance. Finally, digital transformation strategy is used as a moderator between green technology adoption and sustainable performance.Design/methodology/approachA sample of 484 managers from automobile manufacturing companies was used in this study to evaluate the proposed relationships using the Structural Equation Modeling (SEM) methodology.FindingsFindings reveal that green IC, green IS and GMI significantly influence green technology adoption. Besides, green technology adoption plays a crucial role in improving sustainable performance. Moreover, green technology adoption significantly mediates between green IC, green IS, GMI and sustainable performance. Finally, a digital transformation strategy significantly strengthens the relationship between green technology adoption and sustainable performance.Practical implicationsThe organizations need green technology adoption to address environmental concerns, respond to consumer demand, achieve cost savings and comply with government regulations. Besides, in decision-making, organizations must focus on green IC, green IS, GMI, green technology adoption and digital transformation strategy to boost sustainable performance.Originality/valueThe originality of this study lies in its use of the natural ROT as a framework to examine the impact of multiple green resources on green technology adoption, leading to sustainable performance. Digital transformation strategy is used as a moderator between green technology adoption and sustainable performance. This study provides a comprehensive and integrated perspective on the subject with empirical evidence and relevant insights, contributing to the advancement of the field.
Digital tendencies in public libraries in Balochistan, Pakistan: issues and challenges
Authors: Jabeen Munazza , Aslam Sanila , Zareef Muhammad , Zaman Farzana 
Published: February 2024

PurposeIn the digital age, public libraries are facing numerous challenges, and the Balochistan public libraries are no exception. This study aimed to identify current digital trends adopted by the public libraries in Balochistan and to find out about challenges and potential solutions regarding digital trends from library users.Design/methodology/approachA quantitative study was carried out and data were collected through the survey method, employing a structured questionnaire. The target population consisted of 17,953 users of 17 public libraries in Balochistan. A sample of 510 users both male and female was selected by using random sampling technique from the target population.FindingsThe analysis revealed that patrons of public libraries are dissatisfied with the services offered, as they now require access to new digital trends such as fast Internet, download facilities, unlimited content on numerous resources, Wi-Fi, online reference services, universal accessibility and user-friendly interfaces. Unfortunately, public libraries in Balochistan are still lagging in terms of development. The study recommended that public libraries in Balochistan should develop and implement digital services, increase access to digital resources, hire professional librarians, professional development and collaborate with other libraries.Originality/valueThe study’s findings can assist in improving public library services and granting patrons access to current information and resources in Balochisthan and other developing countries. This study’s originality stems from its use of a quantitative survey approach to gather data from 17 public libraries in Balochisthan and provide a comprehensive view of the digital challenges they face. The study’s focus on digital tendencies is relevant in today’s world, where technology is rapidly changing the way, we access and consume information.
Role of product advantage in shaping product outcome: a hybrid review
Authors: Kalro Hitesh , Joshipura Mayank 
Published: February 2024

PurposeThis study examines current dynamics, consolidates current knowledge, elicits trends, identifies and analyzes primary research clusters, offers future directions, and develops an integrated framework for Product Advantage (PA) research.Design/methodology/approachUsing the SCOPUS database, this study applied bibliometric analysis (208 articles) and conducted content analysis on the 35 curated articles selected using a combination of bibliographic coupling and the most cited articles.FindingsThis study presents the field’s publication trends, most relevant authors, articles, journals, and knowledge structures. It identifies six primary research themes and four major clusters using the thematic map and bibliographic coupling. Marketing and PA, New Product Development (NPD) and PA, Product Innovation and PA, and New product speed and PA are the main clusters. Finally, this study offers directions for future research and provides an integrated framework for PA research.Practical implicationsBy developing an ADO framework of PA, the study offers key insights into how PA shapes product outcomes and identifies key antecedents of PA. Firms must focus on firm factors such as market and technological orientation; product factors, such as development time and pre-announcement proficiency; external factors, such as competition; and environmental factors, such as competitive intensity and technological turbulence. It enables firms to create products with high PA, shaping product outcomes and contributing to their competitive advantage.Originality/valueThis is the first study to conduct a two-stage sequential hybrid review of quality articles on PA. It offers an Antecedents-Decisions-Consequences (ADO) framework based on significant studies and offers cluster-wise directors for future research.
“It's kind of preventative maintenance”: social capital and policing in rural schools
Authors: Spencer Dale C. , Ricciardelli Rosemary , Hepburn Taryn 
Published: February 2024

PurposeThe purpose of this article is to examine the expectations, challenges and tensions officers describe while engaged with public schools to demonstrate that officers engage with students in public schools in a conscious, goal-oriented process to establish and maintain useful relationships.Design/methodology/approachData collection involved 104 semi-structured interviews (including follow up interviews) and 31 focus groups, conducted between 2014 and 2018 with police officers working in rural areas of a province in Atlantic Canada.FindingsUtilizing the concept of social capital, we analyze practices of investments alongside the understanding of rurality as socially interconnected and the rural school as a particular site of interconnectedness for police officers. We demonstrate how, while accumulating social capital, officers face role tension and fundamental barriers when trying to integrate into rural school communities.Originality/valueBy demonstrating the specificities of building social capital in schools and community environments in a rural setting, we contribute to understandings regarding the unique opportunities and challenges faced by police in rural schools in integrating effectively into schools and responding to youth-specific problems.