bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recent Advances in Sustainable Total Synthesis and Chiral Pool Strategies with Emphasis on (−)‐Sclareol in Natural Products Synthesis
Authors: Selka Ayyoub , Abidli Abdelnasser , Schiavo Lucie , Jeanmart Loïc , Hanquet Gilles , Lubell William D. 
Published: December 2024

AbstractStarting materials for sustainable total synthesis often come from the chiral pool: carbohydrates, cyclitols, amino acids, and terpenes. In the terpene family, (−)‐sclareol has served as a sustainable, readily available, and versatile chiral building block for the synthesis of numerous natural products. (−)‐Sclareol possesses a unique structure that has consequently promoted its integration as a core framework within various structurally complex and biologically active substances, including sesquiterpenoids, diterpenoids, and sesterterpenoids. (−)‐Sclareol has facilitated access to diverse synthetic key intermediates, promoting the sustainable synthesis of several natural products. Herein, a review is presented covering the recent trends in sustainable total syntheses and the application of chiral pool approaches with emphasis on the preparation of natural products through diverse routes employing (−)‐sclareol as chiral educt. Innovative catalytic and synthetic protocols using (−)‐sclareol are also analyzed and discussed.
Recent Advances in Diphenylmethanone Oxime Reagent Chemistry for Unsaturated Bond Bifunctionalization via Energy Transfer Catalysis
Authors: Luo Xue‐Ling , Luo Di‐Jing , Qin Lu‐Lu , Ye Zhi‐Peng , Xia Peng‐Ju 
Published: December 2024

AbstractThe concurrent installation of C−X (C, O, S, N) and C−N bonds across unsaturated bond skeletons is an effective strategy for the preparation of ubiquitous motifs in pharmaceuticals and bioactive compounds. In recent years, the rapid development of bifunctionalization reactions has resulted in the emergence of bifunctional reagents as a research hotspot in this field. Among these, diphenylmethanone oxime reagents with highly active N−O bonds featuring low dissociation energy have significantly advanced the research of bifunctionalization. These reagents possess special features to simultaneously form two chemical bonds or introduce two functional groups, which not only streamlines synthetic pathways but also enhances synthetic efficiency, displaying an excellent atom‐ and step‐economy. In addition, diphenylmethanone oxime reagents have been extensively employed in organic synthesis, attributed to their ability to facilitate the construction of complex organic structures and to provide innovative reaction pathways. In this review, we present a comprehensive overview of various diphenylmethanone oxime reagents and their applications in the bifunctional modification of unsaturated bonds through visible‐light‐mediated triplet–triplet energy transfer catalysis (TTEnT).
Electrochemical Oxidative Hydroxychalcogenation of Olefins with Disulfides/Thiols/Diselenides and H2O as Nucleophilic Oxygen Sources
Authors: Li Wenxue , Li Junwu , Sun Fengkai , Miao Man , Lan Xiao‐Bing , Yu Jian‐Qiang , Liu Pengpeng , Li Houyuan , Wang Rui , Zhang Jian , An Zhenyu 
Published: December 2024

AbstractA direct electrochemical redox reaction of olefins and disulfides/thiols/diselenides without external oxidants has been developed, which includes the hydroxychalcogenation of olefins. This procedure exhibited good functional group tolerance, and a series of β‐hydroxysulfide/β‐hydroxyselenide derivatives were obtained in moderate to good yields. Mechanistic studies and cyclic voltammetry were also conducted to elucidate the reaction process.
Review: Biomacromolecules‐based encapsulation technologies for the protection of oxygen‐sensitive next‐generation probiotics
Authors: Phùng Thị‐Thanh‐Trúc , Karbowiak Thomas 
Published: December 2024

AbstractIn the recent years, various strains of the gut microbiota have been discovered to possess significant therapeutic potential, they are defined as next‐generation probiotics (NGPs). Akkermansia, Faecalibacterium, Bacteriodes, Eubacterium, and Bifidobacteria are among the typical NGP strains which exhibit several interesting bioactivities as live biotherapeutics. However, some strains of NGP are extremely sensitive to oxygen, such as Faecalibacterium prausnitzii. This hinders their cultivation and large‐scale production. Therefore, it is essential to develop a strategy to protect them during production, storage, and colonic administration. This review, highlights key NGP strains developed in recent years, alongside the encapsulation strategies used to protect them. The primary criterion for selecting encapsulating techniques is their feasibility to be performed under strictly anaerobic conditions. Various processes have been selected according to the physical forms of the products, including liquid, gel, and solid forms, as well as the final shaping of the product. The critical factors for selecting encapsulation materials include biocompatibility, safety, effective oxygen barrier properties, and an optimal release profile in the gastrointestinal tract. This review discusses protection strategies aimed at improving the survival and thereby effectiveness of NGPs.
Prevalence and Factors Associated With Severity of Undernutrition Among Children Aged 6–59 Months in Tanzania
Authors: Khamis Ahmed Gharib , Mwanri Akwilina Wendelin , Ntwenya Julius Edward 
Published: December 2024

ABSTRACTUndernutrition has been identified as a significant public health challenge in developing nations like Tanzania. Severe childhood undernutrition is a life‐threatening problem that can result in impaired growth, weakened immune systems, and even death. The primary aim of this study was to identify the prevalence of multiple forms of severe undernutrition and factors associated with the severity of childhood undernutrition in children aged 6–59 months in Tanzania. This was a secondary data analysis conducted on a cross‐sectional survey obtained from the 2022 Tanzania Demographic and Health Survey Malaria Indicator Survey (TDHS‐MIS). This analysis comprised 4224 children with complete information. The study employed the proportional odds model of ordinal logistic regression to identify factors associated with severity of stunting, wasting, and anemia. Out of the 4224 included children, 8.6% were severely stunted, 0.8% were severely wasted, and 1.7% were severely anemic. The prevalence of multiple forms of severe undernutrition was 10.4%. Significant associations were observed between socioeconomic factors—including the gender and age of the household head, household wealth status, possession of health insurance, and availability of mosquito nets with severe undernutrition. Maternal factors such as nutrition status, current age, age at first birth, education, marriage, and occupation were related to the severity of undernutrition. Approximately one children out of every 10 suffers from some form of severe undernutrition in Tanzania. Several factors including maternal and socioeconomic were identified as potentially influencing severe undernutrition. Multifaceted efforts are required to lessen the severity of undernutrition.
Explainable machine learning model for pre‐frailty risk assessment in community‐dwelling older adults
Authors: Du Chenlin , Zhang Zeyu , Liu Baoqin , Cao Zijian , Jiang Nan , Zhang Zongjiu 
Published: December 2024

AbstractBackgroundFrailty in older adults is linked to increased risks and lower quality of life. Pre‐frailty, a condition preceding frailty, is intervenable, but its determinants and assessment are challenging. This study aims to develop and validate an explainable machine learning model for pre‐frailty risk assessment among community‐dwelling older adults.MethodsThe study included 3141 adults aged 60 or above from the China Health and Retirement Longitudinal Study. Pre‐frailty was characterized by one or two criteria from the physical frailty phenotype scale. We extracted 80 distinct features across seven dimensions to evaluate pre‐frailty risk. A model was constructed using recursive feature elimination and a stacking‐CatBoost distillation module on 80% of the sample and validated on a separate 20% holdout data set.ResultsThe study used data from 2508 community‐dwelling older adults (mean age, 67.24 years [range, 60–96]; 1215 [48.44%] females) to develop a pre‐frailty risk assessment model. We selected 57 predictive features and built a distilled CatBoost model, which achieved the highest discrimination (AUROC: 0.7560 [95% CI: 0.7169, 0.7928]) on the 20% holdout data set. The living city, BMI, and peak expiratory flow (PEF) were the three most significant contributors to pre‐frailty risk. Physical and environmental factors were the top 2 impactful feature dimensions.ConclusionsAn accurate and interpretable pre‐frailty risk assessment framework using state‐of‐the‐art machine learning techniques and explanation methods has been developed. Our framework incorporates a wide range of features and determinants, allowing for a comprehensive and nuanced understanding of pre‐frailty risk.
How an Airport Strike in Copenhagen Led to the Discovery of Septohippocampal Disinhibition
Authors: Freund Tamás F. 
Published: December 2024

ABSTRACTMy most important contribution to research on the hippocampus was the discovery that certain phylogenetically ancient subcortical nuclei that carry information about motivation, emotions and autonomic state exert their profound effects on hippocampal functions by selectively innervating interneurons. Diverse effects on network activity patterns and plasticity can be achieved via activating or inhibiting these functionally distinct interneuron types. In the following, I will present the series of serendipitous events that prompted me to shift my research interest from the visual cortex and the basal ganglia to the hippocampus and its subcortical control.
Choline kinases: Enzymatic activity, involvement in cancer and other diseases, inhibitors
Authors: Korbecki Jan , Bosiacki Mateusz , Kupnicka Patrycja , Barczak Katarzyna , Ziętek Paweł , Chlubek Dariusz , Baranowska‐Bosiacka Irena 
Published: December 2024

AbstractOne of the aspects of tumor metabolism that distinguish it from healthy tissue is the phosphorylation of choline by choline kinases, which initiates the synthesis of phosphatidylcholine. Presently, there is a lack of comprehensive reviews discussing the current understanding of the role of choline kinase in cancer processes, as well as studies on the anti‐tumor properties of choline kinase inhibitors. To address these gaps, this review delves into the enzymatic and non‐enzymatic properties of CHKα and CHKβ and explores their precise involvement in cancer processes, particularly cancer cell proliferation. Additionally, we discuss clinical aspects of choline kinases in various tumor types, including pancreatic ductal adenocarcinoma, ovarian cancer, lung adenocarcinoma, lymphoma, leukemia, hepatocellular carcinoma, colon adenocarcinoma, and breast cancer. We examine the potential of CHKα inhibitors as anti‐tumor drugs, although they are not yet in the clinical trial phase. Finally, the paper also touches upon the significance of choline kinases in non‐cancerous diseases.
Using life history traits to assess climate change vulnerability in understudied species
Authors: Hinderer Ross K. , Hossack Blake R. , Eby Lisa A. 
Published: December 2024

AbstractClimate change is a primary threat to biodiversity, but for many species, we still lack information required to assess their relative vulnerability to changes. Climate change vulnerability assessment (CCVA) is a widely used technique to rank relative vulnerability to climate change based on species characteristics, such as their distributions, habitat associations, environmental tolerances, and life‐history traits. However, for species that we expect are vulnerable to climate change yet are understudied, like many amphibians, we often lack information required to construct CCVAs using existing methods. We used the CCVA framework to construct trait‐based models based on life history theory, using empirical evidence of traits and distributions that reflected sensitivity of amphibians to environmental perturbation. We performed CCVAs for amphibians in 7 states in the north‐central USA, focusing on 31 aquatic‐breeding species listed as species of greatest conservation need by at least 1 state. Because detailed information on habitat requirements is unavailable for most amphibian species, we used species distributions and information on traits expected to influence vulnerability to a drying climate (e.g., clutch size and habitat breadth). We scored species vulnerability based on changes projected for mid‐century (2040−2069) from 2 climate models representing “least‐dry” and “most‐dry” scenarios for the region. Species characteristics useful for discriminating vulnerability in our models included small range size, small clutch size, inflexible diel activity patterns, and smaller habitat breadth. When projected climate scenarios included a mix of drier and wetter conditions in the future, the exposure of a species to drying conditions was most important to relative rankings. When the scenario was universally drier, species characteristics were more important to relative rankings. Using information typically available even for understudied species and a range of climate projections, our results highlight the potential of using life history traits as indicators of relative climate vulnerability. The commonalities we identified provide a framework that can be used to assess other understudied species threatened by climate change.
Finite Element and Density Functional Theory Modeling Effectively Predict Pitting Degradation of Hydroxyapatite‐Coated Pure Magnesium
Authors: Dunne Reese A. , Dickel Doyl E. , Green Addison M. , Kim Dam , Priddy Lauren B. , Priddy Matthew W. 
Published: December 2024

ABSTRACTThe emergence of degradable orthopedic implants for fracture fixation may abrogate the need for implant removal surgery and minimize pain associated with permanent implants. Magnesium (Mg) and its alloys are being explored as a biomaterial for degradable implants due to mechanical properties similar to those of bone. Previous in vitro studies have determined the degradation rate of pure Mg to be relatively fast when compared to bone regeneration. Hydroxyapatite (HA), the mineral component of bone, may serve as a surface coating on Mg‐based implants to effectively slow and control the degradation rate. The objective of this work was to develop and implement a finite element (FE) model that utilizes a damage evolution law for pitting corrosion to predict the degradation of pure Mg (non‐coated) and HA‐coated pure Mg (coated) materials simulated in physiological conditions. Finite element analysis (FEA) was performed on a cylindrical Mg specimen (25.4 mm diameter, 8 mm height) through Abaqus/Standard software to incrementally monitor the damage value of each Mg element and subsequently delete fully‐degraded elements from the simulation. A Fortran user‐material (UMAT) subroutine assigned each element a pitting parameter, controlling the rate of degradation throughout the simulation and providing necessary inputs of elastic material properties and degradation model parameters for pure Mg and HA into Abaqus. The simulations allowed for the visualization of both pure Mg and HA‐coated pure Mg degradation over a 120‐day period, displaying expected degradation trends such as lower corrosion rates for HA‐coated Mg and degradation propagating from the edges inward. Simulation results were calibrated with our prior results from a 30‐day experimental degradation study via direct comparison with mass loss over time. Additionally, lower length scale, density functional theory (DFT) simulations were performed to provide physical meaning for the model pitting parameter. The FE simulation was extended to model resin‐enclosed pure Mg and HA‐coated pure Mg degradation, where only the top surface of the specimen was exposed to the corrosion surface, for investigating changes in Mg surface roughness (height) over time. The impacts of this work include the establishment of a computational model of pure Mg and HA‐coated pure Mg degradation calibrated using in vitro degradation data to advance the use of Mg‐based biomaterials, and more broadly, to predict degradation rates of next‐generation orthopedic implants.
Who Will Rule the Waves? Geopolitical Threats to Maritime Infrastructure
Authors: Braw Elisabeth 
Published: December 2024

ABSTRACTAdherence to global maritime rules is indispensable for the functioning of maritime operations and, as a result, the globalized economy. Though maritime rules and conventions have never seen perfect compliance, adherence is waning. A wide range of companies and even national governments openly violate maritime rules, and some even engage in aggression. That puts maritime activities and the ocean's health in jeopardy and threatens the maritime order itself.
Brain‐derived neurotrophic factor as a promising neuromarker which could predict psychomotor developmental impairment in children with unrepaired congenital heart defects
Authors: Chiperi Lacramioara Eliza , Hagau Asmaa Carla , Tecar Cristina , Hutanu Adina , Muntean Iolanda 
Published: December 2024

AbstractIntroductionThe aim of the study was to assess the predicting value of neuromarkers for psychomotor performances of congenital heart defect (CHD) patients before surgery, as until now the researchers only evaluated neuromarkers after the surgical treatment of the CHD.MethodsThis cross‐sectional study included children with CHD who did not receive treatment (interventional or cardiac surgery). Psychomotor development was evaluated using the Denver II Screening Test. Blood samples were collected for neuromarkers analysis: neuron‐specific enolase (NSE), protein S100 (pS100), brain‐derived neurotrophic factor (BDNF), and glial fibrillary acidic protein (GFAP).ResultsWe enrolled 77 children. Patients with CHD experienced more frequent developmental delays compared to healthy children (12–34% in the non‐cyanotic group and 26–74% in the cyanotic group). The association between type of CHD and psychomotor impairment was statistically significant (p < 0.0001, RR = 2.604, CI = 2.07–3.26). Neuromarkers value was compared between cyanotic and non‐cyanotic groups: NSE and BDNF values were higher in the cyanotic group, respectively, pS100 and GFAP had slightly higher values in the non‐cyanotic group. A correlation coefficient of 0.35 (p = 0.023) was obtained between psychomotor development and BDNF level. An AUC of 0.72 was obtained for psychomotor development and BDNF in ROC analysis with the cut‐off value of 5895 pg/ml.ConclusionBDNF is showing moderate discriminative ability in predicting psychomotor development outcomes in pediatric patients with CHD.
Leveraging transfer learning for predicting total knee arthroplasty failure from post‐operative radiographs
Authors: Corti Anna , Galante Sarah , Rauch Rebecca , Chiappetta Katia , Corino Valentina , Loppini Mattia 
Published: December 2024

AbstractPurposeThe incidence of both primary and revision total knee arthroplasty (TKA) is expected to rise, making early recognition of TKA failure crucial to prevent extensive revision surgeries. This study aims to develop a deep learning (DL) model to predict TKA failure using radiographic images.MethodsTwo patient cohorts who underwent primary TKA were retrospectively collected: one was used for the model development and the other for the external validation. Each cohort encompassed failed and non‐failed subjects, according to the need for TKA revision surgery. Moreover, for each patient, one anteroposterior and one lateral radiographic view obtained during routine TKA follow‐up, were considered. A transfer learning fine‐tuning approach was employed. After pre‐processing, the images were analyzed using a convolutional neuronal network (CNN) that was originally developed for predicting hip prosthesis failure and was based on the Densenet169 pre‐trained on Imagenet. The model was tested on 20% of the images of the first cohort and externally validated on the images of the second cohort. Metrics, such as accuracy, sensitivity, specificity and area under the receiving operating characteristic curve (AUC), were calculated for the final assessment.ResultsThe trained model correctly classified 108 out of 127 images in the test set, providing a classification accuracy of 0.85, sensitivity of 0.80, specificity of 0.89 and AUC of 0.86. Moreover, the model correctly classified 1547 out of 1937 in the external validation set, providing a balanced accuracy of 0.79, sensitivity of 0.80, specificity of 0.78 and AUC of 0.86.ConclusionsThe present DL model predicts TKA failure with moderate accuracy, regardless of the cause of revision surgery. Additionally, the effectiveness of the transfer learning fine‐tuning approach, leveraging a previously developed DL model for hip prosthesis failure, has been successfully demonstrated.Level of EvidenceLevel III, diagnostic study.
Haddon matrix model: Application to workplace violence in a hospital setting
Authors: Derscheid Della J. , Meyer Christopher , Arnetz Judith E. 
Published: December 2024

AbstractThe aim of this study was to identify hospital‐based workplace violence (WPV) risk factors with the Haddon Matrix Model (HMM) to determine its potential utility to conceptualize multiple risks for WPV events. This descriptive study utilized two independent convenience samples Data from behavioral emergencies (2014–2015) for patient violence (N = 192) and from health care staff (N = 380) 12‐month violence survey responses (2015) in a Midwestern academic hospital were analyzed. Logistic regression examined patient features associated with physical violence. Survey questions pertained to employee, environment, and cultural factors associated with WPV; responses were examined with Chi‐square and two‐sample t‐tests. Violence risk factors populated the 4 Haddon Matrix domains at pre‐event time frames as Host (worker)‐age/demographics, Agent (patient)‐age/gender, Physical Environment‐door/window structure, and Social Environment‐worker safety. Risks at event time frames populated for Agent—behavior/delirium, and Physical Environment—event medication/patient identification. The Haddon Matrix identification of hospital violence risks indicates its utility as a comprehensive approach to workplace violence.