bluuebunny/crossref_metadata_2025_split huggingface dataset:
Machine learning model‐based preterm birth prediction and clinical nomogram: A big retrospective cohort study
Authors: Liu Ya , Liu Jiangling , Shen Heqing 
Published: November 2024

AbstractObjectiveThis study sought to develop a multifactorial predictive model for preterm birth risk, with the goal of providing clinical practitioners with early prevention.MethodsThis retrospective cohort study utilized 2022 and 2018 National Vital Statistics System (NVSS) birth data, with the 2022 cohort arbitrarily split into training (70%) and internal verification (30%) subsets, and the 2018 cohort for external validation. Four machine learning algorithms—logistic regression, adaptive lasso regression, bootstrap forest, and boosted trees—identified features associated with preterm birth. The study then integrated the consensus features identified across the four models to construct a logistic regression‐based preterm birth prediction nomogram. To evaluate the model's efficacy, calibration, receiver operating characteristic (ROC), and decision curve analysis were applied to both the internal and external validation sets.ResultsThe study included 2 567 040 mother–infant pairs from the 2022 cohort and 2 688 568 mother–infant pairs from the 2018 cohort. All four machine learning models demonstrated high accuracy (area under the curve [AUC] >0.7) in predicting preterm birth, and the internal validation results indicated good model generalizability. Feature selection identified nine common risk factors associated with preterm birth. The prediction nomogram based on these nine common features achieved AUCs of 0.701, 0.702, and 0.704 in the training, internal validation, and external validation sets, respectively. The calibration curves showed good agreement, and the decision curve analysis confirmed the model's net clinical benefits.ConclusionThis study developed a reliable preterm birth prediction tool using large‐scale birth cohort data, filling the gap of lacking external validation for existing preterm birth prediction models.
A successful in vitro fertilization outcome in a hermaphrodite male
Authors: Albasha Shima Elbakhit M. E. , Al‐Said Sami Saadi , El Bardisi Haitham Tharwat M. H. 
Published: November 2024

SynopsisA case of male hermaphroditism who underwent surgery for the removal of female adnexa and bilateral gonadopexy at 2 years of age is presented.
Depletion of macrophages and osteoclast precursors mitigates iron overload‐mediated bone loss
Authors: Passin Vanessa , Ledesma‐Colunga Maria G. , Altamura Sandro , Muckenthaler Martina U. , Baschant Ulrike , Hofbauer Lorenz C. , Rauner Martina 
Published: November 2024

AbstractIron is an essential element for physiological cellular processes, but is toxic in excess. Iron overload diseases are commonly associated with low bone mass. Increased bone resorption by osteoclasts as well as decreased bone formation by osteoblasts have been implicated in bone loss under iron overload conditions. However, the exact contribution of individual cell types has not yet been formally tested. In this study, we aimed to investigate the role of osteoclast precursors in iron overload‐induced bone loss. To that end, we used clodronate liposomes to deplete phagocytic cells (including macrophages and osteoclast precursors) in male C57BL/6J mice that were exposed to ferric derisomaltose. Bone microarchitecture and bone turnover were assessed after 4 weeks. The application of clodronate resulted in the efficient depletion of circulating myeloid‐lineage cells by about 70%. Depletion of osteoclast precursors mitigated iron overload‐induced trabecular bone loss at the lumbar vertebrae and distal femur. While clodronate treatment led to a profound inhibition of bone turnover in control mice, it significantly reduced osteoclast numbers in iron‐treated mice without further impacting the bone formation rate or serum PINP levels. Our observations suggest that even though bone formation is markedly suppressed by iron overload, osteoclasts also play a key role in iron overload‐induced bone loss and highlight them as potential therapeutic targets.
Scanning Electron Microscopy of the Oropharyngeal Floor of Northern Bobwhite (Colinus virginianus, Linnaeus, 1758) Focusing on the Numerical and Regional Distribution of the Taste Buds
Authors: Madkour Fatma A. , Hiramatsu Kohzy , Mohamed Alsayed A. 
Published: November 2024

ABSTRACTThe architecture of the avian oropharynx corresponds to the feeding pattern. The present study aims to provide data on morphology, morphometry, and spatial distribution of taste buds in the oropharyngeal floor of the northern bobwhite (Colinus virginianus) using gross anatomy, morphometric, and scanning electron microscopy. The lower beak tip and tomia revealed the presence of variably‐sized dermal papillae. The prefrenular part of the oral floor had an interrupted median groove. Numerous taste buds and rostral submandibular salivary gland openings were detected alongside this groove. The tongue partially filled the oral floor. Its rostral end formed a median pointed process, the lingual nail. The dorsolateral aspects of the lingual apex and body showed hair‐like and rosette‐shaped filiform papillae of variable densities and sizes. However, these parts were devoid of taste buds. On the other hand, the surface mucosa of the lingual root presented numerous scale‐like cellular elevations and a large number of taste buds. Examination of cross sections in the lingual root suggested the presence of two groups of caudal lingual salivary glands, central and lateral. The laryngeal mound contained taste buds that protruded from the surface epithelium into the lumen. The mucosa of the pharyngeal floor contained many taste buds that appeared similar to those detected on the laryngeal mound, except for the large taste pores, excessive cellular porosity, and denser microvilli. The total proportions of the taste buds in the oral and pharyngeal floors were 34.1% and 65.81%, respectively. The proportions of taste buds were 34.1%, 57.26%, 4.27%, and 4.27% in the sublingual floor, lingual root, laryngeal mound, and pharyngeal wall, respectively. In conclusion, this study provides comprehensive data on the oropharynx of northern bobwhite and will help to understand mechanisms governing food gustation in the studied bird and other related birds.
A Novel Cold‐Adapted Catechol 1,2‐Dioxygenase From Antarctic Sea‐Ice Bacterium Halomonas sp. ANT108: Characterization and Immobilization
Authors: Wang Quanfu , Zhang Xiaoxuan , Wang Anqi , Zhang Ailin , Wang Yatong , Hou Yanhua 
Published: November 2024

ABSTRACTThe enzyme catechol 1,2‐dioxygenase (CAT) plays a critical role in the biosynthesis pathway of cis, cis‐muconic acid (CCMA), which serves as an indispensable raw material for various industrial applications. In this research, we cloned a novel cold‐adapted CAT (HaCAT) from the Antarctic sea ice bacterium Halomonas sp. ANT108. Homology modeling analysis revealed that HaCAT possessed the characteristic Fe3+ binding site and catalytic active site of typical CATs, and it exhibited unique structural adaptations to cold environments. The optimal temperature and pH for recombinant HaCAT (rHaCAT) were found to be 25°C and 6.5, respectively. At 0°C, the enzyme retained a maximum activity of 43.6%, and in the presence of 1.0 M NaCl, its activity reached 173.9%, demonstrating significant salt tolerance. Additionally, the Vmax and Km of rHaCAT were 6.68 μmol/min/mg and 128.90 μM at 25°C, respectively. Furthermore, rHaCAT was successfully immobilized in the metal‐organic framework ZIF‐8 and retained almost 50% of its activity after five reuse cycles, demonstrating excellent reusability. Overall, these results provided a new resource and theoretical foundation for the industrial biocatalytic production and modification of CAT.
Examining the role of single versus dual decision‐making approach for patient care: Evidence from cardiology patients
Authors: Goradia Deepa , Chandrasekaran Aravind 
Published: November 2024

AbstractResearch in healthcare suggests that repeated interaction between a provider and a patient can support better decision‐making, resulting in improved efficiencies. To date, these repeated interactions enabling continuity of care have not been studied in hospital inpatient settings. During a hospital stay, decisions related to patient treatment are usually made by two key decision‐makers: the attending physician (AP) and the operating physician (OP). Under the single decision‐making approach (S‐DMA), the AP and OP are the same; in contrast, under the dual decision‐making approach (D‐DMA), the AP and OP are different. In recent years, there has been an increasing trend toward the use of D‐DMA over S‐DMA across U.S. hospitals owing to scheduling conflicts. Although research outside healthcare operations management has argued for benefits from both approaches, their impacts on a patient's hospital stay are unclear. In this study, we address this gap by investigating the effects of S‐DMA and D‐DMA on patient care outcomes in terms of patient length of stay (LOS), treatment cost, and mortality. Data for our study come from the state of Florida and involve 520,554 cardiology patients treated by 9483 APs and 18,398 OPs at 241 hospitals between 2014 and 2016. We account for both patient and physician selection issues when choosing a particular decision‐making strategy. Our results suggest that, on average, using S‐DMA is associated with reduced patient LOS and treatment cost but has no effect on mortality. We also find that S‐DMA is more beneficial for patients with low comorbidity and low process uncertainty, whereas D‐DMA is more beneficial for patients with high comorbidity and high process uncertainty. Our results are robust to alternative explanations. We demonstrate that a single decision‐maker offers benefits in the context of healthcare delivery, but dual decision‐makers may yield benefits when caring for patients with high comorbidity and high process complexity. We discuss the implications of these findings for appropriately deploying S‐DMA and D‐DMA in inpatient services.
Risk factors for patellofemoral joint osteoarthritis following ACL reconstruction: A cluster analysis of anatomy and alignment
Authors: Demirjian Thomas , Crues John , Powers Christopher M. 
Published: November 2024

AbstractIndividuals who undergo anterior cruciate ligament reconstruction are at elevated risk for developing early‐onset patellofemoral joint osteoarthritis. Our objective was to use K‐means clustering to ascertain whether individuals at risk for patellofemoral joint osteoarthritis could be identified as determined by the presence of multiple co‐existing anatomical and patella alignment risk factors. Forty participants (20 after anterior cruciate ligament reconstruction, 20 healthy controls) underwent magnetic resonance imaging assessment of the patellofemoral joint. Measures of hypothesized risk factors for patellofemoral joint osteoarthritis were obtained including patella alignment (lateral patella displacement and tilt), trochlear morphology (sulcus angle, lateral inclination angle), patella height (Insall‐Salvati ratio and patella articulating overlap), and patellofemoral joint contact area. K‐means clustering (k = 2) was used to ascertain whether a high‐risk group could be identified. Following clustering, two distinct groups were detected. Participants assigned to cluster 1 exhibited features consistent with patellofemoral joint osteoarthritis including greater lateral patellar displacement and tilt, flatter trochlear grooves and lower lateral trochlear inclination, less patella articulating overlap, and reduced contact area. The proportion of females after anterior cruciate ligament reconstruction assigned to cluster 1 was 75% (N = 15) compared to 25% of healthy females (N = 5). K‐means clustering was capable of characterizing individuals at elevated risk for patellofemoral joint osteoarthritis based on the presence of multiple co‐existing anatomical and patella alignment risk factors. The fact that a significant percentage of females were assigned to the high‐risk cluster supports the clinical observation that these individuals may be at higher risk of early‐onset patellofemoral joint osteoarthritis.
Machine learning‐based prediction of contralateral knee osteoarthritis development using the Osteoarthritis Initiative and the Multicenter Osteoarthritis Study dataset
Authors: Kim Ji‐Sahn , Choi Byung Sun , Kim Sung Eun , Lee Yong Seuk , Lee Do Weon , Ro Du Hyun 
Published: November 2024

AbstractHaving osteoarthritis in one knee is reported as an independent risk factor for developing contralateral knee osteoarthritis (KOA). However, no study has been designed to predict the development of contralateral KOA (cKOA). The authors hypothesized that specific risk factors for cKOA development exist and that it could be accurately predicted with the assistance of machine learning. KOA was defined using the Kellgren‐Lawrence grade (KLG) of 2 or higher. Data from 1353 unilateral KOA patients (900 from the Osteoarthritis Initiative [OAI] and 453 from the Multicenter Osteoarthritis Study [MOST]) over 4–5 years of follow‐up were examined. The risk factors for cKOA development were analyzed, and a machine learning model was developed to predict cKOA using OAI as the development data set and MOST as the test data set. cKOA developed in 172 (19.1%) and 178 (39.3%) of the patients (OAI and MOST, respectively) over a period of 4–5 years. A machine learning model was developed using the Tree‐based Pipeline Optimization Tool algorithm. This model utilized nine variables, including baseline lateral joint space narrowing grade of the contralateral knee (odds ratio 4.475). The area under the curve of the receiver operating characteristics curve, along with accuracy, precision, and F1‐score, were recorded as 0.69, 0.60, 0.50, and 0.58, respectively, in the test data set. The development of cKOA could be effectively predicted using a limited number of variables through machine learning. Surgeons should consider the development of cKOA in patients with identified risk factors when managing KOA patients.
Artificial intelligence with counseling on the treatment outcomes and quality of life in periodontitis patients
Authors: You Fu‐Tzu , Lin Pei‐Chen , Huang Chiung‐Lin , Wu Ju‐Hui , Kabasawa Yuji , Chen Chih‐Chang , Huang Hsiao‐Ling 
Published: November 2024

AbstractBackgroundTo evaluate the effects of artificial intelligence (AI)‐assisted dental monitoring (DM) with and without health counseling on the treatment outcomes and oral health‐related quality of life (OHRQoL) of patients with periodontitis.MethodsPatients with periodontitis were randomly assigned to either an AI group (AI group, n = 28), an AI and health counseling group (AIHC group, n = 27), or a control group (n = 27). All patients underwent nonsurgical periodontal treatment. Patients in the AI and AIHC groups underwent additional AI‐assisted DM and AI‐assisted DM with oral health counseling, respectively, for 6 months. Data on OHRQoL and periodontal measures were collected at baseline and follow‐ups.ResultsAt 3 months of follow‐up, the AI and AIHC groups exhibited a significantly greater reduction in probing pocket depth (mean diff: −0.5 and −0.7) and clinical attachment level (mean diff: −0.5 and −0.6) compared with the control group. At 6 months of follow‐up, the AI and AIHC groups exhibited a significantly greater improvement in OHRQoL (mean diff: −4.5 and −4.7) compared with the control group. At 3‐month follow‐up, the AIHC group exhibited a greater improvement in plaque index (mean diff: −0.2) and OHRQoL (mean diff: −4.3) compared with the AI group.ConclusionAI‐assisted DM can be used to remind patients with periodontitis of their oral hygiene at home and effectively improve their periodontal measures and long‐term OHRQoL.Plain Language Summary
Gum disease is a common problem, but new technology could help. In this study, researchers looked at how AI affects gum health and quality of life (QoL).
The researchers divided participants into 3 groups. One group used an AI system to monitor their gums at home. Another used AI plus got health advice. The third did not use any special technology.
After 3 and 6 months, the AI groups had healthier gums, with less deep pockets and better gum attachment, compared to the group without AI. The group that also got health advice saw even greater improvements, like cleaner teeth and a bigger boost to their QoL.
This is exciting because gum disease is tricky to manage alone. The AI system seems to help by reminding people to care for their teeth and gums. With expert guidance, the AI becomes an even more powerful tool for improving long‐term oral health and well‐being.
This study shows how new technologies like AI could transform how we approach common health problems. By providing personalized support, AI can empower people to better manage their own health, leading to better outcomes.
Portal hypertension in doublecortin domain‐containing protein 2 (DCDC2)‐related neonatal sclerosing cholangitis
Authors: Kaur Prabhsaran , Lal Bikrant Bihari , Janakiraman Deepa , Dheivamani Nirmala , Pandey Snehavardhan , Bavdekar Ashish , Shah Aashay , Verma Sanjeev Kumar , Shah Vaibhav , Maria Arjun , Wadhwa Nishant , Singh Sumit Kumar , Sood Vikrant , Khanna Rajeev , Alam Seema 
Published: November 2024

AbstractMutations in doublecortin domain‐containing protein 2 (DCDC2) lead to neonatal sclerosing cholangitis (NSC), and portal hypertension (PHTN). The objective of the study was to systematically evaluate PHTN, variceal bleeding, and outcomes of patients with DCDC2‐related NSC. The study included children with homozygous or compound heterozygous variants in DCDC2. All 14 children with DCDC2‐related NSC had PHTN. Eight (57.1%) developed variceal bleed at a median age of 3 years (range: 1.9–5 years). Eleven (78.6%) children with high‐risk varices underwent endotherapy. Varices were completely eradicated in three, downstaged to low‐risk in five, and there was no response with endotherapy in three. All three children with failure to eradicate/downstage varices had rebleed, and required listing for liver transplantation (LT). The study shows that children with variants in DCDC2 have a high incidence of variceal bleed at a very young age. Variceal eradication may often be difficult and rebleed rates are high; often necessitating LT.
Eutectic phosphor for high‐power excitation
Authors: Tokumitsu Seika , Kusunoki Tsuneo , Makio Satoshi , Kawabe Hideo 
Published: November 2024

AbstractHigh‐power blue‐emitting laser diodes have been used in projectors and lighting systems as excitation sources for yellow‐emitting phosphors. These phosphors must be robust and should not exhibit thermal quenching. In this work, we developed a durable eutectic phosphor consisting of single‐crystal Ce‐doped yttrium aluminum garnet (Ce:YAG) phosphor and Al2O3 (sapphire), with a thermal conductivity greater than 20 W/(m·K). This eutectic phosphor is named EPOCH‐Neo. EPOCH‐Neo specimens were cut from a large crystal substrate prepared by an edge‐defined film‐fed growth method. We evaluated the optical properties of EPOCH‐Neo specimens and the optical uniformity of an EPOCH‐Neo substrate. In addition, to control the chromaticity, the Y‐sites of Ce:YAG were doped with Gd at concentrations as high as 50% and the chromaticity and thermal characteristics of the resultant phosphors were evaluated. Moreover, the characteristics of a device composed of EPOCH‐Neo on a heatsink under blue laser excitation were examined. The results showed that EPOCH‐Neo is a durable phosphor suitable for use in high‐power‐excitation applications.
Are Nomograms Useful for Predicting Sentinel Lymph Node Status in Melanoma Patients?
Authors: Lourdault Kristel , Cowman Arthur W. , Hanes Douglas , Scholer Anthony J. , Aguilar Tyler , Essner Richard 
Published: November 2024

ABSTRACTBackground and ObjectivesClinical nomograms have been developed to predict sentinel lymph node (SLN) status in early‐stage melanoma patients, but the clinical utility of these tools remains debatable. We created and validated a nomogram using data from a randomized clinical trial and assessed its accuracy against the well‐validated Melanoma Institute Australia (MIA) nomogram.MethodsWe developed our model to predict SLN status using logistic regression on clinicopathological patient data from the Multicenter Selective Lymphadenectomy Trial‐I. The model was externally validated using the National Cancer Database (NCDB) data set, and its performance was compared to that of the MIA nomogram.ResultsOur model had good discrimination between positive and negative SLNs, with a training set area under the curve (AUC) of 0.706 (0.661–0.751). Our model achieved an AUC of 0.715 (0.706–0.724) compared to 0.723 (0.715–0.731) with the MIA model, using the NCDB set.ConclusionOur model performed similarly to the MIA model, confirming that despite using different clinical features and data sets, no clinical nomogram is currently accurate enough for clinical use.
Rehabilitating tigers for range expansion: lessons from the Russian Far East
Authors: Miquelle Dale G. , Mukhacheva Anna S. , Bragina Eugenia V. , Waller Scott J. , Petrunenko Yuri K. , Naidenko Sergei V. , Hernandez‐Blanco Jose. A. , Kastrikin Vyacheslav A. , Rybin Alexander N. , Rybin Nikolai N. , Seryodkin Ivan V. , Blidchenko Ekaterina Yu. , Yachmennikova Anna A. , Chistopolova Maria D. , Soutyrina Svetlana V. , Rozhnov Viatcheslav V. 
Published: November 2024

AbstractEmpty but suitable habitat exists for many of the world's terrestrial large carnivores, yet reintroductions are often considered difficult. In the Russian Far East, orphaned Amur tiger (Panthera tigris altaica) cubs were brought into captivity but prepared for re‐release into the wild. We addressed 2 questions after reintroduction: 1) were individuals raised in captivity capable of killing prey at a rate sufficient to survive, and 2) did individuals avoid use of domestic animals as a primary source of food? We collected data on hunting behavior of 6 orphaned tigers re‐released into their indigenous range, and compared kill composition, kill rate, and consumption rate to individuals studied within the existing range (Sikhote‐Alin) of Amur tigers. Prey composition of rehabilitated tigers varied from that of the Sikhote‐Alin tigers, but composition of major food groups was nearly identical. Kill rate of rehabilitated tigers was higher and prey size was smaller than that of Sikhote‐Alin tigers, but consumption rates were nearly identical. One young male tiger depredated domestic animals, but other individuals only rarely preyed on dogs or cattle they encountered in forests. We documented high survival, reproduction, and recruitment of re‐released individuals. These results indicate that tigers held in captivity during the majority of their early lives can survive in the wild, so long as exposure to humans is kept to a minimum and individuals learn to hunt wild prey before release. Results provide a potential framework for reintroductions of tigers and other large felids across the globe.