bluuebunny/crossref_metadata_2025_split huggingface dataset:
Structured neurological soft signs examination reveals motor coordination deficits in adults diagnosed with high-functioning autism
Authors: Wieting Jelte , Baumann Madita Vanessa , Deest-Gaubatz Stephanie , Bleich Stefan , Eberlein Christian Karl , Frieling Helge , Deest Maximilian 
Published: July 2024

AbstractNeurological soft signs (NSS), discrete deficits in motor coordination and sensory integration, have shown promise as markers in autism diagnosis. While motor impairments, partly associated with core behavioral features, are frequently found in children with autism, there is limited evidence in adults. In this study, NSS were assessed in adults undergoing initial diagnosis of high-functioning autism (HFA), a subgroup difficult to diagnose due to social adaptation and psychiatric comorbidity. Adults with HFA (n = 34) and 1:1 sex-, age-, and intelligence-matched neurotypical controls were administered a structured NSS examination including motor, sensory, and visuospatial tasks. We showed that adults with HFA have significantly increased motor coordination deficits compared with controls. Using hierarchical cluster analysis within the HFA group, we also identified a subgroup that was particularly highly affected by NSS. This subgroup differed from the less affected by intelligence level, but not severity of autism behavioral features nor global psychological distress. It remains questionable whether motor impairment represents a genuinely autistic trait or is more a consequence of factors such as intelligence. Nevertheless, we conclude that examining NSS in terms of motor coordination may help diagnose adults with HFA and identify HFA individuals who might benefit from motor skills interventions.
Gestational bisphenol A exposure alters energy homeostasis and adult hypothalamic neurogenesis in female mice
Authors: Feighan Kira M. , Nesan Dinushan , Kurrasch Deborah M. 
Published: July 2024

AbstractRegulation of physiological homeostasis, including energy balance, is thought to be modified by low levels of adult neurogenesis in the hypothalamus. Hormones such as oestradiol can influence both embryonic and adult hypothalamic neurogenic programs, demonstrating a sensitivity of hypothalamic neural progenitor cells to endogenous hormones. Previously we showed that gestational exposure to environmental levels of the xenoestrogen bisphenol A (BPA) changed neural progenitor cell behaviors in the embryo; however, we did not examine if these changes were permanent to affect adult neurogenesis. Here we investigated whether adult neuro- and/or gliogenesis were altered in mice prenatally exposed to BPA and placed on a high-fat diet challenge. Gestationally exposed adult female mice on a standard diet gained less weight than non-BPA controls, whereas gestationally exposed BPA females on a high-fat diet gained more weight than controls. Males exposed to gestational BPA showed no differences in weight gain relative to control males. Concomitantly, adult neurogenesis was increased in the VMH, DMH, and PVN of adult female mice exposed to BPA on standard diet, suggesting that disrupted adult neurogenesis might perturb normal energy balance regulation in females. These results add to growing evidence that low-dose BPA exposure in utero causes changes to adult hypothalamic function.
A multi-information fusion anomaly detection model based on convolutional neural networks and AutoEncoder
Authors: Zhao Zhongnan , Guo Hongwei , Wang Yue 
Published: July 2024

AbstractNetwork traffic anomaly detection, as an effective analysis method for network security, can identify differentiated traffic information and provide secure operation in complex and changing network environments. To avoid information loss caused when handling traffic data while improving the detection performance of traffic feature information, this paper proposes a multi-information fusion model based on a convolutional neural network and AutoEncoder. The model uses a convolutional neural network to extract features directly from the raw traffic data, and a AutoEncoder to encode the statistical features extracted from the raw traffic data, which are used to supplement the information loss due to cropping. These two features are combined to form a new integrated feature for network traffic, which has the load information from the original traffic data and the global information of the original traffic data obtained from the statistical features, thus providing a complete representation of the information contained in the network traffic and improving the detection performance of the model. The experiments show that the classification accuracy of network traffic anomaly detection using this model outperforms that of classical machine learning methods.
Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare
Authors: Siddiqui Ismaeel A. , Littlefield Nickolas , Carlson Luke A. , Gong Matthew , Chhabra Avani , Menezes Zoe , Mastorakos George M. , Thakar Sakshi Mehul , Abedian Mehrnaz , Lohse Ines , Weiss Kurt R. , Plate Johannes F. , Moradi Hamidreza , Amirian Soheyla , Tafti Ahmad P. 
Published: July 2024

AbstractAI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases inherent within these models remains largely unexplored. This study tackles these concerns by thoroughly re-examining AI-driven segmentation for hip and knee bony anatomy. While advanced imaging modalities like CT and MRI offer comprehensive views, plain radiographs (X-rays) predominate the standard initial clinical assessment due to their widespread availability, low cost, and rapid acquisition. Hence, we focused on plain radiographs to ensure the utilization of our contribution in diverse healthcare settings, including those with limited access to advanced imaging technologies. This work provides insights into the underlying causes of biases in AI-based knee and hip image segmentation through an extensive evaluation, presenting targeted mitigation strategies to alleviate biases related to sex, race, and age, using an automatic segmentation that is fair, impartial, and safe in the context of AI. Our contribution can enhance inclusivity, ethical practices, equity, and an unbiased healthcare environment with advanced clinical outcomes, aiding decision-making and osteoarthritis research. Furthermore, we have made all the codes and datasets publicly and freely accessible to promote open scientific research.
Impact of general anesthesia on postoperative complications in orthognathic surgery: a retrospective comparison of total intravenous anesthesia versus volatile anesthesia
Authors: Aijima Reona , Miura Daisuke , Takamori Ayako , Kamohara Asana , Danjo Atsushi , Sakaguchi Yoshiro , Yamashita Yoshio 
Published: July 2024

AbstractOrthognathic surgery has a high incidence of postoperative nausea (PON) and vomiting (POV), delaying mobility initiation and postoperative recovery. Bleeding is another risk associated with this surgical procedure. We aimed to compare total intravenous anesthesia (TIVA) and volatile anesthesia in patients undergoing orthognathic surgery in terms of postoperative nausea and vomiting (PONV) incidence and hemodynamic changes. This retrospective study included 82 patients who underwent bilateral sagittal split ramus osteotomies at Saga University Hospital between April 2016 and April 2021. We compared the effects of TIVA and volatile anesthesia on PONV onset after surgery, acute postoperative hemodynamic changes (blood pressure and heart rate), and factors contributing to PONV. PON was significantly lower in the TIVA group than in the volatile anesthesia group. The total dose of fentanyl contributed to the onset of POV, while the onset of PON was associated with low volumes of fluid infusion and urine in the TIVA and volatile anesthesia groups, respectively. Furthermore, post-extubation hemodynamic change was significantly smaller in the TIVA group than in the volatile anesthesia group. Therefore, TIVA could have a reduced risk of PONV and hemodynamic changes in patients undergoing orthognathic surgery. Employing TIVA could mitigate perioperative complications and enhance patient safety.
Levels of Sex Hormones and Abdominal Muscle Composition in Men from The Multi-Ethnic Study of Atherosclerosis
Authors: Osmancevic Amar , Allison Matthew , Miljkovic Iva , Vella Chantal A. , Ouyang Pamela , Trimpou Penelope , Daka Bledar 
Published: July 2024

AbstractInformation on the associations of testosterone levels with abdominal muscle volume and density in men is limited, while the role of estradiol and SHBG on these muscle characteristics are unclear. Therefore, this study aimed to investigate the association between fasting serum sex hormones and CT-derived abdominal muscle area and radiodensity in adult men. Conducted as a cross sectional observational study using data from the Multi-Ethnic Study of Atherosclerosis, our analyses focused on a community-based sample of 907 men aged 45–84 years, with 878 men having complete data. CT scans of the abdomen were interrogated for muscle characteristics, and multivariable linear regressions were used to test the associations. After adjustment for relevant factors, higher levels of both total testosterone and estradiol were associated with higher abdominal muscle area (1.74, 0.1–3.4, and 1.84, 0.4–3.3, respectively). In the final analyses, levels of total testosterone showed a positive association, while an inverse relationship was observed for SHBG with abdominal muscle radiodensity (0.3, 0.0–0.6, and − 0.33, − 0.6 to − 0.1, respectively). Our results indicate a complex association between sex hormones and abdominal muscle characteristics in men. Specifically, total testosterone and estradiol were associated with abdominal muscle area, while only total testosterone was associated with muscle radiodensity and SHBG was inversely associated with muscle radiodensity.Clinical Trial: NCT00005487
Underwater small target detection under YOLOv8-LA model
Authors: Qu Shenming , Cui Can , Duan Jiale , Lu Yongyong , Pang Zilong 
Published: July 2024

AbstractIn the realm of marine environmental engineering, the swift and accurate detection of underwater targets is of considerable significance. Recently, methods based on Convolutional Neural Networks (CNN) have been applied to enhance the detection of such targets. However, deep neural networks usually require a large number of parameters, resulting in slow processing speed. Meanwhile, existing methods present challenges in accurate detection when facing small and densely arranged underwater targets. To address these issues, we propose a new neural network model, YOLOv8-LA, for improving the detection performance of underwater targets. First, we design a Lightweight Efficient Partial Convolution (LEPC) module to optimize spatial feature extraction by selectively processing input channels to improve efficiency and significantly reduce redundant computation and storage requirements. Second, we developed the AP-FasterNet architecture for small targets that are commonly found in underwater datasets. By integrating depth-separable convolutions with different expansion rates into FasterNet, AP-FasterNet enhances the model’s ability to capture detailed features of small targets. Finally, we integrate the lightweight and efficient content-aware reorganization (CARAFE) up-sampling operation into YOLOv8 to enhance the model performance by aggregating contextual information over a large perceptual field and mitigating information loss during up-sampling.Evaluation results on the URPC2021 dataset show that the YOLOv8-LA model achieves 84.7% mean accuracy (mAP) on a single Nvidia GeForce RTX 3090 and operates at 189.3 frames per second (FPS), demonstrating that it outperforms existing state-of-the-art methods in terms of performance. This result demonstrates the model’s ability to ensure high detection accuracy while maintaining real-time processing capabilities.
Global burden of anticancer drug-induced acute kidney injury and tubulointerstitial nephritis from 1967 to 2023
Authors: Yoon Soo-Young , Lee Sooji , Lee Kyeongmin , Kim Jin Sug , Hwang Hyeon Seok , Kronbichler Andreas , Jacob Louis , Shin Ju-Young , Lee Jin A. , Park Jaeyu , Lee Hyeri , Lee Hayeon , Jeong Kyunghwan , Yon Dong Keon 
Published: July 2024

AbstractThis study aims to figure out the worldwide prevalence of anticancer therapy-associated acute kidney injury (AKI) and tubulointerstitial nephritis (TIN) and the relative risk of each cancer drug. We conducted an analysis of VigiBase, the World Health Organization pharmacovigilance database, 1967–2023 via disproportionate Bayesian reporting method. We further categorized the anticancer drugs into four groups: cytotoxic therapy, hormone therapy, immunotherapy, and targeted therapy. Reporting odds ratio (ROR) and information component (IC) compares observed and expected values to investigate the associations of each category of anticancer drugs with AKI and TIN. We identified 32,722 and 2056 reports (male, n = 17,829 and 1,293) of anticancer therapy-associated AKI and TIN, respectively, among 4,592,036 reports of all-drug caused AKI and TIN. There has been a significant increase in reports since 2010, primarily due to increased reports of targeted therapy and immunotherapy. Immunotherapy exhibited a significant association with both AKI (ROR: 8.92; IC0.25: 3.06) and TIN (21.74; 4.24), followed by cytotoxic therapy (7.14; 2.68), targeted therapy (5.83; 2.40), and hormone therapy (2.59; 1.24) for AKI, and by cytotoxic therapy (2.60; 1.21) and targeted therapy (1.54; 0.61) for TIN. AKI and TIN were more prevalent among individuals under 45 years of age, with a female preponderance for AKI and males for TIN. These events were reported in close temporal relationship after initiation of the respective drug (16.53 days for AKI and 27.97 days for TIN), and exhibited a high fatality rate, with 23.6% for AKI and 16.3% for TIN. These findings underscore that kidney-related adverse drug reactions are of prognostic significance and strategies to mitigate such side effects are required to optimize anticancer therapy.
Tannic acid coating gauze immobilized with thrombin with ultra-high coagulation activity and antimicrobial property for uncontrollable hemorrhage
Authors: Ye Jian , Shi Chenyang , Lan Jian , Chen Qingqing , Si Qin , Xu Panpan , Zhang Xijiang , Zheng Cheng 
Published: July 2024

AbstractRapid and safe hemostasis is crucial for the survival of bleeding patients in prehospital care. It is urgent to develop high performance hemostatic material to control the massive hemorrhage in the military field and accidental trauma. In this work, an efficient protein hemostat of thrombin was immobilized onto commercial gauze, which was mediated by self-polymerization and anchoring of tannic acid (TA). Through TA treatment, the efficient immobilization of thrombin was achieved, preserving both the biological activity of thrombin and the physical properties of the dressing, including absorbency, breathability, and mechanical performance. Moreover, in the presence of TA coating and thrombin, Gau@TA/Thr could obviously shortened clotting time and enriched blood components such as plasma proteins, platelets, and red blood cells, thereby exhibiting an enhanced in vitro coagulation effect. In SD rat liver volume defect and artery transection hemorrhage models, Gau@TA/Thr still had outstanding hemostatic performance. Besides, the Gau@TA/Thr gauze had inherent antibacterial property and demonstrated excellent biocompatibility. All results suggested that Gau@TA/Thr would be a potential candidate for treating uncontrollable hemorrhage in prehospital care.
Establishment of an in vitro choroid complex system for vascular response screening
Authors: Jeong Heonuk , Lee Deokho , Negishi Kazuno , Tsubota Kazuo , Kurihara Toshihide 
Published: July 2024

AbstractThe choroid, a vascularized tissue situated between the retina and the sclera, plays a crucial role in maintaining ocular homeostasis. Despite its significance, research on choroidal abnormalities and the establishment of effective in vitro models have been limited. In this study, we developed an in vitro choroid model through the co-culture of human induced pluripotent stem cells (hiPSC)-derived endothelial cells (ECs) and mouse choroidal fibroblasts (msCFs) with hiPSC-derived retinal pigment epithelial (RPE) cells via a permeable membrane. This model, inclusive of ECs, CFs, and RPE cells, exhibited similarities with in vivo choroidal vessels, as confirmed through immunohistochemistry of extracellular matrix markers and vascular-related markers, as well as choroid angiogenesis sprouting assay analysis. The effectiveness of our in vitro model was demonstrated in assessing vascular changes induced by drugs targeting vasoregulation. Our model offers a valuable tool for gaining insights into the pathological mechanisms underlying choroid development and the progression of choroidal vascular diseases.
Mimicking classical noise in ion channels by quantum decoherence
Authors: Seifi Mina , Soltanmanesh Ali , Shafiee Afshin 
Published: July 2024

AbstractThe mechanism of selectivity in ion channels is still an open question in biology. Recent studies suggest that the selectivity filter may exhibit quantum coherence, which could help explain how ions are selected and conducted. However, environmental noise causes decoherence and loss of quantum effects. It is hoped that the effect of classical noise on ion channels can be modeled using the framework provided by quantum decoherence theory. In this paper, the behavior of the ion channel system was simulated using two models: the Spin–Boson model and the stochastic Hamiltonian model under classical noise. Additionally, using a different approach, the system’s evolution was modeled as a two-level Spin–Boson model with tunneling, interacting with a bath of harmonic oscillators, based on decoherence theory. We investigated under what conditions the decoherence model approaches and deviates from the noise model. Specifically, we examined Gaussian noise and Ornstein-Uhlenbeck noise in our model. Gaussian noise shows a very good agreement with the decoherence model. By examining the results, it was found that the Spin–Boson model at a high hopping rate of potassium ions can simulate the behavior of the system in the classical noise approach for Gaussian noise.
Association of volatile organic compound levels with chronic obstructive pulmonary diseases in NHANES 2013–2016
Authors: Liu Xiangliang , Chang Yu , Xu Chengyao , Li Yuguang , Wang Yao , Sun Yao , Duan Meilin , Li Wei , Cui Jiuwei 
Published: July 2024

AbstractVolatile organic compounds (VOCs) represent a significant component of air pollution. However, studies evaluating the impact of VOC exposure on chronic obstructive pulmonary disease (COPD) have predominantly focused on single pollutant models. This study aims to comprehensively assess the relationship between multiple VOC exposures and COPD. A large cross-sectional study was conducted on 4983 participants from the National Health and Nutrition Examination Survey. Four models, including weighted logistic regression, restricted cubic splines (RCS), weighted quantile sum regression (WQS), and the dual-pollution model, were used to explore the association between blood VOC levels and the prevalence of COPD in the U.S. general population. Additionally, six machine learning algorithms were employed to develop a predictive model for COPD risk, with the model’s predictive capacity assessed using the area under the curve (AUC) indices. Elevated blood concentrations of benzene, toluene, ortho-xylene, and para-xylene were significantly associated with the incidence of COPD. RCS analysis further revealed a non-linear and non-monotonic relationship between blood levels of toluene and m-p-xylene with COPD prevalence. WQS regression indicated that different VOCs had varying effects on COPD, with benzene and ortho-xylene having the greatest weights. Among the six models, the Extreme Gradient Boosting (XGBoost) model demonstrated the strongest predictive power, with an AUC value of 0.781. Increased blood concentrations of benzene and toluene are significantly correlated with a higher prevalence of COPD in the U.S. population, demonstrating a non-linear relationship. Exposure to environmental VOCs may represent a new risk factor in the etiology of COPD.
Immune cell landscapes are associated with high-grade serous ovarian cancer survival
Authors: Zhang Guoan , Zhang Yan , Zhang Jingjing , Yang Xiaohui , Sun Wenjie , Liu Ying , Liu Yingfu 
Published: July 2024

AbstractHigh-grade serous ovarian cancer (HGSOC) is an aggressive disease known to develop resistance to chemotherapy. We investigated the prognostic significance of tumor cell states and potential mechanisms underlying chemotherapy resistance in HGSOC. Transcriptome deconvolution was performed to address cellular heterogeneity. Kaplan–Meier survival curves were plotted to illustrate the outcomes of patients with varying cellular abundances. The association between gene expression and chemotherapy response was tested. After adjusting for surgery status and grading, several cell states exhibited a significant correlation with patient survival. Cell states can organize into carcinoma ecotypes (CE). CE9 and CE10 were proinflammatory, characterized by higher immunoreactivity, and were associated with favorable survival outcomes. Ratios of cell states and ecotypes had better prognostic abilities than a single cell state or ecotype. A total of 1265 differentially expressed genes were identified between samples with high and low levels of C9 or CE10. These genes were partitioned into three co-expressed modules, which were associated with tumor cells and immune cells. Pogz was identified to be linked with immune cell genes and the chemotherapy response of paclitaxel. Collectively, the survival of HGSOC patients is correlated with specific cell states and ecotypes.
Assessing Relative Linguistic Impairment With Model-Based Item Selection
Authors: Walker Grant M. , Fridriksson Julius , Hickok Gregory 
Published: July 2024

Purpose:
A picture naming test is presented that reveals impairment to specific mechanisms involved in the naming process, using accuracy scores on curated item sets. A series of psychometric validation experiments are reported.

Method:
Using a computational model that enables estimation of item difficulty at the lexical and sublexical stages of word retrieval, two complimentary sets of items were constructed that challenge the respective psycholinguistic levels of representation. The difference in accuracy between these item sets yields the relative linguistic impairment (RLI) score. In a cohort of 91 people with chronic left-hemisphere stroke who enrolled in a clinical trial for anomia, we assessed psychometric properties of the RLI score and then used the new scale to make predictions about other language behaviors, lesion distributions, and functional activation during naming.

Results:
RLI scores had adequate psychometric properties for clinical significance. RLI scores contained predictive information about spontaneous speech fluency, over and above accuracy. A dissociation was observed between performance on the RLI item sets and performance on the subtests of an independent language battery. Sublexical RLI was significantly associated with apraxia of speech and with lesions encompassing perisylvian regions, while lexical RLI was associated with lesions to deep white matter. The RLI construct was reflected in functional brain activity during naming, independent of overall accuracy, with a respective shift of activation between dorsal and ventral networks responsible for different aspects of word retrieval.

Conclusion:
The RLI assessment satisfies the psychometric requirements to serve as a useful clinical measure.