bluuebunny/crossref_metadata_2025 huggingface dataset:
Sclerostin as a new target of diabetes-induced osteoporosis
Authors: Li Yanhua , Luo Yaheng , Huang Debin , Peng Lele
Published: December 2024

Sclerostin, a protein synthesized by bone cells, is a product of the SOST gene. Sclerostin is a potent soluble inhibitor of the WNT signaling pathway, and is known to inhibit bone formation by inhibiting osteocyte differentiation and function. Currently, sclerostin has been the subject of numerous animal experiments and clinical investigations. By conducting a literature review, we have gained insights into the most recent advancements in research. Patients with both type 1 diabetes and type 2 diabetes have high levels of serum sclerostin. Patients with type 1 diabetes and type 2 diabetes are both more likely to suffer from osteoporosis, and serum sclerostin levels are elevated in osteoporosis. Many studies have confirmed that sclerostin has been implicated in the pathogenesis of osteoporosis, so we speculate that sclerostin plays an important role in osteoporosis through the glucose metabolism pathway, which may promote the osteoporosis of morbidity in type 1 diabetes and type 2 diabetes. Based on this, we propose whether serum sclerostin can predict type 1 diabetes and type 2 diabetes-induced osteoporosis, and whether it can be a new target for the prevention and treatment of type 1 diabetes and type 2 diabetes-induced osteoporosis, providing new ideas for clinicians and researchers.
The association between triglyceride-glucose index and neutrophil-lymphocyte ratio and all-cause mortality in the general US population: NHANES 2001–2018
Authors: Wang Yifei , Gu Cheng , Chen Bingbing , Qiu Binxu , Yu Jinhai
Published: December 2024

Background

The association between the triglyceride-glucose (TyG) index and mortality in the general population remains controversial, with inconsistent findings across studies.

Objective

This study aims to investigate the relationship between the TyG index and mortality in the U.S. Additionally, it explores whether a new index, combining the TyG index with the neutrophil-to-lymphocyte ratio (NLR), improves the prediction of all-cause compared to the TyG index alone.

Methods

Systemic inflammatory markers and the TyG index were calculated based on participants’ complete blood counts and fasting triglyceride and glucose levels. The TyG-NLR index was derived by multiplying the TyG index by the NLR. A weighted Cox proportional hazards model was used to evaluate the associations of the TyG and TyG-NLR indices with mortality risk in the general population. Restricted cubic splines (RCS) were applied to explore and visualize the dose-response relationships between the indices and mortality.

Result

This study included 15388 participants. During a median follow-up of 118 months, 2,333 participants died. After adjusting for potential confounders, no significant association was found between the TyG index and mortality. However, compared to the lowest quartile, participants in the highest quartile of the TyG-NLR index showed a significant association with all-cause mortality. Specifically, those in the highest quartile had a 63% higher risk of all-cause mortality.
Enhancing unmanned aerial vehicle and smart grid communication security using a ConvLSTM model for intrusion detection
Authors: Alharthi Raed
Published: December 2024

The emergence of small-drone technology has revolutionized the way we use drones. Small drones leverage the Internet of Things (IoT) to deliver location-based navigation services, making them versatile tools for various applications. Unmanned aerial vehicle (UAV) communication networks and smart grid communication protocols share several similarities, particularly in terms of their architecture, the nature of the data they handle, and the security challenges they face. To ensure the safe, secure, and reliable operation of both, it is imperative to establish a secure and dependable network infrastructure and to develop and implement robust security and privacy mechanisms tailored to the specific needs of this domain. The research evaluates the performance of deep learning models, including convolutional neural networks (CNN), long short-term memory (LSTM), CNN-LSTM, and convolutional long short-term memory (ConvLSTM), in detecting intrusions within UAV communication networks. The study utilizes five diverse and realistic datasets, namely, KDD Cup-99, NSL-KDD, WSN-DS, CICIDS 2017, and Drone, to simulate real-world intrusion scenarios. Notably, the ConvLSTM model consistently achieves an accuracy of 99.99%, showcasing its potential in securing UAVs from cyber threats. By demonstrating its superior performance, this work highlights the importance of tailored security mechanisms in safeguarding UAV technology against evolving cyber threats. Ultimately, this research contributes to the growing body of knowledge on UAV security, emphasizing the necessity of high-quality datasets and advanced models in ensuring the safe, secure, and reliable operation of UAV systems across various industries.
Whole-exome sequencing identified a novel heterozygous variant in UBAP2L in a Chinese family with neurodevelopmental disorder characterized by impaired language, behavioral abnormalities, and dysmorphic facies
Authors: Yang Qi , Zhang Qiang , Zhou Xunzhao , Feng Juntan , Zhang Shujie , Lin Li , Yi Shang , Qin Zailong , Luo Jingsi
Published: December 2024

UBAP2L-deficiency syndrome, also known as neurodevelopmental disorder with impaired language, behavioral abnormalities, and dysmorphic facies (NEDLBF, OMIM 620494), is an extremely rare autosomal dominant disorder. This condition is caused by heterozygous variant in the UBAP2L gene (NM_014847.4, MIM 616472), which encodes the ubiquitin-associated protein 2-like protein involved in the formation of stress granules (SGs). To date, only one report has documented 12 loss-of-function variants in UBAP2L, all of which were identified as de novo variants. In our study, we recruited a Chinese family with two patients exhibiting intellectual disability and seizures. Whole-exome sequencing was performed on the proband, revealing a novel heterozygous frameshift variant, UBAP2L (NM_014847.4):c.2453_2454del (p.Tyr818Trpfs*3). The variant was inherited from the affected mother, and confirmed in the proband and his parents by Sanger sequencing. This is the first familial report of a deleterious UBAP2L variant. The proband in this family presented a clinical phenotype similar to NEDLBF, which includes intellectual disability, developmental delay, speech delay, facial dysmorphism, seizures, and behavioral abnormalities. The affected mother presented only mild intellectual disability and mild language impairment. By clinical evaluation of our patients and previously reported cases with UBAP2L variants, we propose that intellectual disability, developmental delay (particularly in speech), infants’ feeding difficulties, behavioural abnormalities and seizures are the main clinical features of NEDLBF patients. Our study expands the genetic and phenotypic spectrum associated with NEDLBF.
Innate immune cells in the pathogenesis of inflammatory bowel disease - from microbial metabolites to immune modulation
Authors: Mousa Rabia S. , Invernizzi Pietro , Mousa Hani S.
Published: December 2024

Inflammatory Bowel Disease (IBD) is a term used to describe a group of disorders characterized by chronic inflammation of the gastrointestinal tract, with Crohn’s Disease (CD) and Ulcerative Colitis (UC) being the most common. While still not fully understood, pathogenesis is believed to be multifactorial – the result of an interplay between genetic susceptibility, immune dysregulation and environmental factors that all lead to chronic inflammation and tissue remodeling. Innate immune cells, which orchestrate the initial defense mechanisms and modulate the subsequent immune response, play a central role in disease initiation and progression. This review examines the complex involvement of innate immune cells in IBD, emphasizing their interactions with environmental factors and the gut microbiome. We highlight the importance of microbial dysbiosis and impaired intestinal barrier function in disease pathogenesis, and the role that innate immune cells play not only as first responders, but also as key players in maintaining intestinal barrier integrity and gut microbiome. This review provides a comprehensive summary of the role that innate immune cells play in IBD pathogenesis with emphasis on the increasingly recognized role of the gut microbiome. A better understanding of innate immune cell mechanisms and of microbiome-immune interactions is key for the development of novel targeted therapies.
Development and validation of a novel immune-related prognostic model and the potential metastatic mechanism in synovial sarcoma
Authors: Huang Yufeng , Gong Ming , Lin Jiaming , Tang Qinglian , Chen Hongmin , Hu Jinxin , Deng Chuangzhong , Huang Anfei , Feng Huixiong , Song Guohui , Xu Huaiyuan , Lu Jinchang , Zhu Xiaojun , Wang Jin
Published: December 2024

Background

Several clinical trials have shown that immunotherapy plays a pivotal role in the treatment of patients with metastatic synovial sarcoma. Immune-related genes (IRGs) have been demonstrated to predict the immunotherapy response in certain malignant tumours. However, the clinical significance of IRGs in patients with synovial sarcoma (SS) is still unclear.

Methods

We first combined the immune-related ImmPort gene set to search for SS related to metastatic and differentially expressed immune-related genes (DEIRGs) in the GSE40021 dataset from the GEO database. The soft tissue sarcoma database in TCGA was used for univariate Cox regression analyses to identify DEIRGs that were related to overall survival and to build an immune-related prognostic assessment model.

Results

The study screened a total of six DEIRGs that were closely related to prognosis in metastatic SS. Further analysis showed that there was no significant difference in the expression of several immune checkpoints between the two groups in the GSE40021 data. Moreover, the GREM2 and CTSS genes were significantly expressed in metastatic patients. Further verification of clinical SS tissues from our centre by RT-qPCR analysis demonstrated reduced infiltration of activated NK cells and macrophages but increased M2-type macrophages in metastatic patients. Together, our study successfully constructed an immune-related prognostic assessment model and probably explains the poor efficacy of PD-1 inhibitors for SS patients.

Conclusion

The research deepens our understanding of the tumor immune microenvironment and proposes a new immune mechanism for metastatic SS. Early intervention and reversal of immunosuppressive microenvironmental changes are expected to delay metastasis and improve survival.
Immune regulatory adjuvant approach to mitigate subcutaneous immunogenicity of monoclonal antibodies
Authors: Jarvi Nicole L. , Patel Manali , Shetty Krithika A. , Nguyen Nhan H. , Grasperge Brooke F. , Mager Donald E. , Straubinger Robert M. , Balu-Iyer Sathy V.
Published: December 2024

Introduction

Immunogenicity continues to be a challenge for development and clinical utility of monoclonal antibodies, and there are gaps in our current ability to prevent anti-drug antibody development in a safe and antigen-specific manner.

Methods

To mitigate immunogenicity of monoclonal antibodies administered subcutaneously, O-phospho-L-serine (OPLS)—the head group of the tolerance-inducing phospholipid, phosphatidylserine—was investigated as an immunoregulatory adjuvant.

Results

Formulations of adalimumab, trastuzumab or rituximab with OPLS showed reduction in relative immunogenicity in mice compared to vehicle formulations, indicated by reduced anti-drug antibody development and significant reductions in CD138+ plasma cell differentiation in bone marrow. Titer development toward recombinant human hyaluronidase, a dispersion enhancer that was co-formulated with monoclonal antibodies, was similarly reduced. Subcutaneous administration of adalimumab with OPLS resulted in a two-fold increase in expression of type 1 regulatory (Tr1) T cell subset in the spleen. This is consistent with in vitro studies where co-culturing of dendritic cells primed with ovalbumin in the presence and absence of OPLS and antigen specific T-cells induced expression of Tr1 phenotype on live CD4+ T cells.

Conclusion

This adjuvant does not impact immune competence of non-human primates and mice, and repeated administration of the adjuvant does not show renal or hepatic toxicity. Formulation of monoclonal antibodies with the immunoregulatory adjuvant, OPLS, was found to be safe and effective at mitigating immunogenicity.
Case report: Identification of a Chinese patient with RAG1 mutations initially presenting as autoimmune hemolytic anemia
Authors: Chen Xin , Jiang Chunxue , Song Wenliang , Sun Tingting , Yan Jingli , Xu Wei , You Kai
Published: December 2024

Mutations in the recombination-activating gene 1, a pivotal component essential for V(D)J recombination and the formation of T- and B-cell receptors, can result in autoimmune hemolytic anemia, a rare hematological condition characterized by the autoantibody-mediated destruction of red blood cells. Herein, we report the case of a 1-year-and-4-month-old girl who presented with progressively aggravated anemia, fever, and cough. Autoimmune hemolytic anemia was confirmed by bone marrow aspiration and Coombs test. During treatment, the patient experienced two episodes of severe pneumonia and respiratory failure. Next-generation metagenomic sequencing of sputum samples confirmed the presence of cytomegalovirus and Pneumocystis jirovecii infections. Additionally, lymphocyte subset analysis revealed a T-B+ immunodeficiency. Whole exome and Sanger sequencing revealed a pathogenic recombinase-activating gene 1 mutation (c.2095C>T, p.Arg699Trp) and a likely pathogenic variant (c.2690G>A, p.Arg897Gln), resulting in a missense mutation in the amino acid sequence of the coding protein. Consequently, the patient was diagnosed with a recombination-activating gene 1 mutation and autoimmune hemolytic anemia as the initial presentation. This study reports a case of a recombination-activating gene 1 mutation in China and documents a combination of mutation sites and associated clinical phenotypes that were previously unreported. In this study, we outline the diverse clinical phenotypes observed in cases of recombination-activating gene 1 mutations presenting with autoimmune hemolytic anemia, aiming to facilitate timely diagnosis and appropriate treatment.
Integrating machine learning, bioinformatics and experimental verification to identify a novel prognostic marker associated with tumor immune microenvironment in head and neck squamous carcinoma
Authors: Zeng Xiaoxia , Yang Dunhui , Zhang Jin , Li Kang , Wang Xijia , Ma Fang , Liao Xianqin , Wang Zhen , Zeng Xianhai , Zhang Peng
Published: December 2024

Head and neck squamous carcinoma (HNSC), characterized by a high degree of malignancy, develops in close association with the tumor immune microenvironment (TIME). Therefore, identifying effective targets related to HNSC and TIME is of paramount importance. Here, we employed the ESTIMATE algorithm to compute immune and stromal cell scores for HNSC samples from the TCGA database and identified differentially expressed genes (DEGs) based on these scores. Subsequently, we utilized four machine learning algorithms to identify four key genes: ITM2A, FOXP3, WIPF1, and RSPO1 from DEGs. Through a comprehensive pan-cancer analysis, our study identified aberrant expression of ITM2A across various tumor types, with a significant association with the TIME. Specifically, ITM2A expression was markedly reduced and correlated with poor prognosis in HNSC. Functional enrichment analysis revealed that ITM2A is implicated in multiple immune-related pathways, including immune-infiltrating cells, immune checkpoints, and immunotherapeutic responses. ITM2A expression was observed in various immune cell populations through single-cell analysis. Furthermore, we showed that ITM2A overexpression inhibited the growth of HNSC cells. Our results suggest that ITM2A may be a novel prognostic marker associated with TIME.
Probiotics and paraprobiotics in aquaculture: a sustainable strategy for enhancing fish growth, health and disease prevention-a review
Authors: Fachri Muhammad , Amoah Kwaku , Huang Yu , Cai Jia , Alfatat Alma , Ndandala Charles Brighton , Shija Vicent Michael , Jin Xiao , Bissih Fred , Chen Huapu
Published: December 2024

This review delves into the increasing interest in probiotics and paraprobiotics as a viable alternative to antibiotics in aquaculture, highlighting their potential to enhance fish health and prevent diseases. As the aquaculture industry continues its global expansion, addressing the challenges associated with disease outbreaks in high-density fish populations becomes imperative. The review underscores the promising role of probiotics and paraprobiotics as a sustainable strategy to mitigate these challenges. The diverse positive impacts of various probiotic strains such as Arthrobacter, Bacillus, Lactobacillus, Bifidobacterium, Clostridium, and others emphasize their roles in enhancing growth, resistance to diseases (including bacterial, viral, and parasitic infections), stress reduction, water quality management, and environmental sustainability. Challenges such as stability, host specificity, and regulatory considerations must be addressed to optimize the use of probiotics in aquaculture. Additionally, paraprobiotics, or non-viable microbial cells, present a safer alternative to the criticized antibiotics and even live probiotics in environments where microbial viability poses a risk. These inactivated cells retain the ability to modulate the immune system and improve gut health, offering a promising complementary approach to fish disease prevention. The review advocates for a systematic approach combining research, innovation, and collaboration to effectively integrate probiotics and paraprobiotics into fish farming practices. Furthermore, the mechanisms by which probiotics and paraprobiotics modulate gut microbiota, produce antimicrobial compounds, and strengthen fish’s immune system have been elucidated. Moreover, the practical applications of probiotics in fish farming, including optimal administration methods and the challenges and limitations faced by the industry, have been discussed. Emphasis on the importance of continued research to explore new probiotic and paraprobiotic strains and develop innovative delivery systems to ensure the sustainability of aquaculture has been discussed. By enhancing fish health, reducing the need for antibiotics, and improving water quality, probiotics, and paraprobiotics contribute to more sustainable and environmentally responsible aquaculture operations.
Comparative analysis of SDC2 and SEPT9 methylation tests in the early detection of colorectal cancer: a systematic review and meta-analysis
Authors: Zhang Jie , Li Chenhui , An Yu , Wang Bing , Liang Guowei
Published: December 2024

Purpose

This meta-analysis aimed to evaluate the comparative diagnostic efficacy of Syndecan-2(SDC2) and Septin-9(SEPT9) in the early detection of colorectal cancer (CRC).

Methods

We searched PubMed, Embase, Web of Science, and Cochrane Library databases to identify available publications up to October 2024. A direct head-to-head comparator analysis were performed using the random-effects model. Subgroup analyses and corresponding meta-regressions focusing on sample source, number of patients, region, study design, and methylated detection methods were conducted. Intra-group and inter-group heterogeneity were assessed by Cochrane Q and I2 statistics.

Results

Eleven articles involving 1,913 CRC patients and 2,851 healthy people were included in the meta-analysis. The sensitivity of SDC2 was similar compared to SEPT9 for CRC patients (0.67 vs. 0.71, p = 0.61), SDC2 has a similar specificity in comparison to SEPT9 for CRC patients (0.90 vs. 0.91, p = 0.86). In subgroup analysis, stool SDC2 was similar compared to stool SEPT9 for CRC patients (sensitivity of 0.81 vs. 0.80, p = 0.92; specificity of 0.93 vs. 0.91, p = 0.73), plasma SDC2 was similar compared to plasma SEPT9 for CRC patients (sensitivity of 0.57 vs. 0.72, p = 0.27; specificity of 0.90 vs. 0.89, p = 0.89). In the subgroup analysis of clinical staging for colorectal cancer (CRC), the results indicate that there is no significant difference in sensitivity between the two markers for both early (0.7 vs. 0.67, p = 0.64) and advanced (0.76 vs. 0.70, p = 0.23) stages of CRC.

Conclusion

In our head-to-head comparison meta-analysis, it was found that SDC2 and SEPT9 have similar sensitivity and specificity in the diagnosis of colorectal cancer. However, this result may be influenced by high heterogeneity and further confirmation of this finding is needed through large-scale prospective studies.
3D convolutional neural network based on spatial-spectral feature pictures learning for decoding motor imagery EEG signal
Authors: Li Xiaoguang , Chu Yaqi , Wu Xuejian
Published: December 2024

Non-invasive brain-computer interfaces (BCI) hold great promise in the field of neurorehabilitation. They are easy to use and do not require surgery, particularly in the area of motor imagery electroencephalography (EEG). However, motor imagery EEG signals often have a low signal-to-noise ratio and limited spatial and temporal resolution. Traditional deep neural networks typically only focus on the spatial and temporal features of EEG, resulting in relatively low decoding and accuracy rates for motor imagery tasks. To address these challenges, this paper proposes a 3D Convolutional Neural Network (P-3DCNN) decoding method that jointly learns spatial-frequency feature maps from the frequency and spatial domains of the EEG signals. First, the Welch method is used to calculate the frequency band power spectrum of the EEG, and a 2D matrix representing the spatial topology distribution of the electrodes is constructed. These spatial-frequency representations are then generated through cubic interpolation of the temporal EEG data. Next, the paper designs a 3DCNN network with 1D and 2D convolutional layers in series to optimize the convolutional kernel parameters and effectively learn the spatial-frequency features of the EEG. Batch normalization and dropout are also applied to improve the training speed and classification performance of the network. Finally, through experiments, the proposed method is compared to various classic machine learning and deep learning techniques. The results show an average decoding accuracy rate of 86.69%, surpassing other advanced networks. This demonstrates the effectiveness of our approach in decoding motor imagery EEG and offers valuable insights for the development of BCI.
Emerging cancer therapies: targeting physiological networks and cellular bioelectrical differences with non-thermal systemic electromagnetic fields in the human body – a comprehensive review
Authors: Costa Frederico P. , Wiedenmann Bertram , Schöll Eckehard , Tuszynski Jack
Published: December 2024

A steadily increasing number of publications support the concept of physiological networks, and how cellular bioelectrical properties drive cell proliferation and cell synchronization. All cells, especially cancer cells, are known to possess characteristic electrical properties critical for physiological behavior, with major differences between normal and cancer cell counterparts. This opportunity can be explored as a novel treatment modality in Oncology. Cancer cells exhibit autonomous oscillations, deviating from normal rhythms. In this context, a shift from a static view of cellular processes is required for a better understanding of the dynamic connections between cellular metabolism, gene expression, cell signaling and membrane polarization as states in constant flux in realistic human models. In oncology, radiofrequency electromagnetic fields have produced sustained responses and improved quality of life in cancer patients with minimal side effects. This review aims to show how non-thermal systemic radiofrequency electromagnetic fields leads to promising therapeutic responses at cellular and tissue levels in humans, supporting this newly emerging cancer treatment modality with early favorable clinical experience specifically in advanced cancer.
A perspective: neuraxial therapeutics in pain management: now and future
Authors: DeAndres Jose , Dickenson Anthony H. , Hayek Salim , Linninger Andreas , Yaksh Tony L.
Published: December 2024

The neuraxial delivery of drugs for the management of pain and other spinal pathologies is widely employed and is the subject of a large volume of ongoing research with several thousand papers appearing in the past 5 years alone on neuraxial delivery. Several learned texts have been recently published. A number of considerations have contributed to this widespread interest in the development of the use of neuraxial therapeutics to manage pain. In the following section, major topics relevant to spinal encoding and in the use of neuraxial therapeutics are considered by the Frontiers in Pain Research editors of the research topic: “Neuraxial Therapeutics in Pain Management: Now and Future”. This paper seeks to serve as a perspective to encourage the submission of manuscripts reflecting research in this exciting area.
NUP155 and NDC1 interaction in NSCLC: a promising target for tumor progression
Authors: Li Kai-Min , Meng Li-Fei , Yang Zhi-Hao , Hu Wen-Tao
Published: December 2024

Background

NUP155 was reported to involve breast invasive carcinoma and hepatocellular carcinoma. We hypothesized that NUP155 and NDC1impacted the progression of NSCLC.

Methods

The dataset was analyzed to find differentially expressed genes. Functional enrichment analysis and Kaplan-Meier survival analysis were performed for differentially expressed genes. Western blot, Clone formation assay, Transwell assay and CCK-8 assay were performed to determine the performance and role of the target gene in NSCLC.

Results

The research found that the NUP family played a role in various diseases. Differential expression analysis and survival analysis were performed to identify 6 related-genes, including NUP155, NDC1, KPNA2, MAD2L1, NUP62CL, and POM121L2NUP155 and NDC1 could interact with NUP53, respectively. This effect was necessary to complete the assembly of the nuclear pore complex.

Conclusion

NUP155 interacted with NDC1 to complete the assembly of the nuclear pore complex, which promoted the development of NSCLC. Our study demonstrated that NUP155 was expected to be a potential target for the treatment of NSCLC.
Enhancing Nitrogen Nutrition Index estimation in rice using multi-leaf SPAD values and machine learning approaches
Authors: Wang Yuan , Shi Peihua , Qian Yinfei , Chen Gui , Xie Jiang , Guan Xianjiao , Shi Weiming , Xiang Haitao
Published: December 2024

Accurate nitrogen diagnosis is essential for optimizing rice yield and sustainability. This study investigates the potential of using multi-leaf SPAD measurements combined with machine learning models to improve nitrogen nutrition diagnostics in rice. Conducted across five locations with 15 rice cultivars, SPAD values from the first to fifth fully expanded leaves were collected at key growth stages. The study demonstrates that integrating multi-leaf SPAD data with advanced machine learning models, particularly Random Forest and Extreme Gradient Boosting, significantly improves the accuracy of Leaf Nitrogen Concentration (LNC) and Nitrogen Nutrition Index (NNI) estimation. The second fully expanded Leaf From the Top (2LFT) emerged as the most critical variable for predicting LNC, while the 3LFT was pivotal for NNI estimation. The inclusion of statistical metrics, such as maximum and median SPAD values, further enhanced model performance, underscoring the importance of considering both original SPAD measurements and derived indices. This approach provides a more precise method for nitrogen assessment, facilitating improved nitrogen use efficiency and contributing to sustainable agricultural practices through targeted and effective nitrogen management strategies in rice cultivation.
Case report: Depression in an older patient with dysgeusia as the initial symptom
Authors: Guo Longrun , He Zhufa
Published: December 2024

Introduction

Depression is the most common mental illness among older adults, with substantial and persistent mood depression as the main clinical feature, which is unfavorable for improvement. The clinical manifestations can range from melancholy to grief or even numbness. Approximately one-third of older adult patients exhibit physical discomfort as the first symptom; dysgeusia as the first symptom, is very rare in clinical practice. Dysgeusia is a clinical symptom with no specific objective indicator; thus, the likelihood of misdiagnosis and missed diagnosis is high.

Case presentation

In this study, a 60-year-old female housewife with elementary school as her highest level of education, presented to the outpatient department with dysgeusia, poor sleep, and poor mood persisting for >1 year, which aggravated 2 weeks before hospital visit. Psychiatric examination showed clear consciousness; the patient was cleanly and timely dressed and demonstrated self-care but had a worrisome expression. Using the diagnostic criteria of the International Classification of Diseases (10th edition), a diagnosis of a major depressive episode with psychotic symptoms was made. Following pharmacological and psychological treatment, the patient’s condition improved. The patient was compliant to treatment (10 mg/day of escitalopram), had a stable mood, good sleep, and no dysgeusia at >2 years of follow-up as an outpatient. She was able to do housework and take care of her children normally and did not complain about any other issues.

Conclusion

Physical discomfort is a very common complaint in older patients with depression. If persistent physical symptoms do not improve after repeated medical treatment, timely assessment of the patient’s mental state or psychiatric referral should be considered to diagnose geriatric depression. Timely pharmacological and psychological therapy are the preferred treatment for older adults.
Neural correlates of audiovisual integration in schizophrenia – an ERP study
Authors: Borgolte A. , Sinke C. , Michalke L. , Möde L. , Lepsy N. , Wiswede D. , Bleich S. , Szycik G. R. , Ghaneirad E.
Published: December 2024

Introduction

Multisensory integration (MSI) enhances perception by combining information from different sensory modalities. In schizophrenia, individuals often exhibit impaired audiovisual processing, resulting in broader temporal binding windows (TBWs) which appear to be associated with symptom severity. Since the underlying mechanisms of these aberrations are not yet fully understood, the present study aims to investigate multisensory processing in schizophrenia in more detail.

Methods

Individuals with schizophrenia (SZ) and healthy controls (HC) performed a simultaneity judgement task, a paradigm that is suitable for the examination of multisensory integration processes. The paradigm was also conducted to allow for the comparison of perceptions under ecologically valid and invalid conditions. Additionally, EEG recordings were made to explore underlying neural mechanisms.

Results

In line with previous research, we replicated enlarged TBWs in SZ compared to HC, independent of ecological validity. Neurophysiological data further revealed reduced amplitudes in the early ERP complex N1/P2 in SZ compared to HC.

Discussion

Since amplitude reduction in the N1/P2 complex is often associated with audiovisual integration processes, the results highlight perceptual dysfunction in SZ, particularly concerning the disengagement of auditory and visual stimuli.
Bridging trauma and eating disorders: the role of loneliness
Authors: Meneguzzo Paolo , Marzotto Anna , Mezzani Barbara , Conti Fabio , Maggi Luca , Todisco Patrizia
Published: December 2024

Introduction

Eating disorders (EDs) are complex and often linked to traumatic childhood experiences. While childhood trauma is known to increase the risk of EDs, the role of loneliness remains underexplored. This study investigates whether loneliness mediates the relationship between childhood trauma and ED symptoms.

Methods

A total of 230 individuals with EDs completed the Childhood Trauma Questionnaire, the UCLA Loneliness Scale, and the Eating Disorders Examination Questionnaire. Mediation analysis was conducted to assess if loneliness mediates the relationship between childhood trauma and ED severity.

Results

Childhood trauma significantly predicted higher levels of loneliness (p < 0.001), which was associated with more severe ED symptoms (p = 0.001), with age and BMI as covariates. Mediation analysis showed loneliness partially mediated the relationship between childhood trauma and ED severity (indirect effect b = 0.003, 95%CI [0.001, 0.006]).

Conclusion

Loneliness partially mediates childhood trauma and ED symptoms, highlighting the need to address loneliness in treatment to mitigate the impact of childhood trauma on ED severity. These findings suggest the possible role of social connection-focused interventions in ED care and contribute to understanding the mechanisms underlying the development of EDs. Future research should explore additional mediators and moderators to provide a more comprehensive perspective.
Novel concept for the healthy population influencing factors
Authors: Shen Yuhao , Wang Jichao , Ma Lihua , Yan Huizhe
Published: December 2024

In the rapid urbanization process in China, due to reasons such as employment, education, and family reunification, the number of mobile population without registered residence in the local area has increased significantly. By 2020, the group had a population of 276 million, accounting for over 20% of the total population, making significant contributions to urban economic development and resource optimization. However, the health status of migrant populations is affected by unique issues such as occupational risks and socio-economic disparities, which play an important role in personal welfare, social stability, and sustainable economic growth. The deterioration of the health of the floating population will lead to a decrease in productivity, an increase in medical expenses, and an increase in pressure on the public health system. In order to analyze and predict the main elements affecting the well-being of transient population, this study uses advanced machine learning algorithms such as principal component analysis, backpropagation (BP) neural networks, community analysis, random forest models, etc. Principal component analysis will identify and extract the most important variables that affect the health status of mobile populations. The BP neural network models the nonlinear interaction between health determinants and health outcomes. Community analysis divides the floating population into different health records and promotes targeted intervention measures. The random forest model improves the accuracy and universality of predictions. The insights generated by these models will help develop health policies and intervention policies to improve the health status of mobile populations, narrow disparities, and promote social and economic stability. Integrating data-driven methods and emphasizing a shift towards correct, effective, and impactful public health management provides a robust framework for understanding and addressing the complex health issues faced by mobile populations.
Factors related to sedentary behavior in older adult stroke patients in China: a study based on decision tree and logistic regression model
Authors: Liu Shuxian , Li Juan , Chen Xi , Jiang Xiaowen , Tang Rong , Lv Yumei
Published: December 2024

Objective

This study investigates the factors influencing sedentary behavior in older adult Chinese stroke patients using decision trees and logistic regression models.

Methods

Convenience sampling method was employed to enroll 346 respondents aged ≥60 years with stroke from the Department of Neurology of three tertiary-level A hospitals in Heilongjiang province, based on the inclusion criteria. The Sedentary Behavior Questionnaire for Older Adults, the International Physical Activity Questionnaire Short Form (IPAQ-S), the Pittsburgh Sleep Quality Index (PSQI), the Self-Rating Depression Scale (SDS), and the Social Support Scale (SSRS) were used to assess sedentary behavior, physical activity level, sleep quality, depressive symptoms, and social support, respectively. Decision tree and logistic regression models were employed to analyze the factors related to sedentary behavior in older adult stroke patients.

Results

Of the 346 respondents, 233 (67.3%) had sedentary behavior. The logistic regression model showed that education level (OR = 2.843, 95%CI: 1.219–6.626), BMI (OR = 3.686, 95%CI: 1.838–7.393), longest consecutive sitting time (OR = 3.853, 95%CI: 1.867–7.953), and sleep quality (OR = 3.832, 95%CI: 1.716–8.557) were identified as risk factors for sedentary behavior in older adult stroke patients, while drink alcohol (OR = 0.386, 95%CI: 0.184–0.809) and physical activity level (OR = 0.064, 95%CI: 0.030–0.140) were identified as protective factors for sedentary behavior. Besides, the decision tree model showed that physical activity level, longest consecutive sitting time, sleep quality, BMI, depressive symptoms, and age were associated with sedentary behavior. The sensitivity and specificity of the logistic regression model were 69.9 and 93.1%, respectively, and the area under the receiver operating characteristic (ROC) curve was 0.900 (95% CI: 0.863–0.938). The sensitivity and specificity of the decision tree model were 66.4, and 93.1% respectively, and the area under the ROC curve was 0.860 (95% CI: 0.816–0.904).

Conclusion

Our findings indicated that physical activity level, longest consecutive sitting time, sleep quality, and BMI were key factors associated with sedentary behavior. To achieve the purpose of improving rehabilitation effect and quality of life, this study combining decision trees with logistic regression models was of high value in studying factors influencing sedentary behavior in older adult stroke patients.
Plastic policy hypocrisies: evaluating the efficacy of bans and alternatives in the Eastern Caribbean
Authors: Graham Roxanne E. D.
Published: December 2024

This study critically examines the socio-economic impacts and practical challenges of implementing plastic policies and regulations such as bans in Caribbean small island developing states (SIDS), within the broader context of global environmental efforts. By employing a mixed-methods approach, the research uses qualitative data from expert interviews from the Windward Islands in the south-east of the Caribbean, and on the ground observations and documentation of plastic and alternative usage in the island of Grenada. The findings highlight a significant “plastic policy hypocrisy,” where bans on single-use plastics exist alongside a heavy reliance on imported goods predominantly packaged in plastic. This contradiction points to a broader issue in environmental policymaking, where surface-level solutions like bans are employed without addressing underlying systemic challenges, such as inadequate recycling infrastructure or lack of export opportunities for recyclable materials. The research highlights how these policies, though well-intentioned, may fall short in practicality and global alignment. The study highlights the need for holistic, globally informed, and context-sensitive approaches to marine environmental related policies in Caribbean SIDS. Emphasizing the integration of ecological, economic, and cultural dimensions, it advocates for regional and international collaboration to enhance marine litter specifically plastic policy development and technical expertise.
Who Can Donate An Organ?
Authors: Gentile Micaela , Maggiore Umberto
Published: December 2024

The human body is an extraordinary machine that works through the actions of many organs and tissues, such as the kidneys, liver, heart, lungs and cornea, each one carrying out a specific function that helps to keep us alive and functioning. Unfortunately, diseases can cause organs to break down, the so-called organ failure, sometimes putting a person’s life or wellbeing in danger. The good news is that medical science has developed ways to successfully implant a healthy organ into a patients when one of their own organs has stopped functioning. The sad news is that there are not enough available organs for those in need. Who can give organs? People can donate their organs when, at the end of their lives, the brain loses its vital activities. But medical science has also found ways to let living people safely give part of an organ (or one organ when there are two, like the kidneys), with minimal risk for the donor’s health.
Unsteady Dungey cycle from the point of view of Stokes’ theorem
Authors: Semenov Vladimir S. , Kubyshkin Igor V. , Tsyganenko Nikolai A. , Erkaev Nikolai V. , Kubyshkina Marina V. , Wang Xiaogang
Published: December 2024

The Dungey cycle is considered from the formation of a magnetic barrier and necessary for dayside reconnection conditions till the electric field generation around the Birkeland current loop and magnetic flux circulation balance. Data-based modeling of the magnetosheath magnetic field makes it possible to quantitatively assess the main factors that control formation and destruction of the magnetospheric magnetic barrier, such as the field line draping and the field intensity increase from the bow shock to the magnetopause, as well as their dependence on the orientation of the interplanetary magnetic field (IMF). The Dungey cycle has been revised to take into account the essentially time-dependent effects of magnetic reconnection. It is shown by means of the Stokes’ theorem that a powerful electric field with an effective potential difference of several tens of kV is generated around the developing substorm current system. The emerging Birkeland current loop is an important particle acceleration element in the magnetosphere, contributing to the energization of ring current protons and electrons. The electric field that arises in the dipolarization zone magnifies the already existing ring current, and the closure of its amplified part through the ionosphere generates the Region 2 field-aligned currents. The motion of the expanding partial ring current around the magnetosphere, combined with the particle drift, transfers the magnetic flux from the night side of the magnetosphere to the dayside. At the dayside magnetopause, the reconnection is also responsible for the creation of the Birkeland loop, but now the electric field in the loop area decelerates the ring current particles, and regions of weakened ring current are formed. Closure of these weakened loop currents results in a transfer of the magnetic flux from the dayside to the night side, thus ensuring its overall balance and completing the Dungey cycle.
Case report: Discovery of tuberculosis caused by Mycobacterium bovis in free-ranging vervet monkeys in the Greater Kruger Conservation Area
Authors: de Klerk-Lorist Lin-Mari , Miller Michele A. , Mitchell Emily P. , Lorist Rudolf , van Dyk D. Schalk , Mathebula Nomkosi , Goosen Louise , Dwyer-Leonard Rebecca , Ghielmetti Giovanni , Streicher Elizabeth M. , Kerr Tanya J.
Published: December 2024

Animal tuberculosis (TB) has been reported in several wildlife species in the Greater Kruger Conservation Area (GKCA), South Africa. This report describes the discovery of clinical tuberculosis, caused by Mycobacterium bovis (M. bovis), in free-ranging vervet monkeys (Chlorocebus pygerythrus). The “One Health” concept is especially relevant to TB since this is a multi-host disease with zoonotic potential and is endemic in GKCA. Vervet monkeys have become habituated to humans in tourist areas and may be a source of infection through close contact. Indirect transmission of M. bovis through environmental sources has also been suspected to present a risk of spread between host species. Clinically diseased monkeys present in two tourist areas in the GKCA, that died (n = 1) or were euthanized (n = 5), were submitted for diagnostic necropsies. The presence of pathological lesions, Ziehl-Neelsen-stained impression smears, Xpert® MTB/RIF Ultra (GXU) assay, mycobacterial culture and speciation by genomic regions of difference PCR, were used to confirm the diagnosis of M. bovis infection in these monkeys. The finding of multiple cases necessitates further investigation of TB in monkey troops living within the GKCA tourist areas to determine the source of infection and assess the risk of transmission to other animals and humans.
Detecting Online Sexism: Integrating Sentiment Analysis with Contextual Language Models
Authors: Belbachir Faiza , Roustan Thomas , Soukane Assia
Published: December 2024

In the digital era, social media platforms have seen a substantial increase in the volume of online comments. While these platforms provide users with a space to express their opinions, they also serve as fertile ground for the proliferation of hate speech. Hate comments can be categorized into various types, including discrimination, violence, racism, and sexism, all of which can negatively impact mental health. Among these, sexism poses a significant challenge due to its various forms and the difficulty in defining it, making detection complex. Nevertheless, detecting and preventing sexism on social networks remains a critical issue. Recent studies have leveraged language models such as transformers, known for their ability to capture the semantic nuances of textual data. In this study, we explore different transformer models, including multiple versions of RoBERTa (A Robustly Optimized BERT Pretraining Approach), to detect sexism. We hypothesize that combining a sentiment-focused language model with models specialized in sexism detection can improve overall performance. To test this hypothesis, we developed two approaches. The first involved using classical transformers trained on our dataset, while the second combined embeddings generated by transformers with a Long Short-Term Memory (LSTM) model for classification. The probabilistic outputs of each approach were aggregated through various voting strategies to enhance detection accuracy. The LSTM with embeddings approach improved the F1-score by 0.2% compared to the classical transformer approach. Furthermore, the combination of both approaches confirms our hypothesis, achieving a 1.6% improvement in the F1-score in each case. We determined that an F1 score of over 0.84 effectively measures sexism. Additionally, we constructed our own dataset to train and evaluate the models.