The immune factors have complex causal regulation effects on kidney stone disease: a mendelian randomization study.

PURPOSE: Previous studies have reported the potential impact of immune cells on kidney stone disease (KSD), but definitive causal relationships have yet to be established. The purpose of this paper is to elucidate the potential causal association between immune cells and KSD by Mendelian randomization (MR) analysis. METHODS: In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between immune cell traits and kidney stone disease. We included a total of four immune traits (median fluorescence intensity (MFI), relative cellular (RC), absolute cellular (AC), and morphological parameters (MP)), which are publicly available data. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results. RESULTS: After FDR correction, the CD8 on HLA DR + CD8br (OR = 0.95, 95% CI = 0.93-0.98, p-value = 7.20 × 10- 4, q-value = 0.088) was determined to be distinctly associated with KSD, and we also found other 25 suggestive associations between immune cells and KSD, of which 13 associations were suggested as protective factors and 12 associations were suggested as risk factors. There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our Cochrane Q-test, MR Egger's intercept test, and MR-PRESSO, which were all > 0.05. CONCLUSIONS: Our study has explored the potential causal connection between immune cells and KSD by Mendelian randomization analysis, thus providing some insights for future clinical studies.

CircRNA CircZMYM4 inhibits the growth and metastasis of lung adenocarcinoma via the miR-587/ODAM pathway.

Circular RNAs (circRNAs) are known to regulate tumorigenesis. In this study, circRNAs microarray was used to analyze the circRNA expression in lung adenocarcinoma (LUAD) tissues, and CircRNA zinc finger MYM-type containing 4(circZMYM4) was selected for further analysis. In this study, we detected circZMYM4 expression in LUAD specimens and cell lines using RT-PCR. The expression of circZMYM4 was further verified in the GEO datasets and TCGA datasets. Gain-of-function and loss-of-function experiments were used to analyze the effects of circZMYM4 on LUAD in vivo and in vitro. The relationship between miR-587 and circZMYM4 or ODAM was predicted by bioinformatics tools and confirmed using dual-luciferase reporter assays and RNA-pull down. We found that circZMYM4 was distinctly down-regulated in LUAD tissues and cell lines. Functional assays revealed that circZMYM4 overexpression suppressed LUAD cell proliferation, metastasis and suppressed apoptosis, while miR-587 overexpression could weaken these effects. Importantly, circZMYM4 upregulated ODAM expression via sponging miR-587 to suppress LUAD progression. ODAM knockdown could reverse the repressive effect of circZMYM4 overexpression on cell proliferation, migration and invasion abilities. Overall, circZMYM4 regulates the miR-587/ODAM axis to suppress LUAD progression, which may become a potential biomarker and therapeutic target.

An improved clear cell renal cell carcinoma stage prediction model based on gene sets.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and accounts for cancer-related deaths. Survival rates are very low when the tumor is discovered in the late-stage. Thus, developing an efficient strategy to stratify patients by the stage of the cancer and inner mechanisms that drive the development and progression of cancers is critical in early prevention and treatment. RESULTS: In this study, we developed new strategies to extract important gene features and trained machine learning-based classifiers to predict stages of ccRCC samples. The novelty of our approach is that (i) We improved the feature preprocessing procedure by binning and coding, and increased the stability of data and robustness of the classification model. (ii) We proposed a joint gene selection algorithm by combining the Fast-Correlation-Based Filter (FCBF) search with the information value, the linear correlation coefficient, and variance inflation factor, and removed irrelevant/redundant features. Then the logistic regression-based feature selection method was used to determine influencing factors. (iii) Classification models were developed using machine learning algorithms. This method is evaluated on RNA expression value of clear cell renal cell carcinoma derived from The Cancer Genome Atlas (TCGA). The results showed that the result on the testing set (accuracy of 81.15% and AUC 0.86) outperformed state-of-the-art models (accuracy of 72.64% and AUC 0.81) and a gene set FJL-set was developed, which contained 23 genes, far less than 64. Furthermore, a gene function analysis was used to explore molecular mechanisms that might affect cancer development. CONCLUSIONS: The results suggested that our model can extract more prognostic information, and is worthy of further investigation and validation in order to understand the progression mechanism.

Joint Transmit Power Allocation and Splitting for SWIPT Aided OFDM-IDMA in Wireless Sensor Networks.

In this paper, we propose to combine Orthogonal Frequency Division Multiplexing-Interleave Division Multiple Access (OFDM-IDMA) with Simultaneous Wireless Information and Power Transfer (SWIPT), resulting in SWIPT aided OFDM-IDMA scheme for power-limited sensor networks. In the proposed system, the Receive Node (RN) applies Power Splitting (PS) to coordinate the Energy Harvesting (EH) and Information Decoding (ID) process, where the harvested energy is utilized to guarantee the iterative Multi-User Detection (MUD) of IDMA to work under sufficient number of iterations. Our objective is to minimize the total transmit power of Source Node (SN), while satisfying the requirements of both minimum harvested energy and Bit Error Rate (BER) performance from individual receive nodes. We formulate such a problem as a joint power allocation and splitting one, where the iteration number of MUD is also taken into consideration as the key parameter to affect both EH and ID constraints. To solve it, a sub-optimal algorithm is proposed to determine the power profile, PS ratio and iteration number of MUD in an iterative manner. Simulation results verify that the proposed algorithm can provide significant performance improvement.

A MAC protocol for medical monitoring applications of wireless body area networks.

Targeting the medical monitoring applications of wireless body area networks (WBANs), a hybrid medium access control protocol using an interrupt mechanism (I-MAC) is proposed to improve the energy and time slot utilization efficiency and to meet the data delivery delay requirement at the same time. Unlike existing hybrid MAC protocols, a superframe structure with a longer length is adopted to avoid unnecessary beacons. The time slots are mostly allocated to nodes with periodic data sources. Short interruption slots are inserted into the superframe to convey the urgent data and to guarantee the real-time requirements of these data. During these interruption slots, the coordinator can break the running superframe and start a new superframe. A contention access period (CAP) is only activated when there are more data that need to be delivered. Experimental results show the effectiveness of the proposed MAC protocol in WBANs with low urgent traffic.

Artificial intelligence significantly facilitates development in the mental health of college students: a bibliometric analysis.

Objective: College students are currently grappling with severe mental health challenges, and research on artificial intelligence (AI) related to college students mental health, as a crucial catalyst for promoting psychological well-being, is rapidly advancing. Employing bibliometric methods, this study aim to analyze and discuss the research on AI in college student mental health. Methods: Publications pertaining to AI and college student mental health were retrieved from the Web of Science core database. The distribution of publications were analyzed to gage the predominant productivity. Data on countries, authors, journal, and keywords were analyzed using VOSViewer, exploring collaboration patterns, disciplinary composition, research hotspots and trends. Results: Spanning 2003 to 2023, the study encompassed 1722 publications, revealing notable insights: (1) a gradual rise in annual publications, reaching its zenith in 2022; (2) Journal of Affective Disorders and Psychiatry Research emerged were the most productive and influential sources in this field, with significant contributions from China, the United States, and their affiliated higher education institutions; (3) the primary mental health issues were depression and anxiety, with machine learning and AI having the widest range of applications; (4) an imperative for enhanced international and interdisciplinary collaboration; (5) research hotspots exploring factors influencing college student mental health and AI applications. Conclusion: This study provides a succinct yet comprehensive overview of this field, facilitating a nuanced understanding of prospective applications of AI in college student mental health. Professionals can leverage this research to discern the advantages, risks, and potential impacts of AI in this critical field.

Inflammatory cytokines and their potential role in kidney stone disease: a Mendelian randomization study.

PURPOSE: Previous studies have reported a complex relationship between inflammatory cytokines and kidney stone disease (KSD). The purpose of this paper is to investigate the potential causal impact of inflammatory cytokines on KSD by Mendelian randomization (MR) analysis. METHODS: In our study, a thorough two-sample Mendelian randomization (MR) analysis was performed by us to determine the potential causal relationship between inflammatory cytokines and kidney stone disease. Utilizing GWAS summary data of inflammatory cytokines and KSD, we performed the first two-sample MR analysis. Genetic variants in GWASs related to inflammatory cytokines were employed as instrumental variables (IVs). The data on cytokines were derived from 14,824 participants and analyzed by utilizing the Olink Target-96 Inflammation Panel. GWAS summary data related to KSD (9713 cases and 366,693 controls) were obtained from the FinnGen consortium. The primary MR analysis method was Inverse variance weighted. Reverse MR analysis, Cochran's Q test, MR Egger, and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) were used to assess the stability of the results. RESULTS: 91 cytokines were enrolled in the MR analysis after strict quality control of IV. The IVW analysis revealed 2 cytokines as risk factors for KSD: Cystatin D (OR 1.06, 95% CI 1.01-1.11), Fibroblast growth factor 5 (OR 1.06, 95% CI 1.00-1.12), suggesting they are positively associated with the occurrence of kidney stones. We also found 3 protective associations between cytokines and KSD: Artemin (OR 0.86, 95% CI 0.78-0.96), T-cell surface glycoprotein CD6 isoform (OR 0.92, 95% CI 0.88-0.98), STAM-binding protein (OR 0.83, 95% CI 0.69-0.99). There was no horizontal pleiotropy or significant heterogeneity in our MR analysis, as determined by the p-value results of our MR Egger's intercept test, Cochrane Q-test, and MR-PRESSO, which were all > 0.05. CONCLUSIONS: Our study explored a variety of inflammatory cytokines related to KSD through MR analysis, which validated several previous findings and provided some new potential biomarkers for KSD. However, the findings require further investigation to validate their exact functions in the pathogenesis and evolution of KSD.

Perioperative toripalimab plus neoadjuvant chemotherapy might improve outcomes in resectable esophageal cancer: an interim analysis of a phase III randomized clinical trial.

BACKGROUND: In the era of immunotherapy, neoadjuvant immunochemotherapy (NAIC) for the treatment of locally advanced esophageal squamous cell carcinoma (ESCC) is used clinically but lacks of high-level clinical evidence. This study aimed to compare the safety and long-term efficacy of NAIC followed by minimally invasive esophagectomy (MIE) with those of neoadjuvant chemotherapy (NAC) followed by MIE. METHODS: A prospective, single-center, open-label, randomized phase III clinical trial was conducted at Henan Cancer Hospital, Zhengzhou, China. Patients were randomly assigned to receive either neoadjuvant toripalimab (240 mg) plus paclitaxel (175 mg/m2) + cisplatin (75 mg/m2) (toripalimab group) or paclitaxel + cisplatin alone (chemotherapy group) every 3 weeks for 2 cycles. After surgery, the toripalimab group received toripalimab (240 mg every 3 weeks for up to 6 months). The primary endpoint was event-free survival (EFS). The pathological complete response (pCR) and overall survival (OS) were key secondary endpoints. Adverse events (AEs) and quality of life were also assessed. RESULTS: Between May 15, 2020 and August 13, 2021, 252 ESCC patients ranging from T1N1-3M0 to T2-3N0-3M0 were enrolled for interim analysis, with 127 in the toripalimab group and 125 in the chemotherapy group. The 1-year EFS rate was 77.9% in the toripalimab group compared to 64.3% in the chemotherapy group (hazard ratio [HR] = 0.62; 95% confidence interval [CI] = 0.39 to 1.00; P = 0.05). The 1-year OS rates were 94.1% and 83.0% in the toripalimab and chemotherapy groups, respectively (HR = 0.48; 95% CI = 0.24 to 0.97; P = 0.037). The patients in the toripalimab group had a higher pCR rate (18.6% vs. 4.6%; P = 0.001). The rates of postoperative Clavien-Dindo grade IIIb or higher morbidity were 9.8% in the toripalimab group and 6.8% in the chemotherapy group, with no significant difference observed (P = 0.460). The rates of grade 3 or 4 treatment-related AEs did not differ between the two groups (12.5% versus 12.4%). CONCLUSIONS: The interim results of this ongoing trial showed that in resectable ESCC, the addition of perioperative toripalimab to NAC is safe, may improve OS and might change the standard treatment in the future.

Research trend of epigenetics and depression: adolescents' research needs to strengthen.

Objective: With its high prevalence, depression's pathogenesis remains unclear. Recent attention has turned to the interplay between depression and epigenetic modifications. However, quantitative bibliometric analyses are lacking. This study aims to visually analyze depression epigenetics trends, utilizing bibliometric tools, while comprehensively reviewing its epigenetic mechanisms. Methods: Utilizing the Web of Science core dataset, we collected depression and epigenetics-related studies. Employing VOSViewer software, we visualized data on authors, countries, journals, and keywords. A ranking table highlighted field leaders. Results: Analysis encompassed 3,469 depression epigenetics studies published from January 2002 to June 2023. Key findings include: (1) Gradual publication growth, peaking in 2021; (2) The United States and its research institutions leading contributions; (3) Need for enhanced collaborations, spanning international and interdisciplinary efforts; (4) Keyword clustering revealed five main themes-early-life stress, microRNA, genetics, DNA methylation, and histone acetylation-highlighting research hotspots; (5) Limited focus on adolescent depression epigenetics, warranting increased attention. Conclusion: Taken together, this study revealed trends and hotspots in depression epigenetics research, underscoring global collaboration, interdisciplinary fusion, and multi-omics data's importance. It discussed in detail the potential of epigenetic mechanisms in depression diagnosis and treatment, advocating increased focus on adolescent research in this field. Insights aid researchers in shaping their investigative paths toward understanding depression's epigenetic mechanisms and antidepressant interventions.

Research trends of exercise therapy of college students in depression from 2002 to 2022: a bibliometric analysis.

Background: Depression is a serious psychological disorder that college students are experiencing. College students' depression problems, which can be caused by various factors, have been easily ignored and untreated. In recent years, exercise, as a low-cost and easily accessible method for treating depression, has attracted widespread attention. The purpose of this study is to use bibliometrics to explore the hotspots and trends in the field of exercise therapy of college students in depression from 2002 to 2022. Methods: We retrieved relevant literature from the Web of Science (WoS), PubMed, and Scopus databases, and generated a ranking table to describe the core productivity in the field. We used VOSViewer software to generate network maps of authors, countries, co-cited journals, and co-occurring keywords to help us better understand the scientific collaboration patterns, potential disciplinary foundations, as well as research hotspots and trends in this field. Results: From 2002 to 2022, a total of 1,397 articles related to exercise therapy of college students in depression were selected. The key findings of this study are as follows: (1) the number of publications has gradually increased, especially after 2019; (2) United States and its affiliated higher education institutions have made significant contributions to the development of this field; (3) there are multiple research groups in this field, but their connections are relatively limited; (4) the field is relatively interdisciplinary, primarily a convergence of behavioral science, public health, and psychology; (5) based on co-occurring keyword analysis, six main themes were summarized: health-promoting factors, body image, negative behaviors, increased stress, depression coping strategies, and diet. Conclusion: Our study illustrates the research hotspots and trends for the research of exercise therapy of college students in depression, presents some challenges and new insights, and provides valuable information for further research.