Association between sleep duration and subjective memory complaints: A large-scale cross-sectional study based on NHANES.

Objective: When chatting, people often forget what they want to say, that is, they suffer from subjective memory complaints (SMCs). This research examines the Association between sleep duration and self-reported SMC in a sample representing the entire United States. Methods: We examined data from 5567 individuals (aged 20-80) who participated in the National Health and Nutrition Examination Survey (2015-2018) to evaluate the association between sleep duration and SMC. Odds ratios (ORs) and a restricted cubic spline (RCS) curve were calculated with multiple logistic regression, and subgroup analysis was performed. Results: Approximately 5.8 % (3 2 3) reported SMC, and most are older people (1 6 3). RCS analysis treating sleep duration as a continuous variable revealed a J-shaped curve association between sleep duration and SMC. Self-reported sleep duration was significantly linked to a 33 % elevated risk of SMC (OR, 1.33; 95 % confidence interval [CI], 1.23-1.43; P < 0.001). In the group analysis, individuals who slept more than 8 h per day had a greater association of experiencing SMC than those who slept for 6-8 h/day (OR, 1.75; 95 % CI, 1.36-2.23; P < 0.001). In the analysis of age groups, the stable association between sleep duration and SMC was observed only in the 60-80 age bracket (OR, 1.59; 95 % CI, 1.09-2.33; P < 0.001). Conclusions: We found that people with self-report sleep duration exceeding 8 h are more likely to experience SMC, especially older adults. Improving sleep health may be an effective strategy for preventing SMC and cognitive impairment.

Production and characterization of novel monoclonal antibodies against pathological human TDP-43 proteins.

The RNA/DNA-binding protein TDP-43 plays a pivotal role in the ubiquitinated inclusions characteristic of TDP-43 proteinopathies, including most cases of frontotemporal lobar degeneration (FTLD-TDP) and Alzheimer disease (AD). To understand the mechanisms of pathological TDP-43 processing and identify potential biomarkers, we generated novel phosphorylation-independent monoclonal antibodies (MAbs) using bacteria-expressed human full-length recombinant TDP-43. Remarkably, we identified a distinctive MAb, No. 9, targeting an epitope in amino acid (aa) region 311-360 of the C-terminus. This antibody showed preferential reactivity for pathological TDP-43 inclusions, with only mild reactivity for normal nuclear TDP-43. MAb No. 9 revealed more pathology in FTLD-TDP type A and type B brains and in AD brains compared to the commercial p409/410 MAb. Using synthetic phosphorylated peptides, we also obtained MAbs targeting the p409/410 epitope. Interestingly, MAb No. 14 was found to reveal additional pathology in AD compared to the commercial p409/410 MAb, specifically, TDP-43-immunopositive deposits with amyloid plaques in AD brains. These unique immunopositivities observed with MAbs No. 9 and No. 14 are likely attributed to their conformation-dependent binding to TDP-43 inclusions. We expect that this novel set of MAbs will prove valuable as tools for future patient-oriented investigations into TDP-43 proteinopathies.

Risk factors analysis and multidisciplinary team first-aid simulation training for umbilical cord prolapse can improve neonatal outcomes.

OBJECTIVE: In the present study, we sought to identify risk factors for umbilical cord prolapse (UCP) and adapt the multidisciplinary team (MDT) first-aid simulation training for UCP patients. We evaluated the usefulness of the MDT first-aid simulation by comparing delivery outcomes for UCP patients before and after its implementation. MATERIAL AND METHODS: A retrospective review was conducted on 149 UCP cases (48 overt and 101 occult) and 298 control deliveries that occurred at the Third Affiliated Hospital of Sun Yat-sen University from January 1998 to December 2022. Patient data were compared between the groups. One-way analysis of variance (ANOVA) was used for means comparison, and the chi-square test was used for categorical data. Univariate and multivariate logistic regression analyses were performed to identify factors significantly associated with UCP. RESULTS: Overt UCP was strongly associated with all adverse delivery outcomes. Both univariate and multivariate analyses identified multiparity, breech presentation, polyhydramnios, and low birth weight as independent risk factors for overt UCP (all odds ratios [OR] > 1; all p < 0.05). Preterm labor and abnormal placental cord insertion were identified as independent risk factors for occult UCP (all OR > 1; all p < 0.05). After 2014, when obstetrical staff received MDT first-aid simulation training, patients with overt UCP experienced shorter decision-to-delivery intervals due to more timely cesarean sections. They also had higher Apgar scores at 1, 5, and 10 min, and lower admission rates to the neonatal intensive care unit compared to patients before 2014 (all p < 0.05). CONCLUSION: MDT first-aid simulation training for overt UCP can improve neonatal outcomes. However, medical simulation training efforts should initially focus on the early identification of risk factors for both overt and occult UCP.

Overt umbilical cord prolapse (UCP) is an obstetric emergency that can lead to adverse delivery outcomes. Early identification of risk factors for both overt and occult UCP is beneficial for facilitating early interventions. Multidisciplinary team first-aid simulation training specifically for overt UCP has been shown to effectively improve neonatal outcomes.

Targeting the Cdc2-like kinase 2 for overcoming platinum resistance in ovarian cancer.

Platinum resistance represents a major barrier to the survival of patients with ovarian cancer (OC). Cdc2-like kinase 2 (CLK2) is a major protein kinase associated with oncogenic phenotype and development in some solid tumors. However, the exact role and underlying mechanism of CLK2 in the progression of OC is currently unknown. Using microarray gene expression profiling and immunostaining on OC tissues, we found that CLK2 was upregulated in OC tissues and was associated with a short platinum-free interval in patients. Functional assays showed that CLK2 protected OC cells from platinum-induced apoptosis and allowed tumor xenografts to be more resistant to platinum. Mechanistically, CLK2 phosphorylated breast cancer gene 1 (BRCA1) at serine 1423 (Ser1423) to enhance DNA damage repair, resulting in platinum resistance in OC cells. Meanwhile, in OC cells treated with platinum, p38 stabilized CLK2 protein through phosphorylating at threonine 343 of CLK2. Consequently, the combination of CLK2 and poly ADP-ribose polymerase inhibitors achieved synergistic lethal effect to overcome platinum resistance in patient-derived xenografts, especially those with wild-type BRCA1. These findings provide evidence for a potential strategy to overcome platinum resistance in OC patients by targeting CLK2.

Invariable distribution of co-evolutionary complex adaptive systems with agent's behavior and local topological configuration.

In this study, we developed a dynamical Multi-Local-Worlds (MLW) complex adaptive system with co-evolution of agent's behavior and local topological configuration to predict whether agents' behavior would converge to a certain invariable distribution and derive the conditions that should be satisfied by the invariable distribution of the optimal strategies in a dynamical system structure. To this end, a Markov process controlled by agent's behavior and local graphic topology configuration was constructed to describe the dynamic case's interaction property. After analysis, the invariable distribution of the system was obtained using the stochastic process method. Then, three kinds of agent's behavior (smart, normal, and irrational) coupled with corresponding behaviors, were introduced as an example to prove that their strategies converge to a certain invariable distribution. The results showed that an agent selected his/her behavior according to the evolution of random complex networks driven by preferential attachment and a volatility mechanism with its payment, which made the complex adaptive system evolve. We conclude that the corresponding invariable distribution was determined by agent's behavior, the system's topology configuration, the agent's behavior noise, and the system population. The invariable distribution with agent's behavior noise tending to zero differed from that with the population tending to infinity. The universal conclusion, corresponding to the properties of both dynamical MLW complex adaptive system and cooperative/non-cooperative game that are much closer to the common property of actual economic and management events that have not been analyzed before, is instrumental in substantiating managers' decision-making in the development of traffic systems, urban models, industrial clusters, technology innovation centers, and other applications.

FAM76B regulates PI3K/Akt/NF-κB-mediated M1 macrophage polarization by influencing the stability of PIK3CD mRNA.

Macrophage polarization is closely related to inflammation development, yet how macrophages are polarized remains unclear. In our study, the number of M1 macrophages was markedly increased in Fam76b knockout U937 cells vs. wild-type U937 cells, and FAM76B expression was decreased in M1 macrophages induced from different sources of macrophages. Moreover, Fam76b knockout enhanced the mRNA and protein levels of M1 macrophage-associated marker genes. These results suggest that FAM76B inhibits M1 macrophage polarization. We then further explored the mechanism by which FAM76B regulates macrophage polarization. We found that FAM76B can regulate PI3K/Akt/NF-κB pathway-mediated M1 macrophage polarization by stabilizing PIK3CD mRNA. Finally, FAM76B was proven to protect against inflammatory bowel disease (IBD) by inhibiting M1 macrophage polarization through the PI3K/Akt/NF-κB pathway in vivo. In summary, FAM76B regulates M1 macrophage polarization through the PI3K/Akt/NF-κB pathway in vitro and in vivo, which may inform the development of future therapeutic strategies for IBD and other inflammatory diseases.

Adaptive Regularized Tri-Factor Non-Negative Matrix Factorization for Cell Type Deconvolution.

Motivation: Accurate deconvolution of cell types from bulk gene expression is crucial for understanding cellular compositions and uncovering cell-type specific differential expression and physiological states of diseased tissues. Existing deconvolution methods have limitations, such as requiring complete cellular gene expression signatures or neglecting partial biological information. Moreover, these methods often overlook varying cell-type mRNA amounts, leading to biased proportion estimates. Additionally, they do not effectively utilize valuable reference information from external studies, such as means and ranges of population cell-type proportions. Results: To address these challenges, we introduce an Adaptive Regularized Tri-factor non-negative matrix factorization approach for deconvolution (ARTdeConv). We rigorously establish the numerical convergence of our algorithm. Through benchmark simulations, we demonstrate the superior performance of ARTdeConv compared to state-of-the-art reference-free methods. In a real-world application, our method accurately estimates cell proportions, as evidenced by the nearly perfect Pearson's correlation between ARTdeConv estimates and flow cytometry measurements in a dataset from a trivalent influenza vaccine study. Moreover, our analysis of ARTdeConv estimates in COVID-19 patients reveals patterns consistent with important immunological phenomena observed in other studies. Availability and implementation: The proposed method, ARTdeConv, is implemented as an R package and can be accessed on GitHub for researchers and practitioners at https://github.com/gr8lawrence/ARTDeConv .

Effect of thermal softening of double-lumen endobronchial tubes on postoperative sore throat in patients with prior SARS-CoV-2 infection: a randomized controlled trial.

BACKGROUND: The incidence of postoperative sore throat (POST) after tracheal intubation using double-lumen endobronchial tubes (DLTs) is higher in patients with prior severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection than in the general population. This prospective trial was conducted to determine whether thermal softening of DLTs could decrease the incidence of POST or other airway injuries in patients with prior SARS-CoV-2 infection. METHODS: A total of 120 patients with prior SARS-CoV-2 infection undergoing thoracoscopic surgery were randomly assigned to two groups (n = 60 each). In the thermal softening group, the distal portion of the DLT was placed in thermostatic saline (50 °C) for 10 min before endotracheal intubation. In the control group, the distal portion of the DLT was placed in room temperature saline for 10 min before endotracheal intubation. The incidence and severity of POST and hoarseness were assessed at 1, 6 and 24 h postoperatively. The primary outcomes were the incidence and severity of POST at 6 h postoperatively. The secondary outcomes were the incidence and severity of hoarseness, vocal cord and tracheal injuries, and hemodynamic changes in patients at intubation. RESULTS: The incidence of POST at 6 h postoperatively was greater in the control group than in the thermal softening group [41 (68%) vs. 22 (37%), P = 0.001]. The overall incidence of POST at 24 h postoperatively was greater in the control group than in the thermal softening group [46 (76%) vs. 24 (40%), P < 0.001]. The overall incidence of tracheal injuries was also greater in the control group than in the thermal softening group (P = 0.016). Vocal cord injuries occurred more frequently in the control group than in the thermal softening group (P = 0.006). CONCLUSION: Thermal softening of DLTs before intubation can reduce the incidence of POST and airway injuries in patients with prior SARS-CoV-2 infection undergoing DLT insertion. TRIAL REGISTRATION: This trial has been registered at www.chictr.org.cn (registration number: ChiCTR2200066821; registration date: December 19, 2022).

The MYBL2-CCL2 axis promotes tumor progression and resistance to anti-PD-1 therapy in ovarian cancer by inducing immunosuppressive macrophages.

BACKGROUND: An immunosuppressive tumor microenvironment in ovarian cancer facilitates tumor progression and resistance to immunotherapy. The function of MYB Proto-Oncogene Like 2 (MYBL2) in the tumor microenvironment remains largely unexplored. METHODS: A syngeneic intraovarian mouse model, flow cytometry analysis, and immunohistochemistry were used to explore the biological function of MYBL2 in tumor progression and immune escape. Molecular and biochemical strategies-namely RNA-sequencing, western blotting, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay, multiplex immunofluorescence, chromatic immunoprecipitation assay (CHIP) and luciferase assay-were used to reveal the mechanisms of MYBL2 in the OVC microenvironment. RESULTS: We found tumor derived MYBL2 indicated poor prognosis and selectively correlated with tumor associated macrophages (TAMs) in ovarian cancer. Mechanically, C-C motif chemokine ligand 2 (CCL2) transcriptionally activated by MYBL2 induced TAMs recruitment and M2-like polarization in vitro. Using a syngeneic intraovarian mouse model, we identified MYBL2 promoted tumor malignancyand increased tumor-infiltrating immunosuppressive macrophages. Cyclin-dependent kinase 2 (CDK2) was a known upstream kinase to phosphorylate MYBL2 and promote its transcriptional function. The upstream inhibitor of CDK2, CVT-313, reprogrammed the tumor microenvironment and reduced anti-PD-1 resistance. CONCLUSIONS: The MYBL2/CCL2 axis contributing to TAMs recruitment and M2-like polarization is crucial to immune evasion and anti-PD-1 resistance in ovarian cancer, which is a potential target to enhance the efficacy of immunotherapy.

Expression and functional analysis of fam76b in zebrafish.

FAM76B is nuclear speckle-localized protein with a molecular weight of 39 kDa. The amino sequence of FAM76B protein is highly conserved among species, suggesting that FAM76B has important biological functions. However, the biological function of FAM76B is currently still unclear. To explore the biological function of FAM76B, we firstly used zebrafish as the experimental model to study the distribution and expression level of Fam76b. The results indicated that fam76b is highly expressed in hematopoiesis and immune systems of zebrafish by real-time quantitative PCR, in situ hybridization and Tg(fam76b: eGFP) transgenic zebrafish. Then, the fam76b gene was knocked out by CRISPR/Cas9 in zebrafish and fam76b rescue in fam76b-/- zebrafish was performed using the TOL2 transposable system. fam76b gene knockout zebrafish exhibit reduced thymus, excessive inflammatory response, and increased mortality. FAM76B was further found to be involved in regulating the development of hematopoiesis and immune system, and participate in the process of inflammatory response. Our findings in the study lay the groundwork for elucidating the function of the new molecule Fam76b and provide new insights into the development of zebrafish hematopoietic and immune system.

FAM76B regulates NF-κB-mediated inflammatory pathway by influencing the translocation of hnRNPA2B1.

FAM76B has been reported to be a nuclear speckle-localized protein with unknown function. In this study, FAM76B was first demonstrated to inhibit the NF-κB-mediated inflammatory pathway by affecting the translocation of hnRNPA2B1 in vitro. We further showed that FAM76B suppressed inflammation in vivo using a traumatic brain injury (TBI) mouse model. Lastly, FAM76B was shown to interact with hnRNPA2B1 in human tissues taken from patients with acute, organizing, and chronic TBI, and with different neurodegenerative diseases. The results suggested that FAM76B mediated neuroinflammation via influencing the translocation of hnRNPA2B1 in vivo during TBI repair and neurodegenerative diseases. In summary, we for the first time demonstrated the role of FAM76B in regulating inflammation and further showed that FAM76B could regulate the NF-κB-mediated inflammatory pathway by affecting hnRNPA2B1 translocation, which provides new information for studying the mechanism of inflammation regulation.

Unique T cell signatures are associated with reduced Chlamydia trachomatis reinfection in a highly exposed cohort.

Chlamydia trachomatis (CT) is the most common bacterial sexually transmitted infection (STI) in the United States, despite effective antibiotics. Information regarding natural immunity to CT will inform vaccine design. The objectives of this study were to determine immune cell populations and functional features associated with reduced risk of CT reinfection or endometrial CT infection. PBMCs were collected from a cohort of CT-exposed women who were tested for CT and other STIs at the cervix and endometrium (to determine ascension) and were repeatedly tested over the course of a year (to determine reinfection). Mass cytometry identified major immune populations and T cell subsets. Women with CT had increased CD4+ effector memory T cells (TEM) compared to uninfected women. Specifically, Th2, Th17, and Th17 DN CD4+ TEM were increased. Th17 and Th17 DN CD4+ central memory T cells (TCM) were increased in women who did not experience follow-up CT infection, suggesting that these cells may be important for protection. These data indicate that peripheral T cells display distinct features that correlate with natural immunity to CT and suggest that the highly plastic Th17 lineage plays a role in protection against reinfection.

A Machine Learning-Based Analytic Pipeline Applied to Clinical and Serum IgG Immunoproteome Data To Predict Chlamydia trachomatis Genital Tract Ascension and Incident Infection in Women.

We developed a reusable and open-source machine learning (ML) pipeline that can provide an analytical framework for rigorous biomarker discovery. We implemented the ML pipeline to determine the predictive potential of clinical and immunoproteome antibody data for outcomes associated with Chlamydia trachomatis (Ct) infection collected from 222 cis-gender females with high Ct exposure. We compared the predictive performance of 4 ML algorithms (naive Bayes, random forest, extreme gradient boosting with linear booster [xgbLinear], and k-nearest neighbors [KNN]), screened from 215 ML methods, in combination with two different feature selection strategies, Boruta and recursive feature elimination. Recursive feature elimination performed better than Boruta in this study. In prediction of Ct ascending infection, naive Bayes yielded a slightly higher median value of are under the receiver operating characteristic curve (AUROC) 0.57 (95% confidence interval [CI], 0.54 to 0.59) than other methods and provided biological interpretability. For prediction of incident infection among women uninfected at enrollment, KNN performed slightly better than other algorithms, with a median AUROC of 0.61 (95% CI, 0.49 to 0.70). In contrast, xgbLinear and random forest had higher predictive performances, with median AUROC of 0.63 (95% CI, 0.58 to 0.67) and 0.62 (95% CI, 0.58 to 0.64), respectively, for women infected at enrollment. Our findings suggest that clinical factors and serum anti-Ct protein IgGs are inadequate biomarkers for ascension or incident Ct infection. Nevertheless, our analysis highlights the utility of a pipeline that searches for biomarkers and evaluates prediction performance and interpretability. IMPORTANCE Biomarker discovery to aid early diagnosis and treatment using machine learning (ML) approaches is a rapidly developing area in host-microbe studies. However, lack of reproducibility and interpretability of ML-driven biomarker analysis hinders selection of robust biomarkers that can be applied in clinical practice. We thus developed a rigorous ML analytical framework and provide recommendations for enhancing reproducibility of biomarkers. We emphasize the importance of robustness in selection of ML methods, evaluation of performance, and interpretability of biomarkers. Our ML pipeline is reusable and open-source and can be used not only to identify host-pathogen interaction biomarkers but also in microbiome studies and ecological and environmental microbiology research.

Complex behavior of individuals and collectives in a social system: An introduction to exploratory computational experimental methodology based on multi-agent modeling.

Although the multi-agent model has been used to analyze several economic and management problems, and the research results are regarded more profoundly, they all rely on certain scenarios. Once the scenarios are shifted to an unknown one, the results cannot be matched. In this paper, a new research method named exploratory computational experiment is introduced to resolve the problems coming from the social complex system, where individual's behaviors are irrational, diverse, and complex, and collective behavior is dynamical, complex, and critical. Firstly, the foundation of the computational experiment is introduced, then several important problems, how individuals make the decision under complex environment, how collective behavior have emerged when different conflicts co-exist, and how to evaluate collect behaviors, are analyzed. To specify this new method, two examples of how to design a scientific mechanism to make the traffic system more effective and how is the evolution law of giant components in scale-free networks if the parameters are changed continuously. The results show that multi-agent modeling based on irrational behaviors controlled by individual dynamical game radius and memory length limited can describe the social problem more accurately, the exploratory computational experiment can give us more profound conclusions.

A Nomogram for Preoperative Prediction of the Risk of Lymph Node Metastasis in Patients with Epithelial Ovarian Cancer.

OBJECTIVE: To develop a nomogram for predicting lymph node metastasis (LNM) in patients with epithelial ovarian cancer (EOC). METHODS: Between December 2012 and August 2022, patients with EOC who received computed tomography (CT) and serological examinations and were treated with upfront staging or debulking surgery were included. Systematic pelvic and para-aortic lymphadenectomy was performed in all patients. Univariate and multivariate analysis was used to identify significant risk factors associated with LNM. A nomogram was then constructed to assess the risk of LNM, which was evaluated with respect to its area under the receiver operating characteristic curve (AUC), calibration, and clinical usefulness. RESULTS: Of 212 patients enrolled in this study, 78 (36.8%) had positive LNs. The nomogram integrating CT-reported LN status, child-bearing status, tumour laterality, and stage showed good calibration and discrimination with an AUC of 0.775, significantly improving performance over the CT results (0.699, p = 0.0002) with a net reclassification improvement of 0.593 (p < 0.001) and integrated discrimination improvement of 0.054 (p < 0.001). The decision curve analysis showed the nomogram was of clinical use. CONCLUSIONS: A nomogram was constructed and internally validated, which may act as a decision aid in patients with EOC being considered for systemic lymphadenectomy.

Tislelizumab for cervical cancer: A retrospective study and analysis of correlative blood biomarkers.

Background: Tislelizumab is an anti-programmed cell death 1 (PD-1) monoclonal antibody engineered to minimize binding to Fcγ receptors. It has been used to treat several solid tumors. However, its efficacy and toxicity, and the predictive and prognostic value of baseline hematological parameters in patients with recurrent or metastatic cervical cancer (R/M CC) receiving tislelizumab remain unclear. Methods: We reviewed 115 patients treated for R/M CC with tislelizumab from March 2020 to June 2022 in our institute. The antitumor activity of tislelizumab was assessed using RECIST v1.1. Associations between the baseline hematological parameters and efficacy of tislelizumab in these patients were analyzed. Results: With a median follow-up of 11.3 months (range, 2.2-28.7), the overall response rate was 39.1% (95% CI, 30.1-48.2) and the disease control rate was 77.4% (95% CI, 69.6-85.2). The median progression-free survival (PFS) was 19.6 months (95% CI, 10.7 to not reached). The median overall survival (OS) was not reached. Treatment-related adverse events (TRAEs) of any grade occurred in 81.7% of the patients and only 7.0% of the patients experienced grade 3 or 4 TRAEs. Univariate and multivariate regression analyses showed that the level of pretreatment serum C-reactive protein (CRP) was an independent risk factor for the response (complete or partial response) to tislelizumab and the PFS of R/M CC patients treated with tislelizumab (P = 0.0001 and P = 0.002, respectively). R/M CC patients with elevated baseline CRP levels had a short PFS (P = 0.0005). Additionally, the CRP-to-albumin ratio (CAR) was an independent risk factor for the PFS and OS of R/M CC patients treated with tislelizumab (P = 0.001 and P = 0.031, respectively). R/M CC patients with an elevated baseline CAR had short PFS and OS (P < 0.0001 and P = 0.0323, respectively). Conclusions: Tislelizumab showed promising antitumor activity and tolerable toxicity in patients with R/M CC. The baseline serum CRP levels and CAR showed potential for predicting the efficacy of tislelizumab and the prognosis of R/M CC patients receiving tislelizumab.

Decomposition of variation of mixed variables by a latent mixed Gaussian copula model.

Many biomedical studies collect data of mixed types of variables from multiple groups of subjects. Some of these studies aim to find the group-specific and the common variation among all these variables. Even though similar problems have been studied by some previous works, their methods mainly rely on the Pearson correlation, which cannot handle mixed data. To address this issue, we propose a latent mixed Gaussian copula (LMGC) model that can quantify the correlations among binary, ordinal, continuous, and truncated variables in a unified framework. We also provide a tool to decompose the variation into the group-specific and the common variation over multiple groups via solving a regularized M-estimation problem. We conduct extensive simulation studies to show the advantage of our proposed method over the Pearson correlation-based methods. We also demonstrate that by jointly solving the M-estimation problem over multiple groups, our method is better than decomposing the variation group by group. We also apply our method to a Chlamydia trachomatis genital tract infection study to demonstrate how it can be used to discover informative biomarkers that differentiate patients.

Methyltransferase-like 3 promotes cervical cancer metastasis by enhancing cathepsin L mRNA stability in an N6-methyladenosine-dependent manner.

N6-methyladenosine (m6A) is a highly abundant RNA modification in eukaryotic cells. Methyltransferase-like 3 (METTL3), a major protein in the m6A methyltransferase complex, plays important roles in many malignancies, but its role in cervical cancer metastasis remains uncertain. Here, we found that METTL3 was significantly upregulated in cervical cancer tissue, and its upregulation was associated with a poor prognosis in cervical cancer patients. Knockdown of METTL3 significantly reduced cervical cancer cell migration and invasion. Conversely, METTL3 overexpression markedly promoted cervical cancer cell metastasis in vitro and in vivo. Furthermore, METTL3 mediated the m6A modification of cathepsin L (CTSL) mRNA at the 5'-UTR, and the m6A reader protein insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) bound to the m6A sites and enhanced CTSL mRNA stability. Our results indicated that METTL3 enhanced CTSL mRNA stability through an m6A-IGF2BP2-dependent mechanism, thereby promoting cervical cancer cell metastasis. These findings provide insights into a novel m6A modification pattern involved in cervical cancer development.

Genetic susceptibility loci for Chlamydia trachomatis endometrial infection influence expression of genes involved in T cell function, tryptophan metabolism and epithelial integrity.

Objectives: Identify genetic loci of enhanced susceptibility to Chlamydial trachomatis (Ct) upper genital tract infection in women. Methods: We performed an integrated analysis of DNA genotypes and blood-derived mRNA profiles from 200 Ct-exposed women to identify expression quantitative trait loci (eQTL) and determine their association with endometrial chlamydial infection using a mediation test. We further evaluated the effect of a lead eQTL on the expression of CD151 by immune cells from women with genotypes associated with low and high whole blood expression of CD151, respectively. Results: We identified cis-eQTLs modulating mRNA expression of 81 genes (eGenes) associated with altered risk of ascending infection. In women with endometrial infection, eGenes involved in proinflammatory signaling were upregulated. Downregulated eGenes included genes involved in T cell functions pivotal for chlamydial control. eGenes encoding molecules linked to metabolism of tryptophan, an essential chlamydial nutrient, and formation of epithelial tight junctions were also downregulated in women with endometrial infection. A lead eSNP rs10902226 was identified regulating CD151, a tetrospanin molecule important for immune cell adhesion and migration and T cell proliferation. Further in vitro experiments showed that women with a CC genotype at rs10902226 had reduced rates of endometrial infection with increased CD151 expression in whole blood and T cells when compared to women with a GG genotype. Conclusions: We discovered genetic variants associated with altered risk for Ct ascension. A lead eSNP for CD151 is a candidate genetic marker for enhanced CD4 T cell function and reduced susceptibility.

The Critical Gene Screening to Prevent Chromophobe Cell Renal Carcinoma Metastasis through TCGA and WGCNA.

Common chromophobe renal cell carcinoma (chRCC) has a good prognosis when cured by surgery. However, clinical practice shows that a small number of patients with chRCC will produce metastasis, and the prognosis after metastasis is poor. In this regard, we try to find potential biological targets to prevent CRCC metastasis. In this experiment, we analyzed the clinical traits and gene expression data of chRCC samples which were provided by the TCGA database by the WGCNA method. On this basis, we selected MEtan, a module with a significant positive correlation with the M phase of chRCC, for subsequent analysis. The MEtan module genes in the biological process of chRCC were mainly related to steroid metabolic process, cholesterol metabolic process and STEM cell differentiation. KEGG analysis showed that these genes were mainly enriched in cancer-related signaling pathways, such as Neuroactive Ligand-receptor interaction, cAMP signaling pathway, and Wnt signaling pathway. Subsequently, we mapped the PPI interaction network and screened the key gene beta-arrestin 2 (ARRB2). Expression analysis showed that there was a significantly increased expression of ARRB2 in chRCC patients in comparison to the normal group. Expression survival analysis indicated that ARRB2 was inversely associated with overall survival. We firmly believe that the key genes identified in this study would be able to provide new clues and research basis for the treatment of chRCC.