Background Per- and polyfluoroalkyl substances (PFAS) are a class of persistent organic pollutants widely used in various products, leading to population exposure and long-term accumulation. At present, there is a lack of research on the relationships between pre-pregnancy PFAS and menstrual characteristics among women undergoing assisted reproductive technology (ART) in China. Objective To explore the relationships between pre-pregnancy PFAS exposure among women undergoing ART and menstrual characteristics prior to assisted reproductive treatment. Methods This study employed a cross-sectional research design, recruiting women undergoing ART treatment at the Reproductive Clinic of the International Peace Maternity & Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, from 2017 to 2020 as study participants. Ultra-high-performance liquid chromatography-tandem mass spectrometry was used to detect 42 types of PFAS in pre-pregnancy serum samples. Questionnaires were administered to collect information on demographic characteristics, lifestyle habits, and menstrual characteristics (average menstrual cycle length, average menstrual period length, menstrual irregularities, and menstrual bleeding volume) of women undergoing ART. Multiple linear regression, binary logistic regression, and multinomial logistic regression analyses were performed to investigate the relationships between individual PFAS exposure before pregnancy and menstrual characteristics among ART women. Additionally, weighted quantile sum (WQS) model was applied to analyze the association between PFAS mixtures and menstrual characteristics. Results In the pre-pregnancy serum samples of the study population, 15 PFAS were detected in more than 60% of the samples, including perfluoroheptanoic acid (PFHpA), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUnDA), perfluorododecanoic acid (PFDoDA), perfluorobutanesulfonic acid (PFBS), perfluorohexanesulfonic acid (PFHxS), perfluoroheptanesulfonic acid (PFHpS), perfluorooctanesulfonic acid (PFOS), 6:2 chlorinated polyfluorinated ether sulfonate (6:2 Cl-PFESA), 8:2 chlorinated polyfluorinated ether sulfonate (8:2 Cl-PFESA), perfluoro-2-propoxypropanoic acid (HFPO-DA), perfluoro-2-methoxyacetic acid (PFMOAA), and perfluoro-(3,5,7,9,11-pentaoxadodecanoic) acid (PFO5DoDA). Among them, PFOA had the highest median concentration of 9.160 ng·mL⁻¹. The single PFAS exposure analysis revealed a positive correlation between PFAS and irregular menstrual cycles. Specifically, for every natural-log unit (e) increase in PFOA, PFBS, or PFHxS level, the incidence of irregular menstrual cycles increased by 57%, 42%, or 39%, respectively. Most PFAS were positively correlated with the average number of menstrual cycle days, such as PFHpA (b=1.08, 95%CI: 0.11, 2.05), PFOA (b=1.69, 95%CI: 0.39, 3.00), PFBS (b=1.23, 95%CI: 0.25, 2.22), PFHxS (b=1.47, 95%CI: 0.61, 2.32), PFHpS (b=1.48, 95%CI: 0.35, 2.61), and 6:2 Cl-PFESA (b=0.90, 95%CI: 0.08, 1.72). Furthermore, levels of PFHpA (OR=1.39, 95%CI: 1.06, 1.82), PFOA (OR=1.58, 95%CI: 1.09, 2.30), PFBS (OR=1.37, 95%CI: 1.04, 1.80), PFHxS (OR=1.34, 95%CI: 1.05, 1.71), PFHpS (OR=1.53, 95%CI: 1.10, 2.14), and 6:2 Cl-PFESA (OR=1.34, 95%CI: 1.06, 1.70) were positively correlated with low menstrual blood volume, while PFOA (OR=0.40, 95%CI: 0.23, 0.71), PFHpS (OR=0.45, 95%CI: 0.29, 0.71), and HFPO-DA (OR=0.68, 95%CI: 0.48, 0.97) were negatively correlated with high menstrual blood volume. The mixed exposure model showed that PFAS mixtures were positively correlated with the average number of menstrual cycle days (b=1.60, 95%CI: 0.49, 2.71), irregular menstrual cycles (OR=1.77, 95%CI: 1.19, 2.63), and low menstrual blood volume (OR=1.59, 95%CI: 1.08, 2.35), but negatively correlated with high menstrual blood volume (OR=0.40, 95%CI: 0.22, 0.73). Conclusion Women undergoing ART in Shanghai are widely exposed to PFAS prior to conception. Exposure to PFAS before pregnancy may be related to menstrual characteristics among women seeking ART before undergoing fertility treatments, but additional data from larger populations are required to validate the findings of this study.

BACKGROUND: There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to illustrate whether clinical and biological heterogeneity, such as ventilation and gas-exchange, exists among patients with SP using chest computed tomography (CT)-based AI-aided latent class analysis (LCA). METHODS: This retrospective study included 413 patients hospitalized at Xinhua Hospital diagnosed with SP from June 1, 2015 to May 30, 2020. AI quantification results of chest CT and their combination with additional clinical variables were used to develop LCA models in an SP population. The optimal subphenotypes were determined though evaluating statistical indicators of all the LCA models, and clinical implications of them such as guiding ventilation strategies were further explored by statistical methods. RESULTS: The two-class LCA model based on AI quantification results of chest CT can describe the biological characteristics of the SP population well and hence yielded the two clinical subphenotypes. Patients with subphenotype-1 had milder infections ( P <0.001) than patients with subphenotype-2 and had lower 30-day ( P <0.001) and 90-day ( P <0.001) mortality, and lower in-hospital ( P = 0.001) and 2-year ( P <0.001) mortality. Patients with subphenotype-1 showed a better match between the percentage of non-infected lung volume (used to quantify ventilation) and oxygen saturation (used to reflect gas exchange), compared with patients with subphenotype-2. There were significant differences in the matching degree of lung ventilation and gas exchange between the two subphenotypes ( P <0.001). Compared with patients with subphenotype-2, those with subphenotype-1 showed a relatively better match between CT-based AI metrics of the non-infected region and oxygenation, and their clinical outcomes were effectively improved after receiving invasive ventilation treatment. CONCLUSIONS A two-class LCA model based on AI quantification results of chest CT in the SP population particularly revealed clinical heterogeneity of lung function. Identifying the degree of match between ventilation and gas-exchange may help guide decisions about assisted ventilation.
Humans ; Tomography, X-Ray Computed/methods* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Artificial Intelligence ; Aged ; Pneumonia/diagnosis* ; Latent Class Analysis ; Adult

OBJECTIVE: To explore a predictive model that can better predict the prognosis of patients with diffuse large B-cell lymphoma (DLBCL), and validate its clinical value. METHODS: Clinical data of 134 newly treated DLBCL patients were collected from Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from January 2015 to January 2020. Several risk factors of the patients were screened and analyzed, a novel prognostic model were then established based on this, and its clinical application potential was validated. RESULTS: In the novel model, predicting progression-free survival (PFS) based on the age at initial treatment, albumin level, Hans classification, Ann Arbor stage, and BCL2 expression showed better predictive performance than International Prognostic Index (IPI) score (AUC: 0.788 vs 0.620，P <0.001). Predicting overall survival (OS) based on the age at initial treatment, albumin level, lactate dehydrogenase (LDH) level, and expressions of BCL2 and MUM1 proteins also showed better predictive performance for mortality risk than IPI score (AUC: 0.817 vs 0.624，P <0.001). CONCLUSION This novel prognostic model can better predict the survival prognosis of DLBCL patients compared to the IPI scoring system.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Prognosis ; Proto-Oncogene Proteins c-bcl-2/metabolism* ; Risk Factors ; Male ; Female ; Middle Aged

Local anesthetics (LAs), such as articaine (AT), exhibit limited efficacy in inflammatory environments, which constitutes a significant limitation in their clinical application within oral medicine. In our prior research, we developed AT-17, which demonstrated effective properties in chronic inflammatory conditions and appears to function as a novel oral LA that could address this challenge. In the present study, we further elucidated the beneficial effects of AT-17 in acute inflammation, particularly in oral acute inflammation, where mitochondrial-related apoptosis played a crucial role. Our findings indicated that AT-17 effectively inhibited lipopolysaccharide (LPS)-induced nerve cell apoptosis by ameliorating mitochondrial dysfunction in vitro. This process involved the inhibition of mitochondrial reactive oxygen species (mtROS) production and the subsequent activation of the NRF2 pathway. Most notably, improvements in mitochondria-related apoptosis were key contributors to AT-17's inhibition of voltage-gated sodium channels. Additionally, AT-17 was shown to reduce mtROS production in nerve cells through the Na⁺/NCLX/ETC signaling axis. In conclusion, we have developed a novel local anesthetic that exhibits pronounced anesthetic functionality under inflammatory conditions by enhancing mitochondria-related apoptosis. This advancement holds considerable promise for future drug development and deepening our understanding of the underlying mechanisms of action.

OBJECTIVES: To investigate the role of DTX2 in regulating biological behaviors of oxaliplatin-resistant colorectal cancer cells (CRC/OXA cells). METHODS: CCK8 assay was used to determine the inhibition rate of oxaliplatin-treated CRC cells. A CRC/OXA cell line was constructed, in which DTX2 expression level was detected. The cells were transfected with a DTX2-shRNA plasmid or co-transfected with DTX2-shRNA and pcDNA-Notch2, and the changes in cell proliferation, migration and invasion ability were evaluated using plate cloning assay, scratch assay and Transwell invasion assay. The expression levels of Notch2, NICD and epithelial-mesenchymal transition (EMT) proteins of the transfected cells were detected with Western blotting. In a nude mouse model bearing SW620/OXA cell xenografts, the effects of DTX2 knockdown and Notch2 overexpression in the implanted cells on tumor growth and protein expressions were tested. RESULTS: The IC₅₀ of oxaliplatin was 6.00 μmol/L in SW620 cells and 8.00 μmol/L in LoVo cells. CRC/OXA cells showed a significantly increased expression of DTX2. DTX2 knockdown in CRC/OXA cells significantly inhibited cell proliferation, migration and invasion, and these effects were reversed by co-transfection of the cells with pcDNA-Notch2. DTX2 knockdown significantly reduced the expression levels of Notch2, NICD and vimentin proteins and increased E-cadherin expression in CRC/OXA cells, and co-transfection with pcDNA-Notch2 potently attenuated the changes in these proteins. In the tumor-bearing mice, DTX2 overexpression obviously promoted the growth of SW620/OXA cell xenograft, enhanced the protein expressions of Notch2, NICD and vimentin, and lowered the expression of E-cadherin. CONCLUSIONS High expression of DTX2 promotes proliferation, migration, invasion and EMT of CRC/OXA cells through the Notch2 signaling pathway, suggesting the potential of DTX2 as a target to improve the efficacy of oxaliplatin.
Epithelial-Mesenchymal Transition ; Humans ; Cell Proliferation ; Oxaliplatin ; Colorectal Neoplasms/metabolism* ; Animals ; Drug Resistance, Neoplasm ; Receptor, Notch2/metabolism* ; Cell Line, Tumor ; Mice, Nude ; Cell Movement ; Organoplatinum Compounds/pharmacology* ; Neoplasm Invasiveness ; Mice

Periodontitis is a common oral disease characterized by progressive alveolar bone resorption and inflammation of the periodontal tissues. Dimethyl fumarate (DMF) has been used in the treatment of various immune-inflammatory diseases due to its excellent anti-inflammatory and antioxidant functions. Here, we investigated for the first time the therapeutic effect of DMF on periodontitis. In vivo studies showed that DMF significantly inhibited periodontal destruction, enhanced mitophagy, and decreased the M1/M2 macrophage ratio. In vitro studies showed that DMF inhibited macrophage polarization toward M1 macrophages and promoted polarization toward M2 macrophages, with improved mitochondrial function, inhibited oxidative stress, and increased mitophagy in RAW 264.7 cells. Furthermore, DMF increased intracellular mitochondrial Tu translation elongation factor (TUFM) levels to maintain mitochondrial homeostasis, promoted mitophagy, and modulated macrophage polarization, whereas TUFM knockdown decreased the protective effect of DMF. Finally, mechanistic studies showed that DMF increased intracellular TUFM levels by protecting TUFM from degradation via the ubiquitin-proteasomal degradation pathway. Our results demonstrate for the first time that DMF protects mitochondrial function and inhibits oxidative stress through TUFM-mediated mitophagy in macrophages, resulting in a shift in the balance of macrophage polarization, thereby attenuating periodontitis. Importantly, this study provides new insights into the prevention of periodontitis.
Dimethyl Fumarate/pharmacology* ; Mitophagy/drug effects* ; Animals ; Mice ; Macrophages/metabolism* ; Periodontitis/prevention & control* ; RAW 264.7 Cells ; Oxidative Stress/drug effects* ; Peptide Elongation Factor Tu/metabolism* ; Mice, Inbred C57BL ; Male ; Mitochondria/drug effects*