Atorvastatin ameliorates diabetic nephropathy through inhibiting oxidative stress and ferroptosis signaling.

Clinically, statins have long been used for the prevention and treatment of chronic renal diseases, however, the underlying mechanisms are not fully elucidated. The present study investigated the effects of atorvastatin on diabetes renal injury and ferroptosis signaling. A mouse model of diabetes was established by the intraperitoneal injection of streptozotocin (50 mg/kg/day) plus a high fat diet with or without atorvastatin treatment. Diabetes mice manifested increased plasma glucose and lipid profile, proteinuria, renal injury and fibrosis, atorvastatin significantly lowered plasma lipid profile, proteinuria, renal injury in diabetes mice. Atorvastatin reduced renal reactive oxygen species (ROS), iron accumulation and renal expression of malondialdehyde (MDA), 4-hydroxynonenal (4-HNE), transferrin receptor1 (TFR1), and increased renal expression of glutathione peroxidase 4 (GPX4), nuclear factor erythroid 2-related factor (NRF2) and ferritin heavy chain (FTH) in diabetes mice. Consistent with the findings in vivo, atorvastatin prevented high glucose-induced ROS formation and Fe2+ accumulation, an increase in the expression of 4-HNE, MDA and TFR1, and a decrease in cell viability and the expression of NRF2, GPX4 and FTH in HK2 cells. Atorvastatin also reversed ferroptosis inducer erastin-induced ROS production, intracellular Fe2+ accumulation and the changes in the expression of above-mentioned ferroptosis signaling molecules in HK2 cells. In addition, atorvastatin alleviated high glucose- or erastin-induced mitochondria injury. Ferroptosis inhibitor ferrostatin-1 and antioxidant N-acetylcysteine (NAC) equally reversed the expression of high glucose-induced ferroptosis signaling molecules. Our data support the notion that statins can inhibit diabetes-induced renal oxidative stress and ferroptosis, which may contribute to statins protection of diabetic nephropathy.

Enhancing osteogenesis and angiogenesis functions for Ti-24Nb-4Zr-8Sn scaffolds with methacrylated gelatin and deferoxamine.

Repair of large bone defects remains challenge for orthopedic clinical treatment. Porous titanium alloys have been widely fabricated by the additive manufacturing, which possess the elastic modulus close to that of human cortical bone, good osteoconductivity and osteointegration. However, insufficient bone regeneration and vascularization inside the porous titanium scaffolds severely limit their capability for repair of large-size bone defects. Therefore, it is crucially important to improve the osteogenic function and vascularization of the titanium scaffolds. Herein, methacrylated gelatin (GelMA) were incorporated with the porous Ti-24Nb-4Zr-8Sn (Ti2448) scaffolds prepared by the electron beam melting (EBM) method (Ti2448-GelMA). Besides, the deferoxamine (DFO) as an angiogenic agent was doped into the Ti2448-GelMA scaffold (Ti2448-GelMA/DFO), in order to promote vascularization. The results indicate that GelMA can fully infiltrate into the pores of Ti2448 scaffolds with porous cross-linked network (average pore size: 120.2 ± 25.1 µm). Ti2448-GelMA scaffolds facilitated the differentiation of MC3T3-E1 cells by promoting the ALP expression and mineralization, with the amount of calcium contents ∼2.5 times at day 14, compared with the Ti2448 scaffolds. Impressively, the number of vascular meshes for the Ti2448-GelMA/DFO group (∼7.2/mm2) was significantly higher than the control group (∼5.3/mm2) after cultivation for 9 h, demonstrating the excellent angiogenesis ability. The Ti2448-GelMA/DFO scaffolds also exhibited sustained release of DFO, with a cumulative release of 82.3% after 28 days. Therefore, Ti2448-GelMA/DFO scaffolds likely provide a new strategy to improve the osteogenesis and angiogenesis for repair of large bone defects.

Association Analysis of Essential Tremor-Associated Genetic Variants in Sporadic Late-Onset Parkinson's Disease.

Background: Parkinson's disease (PD) and Essential tremor (ET) are the two most common tremor diseases with recognized genetic pathogenesis. The overlapping clinical features suggest they may share genetic predispositions. Our previous study systematically investigated the association between rare coding variants in ET-associated genes and early-onset PD (EOPD), and found the suggestive association between teneurin transmembrane protein 4 (TENM4) and EOPD. In the current research, we explored the potential genetic interplay between ET-associated genetic loci/genes and sporadic late-onset PD (LOPD). Methods: We performed whole-genome sequencing in the 1962 sporadic LOPD cases and 1279 controls from mainland China. We first used logistic regression analysis to test the top 16 SNPs identified by the ET genome-wide association study for the association between ET and LOPD. Then we applied the optimized sequence kernel association testing to explore the rare variant burden of 33 ET-associated genes in this cohort. Results: We did not observe a significant association between the included SNPs with LOPD. We also did not discover a significant burden of rare deleterious variants of ET-associated genes in association with LOPD risk. Conclusion: Our results do not support the role of ET-associated genetic loci and variants in LOPD. Highlights: 1962 cases and 1279 controls were recruited to study the potential genetic interplay between ET-associated genetic loci/variants and sporadic LOPD.No significant association between the ET-associated SNPs and LOPD were observed.No significant burden of rare deleterious variants of ET-associated gene in LOPD risk were found.

Development and validation of a risk nomogram model for predicting peripheral neuropathy in patients with type 2 diabetes mellitus.

Objective: Diabetic peripheral neuropathy frequently occurs and presents severely in individuals suffering from type 2 diabetes mellitus, representing a significant complication. The objective of this research was to develop a risk nomogram for DPN, ensuring its internal validity and evaluating its capacity to predict the condition. Methods: In this retrospective analysis, Suqian First Hospital's cohort from January 2021 to June 2022 encompassed 397 individuals diagnosed with T2DM. A random number table method was utilized to allocate these patients into two groups for training and validation, following a 7:3 ratio. By applying univariate and multivariable logistic regression, predictive factors were refined to construct the nomogram. The model's prediction accuracy was assessed through metrics like the ROC area, HL test, and an analysis of the calibration curve. DCA further appraised the clinical applicability of the model. Emphasis was also placed on internal validation to confirm the model's dependability and consistency. Results: Out of 36 evaluated clinicopathological characteristics, a set of four, duration, TBIL, TG, and DPVD, were identified as key variables for constructing the predictive nomogram. The model exhibited robust discriminatory power, evidenced by an AUC of 0.771 (95% CI: 0.714-0.828) in the training cohort and an AUC of 0.754 (95% CI: 0.663-0.845) in the validation group. The congruence of the model's predictions with actual findings was corroborated by the calibration curve. Furthermore, DCA affirmed the clinical value of the model in predicting DPN. Conclusion: This research introduces an innovative risk nomogram designed for the prediction of diabetic peripheral neuropathy in individuals suffering from type 2 diabetes mellitus. It offers a valuable resource for healthcare professionals to pinpoint those at elevated risk of developing this complication. As a functional instrument, it stands as a viable option for the prognostication of DPN in clinical settings.

Different clinical characteristics and outcomes of adult hospitalized SARS-CoV-2 pneumonia patients complicated by cardiovascular events during the first, delta and omicron waves of COVID-19.

Background: The effects of SARS-CoV-2 have varied between significant waves of hospitalization. Research question: Are cardiovascular complications different among the first, delta and omicron waves of hospitalized COVID-19 pneumonia patients? Study design and methods: This was a multi-centre retrospective study of patients hospitalized with SARS-CoV-2 pneumonia: 632 were hospitalized during the first wave (March-July 2020), 1013 during the delta wave (September 2020-March 2021), and 323 during the omicron wave (January 2022-July 2022). Patients were stratified by wave and occurrence of cardiovascular events. Results: Among all hospitalized patients with cardiovascular events, patients in the omicron wave were younger (62.4 ± 14 years) than patients in the first wave (67.4 ± 7.8 years) and the delta wave (66.9 ± 12.6 years) and had a higher proportion of non-Hispanic White people than in the first wave (78.6% vs. 61.7%). For COVID-19 patients who suffered from cardiovascular events, the omicron wave patients had significantly higher neutrophil/lymphocyte ratio, white blood cell and platelet counts when compared to the first wave. Omicron wave patients had significantly lower albumin and B-type natriuretic peptide levels (only 5.8% of the first wave and 14.6% of the delta wave) when compared to either the first wave or delta wave patients. In COVID-19 patients who suffered cardiovascular events during hospitalization, mortality rate in the omicron wave (26.8%) was significantly lower than the first wave (48.3%), time to mortality for non-survivors of COVID-19 patients who suffered cardiovascular events was significantly longer in the omicron wave (median 16 days) than in the first wave (median 10 days). Conclusions: Younger and white patients were affected with cardiovascular complications more often by the omicron variant. Despite higher neutrophil/lymphocyte ratio and WBC counts, the omicron patients with cardiovascular events showed lower heart injuries, lower mortality and longer time to mortality for non-survivors when compared to the first and delta waves.

Fluorescent biosensor based on magnetic separation platform and spore-like breakable organosilica nanocapsules controlled-release carbon dots for the detection of Escherichia coli O157:H7.

Ultrasensitive and rapid detection of low concentration of Escherichia coli O157: H7 (E. coli O157:H7) in food is essential for food safety and public health. In this study, A novel fluorescence signal amplification biosensor based on magnetic separation platform and red fluorescent carbon dots (R-CDs)-encapsulated breakable organosilica nanocapsules (BONs) for ultrasensitive detection of E. coli O157:H7 was established. Wulff-type boronic acid functionalized magnetic nanoparticles (MNPs@B-N/APBA) with broad-spectrum bacterial recognition ability were synthesized for the first time to recognize and capture E. coli O157: H7 in food samples. R-CDs@BONs labeled with anti-E. coli O157:H7 monoclonal antibody (mAb@R-CDs@BONs-NH2) were used as the second recognition element to ensure the specificity for E. coli O157:H7 and form MNPs@B-N/APBA∼ E. coli O157:H7∼mAb@R-CDs@BONs-NH2 sandwich complexes, followed by releasing R-CDs to generate amplified fluorescence response signals for quantitative detection of E. coli O157:H7. The proposed method had a limit of detection with 25 CFU/mL in pure culture and contaminated lettuce samples, which the whole detection process took about 120 min. This fluorescence signal amplification biosensor has the potential to detect other pathogens in food by altering specific antibodies.

A Self-supervised Learning-Based Fine-Grained Classification Model for Distinguishing Malignant From Benign Subcentimeter Solid Pulmonary Nodules.

RATIONALE AND OBJECTIVES: Diagnosing subcentimeter solid pulmonary nodules (SSPNs) remains challenging in clinical practice. Deep learning may perform better than conventional methods in differentiating benign and malignant pulmonary nodules. This study aimed to develop and validate a model for differentiating malignant and benign SSPNs using CT images. MATERIALS AND METHODS: This retrospective study included consecutive patients with SSPNs detected between January 2015 and October 2021 as an internal dataset. Malignancy was confirmed pathologically; benignity was confirmed pathologically or via follow-up evaluations. The SSPNs were segmented manually. A self-supervision pre-training-based fine-grained network was developed for predicting SSPN malignancy. The pre-trained model was established using data from the National Lung Screening Trial, Lung Nodule Analysis 2016, and a database of 5478 pulmonary nodules from the previous study, with subsequent fine-tuning using the internal dataset. The model's efficacy was investigated using an external cohort from another center, and its accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were determined. RESULTS: Overall, 1276 patients (mean age, 56 ± 10 years; 497 males) with 1389 SSPNs (mean diameter, 7.5 ± 2.0 mm; 625 benign) were enrolled. The internal dataset was specifically enriched for malignancy. The model's performance in the internal testing set (316 SSPNs) was: AUC, 0.964 (95% confidence interval (95%CI): 0.942-0.986); accuracy, 0.934; sensitivity, 0.965; and specificity, 0.908. The model's performance in the external test set (202 SSPNs) was: AUC, 0.945 (95% CI: 0.910-0.979); accuracy, 0.911; sensitivity, 0.977; and specificity, 0.860. CONCLUSION: This deep learning model was robust and exhibited good performance in predicting the malignancy of SSPNs, which could help optimize patient management.

A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds.

BACKGROUND: The COVID-19 pandemic had profound global impacts on daily lives, economic stability, and healthcare systems. Diagnosis of COVID-19 infection via RT-PCR was crucial in reducing spread of disease and informing treatment management. While RT-PCR is a key diagnostic test, there is room for improvement in the development of diagnostic criteria. Identification of volatile organic compounds (VOCs) in exhaled breath provides a fast, reliable, and economically favorable alternative for disease detection. METHODS: This meta-analysis analyzed the diagnostic performance of VOC-based breath analysis in detection of COVID-19 infection. A systematic review of twenty-nine papers using the grading criteria from Newcastle-Ottawa Scale (NOS) and PRISMA guidelines was conducted. RESULTS: The cumulative results showed a sensitivity of 0.92 (95 % CI, 90 %-95 %) and a specificity of 0.90 (95 % CI 87 %-93 %). Subgroup analysis by variant demonstrated strong sensitivity to the original strain compared to the Omicron and Delta variant in detection of SARS-CoV-2 infection. An additional subgroup analysis of detection methods showed eNose technology had the highest sensitivity when compared to GC-MS, GC-IMS, and high sensitivity-MS. CONCLUSION: Overall, these results support the use of breath analysis as a new detection method of COVID-19 infection.

Synergistic Catalysis of SO42-/TiO2-CNT for the CO2 Desorption Process with Low Energy Consumption.

To address the issue of high energy consumption associated with monoethanolamine (MEA) regeneration in the CO2 capture process, solid acid catalysts have been widely investigated due to their performance in accelerating carbamate decomposition. The recently discovered carbon nanotube (CNT) catalyst presents efficient catalytic activity for bicarbonate decomposition. In this paper, bifunctional catalysts SO42-/TiO2-CNT (STC) were prepared, which could simultaneously catalyze carbamate and bicarbonate decomposition, and outstanding catalytic performance has been exhibited. STC significantly increased the CO2 desorption amount by 82.3% and decreased the relative heat duty by 46% compared to the MEA-CO2 solution without catalysts. The excellent stability of STC was confirmed by 15 cyclic absorption-desorption experiments, showing good practical feasibility for decreasing energy consumption in an industrial CO2 capture process. Furthermore, associated with the results of experimental characterization and theoretical calculations, the synergistic catalysis of STC catalysts via proton and charge transfer was proposed. This work demonstrated the potential of STC catalysts in improving the efficiency of amine regeneration processes and reducing energy consumption, contributing to the design of more effective and economical catalysts for carbon capture.

Epimedin B exerts an anti-inflammatory effect by regulating the MAPK/NF-κB/NOD-like receptor signalling pathways.

Epimedin B (EB), a predominant compound found in Herba Epimedii, has been shown to be effective in the treatment of osteoporosis and peripheral neuropathy. However, the anti-inflammatory effect of EB has not yet been reported. The anti-inflammatory activity of EB was evaluated in a zebrafish inflammation model induced by copper sulfate (CuSO4) and tail cutting. Our findings demonstrated that EB effectively inhibited acute inflammation, mitigated the accumulation of reactive oxygen species (ROS), and ameliorated the neuroinflammation-associated impairment of locomotion in zebrafish. Moreover, EB regulates several genes related to the mitogen-activated protein kinase (MAPK)/nuclear factor-κB (NF-κB)/Nod-like receptor signalling pathways (mapk8b, src, mmp9, akt1, mapk14a, mapk14b, mapk1, egfra, map3k4, nfκb2, iκbαa, pycard, nlrp3 and caspase1) and inflammatory cytokine (stat6, arg1, irfɑ, stat1ɑ, il-1ß, il-4, il-6, il-8, cox-2, ptges, tnf-α and tgf-ß). Therefore, our findings indicate that EB could serve as a promising therapeutic candidate for treating inflammation.

The risk of sexual dysfunction in Chinese women with recurrent pregnancy loss and the associated factors: a multicenter cross-sectional study.

Background: Recurrent pregnancy loss (RPL) is a severe traumatic event for women of childbearing age. However, the association between RPL and female sexual dysfunction was unknown. Aim: The study sought to investigate the association between RPL and sexual dysfunction, and to explore the risk factors of sexual dysfunction for RPL patients. Methods: A multicenter cross-sectional study involving both RPL patients and healthy women was performed in 3 different hospitals in West China from May 2021 to January 2023. Baseline information including sociodemographic data and disease histories were collected. The Female Sexual Function Index (FSFI) was used to assess the sexual function of participants. Outcomes: The main outcome was the proportion of women at increased risk of sexual dysfunction (total FSFI scores <26.55), and the secondary outcome was risk factors of sexual dysfunction in RPL patients. Results: A total of 233 RPL patients and 185 healthy women were included in this study. RPL patients had significantly lower total FSFI scores (median 31.7 [interquartile range, 26.6-33.5] vs 33.0 [interquartile range, 31.2-34.1]; P < .001) and a significantly higher risk of sexual dysfunction than healthy women (24.9% vs 8.6%; P < .001). Body mass index >24 kg/m2 (adjusted odds ratio [OR], 4.132; 95% confidence interval [CI], 1.902-8.976, P < .001), working >8 h/d (adjusted OR, 2.111; 95% CI, 1.020-4.369, P = .044), and unexplained RPL (adjusted OR, 3.785; 95% CI, 1.967-7.280, P < .001) were independent risk factors of sexual dysfunction for RPL patients. Clinical Implications: RPL patients, especially those patients with the previously mentioned risk factors, should be focused on the risk of sexual dysfunction, and appropriate preventions could be applied. Strength and Limitations: We explored the association between RPL and sexual dysfunction and explored the risk factors of sexual dysfunction among RPL patients for the first time, and the multicenter data increased the generalizability of results. However, the cross-sectional design did not provide an exact causal relationship between RPL and sexual dysfunction, and potential risk factors related to mental health were not investigated. Conclusion: RPL patients were at an increased risk of sexual dysfunction. Overweight, fatigue caused by work, and unexplained RPL were risk factors of sexual dysfunction for RPL patients.

Redistribution of defective mitochondria-mediated dihydroorotate dehydrogenase imparts 5-fluorouracil resistance in colorectal cancer.

Although 5-fluorouracil (5-FU) is the primary chemotherapy treatment for colorectal cancer (CRC), its efficacy is limited by drug resistance. Ferroptosis activation is a promising treatment for 5-FU-resistant cancer cells; however, potential therapeutic targets remain elusive. This study investigated ferroptosis vulnerability and dihydroorotate dehydrogenase (DHODH) activity using stable, 5-FU-resistant CRC cell lines and xenograft models. Ferroptosis was characterized by measuring malondialdehyde levels, assessing lipid metabolism and peroxidation, and using mitochondrial imaging and assays. DHODH function is investigated through gene knockdown experiments, tumor behavior assays, mitochondrial import reactions, intramitochondrial localization, enzymatic activity analyses, and metabolomics assessments. Intracellular lipid accumulation and mitochondrial DHODH deficiency led to lipid peroxidation overload, weakening the defense system of 5-FU-resistant CRC cells against ferroptosis. DHODH, primarily located within the inner mitochondrial membrane, played a crucial role in driving intracellular pyrimidine biosynthesis and was redistributed to the cytosol in 5-FU-resistant CRC cells. Cytosolic DHODH, like its mitochondrial counterpart, exhibited dihydroorotate catalytic activity and participated in pyrimidine biosynthesis. This amplified intracellular pyrimidine pools, thereby impeding the efficacy of 5-FU treatment through molecular competition. These findings contribute to the understanding of 5-FU resistance mechanisms and suggest that ferroptosis and DHODH are promising therapeutic targets for patients with CRC exhibiting resistance to 5-FU.

Promoting tissue repair using deferoxamine nanoparticles loaded biomimetic gelatin/HA composite hydrogel.

To effectively address underlying issues and enhance the healing process of hard-to-treat soft tissue defects, innovative therapeutic approaches are required. One promising strategy involves the incorporation of bioactive substances into biodegradable scaffolds to facilitate synergistic tissue regeneration, particularly in vascular regeneration. In this study, we introduce a composite hydrogel design that mimics the extracellular matrix by covalently combining gelatin and hyaluronic acid (HA), with the encapsulation of deferoxamine nanoparticles (DFO NPs) for potential tissue regeneration applications. Crosslinked hydrogels were fabricated by controlling the ratio of HA in the gelatin-based hydrogels, resulting in improved mechanical properties, enhanced degradation ability, and optimised porosity, compared with hydrogel formed by gelatin alone. The DFO NPs, synthesized using a double emulsion method with poly (D,L-lactide-co-glycolide acid), exhibited a sustained release of DFO over 12 d. Encapsulating the DFO NPs in the hydrogel enabled controlled release over 15 d. The DFO NPs, composite hydrogel, and the DFO NPs loaded hydrogel exhibited excellent cytocompatibility and promoted cell proliferationin vitro. Subcutaneous implantation of the composite hydrogel and the DFO NPs loaded hydrogel demonstrated biodegradability, tissue integration, and no obvious adverse effects, evidenced by histological analysis. Furthermore, the DFO NPs loaded composite hydrogel exhibited accelerated wound closure and promoted neovascularisation and granular formation when tested in an excisional skin wound model in mice. These findings highlight the potential of our composite hydrogel system for promoting the faster healing of diabetes-induced skin wounds and oral lesions through its ability to modulate tissue regeneration processes.

Radiomics and Clinical Characters Based Gaussian Naive Bayes (GNB) Model for Preoperative Differentiation of Pulmonary Pure Invasive Mucinous Adenocarcinoma From Mixed Mucinous Adenocarcinoma.

Objective: To develop and validate predictive models based on clinical parameters, and radiomic features to distinguish pulmonary pure invasive mucinous adenocarcinoma (pIMA) from mixed mucinous adenocarcinoma (mIMA) before surgery. Method: From January 2017 to December 2022, 193 pIMA and 111 mIMA were retrospectively analyzed at our hospital in this retrospective study. From contrast-enhanced computed tomography, 1037 radiomic features were extracted. The patients were randomly divided into a training group and a test group (n = 213 and 91, respectively) in a 7:3 ratio. The least absolute shrinkage and selection operator algorithm was used to select radiomic features. In this study, 9 machine learning radiomics prediction models were applied. The radiomics score was then calculated based on the best-performing machine learning model adopted. The clinical model was developed using the same machine learning model of radiomics. In the end, a combined model based on clinical factors and radiomics features was developed. The area under the receiver operating characteristic curve (AUC) value and decision curve analysis (DCA) were used to evaluate the clinical usefulness of the prediction model. Results: The combined model established by the Gaussian Naive Bayes machine learning method exhibited the best performance. The AUC of the combined model, clinical model, and radiomics model were 0.81, 0.80, and 0.68 in the training group and 0.91, 0.80, and 0.81 in the test group, respectively. The Brier scores of the combined model were 0.171 and 0.112. The DCA curve also showed that the combined model was beneficial to clinical settings. Conclusion: The combined model integration of radiomics features and clinical parameters may have potential value for the preoperative differentiation of pIMA from mIMA.

Pepsinogen C Interacts with IQGAP1 to Inhibit the Metastasis of Gastric Cancer Cells by Suppressing Rho-GTPase Pathway.

AIM: This study systematically explored the biological effects and mechanisms of PGC on gastric cancer (GC) cells in vitro and in vivo. METHOD: The critical biological roles of PGC in GC were assessed via EdU staining, Hoechst staining, flow cytometry, mouse models, CCK-8, wound healing, transwell, and sphere-forming assays. The interaction study with IQ-domain GTPase-activating protein 1 (IQGAP1) was used by Liquid chromatography-mass spectrometry co-immunoprecipitation, immunofluorescence staining, CHX-chase assay, MG132 assay, and qRT-PCR. RESULTS: PGC inhibited the proliferation, viability, epithelial-mesenchymal transition, migration, invasion, and stemness of GC cells and promoted GC cell differentiation. PGC suppressed subcutaneous tumor growth and peritoneal dissemination in vivo. The interaction study found PGC inhibits GC cell migration and invasion by downregulating IQGAP1 protein and IQGAP1-mediated Rho-GTPase signaling suppression. In addition, PGC disrupts the stability of the IQGAP1 protein, promoting its degradation and significantly shortening its half-life. Moreover, the expression levels of PGC and IQGAP1 in GC tissues were significantly negatively correlated. CONCLUSION: PGC may act as a tumor suppressor in the development and metastasis of GC. PGC can downregulate its interacting protein IQGAP1 and inhibit the Rho-GTPase pathway, thereby participating in the inhibition of GC cell migration and invasion.

Data-Physics Fusion-Driven Defect Predictions for Titanium Alloy Casing Using Neural Network.

The quality of Ti alloy casing is crucial for the safe and stable operation of aero engines. However, the fluctuation of key process parameters during the investment casting process of titanium alloy casings has a significant influence on the volume and number of porosity defects, and this influence cannot be effectively suppressed at present. Therefore, this paper proposes a strategy to control the influence of process parameters on shrinkage volume and number. This study constructed multiple regression prediction models and neural network prediction models of porosity volume and number for a ZTC4 casing by simulating the gravity investment casting process. The results show that the multiple regression prediction model and neural network prediction model of shrinkage cavity total volume have an accuracy of over 99%. The accuracy of the neural network prediction model is higher than that of the multiple regression model, and the neural network model realizes the accurate prediction of shrinkage defect volume and defect number through pouring temperature, pouring time, and mold shell temperature. The sensitivity degree of casing defects to key process parameters, from high to low, is as follows: pouring temperature, pouring time, and mold temperature. Further optimizing the key process parameter window reduces the influence of process parameter fluctuation on the volume and number of porosity defects in casing castings. This study provides a reference for actual production control process parameters to reduce shrinkage cavity and loose defects.

Comprehensive variant analysis of phospholipase A2 superfamily genes in large Chinese Parkinson' s disease cohorts.

To clarify the genetic role of phospholipase A2 (PLA2) genes in Parkinson's disease (PD), we performed a genetic association study in large Chinese population cohorts using next-generation sequencing. In this study, we analyzed both rare and common variants of 38 phospholipase A2 genes in two large cohorts. We detected 1558 and 1115 rare variants in these two cohorts, respectively. In both cohorts, we observed suggestive associations between specific subgroups and the risk of PD. At the single-gene level, several genes (PLA2G2D, PLA2G12A, PLA2G12B, PLA2G4F, PNPLA1, PNPLA3, PNPLA7, PLA2G7, PLA2G15, PLAAT5, and ABHD12) are suggestively associated with PD. Meanwhile, 364 and 2261 common variants were identified in two cohorts, respectively. Our study has expanded the genetic spectrum of the PLA2 family genes and suggested potential pathogenetic roles of PLA2 superfamily in PD.

Genome-wide identification and examination of the wheat glycosyltransferase family 43 regulation during Fusarium graminearum infection.

In Arabidopsis and rice, the glycosyltransferase (GT) 43 family is involved in xylan synthesis. However, there have been limited reports on the study of the TaGT43 family in wheat. In this study, 28 TaGT43 family members were identified in wheat (Triticum aestivum L.) and clustered into three major groups based on the similarity of amino acid sequences. The results of the TaGT43 family's conserved motif and gene structure analyses agree with this result. Collinearity analysis revealed segmental duplications mainly promoted TaGT43 family expansion. cis-Acting element analysis revealed that the TaGT43 genes were involved in the light response, phytohormone response, abiotic/biotic stress response, and growth and development. The TaGT43 family showed a tissue-specific expression pattern, primarily expressed in roots and stems. Besides, the transcriptional and expression levels of multiple TaGT43 genes were upregulated during the infection of F. graminearum. According to metabolomics studies, F. graminearum infection affected the phenylpropanoid biosynthesis pathway in wheat, a critical factor in cell wall construction. Furthermore, GO enrichment analysis indicated that the TaGT43 genes play a significant role in cell wall organization. Based on these results, it may be concluded that the TaGT43 family mediates cell wall organization in response to F. graminearum infection.

Expression profiling and bioinformatics analysis of serum exosomal circular RNAs in lymph node metastasis of papillary thyroid carcinoma.

Most papillary thyroid carcinoma (PTC) patients have a good prognosis, but lymph node metastasis (LNM) is the most common progressive manifestation and often leads to a poor-prognosis. However, few studies focused on the underlying mechanisms of LNM. This study aimed to identity the potential role of exosomal circRNAs that contribute to LNM in PTC. We found that 9000 aberrantly expressed exosomal circRNAs in PTC patients with LNM, including 684 observably upregulation and 2193 notably downregulation. Functional enrichment analyses indicated that these aberrantly expressed circRNAs were mainly enriched in a variety of molecules and signaling pathways related to the progression and LNM of PTC. Bioinformatics analysis screened 14 circRNA-miRNA-mRNA networks associated with LNM-related signaling pathways in PTC. Moreover, circTACC2-miR-7-EGFR and circBIRC6-miR-24-3p-BCL2L11 axes were verified for potential involvement in PTC with LNM. Additionally, 4 upregulated circRNAs-related hub genes and 8 hub genes associated with downregulated circRNAs were screened, some of which were involved in LNM of PTC through verification. Collectively, our data provided a novel framework for in-depth investigation of the function of dysregulated exosomal circRNAs and their potential biomarkers in PTC patients with LNM.