MIR937 amplification potentiates ovarian cancer progression by attenuating FBXO16 inhibition on ULK1-mediated autophagy.

High-grade serous ovarian carcinoma (HGSOC) is one of the most lethal gynecological cancer. Genetic studies have revealed gene copy number alterations (CNAs) frequently occurred in HGSOC pathogenesis, however the function and mechanism of CNAs for microRNAs are still not fully understood. Here, we show the dependence on gene copy number amplification of MIR937 that enhances cell autophagy and dictates HGSOC proliferative activity. Data mining of TCGA database revealed MIR937 amplification is correlated with increased MIR937 expression and cell proliferation of HGSOC. Deletion of MIR937 in HGSOC cells led to impaired autophagy and retarded cell proliferation, and the extent for its inhibitory effects scaled with the degree of MIR937 copy loss. Rescue assay confirmed miR-937-5p, a mature product of MIR937, was sufficient to restore its oncogenic function. Mechanistically, MIR937 amplification raised the expression of miR-937-5p, enhanced its binding to 3' UTR of FBXO16 transcript, and thereby restricting FBXO16 degradative effects on ULK1. Our results demonstrate that MIR937 amplification augments cell autophagy and proliferation, and suggest an alternative strategy of MIR937/FBXO16/ULK1 targeting for HGSOC treatment.

Mendelian study on air pollution and membranous nephropathy outcomes associations.

Membranous nephropathy (MN) is an autoimmune disease of the kidney glomerulus, which mainly leads to nephrotic syndrome. This study investigates the associations between air pollution and MN risk and from an epigenomic perspective. In this study, we examine the associations between genetically predicted deoxyribonucleic acid methylation related to air pollution and MN risk. The data of air pollution included particulate matter (PM) with a diameter of 2.5 µm or less (PM2.5), PM with a diameter between 2.5 and 10 µm (PM2.5-10), PM with a diameter of 10 µm or less (PM10), nitrogen dioxide, and nitrogen oxides. Inverse variance weighted method was used as the main analysis method, and weighted median model and Mendelian randomization-Egger methods were selected for quality control. To assess the reliability of the results of the analyses, heterogeneity test, horizontal pleiotropy test, and the leave-one-out method were applied. There was a causal relationship between nitrogen oxides and MN risk (P = .010). Other types of air pollution were found no statistical association with MN disease (PM2.5: P = .378; PM2.5-10: P = .111; PM10: P = .035; nitrogen dioxide: P = .094). There was no heterogeneity or pleiotropy in the results. Our study suggests the association between nitrogen oxides and membrane nephropathy (MN) risk from the genetic perspective. This provides a theoretical basis for the prevention of MN disease.

A novel single-port robotic proximal gastrectomy with right-sided overlap and single-flap valvuloplasty (RPG-ROSF) to treat gastroesophageal cancer: A case report.

Robotic surgery has been widely used in surgical gastric cancer treatments, including proximal gastrectomy. Single-port robotic system is gaining more popularity in robotic surgery, but there has been no report on its application in robotic proximal gastrectomy with right-sided overlap and single-flap valvuloplasty (RPG-ROSF). Here, we report an RPG-ROSF using a novel single-port robotic system in a 51-year-old male patient with an early-stage gastroesophageal cancer detected by gastroscopy. It took 90 min for robotic setup, 143 min for dissection, and 161 min for digestive tract reconstruction. There was no complication during and after the surgery. The patient was discharged in 8 days postsurgery. The pathological staging of the adenocarcinoma was pT1aN0M0. This preliminary study demonstrated the feasibility and safety of a novel single-port robot in RPG-ROSF.

piR-27222 mediates PM2.5-induced lung cancer by resisting cell PANoptosis through the WTAP/m6A axis.

PM2.5 pollution has been associated with the incidence of lung cancer, but the underlying mechanism is still unclear. PIWI-interacting RNAs (piRNAs), initially identified in germline cells, have emerged as a novel class of small non-coding RNAs (26 - 32 nucleotides) with diverse functions in various diseases, including cancer. However, the role and mechanism of piRNAs in the development of PM2.5-induced lung cancer remain to be clarified. In the presented study, we used a PM2.5-induced malignant transformation cell model to analyze the change of piRNA profiles. Among the disturbed piRNAs, piR-27222 was identified as an oncogene that inhibited cell death in a m6A-dependent manner. Mechanistically, we found that piR-27222 could deubiquitinate and stabilize eIF4B by directly binding to eIF4B and reducing its interaction with PARK2. The enhanced expression of eIF4B, in turn, promoted the expression of WTAP, leading to increased m6A modification in the Casp8 transcript. Consequently, the stability of Casp8 transcripts was reduced, rendering lung cancer cells resistant to PANoptosis. Collectively, our findings reveal that PM2.5 exposure up-regulated piR-27222 expression, which could affect EIF4B/WTAP/m6A axis, thereby inhibiting PANoptosis of cells and promoting lung cancer. Our study provides new insights into understanding the epigenetic mechanisms underlining PM2.5-induced lung cancer.

New insights into the function and mechanisms of piRNA PMLCPIR in promoting PM2.5-induced lung cancer.

INTRODUCTION: Extensive studies have established the correlation between long-term PM2.5 exposure and lung cancer, yet the mechanisms underlying this association remain poorly understood. PIWI-interacting RNAs (piRNAs), a novel category of small non-coding RNAs, serve important roles in various diseases. However, their biological function and mechanism in PM2.5-induced lung cancer have not been thoroughly investigated. OBJECTIVES: We aimed to explore the oncogenic role of piRNA in lung cancer induced by PM2.5 exposure, as well as the underlying mechanisms. METHODS: We conducted a PM2.5-induced human lung epithelial cell malignant transformation model. Human samples were used to further verify the finding. In vitro proliferation, migration, and invasion assays were performed to study the function of piRNA. RNA-sequencing was used to elucidate the the mechanisms of how piRNA mediates cell functions. PiRNA pull-down and computational docking analysis were conducted to identify proteins that binding to piRNA. In vivo experiments were used to explore whether inhibition of PMLCPIR could have a therapeutic effect on lung cancer. RESULTS: We identified a new up-regulated piRNA, termed PM2.5-induced lung cancer up-regulation piRNA (PMLCPIR), which promotes the proliferation of PM2.5-transformed cells and lung cancer cells. RNA sequencing revealed ITGB1 as a downstream target of PMLCPIR. Importantly, PMLCPIR binds to nucleolin (NCL) and increases the expression of its target gene, ITGB1, thereby activating PI3K/AKT signaling. The inhibition of PMLCPIR could promote apoptosis in lung cancer cells and enhance their chemosensitivity to anti-tumor drugs. CONCLUSION: We systematically identified the alterations of piRNA expression profiles in the PM2.5-induced malignant transformation model. Then, PMLCPIR was recognized as a novel oncogenic piRNA in PM2.5-induced lung cancer. Mechanically, PMLCPIR binds to NCL, enhancing ITGB1 expression and activating the ontogenetic PI3K/AKT signaling, potentially contributing to lung cancer progression. This study provides novel insights into the revelation of a new epigenetic regulator in PM2.5-induced lung cancer.

Pramel15 facilitates zygotic nuclear DNMT1 degradation and DNA demethylation.

In mammals, global passive demethylation contributes to epigenetic reprogramming during early embryonic development. At this stage, the majority of DNA-methyltransferase 1 (DNMT1) protein is excluded from nucleus, which is considered the primary cause. However, whether the remaining nuclear activity of DNMT1 is regulated by additional mechanisms is unclear. Here, we report that nuclear DNMT1 abundance is finetuned through proteasomal degradation in mouse zygotes. We identify a maternal factor, Pramel15, which targets DNMT1 for degradation via Cullin-RING E3 ligases. Loss of Pramel15 elevates DNMT1 levels in the zygote pronuclei, impairs zygotic DNA demethylation, and causes a stochastic gain of DNA methylation in early embryos. Thus, Pramel15 can modulate the residual level of DNMT1 in the nucleus during zygotic DNA replication, thereby ensuring efficient DNA methylation reprogramming in early embryos.

Comparison of Cox regression and generalized Cox regression models to machine learning in predicting survival of children with diffuse large B-cell lymphoma.

Background: The incidence of diffuse large B-cell lymphoma (DLBCL) in children is increasing globally. Due to the immature immune system in children, the prognosis of DLBCL is quite different from that of adults. We aim to use the multicenter large retrospective analysis for prognosis study of the disease. Methods: For our retrospective analysis, we retrieved data from the Surveillance, Epidemiology and End Results (SEER) database that included 836 DLBCL patients under 18 years old who were treated at 22 central institutions between 2000 and 2019. The patients were randomly divided into a modeling group and a validation group based on the ratio of 7:3. Cox stepwise regression, generalized Cox regression and eXtreme Gradient Boosting (XGBoost) were used to screen all variables. The selected prognostic variables were used to construct a nomogram through Cox stepwise regression. The importance of variables was ranked using XGBoost. The predictive performance of the model was assessed by using C-index, area under the curve (AUC) of receiver operating characteristic (ROC) curve, sensitivity and specificity. The consistency of the model was evaluated by using a calibration curve. The clinical practicality of the model was verified through decision curve analysis (DCA). Results: ROC curve demonstrated that all models except the non-proportional hazards and non-log linearity (NPHNLL) model, achieved AUC values above 0.7, indicating high accuracy. The calibration curve and DCA further confirmed strong predictive performance and clinical practicability. Conclusions: In this study, we successfully constructed a machine learning model by combining XGBoost with Cox and generalized Cox regression models. This integrated approach accurately predicts the prognosis of children with DLBCL from multiple dimensions. These findings provide a scientific basis for accurate clinical prognosis prediction.

Identification of stable reference genes for relative quantification of long RNA expression in urinary extracellular vesicles.

Urinary extracellular vesicles (uEVs) are rich in valuable biomolecule information which are increasingly recognized as potential biomarkers for various diseases. uEV long RNAs are among the critical cargos capable of providing unique transcriptome information of the source cells. However, consensus regarding ideal reference genes for relative long RNAs quantification in uEVs is not available as of date. Here we explored stable reference genes through profiling the long RNA expression by RNA-seq following unsupervised analysis and validation studies. Candidate reference genes were identified using four algorithms: NormFinder, GeNorm, BestKeeper and the Delta Ct method, followed by validation. RNA profile showed uEVs contained abundant long RNAs information and the core transcriptome was related to cellular structures, especially ribosome which functions mainly as translation, protein and RNA binding molecules. Analysis of RNA-seq data identified RPL18A, RPL11, RPL27, RACK1, RPSA, RPL41, H1-2, RPL4, GAPDH, RPS27A as candidate reference genes. RT-qPCR validation revealed that RPL41, RPSA and RPL18A were reliable reference genes for long RNA quantification in uEVs from patients with diabetes mellitus (DM), diabetic nephropathy (DN), IgA nephropathy (IgAN) and prostate cancer (PCA). Interestingly, RPL41 also outperformed traditional reference genes in renal tissues of DN and IgAN, as well as in plasma EVs of several types of cancers. The stable reference genes identified in this study may facilitate development of uEVs as novel biomarkers and increase the accuracy and comparability of biomarker studies.

Mitochondrial Protease Oct1p Regulates Mitochondrial Homeostasis and Influences Pathogenicity through Affecting Hyphal Growth and Biofilm Formation Activities in Candida albicans.

Mitochondria, as the core metabolic organelles, play a crucial role in aerobic respiration/biosynthesis in fungi. Numerous studies have demonstrated a close relationship between mitochondria and Candida albicans virulence and drug resistance. Here, we report an octapeptide-aminopeptidase located in the mitochondrial matrix named Oct1p. Its homolog in the model fungus Saccharomyces cerevisiae is one of the key proteins in maintaining mitochondrial respiration and protein stability. In this study, we utilized evolutionary tree analysis, gene knockout experiments, mitochondrial function detection, and other methods to demonstrate the impact of Oct1p on the mitochondrial function of C. albicans. Furthermore, through transcriptome analysis, real-time quantitative PCR, and morphological observation, we discovered that the absence of Oct1p results in functional abnormalities in C. albicans, affecting hyphal growth, cell adhesion, and biofilm formation. Finally, the in vivo results of the infection of Galleria mellonella larvae and vulvovaginal candidiasis in mice indicate that the loss of Oct1p led to the decreased virulence of C. albicans. In conclusion, this study provides a solid theoretical foundation for treating Candida diseases, developing new targeted drugs, and serves as a valuable reference for investigating the connection between mitochondria and virulence in other pathogenic fungi.

Mapping global mangrove canopy height by integrating Ice, Cloud, and Land Elevation Satellite-2 photon-counting LiDAR data with multi-source images.

Large-scale and precise measurement of mangrove canopy height is crucial for understanding and evaluating wetland ecosystems' condition, health, and productivity. This study generates a global mangrove canopy height map with a 30 m resolution by integrating Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) photon-counting light detection and ranging (LiDAR) data with multi-source imagery. Initially, high-quality mangrove canopy height samples were extracted using meticulous processing and filtering of ICESat-2 data. Subsequently, mangrove canopy height models were established using the random forest (RF) algorithm, incorporating ICESat-2 canopy height samples, Sentinel-2 data, TanDEM-X DEM data and WorldClim data. Furthermore, a global 30 m mangrove canopy height map was generated utilizing the Google Earth Engine platform. Finally, the global map's accuracy was evaluated by comparing it with reference canopy heights derived from both space-borne and airborne LiDAR data. Results indicate that the global 30 m resolution mangrove height map was found to be consistent with canopy heights obtained from space-borne (r = 0.88, Bisa = -0.07 m, RMSE = 3.66 m, RMSE% = 29.86 %) and airborne LiDAR (r = 0.52, Bisa = -1.08 m, RMSE = 3.39 m, RMSE% = 39.05 %). Additionally, our findings reveal that mangroves worldwide exhibit an average height of 12.65 m, with the tallest mangrove reaching a height of 44.94 m. These results demonstrate the feasibility and effectiveness of using ICESat-2 data integrated with multi-source imagery to generate a global mangrove canopy height map. This dataset offers reliable information that can significantly support government and organizational efforts to protect and conserve mangrove ecosystems.

Syringeable Near-Infrared Light-Activated In Situ Immunogenic Hydrogel Boosts the Cancer-Immunity Cycle to Enhance Anticancer Immunity.

Effective anticancer immunity depends on properly activating multiple stepwise events in the cancer-immunity cycle. An immunologically "cold" tumor microenvironment (TME) engenders immune evasion and refractoriness to conventional checkpoint blockade immunotherapy. Here, we combine nanoparticle formulations and an in situ formed hydrogel scaffold to treat accessible tumors locally and to stimulate systemic immunity against metastatic tumor lesions. The nanoparticles encapsulate poly(ε-caprolactone)-derived cytotoxic chemotherapy and adjuvant of Toll-like receptor 7/8 through a reactive oxygen species (ROS)-cleavable linker that can be self-activated by the coassembled neighboring photosensitizer following near-infrared (NIR) laser irradiation. Further development results in syringeable, NIR light-responsive, and immunogenic hydrogel (iGEL) that can be implanted peritumorally and deposited into the tumor surgical bed. Upon NIR laser irradiation, the generated ROS induces iGEL degradation and bond cleavage in the polymer-drug conjugates, triggering the immunogenic cell death cascade in cancer cells and spontaneously releasing encapsulated agents to rewire the cancer-immunity cycle. Notably, upon application in multiple preclinical models of melanoma and triple-negative breast cancer, which are aggressive and refractory to conventional immunotherapy, iGEL induces durable remission of established tumors, extends postsurgical tumor-free survival, and inhibits metastatic burden. The result of this study is a locally administrable immunogenic hydrogel for triggering host systemic immunity to improve immunotherapeutic efficacy with minimal off-target side effects.

Associations between Geriatric Nutrition Risk Index, bone mineral density and body composition in type 2 diabetes patients.

BACKGROUND: Type 2 diabetes mellitus (T2DM), a fast-growing issue in public health, is one of the most common chronic metabolic disorders in older individuals. Osteoporosis and sarcopenia are highly prevalent in T2DM patients and may result in fractures and disabilities. In people with T2DM, the association between nutrition, sarcopenia, and osteoporosis has rarely been explored. AIM: To evaluate the connections among nutrition, bone mineral density (BMD) and body composition in patients with T2DM. METHODS: We enrolled 689 patients with T2DM for this cross-sectional study. All patients underwent dual energy X-ray absorptiometry (DXA) examination and were categorized according to baseline Geriatric Nutritional Risk Index (GNRI) values calculated from serum albumin levels and body weight. The GNRI was used to evaluate nutritional status, and DXA was used to investigate BMD and body composition. Multivariate forward linear regression analysis was used to identify the factors associated with BMD and skeletal muscle mass index. RESULTS: Of the total patients, 394 were men and 295 were women. Compared with patients in tertile 1, those in tertile 3 who had a high GNRI tended to be younger and had lower HbA1c, higher BMD at all bone sites, and higher appendicular skeletal muscle index (ASMI). These important trends persisted even when the patients were divided into younger and older subgroups. The GNRI was positively related to ASMI (men: r = 0.644, P < 0.001; women: r = 0.649, P < 0.001), total body fat (men: r = 0.453, P < 0.001; women: r = 0.557, P < 0.001), BMD at all bone sites, lumbar spine (L1-L4) BMD (men: r = 0.110, P = 0.029; women: r = 0.256, P < 0.001), FN-BMD (men: r = 0.293, P < 0.001; women: r = 0.273, P < 0.001), and hip BMD (men: r = 0.358, P < 0.001; women: r = 0.377, P < 0.001). After adjustment for other clinical parameters, the GNRI was still significantly associated with BMD at the lumbar spine and femoral neck. Additionally, a low lean mass index and higher ß-collagen special sequence were associated with low BMD at all bone sites. Age was negatively correlated with ASMI, whereas weight was positively correlated with ASMI. CONCLUSION: Poor nutrition, as indicated by a low GNRI, was associated with low levels of ASMI and BMD at all bone sites in T2DM patients. Using the GNRI to evaluate nutritional status and using DXA to investigate body composition in patients with T2DM is of value in assessing bone health and physical performance.

The effect of GnRH analog treatment on BMI in children treated for precocious puberty: a systematic review and meta-analysis.

INTRODUCTION: The purpose of the present meta-analysis was to systematically evaluate the effect of GnRHa treatment on the BMI of children with precocious puberty after GnRHa treatment as compared to before, and to analyze the effect of GnRHa treatment on the body composition of children with precocious puberty at different BMIs by classifying into normal body mass, overweight, and obese groups according to BMI at the time of initial diagnosis. CONTENT: A meta-analysis was performed using Stata 12.0 software by searching PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), Chinese Scientific Journal Database (VIP database), and Wan fang database for relevant literature on standard deviation score of body mass index (BMI-SDS) after GnRHa treatment as compared to before in children with precocious puberty. SUMMARY: A total of eight studies were included with a total sample size of 715 cases, and the results of meta-analysis showed that BMI-SDS increased in children with precocious puberty after GnRHa treatment as compared to before starting [(weighted mean difference (WMD)=0.23, 95 % CI: 0.14-0.33, p=0.000)] and also increased in children with normal body mass [(WMD=0.37, 95 % CI: 0.28-0.46, p=0.000)], and there was no significant change in BMI-SDS in children in the overweight or obese group [(WMD=0.01, 95 % CI: -0.08-0.10, p=0.775)]. OUTLOOK: Overall, there was an observed increase in BMI-SDS at the conclusion of GnRHa treatment in children with precocious puberty. Additionally, it was found that the effect of GnRHa treatment on body composition varied among children with different BMI status. Clinicians should emphasize the promotion of a healthy lifestyle and personalized dietary management for children.

Role of the In-Situ-Formed Surface (Pt-S-O)-Ti Active Structure in SO2-Promoted C3H8 Combustion over a Pt/TiO2 Catalyst.

Typically, SO2 unavoidably deactivates catalysts in most heterogeneous catalytic oxidations. However, for Pt-based catalysts, SO2 exhibits an extraordinary boosting effect in propane catalytic oxidation, but the promotive mechanism remains contentious. In this study, an in situ-formed tactful (Pt-S-O)-Ti structure was concluded to be a key factor for Pt/TiO2 catalysts with a substantial SO2 tolerance ability. The experiments and theoretical calculations confirm that the high degree of hybridization and orbital coupling between Pt 5d and S 3p orbitals enable more charge transfer from Pt to S species, thus forming the (Pt-S-O)-Ti structure with the oxygen atom dissociated from the chemisorbed O2 adsorbed on oxygen vacancies. The active oxygen atom in the (Pt-S-O)-Ti active structure is a robust site for C3H8 adsorption, leading to a better C3H8 combustion performance. This work can provide insights into the rational design of chemical bonds for high SO2 tolerance catalysts, thereby improving economic and environmental benefits.

LncRNA ZNF674-AS1 drives cell growth and inhibits cisplatin-induced pyroptosis via up-regulating CA9 in neuroblastoma.

Neuroblastoma (NB) is a challenging pediatric extracranial solid tumor characterized by a poor prognosis and resistance to chemotherapy. Identifying targets to enhance chemotherapy sensitivity in NB is of utmost importance. Increasing evidence implicates long noncoding RNAs (lncRNAs) play important roles in cancer, but their functional roles remain largely unexplored. Here, we analyzed our RNA sequencing data and identified the upregulated lncRNA ZNF674-AS1 in chemotherapy non-responsive NB patients. Elevated ZNF674-AS1 expression is associated with poor prognosis and high-risk NB. Importantly, targeting ZNF674-AS1 expression in NB cells suppressed tumor growth in vivo. Further functional studies have revealed that ZNF674-AS1 constrains cisplatin sensitivity by suppressing pyroptosis and promoting cell proliferation. Moreover, ZNF674-AS1 primarily relies on CA9 to fulfill its functions on cisplatin resistance. High CA9 levels were associated with high-risk NB and predicted poor patient outcomes. Mechanistically, ZNF674-AS1 directly interacted with the RNA binding protein IGF2BP3 to enhance the stability of CA9 mRNA by binding with CA9 transcript, leading to elevated CA9 expression. As a novel regulator of CA9, IGF2BP3 positively upregulated CA9 expression. Together, these results expand our understanding of the cancer-associated function of lncRNAs, highlighting the ZNF674-AS1/IGF2BP3/CA9 axis as a constituting regulatory mode in NB tumor growth and cisplatin resistance. These insights reveal the pivotal role of ZNF674-AS1 inhibition in recovering cisplatin sensitivity, thus providing potential therapeutic targets for NB treatment.

Gliclazide Ameliorates Neuronal Injury by Attenuating Oxidative Stress in D-gal-Induced Senescent Cells and Aging Mice.

Enhancement of oxidative stress and resultant neuronal injury play important roles in initiating cognitive impairment during the aging process. Thus, attenuating oxidative injury is regarded as a profitable therapeutic strategy for age-associated cognitive impairment. Previous studies showed that gliclazide (Gli) had a protective role in neuronal injury from cerebral ischemia/reperfusion (I/R) injury. However, whether Gli has a profitable effect on age-associated cognitive impairment remains largely unclear. The present study showed that Gli held the potential to attenuate neuronal apoptosis in D-gal-induced senescent cells and aging mice. Additionally, Gli could alleviate synaptic injury and cognitive function in D-gal-induced aging mice. Further study showed that Gli could attenuate oxidative stress in D-gal-induced senescent cells and aging mice. The p38 MAPK pathway was predicted as the downstream target of Gli retarding oxidative stress using in silico analysis. Further studies revealed that Gli attenuated D-gal-induced phosphorylation of p38 and facilitated Nrf2 nuclear expression, indicating that the anti-oxidative property of Gli may be associated with the p38 MAPK pathway. The study demonstrates that Gli has a beneficial effect on ameliorating D-gal-induced neuronal injury and cognitive impairment, making this compound a promising agent for the prevention and treatment of age-associated cognitive impairment.

Facile Synthesis of 2D SiOx -3D Si Hybrid Anode Materials by Ca Modification Effect for Enhanced Lithium Storage Performance.

Al-Si dealloying method is widely used to prepare Si anode for alleviating the issues caused by a drastic volume change of Si-based anode. However, this method suffers from the problems of low Si powder yield (<20 wt.% Si) and complicated cooling equipment due to the hindrance of large-size primary Si particles. Here, a new modification strategy to convert primary Si to 2D SiOx nanosheets by introducing a Ca modifier into Al-Si alloy melt is presented. The thermodynamics calculation shows that the primary Si is preferentially converted to CaAl2 Si2 intermetallic compound in Al-Si-Ca alloy system. After the dealloying process, the CaAl2 Si2 is further converted to 2D SiOx nanosheets, and eutectic Si is converted to 3D Si, thus obtaining the 2D SiOx -3D Si hybrid Si-based materials (HSiBM). Benefiting from the modification effect, the HSiBM anode shows a significantly improved electrochemical performance, which delivers a capacity retention of over 90% after 100 cycles and keeps 98.94% capacity after the rate test. This work exhibits an innovative approach to produce stable Si-based anode through Al-Si dealloying method with a high Si yield and without complicated rapid cooling techniques, which has a certain significance for the scalable production of Si-based anodes.

The utility of quantitative computed tomography in cohort studies of chronic obstructive pulmonary disease: a narrative review.

Background and Objective: Chronic obstructive pulmonary disease (COPD) is a significant contributor to global morbidity and mortality. Quantitative computed tomography (QCT), a non-invasive imaging modality, offers the potential to assess lung structure and function in COPD patients. Amidst the coronavirus disease 2019 (COVID-19) pandemic, chest computed tomography (CT) scans have emerged as a viable alternative for assessing pulmonary function (e.g., spirometry), minimizing the risk of aerosolized virus transmission. However, the clinical application of QCT measurements is not yet widespread enough, necessitating broader validation to determine its usefulness in COPD management. Methods: We conducted a search in the PubMed database in English from January 1, 2013 to April 20, 2023, using keywords and controlled vocabulary related to QCT, COPD, and cohort studies. Key Content and Findings: Existing studies have demonstrated the potential of QCT in providing valuable information on lung volume, airway geometry, airway wall thickness, emphysema, and lung tissue density in COPD patients. Moreover, QCT values have shown robust correlations with pulmonary function tests, and can predict exacerbation risk and mortality in patients with COPD. QCT can even discern COPD subtypes based on phenotypic characteristics such as emphysema predominance, supporting targeted management and interventions. Conclusions: QCT has shown promise in cohort studies related to COPD, since it can provide critical insights into the pathogenesis and progression of the disease. Further research is necessary to determine the clinical significance of QCT measurements for COPD management.

Selection and validation of optimal reference genes for RT-qPCR analyses in Aphidoletes aphidimyza Rondani (Diptera: Cecidomyiidae).

Aphidoletes aphidimyza is a predator that is an important biological agent used to control agricultural and forestry aphids. Although many studies have investigated its biological and ecological characteristics, few molecular studies have been reported. The current study was performed to identify suitable reference genes to facilitate future gene expression and function analyses via quantitative reverse transcription PCR. Eight reference genes glyceraldehyde-3-phosphate dehydrogenase (GAPDH), RPS13, RPL8, RPS3, α-Tub, ß-actin, RPL32, and elongation factor 1 alpha (EF1-α) were selected. Their expression levels were determined under four different experimental conditions (developmental stages, adult tissues, sugar treatment, and starvation treatment) using qRT-PCR technology. The stability was evaluated with five methods (Ct value, geNorm, NormFinder, BestKeeper, and RefFinder). The results showed that GAPDH, RPL32, and EF1-α were ranked as the best reference gene combinations for measuring gene expression levels among different developing stages and in various starvation treatments. RPL8 and RPS3 were recommended to normalize the gene expression levels among different adult tissues. RPL32, ß-actin, and EF1-α were recommended sugar-feeding conditions. To validate the utility of the selected reference pair, RPL8, and RPS3, we estimated the tissue-biased expression level of a chemosensory protein gene (AaphCSP1). As expected, AaphCSP1 is highly expressed in the antennae and lowly expressed in the abdomen. These findings will lay the foundation for future research on the molecular physiology and biochemistry of A. aphidimyza.

An entropy weight method to integrate big omics and mechanistically evaluate DILI.

BACKGROUND AND AIMS: DILI accounts for more than half of acute liver failure cases in the United States and is a major health care issue for the public worldwide. As investigative toxicology is playing an evolving role in the pharmaceutical industry, mechanistic insights into drug hepatotoxicity can facilitate drug development and clinical medication. METHODS: By integrating multisource datasets including gene expression profiles of rat livers from open TG-GATE database and DrugMatrix, drug labels from FDA Liver Toxicity Knowledge Base, and clinical reports from LiverTox, and with the employment of bioinformatic and computational tools, this study developed an approach to characterize and predict DILI based on the molecular understanding of the processes (toxicity pathways). RESULTS: A panel of 11 pathways widely covering biological processes and stress responses was established using a training set of six positive and one negative DILI drugs from open TG-GATEs. An entropy weight method-based model was developed to weight responsive genes within a pathway, and an interpretable machine-learning (ML) model XGBoot-SHAP was trained to rank the importance of pathways to the panel activity. The panel activity was proven to differentiate between injured and noninjured sample points and characterize DILI manifestation using six training drugs. Next, the model was tested using an additional 89 drugs (61 positives + 28 negatives), and a precision of 86% and higher can be achieved. CONCLUSIONS: This study provides a novel approach to mechanisms-driven prediction modeling, as well as big data integration for insights into pharmacology and other human biology areas.