Platelet-to-lymphocyte ratios as a haematological marker of synovitis in rheumatoid arthritis with normal acute phase reactant level.

BACKGROUND: Although normal acute phase reactants (APRs) play an important role in assessing disease activity of rheumatoid arthritis (RA), some studies pointed out the discordance between disease activity and APR level. Neutrophil-to-lymphocyte ratios (NLRs), platelet-to-lymphocyte ratios (PLRs) and lymphocyte-to-monocyte ratios (LMRs) have been reported to be sensitive measures of inflammatory reaction. This study aims to explore the value of these haematological makers in assessment of APR-negative RA patients. METHODS: Out of a cohort of 418 consecutive patients with RA, we enrolled 135 patients with normal APR for this study. We performed ultrasound assessments to evaluate synovitis and bone erosion in the affected joints. Synovitis was evaluated by ultrasound grey scale (GS) and power Doppler (PD) with semi-quantitative scoring (0-3). Demographic, clinical and laboratory data were collected from the patients. Disease Activity Score-28 joints (DAS28), NLR, MLR and PLR were calculated. RESULTS: In RA patients with normal APR, PLR exhibited a positive correlation with ultrasound-detected synovitis and bone erosion, whereas NLR, MLR showed no significant correlation with ultrasonography parameters. The area under the ROC curve (AUC) for identifying synovitis with a GS grade ≥2 based on a PLR cutoff value of ≥159.6 was 0.7868 (sensitivity: 80.95%, specificity: 74.24%). For synovitis with a PD grade ≥2, the AUC was 0.7690, using a PLR cutoff value of ≥166.1 (sensitivity: 68.0%, specificity: 83.87%). CONCLUSIONS: Our findings suggested that PLR might be a reliable and cost-effective marker for identifying moderate-to-severe synovitis in RA patients with normal APR.

Hypericin-mediated photodynamic therapy inhibits metastasis and EMT of colorectal cancer cells by regulating RhoA-ROCK1 signaling pathway.

Colorectal cancer (CRC) is significantly contributed to global cancer mortality rates. Treating CRC is particularly challenging due to metastasis and drug resistance. There is a pressing need for new treatment strategies against metastatic CRC. Photodynamic therapy (PDT) offers a well-established, minimally invasive treatment option for cancer with limited side effects. Hypericin (HYP), a potent photosensitizer for PDT, has been documented to induce cytotoxicity and apoptosis in various types of cancers. However, there are few reports on the inhibitory effects of HYP-mediated PDT on the metastatic ability of CRC cells. Here, we evaluate the inhibitory effects of HYP-mediated PDT against metastatic CRC cells and define its underlying mechanisms. Wound-healing and Transwell assays show that HYP-mediated PDT suppresses migration and invasion of CRC cells. F-actin visualization assays indicate HYP-mediated PDT decreases F-actin formation in CRC cells. TEM assays reveal HYP-mediated PDT disrupts pseudopodia formation of CRC cells. Mechanistically, immunofluorescence and western blotting results show that HYP-mediated PDT upregulates E-cadherin and downregulates N-cadherin and Vimentin. HYP-mediated PDT also suppresses key EMT regulators, including Snail, MMP9, ZEB1 and α-SMA. Additionally, the expressions of RhoA and ROCK1 are downregulated by HYP-mediated PDT. Together, these findings suggest that HYP-mediated PDT inhibits the migration and invasion of HCT116 and SW620 cells by modulating EMT and RhoA-ROCK1 signaling pathway. Thus, HYP-mediated PDT presents a potential therapeutic option for CRC.

Safe Trajectory Planning for Incremental Robots Based on a Spatiotemporal Variable-Step-Size A* Algorithm.

In this paper, a planning method based on the spatiotemporal variable-step-size A* algorithm is proposed to address the problem of safe trajectory planning for incremental, wheeled, mobile robots in complex motion scenarios with multiple robots. After constructing the known conditions, the spatiotemporal variable-step-size A* algorithm is first used to perform a collision-avoiding initial spatiotemporal trajectory search, and a variable time step is utilized to ensure that the robot completes the search at the target speed. Subsequently, the trajectory is instantiated using B-spline curves in a numerical optimization considering constraints to generate the final smooth trajectory. The results of simulation tests in a field-shaped, complex, dynamic scenario show that the proposed trajectory planning method is more applicable, and the results indicate higher efficiency compared to the traditional method in the incremental robot trajectory planning problem.

Manganese-enriched prussian blue nanohybrids with smaller electrode potential and lower charge transfer resistance to enhance combination therapy.

Prussian blue (PB) is authenticated in clinical treatment, while it generally exhibits unfavorable chemodynamic therapy (CDT) performance. Herein, we developed manganese-doped prussian blue (PBM) nanoparticles to significantly enhance both CDT and photothermal therapy (PTT) effect. The lower redox potential of Mn3+/2+ (0.088 V) in PBM against that of Fe2+/3+ (0.192 V) in PB leads to favorable electron transfer of PBM with respect to PB. Besides, PBM has a lower charge-transfer resistance (Rct) of 2.98 Ω than 4.83 Ω of PB. Once PBM entering the tumor microenvironment (TME), Mn3+ may be readily reduced by glutathione (GSH) and therein to enhance intracellular oxidative stress. Meanwhile, the superoxide dismutase (SOD)-like activity of PBM facilitates the conversion of endogenous superoxide (O2•-) into H2O2. Mn2+ subsequently catalyzes H2O2 to generate toxic hydroxyl radicals (•OH). Notably, the PBM plus laser irradiation can effectively trigger a robust immunogenic cell death (ICD) due to the combination therapy of CDT and PTT. Additionally, the mice treated by PBM followed by laser irradiation efficiently avoided splenomegaly and lung metastasis, along with significant up-regulation of the Stimulator of Interferon Genes (STING) expression. Overall, PBM significantly inhibits tumor growth and metastasis, making it a promising multifunctional nanoplatform for cancer treatment.

Identification of key genes and immune infiltration in peripheral blood biomarker analysis of delayed cerebral ischemia: Valproic acid as a potential therapeutic drug.

BACKGROUND: Delayed cerebral ischemia (DCI) is a common and serious complication of subarachnoid hemorrhage (SAH). Its pathogenesis is not fully understood. Here, we developed a predictive model based on peripheral blood biomarkers and validated the model using several bioinformatic multi-analysis methods. METHODS: Six datasets were obtained from the GEO database. Characteristic genes were screened using weighted correlation network analysis (WGCNA) and differentially expressed genes. Three machine learning algorithms, elastic networks-LASSO, support vector machines (SVM-RFE) and random forests (RF), were also used to construct diagnostic prediction models for key genes. To further evaluate the performance and predictive value of the diagnostic models, nomogram model were constructed, and the clinical value of the models was assessed using Decision Curve Analysis (DCA), Area Under the Check Curve (AUC), Clinical Impact Curve (CIC), and validated in the mouse single-cell RNA-seq dataset. Mendelian randomization(MR) analysis explored the causal relationship between SAH and stroke, and the intermediate influencing factors. We validated this by retrospectively analyzing the qPCR levels of the most relevant genes in SAH and SAH-DCI patients. This experiment demonstrated a statistically significant difference between SAH and SAH-DCI and normal group controls. Finally, potential small molecule compounds interacting with the selected features were screened from the Comparative Toxicogenomics Database (CTD). RESULTS: The fGSEA results showed that activation of Toll-like receptor signaling and leukocyte transendothelial cell migration pathways were positively correlated with the DCI phenotype, whereas cytokine signaling pathways and natural killer cell-mediated cytotoxicity were negatively correlated. Consensus feature selection of DEG genes using WGCNA and three machine learning algorithms resulted in the identification of six genes (SPOCK2, TRRAP, CIB1, BCL11B, PDZD8 and LAT), which were used to predict DCI diagnosis with high accuracy. Three external datasets and the mouse single-cell dataset showed high accuracy of the diagnostic model, in addition to high performance and predictive value of the diagnostic model in DCA and CIC. MR analysis looked at stroke after SAH independent of SAH, but associated with multiple intermediate factors including Hypertensive diseases, Total triglycerides levels in medium HDL and Platelet count. qPCR confirmed that significant differences in DCI signature genes were observed between the SAH and SAH-DCI groups. Finally, valproic acid became a potential therapeutic agent for DCI based on the results of target prediction and molecular docking of the characterized genes. CONCLUSION: This diagnostic model can identify SAH patients at high risk for DCI and may provide potential mechanisms and therapeutic targets for DCI. Valproic acid may be an important future drug for the treatment of DCI.

Causal role of immune cells in major depressive disorder and bipolar disorder: Mendelian randomization (MR) study.

BACKGROUND: Major depressive disorder (MDD) and bipolar disorder (BD) are prevalent psychiatric conditions linked to inflammatory processes. However, it is unclear whether associations of immune cells with these disorders are likely to be causal. METHODS: We used two-sample Mendelian randomization (MR) approach to investigate the relationship between 731 immune cells and the risk of MDD and BD. Rigorous sensitivity analyses are conducted to assess the reliability, heterogeneity, and horizontal pleiotropy of the findings. RESULTS: Genetically-predicted CD27 on IgD+ CD38- unswitched memory B cell (inverse variance weighting (IVW): odds ratio (OR) [95 %]: 1.017 [1.007 to 1.027], p = 0.001), CD27 on IgD+ CD24+ B cell (IVW: OR [95 %]: 1.021 [1.011 to 1.031], p = 4.821E-05) and other 12 immune cells were associated with increased risk of MDD in MR, while HLA DR++ monocyte %leukocyte (IVW: OR [95 %]: 0.973 [0.948 to 0.998], p = 0.038), CD4 on Central Memory CD4+ T cell (IVW: OR [95 %]: 0.979 [0.963 to 0.995], p = 0.011) and other 13 immune cells were associated with decreased risk of MDD in MR. Additionally, CD33+ HLA DR+ Absolute Count (IVW: OR [95 %]: 1.022[1.007 to 1.036], p = 0.007), CD28+ CD45RA- CD8+ T cell %T cell (IVW: OR [95 %]: 1.024 [1.008 to 1.041], p = 0.004) and other 18 immune cells were associated with increased risk of BD in MR, while CD62L on CD62L+ myeloid Dendritic Cell (IVW: OR [95 %]: 0.926 [0.871 to 0.985], p = 0.014), IgD- CD27- B cell %lymphocyte (IVW: OR [95 %]: 0.918 [0.880 to 0.956], p = 4.654E-05) and other 13 immune cells were associated with decreased risk of BD in MR. CONCLUSIONS: This MR study provides robust evidence supporting a causal relationship between immune cells and the susceptibility to MDD and BD, offering valuable insights for future clinical investigations. Experimental studies are also required to further examine causality, mechanisms, and treatment potential for these immune cells for MDD and BD.

Structure, function, and research progress of primary cilia in reproductive physiology and reproductive diseases.

Primary cilia, serving as the central hub for cellular signal transduction, possess the remarkable ability to translate diverse extracellular signals, both chemical and mechanical, into intracellular responses. Their ubiquitous presence in the reproductive system underscores their pivotal roles in various cellular processes including development, differentiation, and migration. Emerging evidence suggests primary cilia as key players in reproductive physiology and associated pathologies. Notably, primary cilia have been identified in granulosa cells within mouse ovaries and uterine stromal cells, and perturbations in their structure and function have been implicated in a spectrum of reproductive dysfunctions and ciliary-related diseases. Furthermore, disruptions in primary cilia-mediated signal transduction pathways under pathological conditions exacerbate the onset and progression of reproductive disorders. This review provides a comprehensive overview of current research progress on primary cilia and their associated signaling pathways in reproductive physiology and diseases, with the aim of furnishing theoretical groundwork for the prevention and management of primary cilia-related structural and functional abnormalities contributing to reproductive system pathologies.

Investigating inhibiting factors affecting seed germination index in kitchen waste compost products: Soluble carbon, nitrogen, and salt insights.

The seed germination index (GI) serves as the principal determinant that impedes the integration of aerobic composting products into agricultural lands. The current research work predominantly focuses on exploring the correlation between physical and chemical indicators of the compost products and GI, neglecting the fundamental cause. This study systematically analyzed the composition of GI aqueous extracts from compost products derived from kitchen waste under various composting methodologies, with nitrogen, carbon, and inorganic salt as critical factors. The analytical work concluded that acetic acid, formic acid, and ammonium were the inhibitory factors influencing GI. Validation experiments introduced inhibitory factors, yielding a functional relationship formula depicting GI variations due to a single influential factor. This study conclusively identified acetic acid as the primary constraint, establishing that its inhibitory concentration corresponded to 70 % GI stands at 85 mg/L. This study will provide guidelines for the future research on enhancing aerobic composting techniques.

Hepatic-derived BMP9 is involved in hepatic fibrosis-induced kidney injury through inhibition of renal VEGFA.

Clinical observations suggest that acute kidney injury (AKI) occurs in approximately 20-50% of hospitalized cirrhotic patients, suggesting a link between the liver and kidney. Bone morphogenetic protein 9 (BMP9) is a protein produced primarily by the liver and can act on other tissues at circulating systemic levels. Previous studies have demonstrated that controlling abnormally elevated BMP9 in acute liver injury attenuates liver injury; however, reports on whether BMP9 plays a role in liver injury-induced AKI are lacking. By testing we found that liver injury in mice after bile duct ligation (BDL) was accompanied by a significant upregulation of the kidney injury marker kidney injury molecule (KIM-1). Interestingly, all these impairments were alleviated in the kidneys of hepatic BMP9 knockout (BMP9-KO) mice. Peritubular capillary injury is a key process leading to the progression of AKI, and previous studies have demonstrated that vascular endothelial growth factor A (VEGFA) plays a key role in maintaining the renal microvascular system. In animal experiments, we found that high levels of circulating BMP9 had an inhibitory effect on VEGFA expression, while renal tubular epithelial cell injury was effectively attenuated by VEGFA supplementation in the hypoxia-enriched-oxygen (H/R) constructs of the AKI cell model in both humans and mice. Overall, we found that elevated BMP9 in hepatic fibrosis can affect renal homeostasis by regulating VEGFA expression. Therefore, we believe that targeting BMP9 therapy may be a potential means to address the problem of clinical liver fibrosis combined with AKI.

Intra-bone marrow mesenchymal stem cell transplantation modulates myeloid bias tendency of hematopoietic stem and progenitor cells in severe MRL/lpr lupus mice.

The hematopoietic homeostasis in the bone marrow is inextricably intertwined with the immune milieu in peripheral circulation. Researches investigating the pathogenesis of systemic lupus erythematosus (SLE) have defined considerable secretion of inflammatory mediators and activation of pro-inflammatory cells. However, the impacts of "extrinsic" factors on hematopoietic stem and progenitor cells (HSPCs) remain unclear, and it is uncertain whether treatments can help coordinate the biased differentiation. In this study, we showed differences in the proportions of common myeloid progenitors (CMP) and myeloid output in the bone marrow of premorbid and morbid MRL/lpr mice using flow cytometry. RNA-seq analysis of lineage-affiliated transcriptional factors and dysregulated genes within lin- HSPCs revealed inflammation potentiation during disease progression. Further, intra-bone marrow mesenchymal stem cells transplantation (IBM-MSCT) partially coordinated myeloid generation and counteracted lupus-associated inflammation gene alterations, compared to intravenous injection. Additionally, co-culturing with umbilical cord mesenchymal stem cells (UC-MSCs) intervened in myeloid lineage tendency, as detected by RT-qPCR of myeloid-related genes. Our research demonstrated enhanced tendency toward myeloid differentiation and highlighted the feasibility of IBM-MSCT for lineage-biased HSPCs in MRL/lpr lupus model, providing novel insight into hematopoiesis and MSC-related treatments for SLE.

Exercise interventions for frail older adults with diabetes: A scoping review.

There is a paucity of evidence on exercise interventions for frail older adults with diabetes. This scoping review aims to identify the scope of the current literature on the characteristics and effects of exercise interventions for frail older adults with diabetes. A search without time limitation was conducted in eight databases. 14 studies were finally included. Resistance exercise and multicomponent exercise were the most common types of exercise. There was considerable variation in the frequency, duration and intensity of exercise interventions. Studies reported improvements in frailty status, physical function, blood glucose and lipid levels and economic effectiveness. The most frequent combined interventions involved nutrition and education. Although evidence was limited, the potential benefits of exercise interventions for frail older adults with diabetes were substantial. Further high-quality studies are needed to explore the most effective and cost-saving exercise interventions for frail older adults with diabetes.

Soil organic matter and total nitrogen as key driving factors promoting the assessment of acid-base buffering characteristics in a tea (Camellia sinensis) plantation habitat.

The issue of soil acidification in tea plantations has become a critical concern due to its potential impact on tea quality and plant health. Understanding the factors contributing to soil acidification is essential for implementing effective soil management strategies in tea-growing regions. In this study, a field study was conducted to investigate the effects of tea plantations on soil acidification and the associated acid-base buffering capacity (pHBC). We assessed acidification, pHBC, nutrient concentrations, and cation contents in the top 0-20 cm layer of soil across forty tea gardens of varying stand ages (0-5, 5-10, 10-20, and 20-40 years old) in Anji County, Zhejiang Province, China. The results revealed evident soil acidification due to tea plantation activities, with the lowest soil pH observed in tea gardens aged 10-20 and 20-40 years. Higher levels of soil organic matter (SOM), total nitrogen (TN), Olsen phosphorus (Olsen-P), available iron (Fe), and exchangeable hydrogen (H+) were notably recorded in 10-20 and 20-40 years old tea garden soils, suggesting an increased risk of soil acidification with prolonged tea cultivation. Furthermore, prolonged tea cultivation correlated with increased pHBC, which amplified with tea stand ages. The investigation of the relationship between soil pHBC and various parameters highlighted significant influences from soil pH, SOM, cation exchange capacity, TN, available potassium, Olsen-P, exchangeable acids (including H+ and aluminum), available Fe, and available zinc. Consequently, these findings underscore a substantial risk of soil acidification in tea gardens within the monitored region, with SOM and TN content being key driving factors influencing pHBC.

Cynaroside ameliorates methotrexate-induced enteritis in rats through inhibiting NLRP3 inflammasome activation.

Introduction: Cynaroside exhibits various biological properties, including anti-inflammatory, antiviral, antitumor, and cardioprotective effects. However, its involvement in methotrexate (MTX)-induced intestinal inflammation remains inadequately understood. Thus, we investigated the impact of cynaroside on MTX-induced intestinal inflammation and its potential mechanisms. Methods: To assess the protective potential of cynaroside against intestinal inflammation, Sprague-Dawley rats were subjected to a regimen of 7 mg/kg MTX for 3 days, followed by treatment with cynaroside at varying doses (10, 20, or 40 mg/kg). Histopathological evaluations were conducted alongside measurements of inflammatory mediators to elucidate the involvement of the NLRP3 inflammasome in alleviating intestinal inflammation. Results: Administration of 7 mg/kg MTX resulted in decreased daily food intake, increased weight loss, and elevated disease activity index in rats. Conversely, treatment with cynaroside at 20 or 40 mg/kg ameliorated the reductions in body weight and daily food intake and suppressed the MTX-induced elevation in the disease activity index. Notably, cynaroside administration at 20 or 40 mg/kg attenuated inflammatory cell infiltration, augmented goblet cell numbers and lowered serum levels of tumor necrosis factor-α, interleukin (IL)-1ß, and IL-18, as well as the CD68-positive cell rate in the intestines of MTX-induced rats. Furthermore, cynaroside downregulated the expression levels of NLRP3, cleaved caspase 1, and cleaved IL-1ß in MTX-induced rats. Discussion: Collectively, our findings indicated that cymaroside alleviates intestinal inflammatory injury by inhibiting the activation of NLRP3 inflammasome in MTX-induced rats.

Pseudo-Siamese network combined with label-free Raman spectroscopy for the quantification of mixed trace amounts of antibiotics in human milk: A feasibility study.

The utilization of antibiotics is prevalent among lactating mothers. Hence, the rapid determination of trace amounts of antibiotics in human milk is crucial for ensuring the healthy development of infants. In this study, we constructed a human milk system containing residual doxycycline (DXC) and/or tetracycline (TC). Machine learning models and clustering algorithms were applied to classify and predict deficient concentrations of single and mixed antibiotics via label-free SERS spectra. The experimental results demonstrate that the CNN model has a recognition accuracy of 98.85% across optimal hyperparameter combinations. Furthermore, we employed Independent Component Analysis (ICA) and the pseudo-Siamese Convolutional Neural Network (pSCNN) to quantify the ratios of individual antibiotics in mixed human milk samples. Integrating the SERS technique with machine learning algorithms shows significant potential for rapid discrimination and precise quantification of single and mixed antibiotics at deficient concentrations in human milk.

Intervention of computer-assisted cognitive training combined with occupational therapy in people with mild cognitive impairment: a randomized controlled trial.

Objective: Investigate the impact of combined computerized cognitive training and occupational therapy on individuals with mild cognitive impairment (MCI). Methods: We randomly assigned 118 MCI patients into two groups: a combined intervention group (n = 37) and a control group (n = 81), the latter receiving standard nursing care. The intervention group additionally underwent 12 weeks of computerized cognitive training and occupational therapy. Blind assessors evaluated cognitive performance, anxiety, depression, and daily living activities before the intervention, post-intervention, and at a 3-month follow-up. Results: Repeated-measures analysis of variance showed that the sMoCA scores, HAMA scores, and ADL scores of the experimental group at T2 (post-intervention) and T3 (3-month follow-up) were higher than those of the control group, and the difference was statistically significant (p < 0.001, p < 0.001, p = 0.026). Conclusion: Computerized cognitive training combined with occupational therapy can improve patients' cognitive status, enhance their compliance with continuing care, and maintain their anxiety and self-care ability at a stable level. Clinical trial registration: https://www.chictr.org.cn/index.html, identifier ChiCTR2200065014.

Prediction of drug-target binding affinity based on multi-scale feature fusion.

Accurate prediction of drug-target binding affinity (DTA) plays a pivotal role in drug discovery and repositioning. Although deep learning methods are widely used in DTA prediction, two significant challenges persist: (i) how to effectively represent the complex structural information of proteins and drugs; (ii) how to precisely model the mutual interactions between protein binding sites and key drug substructures. To address these challenges, we propose a MSFFDTA (Multi-scale feature fusion for predicting drug target affinity) model, in which multi-scale encoders effectively capture multi-level structural information of drugs and proteins are designed. And then a Selective Cross Attention (SCA) mechanism is developed to filter out the trivial interactions between drug-protein substructure pairs and retain the important ones, which will make the proposed model better focusing on these key interactions and offering insights into their underlying mechanism. Experimental results on two benchmark datasets demonstrate that MSFFDTA is superior to several state-of-the-art methods across almost all comparison metrics. Finally, we provide the ablation and case studies with visualizations to verify the effectiveness and the interpretability of MSFFDTA. The source code is freely available at https://github.com/whitehat32/MSFF-DTA/.

Identification of diabetic retinopathy classification using machine learning algorithms on clinical data and optical coherence tomography angiography.

BACKGROUND: To apply machine learning (ML) algorithms to perform multiclass diabetic retinopathy (DR) classification using both clinical data and optical coherence tomography angiography (OCTA). METHODS: In this cross-sectional observational study, clinical data and OCTA parameters from 203 diabetic patients (203 eye) were used to establish the ML models, and those from 169 diabetic patients (169 eye) were used for independent external validation. The random forest, gradient boosting machine (GBM), deep learning and logistic regression algorithms were used to identify the presence of DR, referable DR (RDR) and vision-threatening DR (VTDR). Four different variable patterns based on clinical data and OCTA variables were examined. The algorithms' performance were evaluated using receiver operating characteristic curves and the area under the curve (AUC) was used to assess predictive accuracy. RESULTS: The random forest algorithm on OCTA+clinical data-based variables and OCTA+non-laboratory factor-based variables provided the higher AUC values for DR, RDR and VTDR. The GBM algorithm produced similar results, albeit with slightly lower AUC values. Leading predictors of DR status included vessel density, retinal thickness and GCC thickness, as well as the body mass index, waist-to-hip ratio and glucose-lowering treatment. CONCLUSIONS: ML-based multiclass DR classification using OCTA and clinical data can provide reliable assistance for screening, referral, and management DR populations.

General anesthetic agents induce neurotoxicity through oligodendrocytes in the developing brain.

General anesthetic agents can impact brain function through interactions with neurons and their effects on glial cells. Oligodendrocytes perform essential roles in the central nervous system, including myelin sheath formation, axonal metabolism, and neuroplasticity regulation. They are particularly vulnerable to the effects of general anesthetic agents resulting in impaired proliferation, differentiation, and apoptosis. Neurologists are increasingly interested in the effects of general anesthetic agents on oligodendrocytes. These agents not only act on the surface receptors of oligodendrocytes to elicit neuroinflammation through modulation of signaling pathways, but also disrupt metabolic processes and alter the expression of genes involved in oligodendrocyte development and function. In this review, we summarize the effects of general anesthetic agents on oligodendrocytes. We anticipate that future research will continue to explore these effects and develop strategies to decrease the incidence of adverse reactions associated with the use of general anesthetic agents.

AntDAS-GCMS: A New Comprehensive Data Analysis Platform for GC-MS-Based Untargeted Metabolomics with the Advantage of Addressing the Time Shift Problem.

Over the years, a number of state-of-the-art data analysis tools have been developed to provide a comprehensive analysis of data collected from gas chromatography-mass spectrometry (GC-MS). Unfortunately, the time shift problem remains unsolved in these tools. Here, we developed a novel comprehensive data analysis strategy for GC-MS-based untargeted metabolomics (AntDAS-GCMS) to perform total ion chromatogram peak detection, peak resolution, time shift correction, component registration, statistical analysis, and compound identification. Time shift correction was specifically optimized in this work. The information on mass spectra and elution profiles of compounds was used to search for inherent landmarks within analyzed samples to resolve the time shift problem across samples efficiently and accurately. The performance of our AntDAS-GCMS was comprehensively investigated by using four complex GC-MS data sets with various types of time shift problems. Meanwhile, AntDAS-GCMS was compared with advanced GC-MS data analysis tools and classic time shift correction methods. Results indicated that AntDAS-GCMS could achieve the best performance compared to the other methods.

Characterization of ovarian progenitor cells for their potential to generate steroidogenic theca cells in vitro.

In brief: Progenitor cells with ovulation-related tissue repair activity were identified with defined markers (LGR5, EPCR, LY6A, and PDGFRA), but their potentials to form steroidogenic cells were not known. This study shows that the cells can generate progenies with different steroidogenic activities. Abstract: Adult mammalian ovaries contain stem/progenitor cells necessary for folliculogenesis and ovulation-related tissue rupture repair. Theca cells are recruited and developed from progenitors during the folliculogenesis. Theca cell progenitors were not well defined. The aim of current study is to compare the potentials of four ovarian progenitors with defined markers (LY6A, EPCR, LGR5, and PDGFRA) to form steroidogenic theca cells in vitro. The location of the progenitors with defined makers was determined by immunohistochemistry and immunofluorescence staining of ovarian sections of adult mice. Different progenitor populations were purified by magnetic-activated cell sorting (MACS) and/or fluorescence-activated cell sorting (FACS) techniques from ovarian cell preparation and were tested for their abilities to generate steroidogenic theca cells in vitro. The cells were differentiated with a medium containing LH, ITS, and DHH agonist for 12 days. The results showed that EPCR+ and LGR5+ cells primarily distributed along the ovarian surface epithelium (OSE), while LY6A+ cells distributed in both the OSE and parenchyma. However, PDGFRA+ cells were exclusively located in interstitial compartment. When the progenitors were purified by these markers and differentiated in vitro, LY6A+ and PDGFRA+ cells formed steroidogenic cells expressing both CYP11A1 and CYP17A1 and primarily producing androgens, showing characteristics of theca-like cells, while LGR5+ cells generated steroidogenic cells devoid of CYP17A1 expression and androgen production, showing a characteristic of progesterone-producing cells (granulosa- or lutea-like cells). In conclusion, progenitors from both OSE and parenchyma of adult mice are capable of generating steroidogenic cells with different steroidogenic capacities, showing a possible lineage preference.