Synbiotic regulates gut microbiota in patients with lupus nephritis: an analysis using metagenomic and metabolome sequencing

ObjectiveTo investigate the changes in gut microbes and their metabolites after administering synbiotics to patients with new-onset lupus nephritis (LN) treated using a conventional method and provide a theoretical basis for finding new targets for the diagnosis and treatment of LN.MethodsIn this study, a total of 12 participants were divided into the lupus and synbiotic groups. Stool samples and clinical data were collected before and after treatment for metagenomic, nontargeted metabolomic, and statistical analyses.ResultsThe relative abundances of the pathogenic bacteria Prevotella, Bacteroides, and Enterobacteriaceae_unclassified decreased after synbiotic treatment, whereas the abundances of Actinobacteria and Firmicutes increased. Further, the Firmicutes to Bacteroidetes ratio increased; however, the difference was not statistically significant (p > 0.05). α diversity analysis showed no significant differences in the intestinal microbial richness and diversity index of patients with LN between the groups before and after treatment (p > 0.05). β analysis showed the differences in the community structure between the samples of the two groups before and after treatment. Linear discriminant analysis effect size and receiver operating characteristic curve analyses revealed that Negativicutes (AUC = 0.9722) and Enterobacteriaceae_unclassified (AUC = 0.9722) were the best predictors of the lupus and synbiotic groups, respectively, before and after treatment. Joint analyses revealed that amino acid biosynthesis, aminoacyl-tRNA biosynthesis, purine metabolism, and other metabolic pathways may be involved in the changes in the metabolic function of patients with LN after the addition of synbiotics. Spearman’s correlation analysis revealed the interaction between clinical features and flora, and flora exhibited a complex biological network regulatory relationship.ConclusionSynbiotics regulate the metabolic functions of intestinal microorganisms in patients with LN and play a role in various biological functions. Synbiotic supplements may be safe and promising candidates for patients with LN

Extra-large Gα protein (XLαs) deficiency causes severe adenine-induced renal injury with massive FGF23 elevation

Fibroblast growth factor-23 (FGF23) is critical for phosphate and vitamin D homeostasis. Cellular and molecular mechanisms underlying FGF23 production remain poorly defined. The extra-large Gα subunit (XLαs) is a variant of the stimulatory G protein alpha-subunit (Gsα), which mediates the stimulatory action of parathyroid hormone in skeletal FGF23 production. XLαs ablation causes diminished FGF23 levels in early postnatal mice. Herein we found that plasma FGF23 levels were comparable in adult XLαs knockout (XLKO) and wild-type littermates. Upon adenine-rich diet-induced renal injury, a model of chronic kidney disease, both mice showed increased levels of plasma FGF23. Unexpectedly, XLKO mice had markedly higher FGF23 levels than WT mice, with higher blood urea nitrogen and more severe tubulopathy. FGF23 mRNA levels increased substantially in bone and bone marrow in both genotypes; however, the levels in bone were markedly higher than in bone marrow. In XLKO mice, a positive linear correlation was observed between plasma FGF23 and bone, but not bone marrow, FGF23 mRNA levels, suggesting that bone, rather than bone marrow, is an important contributor to severely elevated FGF23 levels in this model. Upon folic acid injection, a model of acute kidney injury, XLKO and WT mice exhibited similar degrees of tubulopathy; however, plasma phosphate and FGF23 elevations were modestly blunted in XLKO males, but not in females, compared to WT counterparts. Our findings suggest that XLαs ablation does not substantially alter FGF23 production in adult mice but increases susceptibility to adenine-induced kidney injury, causing severe FGF23 elevations in plasma and bone

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Dendritic cell vaccines in breast cancer: Immune modulation and immunotherapy

Breast cancer (BC) is the most common cancer in women worldwide. Although substantial progress has been made in the diagnosis and treatment of breast cancer, the efficacy and side effects of traditional treatment methods are still unsatisfactory. In recent years, immunotherapy including tumor vaccine has achieved great success in the treatment of BC. Dendritic cells (DCs) are multifunctional antigen-presenting cells that play an important role in the initiation and regulation of innate and adaptive immune responses. Numerous studies have shown that DC-based treatments might have a potential effect on BC. Among them, the clinical study of DC vaccine in BC has demonstrated considerable anti-tumor effect, and some DC vaccines have entered the stage of clinical trials. In this review, we summarize the immunomodulatory effects and related mechanisms of DC vaccine in breast cancer as well as the progress of clinical trials to propose possible challenges of DC vaccines and new development directions

Prognostic Genes of Breast Cancer Identified by Gene Co-expression Network Analysis

Breast cancer is one of the most common malignancies. The molecular mechanisms of its pathogenesis are still to be investigated. The aim of this study was to identify the potential genes associated with the progression of breast cancer. Weighted gene co-expression network analysis (WGCNA) was used to construct free-scale gene co-expression networks to explore the associations between gene sets and clinical features, and to identify candidate biomarkers. The gene expression profiles of GSE1561 were selected from the Gene Expression Omnibus (GEO) database. RNA-seq data and clinical information of breast cancer from TCGA were used for validation. A total of 18 modules were identified via the average linkage hierarchical clustering. In the significant module (R2 = 0.48), 42 network hub genes were identified. Based on the Cancer Genome Atlas (TCGA) data, 5 hub genes (CCNB2, FBXO5, KIF4A, MCM10, and TPX2) were correlated with poor prognosis. Receiver operating characteristic (ROC) curve validated that the mRNA levels of these 5 genes exhibited excellent diagnostic efficiency for normal and tumor tissues. In addition, the protein levels of these 5 genes were also significantly higher in tumor tissues compared with normal tissues. Among them, CCNB2, KIF4A, and TPX2 were further upregulated in advanced tumor stage. In conclusion, 5 candidate biomarkers were identified for further basic and clinical research on breast cancer with co-expression network analysis

OK-432 (Sapylin) Reduces Seroma Formation After Axillary Lymphadenectomy in Breast Cancer

Purpose/aim: Modified radical mastectomy is the standard surgery for breast cancer in developing countries. However, seroma formation regarded as the most frequent postoperative complication limits the therapeutic benefit of mastectomy and axillary surgery. The purpose of this study was to evaluate the efficacy of OK-432 in reducing seroma formation after axillary dissection. Methods: This prospective cohort study included 80 patients with advanced breast cancer who underwent modified radical mastectomy. Patients were randomized into two groups, which differed with the OK-432 administration. N = 40 patients per group were treated with either OK-432 plus closed suction drainage or drainage-only. Result: In comparison with the drainage-only group, we found that patients in the OK-432 group had a lower drainage volume (p = .030) and a shorter duration of axillary drainage (p < .01). Besides, the use of OK-432 could reduce the incidence of seroma formation (p < .01) and the volume of seroma (p = .040). There were also significant differences in reducing the chance of evacuative punctures (p = .036) and the healing time (p < .01) between control and OK-432 group. Conclusion: OK-432 not only shortened the suction drainage duration, but also significantly reduced seroma formation as well as the needs for aspiration punctures after modified radical mastectomy

Integration of Profile Control and Thermal Recovery to Enhance Heavy Oil Recovery

The proven reserves of heavy oil in the Bohai oilfield exceed 600 million tons. Heavy oil is highly viscous, temperature sensitive, and suitable for thermal extraction, but due to the strong inhomogeneity of the reservoir, the recovery rate of pure thermal extraction development is low, and there is an urgent need to conduct research on profile control + thermal extraction to guide the actual production. In this paper, we propose an integrated technology of profile control and thermal recovery to enhance heavy oil recovery. The heavy oil exhibited strong temperature dependence and nonlinear flow characteristics. An inorganic gel was selected for profile control to assist thermal recovery. Thermal recovery experiments were conducted in the laboratory using cores saturated by crude oil with different viscosities to simulate the oil in areas swept by thermal fluid. The 4% to 6% inorganic gel can seal up to 99% on 2000 × 10−3 μm2 cores. As the thermal recovery temperature increased from 55 to 200 °C, the efficiency of oil recovery increased from 10.8% to 42.9% in experiments with three-layer heterogeneous cores; it increased by 8.9–13.2% when profile control was implemented using the inorganic gel with a concentration of 4%. The injection parameters for thermal recovery were optimized with a thermal fluid swept area of 3/10 times the injector–producer distance, including three slugs of crude oil with different viscosities. According to the experiments involving an inverted nine-point well pattern, the integrated technology of profile control and thermal recovery enhances oil recovery by 1.4% compared to of profile control or thermal recovery alone

Bioinformatic analysis and identification of potential prognostic microRNAs and mRNAs in thyroid cancer

Thyroid cancer is one of the most common endocrine malignancies. Multiple evidences revealed that a large number of microRNAs and mRNAs were abnormally expressed in thyroid cancer tissues. These microRNAs and mRNAs play important roles in tumorigenesis. In the present study, we identified 72 microRNAs and 1,766 mRNAs differentially expressed between thyroid cancer tissues and normal thyroid tissues and evaluated their prognostic values using Kaplan-Meier survival curves by log-rank test. Seven microRNAs (miR-146b, miR-184, miR-767, miR-6730, miR-6860, miR-196a-2 and miR-509-3) were associated with the overall survival. Among them, three microRNAs were linked with six differentially expressed mRNAs (miR-767 was predicted to target COL10A1, PLAG1 and PPP1R1C; miR-146b was predicted to target MMP16; miR-196a-2 was predicted to target SYT9). To identify the key genes in the protein-protein interaction network , we screened out the top 10 hub genes (NPY, NMU, KNG1, LPAR5, CCR3, SST, PPY, GABBR2, ADCY8 and SAA1) with higher degrees. Only LPAR5 was associated with the overall survival. Multivariate analysis demonstrated that miR-184, miR-146b, miR-509-3 and LPAR5 were an independent risk factors for prognosis. Our results of the present study identified a series of prognostic microRNAs and mRNAs that have the potential to be the targets for treatment of thyroid cancer

Immunoenhancement activity of Bletilla striata polysaccharide through MAPK and NF-κB signalling pathways in vivo and in vitro

Bletilla striata (Thunb.) Reichb.f., is a traditional Chinese medicine, and the Bletilla striata polysaccharide (BSP) is one of the principal components extracted from Bletilla striata with various biological activities. Previous studies have shown that many natural polysaccharides have significant immunomodulatory activities. However, as a plant polysaccharide, the research of BSP on immunomodulatory activities is limited. In this study, we aim to investigate the immunomodulatory effect of BSP in vivo and further explore its underlying mechanism in vitro. In vivo, a cyclophosphamide (CTX)-induced immunosuppression mice mode was established by intraperitoneal injection of CTX, and the immune-enhancing effect of BSP (25, 50 and 100 mg/kg) on immunosuppressed mice were evaluated. The result indicated that BSP could significantly improve the immune organ index and the content of immunoglobulin, TNF-α and IL-4 in serum. It was also found that BSP could clearly ameliorate the spleen damage induced by CTX. Meanwhile, the result showed that BSP could not only improve the proliferation of splenocytes, but also activate the lactate dehydrogenase (LDH) and acid phosphatase (ACP) in mouse spleen tissue. In vitro, potential mechanism was further revealed in macrophages. The result supported that BSP could activate macrophages with high phagocytic ability, and induce macrophages to secrete cytokines. Finally, it revealed that activation of NF-κB and MAPK signalling pathway should be the underlying mechanism of the immunoenhancment of BSP