Advances in the mechanism of CDK4/6 inhibitor resistance in HR+/HER2- breast cancer.

Among women, breast cancer is the most prevalent form of a malignant tumour. Among the subtypes of breast cancer, hormone receptor (HR) positive and human epidermal growth factor receptor (HER2) negative kinds make up the biggest proportion. The advent of cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors, which are dependent on cell cycle proteins, has greatly enhanced the prognosis of patients with advanced HR+/HER2- breast cancer. This is a specific treatment that stops the growth of cancer cells by preventing them from dividing. Nevertheless, the drug resistance of the disease unavoidably impacts the effectiveness of treatment and the prognosis of patients. This report provides a thorough analysis of the current research advancements about the resistance mechanism of CDK4/6 inhibitors in HR+/HER2- breast cancer. It presents an in-depth discussion from numerous viewpoints, such as aberrant cell cycle regulation and changes in signalling pathways. In response to the drug resistance problem, subsequent treatment strategies are also being explored, including switching to other CDK4/6 inhibitor drugs, a combination of novel endocrine therapeutic agents, an optimal combination of targeted therapies and switching to chemotherapy. An in-depth study of the resistance mechanism can assist in identifying creative tactics that can overcome or postpone drug resistance, alleviate the problem of restricted treatment strategies following drug resistance and enhance the prognosis of patients.

Neoadjuvant toripalimab plus axitinib for clear cell renal cell carcinoma with inferior vena cava tumor thrombus: NEOTAX, a phase 2 study.

The potential benefit of neoadjuvant toripalimab plus axitinib in cases with clear cell renal cell carcinoma (ccRCC) and inferior vena cava tumor thrombus (IVC-TT) remains unclear. NEOTAX was a phase 2 study to investigate the efficacy and safety of neoadjuvant toripalimab plus axitinib in patients with ccRCC and IVC-TT (ChiCTR2000030405). The primary endpoint was the down-staging rate of IVC-TT level. Secondary endpoints included change in TT length, response rate, percentage change in surgical approach, surgical morbidity, progression-free survival (PFS), safety, and biomarker analyses. In all, 25 patients received study treatment, 44.0% (11/25) patients had a reduction in thrombus level, and none experienced an increase in Mayo level. The median change in tumor thrombus length was -2.3 cm (range: -7.1 to 1.1 cm). Overall, 61.9% (13/21) patients experienced changes in surgical strategy compared with planned surgery, three patients experienced major complications. The median PFS was 25.3 months (95% CI: 17.0-NE). The 1-year PFS was 89.1% (95% CI: 62.7-97.2). No any of grade 4 or 5 treatment-related adverse event was identified. Biopsy samples of non-responders exhibited increased T cytotoxic cell infiltration, but these cells were predominantly PD-1 positive. Biopsy samples of responders exhibited lower T helper cells, however, their subtype, regulatory T cells remained unchanged. In surgical samples of the TT, non-responders exhibited increased CD8T_01_GZMK_CXCR4 subset T cells. NEOTAX met preset endpoints proving that toripalimab in combination with axitinib downstages IVC-TT in a significant proportion of patients leading to simplification in the procedure of surgery.

Intratumoral and fecal microbiota reveals microbial markers associated with gastric carcinogenesis.

Background: The relationship between dysbiosis of the gastrointestinal microbiota and gastric cancer (GC) has been extensively studied. However, microbiota alterations in GC patients vary widely across studies, and reproducible diagnostic biomarkers for early GC are still lacking in multiple populations. Thus, this study aimed to characterize the gastrointestinal microbial communities involved in gastric carcinogenesis through a meta-analysis of multiple published and open datasets. Methods: We analyzed 16S rRNA sequencing data from 1,642 gastric biopsy samples and 394 stool samples across 11 independent studies. VSEARCH, QIIME and R packages such as vegan, phyloseq, cooccur, and random forest were used for data processing and analysis. PICRUSt software was employed to predict functions. Results: The α-diversity results indicated significant differences in the intratumoral microbiota of cancer patients compared to non-cancer patients, while no significant differences were observed in the fecal microbiota. Network analysis showed that the positive correlation with GC-enriched bacteria increased, and the positive correlation with GC-depleted bacteria decreased compared to healthy individuals. Functional analyses indicated that pathways related to carbohydrate metabolism were significantly enriched in GC, while biosynthesis of unsaturated fatty acids was diminished. Additionally, we investigated non-Helicobacter pylori (HP) commensals, which are crucial in both HP-negative and HP-positive GC. Random forest models, constructed using specific taxa associated with GC identified from the LEfSe analysis, revealed that the combination of Lactobacillus and Streptococcus included alone could effectively discriminate between GC patients and healthy individuals in fecal samples (area under the curve (AUC) = 0.7949). This finding was also validated in an independent cohort (AUC = 0.7712). Conclusions: This study examined the intratumoral and fecal microbiota of GC patients from a dual microecological perspective and identified Lactobacillus, Streptococcus, Roseburia, Faecalibacterium and Phascolarctobacterium as intratumoral and intestinal-specific co-differential bacteria. Furthermore, it confirmed the validity of the combination of Lactobacillus and Streptococcus as GC-specific microbial markers across multiple populations, which may aid in the early non-invasive diagnosis of GC.

Astrocytes in the Ventral Hippocampus Bidirectionally Regulate Innate and Stress-Induced Anxiety-Like Behaviors in Male Mice.

The mechanisms of anxiety disorders, the most common mental illness, remain incompletely characterized. The ventral hippocampus (vHPC) is critical for the expression of anxiety. However, current studies primarily focus on vHPC neurons, leaving the role for vHPC astrocytes in anxiety largely unexplored. Here, genetically encoded Ca2+ indicator GCaMP6m and in vivo fiber photometry calcium imaging are used to label vHPC astrocytes and monitor their activity, respectively, genetic and chemogenetic approaches to inhibit and activate vHPC astrocytes, respectively, patch-clamp recordings to measure glutamate currents, and behavioral assays to assess anxiety-like behaviors. It is found that vHPC astrocytic activity is increased in anxiogenic environments and by 3-d subacute restraint stress (SRS), a well-validated mouse model of anxiety disorders. Genetic inhibition of vHPC astrocytes exerts anxiolytic effects on both innate and SRS-induced anxiety-related behaviors, whereas hM3Dq-mediated chemogenetic or SRS-induced activation of vHPC astrocytes enhances anxiety-like behaviors, which are reversed by intra-vHPC application of the ionotropic glutamate N-methyl-d-aspartate receptor antagonists. Furthermore, intra-vHPC or systemic application of the N-methyl-d-aspartate receptor antagonist memantine, a U.S. FDA-approved drug for Alzheimer's disease, fully rescues SRS-induced anxiety-like behaviors. The findings highlight vHPC astrocytes as critical regulators of stress and anxiety and as potential therapeutic targets for anxiety and anxiety-related disorders.

Bacteriocins in Cancer Treatment: Mechanisms and Clinical Potentials.

Cancer poses a severe threat to human health. Although conventional chemotherapy remains a cornerstone of cancer treatment, its significant side effects and the growing issue of drug resistance necessitate the urgent search for more efficient and less toxic anticancer drugs. In recent years, bacteriocins, antimicrobial peptides of microbial origin, have garnered significant attention due to their targeted antitumor activity. This unique activity is mainly attributed to their cationic and amphiphilic nature, which enables bacteriocins to specifically kill tumor cells without harming normal cells. When involving non-membrane-disrupting mechanisms, such as apoptosis induction, cell cycle blockade, and metastasis inhibition, the core mechanism of action is achieved by disrupting cell membranes, which endows bacteriocins with low drug resistance and high selectivity. However, the susceptibility of bacteriocins to hydrolysis and hemolysis in vivo limits their clinical application. To overcome these challenges, structural optimization of bacteriocins or their combination with nanotechnology is proposed for future development. This review aims to study the mechanism of action and current research status of bacteriocins as anticancer treatments, thus providing new insights for their clinical development and application.

The vaginal microbial signatures of preterm birth woman.

To explore the differences of vaginal microbes in women with preterm birth (PTB), and to construct prediction model. We searched for articles related to vaginal microbiology in preterm women and obtained four 16S rRNA-sequence datasets. We analyzed that for species diversity and differences, and constructed a random forest model with 20 differential genera. We introduce an independent whole genome-sequencing (WGS) data for validation. In addition, we collected vaginal and cervical swabs from 33 pregnant women who delivered spontaneously full-term and preterm infants, performed WGS in our lab to further validate the model. Compared to term birth (TB) samples, PTB women vagina were characterized by a decrease in Firmicutes, Lactobacillus, and an increase in diversity accompanied by the colonization of pathogenic bacteria such as Gardnerella, Atopobium and Prevotella. Twenty genus markers, including Lactobacillus, Prevotella, Streptococcus, and Gardnerella performed well in predicting PTB, with study-to-study transfer validation and LODO validation, different gestation validation showing good results, and in two independent cohorts (external WGS cohorts and woman samples WGS cohorts) in which the accuracy was maintained. PTB women have unique vaginal microbiota characteristics. A predictive model of PTB was constructed and its value validated from multiple perspectives.

Microbial metabolites affect tumor progression, immunity and therapy prediction by reshaping the tumor microenvironment (Review).

Several studies have indicated that the gut microbiome and tumor microbiota may affect tumors. Emerging metabolomics research illustrates the need to examine the variations in microbial metabolite composition between patients with cancer and healthy individuals. Microbial metabolites can impact the progression of tumors and the immune response by influencing a number of mechanisms, including modulation of the immune system, cancer or immune­related signaling pathways, epigenetic modification of proteins and DNA damage. Microbial metabolites can also alleviate side effects and drug resistance during chemotherapy and immunotherapy, while effectively activating the immune system to exert tumor immunotherapy. Nevertheless, the impact of microbial metabolites on tumor immunity can be both beneficial and harmful, potentially influenced by the concentration of the metabolites or the specific cancer type. The present review summarizes the roles of various microbial metabolites in different solid tumors, alongside their influence on tumor immunity and treatment. Additionally, clinical trials evaluating the therapeutic effects of microbial metabolites or related microbes on patients with cancer have been listed. In summary, studying microbial metabolites, which play a crucial role in the interaction between the microbiota and tumors, could lead to the identification of new supplementary treatments for cancer. This has the potential to improve the effectiveness of cancer treatment and enhance patient prognosis.

Highly specific vaginal microbiome signature for gynecological cancers.

To investigate the vaginal microbiota signature of patients with gynecologic cancer and evaluate its diagnostic biomarker potential. We incorporated vaginal 16S rRNA-seq data from 529 women and utilized VSEARCH to analyze the raw data. α-Diversity was evaluated utilizing the Chao1, Shannon, and Simpson indices, and ß-diversity was evaluated through principal component analysis using Bray-Curtis distances. Linear discriminant analysis effect size (LEfSe) was utilized to determine species differences between groups. A bacterial co-abundance network was constructed utilizing Spearman correlation analysis. A random forest model of gynecologic tumor risk based on genus was constructed and validated to test its diagnostic efficacy. In gynecologic cancer patients, vaginal α-diversity was significantly greater than in controls, and vaginal ß-diversity was significantly separated from that of controls; there was no correlation between these characteristics and menopause status among the subject women. Women diagnosed with gynecological cancer exhibited a reduction in the abundance of vaginal Firmicutes and Lactobacillus, while an increase was observed in the proportions of Bacteroidetes, Proteobacteria, Prevotella, Streptococcus, and Anaerococcus. A random forest model constructed based on 56 genus achieved high accuracy (area under the curve = 84.96%) in gynecological cancer risk prediction. Furthermore, there were discrepancies observed in the community complexity of co-abundance networks between gynecologic cancer patients and the control group. Our study provides evidence that women with gynecologic cancer have a unique vaginal flora structure and microorganisms may be involved in the gynecologic carcinogenesis process. A gynecological cancer risk prediction model based on characteristic genera has good diagnostic value.

Specific vaginal and gut microbiome and the anti-tumor effect of butyrate in cervical cancer women.

OBJECTIVE: To investigate the vaginal and gut microbes changes during the carcinogenesis of cervical and the auxiliary diagnostic value. To investigate the effect of microbiome-specific metabolites butyric on cervical cancer cells. METHODS: We studied 416 vaginal 16S rRNA sequencing data and 116 gut sequencing data. Reads were processed using VSEARCH. We used Shannon index, Chao1 index, Simpson diversity index, ß diversity index, Linear discriminant analysis Effect Size (LEfSe), co-abundance network and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis to explore microbiome differences between groups. We constructed random forest models based on genus and verified its discriminant effect. Finally, we used the cell counting kit-8 (CCK-8) method to detect cell proliferation capacity and flow cytometry to detect apoptosis and induction of cell cycle progression. RESULTS: Compared to the non-cancerous population, patients with cervical cancer had unique microbial community characteristics in both vaginal and gut ecological niches. Our predictive model based on genus in two ecological regions achieved high accuracy in the diagnosis of cervical cancer (vaginal model AUC=91.58 %; gut model AUC=99.95 %). Butyric inhibited cervical cancer cell proliferation in a concentration-dependent manner and promoted apoptosis of cancer cells. CONCLUSION: Significant differences were found in vaginal and gut microbes in patients with cervical cancer compared to the non-cancerous population. The prediction models constructed at the genus level in both ecological sites have good diagnostic value. Microorganisms may be involved in cervical cancer progression in a metabolite-dependent way, and targeting butyric may provide therapeutic options for cervical cancer.

Prognostic value of the systemic immune-inflammation index in patients with acute respiratory distress syndrome: A retrospective study.

Background: Inflammation is critical in the etiology and progression of acute respiratory distress syndrome (ARDS). This study aims to rigorously assess the predictive capacity of systemic immune-inflammation index (SII) in determining the outcomes of patients with ARDS. Methods: Patient data were extracted from version 2.2 of the Medical Information Mart for Intensive Care IV (MIMIC-IV). The Receiver Operating Characteristic (ROC) curve was deployed to determine the optimal cutoff value for the SII, facilitating the stratification of participants into distinct cohorts based on SII levels. The relationship between SII and survival outcomes was rigorously evaluated using Cox proportional hazards models. The association between SII and patient survival was rigorously examined using Cox proportional-hazard models. The impact of varying SII levels on mortality was quantitatively assessed through these models, with the results articulated as hazard ratios (HRs) and 95% confidence intervals (CIs). Three distinct models were formulated for this analysis: Model 1 employed univariate Cox regression to relate SII with mortality; Model 2 introduced adjustments for age and sex; and Model 3 extended these adjustments to include age, sex, race, SAPS II, APSIII, Hemoglobin, Albumin, Pneumonia, SpO2, and SBP. Results: Post-application of the inclusion criteria, a cohort of 976 eligible patients was delineated for detailed examination. Univariate analysis focusing on 30-day mortality within the SII ≥1694, the hazard ratio (HR) was 1.42 (95% confidence interval (CI): 1.11, 1.81). However, after adjusting for confounding factors such as age, sex, race, Simplified Acute Physiology Score II (SAPS II), Acute Physiology Score (APS) III, Hemoglobin, Albumin, Pneumonia, SpO2, and Systolic Blood Pressure (SBP), an SII value of ≥1694 was identified as an independent and significant risk factor for mortality in patients with ARDS, with an HR of 1.38 (95% CI: 1.08-1.77, P = 0.0016). This trend was consistent for 90-day and one-year mortality rates. Conclusions: SII surfaced as an autonomous determinant of mortality in ARDS patients, affirming its status as an accessible and dependable prognostic indicator for individuals newly diagnosed with this critical condition. Additional research is imperative to further elucidate the prognostic implications of SII in the therapeutic management of patients with ARDS.

The role of microbiota in the development and treatment of gastric cancer.

The stomach was once considered a sterile organ until the discovery of Helicobacter pylori (HP). With the application of high-throughput sequencing technology and macrogenomics, researchers have identified fungi and fivemajor bacterial phyla within the stomachs of healthy individuals. These microbial communities exert regulatory influence over various physiological functions, including energy metabolism and immune responses. HP is a well-recognized risk factor for gastric cancer, significantly altering the stomach's native microecology. Currently, numerous studies are centered on the mechanisms by which HP contributes to gastric cancer development, primarily involving the CagA oncoprotein. However, aside from exogenous infections such as HP and EBV, certain endogenous dysbiosis can also lead to gastric cancer through multiple mechanisms. Additionally, gut microbiota and its metabolites significantly impact the development of gastric cancer. The role of microbial therapies, including diet, phages, probiotics and fecal microbiota transplantation, in treating gastric cancer should not be underestimated. This review aims to study the mechanisms involved in the roles of exogenous pathogen infection and endogenous microbiota dysbiosis in the development of gastric cancer. Also, we describe the application of microbiota therapy in the treatment and prognosis of gastric cancer.

Exploring the growth characteristics of Alicyclobacillus acidoterrestris for controlling juice spoilage with zero additives.

Fruit juice spoilage that caused by contaminated Alicyclobacillus has brought huge losses to beverage industry worldwide. Thus, it is very essential to understand the growth and metabolism processing of Alicyclobacillus acidoterrestris (A. acidoterrestris) in controlling juice spoilage caused by Alicyclobacillus. In this work, simulative models for the growth and metabolism of A. acidoterrestris were systematically conducted in the medium and fruit juice. The results showed that low temperature (4 ℃) and strong acidic environment (pH 3.0-2.0) of medium inhibited the growth and reproduction of A. acidoterrestris. In addition, with decreasing temperature, the color, smell and turbidity of commercially available juice supplemented with A. acidoterrestris significantly improved. This work provided a clear exploration of growth characteristics of A. acidoterrestris by applying theory (medium) to reality (fruit juices), and pave fundamental for exploring the zero additives of controlling juice spoilage.

Identification of microbial markers associated with lung cancer based on multi-cohort 16 s rRNA analyses: A systematic review and meta-analysis.

BACKGROUND: The relationship between commensal microbiota and lung cancer (LC) has been studied extensively. However, developing replicable microbiological markers for early LC diagnosis across multiple populations has remained challenging. Current studies are limited to a single region, single LC subtype, and small sample size. Therefore, we aimed to perform the first large-scale meta-analysis for identifying micro biomarkers for LC screening by integrating gut and respiratory samples from multiple studies and building a machine-learning classifier. METHODS: In total, 712 gut and 393 respiratory samples were assessed via 16 s rRNA amplicon sequencing. After identifying the taxa of differential biomarkers, we established random forest models to distinguish between LC populations and normal controls. We validated the robustness and specificity of the model using external cohorts. Moreover, we also used the KEGG database for the predictive analysis of colony-related functions. RESULTS: The α and ß diversity indices indicated that LC patients' gut microbiota (GM) and lung microbiota (LM) differed significantly from those of the healthy population. Linear discriminant analysis (LDA) of effect size (LEfSe) helped us identify the top-ranked biomarkers, Enterococcus, Lactobacillus, and Escherichia, in two microbial niches. The area under the curve values of the diagnostic model for the two sites were 0.81 and 0.90, respectively. KEGG enrichment analysis also revealed significant differences in microbiota-associated functions between cancer-affected and healthy individuals that were primarily associated with metabolic disturbances. CONCLUSIONS: GM and LM profiles were significantly altered in LC patients, compared to healthy individuals. We identified the taxa of biomarkers at the two loci and constructed accurate diagnostic models. This study demonstrates the effectiveness of LC-specific microbiological markers in multiple populations and contributes to the early diagnosis and screening of LC.

Lung abscess by Fusobacterium nucleatum and Streptococcus spp. co-infection by mNGS: A case series.

A lung abscess is a necrotizing infection caused by microbiomes that lead to the loss of healthy lung tissue. The routine culture is a waste of time and yields false-negative results, and clinicians could only choose empiric therapy or use broad-spectrum antibiotics, which could significantly contribute to the problem of resistance or aggravate the condition. We report three patients with a routine-culture-negative lung abscess. The presenting symptoms included fever, cough, dyspnea, and chest pain, and a computed tomography scan revealed a lesion in the lungs. The bronchoalveolar lavage fluid and pleural fluid were tested for pathogens using metagenome next-generation sequencing (mNGS), and the results revealed Fusobacterium nucleatum and Streptococcus spp. (S. constellatus, S. intermedius) as the most represented microbial pathogens. Our data demonstrated that mNGS could be a promising alternative diagnostic tool for pathogen detection, and the pathogen lists indicate that it will be important to focus on the Streptococcus genus rather than the dominant Streptococcus spp. in terms of co-infection of pathogen determined by shotgun mNGS.

Non-anticoagulant factors affecting coagulation in the extracorporeal circulation circuit and the development of an individualized regional citrate anticoagulation protocol for hemodialysis: A real-world retrospective study.

OBJECTIVE: To investigate non-anticoagulant factors that affect blood coagulation in the extracorporeal circulation (ECC) circuit of regional citrate anticoagulation (RCA) protocol for hemodialysis (HD). METHOD: The clinical characteristics of patients undergoing an individualized RCA protocol for HD between February 2021 and March 2022 were collected; Coagulation scores, pressures in various parts of the ECC circuit, the incidence of coagulation, and citrate concentrations in the ECC circuit during treatment were determined, and non-anticoagulant factors affecting coagulation in the ECC circuit were analyzed. RESULT: The lowest clotting rate was 2.8% in patients with arteriovenous fistula in various vascular access. Patients on Fresenius dialysis had a lower rate of clotting in the cardiopulmonary bypass line than patients on other brands of dialyzer. Low-throughput dialyzers are less likely to clot than high-throughput dialyzers. There are significant differences in the incidence of coagulation among different nurses during citrate anticoagulant hemodialysis. CONCLUSION: In the process of citrate anticoagulant hemodialysis, non-anticoagulant factors such as coagulation status, vascular access, dialyzer selection, and operator quality will affect the anticoagulant effect.

Transcriptomic and Metabolomic Profiling Uncovers Response Mechanisms of Alicyclobacillus acidoterrestris DSM 3922T to Acid Stress.

Alicyclobacillus acidoterrestris, which has strong acidophilic and heat-resistant properties, can cause spoilage of pasteurized acidic juice. The current study determined the physiological performance of A. acidoterrestris under acidic stress (pH 3.0) for 1 h. Metabolomic analysis was carried out to investigate the metabolic responses of A. acidoterrestris to acid stress, and integrative analysis with transcriptome data was also performed. Acid stress inhibited the growth of A. acidoterrestris and altered its metabolic profiles. In total, 63 differential metabolites, mainly enriched in amino acid metabolism, nucleotide metabolism, and energy metabolism, were identified between acid-stressed cells and the control. Integrated transcriptomic and metabolomic analysis revealed that A. acidoterrestris maintains intracellular pH (pHi) homeostasis by enhancing amino acids decarboxylation, urea hydrolysis, and energy supply, which was verified using real-time quantitative PCR and pHi measurement. Additionally, two-component systems, ABC transporters, and unsaturated fatty acid synthesis also play crucial roles in resisting acid stress. Finally, a model of the responses of A. acidoterrestris to acid stress was proposed. IMPORTANCE Fruit juice spoilage caused by A. acidoterrestris contamination has become a major concern and challenge in the food industry, and this bacterium has been suggested as a target microbe in the design of the pasteurization process. However, the response mechanisms of A. acidoterrestris to acid stress still remain unknown. In this study, integrative transcriptomic, metabolomic, and physiological approaches were used to uncover the global responses of A. acidoterrestris to acid stress for the first time. The obtained results can provide new insights into the acid stress responses of A. acidoterrestris, which will point out future possible directions for the effective control and application of A. acidoterrestris.

A new deep convolutional neural network incorporating attentional mechanisms for ECG emotion recognition.

Using ECG signals captured by wearable devices for emotion recognition is a feasible solution. We propose a deep convolutional neural network incorporating attentional mechanisms for ECG emotion recognition. In order to address the problem of individuality differences in emotion recognition tasks, we incorporate an improved Convolutional Block Attention Module (CBAM) into the proposed deep convolutional neural network. The deep convolutional neural network is responsible for capturing ECG features. Channel attention in CBAM is responsible for adding weight information to ECG features of different channels and spatial attention is responsible for the weighted representation of ECG features of different regions inside the channel. We used three publicly available datasets, WESAD, DREAMER, and ASCERTAIN, for the ECG emotion recognition task. The new state-of-the-art results are set in three datasets for multi-class classification results, WESAD for tri-class results, and ASCERTAIN for two-category results, respectively. A large number of experiments are performed, providing an interesting analysis of the design of the convolutional structure parameters and the role of the attention mechanism used. We propose to use large convolutional kernels to improve the effective perceptual field of the model and thus fully capture the ECG signal features, which achieves better performance compared to the commonly used small kernels. In addition, channel attention and spatial attention were added to the deep convolutional model separately to explore their contribution levels. We found that in most cases, channel attention contributed to the model at a higher level than spatial attention.

Contribution of amino acids to Alicyclobacillus acidoterrestris DSM 3922T resistance towards acid stress.

Spoilage of juice and beverages by a thermo-acidophilic bacterium, Alicyclobacillus acidoterrestris, has been considered to be a major and widespread concern for juice industry. Acid-resistant property of A. acidoterrestris supports its survival and multiplication in acidic juice and challenges the development of corresponding control measures. In this study, intracellular amino acid differences caused by acid stress (pH 3.0, 1 h) were determined by targeted metabolomics. The effect of exogenous amino acids on acid resistance of A. acidoterrestris and the related mechanisms were also investigated. The results showed that acid stress affected the amino acid metabolism of A. acidoterrestris, and the selected glutamate, arginine, and lysine contributed to its survival under acid stress. Exogenous glutamate, arginine, and lysine significantly increased the intracellular pH and ATP level, alleviated cell membrane damage, reduced surface roughness, and suppressed deformation caused by acid stress. Additionally, the up-regulated gadA and speA genes and the enhanced enzymatic activity confirmed that glutamate and arginine decarboxylase systems played a crucial role in maintaining pH homeostasis of A. acidoterrestris under acid stress. Our research reveals an important factor contributing to acid resistance of A. acidoterrestris, which provides an alternative target for effectively controlling this contaminant in fruit juices.

Screening for important risk factors for cancer-specific mortality in patients with localized clear cell renal carcinoma.

Aim: To study the risk factors for cancer-specific mortality (CSM) among patients with localized clear cell renal carcinoma (LCCRC) in the Chinese population. Methods: The clinical data of 1,376 LCCRC patients were postoperatively collected to analyze the correlations between CSM and multiple factors using Cox regression analysis. Receiver operating characteristic curves were constructed as per the screened risk factors to identify factors with optimal criticality judgment values, which were then used as the scoring standard for the stratification evaluation of LCCRC prognosis. Results: The CSM rate was 5.6% (77/1,376 cases) and the median follow-up duration was 78.1 (60-105) months. Cox analysis revealed that age, tumor diameter, and nuclear grade were associated with CSM. The optimal criticality judgment values for age and tumor diameter using receiver operating characteristic curve analysis were 53 years and 5.8 cm, respectively. LCCRC prognosis divided into low-risk (≤ 2 points), intermediate-risk (3-4 points), and high-risk (5 points) showed CSM rates of 3.8%, 13.8%, and 58.3%, respectively, among patients with more than 5 years of follow-up. Conclusions: Age, tumor diameter, and nuclear grade were important risk factors for CSM in LCCRC patients. The scoring criteria including these three risk factors may be an important supplement to the prognostic model of LCCRC in the Chinese population.

Vaginal and tumor microbiomes in gynecological cancer (Review).

Cervical, ovarian and endometrial cancer are the three most common types of gynecologic cancer. As a hub, the vagina connects the site of gynecological cancer with the external environment. Lactobacilli participate in the formation of a healthy vaginal microenvironment as the first line of defense against pathogen invasion; a dysbiotic vaginal microenvironment loses its original protective function and is associated with the onset, metastasis, poor efficacy and poor prognosis of gynecological cancer. The early diagnosis of cancer is the key to improve the survival time of patients with cancer. The screening of Porphyromonas, Sneathia and Atopobium vaginae, and other microbial markers, can assist the diagnosis of gynecological cancer, and screen out the high-risk population as early as possible. With the in-depth study of the microbes in tumor tissues, reasearchers have analyzed the immunological associations of microorganisms in tumor tissues. Due to the structural-functional interconnection between the organ of gynecological tumorigenesis and the vagina, the present study aims to review the relationship between vaginal and tumor microorganisms and gynecological cancer in terms of occurrence, screening, treatment and prognosis.