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ABSTRACT Pancreatic cancer, predominantly pancreatic ductal adenocarcinoma (PDAC), is one of the most malignant tumors of the digestive system. Emerging evidence suggests the involvement of the microbiome and metabolic substances in the development of PDAC, yet the results remain contradictory. This study aims to identify the alterations and relationships in intratumoral microbiome and metabolites in PDAC. We collected matched tumor and normal adjacent tissue (NAT) samples from 105 PDAC patients and performed a 6-year follow-up. 2bRAD-M sequencing, untargeted liquid chromatography-tandem mass spectrometry, and untargeted gas chromatography-mass spectrometry were performed. Compared with NATs, microbial α-diversity decreased in PDAC tumors. The relative abundance of Staphylococcus aureus, Cutibacterium acnes, and Cutibacterium granulosum was higher in PDAC tumor after adjusting for confounding factors body mass index and M stage, and the presence of Ralstonia pickettii_B was found associated with a worse overall survival. Metabolomic analysis revealed distinctive differences in composition between PDAC and NAT, with 553 discriminative metabolites identified. Differential metabolites were revealed to originate from the microbiota and showed significant interactions with shifted bacterial species through KO (KEGG Orthology) genes. These findings suggest that the PDAC microenvironment harbors unique microbial-derived enzymatic reactions, potentially influencing the occurrence and development of PDAC by modulating the levels of glycerol-3-phosphate, succinate, carbonate, and beta-alanine.IMPORTANCEWe conducted a large sample-size pancreatic adenocarcinoma microbiome study using a novel microbiome sequencing method and two metabolomic assays. Two significant outcomes of our analysis are: (i) commensal opportunistic pathogens Staphylococcus aureus, Cutibacterium acnes, and Cutibacterium granulosum were enriched in pancreatic ductal adenocarcinoma (PDAC) tumors compared with normal adjacent tissues, and (ii) worse overall survival was found related to the presence of Ralstonia pickettii_B. Microbial species affect the tumorigenesis, metastasis, and prognosis of PDAC via unique microbe-enzyme-metabolite interaction. Thus, our study highlights the need for further investigation of the potential associations between pancreatic microbiota-derived omics signatures, which may drive the clinical transformation of microbiome-derived strategies toward therapy-targeted bacteria.

ABSTRACTBackground The microbiomes on the surface of unclean removable prostheses are complex and yet largely underexplored using metagenomic sequencing technology.Objectives To characterize the microbiome of removable prostheses with different levels of cleanliness using Type IIB Restriction-site Associated DNA for Microbiome (2bRAD-M) sequencing and compare the Microbial Index of Pathogenic Bacteria (MIP) between clean and unclean prostheses.Materials and Methods Ninety-seven removable prostheses were classified into ‘clean’ and ‘unclean’ groups. All prosthesis plaque samples underwent 2bRAD metagenomic sequencing to characterize the species-resolved microbial composition. MIPs for clean and unclean prostheses were calculated based on the sum of the relative abundance of pathogenic bacteria in a microbiome using a reference database that contains opportunistic pathogenic bacteria and disease-associated information.Results Beta diversity analyses based on Jaccard qualitative and Bray-Curtis quantitative distance matrices identified significant differences between the two groups (p

Abstract Gut microbiota can influence host gene expression and physiology through metabolites. Besides, the presence or absence of gut microbiome can reprogram host transcriptome and epitranscriptome as represented by N6‐methyladenosine (m6A), the most abundant mammalian mRNA modification. However, which and how gut microbiota‐derived metabolites reprogram host transcriptome and m6A epitranscriptome remain poorly understood. Here, investigation is conducted into how gut microbiota‐derived metabolites impact host transcriptome and m6A epitranscriptome using multiple mouse models and multi‐omics approaches. Various antibiotics‐induced dysbiotic mice are established, followed by fecal microbiota transplantation (FMT) into germ‐free mice, and the results show that bile acid metabolism is significantly altered along with the abundance change in bile acid‐producing microbiota. Unbalanced gut microbiota and bile acids drastically change the host transcriptome and the m6A epitranscriptome in multiple tissues. Mechanistically, the expression of m6A writer proteins is regulated in animals treated with antibiotics and in cultured cells treated with bile acids, indicating a direct link between bile acid metabolism and m6A biology. Collectively, these results demonstrate that antibiotic‐induced gut dysbiosis regulates the landscape of host transcriptome and m6A epitranscriptome via bile acid metabolism pathway. This work provides novel insights into the interplay between microbial metabolites and host gene expression.

Summary: The high infiltration of tumor-associated macrophages (TAMs) in the immunosuppressive tumor microenvironment prominently attenuates the efficacy of immune checkpoint blockade (ICB) therapies, yet the underlying mechanisms are not fully understood. Here, we investigate the metabolic profile of TAMs and identify S-2-hydroxyglutarate (S-2HG) as a potential immunometabolite that shapes macrophages into an antitumoral phenotype. Blockage of L-2-hydroxyglutarate dehydrogenase (L2HGDH)-mediated S-2HG catabolism in macrophages promotes tumor regression. Mechanistically, based on its structural similarity to α-ketoglutarate (α-KG), S-2HG has the potential to block the enzymatic activity of 2-oxoglutarate-dependent dioxygenases (2-OGDDs), consequently reshaping chromatin accessibility. Moreover, S-2HG-treated macrophages enhance CD8+ T cell-mediated antitumor activity and sensitivity to anti-PD-1 therapy. Overall, our study uncovers the role of blockage of L2HGDH-mediated S-2HG catabolism in orchestrating macrophage antitumoral polarization and, further, provides the potential of repolarizing macrophages by S-2HG to overcome resistance to anti-PD-1 therapy.

Abstract Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death globally. Although the gut microbiota's role in the antitumor efficacy of many cancers has been revealed, its involvement in the response to gefitinib therapy for LUAD remains unclear. To fill this gap, we conducted a longitudinal study that profiled gut microbiota changes in PC-9 tumor-bearing mice under different treatments, including gefitinib monotherapy and combination therapies with probiotics, antibiotics, or Traditional Chinese Medicine (TCM). Our findings demonstrated that combining probiotics or TCM with gefitinib therapy outperformed gefitinib monotherapy, as evidenced by tumor volume, body weight, and tumor marker tests. By contrast, antibiotic intervention suppressed the antitumor efficacy of gefitinib. Notably, the temporal changes in gut microbiota were strongly correlated with the different treatments, prompting us to investigate whether there is a causal relationship between gut microbiota and the antitumor efficacy of gefitinib using Mediation Analysis (MA). Finally, our research revealed that thirteen mediators (Amplicon Sequence Variants, ASVs) regulate the antitumor effect of gefitinib, regardless of treatment. Our study provides robust evidence supporting the gut microbiota's significant and potentially causal role in mediating gefitinib treatment efficacy in mice. Our findings shed light on a novel strategy for antitumor drug development by targeting the gut microbiota.

Abstract Probiotics often acquire potentially adaptive mutations in vivo, gaining new functional traits through gut selection. While both the host and microbiome can contribute to probiotics’ genetic evolution, separating the microbiome and the host’s contribution to such selective pressures remains challenging. Here, we introduced germ-free (GF) and specific pathogen-free (SPF) mouse models to track how probiotic strains, i.e., Lactiplantibacillus plantarum HNU082 (Lp082) and Bifidobacterium animalis subsp. lactis V9 (BV9), genetically evolved under selection pressures derived from host factors alone and both host and microbial ecological factors. Notably, compared to the genome of a probiotic strain before consumption, the host only elicited 99.75%). For a given probiotic, functional genes occurring in potentially adaptive mutations induced by hosts (GF mice) were all shared with those found in mutants of SPF mice. Collectively, the native microbiome consistently drove a more rapid and divergent genetic evolution of probiotic strains in seven days of colonization than host factors did. Our study further laid a theoretical foundation for genetically engineering probiotics for better gut adaptation through in vitro artificial gut ecosystems without the selection pressures derived from host factors.

Abstract Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles.

Introduction: During adulthood, the skin microbiota can be relatively stable if environmental conditions are also stable, yet physiological changes of the skin with age may affect the skin microbiome and its function. The microbiome is an important factor to consider in aging since it constitutes most of the genes that are expressed on the human body. However, severity of specific aging signs (one of the parameters used to measure “apparent” age) and skin surface quality (e.g., texture, hydration, pH, sebum, etc.) may not be indicative of chronological age. For example, older individuals can have young looking skin (young apparent age) and young individuals can be of older apparent age.Methods: Here we aim to identify microbial taxa of interest associated to skin quality/aging signs using a multi-study analysis of 13 microbiome datasets consisting of 16S rRNA amplicon sequence data and paired skin clinical data from the face.Results: We show that there is a negative relationship between microbiome diversity and transepidermal water loss, and a positive association between microbiome diversity and age. Aligned with a tight link between age and wrinkles, we report a global positive association between microbiome diversity and Crow’s feet wrinkles, but with this relationship varying significantly by sub-study. Finally, we identify taxa potentially associated with wrinkles, TEWL and corneometer measures.Discussion: These findings represent a key step towards understanding the implication of the skin microbiota in skin aging signs.

Microbiome has emerged as a promising indicator or predictor of human diseases. However, previous studies have typically labeled each specimen as either healthy or with a specific disease, ignoring prevalence of complications or comorbidities in actual cohorts, which may confound the microbial–disease associations. For instance, a patient may suffer from multiple diseases, making it challenging to detect their health status accurately. Furthermore, host phenotypes like physiological characteristics and lifestyles can alter microbiome structure, but such information has not yet been fully utilized in data models. To address these issues, a highly explainable deep learning (DL) method called Meta‐Spec is proposed. Using a deep neural network (DNN)‐based approach, it encodes and embeds refined host variables with microbiome features, enabling the detection of multiple diseases simultaneously. Experiments show that Meta‐Spec outperforms regular machine learning (ML) strategies for multilabel disease screening in several cohorts. More importantly, Meta‐Spec successfully detects comorbidities that are often missed by other approaches. In addition, for its high interpretability, Meta‐Spec captures key factors that shape disease patterns from host variables and microbes. Hence, these efforts improve the feasibility and sensitivity of microbiome‐based disease screening in practical scenarios, representing a significant step toward personalized medicine and better health outcomes.

ABSTRACT Adaptive evolutionary changes can precede the ecological changes in the gut microbial communities under constant host selection pressure, yet their association with host diseased status was underexplored. Explore shared disease-associated single-nucleotide variants (SNVs) in gut microbes spanning diverse human diseases. We performed a meta-analysis of 1,711 gut metagenomic samples from 16 case-control studies spanning 12 human diseases and included an additional 446-member cohort for validation. Overall, healthy individuals carried more mutated resident gut microbes, and more SNVs, mainly involving the short-chain fatty acids (SCFAs) producing bacteria. Furthermore, the widespread differences in base variant bias of gut microbes were observed between healthy and nonhealthy subjects suggesting divergent gut microbial evolutionary directions under different host medical conditions. We further found that nonsynonymous SNVs can lead to the loss of function of four SCFA-production genes in nonhealthy populations, among which two genes (i.e., ack and scpC) from Faecalibacterium prausnitzii C and Bacteroides stercoris, respectively, were externally validated. Subsequently, we developed a novel gut microbiome health index based on the SNV rate of all mutated strains, classifying host health states with 74.23% accuracy, and validated with high accuracy (AUROC = 69.28%). Our study highlights the importance of employing the genetic variability in gut microbiome to characterize the gut microbial adaptation that can also predict human chronic diseases.IMPORTANCEMost studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status.

Abstract Background Changes in renal microvascular perfusion are involved in several kidney diseases. Contrast-enhanced ultrasonography (CEUS) quantitative analysis can enable the estimation of renal microvascular perfusion non-invasively. However, to date, few pediatric patients with renal disease have been subjected to CEUS quantitative analysis. This study aimed to explore the feasibility of CEUS in evaluating renal microvascular perfusion in pediatric patients and paving its way to clinical practice. Methods Seventeen pediatric patients with chronic kidney disease (CKD) and five children without kidney disease were consecutively examined using CEUS. Quantitative analysis of CEUS images based on time-intensity curve (TIC) fittings was performed using specialized software. Quantitative parameters of wash-in microvascular blood flow, including A, k, B, and TtoPk, were generated from three regions of interest (ROIs) each in the cortex and medulla of each kidney. Results CEUS was performed in all children successfully and safely without the use of sedatives. All parameters (A, B, k, and TtoPk) demonstrated no statistical differences among the three sampling ROIs in the renal cortex and medulla. All parameters (A, B, k, and TtoPk) showed no statistical differences between the left and right sides of kidneys both in cortices and medullas. Comparing with patients with CKD stage 3–5, both control group and patients with CKD stage 1–2 had significantly higher values of parameter A in the renal cortex (p = 0.025 and p = 0.031, respectively). In control group and patients stage 1–2, the values of parameters k in the renal cortices were significantly higher than that in the renal medullas, while in patients with CKD stage 3–5, parameter k showed no statistically significant differences between the renal cortex and medulla (p = 0.173). Conclusion CEUS is safe and practicable in pediatric patients with chronic kidney disease. Renal microvascular perfusion estimated by CEUS could be a robust approach in the evaluation of pediatric renal diseases. Parameters A and k derived from CEUS quantitative analysis can provide great potential in non-invasive assessment of renal microvascular perfusion impairment in pediatric CKD.

As a promising choice of new-generation green propellant fuels, hypergolic ionic liquids (HILs) have attracted a great deal of interest in recent ten years, illustrated by their applications in the field of space science and exploring outer space. The design and syntheses of new ionic liquids (ILs) are the basis of the HILs’ sustainable development. In the recent years, many new HILs have been created through the rational design, and their hypergolic property and applications have been studied extensively. With the aim of familiarizing the reader with new trends in the area of HILs research, in this review we present the latest developments of new HILs including syntheses, properties, structure-property relationship and their applications in the field of liquid bipropellants, while the debatable issues and future challenges that need to be addressed are also discussed. Through this review, we intend that more readers may learn about the newest trends in the field of ionic liquid propellants, and it may also provide an additional catalyst for the vigorous development of new-generation green space propellants.

Background Pulmonary hypertension and right ventricular (RV) dysfunction are drivers of adverse outcomes; however, modifiable risk factors for RV dysfunction are not well described. We investigated the association between clinical markers of metabolic syndrome and echocardiographic RV function in a large referral population. Methods and Results Using electronic health record data, we performed a retrospective cohort study of patients aged ≥18 years referred for transthoracic echocardiography between 2010 and 2020 with RV systolic pressure (RVSP) or tricuspid annular plane systolic excursion (TAPSE) values. Pulmonary hypertension was defined by RVSP >33 mm Hg and RV dysfunction by TAPSE ≤1.8 cm. Our sample included 37 203 patients of whom 19 495 (52%) were women, 29 752 (83%) were White, with a median age of 63 years (interquartile range, 51–73). Median (interquartile range) RVSP was 30.0 mm Hg (24.0–38.7), and median TAPSE was 2.1 cm (1.7–2.4). Within our sample, 40% had recorded RVSP >33 mm Hg, and 32% with TAPSE 39 mm Hg) was associated with lower low‐density lipoprotein and high‐density lipoprotein, and higher hemoglobin A1c and body mass index (P1.8 cm, TAPSE 1.5–1.8 cm, and TAPSE

Here the authors show mutation of the BAF chromatin remodeler subunit ARID1A results in an ARID1B-dependent upregulation of HERVH, an ERV required for the pluripotency regulatory network. These HERVH RNAs can partition into BRD4 foci, affecting BRD4-dependent transcription. Suppression of HERVH in colorectal cancer cells and patient-derived organoids impairs tumor growth.

Summary: Background: Probiotics have been increasingly proposed for enhancing immune checkpoint blockade (ICB) treatments against cancer. However, its causal relationship with immunotherapeutic efficacy remains unclear, which promoted us to explore if and how probiotic Lacticaseibacillus rhamnosus Probio-M9 manipulates gut microbiome for expected outcomes. Methods: We evaluated the effects of Probio-M9 on the anti-PD-1 treatment against colorectal cancer in mice via a multi-omics approach. We defined the mechanisms of Probio-M9-mediated antitumor immunity by comprehensive analyses of metagenome and metabolites of commensal gut microbes as well as the immunologic factors and serum metabolome of the host. Findings: The results indicated that Probio-M9 intervention strengthened the anti-PD-1-based tumor inhibition. Both prophylactic and therapeutic administration of Probio-M9 showed conspicuous performance in controlling tumor growth with ICB treatment. The supplement of Probio-M9 modulated enhanced immunotherapy response through promoting beneficial microbes (e.g., Lactobacillus and Bifidobacterium animalis), producing beneficial metabolites including butyric acids in the gut, and accumulating blood-derived α-ketoglutaric acid, N-acetyl-l-glutamic acid and pyridoxine in particular, which promoted the infiltration and activation of cytotoxic T lymphocytes (CTLs) and suppressing the function of regulatory T cells (Tregs) in the tumor microenvironment (TME). Subsequently, we found that enhanced immunotherapeutic response was transmissible by transplanting either post-probiotic-treatment gut microbes or intestinal metabolites to new tumor-bearing mice. Interpretation: This study offered valuable insight into the causal role of Probio-M9 in correcting the defects in gut microbiota that compromised anti-PD-1 therapeutic efficacy, which can be used as an alternative synergetic agent with ICB for clinical cancer treatment. Funding: This research was supported by Research Fund for the National Key R&D Program of China (2022YFD2100702), Inner Mongolia Science and Technology Major Projects (2021ZD0014), and China Agriculture Research System of MOF and MARA.

Abstract Background Depression and obesity are highly prevalent, often co-occurring conditions marked by inflammation. Microbiome perturbations are implicated in obesity-inflammation-depression interrelationships, but how the microbiome mechanistically contributes to pathology remains unclear. Metabolomic investigations into microbial neuroactive metabolites may offer mechanistic insights into host-microbe interactions. Using 16S sequencing and untargeted mass spectrometry of saliva, and blood monocyte inflammation regulation assays, we identified key microbes, metabolites and host inflammation in association with depressive symptomatology, obesity, and depressive symptomatology-obesity comorbidity. Results Gram-negative bacteria with inflammation potential were enriched relative to Gram-positive bacteria in comorbid obesity-depression, supporting the inflammation-oral microbiome link in obesity-depression interrelationships. Oral microbiome was more highly predictive of depressive symptomatology-obesity co-occurrences than of obesity or depressive symptomatology independently, suggesting specific microbial signatures associated with obesity-depression co-occurrences. Mass spectrometry analysis revealed significant changes in levels of signaling molecules of microbiota, microbial or dietary derived signaling peptides and aromatic amino acids among depressive symptomatology, obesity and comorbid obesity-depression. Furthermore, integration of the microbiome and metabolomics data revealed that key oral microbes, many previously shown to have neuroactive potential, co-occurred with potential neuropeptides and biosynthetic precursors of the neurotransmitters dopamine, epinephrine and serotonin. Conclusions Together, our findings offer novel insights into oral microbial-brain connection and potential neuroactive metabolites involved.

Abstract Objective Body mass index (BMI) is the most commonly used predictor of weight‐related comorbidities and outcomes. However, the presumed relationship between height and weight intrinsic to BMI may introduce bias with respect to prediction of clinical outcomes. A series of analyses comparing the performance of models representing weight and height as separate interacting variables to models using BMI were performed using Vanderbilt University Medical Center's deidentified electronic health records and landmark methodology. Methods Use of BMI or height‐weight interaction in prediction models for established weight‐related cardiometabolic traits and metabolic syndrome was evaluated. Specifically, prediction models for hypertension, diabetes mellitus, low high‐density lipoprotein, and elevated triglycerides, atrial fibrillation, coronary artery disease, heart failure, and peripheral artery disease were developed. Model performance was evaluated using likelihood ratio, R2, and Somers' Dxy rank correlation. Differences in model predictions were visualized using heat maps. Results Compared to BMI, the maximally flexible height‐weight interaction model demonstrated improved prediction, higher likelihood ratio, R2, and Somers' Dxy rank correlation, for event‐free probability for all outcomes. The degree of improvement to the prediction model differed based on the outcome and across the height and weight range. Conclusions Because alternative measures of body composition such as waist‐to‐hip ratio are not routinely collected in the clinic clinical risk models quantifying risk based on height and weight measurements alone are essential to improve practice. Compared to BMI, modeling height and weight as independent, interacting variables results in less bias and improved predictive accuracy for all tested traits. Considering an individual's height and weight opposed to BMI is a better method for quantifying individual disease risk.

Abstract Microbiome samples with low microbial biomass or severe DNA degradation remain challenging for amplicon-based or whole-metagenome sequencing approaches. Here, we introduce 2bRAD-M, a highly reduced and cost-effective strategy which only sequences ~ 1% of metagenome and can simultaneously produce species-level bacterial, archaeal, and fungal profiles. 2bRAD-M can accurately generate species-level taxonomic profiles for otherwise hard-to-sequence samples with merely 1 pg of total DNA, high host DNA contamination, or severely fragmented DNA from degraded samples. Tests of 2bRAD-M on various stool, skin, environmental, and clinical FFPE samples suggest a successful reconstruction of comprehensive, high-resolution microbial profiles.

Chenchen Ma, Chengcheng Zhang, and Denghui Chen et al. examine how probiotic consumption impacts gut microbiota composition in human and mice through a global, cross-cohort metagenomic analysis. Their results suggest that probiotic consumption may result in widespread variation among the native microbiota in both the human and mouse gut.

Background Vitamin D supplementation leads to regression of left ventricular (LV) hypertrophy and improves LV function in animal models. However, limited data exist from prospective human studies. We examined whether vitamin D supplementation improved cardiac structure and function in midlife/older individuals in a large randomized trial. Methods and Results The VITAL (Vitamin D and OmegA‐3 Trial) was a nationwide double‐blind, placebo‐controlled randomized trial that tested the effects of vitamin D3 (2000 IU/d) and n−3 fatty acids (1 g/d) on cardiovascular and cancer risk in 25 871 individuals aged ≥50 years. We conducted a substudy of VITAL in which participants underwent echocardiography at baseline and 2 years. Images were interpreted by a blinded investigator at a central core laboratory. The primary end point was change in LV mass. Among 1054 Greater Boston–area participants attending in‐clinic visits, we enrolled 1025 into this study. Seventy‐nine percent returned for follow‐up and had analyzable echocardiograms at both visits. At baseline, the median age was 64 years (interquartile range, 60–69 years), 52% were men, and 43% had hypertension. After 2 years, the change in LV mass did not significantly differ between the vitamin D and placebo arms (median +1.4 g versus +2.6 g, respectively; P=0.32). Changes in systolic and diastolic LV function also did not differ significantly between arms. There were no significant changes in cardiac structure and function between the n−3 fatty acids and placebo arms. Conclusions Among adults aged ≥50 years, neither vitamin D3 nor n−3 fatty acids supplementation had significant effects on cardiac structure and function after 2 years. Registration URL: https://clinicaltrials.gov/; Unique identifiers: NCT01169259 (VITAL) and NCT01630213 (VITAL‐Echo)

Background Global longitudinal strain (GLS) is a sensitive measure of left ventricular function and a risk marker in severe aortic stenosis. We sought to determine whether biomarkers of cardiac damage (cardiac troponin) and stress (NT‐proBNP [N‐terminal pro‐B‐type natriuretic peptide]) could complement GLS to identify patients with severe aortic stenosis at highest risk. Methods and Results From a multicenter prospective cohort of patients with symptomatic severe aortic stenosis who underwent transcatheter aortic valve implantation, we measured absolute GLS (aGLS), cardiac troponin, and NT‐proBNP at baseline in 499 patients. Left ventricular ejection fraction 2; P≤0.002 for each) when the other biomarker was elevated, but not when the other biomarker was normal (interaction P=0.015). Conclusions Among patients with symptomatic severe aortic stenosis undergoing transcatheter aortic valve implantation, elevations in circulating cardiac troponin and NT‐proBNP are more common as GLS worsens. Biomarkers of cardiac damage and stress are independently associated with mortality after transcatheter aortic valve implantation, whereas GLS is not. These findings may have implications for risk stratification of asymptomatic patients to determine optimal timing of valve replacement.

Abstract The intestinal microbiota is a crucial environmental factor in the development of inflammatory bowel disease (IBD). The abundance of Faecalibacterium prausnitzii is significantly decreased in IBD patients, which is used as a biomarker for IBD diagnosis. However, this can be observed in both IBD and colorectal cancer, which would confound the diagnostic results. Thus, we first established a new model for predicting Crohn's disease (CD) with high precision according to gene characteristics based on single nucleotide variants (SNVs). Next, five gene markers belonging to two species, F. prausnitzii and Eubacterium rectale, that were enriched in the CD group were obtained to build a CD prediction model, and high accuracy in distinguishing the CD and control groups was observed in the discovery (area under curve [AUC] = 91.13%) and validation cohorts (AUC = 79.55%). The model still maintained high accuracy after expanding the healthy cohort (AUC = 89.75%). High disease specificity in distinguishing CD and CRC groups (AUC = 95.74%) was also proven. This study establishes a novel diagnostic method for predicting IBD that also provides unprecedented insight for the early, painless diagnosis of other non‐communicable diseases.

Abstract Objective To assess the clinical and radiographic factors associated with lead failure by comparing subjects with lead failure within 10 years of implantation with an implant‐year‐matched group without lead failure. Methods A case‐control study with 49 subjects who received Cardiac Implantable Electronic Device (CIED) between January 1, 1999 and July 31, 2008 and developed lead failure within 10 years of implantation in a single center. The control group consisted of subjects (n = 54) with normally functioning leads matched one‐to‐one by implant year. Results Among the failure group, the meantime from implantation to device lead failure was 4.70 ± 2.94 years. Older age at implantation was associated with a lower likelihood of lead failure (Odds Ratio (OR) = 0.28 (75 vs 42 years old), 95% CI 0.12‐0.63, P = .002). A larger smallest loop diameter on the chest radiograph was also associated with a lower likelihood of lead failure (OR = 0.51 (31 vs 14 mm), 95% CI 0.27‐0.97, P = .04). CIED type (defibrillator vs pacemaker) and Ottawa scores were not significantly associated with lead failure. Among lead‐specific parameters, defibrillation lead vs pace‐sense lead was associated with lead failure (OR = 3.91, 95% CI 1.95‐7.81, P

Abstract Background SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting. Methods We collected 972 samples from hospitalized patients with COVID-19, their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model. Results Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled high classifier accuracy for SARS-CoV-2 status in not only nares, but also forehead, stool, and floor samples. Across these distinct microbial profiles, a single amplicon sequence variant from the genus Rothia strongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic. Conclusions These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment. Video Abstract

Abstract Background Improving probiotic engraftment in the human gut requires a thorough understanding of the in vivo adaptive strategies of probiotics in diverse contexts. However, for most probiotic strains, these in vivo genetic processes are still poorly characterized. Here, we investigated the effects of gut selection pressures from human, mice, and zebrafish on the genetic stability of a candidate probiotic Lactiplantibacillus plantarum HNU082 (Lp082) as well as its ecological and evolutionary impacts on the indigenous gut microbiota using shotgun metagenomic sequencing in combination with isolate resequencing methods. Results We combined both metagenomics and isolate whole genome sequencing approaches to systematically study the gut-adaptive evolution of probiotic L. plantarum and the ecological and evolutionary changes of resident gut microbiomes in response to probiotic ingestion in multiple host species. Independent of host model, Lp082 colonized and adapted to the gut by acquiring highly consistent single-nucleotide mutations, which primarily modulated carbohydrate utilization and acid tolerance. We cultivated the probiotic mutants and validated that these gut-adapted mutations were genetically stable for at least 3 months and improved their fitness in vitro. In turn, resident gut microbial strains, especially competing strains with Lp082 (e.g., Bacteroides spp. and Bifidobacterium spp.), actively responded to Lp082 engraftment by accumulating 10–70 times more evolutionary changes than usual. Human gut microbiota exhibited a higher ecological and genetic stability than that of mice. Conclusions Collectively, our results suggest a highly convergent adaptation strategy of Lp082 across three different host environments. In contrast, the evolutionary changes within the resident gut microbes in response to Lp082 were more divergent and host-specific; however, these changes were not associated with any adverse outcomes. This work lays a theoretical foundation for leveraging animal models for ex vivo engineering of probiotics to improve engraftment outcomes in humans. Video abstract

Summary: Harmful Microcystis blooms (HMBs) and microcystins (MCs) that are produced by Microcystis seriously threaten water ecosystems and human health. This study demonstrates an eco-friendly strategy for simultaneous removal of MCs and HMBs by adopting unique hyperoxic graphene oxides (HGOs) as carrier and pure microcystinase A (PMlrA) as connecting bridge to form stable HGOs@MlrA composite. After oxidation, HGOs yield inherent structural strain effects for boosting the immobilization of MlrA by material characterization and density functional theory calculations. HGO5 exhibits higher loading capacities for crude MlrA (1,559 mg·g−1) and pure MlrA (1,659 mg·g−1). Moreover, the performances of HGO5@MlrA composite, including the capability of removing MCs and HMBs, the ecological and human safety compared to MlrA or HGO5 treatment alone, have been studied. These results indicate that HGO5 can be used as a promising candidate material to effectively improve the application potential of MlrA in the simultaneous removal of MCs and HMBs.

ABSTRACT Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions and to test whether our past observations linking SARS-CoV-2 abundance to Rothia sp. in hospitals also hold in a residential setting, we performed a detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences (to assess the bacterial community at each location), and to the Cq value of the contemporaneous clinical test. Our results showed that the highest SARS-CoV-2 load in this setting is on touched surfaces, such as light switches and faucets, but a detectable signal was present in many untouched surfaces (e.g., floors) that may be more relevant in settings, such as schools where mask-wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association. IMPORTANCE Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g., touching a light switch) or indirectly (e.g., by droplets or aerosols settling). We found the highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g., in schools, where students did not touch the light switches and also wore masks such that they had no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

Minimally invasive peritoneal dialysis (PD) catheterization is increasingly common, and percutaneous PD catheters may be placed using a trocar or the Seldinger technique. There are few reports of pediatric percutaneous PD catheter insertion. We retrospectively compared the outcomes from percutaneous placement of Tenckhoff catheters using a modified Seldinger technique with catheter placement by open surgery. This single-center retrospective study compared 14 pediatric patients who received percutaneous PD catheter insertion using an ultrasound-guided modified Seldinger technique (August 2018–February 2021) with 10 patients who received open-surgical PD catheter insertion (2015–2018). Complications and catheter survival were evaluated. The overall technical success rate was 100%, but the Seldinger technique required less time (30 vs. 45 min) and smaller incisions (1.1 vs. 4.4 cm). The early complications in the Seldinger and control groups were bleeding (1 vs. 0), catheter dysfunction (1 vs. 1), abdominal pain (3 vs. 7), and exit leakage (0 vs. 1). In the Seldinger group, the median time from insertion to first use was 3 days, and the minimum follow-up was 6 months. Catheter survival at 6 months was 93% (Seldinger group) and 90% (open surgery group). The adoption of this technique at our institution led to a significant increase in the percentage of new pediatric dialysis patients commencing PD rather than hemodialysis. Collectively, the modified Seldinger technique described here was safe and feasible in pediatric patients. This approach is simpler and more rapid than open surgery, and reduces early complications and increases PD uptake.

Abstract Background Approximately 10% of patients would develop symptomatic intracranial hemorrhage (sICH) after endovascular therapy. The aim of our study was to explore the ability of hypersensitive C-reactive protein-albumin ratio (HAR) in predicting sICH after endovascular therapy. Methods From April 2016 to December 2018, 334 consecutive patients with anterior circulation infarction undergoing endovascular therapy were enrolled in our study. sICH was defined using Heidelberg bleeding classification after endovascular therapy. Multiple regression analysis was used to investigate the potential risk factors of sICH after endovascular therapy. We used receiver operating characteristic curve analysis and nomogram analysis to assess the overall discriminative ability of the HAR in predicting sICH after endovascular therapy. Results Among these 334 patients enrolled, 37 (11.1%) patients with anterior circulation infarction were identified with sICH after endovascular therapy. Univariate logistic regression analysis demonstrated that patients with higher levels of HAR may be inclined to develop sICH (odds ratio, 10.994; 95% confidence interval, 4.567–26.463; P = 0.001). This association remained significant even after adjustment for potential confounders. Also, a cutoff value of 0.526× 10− 3 for HAR was detected in predicting sICH (area under curve, 0.763). Furthermore, nomogram analysis also suggested that HAR was an indicator of sICH (c-index was 0.890, P

ABSTRACT We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.

Background Left ventricular hypertrophy (LVH) is associated with increased mortality risk and rehospitalization after transcatheter aortic valve replacement among those with severe aortic stenosis. Whether cardiac troponin (cTnT) and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) risk stratify patients with aortic stenosis and without LVH is unknown. Methods and Results In a multicenter prospective registry of 923 patients with severe aortic stenosis undergoing transcatheter aortic valve replacement, we included 674 with core‐laboratory‐measured LV mass index, cTnT, and NT‐proBNP. LVH was defined by sex‐specific guideline cut‐offs and elevated biomarker levels were based on age and sex cut‐offs. Adjusted Cox proportional hazards models evaluated associations between LVH and biomarkers and all‐cause death out to 5 years. Elevated cTnT and NT‐proBNP were present in 82% and 86% of patients with moderate/severe LVH, respectively, as compared with 66% and 69% of patients with no/mild LVH, respectively (P

Abstract Massive microbiome sequencing data has been generated, which elucidates associations between microbes and their environmental phenotypes such as host health or ecosystem status. Outstanding bioinformatic tools are the basis to decipher the biological information hidden under microbiome data. However, most approaches placed difficulties on the accessibility to nonprofessional users. On the other side, the computing throughput has become a significant bottleneck of many analytical pipelines in processing large‐scale datasets. In this study, we introduce Parallel‐Meta Suite (PMS), an interactive software package for fast and comprehensive microbiome data analysis, visualization, and interpretation. It covers a wide array of functions for data preprocessing, statistics, visualization by state‐of‐the‐art algorithms in a user‐friendly graphical interface, which is accessible to diverse users. To meet the rapidly increasing computational demands, the entire procedure of PMS has been optimized by a parallel computing scheme, enabling the rapid processing of thousands of samples. PMS is compatible with multiple platforms, and an installer has been integrated for full‐automatic installation.

BackgroundChina is a country with a high burden of tuberculosis (TB), and students are the high-risk group for TB. The enrollment scale of colleges has increased dramatically due to the advancement of the enrollment expansion system of Chinese colleges. Consequently, this has brought severe challenges to TB prevention and control in colleges. In 2017, a new TB control guide for schools was issued in China, which included the 8 core knowledge of TB. The target of the overall awareness rate on TB among population was “≥85%,” which was proposed by the “13th Five-Year” National TB Control Plan in China. The cognition of the 8 core knowledge of TB in the new guide among college students is crucial to achieve this target, but few studies on this have been reported. Based on the abovementioned new situation and the new guide, this study aimed to investigate and analyze the cognition, attitudes, and health education needs on TB among freshmen of a medical college in Guangxi province, and discuss how to optimize TB health education in colleges in China.MethodsA cross-sectional study was conducted among freshmen of a medical college in Guangxi, China. A self-designed questionnaire was used to conduct an on-site questionnaire survey. The data was entered in Epidata 4.4.2.1 and was analyzed using SPSS version 25.0. Including descriptive statistics and t-test, and the criterion for statistically significant difference was p < 0.05.ResultsA total of 583 freshmen responded to the survey questionnaires. Regarding cognition about the 5 related knowledge of TB, 551 (94.5%) freshmen knew about the predilection site of TB, while 333 (57.1%), 328 (56.4%), 257 (44.1%), and 201 (34.5%) freshmen knew about the pathogen, the policies about free treatment, the designated hospitals, and the World TB Day, respectively. Regarding cognition on the 8 core knowledge of TB, the overall awareness rate among the freshmen is 73.3%(3,420/4,664); the awareness rate of the knowledge that “guarantee adequate sleep, reasonable diet, and strengthen physical exercise can reduce the incidence of TB” among them was the highest at 88.7% (517/583); and the awareness rate of the knowledge that “coughing or sputum expectoration occurred for more than 2 weeks should be suspected of infecting TB and seeking medical treatment in time” among them was the lowest at 47.5% (277/583). Whether students received health education on TB (T = 4.267, p = 0.000) and whether students heard of TB (T = 3.739, p = 0.000) are the main factors of cognition. Five hundred sixty-two (96.4%) and 565 (96.9%) freshmen were willing to learn and tell others about the knowledge of TB, respectively. Three hundred seventy (63.5%.) freshmen, the highest amount, were willing to accept TB health education in the forms of “website, Weibo, and WeChat.”ConclusionThe cognition on the 5 related knowledge of TB among freshmen is unbalanced, and the overall awareness rate of the 8 core knowledge of TB among freshmen still needs to be improved. Freshmen who have not heard of TB and have not received TB health education before enrollment are the key intervention groups. It is recommended that institutions make full use of modern multimedia technology, continuously optimize the health education forms, implement precise policies, and strengthen the theoretical and practical health education on TB from the initial entry of freshmen into colleges.

Abstract Background Numerous studies have reported the health-promoting effects of exopolysaccharides (EPSs) in in vitro models; however, a functional evaluation of EPSs will provide additional knowledge of EPS-microbe interactions by in vivo intestinal microbial model. In the present study, high-throughput amplicon sequencing, short-chain fatty acid (SCFAs) and intestinal inflammation evaluation were performed to explore the potential benefits of exopolysaccharides (EPSs) and EPS-producing Lactobacillus (HNUB20 group) using the healthy zebrafish (Danio rerio) model. Results The results based on microbial taxonomic analysis revealed that the abundance of four genera, Ochrobactrum, Sediminibacterium, Sphingomonas and Sphingobium, were increased in the control group in comparison to HNUB20 group. Pelomonas spp. levels were significantly higher and that of the genera Lactobacillus and Brachybacterium were significantly decreased in EPS group compared with control group. PICRUSt based functional prediction of gut microbiota metabolic pathways indicated that significantly lower abundance was found for transcription, and membrane transport, whereas folding, sorting and degradation and energy metabolism had significantly higher abundance after HNUB20 treatment. Two metabolic pathways, including metabolism and endocrine functions, were more abundant in the EPS group than control group. Similar to the HNUB20 group, transcription was also decreased in the EPS group compared with the control group. However, SCFAs and immune indexes indicated EPS and HNUB20 performed limited efficacy in the healthy zebrafish. Conclusions The present intestinal microbial model-based study indicated that EPSs and high-yield EPS-producing Lactobacillus can shake the structure of intestinal microbiota, but cannot change SCFAs presence and intestinal inflammation.

As the first hybrid-constellation global navigation system, China’s BeiDou navigation satellite system (BDS) has been fully constructed since July 2020 and provides open services for worldwide users. Due to the natural sensitivity of satellite tracking techniques to geocenter motion, BDS has the capability to determine the geocenter coordinates (GCC). This study aims to improve the precision of geocenter coordinates derived from BDS. To that end, 3-year sets of daily geocenter coordinates have been determined with BDS observations. Different solar radiation pressure (SRP) models, including the empirical CODE orbit model (ECOM), the extended ECOM model (ECOM2), and the a priori box-wing along with the ECOM model (BW + ECOM), have been applied for the BDS geocenter estimation. We show that the BW + ECOM model is beneficial in recovering the geocenter motion. Compared to the ECOM, the BW + ECOM model appears to mitigate the draconitic signal of BDS, which reduces the annual amplitude of the GCC-Z by a factor of 2.9. On the other hand, the amplitude of the 3 cpy signal is also reduced by a factor of 2.9. Furthermore, we studied the impact of BDS constellation configuration on the geocenter estimation. The results indicate that the inclusion of IGSO satellites significantly mitigates the spurious signals in the spectra of the GCC-Z. The amplitudes of the annual signal and 3 cpy signal are reduced by (28%, 14%), (33%, 61%), and (31%, 9%) for ECOM, ECOM2, and BW + ECOM cases, respectively. Meanwhile, the amplitude of the 7-day signal related to the orbital period of MEO satellites is also reduced by 32–45%. Thus, the BW + ECOM model and the MEO+IGSO hybrid configuration are recommended for BDS to determine the geocenter coordinates. However, despite these improvements, a significant annual signal with an amplitude of 20.2 mm and a visible 3 cpy signal with an amplitude of 6.1 mm still exist when compared to the Satellite Laser Ranging (SLR) solution.

The authors build a reference phylogeny of 10,575 evenly-sampled bacterial and archaeal genomes, based on 381 markers. The results indicate a remarkably closer evolutionary proximity between Archaea and Bacteria than previous estimates that used fewer “core” genes, such as the ribosomal proteins.

Objective Red cell distribution width (RDW) is an enigmatic biomarker associated with the presence and severity of multiple cardiovascular diseases (CVDs). It is unclear whether elevated RDW contributes to, results from, or is pleiotropically related to CVDs. We used contemporary genetic techniques to probe for evidence of aetiological associations between RDW, CVDs, and CVD risk factors.Methods Using an electronic health record (EHR)-based cohort, we built and deployed a genetic risk score (GRS) for RDW to test for shared genetic architecture between RDW and the cardiovascular phenome. We also created GRSs for common CVDs (coronary artery disease, heart failure, atrial fibrillation, peripheral arterial disease, venous thromboembolism) and CVD risk factors (body mass index (BMI), low-density lipoprotein, high-density lipoprotein, systolic blood pressure, diastolic blood pressure, serum triglycerides, estimated glomerular filtration rate, diabetes mellitus) to test each for association with RDW. Significant GRS associations were further interrogated by two-sample Mendelian randomisation (MR). In a separate EHR-based cohort, RDW values from 1-year pre-gastric bypass surgery and 1–2 years post-gastric bypass surgery were compared.Results In a cohort of 17 937 subjects, there were no significant associations between the RDW GRS and CVDs. Of the CVDs and CVD risk factors, only genetically predicted BMI was associated with RDW. In subsequent analyses, BMI was associated with RDW by multiple MR methods. In subjects undergoing bariatric surgery, RDW decreased postsurgery and followed a linear relationship with BMI change.Conclusions RDW is unlikely to be aetiologically upstream or downstream of CVDs or CVD risk factors except for BMI. Genetic and clinical association analyses support an aetiological relationship between BMI and RDW.

Cell necrosis and neuroinflammation play an important role in brain injury induced by ischemic stroke. Previous studies reported that Taohong Siwu decoction (THSWD)can reduce heart muscle cell necrosis and has anti-inflammatory properties. In this study, we investigated the effects of THSWD on cell necrosis and neuroinflammation in a rat model of middle cerebral artery occlusion (MCAO). Thirty-six male Sprague-Dawley (SD) rats were randomly divided into three groups with 12 rats in each group. They were the sham operation group, MCAO model group, and MCAO + THSWD group. We used ELISA to determine the levels of TNF-α, Mcp-1, and IL-1β inflammatory factors in rat serum, qRT‐PCR to detect the expression of TNF‐α, Mcp‐1 and IL‐1β mRNA in rat brain, and immunohistochemistry to detect the number of microglia and neutrophils in rat brain. qRT-PCR and Western blot were used to detect the mRNA and protein expression levels of IBA-1 and MPO inflammatory factors and the TNF-α/RIP1/RIP3/MLKL pathway in the rat brain and protein expression levels. Compared with the sham operation group, the expression of MCP-1, IL-1β, IBA-1, and MPO inflammatory factors and the TNF-α/RIP1/RIP3/MLKL pathway were significantly upregulated in the MCAO group. Compared with the MCAO group, the expressions of MCP-1, IL-1β, IBA-1, and MPO inflammatory factors and the TNF-α/RIP1/RIP3/MLKL pathway were significantly downregulated in the MCAO + THSWD group. THSWD can reduce the expression levels of MCP-1, IL-1β, IBA-1, and MPO inflammatory factors as well as the TNF-α/RIP1/RIP3/MLKL pathway. Meanwhile, it can reduce the necrosis and inflammation of brain cells after cerebral ischemia, so as to protect the brain tissue of rats.

Lung carcinoma is the most common type of cancer and the leading cause of cancer-related death worldwide. Among the numerous therapeutic strategies for the treatment of lung cancer, adeno-associated virus (AAV)-mediated gene transfer has been demonstrated to have the potential to effectively suppress tumor growth or reverse the progression of the disease in a number of preclinical studies. AAV vector has a safety profile; however, the relatively low delivery efficacy to particular subtypes of lung carcinoma has limited its prospective clinical translation. Exosomes are nanosized extracellular vesicles secreted from nearly all known cell types. Exosomes have a membrane-enclosed structure carrying a range of cargo molecules for efficient intercellular transfer of functional entities, thus are considered as a superior vector for drug delivery. In the present study, we developed a novel strategy to produce and purify AAV-containing exosomes (AAVExo) from AAV-packaging HEK 293T cells. The cellular uptake capacity of exosomes assisted and enhanced AAV entry into cells and protected AAV from antibody neutralization, which was a serious challenge for AAV in vivo application. We tested a list of lung cancer cell lines representing non-small-cell lung cancer and small-cell lung cancer and found that AAVExo apparently improved the gene transfer efficiency compared to conventional AAV vector. Our in vitro results were supported in vivo in a lung cancer xenograft rodent model. Additionally, we evaluated the gene delivery efficiency in the presence of neutralizing antibody on lung cancer cells. The results demonstrated that AAVExo-mediated gene transfer was not impacted, while the AAV vectors were significantly blocked by the neutralizing antibody. Taken together, we established an efficient methodology for AAVExo purification, and the purified AAVExo largely enhanced gene delivery to lung cancer cells with remarkable resistance to antibody neutralization.

BackgroundTao Hong Si Wu Decoction (THSWD) is a well-known traditional Chinese medicine used clinically alone or combined with drugs to treat breast cancer. However, there has been no study to date on the underlying mechanisms of its therapeutic effects.ObjectivesTo explore the potential mechanism of THSWD for the treatment of breast cancer using network pharmacology and experimental research.MethodsThe active ingredients of THSWD were screened according to Lipinski’s rule of five based on the 107 ingredients of THSWD identified by UPLC-Q-TOF-MSE. The targets of THSWD and breast cancer from multiple databases were collected, and a Compound-Target-Pathway network based on protein-protein interaction (PPI) was constructed. Gene ontology (GO) analysis and KEGG pathway analysis were performed via the DAVID server. Molecular docking studies verified the selected key ingredients and key targets. The results of network pharmacology were verified by in vitro experiments. Including the effects of THSWD drug-containing rat serum (THSWD serum) on cell proliferation, and on the targets HRAS, MAPK1, AKT1, GRB2, and MAPK14 were assayed by RT-qPCR and Western blot assays.ResultsIn total, 27 active ingredients including 8 core components, were obtained from 107 ingredients and 218 THSWD target genes for the treatment of breast cancer were identified. THSWD is active in the treatment of breast cancer by targeting Ras, FoxO, PI3K-Akt and other signaling pathways. MCF-7 and MDA-MB-231 cell proliferation was inhibited by THSWD serum in a time and concentration dependent manner. THSWD could regulated the RNA and protein expression of core targets HRAS, MAPK1, AKT1, GRB2, and MAPK14 for treatment of breast cancer.ConclusionThe results of network pharmacology study showed that THSWD is active against breast cancer by intervening with multiple targets and pathways. Luteolin, kaempferol, senkyunolide E, and other 8 compounds may be the core active ingredients of THSWD in the treatment of breast cancer. THSWD treatment of breast cancer may be related to targeting Ras, FoxO, PI3K-Akt, and other signal pathways associated with the core targets HRAS, MAPK1, AKT1, GRB2, and MAPK14.

Retrospective studies suggest that chimeric antigen receptor T-cell (CAR T) therapy may lead to cardiac injury, but this has not been assessed systematically or prospectively. In this prospective study of 40 patients who received CAR T, we systematically measured high-sensitivity troponin T (hsTropT) and N-terminal pro-B natriuretic peptide (NTproBNP) at baseline and on day 1, days 7, and 21 after CAR T. Biomarker elevations with respect to timepoint and cytokine release syndrome (CRS) status were examined using repeated measure analysis of variance. hsTropT did not differ with time or with the presence of grade 2 CRS. Median hsTropT was 12.1 ng/L [interquartile range (IQR): 9.2, 20.1] at baseline, 13.1 ng/L (IQR: 9.6, 24.2) at day 1, 11.9 ng/L (IQR: 9.6, 18.0) at day 7, and 15.3 ng/L (10.8, 20.2) at day 21. In contrast, NTproBNP rose on day 1 (PWilcox = 0.0002) and day 7 (PWilcox = 2.7 × 10−5), and the degree of elevation differed by the presence of grade 2 CRS (Pinteraction = 0.002). Median NTproBNP was 179 pg/mL (IQR: 116, 325) at baseline, 357 pg/mL (IQR: 98, 813) at day 1, 420 pg/mL (IQR: 239, 1242) at day 7, and 177 pg/mL (IQR: 80, 278) at day 21. In conclusion, hsTropT l did not differ across timepoints after CAR T therapy, but NTproBNP rose at day 7, the prognostic implications of which should be the target of future research, as the indications for this therapy expand.

ABSTRACT To reveal the dynamic features of cellular systems, such as the correlation among phenotypes, a time or condition series set of samples is typically required. Here, we propose intra-ramanome correlation analysis (IRCA) to achieve this goal from just one snapshot of an isogenic population, via pairwise correlation among the cells of the thousands of Raman peaks in single-cell Raman spectra (SCRS), i.e., by taking advantage of the intrinsic metabolic heterogeneity among individual cells. For example, IRCA of Chlamydomonas reinhardtii under nitrogen depletion revealed metabolite conversions at each time point plus their temporal dynamics, such as protein-to-starch conversion followed by starch-to-triacylglycerol (TAG) conversion, and conversion of membrane lipids to TAG. Such among-cell correlations in SCRS vanished when the starch-biosynthesis pathway was knocked out yet were fully restored by genetic complementation. Extension of IRCA to 64 microalgal, fungal, and bacterial ramanomes suggests the IRCA-derived metabolite conversion network as an intrinsic metabolic signature of isogenic cellular population that is reliable, species-resolved, and state-sensitive. The high-throughput, low cost, excellent scalability, and general extendibility of IRCA suggest its broad applications. IMPORTANCE Each isogenic population of cells is characterized by many phenotypes, which change with time and condition. Correlations among such phenotypes are fundamental to system function, yet revelation of such links typically requires multiple samples. Here, we showed that, by exploiting the intrinsic metabolic heterogeneity among individual cells, such interphenotype correlations can be unveiled via just one snapshot of an isogenic cellular population. Specifically, a network of potential metabolite conversions can be reconstructed using intra-ramanome correlation analysis (IRCA), by pairwise correlation of the thousands of Raman peaks or combination of peaks among single-cell Raman spectra sampled from just one instance of the cellular population. The ability to rapidly and noninvasively reveal intermetabolite conversions from just one snapshot of one sample should usher in many new opportunities in functional profiling of cellular systems.

Dental caries is one of the most prevalent chronic oral diseases, affecting approximately half of children worldwide. The microbial composition of dental caries may depend on age, oral health, diet, and geography, yet the effect of geography on these microbiomes is largely underexplored. Here, we profiled and compared saliva microbiota from 130 individuals aged 6 to 8 years old, representing both healthy children (H group) and children with caries-affected (C group) from two geographical regions of China: a northern city (Qingdao group) and a southern city (Guangzhou group). First, the saliva microbiota exhibited profound differences in diversity and composition between the C and H groups. The caries microbiota featured a lower alpha diversity and more variable community structure than the healthy microbiota. Furthermore, the relative abundance of several genera (e.g., Lactobacillus, Gemella, Cryptobacterium and Mitsuokella) was significantly higher in the C group than in the H group (p

Supervised learning for Unmanned Aerial Vehicle (UAVs) visual-based navigation raises the need for reliable datasets with multi-task labels (e.g., classification and regression labels). However, current public datasets have limitations: (a) Outdoor datasets have limited generalization capability when being used to train indoor navigation models; (b) The range of multi-task labels, especially for regression tasks, are in different units which require additional transformation. In this paper, we present a Hull Drone Indoor Navigation (HDIN) dataset to improve the generalization capability for indoor visual-based navigation. Data were collected from the onboard sensors of a UAV. The scaling factor labeling method with three label types has been proposed to overcome the data jitters during collection and unidentical units of regression labels simultaneously. An open-source Convolutional Neural Network (i.e., DroNet) was employed as a baseline algorithm to retrain the proposed HDIN dataset, and compared with DroNet’s pretrained results on its original dataset since we have a similar data format and structure to the DroNet dataset. The results show that the labels in our dataset are reliable and consistent with the image samples.

Background Experimental and observational studies have suggested a link between vitamin D and cardiovascular and metabolic disease, but this has not been confirmed in randomized controlled trials. We sought to determine whether vitamin D supplementation reduces biomarkers of insulin resistance, inflammation, neurohormonal activation, and lipids. Methods and Results This was a prespecified, secondary analysis of the DAYLIGHT (Vitamin D Therapy in Individuals at High Risk of Hypertension) randomized controlled trial. We measured circulating homeostatic model assessment of insulin resistance, hs‐CRP (high‐sensitivity C‐reactive protein), N‐terminal pro‐B‐type natriuretic peptide, renin, aldosterone, and lipids at baseline and at 6 months in 289 individuals with low vitamin D status (25‐hydroxyvitamin‐D [25‐OH‐D] ≤25 ng/mL) receiving low‐dose (400 IU/d) versus high‐dose (4000 IU/d) vitamin D3 for 6 months. A meta‐analysis of randomized controlled trials reporting biomarker changes after vitamin D supplementation was then performed. Levels of 25‐OH‐D increased in the high‐dose relative to the low‐dose vitamin D group (+15.5 versus +4.6 ng/mL, P

Background: Gan–Dou–Fu–Mu decoction (GDFMD) improves liver fibrosis in experimental and clinical studies including those on toxic mouse model of Wilson disease (Model). However, the mechanisms underlying the effect of GDFMD have not been characterized. Herein, we deciphered the potential therapeutic targets of GDFMD using transcriptome analysis.Methods: We constructed a tx-j Wilson disease (WD) mouse model, and assessed the effect of GDFMD on the liver of model mice by hematoxylin and eosin, Masson, and immunohistochemical staining. Subsequently, we identified differentially expressed genes (DEGs) that were upregulated in the Model (Model vs. control) and those that were downregulated upon GDFMD treatment (compared to the Model) using RNA-sequencing (RNA-Seq). Biological functions and signaling pathways in which the DEGs were involved were determined by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses. A protein–protein interaction (PPI) network was constructed using the STRING database, and the modules were identified using MCODE plugin with the Cytoscape software. Several genes identified in the RNA-Seq analysis were validated by real-time quantitative PCR.Results: Total of 2124 DEGs were screened through the Model vs. control and Model vs. GDFMD comparisons, and dozens of GO and KEGG pathway terms modulated by GDFMD were identified. Dozens of pathways involved in metabolism (including metabolic processes for organic acids, carboxylic acids, monocarboxylic acids, lipids, fatty acids, cellular lipids, steroids, alcohols, eicosanoids, long-chain fatty acids), immune and inflammatory response (such as complement and coagulation cascades, cytokine–cytokine receptor interaction, inflammatory mediator regulation of TRP channels, antigen processing and presentation, T-cell receptor signaling pathway), liver fibrosis (such as ECM-receptor interactions), and cell death (PI3K-Akt signaling pathway, apoptosis, TGF-beta signaling pathway, etc.) were identified as potential targets of GDFMD in the Model. Some hub genes and four modules were identified in the PPI network. The results of real-time quantitative PCR analysis were consistent with those of RNA-Seq analysis.Conclusions: We performed gene expression profiling of GDFMD-treated WD model mice using RNA-Seq analysis and found the genes, pathways, and processes effected by the treatment. Our study provides a theoretical basis to prevent liver fibrosis resulting from WD using GDFMD.

A significant portion of world population still fails to brush teeth daily. As a result, the majority of the global adult population is afflicted with chronic gingivitis, and if it is left untreated, some of them will eventually suffer from periodontitis.

Environmental exposure during earlier life stages can govern the assembly and development of gut microbiota, yet it is insufficiently understood. In this study, ex-germ-free mice were cohoused with distinct soil-microbiota (from desert, steppe, and forest) beddings within 60 days after birth and subsequently transferred to new soil beddings from 60 to 90th day. Using metagenomic shotgun sequencing, firstly, we found soil microbes from natural environments (birthplace) greatly influenced the gut community assembly in the housing experiment. About 27% microbial species and 12% functional components that associated with birthplaces at Day 60 were still discriminatory of birthplaces after transferring mice to new environments. Moreover, prior soil-exposure types are associated with the magnitude of temporal microbiome change due to environmental shifts. The appropriate soil-exposure (e.g., steppe) might help mice gut microbiome adapt to changing environments or host development. Our study demonstrated the continuous soil-exposure history earlier is associated with the gut microbiome individuality and development later.