Association of intra-operative red blood cell transfusion on the systemic immune index and recovery in patients undergoing cesarean section: a large propensity score-matched study.

BACKGROUND: Post-partum hemorrhage (PPH) is a leading cause of maternal death worldwide. However, the effect of blood transfusion in patients undergoing cesarean section remains unclear. MATERIALS AND METHODS: The analysis was based on the retrospective evaluation of the pre- and post-operative data for 1231 patients who underwent a cesarean section at our hospital between January 2016 and June 2020. Patients were classified into the blood transfusion group (BT) and the no blood transfusion group (NBT) based on their intra-operative blood transfusion status. RESULTS: After propensity score matching, 322 patients were included in both groups and between-group differences in length of hospital stay (LOS), perioperative systemic inflammation indicators, and post-operative complications were evaluated. The LOS was longer in the BT (median, 6.6 days) than the NBT (median, 4.2 days) group (P = 0.026). The post-operative complication rate was higher for the BT than NBT group, as follows: vomiting, 3.2% vs. 4.9%, P = 0.032; fever, 5.41% vs. 2.24%, P = 0.032; wound complications, 15.44% vs. 10.45%, P = 0.028; and intestinal obstructions, 5.88% vs. 2.75%, P = 0.034. Systemic inflammation indicators increased significantly, from the pre-operative baseline, for both groups at post-operative day (POD) 1 and POD3. On multivariate analysis, intra-operative blood transfusion was associated with a longer LOS (hazard ratio, 1.52; 95% confidence interval, 1.07-2.25). CONCLUSION: Intraoperative blood transfusion for cesarean section was associated with increased levels of systemic inflammation indicators, higher post-operative complication rates, and prolonged hospital stay.

Bone marrow adipogenic lineage precursors are the major regulator of bone resorption in adult mice.

Bone resorption by osteoclasts is a critical step in bone remodeling, a process important for maintaining bone homeostasis and repairing injured bone. We previously identified a bone marrow mesenchymal subpopulation, marrow adipogenic lineage precursors (MALPs), and showed that its production of RANKL stimulates bone resorption in young mice using Adipoq-Cre. To exclude developmental defects and to investigate the role of MALPs-derived RANKL in adult bone, we generated inducible reporter mice (Adipoq-CreER Tomato) and RANKL deficient mice (Adipoq-CreER RANKLflox/flox, iCKO). Single cell-RNA sequencing data analysis, lineage tracing, and in situ hybridization revealed that Adipoq+ cells contain not only MALPs but also late mesenchymal progenitors capable of osteogenic differentiation. However, RANKLmRNA was only detected in MALPs, but not in osteogenic cells. RANKL deficiency in MALPs induced at 3 months of age rapidly increased trabecular bone mass in long bones as well as vertebrae within 1 month due to diminished bone resorption but had no effect on the cortical bone. Ovariectomy (OVX) induced trabecular bone loss at both sites. RANKL depletion either before OVX or at 6 weeks post OVX protected and restored trabecular bone mass. Furthermore, bone healing after drill-hole injury was delayed in iCKO mice. Together, our findings demonstrate that MALPs play a dominant role in controlling trabecular bone resorption and that RANKL from MALPs is essential for trabecular bone turnover in adult bone homeostasis, postmenopausal bone loss, and injury repair.

The antidepressant effect of Shexiang Baoxin Pills on myocardial infarction rats with depression may be achieved through the inhibition of the NLRP3 inflammasome pathway.

BACKGROUND: Patients with myocardial infarction (MI) frequently experience a heightened incidence of depression, thereby increasing the risk of adverse cardiovascular events. Consequently, early detection and intervention in depressive symptoms among patients with MI are imperative. Shexiang Baoxin Pills (SBP), a Chinese patent medicine employed for the treatment of MI, exhibits diverse mechanisms targeting this condition. Nevertheless, its therapeutic efficacy on postmyocardial infarction depressive symptoms remains unclear. The aim of this study is to investigate the effectiveness and mechanism of SBP in managing depression during acute myocardial infarction (AMI). METHODS: A rat model combining MI and depression was established, and the rats were randomly divided into four groups: the model (MOD) group, SBP group, Fluoxetine (FLX) group, and Sham group. After 28 days of drug intervention, cardiac function was assessed using echocardiography while behavior was evaluated through sucrose preference test (SPT), forced swimming test (FST), and open-field test (OFT). Additionally, levels of inflammatory factors in serum and hippocampus were measured along with NLRP3 inflammasome-related protein expression via Western blotting and immunofluorescence. RESULTS: SBP can enhance cardiac function in rats with AMI and depression, while significantly ameliorating depressive-like behavior. Compared to the Sham group, levels of IL-1ß, IL-18, TNF-α, and other inflammatory factors were markedly elevated in the MOD group. However, expressions of these inflammatory factors were reduced to varying degrees following treatment with SBP or FLX. Analysis of NLRP3 inflammasome-related proteins in the hippocampus revealed a significant upregulation of IL-1ß, IL-18, NLRP3, ASC, caspase-1, and GSDMD in the MOD group; conversely, these measures were significantly attenuated after SBP intervention. CONCLUSION: We have observed a significant amelioration in depression-like behavior upon SBP administration during the treatment of AMI, suggesting that this effect may be attributed to the inhibition of NLRP3-mediated pyroptosis. (The main findings are summarized in the graphical abstract in the supplementary file.).

A reliable deep-learning-based method for alveolar bone quantification using a murine model of periodontitis and micro-computed tomography imaging.

OBJECTIVES: This study focuses on artificial intelligence (AI)-assisted analysis of alveolar bone for periodontitis in a mouse model with the aim to create an automatic deep-learning segmentation model that enables researchers to easily examine alveolar bone from micro-computed tomography (µCT) data without needing prior machine learning knowledge. METHODS: Ligature-induced experimental periodontitis was produced by placing a small-diameter silk sling ligature around the left maxillary second molar. At 4, 7, 9, or 14 days, the maxillary bone was harvested and processed with a µCT scanner (µCT-45, Scanco). Using Dragonfly (v2021.3), we developed a 3D deep learning model based on the U-Net AI deep learning engine for segmenting materials in complex images to measure alveolar bone volume (BV) and bone mineral density (BMD) while excluding the teeth from the measurements. RESULTS: This model generates 3D segmentation output for a selected region of interest with over 98 % accuracy on different formats of µCT data. BV on the ligature side gradually decreased from 0.87 mm3 to 0.50 mm3 on day 9 and then increased to 0.63 mm3 on day 14. The ligature side lost 4.6 % of BMD on day 4, 9.6 % on day 7, 17.7 % on day 9, and 21.1 % on day 14. CONCLUSIONS: This study developed an AI model that can be downloaded and easily applied, allowing researchers to assess metrics including BV, BMD, and trabecular bone thickness, while excluding teeth from the measurements of mouse alveolar bone. CLINICAL SIGNIFICANCE: This work offers an innovative, user-friendly automatic segmentation model that is fast, accurate, and reliable, demonstrating new potential uses of artificial intelligence (AI) in dentistry with great potential in diagnosing, treating, and prognosis of oral diseases.

Identification of MYCN non-amplified neuroblastoma subgroups points towards molecular signatures for precision prognosis and therapy stratification.

BACKGROUND: Despite the extensive study of MYCN-amplified neuroblastomas, there is a significant unmet clinical need in MYCN non-amplified cases. In particular, the extent of heterogeneity within the MYCN non-amplified population is unknown. METHODS: A total of 1566 samples from 16 datasets were identified in Gene Expression Omnibus (GEO) and ArrayExpress. Characterisation of the subtypes was analysed by ConsensusClusterPlus. Independent predictors for subgrouping were constructed from the single sample predictor based on the multiclassPairs package. Findings were verified using immunohistochemistry and CIBERSORTx analysis. RESULTS: We demonstrate that MYCN non-amplified neuroblastomas are heterogeneous and can be classified into 3 subgroups based on their transcriptional signatures. Within these groups, subgroup_2 has the worst prognosis and this group shows a 'MYCN' signature that is potentially induced by the overexpression of Aurora Kinase A (AURKA); whilst subgroup_3 is characterised by an 'inflamed' gene signature. The clinical implications of this subtype classification are significant, as each subtype demonstrates a unique prognosis and vulnerability to investigational therapies. A total of 420 genes were identified as independent subgroup predictors with average balanced accuracy of 0.93 and 0.84 for train and test datasets, respectively. CONCLUSION: We propose that transcriptional subtyping may enhance precision prognosis and therapy stratification for patients with MYCN non-amplified neuroblastomas.

A specific enterotype derived from gut microbiome of older individuals enables favorable responses to immune checkpoint blockade therapy.

Immunotherapy has revolutionized cancer treatment, but inconsistent responses persist. Our study delves into the intriguing phenomenon of enhanced immunotherapy sensitivity in older individuals with cancers. Through a meta-analysis encompassing 25 small-to-mid-sized trials of immune checkpoint blockade (ICB), we demonstrate that older individuals exhibit heightened responsiveness to ICB therapy. To understand the underlying mechanism, we reanalyze single-cell RNA sequencing (scRNA-seq) data from multiple studies and unveil distinct upregulation of exhausted and cytotoxic T cell markers within the tumor microenvironment (TME) of older patients. Recognizing the potential role of gut microbiota in modulating the efficacy of immunotherapy, we identify an aging-enriched enterotype linked to improved immunotherapy outcomes in older patients. Fecal microbiota transplantation experiments in mice confirm the therapeutic potential of the aging-enriched enterotype, enhancing treatment sensitivity and reshaping the TME. Our discoveries confront the prevailing paradox and provide encouraging paths for tailoring cancer immunotherapy strategies according to an individual's gut microbiome profile.

Gut microbiome for predicting immune checkpoint blockade-associated adverse events.

BACKGROUND: The impact of the gut microbiome on the initiation and intensity of immune-related adverse events (irAEs) prompted by immune checkpoint inhibitors (ICIs) is widely acknowledged. Nevertheless, there is inconsistency in the gut microbial associations with irAEs reported across various studies. METHODS: We performed a comprehensive analysis leveraging a dataset that included published microbiome data (n = 317) and in-house generated data from 16S rRNA and shotgun metagenome samples of irAEs (n = 115). We utilized a machine learning-based approach, specifically the Random Forest (RF) algorithm, to construct a microbiome-based classifier capable of distinguishing between non-irAEs and irAEs. Additionally, we conducted a comprehensive analysis, integrating transcriptome and metagenome profiling, to explore potential underlying mechanisms. RESULTS: We identified specific microbial species capable of distinguishing between patients experiencing irAEs and non-irAEs. The RF classifier, developed using 14 microbial features, demonstrated robust discriminatory power between non-irAEs and irAEs (AUC = 0.88). Moreover, the predictive score from our classifier exhibited significant discriminative capability for identifying non-irAEs in two independent cohorts. Our functional analysis revealed that the altered microbiome in non-irAEs was characterized by an increased menaquinone biosynthesis, accompanied by elevated expression of rate-limiting enzymes menH and menC. Targeted metabolomics analysis further highlighted a notably higher abundance of menaquinone in the serum of patients who did not develop irAEs compared to the irAEs group. CONCLUSIONS: Our study underscores the potential of microbial biomarkers for predicting the onset of irAEs and highlights menaquinone, a metabolite derived from the microbiome community, as a possible selective therapeutic agent for modulating the occurrence of irAEs.

LKB1 depletion-mediated epithelial-mesenchymal transition induces fibroblast activation in lung fibrosis.

The factors that determine fibrosis progression or normal tissue repair are largely unknown. We previously demonstrated that autophagy inhibition-mediated epithelial-mesenchymal transition (EMT) in human alveolar epithelial type II (ATII) cells augments local myofibroblast differentiation in pulmonary fibrosis by paracrine signalling. Here, we report that liver kinase B1 (LKB1) inactivation in ATII cells inhibits autophagy and induces EMT as a consequence. In IPF lungs, this is caused by downregulation of CAB39L, a key subunit within the LKB1 complex. 3D co-cultures of ATII cells and MRC5 lung fibroblasts coupled with RNA sequencing (RNA-seq) confirmed that paracrine signalling between LKB1-depleted ATII cells and fibroblasts augmented myofibroblast differentiation. Together these data suggest that reduced autophagy caused by LKB1 inhibition can induce EMT in ATII cells and contribute to fibrosis via aberrant epithelial-fibroblast crosstalk.

The effects of pks+ Escherichia coli and bile acid in colorectal tumorigenesis among people with cholelithiasis or cholecystectomy.

BACKGROUND AND AIM: Patients with cholelithiasis (CL) or cholecystectomy (CE) would have more chances of getting colorectal adenoma (CRA) or cancer (CRC). We aimed to figure out the effects of gut microbiota and bile acid on colorectal neoplasm in CL and CE patients. METHODS: This was a retrospective observational study that recruited 514 volunteers, including 199 people with normal gallbladders (normal), 152 CL, and 163 CE patients. Discovery cohort was established to explore the difference in gut microbiota through 16S rRNA and metagenomics sequencing. Validation cohort aimed to verify the results through quantitative polymerase chain reaction (qPCR). RESULTS: Significant enrichment of Escherichia coli was found in patients with cholelithiasis or cholecystectomy both in the discovery cohort (16S rRNA sequencing, PNormal-CL = 0.013, PNormal-CE = 0.042; metagenomics sequencing, PNormal-CE = 0.026) and validation cohort (PNormal-CL < 0.0001, PNormal-CE < 0.0001). Pks+ E. coli was found enriched in CL and CE patients through qPCR (in discovery cohort: PNormal-CE = 0.018; in validation cohort: PNormal-CL < 0.0001, PNormal-CE < 0.0001). The differences in bile acid metabolism were found both through Tax4Fun analysis of 16S rRNA sequencing (Ko00120, primary bile acid biosynthesis, PNormal-CE = 0.014; Ko00121, secondary bile acid biosynthesis, PNormal-CE = 0.010) and through metagenomics sequencing (map 00121, PNormal-CE = 0.026). The elevation of serum total bile acid of CE patients was also found in validation cohort (PNormal-CE < 0.0001). The level of serum total bile acid was associated with the relative abundance of pks+ E. coli (r = 0.1895, P = 0.0012). CONCLUSIONS: E. coli, especially pks+ species, was enriched in CL and CE patients. Pks+ E. coli and bile acid metabolism were found associated with CRA and CRC in people after cholecystectomy.

Disruption of CerS6-mediated sphingolipid metabolism by FTO deficiency aggravates ulcerative colitis.

BACKGROUND AND AIMS: Deregulation of RNA N6-methyladenosine (m6A) modification in intestinal epithelial cells (IECs) influences intestinal immune cells and leads to intestinal inflammation. We studied the function of fat mass-and obesity-associated protein (FTO), one of the m6A demethylases, in patients with ulcerative colitis (UC). METHODS: We analysed colon tissues of Ftoflox/flox; Villin-cre mice and their Ftoflox/flox littermates with dextran sulfate sodium (DSS) using real-time PCR and 16s rRNA sequencing. RNA and methylated RNA immunoprecipitation sequencing were used to analyse immunocytes and IECs. Macrophages were treated with conditioned medium of FTO-knockdown MODE-K cells or sphingosine-1-phosphate (S1P) and analysed for gene expression. Liquid chromatograph mass spectrometry identified C16-ceramide. RESULTS: FTO downregulation was identified in our in-house cohort and external cohorts of UC patients. Dysbiosis of gut microbiota, increased infiltration of proinflammatory macrophages, and enhanced differentiation of Th17 cells were observed in Ftoflox/flox;Villin-cre mice under DSS treatment. FTO deficiency resulted in an increase in m6A modification and a decrease in mRNA stability of CerS6, the gene encoding ceramide synthetase, leading to the downregulation of CerS6 and the accumulation of S1P in IECs. Subsequentially, the secretion of S1P by IECs triggered proinflammatory macrophages to secrete serum amyloid A protein 1/3, ultimately inducing Th17 cell differentiation. In addition, through bioinformatic analysis and experimental validation, we identified UC patients with lower FTO expression might respond better to vedolizumab treatment. CONCLUSIONS: FTO downregulation promoted UC by decreasing CerS6 expression, leading to increased S1P accumulation in IECs and aggravating colitis via m6A-dependent mechanisms. Lower FTO expression in UC patients may enhance their response to vedolizumab treatment.

Development and inter-laboratory validation of analytical methods for glufosinate and its two metabolites in foods of plant origin.

Glufosinate is widely used to control various weeds. Glufosinate and its main metabolites have become the focus of attention because of their high water solubility and persistence in aquatic systems. Quantification of the agrochemical product and its metabolite residues is essential for the safety of agricultural products. In this study, a highly specific, simple method was developed to directly determine glufosinate and its metabolite residues in 21 plant origin foods by liquid chromatography with tandem mass spectrometry (LC-MS/MS), and it was validated on 11 foods in five laboratories. Finally, the repeatability limit, reproducibility limit, and uncertainty of the method were calculated based on these validated data and used to support the more accurate detection results. Four different chromatographic columns were used to analyze three target compounds, and the anionic polar pesticide column showed the optimum separation and peak shape. Composition of the mobile phase, extraction solvent, and the clean-up procedure were optimized. The developed method was validated on 21 plant origin foods. The average recoveries were 74-115% for all matrices. The validation results of five laboratories showed this method had a good repeatability (RSDr < 9.5%) and reproducibility (RSDR < 18.9%). The method validation parameters met the requirements of guidance established by the European Union (EU) and China for pesticide residue analysis. This methodology can be used for a routine monitoring that performs well for glufosinate and its metabolite residues.

Role of IL-33-ST2 pathway in regulating inflammation: current evidence and future perspectives.

Interleukin (IL)-33 is an alarmin of the IL-1 superfamily localized to the nucleus of expressing cells, such as endothelial cells, epithelial cells, and fibroblasts. In response to cellular damage or stress, IL-33 is released and activates innate immune responses in some immune and structural cells via its receptor interleukin-1 receptor like-1 (IL-1RL1 or ST2). Recently, IL-33 has become a hot topic of research because of its role in pulmonary inflammation. The IL-33-ST2 signaling pathway plays a pro-inflammatory role by activating the type 2 inflammatory response, producing type 2 cytokines and chemokines. Elevated levels of IL-33 and ST2 have been observed in chronic pulmonary obstructive disease (COPD). Notably, IL-33 is present in COPD induced by cigarette smoke or acute inflammations. The role of IL-33 in sepsis is becoming increasingly prominent, and understanding its significance in the treatment of sepsis associated with high mortality is critical. In addition to its pro-inflammatory effects, the IL-33-ST2 axis appears to play a role in bacterial clearance and tissue repair. In this review, we focused on the role of the IL-33-ST2 axis in sepsis, asthma, and COPD and summarized the therapeutic targets associated with this axis, providing a basis for future treatment.

Microbiome and metabolome features in inflammatory bowel disease via multi-omics integration analyses across cohorts.

The perturbations of the gut microbiota and metabolites are closely associated with the progression of inflammatory bowel disease (IBD). However, inconsistent findings across studies impede a comprehensive understanding of their roles in IBD and their potential as reliable diagnostic biomarkers. To address this challenge, here we comprehensively analyze 9 metagenomic and 4 metabolomics cohorts of IBD from different populations. Through cross-cohort integrative analysis (CCIA), we identify a consistent characteristic of commensal gut microbiota. Especially, three bacteria, namely Asaccharobacter celatus, Gemmiger formicilis, and Erysipelatoclostridium ramosum, which are rarely reported in IBD. Metagenomic functional analysis reveals that essential gene of Two-component system pathway, linked to fecal calprotectin, are implicated in IBD. Metabolomics analysis shows 36 identified metabolites with significant differences, while the roles of these metabolites in IBD are still unknown. To further elucidate the relationship between gut microbiota and metabolites, we construct multi-omics biological correlation (MOBC) maps, which highlights gut microbial biotransformation deficiencies and significant alterations in aminoacyl-tRNA synthetases. Finally, we identify multi-omics biomarkers for IBD diagnosis, validated across multiple global cohorts (AUROC values ranging from 0.92 to 0.98). Our results offer valuable insights and a significant resource for developing mechanistic hypotheses on host-microbiome interactions in IBD.

Multi-kingdom gut microbiota analyses define bacterial-fungal interplay and microbial markers of pan-cancer immunotherapy across cohorts.

The effect of gut bacteria on the response to immune checkpoint inhibitors (ICIs) has been studied, but the relationship between fungi and ICI responses is not fully understood. Herein, 862 fecal metagenomes from 9 different cohorts were integrated for the identification of differentially abundant fungi and subsequent construction of random forest (RF) models to predict ICI responses. Fungal markers demonstrate excellent performance, with an average area under the curve (AUC) of 0.87. Their performance improves even further, reaching an average AUC of 0.89 when combined with bacterial markers. Higher enrichment of exhausted T cells is detected in responders, as predicted by fungal markers. Multi-kingdom network and functional analysis reveal that the fungus Schizosaccharomyces octosporus may ferment starch into short-chain fatty acids in responders. This study provides a fungal profile of the ICI response and the identification of multi-kingdom microbial markers with good performance that may improve the overall applicability of ICI therapy.

Contributions of deep learning to automated numerical modelling of the interaction of electric fields and cartilage tissue based on 3D images.

Electric fields find use in tissue engineering but also in sensor applications besides the broad classical application range. Accurate numerical models of electrical stimulation devices can pave the way for effective therapies in cartilage regeneration. To this end, the dielectric properties of the electrically stimulated tissue have to be known. However, knowledge of the dielectric properties is scarce. Electric field-based methods such as impedance spectroscopy enable determining the dielectric properties of tissue samples. To develop a detailed understanding of the interaction of the employed electric fields and the tissue, fine-grained numerical models based on tissue-specific 3D geometries are considered. A crucial ingredient in this approach is the automated generation of numerical models from biomedical images. In this work, we explore classical and artificial intelligence methods for volumetric image segmentation to generate model geometries. We find that deep learning, in particular the StarDist algorithm, permits fast and automatic model geometry and discretisation generation once a sufficient amount of training data is available. Our results suggest that already a small number of 3D images (23 images) is sufficient to achieve 80% accuracy on the test data. The proposed method enables the creation of high-quality meshes without the need for computer-aided design geometry post-processing. Particularly, the computational time for the geometrical model creation was reduced by half. Uncertainty quantification as well as a direct comparison between the deep learning and the classical approach reveal that the numerical results mainly depend on the cell volume. This result motivates further research into impedance sensors for tissue characterisation. The presented approach can significantly improve the accuracy and computational speed of image-based models of electrical stimulation for tissue engineering applications.

Increased risk of postpartum depression in women with lactational mastitis: a cross-sectional study.

Background: A high incidence of lactational mastitis mainly occurs during the first month of breastfeeding. It may cause severe pain, frustration, fatigue, stress, and breastfeeding concerns. However, few studies investigated the effects of lactational mastitis on postpartum depression. This study investigated the potential association between lactational mastitis and postpartum depression. Methods: We examined the associations of lactational mastitis with postpartum depression in 1,551 Chinese women. Lactational mastitis was diagnosed by breast specialists. The presence of depression symptoms was evaluated by the Edinburgh Postnatal Depression Scale (EPDS) and Patient Health Questionnaire 9 (PHQ9) at 6 weeks after delivery. Multiple linear regression analysis and multivariable log-binomial regression analysis were performed to estimate the association between lactational mastitis and postpartum depression. Results: Among the 1,551 mothers, 147 (9.5%) experienced lactational mastitis diagnosed by breast specialists during the postpartum period. Compared with women without lactational mastitis, the proportion of women with depression symptoms was significantly higher (38.1% vs. 27.4%, p = 0.008), and the risk of postpartum depression increased by 68% (RR = 1.68, 95% CI, 1.18, 2.40) in women who had experienced lactational mastitis. In addition, the risk of self-harm or suicidal ideation increased by 89% (RR = 1.89, 95% CI, 1.08, 3.29) in women who experienced lactational mastitis. In stratified analysis, the associations of lactational mastitis with postpartum depression appeared stronger among women aged ≥35 years, with maternal comorbidities, and who delivered a female neonate. Conclusion: The study results suggest that lactational mastitis is a risk factor for depression during the postpartum period. The impact of lactational mastitis on maternal mental health requires further attention. Clinical trial registration: chictr.org.cn, ChiCTR2000041519.

Commensal bacteria promote azathioprine therapy failure in inflammatory bowel disease via decreasing 6-mercaptopurine bioavailability.

Azathioprine (AZA) therapy failure, though not the primary cause, contributes to disease relapse and progression in inflammatory bowel disease (IBD). However, the role of gut microbiota in AZA therapy failure remains poorly understood. We found a high prevalence of Blautia wexlerae in patients with IBD with AZA therapy failure, associated with shorter disease flare survival time. Colonization of B. wexlerae increased inflammatory macrophages and compromised AZA's therapeutic efficacy in mice with intestinal colitis. B. wexlerae colonization reduced 6-mercaptopurine (6-MP) bioavailability by enhancing selenium-dependent xanthine dehydrogenase (sd-XDH) activity. The enzyme sd-XDH converts 6-MP into its inactive metabolite, 6-thioxanthine (6-TX), thereby impairing its ability to inhibit inflammation in mice. Supplementation with Bacillus (B.) subtilis enriched in hypoxanthine phosphoribosyltransferase (HPRT) effectively mitigated B. wexlerae-induced AZA treatment failure in mice with intestinal colitis. These findings emphasize the need for tailored management strategies based on B. wexlerae levels in patients with IBD.

Gut microbiota: Guardians of the female gut health.

The role of gut microbiota and their sex-specific differences in colorectal cancer remain to be explored. In the current issue of Cancer Cell, Li et al. discovered that estrogen facilitates the colonization of Carnobacterium maltaromaticum in the mouse gut and exerts its anti-colorectal cancer effects by increasing the production of vitamin D3.

Combined Application of Tank-mix Adjuvants, Mist Sprayer and Nano-selenium Promoted Pesticide Reduction and Enhanced Strawberry Quality.

In this paper, several technologies suitable for strawberry crops, such as armyworm boards, tank-mix adjuvants, mist sprayers combined with pesticide reduction, and biostimulant nano-selenium, were comprehensively applied and evaluated. The combined use of 60% etoxazole and bifenazate, bucket mixing additives, nano-selenium, and mist sprayers achieved an 86% prevention effect on red spiders. The prevention effect of pesticides according to the recommended dosage was 91%. Similarly, the disease index of strawberry powdery mildew in the green control group (60% carbendazim, bucket mixing additives, nano-selenium, and mist sprayer) decreased from 33.16 to 11.11, with a decrease of 22.05. The disease index of the control group decreased from 29.69 to 8.06, with a decrease of 21.63. Additionally, the combination of pesticide reduction and nano-selenium significantly improved the antioxidant activity and soluble sugar level of strawberry fruit and reduced water loss during storage. Therefore, the integrated application of green control technologies is beneficial for reducing the amount of chemical pesticides and improving their effectiveness, while enhancing the quality of strawberry fruits in disease and pest control.

Noninvasive predictive models based on lifestyle analysis and risk factors for early-onset colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) incidence has increased among patients aged <50 years. Exploring high-risk factors and screening high-risk populations may help lower early-onset CRC (EO-CRC) incidence. We developed noninvasive predictive models for EO-CRC and investigated its risk factors. METHODS: This retrospective multicenter study collected information on 1756 patients (811 patients with EO-CRC and 945 healthy controls) from two medical centers in China. Sociodemographic features, clinical symptoms, medical and family history, lifestyle, and dietary factors were measured. Patients from one cohort were randomly assigned (8:2) to two groups for model establishment and internal validation, and another independent cohort was used for external validation. Multivariable logistic regression, random forest, and eXtreme Gradient Boosting (XGBoost) were performed to establish noninvasive predictive models for EO-CRC. Some variables in the model influenced EO-CRC occurrence and were further analyzed. Multivariable logistic regression analysis yielded adjusted odd ratios (ORs) and 95% confidence intervals (CIs). RESULTS: All three models showed good performance, with areas under the receiver operator characteristic curves (AUCs) of 0.82, 0.84, and 0.82 in the internal and 0.78, 0.79, and 0.78 in the external validation cohorts, respectively. Consumption of sweet (OR 2.70, 95% CI 1.89-3.86, P < 0.001) and fried (OR 2.16, 95% CI 1.29-3.62, P < 0.001) foods ≥3 times per week was significantly associated with EO-CRC occurrence. CONCLUSION: We established noninvasive predictive models for EO-CRC and identified multiple nongenetic risk factors, especially sweet and fried foods. The model has good performance and can help predict the occurrence of EO-CRC in the Chinese population.