Association between triglyceride glucose-body mass index and long-term adverse outcomes of heart failure patients with coronary heart disease.

BACKGROUND: The triglyceride glucose-body mass index (TyG-BMI) is recognized as a reliable surrogate for evaluating insulin resistance and an effective predictor of cardiovascular disease. However, the link between TyG-BMI index and adverse outcomes in heart failure (HF) patients remains unclear. This study examines the correlation of the TyG-BMI index with long-term adverse outcomes in HF patients with coronary heart disease (CHD). METHODS: This single-center, prospective cohort study included 823 HF patients with CHD. The TyG-BMI index was calculated as follows: ln [fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI. To explore the association between the TyG-BMI index and the occurrences of all-cause mortality and HF rehospitalization, we utilized multivariate Cox regression models and restricted cubic splines with threshold analysis. RESULTS: Over a follow-up period of 9.4 years, 425 patients died, and 484 were rehospitalized due to HF. Threshold analysis revealed a significant reverse "J"-shaped relationship between the TyG-BMI index and all-cause mortality, indicating a decreased risk of all-cause mortality with higher TyG-BMI index values below 240.0 (adjusted model: HR 0.90, 95% CI 0.86-0.93; Log-likelihood ratio p = 0.003). A distinct "U"-shaped nonlinear relationship was observed with HF rehospitalization, with the inflection point at 228.56 (adjusted model: below: HR 0.95, 95% CI 0.91-0.98; above: HR 1.08, 95% CI 1.03-1.13; Log-likelihood ratio p < 0.001). CONCLUSIONS: This study reveals a nonlinear association between the TyG-BMI index and both all-cause mortality and HF rehospitalization in HF patients with CHD, positioning the TyG-BMI index as a significant prognostic marker in this population.

Effect and mechanism of C-terminal cysteine on the properties of HEV p222 protein.

Preliminary investigations have demonstrated that the cysteines located at the C-terminus of HEV ORF2 protein exhibits disulfide bonding capability during virus-like particles (VLPs) assembly. However, the effect and mechanism underlying the pairing of disulfide bonds formed by C627, C630, and C638 remains unclear. The p222 protein encompasses C-terminus and serves as a representative of HEV ORF2 to investigate the specific impacts of C627, C630, and C638. The three cysteines were subjected to site-directed mutagenesis and expressed in prokaryotes; Both the mutated proteins and p222 underwent polymerization except for p222A; Surprisingly, only p222 was observed as abundant spherical particles under transmission electron microscope (TEM); Stability and immunogenicity of the p222 exhibited higher than other mutated proteins; LC/MS/MS analysis identified four disulfide bonds in the p222. The novel findings suggest that the three cysteines contribute to structural and functional properties of ORF2 protein, highlighting the indispensability of each cysteine.

The added value of ultrasound imaging biomarkers to clinicopathological factors for the prediction of high-risk Oncotype DX recurrence scores in patients with breast cancer.

Background: The Oncotype DX (ODX) recurrence score (RS), a 21-gene assay, has been proven to recognize patients at high risk of recurrence (RS ≥26) who would benefit from chemotherapy. However, it has limited availability and high costs. Our study thus aimed to identify ultrasound (US) imaging biomarkers and develop a prediction model for identifying patients with a high ODX RS. Methods: In this retrospective study, consecutive patients with T1-3N0-1M0 breast cancer who were hormone receptor positive and human epidermal growth factor receptor 2 (HER2) negative who had an available ODX RS were reviewed. Patients treated from May 2012 and December 2015 were placed into a training cohort, and those treated from January 2016 to January 2017 were placed in a validation cohort. Clinicopathologic data were collected, and preoperative US scans were analyzed. Univariable and multivariable regression analyses were performed to evaluate the independent predictors for a high-risk of breast cancer in the training cohort, and a nomogram was developed and evaluated with the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA). Results: A total of 363 patients were in the training cohort and 160 in the validation cohort, with the proportion with a high RS (RS 26-100) being 14% and 13.1%, respectively. Echogenic halo, enhanced posterior echo, low level of progesterone receptor (PR), and high Ki-67 index were identified as independent risk factors for high RS (all P values <0.05). The nomogram was constructed based on the combined model, which showed a better discrimination ability than did the clinicopathological model [combined model: AUC =0.95, 95% confidence interval (CI): 0.93-0.97; clinicopathological model: AUC =0.89, 95% CI: 0.86-0.92; P=0.001] and greater clinical benefit according to DCA. Furthermore, the nomogram was found to be effective in the validation cohort (AUC =0.90, 95% CI: 0.84-0.94), especially in patients with stage T1N0M0 disease (AUC =0.91, 95% CI: 0.84-0.95). Conclusions: US features may serve as valuable imaging biomarkers for the prediction of high recurrence risk in patients with T1-3N0-1M0 breast cancer and hormone receptor (HR)-positive and HER2-negative status. A nomogram incorporating PR status, Ki-67 index, and US imaging biomarkers showed a good discrimination ability in the early selection of patients at high risk of recurrence, especially in those with stage T1N0M0 disease.

Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes.

AIM: To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes. METHODS: Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited. Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients' medical records. A hierarchical cluster analysis was performed. The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts. RESULTS: A total of 164 children (299 eyes) were divided into two clusters based on their ocular features. Cluster 1 (96 eyes) had a shorter axial length (mean±SD, 19.44±1.68 mm), a low prevalence of macular abnormalities (1.04%), and no retinal abnormalities or posterior cataracts. Cluster 2 (203 eyes) had a greater axial length (mean±SD, 20.42±2.10 mm) and a higher prevalence of macular abnormalities (8.37%), retinal abnormalities (98.52%), and posterior cataracts (4.93%). Compared with the eyes in Cluster 2 (57.14%), those in Cluster 1 (71.88%) had a 2.2 times higher chance of good best-corrected visual acuity [<0.7 logMAR; OR (95%CI), 2.20 (1.25-3.81); P=0.006]. CONCLUSION: This retrospective study categorizes congenital cataracts into two distinct clusters, each associated with a different likelihood of visual outcomes. This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit, thereby making strides toward precision medicine in the field of congenital cataracts.

Synthesis and characterisation of K2CO3-activated carbon produced from distilled spent grains for the adsorption of CO2.

Activated carbon was prepared from distilled spent grains (DSG) using K2CO3 activation and chitosan modification. The effects of activator dosage, activation temperature, and the incorporation of chitosan as a nitrogen source on the adsorption performance were studied in this paper. The activated carbons were characterised by scanning electron microscopy, X-ray photoelectron spectroscopy, and nitrogen and carbon dioxide gas adsorption. Under the optimal conditions, the BET-specific surface area, total pore volume, and microporous volume of the activated carbon were as high as 1142 m2/g, 0.62 cm3/g, and 0.40 cm3/g, respectively. Chitosan was used as the nitrogen source, and surface modification was carried out concurrently with the K2CO3 activation process. The results revealed a carbon dioxide adsorption capacity of 5.2 mmol/g at 273.15 K and 1 bar without a nitrogen source, which increased to 5.76 mmol/g after chitosan modification. The isosteric heat of adsorption of CO2 all exceed 20 kJ/mol, hinting at the coexistence of both physisorption and chemisorption. The adsorption behaviour of the DSG-based activated carbon can be well-described by the Freundlich model.

NREP, transcriptionally upregulated by HIF-1α, aggravates breast cancer cell growth and metastasis by promoting glycolysis.

Breast cancer (BC) poses a great threat to women's health. Neuronal regeneration related protein (NREP) is a multifunctional protein that is involved in embryonic development, regeneration, and human disease. However, the biological function of NREP in tumors is rarely reported and its role in BC remains unknown. Bioinformatics analysis showed that NREP is highly expressed and closely correlated with poor survival in BC patients. Under hypoxic conditions, NREP was upregulated in BC cells, and this promotion was reversed by hypoxia-inducible factor HIF-1α suppression. Luciferase reporter system and chromatin immunoprecipitation assays confirmed that HIF-1α directly binds to the promoter of NREP to increase the transcriptional activity of NREP. NREP suppression inhibited cell proliferation, arrested the cell cycle at the G1/S phase, and promoted apoptosis and caspase-3 activity in BC cells. Suppression of NREP decreased the tube formation ability of HUVECs. In addition, NREP downregulation showed an inhibition effect on cell migration, invasion, and EMT of BC cells. In NREP overexpressed cells, all these changes were reversed. In vivo, animal experiments also confirmed that NREP promotes BC tumor growth and metastasis. In addition, NREP promoted cellular glycolysis and enhanced the levels of glucose consumption, ATP, lactate production, and glucose transporters expression in NREP-overexpressed BC cells. In summary, our results demonstrated that NREP could be transcriptional activated by HIF-1α, which may aggravate BC tumor growth and metastasis by promoting cellular glycolysis. This result suggested that NREP may play an essential part in BC progression.

Robust Epileptic Seizure Detection Based on Biomedical Signals Using an Advanced Multi-View Deep Feature Learning Approach.

Epilepsy is a neurological disorder characterized by abnormal neuronal discharges that manifest in life-threatening seizures. These are often monitored via EEG signals, a key aspect of biomedical signal processing (BSP). Accurate epileptic seizure (ES) detection significantly depends on the precise identification of key EEG features, which requires a deep understanding of the data's intrinsic domain. Therefore, this study presents an Advanced Multi-View Deep Feature Learning (AMV-DFL) framework based on machine learning (ML) technology to enhance the detection of relevant EEG signal features for ES. Our method initially applies a fast Fourier transform (FFT) to EEG data for traditional frequency domain feature (TFD-F) extraction and directly incorporates time domain (TD) features from the raw EEG signals, establishing a comprehensive traditional multi-view feature (TMV-F). Deep features are subsequently extracted autonomously from optimal layers of one-dimensional convolutional neural networks (1D CNN), resulting in multi-view deep features (MV-DF) integrating both time and frequency domains. A multi-view forest (MV-F) is an interpretable rule-based advanced ML classifier used to construct a robust, generalized classification. Tree-based SHAP explainable artificial intelligence (T-XAI) is incorporated for interpreting and explaining the underlying rules. Experimental results confirm our method's superiority, surpassing models using TMV-FL and single-view deep features (SV-DF) by 4% and outperforming other state-of-the-art methods by an average of 3% in classification accuracy. The AMV-DFL approach aids clinicians in identifying EEG features indicative of ES, potentially discovering novel biomarkers, and improving diagnostic capabilities in epilepsy management.

Assessment of the impact of residual tumors at different sites post-neoadjuvant chemotherapy on prognosis in breast cancer patients and development of a disease-free survival prediction model.

Background: Residual disease after neoadjuvant chemotherapy (NAC) in breast cancer patients predicts worse outcomes than pathological complete response. Differing prognostic impacts based on the anatomical site of residual tumors are not well studied. Objectives: The study aims to assess disease-free survival (DFS) in breast cancer patients with different residual tumor sites following NAC and to develop a nomogram for predicting 1- to 3-year DFS in these patients. Design: A retrospective cohort study. Methods: Retrospective analysis of 953 lymph node-positive breast cancer patients with residual disease post-NAC. Patients were categorized into three groups: residual disease in breast (RDB), residual disease in lymph nodes (RDN), and residual disease in both (RDBN). DFS compared among groups. Patients were divided into a training set and a validation set in a 7:3 ratio. Prognostic factors for DFS were analyzed to develop a nomogram prediction model. Results: RDB patients had superior 3-year DFS of 94.6% versus 85.2% for RDN and 81.8% for RDBN (p < 0.0001). Clinical T stage, N stage, molecular subtype, and postoperative pN stage were independently associated with DFS on both univariate and multivariate analyses. Nomogram integrating clinical tumor-node-metastasis (TNM) stage, molecular subtype, pathological response demonstrated good discrimination (C-index 0.748 training, 0.796 validation cohort), and calibration. Conclusion: The location of residual disease has prognostic implications, with nodal residuals predicting poorer DFS. The validated nomogram enables personalized DFS prediction to guide treatment decisions.

Understanding the impact of residual tumor location on prognosis after breast cancer treatment After receiving neoadjuvant chemotherapy, a treatment to shrink tumors before surgery, some breast cancer patients may still have residual tumor cells. Our study focuses on how the location of these remaining tumors ­ whether in the breast, lymph nodes, or both ­ affects the likelihood of the cancer not returning within the next 1 to 3 years. This likelihood is known as 'disease-free survival' (DFS). We analyzed data from 953 breast cancer patients who underwent neoadjuvant chemotherapy and still had residual tumors. By comparing DFS among patients with tumors remaining in different locations, we discovered that the specific location of the residual tumor significantly impacts the patient's long-term health and recovery. Additionally, we developed a predictive tool called a 'nomogram' to help doctors and patients assess the risk of cancer recurrence in the next 1 to 3 years. This tool considers various factors such as the size and type of the tumor, as well as the location and extent of the residual tumor after chemotherapy. Our research offers new insights into understanding the risk of recurrence after breast cancer treatment. This work not only enhances our comprehension of breast cancer management but also aids in devising more personalized and effective treatment strategies for patients in the future.

The use of longitudinal CT-based radiomics and clinicopathological features predicts the pathological complete response of metastasized axillary lymph nodes in breast cancer.

BACKGROUND: Accurate assessment of axillary status after neoadjuvant therapy for breast cancer patients with axillary lymph node metastasis is important for the selection of appropriate subsequent axillary treatment decisions. Our objectives were to accurately predict whether the breast cancer patients with axillary lymph node metastases could achieve axillary pathological complete response (pCR). METHODS: We collected imaging data to extract longitudinal CT image features before and after neoadjuvant chemotherapy (NAC), analyzed the correlation between radiomics and clinicopathological features, and developed models to predict whether patients with axillary lymph node metastasis can achieve axillary pCR after NAC. The clinical utility of the models was determined via decision curve analysis (DCA). Subgroup analyses were also performed. Then, a nomogram was developed based on the model with the best predictive efficiency and clinical utility and was validated using the calibration plots. RESULTS: A total of 549 breast cancer patients with metastasized axillary lymph nodes were enrolled in this study. 42 independent radiomics features were selected from LASSO regression to construct a logistic regression model with clinicopathological features (LR radiomics-clinical combined model). The AUC of the LR radiomics-clinical combined model prediction performance was 0.861 in the training set and 0.891 in the testing set. For the HR + /HER2 - , HER2 + , and Triple negative subtype, the LR radiomics-clinical combined model yields the best prediction AUCs of 0.756, 0.812, and 0.928 in training sets, and AUCs of 0.757, 0.777 and 0.838 in testing sets, respectively. CONCLUSIONS: The combination of radiomics features and clinicopathological characteristics can effectively predict axillary pCR status in NAC breast cancer patients.

Why do people always want more? Perceived economic inequality leads people to be greedy by enhancing relative deprivation.

Greedy phenomena have dramatically increased in societies. However, despite the universality of greedy behaviour, empirical research on the causes of greed is scarce. In this context, we propose that perceived economic inequality may be an important factor influencing greed. Study 1 provided primary evidence of a positive relationship between perceived economic inequality and greed, based on data from a large-scale social survey (CFPS 2018, N = 14,317). Employing well-established questionnaires, Study 2A (N = 200) and Study 2B (N = 399) revealed that perceived economic inequality positively predicts greed, with relative deprivation playing a mediating role. Study 3A (N = 200) and Study 3B (N = 200) manipulated perceived economic inequality to provide causal evidence of its effects on greed and to replicate the mediating effect of relative deprivation. Finally, Study 4 (N = 372), using a blockage manipulation design, showed that the effect of perceived economic inequality on greed significantly decreases when relative deprivation is suppressed. In summary, the results of these six studies consistently suggest that perceived economic inequality positively affects greed and that this effect is mediated by relative deprivation.

Prognostic value of growth differentiation factor-15 in heart failure among whole ejection fraction phenotypes.

AIMS: The utility of growth differentiation factor-15 (GDF-15) in predicting long-term adverse outcomes in heart failure (HF) patients is not well established. This study explored the relationship between GDF-15 levels and adverse outcomes in HF patients across various ejection fraction (EF) phenotypes associated with coronary heart disease (CHD) and evaluated the added prognostic value of incorporating GDF-15 into the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score-based model. METHODS AND RESULTS: This single-centre cohort study included 823 HF patients, categorized into 230 (27.9%) reduced EF (HFrEF), 271 (32.9%) mid-range EF (HFmrEF), and 322 (39.1%) preserved EF (HFpEF) groups. The median age was 68.0 years (range: 56.0-77.0), and 245 (29.8%) were females. Compared with the HFrEF and HFmrEF groups, the HFpEF group had a higher GDF-15 concentration (P = 0.002) and a higher MAGGIC risk score (P < 0.001). We examined the associations between GDF-15 levels and the risks of all-cause mortality and HF rehospitalization using Cox regression models. The C-index, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) metrics were employed to assess the incremental prognostic value. During the 9.4 year follow-up period, 425 patients died, and 484 were rehospitalized due to HF. Multivariate Cox regression analysis revealed that elevated GDF-15 levels were significantly associated with an increased risk of all-cause mortality [hazard ratio (HR) = 1.36, 95% confidence interval (CI): 1.20-1.54; P < 0.001] and HF rehospitalization (HR = 1.75, 95% CI: 1.57-1.95; P < 0.001) across all HF phenotypes. This association remained significant when GDF-15 was treated as a categorical variable (high GDF-15 group: all-cause death: HR = 1.73, 95% CI: 1.40-2.14; P < 0.001; HF rehospitalization: HR = 3.37, 95% CI: 2.73-4.15; P < 0.001). Inclusion of GDF-15 in the MAGGIC risk score-based model provided additional prognostic value for all HF patients (Δ C-index = 0.021, 95% CI: 0.002-0.041; IDI = 0.011, 95% CI: 0.001-0.025; continuous NRI = 0.489, 95% CI: 0.174-0.629) and HF rehospitalization (Δ C-index = 0.034, 95% CI: 0.005-0.063; IDI = 0.021, 95% CI: 0.007-0.032; continuous NRI = 0.307, 95% CI: 0.147-0.548), particularly in the HFpEF subgroup. CONCLUSIONS: GDF-15 is identified as an independent risk factor for adverse outcomes in HF patients across the entire EF spectrum in the context of CHD. Integrating GDF-15 into the MAGGIC risk score-based model enhances its prognostic capability for adverse outcomes in the general HF population. This incremental prognostic effect was observed specifically in the HFpEF subgroup and not in other subgroups.

RUNX1-BMP2 promotes vasculogenic mimicry in laryngeal squamous cell carcinoma via activation of the PI3K-AKT signaling pathway.

BACKGROUND: Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignant tumors of the head and neck. Vasculogenic mimicry (VM) is crucial for tumor growth and metastasis and refers to the formation of fluid channels by invasive tumor cells rather than endothelial cells. However, the regulatory mechanisms underlying VM during the malignant progression of LSCC remain largely unknown. METHODS: Gene expression and clinical data for LSCC were obtained from the TCGA and Gene GEO (GSE27020) databases. A risk prediction model associated with VM was established using LASSO and Cox regression analyses. Based on their risk scores, patients with LSCC were categorized into high- and low-risk groups. The disparities in immune infiltration, tumor mutational burden (TMB), and functional enrichment between these two groups were examined. The core genes in LSCC were identified using the machine learning (SVM-RFE) and WGCNA algorithms. Subsequently, the involvement of bone morphogenetic protein 2 (BMP2) in VM and metastasis was investigated both in vitro and in vivo. To elucidate the downstream signaling pathways regulated by BMP2, western blotting was performed. Additionally, ChIP experiments were employed to identify the key transcription factors responsible for modulating the expression of BMP2. RESULTS: We established a new precise prognostic model for LSCC related to VM based on three genes: BMP2, EPO, and AGPS. The ROC curves from both TCGA and GSE27020 validation cohorts demonstrated precision survival prediction capabilities, with the nomogram showing some net clinical benefit. Multiple algorithm analyses indicated BMP2 as a potential core gene. Further experiments suggested that BMP2 promotes VM and metastasis in LSCC. The malignant progression of LSCC is promoted by BMP2 via the activation of the PI3K-AKT signaling pathway, with the high expression of BMP2 in LSCC resulting from its transcriptional activation by runt-related transcription factor 1 (RUNX1). CONCLUSION: BMP2 predicts poor prognosis in LSCC, promotes LSCC VM and metastasis through the PI3K-AKT signaling pathway, and is transcriptionally regulated by RUNX1. BMP2 may be a novel, precise, diagnostic, and therapeutic biomarker of LSCC.

ENO1 promotes trophoblast invasion regulated by E2F8 in recurrent miscarriage.

Recurrent miscarriage (RM) is related to the dysfunction of extravillous trophoblast cells (EVTs), but the comprehensive mechanisms remain largely unexplored. We analyzed single-cell RNA sequencing (scRNA-seq), bulk RNA sequencing and microarray datasets obtained from Gene Expression Omnibus (GEO) database to explore the hub genes in the mechanisms of RM. We identified 1724 differentially expressed genes (DEGs) in EVTs from the RM, and they were all expressed along the trajectory of EVTs. These DEGs were associated with hypoxia and glucose metabolism. Single-cell Regulatory Network Inference and Clustering (SCENIC) analysis revealed that E2F transcription factor (E2F) 8 (E2F8) was a key transcription factor for these DEGs. And the expression of ENO1 can be positively regulated by E2F8 via RNA sequencing analysis. Subsequently, we performed immunofluorescence assay (IF), plasmid transfection, western blotting, chromatin immunoprecipitation (ChIP), real-time quantitative polymerase chain reaction (qRT-PCR), and transwell assays for validation experiments. We found that the expression of alpha-Enolase 1 (ENO1) was lower in the placentas of RM. Importantly, E2F8 can transcriptionally regulate the expression of ENO1 to promote the invasion of trophoblast cells by inhibiting secreted frizzled-related protein 1/4 (SFRP1/4) to activate Wnt signaling pathway. Our results suggest that ENO1 can promote trophoblast invasion via an E2F8-dependent manner, highlighting a potential novel target for the physiological mechanisms of RM.

STING-dependent trained immunity contributes to host defense against Clostridium perfringens infection via mTOR signaling.

Clostridium perfringens (C. perfringens) infection is recognized as one of the most challenging issues threatening food safety and perplexing agricultural development. To date, the molecular mechanisms of the interactions between C. perfringens and the host remain poorly understood. Here, we show that stimulator of interferon genes (STING)-dependent trained immunity protected against C. perfringens infection through mTOR signaling. Heat-killed Candida albicans (HKCA) training elicited elevated TNF-α and IL-6 production after LPS restimulation in mouse peritoneal macrophages (PM). Although HKCA-trained PM produced decreased levels of TNF-α and IL-6, the importance of trained immunity was demonstrated by the fact that HKCA training resulted in enhanced bacterial phagocytic ability and clearance in vivo and in vitro during C. perfringens infection. Interestingly, HKCA training resulted in the activation of STING signaling. We further demonstrate that STING agonist DMXAA is a strong inducer of trained immunity and conferred host resistance to C. perfringens infection in PM. Importantly, corresponding to higher bacterial burden, reduction in cytokine secretion, phagocytosis, and bacterial killing were shown in the absence of STING after HKCA training. Meanwhile, the high expression levels of AKT/mTOR/HIF1α were indeed accompanied by an activated STING signaling under HKCA or DMXAA training. Moreover, inhibiting mTOR signaling with rapamycin dampened the trained response to LPS and C. perfringens challenge in wild-type (WT) PM after HKCA training. Furthermore, STING­deficient PM presented decreased levels of mTOR signaling-related proteins. Altogether, these results support STING involvement in trained immunity which protects against C. perfringens infection via mTOR signaling.

Targeted axillary dissection after neoadjuvant chemotherapy for highly selective patients with initial cN1 breast cancer: A single-center prospective trial.

BACKGROUND: Sentinel lymph node (SLN) biopsy is gradually accepted as the standard of care in breast cancer patients with down-staged axillary disease after neoadjuvant chemotherapy (NAC). However, it is still difficult to precisely define pre-NAC clinical node-positive (cN1) and post-NAC clinical node-negative (ycN0). This prospective single-center trial was designed to evaluate the feasibility and accuracy of standard targeted axillary dissection (TAD) after NAC in highly selective pre-NAC cN1 patients (not considering ultrasound-based axillary ycN staging). METHODS: This prospective trial included patients with initial pre-NAC cT1-3N1M0 invasive breast cancer but with a rigorous definition of cN1 from the Affiliated Cancer Hospital of Zhengzhou University. When NAC was effective (including complete and partial responses) and preoperative axillary palpation was negative, preoperative ultrasound-based axillary staging was not considered, and all patients underwent TAD followed by axillary lymph node (LN) dissection. The detection rate (DR) and false-negative rate (FNR) of TAD were calculated. RESULTS: A total of 82 patients were included, and 77 of them were eligible for data analysis. The DR for TAD was 94.8% (73/77). There were 26 patients with one abnormal LN at the time of diagnosis based on ultrasound, 45 patients with two, and 2 patients with three. One patient had one TAD LN, four patients had two TAD LNs, and 68 patients had three or more TAD LNs. Preoperative axillary palpation yielded negative results for all 73 patients who successfully underwent TAD. Preoperative ultrasound-based ycN0 and ycN+ conditions were detected for 52 and 21 cases, respectively. The FNR was 7.4% (2/27) for standard TAD (≥3 SLNs), which was lower than that of all successful TAD (≥1 SLN; 10.0%, 3/30). CONCLUSIONS: In rigorously defined pre-NAC cN1 breast cancer patients, standard TAD is feasible for those with negative axillary palpation after NAC, and FNR is also less than 10%. REGISTRATION: chictr.org.cn, ChiCTR2100049093.

Identification and biological characteristics of Enterococcus casseliflavus TN-47 isolated from Monochamus alternatus.

With the widespread use of antibiotics, the incidence of antibiotic resistance in microorganisms has increased. Monochamus alternatus is a trunk borer of pine trees. This study aimed to investigate the in vitro antimicrobial and biological characteristics of Enterococcus casseliflavus TN-47 (PP411196), isolated from the gastrointestinal tract of M. alternatus in Jilin Province, PR China. Among 13 isolates obtained from the insects, five were preliminarily screened for antimicrobial activity. E. casseliflavus TN-47, which exhibited the strongest antimicrobial activity, was identified. E. casseliflavus TN-47 possessed antimicrobial activity against Staphylococcus aureus USA300 and Salmonella enterica serovar Pullorum ATCC 19945. Furthermore, E. casseliflavus TN-47 was sensitive to tetracyclines, penicillins (ampicillin, carbenicillin, and piperacillin), quinolones and nitrofuran antibiotics, and resistant to certain beta-lactam antibiotics (oxacillin, cefradine and cephalexin), macrolide antibiotics, sulfonamides and aminoglycosides. E. casseliflavus TN-47 could tolerate low pH and pepsin-rich conditions in the stomach and grow in the presence of bile acids. E. casseliflavus TN-47 retained its strong auto-aggregating ability and hydrophobicity. This strain did not exhibit any haemolytic activity. These results indicate that E. casseliflavus TN-47 has potential as a probiotic. This study provides a theoretical foundation for the future applications of E. casseliflavus TN-47 and its secondary metabolites in animal nutrition and feed.

Bacillus coagulans regulates gut microbiota and ameliorates the alcoholic-associated liver disease in mice.

Introduction: Alcoholic-associated liver diseases (ALD) are now widespread issues worldwide. Alcoholic-induced chronic dysbiosis of the gut microbiota is one of the factors in the pathophysiology of ALD. Methods: In this work, we employed a chronic-binge ethanol feeding mice model, as described in a previous report. Results: Our findings demonstrate that hepatic inflammatory injury damage and accumulation of fat can be effectively reduced in mice with ALD by altering the gut microbiota utilizing Bacillus coagulans. Treatment with B. coagulans significantly modulates the levels of TNF-α, IL-1ß, and IL-22 cytokines while maintaining tight junction proteins and mucin protein expressions to support intestinal barrier function restoration. Treatment with B. coagulans also alters the composition of the gut microbiota and increases the production of short-chain fatty acids (SCFAs). Discussion: This is mostly due to B. coagulans promotes the growth of bacteria that produce SCFAs, such as Ruminococcus species and Akkermansia, while inhibiting the growth of pathogenic bacteria like Escherichia Shigella. Moreover, treatment with B. coagulans causes levels of 2-Ketobutyric acid, ketoleucine, and indoleacetic acid increase while homovanillic acid and 3'-O-Methylguanosine metabolites decrease significantly. This study facilitates the development of therapeutic and preventive strategies for ALD using lactic acid bacteria.

Dihydroartemisinin is an inhibitor of trained immunity through Akt/mTOR/HIF1α signaling pathway.

Trained immunity is mechanistically defined as the metabolically and epigenetically mediated long-term functional adaptation of the innate immune system, characterized by a heightened response to a secondary stimulation. Given appropriate activation, trained immunity represents an attractive anti-infective therapeutic target. Nevertheless, excessive immune response and subsequent inflammatory cascades may contribute to pathological tissue damage, indicating that the negative impacts of trained immunity appear to be significant. In this study, we show that innate immune responses such as the production of extracellular traps, pro-inflammatory cytokines, and autophagy-related proteins were markedly augmented in trained BMDMs. Furthermore, heat-killed C. albicans priming promotes the activation of the AIM2 inflammasome, and AIM2-/- mice exhibit impaired memory response induced by heat-killed C. albicans. Therefore, we establish that the AIM2 inflammasome is involved in trained immunity and emerges as a promising therapeutic target for potentially deleterious effects. Dihydroartemisinin can inhibit the memory response induced by heat-killed C. albicans through modulation of mTOR signaling and the AIM2 inflammasome. The findings suggest that dihydroartemisinin can reduce the induction of trained immunity by heat-killed C. albicans in C57BL/6 mice. Dihydroartemisinin is one such therapeutic intervention that has the potential to treat of diseases characterized by excessive trained immunity.

Metabolomic profiling of the aqueous humor in patients with pediatric cataract.

Pediatric cataract, including congenital and developmental cataract, is a kind of pediatric vision-threatening disease with extensive phenotypic heterogeneity and multiple mechanisms. We aimed to investigate the metabolite profile of aqueous humor (AH) in patients with pediatric cataracts, and identify underlying mutual correlations between differential metabolites. Metabolomic profiles of AH were analyzed and compared between pediatric cataract patients (n = 33) and age-related cataract patients without metabolic diseases (n = 29), using global untargeted metabolomics with ultra-high-performance liquid chromatography tandem mass spectrometry. Principal component analysis, partial least squares discriminant analysis and heat map were applied. Enriched pathway analysis was conducted using Kyoto Encyclopedia of Genes and Genomes. Receiver-operating characteristic (ROC) analyses were employed to select potential biomarkers. A total of 318 metabolites were identified, of which 54 differential metabolites (25 upregulated and 29 downregulated) were detected in pediatric cataract group compared with controls (variable importance of projection >1.0, fold change ≥1.5 or ≤ 0.667 and P < 0.05). A significant accumulation of N-Acetyl-Dl-glutamic acid was observed in pediatric cataract group. The differential metabolites were mainly enriched in histidine metabolism (increased L-Histidine and decreased 1-Methylhistamine) and the tryptophan metabolism (increased N-Formylkynurenine and L-Kynurenine). 5-Aminosalicylic acid showed strong positive mutual inter-correlation with L-Tyrosinemethylester and N,N-Diethylethanolamine, both of which were down-regulated in pediatric cataract group. The ROC analysis implied 11 metabolites served as potential biomarkers for pediatric cataract patients (all area under the ROC curve ≥0.900). These results illustrated novel potential metabolites and metabolic pathways in pediatric cataract, which provides new insights into the pathophysiology of pediatric cataract.

Predicting Marfan Syndrome in Children With Congenital Ectopia Lentis: Development and Validation of a Nomogram.

Purpose: To derive an effective nomogram for predicting Marfan syndrome (MFS) in children with congenital ectopia lentis (CEL) using regularly collected data. Methods: Diagnostic standards (Ghent nosology) and genetic test were applied in all patients with CEL to determine the presence or absence of MFS. Three potential MFS predictors were tested and chosen to build a prediction model using logistic regression. The predictive performance of the nomogram was validated internally through time-dependent receiver operating characteristic curves, calibration curves, and decision curve analysis. Results: Eyes from 103 patients under 20 years old and with CEL were enrolled in this study. Z score of body mass index (odds ratio [OR] = 0.659; 95% confidence interval [CI], 0.453-0.958), corneal curvature radius (OR = 3.397; 95% CI, 1.829-6.307), and aortic root diameter (OR = 2.342; 95% CI, 1.403-3.911) were identified as predictors of MFS. The combination of the above predictors shows good predictive ability, as indicated by area under the curve of 0.889 (95% CI, 0.826-0.953). The calibration curves showed good agreement between the prediction of the nomogram and the actual observations. In addition, decision curve analysis showed that the nomogram was clinically useful and had better discriminatory power in identifying patients with MFS. For better individual prediction, an online MFS calculator was created. Conclusions: The nomogram provides accurate and individualized prediction of MFS in children with CEL who cannot be identified with the Ghent criteria, enabling clinicians to personalize treatment plans and improve MFS outcomes. Translational Relevance: The prediction model may help clinicians identify MFS in its early stages, which could reduce the likelihood of developing severe symptoms and improve MFS outcomes.