Nesfatin-1 inhibits cerebral aneurysms by activating Nrf2 and inhibiting NF-κB signaling.

AIMS: Cerebral aneurysm (CA) has been considered one of the most common cerebrovascular diseases, affecting millions of people worldwide. A therapeutic agent is currently missing for the treatment of CA. Nesfatin-1 (Nes-1) is an 82-amino acid adipokine which possesses a wide range of biological functions. However, the physiological function of Nes-1 in CA is still unknown. Here, we aimed to assess the preventive effects of Nes-1 in the pathological development of CA and elucidate the mechanisms behind this. METHODS: We used an elastase-induced CA model, accompanied by a high-salt diet to induce hypertension. Additionally, diverse experimental techniques, including Verhoeff-Van Gieson staining, real time PCR, enzyme-linked immuno sorbent assay (ELISA), and immunofluorescence staining, were employed to assess CA formation, gene and protein expression, as well as the macrophage infiltration. RESULTS: Our results indicate that administration of Nes-1 significantly decreased the aneurysm size. Additionally, Nes-1 prevented inflammatory response by inhibiting the expression of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and monocyte chemoattractant protein 1 (MCP-1) at both the mRNA and protein levels in the Circle of Willis (COW) region. Also, the increased levels of matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9) in the COW region were reduced by Nes-1. We found that Nes-1 administration suppressed the invasion of macrophages. Mechanistically, Nes-1 activated Nrf-2 by promoting its nuclear translocation but prevented the activation of the IκBα/NF-κB signaling pathway. CONCLUSION: These findings suggest that Nes-1 might be used as a promising agent for the prevention of CA.

Visible Light-Activated Room Temperature NO2 Gas Sensing Based on the In2O3@ZnO Heterostructure with a Hollow Microtube Structure.

The persistent challenge of poor recovery characteristics of NO2 sensors operated at room temperature remains significant. However, the development of In2O3-based gas sensing materials provides a promising approach to accelerate response and recovery for sub-ppm of NO2 detection at room temperature. Herein, we propose a simple two-step method to synthesize a one-dimensional (1D) In2O3@ZnO heterostructure material with hollow microtubes, by coupling metal-organic frameworks (MOFs) (MIL-68 (In)) and zinc ions. Meanwhile, the In2O3@ZnO composite-based gas sensor exhibits superior sensitivity performance to NO2 under visible light activation. The response value to 5 ppm of NO2 at room temperature is as high as 1800, which is 35 times higher than that of the pure In2O3-based sensor. Additionally, the gas sensor based on the In2O3@ZnO heterostructure demonstrates a significantly reduced response/recovery time of 30 s/67 s compared to the sensor based on pure In2O3 (74 s/235 s). The outstanding gas sensing properties of the In2O3@ZnO heterostructure-based sensors can be attributed to the enhanced photogenerated charge separation efficiency resulting from the heterostructure effect, and the improved receptor function toward NO2, which can increase the reactive sites and gas adsorption capacity. In summary, this work proposes a low-cost and efficient method to synthesize a 1D heterostructure material with microtube structures, which can serve as a fundamental technique for developing high-performance room-temperature gas sensors.

Solar evaporation of liquid marbles with Fe3O4/CNT hybrid nanostructures.

HYPOTHESIS: Through the rational design of nanomaterial composites, broadband light harvesting and good thermal insulation can be achieved simultaneously to improve the efficiency of water evaporation. EXPERIMENT: Solar evaporation experiments were carried out on liquid marbles (LMs) coated with Fe3O4 nanoparticles, carbon nanotubes (CNTs) and hybrid nanomaterials (Fe3O4/CNTs) with different mass ratios of 2:1, 1:1 and 1:2. FINDING: The results showed that the mixture of Fe3O4/CNTs enhances the light harvesting ability and solar interfacial evaporation performance. Fe3O4/CNT-LM at the mass ratio of 2:1 case provides the highest evaporation rate of 11.03 µg/s, which is about 1.22 and 1.34 times higher than that of Fe3O4 and CNT, respectively. This high performance is mainly due to the synergistic effect between Fe3O4 nanoparticles and CNTs, as the hybrid nanostructure significantly improves the both photothermal conversion and heat localization capability. Numerical simulation further supports that the composite can concentrate the electromagnetic field and heat at the phase-change interface. This leads to a rapid evaporation of the boundary region. This study provides a novel approach to a three-dimensional interface by assembling nanomaterials on the drop surface to enhance evaporation, which may have far-reaching implications for seawater desalination.

The difference of functional MR imaging in evaluating outcome of patients with diffuse and compact brain arteriovenous malformation.

Microsurgical resection is an effective method to treat brain arteriovenous malformations (BAVMs). Functional magnetic resonance imaging (fMRI) can evaluate the spatial relationship of nidus and eloquent. Diffuse BAVMs are related to poor outcomes postoperatively. The role of fMRI in evaluating outcomes in patients with different nidus types remains unclear. BAVM patients received microsurgical resection were included from a prospective, multicenter cohort study. All patients underwent fMRI evaluation preoperatively and were regularly followed up postoperatively. Diffuse BAVM is radiologically identified as nidus containing normal brain tissue interspersing between malformed vessels. Lesion-to-eloquent distance (LED) was calculated based on the relationship between nidus and eloquent. The primary outcome was 180-day unfavorable neurological status postoperatively. The risk of primary outcome was investigated within different BAVM nidus types. The LED's performance to predict poor outcome was evaluated using area under curve (AUC). 346 BAVM patients were included in this study. 93 (26.9%) patients were found to have a 180-day unfavorable outcome. Multivariate logistic analysis demonstrated LED (odd ratio [OR], 0.44; 0.34-0.57; P < 0.001) and mRS at admission (OR, 2.59; 1.90-3.54; P < 0.001) as factors of unfavorable outcome. Subgroup analysis showed LED and mRS at admission as factors of unfavorable outcome for patients with compact BAVMs (all P < 0.05), but not for patients with diffuse BAVMs. Subsequent analysis showed that LED performed poorly to predict the unfavorable outcome for patients with diffuse BAVMs, compared with patients with compact BAVMs (AUC as 0.69 vs. 0.86, P < 0.05). A larger cutoff value of LED to unfavorable outcome was found in patients with diffuse BAVMs (15 mm) compared with patients with compact BAVMs (4.7 mm). Usage of LED to evaluate postoperative outcome of patients with diffuse BAVMs differs from its use in patients with compact BAVMs. Specific assessment strategy considering BAVM nidus types could help improve patients' outcome. MITASREAVM cohort (unique identifier: NCT02868008, https://clinicaltrials.gov/study/NCT02868008?term=NCT02868008&rank=1 ).

A suitable sampling strategy for the detection of African swine fever virus in living and deceased pigs in the field: a retrospective study.

African swine fever (ASF) is a fatal disease that threatens the health status of the swine population and thus can impact the economic outcome of the global pig industry. Monitoring the ASF virus (ASFV) is of utmost concern to prevent and control its distribution. This study aims to identify a suitable sampling strategy for ASFV detection in living and deceased pigs under field conditions. A range of samples, comprising tissues obtained from deceased pigs, as well as serum and tonsil swab samples from live pigs, were gathered and subjected to detection using the qPCR method. The findings revealed that the mandibular lymph nodes demonstrated the highest viral loads among superficial tissues, thereby indicating their potential suitability for detecting ASFV in deceased pigs. Additionally, the correlations between virus loads in various tissues have demonstrated that tonsil swab samples are a viable specimen for monitoring live pigs, given the strong associations observed with other tissues. These findings indicated two dependable sample types for the detection of ASFV: mandibular lymph nodes for deceased pigs and tonsil swabs for live pigs, which supply some references for the development of efficacious preventive measures against ASFV.

Content-Aware Human Mobility Pattern Extraction.

Extracting meaningful patterns of human mobility from accumulating trajectories is essential for understanding human behavior. However, previous works identify human mobility patterns based on the spatial co-occurrence of trajectories, which ignores the effect of activity content, leaving challenges in effectively extracting and understanding patterns. To bridge this gap, this study incorporates the activity content of trajectories to extract human mobility patterns, and proposes acontent-aware mobility pattern model. The model first embeds the activity content in distributed continuous vector space by taking point-of-interest as an agent and then extracts representative and interpretable mobility patterns from human trajectory sets using a derived topic model. To investigate the performance of the proposed model, several evaluation metrics are developed, including pattern coherence, pattern similarity, and manual scoring. A real-world case study is conducted, and its experimental results show that the proposed model improves interpretability and helps to understand mobility patterns. This study provides not only a novel solution and several evaluation metrics for human mobility patterns but also a method reference for fusing content semantics of human activities for trajectory analysis and mining.

A Decision Tree Model to Help Treatment Decision-Making for Unruptured Intracranial Aneurysms: A Multi-center, Long-Term Follow-up Study in a Large Chinese Cohort.

Chinese population have a high prevalence of unruptured intracranial aneurysm (UIA). Clinical and imaging risk factors predicting UIA growth or rupture are poorly understood in the Chinese population due to the lack of large-scale longitudinal studies, and the treatment decision for UIA patients was challenging. Develop a decision tree (DT) model for UIA instability, and validate its performance in multi-center studies. Single-UIA patients from two prospective, longitudinal multicenter cohort studies were analyzed, and set as the development cohort and validation cohort. The primary endpoint was UIA instability (rupture, growth, or morphological change). A DT was established within the development cohort and validated within the validation cohort. The performance of clinicians in identifying unstable UIAs before and after the help of the DT was compared using the area under curve (AUC). The development cohort included 1270 patients with 1270 UIAs and a follow-up duration of 47.2 ± 15.5 months. Aneurysm instability occurred in 187 (14.7%) patients. Multivariate Cox analysis revealed hypertension (hazard ratio [HR], 1.54; 95%CI, 1.14-2.09), aspect ratio (HR, 1.22; 95%CI, 1.17-1.28), size ratio (HR, 1.31; 95%CI, 1.23-1.41), bifurcation configuration (HR, 2.05; 95%CI, 1.52-2.78) and irregular shape (HR, 4.30; 95%CI, 3.19-5.80) as factors of instability. In the validation cohort (n = 106, 12 was unstable), the DT model incorporating these factors was highly predictive of UIA instability (AUC, 0.88 [95%CI, 0.79-0.97]), and superior to existing UIA risk scales such as PHASES and ELAPSS (AUC, 0.77 [95%CI, 0.67-0.86] and 0.76 [95%CI, 0.66-0.86], P < 0.001). Within all 1376 single-UIA patients, the use of the DT significantly improved the accuracy of junior neurosurgical clinicians to identify unstable UIAs (AUC from 0.63 to 0.82, P < 0.001). The DT incorporating hypertension, aspect ratio, size ratio, bifurcation configuration and irregular shape was able to predict UIA instability better than existing clinical scales in Chinese cohorts. CLINICAL TRIAL REGISTRATION: IARP-CP cohort were included (unique identifier: ChiCTR1900024547. Published July 15, 2019. Completed December 30, 2020), with 100-Project phase-I cohort (unique identifier: NCT04872842, Published May 5, 2021. Completed November 8, 2022) as the development cohort. The 100-Project phase-II cohort (unique identifier: NCT05608122. Published November 8, 2022) as the validation cohort.

The impact of hyperkalemia on ICU admission and mortality: a retrospective study of Chinese emergency department data.

OBJECTIVE: This study assesses the influence of hyperkalemia on both disease severity and the risk of mortality among patients admitted to the emergency room. METHODS: This retrospective observational study utilized data from the Chinese Emergency Triage Assessment and Treatment database (CETAT, version 2.0), which was designed to evaluate and optimize management strategies for emergency room (ER) patients. Patients were systematically categorized based on serum potassium levels. Relationships between serum potassium levels, risk of mortality, and the severity of illness were then analyzed using multifactorial logistic regression and through Receiver Operating Characteristic (ROC) analysis. The effectiveness of various treatments at lowering potassium levels was also investigated. RESULTS: 12,799 emergency patients were enrolled, of whom 20.1% (n = 2,577) were hypokalemic and 2.98% (n = 381) were hyperkalemic. Among hyperkalemic patients, the leading reasons for visiting the ER were altered consciousness 23.88% (n = 91), cardiovascular symptoms 22.31% (n = 85), and gastrointestinal symptoms 20.47% (n = 78). Comparative analysis with patients exhibiting normal potassium levels revealed hyperkalemia as an independent factor associated with mortality in the ER. Mortality risk appears to positively correlate with increasing potassium levels, reaching peaks when blood potassium levels ranged between 6.5 and 7.0. Hyperkalemia emerged as a strong predictor of death in the ER, with an Area Under the Curve (AUC) of 0.89. The most frequently prescribed treatment for hyperkalemia patients was diuretics (57.32%, n = 188), followed by intravenous sodium bicarbonate (50.91%, n = 167), IV calcium (37.2%, n = 122), insulin combined with high glucose (27.74%, n = 91), and Continuous Renal Replacement Therapy (CRRT) for 19.82% (n = 65). Among these, CRRT appeared to be the most efficacious at reducing potassium levels. Diuretics appeared relatively ineffective, while high-glucose insulin, sodium bicarbonate, and calcium preparations having no significant effect on the rate of potassium decline. CONCLUSION: Hyperkalemia is common in emergency situations, especially among patients with altered consciousness. There is a strong positive correlation between the severity of hyperkalemia and mortality risk. CRRT appears to be the most effective potassium reducting strategy, while the use of diuretics should be approached with caution.

Early postoperative acetylsalicylic acid administration does not increase the risk of postoperative intracranial bleeding in patients with spontaneous intracerebral hemorrhage.

Administration of acetylsalicylic acid (ASA) at early stage after surgery for spontaneous intracerebral hemorrhage (SICH) may increase the risk of postoperative intracranial bleeding (PIB), because of potential inhibition of platelet function. This study aimed to investigate whether early ASA administration after surgery was related to increased risk of PIB. This retrospective study enrolled SICH patients receiving surgery from September 2019 to December 2022 in seven medical institution. Based on postoperative ASA administration, patients who continuously received ASA more than three days within seven days post-surgery were identified as ASA users, otherwise as non-ASA users. The primary outcome was symptomatic PIB events within seven days after surgery. Incidence of PIB was compared between ASA users and non-ASA users using survival analysis. This study included 744 appropriate patients from 794 SICH patients. PIB occurred in 42 patients. Survival analysis showed no statistical difference between ASA users and non-ASA users in incidence of PIB (P = 0.900). Multivariate Cox analysis demonstrated current smoker (hazard ratio [HR], 2.50, 95%CI, 1.33-4.71, P = 0.005), dyslipidemia (HR = 3.03; 95%CI, 1.31-6.99; P = 0.010) and pre-hemorrhagic antiplatelet therapy (HR = 3.05; 95% CI, 1.64-5.68; P < 0.001) were associated with PIB. Subgroup analysis manifested no significant difference in incidence of PIB between ASA users and non-ASA users after controlling the effect from factors of PIB (i.e., sex, age, current smoker, regular drinker, dyslipidemia, pre-hemorrhagic antiplatelet therapy and hematoma location). This study revealed that early ASA administration to SICH patients after surgery was not related to increased risk of PIB.

CD1d affects the proliferation, migration, and apoptosis of human papillary thyroid carcinoma TPC-1 cells via regulating MAPK/NF-κB signaling pathway.

The study aimed to investigate the effect of CD1d down-regulation on the proliferation, migration, and apoptosis of papillary thyroid carcinoma cells and explore the underlying mechanism. CD1d expression was silenced in TPC-1 cells by transfection of CD1d siRNA lentivirus. The proliferation, apoptosis rate, and migration ability of TPC-1 cells were detected by CCK-8 assay, flow cytometry, and scratch assay, respectively. Western blot and qPCR analyses were performed to detect the expression of related proteins. CD1d was highly expressed in TPC-1 cells. Down-regulation of CD1d significantly decreased ALMS1, CDKN3, CDK6, Ki-67, Bcl2 expression, increased Bax and Caspase 3 expression (all P < 0.05), and decreased the migration ability of TPC-1 cells. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed to identify the relevant signaling pathways. KEGG pathway enrichment analysis showed that the differentially expressed genes were mainly enriched in MAPK and NF-κB signaling pathways. Our findings suggest that CD1d down-regulation inhibited the proliferation and migration abilities of TPC-1 cells, increased cell apoptosis possibly via the MAPK/NF-κB signaling pathway.

Security Management Method of Public Sentiment Analysis Based on Blockchain and Edge Computing.

The popularization of the Internet and the rise of social media enable people to share and access information rapidly, leading to a significant increase in the importance of public opinion analysis. However, public opinion analysis still needs help with issues, such as data security, data sharing, and data credibility, which may result in information leakage and inaccurate analysis results. This article proposes a secure management method for public opinion analysis to address these issues. First, a group key management framework is proposed, and then device grouping and mutual authentication methods are used to determine device identity, addressing the data security issue. A dynamic key generation algorithm is proposed to solve the data sharing problem, and a group key management algorithm is implemented to manage the entire lifecycle of group keys, addressing the data credibility issue and establishing a more secure data processing, and storage environment for public opinion analysis. This article utilizes OpenEthereum to build a blockchain network and conducts simulation experiments on the proposed solution. After comprehensive evaluation, it is confirmed that the solution is efficient and scalable.

Nanobodies against African swine fever virus p72 and CD2v proteins as reagents for developing two cELISAs to detect viral antibodies.

African swine fever virus (ASFV) poses a significant threat to the global swine industry. Currently, there are no effective vaccines or treatments available to combat ASFV infection in pigs. The primary means of controlling the spread of the disease is through rapid detection and subsequent elimination of infected pig. Recently, a lower virulent ASFV isolate with a deleted EP402R gene (CD2v-deleted) has been reported in China, which further complicates the control of ASFV infection in pig farms. Furthermore, an EP402R-deleted ASFV variant has been developed as a potential live attenuated vaccine candidate strain. Therefore, it is crucial to develop detection methods that can distinguish wild-type and EP402R-deleted ASFV infections. In this study, two recombinant ASFV-p72 and -CD2v proteins were expressed using a prokaryotic system and used to immunize Bactrian camels. Subsequently, eight nanobodies against ASFV-p72 and ten nanobodies against ASFV-CD2v were screened. Following the production of these nanobodies with horse radish peroxidase (HRP) fusion proteins, the ASFV-p72-Nb2-HRP and ASFV-CD2v-Nb22-HRP fusions were selected for the development of two competitive ELISAs (cELISAs) to detect anti-ASFV antibodies. The two cELISAs exhibited high sensitivity, good specificity, repeatability, and stability. The coincidence rate between the two cELISAs and commercial ELISA kits was 98.6% and 97.6%, respectively. Collectively, the two cELISA for detecting antibodies against ASFV demonstrated ease of operation, a low cost, and a simple production process. The two cELISAs could determine whether pigs were infected with wild-type or CD2v-deleted ASFV, and could play an important role in monitoring ASFV infections in pig farms.

Analysis on status quo and related factors of delays in diagnosis and treatment of breast cancer in Ningxia Hui Autonomous Region.

This study aimed to explore factors contributing to the delays in the diagnosis and treatment of breast cancer (BC) in Ningxia Hui Autonomous Region. We conducted a cohort analysis of 1012 patients with BC diagnosed at the General Hospital of Ningxia Medical University between January 2018 and December 2019. Sociodemographic data were collected through questionnaires, and clinical data were gathered and analyzed from relevant databases. Furthermore, observations were made regarding delays in the diagnosis and treatment of BC, followed by an analysis of the correlations between patient delay and both sociological factors within the population and clinical factors specific to patients with BC. Subsequently, the factors associated with patient delay and system delay were examined using Cox regression analysis, along with the inclusion of neoadjuvant therapy. In the prevention and treatment of BC in Ningxia, the patient delay rate was 33.20%, the diagnosis delay rate was 17.89%, the treatment delay rate was 0.0099% and the system delay rate was 41.60%. There was a higher proportion of patient delay and system delay in aged patients (age ≥ 61 years) with rural registered permanent residence (RPR), multiple clinical symptoms (such as nipple spillage, axillary abnormalities, etc), a T4 tumor size classification, and the initial use of neoadjuvant therapy. Besides, significant positive correlations were observed between patient delay and system delay time with BC stage. Patients aged 51 to 60 and those with molecular types (Limanal1B: ki-67 > 14%, Limanal1B: HER-2 positive) were prone to patient delay, whereas molecular characteristics influenced system delay, unrelated to sociodemographic factors. The study identifies significant age, residency, and tumor molecular subtype correlations with diagnostic and treatment delays in Ningxia's patients with BC, predominantly affecting women aged 41 to 60, especially urban dwellers. These findings underscore the need for targeted interventions to reduce delays and improve BC care in this region.

Modeling and optimization of sporulation by Bacillus licheniformis BF-002 based on dynamics and recurrent neural networks.

Bacillus licheniformis is widely utilized in disease prevention and environmental remediation. Spore quantity is a critical factor in determining the quality of microbiological agents containing vegetative cells. To improve the understanding of Bacillus licheniformis BF-002 strain culture, a hybrid model integrating traditional dynamic modeling and recurrent neural network was developed. This model enabled the optimization of carbon/nitrogen source feeding rates, pH, temperature and agitation speed using genetic algorithms. Carbon and nitrogen source consumption in the optimal duplicate batches showed no significant difference compared to the control batch. However, the spore quantity in the broth increased by 16.2% and 35.2% in the respective duplicate batches. Overall, the hybrid model outperformed the traditional dynamic model in accurately tracking the cultivation dynamics of Bacillus licheniformis, leading to increased spore production when used for optimizing cultivation conditions.

Association between smoking and alcohol drinking and benign adrenal tumors: a Mendelian randomization study.

BACKGROUND: In recent years, the detection rate of adrenal tumors has increased, but it is unclear whether smoking and alcohol drinking are risk factors for benign adrenal tumors. The objective of this study is to employ Mendelian randomization (MR) analysis to explore the causal relationship between smoking, alcohol drinking and susceptibility to benign adrenal tumors. METHODS: We acquired large-scale data from publicly accessible databases on genome-wide association studies (GWAS) pertaining to smoking, alcohol drinking and benign adrenal tumors. A total of 11 sets of instrumental variables (IVs) and 281 associated single nucleotide polymorphic (SNP) loci were identified. The Mendelian randomization analyses were conducted using inverse variance weighting (IVW), MR-Egger regression and weighted median estimation (WME) methods, in addition to sensitivity analyses. RESULTS: There is no causal relationship between smoking status, alcohol drinking status, alcohol intake frequency, alcohol taken with meals, alcohol consumption and benign adrenal tumors, while pack years of smoking and cigarettes per day are risk factors for benign adrenal tumors. The IVW analysis revealed that both the pack years of smoking and cigarettes per day were positively associated with an increased risk of benign adrenal tumors (OR = 2.853, 95%CI = 1.384-5.878, p = 0.004; OR = 1.543, 95%CI = 1.147-2.076, p = 0.004). Two SNPs (rs8042849 in the analysis of pack years of smoking and rs8034191 in the analysis of cigarettes per day) significantly drove the observed causal effects. CONCLUSION: Two-sample Mendelian randomization analysis showed a causal effect between smoking but not alcohol consumption and benign adrenal tumors.

A study on a recommendation algorithm based on spectral clustering and GRU.

With the development of e-commerce, the importance of recommendation algorithms has significantly increased. However, traditional recommendation systems struggle to address issues such as data sparsity and cold start. This article proposes an optimization method for a recommendation system based on spectral clustering (SC) and gated recurrent unit (GRU), named the GRU-KSC algorithm. Firstly, this paper improves the original spectral clustering algorithm by introducing Kmc2, proposing a novel spectral clustering recommendation algorithm (K-means++ SC, KSC) based on the existing SC algorithm. Secondly, building upon the original GRU model, the paper presents a hybrid recommendation algorithm (Hybrid GRU, HGRU) capable of capturing long-term user interests for a more personalized recommendation. Experiments conducted on real datasets demonstrate that our method outperforms existing benchmark methods in terms of accuracy and robustness.

Enhanced sporulation of B. licheniformis BF-002 through automatic co-feeding of carbon and nitrogen sources.

Bacillus licheniformis formulations are effective for environmental remediation, gut microbiota modulation, and soil improvement. An adequate spore quantity is crucial for the activity of B. licheniformis formulations. This study investigated the synergistic effects of carbon/nitrogen source consumption and concentration on B. licheniformis BF-002 cultivation, with the aim of developing an automatic co-feeding strategy to enhance spore production. Initial glucose (10 g/L) and amino nitrogen (1.5 g/L) concentrations promote cell growth, followed by reduced glucose (2.0 g/L) and amino nitrogen (0.5 g/L) concentrations for sustained spore generation. The spore quantity reached 2.59 × 1010 CFU/mL. An automatic co-feeding strategy was developed and implemented in 5 and 50 L cultivations, resulting in spore quantities of 2.35 × 1010 and 2.86 × 1010 CFU/mL, respectively, improving by 6.81% and 30.00% compared to that with a fixed glucose concentration (10.0 g/L). The culture broth obtained at both the 5 and 50 L scales was spray-dried, resulting in bacterial powder with cell viability rates of 85.94% and 82.68%, respectively. Even after exposure to harsh conditions involving high temperature and humidity, cell viability remained at 72.80% and 69.89%, respectively. Employing the automatic co-feeding strategy increased the transcription levels of the spore formation-related genes spo0A, spoIIGA, bofA, and spoIV by 7.42%, 8.46%, 8.87%, and 9.79%, respectively. The proposed strategy effectively promoted Bacillus growth and spore formation, thereby enhancing the quality of B. licheniformis formulations.

Multi-Omics Analysis Reveals the Role of Changes in Platelet Activation Pathways in the Survival Outcome of Patients with Esophageal Squamous Cell Carcinoma.

Objective: The objective of this study was to integrate metabolomics and transcriptomics data to identify key diagnostic and prognostic markers for esophageal squamous cell carcinoma (ESCC). Plasma samples were collected from 85 ESCC patients at different stages and 50 healthy volunteers for non-targeted metabolomic analysis. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) was employed for non-targeted metabolomic analysis. Subsequently, we integrated the metabolomic data with transcriptomic data from the Gene Expression Omnibus (GEO) and prognosis data from The Cancer Genome Atlas Program (TCGA) to perform pathway analysis. Our focus was on pathways that involve both metabolites and upstream genes, as they often exhibit higher accuracy. Results: Through the integration of metabolomics and transcriptomics, we identified significant alterations in the platelet activation pathway in ESCC. This pathway involves the participation of both metabolites and genes, making it a more accurate reflection of pathological changes associated with the disease. Notably, metabolite arachidonic acid (AA) and chemokine receptor type 2(CXCR2) were significantly downregulated in ESCC, while genes collagen type I alpha 1(COL1A1), collagen type I alpha 2(COL1A2), collagen type III alpha 1(COL3A1), type 3 inositol 1,4,5-trisphosphate receptor (ITPR3), and insulin-like growth factor II mRNA binding protein 3(IGF2BP3) were significantly upregulated, indicating the presence of tumor-induced platelet activation in ESCC. Further analysis of prognosis data revealed that high expression of COL1A1, IGF2BP3, and ITPR3 was associated with a favorable prognosis for ESCC, while high CXCR2 expression was linked to an adverse prognosis. In addition, we combined COL1A1, ITPR3, IGF2BP3, CXCR2, and AA to form a diagnostic biomarker panel. The receiver operating characteristic curve (ROC) demonstrated excellent diagnostic capability (AUC=0.987). Conclusion: Our study underscores the significant role of platelet activation pathways and related genes in the diagnosis and prognosis of ESCC patients. These findings offer promising insights for improving the clinical management of ESCC.

Identification of Breast Cancer Immune-related Prognostic Characteristics in Tumor Microenvironment.

BACKGROUND: Accumulated evidence suggest that tumor microenvironment (TME) plays a crucial role in breast cancer (BRCA) progression and therapeutic effects. OBJECTIVE: This study aimed to characterize immune-related BRCA subtypes in TME, and identify genes with prognostic value. METHODS: RNA sequencing profiles with corresponding clinical data from The Cancer Genome Atlas (TCGA) database of BRCA patients were downloaded to evaluate immune infiltration using the single-sample gene set enrichment (ssGAEA) algorithm. Further, BRCA was clustered according to immune infiltration status by consensus clustering analysis. Using Venn analysis, differentially expressed genes (DEGs) were overlapped to obtain candidate genes. Kaplan-Meier (K-M) analysis was performed to identify prognostic genes, and the results were verified in the GEO and METABRIC datasets. RT-qPCR was conducted to detect the mRNA expression of prognostic genes. RESULTS: In the TCGA database, 3 immune-related BRCA subtypes were identified [cluster1 (C1), cluster2 (C2), and cluster3 (C2)]. The C2 subtype had better overall survival (OS) compared to the C1 subtype. Higher levels of immune markers and checkpoint protein were found in the C2 subtype than in others. By combining DEGs between BRCA and normal tissues, with the C1 and C2 subtypes associated with different OS, 25 BRCA candidate genes were identified. Among these, 8 genes were identified as prognostic genes for BRCA. RT-qPCR showed that the expressions of 2 genes were significantly elevated in BRCA tissues, while that of other genes were decreased. CONCLUSION: Three BRCA subtypes were identified with the immune index, which may help design advanced treatment of BRCA. The data code used for the analysis in this article was available on GitHub (https://github.com/tangzhn/BRCA1.git).

In-Depth Structure and Function Characterization of Heterogeneous Interchain Cysteine-Conjugated Antibody-Drug Conjugates.

Antibody-drug conjugates (ADCs), integrating high specificity of antigen-targeting antibodies and high potency of cell-killing chemical drugs, have become one of the most rapidly expanding therapeutic biologics in oncology. Although ADCs were widely studied from multiple aspects, overall structural elucidation with comprehensive understanding of variants is scarcely reported. Here, for the first time, we present a holistic and in-depth characterization of an interchain cysteine-conjugated ADC, focusing on conjugation and charge heterogeneity, and in vitro biological activities. Conjugation mapping utilized a bottom-up approach, unraveled positional isomer composition, provided insights into the conjugation process, and elucidated how conjugation affects the physicochemical and biological properties of an ADC. Charge profiling combined bottom-up and top-down approaches to interrogate the origin of charge heterogeneity, its impact on function, and best practice for characterization. Specifically, we pioneered the utilization of capillary isoelectric focusing-mass spectrometry to decode not only critical post-translational modifications but also drug load and positional isomer distribution. The study design provides general guidance for in-depth characterization of ADCs, and the analytical findings in turn benefit the discovery and development of future ADCs.