ObjectiveTo investigate the influence of entecavir （ETV） versus tenofovir alafenamide fumarate （TAF） on renal function in previously untreated patients with chronic hepatitis B （CHB）. MethodsA retrospective analysis was performed for the clinical data of 167 previously untreated CHB patients who received ETV or TAF treatment for at least 48 weeks at the outpatient service of Department of Infectious Diseases in The First Affiliated Hospital of Nanchang University from September 2019 to November 2023， and according to the antiviral drug used， they were divided into ETV group with 117 patients and TAF group with 50 patients. In order to balance baseline clinical data， propensity score matching （PSM） was used for matching and analysis at a ratio of 2∶1， and the two groups were compared in terms of estimated glomerular filtration rate （eGFR） and the incidence rate of abnormal renal function at week 48. According to eGFR at week 48， the patients were divided into normal renal function group and abnormal renal function group. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. The multivariate Logistic regression analysis was used to investigate the influencing factors for abnormal renal function， and the receiver operating characteristic （ROC） curve was used to assess the performance of each indicator in predicting abnormal renal function. The Kaplan-Meier method was used to analyze the cumulative incidence rate of abnormal renal function， and the log-rank test was used for comparison. The analysis of variance with repeated measures was used to compare the dynamic changes of eGFR during antiviral therapy in CHB patients. ResultsAfter PSM matching， there were 100 patients in the ETV group and 50 patients in the TAF group. There were no significant differences in baseline clinical data between the ETV group and the TAF group （all P>0.05）， with an eGFR level of 112.29±9.92 mL/min/1.73 m² in the ETV group and 114.72±12.15 mL/min/1.73 m² in the TAF group. There was a reduction in eGFR from baseline to week 48 in both groups， and compared with the TAF group at week 48， the ETV group had a significantly lower eGFR （106.42±14.12 mL/min/1.73 m² vs 112.25±13.44 mL/min/1.73 m²， t=-2.422， P=0.017） and a significantly higher incidence rate of abnormal renal function （17.00% vs 4.00%， χ²=5.092， P=0.024）. After the patients were divided into normal renal function group with 131 patients and abnormal renal function group with 19 patients， the univariate analysis showed that there were significant differences between the two groups in age （Z=-2.039， P=0.041）， treatment drug （ETV/TAF） （χ²=5.092， P=0.024）， and baseline eGFR level （t=4.023， P<0.001）， and the multivariate Logistic regression analysis showed that baseline eGFR （odds ratio ［OR］=0.896， 95% confidence interval ［CI］： 0.841 — 0.955， P<0.001） and treatment drug （OR=5.589， 95%CI： 1.136 — 27.492， P=0.034） were independent influencing factors for abnormal renal function. Baseline eGFR had an area under the ROC curve of 0.781 in predicting abnormal renal function in CHB patients， with a cut-off value of 105.24 mL/min/1.73 m²， a sensitivity of 73.68%， and a specificity of 82.44%. The Kaplan-Meier curve analysis showed that the patients with baseline eGFR≤105.24 mL/min/1.73 m² had a significantly higher cumulative incidence rate of abnormal renal function than those with baseline eGFR>105.24 mL/min/1.73 m² （χ²=22.330， P<0.001）， and the ETV group had a significantly higher cumulative incidence rate of abnormal renal function than the TAF group （χ²=4.961， P=0.026）. With the initiation of antiviral therapy， both the ETV group and the TAF group had a significant reduction in eGFR （F=5.259， P<0.001）， but the ETV group only had a significant lower level of eGFR than the TAF group at week 48 （t=-2.422， P=0.017）； both the baseline eGFR≤105.24 mL/min/1.73 m² group and the baseline eGFR>105.24 mL/min/1.73 m² group had a significant reduction in eGFR （F=5.712， P<0.001）， and there was a significant difference in eGFR between the two groups at baseline and weeks 12， 24， 36， and 48 （t=-13.927， -9.780， -8.835， -9.489， and -8.953， all P<0.001）. ConclusionFor CHB patients initially treated with ETV or TAF， ETV antiviral therapy has a higher risk of renal injury than TAF therapy at week 48.

Soybean meal (SBM) prepared by soybean crushing is the most popular protein source in the poultry and livestock industries (Cai et al., 2015) due to its economic manufacture, high protein content, and good nutritional value. Despite these benefits, SBM contains various antigen proteins such as glycinin and β-conglycinin, which account for approximately 70% of the total proteins of the SBM and reduce digestibility and damage intestinal function (Peng et al., 2018). Treating SBM with proteases (neutrase, alcalase, and trypsin) or fermentation can eliminate these antigen proteins (Contesini et al., 2018). Because of its safety and rapid growth cycle, Bacillus strains are considered ideal for the fermentation industry (Yao et al., 2021). SBM fermented by Bacillus yields products with high nutritional value and low levels of antinutritional factors (ANFs), stimulating research in this area (Yuan et al., 2017). Kumari et al. (2023) demonstrated that fermentation with Bacillus species effectively degrades antigen proteins and increases crude protein content. The degradation of antigen proteins relies on protease hydrolysis. Low protease production is the major obstacle hindering the widespread use of microbial fermentation techniques.
Bacillus amyloliquefaciens/metabolism* ; Fermentation ; Glycine max/metabolism* ; Soybean Proteins/metabolism* ; Peptide Hydrolases/metabolism* ; Ribosomes/metabolism* ; Globulins ; Antigens, Plant ; Seed Storage Proteins

Biomanufacturing is an advanced manufacturing method that integrates biology, chemistry, and engineering. It utilizes renewable biomass and biological organisms as production media to scale up the production of target products through fermentation. Compared with petrochemical routes, biomanufacturing offers significant advantages in reducing CO₂ emissions, lowering energy consumption, and cutting costs. With the development of systems biology and synthetic biology and the accumulation of bioinformatics data, the integration of information technologies such as artificial intelligence, large models, and high-performance computing with biotechnology is propelling biomanufacturing into a data-driven era. This paper reviews the latest research progress on databases, knowledge bases, and large language models for biomanufacturing. It explores the development directions, challenges, and emerging technical methods in this field, aiming to provide guidance and inspiration for scientific research in related areas.
Biotechnology/methods* ; Knowledge Bases ; Synthetic Biology ; Databases, Factual ; Artificial Intelligence ; Systems Biology ; Computational Biology ; Fermentation

Natural components serve the survival instincts of cells that are obtained through long-term evolution, while they often fail to meet the demands of engineered cells for efficiently performing biological functions in special industrial environments. Enzymes, as biological catalysts, play a key role in biosynthetic pathways, significantly enhancing the rate and selectivity of biochemical reactions. However, the catalytic efficiency, stability, substrate specificity, and tolerance of natural enzymes often fall short of industrial production requirements. Therefore, exploring and modifying enzymes to suit specific biomanufacturing processes has become crucial. In recent years, artificial intelligence (AI) has played an increasingly important role in the discovery, evaluation, engineering, and de novo design of proteins. AI can accelerate the discovery and optimization of proteins by analyzing large amounts of bioinformatics data and predicting protein functions and characteristics by machine learning and deep learning algorithms. Moreover, AI can assist researchers in designing new protein structures by simulating and predicting their performance under different conditions, providing guidance for protein design. This paper reviews the latest research advances in protein discovery, evaluation, engineering, and de novo design for biomanufacturing and explores the hot topics, challenges, and emerging technical methods in this field, aiming to provide guidance and inspiration for researchers in related fields.
Protein Engineering/methods* ; Artificial Intelligence ; Proteins/genetics* ; Computational Biology ; Machine Learning ; Data Mining ; Algorithms ; Deep Learning

Macrophage extracellular traps(METs)are extracellular fibrous web-like structures produced by macro-phages.Under physiological conditions,METs capture and kill microorganisms by releasing high concentrations of granular proteins,serving as an innate immune defense mechanism and playing a vital protective role in resisting the progression of inflammatory diseases.Excessive release of METs can also exacerbate the inflammatory response and cause further tissue damage.

OBJECTIVE To compare the changes of chemical components of Morus alba leaves， screen differential markers， and determine their contents， so as to provide reference for quality control of M. alba leaves before and after baked with honey. METHODS The fingerprints of M. alba leaves before and after baked with honey were established by high-performance liquid chromatography （HPLC）. The common peaks of the fingerprints were identified and the similarity was evaluated. The differential markers of M. alba leaves before and after baked with honey were screened by principal component analysis （PCA） and orthogonal partial least squares-discriminant analysis （OPLS-DA） using common peak are of raw material and product baked with honey of M. alba leaves as index. The quantitative analysis was carried out. RESULTS Twenty-three and twenty-four common peaks were identified from the HPLC fingerprint spectra of ten batches of raw material and ten batches of product baked with honey of M. alba leaves， respectively. The similarities of HPLC fingerprints for raw material and product baked with honey of M. alba leaves were all greater than 0.97. The results of PCA showed that raw material and product baked with honey of M. alba leaves could be divided into two categories. The results of OPLS-DA showed that the variable importance in projection of peak 2， peak H （5- hydroxymethylfurfural）， peak 1， peak 17 （isochlorogenic acid C） and peak 16 were all greater than 1. The average contents of differential marker of isochlorogenic acid C in raw material and product baked with honey of M. alba leaves were 0.093 6 and 0.127 8 mg/g， respectively； there was statistical significance （P＜0.05）. CONCLUSIONS Five differential markers such as isochlorogenic acid C are obtained. The content of isochlorogenic acid C in M. alba leaves is significantly increased after baked with honey.

Objective:To explore the application effect of breakthrough series (BTS) quality improvement model in the prevention of catheter-related bloodstream infection in hospitalized patients with indwelling non-cuffed catheter (NCC).Methods:Using a non synchronous pre and post control study method, convenience sampling was used to select NCC patients from four hospitals in Tianjin from January to September 2022 who received conventional nursing plans as the control group, and NCC patients from February to October 2023 who received nursing plans based on the BTS quality improvement model as the observation group. Compared the incidence of NCC related bloodstream infections between two groups of patients, the implementation of key preventive measures for NCC related bloodstream infections by nursing staff, and patient satisfaction.Results:Among the 984 patients included in the control group, there were 687 males and 297 females, aged (62.43 ± 13.77) years old; among the 959 patients included in the observation group, there were 651 males and 308 females, aged (61.96 ± 13.89) years old. After applying the improved model, the incidence of NCC related bloodstream infections in the observation group was 0.12‰ (1/8 676), lower than the control group′s 0.71‰ (7/9 827), and the difference was statistically significant ( χ 2=4.37, P<0.05) ;the implementation rate of key measures for preventing NCC related bloodstream infections in the observation group was 90.00% (54/60) for catheter outlet care and 91.67% (55/60) for maximizing sterile barrier, both higher than 70.37% (38/54) and 75.93% (41/54) in the control group, with statistical significance ( χ2=7.03, 5.30, both P<0.05); the total satisfaction rate of patients in the observation group was 92.91% (891/959), which was higher than 58.64% (577/984) in the control group, and the difference was statistically significant ( χ2=15.28, P<0.05). Conclusions:The implementation of BTS quality improvement model is helpful to improve the nursing quality of patients with indwelling NCC dialysis and improve the patient outcomes.

Objective:To investigate the expression and prognostic value of ANO1 in oral squamous cell carcinoma(OSCC)tissues.Methods:Immunohistochemistry(IHC,n=163)and Quantitative real-time PCR(qRT-PCR,n=42)were employed to detect the expression level of ANO1 protein and mRNA in OSCC tissues and paracancerous normal tissues.The relationship between ANO1 ex-pression and clinicopathological features(n=163)and prognosis(n=93)of the patients were analyzed,and the results were compared with those in TCGA database.Results:IHC and qRT-PCR confirmed that ANO1 was highly expressed in OSCC(P＜0.05),which was consistent with the results of the TCGA database.Cox regression analysis showed that ANO1 expression was significantly correlated with T stage,lymph node metastasis and TNM stage and poor prognosis(P＜0.05).By Cox regression analysis,ANO1 overexpression(P=0.002)and differentiation degree(P=0.034)were independent prognostic factors.Conclusion:ANO1 is highly expressed in OSCC and is correlated with poor prognosis,which can be used as a novel biomarker for poor prognosis of OSCC patients.

Objective:To analyze the clinical characteristics and all-cause mortality influencing factors of patients with Keshan disease.Methods:Clinical data of patients with Keshan disease from Keshan disease areas in Sichuan Province and Yunnan Province were collected and retrospectively analyzed for clinical characteristics and survival status during regular follow-up. According to the survival status of patients, the survey subjects were divided into a survival group and a death group. All-cause mortality (referring to the death caused by various reasons throughout the follow-up period) was used as the study endpoint. Kaplan-Meier (K-M) survival curve analysis and log-rank χ 2 test were performed, univariate and multivariate Cox regression analysis were used for all-cause mortality factor analysis. Results:A total of 176 patients with Keshan disease were collected, including 92 cases in Sichuan Province and 84 cases in Yunnan Province. Among all the patients, there were 105 males, accounting for 59.66%, and 71 females, accounting for 40.34%. The age was (53.89 ± 13.19) years old. Thirty-five cases died from all causes, with a mortality rate of 19.89%. There were significant differences in age ( t = 2.09, P = 0.038), New York Heart Association (NYHA) cardiac function grading (χ 2 = 14.62, P < 0.001) and ventricular premature contraction (χ 2 = 6.82, P = 0.009) between the survival group and the death group. K-M survival curve analysis showed that patients with Keshan disease complicated by premature ventricular contraction and high NYHA cardiac function grading (Ⅲ and Ⅳ) had higher all-cause mortality (log-rank χ 2 = 8.72, 22.49, P < 0.05). Univariate Cox regression analysis showed that NYHA cardiac function grading and ventricular premature contraction ( HR = 3.09, 2.71, P < 0.05) were predictive influencing factors for all-cause mortality in patients with Keshan disease. Multivariate Cox regression analysis showed that NYHA cardiac function grading ( HR = 6.57, P = 0.002) and ventricular premature contraction ( HR = 2.98, P = 0.050) were independent factors for all-cause mortality in patients with Keshan disease. Conclusions:Among 176 patients with Keshan disease, the number of patients with poor cardiac function (NYHA cardiac function grading Ⅲ and Ⅳ) and arrhythmia is high. NYHA cardiac function grading and ventricular premature contractions are independent influencing factors for all-cause mortality in patients with Keshan disease.

Objective To explore the abnormal changes of resting state functional connectivity of pain networks in patients with cervical discogenic pain(CDP).Methods The resting-state functional magnetic resonance imaging(rs-fMRI)data of 40 patients with CDP and 40 age-and gender-matched healthy controls(HC)were collected.The seed of posterior insula(PI)was used to define the pain network,and seed-based whole-brain functional connectivity analyses were performed to explore the difference of functional connectivity between CDP patients and HC,the associations between functional connectivity and clinical measures were analyzed.Results The functional connectivity between bilateral PI and bilateral thalamus(THA)was increased,and the functional connectivity between left PI and middle cingulate cortex(MCC),left postcentral gyrus(PoCG)and MCC were decreased in CDP patients.Moreover,the func-tional connectivity between right PI and left THA was positively correlated with visual analogue scale(VAS),and the functional connectivity between left PoCG and MCC was negatively correlated with VAS.Conclusion Functional connectivity abnormalities exist in pain network resting state of CDP patients,which may provide an imaging basis for revealing the neuropathological mechanism of pain in CDP patients.