Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Suhuang Zhike Capsules are widely used in clinical practice for the treatment of respiratory diseases and have been included in Medicine Catalogue for National Basic Medical Insurance, Work Injury Insurance, and Maternity Insurance and National Essential Medicines List. However, problems remain, such as unclear definitions of treatment courses and unidentified contraindications for certain populations. Therefore, this consensus was developed collaboratively by clinical experts in traditional Chinese medicine(TCM) related to pulmonary diseases, respiratory, and critical care medicine, as well as methodology and pharmacy experts, adhering strictly to the consensus development procedures established by the China Association of Chinese Medicine for clinical application of Chinese patent medicines, with the aim to guide the correct clinical use of Suhuang Zhike Capsules for the treatment of cough variant asthma, post-infectious cough, and other respiratory diseases. This consensus employed questionnaire surveys and expert interviews to identify clinical concerns based on the PICOS principle and conduct evidence evaluation and GRADE grading. Utilizing nominal group techniques and GRADE networking methods, it resulted in 17 recommendations and consensus suggestions. The consensus further clarifies the indications, TCM syndromes, usage, and clinical safety of Suhuang Zhike Capsules in the treatment of cough variant asthma and post-infectious cough, aiming to promote standardized medication use and facilitate the rational clinical application of Suhuang Zhike Capsules.
Humans ; Drugs, Chinese Herbal/administration & dosage* ; Consensus ; Capsules ; Respiratory Tract Diseases/drug therapy* ; Medicine, Chinese Traditional

The chemical constituents from Cephalotaxus lanceolata were isolated and purified by using multiple chromatographic techniques, including octadecylsilane(ODS), silica gel, Sephadex LH-20 column chromatography, and semi-preparative high-performance liquid chromatography(HPLC). A total of 17 compounds obtained were identified by using spectroscopic methods such as nuclear magnetic resonance(NMR), mass spectrometry(MS), and ultraviolet(UV) combined with literature data. Compound 1 was a new alkaloid dimer, named cephalancetine E. The known compounds were determined as cephalancetine A(2), 11-hydroxycephalotaxine(3), 4-hydroxycephalotaxine(4), cephalotaxine(5), epicephalotaxine(6), cephalotaxine β-N-oxide(7), acetylcephalotaxine(8), cephalotine A(9), cephalotine B(10), 11-hydroxycephalotaxine hemiketal(11), 3-deoxy-3,11-epoxy-cephalotaxine(12), cephalotaxinone(13), isocephalotaxinone(14), 2,11-epoxy-1,2-dihydro-8-oxo-cephalotaxine(15), cephalotaxamide(16), and drupacine(17), respectively. Compounds 11, 12, and 15 were isolated from the Cephalotaxus genus for the first time. The biological activity was tested for compounds 1-17. The results reveal that compound 17 displays potent inhibitory activities against three human cancer cell lines(HepG-2, MCF-7, and SH-SY5Y).
Cephalotaxus/chemistry* ; Humans ; Cell Line, Tumor ; Drugs, Chinese Herbal/pharmacology* ; Harringtonines/pharmacology* ; Molecular Structure ; Dimerization ; Alkaloids/isolation & purification* ; Magnetic Resonance Spectroscopy

OBJECTIVE: To explore clinical efficacy of percutaneous endoscopic discectomy with a lateral approach and dual-channel method in treating highly free lumbar disc herniation(LDH). METHODS: A retrospective analysis was conducted on 54 patients with highly free LDH who were treated with spinal endoscopic techniques from January 2021 to December 2022. Twenty-seven patients were treated with lateral approach dual-channel(lateral approach dual-channel group), including 16 males and 11 females, with an average age of (54.6±10.5) years old. Twenty-seven patients were treated with unilateral biportal endoscopic (UBE group), including 17 males and 10 females, with an average age of (52.9±12.3) years old. The number of intraoperative fluoroscopy, operation time and hospital stay, as well as visual analogue scale (VAS) and Oswestry diability index (ODI) of low back and leg pain between two patients before operation, 1 day, 1, 3, and 12 months after operation, and the efficacy was evaluated by the modified MacNab criteria at 12 mohths after operation. RESULTS: All patients were successfully completed surgical and were followed up, the time raged from 12 to 22 months with an average of (13.57±4.12) months. There was no statistically significant difference in operation time between two groups (P>0.05). The hospital stay of lateral approach dual-channel group was (3.9±1.1) days, which was shorter than that of UBE group (6.5±1.4) days, the number of intraoperative fluoroscopy in lateral approach dual-channel group was (12.7±2.1) times, which was more than that in UBE group (6.6±1.3) times, the differences were statistically significant (t=5.197, -7.532;P<0.05). VAS and ODI for low back pain at 1 day and 1 month after operation, and VAS for leg pain at 1 day after operation of lateral approach dual-channel group were superior to those of UBE group, and the differences were statistically significant (P<0.05). However, there were no statistically significant differences in VAS and ODI for low back and leg pain between two groups before operation and 3 and 12 months after operation (P>0.05). VAS and ODI of low back and leg pain were significantly improved at each time point before and after operation in both groups, and the difference were statistically significant (P<0.05). At 12 months after operation, according to the modified MacNab criteria, the excellent and good rates of therapeutic effects between lateral approach dual-channel group and UBE group were 92.6% (25/27) and 88.9% (24/27), respectively, and the difference was not statistically significant (χ²=0.22, P>0.05). CONCLUSION For patients with highly free lumbar intervertebral disc protrusion, both of lateral approach dual-channel method and UBE endoscopic surgery are safe and effective. Endoscopic surgery with lateral approach and dual-channel method could be performed under local anesthesia, allowing for the removal of the nucleus pulposus under direct vision. It is simpler, more efficient.
Humans ; Male ; Female ; Intervertebral Disc Displacement/surgery* ; Middle Aged ; Diskectomy, Percutaneous/methods* ; Lumbar Vertebrae/surgery* ; Endoscopy/methods* ; Adult ; Retrospective Studies ; Aged

OBJECTIVE: To investigate the effect of TBL1XR1 mutation on cell biological characteristics of diffuse large B-cell lymphoma (DLBCL). METHODS: The TBL1XR1 overexpression vector was constructed and DNA sequencing was performed to determine the mutation status. The effect of TBL1XR1 mutation on apoptosis of DLBCL cell line was detected by flow cytometry and TUNEL fluorescence assay; CCK-8 assay was used to detect the effect of TBL1XR1 mutation on cell proliferation; Transwell assay was used to detect the effect of TBL1XR1 mutation on cell migration and invasion; Western blot was used to detect the effect of TBL1XR1 mutation on the expression level of epithelial-mesenchymal transition (EMT) related proteins. RESULTS: The TBL1XR1 overexpression plasmid was successfully constructed. The in vitro experimental results showed that TBL1XR1 mutation had no significant effect on apoptosis of DLBCL cells. Compared with the control group, TBL1XR1 mutation enhanced cell proliferation, migration and invasion of DLBCL cells. TBL1XR1 gene mutation significantly increased the expression of N-cadherin protein, while the expression of E-cadherin protein decreased. CONCLUSION TBL1XR1 mutation plays a role in promoting tumor cell proliferation, migration and invasion in DLBCL. TBL1XR1 could be considered as a potential target for DLBCL therapy in future research.
Humans ; Lymphoma, Large B-Cell, Diffuse/pathology* ; Cell Proliferation ; Mutation ; Receptors, Cytoplasmic and Nuclear/genetics* ; Apoptosis ; Cell Line, Tumor ; Epithelial-Mesenchymal Transition ; Cell Movement ; Repressor Proteins/genetics* ; Nuclear Proteins/genetics* ; Cadherins/metabolism*

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

In view of the few studies on the influence of Armillaria spp. infection on the content of the chemical components in different parts of Polyporus umbellatus sclerotia, this study determined the biomass of P. umbellatus sclerotia and the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in the separated cavity wall of the sclerotia and the uninfected part of the sclerotia in different harvesting years under the conditions of A. gallica and A. mellea infection respectively. According to the difference of content and dynamic changes of the polysaccharide and the steroid substances, the superior Armillaria sp. was screened to obtain the best harvest years of P. umbellatus. Using HPLC and UV-VIS spectrophotometry methods, the contents of ergosterol, polyporusterone A, polyporusterone B and polysaccharide in P. umbellatus sclerotia infected by the two Armillaria spp. in different years were determined. In addition, the differentially expressed genes related to P. umbellatus polysaccharide synthesis were screened according to the transcriptomic data of different parts of P. umbellatus after A. mellea infection. With the increase of years, the biomass of sclerotia infected by different Armillaria spp. had significant differences, and there were significant differences in the four components of sclerotia. The four components of the separated cavity wall of the sclerotia were significantly higher than those of the uninfected part. The best harvest time was the third year after cultivation. Transcriptomic analysis showed that the infection of Armillaria spp. could significantly promote polysaccharide synthesis, which provided a basis for polysaccharide content determination at the molecular level. The study clarified the influence of different Armillaria spp. infection on the accumulation of chemical components of P. umbellatus sclerotia, laying a foundation for exploring the symbiosis mechanism and provided a scientific clue for screening superior Armillaria sp. and guiding the artificial cultivation of P. umbellatus sclerotia.

ObjectiveThis study leverages structural data from antigen-antibody complexes of the influenza A virus neuraminidase (NA) protein to investigate the spatial recognition relationship between the antigenic epitopes and antibody paratopes. MethodsStructural data on NA protein antigen-antibody complexes were comprehensively collected from the SAbDab database, and processed to obtain the amino acid sequences and spatial distribution information on antigenic epitopes and corresponding antibody paratopes. Statistical analysis was conducted on the antibody sequences, frequency of use of genes, amino acid preferences, and the lengths of complementarity determining regions (CDR). Epitope hotspots for antibody binding were analyzed, and the spatial structural similarity of antibody paratopes was calculated and subjected to clustering, which allowed for a comprehensively exploration of the spatial recognition relationship between antigenic epitopes and antibodies. The specificity of antibodies targeting different antigenic epitope clusters was further validated through bio-layer interferometry (BLI) experiments. ResultsThe collected data revealed that the antigen-antibody complex structure data of influenza A virus NA protein in SAbDab database were mainly from H3N2, H7N9 and H1N1 subtypes. The hotspot regions of antigen epitopes were primarily located around the catalytic active site. The antibodies used for structural analysis were primarily derived from human and murine sources. Among murine antibodies, the most frequently used V-J gene combination was IGHV1-12*01/IGHJ2*01, while for human antibodies, the most common combination was IGHV1-69*01/IGHJ6*01. There were significant differences in the lengths and usage preferences of heavy chain CDR amino acids between antibodies that bind within the catalytic active site and those that bind to regions outside the catalytic active site. The results revealed that structurally similar antibodies could recognize the same epitopes, indicating a specific spatial recognition between antibody and antigen epitopes. Structural overlap in the binding regions was observed for antibodies with similar paratope structures, and the competitive binding of these antibodies to the epitope was confirmed through BLI experiments. ConclusionThe antigen epitopes of NA protein mainly ditributed around the catalytic active site and its surrounding loops. Spatial complementarity and electrostatic interactions play crucial roles in the recognition and binding of antibodies to antigenic epitopes in the catalytic region. There existed a spatial recognition relationship between antigens and antibodies that was independent of the uniqueness of antibody sequences, which means that antibodies with different sequences could potentially form similar local spatial structures and recognize the same epitopes.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.