ObjectiveTo develop an assessment tool for apraxia of speech (AOS) of Chinese Putonghua speakers and test its reliability and validity. MethodsThe Chinese Apraxia of Speech Assessment and Diagnostic Tool (CAADT) was developed based on the Apraxia of Speech Rating Scale 3.5, combined with the linguistic characteristics of Chinese and clinical experience. The tool consistsed of eleven items across three sections: articulation, prosody and alternating motion rates. Six experts evaluated the content validity. From November, 2024 to May, 2025, 51 patients with post-stroke AOS (experimental group) and ten patients with post-stroke aphasia without AOS (control group) were recruited from Anhui Wannan Rehabilitation Hospital (the Fifth People's Hospital of Wuhu), and tested with CAADT. Reliability was assessed using Cronbach's α coefficient, Kendall's coefficient of concordance W and Pearson correlation coefficient. Validity was evaluated using the content validity index (CVI) and Spearman correlation coefficient. Discriminative effect was analyzed using the receiver operating characteristic (ROC) curve. ResultsThe Cronbach's α coefficients for the articulation and prosody sections and the total scale were all > 0.9, while it was 0.454 for the alternating motion rates. Inter-rater reliability was good (W ≥ 0.598, P < 0.001). Test-retest reliability showed high positive correlations for the three sections and the total score between the two assessments (r ≥ 0.84, P < 0.001). The scale-level CVI was 0.95, and the item-level CVI ≥ 0.83. The Spearman correlation coefficients among the sections ranged from 0.30 to 0.70. ROC analysis revealed an area under the curve of 0.953, with a cut-off value of 11, yielding a sensitivity of 0.92 and a specificity of 0.90. ConclusionCAADT demonstrates good reliability, validity and discriminative effect, which can be used for clinical assessment and auxiliary diagnosis of Chinese Putonghua speaking patients with post-stroke AOS.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

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.

ObjectiveTo systematically compare the effects of diverse electromagnetic stimulation protocols on hand function and activities of daily living (ADL) in stroke patients using network meta-analysis (NMA), and screen the optimal stimulation strategy for post-stroke hand dysfunction rehabilitation. MethodsNMA was performed in accordance with the PRISMA-NMA statement. Databases of CNKI, Wanfang data, VIP, CBM, PubMed, Web of Science and Embase were searched from database inception to April, 2026 for eligible randomized controlled trials (RCTs) comparing different electromagnetic stimulation protocols for post-stroke hand impairment. The Cochrane Risk of Bias tool and PEDro scale were used to assess methodological quality of included studies, while the GRADE system was adopted to grade evidence quality of primary outcomes of Fugl-Meyer Assessment-Upper Extremities (FMA-UE) and modified Barthel Index (MBI). After literature screening, data extraction and bias evaluation, RevMan 5.4 and Stata 17.0 were used for meta-analysis and NMA. ResultsA total of 22 RCT involving 17 electromagnetic stimulation protocols were finally included. The PEDro scores ranged from six to ten. The top five protocols for improving FMA-UE score were repetitive peripheral magnetic stimulation (rPMS) + repetitive transcranial magnetic stimulation (rTMS), intermittent theta-burst stimulation (iTBS) + rPMS, iTBS + transcranial direct current stimulation (tDCS), transcutaneous electrical acupoint stimulation (TEAS) and contralaterally controlled functional electrical stimulation (CCFES). tDCS was the most effective on MBI, followed by TEAS and iTBS+rPMS. Evidence quality for FMA-UE and MBI was moderate. Funnel plots suggested low risk of publication bias, and consistency tests verified good coherence between direct and indirect comparisons in network models. ConclusionElectromagnetic stimulation significantly facilitates upper limb and hand functional recovery, and improves ADL in stroke patients. The combined central-peripheral magnetic stimulation protocol may be the most effective on motor rehabilitation, whereas tDCS on ADL.

Objective: To analyze the characteristics and key risk factors of abnormal blood disposal throughout the 2024-2025 blood collection and supply process based on nationwide multi-site monitoring data, develop a comprehensive prevention and control strategy across the entire chain, reduce preventable blood waste, and ensure clinical blood safety. Methods: According to the Guidelines for Haemovigilance (T/CSBT 001-2026), we extracted 74 cases of abnormal blood disposal events reported by the China Blood Transfusion Association′s Blood Safety Monitoring System from January 1 2024, to December 31 2025, and conducted descriptive statistical analysis on the distribution of events, types of deviations, root causes, and classifications of disposal manifestations. Results: A total of 664 adverse events related to blood collection and supply were reported over two years, with 74 cases involving discarded abnormal blood units, accounting for 11.1% of the total. Among these, blood component preparation (40.5%) and blood collection (37.8%) remained traditional high-risk stages. The proportion of blood waste occurring during storage, distribution, and transportation increased from 7.7% in 2024 to 34.3% in 2025. Deviations from standard operating procedures (SOP) by personnel were the primary cause, accounting for 74.3% of cases. Discarded blood units were categorized into four types: compromised closed blood bag systems (40 cases), mainly due to inadequate heat sealing, physical damage, or dropped bags; blood out of the cold chain (12 cases), primarily resulting from blood being left at work sites; imbalanced proportion of preservation solution (10 cases), mostly caused by blood collection volumes exceeding the standard capacity of blood bags; and other causes (12 cases). Conclusion: Human operational errors are the core cause of abnormal blood waste. The collection and preparation stages have long been at high-risk, and the risks in the storage and transportation stages have been increasing year by year. We should focus on standardizing personnel management, improving specialized operation norms such as heat sealing, transportation, and storage, establishing a full-process intelligent cold chain monitoring and multi-node visual verification mechanism, and systematically reducing the occurrence rate of abnormal blood waste through a closed-loop quality intervention system, thereby improving the utilization efficiency of voluntary blood donation resources.

ObjectiveTo establish fingerprint profiles and a quantitative determination method for Lycii Cortex， providing a scientific basis for the formulation of quality standards for Lycii Cortex and its roasted products. MethodsHigh performance liquid chromatography（HPLC） was developed for the quantitative method for determining kukoamine B in Lycii Cortex and its roasted products on an Alphasil XD-C₁₈ CH column（4.6 mm×250 mm， 5 μm）. HPLC fingerprint profiles were established for 10 batches of Lycii Cortex and its roasted products， and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was used to identify the common peaks based on reference standards， literature and MS information. Quality evaluation indicators included yield of decoction pieces， appearance properties， content of kukoamine B， and fingerprint profiles. The temperature and time of the roasting process were investigated to select the optimal preparation process， which was then verified. Additionally， chemical pattern recognition was combined to assess the differences in the chemical composition of Lycii Cortex before and after roasting， as well as among samples from different origins. ResultsQuantitative analysis indicated that the contents of kukoamine B in Lycii Cortex and its roasted products were 0.35%-5.51% and 0.24%-4.15%， respectively. The transfer rate of kukoamine B was 58.6%-78.9% after roasting. The fingerprint profile analysis demonstrated that the method established in this study effectively separated kukoamine B from other components in the samples and distinctly differentiated it from its impurity peak， cis-N-caffeoylputrescine. The HPLC fingerprint profiles of Lycii Cortex and its roasted products showed high similarity（all above 0.95）， with 7 common peaks identified and five common components， including kukoamine B， cis-N-caffeoylputrescine， N-coumaroyl tyramine， feruloyltyramine， and glucosyringic acid， confirmed. Process optimization confirmed that baking at 110 ℃ for 20 min was a stable and feasible method for roasting Lycii Cortex. Principal component analysis and cluster analysis showed that there was little difference in the chemical composition between raw and roasted Lycii Cortex， but the quality of Lycii Cortex from different origins differed greatly. ConclusionThis study successfully established the fingerprint profiles and a quantitative method for the effective component kukoamine B in Lycii Cortex and roasted Lycii Cortex. The qualitative and quantitative analyses clarified that the impact of the roasting process on the chemical composition of Lycii Cortex was less significant than the variations due to its geographical origin. The findings of this study offer a reference for the development of quality evaluation methods and the establishment of quality standards for Lycii Cortex and its processed products.

Objective To design a precision nutrition information management system to improve clinical nutrition diagnosis and treatment.Methods A precision nutrition information management system was developed with such technologies as Internet,big data and remote diagnosis and treatment,which was composed of a hardware system and a software system.The hardware system consisted of a Web and interface server,a database server,a front-end server,a personal digital assistant,a barcode scanner and a label printer;the software system with B/S architecture encapsulated business functions into reusable and easily expandable modular components based on.NET technology stack,which was made up of three subsystems for outpatient nutrition diagnosis and treatment,inpatient nutrition diagnosis and treatment and nutrition stocking management.Results The system developed realized data sharing and interaction among multi information systems,and contributed to implementing rational,normalized and efficient outpatient nutrition diagnosis and treatment,inpatient nutrition support and nutrition stocking management.Conclusion The system developed meets the requirements for clinical nutrition diagnosis and treatment and enhances clinical nutrition service.[Chinese Medical Equipment Journal,2025,46(10):41-48]

Objective:To observe the characteristics of brain functional activity in patients with chronic non-specific low back pain(CNLBP)and to explore the potential mechanism of brain functional remodeling in acupuncture treatment based on resting-state fMRI.Method:The 22 patients with CNLBP were included as the CNLBP group,and 22 healthy subjects(HCs)were included as the HCs group.The visual analogue scale(VAS)for pain,Oswestry disability index(ODI),Japanese Orthopedic Association(JOA)score for lumbar spine were collected before and after acu-puncture treatment in the CNLBP group.Resting-state fMRI data were acquired for all participants.The frac-tional amplitude of low frequency fluctuation(fALFF)values of the different brain regions in CNLBP patients before treatment compared with the HCs group were extracted and correlated with the differences in VAS,ODI,and JOA scores.Result:Acupuncture treatment significantly improved the VAS,ODI,and JOA scores in the CNLBP group(P＜0.001);Before treatment,the CNLBP group showed higher fALFF values in the right orbital middle frontal gy-rus,right anterior cingulate gyrus,left anterior cingulate gyrus and left precuneus compared to the HCs group,while lower fALFF values were observed in the right precentral gyrus/right postcentral gyrus,left precentral gy-rus/left postcentral gyrus,right thalamus,right postcentral gyrus/precentral gyrus,and left thalamus.After treat-ment,the CNLBP group exhibited increased fALFF values in the right precentral gyrus/postcentral gyrus,left precentral gyrus/postcentral gyrus,and left middle temporal gyrus,and decreased fALFF values in the left me-dial superior frontal gyrus,right precuneus/left precuneus compared to pre-treatment.Additionally,pre-treatment fALFF value in the right orbital part of the middle frontal gyrus,right anterior cingulate gyrus and left anteri-or cingulate gyrus in the CNLBP group was negatively correlated with the changes in VAS scores(r=-0.699,P=0.000).Conclusion:Acupuncture treatment can significantly improve pain intensity and lumbar spinal dysfunction in CNLBP.CNLBP has multiple abnormalities in brain functional activities related to pain regulation pathways and the default mode network(DMN),and acupuncture treatment can restore most of these abnormal brain ac-tivities;the characteristic of brain functional activity in the right orbital part of the middle frontal gyrus,right anterior cingulate gyrus and left anterior cingulate gyrus before CNLBP treatment is related to the difference in VAS score,providing a potential imaging biomarker for predicting treatment efficacy.

Thermal ablation (TA) is a widely applied minimally invasive treatment for benign thyroid nodules and low-risk papillary thyroid microcarcinoma. Compared to conventional surgery, TA offers advantages such as minimal trauma, rapid recovery, and no scarring. However, this procedure may lead to various complications, including intraoperative pain, nerve injury, hemorrhage, tracheal injury, skin burns, vasovagal reactions, nodule rupture, and thyroid dysfunction. Although TA demonstrates excellent safety and efficacy, further standardization of procedural protocols is necessary to minimize the incidence of complications.