ObjectiveTo construct a competency model for "dual-qualified" teachers in vocational undergraduate rehabilitation therapy programs based on the World Health Organization's rehabilitation competency framework (RCF) and relevant domestic and international standards, and explore the training pathways for rehabilitation therapy teachers in China. MethodsLiterature analysis and comparative research methods were employed to systematically review RCF, physiotherapist-education-framework-FINAL, the Minimum-Standards-for-the-Education-of-Occupational-Therapists, and the "dual-qualified" teacher standards in vocational education for China. Focusing on the characteristics of vocational undergraduate talent cultivation, it took the integration of the "educator-clinical rehabilitation therapist" dual roles as its starting point, combining rehabilitation industry competence with educator standards as its basic principle, and using RCF as its foundational dimension. It then integrated advanced competency dimensions required of vocational undergraduate teachers to form a dimensional framework. Following the systematic curriculum development concept of the work process, the core activities of each dimension were designed by combining, improving and expanding the concept integration method, and describing the ability characteristics in a graded and progressive manner, to construct a model. ResultsThis model was guided by the core concepts of three types of values ​​and four types of professional beliefs. Vertically, it encompassed 28 activities across eight competency dimensions, including teaching practice, rehabilitation practice, digital literacy, professionalism, learning and development, management and leadership, applied research, and social service. Horizontally, it encompassed 53 corresponding competency characteristics across three advanced levels (beginner, intermediate and advanced). ConclusionThis model, through its vertical dimension design and horizontal progressive development, clearly describes the advancement of vocational undergraduate rehabilitation therapy teachers from newly hired teachers to backbone teachers and professional leaders. It not only aligns with the general requirements of the national standards for "dual-qualified" teachers in higher vocational colleges in China, but also incorporates an international perspective on rehabilitation education and practice, and possesses the characteristics of vocational undergraduate education that integrates multiple abilities and roles. At the theoretical level, it provides core theoretical support for establishing standardized and internationalized "dual-qualified" teacher standards for vocational undergraduate rehabilitation therapy programs in China; at the practical level, it serves as an "action map" for teacher professional development, assessment and evaluation, providing a key reference for constructing a systematic high-end skilled rehabilitation talent training system.

ObjectiveTo construct a competency model for "dual-qualified" teachers in vocational undergraduate rehabilitation therapy programs based on the World Health Organization's rehabilitation competency framework (RCF) and relevant domestic and international standards, and explore the training pathways for rehabilitation therapy teachers in China. MethodsLiterature analysis and comparative research methods were employed to systematically review RCF, physiotherapist-education-framework-FINAL, the Minimum-Standards-for-the-Education-of-Occupational-Therapists, and the "dual-qualified" teacher standards in vocational education for China. Focusing on the characteristics of vocational undergraduate talent cultivation, it took the integration of the "educator-clinical rehabilitation therapist" dual roles as its starting point, combining rehabilitation industry competence with educator standards as its basic principle, and using RCF as its foundational dimension. It then integrated advanced competency dimensions required of vocational undergraduate teachers to form a dimensional framework. Following the systematic curriculum development concept of the work process, the core activities of each dimension were designed by combining, improving and expanding the concept integration method, and describing the ability characteristics in a graded and progressive manner, to construct a model. ResultsThis model was guided by the core concepts of three types of values ​​and four types of professional beliefs. Vertically, it encompassed 28 activities across eight competency dimensions, including teaching practice, rehabilitation practice, digital literacy, professionalism, learning and development, management and leadership, applied research, and social service. Horizontally, it encompassed 53 corresponding competency characteristics across three advanced levels (beginner, intermediate and advanced). ConclusionThis model, through its vertical dimension design and horizontal progressive development, clearly describes the advancement of vocational undergraduate rehabilitation therapy teachers from newly hired teachers to backbone teachers and professional leaders. It not only aligns with the general requirements of the national standards for "dual-qualified" teachers in higher vocational colleges in China, but also incorporates an international perspective on rehabilitation education and practice, and possesses the characteristics of vocational undergraduate education that integrates multiple abilities and roles. At the theoretical level, it provides core theoretical support for establishing standardized and internationalized "dual-qualified" teacher standards for vocational undergraduate rehabilitation therapy programs in China; at the practical level, it serves as an "action map" for teacher professional development, assessment and evaluation, providing a key reference for constructing a systematic high-end skilled rehabilitation talent training system.

ObjectiveTo construct a competency model for "dual-qualified" teachers in vocational undergraduate rehabilitation therapy programs based on the World Health Organization's rehabilitation competency framework (RCF) and relevant domestic and international standards, and explore the training pathways for rehabilitation therapy teachers in China. MethodsLiterature analysis and comparative research methods were employed to systematically review RCF, physiotherapist-education-framework-FINAL, the Minimum-Standards-for-the-Education-of-Occupational-Therapists, and the "dual-qualified" teacher standards in vocational education for China. Focusing on the characteristics of vocational undergraduate talent cultivation, it took the integration of the "educator-clinical rehabilitation therapist" dual roles as its starting point, combining rehabilitation industry competence with educator standards as its basic principle, and using RCF as its foundational dimension. It then integrated advanced competency dimensions required of vocational undergraduate teachers to form a dimensional framework. Following the systematic curriculum development concept of the work process, the core activities of each dimension were designed by combining, improving and expanding the concept integration method, and describing the ability characteristics in a graded and progressive manner, to construct a model. ResultsThis model was guided by the core concepts of three types of values ​​and four types of professional beliefs. Vertically, it encompassed 28 activities across eight competency dimensions, including teaching practice, rehabilitation practice, digital literacy, professionalism, learning and development, management and leadership, applied research, and social service. Horizontally, it encompassed 53 corresponding competency characteristics across three advanced levels (beginner, intermediate and advanced). ConclusionThis model, through its vertical dimension design and horizontal progressive development, clearly describes the advancement of vocational undergraduate rehabilitation therapy teachers from newly hired teachers to backbone teachers and professional leaders. It not only aligns with the general requirements of the national standards for "dual-qualified" teachers in higher vocational colleges in China, but also incorporates an international perspective on rehabilitation education and practice, and possesses the characteristics of vocational undergraduate education that integrates multiple abilities and roles. At the theoretical level, it provides core theoretical support for establishing standardized and internationalized "dual-qualified" teacher standards for vocational undergraduate rehabilitation therapy programs in China; at the practical level, it serves as an "action map" for teacher professional development, assessment and evaluation, providing a key reference for constructing a systematic high-end skilled rehabilitation talent training system.

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.

Objective To investigate the temporal changes in pathological damage and macrophage polarization in liver and spleen tissues of mice infected with Angiostrongylus cantonensis, and to preliminarily unravel the peripheral immune responses during the early stage of A. cantonensis infection. Methods Forty female BALB/c mice at ages of 6 to 8 weeks were randomly divided into four groups, including the control group and 7-, 14-, and 21-day infection groups, with 10 mice in each group. Each mouse in the infection groups was inoculated with 30 third-stage (L3) larvae of A. cantonensis by oral gavage, and five mice were randomly selected from each infection group on days 7, 14, and 21 post-infection, while mice in the control group were given the same volume of physiological saline and five mice were randomly selected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled. The histopathological changes of mouse liver and spleen tissues were observed using hematoxylin and eosin (HE) staining, and the percentage of positive staining area and the co-localization positive rates of the macrophage surface antigens F4/80, CD86, and CD206 were quantified in mouse liver and spleen tissues using immunohistochemical and immunofluorescence staining. In addition, five mice were collected from each infection group on days 7, 14, and 21 post-infection, and five mice were collected from the control group on the day of oral gavage. Mouse liver and spleen tissues were sampled for detection of macrophage markers CD86 and CD206 and macrophage phenotyping using flow cytometry, and the expression of M1 macrophage markers, including inducible nitric oxide synthase (Nos2), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β) and M2 markers, including arginase 1 (Arg1), mannose receptor C-type 1 (Mrc1) and chitinase-like protein 3 (Chil3) was quantified in mouse liver and spleen tissues using real-time quantitative PCR (RT-qPCR) assay. Results Proliferative lesions of the hepatocyte were observed in mouse liver tissues and the follicular structures of the mouse spleen white pulp were disrupted 21 days post-infection with A. cantonensis. Immunohistochemical staining showed that there were significant differences in the percentages of F4/80, CD86 and CD206 positive staining areas in the liver and spleen tissues among the four groups of mice (F = 242.40, 197.14, 183.19, 157.65, 242.35 and 146.24; all P values < 0.001), and the percentages of positive staining in the liver and spleen tissues of mice in the 14-day infection group [(4.45 ± 0.51)%, (3.74 ± 0.67)%, (8.32 ± 0.72)%, (16.56 ± 1.14)%, (11.62 ± 0.52)%, and (8.29 ± 0.72)%, respectively] and the 21-day infection group [(3.70 ± 0.11)%, (3.22 ± 0.43)%, (11.53 ± 1.03)%, (12.59 ± 1.05)%, (9.02 ± 0.83)%, and (11.67 ± 1.10)%, respectively] were higher than in the control group [(0.35 ± 0.16)%, (0.40 ± 0.02)%, (0.93 ± 0.05)%, (2.78 ± 0.26)%, (2.33 ± 0.20)%, and (1.85 ± 0.20)%, respectively] (all P values < 0.05). Immunofluorescence staining showed significant differences in the positive rates of F4/80 co-localization with CD86 and CD206 in mouse liver and spleen tissues among the four groups (F = 24.42, 25.28, 54.51 and 130.55; all P values < 0.001). Flow cytometry detected significant differences in the proportions of CD86⁺ and CD206⁺ macrophages in mouse liver and spleen tissues among the four groups (F = 67.98, 18.41, 29.77, 172.80; all P values < 0.001), and the proportions of CD206⁺ macrophages in the liver and spleen of the 21-day infection group were significantly higher than those in the control group [(9.25 ± 2.55)% vs (3.83 ± 0.72)%, and (4.22 ± 0.56)% vs (0.47 ± 0.18)%, respectively] (both P values < 0.05). In addition, RT-qPCR assay quantified significant differences in the relative mRNA expression of M1 macrophage markers (IL-1β, TNF-α and Nos2) and M2 macrophage markers (Arg1, Chil3 and Mrc1) in mouse liver and spleen tissues among the four groups (F = 41.30, 31.82, 199.33, 19.96, 62.01, 119.76, 23.67, 95.90, 72.27, 82.59, 123.41 and 29.75; all P values < 0.05). Conclusions A. cantonensis infection may cause progressive pathological damage in mouse liver and spleen tissues, accompanied by dynamic temporal changes in macrophage polarization. M1 macrophage polarization predominates at the early stage of A. cantonensis infection and shifts towards M2 polarization at the later stages, suggesting that M2 polarization may participate in immune regulation at late stages of A. cantonensis infection by suppressing excessive inflammatory responses and promoting tissue repair.

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.

Introduction: Diabetic ketoacidosis (DKA) is a life-threatening complication associated with significant morbidity and healthcare burden. Despite advances in diabetes care, recurrent DKA remains common, often reflecting gaps in treatment adherence and patient education. Identifying predictors of recurrence is crucial for risk stratification and targeted intervention. Methodology: We conducted a retrospective observational study of all adult DKA admissions to a tertiary centre between 2001 and 2025. Electronic medical records were reviewed for demographic data, biochemical parameters, precipitating factors, and clinical outcomes. DKA was defined using standard biochemical criteria. Recurrent DKA was defined as ≥2 admissions during the study period. Factors associated with recurrent DKA admissions were analyzed. Patients under the age of 18 years and those with missing vital information were excluded. Results: A total of 667 DKA admissions, comprising 566 patients, were identified, of which 101 admissions (15.1%) were recurrent, involving 65 patients. Among recurrent DKA episodes, the most common precipitating factors were infection (64.4%) and insulin omission (62.4%). After multivariate analyses, patients with type 1 diabetes mellitus (T1DM) were more likely to develop recurrent DKA compared to those with type 2 diabetes mellitus (aOR 4.16; 95% confidence interval [CI] 2.58–6.70; p <0.001). Insulin omission was strongly associated with recurrent DKA (aOR 2.29; 95% CI 1.46–3.60; p <0.001). In contrast, baseline glycated hemoglobin and chronic kidney disease were not significantly associated with recurrence. Diabetic counseling during the first DKA admission did not reduce recurrent DKA. There were no significant differences in mortality (3.9% vs 6.2%, p = 0.524) or critical care admission rates (40.6% vs 38.7%, p = 0.718) between recurrent and first DKA episodes. Conclusion Recurrent DKA accounts for a substantial proportion of DKA admissions and is strongly associated with insulin omission and T1DM. Our findings suggest that recurrent DKA is driven predominantly by behavioral and adherencerelated factors, indicating the need for multidisciplinary interventions beyond standard inpatient counseling.
Diabetic Ketoacidosis ; Retrospective Studies

Introduction: Diabetic ketoacidosis (DKA) in pregnancy is an uncommon yet life-threatening emergency, with disproportionate risks to both mother and fetus. Pregnancy-specific physiological changes predispose patients to rapid metabolic decompensation, often with atypical presentations. Despite this, local data remain limited. We describe the clinical profile, precipitating factors, and outcomes of DKA in pregnancy in a tertiary centre, with emphasis on potentially preventable triggers. Cases: Nine pregnant patients with DKA were identified from a retrospective review of all cases admitted for DKA from 2002 to 2025. Mean age was 31.67 ± 5.20 years; all were Malay. The majority had type 2 diabetes mellitus (55.6%), followed by type 1 diabetes (33.3%) and latent autoimmune diabetes in adults (11.1%). The mean period of amenorrhea was 19.67 ± 12.62 weeks. Infection was the leading precipitant (44.4%), with additional triggers including insulin omission (22.2%), hyperemesis gravidarum, preterm labor, steroid exposure, and perioperative fasting. Most diagnoses were made in the emergency department (55.6%). Biochemical parameters reflected significant severity (mean bicarbonate 7.89 ± 2.98 mmol/L; anion gap 25.00 ± 5.81), with 88.9% classified as severe DKA. Intensive Care Unit (ICU) care was required in 77.8% of cases. The majority (77.8%) were admitted to the ICU unit, with a median time to resolution of 13.00 ± 12.00 hours (interquartile range [IQR]), and the median hospital length of stay was 7.00 ± 5.00 days (IQR). Complications during treatment included hypokalemia (33.3%), acute kidney injury (22.2%), and hypoglycemia (11.1%). Rebound DKA occurred in one-third of patients. All patients were discharged clinically stable. Outcome data demonstrated pregnancy loss in three cases and one preterm birth. Conclusion DKA in pregnancy remains a severe and resource-intensive condition. This series highlights missed opportunities in prevention, with modifiable precipitants such as infection and insulin omission commonly identified. The high severity at presentation suggests delays in recognition. Early detection, optimized metabolic care, and targeted preventive strategies are crucial to improving maternal and fetal outcomes.
Female ; Pregnancy ; Diabetic Ketoacidosis

Objective To systematically evaluate the risk prediction models for anastomotic leakage (AL) in patients with esophageal cancer after surgery. Methods A computer-based search of PubMed, EMbase, Web of Science, Cochrane Library, Chinese Medical Journal Full-text Database, VIP, Wanfang, SinoMed and CNKI was conducted to collect studies on postoperative AL risk prediction model for esophageal cancer from their inception to October 1st, 2023. PROBAST tool was employed to evaluate the bias risk and applicability of the model, and Stata 15 software was utilized for meta-analysis. Results A total of 19 literatures were included covering 25 AL risk prediction models and 7373 patients. The area under the receiver operating characteristic curve (AUC) was 0.670-0.960. Among them, 23 prediction models had a good prediction performance (AUC>0.7); 13 models were tested for calibration of the model; 1 model was externally validated, and 10 models were internally validated. Meta-analysis showed that hypoproteinemia (OR=9.362), postoperative pulmonary complications (OR=7.427), poor incision healing (OR=5.330), anastomosis type (OR=2.965), preoperative history of thoracoabdominal surgery (OR=3.181), preoperative diabetes mellitus (OR=2.445), preoperative cardiovascular disease (OR=3.260), preoperative neoadjuvant therapy (OR=2.977), preoperative respiratory disease (OR=4.744), surgery method (OR=4.312), American Society of Anesthesiologists score (OR=2.424) were predictors for AL after esophageal cancer surgery. Conclusion At present, the prediction model of AL risk in patients with esophageal cancer after surgery is in the development stage, and the overall research quality needs to be improved.