iLABMED最新文献

{"title":"The Expanding Role of Companion Diagnostics in Infectious Diseases: Lessons From Abacavir and Human Immunodeficiency Virus Care","authors":"Yi-Wei Tang, Eric von Hofe","doi":"10.1002/ila2.70054","DOIUrl":"https://doi.org/10.1002/ila2.70054","url":null,"abstract":"<p>Precision medicine has become a defining paradigm in modern healthcare, with companion diagnostics (CDx) playing a central role in tailoring therapies to individual patient characteristics [<span>1, 2</span>]. While the utility of CDx has been well established in oncology, its role in infectious diseases is only now beginning to be realized. The unique intersection between host genetics, pathogen diversity, and therapeutic variability offers fertile ground for applying CDx approaches in infectious disease management.</p><p>One of the most striking early examples of CDx in infectious diseases is the use of HLA-B*57:01 genotyping to prevent hypersensitivity reactions to abacavir, an antiretroviral medication used in HIV treatment. This case not only highlights the power of pharmacogenetics in improving safety and efficacy but also serves as a model for the broader application of companion diagnostics in infectious diseases. In this commentary, we explore the current state, challenges, and future potential of CDx in the infectious disease landscape, using abacavir as a case study and reflecting on broader implications for clinical practice and research.</p><p>A companion diagnostic is a medical test that provides essential information for the safe and effective use of a corresponding drug or therapy. While the term originated in oncology, its broader definition encompasses tests that identify biomarkers—either from the host or the pathogen—that can influence drug response, toxicity, or efficacy. In infectious diseases, this includes pharmacogenetic tests (e.g., host genes affecting drug metabolism or immune response), pathogen genotyping (e.g., identifying resistance mutations), and immunologic profiling.</p><p>Companion diagnostics in infectious diseases can serve several functions: (1) Predict adverse drug reactions (e.g., hypersensitivity, hepatotoxicity), (2) Guide antimicrobial selection based on pathogen genotype or resistance profile, (3) Stratify patients for immune-modulating therapies (e.g., corticosteroids, monoclonal antibodies), and (4) Predict disease progression or response to vaccines. Despite these broad applications, the routine clinical use of CDx in infectious diseases has lagged behind other specialties, in part due to the complexity of host-pathogen interactions and the logistical challenges of implementing molecular testing in real-world settings. However, advances in genomic medicine, decreasing costs of sequencing technologies, and increased awareness of antimicrobial stewardship are creating new momentum for CDx adoption.</p><p>Abacavir is a guanosine analog nucleoside reverse transcriptase inhibitor (NRTI) that has been a component of combination antiretroviral therapy (ART) for HIV (human immunodeficiency virus) infection since its approval in the late 1990s. Although abacavir is generally effective and well-tolerated, approximately 5%–8% of patients were found to develop a severe hypersensitivity reaction (HSR) within","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"113-115"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70054","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148343307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnosis of Acute Hemolytic Transfusion Reaction Caused by Cold Reactive Anti-P1 Antibody: A Case Report","authors":"Ke Song,&nbsp;Chunya Ma,&nbsp;Wenjia Zhang,&nbsp;Shilan Gao,&nbsp;Xin Zhang,&nbsp;Wei Yang,&nbsp;Yang Yu","doi":"10.1002/ila2.70059","DOIUrl":"https://doi.org/10.1002/ila2.70059","url":null,"abstract":"<p>Anti-P1 alloantibody is predominantly an immunoglobulin M class, cold reactive antibody that is non-reactive at 37°C in routine pre-transfusion serology and thus generally regarded as clinically insignificant. However, rare clinically significant anti-P1 antibodies can cause an acute hemolytic transfusion reaction (AHTR), and routine pre-transfusion testing at 37°C may miss such antibodies. We report a case of AHTR caused by an anti-P1 antibody detectable only at 4°C, which evaded detection by unexpected antibody screening performed at 37°C. A 65-year-old woman with blood group B, RhD positive developed AHTR within 24 h following red blood cell transfusion. She presented with coffee-colored urine, markedly elevated bilirubin and lactate dehydrogenase concentrations, and a progressive decline in hemoglobin concentrations. Pre-transfusion antibody screening at 37°C was negative. A retrospective serological analysis identified anti-P1 exclusively at 4°C, which was confirmed by pigeon egg white inhibition. The patient was P1 negative; incompatibility occurred only with the P1-positive donor unit. After transfusion of P1 antigen-negative red blood cells, the hemolysis resolved and hemoglobin concentrations recovered. In patients with a repeated transfusion history, serological testing at 37°C and 4°C, in conjunction with antigen-matched selection, is essential to prevent AHTR caused by clinically significant cold reactive antibodies.</p>","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"108-112"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148343112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatial Organization of Fibrosis in Stricturing Crohn's Disease","authors":"Wenyu Zhang,&nbsp;Changwei Duan,&nbsp;Xianzong Ma","doi":"10.1002/ila2.70063","DOIUrl":"https://doi.org/10.1002/ila2.70063","url":null,"abstract":"&lt;p&gt;Crohn's disease (CD) is a chronic inflammatory bowel disease in which cumulative tissue injury can culminate in irreversible structural damage [&lt;span&gt;1&lt;/span&gt;]. Although biologic therapies targeting tumor necrosis factor, interleukin-23, and integrins have improved the control of inflammatory activity, they have had far less impact on fibrosis-related complications [&lt;span&gt;2, 3&lt;/span&gt;]. In stricturing CD, progressive extracellular matrix deposition, mural thickening, and luminal narrowing lead to obstruction and often surgery [&lt;span&gt;1, 2, 4&lt;/span&gt;]. Fibrosis is therefore one of the most consequential and least tractable features of disease progression.&lt;/p&gt;&lt;p&gt;One of the major challenges in studying fibrosis is that molecular changes can be characterized in detail, but are often difficult to map onto the tissue architecture in which fibrosis develops. Dissociation-based transcriptomic approaches can identify disease-associated cell states with increasing precision but do not preserve the spatial relationships that shape local pathology [&lt;span&gt;5-7&lt;/span&gt;]. Kong et al. [&lt;span&gt;8&lt;/span&gt;] have addressed this limitation by integrating single-cell RNA sequencing with spatial transcriptomics, using intestinal tissue from patients with stricturing CD and appropriate controls. Their study offers more than an expanded cell atlas: it places stromal, immune, and neural populations within the same anatomical framework and explores how these elements are organized in fibrotic tissue.&lt;/p&gt;&lt;p&gt;Fibrosis in CD is often discussed in terms of mesenchymal activation and excessive matrix production [&lt;span&gt;4, 5, 7&lt;/span&gt;]. This framework remains valid, but the present study [&lt;span&gt;8&lt;/span&gt;] indicates that it is incomplete. Tissue changes associated with stricture formation are not distributed at random; rather, they are concentrated within discrete microenvironments in which specific stromal and immune populations co-localize [&lt;span&gt;8&lt;/span&gt;]. Seen in this light, fibrosis is not simply the cumulative outcome of chronic inflammation—it is also a problem of tissue organization.&lt;/p&gt;&lt;p&gt;The enrichment of inflammatory fibroblasts (activated stromal cells, characterized by the expression of inflammatory mediators alongside matrix remodeling programs) and tertiary lymphoid structures within strictured tissue represents an important shift in emphasis [&lt;span&gt;8&lt;/span&gt;]. It suggests that the relevant pathological unit may be a multicellular niche rather than an isolated fibroblast population. The spatial mapping of known CD risk-associated gene modules to areas enriched for inflammatory fibroblasts and lymphoid follicles further strengthens this interpretation. These data do not in themselves establish a causal hierarchy; however, they do provide a relatively concrete anatomical setting in which genetic susceptibility may be translated into local disease behavior.&lt;/p&gt;&lt;p&gt;Single-cell studies have already transformed the study of inflammatory bowel disease by revealing epithelial, strom","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"126-129"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148343046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gut Microbiota: A Reservoir for Extraintestinal Bacterial Infections in Febrile Term Infants","authors":"Ran Wang,&nbsp;Renqiang Yu","doi":"10.1002/ila2.70057","DOIUrl":"https://doi.org/10.1002/ila2.70057","url":null,"abstract":"&lt;p&gt;The rate of extraintestinal bacterial infections (EBIs), which commonly include the urinary tract, blood, and meninges, is particularly high in infants under 60 days of age [&lt;span&gt;1&lt;/span&gt;]. This commentary discusses a recent study of EBIs in infants and identifies future research directions that may support the development of new strategies for their prevention and treatment. Clinical and microbiological approaches often fail to pinpoint the origin of pathogenic strains in term infants, highlighting a major diagnostic challenge in identifying the source of sepsis and invasive EBIs. However, current antibiotic treatment also has limitations. For example, although antibiotic treatment during the perinatal period can reduce the incidence of early-onset group B streptococcal infection in newborns, it cannot reduce the incidence of late-onset early-onset group B streptococcal infection [&lt;span&gt;2&lt;/span&gt;]. Furthermore, antibiotic treatment in the early stages of life can lead to the development of antibiotic resistance and disruption of the gut microbiota in infants [&lt;span&gt;3&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;These unmet clinical needs provide a strong rationale for the gut reservoir hypothesis, as demonstrated by DeVeaux et al. in a multicenter, matched case–control study of febrile term infants (≤ 60 days of age) with and without documented EBIs. Their findings support gut microbiota screening for early-risk stratification of EBIs, facilitating more targeted antibiotic use and advancing the standard of care for young febrile infants [&lt;span&gt;4&lt;/span&gt;]. The gut microbiota plays an important role in infant and childhood development, including aiding digestion to release nutrients, defending against pathogens, and regulating the immune system [&lt;span&gt;5&lt;/span&gt;]. In addition, numerous studies have shown that the infant gut microbiota is closely associated with pediatric diseases, including necrotizing enterocolitis [&lt;span&gt;6&lt;/span&gt;], arthritis [&lt;span&gt;7&lt;/span&gt;], allergic sensitization, asthma, and eczema [&lt;span&gt;8&lt;/span&gt;]. However, the relationship between the gut microbiota and EBIs remains unclear. Through genomics and fecal metagenomics, DeVeaux et al. provide evidence that the gut microbiota may play a role in EBIs among term infants, which may inform future studies on the prevention and treatment of these infections.&lt;/p&gt;&lt;p&gt;DeVeaux et al. selectively cultured the same species as the pathogens causing EBIs from the intestines of infants with EBIs. For each pathogen, a culture medium containing specific antibiotics was used to ensure that the target strains could grow in a competitive environment. Species identity was confirmed by matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry, and the isolated strains underwent multilocus sequence typing. The results showed the presence of intestinal strains that were highly genetically similar to EBI-related pathogens in 60% of cases, consistent with the hypothesis that the gut serves as a reservoir for EBI","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"116-119"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148343117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applications and Challenges of Artificial Intelligence in Predicting Antimicrobial Resistance","authors":"Wenjuan Wu,&nbsp;Zhexiao Ma","doi":"10.1002/ila2.70060","DOIUrl":"https://doi.org/10.1002/ila2.70060","url":null,"abstract":"&lt;p&gt;Over the past few decades, widespread antimicrobial use has reduced mortality from bacterial and fungal infections but has also accelerated the spread of antimicrobial resistance (AMR) [&lt;span&gt;1&lt;/span&gt;]. Multidrug-resistant pathogens are eroding conventional treatment options [&lt;span&gt;2&lt;/span&gt;]. Against this backdrop, the use of AI, especially machine learning and deep learning, for AMR prediction has progressed rapidly.&lt;/p&gt;&lt;p&gt;Recent AI-based approaches have shown strong potential for predicting AMR from whole-genome data. In bacteria, models trained on whole-genome sequences and matched resistance phenotypes use features such as resistance gene presence/absence and single-nucleotide variants to learn resistance-associated patterns, enabling rapid susceptibility profiling and highlighting candidate genes or regulatory signals [&lt;span&gt;3, 4&lt;/span&gt;].&lt;/p&gt;&lt;p&gt;In fungal AMR prediction, the FungAMR database provides a standardized reference of resistance-related genes and variants across clinically important fungi; the ChroQueTas tool, built on this database, enables genome-based detection of resistance mutations [&lt;span&gt;5&lt;/span&gt;]. Although FungAMR is a valuable, integrated mutation repository, the complex basis of fungal resistance, involving coding mutations, promoter tandem repeats, copy-number changes, and chromosomal structural variation, makes the development of prediction tools challenging.&lt;/p&gt;&lt;p&gt;The growing complexity of genotype–phenotype relationships has made it increasingly clear that curated mutation resources alone may be insufficient, motivating greater use of data-driven models. Deep learning is increasingly used in AMR prediction because it can capture complex genomic patterns beyond predefined features. For instance, Green et al. used convolutional neural networks to predict resistance in &lt;i&gt;Mycobacterium tuberculosis&lt;/i&gt; and to highlight candidate resistance-associated loci; however, their study also underscored the need for independent validation and sensitivity to phenotypic noise, particularly for second-line drugs [&lt;span&gt;6&lt;/span&gt;]. Nguyen et al. proposed AMR-GNN, which integrates multiple genomic representations to improve resistance prediction and biomarker discovery, yet its performance drop in an external test set and dependence on continuously updated feature representations illustrate the difficulty of maintaining generalizability across regions and datasets [&lt;span&gt;7&lt;/span&gt;]. Likewise, the transformer-based LLMTB (a large language model to predict AMR in &lt;i&gt;Mycobacterium tuberculosis&lt;/i&gt;) introduced by Testagrose et al. improved interpretability by jointly modeling genes and flanking intergenic regions; however, it showed reduced performance for several last-line drugs, suggesting that class imbalance, incomplete mechanistic knowledge, and limited genomic context remain important constraints [&lt;span&gt;8&lt;/span&gt;]. Taken together, these examples show that stronger architectures can improve prediction and interpretability but do not by","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"120-122"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70060","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148343118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Post-Translational Modifications of Key Proteins in Hematologic Malignancies: Carcinogenic Mechanisms, Biomarker Potential, and New Therapeutic Strategies","authors":"Yuxuan Han,&nbsp;Chaowei Zhang,&nbsp;Weiyi Yao,&nbsp;Qing Hong,&nbsp;Xinyu Tang,&nbsp;Yanan Zhu,&nbsp;Na Chen","doi":"10.1002/ila2.70064","DOIUrl":"https://doi.org/10.1002/ila2.70064","url":null,"abstract":"<p>Post-translational modifications (PTMs) of proteins have emerged as critical regulators in the pathogenesis of hematologic malignancies. This review synthesizes the latest research advances in the regulatory mechanisms, clinical relevance, and translational application of diverse PTMs, including phosphorylation, acetylation, succinylation, and lactylation, in blood cancers. We summarize how these modifications dynamically regulate the stability and interaction of key oncogenic proteins, thereby orchestrating tumor proliferation, apoptosis evasion, and chemotherapy resistance. Crucially, this article emphasizes the clinical potential of PTMs beyond therapeutic targeting, highlighting their emerging role as sensitive biomarkers for early diagnosis. By identifying the specific PTM landscapes across leukemias, lymphomas, and myeloma, we provide a framework for developing next-generation diagnostic tools and precision therapies for hematologic malignancies.</p>","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"91-107"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70064","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148342978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Current Progress in Differentiating Crohn's Disease From Intestinal Tuberculosis","authors":"Chuyao Zhang,&nbsp;Xiaoyin Zhang","doi":"10.1002/ila2.70062","DOIUrl":"https://doi.org/10.1002/ila2.70062","url":null,"abstract":"<p>Crohn's disease and intestinal tuberculosis share similar clinical manifestations and pose significant diagnostic challenges. Inappropriate early treatment may lead to adverse outcomes. In developing countries with high intestinal tuberculosis prevalence and increasing Crohn's disease incidence, accurate diagnostic methods are urgently needed. This article reviews recent advances in diagnostic approaches for both diseases. Simple, non-invasive and highly accurate laboratory tests are available that show promise for early diagnosis. While high-resolution diagnostic models (including artificial intelligence-based models) require more testing, they provide valuable references for difficult cases. Widely used pathological and imaging techniques have incorporated meaningful new indicators while maintaining broad clinical utility. Future research should focus on developing and validating promising clinical laboratory markers, as well as refining diagnostic models for improving real-world practice.</p>","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"78-90"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70062","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148343161","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Translating Generative Digital Pathology to Clinical Workflows: Insights From Transformer-Based Pathology Image and Text Alignment Network","authors":"Xin Xin,&nbsp;Guoliang Zheng","doi":"10.1002/ila2.70058","DOIUrl":"https://doi.org/10.1002/ila2.70058","url":null,"abstract":"&lt;p&gt;As computational pathology expands rapidly, whole-slide images (WSIs) have become integral to digital workflows, supporting diagnosis, prognostic assessment, and biomarker-oriented studies; however, clinical deployment still faces a familiar tension between the gigapixel scale of WSI data and the scarcity of high-quality annotated supervision, especially for rare entities, uncommon subtypes, and therapy-related tissue responses. In this context, Ding et al. introduced Transformer-based Pathology Image and Text Alignment Network (TITAN), a multimodal whole-slide foundation model that uses pathology reports as language supervision during pretraining [&lt;span&gt;1&lt;/span&gt;]. Rather than building a patch-level model around a single endpoint, TITAN learns slide-level representations intended for classification, retrieval, and generation, capabilities that align more closely with everyday pathology work.&lt;/p&gt;&lt;p&gt;TITAN was pretrained on 335,645 WSIs across 20 organs and then aligned with 423,122 region of interest-caption pairs and 182,862 WSI–report pairs [&lt;span&gt;1&lt;/span&gt;]. In Ding et al.’s study, TITAN demonstrated stronger low-data and multimodal performance than prior slide encoders: across zero-shot evaluations, TITAN outperformed pathology report and image summarization model on multiclass tasks by 56.52% in balanced accuracy and on binary tasks by 13.8% in area under the receiver operating characteristic curve; in rare-cancer retrieval, TITAN improved top-K retrieval accuracy by 14.8% over the next-best model; and in report generation, TITAN exceeded PRISM by 161% on average across metric for evaluation of translation with explicit ordering, recall-oriented understudy for gisting evaluation, and bilingual evaluation understudy [&lt;span&gt;1&lt;/span&gt;]. These are evaluation findings from the original study. In clinical translation, they could support more efficient case retrieval, more consistent draft reporting, and more practical decision support when labeled data are limited.&lt;/p&gt;&lt;p&gt;In routine WSI analysis, multiple-instance learning aggregates patch embeddings to a slide-level prediction using slide labels rather than dense pixel annotations [&lt;span&gt;2&lt;/span&gt;]. The analysis presented in Figure 2e of Ding et al.’s study is therefore especially informative: attention-based multiple-instance learning outperforms simple mean pooling, as expected, however, TITAN linear probing outperforms attention-based multiple-instance learning, indicating that large-scale slide pretraining has already captured contextual morphology before downstream task-specific supervision [&lt;span&gt;1&lt;/span&gt;]. Finetuning from a pretrained TITAN model further improves prediction accuracy, whereas finetuning from random initialization performs worse on average [&lt;span&gt;1&lt;/span&gt;]. In other words, much of TITAN's advantage is already present in the frozen representation rather than being rescued by a stronger downstream classifier. TITAN's main contribution is therefore transferable slide-level represe","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"123-125"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148343119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations of C-Reactive Protein–Triglyceride–Glucose Index With the Incidence and Progression of Cardiometabolic Multimorbidity in Middle-Aged and Older Chinese Individuals: A Prospective Cohort Study From CHARLS","authors":"Zhengfeng Wu,&nbsp;Honghong Zhang,&nbsp;Yajun Zheng,&nbsp;Haijing Zhao,&nbsp;Jie Liu,&nbsp;Yuhan Ma,&nbsp;Yuqi Liu","doi":"10.1002/ila2.70061","DOIUrl":"https://doi.org/10.1002/ila2.70061","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Robust longitudinal studies evaluating the association between the C-reactive protein–triglyceride–glucose index (CTI) and cardiometabolic multimorbidity (CMM) are scarce. To better understand the clinical value of the CTI, this study was conducted to explore the association of the CTI with CMM risk and progression, and to compare its predictive performance with indices incorporating central obesity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>This cohort study analyzed data from the China Health and Retirement Longitudinal Study spanning 2011–2020, including 9477 participants. The associations of the CTI, triglyceride–glucose (TyG), TyG–waist circumference (TyG–WC), and TyG-waist-to-height ratio with CMM incidence were assessed using multivariable Cox regression. Predictive performance was compared using the area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination improvement (IDI). Multi-state models were used to analyze disease-stage transitions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>During follow-up, 462 participants developed CMM. After full adjustment, a 1-standard deviation increase in the CTI was associated with a 41% higher CMM risk (hazard ratio [HR]: 1.41, 95% confidence interval [CI]: 1.17–1.69). In direct comparison, TyG–WC showed the highest predictive AUC (0.704, 95% CI: 0.678–0.730). Adding the CTI to a conventional risk model significantly improved the NRI and IDI. Multistate modeling demonstrated that the CTI was associated with the progression from baseline health to diabetes mellitus, stroke, and heart disease, with a stronger association observed for diabetes mellitus (HR: 1.47, 95% CI: 1.36–1.60).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The CTI independently predicted CMM risk and progression. Although the TyG–WC index demonstrated superior predictive performance, the CTI remains a clinically convenient, blood-based composite marker that captures the insulin resistance–inflammation pathway, offering a valuable tool for risk stratification.</p>\u0000 </section>\u0000 </div>","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 2","pages":"65-77"},"PeriodicalIF":0.0,"publicationDate":"2026-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70061","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148342981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Presentation and Management of Addison's Disease in a 10-Year-Old Boy: A Case Report","authors":"Srinivasan Sivannan,&nbsp;Mohammed Azhar Hussain,&nbsp;Syed Mohammed Hussaini,&nbsp;Pasumarthi Tejashree,&nbsp;Karthikeyan Elumalai","doi":"10.1002/ila2.70053","DOIUrl":"https://doi.org/10.1002/ila2.70053","url":null,"abstract":"<p>Addison's disease, or primary adrenal insufficiency, is a rare endocrine disorder characterized by impaired adrenal hormone production. We report a case of a 10-year-old boy with congenital adrenal hyperplasia and secondary Addison's disease on long-term corticosteroid therapy who presented with recurrent non-bilious vomiting, low-grade fever, headache, and epigastric pain. Physical examination revealed short stature (below the third percentile) and overweight status (90th percentile), likely related to prolonged steroid use. He was managed with intravenous fluids, adjustment of antibiotics, and optimized steroid therapy, leading to significant clinical improvement. This case highlights the complexity of managing pediatric adrenal insufficiency, particularly in patients receiving chronic corticosteroids. Lifelong individualized hormone replacement, careful dose adjustment, and regular monitoring are essential to prevent adrenal crises and long-term metabolic complications. A multidisciplinary approach involving endocrinologists, pediatricians, and supportive care teams is crucial for optimal outcomes in children with Addison's disease.</p>","PeriodicalId":100656,"journal":{"name":"iLABMED","volume":"4 1","pages":"59-63"},"PeriodicalIF":0.0,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ila2.70053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147614846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}