Celiac disease is a chronic, immune-mediated enteropathy precipitated by gluten exposure in genetically predisposed individuals, with a global prevalence of approximately 1%. Though diagnostic workflows incorporate serologic techniques with both histologic and genetic evaluation, each approach carries key pitfalls that contribute to diagnostic inaccuracy. Serology testing is limited by selective immunoglobulin A deficiency and low-titer antibodies, in addition to interlaboratory variability of calibration standards and specimen concentrations. While duodenal biopsy is considered the gold standard for celiac diagnosis, patchy villous atrophy (e.g., ultrashort celiac disease) mimics other enteropathies, and the inherent subjectivity of histologic interpretation can compromise accuracy. Furthermore, celiac predisposition is highly correlated with two human leukocyte antigen (HLA) alleles, HLA-DQ2 and HLA-DQ8. However, nearly 30–40% of the general population expresses one of these alleles, thus introducing the risk of overdiagnosis and limiting the practical implications of genetic testing. There exist special celiac presentations, such as seronegative or potential celiac disease, overlap syndromes, and enteropathy-associated T-cell lymphoma, that introduce additional challenges to diagnostic success. The serologic-histologic discordance and nonspecific symptoms associated with these cases may require divergence from the traditional workflow, as well as supplemental investigations, such as a gluten challenge or breath testing, to confirm a celiac diagnosis. These challenges in celiac diagnosis have driven research into novel biomarkers and molecular assays that can not only enable earlier, more accurate detection but also provide longitudinal disease monitoring. Such markers include intestinal fatty acid-binding proteins, specific microRNA expression, and microbiome signatures that are strongly linked to celiac disease, which may one day serve as adjunctive screening tools to optimize diagnostic yield. This narrative review identifies the key pitfalls in adult celiac disease diagnosis — from pre-analytic serology issues to patchy histology and overinterpretation of HLA — and proposes a guideline-aligned, stepwise algorithm (with emerging biomarkers) to enhance accuracy and reduce missed or delayed cases. Ultimately, continued refinement of a comprehensive, multimodal diagnostic strategy that can integrate with emerging molecular tools is necessary for overcoming the current limitations of individual approaches to celiac diagnosis.

Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment. Conventional computer-aided detection systems have shown limitations, including high false-positive rates and low sensitivity. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have shown great potential in improving the accuracy and reliability of nodule detection and classification. This study aimed to develop and evaluate an automatic method for lung nodule detection and classification using a CNN-based architecture applied to computed tomography images from the publicly available LIDC-IDRI database.

This retrospective study was conducted on 82 patients (10,496 computed tomography slices) selected from the LIDC-IDRI database. The proposed method consists of five main steps: image preprocessing, lung parenchyma segmentation using Otsu’s thresholding and morphological operations, detection of nodule candidates, feature extraction, and classification using a CNN model. The CNN architecture includes two convolutional layers (20 and 30 filters, 3×3 kernel), ReLU activation, max-pooling layers, and a Softmax output layer. The network was trained with a mini-batch size of 32 for 50 epochs using the Stochastic Gradient Descent with Momentum optimizer (learning rate = 0.001, momentum = 0.9). Model performance was evaluated in terms of sensitivity, specificity, precision, and accuracy.

The proposed CNN model successfully detected pulmonary nodules and achieved accurate classification between benign and malignant nodules. On the LIDC-IDRI dataset, the model achieved a sensitivity of 98.7%, specificity of 97.5%, precision of 97.9%, and accuracy of 98.4%. Comparative analysis with recent studies, including hybrid CNN-long short-term memory and ResNet-based models, demonstrated that the proposed method provides competitive performance while maintaining lower computational complexity. The classification of nodule subtypes (solid, partially frosted, totally frosted) showed satisfactory discrimination results.

The proposed CNN-based system demonstrates the feasibility and robustness of deep learning for automatic lung nodule detection and classification. Despite strong results, the study acknowledges limitations such as single-database validation and a relatively small training size. Future work will focus on validating the model across other datasets (e.g., ELCAP, NELSON) and optimizing multi-class classification performance to enhance generalizability and clinical applicability.

Portal hypertension can cause serious complications such as upper gastrointestinal bleeding, primarily due to esophageal and gastric varices. The risk of mortality from variceal hemorrhage is significant, particularly when the hepatic venous pressure gradient exceeds 12 mmHg. Established treatments generally include endoscopic variceal band ligation and cyanoacrylate glue for gastric varices; however, challenges such as limited availability and a lack of technical expertise can hinder the use of glue, leading to preventable complications. This study investigates the efficacy of using a 50% glucose solution for injection sclerotherapy in cases of gastric varices. We present three unique patient cases. The first case involves a 21-year-old with persistent upper gastrointestinal bleeding and a portal vein thrombus, who experienced temporary relief after receiving injection sclerotherapy but tragically succumbed to significant bleeding later. The second case describes a 24-year-old who successfully managed his bleeding with the same treatment but was subsequently lost to follow-up. Lastly, a 72-year-old patient with recurrent painless hematemesis remained free of symptoms following injection sclerotherapy. Overall, while cyanoacrylate glue remains the preferred treatment, injection sclerotherapy with 50% dextrose shows promise as an effective alternative, particularly in settings where conventional treatments are not readily available, potentially reducing the risks associated with untreated variceal bleeding.

Insulinoma is a neuroendocrine tumor originating in the pancreas that secretes excess amounts of insulin, leading to severe hypoglycemia. The clinical presentation of hypoglycemia is classically described by Whipple’s Triad. Due to the rarity of this diagnosis, it can often be mistaken for other etiologies with similar presentations. In this paper, we present the case of a woman in her 70s with metastatic insulinoma involving the liver, who was initially diagnosed with an insulin-like growth factor 2-secreting hepatocellular carcinoma. Biochemical and immunohistochemical analyses were instrumental in distinguishing between these two etiologies.

Colorectal cancer (CRC) is a type of cancer that originates in the colon or rectum from precancerous polyps, which can evolve into cancerous growths over time. This review aimed to provide a comprehensive analysis of CRC, its subtypes, clinical manifestations, point-of-care diagnostic approaches, and management strategies. The clinical presentation of CRC often includes symptoms such as blood in stool, changes in bowel habits, abdominal discomfort, weight loss, fatigue, a feeling of incomplete bowel emptying, and anemia. The identification of these signs prompts healthcare professionals to initiate diagnostic measures without delay. Point-of-care diagnosis plays a pivotal role in the early detection of CRC, employing screening tests such as stool tests and colonoscopies. These diagnostic modalities enable healthcare professionals to identify precancerous polyps or early-stage tumors, facilitating timely intervention and significantly improving treatment outcomes. Adherence to screening guidelines is crucial for the prevention and early detection of CRC. Despite advancements in screening and treatment options, there remains a crucial need for more specific, minimally invasive screening methods with minimal side effects. By improving current detection methods, a better screening approach for CRC can be developed. Recent advancements, including single-cell sequencing, spatial transcriptomics, and artificial intelligence integration, hold great promise for enhancing early diagnosis and advancing personalized treatment strategies. Moreover, a healthy lifestyle, including a balanced diet, regular exercise, no tobacco use, and limited alcohol consumption, can significantly lower the risk of CRC. By emphasizing the importance of lifestyle modifications, early screening, and timely intervention, healthcare professionals can significantly reduce the burden of CRC and improve patient outcomes.

Chronic liver cirrhosis (LC) and acute-on-chronic liver failure (ACLF) are interconnected hepatic disorders associated with substantial morbidity and mortality. Despite their distinct clinical characteristics, both conditions share common pathogenic pathways that remain inadequately understood. This study aimed to identify shared gene signatures and elucidate underlying molecular mechanisms.

In this study, we employed Weighted Gene Co-Expression Network Analysis to explore transcriptomic data from the Gene Expression Omnibus for LC and ACLF.

Key co-expression modules enriched with genes involved in glycolysis and gluconeogenesis pathways were identified, implicating metabolic dysfunction as a central feature in both conditions. Furthermore, microRNA analysis revealed that hsa-miR-122 and hsa-miR-194 play pivotal roles in regulating these metabolic pathways, potentially contributing to immune dysregulation.

Our findings indicate that these shared molecular mechanisms are critical in the progression from LC to ACLF, providing novel insights into potential therapeutic targets for mitigating disease severity and improving clinical outcomes.

Autoimmune hepatitis (AIH) is an inflammatory liver disease influenced by genetic, environmental, and immunologic factors. Individuals diagnosed with AIH may exhibit concurrent autoimmune manifestations affecting multiple organ systems. The prevalence of AIH associated with other autoimmune diseases has been reported to range from 20% to 40%. This review indicates that the associations between AIH and autoimmune thyroiditis, type 1 diabetes mellitus, ulcerative colitis, Crohn disease, and celiac disease appear to be significant. However, the associations between AIH and primary sclerosing cholangitis, primary biliary cholangitis, rheumatoid arthritis, systemic lupus erythematosus, Sjögren syndrome, and vitiligo are not well-supported. The aim of this review is to evaluate the strength of the reported associations between AIH and other autoimmune diseases, and to update and present the available evidence on their prevalence, proposed underlying pathogenic mechanisms, diagnostic considerations, and treatment approaches.

High-grade serous carcinoma is a rare diagnosis in cervical biopsies. Cervical serous carcinoma is no longer recognized as a primary cervical tumor in the 2020 World Health Organization classification. This study aimed to characterize the clinicopathologic, immunohistochemical, and molecular features of high-grade serous carcinoma identified in cervical or endocervical biopsies, to assess tumor origin and ensure accurate classification.

Fifty-nine cases originally diagnosed as “serous carcinoma” or “high-grade serous carcinoma” in cervical or endocervical biopsies from 2013 to 2023 were retrospectively reviewed. Clinical data, radiologic findings, and follow-up information were analyzed. Histologic features and immunohistochemical profiles were re-evaluated. Targeted next-generation sequencing was performed on a subset of cases.

The majority of tumors (96%) were determined to originate from the endometrium (n = 47) or the tubo-ovarian region (n = 4), with only one case confirmed as a primary cervical carcinoma. Morphologic patterns varied and could mimic human papillomavirus-associated adenocarcinoma. All tumors showed aberrant p53 expression and diffuse p16 positivity. WT-1 was expressed in all tubo-ovarian tumors but in only 12% of endometrial cases. Estrogen receptor and progesterone receptor were frequently positive in endometrial tumors; human epidermal growth factor receptor 2 was positive in 31% of cases. Molecular analysis confirmed tumor protein p53 mutations and other alterations typical of uterine serous carcinoma.

High-grade serous carcinoma identified in cervical biopsies is overwhelmingly secondary to upper genital tract tumors, most commonly of endometrial origin. A small subset of endocervical adenocarcinomas may mimic serous carcinoma. These findings support the exclusion of primary cervical serous carcinoma from the current World Health Organization classification and emphasize the importance of accurate diagnosis for appropriate management.

The importance of putative folate-biopterin metabolic interactions lies in the role they may play in the expression of several clinically relevant phenotypes. However, to date, clinical studies on folate-biopterin interactions have been limited. The purpose of this article was to highlight the close relationship between these two cofactors, which share structural similarities and exhibit overlapping metabolic pathways. This folate-biopterin crosstalk has generated several ideas and hypotheses that are critical to advancing the biochemical understanding of several important and seemingly disparate clinical and/or biologically important phenotypes. These phenotypes include melanization/pigmentation, phenylketonuria, autism, neural tube defects, affective disorders, and vascular disease. This review provides a timely, integrated overview of this important area of biochemistry, which is under-represented in the literature and would benefit from further scientific and clinical investigation using improved metabolite-specific analytical methodologies applied to clinically relevant questions.