Cannabinoid hyperemesis syndrome is an underrecognized cause of recurrent vomiting, weight loss, and abdominal pain in adolescents, often overlooked due to its nonspecific presentation and overlap with other gastrointestinal conditions. This case report highlights a 13-year-old female who presented with significant weight loss and postprandial bilious vomiting initially attributed to superior mesenteric artery syndrome. Persistent symptoms, despite surgical removal of an incidental ovarian dermoid cyst, prompted reevaluation after nondiagnostic imaging and lack of improvement. Further history obtained on hospital day 12 revealed daily cannabis use since age 10, with reported cessation approximately six weeks prior to admission and probable resumed use approximately two weeks prior to presentation, confirmed by a positive urine toxicology screen for tetrahydrocannabinol consistent with chronic heavy use. Following supportive care and counseling on cannabis cessation, her acute symptoms resolved and she was discharged. She subsequently experienced a symptomatic relapse with resumed cannabis use requiring readmission two months later, but achieved sustained clinical remission at approximately six months following definitive cessation. This case illustrates how incomplete social histories and incidental findings can delay the identification of cannabinoid hyperemesis syndrome and lead to unnecessary procedures, and emphasizes that long-term symptom resolution requires ongoing cannabis abstinence. Early use of validated structured substance use screening tools (CRAFFT, BSTAD, S2BI), with urine toxicology applied as a confirmatory adjunct when the history is unreliable or symptoms remain unexplained, can facilitate timely recognition of cannabinoid hyperemesis syndrome in adolescents with persistent vomiting and abdominal pain, reduce hospital length of stay, and improve outcomes.

Nonalcoholic fatty liver disease (NAFLD) is a prevalent metabolic disorder with a complex pathogenesis. Although epitranscriptomic modifications such as N6-methyladenosine (m6A) have been implicated in NAFLD, the role of N1-methyladenosine (m1A) and its regulators is largely unexplored. Recently, YTHDF1, a well-characterized m6A reader, was also shown to recognize m1A; however, the functional consequences of this dual specificity are unknown. This study aimed to investigate the role of YTHDF1 in NAFLD pathogenesis and to explore whether its function is mediated through recognition of RNA methylation modification on specific target mRNAs.

Expression of YTHDF1 in NAFLD was analyzed in the GEO database. Loss-of-function studies for YTHDF1 were conducted in vivo (high-fat diet-fed mice) and in vitro (free fatty acid-treated HepG2 cells) in models of NAFLD. We employed RNA-seq and m1A-MeRIP-seq to identify key targets, followed by mechanistic validation of the YTHDF1–m1A–NUPR1 axis using biochemical, histological, and mRNA stability assays.

We identified a critical role for YTHDF1 in promoting hepatic steatosis. NUPR1, a stress-induced transcriptional regulator, undergoes m1A modification. YTHDF1 directly binds to m1A-modified NUPR1 mRNA, enhancing its stability, thereby leading to elevated NUPR1 protein levels. Functionally, upregulated NUPR1 acts as a core driver of NAFLD pathogenesis by activating lipogenic and suppressing fatty acid β-oxidation genes, thereby exacerbating hepatic lipid accumulation.

Our study unveils a novel epitranscriptomic mechanism in which YTHDF1, functioning as a dual-specificity reader, governs NAFLD progression through the m1A-NUPR1 axis. This not only expands the understanding of RNA modification recognition but also establishes the YTHDF1–m1A–NUPR1 pathway as a promising therapeutic target for metabolic liver disease.

Pancreatic cystic neoplasms (PCNs) are increasingly detected in clinical practice, yet substantial variability exists in imaging interpretation and reporting, which may affect clinical decision-making. This guideline was developed to standardize diagnostic imaging evaluation and reporting for PCNs. A multidisciplinary expert panel conducted literature search and critical appraisal of domestic and international evidence, identified key clinical questions, and formulated recommendations using the Grading of Recommendations Assessment, Development and Evaluation framework. A modified Delphi consensus process and external review were performed to ensure the robustness of the recommendations. A total of 21 key questions were addressed, covering essential aspects of imaging evaluation and reporting for PCNs, including the preferred imaging modality for suspected lesions; standardized measurement of cyst size and mural nodules and their clinical significance; definitions of cyst wall and septal thickening; optimal imaging approaches for assessing the relationship between cystic lesions and the main pancreatic duct; measurement and evaluation of main pancreatic duct diameter and dilation; imaging-based classification of intraductal papillary mucinous neoplasms and serous cystic neoplasms; assessment of ductal obstruction, calcification, hemorrhage, and pancreatitis-related changes; criteria for suspicious lymph nodes; differentiation of PCNs from pancreatic pseudocysts or retention cysts; and recommended imaging modalities and follow-up intervals. This guideline provides a structured and evidence-based framework for imaging evaluation and reporting of PCNs, which may improve the consistency and clarity of imaging reports and support clinical decision-making.

Unlike the traditional staging treatment of tumors, the core of “Green Tumor Treatment” is to divide the treatment of tumors into three stages: Hegemony (directly targeting the cancer focus), Kingship (supporting the body’s vital energy and eliminating pathogenic factors), and Imperialism (improving the internal environment), based on the urgency of the tumor and the patient’s physical condition. This approach guides the clinical treatment of tumors. Its treatment system incorporates all minimally invasive and low-damage treatment methods, combining internal and external treatments, traditional Chinese medicine and Western medicine, as well as local and systemic treatments. It aims to maximize treatment outcomes while ensuring the patient’s quality of life, which is highly consistent with the treatment goals for primary liver cancer. This review aims to explore the integrated Traditional Chinese and Western medicine treatment model for primary liver cancer under the guidance of the Green Tumor Treatment concept.

Artificial intelligence (AI) is increasingly reshaping diagnostic pathology, with breast pathology representing one of the most advanced and clinically impactful areas of adoption. Despite rapid progress, many practicing pathologists remain unfamiliar with core AI concepts and their practical implications. This review provides a concise and accessible overview of AI in breast pathology, focusing on foundational principles, current clinical applications, and future directions.

Pertinent literature was reviewed. Personal experiences were also summarized and incorporated.

Key AI concepts, including algorithms, models, architectures, machine learning, deep learning, neural networks, and multimodal and foundational models, are introduced to establish a common framework. Important distinctions among generative, black-box, and explainable AI are highlighted, emphasizing the need for transparency and interpretability in clinical settings. The evolution of AI in breast pathology is reviewed, from early rule-based computer-assisted diagnostic systems to modern deep learning approaches leveraging large-scale whole-slide imaging datasets. Current applications span multiple domains, including detection of lymph node metastases, Nottingham grading, classification of benign and malignant lesions, and automated quantification of critical biomarkers. AI-based approaches to prognosis, risk stratification, prediction of treatment response, and analysis of the tumor microenvironment are also discussed. Finally, the review addresses challenges associated with real-world implementation, including data quality, bias, regulatory considerations, cost, infrastructure, and workflow integration.

As AI continues to evolve toward large-scale, multimodal, and explainable models, it is expected to function as an augmentative tool rather than a replacement for pathologists, supporting diagnostic accuracy, standardization, and personalized management in breast cancer care.

Alpha-1 antitrypsin deficiency (AATD) is an autosomal codominant genetic disorder caused by mutations in the SERPINA1 gene. It results in reduced circulating levels of alpha-1 antitrypsin (AAT), a serine proteinase inhibitor (PI) primarily produced by hepatocytes. The most common deficient alleles are PI*S and PI*Z, with PI*ZZ homozygotes having the most severe deficiency and highest risk for lung and liver disease. While AATD is well established as a cause of early-onset emphysema and liver cirrhosis, emerging evidence suggests a potential association with the formation of arterial aneurysms. The pathophysiological rationale for this association centers on protease-antiprotease imbalance and potential extracellular matrix degradation of elastin in arterial vessel walls. Several studies have reported increased frequencies of AATD alleles in patients with abdominal aortic aneurysms and intracranial aneurysms compared to the general population, with some demonstrating statistically significant associations. Additionally, patients with the PI*ZZ genotype have been shown to have larger aortic diameters, greater aortic stiffness, and reduced distensibility compared to controls. However, the evidence is inconsistent, as several large studies have failed to demonstrate significant associations between AATD and aneurysm formation. Overall, current evidence suggests an association of AATD with the development of arterial aneurysms. However, it is also clear that the presence of AATD alone is not sufficient to increase the risk of developing new-onset arterial aneurysms.