Due to the lack of specific Western medicine therapies for post-coronavirus disease 2019 (COVID-19) syndrome in clinical practice, this study aimed to investigate the efficacy of traditional Chinese medicine (TCM) for post-COVID-19 syndrome using a cohort study design and to explore its clinical value in alleviating patients’ symptoms and improving clinical outcomes.

In this cohort study, patients were divided into two groups according to clinical treatment. The control group received conventional Western medicine, and the treatment group received additional TCM syndrome differentiation–based treatment. Propensity score matching methods were used to reduce selection bias by equating groups based on observed covariates. Clinical data, including TCM symptom scores, the Short Form 36 Health Survey, clinical efficacy, and adverse events at Day 7, were collected. The primary outcome was the efficacy rate, defined by improvement at Day 7 compared with the Day 0 score. Data were processed and analyzed using SPSS 23.0 and R 4.5.0 software.

A total of 434 patients were enrolled in the cohort, including 306 patients in the control group and 128 in the treatment group. After 1:1 matching, 94 matched pairs were analyzed. For the primary outcome, the effective rate in the treatment group was higher than that in the control group (30.8% vs. 17.2%; odds ratio (OR) = 2.17, 95% confidence interval (CI): 1.09–4.35, P = 0.003). After seven days of treatment, the TCM syndrome score improved more in the treatment group than in the control group (median difference (MD) = 2.00, 95% CI: 0.50–3.50, P = 0.009). Subgroup analyses showed generally favorable efficacy in the treatment group across subgroups, though not all reached statistical significance.

TCM syndrome differentiation–based therapy effectively relieves clinical symptoms in patients with post-COVID-19 syndrome.

Medullary thyroid carcinoma (MTC) is a neuroendocrine malignancy arising from parafollicular C-cells with known variations in cytomorphologic and immunophenotypic features. New neuroendocrine markers pituitary homeobox 2 (PITX2), paired-like homeobox 2B (PHOX2B), and heart and neural crest derivatives expressed 2 (HAND2) have recently been introduced, but studies using these markers in MTC are limited. The aim of this study was to evaluate the expression and potential diagnostic utility of PITX2, PHOX2B, and HAND2 in primary and secondary MTCs and to compare their expression with chromogranin A, synaptophysin, insulinoma-associated protein 1 (INSM1), and calcitonin.

A total of 34 histologically confirmed cases of MTC with available cell blocks were included. Sixteen MTC samples were fine-needle aspirates from primary thyroid lesions, and eighteen were from secondary metastatic lesions. Twelve samples from thyroid carcinomas of follicular origin were included as controls.

PITX2 positivity was observed in 17 (50.0%) MTC samples and in 4 (33.3%) control samples (P = 0.502). PITX2 positivity was found in 43.8% of primary thyroid MTC lesions and in 55.6% of secondary MTC lesions (P = 0.366). Co-expression of PITX2 with chromogranin A, synaptophysin, INSM1, and calcitonin was observed. PHOX2B and HAND2 were negative in all MTC and control samples.

There were no significant differences in PITX2 expression between primary and secondary MTC samples. PITX2 did not show reliable utility in distinguishing MTC from thyroid carcinomas of follicular origin. PHOX2B and HAND2 were negative in all samples. These results suggest that these new markers do not offer diagnostic value for MTC as stand-alone markers or as additions to the diagnostic workup panel.

Myelodysplastic syndromes (MDS) are a group of hematopoietic disorders characterized by ineffective hematopoiesis, with manifestations of cytopenias in one, two, or three lineages. CD34+ micromegakaryocytes and giant platelets are very rarely seen in MDS patients but may lead to unnecessary treatments. Therefore, we report and follow up on an MDS case with such an unusual finding.

A 57-year-old male veteran with a history of MDS, alcoholic cirrhosis, and portal hypertension presented to the Emergency Department in 2020 for evaluation after a blackout, at which time peripheral blood samples and bone marrow biopsies were obtained. Flow cytometry analysis of his peripheral blood detected 8% CD34+ cells. This finding raised the possibility of acute leukemic transformation from MDS. Further studies revealed that these CD34+ cells represented dysplastic micromegakaryocytes and giant platelets rather than blasts. During his 4-year follow-up, the patient was alive and complained only of easy fatigability, lasting several weeks. His laboratory results showed pancytopenia and persistent iron-deficiency anemia.

The distinction between micromegakaryocytes and giant platelets versus megakaryoblasts is extremely important in patients with MDS. This distinction may prevent misdiagnosis of acute leukemia and unnecessary treatments such as chemotherapy.

Critical care medicine requires rapid, high-stakes decisions informed by dynamic and complex streams of patient data. Traditional predictive models have shown value in forecasting deterioration and identifying subphenotypes. However, this leaves a critical gap between anticipating adverse outcomes and guiding therapeutic interventions. Achieving true personalization demands moving beyond generalized protocols toward individualized strategies that account for patient heterogeneity and consequences of alternative clinical actions. Emerging methods in prescriptive artificial intelligence, particularly causal machine learning (causal ML) and reinforcement learning (RL), are beginning to bridge this gap. Causal ML enables estimation of individualized treatment effects by addressing confounding and enabling counterfactual reasoning, allowing clinicians to ask whether a specific intervention is likely to help or harm a given patient. RL can generate adaptive treatment policies that evolve with patient state. The objective of this review is to examine how critical care can progress from generalized prediction to true personalization through the development of prescriptive artificial intelligence. The review contributes by (1) surveying the achievements and limitations of current predictive models, (2) detailing how causal ML and RL can generate individualized treatment effects and sequential decision strategies, (3) identifying the major translational, technical, clinical, ethical, and regulatory barriers to implementation, and (4) outlining future pathways such as digital twins and clinician in the loop systems that may enable safe and actionable personalized decision support at the bedside.

Ulinastatin, a broad-spectrum serine protease inhibitor widely used in Asia, has attracted increasing interest for its potential role in critical care. This review summarizes current evidence on its efficacy and safety in acute pancreatitis, severe acute pancreatitis, sepsis, acute respiratory distress syndrome, and perioperative management in cardiac surgery with cardiopulmonary bypass. Meta-analyses suggest that ulinastatin may improve outcomes by reducing mortality, shortening intensive care unit and hospital stays, and attenuating inflammatory responses. In severe acute pancreatitis, its use has been associated with reduced mortality and shorter hospitalization. In sepsis and septic shock, ulinastatin appears to lower all-cause mortality, decrease organ dysfunction scores, and reduce inflammatory markers. Evidence in acute respiratory distress syndrome indicates improvements in the oxygenation index and possible mortality reduction. Perioperative administration during cardiac surgery may mitigate postoperative inflammation and shorten the duration of mechanical ventilation. Despite these encouraging findings, most available studies originate from Asia and are limited by small sample sizes, heterogeneous designs, and inconsistent dosing regimens, which restrict generalizability and prevent standardized recommendations. Additionally, although ulinastatin demonstrates a favorable safety profile with a low incidence of adverse drug reactions, long-term and multinational pharmacovigilance data remain limited. Well-designed international, multicenter randomized controlled trials are required to clarify optimal dosing strategies, confirm clinical efficacy across diverse populations, and determine its independent effects compared with combination therapies. Overall, ulinastatin shows promise as a potential adjunctive therapy in critical care through modulation of inflammation and organ protection, but broader global adoption will depend on higher-quality evidence addressing current methodological gaps.

Digital pathology (DP) is transitioning from an adjunct technology to an enterprise diagnostic platform in the United States. Despite accelerating clinical adoption, many laboratories face persistent barriers, including high capital and operating costs, workflow disruption, interoperability challenges, and a complex regulatory and reimbursement environment. This narrative review proposes a practical lifecycle framework for implementing and sustaining DP programs, with an emphasis on defining and operationalizing institutional artificial intelligence (AI) readiness for safe and sustainable adoption.

We performed a targeted narrative review informed by searches of PubMed/MEDLINE and Google Scholar for English-language publications from January 1, 2014 through December 31, 2025. Core search concepts included DP, whole slide imaging, image management/viewing systems, laboratory information system integration, validation, reimbursement, U.S. Food and Drug Administration clearance, Clinical Laboratory Improvement Amendments oversight, College of American Pathologists accreditation, interoperability standards, cybersecurity, and AI. We supplemented database searches with reference screening and review of primary guidance and public databases from regulatory and professional organizations in the United States. We prioritized peer-reviewed literature and used web-based regulatory sources when they represented the authoritative primary reference. We also incorporated our professional experience and knowledge in DP and AI.

Key implementation domains span foundational infrastructure (scanners, storage/networking, and integrated image management platforms), workflow redesign across pre-analytic, analytic, and post-analytic phases, validation and quality management, regulatory compliance and accreditation, cost capture, interoperability strategy, cybersecurity and access control, education and change management, and long-term governance. We also describe an institution-level AI readiness model that can be assessed across data quality, integration, validation, monitoring, governance, and workforce capabilities to support safe clinical AI deployment.

Successful DP implementation requires a lifecycle approach that couples technical build-out with workflow redesign and institutional governance. Early planning for compliance, interoperability, reimbursement strategy, and AI readiness can reduce implementation risk and position laboratories for sustained clinical and computational innovation.

Metabolic dysfunction–associated steatotic liver disease (MASLD), defined by the American Association for the Study of Liver Diseases as hepatic steatosis with at least one cardiometabolic risk factor, affects approximately 30–40% of adults worldwide. This condition may progress to fibrosis, cirrhosis, and hepatocellular carcinoma. The rising prevalence, alongside obesity and type 2 diabetes, underscores the need for early risk stratification and integrated therapeutic strategies. Circadian homeostasis, orchestrated by the suprachiasmatic nucleus and core clock gene feedback loops, synchronizes hepatic metabolic pathways with environmental light–dark cycles. The objective of this review is to evaluate the role of circadian disruption and metabolic dysfunction in the development of hepatic steatosis, as well as to assess current and potential treatment modalities for both disorders. Circadian disruption through shift work, artificial light at night, sleep restriction, and chrono-nutritional misalignment destabilizes hepatic clocks, promoting insulin resistance, dyslipidemia, inflammation, and steatosis. Experimental models demonstrate that clock gene dysfunction alone can induce steatohepatitis, while progressive MASLD further impairs central circadian regulation, establishing a self-reinforcing chrono-metabolic cycle. Pharmacologic therapies, including glucagon-like peptide-1 receptor agonists and thyroid hormone receptor-β agonists, improve histologic endpoints and fibrosis regression, although heterogeneity among clinical trials precludes direct comparison. Recent evidence characterizing MASLD as a predominantly nocturnal metabolic disorder further highlights persistent nighttime insulin dysregulation despite weight loss, emphasizing the potential role of circadian-targeted interventions such as melatonin. In conclusion, the peripheral circadian clock is intricately linked with MASLD pathogenesis, and metabolic dysfunction, in turn, disrupts circadian pathways. Several pharmacologic therapies offer potential for the treatment of MASLD and circadian dysfunction.

Acute leukemias with chimeric fusion genes involving FET (FUS, EWSR1, and TAF15) family proteins and ETS (E26 transformation-specific)-like transcription factors often present with unique clinical and pathological characteristics. This mini-review aims to summarize the clinical and pathological features of acute leukemia cases harboring rearrangements involving the fused in sarcoma (FUS) or Ewing sarcoma breakpoint region 1 (EWSR1) genes.

An extensive literature review was performed on reported acute leukemia cases with fusions involving FUS or EWSR1. The details of the reported cases, as well as summarized information, are presented.

Rare cases of acute leukemia have been found to harbor either FUS or EWSR1 gene rearrangements with ETS or non-ETS proteins as partners and demonstrate heterogeneous clinical and pathological features. Acute leukemias carrying FUS gene rearrangements present with diverse immunophenotypes and are predominantly, but not exclusively, acute myeloid leukemia (AML), with ERG as the most frequent fusion partner. In contrast, acute leukemias with EWSR1 gene rearrangements more commonly present as B-cell acute lymphoblastic leukemia (ALL) and mixed phenotypic acute leukemia (MPAL), with ZNF384 as the predominant partner. At present, FUS::ERG-positive AML is the only specific entity with a FET::ETS fusion that is formally recognized in the World Health Organization 5th edition hematolymphoid tumor classification (WHO-HEM5) and the International Consensus Classification (ICC) systems. Cytogenetic karyotyping and fluorescence in situ hybridization remain crucial tools for detecting chromosomal translocations in over half of acute leukemias harboring FUS or EWSR1 gene rearrangements. However, a subset of patients may exhibit a normal karyotype and require advanced molecular diagnostic methods. EWSR1-rearranged leukemias can be difficult to distinguish from Ewing sarcoma and therefore require particular attention.

As more cases and additional data become available, it may be justified to expand this category of acute leukemias to include other specific acute leukemia entities with fusions involving FET::ETS, such as FUS::FLI1 and FUS::FEV, in addition to FUS::ERG-positive AML. However, additional data are required to support such subclassification. In contrast, AML cases with EWSR1 rearrangements are exceedingly rare and display considerable variability. Cases of B-ALL or B/myeloid MPAL with the EWSR1::ZNF384 fusion may be more appropriately classified together with other ZNF384-rearranged leukemia subtypes. Advanced molecular diagnostic methods, especially RNA-based next-generation sequencing, are suggested to improve the accurate diagnosis of acute leukemias with FUS or EWSR1 fusions. Additional pathologic workup, particularly immunohistochemical staining with hematopoietic markers, is highly recommended to differentiate EWSR1-rearranged leukemia from Ewing sarcoma.