OBJECTIVE To evaluate the effect of clinical pharmacists participating in the treatment of chronic heart failure （CHF） based on the clinical pharmacy pathway （CPP）. METHODS Totally 226 CHF patients recruited from August 24th， 2024 to March 14th， 2025， were divided into an observation group and a control group based on the random number table method， with 113 cases in each group. All patients were treated with conventional therapy. The observation group was additionally given CPP management （including pharmaceutical care during hospitalization， the formulation of individualized discharge medication regimens， and pharmaceutical follow-up after discharge）. The cardiac function parameters at admission， at discharge， at 3 and 6 months after discharge， drug use at 6 months after discharge， economic indicators， as well as the readmission rate and mortality rate at 6 months after discharge were compared between the two groups. Morisky Medication Adherence Scale-8 Items （MMAS-8）， Somatic Self-rating Scale （SSS） and Patient Health Questionnaire-9 （PHQ-9） scores were compared at admission， at discharge and at 3 and 6 months after discharge. RESULTS Six months after discharge， 24 patients dropped out. Eventually， 104 patients in the observation group and 98 patients in the control group completed the study. Compared with at admission， New York Heart Association （NYHA） cardiac functional classification， left ventricular ejection fraction （LVEF） and N -terminal pro-B-type natriuretic peptide （NT-proBNP） of both groups of patients at discharge as well as at 3 and 6 months after discharge were significantly improved； moreover， the improvements at 3 and 6 months after discharge were significantly better than those at discharge. Meanwhile， the above indexes （except for NYHA cardiac functional classification at discharge， NT-proBNP and NYHA cardiac functional classification at 3 months after discharge） of the observation group at discharge， at 3 and 6 months after discharge were significantly better than the control group （ P ＜0.05）. The utilization rates of angiotensin converting enzyme inhibitor （ACEI）/angiotensin Ⅱ receptor blocker （ARB）/angiotensin receptor neprilysin inhibitor （ARNI）， the proportion of β-blockers reaching the target dose， the utilization rate of sodium-glucose linked transporter 2 inhibitor （SGLT2i）， and the proportion of SGLT2i reaching the target dose in the observation group were significantly higher than the control group （ P ＜0.05）， and the proportion of drugs and readmission rate were significantly lower than the control group （ P ＜0.05）. Compared with at admission， MMAS-8 scores of the patients in the observation group at discharge， at 3 and 6 months after discharge were significantly increased， while SSS and PHQ-9 scores were significantly lowered （ P ＜0.05）. And all the above scores gradually decreas ed with the extension of discharge time （ P ＜0.05）. CONCLUSIONS Clinical pharmacists can utilize CPP to significantly improve patients’ cardiac function， medication adherence， somatic symptoms and depression. Additionally， they can significantly improve the utilization rates of ACEI/ARB/ARNI and SGLT2i， as well as the proportion of target doses of β-blockers and SGLT2i， while simultaneously reducing readmission rates.

Hepatitis B virus （HBV） exclusively infects liver parenchymal cells and forms covalently closed circular DNA （cccDNA） within their nuclei. HBV cccDNA serves as the essential template for viral gene transcription， the sole source of progeny virus production， and the key driver of viral antigen expression， and it is the molecular basis for the persistence of HBV infection. Therefore， elimination and/or functional silencing of cccDNA is the key to eradicate chronic HBV infection. This article discusses the critical scientific issues that need to be solved during elimination of the harm of HBV infection from the perspectives of the synthesis， transcription， and clearance of cccDNA， as well as the impact of nonparenchymal cells on cccDNA， in order to provide a reference for eradicating HBV infection in the future.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

OBJECTIVE To provide references for optimizing the review and approval system of clinically urgent overseas-marketed drugs in China. METHODS The characteristics of the review and approval system for clinically urgent overseas-marketed drugs were analyzed. A comparative research method was employed to examine differences between China and Australia， Switzerland， and Canada in three dimensions： qualification determination for clinical urgency （i.e.， access qualification）， review methods， and approval modalities. RESULTS & CONCLUSIONS In China’s current system， the legal nature of communication and consultation meetings is ambiguous， as the qualification determination function is embedded within technical consultation procedures without remedy channels. The pre-marketing clinical trial exemption for drugs is disconnected from the post-marketing confirmation obligation， and insufficient access to complete overseas review information weakens risk control effectiveness. A differentiated triage mechanism based on the timing of global approval has not been established， providing insufficient incentives for global simultaneous research and development. International typical regulatory models set access qualification， review methods， and approval modalities as independent modules， forming a quid pro quo relationship by relaxing pre-marketing access conditions and establishing post-marketing conditional approval mechanisms. It is recommended to formulate technical guidelines for the determination of clinically urgent drugs to clarify objective discretionary benchmarks， clarify the legal nature of communication and consultation meetings and allocate remedy channels， mandatorily include clinical trial-exempted varieties in the conditional approval procedure and establish a negative signal linkage mechanism， and implement differentiated triage based on approval timing， so as to improve China’s review and approval system.

Digital transformation is reshaping disease monitoring. We assessed the real-world utility of linking hospital information systems with the foodborne disease surveillance network in Shenzhen. Analysing data from 53 sentinel hospitals (2024–2025) and surveying 263 staff members, we found that integration triggered a 125% surge in case reports. However, regional performance varied sharply (Nanshan +161% vs Pingshan -44%), and personnel training frequency remained low (3.08/5). While automation solves the volume problem, it exposes a technology capacity gap that requires urgent human-centric intervention.

Objective To evaluate the efficacy and safety of a combination therapy regimen comprising stereotactic body radiation therapy (SBRT) combined with liposomal irinotecan, camrelizumab, and anti-angiogenic therapy (CAP) in patients with advanced bone and soft tissue sarcomas. Methods This study is a prospective subgroup analysis of the multicenter, open-label, single-arm phase Ⅱ CAP trial (NCT04569916), which enrolled 60 patients with advanced solid tumors who had progressed after standard therapy between November 2020 and February 2023, including 11 patients with advanced bone and soft tissue sarcomas. All patients received sequential liposomal irinotecan within 48 hours after stereotactic body radiotherapy (SBRT), followed by maintenance therapy with camrelizumab and an anti-angiogenic agent until disease progression or intolerable toxicity. The primary efficacy endpoint was objective response rate (ORR). Secondary endpoints included disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and safety. Results In the bone and soft tissue sarcoma subgroup (n=11), three patients achieved partial response (PR), five had stable disease (SD), and three experienced disease progression (PD). ORR was 27.3%, and DCR was 72.7%. mPFS was 5.8 months (95%CI: 2.2-10.3), and mOS not reached. Regarding safety, adverse reactions primarily included bone marrow suppression, fatigue, and gastrointestinal reactions, indicating overall manageable toxicity. Conclusion As a subgroup analysis of the CAP study, this research suggests that radiotherapy combined with liposomal irinotecan, camrelizumab, and anti-angiogenic therapy demonstrates certain efficacy in advanced bone and soft tissue sarcomas that have failed multiple lines of treatment, with overall manageable adverse reactions. Future studies should expand the sample size.

Objective:To development a deep learning（DL） model based on conventional MRI for automatic segmentation and differential diagnosis of nasopharyngeal carcinoma（NPC） and nasopharyngeal lymphoma（NPL）. Methods:The retrospective study included 142 patients with NPL and 292 patients with NPC who underwent conventional MRI at Renmin Hospital of Wuhan University from June 2012 to February 2023. MRI from 80 patients were manually segmented to train the segmentation model. The automatically segmented regions of interest（ROIs） formed four datasets: T1 weighted images（T1WI）, T2 weighted images（T2WI）, T1 weighted contrast-enhanced images（T1CE）, and a combination of T1WI and T2WI. The ImageNet-pretrained ResNet101 model was fine-tuned for the classification task. Statistical analysis was conducted using SPSS 22.0. The Dice coefficient loss was used to evaluate performance of segmentation task. Diagnostic performance was assessed using receiver operating characteristic（ROC） curves. Gradient-weighted class activation mapping（Grad-CAM） was imported to visualize the model's function. Results:The DICE score of the segmentation model reached 0.876 in the testing set. The AUC values of classification models in testing set were as follows: T1WI: 0.78（95%CI 0.67-0.81）, T2WI: 0.75（95%CI 0.72-0.86）, T1CE: 0.84（95%CI 0.76-0.87）, and T1WI+T2WI: 0.93（95%CI 0.85-0.94）. The AUC values for the two clinicians were 0.77（95%CI 0.72-0.82） for the junior, and 0.84（95%CI 0.80-0.89） for the senior. Grad-CAM analysis revealed that the central region of the tumor was highly correlated with the model's classification decisions, while the correlation was lower in the peripheral regions. Conclusion:The deep learning model performed well in differentiating NPC from NPL based on conventional MRI. The T1WI+T2WI combination model exhibited the best performance. The model can assist in the early diagnosis of NPC and NPL, facilitating timely and standardized treatment, which may improve patient prognosis.
Humans ; Nasopharyngeal Carcinoma/diagnostic imaging* ; Deep Learning ; Magnetic Resonance Imaging ; Retrospective Studies ; Nasopharyngeal Neoplasms/diagnostic imaging* ; Lymphoma/diagnostic imaging* ; Diagnosis, Differential ; ROC Curve ; Male ; Female ; Middle Aged ; Adult

An ideal dermal filler should integrate filling, repair, and anti-aging effects, with immediate tissue augmentation, slow degradation, and progressive stimulation of collagen regeneration. However, commonly used hyaluronic acid (HA) hydrogels, while effective for rapid filling, suffer from limited duration of support, weak cell adhesion, and an inability to promote collagen regeneration. Silk fibroin (SF), a natural protein from silkworm cocoons, is known for its excellent cell adhesion and collagen-stimulating abilities. However, its limited gelation capability restricts its potential application as a standalone injectable hydrogel. Based on a complementary strategy, this study combines the rapid gelling properties of HA with the collagen regenerative properties of SF to create a co-crosslinked HA-SF hydrogel. The composite hydrogel merges HA's rapid filling effect with SF's strong tissue adhesion and collagen-stimulating abilities. The formulation, physicochemical properties, degradation, biocompatibility, and filling effects of the HA-SF hydrogel were systematically investigated. HA-SF hydrogel exhibits excellent mechanical properties and ensures long-term support while maintaining injectability. Interestingly, after intradermal injection in the UVB-induced photoaging model, HA-SF hydrogel not only enhances hydrogel-cell interaction but also continues to stimulate collagen regeneration, especially type III collagen. This dual action achieves the biological effects of repair and anti-aging while maintaining the filling effect. Proteomic analysis confirms that repair and anti-aging effects are enhanced by the regulation of skin fibroblasts and modulation of amino acid and lipid metabolism. This composite hydrogel holds strong promise for clinical applications, offering a safer, long-lasting, and more natural injectable filler that combines filling, repair, and anti-aging into one system.

Gastric carcinoma (GC) is a malignancy with multifactorial involvement, multicellular regulation, and multistage evolution. The classic Correa's cascade of intestinal GC specifies a trilogy of malignant transformation of the gastric mucosa, in which normal gastric mucosa gradually progresses from inactive or chronic active gastritis (Phase I) to gastric precancerous lesions (Phase II) and finally to GC (Phase III). Correa's cascade highlights the evolutionary pattern of GC and the importance of early intervention to prevent malignant transformation of the gastric mucosa. Intervening in early gastric mucosal lesions, i.e., Phase I and II, will be the key strategy to prevent and treat GC. Natural products (NPs) have been an important source for drug development due to abundant sources, tremendous safety, and multiple pharmacodynamic mechanisms. This review is the first to investigate and summarize the multi-step effects and regulatory mechanisms of NPs on the Correa's cascade in gastric carcinogenesis. In phase I, NPs modulate Helicobacter pylori urease activity, motility, adhesion, virulence factors, and drug resistance, thereby inhibiting H. pylori-induced gastric mucosal inflammation and oxidative stress, and facilitating ulcer healing. In Phase II, NPs modulate multiple pathways and mediators regulating gastric mucosal cell cycle, apoptosis, autophagy, and angiogenesis to reverse gastric precancerous lesions. In Phase III, NPs suppress cell proliferation, migration, invasion, angiogenesis, and cancer stem cells, induce apoptosis and autophagy, and enhance chemotherapeutic drug sensitivity for the treatment of GC. In contrast to existing work, we hope to uncover NPs with sequential therapeutic effects on multiple phases of GC development, providing new ideas for gastric cancer prevention, treatment, and drug development.

Large language models (LLMs), represented by ChatGPT, have garnered significant attention due to their powerful capabilities in understanding and generating human language. Research on the application of LLMs across various medical tasks has shown a vigorous development trend. This review aims to outline the development and clinical applications of LLMs, with a focus on the primary tasks of medical intelligent assistants, including their associated opportunities and challenges. At the technical level, we provide a detailed explanation of the architecture and training processes of existing medical LLMs, and summarize the general technical steps for adapting large models to the healthcare domain. At the application level, we introduce the main tasks of medical intelligent assistants from both healthcare provider- and patient-oriented perspectives, andcompare the performance of different LLMs across various medical tasks to illustrate their unique advantages and limitations in medical applications.