OBJECTIVE To provide a reference for the pharmaceutical care of a patient with type 2 diabetes mellitus （T2DM） and limb-girdle muscular dystrophy （LGMD） who developed euglycemic diabetic ketoacidosis （euDKA） after taking empagliflozin. METHODS Clinical pharmacists provided pharmaceutical care for a patient with T2DM and LGMD who developed euDKA after taking empagliflozin. According to the patient’s recent use of medications and his conditions， clinical pharmacists assessed the correlation between euDKA and empagliflozin as “very likely”. As to euDKA， clinical pharmacists suggested discontinuing empagliflozin and metformin， and giving intravenous infusion of 10% Glucose injection instead of 5% Glucose injection for fluid resuscitation. Clinical pharmacists monitored the patient’s laboratory indicators such as arterial blood gas analysis， blood/urine ketones and electrolytes. They assisted physicians to decide when to stop intravenous supplements of liquid and insulin. Clinical pharmacists also assisted physicians to adjust the antidiabetic drugs and educated the patient to avoid empagliflozin or other sodium- glucose linked transporter 2 inhibitors （SGLT2i）. RESULTS Physicians adopted the suggestions of clinical pharmacists. After treatment， the patient’s condition improved， and he was allowed to be discharged with medication. CONCLUSIONS euDKA is a relatively rare and serious adverse reaction associated with SGLT2i， and the patients with LGMD are susceptible to euDKA. Clinical pharmacists assist physicians in developing personalized medication plans by evaluating the association between euDKA and empagliflozin， adjusting medication regimens，conducting pharmaceutical monitoring，and other pharmaceutical services. Meanwhile， they provide medication education to patients to ensure their medication safety.

OBJECTIVE To provide a reference for the pharmaceutical care of a patient with type 2 diabetes mellitus （T2DM） and limb-girdle muscular dystrophy （LGMD） who developed euglycemic diabetic ketoacidosis （euDKA） after taking empagliflozin. METHODS Clinical pharmacists provided pharmaceutical care for a patient with T2DM and LGMD who developed euDKA after taking empagliflozin. According to the patient’s recent use of medications and his conditions， clinical pharmacists assessed the correlation between euDKA and empagliflozin as “very likely”. As to euDKA， clinical pharmacists suggested discontinuing empagliflozin and metformin， and giving intravenous infusion of 10% Glucose injection instead of 5% Glucose injection for fluid resuscitation. Clinical pharmacists monitored the patient’s laboratory indicators such as arterial blood gas analysis， blood/urine ketones and electrolytes. They assisted physicians to decide when to stop intravenous supplements of liquid and insulin. Clinical pharmacists also assisted physicians to adjust the antidiabetic drugs and educated the patient to avoid empagliflozin or other sodium- glucose linked transporter 2 inhibitors （SGLT2i）. RESULTS Physicians adopted the suggestions of clinical pharmacists. After treatment， the patient’s condition improved， and he was allowed to be discharged with medication. CONCLUSIONS euDKA is a relatively rare and serious adverse reaction associated with SGLT2i， and the patients with LGMD are susceptible to euDKA. Clinical pharmacists assist physicians in developing personalized medication plans by evaluating the association between euDKA and empagliflozin， adjusting medication regimens，conducting pharmaceutical monitoring，and other pharmaceutical services. Meanwhile， they provide medication education to patients to ensure their medication safety.

Objective To explore the clinical characteristics of patients with diffuse large B-cell lymphoma (DLBCL) accompanied with KMT2D gene mutation and the impact of its co-mutated genes on prognosis. Methods Clinical data of 155 newly diagnosed DLBCL patients were obtained. The second-generation sequencing method was used to detect 475 hotspot genes, including KMT2D mutation. Patients were divided into the KMT2D mutation group and KMT2D wild-type group based on the presence or absence of KMT2D gene mutation. Clinical characteristics, differences in co-mutated genes, and survival differences between the two groups were compared. Results The frequency of KMT2D mutation was 31%, which is predominantly observed in elderly patients (P=0.07) and less in the double-expressor phenotype (P=0.07). Compared with the KMT2D wild-type group, KMT2D gene mutation was associated with higher co-mutation rates of CDKN2A (OR=2.82, P=0.01) and BCL2 (OR=3.84, P=0.016), while being mutually exclusive with MYC gene mutation (OR=0.11, P=0.013). In univariate survival analysis, no statistically significant difference in overall survival (OS) was found between the KMT2D mutation group and the wild-type group (P=0.54). Further analysis of the prognostic significance of KMT2D with other gene mutations indicated that patients with KMT2D^mutBTG2^mut had poorer OS than those with KMT2D^wt BTG2^mut (P=0.07) and KMT2D^wt BTG2^wt (P=0.05). On the contrary, patients with KMT2D^mut CD79B^mut had better OS than those with KMT2D^mut CD79B^wt (P=0.09), with no prognostic impact observed for other co-mutated genes. Multivariate Cox regression analysis revealed that Ann Arbor stages Ⅲ and Ⅳ (HR=2.751, 95%CI: 1.169-6.472, P=0.02), elevated LDH levels (HR=2.461, 95%CI: 1.396-4.337, P=0.002), Ki-67 index>80% (HR=1.875, 95%CI: 1.066-3.299, P=0.029), and KMT2D^mutBTG2^mut(HR=4.566, 95%CI: 1.348-15.471, P=0.015) were independent risk factors for OS in patients with DLBCL (P<0.05). Conclusion DLBCL patients with KMT2D mutation often have multiple gene mutations, among which patients with a co-mutated BTG2 gene have poor prognosis.

ObjectiveTo understand the infection characteristics of multidrug-resistant organisms (MDROs) in hospitalized patients in a tertiary sentinel hospital in Shanghai, so as to provide an evidence for the development of targeted prevention and control measures. MethodsData of MDROs strains and corresponding medical records of some hospitalized patients in a hospital in Shanghai from 2021 to 2023 were collected, together with an analysis of the basic information, clinical treatment, underlying diseases and sources of sample collection. ResultsA total of 134 strains of MDROs isolated from hospitalized patients in this hospital were collected from 2021 to 2023 , including 63 strains of methicillin-resistant Staphylococcus aureus (MRSA), 57 strains of carbapenem-resistant Acinetobacter baumannii (CRAB), and 14 strains of carbapenem-resistant Klebsiella pneumoniae (CRKP). Of the 134 strains, 30 strains were found in 2021, 47 strains in 2022 and 57 strains in 2023. The male-to-female ratio of patients was 2.05∶1, with the highest percentage (70.90%) in the age group of 60‒<90 years. The primary diagnosis was mainly respiratory disease, with lung and respiratory tract as the cheif infection sites. There was no statistically significant difference in the distribution of strains between different genders and infection sites (P>0.05). However, the differences in the distribution of strains between different ages and primary diagnosis were statistically significant (P<0.05). Patients who were admitted to the intensive care unit (ICU), had urinary tract intubation, were not artery or vein intubated, were not on a ventilator, were not using immunosuppresants or hormones, and were not applying radiotherapy or chemotherapy were in the majority. There was no statistically significant difference in the distribution of strains for whether received radiotherapy or chemotherapy or not (P>0.05), while the differences in the distribution of strains with ICU admission history, urinary tract intubation, artery or vein intubation, ventilator use, and immunosuppresants or hormones use or not were statistically significant (all P<0.05). The type of specimen was mainly sputum, the hospitalized ward was mainly comprehensive ICU, the sampling time was mainly in the first quarter throughout the year, the number of underlying diseases was mainly between 1 to 2 kinds, the application of antibiotics ≥4 kinds, and those who didn’t receive any surgery recently accounted for the most. There were statistically significant differences in the distribution of strains between different specimen types, wards occupied and history of ICU stay (P<0.05), but no statistically significant difference in the distribution of strains between different sampling times, number of underlying diseases and types of antibiotics applied (P>0.05). ConclusionThe situation of prevention and control on MDROs in this hospital is still serious. Focus should be placed on high-risk factors’ and infection monitoring and preventive measures should be strengthened to reduce the incidence rate of MDROs infection.

Reproductive system diseases are among the primary contributors to the decline in social fertility rates and the intensification of aging, posing significant threats to both physical and mental health, as well as quality of life. Recent research has revealed the substantial potential of the gut microbiota in improving reproductive system diseases. Under healthy conditions, the gut microbiota maintains a dynamic balance, whereas dysfunction can trigger immune-inflammatory responses, metabolic disorders, and other issues, subsequently leading to reproductive system diseases through the gut-gonadal axis. Reproductive diseases, in turn, can exacerbate gut microbiota imbalance. This article reviews the impact of the gut microbiota and its metabolites on both male and female reproductive systems, analyzing changes in typical gut microorganisms and their metabolites related to reproductive function. The composition, diversity, and metabolites of gut bacteria, such as Bacteroides, Prevotella, and Firmicutes, including short-chain fatty acids, 5-hydroxytryptamine, γ-aminobutyric acid, and bile acids, are closely linked to reproductive function. As reproductive diseases develop, intestinal immune function typically undergoes changes, and the expression levels of immune-related factors, such as Toll-like receptors and inflammatory cytokines (including IL-6, TNF-α, and TGF-β), also vary. The gut microbiota and its metabolites influence reproductive hormones such as estrogen, luteinizing hormone, and testosterone, thereby affecting folliculogenesis and spermatogenesis. Additionally, the metabolism and absorption of vitamins can also impact spermatogenesis through the gut-testis axis. As the relationship between the gut microbiota and reproductive diseases becomes clearer, targeted regulation of the gut microbiota can be employed to address reproductive system issues in both humans and animals. This article discusses the regulation of the gut microbiota and intestinal immune function through microecological preparations, fecal microbiota transplantation, and drug therapy to treat reproductive diseases. Microbial preparations and drug therapy can help maintain the intestinal barrier and reduce chronic inflammation. Fecal microbiota transplantation involves transferring feces from healthy individuals into the recipient’s intestine, enhancing mucosal integrity and increasing microbial diversity. This article also delves into the underlying mechanisms by which the gut microbiota influences reproductive capacity through the gut-gonadal axis and explores the latest research in diagnosing and treating reproductive diseases using gut microbiota. The goal is to restore reproductive capacity by targeting the regulation of the gut microbiota. While the gut microbiota holds promise as a therapeutic target for reproductive diseases, several challenges remain. First, research on the association between gut microbiota and reproductive diseases is insufficient to establish a clear causal relationship, which is essential for proposing effective therapeutic methods targeting the gut microbiota. Second, although gut microbiota metabolites can influence lipid, glucose, and hormone synthesis and metabolism via various signaling pathways—thereby indirectly affecting ovarian and testicular function—more in-depth research is required to understand the direct effects of these metabolites on germ cells or granulosa cells. Lastly, the specific efficacy of gut microbiota in treating reproductive diseases is influenced by multiple factors, necessitating further mechanistic research and clinical studies to validate and optimize treatment regimens.

Objective: To compare the changes in the concentration of relevant growth factors released from platelet-rich plasma (PRP) stored at -80℃ by cryopreservation and at 4℃ by refrigerated lyophilization over 2 years, aiming to provide a theoretical basis for prolonging PRP storage duration. Methods: PRP (n=15) was separated using a blood cell separator and stored under -80℃ cryopreservation (F-PRP group) and 4℃ refrigerated freeze-drying conditions (FD-PRP group). The contents of growth factors (PDGF-AA, PDGF-BB, EGF, TGF-β1, and VEGF) in both groups were measured by ELISA at 1, 3, 6, 9, 12 and 24 months. Results: PDGF-AA and VEGF maintained good stability in both groups for up to 24 months. PDGF-BB and TGF-β1 showed high stability in the first 12 months but their stability decreased gradually from 12th to 24th months. EGF demonstrated good stability in the first 6 months, and its stability gradually decreased from the 9th to 24th months. Comparing the F-PRP and FD-PRP groups, the concentrations of the five growth factors in the FD-PRP group were either not statistically different or higher than those in the F-PRP group at all time points. Specifically, the concentrations of EGF were significantly higher in the FD-PRP group at all time points. Conclusion: Both -80℃ freezing and 4℃ freeze-drying enable long-term preservation of PRP. Freeze-drying imposes less stringent storage requirements and facilitates growth factor compared to frozen storage.

Dormant tumor cells constitute a population of cancer cells that reside in a non-proliferative or low-proliferative state, typically arrested in the G0/G1 phase and exhibiting minimal mitotic activity. These cells are commonly observed across multiple cancer types, including breast, lung, and ovarian cancers, and represent a central cellular component of minimal residual disease (MRD) following surgical resection of the primary tumor. Dormant cells are closely associated with long-term clinical latency and late-stage relapse. Due to their quiescent nature, dormant cells are intrinsically resistant to conventional therapies—such as chemotherapy and radiotherapy—that preferentially target rapidly dividing cells. In addition, they display enhanced anti-apoptotic capacity and immune evasion, rendering them particularly difficult to eradicate. More critically, in response to microenvironmental changes or activation of specific signaling pathways, dormant cells can re-enter the cell cycle and initiate metastatic outgrowth or tumor recurrence. This ability to escape dormancy underscores their clinical threat and positions their effective detection and elimination as a major challenge in contemporary cancer treatment. Hypoxia, a hallmark of the solid tumor microenvironment, has been widely recognized as a potent inducer of tumor cell dormancy. However, the molecular mechanisms by which tumor cells sense and respond to hypoxic stress—initiating the transition into dormancy—remain poorly defined. In particular, the lack of a systems-level understanding of the dynamic and multifactorial regulatory landscape has impeded the identification of actionable targets and constrained the development of effective therapeutic strategies. Accumulating evidence indicates that hypoxia-induced dormancy tumor cells are accompanied by a suite of adaptive phenotypes, including cell cycle arrest, global suppression of protein synthesis, metabolic reprogramming, autophagy activation, resistance to apoptosis, immune evasion, and therapy tolerance. These changes are orchestrated by multiple converging signaling pathways—such as PI3K-AKT-mTOR, Ras-Raf-MEK-ERK, and AMPK—that together constitute a highly dynamic and interconnected regulatory network. While individual pathways have been studied in depth, most investigations remain reductionist and fail to capture the temporal progression and network-level coordination underlying dormancy transitions. Systems biology offers a powerful framework to address this complexity. By integrating high-throughput multi-omics data—such as transcriptomics and proteomics—researchers can reconstruct global regulatory networks encompassing the key signaling axes involved in dormancy regulation. These networks facilitate the identification of core regulatory modules and elucidate functional interactions among key effectors. When combined with dynamic modeling approaches—such as ordinary differential equations—these frameworks enable the simulation of temporal behaviors of critical signaling nodes, including phosphorylated AMPK (p-AMPK), phosphorylated S6 (p-S6), and the p38/ERK activity ratio, providing insights into how their dynamic changes govern transitions between proliferation and dormancy. Beyond mapping trajectories from proliferation to dormancy and from shallow to deep dormancy, such dynamic regulatory models support topological analyses to identify central hubs and molecular switches. Key factors—such as NR2F1, mTORC1, ULK1, HIF-1α, and DYRK1A—have emerged as pivotal nodes within these networks and represent promising therapeutic targets. Constructing an integrative, systems-level regulatory framework—anchored in multi-pathway coordination, omics-layer integration, and dynamic modeling—is thus essential for decoding the architecture and progression of tumor dormancy. Such a framework not only advances mechanistic understanding but also lays the foundation for precision therapies targeting dormant tumor cells during the MRD phase, addressing a critical unmet need in cancer management.

In this study, serum metabolomics techniques and molecular biology methods were used to investigate the intervention effect of kaji-ichigoside F1 on chronic unpredictable mild stress(CUMS) depression mouse model and its mechanism. The CUMS depression mouse model was constructed, and the mice were divided into blank group, model group, escitalopram(ESC, 10 mg·kg~(-1)) group, and low-dose, medium-dose, and high-dose kaji-ichigoside F1 groups(1, 2, and 4 mg·kg~(-1)). CUMS modeling was performed on all mice except the blank group, and the cycle was four weeks. At the end of modelling, ESC and kaji-ichigoside F1 were administered by gavage once a day for 28 days. After the end of the administration, behavioral testing(sucrose preference test, open field test, forced swimming test, and tail suspension test) was conducted to evaluate the improvement of depression symptoms of different doses of kaji-ichigoside F1 on CUMS depression mouse model. The morphology of neurons and the number of Nissl bodies in the hippocampus were observed by Nissl staining. Metabolomics technique was used to analyze the changes in serum differential metabolites in mice. Protein expression levels of P2X7 purinergic receptor(P2X7R), adenosine A1 receptor(A1R), and adenosine receptor A2A(A2AR) in mouse hippocampus were detected by Western blot. The results showed that compared with that in the blank group, the body weight of mice in the model group was significantly decreased, and the sucrose preference rate was significantly decreased. The immobility time was significantly increased in the forced swimming and tail suspension tests, and the total moving distance was significantly decreased in the open field test. The number of Nissl bodies was significantly decreased, and the depression-like behavior and the number of Nissl bodies in the hippocampus of mice were significantly improved after administration of kaji-ichigoside F1. In the metabonomics analysis, the purine metabolism of serum after kaji-ichigoside F1 administration was involved in the metabolic passage of depression, and Western blot analysis verified the expression of P2X7R, A1R, and A2AR proteins in purine metabolic pathways. The results show that kaji-ichigoside F1 significantly decreases the expression of P2X7R and A2AR proteins in the hippocampus of CUMS model mice and increases the expression level of A1R proteins. It is suggested that kaji-ichigoside F1 may play an antidepressant role by regulating the expression of P2X7R, A1R, and A2AR proteins in the purine metabolism pathway.
Animals ; Mice ; Antidepressive Agents/administration & dosage* ; Metabolomics ; Depression/genetics* ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Disease Models, Animal ; Hippocampus/metabolism* ; Behavior, Animal/drug effects* ; Humans

OpenSim is an open source, free motion simulation and gait analysis software, which can be used to dynamically simulate and analyze the complex motion of the human body, and is widely used in human biomechanical research. Since OpenSim can analyze multi-dimensional motion data such as muscle strength, joint torque, and muscle synergistic activation during human movement, it can be used to study the biomechanical mechanism of musculoskeletal imbalance diseases and various treatment methods in TCM orthopedics, and has a broad application prospect in the field of TCM orthopedics. By the analysis of the basic characteristics, elements, analysis process, and application prospects of OpenSim, it is concluded that OpenSim musculoskeletal model has a large application space in the field of traditional Chinese medicine orthopedic, which is helpful to explain the pathogenesis and mechanism of diseases, and promote the precision diagnosis and treatment of orthopedics diseases;the application of OpenSim musculoskeletal model can solve the problem that the previous research paid attention to the bone malalignment and not enough attention to the tendon, and provide a new method for the research of orthopedic diseases. At present, there are still problems in the promotion and application of OpenSim, such as large equipment requirements and high operation threshold. Therefore, multidisciplinary cooperation, clinical research, and data sharing are the basic research strategies in this field.
Humans ; Biomechanical Phenomena ; Orthopedics ; Traumatology ; Software ; Medicine, Chinese Traditional ; Musculoskeletal System ; Models, Biological