This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

Recurrent syncopal episodes associated with head and neck lymphoma are rarely reported. Through a typical case study, this article analyzes the clinical features of patients with neck lymphoma presenting with syncope as the initial symptom, aiming to improve understanding of this type of disease. By reviewing the clinical data of this patient with neck masses admitted for recurrent syncope in June 2023 and integrating findings with relevant literature, the clinical characteristics of this patient population is presented. The first symptoms of lymphoma presenting as syncope are relatively rare and often lead to misdiagnosis. Diagnosis is mainly based on pathological and immunohistochemical analysis.
Humans ; Head and Neck Neoplasms/diagnosis* ; Lymphoma/diagnosis* ; Recurrence ; Syncope/etiology* ; Young Adult ; Diagnostic Errors

Tailored lipid nanoparticles (LNPs)-mediated small interfering RNA (siRNA) nanomedicines show promise in treating liver disease, such as acute liver injury (ALI) and non-alcoholic steatohepatitis (NASH). However, constructing LNPs that address biosafety concerns, ensure efficient delivery, and target specific hepatic subcellular fractions has been challenging. To evade above obstacles, we develop three novel self-degradable "gemini-like" ionizable lipids (SS-MA, SS-DC, SS-MH) by incorporating disulfide bonds and modifying the length of ester bond and tertiary amino head. Our findings reveal that the disulfide-bond-bridged LNPs exhibit reduction-responsive drug release, improving both biosafety and siRNA delivery efficiency. Furthermore, the distance of ester bond and tertiary amino head significantly influences the LNPs' pK _a, thereby affecting endosomal escape, hemolytic efficiency, absorption capacity of ApoE, uptake efficiency of hepatocytes and liver accumulation. We also develop the modified-mannose LNPs (M-LNP) to target liver macrophages specifically. The optimized M-MH_LNP@TNFα exhibits potential in preventing ALI by decreasing tumor necrosis factor α (TNFα) levels in the macrophages, while MH_LNP@DGAT2 could treat NASH by selectively degrading diacylglycerol O-acyltransferase 2 (DGAT2) in the hepatocytes. Our findings provide new insights into developing novel highly effective and low-toxic "gemini-like" ionizable lipids for constructing LNPs, potentially achieving more effective treatment for hepatic diseases.

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

OBJECTIVE: Observational studies have found associations between inflammatory bowel disease (IBD) and the risk of dementia, including Alzheimer's dementia (AD) and vascular dementia (VD); however, these findings are inconsistent. It remains unclear whether these associations are causal. METHODS: We conducted a meta-analysis by systematically searching for observational studies on the association between IBD and dementia. Mendelian randomization (MR) analysis based on summary genome-wide association studies (GWASs) was performed. Genetic correlation and Bayesian co-localization analyses were used to provide robust genetic evidence. RESULTS: Ten observational studies involving 80,565,688 participants were included in this meta-analysis. IBD was significantly associated with dementia (risk ratio [ RR] =1.36, 95% CI = 1.04-1.78; I ² = 84.8%) and VD ( RR = 2.60, 95% CI = 1.18-5.70; only one study), but not with AD ( RR = 2.00, 95% CI = 0.96-4.13; I ² = 99.8%). MR analyses did not supported significant causal associations of IBD with dementia (dementia: odds ratio [ OR] = 1.01, 95% CI = 0.98-1.03; AD: OR = 0.98, 95% CI = 0.95-1.01; VD: OR = 1.02, 95% CI = 0.97-1.07). In addition, genetic correlation and co-localization analyses did not reveal any genetic associations between IBD and dementia. CONCLUSION Our study did not provide genetic evidence for a causal association between IBD and dementia risk. The increased risk of dementia observed in observational studies may be attributed to unobserved confounding factors or detection bias.
Humans ; Mendelian Randomization Analysis ; Inflammatory Bowel Diseases/complications* ; Dementia/etiology* ; Observational Studies as Topic ; Genome-Wide Association Study

Objective:To systematically review qualitative studies on the experiences of musculoskeletal symptoms in breast cancer patients undergoing endocrine therapy, and to gain insights into the initiation, development, and effects of these symptoms, along with their implications for patients, to guide the creation of targeted strategies for symptom management.Methods:The qualitative studies on the experiences of musculoskeletal symptoms in breast cancer patients undergoing endocrine therapy were performed across several databases, which included the Cochrane Library, Joanna Briggs Institute Evidence based Healthcare Center Database, PubMed, Embase, CINAHL, Web of Science, Scopus, CNKI, Wanfang Data, and Chinese Biomedical Literature Database. The retrieval period was from the establishment of the database to April 30, 2024. The studies' quality was evaluated utilizing the iteration of the Joanna Briggs Institute Qualitative Assessment and Review Instrument designed for qualitative research. Data synthesis was carried out using Meta-aggregation techniques.Results:A total of 15 articles were included and 41 results were extracted, which were grouped into 11 new categories and integrated into 3 primary themes: the manifestation of bone and joint symptoms was highly unique and varied, prominently featuring experiences such as migratory joint pain, morning stiffness, and cramps affecting both large and small joints, frequently associated with functional limitations; these symptoms significantly influence patients' everyday activities and mental health, contributing to feelings of anxiety, avoidance behaviors, fear, and a reduction in overall quality of life; to manage the intricate nature of their symptoms, patients employ a variety of coping mechanisms, such as engaging in physical activity, taking dietary supplements, consulting about medications, and seeking support from external sources.Conclusions:During endocrine therapy for breast cancer, patients exhibit diverse characteristics of musculoskeletal symptoms, and the resulting fear of recurrence, avoidance behaviors, and anxiety have a negative impact on their psychological well-being and overall health. Healthcare professionals should take into account individual differences, such as age, menopausal status, type of endocrine therapy, medication adherence, and factors that may exacerbate or alleviate symptoms, in order to effectively predict, assess, and manage bone and joint symptoms during endocrine therapy.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective To explore the pharmacokinetic characteristics of sufentanil in individuals with normal body mass index(BMI),overweight BMI,and different CYP3A4/5 enzyme genotypes.Methods The patients receiving laparoscopic surgery under general anesthesia in the First Affiliated Hospital of Army Medical University from November 2020 to September 2021 were prospectively recruited in this study.Before the operation,the oral swabs were collected from all the patients for genotyping using the human CYP3A4/5 gene kit.Based on the potential impact of combination of their polymorphisms on sufentanil metabolism and the proportion of different genotype combinations of CYP3A4/5 enzymes,the patients were divided into groups I(3A4 homozygous mutation or 3A4 heterozygous mutation+3A5 homozygous mutation),II(3A4 heterozygous mutation+3A5 heterozygous mutation),and III(3A4 wild type or 3A4 heterozygous mutation+3A5 wild type).According to their BMI,they were also assigned into a normal body weight group(18.5～24.0 kg/m2)and an overweight group(24～<28 kg/m2),and the differences in drug metabolism parameters were statistically analyze between the 2 groups.After routine general anesthesia induction(sufentanil 0.5 μg/kg),venous blood samples were collected to detect the changes in its concentration using high performance liquid chromatography-mass spectrometry(HPLC-MS).The pharmacokinetic data of sufentanil were calculated between the normal BMI group and overweight group in all participants and between the 2 body weight groups among those with different genotype combinations.Results Among the 90 participants completing the blood drug concentration test,8 patients had their blood samples contaminated(including 1 case with an anesthesia duration of<2 h),and 3 were excluded due to low weight or overweight.Eventually,79 participants were included in the pharmacokinetic analysis on the normal body weight group and the overweight group.Compared with the normal body weight group,the central compartment volume of distribution in the overweight group was significantly reduced(P<0.05),while no obvious differences were observed between the 2 groups in terms of peripheral compartment volume of distribution,total clearance rate,peripheral compartment clearance rate,distribution half-life,clearance half-life,and area under the blood concentration-time curve.In group Ⅰ(n=26),the overweight patients(n=13)had significantly reduced central compartment volume of distribution,peripheral compartment volume of distribution,and peripheral compartment clearance rate when compared with the normal body weight patients(n=13)(P<0.05),while no differences were observed in other pharmacokinetic parameters.In groups Ⅱ(n=25)and Ⅲ(n=28),the overweight patients and normal body weight patients had no statistical differences in all pharmacokinetic parameters.Conclusion Among the patients with the same genotype combination of CYP3A4/5 mutations,there was no difference in the metabolism of sufentanil between the overweight and normal weight patients.Additionally,in the population of 3A4 homozygous mutation or 3A4 heterozygous mutation+3A5 homozygous mutation,the overweight patients have smaller peripheral distribution range of sufentanil,and weakened metabolic process.

Cervical spinal cord injury without fracture-dislocation (CSCIWFD) is referred to as a special type of cervical spinal cord injury characterized by traumatic spinal cord dysfunction and no significant bony structural abnormalities on imagines. Duo to the high risk of missed diagnosis during the initial consultation, CSCIWFD may lead to progressive neurological deterioration or even complete paralysis, severely impacting patients′ prognosis. Currently, there are no established consensuses over the diagnosis and treatment of CSCIWFD, such as the lack of evidence-based standards for indications of non-surgical treatment and risk of secondary neurological injury, as well as debates over the optimal timing for surgical intervention and indications for different surgical approaches. To address these issues, the Spine Trauma Group of the Orthopedic Branch of the Chinese Medical Doctor Association organized experts in the relevant fields to formulate Diagnosis and treatment guideline for acute cervical spinal cord injury without fracture- dislocation in adults ( version 2025) . Based on evidence-based medicine and the principles of scientific rigor and clinical applicability, the guidelines proposed 11 recommendations covering terminology, diagnosis, evaluation treatment, and rehabilitation, etc., aiming to standardize the management of CSCIWFD.

BACKGROUND: T cell dysfunction, which includes exhaustion, anergy, and senescence, is a distinct T cell differentiation state that occurs after antigen exposure. Although T cell dysfunction has been a cornerstone of cancer immunotherapy, its potential in transplant research, while not yet as extensively explored, is attracting growing interest. Interferon regulatory factor 4 (IRF4) has been shown to play a pivotal role in inducing T cell dysfunction. METHODS: A novel ultra-low-dose combination of Trametinib and Rapamycin, targeting IRF4 inhibition, was employed to investigate T cell proliferation, apoptosis, cytokine secretion, expression of T-cell dysfunction-associated molecules, effects of mitogen-activated protein kinase (MAPK) and mammalian target of rapamycin (mTOR) signaling pathways, and allograft survival in both in vitro and BALB/c to C57BL/6 mouse cardiac transplantation models. RESULTS: In vitro , blockade of IRF4 in T cells effectively inhibited T cell proliferation, increased apoptosis, and significantly upregulated the expression of programmed cell death protein 1 (PD-1), Helios, CD160, and cytotoxic T lymphocyte-associated antigen (CTLA-4), markers of T cell dysfunction. Furthermore, it suppressed the secretion of pro-inflammatory cytokines interferon (IFN)-γ and interleukin (IL)-17. Combining ultra-low-dose Trametinib (0.1 mg·kg -1 ·day -1 ) and Rapamycin (0.1 mg·kg -1 ·day -1 ) demonstrably extended graft survival, with 4 out of 5 mice exceeding 100 days post-transplantation. Moreover, analysis of grafts at day 7 confirmed sustained IFN regulatory factor 4 (IRF4) inhibition, enhanced PD-1 expression, and suppressed IFN-γ secretion, reinforcing the in vivo efficacy of this IRF4-targeting approach. The combination of Trametinib and Rapamycin synergistically inhibited the MAPK and mTOR signaling network, leading to a more pronounced suppression of IRF4 expression. CONCLUSIONS Targeting IRF4, a key regulator of T cell dysfunction, presents a promising avenue for inducing transplant immune tolerance. In this study, we demonstrate that a novel ultra-low-dose combination of Trametinib and Rapamycin synergistically suppresses the MAPK and mTOR signaling network, leading to profound IRF4 inhibition, promoting allograft acceptance, and offering a potential new therapeutic strategy for improved transplant outcomes. However, further research is necessary to elucidate the underlying pharmacological mechanisms and facilitate translation to clinical practice.
Animals ; Mice ; Mice, Inbred BALB C ; Mice, Inbred C57BL ; Interferon Regulatory Factors/metabolism* ; Heart Transplantation/methods* ; T-Lymphocytes/immunology* ; Sirolimus/therapeutic use* ; Pyridones/therapeutic use* ; Graft Survival/drug effects* ; Pyrimidinones/therapeutic use* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Male ; Signal Transduction/drug effects*