This article presents a case study of a patient who visited the Geriatric Department of Peking Union Medical College Hospital due to "palpitations, shortness of breath for more than 2 years, limb weakness for 6 months, edema, and nocturnal dyspnea for 2 months". The patient exhibited decreased muscle strength in the limbs and involvement of swallowing and respiratory muscles, alongside complications of heart failure and various arrhythmias which were predominantly atrial. Laboratory tests revealed the presence of multiple autoantibodies and notably anti-mitochondrial antibodies. Following a comprehensive multidisciplinary evaluation, the patient was diagnosed with anti-mitochondrial antibody-associated inflammatory myopathy. Treatment involved a combination of glucocorticoids and immunosuppressants, along with resistance exercises for muscle strength and rehabilitation training for lung function, resulting in significant improvement of clinical symptoms. The case underscores the importance of collaborative multidisciplinary approaches in diagnosing and treating rare diseases in elderly patients, where careful consideration of clinical manifestations and subtle abnormal clinical data can lead to effective interventions.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Background Diseases severely affect the efficiency of workers. Comorbidity refers to the coexistence of two or more chronic diseases or health problems in the same individual. Previous studies have primarily focused on occupational injuries caused by environmental exposures, while the analysis of the epidemiological characteristics of self-reported diseases and occupational injuries among manufacturing workers has been insufficient. Objective To analyze the distribution of self-reported diseases and occupational injuries among manufacturing workers, the strength of correlation between different diseases, and common disease combinations, and to preliminarily explore the relationship between self-reported diseases and occupational injuries. Methods A cross-sectional survey was conducted to investigate the occupational injuries of 2382 workers in 2 manufacturing enterprises over the past year, and 2355 questionnaires were valid after cleaning. The questionnaire included three parts: basic information, occupational injury occurrence, and disease prevalence. The self-reported diseases diagnosed by physicians included musculoskeletal diseases, cardiovascular diseases, respiratory diseases, mental health problems, neurological and sensory organ diseases, digestive organ diseases, reproductive and urinary organ diseases, skin diseases, tumors, endocrine and metabolic system diseases, blood diseases and birth defects, a total of 11 types. Log-binomial model was used to calculate the prevalence ratio (PR) value of the association between different diseases, and UpSet diagram was used to present the disease combination pattern. Results In total, 40.2% (946/2355) of the study participants reported at least one disease, while 8.6% (203/2355), 5.2% (122/2355), and 5.9% (140/2355) reported having two, three, and four or more diseases, respectively. A higher prevalence was observed for musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases, which accounted for 18.0% (423/2355), 13.8% (324/2355), 9.3% (218/2355), and 9.1% (214/2355), respectively. Workers with musculoskeletal disorders, cardiovascular diseases, or neurological and sensory organ diseases reported significantly higher incidence of occupational injuries compared with workers without the corresponding diseases (P<0.001, P=0.041, and P=0.006, respectively). Musculoskeletal diseases were strongly associated with comorbidities of neurological and sensory organ diseases (PR values were 1.86 and 1.98, respectively), and the other patters were musculoskeletal diseases and digestive organ diseases (PR and OR values were 1.57 and 2.35, respectively), and musculoskeletal diseases and cardiovascular diseases (PR and OR values were 1.46 and 2.22, respectively). The largest binomial comorbidity group involved musculoskeletal diseases and neurological and sensory organ diseases, accounting for 5.4% (25/465) of the comorbid workers. Conclusion Among the self-reported diseases of manufacturing workers, musculoskeletal diseases, neurological and sensory organ diseases, digestive organ diseases, and skin diseases are more common. Musculoskeletal diseases and neurological and sensory organ diseases are the most common in all comorbidities. Musculoskeletal diseases, cardiovascular diseases, and neurological and sensory organ diseases are associated with occupational injuries. In the prevention and control of occupational injuries, joint prevention strategies targeting multiple diseases should be strengthened.

The chemical constituents from the n-butanol fraction of ethanol extract of safflower (Carthamus tinctorius L.) were isolated and purified using chromatographic process including MCI Gel CHP-20, ODS, Sephadex LH-20 column chromatography, and semi-preparative HPLC method, and one alkyne and two phenylpropanoid derivants were obtained. Their structures were identified as (5R,E)-tetradecane-12-ene-8,10-diyne-1,5,14-triol (1), (E)-8-O-β-D-glucopyranosyl n-butyl cinnamate (2), and (7S,8S)-7-(4-hydroxy-3-methoxybenzene)-7-butyl-8,9-diol (3) by modern spectroscopy methods (1D NMR, 2D NMR, UV, IR and MS). 1-3 are all new compounds. Compounds 1-3 were screened for their anti-renal fibrosis activities in vitro, and none of them showed obvious effect.

ObjectiveTo collate and compare the characteristics and differences in the methods for constructing animal models of different subtypes of gastroesophageal reflux disease （GERD） based on literature， providing a reference for researchers in this field regarding animal model construction. MethodsExperimental studies related to GERD including reflux esophagitis （RE）， nonerosive reflux disease （NERD） and Barrett's esophagus （BE） model construction from January 1， 2014 to January 27， 2024， were retrieved from databases such as CNKI， Wanfang， VIP， Web of Science， and Pubmed. Information on animal strains， genders， modeling methods including disease-syndrome combination models， modeling cycles were extracted； for studies with model evaluation， the methods of model evaluation were also extracted； then analyzing all those information. ResultsA total of 182 articles were included. SD rats were most frequently selected when inducing animal models of RE （88/148， 59.46%） and NERD （9/14， 64.29%）. For BE， C57BL/6 mice were most commonly used （11/20， 55.00%）. Male animals （RE： 111/135， 82.22%； NERD： 11/14， 78.57%； BE： 10/12， 83.33%） were the most common gender among the three subtypes. The key to constructing RE animal models lies in structural damage to the esophageal mucosal layer， gastric content reflux， or mixed reflux， among which forestomach ligation + incomplete pylorus ligation （42/158， 26.58%） was the most common modeling method； the key to constructing NERD animal models lies in micro-inflammation of the esophageal mucosa， visceral hypersensitivity， and emotional problems， and intraperitoneal injection of a mixed suspension of ovalbumin and aluminum hydroxide combined with acid perfusion in the lower esophagus （8/14， 57.14%） was the most common modeling method； the key to constructing BE animal models lies in long-term inflammatory stimulation of the esophageal mucosa and bile acid reflux， and constructing interleukin 2-interleukin 1β transgenic mice （7/25， 28.00%） was the most common modeling method. Adverse psychological stress was the most common method for inducing liver depression. ConclusionsThe construction key principles and methodologies for RE， NERD， and BE animal models exhibit significant differences. Researchers should select appropriate models based on subtype characteristics （e.g.， RE focusing on structural damage， NERD emphasizing visceral hypersensitivity）. Current studies show insufficient exploration of traditional Chinese medicine disease-syndrome combination models. Future research needs to optimize syndrome modeling approaches （e.g.， composite etiology simulation） and establish integrated Chinese-Western medicine evaluation systems to better support mechanistic investigations of traditional Chinese medicine.

Lung transplantation is the ultimate therapeutic option for end-stage pulmonary diseases such as interstitial pneumonia, chronic obstructive pulmonary disease and pneumoconiosis. Currently, the shortage of allogeneic lung donors significantly limits the opportunity for end-stage lung disease patients to receive lung transplantation. In recent years, with the rapid development of biomedical engineering technologies, especially the major breakthroughs in genetic modification and cloning, xenogeneic lung transplantation has shown important potential for clinical translation. Among them, genetically modified pigs have become the most promising xenogeneic lung source due to the close similarity of organ size and physiological characteristics to humans, and the ability to perform targeted gene knockouts (such as α-Gal antigen knockout) to reduce the occurrence of hyperacute rejection. This article focuses on the research progress of porcine xenogeneic lung transplantation, systematically reviews the latest achievements and challenges in animal experiments and human trials, and introduces the technical experience accumulated by Shenzhen Third People's Hospital in the porcine-to-monkey xenogeneic lung transplantation model, in the hope of providing practical references for future research in this field.

ObjectiveTo retrospectively analyze the effect of modified Shugan Dingji Decoction （疏肝定悸汤） on the occurrence of endpoint events in patients with paroxysmal atrial fibrillation of liver constraint and qi stagnation. MethodsA retrospective cohort study was conducted using the electronic medical record database of Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine to screen and include patients with paroxysmal atrial fibrillation of liver constraint and qi stagnation from January 1st， 2018， to December 31th， 2021. The included patients were divided into an exposure group and a non-exposure group， each consisting of 100 cases， based on whether they received modified Shugan Dingji Decoction. General information of the patients including age， gender， body mass index， duration of illness and comorbidities， medication history， cardiac structure and function indicators such as left atrial diameter， left ventricular end-diastolic diameter， stroke volume and ejection fraction， and the occurrence of endpoint events assessed through 24-hour dynamic electrocardiography or electrocardiogram to determine the recurrence of paroxysmal atrial fibrillation were collected. Kaplan-Meier （K-M） curves and Log-Rank tests were used to conduct survival analysis on the occurrence of endpoint events in the two groups of patients. Univariate and multivariate Cox regression analyses were used to analyze the impact of various factors on entry into endpoint events. Additionally， a safety assessment was performed by comparing liver and kidney function indicators before and after treatment. ResultsIn the non-exposure group， a total of 49 cases （49.0%） experienced endpoint events， while in the exposure group， there were 26 cases （26.0%）. The Log-rank test indicated significant difference between the two groups （χ²=11.211， P=0.001）. Univariate Cox regression analysis showed that age， duration of illness， hypertension， diabetes， chronic heart failure， left atrial diameter， stroke volume， and the use of modified Shugan Dingji Decoction may be the influencing factors for the occurrence of endpoint events in patients with paroxysmal atrial fibrillation of liver constraint and qi stagnation （P＜0.05 or P＜0.01）. Multivariate Cox regression analysis showed that the risk of endpoint events in the exposure group was significantly lower than that in the non-exposure group （P＜0.01）. Patients with a duration of illness ＞12 months had a significantly higher risk of endpoint events compared to those with a duration of illness ≤12 months （P＜0.01）. Patients without concomitant hypertension had a lower risk of endpoint events compared to those with hypertension （P＜0.05）. Patients with left atrial diameter ＞40 mm had significantly higher risk of endpoint events than those with left atrial diameter ≤40 mm （P＜0.01）. There was no statistically significant difference in liver and kidney function indicators between the two groups before and after treatment （P＞0.05）. ConclusionThe use of modified Shugan Dingji Decoction is a protective factor for patients with paroxysmal atrial fibrillation of liver constraint and qi stagnation， which can help to reduce the recurrence and progression of atrial fibrillation. Long duration of illness， concomitant hypertension， and enlarged left atrial diameter are risk factors for patients to experience endpoint events.

Objective To observe the clinical efficacy and safety of spironolactone combined with sacubitril/valsartan in the treatment of patients with hypertensive nephropathy.Methods The patients with hypertensive nephropathy were randomly divided into control group and treatment group.The control group was treated with sacubitril/valsartan(100-200 mg·d-1 in the morning),and treatment group was combined with low-dose spironolactone treatment(20 mg·d-1 in the morning)on the basis of control group.Both groups were treated continuously for 12 weeks.The clinical efficacy was compared;the blood pressure,urinary microalbumin(mAlb),urinary β2 microglobulin(β2-MG)and serum cystatin C(Cys-C),transforming growth factor-β1(TGF-β1),connective tissue growth factor(CTGF)and angiotensin Ⅱ(Ang Ⅱ)and adverse drug reactions were observed before and after treatment.Results There were 87 cases in treatment group and 86 cases in control group were included respectively.After treatment,the total effective rates in treatment group and control group were 95.40％(83 cases/87 cases)and 82.56％(71 cases/86 cases),with significant difference(P＜0.05).After treatment,the systolic blood pressure values in treatment group and control group were(124.65±9.65)and(130.27±8.93)mmHg,the diastolic blood pressure values were(75.08±7.14)and(80.45±7.35)mmHg,urinary mAlb levels were(42.58±5.65)and(51.28±6.64)mg·L-1,urinary β2-MG levels were(0.46±0.17)and(0.75±0.25)mg·L-1,24 h urinary protein quantitation levels were(138.49±46.64)and(216.48±65.27)mg,serum Cys-C levels were(0.63±0.26)and(0.85±0.24)mg·L-1,TGF-β1 levels were(98.67±21.43)and(112.46±26.72)pg·mL-1,CTGF levels were(1 206.54±236.56)and(1 340.51±248.25)pg·mL-1,Ang Ⅱ levels were(101.55±17.62)and(115.65±20.08)pg·mL-1,all with significant difference(all P＜0.05).The incidence of adverse drug reactions in treatment group and control group were 6.90％(6 cases/87 cases)and 2.33％(2 cases/86 cases),with no significant difference(P＞0.05).Conclusion Compared with sacubitril/valsartan alone,spironolactone combined with sacubitril/valsartan can better reduce blood pressure,improve renal function and delay progression of renal fibrosis in the treatment of hypertensive nephropathy,and has definite efficacy,with good safety.

With the advent of an aging society,Alzheimer's disease(AD)has gradually become a major ailment affecting the elderly.AD is a neurodegenerative disorder associated with cognitive impairments.In AD patients,brain network connections are disrupted,and their topological properties are also affected,leading to the disintegration of anatomical and functional connections.Anatomical connections can be tracked and evaluated using structural magnetic imaging(MRI)and diffusion tensor imaging(DTI),while functional connections are detected through functional MRI to assess their connectivity status.This review incorporates the findings of previous scholars and summarizes the current research of AD.It mainly discusses the imaging characteristics of large-scale brain network changes in AD patients,so as to provide researchers with scientific and objective imaging markers for AD prediction and early diagnosis,as well as future research.

Objective: To explore the feasibility of remotely obtaining complex information on traditional Chinese medicine (TCM) pulse conditions through voice signals. Methods: We used multi-label pulse conditions as the entry point and modeled and analyzed TCM pulse diagnosis by combining voice analysis and machine learning. Audio features were extracted from voice recordings in the TCM pulse condition dataset. The obtained features were combined with information from tongue and facial diagnoses. A multi-label pulse condition voice classification DNN model was built using 10-fold cross-validation, and the modeling methods were validated using publicly available datasets. Results: The analysis showed that the proposed method achieved an accuracy of 92.59% on the public dataset. The accuracies of the three single-label pulse manifestation models in the test set were 94.27%, 96.35%, and 95.39%. The absolute accuracy of the multi-label model was 92.74%. Conclusion Voice data analysis may serve as a remote adjunct to the TCM diagnostic method for pulse condition assessment.