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.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

AIM To establish the preparation process and quality standard for Zhenggu Pills.METHODS With decoction time,decoction frequency and water addition as influencing factors,comprehensive score for extract yield and transfer rates of epicatechin and naringin as an evaluation index,the decoction process was optimized by orthogonal test.With sugarless paste relative density,medicinal powder fineness,sugarless paste-corn starch ratio,drying temperature and drying time as influencing factors,soft material traits,pill formability,moisture and disintegration time limit as evaluation indices,the formability process was optimized by single factor test.TLC was adopted in the qualitative identification of Dipsaci Radix,salt-processed Psoraleae Fructus,cooked Rhei Radix et Rhizoma and Notoginseng Radix et Rhizoma.HPLC was used for the content determination of paeoniflorin and naringin.RESULTS The optimal decoction process was determined to be 0.5 h for decoction time,two times for decoction frequency,and 10 times for water addition,the comprehensive score was 0.93.The optimal formability process was determined to be 1.21-1.22 for sugarless paste relative density,80 mesh for medicinal powder fineness,1∶0.17-1∶0.18 for sugarless paste-corn starch ratio,70 ℃ for drying temperature,and 24 h for drying time,good soft material traits and pill formability were observable,and moisture and disintegration time limit accored with 2020 edition of Chinese Pharmacopoeia requirements.The TLC spots were clear without negative interference.Two constituents showed good linear relationships within 61.30-490.41 μg/mL(r=0.999 8)and 3.27-26.18 μg/mL(r=0.999 8),whose average recoveries were 100.15％and 98.15％with the RSDs of 0.55％and 2.30％,respectively.CONCLUSION This stable,reliable and specific method can be used for the production and quality evaluation of Zhenggu Pills.

AIM To establish the quantitative models for gallic acid,mononucleoside,loganin,resveratrol,and rhein in Yishen Xiezhuo Mixture.METHODS HPLC was adopted in the content determination of various effective components,after which the near-infrared spectroscopy(NIRS)data were collected in 128 batches of samples and pretreatment was conducted,competitive adaptive reweighting sampling(CARS)algorithm was used for screening wavelength,partial least square method(PLS)regression analysis was performed.RESULTS There were no significant differences between the predicted values obtained by PLS models and measured values obtained by HPLC for various effective components(P＞0.05).CONCLUSION The quantitative models established by NIRS combined with chemometrics display good predictive performance,which can be used for the rapid determination of effective components in Yishen Xiezhuo Mixture,and provide a reference for the rapid monitoring of other traditional Chinese medicine preparations in production processes.

Purpose To summarize the clinical pathological and immunohistochemical characteristics of esophage-al carcinoma with ductal differentiation of esophageal gland,and analyze the somatic mutation characteristics,key driv-ing mutation genes,and significantly mutated genes based on whole exome sequencing.Methods The clinicopatho-logical features of 9 cases of esophageal carcinoma with esophageal duct differentiation were retrospectively analyzed,and the immunohistochemistry EnVision two-step method was used to stain them,and 3 of the samples were subjected to whole exome sequencing and data analysis.Results Among the 9 patients,6 were males and 3 were females.The average age was 68.3 years old(61-80 years old).All 9 cases were located in the middle-lower segment of the e-sophagus.The diameter of the lesion was from 1.5 cm to 3.5 cm.Most areas of the tumor had a double-layer epithelial structure,including the inner layer of luminal epithelium and the outer layer of basal epithelium.Focal areas could be seen with keratinization and mucinous cells.Immunohistochemistry showed that CK7 was positive in the inner epitheli-um,while p63 was positive in the outer basal epithelium.S-100,SOX10 and c-myb were all negative,and p53 was mutated(diffuse strongly positive).The results of whole exome sequencing analysis showed somatic mutation character-istics(796 SNV,37 InDel,482 CNV),key driving mutation genes(12),and significantly mutated genes(TP53).No intraepithelial neoplasia was observed on the surface squamous epithelium of all cases,and no Barrett's esophagus or ectopic gastric mucosa was observed.The average follow-up time was 21.9 months(8 days-51 months),with 8 ca-ses surviving and 1 case dying of severe pulmonary infection 8 days after surgery.Conclusion Esophageal carcinoma with ductal differentiation of esophageal gland is a rare epithelial derived malignant tumor of the esophagus,character-ized by unique morphological,immunohistochemical,and molecular changes.

Purpose To explore the value of the clinical radiomics nomogram based on ultrasound in evaluating the degree of fibrosis in chronic kidney disease(CKD).Materials and Methods This retrospective study included 350 patients with CKD in Nanchong Central Hospital from January 2014 to July 2022 who underwent renal biopsy.The patients were categorized by the tubule atrophy with interstitial fibrosis(TA/IF)and divided into a training cohort(n=245)and test cohort(n=105).The patient demographics were evaluated to establish a clinical prediction model.The XGBoost machine learning model was constructed by extracting the radiomics features from the ultrasound images.The clinical radiomics nomogram prediction model was constructed by combining the radiomics score(Rad score)and important clinical features.The diagnostic performance of the three models was evaluated using receiver operating characteristic curve analysis.Results Among the 350 patients with CKD,226 had TA/IF 0 and 124 had TA/IF 1.Based on the clinical characteristics and Rad score,the clinical radiomics nomogram prediction model had the highest area under the curve in the training and testing cohorts,with the area under the curve of 0.938(95%CI 0.909-0.969)and 0.933(95%CI 0.891-0.980),respectively.Conclusion The ultrasound-based radiomics prediction model has potential value for the noninvasive diagnosis of TA/IF in CKD.Nomogram prediction models based on renal Rad scores and clinic may help clinicians to manage patients.

Purpose To summarize the clinical pathological and immunohistochemical characteristics of esophage-al carcinoma with ductal differentiation of esophageal gland,and analyze the somatic mutation characteristics,key driv-ing mutation genes,and significantly mutated genes based on whole exome sequencing.Methods The clinicopatho-logical features of 9 cases of esophageal carcinoma with esophageal duct differentiation were retrospectively analyzed,and the immunohistochemistry EnVision two-step method was used to stain them,and 3 of the samples were subjected to whole exome sequencing and data analysis.Results Among the 9 patients,6 were males and 3 were females.The average age was 68.3 years old(61-80 years old).All 9 cases were located in the middle-lower segment of the e-sophagus.The diameter of the lesion was from 1.5 cm to 3.5 cm.Most areas of the tumor had a double-layer epithelial structure,including the inner layer of luminal epithelium and the outer layer of basal epithelium.Focal areas could be seen with keratinization and mucinous cells.Immunohistochemistry showed that CK7 was positive in the inner epitheli-um,while p63 was positive in the outer basal epithelium.S-100,SOX10 and c-myb were all negative,and p53 was mutated(diffuse strongly positive).The results of whole exome sequencing analysis showed somatic mutation character-istics(796 SNV,37 InDel,482 CNV),key driving mutation genes(12),and significantly mutated genes(TP53).No intraepithelial neoplasia was observed on the surface squamous epithelium of all cases,and no Barrett's esophagus or ectopic gastric mucosa was observed.The average follow-up time was 21.9 months(8 days-51 months),with 8 ca-ses surviving and 1 case dying of severe pulmonary infection 8 days after surgery.Conclusion Esophageal carcinoma with ductal differentiation of esophageal gland is a rare epithelial derived malignant tumor of the esophagus,character-ized by unique morphological,immunohistochemical,and molecular changes.

Purpose To explore the value of the clinical radiomics nomogram based on ultrasound in evaluating the degree of fibrosis in chronic kidney disease(CKD).Materials and Methods This retrospective study included 350 patients with CKD in Nanchong Central Hospital from January 2014 to July 2022 who underwent renal biopsy.The patients were categorized by the tubule atrophy with interstitial fibrosis(TA/IF)and divided into a training cohort(n=245)and test cohort(n=105).The patient demographics were evaluated to establish a clinical prediction model.The XGBoost machine learning model was constructed by extracting the radiomics features from the ultrasound images.The clinical radiomics nomogram prediction model was constructed by combining the radiomics score(Rad score)and important clinical features.The diagnostic performance of the three models was evaluated using receiver operating characteristic curve analysis.Results Among the 350 patients with CKD,226 had TA/IF 0 and 124 had TA/IF 1.Based on the clinical characteristics and Rad score,the clinical radiomics nomogram prediction model had the highest area under the curve in the training and testing cohorts,with the area under the curve of 0.938(95%CI 0.909-0.969)and 0.933(95%CI 0.891-0.980),respectively.Conclusion The ultrasound-based radiomics prediction model has potential value for the noninvasive diagnosis of TA/IF in CKD.Nomogram prediction models based on renal Rad scores and clinic may help clinicians to manage patients.

Objective To analyze the diagnostic value of fat content measurement based on magnetic resonance multi-echo Dixon(ME-Dixon)technique combined with serological indicators for early liver fibrosis.Methods A total of 78 patients with early liver fibrosis who underwent liver biopsy at the First Affiliated Hospital of Army Medical University from August 2019 to October 2021 were included.According to the pathological results,the patients with early liver fibrosis were divided into the S0 group(n=21),the S1 group(n=32),and the S2 group(n=25).Meanwhile,the complete imaging examination results(including ME-Dixon sequence)and laboratory examination results[including hyaluronic acid(HA),procollagen Ⅲ(PCⅢ),collagen Ⅳ(CⅣ),laminin(LN),aspartate transaminase(AST),alanine amino-transferase(ALT),gamma-glutamyl transferase(GGT),alkaline phosphatase(ALP)]were collected.And the hepatic fat fraction(HFF)was measured by ME-Dixon technique.One-way ANOVA was used to analyze the differences in HFF and serological indicators among the three groups,and then factors with statistical differences in the univariate analysis were selected to draw receiver operating characteristic(ROC)curve,and the area under the curve(AUC)was calculated to evaluate their value in the diagnosis of liver fibrosis and the degree of early liver fibrosis.Results There was no statistically significant difference in the PCⅢ,LN,AST,or ALT among the S0,S1,and S2 groups(P>0.05),while there were statistically significant differences in the HFF,HA,CⅣ,GGT,and ALP(P<0.05),and the levels of HA,CⅣ,GGT,and ALP in the S2 group were significantly higher than those in the S0 and S1 groups(P<0.05).ROC curve analysis showed that the above indicators for diagnosing liver fibrosis and the degree of early liver fibrosis based on AUC values were in the following order:HFF+GGT(0.72)>HFF(0.68)>GGT(0.61)>CⅣ(0.54)>ALP(0.53)>HA(0.48)and HA+CⅣ(0.71)>CⅣ(0.68)>HA(0.66)>GGT(0.61)>ALP(0.59)>HFF(0.46).Conclusion The fat content measurement based on magnetic resonance ME-Dixon tech-nique combined with serological indicators has significant reference value for the diagnosis of early liver fibrosis,and it plays a certain guid-ing role in clinical diagnosis and treatment.

Depression is a prevalent mental and emotional disor-der that often results in significant emotional disturbances,cog-nitive dysfunction,and memory impairments.It is characterized by a high incidence rate,a substantial disability burden,and limited therapeutic efficacy.Currently,the long-term use of medications for the treatment of depression can result in a range of adverse reactions,highlighting the urgent need to explore no-vel approaches that can effectively alleviate depressive symptoms while minimizing side effects.Curcumin,a natural polyphenolic compound derived from the rhizome of turmeric,demonstrates considerable potential in the prevention and treatment of depres-sion,owing to its diverse array of biological activities.In recent years,numerous studies have investigated the use of curcumin for the treatment of depression.This article aims to provide a comprehensive review of the mechanisms of action underlying curcumin's efficacy in treating depression.Specifically,it focu-ses on its ability to improve neurotransmitter imbalances,restore neural plasticity,alleviate neural damage,mitigate dysfunction of the hypothalamic-pituitary-adrenal(HPA)axis,regulate in-flammatory factors and neuroinflammatory signaling pathways,and inhibit oxidative stress.This review is intended to offer in-sights and methodological references for basic research on curcu-min,as well as for the development of novel therapeutic agents for the treatment of depression.