OBJECTIVES: To analyze the differences in the prognosis of gastric signet ring cell carcinoma (SRCC) among different races using the US Surveillance Epidemiology and End Results (SEER) database and The Cancer Genome Atlas (TCGA) database. METHODS: We analyzed the data of patients with gastric SRCC from the SEER database from 2000 to 2020, and divided the patients into cohorts of whites, blacks, Asians or Pacific Islanders, American Indians/Alaska Natives according to their race. The prognosis and treatment of the cohorts were evaluated using baseline demographic analysis, Kamplan-Meier survival curve, and nomogram analysis. RESULTS: We analyzed the data of a total of 2058 patients, including 8.6% blacks, 72.4% whites, 16.6% Asians or Pacific Islanders, 1.0% American Indians/Alaska Natives, and 1.4% other races. The tumor grade varied among different races, and the prevalence and survival rates of patients differed significantly across races. The differences in the white cohort were the most prominent, and all the differences were statistically significant (P<0.05). Racial differences were also noted in patient management and prognosis. CONCLUSIONS There are racial differences in tumor grades and prognosis of gastric SRCC, and these differences provide evidence for optimizing clinical diagnosis and treatment strategies for this malignancy.
Aged ; Female ; Humans ; Male ; Middle Aged ; Carcinoma, Signet Ring Cell/therapy* ; Databases, Factual ; Prognosis ; Racial Groups ; SEER Program ; Stomach Neoplasms/therapy* ; Survival Rate ; United States/epidemiology* ; White ; Asian American Native Hawaiian and Pacific Islander ; American Indian or Alaska Native ; Black or African American

Identification of disease-specific cell subtypes (DSCSs) has profound implications for understanding disease mechanisms, preoperative diagnosis, and precision therapy. However, achieving unified annotation of DSCSs in heterogeneous single-cell datasets remains a challenge. In this study, we developed the gPRINT algorithm (generalized approach for cell subtype identification with single cell's voicePRINT). Inspired by the principles of speech recognition in noisy environments, gPRINT transforms gene position and gene expression information into voiceprints based on ordered and clustered gene expression phenomena, obtaining unique "gene print" patterns for each cell. Then, we integrated neural networks to mitigate the impact of background noise on cell identity label mapping. We demonstrated the reproducibility of gPRINT across different donors, single-cell sequencing platforms, and disease subtypes, and its utility for automatic cell subtype annotation across datasets. Moreover, gPRINT achieved higher annotation accuracy of 98.37% when externally validated based on the same tissue, surpassing other algorithms. Furthermore, this approach has been applied to fibrosis-associated diseases in multiple tissues throughout the body, as well as to the annotation of fibroblast subtypes in a single tissue, tendon, where fibrosis is prevalent. We successfully achieved automatic prediction of tendinopathy-specific cell subtypes, key targets, and related drugs. In summary, gPRINT provides an automated and unified approach for identifying DSCSs across datasets, facilitating the elucidation of specific cell subtypes under different disease states and providing a powerful tool for exploring therapeutic targets in diseases.
Humans ; Algorithms ; Single-Cell Analysis ; Databases, Genetic ; Molecular Sequence Annotation

This study aims to explore the medication rules and mechanisms of treating chronic renal failure(CRF) by Jinling medical school based on data mining, network pharmacology, and experimental validation systematically and deeply. Firstly, the study selected the papers published by the inherited clinicians in Jinling medical school in Chinese journals using the subject headings named "traditional Chinese medicine(TCM) + chronic renal failure", "TCM + chronic renal inefficiency", or "TCM + consumptive disease" in China National Knowledge Infrastructure, Wanfang, and VIP Chinese Science and Technology Periodical Database and screened TCM formulas for treating CRF according to inclusion and exclusion criteria. The study analyzed the frequency of use of single TCM and the four properties, five tastes, channel tropism, and efficacy of TCM used with high frequency and performed association rule and clustering analysis, respectively. As a result, a total of 215 TCM formulas and 235 different single TCM were screened, respectively. The TCM used with high frequency included Astragali Radix, Rhei Radix et Rhizoma, Salviae Miltiorrhizae Radix et Rhizoma, Poria, and Atractylodis Macrocephalae Rhizoma(top 5). The single TCM characterized by "cold properties, sweet flavor, and restoring spleen channel" and the TCM with the efficacy of tonifying deficiency had the highest frequency of use, respectively. Then, the TCM with the rules of "blood-activating and stasis-removing" and "diuretic and dampness-penetrating" appeared. In addition, the core combination of TCM [(Hexin Formula, HXF)] included "Astragali Radix, Rhei Radix et Rhizoma, Poria, Salviae Miltiorrhizae Radix, and Angelicae Sinensis Radix". The network pharmacology analysis showed that HXF had 91 active compounds and 250 corresponding protein targets including prostaglandin-endoperoxide synthase 2(PTGS2), PTGS1, sodium voltage-gated channel alpha subunit 5(SCN5A), cholinergic receptor muscarinic 1(CHRM1), and heat shock protein 90 alpha family class A member 1(HSP90AA1)(top 5). Gene Ontology(GO) function analysis revealed that the core targets of HXF predominantly affected biological processes, cellular components, and molecular functions such as positive regulation of transcription by ribonucleic acid polymerase Ⅱ and DNA template transcription, formation of cytosol, nucleus, and plasma membrane, and identical protein binding and enzyme binding. Kyoto Encyclopedia of Genes and Genomes(KEGG) analysis revealed that CRF-related genes were involved in a variety of signaling pathways and cellular metabolic pathways, primarily involving "phosphatidylinositol 3-kinase(PI3K)-protein kinase B(Akt) pathway" and "advanced glycation end products-receptor for advanced glycation end products". Molecular docking results showed that the active components in HXF such as isomucronulatol 7-O-glucoside, betulinic acid, sitosterol, and przewaquinone B might be crucial in the treatment of CRF. Finally, a modified rat model with renal failure induced by adenine was used, and the in vivo experimental confirmation was performed based on the above-mentioned predictions. The results verify that HXF can regulate mitochondrial autophagy in the kidneys and the PI3K-Akt-mammalian target of rapamycin(mTOR) signaling pathway activation at upstream, so as to alleviate renal tubulointerstitial fibrosis and then delay the progression of CRF.
Data Mining ; Drugs, Chinese Herbal/chemistry* ; Network Pharmacology ; Humans ; Kidney Failure, Chronic/metabolism* ; Medicine, Chinese Traditional ; China

This study explored the prescription pattern of traditional Chinese medicine(TCM) in the treatment of hypertensive left ventricular hypertrophy(LVH), so as to provide a relevant theoretical basis for the clinical diagnosis and treatment of hypertensive LVH. The study systematically searched the databases of CNKI, Wanfang, VIP, and SinoMed to screen out the qualified literature on TCM treatment of hypertensive LVH and used Microsoft Excel 2021 to establish the relevant prescription database. It also counted the frequency, property, flavor, and meridian affiliation of TCM in the prescriptions and classified their efficacy. The study used Lantern 5.0 and Rstudio software to analyze the hidden structural models and association rules of the high-frequency TCM with a frequency of >3.50% and adopted Origin 2024 software to visualize the data, so as to explore the prescription pattern of TCM in treating hypertensive LVH. The results showed that a total of 128 TCM prescriptions were included, involving 163 TCM with a total frequency of 1 242. The high-frequency TCM included Salviae Miltiorrhizae Radix et Rhizoma, Uncariae Ramulus Cum Uncis, Gastrodiae Rhizoma, Poria, and Chuanxiong Rhizoma, with the main efficacy from blood-activating and stasis-resolving herbs, tonic herbs, and liver-calming and wind-extinguishing herbs. The latent structure analysis(LSA) identified 10 latent variables, 20 latent classes, 7 comprehensive clustering models, and 23 core prescriptions. It was speculated that the common syndromes of hypertensive LVH included blood stasis obstructing the collaterals, ascending hyperactivity of liver Yang, Yin deficiency with Yang hyperactivity, and intermingled phlegm and blood stasis. The association rule analysis yielded 33 strong association rules, with the highest comprehensive association rule being Gastrodiae Rhizoma→Uncariae Ramulus Cum Uncis. Hypertensive LVH is characterized by asthenia in origin and asthenia in superficiality, with Yin deficiency and Qi deficiency as the origin and blood stasis and phlegm as the superficiality. Clinical treatment focuses on activating blood circulation, resolving stasis, tonifying Qi, and nourishing Yin, combined with syndrome-specific therapies such as calming wind and stopping convulsions, clearing heat, eliminating dampness and resolving phlegm, and promoting diuresis and reducing swelling.
Drugs, Chinese Herbal/therapeutic use* ; Data Mining ; Humans ; Hypertension/complications* ; Hypertrophy, Left Ventricular/physiopathology* ; Medicine, Chinese Traditional ; Drug Prescriptions

Medical cross-modal retrieval aims to achieve semantic similarity search between different modalities of medical cases, such as quickly locating relevant ultrasound images through ultrasound reports, or using ultrasound images to retrieve matching reports. However, existing medical cross-modal hash retrieval methods face significant challenges, including semantic and visual differences between modalities and the scalability issues of hash algorithms in handling large-scale data. To address these challenges, this paper proposes a Medical image Semantic Alignment Cross-modal Hashing based on Transformer (MSACH). The algorithm employed a segmented training strategy, combining modality feature extraction and hash function learning, effectively extracting low-dimensional features containing important semantic information. A Transformer encoder was used for cross-modal semantic learning. By introducing manifold similarity constraints, balance constraints, and a linear classification network constraint, the algorithm enhanced the discriminability of the hash codes. Experimental results demonstrated that the MSACH algorithm improved the mean average precision (MAP) by 11.8% and 12.8% on two datasets compared to traditional methods. The algorithm exhibits outstanding performance in enhancing retrieval accuracy and handling large-scale medical data, showing promising potential for practical applications.
Algorithms ; Semantics ; Humans ; Ultrasonography ; Information Storage and Retrieval/methods* ; Image Processing, Computer-Assisted/methods*

Online hashing methods are receiving increasing attention in cross modal medical image retrieval research. However, existing online methods often lack the learning ability to maintain semantic correlation between new and existing data. To this end, we proposed online semantic similarity cross-modal hashing (OSCMH) learning framework to incrementally learn compact binary hash codes of medical stream data. Within it, a sparse representation of existing data based on online anchor datasets was designed to avoid semantic forgetting of the data and adaptively update hash codes, which effectively maintained semantic correlation between existing and arriving data and reduced information loss as well as improved training efficiency. Besides, an online discrete optimization method was proposed to solve the binary optimization problem of hash code by incrementally updating hash function and optimizing hash code on medical stream data. Compared with existing online or offline hashing methods, the proposed algorithm achieved average retrieval accuracy improvements of 12.5% and 14.3% on two datasets, respectively, effectively enhancing the retrieval efficiency in the field of medical images.
Semantics ; Humans ; Algorithms ; Information Storage and Retrieval/methods* ; Diagnostic Imaging ; Image Processing, Computer-Assisted/methods*

Databases, Bibliographic ; Evidence-based Practice ; Health Services Needs And Demand

The rules of acupoint selection and treatment were identified and discovered from the collected ancient acupuncture-moxibustion prescriptions recorded the earliest for epigastric pain. The database of ancient acupuncture-moxibustion prescriptions for epigastric pain was set up using Excel2016 software. After the disease term, etiology, pathogenesis, symptoms and acupoints were normalized, the underlying multi-dimensional correlation among the elements of acupuncture-moxibustion was explored, using the frequency statistics and the association rule of Apriori algorithm. In the ancient time, in treatment with acupuncture-moxibustion therapy for epigastric pain, the acupoints of the high use frequency were sequenced as Zhongwan (CV12), Shangwan (CV13), Zusanli (ST36), Neiguan (PC6), Gongsun (SP4), Pishu (BL20) and Weishu (BL21). The common combinations of acupoints included the pairs of back-shu points, the combination of back-shu points and front-mu points, the combination of front-mu points and yuan-source points and the combination of back-shu points and the lower he-sea points. The highly involved acupoints were those from the conception vessel, pericardium meridian, spleen meridian, stomach meridian and bladder meridian; and they were commonly distributed on the abdomen, the yin parts of the foot and the arm, the yang part of the leg and on the back. Regarding the etiologies such as parasites, food retention, masses, qi stagnation and stomach cold, Zhongwan (CV12) and Shangwan (CV13) were coordinated; and Sanyinjiao (SP6) and Daling (PC7) were highly associated with masses. Besides cold injury, parasites and masses, for the epigastric pain caused by other factors of etiology (qi stagnation, stomach cold and food retention), moxibustion therapy was greatly applicable. For epigastric pain combined with qi reversion in the lower abdominal region, Qichong (ST30), Sanyinjiao (SP6), Tianshu (ST25) and Zusanli (ST36) must be selected. Dadu (SP2) and Taibai (SP3) must be used if the distention in the chest and abdomen accompanied; and Zhongzhu (TE3) be used if back pain involved. Zusanli (ST36) was commonly selected for hiccups. For the other accompanied symptoms, Zhongwan (CV12) was used, which is consistent with the acupoint selection of main symptoms. On the trunk, moxibustion was generally used at Weishu (BL21), Pishu (BL20), Geshu (BL17), Zhongwan (CV12), Juque (CV14) and Qihai (CV6), except Shangwan (CV13). Among the acupoints below the elbows and knees, moxibustion was commonly applicable at Zusanli (ST36), and acupuncture was often used at Gongsun (SP4) and Daling (PC7).
Acupuncture Points ; Humans ; Moxibustion/history* ; History, Ancient ; Acupuncture Therapy/history* ; Data Mining ; Abdominal Pain/history*

OBJECTIVE: To analyze the rules of moxibustion for low back pain by ZHOU Meisheng by using data mining and knowledge graph technology. METHODS: Taking the medical cases of moxibustion for low back pain from ZHOU Meisheng's legacy manuscripts and existing works as the research objects, information on disease types, symptoms, tongue manifestations, pulse conditions, syndrome patterns, moxibustion methods and acupoints were collected. Frequency statistics and community analysis were conducted by the ancient and modern medical record cloud platform V 2.3.7, cluster analysis of high-frequency acupoints was performed by SPSS26.0, association rule analysis of high-frequency acupoints was performed by SPSS Modeler 18.0, and the generated linked data were imported into Cytoscape 3.9.1 for complex network analysis. Knowledge graph of moxibustion for low back pain by ZHOU Meisheng was constructed based on the results of data mining. The data storage and display of knowledge graph were realized through the Neo4j 3.5.25 graph database, and the Cypher query language was used for knowledge graph retrieval and discovery. RESULTS: A total of 219 medical cases were collected, involving 14 disease types, 85 related clinical symptoms, 5 related TCM syndrome types, and 6 moxibustion methods. The acupoints were mostly attributed to the governor vessel, the bladder meridian of foot-taiyang, non-meridian and non-acupoint areas. The core prescription of acupoints derived from complex network analysis included tender points, Shenshu (BL23), Jinsuo (GV8), Yinjiao (CV7), Yaoyangguan (GV3), Yanglingquan (GB34), which were largely coincides with high-frequency acupoints. Cluster analysis obtained 4 cluster combinations. Community analysis yielded 6 communities, each corresponding to different acupoints.The constructed knowledge graph contained 187 nodes and 696 relationships, by retrieving clinical elements related to low back pain, the disease-moxibustion association graph, disease-acupoint association graph, accompanying symptom-acupoint association graph and syndrome type-matching point association graph were obtained. CONCLUSION When treating low back pain with moxibustion, ZHOU Meisheng adopts the principle of promoting circulation, distinguishing diseases to determine the treatment, selecting acupoints according to the diseases, and matching points according to the symptoms.And taking tender points, Shenshu (BL23), Jinsuo (GV8), Yinjiao (CV7), Yaoyangguan (GV3), Yanglingquan (GB34) as core acupoints, combined with tenderness point selection, acupoint selection based on meridian and zangfu syndrome differentiation, "sunshine area" acupoint selection, yin-yang acupoint matching. Additionally, he skillfully employs special points, such as Zhongzhu (KI15) and ear tips, pays attention to the reform of moxibustion tools, and innovates the moxibustion techniques, using distinctive moxibustion tools and methods to treat low back pain.
Moxibustion/methods* ; Humans ; Data Mining ; Low Back Pain/history* ; Acupuncture Points ; History, Ancient ; Female ; China ; Male ; Adult ; Middle Aged

OBJECTIVE: To explore the rules of acupoint selection and compatibility of acupuncture and moxibustion in treatment of chronic cough using data mining. METHODS: The ancient and modern medical record cloud platform, and the databases, i.e. CNKI, Wanfang, VIP, EMbase, Web of Science and PubMed, were searched to screen the ancient and modern literature on acupuncture and moxibustion treatment of chronic cough. The prescription database was established for acupuncture and moxibustion treatment of chronic cough, and the analysis conducted on the frequency and use percentage in the aspects of intervention measures, acupoint selection, acupoint distribution, meridian tropism, special points and acupoint combination, as well as the association rules and clustering rules of acupoint selection. The subgroup analysis was performed in accordance with the etiology of chronic cough and intervention measures. RESULTS: A total of 106 articles were included and 158 prescriptions were extracted. The intervention measures were acupuncture, moxibustion, herbal medication and the combination of several measures. The high-frequency acupoints included Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17), Shenshu (BL23), Lieque (LU7), Dingchuan (EX-B1), Tiantu (CV22), and Fenglong (ST40). These acupoints are mainly distributed on the back, lumbar region, chest and abdomen. The involved meridians were bladder meridian of foot-taiyang, conception vessel, and lung meridian of hand-taiyin. The special points covered back-shu points, crossing points and five-shu point. Regarding the compatibility of acupoints, the combination of upper and lower points, and the combination of front and back points were predominant in treatment. The analysis of association rules found that the support of Feishu (BL13)→Zusanli (ST36) was the highest; the cluster analysis obtained 8 clusters of acupoints. The acupoint compatibility and overall rules were similar when cough variant asthma (CVA) or the mixed reasons were involved, and the local treatment approach was adopted if the etiology of disease was related to upper airway cough syndrome (UACS) and gastroesophageal reflux cough (GERC). The acupoint selection was similar among different intervention measures. When two kinds of measures were combined in treatment, Feishu (BL13), Pishu (BL20) and Zusanli (ST36) were the most common. CONCLUSION In treatment with acupuncture and moxibustion for chronic cough, the acupoints are selected on the affected local area, depending on syndrome differentiation, and focusing on back-shu points. The main acupoints are Feishu (BL13), Zusanli (ST36), Dazhui (GV14), Pishu (BL20), Danzhong (CV17) and Shenshu (BL23). The combined therapy is dominant with acupuncture, moxibustion and herbal medicine involved.
Acupuncture Points ; Moxibustion/history* ; Humans ; Cough/history* ; Acupuncture Therapy/history* ; Chronic Disease/therapy* ; Data Mining ; History, Ancient ; Meridians ; Chronic Cough