Ferroptosis-Enhanced Cancer Immunity by a Ferrocene-Appended Iridium(III) Diphosphine Complex.

Ferroptosis is a programmed cell death pathway discovered in recent years, and ferroptosis-inducing agents have great potential as new antitumor candidates. Here, we report a IrIII complex (Ir1) containing a ferrocene-modified diphosphine ligand that localizes in lysosomes. Under the acidic environments of lysosomes, Ir1 can effectively catalyze Fenton-like reaction, produce hydroxyl radicals, induce lipid peroxidation, down-regulate glutathione peroxidase 4, and result in ferroptosis. RNA sequencing analysis shows that Ir1 can significantly affect pathways related to ferroptosis and cancer immunity. Accordingly, Ir1 can induce immunogenic cells death and suppress tumor growth in vitro, regulate T cell activity and immune microenvironments in vivo. In conclusion, we show the potential of small molecules with ferroptosis-inducing capabilities for effective cancer immunotherapy.

Serum metabonomic study of the effects of Huofeitong tablet on rats with COPD.

Chronic obstructive pulmonary disease (COPD) is a common respiratory disease. The Huofeitong tablet (HFTT), a Chinese compound medicine, exhibits an unambiguous therapeutic effect on COPD. However, the mechanism of its therapeutic effect on COPD is unclear. This study aimed to investigate the effect of HFTT on COPD and its mechanism. The changes in pulmonary function and the inflammatory factors in rats were determined via histopathology and bronchoalveolar lavage fluid. The mechanism of HFTT in COPD treatment was revealed using UPLC-Q-TOF-MS/MS and multivariate statistical analysis. Results showed that after HFTT treatment, the lung function began to recover, the lung tissue improved, and the TNF-α and IL-6 levels decreased, suggesting that HFTT had a therapeutic effect on COPD. In addition, 12 potential biomarkers, including malonate, urea-1-carboxylate, pyruvate, l-cysteate, glutathione, 2-deoxy-α-d-ribose1-phosphate, 3-fumarylpyruvate, 3-maleylpyruvate, 2-inosose, urate, allantoin, and inosine were screened. They associated with COPD development and concentrated in glutathione metabolism, glyoxylate and dicarboxylate metabolism, secondly concentrated in pyruvate metabolism, glycolysis/gluconeogenesis, pentose phosphate pathway, citrate cycle, glycine, serine and threonine metabolism, inositol phosphate, and purine metabolism. This study contributes to the development and application of HFTT in COPD treatment and provides a theoretical basis for COPD diagnosis, prevention, and treatment.

Circular RNA circ_0032821 contributes to oxaliplatin (OXA) resistance of gastric cancer cells by regulating SOX9 via miR-515-5p.

OBJECTIVES: Chemoresistance is one of the major obstacles for gastric cancer (GC) treatment. Exosome-mediated transfer of circular RNAs (circRNAs) is associated with the drug-resistance in GC. Circ_0032821 has been reported as an oncogene in GC. This study is designed to explore the function and mechanism of Exosomal circ_0032821 in oxaliplatin (OXA) resistance of GC. RESULTS: Circ_0032821 was highly expressed in OXA-resistant GC cells, and exosomes secreted by OXA-resistant GC cells. Moreover, circ_0032821-containing exosomes secreted by OXA-resistant GC cells could boost OXA resistance, proliferation, migration, and invasion in OXA-sensitive GC cells. The mechanical analysis discovered that circ_0032821 acted as a sponge of miR-515-5p to regulate SOX9 expression. Circ_0032821 silencing and OXA treatment repressed tumor growth in the GC mice model. CONCLUSIONS: Exosomal circ_0032821 boosted OXA resistance of GC cells partly by the miR-515-5p/SOX9 axis, hinting a promising therapeutic target for GC treatment.

Cardioprotective effects of timosaponin B-II isolated from Anemarrhena rhizome in a zebrafish model.

Timosaponin B-II (TB-II; (25S)-26-(ß-D-glucopyranosyloxy)-3ß-[(2-O-ß-D-glucopyranosyl-ß-D-galactopyranosyl) oxy]-5ß-furostan-22-ol is extracted from Anemarrhena. Its anti-inflammation, anti-oxidation, and anti-asthma properties have been widely explored. However, its effect on the heart has not been reported. In this study, we used zebrafish as a research model to determine the effects of TB-II on the heart and its toxic and anti-inflammatory effects. To explore the cause of cardioprotective effects of TB-II, we used transgenic zebrafish with macrophages and neutrophils labeled with fluorescent protein. We found for the first time that TB-II had a protective effect on the zebrafish heart. It did not affect the survival and hatching rates of zebrafish embryos, indicating its low toxicity. Results showed that TB-II may have cardioprotective effects, which might be related to its anti-inflammatory effects.

Metabolomic profiling of rat urine after oral administration of the prescription antipyretic Hao Jia Xu Re Qing Granules by UPLC/Q-TOF-MS.

Hao Jia Xu Re Qing Granules (HJ), is an effective clinically used antipyretic based on traditional Chinese medicine. Although its antipyretic therapeutic effectiveness is obvious, its therapeutic mechanism has not been comprehensively explored yet. In this research, we first identified potential biomarkers which may be relevant for the antipyretic effect of HJ based on urine metabolomics using ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS). A rat model of fever was established using the yeast-induced febrile response. Total-ion-current metabolic profiles of different groups were acquired and the data were processed by multivariate statistical analysis-partial least-squares discriminant analysis. As envisioned, the results revealed changes of urine metabolites related to the antipyretic effect. Fourteen potential biomarkers were selected from the urine samples based on the results of Student's t-test, "shrinkage t", variable importance in projection and partial least-squares discriminant analysis. N-Acetylleucine, kynurenic acid, indole-3-ethanol, nicotinuric acid, pantothenic acid and tryptophan were the most significant biomarkers found in the urine samples, and may be crucially related to the antipyretic effect of HJ. Consequently, we propose the hypothesis that the significant antipyretic effect the HJ may be related to the inhibition of tryptophan metabolism. This research thus provides strong theoretical support and further direction to explain the antipyretic mechanism of HJ, laying the foundation for future studies.

Metabolomics approach based on ultra-high-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry to identify the chemical constituents of the Traditional Chinese Er-Zhi-Pill.

Er-Zhi-Pill, which consists of Ligustri lucidi fructus and Ecliptae prostratae herba, is a classical traditional Chinese medicinal formulation widely used as a liver-nourishing and kidney-enriching tonic. To identify the bioactive ingredients of Er-Zhi-Pill and characterize the variation of chemical constituents between co-decoction and mix of individually decocted L. lucidi fructus and E. prostratae herba, a novel metabolomics approach based on ultra high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry in both positive and negative ion modes, was established to comprehensively analyze chemical constituents and probe distinguishable chemical markers. In total, 68 constituents were unambiguously or tentatively identified through alignment of accurate molecular weights within an error margin of 5 ppm, elemental composition and fragmentation characteristics, including eight constituents, which were confirmed by comparing to reference standards. Furthermore, principal component analysis and partial least squares discriminant analysis using Simca-p+ 12.0 software were applied to investigate chemical differences between formulations obtained by co-decoction and a mixture of individual decoctions. Global chemical differences were found in samples of two different decoction methods, and 16 components, including salidroside, specneuzhenide and wedelolactone, contributed most to the observed differences. This study provides a basic chemical profile for the quality control and further mechanism research of Er-Zhi-Pill.

Effects of dietary supplementation with green tea waste on growth, digestive enzyme and lipid metabolism of juvenile hybrid tilapia, Oreochromis niloticus × O. aureus.

An 8-week feeding trial was conducted to evaluate the effects of dietary supplementation with green tea waste (GTW) on growth, digestive enzyme and lipid metabolism of juvenile hybrid tilapia, Oreochromis niloticus × O. aureus. The fish (initial mean body weight, 12.63 ± 0.75 g) were fed five experimental diets that included 0 (control), 0.8, 1.6, 3.2 or 6.4 % of GTW in triplicate aquaria, twice daily. Growth performance, plasma metabolites content and liver and intestine digestive enzyme activities were determined. Fish accepted well all experimental diets during the trial, and no mortality was observed. The weight gain increased (P < 0.05) with the increase in GTW inclusion level up to 1.6 %, after which it decreased, but no significant differences between the control and high level (3.2 or 6.4 % of GTW) groups were observed. Moreover, fish fed on diets containing 0.8 and 1.6 % GTW had lower feed conversion ratio (FCR, 1.75 and 1.73, respectively) and had better protein deposition (higher protein efficiency ratio, PER, 1.73 and 1.71, respectively), compared to other treatments. No differences among groups were observed in whole body and dorsal muscle composition with the exception of lipid content which was lower in fish fed 6.4 % GTW diets, compared to other treatments. Lipase activities in liver or intestine were higher in fish fed GTW-supplemented diets with the exception of intestine lipase activities, which was unaffected, compared to the control. Similarly, liver lipoprotein lipase activities were also increased in fish fed diets supplemented a medium dose of GTW (1.6 or 3.2 %), compared to other treatments. However, intestine amylase activities were decreased in fish fed diets containing a high dose of GTW (3.2 and 6.4 %); while the liver amylase activities were unaffected by the GTW supplementation. Blood chemistry parameters were affected by GTW inclusion, except the values of triglycerides, which was unaffected. The values of total cholesterol, HDL cholesterol and LDL cholesterol increased with increasing GTW inclusion level up to 3.2 %, after which the values decreased. These results indicate that diets supplemented with appropriate concentration of GTW (from 0.8 to 1.6 %) may potentially serve as an effective functional food and additive for tilapia to improve growth performance, digestion efficacy and fat metabolism.

TGF ß1 mediates epithelial mesenchymal transition via ß6 integrin signaling pathway in breast cancer.

BACKGROUND: To understand the function of ß6 integrin and elucidate its signaling pathways in TGF-ß-induced EMT in breast cancer. METHODS: The interactions between TGF-ß1 and ß6 integrin were measured by coimmunoprecipitation. The EMT responses, phospherlation of PI3K/Akt and COX-2 expression were determined by real-time PCR, transwell assay, and western blot after the blockage of ß6 integrin. RESULTS: TGF-ß1 and ß6 integrin could bind with each other. Blockage of ß6 integrin rescued TGF-ß1-induced EMT phenotype and reduced expression of COX-2 via dephosphorylation of PI3K/Akt. CONCLUSIONS: ß6 integrin plays a critical role in TGF-ß1-induced EMT and overexpression of COX-2 in breast cancer.

Rapid identification of glycerophospholipids from RAW264.7 cells by UPLC/ESI -QTOF-MS.

The study aims to develop a rapid, sensitive ultra-performance liquid chromatography coupled with an electrospray ionization quadruple time-of-flight tandem mass spectrometry (UPLC/Q-TOF-MS) analytical method for identifying glycerophospholipids (GPLs) from RAW264.7 cells. A total of 78 GPLs including 22 phosphatidylethanolamines (PEs), 49 phosphatidylcholines (PCs), four phosphatidylglycerols, one phosphatidylinositol and two unknown GPLs were identified. PC (14:0/16:1), PC (14:0/16:0), PE (0:0/20:3), PE (22:5/0:0) and PE (22:3/0:0) were identified for the first time. The UPLC/Q-TOF-MS method is suitable for targeting analysis of GPLs from RAW264.7 cells, which allows us to find out new GPLs compositions related to inflammatory diseases and to explain their pharmacological roles in inflammatory process.

Lipidomics based on UHPLC/Q-TOF-MS to characterize lipid metabolic profiling in patients with newly diagnosed type 2 diabetes mellitus with dyslipidemia.

Dyslipidemia often accompanies type 2 diabetes mellitus (T2DM). Elevated blood glucose in patients commonly leads to high levels of lipids. Lipid molecules can play a crucial role in early detection, treatment, and prognosis of T2DM with dyslipidemia. Previous lipid studies on T2DM mainly focused on Western diabetic populations with elevated blood glucose. In this research, we investigate both high blood sugar and high lipid levels to better understand changes in plasma lipid metabolism in newly diagnosed Chinese T2DM patients with dyslipidemia (NDDD). We used a plasma lipid analysis method based on ultra-high performance liquid chromatography coupled with mass spectrometry technology (UHPLC-MS) and statistical analysis to characterize lipid profiles and identify potential biomarkers in NDDD patients compared to healthy control (HC) subjects. Additionally, we examined the differences in lipid profiles between hyperlipidemia (HL) patients and HC subjects. We found significant changes in 15 and 23 lipid molecules, including lysophosphatidylcholine (LysoPC), phosphatidylcholine (PC), phosphatidylethanolamine (PE), sphingomyelin (SM), and ceramide (Cer), in the NDDD and HL groups compared to the HC group. These altered lipid molecules are associated with five metabolic pathways, with sphingolipid metabolism and glycerophospholipid metabolism being the most relevant to glucose and lipid metabolism changes. These lipid biomarkers are strongly correlated with traditional markers of glucose and lipid metabolism. Notably, Cer(d18:1/24:0), SM(d18:1/24:0), SM(d18:1/16:1), SM(d18:1/24:1), and SM(d18:2/24:1) were identified as essential potential biomarkers closely linked to clinical parameters through synthetic analysis of receiver operating characteristic curves, random forest analysis, and Pearson matrix correlation. These lipid biomarkers can enhance the risk prediction for the development of T2DM in individuals with dyslipidemia but no clinical signs of high blood sugar. Furthermore, they offer insights into the pathological mechanisms of T2DM with dyslipidemia.

Provenance, diagenesis, and depositional environment of Miocene Kamlial Formation, Azad Jammu and Kashmir, Sub Himalayas, Pakistan: Evidences from field observations and petrography.

Petrographical characterization and field observations were caried out to evaluate Kamlial Formation in Bagh district, Azad Jammu and Kashmir. Based on detailed petrography, the lithic arenite consisted of quartz (20-25%), feldspar (7-11%), rock fragments (20-37%), cementing materials (11-21%), and accessory minerals. Grains are mostly angular to subrounded and poorly to moderately sorted. The analysis revealed that the lithic arenite is mineralogically immature; also, the current activity during the time of deposition was low. Polycrystalline quartz indicates that the sandstone was derived from metamorphic source, while monocrystalline quartz indicates a granitic origin. Quartz having an angular shape suggests the source rock was near the depositional site, while quartz having a rounded shape represents long transportation. The presence of feldspar in the lithic arenite suggests the rocks were deposited at high relief or cold temperatures. Primary porosity in sandstone was reduced by calcite cements around the grain, while secondary porosity was developed by fracturing of quartz and feldspar. Tectonic uplift in the study area was demonstrated by fractured quartz and mica in thin sections. Field observations of various sedimentary structures were observed such as load casts, ripple marks, and mud cracks, etc. The presence of conglomerates and load casts in the study area indicates that the Kamlial sandstone was deposited by fluvial and shallow marine environment. Furthermore, the ripple marks indicate that the tidal flat environment controlled the deposition of the sediments.

Anemarrhena asphodeloides Bunge total saponins ameliorate diabetic cardiomyopathy by modifying the PI3K/AKT/HIF-1α pathway to restore glycolytic metabolism.

ETHNOPHARMACOLOGICAL RELEVANCE: Based on the theory of traditional Chinese medicine (TCM), diabetic cardiomyopathy (DCM) belongs to the category of "Xiaoke disease" according to the symptoms, and "stasis-heat" is the main pathogenesis of DCM. The Chinese medicine Anemarrhena asphodeloides Bunge (AAB), as a representative of heat-clearing and engendering fluid, is often used clinically in the treatment of DCM. Anemarrhena asphodeloides Bunge total saponins (RATS) are the main bioactive components of AAB, the modern pharmacologic effects of RATS are anti-inflammatory, hypoglycemic, and cardioprotective. However, the potential protective mechanisms of RATS against DCM remain largely undiscovered. AIM OF THE STUDY: The primary goal of this study was to explore the effect of RATS on DCM and its mechanism of action. MATERIALS AND METHODS: Streptozotocin and a high-fat diet were used to induce DCM in rats. UHPLC/Q-TOF-MS was used to determine the chemical components of RATS. The degenerative alterations and apoptotic cells in the heart were assessed by HE staining and TUNEL. Network pharmacology was used to anticipate the probable targets and important pathways of RATS. The alterations in metabolites and main metabolic pathways in heart tissue were discovered using 1 H-NMR metabolomics. Ultimately, immunohistochemistry was used to find critical pathway protein expression. RESULTS: First of all, UHPLC/Q-TOF-MS analysis showed that RATS contained 11 active ingredients. In animal experiments, we found that RATS lowered blood glucose and lipid levels in DCM rats, and alleviated cardiac pathological damage, and decreased cardiomyocyte apoptosis. Furthermore, the study found that RATS effectively reduced inflammatory factor release and the level of oxidative stress. Mechanistically, RATS downregulated the expression levels of PI3K, AKT, HIF-1α, LDHA, and GLUT4 proteins. Additionally, glycolysis was discovered to be a crucial pathway for RATS in the therapy of DCM. CONCLUSIONS: Our findings suggest that the protective effect of RATS on DCM may be attributed to the inhibition of the PI3K/AKT/HIF-1α pathway and the correction of glycolytic metabolism.

[Rapid identification and preliminary study of fragmentation regularity of saponins components of ginseng].

OBJECTIVE: To study a method for rapidly identifying the saponions components in Ginseng and explore the fragmentation regularity. METHODS: Used ACQUITY UPLC/Q-TOF micro system gradient elute wirh 10 mmol/L ammonium acetate-acetonitrile mobile phase under the ESI negative mode; Data were analyzed by Masslynx 4.1 software. RESULTS: 30 kinds of saponins in Ginseng were analyzed and identified by UPLC/Q-TOF-MS, and the fragmentation regularity of ginseng saponins components were explored. CONCLUSION: A analysis method is established for rapid identification of saponin components.

Study on identification algorithm of traditional Chinese medicinals microscopic image based on convolutional neural network.

When the similarity of medicinal materials is high and easily confused, the traditional subjective judgment has an impact on the identification results. Use high-dimensional features to identify medicinal materials to ensure the quality of Chinese herbal concoction products and proprietary Chinese medicines. OBJECTIVE: To study the identification algorithm of traditional Chinese medicinals (TCM) microscopic images based on convolutional neural network (CNN) to improve the objectivity and accuracy of microscopic image identification of TCM powders. METHODS: Microscopic image datasets of 4 TCM powders sclereids of Rhizoma Coptidis, Cortex Magnoliae Officinalis, Cortex Phellodendri Chinensis, and Cortex Cinnamomi were constructed, and 400 collected images, as the model training and testing objects, were identified and classified by AlexNet model, VGGNet-16, VGGNet-19, and GoogLeNet model. RESULTS: The average recognition accuracy in the tested microscopic image of AlexNet model, VGGNet-16, VGGNet-19, and the GoogLeNet model is 93.50%, 95.75%, 95.75%, and 97.50% correspondingly. CONCLUSION: The GoogLeNet model has a higher classification accuracy and is the best model to achieve real-time. Applying the CNN to the identification of microscopic images of TCM powders makes the operation of TCM identification simpler and the measurement more accurate while improving repeatability.

Lipidomics of the erythrocyte membrane and network pharmacology to explore the mechanism of mangiferin from Anemarrhenae rhizoma in treating type 2 diabetes mellitus rats.

Mangiferin, a natural C-glucoside xanthone, is one of the major bioactive ingredients derived from the dry rhizome of Anemarrhenae rhizome, which has been reported to exhibit various pharmacological effects, including anti-oxidant, anti-inflammatory, anti-fatty liver, anti-metabolic syndrome, and anti-diabetic. However, the precise molecular mechanisms underlying its impact on phospholipid metabolism in the erythrocyte membrane of type 2 diabetes mellitus (T2DM) remain unclear. The present research aimed to evaluate the effects of mangiferin on glucose and lipid metabolism in T2DM model rats and discuss the relationship between lipid metabolites and potential targets involved in the hypoglycemic effects by integrating lipidomics and network pharmacology method. After 8 consecutive weeks of treatment with mangiferin, the T2DM model rats exhibited significant improvements in several biochemical indices and cytokines, including fasting blood glucose (FBG) levels after 12 h of fasting, fasting insulin level (FINS), total cholesterol (T-CHO), triacylglycerols (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), homeostasis model assessment of insulin resistance (HMOA-IR), TNF-α and IL-6. A total of 22 differential lipid metabolites were selected from erythrocyte membrane phospholipids, which were closely associated with the processes of T2DM. These metabolites mainly belonged to glycerophospholipid metabolism and sphingolipid metabolism. Based on network pharmacology analysis, 22 genes were recognized as the potential targets of mangiferin against diabetes. Moreover, molecular docking analysis revealed that the targets of TNF, CASP3, PTGS2, MMP9, RELA, PLA2G2A, PPARA, and NOS3 could be involved in the modulation of inflammatory signaling pathways and arachidonic acid (AA) metabolism to improve IR and hyperglycemia. The combination of immunohistochemical staining and PCR showed that mangiferin could treat T2DM by regulating the expression of PPARγ protein and NF-κB mRNA expression to impact glycerophospholipids (GPs) and AA metabolism. The present study showed that mangiferin might alleviate IR and hyperglycemia of T2DM model rats via multiple targets and multiple pathways to adjust their phospholipid metabolism, which may be the underlying mechanism for mangiferin in the treatment of T2DM.

[Spatiotemporal Evolution Characteristics of PM2.5-O3 Compound Pollution in Chinese Cities from 2015 to 2020].

Based on the monitoring data of PM2.5 and O3 concentrations in 333 cities in China from 2015 to 2020, using spatial clustering, trend analysis, and the geographical gravity model, this study quantitatively analyzed the characteristics of PM2.5-O3 compound pollution concentrations and its spatiotemporal dynamic evolution pattern in major cities in China. The results showed that:① there was a synergistic change in PM2.5 and O3 concentrations. When ρ(PM2.5_mean) ≤ 85 µg·m-3, for every 10 µg·m-3 increase in ρ(PM2.5_mean), the peak of the mean value of ρ(O3_perc90) increased by 9.98 µg·m-3. When ρ(PM2.5_mean) exceeded the national Grade II standards of (35±10) µg·m-3, the peak of the mean value of ρ(O3_perc90) increased the fastest, with an average growth rate of 11.81%. In the past six years, on average, 74.97% of Chinese cities with compound pollution had a ρ(PM2.5_mean) in the range of 45 to 85 µg·m-3. When ρ(PM2.5_mean)>85 µg·m-3, the mean value of ρ(O3_perc90) showed a significant decreased trend. ② The spatial clustering pattern of PM2.5 and O3 concentrations in Chinese cities was similar, and hot spots of the six-year mean values of ρ(PM2.5_mean) and ρ(O3_perc90) were distributed in the Beijing-Tianjin-Hebei urban agglomeration and other cities in the Shanxi, Henan, and Anhui provinces. ③ The number of cities with PM2.5-O3 compound pollution showed an interannual variation trend of increasing first (2015-2018) and then decreasing (2018-2020) and a seasonal trend of gradually decreasing from spring to winter. Further, the compound pollution phenomenon mainly occurred in the warm season (April to October). ④ The spatial distribution of PM2.5-O3 compound polluted cities was changing from dispersion to aggregation. From 2015 to 2017, the compound polluted areas spread from the eastern coastal areas to the central and western regions of China, and by 2017, a large-scale polluted area centered on the Beijing-Tianjin-Hebei urban agglomeration, the Central Plains urban agglomeration, and surrounding areas was formed. ⑤ The migration directions of PM2.5 and O3 concentration centers were similar, and there were obvious trends of moving westward and northward. The problem of high-concentration compound pollution was concentrated and highlighted in cities in central and northern China. In addition, since 2017, the distance between the centers of gravity of PM2.5 and O3 concentrations in the compound polluted areas had been significantly reduced, with a reduction of nearly 50%.

Publication Trends in Rehabilitative Effects of Acupuncture: A Visual Analysis of the Literature.

Objectives: To conduct a comprehensive analysis of scientific outputs in 2011-2021 regarding the rehabilitative effects of acupuncture on diseases. Methods: The study was conducted in the form of knowledge graph and data visualization, with data being drawn from the Web of Science Core Collection database. Results: Articles and reviews were the dominant types; China, Guangzhou University of Chinese Medicine and Medicine ranked was the active country, institution, and journal, respectively, in terms of issued articles. Systematic reviews and the meta-analyses of stroke and pain were extensively carried out in the past decade, whose principal interventions were manual acupuncture, electroacupuncture, scalp acupuncture, and dry needling correspondingly at Baihui (DU20) and Zusanli (ST36). And most frequently utilized rehabilitation assessment criteria were the Fugl-Meyer Assessment Scale and the Barthel Index. More recently, motor function and chronic obstructive pulmonary disease have captured researchers' attention, which might be the futuristic frontier. Conclusions: This article provided a relatively panoramic picture of the scientific outputs in acupuncture for disease rehabilitation, which may help readers embrace the heated topic and grasp the recent research focus on this field.

A Traditional Chinese Medicine Syndrome Classification Model Based on Cross-Feature Generation by Convolution Neural Network: Model Development and Validation.

BACKGROUND: Nowadays, intelligent medicine is gaining widespread attention, and great progress has been made in Western medicine with the help of artificial intelligence to assist in decision making. Compared with Western medicine, traditional Chinese medicine (TCM) involves selecting the specific treatment method, prescription, and medication based on the dialectical results of each patient's symptoms. For this reason, the development of a TCM-assisted decision-making system has lagged. Treatment based on syndrome differentiation is the core of TCM treatment; TCM doctors can dialectically classify diseases according to patients' symptoms and optimize treatment in time. Therefore, the essence of a TCM-assisted decision-making system is a TCM intelligent, dialectical algorithm. Symptoms stored in electronic medical records are mostly associated with patients' diseases; however, symptoms of TCM are mostly subjectively identified. In general electronic medical records, there are many missing values. TCM medical records, in which symptoms tend to cause high-dimensional sparse data, reduce algorithm accuracy. OBJECTIVE: This study aims to construct an algorithm model compatible for the multidimensional, highly sparse, and multiclassification task of TCM syndrome differentiation, so that it can be effectively applied to the intelligent dialectic of different diseases. METHODS: The relevant terms in electronic medical records were standardized with respect to symptoms and evidence-based criteria of TCM. We structuralized case data based on the classification of different symptoms and physical signs according to the 4 diagnostic examinations in TCM diagnosis. A novel cross-feature generation by convolution neural network model performed evidence-based recommendations based on the input embedded, structured medical record data. RESULTS: The data set included 5273 real dysmenorrhea cases from the Sichuan TCM big data management platform and the Chinese literature database, which were embedded into 60 fields after being structured and standardized. The training set and test set were randomly constructed in a ratio of 3:1. For the classification of different syndrome types, compared with 6 traditional, intelligent dialectical models and 3 click-through-rate models, the new model showed a good generalization ability and good classification effect. The comprehensive accuracy rate reached 96.21%. CONCLUSIONS: The main contribution of this study is the construction of a new intelligent dialectical model combining the characteristics of TCM by treating intelligent dialectics as a high-dimensional sparse vector classification task. Owing to the standardization of the input symptoms, all the common symptoms of TCM are covered, and the model can differentiate the symptoms with a variety of missing values. Therefore, with the continuous improvement of disease data sets, this model has the potential to be applied to the dialectical classification of different diseases in TCM.

RAFF-Net: An improved tongue segmentation algorithm based on residual attention network and multiscale feature fusion.

Objective: Due to the complexity of face images, tongue segmentation is susceptible to interference from uneven tongue texture, lips and face, resulting in traditional methods failing to segment the tongue accurately. To address this problem, RAFF-Net, an automatic tongue region segmentation network based on residual attention network and multiscale feature fusion, was proposed. It aims to improve tongue segmentation accuracy and achieve end-to-end automated segmentation. Methods: Based on the UNet backbone network, different numbers of ResBlocks combined with the Squeeze-and-Excitation (SE) block was used as an encoder to extract image layered features. The decoder structure of UNet was simplified and the number of parameters of the network model was reduced. Meanwhile, the multiscale feature fusion module was designed to optimize the network parameters by combining a custom loss function instead of the common cross-entropy loss function to further improve the detection accuracy. Results: The RAFF-Net network structure achieved Mean Intersection over Union (MIoU) and F1-score of 97.85% and 97.73%, respectively, which improved 0.56% and 0.46%, respectively, compared with the original UNet; ablation experiments demonstrated that the improved algorithm could contribute to the enhancement of tongue segmentation effect. Conclusion: This study combined the residual attention network with multiscale feature fusion to effectively improve the segmentation accuracy of the tongue region, and optimized the input and output of the UNet network using different numbers of ResBlocks, SE block, multiscale feature fusion and weighted loss function, increased the stability of the network and improved the overall effect of the network.

Effect and Mechanism of Exogenous Melatonin on Cognitive Deficits in Animal Models of Alzheimer's Disease: A Systematic Review and Meta-analysis.

Melatonin (MT) has been reported to control and prevent Alzheimer's disease (AD) in the clinic; however, the effect and mechanism of MT on AD have not been specifically described. Therefore, the main purpose of this meta-analysis was to explore the effect and mechanism of MT on AD models by studying behavioural indicators and pathological features. Seven databases were searched and 583 articles were retrieved. Finally, nine studies (13 analyses, 294 animals) were included according to pre-set criteria. Three authors independently judged the selected literature and the methodological quality. Meta-analysis showed that MT markedly ameliorated the learning ability by reducing the escape latency, and the memory deficit was significantly corrected by increasing the dwell time in the target quadrant and crossings over the platform location in the Morris Water Maze (MWM). Among the pathological features, subgroup analysis found that MT may ease the symptoms of AD mainly by reducing the deposition of Aß40 and Aß42 in the cortex. In addition, MT exerted a superior effect on ameliorating the learning ability of senescence-related and metabolic AD models, and corrected the memory deficit of the toxin-induced AD model. The study was registered at PROSPERO (CRD42021226594).