OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

Transcriptional regulation based on transcription factors is an effective regulatory method widely used in microbial cell factories. Currently, few naturally transcriptional regulatory elements have been discovered from Saccharomyces cerevisiae and applied. Moreover, the discovered elements cannot meet the demand for specific metabolic regulation of exogenous compounds due to the high background expression or narrow dynamic ranges. There are abundant transcriptional regulatory elements in plants. However, the sequences and functions of most elements have not been fully characterized and optimized. Particularly, the applications of these elements in microbial cell factories are still in the infancy stage. In this study, natural regulatory elements from Medicago truncatula were selected, including the transcription factors MtTASR2 and MtTASR3, along with their associated promoter P_roHMGR1, for functional characterization and engineering modification. We constructed an inducible transcriptional regulation tool and applied it in the regulation of heterologous β-carotene synthesis in S. cerevisiae, which increased the β-carotene production by 7.31 folds compared with the original strain. This study demonstrates that plant-derived transcriptional regulatory elements can be used to regulate the expression of multiple genes in S. cerevisiae, providing new strategies and ideas for the specific regulation and application of these elements in microbial cell factories.
Medicago truncatula/metabolism* ; Saccharomyces cerevisiae/metabolism* ; Transcription Factors/genetics* ; beta Carotene/biosynthesis* ; Promoter Regions, Genetic/genetics* ; Gene Expression Regulation, Plant ; Metabolic Engineering/methods* ; Regulatory Elements, Transcriptional/genetics* ; Plant Proteins/genetics*

Objective:To compare the dosimetric differences between volumetric modulated arc therapy(VMAT)and helical tomotherapy(HT)in undergoing protective plan for pelvic bones of patients with cervical cancer.Methods:A total of 40 patients with cervical cancer,who underwent radiotherapy at the First Affiliated Hospital of Bengbu Medical University from January 2023 to February 2024,were selected for this study.The target volumes and organs at risk(OARs)were delineated after the information of computed tomography(CT)simulation images were acquired from each patient.The pelvic bone was alone delineated as OAR.Two kinds of bone marrow dose-limiting radiotherapy plans,coplanar dual-arc VMAT and HT,were respectively designed for each patient by using the treatment planning system(TPS)of radiotherapy.A statistical analysis was conducted to compare the dose parameters of target volume,conformity,homogeneity,OAR dose-volume,mean dose,and maximum dose of point between the two kinds of plans.Results:Both the VMAT and HT plans could meet the requirements of target volume and OARs for dose.For general OARs,the dose-volume percentage(V40 Gy)of V40 Gy at bladder,mean dose(Dmean),rectal V40 Gy,maximum dose(Dmax)at small intestine point of HT plan were respectively(38.97±2.29)%,(38.06±0.45)Gy,(61.50±2.51)%and(50.82±0.36)Gy.The differences of them between HT plan and VMAT plan were statistically significant(t=25.46,13.99,1.56,10.93,P<0.05).The V10 Gy,V20 Gy,V30 Gy and Dmean of VMAT plan were respectively(70.76±2.51)%,(60.84±3.29)%,(52.40±2.56)%and(32.02±4.33)Gy for pelvic bones,which were significantly lower than those of HT plan,and the differences of them between two kinds of plans were also statistically significant(t=-20.68,-13.23,-7.73,-10.26,P<0.05).Conclusion:The HT plan can provide the optimal dose distribution for target region in radiotherapy for patients with cervical cancer,which can better protect OAR nearby target region.VMAT plan has a significant advantage in low-dose regions of protecting pelvis.Thus,individualized treatment design should be conducted according to the conditions of each patient in clinical treatment.

AIM To evaluate the quality of Gegen Formula Granules.METHODS Linear calibration with two reference substances(LCTRS)was adopted in the predicting of retention time with puerarin and daidzein as internal standards.UPLC characteristic chromatograms were established.The contents of 3'-hydroxy puerarin,puerarin(internal standard),3'-methoxy puerarin,puerarin 6"-O-xyloside,puerarin apioside and daidzin were determined by quantitative determination analysis multi-components by a single marker(QAMS),after which their transfer rates were calculated.RESULTS Compared with relative retention time method,LCTRS demonstrated higher positional accuracy for characteristic peaks and wider application range for columns.There were 9 characteristic peaks in the characteristic chromatograms for 14 batches of formula granules and 15 batches of standard decoctions with the similarities of more than 0.95.The contents and transfer rates of various constituents in formula granules and standard decoctions were basically consistent.CONCLUSION The chemical constituents in formula granules and their standard decoctions of Puerariae lobatae Radix display good consistency,reliable preparation process is observable in the former.

As an indispensable"energy factory"within cells,mitochondria efficiently convert chemical energy from food into ATP through oxidative phosphorylation,providing continuous energy support for va-rious cellular life activities.The functional homeostasis of mitochondria maintains the cell's energy sup-ply,redox balance,cell signaling,and metabolic regulation,thereby ensuring normal cell operation and the healthy survival of organisms.Processes such as mitophagy,mitochondrial fusion and fission,mito-chondrial transport,reactive oxygen species accumulation,and calcium signaling are involved in maintai-ning mitochondrial functional homeostasis.The degeneration of dopaminergic neurons in the striatum is the main pathological feature of Parkinson's Disease(PD).Dopaminergic neurons have unique polarized and extended structures with high bioenergetic demands,making them particularly susceptible to mito-chondrial dysfunction.When mitochondrial function is impaired,the energy supply to dopaminergic neu-rons is insufficient,leading to neuronal dysfunction and subsequently triggering a series of neurodegenera-tive diseases,including PD.The molecular basis of PD pathogenesis often involves abnormalities in pro-teins that maintain mitochondrial homeostasis.These proteins play crucial roles in sustaining mitochondri-al function,and any functional abnormalities or genetic mutations can lead to mitochondrial dysfunction,thereby inducing PD.This article provides a comprehensive review of recently reported abnormalities in proteins maintaining mitochondrial function and their association with the onset and progression of PD.The aim is to gain a deeper understanding of the functions of these proteins,their genetic mutations,and their relationship with the disease,providing valuable insights for the development of effective treatments and diagnostic biomarkers for PD.

Objective To propose a novel identification algorithm based on ensemble learning for assessing the severity of acute respiratory distress syndrome(ARDS)to achieve continuous monitoring of the disease severity.Methods Firstly,leve-raging the open-source MIMIC-Ⅳ database,a variety of non-invasive physiological parameters of patients were extracted and subjected to preliminary preprocessing.A multivariate feature selection algorithm was employed to rank these parameters and calculate feature importance scores through weighted computation.Secondly,based on the feature importance scores,a subset search algorithm was utilized to identify the subset of features that could yield optimal performance across four machine learning algorithms:neural networks,logistic regression,AdaBoost and XGBoost.Finally,a soft voting ensemble method was designed using a generalized linear regression model to integrate the results of each single machine learning algorithm,and a multivariate ensemble learning algorithm was proposed by combining the optimal feature subsets.The algorithm proposed when used to identify the severity of ADRS was evaluated with MIMIC-Ⅳ database,and compared with the traditional algorithms.Results The sensitivity,specificity,accuracy and AUC of the algorithm were 87.15％,89.23％,88.34％and 0.923 4,respectively,all of which outperformed those of the traditional algorithms.Conclusion The ARDS severity identification algorithm based on ensemble learning is capable of achieving continuous and real-time monitoring of the severity of ARDS,thereby offering robust support for the early identification and warning of ARDS in patients.[Chinese Medical Equipment Journal,2025,46(2):1-9]

Objective : To investigate the protective effect of total glucosides of paeony ( TGP) on dexamethasone(DEX) ⁃induced liver injury in rats. Methods: Thirty SD rats were randomly divided into normal ( N) , DEX ,DEX + TGP (50 mg/kg) , DEX + TGP ( 100 mg/kg) , and DEX + TGP (200 mg/kg) groups , with 6 rats in each group. A rat model of liver injury was established by intraperitoneal injection of DEX ( 17. 5 mg/kg) . Serum levels of alanine aminotransferase ( ALT) , aspartate aminotransferase ( AST) , and alkaline phosphatase ( ALP) were measured , and the liver⁃to⁃body weight ratio was calculated. HE staining was performed to observe histopathological changes in the liver. The contents of malondialdehyde ( MDA) , superoxide dismutase ( SOD) , and glutathione (GSH) in liver tissues were determined. Western blot analysis was conducted to detect the expression levels of NADPH oxidase 4 ( NOX4 ) and endoplasmic reticulum stress⁃related proteins : glucose regulatory protein 94 homologous protein (CHOP) expression level in liver tissues. Results: Compared with the normal group , the DEX group exhibited significantly elevated serum levels of ALT , AST , ALP and liver⁃to⁃body weight ratio ( t = 14. 96 ,ing, degeneration , and necrosis ( t = 15. 49 , P < 0. 01) . Compared with the DEX group , there was no significant change in liver function biochemical indexes and liver histopathology in the TGP (50 mg/kg) treatment group. TGP treatment at 100 mg/kg and 200 mg/kg significantly attenuated these effects : both doses reduced ALT , AST , ALP and liver⁃to⁃body weight ratio( t = 3. 30 , 4. 13 , 7. 45 , 2. 97 , P < 0. 05 ; t = 8. 92 , 6. 45 , 8. 65 , 7. 47 , P < 0. 01) ,vealed that DEX administration significantly increased hepatic MDA levels ( t = 7. 06 , P < 0. 01) and NOX4 ex⁃pression ( t = 4. 23 , P < 0. 01) , whereas SOD activity ( t = 7. 78 , P < 0. 01) and GSH content ( t = 7. 92 , P <0. 01) were markedly suppressed. There was no significant change in the TGP (50 mg/kg) treatment group , TGP intervention at 100 mg/kg and 200 mg/kg effectively reversed these changes , lowering MDA and NOX4 levels( t = 3. 35 , 4. 30 , P < 0. 05 ; t = 5. 44 , 7. 44 , P < 0. 01) , while restoring SOD ( t200 mg/kg = 4. 04 , P < 0. 05) and GSH ( t = 4. 70 , P < 0. 05 ; t = 5. 50 , P < 0. 01) . Endoplasmic reticulum stress markers , including GRP94、GRP78、p- elF2α、CHOP ( t = 3. 31 , 6. 53 , 5. 18 , 3. 09 ; P < 0. 05 , 0. 01 , 0. 01 , 0. 05 ) , were significantly upregulated in the DEX group compared to the normal group. However, TGP treatment at 100 mg/kg and 200 mg/kg dose-dependent- ly suppressed the expression of GRP94、GRP78、p-elF2α、CHOP ( t = 3. 14 ,4. 95 , 3. 13 ,4. 25 , P < 0. 05 ; t = 4. 03 , 7. 48 ,4. 68 ,5. 10 ,P < 0. 01) expression levels were significantly reduced compared to the DEX group , and there was no significant change in the TGP (50 mg/kg) treatment group. Conclusion TGP exerts protective effects a- gainst DEX-induced liver injury , and its mechanism is likely mediated by suppressing hepatic oxidative stress and endoplasmic reticulum stress triggered by DEX in rats.

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

Microplastics are widely present in various environments such as water bodies,land,and atmosphere,which pose threats to the ecological environment and human health through transmission and accumulation in the food chain.The existing detection techniques for microplastics face challenges such as complex preparation procedure of samples,low efficiency in processing large batches of samples,and difficulties in handling complex samples.Therefore,there is an urgent need for rapid and efficient detection techniques suitable for complex microplastics samples in the field of environmental monitoring.Raman spectroscopy,known for its advantages such as rapidity,accuracy,high sensitivity,non-destructiveness,and non-contact,demonstrates great application potential in detection of microplastics.Deep learning,an artificial intelligence method known for its large-scale data processing,nonlinear modeling and automatic feature extraction capabilities,is receiving increasing attention in the analysis of Raman spectroscopy signals.The application of deep learning-based Raman spectroscopy has significantly improved performance indicators such as detection efficiency and accuracy.This article introduced the existing Raman enhancement techniques,summarized the deep learning methods applied in Raman spectroscopy signal analysis,reviewed the recent research and application progress of deep learning-based Raman spectroscopy in detection of microplastics,and finally discussed the challenges and future prospects of deep learning-based Raman spectroscopy in detection of microplastics.

Resveratrol(Res) is a kind of polyphenolic compound, possessing multiple biological activities such as antioxidant, anti-inflammatory, cardioprotective, and anticancer effects. In recent years, the cardiovascular protective mechanism of Res has become a research hotspot. Studies have shown that Res has a protective effect on the cardiovascular system through various pathways, such as inhibiting oxidative stress, regulating ferroptosis of cells, improving ischemia-reperfusion(I/R) injury, regulating lipid metabolism, suppressing inflammatory responses, and enhancing endothelial function. It can also alleviate cardiotoxicity caused by drugs and chemicals. In terms of oxidative stress, Res reduces the level of intracellular reactive oxygen species(ROS) by enhancing the expression of proteins such as silent information regulator 1(SIRT1) and regulating mitochondrial function, thereby alleviating myocardial cell damage. Regarding ferroptosis, Res inhibits the occurrence of ferroptosis by regulating the expression of proteins related to iron metabolism. Res can also improve I/R injury through mechanisms such as activating autophagy and the mitochondrial quality control network. In regard to improving endothelial function, Res protects the function of endothelial cells by regulating multiple signaling pathways, such as downregulating the PREP1-mediated pathway. Res can also regulate lipid metabolism and inhibit the progression of atherosclerosis. In terms of inflammatory responses, Res exerts anti-inflammatory effects through mechanisms such as inhibiting the nuclear factor-kappa B(NF-κB) signaling pathway. In addition, Res has an improving effect on cardiotoxicity caused by different drugs or environmental factors. However, the clinical application of Res still faces limitations such as poor pharmacokinetic properties. In the future, in-depth exploration is needed at multiple levels from basic research to clinical application to clarify the dose-response relationship and standardize the standards of medication regimens with the expectation of providing more effective strategies for the prevention and treatment of cardiovascular diseases.
Humans ; Resveratrol/pharmacology* ; Animals ; Cardiotonic Agents/pharmacology* ; Oxidative Stress/drug effects* ; Cardiovascular Diseases/genetics* ; Cardiovascular System/metabolism* ; Signal Transduction/drug effects*