Hemoglobin (Hb) concentration is a key clinical biomarker for diagnosing and managing anemia, ischemic stroke, perioperative blood loss, and chronic diseases such as renal failure. Traditional venous blood sampling remains the gold standard due to its high accuracy, but its invasive nature limits frequent testing, real time monitoring, and large scale screening. This has driven growing interest in non-invasive Hb detection technologies over the past decade. Among these, optical methods are the most promising because of their safety, potential for continuous monitoring, and compatibility with portable or wearable devices. This paper systematically reviews major advances in optical non invasive Hb detection from the last ten years. We focus on near-infrared spectroscopy branches—photoplethysmography (PPG) and dynamic spectrum (DS)—and also cover color analysis/RGB imaging, Raman spectroscopy, and photoacoustic spectroscopy. For each technology, we explain its detection principles, analyze advantages and limitations, and summarize optimization strategies reported in recent literature. PPG, based on pulsatile blood volume changes, underpins many commercial continuous monitors. However, its accuracy is constrained by motion artifacts, individual physiological variations (e.g., skin tone, tissue thickness), and low AC signal to noise ratio. In contrast, DS—an advanced derivative of PPG—uses a differential principle to extract absorbance changes between systolic and diastolic peaks. This theoretically eliminates interference from static tissues (skin, bone, venous blood) and common mode noise (e.g., ambient light), positioning DS as a more robust framework for high precision Hb quantification. Beyond spectral methods, color analysis/RGB imaging offers a hardware minimalist approach. By analyzing images of vascular rich, thin tissues (e.g., conjunctiva, nail beds, palms), it enables Hb estimation using smartphone cameras. Recent advances have shifted from manual RGB feature extraction to deep learning models and spectral super resolution that reconstruct hyperspectral data from RGB inputs, significantly improving screening accuracy. Our academic perspective emphasizes critical and integrative analysis. We highlight persistent challenges that hinder clinical translation: profound individual biological variability (skin optics, microvascular architecture), sensitivity to measurement conditions (pressure, ambient light), and a lack of standardized validation protocols and multi center trials. A central thesis is that no single optical method is universally superior; each involves trade offs between accuracy, complexity, cost, and practicality. Looking forward, we posit that the next performance leap will come from multimodal information fusion—combining PPG, electrocardiogram (ECG), bioimpedance, or different optical modalities to compensate for individual differences and environmental noise. AI and deep learning are essential not only for image analysis but also for automated, end to end feature extraction from complex waveforms like PPG sequences. Advancing hardware (tunable lasers, quantum dot LEDs, novel sensor designs) is crucial to improve signal fidelity and portability. Finally, we advocate for clinical scenario specific optimization and rigorous standardized evaluation frameworks to gain regulatory approval (e.g., FDA, NMPA) and achieve widespread clinical acceptance. In conclusion, this review synthesizes a decade of progress. Optical non-invasive Hb detection has evolved from proof of concept studies to emerging products and validated screening tools, but the journey toward reliable, clinic ready quantitative devices continues. The convergence of smarter algorithms, fused sensing modalities, and focused clinical validation offers the most promising path to transform this potential into routine medical practice, ultimately enabling personalized, continuous, and accessible hematological management.

This study investigated the infection status,drug resistance,and molecular characteristics of Shiga toxin-producing Escherichia coli(STEC)in domestic goats in Chengkou county,Chongqing.In August 2023,283 fecal samples were collected from households in Chengkou county.After enrichment with EC broth and inoculation onto selective media,samples that tested positive for stx1/stx2 were selected for further isolation.The positive strains were investigated with antimicrobial susceptibility testing and whole genome sequencing.According to the whole genomic sequences,the stx subtypes,serotypes,multi-locus sequence types,virulence genes,drug resistance genes,and phylogenetic relationships of the STEC strains were analyzed.Forty-six strains of STEC were isolated from 283 goat fecal samples,thus resulting in a detection rate of 16.25%.The 46 STEC strains were categorized into 12 O∶H serotypes,among which O76∶H19 and O8∶H7 predominated,each represented by 9 strains.Five STEC strains were identified as serotype O157∶H7.The 46 STEC strains were categorized into 11 sequence types(STs),among which ST675 and ST196 predominated,each represented by nine strains,accounting for a 19.57%proportion.The strains were categorized into 7 stx subtypes,among which stx1c(26/46,56.52%),followed by stx2k(9/46,19.57%)predominated.All nine Stx2k-STEC strains were identified as serotype O8∶H7 and sequence type ST196.In antimicrobial susceptibility testing,2 STEC strains were resistant to ampicillin,one strain was resistant to ampicillin/sulbactam,one strain was resistant to cefazolin,and one strain was resistant to cefoxitin.Nine Stx2k-STEC strains were found to carry the beta-lactam resistance gene blaEC-18.Antimicrobial sensitivity tests revealed that the nine Stx2k-STEC strains were sensitive to all 15 tested antibiotics.Moreover,phylogenetic analysis indicated that the 9 Stx2k-STEC strains were remarkably similar but showed high genetic diversity with respect to that of the Stx2k-STEC strains isolated from other regions in China.Goatsare an important animal reservoir for STEC in theChengkou district of Chongqing,and novel sequence type Stx2k-STEC strains distinct from those found in other regions of China were identified in this region.

This study investigated the infection status,drug resistance,and molecular characteristics of Shiga toxin-producing Escherichia coli(STEC)in domestic goats in Chengkou county,Chongqing.In August 2023,283 fecal samples were collected from households in Chengkou county.After enrichment with EC broth and inoculation onto selective media,samples that tested positive for stx1/stx2 were selected for further isolation.The positive strains were investigated with antimicrobial susceptibility testing and whole genome sequencing.According to the whole genomic sequences,the stx subtypes,serotypes,multi-locus sequence types,virulence genes,drug resistance genes,and phylogenetic relationships of the STEC strains were analyzed.Forty-six strains of STEC were isolated from 283 goat fecal samples,thus resulting in a detection rate of 16.25%.The 46 STEC strains were categorized into 12 O∶H serotypes,among which O76∶H19 and O8∶H7 predominated,each represented by 9 strains.Five STEC strains were identified as serotype O157∶H7.The 46 STEC strains were categorized into 11 sequence types(STs),among which ST675 and ST196 predominated,each represented by nine strains,accounting for a 19.57%proportion.The strains were categorized into 7 stx subtypes,among which stx1c(26/46,56.52%),followed by stx2k(9/46,19.57%)predominated.All nine Stx2k-STEC strains were identified as serotype O8∶H7 and sequence type ST196.In antimicrobial susceptibility testing,2 STEC strains were resistant to ampicillin,one strain was resistant to ampicillin/sulbactam,one strain was resistant to cefazolin,and one strain was resistant to cefoxitin.Nine Stx2k-STEC strains were found to carry the beta-lactam resistance gene blaEC-18.Antimicrobial sensitivity tests revealed that the nine Stx2k-STEC strains were sensitive to all 15 tested antibiotics.Moreover,phylogenetic analysis indicated that the 9 Stx2k-STEC strains were remarkably similar but showed high genetic diversity with respect to that of the Stx2k-STEC strains isolated from other regions in China.Goatsare an important animal reservoir for STEC in theChengkou district of Chongqing,and novel sequence type Stx2k-STEC strains distinct from those found in other regions of China were identified in this region.

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 explore the incidence status,influencing factors and short-term prognosis characteristics of early onset coronary heart disease in women in Wansheng District of Chongqing,and to provide scientific basis for formulating regional prevention and treatment strategies.Methods:This study was a single-center retrospective study,100 coronary heart disease in women from January 2022 to December 2023 at Chongqing Wansheng Economic and Technological Development Zone People's Hospital were prospective selected,and they were divided into early onset group of 40 cases(≤ 65 years old)and late onset group of 60 cases(＞65 years old)based on their age of onset.Another 60 healthy women who underwent physical examinations during the same period to exclude coronary heart disease were selected as the control group.Univariate factor and multiple factor logistic regression analysis were used to identify independent risk factors for early onset coronary heart disease in women.Draw receiver operating characteristic(ROC)curve for the subjects,the efficacy of risk factors in predicting early onset coronary heart disease based on the area under the curve(AUC)of ROC curve were evaluated.Patients were followed up for 1 year to observe the occurrence of major adverse cardiovascular events(MACE).Result:Among 100 fcoronary heart disease in women,the early onset group accounted for 40.00％(40/100).Univariate analysis showed that age,hyperlipidemia history,smoking history,hypertension history,family history,diabetes history,total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C)were related to the early onset coronary heart disease.Multivariate analysis showed that,hyperlipidemia history(OR=4.124,95％CI:2.343-7.217),smoking history(OR=3.564),hypertension(OR=3.253),family history(OR=2.981),diabetes history(OR=2.873)were independent risk factors.ROC curve analysis results showed that joint evaluation had the best predictive value,with AUC of 0.829,which was higher than the AUC of individual evaluation for each factor.The incidence of MACE in the early onset group(45.00％)was significantly higher than that in the late onset group(P＜0.05).Conclusion:Early onset coronary heart disease in women in Wansheng District of Chongqing is related to the hyperlipidemia history,smoking,hypertension history,family history and diabetes history.The incidence of MACE in early-onset patients followed up for 1 year is higher than that in late-onset patients.

Objective:To explore the incidence status,influencing factors and short-term prognosis characteristics of early onset coronary heart disease in women in Wansheng District of Chongqing,and to provide scientific basis for formulating regional prevention and treatment strategies.Methods:This study was a single-center retrospective study,100 coronary heart disease in women from January 2022 to December 2023 at Chongqing Wansheng Economic and Technological Development Zone People's Hospital were prospective selected,and they were divided into early onset group of 40 cases(≤ 65 years old)and late onset group of 60 cases(＞65 years old)based on their age of onset.Another 60 healthy women who underwent physical examinations during the same period to exclude coronary heart disease were selected as the control group.Univariate factor and multiple factor logistic regression analysis were used to identify independent risk factors for early onset coronary heart disease in women.Draw receiver operating characteristic(ROC)curve for the subjects,the efficacy of risk factors in predicting early onset coronary heart disease based on the area under the curve(AUC)of ROC curve were evaluated.Patients were followed up for 1 year to observe the occurrence of major adverse cardiovascular events(MACE).Result:Among 100 fcoronary heart disease in women,the early onset group accounted for 40.00％(40/100).Univariate analysis showed that age,hyperlipidemia history,smoking history,hypertension history,family history,diabetes history,total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C)were related to the early onset coronary heart disease.Multivariate analysis showed that,hyperlipidemia history(OR=4.124,95％CI:2.343-7.217),smoking history(OR=3.564),hypertension(OR=3.253),family history(OR=2.981),diabetes history(OR=2.873)were independent risk factors.ROC curve analysis results showed that joint evaluation had the best predictive value,with AUC of 0.829,which was higher than the AUC of individual evaluation for each factor.The incidence of MACE in the early onset group(45.00％)was significantly higher than that in the late onset group(P＜0.05).Conclusion:Early onset coronary heart disease in women in Wansheng District of Chongqing is related to the hyperlipidemia history,smoking,hypertension history,family history and diabetes history.The incidence of MACE in early-onset patients followed up for 1 year is higher than that in late-onset patients.

Objective To investigate the mechanism of Ginkgo biloba extracts(GB)in the treatment of cerebral ischemia-reperfusion(CIR)injury based on network pharmacology and animal experiments.Methods The intersection targets of CIR and GB were obtained from TCMSP,GeneCards and other databases.Cytoscape software and Metascape database were used to analyze and map the related targets.The model of transient middle cerebral arterial occlusion(t-MCAO)was constructed in mice by suture method,and the effects of GB on the neurological function of mice after t-MCAO were observed by the neurological deficit score and Morris water maze test.HE staining was used to observe the pathological structural changes of neuron in the hippocampus of mice,and Western blot was used to verify the signal pathways screened by network pharmacology.Results Network pharmacology predicted that GB contained 33 active ingredients,and 116 potential targets of GB in treatment of CIR included Caspase3,Bax,etc.In addition,GB may play a protective role through signaling pathways such as PI3K-Akt and AMPK.Animal experiments showed that GB treatment could significantly improve the neural function and learning spatial memory ability of mice,alleviate the brain histopathological injury,and activate p-Akt/Akt signaling pathway.Conclusion GB has the characteristics of multi-target and multi-pathways therapy for CIR,which may reduce neuronal apoptosis by activating the p-Akt/Akt signaling pathway.

Objective:To evaluate the effect of acupuncture on postoperative delirium (POD) in diabetic patients undergoing surgery under general anesthesia.Methods:In this randomized controlled trial, 92 diabetic patients of either sex, aged 30-80 yr, with a body mass index of 18-28 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅱ or Ⅲ, scheduled for elective surgery under general anesthesia, were divided into 2 groups ( n=46 each) using a table of random numbers: control group (group C) and acupuncture group (group A). Group A received acupuncture at the Baihui (GV20), Shenting (GV24) and Sishencong (EX-HN1) acupoints before anesthesia. The needles were retained for 30 min, with manual stimulation applied every 10 min for 10 s each time. After 4 stimulations, routine anesthesia was carried out. Group C received routine anesthesia only. Regional cerebral oxygen saturation was recorded on admission to the operating room (T 0), after anesthesia induction (T 1), at the start of surgery (T 2), at the end of surgery (T 3), and immediately after tracheal extubation (T 4). The POD developed within 3 days after surgery was assessed. The occurrence of needle-related adverse effects such as fainting, subcutaneous bleeding, and local paresthesia was recorded. Results:Compared with group C, the incidence of POD was significantly reduced, and the regional cerebral oxygen saturation was increased at T 1, 4 in group A ( P<0.05). Conclusions:Acupuncture can decrease the development of POD in diabetic patients undergoing surgery under general anesthesia, which is related to an increase in regional cerebral oxygen saturation.

Rheumatoid arthritis(RA)is a chronic autoimmune disease of unknown etiology that can cause joint destruction and deformity.As a small molecule cytokine,the chemokine C-X-C motif chemokine ligand 12(CXCL12)regulates the pathogenesis of rheumatoid arthritis by binding to the specific receptor CXC chemokine receptor 4(CXCR4).Therefore,based on the bio-logical characteristics of CXCL12 and CXCR4,this paper intro-duces the pathogenesis of CXCL12/CXCR4 in RA and summari-zes the progress in RA-related research,with the aim of providing clinical value for understanding the pathogenesis of RA and de-veloping novel therapeutic targets.

AIM To study the chemical constituents from the leaves of Drynaria fortunei(Kunze)J.Sm.and their antioxidant activity.METHODS ODS-AG-HG,Sephadex LH-20 and semi-preparative HPLC were used for separation and purification,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The antioxidant activity was determined by DPPH mothod.RESULTS Fifteen compounds were isolated and identified as kaempferol-3-O-neohesperidoside(1),dihydrodehydrodiconiferyl alcohol(2),kaempferol-3,7-di-O-α-L-rahmnoside(3),astragalin(4),loliolid(5),trichothecene analogue(6),2,2-[bis-4-(2,3-dihydroxypropoxy)phenyl]propane(7),maculatin(8),trichothecin(9),4-[(Z)-but-2-enoyloxy]-8-chloro-12-hydroxy-7,13-epoxytrichothec-9-ene(10),8-deoxy-trichotecin(11),β-sitosterol(12),daucosterol(13),afzelin(14),samwinol(15).The IC50 values of the leaf and rhizome extracts against DPPH free radicals were(0.072±0.005),(0.287±0.012)mg/mL,respectively.CONCLUSION Compounds 1,2,5-11,15 are isolated from this plant for the first time.The leaves of D.fortunei exhibit strong antioxidant activity.