ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

BACKGROUND:Traumatic brain injury is a condition in which the normal function of the brain is disrupted by a bump or impact to the head.It is necessary to find effective treatments and objective targets that can help doctors diagnose the injury status and restore the brain function of patients. OBJECTIVE:To explore the effect of electroacupuncture combined with low-frequency transcranial ultrasound stimulation on the electroencephalographic signals of rats with traumatic brain injury. METHODS:Forty 6-week-old SPF male Sprague-Dawley rats were randomly divided into five groups:sham group,model group,electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group(electroacupuncture+low-frequency transcranial ultrasound stimulation),with eight rats in each group.Feeney weight-drop method was used to establish the animal model of traumatic brain injury.In the sham group,the bone window was only opened without impact.Interventions were started at 1 day after modeling.Electroacupuncture in the electroacupuncture group,low-frequency transcranial ultrasound stimulation in the low-frequency transcranial ultrasound stimulation group,and electroacupuncture+low-frequency transcranial ultrasound stimulation in the combined group were performed for days in total.The modified neurological severity scale score for assessing rats'neurological deficits was performed at 8 hours after modeling.The percentage of spontaneous alternation behavior in the Y-maze was measured at 7 days after modeling.Then,the electroencephalographic signals were collected and electroencephalographic data of α,β,θ,and δ waves were extracted by fast Fourier transform,and the value of oscillation amplitude and energy ratio were calculated in α,β,θ,and δ waves,as well as the Lempel-Ziv complexity and sample entropy. RESULTS AND CONCLUSION:Compared with the sham group,the modified neurological severity scale scores in the model group,electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group were significantly increased at 8 hours after modeling(P<0.05).Compared with the sham group,the value of oscillation amplitude in δ wave and the value of δ energy ratio were significantly increased in the model group at 7 days after modeling,meanwhile the percentage of spontaneous alternation behavior in Y-maze,and the value of α/β energy ratio,Lempel-Ziv complexity,and sample entropy were significantly decreased(P<0.05).Compared with the model group,the value of oscillation amplitude in α and δ waves was significantly decreased in the combined group(P<0.05),while the value of α/β energy ratio was significantly increased(P<0.05)and the value of δ energy ratio was significantly decreased(P<0.05)in the electroacupuncture group,low-frequency transcranial ultrasound stimulation group and combined group.Compared with the electroacupuncture group and low-frequency transcranial ultrasound stimulation group,the value of δ energy ratio was significantly decreased in the combined group(P<0.05),while the percentage of spontaneous alternation behavior,the value of α/β energy ratio,the Lempel-Ziv complexity,and the sample entropy were significantly increased(P<0.05).To conclude,abnormal electroencephalographic signals can appear in rats with traumatic brain injury,while the electroacupuncture combined with low-frequency transcranial ultrasound stimulation can alleviate the abnormal electroencephalographic signals in rats,which suggests the electroencephalographic frequency domain value and nonlinear features can be used to assess the severity of traumatic brain injury.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To compare the short-term clinical outcomes of robotic gastrectomy (RG) and laparoscopic gastrectomy (LG) in treating gastric cancer, as well as the overall 5-year's survival rate.Methods:In this retrospective cohort study, 874 patients undergoing minimally invasive gastrectomy were recruited from Jan 2016 to Jan 2020 (LG: n=719; RG: n=155). A one-to-one propensity score matching analysis was applied to minimize the selection bias due to confounding factors, yielding 150 patients in each of the RG and LG groups. After matching, the short-term outcomes and 5-year overall survival were compared in the two groups. Results:The propensity score matching cohort analysis showed a similar 5-year overall survival between RG and LG groups ( P=0.235). Concerning the short-term outcomes, the RG compared to LG resulted in lower blood loss ( P=0.011), lower postoperative complications ( P=0.001), less postoperative pain ( P=0.014), earlier initiation of soft diet ( P=0.010), shorter hospital stay ( P=0.011), but higher hospitalization expenses ( P=0.004). Conclusions:RG had a similar overall survival outcome compared to LG while offering better safety and efficacy in terms of less blood loss, lower surgery complications, faster recovery, and less postoperative pain. Higher hospital expenses were the main disadvantage of RG that could limit its application.

Objective To reveal the development characteristics of fat percentage and muscle mass in three nomadic populations in the Hexi Corridor of Gansu.Methods Bioelectrical impedance analysis was used to determine the values of 13 indexes of fat percentage and muscle mass in 263 cases of Gansu Kazakhs,400 cases of Gansu Mongols,and 362 cases of Yugu adults.Results In the three nomadic populations of the Hexi Corridor,visceral fat level of males was significantly positively correlated with age,while total body muscle mass and estimated bone mass were significantly negatively correlated with age.In females,percent body fat,visceral fat grade,percent left and right upper limb fat,percent right lower limb fat and percent trunk fat were all significantly positively correlated with age,while trunk muscle mass was significantly negatively correlated with age.The result of principal component analysis showed that the three nomadic populations in the Hexi Corridor were close to each other in terms of fat percentage and muscle mass characteristics,with high visceral fat grades in males and normal visceral fat grade in females.Among the 13 populations,three nomadic groups in the Hexi Corridor had high fat percentage and muscle mass.Overall,the nomadic population had greater fat percentage and muscle mass than the semi-agricultural and semi-pastoral population,and even more significantly greater than the agrarian population.The long-term integration of the historical Hexi Corridor populations result ed in the relative proximity of the genetic structure of three nomadic populations,which was a genetic factor for the proximity of their fat percentage and muscle mass.Higher per capita disposable income was a socio-economic factor for high fat percentage and muscle mass among Gansu Kazakhs and Gansu Mongolians.Low average annual temperature was an environmental factor for high muscle mass among Gansu Kazakhs and Yugus.Conclusion Gansu Kazakhs,Gansu Mongols,and Yugus have the fat percentage and muscle mass characteristic of northern Chinese populations.

Objective:To observe the efficacy and safety of combined lienal polypeptide injection therapy in the treatment of Mycoplasma pneumoniae pneumonia（MPP）in children aged 3 to 14 years old in multiple clinical centers.Methods:A randomized，controlled，multi-center clinical study design was adopted.A total of 240 hospitalized children aged 3 to 14 years old with MPP from 7 hospitals from September 1，2023 to January 31，2024 were included.According to the severity of pneumonia，they were divided into the mild MPP group with 80 cases and the severe MPP/refractory MPP（SMPP/RMPP）group with 160 cases，and then randomly divided into the control group and the experimental group at a ratio of 1 ∶1，using the random number table method.After screening，subjects entered a treatment period of 5 to 7 days.The control group was treated with azithromycin，while the experimental group was treated with azithromycin plus lienal polypeptide injection .The recovery of lung CT，length of hospital stay，duration of fever，cough score，whether mild cases developed into severe or refractory cases，duration of hormone use，use of intravenous immunoglobulin（IVIG），bronchoscopy treatment，and immune function were observed between the two groups to evaluate the efficacy of lienal polypeptide injection.Adverse events after medication，vital signs，blood routine，urine routine，liver function，myocardial enzymes，renal function，and electrocardiogram were observed to evaluate the safety. Results:A total of 231 subjects have completed the trial in the 7 hospitals，including 118 cases in the experimental group and 113 cases in the control group.Main observation index：the rate of lung CT aggravation in the experimental group was lower than that in the control group（2.6% vs 15.3%， P<0.01），and the difference was statistically significant.Secondary indexes：there were no statistically significant differences in the length of hospital stay，duration of fever，cough score，duration of hormone use，whether IVIG treatment was used，the number of bronchoscopy treatment cases，and immunoglobulin between the two groups（all P>0.05）.However，the rate of cases of plastic bronchitis（PB）found under bronchoscopy in the experimental group was lower than that in the control group（0 vs 18.8%， P=0.03），and the difference was statistically significant.Among the mild MPP（72 cases），there were no statistically significant differences in the length of hospital stay，duration of fever，cough score，duration of hormone use，whether IVIG treatment was used，the number of bronchoscopy treatment cases，and the improvement rate of lung CT between the two groups（all P>0.05）.However，compared with the control group，the rate of cases developing into SMPP/RMPP in the experimental group was less（24.3% vs 48.6%， P=0.03），and the difference in IgG before and after treatment was small［0.53（-0.04，1.18）g/L vs 1.33（0.48，2.25）g/L， P=0.01］.Among the SMPP/RMPP cases（159 cases），the rate of cases of PB found under bronchoscopy in the experimental group was less than that in the control group（0 vs 20%， P=0.04），and the rate of cases with aggravated lung CT in the experimental group was less than that in the control group（1.3% vs 19.5%， P<0.01），and the improvement rate of lung CT in the experimental group was higher than that in the control group（88.8% vs 75.3%， P=0.03），with statistically significant differences.There were no statistically significant differences in the length of hospital stay，duration of fever，cough score，duration of hormone use，whether IVIG treatment was used，the number of bronchoscopy treatment cases，and immunoglobulin between the two groups（all P>0.05）.Two cases in the experimental group developed rashes，which improved after the drug was discontinued.There were no serious adverse reactions such as abnormal vital signs like dyspnea and cyanosis due to the use of lienal polypeptide injection.There were no obvious changes in blood routine，liver function，myocardial enzymes，renal function，electrocardiogram，and urine routine values before and after medication compared with the baseline. Conclusion:The combined use of lienal polypeptide injection in the treatment of MPP in children can reduce the probability of the transformation from mild cases to SMPP/RMPP，reduce the rate of aggravation of the image findings，promote the absorption of lung inflammation，reduce the rate of PB found under bronchoscopy，and has good safety.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.

Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6％of the isolates were Gram-negative bacteria and 17.4％were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)％and(94.0±0.1)％,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P＜0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9％.The prevalence of penicillin-resistant S.pneumoniae was 1.4％.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8％and 41.3％,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7％,20.8％,9.4％,29.8％,and 73.3％,respectively.The prevalence of β-lactamase was 96.1％in Moraxella catarrhalis and 60.0％in Haemophilus influenzae.The H.influenzae isolates from children(＜18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P＜0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.