ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

ObjectiveIn traditional Chinese medicine (TCM), the foundational doctrine that the eyes reflect the essence of the internal viscera establishes ocular observation as a cornerstone of diagnostic practice. Specifically, the morphological characteristics and coloration variations of the scleral microvasculature serve as critical clinical indicators for assessing the dynamic balance of Qi and Blood, as well as the pathological status of internal organs. Historically, however, TCM eye diagnosis has relied predominantly on the subjective clinical experience and visual acuity of individual practitioners, leading to inherent challenges in standardization and reproducibility. While automated computer-aided diagnostic systems offer a promising solution, existing vessel segmentation algorithms encounter significant domain-specific bottlenecks when applied to scleral imagery. These challenges primarily stem from the highly reflective and moist nature of the ocular surface, which generates severe reflective interference. Furthermore, the inherent low contrast of fine capillary networks against complex background textures, compounded by non-uniform illumination, frequently results in high false-positive rates, misdetections, and severe vessel fragmentation. To address these critical limitations and advance the objective quantification of TCM diagnostics, this paper proposes a novel, highly robust sclera vessel segmentation framework that innovatively integrates Frangi-Sato dual-filter adaptive enhancement with pixel-level reflection detection. MethodsThe proposed methodology systematically addresses the segmentation pipeline through three synergistic stages. First, to overcome the structural limitations of single-filter approaches, a multi-scale weighted fusion strategy is meticulously designed to harness the complementary extraction capabilities of both Frangi and Sato filters. This adaptive enhancement optimally balances the preservation of main vessel trunk continuity with the heightened sensitivity required for delineating delicate, low-contrast peripheral capillaries. Second, to tackle the persistent issue of reflective highlights, a sophisticated multi-feature synergistic reflection detection module is introduced. By jointly analyzing local information entropy, gradient field variations, and intensity statistical distributions, this module achieves precise, pixel-level identification and elimination of reflective artifacts without compromising the underlying vascular structures. Finally, a dual-level adaptive thresholding strategy, featuring an innovative “core protection” mechanism, is implemented. This critical step effectively suppresses complex background noise while rigorously preserving the structural and topological integrity of the intricate vessel network, preventing the structural breaks often seen in conventional binarization methods. ResultsThe efficacy of the proposed framework was rigorously evaluated using both self-constructed clinical datasets specifically acquired for TCM research and standardized public datasets. Extensive experimental results demonstrate that the proposed method consistently outperforms state-of-the-art traditional approaches and contemporary deep learning models. Specifically, the proposed method achieves a Dice similarity coefficient of approximately 0.71 on the private clinical dataset, and secures the best performance across the majority of quantitative metrics on both datasets. Notably, the framework exhibits exceptional robustness and generalization capabilities in highly challenging scenarios characterized by intense reflective interference, low signal-to-noise ratios, and cross-domain image variations. ConclusionThis study successfully realizes the high-integrity, automated segmentation of scleral vessel networks under complex clinical imaging conditions. By overcoming the fundamental algorithmic challenges of reflection interference and micro-vessel loss, the proposed methodology provides potential support for the digitization, objective standardization, and intelligent advancement of modern TCM eye diagnosis systems.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

AIM To prepare the sustained-release microspheres of ginsenosides.METHODS The sustained-release microspheres were prepared by SPG membrane emulsification technology with poly(lactic-co-glycolic acid)(PLGA)as a shell carrier.With PLGA concentration,feed rate and Span 60 concentration as influencing factors,comprehensive score for appearance,drug loading and encapsulation efficiency as an evaluation indice,the preparation process was optimized by response surface method.The morphology of sustained-release microspheres was observed,after which the particle size,drug loading and encapsulation efficiency were determined,and the in vitro drug release was investigated.RESULTS The optimal conditons were determined to be 45 s for agitation time of primary emulsion,74.68 mg/mL for PLGA concentration,11％for feed rate,and 4.18 mg/mL for Span 60 concentration,the comprehensive score was 74.98.The round sustained-release microspheres demonstrated the average particle size of 4.33 μm,drug loading of(8.24±0.13)％,and encapsulation efficiency of(74.94±1.17)％,respectively.At 336 h,ginsenosides Rg1,Rb1,Rb2 displayed the accumulative release rates of 84.12％,78.04％,65.88％,respectively.CONCLUSION This reasonable and feasible method can be used for the preparation of sustained-release microspheres of ginsenosides with good appearance and high drug loading,which can provide references for the preparation of other water-soluble drug microspheres and solution of microsphere collapse problem.

OBJECTIVE To investigate the serotypes and antimicrobial resistance rate of clinically isolated Salmonel-la in a children's hospital in Suzhou,and to provide reference for the treatment of salmonellosis.METHOD Totally 177 strains of Salmonella isolated from Children's Hospital of Wujiang District from Jan.2021 to Dec.2023 were collected,and the results of serotypes and drug sensitivity of Salmonella were analyzed.RESULTS The male to fe-male isolation rate of Salmonella was 1.39∶1,with a median age of children infection at 1.3(0.8,2.3)years.The highest number of Salmonella strains were isolated in the month of Jun.,followed by Jul.,Aug.,Sep.,Oct.and May,collectively accounting for 82.49％of all isolates.Acute gastroenteritis was manifested in 142 cases(80.22％),with respiratory tract infections in 38 cases(21.47％)and septicemia in 7 cases(3.95％).The differ-ence in detection rates across the three years was not statistically significant(P=0.806).Salmonella Typhimuri-um was the predominant serotype,representing 54.24％of all isolates.The antimicrobial drug with the highest rate of resistance in Salmonella was ampicillin(71.35％,122/171),followed by sulfamethoxazole/metronidazole(43.60％,75/172),and ampicillin/sulbactam(30.23％,52/172),and no imipenem resistant strains were found.29.07％(50/172)of strains showed multidrug resistance.CONCLUSIONS Boys under three years of age are sus-ceptible to Salmonella infections in summer and fall in this region,with Salmonella Typhimurium being the pre-dominant serotype.Clinical attention should be paid to the characteristics of Salmonella infection and drug resist-ance,as well as the early diagnosis and rational use of antimicrobial drugs.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Aberrant expression of Colgalt1 is closely associated with tumorigenesis and tumor progres-sion;however,the mechanism by which it regulates macrophages to influence tumor development remains poorly understood.This study aimed to establish a macrophage-specific Colgalt1 gene knockout mouse model to delve into the mechanisms through which Colgalt1 modulates macrophage function and subse-quently affects the occurrence and progression of tumor-related diseases.Initially,Colgalt1flox+mice were generated using gene editing techniques,followed by crossing with Lyz2-Cre+mice,which exhibit tissue-specific expression in the myeloid lineage(including monocytes and mature macrophages).Through this strategy,mice with the genotype Colgalt1-/-Lyz2-Cre+were successfully obtained,achieving conditional knockout of the Colgalt1 gene in macrophages.Colgalt1flox/flox Lyz2-Cre-mice were used as control.PCR and agarose gel electrophoresis were employed to identify the Flox and Cre genotypes of the knockout mice.RT-qPCR and Western Blot techniques were utilized to detect the expression levels of Colgalt1 in BMDMs from knockout mice at both the mRNA and protein levels,respectively.Western Blot results re-vealed a significant downregulation of Colgaltl expression in BMDMs from knockout mice compared to controls(P＜0.01).RT-qPCR results demonstrated a significant reduction in Colgalt1 mRNA levels in BMDMs from knockout mice compared to contro1s(P＜0.001),while no significant differences in Col-galt1 mRNA expression were observed in liver,lung,or spleen tissues between the two groups.Addition-ally,immunohistochemistry was employed to detect Colgalt1 expression in liver-specific macrophages,re-vealing an absence of Colgalt l-positive staining in liver macrophages from knockout mice.HE staining was used to observe cellular morphology in liver tissues from both groups of mice,showing no significant differences in cellular morphology or obvious pathological changes in tissues and organs.Moreover,the o-verall survival of the mice was not affected.Finally,RT-qPCR was used to assess the expression of mac-rophage-related inflammatory factors in BMDMs from both groups of mice.The results indicated that com-pared to controls,knockout mice exhibited downregulated expression of TNF-α(P＜0.05)and signifi-cantly upregulated expression of IL-10(P＜0.01),Arginase1(P＜0.001),and CD206(P＜0.001)in BMDMs,suggesting an anti-inflammatory trend and M2 polarization of macrophages following Colgalt 1 knockout.In summary,this study successfully established a macrophage-specific Colgalt1 gene knockout mouse model,providing a more reliable experimental animal model for in-depth exploration of the specific roles of Colgalt1 in macrophage functional regulation and the pathogenesis of tumor-related diseases.This model holds promise for identifying novel therapeutic targets and strategies for tumors and other diseases.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective:To understand spatial aggregation of lung cancer mortality and its changing trends over the past fifty years in different counties and districts of Shandong Province from 1970 to 2021.Methods:The mortality data of lung cancer were obtained from the death registration system of Shandong province and three retrospective surveys of death cause. The mortality rate and age-standardized mortality rate were used to describe the changing trend of lung cancer in different years, and the contribution value of population factors and non-population factors in lung cancer mortality change was calculated by the mortality differential decomposition method. GeoDa 1.20 and ArcGIS 10.8 software were used for spatial autocorrelation analysis and visualization map display.Results:The crude mortality rate of lung cancer in Shandong Province showed a significant upward trend from 1970 to 2021, rising from 7.22 per 100 000 in 1970-1974 to 62.73 per 100 000 in 2020-2021, with an increase of 7.69 times. Meanwhile, the standardized mortality rate of lung cancer exhibited a trend of increasing first and then decreasing. The differential analysis of lung cancer mortality in different years revealed that changes in crude mortality rates were the result of the combined effects of demographic and non-demographic factors. The proportion of population factors (aging population) leading to an increase in lung cancer mortality rate rose from 2.12% in 1990-1992 to 40.20% in 2020-2021. From a spatial distribution perspective, there were significant regional differences in lung cancer mortality rates among counties (cities, districts) in Shandong Province across different eras. Compared to the period of 1970-1974, the lung cancer mortality rates in all counties and districts in 2020-2021 showed a considerable increase, and there were noticeable changes in the areas of high-high and low-low clustering of lung cancer mortality rates across different eras.Conclusion:There have been significant temporal and spatial changes in the mortality rate of lung cancer in Shandong Province from 1970 to 2021. The crude mortality rate has shown an upward trend, while the standardized mortality rate increases first and then decreases. The concentration of lung cancer mortality rates in counties and districts has also undergone significant changes.