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.

The Expert Consensus on Clinical Application of Qinbaohong Zhike Oral Liquid in Treatment of Acute Bronchitis and Acute Attack of Chronic Bronchitis （GS/CACM 337-2023） was released by the China Association of Chinese Medicine on December 13^th， 2023. This expert consensus was developed by experts in methodology， pharmacy， and Chinese medicine in strict accordance with the development requirements of the China Association of Chinese Medicine （CACM） and based on the latest medical evidence and the clinical medication experience of well-known experts in the fields of respiratory medicine （pulmonary diseases） and pediatrics. This expert consensus defines the application of Qinbaohong Zhike oral liquid in the treatment of cough and excessive sputum caused by phlegm-heat obstructing lung， acute bronchitis， and acute attack of chronic bronchitis from the aspects of applicable populations， efficacy evaluation， usage， dosage， drug combination， and safety. It is expected to guide the rational drug use in medical and health institutions， give full play to the unique value of Qinbaohong Zhike oral liquid， and vigorously promote the inheritance and innovation of Chinese patent medicines.

OBJECTIVE To explore the risk factors for hospital-associated infections(HAI)in dead patients so as to provide bases for development of prevention strategies for the hospital-associated infections.METHODS Totally 560 patients who died due to non-SARS-CoV-2 infections and hospitalized in Gansu Provincial People's Hospital for more than 48 hours in 2019 and 2023 were retrospectively analyzed,70 of whom had HAI and were assigned as the HAI group,and the rest of 490 patients were assigned as the non-HAI group.The incidence of HAI,major causes of death,risk factors and economic burden were observed.RESULTS The incidence of HAI was 12.50％a-mong the dead patients,the lower respiratory tract infection was the predominant type of infection,and the re-spiratory failure was the primary and direct cause of death in the HAI group;the total treatment cost of the HAI group was higher than that of the non-HAI group(P＜0.05).Univariate analysis showed that there were signifi-cant differences in the length of hospital stay,multidrug-resistant organisms infections,combined use of antibiot-ics,surgery,hemodialysis/peritoneal dialysis,invasive procedures(drainage,puncture,intubation,tracheoto-my),use of equipment like ventilator or urinary catheter,central venous catheter indwelling,blood transfusion,and use of immunosuppressors/glucocorticoids between the HAI group and the non-HAI group(P＜0.05),while there were no significant differences in the sex,age,underlying diseases,modified early warning score(MEWS)and major diagnosis and chemoradiotherapy between the two groups.Multivariate analysis indicated that the length of hospital stay more than 14 days,history of surgery and combined use of antibiotics were the risk factors for HAI in the dead patients(P＜0.05).CONCLUSION It is necessary for the hospital to identify the high-risk pa-tients as early as possible,pay close attention to the lower respiratory tract infection,reduce the risk of HAI by shortening the length of hospital stay,standardizing the invasive procedures and reasonably using antibiotics so as to improve the prognosis of the patients.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective To investigate the distribution and antimicrobial resistance profiles of clinically isolated Haemophilus influenzae and Moraxella catarrhalis in hospitals across China from 2015 to 2021,and provide evidence for rational use of antimicrobial agents.Methods Data of H.influenzae and M.catarrhalis strains isolated from 2015 to 2021 in CHINET program were collected for analysis,and antimicrobial susceptibility testing was performed by disc diffusion method or automated systems according to the uniform protocol of CHINET.The results were interpreted according to the CLSI breakpoints in 2022.Beta-lactamases was detected by using nitrocefin disk.Results From 2015 to 2021,a total of 43 642 strains of Haemophilus species were isolated,accounting for 2.91％of the total clinical isolates and 4.07％of Gram-negative bacteria in CHINET program.Among the 40 437 strains of H.influenzae,66.89％were isolated from children and 33.11％were isolated from adults.More than 90％of the H.influenzae strains were isolated from respiratory tract specimens.The prevalence of β-lactamase was 53.79％in H.influenzae strains.The H.influenzae strains isolated from children showed higher resistance rate than the strains isolated from adults.Overall,779 strains of H.influenzae did not produce β-lactamase but were resistant to ampicillin(BLNAR).Beta-lactamase-producing strains showed significantly higher resistance rates to these antimicrobial agents than the β-lactamase-nonproducing strains.Of the 16 191 M.catarrhalis strains,80.06％were isolated from children and 19.94％isolated from adults.M.catarrhalis strains were mostly susceptible to both amoxicillin-clavulanic acid and cefuroxime,evidenced by resistance rate lower than 2.0％.Conclusions The emergence of antibiotic-resistant H.influenzae due to β-lactamase production poses a challenge for clinical anti-infective treatment.Therefore,it is very important to implement antibiotic resistance surveillance for H.influenzae and guide rational antibiotic use.All local clinical microbiology laboratories should actively improve antibiotic susceptibility testing and strengthen antibiotic resistance surveillance for H.influenzae.

Objective:To investigate the clinical efficacy of liquid nitrogen cryopreservation and reimplantation versus allograft reconstruction in patients underwent resection of primary malignant bone tumors of the long bones of the extremities.Methods:A retrospective analysis was conducted on 144 patients who underwent resection of primary malignant bone tumors of the long bones of the extremities followed by either liquid nitrogen cryopreservation and reimplantation or massive allografts reconstruction at the Beijing Jishuitan Hospital affiliated with Capital Medical University from January 2012 to July 2023. The study included 82 males and 62 females, with an average age of 23.8±12.3 years (range, 6-64 years). Patients were divided into two groups based on the reconstruction method: the cryopreservation and reimplantation group (72 cases) and the allograft group (72 cases). The following outcomes were recorded during follow-up: local tumor recurrence, bone union, union time, graft survival, and reasons for graft removal. Graft-related complications were recorded using the modified Henderson classification system of the International Limb Salvage Association. Limb function was assessed at the last follow-up using the Musculoskeletal Tumor Society score (MSTS-93).Results:All patients completed surgery and were followed up for a mean of 60.2±32.1 months (range, 12-149 months). At the last follow-up, 24 patients were dead from the tumor, 16 patients survived with the tumor (2 cases of local recurrence and 14 cases of distant metastasis), and 104 patients survived without the tumor. The bone union rate and union time in cryopreservation and reimplantation group were 90% (65/72) and 9.6±4.8 months, respectively, which was significantly superior to those in allograft group [68% (49/72) and 15.9±6.7 months, P<0.05]. The 5-year overall graft survival rate was 86.8% [95% CI (80.1%, 95.7%)] in cryopreservation and reimplantation group, higher than 73.2% [95% CI(68.4%, 84.5%)] in allograft group significantly (χ 2=7.122, P=0.017). The rates of graft removal due to non-union and infection in the cryopreservation and reimplantation group were 0% (0/72) and 1.4% (1/72), respectively, which were significantly lower than those in the allograft group [5.6% (4/72) and 9.7% (7/72), P<0.05]. Overall, 48.6% (70/144) of patients experienced at least one graft-related complication, with a complication rate of 33.3% in cryopreservation and reimplantation group, lower than the 61.1% in allograft group significantly (χ 2=11.146, P<0.001). The complications with the highest incidence rate were nonunion (20.8%, 30/144), followed by structural failure (17.4%, 25/144), tumor progression (10.4%, 15/144), infection (10.4%, 15/144), and soft tissue failure (5.6%, 8/144). The incidence rates of the atrophic non-union and the structural failure of grafts were 9.7% (7/72) and 1.4% (1/72) respectively in the cryopreservation and reimplantation group, which were significantly lower compared to the allograft group [29.2% (21/72) and 13.9% (10/72), P<0.05]. At the last follow-up, the MSTS-93 score was 89.7%±8.3% in the cryopreservation and reimplantation group, and 87.6%±7.5% in the allograft group, with no statistically significant difference ( t=0.326, P=0.542). Conclusion:Compared with allograft reconstruction, autologous inactivated bone grafting demonstrated superior bone union efficiency and fewer complications, it may be considered for reconstruction in cases whose tumor bone is not severely osteolytic or pathologically fractured.

OBJECTIVE: To investigate the clinical efficacy and advantages of robot-assisted total knee arthroplasty (TKA) in patients with varus knee osteoarthritis. METHODS: Between October 2022 and June 2023, a total of 59 patients with severe knee osteoarthritis resulting in varus were treated with total knee arthroplasty, aged from 59 to 81 years with an average (70.90±4.63) years, including 19 mals and 40 females. The patients were divided into two groups based on the surgical method used:28 patients in the robot group and 31 patients in the traditional group. The robot group consisted of 8 males and 20 femalse patients, with an average age of (70.54±4.80) years and an average disease duration of (14.89±8.72) months. The traditional group consisted of 11 males and 20 females patients, with an average age of (71.39±4.5) years and an average disease duration of (12.32±6.73) months. The operative duration, amount of bleeding during the operation, postoperative activity time after the operation, hip-knee-ankle angle (HKA), lateral distal femoral angle (LDFA), medial proximal tibial angle (MPTA), and complications were compared between the two groups before and after the operation. Lateral tibia component (LTC), frontal tibia component (FTC), frontal femoral component (FFC) and lateral femoral component (LFC) were measured 6 months after operation Additionally, the degree of knee joint motility, American Knee Society score (KSS), and visual analogue scale(VAS) were compared before and after the operation. RESULTS: All patients had gradeⅠwound healing without any complications, and all patients were followed up for 6 to 8 months, with an average of (6.5±1.5) months. There were no significant differences preoperative imaging evaluation indexes (including HKA, LDFA, and MPTA), preoperative knee mobility, preoperative VAS, and preoperative KSS between the two groups (P>0.05). Comparing the operation time (109.11±7.16) min vs. (83.90±7.85) min, length of the incision (16.60±2.33) cm vs. (14.47±1.41) cm, intraoperative bleeding (106.93±6.15) ml vs. (147.97±7.62) ml, postoperative activity time (17.86±1.84) h vs. (21.77±2.68) h, between the two groups showed statistically significant differences (P<0.05). There were significant differences in FFC (88.96±0.84)° vs. (87.93±1.09)° and LFC (88.57±1.10)° vs. (87.16±1.2)° between the two groups at 6 months after operation (P<0.05). The robotic group 1, 3, 6 months after KSS (75.96±3.96), (81.53±3.78), (84.50±3.29) scores, VAS (3.68±0.67), (2.43±0.79), (0.54±0.64), knee joint mobility (113.32±4.72) °, (123.93±3.99) °, (135.36±2.34) °;Traditional group KSS (73.77±4.18), (76.48±3.60), (80.19±3.28) scores, VAS (4.16±1.04), (3.03±0.75), (1.42±0.76) scores, knee joint mobility (109.19±6.95) °, (119.94±6.08) °, (134.48±2.14) °. Compared to before surgery, both groups showed significant improvement in KSS, VAS and knee mobility during the three follow-up visits (P<0.001). Additionally, postoperative HKA (180.39±1.95)° vs. (178.52±2.23)°, LDFA (89.67±0.63) ° vs. (89.63±0.63)°, and MPTA (89.44±0.55)° vs. (89.29±0.60)° were significantly improved in both groups compared to before surgery (P<0.001). The robotic group had higher KSS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). The robotic group also had lower VAS than the traditional group at 1, 3, and 6 months after surgery (P<0.05). Furthermore, knee mobility was higher in the robotic group than those in the traditional group at 1 and 6 months after surgery (P<0.05), but there was no significant difference between the two groups at 6 months after surgery. CONCLUSION Robot-assisted total knee arthroplasty is a safe and effective method for total knee replacement. The use of robotics can improve the limb axis and prosthesis alignment for patients with preoperative varus deformity, resulting in better clinical and imaging outcomes compared to the conventional group.
Humans ; Female ; Male ; Arthroplasty, Replacement, Knee/methods* ; Aged ; Middle Aged ; Osteoarthritis, Knee/physiopathology* ; Aged, 80 and over ; Robotic Surgical Procedures/methods*

To guide clinical blood transfusion practices for pediatric patients, the National Health Commission has issued the health standard "Guideline for pediatric transfusion" (WS/T 795-2022). Blood transfusion is one of the most commonly used supportive treatments for children with hematological diseases. This guideline provides guidance and recommendations for blood transfusions in children with aplastic anemia, thalassemia, autoimmune hemolytic anemia, glucose-6-phosphate dehydrogenase deficiency, acute leukemia, myelodysplastic syndromes, immune thrombocytopenic purpura, and thrombotic thrombocytopenic purpura. This article presents the evidence and interpretation of the blood transfusion provisions for children with hematological diseases in the "Guideline for pediatric transfusion", aiming to assist in the understanding and implementing the blood transfusion section of this guideline.
Humans ; Child ; Hematologic Diseases/therapy* ; Blood Transfusion/standards* ; Practice Guidelines as Topic