Objective: To evaluate the current situation of thermal environment in primary and secondary school classrooms during winter, and to analyze students thermal comfort needs, so as to provide a basis for improving classroom thermal environment. Methods: From December 16 to 26, 2024, a stratified cluster random sampling method was used to select 90 classrooms from 15 primary and secondary schools in centralized/air conditioned heating areas(Liaoning Province, Tianjin City, Shanghai City) and naturally ventilated areas(Anhui Province and Jiangxi Province)for on site environmental measurement. A questionnaire survey was conducted among 743 students. The differences between groups using the χ 2 test were compared. Based on actual measurement data, a predicted mean vote prepared percentage of dissatisfied (PMV-PPD) model for centralized/air conditioned classrooms and an adaptive model for naturally ventilated classrooms were established, and the thermal neutral temperature and comfort interval were calculated. Results: The average outdoor temperature during on site measurement was 4.00(0.20，7.00)℃. In classrooms with centralized or air conditioned heating systems, the measured average temperature was (19.33±2.59)℃, with a thermal comfort range of 20.35-25.35 ℃ and a thermal neutral temperature of 22.85 ℃. And 13.92% of students reported feeling cold, while 80.80% felt comfortable. In classrooms with natural ventilation, the measured average temperature was (12.26±1.83)℃, with a thermal neutral temperature of 19.67 ℃ and a thermal comfort range of 16.17-23.17 ℃. About 48.33% of students reported feeling cold, and 49.81 % felt comfortable.The results of univariate analysis showed that there were statistically significant differences in shoe thickness, temperature sensation, relative humidity sensation and wind speed sensation between centralized/air conditioned heating areas ( χ 2= 7.01 , 31.47, 13.57, 13.80,all P <0.05). There were also statistically significant differences in school stage for primary and secondary school students, body mass index, classroom location for seat, temperature sensation, relative humidity sensation and wind speed sensation between naturally ventilated areas ( χ 2=42.13, 11.13, 11.04, 60.39, 29.27, 38.46,all P <0.05). Conclusions There are differences in thermal environment and students subjective thermal comfort in primary and secondary schools under different ventilation modes in winter. The temperature standards for heated classrooms should be revised, and differentiated environmental regulation strategies should be adopted based on different ventilation methods to improve students health and comfort levels.

The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

The theory of constitution in traditional Chinese medicine （TCM） has emerged as a new discipline in recent years. Constitution plays a vital role in the onset，progression，transformation，and prognosis of diseases. At present，some clinical scholars have adopted a novel diagnostic and treatment model of "constitution differentiation-disease identification-syndrome differentiation"，in which constitution is regarded as a core element throughout the diagnostic and therapeutic process. Constitution is closely associated with etiology，onset，pathogenesis，syndrome differentiation，and treatment. Against this background，the construction of animal models based on constitution holds far-reaching significance for advancing clinical research. This paper focuses on the construction and evaluation of rodent models with Qi-deficiency constitution，aiming to explore how to further induce Qi-deficiency syndromes and related disease states on the basis of Qi-deficiency constitution models，thereby developing an integrated animal model that embodies the trinity of "constitution-disease-syndrome". The establishment of this model not only provides a solid experimental foundation for the development of new therapies and drugs in TCM targeting specific constitutions，diseases，and syndromes，but also greatly promotes the modernization and scientific advancement of TCM theory. By comprehensively applying multidisciplinary technologies and methods，the study evaluates the model's validity，reliability，and practicality，with the aim of opening new avenues for future research in TCM and promoting the development of the field.

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 investigate the brain microvascular tissue block culture method for extracting primary rat brain microvascular endothelial cells and identify its effect. Methods : Brain tissue from 4-week-old Sprague Dawley rats was screened, pre-digested and solidified to obtain brain microvascular segments. These segments were subsequently placed in a CO2incubator for primary culture. The target cells were identified by cell morphology and immunocytochemical staining for factor Ⅷ-related antigen. Results : After a 48-hour culture periodin vitro, the short spindle cells crawled out from around the brain microvascular segments. After 72 hours, island-like cell culsters formed. After 96 hours the clusters fused and the cells formed a typical monolayer, cobble stone-like, and mosaic arrangement. Factor Ⅷ-related antigen immunocytochemical staining showed that the cytoplasm of the cells appeared brown-red, indicating positive expression; DAB stained the nucleus, showing blue-dark. Conclusion The brain microvascular tissue block culture method can isolate and culture primary rat brain microvascular endothelial cells.

ObjectiveTo investigate the significance of different non-treatment thresholds or upper limits of normal （ULN） of alanine aminotransferase （ALT） in evaluating significant liver pathological injury in patients with chronic hepatitis B virus （HBV） infection， and to provide guidance for clinical diagnosis and treatment. MethodsThis study was conducted among 733 patients with chronic HBV infection who were hospitalized in Ningbo No. 2 Hospital from January 2015 to December 2023 and underwent liver biopsy and histopathological examination， and all patients had a persistent ALT level of ≤40 U/L and positive HBV DNA （>30 IU/mL）. According to the treatment threshold or ULN of ALT， the patients were divided into group 1 with 575 patients （≤35 U/L for male patients， ≤25 U/L for female patients）， group 2 with 430 patients （≤30 U/L for male patients， ≤19 U/L for female patients）， group 3 with 443 patients （≤27 U/L for male patients， ≤24 U/L for female patients）， group 4 with 446 patients （≤25 U/L）， group 5 with 158 patients （>35 U/L for male patients， >25 U/L for female patients）， and group 6 with 145 patients （>30 — ≤35 U/L for male patients， >19 — ≤25 U/L for female patients）. Groups 2， 5， and 6 were compared to analyze the severity of liver pathological injury in patients with different ALT levels and the constituent ratio of patients with significant liver pathological injury， and groups 1， 2， 3， and 4 were compared to investigate the value of different ULN or non-treatment thresholds of ALT in determining liver inflammation grade （G）， liver fibrosis stage （S）， and the treatment indication based on liver pathology. The independent-samples t test was used for comparison of normally distributed continuous data between two groups； a one-way analysis of variance was used for comparison between multiple groups， and the least significant difference t-test or the Tambane’s test was used for further comparison between two groups； the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups， and the Kruskal-Wallis H test was used for comparison between multiple groups and further comparison between two groups； the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups； a Ridit analysis was used for comparison of ranked data. A multivariate Logistic regression analysis （forward stepwise） was performed with whether liver pathology met the treatment indication （≥G2 and/or ≥S2） as the dependent variable and related factors with a significant impact on the dependent variable （P <0.05） as the independent variable. The receiver operating characteristic （ROC） curve was plotted， and the area under the ROC curve （AUC）， as well as sensitivity， specificity， positive predictive value， negative predictive value， positive likelihood ratio， and negative likelihood ratio， was used to assess the diagnostic value of different non-treatment thresholds of ALT. ResultsAmong the 733 patients， 259 （35.33%） had ≥G2 liver inflammation， 211 （28.79%） had ≥S2 liver fibrosis， and 306 （41.75%） had treatment indication （≥G2 and/or ≥S2）. There was a significant difference in liver inflammation grade （G0 — G4） between groups 2， 5， and 6 （χ²=22.869， P <0.001）， and there were also significant differences in the constituent ratios of patients with ≥G2 or ≥G3 liver inflammation between the three groups （χ²=21.742 and 14.921， P<0.001 and P=0.001）. There was a significant difference in liver fibrosis stage （S0 — S4） between groups 2， 5， and 6 （χ²=16.565， P<0.001）， and there were also significant differences in the constituent ratios of patients with ≥S2， ≥S3 or S4 liver fibrosis between the three groups （χ²=13.264， 13.050， and 6.260， P=0.001， 0.001， and 0.044）. There were significant differences between groups 2， 5， and 6 in the constituent ratios of patients with or without treatment indication based on liver pathology （χ²=20.728， P<0.001）. There were significant differences between groups 2， 5， and 6 in the constituent ratio of male patients （χ²=24.836， P<0.05）， age （F=5.710， P<0.05）， ALT （F=473.193， P<0.05）， aspartate aminotransferase （AST） （F=107.774， P<0.05）， ALT/AST ratio （F=40.167， P<0.05）， γ-glutamyl transpeptidase （GGT） （H=15.463， P<0.05）， aspartate aminotransferase-to-platelet ratio index （APRI） （H=63.024， P<0.05）， and LIF-5 （5 indicators for liver inflammation and fibrosis） （H=46.397， P<0.05）. In groups 1 — 4， compared with the patients without treatment indication， the patients with treatment indication had a significantly lower constituent ratio of patients with positive HBeAg， significantly lower levels of platelet count （PLT） and HBV DNA， and significantly higher age， ALT， AST， GGT， APRI， FIB-4， and LIF-5 （all P<0.05）. The Logistic regression analysis showed that age （odds ratio ［OR］=1.044， 95% confidence interval ［CI］： 1.025 — 1.063， P<0.001）， GGT （OR=1.022， 95%CI： 1.007 — 1.038， P=0.003）， and HBV DNA （OR=0.839， 95%CI： 0.765 — 0.919， P<0.001） were influencing factors for treatment indication based on liver pathology in group 1； HBeAg （OR=1.978， 95%CI： 1.269 — 3.082， P=0.003）， age （OR=1.048， 95%CI： 1.025 — 1.071， P<0.001）， GGT （OR=1.016， 95%CI： 1.001 — 1.031， P=0.041）， and PLT （OR=0.995， 95%CI： 0.991 — 1.000， P=0.049） were influencing factors in group 2； age （OR=1.040， 95%CI： 1.014 — 1.066， P=0.002）， ALT （OR=1.047， 95%CI： 1.005 — 1.092， P=0.029）， HBV DNA （OR=0.817， 95%CI： 0.736 — 0.907， P<0.001）， and LIF-5 （OR=7.382， 95%CI： 1.151 — 47.330， P=0.035） were influencing factors in group 3； age （OR=1.054， 95%CI： 1.031 — 1.077， P<0.001）， ALT （OR=1.061， 95%CI： 1.016 — 1.107， P=0.008）， and HBV DNA （OR=0.825， 95%CI： 0.743 — 0.917， P<0.001） were influencing factors in group 4. The diagnostic performance for identifying ≥G2 liver inflammation， ≥S2 liver fibrosis， and treatment indication in groups 1 — 4 had an AUC of >0.7； group 1 showed the lowest sensitivity （28.76%） and the highest specificity， positive predictive value， positive likelihood ratio， and negative likelihood ratio in judging treatment indication； group 2 had the highest sensitivity and negative predictive value and the lowest negative likelihood ratio； groups 3 and 4 had similar diagnostic indicators. ConclusionIn patients with chronic HBV infection and a persistently low ALT level， the severity of liver histopathological injury and the constituent ratio of significant liver histopathological injury decrease with the reduction in ALT level. A higher non-treatment threshold or ULN of ALT can help to identify the patients requiring treatment （with a higher specificity）， while a lower non-treatment threshold or ULN of ALT can help to identify the patients who do not require treatment （with a higher sensitivity）.

Objective:To explore the therapeutic strategy for laryngeal cysts in infants. Methods:A retrospective analysis of the clinical data of 19 children with laryngeal cysts treated in Kunming Children's Hospital from January 2020 to January 2023. All patients were diagnosed through electronic laryngoscopy examination. Twelve neonates were admitted to the neonatal intensive care unit. Five of them received mechanical ventilation with tracheal intubation before surgery due to severe respiratory distress, and seven received oxygen therapy with a head mask. The remaining seven children were admitted to Department of Otolaryngology Head and Neck Surgery, of which three cases were treated with oxygen therapy through a mask during sleep due to frequent shortness of breath during sleep. All patients underwent low-temperature plasma radiofrequency ablation under general anesthesia to remove the cysts. Results:Three newborns were unable to have their tracheal tubes removed due to complications with pneumonia after surgery, while the rest of the children were able to have their tubes successfully removed after complete anesthesia, and no gastric tubes were placed. All postoperative respiratory difficulties in the children disappeared, and there were no complications such as bleeding, hoarseness, or laryngeal stenosis. Five pediatric patients had incomplete relief of laryngeal ringing symptoms one month after surgery, and electronic laryngoscopy diagnosed laryngeal softening. Regular follow-up is recommended. One child relapsed 4 months after surgery and underwent a follow-up surgery six months later without recurrence. Conclusion:Endoscopic low-temperature plasma radiofrequency ablation is an effective surgical method for treating laryngeal cysts, with a low postoperative recurrence rate. Laryngeal cysts may be accompanied by laryngeal softening, which may be a possible reason for the postoperative symptoms not improving.
Humans ; Retrospective Studies ; Cysts/surgery* ; Laryngeal Diseases/surgery* ; Infant ; Laryngoscopy ; Infant, Newborn ; Male ; Female ; Radiofrequency Ablation

Cancer immunotherapy is currently a very promising therapeutic strategy for treating tumors. However, its effectiveness is restricted by insufficient antigenicity and an immunosuppressive tumor microenvironment (ITME). Pyroptosis, a unique form of programmed cell death (PCD), causes cells to swell and rupture, releasing pro-inflammatory factors that can enhance immunogenicity and remodel the ITME. Nanomaterials, with their distinct advantages and different techniques, are increasingly popular, and nanomaterial-based delivery systems demonstrate significant potential to potentiate, enable, and augment pyroptosis. This review summarizes and discusses the emerging field of nanomaterials-induced pyroptosis, focusing on the mechanisms of nanomaterials-induced pyroptosis pathways and strategies to activate or enhance specific pyroptosis. Additionally, we provide perspectives on the development of this field, aiming to accelerate its further clinical transition.