Objective: To investigate the indoor fine particulate matter (PM 2.5 ) pollution and its influencing factors in children s bedrooms using solid fuel, so as to provide evidence for effective strategy to reduce PM 2.5 pollution. Methods: From December 2019 to November 2020, 198 households (108 in the north, 90 in the south) from two pilots in the north(Jiamusi in Heilongjiang Province) and south of China (Mianyang in Sichuan Province) were selected, and status of solid fuels using were obtained through home visits, dynamic changes in PM 2.5 concentrations in children s bedrooms were monitored by using real time online instruments, and the influencing factors of PM 2.5 pollution were analyzed by using a mixed effects model. Results: During the monitoring period, the daily PM 2.5 concentrations in the northern and southern pilot were 78.33 (40.50, 154.80) and 38.54(26.20, 58.46) μg/m 3, respectively, exceeding standard rates of 44.57% and 33.22%. During the heating period, the daily PM 2.5 concentrations in the northern and southern pilot were 212.50(133.60,244.10) and 104.42(73.97, 134.90) μg/m 3, respectively, with over standard rates of 96.75% and 86.96%. The mixed effects model analysis results showed that children s bedroom PM 2.5 concentrations were associated with solid fuel usage duration, window opening time, room layout (shared entrance door between kitchen and bedroom), indoor smoking, indoor humidity, and solid fuel use in the bedroom ( β =0.19, -0.05, 1.20, 0.43, 0.02, 0.35, all P <0.05). Conclusion Solid fuel combustion significantly comtributes to PM 2.5 pollution in children s bedrooms, with more pronounced impacts observed in northern China compared to southern regions.

The presence of physiological barriers in the eye （both external and internal） makes conventional ophthalmic medications （eye drops， ointments， gels， etc.） less bioavailable and difficult to reach the posterior segment of the eye. Although intravitreal injection can deliver drugs to the posterior segment of the eye， it has disadvantages such as infection， injury， and poor tolerance. Ophthalmic microneedle breaks through the intra- and extra-ocular barriers， enabling the drug to reach the target site accurately and to be released continuously greatly avoiding intraocular infections and injuries， and improving the bioavailability of the drug， which has obvious advantages as an ophthalmic drug delivery tool. Ophthalmic microneedle can be classified into hollow microneedle， dissolving microneedle， and coated microneedle according to the usage methods. Each type of microneedle has its own advantages and has shown satisfactory performance in the treatment of diseases such as bacterial and fungal keratitis， glaucoma， exudative age-related macular degeneration， diabetic macular edema， non-infectious uveitis， corneal neovascularization， and even choroidal melanoma.

BACKGROUND:Zinc-based alloy medical implant materials have excellent mechanical properties,complete degradability and good biocompatibility,and are mainly used in orthopedic implants,cardiovascular stents,bile duct stents,tracheal stents,nerve catheters,etc. OBJECTIVE:To review the research progress of biodegradable zinc-based alloys in bone defect repair and prospect the promising research direction and achievements of zinc-based materials. METHODS:After searching PubMed,Web of Science,WanFang Data,and CNKI databases from the establishment of the database to June 2023,various relevant articles on biodegradable zinc-based alloys for bone implant material research were collected.The basic characteristics of biodegradable zinc based alloys were summarized,and the role of zinc-based alloys in promoting bone tissue repair was sorted and summarized.The current research hotspots and shortcomings were discussed. RESULTS AND CONCLUSION:(1)Zinc-based alloys have good biocompatibility.Using zinc-based alloys as the matrix material,with the help of scaffold structure construction technology and coating optimization process,the bone conductivity of zinc-based alloys will be effectively improved,and their degradation products will have efficient bone induction to regulate the gene expression of osteoblasts and osteoclasts,thereby promoting the repair and reconstruction of bone defects.(2)However,in the research on optimizing zinc-based alloys,the coating process is relatively insufficient,and additive loading technology is still lacking.(3)Zinc-based alloys have excellent mechanical and biological properties.Through special processes,their bone conductivity and osteoinductivity can be increased to effectively improve their ability to promote bone repair and reconstruction,and it is expected to further achieve the development of personalized transplant materials.Further research and development are needed to optimize the integration of coating and additive loading technologies into zinc-based alloys.

Objective To develop and validate a model to predict the risk of radiation-induced lung injury (RILI) and assess its clinical feasibility. Methods Clinical data from 125 patients with non-small cell lung cancer (NSCLC) were included in the study. The patients were divided into training group (88 cases) and validation group (38 cases). Key predictive factors were identified using univariate and multivariate logistic regression analyses combined with least absolute shrinkage and selection operator (LASSO) regression. A predictive model was constructed and evaluated using a nomogram, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results The key variables identified by the model were tumor volume (P = 0.017), Eastern Cooperative Oncology Group performance status score (P = 0.035), 95% of the minimum dose to the target volume (P = 0.028), percentage of bilateral lung volume receiving 20 Gy of radiation (P < 0.001), and neutrophil-to-lymphocyte ratio (P = 0.021). The ROC curve showed that the areas under the curve (AUC) for the model in the training and validation groups were 0.987 and 0.992, respectively, indicating good predictive ability. The calibration curve and decision curve further confirmed the accuracy and clinical practicability of the model. Conclusion The predictive model proposed in this study can accurately assess the risk of developing RILI in patients with NSCLC who have undergone radiotherapy, demonstrating its potential value in clinical practice.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Hepatic Epstein-Barr virus–positive inflammatory follicular dendritic cell sarcoma (EBV+ IFDCS) represents a rare form of liver malignancy. The absence of distinct clinical and radiological characteristics, compounded by its rare occurrence, contributes to a challenging diagnosis. Here, we report a case of a 54-year-old Chinese female with a background of chronic hepatitis B virus treated with entecavir and complicated by advanced fibrosis presenting with a liver mass found on her annual surveillance ultrasound. Hepatectomy was performed under clinical suspicion of hepatocellular carcinoma. Immunomorphologic characteristics of the tumor were consistent with EBV+ IFDCS with distinct non-caseating granulomatous inflammation. Our case illustrates the importance of considering EBV+ IFDCS in the differential diagnosis of hepatic inflammatory lesions. Awareness of this entity and its characteristic features is essential for accurately diagnosing and managing this rare neoplasm.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.