Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Peri-implant keratinized mucosa (PIKM) augmentation refers to surgical procedures aimed at increasing the width of PIKM. Consensus reports emphasize the necessity of maintaining a minimum width of PIKM to ensure long-term peri-implant health. Currently, several surgical techniques have been validated for their effectiveness in increasing PIKM. However, the selection and application of PIKM augmentation methods may present challenges for dental practitioners due to heterogeneity in surgical techniques, variations in clinical scenarios, and anatomical differences. Therefore, clear guidelines and considerations for PIKM augmentation are needed. This expert consensus focuses on the commonly employed surgical techniques for PIKM augmentation and the factors influencing their selection at second-stage surgery. It aims to establish a standardized framework for assessing, planning, and executing PIKM augmentation procedures, with the goal of offering evidence-based guidance to enhance the predictability and success of PIKM augmentation.
Humans ; Consensus ; Dental Implants ; Mouth Mucosa/surgery* ; Keratins

Paclitaxel (PTX), a valuable natural product derived from Taxus species, exhibits remarkable anti-cancer properties. It penetrates nanopores in microtubule walls, interacting with tubulin on the lumen surface and disrupting microtubule dynamics, thereby inducing cytotoxic effects in cancer cells. PTX and its derivatives have gained approval for treating various diseases due to their low toxicity, high efficiency, and broad-spectrum application. The widespread success and expanding applications of PTX have led to increased demand, raising concerns about accessibility. Consequently, researchers globally have focused on developing alternative production methods and applying nanocarriers in PTX delivery systems to enhance bioavailability. This review examines the challenges and advancements in PTX sourcing, production, physicochemical properties, anti-cancer mechanisms, clinical applications, trials, and chemo-immunotherapy. It aims to provide a comprehensive reference for the rational development and effective utilization of PTX.
Humans ; Paclitaxel/pharmacology* ; Antineoplastic Agents, Phytogenic/pharmacology* ; Neoplasms/drug therapy* ; Animals ; Taxus/chemistry*

Mitochondria are the main site of energy metabolism within cells,generating a substantial amount of ATP to supply energy to the human body.Research has shown that alterations in mitochondrial structure and function exist in individuals with schizophrenia,suggesting their potential impact on the onset of psychiatric disorders and clinical treatment efficacy.Therefore,understanding the research progress on the genetic mechanisms,pathological processes,image manifestations of schizophrenia and mitochondrial quality control,and summarizing the relevant evidence of mitochondrial-related targets as potential therapeutic targets for schizophrenia,can provide references for further research.

Schizophrenia is a common chronic mental disorder.Cognitive dysfunction is one of its core symptoms,which severely affects the social functioning of patients.Currently,antipsychotic medication treatments have poor efficacy in improving cognitive functions.Recent studies have found that metformin can improve cognitive dysfunction in patients with schizophrenia.However,the mechanism of action remains unclear.This review summarizes the therapeutic effects of metformin on cognitive dysfunction in schizophrenia patients such as improving insulin resistance,repairing neuronal damage,regulating neuroimmunity,and combating oxidative stress,thereby providing new insights for the treatment of cognitive dysfunction in schizophrenia.

Objective:To construct a predictive model of radiomics based on laparoscopic grayscale ultrasound features and investigate its value in predicting microvascular invasion (MVI) of hepatocellular carcinoma (HCC) during laparoscopic liver resection.Methods:A total of 74 patients (74 lesions)with HCC confirmed by postoperative pathology, who underwent a laparoscopic ultrasonography during laparoscopic hepatectomy were prospectively enrolled in Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from March 2022 to August 2023. The general clinical information of the patients was recorded, and the features were extracted and screened from tumor regions in gray-scale ultrasound images, and eventually the radiomics prediction models were constructed, respectively. Pathological results were used as gold standard to compare the effectiveness of different models in predicting MVI.Results:In the 74 HCC lesions, 12 lesions were MVI positive.The MVI imaging prediction model of HCC lesions was constructed from the screened clinical features, laparoscopic gray scale ultrasound image features, as well as combined screened clinical features, respectively. The obtained data sets were randomly divided into 5 parts (4 parts with 15 lesions, 1 part with 14 lesions), and the effectiveness of the model was trained and tested by the method of 5 folds interaction validation. The performance of support vector machine(SVM) radiomics model based on the characteristics of laparoscopic gray scale ultrasound in predicting the MVI of HCC was the best. Compared with clinical model and combined Adaboost model, the SVM, radiomics model had higher area under ROC curve (0.836 vs 0.696, 0.804), accuracy (0.852 vs 0.687, 0.838), sensitivity (0.900 vs 0.900, 0.833) and specificity (0.837 vs 0.644, 0.838). Conclusions:The radiomics model based on the characteristics of laparoscopic gray-scale ultrasound is an innovative potential approach to predict the MVI status of HCC lesions during laparoscopic hepatectomy.

FLASH radiotherapy (FLASH-RT) has garnered considerable attention globally in recent years. Compared to conventional radiotherapy, FLASH-RT can deliver the total radiation dose to the target volume in an extremely short time, reducing the radiation-induced damage to normal tissue while maintaining similar anti-tumor effects. FLASH-RT has been in the clinical trial stage, with several clinical research result being reported. Based on the collected global clinical research result of FLASH-RT in recent years, this study systematically reviewed FLASH-RT′s safety, radiation-related side effects, treatment efficacy, opportunities, and challenges in clinical trials.

Periodontitis is a chronic inflammatory disease marked by a dysregulated immune microenvironment, posing formidable challenges for effective treatment. The disease is characterized by an altered glucose metabolism in macrophages, specifically an increase in aerobic glycolysis, which is linked to heightened inflammatory responses. This suggests that targeting macrophage metabolism could offer a new therapeutic avenue. In this study, we developed an immunometabolic intervention using quercetin (Q) encapsulated in bioadhesive mesoporous polydopamine (Q@MPDA) to treat periodontitis. Our results demonstrated that Q@MPDA could reprogram inflammatory macrophages to an anti-inflammatory phenotype (i.e., from-M1-to-M2 repolarization). In a murine periodontitis model, locally administered Q@MPDA reduced the presence of inflammatory macrophages, and decreased the levels of inflammatory cytokines (IL-1β and TNF-α) and reactive oxygen species (ROS) in the periodontium. Consequently, it alleviated periodontitis symptoms, reduced alveolar bone loss, and promoted tissue repair. Furthermore, our study revealed that Q@MPDA could inhibit the glycolysis of inflammatory macrophages while enhancing oxidative phosphorylation (OXPHOS), facilitating the shift from M1 to M2 macrophage subtype. Our findings suggest that Q@MPDA is a promising treatment for periodontitis via immunometabolic rewiring.

Objective:To compare the radiation chemistry effects on water molecules after ultra-high dose rate (FLASH) and conventional irradiation.Methods:Both FLASH and conventional irradiation were applied to ultrapure water, with the hydroxyl radical yield in the homogeneous phase detected using electron paramagnetic resonance (EPR) and the hydrogen peroxide (H 2O 2) yield in the diffusion phase analyzed uuxing fluorescence probe. The liposome model was then established to investigate the radiation chemistry effect of FLASH and conventional irradiation in inducing lipid peroxidation. Results:Radiation chemistry reactions were observed in water molecules after irradiation. In the homogeneous phase, the yield of free radicals using FLASH irradiation is similar to those from conventional irradiation ( P>0.05). In the diffusion phase, the amount of H 2O 2 produced by FLASH irradiation was significantly lower than those from conventional irradiation ( t=0.49-12.81, P<0.05). The liposome model confirmed that conventional irradiation could significantly induce lipid peroxidation through the radiation chemistry effect in water molecules as compared with FLASH irradiation ( t=0.31-11.73, P<0.05). Conclusions:The radiation chemistry effect in water molecules after FLASH irradiation was significantly lower than that from conventional irradiation. This could be one of the mechanisms of FLASH effect.

ObjectiveTo analyze the microbial diversity in the rhizosphere soil of Gastrodia elata with different yields and explore the influence of soil microorganisms on the yield of G. elata. MethodThe experiment adopted the 16S DNA and ITS high-throughput sequencing technologies to study the diversity of the bacterial and fungal community in the rhizosphere soil of G. elata with high yield （GC） and low yield （DC）. ResultProteobacteria， Firmicutes， and other unidentified Bacteria were dominant in the rhizosphere soil of G. elata. The dominant rhizosphere fungi were Ascomycota， Basidiomycota， and Mortierellomycota. There was no significant difference in microbial community abundance in the high-yield and low-yield rhizosphere soil of G. elata， but there was a significant difference in species composition. Thirty-eight microbes such as Bradyrhizobium， Schleiferilactobacillus， and Archaeorhizomyces were gathered in large numbers in the high-yield rhizosphere soil， and thirty microbes such as Fusarium， Coprinellus， and Nitrosotalea were gathered in large numbers in the low-yield rhizosphere soil. At the level of genus and species， there were six different species in the high-yield and low-yield rhizosphere soil of G. elata， among which Russula mariae， Archeaeorhizomyces， and Ilyonectria were gathered in the high-yield rhizosphere soil of G. elata， while Nitrosotalea， Coprinellus disserminatus， and Fusarium were gathered in the low-yield rhizosphere soil of G. elata. ConclusionThere are different microorganisms in the rhizosphere soil of G. elata with different yields， and it is speculated that these microorganisms are related to the yields of G. elata. The research results are expected to provide a vital theoretical basis for the follow-up study of the high yield of G. elata.