Tumors exhibit abnormal glucose metabolism, consuming excessive glucose and excreting lactate, which constructs a tumor microenvironment that facilitates cancer progression and disrupts immunotherapeutic efficacy. Currently, tumor glucose metabolic dysregulation to reshape the immunosuppressive microenvironment and enhance immunotherapy efficacy is emerging as an innovative therapeutic strategy. However, glucose metabolism modulators lack specificity and still face significant challenges in overcoming tumor delivery barriers, microenvironmental complexity, and metabolic heterogeneity, resulting in poor clinical benefit. Nanomedicines, with their ability to selectively target tumors or immune cells, respond to the tumor microenvironment, co-deliver multiple drugs, and facilitate combinatorial therapies, hold significant promise for enhancing immunotherapy through tumor glucose metabolic reprogramming. This review explores the complex interactions between tumor glucose metabolism-specifically metabolite transport, glycolysis processes, and lactate-and the immune microenvironment. We summarize how nanomedicine-mediated reprogramming of tumor glucose metabolism can enhance immunotherapy efficacy and outline the prospects and challenges in this field.

To summarize the nursing experience of 5 patients with severe ARDS complicated with hypercapnia who underwent extracorporeal carbon dioxide removal(ECCO2R).Key points of nursing care included:establishing a rapid emergency response nursing team for ECCO2R;PETCO2 real-time monitoring to grasp the timing of the machine;ensuring continuity of treatment and improving the removal efficiency;respiratory-related monitoring;prevention of complications of blood coagulation and hypothermia;and weaning from extracorporeal carbon dioxide removal.After careful treatment and care,all the 5 patients were successfully removed from ECCO2R treatment.

Objective:Analysis of the influencing factors of maternal oral health care behavior based on the health belief model.Methods:From July to December 2023, a cross-sectional survey was conducted in Peking Union Medical College Hospital on 316 pregnant women who received the health belief questionnaire and self-efficacy scale。 t test and χ2 test were used to analyze the factors affecting the oral health care behavior of pregnant women from the perspective of social psychology. Results:Among the 316 pregnant women included, 110(34.8%) had poor daily oral health care behavior, 120 (38.1%)did not have oral examination before or during pregnancy. The health beliefs of pregnant women in overall oral care were not high, with a score of 6.63+3.23, Median score is 7 (5).Perceived susceptibility to oral diseases ( OR=1.51, 95% CI:1.026-2.213), self-efficacy of daily living ( OR=2.64, 95% CI: 1.384-5.040), self-efficacy of oral examination ( OR=1.74, 95% CI:1.184-2.570) were independent factors of daily oral health care behavior in pregnant women. Health motivation ( OR=2.47, 95% CI:1.474-4.126) and self-efficacy of oral examination ( OR=4.17, 95% CI:2.626-6.619) were independent factors of oral examination behavior before and during pregnancy. Conclusion:Health beliefs of maternal oral health, especially perceived susceptibility, health motivation and self-efficacy are closely related to maternal oral health care behaviors. To improve the health belief and self-efficacy of pregnant women′s oral health care and avoid potential obstacles, which could be conducive to the effective promotion of oral health care for pregnant women.

Objective:Analysis of the influencing factors of maternal oral health care behavior based on the health belief model.Methods:From July to December 2023, a cross-sectional survey was conducted in Peking Union Medical College Hospital on 316 pregnant women who received the health belief questionnaire and self-efficacy scale。 t test and χ2 test were used to analyze the factors affecting the oral health care behavior of pregnant women from the perspective of social psychology. Results:Among the 316 pregnant women included, 110(34.8%) had poor daily oral health care behavior, 120 (38.1%)did not have oral examination before or during pregnancy. The health beliefs of pregnant women in overall oral care were not high, with a score of 6.63+3.23, Median score is 7 (5).Perceived susceptibility to oral diseases ( OR=1.51, 95% CI:1.026-2.213), self-efficacy of daily living ( OR=2.64, 95% CI: 1.384-5.040), self-efficacy of oral examination ( OR=1.74, 95% CI:1.184-2.570) were independent factors of daily oral health care behavior in pregnant women. Health motivation ( OR=2.47, 95% CI:1.474-4.126) and self-efficacy of oral examination ( OR=4.17, 95% CI:2.626-6.619) were independent factors of oral examination behavior before and during pregnancy. Conclusion:Health beliefs of maternal oral health, especially perceived susceptibility, health motivation and self-efficacy are closely related to maternal oral health care behaviors. To improve the health belief and self-efficacy of pregnant women′s oral health care and avoid potential obstacles, which could be conducive to the effective promotion of oral health care for pregnant women.

Drug adulteration and contamination are serious threats to human health therefore,their accurate monitoring is very important.Allopurinol(Alp)and theophylline(Thp)are commonly used drugs for the treatment of gout and bronchitis,while their isomers hypoxanthine(Hyt)and theobromine(Thm)have no effect and affect the efficacy of the drug.In this work,the drug isomers of Alp/Hyt and Thp/Thm are simply mixed with α-,β-,y-cyclodextrin(CD)and metal ions and separated using trapped ion mobility spectrometry-mass spectrometry(TIMS-MS).TIMS-MS results showed that Alp/Hyt and Thp/Thm iso-mers could interact with CD and metal ions and form corresponding binary or ternary complexes to achieve their TIMS separation.Different metal ions and CDs showed different separation effect for the isomers,among which Alp and Hyt could be successfully distinguished from the complexes of[Alp/Hyt+y-CD+Cu-H]+with separation resolution(Rp-p)of 1.51;whereas Thp and Thm could be baseline separated by[Thp/Thm+y-CD+Ca-H]+with Rp-p of 1.96.Besides,chemical calculations revealed that the complexes were in the inclusion forms,and microscopic interactions were somewhat different,making their mobility separation.Moreover,relative and absolute quantification was investigated with an internal standard to determine the precise isomers content,and good linearity(R2＞0.99)was ob-tained.Finally,the method was applied for the adulteration detection where different drugs and urine were analyzed.In addition,due to the advantages of fast speed,simple operation,high sensitivity,and no chromatographic separation required,the proposed method provides an effective strategy for the drug adulteration detection of isomers.

Objective:To develop and validate the models based on mixed enhanced computed tomography (CT) radiomics and deep learning features, and evaluate the efficacy for differentiating pancreatic adenosquamous carcinoma (PASC) from pancreatic ductal adenocarcinoma (PDAC) before surgery.Methods:The clinical data of 201 patients with surgically resected and histopathologically confirmed PASC (PASC group) and 332 patients with surgically resected histopathologically confirmed PDAC (PDAC group) who underwent enhanced CT within 1 month before surgery in the First Affiliated Hospital of Naval Medical University from January 2011 to December 2020 were retrospectively collected. The patients were chronologically divided into a training set (treated between January 2011 and January 2018, 156 patients with PASC and 241 patients with PDAC) and a validation set (treated between February 2018 and December 2020, 45 patients with PASC and 91 patients with PDAC) according to the international consensus on the predictive model. The nnU-Net model was used for pancreatic tumor automatic segmentation, the clinical and CT images were evaluated, and radiomics features and deep learning features during portal vein phase were extracted; then the features were dimensionally reduced and screened. Binary logistic analysis was performed to develop the clinical, radiomics and deep learning models in the training set. The models' performances were determined by area under the ROC curve (AUC), sensitivity, specificity, accuracy, and decision curve analysis (DCA).Results:Significant differences were observed in tumor size, ring-enhancement, upstream pancreatic parenchymal atrophy and cystic degeneration of tumor both in PASC and PDAC group in the training and validation set (all P value <0.05). The multivariable logistic regression analysis showed the tumor size, ring-enhancement, dilation of the common bile duct and upstream pancreatic parenchymal atrophy were associated with PASC significantly in the clinical model. The ring-enhancement, dilation of the common bile duct, upstream pancreatic parenchymal atrophy and radiomics score were associated with PASC significantly in the radiomics model. The ring-enhancement, upstream pancreatic parenchymal atrophy and deep learning score were associated with PASC significantly in the deep learning model. The diagnostic efficacy of the deep learning model was highest, and the AUC, sensitivity, specificity, and accuracy of the deep learning model was 0.86 (95% CI 0.82-0.90), 75.00%, 84.23%, and 80.60% and those of clinical and radiomics models were 0.81 (95% CI 0.76-0.85), 62.18%, 85.89%, 76.57% and 0.84 (95% CI 0.80-0.88), 73.08%, 82.16%, 78.59% in the training set. In the validation set, the area AUC, sensitivity, specificity, and accuracy of deep learning model were 0.78 (95% CI 0.67-0.84), 68.89%, 78.02% and 75.00%, those of clinical and radiomics were 0.72 (95% CI 0.63-0.81), 77.78%, 59.34%, 65.44% and 0.75 (95% CI 0.66-0.84), 86.67%, 56.04%, 66.18%. The DCA in the training and validation sets showed that if the threshold probabilities were >0.05 and >0.1, respectively, using the deep learning model to distinguish PASC from PDAC was more beneficial for the patients than the treat-all-patients as having PDAC scheme or the treat-all-patients as having PASC scheme. Conclusions:The deep learning model based on CT automatic image segmentation of pancreatic neoplasm could effectively differentiate PASC from PDAC, and provide a new non-invasive method for confirming PASC before surgery.

Marine microorganisms, especially marine fungi, have historically proven their value as a prolific source for structurally novel and pharmacologically active secondary metabolites (Deshmukh et al., 2018; Carroll et al., 2022). The corals constitute a dominant part of reefs with the highest biodiversity, and harbor highly diverse and abundant microbial symbionts in their tissue, skeleton, and mucus layer, with species-specific core members that are spatially partitioned across coral microhabitats (Wang WQ et al., 2022). The coral-associated fungi were very recently found to be vital producers of structurally diverse compounds, terpenes, alkaloids, peptides, aromatics, lactones, and steroids. They demonstrate a wide range of bioactivity such as anticancer, antimicrobial, and antifouling activity (Chen et al., 2022). The genetically powerful genus Emericella (Ascomycota), which has marine and terrestrial sources, includes over 30 species and is distributed worldwide. It is considered a rich source of diverse secondary metabolites with antimicrobial activity or cytotoxicity (Alburae et al., 2020). Notably, Emericella nidulans, the sexual state of a classic biosynthetic strain Aspergillus nidulans, was recently reported as an important source of highly methylated polyketides (Li et al., 2019) and isoindolone-containing meroterpenoids (Zhou et al., 2016) with unusual skeletons.
Animals ; Aspergillus nidulans ; Polyketides/chemistry* ; Anthozoa/microbiology* ; Anti-Infective Agents/pharmacology* ; Alkaloids

Objective: To understand the online learning related screen use duration and screen types in school aged children in Shanghai during the COVID-19 epidemic. Methods: Random clustering sampling was used to select 5 591 parents of students from 8 primary and junior schools that are in the sampling pool of the national myopia survey in districts of Jiading, Pudong and Baoshan in Shanghai in April 2020. Electronic questionnaire was administered to parents regarding their child s online learning related screen use. Results: On average, the median weekly duration of online learning related screen use was 13.33 hours, the curricular and extracurricular parts of which were 10(8.75，16.67) and 0(0，3.33) hours, respectively. About 29.44% of investigated school aged children only used small size screen for online learning. Children in higher grades, being myopic and parents neither being myopic were associated with reporting higher weekly duration( P <0.05); children in higher grades of primary school and parents neither being myopic were associated with a higher likelihood of using small size screen for online learning( P <0.05). Conclusion At the early stage of the COVID-19 epidemic, the burden associated with online learning related screen use was high in school aged children in Shanghai. Health education regarding online learning related screen use should be addressed in parents to guide their children to use screen appropriately.

Objective:To study the influencing factors for shoulder stiffness after rotator cuff tear.Methods:The data of 228 patients were retrospectively analyzed who had been diagnosed with rotator cuff tear by arthroscopic surgery at Department of Articular Surgery, Hospital Affiliated to Chengde Medical College from June 2019 to May 2021. Their baseline data were recorded immediately after admission, including possible risk factors for shoulder stiffness. The patients were divided into a stiffness group and a non-stiffness group based on passive range of motion of shoulder joint. Univariate and multivariate analyses were performed to find out the influencing factors for shoulder stiffness after rotator cuff tear.Results:Preliminary univariate analysis showed that advanced age, smoking history, misdiagnosis history, no standardized physiotherapy history, high body mass index (BMI) and long duration of disease were all likely risk factors for shoulder stiffness in patients with rotator cuff tear ( P<0.05). Multivariate analysis confirmed that advanced age( OR=1.474, 95% CI: 1.013~2.145, P=0.043), smoking history( OR=2.239, 95% CI: 1.147~4.368, P=0.018), no standardized physiotherapy history( OR=0.167, 95% CI: 0.065~0.424, P<0.001), high BMI( OR=3.029, 95% CI: 1.657~5.536, P<0.001) and long duration of disease ( OR=1.775, 95% CI: 1.384~2.276, P<0.001) were the risk factors for shoulder stiffness. Conclusion:Age>60 years, smoking history, misdiagnosis history, no standardized physiotherapy history, high body mass index and long course of disease may be the important influencing factors for shoulder stiffness after rotator cuff tear.