Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

DNA origami is a powerful technique for generating nanostructures with dynamic properties and intelligent controllability. The precise geometric shapes, high programmability, and excellent biocompatibility make DNA origami nanostructures an emerging drug delivery vehicle. The shape, size of the carrier material, as well as the loading and release of drugs are important factors affecting the bioavailability of drugs. This paper focuses on the controllable design of DNA origami nanostructures, efficient drug loading, and intelligent drug release. It summarizes the cutting-edge applications of DNA origami technology in biomedicine, and discusses areas where researchers can contribute to further advancing the clinical application of DNA origami carriers.

Aim To explore the mechanism of the effect of rosiglitazone(Rsg)on the pancreatic cancer in diabetic mice based on the impact of PPARγ on glu-cose transport and metabolism.Methods A high-fat and high sugar diet combined with STZ was used to construct T2DM model;T2DM mice and normal mice were subcutaneously injected with PANC02 cells to construct a transplanted tumor model.T2DM trans-planted tumor mice and normal transplanted tumor mice were divided into the following groups:Rsg,PPARy inhibitor(PIN-2),rosiglitazone+PPARγ in-hibitor(Rsg+PIN-2),and normal transplanted tumor mice(NDM)and T2DM transplanted tumor mice(DM)were used as control groups,respectively.Tis-sue samples were collected after intervention.Tissue pathological changes were observed by HE staining.The expressions of Ki67 and PCNA proteins were de-tected by immunohistochemistry.Cell apoptosis was detected by TUNEL assay.The expression of PPARγwas detected by immunofluorescence.The expressions of Glucokinase,GLUT2,Nkx6.1,PDX-1RT-PCR were determined by Western blot.Results Rsg could significantly reduce the tumor mass,pathological chan-ges,Ki67 and PCNA expression of transplanted tumors(P＜0.05),increase cell apoptosis and the expression of PPARγ,Glucokinase,GLUT2,Nkx6.1,PDX-1 proteins in NDM and DM mice(P＜0.05).PIN-2 could reverse the indicator changes caused by Rsg in NDM and DM mice.However,compared with NDM mice,the above related indicators of the DM group mice were more sensitive to Rsg and PIN-2.Conclu-sions Compared to non-diabetic pancreatic cancer,rosiglitazone can more sensitively inhibit the prolifera-tion of pancreatic cancer with T2DM,induce apopto-sis,and reprogram the metabolism of pancreatic cancer with T2DM by activating PPA Rγ and altering the ex-pression of glucose and lipid metabolism genes,there-by exerting an anti-cancer effect.

OBJECTIVE: This study assesses the impact of iodine-rich processed foods and dining places on the iodine nutritional status of children. METHODS: School-aged children (SAC) in seven provinces in China were selected by school-based multi-stage sampling. Urinary iodine, salt iodine, and thyroid volume (TVOL) were determined. Questionnaires were used to investigate dining places and iodine-rich processed foods. The water iodine was from the 2017 national survey. Multi-factor regression analysis was used to find correlations between variables. RESULTS: Children ate 78.7% of their meals at home, 15.1% at school canteens, and 6.1% at other places. The percentage of daily iodine intake from water, iodized salt, iodine-rich processed foods, and cooked food were 1.0%, 79.2%, 1.5%, and 18.4%, respectively. The salt iodine was correlated with the urinary iodine and TVOL, respectively (r = 0.999 and -0.997, P < 0.05). The iodine intake in processed foods was weakly correlated with the TVOL (r = 0.080, P < 0.01). Non-iodized salt used in processed foods or diets when eating out had less effect on children's iodine nutrition status. CONCLUSION Iodized salt remains the primary source of daily iodine intake of SAC, and processed food has less effect on iodine nutrition. Therefore, for children, iodized salt should be a compulsory supplement in their routine diet.
Humans ; Child ; Nutritional Status ; Cross-Sectional Studies ; Iodine ; Sodium Chloride, Dietary/analysis* ; China ; Water

Cross-Sectional Studies ; Dietary Supplements ; Female ; Humans ; Iodides ; Iodine ; Nutritional Status ; Pregnancy ; Pregnancy Complications ; Pregnant Women ; Thyroid Gland ; Thyrotropin

GeXIVA[1,2] is a new type of conotoxin recently discovered in the transcriptome of Conus generalis and it is expected to be used clinically as a new type of analgesic. This study established and verified a sandwich enzyme-linked immunosorbent assay method for the marine drug GeXIVA[1,2] in the plasma of rats and Beagle dogs. The mouse monoclonal antibody 4B2 and biotin-labeled rabbit polyclonal antibody 2# were developed. The checkerboard method was used to optimize the antibody pairing concentration, minimum dilution ratio, incubation temperature, and incubation time to establish an antibody sandwich ELISA detection method. Verify the established testing methods. The established ELISA method has a quantitative range of 1.25-80 ng·mL^-1 in rat and Beagle plasma. The precision, accuracy, selectivity, specificity, stability, dilution linearity, and hook effect all meet the requirements for biological sample analysis. All the procedures for the animal experiments were approved by the Animal Ethics Committee of the Institute (Permit Number: IACUC-DWZX-2020-698). This method can support the preclinical pharmacokinetic study of the marine drug GeXIVA.

Objective:To compare magnetic resonance imaging (MRI)-based and computed tomography (CT)-based target volume delineation and dose coverage in partial breast irradiation (PBI) for patients with breast cancer, aiming to explore the application value of MRI localization in PBI after breast-conserving surgery.Methods:Twenty-nine patients with early breast cancer underwent simulating CT and MRI scans in a supine position. The cavity visualization score (CVS) of tumor bed (TB) was evaluated. The TB, clinical target volume (CTV), planning target volume (PTV) were delineated on CT and MRI images, and then statistically compared. Conformity indices (CI) between CT- and MRI-defined target volumes were calculated. PBI treatment plan of 40 Gy in 10 fractions was designed based on PTV-CT, and the dose coverage for PTV-MRI was evaluated.Results:The CVS on CT and MRI images was 2.97±1.40 vs. 3.10±1.40( P=0.408). The volumes of TB, CTV, PTV on MRI were significantly larger than those on CT, (24.48±16.60) cm 3vs. (38.00±19.77) cm 3, (126.76±56.81) cm 3vs. (168.42±70.54) cm 3, (216.63±81.99) cm 3vs. (279.24±101.55) cm 3, respectively, whereas the increasing percentage of CTV and PTV were significantly smaller than those of TB. The CI between CT-based and MRI-based TB, CTV, PTV were 0.43±0.13, 0.66±0.11, 0.70±0.09( P<0.001), respectively. The median percentage of PTV-MRI receiving 40 Gy dose was 81.9%(62.3% to 92.4%), significantly lower than 95.6%(95.0%~97.5%) of PTV-CT. Conclusions:The CVS between CT and MRI is not significantly different, but the MRI-based TB, CTV, PTV are significantly larger than CT-based values. The PTV-MRI is of underdose if PBI treatment plan is designed for PTV-CT. As a supplement of CT scan, MRI can enhance the accuracy of TB delineation after breast-onserving surgery.

Objective:To establish an artificial intelligence (AI)-assisted diagnostic system for lung cancer via deep transfer learning.Methods:The researchers collected 519 lung pathologic slides from 2016 to 2019, covering various lung tissues, including normal tissues, adenocarcinoma, squamous cell carcinoma and small cell carcinoma, from the Beijing Chest Hospital, the Capital Medical University. The slides were digitized by scanner, and 316 slides were used as training set and 203 as the internal test set. The researchers labeled all the training slides by pathologists and establish a semantic segmentation model based on DeepLab v3 with ResNet-50 to detect lung cancers at the pixel level. To perform transfer learning, the researchers utilized the gastric cancer detection model to initialize the deep neural network parameters. The lung cancer detection convolutional neural network was further trained by fine-tuning of the labeled data. The deep learning model was tested by 203 slides in the internal test set and 1 081 slides obtained from TCIA database, named as the external test set.Results:The model trained with transfer learning showed substantial accuracy advantage against the one trained from scratch for the internal test set [area under curve (AUC) 0.988 vs. 0.971, Kappa 0.852 vs. 0.832]. For the external test set, the transferred model achieved an AUC of 0.968 and Kappa of 0.828, indicating superior generalization ability. By studying the predictions made by the model, the researchers obtained deeper understandings of the deep learning model.Conclusions:The lung cancer histopathological diagnostic system achieves higher accuracy and superior generalization ability. With the development of histopathological AI, the transfer learning can effectively train diagnosis models and shorten the learning period, and improve the model performance.

Objective:To analyze the odorous components and their contents in raw products, wine-processed products, vinegar-processed products and wheat bran-processed products of Periplaneta americana. Method:Headspace solid-phase microextraction (HS-SPME) was used to extract the volatile components from different processed products, the chemical compositions were analyzed by gas chromatography-mass spectrometry (GC-MS), and the relative contents of each component was calculated by peak area normalization method. Result:A total of 41, 32, 40 and 47 components were respectively identified from raw, wine-processed, vinegar-processed and wheat bran-processed products of P. americana, involving a total of 13 common components. Conclusion:The odorous components in the raw products are mainly derived from aldehydes, alcohols, amines, hydrocarbons and other volatile substances. Odorous components can be reduced effectively and flavoring substances can be increased by wine, vinegar and wheat bran processing. This study provides a scientific basis for the further study of correcting odor of P. americana, it also provides a reference for analysis and correction of odor of animal medicines.

Objective: To assess the safety and feasibility for treating the patients with severe external carotid artery (ECA) stenosis and ipsilateral internalcarotid artery (ICA)occlusion by external carotid artery steting (ECAS). Methods: A total of 17 consecutive patients with severe ECA stenosis and ipsilateral ICA occlusion treated in our hospital by ECAS from 2008-01 to 2013-06 were retrospectively studied. Post-operative improvements of cerebral ischemia and neurocognitive function [Mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA)] were evaluated, complications at peri-operative and 12 months follow-up period were recorded. Results: The patients' mean age was (65.4±8.0) years including 13(76.5％) male. The success rate of ECAS was 100％;2 patients had hemodynamic depression at peri-operative period and were completely recovered by 2 days treatment.1 patient suffered from contralateral minor stroke at 12 months follow-up time, the other 16 patients were without cerebral ischemia symptoms. No complication occurred at peri-operative and 12 months follow-up period. Compared with pre-operative condition, MMSE score [(25.1±1.4) vs (23.3±1.8), P<0.01] and MOCA score [(23.9±1.2) vs (22.2±1.6), P<0.01] were increased at 3 months after ECAS; both scores were continuously increasing during 12 months follow-up period. Conclusion: ECAS may improve cerebral ischemia and cognitive function in patients with severe ECA stenosis and ipsilateral ICA occlusion.