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.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

Currently,electroencephalogram(EEG),functional near-infrared spectroscopy(fNIRS),and functional magnetic resonance imaging have been widely studied and applied to neuropsychiatric disorders.In recent years,the devices which can realize the simultaneous acquisition of EEG and fNIRS has been developed and gradually applied in the studies on neuropsychiatric disorders.The review provides an introduction of the techniques of synchronized detection and data analysis for EEG-fNIRS,summarizes the analysis methods and new findings of the recent studies of stroke,epilepsy,and other neuropsychiatric disorders using EEG-fNIRS,and also discusses the future research directions.

Objective:To construct a double-layer bone-on-a-chip containing bone matrix, with which the process of osteoblast and osteoclast differentiation in vitro is stimulated, aiming to provide a new platform for the development of osteoporosis medications. Methods:Software WorkSoild was used to design the double-layer and double-channel bone-on-a-chip and the template was fabricated by photolithography. With polydimethylsiloxane (PDMS) as the raw material, the main body of the chip was prepared by mold fabrication. The inlets and outlets of the four channels of the culture room were separated with bovine cortex bones and sealed with liquid storage columns. In the chip verification experiment, chips were divided into osteogenic and osteoclastic induction groups and osteogenic and osteoclastic control groups. In the osteogenic and osteoclastic induction groups, precursor cells of mouse embryonic osteoblast, MC3T3-E1 and mouse macrophage RAW264.7 were inoculated on the chip separately. Osteogenic induction lasted 14 days and osteoclastic induction 7 days. MC3T3-E1 cells and RAW264.7 cells were not induced in the osteogenic and osteoclastic control groups. The following indicators were observed: (1) Appearance and sealing performance of the chip: After the chip was prepared, photos were taken to observe its appearance and sealing tests were conducted to observe its sealing performance. (2) Biocompatibility: At 3 days after MC3T3-E1 cells were inoculated onto the chip and cultured and at 1, 3 and 5 days after RAW264.7 cells were inoculated onto the chip and cultured, the cell survival was observed with calcein acetoxymethyl ester/propidium iodide (AM/PI) staining and Cell Counting Kit 8 (CCK-8). (3) Osteogenic differentiation: Alkaline phosphatase (ALP) staining and alizarin red staining were performed on the cells in the osteogenic induction group to observe the osteogenic induction. RNA was collected from the osteogenic induction group and the osteogenic control group, the expression of osteoblast marker Runt-related transcription factor 2 (RUNX2), osteocalcin (OCN) and type I collagen (COL1A1) was detected by real-time florescent quantitative PCR (qPCR), and the differentiation degree and osteogenic ability of osteoblasts were observed. (4) Osteoclast differentiation: tartrate-resistant acid phosphatase (TRAP) staining was performed on cells in the osteoclastic induction group to observe osteoclast differentiation. RNA was extracted from the osteoclastic induction group and the osteoclastic control group for qPCR of osteoclast differentiation-related genes, and the expression levels of the osteoclast marker gene TRAP, cathepsin K (CTSK) and dendritic cell specific transmembrane protein (DC-STAMP) were detected.Results:The double-layer bone-on-a-chip containing bone matrix was 3 cm×3 cm in size and transparent as a whole. The structure of the system on the chip system was compact and had no seepage. It was shown by calcein AM/PI staining that at 3 days after MC3T3-E1 cells and RAW264.7 cells were cultured, very few red fluorescent dead cells were found. CCK-8 test showed that within 5 days after being cultured, the cell viability was all above 90%, indicating that the biocompatibility of the chip was good and the cells could survive and proliferate normally. The results of ALP and alizarin red staining showed that MC3T3-E1 cells successfully differentiated into osteoblasts and produced calcified nodules in the osteogenic induction group at 14 days after the induction. The qPCR results showed that the relative expression level of RUNX2 in MC3T3-E1 cells in the osteogenic induction group was 4.98±0.74, which was significantly higher than that of the control group (0.99±0.03) ( P<0.01). The relative expression level of OCN in MC3T3-E1 cells was 7.98±0.76, which was significantly higher than that of the control group (1.00±0.06) ( P<0.01). The relative expression level of COL1A1 in MC3T3-E1 cells was 7.07±0.56, which was significantly higher than that of the control group (0.97±0.03) ( P<0.01). The TRAP staining results showed that the RAW264.7 cells in the osteoclastic induction group differentiated to giant multinucleated osteoclasts, and TRAP protein was expressed in large quantity in the osteoclasts. The results of qPCR showed that the relative expression level of TRAP in RAW264.7 cells in the osteoclastic induction group was 3.35±0.37, which was significantly higher than that of the control group (1.01±0.06) ( P<0.01). The relative expression level of CTSK in RAW264.7 cells was 3.46±0.79, which was significantly higher than that of the control group (1.01±0.05) ( P<0.01). The relative expression level of DC-STAMP in RAW264.7 cells was 1.92±0.12, which was significantly higher than that of the control group (0.98±0.08) ( P<0.01). Conclusions:The double-layer bone-on-a-chip containing bone matrix is compact in structure, can be cultured in vitro for a long time, has good biocompatibility and can be used for inducing osteogenic and osteoclast differentiation. Therefore, it is expected to provide a new research platform for exploring the mechanism of osteoporosis and medication screening.

ObjectiveThe biosynthetic pathways of benzylisoquinoline alkaloids（BIAs） in Nelumbo nucifera are of great theoretical and economic value. In this paper， N. nucifera O-methyltransferase（NnOMT） and N. nucifera N-methyltransferase（NnNMT） gene families were identified and analyzed by bioinformatics in order to facilitate the biosynthetic pathway of BIAs in N. nucifera. MethodBased on the whole genome of N. nucifera， UniPort and National Center for Biotechnology Information（NCBI） databases were used to identify the NnOMT and NnNMT gene families of N. nucifera， and analyze their physicochemical properties and subcellular localization， then TBtools， MEME， MEGA 11.0， FigTree 1.4.4 and other tools were used to analyze the phylogeny， sequence characteristics， gene structure， functional annotation and cis-acting elements of NnOMT and NnNMT genes identified in the previous stage. ResultA total of 61 NnOMT and NnNMT genes were identified in this paper， the number of amino acids encoded by these genes ranged from 168 aa to 580 aa， the isoelectric point ranged from 4.76 to 9.16， and the relative molecular weight ranged from 18 699.52 Da to 64 934.53 Da， most of which showed acidic and mostly hydrophilic proteins. There were 10 conserved motifs， Kyoto Encyclopedia of Genes and Genomes（KEGG） analysis enriched a total of 12 pathways， including metabolism， biosynthesis of phenylpropane and isoquinoline alkaloids， etc. And Visualization of Gene Ontology（GO） enrichment results showed that 61 NnOMT and NnNMT genes were annotated to 32 items， which included 16 molecular functions［such as reduced nicotinamide adenine dinucleotide（NADH） activity and exopeptidase activity］ and 16 biological processes（such as metabolic process of carbon tetrachloride， anaerobic carbon tetrachloride metabolic process and responses to exogenous biological stimuli）. There were a variety of cis-acting elements in the promoter regions of NnOMT and NnNMT genes， mainly promoter and enhancer regions element， light responsive element and methyl jasmonate responsive element. ConclusionIn this study， a comprehensive bioinformatics analysis of 61 NnOMT and NnNMT genes is carried out based on the genome data of N. nucifera， which lays a foundation for research on the gene structure and function of NnOMT and NnNMT gene families， and provides a reference for biosynthetic pathway elucidation of BIAs in N. nucifera.

Objective:To analyze the iodine nutrition status of children aged 8 to 10 years in Zhejiang Province from 2016 to 2021.Methods:A multi-stage stratified sampling method was used to select non-residential children aged 8 to 10 years from 90 counties in Zhejiang Province. A total of 114 103 children were included in the study from 2016 to 2021. Direct titration method and arsenic-cerium catalytic spectrophotometry were used to detect salt iodine content and urinary iodine level, respectively, to evaluate the iodine nutritional status of children. Ultrasound was used to detect thyroid volume and analyze the current prevalence of goiter in school-age children.Results:The age of 114 103 children was (9.04 ± 0.81) years old, with 50.0% of (57 083) boys. The median of iodine content M ( Q1, Q3) in children's household salt was 23.00 (19.80, 25.20) mg/kg, including 17 242 non-iodized salt, 6 173 unqualified iodized salt, and 90 688 qualified iodized salt. The coverage rate of iodized salt was 84.89%, and the coverage rate of qualified iodized salt was 79.48%. The proportion of non-iodized salt increased from 11.85% in 2016 to 16.04% in 2021 ( χ 2trend=111.427, P<0.001). The median of urinary iodine concentration M ( Q1, Q3) in children was 182.50 (121.00, 261.00) μg/L, among which the proportions of iodine deficiency, iodine suitability, iodine over suitability, and iodine excess were 17.25% (19 686 cases), 39.21% (44 745 cases), 26.85% (30 638 cases), and 16.68% (19 034 cases), respectively. The median of urinary iodine concentration in children in inland areas [ M ( Q1, Q3): 190.90 (128.80, 269.00) μg/L] was significantly higher than that in children in coastal areas [ M ( Q1, Q3): 173.00 (113.00, 250.30) μg/L] ( P<0.001). From 2016 to 2021, a total of 39 134 ultrasound examinations were conducted, and 1 229 cases of thyroid enlargement were detected. The goiter rate was 3.14% (95% CI: 2.97%-3.32%). The incidence of goiter in children in coastal areas [3.45% (95% CI: 3.19%-3.72%), 641/18 604] was higher than that in children in inland areas [2.86% (95% CI: 2.64%-3.10%), 588/20 530] ( P=0.001). Conclusion:From 2016 to 2021, the iodine nutrition level of children aged 8-10 years in Zhejiang Province is generally suitable, and the rate of goiter in children meets the limit of iodine deficiency disease elimination standards.

Objective:To determine the total and age-specific cut-off values of total prostate specific antigen (tPSA) and the ratio of free PSA divided total PSA (fPSA/tPSA) for screening prostate cancer in China.Methods:Based on the Chinese Colorectal, Breast, Lung, Liver, and Stomach cancer Screening Trial (C-BLAST) and the Tianjin Common Cancer Case Cohort (TJ4C), males who were not diagnosed with any cancers at baseline since 2017 and received both tPSA and fPSA testes were selected. Based on Cox regression, the overall and age-specific (＜60, 60-＜70, and ≥70 years) accuracy and optimal cut-off values of tPSA and fPSA/tPSA ratio for screening prostate cancer were evaluated with time-dependent receiver operating characteristic curve (tdROC) and area under curve (AUC). Bootstrap resampling was used to internally validate the stability of the optimal cut-off value, and the PLCO study was used to externally validate the accuracy under different cut-off values.Results:A total of 5 180 participants were included in the study, and after a median follow-up of 1.48 years, a total of 332 prostate cancer patients were included. In the total population, the tdAUC of tPSA and fPSA/tPSA screening for prostate cancer were 0.852 and 0.748, respectively, with the optimal cut-off values of 5.08 ng/ml and 0.173, respectively. After age stratification, the age specific cut-off values of tPSA in the <60, 60-<70, and ≥70 age groups were 3.13, 4.82, and 11.54 ng/ml, respectively, while the age-specific cut-off values of fPSA/tPSA were 0.153, 0.135, and 0.130, respectively. Under the age-specific cut-off values, the sensitivities of tPSA screening for prostate cancer in males <60, 60-70, and ≥70 years old were 92.3%, 82.0%, and 77.6%, respectively, while the specificities were 84.7%, 81.3%, and 75.4%, respectively. The age-specific sensitivities of fPSA/tPSA for screening prostate cancer were 74.4%, 53.3%, and 55.9%, respectively, while the specificities were 83.8%, 83.7%, and 83.7%, respectively. Both bootstrap's internal validation and PLCO external validation provided similar results. The combination of tPSA and fPSA/tPSA could further improve the accuracy of screening.Conclusion:To improve the screening effects, it is recommended that age-specific cut-off values of tPSA and fPSA/tPSA should be used to screen for prostate cancer in the general risk population.

Head and neck tumor is a common malignant tumor with increasing incidence and mortality worldwide. Traditional diagnostic methods for head and neck tumor are limited by the lack of specific biomarkers and the limitation of invasive detection methods, as well as high time cost and a high rate of misdiagnosis. Therefore, research on head and neck tumor diagnosis based on new technologies is needed. Hyperspectral imaging (HSI) is a non-contact optical imaging technique that captures a series of images in multiple spectral bands to generate a hyperspectral image cube. HSI has shown its corresponding potential in the early diagnosis, tumor margin identification and clinical research of head and neck cancer.