It is important in production to achieve accurate counting and density estimation of high-density culture fry under the environmental conditions of aquaculture scenarios in an efficient and accurate ...manner. However, none of the current methods for fry counting works well under the high-density and high-overlap conditions of real aquaculture scenarios. Therefore, in this paper, we propose a high-density farming fry monitoring network model, Super-Resolution GAN Density Estimate Attention Network (SGDAN), which incorporating an image enhancement algorithm and an attention mechanism, and we create a high-density farming fry dataset (HD-FryDataset) based on the environmental conditions of real aquaculture scenarios. The network model is designed to improve and optimize the targeted subnetworks for several key aspects of high-density fish fry monitoring work. Four subnetworks are included for image optimization, feature extraction, attention, and density map estimation. The experimental results show that the SGDAN network model achieved an average counting accuracy of 97.57% on the high-density culture fry dataset, which was 8.23% and 2.06% higher than those of MCNN and CSRNet, respectively. Additionally, the MAE and RMSE of the model were reduced by 71.9% and 67.3% and by 34.3% and 33.2% compared with those of MCNN and CSRNet, respectively. The model proposed in this paper also has a better ability to generate predictive density maps. The density maps generated by SGDAN have values of the evaluation metrics PSNR and SSIM of 20.33 and 0.933, respectively, which are 3.31 and 0.037 and 2.63 and 0.031 higher than those of MCNN and CSRNet. In general, the network model proposed in this paper outperforms existing network models in two applications: accurate counting of fry and generation of density maps for high-density culture in aquaculture. It also provides a good solution for digitizing the number of fry and visualizing the density of high-density culture in intelligent aquaculture systems.
Individual genetic background can play an essential role in determining the development of esophageal squamous cell carcinoma (ESCC).
and
play important roles in the pathogenesis of ESCC. This ...case-control study aimed to analyze the association between gene polymorphisms and ESCC susceptibility.
DNA was extracted from the peripheral blood of patients. The Agena MassARRAY platform was used for the genotyping. Statistical analysis was conducted using the chi-squared test or Fisher's exact test, logistic regression analysis, and stratification analysis.
The 'G' allele of rs989902 (
) and the 'T' allele of rs738722 (
) were both associated with an increased risk of ESCC (rs989902: OR = 1.23, 95% CI = 1.02-1.47,
= 0.028; rs738722: OR = 1.28, 95% CI = 1.06-1.55,
= 0.011). Stratification analysis showed that SNPs (rs989902 and rs738722) were notably correlated with an increased risk of ESCC after stratification for age, sex, smoking, and drinking status. In addition, rs738722 might be associated with lower stage, while rs989902 had a lower risk of metastasis.
Our findings display that
rs989902 and
rs738722 are associated with an increased risk of ESCC in the Chinese Han population.
Gastric cancer (GC) is one of the most common malignancies, affected by several genetic loci in the clinical phenotype. This study aimed to determine the association between PTGER4 and PRKAA1 gene ...polymorphisms and the risk of GC. A total of 509 GC patients and 507 age and sex-matched healthy controls were recruited to explore the association between PTGER4 and PRKAA1 genetic polymorphisms and GC susceptibility. Logistic regression analysis was used to study the correlation between these SNPs and GC, with odd ratio (OR) and 95% confidence interval (CI) as indicators. Multifactor dimensionality reduction was utilized to analyze the genetic relationships among SNPs. was conducted to predict gene expression, the impact of SNPs on gene expression, and the signaling pathways involved in PTGER4 and PRKAA1. Overall, rs10036575 in PTGER4 (OR = 0.82, p = 0.029), rs10074991 (OR = 0.82, p = 0.024) and rs13361707 (OR = 0.82, p = 0.030) in PRKAA1 were associated with susceptibility to GC. Stratification analysis revealed that the effects of these SNPs in PTGER4 and PRKAA1 on GC susceptibility were dependent on smoking and were associated with a reduced risk of adenocarcinoma (p < 0.05). Bioinformatics analysis showed an association between SNPs and corresponding gene expression (p < 0.05), and PRKAA1 may affect GC by mediating RhoA. This study suggests that PTGER4 and PRKAA1 SNPs might affect the susceptibility of GC, providing a new biological perspective for GC risk assessment, pathogenesis exploration, and personalized treatment.
The present study aimed to identify a specific circular RNA (circRNA) for early diagnosis of gastric cancer (GC).
Totally 82 patients with GC, 30 with chronic nonatrophic gastritis and 30 with ...chronic atrophic gastritis were included in this study. Four of the 82 GC patients were selected for screening. Total RNA from malignant and adjacent tissue samples was extracted, and circRNAs in four patients were screened. According to the screening results, the eight most upregulated and downregulated circRNAs with a statistically significant association with GC were identified by real-time fluorescent quantitative polymerase chain reaction (PCR). Then, the most regulated circRNA was selected for further sensitivity and specificity assessments. CircRNA expression was examined by quantitative reverse transcriptase PCR in 78 GC (21 and 57 early and advanced GC, respectively) and adjacent tissue samples, as well as in gastric fluid samples from 30 patients with chronic nonatrophic gastritis, 30 with chronic atrophic gastritis, and 78 GC.
A total of 445 circRNAs, including 69 upregulated and 376 downregulated circRNAs, showed significantly altered expression in GC tissue samples. Hsa_circ_000780 was significantly downregulated in 80.77% of GC tissue samples, with levels in GC tissue samples correlating with tumor size, tumor stage, T stage, venous invasion, carcinoembryonic antigen amounts, and carbohydrate antigen 19-9 levels. Strikingly, this circRNA was found in the gastric fluid of patients with early and advanced GC.
The present study uncovered a new circRNA expression profile in human GC, with hsa_circ_000780 significantly downregulated in GC tissue and gastric fluid specimens. These findings indicate that hsa_circ_000780 should be considered a novel biomarker for early GC screening.
Abstract In response to the problem of using different single machines to achieve measurement and detection of existing torque instruments, this article introduces a multifunctional reference torque ...standard and proposes specific steps for torque measurement and detection. This standard machine can be used to detect various existing torque instruments and can solve the problem of using a single machine to achieve the detection of a certain type of torque equipment. After adopting this standard machine and its detection method, experimental data shows that the measurement of the torque transducer can meet the requirements of JJG995-2005 “Static Torque Measuring Machines” and the measurement of the reference torque wrench can meet the requirements of JJG1103-2014 “Reference torque wrench Verification Regulations”.
Tongue images (the colour, size and shape of the tongue and the colour, thickness and moisture content of the tongue coating), reflecting the health state of the whole body according to the theory of ...traditional Chinese medicine (TCM), have been widely used in China for thousands of years. Herein, we investigated the value of tongue images and the tongue coating microbiome in the diagnosis of gastric cancer (GC).
From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiome of the tongue coating samples. Then, artificial intelligence (AI) deep learning models were established to evaluate the value of tongue images and the tongue coating microbiome in the diagnosis of GC. Considering that tongue imaging is more convenient and economical as a diagnostic tool, we further conducted a prospective multicentre clinical study from May 2020 to March 2022 in China and recruited 937 patients with GC and 1911 participants with NGC from 10 centres across China to further evaluate the role of tongue images in the diagnosis of GC. Moreover, we verified this approach in another independent external validation cohort that included 294 patients with GC and 521 participants with NGC from 7 centres. This study is registered at ClinicalTrials.gov, NCT01090362.
For the first time, we found that both tongue images and the tongue coating microbiome can be used as tools for the diagnosis of GC, and the area under the curve (AUC) value of the tongue image-based diagnostic model was 0.89. The AUC values of the tongue coating microbiome-based model reached 0.94 using genus data and 0.95 using species data. The results of the prospective multicentre clinical study showed that the AUC values of the three tongue image-based models for GCs reached 0.88–0.92 in the internal verification and 0.83–0.88 in the independent external verification, which were significantly superior to the combination of eight blood biomarkers.
Our results suggest that tongue images can be used as a stable method for GC diagnosis and are significantly superior to conventional blood biomarkers. The three kinds of tongue image-based AI deep learning diagnostic models that we developed can be used to adequately distinguish patients with GC from participants with NGC, even early GC and precancerous lesions, such as atrophic gastritis (AG).
The National Key R&D Program of China (2021YFA0910100), Program of Zhejiang Provincial TCM Sci-tech Plan (2018ZY006), Medical Science and Technology Project of Zhejiang Province (2022KY114, WKJ-ZJ-2104), Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer (JBZX-202006), Natural Science Foundation of Zhejiang Province (HDMY22H160008), Science and Technology Projects of Zhejiang Province (2019C03049), National Natural Science Foundation of China (82074245, 81973634, 82204828), and Chinese Postdoctoral Science Foundation (2022M713203).
Background: ZBTB20 was overexpressed in esophageal cancer (EC). The study aimed to identify genotypes of ZBTB20 polymorphisms and their correlation with EC occurrence in a Chinese Han population. ...Methods: Four single nucleotide polymorphisms (SNPs) in ZBTB20 were randomly selected for genotyping through Agena MassARRAY system among 525 EC patients and 522 healthy controls. Multiple genetic models were applied to assess the association of ZBTB20 polymorphisms with EC susceptibility by calculating odds ratios (ORs) with 95% confidence intervals (CIs). Results: Rs10934270 was associated with lower EC susceptibility (OR = 0.64, p = 0.004) with statistical power >90% in overall analysis. Specifcally, the correlation of rs10934270 with EC susceptibility was found in subgroups including patients with esophageal squamous cell carcinoma (ESCC), males, subjects aged less than or equal to65 years, subjects with BMI less than or equal to 24 kg/m (2), and smokers. Rs9841504 might be a risk-increasing factor for ESCC. Moreover, rs9288999 in subjects aged less than or equal to65 years and rs73230612 in females were related to lower EC risk. Conclusion: Our research is the first to report that ZBTB20 rs10934270 is associated with reduced EC susceptibility in the Chinese Han population. These data provide a scientific basis for understanding the influence of the ZBTB20 gene on EC occurrence. Keywords: esophageal cancer, ZBTB20, genetic polymorphisms, genotype--phenotype analyses, FPRP analysis
We report the detection of a virus, tentatively identified as Seoul virus (SEOV), from a rat (
Rattus norvegicus
) collected in the city of Zhangmu, Tibet. SEOV RNA was detected in lung tissue by ...reverse transcription (RT)-PCR, followed by sequencing. Serum samples collected from Zhangmu were positive for SEOV-specific antibodies (indirect fluorescent antibody test that used SEO antigen). Sequencing and phylogenetic analysis of partial L and S sequences together with serology results suggest that the Zhangmu01 hantavirus is an isolate of SEOV, that hantaviruses circulate in Tibet, and that rats may act as natural reservoirs for the virus.
Background: Tongue images (the colour, size and shape of the tongue and the colour, thickness and moisture content of the tongue coating), reflecting the health state of the whole body according to ...the theory of traditional Chinese medicine (TCM), have been widely used in China for thousands of years. Herein, we investigated the value of tongue images and the tongue coating microbiome in the diagnosis of gastric cancer (GC). Methods: From May 2020 to January 2021, we simultaneously collected tongue images and tongue coating samples from 328 patients with GC (all newly diagnosed with GC) and 304 non-gastric cancer (NGC) participants in China, and 16 S rDNA was used to characterize the microbiome of the tongue coating samples. Then, artificial intelligence (AI) deep learning models were established to evaluate the value of tongue images and the tongue coating microbiome in the diagnosis of GC. Considering that tongue imaging is more convenient and economical as a diagnostic tool, we further conducted a prospective multicentre clinical study from May 2020 to March 2022 in China and recruited 937 patients with GC and 1911 participants with NGC from 10 centres across China to further evaluate the role of tongue images in the diagnosis of GC. Moreover, we verified this approach in another independent external validation cohort that included 294 patients with GC and 521 participants with NGC from 7 centres. This study is registered at ClinicalTrials.gov, NCT01090362. Findings: For the first time, we found that both tongue images and the tongue coating microbiome can be used as tools for the diagnosis of GC, and the area under the curve (AUC) value of the tongue image-based diagnostic model was 0.89. The AUC values of the tongue coating microbiome-based model reached 0.94 using genus data and 0.95 using species data. The results of the prospective multicentre clinical study showed that the AUC values of the three tongue image-based models for GCs reached 0.88–0.92 in the internal verification and 0.83–0.88 in the independent external verification, which were significantly superior to the combination of eight blood biomarkers. Interpretation: Our results suggest that tongue images can be used as a stable method for GC diagnosis and are significantly superior to conventional blood biomarkers. The three kinds of tongue image-based AI deep learning diagnostic models that we developed can be used to adequately distinguish patients with GC from participants with NGC, even early GC and precancerous lesions, such as atrophic gastritis (AG). Funding: The National Key R&D Program of China (2021YFA0910100), Program of Zhejiang Provincial TCM Sci-tech Plan (2018ZY006), Medical Science and Technology Project of Zhejiang Province (2022KY114, WKJ-ZJ-2104), Zhejiang Provincial Research Center for Upper Gastrointestinal Tract Cancer (JBZX-202006), Natural Science Foundation of Zhejiang Province (HDMY22H160008), Science and Technology Projects of Zhejiang Province (2019C03049), National Natural Science Foundation of China (82074245, 81973634, 82204828), and Chinese Postdoctoral Science Foundation (2022M713203).
Objective To investigate the differences of cerebral grey matter atrophy over time between MCI (Mild Cognitive Impairment) and NC (Normal Control), and further investigate the differences of cerebral ...grey matter atrophy between SMCI (Stable MCI) and PMCI (Progressive MCI). Methods Based on improved VBM-DARTEL method, NC and MCI longitudinal datasets of 3 years were processed. Firstly, the atrophy patterns and atrophy rates of NC and MCI were obtained. Then, the differences of atrophy within some certain cerebral regions between SMCI and PMCI were explored applying the ROI (Regions of Interest) method. Fractal dimensions were also applied to describe the texture features of the atrophy regions within ROIs and differences of atrophy rates were also calculated. Results With the time varying, the atrophy regions were gradually expanding. In MCI, the atrophy pace was faster and the atrophy rate at the same time point was higher than that in NC. By longitudinal comparison between SMCI and PMCI, it was found that the atrophy in PMCI appeared earlier in the hippocampus, the temporal lobe, the cingulate gyrus and the caudate nucleus and showed an increasing atrophy rate and decreasing fractal dimensions. Conclusions VBM-DARTEL method can be applied to study the cerebral grey matter atrophy effectively. The results showed that the cerebral grey matter changing over time was more obvious in MCI, which can be used to diagnose early AD. Compared to SMCI, there appeared more obvious atrophy in some certain regions of cerebral grey matter in PMCI. So these atrophy differences between SMCI and PMCI can be the evidence to identify PMCI and was of help for clinical diagnosis, clinical intervention and clinical treatment of early AD.
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