ViroISDC: a method for calling integration sites of hepatitis B virus based on feature encoding.

BACKGROUND: Hepatitis B virus (HBV) integrates into human chromosomes and can lead to genomic instability and hepatocarcinogenesis. Current tools for HBV integration site detection lack accuracy and stability. RESULTS: This study proposes a deep learning-based method, named ViroISDC, for detecting integration sites. ViroISDC generates corresponding grammar rules and encodes the characteristics of the language data to predict integration sites accurately. Compared with Lumpy, Pindel, Seeksv, and SurVirus, ViroISDC exhibits better overall performance and is less sensitive to sequencing depth and integration sequence length, displaying good reliability, stability, and generality. Further downstream analysis of integrated sites detected by ViroISDC reveals the integration patterns and features of HBV. It is observed that HBV integration exhibits specific chromosomal preferences and tends to integrate into cancerous tissue. Moreover, HBV integration frequency was higher in males than females, and high-frequency integration sites were more likely to be present on hepatocarcinogenesis- and anti-cancer-related genes, validating the reliability of the ViroISDC. CONCLUSIONS: ViroISDC pipeline exhibits superior precision, stability, and reliability across various datasets when compared to similar software. It is invaluable in exploring HBV infection in the human body, holding significant implications for the diagnosis, treatment, and prognosis assessment of HCC.

scIALM: A method for sparse scRNA-seq expression matrix imputation using the Inexact Augmented Lagrange Multiplier with low error.

Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology that quantifies gene expression profiles of specific cell populations at the single-cell level, providing a foundation for studying cellular heterogeneity and patient pathological characteristics. It is effective for developmental, fertility, and disease studies. However, the cell-gene expression matrix of single-cell sequencing data is often sparse and contains numerous zero values. Some of the zero values derive from noise, where dropout noise has a large impact on downstream analysis. In this paper, we propose a method named scIALM for imputation recovery of sparse single-cell RNA data expression matrices, which employs the Inexact Augmented Lagrange Multiplier method to use sparse but clean (accurate) data to recover unknown entries in the matrix. We perform experimental analysis on four datasets, calling the expression matrix after Quality Control (QC) as the original matrix, and comparing the performance of scIALM with six other methods using mean squared error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC), and cosine similarity (CS). Our results demonstrate that scIALM accurately recovers the original data of the matrix with an error of 10e-4, and the mean value of the four metrics reaches 4.5072 (MSE), 0.765 (MAE), 0.8701 (PCC), 0.8896 (CS). In addition, at 10%-50% random masking noise, scIALM is the least sensitive to the masking ratio. For downstream analysis, this study uses adjusted rand index (ARI) and normalized mutual information (NMI) to evaluate the clustering effect, and the results are improved on three datasets containing real cluster labels.

Enhancing maize's nitrogen-fixing potential through ZmSBT3, a gene suppressing mucilage secretion.

Maize (Zea mays) requires substantial amounts of nitrogen, posing a challenge for its cultivation. Recent work discovered that some ancient Mexican maize landraces harbored diazotrophic bacteria in mucilage secreted by their aerial roots. To see if this trait is retained in modern maize, we conducted a field study of aerial root mucilage (ARM) in 258 inbred lines. We observed that ARM secretion is common in modern maize, but the amount significantly varies, and only a few lines have retained the nitrogen-fixing traits found in ancient landraces. The mucilage of the high-ARM inbred line HN5-724 had high nitrogen-fixing enzyme activity and abundant diazotrophic bacteria. Our genome-wide association study identified 17 candidate genes associated with ARM across three environments. Knockouts of one candidate gene, the subtilase family gene ZmSBT3, confirmed that it negatively regulates ARM secretion. Notably, the ZmSBT3 knockout lines had increased biomass and total nitrogen accumulation under nitrogen-free culture conditions. High ARM was associated with three ZmSBT3 haplotypes that were gradually lost during maize domestication, being retained in only a few modern inbred lines such as HN5-724. In summary, our results identify ZmSBT3 as a potential tool for enhancing ARM, and thus nitrogen fixation, in maize.

Preparation and Properties of Starch-Cellulose Composite Aerogel.

In this study, we conducted research on the preparation of aerogels using cellulose and starch as the primary materials, with the addition of N,N'-methylenebisacrylamide (MBA) as a cross-linking agent. The chemical, morphological and textural characteristics of the aerogels were found to be influenced by the proportions of cellulose, starch, and cross-linking agent that were utilized. An increase in the proportion of cellulose led to stronger adsorption forces within the aerogel structure. The aerogel showed a fine mesh internal structure, but the pores gradually increased with the further increase in cellulose. Notably, when the mass fractions of starch and cellulose were 5 wt% and 1 wt% respectively, the aerogels exhibited the smallest pore size and largest porosity. With an increase in the crosslinking agent, the internal structure of the aerogel first became dense and then loose, and the best internal structure was displayed at the addition of 3 wt%. Through texture analysis and the swelling test, the impact of the proportion of cellulose and MBA on the aerogel structure was significant. Dye adsorption experiments indicated that MBA affected the water absorption and expansion characteristics of the aerogel by improving the pore structure. Lastly, in tests involving the loading of vitamin E, the aerogels exhibited a higher capacity for incorporating vitamin E compared to native starch.

DeepHipp: accurate segmentation of hippocampus using 3D dense-block based on attention mechanism.

BACKGROUND: The hippocampus is a key area of the brain responsible for learning, memory, and other abilities. Accurately segmenting the hippocampus and precisely calculating the volume of the hippocampus is of great significance for predicting Alzheimer's disease and amnesia. Most of the segmentation algorithms currently involved are based on templates, such as the more popular FreeSufer. METHODS: This study proposes Deephipp, a deep learning network based on a 3D dense block using an attention mechanism for accurate segmentation of the hippocampus. DeepHipp is based on the following novelties: (i) DeepHipp adopts powerful data augmentation schemes to enhance the segmentation ability. (ii) DeepHipp is designed to incorporate 3D dense-block to capture multiple-scale features of the hippocampus. (iii) DeepHipp creatively uses the attention mechanism in the field of hippocampal image segmentation, extracting useful hippocampus information in a massive feature map, and improving the accuracy and sensitivity of the model. CONCLUSIONS: We describe the illustrative results and show extensive qualitative and quantitative comparisons with other methods. Our achievement demonstrates that the accuracy of DeepHipp can reach 83.63%, which is superior to most existing methods in terms of accuracy and efficiency of hippocampus segmentation. It is noticeable that deep learning can potentially lead to an effective segmentation of medical images.

Harnessing ultrasound in photocatalysis: Synthesis and piezo-enhanced effect: A review.

The photocatalytic technique has drawn far-ranging interests in addressing the current issues; however, its property suffers from the limited visible light response and rapid recombination of carriers. To address these issues, two specific approaches have been proposed to enhance the photocatalytic activity: (1) ultrasound-assisted synthesis has been utilized to prepare photocatalysts, resulting in refined grain size, increased specific surface area, and reduced photogenerated carrier recombination; (2) sonophotocatalysis and piezoelectric enhanced photocatalysis have been developed to accelerate the reaction, which utilizes the synergism between ultrasound and light. On one side, sonophotocatalysis generates cavitation bubbles which induce more reactive radicals for redox reactions. On the other side, ultrasound induces deformation of the piezoelectric material structure, which changes the internal piezoelectric potential and improves the photocatalytic performance. Currently, intensive efforts have been devoted to related research and great progress has been reached with applications in pollutant degradation, new energy production, and other fields. This work starts by elucidating the fundamental concept of ultrasound-assisted photocatalyst synthesis and photocatalysis. Then, the synergistic behavior between ultrasonic and light in ultrasonic-assisted photocatalysis has been thoroughly discussed, including pollutant degradation, water splitting, and bacterial sterilization. Finally, the challenge and outlook are investigated and proposed.

CTCs Detection and Whole-exome Sequencing Might Be Used to Differentiate Benign and Malignant Pulmonary Nodules.

BACKGROUND: Low-density computed tomography (LDCT) improved early lung cancer diagnosis but introduces an excess of false-positive pulmonary nodules data. Hence, accurate diagnosis of early-stage lung cancer remains challenging. The purpose of the study was to assess the feasibility of using circulating tumour cells (CTCs) to differentiate malignant from benign pulmonary nodules. METHODS: 122 patients with suspected malignant pulmonary nodules detected on chest CT in preparation for surgery were prospectively recruited. Peripheral blood samples were collected before surgery, and CTCs were identified upon isolation by size of epithelial tumour cells and morphological analysis. Laser capture microdissection, MALBAC amplification, and whole-exome sequencing were performed on 8 samples. The diagnostic efficacy of CTCs counting, and the genomic variation profile of benign and malignant CTCs samples were analysed. RESULTS: Using 2.5 cells/5 mL as the cut-off value, the area under the receiver operating characteristic curve was of 0.651 (95% confidence interval: 0.538-0.764), with a sensitivity and specificity of 0.526 and 0.800, respectively, and positive and negative predictive values of 91.1% and 30.3%, respectively. Distinct sequence variations differences in DNA damage repair-related and driver genes were observed in benign and malignant samples. TP53 mutations were identified in CTCs of four malignant cases; in particular, g.7578115T>C, g.7578645C>T, and g.7579472G>C were exclusively detected in all four malignant samples. CONCLUSIONS: CTCs play an ancillary role in the diagnosis of pulmonary nodules. TP53 mutations in CTCs might be used to identify benign and malignant pulmonary nodules.

Predictive Factors of Menstrual Recovery After Laparoscopic Sleeve Gastrectomy in Polycystic Ovary Syndrome Women with Obesity.

Objective: To explore the predictors of menstrual recovery in polycystic ovary syndrome (PCOS) women with obesity following laparoscopic sleeve gastrectomy (LSG). Methods: A total of 88 PCOS patients with obesity and 76 control patients with obesity aged 18-45 years were enrolled between May 2013 and December 2020. PCOS was diagnosed using the Rotterdam diagnostic criteria (2003). Anthropometric measurements, biochemical parameters, sex hormones, and circulating fibrinogen-like protein 1 (FGL-1) levels were collected before and six-month after LSG. The data on postoperative menstrual status, body weight, and fertility were obtained through telephone follow-ups for all individuals with PCOS. Results: Patients with PCOS were followed up for at least six months after surgery, and the mean follow-up time was 3.23 years. At 6 months after LSG, circulating total testosterone (TT), calculated free testosterone (cFT), and FGL-1 levels declined significantly. The mean percent excess weight loss (%EWL) and percent total weight loss (%TWL) in PCOS patients at the final follow-up was 97.52% ± 33.90% and 31.65% ± 10.31%, respectively. The proportion of regular menstruation in PCOS patients significantly increased within six months (75.86% vs 0.03% at baseline). In the logistic regression analysis, time from PCOS diagnosis (P=0.007), body mass index (BMI) (P=0.007), TT (P=0.038) at baseline were demonstrated to be independent predictive factors for the regular menstruation in women with PCOS and obesity within 6 months after LSG. Conclusion: In PCOS patients with obesity, time from PCOS diagnosis, BMI, and TT levels at baseline were independently and negatively associated with menstrual recovery within 6 months after LSG, which could be applied in preoperative evaluation.

Myeloid FoxO1 depletion attenuates hepatic inflammation and prevents nonalcoholic steatohepatitis.

Hepatic inflammation is culpable for the evolution of asymptomatic steatosis to nonalcoholic steatohepatitis (NASH). Hepatic inflammation results from abnormal macrophage activation. We found that FoxO1 links overnutrition to hepatic inflammation by regulating macrophage polarization and activation. FoxO1 was upregulated in hepatic macrophages, correlating with hepatic inflammation, steatosis, and fibrosis in mice and patients with NASH. Myeloid cell conditional FoxO1 knockout skewed macrophage polarization from proinflammatory M1 to the antiinflammatory M2 phenotype, accompanied by a reduction in macrophage infiltration in liver. These effects mitigated overnutrition-induced hepatic inflammation and insulin resistance, contributing to improved hepatic metabolism and increased energy expenditure in myeloid cell FoxO1-knockout mice on a high-fat diet. When fed a NASH-inducing diet, myeloid cell FoxO1-knockout mice were protected from developing NASH, culminating in a reduction in hepatic inflammation, steatosis, and fibrosis. Mechanistically, FoxO1 counteracts Stat6 to skew macrophage polarization from M2 toward the M1 signature to perpetuate hepatic inflammation in NASH. FoxO1 appears to be a pivotal mediator of macrophage activation in response to overnutrition and a therapeutic target for ameliorating hepatic inflammation to stem the disease progression from benign steatosis to NASH.

Relationship of Vitamin A and Thyroid Function in Individuals With Obesity and After Laparoscopic Sleeve Gastrectomy.

Vitamin A deficiency (VAD) occurs in obesity and may be associated with thyroid dysfunction. We aimed to investigate the association of VA with thyroid function in obesity and after laparoscopic sleeve gastrectomy (LSG). Nine hundred and seventy-six obese subjects were enrolled for this study and were divided into VAD, marginal vitamin A deficiency (MVAD), and vitamin A normal (NVA) groups. VAD was defined as VA ≤ 200 ng/ml, MVAD was defined as VA > 200 but <300 ng/ml, and NVA was defined as VA ≥ 300 ng/ml. Thyroid function was compared among groups and the relationship of VA and thyroid function was analyzed. Two hundred and forty-four of the 976 obese subjects underwent LSG, and the change in thyroid function and VA at 3, 6, and 12 months after surgery was measured. Results showed that 37% of all the subjects had subclinical hypothyroidism (SH), and the SH group had lower VA levels than the non-SH group (P = 0.008). Forty-nine percent of all the subjects had MVAD, 9% had VAD, while the MVAD or VAD group had lower FT4 than the NVA group (P = 0.005 and P = 0.001). The VAD group also had higher TSH than NVA group (P = 0.037). VA was significantly negatively associated with TSH (r = -0.151, P = 0.006) and positively associated with FT4 (r = 0.228, P < 0.001). TSH was significantly decreased at 3, 6, and 12 months (3M: from 4.43 ± 2.70 to 2.63 ± 1.46 mU/l, P < 0.001; 6M: from 4.43 ± 2.70 to 3.84 ± 2.34 mU/l, P = 0.041; 12M: from 4.43 ± 2.70 to 2.85 ± 1.68 mU/l, P = 0.024). After LSG surgery, VA levels were slightly increased, when compared to pre-surgery levels, at 3, 6, and 12 months (3M: from 262.57 ± 68.19 to 410.33 ± 76.55 ng/ml, P = 0.065; 6M: from 262.57 ± 68.19 to 281.36 ± 93.23 ng/ml, P = 0.343; 12M: from 262.57 ± 68.19 to 300.37 ± 86.03 ng/ml, P = 0.083). SH group also had lower TSH and higher VA than the non-SH group at 3 months post-surgery [TSH: -1.4(-2.3, -0.3) vs. -0.2(-0.8, -0.2) mU/l, P < 0.001; VA: 163.99 ± 32.58 vs. 121.69 ± 27.59 ng/ml, P = 0.044]. In conclusion VA, which is related to thyroid hormone production, protects against thyroid dysfunction in obese subjects. The improvement of thyroid function in subjects with SH after LSG may be related to the increased VA levels observed post-surgery. Clinical Trial Registration: ClinicalTrial.gov ID: NCT04548232.

J-Shaped Relationship Between Serum Prolactin and Metabolic-Associated Fatty Liver Disease in Female Patients With Type 2 Diabetes.

Background: Metabolic-associated fatty liver disease (MAFLD) has become a worldwide epidemic. Prolactin (PRL), a pituitary hormone, has been linked to MAFLD. As a result, we set out to look into the relationship between serum PRL and the risk of MAFLD in patients with type 2 diabetes mellitus (T2DM). Methods: A total of 724 adults with T2DM were enrolled and categorized as MAFLD and non-MAFLD groups. Anthropometric data, biochemical parameters, and serum PRL levels were collected. Liver steatosis and fibrosis were assessed using FibroScan. Patients were stratified into normal PRL (NP) and high PRL (HP) groups and divided into four groups based on serum PRL quartiles. Multivariate logistic regression analysis was performed to evaluate the association between serum PRL and MAFLD risk. Results: Female but not male patients with MAFLD, liver steatosis, and fibrosis had significantly lower PRL levels in the NP group but higher PRL levels in the HP group than their counterparts. The proportions of MAFLD, liver steatosis, and fibrosis were significantly decreased in the NP group but increased in the HP group across the PRL quartiles in females but not in males. After multivariate adjustment, the adjusted ORs (AORs) and 95% CI for MAFLD among females were 18.165 (3.425-96.336), 1.784 (0.658-5.002), 1.744 (0.608-4.832), and 1.00 (reference) in the NP group (Q1-Q4, P-trend < 0.001) and 1.00 (reference), 11.098 (1.819-110.356), 15.225 (1.996-116.112), and 18.211 (2.579-128.568) in the HP group (Q1-Q4, P-trend = 0.020). Such associations were also found between serum PRL and liver fibrosis in females but not in males. Conclusion: We observed a J-shaped association between serum PRL and the risk of MAFLD and liver fibrosis in females but not in males with T2DM, indicating that PRL may be relevant to MAFLD and its progression in a gender-specific manner. Clinical Trial Registration: Chinese Clinical Trial Registry, number ChiCTR-OCS-12002381.

Redevelopment of urban brownfield sites in China: Motivation, history, policies and improved management.

Rapid urbanisation in China has resulted in an increased demand for land in towns and cities. To upgrade and modernise, China has also moved many major industries from urban centres to less populated areas. With the high economic value of urban land, the transformation and utilisation of brownfield areas have become important economically and socially. The Chinese government has recognised the need for strong frameworks to safeguard soil and groundwater quality, with brownfield sites a key category for management. Strong scientific, regulatory and decision-making frameworks are needed and being adopted to ensure practical, careful and wise use of central and localised government resources, to manage the reuse and regeneration of these brownfield sites. This paper reviews the context, policies and management procedures of developing brownfield sites in countries with a history of brownfield management and discusses China's current situation and priorities for brownfield governance and redevelopment. These include (1) clarification of brownfield site soil contamination risk control standards and risk assessment procedures, (2) the responsibilities of different national and local agencies, (3) the establishment of a national expert committee to advise on best practices, policy and process, (4) the use of registered brownfield databases at national, provincial, municipal and county levels, and (5) the set up of soil pollution prevention fund at the provincial level.

An efficient scRNA-seq dropout imputation method using graph attention network.

BACKGROUND: Single-cell sequencing technology can address the amount of single-cell library data at the same time and display the heterogeneity of different cells. However, analyzing single-cell data is a computationally challenging problem. Because there are low counts in the gene expression region, it has a high chance of recognizing the non-zero entity as zero, which are called dropout events. At present, the mainstream dropout imputation methods cannot effectively recover the true expression of cells from dropout noise such as DCA, MAGIC, scVI, scImpute and SAVER. RESULTS: In this paper, we propose an autoencoder structure network, named GNNImpute. GNNImpute uses graph attention convolution to aggregate multi-level similar cell information and implements convolution operations on non-Euclidean space on scRNA-seq data. Distinct from current imputation tools, GNNImpute can accurately and effectively impute the dropout and reduce dropout noise. We use mean square error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC) and Cosine similarity (CS) to measure the performance of different methods with GNNImpute. We analyze four real datasets, and our results show that the GNNImpute achieves 3.0130 MSE, 0.6781 MAE, 0.9073 PCC and 0.9134 CS. Furthermore, we use Adjusted rand index (ARI) and Normalized mutual information (NMI) to measure the clustering effect. The GNNImpute achieves 0.8199 (ARI) and 0.8368 (NMI), respectively. CONCLUSIONS: In this investigation, we propose a single-cell dropout imputation method (GNNImpute), which effectively utilizes shared information for imputing the dropout of scRNA-seq data. We test it with different real datasets and evaluate its effectiveness in MSE, MAE, PCC and CS. The results show that graph attention convolution and autoencoder structure have great potential in single-cell dropout imputation.

Incidence and Risk Factors of Hypogonadism in Male Patients With Latent Autoimmune Diabetes and Classic Type 2 Diabetes.

Objectives: This study aimed to compare the prevalence of hypogonadism between male patients with latent autoimmune diabetes (LADA) and type 2 diabetes (T2DM) and investigate the risk factors for hypogonadism in these patients. Methods: This cross-sectional study evaluated 367 male patients with LADA (n=73) and T2DM (n=294) who visited the endocrinology department of Shanghai Tenth People's Hospital between January 2016 and October 2019 for diabetes management. Sex hormones, lipid profiles, sex hormone-binding globulin (SHBG), glycosylated hemoglobin A1c, beta-cell function, uric acid, and osteocalcin were determined in serum samples. Hypogonadism was defined as calculated free testosterone (cFT) less than 220 pmol/L along with the presence of symptoms (positive ADAM score). Results: The rate of hypogonadism in the LADA and T2DM group were 8.2, and 21.7%, respectively (p=0.017). After adjusting possible confounders, the rate of hypogonadism in the LADA group was comparable to those of the T2DM group. Univariate logistic regressions demonstrated that age, BMI, fasting C-peptide, triglycerides, total cholesterol and uric acid were associated with hypogonadism in men with diabetes, BMI, triglycerides and estradiol were independent risk for hypogonadism in men with diabetes. Conclusion: This is the first evidence to explore the rate of hypogonadism in male patients with latent autoimmune diabetes (LADA). In the population requiring admission to a large urban hospital in China, the rate of hypogonadism was comparable to those of the T2DM group after adjusting for possible confounders. BMI, triglycerides and estradiol were independently associated with the presence of HH in male diabetic patients.

The Changes in Body Composition in Obese Patients with Polycystic Ovary Syndrome after Laparoscopic Sleeve Gastrectomy:a 12-Month Follow-up.

OBJECTIVES: To investigate the changes in body fat distribution and predicting factors of these changes in polycystic ovary syndrome (PCOS) patients with obesity, after laparoscopic sleeve gastrectomy (LSG). METHODS: This study consecutively enrolled 153 patients with obesity aged 18-45 years (83 with PCOS and 70 control patients) who underwent LSG from May 2013 to September 2020 at the Department of Endocrinology, Shanghai Tenth People's Hospital, with a 12-month follow-up. Dual-energy X-ray absorptiometry (DEXA) was used to assess body fat distribution. RESULTS: The percentage of fat mass loss in the visceral adipose tissue (VAT) region (55.08%) was more than that in any other body regions at 12 months post-surgery in the PCOS group yet insignificant. Homeostatic model assessment of insulin resistance (HOMA-IR) at baseline and Δ HOMA-IR were only negatively correlated with the variations in VAT mass and volume at 3 months post-surgery in the PCOS group. Logistic regression analysis showed that HOMA-IR <6.65 was an independent predictive factor for the changes in VAT mass and volume at 3 months post-surgery in the PCOS group. CONCLUSIONS: In this study, the percentage loss of fat mass was greater in the VAT region than in any other body regions in all patients. The rate of VAT decrease in the PCOS group was higher than that in the control group yet insignificant. Compared with control patients, HOMA-IR at baseline was an independent risk factor for the changes in VAT mass and volume at 3 months post-surgery in patients with PCOS. KEY POINTS: • The percentage loss of fat mass was greater in the VAT region than in any other body regions in all patients. • The rate of VAT decrease in the PCOS group was higher than that in the control group yet insignificant. • HOMA-IR at baseline was an independent risk factor for the changes of VAT mass in patients with PCOS.

Cnngeno: A high-precision deep learning based strategy for the calling of structural variation genotype.

Genotype plays a significant role in determining characteristics in an organism and genotype calling has been greatly accelerated by sequencing technologies. Furthermore, most parametric statistical models are unable to effectively call genotype, which is influenced by the size of structural variations and the coverage fluctuations of sequencing data. In this study, we propose a new method for calling deletions' genotypes from the next-generation data, called Cnngeno. Cnngeno can convert sequencing data into images and classifies the genotypes from these images using the convolutional neural network(CNN). Moreover, Cnngeno adopted the convolutional bootstrapping strategy to improve the anti-noisy label's ability. The results show that Cnngeno performs better in terms of precision for calling genotype when compared with other existing methods. The Cnngeno is an open-source method, available at https://github.com/BRF123/Cnngeno.

Obesity-associated up-regulation of lipocalin 2 protects gastric mucosa cells from apoptotic cell death by reducing endoplasmic reticulum stress.

Gastric mucosal injury is a less well known complication of obesity. Its mechanism remains to be further elucidated. Here, we explored the protective role of lipocalin 2 (LCN2) against endoplasmic reticulum stress and cell apoptosis in gastric mucosa in patients and mice with obesity. Through molecular and genetic analyses in clinical species, LCN2 secreted by parietal cells expression is elevated in obese. Immunofluorescence, TUNEL, and colorimetry results show that a more significant upregulation of pro-inflammatory factors and increased amount of apoptotic cells in gastric tissue sections in obese groups. Loss- and gain-of-function experiments in gastric epithelial cells demonstrate that increased LCN2 protected against obesity associated gastric injury by inhibiting apoptosis and improving inflammatory state. In addition, this protective effect was mediated by repressing ER stress. Our findings identify LCN2 as a gastric hormone could be a compensatory protective factor against gastric injury in obese.

Glucose-Lipid Metabolism in Obesity with Elevated Prolactin Levels and Alteration of Prolactin Levels After Laparoscopic Sleeve Gastrectomy.

PURPOSE: We investigated the differences in metabolism between obesity with or without increased prolactin (PRL) and the change in PRL after laparoscopic sleeve gastrectomy (LSG). METHODS: Patients were divided into two groups: obesity with normal PRL (NP, n = 123) and high PRL (HP, n = 108). Glucose-lipid metabolism and inflammation were measured. A total of 115 patients with obesity (NP, n = 64; HP, n = 51) underwent LSG were recruited, and PRL was measured at 12 months after LSG. RESULTS: (1) Blood glucose (BG), total cholesterol (TCH), LDL, triglyceride, and TNF-α were lower in the HP than in the NP group in the cross-sectional study (all P < 0.05). (2) PRL was negatively associated with neck circumference, waist-to-hip ratio, systolic blood pressure, heart rate, basal metabolism rate (BMR), ALP, TCH, and LDL in all subjects. PRL levels were positively associated with weight, HC, and BMR in males but were negatively associated with ALT, AST, ALP, BG 30 min, BG 60 min, FFA, and TCH in females (all P < 0.05). (3) Regression analysis showed that PRL negatively correlated with ALP and LDL-C in the whole baseline (ß = - 0.051, P = 0.002; ß = - 1.372, P = 0.033). PRL was a negative factor for ALP in females and a positive factor for BMR2 in males (ß = - 0.099, P = 0.041; ß = 0.005, P = 0.006). (4) PRL decreased in the HP group and increased in the NP group at 12 months post-operation (all P < 0.05). Increased PRL was associated with a change in TCH in the NP group (P < 0.05). CONCLUSION: Increased PRL resulted in improved glucose-lipid metabolism and chronic low-grade inflammation. LSG led to increased PRL in NP and decreased PRL in HP. Improved lipid was associated with increased PRL in NP after surgery. CLINICAL TRIAL REGISTRATION NUMBER: ChiCTR-OCS-12002381.

A review of the application of deep learning in medical image classification and segmentation.

Big medical data mainly include electronic health record data, medical image data, gene information data, etc. Among them, medical image data account for the vast majority of medical data at this stage. How to apply big medical data to clinical practice? This is an issue of great concern to medical and computer researchers, and intelligent imaging and deep learning provide a good answer. This review introduces the application of intelligent imaging and deep learning in the field of big data analysis and early diagnosis of diseases, combining the latest research progress of big data analysis of medical images and the work of our team in the field of big data analysis of medical imagec, especially the classification and segmentation of medical images.