A transcriptomic analysis of incisional hernia based on high-throughput sequencing technology.

PURPOSE: Incisional hernia is a common postoperative complication; however, few transcriptomic studies have been conducted on it. In this study, we used second-generation high-throughput sequencing to explore the pathogenesis and potential therapeutic targets of incisional hernias. METHODS: Superficial fasciae were collected from 15 patients without hernia and 21 patients with an incisional hernia. High-throughput sequencing of the fascia was performed to generate an expression matrix. We analyzed the matrix to identify differentially expressed genes (DEGs) and performed gene ontology and enrichment analyses of these DEGs. Additionally, an external dataset was utilized to identify key DEGs. RESULTS: We identified 1,823 DEGs closely associated with extracellular matrix (ECM) imbalance, bacterial inflammatory response, and fibrillar collagen trimerization. TNNT3, CMAY5, ATP1B4, ASB5, CILP, SIX4, FBN1 and FNDC5 were identified as key DEGs at the intersection of the two expression matrices. Moreover, non-alcoholic fatty liver disease-related, TNF, and IL-17 signaling pathways were identified as key enrichment pathways. CONCLUSIONS: We identified eight key DEGs and three pathways associated with incisional hernias. Our findings offer new insights into the pathogenesis of incisional hernias and highlight potential targets for their prevention and treatment.

The coupling coordination between tourism urbanization and ecosystem services value and its obstacle factors in ecologically fragile areas: a case study of the Wuling Mountain area of Hunan Province, China.

The interrelationship between tourism urbanization (TU) and the ecological environment is extremely complex. Some studies have analyzed the interaction between them but ignored the ecosystem services. Therefore, exploring the coupling coordination relationship between TU and ecosystem services value (ESV) is significant. In this research, we established a coupling coordination degree (CCD) model between TU and ESV and used exploratory spatial data analysis (ESDA), spatial variogram model, and obstacle degree model to evaluate the evolution characteristics of CCD and its obstacle factors in the Wuling Mountain area of Hunan Province (WMAHP). The results are as follows: (1) the comprehensive TU level shows an upward trend, and TU levels in the west are generally higher than in the east. The total ESV shows a fluctuating upward trend, and the average ESV is relatively low in the west and southeast. (2) The comprehensive CCD shows an increasing trend, and the coupling coordination relationship has changed from uncoordinated to coordinated in most counties. Spatially, the global spatial autocorrelation and spatial variation degree of CCD are insignificant. Wulingyuan and Yongding are uplift areas, and a subsidence area is in the southeast. It is worth noting that the problem of TU lag generally exists. (3) For the whole area, TU and economy are always the primary obstacle factors in the system and category layer, respectively, but the obstacle degree of the population has gradually increased. At the county level, TU restricts the CCD improvement in most counties, and the proportion of counties where the economy is the primary obstacle in the criterion layer exceeds 60%. Policymakers need to formulate targeted promotion strategies based on the coupling coordination and relative development level between TU and ESV for different counties. This paper provides valuable references for achieving coordinated development between TU and ESV in ecologically fragile areas worldwide.

GraphCpG: imputation of single-cell methylomes based on locus-aware neighboring subgraphs.

MOTIVATION: Single-cell DNA methylation sequencing can assay DNA methylation at single-cell resolution. However, incomplete coverage compromises related downstream analyses, outlining the importance of imputation techniques. With a rising number of cell samples in recent large datasets, scalable and efficient imputation models are critical to addressing the sparsity for genome-wide analyses. RESULTS: We proposed a novel graph-based deep learning approach to impute methylation matrices based on locus-aware neighboring subgraphs with locus-aware encoding orienting on one cell type. Merely using the CpGs methylation matrix, the obtained GraphCpG outperforms previous methods on datasets containing more than hundreds of cells and achieves competitive performance on smaller datasets, with subgraphs of predicted sites visualized by retrievable bipartite graphs. Besides better imputation performance with increasing cell number, it significantly reduces computation time and demonstrates improvement in downstream analysis. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at https://github.com/yuzhong-deng/graphcpg.git.

Measurements of abdominal wall defect and hernia sac volume for the treatment of incisional hernia: Application of the ultrasonic volume auto-scan in 50 cases.

PURPOSE: Abdominal incisional hernia is one of the most common complications after surgery. The preoperative evaluation of the area of abdominal wall defect and the hernia sac volume(HCV) is very important for the selection of patch size and incisional herniorrhaphy. Meanwhile the overlap range of reinforcement repair is controversial. This study aimed to explore the value of ultrasonic volume auto-scan(UVAS) in the diagnosis, classification and treatment of incisional hernia. METHODS: Both the width and the area of abdominal wall defect and HCV were measured by UVAS in 50 cases with incisional hernias. In 32 of these cases, the measurements of HCV were compared with those of CT. Classification of incisional hernia based on ultrasonic images were compared with operative diagnosis. RESULTS: The measurements of HCV by UVAS and CT 3D reconstruction had good consistency, of which the mean ratio was 1.0084. According to the location and width of abdominal wall defect, UVAS, which showed good accuracy rate (90%, 96%), reached a good agreement in the classification of incisional hernias with operative diagnoses (Kappa = 0.85, Confidence Interval [0.718,0.996]; Kappa = 0.95, Confidence Interval [0.887,0.999]). The patch area should be at least two times as large as the defect area. CONCLUSIONS: UVAS is an accurate alternative to measure the abdominal wall defect and HCV and classify the incisional hernia, with additional benefits of no radiation exposure and instant bedside interpretation. The use of UVAS is conducive to preoperative assessment of the risk of hernia recurrence and abdominal compartment syndrome.

Ultrasensitive Determination of Natural Flavonoid Rutin Using an Electrochemical Sensor Based on Metal-Organic Framework CAU-1/Acidified Carbon Nanotubes Composites.

Rutin, a natural flavonol glycoside, is widely present in plants and foods, such as black tea and wheat tea. The antioxidant and anti-inflammatory effects of flavonoids are well known. In this study, a new electrochemical rutin sensor was developed using multiwalled carbon nanotubes/aluminum-based metal-organic frameworks (MWCNT/CAU-1) (CAU-1, a type of Al-MOF) as the electrode modification material. The suspension of multiwalled carbon tubes was dropped on the surface of the GCE electrode to make MWCNT/GCEs, and CAU-1 was then attached to the electrode surface by electrodeposition. MWCNTs and CAU-1 were characterized using scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Due to the synergistic effect of CAU-1 and MWCNT-COOH, the prepared sensor showed an ultrasensitive electrochemical response to rutin. Under optimized conditions, the sensor showed a linear relationship between 1.0 × 10-9~3.0 × 10-6 M with a detection limit of 6.7 × 10-10 M (S/N = 3). The sensor also showed satisfactory stability and accuracy in the detection of real samples.

scMelody: An Enhanced Consensus-Based Clustering Model for Single-Cell Methylation Data by Reconstructing Cell-to-Cell Similarity.

Single-cell DNA methylation sequencing technology has brought new perspectives to investigate epigenetic heterogeneity, supporting a need for computational methods to cluster cells based on single-cell methylation profiles. Although several methods have been developed, most of them cluster cells based on single (dis)similarity measures, failing to capture complete cell heterogeneity and resulting in locally optimal solutions. Here, we present scMelody, which utilizes an enhanced consensus-based clustering model to reconstruct cell-to-cell methylation similarity patterns and identifies cell subpopulations with the leveraged information from multiple basic similarity measures. Besides, benefitted from the reconstructed cell-to-cell similarity measure, scMelody could conveniently leverage the clustering validation criteria to determine the optimal number of clusters. Assessments on distinct real datasets showed that scMelody accurately recapitulated methylation subpopulations and outperformed existing methods in terms of both cluster partitions and the number of clusters. Moreover, when benchmarking the clustering stability of scMelody on a variety of synthetic datasets, it achieved significant clustering performance gains over existing methods and robustly maintained its clustering accuracy over a wide range of number of cells, number of clusters and CpG dropout proportions. Finally, the real case studies demonstrated the capability of scMelody to assess known cell types and uncover novel cell clusters.

CaMelia: imputation in single-cell methylomes based on local similarities between cells.

MOTIVATION: Single-cell DNA methylation sequencing detects methylation levels with single-cell resolution, while this technology is upgrading our understanding of the regulation of gene expression through epigenetic modifications. Meanwhile, almost all current technologies suffer from the inherent problem of detecting low coverage of the number of CpGs. Therefore, addressing the inherent sparsity of raw data is essential for quantitative analysis of the whole genome. RESULTS: Here, we reported CaMelia, a CatBoost gradient boosting method for predicting the missing methylation states based on the locally paired similarity of intercellular methylation patterns. On real single-cell methylation datasets, CaMelia yielded significant imputation performance gains over previous methods. Furthermore, applying the imputed data to the downstream analysis of cell-type identification, we found that CaMelia helped to discover more intercellular differentially methylated loci that were masked by the sparsity in raw data, and the clustering results demonstrated that CaMelia could preserve cell-cell relationships and improve the identification of cell types and cell subpopulations. AVAILABILITY AND IMPLEMENTATION: Python code is available at https://github.com/JxTang-bioinformatics/CaMelia. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Chinese expert consensus on adult ventral abdominal wall defect repair and reconstruction.

BACKGROUND: Surgical management of patients with ventral abdominal wall defects, especially complex abdominal wall defects, remains a challenging problem for abdominal wall reconstructive surgeons. Effective surgical treatment requires appropriate preoperative assessment, surgical planning, and correct operative procedure in order to improve postoperative clinical outcomes and minimize complications. Although substantial advances have been made in surgical techniques and prosthetic technologies, there is still insufficient high-level evidence favoring a specific technique. Broad variability in existing practice patterns, including clinical pre-operative evaluation, surgical techniques and surgical procedure selection, are still common. DATA SOURCES: With the purpose of providing a best practice algorithm, a comprehensive search was conducted in Medline and PubMed. Sixty-four surgeons considered as experts on abdominal wall defect repair and reconstruction in China were solicited to develop a Chinese consensus and give recommendations to help surgeons standardize their techniques and improve clinical results. CONCLUSIONS: This consensus serves as a starting point to provide recommendations for adult ventral abdominal wall repair and reconstruction in China and may help build opportunities for international cooperation to refine AWR practice.

Transboundary Environmental Footprints of the Urban Food Supply Chain and Mitigation Strategies.

Food supply has been the central issue of human development for millennia and has become increasingly critical in an urbanizing world. However, the environmental footprints and associated mitigation strategies of food consumption have rarely been comprehensively characterized at urban or regional scales. Here, we analyze the water, carbon, reactive nitrogen, and phosphorus footprints of food consumption in Chinese urban regions and demonstrate how such information can help to formulate tailored mitigation strategies. The results show that in three of the largest urban regions of China, 44-93% of the four footprints are embodied in transboundary food supply. The size of the footprints and the effectiveness of mitigation measures in food supply chain vary across the environmental footprints and urban regions. However, targeting agriculture and food processing sectors in Hebei, Shandong, and Henan provinces can reduce these footprints by up to 47%. Our findings show that the analysis of the environmental footprints along the transboundary food supply chains could inform individualized and effective mitigation targets and strategies.

Current prevalence of perioperative early venous thromboembolism and risk factors in Chinese adult patients with inguinal hernia (CHAT-1).

Venous thromboembolism (VTE) is an important postoperative complication. We investigated and analyzed the current inguinal hernia treatment methods and occurrence of early postoperative VTE in Chinese adults. This study involved data for patients with inguinal hernia hospitalized in 58 general hospitals in mainland China from January 1st, 2017 to December 31st, 2017. Data were retrospectively analyzed using a questionnaire. After data inputting and cleaning, we stratified and statistically analyzed patients' data using Caprini scores to create a high-, middle-, and low-risk group. A total of 14,322 patients with inguinal hernia were admitted to the 58 participating hospitals. After data collation and cleaning, 13,886 patients (97.0%) met our inclusion and exclusion criteria. The percentages of laparoscopic surgery and open surgery were 51.2% and 48.8%, respectively. 16 VTEs occurred during the hospitalization, accounting for 0.1% of all adverse events (95% confidence interval (CI) 0.11-0.13). The incidence of VTE was 0.2% (95% CI 0.18-0.2) in the high-risk group and 0.02% (95% CI 0.01-0.03) in the middle-risk group, based on Caprini scoring, with a significant difference (p < 0.0001). No VTE occurred in the low-risk group. Only 3,250 (23.4%) patients underwent Caprini risk assessment regarding treatment, with 13.2% receiving any prevention and only 1.2% receiving appropriate prevention. The treatment of inguinal hernia in Chinese adults has progressed somewhat; however, the evaluation and prevention of perioperative VTE was seriously neglected, in our study, and the incidence of postoperative VTE was underestimated postoperatively. Risk factors continue to be inadequately considered.

Modeling nitrogen flow in a coastal city-A case study of Xiamen in 2015.

Coastal cities, most of them experiencing growing population and rapid urbanization, are facing reactive nitrogen (Nr) pollution crisis and are considered as Nr hotspots worldwide. Increased human activities generate drastic effects on the nitrogen (N) flows of coastal cities. Nevertheless, the N flows of coastal cities are not clearly understood, and the existing city-scale N flow models cannot depict the detailed N flows in coastal cities. Here, we developed a NItrogen MOdel for COastal ciTy (NIMOCOT) which includes four processes and 14 subsystems and used the Material Flow Analysis (MFA) method to model detailed N flows by taking Xiamen as a case study. The results showed that total N inputs to and outputs from Xiamen in 2015 were 403.8 and 201.7 Gg respectively, with half of total N inputs accumulated in the city. The top two N inputs were N embodied in nonfood goods consumption by households and fossil fuel combustion, accounting for 48.5% and 38.5% of total N inputs to Xiamen respectively. After city internal consumption, 109.5 Gg NOx were emitted mainly from energy and industrial subsystems, accounting for 93.2% of total gaseous Nr emissions to the atmosphere. In the typical coastal city, shipping contributed to 34.0% of the total gaseous Nr emissions to the atmosphere in the transportation sector, ranked after highway (58.0%). Moreover, the largest Nr contributor to the hydrosphere came from riparian import (56.0%) which has a significant impact on the hydrosphere of Xiamen. Our results indicated that enhancing the remove ratio of NOx emissions during fossil fuel consumption, and strengthening watershed managements to low riparian N imports from upstream will be useful for reducing N contaminants in environment of Xiamen, and NIMOCOT model is suitable for tracking the key N pollutant sources and could help to make decisions on cutting associate pollutants in coastal cities.

PretiMeth: precise prediction models for DNA methylation based on single methylation mark.

BACKGROUND: The computational prediction of methylation levels at single CpG resolution is promising to explore the methylation levels of CpGs uncovered by existing array techniques, especially for the 450 K beadchip array data with huge reserves. General prediction models concentrate on improving the overall prediction accuracy for the bulk of CpG loci while neglecting whether each locus is precisely predicted. This leads to the limited application of the prediction results, especially when performing downstream analysis with high precision requirements. RESULTS: Here we reported PretiMeth, a method for constructing precise prediction models for each single CpG locus. PretiMeth used a logistic regression algorithm to build a prediction model for each interested locus. Only one DNA methylation feature that shared the most similar methylation pattern with the CpG locus to be predicted was applied in the model. We found that PretiMeth outperformed other algorithms in the prediction accuracy, and kept robust across platforms and cell types. Furthermore, PretiMeth was applied to The Cancer Genome Atlas data (TCGA), the intensive analysis based on precise prediction results showed that several CpG loci and genes (differentially methylated between the tumor and normal samples) were worthy for further biological validation. CONCLUSION: The precise prediction of single CpG locus is important for both methylation array data expansion and downstream analysis of prediction results. PretiMeth achieved precise modeling for each CpG locus by using only one significant feature, which also suggested that our precise prediction models could be probably used for reference in the probe set design when the DNA methylation beadchip update. PretiMeth is provided as an open source tool via https://github.com/JxTang-bioinformatics/PretiMeth.

Assessing Agricultural Livelihood Vulnerability to Climate Change in Coastal Bangladesh.

The adverse impacts of climate change exert mounting pressure on agriculture-dependent livelihoods of many developing and developed nations. However, integrated and spatially specific vulnerability assessments in less-developed countries like Bangladesh are rare, and insufficient to support the decision-making needed for climate-change resilience. Here, we develop an agricultural livelihood vulnerability index (ALVI) and an integrated approach, allowing for (i) mapping out the hot spots of vulnerability distribution; (ii) identifying key factors of spatially heterogeneous vulnerability; and (iii) supporting intervention planning for adaptation. This study conceptualized vulnerability as a function of exposure, sensitivity, and adaptive capacity by developing a composite index from a reliable dataset of 64 indicators comprising biophysical, agro-ecological, and socioeconomic variables. The empirical studies of coastal Bangladesh revealed that Bhola, Patuakhali, and Lakshmipur districts, around the mouth of the deltaic Meghna estuaries, are the hot spot of vulnerability distribution. Furthermore, the spatially heterogeneous vulnerability was triggered by spatial variation of erosion, cyclones, drought, rain-fed agriculture, land degradation, soil phosphorus, crop productivity, sanitation and housing condition, infant mortality, emergency shelters, adoption of agro-technology. The integrated approach could be useful for monitoring and evaluating the effectiveness of adaptation intervention by substituting various hypothetical scenarios into the ALVI framework for baseline comparison.

Identifying the trade-offs between climate change mitigation and adaptation in urban land use planning: An empirical study in a coastal city.

Cities play a significant role in climate change mitigation and adaptation. Urban land planning shapes the urban form and is considered to be an effective approach for climate change mitigation and adaptation. Yet, there is little knowledge about what urban forms can reduce both greenhouse gas (GHG) emissions and climate stresses while considering trade-offs between them. Here, we investigate the role of urban land use in both climate change mitigation and adaptation. In particular, we assess quantitatively the competition between strategies for mitigation and adaptation and identify potential win-win solutions in land use responses. Using a coastal city as a case study, we find that the land use strategies for unilateral mitigation or adaptation can cause contradicting consequences with respect to the reductions in GHG emissions and climate stresses, i.e. reductions in GHGs could increase climate stresses or vice versa. Poorly integrated strategies potentially may compromise international efforts to meet the Climate Action in the Sustainable Development Goals. Properly integrated mitigation and adaptation strategies, or climate-sensitive land use planning, however, can lead to win-win outcomes and eventually achieve co-benefits. Yet, any co-benefits will gradually diminish if there is a delay in climate-sensitive land use planning, implying growing GHGs and intensified climate stresses. Our analysis indicates that integrating climate change mitigation and adaptation in urban land use needs to be enacted as soon as possible: any delays in implementation reduce the window to act to maximize the co-benefits.

A Hybrid Ensemble Approach for Identifying Robust Differentially Methylated Loci in Pan-Cancers.

DNA methylation is a widely investigated epigenetic mark that plays a vital role in tumorigenesis. Advancements in high-throughput assays, such as the Infinium 450K platform, provide genome-scale DNA methylation landscapes in single-CpG locus resolution, and the identification of differentially methylated loci has become an insightful approach to deepen our understanding of cancers. However, the situation with extremely unbalanced numbers of samples and loci (approximately 1:1,000) makes it rather difficult to explore differential methylation between the sick and the normal. In this article, a hybrid approach based on ensemble feature selection for identifying differentially methylated loci (HyDML) was proposed by incorporating instance perturbation and multiple function models. Experiments on data from The Cancer Genome Atlas showed that HyDML not only achieved effective DML identification, but also outperformed the single-feature selection approach in terms of classification performance and the robustness of feature selection. The intensive analysis of the DML indicated that different types of cancers have mutual patterns, and the stable DML sharing in pan-cancers is of the great potential to be biomarkers, which may strengthen the confidence of domain experts to implement biological validations.

MRCNN: a deep learning model for regression of genome-wide DNA methylation.

BACKGROUND: Determination of genome-wide DNA methylation is significant for both basic research and drug development. As a key epigenetic modification, this biochemical process can modulate gene expression to influence the cell differentiation which can possibly lead to cancer. Due to the involuted biochemical mechanism of DNA methylation, obtaining a precise prediction is a considerably tough challenge. Existing approaches have yielded good predictions, but the methods either need to combine plenty of features and prerequisites or deal with only hypermethylation and hypomethylation. RESULTS: In this paper, we propose a deep learning method for prediction of the genome-wide DNA methylation, in which the Methylation Regression is implemented by Convolutional Neural Networks (MRCNN). Through minimizing the continuous loss function, experiments show that our model is convergent and more precise than the state-of-art method (DeepCpG) according to results of the evaluation. MRCNN also achieves the discovery of de novo motifs by analysis of features from the training process. CONCLUSIONS: Genome-wide DNA methylation could be evaluated based on the corresponding local DNA sequences of target CpG loci. With the autonomous learning pattern of deep learning, MRCNN enables accurate predictions of genome-wide DNA methylation status without predefined features and discovers some de novo methylation-related motifs that match known motifs by extracting sequence patterns.

Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers.

The integration of genomic and DNA methylation data has been demonstrated as a powerful strategy in understanding cancer mechanisms and identifying therapeutic targets. The TCGA consortium has mapped DNA methylation in thousands of cancer samples using Illumina Infinium Human Methylation 450 K BeadChip (Illumina 450 K array) that only covers about 1.5% of CpGs in the human genome. Therefore, increasing the coverage of the DNA methylome would significantly leverage the usage of the TCGA data. Here, we present a new model called EAGLING that can expand the Illumina 450 K array data 18 times to cover about 30% of the CpGs in the human genome. We applied it to analyze 13 cancers in TCGA. By integrating the expanded methylation, gene expression, and somatic mutation data, we identified the genes showing differential patterns in each of the 13 cancers. Many of the triple-evidenced genes identified in majority of the cancers are biomarkers or potential biomarkers. Pan-cancer analysis also revealed the pathways in which the triple-evidenced genes are enriched, which include well known ones as well as new ones, such as axonal guidance signaling pathway and pathways related to inflammatory processing or inflammation response. Triple-evidenced genes, particularly TNXB, RRM2, CELSR3, SLC16A3, FANCI, MMP9, MMP11, SIK1, and TRIM59 showed superior predictive power in both tumor diagnosis and prognosis. These results have demonstrated that the integrative analysis using the expanded methylation data is powerful in identifying critical genes/pathways that may serve as new therapeutic targets.

A robust fuzzy rule based integrative feature selection strategy for gene expression data in TCGA.

BACKGROUND: Lots of researches have been conducted in the selection of gene signatures that could distinguish the cancer patients from the normal. However, it is still an open question on how to extract the robust gene features. METHODS: In this work, a gene signature selection strategy for TCGA data was proposed by integrating the gene expression data, the methylation data and the prior knowledge about cancer biomarkers. Different from the traditional integration method, the expanded 450 K methylation data were applied instead of the original 450 K array data, and the reported biomarkers were weighted in the feature selection. Fuzzy rule based classification method and cross validation strategy were applied in the model construction for performance evaluation. RESULTS: Our selected gene features showed prediction accuracy close to 100% in the cross validation with fuzzy rule based classification model on 6 cancers from TCGA. The cross validation performance of our proposed model is similar to other integrative models or RNA-seq only model, while the prediction performance on independent data is obviously better than other 5 models. The gene signatures extracted with our fuzzy rule based integrative feature selection strategy were more robust, and had the potential to get better prediction results. CONCLUSION: The results indicated that the integration of expanded methylation data would cover more genes, and had greater capacity to retrieve the signature genes compared with the original 450 K methylation data. Also, the integration of the reported biomarkers was a promising way to improve the performance. PTCHD3 gene was selected as a discriminating gene in 3 out of the 6 cancers, which suggested that it might play important role in the cancer risk and would be worthy for the intensive investigation.

[China Guideline for Diagnosis and Treatment of Adult Groin Hernia (2018 edition)].

Inguinal hernia refers to an extraperitoneal hernia occurring in the inguinal region. The etiology of inguinal hernia is not completely clear, but is related to gender, age and family history. According to the anatomy of hernia, there are indirect hernia, direct hernia, femoral hernia, composite hernia and peripheral femoral hernia. According to the content of the hernia sac, it is divided into reducible hernia, irreducible hernia, incarcerated hernia and strangulated hernia. There are also several special types of hernia. Typical inguinal hernia can be diagnosed by medical history, symptoms and physical examination. If the diagnosis is unclear or difficult, the imaging examination can assist the establishment of diagnosis. Only through surgery, inguinal hernia in adult patients could heal. The following requirements should be fulfilled: (1)The surgeons need to acquire accreditation of medical residency and should have corresponding surgical training; (2)The qualification of laparoscopic surgeons require the completion of basic laparoscopic training and hernia fellowship training as well as passing relative examinations; (3)Training of hernia and abdominal wall surgeons should be completed in centers with corresponding qualifications; (4)Preoperative education should be provided to patients and/or their families, emphasizing the communication with patients before surgery and indicating the operation principle and measures, whether mesh should be used, and informed consent should be given. Hernia repair materials are mainly non-absorbable inert mesh. Surgery could be divided into two types: open and laparoscopic surgery, including tissue suture repair, repair with materials, total extraperitoneal repair (TEP) and trans-abdominal preperitoneal repair(TAPP), etc. Combined with the clinical practice in China,we completed the "Guideline for Diagnosis and Treatment of Adult Groin Hernia (2018 edition)" on the basis of the previous edition of the guideline. The relevant medical institutions and peers in China are requested to carry out this guideline according to actual clinical reference.

[China Guideline for Diagnosis and Treatment of Incisional Hernia (2018 edition)].

Abdominal incisional hernia is the result of the loss of the integrity and tension balance of the abdominal wall. According to clinical manifestation and physical examination, most incisional hernia can be clearly diagnosed. For small and concealed incisional hernia, the diagnosis can be confirmed by imaging examination. According to size of defect, it can be divided into small, middle, large, and giant incisional hernia. According to location of lesion, it can be divided into incisional hernia in the central or peripheral region of the anterior abdominal wall, in the lateral abdominal wall, and in the back. According to the presence of recurrence, it can be divided into primary and recurrent incisional hernia. Patients with definite diagnosis and suitable for surgical treatment after risk assessment are recommended for elective surgery. For patients who are not suitable for surgery, appropriate abdominal bandages are recommended to limit the development of incisional hernia. Surgical methods:(1) Simple suture repair is suitable for small incisional hernia; (2) Reinforcement repair using materials is recommended for middle incisional hernia or above; (3) When the materials are used in open repair, onlay and sublay methods are usually adopted. (4) IPOM or underlay methods are always adopted when materials are used for laparoscopic repair; (5) Hybrid repair is performed by combining open and laparoscopic techniques; (6) Methods to increase the abdominal cavity capacity include compartmental separation technology(CST) and lateral transverse abdominal muscle release technology (TAR); (7) Abdominal wall reconstruction with muscle fascial flap can be supplemented with mesh. According to the clinical practice of our country in the recent 4 years and based on "China Guideline for Diagnosis and Treatment of Incisional Hernia (2014 edition)", the " China Guideline for Diagnosis and Treatment of Incisional Hernia (2018 edition) " was completed after discussion and consultation with more than 50 experts and scholars in China. The definitions, etiology, pathophysiology, classification, diagnosis, differential diagnosis, treatment were comprehensively updated, and the viewpoints, measures and methods supported by evidence-based medicine were pointed out. The relevant medical institutions and surgeons in China are requested to carry out the guide according to actual clinical reference.