Molecular mechanisms and cellular process in signal transduction pathway related to air pollutants in obstructive lung diseases:A mini-review

Exposure to air pollutants such as PM_(10),PM_(2.5),PM_(0.1),O_(3),CO,NO2,and SO_(2),and biological pollutants are important factors causing the evolution and furtherance of obstructive lung diseases(OLD),including asthma and chronic obstructive pulmonary disease(COPD).Asthma is the most frequent chronic inflammatory airway disease,characterized by breathlessness,wheezing,chest tightness,and cough,together with the presence of exaggerated expiratory airflow fluctuation that varies over time.COPD is a heterogeneous lung condition characterized by chronic respiratory symptoms such as dyspnea,cough,expectoration,and/or exacerbations due to abnormalities of the airways and/or alveoli that cause persistent,often progressive,airflow obstruction.Understanding the molecular mechanisms and cellular processes based on the development of OLD on exposure to air pollutants will provide insights into the solution of pathogenesis,prevention,and treatment of these conditions.The molecular mechanisms and cellular process involved in signal transduction pathway plays a role in the binding of extracellular signaling molecules and ligands to receptors placed on the cell surface or on the inner side cell that trigger inflammation that occurs,especially when something important enters the cell to bring into a cascade response.This binding then alters the cell metabolism,shape,and gene expression in the airway.This review aimed to reveal the effect of air pollutants on the molecular mechanisms and cellular processes involved in the signal transduction pathways in OLD.

Investigation and Identification of Fungal Diseases of Kiwifruit in Qiandongnan Prefecture

[Objectives]The paper was to investigate and identify the fungal diseases of wild and red heart kiwifruit in Qiandongnan Prefecture.[Methods]The pathogenic fungi were isolated from diseased leaves and fruits of wild and red heart kiwifruit by tissue separation method.DNA sequencing was carried out by using the sequence analysis of ribosomal r DNA-ITS region,and molecular evolutionary trees were built by using MEGA 4.0 software.Finally,the pathogenic fungi were classified and identified by combining morphological observation.[Results]The main fungal diseases were anthracnose caused by Colletotrichum gloeosporioides on wild kiwifruit,fruit anthracnose caused by C.acutatum on red heart kiwifruit,leaf soft rot caused by Fusarium incarnatum on red heart kiwifruit,and brown spot caused by Alternaria alternata on red heart kiwifruit.[Conclusions]The study may provide some theoretical basis for the control of kiwifruit diseases in Qiandongnan Prefecture.

Polyphenol from foxtail millet bran alleviates experimental colitis in mice by remodulating intestinal fungal community

Inflammatory bowel disease(IBD)is a chronic relapsing-remitting systemic disease of the gastrointestinal tract,characterized by an inflammatory process.Gut mycobiota community dysbiosis has been reported that is closely related to the development of IBD.Our previous findings indicated that polyphenol of the inner shell(BPIS)from foxtail millet bran could restore the gut microbiome and inhibit the progress of colorectal cancer(CRC).In the present study,we studied the anti-inflammatory potential of BPIS in the dextran sodium sulfate(DSS)-induced mouse colitis model.Data suggested that BPIS alleviated experimental colitis by restoring body weight,colonic length and protecting the epithelial architecture from damage by DSS.Moreover,we found that BPIS strengthened the gut barrier function and inhibited the activation of Wnt1/β-catenin pathway.Gene sequence analysis indicated that BPIS remodeled the overall structure of the gut mycobiota from colitis mice toward that of the normal counterparts,including 1 phylum and 9 genera.Interestingly,BPIS significantly increased the abundance of Aspergillus ruber.It further verified that BPIS significantly promoted the growth of A.ruber in vitro.Collectively,BPIS has great potential to develop into an effective against IBD drug.

Preliminary Investigation on the Main Fungal Diseases of Sugarcane in Guangxi Province of China

[ Objective ] The purpose was to understand species and occurrence status of major fugal diseases in sugarcane cultivation areas of Guangxi in China, so as to provide scientific references for integrated control against sugarcane diseases. [ Method] Species and occurrence degrees of major fugal diseases in sugarcane cultivation areas of Guangxi were investigated through randomized surveys, farmer interviews, literature references and location investigations from 2009 to 2011. Diseased sugarcane samples were collected and their species were identified through pathogen isolated culture and other relevant methods. [ Result] Thirteen spe- cies of fungal diseases were identified in the survey, including pineapple disease [ Thielaviopsis paradoxa （ de Seynes ） V. Hohnel ], smut （ Ustilago scitaminea Sydow）, top rot disease （Fusarium moniliforme Sheldon）, rust （Puccinia melanocephala H. ＆ P. Syd. ）, leaf scald disease （Stagonospora sacchari Lo et Ling）, red rot disease （Colletotrichumfalcatum Went）, zonate spot disease （Phyllosticta saccharicola P. Henn. ）, leaf red spot disease [ Pellicularia sasakii （Shirai） Ito], white rash disease （Elsinoe sacchari L. ）, eye spot [Helminthosporium sacchari （Breda de Haan） Butler], yellow spot [Mycovellosiella koepkei （kruger） Deighton], brown stripe [Bipolaris stenospilum （Drechs.） Shoem. ] and brown spot （Cercospora longipes Butler）. Smut, rust, top rot, and pineapple disease were the most rampantly detrimental to quality and yield of sugarcane. [ Conclusion] Smut is the most serious sugarcane disease; it is urgent to breed sugarcane varieties with high resistance and excellent agronomic characters to replace current sugarcane varieties susceptible to diseases.

TiO_2 photocatalytic antifungal technique for crops diseases control

TiO2 and 1% Ce^3＋-TiO2 prepared by hydrothermal method were characterized by means of XRD and UV-visible diffusive reflectance spectra（DRS）. The results of DRS analysis indicated that the 1% Ce^3＋-TiO2 catalyst had significant optical absorption in the visible region between 400-450 nm because electrons could be excited from the valence band of TiO2 or cerium oxides to Ce 4f level. To investigate the photocatalytic activity of different catalysts for crop fungal disease control, a series of Quine tests were carried out for cucumber powdery mildew and litchi downy blight control in home-made photocatalytic reactor. The results showed that TiO2 photocatalysis technique should be effective to inhibit the growth of fungal diseases to some extent and P-25 had a higher activity for antifungal control than home-made TiO2 catalysts. TiO2-A prepared with Ti（SO4）2 is more active to contro 1 antifungal disease than TiO2-B prepared with TiOSO4 as precursor because the crystalline of TiO2-A was higher than that of TiO2-B. The antifungal index litchi downy blight control was greatly enhanced by doping 1% cerium ion. The antifungal index of 1.0%Ce3^＋-TiO2 was（47.0 ± 4.7）%, （82.2 ± 3.5）%, （100 ±0.0）% under indoor weaker light, solar light and black light, respectively. The results of field experiments showed that the antifungal index of 1.0%Ce^3＋-TiO2 was more than that of P-25. The antifungal index of 1.0%Ce^3＋-TiO2 was （81.7 ± 6.5）%, （67.5 ±4.7）%, （38.6±1.9）% for litchi downy blight, maize southern leaf spot, and rice blast, respectively. It was concluded that TiO2 photocatalysis technique should be an effective way for litchi fungal disease control in practice.

Heterologous expression of the Haynaldia villosa pattern-recognition receptor CERK1-V in wheat increases resistance to three fungal diseases

Wheat production is under continuous threat by various fungal pathogens.Identification of multipledisease resistance genes may lead to effective disease control via the development of cultivars with broad-spectrum resistance.Plant Lysin-motif(LysM)-type pattern-recognition receptors,which elicit innate immunity by recognizing fungal pathogen associated molecular patterns such as chitin,are potential candidates for such resistance.In this study,we cloned a LysM receptor-like kinase gene,CERK1-V,from the diploid wheat relative Haynaldia villosa.CERK1-V expression was induced by chitin and Blumeria graminis f.sp.tritici,the causal agent of wheat powdery mildew.Heterologous overexpression of CERK1-V in wheat inhibited the development of three fungal pathogens,thereby increased resistance to powdery mildew,yellow rust,and Fusarium head blight.CERK1-V physically interacted with the wheat Lys M protein Ta CEBi Ps.CERK1-V/Ta CEBi Ps interaction promoted chitin recognition and activated chitin signal transduction in wheat.Transgenic plants with excessively high CERK1-V expression showed high resistance but abnormal plant growth,whereas plants with moderate expression level showed adequate resistance level with no marked impairment of plant growth.In transgenic lines,RNA-seq showed that gene expression involved in plant innate immunity was activated.Expression of genes involved in photosynthesis,ER stress and multiple phytohormone pathways was also activated.Optimized expression of CERK1-V in wheat can confer disease resistance without compromising growth or defense fitness.

Research progress of red blood cell distribution width in diagnosis and treatment of lung diseases and prognosis

Lung disease is the disease of the lung itself or lung manifestations of other diseases,including COPD,PTE,CAP,etc.In recent years,the incidence rate has been increased year after year.Many of these diseases have hidden onset and complicated causes.Therefore,accurate diagnosis and treatment are very important.Studies have shown that RDW is closely linked to the diagnosis and treatment of lung diseases.This article analyzes the research on RDW and lung diseases at home and abroad,and briefly summarizes the diagnosis,severity and clinical prognosis of lung diseases by RDW,hoping to provide useful clues and reliable basis for clinical workers,to provide assistance for further application research of RDW in lung diseases.

Wheat Genetic Transformation as Efficient Tools to Fight against Fungal Diseases

Wheat ranks first among cereal crops cultivated in the world. In its production, diseases like powdery mildew, fusarium head blight and rusts caused by fungal pathogens represent a major problem. They produce different symptoms that cause severe crop damage by infecting the spikes, leaves, roots, stems and grains. They are causing losses both by reducing the quantity of the harvested crop and the quality of the product. Quality problems of the harvested product can be due to shrivelled seed, which are frequently found as a consequence of the infection by leaf pathogens, such as mildews, rusts and Septoria. Fusarium head blight is the major culprit for mycotoxin contamination from the harvested grain, causing economic losses and in the worst casing human and animal health problems. In severe epidemics, all these fungal diseases can significantly reduce yield. Resistance to fungi is beneficial not only from a commercial point of view （yield）, but also because of the reduced levels of mycotoxins. The integration of transgenic approaches offers a potential chemical-free and environment-friendly solution for controlling fungal pathogens. This is an essential asset for wheat world food security.

Acupoint selection rules for acupoint application in lung diseases in the post-epidemic era

Objective:To summarize the rules of acupoint selection of acupoint application to prevent and treat lung diseases under the background the post-epidemic era using data-mining technology.Method:The CNKI,Wanfang database,and VIP database were searched for clinical study articles on lung diseases treated by acupoint application published in the past 5 years.Data-eligible papers were extracted to establish a database of acupoint application for lung disease using Microsoft Excel 2019,with the goal of analyzing the frequency of acupoints,acupoint-meridian association,acupoint-location association,specific acupoint frequency,and cluster analysis.Association rules,consisting of acupoints with an application frequency of≥10,were devised by the Apriori algorithm to explore the correlation between acupoint groups and to analyze the rules of the compatibility of acupoint prescriptions.Results:A total of 229 eligible papers met our inclusion criteria.Forty-seven acupoints were applied,for a total frequency of acupoints of 1,035 times.Among these,acupoints for lung diseases were primarily distributed in the back-and-waist and chest-and-abdomen areas.From the analysis of the association rules,we obtained four groups of acupoint association rules based on acupoint clusters with a frequency≥10 and found that Feishu(BL 13),Tiantu(CV 22),Dazhui(GV 14),Dingchuan(EX-B1),and Danzhong(CV 17)constitute the core acupoints of prescriptions for clinical acupoint application to prevent and treat lung diseases.Conclusion:It is clearly shown that the core acupoints are relatively concentrated and that the selected acupoints were mainly locally selected,which could be a matching reference for the long-term prevention and treatment of lung diseases,including COVID-19.

Meta-QTL analysis for mining of candidate genes and constitutive gene network development for fungal disease resistance in maize(Zea mays L.)

The development of resistant maize cultivars is the most effective and sustainable approach to combat fungal diseases.Over the last three decades,many quantitative trait loci(QTL)mapping studies reported numerous QTL for fungal disease resistance(FDR)in maize.However,different genetic backgrounds of germplasm and differing QTL analysis algorithms limit the use of identified QTL for comparative studies.The meta-QTL(MQTL)analysis is the meta-analysis of multiple QTL experiments,which entails broader allelic coverage and helps in the combined analysis of diverse QTL mapping studies revealing common genomic regions for target traits.In the present study,128(33.59%)out of 381 reported QTL(from 82 studies)for FDR could be projected on the maize genome through MQTL analysis.It revealed 38 MQTL for FDR(12 diseases)on all chromosomes except chromosome 10.Five MQTL namely 1_4,2_4,3_2,3_4,and 5_4 were linked with multiple FDR.Total of 1910 candidate genes were identified for all the MQTL regions,with protein kinase gene families,TFs,pathogenesis-related,and disease-responsive proteins directly or indirectly associated with FDR.The comparison of physical positions of marker-traits association(MTAs)from genome-wide association studies with genes underlying MQTL interval verified the presence of QTL/candidate genes for particular diseases.The linked markers to MQTL and putative candidate genes underlying identified MQTL can be further validated in the germplasm through marker screening and expression studies.The study also attempted to unravel the underlying mechanism for FDR resistance by analyzing the constitutive gene network,which will be a useful resource to understand the molecular mechanism of defense-response of a particular disease and multiple FDR in maize.

Automated Classification of Lung Diseases in Computed Tomography Images Using a Wavelet Based Convolutional Neural Network

Recently, convolutional neural networks (CNNs) have been utilized in medical imaging research field and have successfully shown their ability in image classification and detection. In this paper we used a CNN combined with a wavelet transform approach for classifying a dataset of 448 lung CT images into 4 categories, e.g. lung adenocarcinoma, lung squamous cell carcinoma, metastatic lung cancer, and normal. The key difference between the commonly-used CNNs and the presented method is that in this method, we adopt the use of redundant wavelet coefficients at level 1 as inputs to the CNN, instead of using original images. One of the main advantages of the proposed method is that it is not necessary to extract regions of interest from original images. The wavelet coefficients of the entire image are used as inputs to the CNN. We compare the classification performance of the proposed method to that of an existing CNN classifier and a CNN-based support vector machine classifier. The experimental results show that the proposed method outperforms the other two methods and achieve the highest overall accuracy of 91.9%. It demonstrates the potential for use in classification of lung diseases in CT images.

The Differences of Interstitial Lung Diseases in High-Resolution Computerized Tomography and Pulmonary Function Test among Different Connective Tissue Diseases, and the Correlated Factors

Objective. To study the difference of interstitial lung diseases (ILDs) in high-resolution computerized tomography and pulmonary function test among different connective tissue diseases (CTDs). Methods. 209 patients with different CTDs were recruited and underwent lung HRCT and PFT. Eerythrocyte sedimentation rate (ESR), C-reactive protein (CRP), serum ferritin (SF), anti-SSA, and so on were tested. Based on HRCT, a patient was classified into ILD group (CTD+ILD) or non-ILD group (CTD-ILD). HRCT, PFT, and laboratory markers were compared according to CTDs and CTD-associated ILDs. Results. The incidences of ILD were 79.6%, 82.0%, 89.7%, and 97.1% respectively for Rheumatoid arthritis (RA), primary Sjogren’s symptom (pSS), dermatomyositis/polymyositis (DM/PM), and systemic sclerosis (SSc) groups. RA and pSS patients exhibited more nodules, patching, ground-glass opacity, and cord shadow foci in HRCT, DM/PM and SSc patients exhibited more reticular opacity and honeycombing foci. RA and pSS patients exhibited more obstructive ventilatory disorder, small airway dysfunction and emphysema in PFT, and DM/PM and SSc patients exhibited more restrictive ventilatory disorder, mixed ventilatory disorder. ESR, CRP and SF were significantly higher in total CTD+ILD group than in total CTD-ILD group (P = 0.047, 0.006, 0.004, respectively), and higher in different CTD+ ILD groups than in comparable CTD-ILD groups (P = 0.049, 0.048, and 0.023, pSS+ILD, SSc+ILD and RA+ILD compared to pSS-ILD, SSc-ILD and RA-ILD, respectively for ESR, CRP, SF). The positive rate of anti-SSA was significantly higher in DM/PM+ILD group than in DM/PM-ILD group (P = 0.025). Conclusions. The manifestations and incidences of ILDs differ among different CTDs in HRCT and PFT, and inflammation and anti-SSA are positively correlated with ILDs in different CTDs, which provide important evidences for judging disease condition and prognosis.

Increased Levels of Hyaluronic Acid in Bronchoalveolar Lavage from Patients with Interstitial Lung Diseases, Relationship with Lung Function and Inflammatory Cells Recruitment

Purpose: Interstitial Lung Diseases (ILD) are characterized by inflammation and fibrosis. It described the role of hyaluronic acid (HA) as an immune-regulator. It is not known if HA contributes to the recruitment of inflammatory cells associated with ILD. If this hypothesis was correct, then concentrations of HA in bronchoalveolar lavage (BAL) should correlate with the severity of ILD. Methods: We collected BAL from 22 ILD patients and 15 control subjects. We determined HA and cytokine levels by ELISA. In vitro chemotaxis assays were performed by using a transwell system. Results: We found that ILD patients showed a significant increase in HA, IL-6 levels and the amount of cells in BAL compared to control subjects. We detected a significant positive correlation between HA and IL-6 levels (r = 0.53 and p In vitro, HA induced migration of macrophages and monocytes through a CD44-dependent process. BAL from patients with ILD stimulated macro-phage migration and this was abrogated by hyaluronidase. Conclusions: Our results support the hypothesis that HA contributes to the recruitment of monocytes towards the alveolar space, leading to exacerbation of lung inflammation in ILD patients.

Psychological and Social Health Status of Patients with Lung Diseases in Jordan

Objective: The study aims to investigate the psychosocial health status of patients with pulmonary diseases in Jordan. Methods: A cross-sectional survey using 230 patients diagnosed with lung diseases from six major hospitals in Jordan used to collect data in regards to depressive symptoms, psychological distress, coping, life satisfaction, and perceived social support. Data were collected from Jan 2013 to May 2013. Results: About 50% of the patients reported moderate levels of ability to effectively cope with life situations, life satisfaction, psychological distress, and perceived social support from family, friends and others. About 29% of the patients reported that they had moderate to severe depressive symptoms. Depressive symptoms had significant and negative correlation with life satisfaction and perceived social support (r = ﹣0.21 to ﹣0.39, p β = 2.72, p = 0.007), marital status (β = 2.63, p = 0.009), and life satisfaction (β = ﹣4.54, p ≤ 0.001) were the significant predictors of depressive symptoms. Conclusion: Health professionals need to screening for psychological disturbances for their patients. There should be integration between early detection of psychological disturbances and implementation of effective treatment plans.

Non-Invasive Early Diagnosis of Obstructive Lung Diseases Leveraging Machine Learning Algorithms

Lungs are a vital human body organ,and different Obstructive Lung Diseases(OLD)such as asthma,bronchitis,or lung cancer are caused by shortcomings within the lungs.Therefore,early diagnosis of OLD is crucial for such patients suffering from OLD since,after early diagnosis,breathing exercises and medical precautions can effectively improve their health state.A secure non-invasive early diagnosis of OLD is a primordial need,and in this context,digital image processing supported by Artificial Intelligence(AI)techniques is reliable and widely used in the medical field,especially for improving early disease diagnosis.Hence,this article presents an AIbased non-invasive and secured diagnosis for OLD using physiological and iris features.This research work implements different machine-learning-based techniques which classify various subjects,which are healthy and effective patients.The iris features include gray-level run-length matrix-based features,gray-level co-occurrence matrix,and statistical features.These features are extracted from iris images.Additionally,ten different classifiers and voting techniques,including hard and soft voting,are implemented and tested,and their performances are evaluated using several parameters,which are precision,accuracy,specificity,F-score,and sensitivity.Based on the statistical analysis,it is concluded that the proposed approach offers promising techniques for the non-invasive early diagnosis of OLD with an accuracy of 97.6%.

Transbronchial Lung Cryobiopsy in the Diagnosis of Interstitial Lung Diseases. Looking at the Holy Grail or Another Misleading Diagnostic Approach?

Interstitial lung diseases (ILD’s) are a group of heterogenous chronic, ferociously progressive lung diseases. The aetiology of the aforementioned diseases is not always recognisable. The diagnosis of these dismal diseases is a vivid challenge for the physicians. Through the intervening years different diagnostic algorithms have been implemented towards more accurate outcome. Different types of ILD’s demand diverse diagnostic approaches. In the latest years a novel diagnostic mini invasive approach seems to gain continuously terrain towards the diagnosis of ILD’s. Transbronchial cryobiopsy may be the Holy Grail in the diagnosis of these diseases or a misleading diagnostic tool in this challenging field.

Interstitial Lung Diseases Associated with Connective Tissue Pathologies: Radiologic Features

Introduction: The high resolution computed tomography (HRCT) is an important part in the diagnostic approach of interstitial lung disease (ILD) associated with connective tissue diseases (CTD) by providing detailed information on the elementary lesion and the radiological pattern of ILD. Aim: to point out the role of HRCT in the diagnosis of ILD associated with CTD (ILD-CTD). Methods: A Retrospective descriptive study was conducted between 2008 and 2017. Data of 24 patients presenting ILD-CTD were collected. A review of HRCT was performed by a radiologist without knowledge of the CTD. Results: Predominant elementary lesion of ILD associated with dermatomyositis (9 cases) was ground glass opacity (n = 9) followed by consolidation (n = 6). Non Specific Interstitial Pneumonia (NSIP) was the most reported pattern (5 cases). Ground glass opacity was also the predominant elementary lesion for the 2 cases of scleroderma and in Sj&#246gren’s syndrome (4 cases/5). NSIP was the predominant radiological presentation in these two CTD. Lymphoid interstitial pneumonia revealed Sj&#246gren’s syndrome in one case. In rheumatoid arthritis (6 cases), the elementary HRCT lesions were irregular interlobular septal thickening (n = 4) and honeycombing (n = 4) consistent with Usual Interstitial Pneumonia (UIP) in 2 cases. Similarly UIP has been described for the 2 patients with lupus and mixed connective tissue disease. Conclusion: HRCT plays an important role in the management of ILD-CTD. Description of the HRCT elementary lesions and the radiological pattern of ILD can be helpful for CTD’s diagnosis.

The implication of dendritic cells in lung diseases:Immunological role of toll-like receptor 4

The immune responses play a profound role in the progression of lung lesions in both infectious and non-infectious diseases.Dendritic cells,as the"frontline"immune cells responsible for antigen presentation,set up a bridge between innate and adaptive immunity in the course of these diseases.Among the receptors equipped in dendritic cells,Toll-like re-ceptors are a group of specialized receptors as one type of pattern recognition receptors,capable of sensing environmental signals including invading pathogens and self-antigens.Toll-like receptor 4,a pivotal member of the Toll-like receptor family,was formerly recognized as a receptor sensitive to the outer membrane component lipopolysaccharide derived from Gram-negative bacteria,triggering the subsequent response.Moreover,its other essential roles in immune responses have drawn significant attention in the past decade.A better under-standing of the implication of Toll-like receptor 4 in dendritic cells could contribute to the management of pulmonary diseases including pneumonia,pulmonary tuberculosis,asthma,acutelung injury,and lung cancer.

Changes in fungal community and diversity in strawberry rhizosphere soil after 12 years in the greenhouse

Soil fungi play a very important role in the soil ecological environment. In agricultural production, long-term monoculture and continuous cropping lead to changes in fungal community diversity. However, the effects of long-term monoculture and continuous cropping on strawberry plant health and fungal community diversity have not been elucidated. In this study, using high-throughput sequencing(HTS), we compared the fungal community and diversity of strawberry rhizosphere soil after various durations of continuous cropping(0, 2, 4, 6, 8, 10 and 12 years). The results showed that soil fungal diversity increased with consecutive cropping years. Specifically, the soil-borne disease pathogens Fusarium and Guehomyces were significantly increased after strawberry continuous cropping, and the abundance of nematicidal(Arthrobotrys) fungi decreased from the fourth year of continuous cropping. The results of correlation analysis suggest that these three genera might be key fungi that contribute to the changes in soil properties that occur during continuous cropping. In addition, physicochemical property analysis showed that the soil nutrient content began to decline after the fourth year of continuous cropping. Spearman's correlation analysis showed that soil pH, available potassium(AK) and ammonium nitrogen(NH_4^+-N) were the most important edaphic factors leading to contrasting beneficial and pathogenic associations across consecutive strawberry cropping systems.

An Integrated QTL Map of Fungal Disease Resistance in Soybean (Glycine max L. Merr):A Method of Meta-Analysis for Mining R Genes

Diseases caused by fungal pathogens account for approximately 50% of all soybean disease losses around the world. Conflicting results of fungal disease resistance QTLs from different populations often occurred. The objectives of this study were to： （i） evaluate evidence for reported fungal disease resistance QTLs associations in soybean and （ii） extract relatively reliable and useful information from the ＂real＂ QTLs and mine putative genes in soybean. An integrated map of fungal disease resistance QTLs in soybean was established with soymap 2 published in 2004 as a reference map. QTLs of fungal disease resistance developed from each of separate populations in recent 10 years were integrated into a combinative map for gene cloning and marker assisted selection in soybean. 107 QTLs from different maps were integrated and projected to the reference map with the software BioMercator 2.1. A method of meta-analysis was used to narrow down the confidence interval, and 23 ＂real＂ QTLs and their corresponding markers were obtained from 12 linkage groups （LG）, respectively. Two published R genes were found in these ＂real＂ QTLs intervals. Sequences in the ＂real＂ QTLs intervals were predicted by GENSCAN, and these predicted genes were annotated in Goblet. 228 resistance gene analogs （RGAs） in 12 different terms were mined. The results will lay the foundation for a bioinformatics platform combining abundant QTLs, and offer the basis for marker assisted selection and gene cloning in soybean.