Supplemental Digital Content is available in the text Long noncoding RNAs (LncRNAs) are involved in the development and progression of various cancers. Accumulating evidences indicated that expression of lncRNAs was related to the prognosis of tumors.Here, 3 well-known lncRNAs associated with cancer were gathered to prove the potential role of lncRNAs as novel predictors of survival in human cancer. This meta-analysis collected all eligible studies about TUG1, SPRY4-IT1, and HULC and explored the relationship between lncRNAs expression and lymph node metastasis (LNM) or overall survival (OS). A comprehensive, computerized literature search was undertaken by using PubMed, EMBASE, Cochrane Library, and Web of Science . Strength of association between 3 lncRNAs and cancer prognosis was assessed by computing the hazard ratios (HR) with its corresponding 95% confidence interval (CI). According to the inclusion and exclusion criteria, respectively, 10, 9, and 7 studies of 3 lncRNAs were included in this meta-analysis.In the current meta-analysis, it could be concluded that the expression of these 3 lncRNAs in tumor tissues is not a direct evidence of LNM. In general, there was a significant negative correlation between TUG1 levels and OS time , SPRY4-IT1 levels and OS time  and HULC levels and OS time . It could be revealed from the result that high level expression of these 3 lncRNAs might be correlated with a bad prognosis.In conclusion, the current meta-analysis demonstrated that TUG1, SPRY4-IT1, and HULC might serve as a moderate predictor of survival in human cancer. As known to us that, in the early stage of tumors without lymph node metastasis (LNM) or distant metastasis, some therapies such as chemotherapy, radiotherapy, and surgery, are effective. However, because of their gradual progression and nonspecific symptoms, most cancers are usually diagnosed in advanced stage.Cancer has been a serious public health problem world widely since the beginning of the 20th century, the overall incidence and mortality rate are on the rise.Furthermore, the prognosis of tumor cannot be fully interpreted by the current cancer staging. The 2 types of commonly used cancer staging methods are as follows. One is Clinical staging: I, II, III, IV, based on a large number of case studies and follow-up results analysis, grouped by the survival rate of patients staging. The other is the TNM staging method. TNM staging determines the local tumor size (T), whether there is regional lymph node metastasis and extent of transfer (N), or distant metastasis (M). TNM stages of tumor lesions are described in detail.As the development of gene sequencing technology and indepth study of cancer biology, these 2 stage standards have encountered enormous challenges. The more we study the biology of cancer, the more things should be updated, like staging standard and diagnostic methods of cancer. Therefore, early detection of tumors, especially, finding a novel molecular cancer marker is both important and necessary for cancer patients to have timely treatment. Biomarker is indispensable to predict LNM and prognosis by observing the progression of cancers and estimating the prognosis.,4 long noncoding RNAs (lncRNAs), defined as noncoding transcripts 200 nucleotides longer in length, have been involved in the development of various human diseases, particularly in cancers.–9 LncRNAs also play crucial regulatory roles in different cellular processes, such as gene regulation, posttranslational processing, and tumor genesis.Because of the rapid development of second-generation sequencing technology,–15 LncRNA-taurine up-regulated1 (TUG1) was initially detected in a genomic screen for genes upregulated in response to taurine treatment in developing mouse retinal cells. SPRY4 intronic transcript 1 (SPRY4-IT1), which was observed in melanoma, could modulate cell proliferation, cell apoptosis, and invasion. Hepatocellular carcinoma upregulated long noncoding RNA (HULC), located in Chromosome 6p24.3, first found in hepatocellular carcinoma (HCC) patients, has been highly associated with cancers’ diagnosis. TUG1, SPRY4-IT1, and HULC were involved in the occurrence and development of various cancers including muscle-invasive bladder cancer (MIBC), esophageal squamous cell carcinoma (ESCC), glioma (GLA), osteosarcoma (OSA), colorectal cancer (CRC), gastric cancer (GC), renal cell carcinoma (RCC), and nonsmall cell lung cancer (NSCLC).,26 Their aberrant expressions were closely linked to the clinical pathological characteristics, such as lymph node metastasis, distant metastasis, and overall survival. Therefore, the lncRNA-TUG1, SPRY4-IT1, and HULC may function as potential markers in predicting the prognosis of patients with various kinds of cancer.Meanwhile, it has been shown that many lncRNAs can function as oncogenes or tumor suppressors.However, major limitation also has been revealed for the insufficient size of samples and inconsistent results. Therefore, a systematic review and meta-analysis has been carried out to explore the expression of these 3 well-known lncRNAs  and lymph node metastasis and the overall survival to prove these 3 lncRNAS might serve as biomarkers in cancer prognosis and diagnosis.22.1 All analyses were based on previous published studies, thus no ethical approval and patient consent are required.This report is strictly in accordance with the PRISMA guidelines.2.2Electronic databases PubMed, EMBASE, Cochrane Library, and Web of Science were systematically performed by using “lncRNA-TUG1 or TUG1 and cancer or tumor or carcinoma,” “lncRNA-SPRY4-IT1 or SPRY4-IT1 and cancer or tumor or carcinoma,” “lncRNA-HULC or HULC and cancer or tumor or carcinoma” as keywords separately, to identify potentially relevant studies. The latest update of searching was on October 10, 2017.2.3Inclusion criteria of the studies are as follows: Articles associating with these 3 well-known lncRNAs  expression and prognosis of the patients should be investigated. Patients were grouped according to the expression levels of lncRNAs, which were measured in primary tumor tissues. Related clinical pathological characteristics were reported, including lymph node metastasis. Clinical outcomes including overall survival were reported. Eligible articles should contain information on hazard ratios (HR) and corresponding 95% confidence intervals (CI), even if there is no explicit HR in the text, a survival curve should be contained. It is available for the full text. Exclusion criteria are as follows: duplicate publications; nonhuman study or noncomparative or irrelevant; reviews, case reports, letters, editorials, and expert opinions; studies were not grouped according to the expression level of lncRNAs; and studies without available data .2.4,29 and the recommendations on the biomarker research report.,31The biased risk assessment of each eligible study was based on the basis for assessing the internal validity of the prognostic article2.5: first author, publication date, country of origin, tumor type, detected sample size, detection method of these 3 well-known lncRNAs  expression levels, cut-off values, number of high lncRNAs expression group and low lncRNAs expression group, number of patients with lymph node metastasis, survival analysis, multivariate analysis, follow-up period, HR, and corresponding 95% CIs for overall survival (OS). If only Kaplan–Meier curves were available, data from the graphical survival plots have been extracted and the HRs have been estimated. The process of data extraction was standardized by 3 authors  and 1 author (YCL) independently intervened to monitor the whole process and achieved consensus in the case of disagreement. All calculations mentioned above were based on the methods illustrated by Parmar et al and Tierney et alAccording to our criteria, 2 authors (BC and PXH) independently assessed the qualification of the retrieved articles being searched. Any doubt was committed by consensus with YEZ. About data extraction tools, firstly, a standardized Microsoft Excel table has been adopted according to the CHARMS checklist and Tierney et al.According to the inclusion and exclusion criteria, data were extracted independently by 3 authors . Disagreements were resolved by 2 investigators  through discussions. The extracted information for each eligible study included: first author, publication date, country of origin, tumor type, detected sample size, detection method of these 3 well-known lncRNAs  expression levels, cut-off values, number of high lncRNAs expression group and low lncRNAs expression group, number of patients with lymph node metastasis, survival analysis, multivariate analysis, follow-up period, HR, and corresponding 95% CIs for OS. If only Kaplan–Meier curves were available, we extracted data from the graphical survival plots and estimated the HRs. All calculations mentioned above were based on the methods illustrated by Parmar et al2.6 To evaluate the heterogeneity of the eligible studies, pooled HR were executed by using I2 statistics in this meta-analysis. Subgroup analysis was performed on the basis of the expression of lncRNAs. For studies evaluating the association between TUG1 expression and prognosis, the subgroup analysis was adopted to discuss the effects of high and low expression of TUG1 in diverse cancers respectively. HULC also uses the above method for subgroup analysis. The random-effects model was employed for the meta-analysis. Sensitivity analyses are important components of meta-analyses to assess the sensitivity of heterogeneity measures to exclusion of studies, and sensible in particular to define a ‘desired threshold’ in terms of the I2 or tau-square statistic. The potential publication bias was measured through the Egger test. P < .05 were examined to be statistically significant.All the statistical analyses were performed with Stata 12.0. The result of the odds ratios was calculated according to the bivariate variables of LNM results. Data of pooled HR were extracted from the qualified studies; the log HR and standard error (SE) were used for combination of the survival results.33.1A total of 79 TUG1), 61 (SPRY4-IT1), and 114 (HULC) published records were retrieved in our preliminary search by looking up the keywords. Moreover, 15, 22, and 36 duplicate references subsequently were excluded. After the title and abstract being screened, 49, 24, and 63 irrelevant references were further excluded. Upon further review of the full articles, a total of 26 publications addressing the relationship between lncRNA and cancer LNM or OS were found to meet all of the inclusion criteria and used for data extraction. Finally, this current meta-analysis was conducted for the remaining 10 (TUG1), 9 (SPRY4-IT1), and 7 (HULC) studies.  in Table –26,36–50The eligible studies were published from 2014 to 2017. In the total 26 included studies, 24 were from China and the other 2 were from Czech Republic and Brazil. The types of cancers in the included studies were as follows: muscle-invasive bladder cancer, nonsmall cell lung cancer, glioma, osteosarcoma, colorectal cancer, gastric cancer, renal cell carcinoma, urothelial carcinoma of the bladder, esophageal squamous cell carcinoma, ovarian cancer, and cervical cancer. All the detected samples were tissues or frozen tissues from patients without chemotherapy or radiotherapy before surgery. The expression of TUG1, SPRY4-IT1, and HULC was measured by qRT-PCR and normalized to GAPDH or β-actin. In all the studies, the patients were divided into 2 groups: high and low expression of lncRNAs. All the diagnoses of lymph node metastasis were based on pathology. Among the 26 included studies, not all studies were examined with both OS and LNM. All the studies were of high quality (Table 3.33.3.1P = .459), which meant the expression of TUG1 might not be a direct predictor of LNM , which revealed that the expression of SPRY4-IT1 might not be an available predictor of LNM  , that is the expression of HULC does have a positive influence on LNM. HULC might serve as a direct predictor of LNM. . However, the significant heterogeneity did not exist across studies in the down-regulated group of 3 studies. The fixed-effects model was used to calculate the pooled HR with corresponding 95% CI for TUG1 expression was confirmed . According to meta-analysis result, it can be found that the expression of TUG1 might be associated with poor overall survival in different cancers.  of 962 patients according to TUG1 expression levels. The random-effects model that was used to calculate the pooled HR with corresponding 95% CI because the between-study heterogeneity among the upregulated group for TUG1 expression was confirmed . According to meta-analysis result, it is known that high expression of SPRY4-IT1 might be associated with poor overall survival in tumors   Fig.  B. In a P = .162 for heterogeneity test, I2 = 38.8%). However, the significant heterogeneity did exist across studies in the other group of 2 studies. The random-effects model that was used to calculate the pooled HR with corresponding 95% CI for HULC expression was confirmed . According to meta-analysis result, it can be seen that the expression of HULC might be associated with poor overall survival in various types of carcinomas , publication bias was shown in group SPRY4-IT1, whereas no significant publication bias was observed by the Egger test in the other 2 groups (Supplement-1). Sensitivity analyses were presented in Supplement-2. Although a single study each time in 3 groups was removed, there was no significant impact on the result patterns.Publication bias of the present meta-analysis was evaluated by Egger test. In OS group, according to Egger's test , it is possible that some relevant papers have been missed out. Second, the cut-off definition of lncRNAs expression was different in each study because it was difficult to define a standard cut-off in different types of cancers. Third, some of retrieved articles may not have provided the most accurate estimate of the HR as much as possible, because these data were extracted from Kaplan–Meier curves at most times. However, this approach does not produce a significantly different result from the direct method of HR estimation. Fourth, tau-square, alike  H19, UCA1,and HOTAIR. More and more reports point out that lncRNAs could act as tumor markers in both diagnosis and predicting the prognosis. Currently, however, there are a few meta-analyses to summarize the study of lncRNAs and molecular markers in prognosis of cancer. There is no doubt that lncRNAs are important regulators in various types of human cancers, thus, the research is promising in the area of tumors.Despite of the significant progress in early diagnosis, surgical techniques, and chemotherapy, the prognosis of patients with cancer is yet unsatisfactory. There are still many challenges to be dealt with, for example, lack of diagnostic and prognostic markers for cancers, limited efficiency treatment, and molecular targeted therapy. Therefore, more and more novel strategies should focus on the identification of innovative prognostic biomarkers of cancers. In recent years, lncRNAs were found out relating with human cancers and more than thousands of lncRNAs have been found and reported, such as AFAP1-AS1,6In conclusion, this meta-analysis provides evidences that expressions of 3 lncRNAs  are significantly associated with overall survival in cancer patients, which means that these 3 lncRNAs may have great potential to be an accurate biomarker to reveal the value of diagnosis and prognosis in diverse cancers. However, there are still many difficulties to overcome, more and more well-designed studies according to the PICOS setting and methodological characteristics  with large sample sizes are required to confirm the validity and effectiveness of applying TUG1, SPRY4-IT1, and HULC in the diagnosis and prognosis of cancer patients.The authors are indebted to the donors whose names were not included in the author list, but participated in this program.


Since the control rate of blood pressure is lower in mainland China, the aim of this study is to investigate the proportion of secondary causes and coexisting diseases of hypertension in hypertensive patients. Data on consecutive patients with hypertension who visited the Hypertension Center. Diseases were detected using an established strict screening protocol. Detection rate of secondary causes and coexisting diseases of hypertension was 39.5% among 3003 hypertensive patients. Obstructive sleep apnea (OSA) was the most common, accounting for 24.7% of patients, followed by primary aldosteronism (PA) (5.8%) and PA + OSA (4.9%). Endocrine hypertension accounted for 12.1% of patients, including 10.7% of patients with PA, 1.1% with hypothyroidism, 0.1% with pheochromocytoma, 0.1% with Cushing's syndrome, and 0.1% with hyperthyroidism, respectively. Those who smoke, those who are obese, and those who have diabetes accounted for 31.3%, 27.5%, and 16.6% of total patients, respectively. There were overlapping conditions in secondary causes and coexisting diseases of hypertension. OSA was the most common in each age- and BMI-stratified group. Findings from the current study suggest an increasing frequency of secondary forms of hypertension, highlighting the burden of OSA and PA in hypertensive patients. Hypertension is a major modifiable risk factor for morbidity and mortality of cardiocerebrovascular diseases and renal failure . The conThe specialty center, Hypertension Center of a provincial general hospital of Xinjiang, Northwest of China, in which this study is conducted provides diagnosis and individualized treatment to hypertensive population in this region, particularly screening, diagnosis, and treatment service of secondary causes and coexisting diseases of hypertension including endocrine diseases such as primary aldosteronism, Cushing's syndrome, pheochromocytoma, and thyroid dysfunctions; respiratory diseases like obstructive sleep apnea; psychological factors such as anxiety; renal disease; and vascular diseases.The aim of this study is to evaluate the proportion of secondary causes and coexisting diseases of hypertension in those who visited the center with the main complaint of elevated BP.Consecutive patients with hypertension referred to Hypertension Center of the People's Hospital of Xinjiang Uygur Autonomous Region, China, since January to December 2010, meeting the following inclusion criteria, were included into the current study. Inclusion criteria were as follows: age ≥ 18 years, new onset hypertension, previously diagnosed hypertension on antihypertensive treatment, or BP could not reach target (SBP < 140 mmHg and/or DBP < 90 mmHg) if without antihypertensive treatment. This study was approved by the Hospital Ethics Committee, and all patients provided written informed consent.Hypertension was defined according to the criteria established by the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood pressure . Office A complete history and physical examination were performed by specialists in the clinic. Laboratory tests include measurements of serum electrolytes, creatinine, blood glucose, cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-c), low density lipoprotein cholesterol (LDL-c), and hemoglobin, as well as tests for proteinuria and urinary sediment. Electrocardiogram and renal ultrasound were recorded in all patients. Patients with suspicious symptoms, signs, and laboratory examinations were suggested for further evaluation of secondary causes of hypertension, with particular attention given to the following: the age < 30 years at onset of hypertension, resistant hypertension, severe hypertension or hypertensive emergencies, sudden increase of BP in a previously stable patient, accelerated hypertension, severe target organ damage not matched for the duration of high BP, hypertension with adrenal incidentaloma, exaggerated diurnal sleepiness, nocturnal snoring, paroxysmal hypertension, hematuria, proteinuria, increased serum creatinine, hypokalemia, an abdominal bruit, particularly when diastolic, differences of >1.5 cm in the length between the two kidneys via renal ultrasound, and so forth . The proPatients were diagnosed with hypertension after a renal disease history. These patients also had abnormalities of urinary sediment including hematuria and proteinuria, and serum creatinine in the upright position (>177 umol/L) and/or pathological diagnosis after kidney biopsy and/or imaging showed abnormalities in morphology and structure of kidney.Renal artery stenosis was confirmed by angiogram and/or computed tomography angiography (CTA). Angiostenosis > 50% was confirmed positive .−1·h−1) in addition to an elevated aldosterone level (>12 ng·L−1) or an ARR (the PAC to PRA ratio) greater than 20 ng/dl per ng/ml/h was considered suggestive of PA. PA was confirmed with saline infusion test. Adrenal vein sampling (AVS) was conducted to identify bilateral or unilateral subtypes of PA.The screening process and diagnosis of PA was made based on 2008 endocrine society's guideline  and on t131I-meta-iodobenzyl guanidine scanning, and PET-CT [Diagnosis of pheochromocytoma was based on elevated plasma metanephrines and normetanephrines, localization of the tumor was visualized by CT, magnetic resonance imaging (MRI), d PET-CT . And finCushing's syndrome was diagnosed on hormonal assessments, including nonsuppressible serum cortisol after 1 mg of overnight dexamethasone and 48 h low-dose (2 mg) dexamethasone suppression tests. The diagnosis of location was based on the measurement of ACTH levels, a 48 h high-dose (8 mg) dexamethasone suppression test, and CT/MRI. A cortisol level higher than 5 ug/dl was not considered suppressed (a positive result) .Serum thyrotropin (TSH), free thyroxine (FT4), and triiodothyronine (FT3) levels were measured. The cut-off levels for TSH were <0.35 IU/dl for hyperthyroidism and >5.5 IU/dl for hypothyroidism. The cut-off levels for FT4 were <11.5 ng/dl for hypothyroidism and >22.7 ng/dl for hyperthyroidism. The cut-off levels for FT3 were <3.0 ng/dl for hypothyroidism and >9.2 ng/dl for hyperthyroidism.All patients suspicious of OSA underwent full-night polysomnography. Diagnosis of OSA was based on 2009 clinical guideline of American Academy of Sleep Medicine . OSA wasPatients with excessive anxiety, fear, worry, avoidance, and compulsive rituals as well as sleeplessness, vague pains, headaches, dizziness, stomach upset, or other somatic symptoms but no parenchymal disease were considered to have anxiety disorders. The Hamilton Anxiety Scale was used to assess the degree of anxiety disorders. The diagnosis was based on clinical practice guidelines  and the If patients complained of both fatigued lower extremities, pulse palpation of arteria cruralis and arteria poplitea were decreased, or if the blood pressure values for the upper extremities are greater than that in the lower ones, then aortic coarctation was considered the probable cause. Then CTA was performed for definite diagnosis of aortic coarctation in these specific subjects.Liddle's syndrome and polycystic ovary syndrome were diagnosed according to the published literature , 17. t-test was used to estimate differences between two independent groups. Comparison of frequencies was performed by the Pearson χ2 test. A P value < 0.05 was considered significant.Analysis was performed with the Statistical Package for the Social Sciences, version 17.0. statistical software. The results were expressed for continuous variables with a normal distribution as the mean and standard deviation (SD). Qualitative variables were expressed as frequencies. The independent Student's3987 hypertensive patients were evaluated during the 12-month study period, of whom 3003 patients (mean age: 52 years) were suggested for further evaluation of secondary causes or coexisting diseases of hypertension, including 1597 males and 1406 females. Study flow chart was shown in As given in As shown in P < 0.001 for both). Inversely, detection of anxiety significantly decreased along with BMI increasing . There was significantly higher detection of PA in nonobese subjects than in obese subjects.Tables The present study systematically evaluated the secondary causes and coexisting diseases of hypertension in hypertensive patients extensive in sample size using strict protocols in the specialty center of hypertension dedicated to screening, diagnosis, and treatment service of secondary causes of hypertension in Northwest of China. The data demonstrated that the detection rate of secondary causes and coexisting diseases of hypertension, including endocrine diseases, RPD, RAS, and OSA, was 39.5% among 3003 hypertensive patients. OSA and PA were the most common secondary causes and coexisting diseases of hypertension among hypertensive patients. Previous studies described that prevalence of secondary causes of hypertension ranges from 4.7% to 10.5% –20 and tPrevalence of secondary causes of hypertension has been encountered with increasing frequency in recent years. A recent study evaluating secondary causes of true resistant hypertension in patients aged 19 to 65 years showed that OSA was present in 71.2%, PA in 15.7%, and RAS in 5.4% , 23, posOSA is considered an important independent risk factor for cardiovascular diseases in general, especially for hypertension , and proConsistent with previous studies, present study also observed that PA is diagnosed in 10.7% of hypertensive patients. Prevalence of PA was initially estimated to be 1-2%, whereas it has been recently reported to be 5–16.6% in patients with hypertension , 35 and A novel finding in our study is that several patients had multiple secondary causes, including 146 patients with PA + OSA and 5 with OSA + hypothyroidism. Previous studies have shown that severity of OSA is related to the degree of aldosterone excess and that it is greater in resistant hypertension with hyperaldosteronism , 37. TheA recent systematic review and meta-analysis suggests that there is an association between anxiety and increased risk of hypertension . Individ2 in our study.In the current study, OSA and PA were observed to be the most common secondary causes of hypertension and coexisting disease in males; PA were in females. Patients with OSA were characterized by male gender, younger to middle-age, and higher BMI, patients with PA were characterized by female gender, younger to middle-age, and higher BMI, and patients with anxiety were by female gender and lower BMI. Patients with RPD were seen more in males and in those with BMI < 24 kg/mThe current study, however, contains some limitations. First, specialist bias might be present since all the subjects had been referred to the hypertension specialty center. Second, this is a single center study, only showing detection of secondary causes and coexisting diseases from single hypertension center in Northwest of China. Therefore, our data may not represent the prevalence of secondary causes of hypertension in general hypertensive population. Third, the current study was not involved in a detailed investigation in all hypertensive patients. Patients with positive initial screening performed additional exams, which may have underestimated the real prevalence of several secondary forms of hypertension. Fourth, we have not flowed up these patients with secondary hypertension to observe the specific treatment effects such as continuous positive airway pressure and adrenalectomy, whereas the follow-up work is planned to be performed recently within the nearest future, and we might obtain further evidence on the effects of pathogenetic cause-specific treatment in this population.In conclusion, this study shows that the detection rate of secondary causes and coexisting diseases in hypertensive patients is 39.5% in a specialty center for hypertension in Northwest China. OSA and PA were the common secondary causes of hypertension. Findings from the current study suggest an increasing frequency of secondary forms of hypertension, highlighting the burden of OSA and PA in hypertensive patients.


The number and amount of man-made chemicals present in the aquatic environment has increased considerably over the past 50 years. Among these contaminants, endocrine-disrupting chemicals (EDCs) represent a significant proportion. This family of compounds interferes with normal hormonal processes through multiple molecular pathways. They represent a potential risk for human and wildlife as they are suspected to be involved in the development of diseases including, but not limited to, reprotoxicity, metabolic disorders, and cancers. More precisely, several studies have suggested that the increase of breast cancers in industrialized countries is linked to exposure to EDCs, particularly estrogen-like compounds. Estrogen receptors alpha (ERα) and beta (ERβ) are the two main transducers of estrogen action and therefore important targets for these estrogen-like endocrine disrupters. More than 70% of human breast cancers are ERα-positive and estrogen-dependent, and their development and growth are not only influenced by endogenous estrogens but also likely by environmental estrogen-like endocrine disrupters. It is, therefore, of major importance to characterize the potential estrogenic activity from contaminated surface water and identify the molecules responsible for the hormonal effects. This information will help us understand how environmental contaminants can potentially impact the development of breast cancer and allow us to fix a maximal limit to the concentration of estrogen-like compounds that should be found in the environment. The aim of this review is to provide an overview of emerging estrogen-like compounds in the environment, sum up studies demonstrating their direct or indirect interactions with ERs, and link their presence to the development of breast cancer. Finally, we emphasize the use of in vitro and in vivo methods based on the zebrafish model to identify and characterize environmental estrogens. Breast cancer is the most commonly diagnosed cancer in women and is the second highest cause of death by cancer in women in Western countries. About 50,000 cases of breast cancer are recorded each year in France and the Breast Cancer Society estimates over 250,000 new cases in the USA for 2017. In general, the incidence of hormone-dependent cancers has increased over the past 30 years in industrialized countries . HormonaThese EDC compounds that interfere with the signaling pathways of endogenous hormones are released in the environment. For example, a large number of pesticides, cosmetics, and phthalates are currently found in surface water and numerous persistent organic pollutants (POPs) are not only found in water, but can accumulate in fat-rich tissues and are found in large concentrations in fish, shrimp, and shellfish. Some of these compounds, called xenoestrogens, mimic endogenous estrogens by binding to and activating estrogen receptors (ERs) and, among other effects, promote mammary cell proliferation, increasing the risk of initiating cell transformation and the development of cancer ,8. FurthOver the last 50 years the use of chemical pollutants and their release in the environment has increased considerably, triggering major concerns about their impact on wildlife and humans. These environmental concerns have been acknowledged by many institutions, however industrial development, agrochemicals and human chemical consumption produce an increasing amount of chemical pollutants into the environment, especially in surface water. With the general low biodegradability  of a numBesides current natural hormones including 17 β-estradiol (E2), estrone (E1), and estriol (E3), and pharmaceuticals like the contraceptives ethinylestradiol (EE2) and levonorgestrel that are found in concentrations up to ng/L in surface water, several families of chemicals are raising new concerns because of the increased scientific evidence of endocrine-disrupting activity, the lack of a legal definition as such, and their significant presence in the environment. These compounds originate from industrial and household applications and include alkylphenols, used mainly in surfactants and detergents, insecticides such as organochlorines and neonicotinoids, plasticizers , heavy metals like cadmium used in electrical batteries, and numerous molecules found in cosmetics such as benzophenones. The EDC activities of some of these commonly used molecules have now been detailed in the general population, and constitute a real societal problem. Therefore, industries have replaced these molecules by some equivalent, for instance Bis(2ethylhexyl) phthalate (DEHP) is replaced by di-isononyl phthalate (DiNP) or Bisphenol A (BPA) is replaced by Biphenol S (BPS) or Biphenol AF (BPAF). These replacement molecules are already found not only in water systems (for instance: BPAF 26.5 ng/L and BPS 6 ng/L), but also in aquatic organisms . The maiThese EDCs are detected throughout the environment  and at concentrations ranging from ng to μg per liter in surface water. These compounds are not totally eliminated by waste water treatment plants and the diversity of the treatment processes suggests that the elimination of molecules will likely be different from one treatment station to another  ,14,15. BSeveral methods for the identification, detection, and quantification of molecules with endocrine activities and their metabolites have been developed up to now. They are mostly based on chromatography (gas and liquid) and mass spectrometry, associated with an efficient pre-concentration step (often Solid Phase Extraction) especially for water monitoring ,21,22,23In healthy breast tissue, a small proportion of the epithelial cells express ERs (10–15%). These so-called ER-positive cells respond to E2 by stimulating the proliferation of adjacent ER-negative cells through paracrine signaling, involving growth factors and cytokines. ERs are also responsible for the differentiation of the lobular structures, controlling the expression of genes related to the maintenance of the epithelial phenotype such as progesterone receptor, E-cadherin or the transcription factor MIST1. Two major subtypes of ERs (ERα and ERβ) have been identified in mammals. The proliferative effect of estrogens in breast tissue seems to be mediated only by ERα, as suggested by ERα knockout mice, in which the proliferative effect of estrogens on breast tissue is completely abolished.The obvious side effects of the mitogenic action of E2/ERα on the breast epithelial cells is the probability of development and progression of breast cancer . Indeed,ERs are ligand-activated transcription factors that interact with chromatin at specific sites to modulate the expression of hundreds of target genes . This ERThe expression of ERs in breast cancer is an important prognostic marker of endocrine therapy and overall survival. Indeed, ER-positive tumors are generally histologically more differentiated and show less metastatic potential than ER-negative cancers. Moreover, the presence of ERs provides the option of hormonal therapy based on anti-estrogenic treatments. These molecules are able to block the action of endogenous E2 by ER binding and to induce tumor growth arrest and regression. Some molecules such as fulvestrant , are considered as pure antagonists which lead to the complete abolition of the estrogenic response. Other molecules called selective ER modulators (SERM), such as tamoxifen (Nolvadex) or raloxifen (Evista), have partial agonist/antagonist activities depending on the tissue, cell type, and target genes . For oveEven though the role of EDCs in the increase of breast cancer incidence has not been clearly established, numerous studies point to the adverse effects of these compounds on this specific pathology. This is perhaps not surprising as EDCs share common structures with the natural hormone E2  and are Among the EDCs found in water, phenol derivatives such as BPA, BPS and other analogs, triclosan, alkylphenols, and benzophenones are the most prevalent. BPA has received the most attention. It is a chemical monomer used in plastics, canned food lining, and thermal receipt paper, to name a few applications. BPA is able to bind and activate ERα in most cell types investigated to date, including breast cancer cells. Consequently, BPA is considered an agonist of ERα and induces cell proliferation as well as E2-dependent gene expression . RecentlA study by Dhimolea et al. , using 2Another phenol derivative present in water is triclosan. It is a broad-spectrum antimicrobial agent used in several cosmetic products such as skin cream and toothpastes. Triclosan is approved by the European Commission for topical administration in humans at a concentration of 0.03% and its acceptable daily intake (ADI), 1/100 of the no-observed-adverse-effect-level (NOAEL), is estimated at 0.17 nmol/kg/day, a concentration often reached in drinking water. However, even if the amount of triclosan found in the environment does not reach the critical NOAEL value, higher concentrations of this compound can be found in human tissues, suggesting bioaccumulation and a potential impact on human physiology . In vitrR = 0.90, while the profile generated by octylphenol was less correlated (R = 0.75), albeit significant. The cluster analysis clearly showed an upregulation of genes linked to proliferation, transcription, and transport in E2 and 4-nonylphenol-treated cells [Alkylphenols represent another group of phenol derivatives found in water. The two most documented are 4-octylphenol and 4-nonylphenol found in soil, air, and water, resulting from intense use in paints, plastics, or as a surfactant in agricultural products ,69. The ed cells . A compaed R = 0., albeit ed cells . NeverthBenzophenones (BP) are used as UV filters and found in watery environments. The major form is BP-3, which can be used up to 10% as an active ingredient in Europe and has been detected in surface water at concentrations up to 125 ng/L. BP-1 is the major metabolite of BP-3 and is found in the environment along with two other metabolites such as BP-8 and trihydroxybenzophenone (THB) . AnotherNeonicotinoids belong to a class of neuroactive insecticides targeting the nicotinic receptor. Neonicotinoids have been reported in water samples since 2012, with a concentration range from 0.002 to 3.6 μg/L . The use−1) in runoff from feedlot surfaces during a rainfall simulation after the animals were removed from the pens [Natural estrogens E1, E2, and E3 are found in the environment. The two main sources of release is the human population, which discharges around 30,000 kg/year, and livestock, which discharges 83,000 kg/year ,88. E1 athe pens . Dairy ethe pens . Similarthe pens ,96. In 2the pens . Howeverthe pens . SurprisIn contraceptive pills, the major synthetic hormones are EE2 and progestins, with the release of EE2 being estimated to reach 700 kg/year . This enIn addition to anthropogenic and natural estrogens of vertebrate origin, emerging natural compounds found in water are phytoestrogens and mycoestrogens. The main compounds detected in surface water from different rivers are biochanin A (0–19 μg/L), genistein (0–2.65 μg/L), and daidzein (0–43 μg/L) for phytoestrogens and zearalenone (0–80 ng/μL) for mycoestrogens . RecentZebrafish are small and hardy fish with a relatively short generation time, and so are currently used in developmental biology, chemical screening, and toxicology studies. Zebrafish have recently become an effective model organism for studying carcinogenesis in ecotoxicological as well as medical research . Human aKd) ranging between 0.42 nM to 0.75 nM. All three zfERs are able to activate E2-target genes in an E2-dependent manner with almost the same efficiency as human ERs, indicating that each form is able to specifically recognize ERE sequences [Previously, we cloned and characterized three distinct ER forms in zebrafish . As in mammals, zfERs are mainly expressed in E2-target tissues such as the ovaries, testes, liver, pituitary, and brain . Sequencequences .Thus, the characterization of the zebrafish ER forms has provided a valuable tool to investigate ecotoxicological potential of thousands of chemicals produced by the industry and commonly found in the aquatic environment . In a reERs, vitellogenin (VTG), and cytochrome P450 aromatase (cyp19a1b) are induced by xenoestrogens in embryonic–larval zebrafish and therefore are commonly used as endocrine biomarkers. Additionally, transgenic zebrafish models expressing an estrogen-dependent Green Fluorescent Protein (GFP)-based reporter gene were recently developed. These animals represent a powerful model to evaluate the in vivo and tissue-specific actions of EDCs present in water samples [cyp19a1b aromatase gene, in the developing zebrafish brain through the activation of ERs [cyp19a1b aromatase gene, in an ER-dependent manner, in radial glial cells of zebrafish embryos. This inhibitory effect was accompanied by a significant downregulation of zfER gene expression in the developing brain. Interestingly, Cd-induced E2 antagonism can be reversed, at the protein level, by zinc supplementation [Zebrafish embryos are also currently used to evaluate the impacts of in vivo exposure to aquatic chemicals on normal physiological processes. E2-target genes such as  samples ,115,116.n of ERs ,117. Furn of ERs ,119. Cadn of ERs ,121. Ourn of ERs . We showentation .Numerous laboratories have successfully used zebrafish models as a powerful in vivo assay to evaluate human cancer cell survival, migration, and metastasis ,127,128.Altogether, this highlights the potential of zebrafish models for (i) discovering therapeutic compounds or toxicity of environmental chemicals that disrupt biological pathways and result in adverse effects; and (ii) identifying the mechanisms of action of these environmental chemicals.It should be noted that zebrafish models can have different metabolism, pharmacodynamics, temperature, tissue anatomy, and behavior than mammals ,138. In Unraveling the effects and underlying mechanisms of endocrine disrupters on human health is a challenging task. However, some deleterious effects can be avoided by monitoring these environmental pollutants and by improving water quality, notably via the reduction of release or removal of these chemical compounds. To do this, we need to develop sensitive, efficient, and specific in vivo and in vitro bioassays to effectively characterize and quantify environmental pollutants, necessary steps to provide a legal limit to the presence of these man-made molecules. Several cell-based assays, developed previously , offer a


Research shows potential effects of floods on intestinal infections. Baise, a city in Guangxi Province (China) had experienced several floods between 2004 and 2012 due to heavy and constant precipitation. This study aimed to examine the relationship between floods and the incidence of bacillary dysentery in Baise. A mixed generalized additive model and Spearman correlation were applied to analyze the relationship between monthly incidence of bacillary dysentery and 14 flood events with two severity levels. Data collected from 2004 to 2010 were utilized to estimate the parameters, whereas data from 2011 to 2012 were used to validate the model. There were in total 9255 cases of bacillary dysentery included in our analyses. According to the mixed generalized additive model, the relative risks (RR) of moderate and severe floods on the incidence of bacillary dysentery were 1.40 : 1.16–1.69) and 1.78 (95% CI: 1.61–1.97), respectively. The regression analysis also indicated that the flood duration was negatively associated with the incidence of bacillary dysentery . Therfore, this research suggests that floods exert a significant part in enhancing the risk of bacillary dysentery in Baise. Moreover, severe floods have a higher proportional contribution to the incidence of bacillary dysentery than moderate floods. In addition, short-term floods may contribute more to the incidence of bacillary dysentery than a long-term flood. The findings from this research will provide more evidence to reduce health risks related to floods. Floods are a common and serious type of natural hazard. On average, flood events account for 50% of the total number of natural disasters globally ,2,3,4. IShigella bacteria, refers to a group of bacterial infections of the intestines, which may cause severe diarrhea. It is still a major public health problem around the world, particularly in developing countries [The influences of floods are widespread and complicated, including increased number of deaths and incidence of diarrhea . Floodwaountries . Accordiountries . Though ountries ,15. In tountries ,16,17,18ountries ,19. Moreountries . HoweverThere have been few studies conducted in southern China to examine the effects of various flood severity levels on bacillary dysentery . Our stu2 and hosting a population of 3,780,000 [Located in the northwest region of Guangxi Province, Baise is an industrial and tourist destination city. It has a longitude of 104°28’E and 107°54’E, and latitude of 22°51’N and 25°07’N, covering an area of 36,000 kmThis study collected monthly disease bacillary dysentery data between January 2004 to December 2012, from the National Notifiable Disease Surveillance System (NDSS). According to the NDSS, bacillary dysentery refers to a group of diseases resulting from Shigellae infection, with typical clinical manifestations such as stomach ache, fever, bloody stools and tenesmus. The occurrences of bacillary dysentery were identified in accordance with the diagnostic codes and management guidelines for bacillary dysentery (GB 16002-1995) promulgated by the Ministry of Health of China . Only thThe yearbooks of meteorological disasters specifically recorded the incidence, mortality, disaster-stricken areas, and economic loss of flood events between 2004 and 2012 . Based oThe meteorological data were obtained from the China Meteorological Data Sharing Service System , which pIn our study, we used monthly data to examine the effects of floods on bacillary dysentery based on time-series data from 2004 to 2010, which included month with and without flooding events.U test to illustrate the dissemination of the number of cases of bacillary dysentery and the climatic variables between the non-flooded and flooded months. Subsequently, Spearman's rank correlation was applied to evaluate the relationship between floods, climate factors, and the incidence of bacillary dysentery with different lagged values. The lagged value with the maximum correlation coefficient of each variable was then included in further regression analysis. Based on the latent period of bacillary dysentery as well as the living habits of the pathogen, a time lag between 0 to 2 months was taken into account [We firstly performed a descriptive analysis and the Mann–Whitney  account .Model 1:Model 2:where tY is the monthly number of cases in time t. Ln (population) was used as an offset to make the model appropriate for rate data. Floods was coded as a categorical variable, with 0, 1, and 2 referring to the various levels of floods, i.e., non-floods, moderate floods, and severe floods. Duration denoted the number of days with flooding in a month. 2s (precipitation), 3s (temperature), 4s (humidity), 5s (wind velocity) and 6s (sunlight duration) represent smooth functions of MCP, MAT, MARH, MAWV and MCSD, respectively, which were applied to adjust the impact of potential climate variable confounding. To control for potential long-term effects from demographic, social and economic development, and changes in health policy and services, the smooth spline of month was expressed as 1s (t). Moreover, due to the seasonality of the disease -bacillary dysentery occurs more often in summer and autumn-, a sinusoidal term sin(2πt/12) was incorporated in the models to control seasonal variations [Secondly, a mixed generalized additive model (MGAM) was established to quantify the association between various levels of floods and monthly incidence of bacillary dysentery, controlled for meteorological variables. Data between 2004 and 2010 were used to estimate the parameters, and data from 2011 and 2012 were used to validate the regression model. The result of the residual test indicated no overdispersion, and therefore, Poisson regression was used to quantify the association between various degrees of floods and monthly incidence of bacillary dysentery. A few studies revealed that meteorological factors, such as average relative dampness, average temperature, cumulative rainfalls, mean wind speed, and cumulative sunlight duration, were associated with diarrheal diseases ,29,30. Hriations . SPSS 16p < 0.05). In total, 9255 cases of bacillary dysentery were diagnosed in Baise during 2004–2012 with a mean annual incidence of 24.48/10,000. Based on the results in 12r = 0.90) for model 1 and 92% (adjusted R square 22r = 0.92) for model 2  of different flood levels for the risk of bacillary dysentery are shown in  model 2 . Both mop < 0.01) [p < 0.05) [Our study, quantified for the first time the relationship between various flood levels and bacillary dysentery incidences in Baise in Southern China. Results suggest that both moderate and severe floods would cause more bacillary dysentery cases in the research region, which is consistent with the findings in developed and developing countries. For instance, a study in Texas, USA, found that people in flooded areas were more likely to suffer from diarrhea than those in non-flooded areas during the floods in 2001 (with odds ratio (OR) = 10.8,  < 0.01) . Another < 0.01) . A surve < 0.01) . As for  < 0.05) . Moreove < 0.05) . Another < 0.05) . CompareShigella, Vibrio cholerae, Salmonella, Staphylococcus aureus, and others. This means the risk of related water-borne disease may increase because of water contamination during flood periods [Our study also identified that more (?) bacillary dysentery incidences may be caused by severe floods than by moderate ones. In Pakistan, a study showed that about 20% of the drinking water samples collected during flood periods were contaminated with  periods . There a periods ,41,42. S periods . Third,  periods ,45,46. CThe results of Model 2 indicate that a negative association exists between the floods duration and the incidence of bacillary dysentery. It indicates that the risk of suffering bacillary dysentery after a long-term flood may be lower than that after a short-term flood. At the early stage of the flood period after extreme rainfalls, the pathogens can develop and reproduce quickly in an appropriate environment, scattering through the polluted water and food . Some stThere are limitations in this study. Firstly, there are other variables, such as pathogen variability, population mobility, socioeconomic status, behavior and lifestyle changes, and environmental hygiene, that could impact the transmission of bacillary dysentery but could not be analyzed in this study. Secondly, the development of the disease from the exposure to diagnosis at hospitals up to being reported in the surveillance system may take 1–9 days. Therefore, more frequent data, e.g., daily or weekly incidences, of the disease, if available, would be more accurate than monthly data in our estimation of lag effects. Finally, underreporting is unavoidable in the research of infectious diseases, including bacillary dysentery. The reported cases included in this study are those who presented serious symptoms and were diagnosed in hospitals. Cases with mild clinical symptoms and treated by themselves usually did not seek health services, which may lead to an underestimate of the bacillary dysentery incidence risk by floods.In conclusion, our study suggests that floods can greatly increase the risk of bacillary dysentery, particularly severe floods. Moreover, a short-term flood may lead to more incidences of bacillary dysentery than a long-term flood event if the floods are at the same severity level. The findings of this study will provide more evidence to reduce health risks of floods in China.


Firmicutes, Proteobacteria, Actinobacteria and Bacteroidetes, that are involved in carbohydrate metabolism, energy metabolism, lipid metabolism, and amino acid metabolism. Ferredoxin-NADP reductase, present in bacteria in genus Azotobacter, is an important enzyme for NADH/NAD+ equilibrium regulation in hydrogen production. The archaeal functional proteins are mainly involved in methane metabolism in energy metabolism, such as acetyl-CoA decarboxylase, and methyl-coenzyme M reductase, and the acetic acid pathway exhibited the highest proportion of the total. The archaea of genus Methanosarcina in phylum Euryarchaeota can produce methane under the effect of multi-functional proteins through acetic acid, CO2 reduction, and methyl nutrient pathways. The study demonstrates metaproteomics as a new way of uncovering community functional and metabolic activity. The combined information was used to identify the metabolic pathways and organisms crucial for lignocellulosic biomass degradation and biogas production. This also regulates the process from its protein levels and improves the efficiency of biogas production using reed straw biomass.A metaproteomic approach was used to analyse the proteins expressed and provide functional evidence of key metabolic pathways in the combined production of hydrogen and methane by anaerobic fermentation (CHMP-AF) for reed straw utilisation. The functions and structures of bacteria and archaea populations show significant succession in the CHMP-AF process. There are many kinds of bacterial functional proteins, mainly belonging to phyla  Due to traditional farming methods, people are unaware of the harm caused and frequently burnt the straw in the open-air, causing severe air pollution, and wasting resources [Notice on Further Accelerating the Comprehensive Utilisation of Straw and Prohibition of Straw Burning. It points out that it is necessary to promote the orderly development of biomass gasification by using lignocellulosic biomass, including straw, as a raw material, to improve China’s rural energy structure.To reduce the reliance on finite fossil fuels and mitigate concern over climate change, conversion of lignocellulosic biomass to energy sources such as biogas is currently receiving much research attention. China produces 7 billion tons of straw esources . In 2015Hydrogen as a clean energy source has characteristics such as: a high calorific value, it is clean, recyclable, efficient, and can be used in fuel cells. Owing to straw being rich in nutrients, cellulose, and hemicellulose, which contain 75% polysaccharide sugars, straw is an ideal hydrogen source . During Traditional methods used in microbiology and next generation sequencing technologies were applied to deepen understanding of the constituents of microbial communities –9; howevThis research studied the microbial community structure and functional succession during the CHMP-AF process based on a metaproteomic analysis for hydrogen and methane production under cellulase pretreatment of reed straw. The metaproteomic approach also gives functional insights into the CHMP-AF as a result of the identified protein sequences. The response correlation between key functional proteins and major metabolic activity of microorganisms was also investigated.Reed straw was collected from field monitoring station of Ulansuhai, which was in charge by Chinese Research Academy of Environmental Sciences, and gave the permission to conduct this study on the site. Reed straw was dried and ground, passed through a 20-mesh screen and stored at 4°C. The inoculation sludge was obtained from the reactor for swine manure anaerobic fermentation and filtered through a 30-mesh sieve to remove coarse particles. The characteristics of the substrate and inocula are summarised in reed / VS sludge ratio of 1.2:1) were added to each bioreactor. The total volume was increased to 1.6 L using distilled water. The initial pH was adjusted to 5.0 using 1 M HCl or NaOH before starting the experiment. The bioreactors were filled with nitrogen gas for 10 min to remove the oxygen and then placed in a water bath (containing a vibrator rotating at 150 rpm) at 37 ± 1°C. The control tests were prepared using reeds straw without pretreatment of cellulase at the same time.Batch experiments were performed in triplicate in 2 L bioreactors. Based on a previous study, the optimum hydrogen and methane production performance from reed straw were observed under the cellulase R-10  pretreatment and compared with acid and alkali pretreatments. Carrillo and Valldeperas reported that pretreatment of straw under alkaline condition will enhance its catalytic efficiency . In thisThe biogas samples were taken at six hourly intervals. The effluent samples were taken once a day for chemical index analyses. The mixed liquor for metaproteomics analyses was taken from bioreactors in four different stages, such as peak stage of hydrogen production , late stage of hydrogen production , peak methanogenic stage , and late methanogenic stage .P is the hydrogen or methane production potential (mL), Rmax is the maximum hydrogen or methane production rate (mL/h), e is 2.72, λ is the lag-phase time (h) and t is the incubation time (h). The values of P, Rmax and λ can be estimated using Origin 8.0 [The cumulative volume of hydrogen and methane produced in the batch experiments can be calculated by the modified Gompertz equation:igin 8.0 .et al. [Proteins were extracted from 50 mL samples using the method published by Benndorf et al.  and subset al. . The prohttp://www.matrixscience.com) against NCBInr. Protein matches were only accepted if they were identified by a minimum of one unique peptide.Digested peptides were separated by nano-LC  and analysed by MS/MS . Database searches were carried out using MS/MS ion search , and the protein hit that showed the highest sequence identity was recorded, including the identity of the protein and the name of the organism. Higher protein abundance is represented by a higher number of MS/MS spectra acquired from peptides of the respective protein. KEGG Orthology and Links Annotation (KOALA) is KEGG's internal annotation tool for K number assignment of KEGG GENES using SSEARCH computation. GhostKOALA assign K numbers to the user's sequence data by GHOSTX searches, against a nonredundant set of KEGG GENES. Thus, KOALA was used to annotate these metagenome sequences, which perform KO (KEGG Orthology) assignments from the proteins identification; it is and freely available at the KEGG Web site  [All proteins were manually annotated with the aid of BLASTP  .Total solids, volatile solids and pH were measured according to the APHA standard methods . The per2, CH4 and CO2) was measured by a gas chromatograph  equipped with a thermal conductivity detector and a 2-m high-porosity polymer bead-packed column. The operating temperatures of the injection port, oven and detector were set to 50, 150 and 150°C, respectively. Argon was used as the carrier gas at a flow rate of 40 mL/min. The VFA and ethanol concentration were determined using a gas chromatograph  equipped with a flame ionisation detector and a 30 m×0.25 mm×0.25 mm fused-silica capillary column . The injection temperature was 200°C. The oven temperature was initially set to 40°C and increased to 220°C thereafter at a rate of 9°C per minute. Helium was used as the carrier gas at a flow rate of 1.2 mL/min and a split to a column flow ratio of 10:1.The composition of the biogas  of the CHMP-AF were identified, thus obtaining 935 bacterial proteins and 375 archaeal proteins. The proteins in the methanogenic stage were more numerous than those in the hydrogen production stage.Firmicutes, Proteobacteria, Actinobacteria and Bacteroidetes. In the peak stage of hydrogen production, classes Clostridia and Bacilli in phylum Firmicutes accounted for 40.9% and 22.8% of the total, while they gradually decreased thereafter. Compared with the hydrogen production stage, the proportion of phyla Proteobacteria and Bacteroidetes increased in the methanogenic stage and classes Gammaproteobacteria and Epsilonproteobacteria reached 56.8% and 2.7%, respectively, in the late stage. Furthermore, classes Alphaproteobacteria, Betaproteobacteria and Deltaproteobacteria show the highest proportions in the peak methanogenic stage, accounting for 13%, 11.7%, and 5.3%, respectively, while class Bacteroidetes reaches 6.2% in the late methanogenic stage. The proportion of class Actinobacteria stabilised in the range between 3.2% to 5.7%.The compositions of bacterial populations at different stages of the CHMP-AF are shown in Clostridium in class Clostridia accounted for the largest proportion in the hydrogen production stage. Genus Caldicellulosiruptor in class Clostridia was omnipresent and could degrade cellulose and showed good thermal stability, which was important for the synergistic hydrolysis of insoluble cellulose [Acidobacteria, belonging to the acidophilus type, was detected. This can adapt to the acidic environment during hydrogen production and plays an important role in maintaining a stable anaerobic system. In the late stage of hydrogen production, the proportion of class Gammaproteobacteria increased to 38.7% in which genus Klebsiella is a microorganism commonly seen in anaerobic fermentation systems. It is reported that bacterium Klebsiella sp. HE1 is able to produce hydrogen and can also synthesise methane by using hydrogen under specific conditions [Escherichia, as the facultative anaerobes, accounting for 25% overall, fermented the glucose and other sugars present to produce pyruvic acid, which was then further transferred to VFA and hydrogen [Escherichia decreased to 8.9% in the late methanogenic stage.Genus ellulose . In the nditions . In the hydrogen . As the Euryarchaeota, Crenarchaeota and Thaumarchaeota were dominant in archaeal populations and a few representatives from phyla Korarchaeota and Nanoarchaeota were found in the stages of hydrogen and methane production, respectively. Class Thermoprotei in phylum Crenarchaeota in the peak stage of hydrogen production accounted for the highest proportion (20%), followed by classes Thermococci (16.7%) and Methanococci (13.3%). Class Methanomicrobia accounted for the highest proportion in the methanogenic stage and the proportions in the peak, and late, methanogenic stages were 68.3% and 65.1%, respectively. During methane production, the proportion of classes Thermococci, and Thermoprotei gradually decreased and class Nanoarchaeota only appeared in the peak methanogenic stage, and accounted for 1.2% overall.Methanosphaera in class Methanobacteria belongs to the archaea and produces methane as a specific metabolite under anaerobic conditions. It can generate methane with hydrogen and methanol. Genus Pyrococcus, containing a soluble HD containing nickel, can generate hydrogen and CO2 by using carbohydrates and proteins. Genus Methanosarcina in class Methanomicrobia not only produces methane by utilising acetic acid in the late stage of hydrogen production, but is also autotrophic as a result of its use of methanol and hydrogen [Methanosarcina presents the largest number and proportion of its functional proteins. Therefore, it is the dominant microorganism in the methanogenic stage during the CHMP-AF process.The study shows that genus hydrogen . In addiThe metaproteomics analysis demonstrates that the bacterial proteins present in the process of CHMP-AF have diverse functions . The funStreptococcus. Pyruvate-flavodoxin oxidoreductase and uncharacterized protein YdiJ which can synthesise acetyl-CoA through the electron transfer from pyruvic acid and is the most important enzyme for hydrogen production from pyruvic acid, came from genera Klebsiella and Escherichia in class Gammaproteobacteria. NADH-quinone oxidoreductase subunit B, which binds the 4Fe-4S cluster, and is involved in proton and energy transfers in the respiratory chain, was a hub for electron transfer between respiratory chain complexes and came from genus Xylella in class Gammaproteobacteria. In the late stage of hydrogen production, isocitrate dehydrogenase and aconitate hydratase, involved in the tricarboxylic acid cycle, and malate synthase G1 and NAD-dependent malic enzyme, taking part in the aldehyde acid cycle, were added to the carbohydrate metabolism process and came from bacteria in genera Azotobacter, Pseudomonas and Sodalis in class Gammaproteobacteria.The hydrogen production pathway was mainly involved in the metabolism of pyruvic acid and glycolysis in carbohydrate metabolism. In the peak stage of hydrogen production, it was found that L-lactate dehydrogenase, involved in pyruvic acid metabolism to produce lactic acid, came from bacteria in genus 2 and came from genus Mycobacterium in class Actinobacteria and genera Enterobacter and Pseudomonas in class Proteobacteria. In this stage, acetate kinase from genera Halothermothrix, Syntrophomonas and Clostridium in class Clostridia was the important enzyme necessary for acetyl-CoA to generate acetic acid and played a linking role in the process of combined hydrogen and methane production [+ and came from genus Azotobacter in class Proteobacteria. Methylenetetrahydrofolate-tRNA-(uracil-5-)- methyltransferase TrmFO, as an important enzyme taking part in methane production with CO2, can catalyse the tetrahydrofolate and came from genus Bacillus in class Firmicutes. Moreover, in the methanogenic stage, those proteins relating to ABC transfer increased significantly and the energy of ATP hydrolysis can be adopted to realise transmembrane transport of sugars, amino acids, metal ions, peptides, proteins, and cellular metabolites [The amounts of functional proteins in bacteria significantly increased in the methanogenic stage and the proportion of functional proteins involved in carbohydrate metabolism also increased. Moreover, those functional proteins relating to glycolytic pathways increased. In the peak methanogenic stage, it was found that pyruvate dehydrogenase E1 component, involved in pyruvate metabolism, can transform pyruvic acid into acetyl-CoA and COoduction . Furtherabolites . CompareAccording to the functional analysis, the detected archaeal proteins were mainly involved in methane metabolism in energy metabolism and accounted for 6.67% (I), 45.16% (II), 31.58% (III), and 34.23% (IV), respectively, during the CHMP-AF process. The functional proteins involved in amino acid metabolism, carbohydrate metabolism, biosynthesis, and transport were also included. This research mainly analysed the functional proteins of archaea involved in methane metabolism at different stages .Methanosarcina in class Methanomicrobia. 5,10-methylenetetrahydromethanopterin reductase catalyses diiodomethane-tetrahydromethanopterin into methyl-H4MPT, while H4MPT, derived from tetrahydrofolate, is used to transfer carbon across the levels of methyl, methylene, and methyl [2 and from archaea in genus Methanobacteriales in class Methanobacteria. In the late stage of hydrogen production, the number of functional proteins involved in the metabolism of methane production increased. Acetyl-CoA decarbonylase accounted for the largest proportion in the methane production pathway based on acetic acid, followed by tetrahydromethanopterin S-methyltransferase subunit H and F420-methylenetetrahydromethanopterin dehydrogenase from genera Methanosarcina and Methanoculleus in class Methanomicrobia as involved in methane production by reducing CO2 [420, as a deazaflavin analogue, is used as an electron acceptor of hydrogenase, formate dehydrogenase and carbon monoxide dehydrogenase, as well as an electron donor for reductase NADP+; moreover, it utilises H2 and formic acid as electron donors to produce methane by reducing CO2 [Methanosarcina through involvement in the methyl nutrient type of methane production pathway, methanol-corrinoid protein co-methyltransferase can produce methane by reducing methyl with H2 in methyl compounds, or produce methane through the dismutation of methyl compounds from genus Methanosarcina. In addition, methyl-coenzyme M reductase, catalysed by the reductase of methyl coenzyme M containing nickel, reduces CH3-S-CoM to produce methane and Co B-S-S-CoM by using HS-CoB as the direct electron donor [Methanos arcina, is the terminal methyl carrier and the critical enzyme for methane production.In the peak stage of hydrogen production, only a few of functional proteins were involved in methane metabolism. Acetyl-CoA decarboxylase is an important enzyme for methane production using acetic acid and it came from genus d methyl . They arcing CO2 . The rescing CO2 ,32. The on donor . This en2 reduction pathway increased and the F420-dependent methylenetetrahydromethanopterin dehydrogenase came from genera Methanosarcina, Methanoculleus and Methanosphaerula. Moreover, coenzyme F420 hydrogenase (sub-unit beta) and coenzyme F420 hydrogenase subunit alpha came from genera Methanococcales and Methanosarcina, respectively. The 5,10-methylenetetrahydromethanopterin reductase came from genera Methanobacteriales and Methanosarcina. Formate dehydrogenase subunit alpha is an important enzymefor formic aciddehydrogenation came from genus Methanococcales in class Methanococci. The number of functional proteins involved in methane production through the methyl nutrition pathway increased. Monomethylamine corrinoid protein 1, monomethylamine methyltransferase MtmB, trimethylamine corrinoid protein 1, and methanol-corrinoid protein co-methyltransferase which use methylamine, trimethylamine, and methanol as the substrates for methane production, and their functional proteins all came from genus Methanosarcina. In the late stage of methane production, similar functional proteins of archaea were involved in the metabolism for methane production, among which functional proteins relating to methyl nutrient types of methane production showed constantly increasing proportions. In this stage, dimethylamine corrinoid protein 2 also appeared; this can use dimethylamine as a methyl donor to produce methane and is from those archaea in genus Methanosarcina.In the methanogenic stage, the number of functional proteins of archaea involved in the metabolism of methane production increased and the proportion stabilised at between 31.58% and 34.23%. In the peak methanogenic stage, acetyl-CoA decarbonylase still accounted for the largest proportion of enzymes involved in the acetic acid type of methane production pathway. The species of archaea participating in methane production by utilising the CO+ equilibrium regulation proposed by Tanisho, et al. [Methanococcales., which can catalyse the dehydrogenation of formic acid and decompose formic acid to produce hydrogen and CO2 under the common effects of hydrogenase [Azotobacter, is an important enzyme for NADH/NAD+ equilibrium regulation in hydrogen production. NADH can couple with the fermentation processes of propionic acid, butyric acid, ethanol, or lactic acid and therefore may be oxidised as NAD+ to produce hydrogen, thus ensuring an NADH/NAD+ equilibrium in the metabolism [2 and one-carbon compounds by microorganisms to be reduced for methane production [The CHMP-AF is a biochemical process in which substrates, enzymes, and microorganisms interact with, and inhibit, each other . Through, et al. . The res, et al. . Formaterogenase . Ferredotabolism . Therefooduction .2 and one-carbon compounds to methane under the common effects of many enzymes and coenzymes in one-carbon metabolism. Coenzymes, closely relating to methane production, can be divided into two categories: one-carbon carriers, including H4MPT, H4SPT and coenzyme M; the other is electron carriers comprising ferredoxin, coenzyme F420, coenzyme B and cytochrome [Methane production from microorganisms is a process able to reduce methyl in COtochrome . The res2. Carboxyl is oxidised to produce electron donating H2 for the methyl reduction and methane generation [Methanosarcina and a few archaea of genus Methanosaeta. The methyl nutrient pathway is active in the methanogenic stage. This study detected many functional proteins by using methanol, methylamine, dimethylamine, and trimethylamine as its substrates. Under the actions of methyl-coenzyme M reductase of the methyl carrier, methane was produced at the end of the methane production stage through that pathway using the participation of genus Methanosarcina. Formic acid was decomposed by formate dehydrogenase subunit alpha to hydrogen and CO2, the latter of which was reduced under catalysis with ferredoxin-NADP reductase in bacterial protein to generate 5,10-methenyl-H4MPT, and then 5-methyl-H4MPT was generated due to the catalysis of 5, 10-methylenetetrahydromethanopterin reductase of those archaeal proteins present [2 reduction pathway, mainly including bacteria of genus Azotobacter and archaea of genera Methanosarcina, Methanoculleus, Methanothermobacter and Methanocaldococcus.The functional proteins relating to methane production through the acetic acid pathway exhibited the highest proportion of the total. Acetyl-CoA decarboxylase uses acetate as its only carbon source and for the energy required to catalyse the decarboxylation of acetyl CoA to decompose to COneration . This pa present . Finally present ,38. It cFirmicutes, Proteobacteria, Actinobacteria and Bacteroidetes, are involved in carbohydrate metabolism, energy metabolism, lipid metabolism, and amino acid metabolism. The archaeal functional proteins are mainly involved in methane metabolism in energy metabolism, such as acetyl-CoA decarboxylase, and methyl-coenzyme M reductase, and the acetic acid pathway exhibited the highest proportion of the total. The genus Methanosarcina in phylum Euryarchaeota present the highest functional diversity in methane metabolism and can produce methane under the influence of multi-functional proteins through acetic acid, CO2 reduction, and methyl nutrient pathways. Therefore, the functional diversity and metabolic activity of microbial communities can be combined with the metabolic pathway during the CHMP-AF to regulate from its protein levels and improve the hydrogen and methane production potential using a lignocellulosic biomass such as reed straw.The biogasification performance significantly improved and the functions and metabolic activity of microbial communities played significant roles during the CHMP-AF after cellulase pretreatment of reed straw. The metaproteomic analysis revealed that bacterial functional proteins, such as ferredoxin-NADP reductase, acetate kinase, and NADH-quinone oxidoreductase, mainly belonging to phyla S1 TableI is the peak stage of hydrogen production. II is the late stage of hydrogen production. III is the peak methanogenic stage. IV is the late methanogenic stage. % is the proportion of the identified bacterial proteins in different stages of the CHMP-AF.(DOCX)Click here for additional data file.S2 TableI is the peak stage of hydrogen production. II is the late stage of hydrogen production. III is the peak methanogenic stage. IV is the late methanogenic stage. % is the proportion of the identified archaea proteins in different stages of the CHMP-AF.(DOCX)Click here for additional data file.S1 Data(RAR)Click here for additional data file.S2 Data(RAR)Click here for additional data file.


Spatiotemporal compartmentalization of signaling pathways and second messengers is pivotal for cell biology and membrane rafts are, therefore, required for several lymphocyte functions. On the other hand, T cells have the specific necessity of tuning signaling amplification depending on the context in which the antigen is presented. In this review, we discuss of membrane rafts in the context of T cell signaling, focusing on CD28-mediated costimulation. In the late 1980 s, accumulating evidence set forth the existence of ordered lipid clusters in the cell membrane, named lipid rafts. According to the “lipid raft hypothesis,” forces between cholesterol and sphingolipids facilitate the dynamic assemblies of lipid domains in an unsaturated glycerophospholipid environment , 3. In 22+ store depletion   , 21, whi2) , 23.As for membrane rafts in immunity, over the last decades it has become evident that these microdomains actively modulate immune signaling, contributing to orchestrate innate and acquired immune responses . CompartThis review will describe how membrane rafts support T cell activation, focusing in particular on CD28-mediated costimulation.In order to become fully activated, T cells require a double signal. The first signal is T cell receptor (TCR) ligation by peptide-major histocompatibility complex on antigen-presenting cells (APCs); the second signal derives from the interaction between a coreceptor on the T cell with counter-receptors expressed by APCs. The major coreceptor molecule expressed by T cells is CD28, whose ligands on professional APCs are CD80/B7.1 and CD86/B7.2 –28.The combination of antigen recognition and costimulation results in the formation of a mature IS , a dynamThe IS is characterized by a peculiar lipid composition, which differs from the lipid composition of other membrane regions . Live-ceImportantly, the functional relevance of membrane rafts is supported by the observation that several signaling molecules involved in T cell activation can be found in raft domains. The Src kinase Lck, which is activated immediately after TCR triggering, is acylated on two cysteine residues on its N-terminus, thus being targeted to membrane rafts . This isAltogether, these results support a model in which lipid rafts act as a docking platform, where the actors involved in T cell activation can organize and integrate downstream signaling events.In T cells, the coupling of the outer and inner lipid microdomains is mediated by cholesterol. By contrast, the crosslinking of TCR/CD3 triggers the formation of large, stable rafts independently of cholesterol . These rThe costimulatory molecule CD28 plays a crucial role in determining T cell sensitivity. Its ligands CD80 and CD86 are highly expressed by pathogen-activated professional APCs, such as mature dendritic cells, macrophages, and activated B cells. As a consequence, CD28 costimulation occurs in the context of infection and/or inflammation, thus representing a possible control mechanism for avoiding excessive T cell responses. Accordingly, CD28 has been indicated as an important regulator of autoimmune diseases . InteresCD28 costimulation is indeed fundamental for full T cell activation, as it lowers the stimulation threshold of naïve T cells, in terms of number of triggered TCRs . T lymphNumerous works have demonstrated that CD28 costimulation regulates T cell function, by enhancing several signaling pathways and, finally, tuning gene transcription , 50. ThiImportantly, CD28-mediated costimulation is intrinsically linked to the reorganization of membrane rafts at T lymphocyte plasma membrane.We and others have shown that CD28 coengagement results in membrane rafts clustering at the site of TCR triggering , 64–69. CD28-mediated raft recruitment is a central event for the orchestration of TCR signaling. Indeed, CD28 coengagement by Abs or natural ligands protects the action of TCR-activated kinases from the inhibition mediated by phosphatases. Consequently, tyrosine phosphorylation of TCR signaling targets is stabilized and can be observed for several minutes, while being transient and unstable in the absence of CD28 costimulation . QuantitAs mentioned before, several proteins involved in TCR signaling have been found associated with membrane rafts and, at least for some of them, the recruitment to the IS depends on CD28-triggered organization of lipid domains. Lck, for example, accumulates at the IS in a CD28-dependent way and this process requires the CD28 COOH-terminal PxxPP motif and Vav1 .Also PKCθ clusters at the IS upon CD3/CD28 engagement translocating to membrane rafts . Its assvia ezrin and leads to the inhibition of T cell function and proliferation  and protein kinase A (PKA). It has been known for a long time that TCR ligation induces an increase in cAMP production , which iferation . Howeverferation , 79. Theferation  and invoThe dynamic and functional assembly of the IS depends on actin cytoskeleton rearrangements . The actOne of the most characterized functions of CD28 is the ability to organize the cytoskeleton. At the immune synapse, the CD3/CD28-activated polymerization of actin is regulated by the activity of the guanine nucleotide-exchange factor Vav1 , 83, thevia the adaptor protein Grb2, mediates the formation of Vav1/SLP-76 complex, which is crucial for initiating downstream signaling (Vav1 is a key regulator of cytoskeletal dynamics and T cell responses: indeed, Vav1-deficient cells present impaired membrane raft clustering at the IS, which correlates with defects in cytoskeletal reorganization and T cell activation , 87, 88.ignaling , 83.The role of Vav1 in CD28-mediated signaling is crucial: T cells lacking the adaptor molecule Cbl-b display enhanced Vav1 activation and are independent of CD28 for their triggering , as wellAlso cofilin has been proposed as a linker between the actin cytoskeleton and T cell costimulation. Indeed, TCR/CD28 engagement, but not TCR stimulation alone, induces cofilin dephosphorylation and its consequent association with actin . In T ce2, produced by PIP5K enzymes. It has been estimated that half of the PIP2 pool is localized in membrane rafts (Cytoskeletal dynamics are also regulated by PIPne rafts  and is ine rafts . Recent ne rafts , 95, 96.Since the first demonstration in 1999 for a role of CD28 in controlling membrane rafts assembly at the IS , severalSZ, BM, and AV conceived and wrote the manuscript and realized the figure.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.