Giardia, one of the most prevalent parasite infections globally, had a particularly large impact on the microbiome. Second, we took a database-driven strategy to integrate microbiome data with clinical data from large human field studies and found that Giardia infection is also associated with marked alteration of the gut microbiome of children, suggesting a possible explanation for why Giardia has been reported to be associated with protection from moderate to severe diarrhea.While enteric parasitic infections are among the most important infections in lower- and middle-income countries, their impact on gut microbiota is poorly understood. We reasoned that clinical symptoms associated with these infections may be influenced by alterations of the microbiome that occur during infection. To explore this notion, we took a two-pronged approach. First, we studied a cohort of dogs naturally infected with various enteric parasites and found a strong association between parasite infection and altered gut microbiota composition.  Giardia was associated with a more pronounced perturbation of the microbiome. To compare our findings to large-scale epidemiological studies of enteric diseases in humans, a database mining approach was employed to integrate clinical and microbiome data. Substantial and consistent alterations to microbiome structure were observed in Giardia-infected children. Importantly, infection was associated with a reduction in the relative abundance of potential pathobionts, including Gammaproteobacteria, and an increase in Prevotella—a profile often associated with gut health. Taken together, these data show that widespread Giardia infection in young animals and humans is associated with significant remodeling of the gut microbiome and provide a possible explanation for the high prevalence of asymptomatic Giardia infections observed across host species.Enteric parasitic infections are among the most prevalent infections in lower- and middle-income countries (LMICs) and have a profound impact on global public health. While the microbiome is increasingly recognized as a key determinant of gut health and human development, the impact of naturally acquired parasite infections on microbial community structure in the gut, and the extent to which parasite-induced changes in the microbiome may contribute to gastrointestinal symptoms, is poorly understood. Enteric parasites are routinely identified in companion animals in the United States, presenting a unique opportunity to leverage this animal model to investigate the impact of naturally acquired parasite infections on the microbiome. Clinical, parasitological, and microbiome profiling of a cohort of 258 dogs revealed a significant correlation between parasite infection and composition of the bacterial community in the gut. Relative to other enteric parasites, IMPORTANCE While enteric parasitic infections are among the most important infections in lower- and middle-income countries, their impact on gut microbiota is poorly understood. We reasoned that clinical symptoms associated with these infections may be influenced by alterations of the microbiome that occur during infection. To explore this notion, we took a two-pronged approach. First, we studied a cohort of dogs naturally infected with various enteric parasites and found a strong association between parasite infection and altered gut microbiota composition. Giardia, one of the most prevalent parasite infections globally, had a particularly large impact on the microbiome. Second, we took a database-driven strategy to integrate microbiome data with clinical data from large human field studies and found that Giardia infection is also associated with marked alteration of the gut microbiome of children, suggesting a possible explanation for why Giardia has been reported to be associated with protection from moderate to severe diarrhea. Giardia, for example, was found in 18 of 1,093 (1.6%) of healthy volunteers in Melbourne, Australia  with an estimated 3.5 billion people affected worldwide , 2. Infe3–Giardia which infected 4% of dogs  investigated the causes of pediatric moderate to severe diarrhea (MSD) in LMICs  Cystoisospora, the causative agent of coccidiosis, an intestinal tract infection; (iv) hookworm, which causes intestinal distress and anemia; (v) whipworm, which causes severe irritation to the large intestine; (vi) ascarid, which causes weakness, diarrhea, and vomiting; (vii) tapeworm, which is generally asymptomatic but indicative of flea infestation and may cause perianal pruritis; (viii) Eucoleus boehmi, a parasite whose eggs are shed in the stool and that can cause chronic rhinitis; and (ix) dogs with coinfections of two or more of these parasites. Since certain enteric parasites, such as Giardia, are more prevalent in young animals, age and other potential confounding variables were controlled for in our statistical analyses. Parasite infection status was associated with significant changes in beta diversity, as determined by both Bray-Curtis and weighted UniFrac metrics, even when covariates such as age, sex, and spay/neuter status were controlled for as confounding variables  (Eucoleus boehmi). Approximately 5% of the variation in microbiome composition was explained by parasite infection status compared to <1% explained by age, sex, or spay/neuter status alone (Adj P > 0.05 by PERMANOVA)  study . A total of 258 canine fecal samples were split into 9 groups based on parasite infection status : (i) no MANOVA]) . The sigRMANOVA) . Specifiy-Curtis  and weigy-Curtis .Giardia infection is associated with a change in Bray-Curtis  and weighted UniFrac  beta diversity compared to NPS controls, without controlling for age, sex, and spay/neuter status , but no longer meets the 0.05 cutoff for significance for weighted UniFrac   effect size (LEfSe) analysis  . The difanalysis  and C. G10.1128/mSphere.00670-20.7TABLE S1Giardia infection compared to NPS controls, as identified by point-biserial correlation coefficient. Point-biserial correlation coefficients showing that Clostridium, Lactobacillus, and Bacteroides are significantly associated with Giardia infection, as seen in the LEfSe analysis , to identify animals with a recent history of diarrhea or antibiotic use (Giardia infection was not associated with diarrhea or antibiotic use (P > 0.25 by chi-squared test): among dogs with clinical data, 4 of 13 (30.1%) Giardia-infected dogs had diarrhea compared to 21 of 118 (18%) NPS control dogs with diarrhea (see Giardia-infected dogs received antibiotics compared to 15 of 118 (12.7%) NPS control dogs , with most dogs on antibiotics having diarrhea (11/15) and over half of dogs with diarrhea being on antibiotics (11/21). Among NPS control animals with clinical data available (n = 118 dogs)  and weighted UniFrac beta diversity  compared to asymptomatic animals; and those receiving antibiotics had significantly different Bray-Curtis beta diversity  and weighted UniFrac beta diversity  compared to those not receiving antibiotics, when controlling for age, sex, and spay/neuter status (n = 118) to define a microbiome signature associated with diarrhea in the absence of observable parasites, allowing us to compare this signature with Giardia-infected animals. LEfSe analysis identified Escherichia as enriched in animals with diarrhea and in those receiving antibiotics, while Bacteroides and Fusobacterium were enriched in asymptomatic dogs (Escherichia and Fusobacterium and show that this signature is distinct from that observed during Giardia infection (It is possible that the microbiota changes observed in otic use . Interesrol dogs . In cont18 dogs) , those wr status . Next, wtic dogs C and S1Dtic dogs . Taken tnfection  and C.10.1128/mSphere.00670-20.1FIG S1Giardia. (A) Pie charts showing the relative proportion of dogs with diarrhea and asymptomatic animals among NPS control and Giardia-infected dogs. The proportion of symptomatic dogs is not significantly different between groups (P > 0.05 by chi-squared test). (B) Histogram showing that diarrhea and antibiotic use are associated with a significant difference in beta diversity compared to asymptomatic and no antibiotic use. Bar height reflects the percentage of total beta diversity variance that is explained by each variable. Age, sex, and spay/neuter status were controlled for all calculations. Asterisks denote bars with adjusted P < 0.05. (C) LEfSe graph showing the magnitude of enrichment for each taxon with a LDA score of >2 comparing animals with and without diarrhea. (D) Boxplots showing the relative abundance of taxa that are differentially abundant between animals with and without diarrhea. Download FIG S1, PDF file, 0.1 MB.Diarrhea is associated with enrichment of a different set of taxa compared to Copyright © 2020 Berry et al.2020Berry et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mSphere.00670-20.2FIG S2n = 174), NPS controls with clinical data (n = 118), and Giardia-positive dogs with clinical data (n = 15). (B) LEfSe graph showing the magnitude of enrichment for each taxon with LDA score > 2 comparing NPS control dogs receiving and not receiving antibiotics. Escherichia is highly enriched in dogs receiving antibiotics and in dogs with diarrhea, while Bacteroides and Fusobacterium are reduced in dogs receiving antibiotics and in dogs with diarrhea, likely because most dogs receiving antibiotics have diarrhea. Megamonas and Faecalibacterium are reduced in dogs receiving antibiotics, but not in dogs with diarrhea. Download FIG S2, PDF file, 0.07 MB.Antibiotic use in dogs is associated with a similar gut microbiota profile as dogs with diarrhea due to strong correlation between antibiotic use and diarrhea. (A) Pie chart showing the relative proportion of dogs receiving antibiotics and those not among all samples that have associated clinical data  were infected with Giardia and one or more other parasites. These 10 Giardia coinfected samples were indistinguishable from Giardia singly infected animals by Bray-Curtis (Adj P > 0.1) and weighted UniFrac (Adj P > 0.1) beta diversity (Giardia singly infected samples were significantly different from the remaining 11 coinfected samples not involving Giardia by Bray-Curtis (Adj P < 0.05) and weighted UniFrac (Adj P < 0.05) beta diversity; however, false discovery rate correction raises these P values slightly above the 0.05 significance threshold . In contrast, fecal samples from dogs infected with multiple, non-Giardia parasites are different from those singly infected with Giardia , and infection status here represents a larger percentage of the variance in beta diversity. Age, sex, and spay/neuter status were controlled for all calculations. Download FIG S3, PDF file, 0.05 MB.The effects of Copyright © 2020 Berry et al.2020Berry et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Giardia, perturb the canine gut microbiome, we asked whether Giardia similarly affected the human gut microbiome. To this end, we employed a database mining approach to integrate and query data from the Global Enteric Multicenter Study (GEMS) and the Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health (MAL-ED) study. Clinical and epidemiological data from GEMS were made available on ClinEpiDB.org  were loaded on MicrobiomeDB.org  were strongly correlated with Bray-Curtis beta diversity (Adj P < 0.001), explaining 11% and 5.5% of the total variation in microbiome structure, respectively , while Cryptosporidium and rotavirus infection were each associated with <0.5% of the variation in microbiota composition in this cohort (Adj P < 0.01). Only 14 of the 215 Giardia-infected children were also coinfected with either Cryptosporidum or rotavirus. Infection with Giardia was also significantly associated with gut microbiota composition in each of the four countries individually  Bars depict the percent variation in Bray-Curtis beta diversity explained by Giardia infection in each of the four countries. Each analysis was stratified by age and MSD status. Giardia is significantly associated with a change in gut microbiota in all four countries; however, the amount of variation explained by Giardia infection varies across countries. (B) LEfSe graph showing the magnitude of enrichment for all taxa meeting the adjusted P value threshold of 0.1, comparing children with and without Giardia infection. Only taxa with relative abundance of >1% across all samples were used in the analysis. Asterisks denote the significance threshold for each taxon in each country. Download FIG S4, PDF file, 0.09 MB.Copyright © 2020 Berry et al.2020Berry et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the Giardia infection among GEMS participants was associated with enrichment of Prevotella and a reduction in Gammaproteobacteria  and for which Giardia prevalence is not correlated with age (P = 0.99 by chi-squared test). Among 12- to 17-month-old children, the association between Giardia infection and reduction in Gammaproteobacteria and enrichment of Prevotella remained  Boxplots showing that, over the first 5 years of life, the relative abundance of the Prevotella genus increases with age (A) and the relative abundance of the Gammaproteobacteria class decreases with age (B). (C and D) Bar graphs showing that the proportion of children infected with Giardia is low for children in the first year of life compared to 1- to 5-year-old children. Download FIG S5, PDF file, 0.1 MB.Copyright © 2020 Berry et al.2020Berry et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/mSphere.00670-20.6FIG S6Giardia is associated with a reduction in Gammaproteobacteria and enrichment of Prevotella among 12- to 17-month-old children. (A) LEfSe graph showing the magnitude of enrichment for each taxon with LDA score > 2 comparing 12- to 17-month-old children with (n = 51) and without (n = 124) Giardia infection. (B) Boxplots showing the differences in relative abundance in taxa associated with Giardia infection among all 12- to 17-month-old participants. (C and D) Boxplots showing that Giardia is associated with a reduction in the Gammaproteobacteria class among 12- to 17-month-old children with MSD (C) but that Giardia is not significantly associated with Gammaproteobacteria among 12 to 17-month-old children without MSD (D), when the relative abundance of Gammaproteobacteria is low. Download FIG S6, PDF file, 0.1 MB.Copyright © 2020 Berry et al.2020Berry et al.Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the n = 913 samples) (Giardia by enzyme-linked immunosorbent assay (ELISA). Giardia was observed more frequently in formed or soft stool samples compared to liquid or watery stools (P = 0.002 by chi-squared test)  were stored on ClinEpiDB.org and were manually integrated with fecal microbiome data (available on microbiomeDB.org) from 271 participants from the Peru cohort, each sampled up to four times at 6, 12, 18, and 24 months of life (samples) , 38. Of ed test) , consistia class . MAL-ED Giardia infection was driving the change in microbiome composition observed in the GEMS data, then the longitudinal aspect of MAL-ED should allow identification of individuals that convert from Giardia negative to positive during the study period, providing a unique context for examining parasite-microbiome interactions. A total of 170 pairs of MAL-ED observations were identified where a Giardia-positive stool sample could be compared to the Giardia-negative sample obtained from the same individual 6 months prior. Analysis of the microbiome in these discordant pairs showed that becoming infected with Giardia was marked by decreased relative abundance of Escherichia and increased Prevotella (Adj P < 1e−9) (Giardia was not associated with a change in relative abundance of Escherichia or Prevotella (Adj P > 0.1), suggesting that the differences observed upon infection cannot be explained by age alone. These data also suggest that clearing Giardia does not have an inversely proportional effect on the gut microbiota composition as acquiring Giardia. Finally, the enrichment of Prevotella and reduction in Escherichia were evident in children with liquid or watery stools  . Since sy stools  as well y stools . Taken tt health –41.Giardia is associated with the largest impact among all parasites surveyed in dogs and humans.Enteric parasite infections are among the most common causes of diarrhea in humans in the developing world. While bacterial infections and the gut microbiome have been well-studied, the impact of enteric eukaryotic parasites on the microbiome is not well understood, with some reports showing altered microbiome composition –46, 105 –47–Giardia is one of the most common enteric parasites in the world and is remarkable in its ability to cause an array of clinical phenotypes, ranging from asymptomatic infection to severe acute diarrheal disease to chronic gastrointestinal disease. Giardia is the causative agent of giardiasis, a diarrheal illness, and is clearly implicated in serious growth stunting and long-term health consequences  and fully reproduces all analyses and figures in the article.A dockerized environment containing code and software is available on Code Ocean (n = 145), one (n = 92), or multiple (n = 21) protozoan parasites, including Giardia (n = 32) and Cystoisospora (n = 12), and helminths, including hookworm (Ancylostoma caninum) (n = 19), whipworm (Trichuris vulpis) (n = 12), ascarid (Toxocara canis) (n = 9), tapeworm (Dipylidium caninum) (n = 5), and Eucoleus boehmi (n = 3)  study were acquired from patients seen at the Ryan Hospital at the University of Pennsylvania’s School of Veterinary Medicine (PennVet) as part of both sick and wellness visits, as well as from healthy dogs in animal shelters that were brought to the Ryan Hospital to be spayed or neutered. Fecal samples were examined for parasites by fecal flotation (using a zinc sulfate solution at a specific gravity of 1.18 g/ml) at the Clinical Parasitology Laboratory of PennVet. Dogs either had no observable parasites ( (n = 3) . AlthougP values were adjusted for multiple hypothesis testing using Benjamini-Hochberg (B-H) false discovery rate (FDR) corrections  controls with 10,000 permutations using the indicspecies package in R  as implemented in the vegan package  in R 9696. Diffe ggplot2 , patchwo ggplot2 , and ggt ggplot2 . Point-bage in R , adjustiGiardia, Cryptosporidium, and rotavirus were determined using ELISA on participant fecal samples. Additionally, sequencing of the V1-V2 region of the 16S rRNA gene was performed on stool samples from 1,007 participants  investigated the causes, incidence, and impact of moderate to severe diarrhea in 23,567 0- to 59-month-old children in Asia and Africa . Clinicaicipants . Taxonomicipants . The datGiardia infection) and Bray-Curtis beta diversity were calculated using the vegan package in R. Patients were divided among five age groups  to control for the effects associated with age. Here, associations with age were stratified by country, associations with country were stratified by age, and all other associations were stratified by age group and country  study investigated the burden of enteropathogens and malnutrition by monitoring 2,145 children across eight sites in Africa, Asia, and South America starting at 17 days of life and followed longitudinally for up to 60 months . Clinican cohort . Taxonomn cohort , 104. Hen cohort . The dat ggplot2 , patchwo ggplot2 , and ggt ggplot2 .PRJNA594732. All sequencing data used for the canine analyses is also publicly available on MIcrobiomeDB.org as part of the CAMP study. All code is available and reproducible on CodeOcean (https://codeocean.com/capsule/2815529/tree).All sequencing data analyzed here are publicly available on the Sequence Read Archive (SRA) under study accession number


To develop and validate a nomogram for early identification of severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics.The initial clinical and CT imaging data of 217 patients with COVID-19 were analyzed retrospectively from January to March 2020. Two hundred seventeen patients with 146 mild cases and 71 severe cases were randomly divided into training and validation cohorts. Independent risk factors were selected to construct the nomogram for predicting severe COVID-19. Nomogram performance in terms of discrimination and calibration ability was evaluated using the area under the curve (AUC), calibration curve, decision curve, clinical impact curve and risk chart.P < 0.001). Age, density, mosaic perfusion sign and severity score of lung were independent risk factors for severe COVID-19. The nomogram had a AUC of 0.929 , sensitivity of 84.0% and specificity of 86.3%, in the training cohort, and a AUC of 0.936 , sensitivity of 90.5% and specificity of 88.6% in the validation cohort. The calibration curve, decision curve, clinical impact curve and risk chart showed that nomogram had high accuracy and superior net benefit in predicting severe COVID-19.In the training cohort, the severity score of lung in the severe group  was significantly higher than that of the mild group  (The nomogram incorporating initial clinical and CT characteristics may help to identify the severe patients with COVID-19 in the early stage. In December 2019, coronavirus disease 2019 (COVID-19) broke out in Wuhan City, Hubei Province of China [The most common clinical symptoms are fever or cough in addition to other non-specific symptomatology including headache, sore throat or fatigue , 3. A smAccording to Wu et al.  study, tIn this study, we analyzed the clinical and CT imaging characteristics of 217 initially admitted patients infected with COVID-19. Independent risk factors associated with severe or critical COVID-19 were identified. A nomogram was developed and validated to predict the severe COVID-19 in the early stage of disease course.Ethical approvals by our institutional review boards were obtained for this retrospective study, and the need to obtain informed consent was waived. One thousand one hundred twenty-seven suspected patients were consecutively enrolled from January 15th to March 10th, 2020 in several hospitals in Jiangsu and Anhui provinces of China. Two hundred sixty-two patients were hospitalized and had confirmed COVID-19 via laboratory testing with real-time reverse transcriptase polymerase chain reaction (RT-PCR) of respiratory secretions. A total of 217 COVID-19 patients  with chest CT abnormality were included in our study Fig. . AccordiAll patients were followed for more than 30 days after admission. The patients underwent laboratory and CT examination, and symptoms, treatments and outcome events were recorded after admission. The initial clinical data analyzed were as follows: age, sex, symptoms, underlying diseases, laboratory results and days from illness onset to admission. The endpoint of this study was the development of severe illness.All patients underwent chest CT examinations in the supine position by using the GE BrightSpeed Elite 16 scanner or GE LightSpeed VCT scanner  or Siemens SOMATOM Definition AS+ scanner . The scanning range was from the apex to the bottom of the lung. The scanning parameters were as follows: tube voltage 120 kV, tube current automatic mA, helical pitch 0.938, rotation speed 0.6 s, slice thickness and spacing 5 mm. CT images were reconstructed with a slice thickness of 0.625–1.25 mm using a lung kernel as part of the reconstruction process.All images were reviewed by two chest radiologists with 5–15 years of experience by consensus. Further review was undertaken by a third radiologist with 20 years of experience if there was disagreement. The initial CT images were evaluated for each of the 152 patients. The radiologists recorded the following lesion features: location, distribution, morphology, density, vascular bundle thickening, air bronchogram sign, crazy-paving sign, fibrosis, mosaic perfusion sign, pleural effusion, thoracic lymphadenopathy (defined as lymph node size of ≥10 mm in short-axis dimension), number of segments involved and “severity score of lung”. Location was recorded as unilateral lung or bilateral lung. Distribution was defined as peripheral, peripheral with central or central. Morphology was described as nodular or patchy, nodular with patchy or patchy with segmental. Density was recorded as ground glass opacity (GGO), GGO with consolidation or consolidation. Each of the five lung lobes was assessed for degree of involvement and scored as 0 (0% involvement), 1 (1–25% involvement), 2 (26–50% involvement), 3 (51–75% involvement), or 4 (76–100% involvement) [http://www.rproject.org).Categorical variables were reported as frequency and proportions, and continuous variables were reported as the mean ± standard deviation or median with interquartile range (IQR). The independent-sample t test or Mann-Whitney U test was performed to compare the quantitative parameters and Chi-square test to compare the qualitative features between the mild group and severe group. After potential risk factors were selected, multivariate logistic regression analysis was used to determine the independent risk factors associated with severe COVID-19. Selected variables were incorporated in the nomogram to predict severe COVID-19 using “rms” package in R software .The performance of nomogram was assessed by discrimination and calibration. The discriminating ability of nomogram was evaluated using area under the receiver operating characteristic (ROC) curve (AUC). Calibration was evaluated using a calibration plot, a graphic representation of the relationship between the observed and predicted probability, with a bootstrapped sample of the study group for 1000 times. Further calibration of the nomogram was evaluated using the Hosmer-Lemeshow goodness of fit test. Decision curve analysis (DCA) was conducted to determine the clinical usefulness of the nomogram by quantifying the net benefits at different threshold probabilities and clinical impact curve to determine the influence on the outcome of patients. A risk chart plotted performance against caseload. The “rmda” package was used in DCA and “rattle” package in risk chart. Statistical analyses were performed with SPSS 20.0 and R software. All analyses were considered significant at P < 0.05) (Table P < 0.05), but no significant difference in sex, hypertension and COPD between the two groups (P > 0.05) (Table P < 0.05) (Table P > 0.05).Of the 217 patients with COVID-19 included in this study, 212 patients have been discharged and 5 patients died. The majority of patients presented with fever, cough, sore throat or fatigue. A small number of patients had diarrhea or dyspnea. There were no significant differences in age, sex, clinical severity and basic disease between the training and validation cohorts (Table P < 0.05), but no significant differences in pulmonary fibrosis, pleural effusion and thoracic lymphadenopathy between the two groups (P > 0.05) (Table P < 0.001)  had unilateral lung lesions and 108 patients 74.0%) showed bilateral lesions. In the severe group, 71 (100%) patients had bilateral lung lesions. In the training cohort, 74 patients (72.5%) presented bilateral lung lesions and 57 patients (55.9%) showed subpleural distribution in the mild group  and validation cohorts . The decision curve showed that if the threshold probability was within a range from 0.01 to 0.93, more net benefit was added by using the nomogram for predicting severe patients than the “treat all” or “treat none” schemes .


Introduction: Distinguishing between inflammatory bowel disease (IBD) and functional gastrointestinal disorders is a diagnostic challenge. The need for non-invasive biomarker as a diagnostic tool in the assessment of gastrointestinal symptoms is required. The objectives of current study were to determine the spectrum of clinical features in patients tested for fecal calprotectin presenting with high levels and to compare calprotectin levels among already diagnosed patients known to have IBD as per biopsy findings and documented on patients' file with newly presenting patients who were being investigated and did not have a diagnosis.Methods: This retrospective cross-sectional study was conducted in the Department of Pathology and Laboratory Medicine and Department of Medicine, Aga Khan University, Karachi, Pakistan from January 2017 to December 2019. Subjects tested for fecal calprotectin who had elevated fecal calprotectin levels (n = 150) were included in the current study. Each patient deposited a random stool sample in an airtight container for calprotectin analysis. Biochemical analysis of calprotectin was performed by enzyme-linked immunosorbent assay using epitope calprotectin test kit  on ETI-Max 3000 immunoassay analyzer . A structured history form was used for data collection. Results: One hundred and fifty patients were available for inclusion in the ﬁnal analysis. Majority of the patients  were adults (>18 years of age), and 52.7% (n = 79) were females. Median fecal calprotectin (IQR) was 317.3 μg/g (549.10 - 239.2 μg/g) in children (n = 33) and 305 μg/g (609.9 - 201.6 μg/g) in adults; the difference was statistically non-significant . On categorization according to disease, fecal calprotectin levels were significantly elevated  in IBD patients compared to normal subjects, 644 μg/g (644 - 587.8 μg/g) vs 308.5 μg/g (505.4 - 233.8 μg/g), respectively. Diarrhea , abdominal cramps , and weight loss  were the most common complaints noted in children with high fecal calprotectin levels, whereas in adults, abdominal cramps , diarrhea , and weight loss  were the common complaints. The median fecal calprotectin levels in children already known to have IBD (n = 3) were higher than the levels noted in children with no diagnosis (n = 30); p value > 0.05. Similarly, median fecal calprotectin levels in adults with IBD (n = 28) were higher than the levels noted in patients with no specific diagnosis (n = 91), 400.7 μg/g (656.6 - 244.3 μg/g) vs 302.7 μg/g (564.6 - 206 μg/g); p value > 0.05.Conclusion: Current study affirms that the fecal calprotectin test can be used in identifying IBD patients in all age groups. Inflammatory bowel disease (IBD) is a chronic disorder that includes two main forms of chronic gastrointestinal (GI) inflammation: ulcerative colitis (UC) and Crohn's disease (CD). Internationally, the incidence of IBD is approximately 0.5-24.5 cases per 100,000 person-years for UC and 0.1-16 cases per 100,000 person-years for CD [Several laboratory studies, like pro-inflammatory markers, are of value in assisting with the management of IBD and providing supporting information. However, no single laboratory investigation can confirm the diagnosis of IBD. One may use the laboratory values as surrogate markers for inflammation and nutritional status and look for vitamins and minerals deficiencies. The biomarkers, such as erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), have been investigated to help diagnose IBD. Still, the findings were not promising ,4. Care Calprotectin is a marker of inflammation from the S100 calcium-binding protein family. It is expressed mainly by granulocytes and, to a lesser extent, by epithelial cells, reactive macrophages, and monocytes . In neutA cross-sectional observational study was conducted at the Section of Chemical Pathology, Department of Pathology and Laboratory Medicine in collaboration with the Department of Medicine from January 2017 to December 2019. Before the initiation of the study, our investigation protocol was reviewed and approved by the Ethics Committee at Aga Khan University (ERC number: 2019-1616-5031), and the study was conducted per the Helsinki Declaration. All included patients and parents or guardians of children recruited in the study provided informed consent over the telephone at enrollment after being informed of the study purpose. Inclusion criteria were all subjects tested for fecal calprotectin who had elevated fecal calprotectin levels. This study included both adults and children (less than 18 years of age). Consecutive purposive sampling technique was used, and subjects fitting into the inclusion criteria during the study period were included. Subjects with incomplete data or repeat testing were excluded. A structured clinical history form was used for data collection via telephone history and review of clinical data on laboratory information management system, which included clinical history, biochemical data , and findings of intestinal biopsy if performed through the telephonic interview. Patients were categorized into two groups as: (1) already diagnosed patients known to have IBD based on biopsy findings and documented on their clinical charts and (2) newly presenting patients who were being investigated and did not have a diagnosis. Analysis of fecal calprotectin consists of an extraction step on a random stool sample followed by quantification by immunoassay. Biochemical analysis of calprotectin was performed by enzyme-linked immunosorbent assay using epitope calprotectin test kit  on ETI-Max 3000 immunoassay analyzer . To validate the fecal calprotectin results, high- and low-quality control material was run with every batch. Fecal calprotectin cutoff of 43.2 μg/g was used as per product insert from the calprotectin test kit to distinguish between IBS (nonorganic disease) and IBD (organic disease) for both adults and pediatric subjects. Additionally, samples were also received for external quality assessment from the College of American Pathologists during the study period, and all results were acceptable.Data were compiled into Microsoft Excel for analysis, and statistical analysis was performed with Statistical Package for the Social Sciences  version 22. Mean and standard deviation for parametric and median with interquartile range for non-parametric quantitative variables were generated, while frequency and percentage of qualitative variables were generated. For comparison of numerical and categorical variables, the Mann-Whitney U test and the chi-squared test or Fischer's exact test were applied as appropriate. Independent “t” test was performed to compare the calprotectin levels between diagnosed patients with IBD as per biopsy findings, and newly presenting patients were being investigated who did not have a diagnosis. In each analysis, p values less than 0.05 were considered statistically significant.A total of 2995 fecal calprotectin tests were performed in the clinical laboratory of Aga Khan University in three years from January 2017 to December 2019. Among the 190 patients initially included who had high fecal calprotectin levels, 40 were excluded as those were repeat testing samples or patients who did not respond to telephonic contact (three times). Therefore, 150 patients were available for inclusion in the ﬁnal assessments of the study outcomes, as shown in Figure The baseline demographic characteristics of the 150 patients included in the study are shown in Table Pediatric subjectsMean age (SD) of the 33 children included was 9.7 (±5) years, as described in Table Adult subjectsMean age (SD) of adults (n = 117) was 36.2 (14.7) years. Median fecal calprotectin was 305 μg/g (609.9 - 201.6 μg/g) in this adult group. Abdominal cramps , diarrhea , and weight loss  were the most common complaints found in adult patients with elevated fecal calprotectin levels. Majority of the adult patients (70.8%) were not on any medical treatment at the time of recruitment. The median fecal calprotectin levels in adult patients already known to have IBD (n = 29) were higher than the levels noted in patients with no specific diagnosis (n = 91), 369 μg/g (692.4 - 223.7μg/g) vs 296 μg/g (587.6 - 197.9 μg/g), but the difference was statistically non-significant .In this study, we observed that median fecal calprotectin levels in diagnosed IBD patients were high in comparison to the group with no definitive diagnosis. In children, the fecal calprotectin levels were significantly higher compared to patients with no established diagnosis, whereas in adults, fecal calprotectin levels although higher in IBD group were not statistically significant. Analogous findings were reported by Carroccio et al. who observed higher diagnostic accuracy of fecal calprotectin in children as compared to adults. The sensitivity and specificity of fecal calprotectin in children were 100% and 95%, respectively, as reported by them, whereas in adults it was 64% and 80%, respectively. The reasons for a greater number of false-positive results in adults was the use of certain drugs such as aspirin, nonsteroidal anti-inflammatory drugs of concomitant occurrence of other inflammatory, or autoimmune diseases . Ashorn Similarly, another study done in children by Henderson et al. reported that fecal calprotectin levels were significantly raised in IBD patients compared to non-IBD controls . HoweverHowever, till to date the gold standard for diagnosing IBD and differentiating UC and CD is ileocolonoscopy with histological studies. In the large majority of patients suffering from IBD, it is possible to reliably differentiate between UC and CD based on the histological features. In UC, the changes are limited to the mucosa. There is ulceration, crypt distortion and disarray, cryptitis, and crypt abscesses . PromineIn some cases, the biopsy may show overlapping features between UC and CD and the histological distinction between the two may not be possible, therefore being labeled as indeterminate colitis -20. It iIn conclusion, the present study affirms that the fecal calprotectin levels were higher in patients with IBD compared to those with no established diagnosis. The performance of this test is better in children with IBD compared to adults. Moreover, since not all IBD patients had significantly high fecal calprotectin levels, endoscopy and histology remain the gold standard for labeling any patients with IBD, and the fecal calprotectin test can be utilized in predicting patients suspected with IBD that can be referred for further invasive investigations.


Amaranth seed oil (ASO) and rapeseed oil (RSO) are functional foods that display antioxidant and hepatoprotective properties. These oils are also known to lower glucose and cholesterol levels. The current study compared the effects exerted by RSO and ASO on weight loss and metabolic parameters during a 3-week body mass reduction program.2), aged 25–70 years, were enrolled in a 3-week body mass reduction program based on a calorie-restricted diet and physical activity. Participants were randomly categorized into an AO group (administered 20 mL/d of ASO), a RO group (administered 20 mL/d of RSO), and a C group . Anthropometric and metabolic parameters were measured at baseline and endpoint.Eighty-one obese subjects (BMI > 30 kg/mP <  0.05). No significant improvements were observed in the clinical parameters of group C. Fasting insulin  and homeostatic model assessment of insulin resistance (HOMA-IR) (Δ − 1.1 and Δ − 0.5) were decreased in both RO and AO groups, respectively. Fasting glucose , total cholesterol , non-HDL cholesterol , TG/HDL ratio , LDL cholesterol , and triglycerides  were significantly improved in the AO group, compared to the RO group.Significant decreases in weight, body mass index (BMI), waist circumference (WC), hip circumference (HC), fat mass (FM), lean body mass (LBM), visceral fat mass (VFM), and total body water (TBW%) were observed in all groups (The 3-week body mass reduction intervention caused a significant reduction in the weight, BMI, WC, HC, FM, and VFM of all groups. Except for HOMA-IR, there were no statistical differences between the clinical parameters of all groups. However, a trend toward improved insulin levels and HDL% was noticeable in AO and RO. Therapies involving edible oils with high nutritional value, such as RSO and ASO, show potential for improving metabolic measurements during body mass reduction programs. Thus, obese patients undertaking weight reduction programs may benefit from RSO and ASO supplementation.DRKS00017708.retrospectively registered,  Obesity, which is a significant public health issue, has reached pandemic levels in the developed world . AccordiAmaranth seed oil (ASO) and rapeseed oil (RSO) are functional food products that are becoming increasingly popular. The health-promoting properties of both oils are mainly due to a high content of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs). In addition, properties of both oils are determined by a unique composition of bioactive substances as follows: squalene, sterols, tocopherols, carotenoids, phospholipids, etc., for ASO; and tocopherols, carotenoids, flavonoids, phytosterols, and phenolic links (sinapine) for RSO , 8. HowePrevious studies have indicated that diets supplemented with ASO improved antioxidant properties, and exhibited anti-inflammatory, hypotensive, and hepatoprotective effects . FurtherHowever, studies comparing the effectiveness of ASO and RSO on weight reduction and normalization of metabolic parameters associated with obesity are lacking. Fatty acid compositions of ASO and RSO are different. RSO contains higher levels of MUFAs and PUFAs than ASO and displays a more beneficial PUFA/saturated fatty acid (SFA) ratio and unsaturated fatty acid (USFA)/SFA ratio than those of ASO. However, ASO is rich in squalene , 15. TheThe objective of this study was to compare the effect of ASO and RSO supplementation on anthropometric parameters , waist circumference (WC), hip circumference (HC), waist/hip ratio (WHR), and body composition) and selected biochemical parameters , total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), triglycerides (TG), non-HDL levels and TG/HDL ratios in obese adults following a strictly controlled weight loss program lasting 3-weeks.The study was designed as a randomized, double-blind, controlled trial with 3 parallel groups, and performed at the Department of Gastroenterology, Internal Diseases and Dietetics, from July 2014 to March 2016. The study protocol was approved by the Research Ethics Committee of the Poznan University of Medical Sciences, Poland , and the study was performed in accordance with the Helsinki Declaration. All patients provided signed informed consent prior to participation in the study. The study was retrospectively registered in the Deutsches Register Klinischer Studien under the number DRKS00017708.2, stable body weight (< 3 kg self-reported change during the previous 3 months) and being 18–70 years old. The exclusion criteria were as follows: (i) secondary form of obesity; (ii) chronic diseases related to metabolism ; (iii) diabetes mellitus type 1 or uncontrolled diabetes mellitus type 2; (iv) uncontrolled disorders of lipid metabolism; (v) vegetarian or any another alternative dietary habit; (vi) a history of using any dietary supplements within the 3 months prior to the study; (vii) diagnosed with hyperlipidemia or hypertension, or diabetes mellitus type 2, or requiring the introduction and/or change of pharmacological treatment for these diseases during the 2 years before the trial; (viii) eating disorders; and (ix) nicotine, alcohol or drug abuse. Prior to randomization, 9 subjects were excluded according to exclusion criteria, while 2 withdrew consent. The remaining 95 patients were randomized and subjected to intervention. During the course of the 3-week period, 14 patients failed to complete the study as follows: 4 from C, 5 from AO, and 5 from RO. Finally, data pertaining to 81 participants were analyzed. Among those analyzed, 49 had hypertension, 27 had type 2 diabetes and 35 had hyperlipidemia. However, these subjects maintained a constant pattern of pharmacotherapy in accordance with exclusion criteria. The flowchart of the study is shown ; 20 mL RSO ; and untreated (C group (control); 19 women, 10 men). Participants and investigators were blinded to randomization and group allocation. Patients from all groups underwent a 3-week body mass reduction program conducted under controlled conditions. The duration of the study was determined to be 3-weeks due to the need to hospitalize participants for the entire intervention period. Thus, the body mass reduction program was implemented during a 21-day hospital stay. The study participants did not have an opportunity to meet people other than medical staff or obtain food except for the meals provided by a specialized food caterer.During the 3-week body mass reduction program, each subject received daily physical training, in the form of aerobics, from a physical therapist as well as a hypocaloric diet ). The TDEE was individually tailored for each participant using the Harris-Benedict formula and the physical activity level (PAL) index. In order to determine the TDEE and assess the real energy value of the diet, before the program, subjects were required to complete a 24-h record for 3 days. All subjects received the same type of diet prepared by a dietetic food caterer based on a planned menu. Each patient received a diet with an identical composition of macronutrients  derived from the same products. The diets were supplemented with 20 mL ASO (AO group) or 20 mL RSO (RO group) per day instead of the 20 g of fat (butter) normally included in the diet. One meal (breakfast) was supplemented with one dose of oil. ASO “Ol’Amar” produced by “Szarłat”  and vitamin E (5–10 mg/100 g) and RSO produced by “Ol’Vita , vitamin E (66.4 mg / 100 g) at a n-6:n-3 ratio of 2.5:1) were used. Each dose of the oil supplement and the meal was delivered to the participant by a nurse. Compliance with the study protocol was assessed daily by a nurse and weekly by a dietician.Physical training included active and passive breathing exercises for 30 min a day, cardiovascular aerobic exercises twice daily for 60 min and resistance training for 30 min daily. The aerobic training session consisted of a 5 min warm-up session (stretching exercises) at low intensity, followed by 45 min of training  at an intensity between 50 and 70% of the maximum heart rate, and 5 min of closing stretching and breathing exercises of low intensity. Resistance training consisted of a 5 min warm-up session (stretching exercises) of low intensity, followed by 20 min of exercises with a neck barbell. Kettlebells and gymnastic ball and a 5 min warm-up session (stretching exercises) at low intensity.2) was defined as the individual’s body mass divided by the square of their height. WHR was estimated as the ratio of WC to the HC.Anthropometric and metabolic parameters were assessed at baseline and endpoint for each patient. WC (cm) was measured at the midpoint between the lower margin of the least palpable rib and top of the iliac crest, while HC was measured around the widest portion of the buttocks with the tape held parallel to the floor. Both measurements were performed using stretch-resistant medical tape (Seco) and repeated twice to obtain a certain result. Height was measured to the nearest centimeter using a stadiometer. Weight and body composition were assessed using bioelectrical impedance, Tanita MC 980 MA . Body composition analysis was performed in accordance with the recommendations of the European Society for Clinical Nutrition and Metabolism (ESPEN) . BMI . LDL was indirectly measured using the Friedewald equation as follows: LDL (mg/dL) = TC – HDL – (TG/5) [Biochemical and anthropometric measurements were made at the baseline and endpoint. Fasting venous blood samples (10 mL) were collected at the beginning and the end of the program. Venous blood samples (10 mL) were collected by qualified nurses. Collection was performed between 8:00 and 10:00 am under conditions of fasting after overnight resting tubes containing biological material were coded according to the system used. In order to obtain serum, blood was centrifuged at 1500×– (TG/5) . Fasting– (TG/5) .www.metaboanalyst.ca). Normality of data was checked using the Shapiro-Wilks test. Normally distributed data are expressed as mean ± SD, while skewed data are represented by the median (interquartile range). Differences among the 3 groups were determined using the Kruskal–Wallis test followed by an appropriate post-hoc test (multiple comparison test) or one-way ANOVA followed by Tukey’s post-hoc test for normally distributed data. In order to test the differences between the baseline and endpoint in each group, the Wilcoxon test or paired t-test  was conducted [P <  0.05 [Statistical analyses were performed using Statistica 10.0 (StatSoft) and the MetaboAnalyst 3.0. server (onducted . Statist <  0.05 .2) were enrolled in the study. Baseline anthropometric and biochemical characteristics of AO, RO and C groups are shown (Tables Eighty-one obese patients (mean BMI: 39.6 ± 7.4 kg/mP < 0.05) decreases in body weight, BMI, WC, HC, FM, LBM, VFM, and TBW% were observed in all study groups following the 3-week body mass reduction program. There were significant differences between the changes caused by intervention in WC (P = 0.022), HC (P = 0.007) and VFM (P = 0.020) of the RO, AO, and C groups.  were also observed only in the AO group. An increase in HDL% was seen in both AO and RO groups. Furthermore, the results revealed significant differences in HOMA-IR between RO, AO and C groups Table .Table 5This is the first study which directly compared the effects of RSO or ASO supplementation on weight loss, as well as anthropometric and metabolic parameters, of obese participants of a weight loss program. RSO and ASO are characterized by a sizeable difference in fatty acid composition. ASO contains lower amounts of MUFAs (~ 24% vs. ~ 59%) and LC n-3 PUFAs (~ 1% vs. ~ 11%) and displays poorer PUFA/SFA and USFA/SFA ratios compared with those of RSO. Furthermore, ASO has a lower n-3/n-6 ratio than that of RSO . By contIn contrast to studies based on long-term body mass reduction protocols, the current study evaluated whether a short-term weight loss program, conducted under strictly controlled conditions, would induce satisfactory anthropometric and metabolic changes in adult patients with obesity.A previous study showed that the replacement of usual edible oils with oils rich in USFAs, such as ASO and RSO, resulted in lipid-modulating, anti-atherogenic, antioxidative, anti-inflammatory, hepatoprotective and hypotensive effects , 12. TheAnimal studies have indicated that LC n-3 PUFAs may protect against weight gain, raising the possibility that LC n-3 PUFA facilitates weight loss or differential changes in body composition when incorporated into weight-loss programs . FurtherNumerous studies have indicated that consumption of high levels of MUFAs and PUFAs may improve glucose metabolism and lipid profile, compared to the consumption of fats containing higher levels of SFAs. However, whether replacement of dietary SFAs with higher concentrations of MUFAs or PUFAs would further enhance metabolic parameters remains unclear , 32. A mThe current study did not indicate any differences between intervention induced changes in the clinical parameters of AO, RO and C, except in HOMA-IR. HOMA-IR was most markedly reduced in the OR group, while an increase in HOMA-IR was noticed in the C group. However, there was a trend toward significantly reduced fasting serum insulin levels and HDL% in AO and RO groups, as opposed to the C group. Additionally, statistically significant changes in the fasting glucose level, TC, non-HDL, TG/HDL ratio, LDL and TG were observed in the AO group.Previous studies have suggested that RSO may be used to normalize glucose profiles in humans –36. A stThe effect of RSO on circulatory cholesterol levels has been reported in most short-term interventions . Lin et Amaranthus cruentus grain, or 2.5 or 5% crude amaranth oil for 4 weeks. The results showed that amaranth oil (5%) significantly decreased TC HLD and VLDL, compared to the control, and increased fecal excretion of particular neutral sterols and the bile acid, ursodeoxycholate [The beneficial effect exerted by ASO on cholesterol and bile acid absorption, cholesterol lipoprotein distribution, hepatic cholesterol content and cholesterol biosynthesis was demonstrated by Berger et al. , via an ycholate . Howeverycholate  and a huycholate  conducteGonor et al. , investiThe current study revealed that a 3-week intervention with ASO supplementation (20 mL/d) led to a significant reduction in TC, %HDL, LDL, and TG levels and caused a slight, nonsignificant, increase in HDL levels. Statistically significant improvements in non-HDL and TG/HDL levels were also observed in the AO group. Although, ASO contains lower amounts of MUFA and LC n-3 PUFA than RSO, the presented study demonstrated that ASO caused more marked changes in lipid profiles than RSO. A better understanding of reasons underlying this finding may require further investigation.The results of the current study showed that supplementation with ASO and RSO during the 3-week body mass reduction program did not cause changes in anthropometric measurements and clinical outcomes that were more effective, compared to group C. However, the study revealed a trend toward a more marked improvement in carbohydrate and lipid profiles in AO and RO groups compared with that in group C.The strength of this study is that the intervention was conducted under strictly controlled conditions. During the 3-weeks program, the participants were in the hospital ward, being under constant control over diet, supplementation and physical activity. The major limitations of this trial were small sample size and the relatively short duration of intervention. The main reason for such a short duration was that continued hospitalization for 3 weeks may interrupt professional and personal activities. However, it is noteworthy that presented study was one of the few studies conducted under specific and strictly controlled conditions, which is rare in nutritional interventions. Participants of the study received the same type of hypocaloric diet prepared by a dietetic food caterer and underwent the same physical activity program with a physical therapist. The 3-week hospitalization allowed the involvement of the study population in the intervention to be controlled. Although dual energy X-ray absorptiometry (DXA) is the gold standard for the assessment of body composition, the bioimpedance method (BIA) was used in the study due to its non-invasiveness, lower cost, and widespread use.The results of this study indicated that although the 3-week diet and physical activity program exerted a significant effect on anthropometric and clinical parameters, this effect was independent of ASO or RSO supplementation. However, ASO or RSO supplementation resulted in a trend toward more marked changes in the carbohydrate and lipid profiles of AO and RO groups, compared with those of the C group. The use of therapies involving edible oils with high nutritional value, such as RSO and ASO, during body mass reduction programs, may enhance metabolic measurements.


Escherichia coli is the main cause of the disease among children under the age of 5 years. This study is aimed at determining the prevalence and antibiogram pattern of diarrheagenic Escherichia coli (DEC) pathotypes associated with diarrhea cases in the study area.  Diarrhea has been reported as the leading cause of childhood mortality and morbidity globally but with disproportionate impacts in developing nations. Among bacterial etiologic agents of diarrhea, diarrheagenic E. coli were obtained from diarrheal stool samples from male and female patients below 12 years of age using chromogenic agar. Confirmation of the isolates and screening for virulence genes were determined by polymerase chain reaction (PCR) while antimicrobial susceptibility testing was performed using the disk diffusion method. The presence of antibiotic resistance genes to chloramphenicol and tetracycline among the confirmed isolates was also profiled by PCR based on the observed phenotypic resistance pattern.  A total of 120 presumptive isolates of E. coli through PCR. The molecular pathotyping of the confirmed isolates showed their distribution as 41% (43/106) of diffusely adhering E. coli (DAEC), 17% (18/106) of enterohemorrhagic E. coli (EHEC), 17% (18/106) of enteropathogenic E. coli (EPEC), and 10% (11/106) of enteroinvasive E. coli (EIEC), while enteroaggregative E. coli (EAEC) and enterotoxigenic E. coli (ETEC) were not detected, and the remaining 15% did not belong to any pathotype. Notably, high resistance of the isolates to commonly used antimicrobials was observed as follows: ampicillin (98%), chloramphenicol (94%), trimethoprim-sulfamethoxazole (96%), and tetracycline (90.6%), while a relatively low number of the confirmed isolates were resistant to ciprofloxacin (45%) and imipenem (36%). In addition, 94% of the isolates that exhibited phenotypic resistance against chloramphenicol harbored the catA1 resistance gene while 89% that showed resistance to tetracycline had tetA genes.  Of the 120 presumptive isolates, 88.3% (106/120) were confirmed as  These findings showed that DEC could be considered as the leading etiologic bacterial agent responsible for diarrhea in the study community, and the observable high degree of resistance of the isolates to antimicrobial agents is of huge significance, calling for stakeholders to adopt and consolidate the existing antimicrobial stewardship scheme of the government, in order to ensure an uncompromised public health. Diarrhea has been described as one of the leading causes of illness and death in children under the age of 5 years, predominantly in underdeveloped countries . HoweverE. coli (DEC) has been described as an incriminating pathogen of acute infectious diarrhea in children in developing countries [A diversity of pathogens including viruses, bacteria, and parasites are causative agents of infectious diarrhea . Variousountries . The Gloountries . In deveountries .E. coli may be even more harmful than rotavirus infections [E. coli as a result of immature immune systems. There are two classes of E. coli pathogenic strains which are DEC and the extra intestinal pathogenic E. coli (ExPEC) that includes UPEC (related to UTI), SEPEC (related to sepsis), and NEMEC  [E. coli (DEC) that are related to diarrhea based on their different clinical features, virulence factors, and serotypes grouping, and they are enteroaggregative E. coli (EAEC), enteroinvasive E. coli (EIEC), enterohemorrhagic E. coli (EHEC), enteropathogenic E. coli (EPEC), diffusely adherent E. coli (DAEC), and enterotoxigenic E. coli (ETEC) [E. coli is known as the leading agent of diarrheal diseases. In a previous study carried out by Ochi et al. [E. coli was detected as an etiologic agent in 20% of diarrheal specimens, 34% of which were from children under 5 years old. In a study based on children with diarrhea in Mozambique, the prevalence of diarrheagenic E. coli was 42%, and rotavirus had a prevalence of 18%, while parasites accounted for 38% [E. coli is a normal flora of the gastrointestinal tract (GIT) of humans and other mammals, where it contributes greatly to metabolic activities and production of some GIT vitamins. The significance of avirulent strains of E. coli has been exploited widely in recombinant DNA technology. However, when it acquires certain pathogenic factors, E. coli can become a highly virulent pathogen [E. coli pathogenic tendencies lie in its ability to express genetic flexibility through the acquisition and/or transfer of virulence genes by both vertical and horizontal gene transfer mechanisms [Diarrheal diseases have been a contributing factor in child undernourishment and deterioration in growth and development. Besides other typical infections, diarrhea caused by fections . Childreingitis) , 10. Thei (ETEC) . Out of i et al. , diarrhe for 38% . E. colipathogen . E. colichanisms .E. coli strains, there have been myriads of cases of antibiotics resistance gene possession by the organism found in both clinical, animal, and environmental samples [E. coli pathotypes isolated from stool samples of diarrheal patients from hospitals in the Eastern Cape Province, South Africa.Apart from the virulence gene acquisition by  samples , 17. TheEthical clearance to carry out this research was obtained from the University of Fort Hare research ethics committee (ref no.: OKO011SOMO01) and the Eastern Cape Department of Health (ref no.: EC-20146RP10-487), while informed consent was obtained from each patient before sampling and strict confidentiality of the participated patients was maintained.In patients' recruitment, only those with symptoms of diarrhea as defined by WHO  and who Between March, 2015 and May, 2017, 95 diarrheal stool samples were collected from diarrhea patients in some private and public medical facilities in the Amatole District Municipality. Patients who were admitted into the health facilities or those who came in as outpatients with complaints of diarrhea were recruited into the study at the once-off sampling procedure. Only patients with symptoms of diarrhea which is defined as passage of three or more loose or liquid stools per day or frequent passage than is normal for the individual were recruited into the study. Fresh samples were obtained directly from the patients who had just passed watery stool at the time of sampling and from the anorectal cavity of some patients who were still passing watery stools but not at the time of sample collection using sterile swab sticks. Patients who had commenced treatment or had taken antibiotics in the last one month were excluded from the study. The samples were taken from patients below 12 years of age irrespective of sex and race. After collection, the samples were conveyed on ice packs to the Applied and Environmental Microbiology Research Group (AEMREG) laboratory at the University of Fort Hare, Alice, for analysis within 24 hours of collection.E. coli chromogenic agar (Sigma-Aldrich-73009). The plates were incubated at 37°C for 24 h, and presumptive isolates (2-3 distinct colonies per plate) which were blue or purple colored were picked with sterile wire loop and inoculated into 2 mL Tryptone Soya Broth (TSB) and incubated at 37°C for 24 h. Thereafter, the culture was used to prepare 30% glycerol stocks and stored at -80°C for further analyses.The bacteriological analyses of collected samples were performed using standard methods as follows: diarrheal samples (on swab sticks) were streaked directly on E. coli isolates were done as described by Iwu et al. [Bacterial genomic DNA extraction using the boiling method and the molecular confirmation of the presumptive u et al. . VerificE. coli isolates into respective pathotypes was done by PCR using specific primer pairs targeting the relevant virulence genes of EHEC, EPEC, ETEC, EIEC, EAEC, and DAEC pathotypes as listed in μL) contained 1 μL each of 10 pmol of both forward and reverse specific primer pairs, 12.5 μL of PCR master mix (New England Biolabs-NEB), 5.5 μL of nuclease free water, and 5.0 μL of DNA template. The cycling conditions were as follows: 94°C initial denaturation for 5 min, followed by 35 cycles at 94°C in 60 sec, annealing temperature as shown in E. coli ATCC 25922 was used as a positive control in the confirmation of the presumptive isolates.Delineation of the confirmed E. coli isolates were determined according to Clinical and Laboratory Standard Institute (CLSI) [β-lactam (ampicillin (10 μg), (ii) cephalosporin: cefotaxime (30 μg) and cefuroxime (30 μg), (iii) chloramphenicol: chloramphenicol (30 μg), (iv) fluoroquinolone: norfloxacin (10 μg) and ciprofloxacin (5 μg), (v) sulfonamides: trimethoprim-sulfamethoxazole (25 μg), (vi) carbapenem: imipenem (10 μg), (vii) macrolide:-erythromycin (15 μg), (viii) aminoglycoside: gentamicin (10 μg), and (ix) tetracyclines: tetracycline (30 μg) and doxycycline (30 μg). Thereafter, the plates were incubated at 37°C for 24 h and read for sensitivity. The antibiotics chosen are typically used for the treatment of diarrheal diseases caused by E. coli.The antibiotic susceptibility profiles of the confirmed 106 e (CLSI)  guidelincatA1 and tetA resistance genes as presented in μL reaction mixture containing 1 μL each of both forward and reverse specific primer pairs, 12.5 μL of PCR master mix (New England Biolabs-NEB), 5.5 μL of nuclease free water, and 5.0 μL of DNA template. The cycling conditions were as follows: 94°C initial denaturation for 5 min, followed by 35 cycles of 94°C in 60 sec, 53°C and 52°C  for 30 sec, 72°C (extension) for 60 sec, and a final elongation step at 72°C for 5 min. Amplification of PCR product was verified by electrophoresis in a 1.5% agarose gel stained with ethidium bromide, visualized and documented in an Alliance 4.7 transilluminator. E. coli ATCC 25922 was used a negative control in antibiotic resistance determinant testing.Chloramphenicol and tetracycline resistance genes among the isolates were assessed based on the observed phenotypic resistance patterns by PCR using specific primers targeting E. coli were obtained from the diarrheal stool samples collected from both outpatients and inpatients attending or admitted in private and public hospitals in the Amatole District Municipality of Eastern Cape Province. A total of 95 stool samples were collected from the study participants whose ages ranged from less than a year to 12 years. The basic information about the patients and the seasonal distribution of diarrhea in the study period are shown in A total of 120 presumptive isolates of E. coli through PCR  isolated from patients attending some hospitals in the Amatole District Municipality of Eastern Cape Province, South Africa, were investigated. Related findings from previous studies in the study area have shown the occurrence of various E. coli strains including the O157 : H7, which is the etiologic agent of enteric infections such as bloody diarrhea, from other sources including surface water, waste water effluents, swine, cattle, and fresh cow milk, representing the environmental and animal sources. In a study, Iweriebor et al. [E. coli O157:H7 in cattle from two dairy farms situated in one of the local municipalities in the district, when faecal samples numbering 400 were screened from the cattle population of 920. Subsequently, Msolo et al. [E. coli O157:H7 with its prevalence of 11% in samples of raw milk, cattle udder, milking machine, and hands of dairy workers. Similarly, some intestinal pathogenic E. coli (InPEC) strains were equally detected in treated final effluents meant to be discharged into the receiving water body in the area, with the prevalence of 1.4% recorded for ETEC and 7.6% for both EPEC and EAEC [E. coli in clinical samples of human origin obtained from patients at some health facilities in the district municipality, thereby confirming the role of the organism as major etiologic agent in diarrhea cases in the study area.In this study, the prevalence and the antibiogram patterns of diarrheagenic r et al.  reportedo et al.  assertedand EAEC . More reand EAEC  equally Salmonella spp. was reported as the most frequently identified enteropathogens [Campylobacter jejuni was described as the leading enteropathogen in adults in Sweden [In this study, 106 isolates were confirmed to be DEC, which is 88.3% of the total isolates obtained from culture prior to molecular confirmation. This result is significant and showed that DEC is a leading bacterial agent causing diarrhea in the study community, thereby solidly supports various epidemiological findings that have previously confirmed DEC as the most frequently isolated enteropathogenic bacteria from diarrhea cases globally –31. Howeathogens , while Cn Sweden . Neverthn Sweden . The notn Sweden , Nigerian Sweden , Thailann Sweden , and Repn Sweden .E. coli (DAEC) (41%), followed by enterohemorrhagic E. coli (EHEC) (17%), enteropathogenic E. coli (EPEC) (17%), and enteroinvasive E. coli (EIEC) (10%), while no enteroaggregative E. coli (EAEC) or enterotoxigenic E.coli (ETEC) were detected. This is in agreement with the reports from Maputo, Mozambique, in which DAEC frequency was higher than that of EPEC, ETEC, EIEC, or EAEC in diarrheal stool samples [The most prevalent pathotype of DEC encountered in this study was diffusely adhering  samples . Studies samples , 31, 38. samples .As earlier mentioned, the relatively higher prevalence of 17% was also recorded for EPEC in this study, and this corroborates findings from various studies in many parts of Africa and worldwide , 40, 41.E coli strain previously rendered in Southern Africa countries and beyond. EHEC was first documented in South Africa in 1990 in a periodic episode of hemorrhagic uremic syndrome caused by EHEC O157 : H7 [In the same vein, the prevalence of 17% that was also recorded for EHEC in this study is of huge significance considering the havoc that outbreaks of the 157 : H7 . Three y157 : H7 . Also, i157 : H7  reported157 : H7 . EHEC di157 : H7 . In esse157 : H7 .E. coli has been rarely reported as a diarrheal agent in teenagers and adults but in Ecuador, reports from one study found EIEC to be a leading cause of infectious diarrhea in all age groups [The EIEC in this study was detected in 10% of the total confirmed isolates. However, no EIEC was identified in a study conducted in Gabon, while reports from studies carried out in Kenya, Mozambique, Ghana, and Nigeria also identified a small number of EIEC pathotypes . The pree groups . Most ote groups  were note groups  identifiE. coli has often been used as an important index in surveying the critical selection of antimicrobial agents and determination of genes responsible for resistance [The conspicuously increased rate of antimicrobial resistance of some strains of diarrheagenic bacterial pathogens across the globe is quite alarming, more significantly in less developed regions . The indsistance . Previousistance . Certainsistance , 55. Thesistance .In this study, a high rate of DEC antimicrobial resistance to frequently used antibiotics such as ampicillin (98%), tetracycline (91%), chloramphenicol (94%), and trimethoprim-sulfamethoxazole (96%) was noticed. This finding is similar to some reports from various studies in children from Bolivia, Peru, Mozambique, Vietnam, Mexico, Argentina, and Tanzania, which observed over 70% prevalence of ampicillin resistance in DEC isolates identified . In anotcatA1 and tetA genes, respectively. This is much comparable to 91% (catA1) and 93% (tetA) obtained in a study conducted at North West England by Ahmed et al. [In this study, resistance to imipenem, ciprofloxacin, and norfloxacin  was relatively lower than other studies. This corroborates a study that recommended fluoroquinolones as first-line drugs to treat diarrhea . In a bid et al. , and it The relatively high prevalence of DEC in this study is remarkable, and it highlights the fact that the organism is a significant agent of infectious diarrhea and could be the leading cause of gastroenteritis in the Eastern Cape. Furthermore, the notable high resistance of the isolates to commonly used antibiotics in the treatment of diarrhea is of huge concern, and it emphasizes the need for more proactive measures by the stakeholders in curbing the menace. However, observable phenotypically high resistance of the isolates to the studied chemotherapeutic agents by the conventional susceptibility profiling should give clues to health practitioners in the area on the best antibiotics of choice in treating diarrhea as a result of DEC infections.


Obsessive-compulsive disorder (OCD) is an anxiety disorder that causes impairment in daily activities. This study aimed to assess the safety and efficacy of transcranial direct current stimulation (tDCS) as adjunctive therapy with fluoxetine in individuals diagnosed with moderate to severe OCD.This is a randomized, double-blind sham-controlled trial. Individuals with OCD who had baseline Yale-Brown obsessive-compulsive scale (Y-BOCS) of > 15 were enrolled. Eligible cases were randomly assigned in 1:1 ratio to receive either 20-min-period of stimulation with tDCS and fluoxetine  or fluoxetine only (sham control arm). The anodal electrode of tDCS was placed over the left dorsolateral prefrontal cortex (Fp3) and the cathodal electrode was placed over the right orbitofrontal cortex (F8). Two mA electrical stimulation with the tDCS was used for 20 min in individuals of experimental group. In the control group, electrodes were placed and stimulation was administered for 30 s to induce the same skin sensation as in experimental group. This procedure was performed three times per week for 8 weeks. Y-BOCS test was assessed at baseline, week 4 (after 12th stimulation), week 8 (after 24th stimulation), and 1 month after the last stimulation. The primary endpoints were the mean changes in Y-BOCS total score from baseline to the last visit. The secondary endpoints were the mean changes in obsession and compulsion sub-scores from baseline to the last visit. Adverse events were also assessed. Mixed design repeated measures analysis of variance assessed the endpoints.(1.85) = 30.83; P < 0.001), OCD obsession (F(2.23) = 25.01; P < 0.001), and compulsion (F(2.06) = 10.81; P < 0.001) scores decreased significantly during the study. No statistical differences were, however, detected between experimental and control groups (P > 0.05). The tDCS was well tolerated and no major adverse events were reported.Sixty individuals (30 in each group) were participated. All individuals in control group and 28 cases in experimental arm completed the trial. The mean Y-BOCS (FThis study showed that among individuals with moderate to severe OCD, there was no significant difference regarding OC symptoms between cases used tDCS as adjunctive therapy with fluoxetine and individuals used fluoxetine only.IRCT2017030632904N1. Registered 14 July 2017, http://irct.ir/user/trial/44193/view The global prevalence of OCD is about 1 to 2% [Obsessive-compulsive disorder (OCD) is a debilitating condition characterized by recurring, unwanted thoughts and ideas , the orbitofrontal cortex, medial prefrontal cortex (e.g. anterior cyngulate gyrus), supplementary motor area, and the basal ganglia , 12. A nThis was a randomized double-blind sham-controlled trial conducted in Amir Kabir Hospital, affiliated to Arak University of Medical Sciences, Iran. Individuals aged 18 to 60 years with recent diagnosis of moderate to severe OCD based on DSM-V criteria  were incThe trial was conducted according to the original protocol. The protocol of this study was reviewed and approved by the local ethics committee (IR.ARAKMU.REC.1395.9). Each subject received a full description of the study. Written informed consent was obtained from all subjects. The study was conducted with adherence to CONSORT guidelines and was registered prospectively with Iranian Registry of Clinical Trials, IRCT.ir; number: IRCT2017030632904N1.Included participants were randomly assigned in 1:1 ratio via an interactive web response system to receive either tDCS and fluoxetine or fluoxetine only. Permuted block randomization method (block size = 4) was used for group allocation. Participants and investigators were blinded during the study. Two individuals  were responsible to perform tDCS on participants. They were trained in the procedure of tDCS and were informed about the aim of the study. They were the only individuals who were not masked during the trial but they had no information regarding the clinical data of participants. They had no contacts with investigators and were monitored during the procedure so they did not reveal any information to participants. The responsible statistician was not aware of the clinical characteristics of subjects. All cases were connected to the tDCS via electrodes and electric current was administered to the sham control group for 30 s so the same sensation as in experimental group (tingling of skin) was induced. The electrodes were remained around the head of these cases for further 20 min without electrical stimulation.Direct electrical stimulation was started with the tDCS device . Two electrodes (size: 7 cm × 5 cm) referenced as anode and cathode were used to deliver stimulation and were held around the head by non-conducting bandage. To minimize the noise pollution, the doors of recording room were closed during the experiment.The anodal electrode generally increases (depolarize neurons) and the cathodal electrode decreases (hyperpolarize neurons) the cortical excitability . Anodal The scale was developed by Goodman et al. , and con8 to 15: mild; 16 to 23: moderate; 24 to 31: severe; 32 to 40: extreme.The study on 40 patients showed that the reliability of Yale-Brown obsessive compulsive scale (Y-BOCS) was 0.98 and the internal consistency coefficient  was 0.89 . The stuAt baseline, Demographic and clinical data were obtained by interviewing individuals. Clinical symptoms and Y-BOCS scores were measured at baseline and during follow-ups at week 4 (after 12th session), week 8 (after 24th session), and 1 month after the last session. The primary endpoints were the mean changes in Y-BOCS total score from baseline to the last follow-up visit. The secondary endpoints were the mean changes in Y-BOCS obsession and compulsion sub-scores from baseline to the last follow-up visit. Adverse events were also assessed. During the follow-up visits we asked the participants to report any side effects. A phone number was also provided so the cases could ask their questions or report any side effects as soon as possible. Participants were requested to visit the emergency department if a major complication happened. A list of common adverse events of SSRI and tDCS was also provided so the cases were aware of those conditions. The interview and procedures were all performed in a calm and stress-free situation for the examiner and participants.When this study was designed in 2017, no similar placebo-controlled study was available. Therefore, we assumed effect size as 0.15 (F = 0.15) to calculate the sample size . Considering α (the probability of type I error) as 0.05 and β (the probability of type II error) as 0.20, the required total sample size was 60 (30 participants per group). G*Power software was used for sample size calculation.p-values< 0.05 were considered statistically significant.Data were analyzed by IBM SPSS Software, version 25.0 . Descriptive statistics  were used to express demographic and clinical data. The normality of data were examined using Kolmogorov-Smirnov test. Baseline characteristics were compared between groups using chi-square tests for categorical variables and independent sample t-tests for numeric variables. Mixed design repeated measures analysis of variance (ANOVA) with terms for group, time, and time*group interaction was used to evaluate changes in outcome measures during the study period. Cohen’s d test with 95% confidence interval (CI) were used to measure the effect sizes that were classified as small (d: 0 to 0.20), medium (d: 0.20 to 0.50), and large (d > 0.50). Two-tailed n = 30) and sham control (n = 30) groups. All participants completed 24 sessions of the allocated treatment. Two individuals in tDCS arm were lost for the last follow-up visit. None of these missed participants reported adverse events. Overall, 28 individuals in the tDCS group and all participants in the sham control arm completed the study  = 30.83; P < 0.001) but no significant group effect (F(1.00) = 0.07; P = 0.799) or interaction between time and group effect were observed (F(1.85) = 0.86; P = 0.420)  = 25.01; P < 0.001 and F(2.06) = 10.81; P < 0.001, respectively). No significant time*group interaction was, however, detected for Y-BOCS obsession (F(1.85) = 0.68; P = 0.523) and compulsion (F(2.06) = 0.147; P = 0.869) scores. The Cohen’s d test at the last follow-up visit showed d: 0.029 with 95%CI: − 0.496 to 0.555 for obsession mean scores and d: 0.119 with 95%CI: − 0.405 to 0.644 for compulsion mean scores.Our study also showed that Y-BOCS obsession and compulsion scores decreased significantly during the study period . No adverse event occurred in the control group.Our trial showed that individuals with moderate to severe OCD in the experimental group (tDCS stimulation + fluoxetine) had about 23% improvements in OC symptoms using Y-BOCS scale. Participants in sham controlled arm had about 22% improvements in symptoms. There was no statistical significant difference between two groups.The lack of significant difference between groups might be partialy explained by tDCS parameters used in this trial. The most appropriate tDCS protocol regarding the electrode placement and the current delivered via electrodes are not well-established. The higher current dosage and longer sessions that were used in other psychiatric disorders might improve OC symptoms significantly . Anodal Different case-report studies assessed the efficacy of tDCS stimulation on individuals with OCD Table . The resFour randomized clinical trials assessed the efficacy of tDCS on people with OCD Table  21, 42––42–44. ARandomization, blinding, and the presence of sham controlled arm were the major strengths of this study. The prospective population-based approach was another important strength of our trial that can increase the external validity of the reported results. Small sample size and short periods of follow-up were main limitations of trial. OC symptoms cannot be objectively evaluated and our outcomes were reliant on the reports of individuals using Y-BOCS test. This can lead to measurement bias (hawthorne effect). The cathodal stimulation with tDCS on individuals with OCD was shown to be effective in case-report studies more than anodal stimulation. Future controlled RCTs should investigate this hypothesis. Further studies with higher number of cases should also evaluate the efficacy of tDCS as the only therapy on improvements of OC symptoms in cases with different severity.The tDCS adjunctive therapy with the anode placed over left DLPFC and cathode placed over right OFC was generally safe and a tolerable procedure. This study didn’t show significant clinical efficacy of add-on therapy with tDCS in the management of individuals with moderate to severe OCD compared to the control group.