We recommend screening Mexican American individuals with T2D, specifically those with poor glycemic control, for bone loss and fracture risk.Altered bone quality, caused by underlying metabolic changes of type 2 diabetes (T2D), has been hypothesized to cause altered bone strength and turnover leading to increased fracture risk in T2D patients. Current understanding about changes in bone turnover markers in T2D patients is mainly based on studies focused on Caucasian men and women. However, Hispanic populations have the highest prevalence of both T2D and osteoporosis in the US. We investigated associations of glycemic control (in terms of glycated hemoglobin [HbA1c]) and bone turnover rate in 69 older (≥50 years) Mexican American Cameron County Hispanic Cohort (CCHC) participants with T2D. Multivariable analyses were conducted to assess the associations between HbA1c (%), serum osteocalcin (OC), and serum sclerostin. In agreement with published reports from other racial/ethnic populations, our study found that lower bone turnover (indicated by lower serum OC) occurred in Mexican American men with T2D who had poorer glycemic control. For the women in our study, we found no significant association between glycemic control and OC. In contrast, HbA1c was positively associated with sclerostin for women, with near significance ( Individuals with type 2 diabetes (T2D) have 10%–30% higher risks of vertebral, hip, and other fractures than age-matched individuals without diabetes [Obesity with greater accumulation of visceral fat, indicating underlying metabolic changes, has been associated with low BMD . The simFew human studies have reported associations between poor glycemic control and low rates of bone turnover indicated by low serum levels of osteocalcin (OC) –13. MostLow bone turnover rates in older patients are indicated by low serum OC, and patients with T2D have been shown to have low OC , 13. RedN = 20) and women (N = 49) diagnosed with T2D (according to American Diabetic Association diagnosis criteria 2010) [Participants were part of the population-based older (≥50 years) cohort of men and women nested in the CCHC study. Details about the setting, data collection, and follow-up plan for the CCHC study have been published previously –17. Brieia 2010) .The main CCHC study and the bone protocol were approved by the committee for protection of human subjects (CPHS) of the University of Texas Health Science Center at Houston. Participants were excluded if they had a history of active cancer, type 1 diabetes, known metabolic bone disease, or known osteoporosis; if they had a history of being treated for osteoporosis; or if they were taking medications affecting bone health, for example, thiazolidinedione. All women included in this study were postmenopausal by self-reported history of no menstrual cycle in the past 6 months.A Hologic Discovery QDR series DXA instrument was used to complete whole-body and hip scans. The left side was the default scan site, but the right side was used if the subject had a history of left hip fracture or history of surgical intervention.Blood samples were collected using standard phlebotomy techniques during data collection visits. After clotting and centrifugation, aliquots of serum were frozen at −70°C. Samples were shipped on dry ice to the National Aeronautics and Space Administration's (NASA) Nutritional Biochemistry Laboratory at the Johnson Space Center (JSC) for subsequent analysis.Osteocalcin levels  were determined by radioimmunoassay (RIA) . 25-hydroxyvitamin D was determined by RIA . Sclerostin was determined by enzyme immunoassay . Parathyroid hormone was determined by immunoradiometric assay . Serum magnesium and phosphorus were determined colorimetrically . The Nutritional Biochemistry Laboratory at JSC participates in several external quality control programs, including DEQAS and NIST.Glycemic control was reported in terms of HbA1c levels. Blood samples collected as part of the cohort study were used for HbA1c analysis performed in the local CLIA-approved laboratory using HPLC methodology. A report showing that an HbA1c level of >8%  was assoBecause of known differences in bone mineral distribution, data were analyzed separately for men and women in this cross-sectional study. Participants' characteristics were described using percentages for categorical variables and mean (±standard deviation) for continuous variables. Univariable and multivariable analyses were conducted to assess the associations between HbA1c (%) and each of the continuous outcome variables, that is, serum OC and serum sclerostin. The multivariable regression models were adjusted for age groups (dichotomized as <65 and ≥65 years ), BMI, fp = 0.12). Mean serum sclerostin was higher in men with good glycemic control than in those with poor control (p = 0.34). While the differences in mean OC levels between women with poor and good glycemic control (14.8 ± 6.1 vs 15.7 ± 6.4 ng/ml) were not significant (p = 0.64), there was a trend for mean sclerostin to be higher in women with poor glycemic control than in those with good control . In men, higher mean OC and lower mean sclerostin were reported in the younger (<65 years) group than in the older group ( control  (61.3 ± er group . In womep = 0.04) (p = 0.07 for both age groups).Tables  = 0.04) . Longer  = 0.04) . In womep = 0.07)  with bone turnover (serum OC levels) in older (≥65 years) Mexican American men with T2D in the CCHC study. Duration of disease was not associated with serum OC . In agre = 0.07) .Mean levels of serum OC in both men and women in our study  did not The negative associations between glycemic control and serum OC were not consistent with the high serum sclerostin (indicator of low bone formation) for both age groups and for both sexes in our study. However, we compared bone turnover with poor or good control of blood glucose levels in the older Mexican American men and women. Mean serum levels of sclerostin for men and women in our study  were higher than the 50th percentile of normal ranges (for men 32–67 pmol/l and for women 22–52 pmol/l). In the absence of clear normative data in clinical practice for older adults without metabolic or bone health problems, clinical judgment of high risk for fracture is often based on a trend of bone turnover that is above or below the 50th percentile. Although this study is limited by a lack of nondiabetic controls, considering the normal ranges, the higher than normal values found in our study indicate that bone formation may be low for both men and women, thereby confirming a similar pattern of bone formation in older adults with T2D reported for people from other racial/ethnic backgrounds , 24.Because BMD often is misleading for fracture risk assessment in patients with T2D, adding serum OC levels to current testing, as an indicator may help to improve screening of T2D patients for their risk of fracture. Because an age-appropriate normal range for older subjects (>65 years) is unavailable, we recommend establishing a baseline level for markers of bone turnover at the time of screening with DXA BMD and continuous monitoring over time in association with HbA1c to monitor bone metabolism in the older T2D Mexican Americans.Bone changes in women are far more complex than those in men because women undergo additional physiological changes due to estrogen deficiency, pregnancy, and lactation. Bone turnover is usually higher in women during the postmenopausal years than it is in men in the same age range . While iThis is the first study reporting relationships between glycemic control and bone turnover in an older Mexican American cohort. While our results may not be applicable to people from other racial/ethnic backgrounds, this study adds valuable scientific information about bone metabolic changes in individuals from Hispanic backgrounds who have T2D. The small number of participants, lack of nondiabetic controls, and the cross-sectional analysis of data are limitations of our study. However, none of the study participants were on medications that are known to affect bone metabolism, for example, thiazolidinedione and bisphosphonates. Future follow-up of this cohort with additional numbers of men and women with and without T2D and addition of more specific resorption and formation markers will help define the impact of T2D on fracture risk of the aging skeleton in older Mexican American men and women. The significant results in men, with a smaller sample size than women, in our study also raise concerns of worse alteration of bone metabolism in men than women, which may indicate worse risks of fragility fracture in men with T2D.Poor glycemic control in older Mexican American men and women is considered risk of developing multiple cardio-metabolic health problems. Our study adds risk of abnormal bone metabolism to this list of concerns, and we recommend screening Mexican American individuals with T2D, specifically those with poor glycemic control, for bone loss and fracture risk.


This study was performed to investigate the relationship between the abundance of pathogenic gut microbes in Chinese patients with inflammatory bowel disease (IBD) and disease severity.Fusobacterium species (spp), enterotoxigenic Bacteroides fragilis (B fragilis), enteropathogenic Escherichia coli (E coli), and Enterococcus faecalis  were assessed by quantitative real-time PCR (qRT-PCR). Spearman correlation coefficients were calculated to test associations between bacterial content and clinical parameters.We collected clinical data and fecal samples from 47 therapy-naive Chinese patients with ulcerative colitis (UC), 67 patients with Crohn disease (CD), and 48 healthy volunteers. Bacteria levels of Fusobacterium spp and E faecalis were significantly increased in the feces of patients with IBD (P < 0.01). B fragilis levels were higher (P < 0.05) and E faecalis levels lower (P < 0.05) in patients with CD compared to those with UC. Increased E faecalis colonization in CD associated positively with disease activity (P = 0.015), Crohn disease activity index , and fecal calprotectin (P = 0.016).Compared to healthy controls, the levels of both E faecalis and Fusobacterium spp are significantly enriched in patients with IBD, and increased E faecalis infection is associated with clinically active CD. The chronic course of recurrence during IBD progression gradually leads to complications, such as stricture, fistula formation, intestinal obstruction, intestinal perforation, toxic megacolon, and even cancer. Although only 1% to 2% of all colorectal cancer (CRC) cases are colitis-associated, CRC is considered a serious complication of IBD accounting for approximately 10% to 15% of all deaths in patients with IBD.,3 For example, antibiotics can ameliorate IBD symptoms, and genetically engineered IBD-susceptible rodents maintained under germ-free conditions are protected from IBD.The etiology and pathogenesis of IBD are not fully understood, but many clinical and experimental observations strongly implicate intestinal bacteria as significant contributors to disease initiation and progression.–8 Ott et al performed 16S ribosomal DNA (rDNA)-based single-strand conformation polymorphism fingerprinting to reveal that mucosal inflammation in IBD was associated with a loss of normal anaerobic bacteria. On the other hand, van der Waaij et al suggested that patients with active IBD or shortly after remission exhibited an increase in immunoglobulin-coated fecal anaerobic bacteria compared to healthy controls.Specific microorganisms directly associated with the pathogenesis of CD or UC have not been identified to date, but clinical and in vitro evidence suggests that the gut microbiome of patients with IBD differs significantly from that of healthy patients.Pseudomonas contributes to the pathogenesis of CD. Another study reported that the frequency of toxigenic Clostridium difficile was 7% higher in IBD patients than in healthy volunteers. Furthermore, an increased abundance in Enterobacteriaceae, Pasteurellacaea, Veillonellaceae, and Fusobacteriaceae, and decreased abundance in Erysipelotrichales, Bacteroidales, and Clostridiales were found to correlate strongly with disease status. Despite intensive research, the mechanisms by which bacteria affect the development of IBD or the disease-specific changes in the intestinal flora have not been determined to date. Thus, if the gut microbiome is considered to be a key driver of inflammation, the dysbiosis that precedes relapse could be a major therapeutic target.The ratio between different pathogenic and beneficial bacterial species is also altered in patients with IBD. Fusobacterium, Bacteroides, Enterococcus, and Streptococcus were enriched in IBD patients . These species or genera have also been observed to be associated with CRC and its clinicopathological features.–18 For example, multiple studies have demonstrated that fecal or tissue samples from CRC patients were enriched for specific bacterial pathogens, including Fusobacterium,–15Enterococcus faecalis , enterotoxigenic Bacteroides fragilis , enteropathogenic Escherichia coli , and Streptococcus gallolyticus.–22 Recently, Nakatsu et al also suggested that a taxonomically defined microbial consortium is implicated in the development of CRC. Furthermore, Ericsson et al identified a naturally occurring variation in gut microbes that was associated with CRC severity, and the abundance of certain taxa correlated with decreased tumor burden. Once we obtain a better understanding of the microbial dysbiosis underlying colorectal carcinogenesis, new strategies toward the diagnosis, treatment, and prevention of CRC may be realized.Using microbial 16S ribosomal RNA (rRNA) sequencing, we previously showed that Fusobacterium species (spp), ETBF, enteropathogenic E coli, and E faecalis. We then performed correlation analyses to determine whether the presence of these bacterial populations was associated with disease severity.The objective of our study was to investigate the relationship between CRC-associated bacterial pathogens and IBD activity. We collected stool samples from Chinese patients presenting with CD or UC and healthy volunteers. We employed quantitative real-time polymerase chain reaction (qRT-PCR) to quantify the levels of four pathogens frequently associated with CRC, including 22.1Patients with CD or UC who had not received any treatment for IBD were recruited between June 2012 and July 2013 at the Department of Gastroenterology of Nanfang Hospital, Southern Medical University, China. Healthy volunteers ranging in age from 20 to 40 years (to match the age and gender of patients with CD) were recruited from the general population around the Southern Medical University. Exclusion criteria included patients with previous IBD-treatment, receiving antibiotics or probiotics in the last 4 weeks, age <15 years, presentation of other known chronic diseases, and pregnancy or breast feeding. Fecal samples were collected from all enrolled subjects and stored at −80 °C before further processing.All study protocols were in compliance with the Declaration of Helsinki and were approved by the Ethics Committee of both Nanfang Hospital, Southern Medical University and Guangzhou First People's Hospital affiliated with Guangzhou Medical University. Written consent for study participation was obtained from each volunteer.2.2 According to the Montreal classification, UC was categorized as ulcerative proctitis (E1), left-sided  UC (E2), and extensive UC , based on the extent of the disease. CD was classified based on location in the ileum (L1), colon (L2), or ileocolon (L3). For the evaluation of disease activity, the Mayo score for UC and Crohn disease activity index (CDAI) score for CD were determined .Diagnoses of UC and CD were based on the internationally accepted Lennard–Jones criteria.2.3 DNA concentrations were measured with a NanoDrop 2000 Bioanalyzer . Samples were stored at −20 °C before qRT-PCR assays.Bacterial DNA was extracted from the fecal samples using the TIANamp Stool DNA Kit  according to the manufacturer's instructions.2.48 copies/μL) were prepared prior to each qRT-PCR assay. Results for each sample were expressed as the copy number of bacterial 16S rDNA per gram of feces. Assays were performed in 96-well optical plates on the Light Cycler 480 Real-Time PCR System  in triplicate. The 20 μL reactions contained Light Cycler 480 SYBR Green I Master solution , the specific primer pairs at a final concentration of 0.5 μM, and 5 μL of DNA template. Amplifications were performed as follows: initial denaturation at 95 °C for 5 minutes, followed by 45 cycles of denaturation at 95 °C for 10 seconds, annealing at 52 to 56 °C (primer dependent) for 10 seconds, and extension at 72 °C for 10 seconds. The specificity of each amplification was assessed by melting curve analysis. The efficiency of amplification for each primer pair was estimated from the standard curves.All primer sets for the 4 bacterial groups or species targeted the 16S rRNA gene and are listed in Table 2.5FC concentrations were measured with a quantitative PhiCal enzyme-linked immunosorbent assay kit  according to the manufacturer's instructions. Fecal specimens were diluted 1:2500. Enzyme-linked immunosorbent assay plates were read by a Thermo Scientific Microplate Reader . Samples containing ≥100 μg of calprotectin per 1 g of feces were considered calprotectin-positive.2.6P value of less than 0.05 was considered statistically significant.Data are presented as means ± standard error of the mean (SEM) for quantitative variables and as frequencies for qualitative variables. Given the nonnormal distribution of the data analyzed, a nonparametric test  was used to assess changes in bacterial number between groups. Results with a false discovery rate ≤0.05 after applying multiple test correction (Bonferroni correction method) for each species were considered significant. The Spearman correlation coefficient was calculated to estimate the correlations between variables. Statistical analyses were performed with the statistical software package SPSS16.0 . A 2-tailed 33.1P < 0.001) nor gender make-up (P = 0.746) different across these 3 groups.The clinical data for each patient cohort are summarized in Table 3.2Fusobacterium spp and E faecalis were significantly increased in the feces of patients with IBD . Conversely, the levels of E faecalis were lower in patients with CD than in patients with UC (P < 0.05). No significant differences in the levels of E coli were detected between IBD patients and healthy controls (P > 0.05).We assessed the abundance of each bacterial species by measuring the expression of the 16S rRNA gene specific to each pathogen by qRT-PCR. The levels of 3.3E faecalis was the most common bacterial species of the 4 pathogens detected in all IBD cases, occurring in 95.74% (N = 45/47) of patients with UC and 86.57% (N = 58/67) of patients with CD .CD Table . A signi CD Fig. A. AccordFusobacterium spp was also frequently observed in patients with UC . In our patient cohort, we found that B fragilis was more enriched in patients with CD than in patients with UC, but its presence was not associated with active disease or relapse. This may be explained by the interindividual variation in B fragilis levels observed in our population, in which the pathogen either could not be detected at all in a few patients or was detected at high levels (l07 copies/g feces) in others. Therefore, this finding also supports the notion that the composition of the human gut microbiome is influenced by geographic and ethnic factors.,54Swidsinski et alE coli is increased in patients with CD,55–59 and CRC,,60 and to a lesser extent in those with UC.,32,61 Prorok-Hamon et al found that IBD and CRC share in common a colonic mucosal E coli that expresses genes relevant to pathogenic processes, including M-cell translocation, angiogenesis, and genotoxicity. In our study, we did not detect significant differences in the total number of adherent E coli between IBD patients and controls or between CD and UC. This inconsistency may be due in part to the method by which E coli was quantified; the aforementioned studies were performed by using intestinal biopsies, which yield higher numbers of intestinal organisms that associate with the mucosal surface and harbor properties that influence the host.It has been previously shown that mucosa-associated Fusobacterium spp and E faecalis was prominent (80.85%) in UC whereas the combination of B fragilis and E faecalis was prominent (65.08%) in CD. These findings support the notion that there may not be a particular single bacterium responsible for the progression of diseases such as IBD and CRC. On the contrary, it could be that disease progression is determined by the interaction of a variety of coexisting bacteria. Indeed, studies of gut microbiota with the 16S rRNA gene sequencing method have suggested that IBD is associated with reduced biodiversity, decreased abundance of several taxa in the Firmicutes phylum, and increased abundance of Gammaproteobacteria.,62In our further analysis of different combinations of bacterial colonization/infection, we found that the combination of Fusobacterium spp or E faecalis causes IBD or represents a consequence of disease must be investigated in future studies. If a causative link is proven, antibiotics or vaccines may be used as potential therapies to treat or prevent IBD. Second, the sample size of the healthy control group was rather small. In addition, due to the lack of follow-up data, we could not evaluate any associations between these bacteria and a longer time-to-relapse. Furthermore, it is plausible that the presence of the pathogens examined in fecal samples may not accurately reflect the microbiome dynamics in the actual gut. Indeed, adherent bacteria may exert greater effects on gene expression in colon mucosal cells than transient bacteria that are flushed in fecal samples. Additional studies are needed to determine the mechanisms by which E faecalis, Fusobacterium spp, and B fragilis contribute to pathogenesis, infiltrate the gastrointestinal tract during chronic inflammation, and confer resistance to therapy. Finally, larger studies encompassing stool and colon tissue samples across different stages of IBD development are required to identify and establish strong bacterial markers of IBD.There are some limitations to our study. First, the implementation of an observational study design cannot untangle the causal relationship between the gut microbiome and IBD. Samples were collected from patients already diagnosed with IBD and therefore, whether infection with The authors thank National Clinical Key Institute Foundation of the Chinese Health and Family Planning Ministry (Grant No. 2013-544), the National Natural Science Foundation of China (81372633), and Guangzhou Medical and Technology Project (2014A011010041) for the support.


P < 0·001). VFR travel is an important contributor to imported disease in Australia. Communicable disease control strategies targeting these travellers, such as targeted health promotion, are likely to impact importation of these travel-related infections.Immigrants and their children who return to their country of origin to visit friends and relatives (VFR) are at increased risk of acquiring infectious diseases compared to other travellers. VFR travel is an important disease control issue, as one quarter of Australia's population are foreign-born and one quarter of departing Australian international travellers are visiting friends and relatives. We conducted a 1-year prospective enhanced surveillance study in New South Wales and Victoria, Australia to determine the contribution of VFR travel to notifiable diseases associated with travel, including typhoid, paratyphoid, measles, hepatitis A, hepatitis E, malaria and chikungunya. Additional data on characteristics of international travel were collected. Recent international travel was reported by 180/222 (81%) enhanced surveillance cases, including all malaria, chikungunya and paratyphoid cases. The majority of cases who acquired infections during travel were immigrant Australians  or their Australian-born children . VFR travel was reported by 117 (65%) travel-associated cases, highest for typhoid . Cases of children (aged <18 years) (86%) were more frequently VFR travellers compared to adult travellers (57%,  Travel is a major pathway for the spread of infections globally, including diseases which constitute a public health emergency of international concern, and international travellers are an important source of infectious diseases in countries with robust national disease control systems and low disease incidence, such as Australia. When travelling from developed to less developed countries, the risk of infectious disease is greater in those travelling to visit friends and relatives (VFR) in their country of origin compared to those travelling for other purposes , 2. Of rGlobally, VFR travellers comprise about one-quarter of international travel episodes and this is forecast to increase . Of the Prospective enhanced surveillance of newly notified cases of typhoid, paratyphoid, measles, hepatitis A, hepatitis E, chikungunya and malaria was conducted in the states of NSW and Victoria from February 2013 to January 2014, inclusive. NSW and Victoria comprise 57% of the Australian population  and 65% Australia has a national notifiable disease surveillance system (NNDSS). Surveillance is the responsibility of each State and Territory and standard national case definitions  are usedEligible participants were confirmed cases of the selected diseases in Australian residents, including temporary residents, notified to the included jurisdictions during the study period. Arriving immigrants and overseas temporary visitors were excluded as their travel plans were not made in Australia and contact details of temporary visitors were not available. During routine follow-up of notified cases of hepatitis A, hepatitis E, typhoid, paratyphoid and measles (and chikungunya for Victoria only), public health surveillance officers sought permission from the case, or the case's parent/guardian, for study investigators to contact them by telephone to administer an enhanced surveillance questionnaire. On notification of malaria (and chikungunya in NSW), in which routine follow-up is not performed, public health surveillance officers provided details of the notifying medical practitioner to study investigators, who then sought permission to contact their patient.χ2 test and linear variables were analysed using independent sample t test for differences in mean age or Mann–Whitney U and Kruskal–Wallis tests for differences in median trip duration. P values of <0·05 were considered significant. This study was approved by the NSW Population & Health Services Research Ethics Committee (2012/04/382).Study investigators contacted participants or the parent/guardian of cases aged <18 years. Verbal informed consent was obtained from participants prior to administering the questionnaire. The enhanced surveillance questionnaire included details of any international travel within the incubation period, reason for travel and length of stay. Reason for travel was collected as a self-reported response as well as a list of possible other reasons for travel. For the purposes of this study, Australian residents born outside Australia were termed immigrants. If one or both parents were born outside Australia, the participants were termed Australian-born children of immigrants. We defined a ‘VFR traveller’ as those participants who self-reported visiting friends or relatives as a reason for travel, as per the capture of reason for travel on immigration overseas arrival and departure cards . GeograpP = 0·34) or gender (P = 0·90). While a similar proportion were immigrants (P = 0·9), data were missing on country of birth for 117 notified cases (18·5%).Between February 2013 and January 2014, 634 confirmed cases of the included diseases were notified to NSW Health and the Victorian Department of Health. Of notified cases, 194 (30·6%) were aged 0–19 years, and 285 (45·0%) were female. Of the notified cases, 220 (34·7%) were Australian-born, 297 (46·8%) were born in a country other than Australia and 117 (18·5%) had no country of birth recorded. Of the overseas-born notified cases, 108 (36·4%) were Indian-born, the most common country of birth after Australia for all included diseases except measles . Of the s.d. = 16·2) compared to other diseases .Of the 222 participants who completed the enhanced surveillance, 99 (45%) were female, with a median age of 26·5 years (range 0–80 years), including 77 (35%) children aged <18 years. The proportion of children aged <18 years was highest for hepatitis A , typhoid  and measles . Only two cases of malaria (8%) and no cases of chikungunya occurred in children. The mean age of cases of vaccine-preventable diseases  was lower  cases were Australian citizens or permanent residents, six were international students, nine temporary residents (work or family visas) and four New Zealand citizens residing in Australia. One hundred and five (47·3%) cases were immigrants, with 89 (85%) originating from low- or middle-income countries, including 40 (38%) born in India. No other country of birth contributed more than seven cases. Of the immigrant cases, 25 (24%) had migrated to Australia <5 years previously, with 66 (64%) migrating within the last 10 years. Of the 117 Australian-born cases, 62 (53%) had immigrant parents, including 14 (23%) with one parent born in Australia and 49 (79%) with at least one parent originating from a low- or middle-income country. Lebanon  and Pakistan  were the most common countries of parents’ birth of these Australian-born cases. Demographic characteristics by disease are shown in P < 0·001). Travel histories by disease are shown in A history of recent international travel was reported by 180 (81%) cases, including all cases of malaria, chikungunya and paratyphoid. There were three cases of typhoid in people with no recent travel – two carriers, and one secondary case from a carrier. Of the 19 cases of hepatitis A acquired in Australia, seven (37%) were contacts of an Australian-born child with immigrant parents. Immigrant cases  were more likely to have a history of recent travel than Australian-born cases . Of the paediatric cases, all hepatitis E, malaria and typhoid cases were VFR travellers and all but one hepatitis A and paratyphoid cases.Of the 180 cases with a history of recent travel, 117 (65%) were travelling for the purpose of VFR. Reasons for travel by country of birth and parents’ country of birth are shown in vs. 16 days, P < 0·001) compared to those travelling for other purposes. Differences in trip duration by disease and migration status are shown in Those travelling to visit friends and relatives had significantly longer trip duration  . States For the diseases included in this study, South Asia was the most common travel region and most common region of origin for immigrants and their Australian-born children, reflecting the global epidemiology of the included diseases and the large population of South Asian immigrants in Australia. One third of Australia's immigrant population are born in countries in Asia, including 9·4% from South Asia, with India the fourth most common country of birth after the UK, New Zealand and China . India wPlasmodium falciparum cases as a proportion of total imported malaria in Australia [Just over half of malaria (54%) and 45% of chikungunya cases were VFR travellers. Australian notification data for these vector-borne diseases have not previously been reported by reason for travel, but other developed countries show a high proportion of malaria cases , 33, 34 ustralia  and New ustralia  have preustralia –37, resuustralia  of ethniChildren, either travelling with immigrant parents or immigrants themselves, were over-represented, particularly for vaccine-preventable diseases, and represented 35% of enhanced surveillance cases. Very little research focuses on paediatric VFR travellers, despite data indicating an increased risk of several travel-associated infections and a greater likelihood of VFR travel. Our data show cases with vaccine-preventable diseases were younger than those with non-vaccine-preventable diseases. Age and vaccination status are important considerations and may contribute to the high proportion of children in our study. Several studies have shown an inverse association between VFR travel and age , 39, 40 There are some limitations to the study. We excluded newly arrived visitors and immigrants from the enhanced surveillance, who comprised over 10% of the notified cases. While the aim was to capture travel characteristics of departing Australians, we may have missed important characteristics of cases of imported disease in visitor arrivals and disease in immigrants on arrival to Australia. Further, notified cases during the study period could opt out of the enhanced surveillance, with 35% of notified cases completing the enhanced surveillance. While there was no difference in the proportion of total and sample cases by age or gender, we may have underestimated the proportion of notified cases who were immigrants, with 18% of notified cases with an unknown country of birth. Response rates were also lower for malaria and chikungunya notifications due to the additional steps required to contact cases not routinely followed up by public health officers. Further, we included the selected travel-associated diseases due to their high likelihood of notification. However, they may not be representative of all travel-associated diseases. For example, dengue was not included in the study as the large number of notified cases (1842 in 2013 ) was beyCoupled with international travel, disparities in the prevalence of infectious diseases between low-burden countries such as Australia and high-burden countries, presents a challenge to national infectious disease control efforts. VFR travellers are a high-risk group for travel-related infectious diseases, and we have described specific risk groups and countries of acquisition in this study, which may assist in the development of more targeted primary prevention strategies. Disease prevention in this group of international travellers will have implications for the importation of infectious diseases into Australia. The expansion of national notification data to include routine collection of travel history, reason for travel as well as indicators of cultural and linguistic data including country of birth, parents’ country of birth and language spoken is important in monitoring high-risk groups in the importation of infectious diseases into Australia.


Poly(glycerol sebacate) (PGS) is an elastomeric polymer which is attracting increasing interest for biomedical applications, including cartilage regeneration. However, its limited mechanical properties and possible negative effects of its degradation byproducts restrict PGS for in vivo application. In this study, a novel PGS–bioactive glass fiber (F18)-reinforced composite was developed and characterized. PGS-based reinforced scaffolds were fabricated via salt leaching and characterized regarding their mechanical properties, degradation, and bioactivity in contact with simulated body fluid. Results indicated that the incorporation of silicate-based bioactive glass fibers could double the composite tensile strength, tailor the polymer degradability, and improve the scaffold bioactivity. Cartilage is an avascular, aneural, and low-metabolic-activity tissue that presents very limited regenerative potential ,2. ThereDamage in cartilage is normally managed by the use of analgesics and physical therapy; however, in severe cases, surgery is required, which leads to immediate to long-term complications . DevelopRegarding these characteristics, poly(glycerol sebacate) (PGS) is a biocompatible, biodegradable, elastomeric polymer, which has shown great potential as a scaffold material for soft and hard tissue engineering applications .PGS is a synthetic polymer, firstly reported in the context of tissue engineering in 2002 . This elIn any tissue engineering strategy, it is important to tailor the rate of degradation of the biomaterial to match the regenerative rate of the engineered tissue. PGS has been reported to undergo fast degradation in vivo, being completely absorbed within 6 weeks . It has Recently, biocomposites reinforced with glass fibers have drawn considerable scientific attention due to the positive results achieved in terms of mechanical strength . HoweverThe obtained scaffolds had a medium pore size of 475 µm (±100 µm) with few pores reaching up to 1 mm. It is noticeable that a highly porous structure was developed. Based on image analysis , the obtained scaffolds reached a mean porosity not lower than 60 vol %, with reasonable pore interconnectivity despite the used technique . The presence of the fibers is not perceptible since they are totally embedded in the polymer matrix, indeed acting as a reinforcement agent in the scaffold structure.t-test was applied.The variation of pH in the ISO degradation solution over time can be observed in Ion-selective tests  showed t−1 (C=O stretch) and 1164 cm−1 (C–O) [Attenuated total reflectance Fourier-transform infrared spectroscopy (ATR-FTIR) confirmed the formation of ester bonds in PGS , as reve−1 (C–O) ,22.2) absorption peaks at around 2925 cm−1 and 2855 cm−1 [−1, linked to hydrogen-bonded hydroxyl groups [PGS samples also exhibited the two characteristic alkane groups (–CH855 cm−1  and the l groups .As the soaking time in simulated body fluid (SBF) solution increased, the intensity of these PGS characteristic peaks decreased. This is an expected phenomenon linked to PGS degradation and hydrolysis, a trend reported in the literature ,24.−1. These peaks are more evident for the PGS + 10% BGF due to the greater amount of bioactive glass. For both composite samples, it is noticeable that these peaks lose intensity as the time of experimentation increased. In −1, with the appearance of the peak at 1700 cm−1—which is linked to PGS degradation—takes longer periods to occur when the bioactive glass fibers are added and are less intense, mainly for the PGS + 10% fibers samples. In these FTIR spectra, the formation of the hydroxycarbonate apatite (HCA) layer is not clearly detected; to verify the formation of this bioactive phase on the surface of the porous scaffolds, SEM images were taken. ATR-FTIR spectra for the PGS + BGF scaffolds are presented in As can be observed, after 2 days in SBF, the HCA layer cannot be easily detected, but after 14 days of incubation this phase precipitated on both fiber concentrations biocomposite scaffolds.Typical tensile stress–strain curves for pure PGS porous scaffolds and for PGS + 5% and PGS + 10% BGF composite scaffolds are shown in t-test showed that the p value was <0.05 when the porous PGS group was compared to all other groups. On the other hand, between PGS + 5% and PGS + 10%, no significant difference was observed.A Tissue engineering presents an alternative approach to repair and regenerate damaged tissues, eliminating the need for permanent implants. Thus, it is highly promising to tackle numerous medical needs. However, many challenges remain, and the pursuit of new, responsive, and appropriate biomaterials is continually growing .Over the past years, numerous tissue-engineering strategies have been considered for cartilage tissue regeneration, using both naturally occurring and artificial polymeric biomaterials. Several studies have shown the potential of PGS in soft tissue regeneration ,6,7,8,9 PGS is a biocompatible, biodegradable, and mechanically stable elastomeric biopolymer that can be synthetized by many different routes, aiming to tailor its mechanical properties to match those of cartilage tissue . As a hiAiming to achieve a more bioactive and mechanically suitable biomaterial for tissue regeneration, several researchers incorporated bioactive glass into PGS ,18,26,28The developed scaffolds exhibited a well-developed porosity obtained by the salt-leaching technique, with pore sizes spanning over a very wide range (from few microns to hundreds of microns), with no sign of agglomeration of the glass fibers. Regarding PGS degradation, it is currently well established that this polymer undergoes surface degradation, the main mechanism being the cleavage of the ester linkages ,4,5. As p < 0.05), indicating that acidification due to the polymer degradation had occurred. This phenomenon is widely described in literature [During the degradation tests, pH changes over time were monitored for all samples . The encterature ,18,28 anterature .In our experiments using ISO degradation solution, after 5 days the pH slightly increased again, which could be attributed to the fact that the bioactive glass fibers were on the interior of the samples and totally surrounded by the PGS matrix, so that the fiber dissolution rate mostly depended on the previous degradation of the PGS matrix. When PGS suffered hydrolysis, it opened pathways for the interaction of the glass fibers with the solution, leading to an increase in the alkaline ions concentration in the medium, as can be observed in −1 appeared with the addition of the bioactive glass fibers into PGS. According to Liang et al. [Through ATR-FTIR analysis, after SBF tests, it was possible to detect that two new peaks at 1545 and 1574 cmg et al.  and Cheng et al. , these pg et al. ,28.−1), linked to the polymer’s degradation, starts to occur later for the reinforced samples, mainly for the PGS + 10% BGF composite. This phenomenon is likely related to the formation of these metallic carboxylates groups during fabrication of the biocomposites—they consume PGS carboxylic groups, thus reducing the level of esterification in the PGS matrix. These reactions confirm the improvement of the mechanical and degradation properties of PGS by incorporating BGF, a relevant feature for a biomaterial aimed at cartilage regeneration, since PGS exhibits an accelerated rate of degradation in vivo [The FTIR spectra also indicate that the breakdown of the crosslinks in the PGS . The viscosity was then adjusted (by tuning the temperature) to be around 102 to 103 Pa·s, and then the glass slowly drained from the Pt crucible’s nozzles. Continuous fibers were pulled mechanically with a controlled velocity for diameter control. The obtained glass fibers had a mean diameter of approximately 20 µm (±5.1 µm).For manufacturing the bioactive glass fibers, a brand new highly bioactive glass formulation, denominated F18, was used. The manufacture process of this glass is described in detail elsewhere ,34,35. BFor the PGS synthesis, 14.6 mL of glycerol  and 40.4 g of sebacic acid  were used. The reagents were stirred at 120 °C for 48 h in a round-bottom three-joint glass flask with a continued nitrogen flux.The fiber-reinforced PGS scaffolds were prepared by the salt-leaching process with the addition of 0.5 g or 1 g of chopped bioactive glass fibers into 10 g of PGS . The fibers had mean length of approximately 1 mm and the mixture was kept stirring for 5 min at 70 °C before casting. Then, the viscous solutions were poured in Teflon plaques of 6 cm of diameter, containing 20 g of NaCl (with a particle size range of 325–500 µm) and placed in a vacuum furnace for 4 days at 140 °C ± 1 °C. After this crosslinking process, discs of 5 mm in thickness were obtained, and the NaCl particles were solubilized in deionized water for 6 h.Stereomicroscopy  and scanning electron microscopy (SEM)  observations were conducted to evaluate the morphology, interaction and dispersion of the bioactive glass fibers in the PGS matrix.To analyze mass and pH changes over time, degradation tests were performed using a modified ISO standard 10993-14 . A TRIS 3 were soaked in 25 mL of SBF-K9 solution, prepared according to the procedure proposed by Kokubo et al. [−1 . SEM images were used to analyze the changes in the glass fibers and in the PGS matrix morphology at the different periods of incubation. X-ray diffraction (XRD) tests  were also conducted to identify any crystalline phase precipitated on the samples surface after the immersion in SBF solution.To evaluate the new composites’ bioactivity, which is related to the formation of hydroxyapatite on the surface of the samples, scaffolds with 10 × 5 × 5 mmo et al. , and incAll composites’ tensile strength was analyzed using a uniaxial testing machine  with a 50 kN load cell at a cross-head speed of 5 mm/min at ambient conditions. All samples were prepared in a prismatic shape with dimensions of 40 mm × 5 mm with a thickness of approximately 2 mm. At least six samples were tested for each type of composite and the average value was reported with standard deviation (±SD) .In this study, we developed bioactive glass (F18) fiber-reinforced PGS biocomposites. The incorporation of the bioactive phase into the PGS porous matrix allowed the manufacture of a more reactive biocomposite with better mechanical properties and controlled degradation rate when compared with those of the polymer alone. Additionally, the presence of the bioactive fibers could effectively counteract the acidity caused by the degradation of PGS in vitro. These preliminary tests have demonstrated promising results for the application of this novel bioactive composite containing glass fibers as a new biomaterial for soft tissue engineering, for example, cartilage regeneration.


Although experimental studies have shown that adiponectin and leptin modulate glucose tolerance and insulin resistance, it remains unclear whether these adipocytokines exert similar effects in general human populations. We evaluated the associations of serum adiponectin and leptin with β-cell function and insulin resistance in a population with low obesity prevalence. A cross-sectional study of 783 rural residents, aged 25–74 years, recruited in Ningxia, China was conducted during 2008–2012. β-cell function and insulin resistance were estimated using the Homeostasis Model Assessment. Serum adiponectin and leptin were measured with ELISA. Serum adiponectin concentrations (mean ± SD) were highest in subjects with normal glucose tolerance (36.65 ± 61.13 μg/ml), intermediate in those with impaired fasting glucose (25.92 ± 34.48 μg/ml), and lowest in those with diabetes (15.08 ± 12.14 μg/ml) (p = 0.001). A similar pattern of differences was found for β-cell function, whereas opposite results were observed for insulin resistance and blood glucose. After adjustment for confounders including metabolic syndrome components, serum adiponectin (μg/ml) was inversely associated with β-cell function (%β) [β (95% CI): -7.57 ] and insulin resistance (100/%S) [β (95% CI): -0.21 ]. A significant inverse association also existed between serum leptin and β-cell function, but serum leptin was not significantly associated with insulin resistance. The present study suggests that adiponectin and leptin play a role in the development of insulin resistance and diabetes independent of metabolic syndrome. The global prevalence of overweight, obesity, and diabetes has reached epidemic proportions and thus poses a tremendous public health problem , 2. The A substantial body of epidemiologic and experimental evidence has revealed that overweight and obesity are associated with an elevated risk of insulin resistance and diabetes , 7. InsuAdipocytokines (e.g. adiponectin and leptin) are excreted by adipose tissue and are involved in the homeostasis of energy and regulation of glucose and lipid metabolism . AdiponeA cross-sectional study was carried out from 2008 to 2012 in three counties or administrative equivalents  in Ningxia Hui Autonomous Region of China. A total of six villages were recruited using stratified cluster sampling according to economic development levels, with two villages (one for Han ethnicity and one for Hui ethnicity) selected from each of the three counties considered. During the study period, 4614 subjects, aged 24–75 years, were enrolled to the study. Pregnant or breastfeeding women and subjects with severe chronic diseases were excluded from the study. Also excluded were subjects who had acute respiratory infection or chronic viral infection and those who underwent surgery in the preceding week of the study recruitment. Of the 4614 subjects who were eligible for the present study, 2393 donated a blood sample to the study. Of the 2393 subjects, 1000 were selected by using mechanical sampling (k = 1) for measuring selected biochemical indicators due to budget constraints. Of the 1000 subjects, serum adipocytokines were determined among 800 subjects due to the depletion of serum samples for the remaining 200 subjects. Of the 800 subjects, six had serum levels of glucose or insulin that were not within the range of clinically plausible values used for calculating the Homeostasis Model Assessment (HOMA) parameters, and 11 subjects were lack of data on insulin concentrations that were not measured due to insufficient amounts of serum samples. After excluding those 17 subjects, valid and complete data from 783 subjects were available for our data analysis. The present study was approved by the Medical Ethics Review Committee of Ningxia Medical University and written informed consent was obtained from all study subjects.Subjects were interviewed by trained research assistants with a validated questionnaire that solicits information on age, sex, ethnicity, education, cigarette smoking, alcohol intake, history of disease, etc. The questionnaire was administered by the research assistants, and the completed questionnaire was then checked for its accuracy and validity at the end of the interview.2). Blood pressure was measured for three times after subjects had rested for at least 30 minutes, and the three readings were averaged and used in data analysis.Body height and waist circumference were measured with a portable ruler (accurate to within 0.1 cm) and body weight was quantified with a weight scale (accurate to within 0.1 kg). Body mass index (BMI) was calculated as weight (kg)/height , then delivered to Ningxia Medical University, and kept in a freezer (-80°C) until time of analysis. Blood glucose was determined by One Touch Ultra 2  immediately after blood was drawn. Serum insulin was measured by enzyme-linked immune chemiluminescence method. Serum high-density lipoprotein (HDL) cholesterol, total cholesterol, and triglycerides were quantified using an automatic biochemical analyzer . Serum low-density lipoprotein (LDL) cholesterol was calculated with the Friedewald formula . Serum ahttp://www.dtu.ox.ac.uk/homacalculator/). As HOMA-IR is simply the reciprocal of HOMA-S, only the former was analyzed in the present study. All subjects were divided into three groups defined by the guidelines of the American Diabetic Association: normal glucose tolerance (fasting blood glucose: <5.6 mmol/L), impaired fasting glucose (fasting blood glucose: 5.6–6.9 mmol/L), and diabetes . Differences in demographics, lifestyle, anthropometrics, blood lipids, serum adipocytokines, and HOMA parameters were compared among the three groups using analysis of variance for continuous variables and Chi-square test for categorical variables. The purpose of these comparisons is to investigate whether there are statistically significant differences in these factors among subjects with various degrees of glucose tolerance.β-cell function  and insulin resistance  were calculated from fasting blood glucose and serum insulin with the HOMA-2 calculator  and 95% confidence interval (CI) for the higher levels (>median) of β-cell function or insulin resistance were calculated for subjects who were in the second, third, and fourth quartile of each of these two parameters, compared with those who were in the respective first (lowest) quartile. Linear trend across quartiles of adiponectin and leptin was evaluated using the median in each quartile to create an ordinal variable and entering it into regression models. As the study population is composed of subjects from two ethnicities (Han and Hui), potential interactions of ethnicity with adiponectin and leptin on β-cell function and insulin resistance were tested. As none of the interaction terms tested was statistically significant, ethnicity-specific analysis was not performed. The SPSS  was used for statistical analyses. A p-value of <0.05 was considered statistically significant.The characteristics of study subjects were compared among the groups of normal glucose tolerance (n = 376), impaired fasting glucose (n = 362), and diabetes (n = 45) in Differences in serum adipocytokines, blood glucose, serum insulin, β-cell function, and insulin resistance among the three groups were shown in The results of the logistic regression analysis for the risk of having the higher level (≥median) of each of the two HOMA parameters examined in relation to adipocytokines were presented in The major findings of the present study were that there was a significant gradient decrease in serum concentrations of adiponectin across the three groups of subjects with different levels of glycemic tolerance . Both serum adiponectin and leptin were inversely associated with β-cell function, whereas only serum adiponectin was inversely associated with insulin resistance. Of note, the inverse associations of serum adipocytokines examined with β-cell function were no longer significant after insulin resistance was further adjusted in the multiple linear regression analysis.Our observation that circulating concentrations of adiponectin were lower in the subjects who were pre-diabetic (i.e. impaired fasting glucose) or diabetic than in the subjects who maintained normal glucose tolerance was generally consistent with the results of previous studies , 24–28. A meta-analysis of 13 prospective cohort studies published in 2009 showed an inverse monotonic association between adiponectin levels and the risk of type 2 diabetes [relative risk (95% CI): 0.72 (0.67–0.78) per 1–log μg/mL increment in adiponectin levels], although most of those studies were conducted in Western populations with a high prevalence of obesity . SubsequAnimal and experimental studies have offered several lines of biological plausibility for the associations of circulating adiponectin with insulin resistance and diabetes. It appears that decreased adiponectin concentrations increase the risk of developing insulin resistance and ensuing diabetes. Adiponectin knockout mice developed hepatic but not peripheral insulin resistance, which was evaluated with the euglycemic insulin clamp technique . AdiponeMounting evidence suggests that leptin is implicated in glycemic tolerance independent of its effect on energy balance , 33. It The associations of leptin levels with insulin resistance and diabetes are overall inconsistent as the positive, inverse, and null associations have been reported previously , 26, 33.There are some advantages in the present study. We investigated the associations of circulating adipocytokines with β-cell function and insulin resistance among 783 normal, prediabetic, and diabetic subjects, a sample size that is larger than that of most previous cross-sectional studies , 30, 33.s or r = 0.62–0.90) and insulin sensitivity (Rs or r = 0.58–0.88) derived from the HOMA model and from the euglycemic clamp [The present study is subject to several weaknesses. Blood glucose levels and serum concentrations of insulin, adiponectin, and leptin were measured only once. Therefore, it is possible that some subjects might have been misclassified with regard to the usual levels of these biomarkers due to their potential daily variations, which could lead to attenuated estimates of the true associations. As insulin secretion is pulsatile, insulin concentrations measured with a single blood sample may vary with the time of sample collection. However, a study has showed acceptable intra-subject coefficients of variation for HOMA parameters (7.7% for β-cell function and 10.3% for insulin sensitivity) . In our ic clamp . Of the The data analyzed were collected from a cross-sectional study, which makes it possible for us to draw any causal inference on the associations of serum adipocytokines with β-cell function and insulin resistance. Women generally have higher circulating concentrations of adiponectin than men . This seIn summary, the present study revealed that serum concentrations of adiponectin significantly decreased across the spectrum of glycemic tolerance from normal glucose tolerance to impaired glucose tolerance to diabetics in a rural Chinese population. Both serum levels of adiponectin and leptin were inversely associated with β-cell function, but the inverse association with insulin resistance was found only for serum adiponectin. These effects of adipocytokines overall persisted after adjustment for the components of metabolic syndrome. It should be pointed out that serum adiponectin and leptin were no longer significantly associated with β-cell function when insulin resistance was additionally controlled for in the multiple linear regression analysis. The findings of the present study are expected to lead to an improved understanding of the role of adiponectin and leptin in the etiology, pathogenesis, and prevention of prediabetics and diabetics if they can be replicated in other populations with low prevalence of overweight and obesity.S1 File(XLS)Click here for additional data file.


The results of this study highlight that human impact is confined to locations that are utilized as campsites and that exploration leaves little microbial trails. Furthermore, we uncovered a highly specialized microbiome, which is perfectly adapted to survive and thrive in an environment with low nutrient availability.The bacterial diversity in the Su Bentu Cave in Sardinia was investigated by means of 16S rRNA gene-based analysis. This 15 km long cave, carved in Jurassic limestone, hosts a variety of calcite speleothems, and a long succession of subterranean lakes with mixed granite and carbonate sands. The lower level is occasionally flooded by a rising groundwater level, but with only scarce input of organic remains . On the quiet cave pools there are visible calcite rafts, whereas walls are locally coated with manganese deposits. In the drier upper levels, where organic input is much more subdued, moonmilk—a hydrated calcium-magnesium carbonate speleothem—can be found. Relative humidity approaches 100% and the measured mean annual cave air temperature is 14.8°C. Samples were obtained in 2014 from calcite rafts, moonmilk, manganese oxide deposits and soil (limestone and granite grains). Microclimatic conditions in the cave near the sampling sites, sample properties, physico-chemical parameters of water, and sediment composition were determined. The microbial community of this system is predominately composed of the phyla Proteobacteria, Actinobacteria, Acidobacteria, Nitrospirae, and Firmicutes. Sampling sites near the entrance of the cave and in close proximity of the underground campsite–located 500 meters deep into the cave—revealed the highest diversity as well as the highest number of human associated microorganisms. Two samples obtained in very close proximity of each other near the campsite, indicate that the human impact is localized and is not distributed freely within the system. Analysis of the abundance of bacterial and archaeal  Microorganisms inhabit a diverse number of extreme environments such as hot springs, glacial lakes and subterranean systems –4. Due t6 cells/g of rock [As most caves are formed in carbonated rocks, the majority of microbiological investigations carried out in caves have been described in such systems –12. Some of rock . Studies of rock  or the k of rock . Further of rock , which h of rock ), karst  of rock  and the  of rock .2 using the 3-hydroxypropionate/4-hydroxybutyrate (HP/HB) cycle [Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, has been suggested to play a critical role in the global biogeochemical nitrogen cycle since the oxygenation of Earth . For cloB) cycle . They haB) cycle , soils [B) cycle , freshwaB) cycle  and subtB) cycle , 28.The impact of human interference on the microbial composition of subterranean systems has been an issue for many decades. Several karst systems are open to the public, e.g. the Naracoorte cave in Australia or the Lascaux Cave in France, and the anthropogenic influence of frequently visiting such environments has been often investigated , 30 OtheFor this study we investigated the microbial diversity of the Su Bentu Cave, a karst system located in the north-western part of Supramonte karst massif . The cave comprises over 15 km explored passages and most of the cave is not subjected to flooding, creating a typical oligotrophic environment. This cavity is not a show cave; however, several local and international speleologists frequent this system throughout the year. Within the cave, one spot is regularly used as campsite , which serves as a test-bed to investigate the human impact of short-term settlement on the present microbial diversity.Besides the naturally occurring biosphere, this study also focuses on the potential human impact occurrence on the microbiome within this subterranean environment and the presence, abundance and distribution of ammonia-oxidizing bacteria and archaea. To deepen our understanding of the microbial interactions within subterranean environments, we elucidated the microbial diversity, as well as the impact of human exploration on the native system of the Su Bentu Cave in Sardinia, Italy.2, topographically elevated over a Paleozoic crystalline basement. With its biodiversity, this region of mountain wilderness preserves small areas of oak and juniper forest surrounded by wide degraded shrubland. This plant community is constituted by sclerophyll species over a very thin soil and by mountain garigue on bare rock pavement [2 and more than 200 meters underneath the surface. They are organized in two main branches: the Lakes Branch, a seasonally flooded underground canyon where an ephemeral stream fed by the phreatic passages at 105 meters asl flows at a lower cave level, and the 4th Wind Branch, a network of dry looping tunnels of considerable dimensions interconnected through large chambers where dripping water creates emerald pools in well-decorate passages. Both branches converge close to the narrow passage called 4th Wind, at a distance of 1,000 meters from the entrance, creating the huge room of Sala Piredda and the “Grande Cengia”. The whole cave system is connected to Su Gologone spring, the major of Supramonte aquifer, located at 104 m asl in the northern edge of the karst massif. Surface runoff in the area is typically absent. The present day recharge of the cave tributaries occurs predominantly during rainfall events by direct infiltration and/or by the rising water table. Its hydrological catchment comprises carbonate rocks, mainly limestones, while there is strong evidence of past allogenic water input from the Paleozoic basement, now at a lower elevation, constituted by weathered granite and metamorphic rocks [Su Bentu Cave is located in the Supramonte karst massif , a Mesozoic carbonate plateau, 9 km wide and 20 km long corresponding to an area of 170 kmpavement The climapavement . The Su pavement . With itic rocks .3of moonmilk (SO3). The limestone cave wall was scraped off at the location “Shaft” (SO4), two samples from manganese oxide were taken at “Water Tower”, one was scraped into a 50 mL falcon tube (S05), the other sample adjacent by swiping a flocked swap over the approx. 1 cm3of the manganese deposit (SO6) and a sediment sample was taken from “Ball Room” (SO7). Representative sampling sites are shown in The samples used in this analysis were collected in 2014 at 5 different remote areas of Su Bentu Cave, namely Ball Room, Shaft, and Water Tower, that only occasionally have been impacted by caver activity, as well as Piredda Hall which is close to a frequently used campsite during explorations and Chaos, a site close to the entrance were all explores have to pass to get into the cave. At these locations the following samples were taken: loose, solid calcite raft samples from “Chaos” (SO1), moonmilk samples from “Piredda Hall” (SO2 and SO3) by aseptically scraping material in a 50 mL falcon tube (SO2) and an additional sample 5 cm adjacent to the first sample by swiping a flocked swap over the approx. 1 cmChaos (SO1) is the most downstream part of the lower Lake’s level and connects through a sump with the Sa Oche cave entrance. It can be accessed descending a series of ropes down to 40 meters below the Witch’s Hat conduit and the main upper cave level. The sample was taken close to the sump area, approximately 5 meters above water level at the time of sampling. The sample regarded the calcite rafts, which were lying on the rocky floor of the cave together with brown muddy sediments. These calcite rafts originally were floating flakes of calcium carbonate formed by oversaturation of the standing water body caused by evaporation of the water. The lowering of the water level caused these rafts to be abandoned on the cave floor. The fine sediments that accompany these white rafts are residual clays mostly of local origin (insoluble remains of limestone dissolution).th Wind branch, and is characterized by the confluence of the air masses flowing though these separate branches. The mixing of these air masses causes formation of underground clouds, where condensation occurs on the upper parts of the cave voids, while evaporation predominates in its lower parts. The over 20 meter high cave roof is characterized by cupola-like and ceiling channel-like morphologies, and lacks any type of speleothem. The lower part hosts flowstones, gours, and some other vadose speleothems. The microbiological samples have been taken along the walls of the cave where white toothpaste-like soft deposits are growing (known as moonmilk). Although this area is frequently visited by cavers, the sampling spot was out of the main path.Piredda Hall (SO2 and SO3) is a very wide cave room located at only less than 100 meters from the main campsite in the cave. This hall forms the junction between the Lakes Branch and the 4The sampling spot “Shaft” (SO4) is located 500 meters deeper into the cave, at the base of a vertical passage, a few meters from Rainbow Lake. This shaft is 15 meters deep and leads into a lower series of galleries that are seasonally flooded by infiltrating waters. Less than 100 meters further into the cave, Baikal Lake is encountered, a small pool that forms a sump during these high water periods. The sampling area is characterized by a floor composed of permanently wet flowstone, together with sands (granite and limestone grains) and some organic material brought in by the infiltration waters.Sampling site “Water Tower” (SO5 and SO6) is located deep into the cave, at the end of the Lakes series. The cave rooms become very large with a sandy floor and a roof up to 80 meters high at some places. This area is flooded seasonally for a couple of days, and the floor is characterized by an admixture of granite and carbonate sands and some organic material. The Water Tower is situated below an area with intense dripping, and a permanent pool is present on a ledge above. Although not frequently used by cavers, the sampling spot is located on the obligate passage point toward the final rooms of the cave. The sampled material occurs as black coating on the cave walls that can be referred to as manganese oxides, the most common black wall crust in caves .The sampling site “Ball Room” (SO7), located 200 meters from “Water Tower”, is characterized by spherical intrasediment concretions now exposed on the cave floor , and a roof only a few meters high. This part of the cave is seasonally flooded during high flow, the water rising from the nearby shaft. When this happens many features indicate the flow to be rather turbulent, creating vortices that have eroded all loose sediments leaving only these hardened parts  on the floor. At the end of these floods water subsides slowly leaving muddy sediments mixed with some organic material. Samples were collected from the cave floor and consisted of limestone sands and muddy sediments.th Wind Branch and Lakes Branch, at three different levels along a 40 meters high vertical profile from the thalweg of the canyon (Great Lake) to the Chessa Camp, and up to the roof of a frequently used campsite . Cave air circulation was measured continuously 100 meters from this last place, between Bell Hall and 4th Wind passage , the second in a lake below campsite, in the lower Lakes Branch. Two hundred and fifty mL samples were collected for major anions  and fundamental metals  respectively. Samples for cation analyses (100 mL in volume) were filtered with a 0.45 μm sterile filter and acidified with 1 mL of concentrated HNO3. The water physical parameters were determined in situ with a portable Hanna HI 991301 probe measuring pH, temperature (T) and electrical conductivity (EC). The range of this probe is between 0.00 and 14.00 for pH , between 0.00 and 20.00 mS/cm for EC  0.00 and 10.00 ppt (g/L) for TDS  and 0.0 to 60.0°C for the temperature . The alkalinity was also determined in situ as bicarbonate ion concentration (HCO3-), by titration with methyl orange and hydrochloric acid. The saturation index (SI) of calcite was computed using Merlak’s algorithm [Two aliquots of water were collected in disposable containers with no headspace for chemical analysis, one at Rainbow Lake in the upper 4lgorithm . Water sth Wind Branch and the Lakes Branch .For chemical analysis, two clastic sediment samples were collected on the cave floors in the 4RNAlater and mixed vigorously. In addition, two flocked swap (MicroRheologics) samples were obtained from moonmilk (SO3) and the manganese oxide deposit (SO6). Samples were stored at ambient temperatures (approx. 14°C) until the end of the expedition and put immediately on ice once the expedition crew left the cave. Samples were transported at 4°C and upon arrival at the laboratory immediately stored at -80°C.Seven samples were taken during cave exploration at the previously described five sampling sites: Approximately 5 g of calcite raft, manganese oxide or moonmilk were sampled with a sterile spoon and filled into a 50 mL falcon tube containing 15 mL of 2O. DNA from flocked swap samples (SO3 and SO6) was extracted using the XS-lysis buffer method as described in detail by Tillett and Neilan [2O. The concentration of extracted DNA was determined with a Nanodrop spectrophotometer at 260 nm. The quality of the extracted DNA was tested by the following PCR setup and protocol. Reactions were performed in 20 μL containing 1 U Platinum Taq polymerase, 1 x polymerase buffer, 3 mM MgCl2, 0.2 mM dNTP’s, and 0.5 μM of PCR primers 515F (5’GTGCCAGCMGCCGCGGTAA’3) and 806R (5’ GGACTACHVGGGTWTCTAAT’3) [www.earthmicrobiome.org) and is described there in detail.DNA from the calcite raft (SO1), moonmilk (SO2), limestone  and manganese deposit (SO6) samples was extracted using the PowerSoil extraction kit (MoBIO) according to the manufacturer’s protocol. Briefly, 0.25 g of soil was employed and DNA was extracted using a combination of bead-beading and lysis buffer. DNA was eluted into a final volume of 50 μL dHd Neilan . DNA wasCTAAT’3) . Amplifi5’GTGCCAGCMG-CCGCGGTAA’3) and 806R (5’ GGACTACHVGGGTWTCTAAT’3) [http://cgenome.net/calypso/) [The community composition and diversity of Archaea and Bacteria in cave samples were studied using amplicon sequencing method: a variable region of 16S rRNA gene, present in Bacteria and Archaea, were amplified with universal PCR primers 515F (CTAAT’3) . The proCTAAT’3)  (SOP accCTAAT’3)  and varialypso/) . SequencamoA genes, quantitative PCR (qPCR) was employed. To identify bacterial amoA genes, primers amoA-1F (5’ GGGGTTTCTACTGGTGGT ‘3) and amoA-2R (5’ CCCCTCKGSAAAGCCTTCTTC ‘3) were used and genes amplified as previously described by Rotthauwe et al. [amoA genes, primers Crenamo1F (5’ AATGGTCTGGCTWAGACGC ‘3) and CrenAmo1R (5’ GACCARGCGGCCATCCA ‘3) were used and amplified as previously described by Könneke et al. [-1) and agarose gel electrophoresis (1% agarose) revealed single amplicons for all samples.To screen for the presence and amount of bacterial and archaeal e et al. . To idene et al. . The qPCth Wind Branch, 2 in cave atmosphere is different at the sampling areas showing values of 4,000 ppm at Piredda Hall in the well-ventilated upper level and 2,680 ppm in the quiet lower level of Ball Room.Relative humidity at each site approaches 100% and the measured mean annual cave air temperature is 14.8°C (±0.18°C). The altitudinal thermal gradient between the sampling sites is 0.05°C/m, with values ranging between 16.0°C at Piredda Hall and 13.9°C at the Water Tower sampling site. Air circulation inside the cave follows a diurnal and seasonal pattern showing a change in direction of the movement of air masses depending mostly on outside temperature. Airflow at the “Wind station”  and total dissolved solid (TDS), and an almost neutral pH . The conth Wind sampling site is dominated by phyllosilicates. It is not surprising that Si ions predominate in the chemical composition. Absolute abundance ranges from 80% for the granite sand to 38% for the muddy clay, respectively. The different silicate minerals are also the major carrier of Al, the second most abundant element. The abundance of Fe is mainly coupled with the occurrence of oxides and hydroxides incorporated in the crystal lattice of clay minerals. The amount of Ca is low compared to most of the cave sediments and the greater part is related to carbonate residues in the clay fraction. The volatile content (LOI) indicates low amount of organic matter in both samples.The bulk chemical analyses of major elements in the sediments of the two main branches (upper and lower) of the cave system is shown in The microbial diversity of the Su Bentu Cave in Sardinia has been investigated at several different sampling locations . Based oTaken together, a total of 37 bacterial and 3 archaeal phyla signatures have been recovered from the different sampling sites. Results indicate that the microbial community  of this cave is predominately composed of the phyla Proteobacteria (43.39%), Actinobacteria (16.21%), Acidobacteria (8.25%), Nitrospirae (7.62%), Firmicutes (7.46%), Chloroflexi (2.91%), Gemmatimonadetes (2.65%), unclassified (2.49%), Planctomycetes (2.45%), and Thaumarchaeota (2.20%) . NotablyThe discovered phyla can be further refined at the class level into β –Proteobacteria (15.38%) being the predominant class of these phyla. This class is followed by γ –Proteobacteria (13.01%), α –Proteobacteria (9.13%), Nitrospira (7.62%), Acidobacteria (7.54%), Actinobacteria (7.15%), Bacilli (7.06%), unclassified (6.30%) and the Thermoleophilia (5.87%) . A complLactobacillus, Propionibacterium, Streptococcus, Bacteroides, Corynebacterium, Staphylococcus, Moraxella, Haemophilus, Prevotella, and Veillonella. The highest amount of human associated microorganisms has been observed in a moonmilk sample (SO2 with 43.93%) obtained near the campsite followed by the sample obtained from a calcite raft near the entrance of the cave (SO1 with 5%). All other sampling points showed a negligible presence (<0.5%) of human associated organisms  was determined as <0.2 mM for all sampling points. Results indicate that the archaeal ammonia-oxidizing gene is significantly more abundant in most of the samples compared to their bacterial counterpart. Low amounts of amoA genes were recovered at SO2, with only bacterial amoA genes present. Due to low amounts of DNA recovered at sampling spot SO3, no analysis of the bacterial and archaeal amoA gene distribution was possible.To investigate the presence/abundance of bacterial and archaeal In this study we investigated the microbiome of the Su Bentu Cave, Sardinia by Illumina MiSeq analysis, focusing on the impact of human exploration on the indigenous microbial community and on the ammonia-oxidizing potential as an energy source.2 in cave atmosphere is evident in the two main cave branches, with lowest values observed in the lower Lakes’ Branch and an increasing concentration in the well-ventilated upper level of Bell Hall room in the 4th Wind Branch, an opposite dynamic respect of the common cave atmosphere with higher CO2 values restricted to places with scarce air circulation [+ and Cl- concentrations slightly increase in the Campo Chessa area with respect to the Lakes Branch as a consequence of active rainwater infiltration observed throughout the year. Moreover, the more likely sulphate source for the Lakes Branch’s sediment is the oxidation of sulfur minerals (pyrite ores) hosted within granite clasts. Finally, the nitrate contamination is in the range of Sardinian precipitations and reaches the groundwater system as seeping water [Subterranean ecosystems are distinguished by a variety of physical  and chemical  parameters. They explain the greatest variance of the chemoautotrophic microorganisms that colonize the subterranean realm . The Su culation . Water sng water . The Su ng water .2 fixation coupled ammonia oxidation process, which likely is the source of primary production in other cave systems [The core microbiome of this environment was assembled from data obtained from SO3, SO4, SO5, and SO7. SO1 and SO2 have been excluded due to the detectable level of human interference and SO6 due to the almost sole presence of the phylum Proteobacteria , discuss systems , 62. The systems . Therefo systems . While d systems , in the  systems , 66; how3 in cave pools occurs because such waters become saturated with respect to CaCO3 due to the loss of CO2 and evaporation at the air-water interface [3 precipitation [The precipitation of CaCOnterface , 68. By nterface . The calnterface –71. Bothpitation . In partpitation , 73, whiMoonmilk refers to a variety of microcrystalline mineral aggregates ranging from soft and wet to a dry and powdery appearance . In contNitrospira dominant) was recovered from those two sampling sites. Nitrification has long been considered to be a two-step process catalyzed by chemolithoautotrophic microorganisms oxidizing either nitrite or ammonia; however, recent work by Daims and colleagues [Nitrospira. Although Nitrospira-like bacteria grow very slowly, with generation times up to 90 h for Nitrospira marina [The limestone samples obtained from this environment appear fairly similar with respect to their relative phyla and class abundance see Figs  and 5, elleagues  reports a marina , cultivaPseudomonas (Pseudomonas putida strain MnB1 are known for their ability of Mn(II) oxidation to form manganese oxide [Pseudomonas was, in addition to Leptothrix and Flavobacterium-related organisms, the most abundant and detectable population. However, samples taken at the same location (SO5), revealed a far broader diversity with similarities to the previously described diversity for ferromanganese deposits in Lechuguilla and Spider caves [Hyphomicrobium, Pedomicrobium and Nitrospira, where its representatives are known for their metal oxidizing abilities [Sampling point SO6 revealed almost exclusively the presence of β and γ –Proteobacteria, however, SO5, which was just adjacent to SO6, showed a much higher diversity. The genus almost exclusive recovered at SO6 was udomonas . Represese oxide , 80. A sse oxide  in ferroer caves . SO5 revbilities , 82, 83.The issue of human contamination of a pristine cave environment has been of interest since several decades and numerous studies have shown the impact of tourism or exploration , 30, 84.Propionibacterium was among the most abundant genera recovered from this area, with Propionibacterium acnes being a major inhabitant of the adult human skin, where it resides within sebaceous follicles, usually as a harmless commensal bacterium, although it has been implicated in the formation of acne vulgaris [Staphylococcus and Streptococcus were recovered in similar number compared to Propionibacterium  [amoA genes was comparable to the other investigated sites. This may be explained by the previously made statement that the regular impact on the microbiome by seasonal water flow may be responsible for this discrepancy.The microbial oxidation of ammonia is a key process in the global cycling of nitrogen. Nowadays we know that two groups of organisms are responsible for ammonia-oxidation, the ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA). Previous research has uncovered that AOA often outnumber their bacterial counterparts in marine and terrestrial environments , 91. Onl. (2016) . This maIn this study we elucidated the microbiome of the Su Bentu Cave in Sardinia as well as the impact of exploration on the native microbiome. Similar to other investigated subterranean environments, a broad diversity of different microorganisms was recovered with Proteobacteria being the dominant phyla. It can be concluded that infrequent exploration has a diminutive impact on the indigenous microbial population, compared to higher impacts for touristic caves e.g. . FurtherS1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.


Pasteurellaceae. Horse behaviour en route predicted clinical and respiratory outcomes. The frequency of stress related behaviours was greatest in the first hour of the journey, and balance-related behaviours were most common in the final hour of the journey. Horses which lowered their heads less frequently en route and showed more stress-related behaviours had higher physiological stress , increased tracheal mucus and inflammation scores, and higher TW bacterial concentration AJ (P<0.05). Six horses with abnormal lung auscultation AJ proved to have had higher tracheal inflammation scores at preloading (P = 0.017), an overall higher concentration of bacteria in their TW (P = 0.013), and an increased percentage of neutrophils in TW at five days AJ (P = 0.003) in comparison to the other horses. While transport-related health problems are multifactorial, clinical examination, including auscultation and endoscopic inspection of the lower respiratory tract before and after journey, and behavioural observation en route may identify animals at increased risk of transport associated respiratory disease.This study aimed to document the effects of an eight hour journey on behavioural, clinical, haematological, environmental and respiratory parameters, and to identify possible associations between factors. Twelve horses underwent clinical examination, respiratory endoscopy with tracheal wash (TW) aspiration, and collection of venous and arterial blood before (BJ) and after the journey (AJ). TW were submitted for conventional quantitative bacteriological evaluation and genetic microbiome analyses. Behaviour was assessed in stables prior to transportation and throughout the journey. Transportation caused mild, but significant, effects on fluid and electrolyte balance and an acute phase response, characterized by neutrophilia, hyperfibrinogenaemia and hyperglobulinaemia. The proportion of neutrophils in TW, tracheal mucus and TW bacterial concentration was increased AJ, with preferential replication of  The smears were stained using Wright-Giemsa stain . Four differential cell counts (DCC) each of 100 cells were made using high-power (100X) light microscopy. Differential cell counts of all samples were performed (by BP), blinded to horse identification, and expressed as a percentage.°C and 6% CO2. Colonies were counted on plates with fewer than 300 colonies after 48h incubation and expressed as colony-forming units (CFU) per mL . Bacterial isolates were identified according to phenotypic definitions  plates and incubated under aerobic conditions at 37initions  based onBacterial DNA was extracted from 1 mL of TW with the addition of 0.5 mL of dithiothreitol (150μg/mL) using a commercial kit . Bacterial DNA was extracted from air samples using a commercial kit . Extracted DNA samples were evaluated for quantity and quality using a NanoDrop-2000 . Purified DNA samples were sent to the Australian Genome Research Facility (AGRF) for microbial diversity profiling based on sequencing of partial 16s rRNA gene amplicons (V1 forward primer (27F): AGAGTTTGATCMTGGCTCAG; V3 reverse primer (519R): GWATTACCGCGGCKGCTG). Amplicons from the primary PCR were indexed by secondary PCR and resultant amplicons were quantified by fluorometry and normalised. The equimolar pool was then measured by qPCR and sequenced  with 2 x 300 base pairs paired-end chemistry. Paired-end reads were assembled by aligning forward and reverse reads using PEAR (version 0.9.5) . Primers2 analyses and linear regression, and ordinal logistic analysis was performed using R [All data were explored initially using summary statistics and normal distribution of all quantitative data was checked using the Anderson-Darling test. Gen Stat Version 14  was used for χ using R . All othEnvironmental data were analysed using ANOVA to determine the effect of situation  on the following variables: T, H, HI and W. A Tukey test was used to perform multiple comparisons in all models.st to 8th) as a fixed factor, with horse and trip  as random factors. A separate model was developed with each of the behavioural parameters as the outcome. Secondly, to identify behavioural differences during travelling, during the rest stop and when inside the box, models were developed using the situation  as a fixed factor, with horse and trip as random factors. A separate model was developed with each of the behavioural parameters as the outcome. A Tukey test was used as for post-hoc testing.All behavioural data (frequency and duration) were analysed by mixed linear model using PROC mixed procedure with random factors utilised to account for multiple records per animal. Firstly, to identify variation in behavioural parameters over the 8 hour journey duration, models were developed using the hour . Based on the results of lung auscultation at unloading, horses were split into two groups: abnormal lung sounds (AB) and normal (N). The effect of transportation, group (AB or N) or their interaction on these parameters was analysed by mixed linear model using PROC mixed procedure with time , group (AB or N) and their interaction as fixed factors. In the model, horse and trip were included as random factors, to account for multiple observations. A separate model was developed with each clinical parameter as the outcome and The observations made during endoscopy and TW scores were analysed by ordinal logistic regression analysis with the time, group (AB or N) and their interaction as fixed factors. The horse and trip were used as random factors. The null hypothesis was that the distribution of the scores was the same.post-hoc test. The effect of time on the bacteria DNA concentration was determined by Kruskal-Wallis test.TW data  were analysed by mixed linear model using time, group (AB or N) and their interaction as fixed factors. Horse and trip were used as random factors. A separate model was developed with each of the TW parameters as the outcome. Tukey test was used as a phyloseq [edgeR [phyloseq object. Bacterial diversity changes were evaluated by comparison of the Shannon diversity index, calculated after exclusion of OTUs for which the variance across all samples was very low, at different times  and between groups (AB and N) by Welch two sample t-test.Statistical analysis of 16s rRNA sequencing data was undertaken using phyloseq  and edgeq [edgeR  packagesq [edgeR . TaxonomPasteurellaceae, the family Streptococcaceae, the family Enterobacteriaceae, anaerobes [post-hoc test. Results are presented as least square mean ± SE.Identified bacteria were classified in 5 groups: the family ella spp), and sapAssociations between behavioural, clinical, haematological respiratory parameters were explored using Spearman correlation. Associations with a significant spearman Spearman correlation (P<0.05) were further investigated using linear regression analysis. Respiratory parameters  were expressed as the difference between endoscopic scores and TW bacterial concentration (log CFU/mL).All horses were normal on clinical evaluation before travelling. Clinical examination findings at unloading are provided in 3, H2S, CO, CH4 gases were not detected.Environmental temperature ranged from 10°C to 27°C in the boxes and from 10°C to 20°C in the truck during transport, with the highest values recorded during the afternoon. Humidity ranged from 21% to 82% inside the boxes and from 28% to 85% during transport, and was higher in the morning than the afternoon. The heat index ranged from 10°C to 25°C in the boxes and from 10°C to 20°C during transport, increasing progressively during the day. The velocity of air movement ranged from 0 to 5.1 km/h in the moving truck, whilst no air movement was recorded during the rest stop. No air movement was registered inside the box. Mean values for temperature, humidity and heat index varied significantly between boxes and trips . Gas analysis demonstrated oxygen concentration of 20.9 vol% in both boxes and throughout both trips, and NH10CFU/m3 at preloading and 3.2 log10CFU/m3 at unloading in trip 1, and 6.2 log10CFU/m3 at preloading and 4.0 log10CFU/m3at unloading in trip 2. The bacterial load inside the stable was 5.9 log10CFU/m3 on the day before travel and 6.1 log10CFU/m3 after the journey.Bacterial concentrations in air samples from the truck were 3.1 logth hour of the journey, H11 showed many aggressive behaviours toward H10, which started kicking in response and was subsequently injured.One horse (H3) showed a locomotory stereotypy (head tossing) after the second hour of travel and H2, which was on the right side of H3, started showing the same stereotypy in the last two hours of the trip. During the 7Balance related behaviours, particularly leaning on partitions or loss of balance, were exhibited most often during the journey, compared to in the truck at rest (P<0.001) or in the stable , unloading (P = 0.019) and 5 days AJ (P = 0.003). The effect of time of collection and group (AB or N) was significant on tracheal mucus which was lower at preloading in comparison with all the other times  and highBoth time (P<0.001) and group  had a significant effect on the percentage of neutrophils in TW samples, and the time*group interaction was also significant (P = 0.012). The percentage of neutrophils was highest in TW obtained 24 hours after travel . Results from Group N had returned to pre-transportation values by Day 5 AJ, whereas results from Group AB showed a persistent airway neutrophilia .3 colony forming units (CFU) / mL in both groups, which was significant when compared with all other sample times (P<0.001). Results from Group AB  had a higher overall concentration of bacteria across all sampling times than was observed for group B (P = 0.013). The effect of the time*group interaction was not significant (P = 0.701). At unloading the predominant bacterial isolates were identified as Pasteurellaceae-like  for the majority of horses (n = 8).The time had a significant effect on the concentration of bacteria recovered from TW P<0.001, . At unloThe quantity of DNA extracted for analysis from TW increased at unloading, as was observed for conventional quantitative bacterial counts . There wCorynebacteriaceae, Yaniellaceae and Staphylococcaceae, whereas TW samples included Pasteurellaceae, with this taxa dominating the respiratory flora of many horses at unloading. As was observed with phenotypic methods, Pasteurellaceae-like bacteria were identified with increased frequency in samples collected at unloading, whereas the relative abundance of strict anaerobes and saprophytes decreased in the total TW microbiome at this time (P<0.001). Genera 10 CFU/ml), but also with stress-related behaviours such as licking/chewing and pawing. Heavier animals showed more licking/chewing behaviours and spent less time with their heads down. On review of video footage it was apparent that that some larger framed horses were physically unable to lower their heads in the available space. The animals that moved more en route showed higher plasma concentrations of total protein and CK on unloading. There was an association between objective indicators of stress at unloading (plasma cortisol concentration and HR) with behaviours interpreted as indicative of stress such as touching the rubber tie cord, evasive behaviours. HR at unloading was also associated with balance related behaviours such as forward and backward movements. The animals which showed more stress related behaviours en route also had higher serum fibrinogen concentrations at unloading. The total white cell count was positively correlated with fibrinogen and globulins  than at preloading, suggesting that transportation is a mental and physical stressor for horses, particularly as circadian secretion of cortisol in horses typically results in higher concentrations in the morning than evening . As bothen route and during the rest stop, accumulating more mucus and bacteria in their lower respiratory tract. As such, recognition of these behaviours might allow pre-emptive identification of individual animals at increased risk for respiratory disease. The highest frequency of stress related behaviours was registered during the first hour of transport, suggesting this to be the most stressful part of a journey. Similar findings have been made in other studies using either cortisol or other stress indicators, such as heart rate variability, thyroid and adrenocortical hormones [th hour, increased lactate and CK at unloading. Individual differences were noticed in behavioural responses, with the more nervous and agitated horses affecting their neighbours. As social animals, anxiety and arousal can be socially transmitted to herd mates [The frequency of stress-associated behaviours was correlated to serum cortisol concentrations at unloading and horses that exhibited stress-associated behaviours more frequently also spent more time with their heads in an elevated position hormones , 48–50. rd mates , 51, a fPasteurellaceae bacteria, as previously reported [Pasteurellaceae as an early, opportunistic invaders when pulmonary clearance mechanisms are compromised [Enterobacteriaceae, Streptococcus spp or strict anaerobes, suggesting that these organisms may become part of the disease process at a later stage or under different circumstances.The transport related changes in respiratory microbiota at unloading are in agreement with the literature , 52 but,reported , 52. Compromised . There w10 CFU/m3) and stabled horses have been reported to spend less time with their heads down [Examination of TW samples showed a return to near normal (preload) concentrations of respiratory bacteria 24 hours AJ along with a return to a more diverse microflora community. However tracheal inflammation and mucus, TW colour and turbidity scores in our horses did not recover in the day after the journey, as had been demonstrated in previous studies , 52, a dads down . FurtherPulmonary auscultation of horses at unloading identified six horses (Group AB) with increased airway sounds, three of which were also observed coughing. This group subsequently proved to have increased airway inflammation and secretions, increased airway neutrophilia and concentration of bacteria recovered from TW samples compared to the remaining horses. As these animals’ tracheal inflammation scores prior to transportation were also higher than Group N horses, these horses may have been at increased risk for airway bacterial proliferation and contamination due to sub-clinical airway inflammation. These observations emphasise the importance of thorough veterinary examination before and after transportation.Transportation was associated with an acute phase inflammatory response characterised by transient neutrophilia, increased fibrinogen and increased globulins, as has been previously observed . Mild, b+ and Ca++, were observed transiently following transportation. Decreased plasma K+ has been previously reported [+. Transportation has been suggested as a predisposing factor for the development of hypocalcaemic tetany [en route affected the musculoskeletal system. Our horses were rested in their home stable following their journey, but lactate and CK remained elevated for a time AJ, suggesting a period of 24 hours rest after journeys of similar or greater duration should be recommended.Systemic electrolyte changes, specifically reduced plasma Kreported  and mighreported  or transc tetany , howeverc tetany . Blood len route, and the monitoring system used did not record sounds, so we could not measure noise inside the truck nor assess vocalizations, which is recognised as a stress indicator in horses [Limitations of the current study include the relatively small number of research horses, which may not have been as well conditioned to transportation as performance horses. However, the study was adequately powered for key outcome variables, and previous studies have used the same or smaller sample size. As even experienced horses still show a pronounced stress response to long distance transportation , these rn horses . Notwithen route is manifested with increased frequency of stress-related behaviours and reduced duration with their head in the downward position. The elevated head position correlated with the accumulation of tracheal mucus and increased numbers of respiratory bacteria, with prominence of commensals within the Pasteurellaceae family. From our findings, accurate clinical examination including auscultation prior to and after journey, monitoring of horse behaviours en route and 24 hour rest AJ are recommended to reduce the incidence of transport-related respiratory disease and to identify the animals at risk of these disease.Overall, this multidisciplinary study showed that the level of stress experienced by the animal S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableWorking definitions for phenotypic identification of bacterial isolates from tracheal wash samples (from ).(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.S1 FigEffect of the Time (a) and Group (b) on the distribution of the Tracheal Mucus score .(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 Fig(DOCX)Click here for additional data file.S1 Appendix(XLSX)Click here for additional data file.