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Only 13 isolates remained as unidentified LAB. Figure 1 Mean abundance of LAB CFUs in the four refineries during the bioethanol process each 30 days. Log10 CFU counts. Figure 2 Restriction profile of the intergenic 16S-23S region of the Lactobacillus vini (A) and Lactobacillus fermentum (B) with the enzymes Sph I (lane 1), Nco I (lane 2), selleck kinase inhibitor Nhe I (lane 3), Ssp I (lane 4), Sfu I (lane 5), Eco RV (lane 6), Dra I (lane 7), Vsp I (lane 8), Hin cII (lane 9), Eco RI (lane 10), Hin dIII (lane 11) and Avr II (lane 12). M, 1 Kb molecular marker.

There was a higher number of LAB species in the first 30 days of the fermentation process (Figure 3A). Lactobacillus plantarum was frequently found in the beginning of the fermentation process at Miriri and Japungu distilleries. L. manihotivorans was found in the beginning of the fermentation process at Miriri, whereas Weissella paramesenteroides was found at Trapiche. Overall, there was a predominance of L. fermentum and L. vini after 60 days of fermentation. The two species, L. fermentum and L. vini, corresponded to the majority of the isolates obtained in this study (Figure 3B). There was a tendency of reduction of the LAB species numbers towards the end of the process, suggesting the occurrence of antibiotic resistance and/or the occurrence

of persistent endemic infections. The harsh conditions of the process (antibiotics, high temperature, low pH, and high ethanol concentration) possibly have a selective pressure over the microbiota, leading to a selection of certain resistant LAB types. L. ferintoshensis, L. diolivorans-like, L. nagelii, unidentified LAB, and

see more Oenococcus kitaharae-like were also found at the end of the fermentation process. Trapiche distillery showed the most distinct LAB composition possibly due to the sole use of molasses. The presumptive identification based on restriction enzyme analysis of rRNA was confirmed for several L. vini and L. fermentum isolates using pheS and 16S rRNA gene sequences (data in attached; GenBank under the accession nos. HQ009762-HQ009795; additional file 3). For instance, the isolates Dichloromethane dehalogenase JP7.3.7, TR7.5.7, TR7.5.13, TR7.5.15 had > 99% pheS sequence similarity towards the L. vini. Oenococcus kitaharae-like isolates and Lactobacillus sp. isolates were also tentatively identified by gene sequences, confirming their status of unknown species. Rep-PCR analysis using GTG5 primers was performed in order to evaluate the intra-specific diversity in L. fermentum and L. vini. Representative isolates of the species L. fermentum from the four distilleries obtained in the same and in different sampling periods had distinct fingerprint patterns, indicating a high genomic diversity of co-occurring populations (Figure 4). Likewise, representative L. vini isolates had different patterns (Figure 5). The high genomic diversity observed in L. fermentum and L.

Methods Subjects and amino acid treatment protocol This randomized, placebo-controlled, double-blind trial was conducted with 36 male college volunteers who did not have any musculoskeletal disorders and had not partaken in any regular resistance training prior to the study (Table 1). The study was carried out in accordance with the Declaration of Helsinki and was approved by the Human Subjects Committee of the University of Tsukuba. All subjects provided written informed consent. Table 1 Grouping conditions and characteristics of subjects   Supply condition Physiological characteristics before experiment Group BCAA Taurine Age (years) Height (cm) Body W.

(kg) Fat (%) Muscle W. (kg) MVC (Nm) CIR (mm) PLCB Seliciclib Placebo-1 Placebo-2 22.2 ± 1.1 170.8 ± 1.9 67.5 ± 3.5 18.3 ± 1.9 51.9 ± 1.8 36.5 ± 3.0 257.4 ± 7.6 BA 3.2 g Placebo-2 22.9 ± 1.1 176.7 ± 3.6 73.5 ± 4.3 20.1 ± 1.7 55.3 ± 2.4

41.9 ± 3.8 267.7 ± 7.9 TAU Placebo-1 2.0 g 22.2 ± 0.8 173.7 ± 2.2 65.5 ± 2.7 17.3 ± 1.3 51.7 ± 1.7 39.1 ± 2.4 251.3 ± 7.4 COMB 3.2 g 2.0 g 23.1 ± 1.3 174.5 ± 1.8 61.5 ± 1.6 14.2 ± 1.0 50.0 ± 1.3 35.0 ± 2.6 243.4 ± 6.6 Footnote: Data are expressed as means ± S. E. Abbreviation: PLCB, double-placebo control H 89 group; BA, branched-chain amino acids and placebo-2 supplement group; TAU, taurine and placebo-1 supplement group; COMB, combined (taurine and BCAA) supplement group; Placebo-1 and 2, placebo of BCAA and taurine supplementation, respectively (3.2g or 2.0g starch

mainly), Body W., body weight; Muscle W., muscle weight; MVC, maximal voluntary strength of isometric contraction; CIR, upper arm circumference. Subjects were randomly and equally divided into the following four groups (n = 9 per group): double-placebo control supplementation (PLCB); BCAA and placebo-2 supplementation (BA); taurine and placebo-1 supplementation (TAU); and BCAA and taurine supplementation (COMB). Subjects were orally administered two sachets containing a combination of BCAA (or placebo-1) and taurine (or placebo-2) after every meal for two weeks prior to exercise (Table 1 and Figure 1). We chose this timeframe because previous studies showed a significant mafosfamide increase in muscular taurine concentration following two weeks of taurine administration in rats [18, 20], but not after one week in humans [21]. Since the present study was designed as a double-blind trial, the duration of BCAA supplementation prior to exercise was matched to the two-week duration of taurine supplementation. All subjects were instructed to fill out a supplemental checklist after every meal. The BCAA and taurine sachets contained 3.2 g (9.6 g/day) of a BCAA mixture (Ile: Leu: Val = 1:2:1; Aminofeel®, Seikatsu Bunkasya Co. Inc., Chiba, Japan) and 2.0 g (6.0 g/day) of taurine, respectively.

Control biofilms also showed rare signs of membrane damage which initiated at the substratum-oriented side of the biofilm. In biofilms grown in the presence of carolacton, a significant part of the cells was stained red, indicating that cell membrane integrity was severely damaged. Vertical optical sections show that membrane damage occurred throughout check details the biofilm, at the substratum-oriented side as well as towards the biofilm surface. Biofilm architecture appeared less dense than in the controls, and small cell

clusters were scattered across the substratum with little empty space in between them. The magnification of the biofilms (Figure 6B) shows that the central regions of cell clusters were affected most find more by carolacton. Figure 6 Confocal laser scanning microscope images of S. mutans biofilms in the absence (A) or presence (B) of 0.5 μM carolacton after 12 h of

anaerobic cultivation. Staining using the LIVE/DEAD BacLight Bacterial Viability Kit assessed bacterial viability: green areas indicate live cells; red areas indicate dead or damaged cells. The top panel shows a bird’s eye view on the biofilm with lines indicating the position of the vertical sections shown at the lower and right margins of both images. Acquired using an UPLSAPO 20× objective lens, size of scale bar 50 μm. The bottom panel shows enlarged horizontal sections of S. mutans biofilms in the absence Depsipeptide solubility dmso (A) or presence (B) of 0.5 μM carolacton, aacquired using an UPLSAPO 40× objective lens with 7× digital magnification, size of scale bar 5 μm. Effect of carolacton on biofilms of quorum sensing negative mutants S. mutans utilizes a density-dependent quorum sensing signalling system to regulate the expression of virulence factors, including biofilm formation. It involves an excreted autoinducer, the competence stimulating peptide (CSP) encoded by comC, which is detected by a two-component signal

transduction system comprising the histidine kinase ComD and the response regulator ComE [34–38]. To find out if carolacton interferes with this system, we tested its effect on biofilm formation of knockout mutants for comC, comD and comE. Biofilms were grown under anaerobic conditions in the presence of 0.53 μM or 5.3 μM carolacton, respectively, and stained and analysed as described after 24 h of biofilm growth. For each strain and carolacton concentration, between 3 and 5 experiments were carried out. The green/red fluorescence ratio for untreated controls was the same for the wildtype and the three mutants. Figure 7 shows that biofilms of the wild-type strain S. mutans were damaged by carolacton with an average level of 61% (5.3 μM carolacton) or 63% (0.0.53 μM carolacton). comC and comE mutants showed slightly lower mean inhibition values, but this difference was not statistically significant. Biofilms of the comD mutant were only damaged by 40% (5.3 μM carolacton) or 42% (0.

3°C + ++ + 035-4 4 Selleckchem EPZ015666 2-3 Formed         035-6

** 9 2-3 Formed         036-1 7 6 Loose Normal ++ + + 036-2 8 3 Loose         036-3 9 2 Loose         * +: 6–10/ high power field (HPF) ++: >10/HPF. **: Fecal samples collected at patient discharge from hospital. Group C2 included eight children with diarrhea, who were further divided into three subgroups, based on the most dominant fecal bacterial species at admission. Group C2a included two children who had S. salivarius as the most dominant fecal bacterial species. Group C2b included three children who had Streptococcus sp. as the most dominant species. Group C2c included three children who had S. bovis group as the most dominant species (Figure 2A and B). For Patient 011 (age 2.5 years) in Group C2a, the percentage of S. salivarius in the fecal microflora was reduced from 78.95% at admission to 31.43% during recovery (Figure 2B), based on 442 sequences analyzed. Patient 021 (age 8 months) had the percentage of S. salivarius in the fecal microflora of 58.56% at admission, which increased to 60.0% during recovery and then to 76.67% after recovery (Figure 2B). Group C2b had Streptococcus sp. as the dominant fecal species at admission. For Patient Pexidartinib order 016 (age 9 months), the percentage of Streptococcus sp. in fecal microflora was reduced from 51.28% to 15.65% during recovery (3 days of treatment), and then to 4.67% after recovery

(12 days of treatment) (Figure 2B), based on 456 16S rRNA gene sequences analyzed. For Patient 019 (age 4 months), the percentage of Streptococcus sp. in fecal microflora was reduced from 40.54% at admission to 7.08% during recovery (6 days Dichloromethane dehalogenase of treatment) and then to 1.77% after recovery (11 days of treatment) (Figure 2A and B), based on 448 16S rRNA gene sequences analyzed. For Patient 023 (age 5 months), the percentage of Streptococcus sp. in fecal microflora was reduced from 26.05% at admission to 13.56% during recovery (5 days of treatment) and then to zero after recovery (9 days of treatment) (Figure 2B), based on 440 16S rRNA gene sequences

analyzed. All three patients in Group C2c had S. bovis group as their most dominant fecal bacterial species at admission. For Patient 033 (age 2 months), the percentage of S. bovis group in fecal microflora was reduced from 26.84% at admission to zero during recovery (3 days of treatment) (Figure 2B). It was not detected in feces sampled at discharge from the hospital, after 5 days of treatment. For Patient 017 (age 1.5 years), the percentage of S. bovis group in fecal microflora was reduced from 39.82% at admission to zero during recovery (3 days of treatment) (Figure 2B). It was not detected in feces sampled at discharge from hospital, after 5 days of treatment. For Patient 035 (age 8 months), the percentage of S. bovis group in fecal microflora was reduced from 42.

(AM491457) – - 20 2 – - – - 2 – - – - – - – - – - Psychrobacter arcticus (CP000082) – - – - – - 2 – - – - – - – - – - – - Vibrio logei (AY771721) – - – 18 – - 2 12 – - – - – - – - 2 – - Moritella spp. (various accession)2 – - – 2 – - – - 5 – - – - – - – - – - Moritella marina (AB038033) – - – 11 – - – - – - – - – - – - – - – Shewanella spp. this website (AB183502)

– - – 4 – 2 – - 2 – - – 3 – - – 2 – - Shewanella benthica (AB008796) – - – - – - – - – - – - – - – - – - 4 Pseudoalteromonas spp. (EF156750) – - – 2 – 2 – - 5 – - – - – - – - – - Uncultured bacterium (EF378155) – 2 – - – - – - – 3 – - – - – - – - – Chryseobacterium spp. (AY536547) – - – - – - – - – - – - 20 – - – - – - Flavobacterium sp. (various accession)3 – - – - – - – - – - – - 10 – - – - – 2 Acidovorax spp. (AM286541) – - – - – - – - – - – - 3 – - – - – - Uncultured alpha proteobacterium (AB074649) – - – - – - – - – - – - 3 – - – - – - Massilia aurea (AM231588) – - – - – - – - – - – - 3 AZD0530 – - – - – - Total sequences analysed 45 46 44 45 42 45 42 41 42 39 42 47 40 37 46 42 42 48 46 Coverage (C) 98 91 98 93 100 93 93 100 95 97 100 100 88 100 100 100 95 100 96 1 Accession numbers of Pseudomonas spp. sequences: EF111250, AF451270, EF451774, DQ777728, EF076789, EF061900 2 Accession numbers of Moritella spp. sequences: EF192283, DQ492814, AB120661 3 Accession numbers of Flavobacterium spp. sequences:

DQ857026, DQ640006, AM689970 second In general, the analysis revealed a high dominance of Photobacterium in all samples except in newly packaged cod loins (LS) where it was not detected. At packaging, the microflora of cod loins was dominated by Sphingomonas spp. and Ps. fluorescens while Variovorax spp. and Bradyrhizobium spp. were present at lower levels (Table 2). A trend towards the succession of P. phosphoreum with time during storage was seen in all storage conditions. Slower succession of P. phosphoreum was observed in samples stored in air than in MA. After six days of aerobic storage, the dominance

of P. phosphoreum was between 60 and 71% and other bacterial species were present in lower numbers, e.g. Pseudomonas spp., Shewanella spp., Acinetobacter spp., Psychrobacter spp., Vibrio logei, Moritella spp., and Pseudoalteromonas spp. After further storage (13-15 days), near the end of shelf life, P. phosphoreum increased its relative dominance up to 83-95% of the population (Table 2). The bacterial flora of fish stored under MA was dominated by P. phosphoreum, reaching levels of 91-100% of the population at all sampling times with one exception (day 7, MAP, -4°C, HS cod loins) where the dominance was 53% with other species in high relative quantity, including Chryseobacterium and Flavobacterium spp. (20 and 10%, respectively). When the same group had been stored for 28 days the bacterial flora was composed of 91% P. phosphoreum (Table 2).

05): FOS, HMGB1, TLR4 and UBE2V1 (Table 2). Table 1 List of genes that are upregulated upon P. acnes infection. Gene name Description Fold upregulation CCL2 Chemokine (C-C motif) ligand 2 41 CSF2 Colony stimulating factor 2 (granulocyte-macrophage) 139 CSF3 Colony stimulating factor 3 (granulocyte) 39 CXCL10 Chemokine (C-X-C motif) ligand 10 107 IFNB1 Interferon, beta 1, fibroblast 12 IL1A Interleukin 1, alpha 12 IL6 Interleukin 6 (interferon, beta 2) 34 IL8 Interleukin 8 336 IRAK2 Interleukin-1 receptor-associated kinase 2 11 IRF1 Interferon regulatory factor 1 12 JUN Jun oncogene 10 LTA

Lymphotoxin alpha (TNF superfamily, member 1) 5 NFKB2 Nuclear factor of kappa light Panobinostat mw polypeptide gene enhancer in B-cells 2 (p49/p100) 8 NFKBIA Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha 6 REL V-rel reticuloendotheliosis viral oncogene homolog 4 RELA V-rel reticuloendotheliosis viral oncogene homolog A, 2 RIPK2 Receptor-interacting serine-threonine kinase 2 4 TLR2 Toll-like receptor 2 3 TNF Tumor necrosis factor (TNF superfamily, member 2) 53 TICAM1 Toll-like receptor adaptor molecule 1 3 Semiconfluent RWPE-1 monocell-layers were infected with P. acnes at a MOI of 16:1. After 24 h infection, the cells were harvested, mRNA was collected and cDNA www.selleckchem.com/products/icg-001.html was prepared. The cDNA corresponding to 84 inflammation-associated genes

was quantified with qRT-PCR and compared with cDNA prepared from non-infected cells. Inclusion criteria: > 2-fold up-regulation, (p = 0.05). Table 2 List of genes that are downregulated upon P. acnes infection. Gene name Description Fold upregulation FOS V-fos FBJ murine osteosarcoma viral oncogene homolog -3 HMGB1 High-mobility group box 1 -3 TLR4 Toll-like receptor 4 -4 UBE2V1 Ubiquitin-conjugating enzyme E2 variant Docetaxel molecular weight 1 -3 Semiconfluent RWPE-1 monocell-layers were infected with P. acnes at a MOI of 16:1. After 24 h infection, the cells were harvested, mRNA was collected and cDNA was prepared. The cDNA corresponding to 84 inflammation-associated genes was

quantified with qRT-PCR and compared with cDNA prepared from non-infected cells. Inclusion criteria: > 2-fold down-regulation, (p = 0.05). Discussion Prostate specimens commonly display signs of chronic histological inflammation, along with occasional acute inflammation. Numerous studies have explored a possible link between prostate inflammation and cancer development and recent reviews of epidemiologic, genetic, and molecular studies have collectively suggested that the two cellular processes may indeed interact [2, 14–16]. Exposure to environmental factors such as infectious agents can lead to injury of the prostate and to the development of chronic inflammation [17]. The intrinsic interplay between microbes and urogenital cells is a key feature in the understanding of the microbial involvement in prostate disease.

This work was supported by the Canadian Institutes of Health Research (CIHR) Catalyst Grant (CPO-94434). Mary N. Elias holds a CIHR Fredrick Banting and Charles Best Scholarship Master’s Award; Andrea M. Burden holds the Graduate Department of Pharmaceutical Sciences 2010 Wyeth Pharmaceutical Fellowship

in Health Outcomes Research and the 2010–2011 University of Toronto Bone and Mineral Group Scholarship (Clinical); and Dr. Cadarette holds a CIHR New Investigator Award in the Area of Aging and Osteoporosis and an Ontario Ministry of Research and Innovation Early Researcher Award. Ms. Elias received funding support through the Leslie Dan Faculty of Pharmacy Student Opaganib cost Experience Fund to present this research at the Canadian Pharmacists Association Annual meeting and through a CIHR Institute of Health Services

and Policy Research Institute Community Support Travel Award to present this research at the Association of Faculties of Pharmacy in Canada’s First Annual Canadian Pharmacy Education and Research Conference. Conflicts of interest None. Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial click here use, distribution, and reproduction in any medium, provided the original ADP ribosylation factor author(s) and source are credited. Appendix Table 4 Search strategy for

MEDLINE, EMBASE, IPA, and HealthStar done April 20, 2010   Search Terms Ovid MEDLINEa Results Ovid EMBASEb Results Ovid IPA c Results Ovid Healthstard Results 1 *Osteoporosis/ 19560 21737 1901 11099 2 osteoporos#s.tw. 34026 35796 1880 19752 3 bone loss$.tw. 14265 11657 315 8013 4 Bone Density/ 30978 29744 251 18825 5 (bone adj2 (density or fragil$)).tw. 26293 24729 753 15811 6 bone mass.tw. 10680 10257 178 5320 7 bmd.tw. 14102 13432 260 8703 8 exp Fractures, Bone/ 117949 119884   77165 9 Fracture$.tw. 138210 121797 1370 87072 10 Postmenopause/ 14361 27716 1238 12392 11 (post menopaus$ or postmenopaus$ or post-menopaus$).tw. 36291 36928 2055 26297 12 Or/1-11 252732 230223 4698 155406 13 pharmacist.mp. or exp Pharmacists/ 11583 28008 29688 10896 14 exp Pharmacy/or pharmacy.mp.

Methods Strains, media and culture conditions C. albicans strains used in this study are listed in Table 2. DAY286, JMR114 and JJH31 were purchased from the Fungal Genetics Stock Centre (Kansas, USA) [59]. Strains CNC13, BRD3 and hAHGI were kind gifts from Jesús Plá and co-workers (Madrid, Spain) [31, 44]. Routinely, all strains were cultivated overnight (16 – 24 h) from frozen glycerol stocks in 20 or 50 ml YPD medium (Sigma-Aldrich Y1375) at 30°C. Growth was followed CCI-779 in vitro by measurements of optical densities (OD) of

cultures at λ = 600 nm (OD600) in transparent 96 well plates by the μQuant microtiter plate reader (Biotek, Bad Friedrichshall, Germany) in triplicates (each 180 μl). Cells from overnight cultures were diluted to an OD600 ~ 0.2 in YPD medium or restricted iron medium (RIM) and grown until early exponential phase (3 h) at 30°C (pre-culture). RIM was produced by adding 200 μM of the potent iron chelator bathophenanthroline disulfonate

(BPS) to YPD (Table 4). Cells were harvested from the pre-culture by centrifugation at 4500 x g and room temperature (RT) for 5 min, followed by resuspension in the respective growth medium. Growth media used in this study are summarized in Table 4. RPMI1640 is a medium comprising no iron salts, YNB is a defined medium with a basal concentration of 1.2 μM Fe3+ (information from the suppliers). selleck chemicals All liquid media used in this study were prepared in ultrapure Milli-Q (MQ) water (Millipore, Billerica, USA) and sterilized by filtration using 0.2 μm Progesterone bottle top filters (Milian). During all experiments, ferric chloride (FeCl3, Sigma-Aldrich) was chosen as ferric iron source, while ferrous sulfate (FeSO4, Sigma-Aldrich) served as source for ferrous iron. All iron containing stock solutions were freshly prepared immediately before use. For cultivations exceeding a cultivation time of 10 min in iron supplemented

media, iron stock solutions were sterile filtered by 0.2 μm Minisart sterile filters (Sartorius, Göttingen, Germany) before being added to the media. Table 4 Growth media used in this work Medium Composition RPMI 8.4 g L-1 RPMI 1640 (Sigma-Aldrich R1383), 2 g L-1 glucose, 0.165 M 3-(N-morpholino propanesulfonic acid (MOPS), adjusted to pH 7.3 with 10 N NaOH YNB 6.7 g L-1 Yeast Nitrogene Base (Sigma Y1250), 2 g L-1 glucose, 0.165 M 3-(N-morpholino propanesulfonic acid (MOPS), adjusted to pH 7.3 with 10 N NaOH YPD Sufficient iron medium: Yeast extract (10 g L-1) peptone (20 g L-1) dextrose (20 g L-1) (Sigma-Aldrich Y1375) RIM Restricted iron medium; YPD + 200 μM bathophenantroline disulfunate (BPS) (Sigma 146617) Protein analysis For the extraction of MCFOs, an overnight culture was diluted in YPD to an OD600 ~ 0.2 and grown until the early exponential phase (pre-culture). Working cultures were prepared by resuspending C. albicans cells from the pre-culture in 20 ml of the respective medium at an OD600 ~ 0.3. Cultures were incubated at 30°C for 3 – 5 h or at an OD = 0.

The magnitude of increased fracture risk with anti-depressant use described here is in line with findings from other epidemiological studies [9, 15–17, 24]. Those studies that compared risk with SSRIs PLX4032 mw and TCAs [9, 15, 16] similarly reported no difference in risk. There is also evidence to support our observation of an increased risk during the initial period of exposure [15, 16]. Richards et al. [17] investigated fracture risk with SSRIs and reported a dose effect and

a sustained elevation in risk with prolonged use. Vestergaard et al. reported a dose-dependent increase in fracture risk for sedating TCAs and most SSRIs. Furthermore, they also found an association between the increase in risk of any fracture and the inhibition of the serotonin transporter system [24]. We observed

OSI-906 chemical structure a similar increase in fracture risk for users of SSRIs and TCAs. The explanation for that increased fracture risk may be related simply to an increase in the risk of falls associated with anti-depressant use, especially as there is evidence to suggest that both SSRIs and TCAs are associated with an increased risk of fall. A large study of nursing home residents showed that, compared with non-users and after adjusting for potential confounders, the risk of falls was similar in new users of TCAs and SSRIs. The association was dose dependent and the increased risk persisted through the first 180 days of use and beyond [8]. TCAs are known to inhibit cardiovascular Na+, Ca2+ and K+ channels which can lead to life-threatening arrhythmias. SSRI use has been associated with an increased Etofibrate risk of syncope [33], postural hypotension

and dizziness [34] during the early days of exposure, and both SSRIs and TCAs can affect sleep patterns [35, 36], thereby increasing the risk of falls [37]. Another explanation for the increased fracture risk observed here is the effect of anti-depressants on bone physiology. Functional 5-HT receptors are present in bone cells and 5-HT stimulates proliferation of osteoblast precursor cells in vitro [23]. There is emerging evidence from animal studies that 5-HT is involved in bone remodelling and can alter bone mineral density (BMD) [18–20, 22]. Indeed, recent findings have shown that SSRIs decrease BMD in animal models [38] and humans [17, 39–41]. Such studies that compared BMD changes with different anti-depressants reported no association between TCA use and BMD [39, 40]. In a recent study of osteoporotic fractures, it was observed that the use of SSRIs (but not TCAs) in older women was independently associated with an increased rate of hip bone loss (0.82% reduction per year) [41], although there was limited information on dose and duration of use. To explore the possibility that fracture risk may be directly related to inhibition of the 5-HTT system, we grouped together the anti-depressants used according to the degree of 5-HTT inhibition afforded.