A specific microbiota signature is associated to various degrees of ulcerative colitis as assessed by a machine learning approach

Ulcerative colitis (UC) is a complex immune-mediated disease in which the gut microbiota plays a central role, and may determine prognosis and disease progression. We aimed to assess whether a specific microbiota profile, as measured by a machine learning approach, can be associated with disease severity in patients with UC. In this prospective pilot study, consecutive patients with active or inactive UC and healthy controls (HCs) were enrolled. Stool samples were collected for fecal microbiota assessment analysis by 16S rRNA gene sequencing approach. A machine learning approach was used to predict the groups’ separation. Thirty-six HCs and forty-six patients with UC (20 active and 26 inactive) were enrolled. Alpha diversity was significantly different between the three groups (Shannon index: p-values: active UC vs HCs = 0.0005; active UC vs inactive UC = 0.0273; HCs vs inactive UC = 0.0260). In particular, patients with active UC showed the lowest values, followed by patients with inactive UC, and HCs. At species level, we found high levels of Bifidobacterium adolescentis and Haemophilus parainfluenzae in inactive UC and active UC, respectively. A specific microbiota profile was found for each group and was confirmed with sparse partial least squares discriminant analysis, a machine learning-supervised approach. The latter allowed us to observe a perfect class prediction and group separation using the complete information (full Operational Taxonomic Unit table), with a minimal loss in performance when using only 5% of features. A machine learning approach to 16S rRNA data identifies a bacterial signature characterizing different degrees of disease activity in UC. Follow-up studies will clarify whether such microbiota profiling are useful for diagnosis and management

Theranostic body fluid cleansing: rationally designed magnetic particles enable capturing and detection of bacterial pathogens

We report on theoretical and experimental considerations on bacteria capturing and enrichment via magnetic separation enabling integrated diagnosis and treatment of blood stream infections. We show optimization of carrier-pathogen interactions based on a mathematical model followed by an experimental proof-of-concept study along with investigations on the process safety

Cellular preservation of musculoskeletal specializations in the Cretaceous bird Confuciusornis

The hindlimb of theropod dinosaurs changed appreciably in the lineage leading to extant birds, becoming more ‘crouched’ in association with changes to body shape and gait dynamics. This postural evolution included anatomical changes of the foot and ankle, altering the moment arms and control of the muscles that manipulated the tarsometatarsus and digits, but the timing of these changes is unknown. Here, we report cellular-level preservation of tendon- and cartilage-like tissues from the lower hindlimb of Early Cretaceous Confuciusornis. The digital flexor tendons passed through cartilages, cartilaginous cristae and ridges on the plantar side of the distal tibiotarsus and proximal tarsometatarsus, as in extant birds. In particular, fibrocartilaginous and cartilaginous structures on the plantar surface of the ankle joint of Confuciusornis may indicate a more crouched hindlimb posture. Recognition of these specialized soft tissues in Confuciusornis is enabled by our combination of imaging and chemical analyses applied to an exceptionally preserved fossil

Review of nanomaterials in dentistry: interactions with the oral microenvironment, clinical applications, hazards, and benefits.

Interest in the use of engineered nanomaterials (ENMs) as either nanomedicines or dental materials/devices in clinical dentistry is growing. This review aims to detail the ultrafine structure, chemical composition, and reactivity of dental tissues in the context of interactions with ENMs, including the saliva, pellicle layer, and oral biofilm; then describes the applications of ENMs in dentistry in context with beneficial clinical outcomes versus potential risks. The flow rate and quality of saliva are likely to influence the behavior of ENMs in the oral cavity, but how the protein corona formed on the ENMs will alter bioavailability, or interact with the structure and proteins of the pellicle layer, as well as microbes in the biofilm, remains unclear. The tooth enamel is a dense crystalline structure that is likely to act as a barrier to ENM penetration, but underlying dentinal tubules are not. Consequently, ENMs may be used to strengthen dentine or regenerate pulp tissue. ENMs have dental applications as antibacterials for infection control, as nanofillers to improve the mechanical and bioactive properties of restoration materials, and as novel coatings on dental implants. Dentifrices and some related personal care products are already available for oral health applications. Overall, the clinical benefits generally outweigh the hazards of using ENMs in the oral cavity, and the latter should not prevent the responsible innovation of nanotechnology in dentistry. However, the clinical safety regulations for dental materials have not been specifically updated for ENMs, and some guidance on occupational health for practitioners is also needed. Knowledge gaps for future research include the formation of protein corona in the oral cavity, ENM diffusion through clinically relevant biofilms, and mechanistic investigations on how ENMs strengthen the tooth structure

Monoamine Oxidase A Gene Promoter Methylation And Transcriptional Downregulation in an Offender Population with Antisocial Personality Disorder

BACKGROUND: Antisocial personality disorder (ASPD) is characterised by elevated impulsive aggression and increased risk for criminal behaviour and incarceration. Deficient activity of the monoamine oxidase A (MAOA) gene is suggested to contribute to serotonergic system dysregulation strongly associated with impulsive aggression and antisocial criminality. AIMS: To elucidate the role of epigenetic processes in altered MAOA expression and serotonin regulation in a population of incarcerated offenders with ASPD compared with a healthy non-incarcerated control population. METHOD: Participants were 86 incarcerated participants with ASPD and 73 healthy controls. MAOA promoter methylation was compared between case and control groups. We explored the functional impact of MAOA promoter methylation on gene expression in vitro and blood 5-HT levels in a subset of the case group. RESULTS: Results suggest that MAOA promoter hypermethylation is associated with ASPD and may contribute to downregulation of MAOA gene expression, as indicated by functional assays in vitro, and regression analysis with whole-blood serotonin levels in offenders with ASPD. CONCLUSIONS: These results are consistent with prior literature suggesting MAOA and serotonergic dysregulation in antisocial populations. Our results offer the first evidence suggesting epigenetic mechanisms may contribute to MAOA dysregulation in antisocial offenders. Royal College of Psychiatrists

A specific microbiota signature is associated to various degrees of ulcerative colitis as assessed by a machine learning approach

Ulcerative colitis (UC) is a complex immune-mediated disease in which the gut microbiota plays a central role, and may determine prognosis and disease progression. We aimed to assess whether a specific microbiota profile, as measured by a machine learning approach, can be associated with disease severity in patients with UC. In this prospective pilot study, consecutive patients with active or inactive UC and healthy controls (HCs) were enrolled. Stool samples were collected for fecal microbiota assessment analysis by 16S rRNA gene sequencing approach. A machine learning approach was used to predict the groups’ separation. Thirty-six HCs and forty-six patients with UC (20 active and 26 inactive) were enrolled. Alpha diversity was significantly different between the three groups (Shannon index: p-values: active UC vs HCs = 0.0005; active UC vs inactive UC = 0.0273; HCs vs inactive UC = 0.0260). In particular, patients with active UC showed the lowest values, followed by patients with inactive UC, and HCs. At species level, we found high levels of Bifidobacterium adolescentis and Haemophilus parainfluenzae in inactive UC and active UC, respectively. A specific microbiota profile was found for each group and was confirmed with sparse partial least squares discriminant analysis, a machine learning-supervised approach. The latter allowed us to observe a perfect class prediction and group separation using the complete information (full Operational Taxonomic Unit table), with a minimal loss in performance when using only 5% of features. A machine learning approach to 16S rRNA data identifies a bacterial signature characterizing different degrees of disease activity in UC. Follow-up studies will clarify whether such microbiota profiling are useful for diagnosis and management

Rationally designed Magnetic Particles enable Capturing and Detection of Bacterial Pathogens

In this work we highlight magnetic blood purification as possible therapy for blood stream infections [1-2], where circulating pathogens are at first removed from the bodily fluid and subsequently recovered and analyzed. (Fig. 1) This process would result in an immediate therapeutic benefit for the patient, while also considerably shortening the diagnosis process, a critical step which heavily affects the final outcome of the treatment. Finally, the use of a newly developed human IgG1 monoclonal antibody against poly-N-acetylglucosamine (PNAG) as targeting moiety extends this therapy to the majority of the pathogens responsible for the most frequent nosocomial infections. We show an experimental proof-of-concept study along with an optimization of carrier-pathogen interactions based on a mathematical model and an investigations on the process safety [3]. [1] I. K. Herrmann, M. Urner, F. M. Koehler, M. Hasler, B. Roth-Z\u2019Graggen, R. N. Grass, U. Ziegler, B. Beck-Schimmer, and W. J. Stark, Small, 2010, 6, 1388 [2] I. K. Herrmann , M. Urner, S. Graf , C. M. Schumacher , B. Roth-Z\u2019graggen , M. Hasler , W. J. Stark , and B. Beck-Schimmer, Adv. Healthcare Mater., 2013, 2, 829\u2013835 [3] M. Lattuada, Q. Ren, F. Zuber, M. Galli, N. Bohmer, A. Wichser, S. Bertazzo, G. B. Pier and I. K. Herrmann, J. Mater Chem. B, under review