Development and external validation of a head and neck cancer risk prediction model

\ua9 2024 The Author(s). Head & Neck published by Wiley Periodicals LLC. Background: Head and neck cancer (HNC) incidence is on the rise, often diagnosed at late stage and associated with poor prognoses. Risk prediction tools have a potential role in prevention and early detection. Methods: The IARC-ARCAGE European case–control study was used as the model development dataset. A clinical HNC risk prediction model using behavioral and demographic predictors was developed via multivariable logistic regression analyses. The model was then externally validated in the UK Biobank cohort. Model performance was tested using discrimination and calibration metrics. Results: 1926 HNC cases and 2043 controls were used for the development of the model. The development dataset model including sociodemographic, smoking, and alcohol variables had moderate discrimination, with an area under curve (AUC) value of 0.75 (95% CI, 0.74–0.77); the calibration slope (0.75) and tests were suggestive of good calibration. 384 616 UK Biobank participants (with 1177 HNC cases) were available for external validation of the model. Upon external validation, the model had an AUC of 0.62 (95% CI, 0.61–0.64). Conclusion: We developed and externally validated a HNC risk prediction model using the ARCAGE and UK Biobank studies, respectively. This model had moderate performance in the development population and acceptable performance in the validation dataset. Demographics and risk behaviors are strong predictors of HNC, and this model may be a helpful tool in primary dental care settings to promote prevention and determine recall intervals for dental examination. Future addition of HPV serology or genetic factors could further enhance individual risk prediction

The Physiotherapy eSkills Training Online resource improves performance of practical skills: A controlled trial

Background: E-learning is a common and popular mode of educational delivery, but little is known about its effectiveness in teaching practical skills. The aim of this study was to determine whether the Physiotherapy eSkills Training Online resource in addition to usual teaching improved the performance of practical skills in physiotherapy students. Method: This study was a non-randomised controlled trial. The participants were graduate entry physiotherapy students enrolled in consecutive semesters of a neurological physiotherapy unit of study. The experimental group received the Physiotherapy eSkills Training Online resource as well as usual teaching. The Physiotherapy eSkills Training Online resource is an online resource incorporating (i) video-clips of patient-therapist simulations; (ii) supportive text describing the aim, rationale, equipment, key points, common errors and methods of progression; and (iii) a downloadable PDF document incorporating the online text information and a still image of the video-clip for each practical skill. The control group received usual teaching only. The primary outcomes were the overall performance of practical skills as well as their individual components, measured using a practical examination. Results: The implementation of the Physiotherapy eSkills Training Online resource resulted in an increase of 1.6 out of 25 (95% CI -0.1 to 3.3) in the experimental group compared with the control group. In addition, the experimental group scored 0.5 points out of 4 (95% CI 0 to 1.1) higher than the control group for 'effectiveness of the practical skill' and 0.6 points out of 4 (95% CI 0.1 to 1.1) higher for 'rationale for the practical skill'. Conclusion: There was improvement in performance of practical skills in students who had access to the Physiotherapy eSkills Training Online resource in addition to usual teaching. Students considered the resource to be very useful for learning.7 page(s

Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classification

<p>Abstract</p> <p>Background</p> <p>Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of identification and annotation of bimodal genes in the human and mouse genomes. These switch-like genes consist of 15% of known human genes, and are enriched with genes coding for extracellular and membrane proteins. It is of interest to determine the prediction potential of bimodal genes for class discovery in large-scale datasets.</p> <p>Results</p> <p>Use of a model-based clustering algorithm accurately classified more than 400 microarray samples into 19 different tissue types on the basis of bimodal gene expression. Bimodal expression patterns were also highly effective in differentiating between infectious diseases in model-based clustering of microarray data. Supervised classification with feature selection restricted to switch-like genes also recognized tissue specific and infectious disease specific signatures in independent test datasets reserved for validation. Determination of "on" and "off" states of switch-like genes in various tissues and diseases allowed for the identification of activated/deactivated pathways. Activated switch-like genes in neural, skeletal muscle and cardiac muscle tissue tend to have tissue-specific roles. A majority of activated genes in infectious disease are involved in processes related to the immune response.</p> <p>Conclusion</p> <p>Switch-like bimodal gene sets capture genome-wide signatures from microarray data in health and infectious disease. A subset of bimodal genes coding for extracellular and membrane proteins are associated with tissue specificity, indicating a potential role for them as biomarkers provided that expression is altered in the onset of disease. Furthermore, we provide evidence that bimodal genes are involved in temporally and spatially active mechanisms including tissue-specific functions and response of the immune system to invading pathogens.</p

First Description of Natural and Experimental Conjugation between Mycobacteria Mediated by a Linear Plasmid

Background: in a previous study, we detected the presence of a Mycobacterium avium species-specific insertion sequence, IS1245, in Mycobacterium kansasii. Both species were isolated from a mixed M. avium-M. kansasii bone marrow culture from an HIV-positive patient. the transfer mechanism of this insertion sequence to M. kansasii was investigated here.Methodology/Principal Findings: A linear plasmid (pMA100) was identified in all colonies isolated from the M. avium-M. kansasii mixed culture carrying the IS1245 element. the linearity of pMA100 was confirmed. Other analyses suggested that pMA100 contained a covalently bound protein in the terminal regions, a characteristic of invertron linear replicons. Partial sequencing of pMA100 showed that it bears one intact copy of IS1245 inserted in a region rich in transposase-related sequences. These types of sequences have been described in other linear mycobacterial plasmids. Mating experiments were performed to confirm that pMA100 could be transferred in vitro from M. avium to M. kansasii. pMA100 was transferred by in vitro conjugation not only to the M. kansasii strain from the mixed culture, but also to two other unrelated M. kansasii clinical isolates, as well as to Mycobacterium bovis BCG Moreau.Conclusions/Significance: Horizontal gene transfer (HGT) is one of most important mechanisms leading to the evolution and diversity of bacteria. This work provides evidence for the first time on the natural occurrence of HGT between different species of mycobacteria. Gene transfer, mediated by a novel conjugative plasmid, was detected and experimentally reproduced.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Cooperacion Interuniversitaria UAM-Banco Santander con America Latina (CEAL), UAM, SpainConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Federal de São Paulo, Dept Microbiol Imunol & Parasitol, Escola Paulista Med, São Paulo, BrazilLab Nacl Comp Cient, Petropolis, BrazilUniv Autonoma Madrid, Fac Med, Dept Prevent Med, Madrid, SpainInst Adolfo Lutz Registro, Nucleo TB & Micobacterioses, São Paulo, BrazilUniversidade Federal de São Paulo, Dept Microbiol Imunol & Parasitol, Escola Paulista Med, São Paulo, BrazilFAPESP: FAPESP - 06/01533-9Web of Scienc