Terrestrial habitat use of Marbled Salamanders Ambystoma opacum: A site specific approach

Habitat destruction, fragmentation and degradation have contributed heavily to the decline of amphibian populations such as Marbled Salamanders (Ambystoma opacum). Often, ambystomatid water resources are conserved without consideration for the equally important terrestrial habitat. This is partly due to a lack of information regarding the relationship between ecological succession, plant community composition, microhabitat and salamander abundance. Three sampling transects consisting of drift fence arrays, vegetation assessments and microhabitat surveys were extended 100 m into the terrestrial habitat surrounding a seasonal wetland at Beech Fork State Park in Wayne County, West Virginia. Principal components analysis was used to identify habitat gradients. Stepwise multiple regressions were used to develop predictive models for Marbled Salamander abundance using raw data and principal components. Models predicted much of the variation in my data set r2 = .9974, .8804 for raw data and principal components respectively. Inverse Distance Weighting was used to explore spatial relationships between variables. This study suggests that Marbled Salamanders are associated with late seral forests, and a high abundance of microhabitat

Cognitive and Behavioural Changes After Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson\u27s Disease

Cognitive and behavioural disturbances in patients with Parkinson’s disease seem to be relatively more frequent after deep brain stimulation of the subthalamic nucleus, as compared with deep brain stimulation of the internal globus pallidus. This finding might be at least partially due to the fact that the subthalamic nucleus is a smaller target, with different neural circuits (motor, associative, and limbic circuits) in close proximity to each other. Thus, electrode misplacements or current spreading to non-motor circuits involving the subthalamic nucleus may give rise to cognitive and behavioural disturbances after subthalamic implants.On the whole, nonetheless, most studies agree about the view that the cognitive and behavioural morbidity of deep brain stimulation of the subthalamic nucleus in patients with Parkinson’s disease can be considered relatively low, even in the long term, provided that appropriate criteria are used to select candidates for neurosurgery. Further studies are certainly needed to elucidate the pathophysiological mechanisms underlying the postoperative cognitive and behavioural changes which may be observed in Parkinsonian patients treated by deep brain stimulation of the subthalamic nucleu

The Reconstructed Cohort Design: A Method to Study Rare Neurodegenerative Diseases in Population-Based Settings

Rare neurodegenerative diseases are characterized by high heterogeneity and high clinical complexity, as well as low incidence and prevalence, thus making tracking small numbers of incident cases in the general population very challenging. Since it is not possible to use classical cohort studies to estimate the incidence of these rare diseases, we can "reconstruct" a theoretical cohort using case information from a well-defined geographic region collected through a surveillance system. The incidence rate is estimated as the ratio between the number of individuals at risk who were diagnosed with the disease of interest during the study period and the estimated overall amount of time individuals in the reference population spent at risk during the study period. If a series of assumptions are met, the approximate incidence proportion of a closed theoretical cohort without competing events and with the same follow-up duration can be calculated by multiplying the incidence rate with the length of the study time. This rationale relies on the presence of an effective referral system, which links all levels of the healthcare system together in the region, from general practitioners to specialized clinical centers. The reconstructed cohort design is a valid and cost-effective method to collect data on the incidence of rare neurodegenerative diseases and represents the theoretical framework for building up population-based registries

Design of custom cranial prostheses combining manufacturing and drop test finite element simulations

AbstractIn this work, impact puncture tests (drop tests) have been used to both tune numerical models and correlate the performance of customised titanium cranial prostheses to the manufacturing process. In fact, experimental drop tests were carried out either on flat disk-shaped samples or on prototypes of titanium cranial prostheses (Ti-Gr5 and Ti-Gr23 were used) fabricated via two innovative sheet metal forming processes (the super plastic forming (SPF) and the single point incremental forming (SPIF)). Results from drop tests on flat disk-shaped samples were used to define the material behaviour of the two investigated alloys in the finite element (FE) model, whereas drop tests on cranial prostheses for validation purposes. Two different approaches were applied and compared for the FE simulation of the drop test: (i) assuming a constant thickness (equal to the one of the undeformed blank) or (ii) importing the thickness distribution determined by the sheet forming processes. The FE model of the drop test was used to numerically evaluate the effect of the manufacturing process parameters on the impact performance of the prostheses: SPF simulations were run changing the strain rate and the tool configuration, whereas SPIF simulations were run changing the initial thickness of the sheet and the forming strategy. The comparison between numerical and experimental data revealed that the performance in terms of impact response of the prostheses strongly depends on its thickness distribution, being strain hardening phenomena absent due to the working conditions adopted for the SPF process or to the annealing treatment conducted after the SPIF process. The manufacturing parameters/routes, able to affect the thickness distribution, can be thus effectively related to the mechanical performance of the prosthesis determined through impact puncture tests

Directed acyclic graphs and causal thinking in clinical risk prediction modeling

Background: In epidemiology, causal inference and prediction modeling methodologies have been historically distinct. Directed Acyclic Graphs (DAGs) are used to model a priori causal assumptions and inform variable selection strategies for causal questions. Although tools originally designed for prediction are finding applications in causal inference, the counterpart has remained largely unexplored. The aim of this theoretical and simulation-based study is to assess the potential benefit of using DAGs in clinical risk prediction modeling. Methods: We explore how incorporating knowledge about the underlying causal structure can provide insights about the transportability of diagnostic clinical risk prediction models to different settings. We further probe whether causal knowledge can be used to improve predictor selection in clinical risk prediction models. Results: A single-predictor model in the causal direction is likely to have better transportability than one in the anticausal direction in some scenarios. We empirically show that the Markov Blanket, the set of variables including the parents, children, and parents of the children of the outcome node in a DAG, is the optimal set of predictors for that outcome. Conclusions: Our findings provide a theoretical basis for the intuition that a diagnostic clinical risk prediction model including causes as predictors is likely to be more transportable. Furthermore, using DAGs to identify Markov Blanket variables may be a useful, efficient strategy to select predictors in clinical risk prediction models if strong knowledge of the underlying causal structure exists or can be learned

Blockchain-Based Innovations for Population-Based Registries for Rare Neurodegenerative Diseases

Rare diseases are difficult if not impossible to study outside of population-based registries. Particularly in the context of rare neurodegenerative diseases characterized by case heterogeneity, difficult differential diagnosis by specialists, and small numbers of patients, registries make otherwise unfeasible incidence studies cost-effective and manageable. Building up and maintaining such registries is challenging and requires strong, active, and collaborative networks. Centralization around a leading institution provides structure and consistency, but this single-site storage leads to inefficiency and bottlenecks and is prone to failures, attacks, and manipulation. Furthermore, a substantial amount of trust is required between parties sharing data in a traditional registry. Patients are increasingly reluctant to share data in light of regular news reports about healthcare data breaches. Underfunded rare disease specialized centers are also hesitant to exchange with the leading institution out of fear that the low numbers of patients may seek treatment elsewhere. A lack of electronic health records and information system interoperability in certain settings leads to information silos and only further exacerbate the other issues. Blockchain technology may provide unique, innovative solutions to many of these challenges. Specifically, through digital trust and the use of an immutable distributed ledger, automated data transaction processing, guaranteed integrity, and enhanced security, blockchain technology seems to be perfectly suitable to optimize current population-based rare neurodegenerative disease registry construction and maintenance

The impact of intra-operative factors in otosclerosis outcomes: retrospective study in a tertiary centre

The aim of the study was to assess results from a large cohort of patients undergoing otosclerosis surgery with respect to the impact of intra-operative variables on post-operative hearing function and complications. We enrolled 384 patients affected by otosclerosis who were subjected to stapes surgery between 2004 and 2013 at a single institution. Surgery was performed in all cases under local anaesthesia, using a manual perforator and/or microdrill. Teflon-piston prosthesis was used in all patients. Audiological data obtained preoperatively and at last follow-up examination (minimum 12 months) were compared. Statistical analysis was performed using the multiple regression model. Peripheral rim otosclerosis and diffuse otosclerosis were associated with better functional results compared to the obliterative pattern (p < 0.05). Mean post-operative Air-Bone Gap was significantly higher in the 0.4 mm, compared to 0.6 mm piston group at 0.5 kHz (p < 0.001) and 1 kHz (p < 0.02); in the stapedotomy group a statistically significant difference was found between 0.4 and 0.6 mm piston groups, in favour of the latter (p < 0.05). No differences were encountered in terms of average hearing threshold and complications. Intra-operative variables cannot be fully predictable and our data could help in stratification of the results and as a landmark for the surgeon’s decisions

Study of Tailor Heat Treated Blanks Using the Fourier-series-based VFM

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Blockchain-Based Innovations for Population-Based Registries for Rare Neurodegenerative Diseases

Rare diseases are difficult if not impossible to study outside of population-based registries. Particularly in the context of rare neurodegenerative diseases characterized by case heterogeneity, difficult differential diagnosis by specialists, and small numbers of patients, registries make otherwise unfeasible incidence studies cost-effective and manageable. Building up and maintaining such registries is challenging and requires strong, active, and collaborative networks. Centralization around a leading institution provides structure and consistency, but this single-site storage leads to inefficiency and bottlenecks and is prone to failures, attacks, and manipulation. Furthermore, a substantial amount of trust is required between parties sharing data in a traditional registry. Patients are increasingly reluctant to share data in light of regular news reports about healthcare data breaches. Underfunded rare disease specialized centers are also hesitant to exchange with the leading institution out of fear that the low numbers of patients may seek treatment elsewhere. A lack of electronic health records and information system interoperability in certain settings leads to information silos and only further exacerbate the other issues. Blockchain technology may provide unique, innovative solutions to many of these challenges. Specifically, through digital trust and the use of an immutable distributed ledger, automated data transaction processing, guaranteed integrity, and enhanced security, blockchain technology seems to be perfectly suitable to optimize current population-based rare neurodegenerative disease registry construction and maintenance

Optimization of the sheet hydroforming process parameters to improve the quality of reshaped EoL components

The reshaping of End-of-Life (EoL) components by means of sheet metal forming process has been considered largely attractive, even from the social and economic point of view. At the same time, EoL parts can be often characterized by non-uniform thicknesses or alternation of work-hardened/undeformed zones as the results of the manufacturing process. Such heterogeneity can hinder a proper reshaping of the EoL part and residual marks on the re-formed blanks can be still present at the end of the reshaping step. In a previous analysis, the authors evaluated the effectiveness of reshaping a blank with a deep drawn feature by means of the Sheet Hydroforming (SHF) process: it was demonstrated that residual marks were still present if the deep drawn feature was located in a region not enough strained during the reshaping step. Starting from this condition and adopting a numerical approach, additional investigations were carried out changing the profile of the load applied by the blankholder and the maximum oil pressure. Numerical results were collected in terms of overall strain severity and residual height of the residual marks from the deep drawn feature at the end of the reshaping step. Data were then fitted by accurate Response Surfaces trained by means of interpolant Radial Basis Functions, subsequently used to carry out a virtual optimization managed by a multi-objective genetic algorithm. Optimization results suggested the optimal value of the output variables to reduce the marks from the deep drawn feature without the occurrence of rupture