Robotic-assisted rehabilitation for balance in stroke patients (ROAR-S): effects of cognitive, motor and functional outcomes.

OBJECTIVE: Due to the aging population, the incidence of stroke is steadily increasing. In patients with stroke outcomes, sensory, motor and cognitive problems limit the performance of activities of daily living. The development of new technologies in rehabilitation is improving the quality and efficiency of functional recovery. Hunova robotic platform (Movendo Technology, srl, Genoa, Italy) is a robotic device for functional assessment and rehabilitation of balance. The purpose of this study is to evaluate the effects of rehabilitation with Hunova on cognitive function and balance in older adults with stroke. PATIENTS AND METHODS: This is a randomized, controlled, single-blind study. Twenty-four older adults with stroke outcomes were randomized into the Hunova group (HuG), which performed a specific rehabilitation program for balance using Hunova for 12 sessions in addition to conventional rehabilitation, and the control group (CoG), which performed only conventional rehabilitation. All patients underwent a clinical cognitive, balance, quality of life and fatigue assessment, and an instrumental balance assessment with Hunova at the beginning and end of treatment. RESULTS: Statistical analysis showed significant improvements in most clinical scales in both groups. Comparing the groups, HuG showed greater improvements in executive functions, speed of information processing, attention and discrimination of multiple stimuli, static and dynamic balance and autonomy in daily activities, standing postural sway, and trunk control in static and dynamic conditions. CONCLUSIONS: Data analysis showed that elderly with stroke who underwent balance technology treatment with Hunova in combination with conventional treatment had a greater improvement in cognitive functions, balance and reduced risk of falling.

Evaluation of the Spatiotemporal Epidemiological Modeler (STEM) during the recent COVID-19 pandemic.

In early December 2019, some people in China were diagnosed with an unknown pneumonia in Wuhan, in the Hubei province. The responsible of the outbreak was identified in a novel human-infecting coronavirus which differs both from severe acute respiratory syndrome coronavirus and from Middle East respiratory syndrome coronavirus. The new coronavirus, officially named severe acute respiratory syndrome coronavirus 2 by the International Committee on Taxonomy of Viruses, has spread worldwide within few weeks. Only two vaccines have been approved by regulatory agencies and some others are under development. Moreover, effective treatments have not been yet identified or developed even if some potential molecules are under investigation. In a pandemic outbreak, when treatments are not available, the only method that contribute to reduce the virus spreading is the adoption of social distancing measures, like quarantine and isolation. With the intention of better managing emergencies like this, which are a great public health threat, it is important to dispose of predictive epidemiological tools that can help to understand both the virus spreading in terms of people infected, hospitalized, dead and recovered and the effectiveness of containment measures.

Not all sales performance is created equal: personality and interpersonal traits in inbound and outbound marketing activities.

A long tradition of research has shown that personality traits, such as extraversion and agreeableness, and interpersonal constructs better predict job performance with a tacit but not explicit distinction in sales marketing activities. In this contribution, we aim to understand the role of job-related and interest data, interpersonal, and personality traits in affecting either inbound or outbound marketing activities and the overall sales performance. An original questionnaire integrates the interpersonal traits and personality factors reported in the literature in sales marketing activities (independent variables). The results were matched with the individual job-related and interest data (control variables) and sales performance (criterion variables) - expressed as the total number of closed contracts over the inbound/outbound related contacts of employees with responsibility in marketing activities for a large banking group. We are able to identify the relevant predictors of sales performance by creating full binary trees using control and independent variables in conditional inference forests and variable importance index measures. Higher performers in either inbound or outbound marketing activities rely on distinct personality sub-traits, which have fundamentally essential implications for interpersonal functioning, and personal data when agreeableness is central to the ability to function effectively in the interpersonal realm of sales activity.

First Prototype of the Infectious Diseases Seeker (IDS) Software for Prompt Identification of Infectious Diseases.

The rapid detection of ongoing outbreak - and the identification of causative pathogen - is pivotal for the early recognition of public health threats. The emergence and re-emergence of infectious diseases are linked to several determinants, both human factors - such as population density, travel, and trade - and ecological factors - like climate change and agricultural practices. Several technologies are available for the rapid molecular identification of pathogens [e.g. real-time polymerase chain reaction (PCR)], and together with on line monitoring tools of infectious disease activity and behaviour, they contribute to the surveillance system for infectious diseases. Web-based surveillance tools, infectious diseases modelling and epidemic intelligence methods represent crucial components for timely outbreak detection and rapid risk assessment. The study aims to integrate the current prevention and control system with a prediction tool for infectious diseases, based on regression analysis, to support decision makers, health care workers, and first responders to quickly and properly recognise an outbreak. This study has the intention to develop an infectious disease regressive prediction tool working with an off-line database built with specific epidemiological parameters of a set of infectious diseases of high consequences. The tool has been developed as a first prototype of a software solution called Infectious Diseases Seeker (IDS) and it had been established in two main steps, the database building stage and the software implementation stage (MATLAB® environment). The IDS has been tested with the epidemiological data of three outbreaks occurred recently: severe acute respiratory syndrome epidemic in China (2002-2003), plague outbreak in Madagascar (2017) and the Ebola virus disease outbreak in the Democratic Republic of Congo (2018). The outcomes are promising and they reveal that the software has been able to recognize and characterize these outbreaks. The future perspective about this software regards the developing of that tool as a useful and user-friendly predictive tool appropriate for first responders, health care workers, and public health decision makers to help them in predicting, assessing and contrasting outbreaks.

Multiple-therapy-resistant major depressive disorder: a clinically important concept.

Many novel therapeutic options for depression exist that are either not mentioned in clinical guidelines or recommended only for use in highly specialist services. The challenge faced by clinicians is when it might be appropriate to consider such 'non-standard' interventions. This analysis proposes a framework to aid this decision.Declaration of interestIn the past 3 years R.H.M.W. has received support for research, expenses to attend conferences and fees for lecturing and consultancy work (including attending advisory boards) from various pharmaceutical companies including Astra Zeneca, Cyberonics, Eli Lilly, Janssen, LivaNova, Lundbeck, MyTomorrows, Otsuka, Pfizer, Roche, Servier, SPIMACO and Sunovion. D.M.B.C. has received fees from LivaNova for attending an advisory board. In the past 3 years A.J.C. has received fees for lecturing from Astra Zeneca and Lundbeck; fees for consulting from LivaNova, Janssen and Allergan; and research grant support from Lundbeck.In the past 3 years A.C. has received fees for lecturing from pharmaceutical companies namely Lundbeck and Sunovion. In the past 3 years A.L.M. has received support for attending seminars and fees for consultancy work (including advisory board) from Medtronic Inc and LivaNova. R.M. holds joint research grants with a number of digital companies that investigate devices for depression including Alpha-stim, Big White Wall, P1vital, Intel, Johnson and Johnson and Lundbeck through his mindTech and CLAHRC EM roles. M.S. is an associate at Blueriver Consulting providing intelligence to NHS organisations, pharmaceutical and devices companies. He has received honoraria for presentations and advisory boards with Lundbeck, Eli Lilly, URGO, AstraZeneca, Phillips and Sanofi and holds shares in Johnson and Johnson. In the past 3 years P.R.A.S. has received support for research, expenses to attend conferences and fees for lecturing and consultancy work (including attending an advisory board) from life sciences companies including Corcept Therapeutics, Indivior and LivaNova. In the past 3 years P.S.T. has received consultancy fees as an advisory board member from the following companies: Galen Limited, Sunovion Pharmaceuticals Europe Ltd, myTomorrows and LivaNova. A.H.Y. has undertaken paid lectures and advisory boards for all major pharmaceutical companies with drugs used in affective and related disorders and LivaNova. He has received funding for investigator initiated studies from AstraZeneca, Eli Lilly, Lundbeck and Wyeth.

Improvement of the shadow tracking setup as a method to measure the velocities values of dark dust in order to reduce the risks of radioactive releases or explosions.

The mobilisation of dust is a key security issue in nuclear and industrial plants because it can provoke both explosions (in particular temperature and pressure conditions) and dangerous radioactive releases. This work is focused on the tungsten dust resuspension inside small tank for aerosol removal and DUST (STARDUST)-Upgrade, an experimental facility used to reproduce different conditions typical of the loss of vacuum accidents. In this paper, the authors present the facility and the materials used to mount the experimental setup together with the methods and algorithms implemented to track the dust velocity vectors. Tungsten dust is also analyzed through scanning electron microscopy and X-ray diffraction to find some correlation between the variation of the dust morphology, due to the different experimental conditions, with the dust mobilisation paths. The materials and methods together with the experimental results are analyzed and discussed to demonstrate the implementation with the shadow tracking setup presented in the previous facility STARDUST.

A novel integrated approach for the hazardous radioactive dust source terms estimation in future nuclear fusion power plants.

An open issue still under investigation by several international entities working on the safety and security field for the foreseen nuclear fusion reactors is the estimation of source terms that are a hazard for the operators and public, and for the machine itself in terms of efficiency and integrity in case of severe accident scenarios. Source term estimation is a crucial key safety issue to be addressed in the future reactors safety assessments, and the estimates available at the time are not sufficiently satisfactory. The lack of neutronic data along with the insufficiently accurate methodologies used until now, calls for an integrated methodology for source term estimation that can provide predictions with an adequate accuracy. This work proposes a complete methodology to estimate dust source terms starting from a broad information gathering. The wide number of parameters that can influence dust source term production is reduced with statistical tools using a combination of screening, sensitivity analysis, and uncertainty analysis. Finally, a preliminary and simplified methodology for dust source term production prediction for future devices is presented.

Testing the accuracy ratio of the Spatio-Temporal Epidemiological Modeler (STEM) through Ebola haemorrhagic fever outbreaks.

Mathematical modelling is an important tool for understanding the dynamics of the spread of infectious diseases, which could be the result of a natural outbreak or of the intentional release of pathogenic biological agents. Decision makers and policymakers responsible for strategies to contain disease, prevent epidemics and fight possible bioterrorism attacks, need accurate computational tools, based on mathematical modelling, for preventing or even managing these complex situations. In this article, we tested the validity, and demonstrate the reliability, of an open-source software, the Spatio-Temporal Epidemiological Modeler (STEM), designed to help scientists and public health officials to evaluate and create models of emerging infectious diseases, analysing three real cases of Ebola haemorrhagic fever (EHF) outbreaks: Uganda (2000), Gabon (2001) and Guinea (2014). We discuss the cases analysed through the simulation results obtained with STEM in order to demonstrate the capability of this software in helping decision makers plan interventions in case of biological emergencies.

Image computing techniques to extrapolate data for dust tracking in case of an experimental accident simulation in a nuclear fusion plant.

In this paper, a preliminary shadowgraph-based analysis of dust particles re-suspension due to loss of vacuum accident (LOVA) in ITER-like nuclear fusion reactors has been presented. Dust particles are produced through different mechanisms in nuclear fusion devices, one of the main issues is that dust particles are capable of being re-suspended in case of events such as LOVA. Shadowgraph is based on an expanded collimated beam of light emitted by a laser or a lamp that emits light transversely compared to the flow field direction. In the STARDUST facility, the dust moves in the flow, and it causes variations of refractive index that can be detected by using a CCD camera. The STARDUST fast camera setup allows to detect and to track dust particles moving in the vessel and then to obtain information about the velocity field of dust mobilized. In particular, the acquired images are processed such that per each frame the moving dust particles are detected by applying a background subtraction technique based on the mixture of Gaussian algorithm. The obtained foreground masks are eventually filtered with morphological operations. Finally, a multi-object tracking algorithm is used to track the detected particles along the experiment. For each particle, a Kalman filter-based tracker is applied; the particles dynamic is described by taking into account position, velocity, and acceleration as state variable. The results demonstrate that it is possible to obtain dust particles' velocity field during LOVA by automatically processing the data obtained with the shadowgraph approach.

Evidence-based guidelines for treating depressive disorders with antidepressants: A revision of the 2008 British Association for Psychopharmacology guidelines.

A revision of the 2008 British Association for Psychopharmacology evidence-based guidelines for treating depressive disorders with antidepressants was undertaken in order to incorporate new evidence and to update the recommendations where appropriate. A consensus meeting involving experts in depressive disorders and their management was held in September 2012. Key areas in treating depression were reviewed and the strength of evidence and clinical implications were considered. The guidelines were then revised after extensive feedback from participants and interested parties. A literature review is provided which identifies the quality of evidence upon which the recommendations are made. These guidelines cover the nature and detection of depressive disorders, acute treatment with antidepressant drugs, choice of drug versus alternative treatment, practical issues in prescribing and management, next-step treatment, relapse prevention, treatment of relapse and stopping treatment. Significant changes since the last guidelines were published in 2008 include the availability of new antidepressant treatment options, improved evidence supporting certain augmentation strategies (drug and non-drug), management of potential long-term side effects, updated guidance for prescribing in elderly and adolescent populations and updated guidance for optimal prescribing. Suggestions for future research priorities are also made.

UMEL: a new regression tool to identify measurement peaks in LIDAR/DIAL systems for environmental physics applications.

Recently, surveying large areas in an automatic way, for early detection of both harmful chemical agents and forest fires, has become a strategic objective of defence and public health organisations. The Lidar and Dial techniques are widely recognized as a cost-effective alternative to monitor large portions of the atmosphere. To maximize the effectiveness of the measurements and to guarantee reliable monitoring of large areas, new data analysis techniques are required. In this paper, an original tool, the Universal Multi Event Locator, is applied to the problem of automatically identifying the time location of peaks in Lidar and Dial measurements for environmental physics applications. This analysis technique improves various aspects of the measurements, ranging from the resilience to drift in the laser sources to the increase of the system sensitivity. The method is also fully general, purely software, and can therefore be applied to a large variety of problems without any additional cost. The potential of the proposed technique is exemplified with the help of data of various instruments acquired during several experimental campaigns in the field.

Rate of tree carbon accumulation increases continuously with tree size.

Forests are major components of the global carbon cycle, providing substantial feedback to atmospheric greenhouse gas concentrations. Our ability to understand and predict changes in the forest carbon cycle--particularly net primary productivity and carbon storage--increasingly relies on models that represent biological processes across several scales of biological organization, from tree leaves to forest stands. Yet, despite advances in our understanding of productivity at the scales of leaves and stands, no consensus exists about the nature of productivity at the scale of the individual tree, in part because we lack a broad empirical assessment of whether rates of absolute tree mass growth (and thus carbon accumulation) decrease, remain constant, or increase as trees increase in size and age. Here we present a global analysis of 403 tropical and temperate tree species, showing that for most species mass growth rate increases continuously with tree size. Thus, large, old trees do not act simply as senescent carbon reservoirs but actively fix large amounts of carbon compared to smaller trees; at the extreme, a single big tree can add the same amount of carbon to the forest within a year as is contained in an entire mid-sized tree. The apparent paradoxes of individual tree growth increasing with tree size despite declining leaf-level and stand-level productivity can be explained, respectively, by increases in a tree's total leaf area that outpace declines in productivity per unit of leaf area and, among other factors, age-related reductions in population density. Our results resolve conflicting assumptions about the nature of tree growth, inform efforts to undertand and model forest carbon dynamics, and have additional implications for theories of resource allocation and plant senescence.

Parasitism underground: determinants of helminth infections in two species of subterranean rodents (Octodontidae).

Patterns of infection among hosts in a population are often driven by intrinsic host features such as age or sex, as well as by positive or negative interactions between parasite species. We investigated helminth parasitism in 2 South American rodent species, Ctenomys australis and C. talarum (Octodontidae), to determine whether the unusual solitary and subterranean nature of these hosts would impact their patterns of infection. We applied generalized linear models to infection data on a total of 7 helminth species (1 in C. australis and 6 in C. talarum). Host age and season of capture influenced infection levels in some of the helminth species, but none were influenced by host body condition. In C. talarum, 4 pairs of helminth species showed significant associations, either asymmetrical or symmetrical, and with 3 of the 4 being positive; strong inter-specific facilitation appears likely in 1 case. Also, we found that female hosts, especially non-pregnant ones, harboured heavier infections of 2 nematode species than male hosts. This is in sharp contrast to the general male-bias reported for most studies of nematodes in wild mammals, and we develop explanations for these results based on the unusual ecology of these subterranean rodents.

Cobalt ions induce chemokine secretion in primary human osteoblasts.

Chemokines are major regulators of the inflammatory response and have been shown to play an important role in periprosthetic osteolysis. Titanium particles have previously been shown to induce IL-8 and MCP-1 secretion in osteoblasts. These chemokines result in the chemotaxis and activation of neutrophils and macrophages, respectively. Despite a resurgence in the use of cobalt-chromium-molybdenum alloys in metal-on-metal arthroplasty, cobalt and chromium ion toxicity in the periprosthetic area has been insufficiently studied. In this study we investigate the in vitro effect of cobalt ions on primary human osteoblast activity. We demonstrate that cobalt ions rapidly induce the protein secretion of IL-8 and MCP-1 in primary human osteoblasts. This elevated chemokine secretion is preceded by an increase in the transcription of the corresponding chemokine gene. Using a Transwell migration chemotaxis assay we also demonstrate that the chemokines secreted are capable of inducing neutrophil and macrophage migration. Furthermore, cobalt ions significantly inhibit osteoblast function as demonstrated by reduced alkaline phosphatase activity and calcium deposition. In aggregate these data demonstrate that cobalt ions can activate transcription of the chemokine genes IL-8 and MCP-1 in primary human osteoblasts. Cobalt ions are not benign and may play an important role in the pathogenesis of osteolysis by suppressing osteoblast function and stimulating the production and secretion of chemokines that attract inflammatory and osteoclastic cells to the periprosthetic area.

New Pudicinae (Trichostrongylina, Heligmosomoidea), Pudica ctenomydis n. sp. parasite of Ctenomys talarum (Rodentia: Octodontidae) from Argentina.

A total of 138 nematodes were found in the small intestine of Ctenomys talarum (Octodontidae) from Mar de Cobo, Argentina. A new nematode species, Pudica ctenomydis n. sp., is described. The new species more closely resembles P. pujoli Durette-Desset, 1990, parasite of Microcavia niata Thomas, from Bolivia. It can be distinguished from P. pujoli by the number of ridges and characteristics of the synlophe, the spicular morphology, differences in length between rays 9 and 10, and by the presence of a symmetrical caudal bursa and a cuticular expansion surrounding the body between vulva and anus in females.

Graphidioides subterraneus n. sp. (Nematoda: Trichostrongyloidea) from the South American subterranean rodent Ctenomys talarum Thomas, 1898 (Rodentia: Octodontidae).

A new nematode species, Graphidioides subterraneus n. sp., found in the stomach of C. talarum from Argentina is described. The new species more closely resembles G. mazzai Lent & Freitas, 1935, parasite of Galea leucoblephara from Argentina, and G. kravetzi Sutton & Durette-Desset, 1995, parasite of Holochilus brasiliensis from Uruguay. It can be distinguished by shorter spicules, by the shape of the gubernaculum, by shorter uterine branches, and by a different number of ridges of the synlophe all along the body.

Thyroid papillary carcinoma: preliminary evidence for a germ-line single nucleotide polymorphism in the Fas gene.

The expression of Fas in thyroid tumours and Graves' disease was analysed by mRNA transcript expression. As compared with unaffected thyroid tissue, Fas expression was enhanced in Graves' disease, adenomas, and papillary and follicular carcinomas. This pattern was also reflected in immunohistochemical studies. The PCR single-strand conformational polymorphism (SSCP) method and DNA sequencing were used to analyse Fas exons 1-9. The study was carried out on five different histotypes of thyroid tumours (n=93) and tissue from Graves' disease patients. As compared with a group of healthy blood donors (n=64), a significant association (P=0.006) emerged between papillary thyroid carcinoma and a silent single nucleotide polymorphism (SNP, 988C-->T) in exon 7 of the Fas gene. Other forms of thyroid pathology were not associated with the above polymorphism. Patients with neoplasia showed the same SNP in tumour tissue, in the unaffected contralateral thyroid lobe, and in peripheral blood cells. Thus, the 988C-->T polymorphism appeared to be of germ-line origin.