Notes

Developments in Books in Cerebral Bypass Surgical treatment: A deliberate Review.
The use of cannabis to treat some symptoms of neurological diseases, including multiple sclerosis (MS), has increased worldwide. We aimed to assess the use of cannabis in patients with MS (PwMS) from Argentina, its reasons and patients' perceptions on the management of MS symptoms. Additionally, we assessed their association with socio-demographic and clinical aspects.

A cross-sectional online survey that included 281 PwMS from Argentina was conducted. Screening instruments Demographics and clinical data, health-related QoL (MS Impact Scale-29), Fatigue Severity Scale, The Hospital Anxiety and Depression Scale, sleep disorders, physical disability (self-administrated Expanded Disability Status Scale) and medical or recreational cannabis use were evaluated. A logistic regression model was carried out.

Current users (cannabis was used within the past year) was reported in 34.2% and former users (had tried cannabis but not used it within the past year) in 22.7%. Daily cannabis use was reported in 31.3% (current+former users) of the studied cohort, 41.9% started their use after MS diagnosis and 54.3% of them had never discussed about cannabis use with their neurologist. Recreational use was reported in 47.5%. Younger (age below 30 years) PwMS (OR=2.39, p=0.03), presence of chronic pain (OR=2.42, p=0.002) and current alcohol intake (OR=3.33, p=0.001) were predictors of current cannabis use in our multivariate model.

A high prevalence of use of cannabis in PwMS from Argentina was observed. Demographic, symptoms and lifestyle factors predict cannabis use. Identifying the presence and severity of these conditions would contribute to a better MS management and treatment.
A high prevalence of use of cannabis in PwMS from Argentina was observed. Demographic, symptoms and lifestyle factors predict cannabis use. EGFR inhibitor Identifying the presence and severity of these conditions would contribute to a better MS management and treatment.
The objective of the study is to explore parents' perceptions of COVID-19-like symptoms in their child and attitudes towards isolating from others in the household when unwell.

The study used qualitative, semistructured interviews.

The study involved thirty semistructured telephone interviews with parents of children between 4 and 18 years. Thirty semistructured telephone interviews with parents of children between 4 and 18 years.

We found four themes relating to symptom attribution ('normalising symptoms', 'err on the side of caution', 'experience of temperature', 'symptoms not normal for us'). In general, parents were more likely to attribute symptoms to COVID-19 if a temperature was present or the symptoms were perceived as 'unusual' for their family. Four themes relating to self-isolation ('difficult to prevent contact with children', 'isolation would be no different to lockdown life', 'ability to get food and supplies', 'limited space'). Parents believed they would find isolation within the household difficult or impossible if they had dependent children, had limited space or could not shop for groceries.

The findings highlight complexities in symptom perception, attribution and household isolation. We suggest that they can be overcome by (a) providing better guidance on what symptoms require action, (b) providing guidance as to how to prevent infection within the household and (c) by supporting families with grocery shopping through a potential second or third wave.
The findings highlight complexities in symptom perception, attribution and household isolation. We suggest that they can be overcome by (a) providing better guidance on what symptoms require action, (b) providing guidance as to how to prevent infection within the household and (c) by supporting families with grocery shopping through a potential second or third wave.
We examined the association between living alone and mental health and the moderating effects of face-to-face and non-face-to-face social contacts, among community-dwelling older adults.

Cross-sectional study.

This cross-sectional study recruited Japanese adults older than 60 years, who attended health check-ups held in a suburban town hall in July and August of 2018 and 2019. As mental health outcomes, depression was assessed using the Geriatric Depression Scale 15-items, loneliness was assessed using the University of California, Los Angeles Loneliness Scale 3-items, and happiness was self-rated on a 10-point scale. Face-to-face social contacts were evaluated by participants' frequency of meetings with relatives or friends, whereas non-face-to-face contacts were measured by the frequency of interactions via letter, telephone or e-mail. Multivariable linear regression analysis was conducted to examine the association between living alone with each mental health outcome and the effect modifications of having face-to-face and non-face-to-face social contacts.

Data from 300 older adults were analysed. The participants' mean age was 73.0 years, 51.3% were female, and 16.0% lived alone. Living alone was significantly associated with poorer mental health. Regarding loneliness and low happiness, having face-to-face and non-face-to-face contacts more than once a week alleviated the adverse association of living alone (loneliness face-to-face contacts, P=0.020; non-face-to-face contacts, P=0.028; happiness face-to-face contacts, P=0.020; non-face-to-face contacts, P=0.001).

Our findings suggest that non-face-to-face, as well as face-to-face social contacts have a moderating effect on the adverse association of living alone with loneliness and happiness.
Our findings suggest that non-face-to-face, as well as face-to-face social contacts have a moderating effect on the adverse association of living alone with loneliness and happiness.The monotypic carboxydophilic genus Carbophilus has recently been transferred to the genus Aminobacter within the family Phyllobacteriaceae, and Carbophilus carboxidus was renamed Aminobacter carboxidus (comb. nov.) [Hördt et al. 2020]. Due to the poor resolution of the 16S rRNA gene-based phylogeny, an extensive phylogenomic analysis of the family Phyllobacteriaceae was conducted, with particular focus on the genus Aminobacter. Whole genome-based analyses of Phyllobacteriaceae type strains provided evidenced that the genus Aminobacter forms a monophyletic cluster, clearly demarcated from all other members of the family. Close relatedness between A. carboxidus DSM 1086T and A. lissarensis DSM 17454T was inferred from core proteome phylogeny, shared gene content, and multilocus sequence analyses. ANI and GGDC provided genetic similarity values above the species demarcating threshold for these two type strains. Metabolic profiling and cell morphology analysis corroborated the phenotypic identity between A. carboxidus DSM 1086T and A. lissarensis DSM 17454T. Search for the presence of carbon monoxide dehydrogenase (CODH) genes in Phyllobacteriaceae genomes revealed that the form II CODH is widespread in the family, whereas form I CODH was detected in few Mesorhizobium type strains, and in both A. carboxidus DSM 1086T and A. lissarensis DSM 17454T. Results of phylogenomic, chemotaxonomic, and morphological investigations, combined with the presence of similarly arranged CODH genes, indicate that A. carboxidus DSM 1086T and A. lissarensis DSM 17454T are distinct strains of the same species. Hence A. carboxidus is a later subjective heterotypic synonym of A. lissarensis.The main objective of this paper was to analyse the roadway, environmental, and driver-related factors associated with an overrepresentation of frequency and severity of run-off-the-road (ROR) crashes. The data used in this study refer to the 6167 crashes occurred in the section Naples-Candela of A16 motorway, Italy in the period from 2001 to 2011. The analysis was carried out using the rule discovery technique due to its ability of extracting knowledge from large amounts of data previously unknown and indistinguishable by investigating patterns that occur together in a given event. The rules were filtered by support, confidence, lift, and validated by the lift increase criterion. A two-step analysis was carried out. In the first step, rules discovering factors contributing to ROR crashes were identified. In the second step, studying only ROR crashes, rules discovering factors contributing to severe and fatal injury (KSI) crashes were identified. As a result, 94 significant rules for ROR crashes and 129 significant rules for KSI crashes were identified. These rules represent several combinations of geometric design, roadside, barrier performance, crash dynamic, vehicle, environmental and drivers' characteristics associated with an overrepresentation of frequency and severity of ROR crashes. From the methodological point of view, study results show that the a priori algorithm was effective in providing new information which was previously hidden in the data. Finally, several countermeasures to solve or mitigate the safety issues identified in this study were discussed. It is worthwhile to observe that the study showed a combination of factors contributing to the overrepresentation of frequency and severity of ROR crashes. Consequently, the implementation of a combination of countermeasures is recommended.Traffic crashes have become a leading cause of preventable deaths globally. Identifying high-risk segments not only benefits safety specialists to better understand crash patterns but also reminds road users to be aware of driving risks. This study reports on a new crowdsourcing solution to identify high-risk highway segments by analyzing driving jerks. Driving jerks represent the abrupt changes of acceleration, which have been shown to be closely related to traffic risks. In this study, we first calculate driving jerks from each participant's naturalistic driving data and identify "unsafe" drivers based on their jerk-ratio. Then, we innovatively propose an improved line-constrained clustering method to identify each participant's jerk clusters on each road. These individual-specific jerk clusters are overlapped with road networks to identify potential risky segments. By synthesizing these potential risky segments reported by different participants, we obtain the final detection results for high-risk highway segments. In this study, we compare the jerk-cluster-determined risky segments with crash-rate-determined risky segments to evaluate the proposed solution's effectiveness. The study results demonstrate that our crowdsourcing solution can effectively identify high-risk road segments with an estimated 75 % accuracy. More importantly, by analyzing this valued surrogate measure, safety specialists can identify hazardous road segments before crashes occur.The aim of this cross-sectional mixed-method study was to understand the current use, and practices to support the implementation, of sit-stand workstations (SSWs) from the perspective of furniture purchasing decision makers in Australian organisations. An online survey, and in-depth interviews with a purposive sub-sample were conducted. A total of 216 eligible participants from 150 organisations across 18 sectors completed the survey with 17 interviews conducted. 40% of organisations provided SSWs on request while 41% reported not using them appropriately. Over half provided no training on the appropriate use of SSWs (n = 109, 51%) nor used any strategies to enhance their use (n = 163, 84%). From the interviews, SSWs were perceived effective in reducing discomforts and increasing employees' satisfaction and productivity. Lack of resources and guidelines to support SSW usage, and lack of wellbeing knowledge, were identified as barriers. Education and ongoing monitoring are important to enhance the appropriate use and uptake of SSWs.
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