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The purpose of this case report is to report the clinical experience of the use of gabapentin in the management of problem behaviors in a person with autism spectrum disorder and comorbid intellectual disability. Autism spectrum disorder is a neurodevelopmental disorder with a high prevalence of intellectual disability. Challenging behaviors in autism spectrum disorder are very common. In recent years, the hypothesis that the symptoms of autism derive from a deficiency of the inhibitory neurotransmission of gamma-aminobutyric acid is gaining considerable weight.

Exploring behavioral symptoms improvement in an adult man with ASD and severe intellectual disability taking gabapentin.

The rating scales used show improvement in challenging behaviors and aggressions. No side effects were observed.

Currently, there are no authorized drugs for the treatment of the symptomatic features of autism spectrum disorder, but drugs are used for comorbid psychopathological aspects. The authors want to speculate on a hypothetical function of gabapentin in remodeling the expression of alpha-2-delta subunits in people with autism and the processing of neural information.

Type 2 diabetes mellitus (T2DM) is a worldwide health problem. Blood pressure (BP) and inflammation are well-established risk factors for the cardiovascular complications of T2DM. Genistein is known to improve endothelial dysfunction. The purpose of this study is to investigate the effects of genistein supplementation on BP, high-sensitive C-reactive protein (hs-CRP) and homocysteine (Hcy) levels in postmenopausal women with T2DM.

This randomized, double-blind, placebo-controlled clinical trial is conducted on postmenopausal women with T2DM. A total of 54 subjects aged between 47 and 69 years are divided into two groups. Participants in the genistein group (n = 28) are given two genistein capsules (each capsule contained 54 mg genistein) and those in the placebo group (n = 26) received two placebo capsules (each capsule contained 54 mg maltodextrin) daily for 12 weeks. General characteristics, BP, hs-CRP and Hcy levels are measured at the baseline and at the end of the trial.

Genistein supplementation resulted in a significant reduction in systolic BP (SBP) (p < 0.001), diastolic BP (DBP) (p = 0.020), mean arterial pressure (MAP) (p < 0.001), serum levels of hs-CRP (p = 0.005) and Hcy (p = 0.001) in genistein group compared with placebo group at the end of the study. Significant decreases are also found in SBP by 5.4%, p < 0.001, DBP by 6.7%, p < 0.001, MAP by 6.2%, p < 0.001, serum levels of hs-CRP by 47.0%, p = 0.015 and Hcy by 18.4%, p < 0.001 in the genistein supplemented group. No significant changes are observed in terms of all post-intervention values in the placebo group.

Genistein administration improved BP, hs-CRP and Hcy levels in postmenopausal women with T2DM and may be useful in control of some CVD risk factors in these subjects.

Although a growing number of companies are using growth hacking (GH) to grow their businesses, scholars know little about its operationalization, namely through growth hacking capability (GHC), its antecedents and its effectiveness in improving their performance. Indeed, there are no studies that have examined the role of intellectual capital (IC) in this sense. The aim of this study is to fill these gaps and explore the effects of IC (composed of human, relational and structural capital) in influencing GHC and – in turn – whether GHC influences companies’ financial and market performance.

Empirical research was conducted using partial least squares structural equation modelling (PLS-SEM) to examine the validity of the proposed hypotheses and research model. Quantitative data were collected from 38 SMEs in the Italian context through a specifically designed questionnaire.

The results of the analysis show that IC has a positive and significant impact on SMEs’ GHC, thus confirming its role as a relevant antecedent; at the same time, the empirical results underscore the positive effect GHC has on SMEs’ financial and market performance.

First, the present body of work operationalizes GH, thereby, following previous work on lean startup and explores for the first time in literature the effect of IC on it. Second, from a contextual standpoint, the article deepens scholars' understanding of GHC by focusing on SMEs. Lastly, the adopted method represents a novel approach to investigating GHC, as scholarly literature has primarily focused on qualitative and theoretical dimensions.

Two-level support with Level 1 consisting of a set of beams and Level 2 consisting of a tree-like structure is an efficient support structure for extrusion-based additive manufacturing (EBAM). However, the literature for finding a slim two-level support is rare. The purpose of this paper is to design a lightweight two-level support structure for EBAM.

To efficiently solve the problem, the lightweight design problem is split into two subproblems: finding a slim Level 1 support and a slim Level 2 support. To solve these two subproblems, this paper develops three efficient metaheuristic algorithms, i.e. genetic algorithm (GA), genetic programming (GP) and particle swarm optimization (PSO). They are problem-independent and are powerful in global search. For the first subproblem, considering the path direction is a critical factor influencing the layout of Level 1 support, this paper solves it by splitting the overhang region into a set of subregions, and determining the path direction (vertical or horizontal) in each subregion using GA. For the second subproblem, a hybrid of two metaheuristic algorithms is proposed: the GP manipulates the topologies of the tree support, while the PSO optimizes the position of nodes and the diameter of tree branches. In particular, each chromosome is encoded as a single virtual tree for GP to make it easy to manipulate Crossover and Mutation. Furthermore, a local strategy of geometric search is designed to help the hybrid algorithm reach a better result.

Simulation results show that the proposed method is preferred over the existing method: it saves the materials of the two-level support up to 26.34%, the materials of the Level 1 support up to 6.62% and the materials of the Level 2 support up to 37.93%. The proposed local strategy of geometric search can further improve the hybrid algorithm, saving up to 17.88% of Level 2 support materials.

The proposed approach for sliming Level 1 support requires the overhanging region to be a rectilinear polygon and the path direction in a subregion to be vertical or horizontal. This limitation limits the further material savings of the Level 1 support. In future research, the proposed approach can be extended to handle an arbitrary overhang region, each with several choices of path directions.

The details of how to integrate the proposed algorithm into the open-source program CuraEngine 4.13.0 is presented. This is helpful for the designers and manufacturers to practice on their own 3D printers.

The path planning of the overhang is a critical factor influencing the distribution of supporting points and will thus influence the shape of the support structure. Different from existing approaches that use single path directions, the proposed method optimizes the volume of the support structure by planning hybrid paths of the overhangs.