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This systematic review summarizes the evidence about toe walking (TW) interventions in persons with autism. Following the PRISMA guidelines, a systematic search of MEDLINE, CINAHL, PsycINFO, The Cochrane Library, Google Scholar, and Opengrey was performed. Nine articles (all case reports or case series) were included. Methodological quality was assessed using the Mayo Evidence-Based Practice Centre tool. The included studies considered 17 subjects (16 males; age range: 4-15 years). All studies reported a reduction of TW frequency, but the follow-up was lacking in seven studies. There is a lack of high-quality studies with a sufficiently large and well-characterized sample to assess the effectiveness of TW interventions in autistic persons. These findings strongly support the need for further research in this area.

In Education 4.0, a personalized learning process is expected, and that students are the protagonist. In this new education format, it is necessary to prepare students with the skills and competencies of the 21st-Century, such as teamwork, creativity, and autonomy. One of the ways to develop skills and competencies in students can be through block programming, which can be used with emerging technologies such as robotics and IoT and in an interdisciplinary way. Thus, block programming in High School is important because it is possible to work on aspects such as problem-solving, algorithmic thinking, among other skills (Perin et al., 2021), which are necessary in the contemporary world. Thus, our Systematic Mapping Study (SMS) aims to identify which block programming tools support of Education 4.0 in High School. Overall, 46 papers were selected, and data were extracted. Based on the results, a total of 24 identified block programming tools that can be used in high school collaboratively and playfully and with an interdisciplinary methodology. Moreover, it was possible to see that most studies address block programming with high school students, demonstrating a lack of studies that address block programming with teachers. This SMS contributed to identifying block programming tools, emerging technologies, audience (teacher or student), and learning spaces where block programming is being worked on.

Abstract Background Personalized disease models are crucial for evaluating how diseased cells respond to treatments, especially in case of innovative biological therapeutics. Extracellular vesicles (EVs), nanosized vesicles released by cells for intercellular communication, have gained therapeutic interest due to their ability to reprogram target cells. We here utilized urinary podocytes obtained from children affected by steroid-resistant nephrotic syndrome with characterized genetic mutations as a model to test the therapeutic potential of EVs derived from kidney progenitor cells (nKPCs). Methods EVs were isolated from nKPCs derived from the urine of a preterm neonate. Three lines of urinary podocytes obtained from nephrotic patients’ urine and a line of Alport syndrome patient podocytes were characterized and used to assess albumin permeability in response to nKPC-EVs or various drugs. RNA sequencing was conducted to identify commonly modulated pathways after nKPC-EV treatment. siRNA transfection was used to demonstrate the involvement of SUMO1 and SENP2 in the modulation of permeability. Results Treatment with the nKPC-EVs significantly reduced permeability across all the steroid-resistant patients-derived and Alport syndrome-derived podocytes. At variance, podocytes appeared unresponsive to standard pharmacological treatments, with the exception of one line, in alignment with the patient’s clinical response at 48 months. By RNA sequencing, only two genes were commonly upregulated in nKPC-EV-treated genetically altered podocytes: small ubiquitin-related modifier 1 (SUMO1) and Sentrin-specific protease 2 (SENP2). SUMO1 and SENP2 downregulation increased podocyte permeability confirming the role of the SUMOylation pathway. Conclusions nKPCs emerge as a promising non-invasive source of EVs with potential therapeutic effects on podocytes with genetic dysfunction, through modulation of SUMOylation, an important pathway for the stability of podocyte slit diaphragm proteins. Our findings also suggest the feasibility of developing a non-invasive in vitro model for screening regenerative compounds on patient-derived podocytes.

Abstract Background The study examined the effects of Happy Mother—Healthy Baby (HMHB), a cognitive-behavioural therapy (CBT) intervention on breastfeeding outcomes for Pakistani women with prenatal anxiety. Methods Breastfeeding practices were evaluated in a randomized controlled trial between 2019 and 2022 in a public hospital in Pakistan. The intervention group was randomized to receive six HMHB sessions targeted towards prenatal anxiety (with breastfeeding discussed in the final session), while both groups also received enhanced usual care. Breastfeeding was defined in four categories: early breastfeeding, exclusive early breastfeeding, recent breastfeeding, and exclusive recent breastfeeding. Early breastfeeding referred to the first 24 h after birth and recent breastfeeding referred to the last 24 h before an assessment at six-weeks postpartum. Potential confounders included were mother’s age, baseline depression and anxiety levels, stress, social support, if the first pregnancy (or not) and history of stillbirth or miscarriage as well as child’s gestational age, gender. Both intent-to-treat and per-protocol analyses were examined. Stratified analyses were also used to compare intervention efficacy for those with mild vs severe anxiety. Results Out of the 1307 eligible women invited to participate, 107 declined to participate and 480 were lost to follow-up, resulting in 720 women who completed the postpartum assessment. Both intervention and control arms were similar on demographic characteristics (e.g. sex, age, income, family structure). In the primary intent-to-treat analysis, there was a marginal impact of the intervention on early breastfeeding (OR 1.38, 95% CI: 0.99–1.92; 75.4% (N = 273) vs. 69.0% (N = 247)) and a non-significant association with other breastfeeding outcomes (OR1.42, 95% CI: 0.89–2.27; (47) 12.9% vs. (34) 9.5%, exclusive early breastfeeding; OR 1.48, 95% CI: 0.94–2.35; 90% (N = 327) vs. 86% (N = 309), recent breastfeeding; OR1.01, 95% CI: 0.76–1.35; 49% (N = 178) vs 49% (N = 175) exclusive recent breastfeeding). Among those who completed the intervention’s six core sessions, the intervention increased the odds of early breastfeeding (OR1.69, 95% CI:1.12–2.54; 79% (N = 154) vs. 69% (N = 247)) and recent breastfeeding (OR 2.05, 95% CI:1.10–3.81; 93% (N = 181) vs. 86% (N = 309)). For women with mild anxiety at enrolment, the intervention increased the odds of recent breastfeeding (OR 2.41, 95% CI:1.17–5.00; 92% (N = 137) vs. 83% (N = 123). Conclusions The study highlights the potential of CBT-based interventions like HMHB to enhance breastfeeding among women with mild perinatal anxiety, contingent upon full participation in the intervention. Trial registration ClinicalTrials.gov NCT03880032.

Abstract Background The growing abundance of in vitro omics data, coupled with the necessity to reduce animal testing in the safety assessment of chemical compounds and even eliminate it in the evaluation of cosmetics, highlights the need for adequate computational methodologies. Data from omics technologies allow the exploration of a wide range of biological processes, therefore providing a better understanding of mechanisms of action (MoA) related to chemical exposure in biological systems. However, the analysis of these large datasets remains difficult due to the complexity of modulations spanning multiple biological processes. Results To address this, we propose a strategy to reduce information overload by computing, based on transcriptomics data, a comprehensive metabolic sub-network reflecting the metabolic impact of a chemical. The proposed strategy integrates transcriptomic data to a genome scale metabolic network through enumeration of condition-specific metabolic models hence translating transcriptomics data into reaction activity probabilities. Based on these results, a graph algorithm is applied to retrieve user readable sub-networks reflecting the possible metabolic MoA (mMoA) of chemicals. This strategy has been implemented as a three-step workflow. The first step consists in building cell condition-specific models reflecting the metabolic impact of each exposure condition while taking into account the diversity of possible optimal solutions with a partial enumeration algorithm. In a second step, we address the challenge of analyzing thousands of enumerated condition-specific networks by computing differentially activated reactions (DARs) between the two sets of enumerated possible condition-specific models. Finally, in the third step, DARs are grouped into clusters of functionally interconnected metabolic reactions, representing possible mMoA, using the distance-based clustering and subnetwork extraction method. The first part of the workflow was exemplified on eight molecules selected for their known human hepatotoxic outcomes associated with specific MoAs well described in the literature and for which we retrieved primary human hepatocytes transcriptomic data in Open TG-GATEs. Then, we further applied this strategy to more precisely model and visualize associated mMoA for two of these eight molecules (amiodarone and valproic acid). The approach proved to go beyond gene-based analysis by identifying mMoA when few genes are significantly differentially expressed (2 differentially expressed genes (DEGs) for amiodarone), bringing additional information from the network topology, or when very large number of genes were differentially expressed (5709 DEGs for valproic acid). In both cases, the results of our strategy well fitted evidence from the literature regarding known MoA. Beyond these confirmations, the workflow highlighted potential other unexplored mMoA. Conclusion The proposed strategy allows toxicology experts to decipher which part of cellular metabolism is expected to be affected by the exposition to a given chemical. The approach originality resides in the combination of different metabolic modelling approaches (constraint based and graph modelling). The application to two model molecules shows the strong potential of the approach for interpretation and visual mining of complex omics in vitro data. The presented strategy is freely available as a python module ( https://pypi.org/project/manamodeller/ ) and jupyter notebooks ( https://github.com/LouisonF/MANA ).

Abstract Antenatal anxiety is among the risk factors for adverse birth outcomes, which are common in Pakistan. Between 2019 and 2022, we conducted a randomized controlled trial to evaluate the effects of the Happy Mother-Healthy Baby program, designed to reduce anxiety during pregnancy through use of Cognitive Behavior Therapy, on birth outcomes with 796 women in Rwalpindi, Pakistan. We performed intent-to-treat analysis and per protocol analyses. Intention-to-treat analyses showed no difference in the odds of low birthweight (LBW) (Adj. OR = 0.82, 95% CI 0.55–1.28 p = 0.37), preterm birth (PTB) (Adj. OR = 1.20 95% CI 0.83–1.71, p = 0.33) or small-for-gestational age (SGA) birth, (Adj. OR = 0.76, 95% CI 0.56–1.09, p = 0.16). Among completers who received ≥ 5 intervention sessions, the odds of LBW and SGA were 39% and 32% lower (Adj. OR = 0.61, 95% CI 0.43–0.87, p

OBJECTIVE: The gastrointestinal tract is commonly involved in patients with systemic sclerosis (SSc) with varied manifestations. As our understanding of SSc gastrointestinal disease pathogenesis and risk stratification is limited, we sought to investigate whether patterns of esophageal dysfunction associate with specific clinical phenotypes in SSc. METHODS: Patients enrolled in the Johns Hopkins Scleroderma Center Research Registry who completed high-resolution esophageal manometry (HREM) studies as part of their clinical care between 2011 and 2020 were identified. Associations between esophageal abnormalities on HREM (absent contractility [AC], ineffective esophageal motility [IEM], hypotensive lower esophageal sphincter [hypoLES]) and patient demographic information, clinical characteristics, and autoantibody profiles were examined. RESULTS: Ninety-five patients with SSc had HREM data. Sixty-five patients (68.4%) had AC (37 patients with only AC, 28 patients with AC and a hypoLES), 9 patients (9.5%) had IEM, and 11 patients (11.6%) had normal studies. AC was significantly associated with diffuse cutaneous disease (38.5% versus 10.0%; P

Life on earth depends on photosynthetic primary producers that exploit sunlight to fix CO2 into biomass. Approximately half of global primary production is associated with microalgae living in aquatic environments. Microalgae also represent a promising source of biomass to complement crop cultivation, and they could contribute to the development of a more sustainable bioeconomy. Photosynthetic organisms evolved multiple mechanisms involved in the regulation of photosynthesis to respond to highly variable environmental conditions. While essential to avoid photodamage, regulation of photosynthesis results in dissipation of absorbed light energy, generating a complex trade-off between protection from stress and light-use efficiency. This work investigates the impact of the xanthophyll cycle, the light-induced reversible conversion of violaxanthin into zeaxanthin, on the protection from excess light and on biomass productivity in the marine microalgae of the genus Nannochloropsis. Zeaxanthin is shown to have an essential role in protection from excess light, contributing to the induction of nonphotochemical quenching and scavenging of reactive oxygen species. On the contrary, the overexpression of zeaxanthin epoxidase enables a faster reconversion of zeaxanthin to violaxanthin that is shown to be advantageous for biomass productivity in dense cultures in photobioreactors. These results demonstrate that zeaxanthin accumulation is critical to respond to strong illumination, but it may lead to unnecessary energy losses in light-limiting conditions and accelerating its reconversion to violaxanthin provides an advantage for biomass productivity in microalgae.