Background. The 15q11.1-13.1 duplication, also known as Dup15q syndrome, is a rare congenital disease affecting 1 in 30,000 to 1 in 60,000 children worldwide. This condition is characterized by the presence of at least one extra copy of genetical material within the Prader-Willi/Angelman Critical Region (PWACR) of the referred 15q11.2-q13.1 chromosome. Case Report. Our study presents the clinical and genetical features of the first patient with a denovo 15q11.2 interstitial duplication on the maternal allele (inv Dup15q) that mimics a milder Prader-Willi syndrome probably due to an atypical disruption of the SNHG14 gene. Methylation-specific MLPA analysis has confirmed the presence of a very unlikely duplication that lies between breakpoint 1 (BP1) and the middle of BP2 and BP3 (BP3). This atypical alteration might be linked to the milder patient’s clinical phenotype. Conclusions. This is the first Dup15q patient reported in Ecuador and of the very few in South America. This aberration has never been described in a patient with Dup15q, and the unusual clinical presentation is probably due to the atypical distal breakpoint occurring within the gene SNHG14 which lies between BP2 and BP3 and does not therefore contain the whole PWACR. If the duplication disrupted the gene, then it is possible that it is the cause of, or contributing to, the patient’s clinical phenotype.

About 8% of the Ecuadorian population suffers some type of amputation of upper or lower limbs. Due to the high cost of a prosthesis and the fact that the salary of an average worker in the country reached 248 USD in August 2021, they experience a great labor disadvantage and only 17% of them are employed. Thanks to advances in 3D printing and the accessibility of bioelectric sensors, it is now possible to create economically accessible proposals. This work proposes the design of a hand prosthesis that uses electromyography (EMG) signals and neural networks for real-time control. The integrated system has a mechanical and electronic design, and the latter integrates artificial intelligence for control. To train the algorithm, an experimental methodology was developed to record muscle activity in upper extremities associated with specific tasks, using three EMG surface sensors. These data were used to train a five-layer neural network. the trained model was compressed and exported using TensorflowLite. The prosthesis consisted of a gripper and a pivot base, which were designed in Fusion 360 considering the movement restrictions and the maximum loads. It was actuated in real time thanks to the design of an electronic circuit that used an ESP32 development board, which was responsible for recording, processing and classifying the EMG signals associated with a motor intention, and to actuate the hand prosthesis. As a result of this work, a database with 60 electromyographic activity records from three tasks was released. The classification algorithm was able to detect the three muscle tasks with an accuracy of 78.67% and a response time of 80 ms. Finally, the 3D printed prosthesis was able to support a weight of 500 g with a safety factor equal to 15.

Agro-industrial residue valorization under the umbrella of the circular bioeconomy (CBE) has prompted the search for further forward-thinking alternatives that encourage the mitigation of the industry’s environmental footprint. From this perspective, second-life valorization (viz., thermoplastic composites) has been explored for agro-industrial waste (viz., oil palm empty fruit bunch fibers, OPEFBFs) that has already been used previously in other circular applications (viz., the removal of domestic wastewater contaminants). Particularly, this ongoing study evaluated the performance of raw residues (R-OPEFBFs) within three different size ranges (250–425, 425–600, 600–800 µm) both before and after their utilization in biofiltration processes (as post-adsorbents, P-OPEFBFs) to reinforce a polymer matrix of acrylic resin. The research examined the changes in R-OPEFBF composition and morphology caused by microorganisms in the biofilters and their impact on the mechanical properties of the composites. Smaller R-OPEFBFs (250–425 µm) demonstrated superior mechanical performance. Additionally, the composites with P-OPEFBFs displayed significant enhancements in their mechanical properties (3.9–40.3%) compared to those with R-OPEFBFs. The combination of the three fiber sizes improved the mechanical behavior of the composites, indicating the potential for both R-OPEFBFs and P-OPEFBFs as reinforcement materials in composite applications.

AbstractBackgroundAnaplastic astrocytoma is a rare disorder in children from 10 to 14 years of age, with an estimated 0.38 new cases per 100,000 people per year worldwide. Panel-based next-generation sequencing opens new possibilities for diagnosis and therapy of rare diseases such as this one. Because it has never been genetically studied in the Ecuadorian population, we chose to genetically characterize an Ecuadorian pediatric patient with anaplastic astrocytoma for the first time. Doing so allows us to provide new insights into anaplastic astrocytoma diagnosis and treatment.Case presentationOur patient was a 13-year-old Mestizo girl with an extensive family history of cancer who was diagnosed with anaplastic astrocytoma. According to ClinVar, SIFT, and PolyPhen, the patient harbored 354 genomic alterations in 100 genes. These variants were mostly implicated in deoxyribonucleic acid (DNA) repair. The top five most altered genes wereFANCD2,NF1,FANCA,FANCI, andWRN.Even thoughTP53presented only five mutations, the rs11540652 single-nucleotide polymorphism classified as pathogenic was found in the patient and her relatives; interestingly, several reports have related it to Li-Fraumeni syndrome. Furthermore,in silicoanalysis using the Open Targets Platform revealed two clinical trials for pediatric anaplastic astrocytoma (studying cabozantinib, ribociclib, and everolimus) and 118 drugs that target the patient’s variants, but the studies were not designed specifically to treat pediatric anaplastic astrocytoma.ConclusionsNext-generation sequencing allows genomic characterization of rare diseases; for instance, this study unraveled a pathogenic single-nucleotide polymorphism related to Li-Fraumeni syndrome and identified possible new drugs that specifically target the patient’s variants. Molecular tools should be implemented in routine clinical practice for early detection and effective preemptive intervention delivery and treatment.

Osteosarcoma is the most common type of primary malignant bone tumor. Although nowadays 5-year survival rates can reach up to 60–70%, acute complications and late effects of osteosarcoma therapy are two of the limiting factors in treatments. We developed a multi-objective algorithm for the repurposing of new anti-osteosarcoma drugs, based on the modeling of molecules with described activity for HOS, MG63, SAOS2, and U2OS cell lines in the ChEMBL database. Several predictive models were obtained for each cell line and those with accuracy greater than 0.8 were integrated into a desirability function for the final multi-objective model. An exhaustive exploration of model combinations was carried out to obtain the best multi-objective model in virtual screening. For the top 1% of the screened list, the final model showed a BEDROC = 0.562, EF = 27.6, and AUC = 0.653. The repositioning was performed on 2218 molecules described in DrugBank. Within the top-ranked drugs, we found: temsirolimus, paclitaxel, sirolimus, everolimus, and cabazitaxel, which are antineoplastic drugs described in clinical trials for cancer in general. Interestingly, we found several broad-spectrum antibiotics and antiretroviral agents. This powerful model predicts several drugs that should be studied in depth to find new chemotherapy regimens and to propose new strategies for osteosarcoma treatment.

Background: Breast cancer (BRCA) and prostate cancer (PRCA) are the most commonly diagnosed cancer types in Latin American women and men, respectively. Although in recent years large-scale efforts from international consortia have focused on improving precision oncology, a better understanding of genomic features of BRCA and PRCA in developing regions and racial/ethnic minority populations is still required.Methods: To fill in this gap, we performed integrated in silico analyses to elucidate oncogenic variants from BRCA and PRCA driver genes; to calculate their deleteriousness scores and allele frequencies from seven human populations worldwide, including Latinos; and to propose the most effective therapeutic strategies based on precision oncology.Results: We analyzed 339,100 variants belonging to 99 BRCA and 82 PRCA driver genes and identified 18,512 and 15,648 known/predicted oncogenic variants, respectively. Regarding known oncogenic variants, we prioritized the most frequent and deleterious variants of BRCA (n = 230) and PRCA (n = 167) from Latino, African, Ashkenazi Jewish, East Asian, South Asian, European Finnish, and European non-Finnish populations, to incorporate them into pharmacogenomics testing. Lastly, we identified which oncogenic variants may shape the response to anti-cancer therapies, detailing the current status of pharmacogenomics guidelines and clinical trials involved in BRCA and PRCA cancer driver proteins.Conclusion: It is imperative to unify efforts where developing countries might invest in obtaining databases of genomic profiles of their populations, and developed countries might incorporate racial/ethnic minority populations in future clinical trials and cancer researches with the overall objective of fomenting pharmacogenomics in clinical practice and public health policies.

Transportation is the major contributor of ever-increasing CO2 and Greenhouse Gas emissions in cities. The ever-increasing hazardous emissions of transportation and energy consumption have persuaded transportation and urban planners to motivate people to non-motorized mode of travel, especially walking. Currently, there are several urban walkability assessment models; however, coping with a limited range of walkability assessment variables make these models not fully able to promote inclusive walkable urban neighborhoods. In this regard, this study develops the path walkability assessment (PWA) index model which evaluates and analyzes path walkability in association with the pedestrian’s decision-tree-making (DTM). The model converts the pedestrian’s DTM qualitative data to quantifiable values. This model involves ninety-two (92) physical and environmental walkability assessment variables clustered into three layers of DTM (Layer 1: features; Layer 2: Criteria; and Layer 3: Sub-Criteria), and scoped to shopping and retail type of walking. The PWA model as a global decision support tool can be applied in any neighborhood in the world, and this study implements it at Taman Universiti neighborhood in Skudai, Malaysia. The PWA model has established the walkability score index which determines the grading rate of walkability accomplishment for each walkability variable of the under-survey neighborhood. Using the PWA grading index enables urban designers to manage properly the financial resource allocation for inspiring walkability in the targeted neighborhood.