Dimensioning Cuboid and Cylindrical Objects Using Only Noisy and Partially Observed Time-of-Flight Data.

One of the challenges of using Time-of-Flight (ToF) sensors for dimensioning objects is that the depth information suffers from issues such as low resolution, self-occlusions, noise, and multipath interference, which distort the shape and size of objects. In this work, we successfully apply a superquadric fitting framework for dimensioning cuboid and cylindrical objects from point cloud data generated using a ToF sensor. Our work demonstrates that an average error of less than 1 cm is possible for a box with the largest dimension of about 30 cm and a cylinder with the largest dimension of about 20 cm that are each placed 1.5 m from a ToF sensor. We also quantify the performance of dimensioning objects using various object orientations, ground plane surfaces, and model fitting methods. For cuboid objects, our results show that the proposed superquadric fitting framework is able to achieve absolute dimensioning errors between 4% and 9% using the bounding technique and between 8% and 15% using the mirroring technique across all tested surfaces. For cylindrical objects, our results show that the proposed superquadric fitting framework is able to achieve absolute dimensioning errors between 2.97% and 6.61% when the object is in a horizontal orientation and between 8.01% and 13.13% when the object is in a vertical orientation using the bounding technique across all tested surfaces.

Probabilistic Modeling of Multicamera Interference for Time-of-Flight Sensors.

The behavior of multicamera interference in 3D images (e.g., depth maps), which is based on infrared (IR) light, is not well understood. In 3D images, when multicamera interference is present, there is an increase in the amount of zero-value pixels, resulting in a loss of depth information. In this work, we demonstrate a framework for synthetically generating direct and indirect multicamera interference using a combination of a probabilistic model and ray tracing. Our mathematical model predicts the locations and probabilities of zero-value pixels in depth maps that contain multicamera interference. Our model accurately predicts where depth information may be lost in a depth map when multicamera interference is present. We compare the proposed synthetic 3D interference images with controlled 3D interference images captured in our laboratory. The proposed framework achieves an average root mean square error (RMSE) of 0.0625, an average peak signal-to-noise ratio (PSNR) of 24.1277 dB, and an average structural similarity index measure (SSIM) of 0.9007 for predicting direct multicamera interference, and an average RMSE of 0.0312, an average PSNR of 26.2280 dB, and an average SSIM of 0.9064 for predicting indirect multicamera interference. The proposed framework can be used to develop and test interference mitigation techniques that will be crucial for the successful proliferation of these devices.

In Silico Identification of Peptides with PPARγ Antagonism in Protein Hydrolysate from Rice (Oryza sativa).

At least half the population in industrialized countries suffers from obesity due to excessive accumulation of adipose tissue. Recently, rice (Oryza sativa) proteins have been considered valuable sources of bioactive peptides with antiadipogenic potential. In this study, the digestibility and bioaccessibility in vitro of a novel protein concentrate (NPC) from rice were determined through INFOGEST protocols. Furthermore, the presence of prolamin and glutelin was evaluated via SDS-PAGE, and their potential digestibility and the bioactivity of ligands against peroxisome proliferator-activated receptor gamma (PPARγ) were explored by BIOPEP UWM and HPEPDOCK. For the top candidates, molecular simulations were conducted using Autodock Vina to evaluate their binding affinity against the antiadipogenic region of PPARγ and their pharmacokinetics and drug-likeness using SwissADME. Simulating gastrointestinal digestion showed a recovery of 43.07% and 35.92% bioaccessibility. The protein banding patterns showed the presence of prolamin (57 kDa) and glutelin (12 kDa) as the predominant proteins in the NPC. The in silico hydrolysis predicts the presence of three and two peptide ligands in glutelin and prolamin fraction, respectively, with high affinity for PPARγ (≤160). Finally, the docking studies suggest that the prolamin-derived peptides QSPVF and QPY (-6.38 & -5.61 kcal/mol, respectively) have expected affinity and pharmacokinetic properties to act as potential PPARγ antagonists. Hence, according to our results, bioactive peptides resulting from NPC rice consumption might have an antiadipogenic effect via PPARγ interactions, but further experimentation and validation in suitable biological model systems are necessary to gain more insight and to provide evidence to support our in silico findings.

Metformin May Alter the Metabolic Reprogramming in Cancer Cells by Disrupting the L-Arginine Metabolism: A Preliminary Computational Study.

Metabolic reprogramming in cancer is considered to be one of the most important hallmarks to drive proliferation, angiogenesis, and invasion. AMP-activated protein kinase activation is one of the established mechanisms for metformin's anti-cancer actions. However, it has been suggested that metformin may exert antitumoral effects by the modulation of other master regulators of cellular energy. Here, based on structural and physicochemical criteria, we tested the hypothesis that metformin may act as an antagonist of L-arginine metabolism and other related metabolic pathways. First, we created a database containing different L-arginine-related metabolites and biguanides. After that, comparisons of structural and physicochemical properties were performed employing different cheminformatic tools. Finally, we performed molecular docking simulations using AutoDock 4.2 to compare the affinities and binding modes of biguanides and L-arginine-related metabolites against their corresponding targets. Our results showed that biguanides, especially metformin and buformin, exhibited a moderate-to-high similarity to the metabolites belonging to the urea cycle, polyamine metabolism, and creatine biosynthesis. The predicted affinities and binding modes for biguanides displayed good concordance with those obtained for some L-arginine-related metabolites, including L-arginine and creatine. In conclusion, metabolic reprogramming in cancer cells by metformin and biguanides may be also driven by metabolic disruption of L-arginine and structurally related compounds.

Antidiabetic Drugs and their Potential Use in COVID-19: A Mechanistic Approach.

Many therapies have been developed against COVID-19 since it first appeared in December 2019. Antivirals, antimalarials, cephalosporins, colchicine, anticoagulants, and corticosteroids, among others, have been evaluated as protecting agents against antibacterial complications due to their anti-inflammatory and immunomodulatory effects against thrombosis and cell death caused by infection with SARS-CoV-2. Nevertheless, the overall balance in their application has not been found to be satisfactory. On the other hand, developing and applying several vaccines against this virus have marked an important watershed in preventive and prophylactic medicine in the new millennium. However, given the regular efficacy reported of some of them, the still scarce affordability, and the emergency of new strains for which no drug has been evaluated, the search for new pharmacological therapy alternatives still represents an essential component in the clinical management of COVID-19, and the rapid identification of drugs with potential antiviral and/or immunomodulatory properties is needed. In the present review, a potential therapeutic effect of metformin and other antidiabetic therapies for the management of COVID-19 are proposed and discussed from the viewpoint of their in vitro and in vivo immunomodulatory effects. Given that acute inflammation is an important component of COVID-19, antidiabetic therapies could be promising alternatives in its management and reducing the disease's severity. In order to understand how metformin and other antidiabetic therapies could work in the context of COVID-19, here we review the possible mechanisms of action through a detailed description of cellular and molecular events.

Acute gut microbiome changes after traumatic brain injury are associated with chronic deficits in decision-making and impulsivity in male rats.

The mechanisms underlying chronic psychiatric-like impairments after traumatic brain injury (TBI) are currently unknown. The goal of the present study was to assess the role of diet and the gut microbiome in psychiatric symptoms after TBI. Rats were randomly assigned to receive a high-fat diet (HFD) or calorie-matched low-fat diet (LFD). After 2 weeks of free access, rats began training on the rodent gambling task (RGT), a measure of risky decision-making and motor impulsivity. After training, rats received a bilateral frontal TBI or a sham procedure and continued postinjury testing for 10 weeks. Fecal samples were collected before injury and 3-, 30-, and 60 days postinjury to evaluate the gut microbiome. HFD altered the microbiome, but ultimately had low-magnitude effects on behavior and did not modify functional outcomes after TBI. Injury-induced functional deficits were far more robust; TBI substantially decreased optimal choice and increased suboptimal choice and motor impulsivity on the RGT. TBI also affected the microbiome, and a model comparison approach revealed that bacterial diversity measured 3 days postinjury was predictive of chronic psychiatric-like deficits on the RGT. A functional metagenomic analysis identified changes to dopamine and serotonin synthesis pathways as a potential candidate mechanism. Thus, the gut may be a potential acute treatment target for psychiatric symptoms after TBI, as well as a biomarker for injury and deficit severity. However, further research will be needed to confirm and extend these findings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

COVID-19 Myopericarditis With Pericardial Effusion Complicated With Cardiac Tamponade and Rhabdomyolysis.

COVID-19 infection is a complex multi-organ disease, including the cardiovascular system, which may present with myocarditis. A 42-year-old female presented to our ED with generalized weakness, myalgia, and epigastric pain. Laboratory workup showed a positive SARS-CoV-2 polymerase chain reaction (PCR). An ECG showed sinus tachycardia with low voltage. A bedside echocardiogram showed a pericardial effusion with cardiac tamponade. An emergent pericardiocentesis was performed with immediate hemodynamic improvement. The patient was admitted to the coronary care unit (CCU), and colchicine and ibuprofen were started for pericarditis. Pericardial fluid bacterial and fungal cultures were negative, and serum antinuclear antibodies were also negative. On day 5 of hospitalization, creatine kinase (CK) level was high compared to on presentation. COVID-induced rhabdomyolysis was suspected and was dramatically improved with IV fluids. The patient was discharged on day 7 of admission. Our case shows that COVID-19 can present with an uncommon presentation like cardiac tamponade. Further studies are warranted to better understand the pathogenesis and management of COVID-19 myopericarditis.

Probabilistic Modeling of Motion Blur for Time-of-Flight Sensors.

Synthetically creating motion blur in two-dimensional (2D) images is a well-understood process and has been used in image processing for developing deblurring systems. There are no well-established techniques for synthetically generating arbitrary motion blur within three-dimensional (3D) images, such as depth maps and point clouds since their behavior is not as well understood. As a prerequisite, we have previously developed a method for generating synthetic motion blur in a plane that is parallel to the sensor detector plane. In this work, as a major extension, we generalize our previously developed framework for synthetically generating linear and radial motion blur along planes that are at arbitrary angles with respect to the sensor detector plane. Our framework accurately captures the behavior of the real motion blur that is encountered using a Time-of-Flight (ToF) sensor. This work uses a probabilistic model that predicts the location of invalid pixels that are typically present within depth maps that contain real motion blur. More specifically, the probabilistic model considers different angles of motion paths and the velocity of an object with respect to the image plane of a ToF sensor. Extensive experimental results are shown that demonstrate how our framework can be applied to synthetically create radial, linear, and combined radial-linear motion blur. We quantify the accuracy of the synthetic generation method by comparing the resulting synthetic depth map to the experimentally captured depth map with motion. Our results indicate that our framework achieves an average Boundary F1 (BF) score of 0.7192 for invalid pixels for synthetic radial motion blur, an average BF score of 0.8778 for synthetic linear motion blur, and an average BF score of 0.62 for synthetic combined radial-linear motion blur.

Comparative Anticancer Activity and Molecular Docking of Different Isatin-Based Scaffolds.

BACKGROUND/AIM: To identify the best of three isatin-based scaffolds in terms of anticancer activity. MATERIALS AND METHODS: Synthesis of isatin-based scaffolds was performed through a reaction to form Schiff bases. In silico analyses consisted of a target prediction with the Swiss Target Prediction tool and a molecular docking by AutoDock Vina. Anticancer activity and cytotoxicity were determined using the WST1 viability assay. RESULTS: Three scaffolds (IA, IB, and IC) were synthesized and confirmed with good reaction yields. The Swiss Target Prediction tool showed a trend towards kinases. Molecular docking assays demonstrated higher affinity of IC towards CDK2. Anticancer activity assays identified IC as the most active against the cancer cell lines. Cytotoxicity results in non-cancer cells suggested a lack of selectivity. CONCLUSION: The scaffold IC was identified as the best in terms of anticancer activity and these effects may be due to inhibition of CDK2, as evidenced by molecular docking.

Cervical Cancer Screening with Human Papillomavirus Self-Sampling Among Transgender Men in El Salvador.

Purpose: Sexual and gender minority persons in low-income countries have very limited access to routine health services. This study evaluated the feasibility of using a self-sampled human papillomavirus (HPV) test to increase access to screening for cervical cancer among transgender men in El Salvador. Methods: We partnered with a local advocacy organization for recruitment. A total of 24 transgender men (men assigned female at birth) ages 19-55 were enrolled and provided consent. Questionnaires assessed sociodemographics, health and sexual histories, and knowledge about HPV and cervical cancer. Screening was performed with a self-sampled HPV test. Participants with a positive test were offered colposcopy and cryotherapy treatment, if appropriate. Those with a negative test were advised to return in 5 years for rescreening. Results: Out of 24 consenting participants, 23 (95.83%) agreed to conduct HPV self-sampling, and 22/23 (95.65%) expressed willingness to self-sample in the future. Among self-sampled individuals, 3/23 (13%) tested positive and accepted colposcopy and biopsy. Analyses of biopsied tissue revealed one case of cervical intraepithelial neoplasia grade 1. Conclusion: HPV self-sampling and subsequent procedures were accepted by the majority of participants. This screening method may be a viable alternative to cytology among transgender men in El Salvador.

Maintenance of the Austenite/Ferrite Ratio Balance in GTAW DSS Joints Through Process Parameters Optimization.

The present work describes the influence of the parameters employed in the gas tungsten arc welding process (GTAW) when nickel powder is used as a filler metal in 2304/2507 duplex stainless-steel dissimilar joints. Multi-objective optimization was applied in order to maintain the austenite/ferrite percentage in the welded zone. A microstructural and phase quantification analysis was performed in each sample through optical and scanning electron microscopes. It was found that a nickel powder addition combined with low heat input increased the biphasic ratio across the different zones of the dissimilar welded samples. Although the austenite volume fraction increased in the 2304 heat-affected zone (HAZ) near to 25%, it was not sufficient according to international standards. The obtained results led to the maintenance of the 50/50 phase percentage in the 2507 HAZ welded joint side, as well as to the increment of the austenite percentage in the 2304 HAZ.

Hybrid Assembly of the Genome of the Entomopathogenic Nematode Steinernema carpocapsae Identifies the X-Chromosome.

Entomopathogenic nematodes from the genus Steinernema are lethal insect parasites that quickly kill their insect hosts with the help of their symbiotic bacteria. Steinernema carpocapsae is one of the most studied entomopathogens due to its broad lethality to diverse insect species and its effective commercial use as a biological control agent for insect pests, as well as a genetic model for studying parasitism, pathogenesis, and symbiosis. In this study, we used long-reads from the Pacific Biosciences platform and BioNano Genomics Irys system to assemble the most complete genome of the S. carpocapsae ALL strain to date, comprising 84.5 Mb in 16 scaffolds, with an N50 of 7.36 Mb. The largest scaffold, with 20.9 Mb, was identified as chromosome X based on sex-specific genome sequencing. The high level of contiguity allowed us to characterize gene density, repeat content, and GC content. RNA-seq data from 17 developmental stages, spanning from embryo to adult, were used to predict 30,957 gene models. Using this improved genome, we performed a macrosyntenic analysis to Caenorhabditis elegans and Pristionchus pacificus and found S. carpocapsae's chromosome X to be primarily orthologous to C. elegans' and P. pacificus' chromosome II and IV. We also investigated the expansion of protein families and gene expression differences between adult male and female stage nematodes. This new genome and more accurate set of annotations provide a foundation for additional comparative genomic and gene expression studies within the Steinernema clade and across the Nematoda phylum.

Comparative Transcriptomics of Steinernema and Caenorhabditis Single Embryos Reveals Orthologous Gene Expression Convergence during Late Embryogenesis.

Cells express distinct sets of genes in a precise spatio-temporal manner during embryonic development. There is a wealth of information on the deterministic embryonic development of Caenorhabditis elegans, but much less is known about embryonic development in nematodes from other taxa, especially at the molecular level. We are interested in insect pathogenic nematodes from the genus Steinernema as models of parasitism and symbiosis as well as a satellite model for evolution in comparison to C. elegans. To explore gene expression differences across taxa, we sequenced the transcriptomes of single embryos of two Steinernema species and two Caenorhabditis species at 11 stages during embryonic development and found several interesting features. Our findings show that zygotic transcription initiates at different developmental stages in each species, with the Steinernema species initiating transcription earlier than Caenorhabditis. We found that ortholog expression conservation during development is higher at the later embryonic stages than at the earlier ones. The surprisingly higher conservation of orthologous gene expression in later embryonic stages strongly suggests a funnel-shaped model of embryonic developmental gene expression divergence in nematodes. This work provides novel insight into embryonic development across distantly related nematode species and demonstrates that the mechanisms controlling early development are more diverse than previously thought at the transcriptional level.

Trastornos hipertensivos del embarazo en sala de labor y parto del Hospital Escuela / Hypertensive Disorders of Pregnancy in the Labor and Delivery Ward of the Hospital Escuela

Los Trastornos Hipertensivos del Embarazo (THE) se caracterizan por presión arterial sistólica mayor o iguala 140 mm Hg o diastólica mayor o igual a 90 mm Hg. Representan la segunda causa de mortalidad materna en Honduras y provocan elevada morbimortalidad perinatal. Objetivo: Describir los datos clínico-epidemiológicos, evaluación, manejo y complicaciones materno-fetales de los trastornos hipertensivos del embarazo en el Hospital Escuela. Métodos:Estudio transversal, descriptivo, realizado del 16 de marzo al 26 de julio de 2010, se revisaron los expedientes clínicos de mujeres con diagnóstico de trastorno hipertensivo del embarazo, excluyendo los casos de hipertensión gestacional. Resultados: La prevalencia de los trastornos hipertensivos del embarazo es 7.8%, de estos 47% presentaron preeclampsia leve y 38% preeclampsia severa; se les realizó inducción y cesárea al 40% respectivamente. Se practicó cardiotocografía en reposo al 10.4% y prueba de provocación con oxitocina al 9%; se presentó crisis hipertensiva en el 35% de los casos. La principal complicación materna fue el Síndrome de HELLP y la principal complicación neonatal el Síndrome de Distrés Respiratorio (SDR), aproximadamente el 50% de los recién nacidos fueron pequeños para la edad gestacional. Se presentaron 8 muertes fetales, 11 muertes neonatales y una muerte materna. Conclusión: las mujeres con THE tienen el doble de riesgo de terminar su embarazo en cesárea comparado con las mujeres sin este trastorno. La mortalidad materna se asocia con eclampsia y Síndrome deHELLP (por sus siglas en inglés: H de hemolysis, EL de elevated liver enzymes y LP de low platelet count); la mortalidad perinatal con preeclampsia severa, APGAR menor a 7 al primer minuto, prematurez y restricción del crecimiento intrauterino...