Enhancing image captioning with depth information using a Transformer-based framework

Captioning images is a challenging scene-understanding task that connects computer vision and natural language processing. While image captioning models have been successful in producing excellent descriptions, the field has primarily focused on generating a single sentence for 2D images. This paper investigates whether integrating depth information with RGB images can enhance the captioning task and generate better descriptions. For this purpose, we propose a Transformer-based encoder-decoder framework for generating a multi-sentence description of a 3D scene. The RGB image and its corresponding depth map are provided as inputs to our framework, which combines them to produce a better understanding of the input scene. Depth maps could be ground truth or estimated, which makes our framework widely applicable to any RGB captioning dataset. We explored different fusion approaches to fuse RGB and depth images. The experiments are performed on the NYU-v2 dataset and the Stanford image paragraph captioning dataset. During our work with the NYU-v2 dataset, we found inconsistent labeling that prevents the benefit of using depth information to enhance the captioning task. The results were even worse than using RGB images only. As a result, we propose a cleaned version of the NYU-v2 dataset that is more consistent and informative. Our results on both datasets demonstrate that the proposed framework effectively benefits from depth information, whether it is ground truth or estimated, and generates better captions. Code, pre-trained models, and the cleaned version of the NYU-v2 dataset will be made publically available.Comment: 19 pages, 5 figures, 13 table

A comprehensive analysis of genetic risk for metabolic syndrome in the Egyptian population via allele frequency investigation and Missense3D predictions

Abstract Diabetes mellitus (DM) represents a major health problem in Egypt and worldwide, with increasing numbers of patients with prediabetes every year. Numerous factors, such as obesity, hyperlipidemia, and hypertension, which have recently become serious concerns, affect the complex pathophysiology of diabetes. These metabolic syndrome diseases are highly linked to genetic variability that drives certain populations, such as Egypt, to be more susceptible to developing DM. Here we conduct a comprehensive analysis to pinpoint the similarities and uniqueness among the Egyptian genome reference and the 1000-genome subpopulations (Europeans, Ad-Mixed Americans, South Asians, East Asians, and Africans), aiming at defining the potential genetic risk of metabolic syndromes. Selected approaches incorporated the analysis of the allele frequency of the different populations’ variations, supported by genotypes’ principal component analysis. Results show that the Egyptian’s reference metabolic genes were clustered together with the Europeans’, Ad-Mixed Americans’, and South-Asians’. Additionally, 8563 variants were uniquely identified in the Egyptian cohort, from those, two were predicted to cause structural damage, namely, CDKAL1: 6_21065070 (A > T) and PPARG: 3_12351660 (C > T) utilizing the Missense3D database. The former is a protein coding gene associated with Type 2 DM while the latter is a key regulator of adipocyte differentiation and glucose homeostasis. Both variants were detected heterozygous in two different Egyptian individuals from overall 110 sample. This analysis sheds light on the unique genetic traits of the Egyptian population that play a role in the DM high prevalence in Egypt. The proposed analysis pipeline -available through GitHub- could be used to conduct similar analysis for other diseases across populations

Phytochemical Screening, Gas Chromatography-mass Spectrometry Analysis, and Antidiabetic Effects of Corchorus olitorius Leaves in Rats

BACKGROUND: Therapies for diabetes mellitus are still meeting failure in most cases, especially in the developed stages of the disease due to incredible associating complications. Hence, there is a need for continuous development of curative therapies for that stubborn disease. AIM: We aimed to investigate the antidiabetic effects of one of the most popular plants cultivated in Egypt, C. olitorius. METHODS: Phytochemical screening of total alcoholic extract of Corchorus olitorius leaves and its aqueous and chloroform fractions revealed the presence of flavonoids, saponins, carbohydrates, tannins, coumarins, and alkaloids. RESULTS: The gas chromatography-mass spectrometry analysis showed the presence of 12 and nine chemical compounds in aqueous and chloroform extracts, respectively. C. olitorius decreased serum glucose level and α-amylase activity. This effect was more pronounced in the total alcoholic extract and its chloroform fraction than the aqueous one. The extracts also adjusted the lipid profile, reduced liver injury parameters, and caused remarkable improvement and increase number, size, and density of functioning β-cells. CONCLUSION: The findings suggest the antihyperglycemic and antioxidant effects of C. olitorius besides its beneficial effect on diabetic complications such as hyperlipidemia and liver injury. The presence of some phytochemicals such as theophylline, trans-2, 3-dimethoxycinnamic acid, 7-hydroxy-4-methyl coumarin, apigenin 7-glucoside, and glycitein may contribute to such pharmacological effects

Cancer Cells Treated by Clusters of Copper Oxide Doped Calcium Silicate

Purpose: Different compositions of copper oxide (CuO)-doped calcium silicate clusters wereused to treat the cancer cells.Methods: The influence of CuO content on the morphology, drug delivering ability,physicochemical properties and cytotoxicity was investigated.Results: The microcrystalline structure revealed the decrement of the size from (20-36 nm) to(5-7 nm) depending on the copper content percentages. Drug delivering ability of doxycyclinehyclate (Dox) was down regulated from 58% to 28%in the presence of the CuO. The inclusionof CuO and Dox didn’t show any remarkable changes on the physicochemical properties of theCuO-doped calcium silicate nanoparticles.Conclusion: The CuO-doped calcium silicate sample (5 weight %) exhibited great cytotoxicityagainst the tested cell lines compared to the CuO-free sample. CuO-doped materials displayedsignificant anticancer effect; this sheds light on its implication in the treatment of cancer

Oropharyngeal Candidiasis among Egyptian COVID-19 Patients: Clinical Characteristics, Species Identification, and Antifungal Susceptibility, with Disease Severity and Fungal Coinfection Prediction Models

The study aimed to investigate the causative species, antifungal susceptibility, and factors associated with oropharyngeal candidiasis (OPC) among Egyptian COVID-19 patients. This is an observational, case-controlled, single-center study that included three groups: COVID-19 patients (30), COVID-19 patients with OPC (39), and healthy individuals (31). Patients’ demographic data (age, sex), laboratory tests, comorbidities, treatment, and outcomes were included. Candida species were isolated from COVID-OPC patient’s oropharyngeal swabs by convenient microbiological methods. Isolated strains were tested for antimicrobial susceptibility, biofilm production, aspartyl protease, and phospholipase activities. The most common respiratory symptoms reported were dyspnea (36/39; 92.4%) and cough (33/39; 84.7%). Candida albicans was the most common isolated species, accounting for 74.36% (29/39), followed by Candida tropicalis and Candida glabrata (15.38% and 10.26%, respectively). Amphotericin was effective against all isolates, while fluconazole was effective against 61.5%. A total of 53.8% of the isolates were biofilm producers. The phospholipase activity of C. albicans was detected among 58.6% (17/29) of the isolates. Significant variables from this study were used to create two equations from a regression model that can predict the severity of disease course and liability to fungal infection, with a stativity of 87% and 91%, respectively. According to our findings, COVID-19 patients with moderate to severe infection under prolonged use of broad-spectrum antibiotics and corticosteroids should be considered a high-risk group for developing OPC, and prophylactic measures are recommended to be included in the treatment protocols. In addition, due to the increased rate of fluconazole resistance, other new antifungals should be considered