Application of the Methylated Markers (Spectrin Beta and DEAD-Box Protein) for Definitive Differentiation Between Fresh and Aged Semen by evaluating Their Role in Identifying Semen From Mixed Body Fluids

Background: Semen identification is assumed a crucial proof of sexual assault. Moreover, body fluids at the crime scene of a human being, such as blood, semen, and saliva, are often mixed.Methods: Hence, in our study, we aimed to use methylation analysis targeting DNA epigenetic markers Spectrin beta chain (B_SPTB_03) and DEAD-box protein (DDX4) to differentiate between fresh semen (less than 4 hours) and aged semen (after 24 hours) as well as to differentiate between semen alone and semen mixed with other body fluids (blood and saliva) in the fresh and dried state.Results: Our findings showed statistically significant differences in the methylation patterns of the SPTB and DDX4 loci to distinguish semen from mixed body fluids in fresh and old samples. We were able to obtain two novel cutoff values to differentiate between fresh and aged semen, which are (52.25) with the SPTB marker and (70.75) with the DDX4 marker. Conclusion: It is concluded that the methylation approach based on the epigenetic markers of Spectrin beta chain and DEAD-box protein (B_SPTB_03 and DDX4) successfully identified fresh from aged semen and semen-derived alleles from mixed stains, hence it is recommended to be employed in forensic practice

Convolutional Neural Network–Based Automatic Classification of Colorectal and Prostate Tumor Biopsies Using Multispectral Imagery: System Development Study

Background: Colorectal and prostate cancers are the most common types of cancer in men worldwide. To diagnose colorectal and prostate cancer, a pathologist performs a histological analysis on needle biopsy samples. This manual process is time-consuming and error-prone, resulting in high intra- and interobserver variability, which affects diagnosis reliability. Objective: This study aims to develop an automatic computerized system for diagnosing colorectal and prostate tumors by using images of biopsy samples to reduce time and diagnosis error rates associated with human analysis. Methods: In this study, we proposed a convolutional neural network (CNN) model for classifying colorectal and prostate tumors from multispectral images of biopsy samples. The key idea was to remove the last block of the convolutional layers and halve the number of filters per layer. Results: Our results showed excellent performance, with an average test accuracy of 99.8% and 99.5% for the prostate and colorectal data sets, respectively. The system showed excellent performance when compared with pretrained CNNs and other classification methods, as it avoids the preprocessing phase while using a single CNN model for the whole classification task. Overall, the proposed CNN architecture was globally the best-performing system for classifying colorectal and prostate tumor images. Conclusions: The proposed CNN architecture was detailed and compared with previously trained network models used as feature extractors. These CNNs were also compared with other classification techniques. As opposed to pretrained CNNs and other classification approaches, the proposed CNN yielded excellent results. The computational complexity of the CNNs was also investigated, and it was shown that the proposed CNN is better at classifying images than pretrained networks because it does not require preprocessing. Thus, the overall analysis was that the proposed CNN architecture was globally the best-performing system for classifying colorectal and prostate tumor images

Prevalence of anti-BK polyomavirus IgG in A Sample of Iraqi renal transplant recipients

Background: BK virus, a human polyomavirus, causes nephropathy and allograft loss in renal transplant recipients. Although it was discovered in 1971, understanding of the humoral immune response to BKV is limited. Objective: To serological detection and level estimation of anti-BK-IgG in renal-transplanted recipients and healthy blood donors as control. Patients and Methods: Serum samples were collected from 106 renal transplant recipient patients and 100 healthy  blood donors as control groups, and were analyzed for anti-BK IgG antibodies by using quantitative and qualitative Human BK Virus IgG (BK-IgG) ELISA kit for detection and estimation positivity of BK_IgG and titration. Results: Out of 206 subjects, 114(55.3%) have a positive result for BK-IgG. seropositivity was detected in 54(50.9%) of 106 RTR patients and 60 (60.0%) in the 100 control group, so there was no significant difference between seropositivity of BKV IgG antibody among the studied groups, p =0.191. Conclusion: The highly significant differences between seropositivity of BK-IgG with high levels of serum creatinine

Assessment and Management of Atopic Dermatitis in Primary Care Settings

An increasingly common chronic inflammatory skin condition is atopic dermatitis (AD). It exhibits severe itching as well as recurring eczematous lesions. New difficulties for treatment selection and approach occur with the expansion of available therapy alternatives for healthcare professionals and patients.  The article highlights recent developments in scientific research on atopic dermatitis diagnosis and assessment that have led to the identification of novel therapeutic targets and the development of targeted therapies, both of which have the potential to completely change the way AD is treated, particularly in a primary care setting

Assessment and Management of Scabies in Primary Care Settings

Scabies is an overlooked tropical illness that yet has significant worldwide effects and lasting health repercussions. The condition is caused by the mite Sarcoptes scabei var. hominis, which is a parasitic organism that dwells on the outer layer of the human skin. Scabies is prevalent in impoverished neighborhoods as a result of the high population density in locations such as nursing homes, correctional facilities, and among homeless and displaced children. Nevertheless, modern nations are also prone to scabies infestations, particularly in cases of institutional outbreaks or mini epidemics occurring after conflict or natural calamities. Scabies diagnosis can be aided by both invasive and noninvasive techniques. This paper reviews assessment diagnosis, and management of scabies in primary health care settings

Transition to IFRS and compliance with mandatory disclosure requirements: What is the signal?

The present study examines 153 Greek listed companies' compliance with all IFRS mandatory disclosure requirements during 2005 and complements and extends prior literature in the following way. The unique setting i.e., measuring compliance with IFRS mandatory disclosure requirements during the first year of IFRS implementation, allows for examination of the possibility that the changes in the 2004 shareholders' equity and net income, as a result of the adoption of IFRS, constitute explanatory factors for compliance. Thus, this study hypothesises that, in addition to the financial measures and other corporate characteristics that prior literature identifies as proxies for explaining compliance, a significant change in fundamental financial measures, because of the change in the accounting regime, may also explain compliance based on the premises of the relevant disclosure theories. The findings confirm these hypotheses. This study also makes a methodological contribution on measuring compliance with all IFRS mandatory disclosure requirements by using two different disclosure index methods and pointing out the different conclusions may be drawn as a result

Mucormycosis co-infection in COVID-19 patients: An update

Mucormycosis (MCM) is a rare fungal disorder that has recently been increased in parallel with novel COVID-19 infection. MCM with COVID-19 is extremely lethal, particularly in immunocompromised individuals. The collection of available scientific information helps in the management of this co-infection, but still, the main question on COVID-19, whether it is occasional, participatory, concurrent, or coincidental needs to be addressed. Several case reports of these co-infections have been explained as causal associations, but the direct contribution in immunocompromised individuals remains to be explored completely. This review aims to provide an update that serves as a guide for the diagnosis and treatment of MCM patients’ co-infection with COVID-19. The initial report has suggested that COVID-19 patients might be susceptible to developing invasive fungal infections by different species, including MCM as a co-infection. In spite of this, co-infection has been explored only in severe cases with common triangles: diabetes, diabetes ketoacidosis, and corticosteroids. Pathogenic mechanisms in the aggressiveness of MCM infection involves the reduction of phagocytic activity, attainable quantities of ferritin attributed with transferrin in diabetic ketoacidosis, and fungal heme oxygenase, which enhances iron absorption for its metabolism. Therefore, severe COVID-19 cases are associated with increased risk factors of invasive fungal co-infections. In addition, COVID-19 infection leads to reduction in cluster of differentiation, especially CD4+ and CD8+ T cell counts, which may be highly implicated in fungal co-infections. Thus, the progress in MCM management is dependent on a different strategy, including reduction or stopping of implicit predisposing factors, early intake of active antifungal drugs at appropriate doses, and complete elimination via surgical debridement of infected tissues

A novel fast Otsu digital image segmentation method

Steganography is the art of hiding user information in various file types including image, audio and video. Security of steganography lies in imperceptibility of secret information in the cover image. Human Visual System (HVS) is not able to detect the changes in low color values of an image. To the best of our knowledge, none of the available steganographic techniques have exploited this weakness of HVS. In this paper, a new LSB technique is presented which hides information in the cover image taking into account the pixel value of color or grey level of every pixel. Our experiments show that the proposed technique has a high payload and low perceptibility of secret information hidden in the cover image as compared to the existing Least Significant Bit (LSB) based algorithms. We have used MATLAB for the implementation of proposed algorithm