Treatments for Pyoderma Gangrenosum: A Systematic Review and Single-Arm Meta-Analysis of Systemic Therapies.

Pyoderma gangrenosum (PG) is a neutrophilic dermatosis associated with significant morbidity and mortality, with no consensus treatment to date. To review all clinical trials of treatments for PG to synthesise clinical evidence regarding the efficacy and safety of different treatments. After PROSPERO (CRD42023459180) registration, we systematically searched five databases (clinicaltrials.

Fibrothecoma/Fibroma of ovary-rare ovarian tumors with varied presentation and different modes of management: 14 years' experience from tertiary care hospitals.

Context: Fibrothecomas are a rare group of tumors of stromal cell origin, accounting for approximately 5%-8% of all ovarian tumors. These tumors are frequently mistaken as malignant due to solid consistency, association with ascites, and pleural effusion leading to unnecessary radical surgery. Due to the relative rarity of these tumors, we want to highlight eleven cases of fibrothecoma/fibromas encountered in our experience with different clinical presentations in various age groups requiring different treatment strategies based on the clinical, radiological, cytological, histopathological, and immunochemical characteristics.

Novel AP39-Loaded Liposomes Sustain the Release of Hydrogen Sulphide, Enhance Blood-Brain Barrier Permeation, and Abrogate Oxidative Stress-Induced Mitochondrial Dysfunction in Brain Cells.

Background: Neurodegenerative diseases are often linked to oxidative stress (OS), which worsen neuroinflammation and cause neuronal damage. Managing OS with gasotransmitters such as hydrogen sulphide (HS) is a promising therapeutic approach to protecting brain cells from oxidative damage. AP39, a mitochondria-targeted HS donor, has shown neuroprotective potential by reducing OS and improving mitochondrial function.

DARNet: Deep Attention Module and Residual Block-Based Lung and Colon Cancer Diagnosis Network.

Accurate and efficient lung and colon cancer classification is vital for early detection and treatment planning. Traditional methods require manual effort and expert analysis, leading researchers to explore deep learning models. However, deep learning-based lung and colon cancer classification models face challenges such as generalization, overfitting, gradient vanishing, and hyperparameter tuning.

Epistasis of ERAP1 With 4 Major Histocompatibility Complex Class I Alleles in Frontal Fibrosing Alopecia: A Genome-Wide Association Study Meta-Analysis.

Importance: Frontal fibrosing alopecia (FFA) is an inflammatory and scarring form of hair loss of increasing prevalence that most commonly affects women. An improved understanding of the genetic basis of FFA will support the identification of pathogenic mechanisms and therapeutic targets.

Objective: To identify novel genomic loci at which common genetic variation affects FFA susceptibility and assess nonadditive effects on genetic risk between susceptibility loci.

Topical corticosteroid powder for peristomal pyoderma gangrenosum: a systematic review.

Background: Peristomal pyoderma gangrenosum (PPG) is a critical complication after surgical ileostomy or colostomy placement. While topical treatments are often effective, most of the available vehicles reduce ostomy pouch adhesion. There are no commercially available corticosteroid powders for topical application; however, using powder from crushed corticosteroid tablets or capsules may circumvent this issue.

Pseudomyxoma peritonei leading to "jelly belly" abdomen: a case report and review of the literature.

Background: Pseudomyxoma peritonei is an infrequent condition with a global annual incidence of only one to two cases per million people. Mucinous neoplasms, widespread intraperitoneal implants, and mucinous ascites characterize it. Currently, most clinicians misdiagnose this condition, which leads to delayed management.

DengueFog: A Fog Computing-Enabled Weighted Random Forest-Based Smart Health Monitoring System for Automatic Dengue Prediction.

Dengue is a distinctive and fatal infectious disease that spreads through female mosquitoes called Aedes aegypti. It is a notable concern for developing countries due to its low diagnosis rate. Dengue has the most astounding mortality level as compared to other diseases due to tremendous platelet depletion.

Deep Drug Synergy Prediction Network Using Modified Triangular Mutation-Based Differential Evolution.

Drug combination therapy is crucial in cancer treatment, but accurately predicting drug synergy remains a challenge due to the complexity of drug combinations. Machine learning and deep learning models have shown promise in drug combination prediction, but they suffer from issues such as gradient vanishing, overfitting, and parameter tuning. To address these problems, the deep drug synergy prediction network, named as EDNet is proposed that leverages a modified triangular mutation-based differential evolution algorithm.

A single-center review of outcomes between COVID-19 vaccinated and unvaccinated liver transplant recipients.

Background: With the availability of vaccines against SARS-COV-2, recommendations for vaccination of transplant candidates are widespread. At our institution, patients may receive liver transplant (LTx) regardless of vaccine status. The purpose of this study is to compare post-LTx outcomes between vaccinated (VAX) and unvaccinated (UNVAX) LTx recipients.

Comparison of outcomes in vaccinated versus unvaccinated COVID-19 kidney transplant recipients, a single center retrospective study-Is the taboo justified?

Introduction: We assessed differences in the post-transplant outcomes between COVID-19 vaccinated and unvaccinated Kidney transplant (KTx) recipients.

Methods: We conducted a retrospective, single-center study of 400 KTx from 2/1/2021 to 4/30/2022 with 6-21 months follow-up. Primary outcomes included differences in the incidence of post-transplant COVID-19, ICU admission for COVID-19, death, and graft failure between the two groups.

Efficient Skip Connections-Based Residual Network (ESRNet) for Brain Tumor Classification.

Brain tumors pose a complex and urgent challenge in medical diagnostics, requiring precise and timely classification due to their diverse characteristics and potentially life-threatening consequences. While existing deep learning (DL)-based brain tumor classification (BTC) models have shown significant progress, they encounter limitations like restricted depth, vanishing gradient issues, and difficulties in capturing intricate features. To address these challenges, this paper proposes an efficient skip connections-based residual network (ESRNet).

DSCNet: Deep Skip Connections-Based Dense Network for ALL Diagnosis Using Peripheral Blood Smear Images.

Acute lymphoblastic leukemia (ALL) is a life-threatening hematological malignancy that requires early and accurate diagnosis for effective treatment. However, the manual diagnosis of ALL is time-consuming and can delay critical treatment decisions. To address this challenge, researchers have turned to advanced technologies such as deep learning (DL) models.

Outcomes After Deceased Donor Kidney Transplantation Using Kidney Allografts With Marginal Perfusion Parameters.

Background: This study examines outcomes of deceased donor kidney transplantation (DDKT) in recipients of kidney allografts with marginal perfusion parameters.

Methods: Allografts with marginal perfusion parameters (resistance index [RI] >0.4 and pump flow rate [F] <70 mL/min; MP group) were compared with those with good parameters (RI <0.

Cytological and histopathological features of recurrent calcifying aponeurotic fibroma of neck in an adolescent male-rare presentation of a rare tumour.

Calcifying aponeurotic fibroma is a rare benign but locally aggressive soft tissue tumour. It is most commonly seen in distal extremities and very rarely seen in head and neck region. In this case report, we describe both cytological and histological features of this tumour in a young adolescent male.