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Imbalance of oxidants/antioxidants results in heart failure, contributing to mortality after burn injury. Cardiac mitochondria are a prime source of ROS, and a mitochondrial-specific antioxidant may improve burn-induced cardiomyopathy. We hypothesize that the mitochondrial-specific antioxidant, Mito-TEMPO, could protect cardiac function after burn.

Male rats had a 60% TBSA scald burn injury and were treated with/without Mito-TEMPO (7 mg·kg-1, ip) and harvested at 24 hours post burn. Echocardiography (ECHO) was employed for measurement of heart function. Masson Trichrome and H & E staining were used for cardiac fibrosis and immune response. O2K system assessed mitochondria function in vivo. qPCR was used for mitochondrial DNA replication and gene expression.

Burn-induced cardiac dysfunction, fibrosis, and mitochondrial damage were assessed by measurement of mitochondrial function, DNA replication, and DNA-encoded ETC-related gene expression. Mito-TEMPO partially improved the abnormal parameters. Burn-induced cardiac dysfunction was associated with crosstalk between the NFE2L2-ARE pathway, PDE5A-PKG pathway, PARP1-POLG-mtDNA replication pathway, and mitochondrial SIRT signaling.

Mitochondrial-specific antioxidant (Mito-TEMPO) reversed burn-induced cardiac dysfunction by rescuing cardiac mitochondrial dysfunction. Mitochondria-targeted antioxidants may be an effective therapy for burn-induced cardiac dysfunction.

Mitochondrial-specific antioxidant (Mito-TEMPO) reversed burn-induced cardiac dysfunction by rescuing cardiac mitochondrial dysfunction. Mitochondria-targeted antioxidants may be an effective therapy for burn-induced cardiac dysfunction.Previously we developed and characterized a novel hydrogel film wound dressing containing Sodium Alginate and Pectin loaded with Simvastatin with multi-functional properties. This study investigated the in-vivo efficacy of the developed wound dressing on type I diabetic wound model. Experiments were performed on male Wistar rats for the period of 21-days. Animals developed diabetes after intraperitoneal injection (50 mg/kg) of Streptozotocin then randomly divided into different groups. On days 7, 14, and 21 of post-wounding, animals were euthanized and the wounds tissue were harvested for analysis. The wound healing rate, hematology and histological analysis, hydroxyproline assay, and Vascular Endothelial Growth Factor A measurements were noted. The results revealed that the wound dressing healed the wounded area significantly (p less then 0.05) higher than the control after 21-day treatment and wound closure was ~99% without any adverse systemic reactions. Histological analysis qualitatively revealed an enhanced re-epithelialization and collagen deposition. Moreover, results also showed an improved rate of collagen synthesis and angiogenesis in the group treated with the hydrogel film loaded with Simvastatin. Thus, the present study demonstrated that developed film holds great potential for the acceleration of diabetic wound healing by its pro-angiogenic effect, faster re-epithelialization and increased collagen deposition.Homologous recombination (HR) is essential for maintenance of genome integrity. Rad51 paralogs fulfill a conserved but undefined role in HR, and their mutations are associated with increased cancer risk in humans. Here, we use single-molecule imaging to reveal that the Saccharomyces cerevisiae Rad51 paralog complex Rad55-Rad57 promotes assembly of Rad51 recombinase filament through transient interactions, providing evidence that it acts like a classical molecular chaperone. Srs2 is an ATP-dependent anti-recombinase that downregulates HR by actively dismantling Rad51 filaments. Contrary to the current model, we find that Rad55-Rad57 does not physically block the movement of Srs2. Instead, Rad55-Rad57 promotes rapid re-assembly of Rad51 filaments after their disruption by Srs2. Our findings support a model in which Rad51 is in flux between free and single-stranded DNA (ssDNA)-bound states, the rate of which is controlled dynamically though the opposing actions of Rad55-Rad57 and Srs2.

To determine whether inorganic nitrite improves peripheral and pulmonary oxygen (O

) transport during exercise in heart failure with preserved ejection fraction (HFpEF).

Data from two invasive, randomized, double-blind, placebo-controlled trials with matched workload exercise of inhaled and intravenous sodium nitrite were pooled for this analysis (n= 51). Directly measured O

consumption (VO

) and blood gas data were used to evaluate the effect of nitrite on skeletal muscle O

conductance (Dm), VO

kinetics, alveolar capillary membrane O

conductance (D

), and O

utilization during submaximal exercise. As compared to placebo, treatment with nitrite resulted in an improvement in Dm (+4.9± 6.5 vs. -0.9± 4.3mL/mmHg*min, P= 0.0008) as well as VO

kinetics measured by mean response time (-5.0± 6.9 vs. -0.6± 6.0s, P= 0.03), with preserved O

utilization despite increased convective O

delivery through cardiac output (+0.4± 0.7 vs. -0.3± 0.9L/min, P= 0.02). Pancuronium dibromide Nitrite improved D

(+2.5± 6.3 vs. -2.0± 9.0mL/mmHg*min, P= 0.05) with exercise, which was associated with lower pulmonary capillary pressures (r=-0.34, P= 0.02), and reduced pulmonary dead space ventilation fraction (-0.01 ± 0.05 vs. +0.02 ± 0.05, P= 0.02).

Sodium nitrite enhances skeletal muscle Dm during exercise as well as pulmonary O

diffusion, optimizing O

kinetics in tandem with increased convective O

delivery through cardiac output augmentation. The favourable combined pulmonary, cardiac and peripheral effects of nitrite may improve exercise tolerance in people with HFpEF and requires further investigation.

ClinicalTrials.gov ID NCT01932606 and NCT02262078.

ClinicalTrials.gov ID NCT01932606 and NCT02262078.Artificial intelligence (AI) utilizes computer algorithms to carry out tasks with human-like intelligence. Convolutional neural networks, a type of deep learning AI, can classify basal cell carcinoma, seborrheic keratosis, and conventional nevi, highlighting the potential for deep learning algorithms to improve diagnostic workflow in dermatopathology of highly routine diagnoses. Additionally, convolutional neural networks can support the diagnosis of melanoma and may help predict disease outcomes. Capabilities of machine learning in dermatopathology can extend beyond clinical diagnosis to education and research. Intelligent tutoring systems can teach visual diagnoses in inflammatory dermatoses, with measurable cognitive effects on learners. Natural language interfaces can instruct dermatopathology trainees to produce diagnostic reports that capture relevant detail for diagnosis in compliance with guidelines. Furthermore, deep learning can power computation- and population-based research. However, there are many limitations of deep learning that need to be addressed before broad incorporation into clinical practice.