Spleen autotransplantation on liver versus greater omentum for simultaneous injuries of liver and spleen: an experimental study.

Purpose: In a simulated situation of simultaneous spleen and liver trauma, we aimed to compare the outcomes of treating both injuries with spleen autotransplantation on the omentum (SAO) alongside hepatorrhaphy versus spleen autotransplantation as a patch on the liver parenchyma. Methods: A total of 24 rats were separated into two groups: the SAO and the spleen autotransplantation on the liver. They underwent a uniform and simultaneous procedure involving full-thickness injuries to the left lobe of the liver and grade 4 spleen injuries. We measured hemoglobin, white blood cell (WBC), complement (C3 and C4), and immunoglobulin G, M, and A (IgG, IgM, IgA) levels before and 4 weeks after the surgery. We utilized Technetium-99m scintigraphy to evaluate the posttransplant splenic graft functions 4 weeks after the surgery. Results: The two groups had no significant difference in the hematologic and immunologic factors before surgery. However, both procedures significantly reduced hemoglobin, C3, IgG, and IgA levels (all P<0.05). WBC counts significantly increased in the SAO group, whereas the IgM level decreased after the intervention (P<0.05). WBC was increased in the SAO group, while IgM and IgA were decreased in the SAO group. The Technetium uptake was similar between the two groups (P=0.3). Conclusions: In simultaneous spleen and liver injuries, the autotransplantation of splenic into the liver parenchyma appears to be a promising surgical approach for preserving spleen function and hepatorrhaphy at the same time instead of doing them separately.

Machine learning-enhanced surface plasmon resonance based photonic crystal fiber sensor.

This study introduces what we believe to be a novel photonic crystal fiber sensor utilizing surface plasmon resonance (SPR), incorporating four gold nanowires to enhance sensing capabilities. The research employs machine learning, specifically artificial neural networks (ANN), to predict confinement loss and sensitivity, achieving high accuracy without needing the imaginary part of the effective refractive index. The machine learning technique is applied in three different scenarios, resulting in mean squared errors of 0.084, 0.002, and 0.003, highlighting the reliability of the ANN models in predicting sensor outputs. Additionally, the sensor demonstrates impressive wavelength sensitivities of 2000-18000 nm/RIU (nanometers per refractive index unit) for refractive indices of 1.31-1.4 within the 720-1280 nm wavelength range, and a notable maximum amplitude sensitivity of 889.89 RIU-1. This integration of SPR, photonic crystal fiber, and machine learning not only optimizes sensor performance but also offers an efficient methodology for prediction, showcasing the potential of machine learning in advancing optical sensor design.

The Protective Effect of N-acetylcysteine against Deltamethrin-Induced Hepatotoxicity in Mice.

Background: Exposure to pesticides is of concern to public health officials worldwide. Deltamethrin is a synthetic pyrethroid pesticide which is widely used in agriculture and veterinary medicine. Deltamethrin poisoning is always one of the concerns in medical centers due to the deltamethrin induced hepatotoxicity. This study evaluated the hepato-protective effects of N-acetylcysteine (NAC) against deltamethrin induced hepatotoxicity in mice. Methods: A total of 40 BALB/c male mice were randomly divided into four groups; the first group was used as a control (0.5 ml normal saline); Groups 2-4 were treated with NAC [160 mg/kg Body Weight (BW)], deltamethrin (50 mg/kg BW), and NAC plus deltamethrin. At 1 and 24 hr after treatment, the animals were sacrificed and blood and liver samples were obtained for analysis and the liver/body ration, hepatic enzymes as Aspartate aminotransferase (AST), Alanine Transaminase (ALT), Alkaline phosphatase (ALP), Lactate dehydrogenase (LDH), Glutathione (GSH) content and Reactive Oxygen Species (ROS) level were measured. For comparison between more than two experimental groups, one-way ANOVA following Tukey test was used by SPSS software. Results: The deltamethrin significantly increased AST, ALT, ALP, and the level of ROS level at the end of 1 and 24 hr after treatment; while the LDH level and GSH content were decreased. Mice in the deltamethrin treated group had a higher liver/body weight ratio than in other treated groups after 24 hr. On the other hand, NAC in combination with deltamethrin significantly reduced the activities of AST, ALT, ALP, and increased GSH levels. Conclusion: This study demonstrated that NAC has a hepatoprotective role against deltamethrin-induced toxicity.

Acute Mesenteric Ischemia in a Patient with COVID-19: A Case Report.

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) presents clinical manifestations similar to the influenza, severe acute respiratory syndrome (SARS-CoV), and Middle East respiratory syndrome (MERS-CoV). However, in the course of the coronavirus disease 2019 (COVID-19), various pathological complications of high clinical significance have remained unknown. Impaired blood supply to the visceral vascular system can cause serious life-threatening acute damage. We report a case of extensive acute mesenteric ischemia associated with SARS-CoV-2 infection confirmed in a patient hospitalized in Amin Hospital - a COVID-19 referral center in Isfahan University of Medical Sciences, Isfahan, Iran. This case highlights the importance of paying attention to serious and less common or less known clinical manifestations other than fever, dry cough, dyspnea, and myalgia.

Scenario modeling for spatial-temporal change detection of carbon storage and sequestration in a forested landscape in Northern Iran.

The present study was conducted, based on scenario modeling approach, in the Do-hezar and Se-hezar forested landscape in the Mazandaran Province in Northern Iran in order to detect spatial-temporal changes of carbon storage and sequestration in four different carbon pools, i.e., aboveground and belowground biomasses, dead organic matter, and organic soils. For this purpose, firstly, the changing trend of land use/land cover (LULC) was detected by analyzing and comparing remotely sensed data of the landscape during the period of 1984-2016. Then, the impacts of future LULC changes on carbon storage and sequestration were predicted and valued using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model under two future plausible scenarios of business as usual (BAU) and balanced development (BD). According to the results of BAU scenario, continuation of the current trend will lead to a significant reduction in the carbon sequestration and a huge amount of social cost due to the loss of carbon stored in the landscape and its release to the atmosphere. The BD scenario which refers to the principled and under control development of human settlements simultaneously with forest conservational and restoration activities, could potentially reverse the downtrend of carbon sequestration service and avoid future socioeconomic costs, hence add to the economic value of the forest landscape in terms of providing a better sink for carbon storage. The results of this research can facilitate the quantitative and accurate assessment of carbon storage and sequestration relying on more precise biophysical and economic data as well as provide insight for effective land-use planning.