1.2% Hydrogen gas inhalation protects the endothelial glycocalyx during hemorrhagic shock: a prospective laboratory study in rats.

PURPOSE: Hydrogen gas (H2) inhalation improved the survival rate of hemorrhagic shock. However, its mechanisms are unknown. We hypothesized that H2 protected the endothelial glycocalyx during hemorrhagic shock and prolonged survival time. METHODS: 83 Sprague-Dawley rats were anesthetized with isoflurane. The animals were randomly assigned to 5 groups: room air with no shock, 1.2% H2 with no shock, room air with shock (Control-S), 1.2% H2 with shock (H21.2%-S), and 3.0% H2 with shock (H23.0%-S). Shock groups were bled to a mean arterial pressure of 30-35 mmHg and held for 60 min, then resuscitated with normal saline at fourfold the amount of the shed blood volume. RESULTS: The syndecan-1 level was significantly lower in the H21.2%-S [8.3 ± 6.6 ng/ml; P = 0.01; 95% confidence interval (CI), 3.2-35.8] than in the Control-S (27.9 ± 17.0 ng/ml). The endothelial glycocalyx was significantly thicker in the H21.2%-S (0.15 ± 0.02 µm; P = 0.007; 95% CI, 0.02-0.2) than in the Control-S (0.06 ± 0.02 µm). The survival time was longer in the H21.2%-S (327 ± 67 min, P = 0.0160) than in the Control-S (246 ± 69 min). The hemoglobin level was significantly lower in the H21.2%-S (9.4 ± 0.5 g/dl; P = 0.0034; 95% CI, 0.6-2.9) than in the Control-S (11.1 ± 0.8 g/dl). However, the H23.0%-S was not significant. CONCLUSIONS: Inhalation of 1.2% H2 gas protected the endothelial glycocalyx and prolonged survival time during hemorrhagic shock. Therapeutic efficacy might vary depending on the concentration.

CarcassFormer: an end-to-end transformer-based framework for simultaneous localization, segmentation and classification of poultry carcass defect.

In the food industry, assessing the quality of poultry carcasses during processing is a crucial step. This study proposes an effective approach for automating the assessment of carcass quality without requiring skilled labor or inspector involvement. The proposed system is based on machine learning (ML) and computer vision (CV) techniques, enabling automated defect detection and carcass quality assessment. To this end, an end-to-end framework called CarcassFormer is introduced. It is built upon a Transformer-based architecture designed to effectively extract visual representations while simultaneously detecting, segmenting, and classifying poultry carcass defects. Our proposed framework is capable of analyzing imperfections resulting from production and transport welfare issues, as well as processing plant stunner, scalder, picker, and other equipment malfunctions. To benchmark the framework, a dataset of 7,321 images was initially acquired, which contained both single and multiple carcasses per image. In this study, the performance of the CarcassFormer system is compared with other state-of-the-art (SOTA) approaches for both classification, detection, and segmentation tasks. Through extensive quantitative experiments, our framework consistently outperforms existing methods, demonstrating re- markable improvements across various evaluation metrics such as AP, AP@50, and AP@75. Furthermore, the qualitative results highlight the strengths of CarcassFormer in capturing fine details, including feathers, and accurately localizing and segmenting carcasses with high precision. To facilitate further research and collaboration, the source code and trained models will be made publicly available upon acceptance.

sCL-ST: Supervised Contrastive Learning With Semantic Transformations for Multiple Lead ECG Arrhythmia Classification.

The automatic classification of electrocardiogram (ECG) signals has played an important role in cardiovascular diseases diagnosis and prediction. With recent advancements in deep neural networks (DNNs), particularly Convolutional Neural Networks (CNNs), learning deep features automatically from the original data is becoming an effective and widespread approach in a variety of intelligent tasks including biomedical and health informatics. However, most of the existing approaches are trained on either 1D CNNs or 2D CNNs, and they suffer from the limitations of random phenomena (i.e. random initial weights). Furthermore, the ability to train such DNNs in a supervised manner in healthcare is often limited due to the scarcity of labeled training data. To address the problems of weight initialization and limited annotated data, in this work, we leverage recent self-supervised learning technique, namely, contrastive learning, and present supervised contrastive learning (sCL). Different from existing self-supervised contrastive learning approaches, which often generate false negatives because of random selection of negative anchors, our contrastive learning makes use of labeled data to pull the same class closer together and push different classes far apart to avoid potential false negatives. Furthermore, unlike other kinds of signals (e.g. speech, image, video), ECG signal is sensitive to changes, and inappropriate transformation could directly affect diagnosis results. To deal with this issue, we present two semantic transformations, i.e. semantic split-join and semantic weighted peaks noise smoothing. The proposed deep neural network sCL-ST with supervised contrastive learning and semantic transformations is trained as an end-to-end framework for the multi-label classification of 12-lead ECGs. Our sCL-ST network contains two sub-networks i.e. pre-text task and down-stream task. Our experimental results have been evaluated on 12-lead PhysioNet 2020 dataset and shown that our proposed network outperforms the state-of-the-art existing approaches.

Hydrogen attenuates endothelial glycocalyx damage associated with partial cardiopulmonary bypass in rats.

Cardiopulmonary bypass (CPB) causes systemic inflammation and endothelial glycocalyx damage. Hydrogen has anti-oxidant and anti-inflammatory properties; therefore, we hypothesized that hydrogen would alleviate endothelial glycocalyx damage caused by CPB. Twenty-eight male Sprague-Dawley rats were randomly divided into four groups (n = 7 per group), as follows: sham, control, 2% hydrogen, and 4% hydrogen. The rats were subjected to 90 minutes of partial CPB followed by 120 minutes of observation. In the hydrogen groups, hydrogen was administered via the ventilator and artificial lung during CPB, and via the ventilator for 60 minutes after CPB. After observation, blood collection, lung extraction, and perfusion fixation were performed, and the heart, lung, and brain endothelial glycocalyx thickness was measured by electron microscopy. The serum syndecan-1 concentration, a glycocalyx component, in the 4% hydrogen group (5.7 ± 4.4 pg/mL) was lower than in the control (19.5 ± 6.6 pg/mL) and 2% hydrogen (19.8 ± 5.0 pg/mL) groups (P < 0.001 for each), but it was not significantly different from the sham group (6.2 ± 4.0 pg/mL, P = 0.999). The endothelial glycocalyces of the heart and lung in the 4% hydrogen group were thicker than in the control group. The 4% hydrogen group had lower inflammatory cytokine concentrations (interleukin-1ß and tumor necrosis factor-α) in serum and lung tissue, as well as a lower serum malondialdehyde concentration, than the control group. The 2% hydrogen group showed no significant difference in the serum syndecan-1 concentration compared with the control group. However, non-significant decreases in serum and lung tissue inflammatory cytokine concentrations, as well as in serum malondialdehyde concentration, were observed. Administration of 4% hydrogen via artificial and autologous lungs attenuated endothelial glycocalyx damage caused by partial CPB in rats, which might be mediated by the anti-inflammatory and anti-oxidant properties of hydrogen.

Dexmedetomidine suppresses serum syndecan-1 elevation and improves survival in a rat hemorrhagic shock model.

Hemorrhagic shock causes vascular endothelial glycocalyx (EGCX) damage and systemic inflammation. Dexmedetomidine (DEX) has anti-inflammatory and EGCX-protective effects, but its effect on hemorrhagic shock has not been investigated. Therefore, we investigated whether DEX reduces inflammation and protects EGCX during hemorrhagic shock. Anesthetized Sprague-Dawley rats were randomly assigned to five groups (n=7 per group): no shock (SHAM), hemorrhagic shock (HS), hemorrhagic shock with DEX (HS+DEX), hemorrhagic shock with DEX and the α7 nicotinic type acetylcholine receptor antagonist methyllycaconitine citrate (HS+DEX/MLA), and hemorrhagic shock with MLA (HS+MLA). HS was induced by shedding blood to a mean blood pressure of 25-30 mmHg, which was maintained for 30 min, after which rats were resuscitated with Ringer's lactate solution at three times the bleeding volume. The survival rate was assessed up to 3 h after the start of fluid resuscitation. Serum tumor necrosis factor-alpha (TNF-α) and syndecan-1 concentrations, and wet-to-dry ratio of the heart were measured 90 min after the start of fluid resuscitation. The survival rate after 3 h was significantly higher in the HS+DEX group than in the HS group. Serum TNF-α and syndecan-1 concentrations, and the wet-to-dry ratio of heart were elevated by HS, but significantly decreased by DEX. These effects were antagonized by MLA. DEX suppressed the inflammatory response and serum syndecan-1 elevation, and prolonged survival in rats with HS.

Inhalation of 2% Hydrogen Improves Survival Rate and Attenuates Shedding of Vascular Endothelial Glycocalyx in Rats with Heat Stroke.

ABSTRACT: Heat stroke is characterized by excessive oxidative stress and inflammatory responses, both of which are implicated in vascular endothelial glycocalyx shedding and heat-stroke mortality. Although molecular hydrogen has antioxidation and anti-inflammatory potency, its effect on the vascular endothelial glycocalyx in heat stroke has not been examined. Therefore, the aim of this study was to investigate the influence of hydrogen inhalation on the survival and thickness of the vascular endothelial glycocalyx of rats subjected to heat stroke. Altogether, 98 Wistar rats were assigned to the experiments. A heat-controlled chamber set at 40°C temperature and 60% humidity was used to induce heat stroke. After preparation, the anesthetized rats that underwent the heating process were subjected to an hour of stabilization in which 0%, 2%, or 4% hydrogen gas was inhaled and maintained until the experiment ended. In addition to survival rate assessments, blood samples and left ventricles were collected to evaluate the thickness of the vascular endothelial glycocalyx and relevant biomarkers. The results showed that 2% hydrogen gas significantly improved survival in the heat-stroked rats and partially preserved the thickness of the endothelial glycocalyx. In addition, serum levels of endotoxin, syndecan-1, malondialdehyde, and tumor necrosis factor-α decreased, whereas superoxide dismutase levels increased, indicating that inhalation of 2% hydrogen attenuated the damage to the vascular endothelial glycocalyx through its antioxidative and anti-inflammatory effects.