Diabetic retinopathy (DR) is an irreversible disease that damages blood vessels and results in permanent visual impairment. Timely detection and proper diagnosis can mitigate severe eye impacts and ...slow DR progression. Color fundus images are commonly used by eye specialists to diagnose DR. However, manual operations are tedious, laborious, time-consuming, and error-prone. As a result, automated techniques are gaining increased attention in the medical domain due to their ability to precisely analyze unstructured clinical notes. In this paper, a novel Gannet-optimized deep belief network-based wavelet kernel extreme learning machine (GO-DBN-WKELM) technique is proposed for detecting DR occurrences and assessing its progressive stages. The GO-DBN-WKELM approach detects and classifies DR severities into six distinct classes: no DR (i.e., normal), early DR, mild non-proliferative DR, moderate non-proliferative DR, severe non-proliferative DR, and proliferative DR. Initially, detailed information from the original datasets is extracted by reducing feature dimensions using the Deep Belief Network (DBN) model. Subsequently, the extracted images are analyzed by the proposed GO-DBN-WKELM classification model, which effectively detects and accurately classifies fundus images based on their severities into distinct classes. The enhanced detection performance is primarily due to the application of the GO algorithm with a wavelet kernel extreme learning machine (WKELM). The GO algorithm not only optimizes the kernel parameters of the WKELM but also increases the convergence speed of the classifier. The proposed classifier is analyzed using three different types of datasets, namely MESSIDOR, DIARETDB1, and IDRiD datasets. The effectiveness of the proposed classification model is determined by evaluating its ability to detect DR in terms of diverse performance metrics, such as accuracy, precision, recall, and F-measure. Simulation results reveal that the proposed GO-DBN-WKELM classifier achieved a high accuracy rate of approximately 98% for the MESSIDOR dataset and 97.8% for the DIARETDB1 dataset. These outcomes demonstrate the potential of the GO-DBN-WKELM approach in detecting and classifying diabetic retinopathy severities, offering an efficient, automated alternative to manual methods that can aid eye specialists in providing timely diagnoses and interventions for patients with this condition.
Diabetic Retinopathy (DR) primarily affects a set of lesions in the eyes, causing retinal degeneration and loss of vision. The DR features serve as a crucial component for ophthalmologists to ...diagnose DR at an earlier stage. This paper presents an automatic DR screening tool using a hybrid GAN-RCNN architecture formulated to categorize and identify different DR grades from the fundus images captured at various resolutions. The hybrid GAN-RCNN architecture is formulated by replacing the discriminator in the GAN with the RCNN classifier. The RCNN model can handle the complex inter-class and intra-class variations present in the fundus retina images and classify them into different classes such as mild, moderate, severe, and nonproliferative DR. The RCNN model not only extracts the pixels present in the fundus image but also focuses on the significant relationship that exists between different DR classes. The Archimedes optimization Algorithm (AOA) is used to optimize the different GAN and RCNN hyperparameters. When compared to the existing techniques the proposed model offers an accuracy of 99%, 98.5%, and 99.4% in the APTOS, Kaggle, and Messidor datasets which is comparatively high. The experimental outcome reveals that the introduced model serves as a concrete baseline for the diagnosis and treatment of DR patients.
Nowadays the eye disease that widely affects the visual impairment of humans is Diabetes Retinopathy (DR). The advanced stage of the disorder leads to cause complete vision loss and creates complex ...situations for treatment. So it is significant to treat prolonged diabetes at an initial stage. Therefore, the main reason for DR is the uncontrolled growth of blood glucose levels in the eye. If it reaches the severity level the bleeding is caused in the eye. However, the lesions generated due to DR are medicated based on fundus images. The significant purpose of affecting DR is the presence of high sugar in the blood and this damages the retina. Therefore proper screening of DR is essential to prevent it from affecting the blood vessels all over the body. Also, it unblocks blood vessels paves the way to function the new blood vessels grown in the eye. Therefore a novel hybrid oppositional fire-fly modified 1D bidirectional recurrent (HOF-M1DBR) method is proposed to detect the DR through fundus images accurately. The datasets Messidor-1 and APTOS-2019 are applied for performing the initial process of fundus images such as denoising, smoothing, cropping, and resizing. The M1DBR is used to validate the accuracy and optimize the weight function using the Opposition-Based Learning-FireFly (OBL-FF) algorithm. Thus prediction and classification of f DR from the fundus images are detected accurately and distinguished the four levels from the extracted features. The validation of the proposed method is performed based on accuracy, precision, recall, and F1-score. The experimental results revealed that the proposed HOF-M1DBR attained an accuracy of 98.9% for the Messidor-1 and APTOS-2019 dataset, thus improving the performance. However, the existing DCNN-PCA-FF, DNN-MSO, SI-GWO, and DCNN-EMF methods diminished the performance by 79.9%, 87%, 83%, and 89.1% respectively.
General anesthesia has been used clinically for more than 170 years, yet its underlying mechanisms are still not fully understood. The parabrachial nucleus (PBN) in the brainstem has been known to be ...crucial for regulating wakefulness and signs of arousal on the cortical electroencephalogram (EEG). Lesions of the parabrachial complex lead to unresponsiveness and a monotonous high-voltage, and a slow-wave EEG, which are the two main features of general anesthesia. However, it is unclear whether and how the PBN functions in the process of general anesthesia. By recording the levels of calcium
in real-time, we found that the neural activity in PBN is suppressed during anesthesia, while it is robustly activated during recovery from propofol and isoflurane anesthesia. The activation of PBN neurons by "designer receptors exclusively activated by designer drugs" (DREADDs) shortened the recovery time but did not change the induction time. Cortical EEG recordings revealed that the neural activation of PBN specifically affected the recovery period, with a decrease of δ-band power or an increase in β-band power; no EEG changes were seen in the anesthesia period. Furthermore, the activation of PBN elicited neural activation in the prefrontal cortex, basal forebrain, lateral hypothalamus, thalamus, and supramammillary nucleus. Thus, PBN is critical for behavioral and electroencephalographic arousal without affecting the induction of general anesthesia.
Background and Purpose- Cerebral ischemic stroke elicits profound responses of CD4
T cells, which in turn significantly affect the ischemic brain injury. ACC1 (acetyl coenzyme A carboxylase 1) is a ...key enzyme that has been recently found to propagate CD4
T cell-associated inflammation by mediating de novo fatty acid synthesis; however, its role in the context of ischemic stroke remains unknown. Methods- Focal cerebral ischemia was induced by transient middle cerebral artery occlusion for 60 minutes in mice. Seahorse XF glycolysis assay and targeted lipidomic profiling were used to detect metabolic changes in CD4
T cell after stroke. CD4
mice were crossed with ACC1
mice to generate the CD4
T-cell-specific deletion of ACC1 (CD4
ACC1
mice) mice. Pretreatment with calorie restriction (CR; with 30% reduction of food for 4 weeks before middle cerebral artery occlusion) or post-treatment with ACC1 inhibitor, soraphen A were both used to test the effect of ACC1 modulation on poststroke neuroinflammation. Results- Cerebral ischemic stroke increased glycolysis and fatty acid synthesis in peripheral CD4
T cells, in which the expression of ACC1 was also upregulated. CR downregulated the expression of ACC1 in CD4
T cells after stroke. Both CD4
ACC1
mice and CR-pretreated mice exhibited significantly reduced ischemic brain injury and preserved the balance of peripheral regulatory T cells/T helper 17 (Th17) cells. Furthermore, conditional knockout of ACC1 in CD4
T cells attenuated the protection exerted by CR both on ischemic brain injury and peripheral balance of regulatory T cells/Th17 cells. Pharmacological inhibition of ACC1 after middle cerebral artery occlusion attenuates neuroinflammation, preserves regulatory T cells/Th17 balance, and improves neurological outcomes after ischemic stroke. Conclusions- ACC1 is a novel immune metabolic modulation target to balance the regulatory T cells and Th17 cells and blunt neuroinflammation after stroke. Inhibition of ACC1 can be a previously unrecognized mechanism that underlies CR-afforded neuroprotection against cerebral ischemic stroke.
To explore the potential therapeutic strategies of different types of neuropathic pain (NP) and to summarize the cutting-edge novel approaches for NP treatment based on the clinical trials registered ...on ClinicalTrials.gov.
The relevant clinical trials were searched using ClinicalTrials.gov Dec 08, 2022. NP is defined as a painful condition caused by neurological lesions or diseases. All data were obtained and reviewed by the investigators to confirm whether they were related to the current topic.
A total of 914 trials were included in this study. They were divided into painful diabetic neuropathy (PDN), postherpetic neuralgia (PHN), sciatica (SC), peripheral nerve injury-related NP (PNI), trigeminal neuralgia (TN), chemotherapy-induced NP (CINP), general peripheral NP (GPNP) and spinal cord injury NP (SCI-NP). Potential novel therapeutic strategies, such as novel drug targets and physical means, were discussed for each type of NP.
NP treatment is mainly dominated by drug therapy, and physical means have become increasingly popular. It is worth noting that novel drug targets, new implications of conventional medicine, and novel physical means can serve as promising strategies for the treatment of NP. However, more attention needs to be paid to the challenges of translating research findings into clinical practice.
Abstract
Touch and itch sensations are crucial for evoking defensive and emotional responses, and light tactile touch may induce unpleasant itch sensations (mechanical itch or alloknesis). The neural ...substrate for touch-to-itch conversion in the spinal cord remains elusive. We report that spinal interneurons expressing
Tachykinin 2-Cre
(
Tac2
Cre
) receive direct Aβ low threshold mechanoreceptor (LTMR) input and form monosynaptic connections with GRPR neurons. Ablation or inhibition markedly reduces mechanical but not acute chemical itch nor noxious touch information. Chemogenetic inhibition of
Tac2
Cre
neurons also displays pronounced deficit in chronic dry skin itch, a type of chemical itch in mice. Consistently, ablation of gastrin-releasing peptide receptor (GRPR) neurons, which are essential for transmitting chemical itch, also abolishes mechanical itch. Together, these results suggest that innocuous touch and chemical itch information converge on GRPR neurons and thus map an exquisite spinal circuitry hard-wired for converting innocuous touch to irritating itch.
ALI/ARDS is a severe lung injury leading to refractory respiratory failure, accounting for high morbidity and mortality. However, therapeutic approaches are rather limited. Targeting long non-coding ...RNA MALAT1 and microRNA miR-181a-5p might be potential option for ALI/ARDS intervention.
We aimed to investigate the role of MALAT and miR-181a-5p in the pathogenesis of ALI/ARDS, and test the therapeutic effects of targeting MALAT and miR-181a-5p for ALI/ARDS intervention in vitro.
MALAT1 and miR-181a-5p levels were measured in plasma from ALI/ARDS patients. In vitro human pulmonary microvascular endothelial cell (HPMEC) injury was induced by LPS treatment, and molecular targets of MALAT1 and miR-181a-5p were explored by molecular biology approaches, mainly focusing on cell apoptosis and vascular inflammation. Interaction between MALAT1 and miR-181a-5p was also detected. Finally, the effects of targeting MALAT1 and miR-181a-5p for ALI/ARDS intervention were validated in a rat ALI/ARDS model.
MALAT1 upregulation and miR-181a-5p downregulation were observed in ALI/ARDS patients. Transfection of mimic miR-181a-5p into HPMECs revealed decreased Fas and apoptosis, along with reduced inflammatory factors. Fas was proved to be a direct target of miR-181a-5p. Similar effects were also present upon MALAT1 knockdown. As for the interaction between MALAT1 and miR-181a-5p, MALAT1 knockdown increased miR-181a-5p expression. Knocking down of MALAT1 and miR-181a-5p could both improve the outcome in ALI/ARDS rats.
MALAT1 antagonism or miR-181a-5p could both be potential therapeutic strategies for ALI/ARDS. Mechanistically, miR-181a-5p directly inhibits Fas and apoptosis, along with reduced inflammation. MALAT1 negatively regulates miR-181a-5p.
A plethora of evidence has suggested that gut microbiota is involved in the occurrence and development of postmenopausal osteoporosis (PMO). It has been suggested that neuropeptide Y (NPY) modulates ...the bone metabolism through Y1 receptor (Y1R), and might be associated with gut microbiota. The present study aims to evaluate the anti-osteoporotic effects of Y1R antagonist and to investigate the potential mechanism by which Y1R antagonist regulates gut microbiota. In this study, eighteen female rats were randomly divided into three groups: the sham surgery (SHAM) group, the ovariectomized (OVX) group, and OVX+BIBO3304 group. After 6 weeks following surgery, Y1R antagonist BIBO3304 was administered to the rats in OVX+BIBO3304 group for 7 days. The bone microstructure and serum biochemical parameters were measured at 12 weeks after operation. The differences in the gut microbiota were analyzed by 16S rDNA gene sequencing. Heat-map and Spearman’s correlation analyses were constructed to investigate the correlations between microbiota and bone metabolism-related parameters. The results indicated that OVX+BIBO3304 group showed significantly higher BMD, BV/TV, Tb.Th, Tb.N, Conn.D, and serum Ca
2+
level than those in OVX group. Additionally, Y1R antagonist changed the gut microbiota composition with lower
Firmicutes
/
Bacteroidetes
ratio and higher proportions of some probiotics, including
Lactobacillus
. The correlation analysis showed that the changes of gut microbiota were closely associated with bone microstructure and serum Ca
2+
levels. Our results suggested that Y1R antagonist played an anti-osteoporotic effect and regulated gut microbiota in OVX rats, indicating the potential to utilize Y1R antagonist as a novel treatment for PMO.
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