Astragalus Polysaccharide Promotes Neuronal Injury Repair via the Notch1/NFκB Signaling Axis in the Ventroposterior Thalamic Nucleus in Rats with Focal Cerebral Ischemia.

BACKGROUND: Ischemic stroke is the most common form of stroke and the second most common cause of death and incapacity worldwide. Its pathogenesis and treatment have been the focus of considerable research. In traditional Chinese medicine, the root of Mongolian astragalus has been important in the treatment of stroke since ancient times. Astragalus polysaccharide (APS) is a key active ingredient of astragalus and offers therapeutic potential for conditions affecting the neurological system, the heart, cancer, and other disorders. However, it is not yet known how APS works to protect against ischemic stroke. METHODS: Rats were subjected to middle cerebral artery occlusion (MCAO) to imitate localized cerebral ischemia. Each of four experimental groups (normal, sham, MCAO, and MCAO+APS) contained 12 adult male Sprague-Dawley (SD) rats selected randomly from a total of 48 rats. Following successful establishment of the model, rats in the MCAO+APS group received intraperitoneal injection of APS (50 mg/kg) once daily for 14 days, whereas all other groups received no APS. The Bederson nerve function score and the forelimb placement test were used to detect motor and sensory function defects, while Nissl staining was used to investigate pathological defects in the ventroposterior thalamic nucleus (VPN). Immunohistochemical staining and Western blot were used to evaluate the expression of Neurogenic locus notch homolog protein 1 (Notch1), hairy and enhancer of split 1 (Hes1), phospho-nuclear factor-κB p65 (p-NFκB p65), and nuclear factor-κB p65 (NFκB p65) proteins in the VPN on the ischemic side of MCAO rats. RESULTS: APS promoted the recovery of sensory and motor function, enhanced neuronal morphology, increased the number of neurons, and inhibited the expression of Notch1/NFκB signaling pathway proteins in the VPN of rats with cerebral ischemia. CONCLUSION: After cerebral ischemia, APS can alleviate symptoms of secondary damage to the VPN, which may be attributed to the suppression of the Notch1/NFκB pathway.

Security at the Edge for Resource-Limited IoT Devices.

The Internet of Things (IoT) is rapidly growing, with an estimated 14.4 billion active endpoints in 2022 and a forecast of approximately 30 billion connected devices by 2027. This proliferation of IoT devices has come with significant security challenges, including intrinsic security vulnerabilities, limited computing power, and the absence of timely security updates. Attacks leveraging such shortcomings could lead to severe consequences, including data breaches and potential disruptions to critical infrastructures. In response to these challenges, this research paper presents the IoT Proxy, a modular component designed to create a more resilient and secure IoT environment, especially in resource-limited scenarios. The core idea behind the IoT Proxy is to externalize security-related aspects of IoT devices by channeling their traffic through a secure network gateway equipped with different Virtual Network Security Functions (VNSFs). Our solution includes a Virtual Private Network (VPN) terminator and an Intrusion Prevention System (IPS) that uses a machine learning-based technique called oblivious authentication to identify connected devices. The IoT Proxy's modular, scalable, and externalized security approach creates a more resilient and secure IoT environment, especially for resource-limited IoT devices. The promising experimental results from laboratory testing demonstrate the suitability of IoT Proxy to secure real-world IoT ecosystems.

Fast and Reliable Sending of Generic Object Oriented Substation Event Frames between Remote Locations over Loss-Prone Networks.

WAMPAC (Wide Area Monitoring Protection and Control) applications are becoming crucial for granting a stable operation of the electricity transmission grid. These systems use a set of sensors distributed between different electrical substations to gather real-time measurements from the field. These sensors are called Phasor Measurement Units (PMUs). Using the gathered data, different monitoring, protection, and control algorithms are run in a Phasor Data Concentrator (PDC) located in a central location. These algorithms close the loop via the generation of remedial commands, which are sent back to the field level with stringent delay, security, and reliability requirements. GOOSE (Generic Object Oriented Substation Events) protocol, defined by IEC 61850 (IEC stands for International Electrotechnical Commission), is used for that aim and also considers the option of sending these commands over IP networks (this option is called Routed-GOOSE). The present article proposes two alternatives for the tunneling of GOOSE frames over IP. Both options allow the decoupling of the transmission and the security aspects, thus increasing flexibility and allowing for easier deployment. The first option, called VX-GOOSE, is a combination of standard protocols, allowing the sending of these frames over UDP/IP tunnels. The tests that have been carried out demonstrate that, under certain network conditions, the transmission of GOOSE frames over UDP may fail, and in some extreme cases, even a whole burst of GOOSEs could be lost. This may have very bad consequences for a distributed electrical system. It should be noted that this limitation affects both VX-GOOSE and Routed-GOOSE. To overcome these limitations, the second option, called Simplemux blast mode, includes a novel mechanism that provides delivery guarantees and a reduced delay, with the counterpart of a certain degree of redundancy. As shown in the experiments, the incurred delays can be significantly reduced when remote locations are connected via unreliable networks, whereas the bandwidth increase caused by redundancy can be kept at reasonable levels. Finally, it should be remarked that although GOOSE is a relevant example use case, this approach can be applied in other fields where flows require very low delay and delivery guarantees.

A Novel Lightweight Anonymous Proxy Traffic Detection Method Based on Spatio-Temporal Features.

Anonymous proxies are used by criminals for illegal network activities due to their anonymity, such as data theft and cyber attacks. Therefore, anonymous proxy traffic detection is very essential for network security. In recent years, detection based on deep learning has become a hot research topic, since deep learning can automatically extract and select traffic features. To make (heterogeneous) network traffic adapt to the homogeneous input of typical deep learning algorithms, a major branch of existing studies convert network traffic into images for detection. However, such studies are commonly subject to the limitation of large-sized image representation of network traffic, resulting in very large storage and computational resource overhead. To address this limitation, a novel method for anonymous proxy traffic detection is proposed. The method is one of the solutions to reduce storage and computational resource overhead. Specifically, it converts the sequences of the size and inter-arrival time of the first N packets of a flow into images, and then categorizes the converted images using the one-dimensional convolutional neural network. Both proprietary and public datasets are used to validate the proposed method. The experimental results show that the converted images of the method are at least 90% smaller than that of existing image-based deep learning methods. With substantially smaller image sizes, the method can still achieve F1 scores up to 98.51% in Shadowsocks traffic detection and 99.8% in VPN traffic detection.

MVDroid: an android malicious VPN detector using neural networks.

The majority of Virtual Private Networks (VPNs) fail when it comes to protecting our privacy. If we are using a VPN to protect our online privacy, many of the well-known VPNs are not secure to use. When examined closely, VPNs can appear to be perfect on the surface but still be a complete privacy and security disaster. Some VPNs will steal our bandwidth, infect our computers with malware, install secret tracking libraries on our devices, steal our personal data, and leave our data exposed to third parties. Generally, Android users should be cautious when installing any VPN software on their devices. As a result, it is important to identify malicious VPNs before downloading and installing them on our Android devices. This paper provides an optimised deep learning neural network for identifying fake VPNs, and VPNs infected by malware based on the permissions of the apps, as well as a novel dataset of malicious and benign Android VPNs. Experimental results indicate that our proposed classifier identifies malicious VPNs with high accuracy, while it outperforms other standard classifiers in terms of evaluation metrics such as accuracy, precision, and recall.

Establishment of a Rapid Phone Consultation Service for COVID-19 Public Health Support in Nepal.

Background The coronavirus disease 2019 (COVID-19) pandemic strained the already weak health system of Nepal, especially during the surge of the delta variant. A telephonic consultation service was rapidly established to provide free consultations to assist those in home isolation due to severe acute respiratory syndrome coronavirus 2 infection. In this study, we describe the process of establishing the hotline and share preliminary findings. During the peak of the delta wave in Nepal, the hotline was started by a local non-profit organization. Methodology We established the hotline with help of a private telecommunication company. The hotline was advertised on social media, radio, and newspapers. Healthcare workers were recruited and trained and the service was provided for free. Patient data were recorded and de-identified for analysis, monitoring, and evaluation. Results The majority of the callers were from Kathmandu valley, which includes three districts, Kathmandu, Lalitpur, and Bhaktapur. Overall, 44% of the callers inquired about the clinical manifestations of COVID-19. On average, there were 75 calls each day between May 2021 and February 2022. The average call duration was three minutes and 42 seconds. Trained healthcare workers answered the calls for 15.5 hours a day. Conclusions Our work established the feasibility of a rapid hotline service in response to the pandemic causing high strain on the health system. Lessons learned from this experience can be useful for future disasters in Nepal and other places with similar health system strains.

Vasculitic Peripheral Neuropathy, Differences Between Systemic and Non-Systemic Etiologies: A Case Series and Biopsy Report.

BACKGROUND: Vasculitic peripheral neuropathy (VPN) is caused by vessel inflammation leading to peripheral nerve injury of acute-to-subacute onset. When VPN occurs in the context of systemic disease it is classified as Systemic Vasculitic Neuropathy (SVN) and as Non-Systemic Vasculitic Neuropathy (NSVN) when restricted to the nerves. OBJECTIVE: This study aimed to compare the clinical characteristics, biopsy findings and disease outcome in patients with VPN. METHODS: Clinical records of adult patients with VPN diagnosed at our institution between June-2002 and June-2019 were retrospectively reviewed. Demographic characteristics, clinical manifestations, nerve conduction studies, nerve biopsies, treatment and clinical evolution were analyzed in all patients with at least 6 months follow-up. RESULTS: Twenty-five patients with VPN were included (SVN, n = 10; NSVN, n = 15). No significant differences in demographic or clinical features were found between groups. The median delay between symptom onset and nerve biopsy was significantly longer in NSVN patients (10 vs 5.5 months, p = 0.009). Erythrocyte sedimentation rate (ESR) values over 20 mm/h were significantly more common in SVN patients (100% vs. 60%, p = 0.024). Nerve biopsies showed active lesions more frequently in treatment-naive patients compared to those who had received at least 2 weeks of corticosteroids (92% vs 38%; p = 0.03), with a higher proportion of definite VPN cases (92 vs 46%; p = 0.04). CONCLUSIONS: Although the clinical manifestations are similar, ESR is an important tool to help distinguish between both conditions. Early nerve biopsy in untreated patients increases diagnostic accuracy, avoiding misdiagnosis.

Identifying VoIP traffic in VPN tunnel via Flow Spatio-Temporal Features.

The persistent emergence of new network applications, along with encrypted network communication, has make traffic analysis become a challenging issue in network management and cyberspace security. Currently, virtual private network (VPNs) has become one of the most popular encrypted communication services for bypassing censorship and guarantee remote access to geographically locked services. In this paper, a novel identification scheme of VoIP traffic tunneled through VPN is proposed. We employed a set of Flow Spatio-Temporal Features (FSTF) to six well-known classifiers, including decision trees, K-Nearest Neighbor (KNN), Bagging and Boosting via C4.5, and Multi-Layer perceptron (MLP). The overall accuracy, precision, sensitivity, and F-measure verify that the proposed scheme can effectively distinguish between the VoIP flows and Non-VoIP ones in VPN traffic.

A combination of Raspberry Pi and SoftEther VPN for controlling research devices via the Internet.

Remote control over devices for experiments may increase the efficiency of operant research and expand the area where behavior can be studied. This article introduces a combination of Raspberry Pi® (Pi) and SoftEther VPN® that allows for such remote control via the Internet. The Pi is a small Linux computer with a great degree of flexibility for customization. Test results indicate that a Pi-based interface meets the requirement for conducting operant research. SoftEther VPN® allows for establishing an extensive private network on the Internet using a single private Wi-Fi router. Step-by-step instructions are provided in the present article for setting up the Pi along with SoftEther VPN® . Their potential for improving the way of conducting research is discussed.

Plant-Derived Chimeric Virus Particles for the Diagnosis of Primary Sjögren Syndrome.

Plants are ideal for the production of protein-based nanomaterials because they synthesize and assemble complex multimeric proteins that cannot be expressed efficiently using other platforms. Plant viruses can be thought of as self-replicating proteinaceous nanomaterials generally stable and easily produced in high titers. We used Potato virus X (PVX), chimeric virus particles, and Cowpea mosaic virus, empty virus-like particles to display a linear peptide (lipo) derived from human lipocalin, which is immunodominant in Sjögren's syndrome (SjS) and is thus recognized by autoantibodies in SjS patient serum. These virus-derived nanoparticles were thus used to develop a diagnostic assay for SjS based on a direct enzyme linked immunosorbent assay format. We found that PVX-lipo formulations were more sensitive than the chemically synthesized immunodominant peptide and equally specific when used to distinguish between healthy individuals and SjS patients. Our novel assay therefore allows the diagnosis of SjS using a simple, low-invasive serum test, contrasting with the invasive labial biopsy required for current tests. Our results demonstrate that nanomaterials based on plant viruses can be used as diagnostic reagents for SjS, and could also be developed for the diagnosis of other diseases.

Neuroprotective effect of chondroitinase ABC on primary and secondary brain injury after stroke in hypertensive rats.

Focal cerebral infarction causes secondary damage in the ipsilateral ventroposterior thalamic nucleus (VPN). Chondroitin sulfate proteoglycans (CSPGs) are a family of putative inhibitory components, and its degradation by chondroitinase ABC (ChABC) promotes post-injury neurogenesis. This study investigated the role of ChABC in the primary and secondary injury post stroke in hypertension. Renovascular hypertensive Sprague-Dawley rats underwent middle cerebral artery occlusion (MCAO), and were subjected to continuous intra-infarct infusion of ChABC (0.12 U/d for 7 days) 24 h later. Neurological function was evaluated by a modified neurologic severity score. Neurons were counted in the peri-infarct region and the ipsilateral VPN 8 and 14 days after MCAO by Nissl staining and NeuN labeling. The expressions of CSPGs, growth-associated protein-43 (GAP-43) and synaptophysin (SYN) were detected with immunofluorescence or Western blotting. The intra-infarct infusion of ChABC, by degrading accumulated CSPGs, rescued neuronal loss and increased the levels of GAP-43 and SYN in both the ipsilateral cortex and VPN, indicating enhancd neuron survival as well as augmented axonal growth and synaptic plasticity, eventually improving overall neurological function. The study demonstrated that intra-infarct ChABC infusion could salvage the brain from both primary and secondary injury by the intervention on the neuroinhibitory environment post focal cerebral infarction.

Implementation of Medical Information Exchange System Based on EHR Standard.

OBJECTIVES: To develop effective ways of sharing patients' medical information, we developed a new medical information exchange system (MIES) based on a registry server, which enabled us to exchange different types of data generated by various systems. METHODS: To assure that patient's medical information can be effectively exchanged under different system environments, we adopted the standardized data transfer methods and terminologies suggested by the Center for Interoperable Electronic Healthcare Record (CIEHR) of Korea in order to guarantee interoperability. Regarding information security, MIES followed the security guidelines suggested by the CIEHR of Korea. This study aimed to develop essential security systems for the implementation of online services, such as encryption of communication, server security, database security, protection against hacking, contents, and network security. RESULTS: The registry server managed information exchange as well as the registration information of the clinical document architecture (CDA) documents, and the CDA Transfer Server was used to locate and transmit the proper CDA document from the relevant repository. The CDA viewer showed the CDA documents via connection with the information systems of related hospitals. CONCLUSIONS: This research chooses transfer items and defines document standards that follow CDA standards, such that exchange of CDA documents between different systems became possible through ebXML. The proposed MIES was designed as an independent central registry server model in order to guarantee the essential security of patients' medical information.

Avaliação da previsibilidade da sutura de menisco através da ressonância magnética / Predictability of meniscal suture by magnetic resonance imaging

The prediction of meniscus reparability is quite useful for surgeons to optimize surgical planning. The main objective of this study was to evaluate the ability of magnetic resonance imaging (MRI) to predict the suture of meniscal lesions. This was an unicentric retrospective study that included 104 patients who underwent knee joint ligament reconstruction and / or arthroscopy for the treatment of meniscal injury at knee joint level. The MRI images of the meniscus were evaluated and later the arthroscopic findings were used as the gold standard. After the operative procedure, the cases were allocated into two groups according to the necessity of meniscus suture: Sutured Group "MSu" (n = 58) and Non sutured Group "MNSu" (n = 150). Considering the lesion detection capacity in the medial meniscus, the sensitivity, specificity and accuracy of MR were 85.3%, 63.9% and 77.9%, respectively. The positive predictive value (PPV) was 81.7% and the negative predictive value (NPV) was 69.7%. The agreement between MRI and arthroscopy was moderate. For the lateral meniscus, sensitivity, specificity and accuracy of MRI were 80.6%, 89.0% and 86.5%, respectively, with PPV of 75.7% and NPV of 91.5% and a substantial agreement. Regarding suture predictability, the sensitivity, specificity and accuracy were respectively 60.3%, 66.7% and 64.9% with PPV of 41.2% and NPV of 81.3%, with weak agreement. According to the arthroscopy, the 58 meniscal lesions of the MSu group were more frequent in the posterior horn, had the longitudinal pattern and were located in the red-red vascular zone. In our study, MRI was not a good predictor of meniscal suture, although it is an useful tool for the diagnosis of medial and lateral meniscal lesions