Efficacy of live and inactivated recombinant Newcastle disease virus vaccines expressing clade 2.3.4.4b H5 hemagglutinin against H5N1 highly pathogenic avian influenza in SPF chickens, Broilers, and domestic ducks.

A Newcastle disease virus (NDV)-vectored vaccine expressing clade 2.3.4.4b H5 Hemagglutinin was developed and assessed for efficacy against H5N1 highly pathogenic avian influenza (HPAI) in specific pathogen-free (SPF) chickens, broilers, and domestic ducks. In SPF chickens, the live recombinant NDV-vectored vaccine, rK148/22-H5, achieved complete survival against HPAI and NDV challenges and significantly reduced viral shedding. Notably, the live rK148/22-H5 vaccine conferred good clinical protection in broilers despite the presence of maternally derived antibodies. Good clinical protection was observed in domestic ducks, with decreased viral shedding. It demonstrated complete survival and reduced cloacal viral shedding when used as an inactivated vaccine from SPF chickens. The rK148/22-H5 vaccine is potentially a viable and supportive option for biosecurity measure, effectively protecting in chickens against the deadly clade 2.3.4.4b H5 HPAI and NDV infections. Furthermore, it aligns with the strategy of Differentiating Infected from Vaccinated Animals (DIVA).

Comparative protective efficacy of a newly generated live recombinant thermostable highly attenuated vaccine rK148/GVII-F using a single regimen against lethal NDV GVII.1.1.

RESEARCH HIGHLIGHTS: A thermostable, safe, and effective NDV GVII recombinant vaccine was generated.Fusion gene replacement with GVII did not affect GI K148/08 virus thermostability.Strain rK148/GVII-F provided adequate protection against a lethal NDV challenge.Oropharyngeal shedding was significantly reduced on post-challenge days 5 and 7.

Proactive Fault Diagnosis of a Radiator: A Combination of Gaussian Mixture Model and LSTM Autoencoder.

Radiator reliability is crucial in environments characterized by high temperatures and friction, where prompt interventions are often required to prevent system failures. This study introduces a proactive approach to radiator fault diagnosis, leveraging the integration of the Gaussian Mixture Model and Long-Short Term Memory autoencoders. Vibration signals from radiators were systematically collected through randomized durability vibration bench tests, resulting in four operating states-two normal, one unknown, and one faulty. Time-domain statistical features of these signals were extracted and subjected to Principal Component Analysis to facilitate efficient data interpretation. Subsequently, this study discusses the comparative effectiveness of the Gaussian Mixture Model and Long Short-Term Memory in fault detection. Gaussian Mixture Models are deployed for initial fault classification, leveraging their clustering capabilities, while Long-Short Term Memory autoencoders excel in capturing time-dependent sequences, facilitating advanced anomaly detection for previously unencountered faults. This alignment offers a potent and adaptable solution for radiator fault diagnosis, particularly in challenging high-temperature or high-friction environments. Consequently, the proposed methodology not only provides a robust framework for early-stage fault diagnosis but also effectively balances diagnostic capabilities during operation. Additionally, this study presents the foundation for advancing reliability life assessment in accelerated life testing, achieved through dynamic threshold adjustments using both the absolute log-likelihood distribution of the Gaussian Mixture Model and the reconstruction error distribution of the Long-Short Term Memory autoencoder model.

Data Modifications in Blockchain Architecture for Big-Data Processing.

Due to the immutability of blockchain, the integration with big-data systems creates limitations on redundancy, scalability, cost, and latency. Additionally, large amounts of invaluable data result in the waste of energy and storage resources. As a result, the demand for data deletion possibilities in blockchain has risen over the last decade. Although several prior studies have introduced methods to address data modification features in blockchain, most of the proposed systems need shorter deletion delays and security requirements. This study proposes a novel blockchain architecture called Unlichain that provides data-modification features within public blockchain architecture. To achieve this goal, Unlichain employed a new indexing technique that defines the deletion time for predefined lifetime data. The indexing technique also enables the deletion possibility for unknown lifetime data. Unlichain employs a new metadata verification consensus among full and meta nodes to avoid delays and extra storage usage. Moreover, Unlichain motivates network nodes to include more transactions in a new block, which motivates nodes to scan for expired data during block mining. The evaluations proved that Unlichain architecture successfully enables instant data deletion while the existing solutions suffer from block dependency issues. Additionally, storage usage is reduced by up to 10%.

Intramuscular administration of recombinant Newcastle disease virus expressing SARS-CoV-2 spike protein protects hACE-2 TG mice against SARS-CoV-2 infection.

Coronavirus disease 2019 (Covid-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) became a pandemic, causing significant burden on public health worldwide. Although the timely development and production of mRNA and adenoviral vector vaccines against SARS-CoV-2 have been successful, issues still exist in vaccine platforms for wide use and production. With the potential for proliferative capability and heat stability, the Newcastle disease virus (NDV)-vectored vaccine is a highly economical and conceivable candidate for treating emerging diseases. In this study, a recombinant NDV-vectored vaccine expressing the spike (S) protein of SARS-CoV-2, rK148/beta-S, was developed and evaluated for its efficacy against SARS-CoV-2 in K18-hACE-2 transgenic mice. Intramuscular vaccination with low dose (106.0 EID50) conferred a survival rate of 76 % after lethal challenge of a SARS-CoV-2 beta (B.1.351) variant. When administered with a high dose (107.0 EID50), vaccinated mice exhibited 100 % survival rate and reduced lung viral load against both beta and delta variants (B.1.617.2). Together with the protective immunity, rK148/beta-S is an accessible and cost-effective SARS-CoV-2 vaccine.

Live recombinant Newcastle disease virus vectored vaccine expressing the haemagglutinin of H9N2 avian influenza virus suppresses viral replication in chickens.

In 2020, the Y280-lineage H9N2 low-pathogenic avian influenza virus (LPAIV) was introduced into South Korea for the first time. Current vaccines are focused on the control of Y439-like viruses; however, there are continuous reports of decrease in egg production and secondary infections caused by Y280-lineage H9N2 LPAI infection in chickens. Therefore, there is an urgent need to develop effective novel vaccines against Y280-lineage H9N2 LPAI. Most commercialized avian influenza vaccines are oil-adjuvanted inactivated vaccines, which are labour-intensive to administer and require higher dosage. In this study, rK148/Y280-HA, a novel recombinant Newcastle disease virus (NDV) vectored vaccine against Y280-lineage H9N2 LPAI, was developed and evaluated using two mass-applicable administration methods, spray vaccination and drinking water vaccination. Regardless of low serum antibody haemagglutination inhibition titres against NDV and Y280-lineage H9N2 LPAI after applying the rK148/Y280-HA vaccine, vaccination with either administration method protected chickens against virulent NDV and Y280-lineage H9N2 LPAIV after the challenge. Taken together, these results indicate that the rK148/Y280 vaccine can be administered using facile mass-application methods to provide protection against the Y280-lineage LPAI.RESEARCH HIGHLIGHTS NDV vectored vaccine harbouring Y280-lineage H9N2 HA protein was successfully generated.NDV vectored vaccine provides protection against NDV.NDV vectored vaccine with H9N2 HA protects against homologous H9N2 LPAIV.

Image Registration of 18F-FDG PET/CT Using the MotionFree Algorithm and CT Protocols through Phantom Study and Clinical Evaluation.

We evaluated the benefits of the MotionFree algorithm through phantom and patient studies. The various sizes of phantom and vacuum vials were linked to RPM moving with or without MotionFree application. A total of 600 patients were divided into six groups by breathing protocols and CT scanning time. Breathing protocols were applied as follows: (a) patients who underwent scanning without any breathing instructions; (b) patients who were instructed to hold their breath after expiration during CT scan; and (c) patients who were instructed to breathe naturally. The length of PET/CT misregistration was measured and we defined the misregistration when it exceeded 10 mm. In the phantom tests, the images produced by the MotionFree algorithm were observed to have excellent agreement with static images. There were significant differences in PET/CT misregistration according to CT scanning time and each breathing protocol. When applying the type (c) protocol, decreasing the CT scanning time significantly reduced the frequency and length of misregistrations (p < 0.05). The MotionFree application is able to correct respiratory motion artifacts and to accurately quantify lesions. The shorter time of CT scan can reduce the frequency, and the natural breathing protocol also decreases the lengths of misregistrations.

Thermal Image Scanning for the Early Detection of Fever Induced by Highly Pathogenic Avian Influenza Virus Infection in Chickens and Ducks and Its Application in Farms.

Highly pathogenic avian influenza (HPAI) is considered as one of the most devastating poultry diseases. It is imperative to immediately report any known outbreaks to the World Organization for Animal Health. Early detection of infected birds is of paramount importance to control virus spread, thus minimizing the associated economic loss. In this study, thermal imaging camera devices were used to detect change in the maximum surface temperature (MST) of chickens (n = 5) and ducks (n = 2) as an early indicator of experimental HPAI infection. The MST of both chickens and ducks increased at least 24 h before the manifestation of clinical signs of HPAI infection, depending on the severity of the infection. The basal MST was recorded for broiler chickens housed under small pen and normal farm conditions without intentional infection. A threshold cutoff of MST was established based on the circadian rhythm of normal MST. This study suggests that thermal imaging of chickens and ducks is a promising tool to screen any potential HPAI-infected flock in order to expedite HPAI diagnosis.

Plant-based, adjuvant-free, potent multivalent vaccines for avian influenza virus via Lactococcus surface display.

Influenza epidemics frequently and unpredictably break out all over the world, and seriously affect the breeding industry and human activity. Inactivated and live attenuated viruses have been used as protective vaccines but exhibit high risks for biosafety. Subunit vaccines enjoy high biosafety and specificity but have a few weak points compared to inactivated virus or live attenuated virus vaccines, especially in low immunogenicity. In this study, we developed a new subunit vaccine platform for a potent, adjuvant-free, and multivalent vaccination. The ectodomains of hemagglutinins (HAs) of influenza viruses were expressed in plants as trimers (tHAs) to mimic their native forms. tHAs in plant extracts were directly used without purification for binding to inactivated Lactococcus (iLact) to produce iLact-tHAs, an antigen-carrying bacteria-like particle (BLP). tHAs BLP showed strong immune responses in mice and chickens without adjuvants. Moreover, simultaneous injection of two different antigens by two different formulas, tHAH5N6 + H9N2 BLP or a combination of tHAH5N6 BLP and tHAH9N2 BLP, led to strong immune responses to both antigens. Based on these results, we propose combinations of plant-based antigen production and BLP-based delivery as a highly potent and cost-effective platform for multivalent vaccination for subunit vaccines.

Live Recombinant NDV-Vectored H5 Vaccine Protects Chickens and Domestic Ducks From Lethal Infection of the Highly Pathogenic H5N6 Avian Influenza Virus.

The H5 subtype highly pathogenic avian influenza virus (HPAIV) has been introduced to South Korea every 2 or 3 years via wild migratory waterfowls, causing devastating damages to the poultry industry. Although most damages and economic losses by HPAIV are focused on chicken layers, domestic ducks are known to play a major role in the farm-to-farm transmission. However, most HPAIV vaccine studies on poultry have been performed with oil-emulsion inactivated vaccines. In this study, we developed a live recombinant Newcastle disease virus (NDV)-vectored vaccine against H5 HPAIV (rK148/ES2-HA) using a previously established NDV vaccine strain (K148/08) isolated from a wild mallard duck. The efficacy of the vaccine when administered via the oculonasal route or as a spray was evaluated against lethal H5 HPAIV infection in domestic ducks and chickens. Oculonasal inoculation of the rK148/ES2-HA in chickens and ducks elicited antibody titers against HPAIV as early as 1 or 2 week after the single dose of vaccination, whereas spray vaccination in ducks elicited antibodies against HPAIV after the booster vaccination. The chickens and ducks vaccinated with rK148/ES2-HA showed high survival rates and low viral shedding after H5N6 HPAIV challenge. Collectively, vaccination with rK148/ES2-HA prevented lethal infection and decreased viral shedding in both chickens and ducks. The vaccine developed in this study could be useful in suppressing the viral shedding in H5 HPAIV outbreaks, with the ease of vaccine application and fast onset of immunity.

Lightweight Driver Behavior Identification Model with Sparse Learning on In-Vehicle CAN-BUS Sensor Data.

This study focuses on driver-behavior identification and its application to finding embedded solutions in a connected car environment. We present a lightweight, end-to-end deep-learning framework for performing driver-behavior identification using in-vehicle controller area network (CAN-BUS) sensor data. The proposed method outperforms the state-of-the-art driver-behavior profiling models. Particularly, it exhibits significantly reduced computations (i.e., reduced numbers both of floating-point operations and parameters), more efficient memory usage (compact model size), and less inference time. The proposed architecture features depth-wise convolution, along with augmented recurrent neural networks (long short-term memory or gated recurrent unit), for time-series classification. The minimum time-step length (window size) required in the proposed method is significantly lower than that required by recent algorithms. We compared our results with compressed versions of existing models by applying efficient channel pruning on several layers of current models. Furthermore, our network can adapt to new classes using sparse-learning techniques, that is, by freezing relatively strong nodes at the fully connected layer for the existing classes and improving the weaker nodes by retraining them using data regarding the new classes. We successfully deploy the proposed method in a container environment using NVIDIA Docker in an embedded system (Xavier, TX2, and Nano) and comprehensively evaluate it with regard to numerous performance metrics.

sEMG-signal and IMU sensor-based gait sub-phase detection and prediction using a user-adaptive classifier.

This paper presents a gait sub-phase detection and prediction approach using surface electromyogram (sEMG) signals, pressure sensors, and the knee angle for a lower-limb power-assist robot. Pattern recognition and machine learning models using sEMG signals have several inherent problems for gait sub-phase detection. These problems are due to recognition delay, lack of consideration for the unique characteristics of sEMG signals based on the subject, and meaningless features. To solve these problems, we propose a new labeling technique based on the heel and toe, a muscle and feature selection, a user-adaptive classifier using a weighted voting technique to achieve gait sub-phase detection, and a gait sub-phase prediction technique using interpolation. Experimental results show that the average accuracies of the proposed labeling, the muscle and feature selection, and the user-adaptive classifier using weighted voting are 7%, 12%, and 17% better, respectively, than the existing methods using physical sensors. Results also show that the average prediction time of the proposed method is 80% faster than the existing methods.

BPC157 as Potential Agent Rescuing from Cancer Cachexia.

Cancer cachexia, one of the metabolic syndromes caused by cancer, is a devastating and miserable condition encountered in more than 50% of terminal cancer patients presenting with significant weight loss associated with skeletal muscle atrophy and fat loss. Though cachexia may account for up to 20% of cancer deaths, no significant treatment is still lacking and is of urgent unmet medical need in cancer treatment. Therefore, understanding the underlying molecular mechanisms is essential for anticipating therapeutic approaches. Since the primary events driving cachexia are mediated via either the central nervous system relatedor inflammation related-anorexia, hypoanabolism, and hypercatabolism, therapy usually targets nutritional support to compensate reduced food intake along with some anti-inflammatory agents to cover specific inflammation-related metabolic derangement, and encourages exercise to supplement reduced physical activity, but all proven to be not so effective so far. Therefore, combination therapies such as a standard multi-modal package including an anorexic agent, megestrol acetate, and anti-inflammatory agent coupled with the development of potential novel therapeutics promise a new era in rescuing patients from cancer cachexia. In this review, we propose the potential application of BPC157, one of the active cytoprotective agents isolated from gastric juices for cancer cachexia. Before clinical trial, we introduced the evidence showing BPC157 rescued from cancer cachexia supported with explored mode of actions.

Automatic evaluation of cardiac hypertrophy using cardiothoracic area ratio in chest radiograph images.

To evaluate the cardiac hypertrophy from chest radiograph images, radiologists usually examine the cardiothoracic ratio (frequently called CTR) which is a standard diagnostic index. The CTR is computed by the maximum transverse diameter of the heart shadow divided by the maximum transverse diameter of right and left lung boundaries. In this paper, we present a method to evaluate the cardiac hypertrophy by comparing the area of heart with that of lung, instead of the cardiothoracic ratio to get more desirable diagnostic results. We introduce a new index, a cardiothoracic area ratio (CTAR), which is computed by dividing the area of heart region by the area of lung region of specific interest. We first segment a chest region of interest in a radiograph image and then automatically compute the traditional CTR and the CTAR to evaluate the cardiac hypertrophy. And finally, we provide the visual presentation of those ratios on the chest radiograph image. The experimental results using a set of radiograph images show that the proposed method can be used effectively for determining the cardiac hypertrophy in a real-time diagnostic environment. It provides the higher discrimination power than the CTR to identify hypertrophied hearts by recognizing the heart enlargement. It also can be used together with the traditional CTR as a complementary measure when it is difficult to determine abnormalities by the CTR, reducing the rate of wrong diagnosis.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM).

Long-term care needs of the elderly in Korea and elderly long-term care insurance.

Korea is one of the fastest-aging societies in the world. According to the Korea National Statistical Office, the number of those aged 65 years and older will dramatically increase from 9.1% in 2005 to 37.3% in 2050. It is very evident that Korea must urgently prepare itself for new times. The government insurance policy for elderly people, now called long-term care insurance, is ultimately designed for providing home- and facility-based supports to seniors with geriatric diseases and dementia, as well as for reducing the support burden on other family members. This article is to introduce the long-term care insurance of Korea and thereby to advocates the necessity of international discussion of the prospects for developing health care for aging populations; its aim is to encourage the sharing of differing national experiences concerning care for the elderly.