Anti-inflammatory and antioxidant traditional Chinese Medicine in treatment and prevention of osteoporosis

A metabolic bone disorder called osteoporosis is characterized by decreased bone mass and compromised microarchitecture. This condition can deteriorate bones and raise the risk of fractures. The two main causes of osteoporosis are an increase in osteoclast activity or quantity and a decrease in osteoblast viability. Numerous mechanisms, including estrogen shortage, aging, chemical agents, and decreased mechanical loads, have been linked to osteoporosis. Inflammation and oxidative stress have recently been linked to osteoporosis, according to an increasing number of studies. The two primary medications used to treat osteoporosis at the moment are bisphosphonates and selective estrogen receptor modulators (SERMs). These medications work well for osteoporosis brought on by aging and estrogen deprivation, however, they do not target inflammation and oxidative stress-induced osteoporosis. In addition, these drugs have some limitations that are attributed to various side effects that have not been overcome. Traditional Chinese medicine (TCM) has been applied in osteoporosis for many years and has a high safety profile. Therefore, in this review, literature related to botanical drugs that have an effect on inflammation and oxidative stress-induced osteoporosis was searched for. Moreover, the pharmacologically active ingredients of these herbs and the pathways were discussed and may contribute to the discovery of more safe and effective drugs for the treatment of osteoporosis

Implementation of carbon pricing in an aging world calls for targeted protection schemes

Understanding the impact of climate fiscal policies on vulnerable groups is a prerequisite for equitable climate mitigation. However, there has been a lack of attention to the impacts of such policies on the elderly, especially the low-income elderly, in existing climate policy literature. Here, we quantify and compare the distributional impacts of carbon pricing on different age-income groups in the United States, the United Kingdom, and Japan and then on different age groups in other 28 developed countries. We find that the elderly are more vulnerable to carbon pricing than younger groups in the same income group. In particular, the low-income elderly and elderly in less wealthy countries face greater challenges because carbon pricing lead to both higher rate of increase in living cost among low-income elderly and greater income inequality within the same age group. In addition, the low-income elderly would benefit less than the younger groups within the same income group in the commonly proposed carbon revenues recycling schemes. The high vulnerability of the low-income elderly to carbon pricing calls for targeted social protection along with climate mitigation polices toward an aging world

Service Differentiated and Adaptive CSMA/CA over IEEE 802.15.4 for Cyber-Physical Systems

Cyber-Physical Systems (CPS) that collect, exchange, manage information, and coordinate actions are an integral part of the Smart Grid. In addition, Quality of Service (QoS) provisioning in CPS, especially in the wireless sensor/actuator networks, plays an essential role in Smart Grid applications. IEEE 802.15.4, which is one of the most widely used communication protocols in this area, still needs to be improved to meet multiple QoS requirements. This is because IEEE 802.15.4 slotted Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA) employs static parameter configuration without supporting differentiated services and network self-adaptivity. To address this issue, this paper proposes a priority-based Service Differentiated and Adaptive CSMA/CA (SDA-CSMA/CA) algorithm to provide differentiated QoS for various Smart Grid applications as well as dynamically initialize backoff exponent according to traffic conditions. Simulation results demonstrate that the proposed SDA-CSMA/CA scheme significantly outperforms the IEEE 802.15.4 slotted CSMA/CA in terms of effective data rate, packet loss rate, and average delay

Study of spatio-temporal modeling in video quality assessment

Video quality assessment (VQA) has received remarkable attention recently. Most of the popular VQA models employ recurrent neural networks (RNNs) to capture the temporal quality variation of videos. However, each long-term video sequence is commonly labeled with a single quality score, with which RNNs might not be able to learn long-term quality variation well. A natural question then arises: What’s the real role of RNNs in learning the visual quality of videos? Does it learn spatio-temporal representation as expected or just aggregating spatial features redundantly? In this study, we conduct a comprehensive study by training a family of VQA models with carefully designed frame sampling strategies and spatio-temporal fusion methods. Our extensive experiments on four publicly available in-the-wild video quality datasets lead to two main findings. First, the plausible spatio-temporal modeling module ( i.e ., RNNs) does not facilitate quality-aware spatio-temporal feature learning. Second, sparsely sampled video frames are capable of obtaining the competitive performance against using all video frames as the input. In other words, spatial features play a vital role in capturing video quality variation for VQA. To our best knowledge, this is the first work to explore the issue of spatio-temporal modeling in VQA

A laser-engraved wearable sensor for sensitive detection of uric acid and tyrosine in sweat

Wearable sweat sensors have the potential to provide continuous measurements of useful biomarkers. However, current sensors cannot accurately detect low analyte concentrations, lack multimodal sensing or are difficult to fabricate at large scale. We report an entirely laser-engraved sensor for simultaneous sweat sampling, chemical sensing and vital-sign monitoring. We demonstrate continuous detection of temperature, respiration rate and low concentrations of uric acid and tyrosine, analytes associated with diseases such as gout and metabolic disorders. We test the performance of the device in both physically trained and untrained subjects under exercise and after a protein-rich diet. We also evaluate its utility for gout monitoring in patients and healthy controls through a purine-rich meal challenge. Levels of uric acid in sweat were higher in patients with gout than in healthy individuals, and a similar trend was observed in serum

Implementation of carbon pricing in an aging world calls for targeted protection schemes

Understanding the impact of climate fiscal policies on vulnerable groups is a prerequisite for equitable climate mitigation. However, there has been a lack of attention to the impacts of such policies on the elderly, especially the low-income elderly, in existing climate policy literature. Here, we quantify and compare the distributional impacts of carbon pricing on different age–income groups in the United States, the United Kingdom, and Japan and then on different age groups in other 28 developed countries. We find that the elderly are more vulnerable to carbon pricing than younger groups in the same income group. In particular, the low-income elderly and elderly in less wealthy countries face greater challenges because carbon pricing lead to both higher rate of increase in living cost among low-income elderly and greater income inequality within the same age group. In addition, the low-income elderly would benefit less than the younger groups within the same income group in the commonly proposed carbon revenues recycling schemes. The high vulnerability of the low-income elderly to carbon pricing calls for targeted social protection along with climate mitigation polices toward an aging world