Nobiletin Inhibits Expression of Inflammatory Mediators and Regulates JNK/ERK/p38 MAPK and PI3K/Akt Pathways in Human Osteoarthritic Chondrocytes

Purpose: To investigate the anti-inflammatory effects of nobiletin on human osteoarthritic chondrocytes and also to explore possible related molecular events.Methods: Isolated human osteoarthritic chondrocytes were stimulated with IL-1β. The effect of nobiletin (75, 150 or 300 μg) on chondrocyte viability was assessed. Furthermore, the effect on NO production was determined using Griess reagent while the levels of IL-6 and PGE2 were assessed by enzyme linked immunosorbent assay (ELISA). The influence of nobiletin on the expression of COX-2, iNOS and proteins of PI3/Akt, NF-κB and MAPK cascades were also assessed.Results: Nobiletin (75, 150 and 300 μg) significantly (p < 0.05) improved the viability of chondrocytes, and remarkably reduced the levels of NO, IL-6 and PGE2. The expression levels of COX-2 and iNOS both at mRNA and protein levels were strikingly reduced by nobiletin, in a dose-dependent way. In addition, nobiletin caused marked (p < 0.05) down-regulation of the NF-κB signalling pathway. IL-1β- induced activation of PI3/Akt, and JNK, ERK and p38 MAPK cascades were significantly (p < 0.05) inhibited by nobiletin with 300 μg dose exhibiting maximum effects.Conclusion: Inflammatory cytokines are critically involved in the pathogenesis of OA. Significant suppression of cytokines and modulation of PI3/Akt and MAPK signalling cascades by nobiletin suggests its potent anti-inflammatory and anti-osteoarthritic effects.Keywords: Chondrocytes, Inflammation, Mitogen-activated protein kinases, NF-κB, Nobiletin, Osteoarthriti

3,5-Dibromo-2-hydroxy­benzoic acid

The title compound, C7H4Br2O3, has an intra­molecular O—H⋯O=C hydrogen bond and aggregates to form hydrogen-bonded dimers via O—H⋯O inter­actions. The formation of zigzag one-dimensional mol­ecular tapes via C—H⋯Br inter­actions and π–π stacking inter­actions (inter­planar separation = 3.42 Å) completes the crystal structure

A low complexity multi-layered space frequency coding detection algorithm for MIMO-OFDM

A low complexity multi-layered space frequency OFDM (MLSF-OFDM) coding scheme is presented with the proposed two detection algorithms, fast QR decomposition detection algorithm or denoted as FAST-QR and enhanced FAST-QR (E-FAST-QR). Both algorithms not only reduce the implementation complexity of QR decomposition but also show a good performance in terms of bit error rate (BER). Hence, the proposed detection algorithms can be used to maintain guaranteed quality of service (QoS) in MIMO-OFDM system

Advances of Machine Learning in Materials Science: Ideas and Techniques

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution, with large database and repositories appearing everywhere. Traditionally, materials science is a trial-and-error field, in both the computational and experimental departments. With the advent of machine learning-based techniques, there has been a paradigm shift: materials can now be screened quickly using ML models and even generated based on materials with similar properties; ML has also quietly infiltrated many sub-disciplinary under materials science. However, ML remains relatively new to the field and is expanding its wing quickly. There are a plethora of readily-available big data architectures and abundance of ML models and software; The call to integrate all these elements in a comprehensive research procedure is becoming an important direction of material science research. In this review, we attempt to provide an introduction and reference of ML to materials scientists, covering as much as possible the commonly used methods and applications, and discussing the future possibilities.Comment: 80 pages; 22 figures. To be published in Frontiers of Physics, 18, xxxxx, (2023

Implementation of convolutional encoder and Viterbi decoder using VHDL

This work focuses on the realization of convolutional encoder and adaptive Viterbi decoder (AVD) with a constraint length, K of 3 and a code rate (k/n) of 1/2 using field-programmable gate array (FPGA) technology. This paper presents a 4-state, radix-2, hard decision AVD which has the ability to decode adaptively through different traceback length (TL). The performance of the implemented AVD is analyzed by using ISE 9.2 and MATLAB simulations. The AVD is targeted to a Xilinx XCV300PQ240-4 FPGA device for hardware realization. The decoder parameter TL can be reconfigured via the implementation of AVD, in accordance with the changing channel noise characteristics of the threshold signal-to-noise ratio (SNR), which is 6 dB. The synthesis results show that the reconfiguration parameter TL of 4 and 15 of AVD implementation has significant difference (>20% improvement) in FPGA device utilization. The results also show that the use of reconfiguration leads to a 28% area occupancy of slice usage improvement over a TL of 15 model compared to a TL of 4 model with tolerable loss of decode accuracy, in accordance with the bit error rate (BER) for real-time voice and video

Impact of COVID-19 lockdown on physical activity and mental health among undergraduate students

With the sudden change of environment and limited studies on the effects of COVID-19 lockdown among university students, this study therefore aims to examine the effects of COVID-19 lockdown on physical activity level and mental health among university students in Malaysia. This is a cross-sectional study involving university students studying in Klang Valley, Malaysia. Demographics information, living status during COVID-19, physical activity level and mental health status were obtained through online questionnaire via Microsoft forms. Paired T-test was used to compare the effect of physical activity level and mental health status during COVID-19 lockdown. Data on falls was available for 383 participants with 254 (66.3 %) women and 129 (33.7%) men. Overall, the metabolic equivalent task (MET) of vigorous, moderate, mild, and total MET has decreased during COVID-19 lockdown as compared to before COVID-19 lockdown. Approximately an increment of 6% of participants reported having depression and anxiety during COVID-19 lockdown. In conclusion, significant impact on physical activity level and mental health was found in our study. Our study findings could therefore assist educational institutions and policymakers in forming strategies to improve student’s overall health, yet further longitudinal studies should be performed to examine the long-term effects of COVID-19 lockdown

Dynamic transmit antenna shuffling scheme for MIMO wireless communication systems

Two novel dynamic transmit antenna shuffling schemes, namely ‘Optimal’ and ‘Max STBC’, are presented in order to reduce the interference in V-BLAST/STBC scheme. These antenna shuffling schemes with the channel state information (CSI) from the receiver, which significantly improves performance of the MIMO system in Rayleigh flat-fading channels by selecting the appropriate antenna shuffling pattern, have been compared with a few other related schemes in terms of BER and system capacity. The ‘Optimal’ antenna shuffling scheme improves the BER performance significantly with a gain of 2 dB at BER of 10–3 compared to all other schemes, while the ‘Max STBC’ antenna shuffling scheme enhances the V-BLAST/STBC system capacity by 4%

Demonstration of Adiabatic Variational Quantum Computing with a Superconducting Quantum Coprocessor

Adiabatic quantum computing enables the preparation of many-body ground states. This is key for applications in chemistry, materials science, and beyond. Realisation poses major experimental challenges: Direct analog implementation requires complex Hamiltonian engineering, while the digitised version needs deep quantum gate circuits. To bypass these obstacles, we suggest an adiabatic variational hybrid algorithm, which employs short quantum circuits and provides a systematic quantum adiabatic optimisation of the circuit parameters. The quantum adiabatic theorem promises not only the ground state but also that the excited eigenstates can be found. We report the first experimental demonstration that many-body eigenstates can be efficiently prepared by an adiabatic variational algorithm assisted with a multi-qubit superconducting coprocessor. We track the real-time evolution of the ground and exited states of transverse-field Ising spins with a fidelity up that can reach about 99%.Comment: 12 pages, 4 figure

GPS based child care system using RSSI technique

In today's society, missing child cases increases rapidly. Child care is a critical issue in solving this epidemic. Various systems and methods have been implemented in solving this crisis. In this paper, the global position system (GPS) based child care system is proposed to solve this problem. This system consists of two nodes; child and parent nodes, each carried by the child and parent respectively. The child node consists of a simple circuit that has a Bluetooth module and a GPS receiver. The parent node is a mobile device that has Bluetooth connection. The GPS technology helps to determine the exact position of the child. The parent node receives the location of the child and displays the information on a designed map using a GUI program that is embedded into the mobile device. Besides the location, the distance between parent and child can also be determined using Bluetooth connection. A data from received signal strength indicator (RSSI) is extracted out from the Bluetooth connection and is used as vital information in determining the distance between parent and child. An alert is triggered when the distance between the parent and child is far apart for a certain range. The proposed system proves to be useful as a locator that could locate missing and wandering child for the parents