Input-output linearization of DC-DC converter with discrete sliding mode fuzzy control strategy

The major thrust of the paper is on designing a fuzzy logic approach has been combined with a well-known robust technique discrete sliding mode control (DSMC) to develop a new strategy for discrete sliding mode fuzzy control (DSMFC) in direct current (DC-DC) converter. Proposed scheme requires human expertise in the design of the rule base and is inherently stable. It also overcomes the limitation of DSMC, which requires bounds of uncertainty to be known for development of a DSMC control law. The scheme is also applicable to higher order systems unlike model following fuzzy control, where formation of rule base becomes difficult with rise in number of error and error derivative inputs. In this paper the linearization of input-output performance is carried out by the DSMFC algorithm for boost converter. The DSMFC strategy minimizes the chattering problem faced by the DSMC. The simulated performance of a discrete sliding mode fuzzy controller is studied and the results are investigated.

Broad-spectrum mono- and combinational drug therapies for global viral pandemic preparedness

Broadly effective antiviral therapies must be developed to be ready for clinical trials, which should begin soon after the emergence of new life-threatening viruses. Here, we pave the way towards this goal by analyzing conserved druggable virus-host interactions, mechanisms of action and immunomodulatory properties of broad-spectrum antivirals (BSAs), routes of BSA delivery, and BSA interactions with other antivirals. Based on the analysis we developed scoring systems, which allowed us to predict novel BSAs and BSA-containing drug combinations (BCCs). Thus, we have developed a new strategy to broaden the spectrum of BSA indications and predict novel mono- and combinational therapies that can help better prepare for imminent future viral outbreaks.

Mirogabalin Decreases Pain-like Behaviours and Improves Opioid and Ketamine Antinociception in a Mouse Model of Neuropathic Pain

Neuropathic pain remains a difficult clinical challenge due to its diverse aetiology and complex pathomechanisms, which are yet to be fully understood. Despite the variety of available therapies, many patients suffer from ineffective pain relief; hence, the search for more efficacious treatments continues. The new gabapentinoid, mirogabalin has recently been approved for clinical use. Although its main mechanism of action occurs at the α2σ-1 and α2σ-2 subunits of calcium channels and is well documented, how the drug affects the disturbed neuropathic interactions at the spinal cord level has not been clarified, which is crucial information from a clinical perspective. The findings of our study suggest that several indirect mechanisms may be responsible for the beneficial analgesic effect of mirogabalin. This is the first study to report that mirogabalin enhances the mRNA expression of spinal antinociceptive factors, such as IL-10 and IL-18BP, and reduces the concentration of the pronociceptive substance P. Importantly, mirogabalin improves the morphine-, buprenorphine-, oxycodone-, and ketamine-induced antinociceptive effects in a neuropathic pain model. Our findings support the hypothesis that enhancing opioid and ketamine analgesia by combining these drugs with mirogabalin may represent a new strategy for the effective pharmacotherapy of neuropathic pain.

High-throughput direct screening of restriction endonuclease using microfluidic fluorescence-activated drop sorter based on SOS response in E. coli

A restriction endonuclease (RE) is an enzyme that can recognize a specific DNA sequence and cleave that DNA into fragments with double-stranded breaks. This sequence-specific cleaving ability and its ease of use have made REs commonly used tools in molecular biology since their first isolation and characterization in 1970s. While artificial REs still face many challenges in large-scale synthesis and precise activity control for practical use, searching for new REs in natural samples remains a viable route for expanding the RE pool for fundamental research and industrial applications. In this paper, we propose a new strategy to search for REs in an efficient fashion. Briefly, we construct a host bacterial cell to link the RE genotype to the phenotype of β-galactosidase expression based on the bacterial SOS response, and use a high-throughput microfluidic platform to isolate, detect and sort the REs. We employ this strategy to screen for the XbaI gene from constructed libraries of varied sizes. In single round of sorting, a 30-fold target enrichment was obtained within 1 h. The direct screening approach we propose shows potential for efficient search of desirable REs in natural samples compared to the conventional RE-screening method, and is amenable to being adapted to high-throughput screening of other genotoxic targets.

Transcription Factor Activation Profiles (TFAP) identify compounds promoting differentiation of Acute Myeloid Leukemia cell lines

Repurposing of drugs for new therapeutic use has received considerable attention for its potential to limit time and cost of drug development. Here we present a new strategy to identify chemicals that are likely to promote a desired phenotype. We used data from the Connectivity Map (CMap) to produce a ranked list of drugs according to their potential to activate transcription factors that mediate myeloid differentiation of leukemic progenitor cells. To validate our strategy, we tested the in vitro differentiation potential of candidate compounds using the HL-60 human cell line as a myeloid differentiation model. Ten out of 22 compounds, which were ranked high in the inferred list, were confirmed to promote significant differentiation of HL-60. These compounds may be considered candidate for differentiation therapy. The method that we have developed is versatile and it can be adapted to different drug repurposing projects.

Highly Sensitive Flexible Modulus Sensor for Softness Perception and Clinical Application

The wearable sensors for softness measuring are emerging as a solution of softness perception, which is an intrinsic function of human skin, for electronic skin and human-machine interaction. However, these wearable sensors suffer from a key challenge: the modulus of an object can not be characterized directly, which originates from the complicated transduction mechanism. To address this key challenge, we developed a flexible and wearable modulus sensor that can simultaneously measure the pressure and modulus without mutual interference. The modulus sensing was realized by merging the electrostatic capacitance response from the pressure sensor and the ionic capacitance response from the indentation sensor. Via the optimized structure, our sensor exhibits high modulus sensitivity of 1.9 × 102 in 0.06 MPa, a fast dynamic response time of 100 ms, and high mechanical robustness for over 2500 cycles. We also integrated the sensor onto a prosthetic hand and surgical probe to demonstrate its capability for pressure and modulus sensing. This work provides a new strategy for modulus measurement, which has great potential in softness sensing and medical application.