Cells sense a variety of different mechanochemical stimuli and promptly react to such signals by reshaping their morphology and adapting their structural organization and tensional state. Cell reactions to mechanical stimuli arising from the local microenvironment, mechanotransduction, play a crucial role in many cellular functions in both physiological and pathological conditions. To decipher this complex process, several studies have been undertaken to develop engineered materials and devices as tools to properly control cell mechanical state and evaluate cellular responses. Recent reports highlight how the nucleus serves as an important mechanosensor organelle and governs cell mechanoresponse. In this review, we will introduce the basic mechanisms linking cytoskeleton organization to the nucleus and how this reacts to mechanical properties of the cell microenvironment. We will also discuss how perturbations of nucleus-cytoskeleton connections, affecting mechanotransduction, influence health and disease. Moreover, we will present some of the main technological tools used to characterize and perturb the nuclear mechanical state.Fatty alcohols (FA-OH) are aliphatic unbranched primary alcohols with a chain of four or more carbon atoms. Besides potential industrial applications, fatty alcohols have important biological functions as well. In nature, fatty alcohols are produced as a part of a mixture of pheromones in several insect species, such as moths, termites, bees, wasps, etc. In addition, FA-OHs have a potential for agricultural applications, for example, they may be used as a suitable substitute for commercial insecticides. The insecticides have several drawbacks associated with their preparation, and they exert a negative impact on the environment. Currently, pheromone components are prepared mainly through the catalytic hydrogenation of plant oils and petrochemicals, which is an unsustainable, ecologically unfriendly, and highly expensive process. The biotechnological production of the pheromone components using engineered microbial strains and through the expression of the enzymes participating in the biosynthesis of these com0 produced only 16 carbon atom-long FA-OHs with a titer of 14.6 mg/L.Synthetic organic compounds (SOCs) are reported as xenobiotics compounds contaminating the environment from various sources including waste from the pulp and paper industries Since the demand and production of paper is growing increasingly, the release of paper and pulp industrial waste consisting of SOCs is also increasing the SOCs' pollution in natural reservoirs to create environmental pollution. In pulp and paper industries, the SOCs viz. phenol compounds, furans, dioxins, benzene compounds etc. are produced during bleaching phase of pulp treatment and they are principal components of industrial discharge. This review gives an overview of various biotechnological interventions for paper mill waste effluent management and elimination strategies. Further, the review also gives the insight overview of various ways to restrict SOCs release in natural reservoirs, its limitations and integrated approaches for SOCs bioremediation using engineered microbial approaches. Furthermore, it gives a brief overview of the sustainable remediation of SOCs via genetically modified biological agents, including bioengineering system innovation at industry level before waste discharge.Substrate surface characteristics such as roughness, wettability and particle density are well-known contributors of a substrate's overall osteogenic potential.  https://www.selleckchem.com/products/abt-199.html  These characteristics are known to regulate cell mechanics as well as induce changes in cell stiffness, cell adhesions, and cytoskeletal structure. Pro-osteogenic particles, such as hydroxyapatite, are often incorporated into a substrate to enhance the substrates osteogenic potential. However, it is unknown which substrate characteristic is the key regulator of osteogenesis. This is partly due to the lack of understanding of how these substrate surface characteristics are transduced by cells. In this study substrates composed of polycaprolactone (PCL) and carbonated hydroxyapatite particles (HAp) were synthesized. HAp concentration was varied, and a range of surface characteristics created. The effect of each substrate characteristic on osteoblastic differentiation was then examined. We found that, of the characteristics examined, only HAp density, and indeed a specific density (85 particles/cm2), significantly increased osteoblastic differentiation. Further, an increase in focal adhesion maturation and turnover was observed in cells cultured on this substrate. Moreover, β-catenin translocation from the membrane bound cell fraction to the nucleus was more rapid in cells on the 85 particle/cm2 substrate compared to cells on tissue culture polystyrene. Together, these data suggest that particle density is one pivotal factor in determining a substrates overall osteogenic potential. Additionally, the observed increase in osteoblastic differentiation is a at least partly the result of β-catenin translocation and transcriptional activity suggesting a β-catenin mediated mechanism by which substrate surface characteristics are transduced.Muscle co-contraction generates joint stiffness to improve stability and accuracy during limb movement but at the expense of higher energetic cost. However, quantification of joint stiffness is difficult using either experimental or computational means. In contrast, quantification of muscle co-contraction using an EMG-based Co-Contraction Index (CCI) is easier and may offer an alternative for estimating joint stiffness. This study investigated the feasibility of using two common CCIs to approximate lower limb joint stiffness trends during gait. Calibrated EMG-driven lower extremity musculoskeletal models constructed for two individuals post-stroke were used to generate the quantities required for CCI calculations and model-based estimation of joint stiffness. CCIs were calculated for various combinations of antagonist muscle pairs based on two common CCI formulations Rudolph et al. (2000) (CCI1) and Falconer and Winter (1985) (CCI2). CCI1 measures antagonist muscle activation relative to not only total activation of agonist plus antagonist muscles but also agonist muscle activation, while CCI2 measures antagonist muscle activation relative to only total muscle activation.