Quantitative biology regarding tactical underneath prescription antibiotic therapies

Advancements in programmable DNA-binding proteins (DBDs) that target the genome, such as zinc fingers, transcription activator-like effectors, and Cas9, have broadened drug target design beyond traditional protein substrates. Effective delivery methodologies remain a major barrier in targeting the central nervous system. Currently, adeno-associated virus is the most well-validated delivery system for the delivery of DBDs towards the central nervous with multiple, on-going clinical trials. While effective in transducing neuronal cells, viral delivery systems for DBDs remain problematic due to inherent viral packaging limits or immune responses that hinder translational potential. Direct administration of DBDs or encapsulation in lipid nanoparticles may provide alternative means towards delivering gene therapies into the central nervous system. This review will evaluate strengths and limitations in current DBD delivery strategies in-vivo. Furthermore, this review will discuss the use of adult stem cells as a putative delivery vehicle for DBDs and potential advantages that these systems have over previous methodologies.Curcuma longa (Turmeric) is a tropical herbaceous perennial plant of the family Zingiberaceae and contains curcuminoids, sesquiterpenoids and monoterpenoids as its major components. Given the broad range of activities that Curcuma Longa possesses and also its use as a traditional epilepsy remedy, this review attempts to systematically review the experimentally proven activities of Curcuma longa and its bioactive components, which are related to the management of epileptic seizures. Using the PRISMA model, five databases (Google Scholar, PubMed, ScienceDirect, SCOPUS and SpringerLink) were searched using the keywords ["Curcuma longa" AND "Epilepsy"] and ["Curcuma longa" AND "Seizures"], leaving with 34 articles that met the inclusion criteria. The present systematic review elaborated on the experimentally proven potential of Curcuma longa components, such as an aqueous extract of Curcuma longa itself, Curcuma longa oil and active constituents like curcuminoids and bisabolene sesquiterpenoids found in Curcuma longa with anti-seizure potential. Using human equivalent dose calculations, human treatment parameters were suggested for each component by analysing various studies in this review. This review also determined that the principal components possibly exert their anti-seizure effect via the reduction of corticosterone, modulation of neurotransmitters signalling, modulation of sodium ion channels, reduction of oxidative DNA damage, reduction of lipid peroxidation, upgregulation of brain-derived neurotrophic factor (BDNF) and γ-aminobutyric acid (GABA) mediated inhibition. It is anticipated that this review will help pave the way for future research into the development of Curcuma longa and its neuroactive constituents as potential drug candidates for the management of epilepsy.Sleep disorders are one of the most common non-motor symptoms in Parkinson's disease (PD). It can cause a notably decrease in quality of life and functioning in PD patients, as well as place a huge burden on both patients and caregivers. The most cited sleep disorders in PD included insomnia, restless legs syndrome (RLS), rapid eye movement (REM) sleep behavior disorders (RBD), excessive daytime sleepiness (EDS) and sleep disordered breathing (SDB), which can appear alone or several at the same time. In this review, we listed the recommended pharmacological treatments for common sleep disorders in PD, and discussed the recommended dosages, benefits and side effects of relative drugs. We also discussed non-pharmacological treatments to improve sleep quality, including sleep hygiene education, exercise, deep brain stimulation, cognitive behavior therapy and complementary therapies. We tried to find proper interventions for different types of sleep disorders in PD, while minimizing relative side effects.Traumatic injuries of the brain and spinal cord are a significant source of mortality and long-term disability. A recent systematic study in a rat model of spinal cord injury (SCI) indicates severe, destructive, and very protracted inflammation as the key mechanism initiated by the massive injury involving the white matter. Although the severe inflammation is localized and counteracted by astrogliosis, it has a damaging effect on the blood vessels in the surrounding spinal cord, leading to persistent vasogenic edema. To evaluate these injuries, imaging of the brain and spinal cord plays a crucial role in the acute trauma work-up, allowing clinicians to quickly identify abnormalities that require immediate medical or surgical intervention or to exclude them from the work-up. selleck chemicals llc Recently, anti-inflammatory agents have been shown to inhibit and accelerate the elimination of post-SCI inflammation in preclinical studies, and an exciting potential has arisen for the use of anti-inflammatory drugs in clinical studies to achieve neuroprotection (i.e., inhibition of destruction caused by inflammation) and to inhibit vasogenic edema in SCI, traumatic brain injury, and stroke. In both subacute and chronic settings, imaging can be a guide to therapy and provide important prognostic information. In this review, we discuss the imaging work-up and evolving imaging findings of neurotrauma in the acute and chronic setting, including conventional and advanced imaging techniques. As neuroimaging is the primary mode of diagnostic analysis in neurotrauma, it is a critical component in future clinical trials evaluating neuroprotective therapies.
Increasing research reveals that long non-coding RNAs (lncRNAs) play an important role in various biological processes of human diseases. Nonetheless, only a handful of lncRNA-disease associations have been experimentally verified. The study of lncRNA-disease association prediction based on the computational model has provided a preliminary basis for biological experiments to a great degree so as to cut down the huge cost of wet lab experiments.
This study aims to learn the real distribution of lncRNA-disease association from a limited number of known lncRNA-disease association data. This paper proposes a new lncRNA-disease association prediction model called LDA-GAN based on a generative adversarial network (GAN).
Aiming at the problems of slow convergence rate, training instabilities, and unavailability of discrete data in traditional GAN, LDA-GAN utilizes the Gumbel-softmax technology to construct a differentiable process for simulating discrete sampling. Meanwhile, the generator and the discriminator of LDA-GAN are integrated to establish the overall optimization goal based on the pairwise loss function.