Views on antioxidant mouthwashes as adjunct in periodontal therapy

Clinical decision is often difficult with chlorhexidine mouthwash. The use of antioxidant mouthwashes for the treatment of periodontal disease is in practise. Therefore, it is of interest to collect gleaned information on Antioxidant mouthwashes as periodontal therapy from known literature. Improvement in treatment using antioxidant mouthwashes is reported in several studies. The mouthwash with antioxidants has similar anti-gingivitis, antiplaque and antimicrobial effects as that of chlorhexidine mouthwash.     

Tracking unstable states: ecosystem dynamics in a changing world

Ecological systems can show complex and sometimes abrupt responses to environmental change, with important implications for their resilience. Theories of alternate stable states have been used to predict regime shifts of ecosystems as equilibrium responses to sufficiently slow environmental change. The actual rate of environmental change is a key factor affecting the response, yet we are still lacking a non-equilibrium theory that explicitly considers the influence of this rate of environmental change. We present a metacommunity model of predator–prey interactions displaying multiple stable states, and we impose an explicit rate of environmental change in habitat quality (carrying capacity) and connectivity (dispersal rate). We study how regime shifts depend on the rate of environmental change and compare the outcome with a stability analysis in the corresponding constant environment. Our results reveal that in a changing environment, the community can track states that are unstable in the constant environment. This tracking can lead to regime shifts, including local extinctions, that are not predicted by alternative stable state theory. In our metacommunity, tracking unstable states also controls the maintenance of spatial heterogeneity and spatial synchrony. Tracking unstable states can also lead to regime shifts that may be reversible or irreversible. Our study extends current regime shift theories to integrate rate-dependent responses to environmental change. It reveals the key role of unstable states for predicting transient dynamics and long-term resilience of ecological systems to climate change.     

RUNX1T1, a potential prognostic marker in breast cancer,is co-ordinately expressed with ERα, and regulated by estrogen receptor signalling in breast cancer cells

Molecular Biology Reports - RUNX1T1 is extensively studied in the context of AML1-RUNX1T1 fusion protein in acute myeloid leukemia. Little is known about the function of RUNX1T1 itself, although...     

Knock-down of glucose transporter and sucrose non-fermenting gene in the hemibiotrophic fungus Colletotrichum falcatum causing sugarcane red rot

Molecular Biology Reports - Red rot caused by Colletotrichum falcatum, is one of the economically important disease of sugarcane and breeding for resistant varieties is considered to be the major...     

MicroRNA profiles in Sorghum exposed to individual drought or heat or their combination

Sorghum is largely grown for food, fodder and for biofuel production in semi-arid regions where the drought or high temperature or their combination co-occur. Plant microRNAs (miRNAs) are integral to the gene regulatory networks that control almost all biological processes including adaptation to stress conditions. Thus far, plant miRNA profiles under separate drought or heat stresses have been reported but not under combined drought and heat. In this study, we report miRNA profiles in leaves of sorghum exposed to individual drought or heat or their combination. Approximately 29 conserved miRNA families represented by 80 individual miRNAs, 26 families represented by 47 members of less conserved or sorghum-specific miRNA families as well as 8 novel miRNA families have been identified. Of these, 25 miRNAs were found to be differentially regulated in response to stress treatments. The comparative profiling revealed that the miRNA regulation was stronger under heat or combination of heat and drought compared to the drought alone. Furthermore, using degradome sequencing, 48 genes were confirmed as targets for the miRNAs in sorghum. Overall, this study provides a framework for understanding of the miRNA-guided gene regulations under combined stresses.

     

Endoplasmic reticulum maintains ion homeostasis required for plasma membrane repair

Of the many crucial functions of the ER, homeostasis of physiological calcium increase is critical for signaling. Plasma membrane (PM) injury causes a pathological calcium influx. Here, we show that the ER helps clear this surge in cytoplasmic calcium through an ER-resident calcium pump, SERCA, and a calcium-activated ion channel, Anoctamin 5 (ANO5). SERCA imports calcium into the ER, and ANO5 supports this by maintaining electroneutrality of the ER lumen through anion import. Preventing either of these transporter activities causes cytosolic calcium overload and disrupts PM repair (PMR). ANO5 deficit in limb girdle muscular dystrophy 2L (LGMD2L) patient cells compromises their cytosolic and ER calcium homeostasis. By generating a mouse model of LGMD2L, we find that PM injury causes cytosolic calcium overload and compromises the ability of ANO5-deficient myofibers to repair. Addressing calcium overload in ANO5-deficient myofibers enables them to repair, supporting the requirement of the ER in calcium homeostasis in injured cells and facilitating PMR.     

Signal-to-signal neural networks for improved spike estimation from calcium imaging data

Spiking information of individual neurons is essential for functional and behavioral analysis in neuroscience research. Calcium imaging techniques are generally employed to obtain activities of neuronal populations. However, these techniques result in slowly-varying fluorescence signals with low temporal resolution. Estimating the temporal positions of the neuronal action potentials from these signals is a challenging problem. In the literature, several generative model-based and data-driven algorithms have been studied with varied levels of success. This article proposes a neural network-based signal-to-signal conversion approach, where it takes as input raw-fluorescence signal and learns to estimate the spike information in an end-to-end fashion. Theoretically, the proposed approach formulates the spike estimation as a single channel source separation problem with unknown mixing conditions. The source corresponding to the action potentials at a lower resolution is estimated at the output. Experimental studies on the spikefinder challenge dataset show that the proposed signal-to-signal conversion approach significantly outperforms state-of-the-art-methods in terms of Pearson’s correlation coefficient, Spearman’s rank correlation coefficient and yields comparable performance for the area under the receiver operating characteristics measure. We also show that the resulting system: (a) has low complexity with respect to existing supervised approaches and is reproducible; (b) is layer-wise interpretable, and (c) has the capability to generalize across different calcium indicators.     

Could Dermaseptin Analogue be a Competitive Inhibitor for ACE2 Towards Binding with Viral Spike Protein Causing COVID19?: Computational Investigation

International Journal of Peptide Research and Therapeutics - Initial phase of COVID-19 infection is associated with the binding of viral spike protein S1 receptor binding domain (RBD) with the host...