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The combined utility of many one and two dimensional NMR methodologies and DFT-based theoretical calculations have been exploited to detect the intramolecular hydrogen bond (HB) in number of different organic fluorine-containing derivatives of molecules, viz. benzanilides, hydrazides, imides, benzamides, and diphenyloxamides. The existence of two and three centered hydrogen bonds has been convincingly established in the investigated molecules. The NMR spectral parameters, viz., coupling mediated through hydrogen bond, one-bond NH scalar couplings, physical parameter dependent variation of chemical shifts of NH protons have paved the way for understanding the presence of hydrogen bond involving organic fluorine in all the investigated molecules. The experimental NMR findings are further corroborated by DFT-based theoretical calculations including NCI, QTAIM, MD simulations and NBO analysis. The monitoring of H/D exchange with NMR spectroscopy established the effect of intramolecular HB and the influence of electronegativity of various substituents on the chemical kinetics in the number of organic building blocks. The utility of DQ-SQ technique in determining the information about HB in various fluorine substituted molecules has been convincingly established.

Who takes risks, and when? The relative state model proposes two non-independent selection pressures governing risk-taking: need-based and ability-based. The need-based account suggests that actors take risks when they cannot reach target states with low-risk options (consistent with risk-sensitivity theory). The ability-based account suggests that actors engage in risk-taking when they possess traits or abilities that increase the expected value of risk-taking (by increasing the probability of success, enhancing payoffs for success or buffering against failure). Adaptive risk-taking involves integrating both considerations. Risk-takers compute the expected value of risk-taking based on their state —the interaction of embodied capital relative to one's situation, to the same individual in other circumstances or to other individuals. We provide mathematical support for this dual pathway model, and show that it can predict who will take the most risks and when (e.g. when risk-taking will be performed by those in good, poor, intermediate or extreme state only). Results confirm and elaborate on the initial verbal model of state-dependent risk-taking: selection favours agents who calibrate risk-taking based on implicit computations of condition and/or competitive (dis)advantage, which in turn drives patterned individual differences in risk-taking behaviour.

Axons are long slender portions of neurons that transmit electrical impulses to maintain proper physiological functioning. Axons in the central nervous system (CNS) and peripheral nervous system (PNS) do not exist in isolation but are found to form a complex association with their surrounding glial cells, oligodendrocytes and Schwann cells. These cells not only myelinate them for faster nerve impulse conduction but are also known to provide metabolic support. Due to their incredible length, continuous growth, and distance from the cell body (where major energy synthesis takes place), axons are in high energetic demand. The stability and integrity of axons have long been associated with axonal energy levels. The current mini-review is thus focused on how axons accomplish their high energetic requirement in a cell-autonomous manner and how the surrounding glial cells help them in maintaining their integrity by fulfilling their energy demands (non-cell autonomous trophic support). The concept that adjacent glial cells (oligodendrocytes and Schwann cells) provide trophic support to axons and assist them in maintaining their integrity comes from the conditional knockout research and the studies in which the metabolic pathways controlling metabolism in these glial cells are modulated and its effect on axonal integrity is evaluated. In the later part of the mini-review, the current knowledge of axon-glial metabolic coupling during various neurodegenerative conditions was discussed, along with the potential lacunae in our current understanding of axon-glial metabolic coupling.

Some evidence suggests that people behave more cooperatively and generously when observed or in the presence of images of eyes (termed the ‘watching eyes’ effect). Eye images are thought to trigger feelings of observation, which in turn motivate people to behave more cooperatively to earn a good reputation. However, several recent studies have failed to find evidence of the eyes effect. One possibility is that inconsistent evidence in support of the eyes effect is a product of individual differences in sensitivity or susceptibility to the cue. In fact, some evidence suggests that people who are generally more prosocial are less susceptible to situation-specific reputation-based cues of observation. In this paper, we sought to (1) replicate the eyes effect, (2) replicate the past finding that people who are dispositionally less prosocial are more responsive to observation than people who are more dispositionally more prosocial, and (3) determine if this effect extends to the watching eyes effect. Results from a pre-registered study showed that people did not give more money in a dictator game when decisions were made public or in the presence of eye images, even though participants felt more observed when decisions were public. That is, we failed to replicate the eyes effect and observation effect. An initial, but underpowered, interaction model suggests that egoists give less than prosocials in private, but not public, conditions. This suggests a direction for future research investigating if and how individual differences in prosociality influence observation effects.

Olfactory perception and learning play a vital role in the animal’s entire life for habituation and survival. Insulin and insulin receptor signaling is well known to modulate the olfactory function and is also involved in the regulation of neurogenesis. A very high density of insulin receptors is present in the olfactory bulb (OB), the brain area involved in the olfactory function, where active adult neurogenesis also takes place. Hence, our study was aimed to explore the effect of intranasal insulin treatment and the involvement of the subventricular zone–olfactory bulb (SVZ-OB) neurogenesis on olfactory discriminative learning and memory in intracerebroventricular streptozotocin (ICV STZ) rat model. Our findings revealed that intranasal insulin treatment significantly increased ICV STZ–induced decrease in the olfactory discriminative learning. No significant change was observed in the post-treatment olfactory memory upon ICV STZ and intranasal insulin treatment. ICV STZ also caused a substantial decline in the SVZ-OB neurogenesis, as indicated by the reduction in the number of 5-bromo-2′-deoxyuridine (BrdU + ) cells, BrdU + Nestin + cells, and Doublecortin (DCX + ) cells, which was reversed by intranasal insulin treatment. Intranasal insulin treatment also increased the number of immature neurons reaching the olfactory bulb (OB) as indicated by an increase in the DCX expression in the OB as compared to the ICV STZ administered group. ICV STZ administration also resulted in the modulation of the expression of the genes regulating postnatal SVZ-OB neurogenesis like Mammalian achaete scute homolog 1 (Mash 1), Neurogenin 2 (Ngn 2), Neuronal differentiation 1 (Neuro D1), and T box brain protein 2 (Tbr 2). Intranasal insulin treatment reverted these changes in gene expression, which might be responsible for the observed increase in the SVZ-OB neurogenesis and hence the olfactory discriminative learning.

We had previously reported that neuroinflammation and memory impairment associated with intracerebroventricular streptozotocin (ICV STZ) injection in rats was due to glial activation and modulation of the N-methyl-D-aspartate (NMDA) receptor function. However, the exact role of the NMDA receptor and the molecules associated with downstream calcium ion signaling in STZ-induced astroglial activation is not known. Thus, in the present study, Memantine (an NMDA receptor antagonist) and Ibuprofen (an anti-inflammatory drug) were used as the pharmacological tool to investigate the molecular mechanisms involved in STZ-induced astroglial inflammation. We have studied the effect of STZ (100 μM) treatment for 24 h on NMDA receptor subunits (NR1, NR2A, and NR2B) expression and its associated calcium ion regulated molecules calcium/calmodulin-dependent protein kinase II subunit α (CaMKIIα), cyclic AMP-response element-binding (CREB) protein, Calpain, and Caspase 3. We have found a significant increase in the expression of NR1, NR2B, Calpain, and Caspase 3 expression, whereas a decrease in the level of NR2A, CaMKIIα, and CREB protein expression after 24 h of STZ treatment. These results indicate that STZ altered the NMDA receptor subunit expression and its downstream calcium (Ca 2+ ) ion signaling molecules. We have also found that both Memantine (5 µM) and Ibuprofen (200 μM) significantly prevented the STZ-induced change in CaMKIIα, CREB, Calpain, and Caspase 3 expressions in C6 astrocytoma cells. Interestingly, only Memantine (and not Ibuprofen) was able to prevent the changes in NMDA receptor subunit expression in STZ-treated astrocytoma cells. STZ treatment also increased the level of glial fibrillary acidic protein (GFAP), tumor necrosis factor-alpha (TNF-α), inducible nitric oxide synthase (iNOS), and decreased the level of interleukin-10 (IL-10), indicating inflammatory condition, which was restored by both Memantine and Ibuprofen. These results suggest that both Memantine and Ibuprofen exert anti-inflammatory effect against STZ-induced astroglial activation and neuroinflammation via modulation of NMDA receptor-associated downstream calcium signaling cascade. However, only Memantine (not Ibuprofen) was able to revert STZ-induced changes in NMDA receptor subunit expression. Graphic abstract

Background Cognitive-behavioral therapy (CBT) is one of the most widely tested and empirically supported psychological treatments for depression. Beck and other scholars established the theoretical foundations of CBT among North American populations, yet surprisingly few studies have examined central hypotheses of the cognitive model of depression among people living in non-Western regions. Methods In the present study, we used the alignment method to minimize measurement bias to examine several central hypotheses of the cognitive model among adults living on four continents ( n  = 752): North America ( n  = 103; female = 29.1%), Europe ( n  = 404; female = 36.4%), South America ( n  = 108; female = 18.5%), and Asia ( n  = 136; female = 19.9%). Results Depressive symptoms were positively and strongly correlated with negative automatic thoughts about self (ATQ-N), and moderately associated with dysfunctional attitudes (DAS) among people living on the four continents. Further, use of emotional suppression strategies to regulate emotion (ERQ-Suppression) was moderately and positively associated with depressive symptoms among people on all four continents, while use of cognitive-reappraisal (ERQ-Reappraisal) was not systematically associated with depressive symptoms. Conclusions Results of this study offer preliminary cross-continental support for foundational hypotheses of the cognitive model of depression. Negative thoughts appear to be associated with depression in all regions of the world, cementing this construct as a hallmark feature of the disorder.

Background and Aims: Airway ultrasound is an emerging tool to predict difficult laryngoscopy. This study aimed to determine the utility of ultrasound measurement of the anterior soft tissue neck thickness at the level of hyoid, thyrohyoid membrane and thickness of tongue to predict difficult laryngoscopy and compare them with clinical parameters for airway assessment. Methods: The distance from skin to hyoid bone, skin to the thyrohyoid membrane in neutral and sniffing position and maximum tongue thickness was measured by ultrasound and correlated with Cormack Lehane (CL) laryngoscope view in 310 adult surgical patients. Receiver operating characteristic curve was plotted and the area under the curve was calculated for each parameter. The sensitivity and specificity of ultrasound-guided parameters were compared with clinical parameters like the inter-incisor gap, modified Mallampatti classification, thyromental, sternomental distance and neck circumference. Results: Incidence of difficult laryngoscopy (CL grade-III and IV) was 11.3%. A significant difference was observed in the ultrasound parameters between the easy and difficult laryngoscopy (P-value = 0.001). Sensitivity and specificity to predict difficult airway was 69.6% and 77% for tongue thickness, 68% and 73% for the skin to hyoid bone distance in a neutral position and found to be higher than clinical parameters. Conclusion: The ultrasound measurements of soft tissue thickness of the anterior neck and tongue thickness along with the clinical assessment of airway can be useful in predicting difficult laryngoscopy.

The Internet of Things (IoT) is rapidly becoming one of the most talked-about and essential components of any digitization process. The IoT is comprised of several key necessary components, the most important of which are sensors, communication (the internet), and user interfaces for data processing. IoTs are currently finding applications in virtually every industry, including healthcare, where they are known as the internet of medical things (IoMT), industry, where they are known as the industrial internet of things (IIoT), and interconnection between people, where they are known as the internet of everything (IoE). The challenge is to leverage the Internet of Things (IoT), technology, and data to create smarter and more sustainable cities that enhance the quality of life for residents. Therefore, in this article; we have demonstrated the use of the IoT in a variety of applications for smart communities. These applications include smart transportation, smart water management, smart garbage management, smart house illumination, smart parking, smart infrastructure, etc. This research also includes an explanation of the flow process of implementing the IoT in different applications of smart communities, as well as their characteristics and particular applications. Along with their flow illustration, the stages involved in the implementation of smart city applications and the components they consist of are also displayed here. We have also taken into consideration the instances of particular cases and their implementation utilizing IoT. Some of these cases include the automated water collection methods of smart water management systems as well as the condition of the water. Based on the findings of the research, we came to the conclusion that IoT devices play an essential role in each and every one of the smart city project implementations.

Environmental pollution is a global concern: currently, there is an increased spread of contaminants with heightened urbanization and industrialization. Such contaminants are pesticides, heavy metals (HMs), metalloids, including xenobiotics viz BPA, PVC, and freons. Currently, numerous HMs, such as cadmium, arsenic, and mercury, are interfering with health impacts people. About 17 HMs come under the category of highly risky and easily accessible. The present article represented the categorization of various HMs, their sources, and their impacts on plants, such as plant growth, health-hazardous impacts human health. Moreover, artificial intelligence (AI) has played a vital role in identifying screening as well as the mitigation of heavy metal and metalloid. AI-driven sensor systems, AI, along with the Internet of Things (IoT) can play pivotal role in monitoring the environment. Pollutant removal potential of plants can be examined in real-time using AI technologies, such as image analysis (IA) and growth pattern recognition (GPR). So that by technology improvement, AI can support efficiency of various remedial strategies to mitigate the adverse impact of toxicants, ensuring both environmental sustainability and human health. The present review highlighted about risk assessment of HMs in living organisms, including plants and humans. Moreover, AI can be a milestone to intensify the screening, mapping, and regulating toxic metals as well as metalloids in the environment. AI undoubtedly streamlines the environmental sustainability and public health.