Although recent years have seen large decreases in the overall global rate of suicide fatalities, this trend is not reflected everywhere. Suicide and suicidal behaviour continue to present key challenges for public policy and health services, with increasing suicide deaths in some countries such as the USA. The development of suicide risk is complex, involving contributions from biological (including genetics), psychological (such as certain personality traits), clinical (such as comorbid psychiatric illness), social and environmental factors. The involvement of multiple risk factors in conveying risk of suicide means that determining an individual’s risk of suicide is challenging. Improving risk assessment, for example, by using computer testing and genetic screening, is an area of ongoing research. Prevention is key to reduce the number of suicide deaths and prevention efforts include universal, selective and indicated interventions, although these interventions are often delivered in combination. These interventions, combined with psychological (such as cognitive behavioural therapy, caring contacts and safety planning) and pharmacological treatments (for example, clozapine and ketamine) along with coordinated social and public health initiatives, should continue to improve the management of individuals who are suicidal and decrease suicide-associated morbidity. Suicide and suicidal behaviour continue to present key challenges for public policy and health services. This Primer discusses the global burden of suicide and suicidal behaviours, and provides an overview of our current understanding of the mechanisms of suicide, including risk factors for suicidal ideation and the transition from ideation to suicide attempt.

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Suicide and suicide risk

Towards an Understanding of Synapse Formation.

Critical fluctuation of the order parameter in type-ii superconductors.

https://europepmc.org/articles/PMC7497728?pdf=render

Microglial Remodeling of the Extracellular Matrix Promotes Synapse Plasticity.

Synaptic Specificity, Recognition Molecules, and Assembly of Neural Circuits

LixTMO2 (TM=Ni, Co, Mn) forms an important family of cathode materials for Li-ion batteries, whose performance is strongly governed by Li composition-dependent crystal structure and phase stability. Here, we use LixCoO2 (LCO) as a model system to benchmark a machine learning-enabled framework for bridging scales in materials physics. We focus on two scales: (a) assemblies of thousands of atoms described by density functional theory-informed statistical mechanics, and (b) continuum phase field models to study the dynamics of order-disorder transitions in LCO. Central to the scale bridging is the rigorous, quantitatively accurate, representation of the free energy density and chemical potentials of this material system by coarsegraining formation energies for specific atomic configurations. We develop active learning workflows to train recently developed integrable deep neural networks for such high-dimensional free energy density and chemical potential functions. The resulting, first principles-informed, machine learning-enabled, phase-field computations allow us to study LCO cathodes' phase evolution in terms of temperature, morphology, charge cycling and particle size.

Bridging scales with Machine Learning: From first principles statistical mechanics to continuum phase field computations to study order disorder transitions in LixCoO2

Most cognitive and psychiatric disorders are thought to be disorders of the synapse, yet the precise synapse defects remain unknown. Because synapses are highly specialized anatomical structures, defects in synapse formation and function can often be observed as changes in micro-scale neuroanatomy. Unfortunately, few methods are available for accurate analysis of synaptic structures in human postmortem tissues. Here, we present a methodological pipeline for assessing pre- and postsynaptic structures in human postmortem tissue that is accurate, rapid, and relatively inexpensive. Our method uses small tissue blocks from postmortem human brains, immersion fixation, DiI labeling, and confocal microscopy. As proof of principle, we analyzed pre- and postsynaptic structures from hippocampi of 13 individuals aged 4 months to 71 years. Our results indicate that postsynaptic CA1 dendritic spine shape and density do not change in adults, while presynaptic DG mossy fiber boutons undergo significant structural rearrangements with normal aging. This suggests that mossy fiber synapses, which play a major role in learning and memory, may remain dynamic throughout life. Importantly, we find that human CA1 spine densities observed using this method on tissue that is up to 28 hours postmortem is comparable to prior studies using tissue with much shorter postmortem intervals. Thus, the ease of our protocol and suitability on tissue with longer postmortem intervals should facilitate higher-powered studies of human pre and postsynaptic structures in healthy and diseased states.

/pdf/dii-mediated-analysis-of-pre-and-postsynaptic-structures-in-568jkfhm5l.pdf

DiI-mediated analysis of pre- and postsynaptic structures in human postmortem brain tissue

Photon-induced deactivation of traps in MAPbI3 can strongly affect charge relaxation behavior. Charge relaxation associated with photo-induced deactivation of various traps in MAPbI3 films was investigated through steady-state and time-resolved photoluminescence (PL) spectroscopy under laser excitation at 635 and 430 nm to investigate the properties of the traps. Three types of traps that could be deactivated by photons were observed in the MAPbI3 films, namely TL, TH, and TGB. TL and TH, which were related to MAPbI3 bulk, had low and high photon energy thresholds (red and blue photons) for deactivation, respectively. TGB was related to the traps at grain boundaries in MAPbI3 and had a low photon energy threshold (red photons) for deactivation. The energy level of TGB was higher than that of the conduction band of MAPbI3. Under blue excitation, TGB mediated a fast nonradiative recombination at few nanoseconds, and TL and TH mediated a slow nonradiative recombination at few 100 ns. The fast nonradiative recombination led to a significantly low initial normalized photoluminescence quantum yield (PLQY) (1/22) under blue excitation, compared with that obtained under red excitation (1/4). The deactivation of TL and TH resulted in increases in both the amplitude of PL and recombination time. The deactivation of TGB resulted only in a significant increase in PLQY of blue excitation.

S. Das

Papers

Bridging scales with Machine Learning: From first principles statistical mechanics to continuum phase field computations to study order disorder transitions in LixCoO2

DiI-mediated analysis of pre- and postsynaptic structures in human postmortem brain tissue

Charge relaxation associated with photon-induced deactivation of various traps in MAPbI3 films

Glutamate Transporter 1 and Cystine-glutamate Anti-porter: Therapeutic Targets for Alcohol Dependence

Study of effective de-Gennes factor and effect of doping on superconductivity in rare-earth nickel borocarbide superconductors