Are sedatives and hypnotics associated with increased suicide risk of suicide in the elderly?

<p>Abstract</p> <p>Background</p> <p>While antidepressant-induced suicidality is a concern in younger age groups, there is mounting evidence that these drugs may reduce suicidality in the elderly. Regarding a possible association between other types of psychoactive drugs and suicide, results are inconclusive. Sedatives and hypnotics are widely prescribed to elderly persons with symptoms of depression, anxiety, and sleep disturbance. The aim of this case-control study was to determine whether specific types of psychoactive drugs were associated with suicide risk in late life, after controlling for appropriate indications.</p> <p>Methods</p> <p>The study area included the city of Gothenburg and two adjacent counties (total 65+ population 210 703 at the start of the study). A case controlled study of elderly (65+) suicides was performed and close informants for 85 suicide cases (46 men, 39 women mean age 75 years) were interviewed by a psychiatrist. A population based comparison group (n = 153) was created and interviewed face-to-face. Primary care and psychiatric records were reviewed for both suicide cases and comparison subjects. All available information was used to determine past-month mental disorders in accordance with DSM-IV.</p> <p>Results</p> <p>Antidepressants, antipsychotics, sedatives and hypnotics were associated with increased suicide risk in the crude analysis. After adjustment for affective and anxiety disorders neither antidepressants in general nor SSRIs showed an association with suicide. Antipsychotics had no association with suicide after adjustment for psychotic disorders. Sedative treatment was associated with an almost fourteen-fold increase of suicide risk in the crude analyses and remained an independent risk factor for suicide even after adjustment for any DSM-IV disorder. Having a current prescription for a hypnotic was associated with a four-fold increase in suicide risk in the adjusted model.</p> <p>Conclusion</p> <p>Sedatives and hypnotics were both associated with increased risk for suicide after adjustment for appropriate indications. Given the extremely high prescription rates, a careful evaluation of the suicide risk should always precede prescribing a sedative or hypnotic to an elderly individual.</p

A Minimal Model of Metabolism Based Chemotaxis

Since the pioneering work by Julius Adler in the 1960's, bacterial chemotaxis has been predominantly studied as metabolism-independent. All available simulation models of bacterial chemotaxis endorse this assumption. Recent studies have shown, however, that many metabolism-dependent chemotactic patterns occur in bacteria. We hereby present the simplest artificial protocell model capable of performing metabolism-based chemotaxis. The model serves as a proof of concept to show how even the simplest metabolism can sustain chemotactic patterns of varying sophistication. It also reproduces a set of phenomena that have recently attracted attention on bacterial chemotaxis and provides insights about alternative mechanisms that could instantiate them. We conclude that relaxing the metabolism-independent assumption provides important theoretical advances, forces us to rethink some established pre-conceptions and may help us better understand unexplored and poorly understood aspects of bacterial chemotaxis

SPARKs: Succinct Parallelizable Arguments of Knowledge

We introduce the notion of a Succinct Parallelizable Argument of Knowledge (SPARK). This is an argument of knowledge with the following three efficiency properties for computing and proving a (non-deterministic, polynomial time) parallel RAM computation that can be computed in parallel time T with at most p processors: (1) The prover’s (parallel) running time is T + polylog(T * p). (In other words, the prover’s running time is essentially T for large computation times!) (2) The prover uses at most p * polylog(T * p) processors, and (3) the communication and verifier complexity are both polylog(T * p). The combination of all three is desirable as it gives a way to leverage a moderate increase in parallelism in favor of near-optimal running time. We emphasize that even a factor two overhead in the prover’s parallel running time is not allowed. Our main contribution is a generic construction of SPARKs from any succinct argument of knowledge where the prover’s parallel running time is T * polylog(T * p) when using p processors, assuming collision-resistant hash functions. When suitably instantiating our construction, we achieve a four-round SPARK for any parallel RAM computation assuming only collision resistance. Additionally assuming the existence of a succinct non-interactive argument of knowledge (SNARK), we construct a non-interactive SPARK that also preserves the space complexity of the underlying computation up to polylog(T * p) factors. We also show the following applications of non-interactive SPARKs. First, they immediately imply delegation protocols with near optimal prover (parallel) running time. This, in turn, gives a way to construct verifiable delay functions (VDFs) from any sequential function. When the sequential function is also memory-hard, this yields the first construction of a memory-hard VDF

Continuous Attractors with Morphed/Correlated Maps

Continuous attractor networks are used to model the storage and representation of analog quantities, such as position of a visual stimulus. The storage of multiple continuous attractors in the same network has previously been studied in the context of self-position coding. Several uncorrelated maps of environments are stored in the synaptic connections, and a position in a given environment is represented by a localized pattern of neural activity in the corresponding map, driven by a spatially tuned input. Here we analyze networks storing a pair of correlated maps, or a morph sequence between two uncorrelated maps. We find a novel state in which the network activity is simultaneously localized in both maps. In this state, a fixed cue presented to the network does not determine uniquely the location of the bump, i.e. the response is unreliable, with neurons not always responding when their preferred input is present. When the tuned input varies smoothly in time, the neuronal responses become reliable and selective for the environment: the subset of neurons responsive to a moving input in one map changes almost completely in the other map. This form of remapping is a non-trivial transformation between the tuned input to the network and the resulting tuning curves of the neurons. The new state of the network could be related to the formation of direction selectivity in one-dimensional environments and hippocampal remapping. The applicability of the model is not confined to self-position representations; we show an instance of the network solving a simple delayed discrimination task

Structure-Preserving Smooth Projective Hashing

International audienceSmooth projective hashing has proven to be an extremely useful primitive, in particular when used in conjunction with commitments to provide implicit decommitment. This has lead to applications proven secure in the UC framework, even in presence of an adversary which can do adaptive corruptions, like for example Password Authenticated Key Exchange (PAKE), and 1-out-of-m Oblivious Transfer (OT). However such solutions still lack in efficiency, since they heavily scale on the underlying message length. Structure-preserving cryptography aims at providing elegant and efficient schemes based on classical assumptions and standard group operations on group elements. Recent trend focuses on constructions of structure- preserving signatures, which require message, signature and verification keys to lie in the base group, while the verification equations only consist of pairing-product equations. Classical constructions of Smooth Projective Hash Function suffer from the same limitation as classical signatures: at least one part of the computation (messages for signature, witnesses for SPHF) is a scalar. In this work, we introduce and instantiate the concept of Structure- Preserving Smooth Projective Hash Function, and give as applications more efficient instantiations for one-round PAKE and three-round OT, and information retrieval thanks to Anonymous Credentials, all UC- secure against adaptive adversaries

Defense Against Cannibalism: The SdpI Family of Bacterial Immunity/Signal Transduction Proteins

The SdpI family consists of putative bacterial toxin immunity and signal transduction proteins. One member of the family in Bacillus subtilis, SdpI, provides immunity to cells from cannibalism in times of nutrient limitation. SdpI family members are transmembrane proteins with 3, 4, 5, 6, 7, 8, or 12 putative transmembrane α-helical segments (TMSs). These varied topologies appear to be genuine rather than artifacts due to sequencing or annotation errors. The basic and most frequently occurring element of the SdpI family has 6 TMSs. Homologues of all topological types were aligned to determine the homologous TMSs and loop regions, and the positive-inside rule was used to determine sidedness. The two most conserved motifs were identified between TMSs 1 and 2 and TMSs 4 and 5 of the 6 TMS proteins. These showed significant sequence similarity, leading us to suggest that the primordial precursor of these proteins was a 3 TMS–encoding genetic element that underwent intragenic duplication. Various deletional and fusional events, as well as intragenic duplications and inversions, may have yielded SdpI homologues with topologies of varying numbers and positions of TMSs. We propose a specific evolutionary pathway that could have given rise to these distantly related bacterial immunity proteins. We further show that genes encoding SdpI homologues often appear in operons with genes for homologues of SdpR, SdpI’s autorepressor. Our analyses allow us to propose structure–function relationships that may be applicable to most family members

No-signaling Linear PCPs

In this paper, we give a no-signaling linear probabilistically checkable proof (PCP) system for polynomial-time deterministic computation, i.e., a PCP system for P such that (1) the honest PCP oracle is a linear function and (2) the soundness holds against any (computational) no-signaling cheating prover, who is allowed to answer each query according to a distribution that depends on the entire query set in a certain way. To the best of our knowledge, our construction is the first PCP system that satisfies these two properties simultaneously. As an application of our PCP system, we obtain a 2-message delegating computation scheme by using a known transformation. Compared with the existing 2-message delegating computation schemes that are based on standard cryptographic assumptions, our scheme requires preprocessing but has a simpler structure and makes use of different (possibly cheaper) standard cryptographic primitives, namely additive/multiplicative homomorphic encryption schemes

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Neural network model of the primary visual cortex: From functional architecture to lateral connectivity and back

The role of intrinsic cortical dynamics is a debatable issue. A recent optical imaging study (Kenet et al., 2003) found that activity patterns similar to orientation maps (OMs), emerge in the primary visual cortex (V1) even in the absence of sensory input, suggesting an intrinsic mechanism of OM activation. To better understand these results and shed light on the intrinsic V1 processing, we suggest a neural network model in which OMs are encoded by the intrinsic lateral connections. The proposed connectivity pattern depends on the preferred orientation and, unlike previous models, on the degree of orientation selectivity of the interconnected neurons. We prove that the network has a ring attractor composed of an approximated version of the OMs. Consequently, OMs emerge spontaneously when the network is presented with an unstructured noisy input. Simulations show that the model can be applied to experimental data and generate realistic OMs. We study a variation of the model with spatially restricted connections, and show that it gives rise to states composed of several OMs. We hypothesize that these states can represent local properties of the visual scene