Full Cluster Research Articles

Cosmological constraints from the Planck cluster catalogue with new multi-wavelength mass calibration from Chandra and CFHT

We provide a new scaling relation between $Y_ SZ $, the integrated Sunyaev-Zeldovich signal and $M_ Y_ X $, the cluster mass derived from X-ray observations, using a sample of clusters from the Planck Early Sunyaev-Zeldovich (ESZ) catalogue observed in X-rays by Chandra and compare it to the results of the Planck collaboration obtained from XMM-Newton observations of a subsample of the ESZ. We calibrated a mass bias on a subset of the Planck cosmological cluster sample using published weak-lensing data from the Canadian Cluster Cosmology Project (CCCP) and Multi Epoch Nearby Cluster Survey (MENeaCS), for the new scaling relation as well as that from the Planck collaboration. We propose a novel method to account for selection effects and find a mass bias of $(1-b)=0.89 for the Chandra -calibrated scaling relation, and $(1-b)=0.76 for the XMM-Newton -calibrated scaling relation. We applied the scaling relations we derived to the full Planck cosmological cluster sample and obtain new constraints on the cosmological parameters. We find identical constraints regardless of the X-ray sample used, with $ and $S_8 We also provide constraints with a redshift evolution of the scaling relation fitted from the data instead of fixing it to the self-similar value. We find a redshift evolution significantly deviating from the self-similar value, leading to a higher value of $S_8=0.81 We compare our results to those from various cosmological probes, and find that our $S_8$ constraints are competitive with the tightest constraints from the literature. When assuming a self-similar redshift evolution, our constraints are in agreement with most late-time probes and in tension with constraints from the cosmic microwave background (CMB) primary anisotropies. When relaxing the assumption of redshift evolution and fitting it to the data, we find no significant tension with results from either late-time probes or the CMB.

Microcystins with Modified Adda5-Residues from a Heterologous Microcystin Expression System.

Microcystins are hepatotoxic cyclic heptapeptides produced by some cyanobacterial species and usually contain the unusual β-amino acid 3S-amino-9S-methoxy-2S,6,8S-trimethyl-10-phenyl-4E,6E-decadienoic acid (Adda) at position-5. The full microcystin gene cluster from Microcystis aeruginosa PCC 7806 has been expressed in Escherichia coli. In an earlier study, the engineered strain was shown to produce MC-LR and [d-Asp3]MC-LR, the main microcystins reported in cultures of M. aeruginosa PCC 7806. However, analysis of the engineered strain of E. coli using semitargeted liquid chromatography with high-resolution tandem mass spectrometry (LC-HRMS/MS) and thiol derivatization revealed the presence of 15 additional microcystin analogues, including four linear peptide variants and, in total, 12 variants with modifications to the Adda moiety. Four of the Adda-variants lacked the phenyl group at the Adda-terminus, a modification that has not previously been reported in cyanobacteria. Their HRMS/MS spectra contained the product-ion from Adda at m/z 135.1168, but the commonly observed product-ion at m/z 135.0804 from Adda-containing microcystins was almost completely absent. In contrast, three of the variants were missing a methyl group between C-2 and C-8 of the Adda moiety, and their LC-HRMS/MS spectra displayed the product-ion from Adda at m/z 135.0804. However, instead of the product-ion at m/z 135.1168, these three variants gave product-ions at m/z 121.1011. These observations, together with spectra from microcystin standards using in-source fragmentation, showed that the product-ion at m/z 135.1168 found in the HRMS/MS spectra of most microcystins originated from the C-2 to C-8 region of the Adda moiety. Identification of the fragmentation pathways for the Adda side chain will facilitate the detection of microcystins containing modifications in their Adda moieties that could otherwise easily be overlooked with standard LC-MS screening methods. Microcystin variants containing Abu at position-1 were also prominent components of the microcystin profile of the engineered bacterium. Microcystin variants with Abu1 or without the phenyl group on the Adda side chain were not detected in the original host cyanobacterium. This suggests not only that the microcystin synthase complex may be affected by substrate availability within its host organism but also that it possesses an unexpected degree of biosynthetic flexibility.

Solvate Suite: A Command-Line Interface for Molecular Simulations and Multiscale Microsolvation Modeling.

In this work, we introduce the Solvate Suite, a comprehensive and modular command-line interface designed for molecular simulation and microsolvation modeling. The suite interfaces with widely used scientific software, streamlining computational experiments for liquid systems through the automated creation of simulation boxes and topology with adjustable simulation parameters. Furthermore, it has features for graphical and statistical analysis of simulated properties and extraction of trajectory configurations with various filters. Additionally, it introduces innovative strategies for microsolvation modeling with a multiscale approach, employing equilibrated dynamics to identify favorable solute-solvent interactions and enabling full cluster optimization for free-energy calculations without imaginary frequency contamination.

Simulation of Full HIV Cluster Networks in a Nationally Representative Model Indicates Intervention Opportunities.

Clusters of rapid HIV transmission in the United States are increasingly recognized through analysis of HIV molecular sequence data reported to the National HIV Surveillance System. Understanding the full extent of cluster networks is important to assess intervention opportunities. However, full cluster networks include undiagnosed and other infections that cannot be systematically observed in real life. We replicated HIV molecular cluster networks during 2015-2017 in the United States using a stochastic dynamic network simulation model of sexual transmission of HIV. Clusters were defined at the 0.5% genetic distance threshold. Ongoing priority clusters had growth of ≥3 diagnoses/year in multiple years; new priority clusters first had ≥3 diagnoses/year in 2017. We assessed the full extent, composition, and transmission rates of new and ongoing priority clusters. Full clusters were 3-9 times larger than detected clusters, with median detected cluster sizes in new and ongoing priority clusters of 4 (range 3-9) and 11 (range 3-33), respectively, corresponding to full cluster sizes with a median of 14 (3-74) and 94 (7-318), respectively. A median of 36.3% (range 11.1%-72.6%) of infections in the full new priority clusters were undiagnosed. HIV transmission rates in these clusters were >4 times the overall rate observed in the entire simulation. Priority clusters reflect networks with rapid HIV transmission. The substantially larger full extent of these clusters, high proportion of undiagnosed infections, and high transmission rates indicate opportunities for public health intervention and impact.

Improved Constraints on Mergers with SZ, Hydrodynamical simulations, Optical, and X-ray (ICM-SHOX)

Galaxy cluster mergers are representative of a wide range of physics, making them an excellent probe of the properties of dark matter and the ionized plasma of the intracluster medium. To date, most studies have focused on mergers occurring in the plane of the sky, where morphological features can be readily identified. To allow study of mergers with arbitrary orientation, we have assembled multi-probe data for the eight-cluster ICM-SHOX sample sensitive to both morphology and line of sight velocity. The first ICM-SHOX paper [1] provided an overview of our methodology applied to one member of the sample, MACS J0018.5+1626, in order to constrain its merger geometry. That work resulted in an exciting new discovery of a velocity space decoupling of its gas and dark matter distributions. In this work, we describe the availability and quality of multi-probe data for the full ICM-SHOX galaxy cluster sample. These datasets will form the observational basis of an upcoming full ICM-SHOX galaxy cluster sample analysis.

On the synergetic effects of cyclic cooperativity in water clusters.

The present study delves into the question of how the strength of a hydrogen bond (HB) common to two or more cyclic HB networks is influenced by the cooperativity contributions (CCs) of these cycles. We employ the molecular tailoring approach-based method to calculate the cyclic CCs in water clusters, Wn (n = 6-20). The energy of an HB in a Wn cluster is estimated by adding the total cyclic CC to its counterpart in the respective dimer. The resulting HB energies closely match their full cluster counterparts, typically within 1.0 kcal mol-1, with substantial CCs of these cyclic networks.

The valuation pairing on an upper cluster algebra

Abstract It is known that many (upper) cluster algebras are not unique factorization domains. We exhibit the local factorization properties with respect to any given seed t: any non-zero element in a full rank upper cluster algebra can be uniquely written as the product of a cluster monomial in t and another element not divisible by the cluster variables in t. Our approach is based on introducing the valuation pairing on an upper cluster algebra: it counts the maximal multiplicity of a cluster variable among the factorizations of any given element. We apply the valuation pairing to obtain many results concerning factoriality, d-vectors, F-polynomials and the combinatorics of cluster Poisson variables. In particular, we obtain that full rank and primitive upper cluster algebras are factorial; an explanation of d-vectors using valuation pairing; a cluster monomial in non-initial cluster variables is determined by its F-polynomial; the F-polynomials of non-initial cluster variables are irreducible; and the cluster Poisson variables parametrize the exchange pairs of the corresponding upper cluster algebra.

A SOC Correction Method Based on Unsynchronized Full Charge and Discharge Control Strategy in Multi-Branch Battery System

LiFePO4 batteries exhibit voltage plateau and voltage hysteresis characteristics during charging and discharging processes; however, the estimation of state-of-charge relies on voltage detection. Thus, the estimation accuracy of SOC is low in a traditional method. In this paper, a full charge and discharge SOC correction method is proposed; i.e., the SOC is corrected to 100% when the battery is fully charged and to 0% when fully discharged, and the actual usable capacity is corrected using the fully discharged capacity after being fully charged. Thereby, the cumulative error of the ampere-hour integration method is dynamically corrected. In engineering applications, however, the battery systems do not always undergo full charge and discharge cycling due to the operating conditions. By making full use of the distributed control characteristics of the multi-branch topology battery system, the present work proposes an optimized system control strategy to realize the unsynchronized full charge and discharge cluster by cluster, which extends the application of the full charge and discharge SOC correction method. The experimental results verify the accuracy of the proposed SOC correction method and the feasibility of the control strategy. A more reliable and efficient battery management scheme is provided for LFP battery system, which has high practical value in engineering.

IgG1-3 MuSK Antibodies Inhibit AChR Cluster Formation, Restored by SHP2 Inhibitor, Despite Normal MuSK, DOK7, or AChR Subunit Phosphorylation.

Up to 50% of patients with myasthenia gravis (MG) without acetylcholine receptor antibodies (AChR-Abs) have antibodies to muscle-specific kinase (MuSK). Most MuSK antibodies (MuSK-Abs) are IgG4 and inhibit agrin-induced MuSK phosphorylation, leading to impaired clustering of AChRs at the developing or mature neuromuscular junction. However, IgG1-3 MuSK-Abs also exist in MuSK-MG patients, and their potential mechanisms have not been explored fully. C2C12 myotubes were exposed to MuSK-MG plasma IgG1-3 or IgG4, with or without purified agrin. MuSK, Downstream of Kinase 7 (DOK7), and βAChR were immunoprecipitated and their phosphorylation levels identified by immunoblotting. Agrin and agrin-independent AChR clusters were measured by immunofluorescence and AChR numbers by binding of 125I-α-bungarotoxin. Transcriptomic analysis was performed on treated myotubes. IgG1-3 MuSK-Abs impaired AChR clustering without inhibiting agrin-induced MuSK phosphorylation. Moreover, the well-established pathway initiated by MuSK through DOK7, resulting in βAChR phosphorylation, was not impaired by MuSK-IgG1-3 and was agrin-independent. Nevertheless, the AChR clusters did not form, and both the number of AChR microclusters that precede full cluster formation and the myotube surface AChRs were reduced. Transcriptomic analysis did not throw light on the pathways involved. However, the SHP2 inhibitor, NSC-87877, increased the number of microclusters and led to fully formed AChR clusters. MuSK-IgG1-3 is pathogenic but seems to act through a noncanonical pathway. Further studies should throw light on the mechanisms involved at the neuromuscular junction.

Mechanical properties and thermal stability of ZrCuAlx thin film metallic glasses: Experiments and first-principle calculations

In this work, we provide a holistic picture about the relationship between atomic structure, mechanical properties, and thermal stability of ZrCuAlx thin film metallic glasses (TFMGs) varying the Al content from 0 to 12 at.%, carrying out a broad characterization involving experiments and ab initio molecular dynamic simulations (AIMD). We show that the addition of Al resulted in a change of average interatomic distances by ∼10 pm with the formation of shorter bonds (Al-Zr and Al-Cu), influencing the mechanical response (shear/elastic moduli and hardness) which increases by ∼15% for 12 at.% Al. Moreover, tensile tests on polymer substrate revealed a maximum value for the crack initiation strain of 2.1% for ZrCuAl9, while the strain-to-failure rapidly decreases at higher Al contents. The observed reduction in damage tolerance is correlated to a transition in atomic configuration. Specifically, a maximum in density of full and defective icosahedral cluster population is observed at 9 at.% Al, inducing a more shear-resistant behavior to the material. Thermal stability is investigated by high-energy and conventional x-ray diffraction and electrical resistivity measurements as a function of the temperature. Glass transition (Tg) and crystallization (Tx) temperature increase by Al addition reaching 450 and 500 °C, respectively for ZrCuAl12. The increase in thermal stability is related to the reduction in atomic mobility due to the formation of shorter chemical bonds, inhibiting atomic reconfiguration during crystallization. In conclusion, we provide guidelines to the design of compositional-tailored ZrCuAlx TFMGs with tuned mechanical properties and thermal stability with potential impact on industrial applications.

An extended full field self-consistent cluster analysis framework for woven composite

In this work, the self-consistent clustering analysis (SCA) framework is extended to include homogenization and full field analysis of 3D anisotropic woven composite Representative Unit Cell (RUC). The developed extended framework has two new features, namely, (i), to reconstruct the local field variables, a strain refinement stage is presented by solving full field Lippmann–Schwinger equations within 3D anisotropic woven composite RUC following the online predictive stage in SCA, and (ii), discrete Green’s operator based on finite difference is adopted to improve the accuracy of refined point-wise physical field variables. To demonstrate the accuracy and efficiency of the proposed method, benchmark problems are analyzed, and results are compared to directly numerical simulation (DNS). For the reproducibility of presented results, the developed code can be freely downloaded from https://github.com/Tong-RuiLiu/Extended-SCA-and-FFT-based-strain-refinement-method-.

The relationship between cluster environment and molecular gas content of star-forming galaxies in the eagle simulation

ABSTRACT We employ the eagle hydrodynamical simulation to uncover the relationship between cluster environment and H2 content of star-forming galaxies at redshifts spanning 0 ≤ z ≤ 1. To do so, we divide the star-forming sample into those that are bound to clusters and those that are not. We find that, at any given redshift, the galaxies in clusters generally have less H2 than their non-cluster counterparts with the same stellar mass (corresponding to an offset of ≲0.5 dex), but this offset varies with stellar mass and is virtually absent at M⋆ ≲ 109.3 M⊙. The H2 deficit in star-forming cluster galaxies can be traced back to a decline in their H2 content that commenced after first infall into a cluster, which occurred later than a typical cluster galaxy. Evolution of the full cluster population after infall is generally consistent with ‘slow-then-rapid’ quenching, but galaxies with M⋆ ≲ 109.5 M⊙ exhibit rapid quenching. Unlike most cluster galaxies, star-forming ones were not pre-processed in groups prior to being accreted by clusters. For both of these cluster samples, the star formation efficiency remained oblivious to the infall. We track the particles associated with star-forming cluster galaxies and attribute the drop in H2 mass after infall to poor replenishment, depletion due to star formation, and stripping of H2 in cluster environments. These results provide predictions for future surveys, along with support and theoretical insights for existing molecular gas observations that suggest there is less H2 in cluster galaxies.

Exploring the Mass and Redshift Dependencies of the Cluster Pressure Profile with Stacks on Thermal Sunyaev–Zel’dovich Maps

We provide novel constraints on the parameters defining the universal pressure profile (UPP) within clusters of galaxies, and explore their dependencies on cluster mass and redshift, from measurements of Sunyaev–Zel’dovich (SZ) Compton y-profiles. We employ both Planck 2015 MILCA and Atacama Cosmology Telescope (ACT) Data Release 4 y-maps over a common ∼2100 deg2 footprint. We combine existing cluster catalogs, based on Kilo Degree Survey, Sloan Digital Sky Survey, and Dark Energy Spectroscopic Instrument Legacy Imaging Surveys observations, for a total of 23,820 clusters, spanning the mass range 1014.0 M ⊙ < M 500 < 1015.1 M ⊙ and the redshift range 0.02 < z < 0.98. We split the clusters into three independent bins in mass and redshift; for each combination, we detect the stacked SZ cluster signal and extract the mean y angular profile. The latter is predicted theoretically by adopting a halo model framework, and a Markov Chain Monte Carlo approach is employed to estimate the UPP parameters, the hydrostatic mass bias b h, and possible cluster miscentering effects. We constrain [P 0, c 500, α, β] to [5.9, 2.0, 1.8, 4.9] with Planck and to [3.8, 1.3, 1.0, 4.4] with ACT, using the full cluster sample, in agreement with previous findings. We do not find any compelling evidence for residual mass or redshift dependencies, thus expanding the validity of the cluster pressure profile over much larger M 500 and z ranges; this is the first time that the model has been tested on such a large (complete and representative) cluster sample. Finally, we obtain loose constraints on the hydrostatic mass bias in the range 0.2–0.3, again in broad agreement with previous works.

Microbial Motility at the Bottom of North America: Digital Holographic Microscopy and Genomic Motility Signatures in Badwater Spring, Death Valley National Park.

Motility is widely distributed across the tree of life and can be recognized by microscopy regardless of phylogenetic affiliation, biochemical composition, or mechanism. Microscopy has thus been proposed as a potential tool for detection of biosignatures for extraterrestrial life; however, traditional light microscopy is poorly suited for this purpose, as it requires sample preparation, involves fragile moving parts, and has a limited volume of view. In this study, we deployed a field-portable digital holographic microscope (DHM) to explore microbial motility in Badwater Spring, a saline spring in Death Valley National Park, and complemented DHM imaging with 16S rRNA gene amplicon sequencing and shotgun metagenomics. The DHM identified diverse morphologies and distinguished run-reverse-flick and run-reverse types of flagellar motility. PICRUSt2- and literature-based predictions based on 16S rRNA gene amplicons were used to predict motility genotypes/phenotypes for 36.0-60.1% of identified taxa, with the predicted motile taxa being dominated by members of Burkholderiaceae and Spirochaetota. A shotgun metagenome confirmed the abundance of genes encoding flagellar motility, and a Ralstonia metagenome-assembled genome encoded a full flagellar gene cluster. This study demonstrates the potential of DHM for planetary life detection, presents the first microbial census of Badwater Spring and brine pool, and confirms the abundance of mobile microbial taxa in an extreme environment.

Toward 5G Edge Computing for Enabling Autonomous Aerial Vehicles

Offloading processes responsible for a robot’s control operation to external computational resources has been in the spotlight for many years. The vision of having access to a full cloud cluster for any autonomous robot has fueled many scientific fields. Such implementations rely strongly on a robust communication link between the robot and the cloud and have been tested over numerous network architectures. However, various limitations have been highlighted upon the realization of such platforms. For small-scale local deployments, technologies such as Wi-Fi, Zigbee, and blacktooth are inexpensive and easy to use but suffer from low transmit power and outdoor coverage limitations. In this study, the offloading time-critical control operations for an unmanned aerial vehicle (UAV) using cellular network technologies were evaluated and demonstrated experimentally, focusing on the 5G technology. The control process was hosted on an edge server that served as a ground control station (GCS). The server performs all the computations required for the autonomous operation of the UAV and sends the action commands back to the UAV over the 5G interface. This research focuses on analyzing the low-latency needs of a closed-loop control system that is put to the test on a real 5G network. Furthermore, practical limitations, integration challenges, the intended cellular architecture, and the corresponding Key Performance Indicators (KPIs) that correlate to the real-life behavior of the UAV are rigorously studied.

The MeerKAT Galaxy Clusters Legacy Survey: star formation in massive clusters at 0.15 &amp;lt; z &amp;lt; 0.35

Abstract We investigate dust-unbiased star formation rates (SFRs) as a function of the environment in 20 massive clusters ($M_{200}\gt 4\times 10^{14}\, {\rm M}_{\odot }$) between 0.15 &amp;lt; $z$ &amp;lt; 0.35 using radio luminosities (L1.4GHz) from the recently released MeerKAT Galaxy Cluster Legacy Survey catalogue. We use optical data from the Dark Energy Camera Legacy Survey to estimate photo-$z$s and assign cluster membership. We observe a steady decline in the fraction (fSF) of star-forming galaxies from 2R200 to the cluster centres in our full cluster sample, but notice a significant difference in fSF gradients between clusters hosting large-scale extended radio emission in the form of haloes and relics (associated with ongoing merger activity) and non-radio-halo/relic hosting clusters. For star-forming galaxies within R200, the fSF in clusters hosting radio haloes and relics (0.148 ± 0.016) is $\approx 23{{\ \rm per\ cent}}$ higher than in non-radio-halo/relic hosting clusters (0.120 ± 0.011). We observe a 3σ difference between the total SFR normalized by cluster mass for non-radio-halo/relic hosting clusters (21.5 ± 1.9 M⊙yr−1/1014M⊙) and for clusters with radio haloes and relics (26.1 ± 1.4 M⊙yr−1/1014M⊙). There is a ≈4× decline in the mass normalized total SFR of clusters for galaxies with SFR above the luminous infrared galaxies (LIRGs) SFR limit at our redshift slice, corresponding to 2 Gyr in lookback time. This is consistent with the rapid decline in SF activity with decreasing redshift amongst cluster LIRGs seen by previous studies using infrared-derived SFR.

Machine learning methods to estimate observational properties of galaxy clusters in large volume cosmological N-body simulations

ABSTRACT In this paper, we study the applicability of a set of supervised machine learning (ML) models specifically trained to infer observed related properties of the baryonic component (stars and gas) from a set of features of dark matter (DM)-only cluster-size haloes. The training set is built from the three hundred project that consists of a series of zoomed hydrodynamical simulations of cluster-size regions extracted from the 1 Gpc volume MultiDark DM-only simulation (MDPL2). We use as target variables a set of baryonic properties for the intracluster gas and stars derived from the hydrodynamical simulations and correlate them with the properties of the DM haloes from the MDPL2 N-body simulation. The different ML models are trained from this data base and subsequently used to infer the same baryonic properties for the whole range of cluster-size haloes identified in the MDPL2. We also test the robustness of the predictions of the models against mass resolution of the DM haloes and conclude that their inferred baryonic properties are rather insensitive to their DM properties that are resolved with almost an order of magnitude smaller number of particles. We conclude that the ML models presented in this paper can be used as an accurate and computationally efficient tool for populating cluster-size haloes with observational related baryonic properties in large volume N-body simulations making them more valuable for comparison with full sky galaxy cluster surveys at different wavelengths. We make the best ML trained model publicly available.

Ca II triplet spectroscopy of Small Magellanic Cloud red giants

Aims. In this paper we analyze the chemical evolution of the main body of the SMC, adding six additional clusters to previously published samples, based on homogeneously determined and accurate metallicities. Methods. We derived radial velocities and Ca II Triplet (CaT) metallicity of more than 150 red giants stars in six SMC star clusters and their surrounding fields, with the instrument GMOS on GEMINI-S. The mean cluster radial velocity and metallicity were obtained with mean errors of 2.2 km s−1 and 0.03 dex, while the mean field metallicities have a mean error of 0.13 dex. We add this information to that available for another 51 clusters and 30 fields with CaT metallicities on the same scale. Using this expanded sample we analyze the chemical properties of the SMC main body, defined as the inner 3.4° in semimajor axis. Results. We found a high probability that the metallicity distribution of the main body clusters is bimodal with a metal-rich and a metal-poor cluster group, having mean metallicities with a dispersion of μ = −0.80, σ = 0.06 and μ = −1.15, σ = 0.10 dex, respectively. On the other hand, main body field stars show a unimodal metallicity distribution peaking at [Fe/H] ∼ −1 and dispersion of 0.3. Neither metal-rich nor metal-poor clusters present a metallicity gradient. However, the full main body cluster sample and field stars have a negative metallicity gradient consistent with each other, but the one corresponding to clusters has a large error due to the large metallicity dispersion present in the clusters studied in that region. Metal-rich clusters present a clear age–metallicity relation, while metal-poor clusters present no chemical enrichment throughout the life of the galaxy. Conclusions. We present observational evidence that the chemical enrichment is complex in the SMC main body. Two cluster groups with potential different origins could be coexisting in the main body. More data with precise and homogeneous metallicities and distances are needed and dynamical simulations are required to understand the possible different origins for the two cluster groups.

Impact of personality functioning and pathological traits on mental wellbeing of older patients with personality disorders

BackgroundAlthough personality disorders are common and consequential, they are largely ignored in geriatric mental healthcare. We examined the relative contributions of different aspects of personality disorders and comorbid mental disorders to the impairment of mental wellbeing in older adults.MethodsBaseline data were used of 138 patients who participated in a randomized controlled trial on schema therapy for geriatric mental health outpatients with a full or subthreshold cluster B or C personality disorder. Personality was assessed according to both the categorical and dimensional model of DSM-5. Aspects of mental wellbeing assessed were; psychological distress, positive mental health, subjective health, and life satisfaction. The current study uses baseline data of the RCT to examine the associations between different aspects of personality pathology and mental wellbeing by multivariate regression analysis, controlling for age, sex, level of education, and number of chronic somatic illnesses.ResultsThe vast majority of patients (79.0%) had one or more mental disorders in addition to personality disorder. Personality pathology was responsible for the core of the mental health burden experienced by patients, and negated the influence of co-occurring mental disorders when entered subsequently in multivariate analysis. Personality dimensions proved to be highly predictive of mental wellbeing, and this contrasted with absence of influence of personality disorder diagnosis. Although the personality functioning dimensions – and in particular Identity integration (large effect size with partial eta-squared = 0.36) – were the primary predictors of mental wellbeing, personality trait dimensions added significant predictive value to that (Disinhibition 0.25 and Negative affect 0.24).ConclusionsPersonality disorders seriously affect the mental wellbeing of patients, and this overshadows the impact of comorbid mental disorders. In particular personality functioning and pathological traits of the Alternative Model of Personality Disorders (AMPD) of DSM-5 contribute to this impact on mental wellbeing. Alertness for and treatment of personality disorders in geriatric mental healthcare seems warranted.

ClusterSheep: A Graphics Processing Unit-Accelerated Software Tool for Large-Scale Clustering of Tandem Mass Spectra from Shotgun Proteomics.

Modern shotgun proteomics experiments generate gigabytes of spectra every hour, only a fraction of which were utilized to form biological conclusions. Instead of being stored as flat files in public data repositories, this large amount of data can be better organized to facilitate data reuse. Clustering these spectra by similarity can be helpful in building high-quality spectral libraries, correcting identification errors, and highlighting frequently observed but unidentified spectra. However, large-scale clustering is time-consuming. Here, we present ClusterSheep, a method utilizing Graphics Processing Units (GPUs) to accelerate the process. Unlike previously proposed algorithms for this purpose, our method performs true pairwise comparison of all spectra within a precursor mass-to-charge ratio tolerance, thereby preserving the full cluster structures. ClusterSheep was benchmarked against previously reported clustering tools, MS-Cluster, MaRaCluster, and msCRUSH. The software tool also functions as an interactive visualization tool with a persistent state, enabling the user to explore the resulting clusters visually and retrieve the clustering results as desired.