Assessment of Approximate Methods for Anharmonic Free Energies

Quantitative evaluations of the thermodynamic properties of materials – most notably their stability, as measured by the free energy – must take into account the role of thermal and zero-point energy fluctuations. While these effects can easily be estimated within a harmonic approximation, corrections arising from the anharmonic nature of the interatomic potential are often crucial and require computationally costly path integral simulations. Consequently, different approximate frameworks for computing affordable estimates of the anharmonic free energies have been developed over the years. Understanding which of the approximations involved are justified for a given system, and therefore choosing the most suitable method, is complicated by the lack of comparative benchmarks. To facilitate this choice we assess the accuracy and efficiency of some of the most commonly used approximate methods – the independent mode framework, the vibrational self-consistent field and self-consistent phonons – by comparing the anharmonic correction to the Helmholtz free energy against reference path integral calculations. These benchmarks are performed for a diverse set of systems, ranging from simple quasi-harmonic solids to flexible molecular crystals with freely-rotating units. Our results suggest that for simple solids such as allotropes of carbon these methods yield results that are in excellent agreement with the reference calculations, at a considerably lower computational cost. For more complex molecular systems such as polymorphs of ice and paracetamol the methods do not consistently provide a reliable approximation of the anharmonic correction. Despite substantial cancellation of errors when comparing the stability of different phases, we do not observe a systematic improvement over the harmonic approximation even for relative free-energies. Our results suggest that efforts towards obtaining computationally-feasible anharmonic free-energies for flexible molecular solids should therefore be directed towards reducing the expense of path integral methods

Activity-dependent coordination of protein synthesis and protein degradation through a neuronal-specific plasma membrane 20S proteasome complex

In the nervous system, rapidly occurring processes such as neuronal transmission and calcium signaling are affected by short-term inhibition of proteasome function. It is unclear how proteasomes are able to acutely regulate such processes, as this action is inconsistent with their canonical role in proteostasis. We discovered a mammalian nervous-system-specific membrane 20S proteasome complex that directly and rapidly modulates neuronal function by degrading intracellular proteins into extracellular peptides that can stimulate neuronal signaling. This proteasome complex is closely associated with neuronal plasma membranes, exposed to the extracellular space, and catalytically active. Selective inhibition of the membrane proteasome complex by a cell-impermeable proteasome inhibitor blocked the production of extracellular peptides and attenuated neuronal-activity-induced calcium signaling. Moreover, we observed that membrane-proteasome-derived peptides were sufficient to induce neuronal calcium signaling. Analyzing the composition of the neuronal membrane proteasome (NMP), we did not find canonical ubiquitin-proteasome components required for recognizing a ubiquitiylated protein. This raised the fundamental question of how substrates were being targeted to the NMP for degradation into extracellular peptides. Remarkably, we observed newly synthesized polypeptides were rapidly turned over by the NMP in a stimulation-dependent manner. This turnover correlated with enhanced production of NMP-derived peptides in the extracellular space. Using parameters determined in these experiments, we constructed Markov process chain models in silico which predicted that the kinetics of this process necessitate coordination of translation and degradation. In a series of biochemical analyses, this predicted coordination was instantiated by NMP-mediated and ubiquitin-independent degradation of ribosome-associated nascent polypeptides. Using in-depth, global, and unbiased mass spectrometry, we identified the nascent protein substrates of the NMP. Among these substrates, we found that immediate-early gene products c-Fos and Npas4 are targeted by the NMP during ongoing activity-dependent protein synthesis, prior to activity-induced transcriptional responses. Our findings challenge the prevailing notion that proteasomes function primarily to maintain proteostasis, and highlight a form of neuronal communication that takes place through the NMP. Together, these findings generally define an activity-dependent protein quality control program unique to the nervous system through the neuronal membrane proteasome

Synthesis of possible room temperature superconductor LK-99:Pb9_9Cu(PO4_4)6_6O

The quest for room-temperature superconductors has been teasing scientists and physicists, since its inception in 1911 itself. Several assertions have already been made about room temperature superconductivity but were never verified or reproduced across the labs. The cuprates were the earliest high transition temperature superconductors, and it seems that copper has done the magic once again. Last week, a Korean group synthesized a Lead Apatite-based compound LK-99, showing a T$_c$ of above 400$^\circ$K. The signatures of superconductivity in the compound are very promising, in terms of resistivity (R = 0) and diamagnetism at T$_c$. Although, the heat capacity (C$_p$) did not show the obvious transition at T$_c$. Inspired by the interesting claims of above room temperature superconductivity in LK-99, in this article, we report the synthesis of polycrystalline samples of LK-99, by following the same heat treatment as reported in [1,2] by the two-step precursor method. The phase is confirmed through X-ray diffraction (XRD) measurements, performed after each heat treatment. The room temperature diamagnetism is not evidenced by the levitation of a permanent magnet over the sample or vice versa. Further measurements for the confirmation of bulk superconductivity on variously synthesized samples are underway. Our results on the present LK-99 sample, being synthesized at 925$^\circ$C, as of now do not approve the appearance of bulk superconductivity at room temperature. Further studies with different heat treatments are though, yet underway.Comment: Short Commun.: 8pages Text + Figs: Comments/suggestion Welcom

Antibiotic resistance pattern of Pseudomonas aeruginosa isolated from pus samples at tertiary care cancer hospital

Background: Pseudomonas aeruginosa is one of the most frequent opportunistic microorganisms causing infections in cancer patients. The aim of the study was to determine the antibiotic susceptibility of Pseudomonas aeruginosa and multidrug-resistant (MDR) isolates in cancer patients. Methods: A retrospective study was conducted from January 2022 to December 2022 at Government Cancer Hospital, Aurangabad. A total of 143 pus samples were collected from both IPD and OPD patients. Pus samples were collected as per standard procedure and were inoculated on blood and MacConkey agar. The isolates were identified by standard protocols using biochemical tests. The antibiotic susceptibility pattern of each isolate was checked as per Clinical and Laboratory Standards Institute (CLSI) guidelines 2022 using Kirby-Bauer's disc diffusion method and VITEK 2 Automation. Data analysis was done by statical method with statistical software SPSS version 22. Results: Out of 143 clinical samples 33 samples (23%) were positive for Pseudomonas aeruginosa growth. mean age of patients was 50 years old out of 33 isolates 12 (36%) isolates were multidrug-resistant, 11 (33%) isolates were extensively drug-resistant and 1 (3%) were pan-drug-resistant. The majority of isolates were responsive to polymyxin B 32 (96%) and colistin 32 (96%); However, the resistance to gentamycin, ceftazidime, and amikacin was higher, at 66%, 60%, and 57%, respectively.   Conclusions: This hospital-based retrospective study will help to implement better infection control strategies and improve the knowledge of antibiotic resistance patterns among clinicians. Thus, there is a need for an antibiotic stewardship program to monitor the resistant pattern in a tertiary care   cancer hospital

Window pane oyster collection - an alternative means of income for fisherwomen of Kudgaon, Raigad, Maharashtra

Along with fisheries related activities, fisherwomen of Kudgaon, 6 km south of Dighi in Raigad district of Maharashtra, recently started collection of Mollusc shells (window pane oyster; Placuna placenta) from the intertidal zone

Labelled Classifier with Weighted Drift Trigger Model using Machine Learning for Streaming Data Analysis

The term “data-drift” refers to a difference between the data used to test and validate a model and the data used to deploy it in production. It is possible for data to drift for a variety of reasons. The track of time is an important consideration. Data mining procedures such as classification, clustering, and data stream mining are critical to information extraction and knowledge discovery because of the possibility for significant data type and dimensionality changes over time. The amount of research on mining and analyzing real-time streaming data has risen dramatically in the recent decade. As the name suggests, it’s a stream of data that originates from a number of sources. Analyzing information assets has taken on increased significance in the quest for real-time analytics fulfilment. Traditional mining methods are no longer effective since data is acting in a different way. Aside from storage and temporal constraints, data streams provide additional challenges because just a single pass of the data is required. The dynamic nature of data streams makes it difficult to run any mining method, such as classification, clustering, or indexing, in a single iteration of data. This research identifies concept drift in streaming data classification. For data classification techniques, a Labelled Classifier with Weighted Drift Trigger Model (LCWDTM) is proposed that provides categorization and the capacity to tackle concept drift difficulties. The proposed classifier efficiency is contrasted with the existing classifiers and the results represent that the proposed model in data drift detection is accurate and efficient

Type-II Superconductivity below 4K in Sn0.4Sb0.6

In this article, we report the occurrence of superconductivity in Sn0.4Sb0.6 single crystal at below 4K. Rietveld refined Powder XRD data confirms the phase purity of as grown crystal, crystallizing in rhombohedral R-3m space group with an elongated (2xc) unit cell in c-direction. Scanning Electron Microscope (SEM) image and EDAX measurement confirm the laminar growth and near to desired stoichiometry ratio. Raman Spectroscopy data shows the vibrational modes of Sn-Sb and Sb-Sb modes at 110 and 135cm-1. ZFC (Zero-Field-Cooled) magnetization measurements done at 10Oe showed sharp superconducting transitions at 4K along with a minor step at 3.5K. On the other hand, Paramagnetic Meissner Effect (PME) is observed in FC measurements. Magnetization vs applied field (M-H) plots at 2, 2.2, 2.5, 2.7, 3, 3.2, 3.5, and 3.7K shows typical Type-II nature of observed superconductivity with lower and upper critical fields (Hc1 and Hc2) at 69.42Oe and 630Oe respectively at 2K. Type-II superconductivity is also confirmed by calculated Ginzburg-Landau Kappa parameter value of 3.55. Characteristics length viz. coherence length and penetration depth are also calculated. Weak granular coupling is observed from R-T plot, in which resistance is not dropping to zero down to 2K.Comment: 21 Pages Text + Fig