Relationship Log Research Articles

CrptAC: Find the Attack Chain with Multiple Encrypted System Logs

Clandestine assailants infiltrate intelligent systems in smart cities and homes for different purposes. These attacks leave clues behind in multiple logs. Systems usually upload their local syslogs as encrypted files to the cloud for longterm storage and resource saving. Therefore, the identification of pre-attack steps through log investigation is crucial for proactive system protection. Current methodologies involve system diagnosis using logs, often relying on datasets for feature training. Furthermore, the prevalence of mass encrypted logs in the cloud introduces a new layer of complexity to this domain. To tackle these challenges, we introduce CrptAC, a system for Multiple Encrypted Log Correlated Analysis, aimed at reconstructing attack chains to prevent further attacks securely. CrptAC initiates by searching and downloading relevant log files from encrypted logs stored in an untrusted cloud environment. Utilizing the obtained logs, it addresses the challenge of discovering event relationships to establish the attack provenance. The system employs various logs to construct event sequences leading up to an attack. Subsequently, we utilize Weighted Graphs and the Longest Common Subsequences algorithm to identify regular steps preceding an attack without the need for third-party training datasets. This approach enables the proactive identification of pre-attack steps by analyzing related log sequences. We apply our methodology to predict attacks in cloud computing and router breach provenance environments. Finally, we validate the proposed method, demonstrating its effectiveness in constructing attack steps and conclusively identifying corresponding syslogs.

Abstract 7423: BATCH-FLEX: Feature-level equalization of x-batch in heterogeneous cancer data

Abstract Purpose: Develop a shiny application to help integrate cancer datasets and guide researchers in selecting an appropriate method of correction for their technical artifacts. Description: Integrative analysis of heterogeneous expression data remains challenging due to variations in platform, RNA quality, sample processing, and other unknown technical effects. As the field performs omics profiling of samples from cancer patients and murine models, there is the need for harmonizing, identifying, and correcting these technical effects to ensure robust analysis on the treatment and conditional effects of the underlying genetics or biological events. However, selecting and implementing different approaches for removing unwanted batch effects can be a time-consuming and tedious process, especially for more biologically focused investigators. In this project, we present Shiny BATCH-FLEX, a Shiny app to rapidly visualize batch correction by established batch correction methods such as ComBat, Mean Centering, ComBatSeq, and Limma RemoveBatchEffect. With BATCH-FLEX, users can visualize the contribution of variance of a factor before and after correction using principal component analysis, relative log expression plots, heatmaps, and explanatory variables. Users can also save all plots and matrices as a single ZIP file for further downstream analysis. Results: As a proof of concept, we assessed BATCH-FLEX using simulated data generated from a linear model framework introduced by Gagnon-Bartsch and Speed, which assumes that gene expression measurements can be distilled to a combination of the biological signal, systemic nose, and random noise. BATCH-FLEX was able to successfully identify and remove the introduced effect using each of the batch correction methods listed above. Next, we evaluated BATCH-FLEX using a comprehensive collection of bladder cancer data consisting of microarray data from 13 studies spanning 1452 samples. Following the cleaning of study-dependent noise, BATCH-FLEX was successful in revealing the heterogeneity among bladder cancer based on known sample type annotations. Conclusion: We have developed BATCH-FLEX, a tool for oncologic researchers to rapidly assess, select, and implement commonly used batch correction methods. This tool is available at https://github.com/shawlab-moffitt/BATCH-FLEX. Our integrative web portal of a Bladder Cancer Resource for Translational Science (BEACON) will also be shared at the meeting. Citation Format: Joshua Davis, Alyssa Obermayer, Thac Duong, Rebecca Hesterberg, Xuefeng Wang, Mingxiang Teng, G. Daniel Grass, Timothy Shaw. BATCH-FLEX: Feature-level equalization of x-batch in heterogeneous cancer data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7423.

Antimatter Enigma Solved: Astronomical Data Allows Identification of 77 Supermassive Antimatter Black Holes and 23 Antimatter Galaxies.

Initial results from the Alpha-CERN antihydrogen experiment indicate no discernible difference in the gravitational behavior between matter and antimatter, challenging CP violation models. Given that antimatter exhibits the same gravitational behavior as matter, distinguishing between a supermassive black hole (SMBH) composed of matter and an antimatter supermassive black hole (ASMBH) becomes challenging, as their gravitational effects are indistinguishable. This raises the question: Could the SMBH in the Milky Way, and all observed spiral galaxies, potentially be an ASMBH, with its event horizon concealing the equivalent number of antimatter particles, thereby preventing matter-antimatter destruction within a matter galaxy? This article assesses astronomical data comparing the mass of 100 SMBHs with their host galaxies. A theoretical value for the logarithmic mass relationship Log( MStellar /MSMBH ) is presented: 2.963 for ASMBHs situated in matter galaxies, and 2.285 for MSBHs in antimatter galaxies. This relationship, derived from the Ulianov Theory, is based on the premise of matter galaxy formation from protons and electrons expelled by ASMBHs during cosmic inflation. The same theory also posits antimatter galaxy formation from antiprotons and positrons released by matter SMBHs during this period. The database analysis (of 100 galaxies and their respective SMBHs) revealed that 77% of the SMBHs are composed of antimatter, resulting in a logarithmic relationship value of (2.945 ± 0.018) for the Log(MStellar/MASMBH ), while 23% are composed of matter, resulting in a value of (2.267 ± 0.036) for the Log( MAStellar/MSMBH). The congruence between these values and the theoretical prediction is likely not mere coincidence. A thorough examination of the results confirms the model's validity and underscores the precision of astronomers' mass measurements, with only 3 cases showing actual measurement errors beyond the predicted range. This discovery is pivotal, as it suggests the Ulianov Theory's potential to produce novel predictions, such as this model. Originating from a cold and empty universe, this model outlines the galaxy mass formation process, in which ASMBHs harness energy from cosmic inflation, converting it into matter and antimatter particles. This process is termed the "Small Bang" model by the author, reflecting its cold and gradual nature, contrasting the explosive nature of the "Big Bang".

Electrophilicity, mechanism and structure–reactivity relationships of cyclic secondary amines addition to 2-methoxy-3,5-dinitropyridine

The second-order rate constants (k) for the nucleophilic aromatic substitution reactions of 2‑methoxy-3,5-dinitropyridine 1 with secondary cyclic amines 2a-c in acetonitrile solution at 20 °C are reported. The logarithms of these rate constants are particularly significant as possible measures of the electrophilicity parameters E for 2‑methoxy-3,5-dinitropyridine 1 according to the linear free energy relationship log k (20 °C) = sN(N + E). Additional kinetic data for reactions of 2-methoxy-3,5-dinitropyridine 1 with a series of nitroalkyl anions in DMSO solution are also measured and found to agree with those calculated by Mayr's approach from the known two solvent-dependent parameters N and sN of nitroalkyl anions and the electrophilicity parameter E measured in this work. A Single Electron Transfer (SET) mechanism is proposed for the SNAr reactions, on the basis of the linear Brönsted plot with the βnuc value of 0.94. The validity of this mechanism is confirmed by the agreement between the rate constants, k, and the oxidation potentials E° of these series of secondary cyclic amines. Also, reactivity descriptors such as the electronic chemical potential (μ), and the chemical hardness (η) for a series of pyridine derivatives were calculated by Density Functional Theory (DFT), and it is shown that the global electrophilicity index (ω = μ2/2η) is significantly correlated with the electrophilicity parameters E.

DecLog: Decentralized Logging in Non-Volatile Memory for Time Series Database Systems

Growing demands for the efficient processing of extreme-scale time series workloads call for more capable time series database management systems (TSDBMS). Specifically, to maintain consistency and durability of transaction processing, systems employ write-ahead logging (WAL) whereby transactions are committed only after the related log entries are flushed to disk. However, when faced with massive I/O, this becomes a throughput bottleneck. Recent advances in byte-addressable Non-Volatile Memory (NVM) provide opportunities to improve logging performance by persisting logs to NVM instead. Existing studies typically track complex transaction dependencies and use barrier instructions of NVM to ensure log ordering. In contrast, few studies consider the heavy-tailed characteristics of time series workloads, where most transactions are independent of each other. We propose DecLog, a decentralized NVM-based logging system that enables concurrent logging of TSDBMS transactions. Specifically, we propose data-driven log sequence numbering and relaxed ordering strategies to track transaction dependencies and resolve serialization issues. We also propose a parallel logging method to persist logs to NVM after being compressed and aligned. An experimental study on the YCSB-TS benchmark offers insight into the performance properties of DecLog, showing that it improves throughput by up to 4.6× while offering lower recovery time in comparison to the open source TSDBMS Beringei.

Limiting mixed Hodge structures on the relative log de Rham cohomology groups of a projective semistable log smooth degeneration

We prove that the relative log de Rham cohomology groups of a projective semistable log smooth degeneration admit a natural limiting mixed Hodge structure. More precisely, we construct a family of increasing filtrations and a family of nilpotent endomorphisms on the relative log de Rham cohomology groups and show that they satisfy a part of good properties of a nilpotent orbit in several variables.

Testing SOAR tools in use

Investigations within Security Operation Centers (SOCs) are tedious as they rely on manual efforts to query diverse data sources, overlay related logs, correlate the data into information, and then document results in a ticketing system. Security Orchestration, Automation, and Response (SOAR) tools are a relatively new technology that promise, with appropriate configuration, to collect, filter, and display needed diverse information; automate many of the common tasks that unnecessarily require SOC analysts’ time; facilitate SOC collaboration; and, in doing so, improve both efficiency and consistency of SOCs. There has been no prior research to test SOAR tools in practice; hence, understanding and evaluation of their effect is nascent and needed. In this paper, we design and administer the first hands-on user study of SOAR tools, involving 24 participants and six commercial SOAR tools. Our contributions include the experimental design, itemizing six defining characteristics of SOAR tools, and a methodology for testing them. We describe configuration of a cyber range test environment, including network, user, and threat emulation; a full SOC tool suite; and creation of artifacts allowing multiple representative investigation scenarios to permit testing. We present the first research results on SOAR tools. Concisely, our findings are that: per-SOC SOAR configuration is extremely important; SOAR tools increase efficiency and reduce context switching, although with potentially decreased ticketing accuracy/completeness; user preference is slightly negatively correlated with their performance with the tool; internet dependence varies widely among SOAR tools; and balance of automation with assisting decision making is preferred by senior participants. We deliver a public user- and tool-anonymized and -obfuscated version of the data.

Application of machine learning algorithms in classification the flow units of the Kazhdumi reservoir in one of the oil fields in southwest of Iran

By determining the hydraulic flow units (HFUs) in the reservoir rock and examining the distribution of porosity and permeability variables, it is possible to identify areas with suitable reservoir quality. In conventional methods, HFUs are determined using core data. This is while considering the non-continuity of the core data along the well, there is a great uncertainty in generalizing their results to the entire depth of the reservoir. Therefore, using related wireline logs as continuous data and using artificial intelligence methods can be an acceptable alternative. In this study, first, the number of HFUs was determined using conventional methods including Winland R35, flow zone index, discrete rock type and k-means. After that, by using petrophysical logs and using machine learning algorithms including support vector machine (SVM), artificial neural network (ANN), LogitBoost (LB), random forest (RF), and logistic regression (LR), HFUs have been determined. The innovation of this article is the use of different intelligent methods in determining the HFUs and comparing these methods with each other in such a way that instead of using only two parameters of porosity and permeability, different data obtained from wireline logging are used. This increases the accuracy and speed of reaching the solution and is the main application of the methodology introduced in this study. Mentioned algorithms are compared with accuracy, and the results show that SVM, ANN, RF, LB, and LR with 90.46%, 88.12%, 91.87%, 94.84%, and 91.56% accuracy classified the HFUs respectively.

Identification and in silico characterization of CSRP3 synonymous variants in dilated cardiomyopathy

Synonymous variations have always been ignored while studying the underlying genetic mechanisms for most of the human diseases. However, recent studies have suggested that these silent changes in the genome can alter the protein expression and folding. CSRP3, which is a well-known candidate gene associated with dilated cardiomyopathy (DCM) and hypertrophic cardiomyopathy (HCM), was screened for 100 idiopathic DCM cases and 100 controls. Three synonymous variations were identified viz., c.96G > A, p.K32=; c.336G > A, p.A112=; c.354G > A, p.E118=. A comprehensive in silico analysis was performed using various web based widely accepted tools, Mfold, Codon Usage, HSF3.1 and RNA22. Mfold predicted structural changes in all the variants except c.96 G > A (p.K32=), however it predicted changes in the stability of mRNA due to all the synonymous variants. Codon bias was observed as evident by the Relative Synonymous Codon Usage and Log Ratio of Codon Usage Frequencies. The Human Splicing Finder also predicted remarkable changes in the regulatory elements in the variants c.336G > A and c.354 G > A. The miRNA target prediction using varied modes available in RNA22 revealed that 70.6% of the target sites of miRNAs in CSRP3 were altered due to variant c.336G > A while 29.41% sites were completely lost. Findings of the present study suggest that synonymous variants revealed striking deviations in the structural conformation of mRNA, stability of mRNA, relative synonymous codon usage, splicing and miRNA binding sites from the wild type suggesting their possible role in the pathogenesis of DCM, either by destabilizing the mRNA structure, or codon usage bias or else altering the cis-acting regulatory elements during splicing.

The First Photometric and Spectroscopic Study of Contact Binary V2840 Cygni

The first photometric, spectroscopic and period variation studies of neglected short-period eclipsing binary V2840 Cygni are presented. High mass ratio contact binaries (HMRCBs), especially those in the weak-contact configuration, are vital when probing the evolutionary models of contact binaries (CBs) using stellar parameters. The photometric solutions reveal the weak-contact nature of V2840 Cygni with a high mass ratio (∼1.36), motivating us to investigate the nature of such binaries. The period variation study of V2840 Cygni spanning 15 yr shows a secular period decrease at a rate of ∼5.5 × 10−7 day yr−1, indicating mass transfer between the components. The superimposed cyclic variation provides a basic understanding of the possible third body (P 3 ∼ 8 yr, m 3 ∼ 0.51 M ⊙). Following the derived parameters, the evolution of the system is discussed based on the thermal relaxation oscillation (TRO) model. It is found that V2840 Cygni falls in a special category of HMRCBs, which validates TRO. To characterize the nature of HMRCBs, a catalog of 59 CBs with high mass ratios has been compiled along with their derived parameters from the literature. For all the HMRCBs in the study, a possible correlation between their contact configuration and observed period variations for relative log J rel is discussed. The spectroscopic study of V2840 Cygni provides evidence of the presence of magnetic activity in the system and the existence of ongoing mass transfer which is additionally deduced from the period variation study. The LAMOST spectra of 17 HMRCBs are collected to interpret the stellar magnetic activity in such systems.

Vs30 Structure of Almeria City (SE Spain) Using SPAC and MASW Methods and Proxy Correlations

The topographic slope method is an innovative, fast and very low-cost technique for estimating the average S-wave velocity in the upper 30 m (Vs30) based on the relationship between this quantity and the slope of the ground, obtained using a Digital Elevation Model (DEM). The method is based on the good linear correlations log(Vs30)–log(slope) found experimentally, which, ideally, should be determined for each region. If measured Vs30 data are not available to carry out this fitting for the study area, correlations from other areas could be used, although the reliability of the estimated Vs30 results would be lower. In this article, Vs30 observations are made for the city of Almeria, using Spatial Autocorrelation Surveys (SPAC) and Multichannel Analysis of Surface Waves (MASW), obtaining two types of fitting: (a) linear relationship log(Vs30)–log(slope); and (b) considering additional dependence on geological units. The reliability, evaluated by Multiple R-Squared (MRS), varies between 79.2% in the first case and 87.0% in the second, lowering the mean absolute values of the residuals at the observation points in the first case from 40.0 m/s to 29.0 m/s. Using a more generic correlation obtained for other areas of the world, the mean absolute residuals increase to 74.7 m/s.

Intracellular autolytic whole cell Salmonella vaccine prevents colonization of pathogenic Salmonella Typhimurium in chicken

Salmonella enterica (SE) is a major foodborne bacterial pathogen in the United States, commonly found as the normal flora of various animals that is attributed to causing at least 1.2 million infections annually. Poultry plays a major role in disseminating SE through direct contact with live animals and consumption of contaminated products. Vaccinating poultry against SE is a sustainable approach that can reduce SE in the host, preventing future infections in humans. An intracellular autolytic SE serovar Typhimurium vaccine (STLT2+P13+19) was developed by integrating genes 13 (holin) and 19 (lysozyme) of bacteriophage P22 into the bacterial chromosome. These were inserted downstream of sseA, an SPI-2 chaperone in SE that expresses during the intracellular phase of SE. Intracellular viability of STLT2+P13+19 reduced by 94.42% at 24 hr compared to the wild type in chicken macrophage cells (HD-11), whereas growth rate and adhesion ability remained unchanged. Inoculating STLT2+P13+19 in HD-11 significantly enhanced the relative log fold expression of genes associated to production of pro-inflammatory cytokines (IL-1β, IL-6, IL-8, IL-10, IL-12 p40, IL-18, and GM-CSF) and Toll-like-receptors (TRL-3 and 7). Vaccination of an in vivo chicken model demonstrated significant changes in secretion of iNOS, IL-6, IL-8, IL-12, and TNF-α, as well as a reduction in the intestinal colonization of SE serovar Typhimurium. Microbiome analysis of cecal fluid using 16S rRNA gene sequencing also showed modulation of intestinal microbial composition, specifically a decrease in relative abundance of Proteobacteria and increasing Firmicutes. This study provides insight into a novel vaccine design that could make food products safer without the use of synthetic compounds.

Dorado and its member galaxies

Context. We are investigating the star formation in galaxies of the actively evolving Dorado group where, for a large fraction of both early- and late-type galaxies, signatures of interactions and merging events are revealed by optical and radio observations. Aims. Our previous Hα+[N II] study, probing ≈10 Myr timescales, suggested that star formation is still ongoing in early-type galaxies. In this work, we use far-UV (FUV) imaging to map recent star formation on longer timescales, on the order of 100 Myr. Methods. We used the Ultraviolet Imaging Telescope UVIT on board Astrosat to image the galaxies of the Dorado backbone previously observed in Hα+[N II], with the far-UV filter FUV.CaF2 (1300–1800 Å). The sample included NGC 1536, NGC 1546, NGC 1549, [CMI2001]4136-01, NGC 1553, IC 2058, PGC 75125, NGC 1566, NGC 1596, and NGC 1602; for the two latter galaxies, the UVIT data provided the first view in far-UV. For the others, previously observed by GALEX, the UVIT data afford a ∼5× improvement in spatial resolution. Results. FUV.CaF2 emission is revealed in all the Dorado galaxies observed, tracing young stellar populations in ring structures and showing tidal distortions. The Sérsic index, derived by fitting the luminosity profiles, is always n < 3, suggesting that the FUV.CaF2 emission originates from a disk also in early-type galaxies. The star formation rate (SFR) ranges from 0.004 ± 0.001 M⊙ yr−1 for [CMI2001]4136-01 to 2.455 ± 0.027 M⊙ yr−1 for NGC 1566. Most of the recent star formation is found at the periphery of the Dorado group, where most of late-type galaxies are located. For these galaxies, the ratio SFRHα/SFRFUV.CaF2 is close to 1, except for the edge-on IC 2058, similar to previously reported relations for local volume samples. For early-type galaxies, however, SFRHα is about 15 times higher than SFRFUV. Dorado’s early-type galaxies define a separate locus in SFRFUV, SFRHα space with respect to the late-type galaxies, which is well represented by the relation log (SFRFUV.CaF2) = 0.70 × log (SFRHα)−1.26. Conclusions. The disk structure of the FUV.CaF2 emitting populations discovered in all the early-types galaxies implies dissipative processes and wet merging events. The systematic discrepancy between SFRs derived from Hα and FUV fluxes suggests that rejuvenation episodes in early-type galaxies cannot sustain constant star formation over ∼100 Myr timescales.

Developing and implementing a self-monitoring toolkit for a coordinated multinational randomized acupuncture trial

BackgroundIn 2019, investigators from China, South Korea and the United States of America initiated a coordinated multinational trial. The trial included three parallel randomized studies with a planned pooled analysis of individual patient data, to test the effectiveness of acupuncture on hot flash-related symptoms in hormone receptor-positive breast cancer patients prescribed adjuvant endocrine therapy. Given the study's approach, there was no central coordinating center or data monitoring committee for the study, so a site performance self-monitoring toolkit was developed and implemented to support study teams in collecting and maintaining high-quality regulatory information, and consistent review of study data and documentation.MethodsThe site performance self-monitoring toolkit was created based on best practices related to post-approval quality assurance/quality improvement (QA/QI) procedures that support data quality. The toolkit included: (1) a binder of essential study management documents and related monitoring logs for sites to complete and maintain (herein called regulator binder), (2) a study start-up checklist, (3) a self-assessment study conduct and oversight checklist to be completed regularly, and (4) a study close-out checklist. In addition, a process of regular virtual meetings to discuss documentation progress coupled with periodic external remote review of completed logs and checklists provided accountability checks.ResultsOver the course of the study, the sites in China and South Korea completed the entirety of the site performance self-monitoring toolkit, and successfully submitted their completed materials for review. The process of implementing a self-monitoring toolkit in a multinational integrative medicine study is described qualitatively. Periodic external review of the completed toolkit materials revealed categories of findings. Written follow-up reports were provided to sites and discussion of the documents occurred via separate virtual meetings.ConclusionsSite study team self-monitoring provides a feasible, consistent, and effective way to review the collection and maintenance of data and regulatory documentation for quality assessment in minimal risk clinical research studies and can augment formal study monitoring activities in higher risk studies. Iterative feedback and support appeared to drive a disciplined approach to maintaining regulatory document compliance and helped sustain investigator and study team engagement in the process.Trial registrationClinicalTrials.gov Identifier NCT03783546 (21/12/2018).

Systematic Analysis of Actively Transcribed Core Matrisome Genes Across Tissues and Cell Phenotypes

The extracellular matrix (ECM) is a highly dynamic, well-organized acellular network of tissue-specific biomolecules, that can be divided into structural or core ECM proteins and ECM-associated proteins. The ECM serves as a blueprint for organ development and function and, when structurally altered through mutation, altered expression, or degradation, can lead to debilitating syndromes that often affect one tissue more than another. Cross-referencing the FANTOM5 SSTAR (Semantic catalog of Samples, Transcription initiation And Regulators) and the defined catalog of core matrisome ECM (glyco)proteins, we conducted a comprehensive analysis of 511 different human samples to annotate the context-specific transcription of the individual components of the defined matrisome. Relative log expression normalized SSTAR cap analysis gene expression peak data files were downloaded from the FANTOM5 online database and filtered to exclude all cell lines and diseased tissues. Promoter-level expression values were categorized further into eight core tissue systems and three major ECM categories: proteoglycans, glycoproteins, and collagens. Hierarchical clustering and correlation analyses were conducted to identify complex relationships in promoter-driven gene expression activity. Integration of the core matrisome and curated FANTOM5 SSTAR data creates a unique tool that provides insight into the promoter-level expression of ECM-encoding genes in a tissue- and cell-specific manner. Unbiased clustering of cap analysis gene expression peak data reveals unique ECM signatures within defined tissue systems. Correlation analysis among tissue systems exposes both positive and negative correlation of ECM promoters with varying levels of significance. This tool can be used to provide new insight into the relationships between ECM components and tissues and can inform future research on the ECM in human disease and development. We invite the matrix biology community to continue to explore and discuss this dataset as part of a larger and continuing conversation about the human ECM. An interactive web tool can be found at matrixpromoterome.github.io along with additional resources that can be found at dx.doi.org/10.6084/m9.figshare.19794481 (figures) and https://figshare.com/s/e18ecbc3ae5aaf919b78 (python notebook).

Signature whistles exhibit a ‘fade-in’ and then ‘fade-out’ pattern of relative amplitude declination

Bottlenose dolphins have individually distinct signature whistles that are characterized by a stereotyped frequency-time contour. Signature whistles are commonly exchanged with short time delays between calls. Dolphin whistles are produced by pressurized nasal sacs that increase and then decrease in pressure over emission. This study found that the relative amplitude modulation pattern over time exhibited the same fade-in and then fade-out pattern in the signature whistles of eight bottlenose dolphins at the Navy in San Diego, CA. Both the initial and final five percent of the whistle’s duration also had significantly lower mean relative amplitude than the center five percent. The current analyses of the amplitude-time relationship was then integrated to a previously reported model of the negative relationship between relative log amplitude and log peak frequency. This produced a more robust model for accounting for the predictable aspects of the more broadly non-stereotyped amplitude modulations of signature whistles. Whether dolphins can intentionally manipulate these amplitude features or they are simple by-products of the sound production system, and further whether they are perceived and utilized by receivers, is an exciting area for continued research.

In Professional Male Soccer Players, Time-Loss Groin Injury Is More Associated With the Team Played for Than With Training/Match-Play Duration.

To investigate the relationship between training/match-play duration and time-loss groin injury in professional male soccer players, and to determine whether previously identified intrinsic risk factors influenced this relationship. Prospective cohort study. A total of 579 professional male soccer players were prospectively followed from July 2013 to June 2015. Time-loss groin injuries and individual training and match-play duration were recorded using standardized surveillance methods. Acute training/match-play duration and chronic training/match-play duration were considered as interacting variables. Nonlinear Cox regression analysis (modeled using restricted cubic splines), clustered by player identification number, examined the relationship between training/match-play duration and groin injury. Previously identified intrinsic risk factors of previous groin injury and eccentric adduction strength were included in the multivariable regression analysis. There was no clinically meaningful relationship between training/match-play duration and groin injury risk. Team played for had the strongest influence on groin injury risk (relative log hazard ratio -2.28 to 0.97). Groin injury risk was highest when accumulated chronic and acute training duration was also highest, but large confidence intervals indicate considerable uncertainty around this finding. Previous groin injury and eccentric adduction strength were not associated with groin injury risk when training/match-play duration and team were included in the model. In professional male soccer players, there was no clinically meaningful relationship between groin injury risk and training/match-play duration. Team played for either protected against or increased groin injury risk, indicating that team-related factors not measured in this study had greater effect on groin injury risk than training/match-play duration. J Orthop Sports Phys Ther 2022;52(4):217-223. Epub 5 Feb 2022. doi:10.2519/jospt.2022.10845.

A data-driven biocomputing pipeline with meta-analysis on high throughput transcriptomics to identify genome-wide miRNA markers associated with type 2 diabetes

BackgroundMicroRNAs (miRNAs) are sought-after biomarkers of complex, polygenic diseases such as type 2 diabetes (T2D). Data-driven biocomputing provides robust and novel avenues for synthesizing evidence from individual miRNA seq studies. ObjectiveTo identify miRNA markers associated with T2D, via a data-driven, biocomputing approach on high throughput transcriptomics. Materials and methodsThe pipeline consisted of five sequential steps using miRNA seq data retrieved from the National Center for Biotechnology Information Gene Expression Omnibus platform: systematic review; identification of differentially expressed miRNAs (DE-miRNAs); meta-analysis of DE-miRNAs; network analysis; and downstream analyses. Three normalization algorithms (trimmed mean of M-values; upper quartile; relative log expression) and two meta-analytic algorithms (robust rank aggregation; Fisher's method of p-value combining) were integrated into the pipeline. Network analysis was conducted on miRNet 2.0 while enrichment and over-representation analyses were conducted on miEAA 2.0. ResultsA total of 1256 DE-miRNAs (821 downregulated; 435 upregulated) were identified from 5 eligible miRNA seq datasets (3 circulatory; 1 adipose; 1 pancreatic). The meta-signature comprised 9 miRNAs (hsa-miR-15b-5p; hsa-miR-33b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p; hsa-miR-483-5p; hsa-miR-539-3p; hsa-miR-1260a; hsa-miR-4454), identified via the two meta-analysis approaches. Two hub nodes (hsa-miR-106b-5p; hsa-miR-15b-5p) with above-average degree and betweenness centralities in the miRNA-gene interactions network were identified. Downstream analyses revealed 5 highly conserved- (hsa-miR-33b-5p; hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p) and 7 highly confident- (hsa-miR-33b-5p; hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-106b-5p; hsa-miR-146a-5p; hsa-miR-483-5p; hsa-miR-539-3p) miRNAs. A total of 288 miRNA-disease associations were identified, in which 3 miRNAs (hsa-miR-15b-5p; hsa-miR-106b-3p; hsa-miR-146a-5p) were highly enriched. ConclusionsA meta-signature of DE-miRNAs associated with T2D was discovered via in-silico analyses and its pathobiological relevance was validated against corroboratory evidence from contemporary studies and downstream analyses. The miRNA meta-signature could be useful for guiding future studies on T2D. There may also be avenues for using the pipeline more broadly for evidence synthesis on other conditions using high throughput transcriptomics.

Complexation Equilibria and Determination of Stability Constants of Some Divalent Metal Ion Complexes of L-Cysteine and Diphenylamine in Aqueous Media

<i>Background. </i>Metal complexes of biologically active ligands had considerable interests. L-cysteinate residue, L-Cys, is a biologically abundant and important versatile binding site of proteins. Diphenylamine, DPA, is an important aromatic amine containing two phenyl groups. Complexation equilibria of the divalent metal ions, Ca²⁺ and Zn²⁺ with the bio- relevant α-amino acid, L-cysteine and the nitrogen-containing diphenylamine ligand were investigated by means of the potentiometric technique at 25.0 ± 0.1°C and constant ionic strength of 0.200 ± 0.001 mol·dm^-3 NaNO₃. <i>Objective.</i> The stability constants and standard free energy changes of the α-amino acid, L-cysteine and diphenylamine complex species were determined at 0.200 ± 0.001 mol·dm^-3ionic strength. <i>Methods.</i> The formation of the different 1:1 and 1:2 binary complexes and 1:1:1 ternary complexes were inferred from the potentiometric titrations. <i>Results.</i> The concentration distribution of L-cysteine species formed in solution was evaluated. The dissociation constants of the α-amino acid and diphenylamine were determined at different ionic strength. The stability constants of these binary and ternary systems were calculated. The values of ∆ log₁₀ K, percent relative stabilization, %R.S. and log₁₀ X for the ternary systems were evaluated and discussed. <i>Concussion.</i> The ternary complex formation occurred in a stepwise manner with L-cysteine acting as the primary ligand. The obtained values of ∆ G⁰ indicated that Complex formation reactions are spontaneous. Also, for all systems studied, the ternary complexes formed are more thermodynamically stable than the binary complexes.

Hyperbolicity for Log Smooth Families with Maximal Variation

Abstract We prove that the base space of a log smooth family of log canonical pairs of log general type is of log general type as well as algebraically degenerate, when the family admits a relative good minimal model over a Zariski open subset of the base and the relative log canonical model is of maximal variation.