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The editorial discusses the history and importance of optometry journals, focusing on the impact of publishing costs on their viability. It highlights the rich history of optometry journals dating back to the late 19th century and the extensive archive of articles published in these journals. The editorial emphasizes the broad reach of optometry journals, with citations coming from various subject areas beyond optometry, indicating their value to a wide range of disciplines. The analysis presented underscores the significance of optometry journals and the need for ongoing support to preserve and nurture these valuable resources. [Extracted from the article]

This work presents a threat modelling approach to represent changes to the attack paths through an Internet of Things (IoT) environment when the environment changes dynamically, that is, when new devices are added or removed from the system or when whole sub-systems join or leave. The proposed approach investigates the propagation of threats using attack graphs, a popular attack modelling method. However, traditional attack-graph approaches have been applied in static environments that do not continuously change, such as enterprise networks, leading to static and usually very large attack graphs. In contrast, IoT environments are often characterised by dynamic change and interconnections; different topologies for different systems may interconnect with each other dynamically and outside the operator's control. Such new interconnections lead to changes in the reachability amongst devices according to which their corresponding attack graphs change. This requires dynamic topology and attack graphs for threat and risk analysis. This article introduces an example scenario based on healthcare systems to motivate the work and illustrate the proposed approach. The proposed approach is implemented using a graph database management tool (GDBM), Neo4j, which is a popular tool for mapping, visualising, and querying the graphs of highly connected data. It is efficient in providing a rapid threat modelling mechanism, making it suitable for capturing security changes in the dynamic IoT environment. Our results show that our developed threat modelling approach copes with dynamic system changes that may occur in IoT environments and enables identifying attack paths, whilst allowing for system dynamics. The developed dynamic topology and attack graphs can cope with the changes in the IoT environment efficiently and rapidly by maintaining their associated graphs. [ABSTRACT FROM AUTHOR]

With the rise of deep learning in various applications, privacy concerns around the protection of training data have become a critical area of research. Whereas prior studies have focused on privacy risks in single-modal models, we introduce a novel method to assess privacy for multi-modal models, specifically vision-language models like CLIP. The proposed Identity Inference Attack (IDIA) reveals whether an individual was included in the training data by querying the model with images of the same person. Letting the model choose from a wide variety of possible text labels, the model reveals whether it recognizes the person and, therefore, was used for training. Our large-scale experiments on CLIP demonstrate that individuals used for training can be identified with very high accuracy. We confirm that the model has learned to associate names with depicted individuals, implying the existence of sensitive information that can be extracted by adversaries. Our results highlight the need for stronger privacy protection in large-scale models and suggest that IDIAs can be used to prove the unauthorized use of data for training and to enforce privacy laws. [ABSTRACT FROM AUTHOR]

Anomaly detection (AD) task corresponds to identifying the true anomalies among a given set of data instances. AD algorithms score the data instances and produce a ranked list of candidate anomalies. The ranked list of anomalies is then analyzed by a human to discover the true anomalies. Ensemble of tree-based anomaly detectors trained in an unsupervised manner and scoring based on uniform weights for ensembles are shown to work well in practice. However, the manual process of analysis can be laborious for the human analyst when the number of false-positives is very high. Therefore, in many real-world AD applications including computer security and fraud prevention, the anomaly detector must be configurable by the human analyst to minimize the effort on false positives. One important way to configure the detector is by providing true labels (nominal or anomaly) for a few instances. Recent work on active anomaly discovery has shown that greedily querying the top-scoring instance and tuning the weights of ensemble detectors based on label feedback allows us to quickly discover true anomalies. This paper makes four main contributions to improve the state-of-the-art in anomaly discovery using tree-based ensembles. First, we provide an important insight that explains the practical successes of unsupervised tree-based ensembles and active learning based on greedy query selection strategy. We also present empirical results on real-world data to support our insights and theoretical analysis to support active learning. Second, we develop a novel batch active learning algorithm to improve the diversity of discovered anomalies based on a formalism called compact description to describe the discovered anomalies. Third, we develop a novel active learning algorithm to handle streaming data setting. We present a data drift detection algorithm that not only detects the drift robustly, but also allows us to take corrective actions to adapt the anomaly detector in a principled manner. Fourth, we present extensive experiments to evaluate our insights and our tree-based active anomaly discovery algorithms in both batch and streaming data settings. Our results show that active learning allows us to discover significantly more anomalies than state-of-the-art unsupervised baselines, our batch active learning algorithm discovers diverse anomalies, and our algorithms under the streaming-data setup are competitive with the batch setup. [ABSTRACT FROM AUTHOR]

In generating adversarial examples, the conventional black-box attack methods rely on sufficient feedback from the to-be-attacked models by repeatedly querying until the attack is successful, which usually results in thousands of trials during an attack. This may be unacceptable in real applications since Machine Learning as a Service Platform (MLaaS) usually only returns the final result (i.e., hard-label) to the client and a system equipped with certain defense mechanisms could easily detect malicious queries. By contrast, a feasible way is a hard-label attack that simulates an attacked action being permitted to conduct a limited number of queries. To implement this idea, in this paper, we bypass the dependency on the to-be-attacked model and benefit from the characteristics of the distributions of adversarial examples to reformulate the attack problem in a distribution transform manner and propose a distribution transform-based attack (DTA). DTA builds a statistical mapping from the benign example to its adversarial counterparts by tackling the conditional likelihood under the hard-label black-box settings. In this way, it is no longer necessary to query the target model frequently. A well-trained DTA model can directly and efficiently generate a batch of adversarial examples for a certain input, which can be used to attack un-seen models based on the assumed transferability. Furthermore, we surprisingly find that the well-trained DTA model is not sensitive to the semantic spaces of the training dataset, meaning that the model yields acceptable attack performance on other datasets. Extensive experiments validate the effectiveness of the proposed idea and the superiority of DTA over the state-of-the-art. [ABSTRACT FROM AUTHOR]

Glucose-6-phosphate dehydrogenase (G6PD) catalyzes the first committed step of the oxidative pentose phosphate pathway (OPPP). Our recent phosphoproteomics study revealed that the cytosolic G6PD6 isozyme became hyperphosphorylated at Ser12, Thr13 and Ser18, 48 h following phosphate (Pi) resupply to Pi-starved (–Pi) Arabidopsis thaliana cell cultures. The aim of the present study was to assess whether G6PD6 phosphorylation also occurs in shoots or roots following Pi resupply to –Pi Arabidopsis seedlings, and to investigate its relationship with G6PD activity. Interrogation of phosphoproteomic databases indicated that N-terminal, multi-site phosphorylation of G6PD6 and its orthologs is quite prevalent. However, the functions of these phosphorylation events remain unknown. Immunoblotting with an anti-(pSer18 phosphosite-specific G6PD6) antibody confirmed that G6PD6 from Pi-resupplied, but not –Pi, Arabidopsis cell cultures or seedlings (i.e., roots) was phosphorylated at Ser18; this correlated with a significant increase in extractable G6PD activity, and biomass accumulation. Peptide kinase assays of Pi-resupplied cell culture extracts indicated that G6PD6 phosphorylation at Ser18 is catalyzed by a Ca2+-dependent protein kinase (CDPK), which correlates with the 'CDPK-like' targeting motif that flanks Ser18. Our results support the hypothesis that N-terminal phosphorylation activates G6PD6 to enhance OPPP flux and thus the production of reducing power (i.e., NADPH) and C-skeletons needed to establish the rapid resumption of growth that ensures Pi-resupply to –Pi Arabidopsis. [ABSTRACT FROM AUTHOR]

Seminoma is the most common testicular cancer. Pituitary tumor-transforming gene 1 (PTTG1) is a securin showing oncogenic activity in several tumors. We previously demonstrated that nuclear PTTG1 promotes seminoma tumor invasion through its transcriptional activity on matrix metalloproteinase 2 (MMP-2) and E-cadherin (CDH1). We wondered if specific interactors could affect its subcellular distribution. To this aim, we investigated the PTTG1 interactome in seminoma cell lines showing different PTTG1 nuclear levels correlated with invasive properties. A proteomic approach upon PTTG1 immunoprecipitation uncovered new specific securin interactors. Western blot, confocal microscopy, cytoplasmic/nuclear fractionation, sphere-forming assay, and Atlas database interrogation were performed to validate the proteomic results and to investigate the interplay between PTTG1 and newly uncovered partners. We observed that spectrin beta-chain (SPTBN1) and PTTG1 were cofactors, with SPTBN1 anchoring the securin in the cytoplasm. SPTBN1 downregulation determined PTTG1 nuclear translocation, promoting its invasive capability. Moreover, a PTTG1 deletion mutant lacking SPTBN1 binding was strongly localized in the nucleus. The Atlas database revealed that seminomas that contained higher nuclear PTTG1 levels showed significantly lower SPTBN1 levels in comparison to non-seminomas. In human seminoma specimens, we found a strong PTTG1/SPTBN1 colocalization that decreases in areas with nuclear PTTG1 distribution. Overall, these results suggest that SPTBN1, along with PTTG1, is a potential prognostic factor useful in the clinical management of seminoma. [ABSTRACT FROM AUTHOR]

The family of GalNAc-Ts (GalNAcpolypeptide:N-Acetylgalactosaminyl transferases) catalyzes the first committed step in the synthesis of O-glycans, which is an abundant and biologically important protein modification. Abnormalities in the activity of individual GalNAc-Ts can result in congenital disorders of O-glycosylation (CDG) and influence a broad array of biological functions. How site-specific O-glycans regulate biology is unclear. Compiling in vivo O-glycosites would be an invaluable step in determining the function of site-specific O-glycans. We integrated chemical and enzymatic conditions that cleave O-glycosites, a higher-energy dissociation product ions-triggered electron-transfer/higher-energy collision dissociation mass spectrometry (MS) workflow and software to study nine mouse tissues and whole blood. We identified 2,154 O-glycosites from 595 glycoproteins. The O-glycosites and glycoproteins displayed consensus motifs and shared functions as classified by Gene Ontology terms. Limited overlap of O-glycosites was observed with protein O-GlcNAcylation and phosphorylation sites. Quantitative glycoproteomics and proteomics revealed a tissue-specific regulation of O-glycosites that the differential expression of Galnt isoenzymes in tissues partly contributes to. We examined the Galnt2-null mouse model, which phenocopies congenital disorder of glycosylation involving GALNT2 and revealed a network of glycoproteins that lack GalNAc-T2-specific O-glycans. The known direct and indirect functions of these glycoproteins appear consistent with the complex metabolic phenotypes observed in the Galnt2-null animals. Through this study and interrogation of databases and the literature, we have compiled an atlas of experimentally identified mouse O-glycosites consisting of 2,925 O-glycosites from 758 glycoproteins. [ABSTRACT FROM AUTHOR]

This paper presents the results of a bibliometric study providing a comprehensive overview of the social science research conducted on criminal interrogations and investigative interviews since the 1900s. The objectives are to help researchers to further understand the research field, to better communicate research findings to practitioners, to help practitioners understand the breadth of scientific knowledge on criminal interrogations and investigative interviews, and to foster dialog between researchers and practitioners. To begin, after a brief description of Web of Science, we describe how we developed our database on criminal interrogations and investigative interviews. Then, we report the yearly evolution of articles, the journals where they were published, the research areas covered by this research field, as well as the authors, the institutions and the countries that published the most on a variety of topics related to criminal interrogations and investigative interviews. Finally, we present the most used keywords and the most cited articles, and examine the research on questionable tactics and techniques in the research field of criminal interrogations and investigative interviews. This paper ends with a critical look at the results, for the benefit of researchers and practitioners interested in criminal interrogations and investigative interviews. [ABSTRACT FROM AUTHOR]

Motivation Despite advances in method development for multiple sequence alignment over the last several decades, the alignment of datasets exhibiting substantial sequence length heterogeneity, especially when the input sequences include very short sequences (either as a result of sequencing technologies or of large deletions during evolution) remains an inadequately solved problem. Results We present HMMerge, a method to compute an alignment of datasets exhibiting high sequence length heterogeneity, or to add short sequences into a given 'backbone' alignment. HMMerge builds on the technique from its predecessor alignment methods, UPP and WITCH, which build an ensemble of profile HMMs to represent the backbone alignment and add the remaining sequences into the backbone alignment using the ensemble. HMMerge differs from UPP and WITCH by building a new 'merged' HMM from the ensemble, and then using that merged HMM to align the query sequences. We show that HMMerge is competitive with WITCH, with an advantage over WITCH when adding very short sequences into backbone alignments. Availability and implementation HMMerge is freely available at https://github.com/MinhyukPark/HMMerge. Supplementary information Supplementary data are available at Bioinformatics Advances online. [ABSTRACT FROM AUTHOR]

Motivation Cell label annotation is a challenging step in the analysis of single-cell RNA sequencing (scRNA-seq) data, especially for tissue types that are less commonly studied. The accumulation of scRNA-seq studies and biological knowledge leads to several well-maintained cell marker databases. Manually examining the cell marker lists against these databases can be difficult due to the large amount of available information. Additionally, simply overlapping the two lists without considering gene ranking might lead to unreliable results. Thus, an automated method with careful statistical testing is needed to facilitate the usage of these databases. Results We develop a user-friendly computational tool, EasyCellType, which automatically checks an input marker list obtained by differential expression analysis against the databases and provides annotation recommendations in graphical outcomes. The package provides two statistical tests, gene set enrichment analysis and a modified version of Fisher's exact test, as well as customized database and tissue type choices. We also provide an interactive shiny application to annotate cells in a user-friendly graphical user interface. The simulation study and real-data applications demonstrate favorable results by the proposed method. Availability and implementation https://biostatistics.mdanderson.org/shinyapps/EasyCellType/ ; https://bioconductor.org/packages/devel/bioc/html/EasyCellType.html. Supplementary information Supplementary data are available at Bioinformatics Advances online. [ABSTRACT FROM AUTHOR]

Simple Summary: Members of the KCTD protein family play major roles in numerous physiopathological functions. Although they are traditionally considered to be involved in neurological and neurodevelopmental processes, there is increasing evidence of their roles as either oncogenic or oncosuppressor factors. Here, we show that KCTD1 has an active role in modulating the stemness and mobility of colon cancer cell lines by affecting the WNT/β-catenin signalling pathway. These findings, which are also supported by analyses of The Cancer Genome Atlas (TCGA) database, provide evidence of the role of KCTD1 as an oncosuppressor. The KCTD protein family is traditionally regarded as proteins that play key roles in neurological physiopathology. However, new studies are increasingly demonstrating their involvement in many other biological processes, including cancers. This is particularly evident for KCTD proteins not involved in protein ubiquitination and degradation, such as KCTD1. We explored the role of KCTD1 in colorectal cancer by knocking down this protein in the human colon adenocarcinoma cell line, SW480. We re-assessed its ability to downregulate β-catenin, a central actor in the WNT/β-catenin signalling pathway. Interestingly, opposite effects are observed when the protein is upregulated in CACO2 colorectal cancer cells. Moreover, interrogation of the TCGA database indicates that KCTD1 downregulation is associated with β-catenin overexpression in colorectal cancer patients. Indeed, knocking down KCTD1 in SW480 cells led to a significant increase in their motility and stemness, two important tumorigenesis traits, suggesting an oncosuppressor role for KCTD1. It is worth noting that similar effects are induced on colorectal cancer cells by the misregulation of KCTD12, a protein that is distantly related to KCTD1. The presented results further expand the spectrum of KCTD1 involvement in apparently unrelated physiopathological processes. The similar effects produced on colorectal cancer cell lines by KCTD1 and KCTD12 suggest novel, previously unreported analogous activities among members of the KCTD protein family. [ABSTRACT FROM AUTHOR]

Background The standard-of-care protocol, based on plasma exchanges, high-dose intravenous immunoglobulin and optimization of maintenance immunosuppression, can slow down the evolution of antibody-mediated rejection (AMR), but with high interindividual variability. Identification of a reliable predictive tool of the response to AMR treatment is a mandatory step for personalization of the follow-up strategy and to guide second-line therapies. Methods Interrogation of the electronic databases of 2 French university hospitals (Lyon and Strasbourg) retrospectively identified 81 renal transplant recipients diagnosed with AMR without chronic lesions (cg score ≤1) at diagnosis and for whom a follow-up biopsy had been performed 3–6 months after initiation of therapy. Results The evolution of humoral lesions on follow-up biopsy (disappearance versus persistence versus progression) correlated with the risk for allograft loss (logrank test, P  = .001). Patients with disappearance of humoral lesions had ∼80% graft survival at 10 years. The hazard ratio for graft loss in multivariate analysis was 3.91 (P  = .04) and 5.15 (P  = .02) for patients with persistence and progression of lesions, respectively. The non-invasive parameters classically used to follow the intensity of humoral alloimmune response (evolution of immunodominant DSA mean fluorescence intensity) and the decline of renal graft function (estimated glomerular filtration rate decrease and persistent proteinuria) showed little clinical value to predict the histological response to AMR therapy. Conclusion We conclude that invasive monitoring of the evolution of humoral lesions by the mean of follow-up biopsy performed 3–6 months after the initiation of therapy is an interesting tool to predict long-term outcome after AMR treatment. [ABSTRACT FROM AUTHOR]

We give solutions to two fundamental computational problems in ontology-based data access with the W3C standard ontology language OWL 2 QL: the succinctness problem for first-order rewritings of ontology-mediated queries (OMQs) and the complexity problem for OMQ answering. We classify OMQs according to the shape of their conjunctive queries (treewidth, the number of leaves) and the existential depth of their ontologies. For each of these classes, we determine the combined complexity of OMQ answering and whether all OMQs in the class have polynomial-size first-order, positive existential, and nonrecursive datalog rewritings. We obtain the succinctness results using hypergraph programs, a new computational model for Boolean functions, which makes it possible to connect the size of OMQ rewritings and circuit complexity. [ABSTRACT FROM AUTHOR]

Patnaik and Immerman introduced the dynamic complexity class DynFO of database queries that can be maintained by first-order dynamic programs with the help of auxiliary relations under insertions and deletions of edges. This article confirms their conjecture that the reachability query is in DynFO. As a byproduct, it is shown that the rank of a matrix with small values can be maintained in DynFO. It is further shown that the (size of the) maximum matching of a graph can be maintained in non-uniform DynFO, an extension of DynFO, with non-uniform initialisation of the auxiliary relations. [ABSTRACT FROM AUTHOR]

Neutrophils are the most abundant type of white blood cells in humans with biological roles relevant to inflammation, and fighting off infections. Neutrophil Extracellular Traps (NETs) act as enxogenous agents controlling invasion by bacteria, viruses, fungi, metabolic, and traumatic agents. Traditionally, studies have focused on elucidating molecular and cellular pathways preceding NET formation. Here, we developed a model to decode the human genome and proteome of developted NETs. Via in vitro system to differentiate HL-60 human myeloid cell line into neutrophil extracellular trap (ecTrap) producing cells, we isolated and captured ectrap derived DNA and proteins for shotgun sequencing. The genomic sequences revealed accurate delineation of gene composition including immune response genes and mitochondrial enrichment, while providing a reference database for future interrogation. Shotgun proteomics showed global proteins in differentiated cells with specific immune pathways when compared to undifferentiated counterparts. Coupled with omics' approaches, we validated our system by functional assays and began to dissect host-microbial interactions. Our work provides a new understanding of the genomic and proteomic sequences, establishing the first human database deposition of neutrophil extracellular traps. Measurement(s) Genome Sequence Reads • Protein Abundance Technology Type(s) Illuminia • liquid chromatography-tandem mass spectrometry Factor Type(s) Neutrophil extracellular trap genome sequence • Neutrophil extracellular trap protein abundance Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment cell culture [ABSTRACT FROM AUTHOR]

Genome-wide chromosomal microarray is extensively used to detect copy number variations (CNVs), which can diagnose microdeletion and microduplication syndromes. These small unbalanced chromosomal structural rearrangements ranging from 1 kb to 10 Mb comprise up to 15% of human mutations leading to monogenic or contiguous genomic disorders. Albeit rare, CNVs at 1p13.3 cause a variety of neurodevelopmental disorders (NDDs) including development delay (DD), intellectual disability (ID), autism, epilepsy, and craniofacial anomalies (CFA). Most of the 1p13.3 CNV cases reported in the pre-microarray era encompassed a large number of genes and lacked the demarcating genomic coordinates, hampering the discovery of positional candidate genes within the boundaries. In this study, we present four subjects with 1p13.3 microdeletions displaying DD, ID, autism, epilepsy, and CFA. In silico comparative genomic mapping with three previously reported subjects with CNVs and 22 unreported DECIPHER CNV cases has resulted in the identification of four different sub-genomic loci harboring five positional candidate genes for DD, ID, and CFA at 1p13.3. Most of these genes have pathogenic variants reported, and their interacting genes are involved in NDDs. RT-qPCR in various human tissues revealed a high expression pattern in the brain and fetal brain, supporting their functional roles in NDDs. Interrogation of variant databases and interacting protein partners led to the identification of another set of 11 potential candidate genes, which might have been dysregulated by the position effect of these CNVs at 1p13.3. Our studies define 1p13.3 as a genomic region harboring 16 NDD candidate genes and underscore the critical roles of small CNVs in in silico comparative genomic mapping for disease gene discovery. Our candidate genes will help accelerate the isolation of pathogenic heterozygous variants from exome/genome sequencing (ES/GS) databases. [ABSTRACT FROM AUTHOR]

In this paper, we introduce Linked Open Data (LOD) in the archaeological domain as a means to connect dispersed data sources and enable cross-querying. The technology behind the design principles and how LOD can be created and published is described to enable less-familiar researchers to understand the presented benefits and drawbacks of LOD. Wikidata is introduced as an open knowledge hub for the creation and dissemination of LOD. Different actors within archaeology have implemented LOD, and we present which challenges have been and are being addressed. A selection of projects showcases how Wikidata is being used by archaeologists to enrich and open their databases to the general public. With this paper, we aim to encourage the creation and re-use of LOD in archaeology, as we believe it offers an improvement on current data publishing practices. [ABSTRACT FROM AUTHOR]

Physical inactivity is a worldwide health problem, an important risk for global mortality and is associated with chronic noncommunicable diseases. The aim of this study was to explore the differences in systemic urine 1H-NMR metabolomes between physically active and inactive healthy young males enrolled in the X-Adapt project in response to controlled exercise (before and after the 3-day exercise testing and 10-day training protocol) in normoxic (21% O2), normobaric (~1000 hPa) and normal-temperature (23 °C) conditions at 1 h of 50% maximal pedaling power output (Wpeak) per day. Interrogation of the exercise database established from past X-Adapt results showed that significant multivariate differences existed in physiological traits between trained and untrained groups before and after training sessions and were mirrored in significant differences in urine pH, salinity, total dissolved solids and conductivity. Cholate, tartrate, cadaverine, lysine and N6-acetyllisine were the most important metabolites distinguishing trained and untrained groups. The relatively little effort of 1 h 50% Wpeak per day invested by the untrained effectively modified their resting urine metabolome into one indistinguishable from the trained group, which hence provides a good basis for the planning of future recommendations for health maintenance in adults, irrespective of the starting fitness value. Finally, the 3-day sessions of morning urine samples represent a good candidate biological matrix for future delineations of active and inactive lifestyles detecting differences unobservable by single-day sampling due to day-to-day variability. [ABSTRACT FROM AUTHOR]

[Display omitted] • Identification of new biomarkers linked to ICD in DUs. • Development of a diagnostic model using a random forest algorithm. • Near-perfect ROC analysis scores indicating high accuracy in differentiating DU from normal tissue. • Categorization of DUs into molecular classifications for a deeper understanding of their pathophysiology. • Potential implications for transformative strategies in DU management and personalized medicine. In this study, we redefine the diagnostic landscape of diabetic ulcers (DUs), a major diabetes complication. Our research uncovers new biomarkers linked to immunogenic cell death (ICD) in DUs by utilizing RNA-sequencing data of Gene Expression Omnibus (GEO) analysis combined with a comprehensive database interrogation. Employing a random forest algorithm, we have developed a diagnostic model that demonstrates improved accuracy in distinguishing DUs from normal tissue, with satisfactory results from ROC analysis. Beyond mere diagnosis, our model categorizes DUs into novel molecular classifications, which may enhance our comprehension of their underlying pathophysiology. This study bridges the gap between molecular insights and clinical practice. It sets the stage for transformative strategies in DUs management, marking a significant step forward in personalized medicine for diabetic patients. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) emerges as the third leading cause of cancer mortality, contributing to approximately 830,000 deaths annually. The mechanisms driving its pathogenesis remain largely elusive. Through bioinformatic scrutiny, Mitochondrial Carrier 1 (MTCH1), a component of the mitochondrial carrier family, has been pinpointed as potentially pivotal in HCC evolution. Examination of The Cancer Genome Atlas (TCGA) database indicated a pronounced increase in MTCH1 expression within HCC tissues versus normal liver counterparts. Subsequent analyses, utilizing both Kaplan-Meier mapper and Gene Expression Profiling Interactive Analysis (GEPIA) datasets, associated elevated MTCH1 levels with reduced overall survival (OS) and disease-free survival (DFS). Complementary in vitro assessments confirmed that MTCH1 downregulation suppresses HCC cell proliferation and notably diminishes HCC xenograft tumor growth in murine models. Additional explorations, including Gene Set Enrichment Analysis (GSEA), STRING database interrogation, and quantitative PCR (qPCR) experiments, suggest MTCH1's involvement in HCC progression via the CDK-RB-E2F signaling axis. Collectively, these insights endorse MTCH1 as a promising therapeutic target for HCC, underscoring its significance in the disease's molecular framework and potential treatment innovation. [ABSTRACT FROM AUTHOR]

Protein stability is a fundamental molecular property enabling organisms to adapt to their biological niches. How this is facilitated and whether there are kingdom specific or more general universal strategies are unknown. A principal obstacle to addressing this issue is that the vast majority of proteins lack annotation, specifically thermodynamic annotation, beyond the amino acid and chromosome information derived from genome sequencing. To address this gap and facilitate future investigation into large-scale patterns of protein stability and dynamics within and between organisms, we applied a unique ensemble-based thermodynamic characterization of protein folds to a substantial portion of extant sequenced genomes. Using this approach, we compiled a database resource focused on the position-specific variation in protein stability. Interrogation of the database reveals: 1) domains of life exhibit distinguishing thermodynamic features, with eukaryotes particularly different from both archaea and bacteria; 2) the optimal growth temperature of an organism is proportional to the average apolar enthalpy of its proteome; 3) intrinsic disorder content is also proportional to the apolar enthalpy (but unexpectedly not the predicted stability at 25 °C); and 4) secondary structure and global stability information of individual proteins is extractable. We hypothesize that wider access to residue-specific thermodynamic information of proteomes will result in deeper understanding of mechanisms driving functional adaptation and protein evolution. Our database is free for download at https://afc-science.github.io/thermo-env-atlas/ (last accessed January 18, 2022). [ABSTRACT FROM AUTHOR]

The “Smart Cities” concepts have been adapted to several environments, to bring technology usage at infrastructure, planning, management, and people levels, in specific geographic space and time. UCM – University Campus Map [1] - is a smart campus initiative developed by Paraná Federal University, which provides geographic information – indoor and outdoor – applied to university campus usage. Data from UCM become an official university base map, considering several contexts of use and diverse necessities, from several actors. Also, the project supplies map interfaces that take into account navigational, querying, visualization, and interaction with all different environments from the University resources and facilities. [ABSTRACT FROM AUTHOR]

Over the years, a growing number of semantic data repositories have been made available on the web. However, this has created new challenges in exploiting these resources efficiently. Querying services require knowledge beyond the typical user's expertise, which is a critical issue in adopting semantic information solutions. Several proposals to overcome this difficulty have suggested using question answering (QA) systems to provide user‐friendly interfaces and allow natural language use. Because question answering over knowledge bases (KBQAs) is a very active research topic, a comprehensive view of the field is essential. The purpose of this study was to conduct a systematic review of methods and systems for KBQAs to identify their main advantages and limitations. The inclusion criteria rationale was English full‐text articles published since 2015 on methods and systems for KBQAs. Sixty‐six articles were reviewed to describe their underlying reference architectures. [ABSTRACT FROM AUTHOR]