julilili42/papers huggingface dataset:
MHCquant2 refines immunopeptidomics tumor antigen discovery
2024-12-04

<title>Abstract</title> The identification of human leukocyte antigen (HLA)-presented peptides as targets of anti-cancer T cell response is pivotal for the development of novel immunotherapies. Mass spectrometry (MS)-based immunopeptidomics enables the detection of these peptides, yet confident identifications and thus implementation in immunotherapy design are hampered by the high diversity and low abundance of naturally presented HLA peptides. Here, we introduce MHCquant2, a Nextflow-based open-source pipeline that leverages OpenMS tools and peptide property predictors (DeepLC, MS<sup>2</sup>PIP) for highly sensitive and scalable HLA peptide identification and quantification across various MS platforms. MHCquant2 increased peptide identifications up to 27% with a significant expansion of low-abundant peptides, outperforming state-of-the-art pipelines. Using MHCquant2 we build a comprehensive benign tissue repository comprising re-analyzed data from available benign immunopeptidomes and a novel benign<sub>MHCquant2</sub> dataset, adding more than 160,000 novel naturally presented HLA peptides. First applications of this benign repository and the MHCquant2 pipeline enabled (i) the refinement of tumor-associated antigens, (ii) the detection of novel, high-frequent tumor-exclusive peptide antigens for multiple tumor entities, and (iii) the identification and quantification of mutation-derived low-abundant neoepitopes. MHCquant2 refines tumor antigen discovery in immunopeptidomics, paving the way for the implementation of off-the-shelf and personalized immunotherapy design.
Energy preserving evolutions over Bosonic systems
2024-12-04

The exponential convergence to invariant subspaces of quantum Markov semigroups plays a crucial role in quantum information theory. One such example is in bosonic error correction schemes, where dissipation is used to drive states back to the code-space – an invariant subspace protected against certain types of errors. In this paper, we investigate perturbations of quantum dynamical semigroups that operate on continuous variable (CV) systems and admit an invariant subspace. First, we prove a generation theorem for quantum Markov semigroups on CV systems under the physical assumptions that (i) the generator is in GKSL form with corresponding jump operators defined as polynomials of annihilation and creation operators; and (ii) the (possibly unbounded) generator increases all moments in a controlled manner. Additionally, we show that the level sets of operators with bounded first moments are admissible subspaces of the evolution, providing the foundations for a perturbative analysis. Our results also extend to time-dependent semigroups and multi-mode systems. We apply our general framework to two settings of interest in continuous variable quantum information processing. First, we provide a new scheme for deriving continuity bounds on the energy-constrained capacities of Markovian perturbations of quantum dynamical semigroups. Second, we provide quantitative perturbation bounds for the steady state of the quantum Ornstein-Uhlenbeck semigroup and the invariant subspace of the photon dissipation used in bosonic error correction.
PCI-DB: A novel primary tissue immunopeptidome database to guide next-generation peptide-based immunotherapy development
2024-12-04

<title>Abstract</title> Various cancer immunotherapies rely on the T cell-mediated recognition of peptide antigens presented on human leukocyte antigens (HLA). However, the identification and selection of naturally presented peptide targets for the development of personalized as well as off-the-shelf immunotherapy approaches remains challenging. Here, we introduce the open-access Peptides for Cancer Immunotherapy Database (PCI-DB, https://pci-db.org/), a comprehensive resource of immunopeptidome data originating from various malignant and benign primary tissues that provides the research community with a convenient tool to facilitate the identification of peptide targets for immunotherapy development. The PCI-DB includes &gt; 6.6 million HLA class I and &gt; 3.4 million HLA class II peptides from over 40 tissue types and cancer entities analyzed uniformly using high-sensitive nf-core bioinformatics pipelines and applying a global peptide false discovery rate. First application of the database provided insights into the representation of cancer-testis antigens across malignant and benign tissues, enabling the identification and characterization of cross-tumor entity and entity-specific tumor-associated antigens as well as naturally presented neoepitopes from frequent cancer mutations. Further, we used the PCI-DB to design personalized peptide vaccines for two patients suffering from metastatic cancer. In a retrospective analysis, PCI-DB enabled the composition of both a multi-peptide vaccine comprising non-mutated, highly frequent tumor-associated antigens matching the immunopeptidome of the individual patient ́s tumor and a neoepitope-based vaccine matching the mutational profile of a cancer patient. Both vaccine approaches induced potent and long-lasting T-cell responses, accompanied by long-term survival of these advanced cancer patients. In conclusion, the PCI-DB provides a highly versatile tool to broaden the understanding of cancer-related antigen presentation and, ultimately, supports the development of novel immunotherapies.
Cranial ontogenetic development and sexual dimorphism of the extant water chevrotain Hyemoschus aquaticus
2024-12-04

Abstract Tragulids or mouse-deer live in tropical Asia and Africa. They are the sister group of Pecora and have a long fossil record dating back into the Eocene. The extant African species, Hyemoschus aquaticus , is the sister taxon of all other extant tragulids and is therefore often used for comparison with fossil mouse deer. However, although many fossil tragulid skulls were found and studied within the last years, no attempt has been made for a comprehensive and comparative study of the ontogenetic development of cranial sexual dimorphism of H. aquaticus . Based on 39 extant skulls we establish an ontogenetic categorization of this species, comprising nine stages of tooth wear. We show that (I) in H. aquaticus upper canine development remains the main character for distinction of male and female, (II) that the eruption of the permanent upper canines and the development of sagittal crests starts before sexual maturity after the eruption of the second upper molar, and (III) that the development of further cranial crests (nuchal crests, temporal lines) varies greatly within the same age class and among the sexes. Thus cranial ornamentation is not useful as a primary distinction feature between the sexes and of limited importance in identifying ontogenetic age. The newly established categories of wear stages and the observed sexual similarity in cranial crest development can be used in future comparative studies with the other extant mouse-deer and especially with their fossil representatives.
From the whole to its parts – A systematic analysis of affordances for learning part-whole-relations in digital apps
2024-12-04

Understanding part-whole relations is crucial in early mathematics education. However, both analogue and digital learning environments often lack systematic approaches to foster part-whole understanding. With the rising popularity of educational apps, it is essential to evaluate how they implement learning of part-whole relations. Accordingly, this review aims to evaluate whether educational math apps provide a systematic approach to learn part-whole relations. Therefore, we first developed a framework for evaluating apps with a focus on opportunities for learning part-whole relations. Second, we applied this framework to evaluate n =&lt;i&gt; &lt;/i&gt;18 apps. Results indicated that none of the reviewed apps implemented a systematic approach to learn part-whole relations from hands-on to more abstract compositions/decompositions including number triples up to ten. In contrast, the automating of number compositions/decompositions is most frequently targeted. These findings underscore the importance of selecting educational apps carefully and integrating principles from effective learning environments and digital learning research into future app design.
Diagnostic challenges of arboviral infections and dengue virus serotype distribution in febrile patients in East Java, Indonesia
2024-12-05

This study highlights the nature of the dengue outbreak in Jember in 2023, where all four DENV serotypes were in circulation, and underlines the need for serological or nucleic acid-based methods to improve arbovirus diagnosis in the region.
Genetic Diversity and Expanded Phenotypes in Dystonia: Insights from Large-Scale Exome Sequencing
2024-12-05

Abstract Dystonia is one of the most prevalent movement disorders, characterized by significant clinical and etiological heterogeneity. Despite considerable heritability (∼25%) and the identification of several disease-linked genes, the etiology in most patients remains elusive. Moreover, understanding the correlations between clinical manifestation and genetic variants has become increasingly complex. To comprehensively unravel dystonia’s genetic spectrum, we performed exome sequencing on 1,924 dystonia patients [40.3% male, 92.9% White, 93.2% isolated dystonia, median age at onset (AAO) 33 years], including 1,895 index patients, who were previously genetically unsolved. The sample was mainly based on two dystonia registries (DysTract and the Dystonia Coalition). Further, 72 additional patients of Asian ethnicity, mainly from Malaysia, were also included. We prioritized patients with negative genetic prescreening, early AAO, positive family history, and multisite involvement of dystonia. Rare variants in genes previously linked to dystonia ( n =405) were examined. Variants were confirmed via Sanger sequencing, and segregation analysis was performed when possible. We identified 137 distinct likely pathogenic or pathogenic variants (according to ACMG criteria) across 51 genes in 163/1,924 patients [42.9% male, 85.9% White, 68.7% isolated dystonia, median AAO 19 years]. This included 153/1,895 index patients, resulting in a diagnostic yield of 8.1%. Notably, 77/137 (56.2%) of these variants were novel, with recurrent variants in EIF2AK2 , VPS16 , KCNMA1 , and SLC2A1 , and novel variant types such as two splice site variants in KMT2B , supported by functional evidence. Additionally, 321 index patients (16.9%) harbored variants of uncertain significance in 102 genes. The most frequently implicated genes included VPS16 , THAP1 , GCH1 , SGCE , GNAL , and KMT2B. Presumably pathogenic variants in less well-established dystonia genes were also found, including KCNMA1 , KIF1A , and ZMYND11. At least six variants (in ADCY5 , GNB1 , IR2BPL, KCNN2 , KMT2B , and VPS16 ) occurred de novo, supporting pathogenicity. ROC curve analysis indicated that AAO and the presence of generalized dystonia were the strongest predictors of a genetic diagnosis, with diagnostic yields of 28.6% in patients with generalized dystonia and 20.4% in those with AAO &lt; 30 years. This study provides a comprehensive examination of the genetic landscape of dystonia, revealing valuable insights into the frequency of dystonia-linked genes and their associated phenotypes. It underscores the utility of exome sequencing in establishing diagnoses within this heterogeneous condition. Despite prescreening, presumably pathogenic variants were identified in almost 10% of patients. Our findings reaffirm several dystonia candidate genes and expand the phenotypic spectrum of some of these genes to include prominent, sometimes isolated dystonia.
UV Hyperspectral Imaging with Xenon and Deuterium Light Sources: Integrating PCA and Neural Networks for Analysis of Different Raw Cotton Types
2024-12-05

Ultraviolet (UV) hyperspectral imaging shows significant promise for the classification and quality assessment of raw cotton, a key material in the textile industry. This study evaluates the efficacy of UV hyperspectral imaging (225–408 nm) using two different light sources: xenon arc (XBO) and deuterium lamps, in comparison to NIR hyperspectral imaging. The aim is to determine which light source provides better differentiation between cotton types in UV hyperspectral imaging, as each interacts differently with the materials, potentially affecting imaging quality and classification accuracy. Principal component analysis (PCA) and Quadratic Discriminant Analysis (QDA) were employed to differentiate between various cotton types and hemp plant. PCA for the XBO illumination revealed that the first three principal components (PCs) accounted for 94.8% of the total variance: PC1 (78.4%) and PC2 (11.6%) clustered the samples into four main groups—hemp (HP), recycled cotton (RcC), and organic cotton (OC) from the other cotton samples—while PC3 (6%) further separated RcC. When using the deuterium light source, the first three PCs explained 89.4% of the variance, effectively distinguishing sample types such as HP, RcC, and OC from the remaining samples, with PC3 clearly separating RcC. When combining the PCA scores with QDA, the classification accuracy reached 76.1% for the XBO light source and 85.1% for the deuterium light source. Furthermore, a deep learning technique called a fully connected neural network for classification was applied. The classification accuracy for the XBO and deuterium light sources reached 83.6% and 90.1%, respectively. The results highlight the ability of this method to differentiate conventional and organic cotton, as well as hemp, and to identify distinct types of recycled cotton, suggesting varying recycling processes and possible common origins with raw cotton. These findings underscore the potential of UV hyperspectral imaging, coupled with chemometric models, as a powerful tool for enhancing cotton classification accuracy in the textile industry.
Deciphering the tight metabolite‐level regulation of glucose‐1‐phosphate adenylyltransferase (GlgC) for glycogen synthesis in cyanobacteria
2024-12-05

The enzyme glucose‐1‐phosphate adenylyltransferase (GlgC, EC:2.7.7.27) catalyses the first step in glycogen synthesis by converting glucose‐1‐phosphate into ADP‐glucose, which is added in turn to a growing glycogen chain by glycogen synthases. Thus far, in vitro studies of GlgC were mainly performed using colorimetric or radiolabel‐based phosphate release assays, limiting the option for analysing this reaction. With this work, we present a novel in vitro continuous assay coupling the subsequent glycogen synthase reaction to the GlgC reaction, thus simulating the process of glycogen synthesis in vivo . Using this assay, we revisited GlgC catalytic parameters and screened for metabolites that affect GlgC activity in Synechocystis sp. PCC 6803. We also describe in further detail the antagonistic interplay between the GlgC activator, 3‐PGA and the inhibitor, inorganic phosphate, revealing the intricate mechanism by which glycogen formation responds to fluctuations in carbon and energy supply in cyanobacteria.
Dona Flor and her two husbands: Discovery of novel HDAC6/AKT2 inhibitors for myeloid cancer treatment
2024-12-05

Abstract Hematological cancer treatment with hybrid kinase/HDAC inhibitors is a novel strategy to overcome the challenge of acquired resistance to drugs. We collected IC 50 datasets from the ChEMBL database for 13 cancer cell lines (72 h cytotoxicity, measured by MTT), known inhibitors for 38 kinases, and 10 HDACs isoforms, that we identified by target fishing and literature review. The data was subjected to rigorous biological and chemical curation leaving the final datasets ranging from 76 to 8173 compounds depending on the target. We generated Random Forest classification models, whereby 14 showed greater than 80% predictability after 5-fold external cross-validation. We screened 30 hybrid kinase/HDAC inhibitor analogs through each of these models. Fragment-contribution maps were constructed to aid the understanding of SARs and the optimization of these compounds as selective kinase/HDAC inhibitors for cancer treatment. Among the predicted compounds, 9 representative hybrids were synthesized and subjected to biological evaluation to validate the models. We observed high hit rates after biological testing for the following models: K562 (62.5%), MV4-11 (75.0%), MM1S (100%), NB-4 (62.5%), U937 (75.0), and HDAC6 (86.0%). This aided the identification of 6b and 6k as potent anticancer inhibitors with IC 50 of 0.2-0.8 μM in three cancer cell lines, linked to HDAC6 inhibition below 2 nM, and blockade of AKT2 phosphorylation at 2 μM, validating the ability of our models to predict novel drug candidates. Graphical Abstract Highlights Novel kinase/HDAC inhibitors for cancer treatment were found using machine learning 61 QSAR models for hematological cancers and its targets were built and validated K562, MV4-11, MM1S, NB-4, U937, and HDAC6 models had hit rates above 62.5% in tests 6b and 6k presented potent IC 50 of 0.2-0.8 μM in three cancer cell lines 6b and 6k inhibited HDAC6 below 2 nM, and blockade of AKT2 phosphorylation at 2 μM
A conserved cell-pole determinant organizes proper polar flagellum formation
2024-12-05

The coordination of cell cycle progression and flagellar synthesis is a complex process in motile bacteria. In γ-proteobacteria, the localization of the flagellum to the cell pole is mediated by the SRP-type GTPase FlhF. However, the mechanism of action of FlhF, and its relationship with the cell pole landmark protein HubP remain unclear. In this study, we discovered a novel protein called FipA that is required for normal FlhF activity and function in polar flagellar synthesis. We demonstrated that membrane-localized FipA interacts with FlhF and is required for normal flagellar synthesis in Vibrio parahaemolyticus , Pseudomonas putida , and Shewanella putrefaciens , and it does so independently of the polar localization mediated by HubP. FipA exhibits a dynamic localization pattern and is present at the designated pole before flagellar synthesis begins, suggesting its role in licensing flagellar formation. This discovery provides insight into a new pathway for regulating flagellum synthesis and coordinating cellular organization in bacteria that rely on polar flagellation and FlhF-dependent localization.
Cognitive Impairment in Cerebral Amyloid Angiopathy: A Single-Center Prospective Cohort Study
2024-12-06

Background/Objectives: Cognitive impairment represents a core and prodromal clinical feature of cerebral amyloid angiopathy (CAA). We sought to assess specific cognitive domains which are mainly affected among patients with CAA and to investigate probable associations with neuroimaging markers and Cerebrospinal Fluid (CSF) biomarkers. Methods: Thirty-five patients fulfilling the Boston Criteria v1.5 or v2.0 for the diagnosis of probable/possible CAA were enrolled in this prospective cohort study. Brain Magnetic Resonance Imaging and CSF biomarker data were collected. Every eligible participant underwent a comprehensive neurocognitive assessment. Spearman’s rank correlation tests were used to identify possible relationships between the Addenbrooke’s Cognitive Examination—Revised (ACE-R) sub-scores and other neurocognitive test scores and the CSF biomarker and neuroimaging parameters among CAA patients. Moreover, linear regression analyses were used to investigate the effects of CSF biomarkers on the ACE-R total score and Mini-Mental State Examination (MMSE) score, based on the outcomes of univariate analyses. Results: Cognitive impairment was detected in 80% of patients, and 60% had a coexistent Alzheimer’s disease (AD) pathology based on CSF biomarker profiles. Notable correlations were identified between increased levels of total tau (t-tau) and phosphorylated tau (p-tau) and diminished performance in terms of overall cognitive function, especially memory. In contrast, neuroimaging indicators, including lobar cerebral microbleeds and superficial siderosis, had no significant associations with cognitive scores. Among the CAA patients, those without AD had superior neurocognitive test performance, with significant differences observed in their ACE-R total scores and memory sub-scores. Conclusions: The significance of tauopathy in cognitive impairment associated with CAA may be greater than previously imagined, underscoring the necessity for additional exploration of the non-hemorrhagic facets of the disease and new neuroimaging markers.
Nitrous oxide is the main product during nitrate reduction by a novel lithoautotrophic iron(II)-oxidizing culture from an organic-rich paddy soil
2024-12-06

ABSTRACT Microbial nitrate reduction coupled to iron(II) oxidation (NRFeOx) occurs in paddy soils due to high levels of dissolved iron(II) and regular application of nitrogen fertilizer. However, to date, there is no lithoautotrophic NRFeOx isolate or enrichment culture available from this soil environment. Thus, resulting impacts on greenhouse gas emissions during nitrate reduction (i.e., nitrous oxide [N 2 O]) and on toxic metalloid (i.e., arsenic) mobility can hardly be investigated. We enriched a lithoautotrophic NRFeOx culture, culture HP (Huilongpu paddy, named after its origin), from a paddy soil (Huilongpu Town, China), which was dominated by Gallionella (71%). The culture reduced 0.45 to 0.63 mM nitrate and oxidized 1.76 to 2.31 mM iron(II) within 4 days leading to N 2 O as the main N-product (62%–88% N 2 O-N of total reduced NO 3 − -N). Nitrite was present as an intermediate at a maximum of 0.16 ± 0.1 mM. Cells were associated with, but mostly not encrusted by, poorly crystalline iron(III) minerals (ferrihydrite). Culture HP performed best below an iron(II) threshold of 2.5–3.5 mM and in a pH range of 6.50–7.05. In the presence of 100 μM arsenite, only 0%–18% of iron(II) was oxidized. Due to low iron(II) oxidation, arsenite was not immobilized. However, the proportion of N 2 O-N of total reduced NO 3 − -N decreased from 77% to 30%. Our results indicate that lithoautotrophic NRFeOx occurs even in organic-rich paddy soils, resulting in denitrification and subsequent N 2 O emissions. The obtained novel enrichment culture allows us to study the impact of lithoautotrophic NRFeOx on arsenic mobility and N 2 O emissions in paddy soils. IMPORTANCE Paddy soils are naturally rich in iron(II) and regularly experience nitrogen inputs due to fertilization. Nitrogen fertilization increases nitrous oxide emissions as it is an intermediate product during nitrate reduction. Microorganisms can live using nitrate and iron(II) as electron acceptor and donor, respectively, but mostly require an organic co-substrate. By contrast, microorganisms that only rely on nitrate, iron(II), and CO 2 could inhabit carbon-limited ecological niches. So far, no isolate or consortium of lithoautotrophic iron(II)-oxidizing, nitrate-reducing microorganisms has been obtained from paddy soil. Here, we describe a lithoautotrophic enrichment culture, dominated by a typical iron(II)-oxidizer ( Gallionella ), that oxidized iron(II) and reduced nitrate to nitrous oxide, negatively impacting greenhouse gas dynamics. High arsenic concentrations were toxic to the culture but decreased the proportion of nitrous oxide of the total reduced nitrate. Our results suggest that autotrophic nitrate reduction coupled with iron(II) oxidation is a relevant, previously overlooked process in paddy soils.