Distinct Regions Research Articles

SURG-08. THE CLEARPOINT ARRAY® FRAME: A NOVEL MRI COMPATIBLE SYSTEM THAT SUPPORTS NON-CRANIOTOMY, MULTI-TRAJECTORY (NCMT) STEREOTACTIC PROCEDURES

Abstract BACKGROUND With continued evolution in stereotactic techniques and an expanding armamentarium of therapeutic options, non-craniotomy stereotactic procedures in neuro-oncology are becoming increasingly complex, often requiring multi-trajectory approaches. Here we demonstrate that the ClearPoint SmartFrame Array®, a second-generation MRI-compatible stereotactic frame, supports such non-craniotomy, multi-trajectory (NCMT) stereotactic procedures. METHODS Through a case report, we previously established the feasibility of NCMT through the ClearPoint SmartFrame Array®. Here we prospectively followed the next ten consecutive patients who underwent such multi-trajectory procedures to establish procedural safety and clinical utility. RESULTS Ten patients underwent complex, multi-trajectory stereotactic procedures, including combinations of needle biopsy + cyst drainage and laser interstitial thermal therapy (LITT) targeting geographically distinct regions of neoplastic lesions under the same anesthetic event. For each intended target, the maximal radial error of stereotaxis ranged 0.1-2.7 mm (with a median of 1.0 mm). In all cases, definitive diagnosis was achieved, and >90% of the intended targets were ablated. The average stereotaxis time (time required to establish the trajectories) for the multi-trajectory procedure was 119 + 22.2 minutes, which is not statistically different from our published results for single-trajectory procedures (80 + 9.59 minutes, p = 0.125). There were no procedural complications. Post-procedure, the neurologic condition of one patient improved, while the remaining nine patients remained stable. All patients were discharged home, with a median hospital stay of one day (range: 1-12 days). With a median follow-up of 376 days (range: 155-1438 days), there were no 30-day readmission or wound complications. There were two 90-day readmissions (a patient with hydrocephalus and another with new spine metastasis) unrelated to the procedures performed. CONCLUSION Geographically distinct regions of a brain cancer can be safely and accurately accessed through the ClearPoint Array® frame in NCMT stereotactic procedures.

Exploring the known chemical space of the plant kingdom: insights into taxonomic patterns, knowledge gaps, and bioactive regions

Plants are one of the primary sources of natural products for drug development. However, despite centuries of research, only a limited region of the phytochemical space has been studied. To understand the scope of what is explored versus unexplored in the phytochemical space, we begin by reconstructing the known chemical space of the plant kingdom, mapping the distribution of secondary metabolites, chemical classes, and plants traditionally used for medicinal purposes (i.e., medicinal plants) across various levels of the taxonomy. We identify hotspot taxonomic clades occupied by a large proportion of medicinal plants and characterized secondary metabolites, as well as clades requiring further characterization with regard to their chemical composition. In a complementary analysis, we build a chemotaxonomy which has a high level of concordance with the taxonomy at the genus level, highlighting the close relationship between chemical profiles and evolutionary relationships within the plant kingdom. Next, we delve into regions of the phytochemical space with known bioactivity that have been used in modern drug discovery. While we find that the vast majority of approved drugs from phytochemicals are derived from known medicinal plants, we also show that medicinal and non-medicinal plants do not occupy distinct regions of the known phytochemical landscape and their phytochemicals exhibit properties similar to bioactive compounds. Moreover, we also reveal that only a few thousand phytochemicals have been screened for bioactivity and that there are hundreds of known bioactive compounds present in both medicinal and non-medicinal plants, suggesting that non-medicinal plants also have potential therapeutic applications. Overall, these results support the hypothesis that there are many plants with medicinal properties awaiting discovery.

Unveiling the role of hypoxic macrophage-derived exosomes in driving colorectal cancer progression.

The crosstalk between tumor cells and macrophages under hypoxic conditions has been acknowledged as a pivotal determinant in the progression of colorectal cancer (CRC). Previous research has underscored the significance of exosomes derived from hypoxic tumor cells in facilitating tumor progression through inducing the polarization of macrophages towards the M2-like phenotype. The precise influence of hypoxic macrophage-derived exosomes (HMDEs) on the progression of CRC has not yet been fully elucidated. The objective of this study was to investigate the role of HMDEs in the progression of CRC. We discovered that there was an elevated release of exosomes derived from macrophages in hypoxic conditions. Additionally, the hypoxia-induced macrophage-derived exosomes played a crucial role in promoting the progression of CRC. We have also demonstrated that HMDEs have the ability to induce cell cycle transition and inhibit cell apoptosis, thereby promoting the growth of CRC cells. Furthermore, the underlying molecular mechanisms of these effects have been identified. The overexpression of Hif-1α results in its direct interaction with distinct regions (-521- -516 bp and -401- -391 bp) of the Hsp90 promoter during hypoxic circumstances. This binding event led to the overexpression of Hsp90 and the subsequent elevation of Hsp90 protein levels within HMDEs. Importantly, the crucial interaction between Hsp90 and Lats1 resulted in the deactivation of Lats1 and the inhibition of Yap phosphorylation. Ultimately, this series of events lead to the deactivation of the Hippo signaling pathway. Our in vivo and in vitro studies presented compelling evidence for the crucial role of hypoxic macrophage-derived exosomal Hsp90 in promoting CRC progression through the inhibition of the Hippo signaling pathway. These findings represented a significant advancement in our comprehension of the complex interplay between macrophages and CRC cells under hypoxic conditions.

Unlocking the WHO's Age-Friendly Healthcare Principles: Portugal's Quest and Recommendations.

Countries worldwide are grappling with a pressing demographic challenge characterized by a growing older population. This poses a significant healthcare dilemma, presenting challenges for healthcare systems and providers. To address these challenges, the World Health Organization (WHO) has devised a set of Age-Friendly Principles, aimed at optimizing healthcare provision for older people. This article delves into the current state of healthcare adaptation for older adults in Portugal and assesses the implementation of the WHO Principles. Case studies were conducted in three distinct regions of Portugal, involving semistructured interviews with key decision makers from both the healthcare sector and organizations wielding direct influence over health policies (n = 11). A comprehensive content analysis was conducted employing the webQDA software. The findings unveiled a noteworthy trend in which most interviewees displayed limited familiarity with the WHO Principles. Nevertheless, all interviewees acknowledged the need to adapt the healthcare system accordingly. Strengths were identified, primarily within the healthcare management system, but noteworthy gaps were also revealed, particularly in terms of facility preparedness and professional training. Interviewees proposed various interventions to enhance age-friendly healthcare provision; however, they concurrently pinpointed challenges related to human resources, infrastructure, and financial management. In their concluding recommendations, interviewees underscored the development of tools to facilitate the application and evaluation of the WHO Principles, as well as the development by the WHO of an accreditation system to encourage the application of the principles in healthcare providers across the world.

AAV.Cas9 and AAV.SERCA2a strategies to mitigate heart failure in DMD pigs

Abstract Aims Duchenne muscular dystrophy is a devastating disease affecting skeletal muscle and heart, which is caused by loss-of-function mutations in the dystrophin (DMD) gene. Since pharmacologic treatment is ineffective over time, gene therapy including gene editing is rapidly evolving. In DMDdelta52 pigs, we have previously demonstrated efficacy of an AAV9-Cas9-gRNA approach, which by excision of exon 51 provided a shortened, but stable dystrophin D51-52. Here, we set out to compare this approach to germline excision of exon 51 in the DMDdelta52 pig, resulting in ubiquitous dystrophin D51-52 expression, a porcine model of Becker muscle dystrophy (BMD). Alternately, we provided locoregional AAV.SERCA2a gene therapy to the DMDdelta52 pigs. Methods and results We generated pigs lacking exon 52 of the DMD gene. Male offspring are characterized by heart failure (EF33±3%), arrhythmogenesis due to distinct regions of low or no-amplitude action potentials and by sudden cardiac death before 4 months of age. Germline correction of the loss of function mutation by additional excision of neighbouring exon 51 induced a Becker phenotype (BMD), with a mildly reduced ejection cardiac function (EF 45±3%) a reduction of vulnerable areas in electrophysiology mapping and a prolonged lifespan. Postnatal AAV9.Cas9-gE51 also improved EF (40±2%) and reduced electrophysiological vulnerability, increasing survival significantly. Using intracoronary delivery of AAV1.SERCA2a at a dose of 3x1013 virus genomes (vg) per pig by slow antegrade infusion of LAD & LCx improved left ventricular ejection fraction (EF 46±5% +AAV1.SERCA2a), but did not alter the amount of no-amplitude areas per LV. Conclusions Compared to ubiquitous excision of exon 51 (DMDdelta51-52) or postnatal AAV.Cas9-gE51 treatment of a DMDdelta52 pig model, which both improved ejection fraction EF and almost normalized action potential amplitudes, a moderate dose of AAV1.SERCA2a sufficed to normalize left ventricular function, but did not affect electrical vulnerability of the heart. Hence, AAV.SERCA2a combined with antitachycardic pacemaker protection may serve as a safe treatment option for DMD cardiomyopathy, whereas Cas9-mediated gene editing may provide additional therapy of electrical vulnerability. Further translational studies will establish novel gene therapeutic options for DMD patients.

Coupling RESI with Multi-Scenario LULC Simulation and Spatiotemporal Variability Analysis: An Ecological Spatial Constraint Approach

Southwest China’s arid river valleys represent ecologically vulnerable areas with intense human activity. Understanding the historical changes in LULC and land cover and projecting the impacts of various development scenarios on future LULC have become crucial for regional spatial information management and territorial spatial planning. This research analyzes the land-use changes in the Yuanmou dry-hot valley over a 30-year span from 1990 to 2020. Building upon the PLUS model, we established a coupled habitat quality spatial and multi-scenario land-use simulation model. Four development scenarios were proposed: natural progression, economic development, ecological conservation, and balanced development. We conducted simulations and evaluations of land-use in the Yuanmou dry-hot valley for 2030 using the PLUS mode, assessing the sustainability of future development scenarios under varying ecological constraints. During the simulation, three distinct RESI regions were employed as restricted development zones, integrating the three ecological constraints with the four simulation scenarios. We introduced a novel approach based on ecological environmental quality as the ecological constraint, providing a scientific reference for sustainable development in ecologically vulnerable areas. The results indicate that under ecological conservation scenarios with high-to-low RESI constraints, the ecological environment is superior to the other three scenarios. The results show the following: (1) From 1990 to 2020, aside from a continuous decrease in grassland area, there was an increasing trend in the areas of water bodies, forests, croplands, construction lands, and unused lands in the Yuanmou dry-hot valley. (2) By 2030, under all four development scenarios, the cropland area is expected to expand rapidly, while forested areas will decrease; grassland areas will decline under natural and economic development scenarios but show opposite trends under the other scenarios; and construction land and unused land areas will decrease under the ecological conservation and balanced development scenarios. (3) Land-use intensity analysis for the four scenarios indicated that, by 2030, unused lands in the Yuanmou dry-hot valley are more likely to be converted into water bodies, forests are more likely to be converted into croplands and grasslands, grasslands are more likely to be converted into croplands, croplands are more likely to be converted into grasslands, and construction lands are more likely to become unused lands. (4) Sustainable LULC management evaluations based on landscape indices reveal that ecological conservation and balanced development scenarios exhibit superior landscape connectivity and clustering. Thus, the balanced development scenario is the most appropriate LULC strategy for the Yuanmou dry-hot valley in the future. These findings provide scientific references for balancing ecological conservation and economic development in the arid river valleys of Southwest China.

Impact of Rare Structural Variant Events in Newly Diagnosed Multiple Myeloma.

Whole-genome sequencing (WGS) of patients with newly diagnosed multiple myeloma (NDMM) has shown recurrent structural variant (SV) involvement in distinct regions of the genome (i.e., hotspots) and causing recurrent copy-number alterations. Together with canonical immunoglobulin translocations, these SVs are recognized as "recurrent SVs." More than half of SVs were not involved in recurrent events. The significance of these "rare SVs" has not been previously examined. In this study, we utilize 752 WGS and 591 RNA sequencing data from patients with NDMM to determine the role of rare SVs in myeloma pathogenesis. Ninety-four percent of patients harbored at least one rare SV event. Rare SVs showed an SV class-specific enrichment within genes and superenhancers associated with outlier gene expression. Furthermore, known myeloma driver genes recurrently impacted by point mutations were dysregulated by rare SVs. Overall, we demonstrate the association of rare SVs with aberrant gene expression supporting a potential driver role in myeloma pathogenesis.

Brain network classification based on dynamic graph attention information bottleneck

Background and ObjectivesGraph neural networks (GNN) have demonstrated remarkable encoding capabilities in the context of brain network classification tasks. They excel at uncovering hidden static connections between brain states. However, brain network signals can be influenced by physiological traits and external variables during clinical detection, resulting in noisy brain graphs. Additionally, many existing algorithms for brain networks primarily focus on static topologies determined by threshold-based criteria, thereby overlooking the real-time variability in brain channel connectivity. These sources of noise and the persistence of static structures inevitably hinder the effective exchange of information during brain network computations. MethodsTo address these challenges, we propose a novel framework called the dynamic graph attention information bottleneck (DGAIB). This framework is designed to dynamically enhance the input raw brain graph structure from the perspective of information theory and graph theory. First, we employ the Spearman function to construct a raw graph. Then, we use a graph information bottleneck (GIB) to optimize the internal graph connections by selectively masking redundant feature embeddings. Finally, we enhance the feature aggregation of each brain state by utilizing a graph attention network (GAT), which promotes improved information exchange among distinct brain regions within the model. These processed representations serve as input for subsequent classification tasks. Experiment and ResultsWe systematically evaluated the robustness and generalizability of our proposed framework through a series of experiments. This evaluation included patient-specific experiments using the electroencephalography (EEG)-based CHB-MIT dataset and cross-patient experiments leveraging the functional magnetic resonance imaging (fMRI)-based ABIDE-I dataset from multiple perspectives.

Assessing the Role of Post-Translational Modifications of Mitochondrial RNA Polymerase.

The mitochondrial proteome is subject to abundant post-translational modifications, including lysine acetylation and phosphorylation of serine, threonine, and tyrosine. The biological function of the majority of these protein modifications is unknown. Proteins required for the transcription and translation of mitochondrial DNA (mtDNA) are subject to modification. This suggests that reversible post-translational modifications may serve as a regulatory mechanism for mitochondrial gene transcription, akin to mechanisms controlling nuclear gene expression. We set out to determine whether acetylation or phosphorylation controls the function of mitochondrial RNA polymerase (POLRMT). Mass spectrometry was used to identify post-translational modifications on POLRMT. We analyzed three POLRMT modification sites (lysine 402, threonine 315, threonine 993) found in distinct structural regions. Amino acid point mutants that mimic the modified and unmodified forms of POLRMT were employed to measure the effect of acetylation or phosphorylation on the promoter binding ability of POLRMT in vitro. We found a slight decrease in binding affinity for the phosphomimic at threonine 315. We did not identify large changes in viability, mtDNA content, or mitochondrial transcript level upon overexpression of POLRMT modification mimics in HeLa cells. Our results suggest minimal biological impact of the POLRMT post-translational modifications studied in our system.

Sharpening the A → Z(*)h signature of the Type-II 2HDM at the LHC through advanced Machine Learning

The A → Z(*)h decay signature has been highlighted as possibly being the first testable probe of the Standard Model (SM) Higgs boson discovered in 2012 (h) interacting with Higgs companion states, such as those existing in a 2-Higgs Doublet Model (2HDM), chiefly, a CP-odd one (A). The production mechanism of the latter at the Large Hadron Collider (LHC) takes place via bb¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ b\\overline{b} $$\\end{document}-annihilation and/or gg-fusion, depending on the 2HDM parameters, in turn dictated by the Yukawa structure of this Beyond the SM (BSM) scenario. Among the possible incarnations of the 2HDM, we test here the so-called Type-II, for a twofold reason. On the one hand, it intriguingly offers two very distinct parameter regions compliant with the SM-like Higgs measurements, i.e., where the so-called ‘SM limit’ of the 2HDM can be achieved. On the other hand, in both configurations, the AZh coupling is generally small, hence the signal is strongly polluted by backgrounds, so that the exploitation of Machine Learning (ML) techniques becomes extremely useful. In this paper, we show that the application of advanced ML implementations can be decisive in establishing such a signal. This is true for all distinctive kinematical configurations involving the A → Z(*)h decay, i.e., below threshold (mA < mZ + mh), at its maximum (mZ + mh < mA < 2mt) and near the onset of tt¯\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ t\\overline{t} $$\\end{document} pair production (mA ≈ 2mt), for which we propose Benchmark Points (BPs) for future phenomenological analyses.

Iron overload in hemodialysis patients: Comparison of serum iron parameters with T2* MRI sequence.

To evaluate correlation between serum iron parameters and liver T2* value in hemodialysis patients with iron overload due to parenteral iron therapy. We evaluated 30 hemodialysis patients using a multiecho T2*-weighted MRI sequence. Age, sex, duration of dialysis, iron and erythropoietin doses taken in the past year, and serum iron parameters were recorded. Liver T2* values were averaged from three distinct liver regions. A T2* value of 33 ± 7 ms is considered normal. Declines below 24, 21, and 14 ms signify iron overload grades 1, 2, and 3, respectively. There was no statistically significant difference comparing the measurements of 3 different ROIs (p > 0.05). A total of 23 patients (76.6%) had iron overload. Serum ferritin levels of patients with iron overload were significantly higher than those without iron overload (687.25 [186.5-1489] ng/mL vs. 371.25 [127.5-542.5] ng/mL, p = 0.008). No linear correlation was observed between age, dialysis duration, serum iron metrics, medication doses, and T2* values. Likewise, no significant differences were found among patients based on iron overload status or its grades concerning these parameters. While standard serum markers might overlook iron overload, elevated ferritin levels are promising. MRI reliably detects iron overload in patients receiving parenteral iron.

Challenges and Strategies of Western Football Coaches in the Glocalized Context of Chinese Youth Football: An Exploration of Cross-Cultural Competence

In the rapidly globalizing world of football, China's youth football landscape presents unique challenges for Western coaches trying to integrate their techniques. This research delves deep into the intersection of Western football coaching methodologies and China's intricate cultural and athletic fabric. Utilizing a qualitative research paradigm, focus group discussions, and in-depth interviews, the study highlights profound barriers, encompassing not just language but also deeper cultural, epistemological, and training philosophical differences. Beyond merely identifying challenges, the research underscores the importance of strategies like cultural immersion, active participation in local events, and collaborative workshops. These strategies not only bridge the technical and linguistic gaps but also foster mutual respect, shared learning, and deeper integration. This study, while rooted in China's context, contributes to the broader discourse on sports globalization, emphasizing the necessity for coaches to be globally aware yet locally sensitive. It culminates in providing both rich theoretical insights and actionable recommendations for crafting a harmonized, effective cross-cultural coaching paradigm in China and other culturally distinct regions.

Hexagonal image segmentation on spatially resolved transcriptomics

Spatial transcriptomics is a rapidly evolving field that enables researchers to capture comprehensive molecular profiles while preserving information about the physical locations. One major challenge in this research area involves the identification of spatial domains, which are distinct regions characterized by unique gene expression patterns. However, current unsupervised methods have struggled to perform well in this regard due to the presence of high levels of noise and dropout events in spatial transcriptomic profiles. In this paper, we propose a novel hexagonal Convolutional Neural Network (hexCNN) for hexagonal image segmentation on spatially resolved transcriptomics. To address the problem of noise and dropout occurrences within spatial transcriptomics data, we first extend an unsupervised algorithm to a supervised learning method that can identify useful features and reduce noise hindrance. Then, inspired by the classical convolution in convolutional neural networks (CNNs), we designed a regular hexagonal convolution to compensate for the missing gene expression patterns from adjacent spots. We evaluated the performance of hexCNN by applying it to the DLPFC dataset. The results show that hexCNN achieves a classification accuracy of 86.8% and an average Rand index (ARI) of 77.1% (1.4% and 2.5% higher than those of GNNs). The results also demonstrate that hexCNN is capable of removing the noise caused by batch effect while preserving the biological signal differences.

Freshwater eDNA reveals dramatic biological shifts linked to deforestation of New Zealand

Deforestation is considered a major threat to biodiversity across many parts of the globe, but the biological impacts of this dramatic ecosystem disturbance often remain incompletely understood. In New Zealand – the world's last major landmass to be colonised by humans – widespread deforestation over recent centuries has left a highly fragmented suite of relict forest stands, ideal for assessing anthropogenic biological change. We hypothesise that this widespread environmental disturbance has underpinned repeated and predictable ecological shifts across distinct rivers and regions. Here we use freshwater environmental DNA (eDNA) data (113 samples across 38 locations; 89 insect taxa) to test for concordant biological shifts linked to this deforestation. eDNA analyses highlight consistent compositional and functional differentiation between forested versus deforested assemblages, including turnover of ‘cryptic’ congeneric taxa that are morphologically similar yet ecologically and genetically distinct. These dramatic biological shifts are evident even over fine spatial scales within streams, emphasising the widespread emergence of a novel ‘deforested’ assemblage. Our results illustrate that environmental change can drive predictable biological shifts across broad geographic regions, and highlight the power of eDNA for assessing anthropogenic ecosystem change over large geographic scales.

Transmission electron microscopy of the rapid solidification microstructure evolution and solidification interface velocity determination in hypereutectic Al-20at.%Cu after laser melting

The evolution of rapid solidification (RS) microstructure and solidification interface velocity has been studied experimentally by in-situ transmission electron microscopy and postmortem characterization for hypereutectic Al-20at.%Cu (37 wt.%Cu) after laser melting. Four morphologically distinct regions formed via growth modes changing from θ-Al2Cu phase dendrites to eutectic cell growth, possibly α-Al dendrite growth (α-cell), banded growth, and α-Al plane front growth. Tendency for faceting and low capacity for solute trapping limited the θ-phase dendrite growth to solidification interface velocity v < 0.07 m/s. Consequently, formation of pro-eutectic micro-constituent was suppressed, and RS microstructure formation was dominated by eutectic, α-cell, and banded morphology grains for the Al-20at.%Cu alloy. Eutectic growth operated for interface velocity of 0.1 m/s ≤ v < 0.3 m/s, with a transition from regular lamellar, 2-λ and 1-λ mode to a dense irregular morphology dominated by α-phase at v = 0.3 m/s. Interface temperature calculations indicated feasibility of α-cell growth mode for 0.3 m/s ≤ v < 0.7 m/s. Banded growth occurred for 0.7 m/s ≤ v < 1.3 m/s. Plane front α-phase growth was evident for interface velocities v ≥ 1.3 m/s. Previous work on rapid solidification microstructure development in hypereutectic Al-Cu alloys reported a regime of α-cell growth subsequently to eutectic and prior to transition to banded growth for Al-19at.%Cu (36 wt.%Cu), while for Al-22at.%Cu (40 wt.%Cu) eutectic growth transitioned directly to α-plane front growth without emergence of a banded regime. Based on the current study the disappearance of the banded growth regime occurs for a composition larger than 20at.%Cu.

Antibody-mediated SARS-CoV-2 entry in cultured cells.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters host cells by first engaging its cellular receptor angiotensin converting enzyme 2 (ACE2) to induce conformational changes in the virus-encoded spike protein and fusion between the viral and target cell membranes. Here, we report that certain monoclonal neutralizing antibodies against distinct epitopic regions of the receptor-binding domain of the spike can replace ACE2 to serve as a receptor and efficiently support membrane fusion and viral infectivity in vitro. These receptor-like antibodies can function in the form of a complex of their soluble immunoglobulin G with Fc-gamma receptor I, a chimera of their antigen-binding fragment with the transmembrane domain of ACE2 or a membrane-bound B cell receptor, indicating that ACE2 and its specific interaction with the spike protein are dispensable for SARS-CoV-2 entry. These results suggest that antibody responses against SARS-CoV-2 may help expand the viral tropism to otherwise nonpermissive cell types with potential implications for viral transmission and pathogenesis.

A region-resolved proteomic map of the human brain enabled by high-throughput proteomics.

Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de).

Quantitatively sensitive and resolution-enhancing strategies in optical signal conversion of SPR images using extensive angle-scanning and image-reconstruction

Surface plasmon resonance imaging (SPRi) is a technology developed from SPR that has emerged in response to the growing need for high-throughput and for discovering diverse applications across multiple domains. Despite its potential, SPRi has encountered limitations in sensitivity when handling low-molecular-mass materials, which emphasizes the need for the quantitative processing of SPRi signals. In this study, an SPRi signal conversion process was developed to enhance the contrast of SPR images and convert them into quantitatively analyzed signals. At first, an optimum incident angle of light was determined as an angle that maximized the difference between sums of the brightness % of functionalized regions and the brightness % of background region in the SPR image, which enabled to obtain a distinct SPR image. In addition, the enhancement of contrast and reduction of noise in the SPR image was achieved using Contrast Limited Adaptive Histogram Equalization (CLAHE) method. Then various pixel domains of the SPR images were simultaneously quantified and visualized the multi-pixel processing technique. For validating the process, an SiO2/Au thin film was modified with four different functionalities and applied to the detection of gas molecules. The SPR images processed using the proposed process exhibited sensitive and quantitative information about the interactions of the functionalities with the target gas in the distinct multiple regions, thus, were applicable to the quantitative monitoring of various phenomena occurring on the plasmonic interface via the advantages of SPRi.

AML with t(4;12)(q12;p13): A Detailed Genomic and Transcriptomic Analysis Reveals Genomic Breakpoint Heterogeneity, Absence of Pdgfra Fusion Transcripts and Presence of Pdgfra Overexpression in a Subset of Cases

Background: Gene fusions are a frequent event in acute myeloid leukaemia (AML). It is estimated that about 40% of AML patients harbour a cytogenetic abnormality resulting in a gene fusion. However, AML with t(4;12)(q12;p13) is very rare, but it is often accompanied by an aggressive clinical course and a poor prognosis. As frequently indicated by fluorescence in situ hybridization analyses (FISH), patients are assumed to harbor an ETV6::PDGFRA fusion, which impacts the choice of therapy, as these patients can be treated with tyrosine kinase inhibitors. The genomic region on chromosome 4 involved in ETV6 rearrangements is densly packed with genes in close spatial proximity. Therefore, the resolution of chromosome banding analysis and also FISH is not sufficient to fully elucidate the fusion partners involved. Recent studies have pointed out that many of these patients do not harbor an ETV6::PDGFRA fusion but other rather unknown fusion partners have been elucidated. Aim: (1) Evaluation of the genomic breakpoints in patients with t(4;12)(q12;p13) ETV6-rearranged AML; (2) determine the alteration of PDGFRA expression in patients with t(4;12). Patients and Methods: 10 patients (F: 4, M: 6; median age: 63 [44-82] years) with a t(4;12)(q12;p13) indicated by FISH and chromosome analysis were included. Samples were analysed by whole genome and whole transcriptome sequencing (WGS/WTS). Sequencing was performed on NovaSeq instrument (Illumina). Fusions were called with Arriba, STAR-Fusion and Manta. For gene expression analysis WTS data were log2 transformed and normalized with the trimmed mean of M-values (TMM) method. Results: Based on chromosome analysis and FISH patients showed break events in 4q12 and 12p13. In all cases a FISH signal constellation typical for an ETV6 rearrangement was observed. The mutation spectrum for each patient of the most commonly mutated genes in AML was examined by use of WGS data. The median number of mutations was 3, with mutations in ASXL1 being the most common (6 patients) and none of the patients featuring mutations in the PDGFRA gene. WTS analysis revealed in-frame fusions in 6 of 10 patients involving genes located on chromosomes 4 and 12 (4 patients with ETV6::CHIC2, 1 patients with ETV6::SCFD2, 1 patient with ETV6::ADAMTS3). None of the 10 examined patients showed a gene fusion, or a fusion transcript involving PDGFRA. Based on WTS data, 7 of the 10 patients showed a PDGFRA overexpression. WGS breakpoint analysis showed that genetic breakpoints on chromosome 12 cluster in introns 1 (4 patients) and 2 (6 patients) of the ETV6 gene. In contrast chromosome breaks on chromosome 4 are heterogeneously distributed in the 4q12 region. Breakpoint comparison indicated that patients with chromosome breaks in a range from chr4:54,804,230-54,962,206 (7 patients) display PDGFRA overexpression. In contrast patients with chromosome breaks further downstream chr4:55,021,511-73,409,362 (3 patients) did not exhibit an increased PDGFRA expression. This suggests an ectopic expression of PDGFRA triggered by the translocation and independent of the existence of an in-frame fusion transcript. A chromosome break in the range of chr4:54,804,230-54,962,206 (seen in 7 patients) might result in the inactivation of a CTCF binding site (chr4:54,796,345-54,796,360) upstream of these chromosome breaks that is already known to induce PDGFRA overexpression when disrupted. Conclusions: Analysis of AML with t(4;12)(q12;p13) translocation by WGS and WTS provides detailed information that separates two subsets distinguished by distinct breakpoint cluster regions on 4q12 and PDGFRA gene expression. The clinical impact of increased PDGFRA gene expression on response to TKI and prognosis as well as the presence of additional fusion transcripts has to be evaluated in further studies.

ANN-based ground motion model for Turkey using stochastic simulation of earthquakes

SUMMARY Turkey is characterized by a high level of seismic activity attributed to its complex tectonic structure. The country has a dense network to record earthquake ground motions; however, to study previous earthquakes and to account for potential future ones, ground motion simulations are required. Ground motion simulation techniques offer an alternative means of generating region-specific time-series data for locations with limited seismic networks or regions with seismic data gaps, facilitating the study of potential catastrophic earthquakes. In this research, a local ground motion model (GMM) for Turkey is developed using region-specific simulated records, thus constructing a homogeneous data set. The simulations employ the stochastic finite-fault approach and utilize validated input-model parameters in distinct regions, namely Afyon, Erzincan, Duzce, Istanbul and Van. To overcome the limitations of linear regression-based models, artificial neural network is used to establish the form of equations and coefficients. The predictive input parameters encompass fault mechanism (FM), focal depth (FD), moment magnitude (Mw), Joyner and Boore distance (RJB) and average shear wave velocity in the top 30 m (Vs30). The data set comprises 7359 records with Mw ranging between 5.0 and 7.5 and RJB ranging from 0 to 272 km. The results are presented in terms of spectral ordinates within the period range of 0.03–2.0 s, as well as peak ground acceleration and peak ground velocity. The quantification of the GMM uncertainty is achieved through the analysis of residuals, enabling insights into inter- and intra-event uncertainties. The simulation results and the effectiveness of the model are verified by comparing the predicted values of ground motion parameters with the observed values recorded during previous events in the region. The results demonstrate the efficacy of the proposed model in simulating physical phenomena.