Heterogeneous Complex Research Articles

Bacterial single-cell RNA sequencing captures biofilm transcriptional heterogeneity and differential responses to immune pressure.

Biofilm formation is an important mechanism of survival and persistence for many bacterial pathogens. These multicellular communities contain subpopulations of cells that display vast metabolic and transcriptional diversity along with high recalcitrance to antibiotics and host immune defenses. Investigating the complex heterogeneity within biofilm has been hindered by the lack of a sensitive and high-throughput method to assess stochastic transcriptional activity and regulation between bacterial subpopulations, which requires single-cell resolution. We have developed an optimized bacterial single-cell RNA sequencing method, BaSSSh-seq, to study Staphylococcus aureus diversity during biofilm growth and transcriptional adaptations following immune cell exposure. We validated the ability of BaSSSh-seq to capture extensive transcriptional heterogeneity during biofilm compared to planktonic growth. Application of new computational tools revealed transcriptional regulatory networks across the heterogeneous biofilm subpopulations and identification of gene sets that were associated with a trajectory from planktonic to biofilm growth. BaSSSh-seq also detected alterations in biofilm metabolism, stress response, and virulence that were tailored to distinct immune cell populations. This work provides an innovative platform to explore biofilm dynamics at single-cell resolution, unlocking the potential for identifying biofilm adaptations to environmental signals and immune pressure.

The Impact of Neoadjuvant Chemotherapy on Ovarian Cancer Tumor Microenvironment: A Systematic Review of the Literature.

Immunotherapy, particularly the use of immune checkpoint inhibitors (ICIs), has shown limited efficacy in treating ovarian cancer (OC), possibly due to diverse T cell infiltration patterns in the tumor microenvironment. This review explores how neoadjuvant chemotherapy (NACT) impacts the immune landscape of OC, focusing on tumor-infiltrating lymphocytes (TILs), PD-1/PD-L1 expression, and their clinical implications. A comprehensive literature search across four databases yielded nine relevant studies. These studies evaluated stromal (sTILs) and intra-epithelial (ieTILs) TILs before and after NACT. sTIL responses varied, impacting prognostic outcomes, and ieTILs increased in some patients without clear survival associations. PD-L1 expression after NACT correlated with improved overall survival (OS), and increases in granzyme B+ and PD-1 correlated with longer progression-free survival (PFS). Remarkably, reduced FoxP3+ TILs post-NACT correlated with better prognosis. NACT often increases sTIL/ieTIL and CD8+ subpopulations, but their correlation with improved PFS and OS varies. Upregulation of co-inhibitory molecules, notably PD-L1, suggests an immunosuppressive response to chemotherapy. Ongoing trials exploring neoadjuvant ICIs and chemotherapy offer promise for advancing OC treatment. Standardized measurements assessing TIL density, location, and heterogeneity are crucial for addressing genetic complexity and immunological heterogeneity in OC.

Graphene oxide-supported molybdenum complex as catalyst for peroxidase and catechol oxidase-like reactions

In this study, we synthesized a molybdenum complex, [MoO2(L)(H2O)] (1), utilizing a Schiff base ligand H2L (I), which was formed by reacting 3,5-di-tert-butyl-2-hydroxybenzaldehyde with the mono hydrazide of terephthalic ester in a methanolic solution. This complex was subsequently immobilized on a functionalized graphene oxide surface (APTES@GO), prepared using 3-aminopropyltriethoxysilane (APTES) and graphene oxide (GO), yielding the supported complex [MoO2(L)(H2O)]@APTES@GO (2). Both complexes were characterized through various analytical techniques, with single-crystal X-ray diffraction (SC-XRD) being specifically employed for complex 1. The catalytic activities of the homogeneous and heterogeneous complexes were assessed for their peroxidase-like and catechol oxidase-like functions, particularly in the oxidation of 3,3′-diaminobenzidine (DAB) and 3,5-di-tert-butylcatechol (3,5-DTBC) in the presence of hydrogen peroxide. Both complexes exhibited excellent catalytic efficiency (Kcat) and substrate binding affinity (KM), comparable to natural enzymes. Additionally, the supported complex demonstrated good reusability, maintaining its catalytic activity over five consecutive cycles.

Single cell RNA-sequencing in uveal melanoma: advances in heterogeneity, tumor microenvironment and immunotherapy.

Uveal melanoma (UM) is a highly aggressive and fatal tumor in the eye, and due the special biology of UM, immunotherapy showed little effect in UM patients. To improve the efficacy of immunotherapy for UM patients is of great clinical importance. Single-cell RNA sequencing(scRNA-seq) provides a critical perspective for deciphering the complexity of intratumor heterogeneity and tumor microenvironment(TME). Combing the bioinformatics analysis, scRNA-seq could help to find prognosis-related molecular indicators, develop new therapeutic targets especially for immunotherapy, and finally to guide the clinical treatment options.

Abstract PO-020: ZBTB24 is a novel tumor suppressor and cooperates with CDKN2A to suppress B-cell lymphomagenesis

Abstract B-cell lymphoma is the most common hematological malignancy that accounts for the sixth highest mortality among all cancers. Despite recent improvements on combined chemotherapy and immunotherapy, treatments remain challenging due to complex genetic heterogeneity and molecular pathogenesis. To explore novel mechanisms in B-cell lymphomagenesis, we performed a genome-wide CRISPR knockout screen in the murine interleukin-3 (IL-3)-dependent Ba/F3 pro-B cell line and identified Zbtb24 as a putative target whose silencing leads to elevated proliferative signaling and reduced apoptosis, conferring IL-3-independent growth in Ba/F3 cells. Silencing of ZBTB24 also accelerated growth in multiple human B-cell lymphoma cell lines. ZBTB24 is a member of the zinc-finger and BTB domain containing transcription factor that is highly expressed in spleen and bone marrow. While it has been shown that ZBTB24 may play an important role in B-cell development and activation, its involvement in B-cell lymphoma has not been described. Analysis of publicly available datasets found that ZBTB24 copy number deletion occurs in various B-cell lymphomas, which frequently co-occurs with deletion of the tumor suppressor CDKN2A. Hence, we generated B-cell specific Zbtb24 single knockout and Zbtb24/Cdkn2a double knockout mice to explore the role of Zbtb24 in vivo. While Zbtb24 and Cdkn2a single knockout mice remained tumor-free or showed low penetrance of tumorigenesis, the double knockout mice developed lymphadenopathy and splenomegaly accompanied with accelerated mortality. Flow cytometry analysis of bone marrow, spleen, and lymph nodes revealed malignant B-cells. Subsequent transplantation of the splenic cells induced identical malignant B-cell lymphomagenesis and immunophenotype in athymic nude mice, further confirming its malignant identity. These results indicate that ZBTB24 is a novel tumor suppressor in B-cell malignancy. Ongoing studies are being conducted to understand the mechanistic basis for ZBTB24 tumor suppressive function that may involve transcriptional regulation of its target gene expression. This project is supported by the NIH R01CA232246, R01CA129536, and the John Colaizzi Endowment Fund. Citation Format: Rongrong Li, Namratha Sheshadri, Jianliang Shen, Junrong Yan, Jaeyong Jung, Muhammad Usama Tariq, Y Lynn Wang, Ping Xie, Wei-Xing Zong. ZBTB24 is a novel tumor suppressor and cooperates with CDKN2A to suppress B-cell lymphomagenesis [abstract]. In: Proceedings of the Fourth AACR International Meeting on Advances in Malignant Lymphoma: Maximizing the Basic-Translational Interface for Clinical Application; 2024 Jun 19-22; Philadelphia, PA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(3_Suppl):Abstract nr PO-020.

LMNA -Related Dilated Cardiomyopathy: Single-Cell Transcriptomics during Patient-derived iPSC Differentiation Support Cell type and Lineage-specific Dysregulation of Gene Expression and Development for Cardiomyocytes and Epicardium-Derived Cells with Lamin A/C Haploinsufficiency.

LMNA -Related Dilated Cardiomyopathy (DCM) is an autosomal-dominant genetic condition with cardiomyocyte and conduction system dysfunction often resulting in heart failure or sudden death. The condition is caused by mutation in the Lamin A/C ( LMNA ) gene encoding Type-A nuclear lamin proteins involved in nuclear integrity, epigenetic regulation of gene expression, and differentiation. Molecular mechanisms of disease are not completely understood, and there are no definitive treatments to reverse progression or prevent mortality. We investigated possible mechanisms of LMNA -Related DCM using induced pluripotent stem cells derived from a family with a heterozygous LMNA c.357-2A>G splice-site mutation. We differentiated one LMNA mutant iPSC line derived from an affected female (Patient) and two non-mutant iPSC lines derived from her unaffected sister (Control) and conducted single-cell RNA sequencing for 12 samples (4 Patient and 8 Control) across seven time points: Day 0, 2, 4, 9, 16, 19, and 30. Our bioinformatics workflow identified 125,554 cells in raw data and 110,521 (88%) high-quality cells in sequentially processed data. Unsupervised clustering, cell annotation, and trajectory inference found complex heterogeneity: ten main cell types; many possible subtypes; and lineage bifurcation for Cardiac Progenitors to Cardiomyocytes (CM) and Epicardium-Derived Cells (EPDC). Data integration and comparative analyses of Patient and Control cells found cell type and lineage differentially expressed genes (DEG) with enrichment to support pathway dysregulation. Top DEG and enriched pathways included: 10 ZNF genes and RNA polymerase II transcription in Pluripotent cells (PP); BMP4 and TGF Beta/BMP signaling, sarcomere gene subsets and cardiogenesis, CDH2 and EMT in CM; LMNA and epigenetic regulation and DDIT4 and mTORC1 signaling in EPDC. Top DEG also included: XIST and other X-linked genes, six imprinted genes: SNRPN , PWAR6 , NDN , PEG10 , MEG3 , MEG8 , and enriched gene sets in metabolism, proliferation, and homeostasis. We confirmed Lamin A/C haploinsufficiency by allelic expression and Western blot. Our complex Patient-derived iPSC model for Lamin A/C haploinsufficiency in PP, CM, and EPDC provided support for dysregulation of genes and pathways, many previously associated with Lamin A/C defects, such as epigenetic gene expression, signaling, and differentiation. Our findings support disruption of epigenomic developmental programs as proposed in other LMNA disease models. We recognized other factors influencing epigenetics and differentiation; thus, our approach needs improvement to further investigate this mechanism in an iPSC-derived model.

Accentuating the Reservoir Potentials of Balkassar Field by Delineating the Fracture Trends and Hydrocarbon Prospects with the Aid of Seismic Attributes.

Carbonates constitute a significant proportion of the world's hydrocarbon reserves, accounting for approximately 43%. Despite their substantial potential, accurately characterizing these reserves is a challenging task due to their complex and anisotropic nature. In the upper Indus basin of Pakistan, Eocene carbonates exhibit strong production capabilities. However, the Eocene reservoir (comprising the Chorgali and Sakesar formations) and the deeper Lockhart formation of the Paleocene age present a considerable challenge. The Chorgali formation is dolomitic in composition, featuring both primary and secondary porosity, while the Sakesar formation has only secondary porosity resulting from tectonic activity. The delineation of tectonically induced porosities is a highly demanding task that requires exceptional quality seismic and well data for reliable results. To address the complex heterogeneities present in the Eocene reservoir of the upper Indus basin, a variety of seismic attributes, such as sweetness, instantaneous frequency, amplitude, curvature, similarity variance, lateral continuity, and fault likelihood, have been employed in conjunction with fundamental interpreting techniques. These advanced seismic attributes greatly contribute to delineating fracture zones and identifying sweet spots with remarkable precision. They also enable a focus on high-frequency data content and differentiate between shale beds and reservoir zones based on frequency and amplitude. This helps in the concise marking of fractured zones to enhance our understanding of secondary porosity. Moreover, these attributes help delineate the continuity of reflectors and pinpoint disruptions caused by compression forces and tectonic activities. This study aims to capture the heterogeneity and complexity of reservoir zones to address a critical question regarding the Balkassar structure. The Western lobe of the field, which demonstrates promising oil production, outperforms the structurally higher Eastern part, which lags behind in production. This research seeks to recognize the geological elements contributing to the superior performance of the Western lobe and provide guidance for maximizing the potential of the Eastern lobe through advanced characterization techniques.

Abstract PR007: Delineating functional drivers of esophageal adenocarcinoma to identify synthetic lethal interactions

Abstract Application of molecular targeted therapies for esophageal adenocarcinoma (EAC) has been limited by a lack of druggable oncogenic drivers. We propose that synthetic lethal interactions may provide new opportunities for targeted therapies in EAC. We have taken an integrated multi-omics approach incorporating Perturb-Seq (CRISPR editing combined with single cell RNA sequencing) and in vivo tumorigenesis assays to perform high-throughput characterisation of >70 high-confidence EAC driver genes, and genome-wide CRISPR-Cas9 knockout screens in isogenic models of EAC tumorigenesis to identify disease relevant synthetic lethal genetic interactions. MS-based proteomics, reverse phase protein arrays, polysome profiling and bulk RNA-sequencing of isogenic models were utilised to interrogate the biology of bona fide EAC drivers and associated driver specific gene dependencies. The overall goals were to (i) enhance our understanding of EAC tumorigenesis, (ii) identify potential opportunities for therapeutic interventions targeting EAC drivers via synthetic lethal-like approaches, and (iii) reduce the complexity of genetic heterogeneity by categorising EAC drivers with similar phenotypic outcomes. Through our approach we have identified complex crosstalk between the tumor suppressor SMAD4 and regulation of mTOR signaling, with specific downstream effects on translational reprogramming in EAC. Mutation or loss of SMAD4 occurs in up to 20% of EAC, but not pre-malignant tissue (Barrett’s esophagus), and is sufficient to promote transformation of pre-malignant cells in our in vivo tumorigenesis model. In this model, xenotransplanted SMAD4-deficient (via CRISPR-Cas9 knockout or shRNA knockdown) Barrett’s metaplasia cells formed invasive, metastatic tumors after a period of latency. SMAD4 deficient cells had downregulated expression of 4E-BP1, which inhibits EIF4E, the cap-dependent translation initiation factor. This was accompanied by increased mTOR activity, including phosphorylation and inactivation of 4EBP1. Moreover, we found that SMAD4-deficient cells preferentially upregulate cap-dependent translation at the expense of IRES mediated translation. Furthermore, perturbation of additional negative regulators of mTOR signaling in combination with SMAD4 knockout exacerbated these effects and accelerated tumorigenesis in vivo. We have extended these findings to a model of Barrett’s esophagus patient-derived organoids (PDOs) and observed increased proliferative potential of our genetically modified PDOs. Finally, analysing gene ontologies for differentially expressed genes from Perturb-seq revealed that driver-dependent transcriptional changes can be categorized into a smaller number of functional pathways allowing us to potentially consider groups of drivers as functional units. This work advances our understanding of EAC tumorigenesis, provides new mechanistic insights into SMAD4-driven transformation as well as novel potential therapeutic avenues for SMAD4-deficient EAC. Citation Format: Julia V. Milne, Ebtihal Mustafa, Kenji Fujihara, Eric Kusnadi, Anna Trigos, Niko Thio, Maree Pechlivanis, Carlos Cabalag, Twishi Gulati, Kaylene Simpson, Cuong Duong, Luc Furic, Wayne Phillips, Nicholas Clemons. Delineating functional drivers of esophageal adenocarcinoma to identify synthetic lethal interactions [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr PR007.

Multivariate copula-based framework for stochastic analysis of landslide runout distance

The increasing frequency of landslide disasters worldwide highlights the importance of accurate prediction of post-failure runout distances for effective risk management. However, the prediction of runout distances of gravitational mass flow remains challenging due to the inherent complex heterogeneities of geomaterials and their inter-correlated spatially varying mechanical properties. To address this challenge, this study proposes a novel multivariate stochastic method based on the combination of the Generalised Interpolation Material Point (GIMP) analysis and the multivariate copula-based approach. The method considers geotechnical uncertainties by simulating copula-based cross-correlated random fields from sparse field data and incorporating them into the GIMP analysis through Monte Carlo simulations (MCS). Two slope cases with similar geometries but different sources of probability information are presented to illustrate the effectiveness of the proposed method. The results show that considering the influence of multivariate random fields can significantly affect the post-failure analysis of landslides. Both slope cases show that over 40 % of all MCS samples exceed the deterministic case, which indicates that the current deterministic analysis notably underestimates the risk associated with large runout distances of landslides. This study highlights the necessity of considering the interdependency of spatial heterogeneity in post-failure modelling of landslides.

Thermal fracturing of anthracite under low-energy microwave irradiation: An experimental study

Microwave-assisted coalbed methane (CBM) development is a very promising technology for engineering applications. The mechanism of the macro and micro thermal fracture of coal must be further discussed because of the thermal inhomogeneity of microwave caused by the heterogeneity and structural complexity of coal. In this study, the temperature, weight and P-wave velocity of anthracite were tested under low-energy microwave irradiation. The characteristics of fracture initiation, extension, and connectivity in coal after microwave irradiation were extracted from macroscopic and microscopic observations. Then the mechanisms of microwave thermal fracturing in anthracite were analyzed. The results showed that the temperature of anthracite under low-energy microwave irradiation varies asynchronously. The temperature distributions with high and low temperature partitions exhibit obvious bedding effects. The coal mass loss varies in stages with microwave irradiation time, first increasing slowly and then increasing dramatically above 500 °C. The P-wave velocity presents a decreasing trend with the increase of input microwave energy. Coal generates a complex fracture network at the micro and macro scales, with fractures expanding outwards in a divergent pattern. The nonuniformity of the temperature distribution promotes fracture development. It is related to the asynchronous heating caused by the mineral composition, water content, pore fracture structure, and electromagnetic field in coal. It is of great significance to improve the thermal fracturing efficiency by using the nonuniformity of microwave heat in the application of microwave-assisted CBM development.

Comprehensive single cell transcriptomics analysis of murine osteosarcoma uncovers Skp2 function in metastasis, genomic instability and immune activation and reveals additional target pathways.

Osteosarcoma (OS) is the most common primary pediatric bone malignancy. One promising new therapeutic target is SKP2, encoding a substrate recognition factor of the SCF E3 ubiquitin ligase responsible for ubiquitination and proteasome degradation of substrate p27, thus driving cellular proliferation. We have shown previously that knockout of Skp2 in an immunocompetent transgenic mouse model of OS improved survival, drove apoptosis, and induced tumor inflammation. Here, we applied single-cell RNA-sequencing (scRNA-seq) to study primary OS tumors derived from Osx-Cre driven conditional knockout of Rb1 and Trp53. We showed that murine OS models recapitulate the tumor heterogeneity and microenvironment complexity observed in patient tumors. We further compared this model with OS models with functional disruption of Skp2: one with Skp2 knockout and the other with the Skp2-p27 interaction disrupted (resulting in p27 overexpression). We found reduction of T cell exhaustion and upregulation of interferon activation, along with evidence of replicative and endoplasmic reticulum-related stress in the Skp2 disruption models, and showed that interferon induction was correlated with improved survival in OS patients. Additionally, our scRNA-seq analysis uncovered decreased activities of metastasis-related gene signatures in the Skp2-disrupted OS, which we validated by observation of a strong reduction in lung metastasis in the Skp2 knockout mice. Finally, we report several potential mechanisms of escape from targeting Skp2 in OS, including upregulation of Myc targets, DNA copy number amplification and overexpression of alternative E3 ligase genes, and potential alternative lineage activation. These mechanistic insights into OS tumor biology and Skp2 function suggest novel targets for new, synergistic therapies, while the data and our comprehensive analysis may serve as a public resource for further big data-driven OS research.

The Challenge of Neuropsychiatric Systemic Lupus Erythematosus: From Symptoms to Therapeutic Strategies.

Systemic lupus erythematosus (SLE) is a chronic autoimmune condition that can seriously impair multiple organs including the nervous system, causing neuropsychiatric SLE (NPSLE), which encompasses a broad range of symptoms. Pathogenesis is not completely understood but is thought to involve inflammatory and vascular pathways. This comprehensive review discusses the complex nature and heterogeneity of NPSLE and the challenges in diagnosis and treatment that result from it. Diagnosis often requires a multidisciplinary approach with multiple assessments, including laboratory testing, imaging, and neuropsychological evaluations. Current treatments focus on managing symptoms through immunosuppressive and anti-thrombotic therapies tailored to the inflammatory or vascular nature of the specific NPSLE manifestations. This paper emphasizes the necessity for interdisciplinary approaches and further research to enhance diagnostic accuracy and treatment effectiveness. It also highlights the importance of understanding the underlying mechanisms of NPSLE to develop more targeted therapies, citing the need for high-quality studies and novel treatment agents.

Genetic Testing for Global Developmental Delay in Early Childhood

Global developmental delay (GDD) is characterized by a complex etiology, diverse phenotypes, and high individual heterogeneity, presenting challenges for early clinical etiologic diagnosis. Cognitive impairment is the core symptom, and despite the pivotal role of genetic factors in GDD development, the understanding of them remains limited. To assess the utility of genetic detection in patients with GDD and to examine the potential molecular pathogenesis of GDD to identify targets for early intervention. This multicenter, prospective cohort study enrolled patients aged 12 to 60 months with GDD from 6 centers in China from July 4, 2020, to August 31, 2023. Participants underwent trio whole exome sequencing (trio-WES) coupled with copy number variation sequencing (CNV-seq). Bioinformatics analysis was used to unravel pathogenesis and identify therapeutic targets. The main outcomes of this study involved enhancing the rate of positive genetic diagnosis for GDD, broadening the scope of genetic testing indications, and investigating the underlying pathogenesis. The classification of children into levels of cognitive impairment was based on the developmental quotient assessed using the Gesell scale. The study encompassed 434 patients with GDD (262 [60%] male; mean [SD] age, 25.75 [13.24] months) with diverse degrees of cognitive impairment: mild (98 [23%]), moderate (141 [32%]), severe (122 [28%]), and profound (73 [17%]). The combined use of trio-WES and CNV-seq resulted in a 61% positive detection rate. Craniofacial abnormalities (odds ratio [OR], 2.27; 95% CI, 1.45-3.56), moderate or severe cognitive impairment (OR, 1.69; 95% CI, 1.05-2.70), and age between 12 and 24 months (OR, 1.57; 95% CI, 1.05-2.35) were associated with a higher risk of carrying genetic variants. Additionally, bioinformatics analysis suggested that genetic variants may induce alterations in brain development and function, which may give rise to cognitive impairment. Moreover, an association was found between the dopaminergic pathway and cognitive impairment. In this cohort study of patients with GDD, combining trio-WES with CNV-seq was a demonstrable, instrumental strategy for advancing the diagnosis of GDD. The close association among genetic variations, brain development, and clinical phenotypes contributed valuable insights into the pathogenesis of GDD. Notably, the dopaminergic pathway emerged as a promising focal point for potential targets in future precision medical interventions for GDD.

Remodeling of tumor microenvironment by extracellular matrix protein 1a differentially regulates ovarian cancer metastasis

We previously reported that extracellular matrix protein 1 isoform a (ECM1a) promotes epithelial ovarian cancer (EOC) through autocrine signaling by binding to cell surface receptors αXβ2. However, the role of ECM1a as a secretory molecule in the tumor microenvironment is rarely reported. In this study, we constructed murine Ecm1-knockout mice and human ECM1a-knockin mice and further generated orthotopic or peritoneal xenograft tumor models to mimic the different metastatic stages of EOC. We show that ECM1a induces oncogenic metastasis of orthotopic xenograft tumors, but inhibits early-metastasis of peritoneal xenograft tumors. ECM1a remodels extracellular matrices (ECM) and promotes remote metastases by recruiting and transforming bone marrow mesenchymal stem cells (BMSCs) into platelet-derived growth factor receptor beta (PDGFRβ+) cancer-associated fibroblasts (CAFs) and facilitating the secretion of angiopoietin-like protein 2 (ANGPTL2). Competing with ECM1a, ANGPTL2 also binds to integrin αX through the P1/P2 peptides, resulting in negative effects on BMSC differentiation. Collectively, this study reveals the dual functions of ECM1a in remodeling of TME during tumor progression, emphasizing the complexity of EOC phenotypic heterogeneity and metastasis.

Hydrogeologic Framework Model‐Based Numerical Simulation of Groundwater Flow and Salt Transport and Analytic Hierarchy Process‐Based Multi‐Criteria Evaluation of Optimal Pumping Location and Rate for Mitigation of Seawater Intrusion in a Complex Coastal Aquifer System

AbstractA series of hydrogeologic framework model (HFM)‐based steady‐ and transient‐state numerical simulations is performed first using a coupled subsurface flow‐transport numerical model to analyze groundwater flow and salt transport in an actual three‐dimensional complex coastal aquifer system before and during groundwater pumping. A series of analytic hierarchy process (AHP)‐based multi‐criteria evaluations is then performed applying a multi‐criteria decision‐making approach to determine optimal pumping location and rate for a new pumping well in the complex coastal aquifer system during groundwater pumping. The complex coastal aquifer system is composed of six anisotropic fractured porous geologic media (five rock formations and one fault) and three isotropic porous geologic media (three soil formations) and shows high geometric irregularity and significant heterogeneity and anisotropy of the nine geologic media. Results of the steady‐state numerical simulations show successful model calibration with 26 measured groundwater levels and two observed seawater intrusion front lines. The latter two are determined by spatial interpolation and extrapolation of electrical conductivity logging data and electrical resistivity survey data, respectively. Based on the status and prospect of necessary water uses and available groundwater resources, the field observations of groundwater and seawater intrusion, and the analyses of the steady‐state numerical simulation after the model calibration, six candidate pumping locations are selected for the new pumping well. In addition, from six preliminary individual transient‐state numerical simulations, maximum pumping rates at the six candidate pumping locations are calculated first, and a set of six incremental candidate pumping rates is then assigned at each of the six candidate pumping locations. Results of the transients‐state numerical simulations show that groundwater flow and salt transport are spatially and temporally changed, and seawater intrusion is further intensified by groundwater pumping. In addition, the magnitudes of such spatial and temporal changes and intensification are significantly different depending on the candidate pumping locations and rates. Results of the steady‐ and transient‐state numerical simulations also show that both complexity (geometric irregularity, heterogeneity, and anisotropy including the fault) and topography have significant effects on the spatial distributions and temporal changes of groundwater flow and salt transport in the coastal aquifer system before and during groundwater pumping. In addition, results of statistical estimations of the mesh Peclet and Courant numbers confirm acceptabilities of minimizing numerical dispersion in the steady‐ and transient‐state numerical simulations. Based on the analyses of the transient‐state numerical simulations, eight multiple criteria are chosen to judge, prioritize, and rank the six candidate pumping locations and six candidate pumping rates for optimal pumping. Results of the multi‐criteria evaluations determine the optimal pumping location and rate for the new pumping well among the six candidate pumping locations and six candidate pumping rates. In addition, results of consistency checks confirm consistencies of judgments in the multi‐criteria evaluations.

Heterogenous phase evolution and mechanical response in additively manufactured low alloy martensitic steel processed via laser-directed energy deposition

This work investigates complex heterogeneity in microstructure and mechanical properties of a low alloy martensitic steel fabricated via laser-directed energy deposition (L-DED). A multi-scale characterization starting from macro-scale optical micrography, micro-scale X-ray diffraction and electron backscatter diffraction mapping to nano-scale transmission electron microscopy was adopted to fully comprehend the microstructural heterogeneity along the build direction. Notably, the top layers of the build demonstrated enhanced mechanical properties, exhibiting hardness of around 550 HV and an ultimate tensile strength of 2 GPa, which decreased progressively towards the base. Interestingly, resurgence in strength and hardness was observed for the layers located 10 mm above the substrate. The primary solidification cycle led to the formation of untempered martensite having high strength and hardness while subsequent reheat cycles led to the alteration of these martensites, enhancing ductility at the expense of strength. Auto-tempering and carbide (Fe-C based) precipitation due to prolonged thermal exposure contributed to the increased the strength in the lower layers. Additionally, the temperature profiles during the L-DED thermal cycles were modeled and correlated with the observed phase transformations, allowing for a detailed understanding of the structure–property relationships at different heights within the build. This study provides a fundamental insight into the microstructural heterogeneities and their implications on the strengthening mechanisms in L-DED fabricated low-alloy martensitic steel.

Flux‐gradient relations and their dependence on turbulence anisotropy

AbstractMonin–Obukhov similarity theory (MOST) is used in virtually all Earth System Models to parametrize the near‐surface turbulent exchanges and mean variable profiles. Despite its widespread use, there is high uncertainty in the literature about the appropriate parametrizations to use. In addition, MOST has limitations in very stable and unstable regimes, over heterogeneous terrain and complex orography, and has been found to represent the surface fluxes incorrectly. A new approach including turbulence anisotropy as a non‐dimensional scaling parameter has recently been developed and has been shown to overcome these limitations and generalize the flux‐variance relations to complex terrain. In this article, we analyze the flux‐gradient relations for five well‐known datasets, ranging from flat and homogeneous to slightly complex terrain. The scaling relations show substantial scatter and highlight the uncertainty in the choice of parametrization even over canonical conditions. We show that, by including information on turbulence anisotropy as an additional scaling parameter, the original scatter becomes well bounded and new formulations can be developed that drastically improve the accuracy of the flux‐gradient relations for wind shear () in unstable conditions and for temperature gradient () in both unstable and stable regimes. This analysis shows that both and are strongly dependent on turbulence anisotropy and allows us finally to settle the extensively discussed free convection regime for , which clearly exhibits a power law when anisotropy is accounted for. Furthermore, we show that the eddy diffusivities for momentum and heat and the turbulent Prandtl number are strongly dependent on anisotropy and that the latter goes to zero in the free convection limit. These results highlight the necessity to include anisotropy in the study of near‐surface atmospheric turbulence and lead the way for theoretically more robust simulations of the boundary layer over complex terrain.

Multiomics integration reveals NETosis heterogeneity and TLR2 as a prognostic biomarker in pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant neoplasm characterized by a poor prognosis and limited therapeutic strategy. The PDAC tumor microenvironment presents a complex heterogeneity, where neutrophils emerge as the predominant constituents of the innate immune cell population. Leveraging the power of single-cell RNA-seq, spatial RNA-seq, and multi-omics approaches, we included both published datasets and our in-house patient cohorts, elucidating the inherent heterogeneity in the formation of neutrophil extracellular traps (NETs) and revealed the correlation between NETs and immune suppression. Meanwhile, we constructed a multi-omics prognostic model that suggested the patients exhibiting downregulated expression of NETs may have an unfavorable outcome. We also confirmed TLR2 as a potent prognosis factor and patients with low TLR2 expression had more effective T cells and an overall survival extension for 6 months. Targeting TLR2 might be a promising strategy to reverse immunosuppression and control tumor progression for an improved prognosis.

Residual network improves the prediction accuracy of genomic selection.

Genetic improvement of complex traits in animal and plant breeding depends on the efficient and accurate estimation of breeding values. Deep learning methods have been shown to be not superior over traditional genomic selection (GS) methods, partially due to the degradation problem (i.e. with the increase of the model depth, the performance of the deeper model deteriorates). Since the deep learning method residual network (ResNet) is designed to solve gradient degradation, we examined its performance and factors related to its prediction accuracy in GS. Here we compared the prediction accuracy of conventional genomic best linear unbiased prediction, Bayesian methods (BayesA, BayesB, BayesC, and Bayesian Lasso), and two deep learning methods, convolutional neural network and ResNet, on three datasets (wheat, simulated and real pig data). ResNet outperformed other methods in both Pearson's correlation coefficient (PCC) and mean squared error (MSE) on the wheat and simulated data. For the pig backfat depth trait, ResNet still had the lowest MSE, whereas Bayesian Lasso had the highest PCC. We further clustered the pig data into four groups and, on one separated group, ResNet had the highest prediction accuracy (both PCC and MSE). Transfer learning was adopted and capable of enhancing the performance of both convolutional neural network and ResNet. Taken together, our findings indicate that ResNet could improve GS prediction accuracy, affected potentially by factors such as the genetic architecture of complex traits, data volume, and heterogeneity.

Application of whole exome sequencing in the diagnosis of muscular disorders: a study of Taiwanese pediatric patients.

Muscular dystrophies and congenital myopathies encompass various inherited muscular disorders that present diagnostic challenges due to clinical complexity and genetic heterogeneity. This study aimed to investigate the use of whole exome sequencing (WES) in diagnosing muscular disorders in pediatric patients in Taiwan. Out of 161 pediatric patients suspected to have genetic/inherited myopathies, 115 received a molecular diagnosis through conventional tests, single gene testing, and gene panels. The remaining 46 patients were divided into three groups: Group 1 (multiplex ligation-dependent probe amplification-negative Duchenne muscular dystrophy) with three patients (6.5%), Group 2 (various forms of muscular dystrophies) with 21 patients (45.7%), and Group 3 (congenital myopathies) with 22 patients (47.8%). WES analysis of these groups found pathogenic variants in 100.0% (3/3), 57.1% (12/21), and 68.2% (15/22) of patients in Groups 1 to 3, respectively. WES had a diagnostic yield of 65.2% (30 patients out of 46), detecting 30 pathogenic or potentially pathogenic variants across 28 genes. WES enables the diagnosis of rare diseases with symptoms and characteristics similar to congenital myopathies and muscular dystrophies, such as muscle weakness. Consequently, this approach facilitates targeted therapy implementation and appropriate genetic counseling.