Trajectory Analysis Research Articles

A salt bridge of the C-terminal carboxyl group regulates PHPT1 substrate affinity and catalytic activity.

PHPT1 is a histidine phosphatase that modulates signaling in eukaryotes through its catalytic activity. Here, we present an analysis of the structure and dynamics of PHPT1 through a combination of solution NMR, molecular dynamics, and biochemical experiments. We identify a salt bridge formed between the R78 guanidinium moiety and the C-terminal carboxyl group on Y125 that is critical for ligand binding. Disruption of the salt bridge by appending a glycine residue at the C-terminus (G126) leads to a decrease in catalytic activity and binding affinity for the pseudo substrate, para-nitrophenylphosphate (pNPP), as well as the active site inhibitor, phenylphosphonic acid (PPA). We show through NMR chemical shift, 15N relaxation measurements, and analysis of molecular dynamics trajectories, that removal of this salt bridge results in an active site that is altered both structurally and dynamically thereby significantly impacting enzymatic function and confirming the importance of this electrostatic interaction.

Single-cell transcriptome reveals the heterogeneity of malignant ductal cells and the prognostic value of REG4 and SPINK1 in primary pancreatic ductal adenocarcinoma

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related deaths, with very limited therapeutic options available. This study aims to comprehensively depict the heterogeneity and identify prognostic targets for PDAC with single-cell RNA sequencing (scRNA-seq) analysis. Methods ScRNA-seq analysis was performed on 16 primary PDAC and three adjacent lesions. A series of analytical methods were applied for analysis in cell clustering, gene profiling, lineage trajectory analysis and cell-to-cell interactions. In vitro experiments including colony formation, wound healing and sphere formation assay were performed to assess the role of makers. Results A total of 32,480 cells were clustered into six major populations, among which the ductal cell cluster expressing high copy number variants (CNVs) was defined as malignant cells. Malignant cells were further subtyped into five subgroups which exhibited specific features in immunologic and metabolic activities. Pseudotime trajectory analysis indicated that components of various oncogenic pathways were differentially expressed along tumor progression. Furthermore, intensive substantial crosstalk between ductal cells and stromal cells was identified. Finally, genes (REG4 and SPINK1) screened out of differentially expressed genes (DEGs) were upregulated in PDAC cell lines. Silencing either of them significantly impaired proliferation, invasion, migration and stemness of PDAC cells. Conclusions Our findings offer a valuable resource for deciphering the heterogeneity of malignant ductal cells in PDAC. REG4 and SPINK1 are expected to be promising targets for PDAC therapy.

Polyaromatic Hydrocarbon Inclusion Complexes with 2-Hydroxylpropyl-β/γ-Cyclodextrin: Molecular Dynamic Simulation and Spectroscopic Studies

In aqueous and solid media, 2-HP-β/γ-CD inclusion complexes with poly aromatic hydrocarbon (PAH) Phenanthrene (PHN), Anthracene (ANT), Benz(a)pyrene (BaP), and Fluoranthene (FLT) were investigated for the first time. The inclusion complexes were characterized and investigated using fluorescence and 1HNMR spectroscopy. The most prevalent complexes consisting of both guests and hosts were those with a 1:1 guest-to-host ratio. The stability constants for the complexes of PHN with 2-HP-β-CD and 2-HP-γ-CD were 85 ± 12 M−1 and 49 ± 29 M−1, respectively. Moreover, the stability constants were found to be 502 ± 46 M−1 and 289 ± 44 M−1 for the complexes of ANT with both hosts. The stability constants for the complexes of BaP with 2-HP-β-CD and 2-HP-γ-CD were (1.5 ± 0.02) × 103 M−1 and (9.41 ± 0.03) × 103 M−1, respectively. The stability constant for the complexes of FLT with 2-HP-β-CD was (1.06 ± 0.06) × 103 M−1. However, FLT was observed to form a weak complex with 2-HP-γ-CD. Molecular dynamic (MD) simulations were used to investigate the mechanism and mode of inclusion processes, and to monitor the atomic-level stability of these complexes. The analysis of MD trajectories demonstrated that all guests formed stable inclusion complexes with both hosts throughout the duration of the simulation time, confirming the experimental findings. However, the flexible Hydroxypropyl arms prevented the PAHs from being encapsulated within the cavity; however, a stable exclusion complex was observed. The main forces that influenced the complexation included van der Waals interactions, hydrophobic forces, and C–H⋯π interaction, which contribute to the stability of these complexes.

Single-nucleus analysis reveals microenvironment-specific neuron and glial cell enrichment in Alzheimer’s disease

BackgroundAlzheimer’s disease (AD) is a complicated neurodegenerative disease. Neuron-glial cell interactions are an important but not fully understood process in the progression of AD. We used bioinformatic methods to analyze single-nucleus RNA sequencing (snRNA-seq) data to investigate the cellular and molecular biological processes of AD.MethodsnRNA-seq data were downloaded from Gene Expression Omnibus (GEO) datasets and reprocessed to identify 240,804 single nuclei from healthy controls and patients with AD. The cellular composition of AD was further explored using Uniform Manifold Approximation and Projection (UMAP). Enrichment analysis for the functions of the DEGs was conducted and cell development trajectory analyses were used to reveal underlying cell fate decisions. iTALK was performed to identify ligand-receptor pairs among various cell types in the pathological ecological microenvironment of AD.ResultsSix cell types and multiple subclusters were identified based on the snRNA-seq data. A subcluster of neuron and glial cells co-expressing lncRNA-SNHG14, myocardin-related transcription factor A (MRTFA), and MRTFB was found to be more abundant in the AD group. This subcluster was enriched in mitogen-activated protein kinase (MAPK)-, immune-, and apoptosis-related pathways. Through molecular docking, we found that lncRNA-SNHG14 may bind MRTFA and MRTFB, resulting in an interaction between neurons and glial cells.ConclusionsThe findings of this study describe a regulatory relationship between lncRNA-SNHG14, MRTFA, and MRTFB in the six main cell types of AD. This relationship may contribute to microenvironment remodeling in AD and provide a theoretical basis for a more in-depth analysis of AD.

Association of Life's Essential 8 with all-cause mortality and risk of cancer: a prospective cohort study.

No study has concentrated on the association of LE8 with cancer risk and death. We aim to examine the association of LE8 with death and cancer. A total of 94733 adults aged 51.42 ± 12.46 years and 77551 participants aged 54.09±12.06 years were enrolled in longitudinal and trajectory analysis respectively. Baseline LE8 was divided into three groups based on the American Heart Association criteria and three trajectory patterns by latent mixture models. We reviewed medical records and clinical examinations to confirm incident cancer during the period from 2006 to 2020. Death information was collected from provincial vital statistics offices. Cox models were used. 12807 all-cause deaths and 5060 cancers were documented during a 14-year follow-up. Relative to participants with high LE8 at baseline, participants with lower levels of LE8 have a significantly increased risk of mortality and incident cancer. All these risks have an increasing trend with LE8 level decreasing. Meanwhile, the trajectory analysis recorded 7483 all-cause deaths and 3037 incident cancers after approximately 10 years. The associations of LE8 with death and cancer were identical to the longitudinal study. In the subtype cancer analysis, LE8 has a strong effect on colorectal cancer risk. Moreover, the cut point is 56.67 in the association between LE8 and death, while the cut point altered to 64.79 in the association between LE8 and incident cancers. These associations were enhanced among younger adults. There was a significant association of LE8 with death and cancer risk, especially for the young population.

Network pharmacology, molecular docking, and dynamics analyses to predict the antiviral activity of ginger constituents against coronavirus infection.

COVID-19 is a global pandemic that caused a dramatic loss of human life worldwide, leading to accelerated research for antiviral drug discovery. Herbal medicine is one of the most commonly used alternative medicine for the prevention and treatment of many conditions including respiratory system diseases. In this study, a computational pipeline was employed, including network pharmacology, molecular docking simulations, and molecular dynamics simulations, to analyze the common phytochemicals of ginger rhizomes and identify candidate constituents as viral inhibitors. Furthermore, experimental assays were performed to analyze the volatile and non-volatile compounds of ginger and to assess the antiviral activity of ginger oil and hydroalcoholic extract. Network pharmacology analysis showed that ginger compounds target human genes that are involved in related cellular processes to the viral infection. Docking analysis highlighted five pungent compounds and zingiberenol as potential inhibitors for the main protease (Mpro), spike receptor-binding domain (RBD), and human angiotensin-converting enzyme 2 (ACE2). Then, (6)-gingerdiacetate was selected for molecular dynamics (MD) simulations as it exhibited the best binding interactions and free energies over the three target proteins. Trajectories analysis of the three complexes showed that RBD and ACE2 complexes with the ligand preserved similar patterns of root mean square deviation (RMSD) and radius of gyration (Rg) values to their respective native structures. Finally, experimental validation of the ginger hydroalcoholic extract confirmed the existence of (6)-gingerdiacetate and revealed the strong antiviral activity of the hydroalcoholic extract with IC of 2.727 . Our study provides insights into the potential antiviral activity of (6)-gingerdiacetate that may enhance the host immune response and block RBD binding to ACE2, thereby, inhibiting SARS-CoV-2 infection.

Single-Cell Data Analysis Reveals Critical Hepatic Cells Subpopulations in the Progression of Non-alcoholic Fatty Liver Disease to Non-Alcoholic Steatohepatitis.

The aim of this study was to reveal the hepatic cell landscape and function in the progression of NAFLD to NASH. Non-alcoholic steatohepatitis (NASH) is the progressive form and turning point of nonalcoholic fatty liver disease (NAFLD), which severely causes irreversible cirrhosis as well as hepatocellular carcinoma. The mechanism underlying the progression of NAFLD to NASH has not been revealed. Unraveling the mechanism of action of NAFLD-NASH is an important goal in improving the survival of patients with liver disease. The aim of this study is to discover heterogeneous hepatic cells during the progression of NAFLD to NASH. Single-nucleus RNA-seq (snRNA-seq) data containing NASH in NAFLD samples were obtained from the Gene Expression Omnibus (GEO) database. Cell types in liver tissues from NASH and NAFLD were identified after dimensionality reduction analysis, cluster analysis, and cell annotation. The cell pathways in which differences existed were identified by analyzing metabolic pathways in Hepatic cells. We also identified cell subpopulations in Hepatic cells. The developmental trajectories of Hepatic cells were characterized by pseudotime trajectory analysis. Single-cell regulatory network inference and clustering analysis identified key transcription factors and gene regulatory networks in Hepatic cells. Moreover, cell communication analysis determined the potential interactions between Hepatic cells and immune cells, and heapatic stellate cells. Seven cell types were identified in NAFLD and NASH. The proportion of Hepatic cells was lower in NASH and showed greater energy metabolism and glucose metabolism activity. Hepatic cells exhibited heterogeneity, showing two cell subpopulations, Hepatic cells 1 and Hepatic cells 2. Dysregulation of lipid metabolism in Hepatic Cell 2 resulted in lipid accumulation in the liver, which might be involved in the progression of NAFLD. Four key transcription factors, BHLHE40, NFEL2L, RUNX1, and INF4A, were primarily found in Hepatic cells 2. The transcription factors within the hepatic cells 2 subpopulation mainly regulated genes related to lipid metabolism, energy metabolism, and inflammatory response. The cell communication analysis showed that hepatocyte interactions with immune cells were associated with inflammatory responses, while interactions with hepatic astrocytes were associated with liver injury and hepatocyte fibrosis. The hepatic cells 2 might promote the progression of NAFLD to NASH by regulating metabolic activity, which might contribute to liver injury through inflammation.

Single-Cell RNA Sequencing Identifies Crucial Genes Influencing the Polarization of Tumor-Associated Macrophages in Liver Cancer

Background. In the context of hepatocellular carcinoma (HCC), tumor-associated macrophages (TAMs) are pivotal for the immunosuppressive nature of the tumor microenvironment (TME). This investigation delves into the functional transformations of TAMs within the TME by leveraging single-cell transcriptomics to pinpoint critical genes influencing TAM subset polarization. Methods. We procured single-cell and bulk transcriptomic data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), implementing quality assurance, dimensional reduction, clustering, and annotation on the single-cell sequencing data. To examine cellular interactions, CellChat was utilized, while single-cell regulatory network inference and clustering (SCENIC) was applied to deduce transcription factors (TFs) and their associated targets. Through gene enrichment, survival, and immune infiltration correlation analyses, we sought to pinpoint and validate influential genes. A TAM model under HCC conditions was then established to confirm the expression levels of these key genes. Results. Our analysis encompassed 74,742 cells and 23,110 genes. Through postdimensional reduction and clustering, we identified seven distinct cell types and nine TAM subtypes. Analysis via CellChat highlighted a predominance of M2-phenotype-inclined TAM subsets within the tumor’s core. SCENIC pinpointed the transcription factor PRDM1 and its target genes as pivotal in this region. Further analysis indicated these genes’ involvement in macrophage polarization. Employing trajectory analysis, survival analysis, and immune infiltration correlation, we scrutinized and validated genes likely directing M2 polarization. Experimental validation confirmed PRDM1’s heightened expression in TAMs conditioned by HCC. Conclusions. Our findings suggest the PRDM1 gene is a key regulator of M2 macrophage polarization, contributing to the immunosuppressive TME in HCC.

Adiposity trajectories and cardiovascular disease risk in women: a population-based cohort study with a focus on menopausal status

ObjectivesA single measurement of adiposity indices could predict the incidence of cardiovascular disease (CVD); nonetheless their long-term pattern and its association with incident CVD are rarely studied. This study aimed to determine distinct trajectories of adiposity indices among participants of Tehran Lipid and Glucose Study (TLGS) and their association with incident CVD. Furthermore, this study aimed to investigate whether this association differed among individuals according to their menopausal status.MethodA total of 6840 women participated in TLGS, aged 20 years and older were included in this study; they were followed for a median of 16 years. Body mass index (BMI), waist circumference (WC), conicity index (CI) and body roundness index (BRI) were included in the analysis as adiposity indices. The cohort outcome panel of medical specialists identified the CVD outcomes. Trajectory analyses were used to identify homogeneous distinct clusters of adiposity indices trajectories. The association between the trajectory group membership and incident CVD were explored by Cox proportional hazard models, with unadjusted and adjusted model for baseline age, physical activity, smoking status, menopause and family history of CVD.ResultsThree BMI trajectory groups of low, medium, and high and two trajectories for WC, BRI and CI were identified. Adjusted cox proportional hazard models revealed significant associations between the hazard of CVD experience and the high trajectory group of the BMI (HR: 2.06, 95% CI: 1.38-3.07), WC (HR: 2.71, 95% CI: 1.98-3.70), CI (HR: 1.87, 95% CI: 1.26-2.77) and BRI (HR: 1.55-95% CI: 1.12-2.15), compared to the low trajectory group. Subgroup analysis based on the menopausal status of participants showed that the HR of CVD incidences for all of trajectories adiposity indices, except BMI, was statistically significant. Adjusted cox proportional hazard models, in those women not reached menopause during study, revealed that the HR (95% CI) of CVD incidences for high trajectory of BMI, WC, CI and BRI were 2.80 (1.86-7.05); 2.09 (1.40-6.16); 1.72 (1.42-5.61), and 3.09 (1.06-9.01), respectively. These values for those were menopause at the initiation of the study were 1.40 (1.11, 2.53); 1.65 (1.04-2.75); 1.69 (1.01-2.87), and 1.61 (0.98-2.65), respectively.ConclusionOur findings suggest that adiposity trajectories, particularly central adiposity index of CI, could precisely predict the CVD risk. Consequently, preventive strategies should be tailored accordingly.

Structural Insight into the Binding Pattern and Interaction Mechanism of Antagonist MCC950 and Agonist BMS986299 with NLRP3 by Molecular Dynamics Simulation.

The NLRP3 inflammasome mediates a range of inflammatory responses that are associated with an increasing number of pathological mechanisms. Over-activation of NLRP3 can exacerbate many diseases. However, NLRP3 antagonists have significant therapeutic potential. Moreover, NLRP3 plays an important role in limiting the growth and spread of some tumors, and NLRP3 agonists also have clinical value. MCC950 and BMS986299 are an antagonist and agonist of NLRP3, respectively. In light of the important clinical applications of NLRP3, especially for NLRP3 inhibitors, a computational method was used to investigate the interaction modes of MCC950 and BMS986299 with NLRP3 in order to design and develop more potent NLRP3 regulators. In this study, the conformational behaviors of NLRP3 bound to the antagonist MCC950 in an inactive state and the agonist BMS986299 in an active state were investigated using 200 ns equilibrium all-atom molecular dynamics (MD) simulations, and then the analyses of the MD trajectories (RMSD, Rg, RMSF, SASA, PCA, and DCCM) were carried out to explore the mechanism of the antagonist and agonist on NLRP3 in the two different states. The RMSD, RMSF, Rg, SASA, and PCA analyses indicated that NLRP3 was more dispersive and less energetically stable in the active state than in the inactive state and that MCC950 significantly reduced the fluctuations of the interactive residues while BMS986299 did not. The antagonist MCC950 interacted with residues mainly in the NBD, HD1, WHD, and HD2 domains of NLRP3, whereas the agonist BMS986299 mainly in the NBD and WHD of NLRP3. Additionally, both compounds did not interact with residues located in the FISNA domain. The conformation of the FISNA domain appeared to change significantly when NLRP3 was translated from an inactive state to an active state. The antagonist may interact with residues mainly in the NBD, HD1, WHD, and HD2 domains, and the agonist may interact in the NBD and WHD domains. Our study provided new insights into the development of NLRP3 regulators.

#2834 Analysis of cyst hetero- and homogeneity to unravel common pathways in autosomal dominant polycystic kidney disease

Abstract Background and Aims Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disease, with a prevalence of 1 in ca. 1000 individuals and accounting for 10% of the European dialysis population. It is most frequently (75-80%) caused by mutations in the PKD1 gene encoding Polycystin-1. Besides systemic manifestations such as liver cysts, hypertension and cardiac abnormalities, the most prominent phenotype is the gradual development of kidney cysts, leading to kidney enlargement and a decline in kidney function leading to end-stage kidney disease at an average age of ca. 50 years. The cysts arise from tubular epithelial cells in the nephron that start to dedifferentiate, proliferate and eventually secrete fluid into the cyst lumen promoting its swelling. This process is molecularly regulated by changes in Ca2+, cAMP, PKA and PI3K-Akt-mTOR signaling, among others. The renal cysts are further characterized by ciliary dysfunction, altered signal transduction, loss of polarity, apoptosis, mitochondrial abnormalities, metabolic reprogramming, inflammation, oxidative stress and epigenetic changes. However, the exact sequence of events and their relative importance in the process of cyst formation remains unclear. Therefore, we analyzed the transcriptomic cyst hetero- and homogeneity to identify the pathways that were different, but also shared among individual cysts. Method We performed RNA-Seq analysis on 40 individual cystic membranes of nephrectomized kidneys of 4 PKD1 patients. We included 4 samples of macroscopically healthy tissue from 2 ADPKD kidneys (histologically confirmed to have microcysts) and 4 samples from 4 healthy kidneys. Principal component, cluster and trajectory analysis was performed to explore cyst heterogeneity. Adjacent pieces of cystic membrane were analyzed for histology (H&E, Sirius Red) or stained with FITC-tagged Lotus Tetragonolobus Lectin (LTL) or Dolichos Biflorus Agglutinin (DBA), a proximal and distal tubular marker, respectively. Results Although the cysts clearly separated from the healthy tissues in the analyses, there was also a distinct heterogeneity observed among the cysts that was independent of patient, gender, cyst size, location or fluid color. Pathway analysis revealed that these changes were characterized by a gradual increase of interstitial (remodeling) and inflammation markers, and a gradual decrease in differentiation markers (e.g. development, intercellular junctions, basement membrane) along the trajectory pseudotime. We could identify 6 clusters of cystic samples, with 2 clusters deviating from the main trajectory. With respect to tubular/epithelial dedifferentiation, the decrease in proximal tubular markers already occurred in microcystic tissue and was stronger compared to the other tubular segments. Consequently, none of the analyzed cystic membranes stained positive for LTL, while others showed clear staining for DBA. Microcysts on the other hand stained positive for LTL or DBA. Several cysts showed RNA marker expression of multiple tubular segments. Indeed, smaller macrocysts (diameter in the mm range) were lined by both LTL- and DBA-positive regions. Conclusion By analyzing transcriptomic hetero- and homogeneity among individual cysts, the molecular alterations in ADPKD progression can be tracked down and determined whether they occur similarly in all cysts or at different levels. Our data also suggest that loss of proximal tubular markers in macrocysts is more prominent compared to the decrease in distal markers. Finally, inner cyst walls can consist of cyst-lining cells of multiple origins.

TSH Trajectories During Levothyroxine Treatment in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) Cohort.

Thyroid-stimulating hormone (TSH) trajectory classification represents a novel approach to defining the adequacy of levothyroxine (LT4) treatment for hypothyroidism over time. This is a proof of principle study that uses longitudinal clinical data, including thyroid hormone levels from a large prospective study to define classes of TSH trajectories and examine changes in cardiovascular (CV) health markers over the study period. Growth mixture modeling (GMM), including latent class growth analysis (LCGA), was used to classify LT4-treated individuals participating in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) based on serial TSH levels. Repeated measure analyses were then utilized to assess within-class changes in blood pressure, lipid levels, hemoglobin A1c, and CV-related medication utilization. From the 621 LT4-treated study participants, the best-fit GMM approach identified 4 TSH trajectory classes, as defined by their relationship to the normal TSH range: (1) high-high normal TSH, (2) normal TSH, (3) normal to low TSH, and (4) low to normal TSH. Notably, the average baseline LT4 dose was lowest in the high-high normal TSH group (77.7 µg, P < .001). There were no significant differences in CV health markers between the classes at baseline. At least 1 significant difference in CV markers occurred in all classes, highlighted by the low to normal class, in which total and high-density lipoprotein cholesterol, triglycerides, and A1c all increased significantly (P = .049, P < .001, P < .001, and P = .001, respectively). Utilization of antihypertensive, antihyperlipidemic, and antidiabetes medications increased in all classes. GMM/LCGA represents a viable approach to define and examine LT4 treatment by TSH trajectory. More comprehensive datasets should allow for more complex trajectory modeling and analysis of clinical outcome differences between trajectory classes.

A developmental trajectory of latent inhibition.

Latent inhibition is said to occur when learning about the relationship between a cue and an outcome proceeds more readily when the cue is novel relative to when the cue has been rendered familiar through mere preexposure. Previous studies suggest that latent inhibition, while evident in 4- to 5-year-old children, is attenuated or even absent in older children. There are, however, acknowledged shortcomings associated with previous demonstrations of this effect, which we attempted to overcome using a letter prediction task that has been employed in recent studies of latent inhibition in adults. One hundred and seventy-five 4- to 14-year-old children and 175 young adults completed a letter prediction task, with a latent inhibition manipulation embedded within it. Using developmental trajectory analysis we found, contrary to other studies, an increase in the magnitude of latent inhibition as children age, with the effect becoming significant when children were around 6.7 years of age. Model comparison revealed that a linear function best described the relationship between latent inhibition and age. We discuss these findings in the context of theories of learning and attention, and consider the role of concurrent task type as a factor that determines the developmental trajectory of latent inhibition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Transboundary migration of Loxostege sticticalis (Lepidoptera: Crambidae) among China, Russia and Mongolia.

The beet webworm, Loxostege sticticalis, a worldwide pest of many crops, performs a seasonal migration, causing periodic outbreaks in Asia, Europe and North America. Although long-distance migration is well documented in China, patterns of transboundary migration among China, Russia and Mongolia are largely unknown. We performed a phase analysis of L. sticticalis periodic outbreaks among three countries based on 30 years of historical population data, analyzed the wind systems during migration over boundary regions, and traced the migratory routes in a case study of outbreaks in 2008 by trajectory simulation. Highly synchronized outbreak years of L. sticticalis were observed between China and Mongolia, China and eastern Siberia, China and western Siberia, Mongolia and eastern Siberia, eastern Siberia and western Siberia from 1978 to 2008, indicating possible transboundary migration between these regions. Winds at 300-600 m altitude, where adult migration usually occurs, also showed a high probability of northwestern winds in Haila'er (China), Chita (Russia) and Choybalsan (Mongolia), favoring successful adult migration from these areas to northern and northeastern China. Back trajectory analysis further showed that the first-generation adults that caused the severe outbreak of second-generation larvae in 2008 originated from eastern Siberia, eastern Mongolia, and the boundary regions of China-Russia and China-Mongolia. Our findings demonstrated that the source of L. sticticalis outbreaks in northern China was closely related to the outbreaks in Siberia and Mongolia via long-distance transboundary windborne migration. This information will help guide international monitoring and management strategies against this notorious pest. © 2024 Society of Chemical Industry.

Mapping the Single-cell Differentiation Landscape of Osteosarcoma.

The genetic intratumoral heterogeneity observed in human osteosarcomas (OS) poses challenges for drug development and the study of cell fate, plasticity, and differentiation, processes linked to tumor grade, cell metastasis, and survival. To pinpoint errors in OS differentiation, we transcriptionally profiled 31,527 cells from a tissue-engineered model that directsMSCs toward adipogenic and osteoblastic fates. Incorporating pre-existing chondrocyte data, we applied trajectory analysis and non-negative matrix factorization (NMF) to generate the first human mesenchymal differentiation atlas. This 'roadmap' served as a reference to delineate the cellular composition of morphologically complex OS tumors and quantify each cell's lineage commitment. Projecting a bulk RNA-seq OS dataset onto this roadmap unveiled a correlation between a stem-like transcriptomic phenotype and poorer survival outcomes. Our study quantifies OS differentiation and lineage, a prerequisite to better understanding lineage-specific differentiation bottlenecks that might someday be targeted therapeutically.

Trajectory mapping of renal clear cell carcinoma transcriptomes identifies stage-independent predictors of favorable prognosis

Abstract Objectives The prognosis of clear cell renal cell carcinoma (ccRCC) is typically based on clinical stage, but it can vary for some patients. Transcriptomic analysis is vital for understanding ccRCC progression, though its correlation with the clinical stage in predicting prognosis is uncertain. We aim to employ trajectory inference to study ccRCC’s molecular progression and identify potential new markers for judging disease progression and prognosis. Methods Using a trajectory inference approach, we characterize the molecular progression profile of ccRCC based on transcriptome profiling. Additional pathway activity, immune response, and miRNA profiling scoring were integrated to identify possible drivers of trajectory progression. Results Scoring based on the trajectory demonstrates a significant improvement in patient prognosis prediction and identifies 10 risk factors in patients with low-grade tumors, and nine protective factors in patients with high-grade tumors. Mechanistically, we demonstrate an association between solute light carrier transporters are associated with ccRCC progression, with SLC7A5 expression being validated through immunohistochemistry to increase in metastatic patients. Conclusions Trajectory analysis of ccRCC transcriptomes can be used to model the molecular progression of disease and may assist in ccRCC prognosis. SLC7A5 is aberrantly expressed in ccRCC and may be a risk factor for poor prognosis.

Sex differences in the trajectories of cognitive decline and affected cognitive domains among older adults with controlled and uncontrolled glycemia.

We aimed to analyze the trajectories of cognitive decline as a function of the presence of type 2 diabetes and glycemic control in analyzes stratified by sex in an eight-year follow-up period. A total of 1,752 men and 2,232 women aged ≥50 years who participated in the English Longitudinal Study of Ageing (ELSA), conducted from 2004 to 2012, were analyzed. The outcomes of interest were performance on the cognitive domains of memory, executive function, and temporal orientation as well as the global cognition score. Cognitive performance was standardized in z-scores in strata based on schooling and age. The participants were classified as without diabetes, with controlled glycemia and with uncontrolled glycemia, according to medical diagnosis, glucose-lowering medications use and HbA1c levels. Generalized linear mixed models controlled by sociodemographic, behavioral, and health-related characteristics were used for the trajectory analyses. No differences in z-scores were found for global cognition or cognitive domains based on diabetes classification in men and women at baseline. Over eight years of follow-up, women with uncontrolled glycemia had a greater decline in z-scores for global cognition (-0.037 SD/year [95%CI: -0.073; -0.001]) and executive function (-0.049 SD/year [95%CI: -0.092; -0.007]) compared to those without diabetes. No significant difference in trajectories of global cognition or any cognitive domain was found in men as a function of diabetes classification. Women with uncontrolled glycemia are at greater risk of a decline in global cognition and executive function than those without diabetes.

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction

Colorectal cancer (CRC) is a malignant tumor originating from epithelial cells of the colon or rectum, and its invasion and metastasis could be regulated by anoikis. However, the key genes and pathways regulating anoikis in CRC are still unclear and require further research. The single cell transcriptome dataset GSE221575 of GEO database was downloaded and applied to cell subpopulation type identification, intercellular communication, pseudo time cell trajectory analysis, and receptor ligand expression analysis of CRC. Meanwhile, the RNA transcriptome dataset of TCGA, the GSE39582, GSE17536, and GSE17537 datasets of GEO were downloaded and merged into one bulk transcriptome dataset. The differentially expressed genes (DEGs) related to anoikis were extracted from these data sets, and key marker genes were obtained after feature selection. A clinical prognosis prediction model was constructed based on the marker genes and the predictive effect was analyzed. Subsequently, gene pathway analysis, immune infiltration analysis, immunosuppressive point analysis, drug sensitivity analysis, and immunotherapy efficacy based on the key marker genes were conducted for the model. In this study, we used single cell datasets to determine the anoikis activity of cells and analyzed the DEGs of cells based on the score to identify the genes involved in anoikis and extracted DEGs related to the disease from the transcriptome dataset. After dimensionality reduction selection, 7 marker genes were obtained, including TIMP1, VEGFA, MYC, MSLN, EPHA2, ABHD2, and CD24. The prognostic risk model scoring system built by these 7 genes, along with patient clinical data (age, tumor stage, grade), were incorporated to create a nomogram, which predicted the 1-, 3-, and 5-years survival of CRC with accuracy of 0.818, 0.821, and 0.824. By using the scoring system, the CRC samples were divided into high/low anoikis-related prognosis risk groups, there are significant differences in immune infiltration, distribution of immune checkpoints, sensitivity to chemotherapy drugs, and efficacy of immunotherapy between these two risk groups. Anoikis genes participate in the differentiation of colorectal cancer tumor cells, promote tumor development, and could predict the prognosis of colorectal cancer.

Using HawkEye Level-2 Satellite Data for Remote Sensing Tasks in the Presence of Dust Aerosol

This paper is the first to examine the operation of the HawkEye satellite in the presence of dust aerosol. The study region is the Black Sea. Dust transport dates were identified using visual inspection of satellite imagery, back-kinematic HYSPLIT trajectory analysis, CALIPSO aerosol stratification and typing maps, and the global forecasting model SILAM. In a comparative analysis of in-situ and satellite measurements of the remote sensing reflectance, an error in the atmospheric correction of HawkEye measurements was found both for a clean atmosphere and in the presence of an absorbing aerosol. It is shown that, on average, the dependence of the atmospheric correction error on wavelength has the form of a power function of the form from λ−3 to λ−9. The largest errors are in the short-wavelength region of the spectrum (412–443 nm) for the dust and dusty marine aerosol domination dates. A comparative analysis of satellite and in situ measurements of the optical characteristics of the atmosphere, namely the AOD and the Ångström parameter, was carried out. It is shown that the aerosol model used by HawkEye underestimates the Angström parameter and, most likely, large errors and outliers in satellite measurements are associated with this.

The three-sided right-handed β-helix is a versatile fold for glycan interactions.

Interactions between proteins and glycans are critical to various biological processes. With databases of carbohydrate-interacting proteins and increasing amounts of structural data, the three-sided right-handed β-helix (RHBH) has emerged as a significant structural fold for glycan interactions. In this review, we provide an overview of the sequence, mechanistic, and structural features that enable the RHBH to interact with glycans. The RHBH is a prevalent fold that exists in eukaryotes, prokaryotes, and viruses associated with adhesin and carbohydrate-active enzyme (CAZyme) functions. An evolutionary trajectory analysis on structurally characterized RHBH-containing proteins shows that they likely evolved from carbohydrate-binding proteins with their carbohydrate-degrading activities evolving later. By examining three polysaccharide lyase and three glycoside hydrolase structures, we provide a detailed view of the modes of glycan binding in RHBH proteins. The 3-dimensional shape of the RHBH creates an electrostatically and spatially favorable glycan binding surface that allows for extensive hydrogen bonding interactions, leading to favorable and stable glycan binding. The RHBH is observed to be an adaptable domain capable of being modified with loop insertions and charge inversions to accommodate heterogeneous and flexible glycans and diverse reaction mechanisms. Understanding this prevalent protein fold can advance our knowledge of glycan binding in biological systems and help guide the efficient design and utilization of RHBH-containing proteins in glycobiology research.