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Results for “heterogeneity”

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At least 19 recordsLinked to original sources

PubMed1978

Heterogeneity in diabetes mellitus--update, 1978. Evidence for further genetic heterogeneity within juvenile-onset insulin-dependent diabetes mellitus.

The concept that idiopathic diabetes mellitus is a genetically heterogeneous group of disorders has been established by twin and HLA studied that have permitted the separation of juvenile-onset and maturity-onset diabetes. The extent of the heterogeneity within the juvenile-onset and maturity-onset types is still in question. On the basis of recent immunologic and metabolic studies we believe that further heterogeneity can be demonstrated within the juvenile-onset diabetic group. We wish to hypothesize that there are at least two distinct forms of juvenile-onset diabetes, one associated with HLA B8 and the other with BW15. The B8 type is characterized by autoimmunity, microangiopathy, and a stronger association with the HLA D locus. The BW15 type is characterized by antibody response to exogenous insulin and a stronger association with the HLA C locus. Greater understanding of the pathogenesis, natural history, and genetics of diabetes mellitus will result as the full extent of genetic heterogeneity is elucidated.

Alleles↗

PubMed1977

Heterogeneous nuclear RNA secondary structure: oligo (U) sequences base-paired with poly (A) and their possible role as binding sites for heterogeneous nuclear RNA-specific proteins.

HeLa cell heterogeneous nuclear RNA derived from high-molecular-weight nuclear ribonucleoprotein (RNP) particles contains oligo(U) sequences of 15-50 nucleotides base-paired with poly(A). These duplexes are resistant to pancreatic RNase at 0.5 M NaCl in native RNP, remain so after chemical deproteinization of the RNP digests, and then copurify with poly(A) on oligo(dT)-cellulose chromatography. Oligo(dT)-cellulose binding capacity of the oligo(U)-poly(A) duplexes is abolished by prior titration of the nonduplex poly(A) regions with excess poly(U). The oligo(dT)-purified fraction is 97.5 mole % A + U and the [3H]uridine-labeled component is resistant to redigestion by pancreatic RNase at 0.5 M NaCl but not at 0.01 M NaCl. After thermal denaturation, the [3H]uridine-labeled chains become RNase-sensitive at 0.5 M NaCl. Electrophoresis of [3H]adenosine- or [3H]uridine-labeled material in polyacrylamide gels containing 99% formamide confirms that the oligo(U) sequences are not covalently linked to poly(A). Controls establish that the A-U duplexes are not formed artifactually during isolation of heterogeneous nuclear RNP or subsequent fractionation. The oligo(U)-poly(A) duplexes appear to be associated with protein in native heterogeneous nuclear RNP, as reflected by the differential pancreatic RNase sensitivity of the duplexed oligo(U) in RNP (resistant) and RNA (sensitive), measured at physiological ionic strength.

Base Sequence↗

PubMed2025

Heterogeneity Analysis of Associations Involving the Large-Scale Online MindCrowd Survey Memory Test.

INTRODUCTION: Alzheimer's disease and related disorders (ADRDs), as well as general age-related cognitive decline, are known to be multifactorial with heterogeneous etiologies. Identifying and accommodating heterogeneity in any one ADRD-related data set can be pursued using different analytical techniques, each with different assumptions or purposes. For example, whereas a great deal of research has explored clustering individuals or variables that exhibit greater similarity in some way, little research has explored evidence for heterogeneity in the relationships between relevant outcomes, such as performance on a memory test, and risk factors such as environmental exposures, behaviors, or genetic factors among individuals. METHODS: We explored evidence of heterogeneity in the relationships between ability on a memory test, specifically the paired associate learning (PAL) test, and multiple social and demographic risk factors using the large MindCrowd study database (n > 90,000 individuals). We focused on mixtures of regression models but compared models assuming many interaction effects among independent variables as well as random effects. RESULTS: We ultimately find substantial evidence for heterogeneity and offer an intuitive explanation for it involving individual motivation for participating in the MindCrowd study. Basically, we argue that our mixture of regression model analysis results suggest that a smaller group of individuals (∼16%) likely participated in the MindCrowd study out of a concern for their cognitive abilities as they exhibit stronger and statistically significant negative associations between age, number of medications they are on, some ancestries, and the number correct on the PAL test. They also exhibit stronger positive associations between education and PAL test results in a dose-dependent manner suggesting that a "cognitive reserve" associated with greater education could benefit them. Analysis models assuming interaction terms and random effects suggested that other forms of heterogeneity in the relationships between variables exist in the data set, but their results do not carry with them the same intuitive explanation that the results of the mixture model analyses do. CONCLUSION: We find evidence for heterogeneity in the relationships between social and demographic variables and PAL test results in the large MindCrowd study database. This heterogeneity is likely due to individuals with and without concerns for their cognitive abilities participating in the study. We also find other types of evidence in the data set. Our results should motivate caution in the use of large epidemiological study or survey-oriented data sets to build predictive models of clinical or subclinical pathologies without exploring or accommodating heterogeneity. Our results also suggest that one should include questions about motivation to participate in large epidemiological studies since different motivations may impact important relationships between independent and dependent variables.

Humans↗

PubMed2025

Multi-omic underpinnings of heterogeneous aging across multiple organ systems.

Aging is the main determinant of chronic diseases and mortality, yet organ-specific aging trajectories vary, and the molecular basis underlying this heterogeneity remains unclear. To elucidate this, we integrated genomic, epigenomic, transcriptomic, proteomic, and metabolomic data, employing post-genome-wide association study methodologies to systematically investigate the molecular mechanisms of nine organ-specific aging clocks and four blood-based epigenetic clocks. We uncovered genetic correlations and specific phenotypic clusters among these aging-related traits, identified prioritized genetic drug targets for heterogeneous aging, and elucidated downstream proteomic and metabolomic effects mediated by heterogeneous aging. We constructed a cross-layer molecular interaction network of heterogeneous aging across multiple organ systems and characterized detectable biomarkers of this heterogeneity. Integrating these findings, we developed an R/Shiny-based framework that provides a comprehensive multi-omic molecular landscape of heterogeneous aging, thereby advancing the understanding of aging heterogeneity and informing precision medicine strategies to delay organ-specific aging and prevent or treat its associated chronic diseases.

Aging↗

PubMed2025

Robustness of Ancestral Sequence Reconstruction to Among-site and Among-lineage Evolutionary Heterogeneity.

Ancestral sequence reconstruction is typically performed using homogeneous evolutionary models, which assume that the same substitution propensities affect all sites and lineages. These assumptions are routinely violated: heterogeneous structural and functional constraints favor different amino acids at different sites, and these constraints often change among lineages as epistatic substitutions accrue at other sites. To evaluate how violations of the homogeneity assumption affect ancestral sequence reconstruction under realistic conditions, we developed site-specific substitution models and parameterized them using data from deep mutational scanning experiments on three protein families; we then used these models to perform ancestral sequence reconstruction on the empirical alignments and on alignments simulated under heterogeneous conditions derived from the experiments. Extensive among-site and -lineage heterogeneity is present in these datasets, but the sequences reconstructed from empirical alignments are almost identical when heterogeneous or homogeneous models are used for ancestral sequence reconstruction. Using models fit to deep mutational scanning data from distantly related proteins in which mutational effects are very different also has a minimal impact on ancestral sequence reconstruction. The rare differences occur primarily where phylogenetic signal is weak-at fast-evolving sites and nodes connected by long branches. When ancestral sequence reconstruction is performed on simulated data, errors in the reconstructed sequences become more likely as branch lengths increase, but incorporating heterogeneity into the model does not improve accuracy. These data establish that ancestral sequence reconstruction is robust to unincorporated realistic forms of evolutionary heterogeneity, because the primary determinant of ancestral sequence reconstruction is phylogenetic signal, not the substitution model. The best way to improve accuracy is therefore not to develop more elaborate models but to apply ancestral sequence reconstruction to densely sampled alignments that maximize phylogenetic signal at the nodes of interest.

Phylogeny↗

PubMed1979

Ontogeny of B-lymphocyte function. IX. Difference in the time of maturation of the capacity of B lymphocytes from foetal and neonatal mice to produce a heterogeneous antibody response to thymic-dependent and thymic-independent antigens.

The ontogeny of the capacity of the B-lymphocyte population to produce a response which is heterogeneous with respect to antibody affinity was studied in a cell transfer system. Lethally irradiated mice were reconstituted with B cells from donors of various ages, together with adult thymus cells when the response to T-dependent antigens was studied. The animals were immunized with one of a variety of antigens one day after cell transfer and the distribution of their splenic plaque-forming cells (PFC) with respect to affinity was assayed, by hapten inhibition of plaque formation, 2 to 3 weeks after immunization. Mice reconstituted with B cells from neonatal donors produced a response of low affinity and restricted heterogeneity. With four different thymic-dependent antigens (DNP-BGG, F-BGG, DNP-KLH and Dan-KLH) the splenic B-cell population acquired the capacity to reconstitute irradiated mice to produce a normal adult-like, highly heterogeneous, high affinity PFC response between 7 and 10 days after birth. The capacity to produce a heterogeneous response to the thymic-dependent protein antigen BGG matured just slightly later between 10 and 14 days of age. The bone marrow matures with regard to the capacity to reconstitute irradiated mice to give a heterogeneous response several days after the spleen, possibly as a consequence of the redistribution of peripheral B cells to the bone marrow. In contrast, maturation of the capacity of the splenic B-cell population to reconstitute irradiated recipients to give a heterogeneous, adult-like PFC response to three 'thymic-independent' antigens (TNP-PA, DNP-Ficoll and TNP-BA) takes place considerably later (between 3 and 4 weeks of age). These results suggest that the population of B-cell precursors which responds to thymic-dependent antigens may represent a different subpopulation of B cells from the population that responds to thymic independent antigens. Furthermore, the results suggest that these B-cell subsets mature at different times, presumably under independent controls.

Age Factors↗

PubMed2026

Multiregion profiling of genomic and transcriptional heterogeneity in head and neck squamous-cell carcinoma.

BACKGROUND: Intratumoral heterogeneity (ITH) is thought to contribute to tumour evolution and treatment resistance but its biological and clinical significance in localised head and neck squamous-cell carcinoma (HNSCC) remains incompletely understood. PATIENTS AND METHODS: In the prospective SCANDARE study, we analysed 87 patients with resectable HNSCC treated with upfront surgery. Two to five spatially distinct tumour regions per patient underwent pathological evaluation, targeted DNA sequencing, and bulk RNA sequencing. Genomic ITH (gITH) was quantified using clonal deconvolution and Shannon diversity indices, whereas transcriptional heterogeneity (tITH) was assessed using the intratumour expression distance metric. Associations between ITH, molecular features, tumour microenvironment composition, and clinical outcomes were explored using multivariable statistical models. RESULTS: Pathology-based spatial heterogeneity showed limited prognostic value. gITH was common, with 37% of tumours displaying regionally heterogeneous pathogenic variants, including spatially actionable alterations in 10% of patients. In an initial multivariable Cox model, higher gITH was associated with shorter disease-free survival. However, after Ridge-penalised modelling and bootstrap internal validation, the effect size was attenuated [corrected hazard ratio 1.42, 95% confidence interval (CI) 0.91-2.75]. The overall model retained moderate discriminative performance (optimism-corrected C-index 0.69, 95% CI 0.59-0.79). gITH was associated with tumour cellularity, reduced estimated endothelial cell infiltration, and alterations in KMT2C and PIK3CA. tITH differed according to human papillomavirus (HPV) status, with lower tITH in HPV-positive tumours, and was associated with distinct biological pathways and genomic alterations. Genomic and tITH were not correlated. CONCLUSIONS: This prospective multiregion study provides a comprehensive characterisation of genomic and tITH in localised HNSCC. Our findings highlight substantial spatial molecular diversity within primary tumours and suggest potential associations between heterogeneity, tumour biology, and clinical outcome that warrant validation in independent cohorts.

head and neck squamous-cell carcinoma (HNSCC)↗

PubMed2025

Unveiling non-small cell lung cancer treatment effect heterogeneity: a comparative analysis of statistical methods.

BACKGROUND: For patients with advanced non-small cell lung cancer lacking targetable genomic alterations, the impact of clinicogenomic characteristics on the effectiveness of combining chemotherapy with immunotherapy is unclear. METHODS: We evaluated 4 statistical methods for detecting heterogeneous treatment effects related to clinical factors, including programmed death-ligand 1 expression, tumor mutation burden, and stage at diagnosis, using the American Association for Cancer Research Project Genomics Evidence Neoplasia Exchange BioPharma Collaborative dataset supplemented with institutional data collected under the same data curation model. A 2-sided P value of no more than .05 was used to denote statistical significance for all analyses. RESULTS: The mixture model revealed 2 latent subgroups: in one subgroup, there was no meaningful treatment effect, with average progression-free survival (PFS) only 5% longer with immunotherapy alone (95% confidence interval [CI] = -19% to 35%); in the second subgroup, immunotherapy alone was associated with a 35% decrease in average PFS (95% CI = -59% to 2%), corresponding to a ratio in treatment effects of 1.62 (95% CI = 1.02 to 2.57). There was a marginal association between lower tumor mutation burden levels and membership in the subgroup with improved PFS following receipt of chemoimmunotherapy. The causal survival forest highlighted the importance of tumor mutation burden (variable importance ranking: 1) and programmed death-ligand 1 (variable importance ranking: 3) when assessing heterogeneity. In contrast, the accelerated failure time and Cox proportional hazards models did not detect any statistically significant heterogeneous treatment effects. In simulations, the mixture model identified heterogeneous treatment effects more frequently than other methods, especially with weak covariate relationships, demonstrating its utility for informing personalized treatment approaches. CONCLUSIONS: The application of novel statistical methods to large scale clinico-genomic databases offers an opportunity to more accurately identify heterogeneous treatment effects in some settings as compared to traditional statistical methods. Applying such methods to the AACR Project GENIE BPC non-small cell lung cancer data indicated a potential association between decreasing tumor mutation burden and improved outcomes with chemoimmunotherapy as compared to immunotherapy alone.

Humans↗

PubMed1976

Resolution in affinity chromatography. The effect of the heterogeneity of immobilized soybean trypsin inhibitor on the separation of pancreatic proteases.

By affinity chromatography, trypsins and chymotrypsins from mouse pancreas homogenates have been separated using soybean trypsin inhibitor immobilized on Sepharose. The effects of the functional heterogeneity of the adsorbent have been investigated in terms of the resolution obtained. Heterogeneity of the adsorbent have been investigated in terms of the resolution obtained. Heterogeneity has been found to originate from the following sources: heterogeneity of the ligand before immobilization; alteration of the ligand by immobilization; and modification of the ligand after immobilization by molecules to be fractionated. Only when the heterogeneity of the adsorbent was minimized could the resolution of closely related enzyme species be achieved. The elution conditions for different enzymes depended on the amount of enzyme applied, as no complete homogeneity could be obtained. In addition, it was found that the adsorbent was partly degraded by the pancreas extract, reducing its fractionating capacity.

Adsorption↗

PubMed2025

H3K27me3 chromatin heterogeneity reveals variable cell responses to estrogen and endocrine treatment.

Gene expression heterogeneity generates subpopulations of tumor cells that can evade therapeutic pressure. This heterogeneity has been observed in both primary Estrogen Receptor alpha positivebreast tumors and cell lines. Therefore, understanding the mechanisms regulating expression heterogeneity is critical towards developing effective therapies. A key contributor to gene expression variability is the stochastic nature of transcription. Transcription occurs in a probabilistic, burst-like manner, in which gene activation occurs intermittently, producing RNA in pulses and interspersed with transcriptional off-periods. The estrogen-responsive gene TFF1 is expressed in the majority ofbreast tumors and exemplifies such heterogeneity, with transcriptional inactivity ranging from minutes to several days. Here, we identify the molecular mechanism underlying the wide range in TFF1 expression by analyzing cells sorted based on their TFF1 activity levels. We observed that TFF1 inactive (TFF1low) cells exhibit a repressive chromatin state marked by H3K27me3 at the TFF1 promoter and enhancer. Despite global similarity inbinding, occupancy at the TFF1 regulatory elements was selectively reduced in TFF1low cells, resulting in fewer active alleles and diminished transcriptional bursting frequency. Conversely, TFF1high cells exhibited more active TFF1 alleles and hyperbursting. These cells also retained sensitivity to endocrine therapy, while TFF1low cells displayed reduced drug responsiveness. Genome-wide, differentially enriched H3K27me3 regions correlated with variable expression of estrogen-responsive genes, highlighting a broader regulatory mechanism that links chromatin state to expression variability. Together, our findings establish how repressive chromatin dynamics contribute to gene expression heterogeneity and endocrine resistance inbreast cancer.

Journal Article↗

PubMed1979

Comparison of heterogeneities of antitrinitrophenyl antibodies in strains of mice immunized by various methods.

Heterogeneity of antibodies directed against the trinitrophenyl (TNP) determinant in immunized mice was analyzed by investigating the band groups of antibodies formed by thin layer isoelectric focusing of serum. The degree of heterogeneity in C57BL/6 mice was markedly higher than that in CBA mice under the following conditions of immunization: immunization with TNP conjugated with bovine gamma-globulin or ovalbumin, interchange of these carrier proteins at the first and second injections, change of epitope density of the antigens, replacement of the hapten by dinitrophenyl group on the antigen for the secondary stimulation, and change of intervals of these injections from 15 days to five months. The degree of heterogeneity within a strain also varied with these immunizing conditions. Furthermore, the heterogeneity in C57BL/6 mice of any immunization group was greater than that in CBA mice in any group. This was also true when the heterogeneity was examined with the immune sera diluted to the same titer. These results indicate that the number of predominant clones of cells producing anti-TNP antibody after immunization is larger in C57BL/6 than in CBA mice.

Animals↗

PubMed2025

The Heterogeneity of Type 1 Diabetes: Implications for Pathogenesis, Prevention, and Treatment-2024 Diabetes, Diabetes Care, and Diabetologia Expert Forum.

This article summarizes the current understanding of the heterogeneity of type 1 diabetes from a June 2024 international Expert Forum organized by the editors of Diabetes, Diabetes Care, and Diabetologia. The Forum reviewed key factors contributing to the development and progression of type 1 diabetes and outlined specific, high-priority research questions. Knowledge gaps were identified, and, notably, opportunities to harness disease heterogeneity to develop personalized therapies were outlined. Herein, we summarize our discussions and review the heterogeneity of genetic risk and immunologic and metabolic phenotypes that influence and characterize type 1 diabetes progression (presented as a palette of risk factors). We discuss how these age-related factors determine disease aggressiveness (along gradients) and describe how variable immunogenetic pathways aggregate (into networks) to affect β-cell and other pancreatic pathologies to cause clinical disease at different ages and with variable severity (described as disease-related thresholds). Heterogeneity of pathogenesis and clinical severity opens avenues to prevention and intervention, including the potential of disease-modifying immunotherapy and islet cell replacement. We conclude with a call for 1) continued research to identify more factors contributing to the disease, both overall and in specific subgroups; 2) investigations focusing on both individuals who surpass metabolic and immune thresholds and develop diabetes and those who remain disease free with the same level of immunogenetic risk; and 3) efforts to identify where the current type 1 diabetes staging system may fall short and determine how it can be improved to capture and leverage heterogeneity in prevention and intervention strategies.

Humans↗

PubMed1979

[Importance of the sialic acid moiety for the heterogeneity in human fibrinogen].

To determine whether the observed heterogeneity of gamma- and B beta-polypeptide chains of human fibrinogen (2 and 1 sialic acid residue per chain) is due to differences in sialic acid content, fibrinogen was desialatgen was compared with normal fibrinogen. The gamma-chain heterogeneity observed in normal fibrinogen was absent in asialofibrinogen, whereas the B beta-chain heterogeneity appeared to be unaffected. Although the variants were indistinguishable on SDS-PAGE, isoelectric focusing in the presence of urea demonstrated heterogeneities of both gamma- and B beta-cahins even in asialofibrinogen. However, fewer bands were recognized in asialofibrinogen. The difference in sialic acid content of the gamma- and B beta-chain variants of human fibrinogen therefore explains on part of the polypeptide chain heterogeneity.

Chromatography, Ion Exchange↗

PubMed2025

Deep Learning on Histologic Slides Accurately Predicts Consensus Molecular Subtypes and Spatial Heterogeneity in Colon Cancer.

Colon cancer (CC) is the third most prevalent cancer type. It is highly heterogeneous, particularly in terms of molecular profiles, which have both prognostic and predictive impacts on the treatment efficacy. However, CC treatment in adjuvant situations is currently guided solely by T and N staging. In this context, consensus molecular subtypes (CMSs) were introduced to stratify patients with CC based on molecular profiles. Recent studies have shown that CMS can be heterogeneous in CC, leading to a worse prognosis. This study focused on predicting CMS and its heterogeneity in CC using deep learning on digitized hematoxylin and eosin ± saffron-stained whole-slide images. Data and whole-slide images of 1996 patients from the PETACC-8, The Cancer Genome Atlas-COAD, and PRODIGE-13 cohorts were used. The model is trained to predict a 4-dimensional CMS vector, reflecting intratumor heterogeneity (ITH). It comprises a self-supervised model for embedding image patches into vectors and a weakly supervised model predicting CMS calls. Ground-truth CMS scores are obtained with the CMSclassifier package. Interpretability analyses are performed at the slide and patch levels. For homogeneous tumors, the model trained on PETACC-8 achieves 93.0% (±1.4%) macroaverage area under the curve in internal cross-validation and 94.4% macroaverage area under the curve in external validation over PRODIGE-13, whereas the The Cancer Genome Atlas-COAD model reaches 85.4% (±3.0%) in cross-validation and 92.4% over PRODIGE-13. The trained models also provide spatial distributions of CMS across tumor slides and associate specific histologic features with each CMS. Finally, the models are able to predict ITH. The results show that a deep learning model trained on routine histology slides is capable of providing an efficient and robust method for predicting CMS and characterizing a patient's ITH, paving the way for the routine consideration of CMS/ITH in clinical decision making in the adjuvant setting.

Humans↗

PubMed2026

Multi-sampling allows intra-tumoral heterogeneity querying and vulnerability profiling in glioblastoma.

BACKGROUND: Glioblastoma (GBM) remains a devastating cancer with limited treatment options, largely due to its heterogeneity. While supramaximal resection has recently provided survival benefits, therapeutic profiling of different tumor compartments, particularly its infiltrative edge remains largely unexplored. METHODS: Here, we leveraged magnetic resonance imaging (MRI)-guided multi-sampling, collecting 2 cores and 2 margins per case, to query GBM heterogeneity. Whole-exome and RNA-seq with drug testing in two patient-derived 3D models were used to reveal similarities and differences in genomic and transcriptomic makeups, cellular compositions, and drug responses across cores and margins. Bioinformatics interrogations further identified response biomarkers. RESULTS: Mutation analysis showed that oncogenes exhibited a higher degree of spatial heterogeneity than tumor suppressor genes, regardless of MRI status. While the mesenchymal transcriptional subtype with extracellular matrix remodeling, stress response, and immune programs were preferentially enriched in enhancing cores, proneural tumors with neurological processes favored non-enhancing margins. Using a 15-drug GBM-targeted panel, ERK (ulixertinib) and PI3K pathway (paxalisib, CC-115) inhibitors showed preferential efficacy in enhancing cores and non-enhancing margins, respectively. The anti-apoptosis, pan-Bcl2 agent navitoclax and the epigenetic drug trotabresib represented the most effective, tumor-wide monotherapies. Importantly, drug combinations generally outperformed single agents across all regions. CONCLUSIONS: This work demonstrates the regional heterogeneity of therapeutic vulnerabilities in GBM ex vivo, showing various drugs with tumor-wide or MRI-enhancement informed activity. These findings offer preclinical bases of numerous monotherapies and drug combinations for future clinical trial design.

Humans↗

PubMed2026

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive genomic, cellular, spatial, and microenvironmental heterogeneity. Multi-omics studies have revealed that GBM follows complex evolutionary trajectories involving genetic, epigenetic, transcriptional, and immune-microenvironmental remodeling as tumors grow, adapt to the brain microenvironment, and acquire therapeutic resistance. Increasing evidence suggests that GBM may originate from aberrant neural stem or progenitor cells, including those residing in the subventricular zone, and that glioblastoma stem cells (GSCs) contribute to tumor propagation, heterogeneity, and recurrence. A key conceptual challenge is to reconcile hierarchical cancer stem cell models, in which GSCs are viewed as relatively stable tumor-propagating subpopulations, with dynamic state plasticity models, in which stem-like properties can be reversibly acquired or lost during transitions among proneural-like, mesenchymal-like, invasive, and therapy-tolerant states. Recent advances in single-cell profiling, spatial transcriptomics, lineage tracing, organoid culture, 3D bioprinting, genetically engineered models, and artificial intelligence (AI)-assisted computational modeling have substantially improved the ability to study these processes. However, no currently available model fully recapitulates human GBM heterogeneity, recurrence, treatment history, and tumor-microenvironment interactions. Therefore, model selection should be guided by clearly defined mechanistic questions rather than by reliance on any single platform. This review summarizes current advances in in vitro, ex vivo, in vivo, and computational models for studying GBM evolution and heterogeneity, and discusses how integrated model pipelines may improve preclinical drug testing, treatment-response prediction, and precision neuro-oncology.

Humans↗

PubMed2026

Heterogeneity in Teriflunomide Treatment Arms: A Systematic Review and Meta‑Regression of Randomised Multiple Sclerosis Trials.

BACKGROUND: Teriflunomide is widely used as an active comparator in Phase 3 randomised trials for relapsing multiple sclerosis (RMS). Temporal changes in disease activity within teriflunomide-treated cohorts have not been systematically examined. OBJECTIVES: To assess temporal trends in relapse and disability outcomes across teriflunomide arms of Phase 3 multiple sclerosis (MS) trials and identify predictors of between-trial heterogeneity. METHODS: We performed a systematic review and meta-analysis of Phase 3 randomised controlled trials including a teriflunomide arm. PubMed, Scopus, and ClinicalTrials.gov were searched up to October 2025. Annualised relapse rate (ARR) and 12- and 24-week confirmed disability worsening (CDW) were extracted together with baseline characteristics. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool. Random-effects meta-analyses, meta-regression, and sensitivity analyses were performed. RESULTS: Twelve teriflunomide cohorts from eight trials involving 4,900 adults with RMS were included. ARR ranged from 0.11 to 0.37 with substantial heterogeneity (I2 = 94%). Trial start year was inversely associated with ARR and explained a large proportion of between-study variability in exploratory meta-regression analyses. Confirmed disability worsening outcomes also showed substantial heterogeneity with a weaker trend toward lower event rates in more recent trials. CONCLUSION: Teriflunomide-treated trial populations have shifted toward lower relapse activity over time, and trial start year was the principal predictor of between-trial heterogeneity in ARR in exploratory analyses. These findings most plausibly reflect evolving recruitment and diagnostic practices rather than changes in drug efficacy. Accounting for these temporal dynamics is essential when interpreting outcomes from RMS trial using teriflunomide as comparator.

Humans↗

PubMed1977

Structural heterogeneity of the cytoplasmic and outer membranes of Escherichia coli.

The cytoplasmic and outer membranes of gram-negative bacteria can be isolated from spheroplasts, and separated on sucrose density gradients. Lysis of spheroplasts causes extensive membrane fragmentation and since the characteristics of the fragments obtained by different lysis procedures need not be identical, the influence of the disruption method on membrane composition has been examined. Spheroplasts of Escherichia coli J5 were lysed by osmotic shock, which did not significantly separate the cytoplasmic and outer membranes, but resulted in mixed membrane vesicles. Lysis in the French press and by sonication caused extensive membrane fragmentation and separation. Sonication, however, also caused some fusion between fragments of the outer and the cytoplasmic membranes; this intermembrane fusion increased with sonication time. When the cytoplasmic and outer membranes were well separated and intermembrane fusion was minimal or absent, the cytoplasmic and outer membrane fragments were heterogeneous with respect to density and ovarll phospholipid, protein and lipopolysaccharide composition. In addition, cytoplasmic, but not outer, membrane fragments were also heterogeneous with respect to protein composition. It is concluded, therefore, that membrane fragments obtained from the cytoplasmic and outer membranes are heterogeneous independently of the lysis procedures used to obtain these fragments. Possible reasons for this heterogeneity are discussed.

Bacterial Proteins↗