Distinct Subtypes Research Articles

Radiographic features and subtypes of congenital thumb duplication type C3 according to Wu et al. and their potential implications for surgical management: new classification and preliminary results

BackgroundWu et al. introduced a modified radiographic system that allows classification of all forms of CTD with excellent interobserver and intraobserver reliability. No study to date has evaluated the radiographic characteristics of Wu et al. type C3 CTD with osseous attachment at the level of the metacarpal.ObjectiveThis study aimed to evaluate the radiographic features of type C3 CTD according to the system of Wu et al., to describe the different anatomical subtypes of the duplication, and to propose a categorization approach to distinguish diverse surgical strategies based on the radiographic anatomy of this specific subtype of duplication.MethodsWe performed a retrospective analysis of 215 patients (221 thumbs) diagnosed with Wu et al. type C3 CTD at our Institution between 2015 and 2021. We evaluated all CTDs by examining the alignment of the interphalangeal (IP) and metacarpophalangeal (MP) joints and by assessing the presence of abnormal hypertrophic epiphysis of the primary thumb on posteroanterior (PA) radiographs. The proposed classification system has four types: Type I with good alignment of both MP and IP joints, Type II with ulnar deviation of the MP joint, Type III with radial deviation in the MP joint and Type IV with abnormal hypertrophic epiphysis of the distal phalanx of the main thumb with ulnar deviation of the IP joint with or without ulnar deviation of the MP joint.ResultsThere were 140 male and 75 female patients with CTD (221 thumbs). There were 65 left, 144 right and 6 bilateral forms. The right-to-left, male-to-female and unilateral-to-bilateral ratios were 2.2:1, 1.9:1 and 35.8:1 respectively. The mean age at surgery was 22.3 ± 11.8 months (range, 8–80). The proposed classification system allowed the classification of all CTDs (n = 221). Specifically, 53 fingers were classified as Type I (24%), 136 as Type II (61.5%), 21 as Type III (9.5%), and 11 as Type IV (5%).ConclusionThe proposed system is based on radiographic pathoanatomy and complements that of Wu et al. by identifying four distinct subtypes of deformity. It has the potential to improve inter-professional communication and guide surgery in patients with Wu et al. type C3 CTD. However, our results are preliminary and further research is needed to validate them.Level of evidenceIII.

Prognostic Prediction and Immune Microenvironment Characterization in Uveal Melanoma: A Novel Mitochondrial Metabolism-Related Gene Signature.

Uveal Melanoma (UM), a highly aggressive and metastatic intraocular cancer with a strong propensity for liver metastasis, presents limited therapeutic alternatives and unfavorable survival outcomes. Despite its low incidence, the underlying mechanisms of UM pathogenesis and the precise role of mitochondrial metabolism in UM remain inadequately understood. Utilizing Cox proportional hazards regression analysis was used to assess prognostic relevance, and consensus clustering was employed for molecular subtyping. A risk signature was constructed using Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression. We further conducted comparative analyses on clinicopathological characteristics, somatic mutation profiles, drug sensitivity, gene expression patterns, and tumor microenvironment features across different molecular subtypes. Moreover, a nomogram was developed and evaluated. Among 1234 mitochondria metabolism-related genes (MMRGs), 343 were identified as significantly associated with the prognosis of UM. These prognosis-associated MMRGs facilitated the classification of UM into two distinct molecular subtypes, which displayed notable differences in prognosis and pathological staging. Furthermore, an index termed the MMRGs-derived index (MMI) was derived from eight MMRGs, serving as a quantitative measure for poor prognosis risk in UM. MMI demonstrated significant associations with clinicopathological characteristics, somatic mutations, drug responsiveness, and the tumor microenvironment, where higher MMI levels corresponded to worse prognosis, advanced pathological stages, and increased immune cell infiltration. The nomogram built upon MMI provided a potential tool for clinical prognosis assessment in UM patients. This study demonstrated the potential value of MMRGs in predicting prognosis and molecular stratification within UM; however, additional clinical and basic research is warranted to validate their applicability and elucidate the related mechanisms.

Cancer-Associated Fibroblast Subtypes Reveal Distinct Gene Signatures in the Tumor Immune Microenvironment of Vestibular Schwannoma.

Cancer-associated fibroblast (CAF) composition within the same organ varies across different cancer subtypes. Distinct CAF subtypes exhibit unique features due to interactions with immune cells and the tumor microenvironment. However, data on CAF subtypes in individuals with vestibular schwannoma (VS) are lacking. Therefore, we aimed to distinguish CAF subtypes at the single-cell level, investigate how stem-like CAF characteristics influence the tumor immune microenvironment, and identify CAF subtype-specific metabolic reprogramming pathways that contribute to tumor development. Data were analyzed from three patients with VS, encompassing 33,081 single cells, one bulk transcriptome cohort, and The Cancer Genome Atlas Pan-Cancer database (RNA sequencing and clinical data). Our findings revealed that antigen-presenting CAFs are linked to substantially heightened immune activity, supported by metabolic reprogramming, which differs from tumorigenesis. High expression of the stem-like CAF gene signature correlated with poor prognosis in low-grade gliomas within the pan-cancer database. This is the first study to classify CAF subtypes in VS patients and identify a therapeutic vulnerability biomarker by developing a stem-like CAF gene signature. Personalized treatments tailored to individual patients show promise in advancing precision medicine.

Advancements in Imaging for the Diagnosis of Wake-up Stroke.

The concept of wake-up stroke (WUS) as a distinct subtype of acute ischaemic stroke, characterized by an uncertain onset time, traditionally resulted in the exclusion of patients from intravenous thrombolysis treatment. Advancements in neuroimaging have prompted a shift in the approach to intravenous thrombolysis treatment, moving away from a strict focus on the onset time window toward consideration of the tissue time window. This paradigm shift has expanded the opportunity for a larger cohort of patients with WUS to receive timely and effective treatment, ultimately leading to improved prognosis. This study reviews the WUS pathogenesis and the progress of various imaging diagnostic techniques to clarify the WUS onset time and select the optimal treatment plan.

Clinicopathologic features and prognosis of steatohepatitic hepatocellular carcinoma based on varying cutoffs of tumoral steatohepatitic changes.

Steatohepatitic hepatocellular carcinoma (SH-HCC) is currently recognized as a distinct histologic subtype of HCC. The prognosis and specific criteria for determining the amount of steatohepatitis required to define SH-HCC are still unclear. After excluding all recognized HCC subtypes from 505 HCC cases (2010-2019), the remaining cases were categorized as conventional HCC (CV-HCC) (n = 223). The cases classified as SH-HCC (n = 171) were further divided into groups based on the percentage of steatohepatitis: 5% or more, 30% or more, and 50% or more. Hepatitis C virus infection was the predominant underlying liver disease in both the CV-HCC and SH-HCC groups. Metabolic dysfunction-associated steatotic liver disease (formerly nonalcoholic fatty liver disease) was more prevalent in all cases of SH-HCC with different steatohepatitic cutoffs than in cases of CV-HCC. There were no differences in the stage of fibrosis of the background liver between the CV-HCC and SH-HCC groups. SH-HCC with different cutoffs exhibited a notable increase in the presence of glycogenated nuclei, Mallory-Denk bodies, and hyaline globules in tumor cells. Survival analysis did not reveal substantial differences in overall survival between the CV-HCC and SH-HCC groups and among patients with SH-HCC with different steatohepatitis cutoffs. The degree of intratumoral steatohepatitis in patients with SH-HCC does not appear to be a notable prognostic factor. The presence of steatohepatitis in the tumor is better recognized as 1 of the histopathologic patterns of HCC.

Exploring transmission dynamics of the Sarcoptes scabiei mite in humans by combining molecular typing and epidemiological variables, the Netherlands 2016–2023

BackgroundScabies, an infestation of the mite Sarcoptes scabiei, has seen an increase in clinical diagnoses in the Netherlands since 2011. This study aimed to analyse PCR-positive S. scabiei skin samples through partial genome sequencing and to link findings to patient epidemiological characteristics.MethodsSkin samples were collected from individuals in the Netherlands between January 2016 and January 2023. On the PCR-positive S. scabiei skin samples, partial mitochondrial cytochrome c oxidase subunit 1 gene (cox1) sequencing was performed to assess genetic variability. Epidemiological information was collected through interviews. We examined associations between cox1 subtypes, epidemiological factors and treatment outcomes.ResultsSequencing results were obtained from 128 patients, with epidemiological information available for 55 (43%) of these patients. Fifteen distinct cox1 subtypes were identified. Subtype 01 was most prevalent (45%) and present across all age groups and social settings. The remaining subtypes were less common and not consistently found in all contexts. Five clusters were identified, each with identical cox1 subtypes. Comparative analysis with GenBank sequences revealed genetic similarities with strains from Australia, the USA and China, suggesting the global distribution and transmission of specific subtypes. A substantial proportion (73%) of patients with scabies required multiple treatments to eradicate the infestation, with no subtype-related differences.ConclusionsThis is the first study linking S. scabiei sequencing results to patient epidemiological data. Several subtypes clustered in specific geographic regions and social contexts, underscoring localised transmission patterns. Further research with larger sample sizes is needed to enhance our understanding of the transmission of this mite. This study provides valuable insights that will strengthen scabies control efforts.Graphical

Multiple Brain Activation Patterns for the Same Perceptual Decision-Making Task.

Meaningful variation in internal states that impacts cognition and behavior remains challenging to discover and characterize. Here we leveraged trial-to-trial fluctuations in the brain-wide signal recorded using functional MRI to test if distinct sets of brain regions are activated on different trials when accomplishing the same task. Across three different perceptual decision-making experiments, we estimated the brain activations for each trial. We then clustered the trials based on their similarity using modularity-maximization, a data-driven classification method. In each experiment, we found multiple distinct but stable subtypes of trials, suggesting that the same task can be accomplished in the presence of widely varying brain activation patterns. Surprisingly, in all experiments, one of the subtypes exhibited strong activation in the default mode network, which is typically thought to decrease in activity during tasks that require externally focused attention. The remaining subtypes were characterized by activations in different task-positive areas. The default mode network subtype was characterized by behavioral signatures that were similar to the other subtypes exhibiting activation with task-positive regions. These findings demonstrate that the same perceptual decision-making task is accomplished through multiple brain activation patterns.

Integrative Analysis of ATAC-Seq and RNA-Seq through Machine Learning Identifies 10 Signature Genes for Breast Cancer Intrinsic Subtypes.

Breast cancer is a heterogeneous disease composed of various biologically distinct subtypes, each characterized by unique molecular features. Its formation and progression involve a complex, multistep process that includes the accumulation of numerous genetic and epigenetic alterations. Although integrating RNA-seq transcriptome data with ATAC-seq epigenetic information provides a more comprehensive understanding of gene regulation and its impact across different conditions, no classification model has yet been developed for breast cancer intrinsic subtypes based on such integrative analyses. In this study, we employed machine learning algorithms to predict intrinsic subtypes through the integrative analysis of ATAC-seq and RNA-seq data. We identified 10 signature genes (CDH3, ERBB2, TYMS, GREB1, OSR1, MYBL2, FAM83D, ESR1, FOXC1, and NAT1) using recursive feature elimination with cross-validation (RFECV) and a support vector machine (SVM) based on SHAP (SHapley Additive exPlanations) feature importance. Furthermore, we found that these genes were primarily associated with immune responses, hormone signaling, cancer progression, and cellular proliferation.

Biallelic and monoallelic variants in EFEMP1 can cause a severe and distinct subtype of heritable connective tissue disorder.

Variants in EFEMP1, encoding Fibulin-3, were previously reported as a rare cause of heritable connective tissue disorder (HCTD) with recurrent hernias and joint hypermobility. We report three new cases with biallelic or monoallelic EFEMP1 variants and severe hernia phenotypes. Two male siblings of 10 and 13 years old presented with marfanoid habitus, recurrent inguinal and umbilical hernias, generalized joint hypermobility, and scoliosis. Parents and halfsiblings reported joint hypermobility and umbilical hernias. The eldest boy died at age 16 from incarcerated gastrointestinal herniation complicated by gastric and bowel necrosis with perforation. Autopsy revealed widespread intestinal diverticula. Immunohistochemistry of skin and fascia tissue did not reveal any abnormalities, including normal staining of elastic fibers. Both siblings harbored compound heterozygous likely pathogenic EFEMP1 variants (c.1320 + 2T > A, p.? and c.698G > A, p.Gly233Asp). An unrelated 58-year-old male had marfanoid features, high myopia, recurrent diaphragmatic and inguinal hernias, and chronic gastrointestinal dilatation with severe malabsorption. Both his dizygotic twin-brother and mother had recurrent hernias and high myopia. This man died at 59 years of age, and autopsy showed extensive diaphragmatic herniation, bowel diverticula, and pulmonary emphysema. A heterozygous EFEMP1 splice-variant (c.81 + 1G > A, p.?) was identified, causing exon skipping leading to a start-loss. Targeted genome reanalysis nor RNA-sequencing revealed a second variant at the other allele. The reported individuals expand the clinical and pathological phenotypes of EFEMP1-related disease, a distinct entity within the spectrum of HCTD. The severe and recurrent hernias, gastrointestinal dilatation, and diverticulosis result in an increased risk for life-threatening complications, demanding early recognition and close monitoring.

Comprehensive transcriptomic analysis identifies three distinct subtypes of pituitary adenomas: insights into tumor behavior, prognosis, and stem cell characteristics

BackgroundPituitary adenomas (PAs) are the second most common intracranial tumor. While current diagnostic practices rely primarily on histological testing, they often fail to capture the molecular complexities of pituitary adenomas, underscoring the need for a molecular-based classification to refine therapeutic strategies and prognostic assessments. This study aims to provide a molecularly unbiased classification of pituitary adenomas and explore their unique gene expression patterns and clinical features.MethodsWe performed unsupervised hierarchical clustering of the gene expression profiles of 117 PA samples to identify three distinct molecular subtypes. Subsequently, we analyzed the compiled transcriptomic profiles of each individual subtype for pathway enrichment. We also validated the new classification with a validation set containing 158 PAs and 24 pituitary adenoma stem cells (PASCs).ResultsConsensus clustering of transcriptomic data from 117 pituitary adenoma (PA) samples identified three distinct molecular subtypes, each showing unique gene expression patterns and associated biological processes: Group I is enriched in signaling pathways, such as the cAMP signaling pathway and the calcium signaling pathway. Group II is primarily related to metabolic processes, including nitrogen metabolism and arginine biosynthesis in cancer. Group III predominantly shows enrichment in immune responses and potential malignant transformation of the disease, especially through cancer-related pathways such as the JAK–STAT signaling pathway and the PI3K–Akt signaling pathway. The immune profiling revealed distinct patterns for each subtype: Group I had higher dendritic cells and fewer CD8+ T cells, Group II had more monocytes and macrophages, and Group III had elevated levels of T cells. Additionally, there were differences in clinical characteristics and prognosis among the subtypes, with Group III having a worse prognosis, despite the smaller tumor size compared to other groups. Notably, differences in PASCs correlated with the molecular subtypes, with Group III stem cells being enriched in tumorigenesis pathways, PI3K–Akt signaling pathway and Ras signaling pathway.ConclusionOur study introduces a novel molecular classification for pituitary adenomas, independent of traditional histological methods. Each subtype features distinct genetic, molecular, and immunological profiles. We have isolated pituitary adenoma stem-like cells (PASCs), pairing them with tumor tissues for detailed transcriptomic analysis. These PASCs exhibit diverse molecular traits consistent with the new classification.

Likelihood adaptively incorporated external aggregate information with uncertainty for survival data.

Population-based cancer registry databases are critical resources to bridge the information gap that results from a lack of sufficient statistical power from primary cohort data with small to moderate sample size. Although comprehensive data associated with tumor biomarkers often remain either unavailable or inconsistently measured in these registry databases, aggregate survival information sourced from these repositories has been well documented and publicly accessible. An appealing option is to integrate the aggregate survival information from the registry data with the primary cohort to enhance the evaluation of treatment impacts or prediction of survival outcomes across distinct tumor subtypes. Nevertheless, for rare types of cancer, even the sample sizes of cancer registries remain modest. The variability linked to the aggregated statistics could be non-negligible compared with the sample variation of the primary cohort. In response, we propose an externally informed likelihood approach, which facilitates the linkage between the primary cohort and external aggregate data, with consideration of the variation from aggregate information. We establish the asymptotic properties of the estimators and evaluate the finite sample performance via simulation studies. Through the application of our proposed method, we integrate data from the cohort of inflammatory breast cancer (IBC) patients at the University of Texas MD Anderson Cancer Center with aggregate survival data from the National Cancer Data Base, enabling us to appraise the effect of tri-modality treatment on survival across various tumor subtypes of IBC.

First-Trimester Preeclampsia-Induced Disturbance in Maternal Blood Serum Proteome: A Pilot Study.

Preeclampsia (PE) is a complex and multifaceted obstetric syndrome characterized by several distinct molecular subtypes. It complicates up to 5% of pregnancies and significantly contributes to maternal and newborn morbidity, thereby diminishing the long-term quality of life for affected women. Due to the widespread dissatisfaction with the effectiveness of existing approaches for assessing PE risk, there is a pressing need for ongoing research to identify newer, more accurate predictors. This study aimed to investigate early changes in the maternal serum proteome and associated signaling pathways. The levels of 125 maternal serum proteins at 11-13 weeks of gestation were quantified using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with the BAK-125 kit. Ten serum proteins emerged as potential early markers for PE: Apolipoprotein M (APOM), Complement C1q subcomponent subunit B (C1QB), Lysozyme (LYZ), Prothrombin (F2), Albumin (ALB), Zinc-alpha-2-glycoprotein (AZGP1), Tenascin-X (TNXB), Alpha-1-antitrypsin (SERPINA1), Attractin (ATRN), and Apolipoprotein A-IV (APOA4). Notably, nine of these proteins have previously been associated with PE in prior research, underscoring the consistency and reliability of our findings. These proteins play key roles in critical molecular processes, including complement and coagulation cascades, platelet activation, and insulin-like growth factor pathways. To improve the early prediction of PE, a highly effective Support Vector Machine (SVM) model was developed, analyzing 19 maternal serum proteins from the first trimester. This model achieved an area under the curve (AUC) of 0.91, with 87% sensitivity and 95% specificity, and a hazard ratio (HR) of 13.5 (4.6-40.8) with p < 0.001. These findings demonstrate that serum protein-based SVM models possess significantly higher predictive power compared to the routine first-trimester screening test, highlighting their superior utility in the early detection and risk stratification of PE.

The Type I superluminous supernova catalogue I: light-curve properties, models, and catalogue description

ABSTRACT We present the most comprehensive catalogue to date of Type I superluminous supernovae (SLSNe), a class of stripped-envelope supernovae (SNe) characterized by exceptionally high luminosities. We have compiled a sample of 262 SLSNe reported through 2022 December 31. We verified the spectroscopic classification of each SLSN and collated an exhaustive data set of ultraviolet, optical, and infrared photometry totalling over 30 000 photometric detections. Using these data, we derive observational parameters such as the peak absolute magnitudes, rise and decline time-scales, as well as bolometric luminosities, temperature, and photospheric radius evolution for all SLSNe. Additionally, we model all light curves using a hybrid model that includes contributions from both a magnetar central engine and the radioactive decay of $^{56}$Ni. We explore correlations among various physical and observational parameters, and recover the previously found relation between ejecta mass and magnetar spin, as well as the overall progenitor pre-explosion mass distribution with a peak at $\approx 6.5$ M$_\odot$. We find no significant redshift dependence for any parameter, and no evidence for distinct subtypes of SLSNe. We find that only a small fraction of SLSNe, $\lt 3$ per cent, are best fit with a significant radioactive decay component $\gtrsim 50$ per cent. We provide several analytical tools designed to simulate typical SLSN light curves across a broad range of wavelengths and phases, enabling accurate K-corrections, bolometric scaling calculations, and inclusion of SLSNe in survey simulations or future comparison works.

B-201 Clinical Performance Evaluation of IRON-qPCR™ RV, a Novel Molecular POCT system, for the Qualitative Detection of Respiratory Viruses in Nasopharyngeal Swab

Abstract Background The availability of Point-of-Care testing (POCT) based on molecular diagnostics to test simultaneously for multiple respiratory viruses is very limited though significant progress has been made in molecular testing for COVID-19 during the pandemic. Considering the similar symptoms presented by patients infected with various respiratory pathogens, it is crucial to have multiple POCT systems capable of detecting multiple respiratory pathogens while distinguishing SARS-CoV-2 from other pathogens. To meet the growing demand for multiplex testing for respiratory pathogens, a molecular POCT, IRON-qPCR™ RV has been developed. IRfON-qPCR™ RV is a multiplex real-time RT-PCR assay designed for the qualitative detection and differentiation of SARS-CoV-2, Influenza A, Influenza B, RSV-A, and RSV-B RNA from human nasopharyngeal swab specimens. The IRON-qPCR™ proceeds the entire process automatically from nucleic acid extraction to real-time RT-PCR within 40 minutes. The main goal of this study is to evaluate the clinical performance of IRON-qPCR™ RV in comparison with other assays and kits using nasopharyngeal swab samples. Methods To assess the clinical performance of the IRON-qPCR™ RV, specimen collection and evaluation were conducted at a clinical institution in France, utilizing a total of 980 nasopharyngeal swab samples. The comparators used were the Xpert® Xpress CoV-2/Flu/RSV plus Kit and the RealStar® RSV RT-PCR Kit 3.0. Since RSV subtypes are not distinguished by the Xpert kit, all RSV without subtype distinction were compared. Additionally, RealStar kit was used to compare the results of IRON-qPCR™ RV for RSV subtypes A and B. Clinical samples showing discrepancies between Xpert and RealStart, and the IRON-qPCR™ RV were further analyzed using Allplex™ SARS-CoV-2/FuA/FluB/RSV Assay and sequencing. Results Through the comparison of clinical performance of the IRON-qPCR™ RV with Xpert for SARS-CoV-2, Influenza A, and Influenza B in nasopharyngeal swab samples, the clinical sensitivity was analyzed to be over 95.5%, and the clinical specificity was over 99.6%. For RSV, compared to Xpert, the clinical sensitivity was analyzed to be 96.9%, and the clinical specificity was 98.9%. Furthermore, in comparison with RealStar, the clinical sensitivity and specificity of IRON-qPCR™ RV for RSV-A were determined to be 96.2% and 100%, respectively, and the clinical sensitivity and specificity for RSV-B were 96.0% and 100%. Additionally, discrepant samples in comparison with Xpert were further tested using the Allplex as a resolver kit. The result showed that the clinical sensitivity and specificity of IRON-qPCR™ RV for SARS-CoV-2, Influenza A, and Influenza B were over 98.3% and 100%. For RSV, the clinical sensitivity and specificity were 99.5% and 99.1%. Conclusions The clinical performance of IRON-qPCR™ RV was analyzed with the clinical sensitivity of over 95% and the clinical specificity of over 99%. Upon analysis including the results of the resolver kit for discrepant samples, increased clinical sensitivity and specificity were determined. The results of this study strongly support that the IRON-qPCR™ RV is a reliable POCT system for the simultaneous detection and differentiation of multiple respiratory viruses. Furthermore, it is applicable to district hospitals as well as clinical laboratories for accurate and timely testing.

Knowledge-guided Deep Temporal Clustering for Alzheimer's Disease Subtypes in Completed Clinical Trials.

Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder with varied patient progression. We aim to test the hypothesis that AD patients can be categorized into subgroups based on differences in progression. We leveraged data from three randomized clinical trials (RCTs) to develop a knowledge-guided, deep temporal clustering (KG-DTC) framework for AD subtyping. This model combined autoencoders for contextual information capture, k-means clustering for representation formation, and clinical outcome classification for clinical knowledge integration. The derived representations, encompassing demographics, APOE genotype, cognitive assessments, brain volumes, and biomarkers, were clustered using the Gaussian Mixture Model to identify AD subtypes. Our novel KG-DTC framework was developed using placebo data from 2,087 AD patients across three solanezumab clinical trials (EXPEDITION, EXPEDITION2, and EXPEDITION3), achieving high performance in outcome prediction and clustering. The KG-DTC model demonstrated superior clustering structures, especially when combined with k-means clustering loss. External validation with independent clinical trial data showed consistent clustering results, with a 0.33 silhouette score for three clusters. The model's stability was confirmed through a leave-one-out approach, with an average adjusted Rand Index around 0.945. Three distinct AD subtypes were identified, each exhibiting unique patterns of cognitive function, neurodegeneration, and amyloid beta levels. Notably, Subtype 3 (S3) showed rapid cognitive decline across multiple clinical measures (e.g., 0.64 in S1 vs. -1.06 in S2 vs. 15.09 in S3 of average ADAS total change score, p<.001). This innovative approach offers promising insights for understanding variability in treatment outcomes and personalizing AD treatment strategies.

Mechanism exploration and model construction for small cell transformation in EGFR-mutant lung adenocarcinomas

Small-cell lung cancer (SCLC) transformation accounts for 3–14% of resistance in EGFR-TKI relapsed lung adenocarcinomas (LUADs), with unknown molecular mechanisms and optimal treatment strategies. We performed transcriptomic analyses (including bulk and spatial transcriptomics) and multiplex immunofluorescence on pre-treated samples from LUADs without transformation after EGFR-TKI treatment (LUAD-NT), primary SCLCs (SCLC-P) and LUADs with transformation after EGFR-TKI treatment (before transformation: LUAD-BT; after transformation: SCLC-AT). Our study found that LUAD-BT exhibited potential transcriptomic characteristics for transformation compared with LUAD-NT. We identified several pathways that shifted during transformation, and the transformation might be promoted by epigenetic alterations (such as HDAC10, HDAC1, DNMT3A) within the tumor cells instead of within the tumor microenvironment. For druggable pathways, transformed-SCLC were proved to be less dependent on EGF signaling but more relied on FGF signaling, while VEGF-VEGFR pathway remained active, indicating potential treatments after transformation. We also found transformed-SCLC showed an immuno-exhausted status which was associated with the duration of EGFR-TKI before transformation. Besides, SCLC-AT exhibited distinct molecular subtypes from SCLC-P. Moreover, we constructed an ideal 4-marker model based on transcriptomic and IHC data to predict SCLC transformation, which obtained a sensitivity of 100% and 87.5%, a specificity of 95.7% and 100% in the training and test cohorts, respectively. We provided insights into the molecular mechanisms of SCLC transformation and the differences between SCLC-AT and SCLC-P, which might shed light on prevention strategies and subsequent therapeutic strategies for SCLC transformation in the future.

EZB-type diffuse large B-cell lymphoma cell lines have superior migration capabilities compared to MCD-type.

Diffuse large B-cell lymphoma (DLBCL) represents the most prevalent aggressive B-cell lymphoma. The group is heterogeneous and the outcome is variable. A variety of approaches have been employed with the objective of improving the stratification of DLBCL patients according to their prognosis, based on the cell of origin. Recently, distinct genetic subtypes of DLBCL have been identified. Given the importance of cell migration in immune cells, the objective of this study was to ascertain whether different genetic subtypes of DLBCL exhibit disparate migration abilities. MCD- and EZB-type DLBCL cell lines were subjected to testing to ascertain their basal velocity in straight microchannels and their ability to overcome tight constrictions of 2 μm. The EZB-type cell lines showed superior basal migration velocity and constriction passage time, and a similar trend was observed in live cell imaging of native human DLBCL tissue. In addition, MCD-type DLBCL exhibited significantly elevated levels of nuclear lamin A/C, which is responsible for the stiffness of the nuclear envelope and could thus explain the disparate migration behaviours observed among these subtypes. Our study suggests that different genetic subtypes of DLBCL may not only influence the outcome after therapy but also the motility of the tumour cells.

Co-activation of selective nicotinic acetylcholine receptor subtypes is required to reverse hippocampal network dysfunction and prevent fear memory loss in Alzheimer's disease.

Alzheimer's disease (AD) is the most common form of dementia with no known cause and cure. Research suggests that a reduction of GABAergic inhibitory interneurons' activity in the hippocampus by beta-amyloid peptide (Aβ) is a crucial trigger for cognitive impairment in AD via hyperexcitability. Therefore, enhancing hippocampal inhibition is thought to be protective against AD. However, hippocampal inhibitory cells are highly diverse, and these distinct interneuron subtypes differentially regulate hippocampal inhibitory circuits and cognitive processes. Moreover, Aβ unlikely affects all subtypes of inhibitory interneurons in the hippocampus equally. Hence, identifying the affected interneuron subtypes in AD to enhance hippocampal inhibition optimally is conceptually and practically challenging. We have previously found that Aβ selectively binds to two of the three major hippocampal nicotinic acetylcholine receptor (nAChR) subtypes, α7- and α4β2-nAChRs, but not α3β4-nAChRs, and inhibits these two receptors in cultured hippocampal inhibitory interneurons to decrease their activity, leading to hyperexcitation and synaptic dysfunction in excitatory neurons. We have also revealed that co-activation of α7- and α4β2-nAChRs is required to reverse the Aβ-induced adverse effects in hippocampal excitatory neurons. Here, we discover that α7- and α4β2-nAChRs predominantly control the nicotinic cholinergic signaling and neuronal activity in hippocampal parvalbumin-positive (PV+) and somatostatin-positive (SST+) inhibitory interneurons, respectively. Furthermore, we reveal that co-activation of these receptors is necessary to reverse hippocampal network dysfunction and fear memory loss in the amyloid pathology model mice. We thus suggest that co-activation of PV+ and SST+ cells is a novel strategy to reverse hippocampal dysfunction and cognitive decline in AD.

The Organism as the Niche: Physiological States Crack the Code of Adult Neural Stem Cell Heterogeneity.

Neural stem cells (NSCs) persist in the adult mammalian brain and are able to give rise to new neurons and glia throughout life. The largest stem cell niche in the adult mouse brain is the ventricular-subventricular zone (V-SVZ) lining the lateral ventricles. Adult NSCs in the V-SVZ coexist in quiescent and actively proliferating states, and they exhibit a regionalized molecular identity. The importance of such spatial diversity is just emerging, as depending on their position within the niche, adult NSCs give rise to distinct subtypes of olfactory bulb interneurons and different types of glia. However, the functional relevance of stem cell heterogeneity in the V-SVZ is still poorly understood. Here, we put into perspective findings highlighting the importance of adult NSC diversity for brain plasticity, and how the body signals to brain stem cells in different physiological states to regulate their behavior.

Integrated analysis of bulk and single-cell RNA-seq data reveals cell differentiation-related subtypes and a scoring system in bladder cancer.

Bladder cancer (BLCA) exhibits notable molecular heterogeneity, influencing diverse clinical outcomes. However, the molecular subtypes associated with cell differentiation-related genes (CDR) and their prognostic implications remain unexplored. Analysing two GEO single-cell datasets, we identified genes linked to cell differentiation. Utilizing these genes, we explored distinct molecular subtypes. WGCNA analysis further identified CDR-associated genes, and the CDR score system, constructed using Lasso and Cox regression, was developed. Clinical prognosis and variations in immune-related factors among patient groups were assessed. Core genes were selected and confirmed through invitro experiments. Two BLCA subtypes related to cell differentiation were identified: Subtype B demonstrated a favourable prognosis, while Subtype A exhibited significant immune cell infiltration. The CDR score system of nine genes revealed a positive correlation between higher scores and a poorer prognosis. The comprehensive analysis uncovered a positive association between CDR genes and M2 macrophages and unresponsiveness to immune therapy. Functional experiments validated that ANXA5 downregulation influences tumour cell migration without affecting proliferation. Our study reveals distinct cell differentiation-related molecular subtypes and introduces the CDR scoring system in BLCA. ANXA5 emerges as a potential therapeutic target, offering promising avenues for personalized treatment strategies.