Distinct Patterns Research Articles

Single-cell transcriptomic landscape deciphers olfactory neuroblastoma subtypes and intra-tumoral heterogeneity.

Olfactory neuroblastoma (ONB) is a rare malignancy known to originate from the olfactory epithelium. The complex tumor ecosystem of this pathology remains unclear. Here, we explored the cellular components within ten ONB tumors and one olfactory mucosa sample based on single-cell RNA profiles. We showed the intra-tumoral heterogeneity by identifying five unique expression programs among malignant epithelial cells. A distinct three-classification system (neural, basal, mesenchymal) for ONB was established according to the distinguished gene expression patterns. Biomarkers for categorizing bulk tumors into uncharacterized subtypes were elucidated. Different responses towards certain chemotherapy regimens could be cautiously inferred according to the molecular features representing the three tumor types, thus helping with precision chemotherapy. We also analyzed subclusters of the tumor microenvironment (TME) and the interactions among different cell types within the TME. The relative abundance of immunosuppressive tumor-associated macrophages suggests potential benefits of immunotherapies targeting macrophages.

High functional vulnerability across the world’s deep-sea hydrothermal vent communities

At the nearly pristine hydrothermal vents of the deep sea, highly endemic animals depend upon bacteria nourished by hydrothermal fluids that emerge as outflows from the seafloor. These animals are remarkable in tolerating extreme conditions, including high heat, toxic reduced sulfide, and low oxygen. Here, we test whether the extreme vent environment has selected for functionally similar species across the world's deep ocean, despite well-established global geographic patterns of high phylogenetic distinctness. High functional redundancy in species pools within regions suggests that the extreme environments select for species with specific traits. Yet, some regions emerge as functional hotspots where species pools with distinct functional trait compositions may represent geological idiosyncrasies of the habitats. Moreover, many species are functionally unique, an outcome of low species richness in a system where the species pool is small at all scales. Given the high proportion of functionally unique species, simulated species extinctions indicate that species losses would rapidly translate to the elimination of functionally irreplaceable species and could tip vent systems to functional collapse. Ocean changes and human-induced threats are expected to significantly impact many vent species as human activities expand in the remote deep sea. The opportunity exists now to take precautionary actions to limit the rates of extinction now ubiquitous in more accessible areas of Earth.

Unveiling the hippocampal subfield changes across the Alzheimer's disease continuum: a systematic review of neuroimaging studies.

Studies exploring the hippocampal subfield atrophy in Alzheimer's disease (AD) have shown contradictory results. This review aims to disentangle such heterogeneity by investigating the dynamic changes of hippocampal subfields across the AD continuum. We systematically searched the PubMed and EMBASE databases for case-control studies. Selected studies included investigations of biomarker-based amyloid status and reported data on hippocampal subfield atrophy using advanced MRI techniques. Twelve studies were included. Despite high heterogeneity, a distinguishable pattern of vulnerability of hippocampal subfields can be recognized from the cognitively unimpaired phase to the dementia stage, shedding light on hippocampal changes with disease progression. Consistent findings revealed atrophy in the subiculum and presubiculum, along with a potential increase in volume in the cornu ammonis (CA) among the cognitively unimpaired group, a feature not observed in patients experiencing subjective cognitive decline. Atrophy in the subiculum, presubiculum, CA 1-4, and the dentate gyrus characterized the mild cognitive impairment stage, with a more pronounced severity in the progression to dementia.

Local Strain-Dependent Etching Patterns of Chemical Vapor Deposited Molybdenum Disulfide.

This study reveals a local strain-dependent etching behavior that enables the formation of distinguished etching patterns in differently strained chemical vapor deposited (CVD) 2D molybdenum disulfide (MoS2) monolayers. It is demonstrated that when the local tensile strain of CVD 2D MoS2 is as uniformly low as ɛ ≈ 0.33% or less, the oxidative etching pattern possesses conventional triangular etching pits (TEPs), while when the local tensile strain is as uniformly high as ɛ ≈ 0.55% or larger, the oxidative etching pattern consist of uniformly oriented hexagonal etching channels (HECs). More interestingly, when the CVD 2D MoS2 monolayer has heterogenous strain distribution from ɛ ≈ 0.55% (center region) to ɛ ≈ 0.33% (perimeter region), the oxidative etching pattern comprise of non-uniformly hexagonal-mixed-parallel etching channels (HPECs). The further characterization and analysis reveal the formation mechanism of such strain-dependent etching patterns is built on the local strain-related fractures propagation under oxidative etching, as well as the anisotropy fractures-based oxidative etching kinetics. This study may enhance the understanding of the relationship between etching and growth features of 2D TMDs, and paves the way to etching-nanostructured (or defect) engineering of 2D TMDs and other 2D materials for potential applications in electrocatalysis and optoelectronics.

Characteristic MR Imaging Findings of Cerebral Air Embolism Infarcts: A Case Series.

Infarcts from cerebral air embolism are rare events with potentially catastrophic clinical consequences. The imaging features of cerebral air embolism are not well-defined in the literature. We report a novel constellation of MR imaging findings of cerebral arterial air emboli-induced infarcts in a series of 6 patients. Awareness of the more distinguishing MR imaging patterns of cerebral air embolism may help establish this diagnosis and facilitate implementation of timely treatment.

Responsive feeding patterns during early childhood in urban areas. Argentina, 2018-2019.

Introduction. Dietary quality involves both the quantity and quality of food offered, the way and the setting in which it is offered, and the responses of the person offering it. The objective of this study was to identify behavioral patterns related to responsive feeding in children aged 6 to 23 months in urban areas from Argentina in 2018-2019. Population and methods. Secondary analysis based on data from the second National Survey on Nutrition and Health of 2018-2019 conducted in a multistage probability sample from urban areas of 5000 inhabitants or more in Argentina. A descriptive analysis and a principal component analysis were performed to identify responsive feeding patterns in 4379 children aged 6 to 23 months. Results. Five responsive feeding patterns were identified; the first 2 dimensions explained 71.1% of inertia (p = 0.013). The pattern with a prevailing possibility of experimentation, autonomy, interaction, and the absence of screens, rewards and distractions was associated with children older than 12 months from the central and south regions (Cuyo, Pampa, Greater Buenos Aires, and Patagonia), whereas the pattern related to a lower autonomy, experimentation, and self-regulation corresponded to children aged 6 to 11 months from the Northwest and Northeast regions. Conclusion. There is evidence of responsive feeding practices that correspond to distinguishable patterns, associated with different stages of life and with the region where the children live.

Assessing the Impact of Cultural Differences on Educational Technology Acceptance

Cultural characteristics in relation to educational technology acceptance (ETA) aims at analyzing the effect of cultural factors that include norms of the society, values, and practices which shape the perception and usage of technology by the individual as incorporated in his/her education. This concept illustrates that cultural factor increases that perception of helpfulness, ease of implementation, and total satisfaction with technology by a significant notch. Understanding these cultural factors is critical to the development and implementation of pedagogical technologies that are aligned with specific target audiences. A number of people in the study was 2100, out of which 1115 were from Mumbai, India and 985 others were from other areas. The sample included people with various education levels, occupations and ages, which gives a comprehensive idea of the variety of users’ perceptions of educational technology. Employing the data based on the collected set of factors, descriptive analysis, factor analysis, and correlation matrixes were used in a process of distinguishing key patterns and relations between particular variables. This cross-sectional research has relied on multiple regression analysis to assess the significant predictor factors that include perceived ease of integration and expected performance of the technology by the users on the two outcomes: user engagement and technology satisfaction. As earlier stated, SPSS was used in this research study to conduct statistical tests. The comparative analysis revealed that there were significant regional differences concerning the social impact expectations, EE and PC but there was no impact of regions as per PEI and TS. The research thus brings out the importance of cultural differences in the explanation of ETA. This just underline the need for a strategic and specific approach that takes into account regional and cultural factors to improve the reception of technologies as well as to improve the user satisfaction even if it is a diverse population. The paper provides important view on rather engaging culturally competent educational technology systems.

Evolutionarily new genes in humans with disease phenotypes reveal functional enrichment patterns shaped by adaptive innovation and sexual selection.

New genes (or young genes) are genetic novelties pivotal in mammalian evolution. However, their phenotypic impacts and evolutionary patterns over time remain elusive in humans due to the technical and ethical complexities of functional studies. Integrating gene age dating with Mendelian disease phenotyping, our research shows a gradual rise in disease gene proportion as gene age increases. Logistic regression modeling indicates that this increase in older genes may be related to their longer sequence lengths and higher burdens of deleterious de novo germline variants (DNVs). We also find a steady integration of new genes with biomedical phenotypes into the human genome over macroevolutionary timescales (~0.07% per million years). Despite this stable pace, we observe distinct patterns in phenotypic enrichment, pleiotropy, and selective pressures across gene ages. Notably, young genes show significant enrichment in diseases related to the male reproductive system, indicating strong sexual selection. Young genes also exhibit disease-related functions in tissues and systems potentially linked to human phenotypic innovations, such as increased brain size, musculoskeletal phenotypes, and color vision. We further reveal a logistic growth pattern of pleiotropy over evolutionary time, indicating a diminishing marginal growth of new functions for older genes due to intensifying selective constraints over time. We propose a pleiotropy-barrier model that delineates higher potentials for phenotypic innovation in young genes compared to older genes, a process that is subject to natural selection. Our study demonstrates that evolutionarily new genes are critical in influencing human reproductive evolution and adaptive phenotypic innovations driven by sexual and natural selection, with low pleiotropy as a selective advantage.

A comparison of infectious and autoimmune meningoencephalitis: Clinical presentation, biochemical markers and MRI findings

Objective: This study investigates distinguishing patterns in lesion distribution, relevant clinical presentation and biochemical markers in MRI to differentiate infective encephalitis (IE) and autoimmune encephalitis (AE). Methods: Retrospective study of adult patients with a confirmed diagnosis of IE and AE admitted to the Neurology unit from January 2012 to December 2020 with MRI Brain. Selected cases with confirmed IE (according to the 2013 Infective Encephalitis Consortium diagnostic criteria) or antibody-positive AE (detection of Neuronal auto-antibody from blood or CSF), coupled by clinical presentation. MRI brain lesion distribution, lobar involvement, enhancement, haemorrhage, vasculopathy and atrophy were analysed. Results: Forty-seven patients (21 IE and 26 AE, respectively) were selected. IE group are older (48.0 ± 16.81) compared to AE (28.4 ± 14.10). Fever and vomiting were significant in IE (p<0.001), whereas psychosis, seizure, movement disorder, and tumour (ovarian teratoma) were significant in the AE cohort. Cerebrospinal fluid (CSF) analysis showed elevated leucocytes with polymorphism and high protein levels in IE (2.081 g/L ± 2.93 vs AE (0.352g/L ± 0.18). MR imaging detected abnormal findings in 61.9% of cases with infectious encephalitis (IE), while 76.9% of cases with autoimmune encephalitis (AE) exhibited normal MRI results. Asymmetrical lesions and inferior frontal lobe distribution (57.1%) were significantly prevalent in IE (p<0.05). Enhancement patterns and haemorrhage were rarely observed in AE patients. Conclusion: IE presented at an older age, with the majority having MRI findings such as asymmetrical lesions, leptomeningeal enhancement, and involvement of medial temporal, hippocampus and inferior frontal cortex. IE clinically presents with fever, vomiting, and elevated CSF leucocytes and protein levels. AE presents at a younger age with seizure, psychosis, movement disorder, tumour (ovarian teratoma). Fewer AE have MRI findings, and if present, tend to be symmetrical in distribution. Lobar involvement in the inferior frontal was the MRI feature that significantly favoured the diagnosis of IE compared to AE. IE and AE have distinct clinical, biochemical, and MRI abnormalities that can be discriminated between the 2 entities.

How blue hat co-regulate pre-service teachers' collective reflection based upon the six-hat thinking technique: A lag sequential analysis

Collective reflection is essential for teachers' professional growth which involves multiple individuals participating in reflective exercises. However, collective reflection often faces problems such as disorganization and inadequate criticism. This study utilized the six-hat thinking framework to structure collective reflection among pre-service teachers during project-based instructional design learning. Despite its known collaboration-boosting effects, the impact of six-hat thinking technique on pre-service teachers' collective reflection, particularly within co-regulation, is under-explored. Focusing on Blue Hat's coordinating role on monitoring and planning, this study employed co-regulation coding and Lag Sequential Analysis (LSA) to analyze collective reflection behaviors. Findings uncovered co-regulation patterns within the six-hat-enhanced reflection, emphasizing Blue Hat's significance. This study distinguished regulation patterns between high and low-level understanding on grasping the six-hat thinking technique. High-understanding groups demonstrated co-regulation centered on regulation-evaluation, fostering self-assessment of instructional design projects and refinement planning. Conversely, low-understanding groups exhibited a pattern focused on task verification, neglecting group work regulation or evaluation. This study also delved into LSA-derived empirical insights on communication dynamics underlying co-regulation in six-hat-integrated collective reflection.

Predictions enable top-down pattern separation in the macaque face-processing hierarchy

Distinguishing faces requires well distinguishable neural activity patterns. Contextual information may separate neural representations, leading to enhanced identity recognition. Here, we use functional magnetic resonance imaging to investigate how predictions derived from contextual information affect the separability of neural activity patterns in the macaque face-processing system, a 3-level processing hierarchy in ventral visual cortex. We find that in the presence of predictions, early stages of this hierarchy exhibit well separable and high-dimensional neural geometries resembling those at the top of the hierarchy. This is accompanied by a systematic shift of tuning properties from higher to lower areas, endowing lower areas with higher-order, invariant representations instead of their feedforward tuning properties. Thus, top-down signals dynamically transform neural representations of faces into separable and high-dimensional neural geometries. Our results provide evidence how predictive context transforms flexible representational spaces to optimally use the computational resources provided by cortical processing hierarchies for better and faster distinction of facial identities.

Autopsy findings from patients diagnosed with COVID-19 demonstrate unique morphological patterns in bone marrow and lymph node

AimsThe identification of haemophagocytosis in bone marrow (BM) is recurrently identified in patients with severe COVID-19. These initial COVID-19 autopsy studies have afforded valuable insight into the pathophysiology of this...

Transforming crocodile traceability: Deep metric learning for identifying Siamese crocodiles

This study introduces a novel method for identifying individual Siamese crocodiles (Crocodylus siamensis), which is a crucial requirement for conservation and sustainable industry practices. Although deep metric learning (DML) has improved identification model robustness and reduced dependency on large datasets, comprehensive field studies and long-term deployments are lacking. To address this, DML combined with convolutional neural network (CNN) was applied for enhancing accuracy using a limited and imbalanced number of images per class and distinguishing dissimilar scale patterns of the head and ventral regions. Individual crocodiles were identified using the k-nearest neighbor (KNN) and support vector machine (SVM) classifiers based on the extracted features. Data were collected from 30 individuals on a crocodile farm using photographs taken over two consecutive years. Two identification types, Type 1, based on a model trained on images collected over two years; and Type 2, based on a model trained exclusively on images from the first year, were implemented. Type 1 identification, which used a CNN combined with the KNN and SVM classifiers, exhibited an accuracy exceeding 99.75 and 92.93% for the ventral and head regions, respectively. Type 2 identification exhibited a reduced accuracy because of a comparatively smaller amount of learning information; the proposed CNN achieved 83.99% accuracy for ventral identification and 67.14 and 65.61% for head identification with KNN and SVM, respectively. This study underscores the efficacy of DML and CNN for handling small, imbalanced datasets in identifying individual crocodiles, and has significant implications for traceability and conservation initiatives in the crocodile industry.

Cryo-EM structures of Kv1.2 potassium channels, conducting and non-conducting.

We present near-atomic-resolution cryo-EM structures of the mammalian voltage-gated potassium channel Kv1.2 in open, C-type inactivated, toxin-blocked and sodium-bound states at 3.2 Å, 2.5 Å, 3.2 Å, and 2.9Å. These structures, all obtained at nominally zero membrane potential in detergent micelles, reveal distinct ion-occupancy patterns in the selectivity filter. The first two structures are very similar to those reported in the related Shaker channel and the much-studied Kv1.2-2.1 chimeric channel. On the other hand, two new structures show unexpected patterns of ion occupancy. First, the toxin α-Dendrotoxin, like Charybdotoxin, is seen to attach to the negatively-charged channel outer mouth, and a lysine residue penetrates into the selectivity filter, with the terminal amine coordinated by carbonyls, partially disrupting the outermost ion-binding site. In the remainder of the filter two densities of bound ions are observed, rather than three as observed with other toxin-blocked Kv channels. Second, a structure of Kv1.2 in Na+ solution does not show collapse or destabilization of the selectivity filter, but instead shows an intact selectivity filter with ion density in each binding site. We also attempted to image the C-type inactivated Kv1.2 W366F channel in Na+ solution, but the protein conformation was seen to be highly variable and only a low-resolution structure could be obtained. These findings present new insights into the stability of the selectivity filter and the mechanism of toxin block of this intensively studied, voltage-gated potassium channel.

Hybrid three-dimensional (3D) bioprinting of retina equivalent for ocular research.

In this article, a hybrid retina construct was created via three-dimensional (3D) bioprinting technology. The construct was composed of a PCL ultrathin membrane, ARPE-19 cell monolayer and Y79 cell-laden alginate/pluronic bioink. 3D bioprinting technology was applied herein to deliver the ARPE-19 cells and Y79 cell-laden bioink to ensure homogeneous ARPE-19 cell seeding; subsequently, two distinctive Y79 cell-seeding patterns were bioprinted on top of the ARPE-19 cell monolayer. The bioprinted ARPE-19 cells were evaluated by prestoblue assay, F-actin, and hematoxylin/eosin (HE) staining, and then the cells were observed under laser scanning and invert microscopy for 14 days. The Y79 cells in alginate/pluronic bioink after bioprinting had been closely monitored for 7 days. Live/dead assay and scanning electrical microscopy (SEM) were employed to investigate Y79 cell viability and morphology. Both the ARPE-19 and Y79 cells were in excellent condition, and the successfully bioprinted retina model could be utilized in drug delivery, disease mechanism and treatment method discoveries.

A Six-gene Prognostic Model Based on Neutrophil Extracellular Traps (NETs)-related Gene Signature for Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most common malignant cancers. Neutrophil extracellular traps (NETs) have been discovered to play a crucial role in the pathogenesis of LUAD. We aimed to establish an innovative prognostic model for LUAD based on the distinct expression patterns of NETs-related genes. The TCGA LUAD dataset was utilized as the training set, while GSE31210, GSE37745, and GSE50081 were undertaken as the verification sets. The patients were grouped into clusters based on the expression signature of NETs-related genes. Differentially expressed genes between clusters were identified through the utilization of the random forest and LASSO algorithms. The NETs score model for LUAD prognosis was developed by multiplying the expression levels of specific genes with their corresponding LASSO coefficients and then summing them. The validity of the model was confirmed by analysis of the survival curves and ROC curves. Additionally, immune infiltration, GSEA, mutation analysis, and drug analysis were conducted. Silencing ABCC2 in A549 cells was achieved to investigate its effect. We identified six novel NETs-related genes, namely UPK1B, SFTA3, GGTLC1, SCGB3A1, ABCC2, and NTS, and developed a NETs score signature, which exhibited a significant correlation with the clinicopathological and immune traits of the LUAD patients. High-risk patients showed inhibition of immune-related processes. Mutation patterns exhibited variability among the different groups. AZD3759, lapatinib, and dasatinib have been identified as potential candidates for LUAD treatment. Moreover, the downregulation of ABCC2 resulted in the induction of apoptosis and suppression of migration and invasion in A549 cells. Altogether, this study has identified a novel NET-score signature based on six novel NET-related genes to predict the prognosis of LUAD and ABCC2 and has also explored a new method for personalized chemo-/immuno-therapy of LUAD.

Skin cancer detection through attention guided dual autoencoder approach with extreme learning machine

Skin cancer is a lethal disease, and its early detection plays a pivotal role in preventing its spread to other body organs and tissues. Artificial Intelligence (AI)-based automated methods can play a significant role in its early detection. This study presents an AI-based novel approach, termed 'DualAutoELM' for the effective identification of various types of skin cancers. The proposed method leverages a network of autoencoders, comprising two distinct autoencoders: the spatial autoencoder and the FFT (Fast Fourier Transform)-autoencoder. The spatial-autoencoder specializes in learning spatial features within input lesion images whereas the FFT-autoencoder learns to capture textural and distinguishing frequency patterns within transformed input skin lesion images through the reconstruction process. The use of attention modules at various levels within the encoder part of these autoencoders significantly improves their discriminative feature learning capabilities. An Extreme Learning Machine (ELM) with a single layer of feedforward is trained to classify skin malignancies using the characteristics that were recovered from the bottleneck layers of these autoencoders. The 'HAM10000' and 'ISIC-2017' are two publicly available datasets used to thoroughly assess the suggested approach. The experimental findings demonstrate the accuracy and robustness of the proposed technique, with AUC, precision, and accuracy values for the 'HAM10000' dataset being 0.98, 97.68% and 97.66%, and for the 'ISIC-2017' dataset being 0.95, 86.75% and 86.68%, respectively. This study highlights the possibility of the suggested approach for accurate detection of skin cancer.

Combined effect of cortical superficial siderosis and cerebral microbleed on short-term and long-term outcomes after intracerebral haemorrhage

Background and purposeCortical superficial siderosis (cSS) and cerebral microbleed (CMB) have distinct effects on intracerebral haemorrhage (ICH). We aim to investigate the combined effect of cSS and CMB on outcomes...

Separation and Characterization of Therapeutic Oligonucleotide Isomer Impurities by Cyclic Ion Mobility Mass Spectrometry.

Therapeutic oligonucleotides such as antisense oligonucleotide (ASO) and small interfering RNA (siRNA) are among the most remarkable modalities in modern medicine. ASOs and siRNA are composed of single- or double-stranded 15-25 mer synthesized oligonucleotides, which can be used to modulate gene expression. Liquid chromatography-mass spectrometry (LC/MS) is a necessary technique for the quality control of therapeutic oligonucleotides; it is used to evaluate the quantities of target oligonucleotides and their impurities. The widely applied oligonucleotide therapeutic quantitation method uses both ultraviolet (UV) absorbance and the MS signal intensity. Peaks separated from the main peak, which contains full-length product, are generally quantitated by UV. However, coeluting impurities, such as n - 1 shortmers, abasic oligonucleotides, and PS → PO (phosphorothiate to phosphodiester) oligonucleotides, are quantitated by MS. These coeluting impurities can also be comprised of various isomers with the same modification, thus increasing the difficulty in their separation and relative quantitation by LC/MS. It is possible that a specific isomer with a certain structural form induces toxicities. Therefore, characterization of each isomer separation is in high demand. In this study, we separated and characterized oligonucleotide isomers by employing a cyclic ion mobility mass spectrometry (cyclic IMS) system, which allows the separation of ions with the same m/z ratio based on their structural differences. Patisiran antisense and sense strands and their n - 1 and abasic isomers were used as sample sequences, and their ratio characterization was achieved by cyclic IMS. In addition, we evaluated the PS → PO conversion isomers of the antisense strand of givosiran, which originally contained four PS modification sites. The PS → PO isomers exhibited specific and distinguishable mobiligram patterns. We believe that cyclic IMS is a promising method for evaluating therapeutic oligonucleotide isomers.

Individual differences in spatial working memory strategies differentially reflected in the engagement of control and default brain networks.

Spatial locations can be encoded and maintained in working memory using different representations and strategies. Fine-grained representations provide detailed stimulus information, but are cognitively demanding and prone to inexactness. The uncertainty in fine-grained representations can be compensated by the use of coarse, but robust categorical representations. In this study, we employed an individual differences approach to identify brain activity correlates of the use of fine-grained and categorical representations in spatial working memory. We combined data from six fMRI studies, resulting in a sample of 155 (77 women, 25 ± 5 years) healthy participants performing a spatial working memory task. Our results showed that individual differences in the use of spatial representations in working memory were associated with distinct patterns of brain activity. Higher precision of fine-grained representations was related to greater engagement of attentional and control brain systems throughout the task trial, and the stronger deactivation of the default network at the time of stimulus encoding. In contrast, the use of categorical representations was associated with lower default network activity during encoding and higher frontoparietal network activation during maintenance. These results may indicate a greater need for attentional resources and protection against interference for fine-grained compared to categorical representations.