Distinct Patterns Research Articles

Clustering and Machine Learning Models of Skeletal Class I and II Parameters of Arab Orthodontic Patients

Background: Orthodontic problems can affect vital quality of life functions, such as swallowing, speech sound production, and the aesthetic effect. Therefore, it is important to diagnose and treat these patients precisely. The main aim of this study is to introduce new classification methods for skeletal class I occlusion (SCIO) and skeletal class II malocclusion (SCIIMO) among Arab patients in Israel. We conducted hierarchical clustering to detect critical trends within malocclusion classes and applied machine learning (ML) models to predict classification outcomes. Methods: This study is based on assessing the lateral cephalometric parameters from the Center for Dentistry Research and Aesthetics based in Jatt, Israel. The study involved the encoded records of 394 Arab patients with diagnoses of SCIO/SCIIMO, according to the individualized ANB of Panagiotidis and Witt. After clustering analysis, an ML model was established by evaluating the performance of different models. Results: The clustering analysis identified three distinct clusters for each skeletal class (SCIO and SCIIMO). Among SCIO clusters, the results showed that in the second cluster, retrognathism of the mandible was less severe, as represented by a lower ANB angle. In addition, the third cluster had a lower NL-ML angle, gonial angle, SN-Ba angle, and lower ML-NSL angle compared to clusters 1 and 2. Among SCIIMO clusters, the results also showed that the second cluster has less severe retrognathism of the mandible, which is represented by a lower ANB angle and Calculated_ANB and a higher SNB angle (p < 0.05). The general ML model that included all measurements for patient classification showed a classification accuracy of 0.87 in the Random Forest and the Classification and Regression Tree models. Using ANB angle and Wits appraisal only in the ML, an accuracy of 0.78 (sensitivity = 0.80, specificity = 0.76) was achieved to classify patients as SCIO or SCIIMO. Conclusions: The clustering analysis revealed distinguished patterns that can be present within SCIO and SCIIMO patients, which can affect the diagnosis and treatment plan. In addition, the ML model can accurately diagnose SCIO/SCIIMO patients, which should improve precise diagnostics.

Network Analyses to Explore Comorbidities Among Older Adults Living With Dementia.

Older persons living with dementia (PLWD) often have multiple other chronic health conditions (i.e., comorbidities). Network analyses can describe complex profiles of chronic health conditions through graphical displays grounded in empirical data. Our study compared patterns of chronic health conditions among PLWD residing in and outside of long-term care (LTC) settings. Population-based administrative data, including outpatient physician claims, inpatient records, pharmaceutical records, and LTC records, for the study were from the Canadian province of Manitoba. We included PLWD, ages ≥ 67 years, with two or more other chronic health conditions, who resided in Manitoba from 2017 to 2020. A total of 138 chronic health conditions were ascertained using a modification of the open-source Clinical Classification Software. Networks defined by nodes (health conditions) and edges (associations between nodes) were stratified by residence location (in versus outside LTC). Network properties were described, including: density (ratio of number of edges to number of potential edges), and modularity (associations between and within clusters of health conditions), and the median and interquartile range (IQR) for node degree (number of associations per node). The population comprised 19,672 PLWD, of which 17,534 (89.1%) had two or more chronic health conditions. The median number of co-occurring conditions was similar among PLWD in LTC (median: 6, IQR: 3-10) versus outside LTC (median: 7, IQR: 4-10). Network properties were similar for PLWD and multiple comorbidities residing in versus outside LTC, including node degree (median 11 vs. 12), density (0.15 vs. 0.14), and modularity (0.18 vs. 0.26). Multiple chronic diseases characterize PLWD residing in and outside of LTC. Using network analyses, chronic diseases among PLWD do not form easily distinguishable groups or patterns. This suggests the need for comprehensive clinical assessments, individualized approaches for disease management, and highlights the importance of person-specific care.

Eye reactions under the influence of drugs of abuse as measured by smartphones: a controlled clinical study in healthy volunteers.

It is known that illicit and prescribed drugs impact pupil size, eye movement and function. Still, comprehensive quantitative evaluations under known ambient light conditions are lacking, when smartphones are used for monitoring. In this clinical study (NCT05731999), four medicinal products with addiction risks were administered to 48 subjects (18-70 years old, all with informed consent, 12 subjects per drug). Videos captured by smartphones at ~50 lux and ~ 500 lux documented the eye's reaction before and after controlled intake of single doses of oral oxycodone (20 mg), lorazepam (2 mg), lisdexamphetamine (70 mg) and inhaled cannabis flos (65 mg with 22% THC) over a 5-h test period. Data from three observational tests, non-convergence (NC, ability to cross the eyes), nystagmus (NY), and pupillary light reflex (PLR) were converted into 24 key features that represent different eye characteristics. Of the acquired data, 87-97% produced key features. At peak drug plasma concentration, oxycodone constricted pupils (p < 0.001); lorazepam induced non-convergence (p < 0.001); lisdexamphetamine induced dilated pupils (p < 0.001), irrespective of ambient light conditions. Inhaled cannabis induced miosis (p = 0.05 at ~50 lux, p = 0.10 at ~500 lux), a reduced light-induced amplitude (p = 0.003 at ~50 lux, p = 0.3 at ~500 lux) and redness of the sclerae (p = 0.14 at ~50 lux, p = 0.007 at ~500 lux). The drug effect lasted at least 5 h (p < 0.005) except for inhaled cannabis (2-3 h, p < 0.05). The ocular response to oxycodone, lorazepam, lisdexamphetamine and cannabis, as measured under controlled light conditions using a smartphone-based assessment, demonstrated distinct and readily distinguishable patterns for each substance. Identifier, NTC05731999.

Speciation of Potentially Carcinogenic Trace Nickel(II) Ion Levels in Human Saliva: A Sequential Metabolomics-Facilitated High-Field 1H NMR Investigation.

Introduction/Objectives: Since the biological activities and toxicities of 'foreign' and/or excess levels of metal ions are predominantly determined by their precise molecular nature, here we have employed high-resolution 1H NMR analysis to explore the 'speciation' of paramagnetic Ni(II) ions in human saliva, a potentially rich source of biomolecular Ni(II)-complexants/chelators. These studies are of relevance to the in vivo corrosion of nickel-containing metal alloy dental prostheses (NiC-MADPs) in addition to the dietary or adverse toxicological intake of Ni(II) ions by humans. Methods: Unstimulated whole-mouth human saliva samples were obtained from n = 12 pre-fasted (≥8 h) healthy participants, and clear whole-mouth salivary supernatants (WMSSs) were obtained from these via centrifugation. Microlitre aliquots of stock aqueous Ni(II) solutions were sequentially titrated into WMSS samples via micropipette. Any possible added concentration-dependent Ni(II)-mediated pH changes therein were experimentally controlled. 1H NMR spectra were acquired on a JEOL JNM-ECZ600R/S1 spectrometer. Results: Univariate and multivariate (MV) metabolomics and MV clustering analyses were conducted in a sequential stepwise manner in order to follow the differential effects of increasing concentrations of added Ni(II). The results acquired showed that important Ni(II)-responsive biomolecules could be clustered into distinguishable patterns on the basis of added concentration-dependent responses of their resonance intensities and line widths. At low added concentrations (71 µmol/L), low-WMSS-level N-donor amino acids (especially histidine) and amines with relatively high stability constants for this paramagnetic metal ion were the most responsive (severe resonance broadenings were observed). However, at higher Ni(II) concentrations (140-670 µmol/L), weaker carboxylate O-donor ligands such as lactate, formate, succinate, and acetate were featured as major Ni(II) ligands, a consequence of their much higher WMSS concentrations, which were sufficient for them to compete for these higher Ni(II) availabilities. From these experiments, the metabolites most affected were found to be histidine ≈ methylamines > taurine ≈ lactate ≈ succinate > formate > acetate ≈ ethanol ≈ glycine ≈ N-acetylneuraminate, although they predominantly comprised carboxylato oxygen donor ligands/chelators at the higher added Ni(II) levels. Removal of the interfering effects arising from the differential biomolecular compositions of the WMSS samples collected from different participants and those from the effects exerted by a first-order interaction effect substantially enhanced the statistical significance of the differences observed between the added Ni(II) levels. The addition of EDTA to Ni(II)-treated WMSS samples successfully reversed these resonance modifications, an observation confirming the transfer of Ni(II) from the above endogenous complexants to this exogenous chelator to form the highly stable diamagnetic octahedral [Ni(II)-EDTA] complex (Kstab = 1.0 × 1019 M-1). Conclusions: The results acquired demonstrated the value of linking advanced experimental design and multivariate metabolomics/statistical analysis techniques to 1H NMR analysis for such speciation studies. These provided valuable molecular information regarding the identities of Ni(II) complexes in human saliva, which is relevant to trace metal ion speciation and toxicology, the in vivo corrosion of NiC-MADPs, and the molecular fate of ingested Ni(II) ions in this biofluid. The carcinogenic potential of these low-molecular-mass Ni(II) complexes is discussed.

PANoptosis Signaling Enables Broad Immune Response in Psoriasis: From Pathogenesis to New Therapeutic Strategies

BackgroundAccumulating evidence suggests that regulated cell death, such as pyroptosis, apoptosis, and necroptosis, is deeply involved in the pathogenesis of psoriasis. As a newly recognized form of systematic cell death, PANoptosis is involved in a variety of inflammatory disorders through amplifying inflammatory and immune cascades, but its role in psoriasis remains elusive. ObjectivesTo reveal the role of PANoptosis in psoriasis for a potential therapeutic strategy. MethodsMultitranscriptomic analysis and experimental validation were used to identify PANoptosis signaling in psoriasis. RNA-seq and scRNA-seq analyses were performed to establish a PANoptosis-mediated immune response in psoriasis, which revealed hub genes through WGCNA and predicted disulfiram as a potential drug. The effect and mechanism of disulfiram were verified in imiquimod (IMQ)-induced psoriasis. ResultsHere, we found a highlighted PANoptosis signature in psoriasis patients through multitranscriptomic analysis and experimental validation. Based on this, two distinct PANoptosis patterns (non/high) were identified, which were the options for clinical classification. The high-PANoptosis-related group had a higher response rate to immune cell infiltration (such as M1 macrophages and keratinocytes). Subsequently, WGCNA showed the hub genes (e.g., S100A12, CYCS, NOD2, STAT1, HSPA4, AIM2, MAPK7), which were significantly associated with clinical phenotype, PANoptosis signature, and identified immune response in psoriasis. Finally, we explored disulfiram (DSF) as a candidate drug for psoriasis through network pharmacology, which ameliorated IMQ-mediated psoriatic symptoms through antipyroptosis-mediated inflammation and enhanced apoptotic progression. By analyzing the specific ligandreceptor interaction pairs within and between cell lineages, we speculated that DSF might exert its effects by targeting keratinocytes directly or targeting M1 macrophages to downregulate the proliferation of keratinocytes. ConclusionsPANoptosis with its mediated immune cell infiltration provides a roadmap for research on the pathogenesis and therapeutic strategies of psoriasis.

Transdermal Drug Delivery System of Linagliptin Sustained-release Microparticle Gels: In vitro Characterization and In vivo Evaluation.

Linagliptin (LNG) exhibits poor bioavailability and numerous side effects, significantly limiting its use. Transdermal drug delivery systems (TDDS) offer a potential solution to overcome the first-pass effect and gastrointestinal reactions associated with oral formulations. The aim of this study was to develop LNG microparticle gels to enhance drug bioavailability and mitigate side effects. Linagliptin hyaluronic acid (LNG-HA) microparticles were prepared by spray drying method and their formulation was optimized via a one-factor method. The solubility and release were investigated using the slurry method. LNG-HA microparticle gels were prepared and optimised using in vitro transdermal permeation assay. The hypoglycaemic effect of the LNG-HA microparticle gel was examined on diabetic mice. The results indicated that the LNG-HA microparticle encapsulation rate was 84.46%. Carbomer was selected as the gel matrix for the microparticle gels. Compared to the oral API, the microparticle gel formulation demonstrated a distinct biphasic release pattern. In the first 30 minutes, only 43.56% of the drug was released, followed by a gradual release. This indicates that the formulation achieved a slow-release effect from a dual reservoir system. Furthermore, pharmacodynamic studies revealed a sustained hypoglycemic effect lasting for 48 hours with the LNG microparticle gel formulation. These findings signify that the LNG microparticle gel holds significant clinical value for providing sustained release and justifies its practical application.

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&lt;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&lt;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.