Extreme Heterogeneity Research Articles

Pollen Diversity in the Tribe Cardueae (Asteraceae) and Its Taxonomic Significance.

The Cardueae with about 74 genera and 2500 species is one of the largest tribes of the family Asteraceae. The taxonomy of the Cardueae is complicated and unresolved, as it contains the largest and most diverse genera. The main distribution centers of the Cardueae are in the eastern and western Mediterranean, the western Irano-Turanian region, central Asia, and North Africa. Using pollen morphology can be a useful tool for the identification and delimitation of Cardueae taxa. Therefore, the current study aims to describe the pollen types of tribe Cardueae based on pollen features. Furthermore, the study addresses the relationships among the genera and species based on palynological features as well as species delimitation based on pollen morphology. Pollen morphology of 39 species of Cardueae distributed in 28 genera was examined by scanning electron microscopy. In the present study, statistical analyses and various clustering and ordination methods were provided for palynological data. Based on these results, the members of nine subtribes of Cardueae showed overlap in palynological data. This extreme heterogeneity of relationships among the taxa of tribe Cardueae could be attributed to the large number of taxa and their high morphological diversity. However, suitable palynological features were distinguished for taxonomic differentiation among the species of Cardueae, including pollen shape, size, polar axis to equatorial diameter ratio [P/E], exine sculpture, and spine size. Consequently, six pollen types were identified in the studied taxa of Cardueae.

The origins of "Kaunayen" game fowls of Manipur, India: Insights from mitochondrial D-loop sequence analysis.

Notably, poultry animals-particularly chickens-are recognized globally for their valuable contributions to the food, ornamental, and game economies. Further, more robust local and regional breeds can be parental donors for these area-specific consumable breeds' resilient traits. Game birds that are locally significant economically or on a much smaller scale are frequently excluded from the procedure. One such breed is the fighting chicken of Manipur, India, known locally as the Kaunayen breed and listed as the 17th breed at the ICAR, the National Bureau of Animal Genetic Resources, India. When Kaunayen fowl from throughout Manipur are considered, they have anatomical characteristics and common behavioural traits despite the breed's extreme genetic heterogeneity. With this gap in mind, we attempted to use mitochondrial D-loop sequences to characterize Manipur's Kaunayen fowls concerning the global breeds of nearly similar molecular characteristics. We found that Kaunayen fowls share evolutionary traits such as a similar transition/transversion ratio with some Southeast Asian breeds, including a few red jungle fowls. Overall Kaunayen are also more closely related to Southeast Asian birds phylogenetically, after which with a few breeds from East Asian, Bangladesh, North-East India, and the Indian island of Nicobar. The global database including our query has 19 haplotypes, and majority of the Kaunayen fowls share haplotypes with North East Indian fowls; the remaining haplotypes are primarily associated with South East Asia and East Asia. The findings additionally indicated that Kaunayen's and the global breed's D-loop region tended to fixed neutral substitution, contributing to the distinct varieties. Further, migration research demonstrated that Kaunayen fowls originated from a substantial maternal genome influx from Southeast Asia, which may have later made a substantial contribution to East Asian and South Asian breeds. We also display a portion of the D-loop that demonstrates the majority of the substitution diversity across all breeds, and we suggest using sequence stretch to create miniature breed-specific identifying barcodes.

Multi-parameter quantitative magnetic resonance imaging for early detecting skeletal muscle involvement and predicting functional decline in children with Becker muscular dystrophy.

The extreme clinical heterogeneity of children with Becker muscular dystrophy significantly poses a great challenge to accurately assess their disease status. To detect skeletal muscle involvement in children with Becker muscular dystrophy using multiple-parameter quantitative magnetic resonance imaging (qMRI), and to determine the preferred muscle site and qMRI biomarker. Fat fraction, T1, and T2 measurements were conducted in Becker muscular dystrophy (n=29) and healthy controls (n=23). North Star Ambulatory Assessment (NSAA) was performed in Becker muscular dystrophy. Group differences were compared by using the Mann-Whitney or Kruskal-Wallis test or a linear mixed-effect model. Receiver operating characteristic analysis with area under curve (AUC) was used to compare the diagnostic performance. Logistic regression was used to identify the predictor of functional decline. Both fat fraction and T2 were effective in detecting muscle involvement across different functional stages that were categorized by NSAA, with fat fraction in gluteus maximus demonstrating the most superior diagnostic performance (AUC range, 0.85-0.98). The combination of T2 and T1 enables a good diagnosis of no abnormal fat-infiltrated muscles (AUC=0.82). Overall, fat fraction in gluteus maximus exhibited the strongest negative correlation with the NSAA score (r=-0.69, P<0.01) and emerged as an independent risk factor for functional decline (odds ratio=1.12, P=0.02). Multi-parametric qMRI demonstrate effective capabilities for early detection of muscle involvement, with gluteus maximus being the preferred muscle site. Fat fraction in gluteus maximus may serve as a potential biomarker for predicting functional decline.

Cardio-metabolic and cytoskeletal proteomic signatures differentiate stress hypersensitivity in dystrophin-deficient mdx mice.

Extreme heterogeneity exists in the hypersensitive stress response exhibited by the dystrophin-deficient mdx mouse model of Duchenne muscular dystrophy. Because stress hypersensitivity can impact dystrophic phenotypes, this research aimed to understand the peripheral pathways driving this inter-individual variability. Male and female mdx mice were phenotypically stratified into "stress-resistant" or "stress-sensitive" groups based on their response to two laboratory stressors. Quantitative proteomics of striated muscle revealed that stress-resistant females were most dissimilar from all other groups, with over 250 proteins differentially regulated with stress hypersensitivity. Males showed less proteomic variation with stress hypersensitivity; however, these changes were associated with pathway enrichment. In the heart, stress-sensitive males had significant enrichment of pathways related to mitochondrial ATP synthesis, suggesting that increased cardio-metabolic capacity is associated with stress hypersensitivity in male mdx mice. In both sexes, stress hypersensitivity was associated with greater expression of beta-actin-like protein 2, indicative of altered cytoskeletal organisation. Despite identifying proteomic signatures associated with stress hypersensitivity, these did not correlate with differences in the serum metabolome acutely after a stressor. These data suggest that the heterogeneity in stress hypersensitivity in mdx mice is partially driven by cytoskeletal organisation, but that sex-specific cardio-metabolic reprogramming may also underpin this phenotype. SIGNIFICANCE: Duchenne muscular dystrophy (DMD) is a fatal muscle wasting disease which is associated with a premature loss of ambulation and neurocognitive dysfunction. The hypersensitive stress response in DMD is a heterogeneous phenotype which is poorly understood. This study provided the first investigation of the peripheral mechanisms regulating the hypersensitive stress response by undertaking multi-omics analysis of phenotypically stratified mdx mice. Variations in behaviour and the striated muscle proteomic profiles suggest that cardio-metabolic remodelling and cytoskeletal organisation may contribute to this phenotype. This research offers significant insights into understanding how peripheral dystrophin deficiency relates to the cognitive abnormalities seen in patients with DMD.

Extreme sulfur isotope heterogeneity in individual Ediacaran pyrite grains revealed by NanoSIMS analysis

Pyrite sulfur isotopic composition (δ34Spy) is a crucial proxy for reconstructing ancient Ediacaran marine environments. However, recent in situ isotopic analyses of sedimentary pyrite have revealed distinct δ34Spy signatures among different pyrite morphologies, indicating that secular changes in bulk δ34Spy may reflect variations in proportions of different pyrite morphologies rather than environmental signals. Up to now, intragrain isotopic patterns within individual pyrite grains have not yet been extensively investigated for Ediacaran samples. The absence of this specific data set has hindered our ability to understand current complexities of bulk δ34Spy in reconstruction paleoenvironment. This study aims to elucidate δ34Spy patterns by conducting in situ isotopic analysis on pyrite grains from Ediacaran drill-core samples. We employed scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), Raman spectroscopy, and nanoscale secondary ion mass spectrometry (NanoSIMS) to examine the crystal texture, element atomic ratios (S/Fe), mineral composition, and in situ isotopic composition within single pyrite grains. SEM-EDS observations reveal that the euhedral/subhedral pyrite crystals generally exhibit uniform mineral texture, although some grains show varying degrees of dissolution edges and surface cavities. Raman spectroscopy demonstrates the possible presence of pyrrhotite mineral within pyrite grains at some specific sites and points. In situ isotopic analysis reveals significant intragrain δ34S heterogeneity, with difference reaching up to 69.3‰ on a micrometer scale. Distinct deposition depths and burial rates may contribute to the varying value ranges and degrees of isotopic heterogeneity amongst pyrite grains. A model suggesting rapid precipitation from numerous nucleation sites simultaneously could account for the observed intragrain heterogeneity of in situ δ34S values. Pyrite grains exhibit general atomic S/Fe ratios of > 2, potentially due to the presence of trace elements incorporated into the pyrite structure. The occurrence of pyrrhotite leads to a slightly positive correlation between in situ δ34Spy values and S/Fe ratios, yet the 32S-enriched pyrrhotite plays less substantial in generating intragrain δ34S heterogeneity of pyrite grains. Our findings reveal clear isotopic heterogeneities within individual pyrite grains, in addition to the notable δ34Spy differences among pyrite of various morphologies. These results highlight significant microenvironmental heterogeneity and dynamic sulfur pool mixing on rapid short-term timescale during pyrite growth.

Conceptualizing an interpretative framework for energy transition among Italian innovative small and medium enterprises

Energy transition (ET) is becoming essential for most countries worldwide. Companies can only adapt their behaviours to the objectives set by countries’ institutions. A new research stream has thus emerged, which investigates the factors facilitating ET among companies. To date, less attention has been paid to small and medium-sized enterprises (SMEs). One of the greatest difficulties in examining SMEs is their extreme heterogeneity, making results difficult to interpret.This study analyses the factors supporting ET among a specific population of companies in a defined territorial context: the so-called innovative SMEs belonging to a special Italian database. The high propensity towards eco-environmental innovations characterizing these SMEs and their inclination towards sustainable development suggests that their experience represents a prospective path that policymakers could adopt for other types of SMEs.Through a partial least squares analysis of data collected from these SMEs, outcomes show that the only factor supporting the ET is the sensitivity of these economic organizations towards energy issues developed over time; that is, the corporate culture with regard to sustainability.This result is only seemingly surprising under the specific features of these SMEs. Conversely, it presupposes new implications regarding policy measures, questioning the traditional approach based on providing incentives and/or regulations.

Whole-genome Sequencing Association Analysis of Quantitative Platelet Traits in A Large Cohort of β-thalassemia.

Platelet acts as a crucial monitoring indicator for hypercoagulability and thrombosis and a key target for drug regulation. Genotype-phenotype association studies have confirmed that platelet traits are quantitatively regulated by multiple genes. However, there is currently a lack of genetic studies on the heterogeneity of platelet traits in β-thalassemia under hypercoagulable state. Here, we studied the phenotypic heterogeneity of platelet count (PLT) and mean platelet volume (MPV) in 1020 β-thalassemia patients. We further performed a functionally informed whole genome sequencing association analysis of common variants and rare variants (RVs) for PLT and MPV in 916 patients through integrative analysis of whole-genome sequencing data and functional annotation data. Extreme phenotypic heterogeneity of platelet traits was observed in β-thalassemia patients. Additionally, the common variant based gene-level analysis identified the novel gene of RNF144B associated with MPV. The RV analysis identified several novel associations in both coding and noncoding genome, including missense RVs of PPP2R5C associated with PLT and missense RVs of TSSK1B associated with MPV. In conclusion, we performed a comprehensive and systematic whole genome scan of platelet traits in the β-thalassemia cohort, demonstrating the specificity of genetic regulation of platelet traits in the context of β-thalassemia, providing potential targets for intervention.

Improving Fault Zones Hydrodynamic Characterization and Simulation in Karstified Carbonate Environments with GLM and IES Invers Methods

A quantitative and qualitative estimation of groundwater resources is a challenge for water management worldwide. In the specific case of the carbonate karstified aquifer, the high sensitivity of this resource is partially due to its level of permeability. Moreover, the extreme heterogeneity of this type of aquifer makes it complex to define vulnerable areas, especially when fault zones exert a significant influence on groundwater hydrodynamics and transport. Improving the management of this type of aquifer involves better assessment of its hydrodynamics properties. Sustainability and management solutions can be estimated through numerical modeling. In this study hydrodynamic parameter of the fault zone in karstified carbonate environments are estimated from cross-hole pumping test data. These analyses allow the simulation and forecasting of fault zone flow and travel time. For this purpose, a flow and travel time model has been set up using MODFLOW6 and MODPATH7 codes. Inverse modeling of hydrodynamic parameters is performed with the PEST++ code suite, with both the Gauss-Levenberg-Marquardt Algorithm (GLM) and the Iterative Ensemble Smoother (IES) which is a recent approach with few applications so far. Simulation, parameter estimation, and forecasts of drawdown and pollutant travel time through the fault zone have been first evaluated on a synthetic fault zone and are eventually applied to a real-world fault zone of interest in karst carbonate environments. A comprehensive comparison and analysis of GLM and IES results are performed for parameter estimation, parametric and predictive uncertainties, ensuring a thorough assessment of results. The numerical inversion approach provided a spatial parametric estimation of the hydraulic conductivity of the fault zone, along with an uncertainty analysis.This approach demonstrates its ability to estimate the hydrodynamic parameter field with a high level of accuracy within the internal structures of the fault zone. This study constitutes valuable and reproducible insights into the simulation and forecasts of fault zones in karst carbonate aquifers. The findings are a step forward in groundwater flow and travel time simulation of fault zones and provide relevant practical help for the management and protection of water resources in these critical areas of interest.

Hydrophilic Interaction Chromatography Coupled to Ultraviolet Photodissociation Affords Identification, Localization, and Relative Quantitation of Glycans on Intact Glycoproteins.

Protein glycosylation is implicated in a wide array of diseases, yet glycoprotein analysis remains elusive owing to the extreme heterogeneity of glycans, including microheterogeneity of some of the glycosites (amino acid residues). Various mass spectrometry (MS) strategies have proven tremendously successful for localizing and identifying glycans, typically utilizing a bottom-up workflow in which glycoproteins are digested to create glycopeptides to facilitate analysis. An emerging alternative is top-down MS that aims to characterize intact glycoproteins to allow precise identification and localization of glycans. The most comprehensive characterization of intact glycoproteins requires integration of a suitable separation method and high performance tandem mass spectrometry to provide both protein sequence information and glycosite localization. Here, we couple ultraviolet photodissociation and hydrophilic interaction chromatography with high resolution mass spectrometry to advance the characterization of intact glycoproteins ranging from 15 to 34 kDa, offering site localization of glycans, providing sequence coverages up to 93%, and affording relative quantitation of individual glycoforms.

Achievements of international rare cancers networks and consortia in the neuro-oncology field.

In this review, we investigated the role of European oncological networks on management and care of patients with central nervous system (CNS) malignancies. Within this universe of tumors, malignancies of the central nervous system (CNS) malignancies represent a challenge because of several reasons such as biological complexity, the need of dedicated experienced physicians (surgeons, pathologists, radiologists and neuro-oncologists) and tertiary healthcare providers. Limits to the development of effective and innovative care are represented by the rarity of these tumors and their extreme heterogeneity in terms of clinical presentation, course of the disease, genetic assessments and site of presentation. The oncological networks are societies or associations, which make possible to connect patients, scientists, doctors and researchers together allowing to obtain several improvements. Oncological networks can cooperate to increase accrual rate and speed in clinical trials, share data about CNS malignancy management and improve knowledge toward this class of tumors within patients and health operators promoting equity and high standard of care.

A 10-Year Review on Advancements in Identifying and Treating Intellectual Disability Caused by Genetic Variations.

Intellectual disability (ID) is a prevalent neurodevelopmental disorder characterized by neurodevelopmental defects such as the congenital impairment of intellectual function and restricted adaptive behavior. However, genetic studies have been significantly hindered by the extreme clinical and genetic heterogeneity of the subjects under investigation. With the development of gene sequencing technologies, more genetic variations have been discovered, assisting efforts in ID identification and treatment. In this review, the physiological basis of gene variations in ID is systematically explained, the diagnosis and therapy of ID is comprehensively described, and the potential of genetic therapies and exercise therapy in the rehabilitation of individuals with intellectual disabilities are highlighted, offering new perspectives for treatment approaches.

Measuring spatial inequalities in maternal and child mortalities in Pakistan: evidence from geographically weighted regression

BackgroundIn developing countries, the death probability of a child and mother is more significant than in developed countries; these inequalities in health outcomes are unfair. The present study encompasses a spatial analysis of maternal and child mortalities in Pakistan. The study aims to estimate the District Mortality Index (DMI), measure the inequality ratio and slope, and ascertain the spatial impact of numerous factors on DMI scores across Pakistani districts.MethodThis study used micro-level household datasets from multiple indicator cluster surveys (MICS) to estimate the DMI. To find out how different the DMI scores were, the inequality ratio and slope were used. This study further utilized spatial autocorrelation tests to determine the magnitude and location of the spatial dependence of the clusters with high and low mortality rates. The Geographically Weighted Regression (GWR) model was also applied to examine the spatial impact of socioeconomic, environmental, health, and housing attributes on DMI.ResultsThe inequality ratio for DMI showed that the upper decile districts are 16 times more prone to mortalities than districts in the lower decile, and the districts of Baluchistan depicted extreme spatial heterogeneity in terms of DMI. The findings of the Local Indicator of Spatial Association (LISA) and Moran's test confirmed spatial homogeneity in all mortalities among the districts in Pakistan. The H–H clusters of maternal mortality and DMI were in Baluchistan, and the H–H clusters of child mortality were seen in Punjab. The results of GWR showed that the wealth index quintile has a significant spatial impact on DMI; however, improved sanitation, handwashing practices, and antenatal care adversely influenced DMI scores.ConclusionThe findings reveal a significant disparity in DMI and spatial relationships among all mortalities in Pakistan's districts. Additionally, socioeconomic, environmental, health, and housing variables have an impact on DMI. Notably, spatial proximity among individuals who are at risk of death occurs in areas with elevated mortality rates. Policymakers may mitigate these mortalities by focusing on vulnerable zones and implementing measures such as raising public awareness, enhancing healthcare services, and improving access to clean drinking water and sanitation facilities.

Multiplexed detection platform implemented with magnetic encoding and deep learning-based decoding for quantitative analysis of exosomes from cancers

Although a number of biosensing technologies have been reported for the detection of cancer-derived exosomes used as early diagnosis markers for cancers, it is necessary to identify them with various biomarkers to distinguish the stages and types of cancers owing to the extreme heterogeneity of cancer. Here, we developed a new multiplexed assay platform for the detection of exosomes using magnetic encoded microparticles (MEMPs), which can recognize multiple proteins expressed on exosomes, and a deep learning-based decoding algorithm. This platform, in which the accuracy of the decoding algorithm was evaluated to be 93 %, was applied to detect exosomes from four types of cancer cell lines and plasma from patients with cancer using three cancer biomarkers: PD-L1 (Programmed Death-Ligand 1), EpCAM (Epithelial cell adhesion molecule), and EGFR (Epidermal growth factor receptor). The limit of detections (LODs) of this platform when applied to the detection of exosomes from MDA-MB-231 cell line were calculated as 4.03 × 106 mL−1 for PD-L1, 1.00 ×107 mL−1 for EpCAM, and 7.17×106 mL−1 for EGFR, respectively. In a clinical study, four types of samples from patients with cancer (n = 92) showed higher signals than those of healthy controls (n = 18). Based on these results, we confirmed that this platform can distinguish patients with cancer from healthy individuals.

Extreme heterogeneity in the microrheology of lamellar surfactant gels analyzed with neural networks.

The heterogeneity of the viscoelasticity of a lamellar gel network based on cetyl-trimethylammonium chloride and cetostearyl alcohol was studied using particle-tracking microrheology. A recurrent neural network (RNN) architecture was used for estimating the Hurst exponent, H, on small sectionsof tracks of probe spheres moving with fractional Brownian motion. Thus, dynamic segmentation of tracks via neural networks was used in microrheology and it is significantly more accurate than using mean square displacements (MSDs). An ensemble of 414 particles produces a MSD that is subdiffusive in time, t, with a power law of the form t^{0.74±0.02}, indicating power law viscoelasticity. RNN analysis of the probability distributions of H, combined with detailed analysis of the time-averaged MSDs of individual tracks, revealed diverse diffusion processes belied by the simple scaling of the ensemble MSD, such as caging phenomena, which give rise to the complex viscoelasticity of lamellar gels.

ALLSTAR: Inference of ReliAble CausaL RuLes between Somatic MuTAtions and CanceR Phenotypes.

Recent advances in DNA sequencing technologies have allowed the detailed characterization of genomes in large cohorts of tumors, highlighting their extreme heterogeneity, with no two tumors sharing the same complement of somatic mutations. Such heterogeneity hinders our ability to identify somatic mutations important for the disease, including mutations that determine clinically relevant phenotypes (e.g., cancer subtypes). Several tools have been developed to identify somatic mutations related to cancer phenotypes. However, such tools identify correlations between somatic mutations and cancer phenotypes, with no guarantee of highlighting causal relations. We describe ALLSTAR, a novel tool to infer reliable causal relations between somatic mutations and cancer phenotypes. ALLSTAR identifies reliable causal rules highlighting combinations of somatic mutations with the highest impact in terms of average effect on the phenotype. While we prove that the underlying computational problem is NP-hard, we develop a branch-and-bound approach that employs protein-protein interaction networks and novel bounds for pruning the search space, while properly correcting for multiple hypothesis testing. Our extensive experimental evaluation on synthetic data shows that our tool is able to identify reliable causal relations in large cancer cohorts. Moreover, the reliable causal rules identified by our tool in cancer data show that our approach identifies several somatic mutations known to be relevant for cancer phenotypes as well as novel biologically meaningful relations. Code, data, and scripts to reproduce the experiments available at https://github.com/VandinLab/ALLSTAR. Supplementary data are available at Bioinformatics online.

Treatment Outcomes in Primary Mediastinal Large B-Cell Lymphoma. Experience of the AF Tsyb Medical Radiological Research Center (Obninsk)

AIM. To assess chemotherapy outcomes in patients with primary mediastinal large B-cell lymphoma (PMBCL) treated at the AF Tsyb Medical Radiological Research Center from 2016 to 2023. MATERIALS &amp; METHODS. The analysis focused on the data from 58 patients with the morphologically verified diagnosis of PMBCL. The patients were aged 17–62 years (median 34 years), there were 39 women and 19 men. The median follow-up was 51.2 months (range 0.4–200.9 months). Depending on drug chemotherapy regimens, patients were divided into 3 groups: R-NHL-BFM-90 (n = 9), R-CHOP (n = 17), and R-MACOP-B (n = 32). Most patients (90 %) received mediastinal radiotherapy of total 30–46 Gy. RESULTS. The 5-year overall survival in the therapy groups was 66.7 %, 88.2 %, and 100 %, respectively (p = 0.007), progression-free survival was 66.7 %, 70.6 %, and 96.9 % (p = 0.006), and event-free survival was 66.7 %, 54.7 %, and 90.6 % (p = 0.038). On the whole, the toxicity profile of chemotherapy was quite acceptable. Neither low blood values nor other adverse events essentially affected a complete implementation of chemoradiotherapy program. The intermediate outcomes were based on PET-CT data after 2–4 therapy cycles in 37 (64 %) patients. PET-CT showed that at the stage of drug chemotherapy, complete response (CR) was achieved in 27 (73 %) patients, and partial response (PR) was achieved in 4 (11 %) patients. With respect to the CR and PR criteria, there were 6 (16 %) non-responders. CONCLUSION. PMBCL is one of extranodal lymphomas with thymic B-cells being primary source of tumor growth. PMBCL is characterized by aggressive course and extreme heterogeneity of clinical manifestations. Up to now, the first-line chemotherapy decision making in PMBCL has remained an issue with practical importance. This paper reports immediate and long-term outcomes of the program chemoradiotherapy regimen R-MACOP-B with subsequent consolidation radiotherapy. The results obtained can be termed quite satisfactory and noninferior to the data from national and international sources. Nevertheless, more effective chemoradiotherapy programs for PMBCL continue to be elaborated. In this context, immune checkpoint inhibitors as part of therapy programs seem to hold promise for the treatment of newly diagnosed PMBCL.

Parallel degradome-seq and DMS-MaPseq substantially revise the miRNA biogenesis atlas in Arabidopsis.

MicroRNAs (miRNAs) are produced from highly structured primary transcripts (pri-miRNAs) and regulate numerous biological processes in eukaryotes. Due to the extreme heterogeneity of these structures, the initial processing sites of plant pri-miRNAs and the structural rules that determine their processing have been predicted for many miRNAs but remain elusive for others. Here we used semi-active DCL1 mutants and advanced degradome-sequencing strategies to accurately identify the initial processing sites for 147 of 326 previously annotated Arabidopsis miRNAs and to illustrate their associated pri-miRNA cleavage patterns. Elucidating the in vivo RNA secondary structures of 73 pri-miRNAs revealed that about 95% of them differ from in silico predictions, and that the revised structures offer clearer interpretation of the processing sites and patterns. Finally, DCL1 partners Serrate and HYL1 could synergistically and independently impact processing patterns and in vivo RNA secondary structures of pri-miRNAs. Together, our work sheds light on the precise processing mechanisms of plant pri-miRNAs.

Extracellular vesicles and glycans: new avenue for biomarker research.

The investigation of biomarkers is constantly evolving. New molecules and molecular assemblies, such as soluble and particulate complexes, emerged as biomarkers from basic research and investigation of different proteomes, genomes, and glycomes. Extracellular vesicles (EVs), and glycans, complex carbohydrates are ubiquitous in nature. The composition and structure of both reflect physiological state of paternal cells and are strikingly changed in diseases. The EV-associated glycans, alone or in combination with soluble glycans in related biological fluids, used as analytes, aim to capture full complex biomarker picture, enabling its use in different clinical settings. Bringing together EVs and glycans can help to extract meaningful data from their extreme and distinct heterogeneities for use in the real-time diagnostics. The glycans on the surface of EVs could mark their subpopulations and establish the glycosignature, the solubilisation signature and molecular patterns. They all contribute to a new way of looking at and looking for composite biomarkers.

(Re-) Defining "Successful Aging" as the Endpoint in Clinical Trials? Current Methods, Challenges, and Emerging Solutions.

"Successful aging" as defined in Rowe & Kahn's model aims to include the major domains of aging under a single overarching concept. From here the question arises how "successful aging" itself can be implemented as an endpoint in clinical research in a way that it is compliant to methodological regulatory framework and recommendations as formulated, for example, by the FDA. This article discusses from an applied perspective approaches and examples of how "successful aging" as a multi domain concept can be put into measurement practice. Narrative literature review. Existing methods of merging insights from, e.g., functional, social, and cognitive outcomes, can fail to perform under conditions of extreme heterogeneity, as often present in samples of older adults. In research on rare diseases, the methodological approach of a Multi Domain Responder Index (MDRI) has been proposed to handle heterogeneity. MDRIs may also provide a solution to combine aging outcomes from different domains into a single "successful aging" endpoint. However, strict measurement criteria will need to be fulfilled to find acceptance in decision making and validated meaningful change thresholds are a critical prerequisite. Gerontology can spearhead methodological approaches of handling multidimensional measurement under heterogeneity by validating a "successful aging" MDRI suitable for use as an endpoint in clinical research.

SCN1A Channels a Wide Range of Epileptic Phenotypes: Report of Novel and Known Variants with Variable Presentations.

SCN1A, the gene encoding for the Nav1.1 channel, exhibits dominant interneuron-specific expression, whereby variants disrupting the channel's function affect the initiation and propagation of action potentials and neuronal excitability causing various types of epilepsy. Dravet syndrome (DS), the first described clinical presentation of SCN1A channelopathy, is characterized by severe myoclonic epilepsy in infancy (SMEI). Variants' characteristics and other genetic or epigenetic factors lead to extreme clinical heterogeneity, ranging from non-epileptic conditions to developmental and epileptic encephalopathy (DEE). This current study reports on findings from 343 patients referred by physicians in hospitals and tertiary care centers in Greece between 2017 and 2023. Positive family history for specific neurologic disorders was disclosed in 89 cases and the one common clinical feature was the onset of seizures, at a mean age of 17 months (range from birth to 15 years old). Most patients were specifically referred for SCN1A investigation (Sanger Sequencing and MLPA) and only five for next generation sequencing. Twenty-six SCN1A variants were detected, including nine novel causative variants (c.4567A>Τ, c.5564C>A, c.2176+2T>C, c.3646G>C, c.4331C>A, c.1130_1131delGAinsAC, c.1574_1580delCTGAGGA, c.4620A>G and c.5462A>C), and are herein presented, along with subsequent genotype-phenotype associations. The identification of novel variants complements SCN1A databases extending our expertise on genetic counseling and patient and family management including gene-based personalized interventions.