Miracle-dz/UniFAR-FTUs huggingface dataset:
Customizing Multifunctional Neural Interfaces through Thermal Drawing Process

Fiber drawing enables scalable fabrication of multifunctional flexible fibers that integrate electrical, optical and microfluidic modalities to record and modulate neural activity. Constraints on thermomechanical properties of materials, however, have prevented integrated drawing of metal electrodes with low-loss polymer waveguides for concurrent electrical recording and optical neuromodulation. Here we introduce two fabrication approaches: (1) an iterative thermal drawing with a soft, low melting temperature (Tm) metal indium, and (2) a metal convergence drawing with traditionally non-drawable high Tm metal tungsten. Both approaches deliver multifunctional flexible neural interfaces with low-impedance metallic electrodes and low-loss waveguides, capable of recording optically-evoked and spontaneous neural activity in mice over several weeks. We couple these fibers with a light-weight mechanical microdrive (1g) that enables depth-specific interrogation of neural circuits in mice following chronic implantation. Finally, we demonstrate the compatibility of these fibers with magnetic resonance imaging (MRI) and apply them to visualize the delivery of chemical payloads through the integrated channels in real time. Together, these advances expand the domains of application of the fiber-based neural probes in neuroscience and neuroengineering.
Trend, population structure, and trait mapping from 15 years of national varietal trials of UK winter wheat

There are now a rich variety of genomic and genotypic resources available to wheat researchers and breeders. However, the generation of high-quality and field-relevant phenotyping data which is required to capture the complexities of gene x environment interactions remains a major bottleneck. Historical datasets from national variety performance trials (NVPT) provide sufficient dimensions, in terms of numbers of years and locations, to examine phenotypic trends and study gene x environment interactions. Using NVPT for winter wheat varieties grown in the UK between 2002 – 2017, we examined temporal trends for eight traits related to yield, adaptation, and grain quality performance. We show a non-stationary linear trend for yield, grain protein content, HFN and days to ripening. Our data also show high environmental stability for yield, grain protein content and specific weight in UK winter wheat varieties and high environmental sensitivity for Hagberg Falling Number. Using the historical NVPT data in a genome-wide association analysis, we uncovered a significant marker-trait association peak on wheat chromosome 6A spanning the NAM-A1 gene that have been previously associated with early senescence. Together our results show the value of utilizing the data routinely collected during variety evaluation process for examining breeding progress and the genetic architecture of important traits.
Impact of COVID-19 Pandemic on Pre-Treatment Delays, Detection, and Clinical Characteristics of Tuberculosis Patients in Ningxia Hui Autonomous Region, China

Background: To contain the pandemic of COVID-19, China has implemented a series of public health interventions that impacted the tuberculosis control substantially, but these impacts may vary greatly depending on the severity of the local COVID-19 epidemic. The impact of COVID-19 on TB control in Ningxia Hui Autonomous Region is little known. Methods: Based on the national TB Information Management System (TBIMS), this study accessed the actual impact of COVID-19 on TB by comparing TB notifications, pre-treatment delays, and clinical characteristics of TB cases between 2020 COVID-19 period and 2017–2019 baseline. The data were divided into three periods based on the response started to fight against COVID-19 in Ningxia Hui Autonomous Region, including the control period (10 weeks before the pandemic), intensive period (10 weeks during the Ningxia Hui Autonomous Region lockdown), and regular (10 additional weeks after Ningxia Hui Autonomous Region reopen). Results: TB notification dropped sharply in the first week of the intensive period but took significantly longer to return to the previous level in 2020 compared with the 2017–2019 baseline. Totally, the TB notification rates decreased by more than 60% in the intensive period of COVID-19 compared with the average level of 2017–2019. The sputum smear-positive rate of TB patients diagnosed in intensive period of COVID-19 was significantly higher than that in the corresponding periods of 2017–2019 (P < 0.001). The rate of cavity on X-ray inspection of TB cases diagnosed in the intensive period of COVID-19 was significantly higher than that in period 2 of 2017–2019 (23.5 vs. 15.4%, P = 0.004). The patients' delay in the intensive period was significantly longer than that before the pandemic (P = 0.047). Conclusions: The TB notification in Ningxia was impacted dramatically by the pandemic of COVID-19. To compensate for the large numbers of missed diagnosis as well as delayed diagnosis during the intensive period of COVID-19, an urgent restoration of normal TB services, and further emphasis on enhanced active case finding and scale-up of household contact tracing and screening for TB-related symptoms or manifestation, will be essential.
Nexus vs. Silo Investment Planning Under Uncertainty

Water, energy, and agricultural infrastructure investments have important inter-relations fulfilling potentially competing objectives. When shaping investment plans, decision makers need to evaluate those interactions and the associated uncertainties. We compare planning infrastructure under uncertainty with an integrated water-energy-food nexus framework and with sector-centered (silo) frameworks. We use WHAT-IF, an open-source hydroeconomic decision support tool with a holistic representation of the power and agriculture sectors. The tool is applied to an illustrative synthetic case and to a complex planning problem in the Zambezi River Basin involving reservoirs, hydropower, irrigation, transmission lines and power plant investments. In the synthetic case, the nexus framework selects investments that generate more synergies across sectors. In sector-centered frameworks, the value of investments that impact multiple sectors (like hydropower, bioenergy, and desalinization) are under- or overestimated. Furthermore, the nexus framework identifies risks related to uncertainties that are not linked to the investments respective sectors. In the Zambezi river case, we find that most investments are mainly sensitive to parameters related to their respective sectors, and that financial parameters like discount rate, capital costs or carbon taxes are driving the feasibility of investments. However, trade-offs between water for irrigation and water for hydropower are important; ignoring trade-offs in silo frameworks increases the irrigation expansion that is perceived as beneficial by 22% compared to a nexus framework that considers irrigation and hydropower jointly. Planning in a nexus framework is expected to be particularly important when projects and uncertainties can considerably affect the current equilibrium.
Insular Connectivity Is Associated With Self-Appraisal of Cognitive Function After a Concussion

Concussion is associated with acute cognitive impairments, with declines in processing speed and reaction time being common. In the clinical setting, these issues are identified via symptom assessments and neurocognitive test (NCT) batteries. Practice guidelines recommend integrating both symptoms and NCTs into clinical decision-making, but correlations between these measures are often poor. This suggests that many patients experience difficulties in the self-appraisal of cognitive issues. It is presently unclear what neural mechanisms give rise to appraisal mismatch after a concussion. One promising target is the insula, which regulates aspects of cognition, particularly interoception and self-monitoring. The present study tested the hypothesis that appraisal mismatch is due to altered functional connectivity of the insula to frontal and midline structures, with hypo-connectivity leading to under-reporting of cognitive issues and hyper-connectivity leading to over-reporting. Data were collected from 59 acutely concussed individuals and 136 normative controls, including symptom assessments, NCTs and magnetic resonance imaging (MRI) data. Analysis of resting-state functional MRI supported the hypothesis, identifying insular networks that were associated with appraisal mismatch in concussed athletes that included frontal, sensorimotor, and cingulate connections. Subsequent analysis of diffusion tensor imaging also determined that symptom over-reporting was associated with reduced fractional anisotropy and increased mean diffusivity of posterior white matter. These findings provide new insights into the mechanisms of cognitive appraisal mismatch after a concussion. They are of particular interest given the central role of symptom assessments in the diagnosis and clinical management of concussion.
Benchmarking Taxonomic and Genetic Diversity After the Fact: Lessons Learned From the Catastrophic 2019–2020 Australian Bushfires

Environmental catastrophes are increasing in frequency and severity under climate change, and they substantially impact biodiversity. Recovery actions after catastrophes depend on prior benchmarking of biodiversity and that in turn minimally requires critical assessment of taxonomy and species-level diversity. Long-term recovery of species also requires an understanding of within-species diversity. Australia’s 2019–2020 bushfires were unprecedented in their extent and severity and impacted large portions of habitats that are not adapted to fire. Assessments of the fires’ impacts on vertebrates identified 114 species that were a high priority for management. In response, we compiled explicit information on taxonomic diversity and genetic diversity within fire-impacted vertebrates to provide to government agencies undertaking rapid conservation assessments. Here we discuss what we learned from our effort to benchmark pre-fire taxonomic and genetic diversity after the event. We identified a significant number of candidate species (genetic units that may be undescribed species), particularly in frogs and mammals. Reptiles and mammals also had high levels of intraspecific genetic structure relevant to conservation management. The first challenge was making published genetic data fit for purpose because original publications often focussed on a different question and did not provide raw sequence read data. Gaining access to analytical files and compiling appropriate individual metadata was also time-consuming. For many species, significant unpublished data was held by researchers. Identifying which data existed was challenging. For both published and unpublished data, substantial sampling gaps prevented areas of a species’ distribution being assigned to a conservation unit. Summarising sampling gaps across species revealed that many areas were poorly sampled across taxonomic groups. To resolve these issues and prepare responses to future catastrophes, we recommend that researchers embrace open data principles including providing detailed metadata. Governments need to invest in a skilled taxonomic workforce to document and describe biodiversity before an event and to assess its impacts afterward. Natural history collections should also target increasing their DNA collections based on sampling gaps and revise their collection strategies to increasingly take population-scale DNA samples in order to document within-species genetic diversity.
A Sight on Single-Cell Transcriptomics in Plants Through the Prism of Cell-Based Computational Modeling Approaches: Benefits and Challenges for Data Analysis

Single-cell technology is a relatively new and promising way to obtain high-resolution transcriptomic data mostly used for animals during the last decade. However, several scientific groups developed and applied the protocols for some plant tissues. Together with deeply-developed cell-resolution imaging techniques, this achievement opens up new horizons for studying the complex mechanisms of plant tissue architecture formation. While the opportunities for integrating data from transcriptomic to morphogenetic levels in a unified system still present several difficulties, plant tissues have some additional peculiarities. One of the plants’ features is that cell-to-cell communication topology through plasmodesmata forms during tissue growth and morphogenesis and results in mutual regulation of expression between neighboring cells affecting internal processes and cell domain development. Undoubtedly, we must take this fact into account when analyzing single-cell transcriptomic data. Cell-based computational modeling approaches successfully used in plant morphogenesis studies promise to be an efficient way to summarize such novel multiscale data. The inverse problem’s solutions for these models computed on the real tissue templates can shed light on the restoration of individual cells’ spatial localization in the initial plant organ—one of the most ambiguous and challenging stages in single-cell transcriptomic data analysis. This review summarizes new opportunities for advanced plant morphogenesis models, which become possible thanks to single-cell transcriptome data. Besides, we show the prospects of microscopy and cell-resolution imaging techniques to solve several spatial problems in single-cell transcriptomic data analysis and enhance the hybrid modeling framework opportunities.
Exploring Multiple Aspects of Taxonomic and Functional Diversity in Microphytobenthic Communities: Effects of Environmental Gradients and Temporal Changes

Biodiversity has traditionally been quantified using taxonomic information but the importance of also considering its functional characteristics has recently gained an increasing attention among microorganisms. However, studies exploring multiple aspects of taxonomic and functional diversity and their temporal variations are scarce for diatoms, which is one of the most important microbial groups in aquatic ecosystems. Here, our aim was to examine the taxonomic and functional alpha and beta diversities of diatoms in a coastal rock pool system characterized by a naturally high environmental heterogeneity. We also investigated the temporal differences in the diversity patterns and drivers. The relationship between the species richness and functional dispersion was temporally coherent, such that species-poor communities tended to be functionally clustered. The trend between the species richness and taxonomic uniqueness of community composition was temporally inconsistent, changing from negative to non-significant over time. Conductivity or distance to the sea or both were key determinants of species richness, functional dispersion, and uniqueness of community composition. The increase of community dissimilarity with an increasing environmental distance was stronger for the taxonomic than the functional composition. Our results suggest that even minor decreases in the species richness may result in a lowered functional diversity and decreased ecosystem functioning. Species-poor ecosystems may, however, have unique species compositions and high contributions to regional biodiversity. Despite changing the species compositions along the environmental gradients, communities may remain to have a high functional similarity and robustness in the face of environmental changes. Our results highlight the advantage of considering multiple biodiversity metrics and incorporating a temporal component for a deeper understanding of the effects of environmental changes on microbial biodiversity.
Development and Validation of a 7-Gene Prognostic Signature to Improve Survival Prediction in Pancreatic Ductal Adenocarcinoma

Background: Previous prognostic signatures of pancreatic ductal adenocarcinoma (PDAC) are mainly constructed to predict the overall survival (OS), and their predictive accuracy needs to be improved. Gene signatures that efficaciously predict both OS and disease-free survival (DFS) are of great clinical significance but are rarely reported. Methods: Univariate Cox regression analysis was adopted to screen common genes that were significantly associated with both OS and DFS in three independent cohorts. Multivariate Cox regression analysis was subsequently performed on the identified genes to determine an optimal gene signature in the MTAB-6134 training cohort. The Kaplan–Meier (K-M), calibration, and receiver operating characteristic (ROC) curves were employed to assess the predictive accuracy. Biological process and pathway enrichment analyses were conducted to elucidate the biological role of this signature. Results: Multivariate Cox regression analysis determined a 7-gene signature that contained ASPH, DDX10, NR0B2, BLOC1S3, FAM83A, SLAMF6, and PPM1H. The signature had the ability to stratify PDAC patients with different OS and DFS, both in the training and validation cohorts. ROC curves confirmed the moderate predictive accuracy of this signature. Mechanically, the signature was related to multiple cancer-related pathways. Conclusion: A novel OS and DFS prediction model was constructed in PDAC with multi-cohort and cross-platform compatibility. This signature might foster individualized therapy and appropriate management of PDAC patients.
Developing a Data-Driven Approach in Order to Improve the Safety and Quality of Patient Care

Objective: To improve the safety and quality of patient care in hospitals by shaping clinical pathways throughout the patient journey. Study Setting: A risk model designed for healthcare organizations in the context of the challenges arising from comorbidity and other treatment-related complexities. Study Design: The core of the model is the patient and his intra-hospital journey, which is analyzed using a data-driven approach. The structure of a predictive model to support organizational and clinical decision-making activities is explained. Data relating to each step of the intra-hospital journey (from hospital admission to discharge) are extracted from clinical records. Principal Findings: The proposed approach is feasible and can be used effectively to improve safety and quality. It enables the evaluation of clinical risks at each step of the patient journey. Conclusion: Based on data from real cases, the model can record and calculate, over time, variables and behaviors that affect the safety and quality of healthcare organizations. This provides a greater understanding of healthcare processes and their complexity which can, in turn, advance research relating to clinical pathways and improve strategies adopted by organizations.
Targeted Next Generation Sequencing and Diagnosis of Congenital Hemolytic Anemias: A Three Years Experience Monocentric Study

Congenital hemolytic anemias (CHAs) are heterogeneous and rare disorders caused by alterations in structure, membrane transport, metabolism, or red blood cell production. The pathophysiology of these diseases, in particular the rarest, is often poorly understood, and easy-to-apply tools for diagnosis, clinical management, and patient stratification are still lacking. We report the 3-years monocentric experience with a 43 genes targeted Next Generation Sequencing (t-NGS) panel in diagnosis of CHAs; 122 patients from 105 unrelated families were investigated and the results compared with conventional laboratory pathway. Patients were divided in two groups: 1) cases diagnosed with hematologic investigations to be confirmed at molecular level, and 2) patients with unexplained anemia after extensive hematologic investigation. The overall sensitivity of t-NGS was 74 and 35% for families of groups 1 and 2, respectively. Inside this cohort of patients we identified 26 new pathogenic variants confirmed by functional evidence. The implementation of laboratory work-up with t-NGS increased the number of diagnoses in cases with unexplained anemia; cytoskeleton defects are well detected by conventional tools, deserving t-NGS to atypical cases; the diagnosis of Gardos channelopathy, some enzyme deficiencies, familial siterosterolemia, X-linked defects in females and other rare and ultra-rare diseases definitely benefits of t-NGS approaches.
Goat AKAP12: Indel Mutation Detection, Association Analysis With Litter Size and Alternative Splicing Variant Expression

A-kinase anchoring protein 12 (AKAP12) plays key roles in male germ cells and female ovarian granulosa cells, whereas its influence on livestock litter size remains unclear. Herein we detected the genetic variants of AKAP12 gene and their effects on litter size as well as alternative splicing variants expression in Shaanbei white cashmere (SBWC) goats, aiming at exploring theoretical basis for goat molecular breeding. We identified two Insertion/deletions (Indels) (7- and 13-bp) within the AKAP12 gene. Statistical analyses demonstrated that the 13-bp indel mutation in the 3′ UTR was significantly associated with litter size (n = 1,019), and the carriers with DD genotypes presented lower litter sizes compared with other carriers (P < 0.01). Bioinformatics analysis predicted that this 13-bp deletion sequence could bind to the seed region of miR-181, which has been documented to suppress porcine reproductive and respiratory syndrome virus (PRRSV) infection by targeting PRRSV receptor CD163 and affect the pig litter size. Therefore, luciferase assay for this 13-bp indel binding with miRNA-181 was performed, and the luciferase activity of pcDNA-miR-181-13bp-Deletion-allele vector was significantly lower than that of the pcDNA-miR-181-13bp-Insertion-allele vector (P < 0.05), suggesting the reduced binding capability with miR-181 in DD genotype. Given that alternative spliced variants and their expression considerably account for the Indel genetic effects on phenotypic traits, we therefore detected the expression of the alternative spliced variants in different tissues and identified that AKAP12-AS2 exhibited the highest expression levels in testis tissues. Interestingly, the AKAP12-AS2 expression levels of homozygote DD carriers were significantly lower than that of individuals with heterozygote ID, in both testis and ovarian tissues (P < 0.05), which is consistent with the effect of the 13-bp deletion on the reduced litter size. Taken together, our results here suggest that this 13-bp indel mutation within goat AKAP12 might be utilized as a novel molecular marker for improving litter size in goat breeding.