Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-tissue proteomics identifies molecular signatures for sporadic and genetically defined Alzheimer disease cases

Alzheimer disease (AD) is a heterogeneous disease with many genes are associated with AD risk. Most proteomic studies, while instrumental in identifying AD pathways and genes, focus on single tissues and sporadic AD cases. Multi-tissue proteomic signatures for sporadic and genetically defined AD (e.g., pathogenic variant carriers in APP and PSEN1/2 and risk variant carriers in TREM2) will illuminate the biology of this heterogeneous disease.1,2 Here, we present one of the largest multi-tissue proteomic profiles, accessible through our web portal, based on 1,305 proteins in brain (n=360), cerebrospinal fluid (CSF; n=717), and plasma (n=490) from the Knight Alzheimer Disease Research Center (Knight ADRC) and Dominantly Inherited Alzheimer Network (DIAN) cohorts.3-5 We identified proteomic signatures in brain, CSF, and plasma for sporadic AD status and replicated these findings in multiple, independent datasets. The area under the curve (AUC) for CSF proteins was 0.89 in discovery and 0.90 in the replication dataset, which was significantly higher than the AUC for CSF p-tau181/Aβ42 (AUC = 0.81; P = 2.4×10-6). We also identified a specific proteomic signature for TREM2 variant carriers that differentiated TREM2 variant carriers from sporadic AD cases and controls with high sensitivity and specificity (AUC = 0.81 - 1). In addition, the proteins that showed differential levels in sporadic AD were also altered in autosomal dominant AD, but with greater effect size (1.4 times, P = 3.8×10-5), and proteins associated with autosomal dominant AD, in brain tissue also replicated on CSF (p=1.36×10-9). Enrichment analyses highlighted several pathways including AD (calcineurin, APOE, GRN), Parkinson disease (α-synuclein, LRRK2), and innate immune response (SHC1, MAPK3, SPP1) for the sporadic AD or TREM2 variant carriers. Our findings show the power of multi-tissue proteomics’ contribution to the understanding of AD biology and to the creation of tissue-specific prediction models for individuals with specific genetic profiles, ultimately supporting its utility in creating individualized disease risk evaluation and treatment.
ELEMENTOS-TRAÇO E ATRIBUTOS QUÍMICOS DO SOLO EM ÁREAS DE CULTIVO DE ERVA-MATE COM APLICAÇÃO DE DEJETO DE SUÍNOS

Com o objetivo de mensurar os efeitos da aplicação de dejeto de suíno na cultura da erva-mate (Ilex paraguariensis St. Hil.), avaliou-se as alterações nos atributos do solo e nos teores de elementos-traço, suas correlações e os teores totais nas plantas. Foram coletadas amostras de solo e plantas em áreas com 45 e 35 anos de cultivo, em quatro profundidades, no município de Presidente Castello Branco - SC, no período de janeiro de 2017. Verificou-se redução nos teores de macronutrientes e aumento da acidez do solo em comparação a área de mata. Os teores pseudototais de Cr, Pb e Ni foram influenciados pela aplicação do dejeto, apresentando valores superiores nas áreas cultivadas, com exceção do Cu e Cd foram superiores na área de mata, fato este que pode ser atribuído ao material de origem dos solos. Entretanto, a aplicação de dejeto não aumentou os teores desses elementos no solo para níveis que atingissem o patamar de prevenção estabelecido pela legislação brasileira. A análise de componentes principais permitiu agrupar nos dois primeiros componentes mais de 50% da variância total para cada profundidade. A área de mata apresentou maior distância das demais áreas nas profundidades estudadas, demonstrando que o manejo alterou significativamente a qualidade do solo. Os teores totais de elementos-traço não variam com o tempo de aplicação do dejeto no solo, entretanto os teores de Cd e Pb nas plantas encontram-se acima do limite considerado tolerável pela Anvisa e União Europeia.
Highly Efficient Spatial–Temporal Correlation Basis for 5G IoT Networks

One of the major concerns in 5G IoT networks is that most of the sensor nodes are powered through limited lifetime, which seriously affects the performance of the networks. In this article, Compressive sensing (CS) technique is used to decrease transmission cost in 5G IoT networks. Sparse basis is one of the important steps in the CS. However, most of the existing sparse basis-based method such as DCT (Discrete cosine transform) and DFT (Discrete Fourier Transform) basis do not capture data structure characteristics in the networks. They also do not take into consideration multi-resolution representations. In addition, some of sparse basis-driven methods exploit either spatial or temporal features, resulting in performance degradation of CS-based strategies. To address these challenging problems, we propose a novel spatial–temporal correlation basis algorithm (SCBA). Subsequently, an optimal basis algorithm (OBA) is provided considering greedy scoring criteria. To evaluate the efficiency of OBA, orthogonal wavelet basis algorithm (OWBA) by employing NS (Numerical Sparsity) and GI (Gini Index) sparse metrics is also presented. In addition, we discuss the complexity of the above three algorithms, and prove that OBA has low numerical rank. After experimental evaluation, we found that OBA is capable of the sparsest representing original signal compared to spatial, DCT, haar-1, haar-2, and rbio5.5. Furthermore, OBA has the low recovery error and the highest efficiency.
Do institutions matter for tourism spending?

Institutional frameworks are important for individuals’ attitudes and behaviours, and thus they are important for travel decisions. This study endeavours to examine the influence of various formal and informal institutional factors on tourism spending for a global sample of 120 countries from 2002 to 2019. Applying the two-step system generalised method of moments estimate, the results are robust and consistent. First, informal institutions, that is, colonial history, socialist history, origin of the legal system, religion and language, are important explanatory factors for differences in tourism spending between countries. Second, improvements in formal institutions appear to increase domestic tourism spending while they decrease outbound tourism spending. The results have important policy implications. JEL code: E02, Z30, Z32.
BIOCHEMICAL RESPONSES FROM BIOMASS OF ISOLATED Chlorella sp., UNDER DIFFERENT CULTIVATION MODES: NON-LINEAR MODELLING OF GROWTH KINETICS

In this study, the effect of different modes of cultivation viz., photoautotrophic (AT), heterotrophic (HT) and photomixotrophic (MT), on the growth and biochemical responses of Chlorella sp. isolated from local ponds. The performance of microalgal growth was quantified using nonlinear growth models such as Gompertz, logistic, Baranyi-Roberts, Morgan under different cultivation conditions. The results revealed that microalgae could grow better in MT than in other cultivation modes with a major increase in biochemical responses for carbohydrates, which showed higher accumulation under HT. The maximum biomass concentration was 1.24 g L-1 (MT), 1.16 g L-1 (HT), 0.76 g L-1 (AT) with maximum specific growth rates of 0.0083 h-1 (HT), 0.0078 h-1 (MT) and 0.0055 h-1 (AT) respectively. The biomass concentration was higher in the order of MT>HT>AT for which MT yielded 8.8 fold higher biomass, compared with the initial biomass concentration, at the end of experiments (16 days). Concomitant increases in biochemical responses were observed in the three cultivation conditions. Protein and lipid accumulation in the MT mode was higher (1.2 fold) compared with the initial protein yield as well as the other cultivation modes. However, the carbohydrate yield was higher (1.12 fold) in the heterotrophic mode than in other cultivation conditions.
Genetic Evidence of the Black Death in the Abbey of San Leonardo (Apulia Region, Italy): Tracing the Cause of Death in Two Individuals Buried with Coins

The Abbey of San Leonardo in Siponto (Apulia, Southern Italy) was an important religious and medical center during the Middle Ages. It was a crossroads for pilgrims heading along the Via Francigena to the Sanctuary of Monte Sant’Angelo and for merchants passing through the harbor of Manfredonia. A recent excavation of Soprintendenza Archeologica della Puglia investigated a portion of the related cemetery, confirming its chronology to be between the end of the 13th and beginning of the 14th century. Two single graves preserved individuals accompanied by numerous coins dating back to the 14th century, hidden in clothes and in a bag tied to the waist. The human remains of the individuals were analyzed in the Laboratorio di Antropologia Fisica of Soprintendenza ABAP della città metropolitana di Bari. Three teeth from each individual were collected and sent to the Istituto Zooprofilattico Sperimentale di Puglia e Basilicata to study infectious diseases such as malaria, plague, tuberculosis, epidemic typhus and Maltese fever (Brucellosis), potentially related to the lack of inspection of the bodies during burial procedures. DNA extracted from six collected teeth and two additional unrelated human teeth (negative controls) were analyzed using PCR to verify the presence of human DNA (β-globulin) and of pathogens such as Plasmodium spp. , Yersinia pestis, Mycobacterium spp. , Rickettsia spp. and Brucella spp. The nucleotide sequence of the amplicon was determined to confirm the results. Human DNA was successfully amplified from all eight dental extracts and two different genes of Y. pestis were amplified and sequenced in 4 out of the 6 teeth. Molecular analyses ascertained that the individuals buried in San Leonardo were victims of the Black Death (1347–1353) and the data confirmed the lack of inspection of the corpses despite the presence of numerous coins. This study represents molecular evidence, for the first time, of Southern Italy’s involvement in the second wave of the plague pandemic.
Fungal laccases production using tomato-based medium: a factorial design approach

This study was aimed to stimulate laccase production by Trametes pubescens MUT 2400 by using a tomato-based medium. Two sequential 2x2 factorial designs were used to determine the effect of carbon (C) and nitrogen (N) source concentration on laccase activity and biomass concentration; copper was used as the sole inducer (0.75 mM). Analysis of the first factorial design showed that N had a strong positive effect on the maximum laccase activity, which occurred at day 12 of cultivation and final biomass concentration. When both C and N concentration (25% v/v, 28.7 g/L) were set at the high level, laccase activity and biomass growth were maximal (9.5 U/mL and 7.15 mg/mL). A second factorial experiment with C and N concentrations in the ranges of 25 - 50 % v/v and 28.7 - 48.7 g/L, respectively, established based on the results of the first one, showed that laccase activity could be further increased by either increasing C or N to their high levels. The enzymatic peak occurred at the 17th day in this second design with a maximum laccase activity of 28.6-32.8 U/mL. Laccase peak occurred when reducing sugars were completely depleted from the medium. The results of this study indicated that laccase activity could be enhanced by acting on nutrient content, and tomato-based medium is a good fermentation substrate.
Towards Potential Content-Based Features Evaluation to Tackle Meaningful Citations

The scientific community has presented various citation classification models to refute the concept of pure quantitative citation analysis systems wherein all citations are treated equally. However, a small number of benchmark datasets exist, which makes the asymmetric citation data-driven modeling quite complex. These models classify citations for varying reasons, mostly harnessing metadata and content-based features derived from research papers. Presently, researchers are more inclined toward binary citation classification with the belief that exploiting the datasets of incomplete nature in the best possible way is adequate to address the issue. We argue that contemporary ML citation classification models overlook essential aspects while selecting the appropriate features that hinder elutriating the asymmetric citation data. This study presents a novel binary citation classification model exploiting a list of potential natural language processing (NLP) based features. Machine learning classifiers, including SVM, KLR, and RF, are harnessed to classify citations into important and non-important classes. The evaluation is performed using two benchmark data sets containing a corpus of around 953 paper-citation pairs annotated by the citing authors and domain experts. The study outcomes exhibit that the proposed model outperformed the contemporary approaches by attaining a precision of 0.88.
Tackling the Biological Meaning of the Human Olfactory Bulb Dyshomeostatic Proteome across Neurological Disorders: An Integrative Bioinformatic Approach

Olfactory dysfunction is considered an early prodromal marker of many neurodegenerative diseases. Neuropathological changes and aberrant protein aggregates occur in the olfactory bulb (OB), triggering a tangled cascade of molecular events that is not completely understood across neurological disorders. This study aims to analyze commonalities and differences in the olfactory protein homeostasis across neurological backgrounds with different spectrums of smell dysfunction. For that, an integrative analysis was performed using OB proteomics datasets derived from subjects with Alzheimer’s disease (AD), Parkinson’s disease (PD), mixed dementia (mixD), dementia with Lewy bodies (DLB), frontotemporal lobar degeneration (FTLD-TDP43), progressive supranuclear palsy (PSP) and amyotrophic lateral sclerosis (ALS) with respect to OB proteome data from neurologically intact controls. A total of 80% of the differential expressed protein products were potentially disease-specific whereas the remaining 20% were commonly altered across two, three or four neurological phenotypes. A multi-level bioinformatic characterization revealed a subset of potential disease-specific transcription factors responsible for the downstream effects detected at the proteome level as well as specific densely connected protein complexes targeted by several neurological phenotypes. Interestingly, common or unique pathways and biofunctions were also identified, providing novel mechanistic clues about each neurological disease at olfactory level. The analysis of olfactory epithelium, olfactory tract and primary olfactory cortical proteotypes in a multi-disease format will functionally complement the OB dyshomeostasis, increasing our knowledge about the neurodegenerative process across the olfactory axis.
Robust Control Design Based on Perturbation Cancellation for Micro-Positioning Design with Hysteresis

Based on the superiority of the piezoelectric elements, including lightweight, high electric mechanical transformation efficiency and a quick response time, a piezoelectric-based micro-positioning actuator is developed in this investigation. For eliminating the effects of hysteresis and modeling uncertainties that appeared in this micro-positioning actuator, a nonlinear adaptive fuzzy robust control design with a perturbation cancellation ability is proposed for this micro-positioning design to achieve a positioning resolution of 1 μm. Structurally, this proposed robust control methodology contains two particular parts: a universal fuzzy approximator and a robust compensator, which are employed to cancel the modeling uncertainties caused by the perturbed parts of the micro-positioning actuator and mitigate the approximation error between the modeling uncertainties and the universal fuzzy approximator, respectively. From both the numerical simulations and real validations, this proposed micro-positioning design performs a promising positioning performance in the micrometer level.
The role of health anxiety in healthcare management transition and health-related quality of life in young adults with medical conditions

ABSTRACT Adolescents and young adults (AYAs) with a chronic medical condition (CMC) are tasked with independent health care management transition. However, the role of health anxiety in care management is unclear. The present study evaluated whether health anxiety moderates transition readiness-to-health-related quality of life (HRQoL). College students (N = 135) completed cross-sectional surveys of demographics, health anxiety, transition readiness, and HRQoL. Analyses revealed interaction effects for health anxiety and transition readiness on HRQoL outcomes. For lower health anxiety, greater transition readiness was associated with greater HRQoL. Therefore, examining health anxiety in AYAs transitioning care may relate to long-term HRQoL outcomes.
MINERALOGY AND GEOCHEMISTRY IMPACT ON MIDDLE AND LATE EOCENE CARBONATE ROCKS., EAST HELWAN AREA, EGYPT

The present study deals with Geochemistry and Mineralogical impact on Middle and Late Eocene rocks exposed at East Helwan area -Egypt. The studied area lies between Latitudes 29o 47' 30ʹʹ and 29o 53 ' 00ʹʹ N. and longitudes 31o 21' 04ʹʹ and 31o 28' 45ʹʹ E. Middle and Late Eocene sediments are subdivided into five rock units from base to top: Middle Eocene (Gebel Houf and Observatory Formations); Late Eocene (EL-Qurn, Wadi Garawi and Wadi Houf Formations). Mineral composition was done on nineteen carbonate samples (using x-ray diffraction method. The study reveals the presence of a number of carbonate minerals; calcite, dolomite, and non-carbonate minerals name Gypsum, Anhydrite, Halite, and quartz in variable amounts. Chemical composition of the carbonate rocks for fifty four samples (major and trace elements) represent Middle and Late Eocene carbonates were done. The data reveal that Middle and Late Eocene carbonates were deposited under shallow, alkaline and oxidizing environmental conditions.
Comparative efficacy of different estrus synchronisation protocols in postpartum acyclic crossbred cows

The present study is undertaken in 24 postpartum acyclic crossbred cows maintained under rural managemental conditions. The cows are randomly divided into three groups viz. , Ovysynch, Ovysynch + PRID, PRID + PG and efficacy was recorded. The estrus response (per cent) is observed as 75.00, 100.00 and 87.50 with the mean duration of estrus (hours) as 50.62 ± 8.39, 68.00 ± 2.61 and 58.63 ± 9.36 for Group I, II and III, respectively. Intensity of estrus exhibited is higher in Group II (62.5%) followed by Group III (50.0%) & Group I (25.0%), respectively. The first service conception rate (per cent) is 50.00 in both Group I and III, whereas it is recorded lower in Group II (37.50). The overall conception rate (per cent) is highest in Group III (62.50) followed by Group I and Group II (50.00, each) with no significant difference ( P >0.05). It is concluded that Ovysynch + PRID protocol resulted in better estrus exhibition, while PRID + PG protocol is effective in obtaining optimum conception rate with fixed time Artificial Insemination in postpartum acyclic cows.
Transcriptomic Analysis of Stropharia Rugosoannulata Reveals Potential Carbohydrate Metabolism and Cold Resistance Mechanisms Under Low-Temperature Stress

Low temperature is an important environmental factor that restricts the growth of Stropharia rugosoannulata; however, the molecular mechanisms underlying S. rugosoannulata responses to low-temperature stress are largely unknown. In this study, we performed a transcriptome analysis of a high-sensitivity strain (DQ-1) and low-sensitivity strain (DQ-3) under low-temperature stress. The liquid hyphae of S. rugosoannulata treated at 25°C and 10°C were analyzed by RNA-Seq, and a total of 9499 differentially expressed genes (DEGs) were identified. GO and KEGG enrichment analyses showed that these genes were enriched in “xenobiotic biodegradation and metabolism”, “carbohydrate metabolism”, “lipid metabolism” and “oxidoreductase activity”. Further research found that carbohydrate enzyme (AA, GH, CE, and GT) genes were downregulated more significantly in DQ-1 than DQ-3 and several cellulase activities were also reduced to a greater extent. Moreover, the CAT1, CAT2, GR, and POD genes and more heat shock protein genes (HSP20, HSP78 and sHSP) were upregulated in the two strains after low-temperature stress, and the GPX gene and more heat shock protein genes were upregulated in DQ-3. In addition, the enzyme activity and qRT–PCR results showed trends similar to those of the RNA-Seq results. This result indicates that low-temperature stress reduces the expression of different AA, GH, CE, and GT enzyme genes and reduces the secretion of cellulase, thereby reducing the carbohydrate metabolism process and mycelial growth of S. rugosoannulata. Moreover, the expression levels of different types of antioxidant enzymes and heat shock proteins are also crucial for S. rugosoannulata to resist low-temperature stress. In short, this study will provide a basis for further research on important signaling pathways, gene functions and variety breeding of S. rugosoannulata related to low-temperature stress.
Numerical Modeling of 3D Slopes with Weak Zones by Random Field and Finite Elements

This work investigates an analysis method for the stability of a three-dimensional (3D) slope with weak zones considering spatial variability on the basis of two-phase random media and the finite element method. By controlling the volume fractions of rock and weak zones, two-phase random media are incorporated into the 3D slope model to simulate the random distribution of rock and weak zones. Then, a rotation of a Gaussian random field is performed to account for the inclination of the weak zones. The validity of the proposed model for use in the analysis of the stability of 3D slopes with weak zones was verified by comparing it to existing results and analytical solutions. The failure mechanism of the slope is considered by examining the plastic failure zone at incipient slope failure. The safety factor is sensitive to the inclination of the weak zones, but it is predictable. Parametric studies on the inclination of the layer of weak zones demonstrate that when the rotation angle of the weak zones is approximately parallel to the slope inclination, the slope is prone to slippage along the weak zones, resulting in a significant reduction in the safety factor. The findings of this research can serve as the foundation for further research on the stability of slopes with weak zones.
A method of atmospheric corrosion prediction for aircraft structure

A simulation prediction system, test pieces → flat test pieces → structural parts, for the atmospheric corrosion of aircraft is proposed to provide guidance for aircraft anti‐corrosion material selection and outfield maintenance. Based on the shell current distribution, a COMSOL corrosion simulation prediction model was constructed and applied to three types of test parts. The correctness of simulation principle is verified by comparing the galvanic current of simulation and test on each electrode surface of multi‐electrode system. Comparing the simulated potential distribution at 100 µm electrolyte layer with the corrosion morphology after 12 wet–dry corrosion periods, it is found that simulation and test are in good agreement. It is also proved that the 100 µm static liquid film can reflect the corrosion of this kind of wet–dry cycle. Comparing the corrosion depths of different periods at three different points and the simulated corrosion depth with time, it is found that the corrosion depth of the first four periods was larger than the simulated depth, which was less than the simulated value after four periods. The model was applied to the local structural parts of aircraft. Then, corrosion position and corrosion area were predicted. The results were compared with the accelerated test results to verify the accuracy of the model's prediction of structural parts. At the same time, the corrosion depth of the structural parts was also predicted.