Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Genetic Variability Amongst Polyploid Genotypes of Pteris vittata L. From Various Geographic Locales of India

Pteris vittata L. is very common and a widely distributed species belongs to the family Pteridaceae. Various cytotypes from diploid to octaploid is available in this fern species. The present work has been carried out for genetic diversity in this fern both within and between the cytotypes. The molecular analysis at inter- as well as intra-species has been carried out with 57 accessions of P. vittata as well as of other species of Pteris with Microsorium punctatum considered as an out group taxon. For the present study 48 P. vittata (36 tetraploid and 12 pentaploid) and five of other species (four P. cretica, one P. pellucida, one P. tremula, one P. quadriaurita, and two P. ensiformis) accessions were used. The UPGMA (unweighted pair group method with arithmetic mean) dendrograms were generated for each method separately, as well as for all methods cumulatively, after a 1000 replicate bootstrap analysis. In order to determine the utility of each of the method, a comparative statistical assessment was done and marker index (MI), expected average heterozygosity, fraction of polymorphic loci and effective multiplex ratio (EMR) were calculated in case of each of the methods used in the present study. At the level of individual methods highest MI was obtained for directed amplification of minisatellites DNA (DAMD) method. Our findings of the present study concluded that out of the three methods Random Amplified Polymorphic DNA (RAPD), Inter-Simple Sequence Repeat (ISSR), and Directed Amplification of Minisatellite DNA (DAMD), DAMD was the best in term of polymorphism and heterozygosity as scores exhibited highest MI. The different accessions of P. vittata collected from different phytogeographical regions falls into six groups. Out of six clusters, one cluster is of pentaploid cytotype, four clusters are of tetraploid cytotype and one for outgroup taxon (M. punctatum). The result thus showed that within tetraploid, heterozygosity with variable genomic structure exists.
Semantic Congruence Drives Long-Term Memory and Similarly Affects Neural Retrieval Dynamics in Young and Older Adults

Learning novel information can be promoted if it is congruent with already stored knowledge. This so-called semantic congruence effect has been broadly studied in healthy young adults with a focus on neural encoding mechanisms. However, the impacts on retrieval, and possible impairments during healthy aging, which is typically associated with changes in declarative long-term memory, remain unclear. To investigate these issues, we used a previously established paradigm in healthy young and older humans with a focus on the neural activity at a final retrieval stage as measured with electroencephalography (EEG). In both age groups, semantic congruence at encoding enhanced subsequent long-term recognition memory of words. Compatible with this observation, semantic congruence led to differences in event-related potentials (ERPs) at retrieval, and this effect was not modulated by age. Specifically, congruence modulated old/new ERPs at a fronto-central (Fz) and left parietal (P3) electrode in a late (400–600 ms) time window, which has previously been associated with recognition memory processes. Importantly, ERPs to old items also correlated with the positive effect of semantic congruence on long-term memory independent of age. Together, our findings suggest that semantic congruence drives subsequent recognition memory across the lifespan through changes in neural retrieval processes.
Coastal Adaptation and Uncertainties: The Need of Ethics for a Shared Coastal Future

Coastal hydro-morphodynamics present significant uncertainties, one order of magnitude larger for sediment transport than for the driving hydrodynamics. Met-ocean factors (waves, currents, and levels essentially) are normally selected from a probability distribution, where only the central trend is considered, and then the analysis of hydro-morphodynamic processes is carried out within a deterministic framework. This analysis is often based on a non-updated topo-bathymetry, with implicit error intervals for many variables, which results in uncertainties that, unless presented from an ethical perspective, tend to hinder proactive decision making and thus result in growing coastal degradation. To address this challenge, the article starts with the uncertainty in water/sediment fluxes and resulting morphodynamic impacts under average and storm conditions, proving the need to include explicit error levels in the analysis and subsequent assessments. The article develops this approach for field and lab data, considering how they are extrapolated to estimate key variables in coastal sustainability and engineering decisions, illustrated in terms of the longshore sand transport. Such a key variable estimation presents large uncertainties and thus requires a stricter ethical approach for extreme events, which serves to illustrate the transmission of uncertainties. The article concludes with a short overview of the implications that these uncertainties may have for coastal risk assessments and proactive decision making, discussing how large error levels without a suitable ethical assessment may result in socio-economic mistrust, which will limit the necessary optimism to address future coastal sustainability.
Molecular Determinants and Pharmacological Analysis for a Class of Competitive Non-transported Bicyclic Inhibitors of the Betaine/GABA Transporter BGT1

The betaine/GABA transporter 1 (BGT1) is a member of the GABA transporter (GAT) family with still elusive function, largely due to a lack of potent and selective tool compounds. Based on modeling, we here present the design, synthesis and pharmacological evaluation of five novel conformationally restricted cyclic GABA analogs related to the previously reported highly potent and selective BGT1 inhibitor (1S,2S,5R)-5-aminobicyclo[3.1. 0]hexane-2-carboxylic acid (bicyclo-GABA). Using [3H]GABA radioligand uptake assays at the four human GATs recombinantly expressed in mammalian cell lines, we identified bicyclo-GABA and its N-methylated analog (2) as the most potent and selective BGT1 inhibitors. Additional pharmacological characterization in a fluorescence-based membrane potential assay showed that bicyclo-GABA and 2 are competitive inhibitors, not substrates, at BGT1, which was validated by a Schild analysis for bicyclo-GABA (pK B value of 6.4). To further elaborate on the selectivity profile both compounds were tested at recombinant α1β2γ2 GABAA receptors. Whereas bicyclo-GABA showed low micromolar agonistic activity, the N-methylated 2 was completely devoid of activity at GABAA receptors. To further reveal the binding mode of bicyclo-GABA and 2 binding hypotheses of the compounds were obtained from in silico-guided mutagenesis studies followed by pharmacological evaluation at selected BGT1 mutants. This identified the non-conserved BGT1 residues Q299 and E52 as the molecular determinants driving BGT1 activity and selectivity. The binding mode of bicyclo-GABA was further validated by the introduction of activity into the corresponding GAT3 mutant L314Q (38 times potency increase cf. wildtype). Altogether, our data reveal the molecular determinants for the activity of bicyclic GABA analogs, that despite their small size act as competitive inhibitors of BGT1. These compounds may serve as valuable tools to selectively and potently target BGT1 in order to decipher its elusive pharmacological role in the brain and periphery such as the liver and kidneys.
Effects of Bicarbonate Stress on Serum Ions and Gill Transporters in Alkali and Freshwater Forms of Amur Ide (Leuciscus waleckii)

The Amur ide (Leuciscus waleckii) is a fish in the Cyprinidae family. Compared with other Amur ide living in freshwater ecosystems, the Amur ide population in Lake Dali Nor of China is famous for its high tolerance to the alkaline conditions of 54 mM (pH 9.6). Yet, surprisingly, the ionoregulatory mechanism responsible for this remarkable alkaline adaptation remains unclear. Therefore, this study sought to investigate how bicarbonate affects the acid-base balancing and ionoregulatory responses of this animal. Here, using a comparative approach, the alkali form of Amur ide and its ancestral freshwater form living in other freshwater basins were each exposed to 50 mM (pH 9.59 ± 0.09), a level close to the alkalinity of Lake Dali Nor, and their physiological (AE1) adjustment of ions and acid-base regulation were investigated. This study highlighted differences in blood pH and serum ions (e.g., Na+, K+, Cl−, and Ca2+), Na+/K+ ATPase (NKA) activity and its mRNA level, and mRNA expression of gill transporters (Na+/H+ exchanger member 2 and/or 3, Na+/HCO3- cotransporter (NBC1), Cl−/HCO3- exchanger, Na+/Cl− cotransporter (NCC), Na+/K+/2Cl− (NKCC1), SLC26A5, and SLC26A6) for alkalinity adaptation between the two forms of Amur ide differing in alkalinity tolerance. Specifically, close relationships among the serum Na+ and mRNA levels of NCC, NKCC1, and NHE, and also NKA and NBC1, in addition to serum Cl− and bicarbonate transporters (e.g., SLC26A5 and SLC26A6), characterized the alkali form of Amur ide. We propose that this ecotype can ensure its transepithelial Cl− and Na+ uptake/base secretions are highly functional, by its basolateral NKA with NBC1 and apical ionic transporters, and especially NCC incorporated with other transporters (e.g., SLC26). This suggests an evolved strong ability to maintain an ion osmotic and acid-base balance for more effectively facilitating its adaptability to the high alkaline environment. This study provides new insights into the physiological responses of the alkaline form of the Amur ide fish for adapting to extreme alkaline conditions. This information could be used as a reference to cultivating alkaline-tolerant fish species in abandoned alkaline waters.
Silicon Anode Design for Lithium-Ion Batteries: Progress and Perspectives

Silicon has long been regarded as a prospective anode material for lithium-ion batteries. However, its huge volumetric changes during cycling are a major obstacle to its commercialization, as these changes result in irreversible cracking and disconnection of the active mass from the current collector, as well as an excessive formation of a highly resistive solid electrolyte interphase. Multiple mechanical stress relief strategies that primarily use silicon nanostructurization have been previously developed. However, despite the significant improvements on the active material cycle life, using nanomaterials still results in complications, such as low conductivity, reduced volumetric energy density, and increased side reactions. This work provides a historical context for the development of silicon anodes and focuses on the surface chemistry and structural integrity of the electrode, thereby highlighting the most effective strategies reported recently for their optimization.
Performance Evaluation of Regression Models for the Prediction of the COVID-19 Reproduction Rate

This paper aims to evaluate the performance of multiple non-linear regression techniques, such as support-vector regression (SVR), k-nearest neighbor (KNN), Random Forest Regressor, Gradient Boosting, and XGBOOST for COVID-19 reproduction rate prediction and to study the impact of feature selection algorithms and hyperparameter tuning on prediction. Sixteen features (for example, Total_cases_per_million and Total_deaths_per_million) related to significant factors, such as testing, death, positivity rate, active cases, stringency index, and population density are considered for the COVID-19 reproduction rate prediction. These 16 features are ranked using Random Forest, Gradient Boosting, and XGBOOST feature selection algorithms. Seven features are selected from the 16 features according to the ranks assigned by most of the above mentioned feature-selection algorithms. Predictions by historical statistical models are based solely on the predicted feature and the assumption that future instances resemble past occurrences. However, techniques, such as Random Forest, XGBOOST, Gradient Boosting, KNN, and SVR considered the influence of other significant features for predicting the result. The performance of reproduction rate prediction is measured by mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), R-Squared, relative absolute error (RAE), and root relative squared error (RRSE) metrics. The performances of algorithms with and without feature selection are similar, but a remarkable difference is seen with hyperparameter tuning. The results suggest that the reproduction rate is highly dependent on many features, and the prediction should not be based solely upon past values. In the case without hyperparameter tuning, the minimum value of RAE is 0.117315935 with feature selection and 0.0968989 without feature selection, respectively. The KNN attains a low MAE value of 0.0008 and performs well without feature selection and with hyperparameter tuning. The results show that predictions performed using all features and hyperparameter tuning is more accurate than predictions performed using selected features.
Hospital Admission to a Window-Side Bed Does Not Prevent Delirium: A Retrospective Cohort Study of Older Medical Inpatients in General Wards

Background: Delirium in older inpatients is a serious problem. The presence of a window in the intensive care unit has been reported to improve delirium. However, no study has investigated whether window-side bed placement is also effective for delirium prevention in a general ward. Objectives: This study aims to clarify the association between admission to a window-side bed and delirium development in older patients in a general ward. Design: This research is designed as a retrospective cohort study of older patients admitted to the internal medicine departments of Shinshu University Hospital, Japan. Participants: The inclusion criteria were the following: (1) admitted to hospital internal medicine departments between April 2009 and December 2018, (2) older than 75 years, (3) admitted to a multi-patient room in a general ward, and (4) unplanned admission. The number of eligible patients was 1,556. Exposure: This study is a comparison of 495 patients assigned to a window-side bed (window group) with 1,061 patients assigned to a non-window-side bed (non-window group). When patients were transferred to the other type bed after admission, observation was censored. Main Measures: The main outcome of interest was “delirium with event” (e.g., the use of medication or physical restraint for delirium) within 14 days after admission as surveyed by medical chart review in a blinded manner. Key Results: The patients had a median age of 80 years and 38.1% were female. The main outcome was recorded in 36 patients in the window group (10.7 per thousand person-days) and 84 in the non-window group (11.7 per thousand person-days). Log-rank testing showed no significant difference between the groups (p = 0.78). Multivariate analysis with Cox regression modeling also revealed no significant association for the window group with main outcome development (adjusted hazard ratio 0.90, 95% confidence interval of 0.61–1.34). Conclusions: Admission to a window-side bed did not prevent delirium development in older patients admitted to a general ward.
Music Augmented With Isochronic Auditory Beats or Vibrotactile Stimulation Does Not Affect Subsequent Ergometer Cycling Performance: A Pilot Study

Methods to enhance the ergogenic effects of music are of interest to athletes of all abilities. The aim of this pilot study was to investigate the ergogenic effects of two commercially available methods of music augmentation: auditory beats and vibrotactile stimulation. Six male and five female cyclists/triathletes cycled for 7 minutes at three different intensities: a rate of perceived exertion (RPE) of 11 (“light”), RPE of 15 (“hard”), and a 7-minute time-trial. Before each 7-minute bout of cycling, participants listened to 10 minutes of self-selected music (MUS), or the same music with the addition of either isochronic auditory beats (ABS) or vibrotactile stimulation via SUBPACTM (VIB). MUS, ABS and VIB trials were performed in a randomized order. Power output was measured during cycling and felt arousal and feeling scores were recorded at timepoints throughout the protocol. The results found the augmented MUS interventions did not influence power output with no significant main effect of trial (p = 0.44, η2 = 0.09) or trial × cycling intensity interaction (p = 0.11, η2 = 0.20). Similarly, both felt arousal and feeling scores were unchanged between the MUS, ABS, and VIB trials (p > 0.05). In conclusion, this pilot study indicated an ineffectiveness of the ABS and VIB to affect subsequent 7-min cycling performance compared to self-selected MUS alone.
Functional Characterization of the Cell Division Gene Cluster of the Wall-less Bacterium Mycoplasma genitalium

It is well-established that FtsZ drives peptidoglycan synthesis at the division site in walled bacteria. However, the function and conservation of FtsZ in wall-less prokaryotes such as mycoplasmas are less clear. In the genome-reduced bacterium Mycoplasma genitalium, the cell division gene cluster is limited to four genes: mraZ, mraW, MG_223, and ftsZ. In a previous study, we demonstrated that ftsZ was dispensable for growth of M. genitalium under laboratory culture conditions. Herein, we show that the entire cell division gene cluster of M. genitalium is non-essential for growth in vitro. Our analyses indicate that loss of the mraZ gene alone is more detrimental for growth of M. genitalium than deletion of ftsZ or the entire cell division gene cluster. Transcriptional analysis revealed a marked upregulation of ftsZ in the mraZ mutant. Stable isotope labeling by amino acids in cell culture (SILAC)-based proteomics confirmed the overexpression of FtsZ in MraZ-deprived cells. Of note, we found that ftsZ expression was upregulated in non-adherent cells of M. genitalium, which arise spontaneously at relatively high rates. Single cell analysis using fluorescent markers showed that FtsZ localization varied throughout the cell cycle of M. genitalium in a coordinated manner with the chromosome and the terminal organelle (TMO). In addition, our results indicate a possible role for the RNA methyltransferase MraW in the regulation of FtsZ expression at the post-transcriptional level. Altogether, this study provides an extensive characterization of the cell division gene cluster of M. genitalium and demonstrates the existence of regulatory elements controlling FtsZ expression at the temporal and spatial level in mycoplasmas.
Construction and Validation of Novel Prediction Tools Based on Large Population-Based Database to Predict the Prognosis of Urachal Cancer After Surgery

Background Urachal cancer is a rare neoplasm in the urological system. To our knowledge, no published study has explored to establish a model for predicting the prognosis of urachal cancer. The present study aims to develop and validate nomograms for predicting the prognosis of urachal cancer based on clinicopathological parameters. Methods Based on the data from the Surveillance, Epidemiology, and End Results database, 445 patients diagnosed with urachal cancer between 1975 and 2018 were identified as training and internal validation cohort; 84 patients diagnosed as urachal cancer from 2001 to 2020 in two medical centers were collected as external validation cohort. Nomograms were developed using a multivariate Cox proportional hazards regression analysis in the training cohort, and their performance was evaluated in terms of its discriminative ability, calibration, and clinical usefulness by statistical analysis. Results Three nomograms based on tumor–node–metastasis (TNM), Sheldon and Mayo staging system were developed for predicting cancer-specific survival (CSS) of urachal cancer; these nomograms all showed similar calibration and discrimination ability. Further internal (c-index 0.78) and external (c-index 0.81) validation suggested that Sheldon model had superior discrimination and calibration ability in predicting CSS than the other two models. Moreover, we found that the Sheldon model was able to successfully classify patients into different risk of mortality both in internal and external validation cohorts. Decision curve analysis proved that the nomogram was clinically useful and applicable. Conclusions The nomogram model with Sheldon staging system was recommended for predicting the prognosis of urachal cancer. The proposed nomograms have promising clinical applicability to help clinicians on individualized patient counseling, decision-making, and clinical trial designing.
Phase transitions of ScOOH under high pressure

ABSTRACT In-situ X-ray diffraction measurements of ScOOH were conducted under high pressure and temperature conditions up to 11 GPa and 900 K to understand its phase transitions. As the pressure increased, α-ScOOH, InOOH-type ScOOH, and YbOOH-type ScOOH were observed. The experimental results indicate that the boundaries between α-ScOOH and InOOH-type ScOOH, and between InOOH-type and YbOOH-type ScOOH are represented by the following linear equations: P(GPa) = (0.0009 ± 0.0015) × [T(K) – 700] + 4.33 ± 0.04 and P(GPa) = (–0.0029 ± 0.0002) × [T(K) – 800] + 8.1 ± 0.3, respectively. By using a least-squares fit of the second-order Birch–Murnaghan equation of state (EoS) to the experimental compression data, the EoS parameters of the three phases of ScOOH at 400 K were obtained. The volume change of the transition from α-ScOOH to InOOH-type ScOOH is ∼3.9% at 4 GPa and 400 K, while the volume change of the transition from InOOH-type to YbOOH-type ScOOH is ∼7.6% at 9 GPa and 400 K.
RecSys 2021 Challenge Workshop: Fairness-aware engagement prediction at scale on Twitter’s Home Timeline

The workshop features presentations of accepted contributions to the RecSys Challenge 2021, organized by Politecnico di Bari, ETH Zürich, Jönköping University, and the data set is provided by Twitter. The challenge focuses on a real-world task of tweet engagement prediction in a dynamic environment. For 2021, the challenge considers four different engagement types: Likes, Retweet, Quote, and replies. This year’s challenge brings the problem even closer to Twitter’s real recommender systems by introducing latency constraints. We also increases the data size to encourage novel methods. Also, the data density is increased in terms of the graph where users are considered to be nodes and interactions as edges. The goal is twofold: to predict the probability of different engagement types of a target user for a set of Tweets based on heterogeneous input data while providing fair recommendations. In fact, multi-goal optimization considering accuracy and fairness is particularly challenging. However, we believed that the recommendation community was nowadays mature enough to face the challenge of providing accurate and, at the same time, fair recommendations. To this end, Twitter has released a public dataset of close to 1 billion data points, > 40 million each day over 28 days. Week 1 − 3 will be used for training and week 4 for evaluation and testing. Each datapoint contains the tweet along with engagement features, user features, and tweet features. A peculiarity of this challenge is related to keeping the dataset updated with the platform: if a user deletes a Tweet, or their data from Twitter, the dataset is promptly updated. Moreover, each change in the dataset implied new evaluations of all submissions and the update of the leaderboard metrics. The challenge was well received with 578 registered users, and 386 submissions.