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Here we present a sample of 12 massive quiescent galaxy candidates at [Formula: see text] observed with the James Webb Space Telescope (JWST) Near Infrared Spectrograph (NIRSpec). These galaxies were pre-selected from the Hubble Space Telescope imaging and 10 of our sources were unable to be spectroscopically confirmed by ground based spectroscopy. By combining spectroscopic data from NIRSpec with multi-wavelength imaging data from the JWST Near Infrared Camera (NIRCam), we analyse their stellar populations and their formation histories. We find that all of our galaxies classify as quiescent based on the reconstruction of their star formation histories but show a variety of quenching timescales and ages. All our galaxies are massive ([Formula: see text] M[Formula: see text]), with masses comparable to massive galaxies in the local Universe. We find that the oldest galaxy in our sample formed [Formula: see text] M[Formula: see text] of mass within the first few hundred million years of the Universe and has been quenched for more than a billion years by the time of observation at [Formula: see text] ([Formula: see text] billion years after the Big Bang). Our results point to very early formation of massive galaxies requiring a high conversion rate of baryons to stars in the early Universe., (© 2024. Crown.)

The biomass higher heating value (HHV) is an important thermal property that determines the amount of recoverable energy from agriculture byproducts. Precise laboratory measurement or accurate prediction of the HHV is essential for designing biomass conversion equipment. The current study combines feature selection scenarios and machine learning tools to establish a general model for estimating biomass HHV. Multiple linear regression and Pearson's correlation coefficients justified that volatile matter, nitrogen, and oxygen content of biomass samples have a slight effect on the HHV and it is better to ignore them during the HHV modeling. Then, the prediction performance of random forest, multilayer and cascade feedforward neural networks, group method of data handling, and least-squares support vector regressor are compared to determine the intelligent estimator with the highest accuracy toward biomass HHV prediction. The ranking test shows that the multilayer perceptron neural network better predicts the HHV of 532 biomass samples than the other intelligent models. This model presents the outstanding absolute average relative error of 2.75% and 3.12% and regression coefficients of 0.9500 and 0.9418 in the learning and testing stages. The model performance is also superior to a recurrent neural network which was recently developed in the literature using the same databank., (© 2023. Springer Nature Limited.)

The early detection of graft failure in pediatric liver transplantation is crucial for appropriate intervention. Graft failure is associated with numerous perioperative risk factors. This study aimed to develop an individualized predictive model for 90-days graft failure in pediatric liver transplantation using machine learning methods. We conducted a single-center retrospective cohort study. A total of 87 liver transplantation cases performed in patients aged < 12 years at the Severance Hospital between January 2010 and September 2020 were included as data samples. Preoperative conditions of recipients and donors, intraoperative care, postoperative serial laboratory parameters, and events observed within seven days of surgery were collected as features. A least absolute shrinkage and selection operator (LASSO) -based method was used for feature selection to overcome the high dimensionality and collinearity of variables. Among 146 features, four variables were selected as the resultant features, namely, preoperative hepatic encephalopathy, sodium level at the end of surgery, hepatic artery thrombosis, and total bilirubin level on postoperative day 7. These features were selected from different times and represent distinct clinical aspects. The model with logistic regression demonstrated the best prediction performance among various machine learning methods tested (area under the receiver operating characteristic curve (AUROC) = 0.898 and area under the precision-recall curve (AUPR) = 0.882). The risk scoring system developed based on the logistic regression model showed an AUROC of 0.910 and an AUPR of 0.830. Together, the prediction of graft failure in pediatric liver transplantation using the proposed machine learning model exhibited superior discrimination power and, therefore, can provide valuable information to clinicians for their decision making during the postoperative management of the patients., (© 2022. The Author(s).)

Tertiary relict flora in East Asia can be divided into northern and southern regions. North China is a diversity hotspot because it can be the secondary contact zone of ancient lineages from the two regions. To test the extent of ancient lineages hybridization and distinguish between the putative species pair Acer pictum subsp. mono and Acer truncatum, we conducted genetic and ecological studies within a maple hybrid zone in North China. Our results suggest that the two lineages of Acer coexist in the hybrid zone and that adult and offspring populations show typical bimodal genetic patterns. Hybrid individuals are established at intermediate altitudes between the two parental lineages. Flowering phenology is divergent between lineages, whereas the complex sexual system of Acer may ensure pollination among lineages. Leaf and fruit morphologies are different between the northern and southern origin lineages, corresponding to A. pictum subsp. mono and A. truncatum, respectively. Reduced gene flow between lineages suggests that they should be considered as two species. However, large morphological variations within each species and the existence of hybrids offer low reliability of species identification based solely on morphological traits. Our study underscores North China as an overlooked diversity hotspot that requires further study in the future., (© 2022. The Author(s).)

This study aimed to identify the correlation among anti-Mullerian Hormone serum levels and 25-OH-D, obesity, metabolic syndrome (MetS), and sexual hormones in climacteric women classified according to stages of reproductive aging (SRA). A cross-sectional study was conducted with a total of 177 Brazilian climacteric women between 40 and 64 years old. Concentrations of AMH were measured using the Access 2 Immunoassay System. A multiple linear regression analysis was used to identify the relationship among AMH, 25-OH-D, obesity, MetS, sexual hormones, sociodemographic and lifestyle factors. AMH levels decreased with increased age (B = - 0.059; p < 0.001), and reproductive aging (B = - 0.483; p < 0.001). Obesity indicators, lifestyle characters, 25-OH-D levels and MetS were not significantly associated with AMH serum concentration. Negative correlation was found for FSH (B = - 0.009; p < 0.001) and LH (B = - 0.006; p = 0.004); positive correlation for E2 (B = 0.001; p = 0.011), DHEAS (B = 0.003; p < 0.001) and SHBG (B = 0.003; p = 0.005). In the model adjusted for SRA, FSH levels (p < 0.001) and DHEAS (p = 0.014) were associated with AMH. Although, with the adjustment for age, only FSH remained with a significant association (p = 0.001). Of the other analytes, none was associated with AMH, regardless of the model fit. Our findings confirm that serum AMH level decreased with age and FSH levels, but there is no correlation between AMH with obesity, 25-OH-D, MetS or other sexual hormones in Brazilian climacteric women., (© 2022. The Author(s).)

Global climate change introduces new combinations of environmental conditions, which is expected to increase stress on plants. This could affect many traits in multiple ways that are as yet unknown but will likely require the modification of existing genetic relationships among functional traits potentially involved in local adaptation. Theoretical evolutionary studies have determined that it is an advantage to have an excess of recombination events under heterogeneous environmental conditions. Our study, conducted on a population of radiata pine (Pinus radiata D. Don), was able to identify individuals that show high genetic recombination at genomic regions, which potentially include pleiotropic or collocating QTLs responsible for the studied traits, reaching a prediction accuracy of 0.80 in random cross-validation and 0.72 when whole family was removed from the training population and predicted. To identify these highly recombined individuals, a training population was constructed from correlation breakers, created through tandem selection of parents in the previous generation and their consequent mating. Although the correlation breakers showed lower observed heterogeneity possibly due to direct selection in both studied traits, the genomic regions with statistically significant differences in the linkage disequilibrium pattern showed higher level of heretozygosity, which has the effect of decomposing unfavourable genetic correlation. We propose undertaking selection of correlation breakers under current environmental conditions and using genomic predictions to increase the frequency of these 'recombined' individuals in future plantations, ensuring the resilience of planted forests to changing climates. The increased frequency of such individuals will decrease the strength of the population-level genetic correlations among traits, increasing the opportunity for new trait combinations to be developed in the future., (© 2022. The Author(s).)

Executive functions (EF) are a core aspect of cognition. Research with adult humans has produced evidence for unity and diversity in the structure of EF. Studies with preschoolers favour a 1-factor model, in which variation in EF tasks is best explained by a single underlying trait on which all EF tasks load. How EF are structured in nonhuman primates remains unknown. This study starts to fill this gap through a comparative, multi-trait multi-method test battery with preschoolers (N = 185) and chimpanzees (N = 55). The battery aimed at measuring working memory updating, inhibition, and attention shifting with three non-verbal tasks per function. For both species the correlations between tasks were low to moderate and not confined to tasks within the same putative function. Factor analyses produced some evidence for the unity of executive functions in both groups, in that our analyses revealed shared variance. However, we could not conclusively distinguish between 1-, 2- or 3-factor models. We discuss the implications of our findings with respect to the ecological validity of current psychometric research., (© 2022. The Author(s).)

This study evaluated the antibacterial effects of short-time exposure of surface pre-reacted glass-ionomer (S-PRG) eluate on oral microcosm biofilm. Biofilms were treated with an S-PRG eluate at different concentrations (25%, 50%, and 100%), distilled water (DW), and 0.1% chlorhexidine (CHX) twice a day for 5 min repeatedly. After 7 days, the total and aciduric bacterial counts and biofilm dry weights were measured. An image analysis program calculated the red/green (R/G) ratios in the biofilm autofluorescence images. Microscopic analyses quantified the biofilm thickness and live/dead cell ratio and determined morphological changes in the biofilm. Bacterial counts and dry weights were not significantly different in the DW group for all S-PRG eluate concentrations. An increasing trend in the R/G ratio for 7 days biofilm treatment was observed for the S-PRG eluate and the DW groups. Furthermore, the live/dead cell ratios in the biofilm and the biofilm thickness of the S-PRG eluate groups were similar to those of the DW group. The bacteria morphology inside the biofilm changed only in the CHX group. Short-time S-PRG eluate treatment showed no significant antibacterial and antibiofilm effects. These results indicated that limited biofilm formation inhibition can be obtained by using only the S-PRG eluate.

Molecular investigations are crucial for further developments in precision medicine. RNA sequencing, alone or in combination with further omic-analyses, resulted in new therapeutic strategies. In this context, biobanks represent infrastructures to store tissue samples and body fluids in combination with clinical data to promote research for new predictive and prognostic biomarkers as well as therapeutic candidate molecules. Until today, the optimal storage conditions are a matter of debate especially with view to the storage temperature. In this unique approach we compared parallel samples from the same tumour, one half stored at - 80 °C and one half in the vapor phase of liquid nitrogen, with almost identical pre-analytical conditions. We demonstrated that RNA isolated from breast cancer samples revealed significantly higher RIN e -values after 10 years of storage in the vapor phase of liquid nitrogen compared to storage at - 80 °C. In contrast, no significant difference was found regarding the DIN-values after DNA isolation. Morphological changes of the nucleus and cytoplasm, especially in the samples stored at - 80 °C, gave insights to degenerative effects, most possibly due to the storage protocol and its respective peculiarities. In addition, our results indicate that exact point-to point documentation beginning at the sample preparation is mandatory.

Ultrasound-induced blood-brain barrier (BBB) opening using microbubbles is a promising technique for local delivery of therapeutic molecules into the brain. The real-time control of the ultrasound dose delivered through the skull is necessary as the range of pressure for efficient and safe BBB opening is very narrow. Passive cavitation detection (PCD) is a method proposed to monitor the microbubble activity during ultrasound exposure. However, there is still no consensus on a reliable safety indicator able to predict potential damage in the brain. Current approaches for the control of the beam intensity based on PCD employ a full-pulse analysis and may suffer from a lack of sensitivity and poor reaction time. To overcome these limitations, we propose an intra-pulse analysis to monitor the evolution of the frequency content during ultrasound bursts. We hypothesized that the destabilization of microbubbles exposed to a critical level of ultrasound would result in the instantaneous generation of subharmonic and ultra-harmonic components. This specific signature was exploited to define a new sensitive indicator of the safety of the ultrasound protocol. The approach was validated in vivo in rats and non-human primates using a retrospective analysis. Our results demonstrate that intra-pulse monitoring was able to exhibit a sudden appearance of ultra-harmonics during the ultrasound excitation pulse. The repeated detection of such a signature within the excitation pulse was highly correlated with the occurrence of side effects such as hemorrhage and edema. Keeping the acoustic pressure at levels where no such sign of microbubble destabilization occurred resulted in safe BBB openings, as shown by MR images and gross pathology. This new indicator should be more sensitive than conventional full-pulse analysis and can be used to distinguish between potentially harmful and safe ultrasound conditions in the brain with very short reaction time.

The influence of an auroral substorm on the total electron content (TEC) jumps and cycle slips on Global Positioning System (GPS) at high-latitudes is studied. For the first time, optical data from the all-sky imager, as well as interplanetary magnetic field and magnetometer data are used to complete the analysis of the slips occurrence and to monitor the substorm evolution. Two types of slips are considered: (i) instrumental slips including losses in the measured phase of the GPS signal and (ii) sharp TEC variations (TEC jumps) It is demonstrated that the jumps in TEC determined from the GPS signals are mainly related to the auroral particle precipitation that normally occurs during geomagnetic substorms in the polar ionosphere. The GPS frequency [Formula: see text] is consistently subject to more slips than frequency [Formula: see text] both for quiet and disturbed conditions. The probability of TEC jumps is higher than for cycle slips in phase at frequencies [Formula: see text] and [Formula: see text]. The maximum of TEC jumps is observed during the recovery phase of the auroral substorm. Our findings are based on a data set obtained for a particular event. A generalization of the obtained numerical estimates to other events requires additional research and further analysis.

How empathically people respond to a stranger's pain or pleasure does not only depend on the situational context, individual traits and intentions, but also on interindividual factors. Here we ask whether empathic responses towards unknown others are modulated by behavioural similarity as a potential marker of genetic relatedness. Participants watched two supposed human players who were modelled as having a strong (player LP) or weak (player NLP) tendency to lead in social situations executing penalty shots in a virtual reality robot soccer game. As predicted, empathic response were modulated by shared behavioural traits: participants whose tendency to lead was more similar to player LP's tendency to lead experienced more reward, and showed stronger neural activity in reward-related brain regions, when they saw player LP score a goal, and participants whose tendency to lead was more similar to player NLP's tendency to lead showed stronger empathic responses when they saw player NLP score a goal. These findings highlight the potentially evolutionary grounded role of phenotypic similarity for neural processes underlying human social perception.

Six components of partial resistance (RCs) were studied in 15 grapevine varieties with partial resistance to Plasmopara viticola: (i) infection frequency (IFR, proportion of inoculation sites showing sporulation), (ii) latent period (LP50, degree-days between inoculation and appearance of 50% of the final number of sporulating lesions), (iii) lesion size (LS, area of single lesions in mm 2 ), (iv) production of sporangia (SPOR, number of sporangia produced per lesion, and SPOR', number of sporangia produced per mm 2 of lesion), (v) infectious period (IP, number of sporulation events on a lesion), and (vi) infectivity of sporangia (INF, infection efficiency of sporangia produced on resistant varieties). Artificial inoculation monocycle experiments were conducted for a 3-year period on leaves collected at leaf development, flowering, and fruit development. Compared to the susceptible variety 'Merlot', the partially resistant varieties showed reduced IFR, longer LP, smaller LS, fewer SPOR and SPOR', shorter IP, and lower INF. At leaf development, IFR, SPOR, and INF were higher and LP was shorter than at flowering and fruit development. RCs analysis through monocyclic experiments provides reliable assessments of the resistance response of grapevine accessions. The workload required for routine assessment in breeding programs could be reduced by measuring IFR and SPOR, while producing robust results.