Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacteriophage resistance increases bacterial productivity by shifting population growth dynamics in the soil bacterium Variovorax sp

Bacteriophages can be important drivers of bacterial densities, and therefore microbial community composition and function. In response to phage infection, bacteria can evolve resistance while phage can reciprocally evolve to increase infectivity. Coevolutionary arms-races between bacteria and phage have been studied in many model systems and in pairs isolated from natural samples. However, how multiple bacteria-phage pairs coevolve simultaneously within a community is poorly understood. Here, we examine how three pairs of coexisting soil bacteria (Ochrobactrum sp., Pseudomonas sp., and Variovorax sp.) evolve with three species-specific bacteriophages over eight weeks of experimental evolution, both as host-parasite pairs in isolation and as a mixed community. Coevolution was very limited, with two phages going extinct after two weeks and Ochrobactrum phage increasing in infectivity without comparable reciprocal increases in bacterial resistance. One surprising finding was that Variovorax sp. increased in density following phage extinction, above that of no-phage controls. We examined the mechanisms behind this density increase through common garden experiments, growth curves, supernatant assays, and sequencing. Our results showed that this density increase resulted from genetic changes and was associated with phage resistance. Growth curves demonstrated that phage resistance shifted population growth curves such that density was higher in the death-phase. That resistance to lytic phage can improve host densities has implications for wider ecology and phage therapy where lytic phages are presumed to have negative effects on their hosts.
Top-down task goals induce the retrieval state

Engaging the retrieval state (Tulving, 1983) impacts processing and behavior (Long & Kuhl, 2019, 2021; Smith, Moore, & Long, 2022), but the extent to which top-down factors – explicit instructions and goals – vs. bottom-up factors – stimulus properties such as repetition and similarity – jointly or independently induce the retrieval state is unclear. Identifying the impact of bottom-up and top-down factors on retrieval state engagement is critical for understanding how control of task-relevant vs. task-irrelevant brain states influence cognition. We conducted between-subjects recognition memory tasks on male and female human participants in which we varied test phase goals. We recorded scalp electroencephalography and used an independently validated mnemonic state classifier (Long, 2023) to measure retrieval state engagement as a function of top-down task goals (recognize old vs. detect new items) and bottom-up stimulus repetition (hits vs. correct rejections). We find that whereas the retrieval state is engaged for hits regardless of top-down goals, the retrieval state is only engaged during correct rejections when the top-down goal is to recognize old items. Furthermore, retrieval state engagement is greater for low compared to high confidence hits when the task goal is to recognize old items. Together, these results suggest that top-down demands to recognize old items induce the retrieval state independent from bottom-up factors, potentially reflecting the recruitment of internal attention to enable access of a stored representation. Significance Statement Both top-down goals and automatic bottom-up influences may lead us into a retrieval brain state – a whole-brain pattern of activity that supports our ability to remember the past. Here we tested the extent to which top-down vs. bottom-up factors independently influence the retrieval state by manipulating participants’ goals and stimulus repetition during a memory test. We find that in response to the top-down goal to recognize old items, the retrieval state is engaged for both old and new probes, suggesting that top-down and bottom-up factors independently engage the retrieval state. Our interpretation is that top-down demands recruit internal attention in service of the attempt to access a stored representation.
Mapping the mutational landscape of a full viral proteome reveals distinct profiles of mutation tolerability

RNA viruses have notoriously high mutation rates due to error-prone replication by their RNA polymerase. However, natural selection concentrates variability in a few key viral proteins. To test whether this stems from different mutation tolerance profiles among viral proteins, we measured the effect of >40,000 non-synonymous mutations across the full proteome of coxsackievirus B3 as well as >97% of all codon deletions in the non-structural proteins. We find significant variation in mutational tolerance within and between individual viral proteins, which correlated with both general and protein-specific structural and functional attributes. Further, mutational fitness effects remained largely constant across cell lines, highlighting conserved selection pressures. In addition to providing a rich dataset for understanding virus biology and evolution, our results illustrate that incorporation of mutational tolerance data into druggable pocket discovery can aid in selecting targets with high barriers to drug resistance.
HUBUNGAN ANTARA KEPERCAYAAN TERHADAP PEMIMPIN DENGAN KETERIKATAN KERJA PADA KARYAWAN PT TELKOM WITEL SEMARANG

Work engagement is the ability of employees who are positive characterized by the physical and mental energy in the work and the involvement of a strong and full of concentration in work. Trust in leaders is the belief that the employee has toward the leader based on the belief that the leader is competent, integrity, consistence, loyal and open-minded. This study aims to determine the relationship between the beliefs of the leader with the engagement of work to the employees of PT Telkom Witel Semarang. The research populations that fulfill the characteristics of 171 employees, the research sample is 114 employees with the characteristics of working period of at least one year by using cluster random sampling technique. Data collection used a scale of work engagement (25 aitem α = 0.87) and a trust-to-leader scale (39 aitems α = 0.93). Simple regression analysis showed a positive and significant correlation between trust toward leader with working engagement (rxy = 0, 55 with <0,001), which means higher trust to leader, hence higher employee engagement. As well if the trust toward the leader is low then the engagement of work owned by employees will be low. Leadership trust contributes 30% to work engagement.
Technical and biological variations in the purification of extrachromosomal circular DNA (eccDNA) and the finding of more eccDNA in the plasma of lung adenocarcinoma patients compared with healthy donors

Human plasma DNA originates from all tissues and organs, holding the potential as a versatile marker for diseases such as cancer, as fragments of cancer-specific alleles can be found circulating in the blood. While linear DNA has been studied intensely as a liquid biomarker, the role of circular circulating DNA in cancer is more unknown due, in part, to a lack of comprehensive testing methods. Our developed method profiles extrachromosomal circular DNA (eccDNA) in plasma, integrating Solid-Phase Reversible Immobilization (SPRI) bead purification, the removal of linear DNA and mitochondrial DNA, and DNA sequencing. As an initial assessment, we examined the method, biological variations, and technical variations using plasma samples from four patients with lung adenocarcinoma and four healthy and physically fit individuals. Despite the small sample group, we observed a significant eccDNA increase in cancer patients in two independent laboratories and that eccDNA covered up to 0.4 % of the genome/mL plasma. We found a subset of eccDNA from recurrent genes present in cancer samples but not in every control. In conclusion, our data reflect the large variation found in eccDNA sequence content and show that the variability observed among replicates in eccDNA stems from a biological source and can cause inconclusive findings for biomarkers. This suggests the need to explore other biological markers, such as epigenetic features on eccDNA.
Unbiased estimation of the coefficient of determination in linear models: an application to fMRI encoding model comparison

Neuroscientific investigation has greatly benefited from the combination of functional Magnetic Resonance Imaging (fMRI) with linearized encoding, which allows to validate and compare computational models of neural activity based on neuroimaging data. In linearized encoding, a multidimensional feature space, usually obtained from a computational model applied to the stimuli, is related to the measured brain activity. This is often done by mapping such space to a dataset (training data, or in-sample), and validating the mapping on a separate dataset (test data, or out-of-sample), to avoid overfitting. When comparing models, the one with the highest explained variance on the test data, as indicated by the coefficient of determination (R2), is the one that better reflects the neural computations performed by the brain. An implicit assumption underlying this procedure is that the out-of-sample R2 is an unbiased estimator of the explanatory power of a computational model in the population of stimuli, and can therefore be safely used to compare models. In this work, we show that this is not the case, as the out-of-sample R2 has a negative bias, related to the amount of overfitting in the training data. This phenomenon has dramatic implications for model comparison when models of different dimensionalities are compared. To this aim, we develop an analytical framework that allows us to evaluate and correct biases in both in- and out-of-sample R2, with and without L2 regularization. Our proposed approach yields unbiased estimators of the population R2, thus enabling a valid model comparison. We validate it through illustrative simulations and with an application to a large public fMRI dataset.
Repeated Binge Alcohol Drinking Leads to Reductions in Corticostriatal Theta Coherence in Female but not Male Mice

Decreased functional connectivity between the striatum and frontal cortex is observed in individuals with alcohol use disorder (AUD), and predicts the probability of relapse in abstinent individuals with AUD. To further our understanding of how repeated alcohol (ethanol; EtOH) consumption impacts the corticostriatal circuit, extracellular electrophysiological recordings (local field potentials; LFPs) were gathered from the nucleus accumbens (NAc) and prefrontal cortex (PFC) of C57BL/6J mice voluntarily consuming EtOH or water using a ‘drinking-in-the-dark’ (DID) procedure. Following a three-day acclimation period wherein only water access was provided during DID, mice were given 15 consecutive days of access to EtOH. Each session consisted of a 30-minute baseline period where water was available and was followed immediately by a 2-hour period where sippers containing water were replaced with new sippers containing either unsweetened 20% (v/v) EtOH (days 4-18; DID) or water (days 1-3; acclimation). Our analyses focused primarily on theta coherence during bouts of drinking, as differences in this band are associated with several behavioral markers of AUD. Both sexes displayed decreases in theta coherence during the first day of binge EtOH consumption. However, only females displayed further decreases in theta coherence on the 14th day of EtOH access. No differences in theta coherence were observed between the first and final bout on any EtOH drinking days. These results provide additional support for decreases in the functional coupling of corticostriatal circuits as a consequence of alcohol consumption and suggests that female mice are uniquely vulnerable to these effects following repeated EtOH drinking.
Multiresolution analysis of characteristic length scales with high‐resolution topographic data

Characteristic length scales (CLS) define landscape structure and delimit geomorphic processes. Here we use multiresolution analysis (MRA) to estimate such scales from high‐resolution topographic data. MRA employs progressive terrain defocusing, via convolution of the terrain data with Gaussian kernels of increasing standard deviation, and calculation at each smoothing resolution of (i) the probability distributions of curvature and topographic index (defined as the ratio of slope to area in log scale) and (ii) characteristic spatial patterns of divergent and convergent topography identified by analyzing the curvature of the terrain. The MRA is first explored using synthetic 1‐D and 2‐D signals whose CLS are known. It is then validated against a set of MARSSIM (a landscape evolution model) steady state landscapes whose CLS were tuned by varying hillslope diffusivity and simulated noise amplitude. The known CLS match the scales at which the distributions of topographic index and curvature show scaling breaks, indicating that the MRA can identify CLS in landscapes based on the scaling behavior of topographic attributes. Finally, the MRA is deployed to measure the CLS of five natural landscapes using meter resolution digital terrain model data. CLS are inferred from the scaling breaks of the topographic index and curvature distributions and equated with (i) small‐scale roughness features and (ii) the hillslope length scale.
Developmental trajectories of EEG aperiodic and periodic power: Implications for understanding the timing of thalamocortical development during infancy

The development of neural circuits has long-lasting effects on brain function, yet our understanding of early circuit development in humans remains limited. Here, periodic EEG power features and aperiodic components were examined from longitudinal EEGs collected from 592 healthy 2–44 month-old infants, revealing age-dependent nonlinear changes suggestive of distinct milestones in early brain maturation. Consistent with the transient developmental progression of thalamocortical circuitry, we observe the presence and then absence of periodic alpha and high beta peaks across the three-year period, as well as the emergence of a low beta peak (12-20Hz) after six months of age. We present preliminary evidence that the emergence of the low beta peak is associated with higher thalamocortical-dependent, anesthesia-induced alpha coherence. Together, these findings suggest that early age-dependent changes in alpha and beta periodic peaks may reflect the state of thalamocortical network development.
Antisense transcription can induce expression memory via stable promoter repression

The capacity of cells to retain a memory of previous signals enables them to adopt unique cell fates and adjust to their surrounding environment. The underlying gene expression memory can arise from mutual repression of two genes, forming a toggle switch. Such mutual repression may occur at antisense loci, where two convergently oriented genes repress each other in cis. Under which conditions antisense transcription can generate expression memory remains poorly understood. To address this question, we combine mathematical modeling, genomics and a synthetic biology approach. Through simulations we show that stable memory can emerge, if both genes in an antisense pair transcribe through the convergent promoter and induce a stable repressive chromatin state. Genome-wide analysis of nascent transcription further supports antisense-mediated promoter repression with promoter-overlapping antisense gene pairs exhibiting mutually exclusive expression. Through constructing a synthetic antisense locus in mouse embryonic stem cells (mESCs) we then show that such a locus architecture can indeed maintain a memory of a transient stimulus. Mutual repression and the capacity for memory formation are elevated, when mESCs differentiate, showing that epigenetic memory is a cell type-specific property. Our finding that stem cells adapt their ability to remember stimuli as they differentiate might help to elucidate how stemness is maintained.
Unsteady fluid flow around certain bluff bodies.

It is shown in this thesis that fluid dynamic forces on unsteadily moving bluff bodies depend on the history of motion as much as on the velocity and acceleration of motion. An empirical relationship between the motion of the body and the resulting force is obtained by analysing the effect of the history of motion on the fluid dynamic force at any instant. The fluid dynamic force, velocity and acceleration are obtained as functions of time, by oscillating test models in water while they are being towed at constant speed. The test models used are: 1. a two-dimensional circular cylinder, 2. a rectangular block with square frontal area and fineness ratio of 3:1, 3. a cruciform parachute canopy with arm ratio of 4:1, and 4. a ring-slot parachute canopy. The functions by which the history of flow affects the future forces, are evaluated by using the Convolution Integral. The results show that the effects due to history of both velocity and acceleration are by no means negligible, that is the velocity and the acceleration at a specific time prior to any instant is so domineering that the fluid dynamic force can approximately be expressed as being delayed by this period of time. This 'time-delay', or time lag (as opposed to phase-lag) in the part of the measured force is found to be independent of the frequency of excitation. In the light of this evidence, a prediction model is suggested for estimating unsteady fluid forces. The data required for the application of this prediction model are obtained experimentally. Chapter One of this thesis gives a brief explanation of the historical background of unsteady fluid dynamics. The effects of acceleration on the fluid dynamic force, in both ideal and real fluids, are discussed in Chapter Two. Explained in Chapter Three are the techniques used for building the force prediction model, and data acquisition. The experimental procedure is explained in Chapter Four. Chapter Five gives the empirical form of the prediction model, and some data that are used in association with this model. Dedicated to my Parents
Assessing the potential of gene tree parsimony for microbial phylogenomics

A key challenge in microbial phylogenomics is that microbial gene families are often affected by extensive horizontal gene transfer (HGT). As a result, most existing methods for microbial phylogenomics can only make use of a small subset of the gene families present in the microbial genomes under consideration, potentially biasing their results and affecting their accuracy. One well-known approach for truly genome-scale phylogenomics is gene tree parsimony (GTP), which takes as input a collection of gene trees and finds a species tree that most parsimo-niously reconciles with the input gene trees. While GTP based methods are widely used for phylogenomic studies of non-microbial species, their underlying reconciliation models are not designed to handle HGT and, therefore, they cannot be meaningfully applied to microbes. No GTP based methods have yet been developed for microbial phylogenomics. In this work, we (i) design and implement the first GTP based approach, PhyloGTP , for microbial phylogenomics, (ii) use an extensive simulation study to systematically assess the accuracies of PhyloGTP and two other recently developed methods, SpeciesRax and ASTRAL-Pro-2, under a range of different conditions, and (iii) analyze two real microbial datasets with different characteristics. We find that PhyloGTP and SpeciesRax are more accurate than ASTRAL-Pro-2 across nearly all tested conditions, that PhyloGTP and SpeciesRax have similar accuracies overall, but there are conditions under which PhyloGTP consistently outperforms SpeciesRax, and that both PhyloGTP and SpeciesRax can some-times yield incorrect, misleading phylogenies on complex real datasets.
Disparities in disruptions to public drinking water services in Texas communities during Winter Storm Uri 2021

Winter Storm Uri of February 2021 left millions of United States residents without access to reliable, clean domestic water during the COVID19 pandemic. In the state of Texas, over 17 million people served by public drinking water systems were placed under boil water adviso-ries for periods ranging from one day to more than one month. We performed a geospatial analysis that combined public boil water advisory data for Texas with demographic information from the 2010 United States Census to understand the affected public water systems and the populations they served. We also issued a cross-sectional survey to account for people’s lived experiences. Geospatial analysis shows that the duration of boil water adviso-ries depended partly on the size of the public water system. Large, urban public water systems issued advisories of intermediate length (5–7 days) and served racially diverse communities of moderate income. Small, mostly rural public water systems issued some of the longest advisories (20 days or more). Many of these systems served disproportionately White communities of lower income, but some served predominantly non-White, Hispanic, and Latino communities. In survey data, “first-generation” participants (whose parents were not college-educated) were more likely to be placed under boil water advisories, pointing to disparate impacts by socioeconomic group. The survey also revealed large communication gaps between public water utilities and individuals: more than half of all respondents were unsure or confused about whether they were issued a boil water advisory. Our study rein-forces the need to improve resilience in public water services for large, diverse, urban communities and small, rural
Lunar ionosphere in the wake region : evidence for an enhanced plasma density using measurements from DFRS onboard Chandrayaan-2

The DFRS (Dual Frequency Radio Science) payload onboard the Chandrayaan-2 orbiter is conducting radio occultation (RO) experiments using coherent X-band and S-band radio signals in one-way dual-frequency RO mode. We present ‘first of its kind measurements of the enhanced integrated electron density (along the path) profiles (iEDPs) in the lunar wake and trans-terminator regions. Detailed analysis of the results shows that the integrated electron content of the lunar ionosphere can be as large as 1.5 TECU, (1 TECU = 10 ∼ 16 m -2 ) in the lunar wake region. Large electron content is also seen near lunar polar regions during solar transition periods. These observations are unique in nature as they show post-sunset enhancements in the iEDPs compared to dayside, as reported by earlier missions. These findings further support the theory for the formation and sustenance of the lunar ionosphere as suggested by 3D lunar ionospheric modeling effort by [1].
SPECTROSCOPIC STUDIES OF EXTREMELY METAL-POOR STARS WITH THE SUBARU HIGH DISPERSION SPECTROGRAPH. V. THE Zn-ENHANCED METAL-POOR STAR BS 16920–017

We report Zn abundances for 18 very metal-poor stars studied in our previous work, covering the metallicity range −3.2< [Fe/H] <−2.5. The [Zn/Fe] values of most stars show an increasing trend with decreasing [Fe/H] in this metallicity range, confirming the results found by previous studies. However, the extremely metal-poor star BS 16920–017([Fe/H] =−3.2) exhibits a significantly high [Zn/Fe] ratio ([Zn/Fe] = +1.0). Comparison of the chemical abundances of this object with HD 4306, which has similar atmospheric parameters to BS 16920–017, clearly demonstrates a deficiency of α elements and neutron-capture elements in this star, along with enhancements of Mn and Ni, as well as Zn. The association with a hypernova explosion that has been proposed to explain the high Zn abundance ratios found in extremely metal-poor stars is a possible explanation, although further studies are required to fully interpret the abundance pattern of this object.