Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural deletions in the SARS-CoV-2 spike glycoprotein drive antibody escape

Zoonotic pandemics follow the spillover of animal viruses into highly susceptible human populations. Often, pandemics wane, becoming endemic pathogens. Sustained circulation requires evasion of protective immunity elicited by previous infections. The emergence of SARS-CoV-2 has initiated a global pandemic. Since coronaviruses have a lower substitution rate than other RNA viruses this gave hope that spike glycoprotein is an antigenically stable vaccine target. However, we describe an evolutionary pattern of recurrent deletions at four antigenic sites in the spike glycoprotein. Deletions abolish binding of a reported neutralizing antibody. Circulating SARS-CoV-2 variants are continually exploring genetic and antigenic space via deletion in individual patients and at global scales. In viruses where substitutions are relatively infrequent, deletions represent a mechanism to drive rapid evolution, potentially promoting antigenic drift.
Mapping the contents of consciousness during musical imagery

Humans can internally represent auditory information without an external stimulus. When imagining music, how similar are unfolding neural representations to those during the original perceived experience? Participants memorized six one-minute-long musical pieces with high accuracy. Functional MRI data were collected during: 1) silent imagery of melodies to the beat of a visual metronome; 2) same but while tapping to the beat; and 3) passive listening. During imagery, inter-subject comparison showed that melody-specific temporal response patterns were reinstated in right associative auditory cortices. When tapping accompanied imagery, the melody-specific neural patterns were extended to associative cortices bilaterally. These results indicate that the specific contents of conscious experience are encoded similarly during imagery and perception in the dynamic activity of auditory cortices. Furthermore, rhythmic motion can enhance the reinstatement of neural patterns associated with the experience of complex sounds, in keeping with models of motor to sensory influences in auditory processing.
Palmitoylation Couples DLK to JNK3 to Facilitate Pro-degenerative Axon-to-Soma Signaling

Dual Leucine-zipper Kinase (DLK, a MAP3K) mediates neuronal responses to diverse injuries and insults via c-Jun N-terminal Kinase (JNK) family Mitogen-activated Protein Kinases (MAPKs). It is unclear why DLK couples to JNKs in mammalian neurons versus other MAPKs, especially because some invertebrate DLK orthologs couple instead to the related p38 family MAPKs. Here we identify two mechanisms that potentially explain this DLK-JNK coupling. First, neural-specific JNK3, but not p38-MAPK, catalyzes positive feedback phosphorylation of DLK that further activates DLK and locks the DLK-JNK3 module in a highly active state. Furthermore, the pro-degenerative JNK2 and JNK3, but not the related JNK1, are endogenously palmitoylated. Moreover, palmitoylation targets both DLK and JNK3 to the same axonal vesicles and JNK3 palmitoylation is essential for pro-degenerative axonal retrograde signaling in vivo. These findings provide insights into DLK-JNK signaling relevant to multiple neuropathological conditions and answer long-standing questions regarding the selective pro-degenerative roles of JNK2/3.
Bioinformatic analysis linking genomic defects to chemosensitivity and mechanism of action

A joint analysis of NCI60 small molecule screening data, their genetically defective genes and mechanisms of action (MOA) of FDA approved cancer drugs screened in the NCI60 is proposed for identifying links between chemosensitivity, genomic defects and MOA. Self-organizing-maps (SOMs) are used to organize the chemosensitivity data. Student’s t-tests are used to identify SOM clusters with chemosensitivity for tumor cells harboring genetically defective genes. Fisher’s exact tests are used to reveal instances where defective gene to chemosensitivity associations have enriched MOAs. The results of this analysis find a relatively small set of defective genes, inclusive of ABL1, AXL, BRAF, CDC25A, CDKN2A, IGF1R, KRAS, MECOM, MMP1, MYC, NOTCH1, NRAS, PIK3CG, PTK2, RPTOR, SPTBN1, STAT2, TNKS and ZHX2, as possible candidates for roles in chemosensitivity for compound MOAs that target primarily, but not exclusively, kinases, nucleic acid synthesis, protein synthesis, apoptosis and tubulin. This analysis may contribute towards the goals of cancer drug discovery, development decision making, and explanation of mechanisms.
Estimating time-varying selection coefficients from time series data of allele frequencies

Time series data of allele frequencies are a powerful resource for detecting and classifying natural and artificial selection. Ancient DNA now allows us to observe these trajectories in natural populations of long-lived species such as humans. Here, we develop a hidden Markov model to infer selection coefficients that vary over time. We show through simulations that our approach can accurately estimate both selection coefficients and the timing of changes in selection. Finally, we analyze some of the strongest signals of selection in the human genome using ancient DNA. We show that the European lactase persistence mutation was selected over the past 5,000 years with a selection coefficient of 2-2.5% in Britain, Central Europe and Iberia, but not Italy. In northern East Asia, selection at the ADH1B locus associated with alcohol metabolism intensified around 4,000 years ago, approximately coinciding with the introduction of rice-based agriculture. Finally, a derived allele at the FADS locus was selected in parallel in both Europe and East Asia, as previously hypothesized. Our approach is broadly applicable to both natural and experimental evolution data and shows how time series data can be used to resolve fine-scale details of selection.
COAL_PHYRE: A Composite Likelihood Method for Estimating Species Tree Parameters from Genomic Data Using Coalescent Theory

Genome-scale data are increasingly being used to infer phylogenetic trees. A major challenge in such inferences is that different regions of the genome may have local topologies that differ from the species tree due to incomplete lineage sorting (ILS). Another source of gene tree discrepancies is estimation errors arising from the randomness of the mutational process during sequence evolution. There are two major groups of methods for estimating species tree from whole-genome data: a set of full likelihood methods, which model both sources of variance, but do not scale to large numbers of independent loci, and a class of faster approximation methods which do not model the mutational variance. To bridge the gap between these two classes of methods, we present COAL_PHYRE (COmposite Approximate Likelihood for PHYlogenetic REconstruction), a composite likelihood based method for inferring population size and divergence time estimates of rooted species trees from aligned gene sequences. COAL_PHYRE jointly models coalescent variation across loci using the MSC and variation in local gene tree reconstruction using a normal approximation. To evaluate the accuracy and speed of the method, we compare against BPP, a powerful MCMC full-likelihood method, as well as ASTRAL-III, a fast approximate method. We show that COAL_PHYRE’s divergence time and population size estimates are more accurate than ASTRAL, and comparable to those obtained using BPP, with an order of magnitude decrease in computational time. We also present results on previously published data from a set of Gibbon species to evaluate the accuracy in topology and parameter inference on real data, and to illustrate the method’s ability to analyze data sets which are prohibitively large for MCMC methods.
Multiple latent clusterisation model for the inference of RNA life-cycle kinetic rates from sequencing data

We propose a hierarchical Bayesian approach to infer the RNA synthesis, processing, and degradation rates from sequencing data. We parametrise kinetic rates with novel functional forms and estimate the parameters through a Dirichlet process defined at a low level of hierarchy. Despite the complexity of this approach, we manage to perform inference, clusterisation and model selection simultaneously. We apply our method to investigate transcriptional and post-transcriptional responses of murine fibroblasts to the activation of proto-oncogene MYC. We uncover a widespread choral regulation of the three rates, which was not previously observed in this biological system.
Structural basis of ligand selectivity by a bacterial adhesin lectin involved in multi- species biofilm formation

Carbohydrate recognition by lectins governs critical host-microbe interactions. MpPA14 lectin is a domain of a 1.5-MDa adhesin responsible for a symbiotic bacterium-diatom interaction in Antarctica. Here we show MpPA14 binds various monosaccharides, with L-fucose and N-acetyl glucosamine being the strongest ligands (Kd ~ 150 μM). High-resolution structures of MpPA14 with 15 different sugars bound elucidated the molecular basis for the lectin’s apparent binding promiscuity but underlying selectivity. MpPA14 mediates strong Ca2+-dependent interactions with the 3, 4 diols of L-fucopyranose and glucopyranoses, and binds other sugars via their specific minor isomers. Thus, MpPA14 only binds polysaccharides like branched glucans and fucoidans with these free end-groups. Consistent with our findings, adhesion of MpPA14 to diatom cells was selectively blocked by L-fucose, but not by N-acetyl galactosamine. With MpPA14 lectin homologs present in adhesins of several pathogens, our work gives insight into an anti-adhesion strategy to block infection via ligand-based antagonists.
Correlated structure of neuronal firing in macaque visual cortex limits information for binocular depth discrimination

Variability in cortical neural activity potentially limits sensory discriminations. Theoretical work shows that information required to discriminate two similar stimuli is limited by the correlation structure of cortical variability. We investigated these information-limiting correlations by recording simultaneously from visual cortical areas V1 and V4 in macaque monkeys, performing a binocular, stereo-depth discrimination task. Within both areas, noise correlations on a rapid temporal scale (20-30ms) were stronger for neuron-pairs with similar selectivity for binocular depth, meaning that these correlations potentially limit information for making the discrimination. Between-area correlations (V1 to V4) were different, being weaker for neuron pairs with similar tuning, and having a slower temporal scale (100+ms). Fluctuations in these information-limiting correlations just prior to the detection event were associated with changes in behavioural accuracy. Although these correlations limit the recovery of information about sensory targets, their impact may be curtailed by integrative processing of signals across multiple brain areas.
Epha1 is a cell surface marker for neuromesodermal progenitors and their early mesoderm derivatives

The vertebrate body is built during embryonic development by the sequential addition of new tissue as the embryo grows at its caudal end. During this process, the neuro-mesodermal progenitors (NMPs) generate the postcranial neural tube and paraxial mesoderm. Recently, several approaches have been designed to determine their molecular fingerprint but a simple method to isolate NMPs from embryos without the need for transgenic markers is still missing. We isolated NMPs using a genetic strategy that exploits their self-renew properties, and searched their transcriptome for cell surface markers. We found a distinct Epha1 expression profile in progenitor-containing areas of the mouse embryo, consisting of two cell subpopulations with different Epha1 expression levels. We show that Sox2+/T+ cells are preferentially associated with the Epha1 compartment, indicating that NMPs might be contained within this cell pool. Transcriptional profiling showed enrichment of high Epha1-expressing cells in known NMP and early mesoderm markers. Also, tail bud cells with lower Epha1 levels contained a molecular signature suggesting the presence of notochord progenitors. Our results thus indicate that Epha1 could represent a valuable cell surface marker for different subsets of axial progenitors, most particularly for NMPs taking mesodermal fates.
IL-23 skin and joint profiling in psoriatic arthritis: novel perspectives in understanding clinical responses to IL-23 inhibitors

Objectives To determine the relationship between synovial versus skin transcriptional/histological profiles in patients with active psoriatic arthritis (PsA) and explore mechanistic links between diseased tissue pathology and clinical outcomes. Methods Twenty-seven active PsA patients were enrolled in an observational/open-label study and underwent biopsies of synovium and paired lesional/non-lesional skin before starting anti-tumour necrosis factor (TNF) (if biologic-naïve) or ustekinumab (if anti-TNF inadequate responders). Molecular analysis of 80-inflammation-related genes and protein levels for interleukin (IL)-23p40/IL-23p19/IL-23R were assessed by real-time-PCR and immunohistochemistry, respectively. Results At baseline, all patients had persistent active disease as per inclusion criteria. At primary end-point (16-weeks post-treatment), skin responses favoured ustekinumab, while joint responses favoured anti-TNF therapies. Principal component analysis revealed distinct clustering of synovial tissue gene expression away from the matched skin. While IL12B, IL23A and IL23R were homogeneously expressed in lesional skin, their expression was extremely heterogeneous in paired synovial tissues. Here, IL-23 transcriptomic/protein expression was strongly linked to patients with high-grade synovitis who, however, were not distinguishable by conventional clinimetric measures. Conclusions PsA synovial tissue shows a heterogeneous IL-23 axis profile when compared with matched skin. Synovial molecular pathology may help to identify among clinically indistinguishable patients those with a greater probability of responding to IL-23 inhibitors.
Combination of Landsat 8 OLI and Sentinel-1 SAR Time-Series Data for Mapping Paddy Fields in Parts of West and Central Java Provinces, Indonesia

The rise of Google Earth Engine, a cloud computing platform for spatial data, has unlocked seamless integration for multi-sensor and multi-temporal analysis, which is useful for the identification of land-cover classes based on their temporal characteristics. Our study aims to employ temporal patterns from monthly-median Sentinel-1 (S1) C-band synthetic aperture radar data and cloud-filled monthly spectral indices, i.e., Normalized Difference Vegetation Index (NDVI), Modified Normalized Difference Water Index (MNDWI), and Normalized Difference Built-up Index (NDBI), from Landsat 8 (L8) OLI for mapping rice cropland areas in the northern part of Central Java Province, Indonesia. The harmonic function was used to fill the cloud and cloud-masked values in the spectral indices from Landsat 8 data, and smile Random Forests (RF) and Classification And Regression Trees (CART) algorithms were used to map rice cropland areas using a combination of monthly S1 and monthly harmonic L8 spectral indices. An additional terrain variable, Terrain Roughness Index (TRI) from the SRTM dataset, was also included in the analysis. Our results demonstrated that RF models with 50 (RF50) and 80 (RF80) trees yielded better accuracy for mapping the extent of paddy fields, with user accuracies of 85.65% (RF50) and 85.75% (RF80), and producer accuracies of 91.63% (RF80) and 93.48% (RF50) (overall accuracies of 92.10% (RF80) and 92.47% (RF50)), respectively, while CART yielded a user accuracy of only 84.83% and a producer accuracy of 80.86%. The model variable importance in both RF50 and RF80 models showed that vertical transmit and horizontal receive (VH) polarization and harmonic-fitted NDVI were identified as the top five important variables, and the variables representing February, April, June, and December contributed more to the RF model. The detection of VH and NDVI as the top variables which contributed up to 51% of the Random Forest model indicated the importance of the multi-sensor combination for the identification of paddy fields.
Nutrient Profiling of Romanian Traditional Dishes - Prerequisite for Supporting the Flexitarian Eating Style

Currently, most countries have to deal with multiple discrepancies that have arisen between the constraints of sustainable development and the return to traditions, involving food producers, as well as consumers, aspects that are also easily noticed in Romania. Thus, the main purpose of this study was to assess the nutritional quality of the Romanian traditional diet using a nutrient profiling method based on the Nutri-Score algorithm, applied to several representative Romanian traditional dishes. Because this algorithm has the capacity to highlight the amount (%) of fruits, vegetables, and nuts from a certain dish, it might be considered an indicator of the sustainable valences of the selected meals. The results showed that the traditional menus do not correspond to a balanced and sustainable eating behavior; thus, it is recommended to improve the Romanian pattern of food consumption and to ensure its sustainable basis. In order to achieve this goal, we propose the development of a new paradigm of the contemporary Romanian food style incorporating three main directions of action: acceptance, adaptation, and transformation.
Natural food antimicrobial systems

Overview, A.S. Naidu Lacto-Antimicrobials Lactoferrin. A.S. Naidu Lactoperoxidase, A.S. Naidu Lactoglobulins, E.F. Bostwick, J. Steijins, and S. Braun Lactolipids, M. Lampe and C. Isaacs Ovo-Antimicrobials Lysozymes, J.N. Losso, S. Nakai, and E.A. Charter Ovotransferrin, H.R. Ibrahim Ovoglobulin IgY, J.S. Sim, H.H. Sunwoo, and E.N. Lee Avidin, Y. Mine Phyto-Antimicrobials Phyto-phenols, P.M. , Davidson and A.S. Naidu Saponins, W.A. Oleszek Flavonoids, A.S. Naidu, W.R. Bidlack, and A.T. Crecelius Thiosulfinates, B.B. Whitmore and A.S. Naidu Catechins, L.R. Juneja, T. Okubo, and P. Hung Glucosinolates, B.B. Whitmore and A.S. Naidu Agar, A.S. Naidu Bacto-Antimicrobials Probiotics, A.S. Naidu and R.A. Clemens Nisin, L.V. Thomas, M.R. Clarkson, and J. Delves-Broughton Pediocin, B. Ray and K. Miller Reuterin, M.G. El-Ziney, J. Debevere, and M.Jakobsen Sakacin, F. Leroy and L. De Vuyst Acid-Antimicrobials Lactic Acid, J-C. Bogeart and A.S. Naidu Sorbic Acid, J.N. Sofos Acetic Acid, D.L. Marshall, L.N. Cotton, and F.A. Bal'a Citric Acid, R.K. Sharma Milieu-Antimicrobials Sodium Chloride, R. Ravishankar and V.K. Juneja Polyphosphates, A. Prakash Chloro-cides, N. Khanna and A.S. Naidu Ozone, M. Muthukumarappin, F. Halaweish, and A.S. Naidu Appendix (Abbreviations and Symbols) Index
Comparison of Post-fire Patterns in Brazilian Savanna and Tropical Forest from Remote Sensing Time Series

Monitoring of fire-related changes is essential to understand vegetation dynamics in the medium and long term. Remote sensing time series allows estimating biophysical variables of terrestrial vegetation and interference by extreme fires. This research evaluated fire recurrence in the Amazon and Cerrado regions, using Moderate Resolution Imaging Spectroradiometer (MODIS) albedo time series, enhanced vegetation index (EVI), gross primary productivity (GPP), and surface temperature. The annual aggregated time series (AAT) method recognized each pixel’s slope trend in the 2001–2016 period and its statistical significance. A comparison of time trends of EVI, GPP, and surface temperature with total fire recurrence indicates that time trends in vegetation are highly affected by high fire recurrence scenarios (R2 between 0.52 and 0.90). The fire recurrence and the albedo’s persistent changes do not have a consistent relationship. Areas with the biggest evaluated changes may increase up to 0.25 Kelvin/Year at surface temperature and decrease up to −0.012 EVI/year in vegetation index. Although savannas are resistant to low severity fires, fire regime and forest structure changes tend to make vegetation more vulnerable to wildfires, reducing their regeneration capacity. In the Amazon area, protection of forests in conservation units and indigenous lands helped in the low occurrence of fires in these sensitive areas, resulting in positive vegetation index trends.
Towards the sampling Lovász Local Lemma

Let <tex>$\Phi=(V, \mathcal{C})$</tex> be a constraint satisfaction problem on variables <tex>$v_{1}, \ldots, v_{n}$</tex> such that each constraint depends on at most <tex>$k$</tex> variables and such that each variable assumes values in an alphabet of size at most [<tex>$q$</tex>]. Suppose that each constraint shares variables with at most <tex>$\Delta$</tex> constraints and that each constraint is violated with probability at most <tex>$p$</tex> (under the product measure on its variables). We show that for <tex>$k, q=O(1)$</tex>, there is a deterministic, polynomial time algorithm to approximately count the number of satisfying assignments and a randomized, polynomial time algorithm to sample from approximately the uniform distribution on satisfying assignments, provided that <tex>$C\cdot q^{2}\cdot k\cdot p\cdot\Delta^{7} < 1$</tex>, where <tex>$C$</tex> is an absolute constant. Previously, a result of this form was known essentially only in the special case when each constraint is violated by exactly one assignment to its variables. For the special case of <tex>$k$</tex> . CNF formulas, the term <tex>$\Delta^{7}$</tex> improves the previously best known <tex>$\Delta^{60}$</tex> for deterministic algorithms [Moitra, J.ACM, 2019] and <tex>$\Delta^{13}$</tex> for randomized algorithms [Feng, Guo, Yin, and Zhang, STOC 2021]. For the special case of properly <tex>$q$</tex>-coloring <tex>$k$</tex>-uniform hypergraphs, the term <tex>$\Delta^{7}$</tex> improves the previously best known <tex>$\Delta^{14}$</tex> for deterministic algorithms [Guo, Liao, Lu, and Zhang, SICOMP, 2019] and <tex>$\Delta^{9}$</tex> for randomized algorithms [Feng, Guo, Yin, and Zhang, STOC 2021].