Empirical Transmit Field Bias Correction of T1w/T2w Myelin Maps T1-weighted divided by T2-weighted (T1w/T2w) myelin maps were initially developed for neuroanatomical analyses such as identifying cortical areas, but they are increasingly used in statistical comparisons across individuals and groups with other variables of interest. Existing T1w/T2w myelin maps contain radiofrequency transmit field (B1+) biases, which may be correlated with these variables of interest, leading to potentially spurious results. Here we propose two empirical methods for correcting these transmit field biases using either explicit measures of the transmit field or alternatively a 'pseudo-transmit' approach that is highly correlated with the transmit field at 3T. We find that the resulting corrected T1w/T2w myelin maps are both better neuroanatomical measures (e.g., for use in cross-species comparisons), and more appropriate for statistical comparisons of relative T1w/T2w differences across individuals and groups (e.g., sex, age, or body-mass-index) within a consistently acquired study at 3T. We recommend that investigators who use the T1w/T2w approach for mapping cortical myelin use these B1+ transmit field corrected myelin maps going forward.
Cortical granularity shapes the organization of afferent paths to the amygdala and its striatal targets in nonhuman primate The prefrontal cortex (PFC) and insula, amygdala, and striatum form interconnected networks that drive motivated behaviors. We previously found a connectional trend in which granularity of the ventromedial and orbital PFC/insula predicted connections to the amygdala, and also the breadth of amygdalo-striatal efferents, including projections beyond the classic ventral striatum. To further interrogate connectional relationships among the cortex, amygdala, and striatum, and to further define the limbic (amygdala-recipient) striatum, we conducted tract tracing studies in two cohorts of Macaques (Male n = 14, Female n = 1). We focused on the cortico-amygdalo-striatal (indirect) and cortico- limbic striatal (direct) paths originating in the entire PFC and insula. Larger data sets and a quantitative approach revealed cortical rules in which cortical granularity predicts the complexity and location of projections to both the basal nucleus of the amygdala and striatum. Remarkably, projections from cortical-like basal nucleus to the striatum followed similar patterns. In both direct and indirect paths to the limbic striatum, agranular cortices formed a foundational, broad projection, and were joined by inputs from progressively more differentiated cortices. In amygdalo-striatal paths, the ventral basal nucleus was the  foundational input, with progressively more dorsal basal nucleus regions gradually adding inputs as the limbic striatum extended caudally. Together, the  indirect and  direct paths followed consistent principles in which cortical granularity dictated the strength and complexity of projections at their targets. Cluster analyses independently confirmed these connectional trends, and also highlighted connectional features that predicted termination in specific subregions of the basal nucleus and limbic striatum.

Significance StatementThe limbic system broadly refers to brain circuits that coordinate emotional responses. Here, we investigate circuits of the amygdala, which are involved in coding the emotional value of external cues, and their influence on the striatum. Regions of prefrontal cortex and insula form gradients of overlapping inputs to the amygdalas basal nucleus, which feed forward to the striatum. Direct cortical inputs to these amygdala-recipient striatal areas are surprisingly organized according to similar principles, but subtly shift from the classic ventral striatum to the caudal ventral striatum. Together, these distinct subsystems--cortico-amygdala-striatal circuits and direct cortico-striatal circuits-- provide substantial opportunity for different levels of internal, sensory, and external experiences to be integrated within the striatum, a major motor-behavioral interface.
Phenomics data processing: Extracting dose-response curve parameters from high-resolution temperature courses and repeated field-based wheat height measurements Temperature is a main driver of plant growth and development. New phenotyping tools enable quantifying the temperature response of hundreds of genotypes. Yet, for field-derived data, temperature response modeling bears flaws and pitfalls concerning the interpretation of derived parameters. In this study, climate data from five growing seasons with differing temperature distributions served as starting point for a growth simulation of wheat stem elongation, based on a four-parametric temperature response function (Wang-Engel) including all cardinal temperatures. In a novel approach, we re-extracted dose-responses from the simulation by combining high-resolution (hours) temperature courses with low-resolution (days) height data. The collection of such data is common in field phenotyping platforms. To take advantage of the lack of supra-optimal temperatures during the stem elongation, simpler (linear and asymptotic) models to predict temperature-response parameters were investigated. The asymptotic model extracted the base temperature of growth and the maximum absolute growth rate with high precision, whereas simpler, linear models failed to do so. Additionally, the asymptotic model provided a proxy estimate for the optimum temperature. However, when including seasonally changing cardinal temperatures, the prediction accuracy of the asymptotic model was strongly reduced. In a field study with three winter wheat varieties, significant differences were found for all three asymptotic dose-response curve parameters. We conclude that the asymptotic model based on high-resolution temperature courses is suitable to extract meaningful parameters from field-based data. High school science fair: Experiences of two groups of undergraduate bioscience students Science fairs offer potential opportunities for students to learn first-hand about the practices of science. Over the past six years we have been carrying out voluntary and anonymous surveys with regional and national groups of high school and post high school students to learn about their high school science fair experiences regarding help received, obstacles encountered, and opinions about the value and impact of science fair. Understanding what students think about science fairs will help educators make science fairs more effective learning opportunities. In this paper, we focus on the findings with two national groups of post high school students - undergraduate research fellows (SURF students) who did research at UT Southwestern Medical Center during 2014-2019 and undergraduates biology students attending the 2019 Howard Hughes Medical Institute Science Education Alliance (SEA) summer symposium. About 25% of the students who completed surveys indicated that they had participated in high school science fair, but more than half attended high schools where science fairs were unavailable. Effectively, 6 out of every 10 students participated in science fair if available. Students who could have participated in high school science fair but chose not to do so identified not enough time and coming up with their project idea as major reasons why not. About half the SURF students favored requiring non-competitive science fair regardless whether they themselves had participated in science fair. On the other hand, less than 1 in 5 thought that competitive science fair should be required. Introduction to the scientific process and general learning were mentioned most frequently as the reasons to require non-competitive science fair; these reasons were mentioned rarely in connection with competitive science fair. Unlike the national cohort of high school students we surveyed previously, who mostly did science fair in 9th and 10th grades, SURF students participated in science fair throughout high school and were twice as likely as high school students to have carried out science fair more than once. In conclusion, our findings suggest that participation of the undergraduate bioscience majors in high school science fairs occurs far more frequently than recognized previously. The findings emphasize further the importance of incentivizing rather than requiring science fair participation, especially in 9th and 10th grades, and the potential value of developing non-competitive science fairs. Chromatin remodelling by INO80 at promoter proximal pause sites promotes premature termination of mRNA synthesis How co-transcriptional RNA quality control is regulated remains poorly understood. Here, we report that in S. cerevisiae premature transcription termination of mRNAs is regulated by the evolutionarily conserved ATP-dependent chromatin remodeling INO80 complex. Loss of INO80 leads to an increase in promoter-proximally paused RNA Polymerase II and defective progression into the gene body. We show that promoter-proximal transcriptional pausing correlates with loading of RNA surveillance and transcription termination factors to mRNA transcripts. Cells lacking INO80 are defective for the Nrd1-Nab3-Sen1 (NNS)-dependent pathway for transcription termination at snRNA genes and promoter-proximally sites of mRNA genes. We demonstrate that INO80 promotes the association of the RNA surveillance and termination factor Nab2 with short promoter-proximal mRNA transcripts. We provide evidence that co-transcriptional recruitment of Nab2 to chromatin is regulated by INO80, which enables the interaction of Nab2 with the histone variant H2A.Z. Our work suggests a chromatin mechanism for premature transcription termination at promoter-proximally pausing sites, linking RNA quality control to the transcriptional process. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Simpati: patient classifier identifies signature pathways based on similarity networks for the disease prediction BACKGROUNDPathway-based patient classification is a supervised learning task which implies a model learning pathways as features to predict the classes of patients. The counterpart of enrichment tools for the pathway analysis are fundamental methods for clinicians and biomedical scientists. They allow to find signature cellular functions which help to define and annotate a disease phenotype. They provide results which lead human experts to manually classify patients. It is a paradox that pathwaybased classifiers which natively resolve this objective are not strongly developed. They could simulate the human way of thinking, decipher hidden multivariate relationships between the deregulated pathways and the disease phenotype, and provide more information than a probability value. Instead, there are currently only two classifiers of such kind, they require a nontrivial hyperparameter tuning, are difficult to interpret and lack in providing new insights. There is the need of new classifiers which can provide novel perspectives about pathways, be easy to apply with different biological omics and produce new data enabling a further analysis of the patients.

RESULTSWe propose Simpati, an innovative and interpretable patient classifier based on pathway-specific patient similarity networks. The first classifier to adopt ad-hoc novel algorithms for such graph type. It standardizes the biological high-throughput dataset of patients profiles with a propagation algorithm that considers the interconnected nature of the cells molecules for inferring a new activity score. This allows Simpati to classify with dense, sparse, and non-homogenous omic data. Simpati organizes patients molecules in pathways represented by patient similarity networks for being interpretable, handling missing data and preserving the patient privacy. A network represents patients as nodes and a novel similarity measure determines how much every pair act co-ordinately in a pathway. Simpati detects signature biological processes based on how much the topological properties of the related networks separate the patient classes. In this step, it includes a new cohesive subgroup detection algorithm to handle patients not showing the same pathway activity as the other class members. An unknown patient is then classified by a unique recommender system which considers how much is similar to known patients and distant from being an outlier. Simpati outperforms previously published classifiers on five cancer datasets described with two biological omics, classifies well with sparse data, identifies more relevant pathways associated to the patients disease than the competitors and has the lowest computational requirements.

CONCLUSIONSimpati can serve as generic-purpose pathway-based classifier of patient classes. It provides signature pathways to unveil the altered biological mechanisms of a disease phenotype and to classify patients according to the learnt pathway-specific similarities. The signature condition and patient prediction can be deciphered considering the patient similarity networks which must reveal the members of a patient class more cohesive and similar than the non-members. Simpati divides the pathways in up and downinvolved. Upinvolved when the signaling cascades generated by the altered molecules of the disease patients impact stronger the pathway than the ones of the control class. We provide an R implementation, a graphical user interface and a visualization function for the patient similarity networks. The software is available at: https://github.com/LucaGiudice/Simpati Changes in Behavior and Salivary Serum Amyloid A in cows with Subclinical Mastitis The aim of this study was to identify detailed changes in behavior, and in salivary serum amyloid A (SAA), associated with subclinical mastitis. This included standard sickness behaviors (which form part of an adaptive response to conserve energy, minimize heat loss and facilitate recovery following infection and inflammation) and lesser-studied behaviors, that are biologically predicted to change at low-level infection, and therefore particularly relevant for detecting subclinical mastitis (here labelled  luxury behaviors). SAA is a physiological marker of systemic inflammation, with levels in milk and serum already known to increase during subclinical mastitis. We investigated whether the same was true for SAA in cow saliva. Data were collected for n = 34 commercial barn-housed dairy cows, tested in 17 matched-pairs. Each pair comprised a cow with subclinical mastitis (SCM) and a healthy control (CTRL), identified using somatic cell count (SCC) (SCM: SCC >200 x1000 cells/ml; CTRL: SCC <100 x1000 cells/ml). SCM cows were selected for study ad-hoc, at which point they were paired with a CTRL cow, based upon parity and calving date; consequently, the full data set was accrued over several months. Data were collected for each pair over 3 days: SCC (l4:00-l5:00h) Day 1; behavior (24h from 00:00h) Day 2; salivary serum amyloid-A (SAA) Day 3. We report, for the first time, that an increase in salivary SAA occurs during subclinical mastitis; SAA was higher in SCM cows and demonstrated a positive (weak) correlation with SCC. The behavioral comparisons revealed that SCM cows had reductions in activity (behavioral transitions and distance moved), social exploration, social reactivity (here: likelihood to move away/be displaced following receipt of agonism), performance of social grooming and head butts, and the receipt of agonistic non-contact challenges. In addition, SCM cows received more head swipes, and spent a greater proportion of time lying with their head on their flank than CTRL cows. SCM cows also displayed an altered feeding pattern; they spent a greater proportion of feeding time in direct contact with two conspecifics, and a lower proportion of feeding time at self-locking feed barriers, than CTRL cows. Behavioral measures were found to correlate, albeit loosely, with serum SAA in a direction consistent with predictions for sickness behavior. These included positive correlations with both lying duration and the receipt of all agonistic behavior, and negative correlations with feeding, drinking, the performance of all social and all agonistic behavior, and social reactivity. We conclude that changes in salivary SAA, social behavior, and activity offer potential in the detection of subclinical mastitis and recommend further investigation to substantiate and refine our findings. ChAdOx1 nCoV-19 (AZD1222) protects Syrian hamsters against SARS-CoV-2 B.1.351 and B.1.1.7 1 disease We investigated ChAdOx1 nCoV-19 (AZD1222) vaccine efficacy against SARS-CoV-2 variants of concern (VOCs) B.1.1.7 and B.1.351 in Syrian hamsters. We previously showed protection against SARS-CoV-2 disease and pneumonia in hamsters vaccinated with a single dose of ChAdOx1 nCoV-19. Here, we observed a 9.5-fold reduction of virus neutralizing antibody titer in vaccinated hamster sera against B.1.351 compared to B.1.1.7. Vaccinated hamsters challenged with B.1.1.7 or B.1.351 did not lose weight compared to control animals. In contrast to control animals, the lungs of vaccinated animals did not show any gross lesions. Minimal to no viral subgenomic RNA (sgRNA) and no infectious virus was detected in lungs of vaccinated animals. Histopathological evaluation showed extensive pulmonary pathology caused by B.1.1.7 or B.1.351 replication in the control animals, but none in the vaccinated animals. These data demonstrate the effectiveness of the ChAdOx1 nCoV-19 vaccine against clinical disease caused by B.1.1.7 or B.1.351 VOCs. Ribosome actuator via the SpoT/ppGpp pathway to mitigate gene overexpression burden Gene overexpression causes a burden on ribosomes, which decreases the expression of other genes and growth rate. Here, we engineer a genetic ribosome actuator that increases gene expression rate and growth rate by over 150% and 80%, respectively. The actuator expresses the hydrolysis domain of the SpoT enzyme (SpoTH) in a bacterial strain with high basal levels of ppGpp, thus increasing ribosome availability. We use this actuator in a feedforward control arrangement, wherein SpoTH is co-expressed with a gene of interest (GOI). Without SpoTH co-expression, activation of the GOI decreases the expression of a constitutive gene and growth rate by over 80% and 40%, respectively. By contrast, with SpoTH co-expression, the ribosome binding site (RBS) of SpoTH can be tuned to achieve inappreciable change of either the expression of the constitutive gene or growth rate when the GOI is activated to the same level. We finally employ the actuator to keep growth rate constant while expressing dCas9 to a level that would otherwise decrease growth rate by more than 40% due to toxicity. This actuator will be relevant in applications where high cellular protein concentrations are desired without growth defects or global reduction of gene expression. Presence of a SARS-COV-2 protein enhances Amyloid Formation of Serum Amyloid A A marker for the severeness and disease progress of COVID-19 is overexpression of serum amyloid A (SAA) to levels that in other diseases are associated with a risk for SAA amyloidosis. In order to understand whether SAA amyloidosis could also be a long-term risk of SARS-COV-2 infections we have used long all-atom molecular dynamic simulations to study the effect of a SARS-COV-2 protein segment on SAA amyloid formation. Sampling over 40 {micro}s we find that presence of the nine-residue segment SK9, located at the C-terminus of the Envelope protein, increases the propensity for SAA fibril formation by three mechanisms: it reduces the stability of the lipid-transporting hexamer shifting the equilibrium toward monomers, it increases the frequency of aggregation-prone configurations in the resulting chains, and it raises the stability of SAA fibrils. Our results therefore suggest that SAA amyloidosis and related pathologies may be a long-term risk of SARS-COV-2 infections. Bispecific antibody neutralizes circulating SARS-CoV-2 variants, prevents escape and protects mice from disease Neutralizing antibodies targeting the receptor binding domain (RBD) of the SARS-CoV-2 Spike (S) are among the most promising approaches against coronavirus disease 2019 (COVID-19)1,2. We developed a bispecific, IgG1-like molecule (CoV-X2) based on two antibodies derived from COVID-19 convalescent donors, C121 and C1353. CoV-X2 simultaneously binds two independent sites on the RBD and, unlike its parental antibodies, prevents detectable S binding to Angiotensin-Converting Enzyme 2 (ACE2), the virus cellular receptor. Furthermore, CoV-X2 neutralizes SARS-CoV-2 and its variants of concern, as well as the escape mutants generated by the parental monoclonals. In a novel animal model of SARS-CoV-2 infection with lung inflammation, CoV-X2 protects mice from disease and suppresses viral escape. Thus, simultaneous targeting of non-overlapping RBD epitopes by IgG-like bispecific antibodies is feasible and effective, combining into a single molecule the advantages of antibody cocktails. Analysis of Drosophila cardiac hypertrophy by micro-computerized tomography for genetic dissection of heart growth mechanisms Heart failure is often preceded by pathological cardiac hypertrophy, a thickening of the heart musculature driven by complex gene regulatory and signaling processes. The Drosophila heart has great potential as a genetic model for deciphering the underlying mechanisms of cardiac hypertrophy. However, current methods for evaluating hypertrophy of the Drosophila heart are laborious and difficult to carry out reproducibly. Here we demonstrate that micro-computerized tomography (microCT) is an accessible, highly reproducible method for non-destructive, quantitative analysis of Drosophila heart morphology and size. To validate our microCT approach for analyzing Drosophila cardiac hypertrophy, we show that expression of constitutively active Ras (Ras85DV12), previously shown to cause hypertrophy of the fly heart, results in significant thickening of both adult and larval heart walls when measured from microCT images. We then show using microCT analysis that genetic upregulation of store-operated Ca2+ entry (SOCE) driven by expression of constitutively active Stim (StimCA) or Orai (OraiCA) proteins also results in significant hypertrophy of the Drosophila heart, through a process that specifically depends on Orai Ca2+ influx channels. Intravital imaging of heart contractility revealed significantly reduced end diastolic dimensions in StimCA and OraiCA expressing hearts, consistent with the hypertrophic phenotype. These results demonstrate that increased SOCE activity is an important driver of hypertrophic cardiomyocyte growth, and demonstrate how microCT analysis combined with tractable genetic tools in Drosophila can be used to delineate molecular signaling processes that underlie cardiac hypertrophy and heart failure.

NEW AND NOTEWORTHYGenetic analysis of cardiac hypertrophy in Drosophila holds immense potential for the discovery of new therapeutic targets to prevent and treat heart failure. However, this potential has been hindered by a lack of rapid and effective methods for analysis of heart size in flies. Here we demonstrate that analysis of the Drosophila heart with micro-computerized tomography yields accurate and highly reproducible heart size measurements that can be used to efficiently analyze heart growth and cardiac hypertrophy in Drosophila. Repeated subfunctionalization of a modular antimicrobial peptide gene for neural function Antimicrobial peptides (AMPs) are host-encoded antibiotics that combat invading pathogens. These genes commonly encode multiple products as post-translationally cleaved polypeptides. Recent studies have highlighted roles for AMPs in neurological contexts suggesting functions for these defence molecules beyond infection. During our immune study characterizing the antimicrobial peptide gene Baramicin, we recovered multiple Baramicin paralogs in Drosophila melanogaster and other species, united by their N-terminal IM24 domain. Not all paralogs were immune-induced. Here, through careful dissection of the Baramicin familys evolutionary history, we find that these non-immune paralogs result from repeated events of duplication and subsequent truncation of the coding sequence from an immune-inducible ancestor. These truncations leave only the IM24 domain as the prominent gene product. Surprisingly, using mutation and targeted gene silencing we demonstrate that two such genes are adapted for function in neural contexts in D. melanogaster. We also show enrichment in the head for independent Baramicin genes in other species. The Baramicin evolutionary history reveals that the IM24 Baramicin domain is not strictly useful in an immune context. We thus provide a case study for how an AMP-encoding gene might play dual roles in both immune and non-immune processes via its multiple peptide products. We reflect on these findings to highlight a blind spot in the way researchers approach AMP research in in vivo contexts.

Significance statementAntimicrobial peptides are immune proteins recently implicated in neurological roles. To date little attention has been paid to the contributions of different gene products in this function. Here we show that an antimicrobial peptide gene encodes multiple products with either immune-specific or neurological roles. Medium-throughput zebrafish optogenetic platform identifies deficits in subsequent neural activity following brief early exposure to cannabidiol and Δ-9-tetrahydrocannabinol In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development. Low dose rate γ-irradiation protects Drosophila melanogaster chromosomes from double strand breaks and telomere fusions by modulating the expression of the esi-RNA biogenesis factor Loquacious. It is still continuously debated whether the low-dose/dose-rate (LDR) of ionizing radiation represents a hazard for humans. Model organisms, such as fruit flies, are considered valuable systems to reveal insights into this issue. We found that, in wild-type Drosophila melanogaster larval neuroblasts, the frequency of Chromosome Breaks (CBs), induced by acute {gamma}-irradiation, is significantly reduced when flies are previously exposed to a protracted dose of 0.4Gy delivered at a dose rate of 2.5mGy/h. This indicates that this exposure, which is associated with an increased expression of DNA damage response proteins, induces a radioadaptive response (RAR) that protects Drosophila from extensive DNA damage. Interestingly, the same exposure reduces the frequency of telomere fusions (TFs) from Drosophila telomere capping mutants suggesting that the LDR can generally promote a protective response on chromatin sites that are recognized as DNA breaks. Deep RNA sequencing revealed that RAR is associated with a reduced expression of Loquacious D (Loqs-RD) gene that encodes a well-conserved dsRNA binding protein required for esiRNAs biogenesis. Remarkably, loss of Loqs mimics the LDR-mediated chromosome protection as it decreases the IR-induced CBs and TF frequency. Thus, our molecular characterization of RAR identifies Loqs as a key factor in the cellular response to LDR and unveils unprecedented epigenetic routes involved in radioresistance. Dynamic tracing using ultra-bright labelling and multi-photon microscopy identifies endothelial uptake of poloxamer-188 coated poly(lactic-co-glycolic acid)nano-carriers in vivo Poly(lactic-co-glycolic acid) (PLGA)-based drug formulations are approved for the use in humans, however, the potential of PLGA to design nanoparticles (NPs) and target the central nervous system remains to be exploited.

The aim of the current study was design PLGA NPs, loading them with bulky fluorophores thereby increasing single particle fluorescence to a level visible by in vivo microscopy, and investigate their brain biodistribution. We developed, highly fluorescent 70 nm PLGA NPs significantly brighter then quantum dots enabling their visualization by intravital real-time 2-photon microscopy. We found that PLGA NPs coated with pluronic F-68 (PF-68) had a substantially longer plasma half-life than uncoated NPs and were taken up by cerebro-vascular endothelial cells. High resolution confocal microscopy revealed that coated PLGA NPs were present in late endothelial endosomes of cerebral vessels within 1 hour after systemic injection and were more readily taken up by endothelial cells in peripheral organs.

The current data suggest that PF-68 coated PLGA NPs are taken up by mouse cerebral and peripheral endothelial cells in vivo. The combination of ultra-bright NPs and in vivo imaging may thus represent a promising approach to reduce the gap between development and clinical application of nanoparticle-based drug carriers. Simultaneous suppression of ribosome biogenesis and Tor activation by TRIM-NHL proteins promotes terminal differentiation Proper tissue development and homeostasis depends on the balance between growth and terminal differentiation, but the mechanisms coordinating these processes remain elusive. Accumulating evidence indicates that ribosome biogenesis (RiBi) and protein synthesis, two of the most energy-consuming cellular processes sustaining growth, are tightly regulated and yet can be uncoupled during stem cell fate transitions. Here, using the Drosophila adult female germline stem cell (GSC) and larval neuroblast (NB) systems, we show that Mei-P26 and Brat, two Drosophila TRIM-NHL paralogs of the mammalian TRIM32 protein family, are responsible for uncoupling RiBi and protein synthesis during GSC and NB differentiation, respectively. Mei-P26 and Brat modify the metabolism of differentiating cells by activating the Target of rapamycin (Tor) kinase to promote translation, while concomitantly repressing RiBi. Depletion of Mei-P26 or Brat results in excessive cellular growth and defective terminal differentiation, which can be rescued by ectopic activation of Tor together with suppression of RiBi. Our results indicate that the anabolic reprogramming established by TRIM-NHL activity by uncoupling RiBi and translation activities creates the conditions required for terminal differentiation. Ultra-sensitive nanoLC-MS of sub nanogram protein samples using second generation micro pillar array LC technology with Orbitrap Exploris 480 and FAIMS PRO In the light of the ongoing single-cell revolution, scientific disciplines are combining forces to retrieve as much relevant data as possible from trace amounts of biological material. For single cell proteomics, this implies optimizing the entire workflow from initial cell isolation down to sample preparation, liquid chromatography (LC) separation, mass spectrometer (MS) data acquisition and data analysis. To demonstrate the potential for single cell and limited sample proteomics, we report on a series of benchmarking experiments where we combine LC separation on a new generation of micro pillar array columns with state-of-the-art Orbitrap MS/MS detection and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS). This dedicated limited sample column has a reduced cross section and micro pillar dimensions that have been further downscaled (inter pillar distance and pillar diameter by a factor of 2), resulting in improved chromatography at reduced void times. A dilution series of a HeLa tryptic digest (5-0.05 ng/L) was used to explore the sensitivity that can be achieved. Comparative processing of the MS/MS data with Sequest HT, MS Amanda, Mascot and SpectroMine pointed out the benefits of using Sequest HT together with INFERYS when analyzing sample amounts below 1 ng. 2855 protein groups were identified from just 1 ng of HeLa tryptic digest hereby increasing detection sensitivity as compared to a previous contribution by a factor well above 10. By successfully identifying 1486 protein groups from as little as 250 pg of HeLa tryptic digest, we demonstrate outstanding sensitivity with great promise for use in limited sample proteomics workflows. A new method for the sampling and preservation of placental specimens in low-resource settings for the identification of P. falciparum and analysis of nucleic acids Collection, preservation, and shipment of histological specimens in low-resource settings is challenging. We present a novel method that achieved excellent preservation of placental specimens from rural Mali by using formalin fixation, ethanol dehydration, and long-term storage in a solar-powered freezer. Sample preservation success was 92%, permitting evaluation of current and past malaria infection, anemia, placental maturity, and inflammation. Using RNAscope(R) hybridization we were able to visualize cell-specific gene expression patterns in the formalin-fixed paraffin-embedded (FFPE) specimens. Additionally, our method entailed mirrored sampling from the two cut faces of a cotyledon, one for the FFPE workflows and the other for storage in RNAlater and RNA-seq. A unified mechanism for innate and learned visual landmark guidance in the insect central complex Insects can navigate efficiently in both novel and familiar environments, and this requires flexiblity in how they are guided by sensory cues. A prominent landmark, for example, can ellicit strong innate behaviours (attraction or menotaxis) but can also be used, after learning, as a specific directional cue as part of a navigation memory. However, the mechanisms that allow both pathways to co-exist, interact or override each other are largely unknown. Here we propose a model for the behavioural integration of innate and learned guidance based on the neuroanatomy of the central complex (CX), adapted to control landmark guided behaviours. We consider a reward signal provided either by an innate attraction to landmarks or a long-term visual memory in the mushroom bodies (MB) that modulates the formation of a local vector memory in the CX. Using an operant strategy for a simulated agent exploring a simple world containing a single visual cue, we show how the generated short-term memory can support both innate and learned steering behaviour. In addition, we show how this architecture is consistent with the observed effects of unilateral MB lesions in ants that cause a reversion to innate behaviour. We suggest the formation of a directional memory in the CX can be interpreted as transforming rewarding (positive or negative) sensory signals into a mapping of the environment that describes the geometrical attractiveness (or repulsion). We discuss how this scheme might represent an ideal way to combine multisensory information gathered during the exploration of an environment and support optimized cue integration.

1 Author summaryIn this paper, we modeled the neural pathway allowing insects to perform landmark guided behaviours using their internal compass. First, we observed the intrinsic property of the connectome, extracted from drosophila online database, between the internal compass neurons and the steering neurons to support an oriented behaviour towards a single landmark. Then, we proposed and evaluated an adaptation of the bees path integration neural circuit, to sustain flexible landmark guidance behaviours such as attraction or menotaxis. We showed the model ability to form a memory during the exploration of the local environment to support both innate or learned navigation behaviour using a single landmark in the environment. In addtion, we demonstrated the transformation of a simple goodness/badness signal, from innate or long-term memory pathways, into an oriented steering signal that could be applied to other sensory pathways. Furthermore, by reproducing lesion experiments in the mushroom bodies of wood ants we highlight the consistency of the model with biological observation. We then discuss the different emergent properties and the potential outcome that this local, and operant, memory supports. Intergenerational Effects of Early Life Starvation on Life-History, Consumption, and Transcriptome of a Holometabolous Insect Intergenerational effects, also known as parental effects in which the offspring phenotype is influenced by the parental phenotype, can occur in response to factors that occur not only in early but also in late parental life. However, little is known about how these parental life stage-specific environments interact with each other and with the offspring environment to influence offspring phenotype, particularly in organisms that realize distinct niches across ontogeny. We examined the effects of parental larval starvation and adult reproductive environment on offspring traits under matching or mismatching offspring larval starvation conditions using the holometabolous, haplo-diploid insect Athalia rosae (turnip sawfly). We show that the parental larval starvation treatment had trait-dependent intergenerational effects on both life-history and consumption traits of offspring larvae, partly in interaction with offspring conditions and sex, while there was no significant effect of parental adult reproductive environment. In addition, while offspring larval starvation led to numerous gene- and pathway-level expression differences, parental larval starvation impacted fewer genes and only the ribosomal pathway. Our findings reveal that parental starvation evokes complex intergenerational effects on offspring life-history traits, consumption patterns as well as gene expression, although the effects are less pronounced than those of offspring starvation. Raman Signal Denoising using Fully Convolutional Encoder Decoder Network Raman spectroscopy is a vibrational method that gives molecular information rapidly and non-invasively. Despite its advantages, the weak intensity of Raman spectroscopy leads to low-quality signals, particularly with tissue samples. The requirement of high exposure times makes Raman a time-consuming process and diminishes its non-invasive property while studying living tissues. Novel denoising techniques using convolutional neural networks (CNN) have achieved remarkable results in image processing. Here, we propose a similar approach for noise reduction for the Raman spectra acquired with 10x lower exposure times. In this work, we developed fully convolutional encoder-decoder architecture (FCED) and trained them with noisy Raman signals. The results demonstrate that our model is superior (p-value < 0.0001) to the conventional denoising techniques such as the Savitzky-Golay filter and wavelet denoising. Improvement in the signal-to-noise ratio values ranges from 20% to 80%, depending on the initial signal-to-noise ratio. Thus, we proved that tissue analysis could be done in a shorter time without any need for instrumental enhancement. A non-canonical convergence of carbohydrate and glutamine metabolism is required after metabolic rewiring in a solid environment The fate of pyruvate, which is modulated by the activity of the mitochondrial pyruvate carrier (MPC), is a defining metabolic feature in many cancers. Diffuse large B-cell lymphomas (DLBCLs) are a genetically and metabolically heterogeneous cancer. Although MPC expression and activity differed between DLBCL subgroups, mitochondrial pyruvate was uniformly consumed by glutamate pyruvate transaminase 2 (GPT2) to support -ketoglutarate production as part of glutaminolysis. This led us to discover that glutamine exceeds pyruvate as a carbon source for the tricarboxylic acid (TCA) cycle in DLBCLs. Furthermore, we found that MPC inhibition unexpectedly leads to decreased glutaminolysis, which is contrary to previous observations in other cell types. We also discovered that MPC inhibition and depletion only decreased DLBCL proliferation in an extracellular matrix (ECM) environment and in vivo xenografts, but not in the typical DLBCL suspension environment. We also have found that the metabolic profile of DLBCL cells in ECM is markedly different from cells in suspension environment. Thus, we report that besides the canonical glutamate dehydrogenase (GDH)-mediated glutaminolysis, the non-canonical GPT2 mediated consumption and assimilation of glutamine and pyruvate in DLBCLs enables their proliferation in an extracellular environment-dependent manner.

HIGHLIGHTSO_LIGlutamine, but not glucose, is a major carbon source for the tricarboxylic acid cycle in diffuse large B-cell lymphomas.
C_LIO_LIMitochondrial pyruvate supports glutaminolysis in diffuse large B-cell lymphomas by supplying pyruvate for glutamate pyruvate transaminase 2-mediated  -ketoglutarate production.
C_LIO_LIMitochondrial pyruvate carrier inhibition leads to decreased glutaminolysis in diffuse large B-cell lymphomas.
C_LIO_LI -ketoglutarate production is important for diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment.
C_LIO_LIMitochondrial pyruvate carrier activity supports diffuse large B-cell lymphoma proliferation in a solid extracellular matrix environment and in mouse xenografts.
C_LI Identifying critical transcriptional targets of the MYC oncogene using a novel competitive precision genome editing (CGE) assay MYC is an oncogenic transcription factor that controls major pathways promoting cell growth and proliferation. MYC has been implicated in the regulation of large number of genes, but the exact target genes responsible for its proliferative effects are still not known. Here, we use a novel competitive genome editing (CGE) assay for studying the functional consequence of precise mutations of MYC binding sites on cell proliferation. The CGE method is based on precision genome editing, where a CRISPR/Cas9-induced DNA break is repaired using a template that either reconstitutes the original feature or introduces an altered sequence. Both types of repair templates harbor sequence tags that allow direct comparison between cells that carry original and mutant features and generate a large number of replicate cultures. The CGE method overcomes the limitations of CRISPR/Cas9-technology in analyzing the effect of genotype on phenotype, namely the difficulty of cutting DNA exactly at the intended site, and the decreased cell proliferation caused by the DNA cuts themselves. Importantly, it provides a powerful method for studying subtle effects elicited by mutation of individual transcription factor binding sites. We show here that E-box mutations at several MYC target gene promoters resulted in reduced cellular fitness, demonstrating a direct correlation between MYC-regulated cellular processes and MYC binding and identifying important transcriptional targets responsible for its functions. Pan-cancer HLA Gene-mediated Tumor Immunogenicity and Immune Evasion Human Leukocyte Antigen (HLA) expression contributes to the activation of anti-tumor immunity through interactions with T cell receptors. However, pan-cancer HLA-mediated immunogenicity and immunoediting mechanisms has not been systematically studied. In a retrospective analysis of 33 tumor types from the Cancer Genome Atlas, we uncovered HLA class I and class II differential expression, which outperformed traditional clinical metrics in predicting patient survival. We also characterized the distribution of HLA supertypes across cancers and showed that patients with high HLA allelic diversity and gene expression had better prognosis. Immune microenvironments with varied survival outcomes could be predicted using a neural network model trained on HLA expression data. Furthermore, we identified a subset of tumors which upregulated HLA class I but not class II genes and exploited HLA-mediated escape strategies. Our results suggest the potential of using HLA expression data to predict patient prognosis. Taken together, we emphasize the crucial role of HLA upregulation in shaping prolonged anti-tumor immunity.

SynopsisIn a retrospective analysis of 11080 patients of 33 TCGA cancer types, we showed HLA class I and class II differential expression shape various immune microenvironments and tumor immunoediting mechanisms, predicting tumor immunogenicity and patient survival.