Antiviral Effect of Antimicrobial Peptoid TM9 and Murine Model of Respiratory Coronavirus Infection.

New antiviral agents are essential to improving treatment and control of SARS-CoV-2 infections that can lead to the disease COVID-19. Antimicrobial peptoids are sequence-specific oligo-N-substituted glycine peptidomimetics that emulate the structure and function of natural antimicrobial peptides but are resistant to proteases. We demonstrate antiviral activity of a new peptoid (TM9) against the coronavirus, murine hepatitis virus (MHV), as a closely related model for the structure and antiviral susceptibility profile of SARS-CoV-2. This peptoid mimics the human cathelicidin LL-37, which has also been shown to have antimicrobial and antiviral activity. In this study, TM9 was effective against three murine coronavirus strains, demonstrating that the therapeutic window is large enough to allow the use of TM9 for treatment. All three isolates of MHV generated infection in mice after 15 min of exposure by aerosol using the Madison aerosol chamber, and all three viral strains could be isolated from the lungs throughout the 5-day observation period post-infection, with the peak titers on day 2. MHV-A59 and MHV-A59-GFP were also isolated from the liver, heart, spleen, olfactory bulbs, and brain. These data demonstrate that MHV serves as a valuable natural murine model of coronavirus pathogenesis in multiple organs, including the brain.

Breast Multiparametric MRI for Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer: The BMMR2 Challenge.

Purpose To describe the design, conduct, and results of the Breast Multiparametric MRI for prediction of neoadjuvant chemotherapy Response (BMMR2) challenge. Materials and Methods The BMMR2 computational challenge opened on May 28, 2021, and closed on December 21, 2021. The goal of the challenge was to identify image-based markers derived from multiparametric breast MRI, including diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) MRI, along with clinical data for predicting pathologic complete response (pCR) following neoadjuvant treatment. Data included 573 breast MRI studies from 191 women (mean age [±SD], 48.9 years ± 10.56) in the I-SPY 2/American College of Radiology Imaging Network (ACRIN) 6698 trial (ClinicalTrials.gov: NCT01042379). The challenge cohort was split into training (60%) and test (40%) sets, with teams blinded to test set pCR outcomes. Prediction performance was evaluated by area under the receiver operating characteristic curve (AUC) and compared with the benchmark established from the ACRIN 6698 primary analysis. Results Eight teams submitted final predictions. Entries from three teams had point estimators of AUC that were higher than the benchmark performance (AUC, 0.782 [95% CI: 0.670, 0.893], with AUCs of 0.803 [95% CI: 0.702, 0.904], 0.838 [95% CI: 0.748, 0.928], and 0.840 [95% CI: 0.748, 0.932]). A variety of approaches were used, ranging from extraction of individual features to deep learning and artificial intelligence methods, incorporating DCE and DWI alone or in combination. Conclusion The BMMR2 challenge identified several models with high predictive performance, which may further expand the value of multiparametric breast MRI as an early marker of treatment response. Clinical trial registration no. NCT01042379 Keywords: MRI, Breast, Tumor Response Supplemental material is available for this article. © RSNA, 2024.

Judgments of learning reflect the encoding of contexts, not items: evidence from a test of recognition exclusion.

Two sources of evidence seem to be shared by judgments of past recognition and judgments of future performance: item memory or familiarity (i.e., memory for the item independent of the context in which it was experienced) and context memory or recollection (i.e., memory for the context specific to a particular prior encounter). However, there are few studies investigating the link between these two putative memory processes and judgments of learning (JOLs). We tested memory and metamemory using a continuous exclusion procedure - a modified recognition memory task where study events for two classes of items are interleaved with test trials in which the subject must endorse items from one class and reject items from the other. This procedure allowed us to estimate the influences of memory for context and memory for item on JOLs and licenses conclusions about the relative role of item and context information in supporting JOLs. An analysis of forgetting revealed that JOLs reflect both the initial degree of learning and the rate of forgetting, but only of memory for context and not of memory for items. These findings suggest that JOLs are predictive of memory for context-bound episodes, rather than for the semantic content of those episodes.

Peptide-mimetic treatment of Pseudomonas aeruginosa in a mouse model of respiratory infection.

The rise of drug resistance has become a global crisis, with >1 million deaths due to resistant bacterial infections each year. Pseudomonas aeruginosa, in particular, remains a serious problem with limited solutions due to complex resistance mechanisms that now lead to more than 32,000 multidrug-resistant (MDR) infections and over 2,000 deaths annually. While the emergence of resistant bacteria has become concerningly common, identification of useful new drug classes has been limited over the past 40+ years. We found that a potential novel therapeutic, the peptide-mimetic TM5, is effective at killing P. aeruginosa and displays sufficiently low toxicity for mammalian cells to allow for use in treatment of infections. Interestingly, TM5 kills P. aeruginosa more rapidly than traditional antibiotics, within 30-60 minutes in vitro , and is effective against a range of clinical isolates. In vivo , TM5 significantly reduced bacterial load in the lungs within 24 hours compared to untreated mice and demonstrated few adverse effects. Taken together, these observations suggest that TM5 shows promise as an alternative therapy for MDR P. aeruginosa respiratory infections.

Bacillus Calmette-Guérin vaccination as defense against SARS-CoV-2 (BADAS): a randomized controlled trial to protect healthcare workers in the USA by enhanced trained immune responses.

BACKGROUND: A large epidemic, such as that observed with SARS-CoV-2, seriously challenges available hospital capacity, and this would be augmented by infection of healthcare workers (HCW). Bacillus Calmette-Guérin (BCG) is a vaccine against tuberculosis, with protective non-specific effects against other respiratory tract infections in vitro and in vivo. Preliminary analyses suggest that regions of the world with existing BCG vaccination programs have lower incidence and mortality from COVID-19. We hypothesize that BCG vaccination can reduce SARS-CoV-2 infection and disease severity. METHODS: This will be a placebo-controlled adaptive multi-center randomized controlled trial. A total of 1800 individuals considered to be at high risk, including those with comorbidities (hypertension, diabetes, obesity, reactive airway disease, smokers), racial and ethnic minorities, elderly, teachers, police, restaurant wait-staff, delivery personnel, health care workers who are defined as personnel working in a healthcare setting, at a hospital, medical center or clinic (veterinary, dental, ophthalmology), and first responders (paramedics, firefighters, or law enforcement), will be randomly assigned to two treatment groups. The treatment groups will receive intradermal administration of BCG vaccine or placebo (saline) with groups at a 1:1 ratio. Individuals will be tracked for evidence of SARS-CoV-2 infection and severity as well as obtaining whole blood to track immunological markers, and a sub-study will include cognitive function and brain imaging. The majority of individuals will be followed for 6 months, with an option to extend for another 6 months, and the cognitive sub-study duration is 2 years. We will plot Kaplan-Meier curves that will be plotted comparing groups and hazard ratios and p-values reported using Cox proportional hazard models. DISCUSSION: It is expected this trial will allow evaluation of the effects of BCG vaccination at a population level in high-risk healthcare individuals through a mitigated clinical course of SARS-CoV-2 infection and inform policy making during the ongoing epidemic. TRIAL REGISTRATION: ClinicalTrials.gov NCT04348370. Registered on April 16, 2020.

Metamnemonic predictions of lineup identification.

After a crime is committed, investigators may query witnesses about whether they believe they will be to identify the perpetrator. However, we know little about how such metacognitive judgments are related to performance on a subsequent lineup identification task. The extant research has found the strength of this relationship to be small or nonexistent, which conflicts with the large body of literature indicating a moderate relationship between predictions and performance on memory tasks. In Studies 1-3, we induce variation in encoding quality by having participants watch a mock crime video with either low, medium, or high exposure quality, and then assess their future lineup performance. Calibration analysis revealed that assessments of future lineup performance were predictive of identification accuracy. This relationship was driven primarily by poor performance following low assessments. Studies 4 and 5 showed that these predictions are not based on a witness's evaluation of their encoding experience, nor on a contemporaneous assessment of memory strength. These results reinforce the argument that variation in memory quality is needed to obtain reliable relationships between predictions and performance. An unexpected finding is that witnesses who made a prediction shortly after encoding evinced superior memory compared to those who made a prediction later.

Strategic regulation of memory in dsyphoria: a quantity-accuracy profile analysis.

The mechanisms underlying a tendency among individuals with depression to report personal episodic memories with low specificity remain to be understood. We assessed a sample of undergraduate students with dysphoria to determine whether depression relates to a broader dysregulation of balancing accuracy and informativeness during memory reports. Specifically, we investigated metamnemonic processes using a quantity-accuracy profile approach. Recall involved three phases with increasing allowance for more general, or coarse-grained, responses: (a) forced-precise responding, requiring high precision; (b) free-choice report with high and low penalty incentives on accuracy; (c) a lexical description phase. Individuals with and without dysphoria were largely indistinguishable across indices of retrieval, monitoring, and control aspects of metamemory. The results indicate intact metacognitive processing in young individuals with dysphoria and provide no support for the view that impaired metacognitive control underlies either memory deficits or bias in memory reports that accompany dysphoria.

MEMCONS: How Contemporaneous Note-Taking Shapes Memory for Conversation.

Written memoranda of conversations, or memcons, provide a near-contemporaneous record of what was said in conversation, and offer important insights into the activities of high-profile individuals. We assess the impact of writing a memcon on memory for conversation. Pairs of participants engaged in conversation and were asked to recall the contents of that conversation 1 week later. One participant in each pair memorialized the content of the interaction in a memcon shortly after the conversation. Participants who generated memcons recalled more details of the conversations than participants who did not, but the content of recall was equally and largely accurate for both participants. Remarkably, only 4.7% of the details of the conversation were recalled by both of the partners after a week delay. Contemporaneous note-taking appears to enhance memory for conversation by increasing the amount of information remembered but not the accuracy of that information. These findings have implications for evaluating the testimony of participants on conversations with major political or legal ramifications.

Structures of chloramphenicol acetyltransferase III and Escherichia coli ß-ketoacylsynthase III co-crystallized with partially hydrolysed acetyl-oxa(dethia)CoA.

Acetyl coenzyme A (acetyl-CoA) is a reactive metabolite that nonproductively hydrolyzes in a number of enzyme active sites in the crystallization time frame. In order to elucidate the enzyme-acetyl-CoA interactions leading to catalysis, acetyl-CoA substrate analogs are needed. One possible analog for use in structural studies is acetyl-oxa(dethia)CoA (AcOCoA), in which the thioester S atom of CoA is replaced by an O atom. Here, structures of chloramphenicol acetyltransferase III (CATIII) and Escherichia coli ketoacylsynthase III (FabH) from crystals grown in the presence of partially hydrolyzed AcOCoA and the respective nucleophile are presented. Based on the structures, the behavior of AcOCoA differs between the enzymes, with FabH reacting with AcOCoA and CATIII being unreactive. The structure of CATIII reveals insight into the catalytic mechanism, with one active site of the trimer having relatively clear electron density for AcOCoA and chloramphenicol and the other active sites having weaker density for AcOCoA. One FabH structure contains a hydrolyzed AcOCoA product oxa(dethia)CoA (OCoA), while the other FabH structure contains an acyl-enzyme intermediate with OCoA. Together, these structures provide preliminary insight into the use of AcOCoA for enzyme structure-function studies with different nucleophiles.

Incorporating Functional Response Time Effects into a Signal Detection Theory Model.

Signal detection theory (SDT; Tanner & Swets in Psychological Review 61:401-409, 1954) is a dominant modeling framework used for evaluating the accuracy of diagnostic systems that seek to distinguish signal from noise in psychology. Although the use of response time data in psychometric models has increased in recent years, the incorporation of response time data into SDT models remains a relatively underexplored approach to distinguishing signal from noise. Functional response time effects are hypothesized in SDT models, based on findings from other related psychometric models with response time data. In this study, an SDT model is extended to incorporate functional response time effects using smooth functions and to include all sources of variability in SDT model parameters across trials, participants, and items in the experimental data. The extended SDT model with smooth functions is formulated as a generalized linear mixed-effects model and implemented in the gamm4 R package. The extended model is illustrated using recognition memory data to understand how conversational language is remembered. Accuracy of parameter estimates and the importance of modeling variability in detecting the experimental condition effects and functional response time effects are shown in conditions similar to the empirical data set via a simulation study. In addition, the type 1 error rate of the test for a smooth function of response time is evaluated.

Social complexity, life-history and lineage influence the molecular basis of castes in vespid wasps.

A key mechanistic hypothesis for the evolution of division of labour in social insects is that a shared set of genes co-opted from a common solitary ancestral ground plan (a genetic toolkit for sociality) regulates caste differentiation across levels of social complexity. Using brain transcriptome data from nine species of vespid wasps, we test for overlap in differentially expressed caste genes and use machine learning models to predict castes using different gene sets. We find evidence of a shared genetic toolkit across species representing different levels of social complexity. We also find evidence of additional fine-scale differences in predictive gene sets, functional enrichment and rates of gene evolution that are related to level of social complexity, lineage and of colony founding. These results suggest that the concept of a shared genetic toolkit for sociality may be too simplistic to fully describe the process of the major transition to sociality.

Lower memory specificity in individuals with dysphoria is not specific to autobiographical memory.

BACKGROUND: A core cognitive attribute of depression is lower specificity in the expression of autobiographical memories. Despite interventions targeting memory specificity in depression, its underlying mechanisms are not yet fully understood. Depression also relates to poorer memory for episodic details; here we examine whether reduced specificity might simply reflect broader episodic memory deficits and weakened memory traces with the passage of time. METHODS: Undergraduate students with and without symptoms of depression completed the Autobiographical Interview and prose-reading episodic memory tasks to assess both same-day and delayed memory. RESULTS: Dysphoria and nondysphoria groups performed similarly on the tasks of immediate episodic and autobiographical memory; notably, the dysphoria group did not display evidence of lower specificity at this time point. After a delay, however, both groups demonstrated less specific memory responses on both memory tasks, and these declines were more pronounced in the group with dysphoria. That is, after a delay, individuals high in dysphoria showed a greater decrease in the quantity of specific event details reported on both the episodic and the autobiographical memory task. Additional analyses incorporating other clinical and cognitive measures indicated that these relations are largely unique to symptoms of depression. LIMITATIONS: The sample comprised mostly female students; the study should be replicated with more diverse samples. CONCLUSIONS: These findings support the claim that lower memory specificity is not peculiar to autobiographical memory, but rather, reflects impoverished memory more generally. This is an important consideration for theories and remedial strategies targeting memory specificity.

Activity of Fatty Acid Biosynthesis Initiating Ketosynthase FabH with Acetyl/Malonyl-oxa/aza(dethia)CoAs.

Fatty acid and polyketide biosynthetic enzymes exploit the reactivity of acyl- and malonyl-thioesters for catalysis. A prime example is FabH, which initiates fatty acid biosynthesis in many bacteria and plants. FabH performs an acyltransferase reaction with acetyl-CoA to generate an acetyl-S-FabH acyl-enzyme intermediate and subsequent decarboxylative Claisen-condensation with a malonyl-thioester carried by an acyl carrier protein (ACP). We envision that crystal structures of FabH with substrate analogues can provide insight into the conformational changes and enzyme/substrate interactions underpinning the distinct reactions. Here, we synthesize acetyl/malonyl-CoA analogues with esters or amides in place of the thioester and characterize their stability and behavior as Escherichia coli FabH substrates or inhibitors to inform structural studies. We also characterize the analogues with mutant FabH C112Q that mimics the acyl-enzyme intermediate allowing dissection of the decarboxylation reaction. The acetyl- and malonyl-oxa(dethia)CoA analogues undergo extremely slow hydrolysis in the presence of FabH or the C112Q mutant. Decarboxylation of malonyl-oxa(dethia)CoA by FabH or C112Q mutant was not detected. The amide analogues were completely stable to enzyme activity. In enzyme assays with acetyl-CoA and malonyl-CoA (rather than malonyl-ACP) as substrates, acetyl-oxa(dethia)CoA is surprisingly slightly activating, while acetyl-aza(dethia)CoA is a moderate inhibitor. The malonyl-oxa/aza(dethia)CoAs are inhibitors with Ki's near the Km of malonyl-CoA. For comparison, we determine the FabH catalyzed decomposition rates for acetyl/malonyl-CoA, revealing some fundamental catalytic traits of FabH, including hysteresis for malonyl-CoA decarboxylation. The stability and inhibitory properties of the substrate analogues make them promising for structure-function studies to reveal fatty acid and polyketide enzyme/substrate interactions.

scikit-matter : A Suite of Generalisable Machine Learning Methods Born out of Chemistry and Materials Science.

Easy-to-use libraries such as scikit-learn have accelerated the adoption and application of machine learning (ML) workflows and data-driven methods. While many of the algorithms implemented in these libraries originated in specific scientific fields, they have gained in popularity in part because of their generalisability across multiple domains. Over the past two decades, researchers in the chemical and materials science community have put forward general-purpose machine learning methods. The deployment of these methods into workflows of other domains, however, is often burdensome due to the entanglement with domainspecific functionalities. We present the python library scikit-matter that targets domain-agnostic implementations of methods developed in the computational chemical and materials science community, following the scikit-learn API and coding guidelines to promote usability and interoperability with existing workflows.

Recent Developments in Drug Delivery for Treatment of Tuberculosis by Targeting Macrophages.

Tuberculosis (TB) is among the greatest public health and safety concerns in the 21st century, Mycobacterium tuberculosis, which causes TB, infects alveolar macrophages and uses these cells as one of its primary sites of replication. The current TB treatment regimen, which consist of chemotherapy involving a combination of 3-4 antimicrobials for a duration of 6-12 months, is marked with significant side effects, toxicity, and poor compliance. Targeted drug delivery offers a strategy that could overcome many of the problems of current TB treatment by specifically targeting infected macrophages. Recent advances in nanotechnology and material science have opened an avenue to explore drug carriers that actively and passively target macrophages. This approach can increase the drug penetration into macrophages by using ligands on the nanocarrier that interact with specific receptors for macrophages. This review encompasses the recent development of drug carriers specifically targeting macrophages actively and passively. Future directions and challenges associated with development of effective TB treatment is also discussed.

Comparing models of learning and relearning in large-scale cognitive training data sets.

Practice in real-world settings exhibits many idiosyncracies of scheduling and duration that can only be roughly approximated by laboratory research. Here we investigate 39,157 individuals' performance on two cognitive games on the Lumosity platform over a span of 5 years. The large-scale nature of the data allows us to observe highly varied lengths of uncontrolled interruptions to practice and offers a unique view of learning in naturalistic settings. We enlist a suite of models that grow in the complexity of the mechanisms they postulate and conclude that long-term naturalistic learning is best described with a combination of long-term skill and task-set preparedness. We focus additionally on the nature and speed of relearning after breaks in practice and conclude that those components must operate interactively to produce the rapid relearning that is evident even at exceptionally long delays (over 2 years). Naturalistic learning over long time spans provides a strong test for the robustness of theoretical accounts of learning, and should be more broadly used in the learning sciences.

Stabilization of Tuberculosis Reporter Enzyme Fluorescence (REFtb) Diagnostic Reagents for Use at the Point of Care.

Tuberculosis is one of the most frequent causes of death in humans worldwide. One of the primary reasons tuberculosis remains a public health threat is that diagnosis can take weeks to months, is often not very sensitive and cannot be accomplished in many remote environments. A rapid, sensitive and inexpensive point-of-care (POC) diagnostic would have a major impact on tuberculosis eradication efforts. The tuberculosis diagnostic system REFtb is based on specific detection of the constitutively expressed ß-lactamase (BlaC) in Mycobacterium tuberculosis using a custom fluorogenic substrate designated as CDG-3. REFtb has potential as a diagnostic for tuberculosis that could be very inexpensive (

Efficacy of Cathelicidin-Mimetic Antimicrobial Peptoids against Staphylococcus aureus.

Staphylococcus aureus is one of the most common pathogens associated with infection in wounds. The current standard of care uses a combination of disinfection and drainage followed by conventional antibiotics such as methicillin. Methicillin and vancomycin resistance has rendered these treatments ineffective, often causing the reemergence of infection. This study examines the use of antimicrobial peptoids (sequence-specific poly-N-substituted glycines) designed to mimic naturally occurring cationic, amphipathic host defense peptides, as an alternative to conventional antibiotics. These peptoids also show efficient and fast (<30 min) killing of methicillin-susceptible S. aureus (MSSA) and methicillin-resistant S. aureus (MRSA) at low micromolar concentrations without having apparent cytotoxic side effects in vivo. Additionally, these novel peptoids show excellent efficacy against biofilm formation and detachment for both MSSA and MRSA. In comparison, conventional antibiotics were unable to detach or prevent formation of biofilms. One cationic 12mer, Peptoid 1, shows great promise, as it could prevent formation of and detach biofilms at concentrations as low as 1.6 µM. The use of a bioluminescent S. aureus murine incision wound model demonstrated clearance of infection in peptoid-treated mice within 8 days, conveying another advantage these peptoids have over conventional antibiotics. These results provide clear evidence of the potential for antimicrobial peptoids for the treatment of S. aureus wound infections. IMPORTANCE Staphylococcus aureus resistance is a consistent problem with a large impact on the health care system. Infections with resistant S. aureus can cause serious adverse effects and can result in death. These antimicrobial peptoids show efficient killing of bacteria both as a biofilm and as free bacteria, often doing so in less than 30 min. As such, these antimicrobials have the potential to alleviate the burden that Staphylococcus infections have on the health care system and cause better outcomes for infected patients.

Substrate Enolate Intermediate and Mimic Captured in the Active Site of Streptomyces coelicolor Methylmalonyl-CoA Epimerase.

Methylmalonyl-CoA epimerase (MMCE) is proposed to use general acid-base catalysis, but the proposed catalytic glutamic acids are highly asymmetrical in the active site unlike many other racemases. To gain insight into the puzzling relationships between catalytic mechanism, structure, and substrate preference, we solved Streptomyces coelicolor MMCE structures with substrate or 2-nitropropionyl-CoA, an intermediate/transition state analogue. Both ligand bound structures have a planar methylmalonate/2-nitropropionyl moiety indicating a deprotonated C2 with ≥4 Šdistances to either catalytic acid. Both glutamates interact with the carboxylate/nitro group, either directly or through other residues. This suggests the proposed catalytic acids sequentially catalyze proton shifts between C2 and carboxylate of the substrate with an enolate intermediate. In addition, our structures provide a platform to design mutations for expanding substrate scope to support combinatorial biosynthesis.

Memory Fidelity Reveals Qualitative Changes in Interactions Between Items in Visual Working Memory.

Memory for objects in a display sometimes reveals attraction-the objects are remembered as more similar to one another than they actually were-and sometimes reveals repulsion-the objects are remembered as more different from one another. The conditions that lead to these opposing memory biases are poorly understood; there is no theoretical framework that explains these contrasting dynamics. In three experiments (each N = 30 adults), we demonstrate that memory fidelity provides a unifying dimension that accommodates the existence of both types of visual working memory interactions. We show that either attraction or repulsion can arise simply as a function of manipulations of memory fidelity. We also demonstrate that subjective ratings of fidelity predict the presence of attraction or repulsion on a trial-by-trial basis. We discuss how these results bear on computational models of visual working memory and contextualize these results within the literature of attraction and repulsion effects in long-term memory and perception.