Single-Cell Analyses Inform Mechanisms of Myeloid-Targeted Therapies in Colon Cancer.

Single-cell RNA sequencing (scRNA-seq) is a powerful tool for defining cellular diversity in tumors, but its application toward dissecting mechanisms underlying immune-modulating therapies is scarce. We performed scRNA-seq analyses on immune and stromal populations from colorectal cancer patients, identifying specific macrophage and conventional dendritic cell (cDC) subsets as key mediators of cellular cross-talk in the tumor microenvironment. Defining comparable myeloid populations in mouse tumors enabled characterization of their response to myeloid-targeted immunotherapy. Treatment with anti-CSF1R preferentially depleted macrophages with an inflammatory signature but spared macrophage populations that in mouse and human expresses pro-angiogenic/tumorigenic genes. Treatment with a CD40 agonist antibody preferentially activated a cDC population and increased Bhlhe40+ Th1-like cells and CD8+ memory T cells. Our comprehensive analysis of key myeloid subsets in human and mouse identifies critical cellular interactions regulating tumor immunity and defines mechanisms underlying myeloid-targeted immunotherapies currently undergoing clinical testing.

Human Anti-tumor Immunity: Insights from Immunotherapy Clinical Trials.

Therapeutics that target the T cell inhibitory checkpoint proteins CTLA-4 and PD(L)1 are efficacious across a broad range of cancers, resulting in reductions in tumor burden and increased long-term survival in subsets of patients. The significant and wide-ranging effects of these immunotherapies have prompted the clinical investigation of additional therapies that modulate anti-tumor immunity through effects on T cells, myeloid cells, and other cell types within the tumor microenvironment. The clinical activity of these newer investigational therapies has been mixed, with some therapeutics showing promise but others not exhibiting appreciable efficacy. In this review, we summarize the results of select recent clinical studies of cancer immunotherapies beyond anti-CTLA-4 and anti-PD(L)1 and discuss how these results are providing new insights into the regulation of human anti-tumor immunity.

The Black Lives Matter movement mitigates bias against racial minority actors.

Watching movies is among the most popular entertainment and cultural activities. How do viewers react when a movie sequel increases racial minority actors in the main cast ("minority increase")? On the one hand, such sequels may receive better evaluations if viewers appreciate racially inclusive casting for its novel elements (the value-in-diversity perspective) and moral appeal (the fairness perspective on diversity). On the other hand, discrimination research suggests that if viewers harbor biases against racial minorities, sequels with minority increase may receive worse evaluations. To examine these competing possibilities, we analyze a unique panel dataset of movie series released from 1998 to 2021 and conduct text analysis of 312,457 reviews of these movies. Consistent with discrimination research, we find that movies with minority increase receive lower ratings and more toxic reviews. Importantly, these effects weaken after the advent of the Black Lives Matter (BLM) movement, especially when the movement's intensity is high. These results are reliable across various robustness checks (e.g., propensity score matching, random implementation test). We conceptually replicate the bias mitigation effect of BLM in a preregistered experiment: Heightening the salience of BLM increases White individuals' acceptance of racial minority increase in a movie sequel. This research demonstrates the power of social movements in fostering diversity, equality, and inclusion.

The genetic landscape of substance use disorders.

Substance use disorders represent a significant public health concern with considerable socioeconomic implications worldwide. Twin and family-based studies have long established a heritable component underlying these disorders. In recent years, genome-wide association studies of large, broadly phenotyped samples have identified regions of the genome that harbour genetic risk variants associated with substance use disorders. These regions have enabled the discovery of putative causal genes and improved our understanding of genetic relationships among substance use disorders and other traits. Furthermore, the integration of these data with clinical information has yielded promising insights into how individuals respond to medications, allowing for the development of personalized treatment approaches based on an individual's genetic profile. This review article provides an overview of recent advances in the genetics of substance use disorders and demonstrates how genetic data may be used to reduce the burden of disease and improve public health outcomes.

The surprising underperformance of East Asians in US law and business schools: The liability of low assertiveness and the ameliorative potential of online classrooms.

SignificanceTo date, researchers and practitioners have focused on the academic challenges of underrepresented ethnic groups in the United States. In comparison, Asians have received limited attention, as they are commonly assumed to excel across all educational stages. Six large studies challenge this assumption by revealing that East Asians (but not South Asians) underperform in US law schools and business schools. This is not because East Asians are less academically motivated or less proficient in English but because their low verbal assertiveness is culturally incongruent with the assertiveness prized by US law and business schools. Online classes (via Zoom) mitigated East Asians' underperformance in courses emphasizing assertiveness and class participation. Educators should reexamine pedagogical practices to create a culturally inclusive classroom.

Masks as a moral symbol: Masks reduce wearers' deviant behavior in China during COVID-19.

Since the outbreak of COVID-19, mask wearing has become a global phenomenon. How do masks influence wearers' behavior in everyday life? We examine the effect of masks on wearers' deviant behavior in China, where mask wearing is mostly a public-health issue rather than a political issue. Drawing on behavioral ethics research, we test two competing hypotheses: (a) masks disinhibit wearers' deviant behavior by increasing their sense of anonymity and (b) masks are a moral symbol that reduces wearers' deviant behavior by heightening their moral awareness. The latter hypothesis was consistently supported by 10 studies (including direct replications) using mixed methods (e.g., traffic camera recording analysis, observational field studies, experiments, and natural field experiment) and different measures of deviant behavior (e.g., running a red light, bike parking in no-parking zones, cheating for money, and deviant behavior in the library). Our research (n = 68,243) is among the first to uncover the psychological and behavioral consequences of mask wearing beyond its health benefits.

Phenome-wide screening of the putative causal determinants of depression using genetic data.

Depression is one of the most common mental health disorders and one of the top causes of disability throughout the world. The present study sought to identify putative causal associations between depression and hundreds of complex human traits through a genome-wide screening of genetic data and a hypothesis-free approach. We leveraged genome-wide association studies summary statistics for depression and 1504 complex traits and investigated potential causal relationships using the latent causal variable method. We identified 559 traits genetically correlated with depression risk at FDR < 5%. Of these, 46 were putative causal genetic determinants of depression, including lifestyle factors, diseases of the nervous system, respiratory disorders, diseases of the musculoskeletal system, traits related to the health of the gastrointestinal system, obesity, vitamin D levels and the use of prescription medications, among others. No phenotypes were identified as potential outcomes of depression. Our results suggest that genetic liability to multiple complex traits may contribute to a higher risk for depression. In particular, we show a putative causal genetic effect of pain, obesity and inflammation on depression. These findings provide novel insights into the potential causal determinants of depression and should be interpreted as testable hypotheses for future studies to confirm, which may facilitate the design of new prevention strategies to reduce depression's burden.

IgE⁺ memory B cells and plasma cells generated through a germinal-center pathway.

Immunoglobulin E (IgE) antibodies are pathogenic in asthma and allergic diseases, but the in vivo biology of IgE-producing (IgE(+)) cells is poorly understood. A model of the differentiation of IgE(+) B cells proposes that IgE(+) cells develop through a germinal-center IgG1(+) intermediate and that IgE memory resides in the compartment of IgG1(+) memory B cells. Here we have used a reporter mouse expressing green fluorescent protein associated with membrane IgE transcripts (IgE-GFP) to assess in vivo IgE responses. In contrast to the IgG1-centered model of IgE switching and memory, we found that IgE(+) cells developed through a germinal-center IgE(+) intermediate to form IgE(+) memory B cells and plasma cells. Our studies delineate a new model for the in vivo biology of IgE switching and memory.

Mucosal-associated invariant T cells modulate innate immune cells and inhibit colon cancer growth.

Mucosal-associated invariant T (MAIT) cells are innate-like T cells that can be activated by microbial antigens and cytokines and are abundant in mucosal tissues including the colon. MAIT cells have cytotoxic and pro-inflammatory functions and have potentials for use as adoptive cell therapy. However, studies into their anti-cancer activity, including their role in colon cancer, are limited. Using an animal model of colon cancer, we showed that peritumoral injection of in vivo-expanded MAIT cells into RAG1-/- mice with MC38-derived tumours inhibits tumour growth compared to control. Multiplex cytokine analyses showed that tumours from the MAIT cell-treated group have higher expression of markers for eosinophil-activating cytokines, suggesting a potential association between eosinophil recruitment and tumour inhibition. In a human peripheral leukocyte co-culture model, we showed that leukocytes stimulated with MAIT ligand showed an increase in eotaxin-1 production and activation of eosinophils, associated with increased cancer cell killing. In conclusion, we showed that MAIT cells have a protective role in a murine colon cancer model, associated with modulation of the immune response to cancer, potentially involving eosinophil-associated mechanisms. Our results highlight the potential of MAIT cells for non-donor restricted colon cancer immunotherapy.

HFIP in Organic Synthesis.

1,1,1,3,3,3-Hexafluoroisopropanol (HFIP) is a polar, strongly hydrogen bond-donating solvent that has found numerous uses in organic synthesis due to its ability to stabilize ionic species, transfer protons, and engage in a range of other intermolecular interactions. The use of this solvent has exponentially increased in the past decade and has become a solvent of choice in some areas, such as C-H functionalization chemistry. In this review, following a brief history of HFIP in organic synthesis and an overview of its physical properties, literature examples of organic reactions using HFIP as a solvent or an additive are presented, emphasizing the effect of solvent of each reaction.

A Socioecological-Genetic Framework of Culture and Personality: Their Roots, Trends, and Interplay.

Culture and personality are two central topics in psychology. Individuals are culturally influenced influencers of culture, yet the research linking culture and personality has been limited and fragmentary. We integrate the literatures on culture and personality with recent advances in socioecology and genetics to formulate the Socioecological-Genetic Framework of Culture and Personality. Our framework not only delineates the mutual constitution of culture and personality but also sheds light on (a) the roots of culture and personality, (b) how socioecological changes partly explain temporal trends in culture and personality, and (c) how genes and culture/socioecology interact to influence personality (i.e., nature × nurture interactions). By spotlighting the roles of socioecology and genetics, our integrative framework advances the understanding of culture and personality.

Collectivism predicts mask use during COVID-19.

Since its outbreak, COVID-19 has impacted world regions differentially. Whereas some regions still record tens of thousands of new infections daily, other regions have contained the virus. What explains these striking regional differences? We advance a cultural psychological perspective on mask usage, a precautionary measure vital for curbing the pandemic. Four large-scale studies provide evidence that collectivism (versus individualism) positively predicts mask usage-both within the United States and across the world. Analyzing a dataset of all 3,141 counties of the 50 US states (based on 248,941 individuals), Study 1a revealed that mask usage was higher in more collectivistic US states. Study 1b replicated this finding in another dataset of 16,737 individuals in the 50 US states. Analyzing a dataset of 367,109 individuals in 29 countries, Study 2 revealed that mask usage was higher in more collectivistic countries. Study 3 replicated this finding in a dataset of 277,219 Facebook users in 67 countries. The link between collectivism and mask usage was robust to a host of control variables, including cultural tightness-looseness, political affiliation, demographics, population density, socioeconomic indicators, universal health coverage, government response stringency, and time. Our research suggests that culture fundamentally shapes how people respond to crises like the COVID-19 pandemic. Understanding cultural differences not only provides insight into the current pandemic, but also helps the world prepare for future crises.

Complex cutaneous leishmaniasis in a pediatric patient.

Cutaneous leishmaniasis (CL), a parasitic infection caused by Leishmania protozoa and transmitted by sandfly bites, can be classified into Old World and New World subtypes. We report a case of a 2-year-old female who developed complex CL after travel to Panama. Ultimately, successful treatment required two rounds of liposomal amphotericin B. We report this case for its challenging clinical course and management.

Survival and Success Rates of Endodontically Treated Teeth Restored with Full Veneer Crowns or Full Cuspal Coverage onlays: A Systematic Review.

INTRODUCTION: The aim of this paper is to compare the survival and success rates of endodontically treated posterior teeth restored with full veneer crowns or full cuspal coverage onlays in vivo. METHODS: A literature search using PubMed, Medline and Embase via Ovid, and The Cochrane Library retrieved English and non-English language articles from 1946 to April 2022. Electronic searches were supplemented with the use of forward citation chaining via Google Scholar. RESULTS: A total of eleven studies met all predetermined search criteria. Data were extracted and tabulated. Survival rates for onlays ranged from 95% to 100% at two years and 90.7% to 100% at three years with success rates ranging from 86.6% - 96.6% at two years and 86.6% to 96% at three years. Survival results for full veneer crowns were reported at 87.8% at over two years, 95.1% at three years, and 84% - 97.73% at five to ten years. Success rates have been reported at 91.11% - 92.64% at five years and 60% at six years. CONCLUSIONS: The data suggest that the use of onlays instead of full veneer crowns in the restoration of endodontically treated posterior teeth is favourable in the short to midterm.

New proposal of viral genome representation applied in the classification of SARS-CoV-2 with deep learning.

BACKGROUND: In December 2019, the first case of COVID-19 was described in Wuhan, China, and by July 2022, there were already 540 million confirmed cases. Due to the rapid spread of the virus, the scientific community has made efforts to develop techniques for the viral classification of SARS-CoV-2. RESULTS: In this context, we developed a new proposal for gene sequence representation with Genomic Signal Processing techniques for the work presented in this paper. First, we applied the mapping approach to samples of six viral species of the Coronaviridae family, which belongs SARS-CoV-2 Virus. We then used the sequence downsized obtained by the method proposed in a deep learning architecture for viral classification, achieving an accuracy of 98.35%, 99.08%, and 99.69% for the 64, 128, and 256 sizes of the viral signatures, respectively, and obtaining 99.95% precision for the vectors with size 256. CONCLUSIONS: The classification results obtained, in comparison to the results produced using other state-of-the-art representation techniques, demonstrate that the proposed mapping can provide a satisfactory performance result with low computational memory and processing time costs.

Unveiling the peptidome diversity of Lachesismuta snake venom: Discovery of novel fragments of metalloproteinase, l-amino acid oxidase, and bradykinin potentiating peptides.

Snake venoms are known to be major sources of peptides with different pharmacological properties. In this study, we comprehensively explored the venom peptidomes of three specimens of Lachesismuta, the largest venomous snake in South America, using mass spectrometry techniques. The analysis revealed 19 main chromatographic peaks common to all specimens. A total of 151 peptides were identified, including 69 from a metalloproteinase, 58 from the BPP-CNP precursor, and 24 from a l-amino acid oxidase. To our knowledge, 126 of these peptides were reported for the first time in this work, including a new SVMP-derived peptide fragment, Lm-10a. Our findings highlight the dynamic nature of toxin maturation in snake venoms, driven by proteolytic processing, post-translational modifications, and cryptide formation.

Brief report: STING expressed in tumor and non-tumor compartments has distinct roles in regulating anti-tumor immunity.

Type I interferon-mediated activation of immune cells can facilitate the generation of productive tumor antigen-specific T cell responses in solid tumors. The cGAS/STING DNA sensing pathway is a critical upstream mediator of type I interferon production and is an important regulator of anti-tumor immunity. Numerous STING pathway agonists are now being tested in clinical trials, but the effectiveness of this approach is not yet clear and a better understanding of the relative importance of this pathway in various tumor settings is needed. We have evaluated syngeneic tumor models with different baseline inflammatory states to determine the contributions of STING activity in both tumor and non-tumor cellular compartments to anti-tumor immune responses. We find that productive anti-tumor immune responses in the poorly immunogenic B16F10 model show a strong dependence on STING expression in non-tumor cells. In the immunogenic MC38 model, constitutive STING activation in tumor cells can partially bypass the requirement for STING-dependent activity from immune cells. Our findings reveal multiple, context-dependent roles for STING activity in the regulation of anti-tumor immunity and the response to immunotherapy. In preclinical models where STING is basally active, checkpoint inhibition is more likely to have a therapeutic effect and removal of STING signaling from either the tumor or the non-tumor compartment has a minimal effect. Removal of STING signaling in both, however, diminishes the efficacy derived from checkpoint therapy. Further work is needed to understand the heterogeneity of STING signaling in patients, both in tumor cells and the tumor microenvironment, and the best means of harnessing this pathway to generate anti-tumor immunity and improve therapeutic outcomes.

Tuning of antigen sensitivity by T cell receptor-dependent negative feedback controls T cell effector function in inflamed tissues.

Activated T cells must mediate effector responses sufficiently to clear pathogens while avoiding excessive tissue damage. Here we have combined dynamic intravital microscopy with ex vivo assessments of T cell cytokine responses to generate a detailed spatiotemporal picture of CD4(+) T cell effector regulation in the skin. In response to antigen, effector T cells arrested transiently on antigen-presenting cells, briefly producing cytokine and then resuming migration. Antigen recognition led to upregulation of the programmed death-1 (PD-1) glycoprotein by T cells and blocking its canonical ligand, programmed death-ligand 1 (PD-L1), lengthened the duration of migration arrest and cytokine production, showing that PD-1 interaction with PD-L1 is a major negative feedback regulator of antigen responsiveness. We speculate that the immune system employs T cell recruitment, transient activation, and rapid desensitization to allow the T cell response to rapidly adjust to changes in antigen presentation and minimize collateral injury to the host.

Cardiorespiratory signature of neonatal sepsis: development and validation of prediction models in 3 NICUs.

BACKGROUND: Heart rate characteristics aid early detection of late-onset sepsis (LOS), but respiratory data contain additional signatures of illness due to infection. Predictive models using cardiorespiratory data may improve early sepsis detection. We hypothesized that heart rate (HR) and oxygenation (SpO2) data contain signatures that improve sepsis risk prediction over HR or demographics alone. METHODS: We analyzed cardiorespiratory data from very low birth weight (VLBW, <1500 g) infants admitted to three NICUs. We developed and externally validated four machine learning models to predict LOS using features calculated every 10 m: mean, standard deviation, skewness, kurtosis of HR and SpO2, and cross-correlation. We compared feature importance, discrimination, calibration, and dynamic prediction across models and cohorts. We built models of demographics and HR or SpO2 features alone for comparison with HR-SpO2 models. RESULTS: Performance, feature importance, and calibration were similar among modeling methods. All models had favorable external validation performance. The HR-SpO2 model performed better than models using either HR or SpO2 alone. Demographics improved the discrimination of all physiologic data models but dampened dynamic performance. CONCLUSIONS: Cardiorespiratory signatures detect LOS in VLBW infants at 3 NICUs. Demographics risk-stratify, but predictive modeling with both HR and SpO2 features provides the best dynamic risk prediction. IMPACT: Heart rate characteristics aid early detection of late-onset sepsis, but respiratory data contain signatures of illness due to infection. Predictive models using both heart rate and respiratory data may improve early sepsis detection. A cardiorespiratory early warning score, analyzing heart rate from electrocardiogram or pulse oximetry with SpO2, predicts late-onset sepsis within 24 h across multiple NICUs and detects sepsis better than heart rate characteristics or demographics alone. Demographics risk-stratify, but predictive modeling with both HR and SpO2 features provides the best dynamic risk prediction. The results increase understanding of physiologic signatures of neonatal sepsis.

Renal Mass Imaging with MRI Clear Cell Likelihood Score: A User's Guide.

Small solid renal masses (SRMs) are frequently detected at imaging. Nearly 20% are benign, making careful evaluation with MRI an important consideration before deciding on management. Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma subtype with potentially aggressive behavior. Thus, confident identification of ccRCC imaging features is a critical task for the radiologist. Imaging features distinguishing ccRCC from other benign and malignant renal masses are based on major features (T2 signal intensity, corticomedullary phase enhancement, and the presence of microscopic fat) and ancillary features (segmental enhancement inversion, arterial-to-delayed enhancement ratio, and diffusion restriction). The clear cell likelihood score (ccLS) system was recently devised to provide a standardized framework for categorizing SRMs, offering a Likert score of the likelihood of ccRCC ranging from 1 (very unlikely) to 5 (very likely). Alternative diagnoses based on imaging appearance are also suggested by the algorithm. Furthermore, the ccLS system aims to stratify which patients may or may not benefit from biopsy. The authors use case examples to guide the reader through the evaluation of major and ancillary MRI features of the ccLS algorithm for assigning a likelihood score to an SRM. The authors also discuss patient selection, imaging parameters, pitfalls, and areas for future development. The goal is for radiologists to be better equipped to guide management and improve shared decision making between the patient and treating physician. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Pedrosa in this issue.