Mycoplasma gallisepticum (MG) can cause chronic respiratory disease (CRD) in chickens. While several studies have reported the inflammatory functions of microRNAs during MG infection, the mechanism by which exosomal miRNAs regulate MG-induced inflammation remains to be elucidated. The expression of exosome-microRNA derived from MG-infected chicken type II pneumocytes (CP-II) was screened, and the target genes and function of differentially expressed miRNAs (DEGs) were predicted. To verify the role of exosomal gga-miR-451, Western blot, ELISA and RT-qPCR were used in this study. The results showed that a total of 722 miRNAs were identified from the two exosomal small RNA (sRNA) libraries, and 30 miRNAs (9 up-regulated and 21 down-regulated) were significantly differentially expressed. The target miRNAs were significantly enriched in the treatment group, such as cell cycle, Toll-like receptor signalling pathway and MAPK signalling pathway. The results have also confirmed that gga-miR-451-absent exosomes derived from MG-infected CP-II cells increased inflammatory cytokine production in chicken fibroblast cells (DF-1), and wild-type CP-II cell-derived exosomes displayed protective effects. Collectively, our work suggests that exosomes from MG-infected CP-II cells alter the dynamics of the DF-1 cells, and may contribute to pathology of the MG infection via exosomal gga-miR-451 targeting YWHAZ involving in inflammation. <<<

Charles N Landen, Luciana Molinero, Habib Hamidi, Jalid Sehouli, Austin Miller, Kathleen N Moore, Cagatay Taskiran, Michael Bookman, Kristina Lindemann, Charles Anderson, Regina Berger, Tashanna Myers, Mario Beiner, Thomas Reid, Els Van Nieuwenhuysen, Andrew Green, Aikou Okamoto, Carol Aghajanian, Premal H Thaker, Stephanie V Blank, Victor K Khor, Ching-Wei Chang, Yvonne G Lin, Sandro Pignata <<<

PURPOSE: To explore whether patients with BRCA1/2-mutated or homologous recombination deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial.PATIENTS AND METHODS: Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. Programmed death-ligand 1 (PD-L1) status of tumor-infiltrating immune cells (IC) was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥ 16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates.RESULTS: Among biomarker-evaluable samples, 22% (234/1,050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1,024) had TMB ≥10 mut/Mb, and 0.3% (3/1,022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on ICs) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors.CONCLUSIONS: Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors. See related commentary by Al-Rawi et al., p. 1645. <<<

For most proteins annotated as enzymes, it is unknown which primary and/or secondary reactions they catalyze. Experimental characterizations of potential substrates are time-consuming and costly. Machine learning predictions could provide an efficient alternative, but are hampered by a lack of information regarding enzyme non-substrates, as available training data comprises mainly positive examples. Here, we present ESP, a general machine-learning model for the prediction of enzyme-substrate pairs with an accuracy of over 91% on independent and diverse test data. ESP can be applied successfully across widely different enzymes and a broad range of metabolites included in the training data, outperforming models designed for individual, well-studied enzyme families. ESP represents enzymes through a modified transformer model, and is trained on data augmented with randomly sampled small molecules assigned as non-substrates. By facilitating easy in silico testing of potential substrates, the ESP web server may support both basic and applied science. <<<

Johann S Bergholz, Qiwei Wang, Qi Wang, Michelle Ramseier, Sanjay Prakadan, Weihua Wang, Rong Fang, Sheheryar Kabraji, Qian Zhou, G Kenneth Gray, Kayley Abell-Hart, Shaozhen Xie, Xiaocan Guo, Hao Gu, Thanh Von, Tao Jiang, Shuang Tang, Gordon J Freeman, Hye-Jung Kim, Alex K Shalek, Thomas M Roberts, Jean J Zhao <<<

Loss of the PTEN tumour suppressor is one of the most common oncogenic drivers across all cancer types. PTEN is the major negative regulator of PI3K signalling. The PI3Kβ isoform has been shown to play an important role in PTEN-deficient tumours, but the mechanisms underlying the importance of PI3Kβ activity remain elusive. Here, using a syngeneic genetically engineered mouse model of invasive breast cancer driven by ablation of both Pten and Trp53 (which encodes p53), we show that genetic inactivation of PI3Kβ led to a robust anti-tumour immune response that abrogated tumour growth in syngeneic immunocompetent mice, but not in immunodeficient mice. Mechanistically, PI3Kβ inactivation in the PTEN-null setting led to reduced STAT3 signalling and increased the expression of immune stimulatory molecules, thereby promoting anti-tumour immune responses. Pharmacological PI3Kβ inhibition also elicited anti-tumour immunity and synergized with immunotherapy to inhibit tumour growth. Mice with complete responses to the combined treatment displayed immune memory and rejected tumours upon re-challenge. Our findings demonstrate a molecular mechanism linking PTEN loss and STAT3 activation in cancer and suggest that PI3Kβ controls immune escape in PTEN-null tumours, providing a rationale for combining PI3Kβ inhibitors with immunotherapy for the treatment of PTEN-deficient breast cancer. <<<

Zhi-Min Zhang, Rui Lu, Pengcheng Wang, Yang Yu, Dongliang Chen, Linfeng Gao, Shuo Liu, Debin Ji, Scott B Rothbart, Yinsheng Wang, Gang Greg Wang, Jikui Song <<<

DNA methylation by de novo DNA methyltransferases 3A (DNMT3A) and 3B (DNMT3B) at cytosines is essential for genome regulation and development. Dysregulation of this process is implicated in various diseases, notably cancer. However, the mechanisms underlying DNMT3 substrate recognition and enzymatic specificity remain elusive. Here we report a 2.65-ångström crystal structure of the DNMT3A-DNMT3L-DNA complex in which two DNMT3A monomers simultaneously attack two cytosine-phosphate-guanine (CpG) dinucleotides, with the target sites separated by 14 base pairs within the same DNA duplex. The DNMT3A-DNA interaction involves a target recognition domain, a catalytic loop, and DNMT3A homodimeric interface. Arg836 of the target recognition domain makes crucial contacts with CpG, ensuring DNMT3A enzymatic preference towards CpG sites in cells. Haematological cancer-associated somatic mutations of the substrate-binding residues decrease DNMT3A activity, induce CpG hypomethylation, and promote transformation of haematopoietic cells. Together, our study reveals the mechanistic basis for DNMT3A-mediated DNA methylation and establishes its aetiological link to human disease. <<<

Tapsi Kumar, Kevin Nee, Runmin Wei, Siyuan He, Quy H Nguyen, Shanshan Bai, Kerrigan Blake, Maren Pein, Yanwen Gong, Emi Sei, Min Hu, Anna K Casasent, Aatish Thennavan, Jianzhuo Li, Tuan Tran, Ken Chen, Benedikt Nilges, Nachiket Kashikar, Oliver Braubach, Bassem Ben Cheikh, Nadya Nikulina, Hui Chen, Mediget Teshome, Brian Menegaz, Huma Javaid, Chandandeep Nagi, Jessica Montalvan, Tatyana Lev, Sharmila Mallya, Delia F Tifrea, Robert Edwards, Erin Lin, Ritesh Parajuli, Summer Hanson, Sebastian Winocour, Alastair Thompson, Bora Lim, Devon A Lawson, Kai Kessenbrock, Nicholas Navin <<<

The adult human breast is comprised of an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue. Although most previous studies have focused on the breast epithelial system, many of the non-epithelial cell types remain understudied. Here we constructed the comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics study profiled 714,331 cells from 126 women, and 117,346 nuclei from 20 women, identifying 12 major cell types and 58 biological cell states. These data reveal abundant perivascular, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Spatial mapping using four different technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide a reference of the adult normal breast tissue for studying mammary biology and diseases such as breast cancer. <<<

Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. In this paper, we formulate SBDD as a 3D-conditional generation problem and present DiffSBDD, an SE(3)-equivariant 3D-conditional diffusion model that generates novel ligands conditioned on protein pockets. Comprehensive in silico experiments demonstrate the efficiency and effectiveness of DiffSBDD in generating novel and diverse drug-like ligands with competitive docking scores. We further explore the flexibility of the diffusion framework for a broader range of tasks in drug design campaigns, such as off-the-shelf property optimization and partial molecular design with inpainting. <<<

Stress influences episodic memory formation via noradrenaline and glucocorticoid effects on amygdala and hippocampus. A common finding is the improvement of memory for central aspects of a stressful episode. This is putatively related to changes in the neural representations of specific experiences, i.e., their memory traces. Here we show that the memory improvement for objects that were encountered in a stressful episode relates to differences in the neural representations of these objects in the amygdala. Using functional magnetic resonance imaging, we found that stress specifically altered the representations of central objects: compared to control objects, they became more similar to one another and more distinct from objects that were not part of this episode. Furthermore, higher similarity of central objects to the main stressor-the faces of the stress-inducing committee members-predicted better memory. This suggests that the central objects were closely integrated into a stressor-centered memory representation. Our findings provide mechanistic insights into how stress shapes the memory trace and have profound implications for neurocognitive models of stressful and emotional memory. <<<

Deformable image registration is one of the fundamental tasks in medical imaging. Classical registration algorithms usually require a high computational cost for iterative optimizations. Although deep-learning-based methods have been developed for fast image registration, it is still challenging to obtain realistic continuous deformations from a moving image to a fixed image with less topological folding problem. To address this, here we present a novel diffusion-model-based image registration method, called DiffuseMorph. DiffuseMorph not only generates synthetic deformed images through reverse diffusion but also allows image registration by deformation fields. Specifically, the deformation fields are generated by the conditional score function of the deformation between the moving and fixed images, so that the registration can be performed from continuous deformation by simply scaling the latent feature of the score. Experimental results on 2D facial and 3D medical image registration tasks demonstrate that our method provides flexible deformations with topology preservation capability. <<<

Noura S Abul-Husn, Priya N Marathe, Nicole R Kelly, Katherine E Bonini, Monisha Sebastin, Jacqueline A Odgis, Avinash Abhyankar, Kaitlyn Brown, Miranda Di Biase, Katie M Gallagher, Saurav Guha, Nicolette Ioele, Volkan Okur, Michelle A Ramos, Jessica E Rodriguez, Atteeq U Rehman, Amanda Thomas-Wilson, Lisa Edelmann, Randi E Zinberg, George A Diaz, John M Greally, Vaidehi Jobanputra, Sabrina A Suckiel, Carol R Horowitz, Melissa P Wasserstein, Eimear E Kenny, Bruce D Gelb <<<

PURPOSE: Adoption of genome sequencing (GS) as a first-line test requires evaluation of its diagnostic yield. We evaluated the GS and targeted gene panel (TGP) testing in diverse pediatric patients (probands) with suspected genetic conditions.METHODS: Probands with neurologic, cardiac, or immunologic conditions were offered GS and TGP testing. Diagnostic yield was compared using a fully paired study design.RESULTS: A total of 645 probands (median age 9 years) underwent genetic testing, and 113 (17.5%) received a molecular diagnosis. Among 642 probands with both GS and TGP testing, GS yielded 106 (16.5%) and TGPs yielded 52 (8.1%) diagnoses (P < .001). Yield was greater for GS vs TGPs in Hispanic/Latino(a) (17.2% vs 9.5%, P < .001) and White/European American (19.8% vs 7.9%, P < .001) but not in Black/African American (11.5% vs 7.7%, P = .22) population groups by self-report. A higher rate of inconclusive results was seen in the Black/African American (63.8%) vs White/European American (47.6%; P = .01) population group. Most causal copy number variants (17 of 19) and mosaic variants (6 of 8) were detected only by GS.CONCLUSION: GS may yield up to twice as many diagnoses in pediatric patients compared with TGP testing but not yet across all population groups. <<<

Daiqi Wang, Hongru Wang, Xiaomei Xu, Man Wang, Yahuan Wang, Hong Chen, Fei Ping, Huanhuan Zhong, Zhengkun Mu, Wantong Xie, Xiangyu Li, Jingbin Feng, Milan Zhang, Zhilan Fan, Tifeng Yang, Junliang Zhao, Bin Liu, Ying Ruan, Guiquan Zhang, Chunlin Liu, Ziqiang Liu <<<

Understanding the evolutionary forces in speciation is a central goal in evolutionary biology. Asian cultivated rice has two subspecies, indica and japonica, but the underlying mechanism of the partial reproductive isolation between them remains obscure. Here we show a presence-absence variation (PAV) at the Se locus functions as an indica-japonica reproductive barrier by causing hybrid sterility (HS) in indica-japonica crosses. The locus comprises two adjacent genes: ORF3 encodes a sporophytic pollen killer, whereas ORF4 protects pollen in a gametophytic manner. In F of indica-japonica crosses, pollen with the japonica haplotype, which lacks the sequence containing the protective ORF4, is aborted due to the pollen-killing effect of ORF3 from indica. Evolutionary analysis suggests ORF3 is a gene associated with the Asian cultivated rice species complex, and the PAV has contributed to the reproductive isolation between the two subspecies of Asian cultivated rice. Our analyses provide perspectives on rice inter-subspecies post-zygotic isolation, and will promote efforts to overcome reproductive barriers in indica-japonica hybrid rice breeding. <<<

Nicolas Vallet, Maud Salmona, Jeanne Malet-Villemagne, Maxime Bredel, Louise Bondeelle, Simon Tournier, Séverine Mercier-Delarue, Stéphane Cassonnet, Brian Ingram, Régis Peffault de Latour, Anne Bergeron, Gérard Socié, Jérome Le Goff, Patricia Lepage, David Michonneau <<<

Early administration of azithromycin after allogeneic hematopoietic stem cell transplantation was shown to increase the relapse of hematological malignancies. To determine the impact of azithromycin on the post-transplant gut ecosystem and its influence on relapse, we characterized overtime gut bacteriome, virome, and metabolome of 55 patients treated with azithromycin or a placebo. We describe four enterotypes and the network of associated bacteriophage species and metabolic pathways. One enterotype associates with sustained remission. One taxon from Bacteroides specifically associates with relapse, while two from Bacteroides and Prevotella correlate with complete remission. These taxa are associated with lipid, pentose, and branched-chain amino acid metabolic pathways and several bacteriophage species. Enterotypes and taxa associate with exhausted T cells and the functional status of circulating immune cells. These results illustrate how an antibiotic influences a complex network of gut bacteria, viruses, and metabolites and may promote cancer relapse through modifications of immune cells. <<<

Michal Bassani-Sternberg, Eva Bräunlein, Richard Klar, Thomas Engleitner, Pavel Sinitcyn, Stefan Audehm, Melanie Straub, Julia Weber, Julia Slotta-Huspenina, Katja Specht, Marc E Martignoni, Angelika Werner, Rüdiger Hein, Dirk H Busch, Christian Peschel, Roland Rad, Jürgen Cox, Matthias Mann, Angela M Krackhardt <<<

Although mutations may represent attractive targets for immunotherapy, direct identification of mutated peptide ligands isolated from human leucocyte antigens (HLA) on the surface of native tumour tissue has so far not been successful. Using advanced mass spectrometry (MS) analysis, we survey the melanoma-associated immunopeptidome to a depth of 95,500 patient-presented peptides. We thereby discover a large spectrum of attractive target antigen candidates including cancer testis antigens and phosphopeptides. Most importantly, we identify peptide ligands presented on native tumour tissue samples harbouring somatic mutations. Four of eleven mutated ligands prove to be immunogenic by neoantigen-specific T-cell responses. Moreover, tumour-reactive T cells with specificity for selected neoantigens identified by MS are detected in the patient's tumour and peripheral blood. We conclude that direct identification of mutated peptide ligands from primary tumour material by MS is possible and yields true neoepitopes with high relevance for immunotherapeutic strategies in cancer. <<<

Hong Yang, Xiao Chen, Zuo-Bing Chen, Le Li, Xue-Ying Li, Francisco Xavier Castellanos, Tong-Jian Bai, Qi-Jing Bo, Jun Cao, Zhi-Kai Chang, Guan-Mao Chen, Ning-Xuan Chen, Wei Chen, Chang Cheng, Yu-Qi Cheng, Xi-Long Cui, Jia Duan, Yiru Fang, Qi-Yong Gong, Wen-Bin Guo, Zheng-Hua Hou, Lan Hu, Li Kuang, Feng Li, Hui-Xian Li, Kai-Ming Li, Tao Li, Yan-Song Liu, Zhe-Ning Liu, Yi-Cheng Long, Bin Lu, Qing-Hua Luo, Hua-Qing Meng, Daihui Peng, Hai-Tang Qiu, Jiang Qiu, Yue-Di Shen, Yu-Shu Shi, Tian-Mei Si, Yan-Qing Tang, Chuan-Yue Wang, Fei Wang, Kai Wang, Li Wang, Xiang Wang, Ying Wang, Yu-Wei Wang, Xiao-Ping Wu, Xin-Ran Wu, Chun-Ming Xie, Guang-Rong Xie, Hai-Yan Xie, Peng Xie, Xiu-Feng Xu, Jian Yang, Jia-Shu Yao, Shu-Qiao Yao, Ying-Ying Yin, Yong-Gui Yuan, Yu-Feng Zang, Ai-Xia Zhang, Hong Zhang, Ke-Rang Zhang, Lei Zhang, Zhi-Jun Zhang, Jing-Ping Zhao, Rubai Zhou, Yi-Ting Zhou, Jun-Juan Zhu, Zhi-Chen Zhu, Chao-Jie Zou, Xi-Nian Zuo, Chao-Gan Yan <<<

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks. <<<

Large language models (LLMs) are shown to possess a wealth of actionable knowledge that can be extracted for robot manipulation in the form of reasoning and planning. Despite the progress, most still rely on pre-defined motion primitives to carry out the physical interactions with the environment, which remains a major bottleneck. In this work, we aim to synthesize robot trajectories, i.e., a dense sequence of 6-DoF end-effector waypoints, for a large variety of manipulation tasks given an open-set of instructions and an open-set of objects. We achieve this by first observing that LLMs excel at inferring affordances and constraints given a free-form language instruction. More importantly, by leveraging their code-writing capabilities, they can interact with a visual-language model (VLM) to compose 3D value maps to ground the knowledge into the observation space of the agent. The composed value maps are then used in a model-based planning framework to zero-shot synthesize closed-loop robot trajectories with robustness to dynamic perturbations. We further demonstrate how the proposed framework can benefit from online experiences by efficiently learning a dynamics model for scenes that involve contact-rich interactions. We present a large-scale study of the proposed method in both simulated and real-robot environments, showcasing the ability to perform a large variety of everyday manipulation tasks specified in free-form natural language. Project website: this https URL <<<

Tianshi Lu, Ze Zhang, James Zhu, Yunguan Wang, Peixin Jiang, Xue Xiao, Chantale Bernatchez, John V Heymach, Don L Gibbons, Jun Wang, Lin Xu, Alexandre Reuben, Tao Wang <<<

Neoantigens play a key role in the recognition of tumor cells by T cells. However, only a small proportion of neoantigens truly elicit T cell responses, and fewer clues exist as to which neoantigens are recognized by which T cell receptors (TCRs). We built a transfer learning-based model, named pMHC-TCR binding prediction network (pMTnet), to predict TCR-binding specificities of neoantigens, and T cell antigens in general, presented by class I major histocompatibility complexes (pMHCs). pMTnet was comprehensively validated by a series of analyses, and showed advance over previous work by a large margin. By applying pMTnet in human tumor genomics data, we discovered that neoantigens were generally more immunogenic than self-antigens, but HERV-E, a special type of self-antigen that is re-activated in kidney cancer, is more immunogenic than neoantigens. We further discovered that patients with more clonally expanded T cells exhibiting better affinity against truncal, rather than subclonal, neoantigens, had more favorable prognosis and treatment response to immunotherapy, in melanoma and lung cancer but not in kidney cancer. Predicting TCR-neoantigen/antigen pairs is one of the most daunting challenges in modern immunology. However, we achieved an accurate prediction of the pairing only using the TCR sequence (CDR3β), antigen sequence, and class I MHC allele, and our work revealed unique insights into the interactions of TCRs and pMHCs in human tumors using pMTnet as a discovery tool. <<<

Matthew F Glasser, Stamatios N Sotiropoulos, J Anthony Wilson, Timothy S Coalson, Bruce Fischl, Jesper L Andersson, Junqian Xu, Saad Jbabdi, Matthew Webster, Jonathan R Polimeni, David C Van Essen, Mark Jenkinson, WU-Minn HCP Consortium <<<

The Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventional 3 Tesla scanners and often require newly developed preprocessing methods. We describe the minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space. These pipelines are specially designed to capitalize on the high quality data offered by the HCP. The final standard space makes use of a recently introduced CIFTI file format and the associated grayordinate spatial coordinate system. This allows for combined cortical surface and subcortical volume analyses while reducing the storage and processing requirements for high spatial and temporal resolution data. Here, we provide the minimum image acquisition requirements for the HCP minimal preprocessing pipelines and additional advice for investigators interested in replicating the HCP's acquisition protocols or using these pipelines. Finally, we discuss some potential future improvements to the pipelines. <<<

Achromobacter xylosoxidans (Ax) is an opportunistic pathogen and causative agent of numerous infections particularly in immunocompromised individuals with increasing prevalence in cystic fibrosis (CF). To date, investigations have focused on the clinical epidemiology and genomic comparisons of Ax isolates, yet little is known about disease pathology or the role that specific virulence factors play in tissue invasion or damage. Here, we model an acute Ax lung infection in immunocompetent C57BL/6 mice and immunocompromised CF mice, revealing a link between cytotoxicity and disease in an intact host. Mice were intratracheally challenged with sublethal doses of a cytotoxic (GN050) or invasive (GN008) strain of Ax. Bacterial burden, immune cell populations, and inflammatory markers in bronchoalveolar lavage fluid and lung homogenates were measured at different time points to assess disease severity. CF mice had a similar but delayed immune response toward both Ax strains compared to C57BL/6J mice. GN050 caused more severe disease and higher mortality which correlated with greater bacterial burden and increased proinflammatory responses in both mouse models. In agreement with the cytotoxicity of GN050 toward macrophages , mice challenged with GN050 had fewer macrophages. Mutants with transposon insertions in predicted virulence factors of GN050 showed that disease severity depended on the type III secretion system, Vi capsule, antisigma-E factor, and partially on the ArtA adhesin. The development of an acute infection model provides an essential tool to better understand the infectivity of diverse Ax isolates and enable improved identification of virulence factors important to bacterial persistence and disease. <<<

Engineering a patient's own T cells to selectively target and eliminate tumour cells has cured patients with untreatable haematologic cancers. These results have energized the field to apply chimaeric antigen receptor (CAR) T therapy throughout oncology. However, evidence from clinical and preclinical studies underscores the potential of CAR T therapy beyond oncology in treating autoimmunity, chronic infections, cardiac fibrosis, senescence-associated disease and other conditions. Concurrently, the deployment of new technologies and platforms provides further opportunity for the application of CAR T therapy to noncancerous pathologies. Here we review the rationale behind CAR T therapy, current challenges faced in oncology, a synopsis of preliminary reports in noncancerous diseases, and a discussion of relevant emerging technologies. We examine potential applications for this therapy in a wide range of contexts. Last, we highlight concerns regarding specificity and safety and outline the path forward for CAR T therapy beyond cancer. <<<

Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibit corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses reveal that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization. <<<