Integrated analysis of multimodal single-cell data.

The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce "weighted-nearest neighbor" analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.

Comprehensive Integration of Single-Cell Data.

Single-cell transcriptomics has transformed our ability to characterize cell states, but deep biological understanding requires more than a taxonomic listing of clusters. As new methods arise to measure distinct cellular modalities, a key analytical challenge is to integrate these datasets to better understand cellular identity and function. Here, we develop a strategy to "anchor" diverse datasets together, enabling us to integrate single-cell measurements not only across scRNA-seq technologies, but also across different modalities. After demonstrating improvement over existing methods for integrating scRNA-seq data, we anchor scRNA-seq experiments with scATAC-seq to explore chromatin differences in closely related interneuron subsets and project protein expression measurements onto a bone marrow atlas to characterize lymphocyte populations. Lastly, we harmonize in situ gene expression and scRNA-seq datasets, allowing transcriptome-wide imputation of spatial gene expression patterns. Our work presents a strategy for the assembly of harmonized references and transfer of information across datasets.

Transcriptome variation in human tissues revealed by long-read sequencing.

Regulation of transcript structure generates transcript diversity and plays an important role in human disease1-7. The advent of long-read sequencing technologies offers the opportunity to study the role of genetic variation in transcript structure8-16. In this Article, we present a large human long-read RNA-seq dataset using the Oxford Nanopore Technologies platform from 88 samples from Genotype-Tissue Expression (GTEx) tissues and cell lines, complementing the GTEx resource. We identified just over 70,000 novel transcripts for annotated genes, and validated the protein expression of 10% of novel transcripts. We developed a new computational package, LORALS, to analyse the genetic effects of rare and common variants on the transcriptome by allele-specific analysis of long reads. We characterized allele-specific expression and transcript structure events, providing new insights into the specific transcript alterations caused by common and rare genetic variants and highlighting the resolution gained from long-read data. We were able to perturb the transcript structure upon knockdown of PTBP1, an RNA binding protein that mediates splicing, thereby finding genetic regulatory effects that are modified by the cellular environment. Finally, we used this dataset to enhance variant interpretation and study rare variants leading to aberrant splicing patterns.

Distinctive and Complementary Roles of Default Mode Network Subsystems in Semantic Cognition.

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and frontotemporal (FT) subsystems, but its functional organization is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial), and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based human functional magnetic resonance imaging (fMRI) datasets, and localized these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks, and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more "tuned" states characterized by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually coupled (scenes) and decoupled (autobiographical memory) tasks and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to the sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks.

Verbal semantic expertise is associated with reduced functional connectivity between left and right anterior temporal lobes.

The left and right anterior temporal lobes (ATLs) encode semantic representations. They show graded hemispheric specialization in function, with the left ATL contributing preferentially to verbal semantic processing. We investigated the cognitive correlates of this organization, using resting-state functional connectivity as a measure of functional segregation between ATLs. We analyzed two independent resting-state fMRI datasets (n = 86 and n = 642) in which participants' verbal semantic expertise was measured using vocabulary tests. In both datasets, people with more advanced verbal semantic knowledge showed weaker functional connectivity between left and right ventral ATLs. This effect was highly specific. It was not observed for within-hemisphere connections between semantic regions (ventral ATL and inferior frontal gyrus (IFG), though it was found for left-right IFG connectivity in one dataset). Effects were not found for tasks probing semantic control, nonsemantic cognition, or face recognition. Our results suggest that hemispheric specialization in the ATLs is not an innate property but rather emerges as people develop highly detailed verbal semantic representations. We speculate that this effect is a consequence of the left ATL's greater connectivity with left-lateralized written word recognition regions, which causes it to preferentially represent meaning for advanced vocabulary acquired primarily through reading.

Representation of event and object concepts in ventral anterior temporal lobe and angular gyrus.

Semantic knowledge includes understanding of objects and their features and also understanding of the characteristics of events. The hub-and-spoke theory holds that these conceptual representations rely on multiple information sources that are integrated in a central hub in the ventral anterior temporal lobes. The dual-hub theory expands this framework with the claim that the ventral anterior temporal lobe hub is specialized for object representation, while a second hub in angular gyrus is specialized for event representation. To test these ideas, we used representational similarity analysis, univariate and psychophysiological interaction analyses of fMRI data collected while participants processed object and event concepts (e.g. "an apple," "a wedding") presented as images and written words. Representational similarity analysis showed that angular gyrus encoded event concept similarity more than object similarity, although the left angular gyrus also encoded object similarity. Bilateral ventral anterior temporal lobes encoded both object and event concept structure, and left ventral anterior temporal lobe exhibited stronger coding for events. Psychophysiological interaction analysis revealed greater connectivity between left ventral anterior temporal lobe and right pMTG, and between right angular gyrus and bilateral ITG and middle occipital gyrus, for event concepts compared to object concepts. These findings support the specialization of angular gyrus for event semantics, though with some involvement in object coding, but do not support ventral anterior temporal lobe specialization for object concepts.

The Year in Thoracic Anesthesia: Selected Highlights from 2022.

This article reviews research highlights in the field of thoracic anesthesia. The highlights of this year included new developments in the preoperative assessment and prehabilitation of patients requiring thoracic surgery, updates on the use of devices for one-lung ventilation (OLV) in adults and children, updates on the anesthetic and postoperative management of these patients, including protective OLV ventilation, the use of opioid-sparing techniques and regional anesthesia, and outcomes using enhanced recovery after surgery, as well as the use of expanding indications for extracorporeal membrane oxygenation, specialized anesthetic techniques for airway surgery, and nonintubated video-assisted thoracic surgery.

The words that little by little revealed everything: Neural response to lexical-semantic content during narrative comprehension.

The ease with which narratives are understood belies the complexity of the information being conveyed and the cognitive processes that support comprehension. The meanings of the words must be rapidly accessed and integrated with the reader's mental representation of the overarching, unfolding scenario. A broad, bilateral brain network is engaged by this process, but it is not clear how words that vary on specific semantic dimensions, such as ambiguity, emotion, or socialness, engage the semantic, semantic control, or social cognition systems. In the present study, data from 48 participants who listened to The Little Prince audiobook during MRI scanning were selected from the Le Petit Prince dataset. The lexical and semantic content within the narrative was quantified from the transcript words with factor scores capturing Word Length, Semantic Flexibility, Emotional Strength, and Social Impact. These scores, along with word quantity variables, were used to investigate where these predictors co-vary with activation across the brain. In contrast to studies of isolated word processing, large networks were found to co-vary with the lexical and semantic content within the narrative. An increase in semantic content engaged the ventral portion of ventrolateral ATL, consistent with its role as a semantic hub. Decreased semantic content engaged temporal pole and inferior parietal lobule, which may reflect semantic integration. The semantic control network was engaged by words with low Semantic Flexibility, perhaps due to the demand required to process infrequent, less semantically diverse language. Activation in ATL co-varied with an increase in Social Impact, which is consistent with the claim that social knowledge is housed within the neural architecture of the semantic system. These results suggest that current models of language processing may present an impoverished estimate of the neural systems that coordinate to support narrative comprehension, and, by extension, real-world language processing.

A common neural code for meaning in discourse production and comprehension.

How does the brain code the meanings conveyed by language? Neuroimaging studies have investigated this by linking neural activity patterns during discourse comprehension to semantic models of language content. Here, we applied this approach to the production of discourse for the first time. Participants underwent fMRI while producing and listening to discourse on a range of topics. We used a distributional semantic model to quantify the similarity between different speech passages and identified where similarity in neural activity was predicted by semantic similarity. When people produced discourse, speech on similar topics elicited similar activation patterns in a widely distributed and bilateral brain network. This network was overlapping with, but more extensive than, the regions that showed similarity effects during comprehension. Critically, cross-task neural similarities between comprehension and production were also predicted by similarities in semantic content. This result suggests that discourse semantics engages a common neural code that is shared between comprehension and production. Effects of semantic similarity were bilateral in all three RSA analyses, even while univariate activation contrasts in the same data indicated left-lateralised BOLD responses. This indicates that right-hemisphere regions encode semantic properties even when they are not activated above baseline. We suggest that right-hemisphere regions play a supporting role in processing the meaning of discourse during both comprehension and production.

Similar neural networks respond to coherence during comprehension and production of discourse.

When comprehending discourse, listeners engage default-mode regions associated with integrative semantic processing to construct a situation model of its content. We investigated how similar networks are engaged when we produce, as well as comprehend, discourse. During functional magnetic resonance imaging, participants spoke about a series of specific topics and listened to discourse on other topics. We tested how activation was predicted by natural fluctuations in the global coherence of the discourse, that is, the degree to which utterances conformed to the expected topic. The neural correlates of coherence were similar across speaking and listening, particularly in default-mode regions. This network showed greater activation when less coherent speech was heard or produced, reflecting updating of mental representations when discourse did not conform to the expected topic. In contrast, regions that exert control over semantic activation showed task-specific effects, correlating negatively with coherence during listening but not during production. Participants who showed greater activation in left inferior prefrontal cortex also produced more coherent discourse, suggesting a specific role for this region in goal-directed regulation of speech content. Results suggest strong correspondence of discourse representations during speaking and listening. However, they indicate that the semantic control network plays different roles in comprehension and production.

Perceptual and Semantic Representations at Encoding Contribute to True and False Recognition of Objects.

When encoding new episodic memories, visual and semantic processing is proposed to make distinct contributions to accurate memory and memory distortions. Here, we used fMRI and preregistered representational similarity analysis to uncover the representations that predict true and false recognition of unfamiliar objects. Two semantic models captured coarse-grained taxonomic categories and specific object features, respectively, while two perceptual models embodied low-level visual properties. Twenty-eight female and male participants encoded images of objects during fMRI scanning, and later had to discriminate studied objects from similar lures and novel objects in a recognition memory test. Both perceptual and semantic models predicted true memory. When studied objects were later identified correctly, neural patterns corresponded to low-level visual representations of these object images in the early visual cortex, lingual, and fusiform gyri. In a similar fashion, alignment of neural patterns with fine-grained semantic feature representations in the fusiform gyrus also predicted true recognition. However, emphasis on coarser taxonomic representations predicted forgetting more anteriorly in the anterior ventral temporal cortex, left inferior frontal gyrus and, in an exploratory analysis, left perirhinal cortex. In contrast, false recognition of similar lure objects was associated with weaker visual analysis posteriorly in early visual and left occipitotemporal cortex. The results implicate multiple perceptual and semantic representations in successful memory encoding and suggest that fine-grained semantic as well as visual analysis contributes to accurate later recognition, while processing visual image detail is critical for avoiding false recognition errors.SIGNIFICANCE STATEMENT People are able to store detailed memories of many similar objects. We offer new insights into the encoding of these specific memories by combining fMRI with explicit models of how image properties and object knowledge are represented in the brain. When people processed fine-grained visual properties in occipital and posterior temporal cortex, they were more likely to recognize the objects later and less likely to falsely recognize similar objects. In contrast, while object-specific feature representations in fusiform gyrus predicted accurate memory, coarse-grained categorical representations in frontal and temporal regions predicted forgetting. The data provide the first direct tests of theoretical assumptions about encoding true and false memories, suggesting that semantic representations contribute to specific memories as well as errors.

Representation of motion concepts in occipitotemporal cortex: fMRI activation, decoding and connectivity analyses.

Embodied theories of semantic cognition predict that brain regions involved in motion perception are engaged when people comprehend motion concepts expressed in language. Left lateral occipitotemporal cortex (LOTC) is implicated in both motion perception and motion concept processing but prior studies have produced mixed findings on which parts of this region are engaged by motion language. We scanned participants performing semantic judgements about sentences describing motion events and static events. We performed univariate analyses, multivariate pattern analyses (MVPA) and psychophysiological interaction (PPI) analyses to investigate the effect of motion on activity and connectivity in different parts of LOTC. In multivariate analyses that decoded whether a sentence described motion or not, the middle and posterior parts of LOTC showed above-chance level performance, with performance exceeding that of other brain regions. Univariate ROI analyses found the middle part of LOTC was more active for motion events than static ones. Finally, PPI analyses found that when processing motion events, the middle and posterior parts of LOTC (overlapping with motion perception regions), increased their connectivity with cognitive control regions. Taken together, these results indicate that the more posterior parts of LOTC, including motion perception cortex, respond differently to motion vs. static events. These findings are consistent with embodiment accounts of semantic processing, and suggest that understanding verbal descriptions of motion engages areas of the occipitotemporal cortex involved in perceiving motion.

Seawater-buffered diagenesis, destruction of carbon isotope excursions, and the composition of DIC in Neoproterozoic oceans.

Carbonate sediments of nonglacial Cryogenian (659 to 649 Ma) and early Ediacaran (635 to 590 Ma) age exhibit large positive and negative δ13Ccarb excursions in a shallow-water marine platform in northern Namibia. The same excursions are recorded in fringing deep-sea fans and in carbonate platforms on other paleocontinents. However, coeval carbonates in the upper foreslope of the Namibian platform, and to a lesser extent in the outermost platform, have relatively uniform δ13Ccarb compositions compatible with dissolved inorganic carbon (DIC) in the modern ocean. We attribute the uniform values to fluid-buffered diagenesis that occurred where seawater invaded the sediment in response to geothermal porewater convection. This attribution, which is testable with paired Ca and Mg isotopes, implies that large δ13Ccarb excursions observed in Neoproterozoic platforms, while sedimentary in origin, do not reflect the composition of ancient open-ocean DIC.

In vitro activity of amixicile against T. vaginalis from clinical isolates.

Trichomoniasis is a sexually transmitted infection in humans caused by the protozoan Trichomonas vaginalis, the leading causative agent of vaginitis in women and urethritis in men worldwide. Metronidazole is the standard treatment for trichomoniasis, with tinidazole as the second line. There are currently no FDA-approved non-nitroimidazole alternative treatments for resistant strains. This study compares the efficacy of a newly synthesized non-nitroimidazole oral drug, amixicile, to that of both metronidazole and the synthetic precursor of amixicile, nitazoxanide with in vitro sensitivity testing. One standard strain from ATCC and three patient-isolated strains of T. vaginalis were used to compare treatments under anaerobic conditions. The minimum inhibitory concentration for metronidazole, nitazoxanide, and amixicile were 12.5 µM, 100 µM, and 6.25 µM, respectively. These results suggest that amixicile may be highly active against T. vaginalis and warrants further investigation as a potential alternative to metronidazole in the treatment of trichomoniasis.

Semantic diversity is best measured with unscaled vectors: Reply to Cevoli, Watkins and Rastle (2020).

Semantic diversity refers to the degree of semantic variability in the contexts in which a particular word is used. We have previously proposed a method for measuring semantic diversity based on latent semantic analysis (LSA). In a recent paper, Cevoli et al. (2020) attempted to replicate our method and obtained different semantic diversity values. They suggested that this discrepancy occurred because they scaled their LSA vectors by their singular values, while we did not. Using their new results, they argued that semantic diversity is not related to ambiguity in word meaning, as we originally proposed. In this reply, we demonstrate that the use of unscaled vectors provides better fits to human semantic judgements than scaled ones. Thus we argue that our original semantic diversity measure should be preferred over the Cevoli et al. version. We replicate Cevoli et al.'s analysis using the original semantic diversity measure and find (a) our original measure is a better predictor of word recognition latencies than the Cevoli et al. equivalent and (b) that, unlike Cevoli et al.'s measure, our semantic diversity is reliably associated with a measure of polysemy based on dictionary definitions. We conclude that the Hoffman et al. semantic diversity measure is better-suited to capturing the contextual variability among words and that words appearing in a more diverse set of contexts have more variable semantic representations. However, we found that homonyms did not have higher semantic diversity values than non-homonyms, suggesting that the measure does not capture this special case of ambiguity.

Stimulus-independent neural coding of event semantics: Evidence from cross-sentence fMRI decoding.

Multivariate neuroimaging studies indicate that the brain represents word and object concepts in a format that readily generalises across stimuli. Here we investigated whether this was true for neural representations of simple events described using sentences. Participants viewed sentences describing four events in different ways. Multivariate classifiers were trained to discriminate the four events using a subset of sentences, allowing us to test generalisation to novel sentences. We found that neural patterns in a left-lateralised network of frontal, temporal and parietal regions discriminated events in a way that generalised successfully over changes in the syntactic and lexical properties of the sentences used to describe them. In contrast, decoding in visual areas was sentence-specific and failed to generalise to novel sentences. In the reverse analysis, we tested for decoding of syntactic and lexical structure, independent of the event being described. Regions displaying this coding were limited and largely fell outside the canonical semantic network. Our results indicate that a distributed neural network represents the meaning of event sentences in a way that is robust to changes in their structure and form. They suggest that the semantic system disregards the surface properties of stimuli in order to represent their underlying conceptual significance.

Constraints on Paleoproterozoic atmospheric oxygen levels.

The oxygenation of Earth's surface environment dramatically altered key biological and geochemical cycles and ultimately ushered in the rise of an ecologically diverse biosphere. However, atmospheric oxygen partial pressures (pO2) estimates for large swaths of the Precambrian remain intensely debated. Here we evaluate and explore the use of carbonate cerium (Ce) anomalies (Ce/Ce*) as a quantitative atmospheric pO2 proxy and provide estimates of Proterozoic pO2 using marine carbonates from a unique Precambrian carbonate succession-the Paleoproterozoic Pethei Group. In contrast to most previous work, we measure Ce/Ce* on marine carbonate precipitates that formed in situ across a depth gradient, building on previous detailed sedimentology and stratigraphy to constrain the paleo-depth of each sample. Measuring Ce/Ce* across a full platform to basin depth gradient, we found only minor depleted Ce anomalies restricted to the platform and upper slope facies. We combine these results with a Ce oxidation model to provide a quantitative constraint on atmospheric pO2 1.87 billion years ago (Ga). Our results suggest Paleoproterozoic atmospheric oxygen concentrations were low, near 0.1% of the present atmospheric level. This work provides another crucial line of empirical evidence that atmospheric oxygen levels returned to low concentrations following the Lomagundi Event, and remained low enough for large portions of the Proterozoic to have impacted the ecology of the earliest complex organisms.

The small molecule nitazoxanide selectively disrupts BAM-mediated folding of the outer membrane usher protein.

Bacterial pathogens assemble adhesive surface structures termed pili or fimbriae to initiate and sustain infection of host tissues. Uropathogenic Escherichia coli, the primary causative agent of urinary tract infections, expresses type 1 and P pili required for colonization of the bladder and kidney, respectively. These pili are assembled by the conserved chaperone-usher (CU) pathway, in which a periplasmic chaperone works together with an outer membrane (OM) usher protein to build and secrete the pilus fiber. Previously, we found that the small molecule and antiparasitic drug nitazoxanide (NTZ) inhibits CU pathway-mediated pilus biogenesis in E. coli by specifically interfering with proper maturation of the usher protein in the OM. The usher is folded and inserted into the OM by the ß-barrel assembly machine (BAM) complex, which in E. coli comprises five proteins, BamA-E. Here, we show that sensitivity of the usher to NTZ is modulated by BAM expression levels and requires the BamB and BamE lipoproteins. Furthermore, a genetic screen for NTZ-resistant bacterial mutants isolated a mutation in the essential BamD lipoprotein. These findings suggest that NTZ selectively interferes with an usher-specific arm of the BAM complex, revealing new details of the usher folding pathway and BAM complex function. Evaluation of a set of NTZ derivatives identified compounds with increased potency and disclosed that NTZ's nitrothiazole ring is critical for usher inhibition. In summary, our findings indicate highly specific effects of NTZ on the usher folding pathway and have uncovered NTZ analogs that specifically decrease usher levels in the OM.

Barking up the right tree: Univariate and multivariate fMRI analyses of homonym comprehension.

Homonyms are a critical test case for investigating how the brain resolves ambiguity in language and, more generally, how context influences semantic processing. Previous neuroimaging studies have associated processing of homonyms with greater engagement of regions involved in executive control of semantic processing. However, the precise role of these areas and the involvement of semantic representational regions in homonym comprehension remain elusive. We addressed this by combining univariate and multivariate fMRI analyses of homonym processing. We tested whether multi-voxel activation patterns could discriminate between presentations of the same homonym in different contexts (e.g., bark following tree vs. bark following dog). The ventral anterior temporal lobe, implicated in semantic representation but not previously in homonym comprehension, showed this meaning-specific coding, despite not showing increased mean activation for homonyms. Within inferior frontal gyrus (IFG), a key site for semantic control, there was a dissociation between pars orbitalis, which also showed meaning-specific coding, and pars triangularis, which discriminated more generally between semantically related and unrelated word pairs. IFG effects were goal-dependent, only occurring when the task required semantic decisions, in line with a top-down control function. Finally, posterior middle temporal cortex showed a hybrid pattern of responses, supporting the idea that it acts as an interface between semantic representations and the control system. The study provides new evidence for context-dependent coding in the semantic system and clarifies the role of control regions in processing ambiguity. It also highlights the importance of combining univariate and multivariate neuroimaging data to fully elucidate the role of a brain region in semantic cognition.

Revealing the neural networks that extract conceptual gestalts from continuously evolving or changing semantic contexts.

Reading a book, understanding the news reports or any other behaviour involving the processing of meaningful stimuli requires the semantic system to have two main features: being active during an extended period of time and flexibly adapting the internal representation according to the changing environment. Despite being key features of many everyday tasks, formation and updating of the semantic "gestalt" are still poorly understood. In this fMRI study we used naturalistic stimuli and task manipulations to identify the neural network that forms and updates conceptual gestalts during time-extended integration of meaningful stimuli. Univariate and multivariate techniques allowed us to draw a distinction between networks that are crucial for the formation of a semantic gestalt (meaning integration) and those that instead are important for linking incoming cues about the current context (e.g., time and space cues) into a schema representation. Specifically, we revealed that time-extended formation of the conceptual gestalt was reflected in the neuro-computations of the anterior temporal lobe accompanied by multi-demand areas and hippocampus, with a key role of brain structures in the right hemisphere. This "semantic gestalt network" was strongly recruited when an update of the current semantic representation was required during narrative processing. A distinct fronto-parietal network, instead, was recruited for context integration, independently from the meaning associations between words (semantic coherence). Finally, in contrast with accounts positing that the default mode network (DMN) may have a crucial role in semantic cognition, our findings revealed that DMN activity was sensitive to task difficulty, but not to semantic integration. The implications of these findings for neurocognitive models of semantic cognition and the literature on narrative processing are discussed.