Survey of spiking in the mouse visual system reveals functional hierarchy.

The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically1. However, direct observation of cellular-level functional interactions across this hierarchy is lacking due to the challenge of simultaneously recording activity across numerous regions. Here we describe a large, open dataset-part of the Allen Brain Observatory2-that surveys spiking from tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli. Using cross-correlation analysis, we reveal that the organization of inter-area functional connectivity during visual stimulation mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas3. We find that four classical hierarchical measures-response latency, receptive-field size, phase-locking to drifting gratings and response decay timescale-are all correlated with the hierarchy. Moreover, recordings obtained during a visual task reveal that the correlation between neural activity and behavioural choice also increases along the hierarchy. Our study provides a foundation for understanding coding and signal propagation across hierarchically organized cortical and thalamic visual areas.

The Transcription Factor Zfp335 Promotes Differentiation and Survival of Effector Th1 Cells by Directly Regulating Lmna Expression.

Ag-specific effector CD4+ T cells play a crucial role in defending against exogenous pathogens. However, the mechanisms governing the differentiation and function of IFN-γ-producing effector CD4+ Th1 cells in immune responses remain largely unknown. In this study, we elucidated the pivotal role of zinc finger protein 335 (Zfp335) in regulating effector Th1 cell differentiation and survival during acute bacterial infection. Mice with Zfp335 knockout in OT-II cells exhibited impaired Ag-specific CD4+ T cell expansion accompanied by a significant reduction in resistance to Listeria infection. Furthermore, Zfp335 deficiency restricted the effector CD4+ Th1 cell population and compromised their survival upon Listeria challenge. The expression of T-bet and IFN-γ was accordingly decreased in Zfp335-deficient Th1 cells. Mechanistically, Zfp335 directly bound to the promoter region of the Lmna gene and regulated its expression. Overexpression of Lmna was able to rescue the survival and function of Zfp335-deficient effector Th1 cells. Therefore, our study provides novel insights into the mechanisms governing effector Th1 cell differentiation and survival during acute infection.

A Machine Learning-Based Unenhanced Radiomics Approach to Distinguishing Between Benign and Malignant Breast Lesions Using T2-Weighted and Diffusion-Weighted MRI.

BACKGROUND: Breast MRI has been recommended as supplemental screening tool to mammography and breast ultrasound of breast cancer by international guidelines, but its long examination time and use of contrast material remains concerning. PURPOSE: To develop an unenhanced radiomics model with using non-gadolinium based sequences for detecting breast cancer based on T2-weighted (T2W) and diffusion-weighted (DW) MRI. STUDY TYPE: Retrospective analysis followed by retrospective and prospective cohorts study. POPULATION: 1760 patients: Of these, 1293 for model construction (n = 775 for training and 518 for validation). The remaining patients for model testing in internal retrospective (n = 167), internal prospective (n = 188), and external retrospective (n = 112) cohorts. FIELD STRENGTH/SEQUENCE: 3.0T MR scanners from two institution. T2WI, DWI, and first contrast-enhanced T1-weighted sequence. ASSESSMENT: AUCs in distinguishing breast cancer were compared between combined model with gadolinium agent sequence and unenhanced model. Subsequently, the AUCs in testing cohorts of unenhanced model was compared with two radiologists' diagnosis for this research. Finally, patient subgroup analysis in testing cohorts was performed based on clinical subgroups and different types of malignancies. STATISTICAL TESTS: Mann-Whitney U test, Kruskal-Wallis H test, chi-square test, weighted kappa test, and DeLong's test. RESULTS: The unenhanced radiomics model performed best under Gaussian process (GP) classifiers (AUC: training, 0.893; validation, 0.848) compared to support vector machine (SVM) and logistic, showing favorable prediction in testing cohorts (AUCs, 0.818-0.840). The AUCs for the unenhanced radiomics model were not statistically different in five cohorts from those of the combined radiomics model (P, 0.317-0.816), as well as the two radiologists (P, 0.181-0.918). The unenhanced radiomics model was least successful in identifying ductal carcinoma in situ, whereas did not show statistical significance in other subgroups. DATA CONCLUSION: An unenhanced radiomics model based on T2WI and DWI has comparable diagnostic accuracy to the combined model using the gadolinium agent. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Risk stratification for 1- to 2-cm gastric gastrointestinal stromal tumors: visual assessment of CT and EUS high-risk features versus CT radiomics analysis.

OBJECTIVES: To investigate the ability of CT and endoscopic sonography (EUS) in predicting the malignant risk of 1-2-cm gastric gastrointestinal stromal tumors (gGISTs) and to clarify whether radiomics could be applied for risk stratification. METHODS: A total of 151 pathologically confirmed 1-2-cm gGISTs from seven institutions were identified by contrast-enhanced CT scans between January 2010 and March 2021. A detailed description of EUS morphological features was available for 73 gGISTs. The association between EUS or CT high-risk features and pathological malignant potential was evaluated. gGISTs were randomly divided into three groups to build the radiomics model, including 74 in the training cohort, 37 in validation cohort, and 40 in testing cohort. The ROIs covering the whole tumor volume were delineated on the CT images of the portal venous phase. The Pearson test and least absolute shrinkage and selection operator (LASSO) algorithm were used for feature selection, and the ROC curves were used to evaluate the model performance. RESULTS: The presence of EUS- and CT-based morphological high-risk features, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not differ between very-low and intermediate risk 1-2-cm gGISTs (p > 0.05). The radiomics model consisting of five radiomics features showed favorable performance in discrimination of malignant 1-2-cm gGISTs, with the AUC of the training, validation, and testing cohort as 0.866, 0.812, and 0.766, respectively. CONCLUSIONS: Instead of CT- and EUS-based morphological high-risk features, the CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs. KEY POINTS: • The presence of EUS- and CT-based morphological high-risk factors, including calcification, necrosis, intratumoral heterogeneity, irregular border, or surface ulceration, did not correlate with the pathological malignant potential of 1-2-cm gGISTs. • The CT radiomics model could potentially be applied for preoperative risk stratification of 1-2-cm gGISTs.

Quantitative proteomics analysis of chicken embryos reveals key proteins that affect right gonadal degeneration in females.

In birds, embryonic gonads of females develop in a way different from mammals, with the left one develops into a functional ovary, while the right one degenerates during embryogenesis. Here, we examined the proteomics profiles of the female and male left and right gonads at embryonic day 6.5 (E6.5) with the label free tandem mass spectrometry proteomics technique. The relative protein abundance of the left and right gonads of female and male embryos was determined to identify their differential proteins. Overall, a total of 7726 proteins were identified, of which 79 and 54 proteins were significantly different in female and male right gonads compared with female left gonads and male left gonads respectively. Bioinformatics analysis showed that the proteins DMRT1, ZFPM2, TSHZ3 were potentially associated with the degeneration of the right gonads in female embryos. The proteomics in this study provide clues for further elucidation of the pathways of sex determination, sex differentiation, and right gonadal degeneration in birds.

High-density extracellular probes reveal dendritic backpropagation and facilitate neuron classification.

Different neuron types serve distinct roles in neural processing. Extracellular electrical recordings are extensively used to study brain function but are typically blind to cell identity. Morphoelectrical properties of neurons measured on spatially dense electrode arrays have the potential to distinguish neuron types. We used high-density silicon probes to record from cortical and subcortical regions of the mouse brain. Extracellular waveforms of each neuron were detected across many channels and showed distinct spatiotemporal profiles among brain regions. Classification of neurons by brain region was improved with multichannel compared with single-channel waveforms. In visual cortex, unsupervised clustering identified the canonical regular-spiking (RS) and fast-spiking (FS) classes but also indicated a subclass of RS units with unidirectional backpropagating action potentials (BAPs). Moreover, BAPs were observed in many hippocampal RS cells. Overall, waveform analysis of spikes from high-density probes aids neuron identification and can reveal dendritic backpropagation. NEW & NOTEWORTHY It is challenging to identify neuron types with extracellular electrophysiology in vivo. We show that spatiotemporal action potentials measured on high-density electrode arrays can capture cell type-specific morphoelectrical properties, allowing classification of neurons across brain structures and within the cortex. Moreover, backpropagating action potentials are reliably detected in vivo from subpopulations of cortical and hippocampal neurons. Together, these results enhance the utility of dense extracellular electrophysiology for cell-type interrogation of brain network function.

MRI for Restaging Locally Advanced Rectal Cancer: Detailed Analysis of Discrepancies With the Pathologic Reference Standard.

OBJECTIVE. The purpose of this study was to analyze causes of discrepancies between restaging MRI and pathologic findings in the assessment of morphologic indicators of tumor response in patients with rectal cancer who have undergone neoadjuvant treatment. MATERIALS AND METHODS. MRI and pathologic data from 57 consecutively registered patients who underwent neoadjuvant treatment and total mesorectal excision between August 2015 and July 2018 were retrospectively analyzed. The sensitivity and specificity of restaging MRI in determining tumor regression grade, T category, N category, circumferential resection margin, and extramural vascular invasion were calculated with pathologic results as the reference standard. One-by-one comparisons between MRI and pathologic findings were conducted to identify causes of discrepancies. RESULTS. The sensitivity of MRI in determining tumor regression grades 3-5 was 77.1%; T3 and T4 category, 100.0%; node-positive disease, 75.0%; circumferential resection margin, 87.5%; and extramural vascular invasion, 91.7%. The specificity values were 72.7%, 62.5%, 70.7%, 85.7%, and 64.4%. Overstaging was mainly caused by misinterpretation of fibrotic areas as residual tumor. Inflammatory cell infiltration could appear as high signal intensity in fibrotic areas on DW images, an appearance similar to that of residual tumor. Edematous mucosa and submucosa adjacent to the tumor and muscularis propria could also be mistaken for residual tumor because of their intermediate signal intensity on T2-weighted MR images. CONCLUSION. MRI was prone to overstaging of disease. Discrepancies between MRI and pathologic findings were mainly caused by misinterpretation of fibrosis. Inflammatory cell infiltration, pure mucin, edematous mucosa and submucosa adjacent to the tumor, and muscularis propria could also be misinterpreted as residual tumor.

Low- Versus High-Risk Rectal Cancer Based on MRI Features: Outcomes in Patients Treated Without Neoadjuvant Chemoradiotherapy.

OBJECTIVE: The objective of this study was to compare the prognoses of patients with low- and high-risk rectal cancer detected by MRI who were treated without neoadjuvant chemoradiotherapy (NCRT) and to determine independent risk factors. MATERIALS AND METHODS: This retrospective study included 185 patients with pathologically proven rectal adenocarcinoma who were treated without NCRT. Cancer was defined as high risk if one or more of the following factors were present: extramural depth of tumor invasion greater than 5 mm or stage T4a or T4b for tumor in the mid or high rectum; involvement of intersphincteric space, levators, or adjacent organs for tumor in the low rectum; extramural venous invasion (EMVI); or circumferential resection margin (CRM) involvement. Patients without any of those risk factors were placed in the low-risk group. The Kaplan-Meier method and Cox proportional hazards regression model were used to compare the survival outcomes between the two groups and to investigate the univariate and multivariate influences of the risk factors. RESULTS: Cancer was deemed to be low risk in 65 (35.1%) patients and high risk in 120 (64.9%) patients. The two patient groups had statistically significant differences in 3-year actuarial overall survival (OS; 100% vs 88.3%, p = 0.0044), disease-free survival (DFS; 92.3% vs 60.0%, p < 0.0001), and local recurrence (LR; 1.5% vs 10.0%, p = 0.0297). CRM involvement was identified as an independent risk factor for OS (hazard ratio [HR], 4.78; 95% CI, 1.24-18.45), DFS (HR, 2.44; 95% CI, 1.24-4.81), and LR (HR, 3.92; 95% CI, 1.07-14.41). Moreover, EMVI was identified as an independent risk factor for DFS (HR, 2.46; 95% CI, 1.28-4.74). CONCLUSION: The LR and long-term survival of patients in the low-risk group were more favorable than those of patients in the high-risk group. EMVI and CRM status were independent risk factors.

No consistent relationship between gamma power and peak frequency in macaque primary visual cortex.

Neural activity in the gamma frequency range ("gamma") is elevated during active cognitive states. Gamma has been proposed to play an important role in cortical function, although this is debated. Understanding what function gamma might fulfill requires a better understanding of its properties and the mechanisms that generate it. Gamma is characterized by its spectral power and peak frequency, and variations in both parameters have been associated with changes in behavioral performance. Modeling studies suggest these properties are co-modulated, but this has not been established. To test the relationship between these properties, we measured local field potentials (LFPs) and neuronal spiking responses in primary visual cortex of anesthetized monkeys, for drifting sinusoidal gratings of different sizes, contrasts, orientations and masked with different levels of noise. We find that there is no fixed relationship between LFP gamma power and peak frequency, and neither is related to the strength of spiking activity. We propose a simple model that can account for the complex stimulus dependence we observe, and suggest that separate mechanisms determine gamma power and peak frequency.

Stimulus type shapes the topology of cellular functional networks in mouse visual cortex.

On the timescale of sensory processing, neuronal networks have relatively fixed anatomical connectivity, while functional interactions between neurons can vary depending on the ongoing activity of the neurons within the network. We thus hypothesized that different types of stimuli could lead those networks to display stimulus-dependent functional connectivity patterns. To test this hypothesis, we analyzed single-cell resolution electrophysiological data from the Allen Institute, with simultaneous recordings of stimulus-evoked activity from neurons across 6 different regions of mouse visual cortex. Comparing the functional connectivity patterns during different stimulus types, we made several nontrivial observations: (1) while the frequencies of different functional motifs were preserved across stimuli, the identities of the neurons within those motifs changed; (2) the degree to which functional modules are contained within a single brain region increases with stimulus complexity. Altogether, our work reveals unexpected stimulus-dependence to the way groups of neurons interact to process incoming sensory information.

Prediction of macrotrabecular-massive hepatocellular carcinoma by using MR-based models and their prognostic implications.

PURPOSE: To evaluate the efficacy of MRI-based radiomics and clinical models in predicting MTM-HCC. Additionally, to investigate the ability of the radiomics model designed for MTM-HCC identification in predicting disease-free survival (DFS) in patients with HCC. METHODS: A total of 336 patients who underwent oncological resection for HCC between June 2007 and March 2021 were included. 127 patients in Cohort1 were used for MTM-HCC identification, and 209 patients in Cohort2 for prognostic analyses. Radiomics analysis was performed using volumes of interest of HCC delineated on pre-operative MRI images. Radiomics and clinical models were developed using Random Forest algorithm in Cohort1 and a radiomics probability (RP) of MTM-HCC was obtained from the radiomics model. Based on the RP, patients in Cohort2 were divided into a RAD-MTM-HCC (RAD-M) group and a RAD-non-MTM-HCC (RAD-nM) group. Univariate and multivariate Cox regression analyses were employed to identify the independent predictors for DFS of patients in Cohort2. Kaplan-Meier curves were used to compare the DFS between different groups pf patients based on the predictors. RESULTS: The radiomics model for identifying MTM-HCC showed AUCs of 0.916 (95% CI: 0.858-0.960) and 0.833 (95% CI: 0.675-0.935), and the clinical model showed AUCs of 0.760 (95% CI: 0.669-0.836) and 0.704 (95% CI: 0.532-0.843) in the respective training and validation sets. Furthermore, the radiomics biomarker RP, portal or hepatic vein tumor thrombus, irregular rim-like arterial phase hyperenhancement (IRE) and AFP were independent predictors of DFS in patients with HCC. The DFS of RAD-nM group was significantly higher than that of the RAD-M group (p < .001). CONCLUSION: MR-based clinical and radiomic models have the potential to accurately diagnose MTM-HCC. Moreover, the radiomics signature designed to identify MTM-HCC also can be used to predict prognosis in patients with HCC, realizing the diagnostic and prognostic aims at the same time.

Targeting a disintegrin and metalloprotease (ADAM) 17-CD122 axis enhances CD8+ T cell effector differentiation and anti-tumor immunity.

CD8+ T cell immune responses are regulated by multi-layer networks, while the post-translational regulation remains largely unknown. Transmembrane ectodomain shedding is an important post-translational process orchestrating receptor expression and signal transduction through proteolytic cleavage of membrane proteins. Here, by targeting the sheddase A Disintegrin and Metalloprotease (ADAM)17, we defined a post-translational regulatory mechanism mediated by the ectodomain shedding in CD8+ T cells. Transcriptomic and proteomic analysis revealed the involvement of post-translational regulation in CD8+ T cells. T cell-specific deletion of ADAM17 led to a dramatic increase in effector CD8+ T cell differentiation and enhanced cytolytic effects to eliminate pathogens and tumors. Mechanistically, ADAM17 regulated CD8+ T cells through cleavage of membrane CD122. ADAM17 inhibition led to elevated CD122 expression and enhanced response to IL-2 and IL-15 stimulation in both mouse and human CD8+ T cells. Intriguingly, inhibition of ADAM17 in CD8+ T cells improved the efficacy of chimeric antigen receptor (CAR) T cells in solid tumors. Our findings reveal a critical post-translational regulation in CD8+ T cells, providing a potential therapeutic strategy of targeting ADAM17 for effective anti-tumor immunity.

A ubiquitous spectrolaminar motif of local field potential power across the primate cortex.

The mammalian cerebral cortex is anatomically organized into a six-layer motif. It is currently unknown whether a corresponding laminar motif of neuronal activity patterns exists across the cortex. Here we report such a motif in the power of local field potentials (LFPs). Using laminar probes, we recorded LFPs from 14 cortical areas across the cortical hierarchy in five macaque monkeys. The laminar locations of recordings were histologically identified by electrolytic lesions. Across all areas, we found a ubiquitous spectrolaminar pattern characterized by an increasing deep-to-superficial layer gradient of high-frequency power peaking in layers 2/3 and an increasing superficial-to-deep gradient of alpha-beta power peaking in layers 5/6. Laminar recordings from additional species showed that the spectrolaminar pattern is highly preserved among primates-macaque, marmoset and human-but more dissimilar in mouse. Our results suggest the existence of a canonical layer-based and frequency-based mechanism for cortical computation.

Ultra-high density electrodes improve detection, yield, and cell type identification in neuronal recordings.

To understand the neural basis of behavior, it is essential to sensitively and accurately measure neural activity at single neuron and single spike resolution. Extracellular electrophysiology delivers this, but it has biases in the neurons it detects and it imperfectly resolves their action potentials. To minimize these limitations, we developed a silicon probe with much smaller and denser recording sites than previous designs, called Neuropixels Ultra (NP Ultra). This device samples neuronal activity at ultra-high spatial density (~10 times higher than previous probes) with low noise levels, while trading off recording span. NP Ultra is effectively an implantable voltage-sensing camera that captures a planar image of a neuron's electrical field. We use a spike sorting algorithm optimized for these probes to demonstrate that the yield of visually-responsive neurons in recordings from mouse visual cortex improves up to ~3-fold. We show that NP Ultra can record from small neuronal structures including axons and dendrites. Recordings across multiple brain regions and four species revealed a subset of extracellular action potentials with unexpectedly small spatial spread and axon-like features. We share a large-scale dataset of these brain-wide recordings in mice as a resource for studies of neuronal biophysics. Finally, using ground-truth identification of three major inhibitory cortical cell types, we found that these cell types were discriminable with approximately 75% success, a significant improvement over lower-resolution recordings. NP Ultra improves spike sorting performance, detection of subcellular compartments, and cell type classification to enable more powerful dissection of neural circuit activity during behavior.

Laminar dependence of neuronal correlations in visual cortex.

Neuronal responses are correlated on a range of timescales. Correlations can affect population coding and may play an important role in cortical function. Correlations are known to depend on stimulus drive, behavioral context, and experience, but the mechanisms that determine their properties are poorly understood. Here we make use of the laminar organization of cortex, with its variations in sources of input, local circuit architecture, and neuronal properties, to test whether networks engaged in similar functions but with distinct properties generate different patterns of correlation. We find that slow timescale correlations are prominent in the superficial and deep layers of primary visual cortex (V1) of macaque monkeys, but near zero in the middle layers. Brief timescale correlation (synchrony), on the other hand, was slightly stronger in the middle layers of V1, although evident at most cortical depths. Laminar variations were also apparent in the power of the local field potential, with a complementary pattern for low frequency (<10 Hz) and gamma (30-50 Hz) power. Recordings in area V2 revealed a laminar dependence similar to V1 for synchrony, but slow timescale correlations were not different between the input layers and nearby locations. Our results reveal that cortical circuits in different laminae can generate remarkably different patterns of correlations, despite being tightly interconnected.

Stimulus-dependent functional network topology in mouse visual cortex.

Information is processed by networks of neurons in the brain. On the timescale of sensory processing, those neuronal networks have relatively fixed anatomical connectivity, while functional connectivity, which defines the interactions between neurons, can vary depending on the ongoing activity of the neurons within the network. We thus hypothesized that different types of stimuli, which drive different neuronal activities in the network, could lead those networks to display stimulus-dependent functional connectivity patterns. To test this hypothesis, we analyzed electrophysiological data from the Allen Brain Observatory, which utilized Neuropixels probes to simultaneously record stimulus-evoked activity from hundreds of neurons across 6 different regions of mouse visual cortex. The recordings had single-cell resolution and high temporal fidelity, enabling us to determine fine-scale functional connectivity. Comparing the functional connectivity patterns observed when different stimuli were presented to the mice, we made several nontrivial observations. First, while the frequencies of different connectivity motifs (i.e., the patterns of connectivity between triplets of neurons) were preserved across stimuli, the identities of the neurons within those motifs changed. This means that functional connectivity dynamically changes along with the input stimulus, but does so in a way that preserves the motif frequencies. Secondly, we found that the degree to which functional modules are contained within a single brain region (as opposed to being distributed between regions) increases with increasing stimulus complexity. This suggests a mechanism for how the brain could dynamically alter its computations based on its inputs. Altogether, our work reveals unexpected stimulus-dependence to the way groups of neurons interact to process incoming sensory information.

Prolonged fasting induces significant germ cell loss in chickens after hatching.

Germ cell loss is a crucial biological event during germ cell development. The number of female germ cells determines the reproductive performance and egg production of hens. Various intrinsic and extrinsic factors affect germ cell loss, such as germ cell nest breakdown in early life and nutritional deficiencies during daily husbandry. Here, we examined the effect of fasting on the germ cell number of chicks. The results showed that 72 h fasting resulted in a higher germ cell loss than that by 24 h fasting in chicks. The RNA-seq analysis revealed that the genes of ribosome pathway were down-regulated and the biological processes of protein processing in endoplasmic reticulum were inhibited in starved chicks. Furthermore, in female chicks treated with 72 h fasting, the qPCR of ovaries showed down-regulation of ribosome-related genes, and transmission electron microscopy imaging of ovaries showed fewer ribosomes. The blood biochemical indices indicated that 72 h fasting reduced the liver functions and affected the glucose metabolism, lipid metabolites and ion metabolites. In summary, the present results concluded negative impacts on the germ cell pool by prolonged fasting in the early life of chicks and manifested that adequate management should be cared for fasted time for breeding.

Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex.

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

Associations between in vitro , in vivo and in silico cell classes in mouse primary visual cortex.

The brain consists of many cell classes yet in vivo electrophysiology recordings are typically unable to identify and monitor their activity in the behaving animal. Here, we employed a systematic approach to link cellular, multi-modal in vitro properties from experiments with in vivo recorded units via computational modeling and optotagging experiments. We found two one-channel and six multi-channel clusters in mouse visual cortex with distinct in vivo properties in terms of activity, cortical depth, and behavior. We used biophysical models to map the two one- and the six multi-channel clusters to specific in vitro classes with unique morphology, excitability and conductance properties that explain their distinct extracellular signatures and functional characteristics. These concepts were tested in ground-truth optotagging experiments with two inhibitory classes unveiling distinct in vivo properties. This multi-modal approach presents a powerful way to separate in vivo clusters and infer their cellular properties from first principles.

Zfp335 establishes eTreg lineage and neonatal immune tolerance by targeting Hadha-mediated fatty acid oxidation.

Regulatory T cells (Tregs) are instrumental in maintaining immune tolerance and preventing destructive autoimmunity, but how heterogeneous Treg populations are established remains largely unknown. Here, we show that Zfp335 deletion in Tregs failed to differentiate into effector Tregs (eTregs) and lose Treg-suppressive function and that KO mice exhibited early-onset lethal autoimmune inflammation with unrestricted activation of conventional T cells. Single-cell RNA-Seq analyses revealed that Zfp335-deficient Tregs lacked a eTreg population and showed dramatic accumulation of a dysfunctional Treg subset. Mechanistically, Zfp335-deficient Tregs displayed reduced oxidative phosphorylation and dysfunctional mitochondrial activity. Further studies revealed that Zfp335 controlled eTreg differentiation by regulating fatty acid oxidation (FAO) through direct targeting of the FAO enzyme Hadha. Importantly, we demonstrate a positive correlation between ZNF335 and HADHA expression in human eTregs. Our findings reveal that Zfp335 controls FAO-driven eTreg differentiation to establish immune tolerance.