For Whom, and for What, is Experience Sampling More Accurate Than Retrospective Report?

The experience sampling method (ESM) is often used in research, and promoted for clinical use, with the rationale that it avoids problematic inaccuracies and biases that attend retrospective measures of mental phenomena. Research suggests that averaged scores from ESM data are more accurate than retrospective ratings. However, it is not known how well individuals can remember information about momentary (rather than averaged) mental states, nor how accurately they estimate the dynamic covariation of these states. Individual differences in retrospective accuracy are also poorly understood. In two pre-registered studies, we examined differences between retrospective memory for stress and self-esteem and data gathered via experience sampling and examined whether alexithymia predicted accuracy. Results of both studies revealed substantial discrepancies between retrospective ratings and ESM ratings, especially for momentary states and their covariation. Alexithymia was positively related to recognition of stress means and variability but unrelated to recall of either stress or self-esteem, their variability, or their covariation. These findings suggest that experience sampling may be more useful than self-report when precise information is needed about the timing of mental states and dynamics among them

The bacterial microbiota regulates normal hematopoiesis via metabolite-induced type 1 interferon signaling

Antibiotic therapy, especially when administered long term, is associated with adverse hematologic effects such as cytopenia. Signals from the intestinal microbiota are critical to maintain normal hematopoiesis, and antibiotics can cause bone marrow suppression through depletion of the microbiota. We reported previously that STAT1 signaling is necessary for microbiota-dependent hematopoiesis, but the precise mechanisms by which the gut microbiota signals to the host bone marrow to regulate hematopoiesis remain undefined. We sought to identify the cell type(s) through which STAT1 promotes microbiota-mediated hematopoiesis and to elucidate which upstream signaling pathways trigger STAT1 signaling. Using conditional knockout and chimeric mice, we found that the microbiota induced STAT1 signaling in non-myeloid hematopoietic cells to support hematopoiesis and that STAT1 signaling was specifically dependent on type I interferons (IFNs). Indeed, basal type I IFN signaling was reduced in hematopoietic progenitor cells with antibiotic treatment. In addition, we discovered that oral administration of a commensal-derived product, NOD1 ligand, rescues the hematopoietic defects induced by antibiotics in mice. Using metabolomics, we identified additional microbially produced candidates that can stimulate type I IFN signaling to potentially rescue the hematopoietic defects induced by antibiotics, including phosphatidylcholine and γ-glutamylalanine. Overall, our studies define a signaling pathway through which microbiota promotes normal hematopoiesis and identify microbial metabolites that may serve as therapeutic agents to ameliorate antibiotic-induced bone marrow suppression and cytopenia

Suppressing Aneuploidy-Associated Phenotypes Improves the Fitness of Trisomy 21 Cells

An abnormal number of chromosomes, or aneuploidy, accounts for most spontaneous abortions, causes developmental defects, and is associated with aging and cancer. The molecular mechanisms by which aneuploidy disrupts cellular function remain largely unknown. Here, we show that aneuploidy disrupts the morphology of the nucleus. Mutations that increase the levels of long-chain bases suppress nuclear abnormalities of aneuploid yeast independent of karyotype identity. Quantitative lipidomics indicates that long-chain bases are integral components of the nuclear membrane in yeast. Cells isolated from patients with Down syndrome also show that abnormal nuclear morphologies and increases in long-chain bases not only suppress these abnormalities but also improve their fitness. We obtained similar results with cells isolated from patients with Patau or Edward syndrome, indicating that increases in long-chain bases improve the fitness of aneuploid cells in yeast and humans. Targeting lipid biosynthesis pathways represents an important strategy to suppress nuclear abnormalities in aneuploidy-associated diseases

The tethering of chromatin to the nuclear envelope supports nuclear mechanics

The nuclear lamina is thought to be the primary mechanical defence of the nucleus. However, the lamina is integrated within a network of lipids, proteins and chromatin; the interdependence of this network poses a challenge to defining the individual mechanical contributions of these components. Here, we isolate the role of chromatin in nuclear mechanics by using a system lacking lamins. Using novel imaging analyses, we observe that untethering chromatin from the inner nuclear membrane results in highly deformable nuclei in vivo, particularly in response to cytoskeletal forces. Using optical tweezers, we find that isolated nuclei lacking inner nuclear membrane tethers are less stiff than wild-type nuclei and exhibit increased chromatin flow, particularly in frequency ranges that recapitulate the kinetics of cytoskeletal dynamics. We suggest that modulating chromatin flow can define both transient and long-lived changes in nuclear shape that are biologically important and may be altered in disease

An open-source deep learning algorithm for efficient and fully-automatic analysis of the choroid in optical coherence tomography

Purpose: To develop an open-source, fully-automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data. Methods: We used a dataset of 715 OCT B-scans (82 subjects, 115 eyes) from 3 clinical studies related to systemic disease. Ground truth segmentations were generated using a clinically validated, semi-automatic choroid segmentation method, Gaussian Process Edge Tracing (GPET). We finetuned a UNet with MobileNetV3 backbone pre-trained on ImageNet. Standard segmentation agreement metrics, as well as derived measures of choroidal thickness and area, were used to evaluate DeepGPET, alongside qualitative evaluation from a clinical ophthalmologist. Results: DeepGPET achieves excellent agreement with GPET on data from 3 clinical studies (AUC=0.9994, Dice=0.9664; Pearson correlation of 0.8908 for choroidal thickness and 0.9082 for choroidal area), while reducing the mean processing time per image on a standard laptop CPU from 34.49s ($\pm$15.09) using GPET to 1.25s ($\pm$0.10) using DeepGPET. Both methods performed similarly according to a clinical ophthalmologist, who qualitatively judged a subset of segmentations by GPET and DeepGPET, based on smoothness and accuracy of segmentations. Conclusions :DeepGPET, a fully-automatic, open-source algorithm for choroidal segmentation, will enable researchers to efficiently extract choroidal measurements, even for large datasets. As no manual interventions are required, DeepGPET is less subjective than semi-automatic methods and could be deployed in clinical practice without necessitating a trained operator. DeepGPET addresses the lack of open-source, fully-automatic and clinically relevant choroid segmentation algorithms, and its subsequent public release will facilitate future choroidal research both in ophthalmology and wider systemic health.Comment: 8 pages, 2 figures, 3 tables. Currently in submission to ARVO TVST (Association for Research in Vision and Ophthalmology, Translational Vision Science & Technology). GitHub link to codebase provided upon publicatio

Lessons Learned from Open-label Deep Brain Stimulation for Tourette Syndrome: Eight Cases over 7 Years

Background: Deep brain stimulation (DBS) remains an experimental but promising treatment for patients with severe refractory Gilles de la Tourette syndrome (TS). Controversial issues include the selection of patients (age and clinical presentation), the choice of brain targets to obtain optimal patient-specific outcomes, and the risk of surgery- and stimulation-related serious adverse events. Methods: This report describes our open-label experience with eight patients with severe refractory malignant TS treated with DBS. The electrodes were placed in the midline thalamic nuclei or globus pallidus, pars internus, or both. Tics were clinically assessed in all patients pre- and postoperatively using the Modified Rush Video Protocol and the Yale Global Tic Severity Scale (YGTSS). Results: Although three patients had marked postoperative improvement in their tics (>50% improvement on the YGTSS), the majority did not reach this level of clinical improvement. Two patients had to have their DBS leads removed (one because of postoperative infection and another because of lack of benefit). Discussion Our clinical experience supports the urgent need for more data and refinements in interventions and outcome measurements for severe, malignant, and medication-refractory TS. Because TS is not an etiologically homogenous clinical entity, the inclusion criteria for DBS patients and the choice of brain targets will require more refinement

Choroidalyzer: An open-source, end-to-end pipeline for choroidal analysis in optical coherence tomography

Purpose: To develop Choroidalyzer, an open-source, end-to-end pipeline for segmenting the choroid region, vessels, and fovea, and deriving choroidal thickness, area, and vascular index. Methods: We used 5,600 OCT B-scans (233 subjects, 6 systemic disease cohorts, 3 device types, 2 manufacturers). To generate region and vessel ground-truths, we used state-of-the-art automatic methods following manual correction of inaccurate segmentations, with foveal positions manually annotated. We trained a U-Net deep-learning model to detect the region, vessels, and fovea to calculate choroid thickness, area, and vascular index in a fovea-centred region of interest. We analysed segmentation agreement (AUC, Dice) and choroid metrics agreement (Pearson, Spearman, mean absolute error (MAE)) in internal and external test sets. We compared Choroidalyzer to two manual graders on a small subset of external test images and examined cases of high error. Results: Choroidalyzer took 0.299 seconds per image on a standard laptop and achieved excellent region (Dice: internal 0.9789, external 0.9749), very good vessel segmentation performance (Dice: internal 0.8817, external 0.8703) and excellent fovea location prediction (MAE: internal 3.9 pixels, external 3.4 pixels). For thickness, area, and vascular index, Pearson correlations were 0.9754, 0.9815, and 0.8285 (internal) / 0.9831, 0.9779, 0.7948 (external), respectively (all p<0.0001). Choroidalyzer's agreement with graders was comparable to the inter-grader agreement across all metrics. Conclusions: Choroidalyzer is an open-source, end-to-end pipeline that accurately segments the choroid and reliably extracts thickness, area, and vascular index. Especially choroidal vessel segmentation is a difficult and subjective task, and fully-automatic methods like Choroidalyzer could provide objectivity and standardisation