The study of the brain is a compelling example of the power of convergent science. Over the last few decades, advances in neuroscience techniques and experimentation, as well as in data science tools to analyze the resulting data, have dramatically furthered our understanding of fundamental brain functions. Historically, it has been common for analytical approaches to have a considerable lag in development following the availability of new neuroscience techniques. However, this relationship has not simply been unidirectional, as there have been examples in which analytical developments have directly led to new scientific questions and experiments. Here we review how this interplay between neuroscience and data science advances has unfolded in the past and into the present, with a focus on electrophysiology and calcium imaging. Applying lessons learned from the past and present, we then discuss expected developments, challenges, and opportunities in the future. We end by providing recommendations on how to foster the necessary team science approach to continue the advancement of research at the intersection of neuroscience and data science, which we call neurodatascience, toward a sustainable future.
INTRODUCTION: Treatment indications for oligometastatic/oligoprogressive lung tumors are growing. Safety and lack of detrimental effect on patients' quality of life are critical for novel local therapies. METHODS: We tested that the additive effect of pulsed electric field (PEF) ablation with lower-dose stereotactic body radiation therapy (SBRT) on health-related quality of life (HRQoL) as a secondary endpoint in a prospective clinical trial. FACT-Lung Cancer Subscale (FACT-LCS) and FACT-General domain surveys were collected at screening, 3 months, and 12 months. Functional clinical data included forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and diffusing capacity of the lung for carbon monoxide (DLCO). RESULTS: Six patients with eight tumors were enrolled. Baseline well-being domain scores were: Physical 25.9 (Std Dev 2.3), Social 21.0 (Std Dev 6.9), Emotional 17.3 (Std Dev 4.7), Functional 21.2 (Std Dev 5.8), and LCS 19.4 (Std Dev 5.3). There were no significant changes following combined modality treatment in HRQoL domain scores or pulmonary function metrics after treatment. Lower EWB and SWB were associated with worse FVC and FEV1. CONCLUSION: In this small pilot study, no clinically meaningful declines in pulmonary function or patient-reported quality of life were observed at 3 months following combination therapy.
[This corrects the article DOI: 10.1016/j.fsisyn.2026.100675.].
Introduction: Quantifying the impacts of armed conflict on civilians and infrastructure remains a major challenge, particularly where reporting is limited. Most conflict measurement tools require affected populations to report events and are limited by short time series, under-reporting, and varying methods. These tools do not capture infrastructural rebuilding, which has important health implications. Given this, we demonstrate the utility of nighttime lights (NTL) as a complementary tool for measuring conflict dynamics and infrastructure recovery with an epidemiological application. Methods: We used monthly NASA Black Marble data to analyze NTL patterns in Yemen (2012–2022) and Ukraine (2019–2024) before and after the onset of large-scale military operations. We calculated month-specific NTL ratios relative to pre-event baselines and assessed the alignment of structural breakpoints, identified using BFAST methods, with aerial attack onset. Generalized additive models were used to measure the relationship between NTL and aerial attacks while accounting for the built environment, population, diesel price (Yemen), and spatiotemporal factors. Finally, we applied NTL to an existing model on the association between conflict, measured via air raids, and cholera in Yemen by replacing the original conflict categories with ones defined by NTL and included a variable for NTL recovery. Results: Mean NTL declined by 53.3% in Yemen and 21.0% in Ukraine following conflict escalation, with detected breakpoints aligning with aerial attack onset in 85.7% of Yemeni governorates and 51.9% of Ukrainian oblasts. Generalized additive models showed that attacks were significantly associated with NTL reductions, independent of built environment factors. Incorporating NTL-based conflict measures into a cholera transmission model for Yemen produced results consistent with attack-based models and found that light recovery was associated with reduced disease risk. Discussion: NTL is a viable tool for measuring conflict and can offer insights on dynamics that are not present in standard tools while avoiding many of these tools’ limitations. These data have epidemiological applications and can be a proxy for important events affecting transmission dynamics. While event-based tools have vast utility, NTL can complement them with specific strengths and means of application.
BACKGROUND: Machine learning methods employing neuroimaging data are useful for monitoring the activation of neural representations. Specifically, they can be used to discern the brain networks engaged in processing specific categories of items. This approach has been employed on neuroimaging data, including functional magnetic resonance imaging data and electroencephalography (EEG) data. NEW METHOD: Here, we present a task and an analytical pipeline for investigating category representations using EEG. Participants (N = 30) viewed a series of images and words of objects belonging to five categories (Animals, Tools, Food, Scenes, and Vehicles) and responded when items from the same category were presented consecutively. RESULTS: We trained support vector machines on EEG data within participants and found that both image trials and word trials yielded significant category classification accuracy, with image trials achieving higher accuracy than word trials. When comparing categories in a pair-wise fashion, all pairs were statistically distinguishable for image trials, whereas only one pair was distinguishable for word trials. Parietal and left temporal electrodes contributed more to image classification than frontal and right temporal electrodes. Category-specific activity patterns also generalized across participants for image trials. COMPARISON WITH EXISTING METHODS: Our data and analytic pipeline yielded high classification accuracies, primarily for image trials, providing support for the utility of EEG data for neural decoding. CONCLUSIONS: These methods can be instrumental for exploring the activation and reactivation of neural representations at the category level during wakefulness and, potentially, during offline states.
We present a measurement of baryon acoustic oscillations (BAO) in the cross correlation of triply ionized carbon (C iv) absorption with the positions of quasars (QSO) and emission-line galaxies (ELGs). We use quasars and ELGs from the second data release (DR2) of the Dark Energy Spectroscopic Instrument survey. Our data sample consists of 2.5 million quasars, 3.1 million ELGs, and the C iv absorption is measured along the line of sight of 1.5 million high-redshift quasars with z > 1.3. We measure the isotropic BAO signal at 4.2σ for the C IV×QSO cross correlation. This translates into a 3.0% precision measurement of the ratio of the isotropic distance scale, DV, and the sound horizon at the drag epoch, rd, with DV/rd(zeff = 1.92) = 30.3 ± 0.9. We make the first detection of the BAO feature in the C IV×ELG cross-correlation at a significance of 2.5σ and find DV/rd(zeff = 1.47) = 24.6 ± 1.0.
Genetic perturbations are one of the great strengths of the model organism Drosophila melanogaster, with approaches such as classical mutagenesis and RNA interference enabling a wealth of biological discoveries. A more recent approach for altering gene expression is CRISPR/Cas9-based mutagenesis. As with any new tool, however, its use must be optimized. High expression of Cas9 has been shown to cause cytotoxicity in some cell types, including class IV dendritic arborization (da) neurons. In this study, we provide evidence that Cas9 expression causes cytotoxicity in class I da neurons, in addition to class IV da neurons, both of which are widely used to study neuronal development and regeneration. We then systematically evaluated available Cas9 transgenes designed to titrate Cas9 expression, called uCas9 transgenes. We show that the expression of these uCas9 transgenes results in little to no cytotoxicity in various classes of da neurons. Immunostaining revealed drastic reductions in Cas9 protein levels for da neurons expressing the uCas9(L) transgene. Lastly, we demonstrate that the uCas9(L) transgene effectively and specifically gene edits in both class I and class IV da neurons, lowering the expression of GFP-tagged proteins and producing loss-of-function morphological phenotypes when targeting endogenous loci. Thus, we refine the use of CRISPR mutagenesis in Drosophila da neurons through titration of Gal4/UAS-mediated Cas9 expression using existing uCas9 transgenes, a feasible and flexible approach that may be useful for other labs encountering Cas9 cytotoxicity in their own model systems.
We build upon Haueis and Colaço's account in two ways. First, we argue that the backgrounding of metabolism was a pragmatic response to a data granularity problem faced by traditional cognitive modelers. Then, we suggest that equivalence demonstrations offer a promising pathway for incrementally introducing metabolic considerations into extant modeling practice.
The first observation of a new meson state decaying into and a photon is presented using a dataset of collisions at a center-of-mass energy collected by the ATLAS detector at the Large Hadron Collider, corresponding to an integrated luminosity of . The mesons are reconstructed from a three-muon final state from decays, along with photons reconstructed via conversions to electron-positron pairs in the detector material. The new state is observed with a significance that exceeds 8 standard deviations. The mass difference between the new meson state and the ground-state meson is measured to be . This corresponds to a mass for the observed state of , where the last uncertainty is due to the precision of the best knowledge of the meson mass. The low mass difference value matches the theory expectations for the lowest vector state of the system, the meson.
The Lorentz-contracted electromagnetic fields of the ions in ultra-relativistic heavy-ion collisions generate intense quasi-real photon fluxes. These lead to photon-induced interactions that are observed in ultra-peripheral collisions (UPCs), such as vector meson and lepton-pair production. The high photon flux also enables the occurrence of multiple photon-induced processes in a single collision. Presented is the first measurement of the coincident production of γ γ → μ + μ − and γ + A → ρ 0 + A in UPC Pb+Pb collisions at centre-of-mass energies of 5.02 TeV and 5.36 TeV with the ATLAS detector at the Large Hadron Collider. The coincident ρ 0 is identified via its decay into a π + π − pair, with the selected π + π − sample also containing the non-resonant continuum contribution. The rate of the coincident process relative to the exclusive γ γ → μ + μ − process is measured differentially in intervals of forward event activity, quantified by the Zero Degree Calorimeters. The relative rate of coincident ρ 0 production, including non-resonant π + π − contributions, is measured to be ( 9.3 ± 0.4 ( stat . ) ± 0.2 ( syst . ) ) × 10 − 3 , summed over forward event activity. Correlations between the dimuon kinematic properties, such as its mass, and the coincident ρ 0 meson production rate, are also presented. These measurements confirm the presence of multi photon-induced processes in UPC collisions, and can provide new insight into the impact parameter dependence of photon-induced vector meson production.
