Age Effects in L2 Grammar Processing as Revealed by ERPs and How (Not) to Study Them

In this study we investigate the effect of age of acquisition (AoA) on grammatical processing in second language learners as measured by event-related brain potentials (ERPs). We compare a traditional analysis involving the calculation of averages across a certain time window of the ERP waveform, analyzed with categorical groups (early vs. late), with a generalized additive modeling analysis, which allows us to take into account the full range of variability in both AoA and time. Sixty-six Slavic advanced learners of German listened to German sentences with correct and incorrect use of non-finite verbs and grammatical gender agreement. We show that the ERP signal depends on the AoA of the learner, as well as on the regularity of the structure under investigation. For gender agreement, a gradual change in processing strategies can be shown that varies by AoA, with younger learners showing a P600 and older learners showing a posterior negativity. For verb agreement, all learners show a P600 effect, irrespective of AoA. Based on their behavioral responses in an offline grammaticality judgment task, we argue that the late learners resort to computationally less efficient processing strategies when confronted with (lexically determined) syntactic constructions different from the L1. In addition, this study highlights the insights the explicit focus on the time course of the ERP signal in our analysis framework can offer compared to the traditional analysis

Mechanism of ribosome shutdown by RsfS in Staphylococcus aureus revealed by integrative structural biology approach.

Funder: The Russian Government Program of Competitive Growth of Kazan Federal UniversityFor the sake of energy preservation, bacteria, upon transition to stationary phase, tone down their protein synthesis. This process is favored by the reversible binding of small stress-induced proteins to the ribosome to prevent unnecessary translation. One example is the conserved bacterial ribosome silencing factor (RsfS) that binds to uL14 protein onto the large ribosomal subunit and prevents its association with the small subunit. Here we describe the binding mode of Staphylococcus aureus RsfS to the large ribosomal subunit and present a 3.2 Å resolution cryo-EM reconstruction of the 50S-RsfS complex together with the crystal structure of uL14-RsfS complex solved at 2.3 Å resolution. The understanding of the detailed landscape of RsfS-uL14 interactions within the ribosome shed light on the mechanism of ribosome shutdown in the human pathogen S. aureus and might deliver a novel target for pharmacological drug development and treatment of bacterial infections

Basal cutaneous pain threshold in headache patients

The aim of this study was to analyze cutaneous pain threshold (CPT) during the interictal phase in headache patients, and the relationships between headache frequency and analgesic use. A consecutive series of 98 headache patients and 26 sex- and age-balanced controls were evaluated. Acute allodynia (AA) was assessed by Jakubowski questionnaire, and interictal allodynia (IA) by a skin test with calibrated monofilaments. AA is widely known as a symptom more present in migraine than in TTH spectrum: in our study this was confirmed only in cases of episodic attacks. When headache index rises towards chronicization, the prevalence of AA increases in both headache spectrums (χ2 13.55; p < 0.01). AA was associated with IA only in cases of chronic headache. When headache becomes chronic, mostly in presence of medication overuse, interictal CPT decreases and IA prevalence increases (χ2 20.44; p < 0.01), with closer association than AA. In MOH patients there were no significant differences depending on the diagnosis of starting headache (migraine or tension type headache) and, in both groups, we found the overuse of analgesics plays an important role: intake of more than one daily drug dramatically reduces the CPT (p < 0.05). Thus, when acute allodynia increases frequency, worsens or appears for the first time in patients with a long-standing history of chronic headache, it could reasonably suggest that the reduction of CPT had started, without using a specific practical skin test but simply by questioning clinical headache history. In conclusion, these results indicate that the role of medication overuse is more important than chronicization in lowering CPT, and suggest that prolonged periods of medication overuse can interfere with pain perception by a reduction of the pain threshold that facilitates the onset of every new attack leading to chronicization

The impact of language co-activation on L1 and L2 speech fluency

Fluent speech depends on the availability of well-established linguistic knowledge and routines for speech planning and articulation. A lack of speech fluency in late second-language (L2) learners may point to a deficiency of these representations, due to incomplete acquisition. Experiments on bilingual language processing have shown, however, that there are strong reasons to believe that multilingual speakers experience co-activation of the languages they speak. We have studied to what degree language co-activation affects fluency in the speech of bilinguals, comparing a monolingual German control group with two bilingual groups: 1) first-language (L1) attriters, who have fully acquired German before emigrating to an L2 English environment, and 2) immersed L2 learners of German (L1: English). We have analysed the temporal fluency and the incidence of disfluency markers (pauses, repetitions and self-corrections) in spontaneous film retellings. Our findings show that learners to speak more slowly than controls and attriters. Also, on each count, the speech of at least one of the bilingual groups contains more disfluency markers than the retellings of the control group. Generally speaking, both bilingual groups-learners and attriters-are equally (dis)fluent and significantly more disfluent than the monolingual speakers. Given that the L1 attriters are unaffected by incomplete acquisition, we interpret these findings as evidence for language competition during speech production

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14