The Language Network Reliably "Tracks" Naturalistic Meaningful Nonverbal Stimuli.

The language network, comprised of brain regions in the left frontal and temporal cortex, responds robustly and reliably during language comprehension but shows little or no response during many nonlinguistic cognitive tasks (e.g., Fedorenko & Blank, 2020). However, one domain whose relationship with language remains debated is semantics-our conceptual knowledge of the world. Given that the language network responds strongly to meaningful linguistic stimuli, could some of this response be driven by the presence of rich conceptual representations encoded in linguistic inputs? In this study, we used a naturalistic cognition paradigm to test whether the cognitive and neural resources that are responsible for language processing are also recruited for processing semantically rich nonverbal stimuli. To do so, we measured BOLD responses to a set of ∼5-minute-long video and audio clips that consisted of meaningful event sequences but did not contain any linguistic content. We then used the intersubject correlation (ISC) approach (Hasson et al., 2004) to examine the extent to which the language network "tracks" these stimuli, that is, exhibits stimulus-related variation. Across all the regions of the language network, meaningful nonverbal stimuli elicited reliable ISCs. These ISCs were higher than the ISCs elicited by semantically impoverished nonverbal stimuli (e.g., a music clip), but substantially lower than the ISCs elicited by linguistic stimuli. Our results complement earlier findings from controlled experiments (e.g., Ivanova et al., 2021) in providing further evidence that the language network shows some sensitivity to semantic content in nonverbal stimuli.

Menstrual attitudes in adult women: A cross-sectional study on the association with menstruation factors, contraceptive use, genital self-image, and sexual openness.

BACKGROUND: Menstruation is a central part of the everyday life of most women, and menstrual attitudes may impact health and well-being. OBJECTIVES: This article aimed to map menstrual attitudes among adult women and examine factors associated with these attitudes, such as aspects of menarche and current menstruation, and rarely studied factors, such as genital self-image and sexual openness. STUDY DESIGN: A cross-sectional online survey. METHOD: A sample of 1470 women, aged 18-50 years, were recruited through social media sites. The Menstrual Self-Evaluation Scale was used to measure three different attitudes: menstruation as natural, shameful, and bothersome. Multiple linear regression analysis was used to investigate the relationship between each attitude and factors related to menarche and current menstruation, contraceptive use, genital self-image (assessed by Female Genital Self-Image Scale), and sexual openness (Personal Comfort with Sexuality Scale). Sociodemographic variables were included into the models as covariates. RESULTS: Agreeing with the attitude of menstruation as something natural was predicted primarily by positive emotions at menarche, experiencing less menstrual pain, using no or nonhormonal contraception, and having a positive genital self-image. Perceiving menstruation as bothersome was predicted by a lower educational level, experiencing stronger menstrual pain, having more perimenstrual psychological symptoms, and using hormonal contraceptives. Menstruation as something shameful was chiefly predicted by lower sexual openness and a negative genital self-image. CONCLUSION: Many women held attitudes about menstruation as both something natural and bothersome. Menarche and current menstruation experiences, and contraceptive method, played central roles in shaping attitudes toward menstruation as natural and bothersome. Viewing menstruation as shameful stood out from other attitudes by indicating a triad of self-objectified shame that includes menstruation, sexuality, and genital self-image. Further research into the relationships between menstruation, contraceptive use, sexuality, and body image is needed to enhance our understanding of women's menstrual health.

The language network as a natural kind within the broader landscape of the human brain.

Language behaviour is complex, but neuroscientific evidence disentangles it into distinct components supported by dedicated brain areas or networks. In this Review, we describe the 'core' language network, which includes left-hemisphere frontal and temporal areas, and show that it is strongly interconnected, independent of input and output modalities, causally important for language and language-selective. We discuss evidence that this language network plausibly stores language knowledge and supports core linguistic computations related to accessing words and constructions from memory and combining them to interpret (decode) or generate (encode) linguistic messages. We emphasize that the language network works closely with, but is distinct from, both lower-level - perceptual and motor - mechanisms and higher-level systems of knowledge and reasoning. The perceptual and motor mechanisms process linguistic signals, but, in contrast to the language network, are sensitive only to these signals' surface properties, not their meanings; the systems of knowledge and reasoning (such as the system that supports social reasoning) are sometimes engaged during language use but are not language-selective. This Review lays a foundation both for in-depth investigations of these different components of the language processing pipeline and for probing inter-component interactions.

Dissociating language and thought in large language models.

Large language models (LLMs) have come closest among all models to date to mastering human language, yet opinions about their linguistic and cognitive capabilities remain split. Here, we evaluate LLMs using a distinction between formal linguistic competence (knowledge of linguistic rules and patterns) and functional linguistic competence (understanding and using language in the world). We ground this distinction in human neuroscience, which has shown that formal and functional competence rely on different neural mechanisms. Although LLMs are surprisingly good at formal competence, their performance on functional competence tasks remains spotty and often requires specialized fine-tuning and/or coupling with external modules. We posit that models that use language in human-like ways would need to master both of these competence types, which, in turn, could require the emergence of separate mechanisms specialized for formal versus functional linguistic competence.

Inaccurately Reported Statin Use Affects the Assessing of Lipid Profile Measures and Their Association with Coronary Artery Disease Risk.

BACKGROUND: Lipid profiling is central for coronary artery disease (CAD) risk assessment. Nonadherence or unreported use of lipid-lowering drugs, particularly statins, can significantly complicate the association between lipid profile measures and CAD clinical outcomes. By combining medication history evaluation with statin analysis in plasma, we determined the effects of inaccurately reported statin use on lipid profile measures and their association with CAD risk. METHODS: We compared medication history of statin use with statin concentration measurements, by liquid chromatography-tandem mass spectrometry, in 690 participants undergoing coronary angiography (63 ± 11 years of age). Nominal logistic regression was employed to model CAD diagnosis with statin measurements, phenotypic, and lipid profile characteristics. RESULTS: Medication history of statin use was confirmed by statin assay for 81% of the patients. Surprisingly, statins were detected in 46% of patients without statin use records. Nonreported statin use was disproportionately higher among older participants. Stratifying samples by statin history resulted in underestimated LDL-lipid measures. Apolipoprotein B concentrations had a significant inverse CAD association, which became nonsignificant upon re-stratification using the statin assay data. CONCLUSIONS: Our study uncovered prominent discrepancies between medication records and actual statin use measured by mass spectrometry. We showed that inaccurate statin use assessments may lead to overestimation and underestimation of LDL levels in statin user and nonuser categories, exaggerating the reverse epidemiology association between LDL levels and CAD diagnosis. Combining medication history and quantitative statin assay data can significantly improve the design, analysis, and interpretation of clinical and epidemiological studies.

Integrative brain omics approach reveals key role for sn-1 lysophosphatidylethanolamine in Alzheimer's dementia.

The biology of individual lipid species and their relevance in Alzheimer's disease (AD) remains incompletely understood. We utilized non-targeted mass spectrometry to examine brain lipids variations across 316 post-mortem brains from participants in the Religious Orders Study (ROS) or Rush Memory and Aging Project (MAP) cohorts classified as either control, asymptomatic AD (AAD), or symptomatic AD (SAD) and integrated the lipidomics data with untargeted proteomic characterization on the same individuals. Lipid enrichment analysis and analysis of variance identified significantly lower abundance of lysophosphatidylethanolamine (LPE) and lysophosphatidylcholine (LPC) species in SAD than controls or AAD. Lipid-protein co-expression network analyses revealed that lipid modules consisting of LPE and LPC exhibited a significant association to protein modules associated with MAPK/metabolism, post-synaptic density, and Cell-ECM interaction pathways and were associated with better antemortem cognition and with neuropathological changes seen in AD. Particularly, LPE 22:6 [sn-1] levels are significantly decreased across AD cases (SAD) and show the most influence on protein changes compared to other lysophospholipid species. LPE 22:6 may be a lipid signature for AD and could be leveraged as potential therapeutic or dietary targets for AD.

Sequence of Structural and Magnetic Phase Transitions in (NO)Mn6(NO3)13.

New nitrosonium manganese(II) nitrate, (NO)Mn6(NO3)13, has been synthesized and structurally characterized. In the temperature range of 45-298 K, the crystal is hexagonal (centrosymmetric sp. gr. P63/m). Mn2+ ions are assembled into tubes along axis c with both NO3- filling and coating. The nitrosonium cation is located in the framework cavity and is disordered by a 3-fold axis. At the temperature TS1 = 190 K, a structural phase transition related to the libration of the intertube NO3 group and a small variation of Mn polyhedron is observed. Moreover, the anomalies in physical properties of (NO)Mn6(NO3)13 allow suggesting that ordering of NO+ units occurs at low temperatures. The antiferromagnetic ordering in this compound is preceded by the formation of a short-range correlation regime at about 25 K and takes place in two steps at TN1 = 12.0 K and TN2 = 8.4 K.

A Novel Anti-CD47 Nanobody Tetramer for Cancer Therapy.

CD47 acts as a defense mechanism for tumor cells by sending a "don't eat me" signal via its bond with SIRPα. With CD47's overexpression linked to poor cancer outcomes, its pathway has become a target in cancer immunotherapy. Though monoclonal antibodies offer specificity, they have limitations like the large size and production costs. Nanobodies, due to their small size and unique properties, present a promising therapeutic alternative. In our study, a high-affinity anti-CD47 nanobody was engineered from an immunized alpaca. We isolated a specific VHH from the phage library, which has nanomolar affinity to SIRPα, and constructed a streptavidin-based tetramer. The efficacy of the nanobody and its derivative was evaluated using various assays. The new nanobody demonstrated higher affinity than the monoclonal anti-CD47 antibody, B6H12.2. The nanobody and its derivatives also stimulated substantial phagocytosis of tumor cell lines and induced apoptosis in U937 cells, a response confirmed in both in vitro and in vivo settings. Our results underscore the potential of the engineered anti-CD47 nanobody as a promising candidate for cancer immunotherapy. The derived nanobody could offer a more effective, cost-efficient alternative to conventional antibodies in disrupting the CD47-SIRPα axis, opening doors for its standalone or combinatorial therapeutic applications in oncology.

Cannabis Use Among Adults in Cigarette Smoking Cessation Treatment in Ontario, Canada: Prevalence and Association With Tobacco Cessation Outcome, 2015-2021.

Objectives. To examine cannabis use prevalence and its association with tobacco cessation among adults enrolled in cigarette smoking cessation treatment before and after Canada legalized recreational cannabis in October 2018. Methods. The sample comprised 83 206 adults enrolled in primary care-based cigarette smoking cessation treatment between 2015 and 2021 in Ontario, Canada. Past-30-day cannabis use was self-reported at enrollment and cigarette smoking abstinence at 6-month follow-up. Results. Past-30-day prevalence of cannabis use increased from 20.2% in 2015 to 37.7% in 2021. The prevalence increased linearly both before and after legalization. Cannabis and tobacco co-use was associated with lower odds of self-reported cigarette smoking abstinence at 6-month follow-up than tobacco use only (24.4% vs 29.3%; odds ratio [OR] = 0.78; 95% confidence interval [CI] = 0.75, 0.81). This association was attenuated after adjustment for covariates (OR = 0.93; 95% CI = 0.89, 0.97) and weakened slightly over time. Conclusions. Cannabis use prevalence almost doubled from 2015 to 2021 among primary care patients in Ontario seeking treatment to quit cigarettes and was associated with poorer quit outcomes. Further research into the impact of cannabis policy on cannabis and tobacco co-use is warranted to mitigate harm. (Am J Public Health. 2024;114(1):98-107. https://doi.org/10.2105/AJPH.2023.307445).

Evaluation of a flexible piecewise linear mixed-effects model in the analysis of randomized cross-over trials.

Cross-over designs are commonly used in randomized clinical trials to estimate efficacy of a new treatment. They have received a lot of attention, particularly in connection with regulatory requirements for new drugs. The main advantage of using cross-over designs over conventional parallel designs is increased precision, thanks to within-subject comparisons. In the statistical literature, more recent developments are discussed in the analysis of cross-over trials, in particular regarding repeated measures. A piecewise linear model within the framework of mixed effects has been proposed in the analysis of cross-over trials. In this article, we report on a simulation study comparing performance of a piecewise linear mixed-effects (PLME) model against two commonly cited models-Grizzle's mixed-effects (GME) and Jones & Kenward's mixed-effects (JKME) models-used in the analysis of cross-over trials. Our simulation study tried to mirror real-life situation by deriving true underlying parameters from empirical data. The findings from real-life data confirmed the original hypothesis that high-dose iodine salt have significantly lowering effect on diastolic blood pressure (DBP). We further sought to evaluate the performance of PLME model against GME and JKME models, within univariate modeling framework through a simulation study mimicking a 2 × 2 cross-over design. The fixed-effects, random-effects and residual error parameters used in the simulation process were estimated from DBP data, using a PLME model. The initial results with full specification of random intercept and slope(s), showed that the univariate PLME model performed better than the GME and JKME models in estimation of variance-covariance matrix (G) governing the random effects, allowing satisfactory model convergence during estimation. When a hierarchical view-point is adopted, in the sense that outcomes are specified conditionally upon random effects, the variance-covariance matrix of the random effects must be positive-definite. The PLME model is preferred especially in modeling an increased number of random effects, compared to the GME and JKME models that work equally well with random intercepts only. In some cases, additional random effects could explain much variability in the data, thus improving precision in estimation of the estimands (effect size) parameters.

Lost in Space? Unmasking the T Cell Reaction to Simulated Space Stressors.

The space environment will expose astronauts to stressors like ionizing radiation, altered gravity fields and elevated cortisol levels, which pose a health risk. Understanding how the interplay between these stressors changes T cells' response is important to better characterize space-related immune dysfunction. We have exposed stimulated Jurkat cells to simulated space stressors (1 Gy, carbon ions/1 Gy photons, 1 µM hydrocortisone (HC), Mars, moon, and microgravity) in a single or combined manner. Pro-inflammatory cytokine IL-2 was measured in the supernatant of Jurkat cells and at the mRNA level. Results show that alone, HC, Mars gravity and microgravity significantly decrease IL-2 presence in the supernatant. 1 Gy carbon ion irradiation showed a smaller impact on IL-2 levels than photon irradiation. Combining exposure to different simulated space stressors seems to have less immunosuppressive effects. Gene expression was less impacted at the time-point collected. These findings showcase a complex T cell response to different conditions and suggest the importance of elevated cortisol levels in the context of space flight, also highlighting the need to use simulated partial gravity technologies to better understand the immune system's response to the space environment.

Problems of human spermatozoa cryopreservation: research methods, solutions.

Cryopreservation of male gametes is one of the most important methods of assisted reproductive technologies, which allows preserving gametes for research or further use. However, the fertilizing ability of spermatozoa after cryopreservation decreases by 30-70%, which makes it urgent to search for new substances with cryoprotective properties. The review considers the main causes of cell damage during cryopreservation. The relevance of methods for assessing the formation of crystals and the physicochemical properties of cryoprotective media depending on various compositions is discussed. The problem of stabilization of the spermatozoa membrane during cryopreservation is considered. A possible solution to the problem of membrane integrity may consist in modification of the basic cryoprotective media with yolk emulsion or development of methods for saturation of the membrane phospholipid layer with cholesterol.

Event Knowledge in Large Language Models: The Gap Between the Impossible and the Unlikely.

Word co-occurrence patterns in language corpora contain a surprising amount of conceptual knowledge. Large language models (LLMs), trained to predict words in context, leverage these patterns to achieve impressive performance on diverse semantic tasks requiring world knowledge. An important but understudied question about LLMs' semantic abilities is whether they acquire generalized knowledge of common events. Here, we test whether five pretrained LLMs (from 2018's BERT to 2023's MPT) assign a higher likelihood to plausible descriptions of agent-patient interactions than to minimally different implausible versions of the same event. Using three curated sets of minimal sentence pairs (total n = 1215), we found that pretrained LLMs possess substantial event knowledge, outperforming other distributional language models. In particular, they almost always assign a higher likelihood to possible versus impossible events (The teacher bought the laptop vs. The laptop bought the teacher). However, LLMs show less consistent preferences for likely versus unlikely events (The nanny tutored the boy vs. The boy tutored the nanny). In follow-up analyses, we show that (i) LLM scores are driven by both plausibility and surface-level sentence features, (ii) LLM scores generalize well across syntactic variants (active vs. passive constructions) but less well across semantic variants (synonymous sentences), (iii) some LLM errors mirror human judgment ambiguity, and (iv) sentence plausibility serves as an organizing dimension in internal LLM representations. Overall, our results show that important aspects of event knowledge naturally emerge from distributional linguistic patterns, but also highlight a gap between representations of possible/impossible and likely/unlikely events.

A high-pressure single-crystal X-ray diffraction study of potassium guaninate hydrate, K+·C5H4N5O-·H2O.

The crystal structure of potassium guaninate hydrate, K+·C5H4N5O-·H2O, was studied in the pressure range of 1 atm to 7.3 GPa by single-crystal diffraction using synchrotron radiation and a laboratory X-ray diffraction source. Structural strain was compared to that of the same salt hydrate on cooling, and in 2Na+·C5H3N5O2-·7H2O under hydrostatic compression and on cooling. A polymorphic transition into a new, incommensurately modulated, phase was observed at ∼4-5 GPa. The transition was reversible with a hysteresis: the satellite reflections disappeared on decompression to ∼1.4 GPa.

3,4-Dihydroxiphenylacetic Acid-Based Universal Coating Technique for Magnetic Nanoparticles Stabilization for Biomedical Applications.

Magnetic nanoparticles based on iron oxide attract researchers' attention due to a wide range of possible applications in biomedicine. As synthesized, most of the magnetic nanoparticles do not form the stable colloidal solutions that are required for the evaluation of their interactions with cells or their efficacy on animal models. For further application in biomedicine, magnetic nanoparticles must be further modified with biocompatible coating. Both the size and shape of magnetic nanoparticles and the chemical composition of the coating have an effect on magnetic nanoparticles' interactions with living objects. Thus, a universal method for magnetic nanoparticles' stabilization in water solutions is needed, regardless of how magnetic nanoparticles were initially synthesized. In this paper, we propose the versatile and highly reproducible ligand exchange technique of coating with 3,4-dihydroxiphenylacetic acid (DOPAC), based on the formation of Fe-O bonds with hydroxyl groups of DOPAC leading to the hydrophilization of the magnetic nanoparticles' surfaces following phase transfer from organic solutions to water. The proposed technique allows for obtaining stable water-colloidal solutions of magnetic nanoparticles with sizes from 21 to 307 nm synthesized by thermal decomposition or coprecipitation techniques. Those stabilized by DOPAC nanoparticles were shown to be efficient in the magnetomechanical actuation of DNA duplexes, drug delivery of doxorubicin to cancer cells, and targeted delivery by conjugation with antibodies. Moreover, the diversity of possible biomedical applications of the resulting nanoparticles was presented. This finding is important in terms of nanoparticle design for various biomedical applications and will reduce nanomedicines manufacturing time, along with difficulties related to comparative studies of magnetic nanoparticles with different magnetic core characteristics.

The language network is not engaged in object categorization.

The relationship between language and thought is the subject of long-standing debate. One claim states that language facilitates categorization of objects based on a certain feature (e.g. color) through the use of category labels that reduce interference from other, irrelevant features. Therefore, language impairment is expected to affect categorization of items grouped by a single feature (low-dimensional categories, e.g. "Yellow Things") more than categorization of items that share many features (high-dimensional categories, e.g. "Animals"). To test this account, we conducted two behavioral studies with individuals with aphasia and an fMRI experiment with healthy adults. The aphasia studies showed that selective low-dimensional categorization impairment was present in some, but not all, individuals with severe anomia and was not characteristic of aphasia in general. fMRI results revealed little activity in language-responsive brain regions during both low- and high-dimensional categorization; instead, categorization recruited the domain-general multiple-demand network (involved in wide-ranging cognitive tasks). Combined, results demonstrate that the language system is not implicated in object categorization. Instead, selective low-dimensional categorization impairment might be caused by damage to brain regions responsible for cognitive control. Our work adds to the growing evidence of the dissociation between the language system and many cognitive tasks in adults.

Non-Fermi-Liquid Behavior of Superconducting SnH4.

The chemical interaction of Sn with H2 by X-ray diffraction methods at pressures of 180-210 GPa is studied. A previously unknown tetrahydride SnH4 with a cubic structure (fcc) exhibiting superconducting properties below TC  = 72 K is obtained; the formation of a high molecular C2/m-SnH14 superhydride and several lower hydrides, fcc SnH2 , and C2-Sn12 H18 , is also detected. The temperature dependence of critical current density JC (T) in SnH4 yields the superconducting gap 2Δ(0) = 21.6 meV at 180 GPa. SnH4 has unusual behavior in strong magnetic fields: B,T-linear dependences of magnetoresistance and the upper critical magnetic field BC2 (T) ∝ (TC - T). The latter contradicts the Wertheimer-Helfand-Hohenberg model developed for conventional superconductors. Along with this, the temperature dependence of electrical resistance of fcc SnH4 in non-superconducting state exhibits a deviation from what is expected for phonon-mediated scattering described by the Bloch-Grüneisen model and is beyond the framework of the Fermi liquid theory. Such anomalies occur for many superhydrides, making them much closer to cuprates than previously believed.