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Introduction: The Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) is part of the undergraduate dental curriculum. Online teaching has nowadays become common also in dentistry. Objective: To compare undergraduate students’ self-assessed ability and satisfaction with learning DC/TMD Axis I between traditional and online learning and to evaluate the possible gains of online teaching. Material and Methods: Third-year undergraduate dental students in 2018 (traditional learning, Group 1, n = 43/50) and in 2019 (online learning, Group 2, n = 34/50) at the University of Oulu, Finland evaluated their self-assessed ability and satisfaction with learning DC/TMD clinical examination and diagnostics on a 10-point scale. Additionally, those participating in online courses answered to two open-ended questions; Group 2 (n = 50) and another group from the University of Eastern Finland in 2019 and 2020 (n = 75, Group 3). Total of 105/125 students (84%) responded. Content analysis was used to open-ended responses. Results: The online course reported significantly higher self-assessed ability in measurements (p = 0.004), identifying referred pain (p = 0.043) and statement for the diagnostics (p = 0.017) and also higher self-assessed satisfaction in measurements (p = 0.046). According to the content analysis, essential gains of online teaching were efficient learning, videos and exercises, and adjustability to own timetable. Conclusion: The online learning course can be considered as a good option for traditional learning of the DC/TMD protocol.

Objective: To describe the occurrence of caries disease from a life course perspective using longitudinal data from the Swedish Quality Registry for Caries and Periodontal Disease (SKaPa). Material and Methods: Data from seven age cohorts (ages 30–90 years), each followed over 10 years, were retrieved from the SKaPa. Using a three-trajectory model, individuals were divided into three trajectories according to their caries development over time: high (15%), moderate (45%), or low (40%). Caries experience was expressed as the mean decayed, missing, and filled surfaces (DMFS) index. Results: Significant differences were found for all three trajectories and in all age groups over the 10 years. The mean DMFS index increase was significantly larger for the high trajectory group than for the moderate and low trajectory groups across all age cohorts. An increase in caries experience was observed for the older cohorts across all trajectories. Conclusions: A three-trajectory model appears useful for identifying and quantifying caries experiences in longitudinal studies. Increased caries disease occurs over time, especially in the highest trajectory group and among older cohorts. These findings emphasise the need for greater attention and more efficient caries prevention methods.

Abstract Studies linking genetics, behavior and life history in any species are rare. In Atlantic salmon (Salmo salar), age at maturity is a key life‐history trait and associates strongly with the vgll3 locus, whereby the vgll3*E allele is linked with younger age at maturity, and higher body condition than the vgll3*L allele. However, the relationship between this genetic variation and behaviors like boldness and exploration which may impact growth and reproductive strategies is poorly understood. The pace‐of‐life syndrome (POLS) framework provides predictions, whereby heightened exploratory behavior and boldness are predicted in individuals with the early maturation‐associated vgll3 genotype (EE). Here, we tested these predictions by investigating the relationship between vgll3 genotypes and exploration and boldness behaviors in 129 juveniles using the novel environment and novel object trials. Our results indicated that contrary to POLS predictions, vgll3*LL fish were bolder and more explorative, suggesting a genotype‐level syndrome including several behaviors. Interestingly, clear sex differences were observed in the latency to move in a new environment, with vgll3*EE males, but not females, taking longer to move than their vgll3*LL counterparts. Our results provide further empirical support for recent calls to consider more nuanced explanations than the pace of life theory for integrating behavior into life‐history theory.

Objective: The aim was to identify caries active individuals among adults by using a trajectory model of longitudinal data from the Swedish national registry (SKaPa) and comparing them with published data from the Dunedin cohort. Materials and methods: Data from two different age groups (30- and 40-year-olds) followed for 10 years were retrieved from SKaPa and were compared with published longitudinal birth-cohort data from the Dunedin study. Using the trajectory model, the subjects were divided into three different trajectories according to their caries development over time (i.e. high, 15%; moderate, 45%; low, 40%). Results: Caries experience, as measured by mean decayed, missing, and filled surfaces (DMFS) index, revealed significant differences among the three trajectories in both age groups. The patterns were similar to those observed in the Dunedin cohort. The mean increase in DMFS during the 10-year follow-up period from SKaPa was significantly higher for the high trajectories in both age groups compared with the moderate and low trajectories. Conclusions: The method using three trajectories for presentation of caries experience over time, may be a useful tool to identify subjects with different disease activities. Identification of subjects in the high caries experience trajectory may increase the possibility to explore and evaluate more effective caries prevention for this group in the future.

Abstract 2D transition metal carbides and nitrides (MXenes) suggest an uncommonly broad combination of important functionalities amongst 2D materials. Nevertheless, MXene suffers from facile oxidation and colloidal instability upon conventional water‐based processing, thus limiting applicability. By experiments and theory, It is suggested that for stability and dispersibility, it is critical to select uncommonly high permittivity solvents such as N‐methylformamide (NMF) and formamide (FA) (εr = 171, 109), unlike the classical solvents characterized by high dipole moment and polarity index. They also allow high MXene stacking order within thin films on carbon nanotube (CNT) substrates, showing very high Terahertz (THz) shielding effectiveness (SE) of 40–60 dB at 0.3–1.6 THz in spite of the film thinness

More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain stability or even revert to cognitive norms, alarmingly, up to half of the cases progress to dementia within 5 years. Current diagnostic practice lacks the necessary screening tools to identify those at risk of progression. The European patient experience often involves a long journey from the initial signs of MCI to the eventual diagnosis of dementia. The trajectory is far from ideal. Here, we introduce the AI-Mind project, a pioneering initiative with an innovative approach to early risk assessment through the implementation of advanced artificial intelligence (AI) on multimodal data. The cutting-edge AI-based tools developed in the project aim not only to accelerate the diagnostic process but also to deliver highly accurate predictions regarding an individual's risk of developing dementia when prevention and intervention may still be possible. AI-Mind is a European Research and Innovation Action (RIA H2020-SC1-BHC-06-2020, No. 964220) financed between 2021 and 2026. First, the AI-Mind Connector identifies dysfunctional brain networks based on high-density magneto- and electroencephalography (M/EEG) recordings. Second, the AI-Mind Predictor predicts dementia risk using data from the Connector, enriched with computerized cognitive tests, genetic and protein biomarkers, as well as sociodemographic and clinical variables. AI-Mind is integrated within a network of major European initiatives, including The Virtual Brain, The Virtual Epileptic Patient, and EBRAINS AISBL service for sensitive data, HealthDataCloud, where big patient data are generated for advancing digital and virtual twin technology development. AI-Mind's innovation lies not only in its early prediction of dementia risk, but it also enables a virtual laboratory scenario for hypothesis-driven personalized intervention research. This article introduces the background of the AI-Mind project and its clinical study protocol, setting the stage for future scientific contributions.

Abstract Introduction Chronic pain associates with various sleep problems. Patients with complex regional pain syndrome (CRPS) often report impaired sleep, but objective measurements of sleep in CRPS patients are scarce. Neuromodulation with repetitive transcranial magnetic stimulation (rTMS) can alleviate pain and improve sleep. Secondary somatosensory cortex (S2) is a possible rTMS target for the treatment of chronic pain, but the effect of S2‐targeted rTMS on sleep is unknown. Methods This randomized, sham‐controlled trial assessed the effect of S2‐targeted rTMS on sleep in patients with CRPS. Patients (n = 31) received either S2‐targeted rTMS (10 Hz) or sham stimulation for 3 weeks. The effect of treatment on sleep was assessed with validated questionnaires, with a sleep and pain diary, and with a consumer‐grade sleep tracker, the Oura ring. In addition to an ordinary univariate analysis of the results, we conducted multivariate testing of the Oura data using linear discriminant analysis (LDA). Results S2‐targeted rTMS decreased sleep restlessness that significantly differed between the rTMS and sham stimulation patient groups (p = .028). In the multivariate analysis of the Oura data, LDA classification accuracy to separate the rTMS and sham groups exceeded 95% confidence level in four out of the seven tested models. In the subjective evaluation of sleep, the effect of rTMS and sham did not differ. Conclusion S2‐targeted rTMS influenced sleep in patients with CRPS. Improved sleep may enhance CRPS symptom alleviation and be of clinical importance. A univariate analysis could separate the rTMS and sham treatments. The multivariate analysis revealed that including multiple sleep‐related parameters can be beneficial when analyzing rTMS effects on sleep. As sleep is related both to pain and quality of life, and sleep rTMS can be directly affected by rTMS, objective monitoring of sleep in various future rTMS trials could be fruitful.

New biomarkers are urgently needed for many brain disorders; for example, the diagnosis of mild traumatic brain injury (mTBI) is challenging as the clinical symptoms are diverse and nonspecific. EEG and MEG studies have demonstrated several population-level indicators of mTBI that could serve as objective markers of brain injury. However, deriving clinically useful biomarkers for mTBI and other brain disorders from EEG/MEG signals is hampered by the large inter-individual variability even across healthy people. Here, we used a multivariate machine-learning approach to detect mTBI from resting-state MEG measurements. To address the heterogeneity of the condition, we employed a normative modeling approach and modeled MEG signal features of individual mTBI patients as deviations with respect to the normal variation. To this end, a normative dataset comprising 621 healthy participants was used to determine the variation in power spectra across the cortex. In addition, we constructed normative datasets based on age-matched subsets of the full normative data. To discriminate patients from healthy control subjects, we trained support-vector-machine classifiers on the quantitative deviation maps for 25 mTBI patients and 20 controls not included in the normative dataset. The best performing classifier made use of the full normative data across the entire age and frequency ranges. This classifier was able to distinguish patients from controls with an accuracy of 79%. Inspection of the trained model revealed that low-frequency activity in the theta frequency band (4-8 Hz) is a significant indicator of mTBI, consistent with earlier studies. The results demonstrate the feasibility of using normative modeling of MEG data combined with machine learning to advance diagnosis of mTBI and identify patients that would benefit from treatment and rehabilitation. The current approach could be applied to a wide range of brain disorders, thus providing a basis for deriving MEG/EEG-based biomarkers.

BackgroundIn response to hypoxia, tumor cells undergo transcriptional reprogramming including upregulation of carbonic anhydrase (CA) IX, a metalloenzyme that maintains acid-base balance. CAIX overexpression has been shown to correlate with poor prognosis in various cancers, but the role of this CA isoform in hepatoblastoma (HB) has not been examined.MethodsWe surveyed the expression of CAIX in HB specimens and assessed the impact of SLC-0111, a CAIX inhibitor, on cultured HB cells in normoxic and hypoxic conditions.ResultsCAIX immunoreactivity was detected in 15 out of 21 archival pathology HB specimens. The CAIX-positive cells clustered in the middle of viable tumor tissue or next to necrotic areas. Tissue expression of CAIX mRNA was associated with metastasis and poor clinical outcome of HB. Hypoxia induced a striking upregulation of CAIX mRNA and protein in three HB cell models: the immortalized human HB cell line HUH6 and patient xenograft-derived lines HB-295 and HB-303. Administration of SLC-0111 abrogated the hypoxia-induced upregulation of CAIX and decreased HB cell viability, both in monolayer and spheroid cultures. In addition, SLC-0111 reduced HB cell motility in a wound healing assay. Transcriptomic changes triggered by SLC-0111 administration differed under normoxic vs. hypoxic conditions, although SLC-0111 elicited upregulation of several tumor suppressor genes under both conditions.ConclusionHypoxia induces CAIX expression in HB cells, and the CAIX inhibitor SLC-0111 has in vitro activity against these malignant cells.

Background: There is substantial evidence that midlife hypertension is a risk factor for late life dementia. Our aim was to investigate if even high blood pressure at a single timepoint in midlife can predict an increased risk for all-cause dementia, Alzheimer’s disease (AD), or vascular dementia (VaD) later in life. Methods: The community-based study population comprised 30,102 dementia-free individuals from the Westmannia Cardiovascular Risk Factors Study. The participants were aged 40 or 50 years when the health examination took place in 1990–2000. Diagnose registers from both hospitals and primary healthcare centers were used to identify individuals who after inclusion to the study developed dementia. The association between midlife high blood pressure (defined as systolic blood pressure >140 and/or diastolic blood pressure >90 mmHg) at a single timepoint and dementia was adjusted for age, gender, body mass index (BMI), fasting blood glucose, education, smoking, and physical activity level. Multivariate binary cox regression analyses were used. Results: After a mean follow-up time of 24 years resulting in 662,244 person/years, 761 (2.5%) individuals had been diagnosed with dementia. Midlife high blood pressure at a single timepoint predicted all-cause dementia (hazard ratio [HR]: 1.22, 95% confidence interval [CI]: 1.02–1.45) and VaD (HR: 2.10, 95% CI: 1.47–3.00) but not AD (HR: 1.06, 95% CI: 0.81–1.38). Conclusion: This study suggests that even midlife high blood pressure at a single timepoint predicts all-cause dementia and more than doubles the risk for VaD later in life independently of established confounders. Even though there was no such association with AD, this strengthens the importance of midlife health examinations in order to identify individuals with hypertension and initiate treatment.

Different neuroimaging methods can yield different views of task-dependent neural engagement. Studies examining the relationship between electromagnetic and hemodynamic measures have revealed correlated patterns across brain regions but the role of the applied stimulation or experimental tasks in these correlation patterns is still poorly understood. Here, we evaluated the across-tasks variability of MEG-fMRI relationship using data recorded during three distinct naming tasks (naming objects and actions from action images, and objects from object images), from the same set of participants. Our results demonstrate that the MEG-fMRI correlation pattern varies according to the performed task, and that this variability shows distinct spectral profiles across brain regions. Notably, analysis of the MEG data alone did not reveal modulations across the examined tasks in the time-frequency windows emerging from the MEG-fMRI correlation analysis. Our results suggest that the electromagnetic-hemodynamic correlation could serve as a more sensitive proxy for task-dependent neural engagement in cognitive tasks than isolated within-modality measures.

In this study, Marlin et al. provide insights into the potential use of subunit vaccines that induce a high level of protection against SARS-CoV-2 in animal models.

Refresher training in cardiopulmonary resuscitation and recognition of patients with failure in vital functions are often completed on separate occasions. In this study, 63 healthcare professionals participated in a pilot course and self-assessed their abilities before and after the course. Combining training scenarios with different diagnoses of patient cases provided a real-life learning environment. The training strengthened the perceived ability of healthcare professionals to respond to an acute situation of a patient with failure of vital functions. [ABSTRACT FROM AUTHOR]

Background: In mild cognitive impairment (MCI), the first neurodegenerative changes may occur years before they can be effectively detected with current clinical tools. Early pathology has been linked to synaptic dysfunction causing brain network disturbances that may be observed with electroencephalography (EEG) and magnetoencephalography (MEG). These methods are still not widely utilized in dementia risk assessment, and the stability of suggested EEG and MEG features and their correlation has not been thoroughly addressed in this patient group. Method: In a 5‐year EU Horizon2020 project 'AI‐Mind', we collect EEG and simultaneous MEG data from MCI subjects, to be compiled with cognitive, genetic and plasma biomarker measures and techniques based on artificial intelligence (AI) for predicting the overall dementia risk. Here, we analyzed a subset of 31 Finnish MCI participants (20 females, age 68 ± 5; mean ± SD) from the AI‐Mind dataset to assess the stability of prominent signal features from resting‐state EEG and MEG recordings. We determined within‐session test‐retest reliability for spectral peak frequencies and relative peak power over occipital brain regions in the 8‐13 Hz range, by utilizing intraclass correlation (ICC) for subsequent 5‐min runs of EEG and MEG data in both eyes‐closed (EC) and eyes‐open (EO) conditions. In addition, we determined the consistency of the features across methods (EEG/MEG). Result: The results indicate good (ICC>0.6) test‐retest reliability across runs for EEG (peak frequency: 0.72 (EC); relative power: 0.86 (EC) and 0.66 (EO); p<0.001) and excellent test‐retest reliability (ICC>0.75) for MEG (peak frequency: 0.83 (EC); relative power: 0.96 (EC) and 0.85 (EO); p<0.001). Consistency across EEG and MEG was excellent (peak frequency: 0.86 (EC); relative power 0.89 (EC) and 0.84 (EO); p<0.001). Conclusion: Electrophysiological recordings of brain networks are emerging as a diagnostic tool for early detection of dementia. Good stability of the measured signal features is a prerequisite for a clinically feasible tool. Here, we demonstrate good or excellent stability for prominent spectral features both within and across EEG and MEG recordings. [ABSTRACT FROM AUTHOR]

Exaggerated subthalamic beta oscillatory activity and increased beta range cortico-subthalamic synchrony have crystallized as the electrophysiological hallmarks of Parkinson's disease. Beta oscillatory activity is not tonic but occurs in ‘bursts’ of transient amplitude increases. In Parkinson's disease, the characteristics of these bursts are altered especially in the basal ganglia. However, beta oscillatory dynamics at the cortical level and how they compare with healthy brain activity is less well studied. We used magnetoencephalography (MEG) to study sensorimotor cortical beta bursting and its modulation by subthalamic deep brain stimulation in Parkinson's disease patients and age-matched healthy controls. We show that the changes in beta bursting amplitude and duration typical of Parkinson's disease can also be observed in the sensorimotor cortex, and that they are modulated by chronic subthalamic deep brain stimulation, which, in turn, is reflected in improved motor function at the behavioural level. In addition to the changes in individual beta bursts, their timing relative to each other was altered in patients compared to controls: bursts were more clustered in untreated Parkinson's disease, occurring in ‘bursts of bursts’, and re-burst probability was higher for longer compared to shorter bursts. During active deep brain stimulation, the beta bursting in patients resembled healthy controls’ data. In summary, both individual bursts’ characteristics and burst patterning are affected in Parkinson's disease, and subthalamic deep brain stimulation normalizes some of these changes to resemble healthy controls’ beta bursting activity, suggesting a non-invasive biomarker for patient and treatment follow-up.

Studies linking genetics, behavior and life history in any species are rare. In Atlantic salmon ( Salmo salar ), age at maturity is a key life-history trait and associates strongly with the vgll3 locus, whereby the vgll3* E allele is linked with younger age at maturity, and higher body condition than the vgll3*L allele. However, the relationship between this genetic variation and behaviors like boldness and exploration which may impact growth and reproductive strategies is poorly understood. The pace-of-life syndrome (POLS) framework provides predictions, whereby heightened exploratory behavior and boldness are predicted in individuals with the early maturation-associated vgll3 genotype ( EE ). Here, we tested these predictions by investigating the relationship between vgll3 genotypes and exploration and boldness behaviors in 129 juveniles using the novel environment and novel object trials. Our results indicated that contrary to POLS predictions, vgll3*LL fish were bolder and more explorative, suggesting a genotype-level syndrome including several behaviors. Interestingly, clear sex differences were observed in the latency to move in a new environment, with vgll3*EE males, but not females, taking longer to move than their vgll3*LL counterparts. Our results provide further empirical support for recent calls to consider more nuanced explanations than the pace of life theory for integrating behavior into life-history theory., Competing Interests: The authors have no conflict of interest., (© 2024 The Author(s). Ecology and Evolution published by John Wiley & Sons Ltd.)

The environment experienced by a female influences reproductive traits in many species of fish. Environmental factors such as temperature and diet are not only important mediators of female maturation and reproduction but also of egg traits and offspring fitness through maternal provisioning. In this study, we use 3-year-old tank-reared Atlantic salmon from two Finnish populations to investigate the effect of temperature and diet on maturation and egg traits. We show that a temperature difference of 2°C is sufficient to delay maturation in female Atlantic salmon whereas a 22% reduction in dietary energy content had no effect on maturation. Diet did not influence the body size, condition or fecundity of the mature females or the size or protein content of the eggs. However, a higher energy diet increased egg lipid content. Neither female body size nor condition were associated with egg size or fat/protein composition. Our results indicate that female salmon that have a poorer diet in terms of energy content may have a reproductive disadvantage due to the lower energy provisioning of eggs. This disadvantage has the potential to translate into fitness consequences for their offspring., (© 2023 Fisheries Society of the British Isles.)

Age at maturity is a key life history trait involving a trade-off between survival risk and reproductive investment, and is an important factor for population structures. In ectotherms, a warming environment may have a dramatic influence on development and life history, but this influence may differ between populations. While an increasing number of studies have examined population-dependent reactions with temperature, few have investigated this in the context of maturation timing. Atlantic salmon, a species of high conservation relevance, is a good study species for this topic as it displays considerable variation in age at maturity, of which a large proportion has been associated with a genomic region including the strong candidate gene vgll3 . Until now, the effect of this gene in the context of different environments and populations has not been studied. Using a large-scale common-garden experiment, we find strong effects of temperature, population-of-origin, and vgll3 genotype on maturation in 2-year-old male Atlantic salmon ( Salmo salar) . With a temperature difference of 1.8°C, maturation probability was 4.8 times higher in the warm treatment than the cold treatment. This temperature effect was population-specific and was higher in the southern (60.48°N) compared to the northern (65.01°N) population. The early maturation vgll3 *E allele was associated with a significantly higher maturation probability, but there was no vgll3 interaction with temperature or population. Both body condition and body mass associated with maturation. The body mass association was only present in the warm treatment. Our findings demonstrate that (i) populations can vary in their response to temperature change in terms of age at maturity, (ii) high intrinsic growth could be associated with higher thermal sensitivity for life history variation and (iii) vgll3 effects on age at maturity might be similar between populations and different thermal environments., (© The Author(s) 2023. Published by Oxford University Press and the Society for Experimental Biology.)

We tested the possibility that vgll3, a gene linked with maturation age in Atlantic salmon (Salmo salar), may be associated with behaviour by measuring aggressiveness and feeding activity in 380 juveniles with different vgll3 genotypes. Contrary to our prediction, individuals with the genotype associated with later maturation (vgll3*LL) were significantly more aggressive than individuals with the genotype associated with earlier maturation (vgll3*EE). Individuals with higher aggression were also significantly lighter in colour and had higher feeding activity. Although higher aggression was associated with higher feeding activity, there was no association between feeding activity and vgll3 genotype. Increased aggression of vgll3*LL individuals was independent of their sex and size, and genotypes did not differ in their condition factor. These results imply that aggressive behaviour may have an energetic cost impairing growth and condition, especially when food cannot be monopolized. This may have implications for individual fitness and aquaculture practices., (© 2022 The Authors. Journal of Fish Biology published by John Wiley & Sons Ltd on behalf of Fisheries Society of the British Isles.)