Language barriers, specifically among refugees, pose significant challenges to delivering quality healthcare in Canada. While the COVID-19 pandemic accelerated the emergence and development of innovative alternatives such as telephone-based and video-conferencing medical interpreting services and AI tools, access remains uneven across Canada. This comprehensive analysis highlights the absence of a cohesive national strategy, reflected in diverse funding models employed across provinces and territories, with gaps and disparities in access to medical interpreting services. Advocating for medical interpreting, both as a moral imperative and a prudent investment, this article draws from human rights principles and ethical considerations, justified in national and international guidelines, charters, codes and regulations. Substantiated by a cost-benefit analysis, it emphasizes that medical interpreting enhances healthcare quality and preserves patient autonomy. Additionally, this article illuminates decision-making processes for utilizing interpreting services; recognizing the pivotal roles of clinicians, interpreters, patients and caregivers within the care circle; appreciating intersectional considerations such as gender, culture and age, underscoring the importance of a collaborative approach. Finally, it provides recommendations at provider, organizational and system levels to ensure equitable access to this right and to promote the health and well-being of refugees and other individuals facing language barriers within Canada’s healthcare system. Full article

Depression is a pervasive issue among college students worldwide, yet there is a significant gap in the literature regarding its prevalence and coping strategies in the Ukrainian context. The present study aims to fill this gap by investigating how substance use and health-promoting behaviors relate to depressive symptoms among Ukrainian college students. Health-promoting behaviors are an important strategy to prevent depression, whereas substance use can contribute to depression or make it harder to manage. Given the substantial psychosocial problems and stressors related to the ongoing war in Ukraine and the limited availability of mental health services for college students, it is important to understand how we can encourage college students to keep themselves mentally healthy. A cross-sectional study was conducted among college students on 10 campuses in 2018. Almost 16% of participants met a cut-off for depression. Female students and those who were older reported significantly higher depressive symptoms. Participants were more likely to report depressive symptoms if they were more often involved with alcohol and cannabis use, were older, and engaged in fewer health-promoting behaviors. Tobacco use was not significantly associated with depressive symptoms. Our findings suggest a moderate prevalence of depressive symptoms in our study population. We recommend implementing balanced public health interventions that address risk factors (such as substance use) while also promoting protective behaviors and can be tailored to the specific cultural and environmental context of the region. Full article

Robot-Assisted Minimally Invasive Surgery (RAMIS) marks a paradigm shift in surgical procedures, enhancing precision and ergonomics. Concurrently it introduces complex stress dynamics and ergonomic challenges regarding the human–robot interface and interaction. This study explores the stress-related aspects of RAMIS, using the da Vinci XI Surgical System and the Sea Spikes model as a standard skill training phantom to establish a link between technological advancement and human factors in RAMIS environments. By employing different physiological and kinematic sensors for heart rate variability, hand movement tracking, and posture analysis, this research aims to develop a framework for quantifying the stress and ergonomic loads applied to surgeons. Preliminary findings reveal significant correlations between stress levels and several of the skill-related metrics measured by external sensors or the SURG-TLX questionnaire. Furthermore, early analysis of this preliminary dataset suggests the potential benefits of applying machine learning for surgeon skill classification and stress analysis. This paper presents the initial findings, identified correlations, and the lessons learned from the clinical setup, aiming to lay down the cornerstones for wider studies in the fields of clinical situation awareness and attention computing. Full article

To address the various challenges in aluminum surface defect detection, such as multiscale intricacies, sensitivity to lighting variations, occlusion, and noise, this study proposes the AluDef-ClassNet model. Firstly, a Gaussian difference pyramid is utilized to capture multiscale image features. Secondly, a self-attention mechanism is introduced to enhance feature representation. Additionally, an improved residual network structure incorporating dilated convolutions is adopted to increase the receptive field, thereby enhancing the network’s ability to learn from extensive information. A small-scale dataset of high-quality aluminum surface defect images is acquired using a CCD camera. To better tackle the challenges in surface defect detection, advanced deep learning techniques and data augmentation strategies are employed. To address the difficulty of data labeling, a transfer learning approach based on fine-tuning is utilized, leveraging prior knowledge to enhance the efficiency and accuracy of model training. In dataset testing, our model achieved a classification accuracy of 98.01%, demonstrating significant advantages over other classification models. Full article

Traditionally, angle measurements have been performed using a goniometer, but the complex motion of shoulder movement has made these measurements intricate. The angle of rotation of the shoulder is particularly difficult to measure from an upright position because of the complicated base and moving axes. In this study, we attempted to estimate the shoulder joint internal/external rotation angle using the combination of pose estimation artificial intelligence (AI) and a machine learning model. Videos of the right shoulder of 10 healthy volunteers (10 males, mean age 37.7 years, mean height 168.3 cm, mean weight 72.7 kg, mean BMI 25.6) were recorded and processed into 10,608 images. Parameters were created using the coordinates measured from the posture estimation AI, and these were used to train the machine learning model. The measured values from the smartphone’s angle device were used as the true values to create a machine learning model. When measuring the parameters at each angle, we compared the performance of the machine learning model using both linear regression and Light GBM. When the pose estimation AI was trained using linear regression, a correlation coefficient of 0.971 was achieved, with a mean absolute error (MAE) of 5.778. When trained with Light GBM, the correlation coefficient was 0.999 and the MAE was 0.945. This method enables the estimation of internal and external rotation angles from a direct-facing position. This approach is considered to be valuable for analyzing motor movements during sports and rehabilitation. Full article

The burgeoning interest in intelligent transportation systems (ITS) and the widespread adoption of in-vehicle amenities like infotainment have spurred a heightened fascination with vehicular ad-hoc networks (VANETs). Multi-hop routing protocols are pivotal in actualizing these in-vehicle services, such as infotainment, wirelessly. This study presents a novel protocol called multiple junction-based traffic-aware routing (MJTAR) for VANET vehicles operating in urban environments. MJTAR represents an advancement over the improved greedy traffic-aware routing (GyTAR) protocol. MJTAR introduces a distributed mechanism capable of recognizing vehicle traffic and computing curve metric distances based on two-hop junctions. Additionally, it employs a technique to dynamically select the most optimal multiple junctions between source and destination using the ant colony optimization (ACO) algorithm. We implemented the proposed protocol using the network simulator 3 (NS-3) and simulation of urban mobility (SUMO) simulators and conducted performance evaluations by comparing it with GSR and GyTAR. Our evaluation demonstrates that the proposed protocol surpasses GSR and GyTAR by over 20% in terms of packet delivery ratio, with the end-to-end delay reduced to less than 1.3 s on average. Full article

Within the context of a smart home, detecting the operating status of appliances in the environment plays a pivotal role, estimating power consumption, issuing overuse reminders, and identifying faults. The traditional contact-based approaches require equipment updates such as incorporating smart sockets or high-precision electric meters. Non-constant approaches involve the use of technologies like laser and Ultra-Wideband (UWB) radar. The former can only monitor one appliance at a time, and the latter is unable to detect appliances with extremely tiny vibrations and tends to be susceptible to interference from human activities. To address these challenges, we introduce HomeOSD, an advanced appliance status-detection system that uses mmWave radar. This innovative solution simultaneously tracks multiple appliances without human activity interference by measuring their extremely tiny vibrations. To reduce interference from other moving objects, like people, we introduce a Vibration-Intensity Metric based on periodic signal characteristics. We present the Adaptive Weighted Minimum Distance Classifier (AWMDC) to counteract appliance vibration fluctuations. Finally, we develop a system using a common mmWave radar and carry out real-world experiments to evaluate HomeOSD’s performance. The detection accuracy is 95.58%, and the promising results demonstrate the feasibility and reliability of our proposed system. Full article

The advancement of novel water treatment technologies requires the implementation of both accurate data measurement and recording processes. These procedures are essential for acquiring results and conducting thorough analyses to enhance operational efficiency. In addition, accurate sensor data facilitate precise control over chemical treatment dosages, ensuring optimal water quality and corrosion inhibition while minimizing chemical usage and associated costs. Under this framework, this paper describes the sensoring and monitoring solution for a hybrid system based on a cooling tower (CT) connected to mechanical vapor compression (MVC) equipment for desalination and brine concentration purposes. Sensors connected to the data commercial logger solution, Almemo 2890-9, are also discussed in detail such as temperature, relative humidity, pressure, flow rate, etc. The monitoring system allows remote control of the MVC based on a server, GateManager, and TightVNC. In this way, the proposed solution provides remote access to the hybrid system, being able to visualize gathered data in real time. A case study located in Cartagena (Spain) is used to assess the proposed solution. Collected data from temperature transmitters, pneumatic valves, level sensors, and power demand are included and discussed in the paper. These variables allow a subsequent forecasting process to estimate brine concentration values. Different sample times are included in this paper to minimize the collected data from the hybrid system within suitable operation conditions. This solution is suitable to be applied to other desalination processes and locations. Full article

Modern society increasingly recognizes brain fatigue as a critical factor affecting human health and productivity. This study introduces a novel, portable, cost-effective, and user-friendly system for real-time collection, monitoring, and analysis of physiological signals aimed at enhancing the precision and efficiency of brain fatigue recognition and broadening its application scope. Utilizing raw physiological data, this study constructed a compact dataset that incorporated EEG and ECG data from 20 subjects to index fatigue characteristics. By employing a Bayesian-optimized multi-granularity cascade forest (Bayes-gcForest) for fatigue state recognition, this study achieved recognition rates of 95.71% and 96.13% on the DROZY public dataset and constructed dataset, respectively. These results highlight the effectiveness of the multi-modal feature fusion model in brain fatigue recognition, providing a viable solution for cost-effective and efficient fatigue monitoring. Furthermore, this approach offers theoretical support for designing rest systems for researchers. Full article

This paper reports on the design, modeling, and characterization of a multi-resonant, directional, MEMS acoustic sensor. The design builds on previous resonant MEMS sensor designs to broaden the sensor’s usable bandwidth while maintaining a high signal-to-noise ratio (SNR). These improvements make the sensor more attractive for detecting and tracking sound sources with acoustic signatures that are broader than discrete tones. In-air sensor characterization was conducted in an anechoic chamber. The sensor was characterized underwater in a semi-anechoic pool and in a standing wave tube. The sensor demonstrated a cosine-like directionality, a maximum acoustic sensitivity of 47.6 V/Pa, and a maximum SNR of 88.6 dB, for 1 Pa sound pressure, over the bandwidth of the sensor circuitry (100 Hz–3 kHz). The presented design represents a significant improvement in sensor performance compared to similar resonant MEMS sensor designs. Increasing the sensitivity of a single-resonator design is typically associated with a decrease in bandwidth. This multi-resonant design overcomes that limitation. Full article

The investigation of functional materials derived from sustainable and eco-friendly bioresources has generated significant attention. Herein, nanocomposite films based on chiral nematic cellulose crystals (CNCs) were developed by incorporating xylose and biocompatible ZnO nanoparticles (NPs) via evaporation-induced self-assembly (EISA). The nanocomposite films exhibited iridescent color changes that corresponded to the birefringence phenomenon under polarized light, which was attributed to the formation of cholesteric structures. ZnO nanoparticles were proved to successfully adjust the helical pitches of the chiral arrangements of the CNCs, resulting in tunable optical light with shifted wavelength bands. Furthermore, the nanocomposite films showed fast humidity and ethanol stimuli response properties, exhibiting the potential of stimuli sensors of the CNC-based sustainable materials. Full article

Osteoporotic vertebral compression fractures (OVCFs) significantly increase morbidity and mortality, presenting a formidable challenge in healthcare. Traditional interventions such as vertebroplasty and kyphoplasty, despite their widespread use, are limited in addressing the secondary effects of vertebral fractures in adjacent areas and do not facilitate bone regeneration. This review paper explores the emerging domain of regenerative therapies, spotlighting stem cell therapy’s transformative potential in OVCF treatment. It thoroughly describes the therapeutic possibilities and mechanisms of action of mesenchymal stem cells against OVCFs, relying on recent clinical trials and preclinical studies for efficacy assessment. Our findings reveal that stem cell therapy, particularly in combination with scaffolding materials, holds substantial promise for bone regeneration, spinal stability improvement, and pain mitigation. This integration of stem cell-based methods with conventional treatments may herald a new era in OVCF management, potentially improving patient outcomes. This review advocates for accelerated research and collaborative efforts to translate laboratory breakthroughs into clinical practice, emphasizing the revolutionary impact of regenerative therapies on OVCF management. In summary, this paper positions stem cell therapy at the forefront of innovation for OVCF treatment, stressing the importance of ongoing research and cross-disciplinary collaboration to unlock its full clinical potential. Full article

One-carbon (1-C) metabolic deficiency impairs homeostasis, driving disease development, including infertility. It is of importance to summarize the current evidence regarding the clinical utility of 1-C metabolism-related biomolecules and methyl donors, namely, folate, betaine, choline, vitamin B12, homocysteine (Hcy), and zinc, as potential biomarkers, dietary supplements, and culture media supplements in the context of medically assisted reproduction (MAR). A narrative review of the literature was conducted in the PubMed/Medline database. Diet, ageing, and the endocrine milieu of individuals affect both 1-C metabolism and fertility status. In vitro fertilization (IVF) techniques, and culture conditions in particular, have a direct impact on 1-C metabolic activity in gametes and embryos. Critical analysis indicated that zinc supplementation in cryopreservation media may be a promising approach to reducing oxidative damage, while female serum homocysteine levels may be employed as a possible biomarker for predicting IVF outcomes. Nonetheless, the level of evidence is low, and future studies are needed to verify these data. One-carbon metabolism-related processes, including redox defense and epigenetic regulation, may be compromised in IVF-derived embryos. The study of 1-C metabolism may lead the way towards improving MAR efficiency and safety and ensuring the lifelong health of MAR infants. Full article

An imbalance between production and excretion of amyloid β peptide (Aβ) in the brain tissues of Alzheimer’s disease (AD) patients leads to Aβ accumulation and the formation of noxious Aβ oligomers/plaques. A promising approach to AD prevention is the reduction of free Aβ levels by directed enhancement of Aβ binding to its natural depot, human serum albumin (HSA). We previously demonstrated the ability of specific low-molecular-weight ligands (LMWLs) in HSA to improve its affinity for Aβ. Here we develop this approach through a bioinformatic search for the clinically approved AD-related LMWLs in HSA, followed by classification of the candidates according to the predicted location of their binding sites on the HSA surface, ranking of the candidates, and selective experimental validation of their impact on HSA affinity for Aβ. The top 100 candidate LMWLs were classified into five clusters. The specific representatives of the different clusters exhibit dramatically different behavior, with 3- to 13-fold changes in equilibrium dissociation constants for the HSA–Aβ40 interaction: prednisone favors HSA–Aβ interaction, mefenamic acid shows the opposite effect, and levothyroxine exhibits bidirectional effects. Overall, the LMWLs in HSA chosen here provide a basis for drug repurposing for AD prevention, and for the search of medications promoting AD progression. Full article

Sport injuries, including the anterior crucial ligament rupture (ACLR) seem to be related to complex genetic backgrounds, including the genes responsible for inflammatory response. This review and meta-analysis investigated the contribution of the polymorphisms of genes encoding inflammatory cytokines and their receptors to the risk of ACLR. The scientific databases Science Direct, EBSCO host, Scopus, PubMed, and Google Scholar were screened (completed on 14^th June 2023) according to the established inclusion/exclusion criteria (only fully accessible, original, human case–control studies written in English concerning the effect of interleukin genes’ polymorphisms on the occurrence of ACL injury were included) and statistical meta-analysis using R version 4.0.3 was performed. The PRISMA methodology was used to review articles. The review protocol was registered under the number CRD42024514316 in the Prospero database. Eighty-nine studies were identified and narrowed down to three original case–control studies used for the meta-analysis. The studies analyzed Polish, South African, and Swedish cohorts, altogether 1282 participants. The candidate polymorphisms indicated in the studies involved IL6 rs1800795, IL6R rs2228145 and IL1B rs16944. The systematic review showed the relationships between IL6 rs1800795 polymorphism and ACLR in the Polish subpopulation, and IL6R rs2228145 and IL1B rs16944 in the South African subpopulations. The meta-analysis revealed that the IL6 rs1800795 CG genotype was over-represented (OR = 1.30, 95% CI 1.02–1.66), while the CC genotype was under-represented (OR = 0.75, 95% CI 0.54–1.03) in ACLR subjects, but no significant impact of IL6R rs2228145 was shown. Additionally, a tendency of the IL1B rs16944 CT genotype to be protective (OR 0.89, 95% CI 0.70–1.14), while the TT to be a risk genotype (OR 1.19, 95% CI 0.84–1.68) was observed. Thus, the relationship between the interleukin receptor IL6R rs2228145 and ACLR risk was not confirmed. however, the impact of genes coding pleiotropic IL6 rs1800795 on the incidences of ACLR was clear and the effect of pro-inflammatory IL1B rs16944 was possible. Full article

Acacia melanoxylon is highly valued for its commercial applications, with the heartwood exhibiting a range of colors from dark to light among its various clones. The underlying mechanisms contributing to this color variation, however, have not been fully elucidated. In an effort to understand the factors that influence the development of dark heartwood, a comparative analysis was conducted on the microstructure, substance composition, differential gene expression, and metabolite profiles in the sapwood (SW), transition zone (TZ), and heartwood (HW) of two distinct clones, SR14 and SR25. A microscopic examination revealed that heartwood color variations are associated with an increased substance content within the ray parenchyma cells. A substance analysis indicated that the levels of starches, sugars, and lignin were more abundant in SP compared to HW, while the concentrations of phenols, flavonoids, and terpenoids were found to be higher in HW than in SP. Notably, the dark heartwood of the SR25 clone exhibited greater quantities of phenols and flavonoids compared to the SR14 clone, suggesting that these compounds are pivotal to the color distinction of the heartwood. An integrated analysis of transcriptome and metabolomics data uncovered a significant accumulation of sinapyl alcohol, sinapoyl aldehyde, hesperetin, 2′, 3, 4, 4′, 6′-peptahydroxychalcone 4′-O-glucoside, homoeriodictyol, and (2S)-liquiritigenin in the heartwood of SR25, which correlates with the up-regulated expression of CCRs (evm.TU.Chr3.1751, evm.TU.Chr4.654_667, evm.TU.Chr4.675, evm.TU.Chr4.699, and evm.TU.Chr4.704), COMTs (evm.TU.Chr13.3082, evm.TU.Chr13.3086, and evm.TU.Chr7.1411), CADs (evm.TU.Chr10.2175, evm.TU.Chr1.3453, and evm.TU.Chr8.1600), and HCTs (evm.TU.Chr4.1122, evm.TU.Chr4.1123, evm.TU.Chr8.1758, and evm.TU.Chr9.2960) in the TZ of A. melanoxylon. Furthermore, a marked differential expression of transcription factors (TFs), including MYBs, AP2/ERFs, bHLHs, bZIPs, C2H2s, and WRKYs, were observed to be closely linked to the phenols and flavonoids metabolites, highlighting the potential role of multiple TFs in regulating the biosynthesis of these metabolites and, consequently, influencing the color variation in the heartwood. This study facilitates molecular breeding for the accumulation of metabolites influencing the heartwood color in A. melanoxylon, and offers new insights into the molecular mechanisms underlying heartwood formation in woody plants. Full article

Sjögren’s Disease (SjD) is an autoimmune disease of the exocrine tissues. Etiological events result in the loss of epithelial homeostasis alongside extracellular matrix (ECM) destruction within the salivary and lacrimal glands, followed by immune cell infiltration. In this review, we have assessed the current understanding of epithelial–mesenchymal transition (EMT)-associated changes within the salivary epithelium potentially involved in salivary dysfunction and SjD pathogenesis. We performed a PubMed literature review pertaining to the determination of pathogenic events that lead to EMT-related epithelial dysfunction and signaling in SjD. Molecular patterns of epithelial dysfunction in SjD salivary glands share commonalities with EMT mediating wound healing. Pathological changes altering salivary gland integrity and function may precede direct immune involvement while perpetuating MMP9-mediated ECM destruction, inflammatory mediator expression, and eventual immune cell infiltration. Dysregulation of EMT-associated factors is present in the salivary epithelium of SjD and may be significant in initiating and perpetuating the disease. In this review, we further highlight the gap regarding mechanisms that drive epithelial dysfunction in salivary glands in the early or subclinical pre-lymphocytic infiltration stages of SjD. Full article

Since we aim to test new options to find medication for cognitive disorders, we have begun to assess the effect of semaglutide and to conduct a review gathering studies that have attempted this purpose. This systematic review focuses on the cognitive effects of semaglutide, a glucagon-like peptide 1 receptor agonist (GLP-1 RA), in the context of neurological and cognitive impairment. Semaglutide, a synthetic GLP-1 analog, showcased neuroprotective effects beyond metabolic regulation. It mitigated apoptosis and improved cognitive dysfunction in cerebrovascular disease, suggesting broader implications for neurological well-being. Also, studies highlighted GLP-1 RAs’ positive impact on olfactory function in obese individuals with type 2 diabetes, on neurodegenerative disorders, multiple sclerosis, and endotoxemia. In order to analyze current studies that assess the impact of semaglutide on cognitive function, a literature search was conducted up to February 2024 on two online databases, MEDLINE (via PubMed) and Web of Science Core Collection, as well as various websites. Fifteen studies on mice populations and two studies on cell lines were included, analyzed, and assessed with bias-specific tools. The neuroprotective and anti-apoptotic properties of GLP-1 and its analogs were emphasized, with animal models and cell line studies demonstrating enhanced cognitive function. While promising, limitations include fewer studies, highlighting the need for extensive research, particularly in the human population. Even though this medication seems promising, there are significant limitations, one of which is the lack of studies on human subjects. Therefore, this review aims to gather current evidence. Full article

RNA transcripts play a crucial role as witnesses of gene expression health. Identifying disruptive short sequences in RNA transcription and regulation is essential for potentially treating diseases. Let us delve into the mathematical intricacies of these sequences. We have previously devised a mathematical approach for defining a “healthy” sequence. This sequence is characterized by having at most four distinct nucleotides (denoted as $nt\le 4$). It serves as the generator of a group denoted as $f_p$. The desired properties of this sequence are as follows: $f_p$ should be close to a free group of rank $nt-1$, it must be aperiodic, and $f_p$ should not have isolated singularities within its $S{L}_2\left(\mathbb{C}\right)$ character variety (specifically within the corresponding Groebner basis). Now, let us explore the concept of singularities. There are cubic surfaces associated with the character variety of a four-punctured sphere denoted as $S_2^4$. When we encounter these singularities, we find ourselves dealing with some algebraic solutions of a dynamical second-order differential (and transcendental) equation known as the Painlevé VI Equation. In certain cases, $S_2^4$ degenerates, in the sense that two punctures collapse, resulting in a “wild” dynamics governed by the Painlevé equations of an index lower than VI. In our paper, we provide examples of these fascinating mathematical structures within the context of miRNAs. Specifically, we find a clear relationship between decorated character varieties of Painlevé equations and the character variety calculated from the seed of oncomirs. These findings should find many applications including cancer research and the investigation of neurodegenative diseases. Full article

The cytoskeleton plays a pivotal role in maintaining the epithelial phenotype and is vital to several hallmark processes of cancer. Over the past decades, researchers have identified the epithelial protein lost in neoplasm (EPLIN, also known as LIMA1) as a key regulator of cytoskeletal dynamics, cytoskeletal organization, motility, as well as cell growth and metabolism. Dysregulation of EPLIN is implicated in various aspects of cancer progression, such as tumor growth, invasion, metastasis, and therapeutic resistance. Its altered expression levels or activity can disrupt cytoskeletal dynamics, leading to aberrant cell motility and invasiveness characteristic of malignant cells. Moreover, the involvement of EPLIN in cell growth and metabolism underscores its significance in orchestrating key processes essential for cancer cell survival and proliferation. This review provides a comprehensive exploration of the intricate roles of EPLIN across diverse cellular processes in both normal physiology and cancer pathogenesis. Additionally, this review discusses the possibility of EPLIN as a potential target for anticancer therapy in future studies. Full article

Today, allergies have become a serious problem. PR-10 proteins are clinically relevant allergens that have the ability to bind hydrophobic ligands, which can significantly increase their allergenicity potential. It has been recently shown that not only the birch pollen allergen Bet v 1 but also the alder pollen allergen Aln g 1, might act as a true sensitizer of the immune system. The current investigation is aimed at the further study of the allergenic and structural features of Aln g 1. By using qPCR, we showed that Aln g 1 was able to upregulate alarmins in epithelial cells, playing an important role in sensitization. With the use of CD-spectroscopy and ELISA assays with the sera of allergic patients, we demonstrated that Aln g 1 did not completely restore its structure after thermal denaturation, which led to a decrease in its IgE-binding capacity. Using site-directed mutagenesis, we revealed that the replacement of two residues (Asp27 and Leu30) in the structure of Aln g 1 led to a decrease in its ability to bind to both IgE from sera of allergic patients and lipid ligands. The obtained data open a prospect for the development of hypoallergenic variants of the major alder allergen Aln g 1 for allergen-specific immunotherapy. Full article

Tau protein misfolding and aggregation are pathological hallmarks of Alzheimer’s disease and over twenty neurodegenerative disorders. However, the molecular mechanisms of tau aggregation in vivo remain incompletely understood. There are two types of tau aggregates in the brain: soluble aggregates (oligomers and protofibrils) and insoluble filaments (fibrils). Compared to filamentous aggregates, soluble aggregates are more toxic and exhibit prion-like transmission, providing seeds for templated misfolding. Curiously, in its native state, tau is a highly soluble, heat-stable protein that does not form fibrils by itself, not even when hyperphosphorylated. In vitro studies have found that negatively charged molecules such as heparin, RNA, or arachidonic acid are generally required to induce tau aggregation. Two recent breakthroughs have provided new insights into tau aggregation mechanisms. First, as an intrinsically disordered protein, tau is found to undergo liquid-liquid phase separation (LLPS) both in vitro and inside cells. Second, cryo-electron microscopy has revealed diverse fibrillar tau conformations associated with different neurodegenerative disorders. Nonetheless, only the fibrillar core is structurally resolved, and the remainder of the protein appears as a “fuzzy coat”. From this review, it appears that further studies are required (1) to clarify the role of LLPS in tau aggregation; (2) to unveil the structural features of soluble tau aggregates; (3) to understand the involvement of fuzzy coat regions in oligomer and fibril formation. Full article