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Abstract This study tested if a high-resolution, multi-modal, multi-scale retinal imaging instrument can provide novel information about structural abnormalities in vivo. The study examined 11 patients with very mild to moderate non-proliferative diabetic retinopathy (NPDR) and 10 healthy subjects using fundus photography, optical coherence tomography (OCT), OCT angiography (OCTA), adaptive optics scanning laser ophthalmoscopy (AO-SLO), adaptive optics OCT and OCTA (AO-OCT(A)). Of 21 eyes of 11 patients, 11 had very mild NPDR, 8 had mild NPDR, 2 had moderate NPDR, and 1 had no retinopathy. Using AO-SLO, capillary looping, inflections and dilations were detected in 8 patients with very mild or mild NPDR, and microaneurysms containing hyperreflective granular elements were visible in 9 patients with mild or moderate NPDR. Most of the abnormalities were seen to be perfused in the corresponding OCTA scans while a few capillary loops appeared to be occluded or perfused at a non-detectable flow rate, possibly because of hypoperfusion. In one patient with moderate NPDR, non-perfused capillaries, also called ghost vessels, were identified by alignment of corresponding en face AO-OCT and AO-OCTA images. The combination of multiple non-invasive imaging methods could identify prominent microscopic abnormalities in diabetic retinopathy earlier and more detailed than conventional fundus imaging devices.

Abstract Alzheimer's disease (AD) shows a high pathological and symptomatological heterogeneity. To study this heterogeneity, we have developed a patient stratification technique based on one of the most significant risk factors for the development of AD: genetics. We addressed this challenge by including network biology concepts, mapping genetic variants data into a brain-specific protein–protein interaction (PPI) network, and obtaining individualized PPI scores that we then used as input for a clustering technique. We then phenotyped each obtained cluster regarding genetics, sociodemographics, biomarkers, fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging, and neurocognitive assessments. We found three clusters defined mainly by genetic variants found in MAPT, APP, and APOE, considering known variants associated with AD and other neurodegenerative disease genetic architectures. Profiling of these clusters revealed minimal variation in AD symptoms and pathology, suggesting different biological mechanisms may activate the neurodegeneration and pathobiological patterns behind AD and result in similar clinical and pathological presentations, even a shared disease diagnosis. Lastly, our research highlighted MAPT, APP, and APOE as key genes where these genetic distinctions manifest, suggesting them as potential targets for personalized drug development strategies to address each AD subgroup individually.

Abstract Post-COVID condition (PCC) and multiple sclerosis (MS) share some clinical and demographic features, including cognitive symptoms and fatigue. Some pathophysiological mechanisms well-known in MS, such as autoimmunity, neuroinflammation and myelin damage, have also been implicated in PCC. In this study, we aimed to compare the cognitive phenotypes of two large cohorts of patients with PCC and MS, and to evaluate the relationship between fatigue and cognitive performance. Cross-sectional study including 218 patients with PCC and 218 with MS matched by age, sex, and years of education. Patients were evaluated with a comprehensive neuropsychological protocol and were categorized according to the International Classification of Cognitive Disorders system. Fatigue and depression were also assessed. Cognitive profiles of PCC and MS largely overlapped, with a greater impairment in episodic memory in MS, but with small effect sizes. The most salient deficits in both disorders were in attention and processing speed. The severity of fatigue was greater in patients with PCC. Still, the correlations between fatigue severity and neuropsychological tests were more prominent in the case of MS. There were no differences in the severity of depression among groups. Our study found similar cognitive profiles in PCC and MS. Fatigue was more severe in PCC, but was more associated with cognitive performance in MS. Further comparative studies addressing the mechanisms related to cognitive dysfunction and fatigue may be of interest to advance the knowledge of these disorders and develop new therapies.

Abstract Healthcare workers (HCWs) were at high risk of experiencing psychological distress during COVID-19 pandemic. The objective of this study was to evaluate the impact on HCWs’ mental health in a Spanish hospital. Cross-sectional study of HCW, active between May and June 2020. A web-based survey assessed probable current mental disorders (major depressive disorder [PHQ-8 ≥ 10], generalized anxiety disorder [GAD-7 ≥ 10], panic attacks, post-traumatic stress disorder [PTSD; PLC-5 ≥ 7], or substance use disorder [CAGE-AID ≥ 2]). The Sheehan Disability Scale (SDS) was used to assess severe impairment and items taken from the modified self‐report version of the Columbia Suicide Severity Rating Scale (C‐SSRS) assessed suicidal thoughts and behaviors. A total of 870 HCWs completed the survey. Most frequent probable mental disorders were major depressive disorder (33.6%), generalized anxiety disorder (25.5%), panic attacks (26.9%), PTSD (27.2%), and substance use disorder (5.0%). Being female, having aged 18–29 years, being an auxiliary nurse, direct exposure to COVID-19-infected patients, and pre-pandemic lifetime mental disorders were positively associated with mental issues. Hospital HCWs presented a high prevalence of symptoms of mental disorders, especially depression, PTSD, panic attacks, and anxiety. Younger individuals and those with lifetime mental disorders have been more vulnerable to experiencing them.

Abstract Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by significant metabolic disruptions, including weight loss and hypermetabolism in both patients and animal models. Leptin, an adipose-derived hormone, displays altered levels in ALS. Genetically reducing leptin levels (Lepob/+) to maintain body weight improved motor performance and extended survival in female SOD1G93A mice, although the exact molecular mechanisms behind these effects remain elusive. Here, we corroborated the sexual dimorphism in circulating leptin levels in ALS patients and in SOD1G93A mice. We reproduced a previous strategy to generate a genetically deficient leptin SOD1G93A mice (SOD1G93ALepob/+) and studied the transcriptomic profile in the subcutaneous adipose tissue and the spinal cord. We found that leptin deficiency reduced the inflammation pathways activated by the SOD1G93A mutation in the adipose tissue, but not in the spinal cord. These findings emphasize the importance of considering sex-specific approaches in metabolic therapies and highlight the role of leptin in the systemic modulation of ALS by regulating immune responses outside the central nervous system.

Abstract The exploration of metal–insulator transitions to produce field-induced reversible resistive switching effects has been a longstanding pursuit in materials science. Although the resistive switching effect in strongly correlated oxides is often associated with the creation or annihilation of oxygen vacancies, the underlying mechanisms behind this phenomenon are complex and, in many cases, still not clear. This study focuses on the analysis of the superconducting performance of cuprate YBa2Cu3O7−δ (YBCO) devices switched to different resistive states through gate voltage pulses. The goal is to evaluate the effect of field-induced oxygen diffusion on the magnetic field and angular dependence of the critical current density and identify the role of induced defects in the switching performance. Transition electron microscopy measurements indicate that field-induced transition to high resistance states occurs through the generation of YBa2Cu4O7 (Y124) intergrowths with a large amount of oxygen vacancies, in agreement with the obtained critical current density dependences. These results have significant implications for better understanding the mechanisms of field-induced oxygen doping in cuprate superconductors and their role on the superconducting performance.

Abstract This study examined the latent structure of the broad range of complex neuropsychiatric morbidities occurring 1 year after COVID-19 infection. As part of the CU-COVID19 study, 248 (response rate=39.3%) of 631 adults hospitalized for COVID-19 infection in Hong Kong completed an online survey between March-2021 and January-2022. Disorder prevalence was compared against a random non-infected household sample (n=1834). 248 surveys were received on average 321 days post-infection (Mean age: 48.9, 54% female, moderate/severe/critical infection: 58.2%). 32.4% were screened to have at least one mental disorder, 78.7% of whom had concurrent fatigue/subjective cognitive impairment (SCI). Only PTSD (19.1%) was significantly more common than control (14%, p=0.047). Latent profile analysis classified individuals into P1 (12·4%)-no current neuropsychiatric morbidities, P2 (23.1%)-SCI/fatigue, P3 (45.2%)-anxiety/PTSD, P4 (19.3%)-depression. SCI and fatigue pervaded in all profiles (P2-4) with neuropsychiatric morbidities one-year post-infection. PTSD, anxiety and depressive symptoms were most important in differentiating P2-4. Past mental health and P4 independently predicted functional impairment. Neuropsychiatric morbidity was associated with past mental health, reduced resilience, financial problems, but not COVID-19 severity. Their confluence with depressive and anxiety symptoms predicted impairment and are associated with psychological and environmental factors.

Abstract Alzheimer's disease (AD) is a neurodegenerative disease whose molecular mechanisms are activated several years before cognitive symptoms appear. Genotype-based prediction of the phenotype is thus a key challenge for the early diagnosis of AD. Machine learning techniques that have been proposed to address this challenge do not consider known biological interactions between the genes used as input features, thus neglecting important information about the disease mechanisms at play. To mitigate this, we first extracted AD subnetworks from several protein–protein interaction (PPI) databases and labeled these with genotype information (number of missense variants) to make them patient-specific. Next, we trained Graph Neural Networks (GNNs) on the patient-specific networks for phenotype prediction. We tested different PPI databases and compared the performance of the GNN models to baseline models using classical machine learning techniques, as well as randomized networks and input datasets. The overall results showed that GNNs could not outperform a baseline predictor only using the APOE gene, suggesting that missense variants are not sufficient to explain disease risk beyond the APOE status. Nevertheless, our results show that GNNs outperformed other machine learning techniques and that protein–protein interactions lead to superior results compared to randomized networks. These findings highlight that gene interactions are a valuable source of information in predicting disease status.

Abstract We tested 35 Lipizzan horses older than 5 years, ridden and healthy in three behavioural tests (handling, fear-reaction, and target training test). Physiological (heart rate and heart rate variability) and anatomical measurements (120 head and body distances and angles) were collected to validate parameters that reliably inform on handling/cooperation, fear/exploration and trainability in horses. Utilizing a standard clustering methodology on the behavioural data, we identified four general types of responses and categorised an individual as intermediate, low fearful, horses with low cooperation or low trainability. We additionally analysed the head morphology following Tellington-Jones and Taylor recommendations and correlated the measurements with data from a horse personality questionnaire. Although allocation to a particular personality group was not associated with these two methods, these groups differed in six anatomical characteristics of head and body. Regardless of the group, our results indicated that shorter horses (10.5 cm) are trustworthy, less fearful and easier to handle and train. We also demonstrated that horses with stronger legs and a wider base of the head have a lower heart rate when exposed to the second trial of the handling test.

Abstract We present a compact multi-modal and multi-scale retinal imaging instrument with an angiographic functional extension for clinical use. The system integrates scanning laser ophthalmoscopy (SLO), optical coherence tomography (OCT) and OCT angiography (OCTA) imaging modalities and provides multi-scale fields of view. For high resolution, and high lateral resolution in particular, cellular imaging correction of aberrations by adaptive optics (AO) is employed. The entire instrument has a compact design and the scanning head is mounted on motorized translation stages that enable 3D self-alignment with respect to the subject’s eye by tracking the pupil position. Retinal tracking, based on the information provided by SLO, is incorporated in the instrument to compensate for retinal motion during OCT imaging. The imaging capabilities of the multi-modal and multi-scale instrument were tested by imaging healthy volunteers and patients.

Abstract $$SiO_2$$ S i O 2 with the $$\alpha$$ α -quartz structure is one of the most popular piezoelectrics. It is widely used in crystal oscillators, bulk acoustic wave (BAW) devices, surface acoustic wave (SAW) devices, and so on. $$GeO_2$$ G e O 2 can also be crystallized into the $$\alpha$$ α -quartz structure and it has better piezoelectric properties, with higher piezoelectric coefficient and electromechanical coupling coefficients, than $$SiO_2$$ S i O 2 . Experiments on bulk crystals and theoretical studies have shown that these properties can be tuned by varying the Si/Ge ratio in the $$Si_xGe_{1-x}O_2$$ S i x G e 1 - x O 2 solid solution. However, to the best of our knowledge, thin films of $$Si_xGe_{1-x}O_2$$ S i x G e 1 - x O 2 quartz have never been reported. Here we present the successful crystallization of $$Si_xGe_{1-x}O_2$$ S i x G e 1 - x O 2 thin films in the $$\alpha$$ α -quartz phase on quartz substrates ( $$SiO_2$$ S i O 2 ) with x up to 0.75. Generally, the films grow semi-epitaxially, with the same orientation as the substrates. Interestingly, the $$Si_{0.75}Ge_{0.25}O_2$$ S i 0.75 G e 0.25 O 2 composition grows fully strained by the quartz substrates and this leads to the formation of circular quartz domains with an ordered Dauphiné twin structure. These studies represent a first step towards the optimization of piezoelectric quartz thin films for high frequency (> 5 GHz) applications.

Abstract As a global health emergency, the rapid spread of the novel coronavirus disease (COVID-19) led to the implementation of widespread restrictions (e.g., quarantine, physical/social distancing measures). However, while these restrictions reduce the viral spread of COVID-19, they may exacerbate behavioural and cognitive symptoms in dementia patients and increase pressure on caregiving. Here, we aimed to assess the impact of COVID-19 and related restrictions on both carers and people living with dementia across the world. We conducted an international survey (Australia, Germany, Spain, and the Netherlands) to assess the impact of COVID-19 on carers and people living with dementia. People with dementia experienced worsened neuropsychiatric symptoms since the outbreak of COVID-19, most commonly, depression, apathy, delusions, anxiety, irritability, and agitation. Regression analyses revealed that limited understanding of the COVID-19 situation and not living with the carer was associated with worsened neuropsychiatric symptoms. Carers also reported a decline in their own mental health, increased stress and reduced social networks as a result of COVID-19 and related restrictions. Regression analyses revealed uncertainty about the future and loneliness were associated with worsened carer mental health. Findings from this study will inform strategies for the development of support services and compassionate protocols that meet the evolving needs of those living with dementia and their carers.

Abstract High-throughput third-generation nanopore sequencing devices have enormous potential for simultaneously observing epigenetic modifications in human cells over large regions of the genome. However, signals generated by these devices are subject to considerable noise that can lead to unsatisfactory detection performance and hamper downstream analysis. Here we develop a statistical method, CpelNano, for the quantification and analysis of 5mC methylation landscapes using nanopore data. CpelNano takes into account nanopore noise by means of a hidden Markov model (HMM) in which the true but unknown (“hidden”) methylation state is modeled through an Ising probability distribution that is consistent with methylation means and pairwise correlations, whereas nanopore current signals constitute the observed state. It then estimates the associated methylation potential energy function by employing the expectation-maximization (EM) algorithm and performs differential methylation analysis via permutation-based hypothesis testing. Using simulations and analysis of published data obtained from three human cell lines (GM12878, MCF-10A, and MDA-MB-231), we show that CpelNano can faithfully estimate DNA methylation potential energy landscapes, substantially improving current methods and leading to a powerful tool for the modeling and analysis of epigenetic landscapes using nanopore sequencing data.

Abstract Venta Micena is an area containing several palaeontological sites marking the beginning of the Calabrian stage (Early Pleistocene). The richness of the fossil accumulation including species of Asian, African and European origin, makes Venta Micena a key site for the the palaeoecological and palaeoenvironmental study of southern Europe during the Early Pleistocene. Thus, research has been focused on Venta Micena 3, which was originally interpreted as a single palaeosurface associated with a marshy context, in which most of the fauna was accumulated by Pachycrocuta brevirostris. Recent excavations have unearthed a new site, Venta Micena 4, located in the same stratigraphic unit (Unit C) and in close proximity to Venta Micena 3. Here we show the first analyses regarding the taphonomic and spatial nature of this new site, defining two stratigraphic boundaries corresponding to two different depositional events. Furthermore, the taphonomic analyses of fossil remains seem to indicate a different accumulative agent than Pachycrocuta, thus adding more complexity to the palaeobiological interpretation of the Venta Micena area. These results contribute to the discussion of traditional interpretations made from Venta Micena 3.

Abstract To obtain crystalline thin films of alpha-Quartz represents a challenge due to the tendency for the material towards spherulitic growth. Thus, understanding the mechanisms that give rise to spherulitic growth can help regulate the growth process. Here the spherulitic type of 2D crystal growth in thin amorphous Quartz films was analyzed by electron back-scatter diffraction (EBSD). EBSD was used to measure the size, orientation, and rotation of crystallographic grains in polycrystalline SiO2 and GeO2 thin films with high spatial resolution. Individual spherulitic Quartz crystal colonies contain primary and secondary single crystal fibers, which grow radially from the colony center towards its edge, and fill a near circular crystalline area completely. During their growth, individual fibers form so-called rotational crystals, when some lattice planes are continuously bent. The directions of the lattice rotation axes in the fibers were determined by an enhanced analysis of EBSD data. A possible mechanism, including the generation of the particular type of dislocation(s), is suggested.

Abstract In Marfan syndrome, the tunica media is disrupted, which leads to the formation of ascending aortic aneurysms. Marfan aortic samples are histologically characterized by the fragmentation of elastic laminae. However, conventional histological techniques using transverse sections provide limited information about the precise location, progression and 3D extension of the microstructural changes that occur in each lamina. We implemented a method using multiphoton excitation fluorescence microscopy and computational image processing, which provides high-resolution en-face images of segmented individual laminae from unstained whole aortic samples. We showed that internal elastic laminae and successive 2nd laminae are injured to a different extent in murine Marfan aortae; in particular, the density and size of fenestrae changed. Moreover, microstructural injuries were concentrated in the aortic proximal and convex anatomical regions. Other parameters such as the waviness and thickness of each lamina remained unaltered. In conclusion, the method reported here is a useful, unique tool for en-face laminae microstructure assessment that can obtain quantitative three-dimensional information about vascular tissue. The application of this method to murine Marfan aortae clearly shows that the microstructural damage in elastic laminae is not equal throughout the thickness of the tunica media and in the different anatomical regions of the ascending aorta.