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Background: Little is known about how intersecting social privilege and disadvantage contribute to inequities in COVID-19 information use and vaccine access. This study explored how social inequities intersect to shape access to and use of COVID-19 information and vaccines among parents in Canada., Methods: We conducted semi-structured interviews on COVID-19 vaccination information use with ethnically diverse parents of children ages 11 to 18 years from April to August 2022. We purposefully invited parents from respondents to a national online survey to ensure representation across diverse intersecting social identities. Five researchers coded transcripts in NVivo using a discourse analysis approach informed by intersectionality. Our analysis focused on use of vaccine information and intersecting privileges and oppressions, including identifying with equity-denied group(s)., Results: Interview participants (N = 48) identified as ethnically diverse non-Indigenous (n = 40) and Indigenous (n = 8) Peoples from seven Canadian provinces. Racialized minority or Indigenous participants reflected on historical and contemporary events of racism from government and medical institutions as barriers to trust and access to COVID-19 information, vaccines, and the Canadian healthcare system. Participants with privileged social locations showed greater comfort in resisting public health measures. Despite the urgency to receive COVID-19 vaccines, information gaps and transportation barriers delayed vaccination among some participants living with chronic medical conditions., Conclusion: Historicization of colonialism and ongoing events of racism are a major barrier to trusting public health information. Fostering partnerships with trusted leaders and/or healthcare workers from racialized communities may help rebuild trust. Healthcare systems need to continuously implement strategies to restore trust with Indigenous and racialized populations., (© 2024. The Author(s).)

Fibromuscular dysplasia (FMD) is a rare nonatherosclerotic, noninflammatory vascular disease affecting mostly renal and carotid arteries and is the second most frequent cause of renal artery stenosis. The symptomatology is dominated by arterial hypertension due to the frequent involvement of the renal arteries and depends on the location of the lesions. Most of the cases are middle-aged women of Caucasian origin. There are two subtypes based on angiographic aspect: multifocal FMD (80% of the cases) and focal FMD (rarer with a more balanced sex ratio). Angioplasty of the renal arteries is generally disappointing with less than 50% cure of hypertension. It appears necessary to improve our knowledge of the FMD and to optimize the selection of eligible patients for revascularization with transdisciplinary collegial therapeutic decision.

Background: A better understanding of the neural mechanisms regulating impaired satiety to palatable foods is essential to treat hyperphagia linked with obesity. The satiation hormone amylin signals centrally at multiple nuclei including the ventral tegmental area (VTA). VTA-to-medial prefrontal cortex (mPFC) projections encode food reward information to influence behaviors including impulsivity. We hypothesized that modulation of VTA-to-mPFC neurons underlies amylin-mediated decreases in palatable food-motivated behaviors., Methods: We used a variety of pharmacological, behavioral, genetic, and viral approaches (n = 4-16/experiment) to investigate the anatomical and functional circuitry of amylin-controlled VTA-to-mPFC signaling in rats., Results: To first establish that VTA amylin receptor (calcitonin receptor) activation can modulate mPFC activity, we showed that intra-VTA amylin decreased food-evoked mPFC cFos. VTA amylin delivery also attenuated food-directed impulsive behavior, implicating VTA amylin signaling as a regulator of mPFC functions. Palatable food activates VTA dopamine and mPFC neurons. Accordingly, dopamine receptor agonism in the mPFC blocked the hypophagic effect of intra-VTA amylin, and VTA amylin injection reduced food-evoked phasic dopamine levels in the mPFC, supporting the idea that VTA calcitonin receptor activation decreases dopamine release in the mPFC. Surprisingly, calcitonin receptor expression was not found on VTA-to-mPFC projecting neurons but was instead found on GABAergic (gamma-aminobutyric acidergic) interneurons in the VTA that provide monosynaptic inputs to this pathway. Blocking intra-VTA GABA signaling, through GABA receptor antagonists and DREADD (designer receptor exclusively activated by designer drugs)-mediated GABAergic neuronal silencing, attenuated intra-VTA amylin-induced hypophagia., Conclusions: These results indicate that VTA amylin signaling stimulates GABA-mediated inhibition of dopaminergic projections to the mPFC to mitigate impulsive consumption of palatable foods., (Copyright © 2023 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Background: We used nationally representative data to explore associations among location of residence (rural/urban) and perceived barriers to physical activity (PA) in Canadian youth., Methods: We analyzed the 2017 Canadian Community Health Survey, Barriers to Physical Activity Rapid Response data for 12- to 17-year-old youth. Nine items from the survey assessing perceived barriers to PA were combined into 3 barrier domains: resources, motivational, and socioenvironmental. The likelihood of reporting barriers to PA based on rural-urban location was examined using survey-weighted binary logistic regression following a model fitting approach. Sociodemographic factors were modeled as covariates and tested in interaction with location. For each barrier domain, we derived the best-fitting model with fewest terms., Results: There were no location-specific effects related to reporting any barrier or motivation-related PA barriers. We found a sex by location interaction predicting the likelihood of reporting resource-related barriers. Rural boys were less likely to report resource-related barriers compared with urban boys (odds ratio [OR] = 0.42 [0.20, 0.88]). Rural girls were more likely to report resource-related barriers compared with boys (OR = 3.72 [1.66, 8.30]). Regarding socioenvironmental barriers, we observed a significant body mass index by location interaction demonstrating that rural youth with body mass index outside the "normal range" showed a higher likelihood of reporting socioenvironmental barriers compared with urban youth (OR = 2.38 [1.32, 4.30]). For urban youth, body mass index was unrelated to reporting socioenvironmental barriers (OR = 1.07 [0.67, 1.71])., Conclusion: PA barriers are not universal among Canadian youth. Our analyses highlight the importance of testing interactions in similar studies as well as considering key sociodemographic characteristics when designing interventions.

Free polymannose-type oligosaccharides (fOS) are processed by cytosolic enzymes to generate Man5GlcNAc which is transferred to lysosomes and degraded. Lysosomal fOS import was demonstrated in vitro but is poorly characterized in part due to lack of convenient substrates. As chitooligosaccharides (COS, oligomers β1,4-linked GlcNAc) block [3H]Man5GlcNAc transport into lysosomes, we asked if COS are themselves transported and if so, can they be chemically modified to generate fluorescent substrates. We show that COS are degraded by lysosomal hydrolases to generate GlcNAc, and robust ATP-dependent transport of [3H]COS2/4 di and tetrasaccharides into intact rat liver lysosomes was observed only after blocking lysosomal [3H]GlcNAc efflux with cytochalasin B. As oligosaccharides with unmodified reducing termini are the most efficient inhibitors of [3H]COS2/4 and [3H]Man5GlcNAc transport, the non-reducing GlcNAc residue of COS2-4 was de-N-acetylated using Sinorhizobium meliloti NodB, and the resulting amine substituted with rhodamine B (RB) to yield RB-COS2-4. The fluorescent compounds inhibit [3H]Man5GlcNAc transport and display temperature-sensitive, ATP-dependent transport into a sedimentable compartment that is ruptured with the lysosomotropic agent L-methyl methionine ester. Once in this compartment, RB-COS3 is converted to RB-COS2 further identifying it as the lysosomal compartment. RB-COS2/3 and [3H]Man5GlcNAc transports are blocked similarly by competing sugars, and are partially inhibited by the vacuolar ATPase inhibitor bafilomycin and high concentrations of the P-type ATPase inhibitor orthovanadate. These data show that Man5GlcNAc, COS2/4 and RB-COS2/3 are transported into lysosomes by the same or closely related mechanism and demonstrate the utility of COS modified at their non-reducing terminus to study lysosomal oligosaccharide transport., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Candida auris is a fungal pathogen of humans responsible for nosocomial infections with high mortality rates. High levels of resistance to antifungal drugs and environmental persistence mean these infections are difficult to treat and eradicate from a healthcare setting. Understanding the life cycle and the genetics of this fungus underpinning clinically relevant traits, such as antifungal resistance and virulence, is of the utmost importance to develop novel treatments and therapies. Epidemiological and genomic studies have identified five geographical clades (I-V), which display phenotypic and genomic differences. Aggregation of cells, a phenotype primarily of clade III strains, has been linked to reduced virulence in some infection models. The aggregation phenotype has thus been associated with conferring an advantage for (skin) colonisation rather than for systemic infection. However, strains with different clade affiliations were compared to infer the effects of different morphologies on virulence. This makes it difficult to distinguish morphology-dependent causes from clade-specific or even strain-specific genetic factors. Here, we identify two different types of aggregation: one induced by antifungal treatment which is a result of a cell separation defect; and a second which is controlled by growth conditions and only occurs in strains with the ability to aggregate. The latter aggregation type depends on an ALS-family adhesin which is differentially expressed during aggregation in an aggregative C. auris strain. Finally, we demonstrate that macrophages cannot clear aggregates, suggesting that aggregation might after all provide a benefit during systemic infection and could facilitate long-term persistence in the host., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Pelletier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Purpose: To qualitatively describe experiences of chronic disease management and prevention in older adults (age ≥65 years) during COVID-19., Approach: Qualitative descriptive approach., Setting: Data collected online via telephone and video-conferencing technologies to participants located in various cities in British Columbia, Canada. Data analyzed by researchers in the cities of Vancouver and Kelowna in British Columbia., Participants: Twenty-four community-living older adults (n = 24) age ≥65 years., Methods: Each participant was invited to complete a 30-to-45-minute virtual, semi-structured, one-on-one interview with a trained interviewer. Interview questions focused on experiences managing health prior to COVID-19 and transitioning experiences of practicing health management and prevention strategies during COVID-19. Audio recordings of interviews were transcribed verbatim and analyzed thematically., Results: The sample's mean age was 73.4 years (58% female) with 75% reporting two or more chronic conditions (12.5% none, 12.5% one). Three themes described participants' strategies for chronic disease management and prevention: (1) having a purpose to optimize health (i.e., managing health challenges and maintaining independence); (2) internal self-control strategies (i.e., self-accountability and adaptability); and (3) external support strategies (i.e., informational support, motivational support, and emotional support)., Conclusion: Helping older adults identify purposes for their own health management, developing internal control strategies, and optimizing social support opportunities may be important person-centred strategies for chronic disease management and prevention during unprecedented times like COVID-19., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

In Quebec (Canada), the roll-out of the vaccination started slowly in December 2020 due to limited vaccine supply. While the first and second doses were well-accepted among adults and vaccine uptake was above 90%, in late 2021 and 2022, vaccine acceptance decreased for children vaccination and receipt of a 3rd or a 4th dose. In the autumn of 2022, four focus groups were conducted with vaccine-hesitant parents of children aged 0-4 and adults who expressed little intention to receive a booster dose. The objective of this study was to gather participants' perspectives on vaccination in general, on the COVID-19 vaccination campaign and the information available, and to gain insights into the underlying reasons for their low intention of either having their child(ren) vaccinated, or receiving an additional dose of vaccine. A total of 35 participants took part in the focus groups. While participants expressed a certain level of trust and confidence in public health and government authorities regarding pandemic management and the vaccination campaign, they were also concerned that transparent information was lacking to support an informed decision on booster doses and children's vaccination. Many participants felt adequately protected against the infection during the focus groups, citing a lack of perceived benefits as the primary reason for refusing a booster dose. Parents who refused to administer the COVID-19 vaccine to their young children felt that the vaccine was not useful for children and were concerned about potential side effects. The majority reported that their opinions regarding other recommended vaccines had not changed since the beginning of the pandemic. While these results are reassuring, our findings highlight the importance of transparency in public health communications about vaccines to increase confidence and to develop strategies to address vaccine fatigue and complacency toward COVID-19 vaccines., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Pelletier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Physical activity improves the well-being of persons living with dementia but few exercise programs include them. The Dementia-Inclusive Choices for Exercise (DICE) toolkit aims to improve exercise providers' understanding of dementia and ability to support persons living with dementia in physical activity. We evaluated the co-designed DICE toolkit with exercise providers using a mixed-methods approach comprising pre/post questionnaires and interviews and reflection diaries. Among 16 participants, self-efficacy for exercise delivery to persons living with dementia and both knowledge and attitudes toward dementia significantly improved. Thematic analysis suggested participants (a) had a deeper understanding of the variability of dementia, (b) were planning for equitable access for persons living with dementia, (c) planned to promote social connection through exercise, and (d) were optimistic for future engagement with persons living with dementia. The DICE toolkit may improve exercise providers' knowledge and confidence to plan proactively to support persons living with dementia in programs and services.

Although self-assembly has emerged as an effective tool for fabricating biomaterials, achieving precise control over the morphologies and functionalities of the resultant assemblies remains an ongoing challenge. Inspired by the copper peptide naturally present in human plasma, in this study, we designed a synthetic precursor, FcGH. FcGH can self-assemble via two distinct pathways: spontaneous and Cu 2+ -induced. These two assembly pathways enabled the formation of assemblies with tunable morphologies by adjusting the amount of added Cu 2+ . We found that the nanoparticles formed by Cu 2+ -induced self-assembly exhibited a significantly higher cellular uptake efficiency than the wormlike fibers formed spontaneously. Moreover, this Cu 2+ -induced assembly process occurred spontaneously at a 1 : 1 molar ratio of Cu 2+ to FcGH, avoiding the excessive use of Cu 2+ and a tedious preparation procedure. By co-assembling with 10-hydroxycamptothecin (HCPT)-conjugated FcGH, Cu 2+ -induced supramolecular nanodrugs elicited multiple cell death modalities in cancer cells with elevated immunogenicity, enhancing the therapeutic effect compared to free HCPT. This study highlights Cu 2+ -induced self-assembly as an efficient tool for directing the assembly of nanodrugs and for synergistic tumor therapy., (© 2024 Wiley-VCH GmbH.)

Innate immune defense mechanisms against infection and cancer encompass the modulation of pattern recognition receptor (PRR)-mediated inflammation, including upregulation of various transcription factors and the activation of pro-inflammatory pathways important for immune surveillance. Dysfunction of PRRs-mediated signaling has been implicated in cancer and autoimmune diseases, while the overactivation of PRRs-driven responses during infection can lead to devastating consequences such as acute lung injury or sepsis. We used crystal structure-based design to develop immunomodulatory lipopolysaccharide (LPS) mimetics targeting one of the ubiquitous PRRs, Toll-like Receptor 4 (TLR4). Taking advantage of an exo-anomeric conformation and specific molecular shape of synthetic nonreducing β,β-diglucosamine, which was investigated by NMR, we developed two sets of lipid A mimicking glycolipids capable of either potently activating innate immune responses or inhibiting pro-inflammatory signaling. Stereoselective 1,1'-glycosylation towards fully orthogonally protected nonreducing GlcNβ(1↔1')βGlcN followed by stepwise assembly of differently functionalised phosphorylated glycolipids provided biologically active molecules that were evaluated for their ability to trigger or to inhibit cellular innate immune responses. Two LPS mimetics, identified as potent TLR4-specific inducers of the intracellular signaling pathways, serve as vaccine adjuvant- and immunotherapy candidates, while anionic glycolipids with TLR4-inhibitory potential hold therapeutic promise for the management of acute or chronic inflammation., (© 2024 The Authors. Angewandte Chemie International Edition published by Wiley-VCH GmbH.)

The first use of the word 'chlorophyll' (chlorophile or chlorophyle in the French original) appeared in two papers by Pierre-Joseph Pelletier and Joseph Bienaimé Caventou, pharmacists in Paris who isolated and studied the green pigment from plants. Here, we provide English translations of their 1818 note and the slightly longer 1817 paper. Historical context is provided including a timeline of key discoveries in chlorophyll chemistry pertaining to photosynthesis., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

A novel, isocratic, sensitive, stability-indicating high-performance liquid chromatography method was developed for the separation and quantification of related substances in nitroxoline (NTL). The chromatographic separation has been achieved on Inertsil ODS-3 V, (250 × 4.6 mm, 5 μm) at 240 nm using ethylenediamine tetraacetic acid buffer and methanol in the ratio of 60:40 v/v as mobile phase. The performance of the method has been checked as per the International Conference on Harmonization guidelines for specificity, linearity, accuracy, precision, and robustness. Regression analysis showed a correlation coefficient value greater than 0.99 for NTL and its three impurities. The detection limit of impurities was in the range of 0.01% (0.05 μg/mL)-0.22% (1.1 μg/mL) indicating the sensitivity of the newly developed method. The accuracy of the method was established based on the recovery obtained between 94.7% and 104.1% for all the impurities. The percentage relative standard deviation obtained for the repeatability was less than 4.0% at the specification level for all impurities. Forced degradation was performed to establish the stability-indicating nature of the method and to know about the degradation products, the quality of a drug substance changes with time under the influence of stress conditions. Thus, the proposed method was validated and found to be specific, sensitive, linear, accurate, precise, reproducible, and beneficial for routine usage., (© 2023 Wiley-VCH GmbH.)

The generalization of deep neural network algorithms to a broader population is an important challenge in the medical field. We aimed to apply self-supervised learning using masked autoencoders (MAEs) to improve the performance of the 12-lead electrocardiography (ECG) analysis model using limited ECG data. We pretrained Vision Transformer (ViT) models by reconstructing the masked ECG data with MAE. We fine-tuned this MAE-based ECG pretrained model on ECG-echocardiography data from The University of Tokyo Hospital (UTokyo) for the detection of left ventricular systolic dysfunction (LVSD), and then evaluated it using multi-center external validation data from seven institutions, employing the area under the receiver operating characteristic curve (AUROC) for assessment. We included 38,245 ECG-echocardiography pairs from UTokyo and 229,439 pairs from all institutions. The performances of MAE-based ECG models pretrained using ECG data from UTokyo were significantly higher than that of other Deep Neural Network models across all external validation cohorts (AUROC, 0.913–0.962 for LVSD, p < 0.001). Moreover, we also found improvements for the MAE-based ECG analysis model depending on the model capacity and the amount of training data. Additionally, the MAE-based ECG analysis model maintained high performance even on the ECG benchmark dataset (PTB-XL). Our proposed method developed high performance MAE-based ECG analysis models using limited ECG data. [ABSTRACT FROM AUTHOR]

Recognising human activities using smart devices has led to countless inventions in various domains like healthcare, security, sports, etc. Sensor-based human activity recognition (HAR), especially smartphone-based HAR, has become popular among the research community due to lightweight computation and user privacy protection. Deep learning models are the most preferred solutions in developing smartphone-based HAR as they can automatically capture salient and distinctive features from input signals and classify them into respective activity classes. However, in most cases, the architecture of these models needs to be deep and complex for better classification performance. Furthermore, training these models requires extensive computational resources. Hence, this research proposes a hybrid lightweight model that integrates an enhanced Temporal Convolutional Network (TCN) with Gated Recurrent Unit (GRU) layers for salient spatiotemporal feature extraction without tedious manual feature extraction. Essentially, dilations are incorporated into each convolutional kernel in the TCN-GRU model to extend the kernel's field of view without imposing additional model parameters. Moreover, fewer short filters are applied for each convolutional layer to alleviate excess parameters. Despite reducing computational cost, the proposed model utilises dilations, residual connections, and GRU layers for longer-term time dependency modelling by retaining longer implicit features of the input inertial sequences throughout training to provide sufficient information for future prediction. The performance of the TCN-GRU model is verified on two benchmark smartphone-based HAR databases, i.e., UCI HAR and UniMiB SHAR. The model attains promising accuracy in recognising human activities with 97.25% on UCI HAR and 93.51% on UniMiB SHAR. Since the current study exclusively works on the inertial signals captured by smartphones, future studies will explore the generalisation of the proposed TCN-GRU across diverse datasets, including various sensor types, to ensure its adaptability across different applications. [ABSTRACT FROM AUTHOR]

The source of the Galactic lithium (Li) has long been a puzzle. With the discovery of Li in novae, extensive research has been conducted. However, there still exists a significant disparity between the observed abundance of Li in novae and the existing theoretical predictions. Using the Modules for Experiments in Stellar Astrophysics, we simulate the evolution of novae with element diffusion and appropriately increase the amount of 3He in the mixtures. Element diffusion enhances the transport efficiency between the nuclear reaction zone and the convective region on the surface of the white dwarf (WD) during nova eruptions, which results in more 7Be being transmitted to the WD surface and ultimately ejected. Compared to the previous predictions, the abundance of 7Be in novae simulated in our model significantly increases. The result is able to explain almost all observed novae. Using the method of population synthesis, we calculate Li yield in the Galaxy. We find that the Galactic occurrence rate of novae is about 130 yr−1, and about 110 M ⊙ Li produced by nova eruption is ejected into the interstellar medium (ISM). About 73% of Li in the Galactic ISM originates from novae and approximately 15%–20% of the entire Galaxy. This means that novae are the important source of Li in the Galaxy. [ABSTRACT FROM AUTHOR]

Major depressive disorder (MDD) is a complex and devastating illness that affects people of all ages. Despite the large use of antidepressants in current medical practice, neither their mechanisms of action nor the aetiology of MDD are completely understood. Experimental evidence supports the involvement of Parvalbumin-positive GABAergic neurons (PV-neurons) in the pathogenesis of MDD. DLX5 and DLX6 (DLX5/6) encode two homeodomain transcription factors involved in cortical GABAergic differentiation and function. In the mouse, the level of expression of these genes is correlated with the cortical density of PV-neurons and with anxiety-like behaviours. The same genomic region generates the lncRNA DLX6-AS1, which, in humans, participates in the GABAergic regulatory module downregulated in schizophrenia and ASD. Here, we show that the expression levels of Dlx5/6 in the adult mouse brain are correlated with the immobility time in the forced swim test, which is used to measure depressive-like behaviours. We show that the administration of the antidepressant fluoxetine (Flx) to normal mice induces, within 24 h, a rapid and stable reduction in Dlx5, Dlx6 and Dlx6-AS1 expression in the cerebral cortex through the activation of the TrkB-CREB pathway. Experimental Dlx5 overexpression counteracts the antidepressant effects induced by Flx treatment. Our findings show that one of the short-term effects of Flx administration is the reduction in Dlx5/6 expression in GABAergic neurons, which, in turn, has direct consequences on PV expression and on behavioural profiles. Variants in the DLX5/6 regulatory network could be implicated in the predisposition to depression and in the variability of patients' response to antidepressant treatment. [ABSTRACT FROM AUTHOR]

Functional mobility tests, such as the L test of functional mobility, are recommended to provide clinicians with information regarding the mobility progress of lower-limb amputees. Smartphone inertial sensors have been used to perform subtask segmentation on functional mobility tests, providing further clinically useful measures such as fall risk. However, L test subtask segmentation rule-based algorithms developed for able-bodied individuals have not produced sufficiently acceptable results when tested with lower-limb amputee data. In this paper, a random forest machine learning model was trained to segment subtasks of the L test for application to lower-limb amputees. The model was trained with 105 trials completed by able-bodied participants and 25 trials completed by lower-limb amputee participants and tested using a leave-one-out method with lower-limb amputees. This algorithm successfully classified subtasks within a one-foot strike for most lower-limb amputee participants. The algorithm produced acceptable results to enhance clinician understanding of a person's mobility status (>85% accuracy, >75% sensitivity, >95% specificity). [ABSTRACT FROM AUTHOR]

In strawberry cultivation, precise disease management is crucial for maximizing yields and reducing unnecessary fungicide use. Traditional methods for measuring leaf wetness duration (LWD), a critical factor in assessing the risk of fungal diseases such as botrytis fruit rot and anthracnose, have been reliant on sensors with known limitations in accuracy and reliability and difficulties with calibrating. To overcome these limitations, this study introduced an innovative algorithm for leaf wetness detection systems employing high-resolution imaging and deep learning technologies, including convolutional neural networks (CNNs). Implemented at the University of Florida's Plant Science Research and Education Unit (PSREU) in Citra, FL, USA, and expanded to three additional locations across Florida, USA, the system captured and analyzed images of a reference plate to accurately determine the wetness and, consequently, the LWD. The comparison of system outputs with manual observations across diverse environmental conditions demonstrated the enhanced accuracy and reliability of the artificial intelligence-driven approach. By integrating this system into the Strawberry Advisory System (SAS), this study provided an efficient solution to improve disease risk assessment and fungicide application strategies, promising significant economic benefits and sustainability advances in strawberry production. [ABSTRACT FROM AUTHOR]

Pancreatic malignancy is the fourth cause of cancer-related death in Western countries and is predicted to become the second leading cause of cancer-related mortality by 2030. The standard therapies (FOLFIRINOX and gemcitabine with nab-paclitaxel) are not resolutive because this type of cancer is also characterized by a high chemoresistance, due in part to the activity of the ATP Binding Cassette (ABC) pumps accounting for the reduction in the intracellular concentration of the drugs. In this work, we analyze the occurrence of single-nucleotide polymorphisms (SNPs) in the MDR-1 gene, in different pancreatic cancer cell lines, and in tissues from pancreatic cancer patients by DNA sequencing, as well as the expression levels of MDR-1 mRNA and protein, by qRT-PCR and Western Blot analysis. We found that gemcitabine-resistant cells, in conjunction with homozygosis of analyzed SNPs, showed high MDR-1 basal levels with further increases after gemcitabine treatment. Nevertheless, we did not observe in the human PDAC samples a correlation between the level of MDR-1 mRNA and protein expression and SNPs. Preliminary, we conclude that in our small cohort, these SNPs cannot be used as molecular markers for predicting the levels of MDR-1 mRNA/protein levels and drug responses in patients with PDAC. [ABSTRACT FROM AUTHOR]

Influenza D virus was isolated from pigs on a mixed pig and beef farm in France. Investigation suggested bullto-pig transmission and spread among pigs. The swine influenza D virus recovered was a reassortant of D/660 and D/OK lineages. Reported mutations in the receptor binding site might be related to swine host adaptation. [ABSTRACT FROM AUTHOR]

The rapid increase of antimicrobial-resistant bacteria in humans and livestock is concerning. Antimicrobials are essential for the treatment of disease in modern day medicine, and their misuse in humans and food animals has contributed to an increase in the prevalence of antimicrobial-resistant bacteria. Globally, antimicrobial resistance is recognized as a One Health problem affecting humans, animals, and environment. Enterococcal species are Gram-positive bacteria that are widely distributed in nature. Their occurrence, prevalence, and persistence across the One Health continuum make them an ideal candidate to study antimicrobial resistance from a One Health perspective. The objective of this review was to summarize the role of enterococci as an indicator of antimicrobial resistance across One Health sectors. We also briefly address the prevalence of enterococci in human, animal, and environmental settings. In addition, a 16S RNA gene-based phylogenetic tree was constructed to visualize the evolutionary relationship among enterococcal species and whether they segregate based on host environment. We also review the genomic basis of antimicrobial resistance in enterococcal species across the One Health continuum. [ABSTRACT FROM AUTHOR]

This study explored the influence of living settings on physical activity (PA) levels and volition in exercise and their correlation, considering sex differences. Five hundred and sixty-six university students (261 rural and 305 urban) from Calabria region (Italy) attending universities courses filled an online survey where Global Physical Activity Questionnaire and Volition in Exercise Questionnaire were administered. Rural females (RF) showed lower PA levels and self-confidence than rural males (RM) (p<0.01). Postponing training and unrelated thoughts were higher in RF than RM (p<0.01 and p<0.05 respectively). PA levels, self-confidence and coping with failure were lower in urban females (UF) than urban males (UM) (p<0.01), Postponing training and unrelated thoughts were higher in UF than UM (p<0.01 and p<0.05). In RF and UF, PA levels positively correlated with self-confidence (Rho = 0.397) and coping with failure (Rho = 0.330), whereas negatively correlated with postponing training (Rho = -0.487) and unrelated thoughts (Rho = -0.283). In RM and UM, PA levels positively correlated with self-confidence (Rho = 0.270) and coping with failure (Rho = 0.258), whereas it negatively correlated with postponing training (Rho = -0.285). PA levels positively correlated with reasons (Rho = 0.260) only in UM. We showed for the first time the relationship between PA and volition factors considering the living setting in university students. Sex differences were observed in some volition facilitators and PA levels independently by the living context. [ABSTRACT FROM AUTHOR]

The global significance of SMEs has traditionally been recognized as a key driver of economic growth and sustainability. The emergence of digital technologies and Information and Communication Technology for Development (ICT4D) holds significant potential to further enhance this impact. However, SMEs in developing countries have faced challenges in adopting sustainable, resource-intensive digital systems. Factors such as limited skills, financial constraints, and the alignment of suitable solutions hinder this adoption. To address these challenges and promote sustainable digital transformation, this study proposes a two-tier approach. The first prong employs Natural Language Processing (NLP) techniques, including Word2Vec, for global analysis and digital systems identification. The second prong involves a country-specific analysis of SMEs' digital requirements. This two-tier analysis aims to uncover the actual digital needs of SMEs while shedding light on high-intensity global SME activities that, if integrated through ICT4D, could effectively address the risks and challenges SMEs face in adopting, implementing, and maintaining digital systems. In addition, the study develops systems required by SMEs to optimize their business processes and production, thereby promoting their growth and sustainability in the digital era. The results of this study demonstrate the effectiveness of these proposed methods in addressing digital challenges for SMEs and fostering sustainable development. [ABSTRACT FROM AUTHOR]

Microbes maneuver strategies to become incessant and biofilms perfectly play a role in scaling up virulence to cause long-lasting infections. The present study was designed to assess the use of an eco-friendly formulation of functionalized silver nanoparticles generated from Mentha longifolia leaf extract (MℓE) for the treatment of biofilm-producing microbes. Nanoparticles synthesized using MℓE as a reducing agent were optimized at different strengths of AgNO3 (1 mM, 2 mM, 3 mM, and 4 mM). Synthesis of M. longifolia silver nanoparticles (MℓAgNPs) was observed spectrophotometrically (450 nm) showing that MℓAgNPs (4 mM) had the highest absorbance. Various techniques e.g., Fourier transforms Infrared spectroscopy (FTIR), Dynamic light scattering (DLS), zeta potential (ZP), X-ray Diffraction (XRD), scanning electron microscope (SEM), and transmission electron microscope (TEM) were used to characterize MℓAgNPs. In the present study, the Kirby—Bauer method revealed 4mM was the most detrimental conc. of MℓAgNPs with MIC and MBC values of 0.62 μg/mL and 1.25 μg/mL, 0.03 μg/mL and 0.078 μg/mL, and 0.07 μg/mL and 0.15 μg/mL against previously isolated and identified clinical strains of Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Staphylococcus aureus, respectively. Moreover, the MℓAgNP antibiofilm activity was examined via tissue culture plate (TCP) assay that revealed biofilm inhibition of up to 87.09%, 85.6%, 83.11%, and 75.09% against E. coli, P. aeruginosa, K. pneumonia, and S. aureus, respectively. Herbal synthesized silver nanoparticles (MℓAgNPs) tend to have excellent antibacterial and antibiofilm properties and are promising for other biomedical applications involving the extrication of irksome biofilms. For our best knowledge, it is the first study on the use of the green-synthesized silver nanoparticle MℓAgNP as an antibiofilm agent, suggesting that this material has antibiotic, therapeutic, and industrial applications. [ABSTRACT FROM AUTHOR]

Purpose: In response to the growing need for organizations to enhance their digital capabilities and the widespread adoption of enterprise social media (ESM) in the workplace, researchers have extensively studied the effects of ESM on various organizational outcomes. Nonetheless, a notable theoretical gap exists regarding the influence of ESM on the development of organizational digital maturity. This paper aims to bridge this gap by conducting a comprehensive literature review to investigate how the utilization of ESM can facilitate the transformation of organizational value-creation processes, thereby contributing to the overall enhancement of digital maturity. Design/methodology/approach: Using the information technology (IT) value-creation framework developed by Mooney et al. (1996) and applying a template analysis methodology as outlined by King (2012), the authors conducted a systematic literature review (Okoli and Schabram, 2010), to investigate the influence of ESM on value creation within the digital business environment. Findings: The study's outcomes are structured around a theoretical framework that combines the contingency theory and the sociotechnical perspective to provide a comprehensive understanding of digital maturity. This paper also delves into how ESM facilitates the transformation of organizational value-creation processes, ultimately contributing to the overall progress of their digital maturity. Research limitations/implications: This study adapts existing theoretical models to fit the context of ESM and integrates multiple perspectives to provide a comprehensive understanding of its impact. It identifies a convergence in the definition of ESM and offers insights into its various dimensions and effects on value creation. Hence, scholars can use the identified theoretical frameworks and conceptual convergence to guide future investigations into the impact of ESM on value creation, fostering theoretical development and empirical research. Practitioners can benefit from the insights to develop effective strategies for implementing ESM within their organizations, aligning with broader organizational objectives to enhance performance, streamline operations and drive structural changes. Furthermore, both scholars and practitioners can use the identified limitations of the study to identify areas for further improvement and exploration, thus contributing to the advancement of knowledge and practice in ESM and value creation. Limitations of this research include the exclusion of gray literature, a relatively small sample size of analyzed articles, and the restriction to specific databases as per systematic review guidelines, potentially overlooking valuable contributions from alternative sources. Practical implications: This paper provides a comprehensive exploration of how ESM can support value-creation processes within organizations. It offers valuable insights to help managers incorporate ESM into their digital strategies and to understand its value-creation effects. Originality/value: Adopting a value-creation perspective and integrating the contingency theory and the sociotechnical perspective to build a comprehensive framework, this research introduces an original approach by showcasing how ESM can facilitate shifts in value-creation processes of organizations, paving the way to contribute to the development of their digital maturity. [ABSTRACT FROM AUTHOR]

The timely and accurate mapping of crop types is crucial for agricultural insurance, futures, and assessments of food security risks. However, crop mapping is currently focused on the post-harvest period, and less attention has been paid to early crop mapping. In this study, the feasibility of using Sentinel-1 (S1) and Sentinel-2 (S2) data for the earliest identifiable time (EIT) for major crops (sunflower, maize, spring wheat, and melon) was explored in the Hetao Irrigation District (HID) of China, based on the Google Earth Engine (GEE) platform. An early crop identification strategy based on the Random Forest (RF) model for HID was proposed, and the performance of the model transfer was evaluated. First, the median synthesis, linear shift interpolation, and the Savitzky–Golay (SG) filter methods were used to reconstruct the time series of S1 and S2. Subsequently, the sensitivity of different input features, time intervals, and data integration to different early crop identifications was evaluated based on the RF model. Finally, the model with optimal parameters was evaluated in terms of its transfer capacity and used for the early mapping of crops in the HID area. The results showed that the features extracted from S2 images synthesized at 10-day intervals performed well in obtaining crop EITs. Sunflower, maize, spring wheat, and melon could be identified 90, 90, 70, and 40 days earlier than the harvest date. The identification accuracy, measured by the F1-score, could reach 0.97, 0.95, 0.98, and 0.90, respectively. The performance of the model transfer is good, with the F1-score decreasing from 0 to 0.04 and no change in EIT for different crops. It was also found that the EIT of crops obtained using S1 data alone was 50–90 days later than that obtained using S2 data alone. Additionally, when S1 and S2 were used jointly, S1 data contributed little to early crop identification. This study highlights the potential of early crop mapping using satellite data, which provides a feasible solution for the early identification of crops in the HID area and valuable information for food security assurance in the region. [ABSTRACT FROM AUTHOR]

As 5G technology becomes more widespread, the significant improvement in network speed and connection density has introduced more challenges to network security. In particular, distributed denial of service (DDoS) attacks have become more frequent and complex in software-defined network (SDN) environments. The complexity and diversity of 5G networks result in a great deal of unnecessary features, which may introduce noise into the detection process of an intrusion detection system (IDS) and reduce the generalization ability of the model. This paper aims to improve the performance of the IDS in 5G networks, especially in terms of detection speed and accuracy. It proposes an innovative feature selection (FS) method to filter out the most representative and distinguishing features from network traffic data to improve the robustness and detection efficiency of the IDS. To confirm the suggested method's efficacy, this paper uses four common machine learning (ML) models to evaluate the InSDN, CICIDS2017, and CICIDS2018 datasets and conducts real-time DDoS attack detection on the simulation platform. According to experimental results, the suggested FS technique may match 5G network requirements for high speed and high reliability of the IDS while also drastically cutting down on detection time and preserving or improving DDoS detection accuracy. [ABSTRACT FROM AUTHOR]

In the electronic nose (E-nose) systems, gas type recognition and accurate concentration prediction are some of the most challenging issues. This study introduced an innovative pattern recognition method of time–frequency attention convolutional neural network (TFA-CNN). A time–frequency attention block was designed in the network, aiming to excavate and effectively integrate the temporal and frequency domain information in the E-nose signals to enhance the performance of gas classification and concentration prediction tasks. Additionally, a novel data augmentation strategy was developed, manipulating the feature channels and time dimensions to reduce the interference of sensor drift and redundant information, thereby enhancing the model's robustness and adaptability. Utilizing two types of metal-oxide-semiconductor gas sensors, this research conducted qualitative and quantitative analysis on five target gases. The evaluation results showed that the classification accuracy could reach 100%, and the coefficient of the determination (R2) score of the regression task was up to 0.99. The Pearson correlation coefficient (r) was 0.99, and the mean absolute error (MAE) was 1.54 ppm. The experimental test results were almost consistent with the system predictions, and the MAE was 1.39 ppm. This study provides a method of network learning that combines time–frequency domain information, exhibiting high performance in gas classification and concentration prediction within the E-nose system. [ABSTRACT FROM AUTHOR]

Due to the intricate terrain and restricted resources, hyperspectral image (HSI) datasets captured in real-world scenarios typically contain noisy labels, which may seriously affect the classification results. To address this issue, we work on a universal method that rectifies the labels first and then trains the classifier with corrected labels. In this study, we relax the common assumption that all training data are potentially corrupted and instead posit the presence of a small set of reliable data points within the training set. Under this framework, we propose a novel label-correction method named adaptive selective loss propagation algorithm (ASLPA). Firstly, the spectral–spatial information is extracted from the hyperspectral image and used to construct the inter-pixel transition probability matrix. Secondly, we construct the trusted set with the known clean data and estimate the proportion of accurate labels within the untrusted set. Then, we enlarge the trusted set according to the estimated proportion and identify an adaptive number of samples with lower loss values from the untrusted set to supplement the trusted set. Finally, we conduct label propagation based on the enlarged trusted set. This approach takes full advantage of label information from the trusted and untrusted sets, and moreover the exploitation on the untrusted set can adjust adaptively according to the estimated noise level. Experimental results on three widely used HSI datasets show that our proposed ASLPA method performs better than the state-of-the-art label-cleaning methods. [ABSTRACT FROM AUTHOR]

Despite its high importance for crop yield prediction and monitoring, early-season crop mapping is severely hampered by the absence of timely ground truth. To cope with this issue, this study aims at evaluating the capability of PRISMA hyperspectral satellite images compared with Sentinel-2 multispectral imagery to produce early- and in-season crop maps using consolidated machine and deep learning algorithms. Results show that the accuracy of crop type classification using Sentinel-2 images is meaningfully poor compared with PRISMA (14% in overall accuracy (OA)). The 1D-CNN algorithm, with 89%, 91%, and 92% OA for winter, summer, and perennial cultivations, respectively, shows for the PRISMA images the highest accuracy in the in-season crop mapping and the fastest algorithm that achieves acceptable accuracy (OA 80%) for the winter, summer, and perennial cultivations early-season mapping using PRISMA images. Moreover, the 1D-CNN algorithm shows a limited reduction (6%) in performance, appearing to be the best algorithm for crop mapping within operational use in cross-farm applications. Machine/deep learning classification algorithms applied on the test fields cross-scene demonstrate that PRISMA hyperspectral time series images can provide good results for early- and in-season crop mapping. [ABSTRACT FROM AUTHOR]

Objectives: Lung cancer is the leading cause of cancer death, and 80-85% of all lung cancer cases are non-small cell lung cancer (NSCLC). Surgical resection is the standard treatment for early-stage NSCLC. However, lung resection, a surgical procedure, can result in complications and increased mortality. Recent studies have shown a significant correlation between complications after lung resection and right ventricular dysfunction. Methods: Transthoracic echocardiography-derived right ventricular-pulmonary artery coupling (RV-PAC) was utilized to assess right ventricular function in these patients. Multivariate logistic regression analysis was also conducted to assess risk factors independently associated with RV-PA uncoupling. The 3- and 5-year cumulative survival rates were estimated with Kaplan-Meier curves, and differences between groups were analyzed using the Mantel-Cox log-rank test. Results: RV-PA uncoupling was defined as a TAPSE/PASP value < 0.67 mm/mm Hg according to spline analysis. The results of multivariable logistic regression analysis indicated that diabetes is an independent risk factor for right ventricular dysfunction after lung resection in patients with NSCLC. Kaplan-Meier analysis revealed a significant decrease in the survival rate of patients with RV-PA uncoupling at both the 3-year follow-up (73% vs 40%, p < 0.001) and 5-year follow-up (64% vs 37%, p < 0.001). Conclusions: After lung resection for NSCLC, the patient's right ventricular function predicts prognosis. Patients with right ventricular dysfunction, particularly those with diabetesmellitus, have a worse prognosis. It is crucial to actively prevent and correct risk factors to reduce the mortality rate in these patients. [ABSTRACT FROM AUTHOR]

Context: Participation in sports is associated with a risk of sports-related health problems. For athletes with an impairment, sports-related health problems further burden an already restricted lifestyle, underlining the importance of prevention strategies in para-sports. Objective: To provide a comprehensive overview with quality assessment of the literature on sports-related health problems, their etiology, and available preventive measures in para-sports following the steps of the Sequence of Prevention. Data Sources: A literature search (in PubMed, Embase, SPORTDiscus, CINAHL and the Cochrane Library) was performed up to December 8, 2021, in collaboration with a medical information specialist. Study Selection: The search yielded 3006 articles, of which 64 met all inclusion criteria. Study Design: Systematic review with quality assessment. Level of Evidence: Level 3. Data Extraction: Two independent researchers carried out the screening process and quality assessment. One researcher extracted data, and the Sequence of Prevention categorized evidence. Results: A total of 64 studies were included, of which 61 reported on the magnitude and risk factors of sports-related health problems, while only 3 reported on the effectiveness of preventive measures. Of these, 30 studies were of high quality. Most studies (84%) included elite-level athletes. The reported injury incidence varied widely between sports (0-91 per 1000 athlete days) and impairment categories (1-50 per 1000 athlete days). The same applies to illness incidence with regard to different sports (3-49 per 1000 athlete days) and impairment categories (6-14 per 1000 athlete days). Conclusion: This review shows the current vast range of reported sport-related health problems in para-sports. There is limited evidence concerning the severity of these sports-related health problems and inconclusive evidence on the risk factors. Lastly, the evidence regarding the development and effectiveness of preventive measures for para-athletes is sparse. [ABSTRACT FROM AUTHOR]

We explore the links between elevation variability of the Antarctic Ice Sheet (AIS) and large‐scale climate modes. Using multiple linear regression, we quantify the time‐cumulative effects of El Niño Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) on gridded AIS elevations. Cumulative ENSO and SAM explain a median of 29% of the partial variance and up to 85% in some coastal areas. After spatial smoothing, these signals have high spatial correlation with those from GRACE gravimetry (r∼ = 0.65 each). Much of the signal is removed by a firn densification model but inter‐model differences exist especially for ENSO. At the lower parts of the Thwaites and Pine Island glaciers, near their grounding line, we find the Amundsen Sea Low (ASL) explains ∼90% of the observed elevation variability. There, modeled firn effects explain only a small fraction of the variability, suggesting significant height changes could be a response to climatological ice‐dynamics. Plain Language Summary: This study investigates how variations in the height of the Antarctic Ice Sheet (AIS) are connected to large‐scale climate patterns. We used a statistical method to measure the effects of two climate phenomena: El Niño Southern Oscillation (ENSO) and the Southern Annular Mode (SAM). We found that the cumulative effects of these phenomena account for about 29% of the variations in AIS height on average, and up to 85% in some coastal areas. These patterns match well with independent data from the GRACE satellites over the same period. Applying a model that considers the accumulation of snow and its compaction into ice (firn densification) removes much of this signal, suggesting much, but not all, of the signals are related to snowfall variations. At the fronts of the rapidly changing Thwaites and Pine Island glaciers, the dominant climate phenomenon is the Amundsen Sea Low (ASL), which varies in strength and location. Here, the cumulative effects of the ASL changes explain about 90% of the variations in height of these glaciers, with only a small part explained by firn effects. We suggest the unexplained variability could be partly due to changes in ice flow. Key Points: Cumulative effects of large‐scale climate modes dominate detrended altimeter time series of Antarctic ice elevation 2002–2020These decadal signals have the same spatial pattern in altimeter ice height and GRACE mass time seriesThese decadal signals are largely due to surface mass balance, but ice dynamic changes may play a role in the Amundsen Sea Embayment [ABSTRACT FROM AUTHOR]

Ophthalmic and many systemic diseases may damage the eyes, resulting in changes in the composition and content of biomolecules in ocular biofluids such as aqueous humor and tear. Therefore, the biomolecules in biofluids are potential biomarkers to reveal pathological processes and diagnose diseases. Raman spectroscopy is a non-invasive, label-free, and cost-effective technique to provide chemical bond information of biomolecules and shows great potential in the detection of ocular biofluids. This review demonstrates the applications of Raman spectroscopy technology in detecting biochemical components in aqueous humor and tear, then summarizes the current problems encountered for clinical applications of Raman spectroscopy and looks forward to possible approaches to overcome technical bottlenecks. This work may provide a reference for wider applications of Raman spectroscopy in biofluid detection and inspire new ideas for the diagnosis of diseases using ocular biofluids. [ABSTRACT FROM AUTHOR]

Oropharyngeal dysphagia, or difficulty initiating swallowing, is a frequent problem in people with Parkinson's disease (PD) and can lead to aspiration pneumonia. The efficacy of pharmacological options is limited. Postural strategies, such as a chin-down manoeuvre when drinking, have had some degree of success but may be difficult for people who have other limitations such as dementia or neck rigidity, to reproduce consistently. Using a user-centred design approach and a multidisciplinary team, we developed and tested an anti-choking mug for people with PD that helps angle the head in the optimum position for drinking. The design reflected anthropometric and ergonomic aspects of user needs with features including regulation of water flow rate and sip volume, an inner slope, a thickened handle and a wide base, which promoted a chin-down posture when used. Prototype testing using digital technology to compare neck flexion angles (the primary outcome), plus clinical outcomes assessed using standard tools (Swallowing Clinical Assessment Score in Parkinson's Disease (SCAS-PD) and Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts II and III), found significant improvements in a range of parameters related to efficient swallowing and safe drinking when using the anti-choking mug versus a sham mug. [ABSTRACT FROM AUTHOR]

The search for gravitational-wave (GW) signals is limited by non-Gaussian transient noises that mimic astrophysical signals. Temporal coincidence between two or more detectors is used to mitigate contamination by these instrumental glitches. However, when a single detector is in operation, coincidence is impossible, and other strategies have to be used. We explore the possibility of using neural network classifiers and present the results obtained with three types of architectures: convolutional neural network, temporal convolutional network, and inception time. The last two architectures are specifically designed to process time-series data. The classifiers are trained on a month of data from the LIGO Livingston detector during the first observing run (O1) to identify data segments that include the signature of a binary black hole merger. Their performances are assessed and compared. We then apply trained classifiers to the remaining three months of O1 data, focusing specifically on single-detector times. The most promising candidate from our search is 4 January 2016 12:24:17 UTC. Although we are not able to constrain the significance of this event to the level conventionally followed in GW searches, we show that the signal is compatible with the merger of two black holes with masses m 1 = 50.7 − 8.9 + 10.4 M ⊙ and m 2 = 24.4 − 9.3 + 20.2 M ⊙ at the luminosity distance of d L = 564 − 338 + 812 Mpc . [ABSTRACT FROM AUTHOR]

A neurogenic dysphagia is dysphagia caused by problems with the central and peripheral nervous systems, is particularly prevalent in conditions such as Parkinson's disease and stroke. It significantly impacts the quality of life for affected individuals and causes additional burdens, such as malnutrition, aspiration pneumonia, asphyxia, or even death from choking due to improper eating. Physical therapy offers a non-invasive treatment with high efficacy and low cost. Evidence supporting the use of physical therapy in dysphagia treatment is increasing, including techniques such as neuromuscular electrical stimulation, sensory stimulation, transcranial direct current stimulation, and repetitive transcranial magnetic stimulation. While initial studies have shown promising results, the effectiveness of specific treatment regimens still requires further validation. At present, there is a lack of scientific evidence to guide patient selection, develop appropriate treatment regimens, and accurately evaluate treatment outcomes. Therefore, the primary objectives of this review are to review the results of existing research, summarize the application of physical therapy in dysphagia management, we also discussed the mechanisms and treatments of physical therapy for neurogenic dysphagia. [ABSTRACT FROM AUTHOR]

This paper uses speculative methods as a way of imagining futures for higher education in open, non-predictive ways. The complexity and 'unknowability' of the highly technologised, environmentally damaged and politically degraded futures we seem to be facing can mean that our conversations about the future of higher education have a tendency to spiral too quickly into dystopianism and hopelessness. Speculative methods can help open up new kinds of conversation capable of supporting active and fundamental hope. Working within a postqualitative framework, we argue that such approaches support the collaborative imagining of multiple alternatives, and represent a way of advocating for those that are preferable. The paper presents a series of speculative scenarios and microfictions focusing on worlds ruptured by climate change, artificial intelligence, revolution and the technological enhancement of humans, connecting each of these to current critical research focused on climate crisis, 'big tech', rising global injustice and 'big pharma'. It emphasises the vital contribution and place of higher education within such futures, and advocates for speculative methods as an approach to maintaining hope. [ABSTRACT FROM AUTHOR]

Our work focuses on the exploration of the internal relationships of signals in an individual sensor. In particular, we address the problem of not being able to evaluate such intrasensor relationships due to missing rich and explicit feature representation. To solve this problem, we propose GraphSensor, a graph attention network, with a shared-weight convolution feature encoder to generate the signal segments and learn the internal relationships between them. Furthermore, we enrich the representation of the features by utilizing a multi-head approach when creating the internal relationship graph. Compared with traditional multi-head approaches, we propose a more efficient convolution-based multi-head mechanism, which only requires 56 % of model parameters compared with the best multi-head baseline as demonstrated in the experiments. Moreover, GraphSensor is capable of achieving state-of-the-art performance in the electroencephalography dataset and improving the accuracy by 13.8 % compared to the best baseline in an inertial measurement unit (IMU) dataset. [ABSTRACT FROM AUTHOR]

Physical literacy (PL) is a lifelong process of developing the motivation, confidence, physical competence, knowledge and understanding to value and take responsibility for engaging in physical activity throughout life. It is also an important concept for understanding and promoting physical activity in children and adolescents and is becoming a theoretical basis for analysing physical education in schools. One of the best known, well-operationalised assessments of PL is the Canadian Assessment of Physical Literacy – CAPL-2. The aim of the study was to translate and culturally adapt the CAPL-2 questionnaires in two EU languages, German and Polish. Data from Poland and Germany were combined for this study, with a total sample size of N=802, consisting of 58.6% Polish and 41.4% German students. We used the TRAPD (the Translation, Review, Adjudication, Pre-test and Documentation) approach to translate the CAPL-2 questionnaires. The main results of this study show that the proposed Polish and German versions of the CAPL-2 questionnaires are satisfactory for use in research or for teachers to assess PL in physical education. Our results also indicate better predictive characteristics of the CAPL-2 questionnaires for children who are very close to or who meet the moderate-to-vigorous physical activity (MVPA) recommendations for health as defined by the WHO. We recommend that adaptations be made that are consistent with the original Canadian version, but which are deeply embedded in the language and culture of the country in question, especially in their wording and terminology. [ABSTRACT FROM AUTHOR]

Recent advancements in deep learning have spurred the development of numerous novel semantic segmentation models for land cover mapping, showcasing exceptional performance in delineating precise boundaries and producing highly accurate land cover maps. However, to date, no systematic literature review has comprehensively examined semantic segmentation models in the context of land cover mapping. This paper addresses this gap by synthesizing recent advancements in semantic segmentation models for land cover mapping from 2017 to 2023, drawing insights on trends, data sources, model structures, and performance metrics based on a review of 106 articles. Our analysis identifies top journals in the field, including MDPI Remote Sensing, IEEE Journal of Selected Topics in Earth Science, and IEEE Transactions on Geoscience and Remote Sensing, IEEE Geoscience and Remote Sensing Letters, and ISPRS Journal Of Photogrammetry And Remote Sensing. We find that research predominantly focuses on land cover, urban areas, precision agriculture, environment, coastal areas, and forests. Geographically, 35.29% of the study areas are located in China, followed by the USA (11.76%), France (5.88%), Spain (4%), and others. Sentinel-2, Sentinel-1, and Landsat satellites emerge as the most used data sources. Benchmark datasets such as ISPRS Vaihingen and Potsdam, LandCover.ai, DeepGlobe, and GID datasets are frequently employed. Model architectures predominantly utilize encoder–decoder and hybrid convolutional neural network-based structures because of their impressive performances, with limited adoption of transformer-based architectures due to its computational complexity issue and slow convergence speed. Lastly, this paper highlights existing key research gaps in the field to guide future research directions. [ABSTRACT FROM AUTHOR]

This cross-sectional study investigated differences in the plasma metabolome in two groups of adults that were of similar age but varied markedly in body composition and dietary and physical activity patterns. Study participants included 52 adults in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females). The results using an extensive untargeted ultra high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) metabolomics analysis with 10,535 metabolite peaks identified 486 important metabolites (variable influence on projections scores of VIP ≥ 1) and 16 significantly enriched metabolic pathways that differentiated LIFE and CON groups. A novel metabolite signature of positive lifestyle habits emerged from this analysis highlighted by lower plasma levels of numerous bile acids, an amino acid profile characterized by higher histidine and lower glutamic acid, glutamine, β-alanine, phenylalanine, tyrosine, and proline, an elevated vitamin D status, higher levels of beneficial fatty acids and gut microbiome catabolism metabolites from plant substrates, and reduced levels of N-glycan degradation metabolites and environmental contaminants. This study established that the plasma metabolome is strongly associated with body composition and lifestyle habits. The robust lifestyle metabolite signature identified in this study is consistent with an improved life expectancy and a reduced risk for chronic disease. [ABSTRACT FROM AUTHOR]

Childhood acute lymphoblastic leukemia (cALL) survivors suffer early-onset chronic diseases classically associated with aging. Normal aging is accompanied by organ dysfunctions, including immunological ones. We hypothesize that thymic immunosenescence occurs in cALL survivors and that its severity may correlate with early-onset chronic diseases. The PETALE study is a cALL survivor cohort with an extensive cardiovascular and metabolic evaluation. The thymic immunosenescence biomarker, signal joint T-cell receptor excision circles (TREC), was evaluated and was highly correlated with age in healthy participants (n = 281) and cALL survivors (n = 248). We observed a systematic thymic immunoage accentuation in each cALL survivor compared to controls ranging from 5.9 to 88.3 years. The immunoage gain was independent of age at diagnosis and treatment modalities and was more severe for females. Thymic aging was associated with several pathophysiological parameters, was greater in survivors suffering from metabolic syndrome, but there was no significant association with global physical condition. The decrease in TREC was independent from blood cell counts, which were normal, suggesting a segmental aging of the thymic compartment. Indeed, increased plasmatic T cell regulatory cytokines IL-6, IL-7 and GM-CSF accompanied high immunoage gain. Our data reveal that cALL or its treatment trigger a rapid immunoage gain followed by further gradual thymic immunosenescence, similar to normal aging. This leads to an enduring shift in accentuated immunoage compared to chronological age. Thus, accentuated thymic immunosenescence is a hallmark of cALL survivorship and TREC levels could be useful immunosenescence biomarkers to help monitoring the health of cancer survivors. [ABSTRACT FROM AUTHOR]