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The interaction of helminth infections with type 2 diabetes (T2D) has been a major area of research in the past few years. This paper, therefore, focuses on the systematic review of the effects of helminthic infections on metabolism and immune regulation related to T2D, with mechanisms through which both direct and indirect effects are mediated. Specifically, the possible therapeutic role of helminths in T2D management, probably mediated through the modulation of host metabolic pathways and immune responses, is of special interest. This paper discusses the current possibilities for translating helminth therapy from basic laboratory research to clinical application, as well as existing and future challenges. Although preliminary studies suggest the potential for helminth therapy for T2D patients, their safety and efficacy still need to be confirmed by larger-scale clinical studies.
During the COVID-19 pandemic, the United States Centers for Disease Control and Prevention provided strategies, such as extended use and reuse, to preserve N95 filtering facepiece respirators (FFR). We aimed to assess the prevalence of N95 FFR contamination with SARS-CoV-2 among healthcare personnel (HCP) in the Emergency Department (ED).
Design:
Real-world, prospective, multicenter cohort study. N95 FFR contamination (primary outcome) was measured by real-time quantitative polymerase chain reaction. Multiple logistic regression was used to assess factors associated with contamination.
Setting:
Six academic medical centers.
Participants:
ED HCP who practiced N95 FFR reuse and extended use during the COVID-19 pandemic between April 2021 and July 2022.
Primary exposure:
Total number of COVID-19-positive patients treated.
Results:
Two-hundred forty-five N95 FFRs were tested. Forty-four N95 FFRs (18.0%, 95% CI 13.4, 23.3) were contaminated with SARS-CoV-2 RNA. The number of patients seen with COVID-19 was associated with N95 FFR contamination (adjusted odds ratio, 2.3 [95% CI 1.5, 3.6]). Wearing either surgical masks or face shields over FFRs was not associated with FFR contamination, and FFR contamination prevalence was high when using these adjuncts [face shields: 25% (16/64), surgical masks: 22% (23/107)].
Conclusions:
Exposure to patients with known COVID-19 was independently associated with N95 FFR contamination. Face shields and overlying surgical masks were not associated with N95 FFR contamination. N95 FFR reuse and extended use should be avoided due to the increased risk of contact exposure from contaminated FFRs.
Discretionary foods that are energy-dense and nutrient-poor contribute to over one third of total energy intake in Australian children and adults, and the typical portion sizes of many discretionary foods have increased significantly in the last two decades(1). The portion size norms (described as a typical perception of how much of a given food people choose to eat at a single eating occasion) are likely to have increased concurrently, with larger sizes now being considered the new normal(2). Public health interventions are urgently needed to reduce the portion size norms and consumption of discretionary foods(3), but the acceptability of such interventions remains unknown. Therefore, this qualitative study aimed to gain insights into consumers’ attitudes towards potential interventions targeted at promoting portion control of discretionary foods. Four online focus group sessions were conducted via Zoom with healthy Australian adults who regularly consume discretionary foods. A question guide was developed to gather participants’ perspectives around four potential public health interventions; reduction of the default serving sizes, increasing serving size options, changes to package sizes, and improving serving size labelling. A female facilitator moderated all focus groups, with a second moderator present to capture other relevant details. Collected data were analysed using a hybrid approach combining deductive and inductive thematic analyses. A total of 35 participants completed the study (19 females, mean age 38 ± 14 years). Participants identified the current food environment as promoting overconsumption; larger serving sizes were reported to be more ubiquitous and better value for money than smaller size options. An overall positive attitude towards the proposed interventions was noted. Out of the four proposed interventions, participants considered the most acceptable intervention to be providing a wider range of serving size options while maintaining a consistent unit price. Other acceptable interventions included reducing the default serving sizes with concurrent price reduction; education and clear guidance around portion size selection (for example, the involvement of health professionals to promote portion control, along with relevant recommendations of appropriate portion sizes from health authorities); more practical on-pack serving size suggestions; and innovative package designs that enable better portion control without contributing to food and plastic waste. In conclusion, participants identified a need for and were in support of interventions aimed at the portion control of discretionary foods. Further research should focus on examining the feasibility and effectiveness of the potential interventions to reduce the purchasing and consumption of large serving sizes. More efforts from public health authorities are required to develop practical and tailored recommendations for consumers around appropriate portion sizes for discretionary foods. Collaboration with the food industry and policy makers is also necessary for implementing public health interventions to reduce the excessive intake of discretionary foods.
I would like to start with by defining what I mean by “Greater China.” It is a term used commonly in economics and investment communities around the world. It includes mainland China (hereafter China), Hong Kong, Macao and Taiwan (Singapore, given its sizable Chinese community, is often included), despite the uneasiness of some Taiwanese scholars about the concept. At a cultural level, “greater China” corresponds with the term “cultural China,” coined by Tu Wei-ming during the 1990s when he spoke about the revival of Confucianism in the postwar period, arguing that instead of an impediment, Confucian values and ideals actually paved the way for the advance of economic expansion in many East Asian countries and regions. This economic expansion continued subsequently powered by globalization. Here, I offer a brief survey of the differing interests in, and engagements with, the study of globalization and global history in mainland China, Hong Kong and Taiwan. I argue that in the face of globalization, each of these regions developed distinct strategies to perceive and interpret its multifaceted impact. Thus, though I use the term “Greater China,” I intend to emphasize the very different approaches to the regional and the global in the case of China, Hong Kong and Taiwan.
Manned lunar landers must ensure astronaut safety while enhancing payload capacity. Due to traditional landers being weak in high-impact energy absorb and heavy payload capacity, a Starship-type manned lunar lander is proposed in this paper. Firstly, a comprehensive analysis was conducted on the traditional cantilever beam cushioning mechanism for manned lander. Subsequently, a 26-ton manned lander and its landing mechanism were designed, and a rigid-flexible coupling dynamic analysis was performed on the compression process of the primary and auxiliary legs. Secondly, the landing performance of the proposed Starship-type manned lunar lander was compared with the traditional 14-ton manned lander in multiple landing conditions. The results indicate that under normal conditions, the largest acceleration of the proposed 26-ton Starship-type manned lander decreases more than 13.1%. It enables a significant increase in payload capacity while mitigating impact loads under various landing conditions.
Motivated by recent developments of quasi-stationary Monte Carlo methods, we investigate the stability of quasi-stationary distributions of killed Markov processes under perturbations of the generator. We first consider a general bounded self-adjoint perturbation operator, and then study a particular unbounded perturbation corresponding to truncation of the killing rate. In both scenarios, we quantify the difference between eigenfunctions of the smallest eigenvalue of the perturbed and unperturbed generators in a Hilbert space norm. As a consequence, $\mathcal{L}^1$-norm estimates of the difference of the resulting quasi-stationary distributions in terms of the perturbation are provided.
The impact of social determinants of health (SDOH) on mental health is increasingly realized. A comprehensive study examining the associations of SDOH with mental health disorders has yet to be accomplished. This study evaluated the associations between five domains of SDOH and the SDOH summary score and mental health disorders in the United States.
Methods
We analyzed data from a diverse group of participants enrolled in the All of Us research programme, a research programme to gather data from one million people living in the United States, in a cross-sectional design. The primary exposure was SDOH based on Healthy People 2030: education access and quality, economic stability, healthcare access and quality, social and community context, and neighbourhood and built environment. A summary SDOH score was calculated by adding each adverse SDOH risk (any SDOH vs. no SDOH). Our primary outcomes were diagnoses of major depression (MD) (i.e., major depressive disorder, recurrent MD or MD in remission) and anxiety disorders (AD) (i.e., generalized AD and other anxiety-related disorders). Multiple logistic regression models were used to determine adjusted odd ratios (aORs) for MD and/or ADs after controlling for covariates.
Results
A total of 63,162 participants with MD were identified (22,277 [35.3%] age 50–64 years old; 41,876 [66.3%] female). A total of 77,624 participants with AD were identified (25,268 [32.6%] age 50–64 years old; 52,224 [67.3%] female). Factors associated with greater odds of MD and AD included having less than a college degree, annual household income less than 200% of federal poverty level, housing concerns, lack of transportation, food insecurity, and unsafe neighbourhoods. Having no health insurance was associated with lower odds of both MD and AD (aOR, 0.48; 95% confidence interval [CI], 0.46–0.51 and aOR, 0.44; 95% CI, 0.42–0.47, respectively). SDOH summary score was strongly associated with the likelihood of having MD and AD (aOR, 1.97; 95% CI, 1.89–2.06 and aOR, 1.69; 95% CI, 1.63–1.75, respectively).
Conclusions
This study found associations between all five domains of SDOH and the higher odds of having MD and/or AD. The strong correlations between the SDOH summary score and mental health disorders indicate a possible use of the summary score as a measure of risk of developing mental health disorders.
Major depressive disorder (MDD) is a prevalent and disabling condition. Approximately 30-50% of patients do not respond to first-line medication or psychotherapy. Therefore, several studies have investigated the predictive potential of pretreatment severity rating or neuroimaging features to guide clinical approaches that can speed optimal treatment selection.
Objectives
To evaluate the performance of 1) severity ratings (scores of Hamilton Depression/Anxiety Scale, illness duration, and sleep quality, etc.) and demographic characteristic and 2) brain magnetic resonance imaging (MRI) features in predicting treatment outcomes for MDD. Second, to assess performance variations among varied modalities and interventions in MRI studies.
Methods
We searched studies in PubMed, Embase, Web of Science, and Science Direct databases before March 22, 2023. We extracted a confusion matrix for prediction in each study. Separate meta-analyses were performed for clinical and MRI studies. The logarithm of diagnostic odds ratio [log(DOR)], sensitivity, and specificity were conducted using Reitsma’s random effect model. The area under curve (AUC) of summary receiver operating characteristic (SROC) curve was calculated.
Subgroup analyses were conducted in MRI studies based on modalities: resting-state functional MRI (rsfMRI), task-based fMRI (tbfMRI), and structural MRI (sMRI), and interventions: antidepressant (including selective serotonin reuptake inhibitors [SSRI]) and electroconvulsive therapy (ECT). Meta-regression was conducted 1) between clinical and MRI studies and 2) among modality or intervention subgroups in MRI studies.
Results
We included ten studies used clinical features covering 6494 patients, yielded a log(DOR) of 1.42, AUC of 0.71, sensitivity of 0.61, and specificity of 0.74. In terms of MRI, 44 studies with 2623 patients were included, revealing an overall log(DOR) of 2.53. The AUC, sensitivity, and specificity were 0.89, 0.78, and 0.75.
Studies using MRI features had a higher sensitivity (0.89 vs. 0.61) in predicting treatment outcomes than clinical features (P < 0.001). RsfMRI had higher specificity (0.79 vs. 0.69) than tbfMRI subgroup (P = 0.01). No significant differences were found between sMRI and other modalities, nor between antidepressants (SSRIs and others) and ECT. Antidepressant studies primarily identified predictive imaging features in limbic and default mode networks, while ECT mainly focused on limbic network.
Conclusions
Our findings suggest a robust promise for pretreatment brain MRI features in predicting treatment outcomes in MDD, offering higher accuracy than clinical studies. While tasks in tbfMRI studies differed, those studies overall had less predictive utility than rsfMRI data. For MRI studies, overlapping but distinct network level measures predicted outcomes for antidepressants and ECT.
Obsessive-compulsive disorder (OCD) is a common psychiatric disorder. It is considered that dysregulation of cytokine levels is related to the pathophysiological mechanism of OCD. However, the results of previous studies on cytokine levels in OCD are inconsistent.
Objectives
To perform a meta-analysis assessing cytokine levels in peripheral blood of OCD patients.
Methods
We searched in PubMed, Web of Science, and Embase from inception to March 31, 2023 for eligible studies. We conducted multivariate meta-analysis in combined proinflammatory cytokines (interleukin-6 [IL-6], IL-1β, IL-2, tumor necrosis factor-α [TNF-α], and interferon-γ [IFN-γ]) and combined anti-inflammatory cytokines (IL-10 and IL-4) respectively, and calculated the same meta-analysis in each cytokine. We also performed sensitivity analysis and publication bias tests, as well as subgroup analysis (i.e. different age groups, varied cytokine measurement methods, medication treated or naïve, and presence of psychiatric comorbidities) and meta-regression analysis (variables including patients’ sex ratio, age, age at symptom onset, illness duration, scores of Y-BOCS, family history of psychiatric disorders, and BMI).
Results
17 original studies (13, 13, 10, 5, 4, 3, 2 studies for IL-6, TNF-α, IL-1β, IL-10, IL-2, IL-4, and IFN-γ, respectively), 573 patients (mean age, 25.2; 50.3% female) and 498 healthy controls (HC; mean age, 25.3; 51.4% female) were included. The results showed that the levels of combined pro- or anti-inflammatory cytokines and each signle cytokine were not significantly different between OCD patients and HC (all P>0.05), with significant heterogeneities in all analyses (I2 from 79.1% to 91.7%). We did not find between-group differences in cytokine levels in all subgroup analyses. Meta-regression analysis suggested that age at onset (P=0.0003) and family history (P=0.0062) might be the source of heterogeneity in TNF-α level. Sensitivity analysis confirmed that all results were stable, except for IL-4 where different cytokine measurement methods may be the contributing factor. Egger test did not find publication bias.
Conclusions
Our study showed no difference in cytokine levels between OCD patients and HC, but age at onset and family history may affect TNF-α level. Confounding factors such as age at onset, family history, and cytokine measurement methods should be controlled in future studies to further explore the immune mechanism of OCD.
There’s large heterogeneity present in major depressive disorder (MDD) and controversial evidence on alterations of brain functional connectivity (FC), making it hard to elucidate the neurobiological basis of MDD. Subtyping is one promising solution to characterize this heterogeneity.
Objectives
To identify neurophysiological subtypes of MDD based on FC derived from resting-state functional magnetic resonance imaging using large multisite data and investigate the differences in genetic mechanisms and neurotransmitter basis of FC alterations, and the differences of FC-related cognition between each subtype.
Methods
Consensus clustering of FC patterns was applied to a population of 829 MDD patients from REST-Meta-MDD database after data cleaning and image quality control. Gene transcriptomic data derived from Allen Human Brain Atlas and neurotransmitter receptor/transporter density data acquired by using neuromap toolbox were used to characterize the molecular mechanism underlying each FC-based subtype by identifying the gene set and neurotransmitters/transporters showing high spatial similarity with the profiles of FC alterations between each subtype and 770 healthy controls. The FC-related cognition in each subtype was also selected by lasso regression.
Results
Two stable neurophysiological MDD subtypes were found and labeled as hypoconnectivity (n=527) and hyperconnectivity (n=299) characterized by the FC differences in each subtype relative to controls, respectively. The two subtypes did not differ in age, sex, and scores of Hamilton Depression/Anxiety Scale.
The genes related to FC alterations were enriched in ion transmembrane transport, synaptic transmission/organization, axon development, and regulation of neurotransmitter level for both subtypes, but specifically enriched in glial cell differentiation for hypoconnectivity subtype, while enriched in regulation of presynaptic membrane and regulation of neuron differentiation for hyperconnectivity subtype.
FC alterations were associated with the density of 5-HT2a receptor in both subtypes. For hyperconnectivity subtype, FC alterations were also correlated with the density of norepinephrine transporter, glutamate receptor, GABA receptor, 5-HT1b receptor, and cannabinoid receptor.
Both subtypes showed correlations between FC and categorization, motor inhibition, and localization. The FC in hypoconnectivity subtype correlated with response inhibition, selective attention, face recognition, sleep, empathy, expertise, uncertainty, and anticipation, while that was related to inference, speech perception, and reward anticipation in hyperconnectivity subtype.
Conclusions
Our findings suggested the presence of two neuroimaging subtypes of MDD characterized by hypo or hyper-connectivity. The two subtypes had both shared and distinct genetic mechanisms, neurotransmitter receptor/transporter profiles, and cognition types.
There has been substantial interest in developing Markov chain Monte Carlo algorithms based on piecewise deterministic Markov processes. However, existing algorithms can only be used if the target distribution of interest is differentiable everywhere. The key to adapting these algorithms so that they can sample from densities with discontinuities is to define appropriate dynamics for the process when it hits a discontinuity. We present a simple condition for the transition of the process at a discontinuity which can be used to extend any existing sampler for smooth densities, and give specific choices for this transition which work with popular algorithms such as the bouncy particle sampler, the coordinate sampler, and the zigzag process. Our theoretical results extend and make rigorous arguments that have been presented previously, for instance constructing samplers for continuous densities restricted to a bounded domain, and we present a version of the zigzag process that can work in such a scenario. Our novel approach to deriving the invariant distribution of a piecewise deterministic Markov process with boundaries may be of independent interest.
Autonomous fabric manipulation is a challenging task due to complex dynamics and potential self-occlusion during fabric handling. An intuitive method of fabric-folding manipulation first involves obtaining a smooth and unfolded fabric configuration before the folding process begins. However, the combination of quasi-static actions like pick & place and dynamic action like fling proves inadequate in effectively unfolding long-sleeved T-shirts with sleeves mostly tucked inside the garment. To address this limitation, this paper introduces an enhanced quasi-static action called pick & drag, specifically designed to handle this type of fabric configuration. Additionally, an efficient dual-arm manipulation system is designed in this paper, which combines quasi-static (including pick & place and pick & drag) and dynamic fling actions to flexibly manipulate fabrics into unfolded and smooth configurations. Subsequently, once it is confirmed that the fabric is sufficiently unfolded and all fabric keypoints are detected, the keypoint-based heuristic folding algorithm is employed for the fabric-folding process. To address the scarcity of publicly available keypoint detection datasets for real fabric, we gathered images of various fabric configurations and types in real scenes to create a comprehensive keypoint dataset for fabric folding. This dataset aims to enhance the success rate of keypoint detection. Moreover, we evaluate the effectiveness of our proposed system in real-world settings, where it consistently and reliably unfolds and folds various types of fabrics, including challenging situations such as long-sleeved T-shirts with most parts of sleeves tucked inside the garment. Specifically, our method achieves a coverage rate of 0.822 and a success rate of 0.88 for long-sleeved T-shirts folding. Supplemental materials and dataset are available on our project webpage at https://sites.google.com/view/fabricfolding.
Due to the environmental problems derived from the use of common surfactants as modifiers for clay mineral adsorbents to mitigate mycotoxin contamination of animal feeds, finding non-toxic modifiers to prepare safe and efficient adsorbents is necessary. The objective of the present study was, therefore, to modify acidified palygorskite with polyhexamethylene biguanide (PHMB) to obtain antibacterial polyhexamethylene biguanide/palygorskite (PHMB/Plg) composites for the removal of zearalenone, a common mycotoxin. The PHMB/Plg composites were characterized and analyzed by X-ray diffraction, Fourier-transform infrared spectroscopy, field-emission scanning electron microscopy, and isothermal nitrogen adsorption analysis. The adsorption properties of the composites with respect to zearalenone and their antibacterial activity with respect to Escherichia coli and Staphylococcus aureus were studied. The results indicated that the hydrophobicity of palygorskite was enhanced after modification with PHMB, which could effectively improve the adsorption property of palygorskite toward the nonpolar zearalenone molecules. The adsorption capacity of PHMB/Plg increased with increasing amounts of polyhexamethylene biguanide and increasing pH. The adsorption data were described well by pseudo-second order kinetics and by the Langmuir adsorption model. The maximum adsorption capacity was 2777 μg/g. When the amount of PHMB added increased to 15 wt.%, the composites obtained exhibited good antibacterial performance, and the minimum inhibitory concentrations for Escherichia coli and Staphylococcus aureus were both at 2.5 mg/mL.
Brick-red deposits with palygorskite (Pal) as the main ingredient are widely distributed in nature, but these have not been deployed at a large scale in industry because of their inherent deep colors. In the present study, the brick-red Pal deposit was treated hydrothermally in various reaction media including water, a urea solution, and a thiourea solution. The effects of these processes on the structure, physicochemical features, and color of Pal were studied intensively to understand the structure and composition of the brick-red Pal deposit and to lay a theoretical foundation for the extension of its industrial application. The changes in structural features after hydrothermal treatment were studied by Fourier-transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, magic-angle spinning nuclear magnetic resonance, and Mössbauer spectroscopy techniques. The results indicated that the color of brick-red Pal did not change after hydrothermal treatment in water or in a urea solution, and the color changed to gray-white after treatment in the thiourea solution. The rod-like crystal morphology of Pal was retained throughout the experiments and no significant change in the main associated minerals, including feldspar, muscovite, and quartz, was observed after hydrothermal treatment. The dissolution of associated hematite (α-Fe2O3 and the reduction of Fe(III) species are the main reason for the change of Pal from brick-red to gray-white.
The poor environmental stability of natural anthocyanin hinders its usefulness in various functional applications. The objectives of the present study were to enhance the environmental stability of anthocyanin extracted from Lycium ruthenicum by mixing it with montmorillonite to form an organic/inorganic hybrid pigment, and then to synthesize allochroic biodegradable composite films by incorporating the hybrid pigment into sodium alginate and test them for potential applications in food testing and packaging. The results of X-ray diffraction, Fourier-transform infrared spectroscopy, and use of the Brunauer–Emmett–Teller method and zeta potential demonstrated that anthocyanin was both adsorbed on the surface and intercalated into the interlayer of montmorillonite via host–guest interaction, and the hybrid pigments obtained allowed good, reversible, acid/base behavior after exposure to HCl and NH3 atmospheres. The composite films containing hybrid pigments had good mechanical properties due to the uniform dispersion of the pigments in a sodium alginate substrate and the formation of hydrogen bonds between them. Interestingly, the composite films also exhibited reversible acidichromism. The as-prepared hybrid pigments in composite films could, therefore, serve simultaneously as a reinforced material and as a smart coloring agent for a polymer substrate.
This article focuses on the luggage trolley transportation problem, an essential part of robotic autonomous luggage trolley collection. To efficiently address the nonholonomic constraints derived from the formation of two collaborative robots and a queue of luggage trolleys, we propose a comprehensive framework consisting of a global planning method and a real-time divide-and-conquer control strategy. The popular Hybrid A* algorithm generates a feasible path as the global planner. A model predictive controller is designed to track this path stably and in real time. To maintain the formation so that the whole queue of robots and luggage trolleys does not split, a safety filter that consists of a discrete-time control Lyapunov function and a decentralized control barrier function is implemented in the transportation process. Finally, we conduct real-world experiments to verify the effectiveness of the proposed method on three representative paths, and the results show that our approach can achieve robust performance. The demonstration video can be found at https://www.youtube.com/watch?v=iPiT8BfLIpU.
Major depressive disorder (MDD) is characterized by both clinical symptoms and cognitive deficits. Prior studies have typically examined either symptoms or cognition correlated with brain measures, thus causing a notable paucity of stable brain markers that capture the full characteristics of MDD. Brain controllability derived from newly proposed brain model integrating both metabolism (energy cost) and dynamics from a control perspective has been considered as a sensitive biomarker for characterizing brain function. Thus, identifying such a biomarker of controllability related to both symptoms and cognition may provide a promising state monitor of MDD.
Objectives
To assess the associations between two multi-dimensional clinical (symptoms and cognition) and brain controllability data of MDD in an integrative model.
Methods
Sparse canonical correlation analysis (sCCA) was used to investigate the association between brain controllability at a network level and both clinical symptoms and cognition in 99 first-episode medication-naïve patients with MDD. The potential mediation effect of cognition on relationship between controllability and symptoms was also tested.
Results
Average controllability was significantly correlated with both symptoms and cognition (rmean=0.54, PBonferroni=0.03). Average controllability of dorsal attention network (DAN) (r=0.46) and visual network (r=0.29) had the highest correlation with both symptoms and cognition. Among clinical variables, depressed mood (r=-0.23) , suicide(r=-0.25), work and activities(r=-0.27), gastrointestinal symptoms (r=-0.25) were significantly negatively associated with average controllability, while cognitive flexibility (r=0.29) was most strongly positively correlated with average controllability. Additionally, cognitive flexibility fully mediated the association between average controllability of DAN and depressed mood (indirect effect=-0.11, 95% CI [-0.18, -0.04], P=0.001) in MDD.
Conclusions
Brain average controllability was correlated with both clinical symptoms and cognition in first-episode medication-naïve patients with MDD. The results suggest that average controllability of DAN and visual network reached high associations with clinical variates in MDD, thus these brain features may serve as stable biomarkers to control the brain functional states transitions to be relevant to cognitions deficits and clinical symptoms of MDD. Additionally, altered average controllability of DAN in patients could induce impairment of cognitive flexibility, and thus cause severe depressed mood, indicating that controllability of DAN may be a potential intervention target for alleviating depressed mood through improving cognitive flexibility in MDD.