Cyto-Genotoxic Assessment of Sulfoxaflor in Allium cepa Root Cells and DNA Docking Studies.

Sulfoxaflor (SFX) is an insecticide that is commonly used for the control of sap-feeding insects. Since SFX is extensively applied globally, it has been implicated in the substantial induction of environmental toxicity. Therefore, in this study, Allium cepa roots have been employed to elucidate the potential cytogenotoxic effects of SFX in non-target cells by examination of mitotic index (MI), chromosomal aberrations (CAs), and DNA damage.

Neuroimaging Biomarkers in Parkinson's Disease.

Idiopathic Parkinson's disease (PD) is a neurodegenerative disorder that affects multiple systems in the body and is characterized by a variety of motor and non-motor (e.g., psychiatric, autonomic) symptoms.

Production of Polyvinyl Alcohol/Amoxicillin - Chitosan/Collagen Hybrid Bilayer Membranes for Regeneration of Gingival Tissues.

Periodontal diseases, if untreated, can cause gum recession and tooth root exposure, resulting in infection and irreversible damage. Traditional treatments using autologous grafts are painful and often result in postoperative complications. Scaffolds offer a less invasive alternative, promoting cell proliferation and healing without additional surgery, thus enhancing comfort for patients and doctors.

Clinical correlates of dopamine transporter availability in cross-sectional and longitudinal studies with [F]FE-PE2I PET: independent validation with new insights.

[F]FE-PE2I PET is a promising alternative to single positron emission computed tomography-based dopamine transporter (DAT) imaging in Parkinson's disease. While the excellent discriminative power of [F]FE-PE2I PET has been established, so far only one study has reported meaningful associations between motor severity scores and DAT availability. In this study, we use high-resolution (∼3 mm isotropic) PET to provide an independent validation for the clinical correlates of [F]FE-PE2I imaging in separate cross-sectional (28 participants with Parkinson's disease, Hoehn-Yahr: 2 and 14 healthy individuals) and longitudinal (initial results from 6 participants with Parkinson's disease with 2-year follow-up) cohorts.

DiracDiffusion: Denoising and Incremental Reconstruction with Assured Data-Consistency.

Diffusion models have established new state of the art in a multitude of computer vision tasks, including image restoration. Diffusion-based inverse problem solvers generate reconstructions of exceptional visual quality from heavily corrupted measurements. However, in what is widely known as the perception-distortion trade-off, the price of perceptually appealing reconstructions is often paid in declined distortion metrics, such as PSNR.

Adapt and Diffuse: Sample-Adaptive Reconstruction Via Latent Diffusion Models.

Inverse problems arise in a multitude of applications, where the goal is to recover a clean signal from noisy and possibly (non)linear observations. The difficulty of a reconstruction problem depends on multiple factors, such as the structure of the ground truth signal, the severity of the degradation and the complex interactions between the above. This results in natural sample-by-sample variation in the difficulty of a reconstruction task, which is often overlooked by contemporary techniques.

Correction to "Design of Cinnamaldehyde- and Gentamicin-Loaded Double-Layer Corneal Nanofiber Patches with Antibiofilm and Antimicrobial Effects".

[This corrects the article DOI: 10.1021/acsomega.3c00914.

Measuring Heart Rate Accurately in Patients With Parkinson Disease During Intense Exercise: Usability Study of Fitbit Charge 4.

Background: Parkinson disease (PD) is the second most common neurodegenerative disease, affecting approximately 1% of the world's population. Increasing evidence suggests that aerobic physical exercise can be beneficial in mitigating both motor and nonmotor symptoms of the disease. In a recent pilot study of the role of exercise on PD, we sought to confirm exercise intensity by monitoring heart rate (HR).

Development of bilayer tissue-engineered scaffolds: combination of 3D printing and electrospinning methodologies.

Although different fabrication methods and biomaterials are used in scaffold development, hydrogels and electrospun materials that provide the closest environment to the extracellular matrix have recently attracted considerable interest in tissue engineering applications. However, some of the limitations encountered in the application of these methods alone in scaffold fabrication have increased the tendency to use these methods together. In this study, a bilayer scaffold was developed using 3D-printed gelatin methacryloyl (GelMA) hydrogel containing ciprofloxacin (CIP) and electrospun polycaprolactone (PCL)-collagen (COL) patches.

Three-Dimensional-Printed GelMA-KerMA Composite Patches as an Innovative Platform for Potential Tissue Engineering of Tympanic Membrane Perforations.

Tympanic membrane (TM) perforations, primarily induced by middle ear infections, the introduction of foreign objects into the ear, and acoustic trauma, lead to hearing abnormalities and ear infections. We describe the design and fabrication of a novel composite patch containing photocrosslinkable gelatin methacryloyl (GelMA) and keratin methacryloyl (KerMA) hydrogels. GelMA-KerMA patches containing conical microneedles in their design were developed using the digital light processing (DLP) 3D printing approach.

Synaptic loss and its association with symptom severity in Parkinson's disease.

Parkinson's disease (PD) is the fastest growing neurodegenerative disease, but at present there is no cure, nor any disease-modifying treatments. Synaptic biomarkers from in vivo imaging have shown promise in imaging loss of synapses in PD and other neurodegenerative disorders. Here, we provide new clinical insights from a cross-sectional, high-resolution positron emission tomography (PET) study of 30 PD individuals and 30 age- and sex-matched healthy controls (HC) with the radiotracer [C]UCB-J, which binds to synaptic vesicle glycoprotein 2A (SV2A), and is therefore, a biomarker of synaptic density in the living brain.

Intense exercise increases dopamine transporter and neuromelanin concentrations in the substantia nigra in Parkinson's disease.

Parkinson's disease (PD) is characterized by a progressive loss of dopaminergic neurons. Exercise has been reported to slow the clinical progression of PD. We evaluated the dopaminergic system of patients with mild and early PD before and after a six-month program of intense exercise.

Objective response to ethanol in essential tremor: results from a standardized ethanol challenge study.

Background And Objectives: Ethanol has been reported to improve tremor severity in approximately two thirds of patients with essential tremor (ET), but the accuracy of that proportion is not certain and the mechanism of action is unknown. The goal of this study was to investigate alcohol response on tremor by applying an a priori objective response definition and subsequently to describe the responder rate to a standardized ethanol dose in a cohort of 85 ET patients. A secondary analysis evaluated other tremor and nontremor features, including demographics, tremor intensity, breath alcohol concentration, nontremor effects of alcohol, self-reported responder status to ethanol, and prior ethanol exposure.

Characterization of Early Stage Parkinson's Disease From Resting-State fMRI Data Using a Long Short-Term Memory Network.

Parkinson's disease (PD) is a common and complex neurodegenerative disorder with five stages on the Hoehn and Yahr scaling. Characterizing brain function alterations with progression of early stage disease would support accurate disease staging, development of new therapies, and objective monitoring of disease progression or treatment response. Functional magnetic resonance imaging (fMRI) is a promising tool in revealing functional connectivity (FC) differences and developing biomarkers in PD.

Magnetic resonance imaging modalities aid in the differential diagnosis of atypical parkinsonian syndromes.

Accurate and timely diagnosis of atypical parkinsonian syndromes (APS) remains a challenge. Especially early in the disease course, the clinical manifestations of the APS overlap with each other and with those of idiopathic Parkinson's disease (PD). Recent advances in magnetic resonance imaging (MRI) technology have introduced promising imaging modalities to aid in the diagnosis of APS.

Stroke in Parkinson's disease: a review of epidemiological studies and potential pathophysiological mechanisms.

Parkinson's disease (PD) is the fastest growing neurological disorder and one of the leading neurological causes of disability worldwide following stroke. An overall aging global population, as well as general changes in lifestyle associated with mass industrialization in the last century, may be linked to both increased incidence rates of PD and an increase in cumulative cardiovascular risk. Recent epidemiological studies show an increased risk of stroke, post-stroke complications, and subclinical ischemic insults in PD.

Mental imagery content is associated with disease severity and specific brain functional connectivity changes in patients with Parkinson's disease.

Mental imagery is the mental re-creation of perceptual experiences, events and scenarios, and motor acts. In our previous study, we assessed whether motor imagery (MI) training combined with functional magnetic resonance imaging-based neurofeedback could improve the motor function of nondemented subjects with mild Parkinson's disease (PD) (N = 22). We used visual imagery (VI) (e.

Semi-Supervised Learning of MRI Synthesis Without Fully-Sampled Ground Truths.

Learning-based translation between MRI contrasts involves supervised deep models trained using high-quality source- and target-contrast images derived from fully-sampled acquisitions, which might be difficult to collect under limitations on scan costs or time. To facilitate curation of training sets, here we introduce the first semi-supervised model for MRI contrast translation (ssGAN) that can be trained directly using undersampled k-space data. To enable semi-supervised learning on undersampled data, ssGAN introduces novel multi-coil losses in image, k-space, and adversarial domains.

The Legacy of Sport Events for Emerging Nations.

Large-scale and mega sport events (SMEs), such as Olympic Games and FIFA World Cups, have been more frequently hosted in emerging nations. Bidding and hosting SMEs is considered an object of policy for many emerging nations, with SMEs viewed as key factors in local and national development strategies. This has largely been driven by the assumption that their legacy provides solutions to economic, social, cultural, or political challenges.

Progressively volumetrized deep generative models for data-efficient contextual learning of MR image recovery.

Magnetic resonance imaging (MRI) offers the flexibility to image a given anatomic volume under a multitude of tissue contrasts. Yet, scan time considerations put stringent limits on the quality and diversity of MRI data. The gold-standard approach to alleviate this limitation is to recover high-quality images from data undersampled across various dimensions, most commonly the Fourier domain or contrast sets.

Hierarchical Denoising of Ordinal Time Series of Clinical Scores.

Clinical scores (disease rating scales) are ordinal in nature. Longitudinal studies which use clinical scores produce ordinal time series. These time series tend to be noisy and often have a short-duration.

Neurofeedback-guided kinesthetic motor imagery training in Parkinson's disease: Randomized trial.

Background: Parkinson's disease (PD) causes difficulty with maintaining the speed, size, and vigor of movements, especially when they are internally generated. We previously proposed that the insula is important in motivating intentional movement via its connections with the dorsomedial frontal cortex (dmFC). We demonstrated that subjects with PD can increase the right insula-dmFC functional connectivity using fMRI-based neurofeedback (NF) combined with kinesthetic motor imagery (MI).

Functional Connectome in Parkinson's Disease and Parkinsonism.

Purpose Of Review: There has been an exponential growth in functional connectomics research in neurodegenerative disorders. This review summarizes the recent findings and limitations of the field in Parkinson's disease (PD) and atypical parkinsonian syndromes.

Recent Findings: Increasingly more sophisticated methods ranging from seed-based to network and whole-brain dynamic functional connectivity have been used.

Distinct neural circuits are associated with subclinical neuropsychiatric symptoms in Parkinson's disease.

Background: Parkinson's disease (PD) can present with neuropsychiatric symptoms (here, anxiety, depression, and apathy) at any stage of the disease. We investigated the neural correlates of subclinical neuropsychiatric symptoms in relation to motor and cognitive symptoms in a high-functioning PD cohort.

Methods: Brain morphometry of the cognitively intact, early-stage (Hoehn & Yahr 2) PD group (n = 48) was compared to matched controls (n = 37).