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Diagnostics (Basel, Switzerland) Jan 2024Salivary DNA is widely used for genetic analyses because of its easy collection. However, its extracellular fraction in particular, similar to the extracellular DNA...
Salivary DNA is widely used for genetic analyses because of its easy collection. However, its extracellular fraction in particular, similar to the extracellular DNA (ecDNA) in plasma, could be a promising biomarker for oral or systemic diseases. In contrast to genetics, the quantity of salivary ecDNA is of importance and can be affected by the pre-analytical processing of samples, but the details are not known. The aim of our study was to analyze the effects of centrifugation and freezing of saliva on the concentration of ecDNA in saliva. Fifteen healthy volunteers, free of any known systemic or oral diseases, were asked to collect unstimulated saliva samples. Aliquots were centrifuged at 1600× and frozen or directly processed. The fresh or thawed cell-free saliva samples underwent subsequent centrifugation at 16,000× . The supernatants were used for DNA isolation and quantification using fluorometry and real-time PCR. While freezing had minimal effects on the salivary ecDNA concentration, another centrifugation step decreased ecDNA considerably in both fresh and frozen samples (by 97.8% and 98.4%, respectively). This was mirrored in the quantitative PCR targeting a nuclear (decrease by 93.5%) and mitochondrial (decrease by 97.7%) ecDNA sequence. In conclusion, in this first study focusing on the technical aspects of salivary ecDNA quantitation, we show that, regardless of its subcellular origin, the concentration of ecDNA in saliva is mainly affected by additional centrifugation and not by the freezing of centrifuged cell-free saliva samples. This suggests that most salivary ecDNA likely is associated with cell debris and apoptotic bodies. Which fraction is affected by a particular disease should be the focus of further targeted studies.
PubMed: 38337765
DOI: 10.3390/diagnostics14030249 -
Polymers Feb 2024The total rate of plastic production is anticipated to surpass 1.1 billion tons per year by 2050. Plastic waste is non-biodegradable and accumulates in natural... (Review)
Review
The total rate of plastic production is anticipated to surpass 1.1 billion tons per year by 2050. Plastic waste is non-biodegradable and accumulates in natural ecosystems. In 2020, the total amount of plastic waste was estimated to be 367 million metric tons, leading to unmanageable waste disposal and environmental pollution issues. Plastics are produced from petroleum and natural gases. Given the limited fossil fuel reserves and the need to circumvent pollution problems, the focus has shifted to biodegradable biopolymers, such as polyhydroxyalkanoates (PHAs), polylactic acid, and polycaprolactone. PHAs are gaining importance because diverse bacteria can produce them as intracellular inclusion bodies using biowastes as feed. A critical component in PHA production is the downstream processing procedures of recovery and purification. In this review, different bioengineering approaches targeted at modifying the cell morphology and synchronizing cell lysis with the biosynthetic cycle are presented for product separation and extraction. Complementing genetic engineering strategies with conventional downstream processes, these approaches are expected to produce PHA sustainably.
PubMed: 38337299
DOI: 10.3390/polym16030410 -
Scientific Reports Feb 2024Accurate annotation of vertebral bodies is crucial for automating the analysis of spinal X-ray images. However, manual annotation of these structures is a laborious and...
Accurate annotation of vertebral bodies is crucial for automating the analysis of spinal X-ray images. However, manual annotation of these structures is a laborious and costly process due to their complex nature, including small sizes and varying shapes. To address this challenge and expedite the annotation process, we propose an ensemble pipeline called VertXNet. This pipeline currently combines two segmentation mechanisms, semantic segmentation using U-Net, and instance segmentation using Mask R-CNN, to automatically segment and label vertebral bodies in lateral cervical and lumbar spinal X-ray images. VertXNet enhances its effectiveness by adopting a rule-based strategy (termed the ensemble rule) for effectively combining segmentation outcomes from U-Net and Mask R-CNN. It determines vertebral body labels by recognizing specific reference vertebral instances, such as cervical vertebra 2 ('C2') in cervical spine X-rays and sacral vertebra 1 ('S1') in lumbar spine X-rays. Those references are commonly relatively easy to identify at the edge of the spine. To assess the performance of our proposed pipeline, we conducted evaluations on three spinal X-ray datasets, including two in-house datasets and one publicly available dataset. The ground truth annotations were provided by radiologists for comparison. Our experimental results have shown that the proposed pipeline outperformed two state-of-the-art (SOTA) segmentation models on our test dataset with a mean Dice of 0.90, vs. a mean Dice of 0.73 for Mask R-CNN and 0.72 for U-Net. We also demonstrated that VertXNet is a modular pipeline that enables using other SOTA model, like nnU-Net to further improve its performance. Furthermore, to evaluate the generalization ability of VertXNet on spinal X-rays, we directly tested the pre-trained pipeline on two additional datasets. A consistently strong performance was observed, with mean Dice coefficients of 0.89 and 0.88, respectively. In summary, VertXNet demonstrated significantly improved performance in vertebral body segmentation and labeling for spinal X-ray imaging. Its robustness and generalization were presented through the evaluation of both in-house clinical trial data and publicly available datasets.
Topics: Tomography, X-Ray Computed; Vertebral Body; X-Rays; Radiography; Cervical Vertebrae; Image Processing, Computer-Assisted
PubMed: 38336974
DOI: 10.1038/s41598-023-49923-3 -
Neurobiology of Pain (Cambridge, Mass.) 2024Pain is a sensory state resulting from complex integration of peripheral nociceptive inputs and central processing. Pain consists of adaptive pain that is acute and... (Review)
Review
Pain is a sensory state resulting from complex integration of peripheral nociceptive inputs and central processing. Pain consists of adaptive pain that is acute and beneficial for healing and maladaptive pain that is often persistent and pathological. Pain is indeed heterogeneous, and can be expressed as nociceptive, inflammatory, or neuropathic in nature. Neuropathic pain is an example of maladaptive pain that occurs after spinal cord injury (SCI), which triggers a wide range of neural plasticity. The nociceptive processing that underlies pain hypersensitivity is well-studied in the spinal cord. However, recent investigations show maladaptive plasticity that leads to pain, including neuropathic pain after SCI, also exists at peripheral sites, such as the dorsal root ganglia (DRG), which contains the cell bodies of sensory neurons. This review discusses the important role DRGs play in nociceptive processing that underlies inflammatory and neuropathic pain. Specifically, it highlights nociceptor hyperexcitability as critical to increased pain states. Furthermore, it reviews prior literature on glutamate and glutamate receptors, voltage-gated sodium channels (VGSC), and brain-derived neurotrophic factor (BDNF) signaling in the DRG as important contributors to inflammatory and neuropathic pain. We previously reviewed BDNF's role as a bidirectional neuromodulator of spinal plasticity. Here, we shift focus to the periphery and discuss BDNF-TrkB expression on nociceptors, non-nociceptor sensory neurons, and non-neuronal cells in the periphery as a potential contributor to induction and persistence of pain after SCI. Overall, this review presents a comprehensive evaluation of large bodies of work that individually focus on pain, DRG, BDNF, and SCI, to understand their interaction in nociceptive processing.
PubMed: 38314104
DOI: 10.1016/j.ynpai.2024.100151 -
PloS One 2024DNA N6-methyladenine (6mA) modification is widespread in organisms and plays an important functional role in the regulation of cellular processes. As a model organism in...
DNA N6-methyladenine (6mA) modification is widespread in organisms and plays an important functional role in the regulation of cellular processes. As a model organism in biohydrometallurgy, Acidithiobacillus ferrooxidans can obtain energy from the oxidation of ferrous iron (Fe2+) and various reduced inorganic sulfides (RISCs) under acidic conditions. To determine the linkage between genomic DNA methylation and the switching between the two oxidative metabolic pathways in A. ferrooxidans, the 6mA landscape in the genome of A. ferrooxidans cultured under different conditions was evaluated by using 6mA-IP-seq. A total of 214 and 47 high-confidence peaks of 6mA were identified under the Fe2+ and RISCs oxidizing conditions, respectively (P<10-5), suggesting that genomic methylation was greater under Fe2+ oxidizing conditions. 6mA experienced a decline at the transcription start site (TSS) and occurs frequently in gene bodies under both oxidizing conditions. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that 7 KEGG pathways were mapped into and most of the differentially methylated genes were enriched in oxidative phosphorylation and metabolic pathways. Fourteen genes were selected for studying the effect of differences in methylation on mRNA expression. Thirteen genes, excluding petA-1, demonstrated a decrease in mRNA expression as methylation levels increased. Overall, the 6mA methylation enrichment patterns are similar under two conditions but show differences in the enriched pathways. The phenomenon of upregulated gene methylation levels coupled with downregulated expression suggests a potential association between the regulation mechanisms of 6mA and the Fe2+ and RISCs oxidation pathways.
Topics: Genome; Genomics; Acidithiobacillus; DNA Methylation; DNA; RNA, Messenger
PubMed: 38306373
DOI: 10.1371/journal.pone.0298204 -
Body Image Mar 2024Recent work has served to dissociate two dimensions of trait body dissatisfaction: body dissatisfaction frequency and body dissatisfaction duration. The present study...
Recent work has served to dissociate two dimensions of trait body dissatisfaction: body dissatisfaction frequency and body dissatisfaction duration. The present study sought to evaluate whether body dissatisfaction frequency and body dissatisfaction duration are each associated with distinct patterns of appearance-related cognitive processing. It was hypothesized that speeded attentional engagement with idealized bodies is associated with higher frequency of body dissatisfaction episodes, while slowed attentional disengagement from such information may instead be associated with higher duration of body dissatisfaction episodes. Participants (238 women, 149 men) completed an attentional task capable of independently assessing attentional engagement with, and attentional disengagement from, idealized bodies. Participants also completed both trait and in vivo (i.e., ecological momentary assessment) measures of body dissatisfaction frequency and duration. Results showed that neither engagement nor disengagement bias index scores predicted variance in either body dissatisfaction frequency measures or body dissatisfaction duration measures. Findings suggest that either biased attentional engagement with, and disengagement from, idealized bodies do not associate with the frequency and duration of body dissatisfaction episodes, or there are other key moderating factors involved in the expression of body dissatisfaction-linked attentional bias.
Topics: Male; Humans; Female; Body Dissatisfaction; Body Image; Attention; Attentional Bias; Cues
PubMed: 38301330
DOI: 10.1016/j.bodyim.2024.101680 -
Frontiers in Endocrinology 2023Fat content in bones and muscles, quantified by magnetic resonance imaging (MRI) as a proton density fat fraction (PDFF) value, is an emerging non-invasive biomarker....
BACKGROUND AND OBJECTIVE
Fat content in bones and muscles, quantified by magnetic resonance imaging (MRI) as a proton density fat fraction (PDFF) value, is an emerging non-invasive biomarker. PDFF has been proposed to indicate bone and metabolic health among postmenopausal women. Premenopausal women with a history of gestational diabetes (GDM) carry an increased risk of developing type 2 diabetes and an increased risk of fractures. However, no studies have investigated the associations between a history of GDM and PDFF of bone or of paraspinal musculature (PSM), composed of autochthonous muscle (AM) and psoas muscle, which are responsible for moving and stabilizing the spine. This study aims to investigate whether PDFF of vertebral bone marrow and of PSM are associated with a history of GDM in premenopausal women.
METHODS
A total of 37 women (mean age 36.3 ± 3.8 years) who were 6 to 15 months postpartum with (n=19) and without (n=18) a history of GDM underwent whole-body 3T MRI, including a chemical shift encoding-based water-fat separation. The PDFF maps were calculated for the vertebral bodies and PSM. The cross-sectional area (CSA) of PSM was obtained. Associations between a history of GDM and PDFF were assessed using multivariable linear and logistic regression models.
RESULTS
The PDFF of the vertebral bodies was significantly higher in women with a history of GDM (GDM group) than in women without (thoracic: median 41.55 (interquartile range 32.21-49.48)% vs. 31.75 (30.03-34.97)%; p=0.02, lumbar: 47.84 (39.19-57.58)% vs. 36.93 (33.36-41.31)%; p=0.02). The results remained significant after adjustment for age and body mass index (BMI) (p=0.01-0.02). The receiver operating characteristic curves showed optimal thoracic and lumbar vertebral PDFF cutoffs at 38.10% and 44.18%, respectively, to differentiate GDM (AUC 0.72 and 0.73, respectively, sensitivity 0.58, specificity 0.89). The PDFF of the AM was significantly higher in the GDM group (12.99 (12.18-15.90)% vs. 10.83 (9.39-14.71)%; p=0.04) without adjustments, while the CSA was similar between the groups (p=0.34).
CONCLUSION
A history of GDM is significantly associated with a higher PDFF of the vertebral bone marrow, independent of age and BMI. This statistical association between GDM and increased PDFF highlights vertebral bone marrow PDFF as a potential biomarker for the assessment of bone health in premenopausal women at risk of diabetes.
Topics: Humans; Female; Pregnancy; Adult; Bone Marrow; Diabetes, Gestational; Protons; Vertebral Body; Diabetes Mellitus, Type 2; Adipose Tissue; Lumbar Vertebrae; Biomarkers
PubMed: 38292769
DOI: 10.3389/fendo.2023.1303126 -
Cognition Apr 2024Words are the primary means by which we communicate meaning and ideas, while faces provide important social cues. Studying visual illusions involving faces and words can...
Words are the primary means by which we communicate meaning and ideas, while faces provide important social cues. Studying visual illusions involving faces and words can elucidate the hierarchical processing of information as different regions of the brain are specialised for face recognition and word processing. A size illusion has previously been demonstrated for faces, whereby an inverted face is perceived as larger than the same stimulus upright. Here, two experiments replicate the face size illusion, and investigate whether the illusion is also present for individual letters (Experiment 1), and visual words and pseudowords (Experiment 2). Results confirm a robust size Illusion for faces. Letters, words and pseudowords and unfamiliar letters all show a reverse size illusion, as we previously demonstrated for human bodies. Overall, results indicate the illusion occurs in early perceptual stages upstream of semantic processing. Results are consistent with the idea of a general-purpose mechanism that encodes curvilinear shapes found in both scripts and our environment. Word and face perception rely on specialised, independent cognitive processes. The underestimation of the size of upright stimuli is specific to faces. Opposite size illusions may reflect differences in how size information is encoded and represented in stimulus-specialised neural networks, resulting in contrasting perceptual effects. Though words and faces differ visually, there is both symmetry and asymmetry in how the brain 'reads' them.
Topics: Humans; Illusions; Face; Brain; Facial Recognition; Human Body; Pattern Recognition, Visual
PubMed: 38281395
DOI: 10.1016/j.cognition.2024.105733 -
Micromachines Jan 2024It is known that ceramic-polymer composite materials can be used to manufacture spherical bodies in the category of balls. Since balls are frequently subjected to...
It is known that ceramic-polymer composite materials can be used to manufacture spherical bodies in the category of balls. Since balls are frequently subjected to compression loads, the paper presents some research results on the compression behavior of balls made of ceramic composite materials with a polymer matrix. The mathematical model of the pressure variation inside the balls highlights the existence of maximum values in the areas of contact with other parts. Experimental research was carried out on balls with a diameter of 20 mm, manufactured by 3D printing from four ceramic-polymer composite materials with a polymer matrix: pottery clay, terracotta, concrete, and granite. The same ceramic-polymer composite material was used, but different dyes were added to it. A gravimetric analysis revealed similar behavior of the four materials upon controlled heating. Through the mathematical processing of the experimental results obtained by compression tests, empirical mathematical models of the power-type function type were determined. These models highlight the influence exerted by different factors on the force at which the initiation of cracks in the ball materials occurs. The decisive influence of the infill factor on the size of the force at which the cracking of the balls begins was found.
PubMed: 38276849
DOI: 10.3390/mi15010150 -
BMC Bioinformatics Jan 2024With the development of single-cell technology, many cell traits can be measured. Furthermore, the multi-omics profiling technology could jointly measure two or more...
BACKGROUND
With the development of single-cell technology, many cell traits can be measured. Furthermore, the multi-omics profiling technology could jointly measure two or more traits in a single cell simultaneously. In order to process the various data accumulated rapidly, computational methods for multimodal data integration are needed.
RESULTS
Here, we present inClust+, a deep generative framework for the multi-omics. It's built on previous inClust that is specific for transcriptome data, and augmented with two mask modules designed for multimodal data processing: an input-mask module in front of the encoder and an output-mask module behind the decoder. InClust+ was first used to integrate scRNA-seq and MERFISH data from similar cell populations, and to impute MERFISH data based on scRNA-seq data. Then, inClust+ was shown to have the capability to integrate the multimodal data (e.g. tri-modal data with gene expression, chromatin accessibility and protein abundance) with batch effect. Finally, inClust+ was used to integrate an unlabeled monomodal scRNA-seq dataset and two labeled multimodal CITE-seq datasets, transfer labels from CITE-seq datasets to scRNA-seq dataset, and generate the missing modality of protein abundance in monomodal scRNA-seq data. In the above examples, the performance of inClust+ is better than or comparable to the most recent tools in the corresponding task.
CONCLUSIONS
The inClust+ is a suitable framework for handling multimodal data. Meanwhile, the successful implementation of mask in inClust+ means that it can be applied to other deep learning methods with similar encoder-decoder architecture to broaden the application scope of these models.
Topics: Chromatin; Phenotype; Transcriptome
PubMed: 38267858
DOI: 10.1186/s12859-024-05656-2