Wiseotte1785

In addition, the marginal relation for whole grain, which may decrease BC incidence (RR = 0.95; 95% CI, 0.86-1.05), but increase BC mortality (RR = 1.02; 95% CI, 0.92-1.14). A marginal positive relation was also observed between sugar and BC incidence (RR = 1.04; 95% CI, 0.94-1.14). This meta-analysis of cohort studies suggested that dietary carbohydrate intake is associated with a lower risk of BC incidence, mortality, and recurrence.Diabetes mellitus is characterized by hyperglycemia. Low-grade bacterial infection with hyperglycemia in patients with diabetes is associated with atherosclerosis development. Therefore, this study hypothesized that macrophages lead to more severe diabetic complications under combined conditions of high glucose and lipopolysaccharide (LPS)-induced inflammation than under normoglycemic conditions. Zerumbone is the main component of Zingiber zerumbet Smith essential oil, a type of wild ginger. It possesses various biomedical activities, including antibacterial, antioxidant, anti-inflammatory, and anticancer activities; however, the precise mechanism of its anti-inflammatory and epigenetic effects is not fully understood. In this study, the effects of zerumbone on the secretion of proinflammatory cytokines and its underlying regulatory mechanism were investigated in THP-1-derived macrophages exposed to high glucose and LPS. THP-1-derived macrophages were cultured under normoglycemic (5.5 mmol/L glucose) or hyperglycemic (25 mmol/L glucose) conditions in the absence or presence of zerumbone (5-50 μM) for 48 hours and then treated with 100 ng/mL LPS for 6 hours. Zerumbone (25 and 50 μM) suppressed the production of tumor necrosis factor-α and interleukin-6 and the activation of cyclooxygenase-2, nuclear factor-κB, histone deacetylases 3 proteins, and Toll-like receptor messenger RNA (mRNA) and increased the transcription of the sirtuin 1 (SIRT1), SIRT3, and SIRT6 mRNAs. Taken together, our results suggest that zerumbone may exert beneficial effects on diabetes and its complications.A pro-inflammatory diet in pregnant women is associated with an increased risk of harmful maternal and fetal health outcomes. The present study aimed to investigate the relationship between the maternal energy-adjusted dietary inflammatory index (E-DII) and the classification of birth weight of newborns. We hypothesized that a maternal pro-inflammatory diet would be associated with a higher chance of inadequate birth weight infants. A prospective cohort study was conducted among 600 mother-infant pairs in Brazil. The E-DII was calculated through 24-hour dietary recalls on 2 occassions, using 36 of its 45 components. Secondary data on birth weight, sex of the newborns, and gestational age at birth were obtained. Adjusted logistic regression models were used to investigate the relationship between the maternal E-DII (in tertiles) and birth weight categories. The mothers' mean (standard deviation [SD]) age was 27 (5) years, 32.2% were overweight, and 21.5% had prepregnancy obesity. In total, 62 (10.3%) cases of small-for-gestational-age newborns and 79 (13.2%) of large-for-gestational-age (LGA) newborns were identified. The mean (SD) of the E-DII was 1.6 (1.5), ranging from -2.6 to 6.0. In adjusted logistic regression models, it was found that women classified in the third tertile of the E-DII had higher odds of having LGA infants (odds ratio, 2.07 [95% confidence interval, 1.07-4.02], P =.03), when compared with the women classified in the first tertile. A maternal pro-inflammatory diet was associated with a higher chance of LGA infants, reinforcing the relevance of the consumption of foods naturally rich in antioxidants during pregnancy.Neuronal homeostasis requires the transport of various organelles to distal compartments and defects in this process lead to neurological disorders. Although several mechanisms for the delivery of organelles to axons and dendrites have been elucidated, exactly how this process is orchestrated is not well-understood. In this review, we discuss the recent literature supporting a novel paradigm - the co-shuttling of mRNAs with different membrane-bound organelles. This model postulates that the tethering of ribonucleoprotein complexes to endolysosomes and mitochondria allows for the spatiotemporal coupling of organelle transport and the delivery of transcripts to axons. Subcellular translation of these "hitchhiking" transcripts may thus provide a proximal source of proteins required for the maintenance and function of organelles in axons.The extracellular microenvironments play a key role in tumor metabolism. To online dynamic monitoring the efficacy of 7-hydroxycoumarin (7-OHC) to cells cultured on microfluidics in acidic microenvironment, we developed an integrated multi-channel chip-mass spectrometry system. This system has six drug-loading units, cell culture chamber, metabolite collection, filtration, HPLC separation and MS detection. The cells in each microchannel will be incubated with continuous flow of culture medium, metabolites will be collected by the fixed card slot, automatic sampling needle will be precise positioned and sampled. Through this new system, the 7-hydroxycoumarin-sulfonate (7-OHC-sulfonate) and 7-hydroxycoumarin-glucuronide (7-OHC-glucuronide) can be determined in real-time. The results revealed that the addition of lactic acid promoted the formation of inactive 7-OHC-sulfonate and 7-OHC-glucuronide metabolites. Besides, acidic extracellular environment amplified cancer cell proliferation, indicating the anticancer effect of 7-OHC was weakened by low extracellular pH.We developed a simple, inexpensive, environmentally friendly one-step fabrication of a flexible laser induced graphene-chitosan-gold nanoparticles (LIG-CS-AuNPs) electrode. The fabrication was based on a laser treatment of polyimide (PI) film coated with CS solution containing gold ions (Au (III)). The AuNPs decorating the induced 3D graphene composite were uniformly distributed. The electrode exhibited good electrical conductivity and excellent electrocatalytic activity toward the oxidation of UA. To enable on-site monitoring of uric acid (UA) in blood serum by differential pulse adsorptive stripping voltammetry (DPAdSV), the electrode was coupled to a portable potentiostat connected to a cellphone to control and monitor analysis. The affecting parameters of DPAdSV were optimized. Under the optimal conditions for UA determination, the limit of detection of the developed sensor was 0.33 μmol L-1 and the limit of quantification 1.10 μmol L-1. find more Two linear ranges were produced 1.0-30 μmol L-1 and 30-100 μmol L-1. The sensor was highly sensitive and demonstrated excellent reproducibility and selectivity, determining UA in blood serum with recoveries between 86.6 ± 0.6 and 94.7 ± 0.4%. The analysis results were in agreement with those of the hospital standard enzymatic method.

This study aims to achieve an automatic differential diagnosis between two types of retinal pathologies with similar pathological features - Polypoidal choroidal vasculopathy (PCV) and wet age-related macular degeneration (AMD) from volumetric optical coherence tomography (OCT) images, and identify clinically-relevant pathological features, using an explainable deep-learning-based framework.

This is a retrospective study with data from a cross-sectional cohort. The OCT volume of 73 eyes from 59 patients was included in this study. Disease differentiation was achieved through single-B-scan-based classification followed by a volumetric probability prediction aggregation step. We compared different labeling strategies with and without identifying pathological B-scans within each OCT volume. Clinical interpretability was achieved through normalized aggregation of B-scan-based saliency maps followed by maximum-intensity-projection onto the en face plane. We derived the PCV score from the proposed differential diagnosis framework with different labeling strategies. The en face projection of saliency map was validated with the pathologies identified in Indocyanine green angiography (ICGA).

Model trained with both labeling strategies achieved similar level differentiation power (>90%), with good correspondence between pathological features detected from the projected en face saliency map and ICGA.

This study demonstrated the potential clinical application of non-invasive differential diagnosis using AI-driven OCT-based analysis, with minimal requirement of labeling efforts, along with clinical explainability achieved through automatically detected disease-related pathologies.

This study demonstrated the potential clinical application of non-invasive differential diagnosis using AI-driven OCT-based analysis, with minimal requirement of labeling efforts, along with clinical explainability achieved through automatically detected disease-related pathologies.The COVID-19 (coronavirus disease 2019) pandemic affected more than 186 million people with over 4 million deaths worldwide by June 2021. The magnitude of which has strained global healthcare systems. Chest Computed Tomography (CT) scans have a potential role in the diagnosis and prognostication of COVID-19. Designing a diagnostic system, which is cost-efficient and convenient to operate on resource-constrained devices like mobile phones would enhance the clinical usage of chest CT scans and provide swift, mobile, and accessible diagnostic capabilities. This work proposes developing a novel Android application that detects COVID-19 infection from chest CT scans using a highly efficient and accurate deep learning algorithm. It further creates an attention heatmap, augmented on the segmented lung parenchyma region in the chest CT scans which shows the regions of infection in the lungs through an algorithm developed as a part of this work, and verified through radiologists. We propose a novel selection approach combined with multi-threading for a faster generation of heatmaps on a Mobile Device, which reduces the processing time by about 93%. The neural network trained to detect COVID-19 in this work is tested with a F1 score and accuracy, both of 99.58% and sensitivity of 99.69%, which is better than most of the results in the domain of COVID diagnosis from CT scans. This work will be beneficial in high-volume practices and help doctors triage patients for the early diagnosis of COVID-19 quickly and efficiently.Temporal interference stimulation (TIS) has been proved to be effective in stimulating deep brain regions while avoiding the stimulation of neocortical regions in animal experiments. In the traditional TIS, two alternating currents are injected with different frequencies via two electrode pairs attached to the scalp. In the human brain, however, it is difficult to achieve a focal stimulation of deep brain structures due to the high complexity of human brain structures. In this study, we hypothesized that the use of multiple electrode pairs may contribute to the more focalized delivery of temporal interference (TI) currents to the target site in the deep area of the brain. Based on this hypothesis, we proposed a novel multipair TIS method that employs more than two electrode pairs for improved focalized stimulation of the deep brain region (in this study, the head of the right hippocampus). Three realistic finite element models were used to validate the feasibility of the proposed multipair TIS. Additional electrode pairs were sequentially added to the conventional two-electrode pairs with the aim of maximizing the delivery of TI currents to the target while minimizing TI currents in the neocortical regions.