Effect of Amorphization Methods on the Properties and Structures of Potato Starch-Monoglyceride Complex

Recently, starch-based fat replacers (FRs) have emerged as unique ingredients, possessing few calories and high vascular scavenger function without adverse organoleptic changes. Here, a two-step modification method for the development of a starch-based FRs is reported. First, native potato starch is amorphized by grinding, alkali and ethanol treatment. Then, the amorphized starch is complexed with monoglyceride. The results show that alkaline amorphous potato starch (AAPS) has the best emulsifying activity; ethanol amorphous potato starch complex (EAPSC) has the highest content of resistant starch (RS) (21.49%), while grinding amorphous potato starch (GAPS) retains the granular structure of the original starch best. The amorphization reduces the amylose content of starch, leading to reduced swelling power and increased digestibility. Complexation, on the other hand, is more like attaching a layer of the hydrophobic membrane. Combined with DSC and XRD, amorphization reduces the value of enthalpy and crystallinity, while the complexation process does the opposite. Overall, EAPSC is the best candidate for novel FRs, due to its greater emulsion stability and enzyme resistance. The experimental results provide a theoretical basis for the application of a novel potato starch-monoglyceride complex in foods such as cakes and snack fillings

Ferroptosis-associated circular RNAs: Opportunities and challenges in the diagnosis and treatment of cancer

Ferroptosis is an emerging form of non-apoptotic regulated cell death which is different from cell death mechanisms such as autophagy, apoptosis and necrosis. It is characterized by iron-dependent lipid peroxide accumulation. Circular RNA (circRNA) is a newly studied evolutionarily conserved type of non-coding RNA with a covalent closed-loop structure. It exhibits universality, conservatism, stability and particularity. At present, the functions that have been studied and found include microRNA sponge, protein scaffold, transcription regulation, translation and production of peptides, etc. CircRNA can be used as a biomarker of tumors and is a hotspot in RNA biology research. Studies have shown that ferroptosis can participate in tumor regulation through the circRNA molecular pathway and then affect cancer progression, which may become a direction of cancer diagnosis and treatment in the future. This paper reviews the molecular biological mechanism of ferroptosis and the role of circular RNA in tumors and summarizes the circRNA related to ferroptosis in tumors, which may inspire research prospects for the precise prevention and treatment of cancer in the future

Recombinant human thioredoxin-1 promotes neurogenesis and facilitates cognitive recovery following cerebral ischemia in mice

AbstractCerebral ischemia (CI) can induce loss of hippocampal neurons, causing cognitive dysfunction such as learning and memory deficits. In adult mammals, the hippocampal dentate gyrus contains neural stem cells (NSCs) that continuously generate newborn neurons and integrate into the pre-existing networks throughout life, which may ameliorate cognitive dysfunction following CI. Recent studies have demonstrated that recombinant human thioredoxin-1 (rhTrx-1) could promote proliferation of human adipose tissue-derived mesenchymal stem cells and angiogenesis. To investigate whether rhTrx-1 also regulates hippocampal neurogenesis following CI and its underlying mechanisms, adult mice were subjected to bilateral common carotid arteries occlusion (BCCAO) to induce CI and treated with rhTrx-1 before reperfusion. Mice treated with rhTrx-1 showed shortened escape latencies in Morris water maze by 30 days and improvements in spatial memory demonstrated by probe trial test. Enhanced NSCs proliferation was observed at day 14, indicated by BrdU and Ki67 immunostaining. Doublecortin (DCX)+ cells were also significantly increased following rhTrx-1 treatment. Despite increases in BrdU+/NeuN+ cells by day 30, the double-labeling to total BrdU+ ratio was not affected by rhTrx-1 treatment. The promotive effects of rhTrx-1 on NSCs proliferation and differentiation were further confirmed in in vitro assays. Western blot revealed increased ERK1/2 phosphorylation after rhTrx-1 treatment, and the ERK inhibitor U0126 abrogated the effects of rhTrx-1 on NSCs proliferation. These results provide initial evidence that rhTrx-1 effects neurogenesis through the ERK signaling pathway and are beneficial for improving spatial learning and memory in adult mice following global CI

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labor-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation; the 3-electrode EEG signals of 55 subjects were recorded in resting state; the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis

Biomechanical Analysis Of The Pars Interarticularis Fracture In Athletes

Pars interarticularis fracture (PIF) means that the bone between the superior and inferior articular is disconnected. For adults, the incidence is about 5%. Especially in L4 and L5 their incidence were seperately 85% and 15%. But among sportsmen the incidence is much higher, about 20.7%. The investigation among the athletes in 26 events showed that the volleyball player's incidence was the highest, about 50%. In other events it was: acrobatic gymnastics 47%. high hump 29%, javelin, pole vault and triple jump 27 %. In other events they were all under 20%. But in weightlifters it is only 8%. By analysing the events having higher incidence, it can be found that PIF often happens in the athletes needing more extending exercise. So that two experiments were done - spine specimen experiment and 3 dimensional photoelastic experiment, to analyse the PIF. The experiment of spine specimen was used to study and compare the forces born by the pars interarticularis in erect and extended spine. A special transducer was designed and horizontally put between L5 and 51. To analogue the different postures of the spine the load was applied in different methods. The experiments showed that in the erect spine, the shear force born by the pars interarticularis of the 5th lumber vertebra was 27% of the applying load, but in the extending spine it is 73%. These result are consistant with the above facts that the PIF often happens in the athletes who have to do more extending exercise and the incidence in weight lifter is the smallest. It was also acquired that the lumbar-sacrum angle is another important factor for the PIF. The bigger is the angle, the easier is the fracture. The photoelastic model of spine was made of epoxy resin. The ligments were substituted by the carbon fibre and the intervertebral discs by silicone rubber. The posterior joint caves were filled with a special material. Six slices, cut from the pars interarticularis of the erect and extended spine model, were analysed in the photoelastic meter. The result shows that the shearing stress distribution among the boundary of the pars in terarticularis in the extended spine is much higher than that in the erect spine. Its maximum shearing stress is about 2.7 times of the maximum one in other slices. It was verified again that PIF is much common in extended spine and its real reason is the shearing stress

Crack Extension and Possibility of Debonding in Encapsulation-Based Self-Healing Materials

The breakage of capsules upon crack propagation is crucial for achieving crack healing in encapsulation-based self-healing materials. A mesomechanical model was developed in this study to simulate the process of crack propagation in a matrix and the potential of debonding. The model used the extended finite element method (XFEM) combined with a cohesive zone model (CZM) in a two-dimensional (2D) configuration. The configuration consisted of an infinite matrix with an embedded crack and a capsule nearby, all subjected to a uniaxial remote tensile load. A parametric study was performed to investigate the effect of geometry, elastic parameters and fracture properties on the fracture response of the system. The results indicated that the effect of the capsule wall on the fracture behavior of the matrix is insignificant for tc/Rc ≤ 0.05. The matrix strength influenced the ultimate crack length, while the Young’s modulus ratio Ec/Em only affected the rate of crack propagation. The potential for capsule breakage or debonding was dependent on the comparative strength between capsule and interface (Sc/Sint), provided the crack could reach the capsule. The critical value of Sc,cr/Sint,cr was obtained using this model for materials design

Characteristics and Residual Health Risk of Organochlorine Pesticides in Fresh Vegetables in the Suburb of Changchun, Northeast China

In this study, eleven organochlorine pesticides (OCPs) in fresh vegetables in the Changchun suburb were investigated, and their potential health risks were evaluated. The average concentrations of OCPs in edible parts of vegetables were found in the following descending order: Σhexachlorocyclohexanes (ΣHCHs) (6.60 µg·kg−1) > Σdichlorodiphenyltrichloroethanes (ΣDDTs) (5.82 µg·kg−1) > ΣChlordanes (2.37 µg·kg−1) > heptachlor (0.29 µg·kg−1). Moreover, OCPs in different types of vegetables exceeded the maximum residue limits (MRLs), and the exceeding rates in various vegetables decreased in the following order: leafy vegetables (19.12%) > root vegetables (18.75%) > fruit vegetables (3.85%). The proportions of OCPs exceeding MRL in different vegetables were found in the following descending order: Welsh onion (22.50%) > radish (18.75%) > Chinese cabbage (14.29%) > pepper (6.90%) > cucumber (3.23%) > eggplant (2.94%) > tomato (2.78%). The sources’ identification results showed that DDTs in vegetables came mainly from newly imported technical DDTs and dicofol, while HCHs originated mainly from lindane. For both adults and children, the average target hazard quotients (avg. THQ) were all less than 1, and the average hazard index (avg. HI) values were 0.043 and 0.036, respectively. There were no significant health risks associated with OCP exposure for the inhabitants of the study area

TAE-Net: Task-Adaptive Embedding Network for Few-Shot Remote Sensing Scene Classification

Recently, approaches based on deep learning are quite prevalent in the area of remote sensing scene classification. Though significant success has been achieved, these approaches are still subject to an excess of parameters and extremely dependent on a large quantity of labeled data. In this study, few-shot learning is used for remote sensing scene classification tasks. The goal of few-shot learning is to recognize unseen scene categories given extremely limited labeled samples. For this purpose, a novel task-adaptive embedding network is proposed to facilitate few-shot scene classification of remote sensing images, referred to as TAE-Net. A feature encoder is first trained on the base set to learn embedding features of input images in the pre-training phase. Then in the meta-training phase, a new task-adaptive attention module is designed to yield the task-specific attention, which can adaptively select informative embedding features among the whole task. In the end, in the meta-testing phase, the query image derived from the novel set is predicted by the meta-trained model with limited support images. Extensive experiments are carried out on three public remote sensing scene datasets: UC Merced, WHU-RS19, and NWPU-RESISC45. The experimental results illustrate that our proposed TAE-Net achieves new state-of-the-art performance for few-shot remote sensing scene classification