Analysis of Eco-Hydrological Characteristics of the Four Famous Carps' Spawning Grounds in the Middle Reach of Yangtze River

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Cryo-EM Studies of TMEM16F Calcium-Activated Ion Channel Suggest Features Important for Lipid Scrambling.

As a Ca2+-activated lipid scramblase and ion channel that mediates Ca2+ influx, TMEM16F relies on both functions to facilitate extracellular vesicle generation, blood coagulation, and bone formation. How a bona fide ion channel scrambles lipids remains elusive. Our structural analyses revealed the coexistence of an intact channel pore and PIP2-dependent protein conformation changes leading to membrane distortion. Correlated to the extent of membrane distortion, many tightly bound lipids are slanted. Structure-based mutagenesis studies further reveal that neutralization of some lipid-binding residues or those near membrane distortion specifically alters the onset of lipid scrambling, but not Ca2+ influx, thus identifying features outside of channel pore that are important for lipid scrambling. Together, our studies demonstrate that membrane distortion does not require open hydrophilic grooves facing the membrane interior and provide further evidence to suggest separate pathways for lipid scrambling and ion permeation

Is histogram manipulation always beneficial when trying to improve model performance across devices? Experiments using a Meibomian gland segmentation model

Meibomian gland dysfunction (MGD) is caused by abnormalities of the meibomian glands (MG) and is one of the causes of evaporative dry eye (DED). Precise MG segmentation is crucial for MGD-related DED diagnosis because the morphological parameters of MG are of importance. Deep learning has achieved state-of-the-art performance in medical image segmentation tasks, especially when training and test data come from the same distribution. But in practice, MG images can be acquired from different devices or hospitals. When testing image data from different distributions, deep learning models that have been trained on a specific distribution are prone to poor performance. Histogram specification (HS) has been reported as an effective method for contrast enhancement and improving model performance on images of different modalities. Additionally, contrast limited adaptive histogram equalization (CLAHE) will be used as a preprocessing method to enhance the contrast of MG images. In this study, we developed and evaluated the automatic segmentation method of the eyelid area and the MG area based on CNN and automatically calculated MG loss rate. This method is evaluated in the internal and external testing sets from two meibography devices. In addition, to assess whether HS and CLAHE improve segmentation results, we trained the network model using images from one device (internal testing set) and tested on images from another device (external testing set). High DSC (0.84 for MG region, 0.92 for eyelid region) for the internal test set was obtained, while for the external testing set, lower DSC (0.69–0.71 for MG region, 0.89–0.91 for eyelid region) was obtained. Also, HS and CLAHE were reported to have no statistical improvement in the segmentation results of MG in this experiment

A geostationary orbit microwave multi-channel radiometer

The geostationary orbit microwave multi-channel radiometer has the advantages of high real-time performance and large coverage, which plays an important role in typhoon, strong precipitation detection, and medium-to-short-term meteorological/oceanic forecasting. However, due to the difficulty in engineering development of the payload, its application on-orbit has not yet been achieved at present. To satisfy the requirements of fine and quantitative application of satellite observation data, a geostationary orbit microwave multi-channel radiometer with a 10-m-caliber is developed, in which the spatial resolution at horizontal polarization is better than 24 km at 54 GHz. In geostationary orbit microwave multi-channel radiometer, a quasi-optical feed network covering nearly 28 frequency octave bands and ranging from 23.8 to 664 GHz is proposed to solve the technical problem of multi-frequency sharing in the system. Meanwhile, a high-precision reflector preparation method and a high-precision unfolding scheme are proposed, which are considered as a solution for the large-diameter reflector with a high maintaining surface accuracy. A high-precision antenna prototype with 0.54-m is developed, and the tests are performed to verify the key technologies, such as the preparation of high-precision grating reflectors at the micron level, high surface accuracy detection, and sub-millimeter wave antenna electrical performance testing. The results indicate that measured main beam efficiency of the 664 GHz antenna is better than 95.5%. In addition, the system sensitivity is greater than 1.5 K, and the calibration accuracy is better than 1.8 K, according to the results of an analysis of the multi-channel radiometer’s essential parameters and calibration errors

A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes

BackgroundTumor infiltrating lymphocytes (TILs), the main component in the tumor microenvironment, play a critical role in the antitumor immune response. Few studies have developed a prognostic model based on TILs in osteosarcoma.MethodsScRNA-seq data was obtained from our previous research and bulk RNA transcriptome data was from TARGET database. WGCNA was used to obtain the immune-related gene modules. Subsequently, we applied LASSO regression analysis and SVM algorithm to construct a prognostic model based on TILs marker genes. What’s more, the prognostic model was verified by external datasets and experiment in vitro. ResultsEleven cell clusters and 2044 TILs marker genes were identified. WGCNA results showed that 545 TILs marker genes were the most strongly related with immune. Subsequently, a risk model including 5 genes was developed. We found that the survival rate was higher in the low-risk group and the risk model could be used as an independent prognostic factor. Meanwhile, high-risk patients had a lower abundance of immune cell infiltration and many immune checkpoint genes were highly expressed in the low-risk group. The prognostic model was also demonstrated to be a good predictive capacity in external datasets. The result of RT-qPCR indicated that these 5 genes have differential expression which accorded with the predicting outcomes.ConclusionsThis study developed a new molecular signature based on TILs marker genes, which is very effective in predicting OS prognosis and immunotherapy response

Convolutional Neural Networks for Classification of T2DM Cognitive Impairment Based on Whole Brain Structural Features

PurposeCognitive impairment is generally found in individuals with type 2 diabetes mellitus (T2DM). Although they may not have visible symptoms of cognitive impairment in the early stages of the disorder, they are considered to be at high risk. Therefore, the classification of these patients is important for preventing the progression of cognitive impairment.MethodsIn this study, a convolutional neural network was used to construct a model for classifying 107 T2DM patients with and without cognitive impairment based on T1-weighted structural MRI. The Montreal cognitive assessment score served as an index of the cognitive status of the patients.ResultsThe classifier could identify T2DM-related cognitive decline with a classification accuracy of 84.85% and achieved an area under the curve of 92.65%.ConclusionsThe model can help clinicians analyze and predict cognitive impairment in patients and enable early treatment

Brain Activities Responding to Acupuncture at ST36 (zusanli) in Healthy Subjects: A Systematic Review and Meta-Analysis of Task-Based fMRI Studies

PurposeStomach 36 (ST36, zusanli) is one of the important acupoints in acupuncture. Despite clinical functional magnetic resonance imaging (fMRI) studies of ST36 acupuncture, the brain activities and the neural mechanism following acupuncture at ST36 remain unclear.MethodsLiterature searches were conducted on online databases, including MEDLINE, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang database, WeiPu database, and China Biology Medicine, for task-based fMRI studies of acupuncture at ST36 in healthy subjects. Brain regions activated by ST36 acupuncture were systematically evaluated and subjected to seed-based d mapping meta-analysis. Subgroup analysis was conducted on control procedures, manual acupuncture, electrical acupuncture (EA), and acupuncture-specific activations. Meta-regression analysis was performed to explore the effects of needle retention time on brain activities following ST36 acupuncture stimulation. The activated brain regions were further decoded and mapped on large-scale functional networks to further decipher the clinical relevance of acupuncturing at ST36.ResultsA total of sixteen studies, involving a total of 401 right-handed healthy participants, that satisfied the inclusion criteria were included in the present meta-analysis. Meta-analysis showed that acupuncturing on ST36 positively activates the opercular part of the right inferior frontal gyrus (IFG.R), left superior temporal gyrus (STG.L), and right median cingulate/paracingulate gyri (MCG.R) regions. Needle retention time in an acupuncture session positively correlates with the activation of the left olfactory cortex, as shown in meta-regression analysis. Subgroup analysis revealed that EA stimulation may be a source of heterogeneity in the pooled results. Functional network mappings showed that the activated areas were mapped to the auditory network and salience network. Further functional decoding analysis showed that acupuncture on ST36 was associated with pain, secondary somatosensory, sound and language processing, and mood regulation.ConclusionAcupuncture at ST36 in healthy individuals positively activates the opercular part of IFG.R, STG.L, and MCG.R. The left olfactory cortex may exhibit positive needle retention time-dependent activities. Our findings may have clinical implications for acupuncture in analgesia, language processing, and mood disorders.Systematic Review Registrationhttps://inplasy.com/inplasy-2021-12-0035

Microstructure and mechanical properties of Cu joints soldered with a Sn-based composite solder, reinforced by metal foam

In this study, Ni foam, Cu coated Ni foam and Cu-Ni alloy foams were used as strengthening phases for pure Sn solder. Cu-Cu joints were fabricated by soldering with these Sn-based composite solders at 260 °C for different times. The tensile strength of pure Sn solder was improved significantly by the addition of metal foams, and the Cu-Ni alloy/Sn composite solder exhibited the highest tensile strength of 50.32 MPa. The skeleton networks of the foams were gradually dissolved into the soldering seam with increasing soldering time, accompanied by the massive formation of (Cu,Ni)6Sn5 phase in the joint. The dissolution rates of Ni foam, Cu coated Ni foam and Cu-Ni alloy foams into the Sn matrix increased successively during soldering. An increased dissolution rate of the metal foam leads to an increase in the Ni content in the soldering seam, which was found to be beneficial in refining the (Cu,Ni)6Sn5 phase and inhibiting the formation of the Cu3Sn IMC layer on the Cu substrate surface. The average shear strength of the Cu joints was improved with increasing soldering time, and a shear strength of 61.2 MPa was obtained for Cu joints soldered with Cu-Ni alloy/Sn composite solder for 60 min