Phenotype Transformation of PitNETs.

Phenotype transformation in pituitary neuroendocrine tumors is a little-known and unpredictable clinical phenomenon. Previous studies have not clearly defined and systematically concluded on the causes of this rare phenomenon. Additionally, the mechanisms of phenotype transformation are not well known. We reviewed cases reported in the literature with the aim of defining phenotype transformation in pituitary neuroendocrine tumors. We present an overview of the wide spectrum of phenotype transformation and its clinical features. We also discuss findings on the potential mechanism of this rare transformation, which may be related to PC1/3, the bioactivity of secretory hormones, gene mutations and the plasticity of pituitary neuroendocrine tumors. Clinicians should be aware of this rare phenomenon and more studies on the underlying mechanisms are required.

The effect and mechanism of inulin on atherosclerosis is mediated by the characteristic intestinal flora and metabolites.

BACKGROUND: Inflammation and hyperlipidemia can cause atherosclerosis. Prebiotic inulin has been proven to effectively reduce inflammation and blood lipid levels. Utilizing a mouse model induced by a high-fat diet, this study aimed to explore whether the characteristic intestinal flora and its metabolites mediate the effects of inulin intervention on atherosclerosis and to clarify the specific mechanism. METHODS: Thirty apolipoprotein E-deficient (ApoE-/-) mice were randomly divided into three groups. They were fed with a normal diet, a high-fat diet or an inulin+high-fat diet for 16 weeks. The total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) in the three groups were compared. The gross aorta and aortic sinus of mice were stained with oil red O, and the area of atherosclerotic plaque was observed and compared. The diversity and structure of the mouse fecal flora were detected by sequencing the V3-V4 region of the 16S rRNA gene, and the levels of metabolites in mouse feces were assessed by gas chromatography-mass spectrometry. The plasma lipopolysaccharide (LPS) levels and aortic inflammatory factors were measured by multi-index flow cytometry (CBA). RESULTS: ApoE-/- mice fed with the high-fat diet exhibited an increase of approximately 46% in the area of atherosclerotic lesions, and the levels of TC, TG and LDL-C were significantly increased (P < 0.05) compared with levels in the normal diet group. After inulin was added to the high-fat group, the area of atherosclerotic lesions, the level of serum LPS and aortic inflammation were reduced, and the levels of TC, TG and LDL-C were decreased (P < 0.05). Based on 16S rRNA gene detection, we found that the composition of the intestinal microbiota, such as Prevotella, and metabolites, such as L-arginine, changed significantly due to hyperlipidemia, and the dietary inulin intervention partially reversed the relevant changes. CONCLUSION: Inulin can inhibit the formation of atherosclerotic plaques, which may be related to the changes in lipid metabolism, the composition of the intestinal microbial community and its metabolites, and the inhibition of the expression of related inflammatory factors. Our study identified the relationships among the characteristic intestinal microbiota, metabolites and atherosclerosis, aiming to provide a new direction for future research to delay or treat atherosclerosis by changing the composition and function of the host intestinal microbiota and metabolites.

Disentangling influences of driving forces on intra-annual variability in sediment discharge in karst watersheds.

The intra-annual variability in sediment discharge was considerably influenced by the climate variability and vegetation dynamics. Because of the coupled or relationships between climatic and vegetation variables, it is still challenging to decouple the direct and indirect effects of climate variability and vegetation dynamics on hydrological and sediment transport processes. The purpose of this study is to decouple influences of individual driving force on intra-annual distribution of sediment discharge during 2003-2017 using the partial least squares structural equation model (PLS-SEM) method in four typical karst watersheds of Southwest China. The coefficient of variation (Cv), Completely regulation coefficient (Cr), Lorenz asymmetry coefficient and Gini coefficient were used to represent the intra-annual sediment discharge variability. Results showed that the monthly sediment discharge (190 % < Cv < 353 %) exhibited greater variability than its potential affecting factors (18 % < Cv < 101 %). From the PLS-SEM analysis, the water discharge, climate, and vegetation together explain 57 %-75 %, 64 %-79 %, and 53 %-80 % of the total variance in Cv, Cr, and Gini coefficient, respectively. Specifically, water discharge exerts the largest influence on sediment discharge variability (0.65 ≤ direct effect ≤0.97, P < 0.05), while vegetation dynamic mainly indirectly affects sediment discharge variability (-0.88 ≤ indirect effect ≤ -0.01) through influencing water discharge. The climate factors also principally indirectly affect the sediment discharge variability (-0.47 ≤ indirect effect ≤0.19) by affecting water discharge and vegetation. The PLS-SEM can effectively reveal the driving force and influencing mechanism of intra-annual sediment discharge changes, and provide an important reference for regional soil and water resources management in karst watersheds. Future studies can decouple the influences of the extreme climate, unique lithology, discontinuous soil, heterogeneous landscape, and special geomorphology on spatial variability in sediment discharge across different karst watersheds.

Multimodal brain tumor image segmentation based on DenseNet.

A brain tumor magnetic resonance image processing algorithm can help doctors to diagnose and treat the patient's condition, which has important application significance in clinical medicine. This paper proposes a network model based on the combination of U-net and DenseNet to solve the problems of class imbalance in multi-modal brain tumor image segmentation and the loss of effective information features caused by the integration of features in the traditional U-net network. The standard convolution blocks of the coding path and decoding path on the original network are improved to dense blocks, which enhances the transmission of features. The mixed loss function composed of the Binary Cross Entropy Loss function and the Tversky coefficient is used to replace the original single cross-entropy loss, which restrains the influence of irrelevant features on segmentation accuracy. Compared with U-Net, U-Net++, and PA-Net the algorithm in this paper has significantly improved the segmentation accuracy, reaching 0.846, 0.861, and 0.782 respectively in the Dice coefficient index of WT, TC, and ET. The PPV coefficient index has reached 0.849, 0.883, and 0.786 respectively. Compared with the traditional U-net network, the Dice coefficient index of the proposed algorithm exceeds 0.8%, 4.0%, and 1.4%, respectively, and the PPV coefficient index in the tumor core area and tumor enhancement area increases by 3% and 1.2% respectively. The proposed algorithm has the best performance in tumor core area segmentation, and its Sensitivity index has reached 0.924, which has good research significance and application value.

Epidemiological behaviour and interventions of malaria in Niger, 2010-2019: a time-series analysis of national surveillance data.

BACKGROUND: Malaria remains a significant public health concern in Niger, with the number of cases increasing from 592,334 in 2000 to 3,138,696 in 2010. In response, a concerted campaign against the disease has been initiated. However, the implementation of these malaria interventions and their association with epidemiological behaviour remains unclear. METHODS: A time-series study was conducted in Niger from 2010 to 2019. Multiple data sources concerning malaria were integrated, encompassing national surveillance data, Statistic Yearbook, targeted malaria control interventions, and meteorological data. Incidence rate, mortality rate, and case fatality ratio (CFR) by different regions and age groups were analysed. Joinpoint regression models were used to estimate annual changes in malaria. The changes in coverage of malaria interventions were evaluated. RESULTS: Between 2010 to 2019, the incidence rate of malaria decreased from 249.43 to 187.00 cases per 1,000 population in Niger. Niamey had a high annual mean incidence rate and the lowest CFR, while Agadez was on the contrary. Joinpoint regression analysis revealed a declining trend in malaria incidence for all age groups except the 10-24 years group, and the mortality rate and the CFR initially decreased followed by an increase in all age groups. Niger has implemented a series of malaria interventions, with the major ones being scaled up to larger populations during the study period. CONCLUSIONS: The scale-up of multi-interventions in Niger has significantly reduced malaria incidence, but the rise in mortality rate and CFR addresses the challenges in malaria control and elimination. Malaria endemic countries should enhance surveillance of malaria cases and drug resistance in Plasmodium, improve diagnosis and treatment, expand the population coverage of insecticide-treated bed nets and seasonal malaria chemoprevention, and strengthen the management of severe malaria cases.

Comorbidity increases the risk of pulmonary tuberculosis: a nested case-control study using multi-source big data.

BACKGROUND: Some medical conditions may increase the risk of developing pulmonary tuberculosis (PTB); however, no systematic study on PTB-associated comorbidities and comorbidity clusters has been undertaken. METHODS: A nested case-control study was conducted from 2013 to 2017 using multi-source big data. We defined cases as patients with incident PTB, and we matched each case with four event-free controls using propensity score matching (PSM). Comorbidities diagnosed prior to PTB were defined with the International Classification of Diseases-10 (ICD-10). The longitudinal relationships between multimorbidity burden and PTB were analyzed using a generalized estimating equation. The associations between PTB and 30 comorbidities were examined using conditional logistic regression, and the comorbidity clusters were identified using network analysis. RESULTS: A total of 4265 cases and 17,060 controls were enrolled during the study period. A total of 849 (19.91%) cases and 1141 (6.69%) controls were multimorbid before the index date. Having 1, 2, and ≥ 3 comorbidities was associated with an increased risk of PTB (aOR 2.85-5.16). Fourteen out of thirty comorbidities were significantly associated with PTB (aOR 1.28-7.27), and the associations differed by sex and age. Network analysis identified three major clusters, mainly in the respiratory, circulatory, and endocrine/metabolic systems, in PTB cases. CONCLUSIONS: Certain comorbidities involving multiple systems may significantly increase the risk of PTB. Enhanced awareness and surveillance of comorbidity are warranted to ensure early prevention and timely control of PTB.

Macroporous Directed and Interconnected Carbon Architectures Endow Amorphous Silicon Nanodots as Low-Strain and Fast-Charging Anode for Lithium-Ion Batteries.

Fabricating low-strain and fast-charging silicon-carbon composite anodes is highly desired but remains a huge challenge for lithium-ion batteries. Herein, we report a unique silicon-carbon composite fabricated by uniformly dispersing amorphous Si nanodots (SiNDs) in carbon nanospheres (SiNDs/C) that are welded on the wall of the macroporous carbon framework (MPCF) by vertical graphene (VG), labeled as MPCF@VG@SiNDs/C. The high dispersity and amorphous features of ultrasmall SiNDs (~ 0.7 nm), the flexible and directed electron/Li+ transport channels of VG, and the MPCF impart the MPCF@VG@SiNDs/C more lithium storage sites, rapid Li+ transport path, and unique low-strain property during Li+ storage. Consequently, the MPCF@VG@SiNDs/C exhibits high cycle stability (1301.4 mAh g-1 at 1 A g-1 after 1000 cycles without apparent decay) and high rate capacity (910.3 mAh g-1, 20 A g-1) in half cells based on industrial electrode standards. The assembled pouch full cell delivers a high energy density (1694.0 Wh L-1; 602.8 Wh kg-1) and an excellent fast-charging capability (498.5 Wh kg-1, charging for 16.8 min at 3 C). This study opens new possibilities for preparing advanced silicon-carbon composite anodes for practical applications.

Trim21 Regulates the Postnatal Development and Thermogenesis of Brown Adipose Tissue.

Brown adipose tissue undergoes rapid postnatal development to mature and plays a crucial role in thermoregulation and energy expenditure, which protects against cold and obesity. Herein, it is shown that the expression of Trim21 mRNA level of interscapular brown adipose tissue elevates after birth, and peaks at P14 (postnatal day 14). Trim21 depletion severely impairs the maturation of interscapular brown adipose tissue, decreases the expression of a series of thermogenic genes, and reduces energy expenditure. Consistently, the loss of Trim21 also leads to a suppression of white adipose tissue "browning", in response to cold exposure and a ß-adrenergic agonist, CL316,243. In addition, Trim21-/- mice are more prone to high-fat diet-induced obesity compared with the control littermates. Taken together, the study for the first time reveals a critical role of Trim21 in regulating iBAT postnatal development and thermogenesis.

Spin-Polarized Surface Capacitance Effects Enable Fe3 O4 Anode Superior Wide Operation-Temperature Sodium Storage.

Fe3 O4 is widely investigated as an anode for ambient sodium-ion batteries (SIBs), but its electrochemical properties in the wide operation-temperature range have rarely been studied. Herein, the Fe3 O4 nanoparticles, which are well encapsulated by carbon nanolayers, are uniformly dispersed on the graphene basal plane (named Fe3 O4 /C@G) to be used as the anode for SIBs. The existence of graphene can reduce the size of Fe3 O4 /C nanoparticles from 150 to 80 nm and greatly boost charge transport capability of electrode, resulting in an obvious size decrease of superparamagnetic Fe nanoparticles generated from the conversion reaction from 5 to 2 nm. Importantly, the ultra-small superparamagnetic Fe nanoparticles (≈2 nm) can induce a strong spin-polarized surface capacitance effect at operating temperatures ranging from -40 to 60 °C, thus achieving highly efficient Na-ion transport and storage in a wide operation-temperature range. Consequently, the Fe3 O4 /C@G anode shows high capacity, excellent fast-charging capability, and cycling stability ranging from -40 to 60 °C in half/full cells. This work demonstrates the viability of Fe3 O4 as anode for wide operation-temperature SIBs and reveals that spin-polarized surface capacitance effects can promote Na-ion storage over a wide operation temperature range.

Species discrimination of multiple botanical origins of Fritillaria species based on infrared spectroscopy, thin layer chromatography-image analysis and untargeted metabolomics.

BACKGROUND: Fritillaria Bulbus (FB), a precious medicinal herb renowned for its heat-clearing, lung-moistening, cough-relieving and phlegm-eliminating effects. In pursuit of profits, unscrupulous merchants have engaged in the substitution or adulteration of valuable varieties with cheaper alternatives. It is, therefore, urgent to develop effective technical approaches to identify FBs from adulterants. METHODS: This paper employed infrared spectroscopy (IR), thin layer chromatography-image analysis (TLC-IA), and untargeted metabolomics techniques to discriminate ten species of FBs. RESULTS: Five species of FBs were successfully differentiated using mid-infrared spectroscopy. Furthermore, the power of TLC-IA technology allowed the differentiation of five species of FBs and two origins of FCBs (Fritillariae Cirrhosae Bulbus). Remarkably, through the application of untargeted metabolomics technique, the precise discrimination of five species of FBs, as well as three origins of FCBs were accomplished. Moreover, a comprehensive identification of 101 markers that reliably distinguished diverse FBs was achieved through the employment of untargeted metabolomics technique. CONCLUSION: The investigation presented powerful means of detection for assuring the quality control of Fritillaria herbs.

Growth of Vertical Graphene Sheets on Silicon Nanoparticles Well-Dispersed on Graphite Particles for High-Performance Lithium-Ion Battery Anode.

With rapidly increasing demand for high energy density, silicon (Si) is greatly expected to play an important role as the anode material of lithium-ion batteries (LIBs) due to its high specific capacity. However, large volume expansion for silicon during the charging process is still a serious problem influencing its cycling stability. Here, a Si/C composite of vertical graphene sheets/silicon/carbon/graphite (VGSs@Si/C/G) is reported to address the electrochemical stability issues of Si/graphite anodes, which is prepared by adhering Si nanoparticles on graphite particles with chitosan and then in situ growing VGSs by thermal chemical vapor deposition. As a promising anode material, due to the buffering effect of VGSs and tight bonding between Si and graphite particles, the composite delivers a high reversible capacity of 782.2 mAh g-1 after 1000 cycles with an initial coulombic efficiency of 87.2%. Furthermore, the VGSs@Si/C/G shows a diffusion coefficient of two orders higher than that without growing the VGSs. The full battery using VGSs@Si/C/G anode and LiNi0.8 Co0.1 Mn0.1 O2 cathode achieves a high gravimetric energy density of 343.6 Wh kg-1 , a high capacity retention of 91.5% after 500 cycles and an excellent average CE of 99.9%.

Transcriptome-wide map of N6-methyladenosine (m6A) profiling in coronary artery disease (CAD) with clopidogrel resistance.

BACKGROUND: Clopidogrel resistance profoundly increases the risk of major cardiovascular events in coronary artery disease (CAD) patients. Here, we comprehensively analyse global m6A modification alterations in clopidogrel-resistant (CR) and non-CR patients. METHODS: After RNA isolation, the RNA transcriptome expression (lncRNA, circRNA, and mRNA) was analysed via RNA-seq, and m6A peaks were identified by MeRIP-seq. The altered m6A methylation sites on mRNAs, lncRNAs, and circRNAs were identified, and then, GO and KEGG pathway analyses were performed. Through joint analysis with RNA-seq and MeRIP-seq data, differentially expressed mRNAs harbouring differentially methylated sites were identified. The changes in m6A regulator levels and the abundance of differentially methylated sites were measured by RT-PCR. The identification of m6A-modified RNAs was verified by m6A-IP-qPCR. RESULTS: The expression of 2919 hypermethylated and 2519 hypomethylated mRNAs, 192 hypermethylated and 391 hypomethylated lncRNAs, and 375 hypermethylated and 546 hypomethylated circRNAs was shown to be altered in CR patients. The m6A peaks related to CR indicated lower mark density at the CDS region. Functional enrichment analysis revealed that inflammatory pathways and insulin signalling pathways might be involved in the pathological processes underlying CR. The expression of mRNAs (ST5, KDM6B, GLB1L2, and LSM14B), lncRNAs (MSTRG.13776.1 and ENST00000627981.1), and circRNAs (hsa_circ_0070675_CBC1, hsa-circRNA13011-5_CBC1, and hsa-circRNA6406-3_CBC1) was upregulated in CR patients, while the expression of mRNAs (RPS16 and CREG1), lncRNAs (MSTRG.9215.1), and circRNAs (hsa_circ_0082972_CBC1) was downregulated in CR patients. Moreover, m6A regulators (FTO, YTHDF3, and WTAP) were also differentially expressed. An additional combined analysis of gene expression and m6A peaks revealed that the expression of mRNAs (such as ST5, LYPD2, and RPS16 mRNAs) was significantly altered in the CR patients. CONCLUSION: The expression of m6A regulators, the RNA transcriptome, and the m6A landscape was altered in CR patients. These findings reveal epitranscriptomic regulation in CR patients, which might be novel therapeutic targets in future.

Asponchimides A-E: new enantiomeric N-acetyldopamine trimers from Aspongopus chinensis.

Five new racemic N-acetyldopamine (NADA) trimers, asponchimides A-E (1-5), were isolated from Aspongopus chinensis, a prominent traditional Chinese medicinal insect employed for alleviating pain, treating indigestion, and addressing kidney ailments. Compounds 1-5 were successfully resolved by chiral high-performance liquid chromatography (HPLC), yielding five pairs of enantiomers: (+)- and (-)-asponchimides A-E (1a/1b-5a/5b). Their structural identities were discerned by extensive spectroscopic analyses, including high-resolution mass spectrometry (HRMS), ultraviolet-visible (UV-Vis) spectroscopy, infrared (IR) spectroscopy, and nuclear magnetic resonance (NMR), and their absolute configurations were determined by electronic circular dichroism (ECD) calculations. Compounds 1-5 are pioneering instances of NADA trimers featuring a Δ7 double bond. When subjected to a series of bioassays, a majority of the compounds exhibited weak inhibitory activity against nitric oxide (NO) production in LPS-induced RAW 264.7 cells.

Analysis of the Impact of Atmospheric Models on the Orbit Prediction of Space Debris.

Atmospheric drag is an important influencing factor in precise orbit determination and the prediction of low-orbit space debris. It has received widespread attention. Currently, calculating atmospheric drag mainly relies on different atmospheric density models. This experiment was designed to explore the impact of different atmospheric density models on the orbit prediction of space debris. In the experiment, satellite laser ranging data published by the ILRS (International Laser Ranging Service) were used as the basis for the precise orbit determination for space debris. The prediction error of space debris orbits at different orbital heights using different atmospheric density models was used as a criterion to evaluate the impact of atmospheric density models on the determination of space-target orbits. Eight atmospheric density models, DTM78, DTM94, DTM2000, J71, RJ71, JB2006, MSIS86, and NRLMSISE00, were compared in the experiment. The experimental results indicated that the DTM2000 atmospheric density model is best for determining and predicting the orbits of LEO (low-Earth-orbit) targets.

Multi-Fundus Diseases Classification Using Retinal Optical Coherence Tomography Images with Swin Transformer V2.

Fundus diseases cause damage to any part of the retina. Untreated fundus diseases can lead to severe vision loss and even blindness. Analyzing optical coherence tomography (OCT) images using deep learning methods can provide early screening and diagnosis of fundus diseases. In this paper, a deep learning model based on Swin Transformer V2 was proposed to diagnose fundus diseases rapidly and accurately. In this method, calculating self-attention within local windows was used to reduce computational complexity and improve its classification efficiency. Meanwhile, the PolyLoss function was introduced to further improve the model's accuracy, and heat maps were generated to visualize the predictions of the model. Two independent public datasets, OCT 2017 and OCT-C8, were applied to train the model and evaluate its performance, respectively. The results showed that the proposed model achieved an average accuracy of 99.9% on OCT 2017 and 99.5% on OCT-C8, performing well in the automatic classification of multi-fundus diseases using retinal OCT images.

Trim21 depletion alleviates bone loss in osteoporosis via activation of YAP1/ß-catenin signaling.

Despite the diverse roles of tripartite motif (Trim)-containing proteins in the regulation of autophagy, the innate immune response, and cell differentiation, their roles in skeletal diseases are largely unknown. We recently demonstrated that Trim21 plays a crucial role in regulating osteoblast (OB) differentiation in osteosarcoma. However, how Trim21 contributes to skeletal degenerative disorders, including osteoporosis, remains unknown. First, human and mouse bone specimens were evaluated, and the results showed that Trim21 expression was significantly elevated in bone tissues obtained from osteoporosis patients. Next, we found that global knockout of the Trim21 gene (KO, Trim21-/-) resulted in higher bone mass compared to that of the control littermates. We further demonstrated that loss of Trim21 promoted bone formation by enhancing the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) and elevating the activity of OBs; moreover, Trim21 depletion suppressed osteoclast (OC) formation of RAW264.7 cells. In addition, the differentiation of OCs from bone marrow-derived macrophages (BMMs) isolated from Trim21-/- and Ctsk-cre; Trim21f/f mice was largely compromised compared to that of the littermate control mice. Mechanistically, YAP1/ß-catenin signaling was identified and demonstrated to be required for the Trim21-mediated osteogenic differentiation of BMSCs. More importantly, the loss of Trim21 prevented ovariectomy (OVX)- and lipopolysaccharide (LPS)-induced bone loss in vivo by orchestrating the coupling of OBs and OCs through YAP1 signaling. Our current study demonstrated that Trim21 is crucial for regulating OB-mediated bone formation and OC-mediated bone resorption, thereby providing a basis for exploring Trim21 as a novel dual-targeting approach for treating osteoporosis and pathological bone loss.

Characterization of natural peptides in Pheretima by integrating proteogenomics and label-free peptidomics.

Pheretima, also called "earthworms", is a well-known animal-derived traditional Chinese medicine that is extensively used in over 50 Chinese patent medicines (CPMs) in Chinese Pharmacopoeia (2020 edition). However, its zoological origin is unclear, both in the herbal market and CPMs. In this study, a strategy for integrating in-house annotated protein databases constructed from close evolutionary relationship-sourced RNA sequencing data from public archival resources and various sequencing algorithms (restricted search, open search, and de novo) was developed to characterize the phenotype of natural peptides of three major commercial species of Pheretima, including Pheretima aspergillum (PA), Pheretima vulgaris (PV), and Metaphire magna (MM). We identified 10,477 natural peptides in the PA, 7,451 in PV, and 5,896 in MM samples. Five specific signature peptides were screened and then validated using synthetic peptides; these demonstrated robust specificity for the authentication of PA, PV, and MM. Finally, all marker peptides were successfully applied to identify the zoological origins of Brain Heart capsules and Xiaohuoluo pills, revealing the inconsistent Pheretima species used in these CPMs. In conclusion, our integrated strategy could be used for the in-depth characterization of natural peptides of other animal-derived traditional Chinese medicines, especially non-model species with poorly annotated protein databases.

A power quality disturbances classification method based on multi-modal parallel feature extraction.

Power quality disturbance (PQD) is an important problem affecting the safe and stable operation of power system. Traditional single modal methods not only have a large number of parameters, but also usually focus on only one type of feature, resulting in incomplete information about the extracted features, and it is difficult to identify complex and diverse PQD types in modern power systems. In this regard, this paper proposes a multi-modal parallel feature extraction and classification model. The model pays attention to both temporal and spatial features of PQD, which effectively improves classification accuracy. And a lightweight approach is adopted to reduce the number of parameters of the model. The model uses Long Short Term Memory Neural Network (LSTM) to extract the temporal features of one-dimensional temporal modes of PQD. At the same time, a lightweight residual network (LResNet) is designed to extract the spatial features of the two-dimensional image modality of PQD. Then, the two types of features are fused into multi-modal spatio-temporal features (MSTF). Finally, MSTF is input to a Support Vector Machine (SVM) for classification. Simulation results of 20 PQD signals show that the classification accuracy of the multi-modal model proposed in this paper reaches 99.94%, and the parameter quantity is only 0.08 MB. Compared with ResNet18, the accuracy of the proposed method has been improved by 2.55% and the number of parameters has been reduced by 99.25%.

An inulin-type fructan isolated from Serratula chinensis alleviated the dextran sulfate sodium-induced colitis in mice through regulation of intestinal barrier and gut microbiota.

Herein, we aimed to explore the polysaccharide material basis of Serratula chinensis and establish its beneficial effects against colitis. A neutral polysaccharide (SCP) was extracted from S. chinensis in high yield using hot water. The molecular weights were calculated by HPSEC as Mw = 2928 Da, Mn = 2634 Da, and Mw/Mn = 1.11. FT-IR and 1D/2D-NMR spectroscopic analyses confirmed that SCP was an inulin-type fructan with α-D-Glcp-(1 â†’ [1)-ß-D-Fruf-(2]17) linkages. Treatment with SCP (200 or 400 mg/kg) alleviated dextran sulfate sodium (DSS)-induced mouse colitis symptoms, including the loss of body weight, increase of disease activity index score, and shortening of colon length. Histopathological and immunofluorescence assessments revealed that SCP could reduce pathological damage to the colon, restore the number of goblet cells, increase the content of glycoproteins in goblet cells and mucins in crypts, and enhance the expression of tight junction proteins ZO-1 and occludin. In addition, metagenomic sequencing revealed that SCP could improve the dysbiosis of gut microbiomes and act on multiple microbial functions. Moreover, SCP treatment increased the content of colonic acetic acid and butanoic acid. Collectively, these results indicated that SCP could alleviate the DSS-induced colitis in mice through regulation of intestinal barrier and gut microbiota.