Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI

Subjective cognitive decline (SCD) is a preclinical stage of Alzheimer's disease (AD) which occurs even before mild cognitive impairment (MCI). Progressive SCD will convert to MCI with the potential of further evolving to AD. Therefore, early identification of progressive SCD with neuroimaging techniques (e.g., structural MRI) is of great clinical value for early intervention of AD. However, existing MRI-based machine/deep learning methods usually suffer the small-sample-size problem which poses a great challenge to related neuroimaging analysis. The central question we aim to tackle in this paper is how to leverage related domains (e.g., AD/NC) to assist the progression prediction of SCD. Meanwhile, we are concerned about which brain areas are more closely linked to the identification of progressive SCD. To this end, we propose an attention-guided autoencoder model for efficient cross-domain adaptation which facilitates the knowledge transfer from AD to SCD. The proposed model is composed of four key components: 1) a feature encoding module for learning shared subspace representations of different domains, 2) an attention module for automatically locating discriminative brain regions of interest defined in brain atlases, 3) a decoding module for reconstructing the original input, 4) a classification module for identification of brain diseases. Through joint training of these four modules, domain invariant features can be learned. Meanwhile, the brain disease related regions can be highlighted by the attention mechanism. Extensive experiments on the publicly available ADNI dataset and a private CLAS dataset have demonstrated the effectiveness of the proposed method. The proposed model is straightforward to train and test with only 5-10 seconds on CPUs and is suitable for medical tasks with small datasets.Comment: 10 pages, 12 figure

Accurate module induced brain network construction for mild cognitive impairment identification with functional MRI

Introduction Functional brain networks (FBNs) estimated from functional magnetic resonance imaging (fMRI) data has become a potentially useful way for computer-aided diagnosis of neurological disorders, such as mild cognitive impairment (MCI), a prodromal stage of Alzheimer's Disease (AD). Currently, Pearson's correlation (PC) is the most widely-used method for constructing FBNs. Despite its popularity and simplicity, the conventional PC-based method usually results in dense networks where regions-of-interest (ROIs) are densely connected. This is not accordance with the biological prior that ROIs may be sparsely connected in the brain. To address this issue, previous studies proposed to employ a threshold or l_1-regularizer to construct sparse FBNs. However, these methods usually ignore rich topology structures, such as modularity that has been proven to be an important property for improving the information processing ability of the brain. Methods To this end, in this paper, we propose an accurate module induced PC (AM-PC) model to estimate FBNs with a clear modular structure, by including sparse and low-rank constraints on the Laplacian matrix of the network. Based on the property that zero eigenvalues of graph Laplacian matrix indicate the connected components, the proposed method can reduce the rank of the Laplacian matrix to a pre-defined number and obtain FBNs with an accurate number of modules. Results To validate the effectiveness of the proposed method, we use the estimated FBNs to classify subjects with MCI from healthy controls. Experimental results on 143 subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) with resting-state functional MRIs show that the proposed method achieves better classification performance than previous methods

Allele-specific induction of IL-1beta expression by C/EBPbeta and PU.1 contributes to increased tuberculosis susceptibility

Mycobacterium tuberculosis infection is associated with a spectrum of clinical outcomes, from long-term latent infection to different manifestations of progressive disease. Pro-inflammatory pathways, such as those controlled by IL-1beta, have the contrasting potential both to prevent disease by restricting bacterial replication, and to promote disease by inflicting tissue damage. Thus, the ultimate contribution of individual inflammatory pathways to the outcome of M. tuberculosis infection remains ambiguous. In this study, we identified a naturally-occurring polymorphism in the human IL1B promoter region, which alters the association of the C/EBPbeta and PU.1 transcription factors and controls Mtb-induced IL-1beta production. The high-IL-1beta expressing genotype was associated with the development of active tuberculosis, the severity of pulmonary disease and poor treatment outcome in TB patients. Higher IL-1beta expression did not suppress the activity of IFN-gamma-producing T cells, but instead correlated with neutrophil accumulation in the lung. These observations support a specific role for IL-1beta and granulocytic inflammation as a driver of TB disease progression in humans, and suggest novel strategies for the prevention and treatment of tuberculosis

AIDA directly connects sympathetic innervation to adaptive thermogenesis by UCP1

AIDA最早是由林圣彩教授团队首先鉴定和命名的。2007年林圣彩教授团队与孟安明院士团队合作发现AIDA在斑马鱼体轴发育中的功能(Rui, 2007)。2018年，林圣彩教授团队首次发现了AIDA在哺乳动物中的功能，即AIDA介导的内质网降解途径通过降解脂肪合成途径中的关键酶，而限制膳食脂肪在肠道的吸收这一内在抵御肥胖(Luo, 2018)。而本次成果揭示了AIDA在棕色脂肪组织中特定的功能。这些工作将AIDA引入了脂质应激代谢的重要环节，包括脂质吸收和依赖于脂质的产热过程。该论文的共同第一作者为生命科学学院博士生史猛和硕士生黄晓羽，林圣彩教授和林舒勇教授则为共同通讯作者。【Abstract】The sympathetic nervous system–catecholamine–uncoupling protein 1 (UCP1) axis plays an essential role in non-shivering adaptive thermogenesis. However, whether there exists a direct effector that physically connects catecholamine signalling to UCP1 in response to acute cold is unknown. Here we report that outer mitochondrial membrane-located AIDA is phosphorylated at S161 by the catecholamine-activated protein kinase A (PKA). Phosphorylated AIDA translocates to the intermembrane space, where it binds to and activates the uncoupling activity of UCP1 by promoting cysteine oxidation of UCP1.Adipocyte-specific depletion of AIDA abrogates UCP1-dependent thermogenesis, resulting in hypothermia during acute cold exposure. Re-expression of S161A-AIDA, unlike wild-type AIDA, fails to restore the acute cold response in Aida-knockout mice.The PKA–AIDA–UCP1 axis is highly conserved in mammals, including hibernators. Denervation of the sympathetic postganglionic fibres abolishes cold-induced AIDA-dependent thermogenesis. These findings uncover a direct mechanistic link between sympathetic input and UCP1-mediated adaptive thermogenesis.We thank Y. Li, E. Gnaiger, T. Kuwaki, J. R. B. Lighton, E. T. Chouchani and D. Jiang for technical instruction; X. Li and X.-D. Jiang (Core Facility of Biomedical, Xiamen University) for raising the p-S161-AIDA antibody; the Xiamen University Laboratory Animal Center for the mouse in vitro fertilization service and all the other members of S.C.L. laboratory for their technical assistance. This work was supported by grants from the National Key Research and Development Project of China (grant no. 2016YFA0502001) and the National Natural Science Foundation of China (grant nos 31822027, 31871168, 31690101, 91854208 and 82088102), the Fundamental Research Funds for the Central Universities (grant nos 20720190084 and 20720200069), Project ‘111’ sponsored by the State Bureau of Foreign Experts and Ministry of Education of China (grant no. BP2018017), the Youth Innovation Fund of Xiamen (grant no. 3502Z20206028), the Natural Science Foundation of Fujian Province of China (grant no. 2017J01364) and XMU Training Program of Innovation and Entrepreneurship for Undergraduates (grant no. 2019×0666). 该工作得到了厦门大学实验动物中心和生物医学学部仪器平台的重要协助和国家重点研究和发展项目，国家自然科学基金，厦门大学校长基金等的支持

Quantifying Light Absorption of Iron Oxides and Carbonaceous Aerosol in Seasonal Snow across Northern China

In this study, we attempted to quantify light absorption by insoluble light-absorbing particles (ILAPs) such as black carbon (BC), organic carbon (OC) and iron oxides in snow using an optical method directly and compared the results with those obtained using optical and chemical analysis methods cooperatively in previous studies. The mass absorption coefficients (MACs) and absorption Ångström exponents (AAEs) of pure hematite, goethite and fullerene soot were also measured using an integrating sphere/integrating sandwich (ISSW) spectrophotometer in the laboratory. The results indicated that the MACs of pure hematite and goethite are 0.97 ± 0.02 m2·g−1 and 0.43 ± 0.01 m2·g−1 at 550 nm, and their AAEs are 5.53 ± 0.47 and 2.18 ± 0.16 from 550 nm to 750 nm, respectively. The MAC and AAE of fullerene soot are 6.40 ± 0.42 m2·g−1 at 550 nm and 0.54 ± 0.06 from 450 to 750 nm. By using the regionally average AAEs of non-BC components in snow, we evaluated the performance of a directly optical analysis, rather than combination of the optical and chemical methods, in quantifying the light absorption of BC, OC and Fe in snow samples. We found that the directly optical method used to measure the light absorption of BC and OC in Northern China snow has substantially low biases of 6.29% and 4.27% in median comparing to previous method. However, the high biases in estimating light absorption of Fe (33.01%) may be associated with the significant underestimation of the AAE of Fe

SYNTHESIS AND CHARACTERIZATION OF LiFePO4/C PREPARED VIA A SOL–GEL METHOD

Carbon-coated lithium ion phosphate was synthesized from a gel precursor with ferric iron and a carbon source of organic chelating agent via a sol–gel method. The dependence of the microstructure and electrochemical performance of the synthesized LiFePO4/C on the pH value of the precursor solution during gel formation and the sintering time was investigated. The obtained LiFePO4/C particles were characterized by X-ray diffraction, field-emission scanning electron microscopy, and element analysis. The results show that the pH value has little effect on the phase purity. At a sintering temperature of 700°C, the discharge capacity of LiFePO4/C under 0.1 C (1 C = 170 mA/g) regime decreased from 152.8 to 62.5 mAh/g with decreasing the sintering time from 12 h to 8 h. Appropriate sintering time can lead to well-crystallized LiFePO4/C, which improves the electrochemical performance.LiFePO4/C, sol–gel, pH, sintering time

Deep-Learning-Based Automatic Extraction of Aquatic Vegetation from Sentinel-2 Images—A Case Study of Lake Honghu

Aquatic vegetation is an important component of aquatic ecosystems; therefore, the classification and mapping of aquatic vegetation is an important aspect of lake management. Currently, the decision tree (DT) classification method based on spectral indices has been widely used in the extraction of aquatic vegetation data, but the disadvantage of this method is that it is difficult to fix the threshold value, which, in turn, affects the automatic classification effect. In this study, Sentinel-2 MSI data were used to produce a sample set (about 930 samples) of aquatic vegetation in four inland lakes (Lake Taihu, Lake Caohai, Lake Honghu, and Lake Dongtinghu) using the visual interpretation method, including emergent, floating-leaved, and submerged vegetation. Based on this sample set, a DL model (Res-U-Net) was used to train an automatic aquatic vegetation extraction model. The DL model achieved a higher overall accuracy, relevant error, and kappa coefficient (90%, 8.18%, and 0.86, respectively) compared to the DT method (79%, 23.07%, and 0.77) and random forest (78%,10.62% and 0.77) when utilizing visual interpretation results as the ground truth. When utilizing measured point data as the ground truth, the DL model exhibited accuracies of 59%, 78%, and 91% for submerged, floating-leaved, and emergent vegetation, respectively. In addition, the model still maintains good recognition in the presence of clouds with the influence of water bloom. When applying the model to Lake Honghu from January 2017 to October 2023, the obtained temporal variation patterns in the aquatic vegetation were consistent with other studies. The study in this paper shows that the proposed DL model has good application potential for extracting aquatic vegetation data

Activation of dorsal horn cannabinoid CB2 receptor suppresses the expression of P2Y12 and P2Y13 receptors in neuropathic pain rats

Abstract Background More evidence suggests that dorsal spinal cord microglia is an important site contributing to CB2 receptor-mediated analgesia. The upregulation of P2Y12 and P2Y13 purinoceptors in spinal dorsal horn microglia is involved in the development of pain behavior caused by peripheral nerve injury. However, it is not known whether the expression of P2Y12 and P2Y13 receptors at spinal dorsal horn will be influenced after CB2 receptor activation in neuropathic pain rats. Methods Chronic constriction injury (CCI) and intrathecal ADPbetaS injection were performed in rats to induce neuropathic pain. The paw withdrawal latency (PWL) was used to evaluate thermal hyperalgesia in neuropathic rats. The expression of P2Y12 and P2Y13 receptors, p-p38MAPK, and NF-kappaBp65 was detected with RT-PCR and western blotting analysis. Results Treatment with AM1241 produces a pronounced inhibition of CCI-induced thermal hyperalgesia and significantly inhibited the increased expression of P2Y12 and P2Y13 receptors at the mRNA and protein levels, which open up the possibility that P2Y12 and P2Y13 receptor expression are downregulated by CB2 receptor agonist AM1241 in CCI rats. Western blot analysis demonstrated that AM1241 reduced the elevated expression of p-p38MAPK and NF-κBp65 in the dorsal spinal cord induced by CCI. After administration with either SB203580 (p38MAPK inhibitor) or PDTC (NF-kappaB inhibitor), the levels of P2Y13 receptor expression in the dorsal spinal cord were lower than those in the CCI group. However, in CCI rats, the increased expression of P2Y12 receptor was prevented by intrathecal administration of PDTC but not by SB203580. In addition, minocycline significantly decreased the increased expression of P2Y12 and P2Y13 receptors. The similar results can be observed in ADPbetaS-treated rats. Intrathecal injection of ADPbataS causes thermal hyperalgesia and increased expression of P2Y12 and P2Y13 receptors in the dorsal spinal cord of naive rats. Moreover, intrathecal injection of AM1241 alleviates pain response and reduces the elevated expression of P2Y12 and P2Y13 receptors, p-p38MAPK, and NF-κBp65 in the dorsal spinal cord of ADPbetaS-treated rats. Intrathecal injection of SB203580 significantly inhibited the ADPbetaS-induced P2Y13 receptor expression, without affecting P2Y12 receptor expression. However, treatment with either SB203580 or PDTC effectively inhibited P2Y13 receptor expression compared to ADPbetaS-treated rats. Conclusions In CCI- and ADPbetaS-treated rats, AM1241 pretreatment could efficiently activate CB2 receptor, while inhibiting p38MAPK and NF-kappaB activation in the dorsal spinal cord. CB2 receptor stimulation decreased P2Y13 receptor expression via p38MAPK/NF-kappaB signaling. On the other hand, CB2 receptor activation decreased P2Y12 receptor expression via p38MAPK-independent NF-kappaB signaling pathway

CDK12 loss inhibits cell proliferation by regulating TBK1 in non-small cell lung cancer cells

Lung cancer is one of the most common malignant tumors and has a poor prognosis and a low survival rate. Traditional treatments, such as radiotherapy and chemotherapy, still face some challenges because of high drug resistance and toxicity. Therefore, it is necessary to discover a new kind of targeted drug with low toxicity and high efficiency. CDK12 is a cell cycle-dependent kinase whose main function is to activate RNA polymerase II (RNAPII) and promote the transcriptional extension of RNA. However, the role and molecular mechanism of CDK12 in lung cancer are still unclear.In this study, the mutation and RNA-Seq data of CDK12 in lung adenocarcinoma and squamous cell carcinoma were downloaded from The Cancer Genome Atlas (TCGA) database and analyzed with the custom scripts. Cell proliferation was evaluated by Cell Counting Kit-8 (CCK-8) and cell colony formation assays. A subcutaneous tumor experiment in nude mice was used to examine the effects of CDK12 knockdown on the in vivo tumor growth of NSCLC cells. The cell cycle distribution and the apoptosis rate of lung cancer cells were assessed by flow cytometry. Regulation of TANK-binding kinase 1 (TBK1) by CDK12 was evaluated by quantitative PCR, immunoprecipitation and Western blot analysis.In this study we have analyzed the mutation and expression data of The Cancer Genome Atlas (TCGA) database and found that CDK12 is highly expressed in lung cancer tissues. Clinical correlation analysis showed that high expression of CDK12 in NSCLC reduces patient survival, but its high expression is only related to early tumor progression and has no significant correlation with late tumor progression and metastasis. Furthermore, we present evidence that CDK12 depletion in lung cancer cell lines not only leads to the inhibition of cell growth and induces apoptosis but also inhibits tumor growth of NSCLC cells in vivo. CDK12 positively regulates the expression of the oncogene TBK1 in lung cancer cells. These results revealed that CDK12 affects the progression of non-small cell lung cancer through positive regulation of TBK1 expression, suggesting that CDK12 might be a potential molecular target for the treatment of non-small cell lung cancer

Gallic acid ameliorates colitis by trapping deleterious metabolite ammonia and improving gut microbiota dysbiosis

ABSTRACTGut microbiota dysbiosis is causally related to inflammatory bowel disease (IBD), and increased levels of the gut metabolite ammonia have been proposed to contribute to IBD development. In this study, we aimed to clarify the anti-colitis mechanism of gallic acid (GA) based on its ability to trap the deleterious metabolite ammonia and improve gut microbiota. Aminated product was detected in the fecal samples of mice after oral gavage of gallic acid (GA) and identified as 4-amino-substituted gallic acid (4-NH2-GA), thus confirming the ability of GA to trap ammonia in vivo. Then, we compared the beneficial effects of GA and 4-NH2-GA on dextran sulfate sodium (DSS)-induced colitis mouse and found that both compounds managed to alleviate colitis phenotypes, indicating ammonia trapping had no adverse effect on the original anti-colitis activity of GA. In addition, both GA and 4-NH2-GA improved the gut microbiota dysbiosis induced by DSS, and fecal microbiota transplantation was subsequently performed, which further revealed that the gut microbiota mediated the anti-colitis activity of both GA and 4-NH2-GA. In summary, this study clarified that GA alleviated colitis by targeting both the symptoms and root causes: it directly reduced the deleterious metabolite ammonia by forming aminated metabolites without compromising the original anti-colitis activity, and it also improved gut microbiota dysbiosis, which in turn contributed to the alleviation of colitis. Since the GA structure is presented in various polyphenols as a common building block, the novel anti-colitis mechanism obtained from GA may also apply to other complex polyphenols.IMPORTANCEThe dysbiosis of the gut microbiota and its metabolism directly cause the emergence of IBD. In this study, we aimed to clarify the anti-colitis mechanism of GA in sight of gut microbiota and its metabolite ammonia. We discovered that GA directly captured and reduced the harmful metabolite ammonia in vivo to produce the aminated metabolite 4-NH2-GA, while the amination of GA had no adverse effect on its initial anti-colitis activity. In addition, both GA and its aminated metabolite improved the gut microbiota in colitis mice, and the modified gut microbiota, in turn, helped to relieve colitis. Since the GA structure is presented in diverse polyphenols as a common building block, the novel anti-colitis mechanism targeting the symptoms and root causes might also apply to other complex polyphenols