YY1-induced upregulation of LncRNA-ARAP1-AS2 and ARAP1 promotes diabetic kidney fibrosis via aberrant glycolysis associated with EGFR/PKM2/HIF-1α pathway.

Objectives: Dimeric pyruvate kinase (PK) M2 (PKM2) plays an important role in promoting the accumulation of hypoxia-inducible factor (HIF)-1α, mediating aberrant glycolysis and inducing fibrosis in diabetic kidney disease (DKD). The aim of this work was to dissect a novel regulatory mechanism of Yin and Yang 1 (YY1) on lncRNA-ARAP1-AS2/ARAP1 to regulate EGFR/PKM2/HIF-1α pathway and glycolysis in DKD. Materials and methods: We used adeno-associated virus (AAV)-ARAP1 shRNA to knocked down ARAP1 in diabetic mice and overexpressed or knocked down YY1, ARAP1-AS2 and ARAP1 expression in human glomerular mesangial cells. Gene levels were assessed by Western blotting, RT-qPCR, immunofluorescence staining and immunohistochemistry. Molecular interactions were determined by RNA pull-down, co-immunoprecipitation, ubiquitination assay and dual-luciferase reporter analysis. Results: YY1, ARAP1-AS2, ARAP1, HIF-1α, glycolysis and fibrosis genes expressions were upregulated and ARAP1 knockdown could inhibit dimeric PKM2 expression and partly restore tetrameric PKM2 formation, while downregulate HIF-1α accumulation and aberrant glycolysis and fibrosis in in-vivo and in-vitro DKD models. ARAP1 knockdown attenuates renal injury and renal dysfunction in diabetic mice. ARAP1 maintains EGFR overactivation in-vivo and in-vitro DKD models. Mechanistically, YY1 transcriptionally upregulates ARAP1-AS2 and indirectly regulates ARAP1 and subsequently promotes EGFR activation, HIF-1α accumulation and aberrant glycolysis and fibrosis. Conclusion: Our results first highlight the role of the novel regulatory mechanism of YY1 on ARAP1-AS2 and ARAP1 in promoting aberrant glycolysis and fibrosis by EGFR/PKM2/HIF-1α pathway in DKD and provide potential therapeutic strategies for DKD treatments.

Leaching characteristics and pollution risk assessment of potentially harmful elements from coal gangue exposed to weathering for different periods of time.

To explore the leaching behavior and potential degree of pollution that can result from the backfilling of goafs with different types of coal gangue (CG), fresh CG from the Hongqi Coal Mine goaf and surface CG (weathered for 1 year) were selected as the research objects in this study. A series of leaching experiments were carried out using the Ordovician limestone karst waters of the mining areas as the soaking solution. A comparative study on the dissolution characteristics of Fe3+, Mn2+, and SO42- and on the traditional water quality parameters of the two types of CG was conducted. The results showed that the soaked, weathered CG displayed a higher ion dissolution value than fresh CG. The ratio of each ion was as follows: Fe3+ was 1, Mn2+ was 2.86 ~ 68.18, and SO42- was 1.34 ~ 2.09. Over time, the ion concentration of water samples that initially contained high ion concentration values showed a decreasing trend after CG was soaked in these waters, but the values were still in the range of high ion release concentrations. The pH and oxidation‒reduction potential (ORP) values of the leachate of both CG types indicated that the leachates were weakly alkaline and weakly oxidizing, and the overall change in total dissolved solids (TDS) was small and consistent with the SO42- trend. SO42- in the leachate of the weathered CG showed a more significant correlation with the pH and TDS of the soaking solution, and it was the major pollutant. According to the geoaccumulation index evaluation, weathered CG had higher pollution potential than fresh CG. Fe3+ presented a slight and moderate risk for contamination.

Deep learning-based fast volumetric imaging using kV and MV projection images for lung cancer radiotherapy: A feasibility study.

PURPOSE: The long acquisition time of CBCT discourages repeat verification imaging, therefore increasing treatment uncertainty. In this study, we present a fast volumetric imaging method for lung cancer radiation therapy using an orthogonal 2D kV/MV image pair. METHODS: The proposed model is a combination of 2D and 3D networks. The proposed model consists of five major parts: (1) kV and MV feature extractors are used to extract deep features from the perpendicular kV and MV projections. (2) The feature-matching step is used to re-align the feature maps to their projection angle in a Cartesian coordinate system. By using a residual module, the feature map can focus more on the difference between the estimated and ground truth images. (3) In addition, the feature map is downsized to include more global semantic information for the 3D estimation, which is useful to reduce inhomogeneity. By using convolution-based reweighting, the model is able to further increase the uniformity of image. (4) To reduce the blurry noise of generated 3D volume, the Laplacian latent space loss calculated via the feature map that is extracted via specifically-learned Gaussian kernel is used to supervise the network. (5) Finally, the 3D volume is derived from the trained model. We conducted a proof-of-concept study using 50 patients with lung cancer. An orthogonal kV/MV pair was generated by ray tracing through CT of each phase in a 4D CT scan. Orthogonal kV/MV pairs from nine respiratory phases were used to train this patient-specific model while the kV/MV pair of the remaining phase was held for model testing. RESULTS: The results are based on simulation data and phantom results from a real Linac system. The mean absolute error (MAE) values achieved by our method were 57.5 HU and 77.4 HU within body and tumor region-of-interest (ROI), respectively. The mean achieved peak-signal-to-noise ratios (PSNR) were 27.6 dB and 19.2 dB within the body and tumor ROI, respectively. The achieved mean normalized cross correlation (NCC) values were 0.97 and 0.94 within the body and tumor ROI, respectively. A phantom study demonstrated that the proposed method can accurately re-position the phantom after shift. It is also shown that the proposed method using both kV and MV is superior to current method using kV or MV only in image quality. CONCLUSION: These results demonstrate the feasibility and accuracy of our proposed fast volumetric imaging method from an orthogonal kV/MV pair, which provides a potential solution for daily treatment setup and verification of patients receiving radiation therapy for lung cancer.

Oxygen stress on age-stage, two-sex life tables and transcriptomic response of diamondback moth (Plutella xylostella).

Elucidating the genetic basis of local adaption is one of the important tasks in evolutionary biology. The Qinghai-Tibet Plateau has the highest biodiversity for an extreme environment worldwide, and provides an ideal natural laboratory to study adaptive evolution. The diamondback moth (DBM), Plutella xylostella, is one of the most devastating pests of the global Brassica industry. A highly heterozygous genome of this pest has facilitated its adaptation to a variety of complex environments, and so provides an ideal model to study fast adaptation. We conducted a pilot study combining RNA-seq with an age-stage, two-sex life table to study the effects of oxygen deprivation on DBM. The developmental periods of all instars were significantly shorter in the hypoxic environment. We compared the transcriptomes of DBM from Fuzhou, Fujian (low-altitude) and Lhasa, Tibet (high-altitude) under hypoxia treatment in a hypoxic chamber. Some DEGs are enriched in pathways associated with DNA replication, such as DNA repair, nucleotide excision repair, base excision repair, mismatch repair and homologous recombination. The pathways with significant changes were associated with metabolism process and cell development. Thus, we assumed that insects could adapt to different environments by regulating their metabolism. Our findings indicated that although adaptive mechanisms to hypoxia in different DBM strains could be similar, DBM individuals from Tibet had superior tolerance to hypoxia compared with those of Fuzhou. Local adaptation of the Tibetan colony was assumed to be responsible for this difference. Our research suggests novel mechanisms of insect responses to hypoxia stress.

Feasibility study of hybrid inverse planning with transmission beams and single-energy spread-out Bragg peaks for proton FLASH radiotherapy.

BACKGROUND: Ultra-high dose rate (FLASH) proton planning with only transmission beams (TBs) has limitations in normal tissue sparing. The single-energy spread-out Bragg peaks (SESOBPs) of the FLASH dose rate have been demonstrated feasible for proton FLASH planning. PURPOSE: To investigate the feasibility of combining TBs and SESOBPs for proton FLASH treatment. METHODS: A hybrid inverse optimization method was developed to combine the TBs and SESOBPs (TB-SESOBP) for FLASH planning. The SESOBPs were generated field-by-field from spreading out the BPs by pre-designed general bar ridge filters (RFs) and placed at the central target by range shifters (RSs) to obtain a uniform dose within the target. The SESOBPs and TBs were fully placed field-by-field allowing automatic spot selection and weighting in the optimization process. A spot reduction strategy was conducted in the optimization process to push up the minimum MU/spot assuring the plan deliverability at beam current of 165 nA. The TB-SESOBP plans were validated in comparison with the TB only (TB-only) plans and the plans with the combination of TBs and BPs (TB-BP plans) regarding 3D dose and dose rate (dose-averaged dose rate) distributions for five lung cases. The FLASH dose rate coverage (V40Gy/s ) was evaluated in the structure volume receiving >10% of the prescription dose. RESULTS: Compared to the TB-only plans, the mean spinal cord D1.2cc drastically reduced by 41% (P < 0.05), the mean lung V7Gy and V7.4Gy moderately reduced by up to 17% (P < 0.05) and the target dose homogeneity slightly increased in the TB-SESOBP plans. Comparable dose homogeneity was achieved in both TB-SESOBP and TB-BP plans. Besides, prominent improvements were achieved in lung sparing for the cases of relatively large targets by the TB-SESOBP plans compared to the TB-BP plans. The targets and the skin were fully covered with the FLASH dose rate in all three plans. For the OARs, V40Gy/s = 100% was achieved by the TB-only plans while V40Gy/s > 85% was obtained by the other two plans. CONCLUSIONS: We have demonstrated that the hybrid TB-SESOBP planning was feasible to achieve FLASH dose rate for proton therapy. With pre-designed general bar RFs, the hybrid TB-SESOBP planning could be implemented for proton adaptive FLASH radiotherapy. As an alternative FLASH planning approach to TB-only planning, the hybrid TB-SESOBP planning has great potential in dosimetrically improving OAR sparing while maintaining high target dose homogeneity. This article is protected by copyright. All rights reserved.

Establishment and verification of a digital PCR assay for the detection of CK19 expression in quantitative analysis of circulating tumor cell.

The objective of this study was to establish and verify a digital PCR assay for the detection of CK19 gene expression, and to use it to detect circulating tumor cells (CTC) by taking advantages of its ultra-high sensitivity and absolute quantitation. Firstly, the primers and probes were designed according to the mRNA sequence of CK19 gene, and housekeeping gene ABL1 was used as the internal control. The best candidate was screened by human breast cancer MCF7 cells and healthy human leukocytes from 13 sets of primer and probes and verified by direct sequencing. Secondly, after the reaction conditions of the selected primers and probes were optimized, limit of blank (LOB) analysis were performed with different concentrations of cDNAs as templates from healthy human leukocytes. The results revealed the LOB of CK19 with ABL1 copy numbers of 20,000, 15,000, 10,000, 5000 and 2500 were 9.24, 8.93, 3.12, 3.17 and 2.53 copies, respectively. Thirdly, the different concentrations of cDNAs from MCF7 cells and healthy human leukocytes were premixed and used in the limit of detection (LOD) analysis, which showed that the CK19 gene could be effectively detected at the concentration ratio of 50%, 10%, 5%, 1%, 0.5% and 0.1%, and the linear R2 value was 0.9998. Finally, the preliminary results of digital PCR in clinical samples indicated that CK19 copy numbers were higher in advanced breast cancer patients than healthy controls. The above results demonstrated the advantages of our CK19 digital PCR assay in sensitivity, specificity, and accurate quantification. If verified further, the assay is expected to play significant roles in the quantitative analysis of CTC in breast cancer with a good application prospect.

Isoelectric point barcode and similarity analysis with the earth mover's distance for identification of species origin of raw meat.

In this work, by combining the microcolumn isoelectric focusing (mIEF) and similarity analysis with the earth mover's distance (EMD) metric, we proposed the concept of isoelectric point (pI) barcode for the identification of species origin of raw meat. At first, we used the mIEF to analyze 14 meat species, including 8 species of livestock and 6 species of poultry, to generate 140 electropherograms of myoglobin/hemoglobin (Mb/Hb) markers. Secondly, we binarized the electropherograms and converted them into the pI barcodes that only showed the major Mb/Hb bands for the EMD analysis. Thirdly, we efficiently developed the barcode database of 14 meat species and successfully used the EMD method to identify 9 meat products thanks to the high throughput of mIEF and the simplified format of the barcode for similarity analysis. The developed method had the merits of facility, rapidity and low cost. The developed concept and method had evident potential to the facile identification of meat species.

Microbiota alteration of Chinese young male adults with high-status negative cognitive processing bias.

Introduction: Evidence suggests that negative cognitive processing bias (NCPB) is a significant risk factor for depression. The microbiota-gut-brain axis has been proven to be a contributing factor to cognitive health and disease. However, the connection between microbiota and NCPB remains unknown. This study mainly sought to explore the key microbiota involved in NCPB and the possible pathways through which NCPB affects depressive symptoms. Methods: Data in our studies were collected from 735 Chinese young adults through a cross-sectional survey. Fecal samples were collected from 35 young adults with different levels of NCPB (18 individuals were recruited as the high-status NCPB group, and another 17 individuals were matched as the low-status NCPB group) and 60 with different degrees of depressive symptoms (27 individuals were recruited into the depressive symptom group, as D group, and 33 individuals were matched into the control group, as C group) and analyzed by the 16S ribosomal RNA sequencing technique. Results: As a result, the level of NCPB correlated with the degree of depressive symptoms as well as anxiety symptoms and sleep quality (p < 0.01). The ß-diversity of microbiota in young adults was proven to be significantly different between the high-status NCPB and the low-status NCPB groups. There were several significantly increased bacteria taxa, including Dorea, Christensenellaceae, Christe -senellaceae_R_7_group, Ruminococcaceae_NK4A214_group, Eggerthellaceae, Family-XIII, Family_XIII_AD3011_group, Faecalibaculum, and Oscillibacter. They were mainly involved in pathways including short-chain fatty acid (SCFA) metabolism. Among these variable bacteria taxa, Faecalibaculum was found associated with both NCPB and depressive symptoms. Furthermore, five pathways turned out to be significantly altered in both the high-status NCPB group and the depressive symptom group, including butanoate metabolism, glyoxylate and dicarboxylate metabolism, propanoate metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis, valine, leucine, and isoleucine degradation. These pathways were related to SCFA metabolism. Discussion: Fecal microbiota is altered in Chinese young male adults with high status NCPB and may be involved in the biochemical progress that influences depressive symptoms.

Association between Serum Iron, Blood Lead, Cadmium, Mercury, Selenium, Manganese and Low Cognitive Performance in Old Adults from National Health and Nutrition Examination Survey (NHANES): A Cross-Sectional Study.

Cognitive decline is a public health problem for the world's aging population. This study was to evaluate the relationships between serum iron, blood lead, cadmium, mercury, selenium, and manganese and cognitive decline in elderly Americans. Data of this cross-sectional study was extracted from the National Health and Nutritional Examination Survey (NHANES 2011-2014). Cognitive performance was measured by the consortium to establish a registry for Alzheimer's disease (CERAD), Animal fluency, and digit symbol substitution test (DSST) tests. Weighted univariable and multivariate logistic regression analyses were used to assess the associations between six trace elements and low cognitive performance, with odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses based on diabetes and hypertension history were further assess the associations. A total of 2,002 adults over 60 years old were included. After adjusting covariates, elevated serum iron levels were associated with the decreased risk of low cognitive performance (OR=0.995, 95%CI: 0.990-0.999), as well as in the elderly without diabetes history (OR=0.992, 95%CI: 0.988-0.997) and with hypertension history (OR=0.993, 95%CI: 0.988-0.997) in the Animal Fluency test. High blood cadmium and blood manganese levels were associated with the odds of low cognitive performance in old adults with diabetes (OR=2.900, 95%CI: 1.311-6.417) and hypertension (OR=1.037, 95%CI: 1.009-1.066) history, respectively. In the DSST test, high blood lead levels were related to the odds of low cognitive performance (OR=1.102, 95%CI: 1.019-1.192), as well as in the elderly without diabetes (OR=1.126, 95%CI: 1.026-1.235) and hypertension (OR=1.121, 95%CI: 1.002-1.255) history. Elevated blood cadmium levels were connected with low cognitive performance in diabetic (OR=3.177, 95%CI: 1.323-7.27) and hypertensive (OR=1.896, 95%CI: 1.056-3.403) old people. High blood selenium levels were linked to the decreased risk of low cognitive performance in all the elderly (OR=0.987, 95%CI: 0.981-0.993). Appropriate iron, selenium supplementation and iron-, selenium-rich foods intake, while reducing exposure to lead, cadmium and manganese may be beneficial for cognitive function in the elderly.

Inter-fraction deformable image registration using unsupervised deep learning for CBCT-guided abdominal radiotherapy.

CBCTs in image-guided radiotherapy provide crucial anatomy information for patient setup and plan evaluation. Longitudinal CBCT image registration could quantify the inter-fractional anatomic changes, e.g. tumor shrinkage, daily OAR variation throughout the course of treatment. The purpose of this study is to propose an unsupervised deep learning based CBCT-CBCT deformable image registration which enables quantitative anatomic variation analysis. The proposed deformable registration workflow consists of training and inference stages that share the same feed-forward path through a spatial transformation-based network (STN). The STN consists of a global generative adversarial network (GlobalGAN) and a local GAN (LocalGAN) to predict the coarse- and fine-scale motions, respectively. The network was trained by minimizing the image similarity loss and the deformable vector field (DVF) regularization loss without the supervision of ground truth DVFs. During the inference stage, patches of local DVF were predicted by the trained LocalGAN and fused to form a whole-image DVF. The local whole-image DVF was subsequently combined with the GlobalGAN generated DVF to obtain final DVF. The proposed method was evaluated using 100 fractional CBCTs from 20 abdominal cancer patients in the experiments and 105 fractional CBCTs from a cohort of 21 different abdominal cancer patients in a holdout test. Qualitatively, the registration results show good alignment between the deformed CBCT images and the target CBCT image. Quantitatively, the average target registration error (TRE) calculated on the fiducial markers and manually identified landmarks was 1.91±1.18 mm. The average mean absolute error (MAE), normalized cross correlation (NCC) between the deformed CBCT and target CBCT were 33.42±7.48 HU, 0.94±0.04, respectively. In summary, an unsupervised deep learning-based CBCT-CBCT registration method is proposed and its feasibility and performance in fractionated image-guided radiotherapy is investigated. This promising registration method could provide fast and accurate longitudinal CBCT alignment to facilitate inter-fractional anatomic changes analysis and prediction.

Rhodiola rosea polysaccharides-based nanoparticles loaded with DOX boosts chemo-immunotherapy for triple-negative breast cancer by re-educating tumor-associated macrophages.

Efficient encapsulation and tumor targeting ability are the key issues for hydrophobic drugs delivery vectors in cancer therapy. In the current study, Rhodiola rosea polysaccharides (RHPs) serve as an immunoactive vector for drug delivery with tumor-associated macrophages (TAMs) modulating ability and typical structural characteristics. Firstly, Folic acid (FA) and stearic acid (SA) were chemically modified to the backbone of RHPs to obtain the self-assemble and tumor targeting behaviors. Then, the hydrophobic drug (Doxorubicin, DOX) was encapsulated in the RHPs derivatives (FA-RHPs-SA) with high efficiency. Moreover, the optimal formed DOX@FA-RHPs-SA were around 196 nm with uniform size distribution and a pH-sensitive release capacity in different acidic conditions. In vitro experiments demonstrated that DOX@FA-RHPs-SA could efficiently uptake by tumor cells. Furthermore, the modulatory function of the FA-RHPs-SA on RAW264.7 macrophages was also demonstrated in the transition from M0 to M1 phenotypes, and the M2 differentiated into the M1. Finally, in vivo antitumor study revealed that the inhibitory effect of DOX@FA-RHPs-SA was superior to the DOX monotherapy treatment, and the new preparation worked synergistically by inducing tumor cell apoptosis and modulating immune cell function. In summary, this study describes a RHPs-based hydrophobic delivery vector and achieved an additional helpful antitumor effect by modulating TAMs.

Automatic segmentation of neurovascular bundle on mri using deep learning based topological modulated network.

PURPOSE: Radiation damage on neurovascular bundles (NVBs) may be the cause of sexual dysfunction after radiotherapy for prostate cancer. However, it is challenging to delineate NVBs as organ-at-risks from planning CTs during radiotherapy. Recently, the integration of MR into radiotherapy made NVBs contour delineating possible. In this study, we aim to develop an MRI-based deep learning method for automatic NVB segmentation. METHODS: The proposed method, named topological modulated network, consists of three subnetworks, that is, a focal modulation, a hierarchical block and a topological fully convolutional network (FCN). The focal modulation is used to derive the location and bounds of left and right NVBs', namely the candidate volume-of-interests (VOIs). The hierarchical block aims to highlight the NVB boundaries information on derived feature map. The topological FCN then segments the NVBs inside the VOIs by considering the topological consistency nature of the vascular delineating. Based on the location information of candidate VOIs, the segmentations of NVBs can then be brought back to the input MRI's coordinate system. RESULTS: A five-fold cross-validation study was performed on 60 patient cases to evaluate the performance of the proposed method. The segmented results were compared with manual contours. The Dice similarity coefficient (DSC) and 95th percentile Hausdorff distance (HD95 ) are (left NVB) 0.81 ± 0.10, 1.49 ± 0.88 mm, and (right NVB) 0.80 ± 0.15, 1.54 ± 1.22 mm, respectively. CONCLUSION: We proposed a novel deep learning-based segmentation method for NVBs on pelvic MR images. The good segmentation agreement of our method with the manually drawn ground truth contours supports the feasibility of the proposed method, which can be potentially used to spare NVBs during proton and photon radiotherapy and thereby improve the quality of life for prostate cancer patients.

Direct Electrochemical Leaching Method for High-Purity Lithium Recovery from Spent Lithium Batteries.

Recovering lithium from lithium batteries (LIBs) is a promising approach for sustainable ternary lithium battery (T-LIB) development. Current lithium recovery methods from spent T-LIBs mainly concentrated on chemical leaching methods. However, chemical leaching relying on the additional acid seriously threatens the global environment and nonselective leaching also leads to low Li recovery purity. Here, we first reported a direct electro-oxidation method for lithium leaching from spent T-LIBs (Li0.8Ni0.6Co0.2Mn0.2O2); 95.02% of Li in the spent T-LIBs was leached under 2.5 V in 3 h. Meanwhile, nearly 100% Li recovery purity was also achieved, attributed to no other metal leaching and additional agents. We also clarified the relationship between lithium leaching and other metals during the electro-oxidation of spent T-LIBs. Under the optimized voltage, Ni and O maintain the electroneutrality in the structure assisting Li leaching, while Co and Mn maintain their valence states. A direct electro-oxidation Li leaching approach achieves high Li recovery purity and meanwhile overcomes the secondary pollution problem.

Effects of L-arginine on Nitric Oxide Synthesis and Larval Metamorphosis of Mytilus coruscus.

To investigate the regulatory functions of L-arginine and nitric oxide (NO) on Mytilus coruscus metamorphosis, M. coruscus larvae were exposed to an inhibitor of nitric oxide synthase (NOS), aminoguanidine hemisulfate (AGH), and a substrate for NO synthesis, L-arginine. We observed that NO levels showed a significant increase, and this trend continued with L-arginine treatment. When NOS activity was inhibited, the larvae could not synthesize NO, and metamorphosis was not inhibited even in the presence of L-arginine. On transfecting pediveliger larvae with NOS siRNA followed by L-arginine exposure, we found that the larvae did not produce NO and that the larval metamorphosis rate was significantly increased, suggesting that L-arginine regulates M. coruscus larval metamorphosis by promoting NO synthesis. Our findings improve our understanding of the effects of marine environmental factors on larval metamorphosis of mollusks.

Landmark tracking in liver US images using cascade convolutional neural networks with long short-term memory.

Accurate tracking of anatomic landmarks is critical for motion management in liver radiation therapy. Ultrasound (US) is a safe, low-cost technology that is broadly available and offer real-time imaging capability. This study proposed a deep learning-based tracking method for the US image-guided radiation therapy. The proposed cascade deep learning model is composed of an attention network, a mask region-based convolutional neural network (mask R-CNN), and a long short-term memory (LSTM) network. The attention network learns a mapping from an US image to a suspected area of landmark motion in order to reduce the search region. The mask R-CNN then produces multiple region-of-interest proposals in the reduced region and identifies the proposed landmark via three network heads: bounding box regression, proposal classification, and landmark segmentation. The LSTM network models the temporal relationship among the successive image frames for bounding box regression and proposal classification. To consolidate the final proposal, a selection method is designed according to the similarities between sequential frames. The proposed method was tested on the liver US tracking datasets used in the medical image computing and computer assisted interventions 2015 challenges, where the landmarks were annotated by three experienced observers to obtain their mean positions. Five-fold cross validation on the 24 given US sequences with ground truths shows that the mean tracking error for all landmarks is 0.65 ± 0.56 mm, and the errors of all landmarks are within 2 mm. We further tested the proposed model on 69 landmarks from the testing dataset that have the similar image pattern with the training pattern, resulting in a mean tracking error of 0.94 ± 0.83 mm. The proposed deep-learning model was implemented on a graphics processing unit (GPU), tracking 47-81 frames s-1. Our experimental results have demonstrated the feasibility and accuracy of our proposed method in tracking liver anatomic landmarks using US images, providing a potential solution for real-time liver tracking for active motion management during radiation therapy.

The Role of C-Reactive Protein in the Prognosis of Prostate Cancer: A Meta-Analysis.

Objective: To investigate the role of C-reactive protein (CRP) in the prognosis of prostate cancer (PCa). Methods: The studies related to C-reactive protein and prostate cancer were searched by computer, including PubMed and Web of Science. The retrieval time was from the establishment of the database to August 2022. QUADAS score was employed to assess the studies' quality, funnel plot was employed to analyze the bias of the included studies, and RevMan and STATA statistical software programs were used to draw forest maps to represent the analysis results. Results: In the initial examination, 432 articles were obtained. After removing the duplicate articles, reading the abstract and theme, and then reading the full text, 12 articles finally met the inclusion criteria. The results revealed that serum C-reactive protein (CRP) levels were associated with overall survival (OS) in patients with PCa (OR = 1.47 [1.19, 1.82], P < 0.05), and patients with high CRP levels had an increased risk of developing prostate cancer (HR = 0.26, 95% CI: 0.23, 0.29). However, there was no obvious difference in circulating CRP levels between patients with prostate cancer and healthy controls (P > 0.05). Conclusions: CRP levels are associated with PCa patients' OS. High CRP levels have an elevated incidence of PCa, but there was no obvious distinction in circulating CRP levels between patients with prostate cancer and healthy controls. Therefore, C-reactive protein has certain reference value for judging the prognosis of prostate cancer.

The huge potential of targeting copper status in the treatment of colorectal cancer.

Colorectal cancer (CRC) commonly leads to cancer deaths and is often diagnosed at advanced stages. It also faces difficulties due to the poor results of conventional treatments such as surgery, chemotherapy, and radiotherapy. Copper is a mineral nutrient whose intrinsic properties have a two-way effect on the production and treatment of cancer. Copper's redox properties allow it to be used in developing anti-cancer drugs, while its potential toxicity leads to oxidative stress and even cancer. Copper status is closely related to colorectal tumors' proliferation and metastasis. The study of the mechanisms of copper homeostasis, cuproplasia, and cuproptosis due to altered copper status plays a crucial role in developing anticancer drugs. Therefore, targeting alteration of copper status becomes a potential option for treating colorectal cancer. This review summarizes the mechanisms by which altered copper status causes CRC progression and emphasizes the potential of regulating copper status in treating CRC.

Iron-Cobalt-Cerium Multimetallic Oxides Derived from Prussian Blue Precursors: Enhanced Oxygen Evolution Electrocatalysis.

Exploring non-precious metal-based electrocatalysts is still challenging in 21st century. In this work, a series of hexagonal bipyramidal Ce-based PBA materials as precursors with different Fe/Co metal ratios, namely as CeFex Co1-x -PBA, are successfully constructed via co-precipitation method and converted into corresponding metal oxides (denoted as Fex Co1-x CeOy ) via thermal treatment. Then, they as electrocatalysts realize highly efficient oxygen evolution reaction (OER). Especially, as-synthesized Fe0.7 Co0.3 CeOy electrocatalyst shows very low overpotentials of 320 mV at the current density of 10 mA cm-2 and the Tafel slop of 98.4 mV dec-1 in 1 M KOH with remarkable durability for 24 h, which was due to the synergistic effect of multi-metal FeCoCe centers. Furthermore, a two-electrode cell of Fe0.7 Co0.3 CeOy /NF||Pt/C/NF realizes outstanding overall water splitting with a voltage of only 1.71 V at 10 mA cm-2 and remarkable long-term durability, that is even superior to benchmark IrO2 /NF||Pt/C/NF counterpart.

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious diseases. Existing prediction and early warning models for influenza and other acute respiratory infectious diseases have limitations and therefore there is room for improvement. OBJECTIVE: The aim of this study was to explore a new and better-performing deep-learning model to predict influenza trends from multisource heterogeneous data in a megacity. METHODS: We collected multisource heterogeneous data from the 26th week of 2012 to the 25th week of 2019, including influenza-like illness (ILI) cases and virological surveillance, data of climate and demography, and search engines data. To avoid collinearity, we selected the best predictor according to the weight and correlation of each factor. We established a new multiattention-long short-term memory (LSTM) deep-learning model (MAL model), which was used to predict the percentage of ILI (ILI%) cases and the product of ILI% and the influenza-positive rate (ILI%×positive%), respectively. We also combined the data in different forms and added several machine-learning and deep-learning models commonly used in the past to predict influenza trends for comparison. The R2 value, explained variance scores, mean absolute error, and mean square error were used to evaluate the quality of the models. RESULTS: The highest correlation coefficients were found for the Baidu search data for ILI% and for air quality for ILI%×positive%. We first used the MAL model to calculate the ILI%, and then combined ILI% with climate, demographic, and Baidu data in different forms. The ILI%+climate+demography+Baidu model had the best prediction effect, with the explained variance score reaching 0.78, R2 reaching 0.76, mean absolute error of 0.08, and mean squared error of 0.01. Similarly, we used the MAL model to calculate the ILI%×positive% and combined this prediction with different data forms. The ILI%×positive%+climate+demography+Baidu model had the best prediction effect, with an explained variance score reaching 0.74, R2 reaching 0.70, mean absolute error of 0.02, and mean squared error of 0.02. Comparisons with random forest, extreme gradient boosting, LSTM, and gated current unit models showed that the MAL model had the best prediction effect. CONCLUSIONS: The newly established MAL model outperformed existing models. Natural factors and search engine query data were more helpful in forecasting ILI patterns in megacities. With more timely and effective prediction of influenza and other respiratory infectious diseases and the epidemic intensity, early and better preparedness can be achieved to reduce the health damage to the population.

[Screening of an Armillaria gallica strain for Gastrodia elata cultivation].

This study aims to screen a strain from Armillaria for the cultivation of Gastrodia elata. Specifically, Armillaria strains were isolated from different producing areas of G. elata and identified. Based on the growth characteristics of the strains and the experiment on the cultivation of G. elata, an optimal A. gallica strain was screened out. The specific process is as follows. The fungus-gro-wing materials of G. elata were collected from four producing areas and the Armillaria strains were isolated(G,Y,S,H). The strains were then identified based on morphological observation and phylogeny analysis and the commonly used strains were determined. The sucrase genotypes of the strains were identified according to our previous research findings, and the growth characteristics of the strains, such as growth rate, diameter, dry weight, and polysaccharide content of the rhizomorphs, were measured. According to the biological characteristics and sucrase genotypes, two strains were selected for the cultivation of G. elata. The tuber yield and the content of gastrodin and p-hydroxybenzyl alcohol in the tuber of G. elata were measured to select the optimal strain. The results showed that the four strains were all A. gallica. The rhizomorphs of strains G and H of the same sucrase genotype had larger/higher length, growth rate, diameter, branch number, dry weight, and polysaccharide content than those of strains S and Y of the same sucrase genotype. The tuber yield and the total content of gastrodin and p-hydroxybenzyl alcohol in tuber of G. elata cultivated with strain H were 6.528 kg·m~(-2) and 0.566%, respectively, which were 4.58 and 1.30 folds those of G. elata cultivated with strain S. Strains H and S were screened out from four strains of A. gallica based on the growth characteristics and sucrase genotype. According to the tuber yield and content of total gastrodin and p-hydroxybenzyl alcohol in the tuber of G. elata, strain H was identified as the optimal one. The findings in this study are expected to lay a basis for cultivating G. elata with high yield and quality of tubers.