Learning a More Continuous Zero Level Set in Unsigned Distance Fields through Level Set Projection

Latest methods represent shapes with open surfaces using unsigned distance functions (UDFs). They train neural networks to learn UDFs and reconstruct surfaces with the gradients around the zero level set of the UDF. However, the differential networks struggle from learning the zero level set where the UDF is not differentiable, which leads to large errors on unsigned distances and gradients around the zero level set, resulting in highly fragmented and discontinuous surfaces. To resolve this problem, we propose to learn a more continuous zero level set in UDFs with level set projections. Our insight is to guide the learning of zero level set using the rest non-zero level sets via a projection procedure. Our idea is inspired from the observations that the non-zero level sets are much smoother and more continuous than the zero level set. We pull the non-zero level sets onto the zero level set with gradient constraints which align gradients over different level sets and correct unsigned distance errors on the zero level set, leading to a smoother and more continuous unsigned distance field. We conduct comprehensive experiments in surface reconstruction for point clouds, real scans or depth maps, and further explore the performance in unsupervised point cloud upsampling and unsupervised point normal estimation with the learned UDF, which demonstrate our non-trivial improvements over the state-of-the-art methods. Code is available at https://github.com/junshengzhou/LevelSetUDF .Comment: To appear at ICCV2023. Code is available at https://github.com/junshengzhou/LevelSetUD

Load regulation application of university campus based on solar power generation forecasting

For a solar photovoltaic power system on a university campus, the electricity generated by the system meets the campus load, and the extra electricity is delivered to the grid. Generally, the price of the photovoltaic system is cheaper than that of the utility power system. The full use of solar electricity can reduce the electricity cost of the school. The deep belief network is used to predict solar photovoltaic generation and electricity load, and the gap is found. According to the gap, the power loads on the campus are adjusted to improve the utilization rate of solar power generation. Through the practical application of Changqing Campus of Qilu University of Technology in China, it is found that the utilization rate of solar photovoltaic power generation effectively improved from 91.24% in 2017 to 98.16% in 2019, and the annual electricity is saved by 68 610 yuan (in 2019)

The transcriptional coactivator TAZ regulates reciprocal differentiation of T(h)17 cells and T(reg) cells

自身免疫性疾病是一类机体对自身抗原发生免疫反应而导致自身多器官、组织受累的慢性炎症性疾病。目前大量研究表明机体内促炎症的TH17细胞和抑制炎症Treg细胞在类群数量和活化状态的失衡是造成自身免疫疾病的主要致病因素。陈兰芬教授和周大旺教授团队的前期研究发现小鼠中Hippo信号通路中激酶Mst1/2缺失导致免疫缺陷，机体易受病原体感染并伴随着严重自身免疫疾病。该研究揭示了Hippo 信号通路转录共激活因子TAZ在决定CD4+初始T细胞分化为促进炎症的TH17效应细胞和抑制免疫反应的Treg调节性细胞过程中发挥着关键作用，拓展了当前对于Hippo信号通路的相关研究内容。 陈兰芬，博士，厦门大学生命科学学院教授。【Abstraact】An imbalance in the lineages of immunosuppressive regulatory T cells (Treg cells) and the inflammatory TH17 subset of helper T cells leads to the development of autoimmune and/or inflammatory disease. Here we found that TAZ, a coactivator of TEAD transcription factors of Hippo signaling, was expressed under T H17 cell–inducing conditions and was required for TH17 differentiation and TH17 cell–mediated inflammatory diseases. TAZ was a critical co-activator of the TH17-defining transcription factor RORγt. In addition, TAZ attenuated Treg cell development by decreasing acetylation of the Treg cell master regulator Foxp3 mediated by the histone acetyltransferase Tip60, which targeted Foxp3 for proteasomal degradation. In contrast, under T regcell–skewing conditions, TEAD1 expression and sequestration of TAZ from the transcription factors RORγt and Foxp3 promoted Treg cell differentiation. Furthermore, deficiency in TAZ or overexpression of TEAD1 induced Treg cell differentiation, whereas expression of a transgene encoding TAZ or activation of TAZ directed TH17 cell differentiation. Our results demonstrate a pivotal role for TAZ in regulating the differentiation of Treg cells and TH17 cells.J. Avruch for comments on the manuscript.Supported by the National Basic Research Program (973) of China (2015CB910502 to L.C.), the National Natural Science Foundation of China (81422018 to L.C.; 31625010 and U1505224 to D.Z.; U1405225 and 81372617 to L.C.; J1310027 to D.Z.; 81472229 to L.H.; and 31600698 to J. Geng), the 111 Projects (B12001 and B06016), China's 1000 Young Talents Program (D.Z., and L.C.), the Fundamental Research Funds for the Central Universities of China-Xiamen University (20720160071 to D.Z. and 20720160054 to L.H.) and Major disease research projects of Xiamen (3502Z20149029 to L.C.)

Prediction of recurrence of ischemic stroke within 1 year of discharge based on machine learning MRI radiomics

PurposeThis study aimed to investigate the value of a machine learning-based magnetic resonance imaging (MRI) radiomics model in predicting the risk of recurrence within 1 year following an acute ischemic stroke (AIS).MethodsThe MRI and clinical data of 612 patients diagnosed with AIS at the Second Affiliated Hospital of Nanchang University from March 1, 2019, to March 5, 2021, were obtained. The patients were divided into recurrence and non-recurrence groups according to whether they had a recurrent stroke within 1 year after discharge. Randomized splitting was used to divide the data into training and validation sets using a ratio of 7:3. Two radiologists used the 3D-slicer software to label the lesions on brain diffusion-weighted (DWI) MRI sequences. Radiomics features were extracted from the annotated images using the pyradiomics software package, and the features were filtered using the Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. Four machine learning algorithms, logistic regression (LR), Support Vector Classification (SVC), LightGBM, and Random forest (RF), were used to construct a recurrence prediction model. For each algorithm, three models were constructed based on the MRI radiomics features, clinical features, and combined MRI radiomics and clinical features. The sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC) were used to compare the predictive efficacy of the models.ResultsTwenty features were selected from 1,037 radiomics features extracted from DWI images. The LightGBM model based on data with three different features achieved the best prediction accuracy from all 4 models in the validation set. The LightGBM model based solely on radiomics features achieved a sensitivity, specificity, and AUC of 0.65, 0.671, and 0.647, respectively, and the model based on clinical data achieved a sensitivity, specificity, and AUC of 0.7, 0.799, 0.735, respectively. The sensitivity, specificity, and AUC of the LightGBM model base on both radiomics and clinical features achieved the best performance with a sensitivity, specificity, and AUC of 0.85, 0.805, 0.789, respectively.ConclusionThe ischemic stroke recurrence prediction model based on LightGBM achieved the best prediction of recurrence within 1 year following an AIS. The combination of MRI radiomics features and clinical data improved the prediction performance of the model

hElp3 Directly Modulates the Expression of HSP70 Gene in HeLa Cells via HAT Activity

Human Elongator complex, which plays a key role in transcript elongation in vitro assay, is incredibly similar in either components or function to its yeast counterpart. However, there are only a few studies focusing on its target gene characterization in vivo. We studied the effect of down-regulation of the human elongation protein 3 (hELP3) on the expression of HSP70 through antisense strategy. Transfecting antisense plasmid p1107 into HeLa cells highly suppressed hELP3 expression, and substantially reduced expression of HSP70 mRNA and protein. Furthermore, chromatin immunoprecipitation assay (ChIP Assay) revealed that hElp3 participates in the transcription elongation of HSPA1A in HeLa cells. Finally, complementation and ChIP Assay in yeast showed that hElp3 can not only complement the growth and slow activation of HSP70 (SSA3) gene transcription, but also directly regulates the transcription of SSA3. On the contrary, these functions are lost when the HAT domain is deleted from hElp3. These data suggest that hElp3 can regulate the transcription of HSP70 gene, and the HAT domain of hElp3 is essential for this function. These findings now provide novel insights and evidence of the functions of hELP3 in human cells

Design-with-Nature for Multifunctional Landscapes: Environmental Benefits and Social Barriers in Community Development

Since the early 1970s, Ian McHarg’s design-with-nature concept has been inspiring landscape architects, community and regional planners, and liked-minded professionals to create designs that take advantage of ecosystem services and promote environmental and public health. This study bridges the gap in the literature that has resulted from a lack of empirical examinations on the multiple performance benefits derived through design-with-nature and the under-investigated social aspect emanated from McHarg’s Ecological Determinism design approach. The Woodlands, TX, USA, an ecologically designed community development under McHarg’s approach, is compared with two adjacent communities that follow the conventional design approach. Using national environmental databases and multiple-year residents’ survey information, this study assesses three landscape performance metrics of McHarg’s approach: stormwater runoff, urban heat island effect, and social acceptance. Geographic Information Systems (GIS) was used to assess the development extent and land surface temperature distribution. Results show that McHarg’s approach demonstrates benefits in reducing runoff and urban heat island effect, whereas it confronts challenges with the general acceptance of manicured landscapes and thus results in a low safety perception level when residents interact with naturally designed landscapes. The authors argue that design-with-nature warrants multifunctionality because of its intrinsic interdisciplinary approach. Moreover, education and dissemination of successful examples can achieve a greater level of awareness among the public and further promote multifunctional design for landscape sustainability.The open access fee for this work was funded through the Texas A&M University Open Access to Knowledge (OAK) Fund

Emergence of Fatal PRRSV Variants: Unparalleled Outbreaks of Atypical PRRS in China and Molecular Dissection of the Unique Hallmark

Porcine reproductive and respiratory syndrome (PRRS) is a severe viral disease in pigs, causing great economic losses worldwide each year. The causative agent of the disease, PRRS virus (PRRSV), is a member of the family Arteriviridae. Here we report our investigation of the unparalleled large-scale outbreaks of an originally unknown, but so-called “high fever” disease in China in 2006 with the essence of PRRS, which spread to more than 10 provinces (autonomous cities or regions) and affected over 2,000,000 pigs with about 400,000 fatal cases. Different from the typical PRRS, numerous adult sows were also infected by the “high fever” disease. This atypical PRRS pandemic was initially identified as a hog cholera-like disease manifesting neurological symptoms (e.g., shivering), high fever (40–42°C), erythematous blanching rash, etc. Autopsies combined with immunological analyses clearly showed that multiple organs were infected by highly pathogenic PRRSVs with severe pathological changes observed. Whole-genome analysis of the isolated viruses revealed that these PRRSV isolates are grouped into Type II and are highly homologous to HB-1, a Chinese strain of PRRSV (96.5% nucleotide identity). More importantly, we observed a unique molecular hallmark in these viral isolates, namely a discontinuous deletion of 30 amino acids in nonstructural protein 2 (NSP2). Taken together, this is the first comprehensive report documenting the 2006 epidemic of atypical PRRS outbreak in China and identifying the 30 amino-acid deletion in NSP2, a novel determining factor for virulence which may be implicated in the high pathogenicity of PRRSV, and will stimulate further study by using the infectious cDNA clone technique

Increased Expression of DNA2 Was Linked to Poor Prognosis in Breast Cancer

DNA double-strand break (DSB) repaired by homologous recombination (HR) is an essential process for breast cancer cells to survive. DNA2 nuclease acts parallel to homologous recombination (HR). Here, we investigated the detailed clinical attribute of DNA2 in breast cancer and the role of DNA2 in breast cancer cells’ growth. We found that elevated expression of DNA2 was obviously linked to poor prognosis in breast cancer. Further, DNA2 expression was increased in the ER-negative group, PR-negative group, HER2-positive group, and high-grade group via analyzing 2,509 breast cancers in “cBioportal” and 3,063 breast cancer data in “bc-GenExMiner.” Besides, the immunohistochemical staining in 26 breast cancer tissues also showed that elevated expression of DNA2 was correlated with ER-/PR-/HER+. To further detect the role of DNA2 in breast cancer cells, we took GESA, GO, and KEGG analyses and found that DNA2 was enriched in cell cycle and DNA replication pathways. Furthermore, silencing of DNA2 inhibited cell growth in T47D and MD-MB-231 breast cancer cells and suppressed tumor growth in vivo, indicating DNA2 functioned importantly in breast cancer progression and maybe a potential prognostic marker in breast cancer. Our research reveals that DNA2 is a biomarker for diagnosis and prognosis in breast cancer from multiple perspectives and gives a new clue for further preclinical and clinical investigation

The Flotation Separation of Magnesite and Limonite Using an Amine Collector

In order to reduce the iron impurities in magnesite ore and improve the purity of magnesium products, the difference in floatability between magnesite and limonite has been studied by using mixtures with a collecting agent—KD (cationic amine collectors, containing soluble components). Sodium hexametaphosphate, pH, sodium silicate, and sodium carboxymethyl cellulose were used as regulators. Adsorption mechanisms of the reagents on minerals were analyzed by a zeta potential analyzer and infrared spectroscopy. Sodium silicate increased the floatability of both minerals at 11.6. All the three regulators reduced the zeta potential of both minerals, while KD increased the zeta potential of magnesite and decreased the zeta potential of limonite. All the three regulators were likely chemically adsorbed on the surface of both minerals; KD has electrostatic adsorption on the surface of the minerals