Generalization of matching extensions in graphs (II)

Proposed as a general framework, Liu and Yu(Discrete Math. 231 (2001) 311-320) introduced $(n,k,d)$-graphs to unify the concepts of deficiency of matchings, $n$-factor-criticality and $k$-extendability. Let $G$ be a graph and let $n,k$ and $d$ be non-negative integers such that $n+2k+d\leq |V(G)|-2$ and $|V(G)|-n-d$ is even. If when deleting any $n$ vertices from $G$, the remaining subgraph $H$ of $G$ contains a $k$-matching and each such $k$- matching can be extended to a defect-$d$ matching in $H$, then $G$ is called an $(n,k,d)$-graph. In \cite{Liu}, the recursive relations for distinct parameters $n, k$ and $d$ were presented and the impact of adding or deleting an edge also was discussed for the case $d = 0$. In this paper, we continue the study begun in \cite{Liu} and obtain new recursive results for $(n,k,d)$-graphs in the general case $d \geq0$.Comment: 12 page

Stock Trading Optimization through Model-based Reinforcement Learning with Normalizing Fl

With the fast development of quantitative portfolio optimization in financial engineering, lots of promising algorithmic trading strategies have shown competitive advantages in recent years. However, the environment from real financial markets is complex and hard to be fully simulated, considering non-stationarity of the stock data, unpredictable hidden causal factors and so on. Fortunately, difference of stock prices is often stationary series, and the internal relationship between difference of stocks can be linked to the decision-making process, then the portfolio should be able to achieve better performance. In this paper, we demonstrate normalizing flows is adopted to simulated high-dimensional joint probability of the complex trading environment, and develop a novel model based reinforcement learning framework to better understand the intrinsic mechanisms of quantitative online trading. Second, we experiment various stocks from three different financial markets (Dow, NASDAQ and S&P 500) and show that among these three financial markets, Dow gets the best performance results on various evaluation metrics under our back-testing system. Especially, our proposed method even resists big drop (less maximum drawdown) during COVID-19 pandemic period when the financial market got unpredictable crisis. All these results are comparatively better than modeling the state transition dynamics with independent Gaussian Processes. Third, we utilize a causal analysis method to study the causal relationship among different stocks of the environment. Further, by visualizing high dimensional state transition data comparisons from real and virtual buffer with t-SNE, we uncover some effective patterns of betComment: arXiv admin note: text overlap with arXiv:2205.1505

Collaborative Perception in Autonomous Driving: Methods, Datasets and Challenges

Collaborative perception is essential to address occlusion and sensor failure issues in autonomous driving. In recent years, theoretical and experimental investigations of novel works for collaborative perception have increased tremendously. So far, however, few reviews have focused on systematical collaboration modules and large-scale collaborative perception datasets. This work reviews recent achievements in this field to bridge this gap and motivate future research. We start with a brief overview of collaboration schemes. After that, we systematically summarize the collaborative perception methods for ideal scenarios and real-world issues. The former focuses on collaboration modules and efficiency, and the latter is devoted to addressing the problems in actual application. Furthermore, we present large-scale public datasets and summarize quantitative results on these benchmarks. Finally, we highlight gaps and overlook challenges between current academic research and real-world applications. The project page is https://github.com/CatOneTwo/Collaborative-Perception-in-Autonomous-DrivingComment: 18 pages, 6 figures. Accepted by IEEE Intelligent Transportation Systems Magazine. URL: https://github.com/CatOneTwo/Collaborative-Perception-in-Autonomous-Drivin

Data from a comparative proteomic analysis of tumor-derived lung-cancer CD105+ endothelial cells

AbstractIncreasing evidence indicates that tumor-derived endothelial cells (TECs) are more relevant for the study of tumor angiogenesis and for screening antiangiogenic drugs than normal ECs (NECs). In this data article, high-purity (>98%) primary CD105+ NECs and TECs purified from a mouse Lewis lung carcinoma model bearing 0.5cm tumors were identified using 2D-PAGE and Matrix-assisted laser desorption/ionization tandem mass spectrometry (MALDI-MS/MS). All the identified proteins were categorized functionally by Gene Ontology (GO) analysis, and gene-pathway annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, protein–protein interaction networks were also built. The proteomics and bioinformatics data presented here provide novel insights into the molecular characteristics and the early modulation of the TEC proteome in the tumor microenvironment

Case report: Treatment of two cases of recurrent/refractory early T-cell precursor acute lymphoblastic leukemia with venetoclax combined with the CAG regimen

Early T-cell precursor acute lymphoblastic leukemia (ETP-ALL) is a highly aggressive subtype of T-ALL. No standard chemotherapy regimen exists for patients with recurrent/refractory (R/R) ETP-ALL; in these patients, the primary goal of salvage therapy is to achieve remission as a foundation for consolidation and intensification treatments. This study reports cases of two patients with R/R ETP-ALL who underwent salvage therapy of venetoclax combined with the CAG regimen and achieved complete remission in the bone marrow. Flow cytometry results were negative for minimal residual disease. Both patients were bridged to allogeneic hematopoietic stem cell transplantation (HSCT) and in complete remission over a 3-year follow-up period. These cases show that the use of venetoclax combined with the CAG regimen may offer patients with R/R ETP-ALL an opportunity for allogeneic HSCT

Tong-Xie-Yao-Fang Regulates 5-HT Level in Diarrhea Predominant Irritable Bowel Syndrome Through Gut Microbiota Modulation

Tong-Xie-Yao-Fang (TXYF) has been widely used for the treatment of diarrhea-predominant irritable bowel syndrome (IBS-D) in traditional Chinese medicine. However, its mechanism of action in the treatment of IBS-D remains to be fully understood. Recent reports have shown that Clostridium species in the gut can induce 5-HT production in the colon, which then contributes to IBS-D. Due to the wide use of TXYF in the clinical treatment of IBS-D and the close relationship between gut microbiota and IBS-D, we hypothesize that TXYF treats IBS-D by modulating gut microbiota and regulating colonic 5-HT levels. In this study, variation analysis of 16S rRNA was conducted to evaluate changes in the distribution of gut microbiota in IBS-D model rats after TXYF treatment. Moreover, we investigated whether TXYF could affect colonic 5-HT levels in IBS-D model rats. We then performed fecal transplantation experiments to confirm the effects of TXYF on gut microbiota and 5-HT levels. We found that TXYF treatment can ameliorate IBS-D and regulate 5-HT levels in colon tissue homogenates. TXYF treatment also affected the diversity of gut microbiota and altered the relative abundance of Akkermansia and Clostridium sensu stricto 1 in gut flora populations. Finally, we showed that fecal transplantation from TXYF-treated rats could relieve IBS-D and regulate 5-HT levels in colon tissue homogenates. In conclusion, the present study demonstrates that TXYF treatment diminishes colonic 5-HT levels and alleviates the symptoms of IBS-D by favorably affecting microbiota levels in gut flora communities

Evaluating the effect of SARS-CoV-2 spike mutations with a linear doubly robust learner

Driven by various mutations on the viral Spike protein, diverse variants of SARS-CoV-2 have emerged and prevailed repeatedly, significantly prolonging the pandemic. This phenomenon necessitates the identification of key Spike mutations for fitness enhancement. To address the need, this manuscript formulates a well-defined framework of causal inference methods for evaluating and identifying key Spike mutations to the viral fitness of SARS-CoV-2. In the context of large-scale genomes of SARS-CoV-2, it estimates the statistical contribution of mutations to viral fitness across lineages and therefore identifies important mutations. Further, identified key mutations are validated by computational methods to possess functional effects, including Spike stability, receptor-binding affinity, and potential for immune escape. Based on the effect score of each mutation, individual key fitness-enhancing mutations such as D614G and T478K are identified and studied. From individual mutations to protein domains, this paper recognizes key protein regions on the Spike protein, including the receptor-binding domain and the N-terminal domain. This research even makes further efforts to investigate viral fitness via mutational effect scores, allowing us to compute the fitness score of different SARS-CoV-2 strains and predict their transmission capacity based solely on their viral sequence. This prediction of viral fitness has been validated using BA.2.12.1, which is not used for regression training but well fits the prediction. To the best of our knowledge, this is the first research to apply causal inference models to mutational analysis on large-scale genomes of SARS-CoV-2. Our findings produce innovative and systematic insights into SARS-CoV-2 and promotes functional studies of its key mutations, serving as reliable guidance about mutations of interest

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.This work is part of the ‘‘SpatioTemporal Omics Consortium’’ (STOC) paper package. A list of STOC members is available at: http://sto-consortium.org. We would like to thank the MOTIC China Group, Rongqin Ke (Huaqiao University, Xiamen, China), Jiazuan Ni (Shenzhen University, Shenzhen, China), Wei Huang (Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China), and Jonathan S. Weissman (Whitehead Institute, Boston, USA) for their help. This work was supported by the grant of Top Ten Foundamental Research Institutes of Shenzhen, the Shenzhen Key Laboratory of Single-Cell Omics (ZDSYS20190902093613831), and the Guangdong Provincial Key Laboratory of Genome Read and Write (2017B030301011); Longqi Liu was supported by the National Natural Science Foundation of China (31900466) and Miguel A. Esteban’s laboratory at the Guangzhou Institutes of Biomedicine and Health by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16030502), National Natural Science Foundation of China (92068106), and the Guangdong Basic and Applied Basic Research Foundation (2021B1515120075).S

Short and long term outcome of bilateral pallidal stimulation in chorea-acanthocytosis

BACKGROUND: Chorea-acanthocytosis (ChAc) is a neuroacanthocytosis syndrome presenting with severe movement disorders poorly responsive to drug therapy. Case reports suggest that bilateral deep brain stimulation (DBS) of the ventro-postero-lateral internal globus pallidus (GPi) may benefit these patients. To explore this issue, the present multicentre (n=12) retrospective study collected the short and long term outcome of 15 patients who underwent DBS. METHODS: Data were collected in a standardized way 2-6 months preoperatively, 1-5 months (early) and 6 months or more (late) after surgery at the last follow-up visit (mean follow-up: 29.5 months). RESULTS: Motor severity, assessed by the Unified Huntington's Disease Rating Scale-Motor Score, UHDRS-MS), was significantly reduced at both early and late post-surgery time points (mean improvement 54.3% and 44.1%, respectively). Functional capacity (UHDRS-Functional Capacity Score) was also significantly improved at both post-surgery time points (mean 75.5% and 73.3%, respectively), whereas incapacity (UHDRS-Independence Score) improvement reached significance at early post-surgery only (mean 37.3%). Long term significant improvement of motor symptom severity (≥ 20 % from baseline) was observed in 61.5 % of the patients. Chorea and dystonia improved, whereas effects on dysarthria and swallowing were variable. Parkinsonism did not improve. Linear regression analysis showed that preoperative motor severity predicted motor improvement at both post-surgery time points. The most serious adverse event was device infection and cerebral abscess, and one patient died suddenly of unclear cause, 4 years after surgery. CONCLUSION: This study shows that bilateral DBS of the GPi effectively reduces the severity of drug-resistant hyperkinetic movement disorders such as present in ChAc