Learning Dynamic Scene-Conditioned 3D Object Detectors.

In this paper, we propose a dynamic 3D object detector named HyperDet3D, which is adaptively adjusted based on the hyper scene-level knowledge on the fly. Existing methods strive for object-level representations of local elements and their relations without scene-level priors, which suffer from ambiguity between similarly-structured objects only based on the understanding of individual points and object candidates. Instead, we design scene-conditioned hypernetworks to simultaneously learn scene-agnostic embeddings to exploit sharable abstracts from various 3D scenes, and scene-specific knowledge which adapts the 3D detector to the given scene at test time. As a result, the lower-level ambiguity in object representations can be addressed by hierarchical context in scene priors. However, since the upstream hypernetwork in HyperDet3D takes raw scenes as input which contain noises and redundancy, it leads to sub-optimal parameters produced for the 3D detector simply under the constraint of downstream detection losses. Based on the fact that the downstream 3D detection task can be factorized into object-level semantic classification and bounding box regression, we furtherly propose HyperFormer3D by correspondingly designing their scene-level prior tasks in upstream hypernetworks, namely Semantic Occurrence and Objectness Localization. To this end, we design a transformer-based hypernetwork that translates the task-oriented scene priors into parameters of the downstream detector, which refrains from noises and redundancy of the scenes. Extensive experimental results on the ScanNet, SUN RGB-D and MatterPort3D datasets demonstrate the effectiveness of the proposed methods.

Development of an Antiswelling Hydrogel System Incorporating M2-Exosomes and Photothermal Effect for Diabetic Wound Healing.

Diabetic wounds represent a persistent global health challenge with a substantial impact on patients' health and overall well-being. Herein, a hydrogel system that integrates functionalized gold nanorods (AuNRs) and M2 macrophage-derived exosomes (M2-Exos) was developed to achieve an efficient and synergistic therapy for diabetic wounds. We introduced an ion-cross-linked dissipative network into a prefabricated covalent cross-linked network (long-chain polymer network), which was prepared using AuNRs as a specific cross-linker. The ion network was then cross-linked with the long-chain polymer in situ to form a specific network structure, imparting antiswelling and photothermal effects to the hydrogel. This integrated hydrogel system effectively scavenged reactive oxygen species levels, inhibited inflammation, promoted angiogenesis, and stimulated photothermal antibacterial activity through near-infrared (NIR) irradiation. To demonstrate the potential of the hydrogel, we established experimental animal models of oral mucosa ulceration and full-thickness skin defects. In vivo results confirmed that M2-Exos released from the hydrogels played a crucial role in wound closure. Furthermore, the synergistic effect of AuNRs and NIR photothermal effects eradicated bacterial infections in the wound area. Overall, our integrated hydrogel system is a promising tool for accelerating chronic diabetic wound healing and tissue regeneration. This study highlights the potential benefits of combining bioactive M2-Exos and the photothermal effect of AuNRs into an antiswelling hydrogel platform to achieve satisfactory wound healing in patients with diabetes.

Accumulated Dose Deviation of Rotational and Residual Setup Errors on Nasopharyngeal Carcinoma Using MIM Treated by Helical Tomotherapy.

BACKGROUND: To analyze the relationship between the rotational and residual setup errors and the dose deviation on nasopharyngeal carcinoma (NPC) treated by helical tomotherapy (HT). METHODS: From 25 July 2017 to 20 August 2019, 16 treated NPC patients were enrolled in the study. These patients were scanned with full target range megavoltage computed tomography (MVCT) every other day. Adaptive radiotherapy function application software MIM7.1.3 were used to accumulate the actual dose. The dose deviation with the initial plan dose of the patients' target and organs at risk (OAR) were compared, and the correlation between the dose change and the setup errors (rotational setup errors and neck residual setup error) was analyzed. RESULTS: Translational setup errors increased farther away from the head. Statistically significant difference among 3 groups was achieved in the directions of left-right (P < .001) and anteroposterior (P < .001) by analysis of variance test. Compared with the initial plan dose, the actual accumulated dose of the target area decreased with the actual exposure dose of the OAR increased. However, most of the dosimetric parameters differed by less than 5%. No correlation was found between dose deviation values and the translational setup errors of target. However, sagittal rotational setup errors (pitch) had a positive relationship (P < .05) with the avearge dose of PTVnd (L) (r = 0.885), PTVnd(R) (r = 0.547) PTV1(r = 0.633) and PTV2(r = 0.584). Transverse rotational setup errors (roll) had a positive relationship (P < .05) with the avearge dose of PTVnd(R) (r = 0.593), PTV1(r = 0.505) and PTV2(r = 0.662). CONCLUSIONS: Dose deviation between the actual accumulated and initial plan is not negligible, but most indicators difference is less than 5%, NPC patients treated by HT with MVCT correction setup errors every other day did not need adaptive radiotherapy model unless got rapid tumor shrinkage or weight loss. Moreover, to minimize the dose deviation, more attention should be paid to the reduction of pitch, roll, and residual error of cervical vertebrae during body positioning.

Self-healing hybrid hydrogels with sustained bioactive components release for guided bone regeneration.

Guided bone regeneration (GBR) is widely used in treating oral bone defects to exclude the influence of non-osteogenic tissue on the bone healing process. The traditional method of GBR with a titanium mesh to treat large-area bone defects is limited by the deficiency of increased trauma and costs to patients. Herein, a bi-layered scaffold for GBR composed of a fiber barrier layer and a self-healing hydrogel repair layer is successfully fabricated. The barrier layer is a fibrous membrane material with specific porosity constructed by electrospinning, while the functional layer is a self-healing hydrogel material formed by multiple dynamic covalent bonds. The system can provide an osteogenic microenvironment by preventing the infiltration of connective tissue to bone defects, maintain the stability of the osteogenic space through the self-healing property, and regulate the release of bioactive substances in the dynamic physical condition, which is beneficial to osteoblast proliferation, differentiation, and bone regeneration. This study focused on exploring the effects of different crosslinkers and bonding methods on the comprehensive properties of hydrogels. and proved that the hybrid scaffold system has good biocompatibility, cell barrier function and can enhance bone regeneration activity. Thereby it could be a promising clinical strategy for bone regeneration.

Effects of Vegetation Restoration on Soil Enzyme Activity in Copper and Coal Mining Areas.

Mining areas are suffering from serious environmental hazards, such as soil erosion, water pollution as well as land degradation. In this study, two types of mining areas in Anhui Province, China-one a copper mining area and the other a coal mining area-were selected to compare the soil properties under different vegetation restoration conditions, which can be generally classified into reclaimed and non-reclaimed areas. Soil catalase and urease activities and soil chemical properties were chosen to be the main indicators of soil quality. Principal component analysis was used to evaluate the overall soil fertility in the copper and coal mining areas. Results showed that in the copper mining area soil catalase activity was between 12.36 and 19.17 µg g-1 h-1 and urease activity was between 0.03 and 12.05 µg g-1 h-1. And in coal mining area, soil catalase activity was between 3.52 and 9.72 µg g-1 h-1 and urease activity was between 2.71 and 10.81 µg g-1 h-1. Moreover, soil catalase and urease activities in degraded areas were lower than those in reclaimed areas. Soil catalase activity and soil urease activity were significantly correlated with total potassium and total nitrogen, respectively. Soil quality in land types with vegetation restoration was higher than in non-reclaimed areas and old subsidence areas, while soil quality in the copper mining area was generally higher than in the coal mining area. Thus, the optimum measure in this region to ameliorate these degraded soils is vegetation restoration, which helps not only to improve the environment, but also to enhance soil quality in these degraded lands.

Characterization of progression-related alternative splicing events in testicular germ cell tumors.

Accumulating evidence supports the significance of aberrant alternative splicing (AS) events in cancer; however, genome-wide profiling of progression-free survival (PFS)-related AS events in testicular germ cell tumors (TGCT) has not been reported. Here, we analyzed high-throughput RNA-sequencing data and percent-spliced-in values for 150 patients with TGCT. Using univariate and multivariate Cox regression analysis and a least absolute shrinkage and selection operator method, we identified the top 15 AS events most closely associated with disease progression. A risk-associated AS score (ASS) for the 15 AS events was calculated for each patient. ASS, pathological stage, and T stage were significantly associated with disease progression by univariate analysis, but only ASS and pathological stage remained significant by multivariate analysis. The ability of these variables to predict 5-year progression was assessed using receiver operating characteristic curve analysis. ASS had stronger predictive value than a combination of age, pathological stage, and T stage (area under the curve = 0.899 and 0.715, respectively). Furthermore, Kaplan-Meier analysis of patients with low and high ASS demonstrated that high ASS was associated with significantly worse PFS than low ASS (P = 1.46 × 10-7). We also analyzed the biological functions of the PFS-related AS-related genes and found enrichment in pathways associated with DNA repair and modification. Finally, we identified a regulatory network of splicing factors with expression levels that correlated significantly with AS events in TGCT. Collectively, this study identifies a novel method for risk stratification of patients and provides insight into the molecular events underlying TGCT.

Depiction of tumor stemlike features and underlying relationships with hazard immune infiltrations based on large prostate cancer cohorts.

Prostate cancer stemness (PCS) cells have been reported to drive tumor progression, recurrence and drug resistance. However, there is lacking systematical assessment of stemlike indices and associations with immunological properties in prostate adenocarcinoma (PRAD). We thus collected 7 PRAD cohorts with 1465 men and calculated the stemlike indices for each sample using one-class logistic regression machine learning algorithm. We selected the mRNAsi to quantify the stemlike indices that correlated significantly with prognosis and accordingly identified 21 PCS-related CpG loci and 13 pivotal signature. The 13-gene based PCS model possessed high predictive significance for progression-free survival (PFS) that was trained and validated in 7 independent cohorts. Meanwhile, we conducted consensus clustering and classified the total cohorts into 5 PCS clusters with distinct outcomes. Samples in PCScluster5 possessed the highest stemness fractions and suffered from the worst prognosis. Additionally, we implemented the CIBERSORT algorithm to infer the differential abundance across 5 PCS clusters. The activated immune cells (CD8+ T cell and dendritic cells) infiltrated significantly less in PCScluster5 than other clusters, supporting the negative regulations between stemlike indices and anticancer immunity. High mRNAsi was also found to be associated with up-regulation of immunosuppressive checkpoints, like PDL1. Lastly, we used the Connectivity Map (CMap) resource to screen potential compounds for targeting PRAD stemness, including the top hits of cell cycle inhibitor and FOXM1 inhibitor. Taken together, our study comprehensively evaluated the PRAD stemlike indices based on large cohorts and established a 13-gene based classifier for predicting prognosis or potential strategies for stemness treatment.

[Impacts of shading on seedling growth and mineral accumulation in Paeonia lactiflora]. / é®è«å¤„ç†å¯¹èŠè¯å¹¼è‹—ç”Ÿé•¿å’ŒçŸ¿è´¨è¥å »ç§¯ç´¯çš„å½±å“.

Shading is one of the important strategies to protect seedlings of Paeonia lactiflora. The effects of shading treatments on seedling growth and mineral accumulation of Duolun P. lactiflora were investigated in a greenhouse experiment to provide guidance for P. lactiflora cultivation. One week after emergence, seedlings were treated with 20%, 40%, 60% or 80% shading for two months, with no-shading as the control (CK). The results showed that shading treatments significantly increased plant height by 19.9%, 31.1%, 52.9%, and 63.7%, respectively. However, shading significantly reduced the root mass ratio and root to shoot ratio by 21.5%, 23.6%, 29.2%, 41.8% and 40.6%, 44.0%, 50.9%, 63.2%, respectively. Moreover, 40%, 60% and 80% shading significantly increased specific leaf area by 77.0%, 84.1% and 65.2%, and significantly increased chlorophyll content by 92.3%, 128.7%, 98.1%, and increased carotenoid content by 86.9%, 113.1% and 90.5%, respectively. The treatments of 40%, 60%, and 80% shading significantly decreased root biomass by 61.4%, 74.3% and 78.6%, respectively. Compared with CK, 20%, 40% and 80% shading, the 60% shading treatment increased root phosphorus content by 245.7%, 65.9%, 40.5% and 10.3%, increased potassium content by 102.9%, 131.7%, 57.0%, 63.3% and magnesium content by 131.3%, 55.1%, 40.4%, 7.7%, respectively. 60% shading was an appropriate shading intensity for P. lactiflora seedling cultivation based on local conditions in Duolun.

Mineral Elements and Active Ingredients in Root of Wild Paeonia lactiflora Growing at Duolun County, Inner Mongolia.

Roots of wild Paeonia lactiflora are often used as herbs in traditional Chinese medicine. In this study, the contents of potassium (K), calcium (Ca), phosphorus (P), magnesium (Mg), iron (Fe), manganese (Mn), copper (Cu), and zinc (Zn) and the concentrations of three active ingredients such as paeoniflorin (PF), catechin (CA) and benzoic acid (BA) in roots of wild P. lactiflora collected from Duolun County of Inner Mongolia in China were evaluated. The results showed that the mean contents of eight elements followed the following order: Ca > K > P > Mg > Fe > Zn > Mn > Cu, and the concentrations of three active ingredients decreased in the order: PF > CA > BA. It was found that PF concentration was positively correlated with the contents of Fe and Mn. However, the concentration of CA was linearly decreased with Mg content. Moreover, BA concentration showed positive linear dependence upon the contents of P and Mn. Results of stepwise regression analyses showed that 39.2% of the variance in PF concentration could be explained by Fe content, whereas 28.1% of the CA concentration changes could be explained by Mg content; moreover, 42.5% of the variance in BA concentration could be accounted for by the combination of Mn and P contents. In a word, the concentrations of active ingredients in roots of P. lactiflora can be changed by adjusting mineral elements levels in roots to meet the need of appropriate quality control of P. lactiflora.

Identification of five long noncoding RNAs signature and risk score for prognosis of bladder urothelial carcinoma.

Nowadays, an increasing number of studies illustrated that bladder urothelial cancer (BLCA) may act as the most common subtype of urological malignancies with a high rate of recurrence and metastasis. In this study, we attempted to establish a prognostic model and identify the possible pathway crosstalk. Long noncoding RNAs (lncRNAs) and mRNA expression and corresponding clinical information of patients with BLCA were downloaded from The Cancer Genome Atlas (TCGA). The differentially expressed genes analysis, univariate Cox analysis, the least absolute shrinkage, and selection operator Cox (LASSO Cox) regression model were then applied to identify five crucial lncRNAs (AC092725.1, AC104071.1, AL023584.1, AL132642.1, and AL137804.1). The multivariate cox analysis was utilized to calculate the regression coefficients (ßi ). The risk-score model was subsequently constructed as follows: (0.13541AC092725.1) + (0.20968AC104071.1) + (0.1525AL023584.1) - (0.14768AL132642.1) + (0.14387AL137804.1). Nomogram and assessment of overall survival (OS) prediction were verificated by the receiver operating characteristic curve in the testing group. As to 3-, 5-year OS prediction, the area under curve (AUC) for the nomogram of training data set was 0.83 and 0.86. Besides, the AUC (0.883 and 0.879) presented excellent predictive power in the testing group. In addition, the calibration plots validated the predictive performance of the nomogram. Weighted correlation network analysis (WGCNA) coupled with functional enrichment analysis contributed to explore the potential pathways, including PI3K-Akt, HIF-1, and Jak-STAT signaling pathways. Construction of the risk-score model and data analysis were both derived from multiple packages on the basis of the R platform chiefly.

Exploration of the relationships between tumor mutation burden with immune infiltrates in clear cell renal cell carcinoma.

BACKGROUND: Whether tumor mutation burden (TMB) correlated with improved survival outcomes or promotion of immunotherapies remained controversy in various malignancies. We aimed to investigate the prognosis of TMB and the potential association with immune infiltrates in clear cell renal cell carcinoma (ccRCC). METHODS: We downloaded the somatic mutation data of 336 ccRCC patients from the Cancer Genome Atlas (TCGA) database, and analyzed the mutation profiles with "maftools" package. TMB was calculated and we classified the samples into high-TMB and low-TMB group. Differential analysis was conducted to compare the expression profiles between two groups using "limma" package, and we identified the 9 hub TMB-related signature from batch survival analysis. Gene ontology (GO) analysis and Gene Set Enrichment Analysis (GSEA) were performed to screen significantly enriched pathways between two groups. Based on the TIMER database, we further assessed the relationships of the mutants of 9 TMB-related signature with immune infiltration levels in ccRCC. Besides, we utilized the "CIBERSORT" package to estimate the abundance of 22 immune fractions between low- and high-TMB groups, and the significant difference were determined by Wilcoxon rank-sum test. Furthermore, Cox regression model combined with survival analysis were used to evaluate the prognostic value of immune cells. Last, we constructed a Tumor Mutation Burden Prognostic Index (TMBPI) from multivariate Cox results and Receiver Operating Characteristic (ROC) curve was drawn to assess the predictive accuracy. RESULTS: Single nucleotide polymorphism (SNP) occurred more frequently than insertion or deletion, and C>T was the most common of SNV in ccRCC. Higher TMB levels conferred poor survival outcomes, associated with higher tumor grades and advanced pathological stages. A total of 1,265 differentially expressed genes were obtained and top 19 immune-related genes were identified in Venn diagram. GSEA revealed that patients in higher TMB groups correlated with MAPK signaling pathway, Wnt signaling pathway and pathway in cancers. Moreover, we identified 9 hub TMB-related immune genes related with survival and mutants of 9 signature were associated with lower immune infiltrates. In addition, infiltration levels of CD8+ T cell, CD4+ memory resting T cell, M1 and M2 macrophages, as well as dendritic resting cells in high-TMB group were lower than that in low-TMB group, especially the level of CD8+ T cell and macrophage correlated negatively with prognosis of ccRCC. Last, the TMBPI was constructed and the AUC of ROC curve was 0.666. CONCLUSIONS: Higher TMB correlated with poor survival outcomes and might inhibit the immune infiltrates in ccRCC. The mutants of 9 hub TMB-related immune signature conferred lower immune cells infiltration which deserved further validation.

Personalizing risk stratification by addition of PAK1 expression to TNM staging: improving the accuracy of clinical decision for gastroesophageal junction adenocarcinoma.

Gastroesophageal junction adenocarcinoma (GEJA) is an aggressive malignancy with an alarmingly rising incidence. TNM staging is widely used by oncologists to stratify prognosis as well as direct therapeutic strategies. However, inadequate lymphadenectomy is frequently encountered for GEJA and largely confounds prognosis resulting from TNM staging. Thus, a molecular biomarker, which can accurately forecast the risk of nodal metastasis in patients with inadequate lymphadenectomy, is required to guide precisely clinical decision. In this study, bioinformatics and pathological analysis identified that p21 protein-activated kinase 1 (PAK1) is associated with lymph nodal metastasis of GEJA. The PAK1 H-score was lower in the patients with negative lymph nodes than that in patients with positive (metastatic) lymph nodes (6.865 ± 3.376, 9.370 ± 2.530, respectively; p < 0.001). The PAK1 H-score in lymph nodes was positively correlated with that in primary tumors (PTs; p < 0.001; r = 0.475). PAK1 H-scores in PTs had the best performance based on its area under the receiver-operating characteristic (ROC) curve compared with PAK1 H-scores in lymph nodes, histological grade, lymph nodal metastasis status, tumor size, depth of tumor, TNM stage and number of resected lymph nodes. Multivariate Cox proportional hazard and Fine and Gray models showed that histological grade 3, Charlson comorbidity index > 7 and high PAK1 expression in PTs were associated with significantly increased risk of recurrence and cancer-related death. In conclusion, high PAK1 expression in PTs is predictive of node metastasis and can be easily integrated in the clinical decision process for personalized therapeutics of GEJA.

Cancer-related fatigue and chemotherapy-associated adverse effects: correlation with TNF-α, IL-1 and 17-hydroxycorticosteroids.

AIM: We sought to determine the relationship between cancer-related fatigue, chemotherapy-associated adverse effects in patients with advanced stages of cancer, and the levels of TNF-α, IL-1 and 17-hydroxycorticosteroids (17-HCS). PATIENTS & METHODS: Two hundred cancer patients were recruited. They were given a Cancer Fatigue Scale survey to assess their general state of health before and after chemotherapy. Their plasma levels of TNF-α and IL-1 and urine levels of 17-HCS were also measured. RESULTS: Increased levels of TNF-α and IL-1 are common in cancer patients. Thirty-five (17.5%) patients suffered from chemotherapy-associated adverse effects, but their plasma levels of TNF-α and IL-1 were not significantly elevated after chemotherapy. However, the urinary levels of 17-HCS levels were significantly elevated in 23 patients after chemotherapy. CONCLUSION: Patients who had elevated urinary levels of 17-HCS before chemotherapy are accompanied by chemotherapy-associated adverse effects. Thus, elevated 17-HCS in urine could be a possible predictor for chemotherapy-associated adverse effects.

Prognostic importance and therapeutic implications of PAK1, a drugable protein kinase, in gastroesophageal junction adenocarcinoma.

Gastroesophageal junction (GEJ) adenocarcinoma is a lethal cancer with rising incidence, yet the molecular biomarkers that have strong prognostic impact and also hold great therapeutic promise remain elusive. We used a data mining approach and identified the p21 protein-activated kinase 1 (PAK1), an oncogene and drugable protein kinase, to be among the most promising targets for GEJ adenocarcinoma. Immunoblot analysis and data mining demonstrated that PAK1 protein and mRNA were upregulated in cancer tissues compared to the noncancerous tissues. Immunohistochemistry revealed PAK1 overexpression in 72.6% of primary GEJ adenocarcinomas (n = 113). A step-wise increase in PAK1 levels was noted from paired normal epithelium, to atypical hyperplasia and adenocarcinoma. PAK1 overexpression in tumor was associated with lymph node (LN) metastasis (P<0.001), advanced tumor stage (P<0.001), large tumor size (P = 0.006), residual surgical margin (P = 0.033), and unfavorable overall survival (P<0.001). Multivariate analysis showed PAK1 overexpression is an independent high-risk prognostic predictor (P<0.001). Collectively, PAK1 is overexpressed during tumorigenic progression and its upregulation correlates with malignant properties mainly relevant to invasion and metastasis. PAK1 expression could serve as a prognostic predictor that holds therapeutic promise for GEJ adenocarcinoma.

PTPRO promoter methylation is predictive of poorer outcome for HER2-positive breast cancer: indication for personalized therapy.

BACKGROUND: Protein Tyrosine Phosphatase Receptor-type O (PTPRO) has recently been in the spotlight as a tumor suppressor, whose encoding gene is frequently methylated in cancers. We examined the methylation status of the PTPRO gene promoter in breast cancer and evaluated the correlation between PTPRO promoter methylation and both clinicopathological parameters and prognosis of breast cancer patients. METHODS: Two hundred twenty-one formalin-fixed, paraffin-embedded (FFPE) tumor tissues, 20 FFPE normal adjacent tissues and 24 matched plasma samples, collected from primary breast cancer patients, were assessed for PTPRO gene promoter methylation using methylation-specific PCR. Associations of promoter methylation with clinicopathological parameters were evaluated. Kaplan-Meier survival analysis and Cox proportional hazards models were used to estimate the effect on survival. RESULTS: 175 samples gave identifiable PCR products, of which 130 cases (74.3%) had PTPRO gene promoter methylation. PTPRO methylation correlated with higher histological grade (P = 0.028), but not other clinical parameters. Multivariate analysis indicated that overall survival (OS) was significantly poorer in HER2-positive, but not ER-positive patients with methylated-PTPRO. Methylated-PTPRO was detectable in matched plasma samples and only observed in plasma from patients whose corresponding primary tumors were also methylated. CONCLUSIONS: PTPRO methylation is a common event in the primary breast cancer and can be reliably detected in peripheral blood samples. PTPRO methylation is associated with poor survival only in HER2-positive patients, suggesting use of PTPRO methylation as a prognostic factor for breast cancer and for optimizing individualized therapy for HER2-positive patients.