To diminish incongruity between bone regeneration and biodegradation of implant magnesium alloy applied for mandibular bone repair, a brushite coating was deposited on a matrix of a Mg-Nd-Zn-Zr (hereafter, denoted as JDBM) alloy to control the degradation rate of the implant and enhance osteogenesis of the mandible bone. Both in vitro and in vivo evaluations were carried out in the present work. Viability and adhesion assays of rabbit bone marrow mesenchyal stem cells (rBM-MSCs) were applied to determine the biocompatibility of a brushite-coated JDBM alloy. Osteogenic gene expression was characterized by quantitative real-time polymerase chain reaction (RT-PCR). Brushite-coated JDBM screws were implanted into mandible bones of rabbits for 1, 4, and 7 months, respectively, using 316L stainless steel screws as a control group. In vivo biodegradation rate was determined by synchrotron radiation X-ray microtomography, and osteogenesis was observed and evaluated using Van Gieson's picric acid-fuchsin. Both the naked JDBM and brushite-coated JDBM samples revealed adequate biosafety and biocompatibility as bone repair substitutes. In vitro results showed that brushite-coated JDBM considerably induced osteogenic differentiation of rBM-MSCs. And in vivo experiments indicated that brushite-coated JDBM screws presented advantages in osteoconductivity and osteogenesis of mandible bone of rabbits. Degradation rate was suppressed at a lower level at the initial stage of implantation when new bone tissue formed. Brushite, which can enhance oeteogenesis and partly control the degradation rate of an implant, is an appropriate coating for JDBM alloys used for mandibular repair. The Mg-Nd-Zn-Zr alloy with brushite coating possesses great potential for clinical applications for mandibular repair.

In plants, a population of non-cell-autonomous proteins (NCAPs), including numerous transcription factors, move cell to cell through plasmodesmata (PD). In many cases, the intercellular trafficking of these NCAPs is regulated by their interaction with specific PD components. To gain further insight into the functions of this NCAP pathway, coimmunoprecipitation experiments were performed on a tobacco (Nicotiana tabacum) plasmodesmal-enriched cell wall protein preparation using as bait the NCAP, pumpkin (Cucurbita maxima) PHLOEM PROTEIN16 (Cm-PP16). A Cm-PP16 interaction partner, Nt-PLASMODESMAL GERMIN-LIKE PROTEIN1 (Nt-PDGLP1) was identified and shown to be a PD-located component. Arabidopsis thaliana putative orthologs, PDGLP1 and PDGLP2, were identified; expression studies indicated that, postgermination, these proteins were preferentially expressed in the root system. The PDGLP1 signal peptide was shown to function in localization to the PD by a novel mechanism involving the endoplasmic reticulum-Golgi secretory pathway. Overexpression of various tagged versions altered root meristem function, leading to reduced primary root but enhanced lateral root growth. This effect on root growth was corrected with an inability of these chimeric proteins to form stable PD-localized complexes. PDGLP1 and PDGLP2 appear to be involved in regulating primary root growth by controlling phloem-mediated allocation of resources between the primary and lateral root meristems.

We previously reported on the strong symbiosis of AMf species (Rhizophagus irregularis CD1) with the cotton (Gossypium hirsutum L.) which is grown worldwide. in current study, it was thus investigated in farmland to determine the biological control effect of AMF on phosphorus acquisition and related gene expression regulation, plant growth and development, and a series of agronomic traits associated with yield and fiber quality in cotton. When AMF and cotton were symbiotic, the expression of the specific phosphate transporter family genes and P concentration in the cotton biomass were significantly enhanced. The photosynthesis, growth, boll number per plant and the maturity of the fiber were increased through the symbiosis between cotton and AMf. Statistical analysis showed a highly significant increase in yield for inoculated plots compared with that from the non inoculated controls, with an increase percentage of 28.54%. These findings clearly demonstrate here the benefits of AMFbased inoculation on phosphorus acquisition, growth, seed cotton yield and fiber quality in cotton. Further improvement of these beneficial inoculants on crops will help increase farmers' income all over the world both now and in the future. Cotton is an important natural fiber and economic crop that provides substantial benefits to humans and is an important raw material worldwide. While a large number of recent studies have confirmed that arbuscular mycorrhizal fungi (AMF) can improve the growth, yield, quality, and phosphorus acquisition in plants 1-5 , the effect of AMF on these economic and agronomic traits in cotton is largely unknown. Previous research evidence suggests that mycorrhiza-mediated inoculants can reduce the need for P fertilization by at least 25% (and even up to 50%) without any decrease in crop yield 6. We also investigated and reported recently as Zhang et al. on the field biological control effect on cotton Verticillium wilt of AMF application. The nutrient acquisition of crops is mainly controlled by root and soil microorganisms 7 , which play a key role in nutrient circulation and absorption and in fighting against soil pathogens 8,9. Beneficial soil microorganisms are an important part of agricultural ecosystems 7,10,11 and have been used in agriculture more frequently over the past few decades. Nevertheless, the cultivation of the target microorganism is not a simple task, given the large number of microbes, their functional diversity, and the complexity of microbial assemblages. AMF are important beneficial soil microbiota which can be cultured in the laboratory and have established close symbioses with plants over the past 455 million years 12. Arbuscular mycorrhizal fungi (AMF) colonize plant roots and can improve the adaptability of host plants, especially by offering additional phosphorus (P) 13,14 , nitrogen (N), and zinc 15 to plants. Root systems were extended, increasing the root surface that is utilized for nutrient uptake by more than 100-fold, by symbiosis with AMF 15. A large group of agricultura...

BackgroundClear cell renal cell carcinoma (ccRCC) is the most common renal cancer and it has the worst prognosis among all renal cancers. However, traditional radiological characteristics on computed tomography (CT) scans of ccRCC have been insufficient to predict the pathological grade of ccRCC before surgery.MethodsPatients with ccRCC were retrospectively enrolled into this study and were separated into two groups according to the World Health Organization (WHO)/International Society of Urological Pathology (ISUP) grading system, i.e., low-grade (Grade I and II) group and high-grade (Grade III and IV) group. Traditional CT radiological characteristics such as tumor size, pre- and post-enhancing CT densities were assessed. In addition, radiomic texture analysis based on the CT imaging of the ccRCC were also performed. A CT-based machine learning method combining the traditional radiological characteristics and radiomic features was used in the predictive modeling for differentiating the low-grade from the high-grade ccRCC. Model performance was evaluated with the receiver operating characteristic curve (ROC) analysis.ResultsA total of 264 patients with pathologically confirmed ccRCC were included in this study. In this cohort, 206 patients had the low-grade tumors and 58 had the high-grade tumors. The model built with traditional radiological characteristics achieved an area under the curve (AUC) of 0.9175 (95% CI: 0.8765–0.9585) and 0.8088 (95% CI: 0.7064–0.9113) in differentiating the low-grade from the high-grade ccRCC for the training cohort and the validation cohort respectively. The model built with the radiomic textural features yielded an AUC value of 0.8170 (95% CI: 0.7353–0.8987) and 0.8017 (95% CI: 0.6878–0.9157) for the training cohort and the validation cohort, respectively. The combined model integrating both the traditional radiological characteristics and the radiomic textural features achieved the highest efficacy, with an AUC of 0.9235 (95% CI: 0.8646–0.9824) and an AUC of 0.9099 (95% CI: 0.8324–0.9873) for the training cohort and validation cohort, respectively.ConclusionWe developed a machine learning radiomic model achieving a satisfying performance in differentiating the low-grade from the high-grade ccRCC. Our study presented a potentially useful non-invasive imaging-focused method to predict the pathological grade of renal cancers prior to surgery.

The copper transporters CTR1, CTR2, ATP7A, and ATP7B regulate intracellular concentration of platinum by mediating its uptake and efflux in cells. We sought to explore the effect of genetic polymorphisms in CTR1, CTR2, ATP7A, and ATP7B on platinum resistance in patients suffering from epithelial ovarian cancer (EOC). A total of 152 Chinese EOC patients were enrolled in this study, all of whom underwent adjuvant chemotherapy using platinum and taxane after maximal debulking surgery. In total, 11 single-nucleotide polymorphisms (SNPs) in CTR1, CTR2, ATP7A, and ATP7B were genotyped in these patients. The CTR1 rs10981694 polymorphism was observed to be associated with carboplatin resistance, while patients with the rs10981694 G allele showed a significantly higher rate of carboplatin resistance (OR = 4.00, 95% CI 1.309 - 12.23, p < 0.01). In addition, we found that ATP7A rs2227291 was associated with cisplatin resistance and that carriers of the C allele were more sensitive to cisplatin (OR = 0.40, 95% CI: 0.17 - 0.94, p = 0.03). Our findings suggest that the CTR1 and ATP7A genetic polymorphisms could affect platinum resistance. The CTR1 and ATP7A genes might be considered a predictive marker for carboplatin and cisplatin resistance, respectively.
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