Adhesion of <i>Shewanella oneidensis</i> MR-1 to Iron (Oxy)(Hydr)Oxides: Microcolony Formation and Isotherm

The adhesion of dissimilatory metal reducing bacteria (DMRB) to iron (oxy)(hydr)oxides may play an important role in their respiration on ferric iron-containing minerals, but few quantitative surface cell density measurements have been made thus far. We used confocal microscopy to examine the adhesion of a common DMRB species, Shewanella oneidensis MR-1, onto iron (oxy)(hydr)oxide particulate-coated glass slides across a broad range of bulk (i.e., solution phase) cell densities from 105 cells/mL to 2 × 109 cells/mL. At bulk cell densities less than 1 × 107 cells/mL, cells adhered to the slide surface formed an evenly distributed, homogeneous monolayer, while at the bulk cell densities higher than 2 × 108 cells/mL the adhered cells formed distinct microcolonies. As a result of this complex adhesion behavior, simple Langmuir or Freundlich adsorption isotherms do not capture the relationship between the surface cell density and the bulk cell density over the entire range of bulk cell densities. Thus a new, two-step isotherm was developed that incorporated both isolated attached cells at low cell densities as well as microcolonies at higher cell densities

A Chiral Quadruple-Stranded Helicate Cage for Enantioselective Recognition and Separation

The self-assembly of enantiopure pyridyl-functionalized metallosalan units affords a homochiral helicate cage, [Zn₈<b>L</b>₄Cl₈], in which the optical rotation of each ligand is increased by a factor of 10 upon coordination. The octanuclear cage featuring a chiral amphiphilic cavity exhibits enantioselective luminescence enhancement by amino acids in solution. The cage exists in two different crystalline polymorphic forms that possess porous structures built of helicate cages interconnected by 1D channels or pentahedral cages and have the ability to separate small racemic molecules by adsorption but with different enantioselectivities

A Chiral Quadruple-Stranded Helicate Cage for Enantioselective Recognition and Separation

The self-assembly of enantiopure pyridyl-functionalized metallosalan units affords a homochiral helicate cage, [Zn₈<b>L</b>₄Cl₈], in which the optical rotation of each ligand is increased by a factor of 10 upon coordination. The octanuclear cage featuring a chiral amphiphilic cavity exhibits enantioselective luminescence enhancement by amino acids in solution. The cage exists in two different crystalline polymorphic forms that possess porous structures built of helicate cages interconnected by 1D channels or pentahedral cages and have the ability to separate small racemic molecules by adsorption but with different enantioselectivities

Analytical Method for the Determination of Trace Toxic Elements in Milk Based on Combining Fe₃O₄ Nanoparticles Accelerated UV Fenton-like Digestion and Solid Phase Extraction

A UV Fenton-like digestion method was developed first time for a complete digestion of milk samples by using 1.6 g L^–1 Fe₃O₄ magnetic nanoparticles, 0.2% (v/v) nitric acid, and 6% (w/w) H₂O₂. During the digestion, the liberated As-, Sb-, and Bi-containing species were preconcentrated onto the surface of Fe₃O₄ magnetic nanoparticles, which were conveniently separated with a hand-held magnet and subsequently dissolved in hydrochloric acid prior to hydride generation atomic fluorescence spectrometric detection. Owing to the integration of UV Fenton-like digestion, solid phase extraction, and magnetic separation into a single step, the developed method significantly simplifies sample preparation steps and reduces chemical consumption and hazardous waste. Limits of detection of 0.0015, 0.0022, and 0.0025 μg L^–1 were obtained for As, Sb, and Bi, respectively, using a 50 mL milk sample. The method was applied to the determination of these elements in a Certified Reference Material and milk samples

Table_1_Radiomic Machine Learning and External Validation Based on 3.0 T mpMRI for Prediction of Intraductal Carcinoma of Prostate With Different Proportion.xlsx

PurposeTo assess the association of radiomics features based on multiparametric MRI (mpMRI) with the proportion of intraductal carcinoma of prostate (IDC-P) and validate the predictive models.Materials and MethodsWe retrospectively included pre-treatment MR images of prostate cancer (PCa) with IDC components of high proportion (≥10%, hpIDC-P), low proportion (ResultsOverall, 97 patients with hpIDC-P, 87 lpIDC-P, and 78 PAC were included for training and internal validation, and 11, 16, and 19 patients for external validation. The integrated model for predicting hpIDC-P got the best ROC-AUC of 0.88 (95%CI = 0.83-0.93) in internal and 0.86 (95%CI = 0.72-1.0) in external validation, which both outperformed clinical models (AUC=0.78, 95% CI = 0.72-0.85, AUC=0.69, 95% CI = 0.5-0.85, respectively) based solely on GS, and the radiomics model (AUC=0.85, 95% CI = 0.79-0.91) was slightly inferior to the integrated model and better than the clinical model in internal dataset. The integrated model for predicting lpIDC-P outperformed both radiomics and clinical models in the internal dataset, while slightly inferior to the integrated model for predicting hpIDC-P.ConclusionsRadiomics signature improved differentiation of both hpIDC-P and lpIDC-P versus PAC when compared with the clinical model based on Gleason score, and was validated in an external cohort.</p

DataSheet_1_Exploration of identifying individual tumor tissue based on probabilistic model.docx

Variations in the tumor genome can result in allelic changes compared to the reference profile of its homogenous body source on genetic markers. This brings a challenge to source identification of tumor samples, such as clinically collected pathological paraffin-embedded tissue and sections. In this study, a probabilistic model was developed for calculating likelihood ratio (LR) to tackle this issue, which utilizes short tandem repeat (STR) genotyping data. The core of the model is to consider tumor tissue as a mixture of normal and tumor cells and introduce the incidence of STR variants (φ) and the percentage of normal cells (Mxn) as a priori parameters when performing calculations. The relationship between LR values and φ or Mxn was also investigated. Analysis of tumor samples and reference blood samples from 17 colorectal cancer patients showed that all samples had Log10(LR) values greater than 1014. In the non-contributor test, 99.9% of the quartiles had Log10(LR) values less than 0. When the defense’s hypothesis took into account the possibility that the tumor samples came from the patient’s relatives, LR greater than 0 was still obtained. Furthermore, this study revealed that LR values increased with decreasing φ and increasing Mxn. Finally, LR interval value was provided for each tumor sample by considering the confidence interval of Mxn. The probabilistic model proposed in this paper could deal with the possibility of tumor allele variability and offers an evaluation of the strength of evidence for determining tumor origin in clinical practice and forensic identification.</p

Table_1_Exploration of identifying individual tumor tissue based on probabilistic model.xlsx

Variations in the tumor genome can result in allelic changes compared to the reference profile of its homogenous body source on genetic markers. This brings a challenge to source identification of tumor samples, such as clinically collected pathological paraffin-embedded tissue and sections. In this study, a probabilistic model was developed for calculating likelihood ratio (LR) to tackle this issue, which utilizes short tandem repeat (STR) genotyping data. The core of the model is to consider tumor tissue as a mixture of normal and tumor cells and introduce the incidence of STR variants (φ) and the percentage of normal cells (Mxn) as a priori parameters when performing calculations. The relationship between LR values and φ or Mxn was also investigated. Analysis of tumor samples and reference blood samples from 17 colorectal cancer patients showed that all samples had Log10(LR) values greater than 1014. In the non-contributor test, 99.9% of the quartiles had Log10(LR) values less than 0. When the defense’s hypothesis took into account the possibility that the tumor samples came from the patient’s relatives, LR greater than 0 was still obtained. Furthermore, this study revealed that LR values increased with decreasing φ and increasing Mxn. Finally, LR interval value was provided for each tumor sample by considering the confidence interval of Mxn. The probabilistic model proposed in this paper could deal with the possibility of tumor allele variability and offers an evaluation of the strength of evidence for determining tumor origin in clinical practice and forensic identification.</p

Table_1_Radiomic Machine Learning and External Validation Based on 3.0 T mpMRI for Prediction of Intraductal Carcinoma of Prostate With Different Proportion.xlsx

PurposeTo assess the association of radiomics features based on multiparametric MRI (mpMRI) with the proportion of intraductal carcinoma of prostate (IDC-P) and validate the predictive models.Materials and MethodsWe retrospectively included pre-treatment MR images of prostate cancer (PCa) with IDC components of high proportion (≥10%, hpIDC-P), low proportion (ResultsOverall, 97 patients with hpIDC-P, 87 lpIDC-P, and 78 PAC were included for training and internal validation, and 11, 16, and 19 patients for external validation. The integrated model for predicting hpIDC-P got the best ROC-AUC of 0.88 (95%CI = 0.83-0.93) in internal and 0.86 (95%CI = 0.72-1.0) in external validation, which both outperformed clinical models (AUC=0.78, 95% CI = 0.72-0.85, AUC=0.69, 95% CI = 0.5-0.85, respectively) based solely on GS, and the radiomics model (AUC=0.85, 95% CI = 0.79-0.91) was slightly inferior to the integrated model and better than the clinical model in internal dataset. The integrated model for predicting lpIDC-P outperformed both radiomics and clinical models in the internal dataset, while slightly inferior to the integrated model for predicting hpIDC-P.ConclusionsRadiomics signature improved differentiation of both hpIDC-P and lpIDC-P versus PAC when compared with the clinical model based on Gleason score, and was validated in an external cohort.</p

Additional file 1 of A novel intronic circular RNA circFGFR1int2 up-regulates FGFR1 by recruiting transcriptional activators P65/FUS and suppressing miR-4687-5p to promote prostate cancer progression

Additional file 1: Figure S1. A Circular RNAs derived from FGFR1 recorded in CircBase ( http://www.circbase.org/ ). B Interference efficiency of circFGFR1int2. Figure S2. Bioinformatics analyses by ORFfinder, IRESbase, and SRAMP databases. Analyses revealed several ORFs (A) in the circFGFR1int2 sequence, but no IRES (internal ribosome entry sites) (B) or m6A modification sites (C). Figure S3. Sanger sequencing of the wild type and mutated sites. Table S1. Sequences of siRNAs, ASOs, and RNA probes. Table S2. PCR primers. Table S3. Primers used in RNA Dot blot experiment. Table S4. Primers used in Dual-luciferase reporter assay

Image_1_Case report: Ultrasonographic findings of retroperitoneum and abdominal wall metastases of renal cell carcinoma with FH gene deletion.jpg

Renal cell carcinoma with FH gene deletion is a rare subtype of renal cell carcinoma. There had been few reports about ultrasonographic imaging of metastasis of renal cell carcinoma with FH gene deletion. This case reported one of the features of metastasis of renal cell carcinoma with FH gene deletion of a male patient 7 months after undergoing radical nephrectomy. He was diagnosed with a renal malignant tumor before the operation and confirmed to be primary FH gene-deficient renal cell carcinoma after undergoing radical nephrectomy in another hospital. Reexamination 7 months after the operation indicated that multiple metastases all over the body were found; therefore, he came to our hospital for further diagnosis and therapy. The tumors have metastasized in the lungs, bones, and lymph nodes adjacent to the left reproductive vessels and external iliac vessels, retroperitoneum, and abdominal wall so far as confirmed by PET/CT or MRI. Ultrasonographic findings of masses in the retroperitoneum and abdominal wall are fully discussed, which have been confirmed by biopsy and diagnosed as renal cell carcinoma with FH gene deletion by pathology.</p