The impact of 5-aminosalicylates on the efficacy of mesenchymal stem cell therapy in a murine model of ulcerative colitis.

Inflammatory bowel disease (IBD) is distinguished by persistent immune-mediated inflammation of the gastrointestinal tract. Previous experimental investigations have shown encouraging outcomes for the use of mesenchymal stem cell (MSC)-based therapy in the treatment of IBD. However, as a primary medication for IBD patients, there is limited information regarding the potential interaction between 5-aminosalicylates (5-ASA) and MSCs. In this present study, we employed the dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) mouse model to examine the influence of a combination of MSCs and 5-ASA on the development of UC. The mice were subjected to weight measurement, DAI scoring, assessment of calprotectin expression, and collection of colons for histological examination. The findings revealed that both 5-ASA and MSCs have demonstrated efficacy in the treatment of UC. However, it is noteworthy that 5-ASA exhibits a quicker onset of action, while MSCs demonstrate more advantageous and enduring therapeutic effects. Additionally, the combination of 5-ASA and MSC treatment shows a less favorable efficacy compared to the MSCs alone group. Moreover, our study conducted in vitro revealed that 5-ASA could promote MSC migration, but it could also inhibit MSC proliferation, induce apoptosis, overexpress inflammatory factors (IL-2, IL-12P70, and TNF-α), and reduce the expression of PD-L1 and PD-L2. Furthermore, a significant decrease in the viability of MSCs within the colon was observed as a result of 5-ASA induction. These findings collectively indicate that the use of 5-ASA has the potential to interfere with the therapeutic efficacy of MSC transplantation for the treatment of IBD.

Benign vs malignant vertebral compression fractures with MRI: a comparison between automatic deep learning network and radiologist's assessment.

OBJECTIVE: To test the diagnostic performance of a deep-learning Two-Stream Compare and Contrast Network (TSCCN) model for differentiating benign and malignant vertebral compression fractures (VCFs) based on MRI. METHODS: We tested a deep-learning system in 123 benign and 86 malignant VCFs. The median sagittal T1-weighted images (T1WI), T2-weighted images with fat suppression (T2WI-FS), and a combination of both (thereafter, T1WI/T2WI-FS) were used to validate TSCCN. The receiver operator characteristic (ROC) curve was analyzed to evaluate the performance of TSCCN. The accuracy, sensitivity, and specificity of TSCCN in differentiating benign and malignant VCFs were calculated and compared with radiologists' assessments. Intraclass correlation coefficients (ICCs) were tested to find intra- and inter-observer agreement of radiologists in differentiating malignant from benign VCFs. RESULTS: The AUC of the ROC plots of TSCCN according to T1WI, T2WI-FS, and T1WI/T2WI-FS images were 99.2%, 91.7%, and 98.2%, respectively. The accuracy of T1W, T2WI-FS, and T1W/T2WI-FS based on TSCCN was 95.2%, 90.4%, and 96.2%, respectively, greater than that achieved by radiologists. Further, the specificity of T1W, T2WI-FS, and T1W/T2WI-FS based on TSCCN was higher at 98.4%, 94.3%, and 99.2% than that achieved by radiologists. The intra- and inter-observer agreements of radiologists were 0.79-0.85 and 0.79-0.80 for T1WI, 0.65-0.72 and 0.70-0.74 for T2WI-FS, and 0.83-0.88 and 0.83-0.84 for T1WI/T2WI-FS. CONCLUSION: The TSCCN model showed better diagnostic performance than radiologists for automatically identifying benign or malignant VCFs, and is a potentially helpful tool for future clinical application. CLINICAL RELEVANCE STATEMENT: TSCCN-assisted MRI has shown superior performance in distinguishing benign and malignant vertebral compression fractures compared to radiologists. This technology has the value to enhance diagnostic accuracy, sensitivity, and specificity. Further integration into clinical practice is required to optimize patient management. KEY POINTS: • The Two-Stream Compare and Contrast Network (TSCCN) model showed better diagnostic performance than radiologists for identifying benign vs malignant vertebral compression fractures. • The processing of TSCCN is fast and stable, better than the subjective evaluation by radiologists in diagnosing vertebral compression fractures. • The TSCCN model provides options for developing a fully automated, streamlined artificial intelligence diagnostic tool.

Placental Area in the Lower Uterine Segment, Cervical Length, and Clinical Outcome in Pregnancies With Complete Placenta Previa.

BACKGROUND: Complete placenta previa is associated with a higher percentage of adverse clinical outcomes and magnetic resonance imaging (MRI) is widely used in the preoperative examination of patients with placenta previa. PURPOSE: To evaluate the effectiveness of the placental area in the lower uterine segment and cervical length in identifying the adverse maternal-fetal outcomes in women with complete placenta previa. STUDY TYPE: Retrospective. POPULATION: A total of 141 pregnant women (median age, 32; age range, 24-40 years) with complete placenta previa were examined by MRI to evaluate the uteroplacental condition. FIELD STRENGTH/SEQUENCE: A 3 T with T1 -weighted imaging (T1 WI), T2 -weighted imaging (T2 WI), and half-Fourier acquisition single-shot turbo spin echo (HASTE) sequence. ASSESSMENT: The association of the placental area in the lower uterine segment and cervical length measured using MRI with the risk of massive intraoperative hemorrhage (MIH) and maternal-fetal perinatal outcomes were determined. The adverse neonatal outcomes (preterm delivery, respiratory distress syndrome [RDS], admission to neonatal intensive care unit [NICU]) were analyzed in different groups. STATISTICAL TESTS: The t-test, Mann-Whitney U test, Chi-square, Fisher's exact test, and receiver operating characteristic (ROC) curve were used, and a P < 0.05 indicated a statistically significant difference. RESULTS: The mean operation time, intraoperative blood loss, and intraoperative blood transfusing were significantly higher in patients with large placental area and short cervix than in patients with the small placental area and long cervix, respectively. The incidence of adverse neonatal outcomes was significantly higher in the large placenta area group and short cervix group than in the small placenta group area and long cervix group, respectively, such as preterm delivery, RDS, and NICU. By combining placental area with cervical length sensitivity and specificity increased to 93% and 92%, respectively, for the identification of MIH > 2000 mL with area under the receiver operating curve (AUC) 0.941. DATA CONCLUSION: Large placental area and short cervical length may be associated with a high risk of MIH and adverse maternal-fetal perinatal outcomes in patients with complete placenta previa. TECHNICAL EFFICACY STAGE: 2.

Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images.

Since segmentation labeling is usually time-consuming and annotating medical images requires professional expertise, it is laborious to obtain a large-scale, high-quality annotated segmentation dataset. We propose a novel weakly- and semi-supervised framework named SOUSA (Segmentation Only Uses Sparse Annotations), aiming at learning from a small set of sparse annotated data and a large amount of unlabeled data. The proposed framework contains a teacher model and a student model. The student model is weakly supervised by scribbles and a Geodesic distance map derived from scribbles. Meanwhile, a large amount of unlabeled data with various perturbations are fed to student and teacher models. The consistency of their output predictions is imposed by Mean Square Error (MSE) loss and a carefully designed Multi-angle Projection Reconstruction (MPR) loss. Extensive experiments are conducted to demonstrate the robustness and generalization ability of our proposed method. Results show that our method outperforms weakly- and semi-supervised state-of-the-art methods on multiple datasets. Furthermore, our method achieves a competitive performance with some fully supervised methods with dense annotation when the size of the dataset is limited.

Two-Stream Compare and Contrast Network for Vertebral Compression Fracture Diagnosis.

Differentiating Vertebral Compression Fractures (VCFs) associated with trauma and osteoporosis (benign VCFs) or those caused by metastatic cancer (malignant VCFs) is critically important for treatment decisions. So far, automatic VCFs diagnosis is solved in a two-step manner, i.e., first identify VCFs and then classify them into benign or malignant. In this paper, we explore to model VCFs diagnosis as a three-class classification problem, i.e., normal vertebrae, benign VCFs, and malignant VCFs. However, VCFs recognition and classification require very different features, and both tasks are characterized by high intra-class variation and high inter-class similarity. Moreover, the dataset is extremely class-imbalanced. To address the above challenges, we propose a novel Two-Stream Compare and Contrast Network (TSCCN) for VCFs diagnosis. This network consists of two streams, a recognition stream which learns to identify VCFs through comparing and contrasting between adjacent vertebrae, and a classification stream which compares and contrasts between intra-class and inter-class to learn features for fine-grained classification. The two streams are integrated via a learnable weight control module which adaptively sets their contribution. TSCCN is evaluated on a dataset consisting of 239 VCFs patients and achieves the average sensitivity and specificity of 92.56% and 96.29%, respectively.

Transfer hydrogenation of CO2 into formaldehyde from aqueous glycerol heterogeneously catalyzed by Ru bound to LDH.

Aqueous glycerol was used in this study as a liquid-phase hydrogen source for the hydrogenation of CO2. It was found that hydrogen could be efficiently evolved from aqueous glycerol upon highly dispersed Ru on layered double hydroxide (LDH), inducing the transformation of CO2 into formaldehyde under base-free conditions at low temperature.

Contribution of the Excited Triplet State of Humic Acid and Superoxide Radical Anion to Generation and Elimination of Phenoxyl Radical.

Contributions of excited triplet state of humic acid (3HA*) and superoxide radical anion (O2•-), which is mainly generated via the reaction of O2 with HA-derived reducing intermediates (HA•-), to phenol transformation were revealed using acetaminophen, 2,4,6-trimethylphenol and tyrosine as probe molecules. Phenol transformation was initiated by 3HA*, leading to the formation of the phenoxyl radical (PhO•), but the distribution of transformation intermediates was codetermined by 3HA* and HA•-. The influence of HA•- essentially resulted from the production of O2•-, which affected the fate of PhO•. PhO• could undergo dimerization, or react with O2•-, leading to either phenol peroxide formation (radical addition) or phenol regeneration (electron transfer). In addition, PhO• could bind to HA or react with HA radicals, particularly in the absence of O2 and O2•-. These PhO• reactions were dependent on the reduction potential and structure of PhO•. This study also proved that the reaction of phenol with 1O2 and the reaction of PhO• with O2•- lead to the same oxidation product. The contributions of 3HA* and its generated 1O2, HA•- and its generated O2•- to phenol transformation were pH-dependent.

New insights into the primary phototransformation of acetaminophen by UV/H2O2: photo-Fries rearrangement versus hydroxyl radical induced hydroxylation.

The phototransformation of acetaminophen (APAP) by UV/H2O2 in deionized water and sewage treatment plant (STP) effluents was studied systematically by a combination of analysis of the reaction intermediates and kinetic study. 1-(2-amino-5-hydroxyphenyl)ethanone (P1) and the reported N-(3,4-dihydroxyphenyl)acetamide (P2) were identified as the main transformation intermediates during the transformation of APAP by UV/H2O2. There was no influence of OH on the formation kinetics of P1, while its decay was promoted. The formation and decay kinetics of P2 were accelerated by increases in the concentration of OH. The second-order rate constants for the reaction of OH with APAP, P1, and P2 were 3.9 × 10(9), 8.1 × 10(9), and 4.7 × 10(9) M(-1) s(-1), respectively. The kinetic study indicated that the main transformation of APAP also included transformation to 1,4-hydroquinone, although the accumulated concentration of 1,4-hydroquinone was quite low. The presence of anions (Cl(-), HCO3(-)/CO3(2-) NO2(-)/NO3(-)), humic acid, commercial drug components or adjuvants, and dissolved organic matters in STP effluents not only changed the transformation kinetics of APAP, but also altered the distribution of the intermediates. The kinetics and pathway of APAP transformation in STP effluent were markedly different from those in deionized water.

Effects of bile salts and divalent cations on the adsorption of norfloxacin by agricultural soils.

The effects of bile salts (sodium cholate and sodium deoxycholate, 0-20 mmol/L), divalent cations (Ca(2+), Mg(2+), Cu(2+) and Zn(2+), 0-20 mmol/L) or pH (3.0-10.0) on the adsorption of norfloxacin by three selected soils (Paddy_H, Paddy_G and Red_J) were systematically studied. Soil adsorption of norfloxacin follows a pseudo second-order kinetics model, and the maximum adsorption capacity has been determined from the nonlinear fit of the Langmuir isotherm model to be 88.8, 88.1 and 63.0 µmol/g for the adsorption onto Paddy_H, Paddy_G and Red_J, respectively. The results indicate that norfloxacin has a high adsorption affinity for the agricultural soils tested and that the organic content of these soils have at least a slight influence on this adsorption. The adsorption of norfloxacin to soils was strongly dependent on pH and exhibited a maximum at approximately pH 6. The presence of divalent cations prominently suppressed the adsorption of norfloxacin by paddy soils, which followed an order of Cu(2+) > Mg(2+) > Ca(2+) > Zn(2+), and by red soil, which followed an order of Cu(2+) > Zn(2+) > Ca(2+) > Mg(2+). The adsorption of norfloxacin (by the soils studied) sharply decreased as the amount of bile salts was increased. For uncharged norfloxacin at environmentally relevant pH values, such factors as soil type, exogenous divalent cations and macromolecules significantly altered the environmental fate and transport of norfloxacin between aquatic and soil interfaces.

Adsorption of norfloxacin onto titanium oxide: effect of drug carrier and dissolved humic acid.

Titanium dioxide is widely used as an effective catalyst in wastewater treatment. The effects of drug carriers (cyclodextrins, 100µM) or dissolved humic acids (0-50mg/L) or pH (3.0-11.0) on adsorption of norfloxacin to two TiO(2) (Hombikat UV-100 and Anatase TiO(2)) surfaces were systematically studied. Norfloxacin shows high adsorption affinity to TiO(2) surface. Specific surface area of TiO(2) shows great influence on norfloxacin adsorption especially in acidic solutions. The effect of pH on norfloxacin adsorption originates from the changes of TiO(2)'s surface charge and speciation of norfloxacin. The presence of humic acids (50mg/L) suppresses the adsorption of norfloxacin onto Hombikat UV-100 and Anatase TiO(2) prominently. The co-effect of heptakis(2,6-di-O-methyl)-ß-cyclodextrin (methyl-ß-CD) and humic acid is similar to the solo effect of humic acid on the adsorption of norfloxacin onto Hombikat UV-100, while the co-effect shows a more retardation effect on the adsorption of norfloxacin onto Anatase TiO(2). Humic acid and ß-CD show a synergetic depressed effect on the adsorption of norfloxacin onto both TiO(2) surfaces. These results show that both aquatic solution chemistry and drug carrier are important to norfloxacin adsorption on TiO(2), which could alter the environmental fate and transport of norfloxacin.