Association Analysis Between Intratumoral and Peritumoral MRI Radiomics Features and Overall Survival of Neoadjuvant Therapy in Rectal Cancer.

BACKGROUND: The use of peritumoral features to determine the survival time of patients with rectal cancer (RC) is still imprecise. PURPOSE: To explore the correlation between intratumoral, peritumoral and combined features, and overall survival (OS). STUDY TYPE: Retrospective. POPULATION: One hundred sixty-six RC patients (53 women, 113 men; average age: 55 ± 12 years) who underwent radical resection after neoadjuvant therapy. FIELD STRENGTH/SEQUENCE: 3 T; T2WI sagittal, T1WI axial, T2WI axial with fat suppression, and high-resolution T2WI axial sequences, enhanced T1WI axial and sagittal sequences with fat suppression. ASSESSMENT: Radiologist A segmented 166 patients, and radiologist B randomly segmented 30 patients. Intratumoral and peritumoral features were extracted, and features with good stability (ICC ≥0.75) were retained through intra-observer analysis. Seven classifiers, including Logistic Regression (LR), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Random Forest (RF), Extremely randomized trees (ET), eXtreme Gradient Boosting (XGBoost), and LightGBM (LGBM), were applied to select the classifier with the best performance. Next, the Rad-score of best classifier and the clinical features were selected to establish the models, thus, nomogram was built to identify the association with 1-, 3-, and 5-year OS. STATISTICAL TESTS: LASSO, regression analysis, ROC, DeLong method, Kaplan-Meier curve. P < 0.05 indicated a significant difference. RESULTS: Only Node (irregular tumor nodules in the surrounding mesentery) and ExtraMRF (lymph nodes outside the perirectal mesentery) were significantly different in 20 clinical features. Twelve intratumoral, 3 peritumoral, and 14 combined features related to OS were selected. LR, SVM, and RF classier showed the best efficacy in the intratumoral, peritumoral, and combined model, respectively. The combined model (AUC = 0.954 and 0.821) had better survival association than the intratumoral model (AUC = 0.833 and 0.813) and the peritumoral model (AUC = 0.824 and 0.687). DATA CONCLUSION: The proposed peritumoral model with radiomics features may serve as a tool to improve estimated survival time. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 4.

Electronic Properties and CO2-Selective Adsorption of (NiB)n (n = 1~10) Clusters: A Density Functional Theory Study.

In this study, we investigated the electronic properties and selective adsorption for CO2 of nickel boride clusters (NiB)n, (n = 1~10) using the first principles method. We optimized the structures of the clusters and analyzed their stability based on binding energy per atom. It was observed that (NiB)n clusters adopt 3D geometries from n = 4, which were more stable compared to the plane clusters. The vertical electron affinity, vertical ionization energy, chemical potential, and highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap were calculated. Our results revealed that (NiB)6 and (NiB)10, with high chemical potential, exhibit a higher affinity for CO2 adsorption due to a charge delivery channel that forms along the Ni→B→CO2 path. Notably, (NiB)10 demonstrated a more practical CO2 desorption temperature, as well as a broader window for the selective adsorption of CO2 over N2. The density of states analysis showed that the enhanced CO2 adsorption on (NiB)10 can be attributed to the synergistic effect between Ni and B, which provides more active sites for CO2 adsorption and promotes the electron transfer from the surface to the CO2 molecule. Our theoretical results imply that (NiB)10 should be a promising candidate for CO2 capture.

Fructo-oligofructose ameliorates 2,4-dinitrofluorobenzene-induced atopic dermatitis-like skin lesions and psychiatric comorbidities in mice.

BACKGROUND: Atopic dermatitis (AD) is a chronic inflammatory skin disorder characterized by pruritus and eczema lesions and psychiatric comorbidities. The gut-brain-skin axis plays a pivotal role during AD development, which might suggest a novel therapeutic strategy for AD. The present study aims to uncover the protective effects and underlying mechanisms of fructo-oligofructose (FOS), a type of prebiotic, on AD-like skin manifestations and comorbid anxiety and depression in AD mice. RESULTS: Female Kunming mice were treated topically with 2,4-dinitrofluorobenzene (DNFB) to induce AD-like symptoms and FOS was administered daily for 14 days. The results showed that FOS could alleviate AD-like skin lesions markedly as evidenced by dramatic decreases in severity score, scratching bouts, the levels of immunoglobulin E (IgE) and T helper 1(Th1)/Th2-related cytokines, and the infiltration of inflammatory cells and mast cells to the dermal tissues. The comorbid anxiety and depressive-like behaviors, estimated by the forced swimming test (FST), the tail-suspension test (TST), the open-field test (OFT), and the zero maze test (ZMT) in AD mice, were significantly attenuated by FOS. Fructo-oligofructose significantly upregulated brain neurotransmitters levels of 5-hydroxytryptamine (5-HT) and dopamine (DA). Furthermore, FOS treatment increased the relative abundance of gut microbiota, such as Prevotella and Lactobacillus and the concentrations of short-chain fatty acids (SCFAs), especially acetate and iso-butyrate in the feces of AD mice. The correlation analysis indicated that the reshaped gut microbiome composition and enhanced SCFAs formation are associated with skin inflammation and behavioral alteration. CONCLUSION: Collectively, these data identify FOS as a promising microbiota-targeted treatment for AD-like skin inflammation and comorbid anxiety and depressive-like behaviors. © 2023 Society of Chemical Industry.

Knockdown of Trnau1ap inhibits the proliferation and migration of NIH3T3, JEG-3 and Bewo cells via the PI3K/Akt signaling pathway.

The tRNA selenocysteine 1 associated protein 1 (Trnau1ap, initially named SECp43) is involved in Selenocysteine (Sec) biosynthesis and incorporation into selenoproteins, which play a key role in biological processes, such as embryonic development. We previously reported that downregulation of Trnau1ap inhibited proliferation of cardiomyocyte-like H9c2 cells. However, the effects of Trnau1ap on cell proliferation and migration of embryonic development are not known, and the mechanisms remain elusive. Herein, lentiviral shRNA vectors were transfected in NIH3T3, JEG-3 and Bewo cells (embryonic, trophoblast and placental cells). We found that knockdown of Trnau1ap resulted in reduced expression levels of selenoproteins. The data of Cell Count Kit-8 (CCK-8) assay and wound scratch assay revealed the proliferation and migration rates were reduced in the Trnau1ap-shRNA groups. Furthermore, western blot analysis showed that the phosphorylation level of Akt in the phosphatidylinositol 3-kinase (PI3K)/Akt pathway was attenuated. These results indicate that Trnau1ap plays an important role in regulation of cell proliferation and migration through the PI3K/Akt signaling pathway, as well as being essential for embryonic development by regulating the expression of selenoproteins.

MicroRNA-328 is involved in the effect of selenium on hydrogen peroxide-induced injury in H9c2 cells.

Oxidative stress induces apoptosis in cardiac cells, and antioxidants attenuate the injury. MicroRNAs (miRNAs) are also involved in cell death; therefore, this study aimed to investigate the role of miRNAs in the effect of selenium on oxidative stress-induced apoptosis. The effects of sodium selenite were analyzed via cell viability, superoxide dismutase (SOD) activity, and malondialdehyde (MDA) concentration. Flow cytometry was used to evaluate cell apoptosis. Fura-2AM was used to calculate intracellular Ca2+ concentration. Sodium selenite could ameliorate hydrogen peroxide (H2 O2 )-induced cell apoptosis and improve expression levels of glutathione peroxidase and thioredoxin reductase. Pretreatment with sodium selenite improved SOD activity and reduced MDA concentration. Treatments with H2 O2 or sodium selenite decreased miR-328 levels. MiR-328 overexpression enhanced cell apoptosis, reduced ATP2A2 levels, and increased intracellular Ca2+ concentration, while inhibition produced opposite effects. MiR-328 might be involved in the effect of sodium selenite on H2 O2 -induced cell death in H9c2 cells.

Exogenous Feeding of Fructose and Phenylalanine Further Improves Betulin Production in Suspended Betula platyphylla Cells under Nitric Oxide Treatment.

The aim of this study was to assay by NMR the metabolites which contribute to betulin production. 8-day-old suspended birch (Betula platyphylla) cells were treated by sodium nitroprusside (SNP) treatment, an NO donor, and 2-(4-carboxyphenyl)-4,4,5,5-tetramethyl-imidazoline-1-oxyl-3-oxide (cPTIO), an NO-specific scavenger. The results showed that betulin production was increased by five times after SNP treatment, similar with that of the control under cPTIO treatment. Forty one metabolites were detected after SNP treatment or cPTIO treatment. Among them, 10 were found to significantly contribute to the differences observed between controls and treated cell culture samples. To validate the contribution of the above 10 metabolites to betulin production, myo-inositol, fructose and phenylalanine based on correlation analysis between the content of 12 metabolites and betulin were used to feed birch suspension cell cultures under SNP treatment. Exogenous feeding of fructose or phenylalanine further enhanced the betulin production under SNP treatment, but myo-inositol had the opposite result.

Preoperative prediction of perineural invasion and lymphovascular invasion with CT radiomics in gastric cancer.

Objectives: To determine whether contrast-enhanced CT radiomics features can preoperatively predict lymphovascular invasion (LVI) and perineural invasion (PNI) in gastric cancer (GC). Methods: A total of 148 patients were included in the LVI group, and 143 patients were included in the PNI group. Three predictive models were constructed, including clinical, radiomics, and combined models. A nomogram was developed with clinical risk factors to predict LVI and PNI status. The predictive performance of the three models was mainly evaluated using the mean area under the curve (AUC). The performance of three predictive models was assessed concerning calibration and clinical usefulness. Results: In the LVI group, the predictive power of the combined model (AUC=0.871, 0.822) outperformed the clinical model (AUC=0.792, 0.728) and the radiomics model (AUC=0.792, 0.728) in both the training and testing cohorts. In the PNI group, the combined model (AUC=0.834, 0.828) also had better predictive power than the clinical model (AUC=0.764, 0.632) and the radiomics model (AUC=0.764, 0.632) in both the training and testing cohorts. The combined models also showed good calibration and clinical usefulness for LVI and PNI prediction. Conclusion: CECT-based radiomics analysis might serve as a non-invasive method to predict LVI and PNI status in GC.

Response of soil fungal communities and their co-occurrence patterns to grazing exclusion in different grassland types.

Overgrazing and climate change are the main causes of grassland degradation, and grazing exclusion is one of the most common measures for restoring degraded grasslands worldwide. Soil fungi can respond rapidly to environmental stresses, but the response of different grassland types to grazing control has not been uniformly determined. Three grassland types (temperate desert, temperate steppe grassland, and mountain meadow) that were closed for grazing exclusion for 9 years were used to study the effects of grazing exclusion on soil nutrients as well as fungal community structure in the three grassland types. The results showed that (1) in the 0-5 cm soil layer, grazing exclusion significantly affected the soil water content of the three grassland types (P < 0.05), and the pH, total phosphorous (TP), and nitrogen-to-phosphorous ratio (N/P) changed significantly in all three grassland types (P < 0.05). Significant changes in soil nutrients in the 5-10 cm soil layer after grazing exclusion occurred in the mountain meadow grasslands (P < 0.05), but not in the temperate desert and temperate steppe grasslands. (2) For the different grassland types, Archaeorhizomycetes was most abundant in the montane meadows, and Dothideomycetes was most abundant in the temperate desert grasslands and was significantly more abundant than in the remaining two grassland types (P < 0.05). Grazing exclusion led to insignificant changes in the dominant soil fungal phyla and α diversity, but significant changes in the ß diversity of soil fungi (P < 0.05). (3) Grazing exclusion areas have higher mean clustering coefficients and modularity classes than grazing areas. In particular, the highest modularity class is found in temperate steppe grassland grazing exclusion areas. (4) We also found that pH is the main driving factor affecting soil fungal community structure, that plant coverage is a key environmental factor affecting soil community composition, and that grazing exclusion indirectly affects soil fungal communities by affecting soil nutrients. The above results suggest that grazing exclusion may regulate microbial ecological processes by changing the soil fungal ß diversity in the three grassland types. Grazing exclusion is not conducive to the recovery of soil nutrients in areas with mountain grassland but improves the stability of soil fungi in temperate steppe grassland. Therefore, the type of degraded grassland should be considered when formulating suitable restoration programmes when grazing exclusion measures are implemented. The results of this study provide new insights into the response of soil fungal communities to grazing exclusion, providing a theoretical basis for the management of degraded grassland restoration.

Quantitative separation of CEST effect by Rex-line-fit analysis of Z-spectra.

The process of chemical exchange saturation transfer (CEST) is quantified by evaluating a Z-spectra, where CEST signal quantification and Z-spectra fitting have been widely used to distinguish the contributions from multiple origins. Based on the exchange-dependent relaxation rate in the rotating frame (Rex), this paper introduces an additional pathway to quantitative separation of CEST effect. The proposed Rex-line-fit method is solved by a multi-pool model and presents the advantage of only being dependent of the specific parameters (solute concentration, solute-water exchange rate, solute transverse relaxation, and irradiation power). Herein we show that both solute-water exchange rate and solute concentration monotonously vary with Rex for Amide, Guanidino, NOE and MT, which has the potential to assist in solving quantitative separation of CEST effect. Furthermore, we achieve Rex imaging of Amide, Guanidino, NOE and MT, which may provide direct insight into the dependency of measurable CEST effects on underlying parameters such as the exchange rate and solute concentration, as well as the solute transverse relaxation.

Constructing a nomogram to predict overall survival of colon cancer based on computed tomography characteristics and clinicopathological factors.

BACKGROUND: The colon cancer prognosis is influenced by multiple factors, including clinical, pathological, and non-biological factors. However, only a few studies have focused on computed tomography (CT) imaging features. Therefore, this study aims to predict the prognosis of patients with colon cancer by combining CT imaging features with clinical and pathological characteristics, and establishes a nomogram to provide critical guidance for the individualized treatment. AIM: To establish and validate a nomogram to predict the overall survival (OS) of patients with colon cancer. METHODS: A retrospective analysis was conducted on the survival data of 249 patients with colon cancer confirmed by surgical pathology between January 2017 and December 2021. The patients were randomly divided into training and testing groups at a 1:1 ratio. Univariate and multivariate logistic regression analyses were performed to identify the independent risk factors associated with OS, and a nomogram model was constructed for the training group. Survival curves were calculated using the Kaplan-Meier method. The concordance index (C-index) and calibration curve were used to evaluate the nomogram model in the training and testing groups. RESULTS: Multivariate logistic regression analysis revealed that lymph node metastasis on CT, perineural invasion, and tumor classification were independent prognostic factors. A nomogram incorporating these variables was constructed, and the C-index of the training and testing groups was 0.804 and 0.692, respectively. The calibration curves demonstrated good consistency between the actual values and predicted probabilities of OS. CONCLUSION: A nomogram combining CT imaging characteristics and clinicopathological factors exhibited good discrimination and reliability. It can aid clinicians in risk stratification and postoperative monitoring and provide important guidance for the individualized treatment of patients with colon cancer.

Effects of grazing exclusion on soil properties, fungal community structure, and diversity in different grassland types.

Soil fungi are involved in the decomposition of organic matter, and they alter soil structure and physicochemical properties and drive the material cycle and energy flow in terrestrial ecosystems. Fungal community assembly processes were dissimilar in different soil layers and significantly affected soil microbial community function and plant growth. Grazing exclusion is one of the most common measures used to restore degraded grasslands worldwide. However, changes in soil fungal community characteristics during grazing exclusion in different types of grasslands are unknown. Here, we investigated the effects of a 9-year grazing exclusion on soil properties, fungal community composition, and diversity in three grassland types (temperate desert, temperate steppe, and mountain meadow). The results showed that (1) in the 0-5 cm soil layer, grazing exclusion significantly increased the differences in SWC, SOC, KN, and N:P among the three grassland types, while the final pH, BD, TP, C:N, and C:P values were consistent with the results before exclusion. In the 5-10 cm soil layer, grazing exclusion significantly increased total phosphorus (TP) in temperate deserts by 34.1%, while significantly decreasing bulk density (BD) by 9.8% and the nitrogen: phosphorus ratio (N:P) by 47.1%. (2) The soil fungal community composition differed among the grassland types, For example, significant differences were found among the three grassland types for the Glomeromycota and Mucoromycota. (3) Under the influence of both grazing exclusion and grassland type, there was no significant change in soil fungal alpha diversity, but there were significant differences in fungal beta diversity. (4) Grassland type was the most important factor influencing changes in fungal community diversity, and vegetation cover and soil kjeldahl nitrogen were the main factors influencing fungal diversity. Our research provides a long-term perspective for better understanding and managing different grasslands, as well as a better scientific basis for future research on grass-soil-microbe interactions.

Integration of dosimetric parameters, clinical factors, and radiomics to predict symptomatic radiation pneumonitis in lung cancer patients undergoing combined immunotherapy and radiotherapy.

PURPOSE: This study aimed to combine clinical/dosimetric factors and handcrafted/deep learning radiomic features to establish a predictive model for symptomatic (grade ≥ 2) radiation pneumonitis (RP) in lung cancer patients who received immunotherapy followed by radiotherapy. MATERIALS AND METHODS: This study retrospectively collected data of 73 lung cancer patients with prior receipt of ICIs who underwent thoracic radiotherapy (TRT). Of these 73 patients, 41 (56.2 %) developed symptomatic grade ≥ 2 RP. RP was defined per multidisciplinary clinician consensus using CTCAE v5.0. Regions of interest (ROIs) (from radiotherapy planning CT images) utilized herein were gross tumor volume (GTV), planning tumor volume (PTV), and PTV-GTV. Clinical/dosimetric (mean lung dose and V5-V30) parameters were collected, and 107 handcrafted radiomic (HCR) features were extracted from each ROI. Deep learning-based radiomic (DLR) features were also extracted based on pre-trained 3D residual network models. HCR models, Fusion HCR model, Fusion HCR + ResNet models, and Fusion HCR + ResNet + Clinical models were built and compared using the receiver operating characteristic (ROC) curve with measurement of the area under the curve (AUC). Five-fold cross-validation was performed to avoid model overfitting. RESULTS: HCR models across various ROIs and the Fusion HCR model showed good predictive ability with AUCs from 0.740 to 0.808 and 0.740-0.802 in the training and testing cohorts, respectively. The addition of DLR features improved the effectiveness of HCR models (AUCs from 0.826 to 0.898 and 0.821-0.898 in both respective cohorts). The best performing prediction model (HCR + ResNet + Clinical) combined HCR & DLR features with 7 clinical/dosimetric characteristics and achieved an average AUC of 0.936 and 0.946 in both respective cohorts. CONCLUSIONS: In patients undergoing combined immunotherapy/RT for lung cancer, integrating clinical/dosimetric factors and handcrafted/deep learning radiomic features can offer a high predictive capacity for RP, and merits further prospective validation.

Diabetes and two kinds of primary tumors in a patient with thalassemia: a case report and literature review.

Background: Thalassemia is a group of common genetic hematologic disorders characterized by deficient synthesis of the hemoglobin chain. Due to effective blood transfusion and optimization of chelate therapy, the survival of thalassemia patients and their overall quality of life have improved noticeably in the past few decades. As a consequence, the longer life expectancy has led to the manifestation of several concomitant morbidities, including heart disease, infections, cirrhosis, endocrine abnormalities, various malignancies, and so on. In this context, the probability and updated literature about some malignancy cases in patients with thalassemia build new scenarios for the next few years. We describe the first report of a thalassemic patient developing diabetes and head and neck cancer and try to summarize the possible predisposing factors and mechanisms behind their phenomenon. Case presentation: The current case report describes a 50-year-old Asian man who has been diagnosed with thalassemia since childhood. In early 2017, he was also diagnosed with diabetes and started on insulin-hypoglycemic treatment. The patient was then diagnosed with primary non-keratinizing undifferentiated carcinoma of the nasopharynx in late February 2013. A biopsy of the left tongue revealed squamous cell carcinoma (SCC) in late March 2019. Conclusions: We report the first case of a thalassemic patient developing diabetes and squamous cell carcinoma of the head and neck and discuss the possibility of a link between the three diseases. This specific case should alert physicians to the possibility of endocrinopathy and malignancy in thalassemic patients.

Correlation between dynamic contrast-enhanced MRI characteristics and apparent diffusion coefficient with Ki-67-positive expression in non-mass enhancement of breast cancer.

As a remarkably specific characteristic of breast cancer observed on magnetic resonance imaging (MRI), the association between the NME type breast cancer and prognosis, including Ki-67, necessitates comprehensive exploration. To investigate the correlation between dynamic contrast-enhanced MRI (DCE-MRI) characteristics and apparent diffusion coefficient (ADC) values with Ki-67-positive expression in NME type breast cancer. A total of 63 NME type breast cancer patients were retrospectively reviewed. Malignancies were confirmed by surgical pathology. All patients underwent DCE and diffusion-weighted imaging (DWI) before surgery. DCE-MRI characteristics, including tumor distribution, internal enhancement pattern, axillary adenopathy, and time-intensity curve types were observed. ADC values and lesion sizes were also measured. The correlation between these features and Ki-67 expression were assessed using Chi-square test, Fisher's exact test, and Spearman rank analysis. The receiver operating characteristic curve and area under the curve (AUC) was used to evaluate the diagnostic performance of Ki-67-positive expression. Regional distribution, TIC type, and ipsilateral axillary lymph node enlargement were correlated with Ki-67-positive expression (χ2 = 0.397, 0.357, and 0.357, respectively; P < 0.01). ADC value and lesion size were positively correlated with Ki-67-positive expression (rs = 0.295, 0.392; P < 0.05). The optimal threshold values for lesion size and ADC value to assess Ki-67 expression were determined to be 5.05 (AUC = 0.759) cm and 0.403 × 10-3 s/mm2 (AUC = 0.695), respectively. The best diagnosis performance was the ADC combined with lesion size (AUC = 0.791). The ADC value, lesion size, regional distribution, and TIC type in NME type breast cancer were correlated with Ki-67-positive expression. These features will aid diagnosis and treatment of NME type breast cancer.

A radiomics nomogram analysis based on CT images and clinical features for preoperative Lauren classification in gastric cancer.

PURPOSE: To develop a combined radiomics nomogram based on computed tomography (CT) images and clinical features to preoperatively distinguish Lauren's diffuse-type gastric cancer (GC) from intestinal-type GC. METHODS: Ninety-five patients with Lauren's intestinal or diffuse-type GC confirmed by postoperative pathology had their preoperative clinical information and dynamic contrast CT images retrospectively analyzed and were subdivided into training and test groups in a 7:3 ratio. To select the optimal features and construct the radiomic signatures, we extracted, filtered, and minimized the radiomic features from arterial phase (AP) and venous phase (VP) CT images. We constructed four models (clinical model, AP radiomics model, VP radiomics model, and radiomics-clinical model) to assess and compare their predictive performance between the intestinal- and diffuse-type GC. Receiver-operating characteristic (ROC) curve, area under the ROC curve (AUC), and the DeLong test were used for assessment and comparison. In this study, radiomic nomograms integrating combined radiomic signatures and clinical characteristics were developed. RESULTS: Compared to the AP radiomics model, the VP radiomics model had better performance, with an AUC of 0.832 (95% confidence interval [CI], 0.735, 0.929) in the training cohort and 0.760 (95% CI 0.580, 0.940) in the test cohort. Among the combined models that assessed Lauren's type GC, the model including age and VP radiomics showed the best performance, with an AUC of 0.849 (95% CI 0.758, 0.940) in the training cohort and 0.793 (95% CI 0.629, 0.957) in the test cohort. CONCLUSIONS: Nomogram incorporating radiomic signatures and clinical features effectively differentiated Lauren's diffuse-type from intestinal-type GC.

Characterization of a polyamine microsphere and its adsorption for protein.

A novel polyamine microsphere, prepared from the water-in-oil emulsion of polyethylenimine, was characterized. The investigation of scanning electron microscopy showed that the polyamine microsphere is a regular ball with a smooth surface. The diameter distribution of the microsphere is 0.37-4.29 µm. The isoelectric point of the microsphere is 10.6. The microsphere can adsorb proteins through the co-effect of electrostatic and hydrophobic interactions. Among the proteins tested, the highest value of adsorption of microsphere, 127.8 mg·g-1 microsphere, was obtained with lipase. In comparison with other proteins, the hydrophobic force is more important in promoting the adsorption of lipase. The microsphere can preferentially adsorb lipase from an even mixture of proteins. The optimum temperature and pH for the selective adsorption of lipase by the microsphere was 35 °C and pH 7.0.

LncRNA CALML3-AS1 regulates chondrocyte apoptosis by acting as a sponge for miR-146a.

Chondrocyte apoptosis contributes to osteoarthritis, while miR-146a is a critical player in chondrocyte apoptosis. Our bioinformatics analysis showed that miR-146a may bind with long non-coding RNA (lncRNA) CALML3 antisense RNA 1 (CALML3-AS1). Our study was therefore carried out to investigate the interactions between lncRNA CALML3-AS1 and miR-146a in osteoarthritis. This study included 66 osteoarthritis patients who were admitted at Shanxi People's Hospital from July 2016 to June 2019. Transfections were performed to analyse gene interactions. RT-qPCR and Western blot were performed to determine the expression levels of gene and protein, respectively. Cell apoptosis of chondrocytes induced by lipopolysaccharide (LPS) was analysed by cell apoptosis assay. We found that CALML3-AS1 was downregulated, while miR-146a was upregulated in osteoarthritis. However, no significant correlation was found between them. In addition, overexpression of CALML3-AS1 or miR-146a did not affect the expression of each other. However, overexpression of CALML3-AS1 resulted in the upregulation of Smad family member 4 (Smad4), a downstream target of miR-146a. We also found that the expression of miR-146a and Smad4 were negatively correlated, while the correlation between CALML3-AS1 and smad4 was not significant. In cell apoptosis assay, overexpression of CALML3-AS1 and Smad4 resulted in decreased proliferation of chondrocytes. MiR-146a played an opposite role and reduced the effects of overexpression of CALML3-AS1 and Smad4. Therefore, CALML3-AS1 may regulate chondrocyte apoptosis by acting as a sponge for miR-146a to upregulate Smad4.

Dosimetric Risk Factors for Acute Radiation Pneumonitis in Patients With Prior Receipt of Immune Checkpoint Inhibitors.

Purpose: Dosimetric parameters (e.g., mean lung dose (MLD), V20, and V5) can predict radiation pneumonitis (RP). Constraints thereof were formulated before the era of combined immune checkpoint inhibitors (ICIs) and radiotherapy, which could amplify the RP risk. Dosimetric predictors of acute RP (aRP) in the context of ICIs are urgently needed because no data exist thus far. Methods and Materials: All included patients underwent thoracic intensity-modulated radiotherapy, previously received ICIs, and followed-up at least once. Logistic regression models examined predictors of aRP (including a priori evaluation of MLD, V20, and V5), and their discriminative capacity was assessed by receiver operating characteristic analysis. Results: Median follow-up of the 40 patients was 5.3 months. Cancers were lung (80%) or esophageal (20%). ICIs were PD-1 (85%) or PD-L1 (15%) inhibitors (median 4 cycles). Patients underwent definitive (n=19), consolidative (n=14), or palliative (n=7) radiotherapy; the median equivalent dose in 2 Gy fractions (EQD2) was 60 Gy (IQR, 51.8-64 Gy). Grades 1-5 aRP occurred in 25%, 17.5%, 15%, 2.5%, and 5%, respectively. The only variables associated with any-grade aRP were V20 (p=0.014) and MLD (p=0.026), and only V20 with grade ≥2 aRP (p=0.035). Neither the number of prior ICI cycles nor the delivery of concurrent systemic therapy significantly associated with aRP risk. Graphs were constructed showing the incrementally increasing risk of aRP based on V20 and MLD (continuous variables). Conclusions: This is the first study illustrating that V20 and MLD may impact aRP in the setting of prior ICIs. However, these data should not be extrapolated to patients without pre-radiotherapy receipt of prior ICIs, or to evaluate the risk of chronic pulmonary effects. If these results are validated by larger studies with more homogeneous populations, the commonly accepted V20/MLD dose constraints could require revision if utilized in the setting of ICIs.

Selenium Deficiency-Induced Damage and Altered Expression of Mitochondrial Biogenesis Markers in the Kidneys of Mice.

Previous studies have raised concerns that kidney disease is often closely related to low serum Se levels in patients and that hyposelenemia may increase the vulnerability of patients to complications. However, few studies examining renal injury caused by Se deficiency have been conducted. To determine the effects of a selenium-deficient diet on renal function, a mouse model was fed a selenium-deficient diet (0.02 mg Se/kg) for 20 weeks. Meanwhile, mice in the control group (selenium-adequate) were fed a standard diet (0.18 mg Se/kg). The cellular models were established by lentiviral Trnau1ap-shRNA vectors transfected into mouse podocyte (MPC5) and mouse renal tubular epithelial (TCMK1) cell lines. Significant increases in serum creatinine levels and urinary protein/creatinine ratios were accompanied by increased MDA content in the Se-deficient group compared to the control group. The morphological observations of tissues showed widespread inflammation and ultrastructural changes in the Se-deficient group, such as swollen mitochondria and extensive podocyte fusion and renal tubular microvilli shedding. In addition, the expression of COXIV and cytochrome c was significantly downregulated in the Se-deficient group. Importantly, the mRNA levels of silent mating type information regulation 2 homolog 1 (SIRT1) and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) and the protein levels of SIRT1 were increased in the Se-deficient group compared with the normal control group. Our data indicate that Se deficiency induces renal injury in mice. The elevated oxidative stress caused by Se deficiency may result in mitochondrial damage, which might affect renal function. Moreover, the SIRT1/PGC1α axis likely plays an important role in the compensatory mechanism of mitochondrial dysfunction.

miR-22 inhibits synovial fibroblasts proliferation and proinflammatory cytokine production in RASF via targeting SIRT1.

BACKGROUND/AIMS: Rheumatoid arthritis synovial fibroblasts (RASF) play an essential role in the pathogenesis of rheumatoid arthritis (RA). This study aimed to investigate the biological effects of miR-22 on RASFs. METHODS: RT-qPCR was used to detect the expressions of miR-22 and SIRT1 in RA synovial tissue. The results of miR-22 on the proliferation of RASF were examined by MTT assay. The effects of miR-22 on the secretion of TNF-α, IL-1ß, and IL-6 in RASF were measured by ELISA. Target gene prediction and screening, and luciferase reporter assay were used to testify downstream target genes of miR-22. RT-qPCR and western blotting were used to detect the mRNA and protein expression of SIRT1. RESULTS: miR-22 was significantly decreased in RA synovial tissue, while SIRT1 was significantly increased in RA synovial tissue. Over-expression of miR-22 significantly inhibited the proliferation of RASFs and the secretions of inflammatory cytokines (TNF-α, IL-1ß, and IL-6) in RASFs. SIRT1 was identified as a direct target of miR-22. Over-expression of miR-22 reduced the expression level of SIRT1 in RASFs. Over-expression of SIRT1 reversed the effect of miR-22 on the proliferation of RASFs and the secretion of inflammatory cytokines. CONCLUSION: MIR-22 was significantly down-regulated in RASF cells, which affected the secretions of inflammatory cytokines and cell proliferation by regulating SIRT1.