Meta-analysis of Palliative Care on End-stage Quality of Life in Cancer Patients.

Objective: This study aimed to investigate the impact of palliative care on the quality of life, depressive state, and physical and psychological symptoms of patients with end-stage cancer. Methods: A systematic literature search of PubMed, Embase, and Scopus databases was conducted for randomized controlled trials (RCTs) published from May 2000 to June 2023, focusing on the impact of palliative care on end-stage cancer patients. The search utilized terms such as "palliative care," "cancer/tumor/malignancy," "terminal/end-stage/advanced," to identify studies meeting our inclusion criteria. Selected RCTs were evaluated for quality, and relevant data were extracted for meta-analysis. Results: Meta-analysis of 16 RCTs revealed that palliative care significantly improved depressive states [OR=-0.88, 95%CI (-1.55, -0.20), P = .01] and alleviated physical and psychological symptoms [OR=-2.38, 95%CI (-3.95, -0.81), P = .003] in end-stage cancer patients compared to conventional oncology care. However, the improvement in overall quality of life was not statistically significant (P > .05). Conclusion: Palliative care significantly enhances the mental and physical well-being of end-stage cancer patients by reducing depressive states and symptom burden, although its impact on overall quality of life requires further exploration.

Impact of Halogen Bonds on Protein-Peptide Binding and Protein Structural Stability Revealed by Computational Approaches.

Halogen bonds (XBs) are essential noncovalent interactions in molecular recognition and drug design. Current studies on XBs in drug design mainly focus on the interactions between halogenated ligands and target proteins, lacking a systematic study of naturally existing and artificially prepared halogenated residue XBs (hr_XBs) and their characteristics. Here, we conducted a computational study on the potential hr_XBs in proteins/peptides using database searching, quantum mechanics calculations, and molecular dynamics simulations. XBs at the protein-peptide interaction interfaces are found to enhance their binding affinity. Additionally, the formation of intramolecular XBs (intra_XBs) within proteins may significantly contribute to the structural stability of structurally flexible proteins while having a minor impact on proteins with inherently high structural rigidity. Impressively, introducing halogens without the formation of intra_XBs may lead to a decrease in the protein structural stability. This study enriches our understanding of the roles and effects of halogenated residue XBs in biological systems.

Automatic segmentation of the gross target volume in radiotherapy for lung cancer using transresSEUnet 2.5D Network.

OBJECTIVE: This paper intends to propose a method of using TransResSEUnet2.5D network for accurate automatic segmentation of the Gross Target Volume (GTV) in Radiotherapy for lung cancer. METHODS: A total of 11,370 computed tomograms (CT), deriving from 137 cases, of lung cancer patients under radiotherapy developed by radiotherapists were used as the training set; 1642 CT images in 20 cases were used as the validation set, and 1685 CT images in 20 cases were used as the test set. The proposed network was tuned and trained to obtain the best segmentation model and its performance was measured by the Dice Similarity Coefficient (DSC) and with 95% Hausdorff distance (HD95). Lastly, as to demonstrate the accuracy of the automatic segmentation of the network proposed in this study, all possible mirrors of the input images were put into Unet2D, Unet2.5D, Unet3D, ResSEUnet3D, ResSEUnet2.5D, and TransResUnet2.5D, and their respective segmentation performances were compared and assessed. RESULTS: The segmentation results of the test set showed that TransResSEUnet2.5D performed the best in the DSC (84.08 ± 0.04) %, HD95 (8.11 ± 3.43) mm and time (6.50 ± 1.31) s metrics compared to the other three networks. CONCLUSIONS: The TransResSEUnet 2.5D proposed in this study can automatically segment the GTV of radiotherapy for lung cancer patients with more accuracy.

Case report: Moderate therapeutic response to Bevacizumab in late-onset Labrune syndrome.

Labrune syndrome (LS) is caused by SNORD118 gene mutations with a particular neuroimaging of white matter disease, intracranial calcification, and cysts. There was no effective treatment until now. An 18-year-old man with infancy-onset LS was first treated with vascular endothelial growth factor (VEGF) inhibitor Bevacizumab for 1 year, resulting in significant clinical and radiological improvements. We adopted a similar regimen in a patient with late-onset LS and demonstrated moderate cognitive improvements but without changes in imaging. As such, Bevacizumab could potentially be clinically effective in adult-onset LS with great safety.

Exploration of the Potential Link, Hub Genes, and Potential Drugs for Coronavirus Disease 2019 and Lung Cancer Based on Bioinformatics Analysis.

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has a huge influence on global public health and the economy. Lung cancer is one of the high-risk factors of COVID-19, but the molecular mechanism of lung cancer and COVID-19 is still unclear, and further research is needed. Therefore, we used the transcriptome information of the public database and adopted bioinformatics methods to identify the common pathways and molecular biomarkers of lung cancer and COVID-19 to further understand the connection between them. The two RNA-seq data sets in this study-GSE147507 (COVID-19) and GSE33532 (lung cancer)-were both derived from the Gene Expression Omnibus (GEO) database and identified differentially expressed genes (DEGs) for lung cancer and COVID-19 patients. We conducted Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis and found some common features between lung cancer and COVID-19. We also performed TFs-gene, miRNAs-gene, and gene-drug analyses. In total, 32 DEGs were found. A protein-protein interaction (PPI) network was constructed by DEGs, and 10 hub genes were screened. Finally, the identified drugs may be helpful for COVID-19 treatment.

Construction of a predictive model for radiation proctitis after radiotherapy for female pelvic tumors based on machine learning. / åŸºäºŽæœºå™¨å­¦ä¹ æž„å»ºå¥³æ€§ç›†è ”è‚¿ç˜¤æ”¾å°„æ²»ç–—åŽæ”¾å°„æ€§ç›´è‚ ç‚Žçš„é¢„æµ‹æ¨¡åž‹.

OBJECTIVES: Radiation therapy is a main method for female pelvic malignancies, which can cause some adverse reactions, such as radiation proctitis (RP). The incidence of RP is highly positively correlated with radiation dose. There is an urgent need for a scientific method to accurately predict the occurrence of RP to help doctors make clinical decisions. In this study, based on the clinical data of female pelvic tumor patients and dosimetric parameters of radiotherapy, the random forest method was used to screen the hub features related to the occurrence of RP, and then a machine learning algorithm was used to construct a risk prediction model for the occurrence of RP, in order to provide technical support and theoretical basis for the prediction and prevention of RP. METHODS: A total of 100 female patients with pelvic tumors, who received static three-dimensional conformal intensity-modulated radiation therapy in the Department of Radiation Oncology of the Affiliated Hospital of Xiangnan University from January 2019 to December 2020, were retrospectively collected, and their clinically relevant data and radiotherapy planning system data were collected. During radiotherapy and 18 months after radiotherapy, 35 cases developed RP (RP group), and the remaining 65 cases had no RP (non-RP group). The clinical and dosimetric characteristics of patients were ranked by the importance of random forest algorithm, and the independent prognostic characteristics associated with the occurrence of RP were selected for machine learning modeling. A total of 6 machine learning algorithms including support vector machines, random forests, logistic regression, lightweight gradient boosting machines, Gaussian naïve Bayes, and adaptive enhancement were used to build models. The performance of the model was evaluated by the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score. Finally, the random forest model was determined as the prediction model, and the calibration curve and decision curve of the prediction model were drawn to evaluate the accuracy and clinical benefit of the model. RESULTS: The parameters for random forest prediction model in the training set were as follow: AUC, 1.000, accuracy, 0.988, sensitivity, 1.000, specificity, 1.000, positive predictive value, 1.000, negative predictive value, 0.981, and F1 score, 1.000. In validation set, AUC was 0.713, accuracy was 0.640, sensitivity was 0.618, specificity was 0.822, positive predictive value was 0.500, negative predictive value was 0.656, and F1 score was 0.440. Random forest showed high predictive performance. Moreover, the Brief of the calibration curve for the prediction model was 0.178, the prediction accuracy was high, and the decision curve showed that the prediction model could benefit clinically. CONCLUSIONS: Based on the clinical and dosimetric parameters for the female pelvic tumor patients, the prediction model of radiation proctitis constructed by random forest algorithm has high predictive ability and strong clinical usability.

Application of intracavitary ECG for positioning the totally implantable venous access port in the upper arm of cancer patients.

Accurate positioning of the catheter tip is one of the most critical procedures in central venous catheter insertion. The traditional surface measurement method frequently has a large deviation and increases the X-ray exposure of doctors and patients. In the present retrospective study, cancer patients who received a totally implantable venous access port (TIVAP) in the upper arm using intracavitary electrocardiogram (ECG) guidance were compared with those where the traditional surface measurement method was used in terms of the rate of correct placement of the catheter tip, the rate of achieving the best position, the operation time and the complications. The results indicated that the correct placement rate and the best position rate of the catheter tip at the first attempt were higher in the ECG-guided group than in the traditional surface measurement method group (95.65 vs. 82.91% and 90.58 vs. 68.38%, respectively). The mean operation time was shorter in the ECG-guided group than in the surface measurement group (46.28 vs. 63.26 min). The incidence of complications in the ECG-guided group was 6.52%, while that in the surface measurement group was 10.26%. This indicated that the intracavitary ECG-guided tip positioning technique may improve the accuracy of tip catheter placement and shorten the operation time, thus reducing ionizing radiation caused by repeated positioning. Therefore, the intracavitary ECG-guided tip positioning technique is able to effectively place the tip of the TIVAD in the upper arm, holding great promise as a clinical application.

[Experimental study on the regulation of subchondral bone plate osteoprotegerin/receptor activator of nuclear factor kappa-B ligand system by berberine to retard the development of osteoarthritis in rabbits].

OBJECTIVE: To investigate the effect of intra-articular berberine injection on the structural remodeling of subchondral bone plate and osteoprotegerin/receptor activator of nuclear factor kappa-B ligand(OPG/RANKL) system expression in rabbits with osteoarthritis(OA). METHODS: Forty 12-month-old male rabbits with an average of(2.73±0.18) kg of body weight, underwent left anterior cruciate ligament transection(ACLT), and were divided into berberine group and placebo groups after operation, 20 rabbits in each group. The berberine group received intra-articular injection of 100 µmol/L berberine 0.3 ml every week for 6 weeks. In placebo group, the same dose of 0.9% sodium chloride injection was injected into the left knee joint cavity every week for 6 weeks. Another 20 12-month-old male rabbits, weighing (2.68±0.18) kg, underwent sham operation on the left knee joint without intra-articular injection intervention (sham operation group). On the last day of the sixth week after operation, three groups of animals were sacrificed to obtain knee joint specimens. The femoral medial condyle samples were obtained for histological evaluation of cartilage and subchondral bone, Mankin scoring system was used to evaluate articular cartilage structure. Image-Pro Plus(IPP) software was used to evaluate subchondral bone plate bone volume(BV), bone volume/total volume(BV/TV), trabecular circumference(TC), mean trabecular thickness (Tb.Th). Real-time quantitative reverse transcription polymerization Enzyme chain reaction(reverse transcription-polymerase chain reaction, RT-PCR) was used to detect the mRNA expression levels of OPG and RANKL in subchondral bone tissue at 6 weeks after operation. RESULTS: The cartilage structure evaluation showed that the surface of cartilage tissue in the sham operation group was smooth and flat, and the safranin coloration was full in the full thickness of the cartilage;the cartilage tissue in the berberine group showed uneven surface layer, and the staining of safranin O was mildly decreased;the surface layer fibrosis was seen in placebo group, Safranin O faded significantly. The Mankin score in the berberine group was lower than that in placebo group(P<0.01), but higher than that in sham operation group(P<0.01). The structural evaluation of subchondral bone plate showed that the trabecular bone in sham-operated group was densely arranged;after berberine intervention, the trabeculae were closely arranged;the subchondral bone trabeculae in placebo group were relatively sparse, and the distance between trabeculae was wider. Subchondral bone plate IPP software evaluation showed that BV, BV/TV, TC, Tb.Th in berberine group were higher than those in placebo group(P<0.01), BV, BV/TV, TC, Tb.Th in berberine group were higher than those in placebo group(P<0.01), while lower than the sham operation group (P<0.01). PCR test results showed that the expression of OPG mRNA in the berberine group was significantly higher than that in placebo group(P<0.01), and OPG mRNA in the berberine group was lower than that in sham operation group (P<0.01). There was no significant difference in mRNA expression of RANKL among three groups(P>0.05);the ratio of OPG/RANKL in berberine group was higher than that in placebo group(P<0.01), but lower than that in sham operation group(P<0.01). CONCLUSION: Intra-articular injection of berberine can effectively inhibit the resorption of subchondral bone in the early stage of OA and delay the development of the disease. The specific mechanism may be that berberine maintains the balance of OPG/RANKL system by up-regulating the expression of OPG gene in subchondral bone.

Grain Boundary-Derived Cu+ /Cu0 Interfaces in CuO Nanosheets for Low Overpotential Carbon Dioxide Electroreduction to Ethylene.

Electrochemical CO2 reduction reaction can be used to produce value-added hydrocarbon fuels and chemicals by coupling with clean electrical energy. However, highly active, selective, and energy-efficient CO2 conversion to multicarbon hydrocarbons, such as C2 H4 , remains challenging because of the lack of efficient catalysts. Herein, an ultrasonication-assisted electrodeposition strategy to synthesize CuO nanosheets for low-overpotential CO2 electroreduction to C2 H4 is reported. A high C2 H4 Faradaic efficiency of 62.5% is achieved over the CuO nanosheets at a small potential of -0.52 V versus a reversible hydrogen electrode, corresponding to a record high half-cell cathodic energy efficiency of 41%. The selectivity toward C2 H4 is maintained for over 60 h of continuous operation. The CuO nanosheets are prone to in situ restructuring during CO2 reduction, forming abundant grain boundaries (GBs). Stable Cu+ /Cu0 interfaces are derived from the low-coordinated Cu atoms in the reconstructed GB regions and act as highly active sites for CO2 reduction at low overpotentials. In situ Raman spectroscopic analysis and density functional theory computation reveal that the Cu+ /Cu0 interfaces offer high *CO surface coverage and lower the activation energy barrier for *CO dimerization, which, in synergy, facilitates CO2 reduction to C2 H4 at low overpotentials.

Age-specific prevalence and genotype distribution of human papillomavirus in women from Northwest China.

BACKGROUND: Human papillomavirus (HPV) is the leading cause of cervical cancer with more than 200 genotypes. Different genotypes have different potentials in causing premalignant lesions and cervical cancers. In this study, we investigated the age-specific prevalence and genotype distribution of HPV genotypes in Northwest China. MATERIALS AND METHODS: We recruited 145,918 unvaccinated women from Northwest China for population-based HPV DNA screening test during June 2015 to December 2020. And a lab-based test was performed for each volunteer by flow fluorescent technology to identify the genotypes of HPV. RESULTS: The overall infection rate of HPV was 22.97%. With the participants divided into 12 groups according to age, a bimodal curve of infection rate was obtained. And the two peaks appeared in the younger than 20 group and 61-65 group, respectively. The five most common HPV genotypes included HPV 16, 58, 52, 53 and 61 in all participants, which were in descending order of frequency. Among women younger than 25 years old, HPV 6 and 11 were more common and even higher than some genotypes mentioned above. Among women older than 65 years old, HPV 18 and 66 were more common than or as high as the six most common genotypes in all populations. Additionally, the distribution of single and multiple infections in each age group was also different. CONCLUSION: The baseline prevalence and genotype distribution of HPV in Northwest China was uncovered for the first time. Age was related to the epidemiology of different HPV genotypes. All the results would be of great significance for future healthcare services.

Inhibition of Nicotinamide adenine dinucleotide phosphate oxidase 4 attenuates cell apoptosis and oxidative stress in a rat model of polycystic ovary syndrome through the activation of Nrf-2/HO-1 signaling pathway.

Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disorder in reproductive-aged women. In this study, a rat model of PCOS was established by subcutaneous injection of dehydroepiandrosterone (DHEA). NOX4 was highly expressed in PCOS rat ovaries, while its specific role in PCOS remains unclear. Lentivirus-mediated shRNA targeting NOX4 inhibited oxidative stress by reducing ROS, 4-HNE and MDA levels, and increasing SOD and GPX activities in rat ovaries. NOX4 deficiency increased Bcl-2 levels and decreased Bax, cleaved caspase-3 and cleaved caspase-9 levels and DHEA-induced cell apoptosis in rat ovaries. Similar to the in vivo results, NOX4 silencing inhibited oxidative stress and cell apoptosis in DHEA-treated rat granulosa cells. Moreover, NOX4 silencing promoted Nrf-2 translocation, and the expression of Nrf-2 and HO-1 both in vivo and in vitro. Thus, NOX4 deficiency may ameliorate PCOS in rats by reducing oxidative stress and cell apoptosis via activating the Nrf-2/HO-1 signal pathway.

Identification of Immune-Related lncRNA Pairs and Construction and Validation of a New Prognostic Signature of Colon Cancer.

Background: More and more evidence has shown that immune-related long noncoding ribonucleic acid (irlncRNAs) is a potential prognostic factor for colon cancer. The relevant gene pair pattern can improve the sensitivity of the prognostic model. Therefore, our present study aimed to identify irlncRNA Pairs and construct and validate a new prognostic signature in colon cancer. Methods: We downloaded the expression matrix of mRNA and lncRNA of patients with colon cancer and their clinical information from the public TCGA database. We obtained immune genes from the ImmPort database. Coexpression analysis was performed to identify irlncRNAs. We built an irlncRNA pair matrix by comparing the expression levels of each lncRNA pair in a cycle. Univariate Cox regression analysis, LASSO penalized regression analysis, and multivariate Cox regression analysis were performed to determine the final variables to construct the prognostic risk score model (a new signature). We draw the receiver operating characteristic (ROC) curves of the signature and clinical characteristics and determine the optimal cutoff value by the optimal Akaike Information Criterion (AIC) value. Based on the optimal cutoff value of the ROC curve of the signature, colon cancer patients were divided into the high- and low-risk groups. Then, the signature was evaluated by clinicopathological features, tumor-infiltrating immune cells, checkpoint-related biomarkers, targeted therapy, and chemotherapy. Results: We identified 8 lncRNA pairs including AC103740.1|LEF1-AS1, LINC02391|AC053503.5, WWC2-AS2|AL355916.2, AC104090.1|NEURL1-AS1, AC099524.1|AL161908.1, AC074011.1|AL078601.2, AL355916.2|LINC01723, and AP003392.4|LINC00598 from 71 differently expressed irlncRNAs. We constructed a prognostic risk score model (a new signature) using these optimal eight irlncRNA pairs. ROC curve analysis revealed that the highest AUC value of the signature was 0.776 at 1 year, with the optimal cutoff value of 1.283. Our present study also showed that the constructed signature could accurately identify adverse survival outcomes, prognostic clinicopathological features, and specify tumor invasion status. The expression of immune checkpoint-related genes and chemical drug sensitivity were related to different risk groups. Conclusion: In our present study, we constructed a new irlncRNA signature of colon cancer based on the irlncRNA pairs instead of the special expression level of lncRNA. We found this signature had not only good prognostic value but also certain clinical value, which might provide a new insight into the treatment and prognosis of colon cancer.

Development and Validation of an Inflammatory Response-Related Gene Signature for Predicting the Prognosis of Pancreatic Adenocarcinoma.

Pancreatic adenocarcinoma (PAAD) is a highly dangerous malignant tumor of the digestive tract, and difficult to diagnose, treat, and predict the prognosis. As we all know, tumor and inflammation can affect each other, and thus the inflammatory response in the microenvironment can be used to affect the prognosis. So far, the prognostic value of inflammatory response-related genes in PAAD is still unclear. Therefore, this study aimed to explore the inflammatory response-related genes for predicting the prognosis of PAAD. In this study, the mRNA expression profiles of PAAD patients and the corresponding clinical characteristics data of PAAD patients were downloaded from the public database. The least absolute shrinkage and selection operator (LASSO) Cox analysis model was used to identify and construct the prognostic gene signature in The Cancer Genome Atlas (TCGA) cohort. The PAAD patients used for verification are from the International Cancer Genome Consortium (ICGC) cohort. The Kaplan-Meier method was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were performed to identify the independent predictors of OS. Gene set enrichment analysis (GSEA) was performed to obtain gene ontology (GO) terms and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and the correlation between gene expression and immune infiltrates was investigated via single sample gene set enrichment analysis (ssGSEA). The GEPIA database was performed to examine prognostic genes in PAAD. LASSO Cox regression analysis was used to construct a model of inflammatory response-related gene signature. Compared with the low-risk group, patients in the high-risk group had significantly lower OS. The receiver operating characteristic curve (ROC) analysis confirmed the signature's predictive capacity. Multivariate Cox analysis showed that risk score is an independent predictor of OS. Functional analysis shows that the immune status between the two risk groups is significantly different, and the cancer-related pathways were abundant in the high-risk group. Moreover, the risk score is significantly related to tumor grade, stage, and immune infiltration types. It was also obtained that the expression level of prognostic genes was significantly correlated with the sensitivity of cancer cells to anti-tumor drugs. In addition, there are significant differences in the expression of PAAD tissues and adjacent non-tumor tissues. The novel signature constructed from five inflammatory response-related genes can be used to predict prognosis and affect the immune status of PAAD. In addition, suppressing these genes may be a treatment option.

Development of a Prognostic Nomogram for Patients with Lung Adenocarcinoma in the Stages I, II, and III Based on Immune Scores.

BACKGROUND: Immunotherapy has significantly changed the treatment prospects of non-small cell lung cancer (NSCLC). However, there is no report based on immune score to predict the overall survival (OS) of lung adenocarcinoma (LUAD) in the stages I, II, and III. Therefore, this study aimed to investigate the immune score and the prognosis-related factors of LUAD and construct a nomogram to predict the prognosis. METHODS: A total of 390 cases with lung adenocarcinoma in the stages I, II, and III were included in the study. The clinicopathological characteristics and immune scores of LUAD patients were downloaded from the TCGA database. Cox proportional hazards regression model was used to estimate hazard ratio (HR) and 95% confidence interval (CI). A Nomogram was composed of the Cox model and internally validated using 1000 bootstrap. The concordance index (c-index) and the calibration curves were used to evaluate the model. The decision curve analysis (DCA) was performed to evaluate the clinical practical value of the model. RESULTS: According to the immune score, the patients were divided into low-, medium-, and high-score groups. This study showed that compared with patients with low and medium immune scores, only patients with high immune scores had significantly improved OS (HR and 95% confidence interval (CI): 0.489 [0.324-0.737]). The C-index for OS prediction was 0.691 (95% CI, 0.646-0.736). The calibration curves for nomogram-predicted probabilities of 3- and 5-year survival have good ability for the calibration and discrimination. CONCLUSION: The high immune score was significantly correlated with better OS of patients with LUAD in the stages I, II, and III. Moreover, the nomogram of predicting prognosis may help assess the survival of LUAD patients.

Application of Deep Convolution Network to Automated Image Segmentation of Chest CT for Patients With Tumor.

OBJECTIVES: To automate image delineation of tissues and organs in oncological radiotherapy by combining the deep learning methods of fully convolutional network (FCN) and atrous convolution (AC). METHODS: A total of 120 sets of chest CT images of patients were selected, on which radiologists had outlined the structures of normal organs. Of these 120 sets of images, 70 sets (8,512 axial slice images) were used as the training set, 30 sets (5,525 axial slice images) as the validation set, and 20 sets (3,602 axial slice images) as the test set. We selected 5 published FCN models and 1 published Unet model, and then combined FCN with AC algorithms to generate 3 improved deep convolutional networks, namely, dilation fully convolutional networks (D-FCN). The images in the training set were used to fine-tune and train the above 8 networks, respectively. The images in the validation set were used to validate the 8 networks in terms of the automated identification and delineation of organs, in order to obtain the optimal segmentation model of each network. Finally, the images of the test set were used to test the optimal segmentation models, and thus we evaluated the capability of each model of image segmentation by comparing their Dice coefficients between automated and physician delineation. RESULTS: After being fully tuned and trained with the images in the training set, all the networks in this study performed well in automated image segmentation. Among them, the improved D-FCN 4s network model yielded the best performance in automated segmentation in the testing experiment, with an global Dice of 87.11%, and a Dice of 87.11%, 97.22%, 97.16%, 89.92%, and 70.51% for left lung, right lung, pericardium, trachea, and esophagus, respectively. CONCLUSION: We proposed an improved D-FCN. Our results showed that this network model might effectively improve the accuracy of automated segmentation of the images in thoracic radiotherapy, and simultaneously perform automated segmentation of multiple targets.

Curcumin Antagonizes Glucose Fluctuation-Induced Renal Injury by Inhibiting Aerobic Glycolysis via the miR-489/LDHA Pathway.

It has been considered that glucose fluctuation (GF) plays a role in renal injury and is related to diabetic nephropathy (DN) development. But the mechanism is still unclear. Aerobic glycolysis has become a topical issue in DN in recent years. There is an internal connection between GF, aerobic glycolysis, and DN. Curcumin (Cur) is a principal curcuminoid of turmeric and possesses specific protective properties in kidney functions. Cur also participates in the regulation of aerobic glycolysis switch. In this study, we first measured the levels of aerobic glycolysis and evaluated Cur's inhibitory ability in a cell model of HEK-293 under the condition of oscillating high glucose. The results indicated that GF exacerbated inflammation injury, oxidative stress, and apoptosis in HEK-293 cell, while Cur alleviated this cytotoxicity induced by GF. We found that GF increased aerobic glycolysis in HEK-293 cells and Cur presented a dose-dependent weakening effect to this exacerbation. Next, we built a panel of 17 miRNAs and 8 lncRNAs that were previously reported to mediate the Warburg effect. Our RT-qPCR results indicated that GF reduced the miR-489 content in the HEK-293 cell model and Cur could prevent this downregulation. Then, we planned to explore the character of miR-489 in Cur-triggered attenuation of the Warburg effect under GF condition. Our findings presented that Cur prevented GF-triggered aerobic glycolysis by upregulating miR-489 in HEK-293 cells. Next, we choose the miR-489/LDHA axis for further investigation. We confirmed that Cur prevented GF-triggered aerobic glycolysis via the miR-489/LDHA axis in HEK-293 cells. In conclusion, this study presented that Cur prevented GF-triggered renal injury by restraining aerobic glycolysis via the miR-489/LDHA axis in the HEK-293 cell model.

Reconstructing two-dimensional defects in CuO nanowires for efficient CO2 electroreduction to ethylene.

Here we report that in situ reconstructed Cu two-dimensional (2D) defects in CuO nanowires during CO2RR lead to significantly enhanced activity and selectivity of C2H4 compared to the CuO nanoplatelets. Specifically, the CuO nanowires achieve high faradaic efficiency of 62% for C2H4 and a partial current density of 324 mA cm-2 yet at a low potential of -0.56 V versus a reversible hydrogen electrode. Structural evolution characterization and in situ Raman spectra reveal that the high yield of C2H4 on CuO nanowires is attributed to the in situ reduction of CuO to Cu followed by structural reconstruction to form 2D defects, e.g., stacking faults and twin boundaries, which improve the CO production rate and *CO adsorption strength. This finding may provide a paradigm for the rational design of nanostructured catalysts for efficient CO2 electroreduction to C2H4.

Identification of key genes in the tumor microenvironment of lung adenocarcinoma.

The tumor microenvironment plays an important role in tumor development and progression, but the role of immune and stromal cells in this environment has not been sufficiently studied. In this study, we aimed to identify key genes associated with the microenvironment of lung adenocarcinoma (LUAD). Raw data for stromal and immune cells in malignant tumors were downloaded from The Cancer Genome Atlas (TCGA). These expression data were used to identify the differentially expressed genes (DEGs) in tissue samples of LUAD with high and low immune scores. A protein-protein interaction (PPI) network based on genes with significant differential expression was constructed. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to functionally annotate putative hub genes. These genes were assessed via Kaplan Meier analysis to determine their correlation with overall survival. In total, we identified 216 DEGs which were correlated with immune and stromal scores, including 30 hub genes which were identified based on the PPI network. Further analysis suggested that the expression levels of 10 of these genes were significantly correlated with overall survival of LUAD patients. These key hub genes included CCR2, CCR5, CD53, CYBB, HCK, IRF8, LCP2, PLEK, PTPRC, and TLR7. Moreover, the expression level of CCR2 was found to have strong prognostic value for LUAD patients. Additionally, high expression of CYBB was also correlated with better survival of patients with LUAD. The results of this study open several new avenues to explore in the treatment of LUAD.

Screening and Identification of a Specific Binding Peptide to Ovarian Cancer Cells from a Phage-Displayed Peptide Library.

To select specific binding peptides for imaging and detection of human ovarian cancer. The phage 12-mer peptide library was used to select specific phage clones to ovarian cancer cells. After four rounds of biopanning, the binding specificity of randomly selected phage clones to ovarian cancer cells was determined by enzyme-linked immunosorbent assay (ELISA). DNA sequencing and homology analysis were performed on specifically bound phages. The binding ability of the selected peptides to SKOV3 cells was confirmed by fluorescence microscopy and flow cytometry. After four rounds of optimized biological panning, phage recovery was 34-fold higher than that of the first round, and the specific phage clones bound to SKOV3 cells were significantly enriched. A total of 32 positive phage clones were preliminarily identified by ELISA from 54 randomly selected clones, and the positive rate was 59.3%. S36 was identified as the clone with best affinity to SKOV3 cells via fluorescence microscopy and flow cytometry. A representative clone of OSP2, S36 is expected to be an effective probe for diagnosis and treatment of ovarian cancer.

Identification and analysis of genes associated with lung adenocarcinoma by integrated bioinformatics methods.

Lung adenocarcinoma (LUAD) is one of the most common forms of lung cancer, with a very high mortality rate. Although the treatments available for LUAD have become more effective in recent years, significant improvement is still needed. Advances in sequencing technologies and bioinformatics analysis have enabled new approaches to be developed for identifying drug targets. In this work we utilized data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to identify hub genes related to LUAD through Weighted Gene Correlation Network Analysis (WGCNA) and other bioinformatics methods, with the goal of identifying new drug targets for cancer treatment.