FUS-stabilized USP35 promotes growth, invasion and angiogenesis in NSCLC through deubiquitinating VEGFA.

Vascular endothelial growth factor A (VEGFA) is an important regulator for non-small cell lung cancer (NSCLC). Our study aimed to reveal its upstream pathway to provide new ideas for developing the therapeutic targets of NSCLC. The mRNA and protein levels of VEGFA, ubiquitin-specific peptidase 35 (USP35), and FUS were determined by quantitative real-time PCR and Western blot. Cell proliferation, apoptosis, invasion and angiogenesis were detected using CCK8 assay, EdU assay, flow cytometry, transwell assay and tube formation assay. The interaction between USP35 and VEGFA was assessed by Co-IP assay and ubiquitination assay. Animal experiments were performed to assess USP35 and VEGFA roles in vivo. VEGFA had elevated expression in NSCLC tissues and cells. Interferences of VEGFA inhibited NSCLC cell proliferation, invasion, angiogenesis, and increased apoptosis. USP35 could stabilize VEGFA protein level by deubiquitination, and USP35 knockdown suppressed NSCLC cell growth, invasion and angiogenesis via reducing VEGFA expression. FUS interacted with USP35 to promote its mRNA stability, thereby positively regulating VEGFA expression. Also, USP35 silencing could reduce NSCLC tumorigenesis by downregulating VEGFA. FUS-stabilized USP35 facilitated NSCLC cell growth, invasion and angiogenesis through deubiquitinating VEGFA, providing a novel idea for NSCLC treatment.

Research on the characteristics of electro-hydraulic position servo system of RBF neural network under fuzzy rules.

A radial basis function neural network PID controller under fuzzy rules (FUZZY-RBF-PID) was designed for the electro-hydraulic position servo system under the influence of uncertain factors such as load mutation, and load stiffness change. Firstly, the mathematical model of the system is established, and the frequency domain and time domain analysis of the system are carried out. Secondly, based on the analysis results, a radial basis function (RBF) neural network PID controller is designed, and fuzzy rules are innovatively used to adjust the learning rate of PID parameters in the RBF neural network learning algorithm in real time. Thirdly, the simulation results show that under the action of the FUZZY-RBF-PID controller, the unit step response of the system has high steady-state accuracy, fast response speed, and under the condition of large load stiffness, the system can recover to the steady-state value faster after being disturbed. At the same time, when the input signal is the sinusoidal signal of 10 HZ, the system under the action of the FUZZY-RBF-PID controller has no obvious phase lag phenomenon, and the tracking error is minimal. The proposed method can effectively improve the comprehensive performance of the electro-hydraulic position servo system under the influence of uncertain factors.

Mesenchymal stem cells-extracellular vesicles alleviate pulmonary fibrosis by regulating immunomodulators.

BACKGROUND: Pulmonary fibrosis (PF) is a chronic interstitial lung disease characterized by fibroblast proliferation and extracellular matrix formation, causing structural damage and lung failure. Stem cell therapy and mesenchymal stem cells-extracellular vesicles (MSC-EVs) offer new hope for PF treatment. AIM: To investigate the therapeutic potential of MSC-EVs in alleviating fibrosis, oxidative stress, and immune inflammation in A549 cells and bleomycin (BLM)-induced mouse model. METHODS: The effect of MSC-EVs on A549 cells was assessed by fibrosis markers [collagen I and α-smooth muscle actin (α-SMA), oxidative stress regulators [nuclear factor E2-related factor 2 (Nrf2) and heme oxygenase-1 (HO-1), and inflammatory regulators [nuclear factor-kappaB (NF-κB) p65, interleukin (IL)-1ß, and IL-2]. Similarly, they were assessed in the lungs of mice where PF was induced by BLM after MSC-EV transfection. MSC-EVs ion PF mice were detected by pathological staining and western blot. Single-cell RNA sequencing was performed to investigate the effects of the MSC-EVs on gene expression profiles of macrophages after modeling in mice. RESULTS: Transforming growth factor (TGF)-ß1 enhanced fibrosis in A549 cells, significantly increasing collagen I and α-SMA levels. Notably, treatment with MSC-EVs demonstrated a remarkable alleviation of these effects. Similarly, the expression of oxidative stress regulators, such as Nrf2 and HO-1, along with inflammatory regulators, including NF-κB p65 and IL-1ß, were mitigated by MSC-EV treatment. Furthermore, in a parallel manner, MSC-EVs exhibited a downregulatory impact on collagen deposition, oxidative stress injuries, and inflammatory-related cytokines in the lungs of mice with PF. Additionally, the mRNA sequencing results suggested that BLM may induce PF in mice by upregulating pulmonary collagen fiber deposition and triggering an immune inflammatory response. The findings collectively highlight the potential therapeutic efficacy of MSC-EVs in ameliorating fibrotic processes, oxidative stress, and inflammatory responses associated with PF. CONCLUSION: MSC-EVs could ameliorate fibrosis in vitro and in vivo by downregulating collagen deposition, oxidative stress, and immune-inflammatory responses.

Deep learning image reconstruction generates thinner slice iodine maps with improved image quality to increase diagnostic acceptance and lesion conspicuity: a prospective study on abdominal dual-energy CT.

BACKGROUND: To assess the improvement of image quality and diagnostic acceptance of thinner slice iodine maps enabled by deep learning image reconstruction (DLIR) in abdominal dual-energy CT (DECT). METHODS: This study prospectively included 104 participants with 136 lesions. Four series of iodine maps were generated based on portal-venous scans of contrast-enhanced abdominal DECT: 5-mm and 1.25-mm using adaptive statistical iterative reconstruction-V (Asir-V) with 50% blending (AV-50), and 1.25-mm using DLIR with medium (DLIR-M), and high strength (DLIR-H). The iodine concentrations (IC) and their standard deviations of nine anatomical sites were measured, and the corresponding coefficient of variations (CV) were calculated. Noise-power-spectrum (NPS) and edge-rise-slope (ERS) were measured. Five radiologists rated image quality in terms of image noise, contrast, sharpness, texture, and small structure visibility, and evaluated overall diagnostic acceptability of images and lesion conspicuity. RESULTS: The four reconstructions maintained the IC values unchanged in nine anatomical sites (all p > 0.999). Compared to 1.25-mm AV-50, 1.25-mm DLIR-M and DLIR-H significantly reduced CV values (all p < 0.001) and presented lower noise and noise peak (both p < 0.001). Compared to 5-mm AV-50, 1.25-mm images had higher ERS (all p < 0.001). The difference of the peak and average spatial frequency among the four reconstructions was relatively small but statistically significant (both p < 0.001). The 1.25-mm DLIR-M images were rated higher than the 5-mm and 1.25-mm AV-50 images for diagnostic acceptability and lesion conspicuity (all P < 0.001). CONCLUSIONS: DLIR may facilitate the thinner slice thickness iodine maps in abdominal DECT for improvement of image quality, diagnostic acceptability, and lesion conspicuity.

First laboratory-confirmed case of scrub typhus in Shijiazhuang City, Hebei Province.

Objective: Defining whether a suspected case was due to scrub typhus through laboratory testing, to understand the prevalence of scrub typhus in Shijiazhuang City, Hebei Province. Methods: An epidemiological investigation was conducted on the suspected case, utilizing Weil-Felix test and indirect immunofluorescence assay (IFA) to detect specific antibodies against O. tsutsugamushi in serum specimens. Additionally, PCR amplification of the 56-kDa and groEL genes was performed, followed by constructing a phylogenetic tree to identify the genotype. Results: The acute phase titer of the Weil-Felix test for the case was 1:160, which increased to 1:320 in the recovery phase. IFA assay revealed IgG titers against O. tsutsugamushi of 1:64 in the acute phase and 1:256 in the recovery phase. Sequence alignment of the PCR amplified fragment showed the highest similarity with the O. tsutsugamushi genotype. Kawasaki sequence, ranging from 99.71 to 100.00%. The strain exhibited the closest genetic relationship with the known O. tsutsugamushi Kawasaki genotype. Conclusion: This study confirms the presence of O. tsutsugamushi in Shijiazhuang City, Hebei Province, with the identified strain belonging to the Kawasaki genotype, marking the first diagnosis of this strain in the region.

Effect of fully automatic classification model from different tube voltage images on bone density screening: A self-controlled study.

PURPOSE: To develop two bone status prediction models combining deep learning and radiomics based on standard-dose chest computed tomography (SDCT) and low-dose chest computed tomography (LDCT), and to evaluate the effect of tube voltage on reproducibility of radiomics features and predictive efficacy of these models. METHODS: A total of 1508 patients were enrolled in this retrospective study. LDCT was conducted using 80 kVp, tube current ranging from 100 to 475 mA. On the other hand, SDCT was performed using 120 kVp, tube current ranging from 100 to 520 mA. We developed an automatic thoracic vertebral cancellous bone (TVCB) segmentation model. Subsequently, 1184 features were extracted and two classifiers were developed based on LDCT and SDCT images. Based on the diagnostic results of quantitative computed tomography examination, the first-level classifier was initially developed to distinguish normal or abnormal BMD (including osteoporosis and osteopenia), while the second-level classifier was employed to identify osteoporosis or osteopenia. The Dice coefficient was used to evaluate the performance of the automated segmentation model. The Concordance Correlation Coefficients (CCC) of radiomics features were calculated between LDCT and SDCT, and the performance of these models was evaluated. RESULTS: Our automated segmentation model achieved a Dice coefficient of 0.98 ± 0.01 and 0.97 ± 0.02 in LDCT and SDCT, respectively. Alterations in tube voltage decreased the reproducibility of the extracted radiomic features, with 85.05 % of the radiomic features exhibiting low reproducibility (CCC < 0.75). The area under the curve (AUC) using LDCT-based and SDCT-based models was 0.97 ± 0.01 and 0.94 ± 0.02, respectively. Nonetheless, cross-validation with independent test sets of different tube voltage scans suggests that variations in tube voltage can impair the diagnostic efficacy of the model. Consequently, radiomics models are not universally applicable to images of varying tube voltages. In clinical settings, ensuring consistency between the tube voltage of the image used for model development and that of the acquired patient image is critical. CONCLUSIONS: Automatic bone status prediction models, utilizing either LDCT or SDCT images, enable accurate assessment of bone status. Tube voltage impacts reproducibility of features and predictive efficacy of models. It is necessary to account for tube voltage variation during the image acquisition.

Aspirin and Celecoxib Regulate Notch1/Hes1 Pathway to Prevent Pressure Overload-Induced Myocardial Hypertrophy.

This study aimed to investigate the molecular mechanisms underlying the protective effects of cyclooxygenase (cox) inhibitors against myocardial hypertrophy.Rat H9c2 cardiomyocytes were induced by mechanical stretching. SD rats underwent transverse aortic constriction to induce pressure overload myocardial hypertrophy. Rats were subjected to echocardiography and tail arterial pressure in 12W. qPCR and western blot were used to detect the expression of Notch-related signaling. The inflammatory factors were tested by ELISA in serum, heart tissue, and cell culture supernatant.Compared with control, levels of pro-inflammatory cytokines IL-6, TNF-α, and IL-1ß were increased and anti-inflammatory cytokine IL-10 was reduced in myocardial tissues and serum of rat models. Levels of Notch1 and Hes1 were reduced in myocardial tissues. However, cox inhibitor treatment (aspirin and celecoxib), the improvement of exacerbated myocardial hypertrophy, fibrosis, dysfunction, and inflammation was parallel to the activation of Notch1/Hes1 pathway. Moreover, in vitro experiments showed that, in cardiomyocyte H9c2 cells, application of ~20% mechanical stretching activated inflammatory mediators (IL-6, TNF-α, and IL-1ß) and hypertrophic markers (ANP and BNP). Moreover, expression levels of Notch1 and Hes1 were decreased. These changes were effectively alleviated by aspirin and celecoxib.Cox inhibitors may protect heart from hypertrophy and inflammation possibly via the Notch1/Hes1 signaling pathway.

Impact of virtual monochromatic images of different low-energy levels in dual-energy CT on radiomics models for predicting muscle invasion in bladder cancer.

OBJECTIVE: The purpose of this study was to investigate the impact of different low-energy virtual monochromatic images (VMIs) in dual-energy CT on the performance of radiomics models for predicting muscle invasive status in bladder cancer (BCa). MATERIALS AND METHODS: A total of 127 patients with pathologically proven muscle-invasive BCa (n = 49) and non-muscle-invasive BCa (n = 78) were randomly allocated into the training and test cohorts at a ratio of 7:3. Feature extraction was performed on the venous phase images reconstructed at 40, 50, 60 and 70-keV (single-energy analysis) or in combination (multi-energy analysis). Recursive feature elimination (RFE) and the least absolute shrinkage and selection operator (LASSO) were employed to select the most relevant features associated with BCa. Models were built using a support vector machine (SVM) classifier. Diagnostic performance was assessed through receiver operating characteristic curves, evaluating sensitivity, specificity, accuracy, precision, and the area-under-the curve (AUC) values. RESULTS: In the test cohort, the multi-energy model achieved the best diagnostic performance with AUC, sensitivity, specificity, accuracy, and precision of 0.917, 0.800, 0.833, 0.821, and 0.750, respectively. Conversely, the single-energy model exhibited lower AUC and sensitivity in predicting the muscle invasion status. CONCLUSIONS: By combining information from VMIs of various energies, the multi-energy model displays superior performance in preoperatively predicting the muscle invasion status of bladder cancer.

Increased water content in multifidus muscles of young adults with chronic nonspecific low back pain detected by dual-energy CT and MRI.

OBJECTIVES: To demonstrate the feasibility of better diagnosing young adults with chronic nonspecific low back pain (CNLBP) by measuring water content in paraspinal muscles using water-muscle decomposition technique in dual-energy CT (DECT) and T2-mapping in MRI. METHODS: This prospective cross-sectional study included 110 young individuals (56 with CNLBP at age of 25.7 ± 2.0 years and 54 of asymptomatic at age of 25.1 ± 1.9 years) who underwent both MRI and DECT on the spine. T2 values on T2 mapping in MRI and water density (WD) value on water(muscle) images in DECT were generated at the L1-L4 levels for erector spinae muscle and L2-L5 for multifidus muscle. Pain duration time, Oswestry Disability Index (ODI), Visual Analogue Scale (VAS) were recorded for CNLBP patients. Difference of T2 value and WD between the two patient groups, and correlations between T2 value and WD, and T2 value and WD with clinical indicators were analyzed. RESULTS: Compared with asymptomatic participants, the mean WD of multifidus muscle at L4-L5 and mean T2 values of multifidus muscle at L5 were significantly higher in CNLBP patients (all P < 0.05). T2 values had moderate to strong positive correlations (r = 0.34-0.60, all P < 0.05) with DECT WD in CNLBP patients and healthy volunteers. There was a weak correlation between VAS and WD in L5-level multifidus muscle (r = 0.29, P < 0.05). CONCLUSIONS: The T2 values in MRI and WD in DECT are higher in multifidus muscles of lower vertebra levels for young CNLBP patients, and there exists positive correlation between WD and T2 values, providing useful information for diagnosing CNLBP.

First Report of Agroathelia rolfsii Causing Southern Blight on Lippia (Phyla canescens) in Guangzhou, China.

Lippia (Phyla canescens) is a fast-growing, mat-forming, and prostrate perennial plant well adapted to infertile, high-saline, and drought environments (Leigh, et al. 2004). It arrived in China from Japan as a flowering ground cover in 2001 (Cai, et al. 2004). In June 2022, southern blight appeared in our nursery of the Floriculture Research Institute of Guangdong Academy of Agricultural Sciences. High temperature and damp environment are major factors for this disease. The symptoms of top-layer plants were not easily detected, but they were slightly yellowed. A yellowish-brown water-soak lesion appeared on the stems and lowest leaves exposed to soil. White mycelium appeared in the middle stage. Finally, the surface plants showed water-soak decay, and a mass of beige to black-brown rapeseed-shaped sclerotia appeared on the residue and surrounding soil; these plants died. Sclerotia and mycelia were collected from disease tissue, and after surface sterilization, sclerotia was cultured on potato dextrose agar (PDA) at 28±2°C in an incubator without light. Eight fungal isolates with similar colony morphologies were consistently isolated by purifying from different sampling areas. The isolates exhibited obvious septa and a clamp connection structure within the white mycelium. The average growth rate was 26.86±0.06 mm/day. Numerous white granular sclerotia were produced on the mycelium 6 days later. The sclerotia with a diameter of 1.24±0.07mm (n=189) gradually changed from diage to yellow to brown. A typical strain B1 was selected for further identification, targeting its 18S rRNA and LSU rRNA sequences (Yang, et al. 2011; Xue, et al. 2019). Its 18S rRNA sequence (GenBank Accession No. OR517233, 1626 bp) is 99.63% and 99.57% identical to Athelia rolfsii (AY665774, 1179bp; KC670714, 1775bp; JF819726, 1781bp). Its LSU rRNA sequence (OR539570, 757 bp) is 99.87% identical to Agroathelia rolfsii (OR526537, 904 bp). For Athelia rolfsii, a synonym of Agroathelia rolfsii, by combining the morphological characteristics and molecular identification, the isolate pathogen B1 was confirmed to be Agroathelia rolfsii (the teleomorph of Sclerotium rolfsii). To fullfill Koch's postulates, we inoculated the mycelial plugs to healthy lippia stems and leaves which has grown for one year, with PDA plugs free of mycelium as the control. All the plants were kept in a greenhouse at 28±2°C with a 14-h photoperiod and 80% relative humidity. Each treatment was repeated thrice and vaccinated with 6 points. At 7 d following inoculation, all plants inoculated with B1 showed typical symptoms, but the control group was asymptomatic, and sclerotia appeared 17d after inoculation. Using the same protocol mentioned above, pathogenic fungal was reisolated only from treated groups, but not from the control group. Chose three of the pathogens for 18S rRNA and LSU rRNA sequencing, the results showed 100% identity to B1, the same as its microstructure. There are few reports about the disease on P. canescens. Sosa (2007) investigated the pathogens on P. canescens in Argentina, 16 fungi were found but no A. rolfsii. Sclerotium rolfsii were identified on P. nodiflora or P. lanceolata (Michaux) Greene in America (Farr, et al. 1989). To our knowledge, this is the first report in China. Because this pathogen has wide-ranging hosts and causes serious damage, the results from this study will offer guidance for the prevention and treatment of this disease.

Using rice straw-augmented ecological floating beds to enhance nitrogen removal in carbon-limited wastewater.

Agricultural biomass used as solid carbon substrates in ecological floating beds (EFBs) has been proven to be applicable in nitrogen removal for carbon-limited wastewater treatment. However, the subtle interactions among plants, rhizosphere microorganisms, and supplementary carbon sources have not been thoroughly studied. This study combined rice straw mats with different aquatic macrophytes in EFBs to investigate denitrification efficiency in carbon-limited eutrophic waters. Results showed that rice straw significantly enhanced the nitrogen removal efficiency of EFBs, while enriching nitrogen-fixing and denitrifying bacteria (such as Rhizobium, Rubrivivax, and Rhodobacter, etc.). Additionally, during the denitrification process in EFBs, rice straw can release humic acid-like fraction as electron donors to support the metabolic activities of microorganisms, while aquatic macrophytes provide a more diverse range of dissolved organic matters, facilitating a sustainable denitrification process. These findings help to understand the synergistic effect of denitrification processes within wetland ecosystems using agricultural biomass.

Fully automated deep learning system for osteoporosis screening using chest computed tomography images.

Background: Osteoporosis, a disease stemming from bone metabolism irregularities, affects approximately 200 million people worldwide. Timely detection of osteoporosis is pivotal in grappling with this public health challenge. Deep learning (DL), emerging as a promising methodology in the field of medical imaging, holds considerable potential for the assessment of bone mineral density (BMD). This study aimed to propose an automated DL framework for BMD assessment that integrates localization, segmentation, and ternary classification using various dominant convolutional neural networks (CNNs). Methods: In this retrospective study, a cohort of 2,274 patients underwent chest computed tomography (CT) was enrolled from January 2022 to June 2023 for the development of the integrated DL system. The study unfolded in 2 phases. Initially, 1,025 patients were selected based on specific criteria to develop an automated segmentation model, utilizing 2 VB-Net networks. Subsequently, a distinct cohort of 902 patients was employed for the development and testing of classification models for BMD assessment. Then, 3 distinct DL network architectures, specifically DenseNet, ResNet-18, and ResNet-50, were applied to formulate the 3-classification BMD assessment model. The performance of both phases was evaluated using an independent test set consisting of 347 individuals. Segmentation performance was evaluated using the Dice similarity coefficient; classification performance was appraised using the receiver operating characteristic (ROC) curve. Furthermore, metrics such as the area under the curve (AUC), accuracy, and precision were meticulously calculated. Results: In the first stage, the automatic segmentation model demonstrated excellent segmentation performance, with mean Dice surpassing 0.93 in the independent test set. In the second stage, both the DenseNet and ResNet-18 demonstrated excellent diagnostic performance in detecting bone status. For osteoporosis, and osteopenia, the AUCs were as follows: DenseNet achieved 0.94 [95% confidence interval (CI): 0.91-0.97], and 0.91 (95% CI: 0.87-0.94), respectively; ResNet-18 attained 0.96 (95% CI: 0.92-0.98), and 0.91 (95% CI: 0.87-0.94), respectively. However, the ResNet-50 model exhibited suboptimal diagnostic performance for osteopenia, with an AUC value of only 0.76 (95% CI: 0.69-0.80). Alterations in tube voltage had a more pronounced impact on the performance of the DenseNet. In the independent test set with tube voltage at 100 kVp images, the accuracy and precision of DenseNet decreased on average by approximately 14.29% and 18.82%, respectively, whereas the accuracy and precision of ResNet-18 decreased by about 8.33% and 7.14%, respectively. Conclusions: The state-of-the-art DL framework model offers an effective and efficient approach for opportunistic osteoporosis screening using chest CT, without incurring additional costs or radiation exposure.

Pangenome analysis reveals transposon-driven genome evolution in cotton.

BACKGROUND: Transposable elements (TEs) have a profound influence on the trajectory of plant evolution, driving genome expansion and catalyzing phenotypic diversification. The pangenome, a comprehensive genetic pool encompassing all variations within a species, serves as an invaluable tool, unaffected by the confounding factors of intraspecific diversity. This allows for a more nuanced exploration of plant TE evolution. RESULTS: Here, we constructed a pangenome for diploid A-genome cotton using 344 accessions from representative geographical regions, including 223 from China as the main component. We found 511 Mb of non-reference sequences (NRSs) and revealed the presence of 5479 previously undiscovered protein-coding genes. Our comprehensive approach enabled us to decipher the genetic underpinnings of the distinct geographic distributions of cotton. Notably, we identified 3301 presence-absence variations (PAVs) that are closely tied to gene expression patterns within the pangenome, among which 2342 novel expression quantitative trait loci (eQTLs) were found residing in NRSs. Our investigation also unveiled contrasting patterns of transposon proliferation between diploid and tetraploid cotton, with long terminal repeat (LTR) retrotransposons exhibiting a synchronized surge in polyploids. Furthermore, the invasion of LTR retrotransposons from the A subgenome to the D subgenome triggered a substantial expansion of the latter following polyploidization. In addition, we found that TE insertions were responsible for the loss of 36.2% of species-specific genes, as well as the generation of entirely new species-specific genes. CONCLUSIONS: Our pangenome analyses provide new insights into cotton genomics and subgenome dynamics after polyploidization and demonstrate the power of pangenome approaches for elucidating transposon impacts and genome evolution.

Largely Improved Creep Resistance and Thermal-Aging Stability of Eco-Friendly Polypropylene High-Voltage Insulation by Long-Chain Branch-Induced Interfacial Constraints.

Polypropylene (PP)-based composites have attracted numerous attention as a replacement of prevailing cross-linked polyethylene (XLPE) for high-voltage insulation due to their ease of processing, recyclability, and excellent electrical performance. However, the poor resistances against high-temperature creep and thermal aging are obstacles to practical applications of PP-based thermoplastic high-voltage insulation. To address these problems, in this Letter, we synthesized an impact polypropylene copolymer (IPC) containing multifold long-chain branched (LCB) structures in phases, especially the interfaces between the PP matrix and the rubber phase. The results indicated that the structural stability of LCBIPC was significantly enhanced under extreme conditions. In comparison to IPC (without LCB structures), 24.1% less creep strain and 75.2% less unrecoverable deformation are achieved in LCBIPC at 90 °C. In addition, the thermal aging experiments were performed at 135 °C for 48 and 88 days for IPC and LCBIPC, respectively. The results show that the resistance against thermal aging was also enhanced in LCBIPC, which showed a 133% longer thermal aging life compared to IPC. Further results revealed that the interfacial layer between the PP matrix and the rubber phase was constructed in LCBIPC. The two phases are tightly linked by chemical bonds in LCB structures, leading to enforced constraints of the rubber phase at the micro level and better resistance performance against creep and thermal aging at the macro level. Evidently, the reported eco-friendly LCBIPC thermoplastic insulation shows great potential for applications in high-voltage cable insulation.

Chidamide plus envafolimab as subsequent treatment in advanced non-small cell lung cancer patients resistant to anti-PD-1 therapy: A multicohort, open-label, phase II trial with biomarker analysis.

BACKGROUND: Combination of chidamide and anti-PD-L1 inhibitor produce synergistic anti-tumor effect in advanced NSCLC patients resistant to anti-PD-1 treatment. However, the effect of chidamide plus envafolimab has not been reported. AIMS: This study aimed to evaluate the efficacy of chidamide plus envafolimab in advanced NSCLC patients resistant toanti-PD-1 treatment. MATERIALS AND METHODS: Eligible advanced NSCLC patients after resistant to anti-PD-1 therapy received chidamide and envafolimab. The primary endpoint was objective response rate (ORR). The secondary end points included disease control rate (DCR), progression-free survival (PFS), and safety. The expression of histone deacetylase 2 (HDAC2), PD-L1, and blood TMB (bTMB) was also analyzed. RESULTS: After a median follow-up of 8.1 (range: 7.6-9.2) months, only two patients achieved partial response. The ORR was 6.7% (2/30), DCR was 50% (15/30), and median PFS (mPFS) was 3.5 (95% confidence interval: 1.9-5.5) months. Biomarker analysis revealed that patients with high-level HDAC2 expression had numerically superior ORR (4.3% vs. 0), DCR (52.2% vs. 0) and mPFS (3.7 vs. 1.4m). Patients with negative PD-L1 had numerically superior DCR (52.2% vs. 33.3%) and mPFS (3.7m vs. 1.8m), so were those with low-level bTMB (DCR: 59.1% vs. 16.7%, mPFS: 3.8 vs.1.9m). Overall safety was controllable. DISCUSSION: High HDAC2patients showed better ORR, DCR, and PFS. In addition, patient with negative PD-L1 and low-level bTMB had better DCR and PFS. This may be related to the epigenetic function of chidamide. However, the sample size was not big enough, so it is necessary to increase sample size to confirm the conclusion. CONCLUSION: Combination of chidamide and envafolimab showed efficacy signals in certain NSCLC patients. But further identification of beneficial population is necessary for precision treatment.

Deep Learning Image Reconstruction for Transcatheter Aortic Valve Implantation Planning: Image Quality, Diagnostic Performance, Contrast volume and Radiation Dose Assessment.

RATIONALE AND OBJECTIVES: To assess image quality, contrast volume and radiation dose reduction potential and diagnostic performance with the use of high-strength deep learning image reconstruction (DLIR-H) in transcatheter aortic valve implantation (TAVI) planning CT. METHODS: We prospectively enrolled 128 patients referred to TAVI-planning CT. Patients were randomly divided into two groups: DLIR-H group (n = 64) and conventional group (n = 64). The DLIR-H group was scanned with tube voltage of 80kVp and body weighted-dependent contrast injection rate of 28mgI/kg/s, images reconstructed using DLIR-H; the conventional group was scanned with 100kVp and contrast injection rate of 40mgI/kg/s, and images reconstructed using adaptive statistical iterative reconstruction-V at 50% (ASIR-V 50%). Radiation dose, contrast volume, contrast injection rate, and image quality were compared between the two groups. The diagnostic performance of TAVI planning CT for coronary stenosis in 115 patients were calculated using invasive coronary angiography as golden standard. RESULTS: DLIR-H group significantly reduced radiation dose (4.94 ± 0.39mSv vs. 7.93 ± 1.20mSv, p < 0.001), contrast dose (45.28 ± 5.38 mL vs. 63.26 ± 9.88 mL, p < 0.001), and contrast injection rate (3.1 ± 0.31 mL/s vs. 4.9 ± 0.2 mL/s, p < 0.001) compared to the conventional group. Images in DLIR-H group had significantly higher SNR and CNR (all p < 0.001). For the diagnostic performance on a per-patient basis, TAVI planning CT in the DLIR-H group provided 100% sensitivity, 92.1% specificity, 100% negative predictive value (NPV), and 84.2% positive predictive value for the detection of > 50% stenosis. In the conventional group, the corresponding results were 94.7%, 95.3%, 97.6%, and 90.0%, respectively. CONCLUSION: DLIR-H in TAVI-planning CT provides improved image quality with reduced radiation and contrast doses, and enables satisfactory diagnostic performance for coronary arteries stenosis.

Predicting overall survival and prophylactic cranial irradiation benefit in small-cell lung cancer with CT-based deep learning: A retrospective multicenter study.

BACKGROUND AND PURPOSE: To develop a computed tomography (CT)-based deep learning model to predict overall survival (OS) among small-cell lung cancer (SCLC) patients and identify patients who could benefit from prophylactic cranial irradiation (PCI) based on OS signature risk stratification. MATERIALS AND METHODS: This study retrospectively included 556 SCLC patients from three medical centers. The training, internal validation, and external validation cohorts comprised 309, 133, and 114 patients, respectively. The OS signature was built using a unified fully connected neural network. A deep learning model was developed based on the OS signature. Clinical and combined models were developed and compared with a deep learning model. Additionally, the benefits of PCI were evaluated after stratification using an OS signature. RESULTS: Within the internal and external validation cohorts, the deep learning model (concordance index [C-index] 0.745, 0.733) was far superior to the clinical model (C-index: 0.635, 0.630) in predicting OS, but slightly worse than the combined model (C-index: 0.771, 0.770). Additionally, the deep learning model had excellent calibration, clinical usefulness, and improved accuracy in classifying survival outcomes. Remarkably, patients at high risk had a survival benefit from PCI in both the limited and extensive stages (all P < 0.05), whereas no significant association was observed in patients at low risk. CONCLUSIONS: The CT-based deep learning model exhibited promising performance in predicting the OS of SCLC patients. The OS signature may aid in individualized treatment planning to select patients who may benefit from PCI.

Cardiac GR Mediates the Diurnal Rhythm in Ventricular Arrhythmia Susceptibility.

BACKGROUND: Ventricular arrhythmias (VAs) demonstrate a prominent day-night rhythm, commonly presenting in the morning. Transcriptional rhythms in cardiac ion channels accompany this phenomenon, but their role in the morning vulnerability to VAs and the underlying mechanisms are not understood. We investigated the recruitment of transcription factors that underpins transcriptional rhythms in ion channels and assessed whether this mechanism was pertinent to the heart's intrinsic diurnal susceptibility to VA. METHODS AND RESULTS: Assay for transposase-accessible chromatin with sequencing performed in mouse ventricular myocyte nuclei at the beginning of the animals' inactive (ZT0) and active (ZT12) periods revealed differentially accessible chromatin sites annotating to rhythmically transcribed ion channels and distinct transcription factor binding motifs in these regions. Notably, motif enrichment for the glucocorticoid receptor (GR; transcriptional effector of corticosteroid signaling) in open chromatin profiles at ZT12 was observed, in line with the well-recognized ZT12 peak in circulating corticosteroids. Molecular, electrophysiological, and in silico biophysically-detailed modeling approaches demonstrated GR-mediated transcriptional control of ion channels (including Scn5a underlying the cardiac Na+ current, Kcnh2 underlying the rapid delayed rectifier K+ current, and Gja1 responsible for electrical coupling) and their contribution to the day-night rhythm in the vulnerability to VA. Strikingly, both pharmacological block of GR and cardiomyocyte-specific genetic knockout of GR blunted or abolished ion channel expression rhythms and abolished the ZT12 susceptibility to pacing-induced VA in isolated hearts. CONCLUSIONS: Our study registers a day-night rhythm in chromatin accessibility that accompanies diurnal cycles in ventricular myocytes. Our approaches directly implicate the cardiac GR in the myocyte excitability rhythm and mechanistically link the ZT12 surge in glucocorticoids to intrinsic VA propensity at this time.

Extend the benchmarking indel set by manual review using the individual cell line sequencing data from the Sequencing Quality Control 2 (SEQC2) project.

Accurate indel calling plays an important role in precision medicine. A benchmarking indel set is essential for thoroughly evaluating the indel calling performance of bioinformatics pipelines. A reference sample with a set of known-positive variants was developed in the FDA-led Sequencing Quality Control Phase 2 (SEQC2) project, but the known indels in the known-positive set were limited. This project sought to provide an enriched set of known indels that would be more translationally relevant by focusing on additional cancer related regions. A thorough manual review process completed by 42 reviewers, two advisors, and a judging panel of three researchers significantly enriched the known indel set by an additional 516 indels. The extended benchmarking indel set has a large range of variant allele frequencies (VAFs), with 87% of them having a VAF below 20% in reference Sample A. The reference Sample A and the indel set can be used for comprehensive benchmarking of indel calling across a wider range of VAF values in the lower range. Indel length was also variable, but the majority were under 10 base pairs (bps). Most of the indels were within coding regions, with the remainder in the gene regulatory regions. Although high confidence can be derived from the robust study design and meticulous human review, this extensive indel set has not undergone orthogonal validation. The extended benchmarking indel set, along with the indels in the previously published known-positive set, was the truth set used to benchmark indel calling pipelines in a community challenge hosted on the precisionFDA platform. This benchmarking indel set and reference samples can be utilized for a comprehensive evaluation of indel calling pipelines. Additionally, the insights and solutions obtained during the manual review process can aid in improving the performance of these pipelines.

High expression of RTEL1 predicates worse progression in gliomas and promotes tumorigenesis through JNK/ELK1 cascade.

Gliomas are the most common primary intracranial tumor worldwide. The maintenance of telomeres serves as an important biomarker of some subtypes of glioma. In order to investigate the biological role of RTEL1 in glioma. Relative telomere length (RTL) and RTEL1 mRNA was explored and regression analysis was performed to further examine the relationship of the RTL and the expression of RTEL1 with clinicopathological characteristics of glioma patients. We observed that high expression of RTEL1 is positively correlated with telomere length in glioma tissue, and serve as a poor prognostic factor in TERT wild-type patients. Further in vitro studies demonstrate that RTEL1 promoted proliferation, formation, migration and invasion ability of glioma cells. In addition, in vivo studies also revealed the oncogene role of RTEL1 in glioma. Further study using RNA sequence and phospho-specific antibody microarray assays identified JNK/ELK1 signaling was up-regulated by RTEL1 in glioma cells through ROS. In conclusion, our results suggested that RTEL1 promotes glioma tumorigenesis through JNK/ELK1 cascade and indicate that RTEL1 may be a prognostic biomarker in gliomas.