LncRNA CCAT1 participates in pancreatic ductal adenocarcinoma progression by forming a positive feedback loop with c-Myc.

Long noncoding RNAs (lncRNAs) play fundamental roles in cancer development; however, the underlying mechanisms for a large proportion of lncRNAs in pancreatic ductal adenocarcinoma (PDAC) have not been elucidated. The expression of colon cancer-associated transcript-1 (CCAT1) in PDAC specimens and cell lines was measured by quantitative real-time polymerase chain reaction (qRT-PCR). The function of CCAT1 was examined in vitro and in vivo. The interactions among CCAT1, miR-24-3p and c-Myc were determined by bioinformatics analysis, RNA immunoprecipitation (RIP), dual-luciferase reporter assay, and rescue experiments. CCAT1 was significantly increased in PDAC, positively correlated with PDAC progression and predicted a worse prognosis. Furthermore, CCAT1 enhanced Adenosine triphosphate (ATP) production to facilitate PDAC cell proliferation, colony formation and motility in vitro and tumor growth in vivo. CCAT1 may serve as an miR-24-3p sponge, thereby counteracting its repression by c-Myc expression. Reciprocally, c-Myc may act as a transcription factor to alter CCAT1 expression by directly targeting its promoter region, thus forming a positive feedback loop with CCAT1. Collectively, these results demonstrate that a positive feedback loop of CCAT1/miR-24-3p/c-Myc is involved in PDAC development, which may serve as a biomarker and therapeutic target for PDAC.

Non-invasive diagnosis of liver fibrosis via MRI using targeted gadolinium-based nanoparticles.

INTRODUCTION: Accurate diagnosis of liver fibrosis is crucial for preventing cirrhosis and liver tumors. Liver fibrosis is driven by activated hepatic stellate cells (HSCs) with elevated CD44 expression. We developed hyaluronic acid (HA)-coated gadolinium-based nanoprobes to specifically target CD44 for diagnosing liver fibrosis using T1-weighted magnetic resonance imaging (MRI). MATERIALS AND METHODS: NaGdF4 nanoparticles (NPs) were synthesized via thermal decomposition and modified with polyethylene glycol (PEG) to obtain non-targeting NaGdF4@PEG NPs. These were subsequently coated with HA to target HSCs, resulting in liver fibrosis-targeting NaGdF4@PEG@HA nanoprobes. Characterization includedd transmission electron microscopy and X-ray diffraction. Cell viability was assessed using the Cell Counting Kit-8 (CCK-8). Internalization of NaGdF4@PEG@HA nanoprobes by mouse HSCs JS1 cells via ligand-receptor interaction was observed using flow cytometry and confocal laser scanning microscopy (CLSM). Liver fibrosis was induced in C57BL/6 mice using a methionine-choline deficient (MCD) diet. MRI performance and nanoprobe distribution in fibrotic and normal livers were analyzed using a GE Discovery 3.0T MR 750 scanner. RESULTS: NaGdF4@PEG@HA nanoprobes exhibited homogeneous morphology, low toxicity, and a high T1 relaxation rate (7.645 mM⁻¹s⁻¹). CLSM and flow cytometry demonstrated effective phagocytosis of NaGdF4@PEG@HA nanoprobes by JS1 cells compared to NaGdF4@PEG. MRI scans revealed higher T1 signals in fibrotic livers compared to normal livers after injection of NaGdF4@PEG@HA. NaGdF4@PEG@HA demonstrated higher targeting ability in fibrotic mice. CONCLUSIONS: NaGdF4@PEG@HA nanoprobes effectively target HSCs with high T1 relaxation rate, facilitating efficient MRI diagnosis of liver fibrosis.

Highly Graphitized Coal Tar Pitch-Derived Porous Carbon as High-Performance Lithium Storage Materials.

Because of its high specific capacity and superior rate performance, porous carbon is regarded as a potential anode material for lithium-ion batteries (LIBs). However, porous carbon materials with wide pore diameter distributions suffer from low structural stability and low electrical conductivity during the application process. During this study, the calcium carbonate nanoparticle template method is used to prepare coal tar pitch-derived porous carbon (CTP-X). The coal tar pitch-derived porous carbon has a well-developed macroporous-mesoporous-microporous hierarchical porous network structure, which provides abundant active sites for Li+ storage, significantly reduces polarization and charge transfer resistance, shortens the diffusion path and promotes the rapid transport of Li+. More specifically, the CTP-2 anode shows high charge capacity (496.9 mAh g-1 at 50 mA g-1), excellent rate performance (413.6 mAh g-1 even at 500 mA g-1), and high cycling stability (capacity retention rate of about 100 % after 1,000 cycles at 2 A g-1). The clean and eco-friendly large-scale utilization of coal tar pitch will facilitate the development of high-performance anodes in the field of LIBs.

Dual Protective Porous Ti3 C2 Tx MXene/Polyimide Composite Film for Thermal Insulation and Electromagnetic Interference Shielding.

The thriving 5G communication technology leads to the high demand for EMI shielding materials and thermal management materials. Particularly, portable thermal-sensitive electronic devices have more stringent requirements for thermal insulation performances. In most cases, ultrathin EMI shielding materials integrated with ultralow thermal conductivity are not easy to be achieved. To overcome this obstacle, dual protective porous composite films based on Ti3 C2 Tx MXene and polyimide are fabricated by sacrificing polymethyl methacrylate (PMMA) templates. By optimizing the contact thermal resistance and Kapitza resistance, the composite film presents superior thermal insulation performances with a thermal conductivity of 0.0136 W m-1 K-1 . Moreover, the hybrid porous film maintains superior EMI shielding effectiveness of 63.0 dB and high SSE/t of 31651.2 dB cm2 g-1 . Nevertheless, the excellent active and passive heating ability based on Joule heating and photothermal conversion makes the composite film an ideal portable material for thermal management. This work sheds light on designing thermal management materials and EMI shielding materials for cutting-edge electronic devices.

Positive feedback regulation of lncRNA TPT1-AS1 and ITGB3 promotes cell growth and metastasis in pancreatic cancer.

Emerging evidence has indicated that long noncoding RNAs (lncRNAs) are potential biomarkers and play crucial roles in cancer development. However, the functions and underlying mechanisms of lncRNA TPT1-AS1 in pancreatic ductal adenocarcinoma (PDAC) remain elusive. RNAseq data of PDAC tissues and normal tissues were analyzed, and lncRNAs which were associated with PDAC prognosis were identified. The clinical relevance of TPT1-AS1 for PDAC patients was explored, and the effects of TPT1-AS1 in PDAC progression were investigated in vitro and in vivo. LncRNA TPT1-AS1 was highly expressed in PDAC, and high TPT1-AS1 levels predicted a poor prognosis. Moreover, functional experiments revealed that TPT1-AS1 promoted pancreatic cancer cell proliferation, migration, invasion, and epithelial-to-mesenchymal transition (EMT) process in vitro and in vivo. Mechanistically, TPT1-AS1 functioned as an endogenous sponge for miR-30a-5p, which increased integrin ß3 (ITGB3) level in pancreatic cancer cells. Conversely, our data revealed that ITGB3 could activate the transcription factor signal transducer and activator of transcription 3 (STAT3), which in turn bound directly to the TPT1-AS1 promoter and affected the expression of TPT1-AS1, thus forming a positive feedback loop with TPT1-AS1. Taken together, our results uncovered a reciprocal loop of TPT1-AS1 and ITGB3 which contributed to pancreatic cancer growth and development, and indicated that TPT1-AS1 might serve as a novel potential diagnostic biomarker and therapeutic target for PDAC patients.

Strong Electron Coupling of Ru and Vacancy-Rich Carbon Dots for Synergistically Enhanced Hydrogen Evolution Reaction.

The exploitation of ingenious strategies to improve the activity and stability of ruthenium (Ru) is crucial for the advancement of Ru-based electrocatalysts. Vacancy engineering is a typical strategy for modulating the catalytic activity of electrocatalysts. However, creating vacancies directly into pure metallic Ru is difficult because of the extremely stringent conditions required and will result in instability because the integrity of the crystal structure is destroyed. In response, a compromise tactic by introducing vacancies in a Ru composite structure is proposed, and vacancy-rich carbon dots coupled with Ru (Ru@CDs) are elaborately constructed. Specifically, the vacancy-rich carbon dots (CDs) serve as an excellent platform for anchoring and trapping Ru nanoparticles, thus restraining their agglomeration and growth. As expected, Ru@CDs exhibited excellent catalytic performance with a low overpotential of 30 mV at 10 mA cm-2 in 1 m KOH, a small Tafel slope of 22 mV decade-1 , and robust stability even after 10 000 cycles. The low overpotential is comparable to those of most previously reported Ru-based electrocatalysts. Additionally, spectroscopic characterizations and theoretical calculations demonstrate that the rich vacancies and the electron interactions between Ru and CDs synergistically lower the intermediate energy barrier and thereby maximize the activity of the Ru@CDs electrocatalyst.

Assistant diagnosis with Chinese electronic medical records based on CNN and BiLSTM with phrase-level and word-level attentions.

BACKGROUND: Inferring diseases related to the patient's electronic medical records (EMRs) is of great significance for assisting doctor diagnosis. Several recent prediction methods have shown that deep learning-based methods can learn the deep and complex information contained in EMRs. However, they do not consider the discriminative contributions of different phrases and words. Moreover, local information and context information of EMRs should be deeply integrated. RESULTS: A new method based on the fusion of a convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) with attention mechanisms is proposed for predicting a disease related to a given EMR, and it is referred to as FCNBLA. FCNBLA deeply integrates local information, context information of the word sequence and more informative phrases and words. A novel framework based on deep learning is developed to learn the local representation, the context representation and the combination representation. The left side of the framework is constructed based on CNN to learn the local representation of adjacent words. The right side of the framework based on BiLSTM focuses on learning the context representation of the word sequence. Not all phrases and words contribute equally to the representation of an EMR meaning. Therefore, we establish the attention mechanisms at the phrase level and word level, and the middle module of the framework learns the combination representation of the enhanced phrases and words. The macro average f-score and accuracy of FCNBLA achieved 91.29 and 92.78%, respectively. CONCLUSION: The experimental results indicate that FCNBLA yields superior performance compared with several state-of-the-art methods. The attention mechanisms and combination representations are also confirmed to be helpful for improving FCNBLA's prediction performance. Our method is helpful for assisting doctors in diagnosing diseases in patients.

Understanding the tolerance of the industrial yeast Saccharomyces cerevisiae against a major class of toxic aldehyde compounds.

Development of the next-generation biocatalyst is vital for fermentation-based industrial applications and a sustainable bio-based economy. Overcoming the major class of toxic compounds associated with lignocellulose-to-biofuels conversion is one of the significant challenges for new strain development. A significant number of investigations have been made to understand mechanisms of the tolerance for industrial yeast. It is humbling to learn how complicated the cell's response to the toxic chemicals is and how little we have known about yeast tolerance in the universe of the living cell. This study updates our current knowledge on the tolerance of industrial yeast against aldehyde inhibitory compounds at cellular, molecular and the genomic levels. It is comprehensive yet specific based on reproducible evidence and cross confirmed findings from different investigations using varied experimental approaches. This research approaches a rational foundation toward a more comprehensive understanding on the yeast tolerance. Discussions and perspectives are also proposed for continued exploring the puzzle of the yeast tolerance to aid the next-generation biocatalyst development.

Construction and Characterization of Phthalocyanine-Loaded Particles of Curdlan and Their Photosensitivity.

To optimize the physicochemical properties of phthalocyanine (PC), we examined its behavior in particles of triple helix glucan curdlan (CUR). CUR was denatured and renatured in DMSO, in the presence of PC. Infrared spectroscopy and transmission electron microscopy (TEM) showed that PC and CUR formed an inclusion complex, in which PC was trapped inside CUR molecules. This redshifted the absorption peak of PC, which would improve its usefulness as a photosensitizer, because infrared light can penetrate more deeply into human tissues. The conductivity of the solution of CUR-PC was higher than the conductivities of either a CUR solution or a PC dispersion, indicating that CUR-PC is more water soluble than PC. In addition, CUR-PC was highly stable in water. Thus, the use of CUR as a carrier of PC improves several of its physical properties. PC is used as a photosensitizer for killing cancer cells, but its use is hampered by its low solubility. Further, its absorption range limits its use to a depth of 1⁻3 mm in tissues. CUR-PC, with its high solubility and infrared absorption peak, was highly effective as a photosensitizer. It killed 84% of HeLa cells under 15 min of long wavelength radiation and had little cytotoxicity in the absence of light. These results demonstrate that CUR-PC has promise as a photosensitizer, as well as provide theoretical support for a wide range of applications for PC and CUR.

Multi-task reconstruction network for synthetic diffusion kurtosis imaging: Predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer.

PURPOSE: To assess the feasibility and clinical value of synthetic diffusion kurtosis imaging (DKI) generated from diffusion weighted imaging (DWI) through multi-task reconstruction network (MTR-Net) for tumor response prediction in patients with locally advanced rectal cancer (LARC). METHODS: In this retrospective study, 120 eligible patients with LARC were enrolled and randomly divided into training and testing datasets with a 7:3 ratio. The MTR-Net was developed for reconstructing Dapp and Kapp images from apparent diffusion coefficient (ADC) images. Tumor regions were manually segmented on both true and synthetic DKI images. The synthetic image quality and manual segmentation agreement were quantitatively assessed. The support vector machine (SVM) classifier was used to construct radiomics models based on the true and synthetic DKI images for pathological complete response (pCR) prediction. The prediction performance for the models was evaluated by the receiver operating characteristic (ROC) curve analysis. RESULTS: The mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM) for tumor regions were 0.212, 24.278, and 0.853, respectively, for the synthetic Dapp images and 0.516, 24.883, and 0.804, respectively, for the synthetic Kapp images. The Dice similarity coefficient (DSC), positive predictive value (PPV), sensitivity (SEN), and Hausdorff distance (HD) for the manually segmented tumor regions were 0.786, 0.844, 0.755, and 0.582, respectively. For predicting pCR, the true and synthetic DKI-based radiomics models achieved area under the curve (AUC) values of 0.825 and 0.807 in the testing datasets, respectively. CONCLUSIONS: Generating synthetic DKI images from DWI images using MTR-Net is feasible, and the efficiency of synthetic DKI images in predicting pCR is comparable to that of true DKI images.

Regulating the zinc ion transport kinetics of Mn3O4 through copper doping towards high-capacity aqueous Zn-ion battery.

High working voltage, large theoretical capacity and cheapness render Mn3O4 promising cathode candidate for aqueous zinc ion batteries (AZIBs). Unfortunately, poor electrochemical activity and bad structural stability lead to low capacity and unsatisfactory cycling performance. Herein, Mn3O4 material was fabricated through a facile precipitation reaction and divalent copper ions were introduced into the crystal framework, and ultra-small Cu-doped Mn3O4 nanocrystalline cathode materials with mixed valence states of Mn2+, Mn3+ and Mn4+ were obtained via post-calcination. The presence of Cu acts as structural stabilizer by partial substitution of Mn, as well as enhance the conductivity and reactivity of Mn3O4. Significantly, based on electrochemical investigations and ex-situ XPS characterization, a synergistic effect between copper and manganese was revealed in the Cu-doped Mn3O4, in which divalent Cu2+ can catalyze the transformation of Mn3+ and Mn4+ to divalent Mn2+, accompanied by the translation of Cu2+ to Cu0 and Cu+. Benefitting from the above advantages, the Mn3O4 cathode doped with moderate copper (abbreviated as CMO-2) delivers large discharge capacity of 352.9 mAh g-1 at 100 mA g-1, which is significantly better than Mn3O4 (only 247.8 mAh g-1). In addition, CMO-2 holds 203.3 mAh g-1 discharge capacity after 1000 cycles at 1 A g-1 with 98.6 % retention, and after 1000 cycles at 5 A g-1, it still performs decent discharge capacity of 104.2 mAh g-1. This work provides new ideas and approaches for constructing manganese-based AZIBs with long lifespan and high capacity.

Berlin Green with tunable iron content as ultra-high rate host for efficient aqueous ammonium ion storage.

Prussian blue analogues (PBAs) are regarded as promising cathode materials for ammonium-ion batteries (AIBs) because of their low cost and superb theoretical capacity. However, its inherently poor conductivity and structural collapse can significantly limit the enhancement of rate property and cycling stability. In this work, Berlin Green (BG) electrode materials with similar wool-like clusters were constructed by direct precipitation method to accelerate the kinetic, which realizes outstanding cycling stability. Berlin Green with the appropriate amount of iron (BG-2) has a fast ion transport channel, enhanced structure stability, highly reversible insertion/extraction of NH4+, and fine electrochemical reaction activity. Benefiting from the unique architecture and component, the BG-2 electrode shows an excellent rate performance with a discharge/charge specific capacity of 60.1/59.3 mAh g-1 at 5 A g-1. Even at 5 A g-1, BG-2 exhibits remarkable cycling stability with an initial discharge capacity of 59.5 mAh g-1 and a capacity retention rate of approximately 76% after 30,000 cycles. The BG-2 reveals exceedingly good electrochemical reversibility during the process of NH4+ (de)insertion. BG materials indicate huge potential as a cathode material for the next generation of high-performance aqueous batteries.

Low Expression of GRIM-19 Correlates with Poor Prognosis in Patients with Upper Urinary Tract Urothelial Carcinoma.

PURPOSE: This study aimed to clarify the expression of a gene associated with Retinoid- Interferon-Induced Mortality-19 (GRIM-19) in Upper Urinary Tract Urothelial Carcinoma (UUTUC) and its prognostic significance for UUTUC patients. MATERIALS AND METHODS: Immunohistochemical (IHC) staining was used to determine the GRIM-19 expression in 70 paired samples. Progression-Free Survival (PFS) and Cancer-Specific Survival (CSS) were assessed using the Kaplan-Meier method. The independent prognostic factors for PFS and CSS were analyzed by multivariable Cox regression models. RESULTS: IHC staining showed that GRIM-19 expression was significantly decreased in UUTUC, and its cellular location changed from being both cytoplasmic and nuclear to only cytoplasmic. Kaplan- Meier analysis revealed that the patients with tumors expressing low GRIM-19 had a significantly higher risk for tumor progression (P = 0.002) and cancer-specific mortality (P < 0.001) compared to those with high GRIM-19 levels. The Cox regression showed that both GRIM-19 expression (P = 0.025) and lymph node metastasis (LN) (P = 0.007) were independent predictors of progression in the muscle-invasive (MIC) subgroup. GRIM-19 expressions (entire cohort: P = 0.011; MIC subgroup: P = 0.025), LN (entire cohort: P = 0.019; MIC subgroup: P = 0.007), and progression (entire cohort: P < 0.001; MIC subgroup: P < 0.001) were independent predictors of cancer-specific survival. CONCLUSION: Low expression of GRIM-19 in patients with UUTUC had significantly shorter PFS or CSS compared to those with high GRIM-19-expressing tumors. High GRIM-19 expression was also strongly associated with longer PFS in MIC patients. It indicates that GRIM-19 might serve as a promising prognostic biomarker for UUTUC patients.

Biobased Inks Based on Cuttlefish Ink and Cellulose Nanofibers for Biodegradable Patterned Soft Actuators.

Soft actuators with stimuli-responsive and reversible deformations have shown great promise in soft robotics. However, some challenges remain in existing actuators, such as the materials involved derived from nonrenewable resources, complex and nonscalable preparation methods, and incapability of complex and programmable deformation. Here, a biobased ink based on cuttlefish ink nanoparticles (CINPs) and cellulose nanofibers (CNFs) was developed, allowing for the preparation of biodegradable patterned actuators by direct ink writing technology. The hybrid CNF/CINP ink displays good rheological properties, allowing it to be accurately printed on a variety of flexible substrates. A bilayer actuator was developed by printing an ink layer on a biodegradable poly(lactic acid) film using extrusion-based 3D printing technology, which exhibits reversible and large bending behavior under the stimuli of humidity and light. Furthermore, programmable and reversible folding and coiling deformations in response to stimuli have been achieved by adjusting the ink patterns. This work offers a fast, scalable, and cost-effective strategy for the development of biodegradable patterned actuators with programmable shape-morphing.

Prediction of viral pneumonia based on machine learning models analyzing pulmonary inflammation index scores.

OBJECT: To obtain Pulmonary Inflammation Index scores from imaging chest CT and combine it with clinical correlates of viral pneumonia to predict the risk and severity of viral pneumonia using a computer learning model. METHODS: All patients with suspected viral pneumonia on CT examination admitted to The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University from December 2022 to March 2023 were retrospectively selected. The respiratory viruses were monitored by RT-PCR and categorized into patients with viral pneumonia and those with non-viral pneumonia. The extent of lung inflammation was quantified according to the Pulmonary Inflammation Index score (PII). Information on patient demographics, comorbidities, laboratory tests, pathogenetic testing, and radiological data were collected. Five machine learning models containing Random Forest(RF), Radial Basis Function Neural Network (RBFNN), Support Vector Machine (SVM), K Nearest Neighbour Algorithm (KNN), and Kernel Ridge Regression (KRR) were used to predict the risk of onset and severity of viral pneumonia based on the clinically relevant factors or PII. RESULTS: Among the five models, the SVM model performed best in ACC (76.75 %), SN (73.99 %), and F1 (72.42 %) and achieved a better area under the receiver operating characteristic curve (ROC) (0.8409) when predicting the risk of developing viral pneumonia. RF had the best overall classification accuracy in predicting the severity of viral pneumonia, especially in predicting pneumonia with a PII classification of grade I, the RF model achieved an accuracy of 98.89%. CONCLUSION: Machine learning models are valuable in assessing the risk of viral pneumonia. Meanwhile, machine learning models confirm the importance in predicting the severity of viral pneumonia through PII. The establishment of machine learning models for predicting the risk and severity of viral pneumonia promotes the further development of machine learning in the medical field.

Broad-spectrum antibiotics disrupt homeostatic efferocytosis.

The clearance of apoptotic cells, termed efferocytosis, is essential for tissue homeostasis and prevention of autoimmunity1. Although past studies have elucidated local molecular signals that regulate homeostatic efferocytosis in a tissue2,3, whether signals arising distally also regulate homeostatic efferocytosis remains elusive. Here, we show that large peritoneal macrophage (LPM) display impairs efferocytosis in broad-spectrum antibiotics (ABX)-treated, vancomycin-treated and germ-free mice in vivo, all of which have a depleted gut microbiota. Mechanistically, the microbiota-derived short-chain fatty acid butyrate directly boosts efferocytosis efficiency and capacity in mouse and human macrophages, and rescues ABX-induced LPM efferocytosis defects in vivo. Bulk messenger RNA sequencing of butyrate-treated macrophages in vitro and single-cell messenger RNA sequencing of LPMs isolated from ABX-treated and butyrate-rescued mice reveals regulation of efferocytosis-supportive transcriptional programmes. Specifically, we find that the efferocytosis receptor T cell immunoglobulin and mucin domain containing 4 (TIM-4, Timd4) is downregulated in LPMs of ABX-treated mice but rescued by oral butyrate. We show that TIM-4 is required for the butyrate-induced enhancement of LPM efferocytosis capacity and that LPM efferocytosis is impaired beyond withdrawal of ABX. ABX-treated mice exhibit significantly worse disease in a mouse model of lupus. Our results demonstrate that homeostatic efferocytosis relies on distal metabolic signals and suggest that defective homeostatic efferocytosis may explain the link between ABX use and inflammatory disease4-7.

Radiomics for predicting survival in patients with locally advanced rectal cancer: a systematic review and meta-analysis.

Background: Radiomics has recently received considerable research attention for providing potential prognostic biomarkers for locally advanced rectal cancer (LARC). We aimed to comprehensively evaluate the methodological quality and prognostic prediction value of radiomic studies for predicting survival outcomes in patients with LARC. Methods: The Cochrane, Embase, Medline, and Web of Science databases were searched. The radiomics quality score (RQS), Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) checklist, the Image Biomarkers Standardization Initiative (IBSI) guideline, and the Prediction Model Risk of Bias Assessment Tool were used to assess the quality of the selected studies. A further meta-analysis of hazard ratio (HR) regarding disease-free survival (DFS) and overall survival (OS) was performed. Results: Among the 358 studies reported, 15 studies were selected for our review. The mean RQS score was 7.73±4.61 (21.5% of the ideal score of 36). The overall TRIPOD adherence rate was 64.4% (251/390). Most of the included studies (60%) were assessed as having a high risk of bias (ROB) overall. The pooled estimates of the HRs were 3.14 [95% confidence interval (CI): 2.12-4.64, P<0.01] for DFS and 3.36 (95% CI: 1.74-6.49, P<0.01) for OS. Conclusions: Radiomics has potential to noninvasively predict outcome in patients with LARC. However, the overall methodological quality of radiomics studies was low, and the adherence to the TRIPOD statement was moderate. Future radiomics research should put a greater focus on enhancing the methodological quality and considering the influence of higher-order features on reproducibility in radiomics.

Achieving fast interfacial solar vapor generation and aqueous acid purification using Ti3C2Tx MXene/PANI non-woven fabrics.

Acid rain is a worldwide problem because of the emission of acidic gases into the atmosphere, leading to the acidification of first-order streams and aggravation of fresh water shortage. Therefore, it is of great importance to develop an environmentally friendly method for removing acid from water. Herein, an advanced technology that can achieve aqueous acid purification using solar energy is realized with Ti3C2Tx MXene/polyaniline (PANI) hybrid non-woven fabrics (MPs) through interfacial solar vapor generation, with PANI acting as an acid absorber through the doping process. Benefiting from the porous structure and crumpled micro-surface of MPs, a high evaporation rate of 2.65 kg m-2 h-1 with an efficiency of 93.7% can be achieved under one-sun illumination. Moreover, MPs present an even higher evaporation rate of 2.83 kg m-2 h-1 in high concentration aqueous acid and can generate clean water with a pH higher than 6.5. More importantly, thanks to the unique reversible doping process of PANI, when used as an aqueous acid purifier, MPs show good stability and reusability after dedoping. Our work sheds light on an efficient strategy for dealing with aqueous acid and acid rain.

[Evaluation of low intensity Nd: YAG laser and traditional drugs in the treatment of myofascial pain].

PURPOSE: To evaluate the efficacy of low intensity Nd: YAG laser and traditional drugs in the treatment of myofascial pain (MP). METHODS: Eighty patients with MP were divided into laser group(n=40) and traditional medicine group(n=40) according to the principle of randomization and double-blindness. The patients in the laser group were treated with low intensity Nd :YAG laser(1 064 nm, 8 J/cm2, 250 mW) , with an interval of 48 h between the two laser treatments. The whole course of treatment was 10 times. Patients in the traditional medicine group uesd celecoxib capsules, 1 capsulet each time(0.2 g), twice a day for 2 weeks. Before and after each treatment, mouth opening, protrusion excursion, lateral movement of the affected side and lateral movement of the contralateral side were measured, and pain visual analogue scores (VAS) were measured and recorded. The data were statistically analyzed with SPSS 22.0 software package. RESULTS: Patients in laser group had significantly improved mandibular function and movement status(P＜0.05) and pain symptoms(P＜0.05); patients in traditional medicine group had the same significant improvement on mandibular functional movement status(P＜0.05) and pain symptoms (P＜0.05). The total effective rate of the two groups had no significant difference(P＞0.05). The VAS score of patients in laser group was lower than that of traditional medicine group, but the difference was not significant(P＞0.05). CONCLUSIONS: Low intensity Nd: YAG laser and traditional medicine can effectively relieve the symptoms of myofascial pain and improve mandibular function and movement. Laser treatment has the advantages of short course of treatment, high efficiency, no pain and fewer side effects, which is worthy of clinical application.

The Prognostic and Immune Significance of CILP2 in Pan-Cancer and Its Relationship with the Progression of Pancreatic Cancer.

Cartilage intermediate layer protein 2 (CILP2) facilitates interactions between matrix components in cartilage and has emerged as a potential prognostic biomarker for cancer. This study aimed to investigate the function and mechanisms of CILP2 in pan-cancer. We evaluated the pan-cancer expression, methylation, and mutation data of CILP2 for its clinical prognostic value. Additionally, we explored the immunological characteristics of CILP2 in pan-cancer and then focused specifically on pancreatic ductal adenocarcinoma (PAAD). The subtype analysis of PAAD identified subtype-specific expression and immunological characteristics. Finally, in vitro and in vivo experiments assessed the impact of CILP2 on pancreatic cancer progression. CILP2 exhibited high expression in most malignancies, with significant heterogeneity in epigenetic modifications across multiple cancer types. The abnormal methylation and copy number variations in CILP2 were correlated with poor prognoses. Upregulated CILP2 was associated with TGFB/TGFBR1 and more malignant subtypes. CILP2 exhibited a negative correlation with immune checkpoints in PAAD, suggesting potential for immunotherapy. CILP2 activated the AKT pathway, and it increased proliferation, invasion, migration, and epithelial-mesenchymal transition (EMT) in pancreatic cancer. We demonstrated that CILP2 significantly contributes to pancreatic cancer progression. It serves as a prognostic biomarker and a potential target for immunotherapy.