Highly restricted near-surface permafrost extent during the mid-Pliocene warm period.

Accurate understanding of permafrost dynamics is critical for evaluating and mitigating impacts that may arise as permafrost degrades in the future; however, existing projections have large uncertainties. Studies of how permafrost responded historically during Earth's past warm periods are helpful in exploring potential future permafrost behavior and to evaluate the uncertainty of future permafrost change projections. Here, we combine a surface frost index model with outputs from the second phase of the Pliocene Model Intercomparison Project to simulate the near-surface (~3 to 4 m depth) permafrost state in the Northern Hemisphere during the mid-Pliocene warm period (mPWP, ~3.264 to 3.025 Ma). This period shares similarities with the projected future climate. Constrained by proxy-based surface air temperature records, our simulations demonstrate that near-surface permafrost was highly spatially restricted during the mPWP and was 93 ± 3% smaller than the preindustrial extent. Near-surface permafrost was present only in the eastern Siberian uplands, Canadian high Arctic Archipelago, and northernmost Greenland. The simulations are similar to near-surface permafrost changes projected for the end of this century under the SSP5-8.5 scenario and provide a perspective on the potential permafrost behavior that may be expected in a warmer world.

Thin Solid Polymer Electrolyte with High-Strength and Thermal-Resistant via Incorporating Nanofibrous Polyimide Framework for Stable Lithium Batteries.

Polyethylene oxide (PEO) based polymer electrolytes show promise in expanding the practical applications of lithium (Li) batteries. However, their applications in Li batteries are usually restricted owing to the lack of mechanical strength, poor oxidative stability, and relatively large thickness. Herein, a nanofibrous polyimide (PI) framework enhanced plasticized-PEO solid electrolyte is prepared to realize good mechanical and electrochemical performances. Following the configuration with the PI matrix, this "polymer in polymer" composite electrolyte with a thickness of 17.5 µm exhibits enhanced mechanical strength (13.9 MPa) and outstanding thermal stability. Additionally, it preserves the high ionic conductivity (2.25 × 10-4  S cm-1 , 25 °C). The Li||Li symmetrical battery with the modified electrolyte could achieve a steady Li plating/stripping of more than 500 h, and the critical current density reaches up to 0.6 mA cm-2 at ambient temperature. The LiFePO4 batteries delivery favorable capacity of 132.2 mAh g-1 with capacity retentions of 96.4% and 85.9% after 500 and 1000 cycles at 1 C, respectively. Acceptable cycling performance also could be achieved in LiNi0.5 Co0. 2 Mn0. 3 O2 solid batteries via an inorganic-rich artificial cathode electrolyte interphase.

Separation and Structural Characterization of a Novel Exopolysaccharide from Rhizopus nigricans.

The present study aims to analyze the structural characterization and antioxidant activity of a novel exopolysaccharide from Rhizopus nigricans (EPS2-1). For this purpose, EPS2-1 was purified through DEAE-52, Sephadex G-100, and Sephadex G-75 chromatography. The structural characterization of EPS2-1 was analyzed using high-performance gel permeation chromatography (HPGPC), Fourier transform infrared spectroscopy (FT-IR), methylation analysis, nuclear magnetic resonance (NMR) spectra, transmission electron microscope (TEM), and atomic force microscope (AFM). The results revealed that EPS2-1 is composed of mannose (Man), galactose (Gal), glucose (Glc), arabinose (Ara), and Fucose (Fuc), and possesses a molecular weight of 32.803 kDa. The backbone of EPS2-1 comprised →2)-α-D-Manp-(1→ and →3)-ß-D-Galp-(1→, linked with the O-6 position of (→2,6)-α-D-Manp-(1→) of the main chain is branch α-D-Manp-(1→6)-α-D-Manp-(1→, linked with the O-6 positions of (→3)-ß-D-Galp-(1→) of the main chain are branches →4)-ß-D-Glcp-(1→ and →3)-ß-D-Galp-(1→, respectively. Finally, we demonstrated that EPS2-1 also shows free radical scavenging activity and iron ion reducing ability. At the same time, EPS2-1 could inhibit the proliferation of MFC cells and increase the cell viability of RAW264.7 cells. Our results suggested that EPS2-1 is a novel polysaccharide, and EPS2-1 has antioxidant activity. In addition, EPS2-1 may possess potential immunomodulatory and antitumor activities. This study promoted the application of EPS2-1 as the functional ingredients in the pharmaceutical and food industries.

Quantitative study of the influence of swimming therapy on osteoporosis rat models based on synchrotron radiation computed tomogaphy.

Osteoporosis is a bone disease with a variety of causes, leading to bone pain and fragility to fracture. Major treatment methods include nutrition therapy, exercise therapy, drug therapy and surgical treatment, among which exercise therapy, such as swimming, is the most effective. To investigate the optimal swimming therapy regime for postmenopausal women, the effects of eight weeks of different intensity swimming exercises were studied in rat models. After the swimming program, lumbar vertebrae were dissected from all the rats and scanned by synchrotron radiation computed tomography (SRCT). Histomorphometry analysis and finite-element analysis were carried out on the trabecular structure of the L4 lumbar based on the acquired SRCT slices. Histomorphometry analysis showed that swimming can alleviate the decrease in bone strength induced by estrogen deficiency, and moderate-intensity swimming was found to have the most significant effect.

New reconstruction method for few-view grating-based phase-contrast imaging via dictionary learning.

Grating-based phase-contrast is a hot topic in recent years owing to its excellent imaging contrast capability on soft tissues. Although it is compatible with conventional X-ray tubes and applicable in many fields, long scanning time, and high radiation dose obstruct its wider use in clinical and medical fields, especially for computed tomography applications. In this study, we solve this challenge by reducing the projection views and compensating the loss of reconstruction quality through dual-dictionary learning algorithm. The algorithm is implemented in two steps. First, estimated high-quality absorption images are obtained from the first dual-quality dictionary learning, which uses the correspondence between high-quality images and low-quality ones reconstructed from highly under-sampled data. Then, the second absorption-phase dual-modality dictionary learning is adopted to yield both estimated phase and absorption images, resulting in complementary information for both modality images. Afterwards the absorption and phase images are gradually improved in iterative reconstructions. By using SSIM RMSE measurements and visual assessment for enlarged regions of interest, our proposed method can improve the resolution of these two modality images and recover smaller structures, as compared to conventional methods.

Computed tomography-based radiomics prediction of CTLA4 expression and prognosis in clear cell renal cell carcinoma.

OBJECTIVES: To predict CTLA4 expression levels and prognosis of clear cell renal cell carcinoma (ccRCC) by constructing a computed tomography-based radiomics model and establishing a nomogram using clinicopathologic factors. METHODS: The clinicopathologic parameters and genomic data were extracted from 493 ccRCC cases of the Cancer Genome Atlas (TCGA)-KIRC database. Univariate and multivariate Cox regression and Kaplan-Meier analysis were performed for prognosis analysis. Cibersortx was applied to evaluate the immune cell composition. Radiomic features were extracted from the TCGA/the Cancer Imaging Archive (TCIA) (n = 102) datasets. The support vector machine (SVM) was employed to establish the radiomics signature for predicting CTLA4 expression. Receiver operating characteristic curve (ROC), decision curve analysis (DCA), and precision-recall curve were utilized to assess the predictive performance of the radiomics signature. Correlations between radiomics score (RS) and selected features were also evaluated. An RS-based nomogram was constructed to predict prognosis. RESULTS: CTLA4 was significantly overexpressed in ccRCC tissues and was related to lower overall survival. A higher CTLA4 expression was independently linked to the poor prognosis (HR = 1.458, 95% CI 1.13-1.881, p = 0.004). The radiomics model for the prediction of CTLA4 expression levels (AUC = 0.769 in the training set, AUC = 0.724 in the validation set) was established using seven radiomic features. A significant elevation in infiltrating M2 macrophages was observed in the RS high group (p < 0.001). The predictive efficiencies of the RS-based nomogram measured by AUC were 0.826 at 12 months, 0.805 at 36 months, and 0.76 at 60 months. CONCLUSIONS: CTLA4 mRNA expression status in ccRCC could be predicted noninvasively using a radiomics model based on nephrographic phase contrast-enhanced CT images. The nomogram established by combining RS and clinicopathologic factors could predict overall survival for ccRCC patients. Our findings may help stratify prognosis of ccRCC patients and identify those who may respond best to ICI-based treatments.

Study on the Thermogravimetric Kinetics of Dehydrated Sewage Sludge Regulated by Cationic Polyacrylamide and Sawdust.

With the continuous increase in sewage-sludge production worldwide, the pyrolytic disposal of sludge has received great attention. To build knowledge on the kinetics of pyrolysis, first, sludge was regulated using appropriate amounts of cationic polyacrylamide (CPAM) and sawdust to study their enhancing effect on dehydration. Due to the effects of the charge neutralization and skeleton hydrophobicity, a certain dose of CPAM and sawdust reduced the sludge's moisture content from 80.3% to 65.7%. Next, the pyrolysis characteristics of the dehydrated sludge regulated by CPAM and sawdust were investigated at a heating rate of 10~40 °C/min by using TGA method. The addition of sawdust enhanced the release of volatile substances and reduced the apparent activation energy of the sample. The maximum weight-loss rate decreased with the heating rate, and the DTG curves moved in the direction of high temperature. A model-free method, namely the Starink method, was adopted to calculate the apparent activation energies, which ranged from 135.3 kJ/mol to 174.8 kJ/mol. Combined with the master-plots method, the most appropriate mechanism function ultimately obtained was the nucleation-and-growth model.

Reduced vowel space in video conferences via Zoom: Evidence from read speecha).

This exploratory study compared vowel space area (VSA) in face-to-face situations and video conference situations using the software Zoom. Twenty native German participants read word lists recorded before and after spontaneous conversation. The overall VSA in Zoom was reduced significantly by 11.9%, with a more reduced VSA before and less reduction after the spontaneous conversation. Of nine peripheral vowels in German, /aː iː yː/ showed a significantly reduced Euclidean distance to the centroid of the vowel space. The observed hypoarticulation is discussed in light of the experimental setup, situational differences, and less involvement in Zoom than in face-to-face situations.

Automatic vertebral fracture and three-column injury diagnosis with fracture visualization by a multi-scale attention-guided network.

Deep learning methods have the potential to improve the efficiency of diagnosis for vertebral fractures with computed tomography (CT) images. Most existing intelligent vertebral fracture diagnosis methods only provide dichotomized results at a patient level. However, a fine-grained and more nuanced outcome is clinically needed. This study proposed a novel network, a multi-scale attention-guided network (MAGNet), to diagnose vertebral fractures and three-column injuries with fracture visualization at a vertebra level. By imposing attention constraints through a disease attention map (DAM), a fusion of multi-scale spatial attention maps, the MAGNet can get task highly relevant features and localize fractures. A total of 989 vertebrae were studied here. After four-fold cross-validation, the area under the ROC curve (AUC) of our model for vertebral fracture dichotomized diagnosis and three-column injury diagnosis was 0.884 ± 0.015 and 0.920 ± 0.104, respectively. The overall performance of our model outperformed classical classification models, attention models, visual explanation methods, and attention-guided methods based on class activation mapping. Our work can promote the clinical application of deep learning to diagnose vertebral fractures and provide a way to visualize and improve the diagnosis results with attention constraints.

Survival Analysis for Multimode Ablation Using Self-Adapted Deep Learning Network Based on Multisource Features.

Novel multimode thermal therapy by freezing before radio-frequency heating has achieved a desirable therapeutic effect in liver cancer. Compared with surgical resection, ablation treatment has a relatively high risk of tumor recurrence. To monitor tumor progression after ablation, we developed a novel survival analysis framework for survival prediction and efficacy assessment. We extracted preoperative and postoperative MRI radiomics features and vision transformer-based deep learning features. We also combined the immune features extracted from peripheral blood immune responses using flow cytometry and routine blood tests before and after treatment. We selected features using random survival forest and improved the deep Cox mixture (DCM) for survival analysis. To properly accommodate multitype input features, we proposed a self-adapted fully connected layer for locally and globally representing features. We evaluated the method using our clinical dataset. Of note, the immune features rank the highest feature importance and contribute significantly to the prediction accuracy. The results showed a promising C td-index of 0.885 ±0.040 and an integrated Brier score of 0.041 ±0.014, which outperformed state-of-the-art method combinations of survival prediction. For each patient, individual survival probability was accurately predicted over time, which provided clinicians with trustable prognosis suggestions.

Two-stage generative adversarial networks for metal artifact reduction and visualization in ablation therapy of liver tumors.

PURPOSE: The strong metal artifacts produced by the electrode needle cause poor image quality, thus preventing physicians from observing the surgical situation during the puncture process. To address this issue, we propose a metal artifact reduction and visualization framework for CT-guided ablation therapy of liver tumors. METHODS: Our framework contains a metal artifact reduction model and an ablation therapy visualization model. A two-stage generative adversarial network is proposed to reduce the metal artifacts of intraoperative CT images and avoid image blurring. To visualize the puncture process, the axis and tip of the needle are localized, and then the needle is rebuilt in 3D space intraoperatively. RESULTS: Experiments show that our proposed metal artifact reduction method achieves higher SSIM (0.891) and PSNR (26.920) values than the state-of-the-art methods. The accuracy of ablation needle reconstruction is 2.76 mm average in needle tip localization and 1.64° average in needle axis localization. CONCLUSION: We propose a novel metal artifact reduction and an ablation therapy visualization framework for CT-guided ablation therapy of liver cancer. The experiment results indicate that our approach can reduce metal artifacts and improve image quality. Furthermore, our proposed method demonstrates the potential for displaying the relative position of the tumor and the needle intraoperatively.

X-ray grating interferometer for biomedical imaging applications at Shanghai Synchrotron Radiation Facility.

An X-ray grating interferometer was installed at the BL13W beamline of Shanghai Synchrotron Radiation Facility (SSRF) for biomedical imaging applications. Compared with imaging results from conventional absorption-based micro-computed tomography, this set-up has shown much better soft tissue imaging capability. In particular, using the set-up, the carotid artery and the carotid vein in a formalin-fixed mouse can be visualized in situ without contrast agents, paving the way for future applications in cancer angiography studies. The overall results have demonstrated the broad prospects of the existing set-up for biomedical imaging applications at SSRF.

Denitrification with corncob as carbon source and biofilm carriers.

In this research the agricultural by-product corncob was investigated as a carbon source as well as a biofilm carrier to remove organic matter, expressed as chemical oxygen demand (COD) and nitrate nitrogen (nitrate-N), from wastewater in a batch laboratory reactor. The performance of a reactor with corncob as the carbon source and the biofilm carrier was compared with a control batch reactor with suspended plastic carriers and glucose as the sole carbon source. With 60 vol% of corncob carriers inside the reactor, a soluble COD/N ratio of 4.2 g COD g N(-1) was enough for total denitrification, nearly half of the control reactor (9.5 g COD g N(-1)), at 23 h reaction time. The specific denitrification rate decreased with increasing soluble COD consumption for both reactors. Nitrate and COD removal efficiencies decreased with shorter retention times, with accentuated effects in the reactor. This study suggested corncob as a feasible carbon source and that reaction time was a limiting factor with corncob used as the carbon source for denitrification.

[The control method design of thermal treatment system via fuzzy logic].

A novel system is proposed to control the liquid nitrogen cooling and radio frequency heating of tissue to achieve effective thermal ablation in the treatment using fuzzy logic controller and fuzzy logic PID type controller separately. Results of ex-vivo pig liver experiments demonstrate that this system is useful and could p control the desired treatment procedure.

[The preliminary quantitative analysis of the structures of neovascular morphology of tumours at different stages based on synchrotron radiation].

Microvessel networks were imaged by means of synchrotron radiation CT, A sliced loading and double threshold method was utilized for extracting vessels from large quantities of data (2 GB-5 GB). Preliminary analysis on the development of tumor microvessel networks was performed by statistically analyzing volume rendering and two qualitative factors, micro vessel density (MVD) and fractal dimension(FD).

A Novel Tumor Progression Prediction Method for Multimode Ablation Treatment.

OBJECTIVE: The multimode ablation of liver cancer, which uses radio-frequency heating after a pre-freezing process to treat the tumor, has shown significantly improved therapeutic effects and enhanced anti-tumor immune response. Unlike open surgery, the ablated lesions remain in the body after treatment, so it is critical to assess the immediate outcome and to monitor disease status over time. Here we propose a novel tumor progression prediction method for simultaneous postoperative evaluation and prognosis analysis. METHODS: We propose to leverage the intraoperative therapeutic information extracted from thermal dose distribution. For tumors with specific sensitivity reflected in medical images, different thermal doses implicitly indicate the degree of instant damage and long-term inhibition excited under specific ablation energy. We further propose a survival analysis framework for the multimode ablation treatment. It extracts carefully designed features from clinical, preoperative, intraoperative, and postoperative data, then uses random survival forest for feature selection and deep neural networks for survival prediction. RESULTS: We evaluated the proposed methods using clinical data. The results show that our method outperforms the state-of-the-art survival analysis methods with a C-index of 0.855±0.090. The thermal dose information contributes significantly to the prediction accuracy by taking up 21.7% of the overall feature importance. CONCLUSION: The proposed methods have been demonstrated to be a powerful tool in tumor progression prediction of multimode ablation therapy. SIGNIFICANCE: This kind of data-driven prognosis analysis may benefit personalized medicine and simplify the follow-up process.

Aggregation caused quenching to aggregation induced emission transformation: a precise tuning based on BN-doped polycyclic aromatic hydrocarbons toward subcellular organelle specific imaging.

Polycyclic aromatic hydrocarbons (PAHs) with boron-nitrogen (BN) moieties have attracted tremendous interest due to their intriguing electronic and optoelectronic properties. However, most of the BN-fused π-systems reported to date are difficult to modify and exhibit traditional aggregation-caused quenching (ACQ) characteristics. This phenomenon greatly limits their scope of application. Thus, continuing efforts to seek novel, structurally distinct and functionally diverse structures are highly desirable. Herein, we proposed a one-stone-two-birds strategy including simultaneous exploration of reactivity and tuning of the optical and electronic properties for BN-containing π-skeletons through flexible regioselective functionalization engineering. In this way, three novel functionalized BN luminogens (DPA-BN-BFT, MeO-DPA-BN-BFT and DMA-DPA-BN-BFT) with similar structures were obtained. Intriguingly, DPA-BN-BFT, MeO-DPA-BN-BFT and DMA-DPA-BN-BFT exhibit completely different emission behaviors. Fluorogens DPA-BN-BFT and MeO-DPA-BN-BFT exhibit a typical ACQ effect; in sharp contrast, DMA-DPA-BN-BFT possesses a prominent aggregation induced emission (AIE) effect. To the best of our knowledge, this is the first report to integrate ACQ and AIE properties into one BN aromatic backbone with subtle modified structures. Comprehensive analysis of the crystal structure and theoretical calculations reveal that relatively large twisting angles, multiple intermolecular interactions and tight crystal packing modes endow DMA-DPA-BN-BFT with strong AIE behavior. More importantly, cell imaging demonstrated that luminescent materials DPA-BN-BFT and DMA-DPA-BN-BFT can highly selectively and sensitively detect lipid droplets (LDs) in living MCF-7 cells. Overall, this work provides a new viewpoint of the rational design and synthesis of advanced BN-polycyclic aromatics with AIE features and triggers the discovery of new functions and properties of azaborine chemistry.

Detecting small lung tumors in mouse models by refractive-index microradiology.

Refractive-index (phase-contrast) radiology was able to detect lung tumors less than 1 mm in live mice. Significant micromorphology differences were observed in the microradiographs between normal, inflamed, and lung cancer tissues. This was made possible by the high phase contrast and by the fast image taking that reduces the motion blur. The detection of cancer and inflammation areas by phase contrast microradiology and microtomography was validated by bioluminescence and histopathological analysis. The smallest tumor detected is less than 1 mm(3) with accuracy better than 1 × 10(-3) mm(3). This level of performance is currently suitable for animal studies, while further developments are required for clinical application.

Design of microprobe for accurate thermal treatment of tumor.

Thermal treatment has become an alternative modality for cancer treatment. Low temperature freezing and high temperature heating kill tumor cells effectively through direct and indirect injuries by biochemical and physical stresses. Hyperthermia at a mildly elevated temperature has also been reported to induce biochemical alternations to kill tumor cells and to stimulate immunological response to prevent metastasis. The comprehensive multi-scale biological responses to different thermal history experienced demand an accurate temperature control of the thermal system used for such a treatment. A thermal system was built in our lab utilizing RF heating and liquid nitrogen cooling through a needle probe. In practice, difficulties involved in temperature measurement for in vivo monitoring and control of thermal input through two-phase LN2 flow inside the probe compromise the treatment outcome. To ensure an accurate temperature control, a new model was developed to study the dynamic freezing capacity of the cryo-probe by accounting for the probe shape and dimensions. The model was validated by experiments and used to predict the freezing processes under different conditions. Numerical simulation results showed that combined with RF heating, the system could be used to perform different treatment protocols with an accurate temperature control.

[A new animal model of osteonecrosis induced by focal alternative cooling and heating insults].

OBJECTIVE: To establish a new animal model of osteonecrosis of the femoral head(ONFH) with improved consistency and incidence of femoral head collapse for studies on the mechanism of osteonecrosis. and on the assessment of treatment effectiveness. METHODS: Twenty adult male emus were used. Guide instrumentation was constructed to position the customized probe just articularly and at the proximal part of the femoral head. An alternating focal liquid nitrogen freezing and radiofrequency heating was applied. At 2, 4, 8, 12 and 16 weeks after surgery, hip magnetic resonance imaging (MRI) was performed. Before the emus were sacrificed, barium sulfate was infused to lower extremities for microangiography. The femoral samples were scanned by micro-computed tomography (Micro-CT) and evaluated histologically. RESULTS: No bird demonstrated signs of infection or died unexpectedly. Hip MRI showed changes massive edema at the 4th week, increasingly localized abnormal signals at the 8th'" week, and femoral head collapse at the 12'h week. Micro-CT scans and histological images at the 16th week showed human-like osteonecrotic changes with impaired local blood supply. Bone mineral density of the collapsed head was (380. 31 + 28. 12) mg/cm3 and trabecular spaces were (0. 86 ±0.32) mm; both were significantly lower than those in the control side, which were (415.75 41.28) mg/cm3 and (1. 17 ± 0. 17) mm, respectively (P < 0. 05). Bone volume fraction of the collapsed head was(47.28 ± 17. 14)% and trabecular thickness was (506. 17 ± 220. 58) p.m; both were significantly higher than those at control side, which were (30. 92 ± 4. 01)% and (325. 50 ±44. 53) pm, respectively (P <0. 05). The microangiography at the 16th week showed that vessel volume fraction was (0. 315 ± 0. 055)% , which was significantly higher than the collapsed side [ (0. 142 ± 0. 059)% ] (P <0. 05). CONCLUSIONS: The emu model of fem-oral head osteonecrosis was successfully established using focal alternating cooling and heating insults. The models, with improved consistency and incidence of femoral head collapse, can be used in studies on the mechanism of osteonecrosis and on the assessment of treatment effectiveness.