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.

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.

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.

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.

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.

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.

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.

Multistimuli-Responsive Actuators Derived from Natural Materials for Entirely Biodegradable and Programmable Untethered Soft Robots.

Untethered soft robots have attracted growing attention due to their safe interaction with living organisms, good flexibility, and accurate remote control. However, the materials involved are often nonbiodegradable or are derived from nonrenewable resources, leading to serious environmental problems. Here, we report a biomass-based multistimuli-responsive actuator based on cuttlefish ink nanoparticles (CINPs), wood-derived cellulose nanofiber (CNF), and bioderived polylactic acid (PLA). Taking advantage of the good photothermal conversion performance and exceptionally hygroscopic sensitivity of the CINPs/CNF composite (CICC) layer and the opposite thermally induced deformation behavior between the CICC layer and PLA layer, the soft actuator exhibits reversible deformation behaviors under near-infrared (NIR) light, humidity, and temperature stimuli, respectively. By introducing patterned or alignment structures and combining them with a macroscopic reassembly strategy, diverse programmable shape-morphing from 2D to 3D such as letter-shape, coiling, self-folding, and more sophisticated 3D deformations have been demonstrated. All of these deformations can be successfully predicted by finite element analysis (FEA) . Furthermore, this actuator has been further applied as an untethered grasping robot, weightlifting robot, and climbing robot capable of climbing a vertical pole. Such actuators consisting entirely of biodegradable materials will offer a sustainable future for untethered soft robots.

[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.

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.

Early life high fructose exposure disrupts microglia function and impedes neurodevelopment.

Despite the success of fructose as a low-cost food additive, recent epidemiological evidence suggests that high fructose consumption by pregnant mothers or during adolescence is associated with disrupted neurodevelopment 1-7 . An essential step in appropriate mammalian neurodevelopment is the synaptic pruning and elimination of newly-formed neurons by microglia, the central nervous system's (CNS) resident professional phagocyte 8-10 . Whether early life high fructose consumption affects microglia function and if this directly impacts neurodevelopment remains unknown. Here, we show that both offspring born to dams fed a high fructose diet and neonates exposed to high fructose exhibit decreased microglial density, increased uncleared apoptotic cells, and decreased synaptic pruning in vivo . Importantly, deletion of the high affinity fructose transporter SLC2A5 (GLUT5) in neonates completely reversed microglia dysfunction, suggesting that high fructose directly affects neonatal development. Mechanistically, we found that high fructose treatment of both mouse and human microglia suppresses synaptic pruning and phagocytosis capacity which is fully reversed in GLUT5-deficient microglia. Using a combination of in vivo and in vitro nuclear magnetic resonance- and mass spectrometry-based fructose tracing, we found that high fructose drives significant GLUT5-dependent fructose uptake and catabolism, rewiring microglia metabolism towards a hypo-phagocytic state. Importantly, mice exposed to high fructose as neonates exhibited cognitive defects and developed anxiety-like behavior which were rescued in GLUT5-deficient animals. Our findings provide a mechanistic explanation for the epidemiological observation that early life high fructose exposure is associated with increased prevalence of adolescent anxiety disorders.

WNK1 enforces macrophage lineage fidelity.

The appropriate development of macrophages, the body's professional phagocyte, is essential for organismal development, especially in mammals. This dependence is exemplified by the observation that loss-of-function mutations in colony stimulating factor 1 receptor (CSF1R) results in multiple tissue abnormalities owing to an absence of macrophages. Despite this importance, little is known about the molecular and cell biological regulation of macrophage development. Here, we report the surprising finding that the chloride-sensing kinase With-no-lysine 1 (WNK1) is required for development of tissue-resident macrophages (TRMs). Myeloid-specific deletion of Wnk1 resulted in a dramatic loss of TRMs, disrupted organ development, systemic neutrophilia, and mortality between 3 and 4 weeks of age. Strikingly, we found that myeloid progenitors or precursors lacking WNK1 not only failed to differentiate into macrophages, but instead differentiated into neutrophils. Mechanistically, the cognate CSF1R cytokine macrophage-colony stimulating factor (M-CSF) stimulates macropinocytosis by both mouse and human myeloid progenitors and precursor cells. Macropinocytosis, in turn, induces chloride flux and WNK1 phosphorylation. Importantly, blocking macropinocytosis, perturbing chloride flux during macropinocytosis, and inhibiting WNK1 chloride-sensing activity each skewed myeloid progenitor differentiation from macrophages into neutrophils. Thus, we have elucidated a role for WNK1 during macropinocytosis and discovered a novel function of macropinocytosis in myeloid progenitors and precursor cells to ensure macrophage lineage fidelity. Highlights: Myeloid-specific WNK1 loss causes failed macrophage development and premature deathM-CSF-stimulated myeloid progenitors and precursors become neutrophils instead of macrophagesM-CSF induces macropinocytosis by myeloid progenitors, which depends on WNK1Macropinocytosis enforces macrophage lineage commitment.

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.

Radiomics based on readout-segmented echo-planar imaging (RS-EPI) diffusion-weighted imaging (DWI) for prognostic risk stratification of patients with rectal cancer: a two-centre, machine learning study using the framework of predictive, preventive, and personalized medicine.

Background: Currently, the rate of recurrence or metastasis (ROM) remains high in rectal cancer (RC) patients treated with the standard regimen. The potential of diffusion-weighted imaging (DWI) in predicting ROM risk has been reported, but the efficacy is insufficient. Aims: This study investigated the potential of a new sequence called readout-segmented echo-planar imaging (RS-EPI) DWI in predicting the ROM risk of patients with RC using machine learning methods to achieve the principle of predictive, preventive, and personalized medicine (PPPM) application in RC treatment. Methods: A total of 195 RC patients from two centres who directly received total mesorectal excision were retrospectively enrolled in our study. Machine learning methods, including recursive feature elimination (RFE), the synthetic minority oversampling technique (SMOTE), and the support vector machine (SVM) classifier, were used to construct models based on clinical-pathological factors (clinical model), radiomic features from RS-EPI DWI (radiomics model), and their combination (merged model). The Harrell concordance index (C-index) and the area under the time-dependent receiver operating characteristic curve (AUC) were calculated to evaluate the predictive performance at 1 year, 3 years, and 5 years. Kaplan‒Meier analysis was performed to evaluate the ability to stratify patients according to the risk of ROM. Findings: The merged model performed well in predicting tumour ROM in patients with RC at 1 year, 3 years, and 5 years in both cohorts (AUC = 0.887/0.813/0.794; 0.819/0.795/0.783) and was significantly superior to the clinical model (AUC = 0.87 [95% CI: 0.80-0.93] vs. 0.71 [95% CI: 0.59-0.81], p = 0.009; C-index = 0.83 [95% CI: 0.76-0.90] vs. 0.68 [95% CI: 0.56-0.79], p = 0.002). It also had a significant ability to differentiate patients with a high and low risk of ROM (HR = 12.189 [95% CI: 4.976-29.853], p < 0.001; HR = 6.427 [95% CI: 2.265-13.036], p = 0.002). Conclusion: Our developed merged model based on RS-EPI DWI accurately predicted and effectively stratified patients with RC according to the ROM risk at an early stage with an individualized profile, which may be able to assist physicians in individualizing the treatment protocols and promote a meaningful paradigm shift in RC treatment from traditional reactive medicine to PPPM. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-022-00303-3.

N-Doped sp2 /sp3 Carbon Derived from Carbon Dots to Boost the Performance of Ruthenium for Efficient Hydrogen Evolution Reaction.

The structure and properties of the carrier significantly affect the catalytic activity of the active centers for supported electrocatalysts. Therefore, elaborate design and regulation of the physicochemical properties of carbon carriers are essential to improve the activity and stability of the carbon-supported ruthenium-based catalysts. Herein, enlightened by the unique characteristics of coexisting sp2 and sp3 carbon nuclei in N-doped carbon dots (NCDs), a hybrid structure of N-doped carbon substrates featuring N-doped sp2 /sp3 carbon interfaces loaded with Ru nanoparticles (Ru/NCDs) is obtained. Spectroscopic analysis and density functional theory calculations illustrate that the interaction between Ru and NCDs effectively modulates the electronic structure of the active center Ru, and the formed N-doped sp2 /sp3 carbon interface lowers the energy barrier of the intermediates in hydrogen evolution reaction (HER) and balances the hydrogen adsorption and desorption and, thereby, greatly improves the activity of Ru/NCDs. Remarkably, Ru/NCDs exhibit excellent HER activity and stability in comparison to Pt/C, which merely requires overpotentials as low as 37 and 14 mV at 10 mA cm-2 in alkaline and acidic electrolytes, respectively. This finding will provide more thoughts about the influence of substrate properties on the catalytic activity and rational design of carbon-loaded electrocatalysts.

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.

An ultra-broad-range pressure sensor based on a gradient stiffness design.

The question of how to make artificial intelligence robots perceive the power of "light as a feather" and "heavy as a mountain" at the same time has always been a goal that people are striving to achieve. However, pressure sensors, the key components of electronic equipment, are often unable to incorporate high sensitivity and wide range performance. Here, we proposed a "gradient stiffness design" strategy to prepare a kind of carbon nanotube sponge with a stiffness difference of up to 254 times between different layers, but still maintaining an integral conductive network without delamination. This gradient stiffness structure sponge shows prominent sensing properties with ultra-broad range (from 0.0022 MPa to 5.47 MPa) and high sensitivity. The low stiffness layer can detect low stress (0.0022 MPa) with high sensitivity of 0.765 MPa-1, and the high stiffness layer can greatly extend the sensing range to an unprecedentedly high value (5.47 MPa). It can concisely detect various motions with different stress, from slight clamping of fragile fries by the robot fingers to heavily stomping motions by a 90 kg person. Moreover, a series of human movements from small-scale to large-scale can be also monitored, revealing the great potential of this gradient stiffness structure in future sensing research.

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.

Nonswelling injectable chitosan hydrogel via UV crosslinking induced hydrophobic effect for minimally invasive tissue engineering.

Injectable chitosan hydrogels exhibit excellent biological properties for application in biomedical engineering, however most of these hydrogels have limited applicability because "Swelling" can induce volume expansion of conventional hydrogels implanted in the body damages the surrounding tissues. Here, we report a new "Nonswelling" pentenyl chitosan (PTL-CS) hydrogel via N‒acylation reaction to graft an UV crosslinkable short hydrophobic alkyl chain (n‒pentenyl groups). The incorporated pentenyl groups can be crosslinked by UV irradiation to form hydrophobic chains via combination termination, which generate strong hydrophobic effect to extrude the excess water in hydrogel, resulting in a "Nonswelling" state at biological temperature. Furthermore, the PTL-CS solution showed no cytotoxicity in vitro and minimally invasive treatment in vivo demonstrated the PTL-CS hydrogel no adverse effects in a rat model. The nonswelling injectable and UV crosslinkable chitosan hydrogel hold potential applications in smart biomaterials and biological engineering as well as providing a new natural hydrogel in minimally invasive tissue engineering..

On the Use of MPC Techniques to Decide Intervention Policies against COVID-19.

This paper aims at demonstrating how and that model predictive control (MPC) strategies can be used to determine optimal intervention policies against the COVID-19 pandemic. Especially for the time after a first wave of infection and before a vaccine can be safely distributed to a sufficient extent, the intervention experience from the first outbreak can be utilized to guide the policy decision in this period. The MPC problem in this paper takes the pandemic in different regions of a country and its neighboring countries into account, while policies such as wearing masks or social distancing are selected as inputs to be optimized. This optimized policy balances the risk of a second outbreak and socio-economic costs, while considering that the measure should not be too severe to be rejected by the population. Effectiveness of this policy compared to standard intervention policies is compared through numerical simulations.