Safety and clinical efficacy of microwave ablation combined with percutaneous vertebroplasty in the treatment of multisegmental spinal metastases.

OBJECTIVE: To evaluate the safety and efficacy of microwave ablation (MWA) combined with percutaneous vertebroplasty (PVP) in the treatment of multisegmental (2-3 segments) osteolytic spinal metastases. MATERIALS AND METHODS: This study comprised a retrospective analysis of data from 20 patients with multisegmental (2-3 segments) osteolytic spinal metastases who received MWA combined with PVP. The visual analog scale (VAS) score, Oswestry Disability Index (ODI) score, Quality of Life Questionnaire-Bone Metastases 22 (QLQ-BM22), and local recurrence before and after the operation were measured. The occurrence of complications was observed to evaluate safety. RESULTS: All operations were completed successfully with no serious complications. Transient nerve injury occurred in two cases, but recovered after symptomatic treatment. The bone cement leakage rate was 13.9% (6/43). The mean baseline VAS scores were 7.25 ± 0.91 before treatment and 7.25 ± 0.91, 3.70 ± 1.12, 2.70 ± 0.73, 2.40 ± 0.68, 2.25 ± 0.71, and 2.70 ± 0.92 at 1 day, 1 week, 1, 3, and 6 months after treatment; all values were significantly lower (P < 0.001). The mean baseline ODI score decreased from 56.90 ± 9.74 before treatment to 41.90 ± 7.09, 38.10 ± 7.93, and 38.80 ± 10.59 at 1, 3, and 6 months after treatment, respectively; all values were significantly lower (P < 0.001). The average QLQ-BM22 baseline score decreased from 54.10 ± 5.36 before treatment to 44.65 ± 5.22, 43.05 ± 4.78, 42.30 ± 4.06, and 42.15 ± 5.47 at 1 week, 1, 3, and 6 months after treatment; all values were significantly lower (all P < 0.001). The postoperative survival time of all patients was >6 months. In three patients, four vertebral segments recurred 6 months after operation. CONCLUSION: MWA combined with PVP is a safe and effective treatment for multisegmental osteolytic vertebral metastases that can effectively relieve pain, improve spinal function, improve quality of life, and delay tumor progression. However, it is a long operation, necessitating good preoperative preparation and effective intraoperative pain relief measures.

3D printing nacre powder/sodium alginate scaffold loaded with PRF promotes bone tissue repair and regeneration.

Bone defects are a common complication of bone diseases, which often affect the quality of life and mental health of patients. The use of biomimetic bone scaffolds loaded with bioactive substances has become a focal point in the research on bone defect repair. In this study, composite scaffolds resembling bone tissue were created using nacre powder (NP) and sodium alginate (SA) through 3D printing. These scaffolds exhibit several physiological structural and mechanical characteristics of bone tissue, such as suitable porosity, an appropriate pore size, applicable degradation performance and satisfying the mechanical requirements of cancellous bone, etc. Then, platelet-rich fibrin (PRF), containing a mass of growth factors, was loaded on the NP/SA scaffolds. This was aimed to fully maximize the synergistic effect with NP, thereby accelerating bone tissue regeneration. Overall, this study marks the first instance of preparing a bionic bone structure scaffold containing NP by 3D printing technology, which is combined with PRF to further accelerate bone regeneration. These findings offer a new treatment strategy for bone tissue regeneration in clinical applications.

Clinical efficacy and safety of microwave ablation combined with percutaneous osteoplasty for palliative treatment in pelvic osteolytic metastases.

OBJECTIVES: To evaluate the impact of microwave ablation (MWA) on pain relief, quality of life, mobility, and local tumour progression in adult patients with pelvic osteolytic bone metastasis and to test the safety of MWA. METHODS: This study retrospectively analysed the data from 20 patients with pelvic osteolytic metastases who received MWA combined with percutaneous osteoplasty (POP). The visual analogue scale (VAS), musculoskeletal tumour society system (MSTS), and Quality of Life Questionnaire-Bone Metastases 22 (QLQ-BM22) were used to evaluate the pain, limb function, and quality of life. The intraoperative and postoperative complications were recorded. The tumour recurrence and survival time were analysed during the follow-up period (range 3-26 months). RESULTS: All (n = 20) MWA and POP operations were completed successfully. Four patients (20%; 95% CI, 6%-44%) had mild bone cement leakage from surrounding tissues, and there were no obvious symptoms or serious complications. There were significant differences in VAS, MSTS, and QLQ-BM22 scores before and after the operation (P < .001). During the postoperative follow-up period, 9 patients died. The median survival time was 8 months (range 3-26 months; IQR: 4.5-13; 95% CI, 4.2-15.3 months), and the 1-year survival rate was 65% (13/20; 95% CI, 41%-85%). Tumour recurrence occurred in 4 cases (20%; 95% CI, 6%-44%) after the operation, and the median time of recurrence was 12 months (range 8-16 months; IQR: 8.25-12.75; 95% CI, 5.5-18.5 months). CONCLUSIONS: MWA combined with POP is an effective and safe treatment for pelvic osteolytic metastases. It can significantly relieve local pain, reconstruct limb function, improve patients' quality of life, and effectively control local tumour progression. ADVANCES IN KNOWLEDGE: So far, the experience of using microwave in the treatment of pelvic metastases is still limited. MWA combined with POP in the treatment of pelvic osteolytic metastases can provide significant clinical benefits in acceptable low-risk minimally invasive situations and should be provided to patients with appropriate pelvic metastases in a multidisciplinary approach.

Mitochondrial Localized In Situ Self-Assembly Reprogramming Tumor Immune and Metabolic Microenvironment for Enhanced Cancer Therapy.

The inherent immune and metabolic tumor microenvironment (TME) of most solid tumors adversely affect the antitumor efficacy of various treatments, which is an urgent issue to be solved in clinical cancer therapy. In this study, a mitochondrial localized in situ self-assembly system is constructed to remodel the TME by improving immunogenicity and disrupting the metabolic plasticity of cancer cells. The peptide-based drug delivery system can be pre-assembled into nanomicelles in vitro and form functional nanofibers on mitochondria through a cascade-responsive process involving reductive release, targeted enrichment, and in situ self-assembly. The organelle-specific in situ self-assemblyeffectively switches the role of mitophagy from pro-survival to pro-death, which finally induces intense endoplasmic reticulum stress and atypical type II immunogenic cell death. Disintegration of the mitochondrial ultrastructure also impedes the metabolic plasticity of tumor cells, which greatly promotes the immunosuppresive TME remodeling into an immunostimulatory TME. Ultimately, the mitochondrial localized in situ self-assembly system effectively suppresses tumor metastases, and converts cold tumors into hot tumors with enhanced sensitivity to radiotherapy and immune checkpoint blockade therapy. This study offers a universal strategy for spatiotemporally controlling supramolecular self-assembly on sub-organelles to determine cancer cell fate and enhance cancer therapy.

The Tautomerase Activity of Tumor Exosomal MIF Promotes Pancreatic Cancer Progression by Modulating MDSC Differentiation.

Pancreatic cancer is a deadly disease that is largely resistant to immunotherapy, in part because of the accumulation of immunosuppressive cells in the tumor microenvironment (TME). Much evidence suggests that tumor-derived exosomes (TDE) contribute to the immunosuppressive activity mediated by myeloid-derived suppressor cells (MDSC) within the pancreatic cancer TME. However, the underlying mechanisms remain elusive. Herein, we report that macrophage migration inhibitory factor (MIF) in TDEs has a key role in inducing MDSC formation in pancreatic cancer. We identified MIF in both human and murine pancreatic cancer-derived exosomes. Upon specific shRNA-mediated knockdown of MIF, the ability of pancreatic cancer-derived exosomes to promote MDSC differentiation was abrogated. This phenotype was rescued by reexpression of the wild-type form of MIF rather than a tautomerase-null mutant or a thiol-protein oxidoreductase-null mutant, indicating that both MIF enzyme activity sites play a role in exosome-induced MDSC formation in pancreatic cancer. RNA sequencing data indicated that MIF tautomerase regulated the expression of genes required for MDSC differentiation, recruitment, and activation. We therefore developed a MIF tautomerase inhibitor, IPG1576. The inhibitor effectively inhibited exosome-induced MDSC differentiation in vitro and reduced tumor growth in an orthotopic pancreatic cancer model, which was associated with decreased numbers of MDSCs and increased infiltration of CD8+ T cells in the TME. Collectively, our findings highlight a pivotal role for MIF in exosome-induced MDSC differentiation in pancreatic cancer and underscore the potential of MIF tautomerase inhibitors to reverse the immunosuppressive pancreatic cancer microenvironment, thereby augmenting anticancer immune responses.

RotNet: A Rotationally Invariant Graph Neural Network for Quantum Mechanical Calculations.

Deep learning has proven promising in biological and chemical applications, aiding in accurate predictions of properties such as atomic forces, energies, and material band gaps. Traditional methods with rotational invariance, one of the most crucial physical laws for predictions made by machine learning, have relied on Fourier transforms or specialized convolution filters, leading to complex model design and reduced accuracy and efficiency. However, models without rotational invariance exhibit poor generalization ability across datasets. Addressing this contradiction, this work proposes a rotationally invariant graph neural network, named RotNet, for accurate and accelerated quantum mechanical calculations that can overcome the generalization deficiency caused by rotations of molecules. RotNet ensures rotational invariance through an effective transformation and learns distance and angular information from atomic coordinates. Benchmark experiments on three datasets (protein fragments, electronic materials, and QM9) demonstrate that the proposed RotNet framework outperforms popular baselines and generalizes well to spatial data with varying rotations. The high accuracy, efficiency, and fast convergence of RotNet suggest that it has tremendous potential to significantly facilitate studies of protein dynamics simulation and materials engineering while maintaining physical plausibility.

CEEM: a Chemically Explainable Deep Learning Platform for Identifying Compounds with Low Effective Mass.

The semiconductor industry occupies a crucial position in the fields of integrated circuits, energy, and communication systems. Effective mass (mE ), which is closely related to electron transition, thermal excitation, and carrier mobility, is a key performance indicator of semiconductor. However, the highly neglected mE is onerous to measure experimentally, which seriously hinders the evaluation of semiconductor properties and the understanding of the carrier migration mechanisms. Here, a chemically explainable effective mass predictive platform (CEEM) is constructed by deep learning, to identify n-type and p-type semiconductors with low mE . Based on the graph network, a versatile explainable network is innovatively designed that enables CEEM to efficiently predict the mE of any structure, with the area under the curve of 0.904 for n-type semiconductors and 0.896 for p-type semiconductors, and derive the most relevant chemical factors. Using CEEM, the currently largest mE database is built that contains 126 335 entries and screens out 466 semiconductors with low mE for transparent conductive materials, photovoltaic materials, and water-splitting materials. Moreover, a user-friendly and interactive CEEM web is provided that supports query, prediction, and explanation of mE . CEEM's high efficiency, accuracy, flexibility, and explainability open up new avenues for the discovery and design of high-performance semiconductors.

MatGPT: A Vane of Materials Informatics from Past, Present, to Future.

Combining materials science, artificial intelligence (AI), physical chemistry, and other disciplines, materials informatics is continuously accelerating the vigorous development of new materials. The emergence of "GPT (Generative Pre-trained Transformer) AI" shows that the scientific research field has entered the era of intelligent civilization with "data" as the basic factor and "algorithm + computing power" as the core productivity. The continuous innovation of AI will impact the cognitive laws and scientific methods, and reconstruct the knowledge and wisdom system. This leads to think more about materials informatics. Here, a comprehensive discussion of AI models and materials infrastructures is provided, and the advances in the discovery and design of new materials are reviewed. With the rise of new research paradigms triggered by "AI for Science", the vane of materials informatics: "MatGPT", is proposed and the technical path planning from the aspects of data, descriptors, generative models, pretraining models, directed design models, collaborative training, experimental robots, as well as the efforts and preparations needed to develop a new generation of materials informatics, is carried out. Finally, the challenges and constraints faced by materials informatics are discussed, in order to achieve a more digital, intelligent, and automated construction of materials informatics with the joint efforts of more interdisciplinary scientists.

Surfactants Influencing the Biocatalytic Performance of Natural Alkane-Degrading Bacteria via Interfacial Biocatalysis in Pickering Emulsions.

Setting superhydrophobic Mycobacterium sp. as an example, the hydrophobic bacteria acting as demulsifying agents of surfactant-stabilized conventional emulsions, vice versa, the synergistic/antagonistic influence of nonionic surfactants (Tween 80 or Span 80) on the stability of the bacteria-stabilized Pickering emulsions was investigated. At the same time, the activated/suppression effect of nonionic surfactants on microbial degradation of tetradecane, which exhibited a dose-response relationship, was also found. The hydrophobic bacteria acting as demulsifying agents and the suppression influence of nonionic surfactants on the biocatalytic performance (indexing as biomass) of natural alkane-degrading bacteria, believed to be totally separated concepts previously, are for the first time found to be closely related to in situ surface modification of bacteria with nonionic surfactants. During the degradation of tetradecane by Mycobacterium sp. in the presence of nonionic surfactants, demulsification due to the bacteria acting as demulsifying agents and interfacial biocatalysis in the bacteria-stabilized Pickering emulsions are involved, which provides useful information to select optimal dispersants for marine oil spills.

Usefulness of attenuation value on computed tomography plain scan for diagnosing enlarged mediastinal lymph nodes metastases.

Background: To evaluate the diagnostic value of computed tomography (CT) attenuation in mediastinal lymph node metastases of malignant tumors. Methods: A retrospective review was conducted of a Chinese institutional database of consecutive patients with a history of malignant tumors. Those who had enlarged, necrotic, or hypermetabolic lymph nodes detected in the mediastinum during routine CT examination or positron emission tomography (PET)/CT imaging from January 2019 to December 2021 were collected for investigation. All patients underwent endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) and were followed up for at least 6 months to diagnose lymph node metastases. One-to-one correlation was attempted between the CT images of the lymph nodes and EBUS-TBNA area of the same lymph node groups and similar size. Radiologists measured size, as well as plain CT and contrast-enhanced CT (CECT) attenuation values of mediastinal lymph nodes, and evaluated the effectiveness of these variables in diagnosing lymph node metastasis. Results: A total of 135 lymph nodes of 114 patients were included in the study. In the univariate analysis, the long-axis diameter, short-axis diameter, short-axis/long-axis ratio, and plain CT attenuation values of lymph nodes were found to be statistically significantly different between the metastatic and non-metastatic lymph nodes. The areas under receiver operator characteristic (ROC) curves (AUCs) of long-axis diameter, short-axis diameter, short-axis/long-axis ratio, and plain CT attenuation value for diagnosing metastases were 0.711, 0.788, 0.671, and 0.827, respectively. The best value of the AUC for diagnosing lymph node metastases was 0.827 [95% confidence interval (CI): 0.749-0.890] using plain CT attenuation value ≤45 Hounsfield units (HU). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 92.8%, 69.2%, 86.5%, and 81.8%, respectively. Similar results were obtained from the 68 cases of lung cancer. Plain CT attenuation values reached the best AUC (0.860) for diagnosing lymph node metastases. Conclusions: Plain CT attenuation of lymph nodes is an effective method for diagnosing enlarged mediastinal lymph nodes with a history of multiple malignancies or lung cancer. Plain CT could be used as an additional test where there is no PET/CT available in cases of diagnostic dilemma.

Artificial intelligence aided precise detection of local recurrence on MRI for nasopharyngeal carcinoma: a multicenter cohort study.

Background: MRI is the routine examination to surveil the recurrence of nasopharyngeal carcinoma, but it has relatively lower sensitivity than PET/CT. We aimed to find if artificial intelligence (AI) could be competent pre-inspector for MRI radiologists and whether AI-aided MRI could perform better or even equal to PET/CT. Methods: This multicenter study enrolled 6916 patients from five hospitals between September 2009 and October 2020. A 2.5D convolutional neural network diagnostic model and a nnU-Net contouring model were developed in the training and test cohorts and used to independently predict and visualize the recurrence of patients in the internal and external validation cohorts. We evaluated the area under the ROC curve (AUC) of AI and compared AI with MRI and PET/CT in sensitivity and specificity using the McNemar test. The prospective cohort was randomized into the AI and non-AI groups, and their sensitivity and specificity were compared using the Chi-square test. Findings: The AI model achieved AUCs of 0.92 and 0.88 in the internal and external validation cohorts, corresponding to the sensitivity of 79.5% and 74.3% and specificity of 91.0% and 92.8%. It had comparable sensitivity to MRI (e.g., 74.3% vs. 74.7%, P = 0.89) but lower sensitivity than PET/CT (77.9% vs. 92.0%, P < 0.0001) at the same individual-specificities. The AI model achieved moderate precision with a median dice similarity coefficient of 0.67. AI-aided MRI improved specificity (92.5% vs. 85.0%, P = 0.034), equaled PET/CT in the internal validation subcohort, and increased sensitivity (81.9% vs. 70.8%, P = 0.021) in the external validation subcohort. In the prospective cohort of 1248 patients, the AI group had higher sensitivity than the non-AI group (78.6% vs. 67.3%, P = 0.23), albeit nonsignificant. In future randomized controlled trials, a sample size of 3943 patients in each arm would be required to demonstrate the statistically significant difference. Interpretation: The AI model equaled MRI by expert radiologists, and AI-aided MRI by expert radiologists equaled PET/CT. A larger randomized controlled trial is warranted to demonstrate the AI's benefit sufficiently. Funding: The Sun Yat-sen University Clinical Research 5010 Program (2015020), Guangdong Basic and Applied Basic Research Foundation (2022A1515110356), and Guangzhou Science and Technology Program (2023A04J1788).

Maternal and embryonic signals cause functional differentiation of luminal epithelial cells and receptivity establishment.

Embryo implantation requires temporospatial maternal-embryonic dialog. Using single-cell RNA sequencing for the uterus from 2.5 to 4.5 days post-coitum (DPC) and bulk sequencing for the corresponding embryos of 3.5 and 4.0 DPC pregnant mice, we found that estrogen-responsive luminal epithelial cells (EECs) functionally differentiated into adhesive epithelial cells (AECs) and supporting epithelial cells (SECs), promoted by progesterone. Along with maternal signals, embryonic Pdgfa and Efna3/4 signaling activated AECs and SECs, respectively, enhancing the attachment of embryos to the endometrium and furthering embryo development. This differentiation process was largely conserved between humans and mice. Notably, the developmental defects of SOX9-positive human endometrial epithelial cells (similar to mouse EEC) were related to thin endometrium, whereas functional defects of SEC-similar unciliated epithelial cells were related to recurrent implantation failure (RIF). Our findings provide insights into endometrial luminal epithelial cell development directed by maternal and embryonic signaling, which is crucial for endometrial receptivity.

A comparative study of establishing rabbit vertebral tumor model by two ways of CT-guided percutaneous puncture.

Objective: To investigate the difference of tumor formation rate of rabbit vertebral tumor model established by percutaneous injection of V×2 tumor tissue suspension and tumor mass under computed tomography (CT) guidance, and the imaging findings of CT, magnetic resonance images (MRI) and positron emission tomography with computed tomography (PET/CT) at 7 days, 14 days and 21 days after implantation, and preliminarily verify the safety and feasibility of microwave ablation (MWA), percutaneous vertebroplasty (PVP) and microwave ablation combined with percutaneous vertebroplasty (MWA + PVP) in rabbit VX2 vertebral tumor model. Methods: Thirty healthy New Zealand rabbits were randomly allocated to tissue suspension group and tumor block group, with 15 rabbits for each group. The VX2 tumor block and mixed suspension were inoculated into the L5 vertebral body under CT-guided percutaneous puncture. The PET/CT, MRI and CT examinations were performed at 7, 14 and 21 days after implantation. Fisher exact probability test was used to compare the success rate of the two implantation methods and the tumor display rate at each time point of the three examination methods. Observe the paralysis of tumor-forming rabbits, and immediately perform MWA/PVP/MWA + PVP treatment according to groups after paralysis to verify the safety and feasibility of treatment. Results: A total of 18 experimental rabbits were successfully modeled in two groups, of which the success rate was 26.6% (4/15) in tissue suspension group and 93.3% (14/15) in tumor block group, with statistically significant differences between two groups (P < 0.01). The tumor display rates by PET/CT, MRI and CT at each time point after implantation were: 83.3% (15/18), 16.6% (3/18), and 0% (0/18) at 7 days after implantation; 100% (18/18), 88.8% (16/18), and 11.1% (2/18) at 14 days after implantation; and 100% (18/18), 100% (18/18), 77.7% (14/18) at 21 days after implantation. The average paralysis time of 18 experimental rabbits successfully modeled was 24.44 ± 2.38 days, and MWA/PVP/MWA + PVP treatment was performed in groups immediately after paralysis. Except for 2 rabbits who died due to anesthesia overdose during anesthesia before treatment, the remaining 16 rabbits were successfully treated with MWA/PVP/MWA + PVP, and the technical success rate was 100% (16/16). In MWA group, one experimental rabbit was randomly selected and killed after ablation, and histopathological examination (H and E staining) was performed together with 2 experimental rabbits who died of anesthesia. The pathological changes before and after ablation were compared. The survival time of the remaining 15 experimental rabbits varied from 3 to 8 days after treatment. Conclusion: The success rate of establishing rabbit vertebral tumor model by injecting tumor masses under the CT-guided percutaneous puncture is high, and the following MWA and PVP treatment can be successfully conducted. PET/CT is the most sensitive method for early detection of tumor compared with MRI and CT. Spectral Presaturation with Inversion Recovery (SPIR) sequence can significantly improve the detection rate of smaller tumors by MRI and shorten the detection time.

A Data-Driven Platform for Two-Dimensional Hybrid Lead-Halide Perovskites.

The exceptional properties of two-dimensional hybrid organic-inorganic lead-halide perovskites (2D HOIPs) have led to a rapid increase in the number of low-dimensional materials for optoelectronic engineering and solar energy conversion. The flexibility and controllability of 2D HOIPs create a vast structural space, which presents an urgent issue to effectively explore 2D HOIPs with better performance for practical applications. However, the traditional RP-DJ classification method falls short in describing the influence of structure on the electronic properties of 2D HOIPs. To overcome this limitation, we employed inorganic structure factors (SF) as a classification descriptor, which considers the influence of inorganic layer distortion of 2D HOIPs. And we investigated the relationship between SF, other physicochemical features, and band gaps of 2D HOIPs. By using this structural descriptor as a feature for a machine learning model, a database of 304920 2D HOIPs and their structural and electronic properties was generated. A large number of previously neglected 2D HOIPs were discovered. With the establishment of this database, experimental data and machine learning methods were combined to develop a 2D HOIPs exploration platform. This platform integrates searching, download, analysis, and online prediction, providing a useful tool for the further discovery of 2D HOIPs.

Epidemic trends of dyslipidemia in young adults: a real-world study including more than 20,000 samples.

BACKGROUND: There is an urgent need to learn more about the epidemiological features of dyslipidemia in youth to address the high burden of cardiovascular disease. METHODS: This experiment was an observational, cross-sectional study. The samples were collected from 22,379 college students at Xinjiang Medical University. RESULT: The overall prevalence of dyslipidemia was 13.17%, which was significantly higher in men (23%) than in women (7.2%), p < 0.01. Similarly, the prevalence rate of obesity in men (11.4%) was significantly higher than that in women (3.4%). The composition of blood lipids, such as triglyceride (TG), total cholesterol (TC), and low density lipoprotein cholesterol (LDL-C), began to increase gradually from the age of 22 and showed a sharp increase after the age of 30; however, a reverse trend was present in high density lipoprotein cholesterol (HDL-C). In terms of the proportion of dyslipidemia in both men and women, low HDL-C accounted for the largest proportion (74%), followed by elevated TGs (14.5%). The overall distribution of rates of dyslipidemia and excess weight showed a U-shaped trend with increasing age, with the lowest rates seen in the 20-24 age group. CONCLUSION: Our study sheds light on the epidemiological features of dyslipidemia in young adults and enriches the limited data available on dyslipidemia, providing a reference for the close monitoring and control of risk factors to reduce the occurrence and progression of atherosclerotic cardiovascular disease events.

Self-powered enzyme-linked microneedle patch for scar-prevention healing of diabetic wounds.

Diabetic wounds with complex pathological features and a difficult-to-heal nature remain a formidable challenge. To address this challenge, we design and fabricate a self-powered enzyme-linked microneedle (MN) patch composed of anode and cathode MN arrays, which respectively contain glucose oxidase (GOx) and horseradish peroxidase (HRP) encapsulated in ZIF-8 nanoparticles. The enzymatic cascade reaction in the MN patch can effectively reduce local hyperglycemia in diabetic wounds while generating stable microcurrents to promote rapid healing of diabetic wounds. Therefore, the diabetic wounds treated with this MN patch exhibit rapid, complete, and scar-preventative healing, which can be attributed to the synergistic actions of hypoglycemic, antibacterial, anti-inflammatory, and bioelectrical stimulation. In brief, the self-powered MN patch is an effective method to rapidly promote diabetic wound healing and prevent scar formation.

Adding nanoparticles to improve emulsion efficiency and enhance microbial degradation in Pickering emulsions.

Interfacial microbial degradation of alkane in Pickering emulsions stabilized by hydrophobic bacterial cells is a new mechanism for microbial degradation of water-insoluble chemicals, where both water-insoluble chemicals in the oil phase and water-soluble nutrients (such as nitrogen and phosphorus) in the water phase are bio-accessible to living microorganisms anchoring onto the oil-water interfaces. In the present work, super-hydrophobic Mycobacterium sp. (contact angle 168.6°) degradation of tetradecane was set up as a model. Addition of fumed SiO2 particles (Aerosil® R974) as a new strategy was developed to enhance tetradecane degradation where the biodegradation rate (based on the accumulated biomass) increased by approximately 80%. The enhanced effect of SiO2 particles on the tetradecane degradation attributed to the synergistic effect of SiO2 particles on the emulsion efficiency of Pickering emulsions stabilized by bacterial cells and then on the enhancement of interfacial microbial degradation in Pickering emulsions. KEY POINTS: • Interfacial microbial degradation in bacterial cells stabilized Pickering emulsions. • Adding fumed SiO2 particles to enhance microbial degradation of tetradecane. • Correlation relationship between emulsion efficiency and interfacial microbial degradation.

Cancer Stem-Like Cells-Oriented Surface Self-Assembly to Conquer Radioresistance.

Cancer stem-like cells (CSCs), capable of indefinite self-renewal and differentiation, are considered to be the root cause of tumor radiotherapy (RT) resistance. However, the CSCs-targeted therapy still remains to be a great challenge because they are commonly located in the deep tumor making drugs hard to approach, and their hypoxic and acidic niche can further aggravate radioresistance. Herein, based on the finding that hypoxic CSCs highly express carbonic anhydrase IX (CAIX) on the cell membrane, a CAIX-targeted induced in situ self-assembly system on the surface of CSC is reported to overcome hypoxic CSC-mediated radioresistance. Via the sequential processes of "monomer release-target accumulation-surface self-assembly", the constructed peptide-based drug delivery system (CA-Pt) exhibits the advantages of deep penetration, amplified CAIX inhibition, and enhanced cellular uptake, which greatly relieves the hypoxic and acidic microenvironment to promote the hypoxic CSC differentiation and combines with platinum to boost the RT-inducing DNA damage. In both lung cancer tumor mouse and zebrafish embryo models, CA-Pt treatment can effectively assist RT in suppressing tumor growth and preventing tumor invasion and metastasis. This study uses a surface-induced self-assembly strategy to differentiate hypoxic CSCs, which may provide a universal treatment strategy for overcoming tumor radioresistance.

Machine-learning-assisted rational design of 2D doped tellurene for fin field-effect transistor devices.

Fin field-effect transistors (FinFETs) have been widely used in electronic devices on account of their excellent performance, but this new type of device is facing many challenges because of size constraints. Two-dimensional (2D) materials with a layer structure can meet the required thickness of FinFETs and provide ideal carrier transport performance. In this work, we used 2D tellurene as the parent material and modified it with doping techniques to improve electronic device performance. High-performance FinFET devices were prepared with 23 systems screened from 385 doping systems by a combination of first-principle calculations and a machine-learning (ML) model. Moreover, theoretical calculations demonstrated that 1S1@Te and 2S2@Te have high carrier mobility and stability with an electron mobility and a hole mobility of 6.211 × 104 cm2 V-1 S-1 and 1.349 × 104 cm2 V-1 S-1, respectively. This work can provide a reference for subsequent experiments and advance the development of functional materials by using an ML-assisted design paradigm.

Robust adaptive beamforming based on zone orthogonal constraint and steering vector estimation.

This Letter solves steering vector estimation under mismatch for adaptive beamforming. The proposed beamformer implements a stepwise estimation of steering vector, and zone orthogonal constraint is added first based on adaptive constraint framework from Khabbazibasmenj [IEEE Trans. Signal Process. 60(6), 2974-2987 (2012)], which ensures that the estimated steering vector does not converge to an interference steering vector outside the predefined sector, even if the sector deviates from the central observation area of arrays. Then uncertainty set error constraint is used to improve the estimation accuracy. The numerical simulation and experimental results verify the effectiveness of the proposed method.