Self-Powered and Self-Recoverable Multimodal Force Sensors Based on Trap State and Interfacial Electron Transfer.

Multi-dimensional force sensing that combines intensity, location, area and the like could gather a wealth of information from mechanical stimuli. Developing materials with force-induced optical and electrical dual responses would provide unique opportunities to multi-dimensional force sensing, with electrical signals quantifying the force amplitude and the luminescence output providing spatial distribution of force. However, the reliance on external power supply and high-energy excitation source brings significant challenges to the applicability of multi-dimensional force sensors. Here we reported the mechanical energy-driven and sunlight-activated materials with force-induced dual responses, and investigated the underlying mechanisms of self-sustainable force sensing. Theoretical analysis and experimental data unraveled that trap-controlled luminescence and interfacial electron transfer play a major role in force-induced optical and electrical output. These materials were manufactured into pressure sensor with renewable dual-mode output for quantifying and visualization of pressures by electrical and optical output, respectively, without power supply and high-energy irradiation. The quantification of tactile sensation and stimuli localization of mice highlighted the multi-dimensional sensing ability of the sensor. Overall, this self-powered pressure sensor with multimodal output provides more modalities of force sensing, poised to change the way that intelligent devices sense with the world.

Orbital Electrowetting-on-Dielectric for Droplet Manipulation on Superhydrophobic Surfaces.

Electrowetting-on-dielectric (EWOD), recognized as the most successful electrical droplet actuation method, is essential in diverse applications, ranging from thermal management to microfluidics and water harvesting. Despite significant advances, it remains challenging to achieve repeatability, high speed, and simple circuitry in EWOD-based droplet manipulation on superhydrophobic surfaces. Moreover, its efficient operation typically requires electrode arrays and sophisticated circuit control. Here, a newly observed droplet manipulation phenomenon on superhydrophobic surfaces with orbital EWOD (OEW) is reported. Due to the asymmetric electrowetting force generated on the orbit, flexible and versatile droplet manipulation is facilitated with OEW. It is demonstrated that OEW droplet manipulation on superhydrophobic surfaces exhibits higher speed (up to 5 times faster), enhanced functionality (antigravity), and manipulation of diverse liquids (acid, base, salt, organic, e.g., methyl blue, artificial blood) without contamination, and good durability after 1000 tests. It is envisioned that this robust droplet manipulation strategy using OEW will provide a valuable platform for various processes involving droplets, spanning from microfluidic devices to controllable chemical reactions. The previously unreported droplet manipulation phenomenon and control strategy shown here can potentially upgrade EWOD-based microfluidics, antifogging, anti-icing, dust removal, and beyond.

A Comprehensive Interaction Network Constructed Using miRNAs and mRNAs Provides New Insights into Potato Tuberization under High Temperatures.

High temperatures delay tuberization and decrease potato (Solanum tuberosum L.) yields. However, the molecular mechanisms and regulatory networks underlying tuberization under high temperatures remain largely unknown. Here, we performed the mRNA and miRNA sequencing of leaves and stems to identify genes and regulatory networks involved in tuberization under high temperatures. A total of 2804 and 5001 differentially expressed genes (DEGs) under high-temperature stress were identified in leaves and stems, respectively. These genes were significantly enriched in gene ontology terms regarding meristem development, the sucrose biosynthetic process, and response to heat. Meanwhile, 101 and 75 differentially expressed miRNAs (DEmiRNAs) were identified in leaves and stems, respectively. We constructed an interaction network between DEmiRNAs and DEGs, identifying 118 and 150 DEmiRNA-DEG pairs in leaves and stems, respectively. We found three miRNA-mRNA candidate modules involved in tuberization under high temperatures, including stu-miR8030-5p/StCPY714, stu-miR7981f-p5/StAGL8a, and stu-miR10532A/StAGL8b. Our study constructed an interaction network between miRNAs and target genes and proposes candidate miRNA-gene modules that regulate tuber formation under high temperatures. Our study provides new insights for revealing the regulatory mechanism of the high-temperature inhibition of tuberization and also provides gene resources for improving the heat tolerance in potatoes.

In Vitro Modeling of Recurrent Dermatofibrosarcoma Protuberans: Assessment of 5-Aminolevulinic Acid Photodynamic Therapy Efficacy.

BACKGROUND: Dermatofibrosarcoma Protuberans (DFSP) is a rare, low-grade malignant tumor of the dermis with a high recurrence rate post-surgery. Current treatments, including surgery, radiotherapy, and targeted therapy, have limitations. Photodynamic therapy (PDT) with 5-aminolevulinic acid (5-ALA) is a promising non-invasive approach, but its efficacy in DFSP treatment remains underexplored. METHODS: This study aimed to evaluate the anti-tumor efficacy of 5-ALA PDT using an in vitro model derived from a recurrent DFSP patient. The cells were treated with varying concentrations of 5-ALA and exposed to red light, followed by assessments of cell viability, proliferation, apoptosis, migration, invasion, angiogenesis, and expression of DFSP-related genes and proteins. RESULTS: 5-ALA PDT significantly reduced DFSP cell viability in a dose-dependent manner and induced apoptosis. It also effectively inhibited cell proliferation, migration, and invasion, as well as suppressed angiogenic activity in conditioned media. Furthermore, 5-ALA PDT downregulated the expression of COL1A1 and PDGFRB, key genes in DFSP pathogenesis. CONCLUSIONS: The findings provide the first evidence of 5-ALA PDT's in vitro anti-tumor efficacy against DFSP, suggesting its potential as a novel therapeutic approach for DFSP. Further studies are warranted to explore the clinical utility of 5-ALA PDT in preventing DFSP recurrence.

IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning.

BACKGROUND: The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and functions in microbial communities. However, the rapid mutation rates of viral genomes pose challenges in developing high-performance tools for classification, potentially limiting downstream analyses. FINDINGS: We present IPEV, a novel method to distinguish prokaryotic and eukaryotic viruses in viromes, with a 2-dimensional convolutional neural network combining trinucleotide pair relative distance and frequency. Cross-validation assessments of IPEV demonstrate its state-of-the-art precision, significantly improving the F1-score by approximately 22% on an independent test set compared to existing methods when query viruses share less than 30% sequence similarity with known viruses. Furthermore, IPEV outperforms other methods in accuracy on marine and gut virome samples based on annotations by sequence alignments. IPEV reduces runtime by at most 1,225 times compared to existing methods under the same computing configuration. We also utilized IPEV to analyze longitudinal samples and found that the gut virome exhibits a higher degree of temporal stability than previously observed in persistent personal viromes, providing novel insights into the resilience of the gut virome in individuals. CONCLUSIONS: IPEV is a high-performance, user-friendly tool that assists biologists in identifying and classifying prokaryotic and eukaryotic viruses within viromes. The tool is available at https://github.com/basehc/IPEV.

Direct aqueous photochemistry of methylglyoxal and its effect on sulfate formation.

In recent years, among many oxidation pathways studied for atmospheric sulfate formation, the aqueous phase oxidation pathways of H2O2 and organic hydroperoxides (ROOHs) have attracted great scientific attention. Higher concentrations of H2O2 and ubiquitous ROOHs have been observed in atmospheric aqueous phase environments (cloud water, fog droplets, etc.). However, there are still some gaps in the study of their aqueous phase generation and their influences on sulfate formation. In this study, the aqueous phase photochemical reaction of methylglyoxal, a ubiquitous organic substance in the atmospheric aqueous phase, was studied under UV irradiation, and the generation of H2O2 and ROOHs in this system was investigated. It is found for the first time that the aqueous phase photolysis of methylglyoxal not only produces H2O2 but also produces ROOHs, and UV light and O2 are necessary for the formation of H2O2 and ROOHs. Based on the experimental results, the possible mechanism of aqueous phase photochemistry of methylglyoxal and the generation of H2O2 and ROOHs were proposed. The effect of aqueous phase photolysis of methylglyoxal on sulfate formation under different conditions was also investigated. The results show that the aqueous phase photolysis of methylglyoxal significantly promoted SO2 oxidation and sulfate formation, in which SO2 oxidation was realized by the generated H2O2, ROOHs and •OH radicals, and the importance of the formed ROOHs cannot be ignored. These results fill some gaps in the field of aqueous phase H2O2 and ROOHs production, and to a certain extent confirm the important roles of the aqueous phase photolysis of methylglyoxal and the formed H2O2 and ROOHs in the production of sulfate. The study reveals the new sources of H2O2 and ROOHs, and provides a new insight into the heterogeneous aqueous phase oxidation pathways and mechanisms of SO2 in cloud and fog droplets and haze particles.

The developmental origins of health and disease and intergenerational inheritance: a scoping review of multigenerational cohort studies.

Epidemiologic research has increasingly acknowledged the importance of developmental origins of health and disease (DOHaD) and suggests that prior exposures can be transferred across generations. Multigenerational cohorts are crucial to verify the intergenerational inheritance among human subjects. We carried out this scoping review aims to summarize multigenerational cohort studies' characteristics, issues, and implications and hence provide evidence to the DOHaD and intergenerational inheritance. We adopted a comprehensive search strategy to identify multigenerational cohorts, searching PubMed, EMBASE, and Web of Science databases from the inception of each dataset to June 20th, 2022, to retrieve relevant articles. After screening, 28 unique multigenerational cohort studies were identified. We classified all studies into four types: population-based cohort extended three-generation cohort, birth cohort extended three-generation cohort, three-generation cohort, and integrated birth and three-generation cohort. Most cohorts (n = 15, 53%) were categorized as birth cohort extended three-generation studies. The sample size of included cohorts varied from 41 to 167,729. The study duration ranged from two years to 31 years. Most cohorts had common exposures, including socioeconomic factors, lifestyle, and grandparents' and parents' health and risk behaviors over the life course. These studies usually investigated intergenerational inheritance of diseases as the outcomes, most frequently, obesity, child health, and cardiovascular diseases. We also found that most multigenerational studies aim to disentangle genetic, lifestyle, and environmental contributions to the DOHaD across generations. We call for more research on large multigenerational well-characterized cohorts, up to four or even more generations, and more studies from low- and middle-income countries.

Evaluating disease status in idiopathic inflammatory myopathies with quantitative muscle ultrasound.

INTRODUCTION/AIMS: Muscle strength, functional status, and muscle enzymes are conventionally used to evaluate disease status in idiopathic inflammatory myopathies (IIM). This study aims to investigate the role of quantitative muscle ultrasound in evaluating disease status in IIM patients. METHODS: Patients with IIM, excluding inclusion body myositis, were recruited along with age- and sex-matched healthy controls (HC). All participants underwent muscle ultrasound and clinical assessments. Six limb muscles were unilaterally scanned using a standardized protocol, measuring muscle thickness (MT) and echo intensity (EI). Results were compared with HC, and correlations were made with outcome measures. RESULTS: Twenty IIM patients and 24 HC were recruited. The subtypes of IIM were dermatomyositis (6), necrotizing myositis (6), polymyositis (3), antisynthetase syndrome (3), and nonspecific myositis (2). Mean disease duration was 8.7 ± 6.9 years. There were no significant differences in demographics and anthropometrics between patients and controls. MT of rectus femoris in IIM patients was significantly lower than HC. Muscle EI of biceps brachii and vastus medialis in IIM patients were higher than HC. There were moderate correlations between MT of rectus femoris and modified Rankin Scale, Physician Global Activity Assessment, and Health Assessment Questionnaire, as well as between EI of biceps brachii and Manual Muscle Testing-8. DISCUSSION: Muscle ultrasound can detect proximal muscle atrophy and hyperechogenicity in patients with IIM. The findings correlate with clinical outcome measures, making it a potential tool for evaluating disease activity of patients with IIM in the late phase of the disease.

Evaluating the accuracy of the Ophthalmologist Robot for multiple blindness-causing eye diseases: a multicentre, prospective study protocol.

INTRODUCTION: Early eye screening and treatment can reduce the incidence of blindness by detecting and addressing eye diseases at an early stage. The Ophthalmologist Robot is an automated device that can simultaneously capture ocular surface and fundus images without the need for ophthalmologists, making it highly suitable for primary application. However, the accuracy of the device's screening capabilities requires further validation. This study aims to evaluate and compare the screening accuracies of ophthalmologists and deep learning models using images captured by the Ophthalmologist Robot, in order to identify a screening method that is both highly accurate and cost-effective. Our findings may provide valuable insights into the potential applications of remote eye screening. METHODS AND ANALYSIS: This is a multicentre, prospective study that will recruit approximately 1578 participants from 3 hospitals. All participants will undergo ocular surface and fundus images taken by the Ophthalmologist Robot. Additionally, 695 participants will have their ocular surface imaged with a slit lamp. Relevant information from outpatient medical records will be collected. The primary objective is to evaluate the accuracy of ophthalmologists' screening for multiple blindness-causing eye diseases using device images through receiver operating characteristic curve analysis. The targeted diseases include keratitis, corneal scar, cataract, diabetic retinopathy, age-related macular degeneration, glaucomatous optic neuropathy and pathological myopia. The secondary objective is to assess the accuracy of deep learning models in disease screening. Furthermore, the study aims to compare the consistency between the Ophthalmologist Robot and the slit lamp in screening for keratitis and corneal scar using the Kappa test. Additionally, the cost-effectiveness of three eye screening methods, based on non-telemedicine screening, ophthalmologist-telemedicine screening and artificial intelligence-telemedicine screening, will be assessed by constructing Markov models. ETHICS AND DISSEMINATION: The study has obtained approval from the ethics committee of the Ophthalmology and Optometry Hospital of Wenzhou Medical University (reference: 2023-026 K-21-01). This work will be disseminated by peer-review publications, abstract presentations at national and international conferences and data sharing with other researchers. TRIAL REGISTRATION NUMBER: ChiCTR2300070082.

Inhibition of HMGB1 improves experimental mice colitis by mediating NETs and macrophage polarization.

OBJECTIVE: Inflammatory bowel disease (IBD) is listed by the World Health Organization as one of the modern intractable diseases. High mobility histone box 1 (HMGB1), originally described as a non-histone nucleoprotein involved in transcriptional regulation, was later identified as a pro-inflammatory cytokine that may contribute to the pathogenesis of inflammatory diseases such as IBD. Neutrophil extracellular traps (NETs) play an important role in the pathophysiology of IBD The aim of this study was to investigate the role of HMGB1 in experimental colitis mice and its potential mechanisms of action. METHODS: We first constructed the experimental colitis mouse model. Intervention of mice by rhHMGB1 supplementation or HMGB1 inhibition. The pathological morphology of the colon was observed using HE staining. Apoptosis of colonic tissue intestinal epithelial cells was evaluated using Tunel assay. The expression of HMGB1, ZO-1 and occludin in colon tissue was detected by immunohistochemistry, ELISA and western-blot. We also assessed the effects of HMGB1 on colonic injury, NETs content, macrophage polarization and inflammatory cells in mice. The regulatory effect of HMGB1 inhibition on NETs was assessed by combining DNase I. RESULTS: Inhibition of HMGB1 significantly reduced the inflammatory model in experimental colitis mice, as evidenced by reduced body weight, increased colonic length, reduced DAI scores and apoptosis, reduced inflammatory response, and improved colonic histopathological morphology and intestinal mucosal barrier function. Meanwhile, inhibition of HMGB1 was able to reduce the expression of CD86, citH3 and MPO and increase the expression of CD206 in the colonic tissue of mice. In addition, DNase I intervention was also able to improve colonic inflammation in mice. And the best effect was observed when DNase I and inhibition of HMGB1 were intervened together. CONCLUSION: Inhibition of HMGB1 ameliorates IBD by mediating NETs and macrophage polarization.

Microwave ablation for recurrent primary hyperparathyroidism in four patients with multiple endocrine neoplasia type 1: a case series report.

Multiple endocrine neoplasia type 1 (MEN1), a rare tumor syndrome, is inherited in an autosomal dominant pattern, mainly manifested as primary hyperparathyroidism (PHPT). Surgery is preferred for patients with MEN1 and PHPT. Thermal ablation has been widely applied for PHPT but rarely for postoperative recurrent PHPT in MEN1 patients. Based on a series of cases, we aimed to investigate the clinical efficacy and safety of ultrasound-guided percutaneous microwave ablation in the treatment of MEN1 patients with postoperative recurrence of PHPT.

Fluorescent sensing platform based on polyethyleneimine-protected copper nanoclusters for detection of chromium(VI) in real samples.

A new type of polyethyleneimine-protected copper nanoclusters (PEI-CuNCs) is favorably developed by a one-pot method under mild conditions. The obtained PEI-CuNCs is characterized by X-ray diffraction, X-ray photoelectron spectroscopy, transmission electron microscopy, Fourier-transform infrared (FTIR) spectroscopy and other techniques. It is worth noting that the proposed PEI-CuNCs demonstrate a selective response to chromium(VI) over other competitive species. Fluorescence quenching of PEI-CuNCs is determined to be chromium(VI) concentrations dependence with a low limit of detection of 8.9 nM. What is more, the as-developed PEI-CuNCs is further employed in building a detection platform for portable recognition of chromium(VI) in real samples with good accuracy. These findings may offer a distinctive strategy for the development of methods for analyzing and monitoring chromium(VI) and expand their application in real sample monitoring.

Ursolic acid loaded tri-block copolymer nanoparticles based on triphenylphosphine for mitochondria-targeted cancer therapy.

A novel biodegradable amphiphilic triblock copolymer, polyphosphate, polyethylene glycol, and polylactic acid (PAEEP-PEG-PLLA), was synthesized by twice ring-opening polymerization and triphenylphosphine (TPP) was grafted onto the block copolymer to synthesize a carrier material TPP-PAEEP-PEG-PLLA, which was identified by1H-nuclear magnetic resonance (1H-NMR) spectroscopy. The TPP-PAEEP-PEG-PLLA nanoparticles encapsulated with ursolic acid (UA) were prepared by the emulsion-solvent evaporation method and characterized by dynamic light scattering. The mitochondrial targeting ability of fluorescently labeled nanoparticles was evaluated by laser confocal microscopy. The average particle size and surface charge of the UA -loaded nanoparticle solution were 180.07 ± 1.67 nm and +15.57 ± 1.33 mV, respectively. The biocompatibility of nanoparticles was briefly evaluated by erythrocyte hemolysis assay.In vitrocell proliferation assay and scratch migration assay were performed to compare the difference in anti-tumor effect between UA and UA nanoparticles. The results showed that TPP-modified triblock copolymers had good mitochondrial targeting and improved the low bioavailability of UA, and UA nanoparticles exhibited more pronounced anti-tumor capabilities. In summary, the results suggested that our UA nanoparticles were a promising drug-targeted delivery system for the treatment of tumors.

It takes two: Dual Branch Augmentation Module for domain generalization.

Although great success has been achieved in various computer vision tasks, deep neural networks (DNNs) suffer dramatic performance degradation when evaluated on out-of-distribution data. Domain generalization (DG) is proposed to handle this problem by learning domain-agnostic information from multiple source domains to generalize well on unseen target domains. Several methods resort to Fourier transform due to its simplicity and efficiency. They argue that amplitude spectra imply domain-specific information, which should be suppressed, while phase counterparts imply domain-agnostic information, which should be preserved. However, these methods only suppress the domain-specific information in source domains and neglect the relationship with target domains, leading to the persistence of the domain gap. Besides, these methods preserve domain-agnostic information by keeping phase components unchanged, causing them to be underutilized. In this paper, we propose Dual Branch Augmentation Module (DBAM) by leveraging Fourier transform and taking advantage of both amplitude and phase spectra. For the amplitude branch, we propose Inner-domain Amplitude Distribution Rectification (IADR) and Cross-domain Amplitude Dirichlet Mixup (CADM) to stabilize the training process and explore more feature space. In addition, we propose Test-time Amplitude Prototype Calibration (TAPC) to construct the connection between source and target domains during evaluation to further mitigate the domain gap. For the phase branch, we propose Random Symmetric Phase Perturbation (RSPP) to enhance the robustness for recognizing domain-agnostic information. With the combined contributions of the two branches, DBAM significantly surpasses other state-of-the-art (SOTA) methods. Extensive experiments on four benchmarks and further analysis demonstrate the effectiveness of DBAM.

The Efficacy of Virtual Fracture Clinics (VFCs) and the Impact of Physician Risk Appetite on Discharge Rates.

Background and objectives Virtual fracture clinics (VFCs) allow the triage of emergency department referrals to identify those requiring further care and those that are suitable for discharge. Appropriate discharge from VFC benefits the patient and the healthcare provider by avoiding unnecessary face-to-face appointments. This study investigates factors associated with VFC discharge rates at our hospital and detects potential areas for improvement. Methodology A retrospective review was conducted on 4819 consecutive VFC referrals between March 17, 2021, and March 16, 2022, from a single hospital. Patient demographics, referral outcomes, and triaging consultant data were collected. Sixteen consultants conducted daily VFCs during the study period. Eleven consultants completed the DOSPERT psychometric test to measure their attitude toward risk. The data was analysed using Spearman's rho and Chi-square tests. Results The mean discharge from VFC was 35.4% (29.6-41.0%). The highest rates of discharge were for back pain (100%), followed by fractures of the pubic ramus (100%), the base of the fifth metatarsal (86.89%), the acetabulum (75%), and the proximal radius (73.03%). Consultant experience was significantly negatively correlated with discharge rate (p<0.05). The frequency of conducting a VFC was not associated with the discharge rate (p=0.758). In subspecialty analysis, 90% of lower limb consultants discharged more lower limb presentations from VFC, compared with upper limb consultants (p=0.001). There was no significant correlation between DOSPERT scores and discharge rates (p=0.65). Conclusions VFC remains an important tool for patient care. Consultant experience is associated with a more cautious approach to discharge; however, there was no relationship between a consultant's risk attitude and their VFC discharge rate in this study. Lower-limb consultants appear to discharge lower-limb injuries more readily when compared with their upper-limb colleagues. These insights could be used to improve emergency department and VFC efficiency.

Inhibitor of PD-1/PD-L1: a new approach may be beneficial for the treatment of idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a globally prevalent, progressive disease with limited treatment options and poor prognosis. Because of its irreversible disease progression, IPF affects the quality and length of life of patients and imposes a significant burden on their families and social healthcare services. The use of the antifibrotic drugs pirfenidone and nintedanib can slow the progression of the disease to some extent, but it does not have a reverse effect on the prognosis. The option of lung transplantion is also limited owing to contraindications to transplantation, possible complications after transplantation, and the risk of death. Therefore, the discovery of new, effective treatment methods is an urgent need. Over recent years, various studies have been undertaken to investigate the relationship between interstitial pneumonia and lung cancer, suggesting that some immune checkpoints in IPF are similar to those in tumors. Immune checkpoints are a class of immunosuppressive molecules that are essential for maintaining autoimmune tolerance and regulating the duration and magnitude of immune responses in peripheral tissues. They can prevent normal tissues from being damaged and destroyed by the immune response. While current studies have focused on PD-1/PD-L1 and CTLA-4, PD-1/PD-L1 may be the only effective immune checkpoint IPF treatment. This review discusses the application of PD-1/PD-L1 checkpoint in IPF, with the aim of finding a new direction for IPF treatment.

CXCL6 promotes the progression of NAFLD through regulation of PPARα.

An increasing number of studies have shown that Nonalcoholic fatty liver disease (NAFLD) is strongly associated with obesity, insulin resistance, dyslipidemia, hypertension and metabolic syndrome, but its specific pathogenesis remains unclear. By analyzing GEO database, we found CXCL6 was upregulated in liver tissues of patients with NAFLD. We also confirmed with qPCR that CXCL6 is highly expressed in serum of patients with NAFLD. To identify the underlying impact of CXCL6 on NAFLD, we established animal and cell models of NAFLD. Similarly, we confirmed by qPCR and Western blot that CXCL6 was upregulated in the NAFLD model in vitro and vivo. After transfecting NAFLD cells with siRNA targeting CXCL6 (si-CXCL6), a series of functional experiments were carried out, and these data indicated that the inhibition of CXCL6 reduced intracellular lipid deposition, decreased AST, ALT and TG level, facilitate cell proliferation and suppress their apoptosis. Furthermore, western blot and qPCR analyses displayed that the suppression of CXCL6 could raise the PPARα expression, but PPAR α inhibitor, GW6471 could partially counteract this effect. What's more, Oil Red O staining, biochemical analyzer and TG detection kit revealed that GW6471 could reverse the inhibitory effect of si-CXCL6 on NAFLD. In summary, we provide convincing evidence that CXCL6 is markedly elevated in NAFLD, and the CXCL6/PPARα regulatory network mediates disease progression of NAFLD.

A Biomimetic Nociceptor Using Centrosymmetric Crystals for Machine Intelligence.

Pain sensation is a crucial aspect of perception in the body. Force-activated nociceptors encode electrochemical signals and yield multilevel information of pain, thus enabling smart feedback. Inspired by the natural template, multi-dimensional mechano-sensing materials provide promising approaches for biomimetic nociceptors in intelligent terminals. However, the reliance on non-centrosymmetric crystals has narrowed the range of these materials. Here centrosymmetric crystal Cr3+ -doped zinc gallogermanate (ZGGO:Cr) with multi-dimensional mechano-sensing is reported, eliminating the limitation of crystal structure. Under forces, ZGGO:Cr generates electrical signals imitating those of neuronal systems, and produces luminescence for spatial mapping of mechanical stimuli, suggesting a path toward bionic pain perception. On that basis, a wireless biomimetic nociceptor system is developed and a smart pain reflex in a robotic hand and robot-assisted biopsy surgery of rat and dog is achieved.

Regulation of Cellular Signaling with an Aptamer Inhibitor to Impede Cancer Metastasis.

Tumor invasion and metastasis are the main causes of tumor progression and are the leading causes of death among cancer patients. In the present study, we propose a strategy to regulate cellular signaling with a tumor metastasis-relevant cytoskeleton-associated protein 4 (CKAP4) specific aptamer for the achievement of tumor metastasis inhibition. The designed aptamer could specifically bind to CKAP4 in the cell membranes and cytoplasm to block the internalization and recycling of α5ß1 integrin, resulting in the disruption of the fibronectin-dependent cell adhesion and the weakening of the cell traction force. Moreover, the aptamer is able to impede the interaction between CKAP4 and Dickkopf1 (DKK1) to further block the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway, which subsequently reduces AKT phosphorylation and inhibits the reorganization of the actin cytoskeleton in cell migration. The synergetic function of the designed aptamer in inhibiting cancer cell adhesion and blocking the PI3K signaling pathway enables efficient tumor cell metastasis suppression. The aptamer with specific targeting ability in regulating cellular signaling paves the way for cancer treatment and further provides a guiding ideology for inhibiting tumor metastasis.

Bridging the gap with grad: Integrating active learning into semi-supervised domain generalization.

Domain generalization (DG) aims to generalize from a large amount of source data that are fully annotated. However, it is laborious to collect labels for all source data in practice. Some research gets inspiration from semi-supervised learning (SSL) and develops a new task called semi-supervised domain generalization (SSDG). Unlabeled source data is trained jointly with labeled one to significantly improve the performance. Nevertheless, different research adopts different settings, leading to unfair comparisons. Moreover, the initial annotation of unlabeled source data is random, causing unstable and unreliable training. To this end, we first specify the training paradigm, and then leverage active learning (AL) to handle the issues. We further develop a new task called Active Semi-supervised Domain Generalization (ASSDG), which consists of two parts, i.e., SSDG and AL. We delve deep into the commonalities of SSL and AL and propose a unified framework called Gradient-Similarity-based Sample Filtering and Sorting (GSSFS) to iteratively train the SSDG and AL parts. Gradient similarity is utilized to select reliable and informative unlabeled source samples for these two parts respectively. Our methods are simple yet efficient, and extensive experiments demonstrate that our methods can achieve the best results on the DG datasets in the low-data regime without bells and whistles.