A nanowell-based MoS2 neuroelectrode for high-sensitivity neural recording.

Implantable neural electrodes are crucial in neurological diagnosis and therapy because of their ultra-high spatial resolution, but they are constrained by high impedance and insufficient charge injection capacity, resulting in noise that often obscures valuable signals. Emerging nanotechnologies are powerful tools to improve sensitivity and biocompatibility. Herein, we developed quantized 2D MoS2 electrodes by incorporating bioactive MoS2 nanosheets onto bare electrodes, achieving sensitive, compatible recording. The 2D materials can create tiny nanowells, which behaved as quantized charge storage units and thus improved sensitivity. The key sensitivity indicators, impedance and cathode charge storage capacity, showed a multifold increase. The 17.7-fold improvement in catalytic activity of MoS2 electrodes facilitated effective current transmission and reduced inflammatory response. In vivo recording showed that the sensitivity of local field potentials increased throughout frequency range and peaked at a 4.7-fold in ß rhythm. This work provides a general strategy for achieving effective diagnoses of neurological disorders.

Sensing the Small Change of Intermolecular Distance in Supramolecular Assembly by Using the Tunable Emission Wavelength of AIE-Active Luminogens.

The distinct molecular states - single molecule, assembly, and aggregate - of two ionic macromolecules, TPPE-APOSS and TPE-APOSS, are easily distinguishable through their tunable fluorescence emission wavelengths, which reflect variations in intermolecular distances. Both ionic macromolecules contain aggregation-induced emission (AIE) active moieties whose emission wavelengths are directly correlated to their mutual distances in solution: far away from each other as individual molecules, maintaining a tunable and relatively long distance in electrostatic interactions-controlled blackberry-type assemblies (microphase separation), or approaching van der Waals close distance in aggregates (macrophase separation). Furthermore, within the blackberry assemblies, the emission wavelength decreases monotonically with increasing assembly size, indicative of shorter intermolecular distances at nanoscale. The emission changes of TPPE-APOSS blackberry assemblies can even be visually distinguishable by eyes when their sizes and intermolecular distances are tuned. Molecular dynamics simulations further revealed that macromolecules are confined in various conformations by controllable intermolecular distances within the blackberry structure, thereby resulting in fluorescence emission with tunable wavelength.

Asymmetrical Contrastive Learning Network via Knowledge Distillation for No-Service Rail Surface Defect Detection.

Owing to extensive research on deep learning, significant progress has recently been made in trackless surface defect detection (SDD). Nevertheless, existing algorithms face two main challenges. First, while depth features contain rich spatial structure features, most models only accept red-green-blue (RGB) features as input, which severely constrains performance. Thus, this study proposes a dual-stream teacher model termed the asymmetrical contrastive learning network (ACLNet-T), which extracts both RGB and depth features to achieve high performance. Second, the introduction of the dual-stream model facilitates an exponential increase in the number of parameters. As a solution, we designed a single-stream student model (ACLNet-S) that extracted RGB features. We leveraged a contrastive distillation loss via knowledge distillation (KD) techniques to transfer rich multimodal features from the ACLNet-T to the ACLNet-S pixel by pixel and channel by channel. Furthermore, to compensate for the lack of contrastive distillation loss that focuses exclusively on local features, we employed multiscale graph mapping to establish long-range dependencies and transfer global features to the ACLNet-S through multiscale graph mapping distillation loss. Finally, an attentional distillation loss based on the adaptive attention decoder (AAD) was designed to further improve the performance of the ACLNet-S. Consequently, we obtained the ACLNet-S ∗ , which achieved performance similar to that of ACLNet-T, despite having a nearly eightfold parameter count gap. Through comprehensive experimentation using the industrial RGB-D dataset NEU RSDDS-AUG, the ACLNet-S ∗ (ACLNet-S with KD) was confirmed to outperform 16 state-of-the-art methods. Moreover, to showcase the generalization capacity of ACLNet-S ∗ , the proposed network was evaluated on three additional public datasets, and ACLNet-S ∗ achieved comparable results. The code is available at https://github.com/Yuride0404127/ACLNet-KD.

Histone deacetylase inhibition enhances extracellular vesicles from muscle to promote osteogenesis via miR-873-3p.

Regular physical activity is widely recognized for reducing the risk of various disorders, with skeletal muscles playing a key role by releasing biomolecules that benefit multiple organs and tissues. However, many individuals, particularly the elderly and those with clinical conditions, are unable to engage in physical exercise, necessitating alternative strategies to stimulate muscle cells to secrete beneficial biomolecules. Histone acetylation and deacetylation significantly influence exercise-induced gene expression, suggesting that targeting histone deacetylases (HDACs) could mimic some exercise responses. In this study, we explored the effects of the HDAC inhibitor Trichostatin A (TSA) on human skeletal muscle myoblasts (HSMMs). Our findings showed that TSA-induced hyperacetylation enhanced myotube fusion and increased the secretion of extracellular vesicles (EVs) enriched with miR-873-3p. These TSA-EVs promoted osteogenic differentiation in human bone marrow mesenchymal stem cells (hBMSCs) by targeting H2 calponin (CNN2). In vivo, systemic administration of TSA-EVs to osteoporosis mice resulted in significant improvements in bone mass. Moreover, TSA-EVs mimicked the osteogenic benefits of exercise-induced EVs, suggesting that HDAC inhibition can replicate exercise-induced bone health benefits. These results demonstrate the potential of TSA-induced muscle-derived EVs as a therapeutic strategy to enhance bone formation and prevent osteoporosis, particularly for individuals unable to exercise. Given the FDA-approved status of various HDAC inhibitors, this approach holds significant promise for rapid clinical translation in osteoporosis treatment.

Protective effects of sodium humate on the intestinal barrier damage of Salmonella Typhimurium-challenged broilers.

Salmonella Typhimurium (S. Typhimurium) infections can lead to severe intestinal damage and reduce growth performance in broilers. Thus, this study examined the potential mitigating impact of sodium humate (HNa) on intestinal barrier damage resulting from S. Typhimurium infection in broilers. A total of 320 1-day-old Arbor Acres broilers were randomly assigned into 5 treatments with 8 replicates. On d 22-24, broilers in the CON group were challenged with 1 ml of PBS, while broilers in the other groups were challenged with 1 ml of 3 × 109 CFU/ml S. Typhimurium, daily. Dietary administration with 4 g/kg of HNa increased (P < 0.05) the final body weight, jejunal secretory immunoglobulin A (sIgA), total antioxidant capacity (T-AOC), total superoxide dismutase (T-SOD), and catalase (CAT) levels as compared with the MOD group broilers. Furthermore, HNa alleviated intestinal barrier damage by increasing villus height (VH), upregulating protein expression of Occludin, Claudin-1, and zonula occludens-1 (ZO-1), inhibiting toll-like receptor 4 (TLR4)/nuclear factor kappa-B (NF-κB) signaling pathway activation, and decreasing the secretion of inflammatory cytokines (P < 0.05). Collectively, the present study showed that HNa mitigated intestinal barrier damage induced by S. Typhimurium infection in broilers.

ESSN: An Efficient Sleep Sequence Network for Automatic Sleep Staging.

By modeling the temporal dependencies of sleep sequence, advanced automatic sleep staging algorithms have achieved satisfactory performance, approaching the level of medical technicians and laying the foundation for clinical assistance. However, existing algorithms cannot adapt well to computing scenarios with limited computing power, such as portable sleep detection and consumer-level sleep disorder screening. In addition, existing algorithms still have the problem of N1 confusion. To address these issues, we propose an efficient sleep sequence network (ESSN) with an ingenious structure to achieve efficient automatic sleep staging at a low computational cost. A novel N1 structure loss is introduced based on the prior knowledge of N1 transition probability to alleviate the N1 stage confusion problem. On the SHHS dataset containing 5,793 subjects, the overall accuracy, macro F1, and Cohen's kappa of ESSN are 88.0%, 81.2%, and 0.831, respectively. When the input length is 200, the parameters and floating-point operations of ESSN are 0.27M and 0.35G, respectively. With a lead in accuracy, ESSN inference is twice as fast as L-SeqSleepNet on the same device. Therefore, our proposed model exhibits solid competitive advantages comparing to other state-of-the-art automatic sleep staging methods.

PIM1-HDAC2 axis modulates intestinal homeostasis through epigenetic modification.

The mucosal barrier is crucial for intestinal homeostasis, and goblet cells are essential for maintaining the mucosal barrier integrity. The proviral integration site for Moloney murine leukemia virus-1 (PIM1) kinase regulates multiple cellular functions, but its role in intestinal homeostasis during colitis is unknown. Here, we demonstrate that PIM1 is prominently elevated in the colonic epithelia of both ulcerative colitis patients and murine models, in the presence of intestinal microbiota. Epithelial PIM1 leads to decreased goblet cells, thus impairing resistance to colitis and colitis-associated colorectal cancer (CAC) in mice. Mechanistically, PIM1 modulates goblet cell differentiation through the Wnt and Notch signaling pathways. Interestingly, PIM1 interacts with histone deacetylase 2 (HDAC2) and downregulates its level via phosphorylation, thereby altering the epigenetic profiles of Wnt signaling pathway genes. Collectively, these findings investigate the unknown function of the PIM1-HDAC2 axis in goblet cell differentiation and ulcerative colitis/CAC pathogenesis, which points to the potential for PIM1-targeted therapies of ulcerative colitis and CAC.

Xeno Nucleic Acids as Functional Materials: From Biophysical Properties to Application.

Xeno nucleic acid (XNA) are artificial nucleic acids, in which the chemical composition of the sugar moiety is changed. These modifications impart distinct physical and chemical properties to XNAs, leading to changes in their biological, chemical, and physical stability. Additionally, these alterations influence the binding dynamics of XNAs to their target molecules. Consequently, XNAs find expanded applications as functional materials in diverse fields. This review provides a comprehensive summary of the distinctive biophysical properties exhibited by various modified XNAs and explores their applications as innovative functional materials in expanded fields.

Glutathione-Coated Gold Nanoparticles Enabling Bifunctional Therapy at the Buried Interface for Efficient and UV-Resistant Perovskite Solar Cells.

Very recently, the poor contact between the perovskite and carrier selective layer has been regarded as a critical issue for improving the performance and stability of perovskite solar cells (PSCs). In this study, the buried interface of regularly structured PSCs has been targeted. Glutathione-coated gold nanoparticles (GSH-AuNPs) are used as double-sided passivating agents to improve the quality of the perovskite films. It has been demonstrated that the GSH-AuNPs interact strongly with the SnO2 underlayer and the upper perovskite layer, significantly reducing the defect densities of this interface. Thus, the power conversion efficiency (PCE) of the PSCs can be increased from 20.46% (control, 19.38%, IPCE corrected) to 22.22% (GSH-AuNPs modified, 21.10%, IPCE corrected) with notable enhancement in Voc and FF. Moreover, the strong interaction between the C═O groups of GSH-AuNPs and the undercoordinated Pb2+ species of the perovskite films inhibits the formation of metallic Pb0. As a result, the unencapsulated GSH-AuNPs-modified devices retained 80% of their initial PCEs after 1000 h at ambient conditions, with a relative humidity (RH) of 60 ± 5%. UV-resistant PSCs have also been demonstrated after introducing GSH-AuNPs. Therefore, our findings demonstrate the bidirectional therapy strategy as a feasible approach for achieving efficient and UV-resistant PSCs.

Electronic Structure Modification of MnO2 Nanosheet Arrays with Enhanced Water Oxidation Activity and Stability by Nitrogen Plasma.

The strategic design of catalysts for the oxygen evolution reaction (OER) is crucial in tackling the substantial energy demands associated with hydrogen production in electrolytic water splitting. Despite extensive research on birnessite (δ-MnO2) manganese oxides to enhance catalytic activity by modulating Mn3+ species, the ongoing challenge is to simultaneously stabilize Mn3+ while improving overall activity. Herein, oxygen (O) vacancies and nitrogen (N) doping have been simultaneously introduced into the MnO2 through a simple nitrogen plasma approach, resulting in efficient OER performance. The optimized N-MnO2v electrocatalyst exhibits outstanding OER activity in alkaline electrolyte, reducing the overpotential by nearly 160 mV compared to pure pristine MnO2 (from 476 to 312 mV) at 10 mA cm-2, and a small Tafel slope of 89 mV dec-1. Moreover, it demonstrates excellent durability over a 122 h stability test. The introduction of O vacancies and incorporation of N not only fine-tune the electronic structure of MnO2, increasing the Mn3+ content to enhance overall activity, but also play a crucial role in stabilizing Mn3+, thereby leading to exceptional stability over time. Subsequently, density functional theory calculations validate the optimized electronic structure of MnO2 achieved through the two engineering methods, effectively lowering the intermediate adsorption free energy barrier. Our synergistic approach, utilizing nitrogen plasma treatment, opens a pathway to concurrently enhance the activity and stability of OER electrocatalysts, applicable not only to Mn-based but also to other transition metal oxides.

Timing determines zooplankton community responses to multiple stressors.

Human activities and climate change cause abiotic factors to fluctuate through time, sometimes passing thresholds for organismal reproduction and survival. Multiple stressors can independently or interactively impact organisms; however, few studies have examined how they interact when they overlap spatially but occur asynchronously. Fluctuations in salinity have been found in freshwater habitats worldwide. Meanwhile, heatwaves have become more frequent and extreme. High salinity pulses and heatwaves are often decoupled in time but can still collectively impact freshwater zooplankton. The time intervals between them, during which population growth and community recovery could happen, can influence combined effects, but no one has examined these effects. We conducted a mesocosm experiment to examine how different recovery times (0-, 3-, 6-week) between salt treatment and heatwave exposure influence their combined effects. We hypothesized that antagonistic effects would appear when having short recovery time, because previous study found that similar species were affected by the two stressors, but effects would become additive with longer recovery time since fully recovered communities would respond to heatwave similar to undisturbed communities. Our findings showed that, when combined, the two-stressor joint impacts changed from antagonistic to additive with increased recovery time between stressors. Surprisingly, full compositional recovery was not achieved despite a recovery period that was long enough for population growth, suggesting legacy effects from earlier treatment. The recovery was mainly driven by small organisms, such as rotifers and small cladocerans. As a result, communities recovering from previous salt exposure responded differently to heatwaves than undisturbed communities, leading to similar zooplankton communities regardless of the recovery time between stressors. Our research bolsters the understanding and management of multiple-stressor issues by revealing that prior exposure to one stressor has long-lasting impacts on community recovery that can lead to unexpected joint effects of multiple stressors.

Bending skyrmion strings under two-dimensional thermal gradients.

Magnetic skyrmions are topologically protected magnetization vortices that form three-dimensional strings in chiral magnets. With the manipulation of skyrmions being key to their application in devices, the focus has been on their dynamics within the vortex plane, while the dynamical control of skyrmion strings remained uncharted territory. Here, we report the effective bending of three-dimensional skyrmion strings in the chiral magnet MnSi in orthogonal thermal gradients using small angle neutron scattering. This dynamical behavior is achieved by exploiting the temperature-dependent skyrmion Hall effect, which is unexpected in the framework of skyrmion dynamics. We thus provide experimental evidence for the existence of magnon friction, which was recently proposed to be a key ingredient for capturing skyrmion dynamics, requiring a modification of Thiele's equation. Our work therefore suggests the existence of an extra degree of freedom for the manipulation of three-dimensional skyrmions.

Metabolic transformation of cyclopiazonic acid in liver microsomes from different species based on UPLC-Q/TOF-MS.

To investigate the metabolic transformation of cyclopiazonic acid (CPA) in the liver of different species and to supplement accurate risk assessment information, the metabolism of CPA in liver microsomes from four animals and humans was studied using the ultra-high-performance liquid chromatography-quadrupole/time-of-flight method. The results showed that a total of four metabolites were obtained, and dehydrogenation, hydroxylation, methylation, and glucuronidation were identified as the main metabolic pathways of CPA. Rat liver microsomes exhibited the highest metabolic capacity for CPA, with dehydrogenated (C20H18N2O3) and glucuronic acid-conjugated (C26H28N2O10) metabolites identified in all liver microsomes except chicken, indicating significant species metabolic differences. Moreover, C20H18N2O3 was only detected in the incubation system with cytochromes P450 3A4 (CYP3A4). The hydroxylated (C20H20N2O4) and methylated (C21H22N2O3) metabolites were detected in all incubation systems except for the CYP2C9, with CYP3A4 demonstrating the strongest metabolic capacity. The "cocktail" probe drug method showed that CPA exhibited a moderate inhibitory effect on the CYP3A4 (IC50 value = 8.658 µM), indicating that the substrate had a negative effect on enzyme activity. Our results provide new insights to understand the biotransformation profile of CPA in animals and humans.

Manipulating the tumour immune microenvironment by N6-methyladenosine RNA modification.

N6-methyladenosine (m6A), a posttranscriptional regulatory mechanism, is the most common epigenetic modification in mammalian mRNA. M6A modifications play a crucial role in the developmental network of immune cells. The expression of m6A-related regulators often affects carcinogenesis and tumour suppression networks. In the tumour microenvironment, m6A-modified enzymes can affect the occurrence and progression of tumours by regulating the activation and invasion of tumour-associated immune cells. Immunotherapy, which utilises immune cells, has been demonstrated to be a powerful weapon in tumour treatment and is increasingly being used in the clinic. Here, we provide an updated and comprehensive overview of how m6A modifications affect invasive immune cells and their potential role in immune regulation. In addition, we summarise the regulation of epigenetic regulators associated with m6A modifications in tumour cells on the antitumour response of immune cells in the tumour immune microenvironment. These findings provide new insights into the role of m6A modifications in the immune response and tumour development, leading to the development of novel immunotherapies for cancer treatment.

Suspected duloxetine-induced restless legs syndrome phenotypic variant: a case report.

BACKGROUND: Restless arms syndrome (RAS) is the most common variant of restless legs syndrome (RLS), which is easy to be ignored in clinical practice due to the lack of specific diagnostic criteria. When effective therapeutic agents induced RAS and symptoms persisted after briefly observation, clinicians will face the challenge of weighing efficacy against side effects. CASE PRESENTATION: A 67-year-old woman was admitted to a geriatric psychiatric ward with depression. Upon admission, the escitalopram dose was reduced from 15 mg to 10 mg per day, and the duloxetine dose was increased from 60 mg to 80 mg per day. The next night before bedtime, she developed itching and creeping sensations deep inside bilateral shoulders and arms, with the urge to move, worsening at rest, and alleviation after hammering. The symptoms persisted when escitalopram was discontinued. A history of RLS was confirmed. Treatment with 40 mg of duloxetine and 0.125 mg of pramipexole significantly improved depression, and the paresthesia disappeared, with no recurrence occurring 6 months after discharge. DISCUSSION AND CONCLUSIONS: This case suggests that psychiatrists should pay attention to RLS variants when increasing doses of duloxetine. Long-term improvement can be achieved through dosage reduction combined with dopaminergic drugs instead of immediate discontinuation.

Identification and classification of the genomes of novel microviruses in poultry slaughterhouse.

Microviridae is a family of phages with circular ssDNA genomes and they are widely found in various environments and organisms. In this study, virome techniques were employed to explore potential members of Microviridae in a poultry slaughterhouse, leading to the identification of 98 novel and complete microvirus genomes. Using a similarity clustering network classification approach, these viruses were found to belong to at least 6 new subfamilies within Microviridae and 3 higher-level taxonomic units. Genome size, GC content and genome structure of these new taxa showed evident regularities, validating the rationality of our classification method. Our method can divide microviruses into about 45 additional detailed clusters, which may serve as a new standard for classifying Microviridae members. Furthermore, by addressing the scarcity of host information for microviruses, the current study significantly broadened their host range and discovered over 20 possible new hosts, including important pathogenic bacteria such as Helicobacter pylori and Vibrio cholerae, as well as different taxa demonstrated different host specificities. The findings of this study effectively expand the diversity of the Microviridae family, providing new insights for their classification and identification. Additionally, it offers a novel perspective for monitoring and controlling pathogenic microorganisms in poultry slaughterhouse environments.

Efficacy of a single low dose of esketamine after childbirth for mothers with symptoms of prenatal depression: randomised clinical trial.

OBJECTIVE: To determine whether a single low dose of esketamine administered after childbirth reduces postpartum depression in mothers with prenatal depression. DESIGN: Randomised, double blind, placebo controlled trial with two parallel arms. SETTING: Five tertiary care hospitals in China, 19 June 2020 to 3 August 2022. PARTICIPANTS: 364 mothers aged ≥18 years who had at least mild prenatal depression as indicated by Edinburgh postnatal depression scale scores of ≥10 (range 0-30, with higher scores indicating worse depression) and who were admitted to hospital for delivery. INTERVENTIONS: Participants were randomly assigned 1:1 to receive either 0.2 mg/kg esketamine or placebo infused intravenously over 40 minutes after childbirth once the umbilical cord had been clamped. MAIN OUTCOME MEASURES: The primary outcome was prevalence of a major depressive episode at 42 days post partum, diagnosed using the mini-international neuropsychiatric interview. Secondary outcomes included the Edinburgh postnatal depression scale score at seven and 42 days post partum and the 17 item Hamilton depression rating scale score at 42 days post partum (range 0-52, with higher scores indicating worse depression). Adverse events were monitored until 24 hours after childbirth. RESULTS: A total of 364 mothers (mean age 31.8 (standard deviation 4.1) years) were enrolled and randomised. At 42 days post partum, a major depressive episode was observed in 6.7% (12/180) of participants in the esketamine group compared with 25.4% (46/181) in the placebo group (relative risk 0.26, 95% confidence interval (CI) 0.14 to 0.48; P<0.001). Edinburgh postnatal depression scale scores were lower in the esketamine group at seven days (median difference -3, 95% CI -4 to -2; P<0.001) and 42 days (-3, -4 to -2; P<0.001). Hamilton depression rating scale scores at 42 days post partum were also lower in the esketamine group (-4, -6 to -3; P<0.001). The overall incidence of neuropsychiatric adverse events was higher in the esketamine group (45.1% (82/182) v 22.0% (40/182); P<0.001); however, symptoms lasted less than a day and none required drug treatment. CONCLUSIONS: For mothers with prenatal depression, a single low dose of esketamine after childbirth decreases major depressive episodes at 42 days post partum by about three quarters. Neuropsychiatric symptoms were more frequent but transient and did not require drug intervention. TRIAL REGISTRATION: ClinicalTrials.gov NCT04414943.

Establishment and validation of an artificial intelligence web application for predicting postoperative in-hospital mortality in patients with hip fracture: a national cohort study of 52 707 cases.

BACKGROUND: In-hospital mortality following hip fractures is a significant concern, and accurate prediction of this outcome is crucial for appropriate clinical management. Nonetheless, there is a lack of effective prediction tools in clinical practice. By utilizing artificial intelligence (AI) and machine learning techniques, this study aims to develop a predictive model that can assist clinicians in identifying geriatric hip fracture patients at a higher risk of in-hospital mortality. METHODS: A total of 52 707 geriatric hip fracture patients treated with surgery from 90 hospitals were included in this study. The primary outcome was postoperative in-hospital mortality. The patients were randomly divided into two groups, with a ratio of 7:3. The majority of patients, assigned to the training cohort, were used to develop the AI models. The remaining patients, assigned to the validation cohort, were used to validate the models. Various machine learning algorithms, including logistic regression (LR), decision tree (DT), naïve bayesian (NB), neural network (NN), eXGBoosting machine (eXGBM), and random forest (RF), were employed for model development. A comprehensive scoring system, incorporating 10 evaluation metrics, was developed to assess the prediction performance, with higher scores indicating superior predictive capability. Based on the best machine learning-based model, an AI application was developed on the Internet. In addition, a comparative testing of prediction performance between doctors and the AI application. FINDINGS: The eXGBM model exhibited the best prediction performance, with an area under the curve (AUC) of 0.908 (95% CI: 0.881-0.932), as well as the highest accuracy (0.820), precision (0.817), specificity (0.814), and F1 score (0.822), and the lowest Brier score (0.120) and log loss (0.374). Additionally, the model showed favorable calibration, with a slope of 0.999 and an intercept of 0.028. According to the scoring system incorporating 10 evaluation metrics, the eXGBM model achieved the highest score (56), followed by the RF model (48) and NN model (41). The LR, DT, and NB models had total scores of 27, 30, and 13, respectively. The AI application has been deployed online at https://in-hospitaldeathinhipfracture-l9vhqo3l55fy8dkdvuskvu.streamlit.app/ , based on the eXGBM model. The comparative testing revealed that the AI application's predictive capabilities significantly outperformed those of the doctors in terms of AUC values (0.908 vs. 0.682, P <0.001). CONCLUSIONS: The eXGBM model demonstrates promising predictive performance in assessing the risk of postoperative in-hospital mortality among geriatric hip fracture patients. The developed AI model serves as a valuable tool to enhance clinical decision-making.

Targeted Drug Nanodelivery and Immunotherapy for Combating Tumor Resistance.

Chemotherapy resistance is a common cause of tumor treatment failure. Various molecular responses, such as increased expression of efflux transporter proteins, including Pglycoprotein (P-gp), changes in the tumor microenvironment (TME), the role of platelets, and the effects of cancer stem cells (CSCs), can lead to drug resistance. Through extensive research on the mechanisms of drug resistance, more effective anti-resistance drugs and therapeutic approaches are being developed. This review explores drug resistance mechanisms and summarizes relevant anti-resistance drugs. In addition, due to the therapeutic limitations of the aforementioned treatments, new advances in nanocarrier-based combination immunotherapy to address the challenge of drug resistance have been described. Nanocarriers combined with immunotherapy can not only target tumor sites for targeted drug release but also modulate the autoimmune system and enhance immune efficacy, thereby overcoming tumor drug resistance. This review suggests new strategies for overcoming tumor drug resistance and is expected to inform tumor treatment and prognosis.

Cryogenic Electron-Beam Writing for Perovskite Metasurface.

Halide perovskites (HPs) metasurfaces have recently attracted significant interest due to their potential to not only further enhance device performance but also reveal the unprecedented functionalities and novel photophysical properties of HPs. However, nanopatterning on HPs is critically challenging as they are readily destructed by the organic solvents in the standard lithographic processes. Here, we present a novel, subtle, and fully nondestructive HPs metasurface fabrication strategy based on cryogenic electron-beam writing. This technique allows for high-precision patterning and in situ imaging of HPs with excellent compatibility. As a proof-of-concept, broadband absorption enhanced metasurfaces were realized by patterning nanopillar arrays on CH3NH3PbI3 film, which results in photodetectors with approximately 14-times improvement on responsivity and excellent stability. Our findings highlight the great feasibility of cryogenic electron-beam writing for producing perovskite metasurface and unlocking the unprecedented photoelectronic properties of HPs.