Self-Assembled Nanoparticles from Xie-Bai-San Decoction: Isolation, Characterization and Enhancing Oral Bioavailability.

Background: Natural nanoparticles have been found to exist in traditional Chinese medicine (TCM) decoctions. However, whether natural nanoparticles can influence the oral bioavailability of active compounds has not been elucidated. Using Xie-Bai-San decoction (XBSD) as an example, the purpose of this study was to isolate, characterize and elucidate the mechanism of the nanoparticles (N-XBSD) in XBSD, and further to explore whether the bioavailability of the main active compounds could be enhanced by N-XBSD. Methods: N-XBSD were isolated from XBSD, and investigated its characterization and study of its formation mechanism, and evaluation of its ability to enhance bioavailability of active compounds. Results: The N-XBSD was successfully isolated with the average particle size of 104.53 nm, PDI of 0.27 and zeta potential of -5.14 mV. Meanwhile, all the eight active compounds were most presented in N-XBSD. Kukoamine B could self-assemble with mulberroside A or liquiritin to form nanoparticles, respectively. And the FT-IR and HRMS results indicated the possible binding of the ammonium group of kukoamine B with the phenolic hydroxyl group of mulberroside A or liquiritin, respectively. The established UPLC-MS/MS method was accurate and reliable and met the quantitative requirements. The pharmacokinetic behaviors of the N-XBSD and decoction were similar in rats. Most notably, compared to that of free drugs, the Cmax, AUC0-∞, AUC0-t, T1/2 and MRT0-∞ values of index compounds were the higher in N-XBSD, with a slower plasma clearance rate in rats. Conclusion: The major active compounds of XBSD were mainly distributed in N-XBSD, and N-XBSD was formed through self-assembly among active compounds. N-XBSD could obviously promote the bioavailability of active compounds, indicating natural nanoparticles of decoctions play an important role in therapeutic effects.

Transapical intramyocardial septal microwave ablation in treatment of hypertrophic obstructive cardiomyopathy: 12-month outcomes of a swine model.

BACKGROUND: To date, the extended Morrow procedure is considered the gold standard treatment for patients with obstructive hypertrophic cardiomyopathy who experience severe symptoms and are unresponsive to medication treatment. We therefore aimed to perform transapical intramyocardial septal microwave ablation to reduce the thickness of the interventricular septum myocardium in a minimally invasive method. METHODS: Fourteen swine were divided to form either a microwave ablation group (n = 7) or a sham group (n = 7). In the microwave ablation group, a transapical microwave antenna was inserted into the septum to ablate each myocardial segment at 40 W for 1 min, while in the sham group, the same operation was performed but without power output. We used echocardiography, electrocardiogram, during the operation. And added computerized tomography, cardiac nuclear magnetic resonance during follow-up. RESULTS: Segment hypokinesis was observed in all swine immediately following ablation. Compared with the sham group, the thickness of ablated segments in the ablation group decreased significantly 1 month post-operation (ablation group, 5.53 ± 1.00 mm vs. 8.03 ± 1.15 mm, respectively, P < 0.01; sham group, 8.40 ± 0.94 mm vs. 8.21 ± 1.09 mm, respectively, P = 0.081), and the outcome was still observed 1 year post-operation (ablation group, 3.36 ± 0.85 mm vs. 8.03 ± 1.15 mm, respectively, P < 0.01). No perforation of the septum was observed during the procedure or follow-up, and no heart failure or sudden cardiac death occurred during postoperative feeding. CONCLUSIONS: Transapical intramyocardial septal microwave ablation can effectively and safely produce a large region of necrosis. This technique can potentially mimic surgical myectomy while avoiding cardiopulmonary bypass and median sternotomy in high-risk hypertrophic obstructive cardiomyopathy patients.

Penicillium oxalicum induced phosphate precipitation enhanced cadmium (Cd) immobilization by simultaneously accelerating Cd biosorption and biomineralization.

Soil cadmium (Cd) is immobilized by the progressing biomineralization process as microbial induced phosphate precipitation (MIPP), which is regulated by phosphate (P) solubilizing microorganisms and P sources. However, little attention has been paid to the implications of Cd biosorption during MIPP. In this study, the newly isolated Penicillium oxalicum could immobilize 5.4-12.6 % of Cd2+, while the presence of hydroxyapatite (HAP) considerably enhanced Cd2+ immobilization in P. oxalicum and reached over 99 % Cd2+ immobilization efficiency within 7 days. Compared to P. oxalicum mono inoculation, MIPP dramatically boosted Cd biosorption and biomineralization efficiency by 71 % and 16 % after 96 h cultivation, respectively. P. oxalicum preferred to absorbing Cd2+ and reaching maximum Cd2+ biosorption efficiency of 87.8 % in the presence of HAP. More surface groups in P. oxalicum and HAP mineral involved adsorption which resulted in the formation of Cd-apatite [Ca8Cd2(PO4)6(OH)2] via ion exchange. Intracellular S2-, secreted organic acids and soluble P via HAP solubilization complexed with Cd2+, progressively mineralized into Cd5(PO4)3OH, Cd(H2PO4)2, C4H6CdO4 and CdS. These results suggested that Cd2+ immobilization was enhanced simultaneously by the accelerated biosorption and biomineralization during P. oxalicum induced P precipitation. Our findings revealed new mechanisms of Cd immobilization in MIPP process and offered clues for remediation practices at metal contaminated sites.

[Effects of Land Use Patterns on Soil Microplastic Pollution in the Luoshijiang Sub-watershed of Erhai Lake Basin].

Microplastic pollution in the soil environment has received extensive attention, but the effects of different land use patterns on the sub-watershed scale on soil microplastic pollution are poorly understood. The Luoshijiang sub-watershed in the north of Erhai Lake was selected as the research object, and the characteristics of microplastic pollution in farmland, riparian zone, grassland, and woodland soils were analyzed. The pollution risks of microplastics in the four types of soil were assessed using the polymer risk index method, and the effects of land use patterns on the distribution and risk of microplastic pollution were further explored. The results showed that:① The abundance of microplastics in the soil of the Luoshijiang sub-watershed ranged from 220 to 1 900 n·kg-1, and the average abundance was (711 ± 55) n·kg-1. The main polymer types were polyester (PES, 32.52%) and polyethylene terephthalate (PET, 21.95%). The particle size of microplastics was concentrated in the range of 0.5-2 mm (61.89%). Fiber was the main shape of microplastics (>75%), and the dominant color was transparent (58.50%). ② Land use patterns determined the abundance and pollution characteristics of soil microplastics in the Luoshijiang sub-watershed. A significantly higher abundance of microplastics was found in the soil of farmland[(885 ± 95) n·kg-1] and riparian zone[(837 ± 155) n·kg-1], which had stronger intensities of human activity, than that in woodland soil[(491 ± 53) n·kg-1] (P<0.05). Film and fragment microplastics mainly occurred in farmland soil, which also had the largest number of polymer types and the most abundant colors. ③ The risk index level of microplastics (Level Ⅲ) in the soil of farmland was higher than that of the other three land use patterns (Level Ⅰ). This research indicated that the higher the intensity of human activities of a sub-watershed was, the more complex the occurrence characteristics of soil microplastics, the richer the types of polymers, and the higher the potential pollution risks would be. Therefore, it is necessary to strengthen the control of soil microplastic pollution in farmland.

A derivative of trihydroxynaphthalenone and a pyrone metabolite from the endophytic fungus Talaromyces purpurpgenus.

A newly discovered trihydroxynaphthalenone derivative, epoxynaphthalenone (1) involving the condensation of ortho-hydroxyl groups into an epoxy structure, and a novel pyrone metabolite characterized as pyroneaceacid (2), were extracted from Talaromyces purpurpgenus, an endophytic fungus residing in Rhododendron molle. The structures of these compounds were elucidated through a comprehensive analysis of their NMR and HRESIMS data. The determination of absolute configurations was accomplished using electronic circular dichroism (ECD) calculations and CD spectra. Notably, these recently identified metabolites exhibited a moderate inhibitory activity against xanthine oxidase (XOD).

Erratum: In Vivo Calcium Imaging of Dorsal Root Ganglia Neurons' Response to Somatic and Visceral Stimuli.

This corrects the article 10.3791/65975.

Clinicopathological characteristics and prognosis in patients with monoclonal gammopathy and renal damage in central China: a multicenter retrospective cohort study.

Renal involvement is common in monoclonal gammopathy (MG); however, the same patient may have both MG and non-paraprotein-associated renal damage. Accordingly, distinguishing the cause of renal damage is necessary because of the different clinical characteristics and associated treatments. In this multicenter retrospective cohort study, we described the clinicopathological characteristics and prognosis of 703 patients with MG and renal damage in central China. Patients were classified as having MG of renal significance (MGRS), MG of undetermined significance (MGUS), or hematological malignancy. 260 (36.98%), 259 (36.84%), and 184 (26.17%) had MGRS, MGUS, and hematological malignancies, respectively. Amyloidosis was the leading pattern of MGRS (74.23%), followed by thrombotic microangiopathy (8.85%) and monoclonal immunoglobulin deposition disease (8.46%). Membranous nephropathy was the leading diagnosis of MGUS (39.38%). Renal pathological findings of patients with hematological malignancies included paraprotein-associated lesions (84.78%) and non-paraprotein-associated lesions (15.22%). The presence of nephrotic syndrome and an abnormal free light chain (FLC) ratio were independently associated with MGRS. The overall survival was better in patients with MGUS than in those with MGRS or hematological malignancies.

Efficient and Robust Point Cloud Registration via Heuristics-guided Parameter Search.

Estimating the rigid transformation with 6 degrees of freedom based on a putative 3D correspondence set is a crucial procedure in point cloud registration. Existing correspondence identification methods usually lead to large outlier ratios (> 95% is common), underscoring the significance of robust registration methods. Many researchers turn to parameter search-based strategies (e.g., Branch-and-Bround) for robust registration. Although related methods show high robustness, their efficiency is limited to the high-dimensional search space. This paper proposes a heuristics-guided parameter search strategy to accelerate the search while maintaining high robustness. We first sample some correspondences (i.e., heuristics) and then just need to sequentially search the feasible regions that make each sample an inlier. Our strategy largely reduces the search space and can guarantee accuracy with only a few inlier samples, therefore enjoying an excellent trade-off between efficiency and robustness. Since directly parameterizing the 6-dimensional nonlinear feasible region for efficient search is intractable, we construct a three-stage decomposition pipeline to reparameterize the feasible region, resulting in three lower-dimensional sub-problems that are easily solvable via our strategy. Besides reducing the searching dimension, our decomposition enables the leverage of 1-dimensional interval stabbing at all three stages for searching acceleration. Moreover, we propose a valid sampling strategy to guarantee our sampling effectiveness, and a compatibility verification setup to further accelerate our search. Extensive experiments on both simulated and real-world datasets demonstrate that our approach exhibits comparable robustness with state-of-the-art methods while achieving a significant efficiency boost.

IFNα-induced BST2+ tumor-associated macrophages facilitate immunosuppression and tumor growth in pancreatic cancer by ERK-CXCL7 signaling.

Pancreatic ductal adenocarcinoma (PDAC) features an immunosuppressive tumor microenvironment (TME) that resists immunotherapy. Tumor-associated macrophages, abundant in the TME, modulate T cell responses. Bone marrow stromal antigen 2-positive (BST2+) macrophages increase in KrasG12D/+; Trp53R172H/+; Pdx1-Cre mouse models during PDAC progression. However, their role in PDAC remains elusive. Our findings reveal a negative correlation between BST2+ macrophage levels and PDAC patient prognosis. Moreover, an increased ratio of exhausted CD8+ T cells is observed in tumors with up-regulated BST2+ macrophages. Mechanistically, BST2+ macrophages secrete CXCL7 through the ERK pathway and bind with CXCR2 to activate the AKT/mTOR pathway, promoting CD8+ T cell exhaustion. The combined blockade of CXCL7 and programmed death-ligand 1 successfully decelerates tumor growth. Additionally, cGAS-STING pathway activation in macrophages induces interferon (IFN)α synthesis leading to BST2 overexpression in the PDAC TME. This study provides insights into IFNα-induced BST2+ macrophages driving an immune-suppressive TME through ERK-CXCL7 signaling to regulate CD8+ T cell exhaustion in PDAC.

A novel nomogram to predict futile recanalization in patients with acute ischemic stroke undergoing mechanical thrombectomy.

Background and objective: Futile recanalization (FR) is defined as patients with acute ischemic stroke (AIS) due to large vessel occlusion who still exhibits functional dependence although undergoing successful mechanical thrombectomy (MT). We aimed to develop and validate a simple nomogram for predicting the probability of FR after MT treatment in AIS patients. Methods: Clinical data of AIS patients in the Jrecan clinical trial in China from March 2018 to June 2019 were collected as the derivation set (n = 162). Meanwhile, clinical data of AIS patients who underwent MT in Baotou Central Hospital and Ningbo No.2 Hospital from 2019 to 2021 were collected as the validation set (n = 170). Multivariate logistic regression analysis was performed for all variables that had p < 0.2 in the univariate analysis in the derivation set. The independent risk factors of FR were further screened out and a nomogram was constructed. The performance of the nomogram was analyzed in the derivation and validation set using C-index, calibration plots, and decision curves. Results: No significant difference in FR rate was detected between the derivation set and the validation set [88/162 (54.32%) and 82/170 (48.23%), p = 0.267]. Multivariate logistic regression analysis showed that age ≥ 65 years old (OR = 2.096, 95%CI 1.024-4.289, p = 0.043), systolic blood pressure (SBP) ≥ 180 mmHg (OR = 5.624, 95%CI 1.141-27.717, p = 0.034), onset to recanalization time (OTR) ≥ 453 min (OR = 2.759, 95%CI 1.323-5.754, p = 0.007), 24 h intracerebral hemorrhage (ICH; OR = 4.029, 95%CI 1.844 ~ 8.803, p < 0.001) were independent risk factors for FR. The C-index of the nomogram of the derivation set and the verification set were 0.739 (95%CI 0.662~0.816) and 0.703 (95%CI 0.621~0.785), respectively. Conclusion: The nomogram composed of age, SBP, OTR, and 24 h ICH can effectively predict the probability of FR after MT in AIS patients.

Using generative AI to investigate medical imagery models and datasets.

BACKGROUND: AI models have shown promise in performing many medical imaging tasks. However, our ability to explain what signals these models have learned is severely lacking. Explanations are needed in order to increase the trust of doctors in AI-based models, especially in domains where AI prediction capabilities surpass those of humans. Moreover, such explanations could enable novel scientific discovery by uncovering signals in the data that aren't yet known to experts. METHODS: In this paper, we present a workflow for generating hypotheses to understand which visual signals in images are correlated with a classification model's predictions for a given task. This approach leverages an automatic visual explanation algorithm followed by interdisciplinary expert review. We propose the following 4 steps: (i) Train a classifier to perform a given task to assess whether the imagery indeed contains signals relevant to the task; (ii) Train a StyleGAN-based image generator with an architecture that enables guidance by the classifier ("StylEx"); (iii) Automatically detect, extract, and visualize the top visual attributes that the classifier is sensitive towards. For visualization, we independently modify each of these attributes to generate counterfactual visualizations for a set of images (i.e., what the image would look like with the attribute increased or decreased); (iv) Formulate hypotheses for the underlying mechanisms, to stimulate future research. Specifically, present the discovered attributes and corresponding counterfactual visualizations to an interdisciplinary panel of experts so that hypotheses can account for social and structural determinants of health (e.g., whether the attributes correspond to known patho-physiological or socio-cultural phenomena, or could be novel discoveries). FINDINGS: To demonstrate the broad applicability of our approach, we present results on eight prediction tasks across three medical imaging modalities-retinal fundus photographs, external eye photographs, and chest radiographs. We showcase examples where many of the automatically-learned attributes clearly capture clinically known features (e.g., types of cataract, enlarged heart), and demonstrate automatically-learned confounders that arise from factors beyond physiological mechanisms (e.g., chest X-ray underexposure is correlated with the classifier predicting abnormality, and eye makeup is correlated with the classifier predicting low hemoglobin levels). We further show that our method reveals a number of physiologically plausible, previously-unknown attributes based on the literature (e.g., differences in the fundus associated with self-reported sex, which were previously unknown). INTERPRETATION: Our approach enables hypotheses generation via attribute visualizations and has the potential to enable researchers to better understand, improve their assessment, and extract new knowledge from AI-based models, as well as debug and design better datasets. Though not designed to infer causality, importantly, we highlight that attributes generated by our framework can capture phenomena beyond physiology or pathophysiology, reflecting the real world nature of healthcare delivery and socio-cultural factors, and hence interdisciplinary perspectives are critical in these investigations. Finally, we will release code to help researchers train their own StylEx models and analyze their predictive tasks of interest, and use the methodology presented in this paper for responsible interpretation of the revealed attributes. FUNDING: Google.

Observation of parity-time symmetry in diffusive systems.

Phase modulation has scarcely been mentioned in diffusive physical systems because the diffusion process does not carry the momentum like waves. Recently, non-Hermitian physics provides a unique perspective for understanding diffusion and shows prospects in thermal phase regulation, exemplified by the discovery of anti-parity-time (APT) symmetry in diffusive systems. However, precise control of thermal phase remains elusive hitherto and can hardly be realized, due to the phase oscillations. Here we construct the PT-symmetric diffusive systems to achieve the complete suppression of thermal phase oscillation. The real coupling of diffusive fields is readily established through a strong convective background, and the decay-rate detuning is enabled by thermal metamaterial design. We observe the phase transition of PT symmetry breaking with the symmetry-determined amplitude and phase regulation of coupled temperature fields. Our work shows the existence of PT symmetry in dissipative energy exchanges and provides unique approaches for harnessing the mass transfer of particles, wave dynamics in strongly scattering systems, and thermal conduction.

Structural properties and adsorption performance relationship towards three categories of lignin and their derived biochar.

The growing interest in utilizing lignin for dye removal has gained momentum, but there is limited information on the intricate relationship between lignin structural characteristics and adsorption efficacy, especially for its biochar derivatives. This study focused on three types of lignin and their corresponding biochar derivatives. Among them, ZnCl2-activated acidic/alkali densified lignin preparation of lignin-derived active carbon exhibited superior adsorption performance, achieving 526.32 mg/g for methylene blue and 2156.77 mg/g for congo red. Its exceptional adsorption capacity was attributed to its unique structural properties, including low alkyl and O-alkyl group content and high aromatic carbon levels. Furthermore, the adsorption mechanisms adhered to pseudo-second-order kinetics and the Langmuir model, signifying a spontaneous process. Intriguingly, lignin-derived active carbon also demonstrated remarkable recovery capabilities. These findings provide valuable insights into the impact of structural attributes on lignin and its biochar's adsorption performance.

Analysis of blood methylation quantitative trait loci in East Asians reveals ancestry-specific impacts on complex traits.

Methylation quantitative trait loci (mQTLs) are essential for understanding the role of DNA methylation changes in genetic predisposition, yet they have not been fully characterized in East Asians (EAs). Here we identified mQTLs in whole blood from 3,523 Chinese individuals and replicated them in additional 1,858 Chinese individuals from two cohorts. Over 9% of mQTLs displayed specificity to EAs, facilitating the fine-mapping of EA-specific genetic associations, as shown for variants associated with height. Trans-mQTL hotspots revealed biological pathways contributing to EA-specific genetic associations, including an ERG-mediated 233 trans-mCpG network, implicated in hematopoietic cell differentiation, which likely reflects binding efficiency modulation of the ERG protein complex. More than 90% of mQTLs were shared between different blood cell lineages, with a smaller fraction of lineage-specific mQTLs displaying preferential hypomethylation in the respective lineages. Our study provides new insights into the mQTL landscape across genetic ancestries and their downstream effects on cellular processes and diseases/traits.

Exploring transvaginal sonographic characteristics of the levator ani muscle in women with postpartum pelvic floor myofascial pain.

BACKGROUND: Pelvic floor myofascial pain is one of the pelvic floor dysfunction diseases disturbing women after delivery. There is a lack of objective standardization for the diagnosis of pelvic floor myofascial pain due to the various symptoms and the dependence on the palpating evaluation. Ultrasound imaging has the advantages of safety, simplicity, economy and high resolution, which makes it an ideal tool for the assistant diagnosis of pelvic floor myofascial pain and evaluation after treatment. METHODS: This is a retrospective case-control study including women accepting evaluation of pelvic floor function at 6 weeks to 1 year postpartum. They were divided into pelvic floor myofascial pain group and normal control group. A BCL 10-5 biplane transducer was applied to observed their puborectalis. The length, minimum width, area, deficiency, deficiency length, deficiency width, deficiency area, rate of deficiency area, local thickening,angle between the tendinous arch of levator ani muscle and puborectalis of corresponding puborectalis in different groups were observed and measured. RESULTS: A total of 220 postpartum women participated in the study, with 77 in the pelvic floor myofascial pain group and 143 in the normal control group. The Intraclass correlation coefficient value was over 0.750, and Kappa ranged from 0.600 to 0.800. puborectalis deficiency (adjusted odds ratio = 11.625, 95% confidence interval = 4.557-29.658) and focal thickening (adjusted odds ratio = 16.891, 95% confidence interval = 1.819-156.805) were significantly associated with higher odds of having postpartum pelvic floor myofascial pain. Grayscale or the angle between the arch tendineus levator ani and puborectalis measurements on the pain side tended to be smaller than on the non-pain side in patients with unilateral puborectalis or iliococcygeus pain (P < 0.05). CONCLUSIONS: This study demonstrated that transvaginal ultrasound was a potentially efficient technique for evaluating postpartum pelvic floor myofascial pain due to its ability to assess various sonographic characteristics of the levator ani muscles.

PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction.

MOTIVATION: Drug combination therapies have shown promise in clinical cancer treatments. However, it is hard to experimentally identify all drug combinations for synergistic interaction even with high-throughput screening due to the vast space of potential combinations. Although a number of computational methods for drug synergy prediction have proven successful in narrowing down this space, fusing drug pairs and cell line features effectively still lacks study, hindering current algorithms from understanding the complex interaction between drugs and cell lines. RESULTS: In this paper, we proposed a Permutable feature fusion network for Drug-Drug Synergy prediction, named PermuteDDS. PermuteDDS takes multiple representations of drugs and cell lines as input and employs a permutable fusion mechanism to combine drug and cell line features. In experiments, PermuteDDS exhibits state-of-the-art performance on two benchmark data sets. Additionally, the results on independent test set grouped by different tissues reveal that PermuteDDS has good generalization performance. We believed that PermuteDDS is an effective and valuable tool for identifying synergistic drug combinations. It is publicly available at https://github.com/littlewei-lazy/PermuteDDS . SCIENTIFIC CONTRIBUTION: First, this paper proposes a permutable feature fusion network for predicting drug synergy termed PermuteDDS, which extract diverse information from multiple drug representations and cell line representations. Second, the permutable fusion mechanism combine the drug and cell line features by integrating information of different channels, enabling the utilization of complex relationships between drugs and cell lines. Third, comparative and ablation experiments provide evidence of the efficacy of PermuteDDS in predicting drug-drug synergy.

Combined collection systems of sewage and rainfall runoff seriously affect the spatial distributions of natural estrogens and their conjugates in river water: Insights from the Pearl River of China.

So far, little has been known about how the combined collection systems of sewage and rainfall runoff (CCSs) affect emerging contaminants in river water. To fill up the knowledge gap, this study was conducted to investigate the spatial distributions of three natural estrogens (NEs, i.e., estrone (E1), 17ß-estradiol (E2) and estriol (E3)) and their conjugates (C-NEs) in the Pearl River in the wet and dry seasons. Results showed that the respective average concentrations of NEs and C-NEs at different locations alongside the Pearl River in the wet season were 7.3 and 1.8 times those in the dry season. Based on estrogen equivalence (EEQ), the average estimated EEQ level in the Pearl River waters in the wet season was nearly 10 times that in the dry season. These seemed to imply that the CCSs in the wet season not only cause untreated sewage into the receiving water body, but greatly decrease the removal efficiency of NEs and C-NEs in wastewater treatment plant. Furthermore, the estimated annual loads of E1, E2, and E3 to the Pearl River in the wet season accounted for about 88.6 %, 100 %, and 99.3 % of the total annual loads. Consequently, this work for the first time demonstrated that the CCSs in cities with high precipitation are unfavorable for controlling of emerging contaminants.

NIR-responsive copper nanoliposome composites for cascaded ferrotherapy via ferroptosis actived ICD and IFN-γ released.

Metallic biomaterials activate tumor ferroptosis by increasing oxidative stress, but their efficacy is severely limited in tumor microenvironment. Although interferon gamma (IFN-γ) can promote tumor ferroptosis sensitivity by inhibiting the antioxidant system and promoting lipid accumulation, this effect limited by the lack of IFN-γ accumulation in tumors. Herein, we report a near-infrared (NIR)-responsive HCuS nanocomposite (HCuS-PE@TSL-tlyp-1) that can stimulate immunogenic cell death (ICD)-mediated IFN-γ secretion through exogenous oxidative stress, thereby achieving cascaded ferrotherapy by mutually reinforcing ferroptosis and systemic immunity. Upon laser irradiation, the dissolution of the thermal coating, and the introduction of Cu ions and piperazine-erastin (PE) simultaneously induce oxidative stress by reactive oxygen species (ROS)/lipid peroxide (LPO) accumulation and deplete cystine-glutamate transporter (xCT)/GSH. The onset of oxidative stress-mediated ferroptosis is thus achieved, and ICD is triggered, significantly promoting cytotoxic T-cell (CTL) infiltration for IFN-γ secretion. Furthermore, IFN-γ induces immunogenic tumor ferroptosis by inhibiting xCT-antioxidant pathways and enhancing the ACSL4-fatty acid recruitment pathway, which further promotes sensitivity to ferroptosis in cells. These HCuS nanocomposites combined with aPD-L1 effectively in inhibiting tumor metastasis and recurrence. Importantly, these cascade ferrotherapy results broadens the application of HCuS biomaterials.

Machine Learning Molecular Dynamics Shows Anomalous Entropic Effect on Catalysis via Surface Pre-melting of Nanoclusters.

Due to the superior catalytic activity and efficient utilization of noble metals, nanocatalysts are extensively used in the modern industrial production of chemicals. The surface structures of these materials are significantly influenced by reactive adsorbates, leading to dynamic behavior under experimental conditions. The dynamic nature poses significant challenges in studying the  structure-activity relations of catalysts. Herein, we unveil an anomalous entropic effect on catalysis via surface pre-melting of nanoclusters through machine learning accelerated molecular dynamics and free energy calculation. We find that due to the pre-melting of shell atoms, there exists a non-linear variation in the catalytic activity of the nanoclusters with temperature. Consequently, two notable changes in catalyst activity occur at the respective temperatures of melting for the shell and core atoms. We further study the nanoclusters with surface point defects, i.e. vacancy and ad-atom, and observe significant decrease in the surface melting temperatures of the nanoclusters, enabling the reaction to take place under more favorable and milder conditions. These findings not only provide novel insights into dynamic catalysis of nanoclusters  but also offer new understanding of the role of point defects in catalytic processes.