MitoH3: Mitochondrial Haplogroup and Homoplasmic/Heteroplasmic Variant Calling Pipeline for Alzheimer's Disease Sequencing Project.

Background: Mitochondrial DNA (mtDNA) is a double-stranded circular DNA and has multiple copies in each cell. Excess heteroplasmy, the coexistence of distinct variants in copies of mtDNA within a cell, may lead to mitochondrial impairments. Accurate determination of heteroplasmy in whole-genome sequencing (WGS) data has posed a significant challenge because mitochondria carrying heteroplasmic variants cannot be distinguished during library preparation. Moreover, sequencing errors, contamination, and nuclear mtDNA segments can reduce the accuracy of heteroplasmic variant calling. Objective: To efficiently and accurately call mtDNA homoplasmic and heteroplasmic variants from the large-scale WGS data generated from the Alzheimer's Disease Sequencing Project (ADSP), and test their association with Alzheimer's disease (AD). Methods: In this study, we present MitoH3-a comprehensive computational pipeline for calling mtDNA homoplasmic and heteroplasmic variants and inferring haplogroups in the ADSP WGS data. We first applied MitoH3 to 45 technical replicates from 6 subjects to define a threshold for detecting heteroplasmic variants. Then using the threshold of 5% ≤variant allele fraction≤95%, we further applied MitoH3 to call heteroplasmic variants from a total of 16,113 DNA samples with 6,742 samples from cognitively normal controls and 6,183 from AD cases. Results: This pipeline is available through the Singularity container engine. For 4,311 heteroplasmic variants identified from 16,113 samples, no significant variant count difference was observed between AD cases and controls. Conclusions: Our streamlined pipeline, MitoH3, enables computationally efficient and accurate analysis of a large number of samples.

Archaea-Inspired Switchable Nanochannels for On-Demand Lithium Detection by pH Activation.

With the rapid development of the lithium ion battery industry, emerging lithium (Li) enrichment in nature has attracted ever-growing attention due to the biotoxicity of high Li levels. To date, fast lithium ion (Li+) detection remains urgent but is limited by the selectivity, sensitivity, and stability of conventional technologies based on passive response processes. In nature, archaeal plasma membrane ion exchangers (NCLX_Mj) exhibit Li+-gated multi/monovalent ion transport behavior, activated by different stimuli. Inspired by NCLX_Mj, we design a pH-controlled biomimetic Li+-responsive solid-state nanochannel system for on-demand Li+ detection using 2-(2-hydroxyphenyl)benzoxazole (HPBO) units as Li+ recognition groups. Pristine HPBO is not reactive to Li+, whereas negatively charged HPBO enables specific Li+ coordination under alkaline conditions to decrease the ion exchange capacity of nanochannels. On-demand Li+ detection is achieved by monitoring the decline in currents, thereby ensuring precise and stable Li+ recognition (>0.1 mM) in the toxic range of Li+ concentration (>1.5 mM) for human beings. This work provides a new approach to constructing Li+ detection nanodevices and has potential for applications of Li-related industries and medical services.

HeadDiff: Exploring Rotation Uncertainty With Diffusion Models for Head Pose Estimation.

In this paper, we propose a probabilistic regression diffusion model for head pose estimation, dubbed HeadDiff, which typically addresses the rotation uncertainty, especially when faces are captured in wild conditions. Unlike conventional image-to-pose methods which cannot explicitly establish the rotational manifold of head poses, our HeadDiff aims to ensure the pose rotation via the diffusion process and in parallel, refine the mapping process iteratively. Specifically, we initially formulate the head pose estimation problem as a reverse diffusion process, defining a paradigm for progressive denoising on the manifold, which explores the uncertainty by decomposing the large gap into intermediate steps. Moreover, our HeadDiff is equipped with an isotropic Gaussian distribution by encoding the incoherence information in our rotation representation. Finally, we learn the facial relationship of nearest neighbors with a cycle-consistent constraint for robust pose estimation versus diverse shape variations. Experimental results on multiple datasets demonstrate that our proposed method outperforms existing state-of-the-art techniques without auxiliary data.

DNA from multiple viral species is associated with Alzheimer's disease risk.

INTRODUCTION: Multiple infectious agents, including viruses, bacteria, fungi, and protozoa, have been linked to Alzheimer's disease (AD) risk by independent lines of evidence. We explored this association by comparing the frequencies of viral species identified in a large sample of AD cases and controls. METHODS: DNA sequence reads that did not align to the human genome in sequences were mapped to viral reference sequences, quantified, and then were tested for association with AD in whole exome sequences (WES) and whole genome sequences (WGS) datasets. RESULTS: Several viruses were significant predictors of AD according to the machine learning classifiers. Subsequent regression analyses showed that herpes simplex type 1 (HSV-1) (odds ratio [OR] = 3.71, p = 8.03 × 10-4) and human papillomavirus 71 (HPV-71; OR = 3.56, p = 0.02), were significantly associated with AD after Bonferroni correction. The phylogenetic-related cluster of Herpesviridae was significantly associated with AD in several strata of the data (p < 0.01). DISCUSSION: Our results support the hypothesis that viral infection, especially HSV-1, is associated with AD risk.

Toxic effects and mechanisms of cationic blue SD-GSL on Chlorella vulgaris before and after the biological decolorization process.

Biodegradation is regarded as an efficient way to decolorize azo dyes. However, the changes in the algal toxicity of azo dyes during biodecolorization are still unclear. In this study, the physiological responses of Chlorella vulgaris to the hydrophobic and hydrophilic components of cationic blue SD-GSL (a typical monoazo dye) and its biodecolorization products were investigated. The toxicity of each component to Chlorella vulgaris and the sources of the toxicity were analyzed. The cationic blue SD-GSL components inhibited the algal cell division and superoxide dismutase (SOD) activity at all concentrations, and inhibited the synthesis of chlorophyll-a (Chl-a) at concentrations >100 mg/L, whereas increased the malondialdehyde (MDA) content. The hydrophobic and hydrophilic components of its biodecolorization products had enhanced inhibition rates on cell density (10.7% and 15.6%, respectively), Chl-a content (31.2% and 8.4%, respectively), and SOD activity (13.5% and 1.9%, respectively) of Chlorella vulgaris, and further stimulated an increase in MDA content (4.4% and 7.0%, respectively), indicating that the biodecolorization products were more toxic than the pristine dye. Moreover, the toxic effect of hydrophobic components on Chlorella vulgaris was stronger than that of hydrophilic components. The sensitivity sequence of Chlorella vulgaris to the toxicity of cationic blue SD-GSL and its biodecolorization product components was: Chl-a synthesis > SOD activity > cell division. SUVA analysis and 3D-EEM analysis revealed that the enhanced algal toxicity of the biodecolorization products of cationic blue SD-GSL was attributed to the aromatic compounds, which were mainly concentrated in the hydrophobic components. UPLC-Q-TOF-MS was used to verify dye biodecolorization byproducts. The information obtained from this study helps to understand the decolorization products toxicities of the biologically treated azo dyes, thereby providing new insights into the environmental safety of textile wastewater after traditional biological treatment.

Neuron-Inspired Nanofluidic Biosensors for Highly Sensitive and Selective Imidacloprid Detection.

Pesticides have caused concerns about food safety due to their residual effects in vegetables and fruits. Imidacloprid, as the frequently used neonicotinoid pesticide, could harm cardiovascular and respiratory function and cause reproductive toxicity in humans. Therefore, reliable methods for portable, selective, and rapid detection are desirable to develop. Herein, we report a neuron-inspired nanofluidic biosensor based on a tyrosine-modified artificial nanochannel for sensitively detecting imidacloprid. The functional tyrosine is modified on the outer surface of porous anodic aluminum oxide to rapidly capture imidacloprid through π-π interactions and hydrogen bonds. The integrated nanofluidic biosensor has a wide concentration range from 10-8 to 10-4 g/mL with an ultralow detection limit of 6.28 × 10-9 g/mL, which outperforms the state-of-the-art sensors. This work provides a new perspective on detecting imidacloprid residues as well as other hazardous pesticide residues in environmental and food samples.

Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK , GRB14 , and KIAA0825 as novel risk loci for Alzheimer's disease: the Alzheimer's Disease Genetics Consortium.

Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset in the Alzheimer's Disease (AD) Genetics Consortium (ADGC) to test for novel shared and ancestry-specific AD susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American, 8,899 Hispanic (HIS), and 3,232 East Asian individuals, performing within-ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. We identified 13 loci with cross-ancestry associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). Reflecting the power of diverse ancestry in GWAS, we observed the SHARPIN locus using 7.1% the sample size of the original discovering single-ancestry GWAS (n=788,989). We additionally identified three GWS ancestry-specific loci at/near ( PTPRK ( P =2.4×10 -8 ) and GRB14 ( P =1.7×10 -8 ) in HIS), and KIAA0825 ( P =2.9×10 -8 in NHW). Pathway analysis implicated multiple amyloid regulation pathways (strongest with P adjusted =1.6×10 -4 ) and the classical complement pathway ( P adjusted =1.3×10 -3 ). Genes at/near our novel loci have known roles in neuronal development ( LRRC4C, LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). These findings provide compelling support for using traditionally-underrepresented populations for gene discovery, even with smaller sample sizes.

Cuproptosis-related miRNAs signature and immune infiltration characteristics in colorectal cancer.

BACKGROUND: A novel form of cell death termed cuproptosis was proposed recently. miRNAs play important roles in colorectal cancer (CRC). However, their relationships have not been reported. METHODS: miRNAs that negatively regulate 16 cuproptosis regulators were predicted using Targetscan database. The univariate Cox, LASSO, and multivariate Cox regression analyses were performed to select cuproptosis-related miRNAs. GSEA and ssGSEA analysis was carried out for functional enrichment analysis. The immune cell proportion score (IPS) and the efficiencies of multiple chemotherapy drugs were compared between different risk groups. The CCK8, cell colony, edu, and flow cytometry assays were performed to validate the roles of miRNA. Luciferase reporter assay confirmed the regulatory mechanism of miRNA on cuproptosis. RESULTS: Six cuproptosis-related miRNAs (hsa-miR-653, hsa-miR-216a, hsa-miR-3684, hsa-miR-4437, hsa-miR-641, and hsa-miR-552) were screened out for model construction. The risk score could act as an independent prognostic indicator in CRC (p < 0.001, 95% HR = 1.243 (1.129-1.369)). The nomogram could efficiently predict the overall survival rate (AUC = 0.836). Then, the level of immunosuppressive pathways, immunosuppressive cells, stromal-activated genes, and stromal score was higher in the high-risk group. The IPS analysis showed a better response to immunotherapy in the low-risk group. Also, the risk score was closely correlated with efficiencies of multiple chemotherapy drugs. Furthermore, miR-653 was highly expressed in CRC tissues (p < 0.001), closely correlated with T stage (p < 0.001), metastasis (p < 0.001), and tumor stage (p < 0.001). High expression of miR-653 predicted a shorter overall survival (p = 0.0282) and disease-free survival (p = 0.0056). In addition, miR-653 promoted cell proliferation, inhibited apoptosis, and negatively regulated the expression of DLD through directly binding to the 3'-UTR of DLD mRNA. CONCLUSION: We constructed a cuproptosis-related miRNA signature for the prediction of CRC patient survival and immunotherapy sensitivity. miR-653 was highly expressed in CRC tissues, promoted cell proliferation, and inhibited apoptosis by negatively regulating the expression of DLD.

Efficient Solar-osmotic Power Generation from Bioinspired Anti-fouling 2D WS2 Composite Membranes.

Nanofluidic reverse electrodialysis provides an attractive way to harvest osmotic energy. However, most attention was paid to monotonous membrane structure optimization to promote selective ion transport, while the role of external fields and relevant mechanisms are rarely explored. Here, we demonstrate a Kevlar-toughened tungsten disulfide (WS2 ) composite membrane with bioinspired serosa-mimetic structures as an efficient osmotic energy generator coupling light. As a result, the output power could be up to 16.43 W m-2 under irradiation, outperforming traditional two-dimensional (2D) membranes. Both the experiment and simulation uncover that the generated photothermal and photoelectronic effects could synergistically promote the confined ion transport process. In addition, this membrane also possesses great anti-fouling properties, endowing its practical application. This work paves new avenues for sustainable power generation by coupling solar energy.

Effect and mechanism of longkui yinxiao soup in treating psoriasis in mice.

Objective: Longkui Yinxiao Soup is a traditional Chinese medicine formula used to treat psoriasis for decades. Although Longkui Yinxiao Soup showed promising efficacy in clinical practice, the regulatory mechanisms of Longkui Yinxiao Soup remain elusive. This study aimed to explore the underlying mechanisms of Longkui Yinxiao Soup in a psoriasis-like mouse model. Methods: Longkui Yinxiao Soup was quality controlled by determining the contents of imperatorin and rhoifolin using high-performance liquid chromatography. The imiquimod-induced psoriasis-like mouse model was used to study the therapeutic effect and mechanism of Longkui Yinxiao Soup. The histopathological skin changes were observed by hematoxylin and eosin staining; the infiltration of proliferating proteins, proliferating cell nuclear antigen and Ki67, in skin tissues were observed by immunohistochemical analysis; and the inflammatory factors such as interleukin (IL)-6, tumor necrosis factor (TNF)-α, IL-23, and IL-17 in serum were detected using enzyme-linked immunosorbent assay. RNA sequencing and bioinformatic analysis were used to predict the mechanism of LYS against psoriasis. mRNA expressions of p38, extracellular regulated protein kinases (ERK), mitogen-activated protein kinase 3 (MEK3), mitogen-activated protein kinase 6 (MEK6), RAP1 GTPase activating protein (Rap1gap), and Rap1 were determined using real-time quantitative polymerase chain reaction. The expression levels of proteins related to Rap1-mitogen-activated protein kinase signaling pathways were measured by Western blotting. Results: A quality-control method for Longkui Yinxiao Soup was successfully established using imperatorin and rhoifolin as content determination indexes. Longkui Yinxiao Soup significantly ameliorated the psoriatic symptoms in mice. The serum levels of inflammatory cytokines such as IL-6, TNF-α, IL-23, and IL-17 were decreased, and the expression levels of antigen identified by monoclonal antibody Ki67 (Ki67) and PCNA in skin tissues were downregulated. Moreover, the inhibition of Rap1-MAPK signaling pathways by Longkui Yinxiao Soup was detected. Conclusion: This study confirmed the antipsoriatic activity of Longkui Yinxiao Soup in psoriasis-like mice. This might be due to the inhibition of inflammatory factor secretion, keratinocyte proliferation, and the Rap1-MAPK signal pathway.

A DNA methylation signature for the prediction of tumour recurrence in stage II colorectal cancer.

BACKGROUND: A major challenge in stage II colorectal carcinoma is to identify patients with increased risk of recurrence. Biomarkers that distinguish patients with poor prognosis from patients without recurrence are currently lacking. This study aims to develop a robust DNA methylation classifier that allows the prediction of recurrence and chemotherapy benefit in patients with stage II colorectal cancer. We performed a genome-wide DNA methylation capture sequencing in 243 stage II colorectal carcinoma samples and identified a relapse-specific DNA methylation signature consisting of eight CpG sites. METHODS: Two hundred and forty-three patients with stage II CRC were enrolled in this study. In order to select differential methylation sites among recurrence and non-recurrence stage II CRC samples, DNA methylation profiles of 62 tumour samples including 31 recurrence and 31 nonrecurrence samples were analysed using the Agilent SureSelectXT Human Methyl-Seq, a comprehensive target enrichment system to analyse CpG methylation. Pyrosequencing was applied to quantify the methylation level of candidate DNA methylation sites in 243 patients. Least absolute shrinkage and selection operator (LASSO) method was employed to build the disease recurrence prediction classifier. RESULTS: We identified a relapse-related DNA methylation signature consisting of eight CpG sites in stage II CRC by DNA methylation capture sequencing. The classifier showed significantly higher prognostic accuracy than any clinicopathological risk factors. The Kaplan-Meier survival curve showed an association of high-risk score with poor prognosis. In multivariate analysis, the signature was the most significant prognosis factor, with an HR of 2.80 (95% CI, 1.71-4.58, P < 0.001). The signature could identify patients who are suitable candidates for adjuvant chemotherapy. CONCLUSIONS: An eight-CpG DNA methylation signature is a reliable prognostic and predictive tool for disease recurrence in patients with stage II CRC.

Model-Based Self-Advising for Multi-Agent Learning.

In multiagent learning, one of the main ways to improve learning performance is to ask for advice from another agent. Contemporary advising methods share a common limitation that a teacher agent can only advise a student agent if the teacher has experience with an identical state. However, in highly complex learning scenarios, such as autonomous driving, it is rare for two agents to experience exactly the same state, which makes the advice less of a learning aid and more of a one-time instruction. In these scenarios, with contemporary methods, agents do not really help each other learn, and the main outcome of their back and forth requests for advice is an exorbitant communications' overhead. In human interactions, teachers are often asked for advice on what to do in situations that students are personally unfamiliar with. In these, we generally draw from similar experiences to formulate advice. This inspired us to provide agents with the same ability when asked for advice on an unfamiliar state. Hence, we propose a model-based self-advising method that allows agents to train a model based on states similar to the state in question to inform its response. As a result, the advice given can not only be used to resolve the current dilemma but also many other similar situations that the student may come across in the future via self-advising. Compared with contemporary methods, our method brings a significant improvement in learning performance with much lower communication overheads.

Vascular Endothelial Growth Factor A VEGFA Inhibition: An Effective Treatment Strategy for Psoriasis.

Psoriasis is an inflammatory skin disease mediated by the immune system and characterized by an inflammatory ring, also known as an epithelial immune microenvironment (EIME). The interaction between the epithelial tissue of the skin and the immune system has a crucial role in the immune cycle of psoriasis. Although the formation of new blood vessels in skin lesions provides energy support for the proliferation of epidermal keratinocytes, the role of angiogenesis in psoriasis has not been extensively studied. Vascular endothelial growth factor A (VEGFA) is a key regulator of angiogenesis that has an important role in the development of psoriasis. VEGFA promotes angiogenesis and directly stimulates epidermal keratinocytes and infiltrating immune cells, thus contributing to the progression of psoriasis. Measuring VEGFA levels to identify angiogenic characteristics in psoriasis patients may be a predictive biomarker for disease severity and response to anti-angiogenic therapy. Clinical data have shown that anti-angiogenic therapy can improve skin lesions in psoriasis patients. Therefore, this study aimed to uncover the underestimated role of blood vessels in psoriasis, explore the relationship between VEGFA and keratinocytes in the EIME, and inspire innovative drug therapies for the treatment of psoriasis.

Comprehensive analysis of cuproptosis-related lncRNAs to predict prognosis and immune infiltration characteristics in colorectal cancer.

Background: Cuproptosis is a novel form of cell death discovered in recent. A great quantity of researches has confirmed the close relationships and crucial roles between long non-coding RNAs (lncRNAs) with the progression of colorectal cancer (CRC). However, the relationship between cuproptosis and lncRNAs remains unclear in CRC. Methods: 1,111 co-expressed lncRNAs with 16 cuproptosis regulators were retrieved from CRC samples of The Cancer Genome Atlas (TCGA) database. Through univariate Cox and least absolute shrinkage and selection operator regression analysis, a prognosis model was constructed with 15 lncRNAs. The Kaplan-Meier, receiver operating characteristic curve, C-index and principal component analysis identified the prognostic power. Furthermore, a cuproptosis-related cluster was generated based on the 15 lncRNAs by unsupervised methods. The correlations between the cuproptosis-related signatures with immune cell infiltration and anti-tumor therapy were explored by multiple algorithms. Results: A risk score and nomogram with great prediction ability were constructed for CRC prognosis evaluation. The immune activate pathways, immune infiltration cells, immune functions, immune score and immune activation genes were remarkably enriched in the high risk group. The cuproptosis-related cluster was generated, of which the cluster 2 showed longer overall survival. The immune cell infiltration analysis indicated the similar results of cluster 2 with the high risk group, implying a significant marker for "hot tumor." The cluster 2 also presented high expression of immune checkpoint molecules, MSI-H status and higher susceptibility to multiple immunotherapy drugs. Conclusion: We appraised a novel cuproptosis-related prognosis model and molecular signature associated with prognosis, immune infiltration and immunotherapy. The identification of cuproptosis-related lncRNAs improved our understanding of immune infiltration and provided a significant marker for prognosis and immunotherapy in CRC.

The impact of increasing levels of blood C-reactive protein on the inflammatory loci SPI1 and CD33 in Alzheimer's disease.

Apolipoprotein ε4 (APOE ε4) is the most significant genetic risk factor for late-onset Alzheimer's disease (AD). Elevated blood C-reactive protein (CRP) further increases the risk of AD for people carrying the APOE ε4 allele. We hypothesized that CRP, as a key inflammatory element, could modulate the impact of other genetic variants on AD risk. We selected ten single nucleotide polymorphisms (SNPs) in reported AD risk loci encoding proteins related to inflammation. We then tested the interaction effects between these SNPs and blood CRP levels on AD incidence using the Cox proportional hazards model in UK Biobank (n = 279,176 white participants with 803 incident AD cases). The five top SNPs were tested for their interaction with different CRP cutoffs for AD incidence in the Framingham Heart Study (FHS) Generation 2 cohort (n = 3009, incident AD = 156). We found that for higher concentrations of serum CRP, the AD risk increased for SNP genotypes in 3 AD-associated genes (SPI1, CD33, and CLU). Using the Cox model in stratified genotype analysis, the hazard ratios (HRs) for the association between a higher CRP level (≥10 vs. <10 mg/L) and the risk of incident AD were 1.94 (95% CI: 1.33-2.84, p < 0.001) for the SPI1 rs1057233-AA genotype, 1.75 (95% CI: 1.20-2.55, p = 0.004) for the CD33 rs3865444-CC genotype, and 1.76 (95% CI: 1.25-2.48, p = 0.001) for the CLU rs9331896-C genotype. In contrast, these associations were not observed in the other genotypes of these genes. Finally, two SNPs were validated in 321 Alzheimer's Disease Neuroimaging (ADNI) Mild Cognitive Impairment (MCI) patients. We observed that the SPI1 and CD33 genotype effects were enhanced by elevated CRP levels for the risk of MCI to AD conversion. Furthermore, the SPI1 genotype was associated with CSF AD biomarkers, including t-Tau and p-Tau, in the ADNI cohort when the blood CRP level was increased (p < 0.01). Our findings suggest that elevated blood CRP, as a peripheral inflammatory biomarker, is an important moderator of the genetic effects of SPI1 and CD33 in addition to APOE ε4 on AD risk. Monitoring peripheral CRP levels may be helpful for precise intervention and prevention of AD for these genotype carriers.

Theoretical analysis of the absorption of CO2 and CO on pristine and Al-doped C3B.

CO2 and CO, the by-products of fossil fuels; one of them is a major cause of global warming and the other endangers the nervous and cardiovascular systems of humans. Therefore, real-time monitoring towards those harmful gases is of practical significance. Nano-structured materials have attracted the attention of scholars for their enormous potential for harmful gas detection. In this work, the adsorption and sensing behavior of C3B and Al-doped C3B monolayers for these two typical hazardous gases were investigated theoretically. The most stable doping model was obtained, and the adsorption process for CO and CO2 was simulated based on this model. The adsorption system shows that the gas molecules are all deformed and that the charge transfer and adsorption energy are significantly increased. Moreover, the adsorption mechanism was investigated by analyzing the electronic behavior of the adsorbent, and the physical adsorption between the hazardous gas and the adsorbent was more favorable for desorption. The good adsorption performance and sensing mechanism suggest that the CO/CO2 sensor prepared using Al-C3B has great potential for application. Our work may provide some guidance for the application of toxic gas monitoring and adsorption.

A novel cuproptosis-related molecular pattern and its tumor microenvironment characterization in colorectal cancer.

Cuproptosis, or copper-induced cell death, has been reported as a novel noncanonical form of cell death in recent times. However, the potential roles of cuproptosis in the alteration of tumor clinicopathological features and the formation of a tumor microenvironment (TME) remain unclear. In this study, we comprehensively analyzed the cuproptosis-related molecular patterns of 1,274 colorectal cancer samples based on 16 cuproptosis regulators. The consensus clustering algorithm was conducted to identify cuproptosis-related molecular patterns and gene signatures. The ssGSEA and ESTIMATE algorithms were used to evaluate the enrichment levels of the infiltrated immune cells and tumor immune scores, respectively. The cuproptosis score was established to assess the cuproptosis patterns of individuals with principal component analysis algorithms based on the expression of cuproptosis-related genes. Three distinct cuproptosis patterns were confirmed and demonstrated to be associated with distinguishable biological processes and clinical prognosis. Interestingly, the three cuproptosis patterns were revealed to be consistent with three immune infiltration characterizations: immune-desert, immune-inflamed, and immune-excluded. Enhanced survival, activation of immune cells, and high tumor purity were presented in patients with low cuproptosisScore, implicating the immune-inflamed phenotype. In addition, low scores were linked to high tumor mutation burden, MSI-H and high CTLA4 expression, showing a higher immune cell proportion score (IPS). Taken together, our study revealed a novel cuproptosis-related molecular pattern associated with the TME phenotype. The formation of cuproptosisScore will further strengthen our understanding of the TME feature and instruct a more personalized immunotherapy schedule in colorectal cancer.

Enhanced Energy Storage Performance of PVDF-Based Composites Using BN@PDA Sheets and Titania Nanosheets.

With the rapid development of modern electrical and electronic applications, the demand for high-performance film capacitors is becoming increasingly urgent. The energy density of a capacitor is dependent on permittivity and breakdown strength. However, the development of polymer-based composites with both high permittivity (εr) and breakdown strength (Eb) remains a huge challenge. In this work, a strategy of doping synergistic dual-fillers with complementary functionalities into polymer is demonstrated, by which high εr and Eb are obtained simultaneously. Small-sized titania nanosheets (STNSs) with high εr and high-insulating boron nitride sheets coated with polydopamine on the surface (BN@PDA) were introduced into poly(vinylidene fluoride) (PVDF) to prepare a ternary composite. Remarkably, a PVDF-based composite with 1 wt% BN@PDA and 0.5 wt% STNSs (1 wt% PVDF/BN@PDA-STNSs) shows an excellent energy storage performance, including a high εr of ~13.9 at 1 Hz, a superior Eb of ~440 kV/mm, and a high discharged energy density Ue of ~12.1 J/cm3. Moreover, the simulation results confirm that BN@PDA sheets improve breakdown strength and STNSs boost polarization, which is consistent with the experimental results. This contribution provides a new design paradigm for energy storage dielectrics.

Macrophage Membrane-Derived Biomimetic Nanoparticles for Treatment of Cytokine Release Syndrome.

Cytokine release syndrome (CRS) is a severe complication of infectious diseases like Coronavirus disease 2019 (COVID-19) that cause serious damage to public health. Currently, supportive therapy is still the main therapeutic strategy exists for CRS treatment. Here, we show the potential of macrophage membrane-derived biomimetic nanoparticles for CRS treatment. By fusing macrophage membrane on the surface of the PLGA nano core, we constructed biomimetic nanoparticles that inherited the membrane receptors from the "parental" macrophages, enabling the neutralization of CRS-related cytokines. We compared three types of macrophage membranes to screen out more effective biomimetic nanoparticles for CRS treatment. Our results show that M0 macrophage membrane-derived biomimetic nanoparticles could neutralize pro-inflammatory cytokines involved in CRS to the greatest extent and reduce organ damage in a mouse model.

Humidity-Based Human-Machine Interaction System for Healthcare Applications.

Human-machine interaction (HMI) systems are widely used in the healthcare field, and they play an essential role in assisting the rehabilitation of patients. Currently, a large number of HMI-related research studies focus on piezoresistive sensors, self-power sensors, visual and auditory receivers, and so forth. These sensing modalities do not possess high reliability with regard to breathing condition detection. The humidity signal conveyed by breathing provides excellent stability and a fast response; however, humidity-based HMI systems have rarely been studied. Herein, we integrate a humidity sensor and a graphene thermoacoustic device into a humidity-based HMI system (HHMIS), which is capable of monitoring respiratory signals and emitting acoustic signals. HHMIS has a practical value in healthcare to assist patients. For example, it works as a prewarning system for respiratory-related disease patients with abnormal respiratory rates, and as an artificial throat device for aphasia patients. Achieved based on a laser direct writing technology, this wearable device features low cost, high flexibility, and can be prepared on a large scale. This portable non-contact HMMIS has broad application prospects in many fields such as medical health and intelligent control.