Plasma Metabolic Profiles-Based Prediction of Induction Chemotherapy Efficacy in Nasopharyngeal Carcinoma: Results of a Bidirectional Clinical Trial.

PURPOSE: The efficacy of induction chemotherapy (IC) as a primary treatment for advanced nasopharyngeal carcinoma (NPC) remains a topic of debate, with a lack of dependable biomarkers for predicting its efficacy. This study seeks to establish a predictive classifier utilizing plasma metabolomics profiling. EXPERIMENTAL DESIGN: A total of 166 NPC patients enrolled in the clinical trial NCT05682703 and undergoing IC were included in the study. Plasma lipoprotein profiles were obtained using 1H-NMR before and after IC treatment. An AI-assisted radiomics method was developed to effectively evaluate the efficacy. Metabolic biomarkers were identified through a machine learning approach based on a discovery cohort and subsequently validated in a validation cohort that mimicked the most unfavorable scenario in real-world. RESULTS: Our research findings indicate that the effectiveness of IC varies among individual patients, with a correlation observed between efficacy and changes in metabolite profiles. Utilizing machine learning techniques, it was determined that the XGB model exhibited notable efficacy, attaining an Area Under the Curve (AUC) value of 0.792 (95% CI, 0.668-0.913). In the validation cohort, the model exhibited strong stability and generalizability with an AUC of 0.786 (95%CI, 0.533-0.922). CONCLUSION: In this study, we found that dysregulation of plasma lipoprotein may result in resistance to IC in NPC patients. The prediction model constructed based on the plasma metabolites' profile as good predictive capabilities and potential for real-world generalization. This discovery has implications for the development of treatment strategies and may offer insight into potential targets for enhancing the effectiveness of IC.

Synergistic Effects of TiO2 and Carbon Black for Water Evaporation-Induced Electricity Generation.

Water evaporation-induced electricity generators (WEGs) have drawn widespread attention in the field of hydrovoltaic technology, which can convert atmospheric thermal energy into sustainable electric power. However, it is restricted in the wide application of WEGs due to the low power output, complex fabrication process, and high cost. Herein, we present a simple and effective approach to fabricate TiO2-carbon black film-based WEGs (TC-WEGs). A single TC-WEG device can sustainably output an open-circuit voltage of 1.9 V and a maximum power density of 40.9 µW/cm2. Moreover, it has been shown that TC-WEGs exhibit stable electrical energy output when operating in seawater, which can yield a short-circuit current of 1.2 µA. The superior electricity generation performance can be attributed to the intrinsic characteristics of the TC-WEGs, including hydrophilicity, porous structure, and electrical conductivity. This work provides an important reference for the constant harvesting of clean energy.

A novel splicing variant in MICAL-1 gene is associated with epilepsy.

Germline MICAL1 defects have been rarely reported in patients with epilepsy and the genotype-phenotype association remains unclear. In this study, the patient was a 4.6 years old girl who presented with onset of recurrent focal seizures with onset at age 3.4 years. EEG showed abnormal δ-wave activity in the right central and middle temporal lobe. Trio WES showed a novel heterozygous variant c.-43-1G > A in the MICAL1 gene in the patient and her normal mother. Minigene verified two abnormal transcripts due to the mutation, which was predicted to interrupt 5'UTR structures of MICAL1. The patient was clinically diagnosed with benign childhood epilepsy with centrotemporal spike (BECTS). As far as we know, this is the first BECTS case with documented MICAL1 mutation. Novel MICAL1 variant c.-43-1G > A putatively interrupted MICAL1 translation by changing 5'UTR structures and, however, further functioning study is needed.

The Association of Malnutrition and Health-Related Factors among 474,467 Older Community-Dwellers: A Population-Based Data Mining Study in Guangzhou, China.

BACKGROUND: This study aimed to examine the prevalence and associated factors of malnutrition in older community-dwellers and explore the interaction between associated factors. METHODS: A total of 474,467 older community-dwellers aged 65 or above were selected in Guangzhou, China. We used a two-step methodology to detect the associated factors of malnutrition and constructed logistic regression models to explore the influencing factors and interactive effects on three patterns of malnutrition. RESULTS: The prevalence of malnutrition was 22.28%. Older adults with both hypertension and diabetes (RERI = 0.13), both meat or fish diet and hypertension (RERI = 0.79), and both meat or fish diet and diabetes (RERI = 0.81) had positive additive interaction effects on the risk of obesity, whereas those on a vegetarian diet with hypertension (RERI = -0.25) or diabetes (RERI = -0.19) had negative additive interaction effects. Moreover, the interactions of physical activity with a meat or fish diet (RERI = -0.84) or dyslipidemia (RERI = -0.09) could lower the risk of obesity. CONCLUSIONS: Malnutrition was influenced by different health factors, and there were interactions between these influencing factors. Pertinent dietary instruction should be given according to different nutritional status indexes and the prevalence of metabolic diseases to avoid the occurrences of malnutrition among older adults.

Fusobacterium nucleatum-induced imbalance in microbiome-derived butyric acid levels promotes the occurrence and development of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) ranks among the most prevalent malignant tumors globally. Recent reports suggest that Fusobacterium nucleatum (F. nucleatum) contributes to the initiation, progression, and prognosis of CRC. Butyrate, a short-chain fatty acid derived from the bacterial fermentation of soluble dietary fiber, is known to inhibit various cancers. This study is designed to explore whether F. nucleatum influences the onset and progression of CRC by impacting the intestinal metabolite butyric acid. AIM: To investigate the mechanism by which F. nucleatum affects CRC occurrence and development. METHODS: Alterations in the gut microbiota of BALB/c mice were observed following the oral administration of F. nucleatum. Additionally, DLD-1 and HCT116 cell lines were exposed to sodium butyrate (NaB) and F. nucleatum in vitro to examine the effects on proliferative proteins and mitochondrial function. RESULTS: Our research indicates that the prevalence of F. nucleatum in fecal samples from CRC patients is significantly greater than in healthy counterparts, while the prevalence of butyrate-producing bacteria is notably lower. In mice colonized with F. nucleatum, the population of butyrate-producing bacteria decreased, resulting in altered levels of butyric acid, a key intestinal metabolite of butyrate. Exposure to NaB can impair mitochondrial morphology and diminish mitochondrial membrane potential in DLD-1 and HCT116 CRC cells. Consequently, this leads to modulated production of adenosine triphosphate and reactive oxygen species, thereby inhibiting cancer cell proliferation. Additionally, NaB triggers the adenosine monophosphate-activated protein kinase (AMPK) signaling pathway, blocks the cell cycle in HCT116 and DLD-1 cells, and curtails the proliferation of CRC cells. The combined presence of F. nucleatum and NaB attenuated the effects of the latter. By employing small interfering RNA to suppress AMPK, it was demonstrated that AMPK is essential for NaB's inhibition of CRC cell proliferation. CONCLUSION: F. nucleatum can promote cancer progression through its inhibitory effect on butyric acid, via the AMPK signaling pathway.

Substrate-Independent Superhydrophobic Coating Capable of Photothermal-Induced Repairability for Multiple Damages Fabricated via Simple Blade Coating.

Repairable superhydrophobic surfaces have promising application potential in many fields. However, so far, it is still a challenge to develop a superhydrophobic surface with repairability for multiple types of damage through a simple method. In this paper, a repairable superhydrophobic coating was obtained on various substrates by blade-coating mixtures of polydimethylsiloxane (PDMS), polyvinylidene fluoride (PVDF), and multiwalled carbon nanotubes (MWCNTs) modified with dopamine (PDA) and octadecylamine (ODA). The obtained coating has a good liquid-repellent property with a water contact angle above 150° and a water sliding angle of ∼6° and possesses an excellent absorbance (∼97%) in the wavelength range of 250-2500 nm. Due to its high absorbance, the coating displays an outstanding photothermal effect with a temperature rise of ∼65 °C under irradiation by 1.0 kW/m2 of simulated sunlight. Furthermore, after being degraded by multiple stimuli, including plasma treatment, acid/alkali/oil immersion, sand impact, and the icing-thawing cycle, the coating can recover superhydrophobicity via sunlight irradiation, demonstrating the good photothermal-induced repairability of the coating. It can be expected that the good water-repellent property, photothermal effect, and repairability give this coating a promising prospect in practical applications.

The development of a novel zeolite-based assay for efficient and deep plasma proteomic profiling.

Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications.

Rising trend and regional disparities of the global burden of disease attributable to ambient low temperature, 1990-2019: An analysis of data from the Global Burden of Disease 2019 study.

Background: Previous studies on the effect of global warming on the global burden of disease have mainly focussed on the impact of high temperatures, thereby providing limited evidence of the effect of lower temperatures. Methods: We adopted a three-stage analysis approach using data from the Global Burden of Disease 2019 study. First, we explored the global burden of disease attributable to low temperatures, examining variations by gender, age, cause, region, and country. Second, we analysed temporal trends in low-temperature-related disease burdens from 1990 to 2019 by meta-regression. Finally, we fitted a mixed-effects meta-regression model to explore the effect modification of country-level characteristics. Results: In 2019, low temperatures were responsible for 2.92% of global deaths and 1.03% of disability-adjusted life years (DALYs), corresponding to a death rate of 21.36 (95% uncertainty interval (UI) = 18.26, 24.73) and a DALY rate of 335 (95% UI = 280, 399) per 100 000 population. Most of the deaths (85.12%) and DALYs (94.38%) attributable to low temperatures were associated with ischaemic heart disease, stroke, and chronic obstructive pulmonary disease. In the last three decades, we observed an upward trend for the annual number of attributable deaths (P < 0.001) and a downward trend for the rates of death (P < 0.001) and DALYs (P < 0.001). The disease burden associated with low temperatures varied considerably among regions and countries, with higher burdens observed in regions with middle or high-middle socio-demographic indices, as well as countries with higher gross domestic product per capita and a larger proportion of ageing population. Conclusions: Our findings emphasise the significance of raising public awareness and prioritising policies to protect global population health from the adverse effects of low temperatures, even in the face of global warming. Particular efforts should be targeted towards individuals with underlying diseases (e.g. cardiovascular diseases) and vulnerable countries or regions (e.g. Central Asia and central Europe).

A sensitive and versatile electrochemical sensor based on hybridization chain reaction and CRISPR/Cas12a system for antibiotic detection.

A sensitive electrochemical platform was constructed with NH2-Cu-MOF as electrochemical probe to detect antibiotics using CRISPR/Cas12a system triggered by hybridization chain reaction (HCR). The sensing system consists of two HCR systems. HCR1 occurred on the electrode surface independent of the target, generating long dsDNA to connect signal probes and producing a strong electrochemical signal. HCR2 was triggered by target, and the resulting dsDNA products activated the CRISPR/Cas12a, thereby resulting in effective and rapid cleavage of the trigger of HCR1, hindering the occurrence of HCR1, and reducing the number of NH2-Cu-MOF on the electrode surface. Eventually, significant signal change depended on the target was obtained. On this basis and with the help of the programmability of DNA, kanamycin and ampicillin were sensitively detected with detection limits of 60 fM and 10 fM (S/N = 3), respectively. Furthermore, the sensing platform showed good detection performance in milk and livestock wastewater samples, demonstrating its great application prospects in the detection of antibiotics in food and environmental water samples.

Immunotherapy and the ovarian cancer microenvironment: Exploring potential strategies for enhanced treatment efficacy.

Despite progress in cancer immunotherapy, ovarian cancer (OC) prognosis continues to be disappointing. Recent studies have shed light on how not just tumour cells, but also the complex tumour microenvironment, contribute to this unfavourable outcome of OC immunotherapy. The complexities of the immune microenvironment categorize OC as a 'cold tumour'. Nonetheless, understanding the precise mechanisms through which the microenvironment influences the effectiveness of OC immunotherapy remains an ongoing scientific endeavour. This review primarily aims to dissect the inherent characteristics and behaviours of diverse cells within the immune microenvironment, along with an exploration into its reprogramming and metabolic changes. It is expected that these insights will elucidate the operational dynamics of the immune microenvironment in OC and lay a theoretical groundwork for improving the efficacy of immunotherapy in OC management.

[Resources and utilization of medicinal plants in countries and regions involved in "the Belt and Road" Initiative].

The protection, development, and utilization of medicinal plant resources are important cornerstones of maintaining human health. However, due to factors such as the reduction of high-quality land resources, deterioration of ecological environments, and excessive and disorderly resource development, medicinal plant resources are becoming scarce, and some of them are insufficiently supplied. With the proposal of "the Belt and Road" Initiative, the cooperation between China and "the Belt and Road" partners(the countries and regions involved in "the Belt and Road" Initiative)is increasingly close, which provides a new opportunity for carrying out trade of medicinal plant resources and alleviating the problem of imbalance and relative inadequacy of medicinal plant resources in countries. This study first determined the distribution and species information of plant resources in countries and regions involved in "the Belt and Road" Initiative by investigating the database of plant distribution and that of medicinal plant resources. Then, according to the published data from the International Union for Conservation of Nature(IUCN) and the Convention on International Trade in Endangered Species of Wild Fauna and Flora(CITES), this study identified the rare and endangered medicinal plants and the medicinal plants under trade control in countries and regions involved in "the Belt and Road" Initiative and finally sorted out the list of potential medicinal plant resources in countries and regions involved in "the Belt and Road" Initiative that can be used by China. This data resource can not only be used for the overall protection of important endangered species but also scientifically guide the development and utilization of medicinal resources, providing guidance and a theoretical basis for the sustainable development of medicinal plant resources in countries and regions involved in "the Belt and Road" Initiative.

Mulberry and Hippophae-based solid beverage promotes weight loss in rats by antagonizing white adipose tissue PPARγ and FGFR1 signaling.

Obesity, a multifactorial disease with many complications, has become a global epidemic. Weight management, including dietary supplementation, has been confirmed to provide relevant health benefits. However, experimental evidence and mechanistic elucidation of dietary supplements in this regard are limited. Here, the weight loss efficacy of MHP, a commercial solid beverage consisting of mulberry leaf aqueous extract and Hippophae protein peptides, was evaluated in a high-fat high-fructose (HFF) diet-induced rat model of obesity. Body component analysis and histopathologic examination confirmed that MHP was effective to facilitate weight loss and adiposity decrease. Pathway enrichment analysis with differential metabolites generated by serum metabolomic profiling suggests that PPAR signal pathway was significantly altered when the rats were challenged by HFF diet but it was rectified after MHP intervention. RNA-Seq based transcriptome data also indicates that MHP intervention rectified the alterations of white adipose tissue mRNA expressions in HFF-induced obese rats. Integrated omics reveals that the efficacy of MHP against obesogenic adipogenesis was potentially associated with its regulation of PPARγ and FGFR1 signaling pathway. Collectively, our findings suggest that MHP could improve obesity, providing an insight into the use of MHP in body weight management.

Identification of molecular characteristics of hepatocellular carcinoma with microvascular invasion based on deep targeted sequencing.

BACKGROUND: As an indicator of tumor invasiveness, microvascular invasion (MVI) is a crucial risk factor for postoperative relapse, metastasis, and unfavorable prognosis in hepatocellular carcinoma (HCC). Nevertheless, the genetic mechanisms underlying MVI, particularly for Chinese patients, remain mostly uncharted. METHODS: We applied deep targeted sequencing on 66 Chinese HCC samples. Focusing on the telomerase reverse transcriptase (TERT) promoter (TERTp) and TP53 co-mutation (TERTp+/TP53+) group, gene set enrichment analysis (GSEA) was used to explore the potential molecular mechanisms of the TERTp+/TP53+ group on tumor progression and metastasis. Additionally, we evaluated the tumor immune microenvironment of the TERTp+/TP53+ group in HCC using multiplex immunofluorescence (mIF) staining. RESULTS: Among the 66 HCC samples, the mutated genes that mostly appeared were TERT, TP53, and CTNNB1. Of note, we found 10 cases with TERTp+/TP53+, of which nine were MVI-positive and one was MVI-negative, and there was a co-occurrence of TERTp and TP53 (p < 0.05). Survival analysis demonstrated that patients with the TERTp+/TP53+ group had lower the disease-free survival (DFS) (p = 0.028). GSEA results indicated that telomere organization, telomere maintenance, DNA replication, positive regulation of cell cycle, and negative regulation of immune response were significantly enriched in the TERTp+/TP53+ group (all adjusted p-values (p.adj) < 0.05). mIF revealed that the TERTp+/TP53+ group decreased CD8+ T cells infiltration (p = 0.25) and enhanced PDL1 expression (p = 0.55). CONCLUSIONS: TERTp+/TP53+ was significantly enriched in MVI-positive patients, leading to poor prognosis for HCC patients by promoting proliferation of HCC cell and inhibiting infiltration of immune cell surrounding HCC. TERTp+/TP53+ can be utilized as a potential indicator for predicting MVI-positive patients and poor prognosis, laying a preliminary foundation for further exploration of co-mutation in HCC with MVI and clinical treatment.

Role of targeting ferroptosis as a component of combination therapy in combating drug resistance in colorectal cancer.

Colorectal cancer (CRC) is a form of cancer that is often resistant to chemotherapy, targeted therapy, radiotherapy, and immunotherapy due to its genomic instability and inflammatory tumor microenvironment. Ferroptosis, a type of non-apoptotic cell death, is characterized by the accumulation of iron and the oxidation of lipids. Studies have revealed that the levels of reactive oxygen species and glutathione in CRC cells are significantly lower than those in healthy colon cells. Erastin has emerged as a promising candidate for CRC treatment by diminishing stemness and chemoresistance. Moreover, the gut, responsible for regulating iron absorption and release, could influence CRC susceptibility through iron metabolism modulation. Investigation into ferroptosis offers new insights into CRC pathogenesis and clinical management, potentially revolutionizing treatment approaches for therapy-resistant cancers.

T2-weighted imaging-based radiomic-clinical machine learning model for predicting the differentiation of colorectal adenocarcinoma.

BACKGROUND: The study on predicting the differentiation grade of colorectal cancer (CRC) based on magnetic resonance imaging (MRI) has not been reported yet. Developing a non-invasive model to predict the differentiation grade of CRC is of great value. AIM: To develop and validate machine learning-based models for predicting the differentiation grade of CRC based on T2-weighted images (T2WI). METHODS: We retrospectively collected the preoperative imaging and clinical data of 315 patients with CRC who underwent surgery from March 2018 to July 2023. Patients were randomly assigned to a training cohort (n = 220) or a validation cohort (n = 95) at a 7:3 ratio. Lesions were delineated layer by layer on high-resolution T2WI. Least absolute shrinkage and selection operator regression was applied to screen for radiomic features. Radiomics and clinical models were constructed using the multilayer perceptron (MLP) algorithm. These radiomic features and clinically relevant variables (selected based on a significance level of P < 0.05 in the training set) were used to construct radiomics-clinical models. The performance of the three models (clinical, radiomic, and radiomic-clinical model) were evaluated using the area under the curve (AUC), calibration curve and decision curve analysis (DCA). RESULTS: After feature selection, eight radiomic features were retained from the initial 1781 features to construct the radiomic model. Eight different classifiers, including logistic regression, support vector machine, k-nearest neighbours, random forest, extreme trees, extreme gradient boosting, light gradient boosting machine, and MLP, were used to construct the model, with MLP demonstrating the best diagnostic performance. The AUC of the radiomic-clinical model was 0.862 (95%CI: 0.796-0.927) in the training cohort and 0.761 (95%CI: 0.635-0.887) in the validation cohort. The AUC for the radiomic model was 0.796 (95%CI: 0.723-0.869) in the training cohort and 0.735 (95%CI: 0.604-0.866) in the validation cohort. The clinical model achieved an AUC of 0.751 (95%CI: 0.661-0.842) in the training cohort and 0.676 (95%CI: 0.525-0.827) in the validation cohort. All three models demonstrated good accuracy. In the training cohort, the AUC of the radiomic-clinical model was significantly greater than that of the clinical model (P = 0.005) and the radiomic model (P = 0.016). DCA confirmed the clinical practicality of incorporating radiomic features into the diagnostic process. CONCLUSION: In this study, we successfully developed and validated a T2WI-based machine learning model as an auxiliary tool for the preoperative differentiation between well/moderately and poorly differentiated CRC. This novel approach may assist clinicians in personalizing treatment strategies for patients and improving treatment efficacy.

Construction of an immune-related gene signature for overall survival prediction and immune infiltration in gastric cancer.

BACKGROUND: Treatment options for patients with gastric cancer (GC) continue to improve, but the overall prognosis is poor. The use of PD-1 inhibitors has also brought benefits to patients with advanced GC and has gradually become the new standard treatment option at present, and there is an urgent need to identify valuable biomarkers to classify patients with different characteristics into subgroups. AIM: To determined the effects of differentially expressed immune-related genes (DEIRGs) on the development, prognosis, tumor microenvironment (TME), and treatment response among GC patients with the expectation of providing new biomarkers for personalized treatment of GC populations. METHODS: Gene expression data and clinical pathologic information were downloaded from The Cancer Genome Atlas (TCGA), and immune-related genes (IRGs) were searched from ImmPort. DEIRGs were extracted from the intersection of the differentially-expressed genes (DEGs) and IRGs lists. The enrichment pathways of key genes were obtained by analyzing the Kyoto Encyclopedia of Genes and Genomes (KEGGs) and Gene Ontology (GO) databases. To identify genes associated with prognosis, a tumor risk score model based on DEIRGs was constructed using Least Absolute Shrinkage and Selection Operator and multivariate Cox regression. The tumor risk score was divided into high- and low-risk groups. The entire cohort was randomly divided into a 2:1 training cohort and a test cohort for internal validation to assess the feasibility of the risk model. The infiltration of immune cells was obtained using 'CIBERSORT,' and the infiltration of immune subgroups in high- and low-risk groups was analyzed. The GC immune score data were obtained and the difference in immune scores between the two groups was analyzed. RESULTS: We collected 412 GC and 36 adjacent tissue samples, and identified 3627 DEGs and 1311 IRGs. A total of 482 DEIRGs were obtained. GO analysis showed that DEIRGs were mainly distributed in immunoglobulin complexes, receptor ligand activity, and signaling receptor activators. KEGG pathway analysis showed that the top three DEIRGs enrichment types were cytokine-cytokine receptors, neuroactive ligand receptor interactions, and viral protein interactions. We ultimately obtained an immune-related signature based on 10 genes, including 9 risk genes (LCN1, LEAP2, TMSB15A mRNA, DEFB126, PI15, IGHD3-16, IGLV3-22, CGB5, and GLP2R) and 1 protective gene (LGR6). Kaplan-Meier survival analysis, receiver operating characteristic curve analysis, and risk curves confirmed that the risk model had good predictive ability. Multivariate COX analysis showed that age, stage, and risk score were independent prognostic factors for patients with GC. Meanwhile, patients in the low-risk group had higher tumor mutation burden and immunophenotype, which can be used to predict the immune checkpoint inhibitor response. Both cytotoxic T lymphocyte antigen4+ and programmed death 1+ patients with lower risk scores were more sensitive to immunotherapy. CONCLUSION: In this study a new prognostic model consisting of 10 DEIRGs was constructed based on the TME. By providing risk factor analysis and prognostic information, our risk model can provide new directions for immunotherapy in GC patients.

Carbon dots with enhanced red emission for ratiometric sensing and encryption applications.

The excitation-dependent emission properties of carbon dots (Cdots) are extensively reported, but their red emission is often weak, limiting their wider application. Here we introduce ethidium bromide, as a functional precursor with red emission, to enhance the red emission for Cdots, with comparable intensity at a broad wavelength range to multi-emission Cdots (M-Cdots). We found that Cdots prepared with ethidium bromide/ethylenediamine exhibited strong blue and red emission at 440 and 615 nm, with optimal excitation at 360 and 470 nm as M-Cdots, respectively, but the Cdots from single ethidium bromide (EB-Cdots) possessed weak red emission. M-Cdots exhibited a broad absorption band at 478 nm, but a band blue-shifted to 425 nm was observed for EB-Cdots, while no absorption was observed at 478-425 nm for the Cdots prepared with citric acid and ethylenediamine. Thus, we proposed that C=O and C=N formed a π-conjugation structure as the absorption band at 478 nm for the red emission of M-Cdots, as also confirmed with the excitation at 470 nm. Moreover, the π-conjugation structure is fragile and sensitive to harsh conditions, so red emission was difficult to observe for the Cdots prepared with citric acid/ethylenediamine or single ethidium bromide. M-Cdots possess two centers for blue and red emission with different structures. The dual emission was therefore used for ratiometric sensing with dichromate (Cr2O72-) and formaldehyde (HCHO) as the targets using the intensity ratio of the emissions at 615 and 440 nm. Due to the comparable intensity at a broad wavelength range, we designed encryption codes with five excitations at 360, 400, 420, 450, and 470 nm as the inputs, and the emission colors were used for information decoding. Thus, we determined why red emission was difficult to realize for Cdots, and our results could motivate the design of red-emission Cdots for extensive applications.

Engineering Phage Nanocarriers Integrated with Bio-Intelligent Plasmids for Personalized and Tunable Enzyme Delivery to Enhance Chemodynamic Therapy.

Customizable and number-tunable enzyme delivery nanocarriers will be useful in tumor therapy. Herein, a phage vehicle, T4-Lox-DNA-Fe (TLDF), which adeptly modulates enzyme numbers using phage display technology to remodel the tumor microenvironment (TME) is presented. Regarding the demand for lactic acid in tumors, each phage is engineered to display 720 lactate oxidase (Lox), contributing to the depletion of lactic acid to restructure the tumor's energy metabolism. The phage vehicle incorporated dextran iron (Fe) with Fenton reaction capabilities. H2O2 is generated through the Lox catalytic reaction, amplifying the H2O2 supply for dextran iron-based chemodynamic therapy (CDT). Drawing inspiration from the erythropoietin (EPO) biosynthetic process, an EPO enhancer is constructed to impart the EPO-Keap1 plasmid (DNA) with tumor hypoxia-activated functionality, disrupting the redox homeostasis of the TME. Lox consumes local oxygen, and positive feedback between the Lox and the plasmid promotes the expression of kelch ECH Associated Protein 1 (Keap1). Consequently, the downregulation of the antioxidant transcription factor Nrf2, in synergy with CDT, amplifies the oxidative killing effect, leading to tumor suppression of up to 78%. This study seamlessly integrates adaptable T4 phage vehicles with bio-intelligent plasmids, presenting a promising approach for tumor therapy.

Palladium-catalyzed three-component radical-polar crossover carboamination of 1,3-dienes or allenes with diazo esters and amines.

Herein, we report a visible-light-mediated palladium-catalyzed three-component radical-polar crossover carboamination of 1,3-dienes or allenes with diazo esters and amines, affording unsaturated γ- and ε-amino acid derivatives with diverse structures. In this methodology, the diazo compound readily transforms into a hybrid α-ester alkylpalladium radical with the release of dinitrogen. The radical intermediate selectively adds to the double bond of a 1,3-diene or allene, followed by the allylpalladium radical-polar crossover path and selective allylic substitution with the amine substrate, thereby leading to a single unsaturated γ- or ε-amino acid derivative. This approach proceeds under mild and simple reaction conditions and shows high functional group tolerance, especially in the incorporation of various bioactive molecules. The studies on scale-up reactions and diverse derivatizations highlight the practical utility of this multicomponent reaction protocol.