New insights into starch, lipid, and protein interactions - Colon microbiota fermentation.

Starch, lipids, and proteins are essential biological macromolecules that play a crucial role in providing energy and nutrition to our bodies. Interactions between these macromolecules have been shown to impact starch digestibility. Understanding and controlling starch digestibility is a key area of research. Investigating the mechanisms behind the interactions of these three components and their influence on starch digestibility is of significant practical importance. Moreover, these interactions can result in the formation of resistant starch, which can be fermented by gut microbiota in the colon, leading to various health benefits. While current research has predominantly focused on the digestive properties of starch in the small intestine, there is a notable gap in understanding the colonic microbial fermentation phase of resistant starch. The benefits of fermentation of resistant starch in the colon may outweigh its glucose-lowering effect in the small intestine. Thus, it is crucial to study the fermentation behavior of resistant starch in the colon. This paper investigates the impact of interactions among starch, lipids, and proteins on starch digestion, with a specific focus on the fermentation phase of indigestible carbohydrates in the colon. Furthermore, valuable insights are offered for guiding future research endeavors.

Two new species of the mealybug genus Paracoccus from Jiangxi, South China (Hemiptera, Coccomorpha, Pseudococcidae).

Two new mealybug species, Paracoccusgillianwatsonae Zhang, sp. nov. and P.wui Zhang, sp. nov., collected from Jiangxi, South China, are described and illustrated based on the morphology of adult females. Paracoccusgillianwatsonae is similar to P.burnerae (Brain, 1915), but it differs in having fewer pairs of cerarii, and in lacking both ventral oral collar tubular ducts on the margins of the head and translucent pores on the hind femur. Paracoccuswui resembles P.keralae Williams, 2004 and P.neocarens (Lit, 1992), but it differs in lacking ventral oral collar tubular ducts on the margins of the head and in having multilocular disc-pores usually in double rows at the posterior edges of abdominal segments V and VI. A key to the Paracoccus species found in China is provided.

Traditional Chinese Medicine in Regulating Tumor Microenvironment.

Tumor microenvironment (TME) is a complex and integrated system containing a variety of tumor-infiltrating immune cells and stromal cells. They are closely connected with cancer cells and influence the development and progression of cancer. Traditional Chinese medicine (TCM) is an important complementary therapy for cancer treatment in China. It mainly eliminates cancer cells by regulating TME. The aim of this review is to systematically summarize the crosstalk between tumor cells and TME, and to summarize the research progress of TCM in regulating TME. The review is of great significance in revealing the therapeutic mechanism of action of TCM, and provides an opportunity for the combined application of TCM and immunotherapy in cancer treatment.

Association of Retinal Neurovascular Impairment with Disease Severity in Patients with Major Depressive Disorder: An Optical Coherence Tomography Angiography Study.

Background: Identifying the fundus objective biomarkers for the major depressive disorders (MDD) may help promote mental health. The aim of this study was to evaluate retinal neurovascular changes and further investigate their association with disease severity in MDD. Methods: This cross-sectional study conducted in the hospital enrolled patients with MDD and healthy controls.The retinal neurovascular parameters for all subjects, including vessel density (VD), thickness of ganglion cell complex (GCC) and retinal nerve fiber layer (RNFL), and optic nerve head (ONH) eg are automatically calculated by the software in optical coherence tomography angiography (OCTA). The severity of MDD including depressive symptoms, anxiety, cognition, and insomnia was assessed by Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Scale (HAMA), Montreal Cognitive Assessment (MoCA), and Insomnia Severity Index (ISI) respectively. Results: This study included 74 MDD patients (n=74 eyes) and 60 healthy controls (HCs) (n=60 eyes). MDD patients showed significantly decreased VD of superficial and deep capillary plexus, thickness of GCC and RNFL, and volume of ONH (all p<0.05) and increased vertical cup-to-disc ratio and global loss volume (GLV) (all p<0.05) compared to HCs. Positive associations were found between HAMD scores and cup area (r=0.30, p=0.035), cup volume (r=0.31, p=0.029), and disc area (r=0.33, p=0.020) as well as ISI scores and RNFL thickness (r=0.34, p=0.047). Conclusion: We found the retinal neurovascular impairment and its association with disease severity in MDD patients. OCTA showed promise as a potential complementary assessment tool for MDD.

A comparison of machine learning methods for radiomics modeling in prediction of occult lymph node metastasis in clinical stage IA lung adenocarcinoma patients.

Background: Accurate prediction of occult lymph node metastasis (ONM) is an important basis for determining whether lymph node (LN) dissection is necessary in clinical stage IA lung adenocarcinoma patients. The aim of this study is to determine the best machine learning algorithm for radiomics modeling and to compare the performances of the radiomics model, the clinical-radilogical model and the combined model incorporate both radiomics features and clinical-radilogical features in preoperatively predicting ONM in clinical stage IA lung adenocarcinoma patients. Methods: Patients with clinical stage IA lung adenocarcinoma undergoing curative surgery from one institution were retrospectively recruited and assigned to training and test cohorts. Radiomics features were extracted from the preoperative computed tomography (CT) images of the primary tumor. Seven machine learning algorithms were used to construct radiomics models, and the model with the best performance, evaluated using the area under the curve (AUC), was selected. Univariate and multivariate logistic regression analyses were performed on the clinical-radiological features to identify statistically significant features and to develop a clinical model. The optimal radiomics and clinical models were integrated to build a combined model, and its predictive performance was assessed using receiver operating characteristic curves, Brier score, and decision curve analysis (DCA). Results: This study included 258 patients who underwent resection (training cohort, n=182; test cohort, n=76). Six radiomics features were identified. Among the seven machine learning algorithms, extreme gradient boosting (XGB) demonstrated the highest performance for radiomics modeling, with an AUC of 0.917. The combined model improved the AUC to 0.933 and achieved a Brier score of 0.092. DCA revealed that the combined model had optimal clinical efficacy. Conclusions: The superior performance of the combined model, based on XGB algorithm in predicting ONM in patients with clinical stage IA lung adenocarcinoma, might aid surgeons in deciding whether to conduct mediastinal LN dissection and contribute to improve patients' prognosis.

Establishment and verification of a prediction model based on clinical characteristics and computed tomography radiomics parameters for distinguishing benign and malignant pulmonary nodules.

Background: The radiographic classification of pulmonary nodules into benign versus malignant categories is a pivotal component of early lung cancer diagnosis. The present study aimed to investigate clinical and computed tomography (CT) clinical-radiomics nomogram for preoperative differentiation of benign and malignant pulmonary nodules. Methods: This retrospective study included 342 patients with pulmonary nodules who underwent high-resolution CT (HRCT) examination. We assigned them to a training dataset (n=239) and a validation dataset (n=103). There are 1781 tumor characteristics quantified by extracted features from the lesion segmented from patients' CT images. The features with poor reproducibility and high redundancy were removed. Then a least absolute shrinkage and selection operator (LASSO) logistic regression model with 10-fold cross-validation was used to further select features and build radiomics signatures. The independent predictive factors were identified by multivariate logistic regression. A radiomics nomogram was developed to predict the malignant probability. The performance and clinical utility of the clinical-radiomics nomogram was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: After dimension reduction by the LASSO algorithm and multivariate logistic regression, four radiomic features were selected, including original_shape_Sphericity, exponential_glcm_Maximum Probability, log_sigma_2_0_mm_3D_glcm_Maximum Probability, and ogarithm_firstorder_90Percentile. Multivariate logistic regression showed that carcinoembryonic antigen (CEA) [odds ratio (OR) 95% confidence interval (CI): 1.40 (1.09-1.88)], CT rad score [OR (95% CI): 2.74 (2.03-3.85)], and cytokeratin-19-fragment (CYFRA21-1) [OR (95% CI): 1.80 (1.14-2.94)] were independent influencing factors of malignant pulmonary nodule (all P<0.05). The clinical-radiomics nomogram combining CEA, CYFRA21-1 and radiomics features achieved an area of curve (AUC) of 0.85 and 0.76 in the training group and verification group for the prediction of malignant pulmonary nodules. The clinical-radiomics nomogram demonstrated excellent agreement and practicality, as evidenced by the calibration curve and DCA. Conclusions: The clinical-radiomics nomogram combined of CT-based radiomics signature, along with CYFRA21-1 and CEA, demonstrated strong predictive ability, calibration, and clinical usefulness in distinguishing between benign and malignant pulmonary nodules. The use of CT-based radiomics has the potential to assist clinicians in making informed decisions prior to biopsy or surgery while avoiding unnecessary treatment for non-cancerous lesions.

Constructing and validating a risk model based on neutrophil-related genes for evaluating prognosis and guiding immunotherapy in colon cancer.

BACKGROUND: Colon cancer is one of the most common digestive tract malignancies. Although immunotherapy has brought new hope to colon cancer patients, there is still a large proportion of patients who do not benefit from immunotherapy. Studies have shown that neutrophils can interact with immune cells and immune factors to affect the prognosis of patients. METHODS: We first determined the infiltration level of neutrophils in tumors using the CIBERSORT algorithm and identified key genes in the final risk model by Spearman correlation analysis and subsequent Cox analysis. The risk score of each patient was obtained by multiplying the Cox regression coefficient and the gene expression level, and patients were divided into two groups based on the median of risk score. Differences in overall survival (OS) and progression-free survival (PFS) were assessed by Kaplan-Meier survival analysis, and model accuracy was validated in independent dataset. Differences in immune infiltration and immunotherapy were evaluated by immunoassay. Finally, immunohistochemistry and western blotting were performed to verify the expression of the three genes in the colon normal and tumor tissues. RESULTS: We established and validated a risk scoring model based on neutrophil-related genes in two independent datasets, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, with SLC11A1 and SLC2A3 as risk factors and MMP3 as a protective factor. A new nomogram was constructed and validated by combining clinical characteristics and the risk score model to better predict patients OS and PFS. Immune analysis showed that patients in the high-risk group had immune cell infiltration level, immune checkpoint level and tumor mutational burden, and were more likely to benefit from immunotherapy. CONCLUSIONS: The low-risk group showed better OS and PFS than the high-risk group in the neutrophil-related gene-based risk model. Patients in the high-risk group presented higher immune infiltration levels and tumor mutational burden and thus may be more responsive to immunotherapy.

Assessment and factors affecting quality of life among patients with Wilson's disease.

Wilson's disease is caused by abnormal copper metabolism resulting in deposition in various organs, including the brain, liver, and cornea, thus disrupting organ function. It is characterized by encephalopathy, extrapyramidal symptoms, progressive liver failure, and copper ring deposition in the cornea. Management of this disease should include quality of life maintenance; however, relevant studies on this topic are lacking. This study aimed to assess the factors affecting the quality of life (QoL) of patients with Wilson's disease. A cross-sectional survey using convenience sampling was conducted between July 2020 and March 2021 at the hospital. Data on patient characteristics, 36-item Short-Form General Health Survey, Uniform Wilson Disease Rating Scale, and Hamilton Depression Rating Scale scores were collected. Associations among quality of life depression, anxiety, and Wilson's disease progression were examined using Pearson correlation analysis. Factors affecting the quality of life of patients, including depression, anxiety, liver function, clinical symptoms, diet, liver function, brain magnetic resonance imaging (MRI) findings, disease duration, Barthel Index, and Morse scores were examined using multivariate linear regression analysis. This study included 134 patients with Wilson's disease whose mean age was 29.12 ± 8.59 years. The mean QoL score in the patient group was 71.38 ± 9.55 points and was negatively correlated with anxiety (r = - 0.883, P = 0.000), depression (r = - 0.852 P = 0.000), and clinical symptoms (r = - 0.542, P = 0.000) scores. Anxiety, depression, and clinical symptoms severity are vital factors for the QoL of patients with Wilson's disease. The study provides foundational evidence to design novel interventions, including symptom management, diet, and self-care ability, which can help in improving the quality of life in patients with Wilson's disease and decreasing the burden associated with this disease.

Multivariate analyses on male factors and construction of a nomogram for predicting low in vitro fertilization rate.

Low fertilization rate (LFR) and total fertilization failure (TFF) are often encountered in routine in vitro fertilization (IVF) procedure. To solve this problem, multivariate analyses on the relationship between male factors and in vitro fertilization rate were performed, and a nomogram for prediction of LFR was constructed. This retrospective study contained 2011 couples who received IVF treatment from January 2017 to December 2021. Man factors and in vitro fertilization rate were collected. Among these couples, 1347 cases had in vitro fertilization rates ≥30 % (control group), and 664 cases had in vitro fertilization rates <30 % (LFR group). Univariate analyses of male factors found that between the two groups there were significant differences (p < 0.05) in sperm progressive motility (SPR), sperm concentration (SC), total sperm number, normal sperm morphology rate (NSMR), DNA fragmentation index (DFI), sperm acrosin activity (SAA) and the clinical diagnosis of primary or secondary infertility. Multivariate logistic regression analyses showed that SPR, SAA, and SC were independent risk factors for LFR. An algorithm and a correspondent nomogram for predicting high LFR risk were constructed using data from the training cohort. The LFR nomogram exhibited an excellent discrimination power and a high fitting degree in both the training cohort (AUC = 0.90, 95 % CI: 0.88-0.92), (H-L: x2 = 5.43, p = 0.71) and validation cohort (AUC = 0.89, 95 % CI:0.87-0.92), (H-L: x2 = 7.85, p = 0.45), respectively. The decision curve analysis (DCA) demonstrated a high efficiency of the LFR nomogram for clinical utility. SPR, SAA, and SC are independent risk factors for LFR. The LFR nomogram established based on these factors could be a useful tool to predict high risk of LFR, and patients with high risk of LFR can be guided to direct ICSI procedure. Clinical application of the LFR nomogram may increase the in vitro fertilization rate by facilitating the decision making in IVF service.

Green natural capital, the environmental Kuznets curve and development financing in the Global South.

This study investigates the nexus between carbon dioxide emissions, economic development, and development finance in seeking an empirical answer to the conundrum at the intersection of development and environmental economics. Employing a theoretical framework that incorporates three dimensions of endowments, the real economy, and the financial sector, our empirical model accounts for the bi-directional causality of environmental degradation and economic growth in the Global South by adopting the simultaneous equations model. Our results confirm an inverted N-shaped environment Kuznets curve which is statistically significant and robust, and consistent with the conceptualized theoretical framework. The results provide insights to enhance the effectiveness of future development finance and policy design by promoting sustainable growth and green transformation through facilitating renewable energy adoption, investing in human capital, and preserving renewable natural capital.

[Spatio-temporal Variation in NEP in Ecological Zoning on the Loess Plateau and Its Driving Factors from 2000 to 2021].

Net ecosystem productivity (NEP) is an important index for the quantitative evaluation of carbon sources and sinks in terrestrial ecosystems. Based on MOD17A3 and meteorological data, the vegetation NEP was estimated from 2000 to 2021 in the Loess Plateau (LP) and its six ecological subregions of the LP (loess sorghum gully subregions:A1, A2; loess hilly and gully subregions:B1, B2; sandy land and agricultural irrigation subregion:C; and earth-rock mountain and river valley plain subregion:D). Combined with the terrain, remote sensing, and human activity data, Theil-Sen Median trend analysis, correlation analysis, multiple regression residual analysis, and geographic detector were used, respectively, to explore the spatio-temporal characteristics of NEP and its response mechanism to climate, terrain, and human activity. The results showed that:① On the temporal scale, from 2000 to 2021 the annual mean NEP of the LP region (in terms of C) was 104.62 g·(m2·a)-1. The annual mean NEP for both the whole LP and each of the ecological subregions showed a significant increase trend, and the NEP of the LP increased by 6.10 g·(m2·a)-1 during the study period. The highest growth rate of the NEP was 9.04 g·(m2·a)-1, occurring in the A2 subregion of the loess sorghum gully subregions. The subregion C had the lowest growth rate of 2.74 g·(m2·a)-1. Except for the C subregion, all other ecological subregions (A1, A2, B1, B2, and D) were carbon sinks. ② On the spatial scale, the spatial distribution of annual NEP on the LP was significantly different, with the higher NEP distribution in the southeast of the LP and the lower in the northwest of the LP. The high carbon sink area was mainly distributed in the southern part of the loess sorghum gully subregions, and the carbon source area was mainly distributed in the northern part of the loess sorghum gully subregions and most of the C subregion. The high growth rate was mainly distributed in the central and the southern part of the A2 subregion and the southwest part of the B2 subregion. ③ Human activities had the greatest influence on the temporal variation in NEP in the LP and all the ecological subregions, with the correlation coefficient between human activity data and NEP being above 0.80, and the relative contribution rates of human factors was greater than 50%. The spatial distribution was greatly affected by meteorological factors, among which the precipitation and solar radiation were the main factors affecting the spatial changes in the NEP of the LP. The temporal and spatial variations in the NEP in the LP were influenced by natural and human social factors. To some extent, these results can provide a reference for the terrestrial ecosystem in the LP to reduce emissions and increase sinks and to achieve the goal of double carbon.

The association between flavonoids intake and hypertension in U.S. adults: A cross-sectional study from The National Health and Nutrition Examination Survey.

Although in vitro experiments have demonstrated the potential of flavonoid compounds in regulating blood pressure, there is still a lack of evidence from large population studies. We conducted a cross-sectional study using the National Health and Nutrition Examination Survey to investigate the relationship between flavonoid intake levels (natural log transformation) and hypertension events. A total of 15 752 participants aged over 20 years were included, and a weighted multivariable logistic regression analysis was performed to explore the relationship between total flavonoids, five sub types intake, and hypertension events. Smooth curve fitting was used to explore potential nonlinear relationships. Higher total flavonoids intake was associated with a lower risk of hypertension than the lowest group. The adjusted odds ratios (95% CIs) were 0.79 (0.70-0.88) for total flavonoids intake. Elevated total flavonoids intake levels were significantly and linearly associated with a lower risk of hypertension. For each unit increase in the total flavonoids intake level, the adjusted ORs for risk of hypertension decrease by 5% (OR 0.95; 95% CI, 0.92-0.98). In addition, in restricted cubic spline regression, we found that flavan-3-ols, anthocyanidins, and flavonols intake were linearly and negatively related to prevalence of hypertension. Flavones intake showed nonlinear associations with prevalence of hypertension with inflection points of -1.90. Within a certain range, a negative correlation exists between flavonoids intake and hypertension events. This finding provides insights into dietary modifications in the prevention of hypertension.

Unveiling novel anti-viral mechanisms of ε-poly-l-lysine on tobacco mosaic virus-infected Nicotiana tabacum through microRNA and transcriptome sequencing.

MicroRNAs (miRNAs) play important roles in plant defense against various pathogens. ε-poly-l-lysine (ε-PL), a natural anti-microbial peptide produced by microorganisms, effectively suppresses tobacco mosaic virus (TMV) infection. To investigate the anti-viral mechanism of ε-PL, the expression profiles of miRNAs in TMV-infected Nicotiana tabacum after ε-PL treatment were analyzed. The results showed that the expression levels of 328 miRNAs were significantly altered by ε-PL. Degradome sequencing was used to identify their target genes. Integrative analysis of miRNAs target genes and gene-enriched GO/KEGG pathways indicated that ε-PL regulates the expression of miRNAs involved in critical pathways of plant hormone signal transduction, host defense response, and plant pathogen interaction. Subsequently, virus induced gene silencing combined with the short tandem targets mimic technology was used to analyze the function of these miRNAs and their target genes. The results indicated that silencing miR319 and miR164 reduced TMV accumulation in N. benthamiana, indicating the essential roles of these miRNAs and their target genes during ε-PL-mediated anti-viral responses. Collectively, this study reveals that microbial source metabolites can inhibit plant viruses by regulating crucial host miRNAs and further elucidate anti-viral mechanisms of ε-PL.

Cu-II-directed self-assembly of fullerenols to ameliorate copper stress in maize seedlings.

Widespread use of copper-based agrochemical may cause copper excessive accumulation in agricultural soil to seriously threaten crop production. Recently, fullerenols are playing important roles in helping crops build resistance to abiotic stresses by giving ingenious and successful resolutions. However, there is a lack of knowledge on their beneficial effects in crops under stresses induced by heavy metals. Herein, the visual observation of Cu2+-mediated assembly of fullerenols via electrostatic and coordination actions was carried out in vitro, showing that water-soluble nanocomplexes and water-insoluble cross-linking nanohybrids were selectively fabricated by precisely adjusting feeding ratios of fullerenols and CuSO4. Furthermore, maize simultaneous exposure of fullerenols and CuSO4 solutions was tested to investigate the comparative effects of seed germination and seedling growth relative to exposure of CuSO4 alone. Under moderate Cu2+ stresses (40 and 80 µM), fullerenols significantly mitigated the detrimental effects of seedlings, including phenotype, root and shoot elongation, biomass accumulation, antioxidant capacity, and Cu2+ uptake and copper transporter-related gene expressions in roots. Under 160 µM of Cu2+ as a stressor, fullerenols also accelerated germination of Cu2+-stressed seeds eventually up to the level of the control. Summarily, fullerenols can enhance tolerance of Cu2+-stressed maize mainly due to direct detoxification through fullerenol-Cu2+ interactions restraining the Cu2+ intake into roots and reducing free Cu2+ content in vivo, as well as fullerenol-maize interactions to enhance resistance by maintaining balance of reactive oxygen species and optimizing the excretion and transport of Cu2+. This will unveil valuable insights into the beneficial roles of fullerenols and its mechanism mode in alleviating heavy metal stress on crop plants.

Clinical Characteristics, Treatment, and Prognosis of Osteoarticular Brucellosis: A Retrospective Real-World Study in Shenyang, China, 2014-2019.

This study aimed to assess the clinical characteristics, treatment, and prognosis of osteoarticular brucellosis. We conducted a retrospective study enrolling brucellosis patients from the Sixth People's Hospital of Shenyang between September 2014 and June 2019. A total of 1917 participants were admitted during this period. After applying propensity score matching, we retrospectively analyzed 429 patients with osteoarthritis and 429 patients without osteoarthritis. The primary outcome was treatment completion. The secondary outcome was symptom disappearance and seroconversion. Brucellosis patients with osteoarthritis had longer treatment course (160 [134.3-185.7] vs. 120 [102.3-137.7] d, p = 0.008) than those without osteoarthritis. The most common involved site was lumbar vertebrae (290 [67.6%]) in brucellosis patients with osteoarthritis. Longer symptom duration (90 [83.0-97.0] vs. 42 [40.2-43.8], p < 0.001) along with no significant difference in seroconversion (180 [178.8-181.2] vs. 180 [135.1-224.9], p = 0.212) was observed in osteoarthritis patients with treatment course >90 d. Peripheral joint involvement (adjusted hazard ratio [95% confidence interval] 1.485 [1.103-1.999]; p = 0.009) had a shorter symptom duration compared with shaft joint involvement. No significant differences were observed in treatment therapy between doxycycline plus rifampin (DR) or plus cephalosporins (DRC) in treatment course (p = 0.190), symptom persistence (p = 0.294), and seroconversion (p = 0.086). Lumbar vertebra was the most commonly involved site. Even if all symptoms disappeared, Serum agglutination test potentially remained positive in some patients. Compared with peripheral arthritis, shaft arthritis was the high-risk factor for longer symptom duration. The therapeutic effects were similar between DR and DRC. In summary, our study provided important insights into the clinical characteristics, treatment, and outcomes of osteoarticular brucellosis. Clinical Trial Registration number: NCT04020536.

Analyte-perturbed balance between reducibility and fluorescence of Ti3C2 MXene quantum dots for label-free, dual-mode detection of silver ions.

BACKGROUND: As an emerging and attractive low-dimensional functional materials, Ti3C2 MXene quantum dots (QDs) enlarge the toolbox of fluorescence sensing. However, monochromatic fluorescence, which only provide one single signal, is often beset by challenges such as false-positive readouts and limitations in selectivity. Consequently, to improve the sensing accuracy by means of cross-verified dual-signal authentication, the endeavor to engineer dual-mode nanoprobes based on Ti3C2 QDs, incorporating both the capability of fluorescence and an alternative sensing mechanism, emerges as a compelling avenue. RESULTS: Here, based on the alterations in colorimetric and fluorescent signals of Ti3C2 QDs with the addition of Ag+, we propose a dual-mode sensor obviating the necessity for nanoprobe labeling. Owing to the decent reducibility of Ti3C2 QDs, Ag+ is adsorbed and reduced, resulting in the generation of plasmonic Ag nanoparticles (NPs), which simultaneously trigger colorimetric responses of the solution and enhance the fluorescent emission of Ti3C2 QDs. The confluence of colorimetry and fluorometry within this strategy optimally harnesses the modulating role of the acquired Ag NPs on the reducing capability and fluorescence characteristics of Ti3C2 QDs. The equilibrium imparts versatility and promising prospects to this analyte-triggered label-free method, which enables a remarkable specificity and an excellent detecting limit (0.45 µM) for Ag+. SIGNIFICANCE: The balance between reducibility and fluorescence of Ti3C2 QDs for dual-mode detection is inventively demonstrated. With the exemplification of a direct influence of both features of the nanoprobe via the introduction of analytes, this study opens the feasibility of the analyte-perturbed felicitous equilibrium, which endows label-free methods with versatility and promising prospects. This design may evoke more biosensing strategies with the function of double-signal mutual verification.

Novel STAT3 oligonucleotide compounds suppress tumor growth and overcome the acquired resistance to sorafenib in hepatocellular carcinoma.

Signal transducer and activator of transcription 3 (STAT3) plays an important role in the occurrence and progression of tumors, leading to resistance and poor prognosis. Activation of STAT3 signaling is frequently detected in hepatocellular carcinoma (HCC), but potent and less toxic STAT3 inhibitors have not been discovered. Here, based on antisense technology, we designed a series of stabilized modified antisense oligonucleotides targeting STAT3 mRNA (STAT3 ASOs). Treatment with STAT3 ASOs decreased the STAT3 mRNA and protein levels in HCC cells. STAT3 ASOs significantly inhibited the proliferation, survival, migration, and invasion of cancer cells by specifically perturbing STAT3 signaling. Treatment with STAT3 ASOs decreased the tumor burden in an HCC xenograft model. Moreover, aberrant STAT3 signaling activation is one of multiple signaling pathways involved in sorafenib resistance in HCC. STAT3 ASOs effectively sensitized resistant HCC cell lines to sorafenib in vitro and improved the inhibitory potency of sorafenib in a resistant HCC xenograft model. The developed STAT3 ASOs enrich the tools capable of targeting STAT3 and modulating STAT3 activity, serve as a promising strategy for treating HCC and other STAT3-addicted tumors, and alleviate the acquired resistance to sorafenib in HCC patients. A series of novel STAT3 antisense oligonucleotide were designed and showed potent anti-cancer efficacy in hepatocellular carcinoma in vitro and in vivo by targeting STAT3 signaling. Moreover, the selected STAT3 ASOs enhance sorafenib sensitivity in resistant cell model and xenograft model.

Comprehensive assessment of copper's effect on marine organisms under ocean acidification and warming in the 21st century.

Copper (Cu) has sparked widespread global concern as one of the most hazardous metals to aquatic animals. Ocean acidification (OA) and warming (OW) are expected to alter copper's bioavailability based on pH and temperature-sensitive effects; research on their effects on copper on marine organisms is still in its infancy. Therefore, under representative concentration pathways (RCP) 2.6, 4.5, and 8.5, we used the multiple linear regression-water quality criteria (MLR-WQC) method to assess the effects of OA and OW on the ecological risk posed by copper in the Ocean of East China (OEC), which includes the Bohai Sea, Yellow Sea, and East China Sea. The results showed that there was a positive correlation between temperature and copper toxicity, while there was a negative correlation between pH and copper toxicity. The short-term water quality criteria (WQC) values were 1.53, 1.41, 1.30 and 1.13 µg·L-1, while the long-term WQC values were 0.58, 0.48, 0.40 and 0.29 µg·L-1 for 2020, 2099-RCP2.6, 2099-RCP4.5 and 2099-RCP8.5, respectively. Cu in the OEC poses a moderate ecological risk. Under the current copper exposure situation, strict intervention (RCP2.6) only increases the ecological risk of copper exposure by 20 %, and no intervention (RCP8.5) will increase the ecological risk of copper exposure by nearly double. The results indicate that intervention on carbon emissions can slow down the rate at which OA and OW worsen the damage copper poses to marine creatures. This study can provide valuable information for a comprehensive understanding of the combined impacts of climate change and copper on marine organisms.