An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth.

Introduction: As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. Methods: This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Results and discussion: Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.

Oral enzyme-responsive nanoprobes for targeted theranostics of inflammatory bowel disease.

BACKGROUND: Inflammatory bowel disease (IBD) is a progressive and debilitating inflammatory disease of the gastrointestinal tract (GIT). Despite recent advances, precise treatment and noninvasive monitoring remain challenging. METHODS: Herein, we developed orally-administered, colitis-targeting and hyaluronic acid (HA)-modified, core-shell curcumin (Cur)- and cerium oxide (CeO2)-loaded nanoprobes (Cur@PC-HA/CeO2 NPs) for computed tomography (CT) imaging-guided treatment and monitoring of IBD in living mice. RESULTS: Following oral administration, high-molecular-weight HA maintains integrity with little absorption in the upper GIT, and then actively accumulates at local colitis sites owing to its colitis-targeting ability, leading to specific CT enhancement lasting for 24 h. The retained NPs are further degraded by hyaluronidase in the colon to release Cur and CeO2, thereby exerting anti-inflammatory and antioxidant effects. Combined with the ability of NPs to regulate intestinal flora, the oral NPs result in substantial relief in symptoms. Following multiple treatments, the gradually decreasing range of the colon with high CT attenuation correlates with the change in the clinical biomarkers, indicating the feasibility of treatment response and remission. CONCLUSION: This study provides a proof-of-concept for the design of a novel theranostic integration strategy for concomitant IBD treatment and the real-time monitoring of treatment responses.

An advanced three-dimensional phenotypic measurement approach for extracting Ginkgo root structural parameters based on terrestrial laser scanning.

The phenotyping of plant roots is essential for improving plant productivity and adaptation. However, traditional techniques for assembling root phenotyping information are limited and often labor-intensive, especially for woody plants. In this study, an advanced approach called accurate and detailed quantitative structure model-based (AdQSM-based) root phenotypic measurement (ARPM) was developed to automatically extract phenotypes from Ginkgo tree root systems. The approach involves three-dimensional (3D) reconstruction of the point cloud obtained from terrestrial laser scanning (TLS) to extract key phenotypic parameters, including root diameter (RD), length, surface area, and volume. To evaluate the proposed method, two approaches [minimum spanning tree (MST)-based and triangulated irregular network (TIN)-based] were used to reconstruct the Ginkgo root systems from point clouds, and the number of lateral roots along with RD were extracted and compared with traditional methods. The results indicated that the RD extracted directly from point clouds [coefficient of determination (R 2) = 0.99, root-mean-square error (RMSE) = 0.41 cm] outperformed the results of 3D models (MST-based: R 2 = 0.71, RMSE = 2.20 cm; TIN-based: R 2 = 0.54, RMSE = 2.80 cm). Additionally, the MST-based model (F1 = 0.81) outperformed the TIN-based model (F1 = 0.80) in detecting the number of first-order and second-order lateral roots. Each phenotyping trait fluctuated with a different cloud parameter (CP), and the CP value of 0.002 (r = 0.94, p < 0.01) was found to be advantageous for better extraction of structural phenotypes. This study has helped with the extraction and quantitative analysis of root phenotypes and enhanced our understanding of the relationship between architectural parameters and corresponding physiological functions of tree roots.

HCGAN: hierarchical contrast generative adversarial network for unpaired sketch face synthesis.

Transforming optical facial images into sketches while preserving realism and facial features poses a significant challenge. The current methods that rely on paired training data are costly and resource-intensive. Furthermore, they often fail to capture the intricate features of faces, resulting in substandard sketch generation. To address these challenges, we propose the novel hierarchical contrast generative adversarial network (HCGAN). Firstly, HCGAN consists of a global sketch synthesis module that generates sketches with well-defined global features and a local sketch refinement module that enhances the ability to extract features in critical areas. Secondly, we introduce local refinement loss based on the local sketch refinement module, refining sketches at a granular level. Finally, we propose an association strategy called "warmup-epoch" and local consistency loss between the two modules to ensure HCGAN is effectively optimized. Evaluations of the CUFS and SKSF-A datasets demonstrate that our method produces high-quality sketches and outperforms existing state-of-the-art methods in terms of fidelity and realism. Compared to the current state-of-the-art methods, HCGAN reduces FID by 12.6941, 4.9124, and 9.0316 on three datasets of CUFS, respectively, and by 7.4679 on the SKSF-A dataset. Additionally, it obtained optimal scores for content fidelity (CF), global effects (GE), and local patterns (LP). The proposed HCGAN model provides a promising solution for realistic sketch synthesis under unpaired data training.

Enhanced 3D dose prediction for hypofractionated SRS (gamma knife radiosurgery) in brain tumor using cascaded-deep-supervised convolutional neural network.

Gamma Knife radiosurgery (GKRS) is a well-established technique in radiation therapy (RT) for treating small-size brain tumors. It administers highly concentrated doses during each treatment fraction, with even minor dose errors posing a significant risk of causing severe damage to healthy tissues. It underscores the critical need for precise and meticulous precision in GKRS. However, the planning process for GKRS is complex and time-consuming, heavily reliant on the expertise of medical physicists. Incorporating deep learning approaches for GKRS dose prediction can reduce this dependency, improve planning efficiency and homogeneity, streamline clinical workflows, and reduce patient lagging times. Despite this, precise Gamma Knife plan dose distribution prediction using existing models remains a significant challenge. The complexity stems from the intricate nature of dose distributions, subtle contrasts in CT scans, and the interdependence of dosimetric metrics. To overcome these challenges, we have developed a "Cascaded-Deep-Supervised" Convolutional Neural Network (CDS-CNN) that employs a hybrid-weighted optimization scheme. Our innovative method incorporates multi-level deep supervision and a strategic sequential multi-network training approach. It enables the extraction of intra-slice and inter-slice features, leading to more realistic dose predictions with additional contextual information. CDS-CNN was trained and evaluated using data from 105 brain cancer patients who underwent GKRS treatment, with 85 cases used for training and 20 for testing. Quantitative assessments and statistical analyses demonstrated high consistency between the predicted dose distributions and the reference doses from the treatment planning system (TPS). The 3D overall gamma passing rates (GPRs) reached 97.15% ± 1.36% (3 mm/3%, 10% threshold), surpassing the previous best performance by 2.53% using the 3D Dense U-Net model. When evaluated against more stringent criteria (2 mm/3%, 10% threshold, and 1 mm/3%, 10% threshold), the overall GPRs still achieved 96.53% ± 1.08% and 95.03% ± 1.18%. Furthermore, the average target coverage (TC) was 98.33% ± 1.16%, dose selectivity (DS) was 0.57 ± 0.10, gradient index (GI) was 2.69 ± 0.30, and homogeneity index (HI) was 1.79 ± 0.09. Compared to the 3D Dense U-Net, CDS-CNN predictions demonstrated a 3.5% improvement in TC, and CDS-CNN's dose prediction yielded better outcomes than the 3D Dense U-Net across all evaluation criteria. The experimental results demonstrated that the proposed CDS-CNN model outperformed other models in predicting GKRS dose distributions, with predictions closely matching the TPS doses.

Effects of Mink-Origin Enterococcus faecium on Growth Performance, Antioxidant Capacity, Immunity, and Intestinal Microbiota of Growing Male Minks.

The purpose of this experiment was to explore the effects of dietary Enterococcus faecium (EF) on the growth performance, antioxidant capacity, immunity, and intestinal microbiota of growing male minks. A total of 60 male Regal White minks at 12 weeks of age were randomly assigned to two groups, each with 15 replicates of two minks per replicate. The minks in two groups were fed the basal diets and the basal diets with viable Enterococcus faecium (more than 107 cfu/kg of diet), respectively. Compared with the minks in control, Enterococcus faecium minks had heavier body weight (BW) at week 4 and week 8 of the study (p < 0.05), greater average daily gain (ADG), and a lower feed/gain ratio (F/G) of male minks during the initial 4 weeks and the entire 8-week study period (p < 0.05). Furthermore, Enterococcus faecium increased the apparent digestibility of crude protein (CP) and dry matter (DM) compared to the control (p < 0.05). Moreover, Enterococcus faecium enhanced the serum superoxide dismutase (SOD) activity and decreased the malondialdehyde (MDA) contents (p < 0.05). The results also confirmed that Enterococcus faecium increased the levels of serum immunoglobulin A (IgA), immunoglobulin G (IgG), and the concentrations of secretory immunoglobulin A (SIgA) in the jejunal mucosa while decreasing the interleukin-8 (IL-8) and interleukin-1ß (IL-1ß) levels in the jejunal mucosa (p < 0.05). Intestinal microbiota analysis revealed that Enterococcus faecium increased the species numbers at the OUT level. Compared with the control, Enterococcus faecium had significant effects on the relative abundance of Paraclostridium, Brevinema, and Comamonas (p < 0.05). The results showed that Enterococcus faecium could improve the growth performance, increase the antioxidant capacity, improve the immunity of growing male minks, and also modulate the gut microbiota.

Construction of Smart Coatings Containing Core-Shell Nanofibers with Self-Healing and Active Corrosion Protection.

With increasingly severe metal corrosion, coating preparation with high-performance corrosion protection has attracted more attention. Herein, the encapsulation of the corrosion inhibitor 8-hydroxyquinoline (8-HQ) as well as the self-healing agent linseed oil (LO) in polyvinyl alcohol (PVA) and chitosan (CS) shells were realized by coaxial electrospinning, which was recorded as PVA/CS@LO/8-HQ core-shell nanofibers. PVA/CS@LO/8-HQ nanofibers were employed to promote the high-performance corrosion protection of the epoxy coating. The anticorrosion mechanism was that the change of the local pH on the metal surface stimulated the release of 8-HQ from the nanofibers, which were then chelated with iron ions to form a complex. When cracks occurred and caused rupture of the nanofibers, LO was released and reacted with oxygen to cure them so that the cracks could be healed autonomously. The dynamic potential polarization curves showed that the corrosion inhibition efficiency of the compound inhibitor LO + 8-HQ reached 87.54%, 90.31%, and 85.57% at pH = 3, 7, and 11, respectively, higher than that of the single corrosion inhibitor. Density functional theory calculations revealed that the LO and 8-HQ combination, forming a hydrogen bond interaction, promoted the adsorption of inhibitors on the steel surface. Scanning Kelvin probe and electrochemical impedance spectroscopy proved the self-healing corrosion protection properties of the epoxy coating. These results demonstrated that embedding PVA/CS@LO/8-HQ nanofibers in the coating could obtain self-healing properties, and promote the mechanical and corrosion protection of epoxy coating.

Effects of dietary supplementation of Enterococcus faecium postbiotics on growth performance and intestinal health of growing male mink.

Recent studies have demonstrated that postbiotics possess bioactivities comparable to those of probiotics. Therefore, our experiment aimed to evaluate the effects of postbiotics derived from Enterococcus faecium on the growth performance and intestinal health of growing male minks. A total of 120 growing male minks were randomly assigned to 4 groups, each with 15 replicates of 2 minks. The minks in the 4 groups were fed a basal diet supplemented with 0 (control), 0.05, 0.1, and 0.15% postbiotics derived from E. faecium (PEF), respectively. Compared to the control, PEF improved feed/gain (F/G) during the first 4 weeks and the entire 8 weeks of the study (p < 0.05); in addition, 0.1% PEF improved average daily gain (ADG) during the first 4 weeks and the entire 8 weeks of the study (p < 0.05), while 0.15% PEF improved ADG during the first 4 weeks of the study (p < 0.05). Consequently, 0.1% PEF minks displayed greater body weight (BW) at weeks 4 and 8 (p < 0.05), and 0.15% PEF minks had greater BW at week 4 (p < 0.05) than minks in the control. Furthermore, compared to the control, both 0.05 and 0.1% PEF enhanced the apparent digestibility of crude protein (CP) and ether extract (EE) (p < 0.05) in the initial 4 weeks, while both 0.1 and 0.15% PEF enhanced the apparent digestibility of CP and DM in the final 4 weeks (p < 0.05). Additionally, trypsin activity was elevated in the 0.1 and 0.15% PEF groups compared to the control (p < 0.05). In terms of intestinal morphology, PEF increased the villus height and villus/crypt (V/C) in the jejunum (p < 0.05), and both 0.1 and 0.15% PEF decreased the crypt depth and increased the villus height and V/C in the duodenum (p < 0.05) compared to the control group. Supplementation with 0.1% PEF increased the SIgA levels but decreased the IL-2, IL-8, and TNF-α levels in the jejunum (p < 0.05). Compared to the control, E. faecium postbiotics decreased the relative abundances of Serratia and Fusobacterium (p < 0.05). In conclusion, the results indicate that the growth performance, digestibility, immunity, and intestine development of minks are considerably affected by E. faecium postbiotics. In particular, dietary supplementation with 0.1% E. faecium postbiotics provides greater benefits than supplementation with 0.05 and 0.15%.

Development and validation of a predictive model for severe white matter hyperintensity with obesity.

Purpose: The purpose of the present study was to identify predictors of severe white matter hyperintensity (WMH) with obesity (SWO), and to build a prediction model for screening obese people with severe WMH without Nuclear Magnetic Resonance Imaging (MRI) examination. Patients subjects and methods: From September 2020 to October 2021, 650 patients with WMH were recruited consecutively. The subjects were divided into two groups, SWO group and non-SWO group. Univariate and Logistic regression analysis were was applied to explore the potential predictors of SWO. The Youden index method was adopted to determine the best cut-off value in the establishment of the prediction model of SWO. Each parameter had two options, low and high. The score table of the prediction model and nomogram based on the logistic regression were constructed. Of the 650 subjects, 487 subjects (75%) were randomly assigned to the training group and 163 subjects (25%) to the validation group. By resampling the area under the curve (AUC) of the subject's operating characteristics and calibration curves 1,000 times, nomogram performance was verified. A decision curve analysis (DCA) was used to evaluate the nomogram's clinical usefulness. By resampling the area under the curve (AUC) of the subject's operating characteristics and calibration curves 1,000 times, nomogram performance was verified. A decision curve analysis (DCA) was used to evaluate the nomogram's clinical usefulness. Results: Logistic regression demonstrated that hypertension, uric acid (UA), complement 3 (C3) and Interleukin 8 (IL-8) were independent risk factors for SWO. Hypertension, UA, C3, IL-8, folic acid (FA), fasting C-peptide (FCP) and eosinophil could be used to predict the occurrence of SWO in the prediction models, with a good diagnostic performance, Areas Under Curves (AUC) of Total score was 0.823 (95% CI: 0.760-0.885, p < 0.001), sensitivity of 60.0%, specificity of 91.4%. In the development group, the nomogram's AUC (C statistic) was 0.829 (95% CI: 0.760-0.899), while in the validation group, it was 0.835 (95% CI: 0.696, 0.975). In both the development and validation groups, the calibration curves following 1,000 bootstraps showed a satisfactory fit between the observed and predicted probabilities. DCA showed that the nomogram had great clinical utility. Conclusion: Hypertension, UA, C3, IL-8, FA, FCP and eosinophil models had the potential to predict the incidence of SWO. When the total score of the model exceeded 9 points, the risk of SWO would increase significantly, and the nomogram enabled visualization of the patient's WMH risk. The application prospect of our models mainly lied in the convenient screening of SWO without MRI examination in order to detect SWO and control the WMH hazards early.

Omicron neutralization character in patients with breast cancer and liver cancer after the nationwide omicron outbreak.

BACKGROUND: The surge in omicron variants has caused nationwide breakthrough infections in mainland China since the December 2022. In this study, we report the neutralization profiles of serum samples from the patients with breast cancer and the patients with liver cancer who had contracted subvariant breakthrough infections. METHODS: In this real-world study, we enrolled 143 COVID-19-vaccinated (81 and 62 patients with breast and liver cancers) and 105 unvaccinated patients with cancer (58 and 47 patients with breast and liver cancers) after omicron infection. Anti-spike receptor binding domain (RBD) IgGs and 50% pseudovirus neutralization titer (pVNT50) for the preceding (wild type), circulating omicron (BA.4-BA.5, and BF.7), and new subvariants (XBB.1.5) were comprehensively analyzed. RESULTS: Patients with liver cancer receiving booster doses had higher levels of anti-spike RBD IgG against circulating omicron (BA.4-BA.5, and BF.7) and a novel subvariant (XBB.1.5) compared to patients with breast cancer after breakthrough infection. Additionally, all vaccinated patients produced higher neutralizing antibody titers against circulating omicron (BA.4-BA.5, and BF.7) compared to unvaccinated patients. However, the unvaccinated patients produced higher neutralizing antibody against XBB.1.5 than vaccinated patients after Omicron infection, with this trend being more pronounced in breast cancer than in liver cancer patients. Moreover, we found that there was no correlation between anti-spike RBD IgG against wildtype virus and the neutralizing antibody titer, but a positive correlation between anti-spike RBD IgG and the neutralizing antibody against XBB.1.5 was found in unvaccinated patients. CONCLUSION: Our study found that there may be differences in vaccine response and protective effect against COVID-19 infection in patients with liver and breast cancer. Therefore, we recommend that COVID-19 vaccine strategies should be optimized based on vaccine components and immunology profiles of different patients with cancer.

Experimental Quantum Homomorphic Encryption Using a Quantum Photonic Chip.

A fully homomorphic encryption system enables computation on encrypted data without the necessity for prior decryption. This facilitates the seamless establishment of a secure quantum channel, bridging the server and client components, and thereby providing the client with secure access to the server's substantial computational capacity for executing quantum operations. However, traditional homomorphic encryption systems lack scalability, programmability, and stability. In this Letter, we experimentally demonstrate a proof-of-concept implementation of a homomorphic encryption scheme on a compact quantum chip, verifying the feasibility of using photonic chips for quantum homomorphic encryption. Our work not only provides a solution for circuit expansion, addressing the longstanding challenge of scalability while significantly reducing the size of quantum network infrastructure, but also lays the groundwork for the development of highly sophisticated quantum fully homomorphic encryption systems.

Clinical potential of serum prostaglandin A2 as a novel diagnostic biomarker for hepatocellular cancer.

BACKGROUND: Hepatocellular cancer (HCC) is one of the most harmful tumors to human health. Currently, there is still a lack of highly sensitive and specific HCC biomarkers in clinical practice. In this study, we aimed to explore the diagnostic performance of prostaglandin A2 (PGA2) for the early detection of HCC. METHODS: Untargeted metabolomic analyses on normal control (NC) and HCC participants in the discovery cohort were performed, and PGA2 was identified to be dysregulated in HCC. A liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for detecting serum PGA2 was established and applied to validate the dysregulation of PGA2 in another independent validation cohort. Receiver operating characteristic (ROC), decision curve analysis (DCA) and some other statistical analyses were performed to evaluate the diagnostic performance of PGA2 for HCC. RESULTS: At first, PGA2 was found to be dysregulated in HCC in untargeted metabolomic analyses. Then a precise quantitative LC-MS/MS method for PGA2 has been established and has passed rigorous method validation. Targeted PGA2 analyses confirmed that serum PGA2 was decreased in HCC compared to normal-risk NC and high-risk cirrhosis group. Subsequently, PGA2 was identified as a novel biomarker for the diagnosis of HCC, with an area under the ROC curve (AUC) of 0.911 for differentiating HCC from the combined NC + cirrhosis groups. In addition, PGA2 exhibited high performance for differentiating small-size (AUC = 0.924), early-stage (AUC = 0.917) and AFP (-) HCC (AUC = 0.909) from the control groups. The combination of PGA2 and AFP might be useful in the surveillance of risk population for HCC and early diagnosis of HCC. CONCLUSION: This study establishes that PGA2 might be a novel diagnostic biomarker for HCC.

Health effect of public sports services and public health services: empirical evidence from China.

There is no clear explanation for the extraordinary rebound in China's population mortality over the past decade. This paper utilizes panel data from 31 Chinese provinces from 2010 to 2020 to determine the distinct impacts of public sports services (PSS), public health services (PMS), and their interaction on population mortality. Empirical results show that public sports services significantly reduce mortality. Every unit increase in public sports services reduces mortality by about 2.3%. It is characterized by delayed realization. Public health services were surprisingly associated with a rebound in mortality. Further studies found strong health effect from interaction of public sports and health services. The effect was significantly strengthened in areas with fewer extreme temperatures or developed economy. The findings have important policy implications for the high-quality development of public sports and health services. It also emphasizes integration of sports and medicine and mitigates health risks associated with extreme temperatures.

The larva and adult of Helicoverpa armigera use differential gustatory receptors to sense sucrose.

Almost all herbivorous insects feed on plants and use sucrose as a feeding stimulant, but the molecular basis of their sucrose reception remains unclear. Helicoverpa armigera as a notorious crop pest worldwide mainly feeds on reproductive organs of many plant species in the larval stage, and its adult draws nectar. In this study, we determined that the sucrose sensory neurons located in the contact chemosensilla on larval maxillary galea were 100-1000 times more sensitive to sucrose than those on adult antennae, tarsi, and proboscis. Using the Xenopus expression system, we discovered that Gr10 highly expressed in the larval sensilla was specifically tuned to sucrose, while Gr6 highly expressed in the adult sensilla responded to fucose, sucrose and fructose. Moreover, using CRISPR/Cas9, we revealed that Gr10 was mainly used by larvae to detect lower sucrose, while Gr6 was primarily used by adults to detect higher sucrose and other saccharides, which results in differences in selectivity and sensitivity between larval and adult sugar sensory neurons. Our results demonstrate the sugar receptors in this moth are evolved to adapt toward the larval and adult foods with different types and amounts of sugar, and fill in a gap in sweet taste of animals.

The close association of micronutrients with COVID-19.

Objectives: The present study was conducted to explore the performance of micronutrients in the prediction and prevention of coronavirus disease 2019 (COVID-19). Methods: This is an observational case-control study. 149 normal controls (NCs) and 214 COVID-19 patients were included in this study. Fat-soluble and water-soluble vitamins were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, and inorganic elements were detected by inductively coupled plasma-mass spectrometry (ICP-MS) analysis. A logistic regression model based on six micronutrients were constructed using DxAI platform. Results: Many micronutrients were dysregulated in COVID-19 compared to normal control (NC). 25-Hydroxyvitamin D3 [25(OH)D3], magnesium (Mg), copper (Cu), calcium (Ca) and vitamin B6 (pyridoxic acid, PA) were significantly independent risk factors for COVID-19. The logistic regression model consisted of 25(OH)D3, Mg, Cu, Ca, vitamin B5 (VB5) and PA was developed, and displayed a strong discriminative capability to differentiate COVID-19 patients from NC individuals [area under the receiver operating characteristic curve (AUROC) = 0.901]. In addition, the model had great predictive ability in discriminating mild/normal COVID-19 patients from NC individuals (AUROC = 0.883). Conclusions: Our study showed that micronutrients were associated with COVID-19, and our logistic regression model based on six micronutrients has potential in clinical management of COVID-19, and will be useful for prediction of COVID-19 and screening of high-risk population.

Synergistic Antimicrobial Glycyrrhizic Acid-Based Functional Biosensing Composite for Sensitive Glucose Monitoring and Collaborative Wound Healing.

High glucose blood and bacterial infection remain major issues for the slow healing of diabetic wounds, so developing functional biosensing composite with excellent antibacterial and remarkable glucose response sensitivity is necessary and prospective. Herein, by in situ synthesis AgNPs on the surface of self-prepared PTIGA elastomers, PTIGA-AgNPs conductive composites are obtained with efficient synergistic antibacterial effect, excellent mechanical and self-healing properties. The strain of the composites can reach 1800%, and its self-healing efficiency exceeds 90% at 60 °C within 8 h. Both elastomers and composites represent excellent biocompatibility and the antibacterial rate against E. coli and S. aureus exceeded 90%. Moreover, the biosensor assembled from the conductive composites exhibits excellent glucose response sensitivity and stability, with a sensitivity coefficient of 0.518 mA mm-1 in the range of 0.2-3.6 × 10-3 m glucose concentration, as well as a low detection limit of 0.08 × 10-3 m. Furthermore, based on the remarkable antibacterial performance and bioactivity derived from GA, the composites reduce the expression of pro-inflammatory factors and promote the production of anti-inflammatory factors, and effectively promote the regeneration of skin and granulation tissue of wounds in a diabetic full-thickness skin defect model, demonstrating the enormous therapeutic potential in diabetic wound healing.

Intestinal-specific oral delivery of lactoferrin with alginate-based composite and hybrid CaCO3-hydrogel beads.

Sodium alginate hydrogel beads and sodium alginate/gellan gum composite hydrogel beads crosslinked by calcium chloride were prepared with different alginate concentrations (3-20 mg·mL-1). Additionally, a simple method for growing CaCO3in situ on the hydrogel to create novel inorganic-organic hybrid hydrogel beads was presented. FT-IR analysis revealed the involvement of hydrogen bonding and electrostatic interactions in bead formation. Swelling behavior in acidic conditions showed a maximum of 13 g/g for composite hydrogels and CaCO3-incorporated hybrid hydrogels. Lactoferrin encapsulation efficiency within these hydrogels ranged from 44.9 to 56.6%. In vitro release experiments demonstrated that these hydrogel beads withstand harsh gastric environments with <16% cumulative release of lactoferrin, achieving controlled release in intestinal surroundings. While composite sodium alginate/gellan gum beads exhibited slower gastrointestinal lactoferrin digestion, facile synthesis and pH responsiveness of CaCO3-incorporated hybrid hydrogel also provide new possibilities for future studies to construct a novel inorganic-organic synergetic system for intestinal-specific oral delivery.

Chinese herbal medicine for the treatment of diabetic nephropathy: From clinical evidence to potential mechanisms.

ETHNOPHARMACOLOGICAL RELEVANCE: Diabetic nephropathy (DN) is a typical chronic microvascular complication of diabetes, characterized by proteinuria and a gradual decline in renal function. At present, there are limited clinical interventions aimed at preventing the progression of DN to end-stage renal disease (ESRD). However, Chinese herbal medicine presents a distinct therapeutic approach that can be effectively combined with conventional Western medicine treatments to safeguard renal function. This combination holds considerable practical implications for the treatment of DN. AIM OF THE STUDY: This review covers commonly used Chinese herbal remedies and decoctions applicable to various types of DN, and we summarize the role played by their active ingredients in the treatment of DN and their mechanisms, which includes how they might improve inflammation and metabolic abnormalities to provide new ideas to cope with the development of DN. MATERIALS AND METHODS: With the keywords "diabetic nephropathy," "Chinese herbal medicine," "clinical effectiveness," and "bioactive components," we conducted an extensive literature search of several databases, including PubMed, Web of Science, CNKI, and Wanfang database, to discover studies on herbal formulas that were effective in slowing the progression of DN. The names of the plants covered in the review have been checked at MPNS (http://mpns.kew.org). RESULTS: This review demonstrates the superior total clinical effective rate of combining Chinese herbal medicines with Western medicines over the use of Western medicines alone, as evidenced by summarizing the results of several clinical trials. Furthermore, the review highlights the nephroprotective effects of seven frequently used herbs exerting beneficial effects such as podocyte repair, anti-fibrosis of renal tissues, and regulation of glucose and lipid metabolism through multiple signaling pathways in the treatment of DN. CONCLUSIONS: The potential of herbs in treating DN is evident from their excellent effectiveness and the ability of different herbs to target various symptoms of the condition. However, limitations arise from the deficiencies in interfacing with objective bioindicators, which hinder the integration of herbal therapies into modern medical practice. Further research is warranted to address these limitations and enhance the compatibility of herbal therapies with contemporary medical standards.

Tanshinone IIA acts as a regulator of lipogenesis to overcome osimertinib acquired resistance in lung cancer.

Osimertinib is a novel epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), acting as the first-line medicine for advanced EGFR-mutated NSCLC. Recently, the acquired resistance to osimertinib brings great challenges to the advanced treatment. Therefore, it is in urgent need to find effective strategy to overcome osimertinib acquired resistance. Here, we demonstrated that SREBP pathway-driven lipogenesis was a key mediator to promote osimertinib acquired resistance, and firstly found Tanshinone IIA (Tan IIA), a natural pharmacologically active constituent isolated from Salvia miltiorrhiza, could overcome osimertinib-acquired resistance in vitro and in vivo via inhibiting SREBP pathway-mediated lipid lipogenesis by using LC-MS based cellular lipidomics analysis, quantitative real-time PCR (qRT-PCR) analysis, western blotting analysis, flow cytometry, small interfering RNAs transfection, and membrane fluidity assay et al. The results showed that SREBP1/2-driven lipogenesis was highly activated in osimertinib acquired resistant NSCLC cells, while knockdown or inhibition of SREBP1/2 could restore the sensitivity of NSCLC to osimertinib via altered the proportion of saturated phospholipids and unsaturated phospholipids in osimertinib acquired-resistant cells. Furthermore, Tanshinone IIA (Tan IIA) could reverse the acquired resistance to osimertinib in lung cancer. Mechanically, Tan IIA inhibited SREBP signaling mediated lipogenesis, changed the profiles of saturated phospholipids and unsaturated phospholipids, and thus promoted osimertinib acquired resistant cancer cells to be attacked by oxidative stress-induced damage and reduce the cell membrane fluidity. The reversal effect of Tan IIA on osimertinib acquired resistant NSCLC cells was also confirmed in vivo, which is helpful for the development of strategies to reverse osimertinib acquired resistance.

Characterizing Local Electronic States of Twin Boundaries in Copper.

Grain boundaries (GBs) and twin boundaries (TBs) in copper (Cu) are two major planar defects that influence electrical conductivity due to their complex electron transport characteristics, involving electron scattering and electron concentration. Understanding their local electronic states is crucial for the design of future conductor materials. In this study, we characterized electron behaviors at TBs and GBs within one Cu grain using atomic force microscopy. Our findings revealed that, compared with GBs, TBs exhibit better current transport capability (direct-current mode) and larger electromagnetic loss (high-frequency microwave mode). Both kelvin probe force microscopy and theoretical analysis suggested that TBs with smaller lattice disorder possess lower density of states at the Fermi level. The reduced density of states may result in decreased electron scattering and a lower electron concentration at TBs. The latter can be highlighted by the high-frequency skinning effect, manifested as larger electromagnetic loss and weaker high-frequency conductivity.