Localized Surface Doping Induced Ultralow Contact Resistance between Metal and (Bi,Sb)2Te3 Thermoelectric Films.

Micro thermoelectric devices are expected to further improve the cooling density for the temperature control of electronic devices; nevertheless, the high contact resistivity between metals and semiconductors critically limits their applications, especially in chip cooling with extremely high heat flux. Herein, based on the calculated results, a low specific contact resistivity of ∼10-7 Ω cm2 at the interface is required to guarantee a desirable cooling power density of micro devices. Thus, we developed a generally applicable interfacial modulation strategy via localized surface doping of thermoelectric films, and the feasibility of such a doping approach for both n/p-type (Bi,Sb)2Te3 films was demonstrated, which can effectively increase the surface-majority carrier concentration explained by the charge transfer mechanism. With a proper doping level, ultralow specific contact resistivities at the interfaces are obtained for n-type (6.71 × 10-8 Ω cm2) and p-type (3.70 × 10-7 Ω cm2) (Bi,Sb)2Te3 layers, respectively, which is mainly attributed to the carrier tunneling enhancement with a narrowed interfacial contact barrier width. This work provides an effective scheme to further reduce the internal resistance of micro thermoelectric coolers, which can also be extended as a kind of universal interfacial modification technique for micro semiconductor devices.

Relationship Between Illness Uncertainty and Family Resilience Among Caregivers of Stroke Patients in Chinese Nuclear Families: The Mediating Role of Perceived Stress.

Purpose: Stroke is a major disease endangering the health of Chinese people, and patients need to rely on the care of family members, which brings heavy caregiving burdens and pressures to caregivers and families, thus disrupting the stable family structure. In view of this, this study was to analyse the current status of family resilience among caregivers of stroke patients in Chinese nuclear families, and to explore the correlation and mechanism of action among perceived stress, illness uncertainty and family resilience. Patients and Methods: This study used a cross-sectional research design. A total of 350 carers of stroke patients in nuclear families from four tertiary hospitals in Suzhou City, Jiangsu Province, China were selected by convenience sampling method and assessed by using demographic questionnaires, the Chinese Perceived Stress Scale (CPSS), the Parental Perceptions of Uncertainty Scale-Family (PPUS-FM), and a short Chinese version of the Family Resilience Assessment Scale (FRAS-C). Based on the above data, structural equation model was used to test the mediating role of perceived stress between illness uncertainty and family resilience. Results: Family resilience among caregivers of stroke patients in nuclear families was at the medium lower level, illness uncertainty was at the medium level, and perceived stress was at the relatively high level. Illness uncertainty was positively correlated with perceived stress (P<0.01) and negatively correlated with family resilience (P<0.01). Illness uncertainty directly predicted family resilience (ß = -0.516, p < 0.05). And the pathway between illness uncertainty and family resilience was partially mediated by perceived stress (Effect= -0.091, 95% CI [-0.141, -0.055]). Conclusion: Healthcare professionals should pay adequate attention to the level of illness uncertainty and perceived stress among carers of stroke patients, with the need to take measures to reduce carers' illness uncertainty and perceived stress in order to improve family resilience.

Impact of microorganisms on key processes of organic acid metabolism during the occurrence and disappearance of paocai pellicle.

In vegetable fermentation, pellicle is a common quality deterioration phenomenon. This study investigates the characteristics of glucose, organic acids, amino acids, and biogenic amines during the pellicle occurrence and disappearance of paocai. The results revealed a slight increase in pH of the fermentation system after pellicle occurred, and glucose was the main carbohydrate that microbial activity primary relied on. The microorganisms responsible for pellicle formation consumed organic acids in brine, but the lactic acid in paocai gradually increased and exceeded 25 mg/g. The appearance of pellicle caused a decrease in total free amino acids from 200.390 mg/100 g to 172.079 when pellicle occurred, whereas its impact on biogenic amines was not apparent. Through Kyoto Encyclopedia of Genes and Genomes pathway enrichment of metagenomics sequencing data, screening, and sorting of the key enzymes involved in organic acid metabolism, it was observed that the composition and species of the key microorganisms capable of metabolizing organic acids were more abundant before the appearance of pellicle. When pellicle occurred, lactic acid may be metabolized by Lactobacillus plantarum; in contrast, Lactobacillus and Pichia were associated with citric acid metabolism, and Lactobacillus, Pichia, Saccharomycodes, and Kazachstania were linked to malic acid metabolism. Moreover, Prevotella, Kazachstania, Lactobacillus, Vibrio, and Siphonobacter were implicated in succinic acid metabolism. Additionally, the production of tartaric acid and oxalic acid in paocai and brine resulted from abiotic effects. This knowledge offers a theoretical basis for precise control of paocai fermentation process. PRACTICAL APPLICATION: Our study revealed the specific situation of the metabolites produced by the microorganisms during the pollution and recovery process of pellicle in paocai fermentation, especially the effect of pellicle on the key process of organic acid metabolism. These research results provided theoretical basis for precise control of paocai fermentation.

Bioinspired Nano-Photosensitizer-Activated Caspase-3/GSDME Pathway Induces Pyroptosis in Lung Cancer Cells.

Noninflammatory apoptosis is transformed into inflammatory pyroptosis by activating caspase-3 to lyse gasdermin E (GSDME), and this process can be used as an effective therapeutic strategy. Thus, a selective and powerful inducer of activated caspase-3 plays a vital role in pyroptosis-based cancer therapy. Herein, a human cell membrane vesicle-based nanoplatform (HCNP) is designed for photodynamic therapy (PDT). HCNP is modified with vesicular stomatitis virus G-protein (VSVG) to anchor nano-photosensitizers on the tumor cell membrane. Photosensitizers are bonded to HCNP by clicking chemical reaction as pyroptosis inducers. The results show that HCNP effectively disrupts the mitochondrial function of cells by generating reactive oxygen species (ROS) upon laser irradiation; concomitantly, GSDME is cleaved by activated caspase-3 and promotes pyroptosis of lung cancer cells. Here an effective intervention strategy is proposed to induce pyroptosis based on light-activated PDT.

Eco-friendly shrink-resist finishing of wool through synergistic effect of disulfide bond reducing agent and papain.

The environmental benefits of utilizing protease as a biocatalyst for wool shrink-resist finishing have been widely recognized. However, the efficacy of individual protease treatment is unsatisfactory due to its incapability towards the outermost cuticle layer of wool fibers that contains hydrophobic fatty acids. In order to weaken the structural integrity of the highly cross-linked scales and promote the enzymatic anti-felting, sodium sulfite and tris (2-carboxyethyl) phosphine hydrochloride (TCEP) were employed in combination with papain, respectively, aiming at obtaining a low shrinkage without unacceptable fiber damages. Based on the synergistic effect of papain and TCEP, the edges of wool scales were slightly destroyed by the reduction of disulfide bonds, accompanied by enzymatic hydrolysis of the keratin component. Through the controlled reduction and hydrolysis of wool scales, satisfactory anti-felting result was achieved without causing severe damage to the fiber interiors. In the presence of 0.25 g/L TCEP and 25 U/mL papain, the area shrinkage of wool fabric decreased to approximately 6 %, with a low strength loss of less than 8 %. Meanwhile, the dyeing behavior of the wool fabric under low-temperature conditions was dramatically improved, leading to decreased energy consumption during production. The present work provides an alternative for eco-friendly finishing of wool fabrics, which can be applied commercially.

Rapid aggregation of amyloid-like protein enhanced by mTGase to prepare functional wool fabrics for efficient and sustainable remove heavy metals from wastewater.

To counteract the increasing severity of water pollution and purify water sources, wastewater treatment materials are essential. In particular, it is necessary to improve the bonding strength between the adsorption material and the substrate in a long-term humid environment, and resist the invasion of microorganisms to prolong the service life. In this study, an amyloid-like aggregation method of lysozyme catalyzed by microbial transglutaminase (mTGase). Lysozyme self-assembles into an amyloid-like phase-transited lysozyme (PTL) in the presence of a reducing agent. Simultaneously, mTGase catalyzes acyl transfer reactions within lysozyme molecules or between lysozyme and keratin molecules, and driving PTL assembly on the wool fiber (TG-PTL@wool). This process enhances the grafting amount and fastness of PTL on the wool. Moreover, the tensile strength of wool fabric increased to 523 N. TG-PTL@wool achieves a 97.32 % removal rate of heavy metals, maintaining a removal rate of over 95 % after 5 cycles. TG-PTL@wool has excellent antibacterial property (99 %), and it remains above 90 % after 50 times of circulating washing. This study proved that mTGase can enhance the amyloid aggregation of lysozyme and enhance the bonding strength between PTL coating and substrate. Moreover, TG-PTL@wool provides a sustainable, efficient and cleaner solution for removing heavy metals from water.

Regulation of phonon localization on thermal transport in complex networks.

The regulation of thermal transport is a challenging topic in complex networks. At present, the hidden physical mechanism behind thermal transport is poorly understood. This paper addresses this issue by proposing a complex network model that focuses on the thermal transport regulation through the manipulation of the network's degree distribution and clustering coefficient. Our findings indicate that increasing the degree distribution regulation parameter σ leads to reduced phonon localization and improved thermal transport efficiency. Conversely, increasing the clustering coefficient c results in enhanced phonon localization and reduced thermal transport efficiency. Meanwhile, by calculating the pseudodispersion relation of the network, we find that the maximum (or the second smallest) eigenfrequency decreases with increasing σ (or c). Finally, we elucidate that phonon localization plays a pivotal role in the thermal transport of the network, as demonstrated through density of states and the participation ratio.

Stable CO2reduction under natural air on Ni-Sn hydroxide photocatalyst with dynamic renewable oxygen vacancies.

Advanced photocatalysts are highly desired to activate the photocatalytic CO2reduction reaction (CO2RR) with low concentration. Herein, the NiSn(OH)6with rich surface lattice hydroxyls was synthesized to boost the activity directly under the natural air. Results showed that terminal Ni-OH could serve as donors to feed protons and generate oxygen vacancies (VO), thus beneficial to convert the activated CO2(HCO3-) mainly into CO (5.60µmol g-1) in the atmosphere. It was flexible and widely applicable for a stable CO2RR from high pure to air level free of additionally adding H2O reactant, and higher than the traditional gas-liquid-solid (1.58µmol g-1) and gas-solid (4.07µmol g-1) reaction system both using high pure CO2and plenty of H2O. The strong hydrophilia by the rich surface hydroxyls allowed robust H2O molecule adsorption and dissociation at VOsites to achieve the Ni-OH regeneration, leading to a stable CO yield (11.61µmol g-1) with the enriched renewable VOregardless of the poor CO2and H2O in air. This work opens up new possibilities for the practical application of natural photosynthesis.

A facile cellulose finishing strategy through in-situ growth of sliver-doped manganese dioxide assisted by amine-quinone for improving indoor living quality.

Nowadays, various harmful indoor pollutants especially including bacteria and residual formaldehyde (HCHO) seriously threaten human health and reduce the quality of public life. Herein, a universal substrate-independence finishing approach for efficiently solving these hybrid indoor threats is demonstrated, in which amine-quinone network (AQN) was employed as reduction agent to guide in-situ growth of Ag@MnO2 particles, and also acted as an adhesion interlayer to firmly anchor nanoparticles onto diverse textiles, especially for cotton fabrics. In contrast with traditional hydrothermal or calcine methods, the highly reactive AQN ensures the efficient generation of functional nanoparticles under mild conditions without any additional catalysts. During the AQN-guided reduction, the doping of Ag atoms onto cellulose fiber surface optimized the crystallinity and oxygen vacancy of MnO2, providing cotton efficient antibacterial efficiency over 90 % after 30 min of contact, companying with encouraging UV-shielding and indoor HCHO purification properties. Besides, even after 30 cycles of standard washing, the Ag@MnO2-decorated textiles can effectively degrade HCHO while well-maintaining their inherent properties. In summary, the presented AQN-mediated strategy of efficiently guiding the deposition of functional particles on fibers has broad application prospects in the green and sustainable functionalization of textiles.

A novel modified polydopamine based on melanin-like materials for antibacterial, hydrophobic, and ultraviolet protective of textiles.

The development of environmentally friendly multifunctional auxiliaries for textile modification is the focus of attention in textile industry in recent years. Polydopamine is an important biological macromolecule and widely used in biomedicine, nanomaterials, material surface modification and other fields. In this study, the novel multifunctional melanin-like nanoparticles (Nha-PDA NPs) were prepared and used for antibacterial, hydrophobic, and UV protective of textiles. Nha-PDA NPs were prepared with dopamine (DA) and n-hexylamine (Nha) by simple autoxidation copolymerization. Nha-PDA NPs were bound to the fabric surface through the PDA structure in Nha-PDA NPs that has been widely confirmed to have strong adhesion on the surface of many materials. The modified fabrics, Nha-PDA NPs@Cotton, had good hydrophobic, antibacterial and UV protective properties. The static water contact angles of the modified fabrics could reach 120°. The antibacterial rates of Nha-PDA NPs@Cotton against E. coli and S. aureus were above 85 %. The maximum UPF value of the modified cotton was 362, indicating that the ultraviolet protection performance was excellent. The fabric modified with multifunctional melanin-like nanoparticle provides a green way for the multifunctional modification of textiles.

AMENet is a monocular depth estimation network designed for automatic stereoscopic display.

Monocular depth estimation has a wide range of applications in the field of autostereoscopic displays, while accuracy and robustness in complex scenes are still a challenge. In this paper, we propose a depth estimation network for autostereoscopic displays, which aims at improving the accuracy of monocular depth estimation by fusing Vision Transformer (ViT) and Convolutional Neural Network (CNN). Our approach feeds the input image as a sequence of visual features into the ViT module and utilizes its global perception capability to extract high-level semantic features of the image. The relationship between the losses is quantified by adding a weight correction module to improve robustness of the model. Experimental evaluation results on several public datasets show that AMENet exhibits higher accuracy and robustness than existing methods in different scenarios and complex conditions. In addition, a detailed experimental analysis was conducted to verify the effectiveness and stability of our method. The accuracy improvement on the KITTI dataset compared to the baseline method is 4.4%. In summary, AMENet is a promising depth estimation method with sufficient high robustness and accuracy for monocular depth estimation tasks.

Photothermal, superhydrophobic, conductive, and anti-UV cotton fabric loaded with polydimethylsiloxane-encapsulated copper sulfide nanoflowers.

Multifunctional textiles have attracted widespread attention with the improvement of awareness of health. Especially, the fluorine-free superhydrophobic and conductive cellulose fiber-based fabrics have received intensive interest due to their broad and high-value applications. Herein, the copper sulfide nanoflowers were in-situ deposited on cotton fabric followed by polydimethylsiloxane (PDMS) treatment for encapsulating CuS nanoflowers and obtaining superhydrophobicity, recorded as Cot@PTA@CuS@PDMS. Cot@PTA@CuS@PDMS possesses superhydrophobicity with contact angles of 153.0 ± 0.4°, photothermal effect, excellent UV resistance, good conductivity, and anti-fouling. Interestingly, the resistance of Cot@PTA@CuS@PDMS is significantly reduced from 856.4 to 393.1 Ω under simulated sunlight irradiation with 250 mW/cm2. Notably, the resistance can be slightly recovered after shutting off simulated sunlight. Besides, Cot@PTA@CuS@PDMS has efficient oil-water separation efficiency for corn germ oil and castor oil, respectively. Briefly, this work provides a novel, facile, and promising strategy to fabricate multifunctional fiber-based textiles with the reversible change of resistance under simulated sunlight irradiation, inspiring more scholars to control the resistance change of textiles by light irradiation.

Dense monocular depth estimation for stereoscopic vision based on pyramid transformer and multi-scale feature fusion.

Stereoscopic display technology plays a significant role in industries, such as film, television and autonomous driving. The accuracy of depth estimation is crucial for achieving high-quality and realistic stereoscopic display effects. In addressing the inherent challenges of applying Transformers to depth estimation, the Stereoscopic Pyramid Transformer-Depth (SPT-Depth) is introduced. This method utilizes stepwise downsampling to acquire both shallow and deep semantic information, which are subsequently fused. The training process is divided into fine and coarse convergence stages, employing distinct training strategies and hyperparameters, resulting in a substantial reduction in both training and validation losses. In the training strategy, a shift and scale-invariant mean square error function is employed to compensate for the lack of translational invariance in the Transformers. Additionally, an edge-smoothing function is applied to reduce noise in the depth map, enhancing the model's robustness. The SPT-Depth achieves a global receptive field while effectively reducing time complexity. In comparison with the baseline method, with the New York University Depth V2 (NYU Depth V2) dataset, there is a 10% reduction in Absolute Relative Error (Abs Rel) and a 36% decrease in Root Mean Square Error (RMSE). When compared with the state-of-the-art methods, there is a 17% reduction in RMSE.

Ultrasonic-enhanced photocatalysis through piezoelectric and cavitation effects for lignin depolymerization.

Although a promising method for lignin depolymerization, photocatalysis faces the challenge of low efficiency. In this study, MoS2/ZnO heterojunction catalysts, endowed with piezocatalysis and photocatalytic capabilities, were crafted through Zn ion intercalation for the depolymerization of phenoxyphenylethanol (PP-ol) and alkali lignin. Then, the synergistic interplay between ultrasonic-induced piezoelectric fields and heterojunctions was analyzed. The amalgamation of the piezoelectric field and heterojunction in MoS2/ZnO catalysts resulted in a diminished photogenerated hole/electron recombination efficiency, thereby fostering the generation of ·OH during the reaction. This pivotal role of ·OH emerged as a crucial reactive substance, converting 95.8 % of PP-ol through ß-O-4 bond breaking within a 3-h treatment. By incorporating ultrasonic, the contact probability of PP-ol with the catalyst was significantly improved, resulting in efficient conversion even with a reduced amount of acetonitrile in the solvent system (20 %). Furthermore, ultrasonic-light methods show high efficiency for depolymerizing Alkali lignin (AL), with 33.2 % of lignin undergoing depolymerization in a 4-h treatment. This treatment simultaneously reduces the molecular weight of AL and cleaves numerous chemical bonds within it. Overall, this work presents a green approach to lignin depolymerization, providing insights into the synergistic action of ultrasonic and photocatalysis.

Inversion of heavy metal content in soil using hyperspectral characteristic bands-based machine learning method.

The global concern regarding the adverse effects of heavy metal pollution in soil has grown significantly. Accurate prediction of heavy metal content in soil is crucial for environmental protection. This study proposes an inversion analysis method for heavy metals (As, Cd, Cr, Cu, Ni, Pb) in soil based on hyperspectral and machine learning algorithms for 21 soil reference materials from multiple provinces in China. On this basis, an integrated learning model called Stacked RF (the base model is XGBoost, LightGBM, CatBoost, and the meta-model is RF) was established to perform soil heavy metal inversion. Specifically, three popular algorithms were initially employed to preprocess the spectral data, then Random Forest (RF) was used to select the best feature bands to reduce the impact of noise, finally Stacking and four basic machine learning algorithms were used to establish comparisons and analysis of inversion model. Compared with traditional machine learning methods, the stacking model showcases enhanced stability and superior accuracy. Research results indicate that machine learning algorithms, especially ensemble learning models, have better inversion effects on heavy metals in soil. Overall, the MF-RF-Stacking model performed best in the inversion of the six heavy metals. The research results will provide a new perspective on the ensemble learning model method for soil heavy metal content inversion using data of hyperspectral characteristic bands collected from soil reference materials.

[MiR-217 Targeting PI3K/Akt Pathway Enhances Sensitivity of Adriamycin to Acute Myeloid Leukemia].

OBJECTIVE: To investigate the effects of miR-217 on proliferation and adriamycin sensitivity of acute myeloid leukemia (AML) cells. METHODS: The mimic NC and miR-217 mimic vectors were constructed and transfected into HL-60 cells, and transfection efficiency was detected by qPCR. The cells were treated with different concentrations of adriamycin for 24 h and 48 h. CCK-8 assay was used to detect the chemical sensitivity of adriamycin and screen the optimal concentration and time of adriamycin treatment. Cells were divided into control group, mimic NC group, miR-217 mimic group, adriamycin group and miR-217 mimic+adriamycin group. Apoptosis was detected by flow cytometry, and the expressions of miR-217, PI3K and Akt3 were detected by qPCR. Western blot was used to detect the expression of PI3K/Akt pathway proteins PI3K, Akt3 and apoptosis proteins Bcl-2, Bax, and double luciferase was used to verify the relationship between miR-217 and Akt3. RESULTS: MiR-217 mimic could enhance the sensitivity of HL-60 cells to adriamycin. The optimal concentration and treatment time of adriamycin were 160 ng/ml and 48 h, respectively. Compared with control group, apoptosis rate, miR-217 and Bax protein levels were significantly increased in miR-217 mimic and adriamycin groups (P < 0.01), while Bcl-2 protein, PI3K, Akt3 mRNA and protein levels were significantly decreased (P < 0.01). Compared with adriamycin group, apoptosis rate, miR-217 and Bax protein levels were significantly increased in miR-217 mimic+adriamycin group (P < 0.01), while Bcl-2 protein, PI3K, Akt3 mRNA and protein levels were significantly decreased (P < 0.01). Dual luciferase assay showed that there was a targeted regulatory relationship between miR-217 and Akt3. CONCLUSION: MiR-217 regulates the PI3K/Akt pathway targeting Akt3, inhibits cell proliferation, promotes cell apoptosis and enhances the sensitivity of adriamycin to AML cells.

A General Spatial-Frequency Learning Framework for Multimodal Image Fusion.

multimodal image fusion involves tasks like pan-sharpening and depth super-resolution. Both tasks aim to generate high-resolution target images by fusing the complementary information from the texture-rich guidance and low-resolution target counterparts. They are inborn with reconstructing high-frequency information. Despite their inherent frequency domain connection, most existing methods only operate solely in the spatial domain and rarely explore the solutions in the frequency domain. This study addresses this limitation by proposing solutions in both the spatial and frequency domains. We devise a Spatial-Frequency Information Integration Network, abbreviated as SFINet for this purpose. The SFINet includes a core module tailored for image fusion. This module consists of three key components: a spatial-domain information branch, a frequency-domain information branch, and a dual-domain interaction. The spatial-domain information branch employs the spatial convolution-equipped invertible neural operators to integrate local information from different modalities in the spatial domain. Meanwhile, the frequency-domain information branch adopts a modality-aware deep Fourier transformation to capture the image-wide receptive field for exploring global contextual information. In addition, the dual-domain interaction facilitates information flow and the learning of complementary representations. We further present an improved version of SFINet, SFINet++, that enhances the representation of spatial information by replacing the basic convolution unit in the original spatial domain branch with the information-lossless invertible neural operator. We conduct extensive experiments to validate the effectiveness of the proposed networks and demonstrate their outstanding performance against state-of-the-art methods in two representative multimodal image fusion tasks: pan-sharpening and depth super-resolution. The source code is publicly available at https://github.com/manman1995/Awaresome-pansharpening.

The effects of Chinese proprietary medicine and vaccination on patients with COVID-19: a retrospective study in Macao.

BACKGROUND: COVID-19 is continuing to ravage globally and has resulted in a huge health and financial burden. Chinese proprietary medicines, such as Lianhua Qingwen (LHQW) and Huoxiang Zhengqi (HXZQ) capsules, have been recommended for non-high-risk patients with COVID-19 in China. Based on this, we described the baseline information, using status of LHQW and HXZQ capsules and inoculation history of quarantined patients in the second half of 2022 in Macao. Additionally, we analyzed the underlying association among medicines administration, vaccination and COVID-19 indices, in order to explore novel clues for the regular control and prevention of local epidemic situation in the future. METHODS: A total of 976 patients in Macao quarantine hotels from June to August 2022 were included in the present study, of which, 857 subjects were followed-up for prognosis evaluation. During quarantine, the baseline demographic information, including sex, age, BMI, occupation and personal habits were collected. Additionally, the inoculation history, medicine employment status and cycle threshold (Ct) values were also reported. We interviewed the patients for collection of their symptoms at the beginning and end of quarantine, as well as prognostic ones. Basic statistical description of baseline information, vaccination history and medication were displayed. Chi-squared test or with continuous correction test was employed for comparison of dichotomous data between two or multiple groups. Binary logistic regression was applied to reveal the correlation between potential risk factors and Ct values or prognosis symptoms. We also used Cox regression model to identify the effect of different types of vaccine products on Ct value altering rate. RESULTS: Patients who were female (52.0%), engaged in service industry (31.8%), from Macao native (65.8%), never took physical exercises (33.6%) and preferred irritated diet (59.5%) enjoyed more dominant proportions. Over 80% of participants were inoculated and 74.6% of them chose inactivated COVID-19 vaccine produced by China National Biotech Group (CNBG). Participants used LHQW capsules accounted for 92.1% and the duration of medicating lasted for one to two weeks. All of the reported symptoms were significantly ameliorated after quarantine and the duration of quarantine was concentrated on 21 days. People with different age, sex, occupation and region had different choices of HXZQ administration and vaccination. Additionally, middle dose (4-5 boxes) of LHQW capsules exhibited evidently negative association with positive Ct values (adjusted, - 0.037 ± 0.19, p = 0.04). Two doses of CNBG and one dose of mRNA vaccine had obvious protective effect on reducing Ct positive rate (p = 0.041). Meanwhile, symptoms after quarantine were significantly positive correlated with those in prognosis (adjusted, 1.38 ± 0.18, p < 0.0001). CONCLUSION: Our study found that the administration of LHQW capsules was beneficial for Ct value turning negative, meanwhile, certain mixed inoculation may be the promoting factor to reduce the positive rate of Ct value. These findings provide data basis for the Chinese proprietary medicine treatment and mixed vaccination applying for prevention and control of local COVID-19 epidemic in the future.

Incorporation of cellulose nanocrystals to improve the physicochemical and bioactive properties of pectin-konjac glucomannan composite films containing clove essential oil.

This study aimed to investigate the effectiveness of cellulose nanocrystals (CNC) isolated from cotton in augmenting pectin (PEC)/konjac glucomannan (KGM) composite films containing clove essential oil (CEO) for food packaging application. The effects of CNC dosage on film properties were examined by analyzing the rheology of film-forming solutions and the mechanical, barrier, antimicrobial, and CEO-release properties of the films. Rheological and FTIR analysis revealed the enhanced interactions among the film components after CNC incorporation due to its high aspect ratio and abundant hydroxyl groups, which can also prevent CEO droplet aggregation, contributing to form a compact microstructure as confirmed by SEM and 3D surface topography observations. Consequently, the addition of CNC reinforced the polysaccharide matrix, increasing the tensile strength of the films and improving their barrier properties to water vapor. More importantly, antibacterial, controlled release and kinetic simulation experiments proved that the addition of CNC could further slow down the release rate of CEO, prolonging the antimicrobial properties of the films. PEC/KGM/CEO composite films with 15 wt% CNC was found to have relatively best comprehensive properties, which was also most effective in delaying deterioration of grape quality during the storage of 9 days at 25 °C.

Advancing Precision: A Controllable Self-Synergistic Nanoplatform Initiating Pyroptosis-Based Immunogenic Cell Death Cascade for Targeted Tumor Therapy.

Heterogeneity of the tumor microenvironment (TME) is primarily responsible for ineffective tumor treatment and uncontrolled tumor progression. Pyroptosis-based immunogenic cell death (ICD) therapy is an ideal strategy to overcome TME heterogeneity and obtain a satisfactory antitumor effect. However, the efficiency of current pyroptosis therapeutics, which mainly depends on a single endogenous or exogenous stimulus, is limited by the intrinsic pathological features of malignant cells. Thus, it is necessary to develop a synergistic strategy with a high tumor specificity and modulability. Herein, a synergistic nanoplatform is constructed by combining a neutrophil camouflaging shell and a self-synergistic reactive oxygen species (ROS) supplier-loaded polymer. The covered neutrophil membranes endow the nanoplatform with stealthy properties and facilitate sufficient tumor accumulation. Under laser irradiation, the photosensitizer (indocyanine green) exogenously triggers ROS generation and converts the laser irradiation into heat to upregulate NAD(P)H:quinone oxidoreductase 1, which further catalyzes ß-Lapachone to self-produce sufficient endogenous ROS, resulting in amplified ICD outcomes. The results confirm that the continuously amplified ROS production not only eliminates the primary tumor but also concurrently enhances gasdermin E-mediated pyroptosis, initiates an ICD cascade, re-educates the heterogeneous TME, and promotes a systemic immune response to suppress distant tumors. Overall, this self-synergistic nanoplatform provides an efficient and durable method for redesigning the immune system for targeted tumor inhibition.