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Abstract The main advantages of microneedles are precise drug delivery through human skin, minimal tissue damage and painlessness. We conducted structural analysis and skin puncture studies of hollow microneedles using ANSYS for three materials: Hafnium Dioxide (HfO2), Polyglycolic acid (PGA) and Polylactic acid (PLA). Firstly, we selected three lengths, three tip diameters and three base diameters to conduct a L9(34) orthogonal experiment. Thus, we obtained nine different single-needle structures for each material, totaling 27 models for three materials. Subsequently, we investigated the stability and puncture properties of single needles. The optimal structures of the single-needle for three materials were same. Then, we used the optimal structure of the single-needle to establish the double-needle, triple-needle and five-needle models with ten different spacings. The simulations were carried out to examine the maximum stress during puncture. Finally, we investigated the hydrodynamic properties of water and lidocaine ibuprofen [Lid][Ibp] in the lumen of the microneedle. The results indicated that the optimal spacing of multi-needles varies depending on the material. The flow velocity of the fluid in the lumen is positively correlated with the pressure. Increasing the pressure can effectively reduce the flow velocity loss of low-viscosity fluid.

Abstract Background Primordial follicle activation is vital for the reproduction of women with advanced age and premature ovarian insufficiency (POI). But there is a lack of effective and safe therapeutic options to activate their primordial follicles in vivo. Berberine (BBR) possesses multiple pharmacological properties, but its impact on primordial follicle activation remains unclear. Methods The role of BBR on primordial activation was investigated by neonatal mouse ovary culture and intraperitoneal injection, and by human ovarian fragment culture. Furthermore, the effect of BBR on the quantity of ovulated oocytes was investigated by the intragastric administration of aged mice. Results BBR in vitro culture and in vivo intraperitoneal injection significantly increased growing follicle number and phosphorylated protein kinase B (p-Akt) levels in neonatal mouse ovaries. BBR also significantly increased the relative fluorescence intensities of p-Akt in the oocytes of primordial follicles. BBR-increased the number of growing follicles and the levels of p-Akt were blocked by LY294002, an inhibitor of phosphatidylinositol 3-kinase (PI3K). Furthermore, BBR intragastric administration significantly increased the quantity of ovulated oocytes in aged mice. Moreover, BBR significantly increased growing follicle proportion and p-Akt levels in cultured human ovarian fragments. Conclusion BBR promotes mouse and human primordial follicle activation through the PI3K/Akt pathway in oocytes, and improves the quantity of ovulated oocytes in aged mice. Our results suggest a potential use of oral medicine BBR to improve fertility in POI patients and aged women.

Grain refinement is the most common strategy to improve the mechanical performance of metals such as strength, wear resistance and fatigue. For the 2101 duplex stainless steel (DSS), a heterogeneous microstructure composed of sub-25 nm fiber grains and submicron elongated grains was successfully prepared by heavily drawing taking advantage of the heterogeneous microstructural design. The DSS possesses ultra-high strength of 3 GPa which is 15% higher than the reported that of DSS or a leading strength-ductility combination of 1.43 GPa and 17%. This study provides a strategy for heterogeneous microstructural design to achieve excellent mechanical performance, specifically high strength.

Abstract Background Research on low-protein-level diets has indicated that even though the profiles of essential amino acids (EAAs) follow the recommendation for a normal-protein-level diet, broilers fed low-protein diets failed to achieve productive performance compared to those fed normal diets. Therefore, it is imperative to reassess the optimum profile of EAAs in low-protein diets and establish a new ideal pattern for amino acid balance. Furthermore, identifying novel sensitive biomarkers for assessing amino acid balance will greatly facilitate the development of amino acid nutrition and application technology. In this study, 12 dietary treatments [Con(+), Con(-), L&A(-), L&A(+), M&C(-), M&C(+), BCAA (-), BCAA(+), Thr(-), Thr(+), Trp(-) and Trp(+)] were established by combining different EAAs including lysine and arginine, methionine and cysteine, branched-chain amino acid (BCAA), threonine, and tryptophan to observe the growth and development of the broiler chickens fed with low-protein-level diets. Based on the biochemical parameters and untargeted metabolomic analysis of animals subjected to different treatments, biomarkers associated with optimal and suboptimal amino acid balance were identified. Results Growth performance, carcass characteristics, hepatic enzyme activity, serum biochemical parameters, and breast muscle mRNA expression differed significantly between male and female broilers under different dietary amino acid patterns. Male broilers exhibited higher sensitivity to the adjustment of amino acid patterns than female broilers. For the low-protein diet, the dietary concentrations of lysine, arginine, and tryptophan, but not of methionine, cystine, or threonine, needed to be increased. Therefore, further research on individual BCAA is required. For untargeted metabolomic analysis, Con(+) was selected as a normal diet (NP) while Con(-) represented a low-protein diet (LP). L&A(+) denotes a low-protein amino acid balanced diet (LPAB) and Thr(+) represents a low-protein amino acid imbalance diet (LPAI). The metabolites oxypurinol, pantothenic acid, and D-octopine in birds were significantly influenced by different dietary amino acid patterns. Conclusion Adjusting the amino acid profile of low-protein diets is required to achieve normal growth performance in broiler chickens fed normal-protein diets. Oxypurinol, pantothenic acid, and D-octopine have been identified as potentially sensitive biomarkers for assessing amino acid balance.

Human reliability analysis (HRA) plays a vital role in probabilistic risk assessment (PRA) by quantifying the reliability and safety of complex technical systems through the estimation of human error probabilities (HEPs). Standardized plant analysis risk human (SPAR-H) reliability analysis is widely used for HRA; it adjusts the nominal HEP by assigning different multipliers to the performance shaping factors (PSFs). However, SPAR-H cannot capture the time-varying nature of HEPs; therefore, it cannot realistically respond to the accumulation and fluctuation of human risk factors across the mission. Hence, this study proposed a systematic method of dynamic HRA. It includes decision-making trial and evaluation laboratory-interpretative structural modeling (DEMATEL-ISM) to qualitatively and quantitatively analyze the hierarchical causality among the PSFs and their influence on each other based on their relative relationship in SPAR-H and construct hierarchical causality diagrams among the PSFs. Additionally, it uses a system dynamics method in conjunction with the analysis of time-dependent PSFs based on the hierarchical causality diagrams of PSFs to respond to the time-varying nature of HEPs. The simulation and rationale check results of the cases show that the proposed dynamic HRA method can realize a more realistic and dynamic estimation of HEPs.

This study investigated the optimal tannic acid dosage and assessed tolerance levels in broiler chickens. In experiment 1, 525 broilers were randomly divided into 5 treatment groups, the control group (CON group) and groups TA1 to TA4, corresponding to treatments of 0.025, 0.05, 0.075, and 0.1 % tannic acid, respectively, to determine the effect of tannic acid on broiler growth performance and gut health. Experiment 2 was performed to evaluate the tolerance of tannic acid; 416 broilers were randomly divided into control (CTR), 0.075 % tannic acid (TA), 0.375 % tannic acid (5TA), and 0.75 % tannic acid (10TA) groups. In the first experiment, compared with that in the CON group, the growth performance and the ileal intestinal villi height to crypt depth ratio showed a quadratic curve increase with tannic acid supplementation (P < 0.05). Adding 0.05 % to 0.075 % tannic acid significantly improved the growth performance, intestinal morphology, and intestinal barrier function (P < 0.05). Tannic acid concentrations of 0.075 % significantly increased the abundance of Firmicutes and Lactobacillaceae in the ileum and decreased the abundance of Vibrionaceae and Yersiniaceae (P < 0.05). In experiment 2, the growth performance of the TA group significantly improved compared with that of the CTR group (P < 0.05). The F/G was significantly higher in the 5TA and 10TA groups than in the CTR group (P < 0.05), and the 10TA group had significantly reduced body weight on d 21 (P < 0.05). The addition of tannic acid resulted in significant glomerular and glandular hyperplasia, as well as muscularis thickening of the gizzard mucosa. However, broilers could not tolerate tannic acid doses of 0.375 % and above. Tannic acid supplementation may protect the proventriculus mucosal layer, reduce villi atrophy, and enhance growth performance by positively influencing the intestinal microbiota, villus morphology, and intestinal barrier function.

Abstract The electrochemical conversion of CO2 into CO represents a promising strategy for mitigating excessive global greenhouse gas emissions. Nevertheless, achieving industrial‐scale electrochemical CO2‐to‐CO conversion with enhanced selectivity and reduced energy consumption presents significant challenges. In this study, a borate‐enhanced molten salt process for CO2 capture and electrochemical transformation is employed, achieving over 98% selectivity for CO and over 55% energy efficiency without the necessity for complex and costly electrocatalysts. Cathodic CO2 electro‐reduction (CO2ER) with the anodic oxygen evolution reaction (OER) at an overall current density of 500 mA cm−2 using non‐nanostructured transition‐metal plate electrodes at 650 °C is coupled. By regulating the electrolyte's oxo‐basicity with earth‐abundant borax (Na2B4O7), a borate‐enhanced electrolyte is established that accelerates the overall electrochemical reaction efficiently. This system involved a series of well‐designed target borate species (BO33−, BO2−, and B4O72−) that acted as mediators shuttling between the cathode and anode, favoring CO as the primary cathodic product. Manipulating the atmosphere above the anode facilitated a spontaneous transformation of borates, further enhancing OER performance with long‐term operational stability over a cumulative period of 50 h, while also reducing overall energy consumption. This work presents a cost‐effective strategy for the industrial‐scale production of CO derived from CO2, contributing to a lower carbon footprint by establishing a sustainable borate‐mediated closed loop.

Background The aim of this study was to investigate the impact of diabetes on mortality and adverse outcomes in COVID-19 patients and to analyse the associated risk factors. Methods This is a retrospective cohort study in 500 hospitalized patients with COVID-19 infection (214 with diabetes and 286 without diabetes) admitted to a tertiary hospital in China from December 2022 to February 2023. Demographic information, clinical characteristics and outcomes were collected. Survival status was investigated at discharge and at 6 months after discharge. Results The mortality rate of COVID-19 patients with diabetes was higher than the rate of non-diabetic COVID-19 patients, both at discharge, and at 6 months after discharge. Body mass index (BMI), C-reactive protein (CRP), pH, D-dimer, blood osmotic pressure, serum creatinine, white blood cell count, creatine kinase and hospitalization expenses were significantly different between diabetic group and non-diabetic group (p < 0.05). Compared with the survivors, non-survived COVID-19 patients with diabetes had worse diabetes control indicators, with random blood glucose increased by 3.58 mmol/L (p < 0.05), and fasting blood glucose increased by 2.77 mmol/L (p < 0.01). In addition, there were significant differences in age, heart rate, CRP, pH, potassium (K+), serum creatinine, white blood cell count, creatine kinase, the proportion with diabetic complications, treatment in ICU and mechanical ventilation between survivors and non-survivors of COVID-19 patients with diabetes. By multivariate logistic regression analysis, the death of COVID-19 patients with diabetes is positively correlated with age and CRP (p < 0.05), and has a trend towards significance with fasting blood glucose (p < 0.1). Conclusion Infection with COVID-19 on the basis of diabetes can significantly increase mortality, which was further associated with diabetes control indicators.

The standardized plant analysis risk human reliability analysis (SPAR-H) method is widely used for human reliability analysis to adjust the nominal human error probability (HEP) by assigning different multipliers to the performance shaping factors (PSFs). Nevertheless, SPAR-H suffers from assuming PSFs to be independent without considering any overlaps and dependencies. Therefore, this study introduces a new systematic method to analyze the relationships among the PSFs in SPAR-H qualitatively and quantitatively to obtain more reasonable HEP estimation results. The proposed method comprises three primary aspects: 1) a regularized autoencoder for the denoising and feature extraction of expert evaluation results, 2) the weighted influence non-linear gauge system-based adversarial interpretive structure modeling (WINGS-AISM) method to analyze the relationships among the PSFs and construct their causal hierarchy, and 3) a new relative weighting system to modify the PSF multipliers based on this hierarchy. The results of experiments comparing the proposed method with conventional methods highlight that our method effectively reduces the double counting of overlapping PSFs in SPAR-H, providing more reasonable and accurate HEP estimation results.

This study proposes a modified extended cognitive reliability and error analysis method (CREAM) for achieving a more accurate human error probability (HEP) in advanced control rooms. The traditional approach lacks failure data and does not consider the common performance condition (CPC) weights in different cognitive functions. The modified extended CREAM decomposes tasks using a method that combines structured information analysis (SIA) and the extended CREAM. The modified extended CREAM performs the weight analysis of CPCs in different cognitive functions, and the weights include cognitive, correlative, and important weights. We used the extended CREAM to obtain the cognitive weight. We determined the correlative weights of the CPCs for different cognitive functions using the triangular fuzzy decision-making trial and evaluation laboratory (TF-DEMATEL), and evaluated the importance weight of CPCs based on the interval 2-tuple linguistic approach and ensured the value of the importance weight using the entropy method in the different cognitive functions. Finally, we obtained the comprehensive weights of the different cognitive functions and calculated the HEPs. The accuracy and sensitivity of the modified extended CREAM were compared with those of the basic CREAM. The results demonstrate that the modified extended CREAM calculates the HEP more effectively in advanced control rooms.

Abstract Background The growth and yield of pepper, a typical temperature-loving vegetable, are limited by low-temperature environments. Using low-temperature sensitive ‘Hangjiao No. 4’ (Capsicum annuum L.) as experimental material, this study analyzed the changes in plant growth and photosynthesis under different treatments: normal control (NT), low-temperature stress alone (LT), low-temperature stress in strigolactone pretreated plants (SL_LT), and low-temperature stress in strigolactone biosynthesis inhibitor pretreated plants (Tis_LT). Results SL pretreatment increased the net photosynthetic rate (Pn) and PSII actual photochemical efficiency (φPSII), reducing the inhibition of LT on the growth of pepper by 17.44% (dry weight of shoot). Due to promoting the accumulation of carotenoids, such as lutein, and the de-epoxidation of the xanthophyll cycle [(Z + A)/(Z + A + V)] by strigolactone after long-term low-temperature stress (120 h), non-photochemical quenching (NPQ) of pepper was increased to reduce the excess excitation energy [(1-qP)/NPQ] and the photoinhibition degree (Fv/Fm) of pepper seedlings under long-term low-temperature stress was alleviated. Twelve cDNA libraries were constructed from pepper leaves by transcriptome sequencing. There were 8776 differentially expressed genes (DEGs), including 4473 (51.0%) upregulated and 4303 (49.0%) downregulated genes. Gene ontology pathway annotation showed that based on LT, the DEGs of SL_LT and Tis_LT were significantly enriched in the cellular component, which is mainly related to the photosystem and thylakoids. Further analysis of the porphyrin and chlorophyll biosynthesis, carotenoid biosynthesis, photosynthesis-antenna protein, and photosynthetic metabolic pathways and the Calvin cycle under low-temperature stress highlighted 18, 15, 21, 29, and 31 DEGs for further study, which were almost all highly expressed under SL_LT treatment and moderately expressed under LT treatment, whereas Tis_LT showed low expression. Conclusion The positive regulatory effect of SLs on the low-temperature tolerance of pepper seedlings was confirmed. This study provided new insights for the development of temperature-tolerant pepper lines through breeding programs.

Abstract Traditional coding methods based on graphics and digital or magnetic labels have gradually decreased their anti-counterfeiting because of market popularity. This paper presents a new magnetic anti-counterfeiting coding method. This method uses a high-performance coding material, which, along with small changes to the material itself and the particle size of the superparamagnetic nanomaterials, results in a large difference in the nonlinear magnetization response. This method, which adopts 12-site coding and establishes a screening model by measuring the voltage amplitude of 12-site variables, can code different kinds of products, establishing long-term stable coding and decoding means. Through the anti-counterfeiting experiment of wine, the experiment results show that the authenticity of the coded products can be verified using the self-developed magnetic encoding and decoding system. The new coding technology can verify the anti-counterfeiting of 9000 products, with a single detection accuracy of 97% and a detection time of less than one minute. Moreover, this coding method completely depends on the production batch of the superparamagnetic nanomaterials, which is difficult to imitate, and it provides a new coding anti-counterfeiting technology for related industries with a wide range of potential applications.

Abstract Background The contribution of cholinergic degeneration to gait disturbance in Parkinson’s disease (PD) is increasingly recognized, yet its relationship with dopaminergic-resistant gait parameters has been poorly investigated. We investigated the association between comprehensive gait parameters and cholinergic nucleus degeneration in PD. Methods This cross-sectional study enrolled 84 PD patients and 69 controls. All subjects underwent brain structural magnetic resonance imaging to assess the gray matter density (GMD) and volume (GMV) of the cholinergic nuclei (Ch123/Ch4). Gait parameters under single-task (ST) and dual-task (DT) walking tests were acquired using sensor wearables in PD group. We compared cholinergic nucleus morphology and gait performance between groups and examined their association. Results PD patients exhibited significantly decreased GMD and GMV of the left Ch4 compared to controls after reaching HY stage > 2. Significant correlations were observed between multiple gait parameters and bilateral Ch123/Ch4. After multiple testing correction, the Ch123/Ch4 degeneration was significantly associated with shorter stride length, lower gait velocity, longer stance phase, smaller ankle toe-off and heel-strike angles under both ST and DT condition. For PD patients with HY stage 1–2, there were no significant degeneration of Ch123/4, and only right side Ch123/Ch4 were corrected with the gait parameters. However, as the disease progressed to HY stage > 2, bilateral Ch123/Ch4 nuclei showed correlations with gait performance, with more extensive significant correlations were observed in the right side. Conclusions Our study demonstrated the progressive association between cholinergic nuclei degeneration and gait impairment across different stages of PD, and highlighting the potential lateralization of the cholinergic nuclei’s impact on gait impairment. These findings offer insights for the design and implementation of future clinical trials investigating cholinergic treatments as a promising approach to address gait impairments in PD.

Abstract Endothelins and their receptors, ETA and ETB, play vital roles in maintaining vascular homeostasis. Therapeutically targeting endothelin receptors, particularly through ETA antagonists, has shown efficacy in treating pulmonary arterial hypertension (PAH) and other cardiovascular- and renal-related diseases. Here we present cryo-electron microscopy structures of ETA in complex with two PAH drugs, macitentan and ambrisentan, along with zibotentan, a selective ETA antagonist, respectively. Notably, a specialized anti-ETA antibody facilitated the structural elucidation. These structures, together with the active-state structures of ET-1-bound ETA and ETB, and the agonist BQ3020-bound ETB, in complex with Gq, unveil the molecular basis of agonist/antagonist binding modes in endothelin receptors. Key residues that confer antagonist selectivity to endothelin receptors were identified along with the activation mechanism of ETA. Furthermore, our results suggest that ECL2 in ETA can serve as an epitope for antibody-mediated receptor antagonism. Collectively, these insights establish a robust theoretical framework for the rational design of small-molecule drugs and antibodies with selective activity against endothelin receptors.

Abstract In this study, the removal effect of a new MOF-on MOF adsorbent based on Cu–Co bimetallic organic frameworks on tetracycline antibiotics (TCs) in water system was studied. The adsorbent (Cu-MOF@Co-MOF) were synthesized by solvothermal and self-assembly method at different concentrations of Co2+/Cu2+. The characterization results of SEM, XRD, XPS, FTIR and BET indicated that the MOF-on MOF structure of Cu-MOF@Co-MOF exhibited the best recombination and physicochemical properties when the molar ratio of Co2+: Cu2+ is 5:1. In addition, the Cu-MOF@Co-MOF have a high specific surface area and bimetallic clusters, which can achieve multi-target synergistic adsorption of TCs. Based on above advantages, Cu-MOF@Co-MOF provided a strong affinity and could efficiently adsorb more than 80% of pollutants in just 5 to 15 min using only 10 mg of the adsorbent. The adsorption capacity of tetracycline and doxycycline was 434.78 and 476.19 mg/g, respectively, showing satisfactory adsorption performance. The fitting results of the experimental data were more consistent with the Langmuir isotherm model and pseudo-second-order kinetic model, indicating that the adsorption process of TC and DOX occurred at the homogeneous adsorption site and was mainly controlled by chemisorption. Thermodynamic experiments showed that Cu-MOF@Co-MOF was thermodynamically advantageous for the removal of TCs, and the whole process was spontaneous. The excellent adsorption capacity and rapid adsorption kinetics indicate the prepared MOF-on MOF adsorbent can adsorb TCs economically and quickly, and have satisfactory application prospects for removing TCs in practical environments. The results of the study pave a new way for preparing novel MOFs-based water treatment materials with great potential for efficient removal.

Many drugs have been discontinued during phase II/III breast cancer clinical trials due to lack of clinical efficacy, indicating shortcomings in predictive value of preclinical data. Nutrient availability in the tumour cell microenvironment and the dimensionality of in vitro tumour cells likely impact on drug responsiveness. Global proteomics experiments were conducted to assess the impact of nutrient availability and dimensionality of culture. Protein set enrichment analyses identified “pathways in cancer”, “focal adhesion” and “ECM receptor in interaction” related to cell culture dimensionality in MDA-MB-231 cells. In MCF-7 cells, 4 pathways were influenced by medium composition, and 2 pathways were influenced by cell culture dimensionality (2D vs. 3D). These pathways were also identified using KEGG analyses. Eight drugs were selected for investigation according to the differential expression of their putative or known target proteins. The influence of medium composition on drug effectiveness was explored using the “Melbourne Medium” (MM), developed to have nutritionally physiological levels of metabolites as compared with conventional (hyper-nutritional) cell culture medium (CM). The influence of dimensionality on drug effectiveness was also explored, using an innovative 3D viability assessment combining automated confocal microscopy and image analysis. Dimensionality of culture appeared to have a greater influence on the proteome and drug effects than variation in nutrient levels. The number of differentially expressed proteins in the different media was greater in 2D than 3D. We conclude that the risk of qualifying inactive compounds in preclinical assessment may be mitigated using additional models incorporating physiological media and 3-dimensionality.

Abstract Artificial ears with intelligence, which can sensitively detect sound—a variant of pressure—and generate consciousness and logical decision‐making abilities, hold great promise to transform life. However, despite the emerging flexible sensors for sound detection, most success is limited to very simple phonemes, such as a couple of letters or words, probably due to the lack of device sensitivity and capability. Herein, the construction of ultrasensitive artificial eardrums enabling intelligent song recognition is reported. This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 103 kPa−1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. The integrated device exhibits unparalleled (exceeding by 1–2 orders of magnitude compared with reported benchmark samples) sound detection sensitivity, and can accurately identify 100% (for training set) and 97.7% (for test set) of a database of the segments from 77 songs varying in language, style, and singer. Overall, the results highlight the outstanding performance of the hollow‐microstructure‐based sensor, indicating its potential applications in human–machine interaction and wearable acoustical technologies.

Due to the continuous production of industrial wastes and the excessive use of chemical fertilizers and pesticides, severe cadmium (Cd) pollution in soil has occurred globally. This study investigated the impacts of incorporating zinc oxide nanoparticles (ZnONPs) into hydroponically grown lettuce (Lactuca sativa) under cadmium stress conditions, to seek effective methods to minimize Cd buildup in green leafy vegetables. The results showed that 1 mg/L of Cd significantly inhibited lettuce growth, decreasing in leaves (29 %) and roots (33 %) biomass. However, when lettuce was exposed to 2.5 mg/L ZnONPs under cadmium stress, the growth, chlorophyll content, net photosynthetic rate (Pn), stomatal conductance (Gs), actual photochemical efficiency of PSII (φPSII), and activity of key enzymes in photosynthesis were all significantly enhanced. Furthermore, ZnONPs significantly decreased the accumulation of Cd in lettuce leaves (36 %) and roots (13 %). They altered the subcellular distribution and chemical morphology of Cd in lettuce by modifying the composition of cell walls (such as pectin content) and the levels of phenolic compounds, resulting in a reduction of 27 % in Cd translocation from roots to leaves. RNA sequencing yielded 45.9 × 107 and 53.4 × 107 clean reads from plant leaves and roots in control (T0), Cd (T1), Cd+ZnONPs (T2), and ZnONPs (T3) treatment groups respectively, and 3614 and 1873 differentially expressed genes (DEGs) were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis identified photosynthesis, carbon fixation, and phenylpropanoid metabolism as the main causes of ZnONPs-mediated alleviation of Cd stress in lettuce. Specifically, the DEGs identified included 12 associated with photosystem I, 13 with photosystem II and 23 DEGs with the carbon fixation pathway of photosynthesis. Additionally, DEGs related to phenylalanine ammonia-lyase, caffeoyl CoA 3-O-methyltransferase, peroxidase, 4-coumarate-CoA ligase, hydroxycinnamoyl transferase, and cytochrome P450 proteins were also identified. Therefore, further research is recommended to elucidate the molecular mechanisms by which ZnONPs reduce Cd absorption in lettuce through phenolic acid components in the phenylpropanoid metabolism pathway. Overall, treatments with ZnONPs are recommended to effectively reduce Cd accumulation in the edible portion of lettuce.

Abstract Non-coding RNAs (ncRNAs) are recognized as pivotal players in the regulation of essential physiological processes such as nutrient homeostasis, development, and stress responses in plants. Common methods for predicting ncRNAs are susceptible to significant effects of experimental conditions and computational methods, resulting in the need for significant investment of time and resources. Therefore, we constructed an ncRNA predictor(MFPINC), to predict potential ncRNA in plants which is based on the PINC tool proposed by our previous studies. Specifically, sequence features were carefully refined using variance thresholding and F-test methods, while deep features were extracted and feature fusion were performed by applying the GRU model. The comprehensive evaluation of multiple standard datasets shows that MFPINC not only achieves more comprehensive and accurate identification of gene sequences, but also significantly improves the expressive and generalization performance of the model, and MFPINC significantly outperforms the existing competing methods in ncRNA identification. In addition, it is worth mentioning that our tool can also be found on Github ( https://github.com/Zhenj-Nie/MFPINC ) the data and source code can also be downloaded for free.

Abstract To study the characteristics of nasal airflow in the presence of nasal cycle by computational fluid dynamics. CT scan data of a healthy Chinese individual was used to construct a three-dimensional model of the nasal cavity to be used as simulation domain. A sinusoidal airflow velocity is set at the nasal cavity entrance to reproduce the breathing pattern of a healthy human. There was a significant difference in the cross-sectional area between the two sides of the nasal cavity. Particularly, the decongested side is characterized by a larger cross-section area, and consequently, by a larger volume with respect to the congested side. The airflow velocity, pressure, and nasal resistance were higher on the congested narrow side. The temperature regulation ability on the congested narrow side was stronger than that on the decongested wider side. During the nasal cycle, there are differences in the nasal cavity function between the congested and decongested sides. Therefore, when evaluating the impact of various factors on nasal cavity function, the nasal cycle should be considered.

Highlights Evaporation and solution two-step hybrid process are used to fabricate conformal growth of perovskite film on textured silicon substrates. F-PMAI additive enlarged the perovskite grains, induced the (111) preferred orientation and passivated interface defects. We obtained a champion efficiency of 30.05% for a monolithic perovskite/silicon tandem solar cell based on a silicon thin film tunneling junction.

Abstract Background Sensor-based gait analysis provides a robust quantitative tool for assessing gait impairments and their associated factors in Parkinson’s disease (PD). Anxiety is observed to interfere with gait clinically, but this has been poorly investigated. Our purpose is to utilize gait analysis to uncover the effect of anxiety on gait in patients with PD. Methods We enrolled 38 and 106 PD patients with and without anxiety, respectively. Gait parameters were quantitively examined and compared between two groups both in single-task (ST) and dual-task (DT) walking tests. Multiple linear regression was applied to evaluate whether anxiety independently contributed to gait impairments. Results During ST, PD patients with anxiety presented significantly shorter stride length, lower gait velocity, longer stride time and stance time, longer stance phase, smaller toe-off (TO) and heel-strike (HS) angles than those without anxiety. While under DT status, the differences were diminished. Multiple linear regression analysis demonstrated that anxiety was an independent factor to a serials of gait parameters, particularly ST-TO (B = -2.599, (-4.82, -0.38)), ST-HS (B = -2.532, (-4.71, -0.35)), ST-TO-CV (B = 4.627, (1.71, 7.64)), ST-HS-CV(B = 4.597, (1.66, 7.53)), ST stance phase (B = 1.4, (0.22, 2.58)), and DT stance phase (B = 1.749, (0.56, 2.94)). Conclusion Our study discovered that anxiety has a significant impact on gait impairments in PD patients, especially exacerbating shuffling steps and prolonging stance phase. These findings highlight the importance of addressing anxiety in PD precision therapy to achieve better treatment outcomes.

Dendrobium, a genus of orchids celebrated for their ornamental, medicinal, and culinary uses, is the focus of this study, which examines the metabolite profiles and bioactivity of five species: Dendrobium officinale, Dendrobium nobile, Dendrobium crepidatum, Dendrobium chrysotoxum, and Dendrobium denneanum. Utilizing UPLC-Q-TOF-MSE analysis, we have identified 88 compounds from the stems and leaves of these species. Notably, extracts from D. denneanum and D. chrysotoxum exhibited the highest antioxidant activities as demonstrated by DPPH, ABTS radical scavenging, and FRAP assays. Additionally, D. officinale showed significant anti-hepatoma activity with an IC50 value of 104 μg/mL. Multivariate analysis, hierarchical cluster analysis, and metabolites correlation analysis further elucidated the bioactive potential of these species. This comprehensive approach revealed distinct metabolite profiles that correlate with the observed bioactivities. The antioxidant activities of D. denneanum and D. chrysotoxum were particularly noteworthy, suggesting their potential as natural sources of antioxidants for pharmaceutical and nutraceutical applications. The anti-hepatoma activity of D. officinale, with its notable IC50 value, indicates its promise as a therapeutic agent against liver cancer. The findings underscore the richness of bioactive compounds in Dendrobium species, highlighting their antioxidant and anti-hepatoma properties. These insights pave the way for further research into the medicinal utilization of Dendrobium leaves and contribute to the development of novel applications in healthcare and wellness industries. The potential health benefits identified in this research emphasize the importance of preserving and studying these valuable plant species for their diverse bioactivities.

Abstract Background Mutations in several translation initiation factors are closely associated with premature ovarian insufficiency (POI), but the underlying pathogenesis remains largely unknown. Methods and results We generated eukaryotic translation initiation factor 5 (Eif5) conditional knockout mice aiming to investigate the function of eIF5 during oocyte growth and follicle development. Here, we demonstrated that Eif5 deletion in mouse primordial and growing oocytes both resulted in the apoptosis of oocytes within the early‐growing follicles. Further studies revealed that Eif5 deletion in oocytes downregulated the levels of mitochondrial fission‐related proteins (p‐DRP1, FIS1, MFF and MTFR) and upregulated the levels of the integrated stress response‐related proteins (AARS1, SHMT2 and SLC7A1) and genes (Atf4, Ddit3 and Fgf21). Consistent with this, Eif5 deletion in oocytes resulted in mitochondrial dysfunction characterized by elongated form, aggregated distribution beneath the oocyte membrane, decreased adenosine triphosphate content and mtDNA copy numbers, and excessive accumulation of reactive oxygen species (ROS) and mitochondrial superoxide. Meanwhile, Eif5 deletion in oocytes led to a significant increase in the levels of DNA damage response proteins (γH2AX, p‐CHK2 and p‐p53) and proapoptotic proteins (PUMA and BAX), as well as a significant decrease in the levels of anti‐apoptotic protein BCL‐xL. Conclusion These findings indicate that Eif5 deletion in mouse oocytes results in the apoptosis of oocytes within the early‐growing follicles via mitochondrial fission defects, excessive ROS accumulation and DNA damage. This study provides new insights into pathogenesis, genetic diagnosis and potential therapeutic targets for POI. Key points Eif5 deletion in oocytes leads to arrest in oocyte growth and follicle development. Eif5 deletion in oocytes impairs the translation of mitochondrial fission‐related proteins, followed by mitochondrial dysfunction. Depletion of Eif5 causes oocyte apoptosis via ROS accumulation and DNA damage response pathway.

BackgroundAccumulating evidence has linked dyslipidemia during pregnancy to the risk of delivering infants born either large for gestational age (LGA) or small for gestational age (SGA). However, the effects of the vitamin D status on these relationships require further investigation. This study investigated whether the relationship between lipid profiles and the risk of LGA or SGA was influenced by vitamin D levels during the second trimester.MethodsMaternal lipid profile levels, including total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and vitamin D levels, were measured in a cohort of 6,499 pregnant women during the second trimester. Multivariate regression models and subgroup analyses were employed to evaluate the potential associations between maternal lipid profiles, vitamin D levels, and the risk of LGA or SGA.ResultsThe prevalence of SGA infants was 9.8% (n=635), whereas that of LGA infants was 6.9% (n=447). Maternal TG levels were found to be positively associated with the risk of LGA (odds ratio [OR] = 1.41, 95% confidence interval [CI]:1.17–1.70), whereas a negative association was observed between maternal TG, TC, LDL-C levels, and risk of SGA. Additionally, mothers with higher HDL-C levels were less likely to give birth to an LGA infant (OR=0.58, 95% CI:0.39–0.85). Importantly, associations between TG, TC, LDL-c, and SGA as well as between TG and LGA were primarily observed among pregnant women with insufficient vitamin D levels. As for HDL-C, the risk of LGA was lower in mothers with sufficient vitamin D (OR = 0.42, 95% CI:0.18–0.98) compared to those with insufficient vitamin D (OR = 0.65, 95% CI:0.42–0.99).ConclusionVitamin D status during the second trimester exerts a modifying effect on the association between lipid profiles and the risk of LGA and SGA infants.

BackgroundIgA nephropathy (IgAN) is a significant contributor to chronic kidney disease (CKD). Renal arteriolar damage is associated with IgAN prognosis. However, simple tools for predicting arteriolar damage of IgAN remain limited. We aim to develop and validate a nomogram model for predicting renal arteriolar damage in IgAN patients.MethodsWe retrospectively analyzed 547 cases of biopsy-proven IgAN patients. Least absolute shrinkage and selection operator (LASSO) regression and logistic regression were applied to screen for factors associated with renal arteriolar damage in patients with IgAN. A nomogram was developed to evaluate the renal arteriolar damage in patients with IgAN. The performance of the proposed nomogram was evaluated based on a calibration plot, ROC curve (AUC) and Harrell’s concordance index (C-index).ResultsIn this study, patients in the arteriolar damage group had higher levels of age, mean arterial pressure (MAP), serum creatinine, serum urea nitrogen, serum uric acid, triglycerides, proteinuria, tubular atrophy/interstitial fibrosis (T1–2) and decreased eGFR than those without arteriolar damage. Predictors contained in the prediction nomogram included age, MAP, eGFR and serum uric acid. Then, a nomogram model for predicting renal arteriolar damage was established combining the above indicators. Our model achieved well-fitted calibration curves and the C-indices of this model were 0.722 (95%CI 0.670–0.774) and 0.784 (95%CI 0.716–0.852) in the development and validation groups, respectively.ConclusionWith excellent predictive abilities, the nomogram may be a simple and reliable tool to predict the risk of renal arteriolar damage in patients with IgAN.

Abstract INTRODUCTION Mild cognitive impairment (MCI) is a significant public health concern and a potential precursor to Alzheimer's disease (AD). This study leverages electronic health record (EHR) data to explore rural‐urban differences in MCI incidence, risk factors, and healthcare navigation in West Michigan. METHODS Analysis was conducted on 1,528,464 patients from Corewell Health West, using face‐to‐face encounters between 1/1/2015 and 7/31/2022. MCI cases were identified using International Classification of Diseases (ICD) codes, focusing on patients aged 45+ without prior MCI, dementia, or AD diagnoses. Incidence rates, cumulative incidences, primary care physicians (PCPs), and neuropsychology referral outcomes were examined across rural and urban areas. Risk factors were evaluated through univariate and multivariate Cox regression analyses. The geographic distribution of patient counts, hospital locations, and neurology department referrals were examined. RESULTS Among 423,592 patients, a higher MCI incidence rate was observed in urban settings compared to rural settings (3.83 vs. 3.22 per 1,000 person‐years). However, sensitivity analysis revealed higher incidence rates in rural areas when including patients who progressed directly to dementia. Urban patients demonstrated higher rates of referrals to and completion of neurological services. While the risk factors for MCI were largely similar across urban and rural populations, urban‐specific factors for incident MCI are hearing loss, inflammatory bowel disease, obstructive sleep apnea, insomnia, being African American, and being underweight. Common risk factors include diabetes, intracranial injury, cerebrovascular disease, coronary artery disease, stroke, Parkinson's disease, epilepsy, chronic obstructive pulmonary disease, depression, and increased age. Lower risk was associated with being female, having a higher body mass index, and having a higher diastolic blood pressure. DISCUSSION This study highlights rural‐urban differences in MCI incidence and access to care, suggesting potential underdiagnosis in rural areas likely due to reduced access to specialists. Future research should explore socioeconomic, environmental, and lifestyle determinants of MCI to refine prevention and management strategies across geographic settings. Highlights Leveraged EHRs to explore rural‐urban differences in MCI in West Michigan. Revealed a significant underdiagnosis of MCI, especially in rural areas. Observed lower rates of neurological referrals and completions for rural patients. Identified risk factors specific to rural and urban populations.

This experiment aimed to discuss and reveal the effect and mechanism of mannanase on intestinal inflammation in broilers triggered by a soybean meal diet. In this experiment, 384 Arbor Acres broilers at 1 d old were randomly divided into 3 treatment groups. The broilers were fed a corn-soybean meal basal diet, a low-energy diet (metabolizable energy reduced by 50 kcal/kg), and a low-energy diet supplemented with 100 mg/kg mannanase for 42 d. The low-energy diet increased feed conversion ratio from 0 to 42 d, reduced ileal villus height and villus height-to-crypt depth ratio and upregulated the expression of nuclear factor kappa B (NF-κB) in the ileum (P

Asymmetric rolling is beneficial for grain refinement and properties improvement through mass production of metals. This study introduces a novel asymmetric rolling technology, known as dynamic offsets and shear force adjustment (DS) rolling. DS rolling not only achieves roll offset and differential speed/diameter, but maintains a constant offset angle in multiple passes. And rolling mechanics model, finite element model, and rolling experiment is established. The results indicate the advantages of DS rolling in reducing the vertical rolling force with increasing offset angles. Moreover, it is observed that the vertical rolling force initially decreases and subsequently increases as the roll-to-diameter ratio increases. DS rolling enhances both average strain and core strain compared to symmetrical rolling, consequently promoting uniformity in strain distribution and permeability into the core region. The shear stress is the primary factor contributing to the increase in equivalent strain during DS rolling. The adjustment of roller diameter ratio and offset angle allows for control over the shear stress level. DS rolling enhances mechanical properties and refines the grain structure. Notably, at an offset angle of 9°, DS rolling results in a substantial increase in microhardness on the upper surface, center, and lower surface of Cu by 3.31 %, 8.40 %, and 8.19 %, respectively, when compared to symmetrical rolling. Furthermore, DS rolling exhibits an enhanced tensile strength and elongation, yielding improvements of 5.12 % and 38.9 % compared to symmetrical rolling, respectively. Additionally, DS rolling leads to a reduction in grain size by 5.77 %, 17.3 %, and 21.7 % on the upper surface, center, and lower surface, respectively.

Abstract Background Dental pulp stem cells (DPSCs) are a kind of undifferentiated dental mesenchymal stem cells with strong self-renewal ability and multi-differentiation potential. This study aimed to investigate the regulatory functions of succinylation modification in DPSCs. Methods DPSCs were isolated from the dental pulp collected from healthy subjects, and then stem cell surface markers were identified using flow cytometry. The osteogenic differentiation ability of DPSCs was verified by alkaline phosphatase (ALP) and alizarin red staining methods, while adipogenic differentiation was detected by oil red O staining. Meanwhile, the mRNA of two desuccinylases (SIRT5 and SIRT7) and three succinylases (KAT2A, KAT3B, and CPT1A) in DPSCs before and after mineralization induction were detected using quantitative real-time PCR. The cell cycle was measured by flow cytometry, and the expression of bone-specific genes, including COL1a1 and Runx2 were evaluated by western blotting and were combined for the proliferation and differentiation of DPSCs. Co-immunoprecipitation (co-IP) and immunofluorescence were combined to verify the binding relationship between proteins. Results The specific markers of mesenchymal stem cells were highly expressed in DPSCs, while the osteogenic differentiation ability of isolated DPSCs was confirmed via ALP and alizarin red staining. Similarly, the oil red O staining also verified the adipogenic differentiation ability of DPSCs. The levels of KAT2A were found to be significantly upregulated in mineralization induction, which significantly decreased the ratio of G0/G1 phase and increased S phase cells; converse results regarding cell cycle distribution were obtained when KAT2A was inhibited. Moreover, overexpression of KAT2A promoted the differentiation of DPSCs, while its inhibition exerted the opposite effect. The elevated KAT2A was found to activate the Notch1 signaling pathway, which succinylated Notch1 at the K2177 site to increase their corresponding protein levels in DPSCs. The co-IP results showed that KAT2A and Notch1 were endogenously bound to each other, while inhibition of Notch1 reversed the effects of KAT2A overexpression on the DPSCs proliferation and differentiation. Conclusion KAT2A interacted directly with Notch1, succinylating the Notch1 at the K2177 site to increase their corresponding protein levels in DPSCs. Similarly, KAT2A-mediated succinylation modification of Notch1 promotes the DPSCs proliferation and differentiation, suggesting that targeting KAT2A and Notch1 may contribute to tooth regeneration.

Abstract Background More and more studies show that miRNA plays a crucial role in plants' response to different abiotic stresses. However, traditional experimental methods are often expensive and inefficient, so it is important to develop efficient and economical computational methods. Although researchers have developed machine learning-based method, the information of miRNAs and abiotic stresses has not been fully exploited. Therefore, we propose a novel approach based on graph neural networks for predicting potential miRNA-abiotic stress associations. Results In this study, we fully considered the multi-source feature information from miRNAs and abiotic stresses, and calculated and integrated the similarity network of miRNA and abiotic stress from different feature perspectives using multiple similarity measures. Then, the above multi-source similarity network and association information between miRNAs and abiotic stresses are effectively fused through heterogeneous networks. Subsequently, the Restart Random Walk (RWR) algorithm is employed to extract global structural information from heterogeneous networks, providing feature vectors for miRNA and abiotic stress. After that, we utilized the graph autoencoder based on GIN (Graph Isomorphism Networks) to learn and reconstruct a miRNA-abiotic stress association matrix to obtain potential miRNA-abiotic stress associations. The experimental results show that our model is superior to all known methods in predicting potential miRNA-abiotic stress associations, and the AUPR and AUC metrics of our model achieve 98.24% and 97.43%, respectively, under five-fold cross-validation. Conclusions The robustness and effectiveness of our proposed model position it as a valuable approach for advancing the field of miRNA-abiotic stress association prediction.

Abstract Background Current studies have shown that longer observation time can improve neoplastic detection rate. This study aimed to clarify whether endoscopists with longer observation times can detect more focal lesions. Methods Based on the mean examination time for Esophagogastroduodenoscopy (EGD) without biopsy, endoscopists were divided into fast and slow groups, and the detection rate of focal lesions was compared between the two groups. Univariate analysis, multivariate analysis and restricted cubic spline were used to explore the factors of focal lesion detection rate. Results Mean examination time of EGD without biopsy was 4.5 min. The cut-off times used were 5 min. 17 endoscopists were classified into the fast (4.7 ± 3.6 min), and 16 into the slow (7.11 ± 4.6 min) groups. Compared with fast endoscopists, slow endoscopists had a higher detection rate of focal lesions (47.2% vs. 51.4%, P

The objective of EEG-based emotion recognition is to classify emotions by decoding signals, with potential applications in the fields of artificial intelligence and bioinformatics. Cross-subject emotion recognition is more difficult than intra-subject emotion recognition. The poor adaptability of classification model parameters is a significant factor of low accuracy in cross-subject emotion recognition. We propose a model of a dynamically optimized Random Forest based on the Sparrow Search Algorithm (SSA-RF). The decision trees number (DTN) and the leave minimum number (LMN) of the RF are dynamically optimized by the SSA. 12 features are used to construct feature combinations for selecting the optimal feature combination. DEAP and SEED datasets are employed for testing the performance of SSA-RF. The experimental results show that the accuracy of binary classification is 76.81% on DEAP, and the accuracy of triple classification is 75.96% on SEED based on SSA-RF, which are both higher than that of traditional RF. This study provides new insights for the development of cross-subject emotion recognition, and has significant theoretical value.

Parkinson's disease is a common neurodegenerative disorder that is associated with abnormal aggregation and accumulation of neurotoxic proteins, including α-synuclein, amyloid-β, and tau, in addition to the impaired elimination of these neurotoxic protein. Atypical parkinsonism, which has the same clinical presentation and neuropathology as Parkinson's disease, expands the disease landscape within the continuum of Parkinson's disease and related disorders. The glymphatic system is a waste clearance system in the brain, which is responsible for eliminating the neurotoxic proteins from the interstitial fluid. Impairment of the glymphatic system has been proposed as a significant contributor to the development and progression of neurodegenerative disease, as it exacerbates the aggregation of neurotoxic proteins and deteriorates neuronal damage. Therefore, impairment of the glymphatic system could be considered as the final common pathway to neurodegeneration. Previous evidence has provided initial insights into the potential effect of the impaired glymphatic system on Parkinson's disease and related disorders; however, many unanswered questions remain. This review aims to provide a comprehensive summary of the growing literature on the glymphatic system in Parkinson's disease and related disorders. The focus of this review is on identifying the manifestations and mechanisms of interplay between the glymphatic system and neurotoxic proteins, including loss of polarization of aquaporin-4 in astrocytic endfeet, sleep and circadian rhythms, neuroinflammation, astrogliosis, and gliosis. This review further delves into the underlying pathophysiology of the glymphatic system in Parkinson's disease and related disorders, and the potential implications of targeting the glymphatic system as a novel and promising therapeutic strategy.

To bolster their competitiveness and profitability, prominent e-commerce platforms have embraced dual retailing channels: self-operating channels and online marketplaces. However, a discernible trend is emerging wherein e-commerce platforms are expanding their marketplaces to encompass competitive third-party suppliers. Motivated by this trend, this study sought to examine the strategic integration of a third-party product amidst the competition between a self-operating channel and a marketplace. This investigation involved the development of a game-theoretic model involving a platform and two representative suppliers—an incumbent supplier and a new entrant. Specifically, we delved into establishing an equilibrium partnership between the platform and the new entrant supplier while also evaluating the self-operating strategy of the established supplier. Our analysis uncovered a counterintuitive outcome: an escalation in the commission rate resulted in diminished profits for the established supplier. Furthermore, we ascertained that the economic implications of a competitive product entry pivot significantly on product quality. Lastly, we demonstrated that the revenue-sharing rate plays a pivotal role in influencing the self-operating strategy of the established supplier, and the market equilibrium hinges on the interplay among product quality, the commission rate, and the revenue-sharing rate. These insights provide invaluable guidance for marketers and e-commerce platforms in their strategic decision-making processes.

Fast nanoindentation technology is a new method used to generate performance maps showing the hardness and elastic modulus distribution of each position, and it has become a research focus. In this paper, nanoindentation combined with scanning electron backscatter diffraction (EBSD) is used to analyze the micro-regional properties of single-phase interstitial-free (IF) steel. Hardness, elastic modulus and the orientation of a 200 μm × 200 μm area were characterized in situ. The relationships between hardness, elastic modulus and orientation were analyzed. The experimental results showed that the hardness varied from 1.25 GPa to 2.57 GPa, while the modulus varied from 122 GPa to 227 GPa with different crystallographic orientations. The hardness value of the (111) crystal plane was particularly high, with an average hardness of about 1.84 GPa, which is due to its higher work hardening rate. This result is consistent with the EBSD kernel average misorientation (KAM) micrograph. The harder locations with greater misorientation are more difficult to deform compared to locations with small hardness regions, for example, the (001) crystal plane. However, there seems to be no obvious strong relationship between modulus and orientation. The modulus of the regions with lower hardness seems to be smaller. The results of the KAM diagram are consistent with those of hardness mapping.

Super-resolution (SR) of remote sensing images is essential to compensate for missing information in the original high-resolution (HR) images. Single-image super-resolution (SISR) technique aims to recover high-resolution images from low-resolution (LR) images. However, traditional SISR methods often result in blurred and unclear images due to the loss of high-frequency details in LR images at high magnifications. In this paper, a super-segmental reconstruction model STGAN for remote sensing images is proposed, which fuses the Generative Adversarial Networks (GANs) and self-attention mechanism based on the Reference Super Resolution method (RefSR). The core module of the model consists of multiple CNN-Swin Transformer blocks (MCST), each of which consists of a CNN layer and a specific modified Swin Transformer, constituting the feature extraction channel. In image hypersegmentation reconstruction, the optimized and improved correlation attention block (RAM-V) uses feature maps and gradient maps to improve the robustness of the model under different scenarios (such as land cover change). The experimental results show that the STGAN model proposed in this paper exhibits the best image data perception quality results with the best performance of LPIPS and PI metrics in the test set under RRSSRD public datasets. In the experimental test set, the PSNR reaches 31.4151, the SSIM is 0.8408, and the performance on the RMSE and SAM metrics is excellent, which demonstrate the model’s superior image reconstruction details in super-resolution reconstruction and highlighting the great potential of RefSR’s application to the task of super-scalar processing of remotely sensed images.

Integrated sensing and communication (ISAC) is considered a key technology supporting Beyond-5G/6G (B5G/6G) networks, which allows the spectrum resources to be used for both sensing and communication. In this paper, we investigate an unmanned aerial vehicle (UAV)-enabled ISAC scenario, where the UAV sends ISAC signals to communicate with multiple users (UEs) and senses potential targets simultaneously, and a reconfigurable intelligent surface (RIS) is deployed to enhance the communication performance. Aiming at maximizing the sum-rate throughput of the system, we formulate the joint optimization problem of the trajectory and the beamforming matrix of the UAV, the passive beamforming matrix of the RIS. Currently, many researchers are working on using deep reinforcement learning (DRL) to address such problems due to its non-convex nature; however, as the environment becomes increasingly complex, high-dimensional state space and action space lead to a decrease in the performance of DRL. To tackle this issue, we propose a novel hierarchical deep reinforcement learning (HDRL) framework to solve the optimization problem. Through decomposing the original problem into the trajectory optimization problem and the sum-rate throughput optimization problem, we adopt a hierarchical twin-delayed deep deterministic policy gradient (HTD3) structure to optimize them alternately. The experimental results demonstrate that the obtained system sum-rate throughputs of the proposed HDRL with an HTD3 structure are 33%, 50%, and 10% higher than those obtained by TD3, twin-TD3 (TTD3), and TD3 with hovering only (TD3HO), respectively.

Traffic flow forecasting is crucial for improving urban traffic management and reducing resource consumption. Accurate traffic conditions prediction requires capturing the complex spatial-temporal dependencies inherent in traffic data. Traditional spatial-temporal graph modeling methods often rely on fixed road network structures, failing to account for the dynamic spatial correlations that vary over time. To address this, we propose a Transformer-Enhanced Adaptive Graph Convolutional Network (TEA-GCN) that alternately learns temporal and spatial correlations in traffic data layer-by-layer. Specifically, we design an adaptive graph convolutional module to dynamically capture implicit road dependencies at different time levels and a local-global temporal attention module to simultaneously capture long-term and short-term temporal dependencies. Experimental results on two public traffic datasets demonstrate the effectiveness of the proposed model compared to other state-of-the-art traffic flow prediction methods.

Background/Objectives: Numerical simulation plays an important role in pharmaceutical preparation recently. Mechanistic models, as a type of numerical model, are widely used in the study of pharmaceutical preparations. Mechanistic models are based on a priori knowledge, i.e., laws of physics, chemistry, and biology. However, due to interdisciplinary reasons, pharmacy researchers have greater difficulties in using computer models. Methods: In this paper, we highlight the application scenarios and examples of mechanistic modelling in pharmacy research and provide a reference for drug researchers to get started. Results: By establishing a suitable model and inputting preparation parameters, researchers can analyze the drug preparation process. Therefore, mechanistic models are effective tools to optimize the preparation parameters and predict potential quality problems of the product. With product quality parameters as the ultimate goal, the experiment design is optimized by mechanistic models. This process emphasizes the concept of quality by design. Conclusions: The use of numerical simulation saves experimental cost and time, and speeds up the experimental process. In pharmacy experiments, part of the physical information and the change processes are difficult to obtain, such as the mechanical phenomena during tablet compression and the airflow details in the nasal cavity. Therefore, it is necessary to predict the information and guide the formulation with the help of mechanistic models.

Given the key role of methionine in biological processes, adequate methionine should be provided to meet the nutritional requirements. DL-2-hydroxy-4-(methylthio)-butanoic acid (DL-HMTBA) has been considered as an important source of methionine. However, the effects of different sources and levels of methionine on the intestinal health status have not been clarified yet. An experiment was carried out to investigate the effects of different dietary sources and levels of methionine on the intestinal epithelial barrier, inflammatory cytokines expression, ileal morphology, microbiota composition, and cecal short chain fatty acids (SCFA) profiles. For this purpose, 720 male Arbor Acre broiler chicks at 1 d old were randomly assigned to a 2 × 3 factorial arrangement with 2 methionine sources (DL-methionine and DL-HMTBA) and 3 total sulfur amino acids (TSAA) levels (80%, 100%, and 120% of Arbor Acre recommendation). The results showed that DL-HMTBA supplementation promoted intestinal physical barrier at both gene expression level of claudin-1 and serum diamine oxidase level (P

Abstract Background Most studies initiated basal-bolus insulin in a ratio of 1:1 and titrated based on glucose. This study aimed to investigate the effectiveness and safety of a weight-based and ratio of 1:1.5 basal-bolus insulin using an algorithm for both initiation and titration in hospitalized patients with type 2 diabetes (T2D). Methods Hospitalized patients with T2D were randomly assigned to two groups in equal numbers to receive 1:1.5 and 1:1 ratios of basal-bolus insulin using a weight-based algorithm for both initiation and titration. The primary outcome was the time taken to reach the fasting blood glucose (FBG) target and 2-h postprandial blood glucose (2hBG) targets after three meals. The secondary outcome included insulin dosage to achieve glycemic control and the incidence of hypoglycemia during hospitalization. Results 250 patients were screened between October 2021 and June 2022, 220 were randomly grouped, and 182 completed the trial (89 in the 1:1.5 and 93 in the 1:1 groups). The time taken to reach FBG targets was comparable between the two groups (3.4 ± 1.7 vs. 3.0 ± 1.3 days, p = 0.137) within about 3 days. The 2hBG after three meals was shorter in the 1:1.5 group than in the 1:1group (2.9 ± 1.5 vs. 3.4 ± 1.4 days, p = 0.015 for breakfast, 3.0 ± 1.6 vs. 3.6 ± 1.4 days, p = 0.005 for lunch, and 3.1 ± 2.1 vs. 4.0 ± 1.5 days, p = 0.002 for dinner). No significant difference in insulin dosages was found between the two groups at the end of the study. The incidence of hypoglycemia was similar in both groups. Conclusions We demonstrated that fixed dose-ratio basal-bolus insulin at 1:1.5 calculated using a weight-based initiation and titration algorithm was simple, as effective, and safe as ratio at 1:1 in managing T2D in hospitalized patients. Trial Registration ChiCTR 2,100,050,963. Date of registration: September 8, 2021.

Abstract Perovskite/silicon tandem solar cells (PK/Si TSCs) blaze the way in pushing power conversion efficiency (PCE) beyond the single‐junction Shockley–Queisser limit. Meanwhile, localized defects in perovskite subcells result in a lower fill factor (FF), which limits further improvement of PCE in PK/Si TSCs. Herein, we report a conductive passivation contact layer by posttreatment of bis(2‐hydroxyethyl)dimethylammonium chloride (BDAC) zwitterion molecule on the perovskite surface. It can passivate the positive and negative localized defects, inhibit the formation of Pb0, and spontaneously convert the perovskite surface to be a more n‐type conductive contact layer for charge separation. These combined enhancements enabled a PCE of 21.4% with an enhanced VOC of 80 mV and an FF of 82.84% for the inverted single‐junction device prepared by the two‐step method. Moreover, BDAC passivation achieved a PCE of 28.67% with an FF of 80.02% for PK/Si TSCs. In addition, the scaling‐up device with an active area of 11.879 cm2 delivers a PCE of 24.46%, and a minimodule with power conversion over 2 W is designed and fabricated.

To further improve the yield of pectinase, the fermentation medium and fermentation conditions for pectinase production by Bacillus subtilis Z-5 were optimized using the response surface methodology, and the optimized pectinase was applied for the clarification of pear juice. Based on the single-factor experiments, the Plackett-Burman test design was applied to screen out three significant factors affecting enzyme production: Yeast powder content, pH and incubation time, and then combined with the response surface design method to determine the optimal fermentation conditions. The results showed that the optimal fermentation medium composition was 10 g/L pectin, 7.99 g/L yeast powder and 0.5 g/L MgSO4·7H2O, the optimal fermentation conditions were initial pH5.66, fermentation temperature 37 ℃, incubation time 72 h, inoculum 6% (v/v), liquid volume 50/250 mL and substrate concentration 10 g/L. On the basis of this, the enzymatic activity of pectinase produced by B. subtilis Z-5 was increased from 879.00 U/mL to 1549.62 U/mL, which was 1.76 times higher than the unoptimised one. In pear juice clarification experiments, it was shown that the optimum addition of pectinase was 4 mL, the optimum enzymatic time was 2.5 h, the optimum enzymatic temperature was 65 ℃ and the optimum enzymatic pH was 6.0，the maximum light transmission rate was 79.77%. Compared with the commercial enzyme, the homemade pectinase is a compound enzyme with multiple enzyme systems, which can act on other components such as protein and starch contained in the pear juice, making the pear juice more clarified. The results of this study have provided theoretical support for the industrial production and application of pectinase.

Abstract Background Esophageal cancer (ESCA) is one of the most aggressive and lethal human malignant cancers. MicroRNA‐1301‐3p (miR‐1301‐3p) plays vital roles in a majority of malignancies. The aim of this study was to investigate the role of miR‐1301‐3p/NBL1 axis on ESCA cell invasion, migration, epithelial‐mesenchymal transition (EMT) process, as well as its association with prognosis of ESCA patients. Methods The expression levels of miR‐1301‐3p and NBL1 were predicted by bioinformatics and further verified by RT‐qPCR assays. Kaplan–Meier (K–M) plotter analysis and univariate and multivariate Cox analyses were used to evaluate the relationship between miR‐1301‐3p and clinicopathological variables and prognosis. The role of miR‐1301‐3p on cell invasion, migration was detected by transwell invasion, and wound healing assays, respectively. The EMT‐related proteins were detected by western blot. The target genes and the target binding sites were predicted by bioinformatics and further determined by RT‐qPCR assay. Results MiR‐1301‐3p was remarkably upregulated in ESCA tissues and cells, and its high expression was associated with poor prognosis of ESCA. Overexpression of miR‐1301‐3p promoted ESCA cell invasion, migration and mediated EMT process in vitro, whereas knockdown of miR‐1301‐3p showed the opposite effects. Moreover, NBL1 was predicted as a target gene of miR‐1301‐3p. NBL1 was lowly expressed in ESCA cells and significantly decreased after upregulation of miR‐1301‐3p. Meanwhile, we found that low expression of NBL1 was significantly associated with poor prognosis of ESCA patients. Conclusion MiR‐1301‐3p is a potential biomarker for predicting the prognosis of ESCA patients. It may promote ESCA invasion, migration and EMT progression by regulating NBL1 expression.

The abuse of nitrous oxide (N2O) poses a substantial public health challenge. In many countries, including China, regulations governing the utilization and accessibility to N2O remain ambiguous, particularly within the food industry. Here, we report a case of a 21-year-old female who presented with symptoms of subacute combined degeneration (SCD) of the spinal cord due to N2O abuse. The patient exhibited bilateral lower limb numbness and weakness, low serum vitamin B12 levels with elevated homocysteine levels, and lumbar spine magnetic resonance imaging (MRI) revealed abnormal signals of the spinal cord. Following cessation of N2O and comprehensive therapy including methylcobalamin and nerve growth factor, the symptoms significantly improved. A follow-up examination 3 months later showed good progress in gait stability. At a 5-year follow-up, the patient’s previous clinical symptoms had completely disappeared, and her quality of life had returned to normal. This case underscores the urgency of raising awareness and prevention of N2O abuse, emphasizing the importance of timely diagnosis and comprehensive treatment for patient recovery. Clear formulation and enforcement of relevant regulatory measures are equally crucial in reducing instances of abuse.

ABSTRACT: As an enzyme, β-mannanase (BM) can be widely used as feed additive to improve the growth performance of animals. This experiment aimed to determine the effect of the addition of BM to low-energy diet on the immune function and intestinal microflora of broiler chickens. In this study, 384 one-day-old Arbor Acres broilers were randomly divided into 3 groups (8 replicates per group): positive control (PC, received a corn-soybean meal basal diet), negative control (NC, received a low-energy diet with Metabolizable Energy (ME) reduced by 50 kcal/kg) and NC + BM group (NC birds + 100 mg/kg BM). All birds were raised for 42 d. The results showed that BM mitigated the damage of immune function in peripheral blood of broilers caused by the decrease of dietary energy level by increasing the Concanavalin A (Con A) index of stimulation (SI) and macrophages phagocytic activity in the peripheral blood of broilers at 42 d (P < 0.05). The analysis of cecum flora showed that the low-energy diet significantly reduced the observed_species index (P < 0.01), Chao1 index and ACE index (P < 0.05), which reduced the abundance and evenness of species in the cecum of broilers at 21 d. It also significantly reduced the relative abundance of Candidatus_Arthromitus and significantly increased the relative abundance of Pseudomonas in the cecum of broilers at 21 d, while also significantly increasing the relative abundance of Monoglobus at 42 d. BM significantly increased the relative abundance of Lachnospiraceae_UCG-001 and Lachnospiraceae_bacterium_615 in the cecum of broilers at 21 d. In addition, BM inhibited microbial Fatty acid degradation by decreasing the activity of glutaryl-CoA dehydrogenase. Collectively, BM could improve intestinal health by enhancing the immune function of broilers, promoting the proliferation of beneficial bacteria and reducing the number of harmful bacteria, regulating intestinal flora, thereby alleviating the adverse effects of lower dietary energy levels.

At present, most methods to improve the accuracy of emotion recognition based on electroencephalogram (EEG) are achieved by means of increasing the number of channels and feature types. This is to use the big data to train the classification model but it also increases the code complexity and consumes a large amount of computer time. We propose a method of Ant Colony Optimization with Convolutional Neural Networks and Long Short-Term Memory (ACO–CNN–LSTM) which can attain the dynamic optimal channels for lightweight data. First, transform the time-domain EEG signal to the frequency domain by Fast Fourier Transform (FFT), and the Differential Entropy (DE) of the three frequency bands (α, β and γ) are extracted as the feature data; Then, based on the DE feature dataset, ACO is employed to plan the path where the electrodes are located in the brain map. The classification accuracy of CNN-LSTM is used as the objective function for path determination, and the electrodes on the optimal path are used as the optimal channels; Next, the initial learning rate and batchsize parameters are exactly matched the data characteristics, which can obtain the best initial learning rate and batchsize; Finally, the SJTU Emotion EEG Dataset (SEED) dataset is used for emotion recognition based on the ACO–CNN–LSTM. From the experimental results, it can be seen that: the average accuracy of three-classification (positive, neutral, negative) can achieve 96.59 %, which is based on the lightweight data by means of ACO–CNN–LSTM proposed in the paper. Meanwhile, the computer time consumed is reduced. The computational efficiency is increased by 15.85 % compared with the traditional CNN-LSTM method. The accuracy can achieve more than 90 % when the data volume is reduced to 50 %. In summary, the proposed method of ACO–CNN–LSTM in the paper can get higher efficiency and accuracy.

Introduction: To study the effects of drug-induced CYP2D6 activity inhibition and genetic polymorphisms on fluoxetine metabolism, rat liver microsomes (RLMs) and SD rats were used to investigate the potential drug‒drug interactions (DDIs), and CYP2D6 http://muchong.com/t-10728934-1 recombinant baculosomes were prepared and subjected to catalytic reactivity studies.Methods and Results: All analytes were detected by ultraperformance liquid chromatography–tandem mass spectrometry (UPLC‒MS/MS). After screening for 27 targeted natural products, miltirone was identified as having obvious inhibitory effect on fluoxetine metabolism in RLMs. In vivo, the concentration of fluoxetine in rat blood increased markedly after miltirone administration. The molecular docking results showed that miltirone bound more strongly to CYP2D6 than fluoxetine, and PHE120 may be the key residue leading to the inhibition of CYP2D6-mediated fluoxetine N-demethylation by miltirone. In terms of the genetic polymorphism of CYP2D6 on fluoxetine metabolism, the intrinsic clearance values of most variants were significantly altered. Among these variants, CYP2D6*92 and CYP2D6*96/Q424X were found to be catalytically inactive for fluoxetine metabolism, five variants (CYP2D6*89/L142S, *97/F457L, *R497, *V342M and *R344Q) exhibited markedly increased clearance values (>125.07%) and seven variants (CYP2D6*2, *10, *87/A5V, *93/T249P, *E215K, *R25Q and *R440C) exhibited significantly decreased clearance values (from 6.62% to 66.79%) compared to those of the wild-type.Conclusion: Our results suggest that more attention should be given to subjects in the clinic who take fluoxetine and also carry one of these infrequent CYP2D6 alleles or are coadministered drugs containing miltirone.