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Abstract Background Impoverished students constitute a group that cannot be overlooked in higher education. It is crucial for pharmaceutical universities worldwide to implement financial assistance programs that promote the development and success of students from poor families. Chinese universities have carried out active exploration of subsidized education, and made important achievements, but there are also problems, which are worth learning from. This study proposed a strategy to improve the core literacy of impoverished pharmaceutical students under the development-oriented funding system. Methods The study centers on clinical pharmacy students from a pharmaceutical college as the research subjects. A sequential explanatory mixed-methods approach was employed, with quantitative data collected through a survey questionnaire, supplemented by qualitative data collected through in-depth interviews. Data gathered from these two levels were integrated and subjected to statistical analysis. Results The quantitative survey yielded a total of 397 valid samples, most of whom were females (73.8%), mainly at undergraduate level (89.67%), and from non-urban area (73.81%). Five of them participated in further qualitative interviews. The combined data identified: (a) financial aid—most students were highly satisfied with the financial support; (b) psychological support—most of the students interviewed reported that the scholarship significantly improved their self-confidence and motivation; (c) academic guidance—funded students had clear expectations for career development and academic guidance, demonstrating a strong need for further professional study; and (d) employment assistance—most students wanted career guidance and career planning support. Conclusions The financial assistance in pharmaceutical colleges and universities should be enriched to resolve the worries of impoverished clinical pharmacy students through economic assistance, improve the moral cultivation with psychological assistance, strengthen their cultural and scientific literacy, and improve their knowledge and practical ability through academic assistance. Through the integration of pharmacy education, the vocational competence of clinical pharmacy students can be improved by employment assistance, and the reform of higher pharmacy education can be further promoted to improve the training quality of pharmaceutical talents.

Abstract Natural products, with their extensive chemical diversity, distinctive biological activities, and vast reservoirs, provide a robust foundation for advancing cancer therapeutics. A comprehensive phytochemical investigation of the skins from Bufo bufo gargarizans afforded two new bufadienolide derivatives identified as bufalactamides A and B (1–2), along with six known compounds: argentinogenin (3), desacetylcinobufagin (4), desacetylcinobufaginol (5), cinobufaginol (6), bufalin (7) and gamabufalin (8). The structural elucidation of these compounds was meticulously carried out by analyses of spectroscopic data (1D and 2D NMR, HR-ESIMS), and comparison with the literature data. Plausible biosynthetic pathways for the new compounds were also discussed. Moreover, the cytotoxicity of the compounds was investigated using various cancer cell lines, including lung cancer (A549), colon cancer (HCT-116), liver cancer (SK-Hep-1), and ovarian cancer (SKOV3). Our research findings indicated that compounds 3, and 6–8 exhibit potent cytotoxic activity (IC50 100 µM). From this data, we conducted a comprehensive analysis of the structure-activity relationships among these compounds.

Abstract Accessibility is one of the crucial criteria for measuring the ease of access to public services in a region. Given China’s historical rural–urban dualism and rapid urbanization process, there exist significant disparities in public services within metropolises. This study selects Nanjing as a representative metropolis and employs the Gaussian two-step floating catchment area method and an improved potential model to calculate the accessibility of comprehensive hospitals. Spatial autocorrelation and urban–rural disparities are analyzed, confirming spatial variations in healthcare service equity. The results show that: ①The spatial variability of accessibility to comprehensive hospitals is significant. The Gaussian two-step floating catchment method overestimates overall accessibility, and for Nanjing, the improved potential model with β = 1.5 proves more suitable. ②Accessibility exhibits pronounced clustering characteristics. Healthcare conditions for residents in the northern part of Liuhe District, eastern part of Qixia District, western part of Pukou District, peripheral areas of Jiangning District, eastern part of Gaochun District, and residents in Lishui District need improvement. ③Comprehensive healthcare services are relatively lacking in nearly 60% of rural areas. Our research findings provide valuable insights for improving spatial justice in public infrastructure in metropolises of developing countries.

The fermented Codonopsis pilosula residue (FCPR) has a promoting effect on animal health, but it has not been studied in livestock feed. This study investigated the effects of FCPR addition on the milk performance, milk metabolites, and blood biochemical parameters and metabolites of lactating donkeys. Twelve healthy multiparous lactating Dezhou donkeys were randomly divided into two groups (with 6 donkeys in each group): control group (without FCPR, C) and FCPR group (200 g of FCPR per head per day, FF). The experiment lasted for 5 weeks. The milk and blood samples were collected at the end of the experiment. The results showed that addition of FCPR significantly increased the daily milk yield and the milk components (protein, lactose, solids, solids-not-fat, and lactoferrin) yield of lactating donkeys and the weight gain of foals (p

The lipid and flavor in milk are key factors that affect its quality, which profiles during donkey lactation are not yet clear. In this study, the lipids and volatile compounds (VOCs) in donkey milk from stages of lactation were analyzed by using LC-MS and GC-IMS. A total of 1774 lipids were identified in donkey milk, spanning over 6 major categories and attributed to 30 subclasses. The 233 differentially expressed lipids were identified between donkey colostrum and mature milk, which participate in 20 metabolic pathways, including glycerophospholipid, linoleic acid, and sphingolipid. Additionally, 35 VOCs in donkey milk were identified, including 28.57% aldehydes, 28.57% ketones, 25.71% esters, and 8.57% alcohols. Of these VOCs, 15 were determined to be characteristic flavors in donkey milk, mainly including methyl 2-methylbutanoate, 2-pentanone, and butyl acetate. 11 significantly different VOCs were found between the groups. Acetone, 2-heptanone, and ethyl acetate-m were considered potential discriminatory markers.

Abstract The newly identified XBB.1.16‐containing sublineages, including XBB.1.5, have become the prevailing severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) variant in circulation. Unlike previous Omicron XBB variants (e.g., XBB.1.5 and XBB.1.9) harboring the F486P substitution, XBB.1.16 also carries a T478R substitution in the receptor‐binding domain (RBD). Numerous researchers have delved into the high transmissibility and immune evasion of XBB.1.16 subvariant. Therefore, developing a new vaccine targeting XBB.1.16, including variants of concern (VOCs), is paramount. In our study, we engineered a recombinant protein by directly linking the S‐RBD sequence of the XBB.1.16 strain of SARS‐CoV‐2 to the sequences of two heptad repeat sequences (HR1 and HR2) from the SARS‐CoV‐2 S2 subunit. Named the recombinant RBDXBB.1.16‐HR/trimeric protein, this fusion protein autonomously assembles into a trimer. Combined with an MF59‐like adjuvant, the RBDXBB.1.16‐HR vaccine induces a robust humoral immune response characterized by high titers of neutralizing antibodies against variant pseudovirus and authentic VOCs and cellular immune responses. Additionally, a fourth heterologous RBDXBB.1.16‐HR vaccine enhances both humoral and cellular immune response elicited by three‐dose mRNA vaccines. These findings demonstrate that the recombinant RBDXBB.1.16‐HR protein, featuring the new T478R mutation, effectively induces solid neutralizing antibodies to combat newly emerged XBB variants.

Abstract This study quantifies the impact of digital innovation on corporate performance, offering insights into the sustainability of digital innovation’s impact and providing guidance for firms embarking on their digital innovation journey. We examine the effect of digital innovation on cost stickiness using patent reports spanning from 2007 to 2022. The baseline analysis results reveal that digital innovation significantly mitigates cost stickiness in companies. This finding remains robust after addressing endogeneity concerns and conducting various robustness tests. We probe potential mechanisms and discover that digital innovation reduces cost stickiness by enhancing the quality of internal controls, improving resource-adjustment efficiency, and addressing managerial over-optimism. Heterogeneity analysis indicates a more pronounced impact of digital innovation on reducing asymmetric cost behaviors in larger firms, those beyond the growth stage, and in regions with active digital procurement, well-developed digital taxation governance, and sound judiciary infrastructures. Additionally, our expanded analysis confirms the financial benefits of digital innovation in reducing cost stickiness. A notable discovery is the negative correlation between digital transformation and cost stickiness within digitally innovative firms, underscoring the greater significance of digital innovation over mere digitization. Overall, this study significantly advances our understanding of how digital innovation influences cost management strategies.

Pesticide residues on fruits pose a global food safety concern, emphasizing the need for effective and practical removal strategies to ensure safe consumption. This study investigates the efficacy of household ingredients (corn starch, all-purpose flour, rice flour and baking soda) and four commercial fresh produce wash products in eliminating a model pesticide thiabendazole with and without a model non-ionic surfactant Alligare 90® from postharvest fruits. Surface-enhanced Raman spectroscopy (SERS) was employed for the rapid, in situ quantification of residue removal on apple surfaces. Soaking in 2% corn starch followed by soaking in 5% baking was the most effective homemade strategy, removing 94.13% and 91.78% of thiabendazole with and without the surfactant. Among commercial washing agents, soaking in 2% Product 4 demonstrated the highest efficiency, removing 95.3% and 95.99% of thiabendazole with and without surfactant. These results suggested that the non-ionic surfactant did not affect removal efficiency. Both protocols were effective across various fruits (apples, grapes, lemons, strawberries), validated by liquid chromatography–mass spectrometry (LC-MS/MS) analyses. However, safety concerns regarding the composition of Product 4 highlighted the benefits of homemade strategies. Overall, this work offers practical guidelines for reducing pesticide residues on fruits and enhancing food.

Abstract Spin defects in van der Waals materials offer a promising platform for advancing quantum technologies. Here, we propose and demonstrate a powerful technique based on isotope engineering of host materials to significantly enhance the coherence properties of embedded spin defects. Focusing on the recently-discovered negatively charged boron vacancy center ( $${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − ) in hexagonal boron nitride (hBN), we grow isotopically purified h10B15N crystals. Compared to $${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − in hBN with the natural distribution of isotopes, we observe substantially narrower and less crowded $${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − spin transitions as well as extended coherence time T 2 and relaxation time T 1. For quantum sensing, $${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − centers in our h10B15N samples exhibit a factor of 4 (2) enhancement in DC (AC) magnetic field sensitivity. For additional quantum resources, the individual addressability of the $${{{{{{{{\rm{V}}}}}}}}}_{{{{{{{{\rm{B}}}}}}}}}^{-}$$ V B − hyperfine levels enables the dynamical polarization and coherent control of the three nearest-neighbor 15N nuclear spins. Our results demonstrate the power of isotope engineering for enhancing the properties of quantum spin defects in hBN, and can be readily extended to improving spin qubits in a broad family of van der Waals materials.

Abstract Biologic therapies targeting the IL-23/IL-17 axis have transformed the treatment of psoriasis. However, the early mechanisms of action of these drugs remain poorly understood. Here, we perform longitudinal single-cell RNA-sequencing in affected individuals receiving IL-23 inhibitor therapy. By profiling skin at baseline, day 3 and day 14 of treatment, we demonstrate that IL-23 blockade causes marked gene expression shifts, with fibroblast and myeloid populations displaying the most extensive changes at day 3. We also identify a transient WNT5A+/IL24+ fibroblast state, which is only detectable in lesional skin. In-silico and in-vitro studies indicate that signals stemming from these WNT5A+/IL24+ fibroblasts upregulate multiple inflammatory genes in keratinocytes. Importantly, the abundance of WNT5A+/IL24+ fibroblasts is significantly reduced after treatment. This observation is validated in-silico, by deconvolution of multiple transcriptomic datasets, and experimentally, by RNA in-situ hybridization. These findings demonstrate that the evolution of inflammatory fibroblast states is a key feature of resolving psoriasis skin.

With the wide applications of industrial wireless network technologies, the industrial control system (ICS) is evolving from wired and centralized to wireless and distributed, during which eavesdropping and attacking become serious problems. To guarantee the security of wireless and distributed ICS, this article establishes an end-edge collaborative lightweight secure federated learning (LSFL) architecture and proposes an LSFL anomaly detection strategy. Specifically, we first design a residual multihead self-attention convolutional neural network for local feature learning, where the variability and dependence of spatial-temporal features can be sufficiently evaluated. Then, to reduce the wireless communication cost for parameter exchange and edge federal learning, we propose a dynamic parameter pruning algorithm by evaluating the contribution of each parameter based on the information entropy gain. Furthermore, to ensure the parameter security during wireless transmission in the open radio environment, we propose an adaptive key generation algorithm for parameter encryption. Finally, the proposed strategy is experimentally validated on representative datasets, including Smart Meter, NSL-KDD, and UNSW-NB15. Experimental results demonstrate that the proposed strategy achieves 99% accuracy on different datasets, where at least 89.6% wireless communication cost is reduced and tampering/injecting attacks are defended.

Industrial control systems are facing ever-increasing security challenges due to the large-scale access of heterogeneous devices in the open Internet environment. Existing anomaly detection methods are mainly based on the priori knowledge of industrial control protocols (ICPs) whose protocol specifications, communication mechanism, and data format are already known. However, when these knowledge are blank, namely, unknown ICPs, existing methods become powerless to detect the anomaly data. To tackle this challenge, we propose a multigranularity feature automatic marking-based deep learning method to classify unknown ICPs for anomaly detection. First, to obtain the feature sequences without priori knowledge assisting, we propose a multigranularity feature extraction algorithm to extract both byte and half-byte information by fully utilizing the intensive key information in the header field of the application layer. Then, to label the feature sequences for deep learning, we propose a feature automatic marking algorithm that utilizes the inconsistency feature sequences to dynamically update the feature sequence set. With the labeled feature sequences, we employ deep learning with 1-D convolutional neural network and gated recurrent unit to classify the unknown ICPs and realize anomaly detection. Extensive experiments on two public datasets show that both the accuracy and precision of the proposed method reach above 98.4%, which is better than the three benchmark methods.

This study investigated the effects of adding methionine (Met) in milk production and the milk and blood metabolites of lactating donkeys. Eighteen healthy multiparous donkeys in early-stage lactation were selected for this study. The donkeys were randomly divided into three groups and fed diets with different levels of Met: control group (C, Met 0 g/d), Met group I (M1, Met 5 g/d), and Met group II (M2, Met 15 g/d). The total duration of the experiment was 5 weeks. Donkey milk and blood samples were collected at the end of the experiment. The milk yield and composition, milk, and serum metabolites were analyzed. The results showed that the addition of 5 g of Met significantly increased milk yield as well as the milk composition contents of protein, fat, lactoferrin, polyunsaturated fatty acid (PFA), solids, and solids-not-fat (SNF) (p < 0.05). Significant differences in metabolites were detected among the different samples of milk (p < 0.05). The addition of Met increased the levels of milk metabolites, such as myristic acid, d-glutamine, l-aspartic acid, and LPS 16:0. A total of 753 metabolites were detected in the serum, including 17 differential metabolites between C and M1 and 48 differential metabolites between C and M2. The levels of serum metabolites, such as l-ascorbate, inositol, and l-lysine, were up-regulated by the addition of Met (p < 0.05). The above results indicated that Met increased donkey milk production and milk composition yield and improved milk metabolites by regulating serum metabolites. These results provide a foundation for improving the nutritional needs of lactating donkeys and the nutritional regulation of donkey milk synthesis.

Abstract Background Recent evidence reveals the emerging functions of circular RNA (circRNA) and protein glycosylation in cancer progression. However, the roles of circRNA in regulating glycosyltransferase expression in gastric cancer remain to be determined. Methods Circular RNAs (circRNAs) were validated by Sanger sequencing. Co-immunoprecipitation, mass spectrometry, and RNA sequencing assays were applied to explore protein interaction and target genes. Gene expression regulation was observed by chromatin immunoprecipitation, RNA immunoprecipitation, dual-luciferase reporter, real-time quantitative RT-PCR, and western blot assays. Gain- and loss-of-function studies were performed to observe the impacts of circRNA and its partners on the glycosylation, growth, invasion, and metastasis of gastric cancer cells. Results Circ-hnRNPU, an exonic circRNA derived from heterogenous nuclear ribonuclear protein U (hnRNPU), was identified to exert tumor suppressive roles in protein glycosylation and progression of gastric cancer. Mechanistically, circ-hnRNPU physically interacted with non-POU domain containing octamer binding (NONO) protein to induce its cytoplasmic retention, resulting in down-regulation of glycosyltransferases (GALNT2, GALNT6, MGAT1) and parental gene hnRNPU via repression of nuclear NONO-mediated c-Myc transactivation or cytoplasmic NONO-facilitated mRNA stability. Rescue studies indicated that circ-hnRNPU inhibited the N- and O-glycosylation, growth, invasion, and metastasis of gastric cancer cells via interacting with NONO protein. Pre-clinically, administration of lentivirus carrying circ-hnRNPU suppressed the protein glycosylation, tumorigenesis, and aggressiveness of gastric cancer xenografts. In clinical cases, low circ-hnRNPU levels and high NONO or c-Myc expression were associated with poor survival outcome of gastric cancer patients. Conclusions These findings indicate that circ-hnRNPU inhibits NONO-mediated c-Myc transactivation and mRNA stabilization essential for glycosylation and cancer progression.

Abstract Background A series of studies have demonstrated the emerging involvement of transfer RNA (tRNA) processing during the progression of tumours. Nevertheless, the roles and regulating mechanisms of tRNA processing genes in neuroblastoma (NB), the prevalent malignant tumour outside the brain in children, are yet unknown. Methods Analysis of multi‐omics results was conducted to identify crucial regulators of downstream tRNA processing genes. Co‐immunoprecipitation and mass spectrometry methods were utilised to measure interaction between proteins. The impact of transcriptional regulators on expression of downstream genes was measured by dual‐luciferase reporter, chromatin immunoprecipitation, western blotting and real‐time quantitative reverse transcription‐polymerase chain reaction (RT‐PCR) methods. Studies have been conducted to reveal impact and mechanisms of transcriptional regulators on biological processes of NB. Survival differences were analysed using the log‐rank test. Results c‐Myc was identified as a transcription factor driving tRNA processing gene expression and subsequent malate‐aspartate shuttle (MAS) in NB cells. Mechanistically, c‐Myc directly promoted the expression of glutamyl‐prolyl‐tRNA synthetase (EPRS) and leucyl‐tRNA synthetase (LARS), resulting in translational up‐regulation of glutamic‐oxaloacetic transaminase 1 (GOT1) as well as malate dehydrogenase 1 (MDH1) via inhibiting general control nonrepressed 2 or activating mechanistic target of rapamycin signalling. Meanwhile, lamin A (LMNA) inhibited c‐Myc transactivation via physical interaction, leading to suppression of MAS, aerobic glycolysis, tumourigenesis and aggressiveness. Pre‐clinically, lobeline was discovered as a LMNA‐binding compound to facilitate its interaction with c‐Myc, which inhibited aminoacyl‐tRNA synthetase expression, MAS and tumour progression of NB, as well as growth of organoid derived from c‐Myc knock‐in mice. Low levels of LMNA or elevated expression of c‐Myc, EPRS, LARS, GOT1 or MDH1 were linked to a worse outcome and a shorter survival time of clinical NB patients. Conclusions These results suggest that targeting c‐Myc transactivation by LMNA inhibits tRNA processing essential for MAS and tumour progression.

Background Parkinson’s disease (PD) is a common degenerative disease caused by abnormal accumulation of α-synuclein. The glymphatic pathway is essential for removing macromolecular proteins including α-synuclein from the brain, which flows into deep cervical lymph nodes (DCLNs) through meningeal lymphatics. As a terminal station for the cerebral lymphatic system drainage, DCLNs can be easily assessed clinically. Objectives Although the drainage function of the cerebral lymphatic system is impaired in PD, the correlation between DCLNs and PD remains unknown. Design Single-center retrospective cross-sectional study. Methods The size of the DCLNs were measured using ultrasound. The Movement Disorder Society Sponsored Revision Unified Parkinson’s Disease Rating Scale and other scales were used to assess PD motor and non-motor symptoms. Results Compared with the healthy control (HC) and the atypical Parkinson’s disease (AP) groups, the size of the second and third DCLNs in the Parkinson’s disease (PD) group was significantly smaller ( P < .05). The width diameter of the third DCLN (DCLN3(y)) was significantly smaller in the PD group than in the AP group ( P = .014). DCLN3(y) combined with a variety of clinical features improved the sensitivity of AP identification (sensitivity = .813). Conclusion DCLNs were able to distinguish HC, PD and AP and were mainly located in Robbins ΙΙA level. PD and AP were associated with different factors that influenced the size of the DCLNs. DCLN3(y) plays an important role in differentiating PD from AP, which, combined with other clinical features, has the ability to distinguish PD from AP; in particular, the sensitivity of AP diagnosis was improved.

AbstractBackground T-cell large granular lymphocyte leukaemia (T-LGLL) generally has a favourable prognosis, but a small proportion of patients are facing a relatively short survival time. This study aimed to identify clinical factors associated with survival in patients with T-LGLL and develop a predictive model for guiding therapeutic decision-making.Materials and Methods We conducted a retrospective study on 120 patients with T-LGLL. Lasso regression was performed for feature selection followed by univariate and multivariate Cox regression analysis. A decision tree algorithm was employed to construct a model for predicting overall survival (OS) in T-LGLL.Results The median age of diagnosis for the entire cohort was 59 years, and 76.7% of patients reported disease-related symptoms. After a median follow-up of 75 months, the median OS was not reached. The 5-year OS rate was 82.2% and the 10-year OS rate was 63.8%. Multivariate analysis revealed that an Eastern Cooperative Oncology Group performance status over two and a platelet count below 100 × 109/L were independently associated with worse OS, leading to the development of a simplified decision tree model. The model’s performance was adequate when internally validated. The median OS of the high- and intermediate-risk- risk groups was 43 and 100 months respectively, whereas the median OS of the low-risk group was not reached. Furthermore, we found that immunosuppressive agent-based conventional treatment was unsatisfactory for our high-risk patients.Conclusions Our model is an easily applicable clinical scoring system for predicting OS in patients with T-LGLL. However, external validation is essential before implementing it widely.

This study employs textual analysis to assess enterprise digitalization. Moreover, it explores the effect of firm digital transformation (DT) on productivity using data from listed enterprises in China from 2007 to 2020. Our empirical findings point to a facilitation effect between firm-level DT and productivity, which is stronger in downstream firms. Mechanism analysis shows that such increase in productivity is driven mainly by the positive effect of firm DT on technological innovation, human capital, operating capability, and investment efficiency. Further investigation reveals that promoting firm productivity through DT can boost profitability. The findings can help us better understand the economics of firm DT and therefore point to an important policy implication for increasing enterprise productivity.

Purpose – Time headway (THW) is an essential parameter in traffic safety and is used as a typical control variable by many vehicle control algorithms, especially in safety-critical ADAS and automated driving systems. However, due to the randomness of human drivers, THW cannot be accurately represented, affecting scholars’ more profound research. Design/methodology/approach – In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified. Findings – In this work, two data sets are used as the experimental data to calculate the goodness-of-fit of 18 commonly used distribution models of THW to select the best distribution model. Subsequently, the characteristic parameters of traffic flow are extracted from the data set, and three variables with higher importance are extracted using the random forest model. Combining the best distribution model parameters of the data set, this study obtained a distribution model with adaptive parameters, and its performance and applicability are verified. Originality/value – The results show that the proposed model has a 62.7% performance improvement over the distribution model with fixed parameters. Moreover, the parameter function of the distribution model can be regarded as a quantitative analysis of the degree of influence of the traffic flow state on THW.

Background: Parkinson's disease (PD) is one of the most common neurodegenerative disease, and half of PD patients have hypertension as well. The effect of antihypertensive drugs on the progression of PD has been less studied. The focus of this study was on the changes in dopamine transporter (DAT) levels to assess the effect of antihypertensive drugs on the progression of PD. Methods: Data from 321 drug-naïve patients from the Parkinson's Disease Progression Marker Initiative (PPMI) were collected over a 2-year period. Patients were divided into the PD with arterial hypertension (AH) group (102 cases) with antihypertensive drugs, the PD with other cardiovascular risk factors (CVRFs) group (60 cases) with antidiabetic and/or lipid-lowering drugs, and the pure PD group (159 cases) without CVRFs. The Movement Disorder Society Sponsored Revision Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and Hoehn-Yahr (H&Y) stage were used to assess progression. DAT semiquantitative values were used to evaluate damage to dopaminergic neurons in the substantia nigra, including the contralateral and ipsilateral count density ratio and asymmetry index. Results: There were no significant differences among the three groups in MDS-UPDRS score and H&Y stage. Changes in DAT levels among the three groups were without distinct differences in the first year and second year. In each group, DAT decreased more in the first year than in the second year. There was no decrease in DAT uptake in the PD with AH group compared with the other groups during the follow-up period. Conclusions: There is no evidence that antihypertensive drugs can delay PD progression within 2 years.

Recently, there has been a significant focus on the issue of pollution caused by livestock and poultry rearing, which is recognized as a prominent contributor to nonpoint source pollution in the agricultural sector. This study employed the life cycle assessment (LCA) methodology to evaluate the environmental impact of several pig manure processing scenarios with the aim of determining the appropriate solid–liquid separation tool for large-scale pig farms. The findings indicate that the utilization of a screw extruder for solid–liquid separation in Scenario 2 has a lower environmental impact. In contrast to Scenario 1, Scenario 2 exhibits reduced environmental potential in the areas of global warming, human toxicity, acidification, and eutrophication. Specifically, the global warming, human toxicity, acidification, and eutrophication impacts decreased by 56%, 81%, 83%, and 273%, respectively, due to the implementation of solid–liquid separation. The type of solid–liquid separation equipment used during the processing of swine manure, as well as the subsequent treatment, have a significant impact on environmental emissions. Compared to Scenario 2, Scenario 3, which utilizes a centrifugal microfilter for solid–liquid separation, exhibits a lower environmental impact in terms of human toxicity, resulting in a reduction of 0.736 kg DCB-eq. In general, solid–liquid separation is a viable and environmentally friendly method for the disposal of waste from large-scale pig farms. The adoption of this method is highly recommended. During its implementation, careful consideration should be given to factors such as separation efficiency and pollution emissions. It is crucial to select appropriate equipment for solid–liquid separation to effectively process the waste.

Proteins in donkey milk (DM) have special biological activities. However, the bioactive proteins and their expression regulation in donkey milk are still unclear. Thus, the differentially expressed proteins (DEPs) in DM in different lactation stages were first investigated by data-independent acquisition (DIA) proteomics. A total of 805 proteins were characterized in DM. The composition and content of milk proteins varied with the lactation stage. A total of 445 candidate DEPs related to biological processes and molecular functions were identified between mature milk and colostrum. The 219 down-regulated DEPs were mainly related to complement and coagulation cascades, staphylococcus aureus infection, systemic lupus erythematosus, prion diseases, AGE-RAGE signaling pathways in diabetic complications, and pertussis. The 226 up-regulated DEPs were mainly involved in metabolic pathways related to nutrient (fat, carbohydrate, nucleic acid, and vitamin) metabolism. Some other DEPs in milk from the lactation period of 30 to 180 days also had activities such as promoting cell proliferation, promoting antioxidant, immunoregulation, anti-inflammatory, and antibacterial effects, and enhancing skin moisture. DM can be used as a nutritional substitute for infants, as well as for cosmetic and medical purposes. Our results provide important insights for understanding the bioactive protein differences in DM in different lactation stages.

ObjectivePrevious studies have reported that white matter hyperintensities (WMHs) are associated with freezing of gait (FOG), but it is not clear whether their distribution areas have correlations with FOG in Parkinson’s disease (PD) and the potential influencing factors about WMHs.MethodsTwo hundred and forty-six patients with PD who underwent brain MRI were included. Participants were divided into PD with FOG (n = 111) and PD without FOG (n = 135) groups. Scheltens score was used to assess the WMHs burden in the areas of deep white matter hyperintensities (DWMHs), periventricular hyperintensities (PVHs), basal ganglia hyperintensities (BGHs), and infratentorial foci of hyperintensities (ITF). Whole brain WMHs volume was evaluated by automatic segmentation. Binary logistic regression was used to evaluate relationships between WMHs and FOG. The common cerebrovascular risk factors that may affect WMHs were evaluated by mediation analysis.ResultsThere were no statistical differences between PD with and without FOG groups in whole brain WMHs volume, total Scheltens score, BGHs, and ITF. Binary logistic regression showed that the total scores of DWMHs (OR = 1.094; 95% CI, 1.001, 1.195; p = 0.047), sum scores of PVHs and DWMHs (OR = 1.080; 95% CI, 1.003, 1.164; p = 0.042), especially the DWMHs in frontal (OR = 1.263; 95% CI, 1.060, 1.505 p = 0.009), and PVHs in frontal caps (OR = 2.699; 95% CI, 1.337, 5.450; p = 0.006) were associated with FOG. Age, hypertension, and serum alkaline phosphatase (ALP) are positively correlated with scores of DWMHs in frontal and PVHs in frontal caps.ConclusionThese results indicate that WMHs distribution areas especially in the frontal of DWMHs and PVHs play a role in PD patients with FOG.

Abstract Background Neuroblastoma (NB) is the most common extracranial malignancy in childhood; however, the mechanisms underlying its aggressive characteristics still remain elusive. Methods Integrative data analysis was performed to reveal tumour‐driving transcriptional regulators. Co‐immunoprecipitation and mass spectrometry assays were applied for protein interaction studies. Real‐time reverse transcription‐polymerase chain reaction, western blotting, sequential chromatin immunoprecipitation and dual‐luciferase reporter assays were carried out to explore gene expression regulation. The biological characteristics of NB cell lines were examined via gain‐ and loss‐of‐function assays. For survival analysis, the Cox regression model and log‐rank tests were used. Results Cellular nucleic acid‐binding protein (CNBP) was found to be an independent factor affecting NB outcome, which exerted oncogenic roles in ribosome biogenesis, tumourigenesis and aggressiveness. Mechanistically, karyopherin subunit beta 1 (KPNB1) was responsible for nuclear transport of CNBP, whereas liquid condensates of CNBP repressed the activity of switch/sucrose‐nonfermentable (SWI/SNF) core subunits (SMARCC2/SMARCC1/SMARCA4) via interaction with SMARCC2, leading to alternatively increased activity of SMARCC1/SMARCA4 binary complex in facilitating gene expression essential for 18S ribosomal RNA (rRNA) processing in tumour cells, extracellular vesicle‐mediated delivery of 18S rRNA and subsequent M2 macrophage polarisation. A cell‐penetrating peptide blocking phase separation and interaction of CNBP with SMARCC2 inhibited ribosome biogenesis and NB progression. High KPNB1, CNBP, SMARCC1 or SMARCA4 expression or low SMARCC2 levels were associated with poor survival of NB patients. Conclusions These findings suggest that CNBP phase separation is a target for inhibiting ribosome biogenesis and tumour progression in NB via modulating SWI/SNF complex activity.

Background: Necroptosis has been demonstrated to play a crucial role in the prognosis prediction and assessment of treatment outcome in cancers, including cervical cancer. The purpose of this study was to explore the potential prognostic value of necroptosis-related lncRNAs and their relationship with immune microenvironment and response to treatment in cervical cancer.Methods: Data from The Cancer Genome Atlas (TCGA) were collected to obtain synthetic data matrices. Necroptosis-related lncRNAs were identified by Pearson Correlation analysis. Univariate Cox and multivariate Cox regression analysis and Lasso regression were used to construct a necroptosis-related LncRNAs signature. Kaplan-Meier analysis, univariate and multivariate Cox regression analyses, receiver operating characteristic (ROC) curve, nomogram, and calibration curves analysis were performed to validate this signature. Gene set enrichment analyses (GSEA), immunoassays, and the half-maximal inhibitory concentration (IC50) were also analyzed.Results: Initially, 119 necroptosis-related lncRNAs were identified based on necroptosis-related genes and differentially expressed lncRNAs between normal and cervical cancer samples. Then, a prognostic risk signature consisting of five necroptosis-related lncRNAs (DDN-AS1, DLEU1, RGS5, RUSC1-AS1, TMPO-AS1) was established by Cox regression analysis, and LASSO regression techniques. Based on this signature, patients with cervical cancer were classified into a low- or high-risk group. Cox regression confirmed this signature as an independent prognostic predictor with an AUC value of 0.789 for predicting 1-year OS. A nomogram including signature, age, and TNM stage grade was then established, and showed an AUC of 0.82 for predicting 1-year OS. Moreover, GSEA analysis showed that immune-related pathways were enriched in the low-risk group; immunoassays showed that most immune cells, ESTIMAT scores and immune scores were negatively correlated with risk score and that the expression of immune checkpoint-proteins (CD27, CD48, CD200, and TNFRSF14) were higher in the low-risk group. In addition, patients in the low-risk group were more sensitive to Rucaparib, Navitoclax and Crizotinib than those in the high-risk group.Conclusion: We established a novel necroptosis-related lncRNA based signature to predict prognosis, tumor microenvironment and response to treatment in cervical cancer. Our study provides clues to tailor prognosis prediction and individualized immunization/targeted therapy strategies.

The microbial community in donkey milk and its impact on the nutritional value of donkey milk are still unclear. We evaluated the effects of different lactation stages on the composition and function of donkey milk microbiota. The milk samples were collected at 1, 30, 60, 90, 120, 150, and 180 days post-delivery. The result showed that the microbial composition and functions in donkey milk were significantly affected by different lactation stages. The dominant bacterial phyla in donkey milk are Proteobacteria (60%) and Firmicutes (22%). Ralstonia (39%), Pseudomonas (4%), and Acinetobacter (2%) were the predominant bacterial genera detected in all milk samples. In the mature milk, the abundance of lactic acid bacteria Streptococcus (7%) was higher. Chloroplast (5%) and Rothia (3%) were more plentiful in milk samples from middle and later lactation stages (90–180 d). Furthermore, the pathogens Escherichia-Shigella and Staphylococcus and thermoduric bacteria Corynebacterium, Arthrobacter, and Microbacterium were also detected. Donkey milk is rich in beneficial bacteria and also poses a potential health risk. The above findings have improved our understanding of the composition and function changes of donkey milk microbiota, which is beneficial for the rational utilization of donkey milk.

Calves raised in barns are usually kept in individual pens separated by either solid or mesh partitions. To quantify the effects that the two types of partition have on airflow speed in an axial-ventilated-barn, the indoor environment of a calf barn was simulated using computational fluid dynamics (CFD) with validation accomplished by means of direct measurement. To ascertain the effects that two types of partition have on the physiological parameters and health of pre-weaned calves, 24 calves (3–11-day-olds) were selected, equally divided into four groups and sequestered as follows: calves placed in pens separated by solid partitions receiving “low-speed” or “high-speed” airflow; calves separated by mesh partitions receiving “low-speed” or “high-speed” airflow. The results of the CFD simulation showed that the percentage of airflow speed that exceeded 0.5 m s−1 at a height of 0.4 m above the floor of the animal occupied zone where calves were separated by mesh partitions was 88%, while the speed was 66–70% for calves separated by solid partitions. The duration of treatment provided to the calves in the MP-LA (mesh partitions and subjected to a low-speed airflow) and MP-HA (mesh partitions and subjected to a high-speed airflow) groups, were both lower than the SP-LA (solid partitions and subjected to a low-speed airflow) and SP-HA (solid partitions and subjected to a high-speed airflow) groups. We conclude that when the fan is operating, contact between calves separated by mesh partitions produces no negative impact on the health of calves; furthermore, this arrangement can provide a higher airflow speed than that delivered to calves raised in pens separated by solid partitions, especially to those calves in pens farther from the fans.

The mechanical and electrical development in dairy farming in China increases energy-related carbon emission (CE). To support the sustainable planning strategy of the department, this study calculated the CE and the carbon emission intensity (CI) of the direct energy consumed in dairy farms from 21 provinces in China. Through four dimensions analysis including the national level, farm scale, inter-provincial distribution, and main producing area, this study illustrates the impact of the environment, production, and management on CE. The total CE of nationwide dairy farming was about 2.4 Tg CO2 eq. in 2019, and the CIs of the 21 provinces varied from 0.009 to 0.216 kg CO2 eq. per kg of milk. The results indicate that the management mode applied in large-scale dairy farms (500 heads and above) varies considerably due to inadequate adaptation to climate. In general, semi-arid and semi-humid regions are more suitable for dairy farming than arid and humid regions. In the main milk-producing area, the spatial aggregation effect is visible in the carbon reduction potential. The present study suggests that further steps to promote sustainability and milk productivity are embodied when the replacement of fossil fuels and the management standardization are adapted to regional characteristics.

Background. Chronic kidney disease (CKD) is a main health problem associated with increased risk of cardiovascular disease, morbidity, and mortality. Recent studies shown that the progression of CKD may be related to the change of intestinal flora. Resistant starch (RS) is a type of dietary fiber that can act as a substrate for microbial fermentation. Some studies have found that the supplementation of RS can improve the intestinal flora disorder in CKD patients. However, the specific effect of RS on CKD patients remains controversial. Objective. We designed this meta-analysis to identify and assess the effects of RS on patients with CKD. Methods. A comprehensive search of MEDLINE, Embase, Web of Science, and Cochrane systematic review databases was conducted in January 2020, and all new trials were updated in August 2021. Randomized trials were collected to assess the effects of RS on patients with CKD. The weighted average effect size of the net change was calculated by using the random-effects model. Results. The meta-analysis included 8 studies involving 301 participants. RS intake significantly reduced serum indolephenol sulfate (IS), blood phosphorus, IL-6, and uric acid levels in dialysis patients. The mean difference (MD) of serum IS (P=0.0002) in the dialysis subgroup was -12.57 μmol/L (95% CI: -19.28, -5.86 μmol/L). The MD of blood phosphorus (P=0.03) was -0.39 mg/dl (95% CI: -0.78, -0.01 mg/dl). The MD of serum uric acid (P=0.004) between the dialysis subgroup and the nondialysis subgroup was -31.58 mmol/L (95% CI: -52.99, -10.17 mmol/L). The mean difference (MD) of IL-6 (P=0.02) in the dialysis subgroup was -1.16 μmol/L (95% CI: -2.16, -0.16 μmol/L). However, there was no significant change of RS on hs-CRP, serum creatinine, blood urea nitrogen (BUN), blood paracresol sulfate, and blood lipid. Conclusions. The intake of RS reduced the serum IS, serum phosphorus, IL-6, and uric acid levels significantly in dialysis patients, while hs-CRP, serum creatinine, BUN, serum paracresol sulfate, and blood lipid showed no significant changes.

We construct a holographic p-wave superconductor with excited states in the 4D Einstein–Gauss–Bonnet gravity using the Maxwell complex vector field model. In the probe limit, we observe that, the higher curvature correction or the higher excited state can hinder the vector condensate to be formed in the full parameter space, which is different from the holographic s-wave superconductor. Regardless of the choice of the vector mass by selecting the value of m2L2 or m2Leff2, we note that the critical chemical potential becomes evenly spaced for the number of nodes and that the difference of the critical chemical potential between the consecutive states depends on the curvature correction. Moreover, we find that the higher curvature correction or the higher excited state will alter the universal relation of the gap frequency, and the pole and delta function of the conductivity for the excited states can be broadened into the peaks with the finite width as the curvature correction increases.

As a promising industrial wireless network technology, 5G URLLC is playing a key role in industrial control systems which employ different kinds of industrial control protocols. This leaves a significant challenge in how to adapt 5G URLLC with existing industrial control protocols and develop novel industrial wireless controllers. Motivated by this, this paper investigates the protocol adaptation and experimental evaluations for the development of a 5G-based industrial wireless controller prototype. Specifically, using the globally used industrial protocol Modbus as an example, we first deeply analyze the characteristics of the data packet format and the communication time sequence of Modbus RTU, Modbus TCP, and 5G protocols. Then, we propose a protocol resolution and conversion scheme for the protocol adaptation between Modbus RTU/Modbus TCP and 5G. Furthermore, we develop a wireless programmable logic controller (PLC) prototype system based on 5G. To evaluate the protocol adaptation scheme and the developed prototype, we perform extensive experiments to test the reliability and latency. The results demonstrate that the latency of the protocol adaptation scheme is smaller than that of protocol transparent transmission without resolution and conversion, while the reliability loss is not large. Moreover, the speed and reliability for the protocol adaptation between Modbus TCP and 5G are better than those between Modbus RTU and 5G.

Despite an increasing appreciation in the importance of host–microbe interactions in ecological and evolutionary processes, information on the gut microbial communities of some marine mammals is still lacking. Moreover, whether diet, environment, or host phylogeny has the greatest impact on microbial community structure is still unknown. To fill part of this knowledge gap, we exploited a natural experiment provided by an aquarium with belugas (Delphinapterus leucas) affiliated with family Monodontidae, Pacific white-sided dolphins (Lagenorhynchus obliquidens) and common bottlenose dolphin (Tursiops truncatus) affiliated with family Delphinidae, and Cape fur seals (Arctocephalus pusillus pusillus) affiliated with family Otariidae. Results show significant differences in microbial community composition of whales, dolphins, and fur seals and indicate that host phylogeny (family level) plays the most important role in shaping the microbial communities, rather than food and environment. In general, the gut microbial communities of dolphins had significantly lower diversity compared to that of whales and fur seals. Overall, the gut microbial communities were mainly composed of Firmicutes and Gammaproteobacteria, together with some from Bacteroidetes, Fusobacteria, and Epsilonbacteraeota. However, specific bacterial lineages were differentially distributed among the marine mammal groups. For instance, Lachnospiraceae, Ruminococcaceae, and Peptostreptococcaceae were the dominant bacterial lineages in the gut of belugas, while for Cape fur seals, Moraxellaceae and Bacteroidaceae were the main bacterial lineages. Moreover, gut microbial communities in both Pacific white-sided dolphins and common bottlenose dolphins were dominated by a number of pathogenic bacteria, including Clostridium perfringens, Vibrio fluvialis, and Morganella morganii, reflecting the poor health condition of these animals. Although there is a growing recognition of the role microorganisms play in the gut of marine mammals, current knowledge about these microbial communities is still severely lacking. Large-scale research studies should be undertaken to reveal the roles played by the gut microbiota of different marine mammal species.

Salinity gradient energy, as a type of blue energy, is a promising sustainable energy source. Its energy conversion efficiency is significantly determined by the selective membranes. Recently, nanofluidic membrane made by two-dimensional (2D) nanomaterials (e.g., graphene) with densely packed nanochannels has been considered as a high-efficient membrane in the osmotic power generation research field. Herein, the graphene oxide-cellulose acetate (GO–CA) heterogeneous membrane was assembled by combining a porous CA membrane and a layered GO membrane; the combination of 2D nanochannels and 3D porous structures make it show high surface-charge-governed property and excellent ion transport stability, resulting in an efficient osmotic power harvesting. A power density of about 0.13 W/m2 is achieved for the sea–river mimicking system and up to 0.55 W/m2 at a 500-fold salinity gradient. With different functions, the CA and GO membranes served as ion storage layer and ion selection layer, respectively. The GO–CA heterogeneous membrane open a promising avenue for fabrication of porous and layered platform for wide potential applications, such as sustainable power generation, water purification, and seawater desalination.

Delirium is increasingly considered to be an important determinant of trajectories of cognitive decline. Therefore, analyses of existing cohort studies measuring cognitive outcomes could benefit from methods to ascertain a retrospective delirium diagnosis. This study aimed to develop and validate such a method for delirium detection using routine medical records in UK and Ireland.A point prevalence study of delirium provided the reference-standard ratings for delirium diagnosis. Blinded to study results, clinical vignettes were compiled from participants' medical records in a standardised manner, describing any relevant delirium symptoms recorded in the whole case record for the period leading up to case-ascertainment. An expert panel rated each vignette as unlikely, possible, or probable delirium and disagreements were resolved by consensus.From 95 case records, 424 vignettes were abstracted by 5 trained clinicians. There were 29 delirium cases according to the reference standard. Median age of subjects was 76.6 years (interquartile range 54.6 to 82.5). Against the original study DSM-IV diagnosis, the chart abstraction method gave a positive likelihood ratio (LR) of 7.8 (95% CI 5.7-12.0) and the negative LR of 0.45 (95% CI 0.40-0.47) for probable delirium (sensitivity 0.58 (95% CI 0.53-0.62); specificity 0.93 (95% CI 0.90-0.95); AUC 0.86 (95% CI 0.82-0.89)). The method diagnosed possible delirium with positive LR 3.5 (95% CI 2.9-4.3) and negative LR 0.15 (95% CI 0.11-0.21) (sensitivity 0.89 (95% CI 0.85-0.91); specificity 0.75 (95% CI 0.71-0.79); AUC 0.86 (95% CI 0.80-0.89)).This chart abstraction method can retrospectively diagnose delirium in hospitalised patients with good accuracy. This has potential for retrospectively identifying delirium in cohort studies where routine medical records are available. This example of record linkage between hospitalisations and epidemiological data may lead to further insights into the inter-relationship between acute illness, as an exposure, for a range of chronic health outcomes.

BACKGROUND: Understanding the role of adjuvants in pesticide persistence is crucial to develop effective pesticide formulations and manage pesticide residues in fresh produce. This study investigated the impact of a commercial non-ionic surfactant product containing alkylphenol ethoxylates (APEOs) on the persistence of thiabendazole on apple and spinach surfaces against the 30 kg m-3 baking soda (sodium bicarbonate, NaHCO3) soaking, which was used to remove the active ingredient (AI) in the cuticular wax layer of fresh produce through alkaline hydrolysis. Surface-enhanced Raman scattering (SERS) mapping method was used to quantify the residue levels on fresh produce surfaces at different experimental scenarios. Four standard curves were established to quantify surface thiabendazole in the absence and presence of APEOs, on apple and spinach leaf surfaces, respectively. RESULTS: Overall, the result showed that APEOs enhanced the persistence of thiabendazole over time. After 3 days of exposure, APEOs increased thiabendazole surface residue against NaHCO3 hydrolysis on apple and spinach surfaces by 5.39% and 10.47%, respectively. CONCLUSION: The study suggests that APEOs led to more pesticide residues on fresh produce and greater difficulty in washing them off from the surfaces using baking soda, posing food safety concerns. [ABSTRACT FROM AUTHOR]

Our understanding of how human skin cells differ according to anatomical site and tumour formation is limited. To address this, we have created a multiscale spatial atlas of healthy skin and basal cell carcinoma (BCC), incorporating in vivo optical coherence tomography, single-cell RNA sequencing, spatial global transcriptional profiling, and in situ sequencing. Computational spatial deconvolution and projection revealed the localisation of distinct cell populations to specific tissue contexts. Although cell populations were conserved between healthy anatomical sites and in BCC, mesenchymal cell populations including fibroblasts and pericytes retained signatures of developmental origin. Spatial profiling and in silico lineage tracing support a hair follicle origin for BCC and demonstrate that cancer-associated fibroblasts are an expansion of a POSTN+ subpopulation associated with hair follicles in healthy skin. RGS5+ pericytes are also expanded in BCC suggesting a role in vascular remodelling. We propose that the identity of mesenchymal cell populations is regulated by signals emanating from adjacent structures and that these signals are repurposed to promote the expansion of skin cancer stroma. The resource we have created is publicly available in an interactive format for the research community. [ABSTRACT FROM AUTHOR]