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To review the current state, hot spots and trends in coffee flavor research for domestic and international regions between 2000 to 2022. Based on bibliometrics, 6818 publications related to this field were identified and retrieved from the core database of Web of Science (WOS), and key information extracted and visually analyzed using software such as CiteSpace and VOSviewer. Extracted fields included authors, keywords, research institutions, countries or regions, and published journals. Collated information was visually displayed, developmental trends of research in this field is discussed, and research hotspots in the field summarized. The results showed an upwards trend in the number of papers on coffee flavor research, with Brazil being the country with the largest number of papers. The Universidade Federal De Lavras (UFLA) was found to be the research institution with the greatest number of publications, while the Journal of Agricultural and Food Chemistry was the journal carrying the most publications in this field. The scholar contributed the most to research in this field was Hofmann from Germany. Research in this field had five directions, namely, the formation mechanism of characteristic aromas, the potential pathogenic risk of compounds, product safety and the utilization of waste, antioxidant activity and bioavailability of compounds, and flavor precursors and planting management. The depth in research in these aspects would show a trend of deepening year by year. This article would provide reference and assistance for future research in the field of coffee flavor.

Abstract Bone formation and deposition are initiated by sensory nerve infiltration in adaptive bone remodeling. Here, we focused on the role of Semaphorin 3A (Sema3A), expressed by sensory nerves, in mechanical loads-induced bone formation and nerve withdrawal using orthodontic tooth movement (OTM) model. Firstly, bone formation was activated after the 3rd day of OTM, coinciding with a decrease in sensory nerves and an increase in pain threshold. Sema3A, rather than nerve growth factor (NGF), highly expressed in both trigeminal ganglion and the axons of periodontal ligament following the 3rd day of OTM. Moreover, in vitro mechanical loads upregulated Sema3A in neurons instead of in human periodontal ligament cells (hPDLCs) within 24 hours. Furthermore, exogenous Sema3A restored the suppressed alveolar bone formation and the osteogenic differentiation of hPDLCs induced by mechanical overload. Mechanistically, Sema3A prevented overstretching of F-actin induced by mechanical overload through ROCK2 pathway, maintaining mitochondrial dynamics as mitochondrial fusion. Therefore, Sema3A exhibits dual therapeutic effects in mechanical loads-induced bone formation, both as a pain-sensitive analgesic and a positive regulator for bone formation.

This study explores the functional attributes of Lactiplantibacillus plantarum (L. plantarum) strains isolated from fermented tomato juice, focusing on their physiological, biochemical, and probiotic characteristics. The identified 66 gram-positive strains included 36 L. plantarum ones, which exhibited robust growth in acidic environments (pH 2.0–5.0) and utilization of various carbohydrates. Notably, seven strains outperformed a commercial strain in extreme acidic conditions. Antioxidant activity varied, with strain A24 showing the highest hydroxyl radical scavenging ability, while strains with high surface hydrophobicity had lower DPPH scavenging activity, indicating no direct correlation between these properties. Strains also showed strain-specific differences in carbohydrate utilization and antibiotic resistance, with some resistant to gentamicin and ciprofloxacin. Survival rates under simulated gastrointestinal conditions were strain-specific, with some strains demonstrating high survival rates, indicating their potential as probiotics. Furthermore, 13 strains used as fermentation starters in tomato juice significantly enhanced antioxidant activity and reduced pH and total soluble solids, indicating efficient sugar utilization and lactic acid production. These findings suggest that L. plantarum strains are well-suited for functional food fermentation and probiotic applications, with strain-specific traits offering versatility for use in acidic food products and probiotic formulations.

In clinical practice and research, the classification and diagnosis of neurological diseases such as Parkinson’s Disease (PD) and Multiple System Atrophy (MSA) have long posed a significant challenge. Currently, deep learning, as a cutting-edge technology, has demonstrated immense potential in computer-aided diagnosis of PD and MSA. However, existing methods rely heavily on manually selecting key feature slices and segmenting regions of interest. This not only increases subjectivity and complexity in the classification process but also limits the model’s comprehensive analysis of global data features. To address this issue, this paper proposes a novel 3D context-aware modeling framework, named 3D-CAM. It considers 3D contextual information based on an attention mechanism. The framework, utilizing a 2D slicing-based strategy, innovatively integrates a Contextual Information Module and a Location Filtering Module. The Contextual Information Module can be applied to feature maps at any layer, effectively combining features from adjacent slices and utilizing an attention mechanism to focus on crucial features. The Location Filtering Module, on the other hand, is employed in the post-processing phase to filter significant slice segments of classification features. By employing this method in the fully automated classification of PD and MSA, an accuracy of 85.71%, a recall rate of 86.36%, and a precision of 90.48% were achieved. These results not only demonstrates potential for clinical applications, but also provides a novel perspective for medical image diagnosis, thereby offering robust support for accurate diagnosis of neurological diseases.

Abstract Microneedles have emerged as a promising platform for transdermal drug delivery with prominent advantages, such as enhanced permeability, mitigated pain, and improved patient adherence. While microneedles have primarily been employed for delivering small molecules, nucleic acids, peptides, and proteins, recent researches have demonstrated their prospect in combination with cell therapy. Cell therapy involving administration or transplantation of living cells (e.g. T cells, stem cells, and pancreatic cells) has gained significant attention in preclinical and clinical applications for various disease treatments. However, the effectiveness of systemic cell delivery may be restricted in localized conditions like solid tumors and skin disorders due to limited penetration and accumulation into the lesions. In this perspective, an overview of recent advances in microneedle‐assisted cell delivery for immunotherapy, tissue regeneration, and hormone modulation, with respect to their mechanical property, cell loading capacity, as well as viability and bioactivity of the loaded cells is provided. Potential challenges and future perspectives with microneedle‐mediated cell therapy are also discussed.

Background: Previous research revealed differences in cerebellar white matter integrity by disease stages, indicating a compensatory role in Parkinson’s disease (PD). However, the temporal evolution of cerebellar white matter microstructure in patients with PD (PwPD) remains unclear. Objective: To unravel temporal evolution of cerebellar white matter and its dopaminergic correlates in PD. Methods: We recruited 124 PwPD from the PPMI study. The participants were divided into two subsets: Subset 1 (n = 41) had three MRI scans (baseline, 2 years, and 4 years), and Subset 2 (n = 106) had at least two MRI scans at baseline, 1 year, and/or 2 years. Free water-corrected diffusion metrics were used to measure the microstructural integrity in cerebellar peduncles (CP), the main white matter tracts connecting to and from the cerebellum. The ACAPULCO processing pipeline was used to assess cerebellar lobules volumes. Linear mixed-effect models were used to study longitudinal changes. We also examined the relationships between microstructural integrity in CP, striatal dopamine transporter specific binding ratio (SBR), and clinical symptoms. Results: Microstructural changes in CP showed a non-linear pattern in PwPD. Free water-corrected fractional anisotropy (FAt) increased in the first two years but declined from 2 to 4 years, while free water-corrected mean diffusivity exhibited the opposite trend. The initial increased FAt in CP correlated with cerebellar regional volume atrophy, striatal dopaminergic SBR decline, and worsening clinical symptoms, but this correlation varied across disease stages. Conclusions: Our findings suggest a non-linear evolution of microstructural integrity in CP throughout the course of PD, indicating the adaptive structural reorganization of the cerebellum simultaneously with progressive striatal dopaminergic degeneration in PD.

Despite recent progress, machine learning methods remain inadequate in modeling the natural protein-protein interaction (PPI) hierarchy for PPI prediction. Here, the authors present a double-viewed hierarchical graph learning model, HIGH-PPI, to predict PPIs and extrapolate the molecular details involved.

With the rapid development of wind power generation， the impact of the construction and operation of utility-scale wind farms on the local climate has attracted extensive attention.In order to study the characteristics of the local climatic response to the deployment of wind farms under different surface conditions， the area from Wulan Chaka to Gonghe Shazhu Yuxiang， which is located in the southwest of Qinghai Lake， was chosen as center， and the mesoscale meteorological numerical model WRF （Weather Research and Forecasting Model） and the Fitch wind turbine model were carried out under the conditions of flat canyons， high-altitude mountains and water body， respectively.The results showed that： Under the ideal situation of the same installed capacity， the averaged wind speed inside the wind farms showed the significant decrease trends under the three sensitivity experiments， and the amplitude and scope of wind speed attenuation was stronger during nighttime than that during the daytime， and the wind speed attenuation in the vertical direction can reached up to 600 m.The 2 m temperature inside the wind farms located in flat canyons or water body mainly decreased， which was possibly related to the negative temperature gradient and the water evaporation enhancement， and the temperature cooling was more significant during nighttime while no significant changes in 2 m temperature were detected over the mountain wind farm.Meanwhile， the changes of 2 m humidity inside the wind farms were not obvious， and the overall decreased trends were mainly weak during nighttime.Due to rotation of the wind turbine， the planetary boundary layer height increased significantly.The characteristics of the local climatic response to the deployment of wind farms under different surface conditions were different， which was mainly related to the different climatic features under different surface conditions， and was also affected by the spatial layout of wind turbines.These results can provide some support for the design of climate-friendly wind farms.

IntroductionSeasonal allergic rhinitis (SAR) is a major health problem with a relatively high worldwide prevalence that severely limits the quality of life for sufferers. Acupuncture is widely used for SAR treatment in China; however, the evidence on the efficacy of acupuncture at the sphenopalatine ganglion (SPG) for SAR is inconclusive. Therefore, this study aims to investigate the efficacy and safety of acupuncture at the SPG acupoint for the treatment of SAR.Methods and analysisA total of 120 participants with SAR will be recruited and randomly assigned to the acupuncture group, placebo acupuncture (PA) group, or rescue medication (RM) group with a 1:1:1 allocation ratio. Participants in the acupuncture group and PA group will receive 8 sessions of acupuncture stimulus at the SPG plus RM or 8 sessions of shallow needling at the SPG acupoint plus RM for 4 weeks with a 4-week follow-up in the first year and a 1-week follow-up in the second year. Participants in the RM group will only receive RM throughout the study. The primary outcome is the change from baseline in the average daily combined symptoms and medication score (CSMS) over weeks 1–4. All analysis will be based on an intention-to-treat principle. All statistical tests will be two-sided and a p-value < 0.05 will be considered to be statistically significant.

In this paper, five new joints of special-shaped double-web steel-reinforced concrete (SDSRC) columns connected with steel beams are designed. The load-displacement curves, joint yield states and damage forms of the beam ends of the five joints under monotonic loading with the same axial pressure ratio are investigated. Additionally, the hysteresis performance, strength and stiffness degradation under cyclic loading are studied. The results show that the bearing capacity of joints with studs can increase by approximately 10%. Since the arrangement of multiple rows of studs at the connection between the beam web and the column has better force transfer performance and concrete synergy behavior, the failure modes of these joints are plastic hinge formation at the end of the beam, satisfying strong column-weak beam requirements. Moreover, these joints exhibit good ductility and energy dissipation capacity under cyclic loading, and their strength and stiffness gradually decrease. In contrast, joints with single-row studs or without studs at the connection between beam web and column exhibit beam flange buckling rather than full-section plastic hinge formation at the beam end, and tensile deformation of column web is larger. Although these joints exhibit good ductility performance, their energy dissipation capacity is weaker than that of joints with multiple rows of studs at the beam web-column connection.

In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing, multi-material bioprinting has become a common solution to construct tissue models in vitro . With the embedded printing method, complex 3D structure can be printed using soft biomaterials with reasonable shape fidelity. However, the current sequential multi-material embedded printing method faces a major challenge, which is the inevitable trade-off between the printed structural integrity and printing precision. Here, we propose a simultaneous multi-material embedded printing method. With this method, we can easily print firmly attached and high-precision multilayer structures. With multiple individually controlled nozzles, different biomaterials can be precisely deposited into a single crevasse, minimizing uncontrolled squeezing and guarantees no contamination of embedding medium within the structure. We analyse the dynamics of the extruded bioink in the embedding medium both analytically and experimentally, and quantitatively evaluate the effects of printing parameters including printing speed and rheology of embedding medium, on the 3D morphology of the printed filament. We demonstrate the printing of double-layer thin-walled structures, each layer less than 200 μ m, as well as intestine and liver models with 5% gelatin methacryloyl that are crosslinked and extracted from the embedding medium without significant impairment or delamination. The peeling test further proves that the proposed method offers better structural integrity than conventional sequential printing methods. The proposed simultaneous multi-material embedded printing method can serve as a powerful tool to support the complex heterogeneous structure fabrication and open unique prospects for personalized medicine.

Deep learning has been proven to provide solutions for computational ghost imaging (CGI). However, in current CGI techniques, the quality of the reconstructed image is adversely affected by the position and intensity of the scattering medium. In this study, the feasibility of using a deep neural network (DNN) by using the hybrid simulated data to facilitate CGI through a scattering medium is demonstrated, particularly when the scattering medium is in front of an object. Under a specific order of the measurement matrix, the CGI measurement equation is introduced along with a disturbance factor of the scattering effect to generate simulation data, thereby representing imaging situations with the scattering medium at different positions. The selection of disturbance parameters is determined by the correlation between the simulation signal and the experimental signal. Then an end-to-end DNN is trained using experimentally obtained light intensity signals, and it shows that the quality of the reconstruction results is improved when there is a scattering medium in the emission path. The reported technique effectively solves the problem of CGI reconstruction under different scattering paths with a common DNN, and may have broad applications in fast adaptive CGI for new and uncertain scenarios.

Caffeine is chemically stable and not readily oxidized under normal physiological conditions but also has antioxidant effects, although the underlying molecular mechanism is not well understood. Superoxide dismutase (SOD) 2 is a manganese-containing enzyme located in mitochondria that protects cells against oxidative stress by scavenging reactive oxygen species (ROS). SOD2 activity is inhibited through acetylation under conditions of stress such as exposure to ultraviolet (UV) radiation. Sirtuin 3 (SIRT3) is the major mitochondrial nicotinamide adenine dinucleotide (NAD+)-dependent deacetylase, which deacetylates two critical lysine residues (lysine 68 and lysine 122) on SOD2 and promotes its antioxidative activity. In this study, we investigated whether the antioxidant effect of caffeine involves modulation of SOD2 by SIRT3 using in vitro and in vivo models. The results show that caffeine interacts with SIRT3 and promotes direct binding of SIRT3 with its substrate, thereby enhancing its enzymatic activity. Mechanistically, caffeine bound to SIRT3 with high affinity (KD = 6.858 × 10–7 M); the binding affinity between SIRT3 and its substrate acetylated p53 was also 9.03 (without NAD+) or 6.87 (with NAD+) times higher in the presence of caffeine. Caffeine effectively protected skin cells from UV irradiation-induced oxidative stress. More importantly, caffeine enhanced SIRT3 activity and reduced SOD2 acetylation, thereby leading to increased SOD2 activity, which could be reversed by treatment with the SIRT3 inhibitor 3-(1H-1,2,3-triazol-4-yl) pyridine (3-TYP) in vitro and in vivo. Taken together, our results show that caffeine targets SIRT3 to enhance SOD2 activity and protect skin cells from UV irradiation-induced oxidative stress. Thus, caffeine, as a small-molecule SIRT3 activator, could be a potential agent to protect human skin against UV radiation.

A novel fuzzy rule is proposed to adopt a positive pitch strategy when the error between the measured and rated generator speed becomes large and continues to increase, and to adopt a negative pitch strategy when the error is small. The improved approach is introduced into the normal Fuzzy-Proportional-Integral (Fuzzy-PI) control strategy by dividing the fuzzy rules into four areas and analyzing the design method for each area. Furthermore, a low pass filter is used to reduce the ultimate loads of the pitch driver caused by the novel fuzzy rules. The modeling of the wind turbine load under turbulent wind conditions is conducted in GH Bladed, and MATLAB/Simulink is used to interact with the modeling to verify the novel Fuzzy-PI control. The results show that, compared with normal Fuzzy-PI control, the novel Fuzzy-PI control can greatly reduce the ultimate loads and fatigue loads of the pitch driver. The novel Fuzzy-PI control not only reduces the extremum of power deviation, but also decreases some ultimate loads and fatigue loads of the tower base and the blade root. It can reduce these loads by up to 21.53% under the normal turbulent wind condition and by up to 18.14% under the extreme turbulent wind condition.