Promotional language and the adoption of innovative ideas in science.

How are the merits of innovative ideas communicated in science? Here, we conduct semantic analyses of grant application success with a focus on scientific promotional language, which may help to convey an innovative idea's originality and significance. Our analysis attempts to surmount the limitations of prior grant studies by examining the full text of tens of thousands of both funded and unfunded grants from three leading public and private funding agencies: the NIH, the NSF, and the Novo Nordisk Foundation, one of the world's largest private science funding foundations. We find a robust association between promotional language and the support and adoption of innovative ideas by funders and other scientists. First, a grant proposal's percentage of promotional language is associated with up to a doubling of the grant's probability of being funded. Second, a grant's promotional language reflects its intrinsic innovativeness. Third, the percentage of promotional language is predictive of the expected citation and productivity impact of publications that are supported by funded grants. Finally, a computer-assisted experiment that manipulates the promotional language in our data demonstrates how promotional language can communicate the merit of ideas through cognitive activation. With the incidence of promotional language in science steeply rising, and the pivotal role of grants in converting promising and aspirational ideas into solutions, our analysis provides empirical evidence that promotional language is associated with effectively communicating the merits of innovative scientific ideas.

An integrated investigation of sulfotransferases (SULTs) in hepatocellular carcinoma and identification of the role of SULT2A1 on stemness.

The cytosolic sulfotransferases (SULTs) are phase II conjugating enzymes, which are widely expressed in the liver and mainly mediate the sulfation of numerous xenobiotics and endogenous compounds. However, the role of various SULTs genes has not been reported in hepatocellular carcinoma (HCC). This study aims to analyze the expression and potential functional roles of SULTs genes in HCC and to identify the role of SULT2A1 in HCC stemness as well as the possible mechanism. We found that all of the 12 SULTs genes were differentially expressed in HCC. Moreover, clinicopathological features and survival rates were also investigated. Multivariate regression analysis showed that SULT2A1 and SULT1C2 could be used as independent prognostic factors in HCC. SULT1C4, SULT1E1, and SULT2A1 were significantly associated with immune infiltration. SULT2A1 deficiency in HCC promoted chemotherapy resistance and stemness maintenance. Mechanistically, silencing of SULT2A1 activated the AKT signaling pathway, on the one hand, promoted the expression of downstream stemness gene c-Myc, on the other hand, facilitated the NRF2 expression to reduce the accumulation of ROS, and jointly increased HCC stemness. Moreover, knockdown NR1I3 was involved in the transcriptional regulation of SULT2A1 in stemness maintenance. In addition, SULT2A1 knockdown HCC cells promoted the proliferation and activation of hepatic stellate cells (HSCs), thereby exerting a potential stroma remodeling effect. Our study revealed the expression and role of SULTs genes in HCC and identified the contribution of SULT2A1 to the initiation and progression of HCC.

Stable SERS Detection of Lactobacillus fermentum Using Optical Tweezers in a Microfluidic Environment.

Rapid identification of fermented lactic acid bacteria has long been a challenge in the brewing industry. This study combined label-free surface-enhanced Raman scattering (SERS) and optical tweezer technology to construct a test platform within a microfluidic environment. Six kinds of lactic acid bacteria common in industry were tested to prove the stability of the SERS spectra. The results demonstrated that the utilization of optical tweezers to securely hold the bacteria significantly enhanced the stability of the SERS spectra. Furthermore, SVM and XGBoost machine learning algorithms were utilized to analyze the obtained Raman spectra for identification, and the identification accuracies exceeded 95% for all tested lactic acid bacteria. The findings of this study highlight the crucial role of optical tweezers in improving the stability of SERS spectra by capturing bacteria in a microfluidic environment, prove that this technology could be used in the rapid identification of lactic acid bacteria, and show great significance in expanding the applicability of the SERS technique for other bacterial testing purposes.

Isotope-Edited Variable Temperature Infrared Spectroscopy for Measuring Transition Temperatures of Single A-T Watson-Crick Base Pairs in DNA Duplexes.

Experimental methods to determine transition temperatures for individual base pair melting events in DNA duplexes are lacking despite intense interest in these thermodynamic parameters. Here, we determine the dimensions of the thymine (T) C2═O stretching vibration when it is within the DNA duplex via isotopic substitutions at other atomic positions in the structure. First, we determined that this stretching state was localized enough to specific atoms in the molecule to make submolecular scale measurements of local structure and stability in high molecular weight complexes. Next, we develop a new isotope-edited variable temperature infrared method to measure melting transitions at various locations in a DNA structure. As an initial test of this "sub-molecular scale thermometer", we applied our T13C2 difference infrared signal to measure location-dependent melting temperatures (TmL) in a DNA duplex via variable temperature attenuated total reflectance Fourier transform infrared (VT-ATR-FTIR) spectroscopy. We report that the TmL of a single Watson-Crick A-T base pair near the end of an A-T rich sequence (poly T) is ∼34.9 ± 0.7°C. This is slightly lower than the TmL of a single base pair near the middle position of the poly T sequence (TmL ∼35.6±0.2°C). In addition, we also report that the TmL of a single Watson-Crick A-T base pair near the end of a 50% G-C sequence (12-mer) is ∼52.5 ± 0.3°C, which is slightly lower than the global melting Tm of the 12-mer sequence (TmL ∼54.0±0.9°C). Our results provide direct physical evidence for end fraying in DNA sequences with our novel spectroscopic methods.

Omaveloxolone ameliorates glucocorticoid-induced osteonecrosis of the femoral head by promoting osteogenesis and angiogenesis.

Steroid (glucocorticoid)-induced necrosis of the femoral head (SONFH) represents a prevalent, progressive, and challenging bone and joint disease characterized by diminished osteogenesis and angiogenesis. Omaveloxolone (OMA), a semi-synthetic oleanocarpane triterpenoid with antioxidant, anti-inflammatory, and osteogenic properties, emerges as a potential therapeutic agent for SONFH. This study investigates the therapeutic impact of OMA on SONFH and elucidates its underlying mechanism. The in vitro environment of SONFH cells was simulated by inducing human bone marrow mesenchymal stem cells (hBMSCs) and human umbilical vein endothelial cells (HUVECs) using dexamethasone (DEX).Various assays, including CCK-8, alizarin red staining, Western blot, qPCR, immunofluorescence, flow cytometry, and TUNNEL, were employed to assess cell viability, STING/NF-κB signaling pathway-related proteins, hBMSCs osteogenesis, HUVECs migration, angiogenesis, and apoptosis. The results demonstrate that OMA promotes DEX-induced osteogenesis, HUVECs migration, angiogenesis, and anti-apoptosis in hBMSCs by inhibiting the STING/NF-κB signaling pathway. This experimental evidence underscores the potential of OMA in regulating DEX-induced osteogenesis, HUVECs migration, angiogenesis, and anti-apoptosis in hBMSCs through the STING/NF-κB pathway, thereby offering a promising avenue for improving the progression of SONFH.

Isolation, identification, and pathogenicity of two novel goose astrovirus from goslings with severe gout in China.

Goose astroviruses (GAstVs) are important pathogens which can cause gout in goslings leading to huge economic losses for the goose farming industry in China. In 2023, an infectious disease characterized by visceral gout broke out in commercial goose farms in Guangxi and Guangdong provinces of China. In this study, two GAstV strains of GXNN and GDCS were successfully isolated from these two disease-ridden goose farms. The complete genomic lengths of these two strains were 7166 bp, and phylogenetic analysis showed that they were both GAstV-2 subtypes. The 3-dimensional structures of the capsid protein were predicted and six characteristic mutation sites at amino acid positions 60, 61, 228, 229, 456 and 523 were found within the strong antigenic regions. A recombination event occurred at 6833-7070 nt between the GAstV TZ03 and Turkey astrovirus CA/00 and this was detected in both the GXNN and GDCS strains. Another recombinant event occurred at 63-2747 nt between the GAstV XT1 and GAstV SDPY and this was detected in the GDCS strain. When 1-day-old goslings were infected with the novel GXNN and GDCS strains, they showed severe visceral gout. This was accompanied by enlarged spleens, liver hemorrhages and urate deposits in the kidneys and ureters and their blood urea nitrogen levels were significantly elevated. The mortality rates of the GXNN- and GDCS-infected groups were pathogenically high at 80 % and 60 %, respectively. These results will promote our understanding of the evolution and epidemic potential of GAstVs in China.

CD11b maintains West Nile virus replication through modulation of immune response in human neuroblastoma cells.

BACKGROUND: West Nile virus (WNV) is a rapidly spreading mosquito-borne virus accounted for neuroinvasive diseases. An insight into WNV-host factors interaction is necessary for development of therapeutic approaches against WNV infection. CD11b has key biological functions and been identified as a therapeutic target for several human diseases. The purpose of this study was to determine whether CD11b was implicated in WNV infection. METHODS: SH-SY5Y cells with and without MEK1/2 inhibitor U0126 or AKT inhibitor MK-2206 treatment were infected with WNV. CD11b mRNA levels were assessed by real-time PCR. WNV replication and expression of stress (ATF6 and CHOP), pro-inflammatory (TNF-α), and antiviral (IFN-α, IFN-ß, and IFN-γ) factors were evaluated in WNV-infected SH-SY5Y cells with CD11b siRNA transfection. Cell viability was determined by MTS assay. RESULTS: CD11b mRNA expression was remarkably up-regulated by WNV in a time-dependent manner. U0126 but not MK-2206 treatment reduced the CD11b induction by WNV. CD11b knockdown significantly decreased WNV replication and protected the infected cells. CD11b knockdown markedly increased TNF-α, IFN-α, IFN-ß, and IFN-γ mRNA expression induced by WNV. ATF6 mRNA expression was reduced upon CD11b knockdown following WNV infection. CONCLUSION: These results demonstrate that CD11b is involved in maintaining WNV replication and modulating inflammatory as well as antiviral immune response, highlighting the potential of CD11b as a target for therapeutics for WNV infection.

Short-Term Prognostic Effect of Comprehensive Complication Index in Patients With Gastric Cardia Adenocarcinoma.

INTRODUCTION: The Clavien-Dindo Classification (CDC) has been traditionally used for assessing postoperative complications. Recently, the Comprehensive Complication Index (CCI) has been introduced as a new tool. However, its prognostic significance in Gastric Cardia Adenocarcinoma (GCA) is yet to be determined. METHODS: The CCI and CDC of 203 patients who underwent radical surgery for GCA at Jinling Hospital from 2016 to 2023 were evaluated. Primary outcome variables included Hospital Length of Stay, duration of intensive care unit stay postoperatively, time to return to normal activities, and total hospitalization cost. The area under the curve was used to measure the correlation strength of the CCI and CDC for these outcomes. RESULTS: The CCI demonstrated superior association strength, indicated by higher area under the curve values for all primary outcome variables compared to the CDC: Hospital Length of Stay (0.956 versus 0.910), intensive care unit stay duration (0.969 versus 0.954), time to return to normal activities (0.983 versus 0.962), and total hospitalization cost (0.925 versus 0.911). CONCLUSIONS: The CCI showed a stronger positive association than the CDC with short-term postoperative complications in GCA. It has potential implications for improving postoperative patient management.

DeepKa Web Server: High-Throughput Protein pKa Prediction.

DeepKa is a deep-learning-based protein pKa predictor proposed in our previous work. In this study, a web server was developed that enables online protein pKa prediction driven by DeepKa. The web server provides a user-friendly interface where a single step of entering a valid PDB code or uploading a PDB format file is required to submit a job. Two case studies have been attached in order to explain how pKa's calculated by the web server could be utilized by users. Finally, combining the web server with post processing as described in case studies, this work suggests a quick workflow of investigating the relationship between protein structure and function that are pH dependent. The web server of DeepKa is freely available at http://www.computbiophys.com/DeepKa/main.

Early and mid-term outcomes of open thoracoabdominal aortic aneurysm repair after thoracic endovascular aortic repair.

OBJECTIVE: To evaluate the early and mid-term outcomes of open repair in patients with thoracoabdominal aortic aneurysm (TAAA) after thoracic endovascular aortic repair (TEVAR). METHODS: This was a retrospective single center study. Data were retrospectively collected and analyzed for consecutive patients undergoing open TAAA repair (TAAAR) after TEVAR from November 2016 to June 2021. Indications for TAAAR included aneurysm progression due to endoleak, persisted false lumen perfusion, proximal/distal disease progression, and aorta rupture. The risk factor of operative mortality was analyzed by multivariable logistic regression model and the survival was evaluated by Kaplan-Meier. RESULTS: Sixty-three patients who met the inclusion criteria for the study were identified. The mean age at TAAAR was 41 ± 12 years and 43 (68.3%) were male. Marfan syndrome (MFS) was presented in 39 patients (61.9%). 60 (95.2%) patients presented with post-dissection aneurysm and 3 (4.8%) patients with degenerative aneurysm. The extent of TAAA was Crawford I in 9 (14.3%), II in 22 (34.9%), III in 23 (36.5%), and IV in 9 (14.3%). Emergent TAAAR was done in 10 (15.9%) patients, and deep hypothermic circulatory arrest was used in 22 (34.6%). Endograft was explanted in 31 (49.2%). Operative mortality was 11 (17.5%). Stroke, paraplegia, and acute kidney failure occurred in 5 (7.9%), 7 (11.1%), and 6 (9.5%) patients, respectively. Pulmonary complications occurred in 19 (30.2%) patients. The estimated survival was 74.8 ± 4.9% at 5 years. Late reoperations were performed in 2 patients at 2.5 years and 1.3 years, respectively. CONCLUSIONS: In this series of TAAA after TEVAR, TAAAR was related with a high risk of operative mortality and morbidity and the midterm outcomes represented a durable treatment and were respectable.

Development and validation of a risk prediction model for invasiveness of pure ground-glass nodules based on a systematic review and meta-analysis.

BACKGROUND: Assessing the aggressiveness of pure ground glass nodules early on significantly aids in making informed clinical decisions. OBJECTIVE: Developing a predictive model to assess the aggressiveness of pure ground glass nodules in lung adenocarcinoma is the study's goal. METHODS: A comprehensive search for studies on the relationship between computed tomography(CT) characteristics and the aggressiveness of pure ground glass nodules was conducted using databases such as PubMed, Embase, Web of Science, Cochrane Library, Scopus, Wanfang, CNKI, VIP, and CBM, up to December 20, 2023. Two independent researchers were responsible for screening literature, extracting data, and assessing the quality of the studies. Meta-analysis was performed using Stata 16.0, with the training data derived from this analysis. To identify publication bias, Funnel plots and Egger tests and Begg test were employed. This meta-analysis facilitated the creation of a risk prediction model for invasive adenocarcinoma in pure ground glass nodules. Data on clinical presentation and CT imaging features of patients treated surgically for these nodules at the Third Affiliated Hospital of Kunming Medical University, from September 2020 to September 2023, were compiled and scrutinized using specific inclusion and exclusion criteria. The model's effectiveness for predicting invasive adenocarcinoma risk in pure ground glass nodules was validated using ROC curves, calibration curves, and decision analysis curves. RESULTS: In this analysis, 17 studies were incorporated. Key variables included in the model were the largest diameter of the lesion, average CT value, presence of pleural traction, and spiculation. The derived formula from the meta-analysis was: 1.16×the largest lesion diameter + 0.01 × the average CT value + 0.66 × pleural traction + 0.44 × spiculation. This model underwent validation using an external set of 512 pure ground glass nodules, demonstrating good diagnostic performance with an ROC curve area of 0.880 (95% CI: 0.852-0.909). The calibration curve indicated accurate predictions, and the decision analysis curve suggested high clinical applicability of the model. CONCLUSION: We established a predictive model for determining the invasiveness of pure ground-glass nodules, incorporating four key radiological indicators. This model is both straightforward and effective for identifying patients with a high likelihood of invasive adenocarcinoma.

H3K27ac modification and transcription characteristics of adipose and muscle tissues in Chuxiang Black pig.

The establishment of high-quality pork breeds for improving meat quality in the pig industry is needed. The Chuxiang Black (CX) pig is a new breed developed from Chinese local pigs and Western lean pigs that has a high proportion of lean meat and excellent meat quality. However, the characteristics of cis-regulatory elements in CX pigs are still unknown. In this study, cis-regulatory elements of muscle and adipose tissues in CX pigs were investigated using ChIP-seq and RNA sequencing. Compared with the reported cis-regulatory elements of muscle and adipose tissues, 1768 and 1012 highly activated enhancers and 433 and 275 highly activated promoters in CX muscle and adipose tissues were identified, respectively. Motif analysis showed that transcription factors, such as MEF2A and MEF2C, were core regulators of highly activated enhancers and promoters in muscle. Similarly, the transcription factors JUNB and CUX1 were identified as essential for highly activated enhancers and promoters in CX adipose tissue. These results enrich the resources for the analysis of cis-regulatory elements in the pig genome and provide new basic data for further meat quality improvement through breeding in pigs.

Comparison of different surgical approaches for treating aortic graft infections.

BACKGROUND: There is still no guideline or consensus on the treatment of aortic graft infection. This study reported and compared conservative and surgical treatment and different surgical methods for aortic graft infection. METHODS: Data from aortic graft infections treated at our institution between February 2017 and June 2022 were retrospectively analyzed. Clinical data and surgical approaches were evaluated. RESULTS: This article retrospectively analyzed the treatment and prognosis of 48 patients (43 males) with aortic graft infection. The patients were divided into conservative treatment group (n = 15) and surgical treatment group (n = 33). During follow-up, the mortality rate of the conservative treatment group was significantly higher than that of the surgical treatment group (P<0.05). The survival curve also showed that the survival time of the surgical treatment group was longer than that of the conservative treatment group (P<0.05). The surgical treatment group included local treatment (n=5), in situ replacement (n=8) and bypass surgery (n=20) groups. There was no significant difference in the mortality rate at 1 month or final follow-up among the local treatment, in situ replacement and bypass surgery groups. CONCLUSION: Surgical treatment is the optimal option for treating aortic graft infections compared to conservative treatment.

Association between vascular aging and cognitive function in Chinese adults.

BACKGROUND: Vascular health has been associated with cognition but related evidence is limited in Chinese. The objective of this study was to examine the association of vascular aging assessed by arterial stiffness and blood pressure with cognitive function in an unselected Chinese population. METHODS: In the Tianning Cohort (N = 5158), indicators of arterial stiffness and blood pressure including carotid-femoral pulse wave velocity (cfPWV), ankle-brachial index (ABI), pulse pressure (PP), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were measured. Cognitive function was assessed using the Mini Mental State Examination (MMSE) questionnaire. We applied Poisson regression and logistic regression to examine the associations of vascular aging and blood pressure with cognitive function. RESULTS: 76 (1.47%) participants had impaired cognitive function diagnosed by a MMSE score of less than 24 points. Participants with a higher level of PP were more likely to have a decreased score of MMSE (ß=-0.0121, P < 0.001 for log-transformed pulse pressure) and a higher risk of having impaired cognitive function (OR = 5.95, 95%CI: 2.02-17.79, P < 0.001 for log-transformed PP). Per standard deviation increment in SBP was significantly associated with lower MMSE score (ß=-0.0020, P < 0.001) and impaired cognitive function (OR = 1.69, 95%CI: 1.38-2.06, P < 0.001). No significant associations were found regarding other parameters. CONCLUSIONS: Blood pressure and hypertension were associated with cognitive function in Chinese adults. PP may be a potential predictor for impaired cognitive function.

Clinical efficiency of three-port inflatable robot-assisted thoracoscopic surgery in mediastinal tumor resection.

BACKGROUND: Aimed to assess clinical effect of three-port inflatable robot-assisted thoracoscopic surgery in mediastinal tumor resection by comparing results of the robot group with the video group. METHODS: Retrospectively analyze 179 patients diagnosed with anterior mediastinal tumor from May 2017 to August 2021. Two groups were divided according to the surgical approach, including 92 cases in the RATS group and 87 cases in the VATS group. The results were analyzed between two groups with variables of age, sex, BMI, tumor size, and diagnosis. Perioperative clinical data was gathered to compare. RESULT: There were no significant differences between the 2 groups with regards to demographic data and clinical features. There were no significant differences inoperative time and duration of chest tube via RATS vs. VATS. The intraoperative blood loss was statistically significantly different among the RATS and VATS groups (75.9 ± 39.6 vs. 97.4 ± 35.8 ml p = 0.042). The postoperative stay of patients in RATS group were significantly shorter than that in VATS group (2.3 ± 1.0 vs. 3.4 ± 1.4 day p = 0.035), CONCLUSION: Three-port inflatable robot-assisted thoracoscopic surgery for mediastinal tumor is feasible and reliable it is more advantageous, and it provides the surgeon with advice on treatment choice.

DEFM: Delay-embedding-based forecast machine for time series forecasting by spatiotemporal information transformation.

Making accurate forecasts for a complex system is a challenge in various practical applications. The major difficulty in solving such a problem concerns nonlinear spatiotemporal dynamics with time-varying characteristics. Takens' delay embedding theory provides a way to transform high-dimensional spatial information into temporal information. In this work, by combining delay embedding theory and deep learning techniques, we propose a novel framework, delay-embedding-based forecast Machine (DEFM), to predict the future values of a target variable in a self-supervised and multistep-ahead manner based on high-dimensional observations. With a three-module spatiotemporal architecture, the DEFM leverages deep neural networks to effectively extract both the spatially and temporally associated information from the observed time series even with time-varying parameters or additive noise. The DEFM can accurately predict future information by transforming spatiotemporal information to the delay embeddings of a target variable. The efficacy and precision of the DEFM are substantiated through applications in three spatiotemporally chaotic systems: a 90-dimensional (90D) coupled Lorenz system, the Lorenz 96 system, and the Kuramoto-Sivashinsky equation with inhomogeneity. Additionally, the performance of the DEFM is evaluated on six real-world datasets spanning various fields. Comparative experiments with five prediction methods illustrate the superiority and robustness of the DEFM and show the great potential of the DEFM in temporal information mining and forecasting.

Spontaneous recovery in random hypergraphs.

In many real-world phenomena, such as the reconstruction of disaster areas after an earthquake or the stock market's recovery after an economic crisis, damaged networks are spontaneously active after receiving assistance. To reveal how the recovery process, the research of dynamic network recovery has become a hot topic in the field of network science. Previous studies on network recovery have been limited to simple networks with pairwise interactions. However, real-world systems are usually networks with higher-order interactions that are composed of multiple units. To better understand the recovery phenomenon on complex networks in the real world, we propose a novel spontaneous recovery model applied to hypergraphs. The model considers two types of recovery, internal recovery and fast recovery, where inactive nodes in the network can either recover internally with independent probabilities or receive sufficient resources from the hyperedge for fast recovery. We find that the number of active nodes in the system shows a phase change from continuous to discontinuous as the fast recovery condition is relaxed. Moreover, under the influence of higher-order interactions, increasing both average hyperedge cardinality and network heterogeneity contribute to increasing the network resilience. These findings help us understand the recovery mechanisms of complex networks and provide essential insights into designing highly resilient systems.

Enhancing Aboveground Biomass Prediction through Integration of the SCDR Paradigm into the U-Like Hierarchical Residual Fusion Model.

Deep learning methodologies employed for biomass prediction often neglect the intricate relationships between labels and samples, resulting in suboptimal predictive performance. This paper introduces an advanced supervised contrastive learning technique, termed Improved Supervised Contrastive Deep Regression (SCDR), which is adept at effectively capturing the nuanced relationships between samples and labels in the feature space, thereby mitigating this limitation. Simultaneously, we propose the U-like Hierarchical Residual Fusion Network (BioUMixer), a bespoke biomass prediction network tailored for image data. BioUMixer enhances feature extraction from biomass image data, facilitating information exchange and fusion while considering both global and local features within the images. The efficacy of the proposed method is validated on the Pepper_Biomass dataset, which encompasses over 600 original images paired with corresponding biomass labels. The results demonstrate a noteworthy enhancement in deep regression tasks, as evidenced by performance metrics on the Pepper_Biomass dataset, including RMSE = 252.18, MAE = 201.98, and MAPE = 0.107. Additionally, assessment on the publicly accessible GrassClover dataset yields metrics of RMSE = 47.92, MAE = 31.74, and MAPE = 0.192. This study not only introduces a novel approach but also provides compelling empirical evidence supporting the digitization and precision improvement of agricultural technology. The research outcomes align closely with the identified problem and research statement, underscoring the significance of the proposed methodologies in advancing the field of biomass prediction through state-of-the-art deep learning techniques.

MultiFuseYOLO: Redefining Wine Grape Variety Recognition through Multisource Information Fusion.

Based on the current research on the wine grape variety recognition task, it has been found that traditional deep learning models relying only on a single feature (e.g., fruit or leaf) for classification can face great challenges, especially when there is a high degree of similarity between varieties. In order to effectively distinguish these similar varieties, this study proposes a multisource information fusion method, which is centered on the SynthDiscrim algorithm, aiming to achieve a more comprehensive and accurate wine grape variety recognition. First, this study optimizes and improves the YOLOV7 model and proposes a novel target detection and recognition model called WineYOLO-RAFusion, which significantly improves the fruit localization precision and recognition compared with YOLOV5, YOLOX, and YOLOV7, which are traditional deep learning models. Secondly, building upon the WineYOLO-RAFusion model, this study incorporated the method of multisource information fusion into the model, ultimately forming the MultiFuseYOLO model. Experiments demonstrated that MultiFuseYOLO significantly outperformed other commonly used models in terms of precision, recall, and F1 score, reaching 0.854, 0.815, and 0.833, respectively. Moreover, the method improved the precision of the hard to distinguish Chardonnay and Sauvignon Blanc varieties, which increased the precision from 0.512 to 0.813 for Chardonnay and from 0.533 to 0.775 for Sauvignon Blanc. In conclusion, the MultiFuseYOLO model offers a reliable and comprehensive solution to the task of wine grape variety identification, especially in terms of distinguishing visually similar varieties and realizing high-precision identifications.

Bioenzyme-free colorimetric assay for creatinine determination based on Mn3O4 nanoparticles catalyzed oxidation of 3,3',5,5'-tetramethylbenzidine.

Mn3O4 nanozyme with good oxidase-like activity was successfully synthesized. The prepared Mn3O4 nanozyme can directly and effectively catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to generate green-blue-colored ox-TMB. Creatinine exhibits distinct inhibition effect on Mn3O4 nanozyme-catalyzed TMB colorimetric reaction system, leading to obvious color fading and absorbance intensity decrease of the reaction system. Furthermore, interference from uric acid can be effectively eliminated by regulating the pH of TMB-Mn3O4 colorimetric reaction system to pH 2.0. Then, a simple and bioenzyme-free colorimetric assay for the determination of creatinine was developed based on TMB-Mn3O4 colorimetric reaction. The linear detection range is from 100 to 800 µM and from 1 to 20 mM. The lowest limit of detection is 35.3 µM. Satisfied results are obtained for the determination of creatinine in real urine and sweat samples. This work provides the synthesis of a good oxidase-like nanozyme Mn3O4 and presents the fabrication of an effective nanozyme-based bioenzyme-free colorimetric assay for the determination of creatinine.