AI-Enabled Crop Management Framework for Pest Detection Using Visual Sensor Data.

Our research focuses on addressing the challenge of crop diseases and pest infestations in agriculture by utilizing UAV technology for improved crop monitoring through unmanned aerial vehicles (UAVs) and enhancing the detection and classification of agricultural pests. Traditional approaches often require arduous manual feature extraction or computationally demanding deep learning (DL) techniques. To address this, we introduce an optimized model tailored specifically for UAV-based applications. Our alterations to the YOLOv5s model, which include advanced attention modules, expanded cross-stage partial network (CSP) modules, and refined multiscale feature extraction mechanisms, enable precise pest detection and classification. Inspired by the efficiency and versatility of UAVs, our study strives to revolutionize pest management in sustainable agriculture while also detecting and preventing crop diseases. We conducted rigorous testing on a medium-scale dataset, identifying five agricultural pests, namely ants, grasshoppers, palm weevils, shield bugs, and wasps. Our comprehensive experimental analysis showcases superior performance compared to various YOLOv5 model versions. The proposed model obtained higher performance, with an average precision of 96.0%, an average recall of 93.0%, and a mean average precision (mAP) of 95.0%. Furthermore, the inherent capabilities of UAVs, combined with the YOLOv5s model tested here, could offer a reliable solution for real-time pest detection, demonstrating significant potential to optimize and improve agricultural production within a drone-centric ecosystem.

P-incorporated CuO/Cu2S heteronanorods as efficient electrocatalysts for the glucose oxidation reaction toward highly sensitive and selective glucose sensing.

Currently, tremendous efforts have been made to explore efficient glucose oxidation electrocatalysts for enzymeless glucose sensors to meet the urgent demands for accurate and fast detection of glucose in the fields of health care and environmental monitoring. In this work, an advanced nanostructured material based on the well-aligned CuO/Cu2S heteronanorods incorporated with P atoms is successfully synthesized on a copper substrate. The as-synthesized material shows high catalytic behavior accompanied by outstanding electrical conductivity. This, combined with the unique morphology of unstacked nanorod arrays, which endow the entire material with a greater number of exposed active sites, make the proposed material act as a highly efficient electrocatalyst for the glucose oxidation reaction. Density functional theory calculations demonstrate that P doping endows P-doped CuO/Cu2S with excellent electrical conductivity and glucose adsorption capability, significantly improving its catalytic performance. As a result, a non-enzymatic glucose sensor fabricated based on our proposed material exhibits a broad linear detection range (0.02-8.2 mM) and a low detection limit (0.95 µM) with a high sensitivity of 2.68 mA mM-1 cm-2 and excellent selectivity.

A novel GPI-anchored dominant-negative TGF-ß receptor II renders T cells unresponsive to TGF-ß signaling.

Transforming growth factor ß (TGF-ß) is a pleiotropic cytokine expressed by a wide range of cell types and is known for hampering the effectiveness of cancer immune cell therapeutic approaches. We have designed a novel construct containing the extracellular domain of the TGF-ß receptor II linked to a glycosylphosphatidylinositol (GPI) anchor (GPI-ecto-TßRII) lacking the transmembrane and cytoplasmic signaling domain of TGF-ß receptor II (TßRII). T cells transduced with lentivirus expressing the GPI-ecto-TßRII construct show 5 to 15 times higher membrane expression compared with a previously established dominant-negative receptor carrying a truncated signaling domain. GPI-ecto-TßRII expression renders T cells unresponsive to TGF-ß-induced signaling seen by a lack of SMAD phosphorylation upon exogeneous TGF-ß treatment. Transduced T cells continue to express high levels of IFNγ and granulocyte-macrophage colony-stimulating factor (GM-CSF), among other cytokines, in the presence of TGF-ß while cytokine expression in untransduced T cells is being markedly suppressed. Furthermore, T cells expressing GPI-ecto-TßRII constructs have been shown to efficiently capture and inactivate TGF-ß from their environment. These results indicate the potential benefits of GPI-ecto-TßRII expressing cytotoxic T cells (CTLs) in future cell therapies.

VPBR: An Automatic and Low-Cost Vision-Based Biophysical Properties Recognition Pipeline for Pumpkin.

Pumpkins are a nutritious and globally enjoyed fruit for their rich and earthy flavor. The biophysical properties of pumpkins play an important role in determining their yield. However, manual in-field techniques for monitoring these properties can be time-consuming and labor-intensive. To address this, this research introduces a novel approach that feeds high-resolution pumpkin images to train a mathematical model to automate the measurement of each pumpkin's biophysical properties. Color correction was performed on the dataset using a color-checker panel to minimize the impact of varying light conditions on the RGB images. A segmentation model was then trained to effectively recognize two fundamental components of each pumpkin: the fruit and vine. Real-life measurements of various biophysical properties, including fruit length, fruit width, stem length, stem width and fruit peel color, were computed and compared with manual measurements. The experimental results on 10 different pumpkin samples revealed that the framework obtained a small average mean absolute percentage error (MAPE) of 2.5% compared to the manual method, highlighting the potential of this approach as a faster and more efficient alternative to conventional techniques for monitoring the biophysical properties of pumpkins.

Development and validation of a prediction model for unsuccessful treatment outcomes in patients with multi-drug resistance tuberculosis.

BACKGROUND: The World Health Organization has reported that the treatment success rate of multi-drug resistance tuberculosis is approximately 57% globally. Although new drugs such as bedaquiline and linezolid is likely improve the treatment outcome, there are other factors associated with unsuccessful treatment outcome. The factors associated with unsuccessful treatment outcomes have been widely examined, but only a few studies have developed prediction models. We aimed to develop and validate a simple clinical prediction model for unsuccessful treatment outcomes in patients with multi-drug resistance pulmonary tuberculosis (MDR-PTB). METHODS: This retrospective cohort study was performed between January 2017 and December 2019 at a special hospital in Xi'an, China. A total of 446 patients with MDR-PTB were included. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to select prognostic factors for unsuccessful treatment outcomes. A nomogram was built based on four prognostic factors. Internal validation and leave-one-out cross-validation was used to assess the model. RESULTS: Of the 446 patients with MDR-PTB, 32.9% (147/446) cases had unsuccessful treatment outcomes, and 67.1% had successful outcomes. After LASSO regression and multivariate logistic analyses, no health education, advanced age, being male, and larger extent lung involvement were identified as prognostic factors. These four prognostic factors were used to build the prediction nomograms. The area under the curve of the model was 0.757 (95%CI 0.711 to 0.804), and the concordance index (C-index) was 0.75. For the bootstrap sampling validation, the corrected C-index was 0.747. In the leave-one-out cross-validation, the C-index was 0.765. The slope of the calibration curve was 0.968, which was approximately 1.0. This indicated that the model was accurate in predicting unsuccessful treatment outcomes. CONCLUSIONS: We built a predictive model and established a nomogram for unsuccessful treatment outcomes of multi-drug resistance pulmonary tuberculosis based on baseline characteristics. This predictive model showed good performance and could be used as a tool by clinicians to predict who among their patients will have an unsuccessful treatment outcome.

Toward explainable heat load patterns prediction for district heating.

Heat networks play a vital role in the energy sector by offering thermal energy to residents in certain countries. Effective management and optimization of heat networks require a deep understanding of users' heat usage patterns. Irregular patterns, such as peak usage periods, can exceed the design capacities of the system. However, previous work has mostly neglected the analysis of heat usage profiles or performed on a small scale. To close the gap, this study proposes a data-driven approach to analyze and predict heat load in a district heating network. The study uses data from over eight heating seasons of a cogeneration DH plant in Cheongju, Korea, to build analysis and forecast models using supervised machine learning (ML) algorithms, including support vector regression (SVR), boosting algorithms, and multilayer perceptron (MLP). The models take weather data, holiday information, and historical hourly heat load as input variables. The performance of these algorithms is compared using different training sample sizes of the dataset. The results show that boosting algorithms, particularly XGBoost, are more suitable ML algorithms with lower prediction errors than SVR and MLP. Finally, different explainable artificial intelligence approaches are applied to provide an in-depth interpretation of the trained model and the importance of input variables.

A multi-centre retrospective study of Nocardia speciation and antimicrobial susceptibility in Queensland, Australia.

The study aims to characterise the species identification and antimicrobial susceptibility testing (AST) results of Nocardial isolates from adult patients across major public hospitals in Queensland, Australia, over a 15-year period. A multi-centre retrospective observational study of Nocardia sp. isolates was conducted from 7 major public hospitals in Queensland, Australia, over a 15-year period. Clinical samples from patients aged ≥ 18 years that isolated Nocardia sp. were included. Demographic and clinical data were collected, along with species identification and AST results. Overall, 484 Nocardia sp. were isolated. Most patients were male (297, 61%) with a mean (IQR) age of 60 (51-75) and a median (IQR) Charlson Comorbidity Index of 4 (2-6). Of these, 239 (49%) patients were immunosuppressed. Organisms were most frequently isolated from sputum (174, 36%), and superficial swabs (102, 21%). Patients presented with pulmonary infections (165, 35%) and superficial skin and soft tissue infections (87, 18%) most commonly. One hundred (21%) isolates were deemed pulmonary colonisation and were not treated. Of the speciated organisms, N. nova complex was the most common (93, 19%), followed by N. farcinica complex (79, 16%). Organisms were reliably susceptible to linezolid (240/245, 98%), amikacin (455/470, 97%), and trimethoprim/sulfamethoxazole (459/476, 96%), but less so to imipenem (243/472, 51%) and ceftriaxone (261/448, 58%). This is the largest Australian description of Nocardia sp. to date. Given antimicrobials are often commenced prior to AST results and sometimes even speciation, characterisation of local species and antibiogram data is important to guide empiric choices and local guidelines.

[3D-printed vertebral body in anterior spinal reconstruction after total spondylectomy for patients with cervical chordoma].

OBJECTIVE: To investigate whether 3D-printed artificial vertebral body can reduce prosthesis subsidence rate for patients with cervical chordomas, through comparing the rates of prosthesis subsidence between 3D printing artificial vertebral body and titanium mesh for anterior spinal reconstruction after total spondylectomy. METHODS: This was a retrospective analysis of patients who underwent surgical treatment for cervical chordoma at our hospital from March 2005 to September 2019. There were nine patients in the group of 3D artificial vertebral body (3D group), and 15 patients in the group of titanium mesh cage (Mesh group). The patients' characteristics and treatment data were extracted from the medical records, including age, gender, CT hounsfield unit of cervical vertebra and surgical information, such as the surgical segments, time and blood loss of surgery, frequency and degree of prosthesis subsidence after surgery. Radiographic observations of prosthesis subsidence during the follow-up, including X-rays, CT, and magnetic resonance imaging were also collected. SPSS 22.0 was used to analysis the data. RESULTS: There was no significant difference between the two groups in gender, age, CT hounsfield unit, surgical segments, time of surgery, blood loss of posterior surgery and total blood loss. Blood loss of anterior surgery was 700 (300, 825) mL in 3D group and 1 500 (750, 2 800) mL in Mesh group (P < 0.05). The prosthesis subsidence during the follow-up, 3 months after surgery, there was significant difference between the two groups in mild prosthesis subsidence (P < 0.05). The vertebral height of the 3D group decreased less than 1 mm in eight cases (no prosthesis subsidence) and more than 1 mm in one case (mild prosthesis subsidence). The vertebral height of the Mesh group decreased less than 1 mm in five cases (no prosthesis subsidence), and more than 1 mm in eight cases (mild prosthesis subsidence). Two patients did not have X-rays in 3 months after surgery. There was a statistically significant difference between the two groups in the prosthesis subsidence rate at the end of 12 months (P < 0.01). The vertebral height of eight cases in the 3D group decreased less than 1 mm (no prosthesis subsidence) and one case more than 3 mm (severe prosthesis subsidence). Four of the 15 cases in the Mesh group decreased less than 1 mm (no prosthesis subsidence), two cases more than 1 mm (mild prosthesis subsidence), and nine cases more than 3 mm (severe prosthesis subsidence). There was a statistically significant difference between the two groups in the prosthesis subsidence rate at the end of 24 months (P < 0.01). The vertebral height of seven cases in the 3D group decreased less than 1 mm (no prosthesis subsidence), one case more than 3 mm (severe prosthesis subsidence), and one case died with tumor. One case in the Mesh group decreased less than 1 mm (no prosthesis subsidence), one case more than 1 mm (mild prosthesis subsidence), 11 case more than 3 mm (severe prosthesis subsidence), one case died with tumor and one lost the follow-up. Moreover, at the end of 12 months and 24 months, there was significant difference between the two groups in severe prosthesis subsidence rate (P < 0.01). CONCLUSION: 3D-printed artificial vertebral body for anterior spinal reconstruction after total spondylectomy for patients with cervical chordoma can provide reliable spinal stability, and reduce the incidence of prosthesis subsidence after 2-year follow-up.

Electrocatalytic CO2 Reduction by [Re(CO)3Cl(3-(pyridin-2-yl)-5-phenyl-1,2,4-triazole)] and [Re(CO)3Cl(3-(2-pyridyl)-1,2,4-triazole)].

The exploration of novel electrocatalysts for CO2 reduction is necessary to overcome global warming and the depletion of fossil fuels. In the current study, the electrocatalytic CO2 reduction of [Re(CO)3Cl(N-N)], where N-N represents 3-(2-pyridyl)-1,2,4-triazole (Hpy), 3-(pyridin-2-yl)-5-phenyl-l,2,4-triazole (Hph), and 2,2'-bipyridine-4,4' dicarboxylic acidic (bpy-COOH) ligands, was investigated. In CO2-saturated electrolytes, cyclic voltammograms showed an enhancement of the current at the second reduction wave for all complexes. In the presence of triethanolamine (TEOA), the currents of Re(Hpy), Re(Hph), and Re(bpy-COOH) enhanced significantly by approximately 4-, 2-, and 5-fold at peak potentials of -1.60, -150, and -1.69 VAg/Ag+, respectively (in comparison to without TEOA). The reduction potential of Re(Hph) was less negative than those of Re(Hpy) and Re(COOH), which was suggested to cause its least efficiency for CO2 reduction. Chronoamperometry measurements showed the stability of the cathodic current at the second reduction wave for at least 300 s, and Re(COOH) was the most stable in the CO2-catalyzed reduction. The appearance and disappearance of the absorption band in the UV/vis spectra indicated the reaction of the catalyst with molecular CO2 and its conversion to new species, which were proposed to be Re-DMF + and Re-TEOA and were supposed to react with CO2 molecules. The CO2 molecules were claimed to be captured and inserted into the oxygen bond of Re-TEOA, resulting in the enhancement of the CO2 reduction efficiency. The results indicate a new way of using these complexes in electrocatalytic CO2 reduction.

Daily and seasonal heat usage patterns analysis in heat networks.

Heat usage patterns, which are greatly affected by the users' behaviors, network performances, and control logic, are a crucial indicator of the effective and efficient management of district heating networks. The variations in the heat load can be daily or seasonal. The daily variations are primarily influenced by the customers' social behaviors, whereas the seasonal variations are mainly caused by the large temperature differences between the seasons over the year. Irregular heat load patterns can significantly raise costs due to pricey peak fuels and increased peak heat load capacities. The in-depth analyses of heat load profiles are regrettably quite rare and small-scale up until now. Therefore, this study offers a comprehensive investigation of a district heating network operation in order to exploit the major features of the heat usage patterns and discover the big factors that affect the heat load patterns. In addition, this study also provides detailed explanations of the features that can be considered the main drivers of the users' heat load demand. Finally, two primary daily heat usage patterns are extracted, which are exploited to efficiently train the prediction model.

[Analysis the influence factors of treatment free remission outcome with chronic myeloid leukemia patients who discontinued tyrosine kinase inhibitors].

Objective: To explore the related factors affecting the outcome of treatment free remission (TFR) in patients with chronic myeloid leukemia (CML). Methods: Clinical data of CML patients with automatic discontinuation of tyrosine kinase inhibitor (TKI) from the CML cooperative organization of Henan province between June 2, 2013 to March 27, 2021 and the follow-up time was ≥ 6 months were retrospectively analyzed. Log-rank test was used for univariate analysis and Cox proportional risk regression model was used for multivariate analysis. Results: A total of 135 patients were enrolled, and 69 patients (51.1%) were femal and 66 patients (48.9%)were male. Median age was[M(Q1,Q3)] 49 years (38, 58)at discontinuation.Before discontinuation, 72 patients (53.3%) were on treatment with second-generation TKI, 63 patients (46.7%) were on treatment with IM, 17patients (12.6%) had a history of TKI reduction/withdrawal;median duration of treatment was months 84 (68, 108) for all patients;median time of TKI treatment to DMR was months 12(8, 26);median duration of DMR was months 65 (54, 84), and 9 patients (6.7%) had unsustained DMR.The median follow-up time was months 16(6-96), 35 patients (25.9%) lost MMR at a median months 3(1-22), overall estimated TFR was 74.1%.The univariate analysis results showed that:second-generation TKI was used, the time of TKI treatment to DMR was ≤12 months, DMR duration time ≥48 months, had sustained DMR, without TKI reduction/withdrawal history were favorable factors affecting of TFR in patients with TKI discontinuation (all P<0.05).The TFR rate of the second-generation TKI therapy group was significantly higher than the IM therapy group (81.9% vs 65.1%, P=0.019).The multivariate analysis results showed that second-generation TKI treatment[RR=0.451, 95%CI (0.227-0.896), P=0.023] and had sustained DMR [RR=0.120, 95%CI (0.053-0.271), P<0.001] were the protective factors of TFR in patients with TKI discontinuation. Conclusions: Treated with second-generation TKI and had sustained DMR are the protective factors of TFR in patients with TKI discontinuation.The CML patients who had sustained DMR more≥48 months before TKI discontinuation showed a better TFR.

Vision-Based Defect Inspection and Condition Assessment for Sewer Pipes: A Comprehensive Survey.

Due to the advantages of economics, safety, and efficiency, vision-based analysis techniques have recently gained conspicuous advancements, enabling them to be extensively applied for autonomous constructions. Although numerous studies regarding the defect inspection and condition assessment in underground sewer pipelines have presently emerged, we still lack a thorough and comprehensive survey of the latest developments. This survey presents a systematical taxonomy of diverse sewer inspection algorithms, which are sorted into three categories that include defect classification, defect detection, and defect segmentation. After reviewing the related sewer defect inspection studies for the past 22 years, the main research trends are organized and discussed in detail according to the proposed technical taxonomy. In addition, different datasets and the evaluation metrics used in the cited literature are described and explained. Furthermore, the performances of the state-of-the-art methods are reported from the aspects of processing accuracy and speed.

[Acceptance evaluation of urine self-sampling, vaginal self-sampling and physician sampling in cervical cancer screening].

Objective: To compare the acceptance of urine self-sampling, vaginal self-sampling and physician sampling in cervical cancer screening. Methods: Questionnaire surveys were conducted in women attending cervical cancer screening in Xiangyuan County and Yangcheng County in Shanxi Province from July to November 2015 and from October to December 2018. Both surveys included the following three parts: feelings and acceptance of women in urine self-sampling, vaginal self-sampling and physician sampling, and the ease evaluation of two self-samplings. Results: There were 3 485 questionnaires were collected finally. The proportions of women felt embarrassed in urine self-sampling, vaginal self-sampling and physician sampling were 2.3% (81/3 472), 7.1% (247/3 472) and 8.6% (299/3 472), and 1.3% (46/3 472), 9.7%(3 37/3 472) and 14.9% (518/3 472) of women felt uncomfortable, and 1.0% (35/3 469), 8.5% (295/3 469) and 15.3% (531/3 469) felt pain, and 98.3% (3 334/3 393), 96.3% (3 267/3 393) and 99.0% (3 360/3 393) thought that the sampling were conducted properly (P<0.05). Based on the feeling during sample collection, 61.2% (1 876/3 064), 39.1% (1 199/3 064) and 66.5% (2 037/3 064) women were willing to use the corresponded sampling methods in cervical cancer screening, respectively (P<0.05). If the accuracy was the same, there were 31.8% (1 109/3 485) women preferred self-sampling and 68.2% (2 376/3 485) preferred physician sampling for cervical cancer screening. Meanwhile, 23.5% (820/3 482) preferred vaginal self-sampling in comparison with 76.5% (2 662/3 482) for urine self-sampling in cervical cancer screening. 86.5% (3 007/3 478) of the women thought urine self-sampling was very easy, comparing 40.9% (1 423/3 478) for vaginal self-sampling. Conclusions: The bad feeling of women during urine self-sampling is less common and less serious than those during physician sampling and vaginal self-sampling, and the acceptance for physician sampling is highest, following by urine self-sampling and vaginal self-sampling. Urine self-sampling is much easier than vaginal self-sampling.

Genome shuffling of Lactobacillus plantarum 163 enhanced antibacterial activity and usefulness in preserving orange juice.

Lactic acid bacteria have been used to inhibit the growth of spoilage bacteria in food and animal feeds. For instance, Lactobacillus plantarum 163 can inhibit efficiently the growth of both gram-positive and gram-negative bacteria. In our study, the antibacterial activity of L. plantarum 163 was further improved significantly by genome shuffling. The optimal conditions for protoplast formation and regeneration were 20 mg ml-1 lysozyme and 5 mg ml-1 mutanolysin for 30 min at 37°C using 0·5 mol l-1 sucrose as stabilizer. The protoplasts were inactivated under ultraviolet light for 120 s or heated at 58°C for 20 min. After two rounds of genome shuffling, the inhibitory activity of strain F2-14 was improved by 2·45- and 1·99-fold, respectively, as compared to their parent strains. The prepared antibacterial peptides supernatant (APS) was added to the orange juice to inhibit spores of Alicyclobacillus acidoterrestris (SAA) at 45 and 28°C. Results showed that the growth of A. acidoterrestris was significantly inhibited, and the decrease in total soluble solids, OD value and pH value was also delayed. After treatment with APS, the thermal sensitivity of spores was increased and its D value was reduced to 13·78, 3·87 and 1·47 min at 80, 90 and 95°C respectively.

Robust Korean License Plate Recognition Based on Deep Neural Networks.

With the rapid rise of private vehicles around the world, License Plate Recognition (LPR) plays a vital role in supporting the government to manage vehicles effectively. However, an introduction of new types of license plate (LP) or slight changes in the LP format can break previous LPR systems, as they fail to recognize the LP. Moreover, the LPR system is extremely sensitive to the conditions of the surrounding environment. Thus, this paper introduces a novel deep learning-based Korean LPR system that can effectively deal with existing challenges. The main contributions of this study include (1) a robust LPR system with the integration of three pre-processing techniques (defogging, low-light enhancement, and super-resolution) that can effectively recognize the LP under various conditions, (2) the establishment of two original Korean LPR approaches for different scenarios, including whole license plate recognition (W-LPR) and single-character license plate recognition (SC-LPR), and (3) the introduction of two Korean LPR datasets (synthetic data and real data) involving a new type of LP introduced by the Korean government. Through several experiments, the proposed LPR framework achieved the highest recognition accuracy of 98.94%.

Association between intraplaque neovascularization assessed by contrast-enhanced ultrasound and the risk of stroke.

AIM: To determine the cut-off value of the area ratio under the curve (ARUC) for predicting symptoms of stroke. MATERIALS AND METHODS: Contrast-enhanced ultrasound was used to analyse intraplaque neovascularization (IPN). The correlations between the ARUC and risk factors of stroke were examined. A receiver operating characteristic curve was used to determine the cut-off value of the ARUC. RESULTS: Using a quantitative analysis method for IPN, the ARUC was significantly higher in the symptomatic group than in the asymptomatic group (p=0.017). The ARUC was positively associated with the homocysteine level (r=0.429, p=0.002) and high-sensitivity C-reactive protein level (r=0.424, p=0.003). Regression analysis showed that the ARUC was a risk factor for symptoms of stroke. The receiver operating characteristic curve showed that the cut-off value for symptoms was 0.24; the sensitivity was 77%, and the specificity was 70%; the positive predictive value was 68%, and the negative predictive value was 78%. CONCLUSION: IPN was a risk factor for the occurrence of the clinical symptoms of stroke. Patients with an ARUC of >0.24 had a higher risk of stroke.

Effect of alprostadil on myocardial fibrosis in rats with diabetes mellitus via TGF-ß1/Smad signaling pathway.

OBJECTIVE: To observe the influence of alprostadil on myocardial fibrosis in rats with diabetes mellitus (DM) through the transforming growth factor beta-1 (TGF-ß1)/Smad signaling pathway. MATERIALS AND METHODS: Wistar rats were employed to induce models of DM (DM group), and alprostadil treatment group (ALPR group) and control group (NC group) were set up. After successful modeling, blood and myocardial tissues were collected from rats. Next, blood glucose level, liver function, and myocardial function were detected. In addition, hematoxylin-eosin (HE) assay was performed to determine pathological changes. The enzyme-linked immunosorbent assay (ELISA) was carried out to measure serum interleukin-6 (IL-6) and cardiac function indexes such as ejection fraction (EF), Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and Western blotting, which were applied to measure the gene and protein expression levels of important molecules in the proliferation and differentiation of myocardial fibroblasts [including checkpoint kinase 1 (Chek1) and alpha-smooth muscle actin (α-SMA)] and the relevant pathway TGF-ß1/Smad2. RESULTS: The blood glucose level was increased in DM group (p<0.01), suggesting that modeling is successful. The tumor necrosis factor-alpha (TNF-α), IL⁃6, and IL-1 levels were higher in DM group than in NC group. DM group had significantly elevated serum content of alkaline phosphatase (ALP), alanine aminotransferase (ALT), and creatine kinase (CK), as well as left ventricular end-diastolic dimension (LVEDd) and left ventricular end-systolic dimension (LVESd), but it clearly decreased fractional shortening (FS) and EF in comparison with NC group. Besides, myocardial cells were orderly arranged in NC group, while myocardial fibrosis was observed in DM group. The results of RT-PCR showed that the levels of Collagen, Chek1, α-SMA, TGF-ß1, and Smad2 in myocardial fibroblasts were notably lowered in ALPR group, but evidently increased in DM group (p<0.05). According to Western blotting, there were evident decreases in the levels of TGF-ß1 and Smad2 in myocardial fibroblasts in ALPR group (p<0.05). The above results suggest that alprostadil represses the expression of the TGF-ß1/Smad2 signaling pathway and its relevant molecules, thus further suppressing the fibrosis of myocardial cells. CONCLUSIONS: Alprostadil treats myocardial fibrosis in DM rats by inhibiting the TGF-ß1/Smad2 signaling pathway.

[The plasma level of amyloid-ß is associated with cognitive decline: a two years follow-up study in Xi'an rural areas].

Objective: To explore the relationship between plasma amyloid-ß (Aß) and cognitive decline during 2 year follow-up in a population-based cohort in Xi'an rural areas. Methods: The study was conducted in Qubao village in Xi'an suburbs cognitively normal residents over 40 years old were recruited from October 2014 to March 2015 and given a face-to-face standardized interview. Mini-mental state examination (MMSE) was employed to evaluate the global cognitive function, and quantification of plasma Aß was measured by sandwich enzyme-linked immunosorbent assay (ELISA) at baseline. Two years later, MMSE was tested at the end of study. Then logistic regression was performed to analyze the relationship between baseline Aß and cognitive change during 2 year follow-up. Results: A total of 1 020 participants completed the study, among whom 223 subjects (21.9%) presented MMSE scores decline (defined as MMSE scores decreased ≥2 points). Compared with those without decline, participants in the MMSE decline group were older (P<0.001) and had lower education level (P<0.001), while gender, hypertension, hyperlipemia, diabetes mellitus and APOE genotype were not significantly different between two groups. One-way analysis of variance (ANOVA) showed that the MMSE score decline was slighter in the lower tertile of baseline Aß(1)-40 compared with middle tertile (P=0.012), while MMSE decline were similar between different Aß(1)-42 level groups and Aß(1-42)/Aß(1-40) ratio groups (P=0.758, P=0.671, respectively). Multivariable logistic regression analysis showed that MMSE scores in the lower baseline plasma Aß(1-40) level declined more slowly (OR=0.565, 95%CI 0.379-0.845, P=0.005). However, the MMSE decline were also similar among different baseline plasma Aß(1-42) levels groups and Aß(1-42)/Aß(1-40) ratio groups. Conclusion: Population with lower level of baseline plasma Aß(1-40) manifests lower cognitive decline during 2 years, however further investigation on dynamics of plasma Aß and long term follow up are needed.

Combination of mRNA of Repair-related Genes in Rat Skeletal Muscles for Wound Age Estimation.

ABSTRACT: Objective To investigate the estimation of early and mid-term wound age by a combination of four mRNAs, the DNA polymerase delta-interacting protein 3 （POLDIP3） mRNA, regulator of chromosome condensation 1 like （RCC1L） mRNA, proline-rich 5 （PRR5） mRNA, and ribonucleic acid export 1 （RAE1） mRNA in rats skeletal muscles. Methods The model of rat skeletal muscle contusion was established, and then contusion area muscle tissue was extracted 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44 and 48 h after injury. Histomorphological changes during the repair process after rat skeletal muscle contusion were observed. The relative expressions of Poldip3, Rcc1l, Prr5 and Rae1 mRNAs were detected by reverse transcription real-time quantitative polymerase chain reaction （RT-qPCR）. Different stages of wound age were classified by using the expression patterns of four genes at various time points after injury. The accuracy of the results was verified by Fisher discriminant analysis. Results Histomorphological results showed that the repair process after skeletal muscle contusion occurred with the prolonging of time. Through combination of the expression trends of the four kinds of mRNAs, the 48 h after injury could be divided into three periods, 4-12 h, 16-28 h and 32-48 h. The Fisher discrimination method showed that the classification accuracy rates of the three periods were 83.3%, 75.0% and 73.3%, respectively. Conclusion The classification discrimination based on the relative expression of every gene has a higher accuracy, and the accuracy of wound age estimation with combination of mRNA relative expressions is higher than that with a single indicator. By combining with Fisher discrimination method, this method can be used for early and mid-term wound age estimation.