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Development of high-performance cutting tool materials is one of the critical parameters enhancing the surface finishing of high-speed machined products. Ti(C,N)-based cermets reinforced with and without different contents of silicon nitride were designed and evaluated to satisfy the requirements. In fact, the effect of silicon nitride addition to Ti(C,N)-based cermet remains unclear. The purpose of this study is to investigate the influence of Si3N4 additive on microstructure, mechanical properties, and thermal stability of Ti(C,N)-based cermet cutting tools. In the present work, α-Si3N4 “grade SN-E10” was utilized with various fractions up to 6 wt.% in the designed cermets. A two-step reactive sintering process under vacuum was carried out for the green compact of Ti(C,N)-based cermet samples. The samples with 4 wt.% Si3N4 have an apparent solid density of about 6.75 g/cm3 (relative density of about 98 %); however, the cermet samples with 2 wt.% Si3N4 exhibit a superior fracture toughness of 10.82 MPa.m1/2 and a traverse rupture strength of 1425.8 MPa. With an increase in the contents of Si3N4, the Vickers hardness and fracture toughness of Ti(C,N)-based cermets have an inverse behavior trend. The influence of Si3N4 addition on thermal stability is clarified to better understand the relationship between thermal stability and mechanical properties of Ti(C,N)-based cermets.

The detection of volatile amines is necessary due to the serious toxicity hazards they pose to human skin, respiratory systems, and nervous systems. However, traditional amines detection methods require bulky equipment, high costs, and complex measurements. Herein, we report a new simple, rapid, convenient, and visual method for the detection of volatile amines based on the gas–solid reactions of tetrachloro-p-benzoquinone (TCBQ) and volatile amines. The gas–solid reactions of TCBQ with a variety of volatile amines showed a visually distinct color in a time-dependent manner. Moreover, TCBQ can be easily fabricated into simple and flexible rapid test strips for detecting and distinguishing n-propylamine from other volatile amines, including ethylamine, n-butyamine, n-pentamine, n-butyamine and dimethylamine, in less than 3 s without any equipment assistance.

Probiotic fermented milk is an important carrier of probiotics. It enhances the nutritional and health properties of fermented milk by improving the balance of host intestinal microflora and promoting the metabolism of beneficial ingredients. This review expounds the auxiliary effects of probiotics fermented milk in improving intestinal function, regulating body immunity, assisting in treating metabolic diseases and improving mental system diseases, etc., in order to provide theoretical support for expanding the application of probiotics fermented milk.

Chlorpyrifos is an organophosphate pesticide that is wildly used among farmers for crop protection. However, there are concerns regarding its contamination in the environment and food chain. In the present study, an in-house indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) specific for detecting chlorpyrifos is developed and validated against gas chromatography-flame photometric detection (GC-FPD) as the conventional method. The developed ic-ELISA was used for detecting chlorpyrifos residue in vegetable samples. The developed ic-ELISA showed good sensitivity to chlorpyrifos at an IC50 of 0.80 µg/kg, with low cross-reactivity to other organophosphate pesticides. The 160 samples were collected from local markets located in the Chiang Rai, Chiang Mai, and Nan provinces in northern Thailand. The positive rate of chlorpyrifos residues in the vegetable samples was 33.8%, with the highest levels found in cucumbers, coriander, and morning glory, at 275, 145, and 35.3 µg/kg, respectively. The highest median levels of chlorpyrifos found in the detected samples were Chinese cabbage (332 μg/kg), cucumber (146.3 μg/kg) and Chinese Kale (26.95 μg/kg). The developed ic-ELISA is suitable for the rapid quantitation of chlorpyrifos residues.

1-naphthol (1-NAP) is the main metabolite of pesticide carbaryl and naphthalene, and is also a genotoxic and carcinogenic intermediate in the synthesis of organic compound, dyes, pigment and pharmaceutical industry. In this work, two novel haptens were designed and synthesized for developing a competitive indirect enzyme-linked immunosorbent assay (ciELISA) method for 1-NAP in urine samples. The assay showed a limit of detection of 2.21 ng/mL and working range from 4.02 ng/mL to 31.25 ng/mL for 1-NAP in optimized working buffer. The matrix effect of samples was eliminated via 15-fold dilution of optimized working buffer. Good average recoveries (102.4%-123.4%) with a coefficient of variation from 11.7% to 14.7% was obtained for spiked urine samples. Subsequent instrument verification test showed good correlation between the results of ciELISA and high-performance liquid chromatography. The developed ciELISA is a high-throughput tool to monitor 1-NAP in urine, which can provide technical support for the establishment of biological exposure level for the exposure to carbaryl, naphthalene and other related pollutants.

Accurately forecasting crude oil prices is challenging due to market noise and non-stationarity. To address these challenges, we propose a forecasting framework that incorporates variational mode decomposition (VMD), time-series imaging, and bidirectional gated recurrent unit network (BGRU). Our approach eliminates additional assumptions and auxiliary data. First, the raw data are preprocessed through normalization, followed by decomposing multiple stationary sub-series through VMD. Subsequently, three time-series imaging techniques, recurrence plot (RP), Gramian angular field (GAF), and Markov transition field (MTF), are employed respectively to transform the sub-series into two-dimensional images. A convolutional neural network (CNN) is then used to extract features from these images. Finally, the extracted features are fed into BGRU for prediction and the Adam optimizer is used to train models. Experimental evaluations are conducted using a dataset from the U.S. Energy Information Administration (EIA), consisting of the weekly spot prices free on board (FOB) of the West Texas Intermediate (WTI) crude oil, spanning from June 19, 1998, to May 12, 2023. Results demonstrate that all three models constructed following our approach outperform benchmark methods. Specifically, our VMD-RP-BGRU model achieves the best forecasting performance with MAE=2.429, MSE=10.94, MAPE=2.94%, and R-squared=0.9418. The model exhibits reductions of 21.64%, 23.15%, and 36.46% in MAE, MSE, and MAPE, respectively, compared to the seasonal autoregressive integrated moving average (SARIMA) model, and reductions of 21.18%, 22.70%, and 36.08% compared to the Holt-Winters exponential smoothing (HWES) model. Our study contributes to the advancement of crude oil price forecasting techniques and supports informed decision-making in the energy sector.

Abstract The occurrence of osteoarthritis (OA) is highly correlated with the reduction of joint lubrication performance, in which persistent excessive inflammation and irreversible destruction of cartilage dominate the mechanism. The inadequate response to monotherapy methods, suboptimal efficacy caused by undesirable bioavailability, short retention, and lack of stimulus-responsiveness, are few unresolved issues. Herein, we report a pH-responsive metal-organic framework (MOF), namely, MIL-101-NH2, for the co-delivery of anti-inflammatory drug curcumin (CCM) and small interfering RNA (siRNA) for hypoxia inducible factor (HIF-2α). CCM and siRNA were loaded via encapsulation and surface coordination ability of MIL-101-NH2. Our vitro tests showed that MIL-101-NH2 protected siRNA from nuclease degradation by lysosomal escape. The pH-responsive MIL-101-NH2 gradually collapsed in an acidic OA microenvironment to release the CCM payloads to down-regulate the level of pro-inflammatory cytokines, and to release the siRNA payloads to cleave the target HIF-2α mRNA for gene-silencing therapy, ultimately exhibiting the synergetic therapeutic efficacy by silencing HIF-2α genes accompanied by inhibiting the inflammation response and cartilage degeneration of OA. The hybrid material reported herein exhibited promising potential performance for OA therapy as supported by both in vitro and in vivo studies and may offer an efficacious therapeutic strategy for OA utilizing MOFs as host materials.

We focus on the two-stage stochastic programming (SP) with information update, and study how to evaluate and acquire information, especially when the information is imperfect. The scarce-data setting in which the probabilistic interdependent relationship within the updating process is unavailable, and thus, the classic Bayes' theorem is inapplicable. To address this issue, a robust approach is proposed to identify the worst probabilistic relationship of information update within the two-stage SP, and the robust Expected Value of Imperfect Information (EVII) is evaluated by developing a scenario-based max-min-min model with the bi-level structure. Three ways are developed to find the optimal solution for different settings. Furthermore, we study a costly information acquisition game between a two-stage SP decision-maker and an exogenous information provider. A linear compensation contract is designed to realize the global optimum. Finally, the proposed approach is applied to address a two-stage production and shipment problem to validate the effectiveness of our work. This paper enriches the interactions between uncertain optimization and information management and enables decision-makers to evaluate and manage imperfect information in a scarce-data setting.

Radiation therapy is considered the most effective non-surgical treatment for brain tumors. However, there are no available treatments for radiation-induced brain injury. Bisdemethoxycurcumin (BDMC) is a demethoxy derivative of curcumin that has anti-proliferative, anti-inflammatory, and anti-oxidant properties. To determine whether BDMC has the potential to treat radiation-induced brain injury, in this study, we established a rat model of radiation-induced brain injury by administering a single 30-Gy vertical dose of irradiation to the whole brain, followed by intraperitoneal injection of 500 μL of a 100 mg/kg BDMC solution every day for 5 successive weeks. Our results showed that BDMC increased the body weight of rats with radiation-induced brain injury, improved learning and memory, attenuated brain edema, inhibited astrocyte activation, and reduced oxidative stress. These findings suggest that BDMC protects against radiation-induced brain injury.

Objective To explore the effect of Toll-like receptor 3 (TLR3) activation on the expression of neuronal disrupted-in-schizophrenia 1 (DISC1). Methods C57BL/6J mouse hippocampal neurons were incubated with polyI:C(1 μg/mL) or/and mIFNα(100 IU/mL) for 24 hrs. DISC1 mRNA and protein were detected by quantitive RT-PCR, immuno-cytochemistry staining and Western blot. The expression of STAT1, phospho-STAT1, p38 MAPK, phospho-p38 MAPK, GSK-3β, and phospho-GSK-3β was also detected by Western blot. Results Comparing with control group, the mRNA and protein expression of DISC1 in polyI:C group and IFNα group didn't show any changes, but significantly decreased with the co-stimulation by polyI:C and IFNα (P＜0.05). In addition, the phosphorylation of STAT1 was significantly increased in both IFNα group and co-stimulation group(P＜0.05) and the phosphorylation of p38 MAPK was elevated in polyI:C group and co-stimulation group (P＜0.05).The expression of GSK-3β and phospho-GSK-3β had no changes. Conclusions The combined stimulations of IFNα and TLR3 activation may inhibit the expression of DISC1 potentially through JAK/STAT1 and p38 MAPK signaling pathways.

During 6–10 January 2021, a recorded strong cold surge took place in China, with over 800 observational stations reaching their historical extremes. Unlike previous studies that focused on the response of either the power load or generation separately, this study quantitatively revealed the impacts on the balance between the demand and supply sides of the grid. On the demand side, the sensitivity of power load was found to increase substantially higher in southern China (0.533 GW °C−1) than in the northern region (0.139 GW °C−1) due to the limited municipal heating system. On the supply side, the hourly wind power generation dropped from the highest of 110 GW on 6 January to the lowest of 54 GW on 9 January due to the reduction in wind speed. In addition, a reduction in solar power generation was observed during 8–10 January. Thus, the balance of the power system was influenced by this cold event. As an effective adaptation measure, results further showed that early warning by three weeks ahead can be obtained by an operational climate model. The sensitivity of China's power system to such cold surge events may increase remarkably due to the expected increase in the proportion of wind and solar power generation in future new-type power systems. Thus, close cooperation between climate scientists and power engineers is needed to build the resilience of the power system to the cold extremes.

The extensive use of tetracycline antibiotics has led to the widespread presence of tetracycline-resistance genes in Gram-negative bacteria and this poses serious threats to human and animal health. In our previous study, we reported a method for rapid detection of Tet(X)-producers using MALDI-TOF MS. However, there have been multiple machineries involved in tetracycline resistance including efflux pump, and ribosomal protection protein. Our previous demonstrated the limitation in probing the non-Tet(X)-producing tetracycline-resistant strains. In this regard, we further developed a MALDI-TOF MS method to detect and differentiate Tet(X)-producers and non-Tet(X)-producing tetracycline-resistant strains. Test strains were incubated with tigecycline and oxytetracycline in separate tubes for 3 h and then analyzed spectral peaks of tigecycline, oxytetracycline, and their metabolite. Strains were distinguished using MS ratio for [metabolite/(metabolite+ tigecycline or oxytetracycline)]. Four control strains and 319 test strains were analyzed and the sensitivity was 98.90% and specificity was 98.34%. This was consistent with the results obtained from LC-MS/MS analysis. Interestingly, we also found that the reactive oxygen species (ROS) produced by tetracycline-susceptible strains were able to promote the degradation of oxytetracycline. Overall, the MALDITet(X)-plus test represents a rapid and reliable method to detect Tet(X)-producers, non-Tet(X)-producing tetracycline-resistant strains, and tetracycline-susceptible strains.

Background Acute kidney injury (AKI) is not a rare complication during anti-tuberculosis treatment in some patients with pulmonary tuberculosis (PTB). We aimed to develop a risk prediction model for early recognition of patients with PTB at high risk for AKI during anti-TB treatment.Methods This retrospective cohort study assessed the clinical baseline, and laboratory test data of 315 inpatients with active PTB who were screened for predictive factors from January 2019 to June 2020. The elements were analyzed by logistic regression analysis. A nomogram was established by the results of the logistic regression analysis. The prediction model discrimination and calibration were evaluated by the concordance index (C-index), ROC curve, and Hosmer-Lemeshow analysis.Results A total of 315 patients with PTB were enrolled (67 patients with AKI and 248 patients without AKI). Seven factors, including microalbuminuria, hematuria, cystatin-C (CYS-C), albumin (ALB), creatinine-based estimated glomerular filtration rates (eGFRs), body mass index (BMI), and CA-125 were acquired to develop the predictive model. According to the logistic regression, microalbuminuria (OR = 3.038, 95%CI 1.168–7.904), hematuria (OR = 3.656, 95%CI 1.325–10.083), CYS-C (OR = 4.416, 95%CI 2.296–8.491), and CA-125 (OR = 3.93, 95%CI 1.436–10.756) were risk parameter, while ALB (OR = 0.741, 95%CI 0.650–0.844) was protective parameter. The nomogram demonstrated good prediction in estimating AKI (C-index= 0.967, AUC = 0.967, 95%CI (0.941–0.984), sensitivity = 91.04%, specificity = 93.95%, Hosmer-Lemeshow analysis SD = 0.00054, and quantile of absolute error = 0.049).Conclusions Microalbuminuria, hematuria, ALB reduction, elevated CYS-C, and CA-125 are predictive factors for the development of AKI in patients with PTB during anti-TB treatments. The predictive nomogram based on five predictive factors is achieved good risk prediction for AKI during anti-TB treatments.