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Biochar provides a suitable microenvironment for the growth of microorganisms. It may directly or indirectly affect changes in the population of microorganisms, thus affecting heavy metal bioavailability. This study aims to explore the effects of microbiological inoculation with and without biochar on microorganisms and on the bioavailability of heavy metals during pig manure composting. Three composting experiments were conducted under various conditions including no treatment (CK), only microbiological inoculation (TA), and integration with biochar (TB). Compared with raw materials before compost, TA reduced the bioavailability of Cu by 25.1%, Zn by 25.64%, and both Pb and Cr by 1.75%. TB reduced the bioavailability of Cu by 35.38%, Zn by 19.34%, Pb by 0.81%, and Cr by 3.9%. Furthermore, correlation analysis demonstrated that Debaryomyces were the primary fungi, possibly controlling the passivation of Cr. Bacillus , Fusarium , Pseudogracilibacillus , Sinibacillus , and Botryotrichum were the primary bacteria and fungi potentially governing the passivation of Zn, Lastly, Debaryomyces and Penicillium were the primary bacteria and fungi potentially controlling the passivation of Pb and Cu, respectively. Overall, we demonstrated that pig manure added to the microbial inoculum and biochar effectively reduced the bioavailability of heavy metals, thereby offering an applicable technology for reducing heavy metal contamination during pig manure composting. • Added in the microbial inoculum and biochar can reduce the bioavailability of heavy mentals. • Critical bacteria and fungi of correlated Cu, Zn, Pb and Cr bioavailability was revealed. • Passivation effect of biochar and microbial inoculum on heavy metals through regulating bacterial and fungi communities. [ABSTRACT FROM AUTHOR]

Abstract: The role of Nrf2 in disease prevention and treatment is well documented; however the specific role of Nrf2 in skeletal muscle is not well described. The current study investigated whether Nrf2 plays a protective role in an STZ-induced model of skeletal muscle atrophy. Modulation of Nrf2 through siRNA resulted in a more robust differentiation of C2C12s, whereas increasing Nrf2 with sulforaphane treatment inhibited differentiation. Diabetic muscle atrophy was not dramatically influenced by Nrf2 genotype, since no differences were observed in total atrophy (all fiber types combined) between WT+STZ and KO+STZ animals. Nrf2-KO animals however illustrated alterations in muscle size of Fast, Type II myosin expressing fibers. KO+STZ animals show significant alterations in myosin isoform expression in the GAST. Similarly, KO controls mimic both WT+STZ and KO+STZ muscle alterations in mitochondrial subunit expression. PGC-1α, a well-established player in mitochondrial biogenesis and myosin isoform expression, was decreased in KO control, WT+STZ and KO+STZ SOL muscle. Similarly, PGC-1α protein levels are correlated with Nrf2 levels in C2C12s after modulation by Nrf2 siRNA or sulforaphane treatment. We provide experimental evidence indicating Nrf2 plays a role in myocyte differentiation and governs molecular alterations in contractile and metabolic properties in an STZ-induced model of muscle atrophy. [Copyright &y& Elsevier]

[Display omitted] • A series of novel berberine analogs were synthesized, and evaluated for their p300 inhibitory activity. • Structure-activity relationship studies yielded a more potent compound 5d. • Compound 5d specifically decreases H3K18Ac and interferes with the function of histone acetyltransferase. • Compound 5d exhibited good antitumor effects in MDA-MB-231 cells in vitro and in vivo. The protein p300 is a positive regulator of cancer progression and is related to many human pathological conditions. To find effective p300/CBP HAT inhibitors, we screened an internal compound library and identified berberine as a lead compound. Next, we designed, synthesized, and screened a series of novel berberine analogs, and discovered that analog 5d was a potent and highly selective p300/CBP HAT inhibitor with IC 50 values of 0.070 μM and 1.755 μM for p300 and CBP, respectively. Western blotting further proved that 5d specifically decreased H3K18Ac and interfere with the function of histone acetyltransferase. Although 5d had only a moderate inhibitory effect on the MDA-MB-231 cell line, 5d suppressed the growth of 4T1 tumor growth in mice with a tumor weight inhibition ratio (TWI) of 39.7%. Further, liposomes-encapsulated 5d increased its inhibition of tumor growth to 57.8 % TWI. In addition, 5d has no obvious toxicity to the main organ of mice and the pharmacokinetic study confirmed that 5d has good absorption properties in vivo. [ABSTRACT FROM AUTHOR]

Sensor pattern noise (SPN) has been widely used in source camera identification. However, the SPN extracted from natural image may be contaminated by its content and eventually introduce side effect to the identification accuracy. In this paper, an effective source camera identification scheme based on guided image estimation and block weighted average is proposed. Before the SPN extraction, an adaptive SPN estimator based on image content is implemented to reduce the influence of image scene and improve the quality of the SPN. Furthermore, a novel camera reference SPN construction method is put forward by using some ordinary images, instead of the blue sky images in the previous schemes, and a block weighted average approach is used to suppress the influence of the image scenes in the reference SPN. Experimental results and analysis indicate that the proposed method can effectively identify the source of the natural image, especially in actual forensics environment with a small number of images. [ABSTRACT FROM AUTHOR]

Aiming at the performance degradation of the existing presentation attack detection methods due to the illumination variation, a two-stream vision transformers framework (TSViT) based on transfer learning in two complementary spaces is proposed in this paper. The face images of RGB color space and multi-scale retinex with color restoration (MSRCR) space are fed to TSViT to learn the distinguishing features of presentation attack detection. To effectively fuse features from two sources (RGB color space images and MSRCR images), a feature fusion method based on self-attention is built, which can effectively capture the complementarity of two features. Experiments and analysis on Oulu-NPU , CASIA-MFSD , and Replay-Attack databases show that it outperforms most existing methods in intra-database testing and achieves good generalization performance in cross-database testing. [ABSTRACT FROM AUTHOR]

• A face PAD model is built based on the analysis of photo/replay attack. • CCoLBP is proposed to depict the discrepancies between real faces and artefacts. • An EL based classifier is proposed to improve the generalization across datasets. • Results and analysis indicate its good performance in cross-dataset testing. To counter face presentation attacks in face recognition (FR), color texture has been successfully used for face presentation attack detection (PAD) in recent years. However, the existing research does not fully consider the correlation between different color channels as well as the optimization of classification for face PAD. To resolve these limitations, a face PAD scheme based on chromatic co-occurrence of local binary pattern (CCoLBP) and ensemble learning (EL) is proposed in this paper. A color distortion-based face PAD model is first built, and then the chromatic discrepancies between bona fide faces and artefacts are analyzed. After that, CCoLBP is extracted as the feature to characterize these discrepancies. Meanwhile, an EL based classifier is put forward to reduce the effect of class imbalance and to improve the generalization ability. Experimental results and analysis indicate that the proposed scheme can achieve an overall good performance. Moreover, it can achieve significant improvement in the cross-database test, and its computational complexity can meet the requirement of real time applications. [ABSTRACT FROM AUTHOR]

Aiming to counterstrike face spoofing attacks such as photo attacks and video attacks, a face spoofing detection scheme based on color texture Markov feature (CTMF) and support vector machine recursive feature elimination (SVM-RFE) is proposed. In this paper, the adjacent facial pixels discrepancy between the real and the fake face is analyzed, and texture information between the color channels is fully considered. Firstly, the directional difference filter is used to capture the facial texture difference between the real and the fake face, which can be regarded as low-level features of CTMF. Then, the facial texture difference is modeled by the Markov process to form a high-level representation of the low-level features. Meanwhile, the mutual information of facial texture between the color channels, which is ignored in the previous literature, is investigated. In addition, SVM-RFE is utilized to reduce the feature dimension and makes it suitable for real-time detection. Experiments on four public benchmark databases indicate that the proposed scheme can effectively resist photo and video spoofing attacks in face recognition. [ABSTRACT FROM AUTHOR]

• Osteopontin is increased in NAFLD patients with T2DM. • The relative risks for NAFLD in T2DM patients increases with increasing osteopontin quartiles. • Osteopontin is an optimal predictor for use in the diagnosis of T2DM with NAFLD. • Osteopontin may contribute to the aggravation of the metabolic state. Nonalcoholic fatty liver disease (NAFLD) commonly occurs in patients with type 2 diabetes mellitus (T2DM). Osteopontin (OPN) is a multifunctional protein with pleiotropic physiological functions. This study aimed to investigate the interrelation between circulating OPN and NAFLD in T2DM patients. Overall, 249 subjects were classified into 4 groups: 53 patients with NAFLD and T2DM; 57 with newly diagnosed T2DM; 59 with NAFLD; and 80 healthy age- and sex-matched controls. Serum OPN was measured by ELISA. The OPN distribution in the pooled data was divided into quartiles; significant trends across increasing quartiles were estimated by the Cochran-Armitage trend test. Compared with the controls, circulating OPN concentrations were significantly elevated in NAFLD patients and T2DM patients with or without NAFLD. Serum OPN levels were higher in the overweight/obese group than that in the lean group. Circulating OPN levels were positively correlated with CRP, age, BMI, SBP, DBP, HbA1c, UA, TGs, WBCs, neutrophils, FBG, and HOMA-IR and negatively correlated with ADP, albumin and HDL. Age, albumin, HbA1c, HDL and hsCRP were independently related to circulating OPN. The relative risks for NAFLD, T2DM and T2DM with NAFLD increased significantly along with increasing OPN quartiles based on the Cochran-Armitage trend test. OPN is an optimal predictor in the diagnosis of T2DM with NAFLD and T2DM and may contribute to the aggravation of the metabolic state. [ABSTRACT FROM AUTHOR]