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Efficient food safety risk assessment significantly affects food safety supervision. However, food detection data of different types and batches show different feature distributions, resulting in unstable detection results of most risk assessment models, lack of interpretability of risk classification, and insufficient risk traceability. This study aims to explore an efficient food safety risk assessment model that takes into account robustness, interpretability and traceability. Therefore, the Explainable unsupervised risk Warning Framework based on the Empirical cumulative Distribution function (EWFED) was proposed. Firstly, the detection data's underlying distribution is estimated as non-parametric by calculating each testing indicator's empirical cumulative distribution. Next, the tail probabilities of each testing indicator are estimated based on these distributions and summarized to obtain the sample risk value. Finally, the "3σ Rule" is used to achieve explainable risk classification of qualified samples, and the reasons for unqualified samples are tracked according to the risk score of each testing indicator. The experiments of the EWFED model on two types of dairy product detection data in actual application scenarios have verified its effectiveness, achieving interpretable risk division and risk tracing of unqualified samples. Therefore, this study provides a more robust and systematic food safety risk assessment method to promote precise management and control of food safety risks effectively., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Maternal secretion of recombinant proteins into chicken eggs may provide a viable approach for pharmaceutical production but remains limited by poor secretion efficiency through the membrane of oviduct cells, despite high expression levels. Here, we used site-specific integration of an EGFP fused to the OVAL gene by a rigid linker, (EAAAK) 3 , at the endogenous ovalbumin locus in chicken primordial germ cells to generate OVAL-E3-EGFP transgenic chickens, with transgenic chickens expressing CMV immediate enhancer/β-actin-driven EGFP (CAG-EGFP) as a non-secreted control. In OVAL-E3-EGFP chickens, EGFP protein produced in maternal oviducts accumulates to high levels in eggs, but not in eggs of CAG-EGFP chickens. These results indicated that the secretion of foreign proteins can be substantially increased through fusion to the highly secreted endogenous ovalbumin. This study describes a basis for high yield recombinant protein expression in chicken eggs, enabling rapid and scalable production of numerous pharmaceutical proteins or metabolites., (© 2024. The Author(s).)

Diabetic kidney disease (DKD) is one of the most common kidney diseases worldwide. It is estimated that approximately 537 million adults worldwide have diabetes, and up to 30%-40% of diabetic patients are at risk of developing nephropathy. The pathogenesis of DKD is complex, and its onset is insidious. Currently, the clinical diagnosis of DKD primarily relies on the increase of urinary albumin and the decrease in glomerular filtration rate in diabetic patients. However, the excretion of urinary albumin is influenced by various factors, such as physical activity, infections, fever, and high blood glucose, making it challenging to achieve an objective and accurate diagnosis. Therefore, there is an urgent need to develop an efficient, fast, and low-cost auxiliary diagnostic technology for DKD. In this study, an improved Dual Branch Attention Network (DBAN) was developed to quickly identify DKD. Serum Raman spectroscopy samples were collected from 32 DKD patients and 32 healthy volunteers. The collected data were preprocessed using the adaptive iteratively reweighted penalized least squares (airPLS) algorithm, and the DBAN was used to classify the serum Raman spectroscopy data of DKD. The model consists of a dual branch structure that extracts features using Convolutional Neural Network (CNN) and bottleneck layer modules. The attention module allows the model to learn features specifically, and lateral connections are added between the dual branches to achieve multi-level and multi-scale fusion of shallow and deep features, as well as local and global features, improving the classification accuracy of the experiment. The results of the study showed that compared to traditional deep learning algorithms such as Artificial Neural Network (ANN), CNN, GoogleNet, ResNet, and AlexNet, our proposed DBAN classification model achieved 95.4% accuracy, 98.0% precision, 96.5% sensitivity, and 97.2% specificity, demonstrating the best classification performance. This is the best method for identifying DKD, and has important reference value for the diagnosis of DKD patients, as well as improving the accuracy of medical auxiliary diagnosis., Competing Interests: Declaration of competing interest The authors declare that they have no conflicting financial interests., (Copyright © 2023 Elsevier B.V. All rights reserved.)

THEMIS plays an indispensable role in T cells, but its mechanism of action has remained highly controversial. Using the systematic proximity labeling methodology PEPSI, we identify THEMIS as an uncharacterized substrate for the phosphatase SHP1. Saturated mutagenesis assays and mass spectrometry analysis reveal that phosphorylation of THEMIS at the evolutionally conserved Tyr34 residue is oppositely regulated by SHP1 and the kinase LCK. Similar to THEMIS - /- mice, THEMIS Y34F/Y34F knock-in mice show a significant decrease in CD4 thymocytes and mature CD4 T cells, but display normal thymic development and peripheral homeostasis of CD8 T cells. Mechanistically, the Tyr34 motif in THEMIS, when phosphorylated upon T cell antigen receptor activation, appears to act as an allosteric regulator, binding and stabilizing SHP1 in its active conformation, thus ensuring appropriate negative regulation of T cell antigen receptor signaling. However, cytokine signaling in CD8 T cells fails to elicit THEMIS Tyr34 phosphorylation, indicating both Tyr34 phosphorylation-dependent and phosphorylation-independent roles of THEMIS in controlling T cell maturation and expansion., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Ag 2 O-Ag-PSi (porous silicon) surface-enhanced Raman scattering (SERS) chip was successfully synthesized by electrochemical corrosion, in situ reduction and heat treatment technology. The influence of different heat treatment temperature on SERS performance of the chip is studied. The results show that the chip treated at 300 °C has the best SERS performance. The chip was composed of Ag 2 O-Ag nano core shell with a diameter of 40-60 nm and porous silicon substrate. Then, the optimized chip was used to perform SERS test on serum samples from 30 healthy volunteers and 30 early breast cancer patients, and the baseline was corrected by LabSpec6 software. Finally, the data were analyzed by principal component analysis combined with t-distributed Stochastic Neighbor Embedding (PCA-t-SNE). The results showed that the accuracy of the improved substrate combined with multivariate statistical method was 98%. The shelf life of the chips exceeded six months due to the presence of the Ag 2 O shell. This study provides a basis for developing a low-cost rapid and sensitive early screening technology for breast cancer., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

The powerful CRISPR genome editing system is hindered by its off-target effects, and existing computational tools achieved limited performance in genome-wide off-target prediction due to the lack of deep understanding of the CRISPR molecular mechanism. In this study, we propose to incorporate molecular dynamics (MD) simulations in the computational analysis of CRISPR system, and present CRISOT, an integrated tool suite containing four related modules, i.e., CRISOT-FP, CRISOT-Score, CRISOT-Spec, CRISORT-Opti for RNA-DNA molecular interaction fingerprint generation, genome-wide CRISPR off-target prediction, sgRNA specificity evaluation and sgRNA optimization of Cas9 system respectively. Our comprehensive computational and experimental tests reveal that CRISOT outperforms existing tools with extensive in silico validations and proof-of-concept experimental validations. In addition, CRISOT shows potential in accurately predicting off-target effects of the base editors and prime editors, indicating that the derived RNA-DNA molecular interaction fingerprint captures the underlying mechanisms of RNA-DNA interaction among distinct CRISPR systems. Collectively, CRISOT provides an efficient and generalizable framework for genome-wide CRISPR off-target prediction, evaluation and sgRNA optimization for improved targeting specificity in CRISPR genome editing., (© 2023. The Author(s).)

Mutations in Rhodopsin (RHO) gene commonly cause autosomal dominant retinitis pigmentosa (adRP) without effective therapeutic treatment so far. Compared with genomic DNA-targeting CRISPR-Cas9 system, Cas13 edits RNA for therapeutic applications, avoiding the risk of causing permanent changes in the genome. In particular, a compact and high-fidelity Cas13X (hfCas13X) recently has been developed to degrade targeted RNA with minimal collateral effects and could also be packaged in a single adeno-associated virus for efficient in vivo delivery. In this study, we engineered single-guide RNA for hfCas13X to specifically knock down human mutant Rhodopsin transcripts RHO-P23H with minimal effect on wild-type transcripts. Moreover, treatment with hfCas13X alleviated the adRP progression in both RHO-P23H overexpression-induced and humanized hRHO P23H/WT mouse models. Our study indicates the potential of hfCas13X in treating adRP caused by RHO mutations and other genetic diseases., Competing Interests: H.Y. is a founder of HuidaGene Therapeutics Co., Ltd., Shanghai., (© 2023 The Author(s).)

The elucidation of protein function and its exploitation in bioengineering have greatly advanced the life sciences. Protein mining efforts generally rely on amino acid sequences rather than protein structures. We describe here the use of AlphaFold2 to predict and subsequently cluster an entire protein family based on predicted structure similarities. We selected deaminase proteins to analyze and identified many previously unknown properties. We were surprised to find that most proteins in the DddA-like clade were not double-stranded DNA deaminases. We engineered the smallest single-strand-specific cytidine deaminase, enabling efficient cytosine base editor (CBE) to be packaged into a single adeno-associated virus (AAV). Importantly, we profiled a deaminase from this clade that edits robustly in soybean plants, which previously was inaccessible to CBEs. These discovered deaminases, based on AI-assisted structural predictions, greatly expand the utility of base editors for therapeutic and agricultural applications., Competing Interests: Declaration of interests The authors have submitted two patent applications based on the results reported in this paper. C.G. is a member of the Cell advisory board. K.T.Z. is a founder and employee at Qi Biodesign., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Approximately 140 million people worldwide are homozygous carriers of APOE4 (ε4), a strong genetic risk factor for late onset familial and sporadic Alzheimer's disease (AD), 91% of whom will develop AD at earlier age than heterozygous carriers and noncarriers. Susceptibility to AD could be reduced by targeted editing of APOE4, but a technical basis for controlling the off-target effects of base editors is necessary to develop low-risk personalized gene therapies. Here, we first screened eight cytosine base editor variants at four injection stages (from 1- to 8-cell stage), and found that FNLS-YE1 variant in 8-cell embryos achieved the comparable base conversion rate (up to 100%) with the lowest bystander effects. In particular, 80% of AD-susceptible ε4 allele copies were converted to the AD-neutral ε3 allele in human ε4-carrying embryos. Stringent control measures combined with targeted deep sequencing, whole genome sequencing, and RNA sequencing showed no DNA or RNA off-target events in FNLS-YE1-treated human embryos or their derived stem cells. Furthermore, base editing with FNLS-YE1 showed no effects on embryo development to the blastocyst stage. Finally, we also demonstrated FNLS-YE1 could introduce known protective variants in human embryos to potentially reduce human susceptivity to systemic lupus erythematosus and familial hypercholesterolemia. Our study therefore suggests that base editing with FNLS-YE1 can efficiently and safely introduce known preventive variants in 8-cell human embryos, a potential approach for reducing human susceptibility to AD or other genetic diseases., (©The Author(s) 2022. Published by Oxford University Press on behalf of Higher Education Press.)

Background: Gastric cancer (GC) is a common malignant tumor of the digestive system. Circular RNAs (circRNAs) play a vital role in tumorigenesis and chemoresistance. The current study aimed to explore the possible role and mechanism of circRNA leucine rich repeats and calponin homology domain containing 3 (circLRCH3) in GC chemoresistance., Methods: The levels of circLRCH3, microRNA-383-5p (miR-383-5p) and fibroblast growth factor 7 (FGF7) were determined by quantitative real-time PCR or Western blot. Cell Counting Kit-8 (CCK-8) assay was utilized to evaluate cell survival rate and proliferation ability. Colony formation, transwell and flow cytometry assays were used to assess cell proliferation, migration, invasion and apoptosis. The expression of multidrug resistance proteins was detected by Western blot. The binding relationship between miR-383-5p and circLRCH3/FGF7 was verified by dual-luciferase reporter assay or RNA immunoprecipitation assay. Xenograft assay was conducted to analyze the role of circLRCH3 in OXA resistance in vivo., Results: CircLRCH3 and FGF7 levels were up-regulated, while miR-383-5p level was reduced in OXA-resistant GC tissues and cells. Depletion of circLRCH3 attenuated the resistance of OXA-resistant cells to OXA. CircLRCH3 silence reduced OXA resistance by regulating miR-383-5p. Besides, miR-383-5p elevated OXA sensitivity of GC cells by repressing FGF7. Moreover, the deletion of circLRCH3 increased OXA sensitivity in vivo., Conclusions: Knockdown of circLRCH3 alleviated OXA resistance of GC by modulating the miR-383-5p/FGF7 axis, which provided a promising therapeutic target for GC chemoresistance., (©The Author(s) 2023. Open Access. This article is licensed under a Creative Commons CC-BY International License.)

Food safety problems are becoming increasingly severe in modern society, and establishing an accurate food safety risk warning and analysis model is of positive significance in avoiding food safety accidents. We propose an algorithmic framework that integrates the analytic hierarchy process based on the entropy weight (AHP-EW) and the autoencoder-recurrent neural network (AE-RNN). Specifically, the AHP-EW method is first used to obtain the weight percentages of each detection index. The comprehensive risk value of the product samples is obtained by weighted summation with the detection data, which is used as the expected output of the AE-RNN network. The AE-RNN network is constructed to predict the comprehensive risk value of unknown products. The detailed risk analysis and control measures are taken based on the risk value. We applied this method to the detection data of a dairy product brand in China for example validation. Compared with the performance of 3 models of the back propagation algorithm (BP), the long short-term memory network (LSTM), and the LSTM based on the attention mechanism (LSTM-Attention), the AE-RNN model has a shorter convergence time, predicts data more accurately. The root mean square error (RMSE) of experimental data is only 0.0018, proving that the model is feasible in practice and helps improve the food safety supervision system in China to avoid food safety incidents., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Zhong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Base editors have been reported to induce off-target mutations in cultured cells, mouse embryos and rice, but their long-term effects in vivo remain unknown. Here, we develop a Systematic evaluation Approach For gene Editing tools by Transgenic mIce (SAFETI), and evaluate the off-target effects of BE3, high fidelity version of CBE (YE1-BE3-FNLS) and ABE (ABE7.10 F148A ) in ~400 transgenic mice over 15 months. Whole-genome sequence analysis reveals BE3 expression generated de novo mutations in the offspring of transgenic mice. RNA-seq analysis reveals both BE3 and YE1-BE3-FNLS induce transcriptome-wide SNVs, and the numbers of RNA SNVs are positively correlated with CBE expression levels across various tissues. By contrast, ABE7.10 F148A shows no detectable off-target DNA or RNA SNVs. Notably, we observe abnormal phenotypes including obesity and developmental delay in mice with permanent genomic BE3 overexpression during long-time monitoring, elucidating a potentially overlooked aspect of side effects of BE3 in vivo., (© 2023. The Author(s).)

Effective contamination warning and control of food quality can significantly reduce the likelihood of food quality safety incidents. Existing food contamination warning models for food quality rely on supervised learning, do not model the complex feature associations between detection samples, and do not consider the unevenness of detection data categories. In this paper, To overcome these limitations, we propose a Contrastive Self-supervised learning-based Graph Neural Network framework (CSGNN) for contamination warning of food quality. Specifically, we structure the graph for detecting correlations between samples and then define the positive and negative instance pairs for contrastive learning based on attribute networks. Further, we use a self-supervised approach to capture the complex relationships between detection samples. Finally, we assessed each sample's contamination level based on the absolute value of the subtraction of the prediction scores from multiple rounds of positive and negative instances obtained by the CSGNN. Moreover, we conducted a sample study on a batch of dairy product detection data in a Chinese province. The experimental results show that CSGNN outperforms other baseline models in contamination assessment of food quality, with AUC and recall of unqualified samples reaching 0.9188 and 1.0000, respectively. Meanwhile, our framework provides interpretable contamination classification for food detection. This study provides an efficient early warning method with precise and hierarchical contamination classification for contamination warning of food quality work.

Liquid biopsy is currently a non-destructive and convenient method of cancer screening, due to human blood containing a variety of cancer-related biomolecules. Therefore, the development of an accurate and rapid breast cancer screening technique combined with breast cancer serum is crucial for the treatment and prognosis of breast cancer patients. In this study, the surface enhanced Raman spectroscopy (SERS) technique is used to enhance the Raman spectroscopy (RS) signal of serum based on a high sensitivity thermally annealed silver nanoparticle/porous silicon bragg mirror (AgNPs/PSB) composite substrate. Compared with RS, SERS reflects more and stronger spectral peak information, which is beneficial to discover new biomarkers of breast cancer. At the same time, to further explore the diagnostic ability of SERS technology for breast cancer. In this study, the raw spectral data are processed by baseline correction, polynomial smoothing, and normalization. Then, the relevant feature information of SERS and RS is extracted by principal component analysis (PCA), and five classification models are established to compare the diagnostic performance of SERS and RS models respectively. The experimental results show that the breast cancer diagnosis model based on the improved SERS substrate combined with the machine learning algorithm can be used to distinguish breast cancer patients from controls. The accuracy, sensitivity, specificity and AUC values of the SVM model are 100%, 100%, 100% and 100%, respectively, as well as the training time of 4 ms. The above experimental results show that the SERS technology based on AgNPs/PSB composite substrate, combined with machine learning methods, has great potential in the rapid and accurate identification of breast cancer patients., (Copyright © 2023. Published by Elsevier B.V.)

Outlier detection is an important topic in machine learning and has been used in a wide range of applications. Outliers are objects that are few in number and deviate from the majority of objects. As a result of these two properties, we show that outliers are susceptible to a mechanism called fluctuation. This article proposes a method called fluctuation-based outlier detection (FBOD) that achieves a low linear time complexity and detects outliers purely based on the concept of fluctuation without employing any distance, density or isolation measure. Fundamentally different from all existing methods. FBOD first converts the Euclidean structure datasets into graphs by using random links, then propagates the feature value according to the connection of the graph. Finally, by comparing the difference between the fluctuation of an object and its neighbors, FBOD determines the object with a larger difference as an outlier. The results of experiments comparing FBOD with eight state-of-the-art algorithms on eight real-worlds tabular datasets and three video datasets show that FBOD outperforms its competitors in the majority of cases and that FBOD has only 5% of the execution time of the fastest algorithm. The experiment codes are available at: https://github.com/FluctuationOD/Fluctuation-based-Outlier-Detection ., (© 2023. The Author(s).)

Approximately 10% of monogenic diseases are caused by nonsense point mutations that generate premature termination codons (PTCs), resulting in a truncated protein and nonsense-mediated decay of the mutant mRNAs. Here, we demonstrate a mini-dCas13X-mediated RNA adenine base editing (mxABE) strategy to treat nonsense mutation-related monogenic diseases via A-to-G editing in a genetically humanized mouse model of Duchenne muscular dystrophy (DMD). Initially, we identified a nonsense point mutation (c.4174C>T, p.Gln1392*) in the DMD gene of a patient and validated its pathogenicity in humanized mice. In this model, mxABE packaged in a single adeno-associated virus (AAV) reached A-to-G editing rates up to 84% in vivo, at least 20-fold greater than rates reported in previous studies using other RNA editing modalities. Furthermore, mxABE restored robust expression of dystrophin protein to over 50% of WT levels by enabling PTC read-through in multiple muscle tissues. Importantly, systemic delivery of mxABE by AAV also rescued dystrophin expression to averages of 37%, 6%, and 54% of WT levels in the diaphragm, tibialis anterior, and heart muscle, respectively, as well as rescued muscle function. Our data strongly suggest that mxABE-based strategies may be a viable new treatment modality for DMD and other monogenic diseases.

According to the limited molecular information reflected by single spectroscopy, and the complementarity of FTIR spectroscopy and Raman spectroscopy, we propose a novel diagnostic technology combining multispectral fusion and deep learning. We used serum samples from 45 healthy controls, 44 non-small cell lung cancer (NSCLC), 38 glioma and 37 esophageal cancer patients, and the Raman spectra and FTIR spectra were collected respectively. Then we performed low-level fusion and feature fusion on the spectral, and used SVM, Convolutional Neural Network-Long-Short Term Memory (CNN-LSTM) and the multi-scale convolutional fusion neural network (MFCNN). The accuracy of low-level fusion and feature fusion models are improved by about 10% compared with single spectral models., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

This study aimed to investigate the prognostic value of tumoral HAMP expression in patients with clear cell renal cell carcinoma (ccRCC). In a TCGA dataset, we found that HAMP mRNA expression was increased in ccRCC tumors compared with normal controls. Tumoral HAMP mRNA expression was positively correlated with clinical stage, tumor grade, and TNM stages. Patients with high HAMP expression had poorer overall survival than those with low HAMP expression. Tumoral HAMP mRNA level independently predicted the survival of patients. HAMP protein expression was increased in real-world ccRCC tumors compared with those in paired, adjacent noncancerous tissue and was positively correlates with tumor grading. These results suggest HAMP as a potential prognostic factor for ccRCC patients.

Reprogramming Müller glia (MG) into functional cells is considered a promising therapeutic strategy to treat ocular diseases and vision loss. However, current AAV-based system for MG-tracing was reported to have high leakage in recent studies. Here, we focused on reducing the leakage of AAV-based labeling systems and found that different AAV serotypes showed a range of efficiency and specificity in labeling MG, leading us to optimize a human GFAP-Cre reporter system packaged in the AAV9 serotype with the woodchuck hepatitis virus post-transcriptional regulatory element (WPRE) removed. The leakage ratio of the AAV9-hGFAP-Cre-ΔWPRE decreased by an approximate 40-fold compared with the AAV9-hGFAP-Cre-WPRE labeling system. In addition, we validated the specificity of the AAV-ΔWPRE system for tracing MG reprogramming under Ptbp1-suppression and observed strict non-MG-conversion, similar to previous studies using genetic lineage tracking mouse models. Thus, the AAV9-hGFAP-Cre-ΔWPRE system showed high efficiency and specificity for MG labeling, providing a promising tool for tracing cell fate in vivo., (© 2022. The Author(s).)

Maojian is one of China's traditional famous teas. There are many Maojian-producing areas in China. Because of different producing areas and production processes, different Maojian have different market prices. Many merchants will mix Maojian in different regions for profit, seriously disrupting the healthy tea market. Due to the similar appearance of Maojian produced in different regions, it is impossible to make a quick and objective distinction. It often requires experienced experts to identify them through multiple steps. Therefore, it is of great significance to develop a rapid and accurate method to identify different regions of Maojian to promote the standardization of the Maojian market and the development of detection technology. In this study, we propose a new method based on Near infra-red (NIR) with deep learning algorithms to distinguish different origins of Maojian. In this experiment, the NIR spectral data of Maojian from different origins are combined with the back propagation neural network (BPNN), improved AlexNet, and improved RepSet models for classification. Among them, improved RepSet has the highest accuracy of 99.30%, which is 8.67% and 0.70% higher than BPNN and improved AlexNet, respectively. The overall results show that it is feasible to use NIR and deep learning methods to quickly and accurately identify Maojian from different origins and prove an effective alternative method to discriminate different origins of Maojian., (© 2022. The Author(s).)

Brain calcification is a critical aging-associated pathology and can cause multifaceted neurological symptoms. Cerebral phosphate homeostasis dysregulation, blood-brain barrier defects, and immune dysregulation have been implicated as major pathological processes in familial brain calcification (FBC). Here, we analyzed two brain calcification families and identified calcification co-segregated biallelic variants in the CMPK2 gene that disrupt mitochondrial functions. Transcriptome analysis of peripheral blood mononuclear cells (PBMCs) isolated from these patients showed impaired mitochondria-associated metabolism pathways. In situ hybridization and single-cell RNA sequencing revealed robust Cmpk2 expression in neurons and vascular endothelial cells (vECs), two cell types with high energy expenditure in the brain. The neurons in Cmpk2-knockout (KO) mice have fewer mitochondrial DNA copies, down-regulated mitochondrial proteins, reduced ATP production, and elevated intracellular inorganic phosphate (Pi) level, recapitulating the mitochondrial dysfunction observed in the PBMCs isolated from the FBC patients. Morphologically, the cristae architecture of the Cmpk2-KO murine neurons was also impaired. Notably, calcification developed in a progressive manner in the homozygous Cmpk2-KO mice thalamus region as well as in the Cmpk2-knock-in mice bearing the patient mutation, thus phenocopying the calcification pathology observed in the patients. Together, our study identifies biallelic variants of CMPK2 as novel genetic factors for FBC; and demonstrates how CMPK2 deficiency alters mitochondrial structures and functions, thereby highlighting the mitochondria dysregulation as a critical pathogenic mechanism underlying brain calcification., (© 2022. The Author(s).)

CRISPR-mediated epigenome editing enables gene expression regulation without changing the underlying DNA sequence, and thus has vast potential for basic research and gene therapy. Effective selection of a single guide RNA (sgRNA) with high on-target efficiency and specificity would facilitate the application of epigenome editing tools. Here we performed an extensive analysis of CRISPR-mediated epigenome editing tools on thousands of experimentally examined on-target sites and established EpiCas-DL , a deep learning framework to optimize sgRNA design for gene silencing or activation. EpiCas-DL achieves high accuracy in sgRNA activity prediction for targeted gene silencing or activation and outperforms other available in silico methods. In addition, EpiCas-DL also identifies both epigenetic and sequence features that affect sgRNA efficacy in gene silencing and activation, facilitating the application of epigenome editing for research and therapy. EpiCas-DL is available at http://www.sunlab.fun:3838/EpiCas-DL., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Fennel contains many antioxidant and antibacterial substances, and it has very important applications in food flavoring and other fields. The kinds and contents of chemical substances in fennel vary from region to region, which can affect the taste and efficacy of the fennel and its derivatives. Therefore, it is of great significance to accurately classify the origin of the fennel. Recently, origin detection methods based on deep networks have shown promising results. However, the existing methods spend a relatively large time cost, a drawback that is fatal for large amounts of data in practical application scenarios. To overcome this limitation, we explore an origin detection method that guarantees faster detection with classification accuracy. This research is the first to use the machine learning algorithm combined with the Fourier transform-near infrared (FT-NIR) spectroscopy to realize the classification and identification of the origin of the fennel. In this experiment, we used Rubberband baseline correction on the FT-NIR spectral data of fennel (Yumen, Gansu and Turpan, Xinjiang), using principal component analysis (PCA) for data dimensionality reduction, and selecting extreme learning machine (ELM), Convolutional Neural Network (CNN), recurrent neural network (RNN), Transformer, generative adversarial networks (GAN) and back propagation neural network (BPNN) classification model of the company realizes the classification of the sample origin. The experimental results show that the classification accuracy of ELM, RNN, Transformer, GAN and BPNN models are above 96%, and the ELM model using the hardlim as the activation function has the best classification effect, with an average accuracy of 100% and a fast classification speed. The average time of 30 experiments is 0.05 s. This research shows the potential of the machine learning algorithm combined with the FT-NIR spectra in the field of food production area classification, and provides an effective means for realizing rapid detection of the food production area, so as to merchants from selling shoddy products as good ones and seeking illegal profits., (© 2022. The Author(s).)

Food safety is a high-priority issue for all countries. Early warning analysis and risk control are essential for food safety management practices. This paper innovatively proposes an anomaly score-based risk early warning system (ASRWS) via an unsupervised auto-encoder (AE) for the effective early warning of detection products, which classifies qualified and unqualified products by reconstructing errors. The early warning analysis of qualified samples is carried out by early warning thresholds. The proposed method is applied to a batch of dairy product testing data from a Chinese province. Extensive experimental results show that the unsupervised anomaly detection model AE can effectively analyze the dairy product testing data, with a prediction accuracy and fault detection rate of 0.9954 and 0.9024, respectively, within only 0.54 s. We provided an early warning threshold-based method to conduct the risk analysis, and then a panel of food safety experts performed a risk revision on the prediction results produced by the proposed method. In this way, AI improves the panel's efficiency, whereas the panel enhances the model's reliability. This study provides a fast and cost-effective, food safety early warning method for detection data and assists market supervision departments in controlling food safety risk.

With the development of commodity economy, the emergence of fake and shoddy raisin has seriously harmed the interests of consumers and enterprises. To deal with this problem, a classification method combining near-infrared spectroscopy and pattern recognition algorithms were proposed for adulterated raisins. In this study, the experiment was performed by three kinds of raisins in Xinjiang (Hongxiangfei, Manaiti, Munage). After collecting and normalizing the spectral data, we compared the spectra of three kinds of raisins. Next the principal component analysis (PCA) was preformed to compress the dimension of the spectral data, and then classification models including support vector machine (SVM), multiscale fusion convolutional neural network (MCNN) and improved AlexNet were established to identify raisins. The accuracy of SVM, MCNN, and improved AlexNet is 100%, 92.83%, and 97.78% respectively. This study proves that near-infrared spectroscopy combined with pattern recognition is feasible for the raisin inspection., (© 2022. The Author(s).)

Cobalt-chromium (Co-Cr) alloys have been widely used as dental-restoration materials for many years. This study sought to investigate whether selective laser melting (SLM) is a more appropriate process than traditional casting (CAST) for fabricating dental Co-Cr alloys. Metallurgical microscopy, X-ray photoelectron spectroscopy (XPS), Vickers hardness and nanoindentation tests, and friction and wear tests were used to evaluate the microstructure, surface compositions, mechanical properties, and wear resistance, respectively. Additionally, the biocompatibilities and cell adhesion of the alloys were evaluated with L-929 fibroblasts via CCK-8 assay, Live/Dead staining, flow cytometric analysis, scanning electron microscopy (SEM) observation and real-time PCR (RT-PCR) assay. The XPS results showed that the two alloys were all mainly comprised of Co, Cr, and O. The hardness in the CAST group equaled 7.15 ± 0.48 GPa, while in the SLM group, it equaled 9.06 ± 0.49 GPa. The friction coefficient of SLM alloys remained at approximately 0.46, but the CAST specimens fluctuated significantly. SLM alloys exhibited shallower wear scars and less wear debris compared with CAST alloys, simultaneously. Additionally, there were higher survival and expression of cell-adhesion-related genes on SLM alloys of L-929 cells, which meant that the deleterious effect on L-929 cells was significantly reduced compared with that for the CAST alloys. Overall, the wear resistances and biocompatibilities of the Co-Cr dental alloys were dramatically affected by the fabrication technique. The SLM technique is advantageous over the CAST technique for fabricating Co-Cr dental alloys.

Purpose: The aim of this study was to investigate the differential effects of Tai Chi vs. brisk walking on cognitive function among individuals aged 60 and greater., Patients and Methods: For participant recruitment, a health talk was arranged at two communities in which two different exercise modalities (Tai Chi and brisk walking) were assigned to participants of each community free of charge. The intervention programs lasted 10 weeks, with three 60-min training sessions per week. General cognitive ability and specific cognitive outcomes were measured using the Chinese version of the Montreal Cognitive Assessment (MoCA)., Results: A significant interaction on total scores of the MoCA was observed ( F = 11.15, p < 0.05). Post hoc analysis indicated significant improvements on general cognitive performance as measured in performance on the MoCA for both exercise groups at the end of 10 weeks. A significant interaction was only observed on the delayed recall sub-domain ( F = 12.93, p < 0.001). Results from post hoc analysis indicate that the Tai Chi group had a significantly better memory performance relative to brisk walking group ( p < 0.05). Specifically, significant improvement was observed in Tai Chi group ( p < 0.05), but not in the brisk walking group. Both exercise groups demonstrated significant improvements from baseline to Week 10, which emerged in visualspatial ability ( p < 0.05) and attention performance ( p < 0.001). Lastly, animal naming and orientation significantly benefited from brisk walking ( p < 0.05) and Tai Chi training ( p < 0.05), respectively., Conclusion: Tai Chi and brisk walking as the most commonly used, culture-specific mind-body exercise method have been proven to be effective in improving general cognitive performance and specific cognitive domains. Furthermore, differential effects of two different exercise modalities on cognitive domains were observed, which has provided insightful information for customized exercise programs. Finally, aging individuals who are experiencing cognitive decline should either take Tai Chi classes regularly or engage in brisk walking, which could contribute to brain health., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yu, Zuo and Doig.)

Objective: To investigate the effect of sarcopenia on the prognosis of stage II-III colorectal cancer patients undergoing adjuvant chemotherapy., Methods: A total of 196 stage II-III colorectal cancer patients who received 8 cycles of postoperative chemotherapy were retrospectively analyzed. An abdominal CT acquired at 3-4 weeks after surgery was used to calculate the psoas muscle index. Subsequently, once gender-specific receiver operating characteristic curves were plotted and cut-off values of psoas muscle index were defined, the clinicopathological characteristics and the prognosis of patients with high and low values were compared. Lastly, prognostic models were established based on the independent prognostic factors of relapse-free survival and overall survival identified by COX analysis., Results: Based on the psoas muscle index, the prevalence of sarcopenia was 37.5% among 196 patients. This prevalence has significant correlation with patients' age and gender. However, it was not related to the AJCC stage, T stage, lymph node metastasis, pathological grade, grade III-IV myelosuppression, or preoperative carcinoembryonic antigen level. In addition, both the relapse-free and the overall survival of patients with low and high psoas muscle indexes were significantly different. COX analysis indicated that the psoas muscle index was an independent prognostic factor. Both the overall survival prognostic model based on patients' psoas muscle index, stage, pathological grade, and preoperative carcinoembryonic antigen level and the relapse-free survival prognostic model based on patients' psoas muscle index, pathological grade, and preoperative carcinoembryonic antigen level could accurately predict the prognosis of patients., Conclusion: For stage II-III colorectal cancer patients, the presence of sarcopenia before adjuvant chemotherapy would adversely affect their recurrence-free and overall survival. Prognostic models based on psoas muscle index, stage, pathological grade, and preoperative carcinoembryonic antigen level could accurately predict the prognosis in these patients., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Li Shan et al.)

Myosin VI（MYO6） is an unconventional myosin that is vital for auditory and vestibular function. Pathogenic variants in the human MYO6 gene cause autosomal-dominant or -recessive forms of hearing loss. Effective treatments for Myo6 mutation causing hearing loss are limited. We studied whether adeno-associated virus (AAV)-PHP.eB vector-mediated in vivo delivery of Staphylococcus aureus Cas9 (SaCas9-KKH)-single-guide RNA (sgRNA) complexes could ameliorate hearing loss in a Myo6 WT/C442Y mouse model that recapitulated the phenotypes of human patients. The in vivo editing efficiency of the AAV-SaCas9-KKH-Myo6-g2 system on Myo6 C442Y is 4.05% on average in Myo6 WT/C442Y mice, which was ∼17-fold greater than editing efficiency of Myo6 WT alleles. Rescue of auditory function was observed up to 5 months post AAV-SaCas9-KKH-Myo6-g2 injection in Myo6 WT/C442Y mice. Meanwhile, shorter latencies of auditory brainstem response (ABR) wave I, lower distortion product otoacoustic emission (DPOAE) thresholds, increased cell survival rates, more regular hair bundle morphology, and recovery of inward calcium levels were also observed in the AAV-SaCas9-KKH-Myo6-g2-treated ears compared to untreated ears. These findings provide further reference for in vivo genome editing as a therapeutic treatment for various semi-dominant forms of hearing loss and other semi-dominant diseases., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.)

Clustered regularly interspaced short palindromic repeats (CRISPR) is a promising innovative technology for genomic editing that offers scientists the chance to edit DNA structures and change gene function. It has several possible uses consisting of editing inherited deficiencies, treating, and reducing the spread of disorders. Recently, reports have demonstrated the creation of synthetic RNA molecules and supplying them alongside Cas9 into genome of eukaryotes, since distinct specific regions of the genome can be manipulated and targeted. The therapeutic potential of CRISPR/Cas9 technology is great, especially in gene therapy, in which a patient-specific mutation is genetically edited, or in the treating of human disorders that are untreatable with traditional treatments. This review focused on numerous, in vivo , in vitro, and ex vivo uses of the CRISPR/Cas9 technology in human inherited diseases, discovering the capability of this versatile in medicine and examining some of the main limitations for its upcoming use in patients. In addition to introducing a brief impression of the biology of the CRISPR/Cas9 scheme and its mechanisms, we presented the utmost recent progress in the uses of CRISPR/Cas9 technology in editing and treating of human genetic diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Abdelnour, Xie, Hassanin, Zuo and Lu.)

For the benefit of antibacterial Ti on orthopedic and dental implants, a bioactive coating (Pac@PLGA MS/HA coated Ti) was deposited on the surface of pure titanium (Ti), which included two layers: an acid-alkali heat pretreated biomimetic mineralization layer and an electrosprayed Poly (D,L-lactide-co- glycolic acid) (PLGA) microsphere layer as a sustained-release system. Hydroxyapatite (HA) in mineralization layer was primarily prepared on the Ti followed by the antibacterial coating of Pac-525 loaded by PLGA microspheres. After observing the antimicrobial peptides distributed uniformly on the titanium surface, the release assay showed that the release of Pac-525 from Pac@PLGA MS/HA coated Ti provided a large initial burst followed by a slow release at a flat rate. Pac@PLGA MS/HA coated Ti exhibited a strong cytotoxicity to both Gram-negative bacteria ( Escherichia coli ) and Gram-positive bacteria ( Staphylococcus aureus ). In addition, Pac@PLGA MS/HA coated Ti did not affect the growth and adhesion of the osteoblast-like cell line, MC3T3-E1. These data suggested that a bionic mineralized composite coating with long-term antimicrobial activity was successfully prepared.

Cross-domain sentiment classification could be attributed to two steps. The first step is used to extract the text representation, and the other is to reduce domain discrepancy. Existing methods mostly focus on learning the domain-invariant information, rarely consider using the domain-specific semantic information, which could help cross-domain sentiment classification; traditional adversarial-based models merely focus on aligning the global distribution ignore maximizing the class-specific decision boundaries. To solve these problems, we propose a context-aware semantic adaptation (CASA) network for cross-domain implicit sentiment classification (ISC). CASA can provide more semantic relationships and an accurate understanding of the emotion-changing process for ISC tasks lacking explicit emotion words. (1) To obtain inter- and intrasentence semantic associations, our model builds a context-aware heterogeneous graph (CAHG), which can aggregate the intrasentence dependency information and the intersentence node interaction information, followed by an attention mechanism that remains high-level domain-specific features. (2) Moreover, we conduct a new multigrain discriminator (MGD) to effectively reduce the interdomain distribution discrepancy and improve intradomain class discrimination. Experimental results demonstrate the effectiveness of different modules compared with existing models on the Chinese implicit emotion dataset and four public explicit datasets., (© 2021. The Author(s).)

Efficient and precise base editors (BEs) for C-to-G transversion are highly desirable. However, the sequence context affecting editing outcome largely remains unclear. Here we report engineered C-to-G BEs of high efficiency and fidelity, with the sequence context predictable via machine-learning methods. By changing the species origin and relative position of uracil-DNA glycosylase and deaminase, together with codon optimization, we obtain optimized C-to-G BEs (OPTI-CGBEs) for efficient C-to-G transversion. The motif preference of OPTI-CGBEs for editing 100 endogenous sites is determined in HEK293T cells. Using a sgRNA library comprising 41,388 sequences, we develop a deep-learning model that accurately predicts the OPTI-CGBE editing outcome for targeted sites with specific sequence context. These OPTI-CGBEs are further shown to be capable of efficient base editing in mouse embryos for generating Tyr-edited offspring. Thus, these engineered CGBEs are useful for efficient and precise base editing, with outcome predictable based on sequence context of targeted sites., (© 2021. The Author(s).)

Background: N-hexane, with its metabolite 2,5-hexanedine (HD), is an industrial hazardous material. Chronic hexane exposure causes segmental demyelination in the peripheral nerves, and high-dose intoxication may also affect central nervous system. Demyelinating conditions are difficult to treat and stem cell therapy using bone marrow mesenchymal stem cells (BMSCs) is a promising novel strategy. Our previous study found that BMSCs promoted motor function recovery in rats modeling hexane neurotoxicity. This work aimed to explore the underlying mechanisms and focused on the changes in spinal cord., Methods: Sprague Dawley rats were intoxicated with HD (400 mg/kg/day, i.p, for 5 weeks). A bolus of BMSCs (5 × 10 7 cells/kg) was injected via tail vein. Demyelination and remyelination of the spinal cord before and after BMSC treatment were examined microscopically. Cultured oligodendrocyte progenitor cells (OPCs) were incubated with HD ± BMSC-derived conditional medium (BMSC-CM). OPC differentiation was studied by immunostaining and morphometric analysis. The expressional changes of Hes1, a transcription factor negatively regulating OPC-differentiation, were studied. The upstream Notch1 and TNFα/RelB pathways were studied, and some key signaling molecules were measured. The correlation between neurotrophin NGF and TNFα was also investigated. Statistical significance was evaluated using one-way ANOVA and performed using SPSS 13.0., Results: The demyelinating damage by HD and remyelination by BMSCs were evidenced by electron microscopy, LFB staining and NG2/MBP immunohistochemistry. In vitro cultured OPCs showed more differentiation after incubation with BMSC-CM. Hes1 expression was found to be significantly increased by HD and decreased by BMSC or BMSC-CM. The change of Hes1 was found, however, independent of Notch1 activation, but dependent on TNFα/RelB signaling. HD was found to increase TNFα, RelB and Hes1 expression, and BMSCs were found to have the opposite effect. Addition of recombinant TNFα to OPCs or RelB overexpression similarly caused upregulation of Hes1 expression. The secretion of NGF by BMSC and activation of NGF receptor was found important for suppression of TNFα production in OPCs., Conclusions: Our findings demonstrated that BMSCs promote remyelination in the spinal cord of HD-exposed rats via TNFα/RelB-Hes1 pathway, providing novel insights for evaluating and further exploring the therapeutical effect of BMSCs on demyelinating neurodegenerative disease., (© 2021. The Author(s).)

Clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (CRISPR/Cas9) genome editing technology has dramatically influenced swine research by enabling the production of high-quality disease-resistant pig breeds, thus improving yields. In addition, CRISPR/Cas9 has been used extensively in pigs as one of the tools in biomedical research. In this review, we present the advancements of the CRISPR/Cas9 system in swine research, such as animal breeding, vaccine development, xenotransplantation, and disease modeling. We also highlight the current challenges and some potential applications of the CRISPR/Cas9 technologies., (Copyright © 2021 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.)

Programmable RNA cytidine deamination has recently been achieved using a bifunctional editor (RESCUE-S) capable of deaminating both adenine and cysteine. Here, we report the development of "CURE", the first cytidine-specific C-to-U RNA Editor. CURE comprises the cytidine deaminase enzyme APOBEC3A fused to dCas13 and acts in conjunction with unconventional guide RNAs (gRNAs) designed to induce loops at the target sites. Importantly, CURE does not deaminate adenosine, enabling the high-specificity versions of CURE to create fewer missense mutations than RESCUE-S at the off-targets transcriptome-wide. The two editing approaches exhibit overlapping editing motif preferences, with CURE and RESCUE-S being uniquely able to edit UCC and AC motifs, respectively, while they outperform each other at different subsets of the UC targets. Finally, a nuclear-localized version of CURE, but not that of RESCUE-S, can efficiently edit nuclear RNAs. Thus, CURE and RESCUE are distinct in design and complementary in utility., (© 2020 The Authors.)

Genome editing holds great potential for correcting pathogenic mutations. We developed a method called GOTI (genome-wide off-target analysis by two-cell embryo injection) to detect off-target mutations by editing one blastomere of two-cell mouse embryos using either CRISPR-Cas9 or base editors. GOTI directly compares edited and non-edited cells without the interference of genetic background and thus could detect potential off-target variants with high sensitivity. Notably, the GOTI method was designed to detect potential off-target variants of any genome editing tools by the combination of experimental and computational approaches, which is critical for accurate evaluation of the safety of genome editing tools. Here we provide a detailed protocol for GOTI, including mice mating, two-cell embryo injection, embryonic day 14.5 embryo digestion, fluorescence-activated cell sorting, whole-genome sequencing and data analysis. To enhance the utility of GOTI, we also include a computational workflow called GOTI-seq (https://github.com/sydaileen/GOTI-seq) for the sequencing data analysis, which can generate the final genome-wide off-target variants from raw sequencing data directly. The protocol typically takes 20 d from the mice mating to sequencing and 7 d for sequencing data analysis.

Cytosine base editors (CBEs) enable efficient cytidine-to-thymidine (C-to-T) substitutions at targeted loci without double-stranded breaks. However, current CBEs edit all Cs within their activity windows, generating undesired bystander mutations. In the most challenging circumstance, when a bystander C is adjacent to the targeted C, existing base editors fail to discriminate them and edit both Cs. To improve the precision of CBE, we identified and engineered the human APOBEC3G (A3G) deaminase; when fused to the Cas9 nickase, the resulting A3G-BEs exhibit selective editing of the second C in the 5'-CC-3' motif in human cells. Our A3G-BEs could install a single disease-associated C-to-T substitution with high precision. The percentage of perfectly modified alleles is more than 6000-fold for disease correction and more than 600-fold for disease modeling compared with BE4max. On the basis of the two-cell embryo injection method and RNA sequencing analysis, our A3G-BEs showed minimum genome- and transcriptome-wide off-target effects, achieving high targeting fidelity., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Cytosine base editors (CBEs) offer a powerful tool for correcting point mutations, yet their DNA and RNA off-target activities have caused concerns in biomedical applications. We describe screens of 23 rationally engineered CBE variants, which reveal mutation residues in the predicted DNA-binding site can dramatically decrease the Cas9-independent off-target effects. Furthermore, we obtained a CBE variant-YE1-BE3-FNLS-that retains high on-target editing efficiency while causing extremely low off-target edits and bystander edits.

Genome stability is critical for the normal development of preimplantation embryos, as DNA damages may result in mutation and even embryo lethality. Anti-silencing factor 1A (ASF1A) is a histone chaperone and enriched in the MII oocytes as a maternal factor, which may be associated with the maintenance of genome stability. Thus, this study was undertaken to explore the role of ASF1A in maintaining the genome stability of early mouse embryos. The ASF1A expressed in the preimplantation embryos and displayed a dynamic pattern throughout the early embryonic development. Inhibition of ASF1A expression decreased embryonic development and increased DNA damages. Overexpression of ASF1A improved the developmental potential and decreased DNA damages. When 293T cells that had been integrated with RGS-NHEJ were co-transfected with plasmids of pcDNA3.1-ASF1A, gRNA-NHEJ, and hCas9, less cells expressed eGFP, indicating that non-homologous end joining was reduced by ASF1A. When 293T cells were co-transfected with plasmids of HR-donor, gRNA-HR, hCas9, and pcDNA3.1-ASF1A, more cells expressed eGFP, indicating that homologous recombination (HR) was enhanced by ASF1A. These results indicate that ASF1A may be associated with the genome stability maintenance of early mouse embryos and this action may be mediated by promoting DNA damage repair through HR pathway., (© The Author(s) 2020. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Osteoporosis is a skeletal disorder characterized by a systemic impairment of bone mineral density (BMD). Genome-wide association studies (GWAS) have identified hundreds of susceptibility loci for osteoporosis and BMD. However, the vast majority of susceptibility loci are located in non-coding regions of the genome and provide limited information about the genetic mechanisms of osteoporosis. Herein we performed a comprehensive functional analysis to investigate the genetic and epigenetic mechanisms of osteoporosis and BMD. BMD and osteoporosis are found to share many common susceptibility loci, and the corresponding susceptibility genes are significantly enriched in bone-related biological pathways. The regulatory element enrichment analysis indicated that BMD and osteoporosis susceptibility loci are significantly enriched in 5'UTR and DNase I hypersensitive sites (DHSs) of peripheral blood immune cells. By integrating GWAS and expression Quantitative Trait Locus (eQTL) data, we found that 15 protein-coding genes are regulated by the osteoporosis and BMD susceptibility loci. Our analysis provides new clues for a better understanding of the pathogenic mechanisms and offers potential therapeutic targets for osteoporosis., (Copyright © 2020 Dong, Zhou, Wang, Zuo, Ying, Chai, Fei, Jin, Chen, Ma and Liu.)

CRISPR-mediated genome editing is a revolutionary technology for genome manipulation that uses the CRISPR-Cas systems and base editors. Currently, poor efficiency and off-target problems have impeded the application of CRISPR systems. The on-target efficiency has been improved in several advanced versions of CRISPR systems, whereas the off-target detection still remains a key challenge. Here, we outline the different versions of CRISPR systems and off-target detection strategies, discuss the merits and limitations of off-target detection methods, and provide potential implications for further gene editing research., (Copyright © 2019 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.)

The moss Physcomitrella patens is tolerant of highly saline environments. In plants, salinity stress may induce the production of toxic reactive carbonyl species (RCS) and oxidative damage. Aldo-keto reductases (AKRs) are a large group of NADP-dependent oxidoreductases involved in RCS detoxification. However, many members in this superfamily remain uncharacterized. In this study, we cloned and characterised a putative AKR1 from P. patens , named PpAKR1A. Notably, the transcription level of PpAKR1A was induced by salt and methylglyoxal (MG) stress, and the recombinant PpAKR1A protein catalysed the reduction of toxic aldehydes. PpAKR1A knockout mutants of P. patens ( ppakr1a ) were sensitive to NaCl and MG treatment, as indicated by much lower concentrations of chlorophyll and much higher concentrations of MG and H 2 O 2 than those in WT plants. Meanwhile, ppakr1a plants exhibited decreases in the MG-reducing activity and reactive oxygen species-scavenging ability in response to salt stress, possibly due to decreases in the activities of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD). Our results indicate that PpAKR1A is an aldo-keto reductase that detoxifies MG and thus plays an important role in salt stress tolerance in P. patens .