Crop switching can enhance environmental sustainability and farmer incomes in China.

Achieving food-system sustainability is a multidimensional challenge. In China, a doubling of crop production since 1990 has compromised other dimensions of sustainability1,2. Although the country is promoting various interventions to enhance production efficiency and reduce environmental impacts3, there is little understanding of whether crop switching can achieve more sustainable cropping systems and whether coordinated action is needed to avoid tradeoffs. Here we combine high-resolution data on crop-specific yields, harvested areas, environmental footprints and farmer incomes to first quantify the current state of crop-production sustainability. Under varying levels of inter-ministerial and central coordination, we perform spatial optimizations that redistribute crops to meet a suite of agricultural sustainable development targets. With a siloed approach-in which each government ministry seeks to improve a single sustainability outcome in isolation-crop switching could realize large individual benefits but produce tradeoffs for other dimensions and between regions. In cases of central coordination-in which tradeoffs are prevented-we find marked co-benefits for environmental-impact reductions (blue water (-4.5% to -18.5%), green water (-4.4% to -9.5%), greenhouse gases (GHGs) (-1.7% to -7.7%), fertilizers (-5.2% to -10.9%), pesticides (-4.3% to -10.8%)) and increased farmer incomes (+2.9% to +7.5%). These outcomes of centrally coordinated crop switching can contribute substantially (23-40% across dimensions) towards China's 2030 agricultural sustainable development targets and potentially produce global resource savings. This integrated approach can inform feasible targeted agricultural interventions that achieve sustainability co-benefits across several dimensions.

Progranulin promotes regulatory T cells plasticity by mitochondrial metabolism through AMPK/PGC-1α pathway in ARDS.

As the aging population increases, the focus on elderly patients with acute respiratory distress syndrome (ARDS) is also increasing. In this article, we found progranulin (PGRN) differential expression in ARDS patients and healthy controls, even in young and old ARDS patients. Its expression strongly correlates with several cytokines in both young and elderly ARDS patients. PGRN has comparable therapeutic effects in young and elderly mice with lipopolysaccharide-induced acute lung injury, manifesting as lung injury, apoptosis, inflammation, and regulatory T cells (Tregs) differentiation. Considering that Tregs differentiation relies on metabolic reprogramming, we discovered that Tregs differentiation was mediated by mitochondrial function, especially in the aged population. Furthermore, we demonstrated that PGRN alleviated the mitochondrial damage during Tregs differentiation through the AMPK/PGC-1α pathway in T cells. Collectively, PGRN may regulate mitochondria function to promote Tregs differentiation through the AMPK/PGC-1α pathway to improve ARDS.

Progress in patient-derived liver cancer cell models: a step forward for precision medicine.

The development of effective precision treatments for liver cancers has been hindered by the scarcity of preclinical models that accurately reflect the heterogeneity of this disease. Recent progress in developing patient-derived liver cancer cell lines and organoids has paved the way for precision medicine research. These expandable resources of liver cancer cell models enable a full spectrum of pharmacogenomic analysis for liver cancers. Moreover, patient-derived and short-term cultured two-dimensional tumor cells or three-dimensional organoids can serve as patient avatars, allowing for the prediction of patients' response to drugs and facilitating personalized treatment for liver cancer patients. Furthermore, the current novel techniques have expanded the scope of cancer research, including innovative organoid culture, gene editing and bioengineering. In this review, we provide an overview of the progress in patient-derived liver cancer cell models, focusing on their applications in precision and personalized medicine research. We also discuss the challenges and future perspectives in this field.

Dexmedetomidine alleviates acute lung injury by promoting Tregs differentiation via activation of AMPK/SIRT1 pathway.

OBJECTIVES: To explore the anti-inflammatory effect and the potential mechanism of dexmedetomidine in ARDS/ALI. MATERIALS AND METHODS: C57BL/6 mice and EL-4 cells were used in this research. The ALI model was established by CLP. The level of inflammatory cytokines in the lung and blood, the severity of lung injury, the expression of Foxp3, and the proportion of Tregs were detected before and after dexmedetomidine treatment. The expression of the AMPK/SIRT1 after dexmedetomidine treatment was detected in vivo and in vitro. After blocking the AMPK/SIRT1 pathway or depleting Tregs in vivo, the level of the inflammatory response, tissue injury, and Tregs differentiation were detected again to clarify the effect of dexmedetomidine. RESULTS: Dexmedetomidine significantly reduced systemic inflammation and lung injury in CLP mice. Dexmedetomidine enhanced the Foxp3 expression in the lungs and the frequency of Tregs in the spleen. Dexmedetomidine up-regulated the protein expression of p-AMPK and SIRT1 in lungs and EL-4 cells and facilitated the differentiation of naïve CD4+ T cells into Tregs in vitro. Meanwhile, DEX also increased the expression of Helios in Treg cells. CONCLUSIONS: DEX could improve ARDS/ALI by facilitating the differentiation of Tregs from naïve CD4+ T cells via activating the AMPK/SIRT1 pathway.

RNA helicase DDX5 enables STAT1 mRNA translation and interferon signalling in hepatitis B virus replicating hepatocytes.

OBJECTIVE: RNA helicase DDX5 is downregulated during HBV replication and poor prognosis HBV-related hepatocellular carcinoma (HCC). The objective of this study is to investigate the role of DDX5 in interferon (IFN) signalling. We provide evidence of a novel mechanism involving DDX5 that enables translation of transcription factor STAT1 mediating the IFN response. DESIGN AND RESULTS: Molecular, pharmacological and biophysical assays were used together with cellular models of HBV replication, HCC cell lines and liver tumours. We demonstrate that DDX5 regulates STAT1 mRNA translation by resolving a G-quadruplex (rG4) RNA structure, proximal to the 5' end of STAT1 5'UTR. We employed luciferase reporter assays comparing wild type (WT) versus mutant rG4 sequence, rG4-stabilising compounds, CRISPR/Cas9 editing of the STAT1-rG4 sequence and circular dichroism determination of the rG4 structure. STAT1-rG4 edited cell lines were resistant to the effect of rG4-stabilising compounds in response to IFN-α, while HCC cell lines expressing low DDX5 exhibited reduced IFN response. Ribonucleoprotein and electrophoretic mobility assays demonstrated direct and selective binding of RNA helicase-active DDX5 to the WT STAT1-rG4 sequence. Immunohistochemistry of normal liver and liver tumours demonstrated that absence of DDX5 corresponded to absence of STAT1. Significantly, knockdown of DDX5 in HBV infected HepaRG cells reduced the anti-viral effect of IFN-α. CONCLUSION: RNA helicase DDX5 resolves a G-quadruplex structure in 5'UTR of STAT1 mRNA, enabling STAT1 translation. We propose that DDX5 is a key regulator of the dynamic range of IFN response during innate immunity and adjuvant IFN-α therapy.

Chinese nurses' innovation capacity: The influence of inclusive leadership, empowering leadership and psychological empowerment.

AIM: To explore the relationships between inclusive leadership, empowering leadership, nurses' perceived psychological empowerment and nurses' innovation capacity. BACKGROUND: Innovation capacity is essential for nurses to adapt to the changing health care environment. However, the current knowledge of nurses' innovation capacity and its' relationships between inclusive leadership, empowering leadership and psychological empowerment, is limited. METHODS: A cross-sectional survey using a convenience sample was conducted among 1355 nurses in 10 hospitals in Tianjin, China. The data were analysed by correlation analysis, univariate analysis and PROCESS macro. RESULTS: High inclusive leadership, empowering leadership and high psychological empowerment were associated with high innovation capacity. The total effect of inclusive leadership and empowering leadership on innovation capacity through psychological empowerment was significant, with their indirect effects accounting for 69.19% and 61.29% of the total effect, respectively. CONCLUSIONS: To cultivate nurses' innovation capacity, the development of inclusive leadership, empowering leadership and psychological empowerment is important. IMPLICATIONS FOR NURSING MANAGEMENT: This research highlights the importance of inclusive leadership and empowering leadership to foster nurses' innovation capacity. Understanding the mediating role of psychological empowerment is expected to help nurse managers develop relevant intervention strategies to cultivate nurses' innovation capacity.

Dual-recognition-based determination of ctDNA via the clamping function of peptide nucleic acid and terminal protection of small-molecule-linked DNA.

A new dual-recognition fluorescent biosensor for circulating tumor DNA (ctDNA) detection has been developed, which combines the clamping function of peptide nucleic acid (PNA) and terminal protection of small-molecule-linked DNA (TPSMLD). Taking the tumor-specific E542K mutation and methylation of the PIK3CA gene as the target ctDNA, a low detection limit of 0.3161 pM ctDNA is achieved with good selectivity. This study not only offers a sensitive, selective and accurate ctDNA detection method, but can also be used to detect the target in complex biological samples.

How to Integrate Labor Disruption into an Economic Impact Evaluation Model for Postdisaster Recovery Periods.

Evaluating the economic impacts caused by capital destruction is an effective method for disaster management and prevention, but the magnitude of the economic impact of labor disruption on an economic system remains unclear. This article emphasizes the importance of considering labor disruption when evaluating the economic impact of natural disasters. Based on the principle of disasters and resilience theory, our model integrates nonlinear recovery of labor losses and the demand of labor from outside the disaster area into the dynamic evaluation of the economic impact in the postdisaster recovery period. We exemplify this through a case study: the flood disaster that occurred in Wuhan city, China, on July 6, 2016 (the "7.6 Wuhan flood disaster"). The results indicate that (i) the indirect economic impacts of the "7.6 Wuhan flood disaster" will underestimate 15.12% if we do not consider labor disruption; (ii) the economic impact in secondary industry caused by insufficient labor forces accounts for 42.27% of its total impact, while that in the tertiary industry is 36.29%, which can cause enormous losses if both industries suffer shocks; and (iii) the agricultural sector of Wuhan city experiences an increase in output demand of 0.07% that is created by the introduction of 50,000 short-term laborers from outside the disaster area to meet the postdisaster reconstruction need. These results provide evidence for the important role of labor disruption and prove that it is a nonnegligible component of postdisaster economic recovery and postdisaster reduction.

Radiomics models to predict bone marrow metastasis of neuroblastoma using CT.

Background: Bone marrow is the leading site for metastasis from neuroblastoma and affects the prognosis of patients with neuroblastoma. However, the accurate diagnosis of bone marrow metastasis is limited by the high spatial and temporal heterogeneity of neuroblastoma. Radiomics analysis has been applied in various cancers to build accurate diagnostic models but has not yet been applied to bone marrow metastasis of neuroblastoma. Methods: We retrospectively collected information from 187 patients pathologically diagnosed with neuroblastoma and divided them into training and validation sets in a ratio of 7:3. A total of 2632 radiomics features were retrieved from venous and arterial phases of contrast-enhanced computed tomography (CT), and nine machine learning approaches were used to build radiomics models, including multilayer perceptron (MLP), extreme gradient boosting, and random forest. We also constructed radiomics-clinical models that combined radiomics features with clinical predictors such as age, gender, ascites, and lymph gland metastasis. The performance of the models was evaluated with receiver operating characteristics (ROC) curves, calibration curves, and risk decile plots. Results: The MLP radiomics model yielded an area under the ROC curve (AUC) of 0.97 (95% confidence interval [CI]: 0.95-0.99) on the training set and 0.90 (95% CI: 0.82-0.95) on the validation set. The radiomics-clinical model using an MLP yielded an AUC of 0.93 (95% CI: 0.89-0.96) on the training set and 0.91 (95% CI: 0.85-0.97) on the validation set. Conclusions: MLP-based radiomics and radiomics-clinical models can precisely predict bone marrow metastasis in patients with neuroblastoma.

Identifying the risk factors of ICU-acquired fungal infections: clinical evidence from using machine learning.

Background: Fungal infections are associated with high morbidity and mortality in the intensive care unit (ICU), but their diagnosis is difficult. In this study, machine learning was applied to design and define the predictive model of ICU-acquired fungi (ICU-AF) in the early stage of fungal infections using Random Forest. Objectives: This study aimed to provide evidence for the early warning and management of fungal infections. Methods: We analyzed the data of patients with culture-positive fungi during their admission to seven ICUs of the First Affiliated Hospital of Chongqing Medical University from January 1, 2015, to December 31, 2019. Patients whose first culture was positive for fungi longer than 48 h after ICU admission were included in the ICU-AF cohort. A predictive model of ICU-AF was obtained using the Least Absolute Shrinkage and Selection Operator and machine learning, and the relationship between the features within the model and the disease severity and mortality of patients was analyzed. Finally, the relationships between the ICU-AF model, antifungal therapy and empirical antifungal therapy were analyzed. Results: A total of 1,434 cases were included finally. We used lasso dimensionality reduction for all features and selected six features with importance ≥0.05 in the optimal model, namely, times of arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation. The area under the curve of the model for predicting ICU-AF was 0.981 in the test set, with a sensitivity of 0.960 and specificity of 0.990. The times of arterial catheter (p = 0.011, OR = 1.057, 95% CI = 1.053-1.104) and invasive mechanical ventilation (p = 0.007, OR = 1.056, 95%CI = 1.015-1.098) were independent risk factors for antifungal therapy in ICU-AF. The times of arterial catheter (p = 0.004, OR = 1.098, 95%CI = 0.855-0.970) were an independent risk factor for empirical antifungal therapy. Conclusion: The most important risk factors for ICU-AF are the six time-related features of clinical parameters (arterial catheter, enteral nutrition, corticosteroids, broadspectrum antibiotics, urinary catheter, and invasive mechanical ventilation), which provide early warning for the occurrence of fungal infection. Furthermore, this model can help ICU physicians to assess whether empiric antifungal therapy should be administered to ICU patients who are susceptible to fungal infections.

Three-Dimensional PLGA Nanofiber-Based Microchip for High-Efficiency Cancer Cell Capture.

A 3D network capture substrate based on poly(lactic-co-glycolic acid) (PLGA) nanofibers was studied and successfully used for high-efficiency cancer cell capture. The arc-shaped glass micropillars were prepared by chemical wet etching and soft lithography. PLGA nanofibers were coupled with micropillars by electrospinning. Given the size effect of the microcolumn and PLGA nanofibers, a three-dimensional of micro-nanometer spatial network was prepared to form a network cell trapping substrate. After the modification of a specific anti-EpCAM antibody, MCF-7 cancer cells were captured successfully with a capture efficiency of 91%. Compared with the substrate composed of 2D nanofibers or nanoparticles, the developed 3D structure based on microcolumns and nanofibers had a greater contact probability between cells and the capture substrate, leading to a high capture efficiency. Cell capture based on this method can provide technical support for rare cells in peripheral blood detection, such as circulating tumor cells and circulating fetal nucleated red cells.

Machine-learning radiomics to predict bone marrow metastasis of neuroblastoma using magnetic resonance imaging.

Background: Neuroblastoma is one common pediatric malignancy notorious for high temporal and spatial heterogeneities. More than half of its patients develop distant metastases involving vascularized organs, especially the bone marrow. It is thus necessary to have an economical, noninvasive method without much radiation for follow-ups. Radiomics has been used in many cancers to assist accurate diagnosis but not yet in bone marrow metastasis in neuroblastoma. Methods: A total of 182 patients with neuroblastoma were retrospectively collected and randomly divided into the training and validation sets. Five-hundred and seventy-two radiomics features were extracted from magnetic resonance imaging, among which 41 significant ones were selected via T-test for model development. We attempted 13 machine-learning algorithms and eventually chose three best-performed models. The integrative performance evaluations are based on the area under the curves (AUCs), calibration curves, risk deciles plots, and other indexes. Results: Extreme gradient boosting, random forest (RF), and adaptive boosting were the top three to predict bone marrow metastases in neuroblastoma while RF was the most accurate one. Its AUC was 0.90 (0.86-0.93), F1 score was 0.82, sensitivity was 0.76, and negative predictive value was 0.79 in the training set. The values were 0.82 (0.71-0.93), 0.80, 0.75, and 0.92 in the validation set, respectively. Conclusions: Radiomics models are likely to contribute more to metastatic diagnoses and the formulation of personalized healthcare strategies in clinics. It has great potential of being a revolutionary method to replace traditional interventions in the future.

WDR4 gene polymorphisms and Wilms tumor susceptibility in Chinese children: A five-center case-control study.

Wilms tumor is the most common embryonal renal malignancy in children. WDR4 is an indispensable noncatalytic subunit of the RNA N7-methylguanosine (m7G) methyltransferase complex and plays an essential role in tumorigenesis. However, the relationship between polymorphisms in the WDR4 gene and susceptibility to Wilms tumor remains to be fully investigated. We performed a large case-control study involving 414 patients and 1199 cancer-free controls to investigate whether single nucleotide polymorphisms (SNPs) in the WDR4 gene are associated with Wilms tumor susceptibility. WDR4 gene polymorphisms (rs2156315 C > T, rs2156316 C > G, rs6586250 C > T, rs15736 G > A, and rs2248490 C > G) were genotyped using the TaqMan assay. In addition, unconditioned logistic regression analysis was performed, odds ratios (ORs) and 95% confidence intervals (CIs) were used to assess the association between WDR4 gene SNPs and Wilms tumor susceptibility as well as the strength of the associations. We found that only the rs6586250 C>T polymorphism was significantly associated with an increased risk of Wilms tumor (adjusted OR=2.99, 95% CI = 1.28-6.97, P = 0.011 for the rs6586250 TT genotype; adjusted OR=3.08, 95% CI = 1.33-7.17, P = 0.009 for the rs6586250 CC/CT genotype). Furthermore, the stratification analysis revealed that patients with the rs6586250 TT genotype and carriers with 1-5 risk genotypes exhibited statistically significant associations with increased Wilms tumor risk in specific subgroups. However, the rs2156315 CT/TT genotype was identified as having a protective effect against Wilms tumor in the age >18 months subgroup compared with the rs2156315 CC genotype. In brief, our study demonstrated that the rs6586250 C > T polymorphism of the WDR4 gene was significantly associated with Wilms tumor. This finding may contribute to the understanding of the genetic mechanism of Wilms tumor.

Development of a nomogram for predicting grade 2 or higher acute hematologic toxicity of cervical cancer after the pelvic bone marrow sparing radiotherapy.

Background: Acute hematologic toxicity (HT) is a common complication during radiotherapy of cervical cancer which may lead to treatment delay or interruption. Despite the use of intensity-modulated radiation therapy (IMRT) with the pelvic bone marrow (PBM) sparing, some patients still suffer from acute HT. We aimed to identify predictors associated with HT and develop a nomogram for predicting grade 2 or higher (G2+) acute HT in cervical cancer following the PBM sparing strategy. Methods: This study retrospectively analyzed 125 patients with cervical cancer who underwent IMRT with the PBM sparing strategy at our institution. Univariate and multivariate logistic regression, best subset regression, and least absolute shrinkage and selection operator (LASSO) regression, respectively, were used for predictor screening, and Akaike information criterion (AIC) was used to determine the best model for developing the nomogram. Finally, we quantified the risk of G2+ acute HT based on this model to establish a risk stratification. Results: The independent predictors used to develop the nomogram were histological grade, pre-radiotherapy chemotherapy, pre-radiotherapy HT, and radiotherapy [IMRT alone vs. concurrent chemoradiotherapy (CCRT)] which were determined by the univariate and multivariate logistic regression with the minimum AIC of 125.49. Meanwhile, the heat map showed that there is no multicollinearity among the predictors. The nomogram was well-calibrated to reality, with a Brier score of 0.15. The AUC value was 0.82, and the median Brier score and AUC in 1000 five-fold cross-validation were 0.16 and 0.80, respectively. The web version developed together was very easy to use. The risk stratification indicated that high-risk patients (risk point > 195.67) were more likely to develop G2+ acute HT [odds ratio (OR) = 2.17, 95% confidence interval (CI): 1.30-3.05]. Conclusion: This nomogram well-predicted the risk of G2+ acute HT during IMRT in cervical cancer after the PBM sparing strategy, and the constructed risk stratification could assist physicians in screening high-risk patients and provide a useful reference for future prevention and treatment strategies for acute HT.

Asymptomatic uterine metastasis of breast cancer: Case report and literature review.

RATIONALE: Uterine metastasis from breast cancer is extremely rare. Asymptomatic patients with cervical metastases from breast cancer are rarer and more likely to be missed. We present an asymptomatic patient with breast cancer metastasized to the uterus and share opinions on diagnosing and treating for this kind of cases. PATIENT CONCERNS: We present the case of a 64-year-old woman who was diagnosed with both breast cancer and uterine fibroids after examination. She had no symptoms of gynecological disease during breast cancer treatment. A positron emission tomography/computed tomography (PET/CT) scan was performed during reexamination, revealing multiple metastases of the bone throughout the body and an abnormal hypermetabolic mass in the uterus. It was later confirmed as uterine metastasis by pathology. DIAGNOSIS: A diagnosis of metastatic breast invasive lobular carcinoma was established after a uterine curettage. INTERVENTIONS AND OUTCOMES: Treatment of the uterine metastasis included systemic chemotherapy, total abdominal hysterectomy and bilateral salpingo-oophorectomy (TAH and BSO), postoperative radiotherapy, and postoperative chemotherapy. The patient eventually refused further treatment for personal reasons and died at home. LESSONS: Breast cancer metastases to the uterus are very rare and further research is needed for their diagnosis and treatment. During reexamination of breast cancer patients, clinicians must be alert to metastasis to gynecologic organs. This is particularly important in hormone receptor-positive patients with asymptomatic distant metastasis.

Multiscale analysis of factors affecting food security in China, 1980-2017.

Food security is an important issue affecting people's lives and social stability. Clarifying levels of food security and the factors affecting it (social, economic, agricultural, climatic) can help improve regional food security. The spatiotemporal patterns and driving factors of food security vary at different scales. There is, however, a lack of research that considers the various factors affecting food security at multiple scales. This study, therefore, analyzed dynamic spatiotemporal changes in food security at small (city), medium (province), and large (country) scales; identified hot and cold areas of food security; and revealed the main factors affecting food security at different scales. A food security index (FSI) was built based on the coupling of grain yield, population, and GDP, and spatial analysis was used to evaluate dynamic spatiotemporal changes in China's food security from 1980 to 2017. Further, the relationship between food security and its driving factors was quantitatively analyzed using stepwise regression. The results showed greater heterogeneity in food security at the smaller scale than at the larger scale. The key factors affecting food security varied substantially at different scales: the added value of tertiary industry dominated the prefecture level, and gross agricultural output value was the main factor at the provincial and national levels. Multiple-scale research can reveal the status and primary factors of food security and provide a decision-making basis for improving regional food security.

Association between LIN28B gene polymorphisms and Wilms' tumor susceptibility.

Aim: To survey the association between LIN28B gene polymorphisms and the increased risk of Wilms' tumor (WT). Methods: Five LIN28B polymorphisms (rs314276 C>A, rs221634 A>T, rs221635 T>C, the rs4145418 A>C and rs9404590 T>G) were genotyped in 355 WT patients and 1070 healthy controls to assess the association. Result: The rs314276 CA/AA genotype was a protective factor against WT (corrected odds ratio [OR]: 0.71; p = 0.006). Individuals older than 18 months (corrected OR: 0.60; p = 0.001), males (corrected OR: 0.65; p = 0.011) and in clinical stage I + II patients (corrected OR: 0.60; p = 0.0008) with this genotype were less susceptible to WT. Conclusion: The rs314276 CA/AA genotype may protect against WT.

Highly sensitive microRNA detection by a duplex-specific nuclease amplification triggered three-dimensional DNA machine.

MicroRNAs play important roles in disease diagnosis and therapy. However, current methods for microRNA detection suffer from low sensitivity and cannot directly detect short microRNAs. Herein, we have developed a highly sensitive and selective fluorescent method for direct microRNA detection by combining the duplex-specific nuclease-assisted recycling amplification and the nicking enzyme-powered three-dimensional DNA walker. Target microRNA initiates duplex-specific nuclease-assisted recycling amplification, releasing numerous bipedal walking strands. The released bipedal walking strands hybridize with carboxyfluorescein-labeled track DNA and form nicking recognition site. Driven by the hydrolysis of the nicking enzyme, the bipedal walking strand autonomously moves along the track strand, releasing a large number of carboxyfluorescein-labeled DNA fragments and generating obvious fluorescence signals. This dual-signal amplification method can directly detect microRNA 21 as low as 130 fM and has good selectivity. The proposed method is not only simple for nucleic acid design, but also can be used as a universal method for the highly sensitive detection of all RNAs.

A sensitive platform for DNA detection based on organic electrochemical transistor and nucleic acid self-assembly signal amplification.

Highly sensitive detection of DNA is of great importance for the detection of genetic damage and errors for the diagnosis of many diseases. Traditional highly sensitive organic electrochemical transistor (OECT)-based methods mainly rely on good conductivity materials, which may be limited by complex synthesis and modification steps. In this work, DNA biosensor based on OECT and hybridization chain reaction (HCR) signal amplification was demonstrated for the first time. Au nanoparticles were electrochemically deposited on the Au gate electrode to increase the surface area. Then, the HCR products, long negatively charged double-stranded DNA, were connected to the target by hybridization, which can increase the effective gate voltage offset of OECT. This sensor exhibited high sensitivity and even 0.1 pM target DNA could be directly detected with a significant voltage shift. In addition, it could discriminate target DNA from the mismatched DNA with good selectivity. This proposed method based on HCR in DNA detection exhibited an efficient amplification performance on OECT, which provided new opportunities for highly sensitive and selective detection of DNA.