SARS-Coronavirus-2 nucleocapsid protein measured in blood using a Simoa ultra-sensitive immunoassay differentiates COVID-19 infection with high clinical sensitivity. [preprint]

The COVID-19 pandemic continues to have an unprecedented impact on societies and economies worldwide. Despite rapid advances in diagnostic test development and scale-up, there remains an ongoing need for SARS-CoV-2 tests which are highly sensitive, specific, minimally invasive, cost-effective and scalable for broad testing and surveillance. Here we report development of a highly sensitive single molecule array (Simoa) immunoassay on the automated HD-X platform for the detection of SARS-CoV-2 Nucleocapsid protein (N-protein) in venous and capillary blood (fingerstick). In pre-pandemic and clinical sample sets, the assay has 100% specificity and 97.4% sensitivity for serum / plasma samples. The limit of detection (LoD) estimated by titration of inactivated SARS-CoV-2 virus is 0.2 pg/ml, corresponding to 0.05 Median Tissue Culture Infectious Dose (TCID50) per ml, \u3e 2000 times more sensitive than current EUA approved antigen tests. No cross-reactivity to other common respiratory viruses, including hCoV229E, hCoVOC43, hCoVNL63, Influenza A or Influenza B, was observed. We detected elevated N-protein concentrations in symptomatic, asymptomatic, and pre-symptomatic PCR+ individuals using capillary blood from a finger-stick collection device. The Simoa SARS-CoV-2 N-protein assay has the potential to detect COVID-19 infection via antigen in blood with similar or better performance characteristics of molecular tests, while also enabling at home and point of care sample collection

ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation

Most recent scribble-supervised segmentation methods commonly adopt a CNN framework with an encoder-decoder architecture. Despite its multiple benefits, this framework generally can only capture small-range feature dependency for the convolutional layer with the local receptive field, which makes it difficult to learn global shape information from the limited information provided by scribble annotations. To address this issue, this paper proposes a new CNN-Transformer hybrid solution for scribble-supervised medical image segmentation called ScribFormer. The proposed ScribFormer model has a triple-branch structure, i.e., the hybrid of a CNN branch, a Transformer branch, and an attention-guided class activation map (ACAM) branch. Specifically, the CNN branch collaborates with the Transformer branch to fuse the local features learned from CNN with the global representations obtained from Transformer, which can effectively overcome limitations of existing scribble-supervised segmentation methods. Furthermore, the ACAM branch assists in unifying the shallow convolution features and the deep convolution features to improve model’s performance further. Extensive experiments on two public datasets and one private dataset show that our ScribFormer has superior performance over the state-of-the-art scribble-supervised segmentation methods, and achieves even better results than the fully-supervised segmentation methods. The code is released at https://github.com/HUANGLIZI/ScribFormer

New insights into fibrotic signaling in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) mostly occurs in the background of liver fibrosis, and activated hepatic stellate cells (HSCs) exist in HCC tissues and adjacent tissues. HSC activation is involved throughout the development of HCC precancerous lesions, which has gradually attracted the attention of related researchers. In addition, HCC can promote the activation of HSCs, which in turn accelerates the occurrence and development of HCC by promoting tumor angiogenesis. In this review, we reviewed 264 studies from PubMed and ScienceDirect to summarize and analyze current significant fibrotic signaling in HCC. As a result, we found 10 fibrotic signaling pathways that are closely related to the activation, proliferation, invasion, migration, and promotion of apoptosis of HCC cells. In addition, we found that crosstalk between various fibrotic signaling pathways of HCC, hypoxia-induced energy metabolic reprogramming of HCC cells, matrix stiffness and stemness of HCC cells, and ferroptosis of HCC cells and HSCs are the latest research hotspots. Furthermore, related drugs that have been found to target these 10 fibrotic signaling pathways of HCC are listed. Our study provides a new reference for developing anti-HCC drugs

HCV genotype 6 prevalence, spontaneous clearance and diversity amongst elderly members of the Li ethnic minority in Baisha County, China

The epidemiology of hepatitis C virus varies widely across geographical regions and ethnic groups. Our previous study showed that 6 strains isolated from Baisha County, Hainan Island, China, were all new genotype 6 (gt6) subtypes which differed significantly from subtypes of other regions. In the current study, we conducted a comprehensive epidemiological survey of HCV in the Li ethnic group, native to Baisha County. Anti‐HCV antibodies were detected by 2 independent ELISAs in all participants, and positive results confirmed by the recombinant immunoblot assay (RIBA) and HCV RNA viral loads were measured. Univariate chi‐square test and multivariable logistic regression analyses were used to determine the risk factors for HCV infection and spontaneous clearance rates. Indeterminate RIBA results were excluded or included in analyses; consequently, findings were expressed as a range. Direct sequencing of partial regions within NS5B and E1 was employed for genotyping. Among 1682 participants, 117 to 153 were anti‐HCV positive (7.0%‐9.1%), with 42.7%‐52.6% confirmed to have cleared infection. Anti‐HCV positivity was associated with older age (≥60 years) (OR = 0.02, 95% CI 0.01‐0.05, P < 0.01) and surgery (OR = 2.75, 95% CI 1.36‐5.57, P < 0.01), with no significant difference found between the HCV infection group and the HCV spontaneous clearance group. The gt6 subtype distribution characteristics of Baisha County were unique, complex and diverse. The sequences did not cluster with known gt6 subtypes but formed 4 Baisha community‐specific groups. HCV infection in members of the Li minority ethnic group is characterized by high prevalence rates in the elderly, high spontaneous clearance rates and broad gt6 diversity

Leveraging opportunity of low carbon transition by super-emitter cities in China

Funding Information: The work was supported by the National Natural Science Foundation of China (7224100119), the National Key Research and Development Program of China (2022YFE0208700 and 2022YFE0208500), and the Norwegian Research Council (287690/F20). We appreciate the suggestions from Prof. Edgar Hertwich of Norweign University of Science andTechnology. Publisher Copyright: © 2023 Science China PressChinese cities are core in the national carbon mitigation and largely affect global decarbonisation initiatives, yet disparities between cities challenge country-wide progress. Low-carbon transition should preferably lead to a convergence of both equity and mitigation targets among cities. Inter-city supply chains that link the production and consumption of cities are a factor in shaping inequality and mitigation but less considered aggregately. Here, we modelled supply chains of 309 Chinese cities for 2012 to quantify carbon footprint inequality, as well as explored a leverage opportunity to achieve an inclusive low-carbon transition. We revealed significant carbon inequalities: the 10 richest cities in China have per capita carbon footprints comparable to the US level, while half of the Chinese cities sit below the global average. Inter-city supply chains in China, which are associated with 80% of carbon emissions, imply substantial carbon leakage risks and also contribute to socioeconomic disparities. However, the significant carbon inequality implies a leveraging opportunity that substantial mitigation can be achieved by 32 super-emitting cities. If the super-emitting cities adopt their differentiated mitigation pathway based on affluence, industrial structure, and role of supply chains, up to 1.4 Gt carbon quota can be created, raising 30% of the projected carbon quota to carbon peak. The additional carbon quota allows the average living standard of the other 60% of Chinese people to reach an upper-middle-income level, highlighting collaborative mechanism at the city level has a great potential to lead to a convergence of both equity and mitigation targets.Peer reviewe

Leveraging opportunity of low carbon transition by super-emitter cities in China

Chinese cities are core in the national carbon mitigation and largely affect global decarbonisation initiatives, yet disparities between cities challenge country-wide progress. Low-carbon transition should preferably lead to a convergence of both equity and mitigation targets among cities. Inter-city supply chains that link the production and consumption of cities are a factor in shaping inequality and mitigation but less considered aggregately. Here, we modelled supply chains of 309 Chinese cities for 2012 to quantify carbon footprint inequality, as well as explored a leverage opportunity to achieve an inclusive low-carbon transition. We revealed significant carbon inequalities: the 10 richest cities in China have per capita carbon footprints comparable to the US level, while half of the Chinese cities sit below the global average. Inter-city supply chains in China, which are associated with 80% of carbon emissions, imply substantial carbon leakage risks and also contribute to socioeconomic disparities. However, the significant carbon inequality implies a leveraging opportunity that substantial mitigation can be achieved by 32 super-emitting cities. If the super-emitting cities adopt their differentiated mitigation pathway based on affluence, industrial structure, and role of supply chains, up to 1.4 Gt carbon quota can be created, raising 30% of the projected carbon quota to carbon peak. The additional carbon quota allows the average living standard of the other 60% of Chinese people to reach an upper-middle-income level, highlighting collaborative mechanism at the city level has a great potential to lead to a convergence of both equity and mitigation targets

Children neuropsychological and behavioral scale-revision 2016 in the early detection of autism spectrum disorder

BackgroundThe Children Neuropsychological and Behavioral Scale-Revision 2016 (CNBS-R2016) is a widely used developmental assessment tool for children aged 0–6 years in China. The communication warning behavior subscale of CNBS-R2016 is used to assess the symptoms of autism spectrum disorder (ASD), and its value of >30 points indicates ASD based on CNBS-R2016. However, we observed that children with relatively lower values were also diagnosed with ASD later on in clinical practice. Thus, this study aimed to identify the suitable cutoff value for ASD screening recommended by the communication warning behavior of CNBS-R2016.Materials and methodsA total of 90 typically developing (TD) children and 316 children with developmental disorders such as ASD, developmental language disorder (DLD), and global developmental delay (GDD; 130 in the ASD group, 100 in the DLD group, and 86 in the GDD group) were enrolled in this study. All subjects were evaluated based on the CNBS-R2016. The newly recommended cutoff value of communication warning behavior for screening ASD was analyzed with receiver operating curves.ResultsChildren in the ASD group presented with lower developmental levels than TD, DLD, and GDD groups in overall developmental quotient assessed by CNBS-R2016. We compared the consistency between the scores of communication warning behavior subscale and Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), Autism Diagnostic Observation Schedule, second edition (ADOS-2), and clinical diagnosis for the classification of ASD at a value of 30 based on the previously and newly recommended cutoff value of 12 by the CNBS-R2016. The Kappa values between the communication warning behavior and ABC, CARS, ADOS-2, and clinical diagnosis were 0.494, 0.476, 0.137, and 0.529, respectively, with an agreement rate of 76.90%, 76.26%, 52.03%, and 82.27%, respectively, when the cutoff point was 30. The corresponding Kappa values were 0.891, 0.816, 0.613, and 0.844, respectively, and the corresponding agreement rate was 94.62%, 90.82%, 90.54%, and 93.10%, respectively, when the cutoff point was 12.ConclusionThe communication warning behavior subscale of CNBS-R2016 is important for screening ASD. When the communication warning behavior score is 12 points or greater, considerable attention and further comprehensive diagnostic evaluation for ASD are required to achieve the early detection and diagnosis of ASD in children