Rethinking the country-level percentage of population residing in urban area with a global harmonized urban definition.

The UN (United Nations) collects global data on the country-level Percentage of Population Residing in Urban Area (PPRUA). However, variations in urban definitions make these data incomparable across countries. This study assesses national defined PPRUA within UN statistics against estimates we derived using global comparable definitions. Refer to the UN's Degree of Urbanization framework, we propose 90 global harmonized methods for estimating PPRUA by combining different configurations of three global population datasets, six urban total population thresholds, and five urban population density thresholds. This approach demonstrated significant variations in country-level PPRUA estimations, with wide 95% confidence intervals using the Z score method. Most national defined PPRUA fall between the upper 95% CI and the median of the estimations, underscoring the need for globally harmonious PPRUA estimates. This study advocates for a reassessment of datasets and thresholds in the future and for investigating urbanization on a scale beyond the country level.

High-accuracy gastric cancer cell viability evaluation based on multi-impedance spectrum characteristics.

The increasing attention to precision medicine is widely paid to greatly rise the cure rate of cancer. Improving the stability and accuracy of cancer cell viability evaluation is one of the keys for precision medicine, as excess dosage of anti-cancer drugs not only kills the cancer cells, but also does harm to normal cells. Electrochemical impedance sensing (EIS) method is well known as a label-free, non-invasive approach for real-time, online monitoring of cell viability. However, the existing EIS methods using single-frequency impedances cannot reflect the comprehensive information of cellular impedance spectroscopy (CIS), ultimately leading to a poor stability and low accuracy of cancer cell viability evaluation. In this paper, we proposed a multi-frequency approach for improving the stability and accuracy of cancer cell viability evaluation based on multi-physical properties of CIS, including cell adhesion state and cell membrane capacitance. The results show that the mean relative error of multi-frequency method is reduced by 50% compared with single-frequency method, while the maximum relative error of the former is 7∼fold smaller than that of the latter. The accuracy of cancer cell viability evaluation is up to 99.6%.

Study on Microfluidic Chip Flow Rate Uniformity for Cell Activity Detection.

During the cell viability detection process inside a microfluidic chip, the more uniform the distribution of medium flow rates, the higher the accuracy of detection results. In order to achieve this goal, a multichannel microfluidic chip with uniform distribution of medium flow rates has been successfully designed. The multichannel microfluidic chip is designed with cell injection channels, vascular network-shaped medium injection channels, buffer zones, and a culture chamber. The medium flow rates inside culture chambers of the multichannel microfluidic chip and the common single-channel microfluidic chip are compared by COMSOL Multiphysics software and particle velocimetry experiment. The simulation and experimental results show that the medium flow rate distribution inside the culture chamber of the multichannel microfluidic chip is more uniform and changes more smoothly. When the medium perfusion flow rate is 0.5 µL/min, the maximum flow rate difference inside the culture chamber of the single-channel microfluidic chip is more than 13 times that of the multichannel microfluidic chip. Therefore, the multichannel microfluidic chip can ensure a uniform supply of medium inside the culture chamber, which is beneficial to improve the accuracy of cell viability detection.

Modular Assembly of MXene Frameworks for Noninvasive Disease Diagnosis via Urinary Volatiles.

Volatile organic compounds (VOCs) in urine are valuable biomarkers for noninvasive disease diagnosis. Herein, a facile coordination-driven modular assembly strategy is used for developing a library of gas-sensing materials based on porous MXene frameworks (MFs). Taking advantage of modules with diverse composition and tunable structure, our MFs-based library can provide more choices to satisfy gas-sensing demands. Meanwhile, the laser-induced graphene interdigital electrodes array and microchamber are laser-engraved for the assembly of a microchamber-hosted MF (MHMF) e-nose. Our MHMF e-nose possesses high-discriminative pattern recognition for simultaneous sensing and distinguishing of complex VOCs. Furthermore, with the MHMF e-nose being a plug-and-play module, a point-of-care testing (POCT) platform is modularly assembled for wireless and real-time monitoring of urinary volatiles from clinical samples. By virtue of machine learning, our POCT platform achieves noninvasive diagnosis of multiple diseases with a high accuracy of 91.7%, providing a favorable opportunity for early disease diagnosis, disease course monitoring, and relevant research.

Urban spatial risk prediction and optimization analysis of POI based on deep learning from the perspective of an epidemic.

From an epidemiological perspective, previous research on COVID-19 has generally been based on classical statistical analyses. As a result, spatial information is often not used effectively. This paper uses image-based neural networks to explore the relationship between urban spatial risk and the distribution of infected populations, and the design of urban facilities. To achieve this objective, we use spatio-temporal data of people infected with new coronary pneumonia prior to 28 February 2020 in Wuhan. We then use kriging, which is a method of spatial interpolation, as well as core density estimation technology to establish the epidemic heat distribution on fine grid units. We further evaluate the influence of nine major spatial risk factors, including the distribution of agencies, hospitals, park squares, sports fields, banks and hotels, by testing them for significant positive correlation with the distribution of the epidemic. The weights of these spatial risk factors are used for training Generative Adversarial Network (GAN) models, which predict the distribution of cases in a given area. The input image for the machine learning model is a city plan converted by public infrastructures, and the output image is a map of urban spatial risk factors in the given area. The results of the trained model demonstrate that optimising the relevant point of interests (POI) in urban areas to effectively control potential risk factors can aid in managing the epidemic and preventing it from dispersing further.

The structure-based design of peptidomimetic inhibitors against SARS-CoV-2 3C like protease as Potent anti-viral drug candidate.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), as the pathogen of coronavirus disease 2019 (COVID-19), has infected millions of people and took hundreds of thousands of lives. Unfortunately, there is deficiency of effective medicines to prevent or treat COVID-19. 3C like protease (3CLPro) of SARS-CoV-2 is essential to the viral replication and transcription, and is an attractive target to develop anti-SARS-CoV-2 agents. Targeting on the 3CLPro, we screened our protease inhibitor library and obtained compound 10a as hit to weakly inhibit the SARS-CoV-2 3CLPro, and determined the co-crystal structure of 10a and the protease. Based on the deep understanding on the protein-ligand complexes between the hit and SARS-CoV-2 3CLPro, we designed a series of peptidomimetic inhibitors, with outstanding inhibitory activity against SARS-CoV-2 3CLPro and excellent anti-viral potency against SARS-CoV-2. The protein-ligand complexes of the other key inhibitors with SARS-CoV-2 3CLPro were explicitly described by the X-ray co-crystal study. All such results suggest these peptidomimetic inhibitors could be further applied as encouraging drug candidates.

Diagnostic and prognostic value of serum Chitinase 3-like protein 1 in hepatocellular carcinoma.

The serum Chitinase 3-like protein 1 (CHI3L1) protein level can distinguish the stages of liver fibrosis to a great extent. However, the diagnostic and prognostic significance of serum CHI3L1 in hepatocellular carcinoma (HCC) is not clarified. To evaluate the diagnostic and prognostic value of CHI3L1 in HCC, a total of 128 HCC patients treated in the HwaMei Hospital, University of Chinese Academy of Sciences, from December 2018 to April 2020 were collected retrospectively. Matched age and gender subjects, 40 patients with liver cirrhosis, 40 patients with chronic hepatitis, and 40 healthy subjects were enrolled in the control group. The relevant clinical laboratory and examination data and the overall survival time (OS) of the HCC patients were collected. The serum CHI3L1 expression level is related to α-fetoprotein (AFP), tumor-node-metastasis (TNM) stage, maximum tumor diameter, liver cirrhosis, and HCC patient's OS (p < 0.05). The area under the curve (AUC) of CHI3L1 was 0.7875 with the cutoff value of 91.36 ng/ml. Combining the serum CHI3L1 and α-fetoprotein (AFP) by a binary logistic regression model can increase the diagnostic sensitivity to 97.5%. Multivariate Cox regression analysis indicated that CHI3L1 is an independent prognostic factor in patients with HCC.

Suppression and Activation of Intracellular Immune Response in Initial Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the most important emerging pathogen worldwide, but its early transcriptional dynamics and host immune response remain unclear. Herein, the expression profiles of viral interactions with different types of hosts were comprehensively dissected to shed light on the early infection strategy of SARS-CoV-2 and the host immune response against infection. SARS-CoV-2 was found to exhibit a two-stage transcriptional strategy within the first 24 h of infection, comprising a lag phase that ends with the virus being paused and a log phase that starts when the viral load increases rapidly. Interestingly, the host innate immune response was found not to be activated (latent period) until the virus entered the log stage. Noteworthy, when intracellular immunity is suppressed, SARS-CoV-2 shows a correlation with dysregulation of metal ion homeostasis. Herein, the inhibitory activity of copper ions against SARS-CoV-2 was further validated in in vitro experiments. Coronavirus disease 2019-related genes (including CD38, PTX3, and TCN1) were also identified, which may serve as candidate host-restricted factors for interventional therapy. Collectively, these results confirm that the two-stage strategy of SARS-CoV-2 effectively aids its survival in early infection by regulating the host intracellular immunity, highlighting the key role of interferon in viral infection and potential therapeutic candidates for further investigations on antiviral strategies.

Chemiluminescence Immunoassay Based Serological Immunoassays for Detection of SARS-CoV-2 Neutralizing Antibodies in COVID-19 Convalescent Patients and Vaccinated Population.

The development of rapid serological detection methods re urgently needed for determination of neutralizing antibodies in sera. In this study, four rapid methods (ACE2-RBD inhibition assay, S1-IgG detection, RBD-IgG detection, and N-IgG detection) were established and evaluated based on chemiluminescence technology. For the first time, a broadly neutralizing antibody with high affinity was used as a standard for the quantitative detection of SARS-CoV-2 specific neutralizing antibodies in human sera. Sera from COVID-19 convalescent patients (N = 119), vaccinated donors (N = 86), and healthy donors (N = 299) confirmed by microneutralization test (MNT) were used to evaluate the above methods. The result showed that the ACE2-RBD inhibition assay calculated with either ACE2-RBD binding inhibition percentage rate or ACE2-RBD inhibiting antibody concentration were strongly correlated with MNT (r ≥ 0.78, p < 0.0001) and also highly consistent with MNT (Kappa Value ≥ 0.94, p < 0.01). There was also a strong correlation between the two evaluation indices (r ≥ 0.99, p < 0.0001). Meanwhile, S1-IgG and RBD-IgG quantitative detection were also significantly correlated with MNT (r ≥ 0.73, p < 0.0001), and both methods were highly correlated with each other (r ≥ 0.95, p < 0.0001). However, the concentration of N-IgG antibodies showed a lower correlation with the MNT results (r < 0.49, p < 0.0001). The diagnostic assays presented here could be used for the evaluation of SARS-CoV-2 vaccine immunization effect and serological diagnosis of COVID-19 patients, and could also have guiding significance for establishing other rapid serological methods to surrogate neutralization tests for SARS-CoV-2.

Methyltransferase-like 3 Modulates Severe Acute Respiratory Syndrome Coronavirus-2 RNA N6-Methyladenosine Modification and Replication.

The coronavirus disease 2019 pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is an ongoing global public crisis. Although viral RNA modification has been reported based on the transcriptome architecture, the types and functions of RNA modification are still unknown. In this study, we evaluated the roles of RNA N6-methyladenosine (m6A) modification in SARS-CoV-2. Our methylated RNA immunoprecipitation sequencing (MeRIP-Seq) and Nanopore direct RNA sequencing (DRS) analysis showed that SARS-CoV-2 RNA contained m6A modification. Moreover, SARS-CoV-2 infection not only increased the expression of methyltransferase-like 3 (METTL3) but also altered its distribution. Modification of METTL3 expression by short hairpin RNA or plasmid transfection for knockdown or overexpression, respectively, affected viral replication. Furthermore, the viral key protein RdRp interacted with METTL3, and METTL3 was distributed in both the nucleus and cytoplasm in the presence of RdRp. RdRp appeared to modulate the sumoylation and ubiquitination of METTL3 via an unknown mechanism. Taken together, our findings demonstrated that the host m6A modification complex interacted with viral proteins to modulate SARS-CoV-2 replication. IMPORTANCE Internal chemical modifications of viral RNA play key roles in the regulation of viral replication and gene expression. Although potential internal modifications have been reported in SARS-CoV-2 RNA, the function of the SARS-CoV-2 N6-methyladenosine (m6A) modification in the viral life cycle is unclear. In the current study, we demonstrated that SARS-CoV-2 RNA underwent m6A modification by host m6A machinery. SARS-CoV-2 infection altered the expression pattern of methyltransferases and demethylases, while the expression level of methyltransferase-like 3 (METTL3) and fat mass and obesity-associated protein (FTO) was linked to the viral replication. Further study showed that METTL3 interacted with viral RNA polymerase RNA-dependent RNA polymerase (RdRp), which influenced not only the distribution but also the posttranslational modification of METTL3. Our study provided evidence that host m6A components interacted with viral proteins to modulate viral replication.

A human antibody of potent efficacy against SARS-CoV-2 in rhesus macaques showed strong blocking activity to B.1.351.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease-2019 (COVID-19), interacts with the host cell receptor angiotensin-converting enzyme 2 (hACE2) via its spike 1 protein during infection. After the virus sequence was published, we identified two potent antibodies against the SARS-CoV-2 receptor binding domain (RBD) from antibody libraries using a phage-to-yeast (PtY) display platform in only 10 days. Our lead antibody JMB2002, now in a Phase 1 clinical trial (ChiCTR2100042150), showed broad-spectrum in vitro blocking activity against hACE2 binding to the RBD of multiple SARS-CoV-2 variants, including B.1.351 that was reportedly much more resistant to neutralization by convalescent plasma, vaccine sera and some clinical-stage neutralizing antibodies. Furthermore, JMB2002 has demonstrated complete prophylactic and potent therapeutic efficacy in a rhesus macaque disease model. Prophylactic and therapeutic countermeasure intervention of SARS-CoV-2 using JMB2002 would likely slow down the transmission of currently emerged SARS-CoV-2 variants and result in more efficient control of the COVID-19 pandemic.

How to Choose a Proper Theoretical Analysis Model Based on Cell Adhesion and Nonadhesion Impedance Measurement.

The accurate equivalent circuit model contributes to the better fitting of required cell characteristics, such as cell impedance, cell adhesion area, and cell-electrode distance. However, so many theoretical models on specific modules make it difficult for new researchers to understand the whole model of electrode system physically. Besides, the accurate theoretical model and the simplified calculations obviously contradict each other; therefore, it is confusing for many researchers to choose the proper theoretical model to calculate the specific parameters required. In this review, we first discuss the problems and suggestions of electrode system design for cell adhesion-based measurement in terms of parasitic capacitance, detection range of cell number, electric field distribution, and interelectrode distance. The design of electrode system for cell nonadhesion measurement was analyzed in terms of microchannel size and electrode position. Then, we discuss the advantages and disadvantages of various equivalent circuit models according to different requirements of researchers, and simultaneously provide a corresponding theoretical model for researchers. Various factors influencing electric impedance spectroscopy (EIS) such as the parasitic capacitance between microelectrodes, the changes of cell adhesion area and cell-electrode distance, the electrode geometry, and the surface conductivity of electrode were quantitatively analyzed to contribute to better understanding of the equivalent models. Finally, we gave advice to optimize the theoretical models further and perspectives on building uniform principles of theoretical model optimization in the future.

Evaluating cell viability heterogeneity based on information fusion of multiple adhesion strengths.

Cell viability evaluation is significantly meaningful for cellular assays. Some cells with weak viability are easily killed in the detection of anticancer drugs, while others with strong viability survive and proliferate, ultimately leading to the treatment failure or the inaccuracy of biological assays. Accurately evaluating cell viability heterogeneity still remains difficult. This article proposed a multiphysical property information fusion method for evaluating cell viability heterogeneity based on polynomial regression in a single-channel integrated microfluidic chip. In this method, adhesion strengths τN , that are defined as the magnitude of shear stress needed to detach (100 - N) % of cell population, were extracted as the independent variables of polynomial regression model by calculating the nonlinear fitting of the impedance-response curves for shear stress (cell detachment assay). Besides, by calculating the nonlinear fitting of the drug dose-response curves for cancer cells (IC50 assay), the half-maximal inhibitory concentration (IC50 ) was extracted as the dependent variables of polynomial regression model. The results show that the mean relative error of our fusion method averagely reduces by 6.04% and 62.79% compared with the multiple linear regression method and the cell counting method. Moreover, a simplified theoretical model used to describe the quantitative relationship between cell viability and its adhesion strengths was built to provide a theoretical basis for our fusion method.

Host metabolism dysregulation and cell tropism identification in human airway and alveolar organoids upon SARS-CoV-2 infection.

The coronavirus disease 2019 (COVID-19) pandemic is caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is spread primary via respiratory droplets and infects the lungs. Currently widely used cell lines and animals are unable to accurately mimic human physiological conditions because of the abnormal status of cell lines (transformed or cancer cells) and species differences between animals and humans. Organoids are stem cell-derived self-organized three-dimensional culture in vitro and model the physiological conditions of natural organs. Here we showed that SARS-CoV-2 infected and extensively replicated in human embryonic stem cells (hESCs)-derived lung organoids, including airway and alveolar organoids which covered the complete infection and spread route for SARS-CoV-2 within lungs. The infected cells were ciliated, club, and alveolar type 2 (AT2) cells, which were sequentially located from the proximal to the distal airway and terminal alveoli, respectively. Additionally, RNA-seq revealed early cell response to virus infection including an unexpected downregulation of the metabolic processes, especially lipid metabolism, in addition to the well-known upregulation of immune response. Further, Remdesivir and a human neutralizing antibody potently inhibited SARS-CoV-2 replication in lung organoids. Therefore, human lung organoids can serve as a pathophysiological model to investigate the underlying mechanism of SARS-CoV-2 infection and to discover and test therapeutic drugs for COVID-19.

A novel method of cell culture based on the microfluidic chip for regulation of cell density.

The regulation of cell density is an important segment in microfluidic cell culture, particularly in the repeated assays. Traditionally, consistent cell density is difficult to achieve, owing to the inaccurate regulation of cell density with manual feedback. A novel cell culture method with automatic feedback is proposed for real-time regulation of cell density based on microfluidic chip in this paper. Here, an integrated microfluidic system combining cell culture, density detection, and control of proliferation rate was developed. Interdigital electrode structures were sputtered on the microchannel automatically to provide the real-time feedback information of impedance. The most sensitive frequency was studied to improve the detection resolution of the sensing chip. Cells were cultured on the chip surface and cell density was detected by monitoring the alternation of the impedance. The feedback controller was established by the least squares support vector machines. Then, the cell proliferation rate was automatically controlled using the feedback controller to achieve the desired cell density in the repeated assays. The results show that the standard error of this method is 2.8% indicating that the method can keep a consistency of cell density in the repeated assays. This study provides a basis for improving the accuracy and repeatability in the further assays of finding the optimal drug concentration.

Identification of SARS-CoV-2 entry inhibitors among already approved drugs.

To discover effective drugs for COVID-19 treatment amongst already clinically approved drugs, we developed a high throughput screening assay for SARS-CoV-2 virus entry inhibitors using SARS2-S pseudotyped virus. An approved drug library of 1800 small molecular drugs was screened for SARS2 entry inhibitors and 15 active drugs were identified as specific SARS2-S pseudovirus entry inhibitors. Antiviral tests using native SARS-CoV-2 virus in Vero E6 cells confirmed that 7 of these drugs (clemastine, amiodarone, trimeprazine, bosutinib, toremifene, flupenthixol, and azelastine) significantly inhibited SARS2 replication, reducing supernatant viral RNA load with a promising level of activity. Three of the drugs were classified as histamine receptor antagonists with clemastine showing the strongest anti-SARS2 activity (EC50 = 0.95 ± 0.83 µM). Our work suggests that these 7 drugs could enter into further in vivo studies and clinical investigations for COVID-19 treatment.

Determination of a novel parvovirus pathogen associated with massive mortality in adult tilapia.

Tilapia is one of the most important economic and fastest-growing species in aquaculture worldwide. In 2015, an epidemic associated with severe mortality occurred in adult tilapia in Hubei, China. The causative pathogen was identified as Tilapia parvovirus (TiPV) by virus isolation, electron microscopy, experimental challenge, In situ hybridization (ISH), indirect immunofluorescence (IFA), and viral gene sequencing. Electron microscopy revealed large numbers of parvovirus particles in the organs of diseased fish, including kidney, spleen, liver, heart, brain, gill, intestine, etc. The virions were spherical in shape, non-enveloped and approximately 30nm in diameter. The TiPV was isolated and propagated in tilapia brain cells (TiB) and induced a typical cytopathic effect (CPE) after 3 days post-infection (dpi). This virus was used to experimentally infect adult tilapia and clinical disease symptoms similar to those observed naturally were replicated. Additionally, the results of ISH and IFA showed positive signals in kidney and spleen tissues from TiPV-infected fish. To identify TiPV-specific sequences, the near complete genome of TiPV was obtained and determined to be 4269 bp in size. Phylogenetic analysis of the NS1 sequence revealed that TiPV is a novel parvovirus, forms a separate branch in proposed genus Chapparvovirus of Parvoviridae. Results presented here confirm that TiPV is a novel parvovirus pathogen that can cause massive mortality in adult tilapia. This provides a basis for the further studies to define the epidemiology, pathology, diagnosis, prevention and treatment of this emerging viral disease.

Lensfree Diffraction Reconstruction Approach Enables Early Detection of Cancer In Vitro Based on Molecular Diagnosis.

Before there are any megascopic cancer clinical symptoms, molecular diagnosis is the main method for detecting cancer-associated gene and tumor marker. The existing detection facilities are all expensive, complicated to operate, and time-consuming, thereby making them difficult to popularize and benefit humans. In this study, we proposed a high-throughput and cost-effective approach, which enables accurate detection of extremely rare cancer cells based on molecular diagnosis of target tumor marker and a lensfree diffraction imaging platform. This approach achieves high-speed and high-quality reconstruction of huge images, which well solves the problem that precise recognition is almost impossible utilizing raw image because of significant pattern magnification and serious overlaps. Furthermore, the cells which are labeled with immune microbeads can be screened using the determined covered pixel sets, which are extracted in different focus reconstruction planes. The recognition strategy is implemented based on set intersection. With this method, the target cancer cells can be rapidly and accurately screened in a large number of benign cell samples. Besides, the detection equipment is cost-effective and easy to operate and popularize. It is expected to be widely used as a diagnostic tool for early detection of cancer.

Evaluation of fish freshness using impedance spectroscopy based on the characteristic parameter of orthogonal direction difference.

BACKGROUND: As a nondestructive testing technology, electrochemical impedance spectroscopy (EIS) has been applied to evaluate food quality because of its features of rapidity, low cost, nondestructiveness and portability. However, fish freshness evaluation based on existing EIS technology is affected by the differences of individual biological samples. In this study, the difference of electrical properties between two orthogonal directions was extracted to develop a new freshness indicator. A real part orthogonal direction difference parameter set (RODDS) was used to establish a prediction model for total volatile basic nitrogen (TVB-N). RESULTS: Compared with the traditional parameter of EIS, coefficient of determination between RODDS and TVB-N increased from 0.55 to 0.71 for the calibration group, and root mean squared error between predicted and measured values of TVB-N decreased from 5.46 to 3.81 for the test group. CONCLUSIONS: The results implied that RODDS could effectively offset individual differences in basic electrical properties and improve the TVB-N prediction accuracy in practical application scenarios with samples from multiple origins. The proposed method may provide a new idea for the development and improvement of EIS-based portable testing devices for fish and meat. © 2020 Society of Chemical Industry.