Specific convulsions and brain damage in children hospitalized for Omicron BA.5 infection: an observational study using two cohorts.

BACKGROUND: SARS-CoV-2 continues to mutate over time, and reports on children infected with Omicron BA.5 are limited. We aimed to analyze the specific symptoms of Omicron-infected children and to improve patient care. METHODS: We selected 315 consecutively hospitalized children with Omicron BA.5 and 16,744 non-Omicron-infected febrile children visiting the fever clinic at our hospital between December 8 and 30, 2022. Specific convulsions and body temperatures were compared between the two cohorts. We analyzed potential associations between convulsions and vaccination, and additionally evaluated the brain damage among severe Omicron-infected children. RESULTS: Convulsion rates (97.5% vs. 4.3%, P < 0.001) and frequencies (median: 2.0 vs. 1.6, P < 0.001) significantly differed between Omicron-infected and non-Omicron-infected febrile children. The body temperatures of Omicron-infected children were significantly higher during convulsions than when they were not convulsing and those of non-Omicron-infected febrile children during convulsions (median: 39.5 vs. 38.2 and 38.6 °C, both P < 0.001). In the three Omicron-subgroups, the temperature during convulsions was proportional to the percentage of patients and significantly differed ( P < 0.001), while not in the three non-Omicron-subgroups ( P = 0.244). The convulsion frequency was lower in the 55 vaccinated children compared to the 260 non-vaccinated children (average: 1.8 vs. 2.1, P < 0.001). The vaccination dose and convulsion frequency in Omicron-infected children were significantly correlated ( P < 0.001). Fifteen of the 112 severe Omicron cases had brain damage. CONCLUSIONS: Omicron-infected children experience higher body temperatures and frequencies during convulsions than those of non-Omicron-infected febrile children. We additionally found evidence of brain damage caused by infection with omicron BA.5. Vaccination and prompt fever reduction may relieve symptoms.

Deep Learning Bridged Bioactivity, Structure, and GC-HRMS-Readable Evidence to Decipher Nontarget Toxicants in Sediments.

Identifying causative toxicants in mixtures is critical, but this task is challenging when mixtures contain multiple chemical classes. Effect-based methods are used to complement chemical analyses to identify toxicants, yet conventional bioassays typically rely on an apical and/or single endpoint, providing limited diagnostic potential to guide chemical prioritization. We proposed an event-driven taxonomy framework for mixture risk assessment that relied on high-throughput screening bioassays and toxicant identification integrated by deep learning. In this work, the framework was evaluated using chemical mixtures in sediments eliciting aryl-hydrocarbon receptor activation and oxidative stress response. Mixture prediction using target analysis explained <10% of observed sediment bioactivity. To identify additional contaminants, two deep learning models were developed to predict fingerprints of a pool of bioactive substances (event driver fingerprint, EDFP) and convert these candidates to MS-readable information (event driver ion, EDION) for nontarget analysis. Two libraries with 121 and 118 fingerprints were established, and 247 bioactive compounds were identified at confidence level 2 or 3 in sediment extract using GC-qToF-MS. Among them, 12 toxicants were analytically confirmed using reference standards. Collectively, we present a "bioactivity-signature-toxicant" strategy to deconvolute mixtures and to connect patchy data sets and guide nontarget analysis for diverse chemicals that elicit the same bioactivity.

Evolutionary trajectory of diverse SARS-CoV-2 variants at the beginning of COVID-19 outbreak.

Despite extensive scientific efforts directed toward the evolutionary trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans at the beginning of the COVID-19 epidemic, it remains unclear how the virus jumped into and evolved in humans so far. Herein, we recruited almost all adult coronavirus disease 2019 (COVID-19) cases appeared locally or imported from abroad during the first 8 months of the outbreak in Shanghai. From these patients, SARS-CoV-2 genomes occupying the important phylogenetic positions in the virus phylogeny were recovered. Phylogenetic and mutational landscape analyses of viral genomes recovered here and those collected in and outside of China revealed that all known SARS-CoV-2 variants exhibited the evolutionary continuity despite the co-circulation of multiple lineages during the early period of the epidemic. Various mutations have driven the rapid SARS-CoV-2 diversification, and some of them favor its better adaptation and circulation in humans, which may have determined the waxing and waning of various lineages.

Prognostic factors in patients with secondary hemophagocytic lymphohistioc ytosis in a Chinese cohort.

Hemophagocytic lymphohistiocytosis (HLH) is a rare hyperinflammatory syndrome with high mortality mediated by an unbridled and persistent activation of cytotoxic T lymphocytes and natural killer cells. However, the influence factors of early death in adult sHLH patients are still not fully elucidated, which need further investigating. We have conducted an observational study of adult HLH patients between January 2016 and December 2022. All patients are enrolled according to HLH-2004 criteria. Clinical manifestations, laboratory data, treatments, and outcomes have been recorded. Influence factors associated with prognosis are calculated by using logistic regression models. Overall, 220 patients enrolled in this study. The etiologies of HLH were divided into five groups including autoimmune-associated hemophagocytic syndrome (AAHS) (n = 90, 40.9%), malignancies (n = 73, 33.2%), EBV-HLH (n = 18, 8.2%), infection excluded EBV (n = 24, 10.9%), and other triggers (n = 15, 6.8%). Among them, EBV-HLH had the highest mortality (77.8%), and AAHS had the lowest mortality (14.4%). Multivariate analysis indicated that age (≥ 38 years old), cytopenia ≥ 2 lines, platelets (≤ 50 × 109/L), aspartate aminotransferase (≥ 135U/L), prothrombin time (≥ 14.9 s) and activated partial thromboplastin time (≥ 38.5s), EBV, and fungal infection are independent risk factors for poor prognosis of HLH. Adult HLH patients with elder age, cytopenia ≥ 2 lines, levels of decreased platelets, increased AST, prolonged PT and APTT, EBV, and fungal infection tend to have a poor prognosis.

Discovery of the cereblon-recruiting tubulin PROTACs effective in overcoming Taxol resistance in vitro and in vivo.

Overexpression of ß3-tubulin is a common occurrence in human tumors and is associated with resistance to microtubule-targeting agents. PROTAC strategy has demonstrated significant potential in overcoming drug resistance. Herein, we report the discovery of W13 as the first PROTAC against tubulin, which was created by connecting a CRBN ligand to the widely recognized microtubule-destabilizing agent CA-4. Notably, it retains the inhibitory activity of the parental CA-4 and further exhibits substantial degradation of α/ß/ß3-tubulin in both A549 and A549/Taxol cell lines. The degradation of tubulin was subsequently verified to be mediated by the ubiquitin-proteasome system. Importantly, tumor xenograft research clearly showed W13's promising antitumor activity against human lung cancer. Taken together, the discovery of W13 demonstrated the practicality and feasibility of PROTAC targeting tubulin, hence establishing a potential therapeutic approach for treating NSCLC caused by the overexpression of ß3-tubulin.

A deep-learning pipeline to diagnose pediatric intussusception and assess severity during ultrasound scanning: a multicenter retrospective-prospective study.

Ileocolic intussusception is one of the common acute abdomens in children and is first diagnosed urgently using ultrasound. Manual diagnosis requires extensive experience and skill, and identifying surgical indications in assessing the disease severity is more challenging. We aimed to develop a real-time lesion visualization deep-learning pipeline to solve this problem. This multicenter retrospective-prospective study used 14,085 images in 8736 consecutive patients (median age, eight months) with ileocolic intussusception who underwent ultrasound at six hospitals to train, validate, and test the deep-learning pipeline. Subsequently, the algorithm was validated in an internal image test set and an external video dataset. Furthermore, the performances of junior, intermediate, senior, and junior sonographers with AI-assistance were prospectively compared in 242 volunteers using the DeLong test. This tool recognized 1,086 images with three ileocolic intussusception signs with an average of the area under the receiver operating characteristic curve (average-AUC) of 0.972. It diagnosed 184 patients with no intussusception, nonsurgical intussusception, and surgical intussusception in 184 ultrasound videos with an average-AUC of 0.956. In the prospective pilot study using 242 volunteers, junior sonographers' performances were significantly improved with AI-assistance (average-AUC: 0.966 vs. 0.857, P < 0.001; median scanning-time: 9.46 min vs. 3.66 min, P < 0.001), which were comparable to those of senior sonographers (average-AUC: 0.966 vs. 0.973, P = 0.600). Thus, here, we report that the deep-learning pipeline that guides lesions in real-time and is interpretable during ultrasound scanning could assist sonographers in improving the accuracy and efficiency of diagnosing intussusception and identifying surgical indications.

Host traits shape virome composition and virus transmission in wild small mammals.

Bats, rodents, and shrews are the most important animal sources of human infectious diseases. However, the evolution and transmission of viruses among them remain largely unexplored. Through the meta-transcriptomic sequencing of internal organ and fecal samples from 2,443 wild bats, rodents, and shrews sampled from four Chinese habitats, we identified 669 viruses, including 534 novel viruses, thereby greatly expanding the mammalian virome. Our analysis revealed high levels of phylogenetic diversity, identified cross-species virus transmission events, elucidated virus origins, and identified cases of invertebrate viruses in mammalian hosts. Host order and sample size were the most important factors impacting virome composition and patterns of virus spillover. Shrews harbored a high richness of viruses, including many invertebrate-associated viruses with multi-organ distributions, whereas rodents carried viruses with a greater capacity for host jumping. These data highlight the remarkable diversity of mammalian viruses in local habitats and their ability to emerge in new hosts.

Combining deep learning and intelligent biometry to extract ultrasound standard planes and assess early gestational weeks.

OBJECTIVES: To develop and validate a fully automated AI system to extract standard planes, assess early gestational weeks, and compare the performance of the developed system to sonographers. METHODS: In this three-center retrospective study, 214 consecutive pregnant women that underwent transvaginal ultrasounds between January and December 2018 were selected. Their ultrasound videos were automatically split into 38,941 frames using a particular program. First, an optimal deep-learning classifier was selected to extract the standard planes with key anatomical structures from the ultrasound frames. Second, an optimal segmentation model was selected to outline gestational sacs. Third, novel biometry was used to measure, select the largest gestational sac in the same video, and assess gestational weeks automatically. Finally, an independent test set was used to compare the performance of the system with that of sonographers. The outcomes were analyzed using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and mean similarity between two samples (mDice). RESULTS: The standard planes were extracted with an AUC of 0.975, a sensitivity of 0.961, and a specificity of 0.979. The gestational sacs' contours were segmented with a mDice of 0.974 (error less than 2 pixels). The comparison showed that the relative error of the tool in assessing gestational weeks was 12.44% and 6.92% lower and faster (min, 0.17 vs. 16.6 and 12.63) than that of the intermediate and senior sonographers, respectively. CONCLUSIONS: This proposed end-to-end tool allows automatic assessment of gestational weeks in early pregnancy and may reduce manual analysis time and measurement errors. CLINICAL RELEVANCE STATEMENT: The fully automated tool achieved high accuracy showing its potential to optimize the increasingly scarce resources of sonographers. Explainable predictions can assist in their confidence in assessing gestational weeks and provide a reliable basis for managing early pregnancy cases. KEY POINTS: • The end-to-end pipeline enabled automatic identification of the standard plane containing the gestational sac in an ultrasound video, as well as segmentation of the sac contour, automatic multi-angle measurements, and the selection of the sac with the largest mean internal diameter to calculate the early gestational week. • This fully automated tool combining deep learning and intelligent biometry may assist the sonographer in assessing the early gestational week, increasing accuracy and reducing the analyzing time, thereby reducing observer dependence.

Design, synthesis, and biological activity evaluation of novel tubulin polymerization inhibitors based on pyrimidine ring skeletons.

A library of new pyrimidine analogs was designed and synthesized of these, compound K10 bearing a 1,4­benzodioxane moiety and 3,4,5­trimethoxyphenyl group, exhibiting the most potent activity, with IC50 values of 0.07-0.80 µM against four cancer cell lines. Cellular-based mechanism studies elucidated that K10 inhibited microtubule polymerization, blocked the cell cycle at the G2/M phase, and eventually induced apoptosis of HepG2 cells. Additionally, K10 inhibited the migration and invasion of HepG2 cells in a dose-dependent manner. Overall, our work indicates that the tubulin polymerization inhibitor incorporating pyrimidine and the 3,4,5­trimethoxyphenyl ring may deserve consideration for cancer therapy.

P2Y6R: A Promising New Target in Inflammatory Diseases and Advances in its Antagonists.

P2Y receptors (P2YRs) are G protein-coupled receptors that are activated by extracellular nucleotides. The P2Y6 receptor (P2Y6R) is specifically activated by UDP, causing PKC activation and intracellular calcium ion release through the PLC pathway. Based on receptor tissue distribution and related pathways, several studies have reported that P2Y6R plays a physiological role in mediating inflammation, which suggests that P2Y6R could be a promising molecular target for the treatment of inflammatory diseases. In the past ten years, several P2Y6R antagonists have been discovered as new therapeutic strategies for inflammatory diseases. In this article, we systematically summarize the role of P2Y6R in inflammation and highlight the anti-inflammatory mechanism of a key P2Y6R antagonist, MRS2578. Insight into recent progress on the discovery of P2Y6R antagonists is also discussed.

α-Klotho: An Early Risk-Predictive Biomarker for Acute Kidney Injury in Patients with Acute Myocardial Infarction.

Background: Acute kidney injury (AKI) was a common and serious complication in patients with acute myocardial infarction (AMI). Novel biomarkers and therapies were deficient and imperative for AKI's early diagnosis and therapy after AMI. α-Klotho was considered as an early biomarker and potential therapy for AKI recently. Previous studies reported that the expression of α-Klotho was decreased in AKI rodents, and supplement of α-Klotho alleviated kidney injury. Nevertheless, its effect has not been studied in patients presenting with AMI. Methods: A total of 155 consecutive diagnosed with AMI at emergency department whose eGFR >60 ml/min ∗ 1.73 m2 were enrolled in this prospective observational cohort study which conducted between May 2016 and April 2019 in Peking University People's Hospital. AKI was defined according to the KDIGO criteria in 2012. At admission, the clinical data of patients were collected and serum α-Klotho was tested by ELISA. The relationship between α-Klotho, serum creatinine, eGFR, systolic pressure, BNP, LVEF, and Hgb of AKI were analyzed and their discrimination performances were compared. The association variables were calculated (adjusted odds ratio) with a confidence interval (CI) of 95% by binary logistic regression. And, we followed up the incidence of CKD and rehospitalization after patients' discharge in one year. Our study was approved by the ethics committee (no. 2016PHB042-01). Results: AKI incidence was 17.4% (27/155) during hospitalization. Compared to patients without AKI, the AKI group had obviously higher mortality and was more female and had higher incidence of chronic kidney disease, worse cardiac function, more cardiac complications, larger doses of diuretics, and less use of angiotensin-converting enzyme inhibitors/angiotensin receptor blocker. By contrary to previous animal experiments, we found serum α-Klotho levels were increased significantly in AKI patients (740.2 ± 306.8 vs. 419.0 ± 272.6 pg/mL, p < 0.001). And, the areas under the receiver operating curves indicated serum α-Klotho levels had a superior discriminative power for predicting AKI after AMI compared with other risk factors (0.792, 95% CI, 0.706-0.878, p < 0.001). Meanwhile, logistic regression model indicates extensive anterior myocardial infarction, Killip classification ≥2 grade, α-Klotho ≥516.9 pg/mL, eGFR (decrease per 10 ml/min ∗ 1.73 m2), Hgb, and nonuse of ACEI/ARB were the risk factors of AKI after AMI. Moreover, one-year follow-up presented AMI patients developed CKD had higher α-Klotho levels (739.7 ± 315.2 vs. 443.8 ± 292.5 pg/mL, p = 0.001), but no significant difference in rehospitalization. And, patients with α-Klotho ≥516.9 pg/ml was 6.699 times more likely to develop CKD than those with α-Klotho <516.9 pg/ml (relative risk 6.699, 95% CI 1.631-27.519, p = 0.007). Conclusion: Compared with traditional cardiac and renal biomarkers, serum α-Klotho could be a more appropriate predict biomarker for AKI after AMI in patients' eGFR >60 ml/min ∗ 1.73 m2. Higher α-Klotho levels are related to the development of AKI during hospitalization and suggest a higher prevalence of CKD after discharge. By contrary to animal experiments, whether the increased expression of α-Klotho could be a protective factor secreted by AKI after AMI, is remained to be further studied.

First report of a Chinese patient carrying Hb Ty Gard: A case report.

RATIONALE: More than 1300 mutations which lead to abnormal hemoglobin (Hb) have been recorded in the HbVar database. Hb Ty Gard has rarely been reported and has not been reported in China. PATIENT CONCERNS AND DIAGNOSES: A 2-year-old Chinese girl was healthy with normal physical development and hematological parameters. Capillary electrophoresis suggested that Hb F increased slightly, while Hb A2 levels were normal. Flow cytometry, fluorescence hybridization, and Sanger sequencing were used to characterize the genotypes. Sanger sequencing detected a heterozygous mutation at codon 124 of the ß-globin gene (HBB: c.374 C > A), which was previously reported as Hb Ty Gard in the HbVar database. OUTCOMES: We report the first case of HbTy Gard in a Chinese population. In areas with a high incidence of Hb diseases, sensitive detection of Hb components and accurate diagnosis of Hb variation are very important, and the combined application of capillary electrophoresis and gene sequencing can diagnose more Hb variants.

Experimental study on FBG sensing technology-based stress monitoring at the corners of reinforced soil retaining walls.

As a unique type of flexible slope fill-retaining structure, reinforced soil-retaining walls have the advantages of convenient construction, broad application conditions, good seismic performance, and high economic benefits. In general, reinforced soil-retaining walls appear at corners due to the restriction in topographic conditions during engineering construction. However, their special structures and stress conditions are usually ignored, thus triggering panel bulging, cracking, and collapse. In this study, an experimental method based on fiber Bragg grating (FBG) sensing technology was proposed for a physical model of reinforced soil-retaining walls. Then, a uniformly distributed load experiment was performed on this model by combining the measurement advantages of intelligent wire-type soil pressure sensors and the flexible characteristics of geotechnical reinforcement materials. The deformation development of this reinforced soil-retaining wall was monitored. Results revealed that before and after the loading of the reinforced soil-retaining wall, the deformation was mainly concentrated above the retaining wall, and the deformation scale at the corners was larger than that in the bilateral linear parts. After loading, the largest force deformation area on the retaining wall was transferred from the corners to the load area. The maximum strain was right beneath the load above the retaining wall, and the peak value at the other layers gradually approached the retaining wall. The experimental results prove that FBG sensing technology is feasible and effective for the whole-process monitoring of reinforced soil-retaining walls and is thus worthy of popularization and application.

[Effect of Flax lignans on apoptosis of growth plate chondrocytes in rats].

OBJECTIVE: To compare the effects of different concentrations of linolenin on inhibiting apoptosis of chondrocytes in the growth plate, and to screen the optimal concentration of linolenin, so as to provide theoretical support for delaying epiphyseal closure and promoting long bone growth in rats. METHODS: Two 4-week-old male SD rats (SPF grade) with a body mass of 80 g were selected. The growth plate cartilage of rat tibia and femur was dissected and isolated in vitro to obtain growth plate chondrocytes for culture. The chondrocytes were observed and identified by inverted phase contrast microscope and typeⅡ collagen immunofluorescence test, and then 20 ng/ml IL-1ß was used to induce apoptosis of growth plate chondrocytes as model group, and added with 1, 10, 20, 40 µM linolenin as the experimental group, and 5 µM letrozole as the positive control group. The cells were cultured for 24 and 48 hours respectively. The drug promoted cell proliferation was observed by MTT method, and the drug inhibited cell apoptosis was detected by flow cytometry. RESULTS: Contents 1, 10, 20, 40 µM could promote cell proliferation in varying degrees, and the principle was that the drug inhibits IL-1ß induced chondrocyte apoptosis in the growth plate, and the optimal concentration of drugs to inhibit apoptosis was 20 µM. CONCLUSION: The appropriate concentration of linseed lignans can significantly inhibit the apoptosis of chondrocytes in the growth plate of rats, and the optimal drug concentration is 20 µM. It provides possibility for delayed bone closure and longer growth time to promote bone growth during development.

Quantifying the dynamic transmission of COVID-19 asymptomatic and symptomatic infections: Evidence from four Chinese regions.

The dynamic transmission of asymptomatic and symptomatic COVID-19 infections is difficult to quantify because asymptomatic infections are not readily recognized or self-identified. To address this issue, we collected data on asymptomatic and symptomatic infections from four Chinese regions (Beijing, Dalian, Xinjiang, and Guangzhou). These data were considered reliable because the government had implemented large-scale multiple testing during the outbreak in the four regions. We modified the classical susceptible-exposure-infection-recovery model and combined it with mathematical tools to quantitatively analyze the number of infections caused by asymptomatic and symptomatic infections during dynamic transmission, respectively. The results indicated that the ratios of the total number of asymptomatic to symptomatic infections were 0.13:1, 0.48:1, 0.29:1, and 0.15:1, respectively, in the four regions. However, the ratio of the total number of infections caused by asymptomatic and symptomatic infections were 4.64:1, 6.21:1, 1.49:1, and 1.76:1, respectively. Furthermore, the present study describes the daily number of healthy people infected by symptomatic and asymptomatic transmission and the dynamic transmission process. Although there were fewer asymptomatic infections in the four aforementioned regions, their infectivity was found to be significantly higher, implying a greater need for timely screening and control of infections, particularly asymptomatic ones, to contain the spread of COVID-19.

Using homing pigeons to monitor atmospheric organic pollutants in a city heavily involving in coal mining industry.

Coal is the most extensively used fossil fuel in China. It is well documented that coal combustion detrimentally affected air quality, yet the contribution of coal mining activity to air pollution is still largely unknown. Homing pigeons have been applied to assess the occurrence of atmospheric pollutants within cities. Herein, we sampled homing pigeons from both urban and mining areas in a typical coal industry city (Datong, China) as biomonitors for assessing local air pollution. Target organic contaminants, including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and organochlorine pesticides (OCPs) were frequently detected in lung, liver, and fat tissues of the pigeons. The pollutants were predominately accumulated in lung, validating that respiration was the main accumulation route for these compounds in homing pigeons. In addition, pathological damage examination in lung and liver tissues revealed that the exposure to atmospheric pollutants impaired pigeon health. While the concentrations of PCBs and OCPs were similar in pigeons from urban and mining areas, the concentrations of PAHs were higher in pigeons from urban area. In contrast, more elevated levels of PBDEs (particularly BDE-209) were found in the mining area, which was consistent with the greater pathological damages and particulate matter levels. Unlike coal combustion, coal mining activities did not increase atmospheric PAH exposure to homing pigeons, but intensified PBDE contamination along with increasing emission of particulate matters. Overall, homing pigeons are promising biomonitors for assessing the respiratory exposure and risk of atmospheric pollutants within cities.

Coronaviruses in wild animals sampled in and around Wuhan at the beginning of COVID-19 emergence.

Over the last several decades, no emerging virus has had a profound impact on the world as the SARS-CoV-2 that emerged at the end of 2019 has done. To know where severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated from and how it jumped into human population, we immediately started a surveillance investigation in wild mammals in and around Wuhan when we determined the agent. Herein, coronaviruses were screened in the lung, liver, and intestinal tissue samples from fifteen raccoon dogs, seven Siberian weasels, three hog badgers, and three Reeves's muntjacs collected in Wuhan and 334 bats collected around Wuhan. Consequently, eight alphacoronaviruses were identified in raccoon dogs, while nine betacoronaviruses were found in bats. Notably, the newly discovered alphacoronaviruses shared a high whole-genome sequence similarity (97.9 per cent) with the canine coronavirus (CCoV) strain 2020/7 sampled from domestic dog in the UK. Some betacoronaviruses identified here were closely related to previously known bat SARS-CoV-related viruses sampled from Hubei province and its neighbors, while the remaining betacoronaviruses exhibited a close evolutionary relationship with SARS-CoV-related bat viruses in the RdRp gene tree and clustered together with SARS-CoV-2-related bat coronaviruses in the M, N and S gene trees, but with relatively low similarity. Additionally, these newly discovered betacoronaviruses seem unlikely to bind angiotensin-converting enzyme 2 because of the deletions in the two key regions of their receptor-binding motifs. Finally, we did not find SARS-CoV-2 or its progenitor virus in these animal samples. Due to the high circulation of CCoVs in raccoon dogs in Wuhan, more scientific efforts are warranted to better understand their diversity and evolution in China and the possibility of a potential human agent.

Rapid and automatic assessment of early gestational age using computer vision and biometric measurements based on ultrasound video.

Background: Early gestational age (GA) assessment using ultrasound is a routine and frequent examination performed in hospitals whereby clinicians manually measure the size of the gestational sac using ultrasound and calculate GA. However, the error is often substantial, and the process is laborious. To overcome these challenges, we propose a new system to assess early GA using a new end-to-end computer vision system and a new biometric measurement method based on ultrasound video. Methods: In this retrospective study, a new system was provided. B-ultrasound videos were first decomposed into two-dimensional (2D) images, and the contours of the gestational sac were extracted and drawn. The maximum length and short diameter of the gestational sac were then automatically measured and GA was calculated using the Hellman formula. Finally, through human-machine comparison, the clinicians' assessment errors were analyzed by SPSS 26. Results: In this study, 29,829 2D images of 191 B-ultrasound videos were evaluated using the new system. Clinicians usually require 15-20 min to complete assessments of GA, whereas with the new system assessments can be completed in approximately 30 s. Moreover, a human-machine comparison showed that the system helped intermediate skills clinicians improve their relative diagnostic error by 13.45% with an absolute error of 7 days. In addition, the new system was used to identify other lesions in the uterus and measure their size as a "sanity check". Conclusions: The proposed new system is a practical, reproducible, and reliable approach for assessing early GA.

Adaptive Multi-Factor Quantitative Analysis and Prediction Models: Vaccination, Virus Mutation and Social Isolation on COVID-19.

Different countries have adopted various control measures for the COVID-19 pandemic in different periods, and as the virus continues to mutate, the progression of the pandemic and preventive measures adopted have varied dynamically over time. Thus, quantitative analysis of the dynamic impact of different factors such as vaccination, mutant virus, social isolation, etc., on transmission and predicting pandemic progress has become a difficult task. To overcome the challenges above and enable governments to formulate reasonable countermeasures against the ongoing COVID-19 pandemic, we integrate several mathematical methods and propose a new adaptive multifactorial and geographically diverse epidemiological model based on a modified version of the classical susceptible-exposed-infectious-recovered (SEIR) model. Based on public datasets, a multi-center study was carried out considering 21 regions. First, a retrospective study was conducted to predict the number of infections over the next 30 days in 13 representative pandemic areas worldwide with an accuracy of 87.53%, confirming the robustness of the proposed model. Second, the impact of three scenarios on COVID-19 was quantified based on the scalability of the model: two different vaccination regimens were analyzed, and it was found that the number of infections would progressively decrease over time after vaccination; variant virus caused a 301.55% increase in infections in the United Kingdom; and 3-tier social lockdown in the United Kingdom reduced the infections by 47.01%. Third, we made short-term prospective predictions for the next 15 and 30 days for six countries with severe COVID-19 transmission and the predicted trend is accurate. This study is expected to inform public health responses. Code and data are publicly available at https://github.com/yuanyuanpei7/covid-19.

Serum cystatin C, kidney injury molecule-1, neutrophil gelatinase-associated lipocalin, klotho and fibroblast growth factor-23 in the early prediction of acute kidney injury associated with sepsis in a Chinese emergency cohort study.

BACKGROUND: Acute kidney injury (AKI) is a common and critical complication of sepsis, and is associated with unacceptable morbidity and mortality. Current diagnostic criteria for AKI was insensitive for early detection. Novel biomarkers including cystatin C, kidney injury molecule-1 (KIM-1), neutrophil gelatinase-associated lipocalin (NGAL), klotho and fibroblast growth factor-23 (FGF-23) can predict AKI earlier and allow immediate interventions. We aimed to determine the diagnostic performance of these biomarkers for detecting AKI in sepsis patients. METHODS: This prospective observational study was conducted between May 2018 and November 2020, enrolling 162 sepsis patients eventually. The AKI was defined in accordance with 2012 KDIGO criteria and we divided patients into non-AKI (n = 102) and AKI (n = 60) groups. Serum levels of several AKI biomarkers were detected by ELISA. The relationship between biomarker levels on admission of AKI was analyzed and discrimination performances comparison were performed. RESULTS: AKI incidence was up to 37.0% (60/162) during hospitalization. Compared with non-AKI group, both serum cystatin C, KIM-1, NGAL and FGF-23 were significantly elevated at admission in septic AKI patients. The areas under the receiver operating curves demonstrated that serum cystatin C had modest discriminative powers for predicting AKI after sepsis, and cystatin C combined with serum creatinine in the prediction of septic AKI increased the diagnostic sensitivity prominently. CONCLUSION: Serum cystatin C, KIM-1, NGAL and FGF-23 levels were both increased in septic AKI patients. Our study provided reliable evidence that cystatin C solely and combined with serum creatinine may accurately and sensitively predict septic AKI of patients on admission.