Global burden and management of women with epilepsy in pregnancy: A modeling study.

BACKGROUND: Most pregnant women with epilepsy do not receive proper medical care, which creates a special burden worldwide. We aimed to qualify this special global burden and assess the impact of different clinical management strategies to reduce it. METHODS: The data used in this study were extracted from articles published between 2005 and 2022. We calculated the economic costs associated with major burdens experienced by pregnant women with epilepsy. We developed a microsimulation model to estimate the different effects of various interventions and their combinations as integrated strategies for pregnant women with epilepsy and related burden reduction. We also compared the regional differences in disease burden and interventions. FINDINGS: The total economic burden for pregnant women with epilepsy is estimated to reach $1.8 billion globally annually, which is more than three times the burden for epilepsy alone. Folic acid supplementation is projected to be the most effective intervention, with a 9.1% reduction in major congenital malformations, a 14.9% reduction in autism spectrum disorder, and a 10.8% reduction in offspring-related economic burden globally annually. Integrated strategies are associated with a reduced economic burden of up to $37.7 million annually globally. Folic acid supplementation is the most effective intervention in high- and upper-middle-income countries, whereas changes in antiseizure medication prescriptions are more effective in lower-middle- and low-income countries. CONCLUSION: This study highlights the huge burden for pregnant women with epilepsy and actions that must be taken to improve their quality of life. FUNDING: This work was supported by the Sichuan Science and Technology Program (2023YFS0047).

INT-1B3, an LNP formulated miR-193a-3p mimic, promotes anti-tumor immunity by enhancing T cell mediated immune responses via modulation of the tumor microenvironment and induction of immunogenic cell death.

microRNAs (miRNAs) are small, non-coding RNAs that regulate expression of multiple genes. MiR-193a-3p functions as a tumor suppressor in many cancer types, but its effect on inducing specific anti-tumor immune responses is unclear. Therefore, we examined the effect of our lipid nanoparticle (LNP) formulated, chemically modified, synthetic miR-193a-3p mimic (INT-1B3) on anti-tumor immunity. INT-1B3 inhibited distant tumor metastasis and significantly prolonged survival. INT-1B3-treated animals were fully protected against challenge with autologous tumor cells even in absence of treatment indicating long-term immunization. Protection against autologous tumor cell challenge was hampered upon T cell depletion and adoptive T cell transfer abrogated tumor growth. Transfection of tumor cells with our miR-193a-3p mimic (1B3) resulted in tumor cell death and apoptosis accompanied by increased expression of DAMPs. Co-culture of 1B3-transfected tumor cells and immature DC led to DC maturation and these mature DC were able to stimulate production of type 1 cytokines by CD4+ and CD8+ T cells. CD4-CD8- T cells also produced type 1 cytokines, even in response to 1B3-transfected tumor cells directly. Live cell imaging demonstrated PBMC-mediated cytotoxicity against 1B3-transfected tumor cells. These data demonstrate for the first time that miR-193a-3p induces long-term immunity against tumor development via modulation of the tumor microenvironment and induction of immunogenic cell death.

Cost prediction for ischemic heart disease hospitalization: Interpretable feature extraction using network analysis.

OBJECTIVES: Ischemic heart disease (IHD) is a significant contributor to global mortality and disability, imposing a substantial social and economic burden on individuals and healthcare systems. To enhance the efficient allocation of medical resources and ultimately benefit a larger population, accurate prediction of healthcare costs is crucial. METHODS: We developed an interpretable IHD hospitalization cost prediction model that integrates network analysis with machine learning. Specifically, our network-enhanced model extracts explainable features by leveraging a diagnosis-procedure concurrence network and advanced graph kernel techniques, facilitating the capture of intricate relationships between medical codes. RESULTS: The proposed model achieved an R2 of 0.804 ± 0.008 and a root mean square error (RMSE) of 17,076 ± 420 CNY on the temporal validation dataset, demonstrating comparable performance to the model employing less interpretable code embedding features (R2: 0.800 ± 0.008; RMSE: 17,279 ± 437 CNY) and the hybrid graph isomorphism network (R2: 0.802 ± 0.007; RMSE: 17,249 ± 387 CNY). The interpretation of the network-enhanced model assisted in pinpointing specific diagnoses and procedures associated with higher hospitalization costs, including acute kidney injury, permanent atrial fibrillation, intra-aortic balloon bump, and temporary pacemaker placement, among others. CONCLUSION: Our analysis results demonstrate that the proposed model strikes a balance between predictive accuracy and interpretability. It aids in identifying specific diagnoses and procedures associated with higher hospitalization costs, underscoring its potential to support intelligent management of IHD.

Chemical Synthesis of Proteins Using an o-Nitrobenzyl Group as a Robust Temporary Protective Group for N-Terminal Cysteine Protection.

We report here a robust and practical strategy for chemical protein synthesis using an o-nitrobenzyl group as a temporary protective group for an N-terminal cysteine residue of intermediate hydrazide fragments. By reinvestigating the photoremoval of an o-nitrobenzyl group, we establish a robust and reliable strategy for its quantitative photodeprotection. The o-nitrobenzyl group is completely stable to oxidative NaNO2 treatment and has been applied to the convergent chemical synthesis of programmed death ligand 1 fragment, providing a practical avenue for hydrazide-based native chemical ligation.

Genotype-Phenotype Correlations for Putative Haploinsufficient Genes in Deletions of 6q26-q27: Report of Eight Patients and Review of Literature.

Background Cytogenomic analyses have been used to detect pathogenic copy number variants. Patients with deletions at 6q26-q27 present variable clinical features. We reported clinical and cytogenomic findings of eight unrelated patients with a deletion of 6q26-q27. A systematic review of the literature found 28 patients with a deletion of 6q26-q27 from 2010 to 2020. Results For these 36 patients, the sex ratio showed equal occurrence between males and females; 29 patients (81%) had a terminal deletion and seven patients (19%) had a proximal or distal interstitial deletion. Of the 22 patients with parental studies, deletions of de novo, maternal, paternal, and bi-parental inheritance accounted for 64, 18, 14, and 4% of patients, respectively. The most common clinical findings were brain abnormalities (100%) in fetuses observed by ultrasonography followed by developmental delay and intellectual disability (81%), brain abnormalities (72%), facial dysmorphism (66%), hypotonia (63%), learning difficulty or language delay (50%), and seizures (47%) in pediatric and adult patients. Anti-epilepsy treatment showed the effect on controlling seizures in these patients. Cytogenomic mapping defined one proximal critical region at 6q26 containing the putative haploinsufficient gene PRKN and one distal critical region at 6q27 containing two haploinsufficient genes DLL1 and TBP . Deletions involving the PRKN gene could associate with early-onset Parkinson disease and autism spectrum disorder; deletions involving the DLL1 gene correlate with the 6q terminal deletion syndrome. Conclusion The genotype-phenotype correlations for putative haploinsufficient genes in deletions of 6q26-q27 provided evidence for precise diagnostic interpretation, genetic counseling, and clinical management of patients with a deletion of 6q26-q27.

A dynamic sequential decision-making model on MRI real-time scheduling with simulation-based optimization.

Magnetic resonance imaging (MRI) is widely used in diagnostic medicine and contributes significantly to US health care spending. Scheduling MRI jobs involves uncertainties (e.g., patient arrival time, scanning time, and preparation time) that can lead to excessive delays and high costs in MRI operations. This study addresses real-time decision making in use of MRI scanners based on job assignment and sequencing decisions that override the appointment schedule. The decisions are made using real-time information of the waiting patients, the utilization status of the MRI scanners, and the partially revealed uncertainties of scanning times of current patients. A sequential decision-making framework and a simulation-based solution method are proposed to utilize massive real-time information and match the use of MRI rescheduling in practice. The results are then compared with a real case in a large midwestern academic medical center in the US. This study illustrates that the proposed method reduces patient waiting time by 21.7% and improves utilization of MRI scanners by 23.0%. An optimality gap of 13.6% is provided when compared to off line scheduling methods based on a mixed integer programming (MIP) model. The number of simulation replications in this approach uses the ranking and selection method, which not only reduces solution time, but also provides solution quality guarantees wherein the probability of errors in the proposed method for one day is less than 0.1%. In 100 randomly generated workday experiments, all of the scheduling decisions given by the proposed method perform better than current policy, with an average reduction of 17.93 minutes in each patient's waiting time and an improvement of scanner utilization by 7.20%.

Chinese Medicine Formula Huashibaidu Granule Early Treatment for Mild COVID-19 Patients: An Unblinded, Cluster-Randomized Clinical Trial.

Background: Previous research suggested that Chinese Medicine (CM) Formula Huashibaidu granule might shorten the disease course in coronavirus disease 2019 (COVID-19) patients. This research aimed to investigate the early treatment effect of Huashibaidu granule in well-managed patients with mild COVID-19. Methods: An unblinded cluster-randomized clinical trial was conducted at the Dongxihu FangCang hospital. Two cabins were randomly allocated to a CM or control group, with 204 mild COVID-19 participants in each cabin. All participants received conventional treatment over a 7 day period, while the ones in CM group were additionally given Huashibaidu granule 10 g twice daily. Participants were followed up to their clinical endpoint. The primary outcome was worsening symptoms before the clinical endpoint. The secondary outcomes were cure and discharge before the clinical endpoint and alleviation of composite symptoms after the 7 days of treatment. Results: All 408 participants were followed up to their clinical endpoint and included in statistical analysis. Baseline characteristics were comparable between the two groups (P > 0.05). The number of worsening patients in the CM group was 5 (2.5%), and that in the control group was 16 (7.8%) with a significant difference between groups (P = 0.014). Eight foreseeable mild adverse events occurred without statistical difference between groups (P = 0.151). Conclusion: Seven days of early treatment with Huashibaidu granule reduced the likelihood of worsening symptoms in patients with mild COVID-19. Our study supports Huashibaidu granule as an active option for early treatment of mild COVID-19 in similar well-managed medical environments. Clinical Trial Registration:www.chictr.org.cn/showproj.aspx?proj=49408, identifier: ChiCTR2000029763.

A predictive model incorporating the change detection and Winsorization methods for alerting hypoglycemia and hyperglycemia.

This paper focuses on establishing an effective predictive model to quickly and accurately alert hypoglycemia and hyperglycemia for helping control blood glucose levels of people with diabetes. In general, a good predictive model is established on the features of data. Inspired by this, we first analyze the characteristics of continuous glucose monitoring (CGM) data by the equality of variances test and outlier detection, which show time-varying fluctuations and jump points in CGM data. Therefore, we incorporate the change detection method and the Winsorization method into the predictive model based on the autoregressive moving average (ARMA) model and the recursive least squares (RLS) method to fit the above characteristics. To the best of our knowledge, the proposed method is the first attempt to give a solution for matching the time-varying fluctuations and jump points of CGM data simultaneously. A case study using CGM data is given to validate the effectiveness of the proposed method under 30-min-ahead prediction. The results show that the proposed method can improve the true alarm ratio of hypoglycemia and hyperglycemia from 0.7983 to 0.8783, and lengthen the average advance detection time of hypoglycemia and hyperglycemia from 19.77 to 22.64 min.

Combination of Hua Shi Bai Du granule (Q-14) and standard care in the treatment of patients with coronavirus disease 2019 (COVID-19): A single-center, open-label, randomized controlled trial.

OBJECTIVE: To evaluate the efficacy and safety of Hua Shi Bai Du Granule (Q-14) plus standard care compared with standard care alone in adults with coronavirus disease (COVID-19). STUDY DESIGN: A single-center, open-label, randomized controlled trial. SETTING: Wuhan Jinyintan Hospital, Wuhan, China, February 27 to March 27, 2020. PARTICIPANTS: A total of 204 patients with laboratory-confirmed COVID-19 were randomized into the treatment group and control group, consisting of 102 patients in each group. INTERVENTIONS: In the treatment group, Q-14 was administered at 10 g (granules) twice daily for 14 days, plus standard care. In the control group, patients were provided standard care alone for 14 days. MAIN OUTCOME MEASURE: The primary outcome was the conversion time for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral assay. Adverse events were analyzed in the safety population. RESULTS: Among the 204 patients, 195 were analyzed according to the intention-to-treat principle. A total of 149 patients (71 vs. 78 in the treatment and control groups, respectively) tested negative via the SARS-CoV-2 viral assay. There was no statistical significance in the conversion time between the treatment group and control group (Full analysis set: Median [interquartile range]: 10.00 [9.00-11.00] vs. 10.00 [9.00-11.00]; Mean rank: 67.92 vs. 81.44; P = 0.051). The recovery time for fever was shorter in the treatment group than in the control group. The disappearance rate of symptoms like cough, fatigue, and chest discomfort was significantly higher in the treatment group. In chest computed tomography (CT) examinations, the overall evaluation of chest CT examination after treatment compared with baseline showed that more patients improved in the treatment group. There were no significant differences in the other outcomes. CONCLUSION: The combination of Q-14 and standard care for COVID-19 was useful for the improvement of symptoms (such as fever, cough, fatigue, and chest discomfort), but did not result in a significantly higher probability of negative conversion in the SARS-CoV-2 viral assay. No serious adverse events were observed. TRIAL REGISTRATION: ChiCTR2000030288.

[A review of consensus statements, practice resources, standards and guidelines for clinical applications of next-generation sequencing technologies in the United States].

The use of whole exome sequencing (WES) for the detection of disease-causing variants of genetic diseases and for non-invasive prenatal screening (NIPS) of fetal aneuploidies are two major clinical applications of next generation sequencing (NGS). This article has summarized the official documents developed and updated by the American College of Medical Genetics and Genomics (ACMG) on governing WES and NIPS. These include the development of expert consensus policies and position statements on an ongoing basis to guide clinical application of NGS technology and variant analysis, establish evidence-based practical resources, as well as standards and guidelines to govern diagnosis and screening. These ACMG documents are valuable references to Chinese geneticists, but direct adoption of these standards and guidelines may not be practical due to the differences in disease-associated variant frequencies in Chinese population, socioeconomic status, and medical practice between the two countries. It is hoped that this review could facilitate the development of NGS and NIPS standards and guidelines that are consistent with international standards and concordant with medical genetics practice in China to provide high-quality, efficient and safe clinical services for patients and their families with genetic diseases.

[Experience and lessons on guiding and governing clinical applications of chromosome microarray analysis in the United States].

Chromosome microarray analysis (CMA) has become the first-tier testing for chromosomal abnormalities and copy number variations (CNV). This review described the clinical validation of CMA, the development and updating of technical standards and guidelines and their diagnostic impacts. The main focuses were on the development and updating of expert consensus, practice resources, and a series of technical standards and guidelines through systematic review of case series with CMA application in the literature. Expert consensus and practice resource supported the use of CMA as the first-tier testing for detecting chromosomal abnormalities and CNV in developmental and intellectual disabilities, multiple congenital anomalies and autism. The standards and guidelines have been applied to pre- and postnatal testing for constitutional CNV and tumor testing for acquired CNV. CMA has significantly improved the diagnostic yields but still needs to overcome its technical limitations and face challenges of new technologies. Guiding and governing CMA through expert consensus, practice resource, standards and guidelines in the United States has provided effective and safe diagnostic services to patients and their families, reliable diagnosis on related genetic diseases for clinical database and basic research, and references for clinical translation of new technologies.

Fabrication of Bioresource-Derived Porous Carbon-Supported Iron as an Efficient Oxidase Mimic for Dual-Channel Biosensing.

Herein, we designed a new strategy for fabricating a renewable bioresource-derived N-doped hierarchical porous carbon-supported iron (Fe/NPC)-based oxidase mimic. The obtained results suggested that Fe/NPC possessed a large specific surface area (1144 m2/g) and pore volume (0.62 cm3/g) to afford extensive Fe-Nx active sites. Taking advantages of the remarkable oxidase-mimicking activity, outstanding stability, and reusability of Fe/NPC, a novel dual-channel biosensing system was strategically fabricated for sensitively determining acetylcholinesterase (AChE) through the integration of Fe/NPC and fluorescent silver nanoclusters (AgNCs) for the first time. The limits of detection for AChE can achieve as low as 0.0032 and 0.0073 U/L by the outputting fluorometric and colorimetric dual signals, respectively. Additionally, this dual-signal system was applied to analyze human erythrocyte AChE and its inhibitor with robust analytical performance. This work provides one sustainable and effective avenue to apply a bioresource for fabricating an Fe/NPC-based oxidase mimic with high catalytic performance and also gives new impetuses for developing novel biosensors by applying Fe/NPC-based enzyme mimics as substitutes for the natural enzyme.

Combining econometric analysis and simulation modeling to evaluate Population-Based health policies for chronic disease prevention and control.

OBJECTIVES: Population-based health policies play an important role in preventing and controlling chronic disease. Policymakers need to understand both the short- and long-term impacts of different policies to optimize resource allocation. The objective of this study is to develop a framework that combines econometric analysis and simulation modeling for a comprehensive evaluation of population-based health policies. STUDY DESIGN: Both econometric analysis and simulation modeling were used to evaluate the impact of a population-based health policy. METHODS: We identified a cohort of hypertensive patients from the 2011-2013 China Health and Retirement Longitudinal Study and fitted the data into our framework to evaluate the effectiveness of a community-based hypertension-screening program under the Essential Public Health Services (EPHS) policy on the future burden of cardiovascular disease in China. RESULTS: Using an econometric approach, we identified that the community-based hypertension screening program would lead to a 7.9% improvement in the rate of hypertension control. Using a validated simulation model, we further estimated that if the policy was fully implemented nationwide, it could avert 97,100 cases of myocardial infarction and 215,600 cases of stroke. The policy would cost $2131 on average to save 1 quality-adjusted life year over 10 years. CONCLUSIONS: This study proposed a framework integrating two different methods and assessing both short- and long-term impact of a population-based health policy. Through a case study, we demonstrated that combining econometric analysis and simulation modeling could provide policymakers with a more powerful tool to evaluate health policies for controlling chronic disease.

Construction of a Sensing Platform Based on DNA-Encoded Magnetic Beads and Copper Nanoclusters for Viral Gene Analysis with Target Recycling Amplification.

The rapid and accurate monitoring of viral genes plays an important role in the area of disease diagnosis, biomedical research, and food safety. Herein, we successfully designed a sensing system that combined the technologies of target DNA recycling amplification, magnetic separation, and in situ formation of fluorescent copper nanoclusters (CuNCs) for viral DNA analysis. In the presence of target viral DNA (tDNA), a large quantity of output DNA (oDNA) was produced from hairpin DNA (hDNA) through an exonuclease III-assisted target recycling amplification strategy. Magnetic beads (MBs) labeled with capture DNA (cDNA) were hybridized with oDNA, and the partially complementary oDNA served as a bridge that could link AT-rich dsDNA on the surface of MBs, which led to a decrease of AT-rich dsDNA in solution after magnetic separation. On account of the lack of AT-rich dsDNA as a template in solution, in situ formation of fluorescent CuNCs was blocked, which resulted in a decrease in the fluorescence intensity at 590 nm. Therefore, taking advantage of one-step magnetic separation and in situ formation of CuNCs, the target viral DNA was sensitively and specifically detected in a linear range from 5 pM to 5 nM with a detection limit of 1 pM. The MB-based platform was not only reusable but also achieved magnetic separation, which could eliminate interferences in complex samples. The assay combining the MB-based probe with fluorescent CuNCs provided a universal, label-free, and reusable platform for viral DNA detection.

A prediction and interpretation framework of acute kidney injury in critical care.

Acute kidney injury (AKI) is a common clinical condition with high mortality and resource consumption. Early identification of high-risk patients to achieve an appropriate allocation of limited clinical resources and timely interventions is of significant importance, which has attracted substantial research to develop prediction models for AKI risk stratification. However, most available AKI prediction models have moderate performance and lack of interpretability, which limits their applicability in supporting care intervention. In this paper, a machine learning-based framework for AKI prediction and interpretation in critical care is presented. First, an ensemble model is developed to predict a patient's risk of AKI within 72 h of admission to the intensive care units. Next, the model is interpreted both globally and locally. For the global interpretation, the important predictors are pinpointed and the detailed relationships between AKI risk and these predictors are illustrated. For the local interpretation, patient-specific analysis is presented to provide a visualized explanation for each individual prediction. Experimental results show that such a prediction and interpretation framework can lead to good prediction and interpretation performance, which has the potential to provide effective clinical decision support.

Efficacy and safety of Chinese herbal medicine versus Lopinavir-Ritonavir in adult patients with coronavirus disease 2019: A non-randomized controlled trial.

BACKGROUND: Treatments for coronavirus disease 2019 (COVID-19) are limited by suboptimal efficacy. METHODS: From January 30, 2020 to March 23, 2020, we conducted a non-randomised controlled trial, in which all adult patients with laboratory-confirmed COVID-19 were assigned to three groups non-randomly and given supportive treatments: Group A, Lopinavir-Ritonavir; Group B, Huashi Baidu Formula (a Chinese medicineformula made by the China Academy of Chinese Medical Sciences to treat COVID-19, which is now in the clinical trial period) and Lopinavir-Ritonavir; and Group C, Huashi Baidu Formula. The use of antibiotics, antiviruses, and corticosteroids was permitted in Group A and B. Traditional Chinese medicine injections were permitted in Group C. The primary outcomes were clinical remission time (interval from admission to the first time the patient tested negatively for novel coronavirus or an obvious improvement was observed from chest CT) and clinical remission rate (number of patients whose clinical time was within 16 days/total number of patients). RESULTS: A total of 60 adult patients with COVID-19 were enrolled at sites in Wuhan, China, and the sample size of each group was 20. In Groups A, B and C, the clinical remission rates were 95.0%%(19/20), 100.0%%(20/20) and 100.0%%(20/20), respectively. Compared with Groups A and B, the clinical remission time of Group C was significantly shorter (5.9 days vs. 10.8 days, p < 0.05; 5.9 days vs. 9.7 days, p < 0.05). There was no significant difference among Groups A, B, and C in terms of the time taken to be released from quarantine. The clinical biochemical indicators and safety indexes showed no significant differences among the three groups. CONCLUSIONS: Our findings suggest that Lopinavir-Ritonavir has some efficacy in the treatment of COVID-19, and the Huashi Baidu Formula might enhance this effect to an extent. In addition, superiority was displayed in the treatment of COVID-19 through a combination of the Huashi Baidu Formula and traditional Chinese medicine injection. In future, well-designed prospective double-blinded randomised control trials are required to confirm our findings.

Fe-N-C single-atom nanozymes with peroxidase-like activity for the detection of alkaline phosphatase.

Single-atom nanozymes have drawn wide attention in bio-sensing for their remarkable merits such as low cost, high stability, and maximum atom utilization. Herein, a colorimetric strategy based on Fe-N-C single-atom nanozymes (Fe/NC-SAs) was established for the detection of alkaline phosphatase (ALP) activity. The Fe/NC-SAs prepared by pyrolysis have excellent peroxidase-like activity and can oxidize 3,3',5,5'-tetramethylbenzidine (TMB) to a blue color product in the presence of hydrogen peroxide (H2O2). When ascorbic acid (AA) is added to the system, the blue color fades, and the absorbance has a linear relationship with the concentration of AA. Alkaline phosphatase (ALP) can catalyze the hydrolysis of ascorbic acid 2-phosphate (AAP) to produce AA. Thus, a strategy based on Fe/NC-SAs for the detection of ALP activity was established, which provided a linear range of 0.1-1.5 U L-1 and a limit of detection as low as 0.05 U L-1. Besides, Fe/NC-SAs showed high stability under harsh conditions. Moreover, an Fe/NC-SA-based assay was successfully validated using human serum samples for ALP determination with satisfactory results, and has broad prospects in the field of biosensing.

Analysis of the clinical features of pericentric inversion of chromosome 9.

OBJECTIVE: The pericentric inversion of chromosome 9 (inv9) is one of the most common structural balanced chromosomal variations, and it is considered to be a normal population variant. The aim of this study was to re-evaluate the clinical impact of patients with inv9. METHODS: We studied the karyotypes from 4853 patients at a single center and retrospectively reviewed their clinical data. RESULTS: There were 67 inv9 patients among 2988 adults, and 62 of them showed different clinical features, including male and female infertility, oligoasthenozoospermia, and azoospermia. Thirty-one cases of inv9 were found in 1865 fetuses, including two cases in chorionic villus (6.90%) and 29 in amniotic fluid (1.67%), but there were no cases in umbilical cord blood. The rates of fetal phenotype abnormal and adverse pregnancy outcome with inv9 in the chorionic villus were 100.00% (2/2), while only 17.24% (5/29) in the amniotic fluid showed abnormalities, among which 60.00% (3/5) had adverse pregnancy outcomes. CONCLUSIONS: Although there is no clear evidence that inv9 is pathogenic, the genetic counseling on inv9 in early pregnancy and adults needs to be given more attention.

Development of early warning and rapid response system for patients with novel coronavirus pneumonia (COVID-19): A research protocol.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has caused serious damage to public health. COVID-19 has no vaccine or specific therapy; its mortality rate increases significantly once patients deteriorate. Furthermore, intensive monitoring of COVID-19 is limited by insufficient medical resources and increased risks of exposure to medical staff. We therefore aim to build an early warning and rapid response system (EWRRS) to address these problems. METHOD: The research is designed as a prospective cohort study, to verify a dynamic and interactive evaluation system; it includes patient self-reporting, active monitoring, early alarming and treatment recommendations. Adult patients diagnosed with COVID-19 will be recruited from Sept 2020 to Aug 2021 at a tertiary contagious hospital. Patients with life expectancy <48 hours, pregnant or lactating, in immunosuppression states or end-stage diseases will be excluded. The intervention is implementation of EWRRS to detect early signs of clinical deterioration of COVID-19 patients, to provide timely and efficient treatment suggestions by the system. EWRRS can determine the classification and interactive evaluation of patient information; the determination is based on the application of 3 different scenario modules, separately driven by patients, nurses, and physicians. The primary outcome is change in disease severity category after treatment. Secondary outcomes include the proportion of patients with different disease severity types; critical deterioration events; patients who had unplanned transfers to an intensive care unit (ICU) and required critical care interventions; intervals from warning to implementation of clinical interventions; hospital mortality; length of ICU and hospital stay; workload of medical staff and risks of exposure to COVID-19. DISCUSSION: Our hypothesis is that EWRRS provides an example of an early identification, warning, and response system for COVID-19. In addition, EWRRS can potentially be extended to use as a grading metric for general critically ill patients in an ICU setting.

Peroxidase-like activity of Fe-N-C single-atom nanozyme based colorimetric detection of galactose.

Single atom nanozymes are the artificial enzymes with enzyme-like activity, which have attracted a great deal attention in recent years due to their unique merits such as remarkable stability, excellent atom utilization and low cost. Herein, a convenient and sensitive colorimetric strategy was developed for the sensing of galactose based on Fe-N-C single-atom nanozyme (Fe-SAzyme). The Fe-SAzyme was prepared through "isolation-pyrolysis" method that exhibited intrinsic peroxidase mimicking activity, which can quickly catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) to produce blue-colored oxTMB in the presence of hydrogen peroxide (H2O2). Galactose can be oxidized by galactose oxidase (Gal Ox) to generate H2O2, and Fe-SAzyme can be utilized for quantitative colorimetric detection of galactose. A good linearity between absorbance and the galactose concentration in the range of 50-500 µM was obtained with a detection limit of (LOD) 10 µM. The Fe-SAzyme based colorimetric strategy offered a rapid, convenient and economic way for galactose quantification detection, which could be used as an alternative method for galactosemia diagnosis.