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Neonatal clinical sepsis is recognized as a significant health problem, This study sought to identify a predictive model of risk factors for clinical neonatal sepsis. A retrospective study was conducted from 1 October 2018 to 31 March 2023 in a large tertiary hospital in China. Neonates were divided into patients and controls based on the occurrence of neonatal sepsis. A multivariable model was used to determine risk factors and construct models.The utilization and assessment of model presentation were conducted using Norman charts and web calculators, with a focus on model differentiation, calibration, and clinical applicability (DCA). Furthermore, the hospital's data from 1 April 2023 to 1 January 2024 was utilized for internal validation. In the modelling dataset, a total of 339 pairs of mothers and their newborns were included in the study and divided into two groups: patients (n = 84, 24.78%) and controls (n = 255, 75.22%). Logistic regression analysis was performed to examine the relationship between various factors and outcome. The results showed that maternal age < 26 years (odds ratio [OR] = 2.16, 95% confidence interval [CI] 1.06–4.42, p = 0.034), maternal gestational diabetes (OR = 2.17, 95% CI 1.11–4.27, p = 0.024), forceps assisted delivery (OR = 3.76, 95% CI 1.72–5.21, p = 0.032), umbilical cord winding (OR = 1.75, 95% CI 1.32–2.67, p = 0.041) and male neonatal sex (OR = 1.59, 95% CI 1.00–2.62, p = 0.050) were identified as independent factors influencing the outcome of neonatal clinical sepsis. A main effects model was developed incorporating these five significant factors, resulting in an area under the curve (AUC) value of 0.713 (95% CI 0.635–0.773) for predicting the occurrence of neonatal clinical sepsis. In the internal validation cohort, the AUC value of the model was 0.711, with a 95% CI of 0.592–0.808. A main effects model incorporating the five significant factors was constructed to help healthcare professionals make informed decisions and improve clinical outcomes. [ABSTRACT FROM AUTHOR]

It was a challenge to deal with the concentrated leachate (CL) produced by membrane treatment technique in the waste incineration. In this study, the characteristics of the condensate and solid precipitation produced from treatment of CL by lab-scale direct contact evaporation system were investigated, and a process for the treatment of CL with no waste produced was put forward. The air was heated by exhaust steam and high temperature flue gas in the waste incineration to 500℃ and used for evaporating CL. The results showed that the concentrations of COD, NH3-N, and Cl− in the condensate were 17.6 mg/L, 3.1 mg/L, and 40 mg/L at the condition of the volume of hot air = 600 L/h, pH = 7.2, and concentration factor (CF) = 10, which were lower than the limited values in the water quality standard for industry uses (GB/T 19923–2005) in China, and the condensate can be used in circulating cooling water system for supplying water. Solid precipitation consisted of K2Ca(SO4)2·H2O, NaCl, KNO3, and NaNO3. CF was not over 10 because a larger amount of CaSO4 precipitated on the wall of pipe for passing through hot air, which hindered the continuous operation of the evaporation equipment, when CF > 10. Based on thermogravimetric analysis of solid phase precipitation, the most of organic matter in CL were oxidized and decomposed, while inorganic salts were not volatilized when the heating temperature reached about 760℃. The process for the treatment of CL with no waste produced can produce char and inorganic salts such as KCl and NaCl for waste recycling. [ABSTRACT FROM AUTHOR]

Background: Human respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection and hospitalization, especially in children. Highly mutagenic nature and antigenic diversity enable the RSV to successfully survive in human population. We conducted a molecular epidemiological study during 2017–2021 to investigate the prevalence and genetic characteristics of RSV. Methods: A total of 6499 nasopharyngeal (NP) swabs were collected from hospitalized children at Department of Pediatrics, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, Guangdong, China. All NP swab specimens were preliminary screened for common respiratory viruses and then tested for RSV using specific PCR assays. Partial G genes of RSV were amplified for phylogenetic analysis and genetic characterization. Results: The overall detection rate for common respiratory viruses was 16.12% (1048/6499). Among those, 405 specimens (6.20%, 405/6499) were found positive for RSV. The monthly distribution of RSV and other respiratory viruses was variable, and the highest incidence was recorded in Autumn and Winter. Based on the sequencing of hypervariable region of G gene, 93 RSV sequences were sub-grouped into RSV-A (56, 60.2%) and RSV-B (37, 39.8%). There was no coinfection of RSV-A and RSV-B in the tested samples. Phylogenetic analysis revealed that RSV-A and RSV-B strains belonged to ON1 and BA9 genotypes respectively, indicating predominance of these genotypes in Guangzhou. Several substitutions were observed which may likely change the antigenicity and pathogenicity of RSV. Multiple glycosylation sites were noticed, demonstrating high selection pressure on these genotypes. Conclusion: This study illustrated useful information about epidemiology, genetic characteristics, and circulating genotypes of RSV in Guangzhou China. Regular monitoring of the circulating strains of RSV in different parts of China could assist in the development of more effective vaccines and preventive measures. [ABSTRACT FROM AUTHOR]

Background: Human Adenoviruses (HAdVs) cause a wide array of illnesses in all age groups. They particularly cause frequent morbidity among children. In China, human adenovirus types 3, 4, 7, 11, 14, 21, and 55 have caused at least seven outbreaks since 2000. However, limited studies are available regarding the epidemiological patterns and diversity of HAdVs types among hospitalized patients with respiratory tract infections (RTIs).Methods: To understand the epidemiology and subtype distribution of HAdV infections associated with RTIs in China, nasal swab (NS) clinical samples were collected from 4129 patients in a Guangzhou hospital between August 2017 and October 2019. PCR, sequencing, and phylogenetic analysis were performed on these specimens to identify HAdV subtypes.Results: HAdV was successfully sequenced in 99 (2.4%) of the 4129 NS specimens, with the highest HAdV prevalence (6.3%) found in children between the ages of 5 and 10 years. Among HAdV-positive specimens, the most prevalent genotypes identified were HAdV-B3 (55.6%) and HAdV-B7 (25.3%). The most common symptoms in the HAdV-infected patients were fever (100%), cough (80.8%), and rhinorrhea (71.8%). HAdV infections were detected throughout the year with a relatively higher prevalence in summer.Conclusion: All ages suffer adenovirus infections, but young children are at the greatest risk. This study data demonstrates that at least three species of HAdVs (species B, C, and E) are circulating in Guangzhou City, China. As antiviral therapies and type-specific vaccines become available, such epidemiological data will be useful in guiding therapy and public health interventions. [ABSTRACT FROM AUTHOR]

Simple Summary: This manuscript reports a deep sequencing study comprehensively analyzing the clinical impact of mutations considering the abundance of mutations. We built an eight-gene mutation predictor considering intratumoral heterogeneity to predict post-surgery recurrence in ESCC patients. Unlike previous studies that simply treated mutations as binary variables (mutant and wild type), we quantified mutations by the fraction of cancer cells carrying the mutations, and our results showed that the cancer cell fraction of mutations was more informative than the mutation status of genes in recurrence prediction. The predictor was further validated as a powerful recurrence indicator in our validation set and the TCGA-ESCC cohort. With the popularization of targeted deep sequencing in clinical work, our study will help clinicians make accurate predictions of recurrence for patients and will provide a new perspective in the clinical transformation of genomic findings. Esophageal squamous cell carcinoma (ESCC) is one of the deadliest malignancies in China. The prognostic value of mutations, especially those in minor tumor clones, has not been systematically investigated. We conducted targeted deep sequencing to analyze the mutation status and the cancer cell fraction (CCF) of mutations in 201 ESCC patients. Our analysis showed that the prognostic effect of mutations was relevant to the CCF, and it should be considered in prognosis prediction. EP300 was a promising biomarker for overall survival, impairing prognosis in a CCF dose-dependent manner. We constructed a CCF-based predictor using a smooth clipped absolute deviation Cox model in the training set of 143 patients. The 3-year disease-free survival rates were 6.3% (95% CI: 1.6–23.9%), 29.8% (20.9–42.6%) and 70.5% (56.6–87.7%) in high-, intermediate- and low-risk patients, respectively, in the training set. The prognostic accuracy was verified in a validation set of 58 patients and the TCGA-ESCC cohort. The eight-gene model predicted prognosis independent of clinicopathological factors and the combination of our model and pathological staging markedly improved the prognostic accuracy of pathological staging alone. Our study describes a novel recurrence predictor for ESCC patients and provides a new perspective for the clinical translation of genomic findings. [ABSTRACT FROM AUTHOR]

In order to provide more useful information for the decision makers in China to implement sustainable energy policies and to identify which region in China is most suitable to build the biofuel production plants for fast pyrolysis and hydroprocessing of corn stover, the present study has evaluated the production efficiency and sustainability of large-scale transportation fuel production via fast pyrolysis and hydroprocessing of corn stover in China using emergy analysis approach. Both the hydrogen production scenario (i.e. oil hydroprocessing using the hydrogen derived from bio-oil reforming) and the hydrogen purchase scenario (i.e. oil hydroprocessing using the hydrogen purchased from market) in three regions of China (Northeast China Plain (NECP), North China Plain (NCP) and Shaanxi Province (SXP)) have been investigated. The results have shown that maize production, and fast pyrolysis and hydroprocessing are the two biggest emergy input stages of the biofuel production system. The comparison of the emergy indices of all of the six cases investigated indicates that the hydrogen purchase scenario in NCP is the best biofuel production case due to its second best sustainability and the second highest production efficiency. In comparison to bioethanol from cassava chips and wheat and biodiesel from jatropha curcas L, the hydrogen purchase scenario in NCP is also the most sustainable plan for a biofuel production plant in China. As water, fertilizer and hydrogen are the three biggest emergy inputs in this case, improvements on the water management, fertilizer management and hydrogen production technology have been discussed. In order to further increase the efficiency and sustainability of the hydrogen purchase scenario in NCP, some of the necessary efforts required from the relevant sectors have also been put forward based on the results of the emergy analysis. [ABSTRACT FROM AUTHOR]

Coal is widely utilized as an important energy source, but coal-fired power plant was considered to be an important anthropogenic lead emission source. In the present study, the distribution characteristics of lead in coal and combustion by-products are reviewed. Specifically, lead is mainly transferred to ash particles and the formation and migration mechanisms of particulate lead are summarized. Also, targeted measures are proposed to control the formation of fine particulate lead as well as to increase the removal efficiency during the low-temperature flue gas clean process. In detail, interactions between gaseous lead and some coal-bearing minerals or added adsorbents could obviously suppress the formation of fine particulate lead. On the other hand, some efforts (including promoting capture of fine particles, reducing resistivity of particles and strengthening the gas-liquid contact) could be made to improve the fine particulate lead removal capacity. Notably, the formation mechanism of fine particulate lead is still unclear due to the limitations of research methods. Some differences in the removal principles of fine particles and particulate lead make the lead emission precisely control a great challenge. Finally, the environmental potential risk of lead emission from flue gas and ash residues is addressed and further discussed., (Copyright © 2021. Published by Elsevier B.V.)

Based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the impact factors of industrial carbon emission in Nanjing were considered as total population, industrial output value, labor productivity, industrialization rate, energy intensity, research and development (R&D) intensity, and energy structure. Among them, the total population, industrial output value, labor productivity, and industrial energy structure played a role in promoting the increase of industrial carbon emissions in Nanjing, and the degree of influence weakened in turn. For every 1% change in these four factors, carbon emissions increased by 0.52%, 0.49%, 0.17% and 0.12%, respectively. The industrialization rate, R&D intensity, and energy intensity inhibited the increase of industrial carbon emissions, and the inhibiting effect weakened in turn. Every 1% change in these three factors inhibited the increase of industrial carbon emissions in Nanjing by 0.03%, 0.07%, and 0.02%, respectively. Then, taking the relevant data of industrial carbon emissions in Nanjing from 2006 to 2020 as a sample, the gray rolling prediction model with one variable and one first-order equation (GRPM (1,1)) forecast and scenario analysis is used to predict the industrial carbon emission in Nanjing under the influence of the pandemic from 2021 to 2030, and the three development scenarios were established as three levels of high-carbon, benchmark and low-carbon, It was concluded that Nanjing's industrial carbon emissions in 2030 would be 229.95 million tons under the high-carbon development scenario, 226.92 million tons under the benchmark development scenario, and 220.91 million tons under the low-carbon development scenario. It can not only provide data reference for controlling industrial carbon emissions in the future but also provide policy suggestions and development routes for urban planning decision-makers. Finally, it is hoped that this provides a reference for other cities with similar development as Nanjing.