Diagnostic performance of mpox virus (MPXV) real-time PCR assays: multicenter assessment and extended sensitivity analysis.

PURPOSE: To comprehensively investigate the diagnostic performance of routinely used assays in MPXV testing, the National Center of Clinical Laboratories in China conducted a nationwide external quality assessment (EQA) scheme and an evaluated nine assays used by ≥ 5 laboratories in the EQA. METHODS: MPXV virus-like particles with 2700, 900 and 300 copies/mL were distributed to 195 EQA laboratories. For extended analysis, triple-diluted samples from 9000 to 4.12 copies/mL were repeated 20 times using the assays employed by ≥ 5 laboratories. The diagnostic performance was assessed by analyzing EQA data and calculating the limits of detection (LODs). RESULTS: The performance was competent in 87.69% (171/195) of the participants and 87.94% (175/199) of the datasets. The positive percentage agreements (PPAs) were greater than 99% for samples at 2700 and 900 copies/mL, and 95.60% (761/796) for samples at 300 copies/mL. The calculated LODs for the two clades ranged from 228.44 to 924.31 copies/mL and were greater than the LODs specified by the respective kits. EasyDiagnosis had the lowest calculated LODs and showed superior performance in EQA, whereas BioGerm and Sansure, with higher calculated LODs, did not perform well in EQA. CONCLUSION: This study provides valuable information from the EQA data and evaluation of the diagnostic performance of MPXV detection assays. It also provided insights into reagent optimization and enabled prompt public health interventions for the outbreak.

A collapse risk assessment method for subway foundation pit based on cloud model and improved Dempster-Shafer evidence theory.

Collapse is a major engineering hazard in open-cut foundation pit construction, and risk assessment is crucial for considerably reducing engineering hazards. This study aims to address the ambiguity problem of qualitative index quantification and the failure of high-conflict evidence fusion in risk assessment. Thus, a fast-converging and high-reliability multi-source data fusion method based on the cloud model (CM) and improved Dempster-Shafer evidence theory is proposed. The method can achieve an accurate assessment of subway pit collapse risks. First, the CM is introduced to quantify the qualitative metrics. Then, a new correction parameter is defined for improving the conflicts among evidence bodies based on conflict degree, discrepancy degree and uncertainty, while a fine-tuning term is added to reduce the subjective effect of global focal element assignment. Finally, the risk assessment result is obtained according to the maximum affiliation principle. The method is successfully applied to Luochongwei Station, where the difference between the maximum value and the second largest value of the basic probability assignment is 0.624, and the global uncertainty degree is 0.087. Both values satisfy the decision evaluation condition; however, values of other methods only satisfy one or neither condition. In addition, the proposed method requires only four cycles to reach the steady state by fusing data of the same index, which has faster convergence compared with that of other methods. The proposed method has good universality and effectiveness in subway pit collapse risk assessment.

Malingering assessment after severe traumatic brain injury in forensic psychology with a potential embedded symptom validity indicator of Symptom Checklist 90.

Objective: Malingering of neuropsychological damage is common among traumatic brain injury patients pursuing disability compensation in forensic contexts. There is an urgent need to explore differences in neuropsychological assessment outcomes with different levels of cooperation. Methods: A total of 420 participants with severe traumatic brain injury were classified into malingering group, partial cooperation group, and complete cooperation group according to the Binomial forced-choice digit memory test. The Wechsler Adult Intelligence Scale, event-related potential component, and Symptom Checklist 90 were applied subsequently to assess the psychological status of participants. Results: Participants in the malingering group presented lower scores in the binomial forced-choice digit memory test and the Wechsler Adult Intelligence Scale, lower P3 amplitude, and simultaneously higher scores in the Symptom Checklist 90 than the other two groups. The actual intelligence quotient of participants with malingering tendencies ranged mostly between normal and marginal damage, and they often reported elevated whole scale scores in the Symptom Checklist 90. The Cooperation Index (defined as the ratio of positive symptom distress index to global severity index, CI) was proposed and validated to function as an embedded validity indicator of the Symptom Checklist 90, and the area under the receiver operating characteristic (ROC) curve was 0.938. When valued at 1.28, CI has the highest classification ability in differentiating malingering from non-malingering. Combined with the CI and P3 amplitude, the area under the ROC curve for malingering diagnosis further reached 0.952. Conclusion: Any non-optimal effort in a forensic context will lead to unexpected deviation in psychology evaluation results. CI is a potential candidate to act as an embedded validity indicator of the Symptom Checklist 90. The combination of CI and P3 amplitude can help to identify malingering in participants after severe traumatic brain injury.

Global warming may significantly increase childhood anemia burden in sub-Saharan Africa.

Childhood anemia constitutes a global public health problem, especially in low- and middle-income countries (LMICs). However, it remains unknown whether global warming has an impact on childhood anemia. Here, we examined the association between annual temperatures and childhood anemia prevalence in sub-Saharan Africa and then projected childhood anemia burden attributable to climate change. Each 1°C increment in annual temperature was associated with increased odds of childhood anemia (odd ratio = 1.138, 95% confidence interval: 1.134-1.142). Compared with the baseline period (1985-2014), the attributable childhood anemia cases would increase by 7,597 per 100,000 person-years under a high-emission scenario in the 2090s, which would be almost 2-fold and over 3-fold more than those projected in moderate- and low-emission scenarios. Our results reveal the vulnerabilities and inequalities of children for the excess burden of anemia due to climate warming and highlight the importance of climate mitigation and adaptation strategies in LMICs.

Machine Learning Predicts the Methane Clumped Isotopologue (12CH2D2) Distributions Constrain Biogeochemical Processes and Estimates the Potential Budget.

Methane (CH4) is a matter of environmental concern; however, global methane isotopologue data remain inadequate. This is due to the challenges posed by high-resolution testing technology and the need for larger sample volumes. Here, worldwide methane clumped isotope databases (n = 465) were compiled. We compared machine-learning (ML) models and used random forest (RF) to predict new Δ12CH2D2 distributions, which cover valuable and hard-to-replicate methane clumped isotope experimental data. Our RF model yields a reliable and continuous database including ruminants, acetoclastic methane, multiple pyrolysis, and controlled experiments. We showed the effectiveness of utilizing a new data set to quantify isotopologue fractionations in biogeochemical methane processes, as well as predicting the steady-state atmospheric methane clumped isotope composition (Δ13CH3D of +2.26 ± 0.71‰ and Δ12CH2D2 of +62.06 ± 4.42‰) with notable biological contributions. Our measured summer and winter water emitted gases (n = 6) demonstrated temperature-driven seasonal microbial community evolution determined by atmospheric clumped isotope temporal variations (Δ 13CH3D ∼ -0.91 ± 0.25 ‰ and Δ12CH2D2 ∼ +3.86 ± 0.84 ‰), which in turn is relevant for future models quantifying the contribution of methane sources and sinks. Predicting clumped isotopologues translates our methane geochemical understanding into quantifiable variables for modeling that can continue to improve predictions and potentially inform global greenhouse gas emissions and mitigation policy.

Performance evaluation of SARS-CoV-2 antigen detection in the post-pandemic era: multi-laboratory assessment.

OBJECTIVES: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigen detection is an indispensable tool for epidemic surveillance in the post-pandemic era. Faced with irregular performance, a comprehensive external quality assessment (EQA) scheme was conducted by the National Center for Clinical Laboratories (NCCL) to evaluate the analytical performance and status of SARS-CoV-2 antigen tests. METHODS: The EQA panel included ten lyophilized samples containing serial 5-fold dilutions of inactivated SARS-CoV-2-positive supernatants of the Omicron BA.1 and BA.5 strains and negative samples, which were classified into "validating" samples and "educational" samples. Data were analyzed according to qualitative results for each sample. RESULTS: A total of 339 laboratories in China participated in this EQA scheme, and 378 effective results were collected. All validating samples were correctly reported by 90.56 % (307/339) of the participants and 90.21 % (341/378) of the datasets. The positive percent agreement (PPA) was >99 % for samples with concentrations of 2 × 107 copies/mL but was 92.20 % (697/756) for 4 × 106 copies/mL and 25.26 % (382/1,512) for 8 × 105 copies/mL samples. Colloidal gold was the most frequently used (84.66 %, 320/378) but showed the lowest PPAs (57.11 %, 1,462/2,560) for positive samples compared with fluorescence immunochromatography (90 %, 36/40) and latex chromatography (79.01 %, 335/424). Among 11 assays used in more than 10 clinical laboratories, ACON showed a higher sensitivity than other assays. CONCLUSIONS: The EQA study can help to validate whether it's necessary to update antigen detection assays for manufacturers and provide participants with information about the performance of assays to take the first step toward routine post-market surveillance.

Association of Ambient Temperature With the Prevalence of Intimate Partner Violence Among Partnered Women in Low- and Middle-Income South Asian Countries.

Importance: Intimate partner violence (IPV), including physical, sexual, and emotional violence, constitutes a critical public health problem, particularly in low- and middle-income countries. While climate change could escalate violent events, data quantifying its possible association with IPV are scant. Objective: To evaluate the association of ambient temperature with the prevalence of IPV among partnered women in low- and middle-income countries in South Asia, and to estimate the association of future climate warming with IPV. Design, Setting, and Participants: This cross-sectional study used data from the Demographic and Health Survey and included 194 871 ever-partnered women aged 15 to 49 years from 3 South Asian countries (India, Nepal, and Pakistan). The study applied the mixed-effect multivariable logistic regression model to investigate the association of ambient temperature with IPV prevalence. The study further modeled the change in IPV prevalence under various future climate change scenarios. The data included in the analyses were collected from October 1, 2010, to April 30, 2018, and the current analyses were performed from January 2, 2022, to July 11, 2022. Exposure: Annual ambient temperature exposure for each woman, estimated based on an atmospheric reanalysis model of the global climate. Main Outcomes and Measures: The prevalence of IPV and its types (physical, sexual, and emotional violence) were assessed based on self-reported questionnaires from October 1, 2010, to April 30, 2018, and the changes in the prevalence with climate changes were estimated through the 2090s. Results: The study included 194 871 ever-partnered women aged 15 to 49 years (mean [SD] age, 35.4 [7.6] years; overall IPV prevalence, 27.0%) from 3 South Asian countries. The prevalence of physical violence was highest (23.0%), followed by emotional (12.5%), and sexual violence (9.5%). The annual temperature ranges were mostly between 20 °C and 30 °C. A significant association was found between high ambient temperature and the prevalence of IPV against women, with each 1 °C increase in the annual mean temperature associated with a mean increase in IPV prevalence of 4.49% (95% CI, 4.20%-4.78%). According to the study's projections under the unlimited emissions scenarios (SSPs [shared socioeconomic pathways], as defined by the Intergovernmental Panel on Climate Change] 5-8.5), IPV prevalence would increase by 21.0% by the end of the 21st century, while it would only moderately increase under increasingly stricter scenarios (SSP2-4.5 [9.8%] and SSP1-2.6 [5.8%]). In addition, the projected increases in the prevalence of physical (28.3%) and sexual (26.1%) violence were greater than that of emotional violence (8.9%). In the 2090s, India was estimated to experience the highest IPV prevalence increase (23.5%) among the 3 countries, compared with Nepal (14.8%) and Pakistan (5.9%). Conclusions and Relevance: This cross-sectional, multicountry study provides ample epidemiological evidence to support that high ambient temperature may be associated with the risk of IPV against women. These findings highlight the vulnerabilities and inequalities of women experiencing IPV in low- and middle-income countries in the context of global climate warming.

Does economic agglomeration improve agricultural green total factor productivity? Evidence from China's Yangtze river delta.

Economic agglomeration plays an important role in China's social transformation process of industry feeding agriculture and urban supporting rural areas, and is one of the core weapons to promote agricultural economic growth and green and efficient development. Based on panel data of 41 cities in the Yangtze River Delta (YRD) from 2010 to 2020, this paper constructs an "environment-resource-energy-economy" agricultural input-output system, taking into account carbon emissions and surface pollution, and provides a more comprehensive accounting of agricultural green total factor productivity (AGTFP), the non-linear effects of economic agglomeration on AGTFP and shock responses were empirically analyzed using a panel threshold model and a panel vector autoregression (VAR), respectively. The findings show that: (1) during the period 2010-2020, the AGTFP in the YRD showed an overall rising trend with regional spatial agglomeration characteristics. (2) Economic agglomeration has a triple threshold effect on AGTFP, which was a weak facilitative effect in the early stage, inhibited by the siphoning effect of resource loss and arable land fragmentation in the growth stage, promoted by the radiation effect of external increasing return to scale in the form of sharing, matching and learning in the maturity stage, and finally tends to decline. (3) The shock response of economic agglomeration to AGTFP showed a continuous positive shock, peaking in the first period and then gradually converging to zero. (4) The heterogeneity analysis demonstrated that economic agglomeration has a considerable impact on boosting AGTFP in non-metropolitan areas and cities on the outskirts of YRD. In the future, China should effectively play a positive role in economic agglomeration on AGTFP and enhance the mutual coordination of economic agglomeration and agricultural green development in the process of urban cluster economic growth.

The role of employee psychological stress assessment in reducing human resource turnover in enterprises.

In this paper, the model is constructed by measuring the psychological stress condition of employees; the psychological stress condition measurement model analyzes and tests the reasons for reducing human resource turnover in enterprises. In this paper, through the research related to the problem of talent loss in enterprises, we found that enterprises of other ownership often use the talent loss early warning model, to measure the possibility of talent loss in enterprises and issue an early warning, which enables enterprises to solve the talent loss crisis in time and minimize the negative impact of talent loss on enterprises. In this paper, we analyze the causes of human resource attrition risk from a theoretical point of view, construct a system of human resource attrition risk indicators for enterprises, and explain the content of each technical indicator and its measurement method. The PLS structural equation of the HR attrition risk evaluation model is established based on the constructed risk index system. In addition, the analysis of the causes of human resources turnover risk in the company also proposes strategies to avoid and prevent the threat. The PLS structural equation evaluation model of HR turnover risk is applied to various situations of human resource management to analyze the case of the comprehensive evaluation of HR turnover risk to guide the practical application of the model. Therefore, the research results of this paper have significant reference value for enterprises to solve similar human resource attrition problems. At the same time, it will provide a reference for enterprises to improve their human resource diagnostic capability and promote the development of human resource management.

Screening of miRNAs in White Blood Cell as a Radiation Biomarkers for Rapid Assessment of Acute Radiation Injury.

Accidental radiation exposure is a threat to human health that necessitates effective clinical diagnosis. Suitable biomarkers are urgently needed for early assessment of exposure dose. Existing technologies being used to assess the extent of radiation have notable limitations. As a radiation biomarker, miRNA has the advantages of simple detection and high throughput. In this study, we screened for miRNAs with dose and time dependent responses in peripheral blood leukocytes via miRNA sequencing in establishing the animal model of acute radiation injury. Four radiation-sensitive and stably expressed miRNAs were selected out in the 24 h group of leukocyte miRNAs: mmu-miR-130b-5p, mmu-miR-148b-5p, mmu-miR-184-3p, mmu-miR-26a-2-3p, and five were screened in the 48 h group of leukocyte miRNAs: mmu-miR-130b-5p, mmu-miR-423-5p, mmu-miR-676-3p, mmu-miR-150-5p, mmu-miR-342-3p.The correlation curves between their expression and irradiation dose were plotted. Then, the results were validated by RT-qPCR in mouse peripheral blood. As a result, mmu-miR-150-5p and mmu-miR-342-3p showed the highest correlation at 48h after irradiation, and mmu-miR-130b-5p showed good correlation at both 24 h and 48 h after irradiation. In a conclusion, the miRNAs that are sensitive to ionizing radiation with dose dependent effects were selected out, which have the potential of forming a rapid assessment scheme for acute radiation injury.

The hidden performance costs of professional isolation? A latent change score model of professional isolation during the early stage of COVID-19 pandemic.

Although past research has found that professional isolation can affect discernible work-related outcomes (e.g. job performance and turnover) and important job attitudes, researchers have not examined its impact on those less discernible but still costly work behaviours. Drawing on self-regulation theories, this study examined the effect of professional isolation on employees' cyberloafing and time theft through self-control capacity impairment. With longitudinal data collected from 343 U.S. employees across five consecutive weeks at the early stage of the pandemic (i.e. from mid-March to late April 2020), our results of latent change score modelling analyses found that professional isolation change was positively related with changes in cyberloafing and time theft via change in self-control capacity impairment. The results increase our understanding of the hidden performance cost of professional isolation. This research also shifts the research focus from a static, between-person perspective to dynamic, within-person changes in professional isolation and related outcomes. The findings shed light on the self-regulation perspective in understanding the harmful consequences of professional isolation. Implications for future research are discussed along with practical implications for organisations.

Low Cost, Easily-Assembled Centrifugal Buoyancy-Based Emulsification and Digital PCR.

Microfluidic-based droplet generation approaches require the design of microfluidic chips and a precise lithography process, which require skilled technicians and a long manufacturing time. Here we developed a centrifugal buoyancy-based emulsification (CBbE) method for producing droplets with high efficiency and minimal fabrication time. Our approach is to fabricate a droplet generation module that can be easily assembled using syringe needles and PCR tubes. With this module and a common centrifuge, high-throughput droplet generation with controllable droplet size could be realized in a few minutes. Experiments showed that the droplet diameter depended mainly on centrifugal speed, and droplets with controllable diameter from 206 to 158 µm could be generated under a centrifugal acceleration range from 14 to 171.9 g. Excellent droplet uniformity was achieved (CV < 3%) when centrifugal acceleration was greater than 108 g. We performed digital PCR tests through the CBbE approach and demonstrated that this cost-effective method not only eliminates the usage of complex microfluidic devices and control systems but also greatly suppresses the loss of materials and cross-contamination. CBbE-enabled droplet generation combines both easiness and robustness, and breaks the technical challenges by using conventional lab equipment and supplies.

Unveiling the mechanism of imidacloprid removal by ferrate(VI): Kinetics, role of oxidation and adsorption, reaction pathway and toxicity assessment.

Imidacloprid (IMI), an emerging pollutant, has high toxicity to non-target organisms. This paper presents the kinetics of IMI removal by ferrate(VI) at different pH (6.0-9.0), molar ratios ([ferrate(VI)]:[IMI]) and added Fe(III) ions. The apparent second-order rate constant (kapp) decreased with increase in pH from pH 6.0 to 9.0 (i.e., (1.2 ± 0.1) × 102 M-1 s-1 to (8.3 ± 0.3) M-1 s-1). The species-specific rate constants were obtained as k (HFeO4-) = 1.3 × 102 M-1 s-1 and k (FeO42-) = 6.9 M-1 s-1. The decreases in the concentration of HFeO4- with increase in pH caused the observed pH dependence in kapp. At pH 7.0, the removal of IMI increased with the molar ratio from 1.0 to 10.0 with complete removal at the highest ratio. The variation in pH from 6.0 to 9.0 had no obvious effect on removal of IMI. Experiments indicate that IMI removal is mainly by ferrate(VI) oxidation and to a lesser extent by Fe(III) adsorption. Mineralization of IMI was also observed (20-26%). The addition of Fe(III) ions to ferrate(VI)-IMI at pH 7.0 and 8.0 resulted in enhanced removal of IMI, but the presence of Ca2+, SO42-, HCO3-, and humic acid (HA) has negative effects. The presence of coexisting substances in river water slightly decreased IMI removal by ferrate(VI) by less than 10%. Identification of products and frontier electron density (FED) calculations demonstrated involvement of opening of the five-membered heterocyclic moiety of IMI by ferrate(VI). Toxicity assessment with NIH 3T3 fibroblasts and ECOSAR analysis indicated lower toxicity of oxidized products than parent IMI.

Sociodemographic Factors Associated With HIV/HCV High-Risk Behaviors Among People Who Use Drugs on Methadone Maintenance Treatment: A 10-Year Observational Study.

Background: Sociodemographic factors have an impact worldwide on the behavior of people who use drugs (PWUD). This study attempts to clarify the sociodemographic factors related to HIV/HCV high-risk behaviors (injection drug use, syringe sharing, and multiple sex partners) among PWUD on methadone maintenance treatment (MMT) in the long term. Methods: The 13,300 PWUD recruited into the MMT program were followed during 2006-2015. Generalized estimating equations were used to examine the relationship between sociodemographic characteristics and HIV/HCV high-risk behaviors. Results: We found that male (vs. female), living alone (vs. living with family or relatives), temporary income, financial support from family/friends, and financial support from social welfare (vs. regular salary) were positively associated with injection drug use. Age of initial drug use was negatively associated with injection drug use and syringe sharing. For both genders, being unmarried (vs. married or in cohabitation), living with friends, living alone (vs. living with family or relatives), temporary income, financial supports from family/friends (vs. regular salary), being employed (vs. unemployed/between jobs) was positively associated. In contrast, age at baseline was negatively associated with having multiple sexual partners for both genders. Ethnic of non-Han (vs. Han) was positively associated with having multiple sexual partners simply for males. Being divorced or widowed (vs. married or cohabitated) was positively associated with having multiple sexual partners merely for females. Conclusion: HIV/HCV high-risk behaviors correlated with certain sociodemographic factors of PWUD receiving MMT. There is a need for improving the well-being, employment, and housing status of PWUD on MMT to reduce their HIV/HCV risk behaviors.

NeuralDAO: Incorporating neural network generated dose into direct aperture optimization for end-to-end IMRT planning.

PURPOSE: Thecurrent practice in intensity-modulated radiation therapy (IMRT) planning almost always includes different dose calculation strategies for plan optimization and final dose verification. The accurate Monte Carlo (MC) dose algorithm is considered to be time-consuming for the optimization. Thus a fast, simplified dose algorithm is used in the optimization. The significant differences between the optimized dose and the delivered dose lead to tediously planning loops and potentially suboptimal solutions. This work aims to develop an IMRT optimization algorithm to minimize the dose discrepancy so that the delivered dose can be optimized in a holistic, end-to-end manner. METHODS: The proposed algorithm, namely NeuralDAO, integrates a neural dose network into the column generation (CG) direct aperture optimization (DAO) formulation for step-and-shoot IMRT planning. The neural dose network is designed and trained to produce doses of MC-level accuracy within few milliseconds. Its differentiability is fully exploited to compute gradients for identifying potential aperture shapes. A prototype of NeuralDAO was developed in PyTorch and available to the public. Five lung patient cases have been studied. Dosimetric accuracy was compared with the MC dose. Plan quality and time were compared with a state-of-the-art (SoA) dose-correct algorithm. Statistical analysis was performed by Wilcoxon signed-rank test. RESULTS: The average gamma passing rate at 2 mm/2% is 99.7% between the optimized and delivered doses. The convergence process produced by NeuralDAO is virtually identical to that produced by an MC-based DAO. The average dose calculation time is 12.1 ms for an aperture on GPU. One session of optimization took 10-36 min. Compared with the SoA, better conformity index and homogeneity index were observed for the target. The esophagus was significantly spared. Significant reductions were observed for the replanning number and the planning time. CONCLUSIONS: A new DAO algorithm based on the neural dose network has been developed. The results suggest that this algorithm minimizes the discrepancy between the optimized and delivered doses, which offers a promising approach to reduce the time and effort required in IMRT planning. This work demonstrates the possibility of applying the neural network in IMRT optimization. It is of great potential to extend this algorithm to other treatment modalities.

Recent advances and perspectives in efforts to reduce the production and application cost of microbial flocculants.

Microbial flocculants are macromolecular substances produced by microorganisms. Due to its non-toxic, harmless, and biodegradable advantages, microbial flocculants have been widely used in various industrial fields, such as wastewater treatment, microalgae harvest, activated sludge dewatering, heavy metal ion adsorption, and nanoparticle synthesis, especially in the post-treatment process of fermentation with high safety requirement. However, compared with the traditional inorganic flocculants and organic polymeric flocculants, the high production cost is the main bottleneck that restricts the large-scale production and application of microbial flocculants. To reduce the production cost of microbial flocculant, a series of efforts have been carried out and some exciting research progresses have been achieved. This paper summarized the research advances in the last decade, including the screening of high-yield strains and the construction of genetically engineered strains, search of cheap alternative medium, the extraction and preservation methods, microbial flocculants production as an incidental product of other biological processes, combined use of traditional flocculant and microbial flocculant, and the production of microbial flocculant promoted by inducer. Moreover, this paper prospects the future research directions to further reduce the production cost of microbial flocculants, thereby promoting the industrial production and large-scale application of microbial flocculants.

Sampling and refinement protocols for template-based macrocycle docking: 2018 D3R Grand Challenge 4.

We describe a new template-based method for docking flexible ligands such as macrocycles to proteins. It combines Monte-Carlo energy minimization on the manifold, a fast manifold search method, with BRIKARD for complex flexible ligand searching, and with the MELD accelerator of Replica-Exchange Molecular Dynamics simulations for atomistic degrees of freedom. Here we test the method in the Drug Design Data Resource blind Grand Challenge competition. This method was among the best performers in the competition, giving sub-angstrom prediction quality for the majority of the targets.

Measuring DNA Hybridization Kinetics in Live Cells Using a Time-Resolved 3D Single-Molecule Tracking Method.

Single-molecule detection enables direct characterization of annealing/melting kinetics of nucleic acids without the need for synchronization of molecular states, but the current experiments are not carried out in a native cellular context. Here we describe an integrated 3D single-molecule tracking and lifetime measurement method that can follow individual DNA molecules diffusing inside a mammalian cell and observe multiple annealing and melting events on the same molecules. By comparing the hybridization kinetics of the same DNA strand in vitro, we found the association constants can be 13- to 163-fold higher in the molecular crowding cellular environment.

Recovery Degree of the Natural Flow Regimes and the Corresponding Economic Costs for Reservoir Operation in Fish Spawning Seasons.

The construction of large-scale reservoirs alters the natural flow process downstream and inevitably affects the aquatic organism. Current studies have verified that flow regimes play an important role in fish spawning stimulus. Recovery of the flow regimes may be incompatible with the economic benefit, mainly referring to hydropower generation. In this study, multiple models are established to study the relationship between the recovery degree of the natural flow regimes and the cost of the hydropower generation in spawning season for different hydrological years. The flow regimes are first quantitatively described by three characteristic parameters including the number of floods, the average duration of each flood, and the daily increment of the natural flow. The model for ecological operation needs to approach these characteristics as close as possible, while the model for economic benefit is set to generate power as much as possible. The ecological flow constraint is also considered to shape the flow process pattern. The proposed methodology is applied on the upper reaches of the Yellow River, where a large-scale reservoir is under planning. Different schemes are compared for different hydrological years to answer the question that to what extent can we recover the flow regime by reservoir operation, and how much the corresponding economic cost is.

Flux of organic carbon burial and carbon emission from a large reservoir: implications for the cleanliness assessment of hydropower.

Accurately quantifying the budget of carbon sources and sinks in hydropower reservoirs is important for evaluating the cleanliness of hydroelectricity. However, current research on carbon emissions from reservoirs has rarely taken into account the organic carbon (OC) buried in sediment. Only greenhouse gas emissions from the water-air interface at reservoirs have been examined, which would result in an overestimation of the greenhouse effect of reservoirs. In November 2017, this study investigated the distribution of sediment in the Hongfeng Reservoir (HFR) in southwest China, a typical large hydropower reservoir, by using an underwater seismology monitoring system. We estimated the flux of OC into sediment using the results of a sediment survey and a dataset compiled from references. Our results show that, the HFR retained 200,715 t of OC in the sediment since its impounding after dam construction to the sampling year of 2017, when the average burial flux was 3,521 t-C a-1 (106 g C a-1) and the modern burial flux was 5,449 t-C a-1. After excluding the exogenous OC, the modern valid carbon sink of the sediment was 4,632 t per year. Under the current state of the reservoir, taking the modern valid carbon sink value, the carbon emissions from the reservoir's surface, and the discharge water from the dam into consideration, the net carbon sink of the HFR is found to be 1,098.9 t-C a-1. If the hydroelectricity generated by the reservoir is converted to a carbon sink, then the total net carbon sink becomes 12,972.9 t-C a-1. This work argues that both reservoir sediment and hydroelectricity are important carbon sinks and both should be included in assessments of the greenhouse effects of reservoirs.