Numerical Modeling of Mineralizing Processes During the Formation of the Yangzhuang Kiruna-Type Iron Deposit, Middle and Lower Yangtze River Metallogenic Belt, China: Implications for the Genesis and Longevity of Kiruna-Type Iron Oxide-Apatite Systems

The Yangzhuang iron deposit is a Kiruna-type iron oxide-apatite (IOA) deposit within the Ningwu mining district of the Middle and Lower Yangtze River Metallogenic Belt (MLYRMB), China. This study applies a numerical modeling approach to identify the key processes associated with the formation of the deposit that cannot be easily identified using traditional analytical approaches, including the duration of the mineralizing process and the genesis of iron orebodies within intrusions associated with the deposit. This approach highlights the practical value of numerical modeling in quantitatively analyzing mineralizing processes during the formation of mineral deposits and assesses how these methods can be used in future geological research. Our numerical model links heat transfer, pressure, fluid flow, chemical reactions, and the movement of ore-forming material. Results show that temperature anomaly and structure (occurrence of the contact of intrusion and the Triassic Xujiashan group) are two key factors controlling the formation of the Yangzhuang deposit. This modeling also indicates that the formation of the Yangzhuang deposit only took some 8000 years, a reaction that is likely to be controlled by temperature and diffusion rates within the system. The dynamic changes of temperature and the distribution of mineralization also indicate that the orebodies located inside the intrusions most likely formed after magma ascent rather than representing blocks of existing mineralization that descended into the magma as a result of stoping or other similar processes. All these data form the basis for future research into the forming processes of Kiruna-type IOA systems as well as magmatic–hydrothermal systems more broadly, including providing useful insights for future exploration for these systems. The simulation approach used in this study has several limitations, such as oversimplified chemical reactions, uncertainty of pre-metallogenic conditions and limitation of 2D model. Future development into both theories and methods will definitely improve the practical significance of numerical simulation of ore-forming processes and provide quantitative results for more geological issues

New dinosaur egg material from Yunxian, Hubei Province, China resolves the classification of dendroolithid eggs

The oofamily Dendroolithidae is a distinct group of dinosaur eggs reported from China and Mongolia, which is characterized by branched eggshell units and irregular pore canals. The ootaxonomic inferences, however, were rarely discussed until now. A colonial nesting site was recently uncovered from the Qinglongshan region, Yunxian, Hubei Province, China. More than 30 dendroolithid egg clutches outcrop on the Tumiaoling Hill, including an extremely gigantic clutch containing 77 eggs. All clutches were exposed in the Upper Cretaceous fluvial-deposited Gaogou For mation. In this study, we emend the diagnosis of the oogenus Placoolithus and assign all dendroolithid eggs from the Tumiaoling Hill to a newly emended oospecies Placoolithus tumiaolingensis that shows greatly variable eggshell microstructure. Moreover, our study also disentangles the previous vexing classification of dendroolithid eggs. We conclude that Dendroolithus tumiaolingensis, D. hongzhaiziensis, and Paradendroolithus qinglongshanensis, all of which were previously reported from Yunxian, should be assigned to the newly emended oospecies Placoolithus tumiaolingensis

A Novel Scheme for Image Encryption Based on Piecewise Linear Chaotic Map

Abstract-Recently, the chaos based cryptographic algorithms have suggested some meaningful techniques to develop efficient image encryption schemes. In this paper, we propose a new digital image encryption scheme based on the piecewise linear chaotic map (PWLCM) in order to meet the requirements of the secure encryption. The proposed scheme is described in detail, along with the security analyses including key space analysis, sensitivity analysis, information entropy analysis and differential attack analysis. The results show that the suggested image encryption scheme has some properties desirable in a good security cryptosystem

Evaluation of Tolerability, Pharmacokinetics and Pharmacodynamics of Vicagrel, a Novel P2Y12 Antagonist, in Healthy Chinese Volunteers

Background: Vicagrel is a novel anti-platelet drug and hydrolyzed to the same intermediate as clopidogrel via esterase, instead of CYP2C19. Here we report the first clinical trial on the tolerability, pharmacokinetics and pharmacodynamics of different doses of vicagrel, and comparison with clopidogrel in healthy Chinese volunteers.Methods: This study was conducted in two parts. Study I was a dose-escalating (5–15 mg) study. For each dose, 15 participants were randomized into three groups (total n = 45); nine participants were given vicagrel, three were given clopidogrel, and three were given a placebo. Study II was conducted to assess interactions between vicagrel and aspirin in 15 healthy participants. The plasma concentrations of the metabolites of vicagrel and clopidogrel were determined using a LC-MS/MS method. Platelet aggregation was assessed using the VerifyNow-P2Y12 assay.Results: Vicagrel (5–15 mg per day) dosing for 10 days or addition of aspirin was well tolerated in healthy volunteers. The exposure of the active metabolite increased proportionally across the dose range and was higher (~10-fold) than clopidogrel. The levels of IPA dosing 75 mg clopidogrel were between the responses of 5 mg and 10 mg vicagrel. After a single loading dose of vicagrel (30 mg) and a once-daily maintenance dose (7.5 mg) for 8 days, the maximum inhibition of platelet aggregation was similar to that seen with the combined use of vicagrel and aspirin (100 mg/day).Conclusion: Oral vicagrel demonstrated a favorable safety profile and excellent anti-platelet activity, which could be a promising P2Y12 antagonist as anti-platelet drug and can be further developed in phase II/III studies, and marketing for the unmet medical needs of cardiovascular diseases. The study was registered at http://www.chictr.org.cn (ChiCTR-IIR-16009260)

Multiple cystic echinococcosis in abdominal and pelvic cavity treated by surgery with a 4-year follow-up: a case report

We report a case of a male patient who presented with multiple abdominal and pelvic echinococcosis. The patient had been diagnosed with hepatic echinococcosis for 7 years and developed intermittent distension and discomfort in the upper abdomen after an accidental fall. In recent years, the patient’s abdominal distention increased gradually. Computed tomography revealed multiple hydatid cysts in the liver, spleen, abdominal cavity, and pelvic cavity. Abdominal organs were severely compressed, such that he could not eat normally except for a liquid diet. The patient underwent radical surgical resection based on the multi-disciplinary treatment (MDT) and the operation lasted 10 h, nearly 100 hydatid cysts were excised, about 18 liters of cyst fluid and cyst contents were removed, and the patient lost 20 kg of weight after surgery. The operation was successful, but there were still some postoperative complications such as hypovolemic shock, postoperative ascites, postoperative bile leakage. Treatment measures for the patient were anti-infection, antishock, clamping the abdominal drainage tube, and negative pressure abdominal puncture drainage. At follow up the patient’s quality of life had been significantly improved with 15 kg weight gain compared to before

Metagenomic Analysis of Bacteria, Fungi, Bacteriophages, and Helminths in the Gut of Giant Pandas

To obtain full details of gut microbiota, including bacteria, fungi, bacteriophages, and helminths, in giant pandas (GPs), we created a comprehensive microbial genome database and used metagenomic sequences to align against the database. We delineated a detailed and different gut microbiota structures of GPs. A total of 680 species of bacteria, 198 fungi, 185 bacteriophages, and 45 helminths were found. Compared with 16S rRNA sequencing, the dominant bacterium phyla not only included Proteobacteria, Firmicutes, Bacteroidetes, and Actinobacteria but also Cyanobacteria and other eight phyla. Aside from Ascomycota, Basidiomycota, and Glomeromycota, Mucoromycota, and Microsporidia were the dominant fungi phyla. The bacteriophages were predominantly dsDNA Myoviridae, Siphoviridae, Podoviridae, ssDNA Inoviridae, and Microviridae. For helminths, phylum Nematoda was the dominant. In addition to previously described parasites, another 44 species of helminths were found in GPs. Also, differences in abundance of microbiota were found between the captive, semiwild, and wild GPs. A total of 1,739 genes encoding cellulase, β-glucosidase, and cellulose β-1,4-cellobiosidase were responsible for the metabolism of cellulose, and 128,707 putative glycoside hydrolase genes were found in bacteria/fungi. Taken together, the results indicated not only bacteria but also fungi, bacteriophages, and helminths were diverse in gut of giant pandas, which provided basis for the further identification of role of gut microbiota. Besides, metagenomics revealed that the bacteria/fungi in gut of GPs harbor the ability of cellulose and hemicellulose degradation

Genetic Evaluation of 114 Chinese Short Stature Children in the Next Generation Era: a Single Center Study

Background/Aims: The genetics of human height is a frequently studied and complex issue. However, there is limited genetic research of short stature. To uncover the subgroup of patients to have higher yield and to propose a simplified diagnostic algorithm in the next generation era. Methods: This study included 114 Chinese children with height SDS ≤ -2.5 and unknown etiology from 2014 to 2015. Target/whole exome sequencing (referred as NGS) and chromosomal microarray analysis (CMA) were performed on the enrolled patients sequentially to identify potential genetic etiologies. The samples solved by NGS and CMA were retrospectively studied to evaluate the clinical pathway of the patients following a standard diagnostic algorithm. Results: In total, a potential genetic etiology was identified in 41 (36%) patients: 38 by NGS (33.3%), two by CMA (1.8%), and an additional one by both (0.9%). There were 46 different variants in 29 genes and 2 pathogenic CNVs identified. The diagnostic yield was significantly higher in patients with facial dysmorphism or skeletal abnormalities than those without the corresponding phenotype (P=0.006 and P=0.009, respectively, Pearson’s χ2 test). Retrospectively study the cohort indicate 83.3% patients eventually would be evaluated by NGS/CMA. Conclusion: This study confirms the utility of high-throughput molecular detection techniques for the etiological diagnosis of undiagnosed short stature and suggests that NGS could be used as a primary diagnostic strategy. Patients with facial dysmorphism and/or skeletal abnormalities are more likely to have a known genetic etiology. Moving NGS forward would simplified the diagnostic algorithm

Incidence and Etiology of Drug-Induced Liver Injury in Mainland China

Background & Aims: We performed a nationwide, retrospective study to determine the incidence and causes of drug-induced liver injury (DILI) in mainland China.Methods: We collected data on a total of 25,927 confirmed DILI cases, hospitalized from 2012 through 2014 at 308 medical centers in mainland China. We collected demographic, medical history, treatment, laboratory, disease severity, and mortality data from all patients. Investigators at each site were asked to complete causality assessments for each case whose diagnosis at discharge was DILI (n=29,478) according to the Roussel Uclaf Causality Assessment Method.Results: Most cases of DILI presented with hepatocellular injury (51.39%; 95% CI, 50.76–52.03), followed by mixed injury (28.30%; 95% CI, 27.73–28.87) and cholestatic injury (20.31%; 95% CI, 19.80–20.82). The leading single classes of implicated drugs were traditional Chinese medicines or herbal and dietary supplements (26.81%) and anti-tuberculosis medications (21.99%). Chronic DILI occurred in 13.00% of the cases and, although 44.40% of the hepatocellular DILI cases fulfilled Hy’s Law criteria, only 280 cases (1.08%) progressed to hepatic failure, 2 cases underwent liver transplantation (0.01%), and 102 patients died (0.39%). Among deaths, DILI was judged to have a primary role in 72 (70.59%), a contributory role in 21 (20.59%), and no role in 9 (8.82%). Assuming the proportion of DILI in the entire hospitalized population of China was represented by that observed in the 66 centers where DILI capture was complete, we estimated the annual incidence in the general population to be 23.80 per 100,000 persons (95% CI, 20.86–26.74). Only hospitalized patients were included in this analysis, so the true incidence is likely to be higher.Conclusions: In a retrospective study to determine the incidence and causes of drug-induced liver injury (DILI) in mainland China, the annual incidence in the general population was estimated to be 23.80 per 100,000 persons—higher than that reported from western countries. Traditional Chinese medicines, herbal and dietary supplements, and anti-tuberculosis drugs were the leading causes of DILI in mainland Chin

Modeling Evapotranspiration Response to Climatic Forcings Using Data-Driven Techniques in Grassland Ecosystems

Remarkable progress has been made over the last decade toward characterizing the mechanisms that dominate the exchange of water vapor between the biosphere and the atmosphere. This is attributed partly to the considerable development of machine learning techniques that allow the scientific community to use these advanced tools for approximating the nonlinear processes affecting the variation of water vapor in terrestrial ecosystems. Three novel machine learning approaches, namely, group method of data handling, extreme learning machine (ELM), and adaptive neurofuzzy inference system (ANFIS), were developed to simulate and forecast the daily evapotranspiration (ET) at four different grassland sites based on the flux tower data using the eddy covariance method. These models were compared with the extensively utilized data-driven models, including artificial neural network, generalized regression neural network, and support vector machine (SVM). Moreover, the influences of internal functions on their corresponding models (SVM, ELM, and ANFIS) were investigated together. It was demonstrated that most developed models did good job of simulating and forecasting daily ET at the four sites. In addition to strengths of robustness and simplicity, the newly proposed methods achieved the estimates comparable to those of the conventional approaches and accordingly can be used as promising alternatives to traditional methods. It was further discovered that the generalization performance of the ELM, ANFIS, and SVM models strongly depended on their respective internal functions, especially for SVM

Comprehensive Evaluation of Machine Learning Techniques for Estimating the Responses of Carbon Fluxes to Climatic Forces in Different Terrestrial Ecosystems

Accurately estimating the carbon budgets in terrestrial ecosystems ranging from flux towers to regional or global scales is particularly crucial for diagnosing past and future climate change. This research investigated the feasibility of two comparatively advanced machine learning approaches, namely adaptive neuro-fuzzy inference system (ANFIS) and extreme learning machine (ELM), for reproducing terrestrial carbon fluxes in five different types of ecosystems. Traditional artificial neural network (ANN) and support vector machine (SVM) models were also utilized as reliable benchmarks to measure the generalization ability of these models according to the following statistical metrics: coefficient of determination (R2), index of agreement (IA), root mean square error (RMSE), and mean absolute error (MAE). In addition, we attempted to explore the responses of all methods to their corresponding intrinsic parameters in terms of the generalization performance. It was found that both the newly proposed ELM and ANFIS models achieved highly satisfactory estimates and were comparable to the ANN and SVM models. The modeling ability of each approach depended upon their respective internal parameters. For example, the SVM model with the radial basis kernel function produced the most accurate estimates and performed substantially better than the SVM models with the polynomial and sigmoid functions. Furthermore, a remarkable difference was found in the estimated accuracy among different carbon fluxes. Specifically, in the forest ecosystem (CA-Obs site), the optimal ANN model obtained slightly higher performance for gross primary productivity, with R2 = 0.9622, IA = 0.9836, RMSE = 0.6548 g C m−2 day−1, and MAE = 0.4220 g C m−2 day−1, compared with, respectively, 0.9554, 0.9845, 0.4280 g C m−2 day−1, and 0.2944 g C m−2 day−1 for ecosystem respiration and 0.8292, 0.9306, 0.6165 g C m−2 day−1, and 0.4407 g C m−2 day−1 for net ecosystem exchange. According to the findings in this study, we concluded that the proposed ELM and ANFIS models can be effectively employed for estimating terrestrial carbon fluxes