bluuebunny/crossref_metadata_2025 huggingface dataset:
Case report: Evaluation of myocardial microcirculation in patients with breast cancer after anthracycline chemotherapy by using intravoxel incoherent motion imaging
Authors: Li Shilan , Tian Di , Li Xin , Li Jia , Song Qingwei , Xia Yunlong , Li Zhiyong
Published: September 2022

Introduction

Anthracycline chemotherapy drugs can produce cardiotoxicity in patients with breast cancer, leading to myocardial cell death and fibrosis, further developing into cardiac failure. However, the condition of myocardial microcirculation was unknown in breast cancer after anthracycline chemotherapy. As a result, intravoxel incoherent motion (IVIM) imaging was used to non-invasively observe the condition of myocardial microcirculation in a patient with breast cancer after anthracycline chemotherapy.

Case report

A 43-year-old female patient with a right breast lump was reported. Preoperative ultrasound-guided needle biopsy showed invasive carcinoma of the right breast with fibroadenoma. Sentinel lymph node biopsy combined with simplified radical surgery for right breast cancer was performed. Postoperative pathological findings reported breast cancer (pT2N2M0 IIIA). The patient underwent eight sessions of the EC-TH chemotherapy scheme, and the EC and the TH schemes were adopted for the first four sessions and the last four sessions, respectively. During chemotherapy, during which there was the occurrence of Grade II myelosuppression, chest CT and abdomen CT showed no metastasis, and ECG and cardiac ultrasound reports returned to normal. Cardiac cine magnetic resonance and IVIM imaging were performed at the beginning of the first chemotherapy session (baseline) and after the third, fifth, and eighth chemotherapy sessions, respectively. We found that the fast apparent diffusion coefficient (ADCfast) and f parameters appeared to show a downward trend from the baseline to the fifth chemotherapy session, where the IVIMfast values declined from 163 × 10−3 mm2/s to 148 × 10−3 mm2/s and finally to 134 × 10−3 mm2/s and f values declined from 45% to 36% and then to 30%, respectively. ADCfast and f values showed an inclination from the fifth and eighth chemotherapy sessions.

Conclusion

Our case report showed that IVIM technology can likely detect non-invasive myocardial microcirculation early and quantitatively after anthracycline chemotherapy in patients with breast cancer. That is, IVIM technology seems to be helpful for cardiovascular risk monitoring and prognosis assessment of myocardial microcirculation in patients with breast cancer after anthracycline chemotherapy.
Cardiovascular disease and chimeric antigen receptor cellular therapy
Authors: Rao Anjali , Stewart Andrew , Eljalby Mahmoud , Ramakrishnan Praveen , Anderson Larry D. , Awan Farrukh T. , Chandra Alvin , Vallabhaneni Srilakshmi , Zhang Kathleen , Zaha Vlad G.
Published: September 2022

Chimeric antigen receptor T-cell (CAR T) therapy is a revolutionary personalized therapy that has significantly impacted the treatment of patients with hematologic malignancies refractory to other therapies. Cytokine release syndrome (CRS) is a major side effect of CAR T therapy that can occur in 70–90% of patients, with roughly 40% of patients at grade 2 or higher. CRS can cause an intense inflammatory state leading to cardiovascular complications, including troponin elevation, arrhythmias, hemodynamic instability, and depressed left ventricular systolic function. There are currently no standardized guidelines for the management of cardiovascular complications due to CAR T therapy, but systematic practice patterns are emerging. In this review, we contextualize the history and indications of CAR T cell therapy, side effects related to this treatment, strategies to optimize the cardiovascular health prior to CAR T and the management of cardiovascular complications related to CRS. We analyze the existing data and discuss potential future approaches.
Stimulating myocardial pyruvate dehydrogenase activity fails to alleviate cardiac abnormalities in a mouse model of human Barth syndrome
Authors: Greenwell Amanda A. , Tabatabaei Dakhili Seyed Amirhossein , Gopal Keshav , Saed Christina T. , Chan Jordan S. F. , Kazungu Mugabo Nick , Zhabyeyev Pavel , Eaton Farah , Kruger Jennifer , Oudit Gavin Y. , Ussher John R.
Published: September 2022

Barth syndrome (BTHS) is a rare genetic disorder due to mutations in the TAFAZZIN gene, leading to impaired maturation of cardiolipin and thereby adversely affecting mitochondrial function and energy metabolism, often resulting in cardiomyopathy. In a murine model of BTHS involving short-hairpin RNA mediated knockdown of Tafazzin (TazKD mice), myocardial glucose oxidation rates were markedly reduced, likely secondary to an impairment in the activity of pyruvate dehydrogenase (PDH), the rate-limiting enzyme of glucose oxidation. Furthermore, TazKD mice exhibited cardiac hypertrophy with minimal cardiac dysfunction. Because the stimulation of myocardial glucose oxidation has been shown to alleviate diabetic cardiomyopathy and heart failure, we hypothesized that stimulating PDH activity would alleviate the cardiac hypertrophy present in TazKD mice. In order to address our hypothesis, 6-week-old male TazKD mice and their wild-type (WT) littermates were treated with dichloroacetate (DCA; 70 mM in the drinking water), which stimulates PDH activity via inhibiting PDH kinase to prevent inhibitory phosphorylation of PDH. We utilized ultrasound echocardiography to assess cardiac function and left ventricular wall structure in all mice prior to and following 6-weeks of treatment. Consistent with systemic activation of PDH and glucose oxidation, DCA treatment improved glycemia in both TazKD mice and their WT littermates, and decreased PDH phosphorylation equivalently at all 3 of its inhibitory sites (serine 293/300/232). However, DCA treatment had no impact on left ventricular structure, or systolic and diastolic function in TazKD mice. Therefore, it is unlikely that stimulating glucose oxidation is a viable target to improve BTHS-related cardiomyopathy.
Observational study of the influences of thermal and dynamic boundary layer on the vertical distribution of black carbon aerosol in ShouXian county in wintertime, 2016
Authors: Cheng-gang Wang , Xia-lu Wei , Jia-de Yang , Ting Ni
Published: September 2022

Using vertical observation data of black carbon aerosol and meteorological parameters in the ShouXian area of Anhui Province from 14 December 2016 to 3 January 2017, the thermal and dynamic effects of the boundary layer on the vertical distribution structure of black carbon were studied. The results show that 1) of 82 vertical sounding profiles obtained during the observation period, there were 72 boundary layer sounding profiles dominated by heat and 10 profiles dominated by dynamics. 2) When thermal effects were dominant, the concentration of black carbon aerosol was significantly affected by diurnal changes in the boundary layer. In the unstable boundary layer, black carbon aerosol was uniformly distributed in the vertical direction; during the transition from an unstable to a stable boundary layer, the concentrations of black carbon aerosol were significantly higher in the lower layer than in the upper layer; in the stable boundary layer, the concentrations of black carbon aerosol decreased continuously with height; and during the transition from a stable to an unstable boundary layer, the black carbon aerosol concentrations exhibited high values in the upper layer, with the concentration difference reaching 4 μg m−3. 3) When the dynamic effect was dominant, the structure of the vertical distribution of black carbon aerosol was affected by wind and by diurnal changes in the boundary layer simultaneously. The high winds (>4 m/s) removed the black carbon aerosol. In the unstable boundary layer, the black carbon aerosol uniformly distributed in the vertical direction had significantly lower concentrations in the high-wind range; when stable boundary layers occurred and during transitions from stable to unstable boundary layers, the black carbon aerosol concentrations were higher in the lower layer and lower in the upper layer. The stratification was more obvious than that observed under thermal control.
Sand-ratio distribution in an unconventional tight sandstone reservoir of Hangjinqi area, Ordos Basin: Acoustic impedance inversion-based reservoir quality prediction
Authors: Anees Aqsa , Zhang Hucai , Ashraf Umar , Wang Ren , Thanh Hung Vo , Radwan Ahmed E. , Ullah Jar , Abbasi Ghazanfer Raza , Iqbal Ibrar , Ali Nafees , Zhang Xiaonan , Tan Shucheng , Shi Wanzhong
Published: September 2022

Future gas field development and prospect assessment depend on accurate reservoir parameter characterization. The understanding of the tight sand distribution of the Shanxi and Taiyuan Formations within the Hangjinqi area is ambiguous due to the presence of coal and mudstone lithofacies, high heterogeneity, and poor resolution of the seismic data. Thus, it is difficult to determine the reservoir’s thickness. To cope with this challenge, we have employed the advanced method of constrained sparse spike inversion (CSSI) utilizing 3D seismic and nine wells for the distinction of tight sandstone facies from the coal and mudstone facies. Results of petrophysical analysis of studied well J54 show that the coal and mudstone facies are dominant towards the T9c horizon, whereas tight sandstone facies are present towards the T9d horizon. The obtained findings show that the CSSI accurately identified the spatial distribution of sand-ratio in the zone of interest (ZOI) that lies between the T9c and T9d horizons. The acoustic impedance (AI) of coal shows the lowest AI values, whereas the tight sandstone shows the highest AI values. The tight sandstone facies shows moderate values of AI in the range of 8.5 × 106 kg/m2s to 1.20 × 107 kg/m2s. The impedance map of T9c suggested the presence of coal and mud facies, whereas the T9d impedance map suggest the presence of maximum tight sandstone facies. The sand-ratio map of T9d showed maximum reservoir thickness that ranges from 0.65-0-95, whereas the sand-ratio value mostly ranges from 0 to 0.5 on the T9c map. The maximum sand-ratio values on T9d show that the lower Shanxi Formation has good reservoir characteristics. Whereas, due to the presence of coal and mudstone in the Taiyuan Formation, the T9c map shows low values of sand-ratio. The maximum sand-ratio regions within the targeted T9c-T9d layers should be exploited for future gas explorations.
A Review of Gassy Sediments: Mechanical Property, Disaster Simulation and In-Situ Test
Authors: Liu Tao , Yang Xiaotong , Zhang Yan
Published: September 2022

Gassy sediments are an important cause of engineering disasters such as large-area coastal submarine landslides, excessive tilting of marine foundations, and excessive deformation of tunnels. Under different stress paths, the gassy soil exhibits different microstructure changes and mechanical responses. This paper introduces the current research status regarding the mechanical responses, numerical simulation and the in-situ test methods of gassy sediment. In terms of mechanical responses, it summarized the strength and deformation characteristics of gassy soil under different stress paths, tracking the study on constitutive model. The disaster simulation work using constitutive model of gassy sediment is introduced. It also analyzes the advantages and limitations of various methods in the in-situ test. It can provide theoretical support for further study on disaster prevention and geological risk assessment of gassy sediments.
Temporal variations of the probability distribution of voronoi cells generated by earthquake epicenters
Authors: Rotondi Renata , Varini Elisa
Published: September 2022

The area of the cells of Voronoi tessellations has been modelled through different probability distributions among which the most promising are the generalized gamma and tapered Pareto distributions. In particular the latter has been used to model times and distances between successive earthquakes besides area and perimeter of cells generated by earthquake epicenters. In the framework of nonextensive statistical mechanics applied in geophysics, variables like seismic moment, inter-event time or Euclidean distance between successive earthquakes or length of faults in a given region have been studied through the so-calledq-exponential distributions obtained by maximizing the Tsallis entropy under suitable conditions. These distributions take also the name of generalized Pareto distributions in the context of the limit distributions of excesses. In this work we consider the spatial distribution of a set of earthquakes and its temporal variations by modelling the area of Voronoi cells generated by the epicenters through a generalized Pareto distribution. Following the Bayesian paradigm we analyze the recent seismicity of the central Italy and we compare the posterior marginal likelihood of the aforementioned distributions in shifting time windows. We point out that the best fitting distribution varies over time and the trend of all three distributions converges to that of the exponential distribution in the preparatory phase for the mainshock.
Trace element signatures of sphalerite in the Sichuan Daliangzi Ge-rich Pb-Zn deposit and its implications for deep ore prospecting
Authors: Li Lingjie , Han Runsheng , Zhang Yan , Wu Jianbiao , Feng Zhixing
Published: September 2022

The Daliangzi Pb-Zn deposit is one of the typical Ge-rich Pb-Zn deposits in the Sichuan-Yunnan-Guizhou Pb-Zn polymetallic metallogenic triangle area (SYGT), with its Pb, Zn, and Cd reserves reaching the scale of a large-sized deposit and its Ge reserve reaching that of a medium-sized deposit. Based on LA-ICP-MS in-situ analysis in combination with element mapping, this study reveals the occurrence state of trace elements and ore-forming temperature of sphalerite in ores. The study shows that the sphalerite in the deposit is characterized by rich Cd, Ge, and Ga, relatively rich Fe, very variable Cu and Pb contents, and poor Mn, In, and Sn. This data indicates that Cd, Mn, Fe, and Pb occur in sphalerite in the form of isomorphism or locally in the form of microinclusions in galena. Good correlation between Cu(Ag) and Ge and that between (Cu+Ag) and (Ga+As+Sb) suggest that the substitution relationship with Zn is nCu2++Ge2+↔(n+1)Zn2+ or n(Cu, Ag)2++Ge2+↔(n+1)Zn2+ and (Cu+Ag)1++(Ga+As+Sb)3+↔2Zn2+, and chalcopyrite and Ge, Gu, and Ga-rich microinclusions exist locally; the contents of Ge, Cd, Cu, Pb, Fe, Mn, and other elements in brown yellow sphalerite are higher than those in light yellow sphalerite while Ga and In are relatively more enriched in the latter. The estimation by GGIMFis geothermometer and the trace element signature of the sphalerite indicates that the temperature of the deposit is low-moderate: the formation temperature of the sphalerite in stage II is 86–213°C (134°C on average) ∼ 106–238°C (170°C on average) and that in stage III is 88–105°C (96°C on average) ∼ 134–147°C (140°C on average), demonstrating that the precipitation mechanism of ore-forming elements is the drop in fluid temperature. Based on this, an ore-forming model of the deposit has been established, and it is believed that the ore district has potential for deep prospecting of Cu, Pb, Zn, and other metal resources.
On the feasibility and usefulness of high-performance computing in probabilistic volcanic hazard assessment: An application to tephra hazard from Campi Flegrei
Authors: Montesinos Beatriz Martínez , Luzón Manuel Titos , Sandri Laura , Rudyy Oleksandr , Cheptsov Alexey , Macedonio Giovanni , Folch Arnau , Barsotti Sara , Selva Jacopo , Costa Antonio
Published: September 2022

For active volcanoes, knowledge about probabilities of eruption and impacted areas becomes valuable information for decision-makers to develop short- and long-term emergency plans, for which probabilistic volcanic hazard assessment (PVHA) is needed. High-resolution or spatially extended PVHA requires extreme-scale high-performance computing systems. Within the framework of ChEESE (Center of Excellence for Exascale in Solid Earth; www.cheese-coe.eu), an effort was made to generate exascale-suitable codes and workflows to collect and process in some hours the large amount of data that a quality PVHA requires. To this end, we created an optimized HPC-based workflow coined PVHA_HPC-WF to develop PVHA for a volcano. This tool uses the Bayesian event tree methodology to calculate eruption probabilities, vent-opening location(s), and eruptive source parameters (ESPs) based on volcano history, monitoring system data, and meteorological conditions. Then, the tool interacts with the chosen hazard model, performing a simulation for each ESP set or volcanic scenario (VS). Finally, the resulting information is processed by proof-of-concept-subjected high-performance data analytics (HPDA) scripts, producing the hazard maps which describe the probability over time of exceeding critical thresholds at each location in the investigated geographical domain. Although PVHA_HPC-WF can be adapted to other hazards, we focus here on tephra (i.e., lapilli and ash) transport and deposition. As an application, we performed PVHA for Campi Flegrei (CF), Italy, an active volcano located in one of the most densely inhabited areas in Europe and under busy air traffic routes. CF is currently in unrest, classified as being in an attention level by the Italian Civil Protection. We consider an approximate 2,000 × 2,000 × 40 km computational domain with 2 km grid resolution in the horizontal and 40 vertical levels, centered in CF. To explore the natural variability and uncertainty of the eruptive conditions, we consider a large number of VSs allowing us to include those of low probability but high impact, and simulations of tephra dispersal are performed for each of them using the FALL3D model. Results show the potential of HPC to timely execute a vast range of simulations of complex numerical models in large high-resolution computational domains and analyze great volumes of data to obtain quality hazard maps.
High-yield webinar engagement strategies and teacher candidate professional learning
Authors: Cosier Meghan , Morgan Sara , Sandoval Gomez Audri
Published: September 2022

In response to the COVID-19 school closures in both K-12 and higher education, a group of education partners in the United States collaborated to offer a statewide webinar series, 12 webinars in total, to support preservice teachers as they worked to complete their clinical hour requirements. The webinars and extension activities provided via Padlets covered topics associated with best practices and related to credential requirements such as applying universal design for learning and differentiating instruction. This study explored the perceptions of 248 preservice teachers regarding the virtual professional learning format and extension activities, as well as what professional learning they felt they needed in the future as they began their first year teaching during COVID-19. Findings suggest preservice teachers were receptive to learning through the structured webinar platform and found extension activities helpful in applying content. Their knowledge, sense of preparedness, and application of the topics and strategies presented increased, and the topics were relevant and supported the required practicum hours and future teaching practice.
Different types of diabetes mellitus and risk of thyroid cancer: A meta-analysis of cohort studies
Authors: Dong Wen-wu , Zhang Da-Lin , Wang Zhi-Hong , Lv Cheng-Zhou , Zhang Ping , Zhang Hao
Published: September 2022

Objective

Sex-specific thyroid cancer risk exists in patients diagnosed with diabetes mellitus (DM). However, thyroid cancer risk in different types of DM is still unclear. This meta-analysis aims to identify the real correlation between different types of DM and thyroid cancer risk in both sexes.

Methods

Studies were identified by an electronic search of PubMed, EMBASE, and Cochrane Library on 16 January 2022. A random-effects model was used to estimate the relative risks (RRs). The Cochran’s Q and I2 statistics were computed to detect heterogeneity between studies.

Results

In comparison with non-DM counterparts, patients with DM had a 1.32-fold higher risk of thyroid cancer (95% CI, 1.22–1.44) with 1.26-fold (95% CI, 1.12–1.41) in men and 1.36-fold (95% CI, 1.22–1.52) in women, respectively. Subgroup analysis by the type of DM showed that the RR of thyroid cancer in patients with type 2 diabetes was 1.34 (95% CI, 1.17–1.53) in the study population with 1.32 (95% CI, 1.12–1.54) in men and 1.37 (95% CI, 1.12–1.68) in women, respectively; the RR of thyroid cancer was 1.30 (95% CI, 1.17–1.43) in patients with gestational diabetes; the risk of thyroid cancer in patients with type 1 diabetes was 1.51-fold in women but not in men. Although there were some heterogeneities, it did not affect the above results of this study.

Conclusion

This study indicates that, compared with non-DM individuals, patients with any type of DM have an elevated thyroid cancer risk. This positive correlation between type 2 diabetes and thyroid cancer risk exists in both men and women.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, CRD42022304028.
Fault diagnosis of transformer using artificial intelligence: A review
Authors: Zhang Yan , Tang Yufeng , Liu Yongqiang , Liang Zhaowen
Published: September 2022

Transformer is one of the important components of the power system, capable of transmitting and distributing the electricity generated by renewable energy sources. Dissolved Gas Analysis (DGA) is one of the effective techniques to diagnose early faults in oil-immersed transformers. It correlates the concentration and ratio of dissolved gases with transformer faults. Researchers have proposed many methods for fault diagnosis, such as double ratio method, Rogers method, Duval triangle method, etc., but all of them have some problems. Based on the strong data mining capability and good robustness of AI techniques, many researchers introduced AI techniques to mine the features of DGA data. According to the characteristics and scale of DGA data, researchers select appropriate AI techniques or make appropriate improvements to AI techniques to improve diagnostic performance. This paper presents a systematic review of the literature on the application of artificial intelligence techniques for DGA-based diagnosis and for solving intractable problems in early transformer fault diagnosis, which include neural networks, clustering, support vector machines, etc. In addition to reviewing the applications of these intelligent techniques, the diagnostic thinking proposed in this literature, such as the introduction of temporal parameters for comprehensive analysis of DGA data and the extraction of optimal features for DGA data, is also reviewed. Finally, this paper summarizes and prospects the artificial intelligence techniques applied by researchers in transformer fault diagnosis.
Drivers of nutrient content and spatial variability of soil multifunctionality in the topsoil of Kyrgyzstan
Authors: Chen Yusen , Zhang Shihang , Li Huiliang , Wang Yongdong
Published: September 2022

Soil nutrient status is a crucial measure of soil fertility, which not only coordinates and provides the nutrients necessary for plant growth, but also stimulates the decomposition of soil humus and biogeochemical cycles. Therefore, understanding the distribution characteristics of soil nutrients in the Kyrgyzstan, while exploring the drivers of their variability, is important for understanding ecological processes and the distribution of soil resources. Simultaneously, the study of the spatial distribution of soil multifunctionality and its drivers across Kyrgyzstan can better elucidate the functions of the entire ecosystem, assist in optimizing the allocation of resources and serve as a reference material for the scientific and rational management of the country’s soil ecosystems. In this paper, We have used field sampling data from Kyrgyzstan, to examined the geographic variability and distribution of soil nutrients and soil multifunctionality within different soil depths, as well as the drivers in the country, using a combination of factor analysis and structural equation modeling (SEM). Findings indicated: (1)The topsoil of Kyrgyzstan (0–30 cm) stores 4.24 ± 0.59 Pg of SOC, 0.33 ± 0.06 Pg of total nitrogen (TN), 0.31 ± 0.03 Pg of total phosphorus (TP), and 5.12 ± 1.84 Pg of total potassium (TK). The nutrient reserves of various land-cover categories vary greatly across the nation, with grasslands accounting for the largest reserves (40%) but urban areas allocating the smallest proportion (0.3%). (2): the analysis revealed that using the linear or nonlinear fitting equations, the majority of soil nutrients exhibited a strong correlation with each other and also environmental parameters; (3): in Kyrgyzstan, soil multifunctionality varied substantially from –0.63 to 2.30 across regions. (4): according to the SEM results, NPP, wind speed (VS), MAP, longitude (Lon), SWC, and pH directly affected soil multifunctionality. In addition, several indirect effects of ST, MAT, Sard, and latitude (Lat) on soil multifunctionality were observed. Lon, map, SWC, and pH also had various direct and indirect impacts on soil multifunctionality. The findings of this study shed light on the functions of the entire soil ecosystem in the Kyrgyz Republic that help better predict the effects of environmental changes on ecosystem multifunctionality in drylands and provide a scientific basis for rational utilization of soil resources, efficient management of dryland soils, and prevention of land productivity decline in the country.
Differential characteristics and source contribution of water pollutants before and after the extreme rainfall event in the Huaihe River Basin
Authors: Zhang Yan , Zou Lei , Li Ping , Du Zhenjie , Dou Ming , Huang Zhongdong , Liang Zhijie , Qi Xuebin
Published: September 2022

Various pollutants are collected into rivers through runoff when rainstorms occur, which can harm the aquatic ecological environment, therefore, strengthening the analysis of river pollution sources before and after rainstorms can reduce the impact of rainstorm runoff periods in regard to the risk from river water pollutants. In this study, the water pollutant differential characteristics and pollution source identification in the Henan section in the Huaihe River Basin were explored before and after the extreme rainfall event, and the monitoring data for nine water quality indicators in the monitoring sections were selected. The changing and differential characteristics and processes of the water quality indicators in the Huaihe River Basin before and after the rainstorm were analyzed by using statistical analytical methods and the comprehensive water quality identification index (IWq), and the absolute contribution rates of pollution sources were calculated by the absolute principal components-multiple linear regression model (APCS-MLR). The results showed that the values of pH, DO (Dissolved oxygen) and EC (Electrical conductance) after the rainstorm were lower than those before the rainstorm, while the turbidity, CODMn (Permanganate index), NH3−N (Ammonia nitrogen), TP (Total phosphorus) and TN (Total nitrogen) increased after the rainstorm. The correlations between pH and DO and other water quality indicators increased after the rainstorm, while the correlations between WT (Water temperature), turbidity, CODMn, NH3−N, TP and TN decreased significantly after the rainstorm. The water pollution of each monitoring section increased after the rainstorm; for example, the water quality conditions at Zhoukou Kangdian (ZKKD), Xihua Zhifang (XHZF) and Suixian Banqiao (SXBQ) increased by 42.11, 36.84 and 25.73% to Class V of the environmental quality standards for surface water in China, respectively. The absolute contribution rates of the PC1 to CODMn and TP were 33.86 and 41.11% before the rainstorm, respectively. The absolute contribution rates of the PC2 to DO and TN were 50.77 and 60.26% after the rainstorm, respectively.
The Temporal-Based Forest Disturbance Monitoring Analysis: A Case Study of Nature Reserves of Hainan Island of China From 1987 to 2020
Authors: Xiao Han , Zhang Xiaoqian , Yan Min , Zhang Li , Wang Hua , Ma Yan , Liu Jianbo
Published: September 2022

Forest disturbance monitoring can provide scientific data for the decision making and management of nature reserves. LandTrendr algorithm has been applied to identify forest disturbances on a long-time scale through appropriate segmentation and linear fitting. In this study, 23 nature reserves were detected using LandTrendr during 1987–2020, and the vegetation loss was quantified by years and pixel numbers. The results illustrated that (1) most disturbances occurred in the 1990s and early 21st century. (2) From the spatial distribution of forest loss, the area of forest vegetation disturbance in the coastal zone was larger than the protected area in the internal Hainan Island, the area disturbed in the coastal zone protected area was 97.12 km2, and the area disturbed in the internal area of Hainan Island protected area was 63.02 km2. (3) In terms of different levels of nature reserves, the disturbed area of national nature reserves was 28.39 km2 and the total disturbed area of provincial nature reserves was 131.75 km2. (4) In terms of different types of nature reserves, forest ecological nature reserves had the largest disturbed area of 102.96 km2, followed by marine coastal nature reserves with a disturbed area of 36.99 km2, wildlife nature reserves with a disturbed area of 10.22 km2, and wild plant nature reserves with the smallest disturbed area of 9.96 km2. The results are hoped to provide scientific support and data for the management and planning of nature reserves in Hainan Island.
Application of Spatiotemporal Pattern Mining Methods for Land Use Transition Research: A Case Study of Baiyun District in Guangzhou
Authors: Jian Yuqing , Chen Yuangong , Gong Jianzhou , Wenli Chen , Chen Kanglin
Published: September 2022

The use of spatio-temporal statistical combination method to explore the land use transition in urban suburbs provides an essential resource for promoting urban-rural integration and management of further urbanization. A combination of Space Time Cube and Geodetector methods was used to quantitatively identify the dominant morphology of land use change, and explore the recessive morphology and driving mechanism in Baiyun District, a suburb of Guangzhou from 1980 to 2020. Between these years, the land use changes were dominated by the expansion of built-up land and the shrinkage of cropland. The expansion took place in southern (1990-2000) to central (2000-2005) areas of the jurisdiction, followed by large-scale decentralization (2005-2010). Land use activities showed a downward trend. A continuous cold spot was mainly distributed in the southeast and remote areas near the urban center, whereas a continuous hot spot was spatially characterized by a multinuclear pattern, mainly concentrated in the center and south. Socioeconomic factors significantly affected the spatial pattern of land use activities. The trend turning in land use morphology of land use change can be divided into four stages: land primitivation from 1980 to 1990, land fragmentation from 1990 to 2000, land overflow from 2000 to 2010, and land intensification from 2010 to the present. Baiyun District is at the forefront of China’s development and has typical “suburban” characteristics, which can provide a reference for other suburbs in China to develop in stages. Today, urban suburbs in China face the problems of limited land resources and mixed land use space. Taking advantage of the new national strategic environment could effectively solve these land use issues in urban suburbs and achieve sustainable development. New trends in land use morphology research, also considering land use effects and land use change mechanisms in an integrated manner, are conducive to further deepening the understanding of land use transitions. Moreover, spatiotemporal statistical methods have innovated the field of mining the spatiotemporal characteristics of land use. Based on a scientific method for spatiotemporal analysis, we were able to reconstruct the three-dimensional space of land and improve the methods applied for research into land use change.
Macrophyte habitat architecture and benthic-pelagic coupling: Photic habitat demand to build up large P storage capacity and bio-surface by underwater vegetation
Authors: Teubner Katrin , Teubner Irene E. , Pall Karin , Tolotti Monica , Kabas Willi , Drexler Silke-Silvia , Waidbacher Herwig , Dokulil Martin T.
Published: September 2022

Macrophytes play an important role in shallow lakes if large standing crop can be achieved. Here we stress the role of submerged macrophytes for benthic-pelagic coupling in the shallow oxbow lake Alte Donau (Austria) during restoration triggered by sufficient light availability (12% surface ambient light, photic>12% depth, zoptimum) in both, the benthic and the pelagic habitat. Focusing on zoptimum, rather than on minimum light requirement (euphotic depth), seemed to be more meaningful to follow the macrophyte development. After phosphate precipitation treatment, the photic>12% pelagic habitat accounted for more than half of the total water volume in summer, while the achievement of the same photic>12% conditions for half of the total sediment surface area was delayed by 8 years. A delay of light exposure on the lake bottom area compared to the lake water volume is given by the basin morphometry, but the time span that is required for passing this delay depends on the efficiency of restoration measures. The 8-year delay for Alte Donau means that lake restoration focusing on macrophyte re-establishment was difficult to stimulate due to insufficient light exposure at the lake bottom. A further increase of photic>12% conditions to more than 3/4 size of both pelagic and benthic habitat, however, eventually stimulated sustained macrophyte growth. With the onset of this large macrophyte biomass yield, the phosphorus storage pool of submerged macrophytes exceeded the annual peak concentration of total phosphorus of the whole lake water by about one order of magnitude for the first time. Further, the submerged macrophyte bio-surface exceeded the size of lake bottom surface, also by about one order of magnitude. Our results support that macrophytes can act as a significant sink of phosphorus by retaining this nutrient at least during the growing season. We further see the immensely large macrophyte bio-surface as a vast spatial dimension for an additional habitat for freshwater biota. Therefore, we conclude that mature submerged macrophyte formations need to be considered not only as biomass yield, but create a unique macrophyte habitat architecture as a third main component in the network between benthic (lake bottom) and pelagic (lake water) habitat.
Environmental legacy of pre-Columbian Maya mercury
Authors: Cook Duncan E. , Beach Timothy P. , Luzzadder-Beach Sheryl , Dunning Nicholas P. , Turner Simon D.
Published: September 2022

The Mexico and Central American region has a history of mercury use that began at least two millennia before European colonisation in the 16th century. Archaeologists have reported extensive deposits of cinnabar (HgS) and other mercury materials in ancient human settlements across the region. However, there has been no consideration to date of the environmental legacy of this long history of anthropogenic mercury use. This review begins by synthesising our knowledge of the history and nature of anthropogenic mercury in ancient Mesoamerica based on archaeological data, with a particular focus on the Maya culture of lowland Guatemala, Belize, the Yucatan of Mexico, El Salvador, and Honduras. The Classic Period Maya used mercury for decorative and ceremonial (including funerary) purposes: Cinnabar (HgS) predominantly, but the archaeological record also shows rare finds of elemental mercury (Hg0) in important burial and religious contexts. In this review, we have located and summarised all published data sets collected from (or near) ancient Maya settlements that include environmental mercury measurements. Comparing mercury determinations from pre-Columbian Maya settlements located across the region confirms that seven sites from ten have reported at least one location with mercury concentrations that equal or exceed modern benchmarks for environmental toxicity. The locations with elevated mercury are typically former Maya occupation areas used in the Late Classic Period, situated within large urban settlements abandoned by c. 10th century CE. It is most likely that the mercury detected in buried contexts at Maya archaeological sites is associated with pre-Columbian mercury use, especially of cinnabar. In more complex contexts, where modern biological or specifically anthropogenic inputs are more probable, legacy mercury in the environment will have a more complex, and time transgressive input history. This review identifies current research gaps in our understanding of the long history of Maya mercury use and in the collection of robust total mercury datasets from the Maya world. We identify important areas for future research on the environmental persistence and legacy of mercury, including the need to interpret environment mercury data in the context of mercury exposure and human health at Maya archaeological sites.
A maximum-likelihood method to estimate haplotype frequencies and prevalence alongside multiplicity of infection from SNP data
Authors: Tsoungui Obama Henri Christian Junior , Schneider Kristan Alexander
Published: September 2022

The introduction of genomic methods facilitated standardized molecular disease surveillance. For instance, SNP barcodes inPlasmodium vivaxandPlasmodium falciparummalaria allows the characterization of haplotypes, their frequencies and prevalence to reveal temporal and spatial transmission patterns. A confounding factor is the presence of multiple genetically distinct pathogen variants within the same infection, known as multiplicity of infection (MOI). Disregarding ambiguous information, as usually done inad-hocapproaches, leads to less confident and biased estimates. We introduce a statistical framework to obtain maximum-likelihood estimates (MLE) of haplotype frequencies and prevalence alongside MOI from malaria SNP data, i.e., multiple biallelic marker loci. The number of model parameters increases geometrically with the number of genetic markers considered and no closed-form solution exists for the MLE. Therefore, the MLE needs to be derived numerically. We use the Expectation-Maximization (EM) algorithm to derive the maximum-likelihood estimates, an efficient and easy-to-implement algorithm that yields a numerically stable solution. We also derive expressions for haplotype prevalence based on either all or just the unambiguous genetic information and compare both approaches. The latter corresponds to a biasedad-hocestimate of prevalence. We assess the performance of our estimator by systematic numerical simulations assuming realistic sample sizes and various scenarios of transmission intensity. For reasonable sample sizes, and number of loci, the method has little bias. As an example, we apply the method to a dataset from Cameroon on sulfadoxine-pyrimethamine resistance inP. falciparummalaria. The method is not confined to malaria and can be applied to any infectious disease with similar transmission behavior. An easy-to-use implementation of the method as an R-script is provided.
Coalescent simulations indicate that the São Francisco River is a biogeographic barrier for six vertebrates in a seasonally dry South American forest
Authors: Coelho Felipe Eduardo Alves , Guillory Wilson Xavier , Gehara Marcelo
Published: September 2022

The riverine barrier hypothesis has been extensively explored in Neotropical rainforests, while its importance in drier regions such as the Caatinga, a seasonally dry tropical forest in northeastern Brazil, has only recently received more attention. The Caatinga is bisected by the São Francisco River (SFR), which has long been suggested to be an important biogeographic feature in the region. However, recent studies have found mixed support for the role of the SFR as a hard barrier, most of them relying on the presence or absence of genetic breaks congruent with its course. Here, we used published multilocus and next-generation data from six vertebrate species to test the SFR’s strength as a barrier. Using model-based approaches (approximate Bayesian computation and supervised machine learning), we tested demographic models incorporating full, intermediate, and zero migration across the SFR, estimating divergence times and migration rates for each species. We found support for the SFR’s role as a barrier, allowing gene flow for some species. Estimated divergence times varied among species but are limited to the late Pleistocene, coherent with one of several proposed paleocourse changes in the river’s geological history. Contrary to the mixed results of previous studies, our study supports the SFR as an important phylogeographic barrier across different taxonomic groups, driving diversification in the Caatinga.
Including forestry in an emissions trading scheme: Lessons from New Zealand
Authors: Carver Thomas , Dawson Patrick , O’Brien Sophie , Kotula Hannah , Kerr Suzi , Leining Catherine
Published: September 2022

The forestry sector has a crucial role to play in mitigating climate change. Given the share of global emissions covered by emissions trading is expected to rise, there is a need to understand how emissions trading might drive behavior change in the forestry sector. To explore this, we analyze the New Zealand Emissions Trading Scheme (NZ ETS) − the only system in the world with symmetrical incentives that reward forest owners who afforest and make liable those who deforest. In theory, these incentives should drive net carbon dioxide removals in the forestry sector, but the sectoral response has proven complex. We evaluate the NZ ETS policies that directly affect forestry and the sectoral response to these policies by analyzing trends in deforestation, afforestation, and participation over 2008 to 2022. Our findings indicate that the forestry sector, and the NZ ETS participants within it, have responded rationally to emissions pricing over time. However, multiple factors such as complex participation requirements, extended periods of policy uncertainty, and weak emissions price signals (particularly over 2011–2016) have likely restricted the effectiveness of the NZ ETS in changing forestry outcomes over much of its operating life. The Climate Change Response (Emissions Trading Reform) Amendment Act, 2020 reformed forestry and other provisions in the NZ ETS to address demonstrated shortcomings, improve policy predictability, and incentivize more ambitious mitigation action in line with Aotearoa New Zealand’s targets. However, the signaling of further changes to NZ ETS forestry policy in 2022 has created new uncertainty for market participants. Despite past challenges, the sector’s dramatic response to rising emissions prices in recent years demonstrates the NZ ETS is changing landowner behavior to produce net forestry removals. The NZ ETS remains a unique and strong model from which other nations can gain insights in how to design and operate emissions trading systems to harness mitigation potential from the forestry sector and help meet their emission reduction targets.
The consequences of urbanization on vegetation photosynthesis in the Yangtze River Delta, China
Authors: Yu Huilin , Zhang Jie , Kong Xiangcong , Du Gege , Meng Baoping , Li Meng , Yi Shuhua
Published: September 2022

Vegetation photosynthesis is a critical component of terrestrial carbon cycles, and its peak value (peak photosynthetic rate) dominates plant CO2 uptake. Urbanization has significantly influenced vegetation photosynthesis by changing environmental conditions directly (replacement of vegetated surfaces with impervious surfaces) and indirectly (e.g., atmospheric and climatic conditions). Although some studies have investigated the effects of urbanization on vegetation productivity across the whole study area, how the peak photosynthetic rate responds to urbanization for different vegetation types has received scant scholarly attention. Here, using the urban-rural gradient approach, we explored the effects of urbanization on the peak photosynthetic rate (surrogated by GPPmax and EVImax) of different vegetation types across urbanization intensity (UI) gradients in the Yangtze River Delta Urban Agglomeration (YRDUA). The results showed that (1) the GPPmax and EVImax of the forest, grassland, and wetland decreased with urban intensity. GPPmax and EVImax in rural areas (UI ≦ 1%) were 36.62 and 30.47% higher than those of urban areas (UI > 1%) overall vegetation types. (2) The indirect impacts can offset or exacerbate the direct loss of vegetation photosynthesis caused by urbanization in YRDUA. Especially for forest ecosystems in YRDUA, the negative direct urbanization effect is exacerbated by the indirect reduction in vegetation growth. However, the indirect effects of urbanization on grassland and wetland offset 47.08 and 87.23% loss of GPPmax, and 34.17 and 79.73% loss of EVImax due to the reduction of vegetated surface area, respectively. (3) The indirect impact of urbanization on vegetation photosynthesis was dominated by the elevated daytime land surface temperature (LSTday). Our study highlights the necessity of distinguishing the various effects of urbanization on vegetation photosynthesis, which may help stakeholders formulate more reasonable urban environmental planning.
Identification of functional TF-miRNA-hub gene regulatory network associated with ovarian endometriosis
Authors: Li Lu , Sun Bo , Sun Yingpu
Published: September 2022

Endometriosis (EMs), one of the most common gynecological diseases, seriously affects the health and wellness of women; however, the underlying pathogenesis remains unclear. This study focused on dysregulated genes and their predicted transcription factors (TFs) and miRNAs, which may provide ideas for further mechanistic research. The microarray expression dataset GSE58178, which included six ovarian endometriosis (OE) samples and six control samples, was downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to study the cellular and organism-level functions of DEGs. The protein-protein interaction (PPI) network was built and visualized using Cytoscape, and modules and hub genes were explored using various algorithms. Furthermore, we predicted miRNAs and TFs of hub genes using online databases, and constructed the TF-miRNA-hub gene network. There were 124 upregulated genes and 66 downregulated genes in EMs tissues. GO enrichment analysis showed that DEGs were concentrated in reproductive structure development and collagen-containing extracellular matrix, while KEGG pathway analysis showed that glycolysis/gluconeogenesis and central carbon metabolism in cancer require further exploration. Subsequently, HIF1A, LDHA, PGK1, TFRC, and CD9 were identified as hub genes, 22 miRNAs and 34 TFs were predicted to be upstream regulators of hub genes, and these molecules were pooled together. In addition, we found three key feedback loops in the network, MYC-miR-34a-5p-LDHA, YY1-miR-155-5p-HIF1A, and RELA-miR-93-5p-HIF1A, which may be closely related to OE development. Taken together, our study structured a TF-miRNA-hub gene network to decipher the molecular mechanism of OE, which may provide novel insights for clinical diagnosis and treatment.