bluuebunny/crossref_metadata_2025 huggingface dataset:
Cuscuta species: Model organisms for haustorium development in stem holoparasitic plants
Authors: Jhu Min-Yao , Sinha Neelima R.
Published: December 2022

Parasitic plants are notorious for causing serious agricultural losses in many countries. Specialized intrusive organs, haustoria, confer on parasitic plants the ability to acquire water and nutrients from their host plants. Investigating the mechanism involved in haustorium development not only reveals the fascinating mystery of how autotrophic plants evolved parasitism but also provides the foundation for developing more effective methods to control the agricultural damage caused by parasitic plants. Cuscuta species, also known as dodders, are one of the most well-known and widely spread stem holoparasitic plants. Although progress has been made recently in understanding the evolution and development of haustoria in root parasitic plants, more and more studies indicate that the behaviors between root and stem haustorium formation are distinct, and the mechanisms involved in the formation of these organs remain largely unknown. Unlike most endoparasites and root holoparasitic plants, which have high host-specificity and self- or kin-recognition to avoid forming haustoria on themselves or closely related species, auto-parasitism and hyper-parasitism are commonly observed among Cuscuta species. In this review, we summarize the current understanding of haustorium development in dodders and the unique characteristics of their parasitizing behaviors. We also outline the advantages of using Cuscuta species as model organisms for haustorium development in stem holoparasitic plants, the current unknown mysteries and limitations in the Cuscuta system, and potential future research directions to overcome these challenges.
Sugarcane stem node detection and localization for cutting using deep learning
Authors: Wang Weiwei , Li Cheng , Wang Kui , Tang Lingling , Ndiluau Pedro Final , Cao Yuhe
Published: December 2022

Introduction

In order to promote sugarcane pre-cut seed good seed and good method planting technology, we combine the development of sugarcane pre-cut seed intelligent 0p99oposeed cutting machine to realize the accurate and fast identification and cutting of sugarcane stem nodes.

Methods

In this paper, we proposed an algorithm to improve YOLOv4-Tiny for sugarcane stem node recognition. Based on the original YOLOv4-Tiny network, the three maximum pooling layers of the original YOLOv4-tiny network were replaced with SPP (Spatial Pyramid Pooling) modules, which fuse the local and global features of the images and enhance the accurate localization ability of the network. And a 1×1 convolution module was added to each feature layer to reduce the parameters of the network and improve the prediction speed of the network.

Results

On the sugarcane dataset, compared with the Faster-RCNN algorithm and YOLOv4 algorithm, the improved algorithm yielded an mean accuracy precision (MAP) of 99.11%, a detection accuracy of 97.07%, and a transmission frame per second (fps) of 30, which can quickly and accurately detect and identify sugarcane stem nodes.

Discussion

In this paper, the improved algorithm is deployed in the sugarcane stem node fast identification and dynamic cutting system to achieve accurate and fast sugarcane stem node identification and cutting in real time. It improves the seed cutting quality and cutting efficiency and reduces the labor intensity.
Air pollution exposure and pregnancy outcomes among women with polycystic ovary syndrome
Authors: Zhu Qianqian , Cai Jing , Guo Haiyan , Zhao Yan , Lin Jiaying
Published: December 2022

Background

Recently, the relationship between air pollution and reproductive outcomes has become a research focus. However, there is a lack of research on the relationship between air pollution and polycystic ovary syndrome (PCOS).

Methods

This is a retrospective cohort study included a total of 1,652 women with PCOS and 12,543 women without PCOS conducted from 1 January 2015 to 31 December 2019. The average daily concentration data of six air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) during different exposure windows were obtained. Generalized estimating equation models were used to evaluate the association of air pollution with pregnancy outcomes.

Results

Air pollutants were not found to have a significant association with pregnancy rates among patients with PCOS. However, each IQR increase in PM10 exposure during period 3 (embryo transfer to serum HCG test) was associated with the reduced clinical pregnancy rate (adjusted OR = 0.92, 95% CI: 0.84–0.99) for patients without PCOS. Patients without PCOS showed lower clinical pregnancy rates with increased exposure to NO2 during periods 2 (oocyte retrieval to embryo transfer) and 5 (start of gonadotropin medication to embryo transfer), with aORs and 95% CIs of 0.94 (0.88, 0.99) and 0.94 (0.88, 0.98), respectively. Each IQR increase in SO2 among patients without PCOS during periods 1 (start of gonadotropin medication to oocyte retrieval), 2, 5, and 6 (start of gonadotropin medication to serum HCG test) was related to a decrease in clinical pregnancy rate. For the live birth rate, no significant relationship was found between air pollutants, including PM2.5, PM10, SO2, NO2, CO, and O3, and the live birth rate for women with PCOS. However, women without PCOS presented a lower probability of live birth with exposure to SO2 during periods 1, 2, 5, and 6.

Conclusion

This retrospective study of reproductive-aged women observed no significant relationships between ambient pollutants and pregnancy outcomes among women with PCOS but found negative associations among women without PCOS.
Body mass index and immune checkpoint inhibitor efficacy in metastatic cancer patients: A Brazilian retrospective study
Authors: Moreira Raphael Brandao , Fernandes Mauricio , Monteiro Mariana Ribeiro , Luiz Francine Maria Agostinho , Silva Erika Simplicio , Andrade Perla de Mello , Pinto Mayara Batista , Lima Letycia , Silva Astrid , Nunez Juliana , Freitas Daniele , de Lima Araujo Luiz Henrique , Rossini Caio Vinicius Teles , Aguiar Pedro Nazareth
Published: December 2022

Previous studies suggested that obesity pro-inflammatory state could improve immune checkpoint inhibitors (ICI) clinical efficacy. This is a retrospective, multicenter, and observational study that included patients treated in a private Brazilian Oncology Group. Primary outcomes were the association of body mass index (BMI) category with overall survival (OS) and progression free survival (PFS). Secondary outcomes were association between BMI and objective response rate (ORR). In the total cohort, 448 patients were classified as a normal weight (43%), overweight (36%), obese (17%) and underweight (4%). The patients were predominantly male gender (62%), with stage IV lung cancer (57%) and melanoma (19%). The obese group (BMI ≥ 30 kg/m2) had a not statistically significant longer median OS than the non-obese group (BMI < 30 kg/m2) - 21.8 months (95% CI NR - NR) versus 14.9 months (95% CI 8.3 - 21.5); HR = 0.82, (95% CI 0.57 - 1.18, P = 0.28). Obese patients treated with anti-CTLA4 did not reach the mOS, while the non-obese group had a mOS of 23.1 months (P = 0.04). PFS did not differ between subgroups. Obese patients had also lower ORR, but without reaching statistical significance. In conclusion, this study did not report an improved OS among high BMI patients treated with ICI.
Assessing the Italian Innovative Start-Ups Performance with a Composite Index
Authors: Onesti Gianni , Monaco Eleonora , Palumbo Riccardo
Published: December 2022

This paper aims to assess the profitability and employees’ productivity of Italian innovative start-ups with a new composite index: the Start-ups Performance score (SP-score). In recent years, the Italian government has made several efforts to foster the economy, establishment, and growth of start-ups. Specifically, the issuing of the Italian Start-up Act in 2012 offers a unique opportunity to examine the Italian setting, given the special conditions that the government granted to the start-ups. The latter obtain generic benefits, tax reductions and hiring facilitations if they meet specific criteria granting the status (label) of “innovative” by law. Based on a sample of Italian start-ups firms (ISPs) and financial statement data for the period 2016–2020, we test whether the performance of the Italian start-ups which are granted the status of “innovative” is higher compared to start-ups without the mentioned status (NISPs). We measure the firm’s performance by building a composite index which synthesizes both profitability and employees’ productivity (controlling for the firms’ size), and find that the ISPs report higher SP-score compared to the NISPs. In addition, we examine whether the SP-score is higher (or lower) among Innovative start-ups located in different regional areas. The derivation of the composite indicator (SP-score) allows a clear and effective evaluation of several characteristics, permitting a more comprehensive understanding of the data that support the strategic choices of management and localization entrepreneurship policies. In addition, our study highlights a certain homogeneity of innovative start-ups’ performance among the Italian territories, which overcomes the classic dualistic division between Northern and Southern regions.
Design of a Machine Vision-Based Automatic Digging Depth Control System for Garlic Combine Harvester
Authors: Ding Anlan , Peng Baoliang , Yang Ke , Zhang Yanhua , Yang Xiaoxuan , Zou Xiuguo , Zhu Zhangqing
Published: December 2022

The digging depth is an important factor affecting the mechanized garlic harvesting quality. At present, the digging depth of the garlic combine harvester (GCH) is adjusted manually, which leads to disadvantages such as slow response, poor accuracy, and being very dependent on the operator’s experience. To solve this problem, this paper proposes a machine vision-based automatic digging depth control system for the original garlic digging device. The system uses the improved YOLOv5 algorithm to calculate the length of the garlic root at the front end of the clamping conveyor chain in real-time, and the calculation result is sent back to the system as feedback. Then, the STM32 microcontroller is used to control the digging depth by expanding and contracting the electric putter of the garlic digging device. The experimental results of the presented control system show that the detection time of the system is 30.4 ms, the average accuracy of detection is 99.1%, and the space occupied by the model deployment is 11.4 MB, which suits the design of the real-time detection of the system. Moreover, the length of the excavated garlic roots is shorter than that of the system before modification, which represents a lower energy consumption of the system and a lower rate of impurities in harvesting, and the modified system is automatically controlled, reducing the operator’s workload.
Mitigation of High Solar Irradiance and Heat Stress in Kiwifruit during Summer via the Use of Alleviating Products with Different Modes of Action—Part 1 Effects on Leaf Physiology and Biochemistry
Authors: Ntanos Efstathios , Tsafouros Athanassios , Denaxa Nikoleta-Kleio , Kosta Anna , Bouchagier Pavlos , Roussos Peter Anargyrou
Published: December 2022

Kiwifruit is a significant fruit crop species for many countries around the world. Due to climate change, it undergoes significant heat stress during the summer months in the Mediterranean area. Heat stress, along with high irradiance, generally imposes significant reductions in leaf photosynthetic activity and changes in leaf antioxidant status. In order to ameliorate these impacts, three alleviating commercial products (the osmoprotectant glycine betaine—commercial product BlueStim SP, the antioxidant mixture of tocopherol and phenolic compounds—commercial product Sun Protect, and reflectance calcium carbonate—commercial product Pureshade) were tested. In a fully mature kiwifruit orchard (‘Hayward’ cultivar), the prementioned products were foliarly applied during the summer months, and three assessments took place (in early and late August and late September) to assess their effects on photosynthetic activity, leaf carbohydrate concentration, the leaf sclerophylly indexes, leaf phenolic compound concentration, and antioxidant capacity. The three products induced various effects on leaf physiology and biochemistry, alleviating stress impact to some extent. Glycine betaine proved to be more efficient in alleviating the negative effects on the photosynthetic machinery, while leaf relative water content and, therefore, succulence remained at high levels. The reflectance calcium carbonate product resulted in lower leaf temperatures during the August measurements and in relatively high leaf carbohydrate concentrations. The discriminant analysis, which took place regarding all the measured parameters per assessment, resulted in distinct differences among the treatments, revealing the different modes of action and the effects of the products used. The alleviating products ameliorated the effects of heat and high irradiance stress in the kiwifruit leaves in terms of photosynthetic activity and hydration status, with glycine betaine being more effective than the others, especially under unfavorable conditions in mid-summer.
The Impact of Climate Change on Agricultural Total Factor Productivity: A Cross-Country Panel Data Analysis, 1961–2013
Authors: Xiang Tao , Malik Tariq H. , Hou Jack W. , Ma Jiliang
Published: December 2022

The literature has mixed findings regarding the impact of climate change on agricultural production, probably due to different choices of dependent variables. Based on panel data analysis of 140 countries from an extended period, i.e., 1961 to 2013, this study applies the explicit method of using TFP as the dependent variable, but also delivers estimations with the implicit approach of using agricultural output as the dependent variable, so as to be able to directly compare the results with the mainstream trends in the existing literature. We found that using agricultural TFP as the dependent variable generates more consistent and robust results. We also found a strong negative impact of climate change on agricultural productivity. A one-unit downward deviation of precipitation (i.e., drought) and one unit of upward deviation of temperature (i.e., global warming) decrease the TFP by 0.530 and 0.494, respectively. As we have one of the largest sample sizes when it comes to studying the effect of climate change, we carried out an exploration by dividing the sample into different categories of developed vs. developing countries and cold vs. warm climates, as well as by splitting the time series into two distinct periods. We found that climate change has had a heterogeneous impact on countries with different development levels, with negative impacts on developing countries and positive effects on developed countries, which leads to the rising concern of the impact of climate change on inequality. This heterogeneity and the uneven impact found in this study strongly suggest the need for countries to work together to coordinate and mitigate these adverse effects rather than to adapt to the situation by focusing on the input variations, as the latter will increase the inequality effect of climate change and add to an already unstable global environment.
Maize Rotation Combined with Streptomyces rochei D74 to Eliminate Orobanche cumana Seed Bank in the Farmland
Authors: Xi Jiao , Ding Zanbo , Xu Tengqi , Qu Wenxing , Xu Yanzhi , Ma Yongqing , Xue Quanhong , Liu Yongxin , Lin Yanbing
Published: December 2022

Orobanche cumama wallr. is the sunflower root parasitic weed with special life stage in which seed germination and parasitism take place in the soil. In practice, applying microbial agents and trapping crop rotation are utilized separately, or just one of them is selected to control O. cumana. The development of the sunflower industry is severely constrained on the farmland, where there is high density of O. cumana’s seed banks. In this study, two biological control methods were combined to solve the problem of O. cumana parasitism. The bioassay experiment showed that the high concentration fermentation filtrates of Streptomyces rochei D74 could effectively inhibit the germination and growth of the germ tube of O. cumana seeds. As the concentration was increased to 3.1 mg/mL, O. cumana was almost unable to sprout. A two-year pot experiment revealed that the use of D74 agents and sunflower–maize–sunflower rotation together promoted sunflower growth, as shown by the biomass accumulation, plant height, and denser root systems. The combined method resulted in a significant decrease in the number of O. cumana parasitism, compared to one method alone. Additionally, it affected the bacterial community composition of sunflower rhizosphere, mostly leading to an increase in Streptomyces and Brevibacterium and a decrease in Arthrobacter. This experiment, combined with multiple biological control, means significantly reducing the parasitism of O. cumana, which provides an effective foundation for practical application.
Early Effects of No-Till Use on Durum Wheat (Triticum durum Desf.): Productivity and Soil Functioning Vary between Two Contrasting Mediterranean Soils
Authors: Badagliacca Giuseppe , Lo Presti Emilio , Ferrarini Andrea , Fornasier Flavio , Laudicina Vito Armando , Monti Michele , Preiti Giovanni
Published: December 2022

The diffusion of no-tillage (NT) is to be encouraged because of the benefits it can provide in terms of improving soil fertility and counteracting global warming and climate change as part of climate-smart agriculture practices. However, the introduction of this management can be difficult, especially in the first years of application, and can lead to unpredictable yield results depending on the soil type. Therefore, the aim of this experiment was to evaluate the early effect of NT use, compared to the conventional mouldboard ploughing (CT), on two different soils, a clay-loam (GAL) and a sandy-clay-loam soil (SMA), by monitoring a set of 43 different soil and plant variables that were expected to vary with tillage and/or soil type. At both experimental sites, NT showed lower wheat total biomass (−29%) and grain yields (−17%) than CT with a more pronounced decrease in GAL than in SMA. Yield differences were accompanied by modifications in nutrient, microbial community and soil enzyme activity dynamics which highlighted higher stress in GAL, than in SMA soil, attributable to lower crop residues decomposition and substrate availability. Therefore, our findings suggest that the negative consequences due to the transition to NT depend on specific soil characteristics, like texture and organic matter concentration, with different repercussions on soil quality as well as on wheat growth and productivity.
Prognostic Role of Red Cell Distribution Width and Other Routine Clinico-Pathological Parameters in Dogs with Acute Pancreatitis
Authors: Guglielmini Carlo , Crisi Paolo Emidio , Tardo Antonio Maria , Di Maggio Roberta , Contiero Barbara , Boari Andrea , Fracassi Federico , Miglio Arianna
Published: December 2022

This study aimed to assess the prognostic value of red cell distribution width (RDW) RDW-to-calcium ratio (RDW/Ca), neutrophils-to-lymphocytes ratio (N/L), platelets-to-lymphocytes ratio (P/L) and other easy to obtain and inexpensive hematological and biochemical parameters in dogs with acute pancreatitis. This is a multicenter, retrospective cohort study including 70 client-owned dogs. The accuracy of clinical and laboratory variables to predict short-term death (i.e., dead by 14 days) was tested by calculating the area under the receiver-operating characteristic curve (AUC). Independent predictors of death were identified using the multivariable Cox proportional hazards regression model. The survival rate was 72.9% (51 dogs) and 19 dogs died within 14 days of admission from AP. RDW and blood urea nitrogen (BUN) had good accuracy to predict short-term dead with AUC of 0.74 and 0.70 at the cut-off of >12.7% and >42 mg/dL, respectively. According to the multivariable model, RDW (hazard ratio and 95% confidence interval [HR, 95% CI] = 5.08, 95% CI = 1.14–22.67; p = 0.03), BUN (HR = 1.00, 95% CI = 1.00–1.01; p < 0.01) and bilirubin (HR = 2.46, 95% CI = 1.38–4.39; p < 0.01) were independent predictors of death. The results indicate that RDW, BUN and bilirubin are useful predictors of short-term death in dogs with acute pancreatitis.
Joint Models to Predict Dairy Cow Survival from Sensor Data Recorded during the First Lactation
Authors: Ranzato Giovanna , Adriaens Ines , Lora Isabella , Aernouts Ben , Statham Jonathan , Azzolina Danila , Meuwissen Dyan , Prosepe Ilaria , Zidi Ali , Cozzi Giulio
Published: December 2022

Early predictions of cows’ probability of survival to different lactations would help farmers in making successful management and breeding decisions. For this purpose, this research explored the adoption of joint models for longitudinal and survival data in the dairy field. An algorithm jointly modelled daily first-lactation sensor data (milk yield, body weight, rumination time) and survival data (i.e., time to culling) from 6 Holstein dairy farms. The algorithm was set to predict survival to the beginning of the second and third lactations (i.e., second and third calving) from sensor observations of the first 60, 150, and 240 days in milk of cows’ first lactation. Using 3-time-repeated 3-fold cross-validation, the performance was evaluated in terms of Area Under the Curve and expected error of prediction. Across the different scenarios and farms, the former varied between 45% and 76%, while the latter was between 3.5% and 26%. Significant results were obtained in terms of expected error of prediction, meaning that the method provided survival probabilities in line with the observed events in the datasets (i.e., culling). Furthermore, the performances were stable among farms. These features may justify further research on the use of joint models to predict the survival of dairy cattle.
Does the Wolf (Canis lupus) Exhibit Human Habituation Behaviours after Rehabilitation and Release into the Wild? A Case Report from Central Italy
Authors: Viola Paolo , Girotti Pedro , Adriani Settimio , Ronchi Bruno , Zaccaroni Marco , Primi Riccardo
Published: December 2022

The knowledge of how wolves’ movement patterns and habitat selection are affected by habituation to persons after a period of veterinary isolation, treatment and non-agonistic experience with humans is scarce. Unnatural behaviours could be transferred by imitation to members of the pack and to subsequent generations, increasing direct interaction risks. We used GPS data from a rescued radio-collared female wolf after an 11-day rehabilitation to estimate home range, movement patterns, circadian rhythms, and habitat selection, searching for signals of eventual behavioural distortions. In the period 1 August–26 November 2013, 870 valid locations were acquired. The wolf moved within a minimum convex polygon (95%) of 6541.1 ha (79% wooded), avoiding anthropized areas. Nocturnal and diurnal displacements were significantly different (p < 0.01). Nocturnal displacements were 4409.4 ± 617.5 m during summer and 3684.8 ± 468.1 m during autumn, without differences between seasons. Diurnal movements were significantly higher (p < 0.01) in the summer (2239.0 ± 329.0 m) than in the autumn (595.9 ± 110.3 m), when the hunting season was running. As for a wild wolf, clear complementarity concerning human activities was recorded and no habituation signals were detected, but this is only a first case study that aims to be a stimulus for further research and a call for widespread data sharing.
First Assessment of Micro-Litter Ingested by Dolphins, Sea Turtles and Monk Seals Found Stranded along the Coasts of Samos Island, Greece
Authors: Pietroluongo Guido , Quintana Martín-Montalvo Belén , Antichi Simone , Miliou Anastasia , Costa Valentina
Published: December 2022

This study is the first to assess the occurrence of micro-litter ingested by marine megafauna in the north-eastern Aegean Sea. A total of 25 specimens from four species of marine mammals, including dolphins and monk seals, and two species of sea turtles, found stranded along the coastline of Samos Island, Greece, were selected for the analysis. Litter particles, identified as microplastics (MPs), were ubiquitous throughout all sections of the gastrointestinal tract (oesophagus, stomach and intestine) in all specimens. Overall, the MPs most frequently found were black fibres 0.21–0.50 mm in size. These results provide insight into the extent of micro-litter ingestion and contamination in marine vertebrates. Here we propose a method of standardisation to establish a baseline for marine taxa in this region of the Mediterranean Sea, where knowledge of the topic is still lacking.
Oil Extracted Moringa peregrina Seed Cake as a Feed Ingredient in Poultry: A Chemical Composition and Nutritional Value Study
Authors: Al-Harthi Mohammed A. , Attia Youssef A. , Elgandy Mohamed F. , Bovera Fulvia
Published: December 2022

The chemical composition, antioxidant activity, tannic acid content, mineral, fatty acid, and amino acid profiles of oil-extracted Moringa peregrina seed meal (OEMPSM) were determined. Apparent (AME) and true (AMEn) metabolizable energy and apparent (AAAU) and true (TAAU) amino acid utilization were evaluated using a precision feeding trial. The protein (CP) quality was evaluated by a total efficiency analysis method. The antioxidant activity, gauged by 2,2-diphenyl-1-picrylhydrazyl (DPPH), was 237, 353, and 15.2 mg/mL for the water and ethanol extracts, and ascorbic acid, respectively. Tannic acids were 131.4 mg/100 g dry weight. The OEMPSM had 27.2% CP and 22.4, 15.1, and 15.8 MJ/kg of gross energy, AME and AMEn, respectively. The neutral detergent fiber, acid detergent fiber, and hemicellulose were 40.2, 29.7, and 10.5% DM, respectively. The 15.41% of total fatty acids were saturated and 84.57% unsaturated. The AAAU and TAAU of OEMPSM were 30.92% and 61.06%, respectively. From findings, OEMPSM comprises a valuable level of bioactive substances, amino acids, fatty acids, minerals, and energy; it can provide up to 1.12% of the requirements of total amino acids of chickens (1–21 days); however, the quality of its protein was found to be 44.6% less than that of protein of soybean meal.
Acinetobacter baumannii Resistance to Sulbactam/Durlobactam: A Systematic Review
Authors: Principe Luigi , Di Bella Stefano , Conti Jacopo , Perilli Mariagrazia , Piccirilli Alessandra , Mussini Cristina , Decorti Giuliana
Published: December 2022

Infections caused by carbapenem-resistant Acinetobacter baumannii (CRAB) have limited therapeutic options. Sulbactam-durlobactam is a combination of two βlactamase inhibitors with activity against CRAB under phase 3 clinical investigation. We performed a systematic review on in vitro studies reporting A. baumannii resistances against sulbactam/durlobactam. We considered “resistant” species to be those with MIC ≥ 8 mg/L. Ten studies were included in the review (9754 tested isolates). Overall, 2.3% of A. baumannii were resistant to sulbactam/durlobactam, and this percentage rose to 3.4% among CRAB subgroups and to 3.7% among colistin-resistant strains. Resistance was 100% among metallo β-lactamase-producing strains. Overall, in 12.5% of cases, sulbactam/durlobactam resistance was associated with the production of NDM-1, in 31.7% of cases with the substitutions in the PBP3 determinants, and in the remaining cases the resistance mechanism was unknown. In conclusion, A. baumannii resistance towards sulbactam/durlobactam is limited, except for MBL-producing strains.
Isolation and Identification of Bioactive Compounds from Streptomyces actinomycinicus PJ85 and Their In Vitro Antimicrobial Activities against Methicillin-Resistant Staphylococcus aureus
Authors: Chanthasena Panjamaphon , Hua Yanling , Rosyidah A’liyatur , Pathom-Aree Wasu , Limphirat Wanwisa , Nantapong Nawarat
Published: December 2022

Antibiotic-resistant strains are a global health-threatening problem. Drug-resistant microbes have compromised the control of infectious diseases. Therefore, the search for a novel class of antibiotic drugs is necessary. Streptomycetes have been described as the richest source of bioactive compounds, including antibiotics. This study was aimed to characterize the antibacterial compounds of Streptomyces sp. PJ85 isolated from dry dipterocarp forest soil in Northeast Thailand. The 16S rRNA gene sequence and phylogenetic analysis showed that PJ85 possessed a high similarity to Streptomyces actinomycinicus RCU-197T of 98.90%. The PJ85 strain was shown to produce antibacterial compounds that were active against Gram-positive bacteria including methicillin-resistant Staphylococcus aureus (MRSA). The active compounds of PJ85 were extracted and purified using silica gel column chromatography. Two active antibacterial compounds, compound 1 and compound PJ85_F39, were purified and characterized with spectroscopy, including liquid chromatography and mass spectrometry (LC–MS). Compound 1 was identified as actinomycin D, and compound PJ85_F39 was identified as dihomo-γ-linolenic acid (DGLA). To the best of our knowledge, this is the first report of the purification and characterization of the antibacterial compounds of S. actinomycinicus.
Utility of Metagenomic Next-Generation Sequencing in Infective Endocarditis: A Systematic Review
Authors: Haddad Sara F. , DeSimone Daniel C. , Chesdachai Supavit , Gerberi Danielle J. , Baddour Larry M.
Published: December 2022

Blood cultures have been the gold standard for identifying pathogens in infective endocarditis (IE). Blood culture-negative endocarditis (BCNE), however, occurs in 40% or more of IE cases with the bulk of them due to recent antibiotic exposure prior to obtaining blood cultures. Increasingly, molecular techniques are being used for pathogen identification in cases of BCNE and more recently has included metagenomic next-generation sequencing (mNGS). We therefore performed a literature search on August 31, 2022, that assessed the mNGS in IE and 13 publications were identified and included in a systematic review. Eight (61.5%) of them focused only on IE with mNGS performed on cardiac valve tissue in four studies, plasma in three studies and cardiac implantable electronic devices (CIED) in one study. Gram-positive cocci, including Staphylococcus aureus (n = 31, 8.9%), coagulase-negative staphylococci (n = 61, 17.6%), streptococci (n = 130, 37.5%), and Enterococcus faecalis (n = 23, 6.6%) were the predominant organisms identified by mNGS. Subsequent investigations are needed to further define the utility of mNGS in BCNE and its impact on patient outcomes. Despite some pitfalls, mNGS seems to be of value in pathogen identification in IE cases, particularly in those with BCNE. This study was registered and on the Open Science Framework platform.
Oxidative-Stress-Associated Proteostasis Disturbances and Increased DNA Damage in the Hippocampal Granule Cells of the Ts65Dn Model of Down Syndrome
Authors: Puente-Bedia Alba , Berciano María T. , Martínez-Cué Carmen , Lafarga Miguel , Rueda Noemí
Published: December 2022

Oxidative stress (OS) is one of the neuropathological mechanisms responsible for the deficits in cognition and neuronal function in Down syndrome (DS). The Ts65Dn (TS) mouse replicates multiple DS phenotypes including hippocampal-dependent learning and memory deficits and similar brain oxidative status. To better understand the hippocampal oxidative profile in the adult TS mouse, we analyzed cellular OS-associated alterations in hippocampal granule cells (GCs), a neuronal population that plays an important role in memory formation and that is particularly affected in DS. For this purpose, we used biochemical, molecular, immunohistochemical, and electron microscopy techniques. Our results indicate that TS GCs show important OS-associated alterations in the systems essential for neuronal homeostasis: DNA damage response and proteostasis, particularly of the proteasome and lysosomal system. Specifically, TS GCs showed: (i) increased DNA damage, (ii) reorganization of nuclear proteolytic factories accompanied by a decline in proteasome activity and cytoplasmic aggregation of ubiquitinated proteins, (iii) formation of lysosomal-related structures containing lipid droplets of cytotoxic peroxidation products, and (iv) mitochondrial ultrastructural defects. These alterations could be implicated in enhanced cellular senescence, accelerated aging and neurodegeneration, and the early development of Alzheimer’s disease neuropathology present in TS mice and the DS population.
Protective Actions of α-Tocopherol on Cell Membrane Lipids of Paraquat-Stressed Human Astrocytes Using Microarray Technology, MALDI-MS and Lipidomic Analysis
Authors: Sánchez-Sánchez Laura , Fernández Roberto , Ganfornina Maria Dolores , Astigarraga Egoitz , Barreda-Gómez Gabriel
Published: December 2022

Cellular senescence is one of the main contributors to some neurodegenerative disorders. The early detection of senescent cells or their related effects is a key aspect in treating disease progression. In this functional deterioration, oxidative stress and lipid peroxidation play an important role. Endogenous antioxidant compounds, such as α-tocopherol (vitamin E), can mitigate these undesirable effects, particularly lipid peroxidation, by blocking the reaction between free radicals and unsaturated fatty acid. While the antioxidant actions of α-tocopherol have been studied in various systems, monitoring the specific effects on cell membrane lipids at scales compatible with large screenings has not yet been accomplished. Understanding the changes responsible for this protection against one of the consequences of senescence is therefore necessary. Thus, the goal of this study was to determinate the changes in the lipid environment of a Paraquat-treated human astrocytic cell line, as a cellular oxidative stress model, and the specific actions of the antioxidant, α-tocopherol, using cell membrane microarray technology, MALDI-MS and lipidomic analysis. The stress induced by Paraquat exposure significantly decreased cell viability and triggered membrane lipid changes, such as an increase in certain species of ceramides that are lipid mediators of apoptotic pathways. The pre-treatment of cells with α-tocopherol mitigated these effects, enhancing cell viability and modulating the lipid profile in Paraquat-treated astrocytes. These results demonstrate the lipid modulation effects of α-tocopherol against Paraquat-promoted oxidative stress and validate a novel analytical high-throughput method combining cell cultures, microarray technology, MALDI-MS and multivariate analysis to study antioxidant compounds against cellular senescence.
Apple Antioxidant Properties as an Effect of N Dose and Rate—Mycorrhization Involvement: A Long-Term Study
Authors: Łata Barbara , Żakowska-Biemans Sylwia , Wrona Dariusz
Published: December 2022

The genetic and/or the agronomic approaches are two main ways to enhance concentrations of biologically active compounds in fruits and vegetables. In this study, the apple antioxidant status was evaluated from the second to the fourth year after planting in relation to an increasing N-dose applied—with or without plant microbial inoculation in the field conditions. Cultivar ‘Šampion Arno’ was selected to test these relationships. In the growing season, N treatment and inoculation effects were monitored for the apple peel total phenolics and selected individual phenolic compounds ((+)-catechin, (−)-epicatechin, chlorogenic and caffeic acids, rutin and phloridzin) and total ascorbate concentration. Additionally, as an environmental stress marker measurement of glutathione reductase, ascorbate peroxidase and catalase activity were conducted. The year effect was most pronounced, while the N or applied inoculum effects were much weaker. Great differences in antioxidative enzyme activity and phenolic concentrations between years were revealed. Nitrogen fertilization reduced the fruit’s global phenolic accumulation compared to the control, but the N-effect varied depending on individual phenolic compounds, N dose and N application method. None of the tested factors influenced the ascorbate concentration. There was a certain tendency to increase antioxidant properties in the control group (without mineral N fertilization) but with the application of bio-fertilizer, which may seem promising for future research in this scope.
Filtration Performance of Nonwoven Geotextile Filtering Fine-Grained Soil under Normal Compressive Stresses
Authors: Du Chunxue , Xu Chao , Yang Yang , Wang Jiangfeng
Published: December 2022

To avoid serious clogging and loss of drainage capacity, which puts the underground structure at risk of anti-floating failure, the buried drainage filter must be equipped with a nonwoven geotextile layer. In this scenario, nonwoven geotextiles are subjected to normal compressive stress, which can cause changes in geotextile porosity and structure, affecting the filtration behavior of the geotextile filter. In this paper, in order to evaluate the filtration compatibility of the soil–geotextile system, gradient ratio (GR) tests were performed under a hydraulic gradient of 1.0 using a specially designed gradient ratio filtration device capable of applying normal stress. In total four nonwoven geotextiles and two types of soil were used. The results of the gradient ratio filtration tests were discussed in terms of GR values, the permeability of the soil–geotextile system, and the amount of fines retained in geotextiles. It was shown that under a larger normal compressive stress, the GR value would also increase, while the permeability coefficient of the soil–geotextile system decreased. The filtration responses to various soil–geotextile combinations differed under normal compressive stress. A thick nonwoven geotextile with a small filtration opening size exhibited poor filtration performance while benefiting soil retention. Fines retention was influenced by geotextile thickness, soil type, and normal compressive stress magnitude. In addition, for nonwoven geotextiles filter fine-grained soil under normal compressive stress, the test results indicated that anticlogging design criteria should be improved.
Evolution of China’s Building Energy Service Industry Based on Synergetic Theory
Authors: Zheng Saina , Huang Ruopeng , Zhuang Taozhi
Published: December 2022

Global climate crises are forcing the world to behave sustainably. The building energy service industry (BESI) emerged and promoted building energy conservation by providing a market-oriented mechanism for initial investment. However, the BESI lacks scientific and rational planning, lagging far behind the energy service in the industrial sector. This paper attempts to analyze BESI from the perspective of order parameter-based analysis by adopting the DEMATEL (Decision-Making and Trial Evaluation Laboratory) method, thereby revealing the characteristics of industrial evolution and ascertaining the main order parameters. Consequently, the results show that the evolution of the BESI industry relies on synergistic interaction in the corporate operation, industry-standard, production factor-related, and external environmental industry subsystems. The synergy of the BESI consists of synergy in subsystems, between subsystems, and between the system and the external environment. Three main order parameters dominating the evolution of the BESIs system are determined, namely, “financial support”, “industry standard”, and “technology innovation”. Financial support and industry standard drove the development of the BESI in China over the last few years, while technological innovation will lead its evolution in the coming years. Based on these results, policy suggestions can be proposed to foster BESI development, especially regarding technological innovation.
A Proactive Microgrid Management Strategy for Resilience Enhancement Based on Nested Chance Constrained Problems
Authors: Park Sangjun , Shin Hunyoung
Published: December 2022

As the frequency of extreme weather events rises, the resilience of power systems is becoming increasingly important. This paper proposes a proactive microgrid management strategy for enhancing the resilience of microgrids (MGs) based on nested Mixed Integer Linear Programming problems with chance constraints. In the proposed method, MGs operate in a special operating mode referred to as the “preparation mode” to protect the vital load and maximize resource operation efficiency when an external grid outage warning is issued. The preparation mode problem is formulated to reflect both the normal and emergency mode operation conditions. The on-event phase-operation problem under emergency-mode operation conditions is nested within the pre-scheduling problem under normal-mode operation conditions in the preparation mode. Further, according to their importance, loads are divided into critical and non-critical ones in the problems. The former is represented by a chance constraint, and the latter is represented by the expected cost of load shedding in the cost function. The numerical examples demonstrate that the proposed preparation mode enables the MG to guarantee a high chance that the critical load will survive and to lower the cost of the non-critical load shedding with a minor increase in resource operation costs.
An Improved Shoulder Line Extraction Method Fusing Edge Detection and Regional Growing Algorithm
Authors: Jiao Haoyang , Li Fayuan , Wei Hong , Liu Wei
Published: December 2022

Shoulder lines can best depict the morphological characteristics of the Loess Plateau. Moreover, a shoulder line depicts the external appearance of spatial differentiation of loess landforms and the internal mechanism of loess landform evolution. The efficient and accurate extraction of shoulder lines can help to deepen the re-understanding of the morphological structure and differentiation of loess landforms. However, the problem of shoulder line continuity in the extraction process has not been effectively solved. Therefore, based on high-resolution satellite images and digital elevation model (DEM) data, this study introduced the regional growing algorithm to further correct edge detection results, thereby achieving complementary advantages and improving the accuracy and continuity of shoulder line extraction. First, based on satellite images, the edge detection method was used to extract the original shoulder lines. Subsequently, by introducing the regional growing algorithm, the peaks and the outlet point extracted with the DEM were used as the growth points of the positive and negative (P-N) terrains to grow in four-neighborhood fields until they reached a P-N terrain boundary or a slope threshold. Finally, the P-N terrains extracted by the regional growing method were used to correct the edge detection results, and the “burr” was removed using a morphological image-processing method to obtain the shoulder lines. The experimental results showed that the method proposed in this paper can accurately and effectively complete the extraction of shoulder lines. Furthermore, the applicability of this method is better and opens new ideas for quantitative research on loess landforms.
Parallel Computation for Inversion Algorithm of 2D ZTEM
Authors: Wang Mao , Tan Handong , Wang Yuzhu , Lin Changhong , Peng Miao
Published: December 2022

ZTEM refers to the Z-axis tipper electromagnetic method. The ZTEM method is an airborne magnetotelluric sounding method based on the difference in rocks’ resistivity using the native electromagnetic field. The method is effective in exploring large-scale structures when the ground is fluctuant. The paper introduces the inversion algorithm of 2D ZTEM named the conjugate gradient method. This method, which avoids solving the Jacobi matrix, is very effective but not effective enough when the model is divided into a big grid. This study can perform further computation using parallel computation and then receive the processed data. We compare the results of the serial algorithm with the result of the parallel algorithm, which proves that the parallel algorithm is correct. When the number of processes is between three and six, the speedup ratio is between 1.74 and 3.19. It improves the effectiveness of the parallel algorithm of 2D ZTEM.
Prediction of Suzhou’s Industrial Power Consumption Based on Grey Model with Seasonal Index Adjustment
Authors: Chen Huimin , Sun Xiaoyan , Li Mei
Published: December 2022

The accurate prediction of industrial power consumption is conducive to the effective allocation of power resources by power and energy institutions, and it is also of great significance for the construction and planning of the national grid. By analyzing the characteristics of the data of Suzhou’s industrial power consumption between 2003 and 2005, this paper proposes a grey model with a seasonal index adjustment to predict industrial power consumption. The model results are compared with the traditional grey model, as well as the real value of Suzhou’s industrial power consumption, which shows that our model is more suitable for the prediction of industrial power consumption. The lasted Suzhou’s industrial power consumption data, from 2019–2021, are also investigated, and the results show that the prediction results are in very good agreement with the real data. The highlights of the paper are that all precision inspection indexes are excellent and the seasonal fluctuations in the data changes can be reflected in the present model.
Off-Axis Holographic Interferometer with Ensemble Deep Learning for Biological Tissues Identification
Authors: Lam Hoson , Zhu Yanmin , Buranasiri Prathan
Published: December 2022

This paper proposes a method with an off-axis interferometer and an ensemble deep learning (I-EDL) hologram-classifier to interpret noisy digital holograms captured from the tissues of flawed biological specimens. The holograms are captured by an interferometer, which serves as a digital holographic scanner to scan the tissue with 3D information. The method achieves a high success rate of 99.60% in identifying the specimens through the tissue holograms. It is found that the ensemble deep learning hologram-classifier can effectively adapt to optical aberration coming from dust on mirrors and optical lens aberrations such as the Airy-plaque-like rings out-turn from the lenses in the interferometer. The deep learning network effectively adapts to these irregularities during the training stage and performs well in the later recognition stage without prior optical background compensations. The method does not require an intact sample with a full outline shape of the specimens or the organs to understand the objects’ identities. It demonstrates a new paradigm in object identification by ensemble deep learning through a direct wavefront recognition technique.