bluuebunny/crossref_metadata_2025 huggingface dataset:
The signature of pyroptosis-related gene prognostic and immune microenvironment in adrenocortical carcinoma
Authors: Gao Jun , Wang Dai , Yang Qingping , Tang Mengjie , Du Jiayi , He Leye , Liu Wei
Published: February 2023

Adrenocortical carcinoma (ACC) has a low incidence but a poor prognosis. And ACC has complex clinical manifestations and limited treatment. Pyroptosis has a dual character and has both positive and negative effects on cancer. However, the role of pyroptosis-related genes (PRGs) in ACC and the impact on ACC progression remains unelucidated. This study performed systematic bioinformatics analysis and basic experimental validation to enable the establishment of prognostic models and demonstrate levels of immune infiltration. Pearson’s correlation analysis was used to assess the association of PRGs with tumor immune infiltration, tumor mutation burden (TMB), microsatellite instability (MSI), and immune checkpoints. There 4 PRGs were upregulated, and 25 PRGs were downregulated in ACC. At the same time, we analyzed and reviewed the genetic mutation variation landscape of PRGs. Functional enrichment analysis was also performed to clarify the function of PRGs. Pyroptosis, the inflammatory response, the Toll-like receptor signaling pathway, and the NOD-like receptor signaling pathway are the functions and pathways mainly involved and exerted effects by these 33 PRGs. The results of the prognosis analysis revealed high expression of CASP3, CASP9, GSDMB, GSDMD, NLRC4, PRKACA, and SCAF11 caused a poor survival rate for ACC patients. The above seven PRGs were screened by the optimal λ value of LASSO Cox analysis, and the five selected genes (CASP3, CASP9, GSDMB, GSDMD, NLRC4) were involved in constructing a prognostic PRGs model which enables the overall survival in ACC patients can be predicted with moderate to high accuracy. Prognostic PRGs, especially CASP9, which is the independent factor of ACC prognosis, may be closely correlated with immune-cell infiltration, tumor mutation burden, microsatellite instability, and immune checkpoints. Quantitative Real-Time PCR (qRT-PCR), Western blot and immunohistochemical were performed to validate the mRNA expression levels of CASP9 in adjacent normal tissues and ACC tissues. According to the result of immune checkpoints analysis, NLRC4 and GSDMB may be identified as potential therapeutic targets. In conclusion, we established a prognostic model of PRG characteristics in ACC and analyzed the relationship between PRGs and immune infiltration. Through our study, it may be helpful to find the mechanism of pyroptosis in ACC.
Forebrain E-I balance controlled in cognition through coordinated inhibition and inhibitory transcriptome mechanism
Authors: Tian Tian , Cai You , Qin Xin , Wang Jiangang , Wang Yali , Yang Xin
Published: February 2023

Introduction

Forebrain neural networks are vital for cognitive functioning, and their excitatory-inhibitory (E-I) balance is governed by neural homeostasis. However, the homeostatic control strategies and transcriptomic mechanisms that maintain forebrain E-I balance and optimal cognition remain unclear.

Methods

We used patch-clamp and RNA sequencing to investigate the patterns of neural network homeostasis with suppressing forebrain excitatory neural activity and spatial training.

Results

We found that inhibitory transmission and receptor transcription were reduced in tamoxifen-inducible Kir2.1 conditional knock-in mice. In contrast, spatial training increased inhibitory synaptic connections and the transcription of inhibitory receptors.

Discussion

Our study provides significant evidence that inhibitory systems play a critical role in the homeostatic control of the E-I balance in the forebrain during cognitive training and E-I rebalance, and we have provided insights into multiple gene candidates for cognition-related homeostasis in the forebrain.
Preoperative hydronephrosis is an independent protective factor of renal function decline after nephroureterectomy for upper tract urothelial carcinoma
Authors: Cheng Pai-Yu , Lee Hsiang-Ying , Li Wei-Ming , Huang Steven K. , Liu Chien-Liang , Chen I-Hsuan Alan , Lin Jen-Tai , Lo Chi-Wen , Yu Chih-Chin , Wang Shian-Shiang , Chen Chuan-Shu , Tseng Jen-Shu , Lin Wun-Rong , Yeong-Chin Jou , Cheong Ian-Seng , Jiang Yuan-Hong , Lee Yu Khun , Chen Yung-Tai , Chen Shin-Hong , Chiang Bing-Juin , Hsueh Thomas Y. , Huang Chao-Yuan , Wu Chia-Chang , Lin Wei Yu , Tsai Yao-Chou , Yu Kai-Jie , Huang Chi-Ping , Huang Yi-You , Tsai Chung-You
Published: February 2023

Objectives

To evaluate the predictive role of pre-nephroureterectomy (NU) hydronephrosis on post-NU renal function (RF) change and preserved eligibility rate for adjuvant therapy in patients with upper tract urothelial carcinoma (UTUC).

Patients and methods

This retrospective study collected data of 1018 patients from the Taiwan UTUC Collaboration Group registry of 26 institutions. The patients were divided into two groups based on the absence or presence of pre-NU hydronephrosis. Estimated glomerular filtration rate (eGFR) was calculated pre- and post-NU respectively. The one month post-NU RF change, chronic kidney disease (CKD) progression, and the preserved eligibility rate for adjuvant therapy were compared for each CKD stage.

Results

404 (39.2%) patients without and 614 (60.8%) patients with pre-NU hydronephrosis were enrolled. The median post-NU change in the eGFR was significantly lower in the hydronephrosis group (-3.84 versus -12.88, p<0.001). Pre-NU hydronephrosis was associated with a lower post-NU CKD progression rate (33.1% versus 50.7%, p< 0.001) and was an independent protective factor for RF decline after covariate adjustment (OR=0.46, p<0.001). Patients with pre-NU hydronephrosis had a higher preserved eligibility rate for either adjuvant cisplatin-based chemotherapy (OR=3.09, 95%CI 1.95–4.69) or immune-oncology therapy (OR=2.31, 95%CI 1.23–4.34).

Conclusion

Pre-NU hydronephrosis is an independent protective predictor for post-NU RF decline, CKD progression, and eligibility for adjuvant therapy. With cautious selection for those unfavorably prognostic, non-metastatic UTUC patients with preoperative hydronephrosis, adjuvant rather than neoadjuvant therapy could be considered due to higher chance of preserving eligibility.
Effects of qigong exercise on cardiovascular risk factors in patients with metabolic syndrome: A systematic review and meta-analysis
Authors: Tao Shuoxiu , Li Zaimin
Published: February 2023

Background: As a traditional Chinese exercise system, Qigong includes many types of exercises, including Baduanjin, Wuqinxi, Yijinjing, and Liuzijue. However, reviews highlighting the effects of a specific type of Qigong exercise in patients with metabolic syndrome or risk factors for metabolic syndrome are limited, and no articles have systematically evaluated the effects of Qigong exercise on cardiovascular risk factors in patients with metabolic syndrome. Therefore, this systematic review aimed to evaluate the effects of Qigong exercise on cardiovascular risk factors in patients with metabolic syndrome.

Objective: Relevant randomized controlled trials were identified to conduct a meta-analysis of the effects of Qigong exercise on patients with metabolic syndrome, and to further explore the overall impact, heterogeneity, and publication bias related to the effects of Qigong exercise on metabolic syndrome.

Methods: We searched for RCTs of Qigong exercise in patients with metabolic syndrome from the following databases: Pubmed, Web of Science, The Cochrane Library, Scopus, Embase, Physiotherapy Evidenced Database (PEDro), Google Scholar, Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure Database (CNKI), Chinese Science, Wanfang Data, and the VIP database. The search duration was set from the establishment of the database to 16 April 2022. We used the “Bias Risk Assessment” tool recommended by Cochrane Manual 5.0 to assess the methodological quality of the included literature and the R (version 3.6.2) package gemtc to analyze the data.

Results: A total of seven RCTs with 486 participants were included in the meta-analysis. The results showed that Qigong exercise had significant effects on waist circumference (standardized mean difference [SMD] = −0.67; 95% CI, −1.16 to −0.17), systolic blood pressure (standardized mean difference = −0.53; 95% CI, −0.78 to −0.28) and triglyceride level (SMD = −0.60; 95% CI, −0.79 to −0.41). Subgroup analyses showed that 6-month Qigong exercise significantly improved diastolic blood pressure (SMD = −1.06; 95% CI, −1.57 to −0.56), high-density lipoprotein cholesterol level (SMD = 1.45; 95% CI, 1.06–1.85), total cholesterol level (SMD = −0.65; 95% CI, −1.04 to −0.27), and body mass index (SMD = −0.97; 95% CI, −1.23 to −0.72). For fasting blood glucose (SMD = −1.12; 95% CI, −1.58 to −0.67), the effect of a 3-month intervention seemed more effective than 6 months of Qigong exercise, but the evidence was insufficient. In addition, Qigong exercise had minimal effects on low-density lipoprotein cholesterol levels (SMD = −1.22; 95% CI, −1.95 to −0.50).

Conclusion: Qigong may be an alternative exercise mode to improve cardiovascular risk factors in patients with metabolic syndrome. However, the findings are limited by the number and quality of the included studies, and require validation through more high-quality studies.
Comparison and analysis of the biomechanics of the lower limbs of female tennis players of different levels in foot-up serve
Authors: Liang Zhiqiang , Wu Jinan , Yu Jiabin , Ying Shanshan , Liu Zhiyong , Zhang Yu , Gu Yaodong , Li Jianshe
Published: February 2023

Purpose: The purpose of this study was to examine biomechanical performance of the foot-up serve (FUS) in female tennis players at different skill levels.

Methods: FUS analysis was completed in the biomechanical laboratory by 32 female college tennis players at three different levels. During FUS, 3D-biomechanical data from tennis players’ lower limbs were collected. One-way ANOVA was used to examine differences in kinematic and kinetic data between groups

Results: Range of motion (ROM) of bilateral lower-limb joints revealed significant differences in kinematics performance during both the preparation and landing cushion phases (p < 0.05). During preparation, Level 3 was significantly longer than Level 2 (P-a = 0.042, P-b = 0.001, and P-c = 0.006). During the flight phase, significant differences between levels 1 and 3 (P-a:0.002) and levels 1 and 2 (P-c:0.000) were discovered (P-a:0.002 and P-c:0.000). There were significant height differences between levels 1 and 2 as well as between levels 1 and 3. (P-a = 0.001, P-c = 0.000). During serve preparation (P-c = 0.001) and landing, GRF’s peak was significantly higher than level 3. (P-c:0.007). Significant differences were found between groups in the LLS preparation stage, with level 3 significantly higher than levels 1 and 2. (P-a = 0.000, P-b = 0.001, and P-c = 0.000); during landing, level 2 LLS was significantly higher than levels 1 and 3. (P-a = 0.000, P-b = 0.000, and P-c = 0.035).

Conclusion: The range of motion of joints and the stiffness of the lower limbs have a significant impact on a tennis player’s FUS performance. A larger of joint mobility and lower-limb stiffness promote better performance during the FUS preparation stage.
Investigations into the impact of non-coding RNA on the sensitivity of gastric cancer to radiotherapy
Authors: Usman Muhammad , Beilerli Aferin , Sufianov Albert , Kudryashov Valentin , Ilyasova Tatiana , Balaev Pavel , Danilov Andrei , Lu Hong , Gareev Ilgiz
Published: February 2023

Non-coding RNAs (ncRNAs) are a newly discovered functional RNA different from messenger RNA, which can participate in regulating the occurrence and development of tumors. More and more research results show that ncRNAs can participate in the regulation of gastric cancer (GC) radiotherapy response, and its mechanism may be related to its effect on DNA damage repair, gastric cancer cell stemness, cell apoptosis, activation of epidermal growth factor receptor signaling pathway, etc. This article summarizes the relevant mechanisms of ncRNAs regulating the response to radiotherapy in gastric cancer, which will be directly important for the introduction of ncRNAs particularly microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) into clinical medicine as biomarkers and therapeutic targets.
Genome-wide analysis of long non-coding RNAs (lncRNAs) in tea plants (Camellia sinensis) lateral roots in response to nitrogen application
Authors: Hu Shunkai , Hu Yimeng , Mei Huiling , Li Jianjie , Xuan Wei , Jeyaraj Anburaj , Zhao Zhen , Zhao Yuxin , Han Rui , Chen Xuan , Li Xinghui
Published: February 2023

Tea (Camellia sinensis) is one of the significant cash crops in China. As a leaf crop, nitrogen supply can not only increase the number of new shoots and leaves but also improve the tenderness of the former. However, a conundrum remains in science, which is the molecular mechanism of nitrogen use efficiency, especially long non-coding RNA (lncRNA). In this study, a total of 16,452 lncRNAs were identified through high-throughput sequencing analysis of lateral roots under nitrogen stress and control conditions, of which 9,451 were differentially expressed lncRNAs (DE-lncRNAs). To figure out the potential function of nitrogen-responsive lncRNAs, co-expression clustering was employed between lncRNAs and coding genes. KEGG enrichment analysis revealed nitrogen-responsive lncRNAs may involve in many biological processes such as plant hormone signal transduction, nitrogen metabolism and protein processing in endoplasmic reticulum. The expression abundance of 12 DE-lncRNAs were further verified by RT-PCR, and their expression trends were consistent with the results of RNA-seq. This study expands the research on lncRNAs in tea plants, provides a novel perspective for the potential regulation of lncRNAs on nitrogen stress, and valuable resources for further improving the nitrogen use efficiency of tea plants.
Enhancing the accumulation of linoleic acid and α-linolenic acid through the pre-harvest ethylene treatment in Camellia oleifera
Authors: Li Hongbo , Ma Xiaoling , Wang Weiqi , Zhang Jiaxi , Liu Yuanzhe , Yuan Deyi
Published: February 2023

Camellia oleifera Abel. (C. oleifera) is an important woody edible oil tree species in China. The quality of C. oleifera oil (tea oil) is mainly determined by the contents of linoleic acid (LA) and α-linolenic acid (ALA). However, how to increase the contents of LA and ALA in tea oil and the corresponding regulating mechanism have not been clarified. In the present study, we found that the LA and ALA contents in C. oleifera seeds were significant positively associated with the concentrations of ethephon and were decreased by ethylene inhibitor treatment. Furthermore, 1.5 g L-1 ethephon could receive an optimal LA and ALA contents without adverse effects to the growth of ‘Huashuo’ trees in this study. The ethephon treatment also increased the contents of 1-aminocyclopropane-1-carboxylic acid (ACC), sucrose, soluble sugar and reducing sugar contents in seeds. Transcriptome analysis further suggested that exogenous ethephon application enhanced the accumulation of LA and ALA via regulating genes involved in LA and ALA metabolism, plant hormone signal transduction pathways, and starch and sucrose metabolism. Our findings confirm the role of ethylene in LA and ALA regulation and provide new insights into the potential utilization of ethylene as a LA and ALA inducer in C. oleifera cultivation.
Genome-wide identification and expression analysis of the regulator of chromosome condensation 1 gene family in wheat (Triticum aestivum L.)
Authors: An Xia , Zhao Shuqi , Luo Xiahong , Chen Changli , Liu Tingting , Li Wenlue , Zou Lina , Sun Chendong
Published: February 2023

Wheat (Triticum aestivum L., 2n = 6x = 42, AABBDD) is the world’s most widely cultivated crop and an important staple food for humans, accounting for one-fifth of calories consumed. Proteins encoded by the regulator of chromosome condensation 1 (RCC1) are highly conserved among eukaryotes and consist of seven repeated domains that fold into a seven-bladed propeller structure. In this study, a total of 76 RCC1 genes of bread wheat were identified via a genome-wide search, and their phylogenetic relationship, gene structure, protein-conserved domain, chromosome localization, conserved motif, and transcription factor binding sites were systematically analyzed using the bioinformatics approach to indicate the evolutionary and functional features of these genes. The expression patterns of 76 TaRCC1 family genes in wheat under various stresses were further analyzed, and RT-PCR verified that RCC1-3A (TraesCS3A02G362800), RCC1-3B (TraesCS3B02G395200), and RCC1-3D (TraesCS3D02G35650) were significantly induced by salt, cold, and drought stresses. Additionally, the co-expression network analysis and binding site prediction suggested that Myb-7B (TraesCS7B02G188000) and Myb-7D (TraesCS7D02G295400) may bind to the promoter of RCC1-3A/3B and upregulate their expression in response to abiotic stresses in wheat. The results have furthered our understanding of the wheat RCC1 family members and will provide important information for subsequent studies and the use of RCC1 genes in wheat.
Development and cytological characterization of wheat–Thinopyrum intermedium translocation lines with novel stripe rust resistance gene
Authors: Guo Xianrui , Huang Yuhong , Wang Jing , Fu Shulan , Wang Chunhui , Wang Mian , Zhou Chen , Hu Xiaojun , Wang Tao , Yang Wuyun , Han Fangpu
Published: February 2023

Wheat stripe rust is a destructive disease in many cool and temperate regions around the world. Exploiting novel sources of resistance can provide wheat cultivars with robust and durable resistance to stripe rust. The wheat–Thinopyrum intermedium addition line TAI-14 was proven to carry a stripe rust resistance gene (named as YrT14) on the alien Th. intermedium chromosome. In order to transfer the resistance gene to wheat, wheat–Th. intermedium translocation lines were created by irradiating the pollen of the line TAI-14. We totally obtained 153 wheat–Th. intermedium translocation lines, among which the long alien segmental translocation line Zhongke 78 and the intercalary translocation line Zhongke 15 not only showed good integrated agronomic traits but also were identified as highly resistant to stripe rust in both seedling and adult plant stages. The alien chromatin in Zhongke 15 was identified as an insertion into the satellite of chromosome 6B, a type of translocation never reported before in chromosome engineering. By screening Simple Sequence Repeat (SSR) and Expressed Sequence Tag (EST) markers as well as the markers developed from RNA-sequencing (RNA-Seq) data, 14 markers were identified specific for the alien chromosome and a physical map was constructed. Both Zhongke 78 and Zhongke 15 could be used as a novel source of stripe rust resistance for wheat breeding, and the linked marker T14K50 can be used for molecular marker–assisted breeding. Finally, based on the karyotype, reaction to stripe rust, and genome resequencing data of different wheat–Th. intermedium translocation lines, the stripe rust resistance gene YrT14 was located to an 88.1 Mb interval from 636.7 to 724.8 Mb on Th. intermedium chromosome 19 corresponding to 7J or 7Js.
Prevalence, pattern and determinants of disabilities in India: Insights from NFHS-5 (2019–21)
Authors: Pattnaik Sweta , Murmu Jogesh , Agrawal Ritik , Rehman Tanveer , Kanungo Srikanta , Pati Sanghamitra
Published: February 2023

There is a need to provide an overview of the disability burden in India as there are limited studies. The present study aimed to estimate the prevalence and assess the pattern and determinants of disability in India. We analyzed National Family Health Survey-5 data using the “svyset” command in STATA software. We assessed the correlates by multivariable regression and reported an adjusted prevalence ratio (aPR) with a 95% confidence interval (CI). QGIS 3.2.1 software was used for spatial analysis of distributions of different disabilities. The mean (SD) age of 28,43,917 respondents was 30.82 (20.62) years, with 75.83% (n = 21,56,633) and 44.44% (n = 12,63,086) of them being from a rural area and were not educated, respectively. The overall prevalence of disability was 0.93% [(95% CI: 0.92–0.95), n = 26,435] and 5.11% of households have one or more people with disability (PwD). Locomotor disabilities accounted for 44.73% of all disabilities (n = 10,730), followed by mental disabilities (20.07%, n = 4,814). Age 75 years and above (vs. 0–14 years) [aPR: 26.35 (23.63–29.37)], male (vs. female) [aPR: 1.58 (1.52–1.64)], no education (vs. higher education) [aPR: 4.42 (4–4.87)], unmarried (vs. married) [aPR: 8.85 (8.27–9.47)], seeking care of non-governmental organization (NGO) (vs. other) [aPR: 1.34 (0.95–1.89)] were significant independent determinants. The highest overall prevalence of disability and locomotor was in Lakshadweep/UTs (1.68%) and Delhi (58.5%), respectively. Out of every hundred individuals in India, one has a disability, and five out of every hundred households have one or more people with a disability. More intervention strategies should be planned, considering factors like education, residence, health promotion and caste so that the services provided by the government can be available and accessible to everyone in need.
Prediction of patient choice tendency in medical decision-making based on machine learning algorithm
Authors: Lyu Yuwen , Xu Qian , Yang Zhenchao , Liu Junrong
Published: February 2023

Objective

Machine learning (ML) algorithms, as an early branch of artificial intelligence technology, can effectively simulate human behavior by training on data from the training set. Machine learning algorithms were used in this study to predict patient choice tendencies in medical decision-making. Its goal was to help physicians understand patient preferences and to serve as a resource for the development of decision-making schemes in clinical treatment. As a result, physicians and patients can have better conversations at lower expenses, leading to better medical decisions.

Method

Patient medical decision-making tendencies were predicted by primary survey data obtained from 248 participants at third-level grade-A hospitals in China. Specifically, 12 predictor variables were set according to the literature review, and four types of outcome variables were set based on the optimization principle of clinical diagnosis and treatment. That is, the patient's medical decision-making tendency, which is classified as treatment effect, treatment cost, treatment side effect, and treatment experience. In conjunction with the study's data characteristics, three ML classification algorithms, decision tree (DT), k-nearest neighbor (KNN), and support vector machine (SVM), were used to predict patients' medical decision-making tendency, and the performance of the three types of algorithms was compared.

Results

The accuracy of the DT algorithm for predicting patients' choice tendency in medical decision making is 80% for treatment effect, 60% for treatment cost, 56% for treatment side effects, and 60% for treatment experience, followed by the KNN algorithm at 78%, 66%, 74%, 84%, and the SVM algorithm at 82%, 76%, 80%, 94%. At the same time, the comprehensive evaluation index F1-score of the DT algorithm are 0.80, 0.61, 0.58, 0.60, the KNN algorithm are 0.75, 0.65, 0.71, 0.84, and the SVM algorithm are 0.81, 0.74, 0.73, 0.94.

Conclusion

Among the three ML classification algorithms, SVM has the highest accuracy and the best performance. Therefore, the prediction results have certain reference values and guiding significance for physicians to formulate clinical treatment plans. The research results are helpful to promote the development and application of a patient-centered medical decision assistance system, to resolve the conflict of interests between physicians and patients and assist them to realize scientific decision-making.
Fear and Anxiety in Pregnant Women During the COVID-19 Pandemic: A Systematic Review
Authors: Muñoz-Vela Francisco Javier , Rodríguez-Díaz Luciano , Gómez-Salgado Juan , Fernández-Carrasco Francisco Javier , Allande-Cussó Regina , Vázquez-Lara Juana María , Fagundo-Rivera Javier
Published: February 2023

Objectives: The aim of this study was to explore the impact of the 2020–2022 pandemic on the levels of fear and anxiety in pregnant women and to identify risk and protective factors.

Methods: A systematic review was conducted. Electronic databases were consulted for studies published between January 2020 and August 2022. The methodological quality was assessed using a critical appraisal tool for non-randomised studies.

Results: Seventeen studies were included in the review. A high prevalence of levels of fear and anxiety were observed. Risk factors such as unplanned pregnancy, poor support from partners, or intolerance of uncertainty were identified for high levels of fear. Regarding anxiety, risk factors such as maternal age, social support, financial status, or concern about being able to maintain antenatal follow-ups were identified.

Conclusion: The COVID-19 pandemic had a significant impact on the mental health of pregnant women through increased levels of fear and anxiety. It has not been possible to establish a relationship between significant factors such as gestational age or health emergency control measures with high levels of fear or anxiety.
Nutritional Value and Sensory Quality of New Potatoes in Response to Silicon Application
Authors: Wadas Wanda
Published: February 2023

Since silicon regulates plant physiological and biochemical processes, it was hypothesized that foliar silicon application could contribute to improving the quality of new potatoes. This paper analyzes the effect of silicon (sodium silicate) on the nutritional value and sensory quality of new potatoes. Silicon was applied at the dose of 23.25 g Si·ha−1 or 46.50 g Si·ha−1 once at the leaf development stage (BBCH 14–16) or at the tuber initiation stage (BBCH 40–41) and twice, at the leaf development and tuber initiation stages. Potatoes were harvested 75 days after planting (the end of June). Silicon had no effect on the dry matter, total sugars and monosaccharides, protein, L-ascorbic acid or nitrate content in new potato tubers, but it increased the starch content under water deficit conditions. The most starch was accumulated by tubers following the application of 46.50 g Si·ha−1 at the leaf development stage (BBCH 14–16). Silicon did not affect the color of tuber flesh after cooking.
Toxicity of Insecticides in the Adult and Larva Olive Fruit Fly, after Estimation of the Dislodgeable Foliar and Fruit Residues in Olive Trees by LC-MS/MS and GC-MS/MS
Authors: Bempelou Eleftheria , Varikou Kyriaki , Anagnostopoulos Chris , Charalampous Angeliki , Samari Nikolia , Economou Leonidas , Garantonakis Nikolaos , Liapis Konstantinos
Published: February 2023

“Can systemic insecticides be used in bait spots in order to kill the adult olive fly?” Effort was directed toward providing an answer to that question. Both field and laboratory tests were implemented to detect the dislodgeable residues of dimethoate, phosmet and b-cyfluthrin in olive leaves and fruit using the LC-MS/MS and GC-MS/MS chromatographic techniques. Residues of dimethoate declined more over time than those of phosmet, while levels of beta-cyfluthrin remained almost stable, both in leaves and fruit. Additionally, significantly higher and faster toxicity of dimethoate and beta-cyfluthrin (>92%) compared to phosmet (80%) to fly adults was shown, which was reduced significantly after a two-week period. Conversely, 100% mortality of the larval stages within olive flesh was observed at the 2nd day for dimethoate and at the 7th day for phosmet. Although phosmet was not expected to contribute to preventing larval development, its application in bait sprays presented similar toxicity to that of dimethoate. However, no larval toxicity was recorded in beta-cyfluthrin. As a primary conclusion, we recommend the avoidance of the use of systemic insecticides in bait sprays.
Heritability and Genetic Advance Estimates of Key Shea Fruit Traits
Authors: Anyomi Wisdom Edem , Barnor Michael Teye , Danquah Agyemang , Ofori Kwadwo , Padi Francis Kwame , Avicor Silas Wintuma , Hale Iago , Danquah Eric Yirenkyi
Published: February 2023

Genetic erosion of shea trees, which has been on-going at an alarming rate, has necessitated urgent conservation attentions. Owing to the vast geographical distribution of the species across Ghana, in situ germplasms conservation was established by tagging and monitoring selected trees annually. Technologies have been developed that enable shea germplasms to be grafted, allowing for the development of germplasm banks at the research station of the Cocoa Research Institute of Ghana, Bole. However, before these materials could be used in crop improvement programs, there is a need to evaluate them for key fruit traits relevant to the global shea business. This experiment was carried out to evaluate the tagged in situ shea trees for fruit and nut traits. Freshly harvested shea fruits were evaluated for their brix, pulp yield and kernel size properties to see if there was the needed diversity for crop improvement gains. Eight key traits were studied, with all showing significant difference, with high broad sense heritability and genetic advance for all the traits, indicating the potential for genetic gains in breeding programs. Qualitative analysis classified the fruits into five shapes, ellipsoid fruit shape was the most frequent observation (69.5%), while oblong was the least represented (1%). Fruit surface pubescence indicated that the surfaces without hairs (smooth) were slightly higher in number (52.6%) than the surface with hairs (rough), which were 47.4%. Pearson correlation studies showed a positive significant relationship between kernel weight and fruit weight (0.68), fruit length (0.48), fruit width (0.51), pulp weight (0.5) and shell weight (0.77). Key components responsible for total variations observed were decomposed from the first two principal components (PC), which cumulatively explained 78.4% of the total observed variation within the materials. PC1 alone contributed 46.4%, while PC2 contributed 32%. Fruit weight, fruit length, fruit width, pulp weight, nut weight, shell weight and kernel weight were contributing traits to variations observed in PC1, while brix and percent pulp contributed to the variations observed in PC2. Percent kernel to nut ratio contributed to the variations observed in PC3. Clustering of the germplasms showed no regular pattern based on location or any particular trait, indicating a high level of diversity at 58% of the Pearson dissimilarity index.
Revealing Genetic Variations Associated with Chip-Processing Properties in Potato (Solanum tuberosum L.)
Authors: Jo Kwang Ryong , Choi Jang-Gyu , Kwon Do-Hee , Park Young-Eun , Kim Su-Jeong
Published: February 2023

Although the potato chip industry is booming, and distinct chip-processing clones have been released over the past 60 years, the genetic architecture of their chip-processing characteristics remains largely unknown. Case-control genome-wide association studies (GWAS) with SolCAP SNP array data for chip-processing clones versus all other market classes in the 393-line potato diversity panel were performed using the GWASpoly R package, enabling detection of significant signals on chromosome 10. Our results were replicated using internal replication of a strata-corrected 190-line panel. Furthermore, the genomic scans employing selective sweep approaches such as the cross-population composite likelihood ratio method (XP-CLR) and PCAdapt redetected the same signals as those in our GWAS. Through applications of four selective sweep approaches, various genetic variants were found across the genome that had been differentially selected. These genomic regions under selection along with transcriptomic data analysis are involved in carbohydrate metabolism-related genes or loci and transcription factors, indicating to be associated with the improvement of chip-processing performance of potato cultivars. Kompetitive allele-specific PCR (KASP) assays were designed for the causal SNPs to use in validating the chip-processing clones. The results could have implications for genomics-assisted breeding of the promising chip-processing cultivars in potato.
Sour Orange Microbiome Is Affected by Infections of Plenodomus tracheiphilus Causal Agent of Citrus Mal Secco Disease
Authors: Dimaria Giulio , Mosca Alexandros , Anzalone Alice , Paradiso Giuseppe , Nicotra Daniele , Privitera Grete Francesca , Pulvirenti Alfredo , Catara Vittoria
Published: February 2023

Mal secco is a severe vascular citrus disease (MSD) caused by the mitosporic fungus Plenodomus tracheiphilus (Pt). The pathogen enters through wounds on the above- and below-ground parts of the tree. The susceptible species sour orange (Citrus aurantium) is the most commonly used rootstock for lemon trees in Italy. In this study, sour orange seedlings were wound-inoculated with P. tracheiphilus in leaves or roots. Six months post-inoculation, the microbial communities of rhizosphere, endorhizosphere, and xylem endosphere samples from inoculated and healthy plants were analyzed by 16S rRNA and ITS (internal transcribed spacer) amplicon sequencing. The DNA of Pt was quantified by real-time PCR in the three compartments. According to our results, the endorhizosphere of root-inoculated plants showed the highest concentration of the pathogen DNA. Bacterial populations of potentially beneficial taxa (e.g., Pseudomonas and Burkholderia) were depleted in the rhizosphere of the inoculated plants. Infection through leaves and roots also produced a network-wide rewiring of microbial associations in sour orange roots. Overall, our findings revealed community-level changes induced by Pt infection in the sour orange root and xylem microbiome, providing further insights into the beneficial multispecies interactions in Citrus-associated microbial communities.
A Combined Ridging and Cover Crop Tillage System for Sustainable Coffee Plantation in Kenya
Authors: Alele Joseph O. , Ding Qishuo , Sayed Hassan A. A.
Published: February 2023

The introduction of ridge tillage and beans as a cover crop was investigated as a means of management for mitigating soil erosion and increasing the physical functionalities of soil. In a completely randomized design, four treatments were applied to twelve plots, three with ridges introduced (T1), three with beans as the cover crop (T2), three with cover crops combined with ridges (T3), and another three as controls without intervention (T4). Four physical properties were monitored, i.e., soil moisture content, bulk density, infiltration rate, and aggregate stability. Data were collected from two seasons with beans as the cover crop, with each season lasting three months. The results showed that T3 resulted in the highest soil moisture content at 34.87 ± 6.78%, followed by T2 and T1 with 34.20 ± 0.65% and 32.65 ± 1.71%, respectively, while T4 had the minimum value of 28.28 ± 5.30%. The bulk density of the soil was found to be lowest at T2 and T3, both having a value of 0.92 g cm−3 with standard deviations of ±0.03 and ±0.11, respectively. This was followed by T1 with 0.98 ± 0.05 g cm−3 while T4 had the highest bulk density of 1.17 ± 0.13 g cm−3. A similar trend was observed for both the basic infiltration rate and aggregate stability, except that, in terms of the latter, T1 was ranking second after T3, with 64.07% of water stable aggregates greater than 0.25 mm diameter. The interventions introduced in coffee plantations had significant effects on the bulk density and infiltration rate; however, there was no significant difference in the moisture content and aggregate stability. Further investigation is needed to quantify the environmental effects of these interventions, e.g., greenhouse gas emissions and yields.
Using Machine Learning to Predict Antimicrobial Resistance―A Literature Review
Authors: Sakagianni Aikaterini , Koufopoulou Christina , Feretzakis Georgios , Kalles Dimitris , Verykios Vassilios S. , Myrianthefs Pavlos , Fildisis Georgios
Published: February 2023

Machine learning (ML) algorithms are increasingly applied in medical research and in healthcare, gradually improving clinical practice. Among various applications of these novel methods, their usage in the combat against antimicrobial resistance (AMR) is one of the most crucial areas of interest, as increasing resistance to antibiotics and management of difficult-to-treat multidrug-resistant infections are significant challenges for most countries worldwide, with life-threatening consequences. As antibiotic efficacy and treatment options decrease, the need for implementation of multimodal antibiotic stewardship programs is of utmost importance in order to restrict antibiotic misuse and prevent further aggravation of the AMR problem. Both supervised and unsupervised machine learning tools have been successfully used to predict early antibiotic resistance, and thus support clinicians in selecting appropriate therapy. In this paper, we reviewed the existing literature on machine learning and artificial intelligence (AI) in general in conjunction with antimicrobial resistance prediction. This is a narrative review, where we discuss the applications of ML methods in the field of AMR and their value as a complementary tool in the antibiotic stewardship practice, mainly from the clinician’s point of view.
Omega-Class Glutathione Transferases Protect DNA from Oxidative Stress in Pathogenic Helminth Reproductive Cells
Authors: Kim Jeong-Geun , Kang Insug , Ahn Chun-Seob , Sohn Woon-Mok , Kong Yoon
Published: February 2023

Pathogenic helminths have evolved mechanisms to preserve reproductive function while surviving long-term in the host via robust protective responses. A protective role of antioxidant enzymes in preventing DNA degradation has long been proposed, but little evidence has been provided. Here, we show that omega-class glutathione transferases (GSTOs) are critical for maintaining viability by protecting the reproductive cell DNA of the carcinogenic liver fluke, Clonorchis sinensis. Clonorchis sinensis GSTO (CsGSTO) activities modified by changes in the GSH/GSSG and NADPH/NADP+ molar ratios suppressed the overproduction of reactive oxygen species. CsGSTO1 and CsGSTO2 catalyzed deglutathionylation under physiologic and low-stress conditions (GSH/GSSG ratio of 6:1 or higher) but promoted glutathionylation under high-stress conditions (GSH/GSSG ratio of 3:1 or lower). Gliotoxin-induced functional disruption of CsGSTOs in living C. sinensis reduced the GSH/GSSG molar ratio and increased the production of protein glutathionylation (PSSG) under physiologic and low-stress conditions, indicating that suppression of GSTO function did not affect deglutathionylation. However, the perturbation of CsGSTOs decreased the GSH/GSSG ratio but also reduced PSSG production under high oxidative stress, demonstrating that glutathionylation was impeded. In response to oxidative stimuli, C. sinensis decreased GSTO-specific dehydroascorbate reductase and thiol transferase activities and the GSH/GSSG ratio, while it increased the NADPH/NADP+ ratio and PSSG. CsGSTOs utilized GSH to regulate GSH/GSSG and NADPH/NADP+ recycling and triggered a redox signal leading to nuclear translocation. Nuclear-imported CsGSTOs were modified by glutathionylation to prevent DNA damage. Antibodies specific to CsGSTOs dose-dependently inhibited this process. Disruption of CsGSTOs or the depletion of GSH caused glutathionylation defects, leading to DNA degradation. Our results demonstrate that CsGSTOs and the GSH system play a previously unappreciated role in protecting DNA from oxidative stress.
LC-MS and GC-MS Data Fusion Metabolomics Profiling Coupled with Multivariate Analysis for the Discrimination of Different Parts of Faustrime Fruit and Evaluation of Their Antioxidant Activity
Authors: Cannavacciuolo Ciro , Pagliari Stefania , Giustra Chiara Maria , Carabetta Sonia , Guidi Nissim Werther , Russo Mariateresa , Branduardi Paola , Labra Massimo , Campone Luca
Published: February 2023

The comparative chemical composition of different part of Faustrime fruits (peels, pulp, albedo, and seeds) extracted with different solvents was determined by GC-MS and UHPLC-HRMS QTof. The obtained data were also combined for their in vitro antioxidant activity by multivariate analysis to define a complex fingerprint of the fruit. The principal component analysis model showed the significative occurrence of volatile organic compounds as α-bisabolol and α-trans-bergamotol in the pulp and albedo, hexanoic acid in the seeds, and several coumarins and phenolics in the peels. The higher radical scavenging activity of the pulp was related to the incidence of citric acid in partial least square regression.
Addition of Mentha arvensis in Infusions of Cleistocalyx operculatus Improves the Hedonic Score and Retains the High Antioxidant and Anti Lipid-Peroxidation Effects
Authors: Minh Tran Thi Le , Kieu Luu Thi Bich , Mai Son Thi Tuyet , Ngoc Dang Long Bao , Thuy Le Thi Bich , Quyen Nguyen Thi , Anh Ton Trang , Huy Le Van , Phong Nguyen Vu , Duyen Chung Thi My , Minh Nguyen Hoang , Eric Gontier
Published: February 2023

(1) Background: Many human diseases are associated with oxidative stress, which is caused by reactive oxygen species and free radicals generated in living cells. Some biomass extracts derived from various types of plants can act as efficient drugs against pathological disorders related to oxidative stress. Numerous herbal blends have thus been shown to improve health. Cleistocalyx operculatus (Roxb.) Merr. and L.M.Perry teas have been considered in that way. Problem: Because of amertume, the taste of C. operculatus avoids or limits a large use of such alleged healthy leaf infusions. (2) Methods: The phytochemistry, oxygen, free radical scavenging activity, and antilipid peroxidation of C. operculatus teas were here studied in vitro. Then different mixes of C. operculatus and Mentha arvensis were infused together and tasted in a hedonic test. The chemical and biological properties of the best mix were then analyzed. (3) Results: The herbal blend of C. operculatus revealed significant scavenging effects on 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) with IC50 values of 35.6 µg/mL. Induced by hydroxyl radicals, this beverage could significantly inhibit the lipid peroxidation of mouse brain homogenates. Our results demonstrate that the lipid peroxidation inhibition of dried leaves of C. operculatus might be related to its scavenging effects on oxygen free radicals. This C. operculatus bitter blend was then combined with various amounts of M. arvensis Linn. The taste was evaluated, and further biochemical analyses were conducted on the best 7/3 ratio. They showed that the healthy properties were maintained. (4) Conclusion: The optimized 7/3 ratio of the Cleistocalyx/Mentha mix led to the best results in terms of taste (sensory tests). It is demonstrated that the potential health benefits against oxidative stress remained high as compared with pure C. operculatus infusion.
AI-For-Mobility—A New Research Platform for AI-Based Control Methods
Authors: Ruggaber Julian , Ahmic Kenan , Brembeck Jonathan , Baumgartner Daniel , Tobolář Jakub
Published: February 2023

AI-For-Mobility (AFM) is the new research platform to investigate and implement novel control methods based on Artificial Intelligence (AI) within the Department of Vehicle System Dynamics at the German Aerospace Center (DLR). A production hybrid vehicle serves as a base platform. Since AI-based methods are data-driven, the vehicle is equipped with manifold sensors to provide the required data. They measure the vehicle’s state holistically and perceive the surrounding environment, while high performance on-board CPUs and GPUs handle the sensor data. A full by-wire control system enables the vehicle to be used for applications in the field of automated driving. Despite all modifications, it is approved for public road use and meets the driving dynamics properties of a standard road vehicle. This makes it an attractive research and test platform, both for automotive applications and technology demonstrations in other scientific fields (e.g., robotics, aviation, etc.). This paper presents the vehicle’s design and architecture in a detailed manner and shows a promising application potential of AFM in the context of AI-based control methods.
Classification of Bugs in Cloud Computing Applications Using Machine Learning Techniques
Authors: Tabassum Nadia , Namoun Abdallah , Alyas Tahir , Tufail Ali , Taqi Muhammad , Kim Ki-Hyung
Published: February 2023

In software development, the main problem is recognizing the security-oriented issues within the reported bugs due to their unacceptable failure rate to provide satisfactory reliability on customer and software datasets. The misclassification of bug reports has a direct impact on the effectiveness of the bug prediction model. The misclassification issue surely compromises the accuracy of the system. Manually reviewing bug reports is necessary to solve this problem, but doing so takes a lot of time and is tiresome for developers and testers. This paper proposes a novel hybrid approach based on natural language processing (NLP) and machine learning. To address these issues, the intended outcomes are multi-class supervised classification and bug prioritization using supervised classifiers. After being collected, the dataset was prepared for vectorization, subjected to exploratory data analysis, and preprocessed. The feature extraction and selection methods used for a bag of words are TF-IDF and word2vec. Machine learning models are created after the dataset has undergone a full transformation. This study proposes, develops, and assesses four classifiers: multinomial Naive Bayes, decision tree, logistic regression, and random forest. The hyper-parameters of the models are tuned, and it is concluded that random forest outperformed with a 91.73% test and 100% training accuracy. The SMOTE technique was used to balance the highly imbalanced dataset, which was initially created for the justified classification. The comparison between balanced and imbalanced dataset models clearly showed the importance of the balanced dataset in classification as it outperformed in all experiments.
Efficient Data Preprocessing with Ensemble Machine Learning Technique for the Early Detection of Chronic Kidney Disease
Authors: Venkatesan Vinoth Kumar , Ramakrishna Mahesh Thyluru , Izonin Ivan , Tkachenko Roman , Havryliuk Myroslav
Published: February 2023

It is a serious global health concern that chronic kidney disease (CKD) kills millions of people each year as a result of poor lifestyle choices and inherited factors. Effective prediction tools for prior detection are essential due to the growing number of patients with this disease. By utilizing machine learning (ML) approaches, this study aids specialists in studying precautionary measures for CKD through prior detection. The main objective of this paper is to predict and classify chronic kidney disease using ML approaches on a publicly available dataset. The dataset of CKD has been taken from the publicly available and accessible dataset Irvine ML Repository, which included 400 instances. ML methods (Support Vector Machine (SVM), K-Nearest Neighbors (KNN), random forest (RF), Logistic Regression (LR), and Decision Tree (DT) Classifier) are used as base learners and their performance has been compared with eXtreme Gradient Boosting (XGBoost). All ML algorithms are evaluated against different performance parameters: accuracy, recall, precision, and F1-measure. The results indicated that XGBoost outperformed with 98.00% accuracy as compared to other ML algorithms. For policymakers to forecast patterns of CKD in the population, the model put forth in this paper may be helpful. The model may enable careful monitoring of individuals who are at risk, early CKD detection, better resource allocation, and management that is patient-centered.