bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of different water and fertilizer treatments on the matrix properties and plant growth of tailings waste
Authors: Li Yanchen , Yang Yang , He Jialin , Guo Shan , An Xuejing , Li Yan , Guo Rui , Lin Yipeng , Zhang Ruipeng 
Published: May 2024

Abstract

Phytoremediation is widely regarded as the most environmentally sustainable green technology for remediating mineral waste. The appropriate ratio of amendments can improve the substrate environment for plant growth and improve the repair efficiency. Study its improvement effect on tailings wasteland from the aspects of plant growth and nutritional elements. Considering that, this study explored the effects of water and fertilizer treatment on the physical and chemical properties and plant growth of quarry waste matrix with different ratios. The original soilwithout fertilizer and 45% water treatment was used as the control group (CK), and and the composite soil with different ratios of original soil and slag and various water and nitrogen fertilizer treatment combinations was used as the experimental group. Pennisetum alopecuroides (L.) Spreng, Campsis grandiflora (Thunb.) Schum, Setaria glauca (L.) Beauv, Periploca sepium Bunge and mugwort (Artemisia argyi Levl. Et Vant.)were planted in the control group and the experimental group respectively. After 30 days of nitrogen fertilizer and water treatment, an analysis was conducted to assess the physicochemical properties and the plant growth status of the tailing matrix for each experimental treatment. The results showed that the M5 treatment fostered the growth of Pennisetum alopecuroides (L.) Spreng and mugwort, while the M2 treatment promoted the growth of Campsis grandiflora (Thunb.) Schum, and the M3 treatment was beneficial to the growth of Setaria glauca (L.) Beauv and Periploca sepium Bunge. The soil matrix pH of Pennisetum alopecuroides (L.) Spreng, Campsis grandiflora (Thunb.) Schum, setaria glauca (L.) Beauv, and Periploca sepium Bunge and mugwort are all greater than 7.5, and macronutrient elements such as TK, AK, TN, AN, TP, and AP all have certain levels of improvement. PCA analysis showed that there were significant differences in substrate properties and plant growth properties between treatments for Pennisetum alopecuroides (L.) Spreng, Campsis grandiflora (Thunb.) Schum, Setaria glauca (L.) Beauv, Periploca sepium Bunge and mugwort (P<0.05). Correlation network and structural equation analysis showed that the water and fertilizer10 matrix had a significant positive correlation with soil AN and TN (P<0.05), and TK had a positive correlation with the growth status of five plants. The water and fertilizer substrate has a positive correlation with the growth status of Pennisetum alopecuroides (L.) Spreng, Setaria glauca (L.) Beauv, Periploca sepium Bunge and mugwort, and a negative correlation with the growth status of Campsis grandiflora (Thunb.) Schum.
Report of one case with de novo mutation in TLK2 and literature review
Authors: Li Han-Yue , Jiang Chun-Ming , Liu Ruo-Yan , Zou Chao-Chun 
Published: May 2024

Abstract

TLK2 variants were identified as the cause for several neurodevelopmental disorders by impacting brain development. The incidence of mutation in TLK2 is low, which has common clinical features with other rare diseases. Herein, we reported a 5-year-old boy with TLK2 heterozygous mutation who presented distinctive facial features, gastrointestinal diseases, short stature, language delay, autism spectrum disorder, heart diseases, abnormal genitourinary system and skeletal abnormality. Moreover, we reviewed previous reported patients and our case to investigate more information on genotype-phenotype correlation to conclude noteworthy clinical characteristics for the improvement of diagnosis.
Estimation of stress-strength reliability for type-1 pathway generated exponential distribution
Authors: James Gladvin V. , Xavier Thomas , Sebastian Nicy 
Published: May 2024

Abstract

A special case of the pathway generated family is computed with the exponential distribution and is called the type-1 pathway generated exponential distribution. The survival, hazard and moment generating function, likelihood ratio ordering, and stress-strength reliability are computed. For the estimation of stress-strength reliability parameter, point and interval estimator are computed using the maximum likelihood, and asymptotic confidence interval and bootstrap methods respectively. To verify the performance of the methods developed, an extensive Monte Carlo simulation study is conducted. The application of the developed results is illustrated on AIDS blood transfusion data.
Can Robotic Feedback and Adaptation Possibilities match Therapeutic Needs? - An Observational Study
Authors: Sommerhalder Michael , Büchi Madlaina , Risch Saskia , Raab Anja M , Widmer Mario , Riener Robert , Wolf Peter 
Published: May 2024

Abstract

Purpose: An observational study on therapists was executed as a joint project between the Sensory-Motor Systems Lab, ETH Zurich, and the Swiss Paraplegic Centre, Nottwil. The primary goal was to establish a methodology to reasonably tailor current robotic systems to the therapist's preferences in terms of their interaction strategies with the patient.
Methods: Therapist's interactions with the patient were recorded, either directly or through a robotic device with extended analysis tools and adaptation possibilities. Experience, operability bias and adaptation confidence of therapists were acquired through questionnaires. Correlation maps were derived to quantify the interaction strategies of the therapists.
Results: A total of three distinct interaction strategies emerged based on therapist's personal preferences: Observation of compensatory movement and posture issues caused tactile reaction, issues with robotic settings led to robotic support adaptations, and robotic support adaptations preceded support adaptations. Two strategies emerged based on the exercise type: Mainly direct tactile reactions for reach-goal exercises, and mainly robotic support adaptations for nominal path exercises. The adaptation confidence of therapists strongly depended on the chosen strategies.
Conclusion: Robotic systems can be tailored to the therapist's preferences in terms of their interaction strategies by quantifying the therapist's interactions with the robot and the patient. Missing parameters and analysis tools can be found by identifying compensatory strategies, i.e., situations where therapists are forced to swap to direct patient interactions or random parameter adaptations. With this study we presented a method to quantify these strategies with feasible effort.
AtML: Accurate identification of Arabidopsis thaliana root cell identity via single-cell sequencing analysis using interpretable machine learning
Authors: Yu Shicong , Fu Xiangzheng , Deng Xiaoshu , wang Hao , yan shen , Zheng shuqin , Ning Jingpeng , deng xiaoshu 
Published: May 2024

Abstract

Single-cell transcriptomics technologies are essential for understanding the developmental trajectory of plant roots. Although methods for interpreting single-cell transcriptomics data are rapidly advancing in Arabidopsis, precisely annotating cell identity and the occasional lack of canonical markers for certain cell types are major challenges in plant single-cell RNA sequencing (scRNA-seq) analysis. In this work, we trained a machine learning system, namely, AtML, using sequencing datasets from six cell subpopulations (comprising a total of 6000 cells) to predict Arabidopsis root cell stages and mine biomarkers via complete model interpretability. The results of performance testing using an external dataset revealed that AtML achieved 96.50% accuracy and 96.51% recall. With the power of interpretability provided by AtML, our model recognized 160 important marker genes, thus contributing to the understanding of cell type annotations. In conclusion, we trained AtML to efficiently identify Arabidopsis root cell stages, thereby providing insights into cellular heterogeneity in Arabidopsis root development studies.
Factors Associated with Uptake of Human Papilloma virus Vaccine among Adolescent girls : A cross sectional survey on insights into HPV Infection Prevention in Kabarole District
Authors: Asiimwe Solomon , Bagenda Fred N. , Mugisa Tony 
Published: May 2024

Abstract

Background: Human papilloma virus (HPV) infection imposes a substantial global disease burden and represents a critical public health concern. The persistently low uptake of HPV vaccination poses a significant obstacle to reducing cervical cancer incidence, particularly in remote rural areas of developing nations.
Objective: This study aims to assess the extent of Human papilloma virus vaccine coverage among adolescents and explore the associated determinants to facilitate enhanced planning strategies within the Kabarole district.
Methodology: Employing a cross-sectional survey approach, data were gathered from 240 adolescent girls residing in the Kabarole district between October 2021 and February 2022. Simple and multiple logistic regression analyses were employed to investigate the relationships between HPV vaccination uptake and various independent variables, including demographics, HPV knowledge, and health system factors.
Results : Of the 240 adolescents enrolled, the overall prevalence of uptake of HPV vaccination was 63%. The uptake of human papilloma was associated with demographics knowledge about HPV and health systems factors. The multivariate analysis showed that parents who completed secondary level of education were 4.1 times more likely to take their children for HPV vaccination compared to parents whose education level was primary or had no formal education(AOR=4.06; 95%CI(0.69-0.087); p=0.004). Distance from home to facility was associated with uptake HPV vaccination. Participants who came from the distance of more than 5 km were 60% less likely to uptake HPV vaccination compared to those who come from 5km or less (OR=0.4; 95%CI (1.43 – 8.09); p=0.006). Results further revealed that parents whose knowledge about HPV vaccination was moderate were three times more likely to take up HPV vaccine compared to those whose knowledge was low (OR = 2.99; 95%CI(1.14 – 7.87); p=0.026).
Conclusion : HPV vaccination uptake was at 63% and relatively lower than national average. Education of parents, Knowledge of HPV vaccination and distance to facility were factors significantly associated with uptake of Human papilloma virus vaccine
Investigation into Stethoscope Hygiene: Bacterial Contamination and Disinfection Methods among Medical Trainees
Authors: Ali Mousa , Awwad Mahdi , Eid Mahmoud , Jawabreh Ahmad , Abu-Tair Fatema , Zarour Abdalraziq , Mousa Ahmed , Qadi Mohammad , Zayed Ashraf R. , Alkaiyat Abdulsalam 
Published: May 2024

Abstract

The stethoscope, crucial in medical diagnosis, links doctors and patients. With the threat of hospital-acquired infections (HAIs), understanding stethoscope contamination and medical students' awareness is imperative. This study conducted from September to December 2022, the research involved 293 stethoscopes from three hospitals in the West Bank. Questionnaires probed students' practices, and Staphylococcus spp isolations were analyzed. Contamination rates, bacterial species, associations with disinfection practices and other hospital factors were explored. Stethoscope contamination rate was high in the three hospitals (range: 26.5–50.8 CFU/cm2). Staphylococcus spp contaminated 36.9% of stethoscopes. Methicillin Resistant S. aureus (MRSA) and Vancomycin Resistant S. aureus (VRSA) occurred in 16.6% and 1.8% respectively. 36% exhibited resistance to two or more antibiotics. The study revealed significant findings regarding stethoscope contamination. Those disinfecting stethoscopes between patients achieved a 29.4% acceptable rate, contrasting with a significantly higher 60.7% rate for non-disinfectors (P < 0.05). Reminders for disinfection in study units resulted in a 32.1% acceptable rate, whereas units without reminders had a significantly higher 67.9% rate (P < 0.001). Stethoscope usage also played a role, with a 34.4% acceptable rate for those examining only patients, compared to a significantly higher 65.8% rate for those examining both patients and peers (P < 0.05). Additionally, significant differences were observed in hospital, rotation, year-wise, disinfection frequency, and the presence of reminders. This study emphasizes the importance of stethoscope disinfection, reminders, and hand hygiene in reducing contamination. Educational interventions are critical.
Comparative assessment of multimodal sensor data quality collected using Android and iOS smartphones in real-world settings
Authors: Halabi Ramzi , Selvarajan Rahavi , Lin Zixiong , Herd Calvin , Li Sophia Xueying , Kabrit Jana , Tummalacherla Meghasyam , Neto Elias Chaibub , Pratap Abhishek 
Published: May 2024

Abstract

Healthcare researchers are increasingly utilizing smartphone sensor data as a scalable and cost-effective approach to studying individualized health-related behaviors in real-world settings. However, to develop reliable and robust digital behavioral signatures that may help predict disease trajectory early and future prognosis, there is a critical need to quantify potential technical variability that may be present in underlying sensor data due to variations in smartphone hardware and software used by large populations. Using sensor data collected in real-world settings from 3000 participants' smartphones for up to 84 days, we compared differences in completeness, correctness, and consistency of the three most common smartphone sensors — accelerometer, gyroscope, and GPS across Android and iOS devices. Our findings show considerable variation in sensor data quality within and across Android and iOS devices. Sensor data from iOS devices showed significantly lower levels of anomalous point density (APD) compared to Android across all sensors (p < 1e-4). iOS devices showed a considerably lower missing data ratio (MDR) for the accelerometer compared to the GPS data (p < 1e-4). Notably, the device type could be predicted with up to 0.98 accuracy 95% CI [0.977, 0.982] using the quality features derived from raw sensor data across devices. With a high degree of heterogeneity in smartphone devices, including iOS and Android, it's crucial to comprehend, measure, and address technical variations in underlying sensor data for creating robust, representative, and clinically actionable digital behavioral signatures linked to health outcomes.
Discovery of a novel methionine biosynthetic route via O-phospho-L-homoserine
Authors: Hasebe Fumihito , Adachi Kazuya , Maruyama Chitose , Hamano Yoshimitsu 
Published: May 2024

Abstract

Methionine (Met), a sulfur-containing amino acid, is essential for the underlying biological processes in living organisms. In addition to its importance as a starting building block for peptide chain elongation in protein biosynthesis, Met is a direct precursor of S-adenosyl-l-methionine, an indispensable methyl donor molecule in primary and secondary metabolism. Streptomycesbacteria are well known to produce diverse secondary metabolites, but many strains lack canonical Met pathway genes for L-homocysteine, a direct precursor of Met in bacteria, plants, and archaea. Here, we report the identification of a novel gene (metM) responsible for the Met biosynthesis in Streptomycesstrains and demonstrate the catalytic function of the gene product, MetM. We further identified the metO gene, a downstream gene of metM, and showed that it encodes a sulfur carrier protein (SCP). In in vitroanalysis, MetO was found to play an important role in a sulfur donor by forming a thiocarboxylated SCP. Together with MetO (thiocarboxylate), MetM directly converted O-phospho-L-homoserine to L-homocysteine. O-phospho-L-homoserine is also known as an intermediate for threonine biosynthesis in bacteria and plants, and MetM shares sequence homology with threonine synthase. Our findings thus revealed that MetM seizes O-phospho-L-homoserine from the threonine biosynthetic pathway and uses it as an intermediate of the Met biosynthesis to generate the sulfur-containing amino acid. Importantly, this MetM/MetO pathway is highly conserved in Streptomyces bacteria and distributed in other bacteria and archaea.
Evaluation of rain-shelter cultivation mode effects on microecological environment of mountain-cultivated ginseng rhizosphere
Authors: Yu Yinan , Piao Jingzi , Guo Siyi , Li Bing , Li Zibo , Zhou Rujun 
Published: May 2024

Abstract

Rainfall, particularly in continental climates with a monsoonal tendency, impacts the microbial niches during mountain-cultivated ginseng growth. With microbial community shifts, ginseng diseases cultivated and protected under rain-shelter cultivation may ultimately be altered. Such cultivation may influence microflora dynamics via meteorological parameter variations; however, this is unclear yet. The present study found that rain-shelter cultivation affects the distribution of fungal communities within the mountain-cultivated ginseng. This led to an improved community structure in the ginseng rhizosphere, characterized by the proliferation of antagonistic fungi and a reduction in pathogenic fungi. Alternaria, the pathogen of black spot, has exhibited larger differences, reaching more than 2 times during the flowering period and 4 times during the withering period. The correlation analysis of meteorological factors indicates that soil temperature and humidity are the primary meteorological factors that affect mountain-cultivated ginseng. It is evident that rain-shelter cultivation regulated the microecological environment of the mountain-cultivated ginseng rhizosphere and resulted in positive outcomes. The disease investigation supports this point; the number of main diseases under rain-shelter cultivation was lower than those under open-field cultivation. The incidence of ginseng root diseases, such as rust rot and root rot, was reduced by 5–6%. And the incidence of ginseng leaf diseases, including gray mold and black spot, was reduced by 5–10%. This research provides evidence to address the dynamics of microbial ecology under rain-shelter cultivation and its benefits for sustainable mountain-cultivated ginseng management.
Intraband Transitions at a CsPbBr3/GaAs Heterointerface in a Two-Step Photon Upconversion Solar Cell
Authors: Mahamu Hambalee , Asahi Shigeo , Kita Takashi 
Published: May 2024

Abstract

Two-step photon upconversion solar cells (TPU-SCs) based on III–V semiconductors can achieve enhanced sub-bandgap photon absorption because of intraband transitions at the heterointerface. From a technological aspect, the question arose whether similar intraband transitions can be realized by using perovskite/III–V semiconductor heterointerfaces. In this article, we demonstrate a TPU-SC based on a CsPbBr3/GaAs heterointerface. Such a solar cell can ideally achieve an energy conversion efficiency of 48.5% under 1-sun illumination. This is 2.1% higher than the theoretical efficiency of an Al0.3Ga0.7As/GaAs-based TPU-SC. Experimental results of the CsPbBr3/GaAs-based TPU-SC show that both the short-circuit current JSC and the open-circuit voltage VOC increase with additional illumination of sub-bandgap photons. We analyze the excitation power dependence of JSC for different excitation conditions to discuss the mechanisms behind the enhancement. In addition, the observed voltage-boost clarifies that the JSC enhancement is caused by an adiabatic optical process at the CsPbBr3/GaAs heterointerface, where sub-bandgap photons efficiently pump the electrons accumulated at the heterointerface to the conduction band of CsPbBr3. Besides the exceptional optoelectronic properties of CsPbBr3 and GaAs, the availability of a CsPbBr3/GaAs heterointerface for two-step photon upconversion paves the way for the development of high-efficiency perovskite/III–V semiconductor-based single-junction solar cells.
LASSO Based Analysis for Prediction of Prognostic Signature Genes Associated with Breast Cancer
Authors: Guha Souvik , Seth Soumita , Bhadra Tapas , Mukhopadhyay Anirban , Li Aimin , Mallik Saurav , Shah Mohd Asif 
Published: May 2024

Abstract

Background
Cancer is a genetic disease, where gene alterations play a significant role in the disease onset and pathogenesis. Analysis of the underlying gene interaction pathways could reveal new biomarkers and could also potentially help in the development of targeted drugs for therapeutics. Microarray techniques have emerged as powerful tools capable of simultaneously measuring the expression levels of thousands of genes, making them invaluable in cancer biology research. However, the processing of the resultant datasets poses significant challenges due to their high dimensionality. Also, feature extraction becomes essential to discern the crucial features within these extensive datasets. To mitigate these difficulties advanced computational techniques like Machine Learning (ML) could be instrumental. LASSO- regression-based classification is an advanced ML technique that can help in feature selection by evaluating individual parameters like genes.
Methods
This study focuses on uncovering key prognostic genes for breast cancer using a combination of LASSO regression-based classifier and statistical bioinformatics models. Differentially expressed genes (DEGs) were identified using the "Limma" package in R, and significant genes were further filtered using the LASSO-based classifier significance coefficient. Genes common to both methods were considered as the focus of this study. Additionally, Protein-Protein Interaction (PPI) networks of these key genes were constructed using STRING, and hub genes, significant modules, and associated genes were identified using Cytoscape.
Results
This study identified CCR8, CXCL11, CCL23, CCL24, CCL28, and CCL21 as signature prognostic genes for breast cancer, revealing a strong association between chemokines and breast cancer pathogenesis. Extensive literature searches were conducted to validate and confirm their prognostic significance in the disease.
Conclusion
These findings are pivotal for enhancing our comprehension of the pathways involved in breast cancer. Additionally, they hold promise as novel biomarkers for diagnostic purposes and may also reveal significant therapeutic targets for the management of breast cancer. The codes are available in the following GitHub repository: https://github.com/guhasouvik/LASSO_BRCA.git
Computational Pathology Assessments of Cardiac Stromal Remodeling: Clinical Correlates and Prognostic Implications in Heart Transplantation
Authors: Peyster Eliot , Yuan Cai , Arabyarmohammadi Sara , Lal Priti , Feldman Michael , Fu Pingfu , Margulies Kenneth , Madabhushi Anant 
Published: May 2024

Abstract

Both overt and indolent inflammatory insults in heart transplantation can accelerate pathologic cardiac remodeling, but there are few tools for monitoring the speed and severity of remodeling over time. To address this need, we developed an automated computational pathology system to measure pathologic remodeling in transplant biopsy samples in a large, retrospective cohort of n=2167 digitized heart transplant biopsy slides. Biopsy images were analyzed to identify the pathologic stromal changes associated with future allograft loss or advanced allograft vasculopathy. Biopsy images were then analyzed to assess which historical allo-inflammatory events drive progression of these pathologic stromal changes over time in serial biopsy samples. The top-5 features of pathologic stromal remodeling most strongly associated with adverse outcomes were also strongly associated with histories of both overt and indolent inflammatory events. Our findings identify previously unappreciated subgroups of higher- and lower-risk transplant patients, and highlight the translational potential of digital pathology analysis.