Miracle-dz/UniFAR-FTUs huggingface dataset:
A genome-wide association analysis for salt tolerance during the soybean germination stage and development of KASP markers

Salt stress poses a significant challenge to crop productivity, and understanding the genetic basis of salt tolerance is paramount for breeding resilient soybean varieties. In this study, a soybean natural population was evaluated for salt tolerance during the germination stage, focusing on key germination traits, including germination rate (GR), germination energy (GE), and germination index (GI). It was seen that under salt stress, obvious inhibitions were found on these traits, with GR, GE, and GI diminishing by 32% to 54% when compared to normal conditions. These traits displayed a coefficient of variation (31.81% to 50.6%) and a substantial generalized heritability (63.87% to 86.48%). Through GWAS, a total of 1841 significant single-nucleotide polymorphisms (SNPs) were identified to be associated with these traits, distributed across chromosome 2, 5, 6, and 20. Leveraging these significant association loci, 12 candidate genes were identified to be associated with essential functions in coordinating cellular responses, regulating osmotic stress, mitigating oxidative stress, clearing reactive oxygen species (ROS), and facilitating heavy metal ion transport - all of which are pivotal for plant development and stress tolerance. To validate the candidate genes, quantitative real-time polymerase chain reaction (qRT-PCR) analysis was conducted, revealing three highly expressed genes (Glyma.02G067700, Glyma.02G068900, and Glyma.02G070000) that play pivotal roles in plant growth, development, and osmoregulation. In addition, based on these SNPs related with salt tolerance, KASP (Kompetitive Allele-Specific PCR)markers were successfully designed to genotype soybean accessions. These findings provide insight into the genetic base of soybean salt tolerance and candidate genes for enhancing soybean breeding programs in this study.
Are Supra-Physiological Plant-Based Antioxidants Ready for the Clinic? A Scoping Review of Hormetic Influences Driving Positive Clinical Outcomes

Background: A pro-inflammatory metabolic state is key to the chronic disease epidemic. Clinicians’ ability to use nutrients to balance inflammation via oxidant homeostasis depends on the quality of antioxidants research. Understanding the intersection of two prominent theories for how antioxidants quell inflammation—nutritional hormesis and oxidant scavenging—will enable therapeutic antioxidant use in clinical practice. Purpose: We sought to survey the literature to answer the question: has the hormetic response of exogenous antioxidants been studied in humans and if so, what is its effect Research Design: This review investigates the less well-established theory, nutritional hormesis. To understand the state of hormetic response research, we conducted a literature review describing the relationship between exogenous antioxidants, hormesis, and chronic disease. We used an adaptive search strategy (PubMed and Scopus), retrieving 343 articles, of which 218 were unique. Most studies reviewed the hormetic response in plant and cell models (73.6%) while only 2.2% were in humans. Results: Given the limited robust evidence, clinicians lack research-based guidance on the appropriate therapeutic dose of exogenous antioxidants or, more concerning, supra-physiological dosing via supplements. A critical hurdle in searching the literature is the lack of standardized nomenclature describing the hormetic effect, challenging the ability of clinicians to make informed decisions. Conclusion: Non-human research shows a biphasic, hormetic relationship with antioxidants but observational studies have yet to translate this into the complexities of human biochemistry and physiology. Therefore, we cannot accurately translate this into clinical care. To remedy this insufficiency, we suggest: (1) Improved data collection quality: controlled diet, standardized antioxidant measurements, bioavailability assessed via biomarkers; (2) Larger, harmonized datasets: research subject transparency, keyword standardization, consensus on a hormesis definition.
Geometric Variation Adaptive Network for Remote Sensing Image Change Detection

Change detection identifies surface changes on the Earth by comparing two images from the same area at different times. To generate smooth change maps, a common method is fusing information from neighboring areas around each pixel. While the conventional fusion methods primarily rely on fixed regular-shaped neighboring areas, which may be inadequate in capturing the diverse and irregular geometric structures of changed ground objects. To address this limitation, we propose a novel geometric variation adaptive change detector (GVA-CD), which adaptively adjusts the shape and size of neighboring areas based on the geometrical structure of ground objects. More specifically, we design a new geometric variation adaptive module (GVAM) as a component of GVA-CD. GVAM captures the structure of the ground objects to construct geometrically flexible neighboring areas for each pixel, enabling the model to adapt to different ground object structures and generate discriminative difference features. We further propose a new difference measurement module to compute the difference between the features of pre- and post-change images by leveraging the adaptive neighboring areas. In addition, the GVA-CD introduces a multistage cross-scale fusion mechanism in both feature extraction and change map generation, to enhance the scale adaption ability of the feature extraction and change map generation. Extensive experiments on three large datasets demonstrate that our GVA-CD can outperform existing methods in change detection.
Historiografía de la Edad del Hierro en Asturias Historiography of the Iron Age in Asturias

This paper intends to show the importance of historiographic studies in our discipline since our aim is making interpretations as objective as possible. To this end the concrete case of Iron Age Archaeology in Asturias (Northern Spain) is analysed by means of its division, from its birth at the beginning of the 19th century to the present day, into three clearly distinguished historiographic periods. Adiccionally the use of Bourdieu’s theory of social fields is suggested in order to develop the Social History of our discipline.
Few-shot disease recognition algorithm based on supervised contrastive learning

Diseases cause crop yield reduction and quality decline, which has a great impact on agricultural production. Plant disease recognition based on computer vision can help farmers quickly and accurately recognize diseases. However, the occurrence of diseases is random and the collection cost is very high. In many cases, the number of disease samples that can be used to train the disease classifier is small. To address this problem, we propose a few-shot disease recognition algorithm that uses supervised contrastive learning. Our algorithm is divided into two phases: supervised contrastive learning and meta-learning. In the first phase, we use a supervised contrastive learning algorithm to train an encoder with strong generalization capabilities using a large number of samples. In the second phase, we treat this encoder as an extractor of plant disease features and adopt the meta-learning training mechanism to accomplish the few-shot disease recognition tasks by training a nearest-centroid classifier based on distance metrics. The experimental results indicate that the proposed method outperforms the other nine popular few-shot learning algorithms as a comparison in the disease recognition accuracy over the public plant disease dataset PlantVillage. In few-shot potato leaf disease recognition tasks in natural scenarios, the accuracy of the model reaches the accuracy of 79.51% with only 30 training images. The experiment also revealed that, in the contrastive learning phase, the combination of different image augmentation operations has a greater impact on model. Furthermore, the introduction of label information in supervised contrastive learning enables our algorithm to still obtain high accuracy in few-shot disease recognition tasks with smaller batch size, thus allowing us to complete the training with less GPU resource compared to traditional contrastive learning.
Improvement of Shoulder Motion in Two-Stage Dual-Plane Implant-Based Breast Reconstruction followed by Radiation Therapy through Delayed Prepectoral Conversion

Background Although prepectoral implant-based breast reconstruction has recently gained popularity, dual-plane reconstruction is still a better option for patients with poor-quality mastectomy skin flaps. However, shoulder morbidity is aggravated by subpectoral reconstruction, especially in irradiated patients. This study aimed to demonstrate shoulder exercise improvement in subpectoral reconstruction by delayed prepectoral conversion with an acellular dermal matrix (ADM) inlay graft technique at the time of expander-to-implant exchange after irradiation. Methods Patients with breast cancer treated for expander-to-implant exchange after subpectoral expander insertion and subsequent radiotherapy between January 2021 and June 2022 were enrolled. An ADM inlay graft was inserted between the pectoralis major muscle and the previously inserted ADM. The ADM was sutured partially overlapping the pectoralis muscle from the medial side with the transition part, to the muscle border at the lateral side. Perioperative shoulder joint active range-of-motion (ROM) for forward flexion, abduction, and external rotation was also evaluated. Results A total of 35 patients were enrolled in the study. Active shoulder ROM significantly improved from 163 degrees preoperatively to 176 degrees postoperatively in forward flexion, 153 to 175 degrees in abduction, and 69 to 84 degrees in external rotation. There was no difference in patient satisfaction regarding the final outcome between the conventional prepectoral reconstruction group and the study group. Conclusion Shoulder exercises in irradiated patients who underwent subpectoral reconstruction were improved by delayed prepectoral conversion using an ADM inlay graft. It is recommended that subpectoral reconstruction not be ruled out due to concerns regarding muscle contracture and shoulder morbidity in radiation-planned patients with poor mastectomy skin flaps.
Movilidad social en la educación: el caso de la Universidad de los Andes en Colombia entre 1949 y 2018

La literatura académica ha destacado el papel de la educación para promover la movilidad social. Pero ¿cuánta movilidad han permitido históricamente las universidades de alta calidad? Esta investigación se centra en un estudio de caso de movilidad social histórica en una institución educativa de alta calidad en Colombia. Utilizando estimaciones basadas en apellidos poco frecuentes y su representación relativa en las personas graduadas de la Universidad de los Andes desde 1949 hasta 2018 se estiman coeficientes de movilidad intergeneracional para apellidos étnicos y de élite. Estas estimaciones proporcionan nueva evidencia de patrones de baja movilidad social, que se reflejan en la alta persistencia histórica de los grupos de élite, así como la ausencia o baja representación de las minorías étnicas. Además, se concluye que este enfoque metodológico puede ser una herramienta útil para medir movilidad social en países con limitaciones de datos históricos.
Progress Analytics in Support of Engineering Advising and Program Reform

Students in engineering programs are typically among those having the highest time-to-degree for any of the programs offered on a university campus. Keeping a cohort of students on track towards on-time graduation is extremely difﬁcult given the tightly prescribed nature of engineering programs. Any deviation from the standard degree plan, for any reason, including not passing a class, taking courses out of sequence, etc., often precludes the ability to graduate in four years. In this paper, we describe a cohort tracking analytics platform that can be used by advisors as an aid in keeping students on track, and by program administrators as a tool to better understand the curricular impediments associated with delays in graduation. This cohort analytics platform provides analyses over a population of students, rather than individual students, yielding valuable (often hidden) information regarding the impediments that students face. For instance, this platform makes it easier to determine what courses are most signiﬁcant in blocking the progress of a cohort, the efﬁciency of credit hour production within a cohort, where students are losing credit hours (i.e., generating credit hours that do not count towards the satisfaction of any degree requirements), etc. Advisors and administrators often suggest programmatic improvements based on anecdotal evidence
A pharmacovigilance study on antibody-drug conjugate (ADC)-related neurotoxicity based on the FDA adverse event reporting system (FAERS)

Background: Antibody-drug conjugates (ADCs) are a relatively new class of anticancer agents that use monoclonal antibodies to specifically recognize tumour cell surface antigens. However, off-target effects may lead to severe adverse events. This study evaluated the neurotoxicity of ADCs using the FDA Adverse Event Reporting System (FAERS) database. Research design and methods: Data were extracted from the FAERS database for 2004 Q1 to 2022 Q4. We analysed the clinical characteristics of ADC-related neurological adverse events (AEs). We used the reporting odds ratio (ROR) and proportional reporting ratio (PRR) for the disproportionality analysis to evaluate the potential association between AEs and ADCs. Results: A total of 562 cases of neurological AEs were attributed to ADCs. The median age was 65 years old [(Min; Max) = 3; 92]. Neurotoxic signals were detected in patients receiving brentuximab vedotin, enfortumab vedotin, polatuzumab vedotin, trastuzumab emtansine, gemtuzumab ozogamicin, inotuzumab ozogamicin, and trastuzumab deruxtecan. The payloads of brentuximab vedotin, enfortumab vedotin, polatuzumab vedotin, and trastuzumab emtansine were microtubule polymerization inhibitors, which are more likely to develop neurotoxicity. We also found that brentuximab vedotin- and gemtuzumab ozogamicin-related neurological AEs were more likely to result in serious outcomes. The eight most common ADC-related nervous system AE signals were peripheral neuropathy [ROR (95% CI) = 16.98 (14.94–19.30), PRR (95% CI) = 16.0 (14.21–18.09)], cerebral haemorrhage [ROR (95% CI) = 9.45 (7.01–12.73), PRR (95% CI) = 9.32 (6.95–12.50)], peripheral sensory neuropathy [ROR (95% CI) = 47.87 (33.13–69.19), PRR (95% CI) = 47.43 (32.93–68.30)], polyneuropathy [ROR (95% CI) = 26.01 (18.61–36.33), PRR (95% CI) = 25.75 (18.50–35.86)], encephalopathy [ROR (95% CI) = 5.16 (3.32–8.01), PRR (95% CI) = 5.14 (3.32–7.96)], progressive multifocal leukoencephalopathy [ROR (95% CI) = 22.67 (14.05–36.58), PRR (95% CI) = 22.52 (14.01–36.21)], taste disorder [ROR (95% CI) = 26.09 (15.92–42.76), PRR (95% CI) = 25.78 (15.83–42.00)], and guillain barrier syndrome [ROR (95% CI) = 17.844 (10.11–31.51), PRR (95% CI) = 17.79 (10.09–31.35)]. The mortality rate appeared to be relatively high concomitantly with AEs in the central nervous system. Conclusion: ADCs may increase the risk of neurotoxicity in cancer patients, leading to serious mortality. With the widespread application of newly launched ADC drugs, combining the FAERS data with other data sources is crucial for monitoring the neurotoxicity of ADCs. Further studies on the potential mechanisms and preventive measures for ADC-related neurotoxicity are necessary.
Use of Models as Non-destructive Method for Leaf Area Estimation in Horticultural Crops

Leaf area estimation is an important biometrical trait for evaluating leaf development and plant growth analysis in field study of horticultural as well as other species of crop plants. These measurements can be made either destructively and/or non-destructively by using a variety of sensitive instruments as well as models of leaf area estimation. Easy, accurate, cost-effective, and nondestructive methods of leaf area estimation are useful tool in physiological studies related to plant growth and development. The use of regression equations is a nondestructive, simple, quick, accurate, reliable and not expensive method of leaf area estimation. The usual procedure of this method involves measuring length (L), breadth (W) and/or dry mass (M) of a sample of leaves and then calculating the several possible regression coefficients or leaf factors to estimate the area of subsequent leaf samples. Computer programs such as Excel, SAS and SPSS may be used in this process. The paper thrashed out several leaf area estimation models of horticultural crops from the available literature and synthesized in tabular form for the use of researchers. Article also offered some advantages and disadvantages of leaf area estimation models used for analyzing the plant growth and development.
Sample Size Requirements of a Pharmaceutical Material Library: A Case in Predicting Direct Compression Tablet Tensile Strength by Latent Variable Modeling

The material library is an emerging, new data-driven approach for developing pharmaceutical process models. How many materials or samples should be involved in a particular application scenario is unclear, and the impact of sample size on process modeling is worth discussing. In this work, the direct compression process was taken as the research object, and the effects of different sample sizes of material libraries on partial least squares (PLS) modeling in the prediction of tablet tensile strength were investigated. A primary material library comprising 45 materials was built. Then, material subsets containing 5 × i (i = 1, 2, 3, …, 8) materials were sampled from the primary material library. Each subset underwent sampling 1000 times to analyze variations in model fitting performance. Both hierarchical sampling and random sampling were employed and compared, with hierarchical sampling implemented with the help of the tabletability classification index d. For each subset, modeling data were organized, incorporating 18 physical properties and tableting pressure as the independent variables and tablet tensile strength as the dependent variable. A series of chemometric indicators was used to assess model performance and find important materials for model training. It was found that the minimum R2 and RMSE values reached their maximum, and the corresponding values were kept almost unchanged when the sample sizes varied from 20 to 45. When the sample size was smaller than 15, the hierarchical sampling method was more reliable in avoiding low-quality few-shot PLS models than the random sampling method. Two important materials were identified as useful for building an initial material library. Overall, this work demonstrated that as the number of materials increased, the model’s reliability improved. It also highlighted the potential for effective few-shot modeling on a small material library by controlling its information richness.
Syringaldehyde Exhibits Antibacterial and Antioxidant Activities against Mycobacterium marinum Infection

Tuberculosis (TB) is caused by infection with Mycobacterium tuberculosis (Mtb), which has a unique resistance to many antimicrobial agents. TB has emerged as a significant worldwide health issue because of the rise of multidrug-resistant strains causing drug-resistant TB (DR-TB). As a result, the development of new drugs or effective strategies is crucial for patients with TB. Mycobacterium marinum (Mm) and Mtb are both species of mycobacteria. In zebrafish, Mm proliferates and forms chronic granulomatous infections, which are similar to Mtb infections in lung tissue. Syringaldehyde (SA) is a member of the phenolic aldehyde family found in various plants. Here, we investigated its antioxidative and antibacterial properties in Mm-infected cells and zebrafish. Our results demonstrated that SA inhibits Mm-infected pulmonary epithelial cells and inhibits the proliferation of Mm in Mm-infected zebrafish, suggesting that SA provides an antibacterial effect during Mm infection. Further study demonstrated that supplementation with SA inhibits the production of malondialdehyde (MDA) and reactive oxygen species (ROS) and increases the levels of reduced glutathione (GSH) in Mm-infection-induced macrophages. SA inhibits the levels of MDA in Mm-infected zebrafish, suggesting that SA exerts antioxidative effects in vivo. Additionally, we found that SA promotes the expression of NRF2/HO-1/NQO-1 and the activation of the AMPK-α1/AKT/GSK-3β signaling pathway. In summary, our data demonstrated that SA exerts antioxidative and antibacterial effects during Mm infection both in vivo and in vitro and that the antioxidative effects of SA may be due to the regulation of NRF2/HO-1/NQO-1 and the AMPK-α1/AKT/GSK-3β signaling pathway.
Container Preference of the Asian Tiger Mosquito (Aedes albopictus) in Kathmandu and Lalitpur Districts of Nepal

In various countries the Asian Tiger Mosquito (Aedes albopictus) is a known vector of dengue and chikungunya viruses and other pathogens, but its ecology and role in disease transmission in Nepal has not been studied yet. Here, we report on an investigation of the seasonal distribution of potential artificial breeding habitats of A. albopictus in urban areas of the Kathmandu and Lalitpur districts of Nepal. Larval collections were performed from April 2009 to March 2010 simultaneously in all the wet containers present in and around the houses of the study areas. Altogether 1873 water containers in Kathmandu district and 1807 in Lalitpur district were searched in 12 months, out of which 107 (5.7%) and 129 (7.1%), respectively, were found positive for A. albopictus breeding. Within the urban agglomeration of both districts, the breeding was found to vary between localities. Immature stages of A. albopictus were recorded in pre-monsoon, monsoon and post-monsoon seasons as 1.9%, 6.7% and 5.6%, respectively, in wet containers in Kathmandu district. In Lalitpur district, A. albopictus larvae were detected in 4.6%, 7.6% and 7.1% of the wet containers in the pre-monsoon, monsoon and post-monsoon, respectively. The breeding preference ratio during all seasons was highest for discarded tires lying outdoors in both Kathmandu and Lalitpur districts. Among nine container types searched and examined, 95% of discarded tires were found positive for A. albopictus larvae and pupae, followed by metal drums (2%) and plastic drums (1.25%). Continued and increased urbanization and vehicle movement in Kathmandu and Lalitpur districts have resulted in increased amounts of non-biodegradable containers such as tires around human dwellings, thereby creating ideal breeding habitats for A. albopictus.