bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sperm DNA methylome abnormalities occur both pre- and post-treatment in men with Hodgkin disease and testicular cancer
Authors: Chan Donovan , Klein Kathleen Oros , Riera-Escamilla Antoni , Krausz Csilla , O’Flaherty Cristian , Chan Peter , Robaire Bernard , Trasler Jacquetta 
Published: May 2022

Abstract
Background
Combination chemotherapy has contributed to increased survival from Hodgkin disease (HD) and testicular cancer (TC). However, questions concerning the quality of spermatozoa after treatment have arisen. While studies have shown evidence of DNA damage and aneuploidy in spermatozoa years following anticancer treatment, the sperm epigenome has received little attention. Our objectives here were to determine the impact of HD and TC, as well as their treatments, on sperm DNA methylation. Semen samples were collected from community controls (CC) and from men undergoing treatment for HD or TC, both before initiation of chemotherapy and at multiple times post-treatment. Sperm DNA methylation was assessed using genome-wide and locus-specific approaches.
Results
Imprinted gene methylation was not affected in the sperm of HD or TC men, before or after treatment. Prior to treatment, using Illumina HumanMethylation450 BeadChip (450K) arrays, a subset of 500 probes was able to distinguish sperm samples from TC, HD and CC subjects; differences between groups persisted post-treatment. Comparing altered sperm methylation between HD or TC patients versus CC men, twice as many sites were affected in TC versus HD men; for both groups, the most affected CpGs were hypomethylated. For TC patients, the promoter region of GDF2 contained the largest region of differential methylation. To assess alterations in DNA methylation over time/post-chemotherapy, serial samples from individual patients were compared. With restriction landmark genome scanning and 450K array analyses, some patients who underwent chemotherapy showed increased alterations in DNA methylation, up to two to three years post-treatment, when compared to the CC cohort. Similarly, a higher resolution human sperm-specific assay that includes assessment of environmentally-sensitive regions, or “dynamic sites”, also demonstrated persistently altered sperm DNA methylation in cancer patients post-treatment and suggested preferential susceptibility of “dynamic” CpG sites.
Conclusions
Distinct sperm DNA methylation signatures were present pre-treatment in men with HD and TC and may help explain increases in birth defects reported in recent clinical studies. Epigenetic defects in spermatozoa of some cancer survivors were evident even up to two years post-treatment. Abnormalities in the sperm epigenome both pre- and post-chemotherapy may contribute to detrimental effects on future reproductive health.
Response of Reinforced Concrete Box Girders Strengthened with composite Materials
Authors: Shaheen Yousry B.I. , Eltaly Boshra , Henish Amany 
Published: May 2022

Abstract
The current research includes the results of a practical and numerical program to determine the best way to enhance the behavior of RC box beams where the practical program relied on casting and testing 15 samples under bending. The factors that were taken into account were the use of ferrocement laminate at the tensile side or in the form of a U-shape, the number of meshes, as well as its type (welded or expanded) and the use of composite materials (CFRP, GFR). For composite materials, the strengthening was carried out in different ways, where it was applied at the tensile side only and wrapping the composite material around the web like a U-shape along the total beam’s length or as strips with different sizes and spacing. The outcomes showed that the girders strengthened by 4 GFRP and 1 CFRP layers as a U-shaped have the highest service load and ultimate load.
Smoothing Target Encoding and Class Center-Based Firefly Algorithm for Handling Missing Values in Categorical Variable
Authors: Nugroho Heru , Utama Nugraha Priya , Surendro Kridanto 
Published: May 2022

Abstract
One of the most common causes of incompleteness is missing data, which occurs when no data value for the variables in observation is stored. These common occurrences significantly affect the conclusions obtained from the specific data. An adaptive approach model outperforming other numerical methods in the classification problem was developed using the class center-based Firefly algorithm. This was accomplished by incorporating attribute correlations into the imputation process (C3FA). However, this model has not been tested on categorical data, which is essential in the preprocessing stage. This is because most machine learning algorithms only consider numerical variables. For processing, encoding is used to convert text or Boolean values into numeric parameters, and the target method is often utilized. This method uses target variable information to encode categorical data. However, it carries the risk of overfitting and inaccuracy within the infrequent categories. Therefore, this study aims to use the smoothing target encoding (STE) method to perform the imputation process by combining C3FA and standard deviation (STD). It also aimed to compare several methods for categorical data, such as mode imputation, DT imputation, and C3FA. The results on the tic tac toe dataset showed that the proposed method (STE + C3FA-STD) produced AUC, CA, F1-Score, precision, and recall values of 0.939, 0.882, 0.881, 0.881, and 0.882, respectively, based on the evaluation using the kNN classifier.
Reduced sensitivity of commercial Spike-specific antibody assays after primary infection with the SARS-CoV-2 Omicron variant
Authors: Springer David Niklas , Perkmann Thomas , Jani Claudia , Mucher Patrick , Prüger Katja , Marculescu Rodrig , Reuberger Elisabeth , Camp Jeremy Vann , Graninger Marianne , Borsodi Christian , Deutsch Josef , Lammel Oliver , Aberle Stephan Walter , Puchhammer-Stöckl Elisabeth , Haslacher Helmuth , Höltl Eva , Aberle Judith Helene , Stiasny Karin , Weseslindtner Lukas 
Published: May 2022

Abstract
ObjectivesThe SARS-CoV-2 Omicron variant is characterized by substantial changes in the antigenic structure of the Spike (S) protein. Therefore, antibodies induced by primary Omicron infection lack neutralizing activity against earlier variants. In this study, we analyzed whether these antigenic changes impact the sensitivity of commercial anti-SARS-CoV-2 antibody assays. MethodsSera from 37 unvaccinated, convalescent individuals after primary Omicron infection were tested with a panel of 20 commercial anti-SARS-CoV-2 immunoassays. As controls, we used samples from 43 individuals after primary infection with the SARS-CoV-2 ancestral wildtype strain. In addition, variant-specific live-virus neutralization assays were used as a reference for the presence of SARS-CoV-2-specific antibodies in the samples. Results Notably, in Omicron convalescents, there was a statistically significant reduction in the sensitivity of all antibody assays containing S or its receptor-binding-domain (RBD) as antigens. Furthermore, antibody levels quantified by these assays displayed a weaker correlation with Omicron-specific neutralizing antibody titers than with those against the wildtype. In contrast, the sensitivity of nucleocapsid-protein-specific immunoassays was similar in wildtype and Omicron-infected subjects. ConclusionsIn summary, the antigenic changes in the Omicron S lead to reduced detection rates in commercial S- and RBD-specific antibody assays, impairing their diagnostic performance.
Identifying Soil Erosion Hotspot Area Using GIS and MCDA Techniques, Case Study of Dengora and Meno Watersheds in Belesa Woredas, Amhara Region
Authors: Munye Kefale , Sintayehu Gashaw , Belayneh Alemshet , Mulat Chalachew 
Published: May 2022

Abstract
In Ethiopia soil erosion and land degradation has become a key issue, because of roughed and steep slope topography that soil erosion become accelerating. The main objective of this study was to identify soil erosion hotspot areas in Dengora and Meno watersheds using Revised Universal Soil Loss Equation (RUSLE) and Multi Criteria Decision Analysis (MCDA) techniques. To achieve such objective RUSLE model was used to estimate potential soil losses by utilizing information on Soil, land use/cover, topography, and climatic data. MCDA technique considered land use, soil type, topographic wetness index, stream power index and potential location of gullies. The factors were weighted using pair-wise comparison matrix and weights were combined using Weighted Overlay. Based on RUSLE model, the average annual soil loss of Dengora and Meno watersheds were reaches up to 223.97and 256.09-ton ha-1yr-1 respectively. In Dengora watershed 70.4%, 18.7%, 10.74% and 0.14% and Meno watershed 76%, 16.54%, 7.3% and 0.14% of the total watershed area slightly, moderately, highly and very highly sensitive to soil erosion respectively. On the other hand, GIS based MCDA technique reveals that in Dengora watershed 9.7%, 64.5%, 18% and 7.8% and Meno watershed 6.1%, 71.3%, 23.23% and 0.375% of the total watershed area was highly, moderately, slightly and currently not sensitive to soil erosion respectively. Based on validation, field level observation, MCDA model prediction was more accurate than RUSLE. Both of the watersheds were at moderate risk. Bottomlands of the watersheds under were highly sensitive areas for erosion. Therefore, immediate attention for soil and water conservation practices.
Over supplementation with vitamin B12 alters microbe-host interactions in the gut leading to accelerated Citrobacter rodentium colonization and pathogenesis in mice
Authors: Forgie Andrew J. , Pepin Deanna M. , Ju Tingting , Tollenaar Stephanie L. , Sergi Consolato M. , Gruenheid Samantha , Willing Benjamin P. 
Published: May 2022

Abstract
Background: Vitamin B12 supplements typically contain doses that far exceed the recommended daily amount, and high exposures are generally considered safe. Competitive and syntrophic interactions for B12 exist between microbes in the gut. Yet, to what extent excessive levels contributes to the activities of the gut microbiota remains unclear. The objective of this study was to evaluate the effect of B12 on microbial ecology using a B12 supplemented mouse model with Citrobacter rodentium, a mouse-specific pathogen. Mice were fed a standard chow diet and received either water or water supplemented with B12 (cyanocobalamin: ~120 mg/day), which equates to approximately 25 mg in humans. Infection severity was determined by body weight, pathogen load, and histopathologic scoring. Host biomarkers of inflammation were assessed in the colon before and after the pathogen challenge.Results: Cyanocobalamin supplementation enhanced pathogen colonization at day 1 (P < 0.05) and day 3 (P < 0.01) post-infection. The impact of B12 on gut microbial communities, although minor, was distinct and attributed to the changes in the Lachnospiraceae populations and reduced alpha diversity. Cyanocobalamin treatment disrupted the activity of the low-abundance community members of the gut microbiota. It enhanced the amount of interleukin-12 p40 subunit protein (IL12/23p40; P < 0.001) and interleukin-17a (IL-17A; P < 0.05) in the colon of naïve mice. This immune phenotype was microbe-dependent, and the response varied based on the baseline microbiota. The cecal metatranscriptome revealed that excessive cyanocobalamin decreased the expression of glucose utilizing genes by C. rodentium, a metabolic attribute previously associated with pathogen virulence.Conclusions: Oral vitamin B12 supplementation promoted C. rodentium colonization in mice by altering the activities of the Lachnospiraceae populations in the gut. A lower abundance of select Lachnospiraceae species correlated to higher p40 subunit levels, while the detection of Parasutterella exacerbated inflammatory markers in the colon of naïve mice. The B12-induced change in gut ecology enhanced the ability of C. rodentium colonization by impacting key microbe-host interactions that help with pathogen exclusion. This research provides insight into how B12 impacts the gut microbiota and highlights potential consequences of disrupting microbial B12 competition/sharing through over-supplementation.
PTPAMP: Prediction Tool for Plant-derived Antimicrobial Peptides
Authors: Jaiswal Mohini , Singh Ajeet , Kumar Shailesh 
Published: May 2022

Abstract
The emergence of antimicrobial peptides (AMPs) as a potential alternative to conventional antibiotics has led to the development of efficient computational methods for predicting AMPs. Amongst all organisms, the presence of multiple genes encoding AMPs in plants demands development of a plant-based prediction tool. To this end, we developed models based on multiple peptide features like amino acid composition, dipeptide composition, and physicochemical attributes for predicting plant-derived AMPs. The selected compositional models are integrated in a web server termed PTPAMP. The designed web server is capable to classify a query peptide sequence into four functional activities i.e. antimicrobial (AMP), antibacterial (ABP), antifungal (AFP), and antiviral (AVP). PTPAMP achieved an average area under the curve (AUC) of 0.95, 0.91, 0.85, and 0.88 for AMP, ABP, AFP, and AVP, respectively on benchmark datasets, which were ~ 6.75% higher than the state-of-the-art methods. Moreover, our analysis indicates the abundance of cysteine residue in plant-derived AMPs and distribution of other residues like G, S, K, and R which differs as per the peptide structural family. Finally, the developed web server is made user-friendly and presently available at http://www.nipgr.ac.in/PTPAMP/. We expect the substantial input of this predictor for high throughput identification of plant-derived AMPs followed by the additional insights into their functions.
Isolation and In silico prediction of potential drug-like compounds with a new dimeric prenylated quinolone alkaloid from Zanthoxylum rhetsa (Roxb.) root extracts targeted against SARS-CoV-2 (Mpro)
Authors: Zohora Fatema -Tuz- , Ahmed Sinthyia , Rahman Khondaker Miraz , Halim Mohammad A. , Anwar Md. Rafi , Sohrab Md. Hossain , Tabassum Fatema , Hasan Choudhury Mahmood , Ahsan Monira 
Published: May 2022

Abstract
A new dimeric prenylated quinolone alkaloid, named 2,11-didemethoxy-vepridimerine A, was isolated from the root bark of Zanthoxylum rhetsa, together with thirteen known compounds. The structure of the new compound was elucidated on the basis of spectroscopic investigations (NMR and Mass). The interaction of the isolated compounds with the main protease of SARS-CoV-2 (Mpro) was evaluated using molecular docking followed by MD simulations. The result suggests that 2, 11-didemethoxy- vepridimerine A, the new compound has the highest negative binding affinity against the Mpro with free energy of binding of-8.5 Kcal/mol indicating interaction with the Mpro. This interaction was further validated with the help of MD simulation using remdesivir, one of the currently approved drugs against SARS-CoV-2, as a control.
Resolving glycogen and related enzymes reveals correlates of Lactobacillus crispatus dominance in a cohort of young African women
Authors: Lithgow Karen V. , Cochinamogulos Athena , Muirhead Kevin , Konschuh Shaelen , Oluoch Lynda M. , Mugo Nelly R. , Roxby Alison C. , Sycuro Laura K. 
Published: May 2022

Abstract
Background: A healthy vaginal microbiome is dominated by Lactobacillus species that produce lactic acid, lowering vaginal pH and limiting colonization by pathogens. Lactobacillus dominance (LD) is established during puberty, but many women, especially those of Black race, lose LD during their reproductive years. Glycogen is thought to be a key host nutrient that supports vaginal lactobacilli and their fermentative lactic acid production, but mechanisms of glycogen utilization by Lactobacillus species are incompletely understood. By partitioning glycogen and glycogen-derived maltodextrin, as well as the activity of glycogen-degrading amylase and pullulanase enzymes (targeting glycogen α-1,4 and α-1,6 linkages, respectively) in vivo, this work refines understanding of vaginal glycogen catabolism and identifies correlates of LD. Results: Vaginal swab samples were collected from a cohort of young women with limited sexual experience in Thika, Kenya (N=17, ages 16–21). Metagenomic profiling of the vaginal microbiome revealed that most samples exhibited LD, particularly dominant Lactobacillus crispatus. Glycogen and pullulanase activity, but not maltodextrin and amylase activity correlated with lactic acid levels. Amylase activity showed a positive correlation with glycogen-derived maltodextrin, but no relationship with L. crispatus dominance. In contrast, pullulanase activity was 3-fold higher in L. crispatus-dominated samples. Metagenomics and targeted PCR revealed that 36% of L. crispatus-dominated metagenomes from our African cohort lacked a functional L. crispatus pullulanase (pulA) gene, a 3-fold higher frequency of gene loss than that seen in metagenomes from European and North American women. Our findings suggest pulA gene loss or inactivation may correspond with reductions in pullulanase activity, lactic acid, and L. crispatus abundance compared to samples dominated by pulA-competent L. crispatus. Conclusions: Our results indicate that although amylase activity drives the accumulation of glycogen catabolites in vaginal fluid, pullulanase appears to specifically contribute to maximal D-lactic acid production by L. crispatus. However, this is only possible when a functional pulA gene is present, which was not the case in a substantial proportion of young African women with dominant L. crispatus. Scaling this analysis to a larger cohort will address whether genomic and enzymatic indicators of L. crispatus pullulanase activity are predictive of sustained LD and vaginal health.
Climate Change, Rural Livelihood, and Sustainability: In Higher Himalayas of Kishtwar, Jammu and Kashmir
Authors: Jamal Shahid , Namkha Tenzen 
Published: May 2022

Abstract
Mountains host rich cultural and biological diversity and generate different ecosystem services. It acts as a water tower and source of food, but at the same time suffers from poverty, risks, and vulnerabilities. Climate change is the biggest threat overshadowing living organisms negatively impacting the rural livelihood of people living in the Himalayas. The warming has accelerated surpassing the global average over the past hundred years. Receding glaciers are leading to water scarcity not only for drinking but also for agriculture and allied activities. The erratic rainfall results in frequent flash floods and landslides causing huge damage to public and private infrastructures, life, and property. The basic objective of the study is to identify and analyse the interdependence between climate change and rural livelihood in the higher Himalayas. Both primary and secondary data were used for data analysis while descriptive and ethnographic methods were applied to achieve the desired result. A household survey using purposive sampling was conducted in Gandhari valley of Kishtwar district, Jammu and Kashmir in the year 2019. It was concluded that climate change has brought multiple changes in their environment and affected their livelihood in many folds. Migration has become a natural phenomenon in the valley where mostly males migrate to cities in winter due to unemployment and unbearable climatic condition. The rural poor were the worst hit because they were the most economically backward and vulnerable to these changes. Adaption to climate change is quite necessary and there is more need to promote traditional practices to retain sustainability in the valley.
Value of ypTNM stage in patients with rectal cancer
Authors: Chen Yue , Sun Zhe , Dong Xinxin , Liu Fang , Sun Deyu 
Published: May 2022

Abstract
Purpose: In the current NCCN guidelines, the prognosis and adjuvant chemotherapy regimen of patients who underwent neoadjuvant chemoradiotherapy, which are based on pre-radiotherapy clinical TNM stage or neoadjuvant pathologic TNM stage, are not clearly described. We investigated neoadjuvant pathologic TNM stage and clinical TNM stage, which can better reflect the prognosis of patients. Moreover, the clinical significance of the adjuvant chemotherapy regimen in different neoadjuvant pathologic TNM stages was studied.Methods: Between 2010 and 2015, a total of 316 rectal cancer patients who underwent neoadjuvant chemoradiotherapy, followed by radical resection, were retrospectively studied.Results: Our findings revealed that neoadjuvant pathologic TNM stage was a more important prognostic factor than clinical TNM stage. In different neoadjuvant pathologic TNM stages, adjuvant chemotherapy played important roles in stage-II and -III disease, but played no significant role in pCR and stage-I disease.Conclusion: Neoadjuvant pathologic TNM stage, rather than clinical TNM stage, was a more important prognostic factor. Among the patients who underwent neoadjuvant chemoradiotherapy, adjuvant chemotherapy had no significant benefit on the survival of patients in terms of pCR and neoadjuvant pathologic TNM stage I, but had different benefits in stage-II and -III disease.
Cognitive-aware Short-text Understanding for Inferring Professions
Authors: Esmailzadeh Sayna , Hosseini Saeid , Kamran Sara , Kangavari Mohammad Reza , Hua Wen 
Published: May 2022

Abstract
Leveraging short-text contents to estimate the occupation of microblog authors has significant gains in many applications. Yet challenges abound. Firstly brief textual contents come with excessive lexical noise that makes the inference problem challenging. Secondly, cognitive-semantics are not evident, and important linguistic features are latent in short-text contents. Thirdly, it is hard to measure the correlation between the cognitive short-text semantics and the features pertaining to various occupations. We argue that the multi-aspect cognitive features are needed to correctly associate short-text contents to a particular job and discover suitable people for the careers. To this end, we devise a novel framework that on the one hand, can infer short-text contents and exploit cognitive features, and on the other hand, fuses various adopted novel algorithms, such as curve fitting, support vector, and boosting modules to better predict the occupation of the authors. The final estimation module manufactures the R w-tree via coherence weight to tune the best outcome in the inferring process. We conduct comprehensive experiments on real-life Twitter data. The experimental results show that compared to other rivals, our cognitive multi-aspect model can achieve a higher performance in the career estimation procedure, where it is inevitable to neglect the contextual semantics of users.