Types Of Samples Research Articles

Evaluating the Impact of Laundering on the Electrical Performance of Wearable Photovoltaic Cells: A Comparative Study of Current Consistency and Resistance

Wearable photovoltaic technology has been prominent in recent years because electronic devices need to be powered continuously without reliance on traditional methods. However, the practical adoption of wearable PV cells is hindered by the need for laundering, potentially degrading performance. This research compared PV cells’ maximum current and electrical resistance before and after laundering testing conditions. This study used eight samples of two types of PV panel cells and laundered them up to five cycles. The current and electrical resistance values were recorded before and after each laundering cycle. This study analyzed the data using a paired sample t-test and MANOVA. It was found that laundering cycles significantly affected the current values in both types of samples, with no differential impact between the types; on the other hand, laundering cycles did not significantly affect the electrical resistance values in both types of samples, with no differential impact between the types. These results are crucial for industries developing textile-based PV panels, where maintaining electrical performance after laundering is essential. These findings could pave the way for more sustainable, self-powered wearable PV technologies, ultimately transforming how users interact with electronic devices daily.

Seroprevalence of Toxoplasma gondii in Cattle in Southern Egypt: Do Milk and Serum Samples Tell the Same Story?

Toxoplasma gondii is an intracellular protozoan parasite of veterinary and public health importance. Infection may lead to abortion in susceptible pregnant animals and women, and potentially fatal health complications in immunocompromised individuals. In this study, we aimed to provide an update on the seroprevalence of, and risk factors for, T. gondii antibodies in cattle from Qena, southern Egypt. Additionally, we investigated if raw milk and serum samples from the same animals reacted similarly in a commercial ELISA, thus potentially reducing the invasiveness of future serosurveillance studies. Cattle serum samples (n = 362) from three locations in the Qena governorate (Qena, Qus, and Al Waqf cities), of both sexes and different ages were collected. From most dairy cows, a corresponding milk sample (n = 154) was additionally obtained. We found that the overall seroprevalence in serum samples was 9.1% (33/362). Increasing age was the sole risk factor identified in our study among all tested parameters (location, age, sex, lactating yes or no). Thus, older cattle (more than 3 years old) exhibited significantly higher rates of T. gondii antibodies (11.7%; p = 0.033, odd ratio = 4.3) in comparison to animals younger than 1 year (2.9%). In the corresponding serum and milk samples, the prevalence was 12.3% (19/154) in serum samples, and 9.7% (15/154) in milk samples, respectively. A high correlation was observed between the two sample types with a concordance of 97.4%, a kappa value of 0.87, and a Pearson r correlation coefficient of 0.85. When the serum ELISA was taken as the gold standard, the milk ELISA had the following characteristics: sensitivity (78.9%), specificity (100%), positive predictive value (100%), negative predictive value (97.1%), and area under the receiver operating characteristic (ROC) curve (0.6, p = 0.0011). In this study, we confirmed the frequent occurrence of T. gondii antibodies in cattle in southern Egypt and demonstrated that non-invasive milk samples may be used instead of serum samples for seroprevalence studies in dairy cows.

Online Impulse Buying: A Systematic Review of 25 Years of Research Using Meta Regression

ABSTRACTIn the dynamic realm of online commerce, the phenomenon of Online Impulse Buying (OIB) has become a focal point of extensive research. Despite the multitude of studies exploring antecedents, mediators, and moderating factors, inconsistencies in findings have hindered generalization. To bridge this gap, we conducted a comprehensive meta‐analysis, synthesizing data from 84 empirical results across 75 research articles up to December 2023. Encompassing a cumulative sample size of 139,545 participants and 341 effects, our analysis aimed to evaluate the strength and significance of associations with OIB. Results revealed substantial influences on OIB, with Situational stimuli (ESr = 0.477), Marketing stimuli (ESr = 0.433), Customer related factors (ESr = 0.388), and Platform related factors (ESr = 0.362) emerging as key contributors. The heightened impact of situational and marketing stimuli reflects the evolving landscape of OIB. Additionally, we explored six potential moderators—culture, sample type, sampling method, online commerce type, and data collection technique—uncovering statistically significant effects on some aggregated correlations. By shedding light on the changing dynamics of OIB, our findings provide valuable insights for both researchers and practitioners navigating the intricate landscape of online impulse buying. Finally, we outline future research directions to guide ongoing exploration in this rapidly evolving field.

Study on the Mechanical and Permeability Evolution of a Composite Rock Mass in an Aquifuge Under Hydraulic Coupling

The lithology and composition type of an aquifuge in overburden play a crucial role in influencing the crack evolution and permeability changes of the aquifuge. This study utilized the high-temperature and high-pressure rock triaxial seepage test system to conduct triaxial compression tests on mudstone, sandstone, and their combined rock samples. The mechanical characteristics and permeability evolution of each lithology law during the failure were investigated. Furthermore, computed tomography (CT) scanning technology was utilized for the three-dimensional (3D) reconstruction and theoretical permeability calculation of single and combined rock samples. The results indicated that the stress–strain curves for single and combined rock samples exhibited similar patterns, which were divided into four stages: pore compaction, linear elasticity, yield deformation, and post-peak residual deformation. The peak strength of rock samples positively correlated with confining pressure. Permeability trends for mudstone and sandstone exhibited an “N”-type pattern characterized by “slow decrease–gradual stabilization–sudden increase–rebound decrease”, while the permeability of mudstone–sandstone combined rock followed a “U”-type pattern of “initial decrease–stabilization–subsequent increase”. Notably, the permeability of the combined rock samples was significantly lower compared to the single rock samples. The failure mode indicated that fractures in a single rock sample transversed the entire sample, whereas failures in the combined rock samples were confined to the mudstone component. This observation accounted for the differences in the permeability changes between the rock sample types. Additionally, the theoretical permeability results from the 3D reconstruction correlated with the experimental results.

Macrophage Immunomodulation and Suppression of Bacterial Growth by Polydimethylsiloxane Surface-Interrupted Microlines’ Topography Targeting Breast Implant Applications

Since breast cancer is one of the most common forms of cancer in women, silicone mammary implants have been extensively employed in numerous breast reconstruction procedures. However, despite the crucial role they play, their interaction with the host’s immune system and microbiome is poorly understood. Considering this, the present work investigates the immunomodulatory and bacterial mitigation potential of six textured surfaces, based on linear step-like features with various regular and irregular multiscaled arrangements, in comparison to a flat PDMS surface. We hypothesise that the chosen surface geometries are capable of modulating the cellular response through mechanical interdigitation within the multiscaled surface morphology, independent of the surface chemical properties. Each type of sample was characterised from a physico-chemical and biological points of view and by comparison to the flat PDMS surface. The overall results proved that the presence of linear multiscaled step-like features on the PDMS surface influenced both the surface’s characteristics (e.g., surface energy, wettability, and roughness parameters), as well as the cellular response. Thus, the biological evaluation revealed that, to different degrees, biomaterial-induced macrophage activation can be mitigated by the newly designed microtextured surfaces. Moreover, the reduction in bacteria adherence up to 90%, suggested that the topographical altered surfaces are capable of suppressing bacterial colonisation, therefore demonstrating that in a surgical environment at risk of bacterial contamination, they can be better tolerated.

Defining the optimal setting for transcriptomic analyses on blood samples for response prediction in immunotherapy-treated NSCLC patients

Transcriptomic profiling of blood immune cells offers a promising alternative to invasive, sampling bias-prone tissue-based biomarker assays for predicting immune checkpoint inhibitor (ICI) therapy response in non-small cell lung cancer (NSCLC) patients. However, the optimal analytical approach to identify systemic correlates of response still needs to be explored. We collected peripheral blood mononuclear cells and whole blood (WB) samples from 33 ICI-treated NSCLC patients before ICI treatment and at the first response evaluation. After bulk polyadenylated RNA-sequencing, we assessed differences in gene expression profiles between non-responders and responders using differential expression analysis, single sample gene set enrichment analysis (ssGSEA), and cell type deconvolution. We evaluated gene expression values, ssGSEA scores, and deconvolved cell type proportions to distinguish non-responders from responders via ROC curve (AUC) analysis, training a logistic regression classification model. Gene expression values and deconvolved proportions yielded the best results with WB samples after treatment (AUC = 0.87 and 0.85, respectively). Overall, ssGSEA scores showed superior classification performance across all sample types and timepoints (AUC > 0.7). In conclusion, transcriptomic analysis through ssGSEA demonstrated the best performance as a non-invasive biomarker for predicting clinical benefit in ICI-treated NSCLC patients, with gene expression and deconvolution on post-treatment WB samples also showing promising results.

Quality assessment of various Xiushui Ninghong tea types.

Xiushui Ninghong tea (XSNH) has a long history and is renowned both in China and internationally. Based on different processing techniques, XSNH can be classified into Ninghong Congou, Ninghong Tea Jinhao, Ninghong Tea Longxucha and other types. To investigate the differences in nutrient compounds and mineral element contents among various types of XSNH, 34 samples from seven types were collected, primarily from tea-producing areas. Statistical analysis indicated no significant differences in the contents of crude polysaccharides, K, Mg and Fe, whereas significant differences were observed in the levels of moisture, free amino acids, caffeine, tea polyphenols, thearubigin, theaflavins, Zn, P, Mn, Cu and Se. The data were analyzed using various statistical methods such as hierarchical cluster analysis, principal component analysis and partial least squares discriminant analysis. Characteristic compounds and elements such as theaflavin, Se, free amino acids, P and tea polyphenols were identified as key differential components for distinguishing different sample types. Our research has highlighted the differences in chemical indicators among various types of XSNH, providing a crucial theoretical basis for the future classification and grading of XSNH quality. © 2024 Society of Chemical Industry.

Multiomic characterization of RNA microenvironments by oligonucleotide-mediated proximity-interactome mapping.

RNA molecules form complex networks of molecular interactions that are central to their function and to cellular architecture. But these interaction networks are difficult to probe in situ. Here, we introduce Oligonucleotide-mediated proximity-interactome MAPping (O-MAP), a method for elucidating the biomolecules near an RNA of interest, within its native context. O-MAP uses RNA-fluorescence in situ hybridization-like oligonucleotide probes to deliver proximity-biotinylating enzymes to a target RNA in situ, enabling nearby molecules to be enriched by streptavidin pulldown. This induces exceptionally precise biotinylation that can be easily optimized and ported to new targets or sample types. Using the noncoding RNAs 47S, 7SK and Xist as models, we develop O-MAP workflows for discovering RNA-proximal proteins, transcripts and genomic loci, yielding a multiomic characterization of these RNAs' subcellular compartments and new regulatory interactions. O-MAP requires no genetic manipulation, uses exclusively off-the-shelf parts and requires orders of magnitude fewer cells than established methods, making it accessible to most laboratories.

Nymphaea lotus Distribution in Oguta Lake: Implications for Heavy Metal Pollution in Surface Water and Sediments

Water quality is increasingly deteriorating and has affected lakes, which are important sources of freshwater. Heavy metals are of great concern because they are mostly toxic and resistant to decomposition. Aquatic macrophytes serve as stable biological filters that purify water bodies by accumulating dissolved metals and toxins in their tissues. Given their ability to trap various toxic heavy metals, the macrophyte Nymphaea lotus, which is observed on the surface waters of Oguta Lake, was studied to estimate the concentrations of six heavy metals in the water, sediment, and macrophytes. This was achieved by studying the spatial and temporal distribution of Nymphaea lotus in the lake and analysing the concentrations of heavy metals in the surface water, macrophytes, and sediment samples. Descriptive statistics, exploratory data analysis, and correlation analysis were used to analyse data obtained. Results revealed that the population of Nymphaea lotus declines over time from June to November in all regions. Upstream had the highest concentration of macrophytes (64%), while the downstream area has the lowest (2%). The heavy metal concentrations in the three samples ranges from 0.16 mg/kg to 2.96 mg/kg in sediments and Nymphaea lotus, and from 0.16 mg/L to 2.16 mg/L in water, with lead showing the highest concentration across all sample type. This highlights heavy metal contamination in the lake. The sparsely populated Nymphaea lotus exhibits selective bioaccumulation of lead, mercury, and zinc, while it seems to exclude or inefficiently absorb arsenic and chromium. Correlation analysis suggests a close interdependence between the concentrations of metals in sediments, water, and macrophytes, with sediments playing a key role in both water contamination and macrophyte metal absorption. Corrective and preventive measures should be taken to restore the lake.

SRSF12 is a prognostic biomarker involved in immune infiltration in acute myeloid leukemia

ABSTRACT Background Acute myeloid leukemia (AML) is a disease characterized by the proliferation of abnormal cells originating from blood stem cells. Understanding the pathogenesis and progression of AML, as well as identifying molecular markers for early diagnosis and prognosis assessment, is of paramount importance. Methods The AML dataset was obtained from the Cancer Genome Atlas (TCGA), while the normal sample dataset was derived from the Genotype-Tissue Expression(GTEx) dataset. Furthermore, the association between SRSF12 expression and drug response was assessed using the Cancer Therapeutic Response Portal (CTRP) database to evaluate its potential therapeutic value. Finally, SRSF12 expression in AML cells was measured using quantitative real-time PCR (qRT-PCR). Result The difference in SRSF12 expression between 13 types of tumors and normal tissue samples was found to be statistically significant (P < 0.05). SRSF12 exhibited predominantly high expression in AML, indicating its potential as a diagnostic and prognostic marker for AML patients. High expression of SRSF12, along with age and cytogenetic risk, emerged as independent predictors of favorable prognosis in AML patients (P < 0.05). PCR demonstrated a significant increase in SRSF12 expression in AML patients. Conclusion Overall, our findings suggest that the high expression of SRSF12 in AML patients is a poor prognostic factor, which may provide a new option for the diagnosis, and targeted therapy of AML.

ADVANCED PREDICTIVE MODELING FOR THE BIOFIRE FILMARRAY SYSTEM IN INFECTIOUS DISEASE DIAGNOSTICS

The Bio Fire Film Array System has emerged as a powerful tool in clinical diagnostics, offering rapid and multiplexed detection of infectious pathogens. This study presents the development of a comprehensive mathematical model aimed at predicting the accuracy and sensitivity of the BioFire FilmArray System under diverse conditions. Key factors such as sample type, pathogen load, specimen characteristics, and environmental variables were systematically analyzed to elucidate their impact on the system's performance. The model incorporates a range of parameters including sample volume, specimen complexity, microbial diversity, and system-specific variables to generate probabilistic estimates of diagnostic outcomes. By leveraging large datasets encompassing diverse clinical scenarios and pathogen profiles, the model achieves robustness and generalizability, thereby facilitating its applicability across different healthcare settings and populations. Validation of the model against independent datasets demonstrates its efficacy in accurately predicting the performance of the BioFire FilmArray System across a spectrum of conditions. Overall, this mathematical model represents a significant advancement in optimizing the utility of the BioFire FilmArray System for infectious disease diagnosis. Its integration into clinical practice holds promise for improving patient care, guiding sample processing protocols, and informing decision-making processes in infectious disease management.

The Corrosive Effect of School Administrators as Toxic Leaders on Teacher Accountability

Purpose: To examine teachers' views on the corrosive effect of toxic leadership behaviours of school administrators on teacher accountability. Design/Methodology/Approach: The study group of this research, which uses phenomenology as a qualitative research design, was selected using maximum variation sampling method, which is a type of purposive sampling. This group consists of 20 teachers working in 10 public schools in the central district of Isparta. Data were collected from the teachers through a semi-structured interview form. The collected qualitative data were subjected to contextual analysis through MAXQDA software and visualised. The findings show that the majority of teachers reported that toxic leadership has a detrimental effect on teacher accountability. Findings: Toxic leaders, characterised by behaviours such as micromanagement, lack of empathy, and aggressive communication, were found to cause teacher demotivation, alienation, and professional burnout. In addition, toxic leaders erode teacher accountability by creating a negative and insecure organisational climate. Highlights: Toxic leadership behaviours of school administrators are a critical factor that significantly affects teacher accountability. The various dimensions of this impact are as follows: Decreased teacher motivation, psychological safety and job satisfaction, decreased performance and productivity, impeded professional development, stress and burnout. In addition to these, toxic leadership has a negative impact on school climate. A negative school climate leads to a decrease in teachers' willingness to cooperate and be accountable. This can also negatively impact student achievement because lack of co-operation and support among teachers reduces the quality of education. Therefore, it is important for school administrators to exhibit more positive and supportive leadership behaviours to increase teachers' motivation and strengthen their accountability.

Identification of diagnostic markers pyrodeath-related genes in non-alcoholic fatty liver disease based on machine learning and experiment validation

Non-alcoholic fatty liver disease (NAFLD) poses a global health challenge. While pyroptosis is implicated in various diseases, its specific involvement in NAFLD remains unclear. Thus, our study aims to elucidate the role and mechanisms of pyroptosis in NAFLD. Utilizing data from the Gene Expression Omnibus (GEO) database, we analyzed the expression levels of pyroptosis-related genes (PRGs) in NAFLD and normal tissues using the R data package. We investigated protein interactions, correlations, and functional enrichment of these genes. Key genes were identified employing multiple machine learning techniques. Immunoinfiltration analyses were conducted to discern differences in immune cell populations between NAFLD patients and controls. Key gene expression was validated using a cell model. Analysis of GEO datasets, comprising 206 NAFLD samples and 10 controls, revealed two key PRGs (TIRAP, and GSDMD). Combining these genes yielded an area under the curve (AUC) of 0.996 for diagnosing NAFLD. In an external dataset, the AUC for the two key genes was 0.825. Nomogram, decision curve, and calibration curve analyses further validated their diagnostic efficacy. These genes were implicated in multiple pathways associated with NAFLD progression. Immunoinfiltration analysis showed significantly lower numbers of various immune cell types in NAFLD patient samples compared to controls. Single sample gene set enrichment analysis (ssGSEA) was employed to assess the immune microenvironment. Finally, the expression of the two key genes was validated in cell NAFLD model using qRT-PCR. We developed a prognostic model for NAFLD based on two PRGs, demonstrating robust predictive efficacy. Our findings enhance the understanding of pyroptosis in NAFLD and suggest potential avenues for therapeutic exploration.

Effect of Surface Roughness on the Electrochemical Behavior and Corrosion Resistance of TiTaNbZrAg Alloy with Different Amounts of Tantalum in Bulk Composition

The corrosion behavior of the TiTaNbZrAg alloys with different amounts of tantalum (0%, 10% and 20%) and with distinct surface topography (smooth and rough) was investigated in phosphate buffer solution (PBS) for long-time immersion (1000 h). By this approach, we expect to bring about new insights into the influence of both the amount of Ta in the alloy composition and the surface topography on the corrosion behavior of the Ti-based alloys. The corrosion resistance was studied by Open Circuit Potential (OCP), Potentiodynamic Polarization (PP), and Electrochemical Impedance Spectroscopy (EIS). From the potentiodynamic investigations, it was observed that all types of samples showed good corrosion resistance (i.e., Rcorr &lt; 10 µm y−1) and may be used successfully for medical applications. However, the samples with smooth surfaces and with a certain amount of Ta (10% and 20%) exhibit the best corrosion performance (Rcorr &lt; 1 µm y−1). As regards the samples with rough surfaces, the results evidenced that they showed lower corrosion resistance (1 &lt; Rcorr &lt; 3 µm y−1), suggesting that the Ta presence does not necessarily hinder the corrosion processes. Actually, the synergetic effect of both the presence of Ta and surface roughness plays an important role in corrosion resistance.

Reverse-transcriptase real-time PCR in the diagnostic strategy for invasive infections caused by Aspergillus fumigatus.

The aim was to develop an RT-qPCR targeting Aspergillus fumigatus and compare its performance to that of Aspergillus fumigatus qPCR for the diagnosis of invasive aspergillosis (IA). Samples from patients of the Lyon University hospitals for whom a suspicion of IA led to the realization of an Aspergillus fumigatus qPCR molecular diagnostic test over a 2-year period were included. The patients were classified according to the European Organization for Research and Treatment of Cancer/Mycoses Study Group (EORTC-MSGERC) criteria for suspected IA; RT-qPCR and qPCR assays were performed on all included samples. The sensitivities and specificities of RT-qPCR and qPCR were calculated and compared using the results of the EORTC-MSGERC classification as reference. The cycle threshold (Ct) results were compared according to IA classification and sample type. Among the 193 samples analyzed, 91 were classified as IA excluded, 46 as possible IA, 53 as probable IA, and 3 as proven IA. For all sample types, RT-qPCR was significantly more sensitive than qPCR for all IA classifications with an additional 17/102 samples detected (P-value < 0.01). For plasma samples, sensitivity was significantly higher and specificity significantly lower using RT-qPCR for all IA classifications (P-value < 0.001). The mean Ct obtained with RT-qPCR were significantly lower than those obtained with qPCR for all IA classifications and all sample types (P-value < 0.001 and P-value < 0.0001, respectively). RT-qPCR presents a higher sensitivity than qPCR for the diagnosis of IA due to Aspergillus fumigatus, particularly in samples with an intrinsically low fungal load.IMPORTANCEAspergillus fumigatus belongs to the critical priority group of the World Health Organization fungal priority pathogens list. Invasive aspergillosis (IA) is a life-threatening infection with poor prognosis and challenging diagnosis. PCR has been integrated into the 2020 European Organization for Research and Treatment of Cancer/Mycoses Study Group consensus definitions for IA diagnosis. However, due to frequent low fungal burdens, its sensitivity needs to be improved. This work presents an innovative method for detecting total nucleic acids, corresponding to both ribosomal RNA and DNA, that enables IA diagnosis with greater sensitivity than conventional techniques, especially in non-invasive samples such as blood, enhancing the monitoring of this infection in high-risk patients.

Creation of an Anomaly Detection System for Blockchain-based Cloud Deployments that Consider Privacy and Delay.

Cloud-based deployments are increasingly vulnerable to many kinds of assaults; hence powerful anomaly detection systems are needed to prevent security breaches. While effective to some degree, current methods like RSSI, GTM, and APG have drawbacks in terms of scalability, precision, and accuracy. In order to improve the forecast accuracy of cloud assaults and optimize blockchain-based cloud installations, this study suggests a novel anomaly detection system that combines multimodal feature analysis, deep learning models, and QoS-aware sidechains. The suggested strategy considerably surpasses traditional approaches in terms of precision, accuracy, recall, and AUC performance by optimizing feature variance across various sample types and utilizing cutting-edge deep learning algorithms. Additionally, the framework shows increased efficiency in terms of throughput, energy usage, and block mining latency, makingcombining Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), the system analyses system logs to find anomalous patterns of activity linked to various threats. The architecture guarantees the transparency and integrity of system records through the use of Blockchain technology, while Deep Learning models offer accurate and quick anomaly detection. The advantages of both Deep Learning and Blockchain technology support the choice to merge them. Blockchain technology ensures the accuracy of anomaly detection and prevents tampering with system records by providing a distributed, immutable ledger. On the other hand, deep learning models produce high precision, accuracy, recall, and AUC measures because of their remarkable pattern recognition skills and ability to adjust to shifting attack strategies. Experimental data analyses show the effectiveness of the suggested framework.

Assessment of cell-binding capacity of shed rAAV particles after gene therapy vector administration: implications for environmental risk and hygiene recommendations

ABSTRACT Background Currently, adeno-associated viruses (AAVs) are the most commonly used in vivo gene therapy (GT) vector platform. Risks posed to the environment, including the public, have not been well studied in the past. There is uncertainty concerning the necessary level of biocontainment and appropriate hygiene behavior for the handling of secreta/excreta of GT patients during the shedding phase. Research design and methods Here, feces and urine samples from non-human primates, treated with an AAV9-based vector at 2 × 1013 vector genomes per kilogram body weight (vg/kg), were analyzed for vector presence and subsequently analyzed for their capacity to bind to cells. Results Both sample types contained particles which bound to cells at concentrations in the range of ~104 (and higher) vg/mL of culture medium. Novel control rAAV vector displayed a ~2-3 orders of magnitude higher affinity to cells than shed particles. Conclusions The lower binding capacity of the shed vector particles speaks in favor of a more relaxed containment and hygiene approach in the context of GT. It is recommended that current hygiene and contact-avoidance-based containment measures after GT administration are reduced. The results also support the efforts to achieve a simplification of the regulatory review process of medicinal genetically modified organisms.

Application ICP-OES to Multielement Analysis on Plastic Waste and Blends with Vacuum Gas Oil: Developing a Sample Preparation Protocol

This paper introduces a new methodology for a routine metal analysis of plastic waste (PW) and PW blended with petroleum feedstock such as vacuum gas oil and VGO (PW/VGO). For such purposes, recycled polyethylene and polypropylene plastic were selected to mimic the potential feeds to be integrated at the Fluid Catalytic Cracking unit (FCC) to produce valuable products. Elements such as P, Ca, Al, Mg, Na, Zn, B, Fe, Ti, and Si were included in the method development. Different sample preparation methods were evaluated, such as microwave-assisted acid digestion (MWAD) and dry/wet ashing, followed by a fusion of the ash with lithium borate flux. Some PW homogenization pretreatments, such as cryogenic grinding and hot press molding, were also covered. The finding of this work suggests that MWAD with HNO3 and H2O2 is adequate for both types of samples and is the quickest sample preparation; however, the sample needed to be homogenized, and recoveries for Si and Ti may be biased for PW due to the limited solubilities of these elements in the nitric acid media. Carbon removal is required before fusion sample preparation and analysis due to the amount of carbon in PW samples. The sample needed to be homogenized for wet ash fusion but not for the pre-ash (dry) method. A benefit to the damp ash pretreatment is that the ash for the sample was created in the same crucible used for fusion digestion, avoiding material loss during sample management. Fusion from wet ash or carbon removal allowed for better acid solubility for Si and Ti in PW. The results of the PW samples evaluated matched well with those of both sample preparation methodologies. For most elements, precision was &lt;10% regardless of the sample preparation; however, Fe and P had some variation using wet ash fusion, possibly due to contamination in an open digestion system or variation due to being close to the method limit of quantification (LOQ). The methodology reported here is robust enough to be implemented as routine analysis in any laboratory facility.

Evaluation and real-world experience of a neutralization susceptibility screening assay for broadly neutralizing anti-HIV-1 antibodies.

Development of a screening assay for the clinical use of broadly neutralizing antibodies (bnAbs) is a priority for HIV therapy and cure initiatives. We assessed the PhenoSense Monoclonal Antibody (mAb) Assay (Labcorp-Monogram Biosciences) which is CLIA-validated and has been used prospectively and retrospectively in multiple recent bnAb clinical trials. When performed on pre-ART plasma and on-ART longitudinal PBMC samples sourced from a recent clinical trial, the PhenoSense mAb Assay produced robust reproducibility, concordance across sample types, and expected ranges in the susceptibility measures of bnAbs in clinical development. PhenoSense mAb applied retrospectively to baseline samples from three recent studies correlated with published laboratory-based study evaluations, but baseline bnAb susceptibility was not consistently predictive of durable virus suppression. Assessment of the feasibility of the assay in four recent clinical studies provides estimates of assay success rate and processing time. The PhenoSense mAb Assay provides reproducible bnAb susceptibility measurements across relevant sample types yet was not consistently predictive of virus suppression. Logistical and operational assay requirements can impact timely clinical trial conduct. These results inform bnAb studies in development.

Politics of International Oil Companies (IOCs): Understanding PETRONAS Carigali Nile Ltd Exit From South Sudanese Oilfields

The study has examined the politics of the International Oil Companies (IOCs), the case study of PETRONAS Carigali Nile Ltd. It does this by appraising the legal violations of PETRONAS Carigali Nile Ltd exit and farming out from South Sudanese oilfields. The study explains the politics of IOCs and particularly, PETRONAS Carigali Nile Ltd as dependent variable and independent variables such as legal violations of Petronas Carigali Nile Ltd, types of residual liabilities and responsibility of these liabilities.The study was subjected to stringent empirical literature review and the gaps in the literature were filled through fieldwork. During fieldwork, the methodology of research tools and instruments such as questionnaires and interview guides/schedules were deployed with target of 52 respondents. Persuasive and cluster type of sampling amongst the senior staff of Ministry of Petroleum (MOP), Nile Petroleum Corporation (NILEPET), Dar Petroleum Operating Company (DPOC), Sudd Petroleum Operating Company (SPOC) and Greater Pioneer Operating Company (GPOC) were applied. The study findings indicate that PETRONAS Carigali Nile Ltd has politicized and violated sections 12, 22, 23, 24, 41 &amp; 42 of the Petroleum Act 2012. Various types of liabilities such as cost recovery audits, environmental audit, petroleum taxes, surface rentals, and cash calls should be taken care off by Petronas Carigali Nile Ltd or by a company that farms into its shares. While the study concludes that PETRONAS Carigali Nile Ltd exit and farming out has been politicized and violated the laws of the Republic of South Sudan, the study recommends that the Ministry of Petroleum should be held responsible for all the legal violations Petronas Carigali Nile Ltd have committed in South Sudan without any action. Whether Savannah Energy Ltd farms into Petronas Carigali Nile Ltd shares or not after the PETRONAS has exited, consequences should be rolled out for such violations so that no any other IOC can do it again in the near future in this volatile oil and gas industry.