Types Of Samples Research Articles

Development of a New Personalized Molecular Test Based on Endometrial Receptivity and Maternal-Fetal Dialogue: Adhesio.

Successful embryo implantation relies on a receptive endometrium and a maternofetal dialogue. Abnormal receptivity is a common cause of implantation failure in assisted reproductive techniques. This study aimed to develop a novel transcriptomic-based diagnostic assay, Adhesio, for assessing endometrial receptivity and guiding personalized embryo transfer. Adhesio was developed based on an initial dataset of 74 endometrial biopsies. Two types of biopsy samples were involved: 45 endometrial biopsies collected during the optimal theoretical window of implantation (WOI) and 29 endometrial biopsies which cells have been cultured with or without an autologous embryo. Microarray analysis was performed to identify differentially expressed genes associated with endometrial receptivity and selected candidate genes were assessed using quantitative real-time polymerase chain reaction (RT-qPCR) on biopsy samples. Statistical analyses were conducted to assess the performance and accuracy of Adhesio. The microarray analysis identified three distinct clusters of endometrial samples with differential gene expression patterns. Cluster 1 exhibited 1717 differentially expressed genes involved in biological processes associated with endometrial receptivity. A specific transcriptomic signature of 60 genes associated with endometrial co-culture was obtained using class prediction approach. Thereafter, an original panel of 10 genes was selected as potential biomarkers for endometrial receptivity based on their expression profiles in both endometrial biopsies and co-cultured cells. This article outlines the methodology employed to develop Adhesio, a test that assesses endometrial receptivity using an original panel of 10 genes. These genes are not only involved during the WOI but are also influenced by the maternal-fetal dialogue.

Identification and antimicrobial susceptibility profiles of Campylobacter isolated from camel at municipal abattoirs in eastern Ethiopia

Campylobacteriosis is an infectious zoonotic disease caused by the genus Campylobacter. The disease is transmitted from animals to humans predominantly through the consumption of contaminated food and water. However, the lack of information on the status of Campylobacter makes it difficult to quantify the role of camel meat in the dissemination of the pathogen. A cross-sectional study was conducted from June 2022 to August 2023 to investigate the occurrence of Campylobacter and associated risk factors and to determine the antimicrobial susceptibility profiles of Campylobacter species from camels slaughtered at municipal abattoirs in the towns of Harar, Babile, Jigjiga and Dire Dawa in eastern Ethiopia. A total of 324 (146 carcass swabs, 146 camel feces and 32 abattoir environmental swab samples) were collected and analyzed using TaqMan real-time PCR and culture techniques following standard procedures. In addition, antimicrobial susceptibility tests were performed using the disk diffusion method for eight antimicrobial agents according to the Clinical Laboratory Standards Institute. The overall prevalence of Campylobacter was 7.7%. Campylobacter was more frequently detected from carcasses and surface contact environmental swabs. We isolated Campylobacter at the genus level from approximately half of the PCR-positive samples, representing 54.2% (13 out of 24) of the total. The isolation levels of C. jejuni and C. coli were also 5.56% and 2.2%, respectively, which varied significantly (p = 0.037) based on sample type and site. The odds of occurrence of C. jejuni in samples collected from abattoir environments was 7.52 times greater than those in carcass and fecal samples. We detected resistance to chloramphenicol (78.6%), followed by amoxicillin (71.4%). However, 93%, 78.6%, and 71.4% of the isolates were susceptible to ceftriaxone, ciprofloxacin, and nalidixic acid, respectively. Multidrug resistance (MDR) was detected in 60% of the isolates. Of these MDR isolates, 9 (75%) were C. jejuni and 3 (25%) were C. coli. This study revealed that a considerable proportion of multidrug-resistant Campylobacter species circulate in both camel meat and abattoir environments. This indicates possible carcass cross-contamination by Campylobacter during slaughtering that can pose a threat to humans and limit therapeutic options, which could be prevented by applying good hygienic practices at abattoirs. Therefore, abattoir workers need to be aware of abattoir hygienic standard operating procedures. Regular coordinated actions should be implemented for the rational use of veterinary and medical drugs at the national level, together with training and awareness of hygienic practices.

The role of shame and trauma type on posttraumatic stress disorder and depression severity in a treatment-seeking veteran population.

Research on how different types of trauma affect depression and posttraumatic stress disorder (PTSD) symptoms in veterans has yielded inconsistent results. Shame, a painful and negative self-evaluative emotion observed in PTSD and across interpersonal traumas, may help explain past findings. The present study explored (a) how trauma types (childhood abuse, combat exposure, and military sexual trauma [MST]) may be associated with depression and PTSD severity and (b) how shame may be associated with trauma type, PTSD symptoms, and depression symptoms in a treatment-seeking veteran sample. Veterans (N = 372) completed self-report questionnaires assessing trauma exposure, PTSD symptoms, depression symptoms, and shame upon admission to treatment programs across two Veterans Affairs Medical Centers. We found that veterans with combat exposure or MST had greater depression and PTSD symptoms than those without these trauma experiences. Among veterans without a history of combat exposure and MST, a history of childhood abuse was associated with depression symptoms. Among veterans who did not experience combat but did experience MST, a history of childhood abuse was not associated with depression symptoms. We found that characterological shame (i.e., shame about oneself) partially mediated MST status and PTSD symptoms and fully mediated MST status and depression symptoms. These results suggest that different trauma exposures can have complex effects on clinical presentations and that shame may be a mechanism of PTSD and depression severity in veterans with MST. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Mass Spectrometry Probe Combined with Machine Learning to Capture the Relationship between Metabolites and Mitochondrial Complex Activity at the Whole-Cell Level.

Mitochondrial complex activity controls a multitude of physiological processes by regulating the cellular metabolism. Current methods for evaluating mitochondrial complex activity mainly focus on single metabolic reactions within mitochondria. These methods often require fresh samples in large quantities for mitochondria purification or intact mitochondrial membranes for real-time monitoring. Confronting these limitations, we shifted the analytical perspective toward interactive metabolic networks at the whole-cell level to reflect mitochondrial complex activity. To this end, we compiled a panel of mitochondrial respiratory chain-mapped metabolites (MRCMs), whose perturbations theoretically provide an overall reflection on mitochondrial complex activity. By introducing N-dimethyl-p-phenylenediamine and N-methyl-p-phenylenediamine as a pair of mass spectrometry probes, an ultraperformance liquid chromatography-tandem mass spectrometry method with high sensitivity (LLOQ as low as 0.2 fmol) was developed to obtain accurate quantitative data of MRCMs. Machine learning was then combined to capture the relationship between MRCMs and mitochondrial complex activity. Using Complex I as a proof-of-concept, we identified NADH, alanine, and phosphoenolpyruvate as metabolites associated with Complex I activity based on the whole-cell level. The effectiveness of using their concentrations to reflect Complex I activity was further validated in external data sets. Hence, by capturing the relationship between metabolites and mitochondrial complex activity at the whole-cell level, this study explores a novel analytical paradigm for the interrogation of mitochondrial complex activity, offering a favorable complement to existing methods particularly when sample quantities, type, and treatment timeliness pose challenges. More importantly, it shifts the focus from individual metabolic reactions within mitochondria to a more comprehensive view of an interactive metabolic network, which should serve as a promising direction for future research into the functional architecture between mitochondrial complexes and metabolites.

Blood-Based Nanoparticle-Enhanced Quaking-Induced Conversion (Nano-QuIC): Inhibitor-Resistant Detection of Seeding Activity in Patients Diagnosed with Parkinson's Disease.

A hallmark of α-synucleinopathies (e.g., Parkinson's disease) is the misfolding and aggregation of α-synuclein in tissues and biological fluids. Protein amplification assays like real-time quaking-induced conversion (RT-QuIC) are sensitive yet currently limited to semi-invasive sample types such as cerebrospinal fluid because more accessible samples, such as blood, contain inhibitors. Here, we show that Nanoparticle-enhanced Quaking-induced Conversion (Nano-QuIC) can double the speed of reactions spiked with misfolded α-synuclein while increasing sensitivity 100-fold in human plasma. Nano-QuIC detected spike concentrations down to 90 pg/mL in lysed whole blood, while reactions without nanoparticles (RT-QuIC) failed to have any detection due to the presence of strong inhibitors. Moreover, Nano-QuIC showed increased seeding activity in plasma samples from Parkinson's patients (n = 4) versus healthy controls (n = 4). This sets the groundwork for the noninvasive diagnostic use of Nano-QuIC, potentially enabling early disease detection and management through blood-based testing.

Microbiome divergence of marine gastropod species separated by the Isthmus of Panama.

The rise of the Isthmus of Panama separated the populations of many marine organisms, which then diverged into new geminate sister species currently living in the Eastern Pacific Ocean and the Caribbean Sea. However, we know very little about how such evolutionary divergences of host species have shaped the compositions of their microbiomes. Here, we compared the microbiomes of whole-body and shell-surface samples of geminate species of marine gastropods in the genera Cerithium and Cerithideopsis to those of congeneric outgroups. Our results suggest that the effects of ~3 million years of separation and isolation on microbiome composition varied among host genera and between sample types within the same hosts. In the whole-body samples, microbiome compositions of geminate species pairs tended to be similar, likely due to host filtering, although the strength of this relationship varied among the two groups and across similarity metrics. Shell-surface microbiomes show contrasting patterns, with co-divergence between the host taxa and a small number of microbial clades evident in Cerithideopsis but not Cerithium. These results suggest that (i) isolation of host populations after the rise of the Isthmus of Panama affected microbiomes of geminate hosts in a complex and host-specific manner, and (ii) host-associated microbial taxa respond differently to vicariance events than the hosts themselves.IMPORTANCEWhile considerable work has been done on evolutionary divergences of marine species in response to the rise of the Isthmus of Panama, which separated two previously connected oceans, how this event shaped the microbiomes of these marine hosts remains poorly known. Using whole-body and shell-surface microbiomes of closely related gastropod species from opposite sides of the Isthmus, we show that divergences of microbial taxa after the formation of the Isthmus are often not concordant with those of their gastropod hosts. Our results show that evolutionary responses of marine gastropod-associated microbiomes to major environmental perturbations are complex and are shaped more by local environments than host evolutionary history.

Time‐domain spectra of ultrasonic wave transmitted through granite and gypsum samples containing artificial defects

AbstractThe internal defects in rock masses can significantly impact the quality and safety of geotechnical projects. Mechanical waves, as a common nondestructive testing (NDT) method, can reflect the external and internal structures of rock or rock masses. Analyses on the reflected and transmitted waves enable nondestructive identification and assessment of potential defects within rocks. Previous studies mainly focused on the variation of single or limited wave features like main frequency, amplitude and energy between the intact and non‐intact samples. In fact, most information contained in the waveforms is neglected. Techniques of data mining can provide a powerful tool to reveal this information and therefore a more accurate determination of the internal structures. In this study, 995,412 NDT data from 14 types of granite and gypsum samples with different cross‐section shapes and different types of defects are recorded by an ultrasonic wave generation and collection system. This dataset can be used not only as the training data for defect classification in NDT but also as a good reference for conventional NDT analyses. Besides, time‐series data analysis is an opportunity and challenging issue, this dataset holds great potential for broader application in general time‐series classification analysis.

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.