Potential Screening Research Articles

Screening potential biomarkers associated with insulin resistance in high-fat diet-fed mice by integrating metagenomics and untargeted metabolomics.

In this study, we aim to identify the microbes and metabolites linked to insulin resistance, some of which have not been previously reported in insulin resistance-related studies. This adds a complementary dimension to existing research. Furthermore, we establish a correlation between alterations in the gut microbiota and metabolite levels. These findings serve as a foundation for identifying the causal bacterial species and metabolites. They also offer insights that guide further exploration into the mechanisms through which these factors influence host insulin resistance.

Modeling inflammatory response using 3D bioprinting of polarized macrophages

The field of drug discovery has seen the rise of three-dimensional (3D) bioprinting as a promising tool for disease modeling. The focus to date has been on tissue engineering and cancer modeling, although the application of 3D-bioprinted models for the study of inflammation using macrophages is still in its infancy. This study explores the potential of bioprinting technology in the development of a 3D macrophage model and macrophage response to inflammatory stimuli using this platform. To this end, we established a 3D-bioprinted macrophage model and assessed the inflammatory and anti-inflammatory response to bacterial endotoxin (lipopolysaccharide, LPS) and the drug ibuprofen (Ibu), respectively. Optimal conditions for macrophage differentiation of the human monocytic cell line, THP-1, in the 3D environment were studied, as well as the effect of the 3D microenvironment on macrophage polarization. Viability of THP-1 cells following the 3D bioprinting process was demonstrated and maintained, allowing successful macrophage differentiation of the cells. The developed 3D-bioprinted macrophage model exhibited elevated expression of selected pro-inflammatory gene and protein markers following exposure to LPS, consistent with polarization from M0 to M1 phenotype. Additionally, the model was responsive to the anti-inflammatory properties of Ibu, demonstrating its potential in drug screening and discovery. The current study highlights the potential of bioprinting in the investigation of inflammatory cell response and behavior in a 3D environment ex vivo, opening new avenues for research in modeling inflammatory responses to various stimuli.  

Serum analysis based on SERS combined with 2D convolutional neural network and Gramian angular field for breast cancer screening

Breast cancer is a significant cause of death among women worldwide. It is crucial to quickly and accurately diagnose breast cancer in order to reduce mortality rates. While traditional diagnostic techniques for medical imaging and pathology samples have been commonly used in breast cancer screening, they still have certain limitations. Surface-enhanced Raman spectroscopy (SERS) is a fast, highly sensitive and user-friendly method that is often combined with deep learning techniques like convolutional neural networks. This combination helps identify unique molecular spectral features, also known as “fingerprint”, in biological samples such as serum. Ultimately, this approach is able to accurately screen for cancer. The Gramian angular field (GAF) algorithm can convert one-dimensional (1D) time series into two-dimensional (2D) images. These images can be used for data visualization, pattern recognition and machine learning tasks. In this study, 640 serum SERS from breast cancer patients and healthy volunteers were converted into 2D spectral images by Gramian angular field (GAF) technique. These images were then used to train and test a two-dimensional convolutional neural network-GAF (2D-CNN-GAF) model for breast cancer classification. We compared the performance of the 2D-CNN-GAF model with other methods, including one-dimensional convolutional neural network (1D-CNN), support vector machine (SVM), K-nearest neighbor (KNN) and principal component analysis-linear discriminant analysis (PCA-LDA), using various evaluation metrics such as accuracy, precision, sensitivity, F1-score, receiver operating characteristic (ROC) curve and area under curve (AUC) value. The results showed that the 2D-CNN model outperformed the traditional models, achieving an AUC value of 0.9884, an accuracy of 98.13%, sensitivity of 98.65% and specificity of 97.67% for breast cancer classification. In this study, we used conventional nano-silver sol as the SERS-enhanced substrate and a portable laser Raman spectrometer to obtain the serum SERS data. The 2D-CNN-GAF model demonstrated accurate and automatic classification of breast cancer patients and healthy volunteers. The method does not require augmentation and preprocessing of spectral data, simplifying the processing steps of spectral data. This method has great potential for accurate breast cancer screening and also provides a useful reference in more types of cancer classification and automatic screening.

Simultaneous and Sensitive Sensing of Intracellular MicroRNA and mRNA for the Detection of the PI3K/AKT Signaling Pathway in Live Cells.

Simultaneous detection of the concentration variations of microRNA-221 (miRNA-221) and PTEN mRNA molecules in the PI3K/AKT signaling pathway is of significance to elucidate cancer cell migration and invasion, which is useful for cancer diagnosis and therapy. In this work, we show the biodegradable MnO2 nanosheet-assisted and target-triggered DNAzyme recycling signal amplification cascaded approach for the specific detection of the PI3K/AKT signaling pathway in live cells via simultaneous and sensitive monitoring of the variation of intracellular miRNA-221 and PTEN mRNA. Our nanoprobes enable highly sensitive and multiplexed sensing of miRNA-221 and PTEN mRNA with low detection limits of 23.6 and 0.59 pM in vitro, respectively, due to the signal amplification cascades. Importantly, the nanoprobes can be readily delivered into cancer cells and the MnO2 nanosheets can be degraded by intracellular glutathione to release the Mn2+ cofactors to trigger multiple DNAzyme recycling cycles to show highly enhanced fluorescence at different wavelengths to realize sensitive and multiplexed imaging of PTEN mRNA and miRNA-221 for detecting the PI3K/AKT signaling pathway. Moreover, the regulation of PTEN mRNA expression by miRNA-221 upon stimulation by various drugs can also be verified by our method, indicating its promising potentials for both disease diagnosis and drug screening.

ICP wave morphology as a screening test to exclude intracranial hypertension in brain-injured patients: a non-invasive perspective.

Intracranial hypertension (IH) is a life-threating condition especially for the brain injured patient. In such cases, an external ventricular drain (EVD) or an intraparenchymal bolt are the conventional gold standard for intracranial pressure (ICPi) monitoring. However, these techniques have several limitations. Therefore, identifying an ideal screening method for IH is important to avoid the unnecessary placement of ICPi and expedite its introduction in patients who require it. A potential screening tool is the ICP wave morphology (ICPW) which changes according to the intracranial volume-pressure curve. Specifically, the P2/P1 ratio of the ICPW has shown promise as a triage test to indicate normal ICP. In this study, we propose evaluating the noninvasive ICPW (nICPW-B4C sensor) as a screening method for ICPi monitoring in patients with moderate to high probability of IH. This is a retrospective analysis of a prospective, multicenter study that recruited adult patients requiring ICPi monitoring from both Federal University of São Paulo and University of São Paulo Medical School Hospitals. ICPi values and the nICPW parameters were obtained from both the invasive and the noninvasive methods simultaneously 5 min after the closure of the EVD drainage. ICP assessment was performed using a catheter inserted into the ventricle and connected to a pressure transducer and a drainage system. The B4C sensor was positioned on the patient's scalp without the need for trichotomy, surgical incision or trepanation, and the morphology of the ICP waves acquired through a strain sensor that can detect and monitor skull bone deformations caused by changes in ICP. All patients were monitored using this noninvasive system for at least 10min per session. The area under the curve (AUC) was used to describe discriminatory power of the P2/P1 ratio for IH, with emphasis in the Negative Predictive value (NPV), based on the Youden index, and the negative likelihood ratio [LR-]. Recruitment occurred from August 2017 to March 2020. A total of 69 patients fulfilled inclusion and exclusion criteria in the two centers and a total of 111 monitorizations were performed. The mean P2/P1 ratio value in the sample was 1.12. The mean P2/P1 value in the no IH population was 1.01 meanwhile in the IH population was 1.32 (p < 0.01). The best Youden index for the mean P2/P1 ratio was with a cut-off value of 1.13 showing a sensitivity of 93%, specificity of 60%, and a NPV of 97%, as well as an AUC of 0.83 to predict IH. With the 1.13 cut-off value for P2/P1 ratio, the LR- for IH was 0.11, corresponding to a strong performance in ruling out the condition (IH), with an approximate 45% reduction in condition probability after a negative test (ICPW). To conclude, the P2/P1 ratio of the noninvasive ICP waveform showed in this study a high Negative Predictive Value and Likelihood Ratio in different acute neurological conditions to rule out IH. As a result, this parameter may be beneficial in situations where invasive methods are not feasible or unavailable and to screen high-risk patients for potential invasive ICP monitoring.Trial registration: At clinicaltrials.gov under numbers NCT05121155 (Registered 16 November 2021-retrospectively registered) and NCT03144219 (Registered 30 September 2022-retrospectively registered).

Development of a Short Version of the ADHD Rating Scale-IV.es (sADHD-RS-IV.es)

Objective: To develop a short version of the Spanish 18-item ADHD-Rating Scale IV.es (sADHD-RS-IV.es) to be used as a potential screening tool in pediatric population. Methods: We recruited 652 subjects, ages 6 to 18 (mean ± SD = 11.14 ± 3.27): 518 patients with ADHD (per DSM-IV criteria); and 134 healthy controls. We performed a stepwise logistic regression to select the best subset of ADHD-RS-IV.es items to create a short-form. We calculated internal consistency reliability (Cronbach’s and ordinal alphas) and diagnostic accuracy using receiver operating characteristic (ROC) curve. Results: Six items were found to enter the stepwise analysis significantly. Internal consistency was high (Cronbach’s alpha = 0.86; ordinal alpha = 0.90) and offered a good concordance with clinician diagnosis and a high discriminatory power (AUC = 0.98) with an optimal cut-off at a score of six points. Conclusions: This shorter questionnaire (six items) was able to discriminate ADHD cases from healthy controls.

The role of second trimester uterine artery Doppler in predicting obstetric and neonatal outcomes in abnormal first trimester maternal serum pregnancy-associated plasma protein-A and free β-human chorionic gonadotropin values.

This study aims to determine whether second-trimester uterine artery (UtA) Doppler combined with first-trimester abnormal pregnancy-associated plasma protein-A (PAPP-A) and β-human chorionic gonadotropin (β-Hcg) levels predicts adverse obstetric and neonatal outcomes. This study of 289 pregnant women included 196 with normal PAPP-A and free β-HCG values (control group) and 93 with abnormal values (study group) in the first-trimester screening test. Second-trimester UtA Doppler sonography was done in these pregnancies. The perinatal prediction and screening potential of UtA Doppler pulsatility index (PI) parameters were examined in the study group. UtA PI >95 percentile increased birth before the 37th week by 4.46 times, birth before the 34th week by 7.44 times, preeclampsia risk by 3.25 times, fetal growth restriction (FGR) risk by 4.89 times, and neonatal intensive care unit (NICU) admission rates by 3.66 times in the study group (p < 0.05 for all). UtA PI >95 percentile had 49.2% sensitivity and 82.1% specificity for birth before 37 weeks. For birth before 34 weeks, sensitivity was 80.0% and specificity 65.0%. FGR has 70.5% sensitivity and 67.1% specificity. Screening for preeclampsia has 66.6% sensitivity and 61.9% specificity. Adding UtA Doppler in the second trimester to pregnancies with abnormal PAPP-A and/or free β-Hcg values in the first trimester may be a useful screening method for adverse outcomes.

Early signs of myocardial systolic dysfunction in patients with type 2 diabetes are strongly associated with myocardial microvascular dysfunction independent of myocardial fibrosis: a prospective cohort study

BackgroundPatients with diabetes demonstrate early left ventricular systolic dysfunction. Notably reduced global longitudinal strain (GLS) is related to poor outcomes, the underlying pathophysiology is however still not clearly understood. We hypothesized that pathophysiologic changes with microvascular dysfunction and interstitial fibrosis contribute to reduced strain.Methods211 patients with type 2 diabetes and 25 control subjects underwent comprehensive cardiovascular phenotyping by magnetic resonance imaging. Myocardial blood flow (MBF), perfusion reserve (MPR), extracellular volume (ECV), and 3D feature tracking GLS and global circumferential (GCS) and radial strain (GRS) were quantified.ResultsPatients (median age 57 [IQR 50, 67] years, 70% males) had a median diabetes duration of 12 [IQR 6, 18] years. Compared to control subjects GLS, GCS, and GRS were reduced in the total diabetes cohort, and GLS was also reduced in the sub-group of patients without diabetic complications compared to control subjects (controls − 13.9 ± 2.0%, total cohort − 11.6 ± 3.0%; subgroup − 12.3 ± 2.6%, all p < 0.05). Reduced GLS, but not GCS or GRS, was associated with classic diabetes complications of albuminuria (UACR ≥ 30 mg/g) [β (95% CI) 1.09 (0.22–1.96)] and autonomic neuropathy [β (95% CI) 1.43 (0.54–2.31)] but GLS was not associated with retinopathy or peripheral neuropathy. Independently of ECV, a 10% increase in MBF at stress and MPR was associated with higher GLS [multivariable regression adjusted for age, sex, hypertension, smoking, and ECV: MBF stress (β (95% CI) − 0.2 (− 0.3 to − 0.08), MPR (β (95% CI) − 0.5 (− 0.8 to − 0.3), p < 0.001 for both]. A 10% increase in ECV was associated with a decrease in GLS in univariable [β (95% CI) 0.6 (0.2 to 1.1)] and multivariable regression, but this was abolished when adjusted for MPR [multivariable regression adjusted for age, sex, hypertension, smoking, and MPR (β (95% CI) 0.1 (− 0.3 to 0.6)]. On the receiver operating characteristics curve, GLS showed a moderate ability to discriminate a significantly lowered stress MBF (AUC 0.72) and MPR (AUC 0.73).ConclusionsMyocardial microvascular dysfunction was independent of ECV, a biomarker of myocardial fibrosis, associated with GLS. Further, 3D GLS could be a potential screening tool for myocardial microvascular dysfunction. Future directions should focus on confirming these results in longitudinal and/or interventional studies.

High-throughput screening of transient receptor potential (TRP) channels in pterygium.

Pterygium is a hyaline degenerative disease of the conjunctiva characterized by the progression of fibrovascular connective tissue from the bulbar conjunctiva to the cornea. The mechanism of pterygium formation is still not fully understood. Transient receptor potential (TRP) channels are a group of ion channels with distinct characteristics. Recent indications suggest TRP channels may play a significant regulatory role in pterygium development, but previous studies have mainly focused on in silico analysis. Accordingly, in the present study, we aimed to decipher the expression signatures and role of TRP channels in pterygium development. The study encompassed a cohort of 45 patients matched for age and gender distribution, comprising 30 individuals with primary pterygium (PP) and 15 individuals with recurrent pterygium(RP). The control group consisted of unaffected conjunctival tissue obtained from the same set of patients. High-throughput screening of differentially expressed TRP channels in pterygium tissues was achieved with the help of Fluidigm 96.96 Dynamic Array Expression Chip and reactions were held in BioMark™ HD System Real-Time PCR platform. Statistically significant increases were found in the expression of 21 genes, mainly TRPA1 (p = 0.021), TRPC2 (p = 0.001), and TRPM8 (p = 0.003), in patients with PP, and in TRPC5 (p = 0.05), TRPM2 (p = 0.029), TRPM4 (p = 0.03), TRPM6 (p = 0.045), TRPM8 (p = 0.038), TRPV1 (p = 0.01) and TRPV4 (p = 0.025) genes in RP tissues. Collectively, TRP channel proteins appear to play pivotal roles in both the development and progression of pterygium, making them promising candidates for future therapeutic interventions in patients afflicted by this condition.

New Insights into Antioxidant Peptides: An Overview of Efficient Screening, Evaluation Models, Molecular Mechanisms, and Applications.

Antioxidant peptides are currently a hotspot in food science, pharmaceuticals, and cosmetics. In different fields, the screening, activity evaluation, mechanisms, and applications of antioxidant peptides are the pivotal areas of research. Among these topics, the efficient screening of antioxidant peptides stands at the forefront of cutting-edge research. To this end, efficient screening with novel technologies has significantly accelerated the research process, gradually replacing the traditional approach. After the novel antioxidant peptides are screened and identified, a time-consuming activity evaluation is another indispensable procedure, especially in in vivo models. Cellular and rodent models have been widely used for activity evaluation, whilst non-rodent models provide an efficient solution, even with the potential for high-throughput screening. Meanwhile, further research of molecular mechanisms can elucidate the essence underlying the activity, which is related to several signaling pathways, including Keap1-Nrf2/ARE, mitochondria-dependent apoptosis, TGF-β/SMAD, AMPK/SIRT1/PGC-1α, PI3K/Akt/mTOR, and NF-κB. Last but not least, antioxidant peptides have broad applications in food manufacture, therapy, and the cosmetics industry, which requires a systematic review. This review introduces novel technologies for the efficient screening of antioxidant peptides, categorized with a new vision. A wide range of activity evaluation assays, encompassing cellular models, as well as rodent and non-rodent models, are provided in a comprehensive manner. In addition, recent advances in molecular mechanisms are analyzed with specific cases. Finally, the applications of antioxidant peptides in food production, therapy, and cosmetics are systematically reviewed.

An Accelerated Failure Time Model to Predict Cause-Specific Survival and Prognostic Factors of Lung and Bronchus Cancer Patients with at Least Bone or Brain Metastases: Development and Internal Validation Using a SEER-Based Study

Background: This study addresses the significant challenge of low survival rates in patients with cause-specific lung cancer accompanied by bone or brain metastases. Recognizing the critical need for an effective predictive model, the research aims to establish survival prediction models using both parametric and non-parametric approaches. Methods: Clinical data from lung cancer patients with at least one bone or brain metastasis between 2000 and 2020 from the SEER database were utilized. Four models were constructed: Cox proportional hazard, Weibull accelerated failure time (AFT), log-normal AFT, and Zografos–Balakrishnan log-normal (ZBLN). Independent prognostic factors for cause-specific survival were identified, and model fit was evaluated using Akaike’s and Bayesian information criteria. Internal validation assessed predictive accuracy and discriminability through the Harriel Concordance Index (C-index) and calibration plots. Results: A total of 20,412 patients were included, with 14,290 (70%) as the training cohort and 6122 (30%) validation. Independent prognostic factors selected for the study were age, race, sex, primary tumor site, disease grade, total malignant tumor in situ, metastases, treatment modality, and histology. Among the accelerated failure time (AFT) models considered, the ZBLN distribution exhibited the most robust model fit for the 3- and 5-year survival, as evidenced by the lowest values of Akaike’s information criterion of 6322 and 79,396, and the Bayesian information criterion of 63,495 and 79,396, respectively. This outperformed other AFT and Cox models (AIC = [156,891, 211,125]; BIC = [158,848, 211,287]). Regarding predictive accuracy, the ZBLN AFT model achieved the highest concordance C-index (0.682, 0.667), a better performance than the Cox model (0.669, 0.643). The calibration curves of the ZBLN AFT model demonstrated a high degree of concordance between actual and predicted values. All variables considered in this study demonstrated significance at the 0.05 level for the ZBLN AFT model. However, differences emerged in the significant variations in survival times between subgroups. The study revealed that patients with only bone metastases have a higher chance of survival compared to only brain and those with bone and brain metastases. Conclusions: The study highlights the underutilized but accurate nature of the accelerated failure time model in predicting lung cancer survival and identifying prognostic factors. These findings have implications for individualized clinical decisions, indicating the potential for screening and professional care of lung cancer patients with at least one bone or brain metastasis in the future.

Transfer doping of epitaxial graphene on SiC(0001) using Cs

Control of the charge carrier concentration is essential for applications of graphene. Here, we demonstrate the doping of epitaxial graphene on SiC(0001) via charge transfer from an adsorbed layer of Cs atoms with sub-monolayer coverage. The electronic structure of the graphene is analyzed using x-ray and angle-resolved photoelectron spectroscopy. In H-intercalated, quasi-freestanding monolayer graphene (QFMLG), the Dirac point can be tuned continuously from p-type to strong n-type doping. For strong n-type doping, analysis of the core level binding energies implies a deviation from a rigid band shift. This might be explained by an increased screening of the atomic core potential due to the higher number of charge carriers per C atom in the graphene layer. Furthermore, charge transfer into the SiC substrate leads to a change in band bending at the SiC/QFMLG interface, which saturates into a flat band scenario at higher Cs coverage. An analysis of the Fermi surfaces suggests an increasing electron-phonon-coupling in strongly doped QFMLG. In monolayer graphene (MLG), which is intrinsically n-type doped due to the presence of the buffer layer at the SiC interface, n-type doping can be enhanced by Cs evaporation in a similar fashion. In contrast to QFMLG, core level spectra and Dirac cone position in MLG apparently show a rigid band shift even for very high doping, emphasizing the importance of the substrate.

Silver nanoparticles enhanced enzyme-linked immunosorbent assay (ELISA) detection of cancer testis antigens (CTAs).

The Enzyme-Linked Immunosorbent Assay (ELISA) has been a cornerstone technique in laboratory medicine for over 55 years, relying on the specific binding of antibodies to antigens. ELISA's widespread use stems from its ability to detect low concentrations, its specificity, reproducibility, and potential for high-throughput screening. However, its sensitivity has limitations, prompting the exploration of innovative methods to improve the limit of detection (LOD). Nanoparticles provide a promising platform for enhancing ELISA sensitivity. Due to their high surface-to-volume ratio, they offer increased binding sites for capture elements and reporting tags, leading to amplified analytical signals. Recent studies have demonstrated improved sensitivity in ELISA through nanoparticle application, yielding faster detection times and enhanced sensitivities. This study investigates the potential of 50 nm citrate-capped silver nanoparticles to enhance ELISA's performance in quantifying cancer testis antigens (CTAs). In our study, we used the Human NY-ESO-1 ELISA kit (for research purposes) to determine the concentration of CTAs in randomly selected samples from healthy (n=89) and oncological (n=80) subjects, aged 18-75. We employed 50 nm citrate-capped silver nanoparticles (AGCB50-1M, BioPure Silver Nanoparticles - bare citrate, nano-Composix, San Diego, CA, USA). ELISA reactions followed the manufacturer's instructions, and data processing aligned with the same guidelines. Absorbance (OD) measurements occurred at 450 nm, influencing nanoparticle selection. Each ELISA well contained 5 ml of nanoparticles' stock solution with specified concentrations. CTAs concentrations were derived from the standard curve through CurveExpert Basic software. Statistical analysis was performed using SPSS v. 27 software, with p-values indicating significance if <0.03. The study adhered to Helsinki Declaration principles and received ethical approval. Participants provided informed written consent. The increased concentration values of CTAs for healthy individuals and cancer patients were determined in the case of the application of silver nanoparticles. The usage of nanoparticles can enhance the sensitivity of the ELISA method and positively influence its specific detection limit.

The blood routine test holds screening values for influenza A in 2023: a retrospective study.

Influenza A is the most common viral pathogen isolated from pediatric clinics during influenza seasons. Some young patients with influenza manifest rapid progression with high fever and severe sequelae, such as pneumonia and meningitis. Therefore, early diagnosis and prompt treatment are highly important. Specific diagnostic tests currently include antigen detection, antibody detection, nucleic acid test and virus isolation. Rapid antigen testing is the most commonly adopted method in the outpatient setting, but false negative results are frequently observed, which causes delayed treatment and severe outcome. Routine blood test is the most commonly used detection for the outpatients. Incorporating specific blood cell counts into rapid antigen test may overcome some technical issues and enable accurate early diagnosis. We enrolled 537 children with influenza-like symptoms like fever or respiratory symptoms from pediatric outpatients and 110 children without infectious diseases for control. Routine blood tests detected by a routine analyzer and influenza A virus antigen detection were performed in the patients. Significant blood routine parameters between groups were examined by statistical tests. Parameters in routine blood test were assessed by the receiver operating characteristic curve to find the screening indicators of influenza A. Multivariate logistic regression were used to establish the optimal combinations of blood routine parameters in our screening model. Two subgroups were set according to age: ≤6 years old group and >6 years old group. In each group, patients were further divided into three subgroups: the influenza A-positive-result group (A+ group) (n=259), influenza A-negative-result group (A- group) (n=277) and healthy control group (H group) (n=110). Most routine blood parameters showed significant differences among the three subgroups in each age group. Notably, lymphocyte (LYM) number, platelet (PLT) number, lymphocyte-to-monocyte ratio (LMR) and LYM multiplied by PLT (LYM*PLT) exhibited extremely significant differences. Using A- group as a reference based on the area under the curve (AUC), both age groups had a similar trend. For A- group, the optimal cutoff value of LYM*PLT was 221.6, the AUC, the sensitivity and specificity were 0.6830, 55.71% and 76.92% in the ≤6 years old group. Meanwhile, the cutoff value of LYM*PLT was 196.7, and the AUC, the sensitivity and specificity were 0.6448, 53.97% and 70.81%, respectively in the >6 years old group. Screening model based on multivariate logistic regression model revealed that LYM*PLT was the optimal parameter combinations in ≤6 years old group (AUC =0.7202), while LYM and PLT were the optimal parameter combinations in >6 years old group (AUC =0.6760). Several blood routine parameters in children with influenza A demonstrate differential levels in both age subgroups. The LYM*PLT exhibits the potential screening value of influenza infection.

Cultural adaptation and reliability testing of the Chinese version of evidence-based practice knowledge assessment in nursing: A cross-sectional study

ObjectiveThe EKAN is a reliable and validated tool for objectively measuring the evidence-based practice (EBP) knowledge of nurses. Thus, we set out to translate and culturally modify the Evidence-Based Practice Knowledge Assessment in Nursing (EKAN), and then evaluate its validity and reliability among Chinese practicing nurses. MethodsThis cross-sectional study consisted of two phases. The first phase involved translating the EKAN into Chinese (EKAN-Chinese), using a process of forward translation, back translation, review, cultural adjustment as well as a pilot study. The second phase aimed to assess the psychometric properties of the EKAN-Chinese and establish a baseline measure of EBP knowledge among 120 nurses from a large general hospital in Beijing, China. Data were collected from August to November 2022 and analyzed with Rasch software. This study was reported using the cross-sectional STROBE checklist. ResultsThe newly translated, EKAN-Chinese was pilot-tested after slight modification of four items without altering the intended meaning. The outfit unweighted mean square was 1.03 (SD = −0.13), the infit weighted mean square was 1.00 (−0.17), and the mean difficulty index ranged from −3.43 to 2.85 according to validity indices. The results of the reliability indices revealed low person reliability (0.49), high item reliability (0.96), moderate person separation index (0.99), and sufficient item separation index (4.71). The mean EKAN-Chinese sum score was 9.8 (max score = 20, SD = 2.9). ConclusionThe newly translated EKAN-Chinese showed sufficient psychometric evidence to support use in practicing Chinese nurses. The EKAN-Chinese can be used by nurse leaders in China as a potential screening tool to 1) objectively identify nurses who need educational training in evidence-based nursing practice, and 2) gauge the effectiveness of education and training programs to improve EBP knowledge and ultimately, evidence-based care.

PICLS with human cells is the first high throughput screening method for identifying novel compounds that extend lifespan

Gerontology research on anti-aging interventions with drugs could be an answer to age-related diseases, aiming at closing the gap between lifespan and healthspan. Here, we present two methods for assaying chronological lifespan in human cells: (1) a version of the classical outgrowth assay with quantitative assessment of surviving cells and (2) a version of the PICLS method (propidium iodide fluorescent-based measurement of cell death). Both methods are fast, simple to conduct, cost-effective, produce quantitative data for further analysis and can be used with diverse human cell lines. Whereas the first method is ideal for validation and testing the post-intervention reproductive potential of surviving cells, the second method has true high-throughput screening potential. The new technologies were validated with known anti-aging compounds (2,5-anhydro-d-mannitol and rapamycin). Using the high-throughput screening method, we screened a library of 162 chemical entities and identified three compounds that extend the longevity of human cells.

Analysis of the cross section and characteristic of fluorescence emission of the He atom confined in the plasma conditions

The structural properties, angle-integrated total and magnetic sublevel excitation cross sections, alignments of the residual ion, and polarization properties of the line emission are investigated for the plasma-embedded atomic system. This is done using the developed distorted wave approach which solves the Dirac equation by employing a modified Debye potential to represent the screened interaction in plasmas. The effective Hamiltonian is employed to obtain the level energies as functions of the screening parameters. The Coulomb interaction is replaced by shielded Coulomb interaction during the collision dynamics. As an illustrating example, detailed calculations are carried out for the 1s2→1s2p3,1P1 excitations of the plasma-embedded He atom by electron impact. Our results suggest that the energy levels are pushed towards continuum as the effect of (plasma) confinement increases. The cross sections decreases monotonically if the screening effect is enhanced continuously, while the alignments of the residual He+ ion and polarizations of the fluorescence emission change slightly for the corresponding screening parameters. A comparison of our results in the absence of the screening potential with other available experimental and theoretical data shows satisfactory agreement. The present study not only provides a helpful approach to study the influence of plasma effect, but also has important applications in laser produced plasmas, stellar atmospheres, fusion research plasmas and so on.

Potential urinary biomarkers in preeclampsia: a narrative review.

Preeclampsia (PE) is a highly relevant pregnancy-related disorder. An early and accurate diagnosis is crucial to prevent major maternal and neonatal complications and mortality. Due to the association of kidney dysfunction with the pathophysiology of the disease, urine samples have the potential to provide biomarkers for PE prediction, being minimally invasive and easy to perform. Therefore, searching for novel biomarkers may improve outcomes. This narrative review aimed to summarize the scientific literature about the traditional and potential urinary biomarkers in PE and to investigate their applicability to screen and diagnose the disorder. A non-systematic search was performed in PubMed/MEDLINE, Scopus, and SciELO databases. There is significant divergence in the literature regarding traditionally used serum markers creatinine, cystatin C, and albuminuria, accuracy in PE prediction. As for the potential renal biomarkers investigated, including vascular epithelial growth factor (VEGF), placental growth factor (PlGF), and soluble fms-like tyrosine kinase (sFlt-1), urinary levels of PlGF and sFtl-1/PlGF ratio in urine seem to be the most promising as screening tests. The assessment of the global load of misfolded proteins through urinary congophilia, podocyturia, and nephrinuria has also shown potential for screening and diagnosis. Studies regarding the use of proteomics and metabolomics have shown good accuracy, sensitivity, and specificity for predicting the development and severity of PE. However, there are still many divergences in the literature, which requires future and more conclusive research to confirm the predictive role of urinary biomarkers in pregnant women with PE.

Epidemiological characteristics of patients with cholangiocarcinoma with and without ulcerative colitis: A retrospective cohort study.

564 Background: Ulcerative colitis (UC) is correlated with gastrointestinal cancer. While the exact mechanism is unknown, it is thought that a chronic inflammatory state may result in the development of malignancies including cholangiocarcinoma. Patients with UC that develop cholangiocarcinoma usually have a poor prognosis and early detection is key to improve survival. Methods: We used the 2016-2019 National Inpatient Sample (NIS) database, the largest all-payer inpatient care database in the United States, to stratify all patients admitted with a diagnosis of cholangiocarcinoma with and without ulcerative colitis, to further characterize their epidemiological characteristics. Results: There were at total of 46,001 patients with a diagnosis of cholangiocarcinoma studied. Of these patients with cholangiocarcinoma, 401 had concomitant UC (0.87%). Individuals with UC in the database had an increased association with cholangiocarcinoma (OR=7.67, 95% CI 6.96-8.46) compared to those without UC. Patients with cholangiocarcinoma and UC tended to be younger (57.8 vs. 67.9 years old without UC), male (69.51% vs. 53.23% without UC), with private insurance (57.5%) vs. patients without UC who predominately had Medicare (59.46%). Patients with cholangiocarcinoma and UC had on average fewer Charleston Comorbidities (64.63% with 3 comorbidities) vs. patients without UC (74.52% with 3 comorbidities). Of patients with cholangiocarcinoma and UC, 65.85% were Caucasian (vs. 64.85% without UC), 6.1% were Black (vs. 10.09% without UC), 3.66% were Hispanic (vs. 12.37% without), and 24.39% were Asian or Pacific Islander (vs 12.79% without). Conclusions: In the population studied, there was a significant correlation between UC and cholangiocarcinoma. Patients with cholangiocarcinoma and UC tended to be younger with fewer comorbidities than their counterparts without. There were nearly double the percentage of Asian patients with cholangiocarcinoma and UC as compared to Asian patients without UC. Understanding the characteristics of patients with UC who develop cholangiocarcinoma is important as it could inform future best practices in potential screening and early detection of carcinomas in patients with UC. [Table: see text]

Diagnostic Accuracy of Deep Learning for the Prediction of Osteoporosis Using Plain X-rays: A Systematic Review and Meta-Analysis.

(1) Background: This meta-analysis assessed the diagnostic accuracy of deep learning model-based osteoporosis prediction using plain X-ray images. (2) Methods: We searched PubMed, Web of Science, SCOPUS, and Google Scholar from no set beginning date to 28 February 2023, for eligible studies that applied deep learning methods for diagnosing osteoporosis using X-ray images. The quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 criteria. The area under the receiver operating characteristic curve (AUROC) was used to quantify the predictive performance. Subgroup, meta-regression, and sensitivity analyses were performed to identify the potential sources of study heterogeneity. (3) Results: Six studies were included; the pooled AUROC, sensitivity, and specificity were 0.88 (95% confidence interval [CI] 0.85-0.91), 0.81 (95% CI 0.78-0.84), and 0.87 (95% CI 0.81-0.92), respectively, indicating good performance. Moderate heterogeneity was observed. Mega-regression and subgroup analyses were not performed due to the limited number of studies included. (4) Conclusion: Deep learning methods effectively extract bone density information from plain radiographs, highlighting their potential for opportunistic screening. Nevertheless, additional prospective multicenter studies involving diverse patient populations are required to confirm the applicability of this novel technique.