Statistical Relevance Research Articles

EXPLORING THE PLIGHT OF THE HONEYBEE: USING DATA SENSORS AND CODAP TO SUPPORT EMERGING BILINGUAL LEARNERS IN REASONING ABOUT BIG STATISTICAL IDEAS

Children require access to high-quality statistics education to develop the skills to participate in a technological and data-reliant workforce. This study consisted of a five-lesson integrated STEM unit designed to develop the statistical literacy of 62 6th-grade (11–12 years old) emerging bilingual (EB) learners. Learning was situated in the study of the honeybee, utilising innovative technologies to gather data and support data visualisation and analysis. Lesson study was used to design lessons targeting understandings of distribution, centre, variability, data comparison, informal measures of association and informal inference. This paper reports on the data comparison lesson. It reveals the influential role of digital technologies in highlighting the relevance of statistics in understanding societal issues and developing students’ statistical agency. This qualitative study also revealed that the development of statistical understanding was supported by the use of inclusive pedagogies guided by the principles of universal design and the incorporation of data analysis technologies.

Ecological Management Zoning Based on the Supply–Demand Relationship and Synergies of Urban Forest Ecosystem Services: A Case Study from Fuzhou, China

Urban forests, as vital components of green infrastructure, provide essential ecosystem services (ESs) that support urban sustainability. However, rapid urban expansion and increased density threaten these forests, creating significant imbalances between the supply and demand for these services. Understanding the characteristics of ecosystem services and reasonably dividing ecological management zones are crucial for promoting sustainable urban development. This study introduces an innovative ecological management zoning framework based on the matching degree and synergies relationships of ESs. Focusing on Fuzhou’s fourth ring road area in China, data from 1038 urban forest sample plots were collected using mobile LIDAR. By integrating the i-Tree Eco model and Kriging interpolation, we assessed the spatial distribution of four key ESs—carbon sequestration, avoided runoff, air purification, and heat mitigation—and analyzed their supply–demand relationships and synergies. Based on these ecological characteristics, we employed unsupervised machine learning classification to identify eight distinct ecological management zones, each accompanied by targeted recommendations. Key findings include the following: (1) ecosystem services of urban forests in Fuzhou exhibit pronounced spatial heterogeneity, with clearly identifiable high-value and low-value areas of significant statistical relevance; (2) heat mitigation, avoided runoff, and air purification services all exhibit synergistic effects, while carbon sequestration shows trade-offs with the other three services in high-value areas, necessitating targeted optimization; (3) eight ecological management zones were identified, each with unique ecological characteristics. This study offers precise spatial insights into Fuzhou’s urban forests, providing a foundation for sustainable ecological management strategies.

Assessment of ComBat Harmonization Performance on Structural Magnetic Resonance Imaging Measurements.

Data aggregation across multiple research centers is gaining importance in the context of MRI research, driving diverse high-dimensional datasets to form large-scale heterogeneous sample, increasing statistical power and relevance of machine learning and deep learning algorithm. Site-related effects have been demonstrated to introduce bias in MRI features and confound subsequent analyses. Although Combating Batch (ComBat) technique has been recently reported to successfully harmonize multi-scale neuroimaging features, its performance assessments are still limited and largely based on qualitative visualizations and statistical analyses. In this study, we stand out by using a robust cross-validation approach to assess ComBat performances applied on volume- and surface-based measures acquired across three sites. A machine learning approach based on Multi-Class Gaussian Process Classifier was applied to predict imaging site based on raw and harmonized brain features, providing quantitative insights into ComBat effectiveness, and verifying the association between biological covariates and harmonized brain features. Our findings showed differences in terms of ComBat performances across measures of regional brain morphology, demonstrating tissue specific site effect modeling. ComBat adjustment of site effects also varied across regional level of each specific volume-based and surface-based measures. ComBat effectively eliminates unwanted data site-related variability, by maintaining or even enhancing data association with biological factors. Of note, ComBat has demonstrated flexibility and robustness of application on unseen independent gray matter volume data from the same sites.

CD105-microvessel density analysis and its clinical value in urothelial carcinoma of bladder patients

Background Endoglin/CD105-microvessel density (CD105-MVD) is identified as one of the most potential methods for semi-quantification of angiogenesis in human cancer tissues. Present study aimed to examine the diagnosticand prognostic value of CD105-MVD in two clinically distinct subtypes of urothelial carcinoma of bladder (UCB) namely non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC) patients. Methods Message expression of endoglin was analysed by real-time quantitative polymerase chain reaction (RT-qPCR) and MVD measurement was done by immunohistochemical staining in 90 UCB [NMIBC: 60; MIBC: 30] patients. SEM studies were carried out to examine tumor vasculature and extent of neoangiogenesis in NMIBC and MIBC patients. Results Elevated message expression of CD105 showed statistical significance with tumor stage, grade, smoking/tobacco chewing history in NMIBC andage in MIBC cohort. Higher values of CD105-MVD showed statistical relevance with tumor stage, grade, size, smoking/tobacco chewing history in NMIBC cohort. Kaplan Meier test identified high CD105-MVD as strong predictor of poor RFS in NMIBC patients. Conclusions Association of CD105 expression and MVD with the clinicohistopathological features as well as poor survival outcomes potentially identify it as a preferred marker of clinical significance in a given cohort of UCB patients. Clinical significance Strong association of CD105 at message level with the demographics of UCB patients identifies it as a marker of diagnosis in a given cohort of patients. Survival analysis examined CD105-MVD as an independent strong predictor of poor recurrence free survival in NMIBC patients. Present study provides clear evidence of increased vascular density, vascular sprouts proliferation and new blood vessel formation with disease aggressiveness indicating CD105 as a preferred marker of neoangiogenesis in the given cohort of patients. The study describes CD105-MVD as a biomarker of diagnosis and prognosis with the sensitivity of 91.67% and 93.33% in a given cohort of NMIBC and MIBC patients.

Decadal Trend in Humidex: Cooling and Heat Perception in Ibadan, Southwestern Nigeria

Rising global temperatures have resulted in more frequent and intense weather phenomena like heatwaves, storms, and floods, with heatwaves posing notable risks to environment, agricultural and human health. Many studies use localized thresholds to assess heat indexes, taking into account the unique climate patterns of different regions. The Humidex, which measures thermal discomfort, provides a deeper understanding of how temperature and humidity combine to impact human comfort and environmental stress. Weather data from Ibadan, South-Western Nigeria, provided by the Nigerian Meteorological Agency (NIMET), were analyzed for key climate variables to calculate the Humidex. The Mann-Kendall test determined statistical relevance, while Sen's slope measured trend magnitude. Originally developed by Canadian meteorologists, the Humidex assesses how humidity impacts human comfort. The analysis of temperature, relative humidity, and Humidex trends from 2014 to 2023 shows a clear pattern of heat stress during the dry season (February-April) with some relief during the rainy season (June-August). The Mann-Kendall test and Sen's slope revealed a notable downward trend in temperatures, especially in January, March, June, and November, with decreases ranging from -0.08°C to -0.27°C annually. This cooling trend is mirrored by decreasing Humidex values, particularly in January, March and June, indicating reduced heat stress. High humidity levels during the rainy season are mitigated by the cooling effects of rainfall, leading to lower overall heat perception (Humidex). This relationship between temperature and humidity underscores their combined role in influencing heat stress and comfort levels. The annual variations emphasize the importance of monitoring and managing climate risks in regions prone to extreme heat and humidity. Overall, the decline in both temperature and Humidex suggests a shift toward cooler conditions, which could alleviate extreme heat but also prompt concerns about the broader impacts of these changes on regional climate and agriculture.

Performance of Triple-Cation Perovskite Solar Cells under Different Indoor Operating Conditions.

We systematically analyze triple-cation perovskite solar cells for indoor applications. A large number of devices with different bandgaps from 1.6 to 1.77 eV were fabricated, and their performance under 1-sun AM1.5 and indoor white light emitting diode (LED) light was compared. We find that the trends agree well with the detailed balance limit; however, the devices near the optimal bandgap (1.77 eV) perform worse due to the lower perovskite quality. Instead, we achieve the highest power conversion efficiency (PCE) of 34.0% under 870 lx with 1.67 eV and Al2O3 passivation. The perovskite with a bandgap of 1.71 eV is not far behind, with a high VOC of 1.02 V. Measurements under different white LED color temperatures confirm that the highest PCE is achieved under the warmest colors. All measurements were carried out in a dedicated indoor setup that ensures the diffuse light typical of indoor environments and allows both short- and long-term measurements. In the best case, we observe no degradation during the 33-day test under simulated office conditions with regular switching on and off of the light and a T80 of 30 days under continuous illumination. The results were obtained from multiple batches, which corroborates our findings and gives them statistical relevance.

Prevalence of anxiety and depression disorders in patients with inflammatory bowel disease in a city in southern Brazil

Inflammatory bowel disease is a chronic disease with symptoms and possible complications that can bring disability to the patient and trigger impairment in mental health such as depression and anxiety disorder. Objective: To evaluate the prevalence of Anxiety and Depression Disorder in patients with IBD in the Inflammatory Bowel Disease outpatient clinic of UFPEL. Methodology: Applied socio-economic questionnaire, M.I.N.I. instrument and collection of data from the medical record during the medical consultation. In patients attending the FAMED-UFPEL outpatient clinic with a diagnosis of Inflammatory bowel disease and over 16 years of age in the period from 06/01/2021 to 02/28/2022. Results: During the exposed period, 59 patients diagnosed with IBD were evaluated, being 37 (62.7%) with Crohn's Disease and 22 (37.3%) with Ulcerative Colitis, the average age was 46 years. In the current study, disease activity was evaluated using the Mayo Score for patients with ulcerative colitis with a result with no statistical significance for depression (p:0,494) and anxiety disorder (p:0,484). The Harvey Bradshaw Score was used in patients with Crohn's Disease that also has no statistical relevance for depression (p:0.969) and anxiety disorder (p:0.380). In the present study, 29.4% of patients had Ulcerative Colitis and recurrent depressive episode and 54.2% of patients had generalized anxiety disorder. Conclusion: there is a high prevalence of mood disorders in the population studied, it is emphasized the need for the active search of these diagnoses in this population, offering adequate treatment of the pathologies found with a view to better quality of life.

Correlative Multi-Scale Characterization of Nanoparticles Using Transmission Electron Microscopy

Chemical and physical properties of nanoparticles (NPs) are strongly influenced not only by the crystal structure of the respective material, including crystal structure defects but also by the NP size and shape. Contemporary transmission electron microscopy (TEM) can describe all these NP characteristics, however typically with a different statistical relevance. While the size and shape of NPs are frequently determined on a large ensemble of NPs and thus with good statistics, the characteristics on the atomic scale are usually quantified for a small number of individual NPs and thus with low statistical relevance. In this contribution, we present a TEM-based characterization technique, which can determine relevant characteristics of NPs in a scale-bridging way—from the crystal structure and crystal structure defects up to the NP size and morphology—with sufficient statistical relevance. This technique is based on a correlative multi-scale TEM approach that combines information on atomic scale obtained from the high-resolution imaging with the results of the low-resolution imaging assisted by a semi-automatic segmentation routine. The capability of the technique is illustrated in several examples, including Au NPs with different shapes, Au nanorods with different facet configurations, and multi-core iron oxide nanoparticles with a hierarchical structure.

Cavity formation in silica‐filled rubber compounds observed during deformation by ultra small‐angle x‐ray scattering

AbstractWhen silica‐filled rubber compounds are deformed, structural modifications in the material's bulk lead to irreversible damage, the most significant of which is cavitation appearing within the interfaces of interconnected polymer and filler networks. This work introduces a new method to analyze cavitation in industrial‐grade rubbers based on ultra small‐angle x‐ray scattering. This method employs a specially designed multi‐sample stretching device for high‐throughput measurements with statistical relevance. The proposed data reduction approach allows for early detection and quantification of cavitation while providing at the same time information on the hierarchical filler structures at length scales ranging from the primary particle size to large silica agglomerates over four orders of magnitude. To validate the method, the scattering of SSBR rubber compounds filled with highly dispersible silica at different ratios was measured under quasi‐static strain. The strain was applied in incremental steps up to a maximum achievable elongation or breakage of the sample. From the measurements performed in multiple repetitions, it was found that the minimum strain necessary for cavity formation and the size evolution of the cavities with increasing strain are comparable between these samples. The sample with the highest polymer content showed the lowest rate of cavity formation and higher durability of silica structures. The structural stability of the compounds was determined by the evolution of the filler hierarchical structures, obtained by fitting data across the available strain range.

Performance of Closed-Ended Mutual Funds: A Test of Market Efficiency

Background: Mutual funds, known for aggregating funds from a diverse investor base, play a crucial role in managing small funds smartly. This study evaluates the performance of selected closed-ended mutual funds and examines market efficiency in Nepal. Methods: Using a descriptive and casual-comparative research design, the study spans forty-eight months from January 15, 2018, to January 14, 2022. Monthly data from five mutual funds are analyzed, with metrics such as the Treynor ratio, Sharpe ratio, and Jensen alpha. The study variables include market returns, assets, expense ratios, fund age, liquidity, and mutual fund returns. Various statistical tests, including correlation analysis, Integrated Ranking Analysis, ANOVA test, t-test, and P-value tests, are conducted to determine the significance and statistical relevance of the study variables. Results: The findings reveal that mutual fund performance is influenced by factors such as return, age, liquidity, asset, and expense ratio. Expense ratio and age emerge as the most impactful factors, demonstrating a statistically significant relationship with market return (p < 0.05). All selected mutual funds outperform the market return (NEPSE), with Sanima Equity Fund securing the top rank in all three measures. Conclusion: The Sharpe ratio, Treynor ratio, and Jensen alpha measures for mutual funds surpass those of the market, indicating market inefficiency in its semi-strong form. Novelty: This study uniquely evaluates closed-ended mutual funds using comprehensive performance metrics, demonstrating their significant outperformance compared to market benchmarks. It underscores their effectiveness in actively managing passive funds and challenges the efficient market hypothesis.

A-212 Comparison of formulas for measuring LDL in cancer patients with hypertriglyceridemia

Abstract Background Treatments in recent years in cancer patients have been very favorable. However, some data suggest that dyslipidemia plays a role in carcinogenesis through the deregulation of the lipid signal, and this possibly leads to the development of cardiovascular diseases. A marker for the diagnosis and treatment of dyslipidemias is low density lipoproteins (LDL), and currently, the primary care level still calculates LDL due to the high costs of the direct method; Friedewald has been used since 1972, and in recent years, new equations have appeared such as Sampson and Martin - Hopkins (MH). These formulas use total cholesterol (TC), high-density lipoproteins (HDL), and triglycerides (TG). Objective was to compare the formulas for measuring LDL in cancer patients with hypertriglyceridemia. Methods It´s an observational, cross-sectional - and analytical study. The sample size was 880 lipid profiles processed in an automated dry chemistry analyzer between January and March 2023 at an Oncology Institute in Lima, Peru. The population was divided into several groups of triglyceride levels (<200 mg/dl, 200- 399 mg/dl, ≥ 400 mg/dl), and LDL was stratified according to ATP III to evaluate the classification of patients with respect to LDL formulas. The statistical analysis was performed by descriptive analysis of the categorical and numerical variables; The correlation was performed using Pearson, and a comparison of the LDL formulas was used by Bland Altman to determine the bias and percentage bias. To clinical relevance, it was compared with the biological variation of the Westgard table. A p-value <0.05 was considered significant, and the data were processed in MedCalc v20.027. Results The average age of the patients was 55.02 ± 13.92 years, and the frequency of female sex was 77.39% (n = 681). The average measured TC, HDL, and LDL were 208.95 ± 54.84 mg/dl, 41.53 ± 13.83 mg/dl, and 115.70 ±45.53 mg/dl, respectively, while the calculated average LDL in Friedewald was 120.40 ± 48.57, MH was 130.49 ± 44.15 mg/dl and Sampson was 125.97 ± 45.53 mg/dl. The correlations of measured versus calculated LDL were strong (r > 0.89) at different TG levels; Statistical (p<0.05) and clinical relevance was observed in the Friedewald formula when TG ≥ 400 mg/dl, while the MH and Sampson formulas presented clinical and significant relevance at all triglyceride levels. Patients with an LDL level between 130 and 159 mg/dl presented a more substantial classification error according to the Friedewald, MH, and Sampson formulas. Conclusions Friedewald formula presented a clinically acceptable bias up to 400 mg/dl, unlike the MH and Sampson formulas, which were affected by triglycerides ≥ 150 mg/dl.

Hypernetwork modeling and topology of high-order interactions for complex systems

Interactions among the underlying agents of a complex system are not only limited to dyads but can also occur in larger groups. Currently, no generic model has been developed to capture high-order interactions (HOI), which, along with pairwise interactions, portray a detailed landscape of complex systems. Here, we integrate evolutionary game theory and behavioral ecology into a unified statistical mechanics framework, allowing all agents (modeled as nodes) and their bidirectional, signed, and weighted interactions at various orders (modeled as links or hyperlinks) to be coded into hypernetworks. Such hypernetworks can distinguish between how pairwise interactions modulate a third agent (active HOI) and how the altered state of each agent in turn governs interactions between other agents (passive HOI). The simultaneous occurrence of active and passive HOI can drive complex systems to evolve at multiple time and space scales. We apply the model to reconstruct a hypernetwork of hexa-species microbial communities, and by dissecting the topological architecture of the hypernetwork using GLMY homology theory, we find distinct roles of pairwise interactions and HOI in shaping community behavior and dynamics. The statistical relevance of the hypernetwork model is validated using a series of in vitro mono-, co-, and tricultural experiments based on three bacterial species.

Higher Nodal expression is often associated with poorer survival in patients diagnosed with melanoma and treated with anti-PD1 therapy.

Advanced melanoma is considered the most aggressive and deadly form of skin cancer whose incidence has been rising over the past three decades. In the absence of treatment, the median overall survival for advanced-stage metastatic disease is less than 6months. Although most melanomas detected at an early stage can be cured with surgery, a subset of these eventually metastasize. Therefore, a critical need exists to identify unique molecular features that would be predictive of long-term outcome and response to specific therapies. Recent promising therapeutic regimens have included the use of immune checkpoint inhibitors, such as anti-PD1 antibodies. However, the ability to identify responders and non-responders to this therapy remains elusive. To address this challenge at the molecular level, previously our laboratory identified the emergence of a stem cell phenotype associated with advanced melanoma and other aggressive forms of cancer. Underlying this phenotype is the aberrant re-expression of the embryonic morphogen "Nodal". Particularly noteworthy, we have observed Nodal to remain in advanced tumors of non-responders to standard-of-care therapies (i.e., BRAFi). This pilot study is the first proof-of-principle attempt to predict treatment response survival outcome in a small cohort of melanoma patients receiving anti-PD1 immune checkpoint inhibitor therapy - based on their Nodal expression profile. Using advanced multiplex immunohistochemistry-based digital pathology, the major finding of this preliminary study indicates that higher Nodal expression is often associated with poorer overall survival after anti-PD1 therapy, reaching nearly statistical relevance.

Deep Learning Based 3D Resolution Recovery for Breakthrough Imaging of Electrochemical Energy Devices

Many energy materials can only be understood within the context of the (often sealed) devices they make up. Batteries and fuel cells contain intricate mixtures of materials with features and arrangements that span across many orders of magnitude in size and operate under non-ambient conditions. In these devices, the microstructures of the constituent materials and how they are arranged with respect to each other is directly linked to the device performance and degradation behaviors. Complicating matters, opening the devices for inspection and analysis can irreversibly alter the very microstructures in question and can pose safety hazards to researchers if not done correctly. Furthermore, critical material and device properties such as tortuosity or ion transport pathways can only be accurately quantified in 3D. As such, observing microstructures and their evolution in 3D and in their native state is essential for developing a robust understanding of how to engineer new battery and fuel cell materials and architectures with improved performance.X-ray microscopy (XRM) provides a unique method for observing these microstructures in 3D at high resolutions without needing to open them. However, microscopy techniques like XRM make tradeoffs between FOV and resolution, which can pose challenges for strongly multiscale systems like batteries and fuel cells. For example, if images are acquired at high enough resolution to observe critical features like electrode particle sizes in lithium-ion batteries or gas diffusion layer fiber weaves, catalyst distributions, and microporous layer cracks in polymer electrolyte fuel cells, the field of view of that image is restricted to a small local region of the sample. This means that broader defect distributions or larger scale inhomogeneities will be missed. Additionally, for quantitative analysis applications, this means that statistical relevance will be sacrificed because of the limited analysis volume at the appropriate resolution. And for computational modelling efforts, device level phenomena will not be captured well due to the restricted field of view.Advances in modern AI-based resolution recovery methods combined with the non-destructive multiscale imaging capabilities of X-ray microscopy have allowed researchers to overcome this dependency between resolution and field of view to produce 3D images with both high resolution and large field of view. We present here examples of applying these methods to applications in lithium-ion battery and polymer electrolyte fuel cell research [1].[1] Wang, Y.D., Meyer, Q., Tang, K. et al. Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning. Nat Commun 14, 745 (2023).

Eco-efficiency approach in sustainable waste management: An uncertainty analysis for Chile

Municipalities require eco-efficiency in managing solid waste to enhance sustainability and achieve a circular economy. Despite the relevance of waste statistics, there is high data uncertainty, which limits attempts to benchmark eco-efficiency in this sector. To overcome this limitation, the data envelopment analysis tolerance method was used to evaluate the eco-efficiency of solid waste management for a sample of municipalities in Chile. For each municipality, a composite indicator embracing operational cost, recycled waste rates, and non-valorized waste rate was estimated. Data uncertainty was integrated in the assessment by simulating 729 scenarios for each municipality. Average eco-efficiency of the sample was 0.180, demonstrating the extremely poor performance of the municipalities in sustainable waste management. However, the eco-efficiency scores varied across municipalities, indicating differences in local capacity to develop and implement strategies for promoting circular economy. Large potential to improve eco-efficiency estimated in this study clearly shows that current solid waste management policies are not suitable for achieving circular economy objectives in Chile, thus alternative approaches should be adopted to enhance sustainable waste management.

A Comparative Analysis of Socio-Economic Development in Communities Near Special Economic Zones: A Global and Indian Perspective

The study examines the socio-economic effects of Special Economic Zones (SEZs) on adjacent communities nationally and globally. It assesses how SEZs promote industrial expansion, draw foreign investment and enhance local economic development, focusing on their impact on neighbouring areas. By comparing data from various countries, the research identifies common challenges and successes, highlighting the superior performance of Indian SEZs. Indian SEZs outperformed others in policy implementation and operational efficiency, with a mean score of 3.488 versus 2.940 for other countries, showing significant statistical relevance (p-value < 0.001). The t-value is 60.660 for Indian SEZs and 49.000 for those in other nations, each with 499 degrees of freedom. The 95% confidence interval for the mean difference is 3.375 to 3.601 for India and 2.822 to 3.058 for other countries. The comparison between policy implementation and operational performance of SEZs in India and those in other countries reveals notable differences. The mean score for policy implementation and operational performance in Indian SEZs is 3.488, while the mean score for SEZs in other countries is 2.940. This suggests that, on average, SEZs in India are perceived to be more efficient than their counterparts in other countries. The study addresses key questions: How do SEZs impact socio-economic growth in nearby communities? How do Indian SEZs compare to those in other countries? Regression analysis confirms that communities near SEZs see greater socio-economic development, with a Beta value of 0.707 indicating a strong positive correlation. These findings contribute to policy debates and guide future research on maximizing SEZ benefits for inclusive and sustainable development.

Blood type ABO and the cytokine profile of follicular fluid in women undergoing IVF/ET.

ABO blood type was hypothesised to be related to a number of infertility processes. There is still an open debate on ABO blood group's incompatibility and infertility. It was associated with ovarian reserve in women with subfertility. There is still not enough information on the influence of blood type and the immunology of follicular fluid (FF). 78 patients were selected, who underwent in vitro fertilization (IVF) between April 2021 and January 2022. FF samples from each individual patient were taken on the day of ovarian puncture and stored at -80°C until immunological assessment. Concentration of chosen interleukins - IL-1α, IL-2, IL-4, IL-5, IL-6, IL-8 IL-10, IL-15, IL-1β, IL-18, IFN, LIF, TNFα, GCSF and PIBF-1 were measured using commercially available ELISA kits. All assessed cytokines were present in the FF of exanimated patients. The concentration was compared to the blood type ABO of all women undergoing in vitro fertilization. No statistical relevance was found between blood type ABO and the concentration of GCSF, PIBF1, LIF, IL-15, IL-5, IL-8, IL-1 alfa, IL-1 beta, INF gamma, IL-2HS, IL-4HS, IL-6HS, IL-10HS in the FF obtained during ovarian puncture (p > 0,05). There was no statistically significant correlation between blood type ABO and the quality of embryo, and the positive pregnancy test in patients undergoing IVF/ET. The blood type ABO does not influence the wide cytokine profile of FF obtained during ovarian puncture in women with infertility of different origin, as well as embryo quality and pregnancy rate.

Alterations in Intestinal Mucosal Barrier Visualized by Confocal Laser Endomicroscopy in Liver Cirrhosis: A Pilot Trial (AMBIC).

Chronic liver disease occurs throughout the world irrespective of region, age, sex, or race, and it is caused by a variety of liver conditions. One of the most frequent infectious complications in liver cirrhosis that severely reduces the median survival is spontaneous bacterial peritonitis. Current guidelines recommend a paracentesis before starting an antibiotic prophylaxis for this complication. Selective intestinal decontamination significantly lowers the rate of first or recurrent SBP in cirrhotic patients, so in this study we aimed to investigate and quantify the intestinal integrity of patients with liver cirrhosis and correlate a pathologically increased permeability with the incidence of SPB. We included 14 patients who met the inclusion criteria. No patient was excluded. For the CLE investigation, we use probe based confocal laser endomicroscopy techniques from Mauna Kea (Cellvizio), enabling in vivo surface imaging. The images (optical biopsies) were analyzed for functional and structural barrier defects after the procedure using Mauna Kea software (version 1.0.09). Because of the small number of included patients and healthy controls, most results are lacking statistical relevance. We found that the CLE investigation showed an increased intestinal permeability in patients with liver cirrhosis, in concordance with previous published data, based on other assessment methods. This study confirms that previously published permeability scores can be applied for patients with liver cirrhosis and is, to our knowledge, the first to investigate the intestinal permeability in vivo in patients with liver cirrhosis. Further data are needed to identify patients at risk and help develop new and less invasive diagnostic criteria for cirrhotic patients who may profit from a prophylactic antibiotic treatment.

Statistics of Periodicals in the Baltic States: Data Sources and Collections

Publishing is a significant part of the cultural, creative, and economic sectors. Its research, assessment, and forecasting require grounded, reliable, accurate, consistent, and comparable statistical data. Considering the lack of research in periodicals statistics and the relevance of publishing statistics, as well as the fact that in the Baltic countries, publishing statistics data are collected by institutions at the same level, the problem arises whether the national libraries’ applied foundational recommendations and legal documents, as well as data collection methodology, can ensure data validity, reliability, comprehensiveness, and comparability. This article aims to examine and compare the data collection practices of periodical statistics in the Baltic States. The research object includes the legal foundation of publishing statistics in Lithuania, Latvia, and Estonia, as well as the 2022 publishing statistics resources and official statistics data collections. UNESCO recommendations and International Organization for Standardization standards can be considered guidelines for such data collection and accounting. The legal foundation of publishing statistics consists of legal deposit laws, which must ensure the sources of statistical data. Even though publishing statistics data are collected by national libraries and the source of statistical data in all countries is legal deposits, the statistical data collections are not identical. Countries choose which data to collect, what criteria to apply, and in what form to present them. It is important to emphasize that data on the publishing industry are not presented in statistical collections, although their collection guidelines and presentation importance are highlighted in international recommendations and normative documents. Statistical data on electronic periodicals are provided only by Estonia. National libraries in the Baltic States are official statistics compilers, so summarized publishing statistics data are provided to national statistics institutions, opening new technological possibilities for data analysis and integration of new data. The collections of statistical data on newspapers and magazines can only be compared according to a few main criteria, as countries have chosen different statistical data presentation features, the main ones being the varying categorization and periodicity characteristics of newspapers and magazines.

Factors Influencing Central Venous Catheter-Associated Bloodstream Infections in COVID-19 Patients

During the pandemic of COVID-19, the rates of bloodstream infection associated with venous catheter in patients infected with the disease admitted to an intensive care unit rose significantly. In this study, we evaluated the occurrence of bloodstream infections in patients with SARS-CoV-2 and the variables that made the patients more susceptible to the catheter-associated bloodstream infection (CABSI). Blood culture results from patients interned between March 2020 and December 2021 (n= 109) were collected electronically from the hospital information system and then analyzed. The following variables presented statistical relevance after an adjusted model as follows: obesity (p = 0.003) and time of use of catheter before infection (p = 0.019). In conclusion, patients with shorter catheter use time and obesity had higher incidence of CABSI.