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Menstrual disturbance associated with COVID-19 vaccines: A comprehensive systematic review and meta-analysis
Background The relationship between COVID-19 vaccines and menstrual disturbance is unclear, in part because researchers have measured different outcomes (e.g., delays vs. changes to cycle length) with various study designs. Menstrual disruption could be a decisive factor in people’s willingness to accept the COVID-19 vaccine. Methods We searched Medline, Embase, and Web of Science for studies investigating menstrual cycle length, flow volume, post-menopausal bleeding, and unexpected or intermenstrual bleeding. Data were analyzed using fixed-effects meta-analysis with Shore’s adjusted confidence intervals for heterogeneity. Findings Seventeen studies with >1·9 million participants were analyzed. We found a 19% greater risk of increase in menstrual cycle length as compared to unvaccinated people or pre-vaccination time-periods (summary relative risk (sRR): 1·19; 95% CI: 1·11–1·26; n = 23,718 participants). The increase in risk was the same for Pfizer-BioNTech (sRR: 1·15; 1·05–1·27; n = 16,595) and Moderna vaccines (sRR: 1·15; 1·05–1·25; n = 7,523), similar for AstraZeneca (sRR: 1·27; 1·02–1·59; n = 532), and higher for the Janssen (sRR: 1·69; 1·14–2·52; n = 751) vaccine. In the first cycle after vaccination, length increased by <half-day (summary mean difference (sMD): 0·34 days; 0·21–0·46 days; n = 30,320) after the first dose and by 0·62 days (sMD: 0·62: 0·41–0·82; n = 17,608) after the second dose. In the second cycle after vaccination, the risk was not elevated (sMD: –0·02; –0·16–0·12; n = 18,602). The increase in risk was between 7–9% but statistically insignificant for heavier flow; 7% for post-menopausal bleeding (first dose: 1·07; 1·01–1·12; n = 1,321,268 and second dose: 1·07; 1·03–1·11; n = 1,482,884); and 16–41% for unexpected or intermenstrual bleeding (first dose: 1·16; 0·83–1·61; n = 1,303,687 and second dose: 1·41; 0·99–2·01; n = 1,390,317). Interpretation We observed a mild increase in the risk of menstrual disturbance associated with COVID-19 vaccines. Such risks are likely clinically unmeaningful. Vaccine recipients should be appropriately counseled.
Deformation mechanism of soft rock based on mineral crystal models
Flourishing at work: Psychometric properties of the Polish version of the Workplace PERMA-Profiler
The main purpose of this study was to investigate the validity of the Polish version of the Workplace PERMA-Profiler (WPP). Our work was guided by Martin Seligman’s perspective on positive psychology, emphasizing well-being as its central theme, flourishing as the gold standard for measuring well-being, and the ultimate goal of increasing flourishing. According to his PERMA model, flourishing encompasses five key elements: positive emotions, engagement, relationships, meaning, and accomplishment. The WPP is a tool specifically designed to measure this construct in the workplace context. Polish workers completed online surveys at the initial measurement (N = 1070). In addition, a group of working adults (N = 66) took part in a survey with a repeated measure diagnosing measurement stability. Flourishing, perceived stress, and work satisfaction were measured for comparisons of convergent validity, while zero-sum belief was measured for divergent validity. The reliability indices of the Polish version of the WPP met the minimum reliability requirements, and the Confirmatory Factor Analysis indicated that the five-factor model (contrasted to the single-factor model) achieved the desired goodness-of-fit properties. The WPP also demonstrated convergent validity through strong interrelationships with related constructs and strong stability. Obtaining satisfactory psychometric properties of the Polish version of the WPP enabled the conduction of additional type of exploratory analyzes focused on the relationship between workplace flourishing and the efforts aimed at building employee well-being undertaken by the organization where the respondents work. The study revealed a positive, moderate relationship between employees’ flourishing and the evaluation of organizational practices for increasing employee well-being.
Colonization effect of Beauveria bassiana (Bals.) Vuill. on tomato plant and Bemisia tabaci
Abstract Whitefly (Bemisia tabaci) is an insect threatening tomato production in Egypt. This study investigated the impacts of the entomopathogenic fungi species, Beauveria bassiana, isolate against B. tabaci on tomato plants under natural conditions in two seasons (2023–2024). Conidial powder was directly applied to the soil. Fungus was added to the fertilization treatments (BF) and was compared with fertilization (CF) and control (C0). The findings indicated notable significant variations in the population densities of B. tabaci in comparison to the other groups in two seasons. This fungus can also be used as a growth enhancer besides being a biopesticide for tomato crops. Tomato leaf samples were collected in three growth phases: vegetative, flowering, and fruiting phases in addition to ripe tomato fruits. Collected leaves were dried and used to detect defense mechanisms through estimating phenolic compounds such as tannins and flavonoids and total protein content, while tomato fruits were used to estimate ascorbic acid level as a growth promotion indicator in the tested tomato plants. B. bassiana -treated plants showed a significant increase in total tannins compared to fertilization-treated plants and non-significant increase compared to control. While Total Protein Content (TPC) was significantly higher in fertilization-treated plants than in B. bassiana -treated plants and control it was only increased significantly in the bioagent treatment than in the control. For total flavonoids, a non-significant increase was detected in total flavonoids content in B. bassiana-treated plants than in fertilization- treated plants and controls. Beauveria bassiana -treated tomato fruits recorded the highest value of ascorbic acid content, which significantly increased than fertilization treatment and non-significantly increased compared to the control. Generally, the interaction between treatments and growth phases in total tannin content, total protein content, and total flavonoid content was not statistically significant, which means there is no behavior for B. bassiana treatment on the plant resistance mechanism during the different growth stages, and the highest level for each was recorded in the flowering phase compared to the vegetative and fruiting phases. Also, the findings indicated the highest yield was represented by adding B. bassiana to the soil. The obtained results from this study refer to the beneficial role of B. bassiana in systemic resistance induction stimulated by tannin content in the tested tomato plants against whitefly attacks.
A comparative study on immune responses to demineralized and decellularized bone substitute following intraperitoneal implantation in mouse model
The immunological sensitization of implanted bone grafts is crucial for long-term success. This study aimed to investigate the immune responses following implantation of lyophilized demineralized (DMB) and lyophilized decellularized (DCC) bovine cancellous bone substitutes, respectively, in mouse models of peritoneal implantation to evaluate the effectiveness of DMB and DCC processing methods. The DMB and DCC substitutes were prepared using published methods. BALB/c mice were divided into four groups (n = 4). A small abdominal incision was created to deliver the DMB or DCC materials into the peritoneal cavity. The first group received native unprocessed bone, while the second group was sham-operated (SO). The third and fourth groups received DMB and DCC substitutes, respectively. The immunogenicity effects of the implants were assessed through WBC count, spleen index, CD4 + /CD8 + counts, cytokine expression, and histology analysis of the spleen, liver and kidney. Native controls displayed systemic inflammation. The DMB group showed an increased trend in WBC count, cytokine profile and spleen index on day seven, followed by a considerable reduction in the DCC group compared to DMB on days 14 and 21. The native group showed significantly higher CD4+ /CD8+ T-cells and proinflammatory cytokines (IL-12, TNF-α, IFN-γ, MCP-1, IL-6). Additionally, the DMB group showed significantly higher mRNA levels for IL-1β, TNF-α, IL-6, and the anti-inflammatory cytokine IL-10. The DMB group further exhibited a significantly higher CD4 + count, while the DCC group demonstrated higher CD8+ T-cells on day 1. Histological assessments of the liver and kidney revealed pyknotic nuclei, necrotic cells, and extravasated RBCs in the native group and, to a lesser extent, in the DMB group, while the DCC group showed normal morphology similar to Sham. Both DMB and DCC demonstrated favourable immunocompatibility properties, while DCC exhibited further immune tolerance in the mouse model.
Comparative analysis of neurosteroid levels in normal and adenomatous human pituitary tissue
A robust optimization model for allocation-routing problems under uncertain conditions
Post-earthquake emergency logistics faces significant challenges such as limited resources, uncertain casualty numbers, and time constraints. Developing a scientific and efficient rescue plan is crucial. One of the key issues is integrating facility location and casualty allocation in emergency medical services, an area rarely explored in existing research. This study proposes a robust optimization model to optimize the location of medical facilities and the transfer of casualties within a three-level rescue chain consisting of disaster areas, temporary hospitals, and general hospitals. The model accounts for limited medical resources, casualty classification, and uncertainty in casualty numbers. The Trauma Index Score (TIS) method is used to classify casualties into two groups, and the dynamic changes in their injuries after treatment at temporary hospitals are considered. The objective is to minimize the total TIS of all casualties. A robust optimization approach is applied to derive the corresponding robust model, and its validity is verified through case studies based on the Lushan earthquake. The findings show that data variability and the uncertainty budget play a critical role in determining hospital locations and casualty transportation plans. Temporary hospital capacity significantly influences the objective function more than general hospitals. As the problem size increases, the robust optimization model performs better than the deterministic model. Furthermore, uncertainty in casualty numbers has a more significant impact on serious casualties than moderate casualties. To enhance the model’s applicability, it is extended into a two-stage dynamic location-allocation model to better address the complexity of post-disaster scenarios.
Transforming tabular data into images via enhanced spatial relationships for CNN processing
Abstract Convolutional neural networks (CNNs), renowned for their efficiency in image analysis, have revolutionized pattern and structure recognition in visual data. Despite their success in image-based applications, CNNs face challenges when applied to tabular data due to the lack of inherent spatial relationships among features. This weakness can be overcome if the original tabular data is expanded to create an enhanced image that exhibits pseudo-spatial relationships. This paper introduces an original approach that transforms tabular data into a format suitable for CNN processing. The Novel Algorithm for Convolving Tabular Data (NCTD) applies mathematical transformations including rotation translation and reflection, to simulate spatial relationships within the data, thereby constructing a data structure analogous to a 2D synthetic image. This transformation enables CNNs to process tabular data efficiently by leveraging automated feature extraction and enhanced pattern recognition. The NCTD algorithm was extensively evaluated and compared with traditional machine learning algorithms and existing methods on ten benchmark datasets. The results showed that NCTD consistently surpassed the majority of competing algorithms in nine out of ten datasets, indicating its potential as a robust tool for extending CNN applicability beyond conventional image-based domains, particularly in complex classification and prediction.
What factors enhance students’ achievement? A machine learning and interpretable methods approach
Prior research on student achievement has typically examined isolated factors or bivariate correlations, failing to capture the complex interplay between learning behaviors, pedagogical environments, and instructional design. This study addresses these limitations by employing an ensemble of five machine learning algorithms (SVM, DT, ANN, RF, and XGBoost) to model multivariate relationships between four behavioral and six instructional predictors, using final exam performance as our outcome variable. Through interpretable AI techniques, we identify several key patterns: (1) Machine learning with explainability methods effectively reveals nuanced factor-achievement relationships; (2) Behavioral metrics (hw_score, ans_score, discus_score, attend_score) show consistent positive associations; (3) High-achievers demonstrate both superior collaborative skills and preference for technology-enhanced environments; (4) Gamification frequency (s&v_num) significantly boosts outcomes; while (5) Assignment frequency (hw_num) exhibits counterproductive effects. The results advocate for: (a) teachers should balance direct instruction with active learning modalities to optimize achievement, and (b) early warning systems should leverage identifiable learning features to proactively support struggling students. Our framework enables educators to transform predictive analytics into actionable pedagogical improvements.
The causal effects of systemic antioxidant capacity on male infertility: A two-sample mendelian randomization analysis
Applying a system dynamics approach for decision-making in software testing projects
Enhancing software quality remains a main objective for software developers and engineers, with a specific emphasis on improving software stability to increase user satisfaction. Developers must balance rigorous software testing with tight schedules and budgets. This often forces them to choose between quality and cost. Traditional approaches rely on software reliability growth models but are often too complex and impractical for testing complex software environments. Addressing this issue, our study introduces a system dynamics approach to develop a more adaptable software reliability growth model. This model is specifically designed to handle the complexities of modern software testing scenarios. By utilizing a system dynamics model and a set of defined rules, we can effectively simulate and illustrate the impacts of testing and debugging processes on the growth of software reliability. This method simplifies the complex mathematical derivations that are commonly associated with traditional models, making it more accessible for real-world applications. The key innovation of our approach lies in its ability to create a dynamic and interactive model that captures the various elements influencing software reliability. This includes factors such as resource allocation, testing efficiency, error detection rates, and the feedback loops among these elements. By simulating different scenarios, software developers and project managers can gain deeper insights into the impact of their decisions on software quality and testing efficiency. This can provide valuable insights for decision-making and strategy formulation in software development and quality assurance.
A cross-sectional online survey on oncologists’ attitudes toward and experiences with providing patients with audio recordings of their medical encounters
Abstract Providing patients with audio recordings of their medical encounters, termed consultation recordings, has shown promising benefits, especially for patients with cancer. While patients favor these recordings, international research indicated that physicians have mixed feelings. To date, research specific to Germany remains limited. This study investigated German oncologists’ attitudes and experiences through a nationwide cross-sectional quantitative online survey, informed by semi-structured interviews. Attitudes, prior experiences and desire for consultation recordings were assessed. Data was analyzed using descriptive statistics and subgroup analyses. Ninety-four physicians participated, with about half expressing a generally positive attitude, though overall attitudes were mixed. Expected benefits included improved patient recall and communication, while concerns centered around potential misuse of recordings, data confidentiality, and increased legal risks. Experiences were limited, with 12% reporting previous use. Fourteen percent expressed a willingness to offer recordings in future and 31% were undecided. This study highlights cautious openness among German oncologists, tempered by concerns over data security and legal implications, which may hinder adoption. This could be addressed by providing sound evidence regarding benefits and concerns, and enabling positive experiences. Further research should include feasibility testing in routine cancer care and re-evaluation of these results in representative samples and other specialties.
Pre-transplant residual diuresis and oxalic acid concentration influence kidney graft survival
Background and hypothesis Oxalic acid, a toxic metabolic end product, accumulates when kidney function deteriorates. Apart from its direct tubulotoxicity, it crystallizes at concentrations above 30–40 µmol/L. High oxalic acid concentrations at transplantation might negatively influence kidney transplant function. The influence of the concentrations of oxalic acid and its precursors and residual diuresis on kidney transplant outcomes was studied. Methods In this prospective cohort study, patients who received a kidney transplant between September 2018 and January 2022 participated. Concentrations of oxalic acid and precursors were determined in pre-transplant blood samples. Data on residual diuresis and other recipient, donor or transplant related variables were collected. Follow-up lasted until July 1st 2023. Results 496 patients were included, 154 were not on dialysis. Median residual diuresis was 1000 mL/day (IQR 200; 2000 mL/day). There were 230 living donor transplantations. Oxalic acid concentrations exceeded the upper normal concentration in 99% of patients, glyoxylic acid in all patients. There were 52 (10%) graft failures. As the influence of oxalic acid on the risk of graft failure censored for death was non-linear, it was categorized into two groups: ≤ 60 and > 60 μmol/L. In multivariable Cox analysis the graft failure censored for death risk was significantly influenced by residual diuresis, donor type (living versus deceased), donor age and oxalic acid. In 180 patients oxalic acid concentration shortly after transplantation was significantly lower than pre-transplant concentrations, suggesting excretion by the new graft. A better eGFR at day 7 was associated with lower oxalic acid concentration. Oxalic acid and residual diuresis did not influence patient survival. Conclusion Residual diuresis and oxalic acid concentration are important and independent predictors of graft survival censored for death. These results underline the importance of pre-emptive transplantation, or optimizing the pre-transplant patients’ condition regarding waste product concentrations.
Three-dimensional optical trapping with a low-NA objective using a flat-top beam
Efficacy and safety of rifaximin in preventing hepatic encephalopathy: A systematic review and meta-analysis
Rifaximin (RFX) is recommended for the treatment of hepatic encephalopathy (HE). However, evidence on whether RFX application could yield additional benefits for preventing HE in patients with cirrhosis is limited. In this study, we aimed to assess the safety and efficacy of RFX in preventing HE. We conducted a systematic search of randomized controlled trials to evaluate the use of RFX by analyzing HE incidence, hospitalization, all-cause mortality, and adverse events. Compared with the control group, RFX had a beneficial effect on the primary prevention of HE (RR = 0.58, 95% CI: 0.50–0.68), with noncomparable effects to NADs (including lactulose and lactitol, RR = 0.65, 95% CI: 0.38–1.11), but more effective than placebo (RR = 0.57, 95% CI: 0.47–0.69). After more than 1 month of RFX treatment, the risk of HE decreased significantly (RR = 0.55, 95% CI: 0.47–0.65). In secondary prevention of HE, RFX decreased the recurrence risk (RR = 0.49, 95% CI: 0.40–0.61). RFX helped to reduce the incidence of HE after transjugular intrahepatic portosystemic stent shunt (TIPSS) (RR = 0.70, 95% CI: 0.51–0.96). In terms of adverse effects, RFX was associated with a lower risk of diarrhea than NADs (RR = 0.04, 95% CI: 0.00–0.25). So, RFX therapy is effective and well-tolerated in preventing HE, and can be used as the first choice in the prophylaxis of HE after TIPSS.
Sleep architecture characteristics in patients with acute ischemic stroke
Studying the decontamination process of an irradiated beryllium reflector in a chlorine environment
Beryllium, possessing unique nuclear physical properties, is currently widely used as a material for reflector and neutron moderator blocks of research nuclear reactors. It can also be applied in fusion energy as a first-wall material and neutron multiplier. However, when beryllium is irradiated, its physical-mechanical properties deteriorate due to radiation-induced microstructural damage, the generation of tritium and helium, the activation of impurities under the radiation exposure, and the absorption of fission products, which determines the need for periodic replacement of the beryllium components in nuclear installations. Moreover, due to the relatively low abundance of beryllium, a relevant problem is its purification from radioactive isotopes for potential reuse. To date, chlorination has emerged as one of the most promising methods for purifying irradiated beryllium. This study addresses the optimization of the chemical process parameters and the isolation of the beryllium component from the resulting mixture of chlorination products, including the most active radionuclides: 3H, 60Co, 108mAg, and 137Cs. Laboratory-scale experiments confirmed the effectiveness of the irradiated beryllium chlorination technology for its purification. The reduction in the activity level of beryllium and its compounds was objectively monitored using gamma and beta spectrometry methods.
Gene expression and agent-based modeling improve precision prognosis in breast cancer
Abstract Breast cancer survival is hard to predict because of the complex ways genes and cells interact. This study offers a new method to improve these predictions by combining gene expression profiling (GEP) with agent-based modeling (ABM). First, GEP will pinpoint genes that are important in breast cancer development. Then, a mathematical model will be built to show how these genes influence cell behavior. This data will be used in ABM to simulate tumor growth and treatment response. The ABM allows us to virtually test different treatments and see how they might affect patient survival. Finally, the model’s accuracy will be checked against real patient data and compared to other models. By combining the strengths of GEP and ABM, this research could significantly improve breast cancer survival prediction. ABM’s ability to analyze interactions mathematically could pave the way for more personalized and effective treatments.
Protocol: Weight-adjusted effective volume of 0.5% ropivacaine for combined costoclavicular brachial plexus block–cervical plexus blocks undergoing arthroscopic shoulder surgery: A dose-finding study protocol
Introduction Rotator cuff injuries are common clinically, and arthroscopic repair is widely applied. Postoperative analgesia can be assisted by the interscalene brachial plexus block; however, it comes with side effects, among which a high incidence of hemidiaphragmatic paralysis (HDP) is included. Costoclavicular brachial plexus–cervical plexus blocks (CCB–CPBs) offer comparable analgesia with lower HDP risk, yet local anesthetic volume issues can affect outcomes. In patients undergoing arthroscopic shoulder surgeries under general anesthesia with CCB–CPBs, the aim is to determine the optimal dose of ropivacaine for postoperative analgesia while avoiding hemidiaphragmatic paralysis (HDP), Methods and analysis This trial will be a prospective, single-arm, double-blind dose finding study. We plan to enroll 40 patients who will be scheduled to undergo arthroscopic shoulder surgeries under anesthesia that combines general anesthesia with CCB–CPBs. The volume of the local anesthetic will be determined by adopting the Up-and-Down sequential allocation study design. The primary outcome will be the numerical rating scale (NRS) scores of the patients prior to their departure from the post-anesthesia care unit (PACU). As for the secondary outcomes, they will include the ipsilateral diaphragmatic excursion, the characteristics of the sensory–motor block, the occurrence of complications, as well as the consumption of fentanyl during the operation. Ethics and dissemination Approval for the protocol of this study was granted by the Ethics Committee of Ningbo No. 6 Hospital in Zhejiang Province, China, on July 29, 2024 (Approval No. 2024-67L). Once the study is completed, we are committed to guaranteeing that the results will be accessible to the public, irrespective of the outcome. This will involve either publishing them in an appropriate journal or presenting them orally at academic conferences. Trial registration Trial registration number ChiCTR2400090292