Jakub Wojtasik

Tree‐ring width (RW) records primarily capture low‐frequency temperature variability, yet resolving high‐frequency signals is critical for testing climate models and contextualizing modern extremes. Blue rings (BRs)—bands of unlignified cells revealed by micro‐anatomical staining—capture short‐lived cooling events. Using 83 Pinus longaeva cores, we present the first millennial‐length (900–2014 CE) BR chronology and explore its paleoclimatic significance. BRs are largely decoupled from growth reductions: they often occur in rings of normal or above‐average width, preceding RW minima by one year, recording abrupt late‐season cooling that does not immediately suppress growth but frequently triggers reduced growth the following year. Events include anomalies associated with major volcanic eruptions, whose impacts are delayed and smoothed in RW chronologies. By capturing transient temperature declines with annual precision, BRs provide a novel dendroclimatic proxy that bridges low‐frequency and sub‐seasonal climate signals, offering benchmarks for climate‐model evaluation and attribution under past and contemporary climate change.

This study endeavors to fill the gap between demand forecasting and inventory control by evaluating and comparing classical, semiparametric, machine learning (ML), and deep learning (DL) forecasting models in a periodic-review, order-up-to inventory system with fill-rate service-level targets. We emphasize the superiority of global, probabilistic ML/DL models compared to traditional methods and the impact of integrating downstream inventory decision criteria into model training. This holistic approach to inventory planning improves both effectiveness and service-level requirements.

Background: Poland’s COVID-19 experience resulted in one of Europe’s most severe mortality shocks, yet the share of lost life-years occurring at working age has not been quantified. Methods: We analysed weekly all-cause deaths by sex and 5-year age groups for 2011–2019, and fitted fixed effects linear models to forecast expected mortality rates for 2020–2024. Next, we compared predicted and observed rates to estimate excess mortality. These estimates were converted into excess deaths and p-scores, excess Years of Potential Life Lost (eYPLL) and excess Years of Potential Productive Life Lost (eYPPLL). Results: We estimated 257,246 excess deaths in Poland over the five-year horizon (13.4% and 12.2% more deaths than expected in men and women, respectively). These deaths yielded 1,921,265 eYPLL and 521,887 eYPPLL, meaning that 27% of all life-years lost fell within working age. Men accounted for 54% of excess deaths but 72% of eYPLL and 79% of eYPPLL. More than half of the female and more than a third of the male productive-life loss accrued between ages 30 and 49. Temporal concentration was marked, 46% of excess deaths and 40% of eYPPLL occurred in 2021 alone. In 2023–2024, negative excess mortality emerged among older adults (aged 55–69), but without fully offsetting losses among the working-age and 70 + population. This translated to negative eYPLL in women in 2024, but persistent productive-age losses were still identified in this group. COVID-19-coded fatalities explained almost two-thirds of eYPLL and 40% of eYPPLL during 2020–2024. Poland’s excess mortality resulted in an average loss of 14–15 productive years for every excess death before retirement. Conclusions: This study extends usual excess deaths estimates to the productive life lost dimension and shows that the pandemic curtailed not only longevity but also burdened Poland with over half a million labour-force years lost. These losses magnify pre-pandemic labour shortages and add demographic pressure, translating to reduced labour supply and potential output, and underscoring the macroeconomic cost of major health shocks such as the COVID-19 pandemic.

This study addresses the challenge of aligning inventory forecasting with sustainability and service level goals in re-order point systems. It introduces a semiparametric forecasting method based on exponential smoothing and M-estimation, designed to directly model reorder levels under fill rate (P2) constraints. The proposed approach is benchmarked against state-of-the-art techniques, including Generalized Autoregressive Score (GAS) models, volatility-adjusted smoothing, and DeepAR—a deep learning model for probabilistic time series forecasting. Using monthly demand data from the M3 competition, empirical evaluation demonstrates that the semiparametric method achieves high service level accuracy with low inventory and logistics costs, particularly under short lead times. DeepAR shows strong performance in minimizing inventory levels but tends to underestimate stock requirements under high service level targets. A hybrid strategy combining forecasts from multiple models proves robust across scenarios, reducing forecast risk. The findings highlight the potential of integrating traditional statistical methods with AI-based approaches to support resource-efficient inventory management. By minimizing excess stock and backorders, the proposed methods contribute to reducing environmental impact, offering practical solutions for organizations seeking to balance operational efficiency with sustainability.

Background/Objectives: The concentration of uric acid in the body of older adults may have various effects. Due to the multidirectional influence on metabolism, its significance in the daily functioning of older persons remains unclear. The present investigation explored whether serum uric acid levels are associated with scores on standard geriatric assessment scales in hospitalized older adults. Methods: In total, 77 patients admitted to the hospital for the Comprehensive Geriatric Assessment were recruited and classified into three groups: successfully treated for hyperuricemia, untreated or unsuccessfully treated with elevated uric acid levels, and untreated controls having normal uric acid levels. The analysis considered the relationship between the concentration of uric acid in patients from different study groups and the assigned classes defined by the ranges of the questionnaires used for the study. Results: Significant differences were shown in the distribution of classes defined by Addenbrooke’s Cognitive Examination III (ACE-III) and the MNA questionnaires concerning the study groups. Moreover, significant differences were confirmed when using compartmentalization based only on the screening test results for the ACE-III, the Mini Nutritional Assessment (MNA), and the Mini-Mental State Examination (MMSE). For ACE-III, a lower percentage of people with probable dementia was observed in the control group (34.5%) than in the group with elevated uric acid values (78.3%). Conclusions: Although the mechanisms related to uric acid’s influence on older people’s functioning require further research, the available evidence indicates a negative impact of elevated uric acid levels on cognitive functions and the nutritional status of older individuals.

Previous studies have shown the role of uric acid in triggering inflammatory reactions through its influence on a large group of cytokines. Therefore, searching for possible relationships between treating hyperuricemia and the course of inflammatory processes may provide valuable knowledge for clinical practice. The study was designed to determine the relationship between uric acid levels and interleukin-6 (IL-6) and interleukin-1-beta (IL-1 beta) levels determined in older adults during hospitalization. Patients were assigned to different study groups based on the uric acid levels and effectiveness, lack of treatment, or recognition of hyperuricemia. Classical variance analysis methods or nonparametric Kruskal-Wallis tests were used for statistical analysis. The analysis showed different correlations between the concentration of uric acid and the mentioned interleukins and designated study groups. In the case of properly treated hyperuricemia, a weak negative correlation is observed between the level of uric acid and interleukin IL-1β. There is a statistically significant positive correlation between the value of uric acid and interleukins IL-6 and IL-1β in people with untreated hyperuricemia and, to a lesser extent, in people with normal uric acid levels. The study’s results suggest that effective treatment may be associated with appropriate control of uric acid concentration and modulation of the inflammatory response. However, due to several measurement limitations, further research is warranted to better elucidate these associations.

Background: The COVID-19 pandemic profoundly disrupted workplace attendance, yet its impact on cause-specific work absence remains largely unexplored. Aim: To estimate the cause-specific excess/reduced work absence associated with COVID-19 in Poland. Methods: Following the concept of excess mortality, we define excess work absence as the difference between observed and expected absence, where the latter reflects the level anticipated in the absence of the pandemic. Using time-series analysis (Seasonal Autoregressive Integrated Moving Average) on pre-pandemic (2012–2019) quarterly (Q) social insurance data, we forecasted absence rates for disease groups (classified by ICD-10 chapters) and caregiving-related absenteeism. Forecasted absence rates were then compared to observed values during 2020–2024, allowing for the identification of excess or reduced work absence. Results: We observed notable deviations in work absence rates during the pandemic period (until the end of Q1-2022). The highest excess absence was identified in caregiving-related absenteeism at the pandemic’s onset, exceeding expected levels by over fivefold. A mental health crisis that began with the pandemic resulted in four consecutive quarters of excess absence, reaching a 54% excess in Q2-2020. We identified a notable excess absence in three ICD-10 chapters that reflect the indirect effects of the pandemic, such as increased diagnostic uncertainty, modified coding practices during early COVID-19 waves, and widespread implementation of public health interventions. Absence rates were lower than expected in neoplasms, endocrine and digestive diseases until the end of the pandemic period, likely reflecting reduced healthcare accessibility. Similarly, absence related to injuries and poisoning was below the expected level until mid-2022, indicating decreased social mobility. Conclusions: COVID-19 substantially reshaped work absence patterns in Poland, particularly during the early pandemic phase. Pronounced increases and decreases were identified across disease categories. These diverging trends plausibly reflect both the COVID-19’s effects on the development of other conditions and disruptions in healthcare access. These findings highlight the need for disease-specific policy responses to mitigate future health crises and ensure continuity of care during pandemics.

Background Bariatric surgeries, such as laparoscopic sleeve gastrectomy (LSG), not only result in significant weight loss but also improve the inflammatory state in obese patients. This study aimed to investigate the effects of LSG on weight loss and inflammation status in bariatric patients 1-year post-procedure. Methods This prospective cohort study was conducted from September 2022 to May 2024. Fifty obese adults were enrolled for LSG. All patients underwent assessments of body measurements, as well as levels of interleukin-6 (IL-6) and interleukin-10 (IL-10) at baseline, and then at 3 and 12 months post-surgery. Results Twelve months post-surgery, body measurements showed a significant reduction, with a median excess weight loss (%EWL) of 56.8%, indicating the clinical success of the bariatric procedure. %EWL showed a strong correlation with waist circumference (R = − 0.738, p < 0.00001). A logistic regression model indicated that a reduction of just 1 cm in initial waist circumference increases the likelihood of a positive outcome in laparoscopic sleeve gastrectomy by 12%. Moreover, a significant increase was observed for IL-10 (p < 0.0001), simultaneously with a significant decrease in IL-6 (p < 0.0001). Conclusions This study provides valuable evidence supporting the benefits of laparoscopic sleeve gastrectomy for both weight loss and reducing inflammation. Waist circumference emerged as a strong predictor of metabolic success 1-year post-surgery, while increased IL-10 levels signaled positive immunological changes.