UNASSIGNED: Blood counts and biochemical markers are among the most common tests performed in hospitals and most readily accepted by patients, and are widely regarded as reliable biomarkers in the literature. The aim of this study was to assess the causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension (PAH).
UNASSIGNED: A two-sample Mendelian randomization (MR) analysis was performed to assess the causal relationship between blood counts and biochemical indicators with PAH. The genome-wide association study (GWAS) for blood counts and biochemical indicators were obtained from the UK Biobank (UKBB), while the GWAS for PAH were sourced from the FinnGen Biobank. Inverse variance weighting (IVW) was used as the primary analysis method, supplemented by three sensitivity analyses to assess the robustness of the results. And we conducted an observational study using data from National Health and Nutrition Examination Survey (NHANES) 2003-2018 to verify the relationship.
UNASSIGNED: The MR analysis primarily using the IVW method revealed genetic variants of platelet count (OR=2.51, 95% CI 1.56-4.22, P<0.001), platelet crit(OR=1.87, 95% CI1.17-7.65, P=0.022), direct bilirubin (DBIL)(OR=1.71, 95%CI 1.18-2.47,P=0.004), insulin-like growth factor (IGF-1)(OR=0.51, 95% CI 0.27-0.96, P=0.038), Lipoprotein A (Lp(a))(OR=0.66, 95% CI 0.45-0.98, P=0.037) and total bilirubin (TBIL)(OR=0.51, 95% CI 0.27-0.96, P=0.038) were significantly associated with PAH. In NHANES, multivariate logistic regression analyses revealed a significant positive correlation between platelet count and volume and the risk of PAH, and a significant negative correlation between total bilirubin and PAH.
UNASSIGNED: Our study reveals a causal relationship between blood counts, biochemical indicators and pulmonary arterial hypertension. These findings offer novel insights into the etiology and pathological mechanisms of PAH, and emphasizes the important value of these markers as potential targets for the prevention and treatment of PAH.

The existing literature on the relationship of hyperparathyroidism with both blood counts and biochemical indicators primarily comprises observational studies, which have produced inconsistent findings. This study aimed to evaluate the causal relationship between hyperparathyroidism and blood counts and biochemical indicators.
Mendelian randomization (MR) analyses were conducted to investigate the associations between hyperparathyroidism and the identified 55 blood counts and biochemical indicators. The genome-wide association study (GWAS) for hyperparathyroidism data was obtained from FinnGen, while the GWASs for the blood counts and biochemical indicators were sourced from the UK Biobank (UKBB).
The MR analysis using the inverse-variance weighted (IVW) method revealed potential causality between genetically predicted hyperparathyroidism and seven out of 55 blood counts and biochemical indicators. These markers include \"Platelet count\" (Beta = -0.041; 95% CI: -0.066, -0.016; p = 0.001), \"Platelet distribution width (PDW)\" (Beta = 0.031; 95% CI: 0.006, 0.056; p = 0.016), \"Mean platelet volume (MPV)\" (Beta = 0.043; 95% CI: 0.010, 0.076; p = 0.011), \"Vitamin D\" (Beta = -0.038; 95% CI: -0.063, -0.013; p = 0.003), \"Calcium (Ca2+)\" (Beta = 0.266; 95% CI: 0.022, 0.509; p = 0.033), \"Phosphate\" (Beta = -0.114; 95% CI: -0.214, -0.014; p = 0.025), and \"Alkaline phosphatase (ALP)\" (Beta = 0.030; 95% CI: 0.010, 0.049; p = 0.003).
The findings of our study revealed a suggestive causal relationship between hyperparathyroidism and blood cell count as well as biochemical markers. This presents a novel perspective for further investigating the etiology and pathological mechanisms underlying hyperparathyroidism.

Macrophages are large highly motile phagocytic leukocytes that appear early during embryonic development and have been conserved during evolution. The developmental roles of macrophages were first described nearly a century ago, at about the time these cells were being identified as central effectors in phagocytosis and elimination of microbes. Since then, we have made considerable progress in understanding the development of various subsets of macrophages and the diverse roles these cells play in both physiology and disease. This article reviews the phylogeny and the ontogeny of macrophages with a particular focus on the gastrointestinal tract, and the role of these mucosal macrophages in immune surveillance, innate immunity, homeostasis, tissue remodeling, angiogenesis, and repair of damaged tissues. We also discuss the importance of these macrophages in the inflammatory changes in neonatal necrotizing enterocolitis (NEC). This article presents a combination of our own peer-reviewed clinical and preclinical studies, with an extensive review of the literature using the databases PubMed, EMBASE, and Scopus.

UNASSIGNED: The aim of the study was to examine the demographic, clinical features, treatment responses, and outcomes of Hodgkin lymphoma (HL) patients and to investigate the factors affecting their survival.
UNASSIGNED: A retrospective analysis was made of patients diagnosed with HL in our department between 2009 and 2019. Treatment regimen, treatment response, and follow-up times were recorded for all patients. Using these data, complete response (CR) rates, overall survival (OS), and progression-free survival (PFS) were calculated. The effects of parameters on survival were investigated with Cox regression analysis.
UNASSIGNED: Evaluation was made of 60 patients with a median age of 33.5 years [18.0-80.0] and mean follow-up duration of 29.34 ± 23.64 months. Median OS and PFS could not be reached with a mean OS of 85.6 months, and PFS of 71.7 months at the final visit. Only initial leukocyte and neurophil count were determined to have a statistically significant impact on survival (OR = 1.004; P = 0.031 vs OR = 0.996; P = 0.036).
UNASSIGNED: In HL patients, in addition to the many prognostic scoring systems, leukocyte and neutrophil count can be used as an independent prognostic parameter. Patients with higher leukocyte and lower neutrophil counts at the time of diagnosis should be managed more carefully.

Introduction: There are few reports on the effect of radiation alone on blood cells (without chemotherapy). We sought to develop a single source as a reference. Materials and Methods: For over 300 prostate cancer patients treated with radiation alone, we collected the baseline, end-of-treatment and three-month post-therapy complete blood counts (CBC). Results: The hemoglobin dropped by a mean of 1.00 g/dL (−7.1%), with an RBC count of 0.40 × 1012 (−8.6%) at the end of treatment and remained significantly (but <5%) below baseline at follow-up. Significant declines were seen in the levels of the granulocytes (−12.2%; −0.67 × 109), monocytes (−2.2%; −0.05 × 109) and platelets (−12.7%; −30.31 × 109) at the end of treatment, but all returned to baseline on follow-up. The neutrophils and basophils (the primary components of the granulocytes) suffered a significant decline but returned to baseline by the follow-up. The other granulocyte components, the eosinophils, did not decline significantly. The most dramatic decline was in the levels of lymphocytes −62.5% (−1.29 × 109), which were still significantly below baseline (−38%) after two years. Conclusion: The effect of radiation is mostly transitory, with some persistence in hemoglobin/erythrocyte levels (<5%). Lymphocytes are slower to recover, remaining significantly below baseline after two years. It is noteworthy that of the patients whose lymphocytes were in the normal range at the start of therapy, only 14% were below normal at follow-up. Radiation alone has negligible-to-modest long-term effects on blood counts.

Recent advances in sequencing technologies provide unprecedented opportunities for epigenetic biomarker development. Particularly the DNA methylation pattern-which is modified at specific sites in the genome during cellular differentiation, aging, and disease-holds high hopes for a wide variety of diagnostic applications. While many epigenetic biomarkers have been described, only very few of them have so far been successfully translated into clinical practice and almost exclusively in the field of oncology. This discrepancy might be attributed to the different demands of either publishing a new finding or establishing a standardized and approved diagnostic procedure. This is exemplified for epigenetic leukocyte counts and epigenetic age-predictions. To ease later clinical translation, the following hallmarks should already be taken into consideration when designing epigenetic biomarkers: 1) Identification of best genomic regions, 2) pre-analytical processing, 3) accuracy of DNA methylation measurements, 4) identification of confounding parameters, 5) accreditation as diagnostic procedure, 6) standardized data analysis, 7) turnaround time, and 8) costs and customer requirements. While the initial selection of relevant genomic regions is usually performed on genome wide DNA methylation profiles, it might be advantageous to subsequently establish targeted assays that focus on specific genomic regions. Development of an epigenetic biomarker for clinical application is a long and cumbersome process that is only initiated with the identification of an epigenetic signature.

BACKGROUND: Intraoperative radiotherapy (IORT) for breast cancer is used as an upfront boost or as accelerated partial breast irradiation (APBI). To date, no description of blood count changes after IORT are available. Our analysis shows blood count changes in breast cancer patients up to 5 years after IORT ± whole breast radiotherapy (WBRT).
METHODS: IORT was given as APBI in 58 patients (IORT/APBI-group) and as a boost in 198 patients (IORT/WBRT-group). A median dose of 20 Gy was given intraoperatively with low energy X-rays [INTRABEAM (TM) System] and additionally 46 Gy/2 Gy per fraction to the whole breast, if WBRT was added. Blood counts were collected preoperatively, after 90 days and through year 1-5 of follow-up. Dunnett\'s tests were used to calculate changes in blood counts over time. Additionally, platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR) and derived neutrophil-to-lymphocyte ratio (dNLR) were calculated for each time point.
RESULTS: Significantly decreases in the IORT/WBRT-group were seen for erythrocytes, hemoglobin, platelets and leucocytes and an increase for lymphocytes for the total follow-up period. In the IORT/APBI-group significantly decreases were seen for erythrocytes and hemoglobin for the total follow-up period. Regarding changes during follow-up compared to the preoperative value, much more significant changes were seen in the IORT/WBRT-group compared to IORT/APBI-group without any relevant impact of chemotherapy. Regarding PLR-, NLR- and dNLR-values the rate of patients over the range improved over time in both groups.
CONCLUSIONS: IORT/APBI seems to have a smaller effect on blood counts compared to IORT/WBRT. Furthermore, PLR-, NLR- and dNLR-values improved over time, suggesting a positive effect on outcome after IORT in general.

BACKGROUND: Immune checkpoint inhibitors (ICIs) are now a therapeutic standard in advanced non-small cell lung cancer (NSCLC), but strong predictive markers for ICIs efficacy are still lacking. We evaluated machine learning models built on simple clinical and biological data to individually predict response to ICIs.
METHODS: Patients with metastatic NSCLC who received ICI in second line or later were included. We collected clinical and hematological data and studied the association of this data with disease control rate (DCR), progression free survival (PFS) and overall survival (OS). Multiple machine learning (ML) algorithms were assessed for their ability to predict response.
RESULTS: Overall, 298 patients were enrolled. The overall response rate and DCR were 15.3% and 53%, respectively. Median PFS and OS were 3.3 and 11.4 months, respectively. In multivariable analysis, DCR was significantly associated with performance status (PS) and hemoglobin level (OR 0.58, p < 0.0001; OR 1.8, p < 0.001). These variables were also associated with PFS and OS and ranked top in random forest-based feature importance. Neutrophil-to-lymphocyte ratio was also associated with DCR, PFS and OS. The best ML algorithm was a random forest. It could predict DCR with satisfactory efficacy based on these three variables. Ten-fold cross-validated performances were: accuracy 0.68 ± 0.04, sensitivity 0.58 ± 0.08; specificity 0.78 ± 0.06; positive predictive value 0.70 ± 0.08; negative predictive value 0.68 ± 0.06; AUC 0.74 ± 0.03.
CONCLUSIONS: Combination of simple clinical and biological data could accurately predict disease control rate at the individual level.

This study aimed to indicate the influence of infection caused by genotype II African swine fever virus (ASFV)-isolate Pol18_28298_O111, currently circulating in Poland, on blood counts, biochemical parameters, as well as inflammatory and immune responses. Blood and sera collected from 21 domestic pigs infected intranasally with different doses of virulent ASFV were analysed. The infection led to variable changes in blood counts depending on the stage of the disease with a tendency towards leukopenia and thrombocytopenia. The elevated C-reactive protein (CRP) concentrations and microscopic lesions in organs confirmed the development of the inflammation process, which also resulted in an increased level of biochemical markers such as: Aspartate transaminase (AST), creatine kinase (CK), creatinine, and urea. Antibodies could be detected from 9 to 18 days post infection (dpi). Two survivors presented the highest titer of antibodies (>5 log10/mL) with a simultaneous increase in the lymphocyte T (CD3+) percentage-revealed by flow cytometry. Results confirmed a progressive inflammatory process occurring during the ASFV infection, which may lead to multiple organs failure and death of the majority of affected animals.

One of the urgent problems of nursing premature babies is the timely prediction, diagnosis and treatment of anemia, the frequency of which reaches 90%. Of particular importance is the study of reticulocytic blood parameters in deep-premature newborns, since the correct assessment of hemograms is crucial in the management of this category of children. To determine the characteristics of red blood cells and reticulocyte parameters of venous blood hemogram in premature newborns 24-32 weeks of gestation in the dynamics of the neonatal period. 111 newborns were examined at 24-32 weeks of gestation in the early neonatal period (on day 3-7) and at the age of 1 month of life. Along with standard diagnostic procedures, in accordance with current clinical recommendations and standards, 28 parameters of erythrocyte and reticulocyte hemogram parameters were determined for children. Venous blood was examined using an automatic hematological analyzer ADVIA 2120i, Siemens, USA. In deep-premature newborns in the early neonatal period, there is a high activity of erythropoiesis, respectively, the severity of respiratory and metabolic disorders with rejuvenation of reticulocytic subpopulations. Negative values of Delta hemoglobin were found against the background of a decrease in the average amount of hemoglobin in reticulocytes in children 24-27 weeks of gestation, which characterizes the lowest values of iron availability for erythropoiesis in this category of newborns. It is shown that a decrease in reticulocyte counts and normochromia in all examined newborns by the age of one month are accompanied by high levels of immature reticulocyte fraction, while a third of children still have limited iron availability for erythropoiesis.