Heterogeneous Sample Research Articles

Single-cell profiling transcriptomic reveals cellular heterogeneity and cellular crosstalk in breast cancer lymphatic node, bone, and brain metastases

Breast cancer is the most common malignant tumor in the world, and its metastasis is the main cause of death in breast cancer patients. However, the differences between primary breast cancer tissue and lymphatic node, bone, and brain metastases at the single-cell level are not fully understood. We analyzed the microenvironment heterogeneity in samples of primary breast cancer (n = 4), breast cancer lymphatic node metastasis (n = 4), breast cancer brain metastasis (n = 3), and breast cancer bone metastasis (n = 2) using single-cell sequencing data from the GEO database. The malignant epithelial cells were characterized by InferCNV algorithm. The cell-cell communication was analyzed using CellChat package. The biological function of cell subpopulations was analyzed using gene set variation analysis. The expression of STMN1 was analyzed using immunohistochemical staining. The proportion of pCAFs in breast cancer was explored using multispectral immunohistochemical staining. We identified seven cell clusters in primary and metastatic breast cancer (Lymphatic node, brain, and bone metastases) by analyzing single-cell transcriptomic profiles. T-NK and B cells dominated breast cancer with lymphatic node metastasis, whereas fibroblasts were prevalent in brain metastases and primary breast cancer. We identified five T cells (T memory, CD8 + T cells, regulatory T cells, natural killer cells, CD4 + T cells), three B cells (naïve B cells, memory B cells, plasma B cells), and five cancer-associated fibroblasts (CAFs) subpopulations (Smooth muscle cells (SMC), pericyte, antigen-presenting CAFs (apCAFs), proliferative CAFs (pCAFs), and matrix CAFs (mCAFs)). Notably. pCAFs dominated breast cancer with lymphatic node, bone, and brain metastasis. Furthermore, we identified four malignant epithelial cell subpopulations: G0, G1, G2, and G3. The G2 cell population exhibited strong invasion ability, it can differentiate into G3 with strong proliferative ability and proliferation-related G1 cell population after metastasis. Cell-cell communication demonstrated an interaction between pCAFs and metastasis-associated malignant epithelial cells. Finally, we discovered that in advanced breast cancer, the proportion of pCAF increased and was associated with a poor prognosis of breast cancer. This study elucidated the potential cellular origins and drivers of breast cancer metastases to lymphatic nodes, brain, and bone, utilizing single-cell transcriptomic profiles. Furthermore, it demonstrated that increased pCAFs were associated with advanced breast cancer and a poor prognosis.

Evidence of DNA methylation heterogeneity and epipolymorphism in kidney cancer tissue samples.

Clear cell renal cell carcinoma (ccRCC) is characterised by significant genetic heterogeneity, which has diagnostic and prognostic implications. Very limited evidence is available regarding DNA methylation heterogeneity. We therefore generate sequence level DNA methylation data on 136 multi-region tumour and normal kidney tissue from 18 ccRCC patients, along with matched whole exome sequencing (85 samples) and gene expression (47 samples) data on a subset of samples. We perform a comprehensive systematic analysis of heterogeneity between patients, within a patient and within a sample. We demonstrate that bulk methylation data may be deconvoluted into cell-type-specific latent methylation components (LMCs), and that LMC1, which is likely to represent T cells, is associated with prognostic parameters. Differential epipolymorphism was noted between ccRCC and normal tissue in the promoter region of genes which are known to be associated with kidney cancer. This was externally validated in an independent cohort of 71 ccRCC and normal kidney tissues. Differential epipolymorphism in the gene promoter was a predictor of gene expression, after adjusting for average methylation. This represents the first evaluation of epipolymorphism in ccRCC and suggests that gains and losses in methylation disorder may have a functional relevance, gleaning important information on tumourigenesis.

Heterogeneity in Seed Samples from Vineyards and Natural Habitats Along the Eurasian Vitis vinifera Range: Implications for Domestication and Hybridization

By exploring seed samples from vineyards and natural habitats across the Eurasian range of Vitis vinifera, our analysis revealed substantial morphological variation within populations. Through the analysis of domestication index values, probabilities, and entropy, we assessed seed diversity. Samples with high domestication probability values—predominantly from vineyards—exhibited low heterogeneity and entropy, with similar patterns observed in natural habitats, suggesting the presence of feral vines. In parallel, seeds with low domestication index values, found mainly in natural habitats, also displayed low entropy and are likely associated with Vitis sylvestris or other wild Vitaceae species. Intermediate domestication values pointed to hybrid swarms, highlighting the crucial role of hybridization in the development of modern grapevine cultivars. The study identified mixed populations across the Iberian Peninsula, Italy, and the South Caucasus, which act as significant gene reservoirs. A domestication gradient is evident, with higher domestication rates in the South Caucasus compared to Western Europe and East Asia. The results demonstrate the significance of these mixed populations as repositories of genetic diversity, underscoring their conservation value, particularly considering the negative impact of habitat alterations, especially in riparian forests due to major public works.

Quality attributes of test cases and test suites – importance & challenges from practitioners’ perspectives

The quality of the test suites and the constituent test cases significantly impacts confidence in software testing. While research has identified several quality attributes of test cases and test suites, there is a need for a better understanding of their relative importance in practice. We investigate practitioners’ perceptions regarding the relative importance of quality attributes of test cases and test suites and the challenges that they face in ensuring the perceived important quality attributes. To capture the practitioners’ perceptions, we conducted an industrial survey using a questionnaire based on the quality attributes identified in an extensive literature review. We used a sampling strategy that leverages LinkedIn to draw a large and heterogeneous sample of professionals with experience in software testing. We collected 354 responses from practitioners with a wide range of experience (from less than one year to 42 years of experience). We found that the majority of practitioners rated Fault Detection, Usability, Maintainability, Reliability, and Coverage to be the most important quality attributes. Resource Efficiency, Reusability, and Simplicity received the most divergent opinions, which, according to our analysis, depend on the software-testing contexts. Also, we identified common challenges that apply to the important attributes, namely inadequate definition, lack of useful metrics, lack of an established review process, and lack of external support. The findings point out where practitioners actually need further support with respect to achieving high-quality test cases and test suites under different software testing contexts. Hence, the findings can serve as a guideline for academic researchers when looking for research directions on the topic. Furthermore, the findings can be used to encourage companies to provide more support to practitioners to achieve high-quality test cases and test suites.

Associations between childhood trauma and epistemic trust, attachment, mentalizing, and symptoms of borderline personality disorder.

Introduction The construct of epistemic trust (ET) has gained wide acceptance and support in the field, although there is little empirical evidence to substantiate the theoretical assumed model. Studies of the assessment of ET were conducted in community samples only and the mediating role of attachment and mentalizing in addition to ET was not investigated. This study examines the theoretical assumed relationships between ET and attachment and mentalizing as well as the mediating role of attachment, mentalizing and ET in the association between childhood adversity and borderline personality disorder (BPD) in a heterogeneous sample containing also patients. Methods The associations between ET and attachment, mentalizing, childhood maltreatment and BPD were explored in a sample of 245 participants, including subjects from the community as well as patients diagnosed with anxiety and personality disorders from two clinical samples. Multiple mediation analysis was performed to explore the mediating role of attachment (ECR-R), mentalizing (RFQ) and ET within the relationship between childhood trauma (CTQ-SF) and BPD (MSI-BPD). Results Strong relationships between ET and attachment and mentalizing were found indicating that lower degrees of ET are associated with insecure attachment and lower reflective functioning. Attachment, mentalizing, and ET together accounted for 75% of the mediation between childhood adversity and BPD. Hypomentalizing and anxious attachment accounted for the largest share of the mediation. Conclusion Our findings provide preliminary evidence for the theoretical supposed model of ET and suggest relevance of ET in the mediation between childhood adversity and PDs, although the role of ET seems smaller than assumed by recent theories.

Impact of age-related changes in buccal epithelial cells on pediatric epigenetic biomarker research

Cheek swabs, heterogeneous samples consisting primarily of buccal epithelial cells, are widely used in pediatric DNA methylation studies and biomarker creation. However, the decrease in buccal proportion with age in adults remains unexamined in childhood. We analyzed cheek swabs from 4626 typically developing children 2-months to 20-years-old. Estimated buccal proportion declined throughout childhood with both increasing chronological and predicted epigenetic age. However, buccal proportion did not associate with age throughout adolescence. Variability in buccal proportion increased with age through the entire developmental range. These trends held inversely true for neutrophil proportions. Correcting for buccal proportion attenuated the weak association with PedBE age acceleration to non-significance during initial estimation. Notably, correcting for buccal proportion attenuated the association of PedBE age acceleration with obsessive-compulsive disorder and strengthened the association with diurnal cortisol slope. Thus, the age-related change in children’s oral cells is a crucial consideration for cell type-sensitive research.

Distinct clinical phenotypes in gastric pathologies: a cluster analysis of demographic and biomarker profiles in a diverse patient population.

Understanding the heterogeneity of a population at risk is an important step in the early detection of gastric cancer. We aimed to cluster demographic, hematological, and biochemical markers of gastric cancer in a heterogeneous sample of patients. Data of 695 adult patients (50.0% women) who were diagnosed with histologically confirmed gastric cancer, benign gastric disease, or identified as healthy individuals (December 2018 to August 2019, Hangzhou, China) were analyzed. We conducted hierarchical clustering using a factorial analysis of mixed data. To assess the clustering scheme, we also developed a machine-learning classification model using the Extreme Gradient Boosting algorithm and subsequently ranked the variables for differentiating patient phenotypes. Three clusters were identified using patient characteristics. The classification model showed high performance (multi-class AUC = 0.921) for recognizing the clusters. The top five important variables in differentiating the clusters were sex, hemoglobin, albumin, creatinine, and high-density lipoprotein (all ANOVA P <0.001) in decreasing order of importance. The prevalence of gastric cancer in clusters I, II, and III was 95.8%, 53.8%, and 34%, respectively [χ2(2) = 164.050, P <0.001]. Cluster I (N = 167) predominantly had an inflammatory profile, Cluster II (N = 240) showed metabolic disturbances, and Cluster III (N = 288) presented a relatively favorable metabolic and inflammatory profile. There were distinct clinical phenotypes in the population, each with varying prevalence of gastric cancer. A combination of routine clinical data outperformed carbohydrate or carcinoembryonic antigens in capturing the heterogeneity of the population regarding gastric pathologies.

Subjective cognitive functioning in patients with cancer: A network approach

Purpose The current study aimed to (1) examine the sociodemographic, clinical and psychological factors related to subjective cognitive functioning (SCF); (2) analyze the complex mutual interconnections between SCFs; and (3) address patients’ perspectives on SCF and supportive care. Method A heterogeneous sample of oncological patients (N = 566) was recruited. Items inquiring about the senses, attention, memory, spatial functions, decision-making and speech were administered. A network of subjectively perceived changes in cognitive functions was estimated while three open-ended questions addressed patients’ perspectives on SCF. Results Within the network, deficits in spatial perception, attention focus and problem-solving ability had the highest strength index while the deficits related to the senses were the least influential. Conclusion The findings indicate that psychological-based interventions focused on higher cognitive functions could improve patients’ quality of life. The presence of supportive care and available information could strengthen SCF intervention and prevention for patients with cancer.

Collection and Processing of Samples for Next-Generation Sequencing to Study the Gut Microbiome.

16S rRNA gene sequencing is commonly used for identification and quantitation of microorganisms in complex biological mixtures, such as the human gut microbiome. The 16S rRNA gene is an excellent target gene for sequencing DNA in a heterogenous sample, as it is a highly conserved part of the transcriptional machinery. Universal PCR primers are used to amplify the conserved regions of 16S. Thus, it is possible to amplify the gene in a wide range of different microorganisms from a single sample. As the 16S rRNA gene consists of both conserved and variable regions, sequencing of the variable regions can be used to differentiate between different bacterial species.

Impact of sample heterogeneity on the evaluation of uncertainty from sampling and analytical steps in pharmaceutical analysis.

Measurement uncertainty is a critical factor in the reliability of pharmaceutical analyses, since it directly affects batch acceptance and regulatory compliance. While analytical uncertainty has been extensively studied, uncertainty arising from sampling remains less explored. This study aims to address this gap by evaluating the contributions of sampling and analytical uncertainties to the overall uncertainty for acetaminophen tablets and oral solution. The duplicate method and analysis of variance (ANOVA) were used to assess the uncertainty from sampling and analytical steps. Ten different batches of acetaminophen tablets and oral solution were analyzed, and the combined uncertainties were calculated. For tablets, uncertainty from sampling accounted for 89 % of the overall uncertainty, highlighting the critical role of sample heterogeneity. In contrast, for oral solutions, analytical uncertainty dominated (90 % of the total), reflecting the homogeneous nature of the solution. Considering the uncertainty from sampling can be important to ensure a reduced risk of false acceptance or false rejection, particularly for heterogeneous dosage forms. In conclusion, incorporating sampling uncertainty into uncertainty budgets can significantly improve decision-making in pharmaceutical quality control.

Advances and challenges in preparing membrane proteins for native mass spectrometry.

Native mass spectrometry (nMS) is becoming a crucial tool for analyzing membrane proteins (MPs), yet challenges remain in solubilizing and stabilizing their native conformations while resolving and characterizing the heterogeneity introduced by post-translational modifications and ligand binding. This review highlights recent advancements and persistent challenges in preparing MPs for nMS. Optimizing detergents and additives can significantly reduce sample heterogeneity and surface charge, enhancing MP signal quality and structural preservation in nMS. A strategic workflow incorporating affinity capture, stabilization agents, and size-exclusion chromatography to remove unfolded species demonstrates success in improving nMS characterization. Continued development of customized detergents and reagents tailored for specific MPs may further minimize heterogeneity and boost signals. Instrumental advances are also needed to elucidate more dynamically complex and labile MPs. Effective sample preparation workflows may provide insights into MP structures, dynamics, and interactions underpinning membrane biology. With ongoing methodological innovation, nMS shows promise to complement biophysical studies and facilitate drug discovery targeting this clinically important yet technically demanding protein class.

Perceptions of dental professionals on the use of silver diamine fluoride with or without light-curing

BackgroundAccording to anecdotal reports, SDF’s ability to arrest caries can be enhanced by light-curing in a clinical setting. The purpose of the present study was to explore the dental professionals’ perceptions of using SDF and to understand the barriers and enabling factors to using SDF with and without light-curing.MethodsA qualitative study was conducted with dental professionals who had experience with using SDF with and without light-curing. A purposive heterogeneous and convenience sampling approach was applied to ensure the inclusion of participants with different employment and experience levels. Eighteen participants (dental students (undergraduate and postgraduate), dental personnel (practicing dentists and dental hygienists), and academics) with ages ranging from 22 to 53 years old participated in the study. The data were collected through a semi-structured open-ended questionnaire. Manual line-by-line coding and content analysis methods were used for data analysis.ResultsMost participants indicated a preference for light-curing, citing perceived benefits, such as quicker treatment, convenience, better visibility, prevention of saliva contamination, and ensuring thorough SDF coverage. However, some participants voiced concerns, based either on existing practice guidelines or due to insufficient evidence regarding the efficacy of light-curing. Additionally, one participant proposed a hybrid approach based on tooth location, suggesting avoiding using light-curing on anterior teeth, while utilizing it on posterior teeth.ConclusionThe participants’ responses indicated that the use of SDF with and without light-curing each has its merits. Using SDF with light-curing emerged as the preferred method due to perceived benefits. e.g., quicker treatment, better moisture control. However, concerns regarding existing guidelines and the lack of robust evidence for its efficacy were also identified. This study highlights the need for additional research to address the knowledge gaps and provide stronger evidence to support the use of light-curing after SDF application.

Linguistic escapism and symbolic value of signs of (good) times

Our research describes the linguistic landscape of three Croatian towns where we compare the signs on coffee shops and bars in reference to the symbolic function of foreign languages used on them, especially when compared to the mostly informative value of signs in Croatian. The sampling method applied was Cook’s and Campbell’s Diversity or Heterogeneity Sampling (1979:75–77) where the survey areas are illustrative, and not representative examples of the linguistic landscape. The results indicate that the higher percentage of signs in a foreign language, predominantly English, may be seen as an instantiation of processes related to economic and cultural globalization in a multilingual world (Gorter, 2013) when foreign language signs imply prestige and positive connotations, as confirmed by the sample of interviews with informants, coffee shop owners and patrons alike. In areas burdened by the politically charged atmosphere foreign language signs are seen as a form of escapism from the implications the use of any of the minority or majority language signs may cause.

Combining Fourier Transform Ion Mobility with Charge Detection Mass Spectrometry for the Analysis of Multimeric Protein Complexes.

Charge detection mass spectrometry (CDMS) allows direct mass measurement of heterogeneous samples by simultaneously determining the charge state and the mass-to-charge ratio (m/z) of individual ions, unlike conventional MS methods that use large ensembles of ions. CDMS typically requires long acquisition times and the collection of thousands of spectra, each containing tens to hundreds of ions, to generate sufficient ion statistics, making it difficult to interface with the time scales of online separation techniques such as ion mobility. Here, we demonstrate the application of Fourier transform multiplexing and drift tube ion mobility joined with Orbitrap-based CDMS for the analysis of multimeric protein complexes. Stepped frequency modulation was utilized to enable unambiguous frequency assignment during mobility sweeps and allow spectral averaging, which improves the accuracy and signal-to-noise of ion mobility spectra and CDMS measurements. Fourier transformation of the signal reveals the arrival times and collision cross sections of ions while simultaneously collecting charge information for thousands of individual ions. Combining Fourier transform multiplexing ion mobility and CDMS provides insight into each ion's size and mass while showcasing a potential solution to the duty cycle mismatch of online separation techniques in the single ion regime.

Judged by your neighbors: Brain structural normativity profiles for large and heterogeneous samples.

The detection of norm deviations is fundamental to clinical decision making and impacts our ability to diagnose and treat diseases effectively. Current normative modeling approaches rely on generic comparisons and quantify deviations in relation to the population average. However, generic models interpolate subtle nuances and risk the loss of critical information, thereby compromising effective personalization of health care strategies. To acknowledge the substantial heterogeneity among patients and support the paradigm shift of precision medicine, we introduce Nearest Neighbor Normativity (N3), which is a strategy to refine normativity evaluations in diverse and heterogeneous clinical study populations. We address current methodological shortcomings by accommodating several equally normative population prototypes, comparing individuals from multiple perspectives and designing specifically tailored control groups. Applied to brain structure in 36,896 individuals, the N3 framework provides empirical evidence for its utility and significantly outperforms traditional methods in the detection of pathological alterations. Our results underscore N3's potential for individual assessments in medical practice, where normativity is not merely a benchmark, but a dynamic tool that adapts to the intricacies of personalized patient care.

How does global economic policy uncertainty affect Islamic bank performance? An exploration from heterogeneous sample

This study investigates the impact of Global Economic Policy Uncertainty (GEPU) on the performance of Islamic banking, as measured by Non-Performing Financing (NPF) and Return on Assets (ROA). Utilizing quarterly data from 2014 to 2022 across three countries – Indonesia, Nigeria, and the UAE – and employing the Autoregressive Distributed Lag (ARDL) model with a Mean Group (MG) estimator, the findings indicate that GEPU does not significantly impact NPF in either the short or long term. In the short term, GEPU has the potential to reduce ROA; however, in the long term, it positively influences the profitability of Islamic banks. Specifically, in Indonesia, the results suggest an initial increase in NPF and a decrease in ROA in the short term. Conversely, in the long term, this trend reverses, with NPF declining and ROA increasing. In Nigeria, although GEPU may elevate NPF in the short term, this negative effect dissipates over time, with profitability remaining unaffected in both timeframes. In the UAE, NPF is stable in the short term, but there are indications of a long-term increase in NPF, while profitability remains stable across both short and long terms.

Artificial intelligence-based tissue segmentation and cell identification in multiplex-stained histological endometriosis sections.

How can we best achieve tissue segmentation and cell counting of multichannel-stained endometriosis sections to understand tissue composition? A combination of a machine learning-based tissue analysis software for tissue segmentation and a deep learning-based algorithm for segmentation-independent cell identification shows strong performance on the automated histological analysis of endometriosis sections. Endometriosis is characterized by the complex interplay of various cell types and exhibits great variation between patients and endometriosis subtypes. Endometriosis tissue samples of eight patients of different subtypes were obtained during surgery. Endometriosis tissue was formalin-fixed and paraffin-embedded before sectioning and staining by (multiplex) immunohistochemistry. A 6-plex immunofluorescence panel in combination with a nuclear stain was established following a standardized protocol. This panel enabled the distinction of different tissue structures and dividing cells. Artificial intelligence-based tissue and cell phenotyping were employed to automatically segment the various tissue structures and extract quantitative features. An endometriosis-specific multiplex panel comprised of PanCK, CD10, α-SMA, calretinin, CD45, Ki67, and DAPI enabled the distinction of tissue structures in endometriosis. Whereas a machine learning approach enabled a reliable segmentation of tissue substructure, for cell identification, the segmentation-free deep learning-based algorithm was superior. The present analysis was conducted on a limited number of samples for method establishment. For further refinement, quantification of collagen-rich cell-free areas should be included which could further enhance the assessment of the extent of fibrotic changes. Moreover, the method should be applied to a larger number of samples to delineate subtype-specific differences. We demonstrate the great potential of combining multiplex staining and cell phenotyping for endometriosis research. The optimization procedure of the multiplex panel was transferred from a cancer-related project, demonstrating the robustness of the procedure beyond the cancer context. This panel can be employed for larger batch analyses. Furthermore, we demonstrate that the deep learning-based approach is capable of performing cell phenotyping on tissue types that were not part of the training set underlining the potential of the method for heterogenous endometriosis samples. All funding was provided through departmental funds. The authors declare no competing interests. N/A.

Proteomic profiling of kidney biopsies in nephrotic syndrome

Background Minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) are patterns of kidney injury observed in the filtering units of the kidney known as glomeruli. These histological patterns are seen in kidney biopsies from individuals with idiopathic nephrotic syndrome (iNS), which occurs in both children and adults. However, there is some indication that MCD and FSGS are within the same phenotypic spectrum. Methods From the NURTuRE cohort of individuals with NS, we performed laser microdissection and mass spectrometry analysis of kidney biopsy samples to identify proteomic patterns of disease. 56 individuals with iNS segregated by histological pattern (37 MCD and 19 FSGS) across three age groups: early childhood (0–6 years), late childhood (6–18 years) and adult (&gt;18 years). Results We found no distinct clustering of proteomic profiles between MCD and FSGS, but identified global differences in glomerular cell and extracellular matrix composition related to both histological pattern and age. The proteomic data are available via ProteomeXchange with identifier PXD053362. Conclusions The lack of distinct clustering between MCD and FSGS in our study suggests shared biological processes between these injury patterns of iNS, supporting the hypothesis that they are part of the same disease spectrum. The global differences observed in glomerular cell and extracellular matrix composition suggest involvement of diverse biogeological processes as different patterns of iNS manifests in different age groups. This study also demonstrates the feasibility of pooling bioresources, central processing of heterogeneous tissue samples, and developing laser-microdissection and proteomic analysis methodology.

GJFocuser: a Gaussian difference and joint learning-based autofocus method for whole slide imaging.

Whole slide imaging (WSI) provides tissue visualization at the cellular level, thereby enhancing the effectiveness of computer-aided diagnostic systems. High-precision autofocusing methods are essential for ensuring the quality of WSI. However, the accuracy of existing autofocusing techniques can be notably affected by variations in staining and sample heterogeneity, particularly without the addition of extra hardware. This study proposes a robust autofocusing method based on the difference between Gaussians (DoG) and joint learning. The DoG emphasizes image edge information that is closely related to focal distance, thereby mitigating the influence of staining variations. The joint learning framework constrains the network's sensitivity to defocus distance, effectively addressing the impact of the differences in sample morphology. We first conduct comparative experiments on public datasets against state-of-the-art methods, with results indicating that our approach achieves cutting-edge performance. Subsequently, we apply this method in a low-cost digital microscopy system, showcasing its effectiveness and versatility in practical scenarios.

Excess Relative Risk of Mortality from Diseases of the Circulation System after Irradiation. Report 2. Combined Data Analysis for Nuclear Workers

In the second part of the review on estimates of excess relative risks (ERR) per 1 Gy/Sv for mortality from diseases of the circulatory system (ICD-9: 390–459; ICD-10: I00–I99) after irradiation, a combined analysis and meta-analysis was carried out for nuclear industry workers of various countries. The completeness of the sample at the end of 2021 appeared to be exhaustive. The combined analysis of the data consisted in assessing the average for the sample after eliminating outliers from it; ERR per 1 Gy/Sv was 0.20 (95% CI: 0.11; 0.30). The meta-analysis was performed on the full sample, without removing outliers. Some heterogeneity was identified, so a Random effect model was used for the meta-analysis, and the ERR per 1 Gy/Sv was 0.11 (95% CI: 0.01; 0.22). The mean value of ERR per 1 Gy/Sv obtained here only for nuclear industry workers, as well as the result of the meta-analysis, did not differ much from the data of M.P. Little and co-workers (2010–2016) for heterogeneous samples from different populations. At the same time, the data for ‘Mayak’ PA on mortality from circulatory pathologies in general, and not for their individual types, indicate lower risks for external exposure (Azizova TV et al., 2018): ERR per 1 Gy/Sv was 0.04 (95% CI: –0.00; 0.09). All listed risks from the point of view of classical epidemiology, when using the common Monson scale for relative risks (RR), should be considered either ignorable (RR = = 1.0–1.2) or weak (RR = 1.2–1.5). An estimation of the absolute risk of mortality from circulatory pathologies for a hypothetical group of 100,000 nuclear workers who each accumulated a dose of 1 Gy, based on data on the baseline mortality of men from these pathologies for the United States, showed an increase of 1400 deaths over 20 years of employment. However, recalculation for the real average dose accumulated by workers in different countries (31.1 mSv; Koterov A.N. et al., 2021) revealed an insignificant increase in mortality at 0.6% of the baseline level, which risk cannot be taken into account for such multifactorial pathologies. The results obtained in the second part of the presented study: a) reinforce the conclusion made in Report 1 about the advisability of adhering to the dose threshold of 0.5 Gy for circulatory pathologies mortality established by UNSCEAR, ICRP, NCRP, BEIR, etc.; b) they indicate very low, negligible risks of mortality from circulatory pathologies attributed to the radiation factor for nuclear industry workers in recent decades and for most of those even in the previous period; c) they show that for the real activity and health protection of the majority of workers in the nuclear industry, the determination/calculation of the radiation risks of mortality from circulatory pathologies is of an exclusively theoretical nature. These conclusions are important, among other things, for expert advices on establishing the causality of occupational pathologies in nuclear industry workers.