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BioRxiv : the Preprint Server For... Apr 2024Hematopoietic dysfunction has been associated with a reduction in the number of active precursors. However, precursor quantification at homeostasis and under diseased...
Hematopoietic dysfunction has been associated with a reduction in the number of active precursors. However, precursor quantification at homeostasis and under diseased conditions is constrained by the scarcity of available methods. To address this issue, we optimized a method for quantifying a wide range of hematopoietic precursors. Assuming the random induction of a stable label in precursors following a binomial distribution, the estimation depends on the inverse correlation between precursor numbers and the variance of precursor labeling among independent samples. Experimentally validated to cover the full dynamic range of hematopoietic precursors in mice (1 to 10), we utilized this approach to demonstrate that thousands of precursors, which emerge after modest expansion during fetal-to-adult transition, contribute to native and perturbed hematopoiesis. We further estimated the number of precursors in a mouse model of Fanconi Anemia, showcasing how repopulation deficits can be segregated into autologous (cell proliferation) and non-autologous causes (lack of precursor). Our results support an accessible and reliable approach for precursor quantification, emphasizing the contemporary perspective that native hematopoiesis is highly polyclonal.
PubMed: 38617223
DOI: 10.1101/2024.04.02.587737 -
Heliyon Apr 2024Cervical cancer remains the fourth most common female malignancy with increasing newly cases around the world. It is of clinical value to precisely evaluate whether...
BACKGROUND
Cervical cancer remains the fourth most common female malignancy with increasing newly cases around the world. It is of clinical value to precisely evaluate whether false negative nodal existed and develop a nodal staging model in cervical cancer.
MATERIALS AND METHODS
Clinical data of cervical cancer patients was retrieved from the Surveillance, Epidemiology, and End Results database. Probability of missing nodal disease and nodal staging score (NSS) was computed to assess the nodal status of each individual.Prognostic value of NSS was assessed.
RESULTS
A total of 9056 individuals were in this study, with 5115 squamous cell carcinoma, 2791 adenocarcinoma, 512 adenosquamous carcinoma, and 638 other type individuals. A beta-binomial model was used to compute the probability of nodal disease in four histological types, respectively. False negative probability drastically decreased as more nodes examined. To reach 0.05 of false negative probability, it required at least 17 lymph nodes in squamous cell carcinoma patients,18 in adenocarcinoma, 12 in adenosquamous carcinoma patients and 14 in other types. To reach 0.95 of NSS, it took 10 lymph nodes in squamous cell carcinoma, 6 in adenocarcinoma, 10 in adenosquamous carcinoma and 7 in other types. Significant prognostic values of NSS quartiles subsets were found in all four histological sets.
CONCLUSION
NSS tool enables adequate nodal staging of cervical cancer with significant prognostic value. Exact number of lymph nodes required for surgery in cervical cancer is specified based on histologic type.
PubMed: 38596019
DOI: 10.1016/j.heliyon.2024.e26116 -
PLoS Neglected Tropical Diseases Apr 2024Schistosomiasis and fasciolosis are snail-borne diseases of great medical and veterinary health importance. The World Health Organization recommends complementing drug...
INTRODUCTION
Schistosomiasis and fasciolosis are snail-borne diseases of great medical and veterinary health importance. The World Health Organization recommends complementing drug treatment with snail control and community involvement for disease elimination, but there is a general lack of snail experts and hence snail distribution data. Therefore, we adopted a citizen science approach and involved citizens in the monitoring of medically and veterinary important snail taxa.
MATERIALS AND METHODS
Snail data was collected weekly by 25 trained citizen scientists (CSs) at 76 sites around southern Lake Albert (Uganda) for 20 months. At each site, snails were searched for 30 minutes, sorted, target snail hosts identified to genus level, counted and data submitted through a smartphone application. The quality of this data was assessed by comparing it to monthly data collected by an 'expert' malacologist using the same sampling protocol. Generalised binomial logistic and linear mixed-effects models were used to analyse the variables for agreement between the CSs and expert.
FINDINGS
The binary agreement in presence/absence of Biomphalaria, Bulinus and Radix snails reported by the expert and CSs ranged between 70% and 86% (900 reports) with an average of 17% false negatives (sites wrongly defined as snail-free). The agreement for Biomphalaria and Radix increased with snail abundance, and false negatives decreased when the number of snails collected by citizens was aggregated per month. Site type significantly predicted binary agreement, which was lowest at lake sites (55%) and highest at spring sites (99%) with variations across genera. Similar temporal trends in snail abundance were recorded despite the expert reporting higher abundance. However, the relative abundance was consistent across site types. The match between the sites with highest Biomphalaria spp. abundance identified by CSs and expert was consistently high (~84.1%) and increased over time.
CONCLUSIONS AND RECOMMENDATIONS
Our results demonstrate the potential of citizen science to map putative schistosomiasis transmission sites. We therefore argue that this inclusive, powerful and cost-effective approach can be more sustainable than top-down monitoring and intervention campaigns.
Topics: Animals; Humans; Schistosomiasis; Biomphalaria; Bulinus; Seasons; Disease Vectors
PubMed: 38574112
DOI: 10.1371/journal.pntd.0012062 -
Scandinavian Journal of Public Health Apr 2024To examine how a positive change in one to three psychosocial stressors (job demands, job rewards, and workplace social capital) influenced psychological distress.
AIMS
To examine how a positive change in one to three psychosocial stressors (job demands, job rewards, and workplace social capital) influenced psychological distress.
METHODS
The analysis included 3605 Finnish health and social services workers who completed surveys in 2019, 2020 and 2021. A logistic regression model was used to estimate the propensity score of experiencing a positive change in one to three psychosocial stressors between 2019 and 2020. We balanced the baseline characteristics with propensity scoring. A generalised linear model with a binomial distribution and a log link function was used to compare the quasi-intervention and quasi-control groups for the risk of psychological distress in 2021.
RESULTS
Among the total sample, neither improving a single stressor nor two or three stressors affected psychological distress. However, among employees younger than 50 years, improving two or three psychosocial stressors in 2019-2020 decreased the risk of moderate to severe psychological distress in 2021 by 41% (risk ratio 0.59, 95% confidence interval 0.36-0.96). Among employees aged 50 years or older, improving job rewards lowered the risk of mild to severe psychological distress by 23% (risk ratio 0.77, 95% confidence interval 0.62-0.96).
CONCLUSIONS
PubMed: 38570315
DOI: 10.1177/14034948241242160 -
BioRxiv : the Preprint Server For... Mar 2024Tumors are comprised of a mixture of distinct cell populations that differ in terms of genetic makeup and function. Such heterogeneity plays a role in the development of...
Tumors are comprised of a mixture of distinct cell populations that differ in terms of genetic makeup and function. Such heterogeneity plays a role in the development of drug resistance and the ineffectiveness of targeted cancer therapies. Insight into this complexity can be obtained through the construction of a phylogenetic tree, which illustrates the evolutionary lineage of tumor cells as they acquire mutations over time. We propose Canopy2, a Bayesian framework that uses single nucleotide variants derived from bulk DNA and single-cell RNA sequencing to infer tumor phylogeny and conduct mutational profiling of tumor subpopulations. Canopy2 uses Markov chain Monte Carlo methods to sample from a joint probability distribution involving a mixture of binomial and beta-binomial distributions, specifically chosen to account for the sparsity and stochasticity of the single-cell data. Canopy2 demystifies the sources of zeros in the single-cell data and separates zeros categorized as non-cancerous (cells without mutations), stochastic (mutations not expressed due to bursting), and technical (expressed mutations not picked up by sequencing). Simulations demonstrate that Canopy2 consistently outperforms competing methods and reconstructs the clonal tree with high fidelity, even in situations involving low sequencing depth, poor single-cell yield, and highly-advanced and polyclonal tumors. We further assess the performance of Canopy2 through application to breast cancer and glioblastoma data, benchmarking against existing methods. Canopy2 is an open-source R package available at https://github.com/annweideman/canopy2.
PubMed: 38562795
DOI: 10.1101/2024.03.18.585595 -
Advances in Radiation Oncology May 2024In real-time image-gated spot-scanning proton therapy (RGPT), the dose distribution is distorted by gold fiducial markers placed in the prostate. Distortion can be...
PURPOSE
In real-time image-gated spot-scanning proton therapy (RGPT), the dose distribution is distorted by gold fiducial markers placed in the prostate. Distortion can be suppressed by using small markers and more than 2 fields, but additional fields may increase the dose to organs at risk. Therefore, we conducted a prospective study to evaluate the safety and short-term clinical outcome of RGPT for prostate cancer.
METHODS AND MATERIALS
Based on the previously reported frequency of early adverse events (AE) and the noninferiority margin of 10%, the required number of cases was calculated to be 43 using the one-sample binomial test by the Southwest Oncology Group statistical tools with the one-sided significance level of 2.5% and the power 80%. Patients with localized prostate cancer were enrolled and 3 to 4 pure gold fiducial markers of 1.5-mm diameter were inserted in the prostate. The prescribed dose was 70 Gy(relative biologic effectiveness) in 30 fractions, and treatment was performed with 3 fields from the left, right, and the back, or 4 fields from either side of slightly anterior and posterior oblique fields. The primary endpoint was the frequency of early AE (≥grade 2) and the secondary endpoint was the biochemical relapse-free survival rate and the frequency of late AE.
RESULTS
Forty-five cases were enrolled between 2015 and 2017, and all patients completed the treatment protocol. The median follow-up period was 63.0 months. The frequency of early AE (≥grade 2) was observed in 4 cases (8.9%), therefore the noninferiority was verified. The overall 5-year biochemical relapse-free survival rate was 88.9%. As late AE, grade 2 rectal bleeding was observed in 8 cases (17.8%).
CONCLUSIONS
The RGPT for prostate cancer with 1.5-mm markers and 3- or 4- fields was as safe as conventional proton therapy in early AE, and its efficacy was comparable with previous studies.
PubMed: 38560429
DOI: 10.1016/j.adro.2024.101464 -
BMC Medical Research Methodology Mar 2024Diabetes is one of the top four non-communicable diseases that cause death and illness to many people around the world. This study aims to use an efficient count data...
BACKGROUND
Diabetes is one of the top four non-communicable diseases that cause death and illness to many people around the world. This study aims to use an efficient count data model to estimate socio-environmental factors associated with diabetes incidences in Tanzania mainland, addressing lack of evidence on the efficient count data model for estimating factors associated with disease incidences disparities.
METHODS
This study analyzed diabetes counts in 184 Tanzania mainland councils collected in 2020. The study applied generalized Poisson, negative binomial, and Poisson count data models and evaluated their adequacy using information criteria and Pearson chi-square values.
RESULTS
The data were over-dispersed, as evidenced by the mean and variance values and the positively skewed histograms. The results revealed uneven distribution of diabetes incidence across geographical locations, with northern and urban councils having more cases. Factors like population, GDP, and hospital numbers were associated with diabetes counts. The GP model performed better than NB and Poisson models.
CONCLUSION
The occurrence of diabetes can be attributed to geographical locations. To address this public health issue, environmental interventions can be implemented. Additionally, the generalized Poisson model is an effective tool for analyzing health information system count data across different population subgroups.
Topics: Humans; Models, Statistical; Incidence; Tanzania; Poisson Distribution; Diabetes Mellitus
PubMed: 38532325
DOI: 10.1186/s12874-024-02166-w -
Translational Vision Science &... Mar 2024In the United States, the ZIP Code has long been used to collect geospatial data revealing disparities in social determinants of health. This cross-sectional study...
PURPOSE
In the United States, the ZIP Code has long been used to collect geospatial data revealing disparities in social determinants of health. This cross-sectional study examines the distribution of eye care access in association with local socioeconomic factors at a ZIP Code level.
METHODS
Data from the 2020 Centers of Medicare and Medicaid Services and American Community Survey were used to examine locations of 47,949 providers (17,631 ophthalmologists and 30,318 optometrists) and corresponding local socioeconomic variables (education, employment, and income). Multivariable zero-inflated negative binomial regression was used to model eye care provider count per capita in each ZIP Code area with socioeconomic factors as independent covariates.
RESULTS
For every 1% increase in percentage of population over 25 years with a bachelor's degree or higher, the expected number of providers increases by 4.4% (incidence rate ratio [IRR] = 1.044; 95% confidence interval [CI], 1.041-1.046; P < 0.001). For every 1% increase in percentage unemployment, the expected number of providers decreases by 2.7% (IRR = 0.973; 95% CI, 0.964-0.983; P < 0.001). However, for every $1000 increase in median household income, the expected number of providers decreases by 1.6% (IRR = 0.984; 95% CI, 0.983-0.986; P < 0.001).
CONCLUSIONS
Disparities in access exist in areas of lower employment and educational attainment, as both have positive correlations with eye care provider access. Conversely, areas of greater median household income have lower access to providers.
TRANSLATIONAL RELEVANCE
This research contributes to a greater field studying social determinants of health and may inform public health strategies on allocation of providers to improve equitable access to vision care.
Topics: Aged; United States; Humans; Cross-Sectional Studies; Medicare; Socioeconomic Factors; Ophthalmologists
PubMed: 38530303
DOI: 10.1167/tvst.13.3.21 -
Ghana Medical Journal Jun 2023To evaluate the risk of prematurity in Cameroonian children born after in vitro Fertilisation.
OBJECTIVE
To evaluate the risk of prematurity in Cameroonian children born after in vitro Fertilisation.
DESIGN
A retrospective cohort study.
SETTING
Conducted at the pediatric department of the Hospital Center for Research and Application in Endoscopic Surgery and Human Reproduction (HCRAESHR) in Yaoundé over eight months.
PARTICIPANTS
Every newborn born after in vitro fertilisation (exposed group) and those born after spontaneous conception (non-exposed group) from a singleton pregnancy were included. Multiple pregnancies were excluded. One hundred newborns per group were recruited and matched according to the mode of delivery.
INTERVENTIONS
The main outcome measure was prematurity at birth. Data were collected from the medical records of the newborns and reported on individual questionnaires. The t Student test was used to assess the differences in gestational age between the two groups. The generalised linear model using binomial probability distribution was used for multivariate analysis to determine prematurity risk factors. All results with a p-value ≤ 0.05 were considered statistically significant.
RESULTS
Prematurity was significantly predominant in the exposed group (22% and 5%, respectively, p=0.002) compared to the non-exposed group. The risk of prematurity in the exposed group was 4.4 times higher than in the non-exposed group. After controlling for confounders (the maternal age, the sex of the baby, and maternal hypertension), this risk increased significantly from 4.4 to 7.67 (p=0.001).
CONCLUSION
This study demonstrated the first evidence from our part of the world showing that in vitro fertilisation is an absolute risk of prematurity.
FUNDING
None declared.
Topics: Pregnancy; Female; Child; Infant, Newborn; Humans; Retrospective Studies; Cameroon; Fertilization in Vitro; Maternal Age; Risk Factors
PubMed: 38504759
DOI: 10.4314/gmj.v57i2.6 -
Briefings in Bioinformatics Jan 2024In recent years, there has been a growing trend in the realm of parallel clustering analysis for single-cell RNA-seq (scRNA) and single-cell Assay of Transposase...
In recent years, there has been a growing trend in the realm of parallel clustering analysis for single-cell RNA-seq (scRNA) and single-cell Assay of Transposase Accessible Chromatin (scATAC) data. However, prevailing methods often treat these two data modalities as equals, neglecting the fact that the scRNA mode holds significantly richer information compared to the scATAC. This disregard hinders the model benefits from the insights derived from multiple modalities, compromising the overall clustering performance. To this end, we propose an effective multi-modal clustering model scEMC for parallel scRNA and Assay of Transposase Accessible Chromatin data. Concretely, we have devised a skip aggregation network to simultaneously learn global structural information among cells and integrate data from diverse modalities. To safeguard the quality of integrated cell representation against the influence stemming from sparse scATAC data, we connect the scRNA data with the aggregated representation via skip connection. Moreover, to effectively fit the real distribution of cells, we introduced a Zero Inflated Negative Binomial-based denoising autoencoder that accommodates corrupted data containing synthetic noise, concurrently integrating a joint optimization module that employs multiple losses. Extensive experiments serve to underscore the effectiveness of our model. This work contributes significantly to the ongoing exploration of cell subpopulations and tumor microenvironments, and the code of our work will be public at https://github.com/DayuHuu/scEMC.
Topics: Chromatin; Single-Cell Gene Expression Analysis; Cluster Analysis; Learning; RNA, Small Cytoplasmic; Transposases; Sequence Analysis, RNA; Gene Expression Profiling
PubMed: 38493338
DOI: 10.1093/bib/bbae102