Tag: nevin manimala

Eye (Lond). 2023 Jun 10. doi: 10.1038/s41433-023-02617-6. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the safety and efficacy of a new surgical technique for the management of primary rhegmatogenous retinal detachment (RRD), consisting of localized PPV near the retinal break(s), without infusion line, associated with a drainage of subretinal fluid and cryoretinopexy.

METHODS: Multicentric prospective study conducted at the University Hospital of Cagliari and IRCCS Fondazione Policlinico Universitario A. Gemelli, Roma. Twenty eyes affected by RRD with the causative retinal break(s) in the superior meridians were enrolled between February 2022 and June 2022. Patients with cataract ≥3, aphakia, significant posterior capsule opacification, giant retinal tears, retinal dialysis, history of trauma and PVR ≥C2 were excluded. All eyes underwent a two-port 25-gauge PPV with localized removal of the vitreous surrounding retinal break(s), followed by 20% SF6 injection and cryopexy. The surgical time was recorded for each procedure. Best-corrected visual acuity (BCVA) was measured at baseline and postoperative 6 months.

RESULTS: Primary anatomic success at 6 months was achieved by 85% of patients. No complications occurred, except for three (15%) retinal re-detachments. The average surgical time was 8.61 ± 2.16 min. Overall, the difference between pre- and last postoperative mean BCVA was statistically significant (p = 0.02).

CONCLUSIONS: Two-port dry PPV demonstrated safety and efficacy for the treatment of RRD, reaching an 85% of anatomical success rate. Although further studies are necessary to confirm the efficacy and long-term benefit of this treatment, we believe that this surgical technique could be considered a valid and safe alternative for the management of primary RRD.

PMID:37301938 | DOI:10.1038/s41433-023-02617-6

NPJ Precis Oncol. 2023 Jun 10;7(1):57. doi: 10.1038/s41698-023-00406-8.

ABSTRACT

Routine tumor-node-metastasis (TNM) staging of colorectal cancer is imperfect in predicting survival due to tumor pathobiological heterogeneity and imprecise assessment of tumor spread. We leveraged Bayesian additive regression trees (BART), a statistical learning technique, to comprehensively analyze patient-specific tumor characteristics for the improvement of prognostic prediction. Of 75 clinicopathologic, immune, microbial, and genomic variables in 815 stage II-III patients within two U.S.-wide prospective cohort studies, the BART risk model identified seven stable survival predictors. Risk stratifications (low risk, intermediate risk, and high risk) based on model-predicted survival were statistically significant (hazard ratios 0.19-0.45, vs. higher risk; P < 0.0001) and could be externally validated using The Cancer Genome Atlas (TCGA) data (P = 0.0004). BART demonstrated model flexibility, interpretability, and comparable or superior performance to other machine-learning models. Integrated bioinformatic analyses using BART with tumor-specific factors can robustly stratify colorectal cancer patients into prognostic groups and be readily applied to clinical oncology practice.

PMID:37301916 | DOI:10.1038/s41698-023-00406-8

Nat Commun. 2023 Jun 10;14(1):3453. doi: 10.1038/s41467-023-38951-2.

ABSTRACT

Genotypes causing pregnancy loss and perinatal mortality are depleted among living individuals and are therefore difficult to find. To explore genetic causes of recessive lethality, we searched for sequence variants with deficit of homozygosity among 1.52 million individuals from six European populations. In this study, we identified 25 genes harboring protein-altering sequence variants with a strong deficit of homozygosity (10% or less of predicted homozygotes). Sequence variants in 12 of the genes cause Mendelian disease under a recessive mode of inheritance, two under a dominant mode, but variants in the remaining 11 have not been reported to cause disease. Sequence variants with a strong deficit of homozygosity are over-represented among genes essential for growth of human cell lines and genes orthologous to mouse genes known to affect viability. The function of these genes gives insight into the genetics of intrauterine lethality. We also identified 1077 genes with homozygous predicted loss-of-function genotypes not previously described, bringing the total set of genes completely knocked out in humans to 4785.

PMID:37301908 | DOI:10.1038/s41467-023-38951-2

Sci Rep. 2023 Jun 10;13(1):9479. doi: 10.1038/s41598-023-36635-x.

ABSTRACT

Exposure to extreme temperatures or fine particles is associated with adverse health outcomes but their interactive effects remain unclear. We aimed to explore the interactions of extreme temperatures and PM_2.5 pollution on mortalities. Based on the daily mortality data collected during 2015-2019 in Jiangsu Province, China, we conducted generalized linear models with distributed lag non-linear model to estimate the regional-level effects of cold/hot extremes and PM_2.5 pollution. The relative excess risk due to interaction (RERI) was evaluated to represent the interaction. The relative risks (RRs) and cumulative relative risks (CRRs) of total and cause-specific mortalities associated with hot extremes were significantly stronger (p < 0.05) than those related to cold extremes across Jiangsu. We identified significantly higher interactions between hot extremes and PM_2.5 pollution, with the RERI range of 0.00-1.15. The interactions peaked on ischaemic heart disease (RERI = 1.13 [95%CI: 0.85, 1.41]) in middle Jiangsu. For respiratory mortality, RERIs were higher in females and the less educated. The interaction pattern remained consistent when defining the extremes/pollution with different thresholds. This study provides a comprehensive picture of the interactions between extreme temperatures and PM_2.5 pollution on total and cause-specific mortalities. The projected interactions call for public health actions to face the twin challenges, especially the co-appearance of hot extremes and PM pollution.

PMID:37301905 | DOI:10.1038/s41598-023-36635-x

J Expo Sci Environ Epidemiol. 2023 Jun 10. doi: 10.1038/s41370-023-00563-9. Online ahead of print.

ABSTRACT

BACKGROUND: Manganese (Mn) is a metal commonly found in drinking water, but the level that is safe for consumption is unknown. In the United States (U.S.), Mn is not regulated in drinking water and data on water Mn concentrations are temporally and spatially sparse.

OBJECTIVE: Examine temporal and spatial variability of Mn concentrations in repeated tap water samples in a case study of Holliston, Massachusetts (MA), U.S., where drinking water is pumped from shallow aquifers that are vulnerable to Mn contamination.

METHODS: We collected 79 residential tap water samples from 21 households between September 2018 and December 2019. Mn concentrations were measured using inductively coupled plasma mass spectrometry. We calculated descriptive statistics and percent of samples exceeding aesthetic (secondary maximum containment level; SMCL) and lifetime health advisory (LHA) guidelines of 50 µg/L and 300 µg/L, respectively. We compared these concentrations to concurrent and historic water Mn concentrations from publicly available data across MA.

RESULTS: The median Mn concentration in Holliston residential tap water was 2.3 µg/L and levels were highly variable (range: 0.03-5,301.8 µg/L). Mn concentrations exceeded the SMCL and LHA in 14% and 12% of samples, respectively. Based on publicly available data across MA from 1994-2022, median Mn concentration was 17.0 µg/L (N = 37,210; range: 1-159,000 µg/L). On average 40% of samples each year exceeded the SMCL and 9% exceeded the LHA. Samples from publicly available data were not evenly distributed between MA towns or across sampling years.

IMPACT STATEMENT: This study is one of the first to examine Mn concentrations in drinking water both spatially and temporally in the U.S. Findings suggest that concentrations of Mn in drinking water frequently exceed current guidelines and occur at concentrations shown to be associated with adverse health outcomes, especially for vulnerable and susceptible subpopulations like children. Future studies that comprehensively examine exposure to Mn in drinking water and its associations with children’s health are needed to protect public health.

PMID:37301899 | DOI:10.1038/s41370-023-00563-9

Sci Rep. 2023 Jun 10;13(1):9463. doi: 10.1038/s41598-023-36469-7.

ABSTRACT

The memory-type control charts, such as cumulative sum (CUSUM) and exponentially weighted moving average control chart, are more desirable for detecting a small or moderate shift in the production process of a location parameter. In this article, a novel Bayesian adaptive EWMA (AEWMA) control chat utilizing ranked set sampling (RSS) designs is proposed under two different loss functions, i.e., square error loss function (SELF) and linex loss function (LLF), and with informative prior distribution to monitor the mean shift of the normally distributed process. The extensive Monte Carlo simulation method is used to check the performance of the suggested Bayesian-AEWMA control chart using RSS schemes. The effectiveness of the proposed AEWMA control chart is evaluated through the average run length (ARL) and standard deviation of run length (SDRL). The results indicate that the proposed Bayesian control chart applying RSS schemes is more sensitive in detecting mean shifts than the existing Bayesian AEWAM control chart based on simple random sampling (SRS). Finally, to demonstrate the effectiveness of the proposed Bayesian-AEWMA control chart under different RSS schemes, we present a numerical example involving the hard-bake process in semiconductor fabrication. Our results show that the Bayesian-AEWMA control chart using RSS schemes outperforms the EWMA and AEWMA control charts utilizing the Bayesian approach under simple random sampling in detecting out-of-control signals.

PMID:37301897 | DOI:10.1038/s41598-023-36469-7

Sci Rep. 2023 Jun 10;13(1):9480. doi: 10.1038/s41598-023-36362-3.

ABSTRACT

Machine learning (ML) could have advantages over traditional statistical models in identifying risk factors. Using ML algorithms, our objective was to identify the most important variables associated with mortality after dementia diagnosis in the Swedish Registry for Cognitive/Dementia Disorders (SveDem). From SveDem, a longitudinal cohort of 28,023 dementia-diagnosed patients was selected for this study. Sixty variables were considered as potential predictors of mortality risk, such as age at dementia diagnosis, dementia type, sex, body mass index (BMI), mini-mental state examination (MMSE) score, time from referral to initiation of work-up, time from initiation of work-up to diagnosis, dementia medications, comorbidities, and some specific medications for chronic comorbidities (e.g., cardiovascular disease). We applied sparsity-inducing penalties for three ML algorithms and identified twenty important variables for the binary classification task in mortality risk prediction and fifteen variables to predict time to death. Area-under-ROC curve (AUC) measure was used to evaluate the classification algorithms. Then, an unsupervised clustering algorithm was applied on the set of twenty-selected variables to find two main clusters which accurately matched surviving and dead patient clusters. A support-vector-machines with an appropriate sparsity penalty provided the classification of mortality risk with accuracy = 0.7077, AUROC = 0.7375, sensitivity = 0.6436, and specificity = 0.740. Across three ML algorithms, the majority of the identified twenty variables were compatible with literature and with our previous studies on SveDem. We also found new variables which were not previously reported in literature as associated with mortality in dementia. Performance of basic dementia diagnostic work-up, time from referral to initiation of work-up, and time from initiation of work-up to diagnosis were found to be elements of the diagnostic process identified by the ML algorithms. The median follow-up time was 1053 (IQR = 516-1771) days in surviving and 1125 (IQR = 605-1770) days in dead patients. For prediction of time to death, the CoxBoost model identified 15 variables and classified them in order of importance. These highly important variables were age at diagnosis, MMSE score, sex, BMI, and Charlson Comorbidity Index with selection scores of 23%, 15%, 14%, 12% and 10%, respectively. This study demonstrates the potential of sparsity-inducing ML algorithms in improving our understanding of mortality risk factors in dementia patients and their application in clinical settings. Moreover, ML methods can be used as a complement to traditional statistical methods.

PMID:37301891 | DOI:10.1038/s41598-023-36362-3

Sci Rep. 2023 Jun 10;13(1):9461. doi: 10.1038/s41598-023-36454-0.

ABSTRACT

Acetabular labral tears have shown to be difficult to diagnose and manage in an active and competitive athletic population. The goal of this study was to compare NCAA Division 1 collegiate athletes undergoing operative and non-operative management of their labral injuries by assessing ability to return to competition and secondarily evaluate days lost from sport. A retrospective cohort analysis was conducted on Division 1 collegiate athletes from 2005 to 2020, incorporating all varsity university sports. Records showing MRI confirmed diagnosis were included in the cohort, as well as all pertinent clinical data. Data revealed 10/18 (55%) of individuals managed conservatively versus 23/29 (79%) surgically (p-value = 0.0834) were able to return to sport following treatment. Of those athletes, 22 surgical patients experienced a mean of 324 days ± 223 days lost from sport and nine conservatively managed patients experienced a mean of 27 days ± 70 lost days (p-value < 0.001) Seven of nine conservatively managed patients were able to continue competition while undergoing treatment. Findings suggest no statistical significance regarding operative vs non-operative management of acetabular labral tears. The majority of athletes returning to sport and treated conservatively were able to resume competition during treatment. Therefore, treatment of these injuries should be individualized based on athlete’s symptoms.

PMID:37301848 | DOI:10.1038/s41598-023-36454-0

Cell Death Dis. 2023 Jun 10;14(6):357. doi: 10.1038/s41419-023-05870-5.

ABSTRACT

Pediatric Acute Myeloid Leukemia (AML) is a rare and heterogeneous disease characterized by a high prevalence of gene fusions as driver mutations. Despite the improvement of survival in the last years, about 50% of patients still experience a relapse. It is not possible to improve prognosis only with further intensification of chemotherapy, as come with a severe cost to the health of patients, often resulting in treatment-related death or long-term sequels. To design more effective and less toxic therapies we need a better understanding of pediatric AML biology. The NUP98-KDM5A chimeric protein is exclusively found in a particular subgroup of young pediatric AML patients with complex karyotypes and poor prognosis. In this study, we investigated the impact of NUP98-KDM5A expression on cellular processes in human Pluripotent Stem Cell models and a patient-derived cell line. We found that NUP98-KDM5A generates genomic instability through two complementary mechanisms that involve accumulation of DNA damage and direct interference of RAE1 activity during mitosis. Overall, our data support that NUP98-KDM5A promotes genomic instability and likely contributes to malignant transformation.

PMID:37301844 | DOI:10.1038/s41419-023-05870-5

BMC Cancer. 2023 Jun 10;23(1):532. doi: 10.1186/s12885-023-10919-x.

ABSTRACT

BACKGROUND: Cancer patients with newly created ostomies face complications that reduce quality of life (QOL) and increase morbidity and mortality. This proof-of-concept study examined the feasibility, usability, acceptability, and initial efficacy of an eHealth program titled the “Patient Reported Outcomes-Informed Symptom Management System” (PRISMS) during post-ostomy creation care transition.

METHODS: We conducted a 2-arm pilot randomized controlled trial among 23 patients who received surgical treatment with curative intent for bladder and colorectal cancer and their caregivers. After assessing QOL, general symptoms, and caregiver burden at baseline, participants were randomly assigned to PRISMS (n = 16 dyads) or usual care (UC) (n = 7 dyads). After a 60-day intervention period, participants completed a follow-up survey and post-exit interview. We used descriptive statistics and t-tests to analyze the data.

RESULTS: We achieved an 86.21% recruitment rate and a 73.91% retention rate. Among the PRISMS participants who used the system and biometric devices (n = 14, 87.50%), 46.43% used the devices for ≥ 50 days during the study period. Participants reported PRISMS as useful and acceptable. Compared to their UC counterparts, PRISMS patient social well-being scores decreased over time and had an increased trend of physical and emotional well-being; PRISMS caregivers experienced a greater decrease in caregiver burden.

CONCLUSIONS: PRISMS recruitment and retention rates were comparable to existing family-based intervention studies. PRISMS is a useful and acceptable multilevel intervention with the potential to improve the health outcomes of cancer patients needing ostomy care and their caregivers during post-surgery care transition. A sufficiently powered RCT is needed to test its effects.

TRIAL REGISTRATION: ClinicalTrial.gov ID: NCT04492007. Registration date: 30/07/2020.

PMID:37301841 | DOI:10.1186/s12885-023-10919-x