Tag: statistics

J Hum Hypertens. 2023 Apr 29. doi: 10.1038/s41371-023-00833-x. Online ahead of print.

ABSTRACT

Hypertension is a leading cause of non-communicable morbidity in Sub Saharan Africa. Recent studies suggest and increase in the prevalence of hypertension in rural Sub-Saharan Africa. Using a three-phase approach, a structured questionnaire was used to determine the prevalence of hypertension in a rural settlement is Enugu State, Southeast Nigeria. Blood pressure measurement was done according to the guidelines of the European Society of Hypertension. Out of 1576 participants aged 18 years and above, 1082 (68.7%) completed the full survey, their blood pressure was measured, and data analyzed. The prevalence of hypertension in this study was 27.6%, (95%CI 25-30.4), similar in males 29.2, (95%CI 24.7-30.4) and females 26.8%, (95%CI 23.5-30.2). p = 0.39. The prevalence of hypertension increased with age reaching a peak of 32.8% (95%CI 26.2-40) in the 40-49 age group, however this was not statistically significant P = 0.22. This age-related increase in the prevalence of hypertension tended towards significance in males (p = 0.05) but not in females (p = 0.44). Awareness of hypertension was 7.2%. Systolic blood pressure positively correlated with older age, higher blood glucose levels and waist-hip ratio. Diastolic blood pressure correlated with the type of work the patients is involved in and blood glucose levels. In conclusion, the prevalence of hypertension in a rural southeastern Nigeria community was 27.6%, however awareness was very low (7.9%). Most participants had mild hypertension thus offering a window of opportunity for public health educators in preventing the complications of hypertension. There is therefore the need for awareness campaigns to be intensified in rural communities.

PMID:37120682 | DOI:10.1038/s41371-023-00833-x

Nat Methods. 2023 Apr 29. doi: 10.1038/s41592-023-01887-y. Online ahead of print.

NO ABSTRACT

PMID:37120675 | DOI:10.1038/s41592-023-01887-y

Sci Rep. 2023 Apr 29;13(1):7049. doi: 10.1038/s41598-023-34161-4.

ABSTRACT

Discovering synthetic lethal (SL) gene partners of cancer genes is an important step in developing cancer therapies. However, identification of SL interactions is challenging, due to a large number of possible gene pairs, inherent noise and confounding factors in the observed signal. To discover robust SL interactions, we devised SLIDE-VIP, a novel framework combining eight statistical tests, including a new patient data-based test iSurvLRT. SLIDE-VIP leverages multi-omics data from four different sources: gene inactivation cell line screens, cancer patient data, drug screens and gene pathways. We applied SLIDE-VIP to discover SL interactions between genes involved in DNA damage repair, chromatin remodeling and cell cycle, and their potentially druggable partners. The top 883 ranking SL candidates had strong evidence in cell line and patient data, 250-fold reducing the initial space of 200K pairs. Drug screen and pathway tests provided additional corroboration and insights into these interactions. We rediscovered well-known SL pairs such as RB1 and E2F3 or PRKDC and ATM, and in addition, proposed strong novel SL candidates such as PTEN and PIK3CB. In summary, SLIDE-VIP opens the door to the discovery of SL interactions with clinical potential. All analysis and visualizations are available via the online SLIDE-VIP WebApp.

PMID:37120674 | DOI:10.1038/s41598-023-34161-4

Eye (Lond). 2023 Apr 29. doi: 10.1038/s41433-023-02549-1. Online ahead of print.

ABSTRACT

PURPOSE: This study compared the efficiency of diabetic retinopathy (DR) diagnosis and differences in the relative visible retinal area among the Early Treatment Diabetic Retinopathy Study (ETDRS) seven-field, ultra-widefield (UWF)-Optos, and UWF-Clarus fundus imaging methods.

METHODS: This was a prospective and clinic-based comparative study. All patients underwent three fundus examinations, and all images were graded using the ETDRS severity scale. We compared and analysed the agreement of DR severity and the relative visible retinal area among the three fundus examination methods, and the number and type of lesions outside the ETDRS seven-field (peripheral lesions) between the two UWF imaging methods.

RESULTS: A total of 202 patients (386 eyes) were included. Weighted kappa for the agreement between ETDRS seven-field and blinded Optos images was 0.485; between ETDRS seven-field and blinded Clarus images, 0.924; and between blinded Optos and Clarus images, 0.461. Blinded Clarus showed excellent performance when a ETDRS scale was used for grading the images. The relative visible retinal area for ETDRS seven-field images was 195 ± 28 disc area (DA); single Optos images, 371 ± 69 DA; single Clarus images, 261 ± 65 DA; two-montage Clarus images, 462 ± 112 DA; and four-montage Clarus images, 598 ± 139 DA. The relative visible retinal area was statistically significant between any two of the imaging systems used. In total, 2015 and 4200 peripheral lesions were detected in single Optos and Clarus images, respectively (P < 0.001). These peripheral lesions on two UWF images suggested a more severe DR level in approximately 10% and 12% of eyes, respectively.

CONCLUSION: UWF-Clarus fundus imaging offers a suitable assessment approach for DR severity; it could improve DR diagnosis and has the potential to replace ETDRS seven-field imaging after additional clinical trials.

PMID:37120657 | DOI:10.1038/s41433-023-02549-1

Sci Rep. 2023 Apr 29;13(1):7055. doi: 10.1038/s41598-023-34305-6.

ABSTRACT

With the rapid rate of SARS-CoV-2 Main protease (M^pro) structures deposition, a computational method that can combine all the useful structural features becomes crucial. This research focuses on the frequently occurring atoms and residues to find a generalized strategy for inhibitor design given a large amount of protein complexes from SARS-CoV in contrast to SARS-CoV-2 M^pro. By superposing large numbers of the ligands onto the protein template and grid box, we can analyse which part of the structure is conserved from position-specific interaction for both data sets for the development of pan-M^pro antiviral design. The difference in conserved recognition sites from the crystal structures can be used to determine specificity determining residues for designing selective drugs. We can display pictures of the imaginary shape of the ligand by unionising all atoms from the ligand. We also pinpoint the most probable atom adjustments to imitate the frequently found densities from the ligand atoms statistics. With molecular docking, Molecular Dynamics simulation, and MM-PBSA methods, a carbonyl replacement at the nitrile warhead (N5) of Paxlovid’s Nirmatrelvir (PF-07321332) was suggested. By gaining insights into the selectivity and promiscuity regions for proteins and ligands, crucial residues are highlighted, and the antiviral design strategies are proposed.

PMID:37120654 | DOI:10.1038/s41598-023-34305-6

Transl Psychiatry. 2023 Apr 29;13(1):141. doi: 10.1038/s41398-023-02443-0.

ABSTRACT

Treatment effect in clinical trials for major depressive disorders (RCT) can be viewed as the resultant of treatment specific and non-specific effects. Baseline individual propensity to respond non-specifically to any treatment or intervention can be considered as a major non-specific confounding effect. The greater is the baseline propensity, the lower will be the chance to detect any treatment-specific effect. The statistical methodologies currently applied for analyzing RCTs doesn’t account for potential unbalance in the allocation of subjects to treatment arms due to heterogenous distributions of propensity. Hence, the groups to be compared may be imbalanced, and thus incomparable. Propensity weighting methodology was used to reduce baseline imbalances between arms. A randomized, double-blind, placebo controlled, three arms, parallel group, 8-week, fixed-dose study to evaluate efficacy of paroxetine CR 12.5 and 25 mg/day is presented as a cases study. An artificial intelligence model was developed to predict placebo response at week 8 in subjects assigned to placebo arm using changes from screening to baseline of individual Hamilton Depression Rating Scale items. This model was used to predict the probability to respond to placebo in each subject. The inverse of the probability was used as weight in the mixed-effects model applied to assess treatment effect. The analysis with and without propensity weight indicated that the weighted analysis provided an estimate of treatment effect and effect-size about twice larger than the non-weighted analysis. Propensity weighting provides an unbiased strategy to account for heterogeneous and uncontrolled placebo effect making patients’ data comparable across treatment arms.

PMID:37120641 | DOI:10.1038/s41398-023-02443-0

Clin Epigenetics. 2023 Apr 29;15(1):73. doi: 10.1186/s13148-023-01482-0.

ABSTRACT

BACKGROUND: Epigenetic silencing of tumor suppressor genes (TSGs) is a key feature of oncogenesis in hepatocellular carcinoma (HCC). Liver-targeted delivery of CRISPR-activation (CRISPRa) systems makes it possible to exploit chromatin plasticity, by reprogramming transcriptional dysregulation.

RESULTS: Using The Cancer Genome Atlas HCC data, we identify 12 putative TSGs with negative associations between promoter DNA methylation and transcript abundance, with limited genetic alterations. All HCC samples harbor at least one silenced TSG, suggesting that combining a specific panel of genomic targets could maximize efficacy, and potentially improve outcomes as a personalized treatment strategy for HCC patients. Unlike epigenetic modifying drugs lacking locus selectivity, CRISPRa systems enable potent and precise reactivation of at least 4 TSGs tailored to representative HCC lines. Concerted reactivation of HHIP, MT1M, PZP, and TTC36 in Hep3B cells inhibits multiple facets of HCC pathogenesis, such as cell viability, proliferation, and migration.

CONCLUSIONS: By combining multiple effector domains, we demonstrate the utility of a CRISPRa toolbox of epigenetic effectors and gRNAs for patient-specific treatment of aggressive HCC.

PMID:37120619 | DOI:10.1186/s13148-023-01482-0

Sci Rep. 2023 Apr 29;13(1):7017. doi: 10.1038/s41598-023-34024-y.

ABSTRACT

To achieve sustainable development worldwide, the United Nations set 17 Sustainable Development Goals (SDGs) for humanity to reach by 2030. Society is involved in the challenge, with firms playing a crucial role. Thus, a key question is to what extent firms engage with the SDGs. Efforts to map firms’ contributions have mainly focused on analysing companies’ reports based on limited samples and non-real-time data. We present a novel interdisciplinary approach based on analysing big data from an online social network (Twitter) with complex network methods from statistical physics. By doing so, we provide a comprehensive and nearly real-time picture of firms’ engagement with SDGs. Results show that: (1) SDGs themes tie conversations among major UK firms together; (2) the social dimension is predominant; (3) the attention to different SDGs themes varies depending on the community and sector firms belong to; (4) stakeholder engagement is higher on posts related to global challenges compared to general ones; (5) large UK companies and stakeholders generally behave differently from Italian ones. This paper provides theoretical contributions and practical implications relevant to firms, policymakers and management education. Most importantly, it provides a novel tool and a set of keywords to monitor the influence of the private sector on the implementation of the 2030 Agenda.

PMID:37120611 | DOI:10.1038/s41598-023-34024-y

NPJ Digit Med. 2023 Apr 29;6(1):83. doi: 10.1038/s41746-023-00822-x.

ABSTRACT

Data-driven medical care delivery must always respect patient privacy-a requirement that is not easily met. This issue has impeded improvements to healthcare software and has delayed the long-predicted prevalence of artificial intelligence in healthcare. Until now, it has been very difficult to share data between healthcare organizations, resulting in poor statistical models due to unrepresentative patient cohorts. Synthetic data, i.e., artificial but realistic electronic health records, could overcome the drought that is troubling the healthcare sector. Deep neural network architectures, in particular, have shown an incredible ability to learn from complex data sets and generate large amounts of unseen data points with the same statistical properties as the training data. Here, we present a generative neural network model that can create synthetic health records with realistic timelines. These clinical trajectories are generated on a per-patient basis and are represented as linear-sequence graphs of clinical events over time. We use a variational graph autoencoder (VGAE) to generate synthetic samples from real-world electronic health records. Our approach generates health records not seen in the training data. We show that these artificial patient trajectories are realistic and preserve patient privacy and can therefore support the safe sharing of data across organizations.

PMID:37120594 | DOI:10.1038/s41746-023-00822-x

World J Surg Oncol. 2023 Apr 29;21(1):138. doi: 10.1186/s12957-023-03019-4.

ABSTRACT

BACKGROUND: Anaplastic lymphoma kinase (ALK) overexpression and gene alterations have been detected in several mesenchymal tumors, with significant implications for diagnosis, therapy and prognosis. However, few studies have investigated the correlation between ALK expression status and clinicopathological characteristics in patients with gastrointestinal stromal tumors (GISTs).

METHODS: A total of 506 GIST patients were enrolled. Sanger sequencing was employed to detect c-KIT and PDGFRA gene mutations. The tissue microarray (TMA) technique and immunohistochemistry were employed to identify the ALK (clone: 1A4 and D5F3) expression status in the tumor tissues. The ALK gene variants of IHC-positive cases were analyzed by fluorescence in situ hybridization (FISH) and next-generation sequencing (NGS). The clinicopathological data were analyzed using SPSS Statistics 26.0.

RESULTS: Among the 506 GIST patients, the c-KIT mutation accounted for 84.2% (426/506), followed by PDGFRA mutation (10.3%, 52/506), while the wild-type accounted for the least (5.5%, 28/506). ALK-positive expression was detected in PDGFRA-mutant GISTs (7.7%, 4/52) but negative for c-KIT-mutant or wild-type GISTs by IHC. Four ALK IHC-positive patients were all male. The tumors all occurred outside the stomach. The predominant patterns of growth were epithelioid (2/4), spindle (1/4), and mixed type (1/4). They were all identified as high-risk classification according to the National Institutes of Health (NIH) classification. Aberrant ALK mutations were not identified by DNA-based NGS except in one of the 4 cases with amplification by FISH.

CONCLUSION: Our study revealed 7.7% (4/52) of ALK expression in PDGFRA-mutant GISTs, indicating that molecular tests were required to rule out the possibility of PDGFRA-mutant GISTs when encountering ALK-positive mesenchymal tumors with CD117-negative or weakly positive in immunohistochemical staining.

PMID:37120571 | DOI:10.1186/s12957-023-03019-4