Nevin Manimala

Cancer Epidemiol Biomarkers Prev. 2022 Nov 1:EPI-22-0877. doi: 10.1158/1055-9965.EPI-22-0877. Online ahead of print.

ABSTRACT

BACKGROUND: Exposure to cigarette smoke, particularly in early life, is modestly associated with ovarian cancer risk and may impact systemic immunity and the tumor immune response. However, no studies have evaluated whether cigarette smoke exposure impacts the ovarian tumor immune microenvironment.

METHODS: Participants in the Nurses’ Health Study (NHS) and NHSII reported on early life exposure to cigarette smoke and personal smoking history on questionnaires (n=165,760). Multiplex immunofluorescence assays were used to measure markers of T cells and immune checkpoints in tumor tissue from 385 incident ovarian cancer cases. We used Cox proportional hazards models to evaluate hazard ratios (HR) and 95% confidence intervals (CI) for developing ovarian tumors with a low (<median) or high (≥median) immune cell percentage by cigarette exposure categories.

RESULTS: Women exposed versus not to cigarette smoke early in life had a higher risk of developing ovarian cancer with low levels of T cells overall (CD3+: HR: 1.54, 95%CI: 1.08, 2.20) and recently activated cytotoxic T cells (CD3+CD8+CD69+: HR: 1.45, 95%CI: 1.05, 2.00). These findings were not statistically significant at the Bonferroni corrected p-value of 0.0083. Adult smoking was not significantly associated with tumor immune markers after Bonferroni correction.

CONCLUSION: These results suggest early life cigarette smoke exposure may modestly increase risk of developing ovarian tumors with low abundance of total T cells and recently activated cytotoxic T cells.

IMPACT: Future research should focus on understanding the impact of exposures throughout the life course on the ovarian tumor immune microenvironment.

PMID:36318652 | DOI:10.1158/1055-9965.EPI-22-0877

Ultrasound Obstet Gynecol. 2022 Nov;60(5):673-680. doi: 10.1002/uog.26050.

ABSTRACT

OBJECTIVE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in pregnancy is associated with increased risk of adverse maternal and perinatal outcomes. Vaccines are highly effective at preventing severe coronavirus disease 2019 (COVID-19), but there are limited data on COVID-19 vaccines in pregnancy. This study aimed to investigate the reactogenicity and immunogenicity of COVID-19 vaccines in pregnant women when administered according to the 12-week-interval dosing schedule recommended in the UK.

METHODS: This was a cohort study of pregnant women receiving COVID-19 vaccination between April and September 2021. The outcomes were immunogenicity and reactogenicity after COVID-19 vaccination. Pregnant women were recruited by phone, e-mail and/or text and were vaccinated according to vaccine availability at their local vaccination center. For immunogenicity assessment, blood samples were taken at specific timepoints after each dose to evaluate nucleocapsid protein (N) and spike protein (S) antibody titers. The comparator group comprised non-pregnant female healthcare workers in the same age group who were vaccinated as part of the national immunization program in a contemporaneous longitudinal cohort study. Longitudinal changes in serum antibody titers and association with pregnancy status were assessed using a two-step regression approach. Reactogenicity assessment in pregnant women was undertaken using an online questionnaire. The comparator group comprised non-pregnant women aged 18-49 years who had received two vaccine doses in primary care. The association of pregnancy status with reactogenicity was assessed using logistic regression analysis.

RESULTS: Overall, 67 pregnant women, of whom 66 had received a mRNA vaccine, and 79 non-pregnant women, of whom 50 had received a mRNA vaccine, were included in the immunogenicity study. Most (61.2%) pregnant women received their first vaccine dose in the third trimester, while 3.0% received it in the first trimester and 35.8% in the second trimester. SARS-CoV-2 S-antibody geometric mean concentrations after mRNA vaccination were not significantly different at 2-6 weeks after the first dose but were significantly lower at 2-6 weeks after the second dose in infection-naïve pregnant compared with non-pregnant women. In pregnant women, prior infection was associated with higher antibody levels at 2-6 weeks after the second vaccine dose. Reactogenicity analysis included 108 pregnant women and 116 non-pregnant women. After the first dose, tiredness and chills were reported less commonly in pregnant compared with non-pregnant women (P = 0.043 and P = 0.029, respectively). After the second dose, feeling generally unwell was reported less commonly (P = 0.046) in pregnant compared with non-pregnant women.

CONCLUSIONS: Using an extended 12-week interval between vaccine doses, antibody responses after two doses of mRNA COVID-19 vaccine were found to be lower in pregnant compared with non-pregnant women. Strong antibody responses were achieved after one dose in previously infected women, regardless of pregnancy status. Pregnant women reported fewer adverse events after both the first and second dose of vaccine. These findings should now be addressed in larger controlled studies. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

PMID:36318630 | DOI:10.1002/uog.26050

Gut Microbes. 2022 Jan-Dec;14(1):2138672. doi: 10.1080/19490976.2022.2138672.

ABSTRACT

We enrolled consecutive IBS-M patients (n = 25) according to Rome IV criteria. Fecal samples were obtained from all patients twice (pre-and post-intervention) and high-throughput 16S rRNA sequencing was performed. Six weeks of personalized nutrition diet (n = 14) for group 1 and a standard IBS diet (n = 11) for group 2 were followed. AI-based diet was designed based on optimizing a personalized nutritional strategy by an algorithm regarding individual gut microbiome features. The IBS-SSS evaluation for pre- and post-intervention exhibited significant improvement (p < .02 and p < .001 for the standard IBS diet and personalized nutrition groups, respectively). While the IBS-SSS evaluation changed to moderate from severe in 78% (11 out of 14) of the personalized nutrition group, no such change was observed in the standard IBS diet group. A statistically significant increase in the Faecalibacterium genus was observed in the personalized nutrition group (p = .04). Bacteroides and putatively probiotic genus Propionibacterium were increased in the personalized nutrition group. The change (delta) values in IBS-SSS scores (before-after) in personalized nutrition and standard IBS diet groups are significantly higher in the personalized nutrition group. AI-based personalized microbiome modulation through diet significantly improves IBS-related symptoms in patients with IBS-M. Further large-scale, randomized placebo-controlled trials with long-term follow-up (durability) are needed.

PMID:36318623 | DOI:10.1080/19490976.2022.2138672

J Am Chem Soc. 2022 Nov 1. doi: 10.1021/jacs.2c07918. Online ahead of print.

ABSTRACT

Amidines are a ubiquitous class of bioactive compounds found in a wide variety of natural products; thus, efficient strategies for their preparation are in great demand. Specifically, their common structural core decorated with three substituents sets amidines as perfect candidates for multicomponent synthesis. Herein, we present a highly modular metal-free multicomponent strategy for the synthesis of sulfonyl amidines. This work was focused on selecting readily accessible reagents to facilitate the in situ formation of enamines by the addition of amines to ketones. These components were coupled with azides to provide a broad reaction scope with respect to all three coupling partners. Aromatic and aliphatic amines and ketones were tolerated under our reaction conditions. Likewise, the presence of a methyl group on the ketone was critical to reactivity, which was leveraged for the design of a highly regioselective reaction with aliphatic ketones. A biologically active compound was successfully synthesized in one step, demonstrating the practical utility of our methodology. Finally, the postulated mechanism was investigated and supported both experimentally and by means of a multivariate statistical model.

PMID:36318611 | DOI:10.1021/jacs.2c07918

PLoS Genet. 2022 Nov 1;18(11):e1010474. doi: 10.1371/journal.pgen.1010474. eCollection 2022 Nov.

ABSTRACT

Insular organisms often evolve predictable phenotypes, like flightlessness, extreme body sizes, or increased melanin deposition. The evolutionary forces and molecular targets mediating these patterns remain mostly unknown. Here we study the Chestnut-bellied Monarch (Monarcha castaneiventris) from the Solomon Islands, a complex of closely related subspecies in the early stages of speciation. On the large island of Makira M. c. megarhynchus has a chestnut belly, whereas on the small satellite islands of Ugi, and Santa Ana and Santa Catalina (SA/SC) M. c. ugiensis is entirely iridescent blue-black (i.e., melanic). Melanism has likely evolved twice, as the Ugi and SA/SC populations were established independently. To investigate the genetic basis of melanism on each island we generated whole genome sequence data from all three populations. Non-synonymous mutations at the MC1R pigmentation gene are associated with melanism on SA/SC, while ASIP, an antagonistic ligand of MC1R, is associated with melanism on Ugi. Both genes show evidence of selective sweeps in traditional summary statistics and statistics derived from the ancestral recombination graph (ARG). Using the ARG in combination with machine learning, we inferred selection strength, timing of onset and allele frequency trajectories. MC1R shows evidence of a recent, strong, soft selective sweep. The region including ASIP shows more complex signatures; however, we find evidence for sweeps in mutations near ASIP, which are comparatively older than those on MC1R and have been under relatively strong selection. Overall, our study shows convergent melanism results from selective sweeps at independent molecular targets, evolving in taxa where coloration likely mediates reproductive isolation with the neighboring chestnut-bellied subspecies.

PMID:36318577 | DOI:10.1371/journal.pgen.1010474

PLoS One. 2022 Nov 1;17(11):e0265799. doi: 10.1371/journal.pone.0265799. eCollection 2022.

ABSTRACT

BACKGROUND: Understanding the perspectives of the key players in the community regarding female genital cutting (FGC) is very important for directing preventive programs. Religious leaders help shape community behaviors, which is highly pertinent in the case of FGC as it is frequently perceived to be a religious requirement. This study assesses religious leaders’ knowledge, attitudes, and positions towards FGC in the Kurdistan Region of Iraq.

METHODS: This cross-sectional study was conducted in the Kurdistan Region of Iraq. It included a purposive sample of 147 local religious leaders (khateebs) representing the three governorates of Erbil, Sulaimaniyah, and Duhok. A self-administered questionnaire was used to collect data about the religious leaders’ knowledge, attitude, and position towards FGC.

RESULTS: The participants identified reduction of the sexual desire of women as the main benefit (37%) and risk (24%) of FGC. Cultural tradition and religious requirements were the main reported reasons for practicing FGC. About 59% of the religious leaders stated that people ask for their advice on FGC. Around 14% of the participants supported performing FGC, compared to 39.1% who opposed it. Religious (73.9%) and cultural (26.1%) rationales were the main reasons given for supporting FGC. Being a cultural practice with harmful effects (53.5%) and lack of clear religious evidence (46.6%) were the main reasons for being against FGC. Around 52% of the participants recommended banning FGC by law, while 43.5% did not support banning it. A statistically significant association (P = 0.015) was found between religious leaders’ residence and their position on performing FGC. More than 46% of those residing in Duhok were against performing FGC, compared to lower proportions in Erbil (38.8%) and Sulaimaniyah (30%).

CONCLUSION: Religious leaders believed that cultural tradition was the main reason behind practicing FGC and they believed that FGC is not common in KRI, and even that it is decreasing. The religious leaders in our study reported that they could have an influential role in the FGC issue due to their position in the community. There was no statistically significant association between religious leaders’ age, education level, or work experience and their position on performing FGC. However, a statistically significant association was found between religious leaders’ residence and their position on performing FGC. A conclusive decision concerning the prohibition of FGC needs to be made by religious authorities. Health awareness activities incorporating FGC risks should be carried out to inform religious leaders at different levels of religious positions. Further research exploring perspectives of religious authorities concerning religious leaders’ inconclusive judgment about FGC is deemed necessary.

PMID:36318575 | DOI:10.1371/journal.pone.0265799

IEEE Trans Med Imaging. 2022 Nov 1;PP. doi: 10.1109/TMI.2022.3218662. Online ahead of print.

ABSTRACT

Non-rigid registration between 3D surfaces is an important but notorious problem in medical imaging, because finding correspondences between non-isometric instances is mathematically non-trivial. We propose a novel self-supervised method to learn shape correspondences directly from a group of bone surfaces segmented from CT scans, without any supervision from time-consuming and error-prone manual annotations. Relying on a Siamese architecture, DiffusionNet as the feature extractor is jointly trained with a pair of randomly rotated and scaled copies of the same shape. The learned embeddings are aligned in spectral domain using eigenfunctions of the Laplace-Beltrami Operator. Additional normalization and regularization losses are incorporated to guide the learned embeddings towards a similar uniform representation over spectrum, which promotes the embeddings to encode multiscale features and advocates sparsity and diagonality of the inferred functional maps. Our method achieves state-of-the-art results among the unsupervised methods on several benchmarks, and presents greater robustness and efficacy in registering moderately deformed shapes. A hybrid refinement strategy is proposed to retrieve smooth and close-to-conformal point-to-point correspondences from the inferred functional map. Our method is orientation and discretization-invariant. Given a pair of near-isometric surfaces, our method automatically computes registration in high accuracy, and outputs anatomically meaningful correspondences. In this study, we show that it is possible to use neural networks to learn general embeddings from 3D shapes in a self-supervised way. The learned features are multiscale, informative, and discriminative, which might potentially benefit almost all types of morphology-related downstream tasks, such as diagnostics, data screening and statistical shape analysis in future.

PMID:36318555 | DOI:10.1109/TMI.2022.3218662

IEEE J Biomed Health Inform. 2022 Nov 1;PP. doi: 10.1109/JBHI.2022.3218293. Online ahead of print.

ABSTRACT

Cervical squamous intra-epithelial lesions (SIL) are precursor cancer lesions and their diagnosis is important because patients have a chance to be cured before cancer develops. In the diagnosis of the disease, pathologists decide by considering the cell distribution from the basal to the upper membrane. The idea, inspired by the pathologists’ point of view, is based on the fact that cell amounts differ in the basal, central, and upper regions of tissue according to the level of Cervical Intraep- ithelial Neoplasia (CIN). Therefore, histogram information can be used for tissue classification so that the model can be explainable. In this study, two different classification schemes are proposed to show that the local histogram is a useful feature for the classification of cervical tissues. The first classifier is Kullback Leibler divergence-based, and the second one is the classification of the histogram by combining the embedding feature vector from morpho- metric features. These algorithms have been tested on a public dataset.¹ The method we propose in the study achieved an accuracy performance of 78.69% in a data set where morphology-based methods were 69.07% and Convo- lutional Neural Network (CNN) patch-based algorithms were 75.77%. The proposed statistical features are robust for tackling real-life problems as they operate independently of the lesions manifold.

PMID:36318553 | DOI:10.1109/JBHI.2022.3218293

IEEE J Biomed Health Inform. 2022 Nov 1;PP. doi: 10.1109/JBHI.2022.3218585. Online ahead of print.

ABSTRACT

To exploit large-scale biomedical data, the application of common data models and the establishment of data networks are being actively carried out worldwide. However, due to the privacy issues, it is difficult to share data distributed among institutions. In this study, we developed and evaluated weight-based integrated Cox model (WICOX) as a privacy-protecting method without sharing patient-level information across institutions. WICOX generates a weight for each institutional model and builds an integrated model of multi-institutional data based on these weights. WICOX does not require iterative communication until the centralized parameter converges. We performed experiments to show the weight characteristic of our algorithm based on 10 hospitals (2910 intensive care unit (ICU) stays in total) from the electronic intensive care unit Collaborative Research Database to predict time to ICU mortality with eight risk factors. Compared with the centralized Cox model, WICOX showed biases from 0 to 0.68E-2, from 0.00E-2 to 4.98E-2, and from 0.74E-2 to 1.7E-2 for time-dependent AUC, log hazard ratio, and survival rate, respectively. In addition, through simulation results using real 10 hospitals, WICOX showed robust results in accuracy under any composition of hospitals. The results of the experiments highlight that WICOX has robust characteristics and provides predictive performance and statistical inference results nearly the same as those of the centralized model. WICOX is a non-iterative method using the weight of institutional model for implementing the Cox model across multiple institutions in a privacy-preserving manner.

PMID:36318551 | DOI:10.1109/JBHI.2022.3218585

Nucleic Acids Res. 2022 Nov 1:gkac944. doi: 10.1093/nar/gkac944. Online ahead of print.

ABSTRACT

Evolutionary developmental biology (evo-devo) has been among the most fascinating interdisciplinary fields for decades, which aims to elucidate the origin and evolution of diverse developmental processes. The rapid accumulation of omics data provides unprecedented opportunities to answer many interesting but unresolved evo-devo questions. However, the access and utilization of these resources are hindered by challenges particularly in non-model animals. Here, we establish a comparative multi-omics database for animal evo-devo (EDomics, http://edomics.qnlm.ac) containing comprehensive genomes, bulk transcriptomes, and single-cell data across 40 representative species, many of which are generally used as model organisms for animal evo-devo study. EDomics provides a systematic view of genomic/transcriptomic information from various aspects, including genome assembly statistics, gene features and families, transcription factors, transposable elements, and gene expressional profiles/networks. It also exhibits spatiotemporal gene expression profiles at a single-cell level, such as cell atlas, cell markers, and spatial-map information. Moreover, EDomics provides highly valuable, customized datasets/resources for evo-devo research, including gene family expansion/contraction, inferred core gene repertoires, macrosynteny analysis for karyotype evolution, and cell type evolution analysis. EDomics presents a comprehensive and comparative multi-omics platform for animal evo-devo community to decipher the whole history of developmental evolution across the tree of life.

PMID:36318263 | DOI:10.1093/nar/gkac944