Category: Nevin Manimala

Clin Oral Implants Res. 2021 Aug 6. doi: 10.1111/clr.13817. Online ahead of print.

ABSTRACT

OBJECTIVES: Resonance frequency analysis (RFA) is used to monitor implant stability. Its output, the Implant Stability Quotient (ISQ), supposedly correlates with insertion torque, a common measurement of primary stability. However, the reliability of RFA in condensed bone remains unclear.

MATERIAL AND METHODS: In this human cadaver study in edentulous jaws and fresh extraction sockets, implants were inserted using a split-mouth approach into condensed or untreated bone. Mean ISQ, peak insertion torque, as well as pre- and postoperative bone volume fractions (BV/TV) were assessed.

RESULTS: In edentulous jaws, insertion torque and ISQ correlated both in untreated (r = 0.63, p = 0.02) and in condensed (r = 0.82, p = < 0.01) bone. In extraction sockets, insertion torque and ISQ only correlated in untreated (r = 0.78, p < 0.01), but not in condensed bone (r = 0.15, p = 0.58). In all edentulous jaws, preoperative BV/TV correlated with insertion torque (r = 0.90, p < 0.0001), ISQ (r = 0.64, p < 0.001), and changes in BV/TV (r = -0.71, p < 0.01). In all extraction sockets, preoperative BV/TV did not correlate with either insertion torque (r = 0.33, p = 0.15), ISQ (r = 0.38, p = 0.09), or changes in BV/TV (r = -0.41, p = 0.09). Joint analysis identified preoperative BV/TV as a predictor of postoperative BV/TV (p < 0.001), insertion torque (p < 0.001), and ISQ (p < 0.001).

CONCLUSIONS: RFA is feasible for monitoring stability after late implant placement into condensed bone, but not after immediate placement into condensed fresh extraction sites.

PMID:34358360 | DOI:10.1111/clr.13817

J Oral Pathol Med. 2021 Aug 6. doi: 10.1111/jop.13226. Online ahead of print.

ABSTRACT

BACKGROUND: Oral lichen planus is a relatively common oral disorder which shares clinical and histopathological features with other lichenoid lesions, leading to considerable inter-observer disagreement. This negatively impacts understanding of the pathogenesis and malignant transformation potential of this condition.

METHODS: Artificial intelligence was employed to create a machine-learning artificial neural network to identify and quantify mononuclear cells and granulocytes within the inflammatory infiltrates in digitized hematoxylin and eosin microscopic slides. Twenty-four regions of interest were extracted from oral lichen planus cases for learning purposes and validated on a retrospective cohort of 130 cases. All cases were related to patients with confirmed diagnoses of oral lichen planus, oral lichenoid lesions, or oral epithelial dysplasia with lichenoid host response.

RESULTS: The number of inflammatory cells was statistically significantly higher in oral lichen planus compared to oral lichenoid lesions or oral epithelial dysplasia with lichenoid host response (p <.0005). The proposed machine-learning method was reliably capable of detecting oral lichen planus cases based on the number of inflammatory cells and the number of mononuclear cells with an area under the curve of 0.982 and 0.988, respectively. Identifying a cut-off point between oral lichen planus and other lichenoid conditions based on the number of mononuclear cells showed a sensitivity of 100% and an accuracy of 94.62%.

CONCLUSION: Artificial intelligence has shown promising outcomes and provides a robust approach to enhance the accuracy of anatomical pathologists in accurately diagnosing oral lichen planus using features of disease pathogenesis.

PMID:34358361 | DOI:10.1111/jop.13226

Sleep. 2021 Aug 6:zsab200. doi: 10.1093/sleep/zsab200. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: To assess the efficacy and safety of FT218, a novel once-nightly formulation of sodium oxybate (ON-SXB), in patients with narcolepsy in the phase 3 REST-ON trial.

METHODS: Narcolepsy patients aged ≥16 years were randomized 1:1 to uptitration of ON-SXB (4.5, 6, 7.5, and 9 g) or placebo. Three coprimary endpoints were change from baseline in mean sleep latency on the Maintenance of Wakefulness test, Clinical Global Impression-Improvement rating, and weekly cataplexy attacks at 9, 7.5, and 6 g. Secondary endpoints included change from baseline on the Epworth Sleepiness Scale. Safety included adverse drug reactions and clinical laboratory assessments.

RESULTS: In total, 222 patients were randomized; 212 received ≥1 dose of ON-SXB (n=107) or placebo (n=105). For the 3 coprimary endpoints and Epworth Sleepiness Scale, all 3 doses of ON-SXB demonstrated clinically meaningful, statistically significant improvement vs placebo (all P<0.001). For ON-SXB 9 g vs placebo, increase in mean sleep latency was 10.8 vs 4.7 min (LSMD [95% CI], 6.13 [3.52-8.75]), 72.0% vs 31.6% were rated much/very much improved on Clinical Global Impression-Improvement (OR [95% CI], 5.56 [2.76-11.23]), change in mean weekly number of cataplexy attacks was -11.5 vs -4.9 (LSMD [95% CI], -6.65 [-9.32 to -3.98]), and change in Epworth Sleepiness Scale was -6.5 and -2.7 (LSMD [95% CI], -6.52 [-5.47 to -2.26]). Common adverse reactions included nausea, vomiting, headache, dizziness, and enuresis.

CONCLUSIONS: ON-SXB significantly improved narcolepsy symptoms; its safety profile was consistent with SXB. ON-SXB conferred efficacy with a clearly beneficial single nighttime dose.

PMID:34358324 | DOI:10.1093/sleep/zsab200

Cancer. 2021 Aug 6. doi: 10.1002/cncr.33830. Online ahead of print.

ABSTRACT

BACKGROUND: Few evidence-based psychosocial programs have been tested among adolescents and young adults (AYAs) with advanced cancer (AC), and early advance care planning (ACP) in this population is rare. The authors aimed to determine the feasibility and acceptability of 1) delivering an established resilience-coaching program, and 2) integrating ACP into that program, among AYAs with AC.

METHODS: Eligible AYAs were 12 to 24 years old, diagnosed with advanced cancer (recurrent/refractory disease or a diagnosis associated with <50% survival) and fluent in English. The Promoting Resilience in Stress Management-Advanced Cancer (PRISM-AC) program included PRISM’s standard sessions targeting stress-management, goal-setting, cognitive-restructuring, and meaning-making, delivered 1:1, 1 to 2 weeks apart, plus a new session involving elements of the AYA-specific Voicing My Choices ACP guide. Participants completed surveys at baseline and 12 weeks, and exit interviews following study completion. Feasibility was defined as ≥70% completion of 1) standard 4-session PRISM and 2) the new ACP session among those completing standard PRISM. Acceptability was defined qualitatively. Trajectories of patient-reported anxiety, depression, and hope were examined descriptively.

RESULTS: Of 50 eligible, approached AYAs, 26 (52%) enrolled and completed baseline surveys. The AYAs had a mean age of 16 years (SD = 2.7 years), and the majority were male (73%) and White/Caucasian (62%). Twenty-two AYAs (85%) completed standard PRISM, and of those, 18 (82%) completed the ACP session. Feedback was highly positive; 100% and 91% described the overall and ACP programs as valuable, respectively. Anxiety, depression, and hope were unchanged after the program.

CONCLUSIONS: Resilience coaching followed by integrated ACP is feasible and acceptable for AYAs with AC. Participating did not cause distress or decrease hope.

LAY SUMMARY: Advance care planning (ACP) among adolescents and young adults (AYAs) with advanced cancer can be difficult to introduce. We investigated whether it is feasible and acceptable to integrate ACP into an existing resilience-coaching program for AYAs. In this cohort study of 26 AYAs with advanced cancer, we found the Promoting Resilience in Stress Management-Advanced Cancer program to be feasible (≥70% intervention-completion) and highly acceptable (positive post-participation feedback, no evidence of participant-distress). We conclude that an intervention integrating resilience coaching and ACP is feasible and acceptable among AYAs with advanced cancer.

PMID:34358332 | DOI:10.1002/cncr.33830

Bioinformatics. 2021 Aug 6:btab569. doi: 10.1093/bioinformatics/btab569. Online ahead of print.

ABSTRACT

MOTIVATION: Tumour heterogeneity is being increasingly recognised as an important characteristic of cancer and as a determinant of prognosis and treatment outcome. Emerging spatial transcriptomics data hold the potential to further our understanding of tumour heterogeneity and its implications. However, existing statistical tools are not sufficiently powerful to capture heterogeneity in the complex setting of spatial molecular biology.

RESULTS: We provide a statistical solution, the HeTerogeneity Average index (HTA), specifically designed to handle the multivariate nature of spatial transcriptomics. We prove that HTA has an approximately normal distribution, therefore lending itself to efficient statistical assessment and inference. We first demonstrate that HTA accurately reflects the level of heterogeneity in simulated data. We then use HTA to analyse heterogeneity in two cancer spatial transcriptomics datasets: spatial RNA sequencing by 10x Genomics and spatial transcriptomics inferred from H&E. Finally, we demonstrate that HTA also applies to 3D spatial data using brain MRI. In spatial RNA sequencing we use a known combination of molecular traits to assert that HTA aligns with the expected outcome for this combination. We also show that HTA captures immune-cell infiltration at multiple resolutions. In digital pathology we show how HTA can be used in survival analysis and demonstrate that high levels of heterogeneity may be linked to poor survival. In brain MRI we show that HTA differentiates between normal ageing, Alzheimer’s disease and two tumours. HTA also extends beyond molecular biology and medical imaging, and can be applied to many domains, including GIS.

AVAILABILITY: Python package and source code are available at: https://github.com/alonalj/hta.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34358288 | DOI:10.1093/bioinformatics/btab569

Clin Infect Dis. 2021 Aug 6:ciab679. doi: 10.1093/cid/ciab679. Online ahead of print.

ABSTRACT

BACKGROUND: 240-million people have schistosomiasis despite decades of interventions. Infections cannot be directly observed, and egg-based Kato-Katz thick smears lack sensitivity, impacting treatment efficacy and reinfection rate estimates. The Point-of-Care Circulating Cathodic Antigen test (POC-CCA) is advocated as an improvement upon the Kato-Katz, however improved estimates are limited by ambiguities in the interpretation of Trace results.

METHOD: We collected repeated Kato-Katz counts from 210 school-aged children and scored POC-CCAs according to manufacturer’s guidelines (POC-CCA+) and the externally developed G-Score. We used Hidden Markov Models parameterised with Kato-Katz; Kato-Katz and POC-CCA+; and Kato-Katz and G-Scores, inferring latent clearance and reinfection probabilities at four timepoints over six-months through a more formal statistical reconciliation of these diagnostics than previously conducted. Our approach required minimal but robust assumptions regarding Trace interpretations.

RESULTS: Antigen-based models estimated higher infection prevalence across all timepoints compared with the Kato-Katz model, corresponding to lower clearance and higher reinfection estimates. Specifically, pre-treatment prevalence estimates were 85% (Kato-Katz; 95% CI: 79-92%), 99% (POC-CCA+; 97-100%) and 98% (G-Score; 95-100%). Post-treatment, 93% (Kato-Katz; 88-96%), 72% (POC-CCA+; 64-79%) and 65% (G-Score; 57-73%) of those infected were estimated to clear infection. Of those who cleared infection, 35% (Kato-Katz; 27-42%), 51% (POC-CCA+; 41-62%) and 44% (G-Score; 33-55%) were estimated to have been reinfected by nine-weeks.

CONCLUSION: Treatment impact was shorter-lived than only Kato-Katz-based estimates suggested, with lower clearance and rapid reinfection. Three-weeks-post-treatment captured longer-term clearance dynamics. Nine-weeks-post-treatment captured reinfection, but alone could not discern between failed clearance and rapid reinfection. Therefore, frequent sampling is required to understand these important epidemiological dynamics.

PMID:34358299 | DOI:10.1093/cid/ciab679

Bioinformatics. 2021 Aug 6:btab574. doi: 10.1093/bioinformatics/btab574. Online ahead of print.

ABSTRACT

MOTIVATION: The investigation of quantitative trait loci (QTL) is an essential component in our understanding of how organisms vary phenotypically. However, many important crop species are polyploid (carrying more than two copies of each chromosome), requiring specialised tools for such analyses. Moreover, deciphering meiotic processes at higher ploidy levels is not straightforward, but is necessary to understand the reproductive dynamics of these species, or uncover potential barriers to their genetic improvement.

RESULTS: Here we present polyqtlR, a novel software tool to facilitate such analyses in (auto)polyploid crops. It performs QTL interval mapping in F1 populations of outcrossing polyploids of any ploidy level using identity-by-descent (IBD) probabilities. The allelic composition of discovered QTL can be explored, enabling favourable alleles to be identified and tracked in the population. Visualisation tools within the package facilitate this process, and options to include genetic co-factors and experimental factors are included. Detailed information on polyploid meiosis including prediction of multivalent pairing structures, detection of preferential chromosomal pairing and location of double reduction events can be performed.

AVAILABILITY: polyqtlR is freely available from the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org/package=polyqtlR.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34358315 | DOI:10.1093/bioinformatics/btab574

PLoS One. 2021 Aug 6;16(8):e0255884. doi: 10.1371/journal.pone.0255884. eCollection 2021.

ABSTRACT

BACKGROUND: COVID-19 is highly infectious viral disease that can lead to main clinical symptoms like fever, dry cough, fatigue, myalgia, and dyspnea. Since there is no drug to cure the disease, focusing on improving community awareness related to prevention methods is crucial. But there was no regional level study addressing the reach of information, community knowledge and attitude related to COVID-19 and its prevention, and this study was done to inform and assist communication related to the disease responses during early introduction of the disease to the setting.

METHODS: Community based cross sectional study was conducted in selected ten towns of SNNPR, Ethiopia. Multi-stage sampling was used to select 1239 participants. Semi-structured questionnaire was designed, pre-tested and uploaded to SurveyCTO data collection system with security patterns. Knowledge was assessed considering awareness about signs and symptoms, confirmatory test (laboratory test), what to do if there is a suspect, availability of drug to cure the disease, mechanisms of transmission, prevention methods and most at risk groups. Attitude was assessed using 11 statements including seriousness of disease, being at risk, possibility of prevention, and benefits of staying at health facilities. Descriptive statistics and binary logistic regression were performed to manage data using SPSS version 25.

RESULTS: Almost all respondents (99.8%) heard about the disease. The mean score of knowledge was 52.3% (SD = 18.9) while the mean score attitude was 80.8% (SD = 6.48). Educational status, housing condition and marital status were associated with having good knowledge while occupation, housing condition, age and overall knowledge were associated with having positive attitude.

CONCLUSION: Even though almost all respondents had heard about the COVID-19, knowledge and attitude related to COVID-19 and its prevention were low. Awareness creation should be intensified using different local languages to improve community awareness, overcome misconceptions and minimize consequences of the disease.

PMID:34358267 | DOI:10.1371/journal.pone.0255884

Bioinformatics. 2021 Aug 6:btab572. doi: 10.1093/bioinformatics/btab572. Online ahead of print.

ABSTRACT

MOTIVATION: High-throughput sequencing technologies generate a huge amount of data, permitting the quantification of microbiome compositions. The obtained data are essentially sparse compositional data vectors, namely vectors of bacterial gene proportions which compose the microbiome. Subsequently, the need for statistical and computational methods that consider the special nature of microbiome data has increased. A critical aspect in microbiome research is to identify microbes associated with a clinical outcome. Another crucial aspect with high-dimensional data is the detection of outlying observations, whose presence affects seriously the prediction accuracy.

RESULTS: In this article we connect robustness and sparsity in the context of variable selection in regression with compositional covariates with a continuous response. The compositional character of the covariates is taken into account by a linear log-contrast model, and elastic-net regularization achieves sparsity in the regression coefficient estimates. Robustness is obtained by performing trimming in the objective function of the estimator. A reweighting step increases the efficiency of the estimator, and it also allows for diagnostics in terms of outlier identification. The numerical performance of the proposed method is evaluated via simulation studies, and its usefulness is illustrated by an application to a microbiome study with the aim to predict caffeine intake based on the human gut microbiome composition.

AVAILABILITY: The R-package “RobZS” can be downloaded at https://github.com/giannamonti/RobZS.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PMID:34358286 | DOI:10.1093/bioinformatics/btab572

PLoS One. 2021 Aug 6;16(8):e0253517. doi: 10.1371/journal.pone.0253517. eCollection 2021.

ABSTRACT

The dimensions of patient-centred care include not only clinical effectiveness and patient safety, but, importantly, the preferences of patients as consumers of healthcare services. A total of 249 participants were included in the study, with a balanced population proportional representation by age, gender, ethnicity and geographic region of New Zealand. An online questionnaire was used to identify participants’ decision-making process, and what factors and barriers for participants to seek dental treatment. Cross-tabulations, Spearman correlation analysis and Pearson Chi-Square analysis were used for the statistical analyses. Three most common reasons for visit were check-up (77%), clean (57%) and relief of pain 36%). A desire to treat a perceived problem was the most common encouraging factor to seek dental care. Cost was the most common barrier to seeking dental services. The majority of participants attended a private practice (84%), with convenience of location and referral from professionals the most likely to influence their choice. Participants felt the most important trait a dental practitioner could demonstrate was to discuss treatment options with them before any treatment. Dental check-up, teeth cleaning and relief of pain were the most common reasons for patients to choose dental services. Cost and ethnicity of the consumers had a significant impact on how dental services were perceived and sought. Dental practitioners may need to reorientate how they express value of oral health practice, not just in regard to communication with patients, but also with government funding agencies.

PMID:34358252 | DOI:10.1371/journal.pone.0253517