Nevin Manimala

Clin Exp Immunol. 2023 Oct 31:uxad121. doi: 10.1093/cei/uxad121. Online ahead of print.

ABSTRACT

The adaptive and innate immune system is important in both initiating and preventing functional disorders during pregnancy, one of which is pre-eclampsia. The research aims to conduct the comparative quantification of selected subpopulations of peripheral blood immunoregulatory cells in pregnant women with pre-eclampsia in the third trimester. The marker receptors CD4, CD8, CD95, CD25, CD27, and the marker antigen HLA-DR were considered. The screening was performed by flow cytometry with dual phenotyping using phycoerythrin- and fluorescein-isothiocyanate-labeled monoclonal antibodies. Data processing consisted in calculating a likelihood value to assess the statistical significance of the difference between the samples. A statistically significant decrease in the subpopulation titer of T- and B-lymphocytes with marker receptors CD4, CD8, and CD19 was found in pre-eclampsia patients. In the CD4 carrier T-lymphocyte population, there was an increased expression of the CD25/CD95 activation and apoptosis markers. In the CD8 T-killer population, a decreased representation of the CD27/CD25/CD95 markers of differentiation, activation, and apoptosis was deterministic. The expression pattern of the major histocompatibility complex antigen HLA-DR did not change significantly in normality and pathology. The titer of peripheral natural killer cells carrying the CD56 marker increased in patients with various degrees of disease severity, while the number of CD16 natural killer remained at the level of the control group. The research results suggest that a change in the ratio of the above receptors is a diagnostic indicator for pre-eclampsia.

PMID:37921073 | DOI:10.1093/cei/uxad121

Int J Oncol. 2023 Dec;63(6):138. doi: 10.3892/ijo.2023.5586. Epub 2023 Nov 3.

ABSTRACT

The aim of the present study was to elucidate the role and downstream mechanism of long non‑coding RNA (lncRNA) metastasis‑associated lung adenocarcinoma transcript 1 (MALAT1) in the process of cervical cancer cell pyroptosis. The effect of inhibiting lncRNA MALAT1 on cervical cancer cells was determined using primary cells isolated from patients and U14 cervical tumor‑bearing nude mice. The level of lncRNA MALAT1 expression and cell viability were determined for relationship analysis. Pyroptosis was then investigated in HeLa cells with lncRNA MALAT1 knockdown or overexpression with or without lipopolysaccharide (LPS) treatment. Bioinformatics tools were used to identify downstream factors of lncRNA MALAT1, which were subsequently verified by gain‑ or loss‑of‑function analyses in the process of cervical cancer cell pyroptosis. It was observed that the level of lncRNA MALAT1 was markedly higher in cervical carcinoma cells compared with expression in paracarcinoma cells, and knockdown of lncRNA MALAT1 induced cervical cancer cell death through pyroptosis. By contrast, overexpression of lncRNA MALAT1 blocked LPS‑induced pyroptosis. These results, combined with bioinformatics statistical tools, demonstrated that the microRNA (miR)‑124/sirtuin 1 (SIRT1) axis may affect the progression of cervical cancer at least partly by mediating the effect of lncRNA MALAT1 on the pyroptosis of cervical cancer cells. In conclusion, the lncRNA MALAT1/miR‑124/SIRT1 regulatory axis in cervical cancer cells may mediate pyroptosis and may provide potential targets against the progression of cervical cancer.

PMID:37921054 | DOI:10.3892/ijo.2023.5586

Sports Biomech. 2023 Nov 3:1-23. doi: 10.1080/14763141.2023.2269543. Online ahead of print.

ABSTRACT

Eccentric quasi-isometrics (EQIs) are a novel, low-velocity resistance exercise technique that incorporates a holding isometric contraction to positional fatigue, followed by voluntary resistance of the resulting eccentric muscle action. As females are typically more fatigue resistant than males during isometric and low-velocity dynamic muscle actions, this study explored sex-differences in the muscle fatigue response to an EQI protocol. Twenty-five (n = 12 female) participants completed 4 unilateral EQI elbow flexions. Absolute and relative surface electromyography (sEMG) amplitude (iEMG, LE peak), mean power frequency (MPF), angular impulse (aIMP), and elbow angle were compared across repetitions and between sexes using discrete values and statistical parametric/non-parametric mapping. There were significant and substantial sex and repetition differences in absolute iEMG, MPF, and aIMP, however, males and females had statistically similar absolute aIMP by repetition 4. When expressed relatively, there were no significant sex-differences. Additionally, there were significant between repetition changes in sEMG amplitude and elbow angle with an increasing number of repetitions, largely in the first-two thirds of repetition time. The current study suggests that there are absolute, but not relative sex-differences in EQI induced muscle fatigue, and the effects across repetitions occur predominately in the first two-thirds of repetition time.

PMID:37921046 | DOI:10.1080/14763141.2023.2269543

Stat Med. 2023 Nov 3. doi: 10.1002/sim.9944. Online ahead of print.

ABSTRACT

Human microbiome research has gained increasing importance due to its critical roles in comprehending human health and disease. Within the realm of microbiome research, the data generated often involves operational taxonomic unit counts, which can frequently present challenges such as over-dispersion and zero-inflation. To address dispersion-related concerns, the generalized Poisson model offers a flexible solution, effectively handling data characterized by over-dispersion, equi-dispersion, and under-dispersion. Furthermore, the realm of zero-inflated generalized Poisson models provides a strategic avenue to simultaneously tackle both over-dispersion and zero-inflation. The phenomenon of zero-inflation frequently stems from the heterogeneous nature of study populations. It emerges when specific microbial taxa fail to thrive in the microbial community of certain subjects, consequently resulting in a consistent count of zeros for these individuals. This subset of subjects represents a latent class, where their zeros originate from the genuine absence of the microbial taxa. In this paper, we introduce a novel testing methodology designed to uncover such latent classes within generalized Poisson regression models. We establish a closed-form test statistic and deduce its asymptotic distribution based on estimating equations. To assess its efficacy, we conduct an extensive array of simulation studies, and further apply the test to detect latent classes in human gut microbiome data from the Bogalusa Heart Study.

PMID:37921025 | DOI:10.1002/sim.9944

Transfusion. 2023 Nov 3. doi: 10.1111/trf.17580. Online ahead of print.

ABSTRACT

BACKGROUND: Management of major hemorrhage frequently requires massive transfusion (MT) support, which should be delivered effectively and efficiently. We have previously developed a clinical decision support system (CDS) for MT using a multicenter multidisciplinary user-centered design study. Here we examine its impact when administering a MT.

STUDY DESIGN AND METHODS: We conducted a randomized simulation trial to compare a CDS for MT with a paper-based MT protocol for the management of simulated hemorrhage. A total of 44 specialist physicians, trainees (residents), and nurses were recruited across critical care to participate in two 20-min simulated bleeding scenarios. The primary outcome was the decision velocity (correct decisions per hour) and overall task completion. Secondary outcomes included cognitive workload and System Usability Scale (SUS).

RESULTS: There was a statistically significant increase in decision velocity for CDS-based management (mean 8.5 decisions per hour) compared to paper based (mean 6.9 decisions per hour; p .003, 95% CI 0.6-2.6). There was no significant difference in the overall task completion using CDS-based management (mean 13.3) compared to paper-based (mean 13.2; p .92, 95% CI -1.2-1.3). Cognitive workload was statistically significantly lower using the CDS compared to the paper protocol (mean 57.1 vs. mean 64.5, p .005, 95% CI 2.4-12.5). CDS usability was assessed as a SUS score of 82.5 (IQR 75-87.5).

DISCUSSION: Compared to paper-based management, CDS-based MT supports more time-efficient decision-making by users with limited CDS training and achieves similar overall task completion while reducing cognitive load. Clinical implementation will determine whether the benefits demonstrated translate to improved patient outcomes.

PMID:37921017 | DOI:10.1111/trf.17580

J Esthet Restor Dent. 2023 Nov 3. doi: 10.1111/jerd.13159. Online ahead of print.

ABSTRACT

STATEMENT OF PROBLEM: Despite the growing utilization of direct intraoral scanners (IOSs) in dentistry, there is a scarcity of research investigating their accuracy, specifically in post and core. Few studies have conducted comprehensive three-dimensional assessments and comparisons of IOSs with the conventional impression technique, particularly in different post space lengths.

PURPOSE: The purpose of this in vitro study was to digitally assess the accuracy of direct intraoral scanner (IOS) impressions for different post space lengths, specifically 6, 8, and 10 mm.

MATERIALS AND METHODS: A total of 45 typodont teeth (maxillary central incisors) were selected for this study. The teeth underwent endodontic treatment and were divided into three subgroups, each with 15 teeth, based on the desired post space lengths: 6, 8, and 10 mm. Intraoral scans of all specimens were acquired directly using the CEREC Primescan intraoral scanners by two trained examiners. The obtained scan data were compared with conventional impressions obtained using light and heavy bodies of polyvinyl siloxane (PVS). As a control, the conventional impressions were subsequently scanned using an inEos X5a lab scanner. The accuracy of the digital scans was evaluated in the coronal, middle, and apical thirds using the Geomagic Control X software. Statistical analysis was performed using Bonferroni Post-hoc and One-way ANOVA tests to analyze the data.

RESULTS: The overall mean root mean square (RMS) deviations for the different post lengths across the three thirds groups were 58, 81, and 101 μm for the 6, 8, and 10 mm subgroups, respectively. There were no statistically significant differences in the accuracy of the coronal and middle thirds among all subgroups (p > 0.5). However, in the apical third, the 10 mm subgroup exhibited a significantly lower accuracy (163 μm) compared to the 6 mm (96 μm) and 8 mm (131 μm) subgroups (p < 0.05). These results suggest that while the accuracy of intraoral scans using direct IOS impressions was consistent in the coronal and middle thirds regardless of the post length, there was a noticeable decrease in accuracy in the apical third, particularly with longer post lengths.

CONCLUSION: Considering the limitations of this in vitro study, chairside direct IOS impressions offer a viable and clinically acceptable alternative to the conventional impression technique for post space lengths of 6 and 8 mm. However, as the post space length preparation increases, the accuracy of IOS decreases.

CLINICAL SIGNIFICANCE: The Chairside direct IOS enables expedited and efficient digital impression capture within the root canal, ensuring acceptable accuracy for intracanal post length preparation of up to 8 mm.

PMID:37921014 | DOI:10.1111/jerd.13159

Psychol Med. 2023 Nov 3:1-9. doi: 10.1017/S003329172300291X. Online ahead of print.

ABSTRACT

BACKGROUND: Non-suicidal self-injury (NSSI) is prevalent in major depressive disorder (MDD) during adolescence, but the underlying neural mechanisms are unclear. This study aimed to investigate microstructural abnormalities in the cingulum bundle associated with NSSI and its clinical characteristics.

METHODS: 130 individuals completed the study, including 35 healthy controls, 47 MDD patients with NSSI, and 48 MDD patients without NSSI. We used tract-based spatial statistics (TBSS) with a region of interest (ROI) analysis to compare the fractional anisotropy (FA) of the cingulum bundle across the three groups. receiver-operating characteristics (ROC) analysis was employed to evaluate the ability of the difficulties with emotion regulation (DERS) score and mean FA of the cingulum to differentiate between the groups.

RESULTS: MDD patients with NSSI showed reduced cingulum integrity in the left dorsal cingulum compared to MDD patients without NSSI and healthy controls. The severity of NSSI was negatively associated with cingulum integrity (r = -0.344, p = 0.005). Combining cingulum integrity and DERS scores allowed for successful differentiation between MDD patients with and without NSSI, achieving a sensitivity of 70% and specificity of 83%.

CONCLUSIONS: Our study highlights the role of the cingulum bundle in the development of NSSI in adolescents with MDD. The findings support a frontolimbic theory of emotion regulation and suggest that cingulum integrity and DERS scores may serve as potential early diagnostic tools for identifying MDD patients with NSSI.

PMID:37921013 | DOI:10.1017/S003329172300291X

Microsc Res Tech. 2023 Nov 3. doi: 10.1002/jemt.24451. Online ahead of print.

ABSTRACT

Most of the food consumed worldwide is produced by plants. Plant disease is a major cause of reduced production, but can be managed with regular monitoring. Manually observing plant diseases takes more time and is error-prone. Early detection of plant diseases with the aid of artificial intelligence and computer vision can decrease the effects of disease and help plants withstand the downsides of continuing surveillance. In this manuscript, plant disease identification using contextual mask auto-encoder optimized with dynamic differential annealed optimization algorithm (PDI-CMAE-DDAOA) is proposed. The plant village dataset is used to collect the images. Then the image is fed to preprocessing. Using an adaptive self-guided filter approach, the noise is removed from the input images during the pre-processing phase. The result of the pre-processing section serves as input for the feature extraction segment. Four statistical features, including mean, variance, entropy, and kurtosis, are recovered from the cosine similarity hidden Markov model (CSHMM). The contextual mask auto-encoder (CMAE) is given the extracted features to accurately classify the healthy and unhealthy regions of the plant image. The issue of slow convergence affects the CMAE. However, it is noted that the CMAE converges more quickly with deep learning features than with texture features in this instance. The CMAE classifier generally does not exhibit any adaptation of optimization algorithms for determining the best parameters to ensure the precise classification of plant disease. Therefore, dynamic differential annealed optimization algorithm (DDAOA) is considered to enhance the CMAE classifier, which accurately distinguishes between healthy and diseased plants. The proposed PDI-CMAE-DDAOA is done in Python. The efficacy of PDI-CMAE-DDAOA is evaluated under some performance metrics, like accuracy, precision, sensitivity, F1-score, specificity, error rate, receiver operating characteristic curve (ROC), computational time. The proposed method provides higher accuracy 23.34%, 34.33%, and 32.07%; higher sensitivity 36.67%, 36.33%, and 23.21%; higher F1-score 46.67%, 57.56%, and 43.21%; higher specificity 56.67%, 67.56%, and 23.21% analyzed with existing models, like transfer learning-based deep ensemble neural network for plant leaf infection recognition (PDI-DENN), plant disease detection with hybrid model based on convolutional auto-encoder and convolutional neural network (PDI-CAE-CNN), and automatic and reliable leaf disease finding depending on deep learning methods (PDI-EN-CNN), respectively. RESEARCH HIGHLIGHTS: To find the plant disease at early stage. To present PDI-CMAE-DDAOA. To get better classification accuracy by extracting the optimal features with the help of efficient CSHMM. To minimize the error during classification process. To maximize high area under curve value.

PMID:37921010 | DOI:10.1002/jemt.24451

Trauma Violence Abuse. 2023 Nov 3:15248380231205821. doi: 10.1177/15248380231205821. Online ahead of print.

ABSTRACT

As opioid use-related behaviors continue at epidemic proportions, identifying the root causes of these behaviors is critical. Adverse childhood experiences (ACEs) are shown to be an important predictor of opioid initiation, opioid dependence, and lifetime opioid overdose. The purpose of this systematic review is to examine the association between ACEs and opioid use-related behaviors later in life and to discuss implications for policy, practice, and research regarding ACEs and opioids. Five databases (PubMed, PsycINFO, CINAHL, Medline, and Scopus) were used to identify studies investigating the association between ACEs and opioid use-related behaviors. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 20 studies out of the initial 428 met the inclusion criteria for this review. Among the included 20 studies, 15 focused on the relationship between ACEs and lifetime opioid use-related behaviors, and five focused on current opioid use-related behaviors. All studies found statistical associations between ACEs and lifetime or current opioid use-related behaviors. Five studies found a significant gradient effect; that is, as the number of ACEs increased, the risk of opioid use-related behaviors also increased. A significant dose-response relationship exists between ACEs and opioid use-related behaviors. Hence, it is essential for clinicians to screen for ACEs before prescribing opioid medications, for opioid treatment to incorporate trauma-informed methods, and for messaging around opioid use interventions to include information about ACEs. The current review points to a critical need to implement standardized ACE screening instruments in clinical and research settings.

PMID:37920999 | DOI:10.1177/15248380231205821

Stat Methods Med Res. 2023 Nov 3:9622802231211010. doi: 10.1177/09622802231211010. Online ahead of print.

ABSTRACT

Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-specific treatments. In the second case, whole-genome sequencing has had a huge impact in two ways: first, it is becoming cheaper and faster to perform whole-genome sequencing, and this makes it competitive with respect to standard phenotypic tests; second, it is possible to statistically associate the phenotypic patterns of resistance to specific mutations in the genome. Therefore, it is now possible to develop catalogues of genomic variants associated with resistance to specific antibiotics, in order to improve prediction of resistance and suggest treatments. It is essential to have robust methods for identifying mutations associated to resistance and continuously updating the available catalogues. This work proposes a general method to study minimal inhibitory concentration distributions and to identify clusters of strains showing different levels of resistance to antimicrobials. Once the clusters are identified and strains allocated to each of them, it is possible to perform regression method to identify with high statistical power the mutations associated with resistance. The method is applied to a new 96-well microtiter plate used for testing Mycobacterium tuberculosis.

PMID:37920984 | DOI:10.1177/09622802231211010