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Abstract Introduction Postpartum depression has costly consequences for the mother, baby, and society. Numerous pharmacological and non-pharmacological interventions are available for the prevention and treatment of postpartum depression. To date, no attempt has been made to synthesize the evidence from comparisons of interventions both within and across these categories. Methods We will perform a systematic review of the literature and perform network meta-analysis of interventions to (a) prevent and (b) treat postpartum depression. This review will include studies of primiparous or multiparous women during pregnancy or within 12 months of delivery of their baby that assess either interventions initiated during pregnancy or within 1 year of childbirth. Comparators will be other eligible interventions or control conditions. The outcome of interests will be related to the antidepressant efficacy of the interventions as well as their acceptability. The published literature will be searched in Ovid MEDLINE 1946-, Embase.com 1947-, Scopus 1823-, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. The search will use a combination of standardized terms and keywords for postpartum depression, a sensitive search filter to limit for randomized controlled trials, and a librarian-created “humans” filter. The search results will be uploaded to the Covidence online systematic review platform (Veritas Health Information Ltd., Victoria, Australia) where two review team members will independently screen articles. We will extract data to include year of publication, language, country, participants (number, demographic data, eligibility criteria, psychiatric symptoms, and co-morbidities), characteristics of the intervention and control conditions, and reported outcomes. Risk of bias for each study will be assessed independently by two review authors using the RoB 2: A revised Cochrane risk of bias tool for randomized trials. Network meta-analysis will be performed using a Bayesian hierarchical model supplemented with a Markov chain Monte Carlo approach. Discussion Postpartum depression is a devastating disease with long-lasting consequences. Given the numerous available interventions to both prevent and treat postpartum depression and the great number of studies comparing them, it is imperative that clinicians and patients are provided with an assessment of their comparative efficacy and acceptability. Systematic review registration Prospero registration (CRD42022303247).

To explore the potential of conventional image processing techniques in the classification of cervical cancer cells, in this work, a co-occurrence histogram method was employed for image feature extraction and an ensemble classifier was developed by combining the base classifiers, namely, the artificial neural network (ANN), random forest (RF), and support vector machine (SVM), for image classification. The segmented pap-smear cell image dataset was constructed by the k-means clustering technique and used to evaluate the performance of the ensemble classifier which was formed by the combination of the above considered base classifiers. The result was also compared with that achieved by the individual base classifiers as well as that trained with color, texture, and shape features. The maximum average classification accuracy of 93.44% was obtained when the ensemble classifier was applied and trained with co-occurrence histogram features, which indicates that the ensemble classifier trained with the co-occurrence histogram features is more suitable for the classification of cervical cancer cells.

This paper describes the solution combustion (SCS) synthesis of nanocrystalline Cr3+ doped ZnAl2O4 (ZAC) particles using a new efficient fuel. A thorough investigation was conducted to comprehend the interaction of dopant (Cr3+) and ZnAl2O4 host matrix, as well as the influence of doping on their structural, optical, and luminescence characteristic properties. The powder samples were thoroughly characterized using XRD, UV–Visible Diffuse Reflectance, and Photoluminescence spectroscopic techniques. The XRD analysis demonstrates the formation of polycrystalline nanoparticles, as well as a decrease in crystallite size with increasing Cr3+ concentration. The band gap energy red-shifted as Cr3+ was incorporated into the host matrix. The diffuse reflectance spectra show two absorption peaks at 395 nm and 540 nm are assigned to the 4A2g →4T1g and 4A2g →4T2g characteristic transitions of Cr3+ ions. The PL emission spectrum, on the other hand, shows four distinct peaks, indicating the manifestation of Cr3+ ions in octahedral symmetry, that is, Cr3+ ions in a strong crystal field. Increases in Cr3+ concentration result in luminescence enhancement up to x = 0.07 and suppression of luminescence observed beyond that concentration. In addition, the dopant ion's Racah parameters, crystal field parameters, and local site symmetry are calculated.

Introduction Platelet-rich plasma (PRP) contains high platelet concentration and growth factors that help in rapid wound healing, hemostasis, and decreased scarring. It has been used in various conditions to aid in healing, but its use in ear, nose, and throat (ENT) is not yet common.

Determining the genetic architecture of Alzheimer's disease pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we perform a genome-wide association study of cortical tau quantified by positron emission tomography in 3046 participants from 12 independent studies. The CYP1B1-RMDN2 locus is associated with tau deposition. The most significant signal is at rs2113389, explaining 4.3% of the variation in cortical tau, while APOE4 rs429358 accounts for 3.6%. rs2113389 is associated with higher tau and faster cognitive decline. Additive effects, but no interactions, are observed between rs2113389 and diagnosis, APOE4, and amyloid beta positivity. CYP1B1 expression is upregulated in AD. rs2113389 is associated with higher CYP1B1 expression and methylation levels. Mouse model studies provide additional functional evidence for a relationship between CYP1B1 and tau deposition but not amyloid beta. These results provide insight into the genetic basis of cerebral tau deposition and support novel pathways for therapeutic development in AD.

Abstract Developing novel materials is an essential requirement in the engineering field. This study investigates the effects of incorporating wood dust particles on the mechanical and erosive wear properties of Luffa acutangula fiber (LAF)-reinforced phenol-formaldehyde composites, fabricated using the hand layup method with a constant 20% fiber content and varying wood dust particle contents of 0%, 10%, 20%, and 30%. Using the Taguchi method, the study identifies the optimal combination for minimizing erosive wear − 20% wood dust content, 45 m/s impact velocity, 60° impingement angle, 600 μm erodent size, and 60 mm standoff distance—achieving a minimum erosion rate of 189.8 mg/kg. The addition of 20% wood dust results in significant enhancements in mechanical properties, with tensile strength increasing by 17.56%, flexural strength by 48.78%, and impact strength by 54.64%, compared to composites without wood dust. These findings underscore the potential of LAF composites with bio-fillers for lightweight structural applications in sectors prioritizing sustainability and mechanical durability, such as automotive and aerospace.

Fowlpox is a highly contagious viral disease that is endemic worldwide, caused by the Avipoxvirus genus within the Poxviridae family. To diagnose and study the evolution of this virus, PCR amplification combined with sequencing and phylogenetic analysis are effective methodologies. In this study, nodular tissue from a suspected infected bird was collected and tested for the presence of the Fowlpox virus. The virus was identified using conventional PCR, targeting the virion core protein (P4b) gene with specific primers, resulting in an amplicon of 415 bp. The virus was subsequently isolated from chicken embryonated eggs and confirmed through conventional PCR. The partial P4b gene was sequenced and the sequence was submitted to GenBank with the accession number OQ469498. Phylogenetic analysis of the Fowlpox virus outbreak isolates revealed that it formed a distinct clade with isolates from Germany, the United States, China, South Africa, New Zealand, and Australia, all exhibiting 100% homology. This analysis indicated minimal genetic diversity within the Fowlpox virus, suggesting its stability. Additionally, the investigation into the outbreak highlighted issues such as vaccine failure, changes in tissue tropism, and variations in disease outbreak patterns. Therefore, it is essential to conduct focused and comprehensive molecular epidemiological studies and research on host-pathogen interactions to understand better these factors, which will aid in the effective control and eradication of Fowlpox disease.

Our prior study focused on development of internet of things (IoT) and edge-compute enabled crop physiology sensing system (CPSS) for apple sunburn monitoring. Edge compute algorithm on CPSS estimated sunburn susceptibility as fruit surface temperature (FST) through pixel-by-pixel multiplication of captured thermal infrared images with segmented fruits binary mask. The segmentation was performed using color-based K means clustering approach. This limited CPSS applicability to monitor sunburn of red colored cultivars only and when fruits develop color, typically late growing season. This is a key research gap as recent weather patterns have shown that sunburn can occur during early growing season when fruits are green to yellow. Therefore, aim of this study was to develop and field evaluate cultivar and color independent mask region-convolution neural network (R-CNN) aided fruit segmentation model and edge compute compatible FST estimation algorithm. Season long field data were collected in 2021 using eight CPSS nodes (three in cv. WA38 [Cosmic crisp] and five in cv. Honeycrisp). Collected data were used to develop and validate mask R-CNN based fruit segmentation model. Developed mask R-CNN based model was able to segment fruits of two apple cultivars and of varying colors with 91.4 % average precision. In orchard evaluations (2022 season), the resulting algorithm ported on CPSS was able to accurately segment (dice similarity coefficient = 0.89) and estimate apple FST with 35 °C) on a warmer day resulted in multiple throttling errors caused by excessive CPU temperature; however, the CPSS performance was uncompromised in FST estimation. Ambient air temperature did not affect RAM utilization and CPU clock frequency. Overall, developed FST algorithm can potentially be used as input to actuate water-based cooling system.