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This study theoretically investigates blood rheology in arteries by modeling blood as an Oldroyd-B nanofluid with uniformly suspended Au, Cu, and Al2O3 nanoparticles. A fractional order framework is employed to capture memory and hereditary effects while preserving the invariance of governing equations. The influence of nanoparticle geometry is examined by considering spherical (isotropic), cylindrical (axial), and platelet-like (planar) shapes. Using integral transform techniques, a comparative analysis highlights how particle symmetry and system parameters affect flow behavior and heat transfer. Thermal effects are further analyzed as both a contributor to flow resistance and a source of symmetry breaking in conduction, with implications for optimizing nanofluid-based blood rheology in biomedical applications such as cryosurgery.

Introduction Pakistan has a high prevalence of oral cavity cancer (OCC) with a significant recurrence rate. This study aims to explore the factors associated with OCC recurrence in Karachi, Pakistan. Methods This cross-sectional study was conducted at the Aga Khan University Hospital (AKUH) Karachi, Pakistan, using data from the AKUH Cancer Registry. A total of 1692 biopsy-confirmed cases of OCC including cancers of mucosal lip, tongue, gum, oral cavity floor, palate and other subsites like retromolar area, diagnosed between May 2011 and December 2020, were included in our study. Results Of the 1692 patients, 611 (36.1%) experienced recurrence. Being male was associated with significantly increased odds of OCC recurrence compared to being female (Prevalence Odds Ratio (POR) = 1.70, 95% CI = 1.25–2.30). Moderately and poorly differentiated tumors had higher odds of recurrence (POR = 1.44, 95% CI = 1.02–2.02 and POR = 2.35, 95% CI = 1.49–3.71 respectively). Lymph node involvement was significantly associated with increased odds of recurrence. Patients with N1, N2 and N3 lymph node involvement had significantly higher odds of recurrence (POR = 1.45, 95% CI = 1.02–2.07 for N1, POR = 2.12, 95% CI = 1.57–2.87 for N2 and POR = 3.50, 95% CI = 1.72–7.11 for N3 respectively). Surgical treatment outside AKUH was associated with higher OCC recurrence (POR = 1.68, 95% CI = 1.12–2.50). Surgery alone (POR = 0.02, 95% CI = 0.00-0.16) and in combination with radiation (POR = 0.02, 95% CI = 0.00-0.16) or chemoradiation (POR = 0.04, 95% CI = 0.01–0.33) was protective against recurrence. Conclusion This study’s findings identified factors increasing oral cavity cancer recurrence, highlighting the importance of considering these factors in the management and follow up of patients with OCC. Understanding these factors will not only help enhance patient care, but also improve patient education about their disease prognosis. Further research is needed to explore the underlying mechanisms and develop targeted interventions to improve outcomes for patients with OCC.

The Ovate Family Proteins (OFPs) gene family houses a class of proteins that are involved in regulating plant growth and development. To date, there is no report of the simultaneous functional characterization of this gene family in all members of U’s Triangle of Brassica . Here, we retrieved a combined total of 256 OFP protein sequences and analyzed their chromosomal localization, gene structure, conserved protein motif domains, and the pattern of cis -acting regulatory elements. The abundance of light-responsive elements like G-box , MRE , and GT1 motif suggests that OFPs are sensitive to the stimuli of light. The protein-protein interaction network analysis revealed that OFP05 and its orthologous genes were involved in regulating the process of transcriptional repression through their interaction with homeodomain transcription factors like KNAT and BLH . The presence of domains like DNA binding 2 and its superfamily speculated the involvement of OFPs in regulating gene expression. The biotic and abiotic stress, and the tissue-specific expression analysis of the RNA-seq datasets revealed that some of the genes such as BjuOFP30 , and BnaOFP27 , BolOFP11 , and BolOFP10 were highly upregulated in seed coat at the mature stage and roots under various chemical stress conditions respectively which suggests their crucial role in plant growth and development processes. Experimental validation of prominent BnaOFPs such as BnaOFP27 confirmed their involvement in regulating gene expression under salinity, heavy metal, drought, heat, and cold stress. The GO and KEGG pathway enrichment analysis also sheds light on the involvement of OFPs in regulating plant growth and development. These findings have the potential to serve as a forerunner for future studies in terms of functionally diverse analysis of the OFP gene family in Brassica and other plant species.

Robotics and artificial intelligence have played a significant role in developing assistive technologies for people with motor disabilities. Brain-Computer Interface (BCI) is a communication system that allows humans to communicate with their environment by detecting and quantifying control signals produced from different modalities and translating them into voluntary commands for actuating an external device. For that purpose, classification the brain signals with a very high accuracy and minimization of the errors is of profound importance to the researchers. So in this study, a novel framework has been proposed to classify the binary-class electroencephalogram (EEG) data. The proposed framework is tested on BCI Competition IV dataset 1 and BCI Competition III dataset 4a. Artifact removal from EEG data is done through preprocessing, followed by feature extraction for recognizing discriminative information in the recorded brain signals. Signal preprocessing involves the application of independent component analysis (ICA) on raw EEG data, accompanied by the employment of common spatial pattern (CSP) and log-variance for extracting useful features. Six different classification algorithms, namely support vector machine, linear discriminant analysis, k-nearest neighbor, naïve Bayes, decision trees, and logistic regression, have been compared to classify the EEG data accurately. The proposed framework achieved the best classification accuracies with logistic regression classifier for both datasets. Average classification accuracy of 90.42% has been attained on BCI Competition IV dataset 1 for seven different subjects, while for BCI Competition III dataset 4a, an average accuracy of 95.42% has been attained on five subjects. This indicates that the model can be used in real time BCI systems and provide extra-ordinary results for 2-class Motor Imagery (MI) signals classification applications and with some modifications this framework can also be made compatible for multi-class classification in the future.

Cannabidiol (CBD), a non-psychoactive phytocannabinoid derived from Cannabis sativa , has emerged as a promising therapeutic agent due to its diverse pharmacological properties, including potent anti-inflammatory, neuroprotective, and immunomodulatory effects. CBD modulates immune responses, including the regulation of T cell activity, induction of macrophage apoptosis, suppression of pro-inflammatory cytokines, and modulation of signaling pathways involved in inflammation and immune homeostasis. A comprehensive literature search was conducted using PubMed, Scopus, and Web of Science databases to identify relevant preclinical and clinical studies on CBD’s immunomodulatory effects. Preclinical and clinical studies demonstrate its efficacy in treating autoimmune diseases such as Type 1 diabetes, multiple sclerosis, rheumatoid arthritis, and inflammatory bowel disease, along with its potential in neuropathic pain and cancer therapy. Recent advancements in nanotechnology-based delivery systems have further enhanced CBD's therapeutic potential by improving its solubility, bioavailability, and targeted delivery, enabling innovative approaches for wound healing, inflammation management, and cancer treatment. However, challenges such as variability in immune responses, limited long-term safety data, and potential drug-drug interactions persist. This review comprehensively examines CBD’s pharmacokinetics, pharmacodynamics, and immunomodulatory mechanisms, highlighting its clinical potential, existing limitations, and future directions in advancing its integration into precision medicine and immune regulation.

Dalbergia sissoo Roxb. (Shisham) is a timber-producing species of economic, cultural, and medicinal importance in the Indian subcontinent. In the past few decades, Shisham's dieback disease caused by the fungus Botryodiplodia theobromae has become an evolving issue in the subcontinent endangering its survival. To gain insights into this issue, a standard transcriptome assembly was deployed to assess the response of D. sissoo at the transcriptomic level under the stress of B. theobromae infection. For RNA isolation, the control and infected leaf tissue samples were taken from 1-year-old greenhouse-grown D. sissoo plants after 20 days of stem-base spore inoculation. cDNA synthesis was performed from these freshly isolated RNA samples that were then sent for sequencing. About 18.14 Gb (Giga base) of data was generated using the BGISEQ-500 sequencing platform. In terms of Unigenes, 513,821 were identified after a combined assembly of all samples and then filtering the abundance. The total length of Unigenes, their average length, N50, and GC-content were 310,523,693 bp, 604 bp, 1,101 bp, and 39.95% respectively. The Unigenes were annotated using 7 functional databases i.e., 200,355 (NR: 38.99%), 164,973 (NT: 32.11%), 123,733 (Swissprot: 24.08%), 142,580 (KOG: 27.75%), 139,588 (KEGG: 27.17%), 99,752 (GO: 19.41%), and 137,281 (InterPro: 26.72%). Furthermore, the Transdecoder detected 115,762 CDS. In terms of SSR (Simple Sequence Repeat) markers, 62,863 of them were distributed on 51,508 Unigenes and on the predicted 4673 TF (Transcription Factor) coding Unigenes. A total of 16,018 up- and 19,530 down-regulated Differentially Expressed Genes (DEGs) were also identified. Moreover, the Plant Resistance Genes (PRGs) had a count of 9230. We are hopeful that in the future, these identified Unigenes, SSR markers, DEGs and PRGs will provide the prerequisites for managing Shisham dieback disease, its breeding, and in tree improvement programs.