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Mesenchymal stromal cells (MSCs) have the potential for novel treatments of several musculoskeletal conditions due to their ability to differentiate into several cell lineages including chondrocytes, adipocytes and osteocytes. Researchers are exploring whether this could be utilized for novel therapies for joint afflictions. The role of gender in the ability of MSCs to differentiate and proliferate into different cells has not been clearly defined. This systematic review aims to report the current literature on studies, characterized by high quality and in-depth analysis even though quantitatively limited, that have looked at the role of gender in the differentiation and proliferation of MSCs. Sixteen studies were identified during the literature search, reporting 533 patients, of which 202 were male and 331 were female. MSC proliferation, phenotypic analysis and differentiation are reported and contrasted in terms of donor gender. Heterogeneity in methodologies across studies likely contributes to the inconclusive findings presented here, with no discernible statistical disparity observed between genders in differentiation traits. Nevertheless, the proliferation results indicate a notable gender-related impact. Future investigations should aim to ascertain the potential influence of gender on MSC proliferation capacities more conclusively, emphasizing the necessity of standardized protocols for MSC analyses to enhance accuracy and comparability across studies.

Background/objectives: This study aimed to fabricate, optimize, and characterize nanostructured lipid carriers (NLCs) loaded with trans-resveratrol (TRES) as an anti-cancer drug for pulmonary drug delivery using medical nebulizers., Methods: Novel TRES-NLC formulations (F1-F24) were prepared via hot, high-pressure homogenization. One solid lipid (Dynasan 116) was combined with four liquid lipids (Capryol 90, Lauroglycol 90, Miglyol 810, and Tributyrin) in three different ratios (10:90, 50:50, and 90:10 w / w ), with a surfactant (Tween 80) in two different concentrations (0.5 and 1.5%), and a co-surfactant, soya phosphatidylcholine (SPC S-75; 50 mg)., Results: Amongst the analyzed 24 TR-NLC formulations, F8, F14, and F22 were selected based on their physicochemical stability when freshly prepared and following storage (4 weeks 25 °C), as well as in terms of particle size (<145 nm), polydispersity index (PDI; <0.21) and entrapment efficiency (>96%). Furthermore, F14 showed greater stability at 4 and 25 °C for six months and exhibited enhanced aerosolization performance, demonstrating the greater deposition of TRES in the later stages of the next-generation impactor (NGI) when using an air-jet nebulizer than when using an ultrasonic nebulizer. The F14 formulation exhibited greater stability and release in acetate buffer (pH 5.4), with a cumulative release of 95%., Conclusions: Overall, formulation F14 in combination with an air-jet nebulizer was identified as a superior combination, demonstrating higher emitted dose (ED; 80%), fine particle dose (FPD; 1150 µg), fine particle fraction (FPF; 24%), and respirable fraction (RF; 94%). These findings are promising in the optimization and development of NLC formulations, highlighting their versatility and targeting the pulmonary system via nebulization.

Background : The worldwide misuse of antibiotics is one of the main factors in microbial resistance that is a serious threat worldwide. Alternative strategies are needed to overcome this issue. Objectives : In this study, a novel strategy was adopted to suppress the growth of resistant pathogens through immobilization of silver nanoparticles (AgNPs) in gum of Moringa oleifera . Methods : The AgNPs were prepared from the leaves of Moringa oleifera and subsequently characterized through UV-spectrophotometry, FTIR, SEM, and XRD. The differential ratios of characterized AgNPs were immobilized with gum of M. oleifera and investigated for antimicrobial potential against highly resistant pathogens. Results : The immobilized AgNPs displayed promising activities against highly resistant B. subtilis (23.6 mm; 50 µL:200 µL), E. coli (19.3 mm; 75 µL:200 µL), K. pneumoniae (22 mm; 200 µL:200 µL), P. mirabilis (16.3 mm; 100 µL:200 µL), P. aeruginosa (22 mm; 175 µL:200 µL), and S. typhi (19.3; 25 µL:200 µL) than either AgNPs alone or gum. The immobilized AgNPs released positive sliver ions that easily attached to negatively charged bacterial cells. After attachment and permeation to bacterial cells, the immobilized NPs alter the cell membrane permeability, protein/enzymes denaturation, oxidative stress (ROS), damage DNA, and change the gene expression level. It has been mechanistically considered that the immobilized AgNPs can kill bacteria by damaging their cell membranes, dephosphorylating tyrosine residues during their signal transduction pathways, inducing cell apoptosis, rupturing organelles, and inhibiting cell division, which finally leads to cell death. Conclusions : This study proposes a potential alternative drug for curing various infections.

In this paper, an artificial neural network (ANN) has been proposed to estimate the required values of the adjustable parameters of a Semi-Coprime array with staggered steering (SCASS), which was proposed recently. By adjusting the amount of staggering and the sidelobe attenuation (SLA) factor of Chebyshev weights, SCASS can promise a quite small half-power beamwidth (HPBW) and a high peak-to-side-lobe ratio (PLSR), even when the beam is steered away from broadside direction. However, HPBW and PSLR cannot be improved simultaneously. There is always a trade-off between the two performance metrics. Therefore, in this paper, a mechanism has been introduced to minimize HPBW for a desired PSLR. The proposed ANN takes the array of architectural parameters, the required steering angle, and the desired performance metric, i.e., PSLR, as input and suggests the values of the adjustable parameters, which can promise the minimum HPBW for the desired PSLR and steering angle. To train the ANN, we have developed a dataset in Matlab by calculating HPBW and PSLR from the beampattern generated for a large number of combinations of all the variable parameters. It has been shown in this work that the trained ANN can suggest the optimum values of the adjustable parameters that promise the minimum HPBW for the given steering angle, PSLR, and array architectural parameters. The trained ANN can suggest the required adjustable parameters for the desired performance with mean absolute error within just 0.83%.

Localized calcium deficiency at the tomato flower end causes a physiological disorder called blossom end rot, resulting in yield losses of up to 50 percent. Fruit cracking is another physiological disorder of tomatoes that most often occurs when the movement of water and solutes to the tomato is protracted or rapid, but the underlying cause of fruit cracking is, again, calcium deficiency. Therefore, the present field experiment was conducted with the aim of increasing yield and reducing physiological disorders in tomatoes with a foliar application of calcium and micronutrients (zinc and boron). Four levels of calcium (0, 0.3, 0.6, and 0.9%), three levels of boron (0, 0.25, and 0.5%), and three levels of Zinc (0, 0.25, and 0.5%) were applied foliarly three times (starting at flowering, the 2nd application was repeated when the fruits set, and the 3rd after a period of 15 days from the fruits set). An addition of 0.6% calcium increased yield and associated traits with a decreased flower drop. Likewise, a 0.9% calcium addition increased fruit Ca content and decreased blossom end rot, fruit cracking, and Zn content. Foliar spraying with 0.25% boron (compound B) improved flowering and production while reducing flower drop and tomato fruit cracking. Similarly, an application of 0.5% B significantly increased Ca and B content with minimal blossom end rot and Zn content. Likewise, a 0.5% Zn application resulted in yield and yield-related traits with increased fruit B and Zn contents while blossom end rot, fruit cracking, and fruit Ca content were lower when 0.5% of foliar Zn was applied. Therefore, it is concluded that a foliar application of Ca, B, and Zn can be used alone or in combination to minimize the physiological disorders, increase production, and improve tomato fruit quality.

Roots are the hidden and most important part of plants. They serve as stabilizers and channels for uptaking water and nutrients and play a crucial role in the growth and development of plants. Here, two-dimensional image data were used to identify quantitative trait loci (QTL) controlling root traits in an interspecific mapping population derived from a cross between wild soybean 'PI366121' and cultivar 'Williams 82'. A total of 2830 single-nucleotide polymorphisms were used for genotyping, constructing genetic linkage maps, and analyzing QTLs. Forty-two QTLs were identified on twelve chromosomes, twelve of which were identified as major QTLs, with a phenotypic variation range of 36.12% to 39.11% and a logarithm of odds value range of 12.01 to 17.35. Two significant QTL regions for the average diameter, root volume, and link average diameter root traits were detected on chromosomes 3 and 13, and both wild and cultivated soybeans contributed positive alleles. Six candidate genes, Glyma.03G027500 (transketolase/glycoaldehyde transferase), Glyma.03G014500 (dehydrogenases), Glyma.13G341500 (leucine-rich repeat receptor-like protein kinase), Glyma.13G341400 (AGC kinase family protein), Glyma.13G331900 (60S ribosomal protein), and Glyma.13G333100 (aquaporin transporter) showed higher expression in root tissues based on publicly available transcriptome data. These results will help breeders improve soybean genetic components and enhance soybean root morphological traits using desirable alleles from wild soybeans.

Background: Diabetes mellitus (DM) is a non-communicable, life-threatening syndrome that is present all over the world. The use of eco-friendly, cost-effective, and green-synthesised nanoparticles as a medicinal therapy in the treatment of DM is an attractive option., Objective: In the present study, silver nanoparticles (AI-AgNPs) were biosynthesized through the green synthesis method using Azadirachta indica seed extract to evaluate their anti-diabetic potentials., Methods: These nanoparticles were characterized by using UV-visible spectroscopy, Fourier transform infrared spectrophotometers (FTIR), scanning electron microscopy (SEM), DLS, and X-ray diffraction (XRD). The biosynthesized AI-AgNPs and crude extracts of Azadirachta indica seeds were evaluated for anti-diabetic potentials using glucose adsorption assays, glucose uptake by yeast cells assays, and alpha-amylase inhibitory assays., Results: Al-AgNPs showed the highest activity (75 ± 1.528%), while crude extract showed (63 ± 2.5%) glucose uptake by yeast at 80 µg/mL. In the glucose adsorption assay, the highest activity of Al-AgNPs was 10.65 ± 1.58%, while crude extract showed 8.32 ± 0.258% at 30 mM, whereas in the alpha-amylase assay, Al-AgNPs exhibited the maximum activity of 73.85 ± 1.114% and crude extract 65.85 ± 2.101% at 100 µg/mL. The assay results of AI-AgNPs and crude showed substantial dose-dependent activities. Further, anti-diabetic potentials were also investigated in streptozotocin-induced diabetic mice. Mice were administered with AI-AgNPs (10 to 40 mg/kg b.w) for 30 days., Conclusions: The results showed a considerable drop in blood sugar levels, including pancreatic and liver cell regeneration, demonstrating that AI-AgNPs have strong anti-diabetic potential.

Tissue engineering and cell therapy for regenerative medicine have great potential to treat chronic disorders. In musculoskeletal disorders, mesenchymal stromal cells (MSCs) have been identified as a relevant cell type in cell and regenerative strategies due to their multi-lineage potential, although this is likely to be a result of their trophic and immunomodulatory effects on other cells. This PRISMA systematic review aims to assess whether the age of the patient influences the chondrogenic potential of MSCs in regenerative therapy. We identified a total of 3027 studies after performing a search of four databases, including Cochrane, Web of Science, Medline, and PubMed. After applying inclusion and exclusion criteria, a total of 14 papers were identified that were reviewed, assessed, and reported. Cell surface characterization and proliferation, as well as the osteogenic, adipogenic, and chondrogenic differentiation, were investigated as part of the analysis of these studies. Most included studies suggest a clear link between aged donor MSCs and diminished clonogenic and proliferative potential. Our study reveals a heterogeneous and conflicting range of outcomes concerning the chondrogenic, osteogenic, and adipogenic potential of MSCs in relation to age. Further investigations on the in vitro effects of chronological age on the chondrogenic potential of MSCs should follow the outcomes of this systematic review, shedding more light on this complex relationship.

In this paper, we design constant modulus waveforms for dual-function radar-communication (DFRC) systems based on a multi-input multi-output (MIMO) configuration of sensors for a far-field scenario. At first, we formulate a non-convex optimization problem subject to waveform synthesis for minimizing the interference power while maintaining a constant modulus constraint. Next, we solve this non-convex problem, iteratively, using the alternating direction method of multipliers (ADMM) algorithm. Importantly, the designed waveforms approximate a desired beampattern in terms of a high-gain radar beam and a slightly high gain communication beam while maintaining a desired low sidelobe level. The designed waveforms ensure an improved detection probability and an improved bit error rate (BER) for radar and communications parts, respectively. Finally, we demonstrate the effectiveness of the proposed method through simulation results.

Typically, antibody-drug conjugates (ADCs) are made up of a humanized antibody and a small-molecule medication connected by a chemical linker. ADCs' ability to deliver cytotoxic agents to the specific site with reduced side effects showed promising results in oncology. To date, fourteen ADCs have been approved by the US Food and Drug Administration, and approximately 297 ADCs are in pre-clinical/clinical stages in the oncology area. Inspired by these outcomes, a few scientists explored the potential of antibody-drug conjugates in non-oncological conditions such as arthritis, myasthenia gravis, immunological disorders, and kidney failure. However, there are limited data available on the non-oncological applications of antibody-drug conjugates. This current review focuses on the non-oncological applications of antibody-drug conjugates, their developmental studies, testing procedures, in vitro evaluations, and pre-clinical testing. Additionally, a summary of the restrictions, difficulties, and prospects for ADCs in non-oncological applications is provided.

A split-aperture array (SAA) is an array of sensors or antenna elements in which the array is split into two or more sub-arrays (SAs). Recently proposed SAAs, namely coprime and semi-coprime arrays, offer to attain a small half-power beamwidth (HPBW) with a small number of elements, compared to most conventional unified-aperture arrays, at the cost of reduced peak-to-side-lobe ratio (PSLR). To reduce HPBW and increase PSLR, non-uniform inter-element spacing and excitation amplitudes have proven helpful. However, all the existing arrays and beam-formers suffer increased HPBW, degraded PSLR or both when the main beam is steered away from the broadside. In this paper, we propose staggered beam-steering of SAs, a novel technique for decreasing HPBW. In this technique, we steer the main beams of the SAs of a semi-coprime array to angles slightly different from the desired steering angle. In conjunction with staggered beam-steering of SAs, we have utilized Chebyshev weights to suppress the side lobes. The results show that the beam-widening effect of Chebyshev weights can be mitigated considerably by staggered beam-steering of the SAs. Ultimately, the unified beam-pattern of the whole array offers HPBW and PSLR better than the existing SAAs, uniform and non-uniform linear arrays, especially when the desired steering angle is away from the broadside direction.

In this paper, we present a hybrid frequency shift keying and frequency division multiplexing (i.e., FSK-FDM) approach for information embedding in dual-function radar and communication (DFRC) design to achieve an improved communication data rate. Since most of the existing works focus on merely two-bit transmission in each pulse repetition interval (PRI) using different amplitude modulation (AM)- and phased modulation (PM)-based techniques, this paper proposes a new technique that doubles the data rate by using a hybrid FSK-FDM technique. Note that the AM-based techniques are used when the communication receiver resides in the side lobe region of the radar. In contrast, the PM-based techniques perform better if the communication receiver is in the main lobe region. However, the proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar's main lobe or side lobe regions. That is, the proposed scheme enables information encoding according to the transmitted waveforms and frequencies using FSK modulation. Next, the modulated symbols are added together to achieve a double data rate using the FDM technique. Finally, each transmitted composite symbol contains multiple FSK-modulated symbols, resulting in an increased data rate for the communication receiver. Numerous simulation results are presented to validate the effectiveness of the proposed technique.

Green synthesis is the most effective and environmentally friendly way to produce nanoparticles. The present research aimed at the biosynthesizing of silver nanoparticles (AgNPs) using Tribulus terrestris seed extract as the reducing and stabilizing agent and investigating their anti-diabetic properties. Fourier transformation infrared (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and UV-Vis spectroscopy were used to analyze the synthesized silver nanoparticles from Tribulus terrestris (TT-AgNPs). The spectroscopic characterization revealed a surface Plasmon resonance band at 380 nm, which verified the development of TT-AgNPs. The transmittance peaks were observed at 596, 1450, 1631, 2856, 2921, and 3422 cm -1 through the FTIR spectrophotometer. The XRD spectrum showed four distinct diffraction peaks in the 2θ range at 20° to 60°. Intense peaks were at 26.32°, 30.70°, 44.70°, 56.07°, 53.75°, 66.28°, and 75.32°. The SEM analysis revealed that the prepared TT-AgNPs were clustered loosely with a smooth and spherical structure and were of relatively uniform size. The in vitro antidiabetic potential of TT-AgNPs was assessed by using glucose yeast uptake, glucose adsorption, and alpha-amylase assays. TT-AgNPs showed the highest activity (78.45 ± 0.84%) of glucose uptake by yeast at 80 µg/mL. In the glucose adsorption assay, the highest activity of TT-AgNPs was 10.40 ± 0.52% at 30 mM, while in the alpha-amylase assay, TT-AgNPs exhibited the maximum activity of 75.68 ± 0.11% at 100 µg/mL. The results indicate a substantial anti-diabetic effect of the TT-AgNPs. Furthermore, the in vivo antidiabetic study was performed on TT-AgNPs in streptozotocin-induced diabetic mice. After receiving TT-AgNPs treatment for 30 days, the mice were sacrificed for biochemical and histological analyses of pancreatic and liver samples, which demonstrated a good improvement when compared to the control group. Mice treated with TT-AgNPs showed a significant drop in blood sugar levels, showing that the biosynthesized TT-AgNPs have effective anti-diabetic properties.

The synthetic benzimidazole opioid etazene (which has a 70-times higher analgesic activity than morphine), a recreational drug, has gained popularity as a novel psychoactive substance (NPS) on the illegal/darknet market; however, no experimental information is available at the molecular level on the binding mechanism and putative binding site of etazene and its metabolites at the µ-opioid receptor (MOR). In the present study, we investigated the metabolism of etazene in human liver microsomes using ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). We also explored the possibilities of MOR activation by etazene and its metabolites by studying their binding mechanisms and interaction profiles at an active-state MOR model via molecular docking, binding free energy calculations, and all-atom molecular dynamics (MD) simulations. The putative metabolites of etazene were also predicted using the ADMET Predictor 10.1. The molecular docking studies and free energy calculations showed that etazene and its metabolites (M1, M2, and M5-M7) exhibited strong predicted binding affinity at MOR and showed overlapped binding orientation with MOR-bound agonist BU72, which was co-crystallized in the MOR X-ray crystal structure (PDB ID: 5C1M). MD also confirmed the stability of the MOR-etazene and MOR-M6 complexes. These results suggest that etazene and its metabolites may act as strong MOR agonists, highlighting the necessity of experimental validation. The insights from this study, such as key interactions between etazene and its metabolites and the MOR, will allow authorities to predict potential analogs and clarify the target-protein interactions associated with this illicit substance, granting advanced or rapid reactions to confiscating or banning potential emerging drugs.

Osteoarthritis remains an unfortunate long-term consequence of focal cartilage defects of the knee. Associated with functional loss and pain, it has necessitated the exploration of new therapies to regenerate cartilage before significant deterioration and subsequent joint replacement take place. Recent studies have investigated a multitude of mesenchymal stem cell (MSC) sources and polymer scaffold compositions. It is uncertain how different combinations affect the extent of integration of native and implant cartilage and the quality of new cartilage formed. Implants seeded with bone marrow-derived MSCs (BMSCs) have demonstrated promising results in restoring these defects, largely through in vitro and animal studies. A PRISMA systematic review and meta-analysis was conducted using five databases (PubMed, MEDLINE, EMBASE, Web of Science, and CINAHL) to identify studies using BMSC-seeded implants in animal models of focal cartilage defects of the knee. Quantitative results from the histological assessment of integration quality were extracted. Repair cartilage morphology and staining characteristics were also recorded. Meta-analysis demonstrated that high-quality integration was achieved, exceeding that of cell-free comparators and control groups. This was associated with repair tissue morphology and staining properties which resembled those of native cartilage. Subgroup analysis showed better integration outcomes for studies using poly-glycolic acid-based scaffolds. In conclusion, BMSC-seeded implants represent promising strategies for the advancement of focal cartilage defect repair. While a greater number of studies treating human patients is necessary to realize the full clinical potential of BMSC therapy, high-quality integration scores suggest that these implants could generate repair cartilage of substantial longevity.

mRNA vaccines have been demonstrated as a powerful alternative to traditional conventional vaccines because of their high potency, safety and efficacy, capacity for rapid clinical development, and potential for rapid, low-cost manufacturing. These vaccines have progressed from being a mere curiosity to emerging as COVID-19 pandemic vaccine front-runners. The advancements in the field of nanotechnology for developing delivery vehicles for mRNA vaccines are highly significant. In this review we have summarized each and every aspect of the mRNA vaccine. The article describes the mRNA structure, its pharmacological function of immunity induction, lipid nanoparticles (LNPs), and the upstream, downstream, and formulation process of mRNA vaccine manufacturing. Additionally, mRNA vaccines in clinical trials are also described. A deep dive into the future perspectives of mRNA vaccines, such as its freeze-drying, delivery systems, and LNPs targeting antigen-presenting cells and dendritic cells, are also summarized.

Low Birth weight (LBW) infants pose a serious public health concern worldwide in both the short and long term for infants and their mothers. Infant weight prediction prior to birth can help to identify risk factors and reduce the risk of infant morbidity and mortality. Although many Machine Learning (ML) algorithms have been proposed for LBW prediction using maternal features and produced considerable model performance, their performance needs to be improved so that they can be adapted in real-world clinical settings. Existing algorithms used for LBW classification often fail to capture structural information from the tabular dataset of patients with different complications. Therefore, to improve the LBW classification performance, we propose a solution by transforming the tabular data into a knowledge graph with the aim that patients from the same class (normal or LBW) exhibit similar patterns in the graphs. To achieve this, several features related to each node are extracted such as node embedding using node2vec algorithm, node degree, node similarity, nearest neighbors, etc. Our method is evaluated on a real-life dataset obtained from a large cohort study in the United Arab Emirates which contains data from 3453 patients. Multiple experiments were performed using the seven most commonly used ML models on the original dataset, graph features, and a combination of features, respectively. Experimental results show that our proposed method achieved the best performance with an area under the curve of 0.834 which is over 6% improvement compared to using the original risk factors without transforming them into knowledge graphs. Furthermore, we provide the clinical relevance of the proposed model that are important for the model to be adapted in clinical settings.

Few guidelines exist for COVID-19 vaccination amongst cancer patients, fostering uncertainty regarding the immunogenicity, safety, and effects of cancer therapies on vaccination, which this review aims to address. A literature review was conducted to include the latest articles covering the immunogenicity and safety of COVID-19 vaccination in patients with solid and hematologic cancers receiving various treatments. Lower seropositivity following vaccination was associated with malignancy (compared to the general population), and hematologic malignancy (compared to solid cancers). Patients receiving active cancer therapy (unspecified), chemotherapy, radiotherapy, and immunosuppressants generally demonstrated lower seropositivity compared to healthy controls; though checkpoint inhibition, endocrine therapy, and cyclin dependent kinase inhibition did not appear to affect seropositivity. Vaccination appeared safe and well-tolerated in patients with current or past cancer and those undergoing treatment. Adverse events were comparable to the general population, but inflammatory lymphadenopathy following vaccination was commonly reported and may be mistaken for malignant etiology. Additionally, radiation recall phenomenon was sporadically reported in patients who had received radiotherapy. Overall, while seropositivity rates were decreased, cancer patients showed capacity to generate safe and effective immune responses to COVID-19 vaccination, thus vaccination should be encouraged and hesitancy should be addressed in this population.

In this study, we surveyed 635 participants to determine: (a) major causes of mental stress during the pandemic and its future impacts, and (b) diversity in public perception of the COVID-19 vaccination and its acceptance (specifically for children). Statistical results and intelligent clustering outcomes indicate significant associations between sociodemographic diversity, mental stress causes, and vaccination perception. For instance, statistical results indicate significant dependence between gender (we will use term 'sex' in the rest of the manuscript) and mental stress due to COVID-19 infection ( p = 1.7 × 10 -5 ). Over 25% of males indicated work-related stress compared to 35% in females, however, females indicated that they were more stressed (17%) due to relationships compared to males (12%). Around 30% of Asian/Arabic participants do not feel that the vaccination is safe as compared to 8% of white British and 22% of white Europeans, indicating significant dependence ( p = 1.8 × 10 -8 ) with ethnicity. More specifically, vaccination acceptance for children is significantly dependent with ethnicity ( p = 3.7 × 10 -5 ) where only 47% participants show willingness towards children's vaccination. The primary dataset in this study along with experimental outcomes identifying sociodemographic information diversity with respect to public perception and acceptance of vaccination in children and potential stress factors might be useful for the public and policymakers to help them be better prepared for future epidemics, as well as working globally to combat mental health issues.

Risk factors for osteoarthritis (OA) often exert effects over protracted time-courses. Mendelian randomization (MR) studies therefore have an advantage over conventional observational studies when studying the causal effect of long-term lifestyle-related risk factors on OA. However, given the heterogeneous design of existing MR studies on OA, the reported causal estimates of these effects remain inconsistent, thus obscuring the true extent of the biological effects of OA lifestyle-risk factors. We conducted a PRISMA systematic review and specifically included MR studies that investigated the causal effect between lifestyle-related risk factors and OA, where causal estimates for various lifestyle factors were pooled for meta-analysis. Quality of studies was assessed according to STROBE-MR guidelines. A total of 1576 studies were evaluated and 23 were included. Overall, the studies included were of high quality and had a low risk of bias. Our meta-analysis demonstrates the positive causal effect of BMI (OR IVW-random effects 1.49 [1.23-1.80]) and negative causal effects of serum calcium (OR IVW-random effects 0.69 [0.57-0.83]) and LDL levels (OR IVW-random effects 0.93 [0.90-0.96]) on OA. Despite the heterogeneous designs and estimates of causal effects provided by various MR studies, our meta-analysis suggests that lifestyle-related risk factors in the form of BMI, serum calcium, and LDL have true biological effects on the development of OA., Competing Interests: The authors declare no conflict of interest.

Usefulness of Vaccine-Adverse Event-Reporting System (VAERS) data and protocols required for statistical analyses were pinpointed with a set of recommendations for the application of machine learning modeling or exploratory analyses on VAERS data with a case study of COVID-19 vaccines (Pfizer-BioNTech, Moderna, Janssen). A total of 262,454 duplicate reports (29%) from 905,976 reports were identified, which were merged into a total of 643,522 distinct reports. A customized online survey was also conducted providing 211 reports. A total of 20 highest reported adverse events were first identified. Differences in results after applying various machine learning algorithms (association rule mining, self-organizing maps, hierarchical clustering, bipartite graphs) on VAERS data were noticed. Moderna reports showed injection-site-related AEs of higher frequencies by 15.2%, consistent with the online survey (12% higher reporting rate for pain in the muscle for Moderna compared to Pfizer-BioNTech). AEs {headache, pyrexia, fatigue, chills, pain, dizziness} constituted >50% of the total reports. Chest pain in male children reports was 295% higher than in female children reports. Penicillin and sulfa were of the highest frequencies (22%, and 19%, respectively). Analysis of uncleaned VAERS data demonstrated major differences from the above (7% variations). Spelling/grammatical mistakes in allergies were discovered (e.g., ~14% reports with incorrect spellings for penicillin).

Silicon (Si), despite being abundant in nature, is still not considered a necessary element for plants. Si supplementation in plants has been extensively studied over the last two decades, and the role of Si in alleviating biotic and abiotic stress has been well documented. Owing to the noncorrosive nature and sustainability of elemental Si, Si fertilization in agricultural practices has gained more attention. In this review, we provide an overview of different smart fertilizer types, application of Si fertilizers in agriculture, availability of Si fertilizers, and experiments conducted in greenhouses, growth chambers, and open fields. We also discuss the prospects of promoting Si as a smart fertilizer among farmers and the research community for sustainable agriculture and yield improvement. Literature review and empirical studies have suggested that the application of Si-based fertilizers is expected to increase in the future. With the potential of nanotechnology, new nanoSi (NSi) fertilizer applications may further increase the use and efficiency of Si fertilizers. However, the general awareness and scientific investigation of NSi need to be thoughtfully considered. Thus, we believe this review can provide insight for further research into Si fertilizers as well as promote Si as a smart fertilizer for sustainability and crop improvement.

In this work, we report the results of the compositional analysis of an aluminum gallium arsenide (AlGaAs) sample using the calibration-free laser-induced breakdown spectroscopy (CF-LIBS) technique. The AlGaAs sample was doped with three various concentrations of gallium (Ga), arsenic (As), and aluminum (Al), as reported by the manufacturer, and the CF-LIBS technique was employed to identify the doping concentration. A pulsed Q-switched Nd: YAG laser capable of delivering 200 and 400 mJ energy at 532 and 1064 nm, respectively, was focused on the target sample for ablation, and the resulting emission spectra were captured using a LIBS 2000+ spectrometer covering the spectral range from 200 to 720 nm. The emission spectra of the AlGaAs sample yielded spectral lines of Ga, As, and Al. These lines were further used to calculate the plasma parameters, including electron temperature and electron number density. The Boltzmann plot method was used to calculate the electron temperature, and the average electron temperature was found to be 5744 ± 500 K. Furthermore, the electron number density was calculated from the Stark-broadened line profile method, and the average number density was calculated to be 6.5 × 10 17 cm -3 . It is further observed that the plasma parameters including electron temperature and electron number density have an increasing trend with laser irradiance and a decreasing trend along the plume length up to 2 mm. Finally, the elemental concentrations in terms of weight percentage using the CF-LIBS method were calculated to be Ga: 94%, Al: 4.77% and As: 1.23% for sample-1; Ga: 95.63%, Al: 1.15% and As: 3.22% for sample-2; and Ga: 97.32%, Al: 0.69% and As: 1.99% for sample-3. The certified concentrations were Ga: 95%, Al: 3% and As: 2% for sample-1; Ga: 96.05%, Al: 1% and As: 2.95% for sample-2; and Ga: 97.32%, Al: 0.69% and As: 1.99% for sample-3. The concentrations measured by CF-LIBS showed good agreement with the certified values reported by the manufacturer. These findings suggest that the CF-LIBS technique opens up an avenue for the industrial application of LIBS, where quantitative/qualitative analysis of the material is highly desirable.

Focal chondral defects of the knee occur commonly in the young, active population due to trauma. Damage can insidiously spread and lead to osteoarthritis with significant functional and socioeconomic consequences. Implants consisting of autologous chondrocytes or mesenchymal stem cells (MSC) seeded onto scaffolds have been suggested as promising therapies to restore these defects. However, the degree of integration between the implant and native cartilage still requires optimization. A PRISMA systematic review and meta-analysis was conducted using five databases (PubMed, MEDLINE, EMBASE, Web of Science, CINAHL) to identify studies that used autologous chondrocyte implants (ACI) or MSC implant therapies to repair chondral defects of the tibiofemoral joint. Data on the integration of the implant-cartilage interface, as well as outcomes of clinical scoring systems, were extracted. Most eligible studies investigated the use of ACI only. Our meta-analysis showed that, across a total of 200 patients, 64% (95% CI (51%, 75%)) achieved complete integration with native cartilage. In addition, a pooled improvement in the mean MOCART integration score was observed during post-operative follow-up (standardized mean difference: 1.16; 95% CI (0.07, 2.24), p = 0.04). All studies showed an improvement in the clinical scores. The use of a collagen-based scaffold was associated with better integration and clinical outcomes. This review demonstrated that cell-seeded scaffolds can achieve good quality integration in most patients, which improves over time and is associated with clinical improvements. A greater number of studies comparing these techniques to traditional cartilage repair methods, with more inclusion of MSC-seeded scaffolds, should allow for a standardized approach to cartilage regeneration to develop.

For the protection of civil and military armored vehicles, advanced steels are used, due to their outstanding mechanical properties, high ballistic performance, ease of manufacturing and low cost. However, after retrofitting, weight is the prominent issue. In this regard, several strategies are being proposed, which include the surface engineering of either low-thickness ballistic steels or conventional steels, in addition to new alloys and composites. Therefore, to better understand the response of such materials under various stimuli, the existing state of the art ballistic steels was utilized in this study. The aim of this study was to better understand the existing materials and their corrosion behavior. Therefore, in this connection, two thicknesses were selected, i.e., thin (6.7-7.0 mm) and thick (13.0-15.0 mm), henceforth termed as low thickness (LT) and high thickness (HT), respectively. This was followed by characterization using tensile, Charpy, micro-Vickers, nanoindentation, XRD, SEM-EDS and corrosion tests. Microstructurally, the LT samples only exhibited ε-carbide precipitates, whereas the HT samples contained both ε-carbides and Mo 2 C (molybdenum carbides). However, both samples were found to be tempered martensite with a lath morphology. Moreover, higher hardness, and lower elastic modulus and stiffness were noticed in the HT samples compared with their LT counterparts. Fractured surfaces of both of these alloys were also examined, wherein a ductile mode of fracturing was observed. Further, a corrosion study was also carried out in brine solution. The results showed a higher corrosion rate in the HT samples than that of their LT counterparts. An extensive discussion is presented in light of the observed findings.

Ganoderma lucidum P. karst is an edible fungus that is used in traditional medicine and contains triterpenoids as the major phytoconstituents. Ganoderic acids are the most abundant triterpenoids that showed pharmacological activity. As Indian varieties contain ganoderic acid H (GA-H), we aimed to prepare GA-H-based triterpenoid enriched fraction (TEF) and evaluated its pharmacokinetics, metabolomics, and stability analysis. A high-performance liquid chromatography (HPLC) method was developed to quantify GA-H in TEF and rat plasma. Based on GA-H content, a stability assessment and pharmacokinetic study of TEF were also performed. After its oral administration to rats, TEF's the metabolic pattern recognition was performed through ultra-performance liquid chromatography mass spectroscopy (UPLC-MS). The developed HPLC method was found to be simple, sensitive, precise (<15%), and accurate (>90% recovery) for the quantification of GA-H. Pharmacokinetic analysis showed that GA-H reached its maximum plasma concentration (C max 2509.9 ng/mL) within two hours and sustained quantifiable amount up to 12 h with a low elimination rate (K el ) 0.05 L/h. TEF contained ten bioavailable constituents. The prepared TEF was found to be stable for up to one year at room temperature. The prepared TEF, enriched with ganoderic acid, is stable, contains bioavailable constituents, and can be explored as phytopharmaceuticals for different pharmacological properties. Highlights: (1). Preparation of triterpenoid enriched fraction (TEF) from Ganoderma lucidum. (2). Major triterpenoid in TEF is ganoderic acid H (GA-H). (3). TEF contains several bioavailable phytoconstituents. (4). TEF (considering only GA-H) is stable for up to one year at room temperature. (5). GA-H is rapidly absorbed and has high systemic exposure.

Cartilage defects are a predisposing factor for osteoarthritis. Conventional therapies are mostly palliative and there is an interest in developing newer therapies that target the disease's progression. Mesenchymal stem cells (MSCs) have been suggested as a promising therapy to restore hyaline cartilage to cartilage defects, though the optimal cell source has remained under investigation. A PRISMA systematic review was conducted utilising five databases (MEDLINE, EMBASE, Cochrane Library, Scopus, Web of Science) which identified nineteen human studies that used adipose tissue-derived MSC (AMSC)-based therapies, including culture-expanded AMSCs and stromal vascular fraction, to treat cartilage defects. Clinical, imaging and histological outcomes, as well as other relevant details pertaining to cartilage regeneration, were extracted from each study. Pooled analysis revealed a significant improvement in WOMAC scores (mean difference: -25.52; 95%CI (-30.93, -20.10); p < 0.001), VAS scores (mean difference: -3.30; 95%CI (-3.72, -2.89); p < 0.001), KOOS scores and end point MOCART score (mean: 68.12; 95%CI (62.18, 74.05)), thus showing improvement. The studies in this review demonstrate the safety and efficacy of AMSC-based therapies for cartilage defects. Establishing standardised methods for MSC extraction and delivery, and performing studies with long follow-up should enable future high-quality research to provide the evidence needed to bring AMSC-based therapies into the market.

Metabolic disorders often lead to cardiac complications. Metabolic deregulations during diabetic conditions are linked to mitochondrial dysfunctions, which are the key contributing factors in cardiac hypertrophy. However, the underlying mechanisms involved in diabetes-induced cardiac hypertrophy are poorly understood. In the current study, we initially established a diabetic rat model by alloxan-administration, which was validated by peripheral glucose measurement. Diabetic rats displayed myocardial stiffness and fibrosis, changes in heart weight/body weight, heart weight/tibia length ratios, and enhanced size of myocytes, which altogether demonstrated the establishment of diabetic cardiac hypertrophy (DCH). Furthermore, we examined the expression of genes associated with mitochondrial signaling impairment. Our data show that the expression of PGC-1α, cytochrome c, MFN-2, and Drp-1 was deregulated. Mitochondrial-signaling impairment was further validated by redox-system dysregulation, which showed a significant increase in ROS and thiobarbituric acid reactive substances, both in serum and heart tissue, whereas the superoxide dismutase, catalase, and glutathione levels were decreased. Additionally, the expression levels of pro-apoptotic gene PUMA and stress marker GATA-4 genes were elevated, whereas ARC, PPARα, and Bcl-2 expression levels were decreased in the heart tissues of diabetic rats. Importantly, these alloxan-induced impairments were rescued by N-acetyl cysteine, ascorbic acid, and selenium treatment. This was demonstrated by the amelioration of myocardial stiffness, fibrosis, mitochondrial gene expression, lipid profile, restoration of myocyte size, reduced oxidative stress, and the activation of enzymes associated with antioxidant activities. Altogether, these data indicate that the improvement of mitochondrial dysfunction by protective agents such as N-acetyl cysteine, selenium, and ascorbic acid could rescue diabetes-associated cardiac complications, including DCH.

In this work, we studied the impacts of transmitting light, nonlinear thermal, and micropolar fluid mechanics on a wire surface coating utilizing non-Newtonian viscoelastic flow. Models with temperature-dependent variable viscosity were used. The boundary layer equations governing the flow and heat transport processes were solved using the Runge-Kutta fourth order method. A distinguished constituent of this study was the use of a porous matrix that acted as an insulator to reduce heat loss. In this paper we discuss the effects of numerous development parameters, including β0, Q,&nbsp;m,&nbsp;Ω,&nbsp;Kp, and Br (non-Newtonian parameter, heat-producing parameter, viscosity parameter, variable viscosity parameter, porosity parameter, and Brinkman number, respectively). Furthermore, the effects of two other parameters, D and M , are also discussed as they relate to velocity and temperature distributions. We observed that the velocity profiles decreased with increasing values of Kp. Fluid velocity increased as the values of M,&nbsp;Br,&nbsp;N, and D increased, while it decreased when the values of Kp, Q and D increased. For increasing values of M, the temperature profile showed increasing behavior, while Br&nbsp;and&nbsp;Q showed decreasing behavior. Furthermore, the present work is validated by comparison with HAM and previously published work, with good results.

Tendon and ligament injury poses an increasingly large burden to society. This systematic review explores whether mesenchymal stem cell-derived extracellular vesicles (MSC-EVs) can facilitate tendon/ligament repair in vivo. On 26 May 2021, a systematic search was performed on PubMed, Web of Science, Cochrane Library, Embase, to identify all studies that utilised MSC-EVs for tendon/ligament healing. Studies administering EVs isolated from human or animal-derived MSCs into in vivo models of tendon/ligament injury were included. In vitro, ex vivo, and in silico studies were excluded, and studies without a control group were excluded. Out of 383 studies identified, 11 met the inclusion criteria. Data on isolation, the characterisation of MSCs and EVs, and the in vivo findings in in vivo models were extracted. All included studies reported better tendon/ligament repair following MSC-EV treatment, but not all found improvements in every parameter measured. Biomechanics, an important index for tendon/ligament repair, was reported by only eight studies, from which evidence linking biomechanical alterations to functional improvement was weak. Nevertheless, the studies in this review showcased the safety and efficacy of MSC-EV therapy for tendon/ligament healing, by attenuating the initial inflammatory response and accelerating tendon matrix regeneration, providing a basis for potential clinical use in tendon/ligament repair.

The use of mesenchymal stromal cells (MSCs) in regenerative medicine and tissue engineering is well established, given their properties of self-renewal and differentiation. However, several studies have shown that these properties diminish with age, and understanding the pathways involved are important to provide regenerative therapies in an ageing population. In this PRISMA systematic review, we investigated the effects of chronological donor ageing on the senescence of MSCs. We identified 3023 studies after searching four databases including PubMed, Web of Science, Cochrane, and Medline. Nine studies met the inclusion and exclusion criteria and were included in the final analyses. These studies showed an increase in the expression of p21, p53, p16, ROS, and NF-κB with chronological age. This implies an activated DNA damage response (DDR), as well as increased levels of stress and inflammation in the MSCs of older donors. Additionally, highlighting the effects of an activated DDR in cells from older donors, a decrease in the expression of proliferative markers including Ki67, MAPK pathway elements, and Wnt/β-catenin pathway elements was observed. Furthermore, we found an increase in the levels of SA-β-galactosidase, a specific marker of cellular senescence. Together, these findings support an association between chronological age and MSC senescence. The precise threshold for chronological age where the reported changes become significant is yet to be defined and should form the basis for further scientific investigations. The outcomes of this review should direct further investigations into reversing the biological effects of chronological age on the MSC senescence phenotype.

During the novel coronavirus (COVID-19) pandemic, physical activity (PA) behaviors were altered worldwide due to public health measures such as "lockdown." This study described PA among adults residing in 11 countries during COVID-19 lockdown and examined factors associated with PA engagement. We conducted a cross-sectional anonymous survey among adults (≥18 years old) in 11 countries (Brazil, Bulgaria, China, India, Ireland, Malaysia, North Macedonia, Singapore, Spain, Turkey, United States). Of 11,775 participants, 63.7% were female and 52.8% were 18-34 years old. More than 40% of participants were insufficiently active (43.9%) and reported a decrease in their PA during lockdown (44.8%). Statistically significant differences were observed in (1) proportions of participants being insufficiently active, (2) level of PA, and (3) decrease in PA across the 11 countries. More stringent governmental policy responses were associated with greater likelihood of being insufficiently active during lockdown (adjusted odds ratio = 1.22, 95% confidence interval = 1.03, 1.45). Higher depression or anxiety scores were associated with greater likelihood of decreased level of PA during lockdown.We found substantial reductions in PA levels during COVID-19 lockdown across countries. Country-specific PA promotion interventions are needed during this and similar global emergencies.

Osteoarthritis (OA) is a degenerative disorder associated with cartilage loss and is a leading cause of disability around the world. In old age, the capacity of cartilage to regenerate is diminished. With an aging population, the burden of OA is set to rise. Currently, there is no definitive treatment for OA. However, cell-based therapies derived from adipose tissue are promising. A PRISMA systematic review was conducted employing four databases (MEDLINE, EMBASE, Cochrane, Web of Science) to identify all clinical studies that utilized adipose tissue derived mesenchymal stem cells (AMSCs) or stromal vascular fraction (SVF) for the treatment of knee OA. Eighteen studies were included, which met the inclusion criteria. Meta-analyses were conducted on fourteen of these studies, which all documented WOMAC scores after the administration of AMSCs. Pooled analysis revealed that cell-based treatments definitively improve WOMAC scores, post treatment. These improvements increased with time. The studies in this meta-analysis have established the safety and efficacy of both AMSC therapy and SVF therapy for knee OA in old adults and show that they reduce pain and improve knee function in symptomatic knee OA suggesting that they may be effective therapies to improve mobility in an aging population.

Despite the global impact of COVID-19, studies comparing the effects of COVID-19 on population mental health across countries are sparse. This study aimed to compare anxiety and depression symptoms during the COVID-19 lockdown among adults from 11 countries and to examine their associations with country-level COVID-19 factors and personal COVID-19 exposure. A cross-sectional survey was conducted among adults (≥18 years) in 11 countries (Brazil, Bulgaria, China, India, Ireland, North Macedonia, Malaysia, Singapore, Spain, Turkey, United States). Mental health (anxiety, depression, resilient coping, hope) and other study data were collected between June-August 2020. Of the 13,263 participants, 62.8% were female and 51.7% were 18-34 years old. Participants living in Brazil had the highest anxiety and depression symptoms while participants living in Singapore had the lowest. Greater personal COVID-19 exposure was associated with increased anxiety and depression symptoms, but country-level COVID-19 factors were not. Higher levels of hope were associated with reduced anxiety and depression; higher levels of resilient coping were associated with reduced anxiety but not depression. Substantial variations exist in anxiety and depression symptoms across countries during the COVID-19 lockdown, with personal COVID-19 exposure being a significant risk factor. Strategies that mitigate COVID-19 exposure and enhance hope and resilience may reduce anxiety and depression during global emergencies.

This paper proposes a customized convolutional neural network for crack detection in concrete structures. The proposed method is compared to four existing deep learning methods based on training data size, data heterogeneity, network complexity, and the number of epochs. The performance of the proposed convolutional neural network (CNN) model is evaluated and compared to pretrained networks, i.e., the VGG-16, VGG-19, ResNet-50, and Inception V3 models, on eight datasets of different sizes, created from two public datasets. For each model, the evaluation considered computational time, crack localization results, and classification measures, e.g., accuracy, precision, recall, and F1-score. Experimental results demonstrated that training data size and heterogeneity among data samples significantly affect model performance. All models demonstrated promising performance on a limited number of diverse training data; however, increasing the training data size and reducing diversity reduced generalization performance, and led to overfitting. The proposed customized CNN and VGG-16 models outperformed the other methods in terms of classification, localization, and computational time on a small amount of data, and the results indicate that these two models demonstrate superior crack detection and localization for concrete structures.

Marine rhodophyte polysaccharides have a wide range of described biological properties with nontoxic characteristics, and show great potential in prebiotics and the functional foods industries. However, there is a virtual lack of Gracilaria blodgettii polysaccharides (GBP) profiling and their bioactivities. This study was designed while keeping in view the lack of physical and chemical characterization of GBP. This polysaccharide was also not previously tested for any bioactivities. A linear random coil conformation was observed for GBP, which was found to be a polysaccharide. A significant sulfate ( w/w , 9.16%) and 3,6-anhydrogalactose (AHG, w/w , 17.97%) content was found in GBP. The significant difference in its setting (27.33 °C) and melting (64.33 °C) points makes it resistant to increasing heat. This, in turn, points to its utility in industrial scale processing and in enhancing the shelf-life of products under high temperatures. A radical scavenging activity of 19.80%, 25.42% and 8.80% was noted for GBP (3 mg/mL) in 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis (ABTS) and hydroxyl radical (HO) scavenging assays, respectively. Therefore, the findings suggest that Gracilaria blodgettii polysaccharides display a good antioxidant potential and may have potential applications in the functional food industry.

The lack of sentiment resources in poor resource languages poses challenges for the sentiment analysis in which machine learning is involved. Cross-lingual and semi-supervised learning approaches have been deployed to represent the most common ways that can overcome this issue. However, performance of the existing methods degrades due to the poor quality of translated resources, data sparseness and more specifically, language divergence. An integrated learning model that uses a semi-supervised and an ensembled model while utilizing the available sentiment resources to tackle language divergence related issues is proposed. Additionally, to reduce the impact of translation errors and handle instance selection problem, we propose a clustering-based bee-colony-sample selection method for the optimal selection of most distinguishing features representing the target data. To evaluate the proposed model, various experiments are conducted employing an English-Arabic cross-lingual data set. Simulations results demonstrate that the proposed model outperforms the baseline approaches in terms of classification performances. Furthermore, the statistical outcomes indicate the advantages of the proposed training data sampling and target-based feature selection to reduce the negative effect of translation errors. These results highlight the fact that the proposed approach achieves a performance that is close to in-language supervised models.

Various methods have been used to estimate the pupil location within an image or a real-time video frame in many fields. However, these methods lack the performance specifically in low-resolution images and varying background conditions. We propose a coarse-to-fine pupil localisation method using a composite of machine learning and image processing algorithms. First, a pre-trained model is employed for the facial landmark identification to extract the desired eye frames within the input image. Then, we use multi-stage convolution to find the optimal horizontal and vertical coordinates of the pupil within the identified eye frames. For this purpose, we define an adaptive kernel to deal with the varying resolution and size of input images. Furthermore, a dynamic threshold is calculated recursively for reliable identification of the best-matched candidate. We evaluated our method using various statistical and standard metrics along with a standardised distance metric that we introduce for the first time in this study. The proposed method outperforms previous works in terms of accuracy and reliability when benchmarked on multiple standard datasets. The work has diverse artificial intelligence and industrial applications including human computer interfaces, emotion recognition, psychological profiling, healthcare, and automated deception detection.

The object of this study was to demonstrate the ability of machine learning (ML) methods for the segmentation and classification of diabetic retinopathy (DR). Two-dimensional (2D) retinal fundus (RF) images were used. The datasets of DR-that is, the mild, moderate, non-proliferative, proliferative, and normal human eye ones-were acquired from 500 patients at Bahawal Victoria Hospital (BVH), Bahawalpur, Pakistan. Five hundred RF datasets (sized 256 × 256) for each DR stage and a total of 2500 (500 × 5) datasets of the five DR stages were acquired. This research introduces the novel clustering-based automated region growing framework. For texture analysis, four types of features-histogram (H), wavelet (W), co-occurrence matrix (COM) and run-length matrix (RLM)-were extracted, and various ML classifiers were employed, achieving 77.67%, 80%, 89.87%, and 96.33% classification accuracies, respectively. To improve classification accuracy, a fused hybrid-feature dataset was generated by applying the data fusion approach. From each image, 245 pieces of hybrid feature data (H, W, COM, and RLM) were observed, while 13 optimized features were selected after applying four different feature selection techniques, namely Fisher, correlation-based feature selection, mutual information, and probability of error plus average correlation. Five ML classifiers named sequential minimal optimization (SMO), logistic (Lg), multi-layer perceptron (MLP), logistic model tree (LMT), and simple logistic (SLg) were deployed on selected optimized features (using 10-fold cross-validation), and they showed considerably high classification accuracies of 98.53%, 99%, 99.66%, 99.73%, and 99.73%, respectively.

In this research work, a 3D rotating flow of carbon nanotubes (CNTs) over a porous stretchable sheet for heat and mass transfer is investigated. Kerosene oil is considered as a base liquid and two types of CNTs, (Single & Multi) WCNTs are added as the additives to the base liquid. The present analysis further comprises the combined effect of the Hall, ion-slip, and thermal radiation, along with heat generation/absorption. The appropriate ordinary differential system of equations after applying appropriate transformation is calculated. The resulting nonlinear system of equations (conservation of mass, momentum, temperature) is explained by HAM (Homotopy Analysis Method). Solution of velocities and thermal fields are obtained and discussed graphically. Expression of C f and N u are intended for both type of nanoliquids. The influences of prominent physical factors are plotted for velocities and thermal profiles using Methematica. These graphical results are qualitatively in excellent agreement with the previous published results. Also, single wall nanoparticles are found to have higher temperatures than multi wall CNTs nanoparticles.

The impact of nonlinear thermal radiations rotating with the augmentation of heat transfer flow of time-dependent single-walled carbon nanotubes is investigated. Nanofluid flow is induced by a shrinking sheet within the rotating system. The impact of viscous dissipation is taken into account. Nanofluid flow is assumed to be electrically conducting. Similarity transformations are applied to transform PDEs (partial differential equations) into ODEs (ordinary differential equations). Transformed equations are solved by the homotopy analysis method (HAM). The radiative source term is involved in the energy equation. For entropy generation, the second law of thermodynamics is applied. The Bejan number represents the current investigation of non-dimensional entropy generation due to heat transfer and fluid friction. The results obtained indicate that the thickness of the boundary layer decreases for greater values of the rotation parameter. Moreover, the unsteadiness parameter decreases the temperature profile and increases the velocity field. Skin friction and the Nusselt number are also physically and numerically analyzed.

Jevtana ® is a micellar cabazitaxel (CBZ) solution that was approved for prostate cancer in 2010, and recently, this drug has been reported for breast cancer. The purpose of this study is to evaluate the mediated delivery of CBZ via liposomes and nanoparticles (NPs) for the treatment of breast cancer and compare these with a micellar formulation that is currently in clinical use. CBZ-loaded nanocarriers were prepared with particle sizes between 70⁻110 nm, and with the sustained in vitro release of CBZ for more than 28 days. Cytotoxicity studies on MCF-7 and MDA-MB-231 cells demonstrated the toxic potential of these nanocarriers. Cellular internalization revealed that NPs and liposomes have better permeability than micelles. Cell cycle analysis and apoptosis studies on MCF-7 and MDA-MB-231 cells confirmed G2/M phase arrest as well as cell death due to apoptosis and necrosis, where formulations were found to be effective compared to a micellar CBZ solution. Results from pharmacokinetic studies revealed that there is an increased circulation half-life and mean residence time for CBZ liposomes and NPs in comparison with a micellar CBZ solution. CBZ liposomes and NPs showed a reduction in hemolysis and neutropenia in comparison with a micellar CBZ solution in rats.

This article examines the entropy analysis of magnetohydrodynamic (MHD) nanofluid flow of single and multiwall carbon nanotubes between two rotating parallel plates. The nanofluid flow is taken under the existence of Hall current and ion-slip effect. Carbon nanotubes (CNTs) are highly proficient heat transmission agents with bordering entropy generation and, thus, are considered to be a capable cooling medium. Entropy generation and Hall effect are mainly focused upon in this work. Using the appropriate similarity transformation, the central partial differential equations are changed to a system of ordinary differential equations, and an optimal approach is used for solution purposes. The resultant non-dimensional physical parameter appear in the velocity and temperature fields discussed using graphs. Also, the effect of skin fraction coefficient and Nusselt number of enclosed physical parameters are discussed using tables. It is observed that increased values of magnetic and ion-slip parameters reduce the velocity of the nanofluids and increase entropy generation. The results reveal that considering higher magnetic forces results in greater conduction mechanism.

We report the first results of functional properties of nitrogenized silver-permalloy thin films deposited on polyethylene terephthalic ester {PETE (C 10 H₈O₄) n } flexible substrates by magnetron sputtering. These new soft magnetic thin films have magnetization that is comparable to pure Ni 81 Fe 19 permalloy films. Two target compositions (Ni 76 Fe 19 Ag₅ and Ni 72 Fe 18 Ag 10 ) were used to study the effect of compositional variation and sputtering parameters, including nitrogen flow rate on the phase evolution and surface properties. Aggregate flow rate and total pressure of Ar+N₂ mixture was 60 sccm and 0.55 Pa, respectively. The distance between target and the substrate was kept at 100 mm, while using sputtering power from 100-130 W. Average film deposition rate was confirmed at around 2.05 nm/min for argon atmosphere and was reduced to 1.8 nm/min in reactive nitrogen atmosphere. X-ray diffraction, X-ray photoelectron spectroscopy, scanning electron microscopy, vibrating sample magnetometer, and contact angle measurements were used to characterize the functional properties. Nano sized character of films was confirmed by XRD and SEM. It is found that the grain size was reduced by the formation of nitride phase, which in turns enhanced the magnetization and lowers the coercivity. Magnetic field coupling efficiency limit was determined from 1.6-2 GHz frequency limit. The results of comparable magnetic performance, lowest magnetic loss, and highest surface free energy, confirming that 15 sccm nitrogen flow rate at 115 W is optimal for producing Ag-doped permalloy flexible thin films having excellent magnetic field coupling efficiency., Competing Interests: The authors declare no conflict of interest.

Liposomes are the first nano drug delivery systems that have been successfully translated into real-time clinical applications. These closed bilayer phospholipid vesicles have witnessed many technical advances in recent years since their first development in 1965. Delivery of therapeutics by liposomes alters their biodistribution profile, which further enhances the therapeutic index of various drugs. Extensive research is being carried out using these nano drug delivery systems in diverse areas including the delivery of anti-cancer, anti-fungal, anti-inflammatory drugs and therapeutic genes. The significant contribution of liposomes as drug delivery systems in the healthcare sector is known by many clinical products, e.g., Doxil ® , Ambisome ® , DepoDur™, etc. This review provides a detailed update on liposomal technologies e.g., DepoFoam™ Technology, Stealth technology, etc., the formulation aspects of clinically used products and ongoing clinical trials on liposomes.

The objective of this study was to deposit thin films on PET polymer substrate and examine the functional properties systematically. Their properties have been studied as a function of the N₂-Ar flow rates, deposition time span and Cu doping. Iron nitride film deposited on both sides exhibits ferromagnetic phases, γ'-Fe₄N and ε-Fe₃N co-existed, shows negligible magnetic anisotropy. Other samples show the evolution of N-rich (FeN, Fe₂N) and N-poor (Fe 16 N₂, Fe₃N, Fe₄N) phases under different deposition time conditions. XPS analysis and free energy calculations confirmed that co-sputtered Fe-Cu thin films are more stable than layer deposited counterparts. From VSM results it is evident that the dominant phase, changes steadily from the ferromagnetic α-Fe (N) to the paramagnetic ξ-Fe₂N with the increase of nitrogen flow rates and the ordering of the nitrogen atoms. Binding energy increases steadily from 733 eV to 740 eV with the increasing thickness of thin films from 74 nm to 94 nm. It was observed that surface energy decreases as the contact angle of glycol increases and changes the thin film surface from polar to nonpolar. TEM images indicate that cubic γ'-Fe₄N and ε-Fe₃N nano particles oriented in preferred directions dispersed uniformly in the amorphous iron nitride matrix.

The antifungal, antibacterial, and antioxidant activity of four commercial essential oils (EOs) (thyme, clove, rosemary, and tea tree) from Romanian production were studied in order to assess them as bioactive compounds for active food packaging applications. The chemical composition of the oils was determined with the Folin-Ciocâlteu method and gas chromatography coupled with mass spectrometry and flame ionization detectors, and it was found that they respect the AFNOR/ISO standard limits. The EOs were tested against three food spoilage fungi- Fusarium graminearum , Penicillium corylophilum, and Aspergillus brasiliensis -and three potential pathogenic food bacteria- Staphylococcus aureus , Escherichia coli, and Listeria monocytogenes -using the disc diffusion method. It was found that the EOs of thyme, clove, and tea tree can be used as antimicrobial agents against the tested fungi and bacteria, thyme having the highest inhibitory effect. Concerning antioxidant activity determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis 3-ethylbenzthiazoline-6-sulfonic acid (ABTS) methods, it has been established that the clove oil exhibits the highest activity because of its high phenolic content. Promising results were obtained by their incorporation into chitosan emulsions and films, which show potential for food packaging. Therefore, these essential oils could be suitable alternatives to chemical additives, satisfying the consumer demand for naturally preserved food products ensuring its safety.

The effect of carrageenans on tomato chlorotic dwarf viroid (TCDVd) replication and symptom expression was studied. Three-week-old tomato plants were spray-treated with iota(ɩ)-, lambda(λ)-, and kappa(κ)-carrageenan at 1 g·L-1 and inoculated with TCDVd after 48 h. The λ-carrageenan significantly suppressed viroid symptom expression after eight weeks of inoculation, only 28% plants showed distinctive bunchy-top symptoms as compared to the 82% in the control group. Viroid concentration was reduced in the infected shoot cuttings incubated in λ-carrageenan amended growth medium. Proteome analysis revealed that 16 tomato proteins were differentially expressed in the λ-carrageenan treated plants. Jasmonic acid related genes, allene oxide synthase (AOS) and lipoxygenase (LOX), were up-regulated in λ-carrageenan treatment during viroid infection. Taken together, our results suggest that λ-carrageenan induced tomato defense against TCDVd, which was partly jasmonic acid (JA) dependent, and that it could be explored in plant protection against viroid infection.