The population of the medicinal plant, Malabar nut (Justicia adhatoda L.) is shrinking in Dun valley due to habitat fragmentation, invasion by Lantana camara, over-exploitation, and an ...ever-increasing human population – the most important being the increasing demand on land for agriculture, industries and the urbanization. Predicting potential geographic distribution of the species is important from species and habitat restoration point of view. This paper reports the results of a study carried out in the Lesser Himalayan foothills in India (Dun valley) on potential distribution modeling for Malabar nut using Maxent model. The Worldclim bioclimatic variables, slope, aspect, elevation, and the land use/land cover (based on IRS LISS-III) data and 46 spatially well-dispersed species occurrence points were used to predict the potential distribution of J. adhatoda in ca. 1877km2 study area. Jackknife test was used to evaluate the importance of the environmental variables for predictive modeling. Maxent model was highly accurate with a statistically significant AUC value of 92.3. The approach could be promising in predicting the potential distribution of medicinal plant species and thus, can be an effective tool in species restoration and conservation planning.
A facile and eco-friendly green synthesis of silver-copper@zinc oxide (Ag–Cu@ZnO) nanocomposite using Acacia caesia flower extract and their application on catalytic reduction of toxic compounds and ...electrochemical sensing of nitrite ions are reported. The phytochemicals present in the extract were utilized for the Ag–Cu metal nanoparticles synthesis and also enhanced the binding capability between ZnO and Ag–Cu NPs. The synthesized nanocomposites were characterized by XRD, UV–Vis spectroscopy, Raman spectra, FTIR, SEM, TEM, EDX, XPS and ICP-AES for the formation of Ag–Cu NPs on ZnO. The Ag–Cu@ZnO nanocomposite showed better catalytic efficiency as compared to monometallic nanoparticles for 4-nitrophenol to 4-aminophenol conversion and Rhodamine B and Congo red dye degradation with 99% efficiency up to four cycles. The Ag–Cu@ZnO modified GC electrode showed enhanced catalytic activity towards nitrite oxidation, and it exhibited better performance compared to the other nanocomposites. An appreciable detection limit (17 μM) was achieved with excellent sensitivity for nitrite detection. The sensor was highly selective even in a many-fold higher concentration of co-existing interfering compounds. The good catalytic and electrochemical sensing is mainly ascribed due to the synergistic effect of Ag–Cu on the ZnO in the Ag–Cu@ZnO nanocomposite materials.
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•Highly dispersed Ag–Cu@ZnO nanocomposite was synthesized via a greener process.•Acacia caesia extract acts as reducing, capping and stabilizing agent for the synthesis of nanoparticles.•The Ag–Cu@ZnO showed better electrochemical sensing towards Nitrate ions.•The nanocomposites exhibit enhanced performance in the conversion of 4 nitrophenol to 4 aminophenol.•The bimetallic nanocomposite shows boosting catalytic activity on organic compounds reduction.
This review explores the impact of exercise on post-surgical recovery in breast cancer patients. Breast cancer, the most prevalent cancer globally, necessitates treatments beyond conventional ...modalities such as surgery, chemotherapy, radiotherapy, and immunotherapy. While exercise as an adjuvant therapeutic tool is not novel, it is generally accepted for improving cancer outcomes. Yet, it is not included in current treatment guidelines. This study reviews literature using the FACT-B (Functional Assessment of Cancer Therapy – Breast) tool to evaluate quality of life in breast cancer patients undergoing exercise interventions post-surgery. Despite mixed results, with some studies showing significant improvements and others indicating no notable benefits, the general consensus suggests potential advantages of integrating structured exercise programs into recovery protocols. Standardizing the use of quality of life measures like FACT-B could enhance future research and clinical practices, leading to more effective patient care strategies.
Ag-Cu monometallic and bimetallic nanoparticles were prepared directly using aqueous extract of Walsura trifoliata supported on TiO2. The extract helps in the in situ immobilization of Ag, Cu and ...Ag-Cu alloy nanoparticles with face-centered cubic structure using phytochemical compounds as template and reducing agent at ambient conditions. The aqueous extract of W. trifoliata flower acts as reducing, binding, dispersion agent and plays a major role in the synthesis of the nanocomposites which was confirmed using GC-MS. The nanocomposite were characterized using UV–Vis, FTIR, XRD, TEM, SAED, EDS, and Raman Spectra techniques. The efficiency of prepared nanocomposite on the catalytic activity for the reduction and degradation of 4-Nitrophenol (4-NP), Methyl orange (MO), and Rhodamine B (Rh B) with sodium borohydride (NaBH4) were investigated in detail. The Ag-Cu/TiO2 bimetal nanocomposite exhibit very high activity for the degradation of dyes, confirmed using UV–Vis and HPLC analysis. In addition, Ag/TiO2, Cu/TiO2 and Ag-Cu/TiO2 nanocomposites exhibit good reusability with 100% conversion efficiency of 4-NP, MO and Rh B up to 6 successive cycles. The phytogenic mediated synthesis of metal nanocatalyst supported on TiO2 makes it an ideal platform for heterogeneous catalytic process and for potential application in a wide range of fields.
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•Phytogenic synthesis methods applied for immobilization of Ag, Cu and Ag-Cu alloy on TiO2.•Phytogenic synthesis promotes the formation of reduced metal nanoparticles on TiO2.•Ag-Cu/TiO2 shown eminently active catalytic on organic pollutants degradation in few seconds.•High recyclability and reuse of catalyst.
Deep learning techniques have become crucial in the detection of brain tumors but classifying numerous images is time‐consuming and error‐prone, impacting timely diagnosis. This can hinder the ...effectiveness of these techniques in detecting brain tumors in a timely manner. To address this limitation, this study introduces a novel brain tumor detection system. The main objective is to overcome the challenges associated with acquiring a large and well‐classified dataset. The proposed approach involves generating synthetic Magnetic Resonance Imaging (MRI) images that mimic the patterns commonly found in brain MRI images. The system utilizes a dataset consisting of small images that are unbalanced in terms of class distribution. To enhance the accuracy of tumor detection, two deep learning models are employed. Using a hybrid ResNet+SE model, we capture feature distributions within unbalanced classes, creating a more balanced dataset. The second model, a tailored classifier identifies brain tumors in MRI images. The proposed method has shown promising results, achieving a high detection accuracy of 98.79%. This highlights the potential of the model as an efficient and cost‐effective system for brain tumor detection.
The following are the significant research contributions: 1. A novel hybrid ResNet+SE model has been proposed, capable of extracting detailed features from MRI datasets and highlighting essential tumor information. ResNet adopts a technique known as residual mapping for handling the issues. Indeed, of hoping every stacking layer, it directly fit to a desirable mapping where the network lets these layers to explicitly fit a residual mapping. ResNet helps in easier optimization and attains superior accuracy than prevailing networks. The integration of SqueezeNet is to reduce the hyper‐parameters and to attain better prediction. The proposed model works well compared to conventional approaches like AlexNet. 2. The research analyzed and contrasted the effectiveness of different methods, measuring their performance through various metrics, including accuracy, F‐score, precision, recall, error rate, and ROC. Furthermore, the study calculated weighted F1 values and assessed the training accuracy and loss, as well as the validation accuracy and loss. 3. The proposed ResNet+SE model is employed to provide better performance for problems like identifying the various stages of brain tumors.
Sestrins are highly conserved; stress inducible proteins that help maintain metabolic homeostasis and protect cells under stress conditions. They are up-regulated during stress and influence AMPK and ...mTOR pathways. Our objective was to find the role of Sestrin protein from Dictyostelium discoideum (Dd), a lower eukaryote where starvation stress initiates multicellular development. The single DdSesn-like gene was expressed and its endogenous functions were characterized. Both, the knockout and constitutively expressing strains were made and their involvement in starvation-induced autophagy was analyzed. Autophagic fluxes and ROS levels were also monitored. Additionally, overexpression of DdSesn decreased cell growth and showed a longer lag phase. Upon starvation both DdSesn and ROS levels increased. SesnOE showed reduced ROS levels while sesn− showed increased ROS levels when compared to the wild type. Therefore, we suggest that increased sesn expression may be beneficial in reducing ROS levels during starvation. Deletion of sesn showed reduced autophagic flux and increased p4EBP1 levels. We show that DdSesn promotes autophagy in D. discoideum upon starvation.
Purpose. The article is aimed at improving the understanding of the sociocultural profile of adult orthodontic patients and their expectations. In particular, it addresses three main aspects: the ...motivation and needs that underpin the decision to start orthodontic treatment, how it influences the patients’ daily life, and the different oral hygiene demands. Materials and Methods. An online survey was completed by 276 patients undergoing orthodontic treatment with different techniques. The questions asked concerned gender, age, type of appliance, any previous orthodontic treatments, type of any previous retainers, reasons for therapy, satisfaction, pain, problems in eating, daily number of teeth brushings and flossings before and during the treatment, perception of cost, sensation of visibility of the appliance, and if they would recommend orthodontic treatment. Results. A significant role within our sample is played by gender; 87.94% consisted of female patients out of which 72.57% wanted to improve their aesthetics, while only 54.84% of male patients cited the same reason. Invisible aligners were preferred by 67.70% of the patients due to them being considered the least painful, causing the fewest problems with eating, and the least visible. Metal braces were perceived as the less expensive treatment. Over a third of the patients (33.85%) had previously undergone orthodontic treatment, among them 54.05% wore a mobile retainer, 31.08% a fixed one, and 14.86% both. Daily tooth brushing and flossing increased during therapy with clear aligners by 48.94% and 126.39%, respectively. Conclusions. The greatest demand for orthodontic treatments comes from women, as they pay more attention to aesthetics, which makes the clear aligners the most common choice. The relapse after orthodontic treatment seems to cause a higher demand for retreatment, and oral hygiene habits significantly improve during orthodontic treatment, especially with the clear aligners.
Total knee arthroplasty (TKA) is a common surgery for osteoarthritis, with increasing prevalence expected in the near future. This systematic review and meta‐analysis compared the effectiveness of ...computerized TKA versus traditional TKA, focusing on postoperative outcomes measured by the Western Ontario and McMaster Universities osteoarthritis index (WOMAC) and the Knee Society score (KSS). A search on PubMed and Cochrane databases on November 14, 2023 for retrospective randomized controlled trials (RCTs) yielded data on WOMAC and KSS. The search strategy was predefined, and methodological quality of studies was critically appraised. Two researchers extracted data. Unpaired t‐testing assessed the mean monthly changes in KSS and WOMAC for computer‐aided versus traditional TKA. Review Manager 5.3 was used for data synthesis and analysis. Out of 729 records, five RCTs enrolling 339 patients were eligible and analyzed using a random effects meta‐analysis. The mean monthly ΔKSS score differed significantly between the traditional and computerized groups (11.47 ± 8.76 vs. 9.26 ± 6.05, respectively; p < 0.01). However, the pooled mean difference estimate showed no significant differences (D = 0.20, 95% CI = −0.53 to 0.93, p = 0.59), with high heterogeneity (I2 = 85%, p < 0.001). The mean monthly ΔWOMAC score also differed significantly (−14.18 ± 21.54 vs. −18.43 ± 20.65, respectively; p < 0.05), but again, no significant differences were found in the pooled estimate (D = 0.17, 95% CI = −0.46 to 0.79, p = 0.60), with moderate heterogeneity (I2 = 28%, p = 0.24).There is no significant difference in KSS or WOMAC outcomes between traditional and computerized TKA. The study suggests the need for further research with longer follow‐up periods, more timepoints, and a broader range of patient outcome measures to fully evaluate the advantages and disadvantages of each method.
There is no significant difference in McMaster Universities osteoarthritis index (WOMAC) and the Knee Society score (KSS) outcomes between traditional and computerized total knee arthroplasty (TKA). The study suggests the need for further research with longer follow‐up periods, more timepoints, and a broader range of patient outcome measures to fully evaluate the advantages and disadvantages of each method.
Green synthesis of silver nanoparticles-calcium alginate beads (AgNP-CA) was prepared using five different methods. The immobilization/reduction/incorporation of AgNPs on alginate biopolymer using
...Walsura trifoliata
bark extract as reducing and capping agent were confirmed by the characterization results of UV–Vis spectra, XRD, FTIR, and TEM techniques. The prepared Ag-CA nanocomposite catalyst was used for the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP) in the presence of sodium borohydride (NaBH
4
) in a liquid phase at ambient conditions. Comparatively, AgNPs-ACA (Adsorption calcium alginate) exhibited very high catalytic activity in the reduction of 4-nitrophenol within few seconds with exceptional stability, up to ten cycles without any loss in the catalytic activity. This study reports effective synthesis of AgNPs on alginate polymer beads via phytochemicals of aqueous extract of
W. trifoliata
and its excellent catalytic efficiency towards 4-nitrophenol reduction as of the practical application.
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