Expanding Global Radiotherapy Access via Telemedicine.

AIMS: Cancer is a leading cause of death globally. Over 70% of the 10 million cancer deaths worldwide in 2020 occurred in low- and middle-income countries. Radiotherapy is an important cancer treatment, used in half of cancer patients. Significant global disparities in radiotherapy access exist, with low access in low- and middle-income countries. The benefits of tele-radiotherapy in low- and middle-income countries for expanding global radiotherapy access are yet to be fully realized. In this paper, we highlight potential applications of tele-radiotherapy in expanding access to high-quality radiotherapy in developing countries. MATERIALS AND METHODS: We performed a literature search to retrieve studies involving telemedicine applications in radiotherapy to provide a comprehensive overview of the topic. PubMed database served as the main source for retrieving studies, using the following search terms: ("telemedicine", "radiotherapy", "telehealth", "remote monitoring", "oncology", and "remote training"). Additional selected papers were obtained from Web of Science, and Google Scholar using the same search terms. RESULTS: Telemedicine in radiotherapy has many applications. Virtual training could upgrade radiotherapy skills in low- and middle-income countries, enabling safe adoption of new radiotherapy techniques and quality assurance. Tele-radiotherapy consultations and patient follow-up could improve the efficiency of clinics while tele-radiotherapy planning and peer-review could enable equitable global access to radiotherapy expertise. Telemedicine could also facilitate wider global access to radiotherapy trials. While telemedicine in radiotherapy holds significant promise in improving global radiotherapy access, several barriers to its adoption exist. These include a lack of infrastructure, data security concerns, regulatory challenges, resistance from providers and patients, financial constraints, miscommunication during remote consultations, and lack of training. CONCLUSION: Tele-radiotherapy applications hold promise in providing solutions to overcome global radiotherapy access inequity but the benefits of tele-radiotherapy in low- and middle-income countries are yet to be fully realized.

A simple technical innovation to prevent needle stick injuries among dental professionals.

OBJECTIVE: Dental healthcare personnel face the potential danger of being exposed to infectious patients while administering local anesthesia injections during dental operations. This could lead to unintentional transfer of infectious diseases from patients to physicians. Although safety measures such as the One-hand-scoop technique and the use of safety syringes, plastic needle cap holders, and needles with safety caps are in place, there have been instances of needle stick injuries reported in clinics. This might be due to the lack of adherence to conventional safety measures or the impracticality of safety techniques and safety syringes. This article aims to demonstrate the utilization of dental tweezers, specifically London College tweezers or dental forceps, for the secure recapping of needles, eliminating the requirement for extra equipment or devices. SUBJECTS AND METHODS: After obtaining ethical approval (Approval No.: 024-01-2024) from the College of Dentistry, Dar Al Uloom University, 67 dental professionals, with consent for participation in the study, were included. They were requested to use dental tweezers/London College tweezers and dental extraction forceps such as maxillary anterior, mandibular anterior, and maxillary bayonet root forceps individually to recap the local anesthetic needles. The efficacy of these techniques was evaluated against the one-hand scoop technique for its ease, convenience, and reliability in preventing needle stick injuries. RESULTS: The evaluation of dental professionals regarding the ease of using dental tweezers to recap needles, compared to the one-hand scoop technique (p=0.592), maxillary bayonet root forceps (p=0.746), mandibular anterior forceps (p=0.380), and maxillary anterior forceps (p=0.808), did not yield statistically significant results. The assessment of the procedural simplicity of the one-hand scoop technique showed a satisfaction rate of over 40%, whereas the application of dental tweezers resulted in a satisfaction rate of 30%. However, the use of dental tweezers for needle recapping resulted in a satisfaction rate of over 50%, compared to a satisfaction rate of 30% for the one-handed scoop technique. CONCLUSIONS: There is no statistically significant difference in the assessment of the efficacy of dental tweezers and the one-hand scoop technique, bayonet root forceps, mandibular anterior forceps, maxillary anterior forceps, and dental tweezers for the needle capping technique. Therefore, dental forceps can be used instead of the one-handed scoop approach. The needle recapping procedure outlined in our study, aimed at preventing needle stick injuries, is simple to implement, and all dental specialties have convenient access to the required instruments.

Adsorptive removal of organic pollutants from aqueous solutions using novel GO/bentonite/MgFeAl-LTH nanocomposite.

The contamination of water with organic pollutants such as dyes and phenols is a serious environmental problem, requiring effective treatment methods. In the present study, a novel nanocomposite was synthesized by intercalating graphene oxide and bentonite clay into MgFeAl-layered triple hydroxide (GO/BENT/LTH), which was characterized using different techniques. The adsorption efficacy of the GO/BENT/LTH nanocomposite was assessed via the removal of two harmful organic water pollutants, namely methyl orange (MO) and 2-nitrophenol (2NP). The obtained results revealed that the maximum adsorption capacities (qmax) of MO and 2NP reached 3106.3 and 2063.5 mg/g, respectively, demonstrating the excellent adsorption performance of the nanocomposite. Furthermore, this study examined the effects of contact time, initial MO and 2NP concentrations, pH, and temperature of the wastewater samples on the adsorptive removal of MO and 2NP by the GO/BENT/LTH nanocomposite. The pH, zeta potential, and FTIR investigations suggested the presence of more than one adsorption mechanism. Thermodynamic investigations elucidated the exothermic nature of the adsorption of MO and 2NP onto the GO/BENT/LTH nanocomposite, with MO adsorption being more sensitive to temperature change. Additionally, regeneration studies revealed a marginal loss in the MO and 2NP removal with the repetitive use of the GO/BENT/LTH nanocomposite, demonstrating its reusability. Overall, the findings of this study reveal the promise of the GO/BENT/LTH nanocomposite for effective water decontamination.

Retraction: Ruptured Isolated Common Iliac Artery Aneurysm Masquerading as Renal Colic.

[This retracts the article DOI: 10.7759/cureus.19752.].

Multi-Disease Detection Using a Prism-Based Surface Plasmon Resonance Sensor: A TMM and FEM Approach.

This research introduces a surface plasmon resonance (SPR)-based biosensor with multilayered structures for telecommunication wavelength in order to detect multiple diseases. The malaria and the chikungunya viruses are taken into account and the presence of these viruses are determined by examining several blood components in healthy and affected phases. Here, two distinct configurations (Al-BTO-Al-MoS2 and Cu-BTO-Cu-MoS2) are proposed and contrasted for the detection of numerous viruses. The performance characteristics of this work have been analyzed using Transfer Matrix Method (TMM) method and Finite Element Method (FEM) method under angle interrogation technique. From the TMM and FEM solutions, it is evident that the Al-BTO-Al-MoS2 structure provides the highest sensitivities of ~270 deg./RIU for malaria and ~262 deg./RIU for chikungunya viruses, with satisfactory detection accuracy of ~1.10 for malaria, ~1.64 for chikungunya, and quality factor of ~204.40 for malaria, ~208.20 for chikungunya. In addition, the Cu-BTO-Cu MoS2 structure offers the highest sensitivities of ~310 deg./RIU for malaria and ~298 deg./RIU for chikungunya, with satisfactory detection accuracy of ~0.40 for malaria, ~0.58 for chikungunya, and quality factor of ~89.85 for malaria, ~86.38 for chikungunya viruses. Therefore, the performance of the proposed sensors is analyzed using two distinct methods and gives around similar results. In a sum, this research could be utilized as a theoretical foundation and first step in the development of a real sensor.

Ensemble meta machine learning for predicting the adsorption of anionic and cationic dyes from aqueous solutions using Polymer/graphene/clay/MgFeAl-LTH nanocomposite.

Adsorption is one of the most promising wastewater treatment methods due to its simplicity and efficacy at ambient temperature and pressure. However, the technical and economic feasibility of this process largely depends on the performance of the utilized adsorbents. In this study, a promising adsorbent made of polyethyleneimine, graphene oxide (GO), bentonite, and MgFeAl-layered triple hydroxide (MgFeAl-LTH) has been synthesized and characterized. The results revealed that the synthesized nanocomposite (abbreviated as PGB-LTH) possesses good porosity and crystallinity. The adsorption performance of the PGB-LTH nanocomposite towards two harmful water pollutants (i.e., methyl orange (MO) and crystal violet (CV)) was investigated, and the results revealed that the nanocomposite outperforms its parental materials (i.e., GO, bentonite, and MgFeAl-LTH). The maximum adsorption capacity (qmax) of MO and CV onto the nanocomposite could reach 1666.7 and 1250.0 mg/g, respectively, as predicted using the Langmuir adsorption isotherm. Additionally, the PGB-LTH nanocomposite is highly reusable with an insignificant decline in performance upon repetitive use. In terms of thermodynamics, MO adsorption onto the nanocomposite is exothermic while CV adsorption is endothermic despite that both dyes adsorb spontaneously as revealed by the negative values of the Gibbs free energy change at all the examined temperatures. The generated adsorption data were utilized for constructing and assessing ensemble meta-machine learning techniques aimed at cost-effective simulation and prediction of the proposed adsorption method. Bagging and boosting methods were developed and evaluated intensively using the obtained adsorption data. The Extra Trees model achieved promising results as evidenced by the high correlation coefficient of 99% as well as low computed RMSE and MAE errors of 11.42 and 5.11, respectively, during the testing phase. These results demonstrate the model strong capability to effectively simulate and predict the adsorption process in question.

Impact of maternal topiramate ingestion on ossification of skull and appendicular bones in rat fetuses.

The skull and appendicular bones are derived from different embryological sources during their development. The impact of prenatal exposure of topiramate on ossification of these bones is not adequately studied. The goal of this study was to assess the ossification patterns of the craniofacial bones and bones of the forelimbs and hindlimbs in 20-day-old rat fetuses after maternal exposure to topiramate at doses equivalent to human therapeutic doses. Three groups of Sprague-Dawley pregnant rats were used: control, topiramate 50mg/kg/day (T50) and topiramate 100mg/kg/day (T100). Topiramate was given by oral gavage from day 6 to day19 of gestation. Ossification was evaluated in the bones of 20 days fetuses after staining with Alizarin red. Results showed a significant reduction in complete ossified centers of the metacarpal, metatarsal and craniofacial bones in topiramate-exposed fetuses at both doses when compared to the control group. Also, a significant decrease in the length of ossified part of the long bones of the forelimbs and hindlimbs in topiramate-exposed fetuses at both doses was noted when compared to the control group. Crown-rump length and fetal weight were significantly decreased in topiramate treated groups compared to the control group. In all examined groups, there was a positive correlation between the crown-rump length and the lengths of humerus and femur. No abnormalities in the ossified bones and no significant changes in their ossification pattern were observed between the treated groups. In conclusion, prenatal administration of topiramate in doses equivalent to human therapeutic doses delayed ossification and development of craniofacial and appendicular bones in rat fetuses and their effects are not dose dependent at doses investigated. The implications of these findings in women who require topiramate therapy in pregnancy merit further evaluation.

The Cross Talk Between Psoriasis, Obesity, and Dyslipidemia: A Meta-Analysis.

Although psoriasis is a multi-organ disease, it is usually managed as a skin disease, ignoring its associated serious comorbidities. This meta-analysis aimed to investigate the relationship between psoriasis, dyslipidemia, and obesity. Two authors independently searched three databases (PubMed, Medical Literature Analysis and Retrieval System Online (MEDLINE), The Cochrane Library, and Google Scholar). The search was set for articles published in the English language during the period from January 2013 to August 2023. The keywords "psoriasis", "hypercholesterolemia", "dyslipidemia", "low-density lipoproteins", "high body mass index", and "obesity", were used. Out of the 145 full texts reviewed, only seven studies fulfilled the inclusion and exclusion criteria (773,761 participants and 196,593 events). Psoriasis was associated with dyslipidemia and obesity (odds ratio (OR)=1.63, 95% CI: 1.42-1.88 and OR=1.70, 95% CI: 1.43-2.02), respectively, with significant heterogeneity (98% and 97%, respectively). Dyslipidemia and obesity were significant psoriasis comorbidities; a broader approach, viewing psoriasis as a multi-organ disease, is recommended for optimal treatment and outcomes.

Solitary Osteochondroma at Unusual Sites: A Case Report and Literature Review.

Osteochondromas (OCs) are bone lesions composed of cartilaginous and medullary bone capped with hyaline cartilage. OCs result from the separation of epiphyseal growth plate cartilage, pushing through the periosteal bone cuff. They commonly appear as pedunculated or sessile masses in the metaphysis of long bones and are the most common benign bone tumors. While rare in the scapula, OCs can occur there. Symptoms may arise from fractures, osseous abnormalities, or potential malignant transformation, especially in the presence of hereditary multiple exostoses (HME). The estimated rate of malignant transformation in solitary lesions is 1%, whereas in hereditary multiple OCs, it can reach up to 3-5%. We report a case of a 10-year-old female who presented with a gradually progressive swelling on the back of her right scapula. This progressive growth has been observed over the course of the past two years accompanied by mild pain. The pain was intermittent and did not affect her daily activities. On examination, a hard, tender, non-mobile swelling of approximately 2 × 2 cm was found over the right scapula. The patient had a normal range of motion in the shoulder and scapulothoracic regions. In conclusion, since solitary scapular OCs are extremely rare, they are quite common when associated with HME. This study aimed to increase awareness of the unusual site of OCs. Furthermore, we have included a full account of the surgical therapy we administered to this patient in order to assist future surgeons who may come across similar conditions.

BOO-ST and CBCEC: two novel hybrid machine learning methods aim to reduce the mortality of heart failure patients.

Heart failure (HF) is a leading cause of mortality worldwide. Machine learning (ML) approaches have shown potential as an early detection tool for improving patient outcomes. Enhancing the effectiveness and clinical applicability of the ML model necessitates training an efficient classifier with a diverse set of high-quality datasets. Hence, we proposed two novel hybrid ML methods ((a) consisting of Boosting, SMOTE, and Tomek links (BOO-ST); (b) combining the best-performing conventional classifier with ensemble classifiers (CBCEC)) to serve as an efficient early warning system for HF mortality. The BOO-ST was introduced to tackle the challenge of class imbalance, while CBCEC was responsible for training the processed and selected features derived from the Feature Importance (FI) and Information Gain (IG) feature selection techniques. We also conducted an explicit and intuitive comprehension to explore the impact of potential characteristics correlating with the fatality cases of HF. The experimental results demonstrated the proposed classifier CBCEC showcases a significant accuracy of 93.67% in terms of providing the early forecasting of HF mortality. Therefore, we can reveal that our proposed aspects (BOO-ST and CBCEC) can be able to play a crucial role in preventing the death rate of HF and reducing stress in the healthcare sector.

Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches.

Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and interconnection still need to be better understood. Thus, this study aims to detect common differential genes and potential hub genes (HubGs), emphasizing their actions, signaling pathways, regulatory biomarkers for diagnosing RD and candidate drugs for treating RD. In this paper we used integrated bioinformatics approaches (such as, gene ontology (GO) and KEGG pathway enrichment analysis, molecular docking, molecular dynamic simulation and network-based molecular interaction analysis). We discovered 73 common DEGs (CDEGs) and ten HubGs (ATAD2B, PPP1CB, FOXO1, AKT3, BCR, PDE4D, ITGB1, PCBP2, CD44 and SMARCA2). Several significant functions and signaling pathways were strongly related to RD. We recognized six transcription factor (TF) proteins (FOXC1, GATA2, FOXL1, YY1, POU2F2 and HINFP) and five microRNAs (hsa-mir-218-5p, hsa-mir-335-5p, hsa-mir-16-5p, hsa-mir-106b-5p and hsa-mir-15b-5p) as the important transcription and post-transcription regulators of RD. Ten HubGs and six major TF proteins were considered drug-specific receptors. Their binding energy analysis study was carried out with the 63 drug agents detected from network analysis. Finally, the five complexes (the PDE4D-benzo[a]pyrene, SMARCA2-benzo[a]pyrene, HINFP-benzo[a]pyrene, CD44-ketotifen and ATAD2B-ponatinib) were selected for RD based on their strong binding affinity scores and stable performance as the most probable repurposable protein-drug complexes. We believe our findings will give readers, wet-lab scientists, and pharmaceuticals a thorough grasp of the biology behind RD.

Perspectives and challenges in lip rejuvenation: a systematic review.

OBJECTIVE: There is an abundance of information on facelifts, blepharoplasties, rhinoplasty, and other cosmetic surgical procedures for the upper third of the face, but little is known about perioral lip rejuvenation. The aim of this article is to examine the existing literature on lip rejuvenation and perioral procedures related to lip rejuvenation. Additionally, this article aims to highlight the importance of addressing perioral areas alongside lip rejuvenation procedures, rather than solely focusing on lip rejuvenation. We also discussed the extensive procedures and materials used for lip rejuvenation, such as hyaluronic acid, botulinum toxin A, abobotulinum, onabotulinum, incobotulinum, prabobotulinum, fat grafts, silicone fillers, human collagen, collagen stimulating procedures such as derma pens and derma rolls, radiation frequency, stem cells, and plasma therapy, as well as the underlying factors that contribute to varying success rates. MATERIALS AND METHODS: A thorough literature search was done using PubMed, Cochrane, Ebsco search, Google Scholar, Scopus, and Web of Science for the articles pertaining to facial and lip cosmetic surgeries 1995-2020. Keywords for the search included anatomy of the face, facial aging, perioral areas, lip rejuvenation, botox, grafts, facelift, plastic surgery, stem cell therapy, plasma treatment, and cosmetic surgery. RESULTS: 37 articles met the study criteria. 14 out of 37 studies included procedures for lip and perioral region rejuvenation. The remaining 23 studies either involved lip procedures alone or lip procedures in conjunction with facial cosmetic procedures. Lip rejuvenation with perioral enhancement with hyaluronic acid gel demonstrated a 94.3% improvement on the lip fullness scale (LFS) one month after re-treatment. The amalgamation of lip and perioral region rejuvenation produces a synergistic effect. Whereas, sole lip rejuvenation procedures showed short-term results with less patient satisfaction, calling for secondary lip rejuvenation procedures. It was also observed that hyaluronic acid was the most commonly used agent for lip rejuvenation procedures with minimal or no side effects. CONCLUSIONS: In conjunction with perioral rejuvenation, lip rejuvenation procedures produce more aesthetically appealing results. However, any cosmetic surgical or non-surgical procedure is limited by the nature and composition of the products used. The use of FDA-approved products for rejuvenation is strongly advised to avoid undesirable side effects. Further extensive research is required on the long-term outcomes and adverse effects of stem cell transplants, such as tumor development.

Systems biology approach discovers comorbidity interaction of Parkinson's disease with psychiatric disorders utilizing brain transcriptome.

Several studies found that most patients with Parkinson's disorder (PD) appear to have psychiatric symptoms such as depression, anxiety, hallucination, delusion, and cognitive dysfunction. Therefore, recognizing these psychiatrically symptoms of PD patients is crucial for both symptomatic therapy and better knowledge of the pathophysiology of PD. In order to address this issue, we created a bioinformatics framework to determine the effects of PD mRNA expression on understanding its relationship with psychiatric symptoms in PD patients. We have discovered a significant overlap between the sets of differentially expressed genes from PD exposed tissue and psychiatric disordered tissues using RNA-seq datasets. We have chosen Bipolar disorder and Schizophrenia as psychiatric disorders in our study. A number of significant correlations between PD and the occurrence of psychiatric diseases were also found by gene set enrichment analysis, investigations of the protein-protein interaction network, gene regulatory network, and protein-chemical agent interaction network. We anticipate that the results of this pathogenetic study will provide crucial information for understanding the intricate relationship between PD and psychiatric diseases.

Neonatal Septic Arthritis of the Hip: A Case Report.

Neonatal septic arthritis is a bacterial infection that, if not identified and treated right away, can affect human joints and result in osteonecrosis, joint destruction, and permanent abnormalities. Around 0.3 out of every 1,000 live births are impacted by septic arthritis worldwide. Although there is very little available data on the newborn population, we present a novel case of neonatal hip septic arthritis that was presented to our hospital and was successfully treated with surgical irrigation and debridement through arthrotomy with the Smith-Petersen approach in addition to antibiotics, despite its early vague presentation and lack of complications. Thus, it is crucial to clinically and radiologically evaluate neonates presenting with obscure symptoms and signs to prevent future disabilities and complications resulting from septic arthritis.

An Explainable EEG-Based Human Activity Recognition Model Using Machine-Learning Approach and LIME.

Electroencephalography (EEG) is a non-invasive method employed to discern human behaviors by monitoring the neurological responses during cognitive and motor tasks. Machine learning (ML) represents a promising tool for the recognition of human activities (HAR), and eXplainable artificial intelligence (XAI) can elucidate the role of EEG features in ML-based HAR models. The primary objective of this investigation is to investigate the feasibility of an EEG-based ML model for categorizing everyday activities, such as resting, motor, and cognitive tasks, and interpreting models clinically through XAI techniques to explicate the EEG features that contribute the most to different HAR states. The study involved an examination of 75 healthy individuals with no prior diagnosis of neurological disorders. EEG recordings were obtained during the resting state, as well as two motor control states (walking and working tasks), and a cognition state (reading task). Electrodes were placed in specific regions of the brain, including the frontal, central, temporal, and occipital lobes (Fz, C1, C2, T7, T8, Oz). Several ML models were trained using EEG data for activity recognition and LIME (Local Interpretable Model-Agnostic Explanations) was employed for interpreting clinically the most influential EEG spectral features in HAR models. The classification results of the HAR models, particularly the Random Forest and Gradient Boosting models, demonstrated outstanding performances in distinguishing the analyzed human activities. The ML models exhibited alignment with EEG spectral bands in the recognition of human activity, a finding supported by the XAI explanations. To sum up, incorporating eXplainable Artificial Intelligence (XAI) into Human Activity Recognition (HAR) studies may improve activity monitoring for patient recovery, motor imagery, the healthcare metaverse, and clinical virtual reality settings.

FP-CNN: Fuzzy pooling-based convolutional neural network for lung ultrasound image classification with explainable AI.

The COVID-19 pandemic wreaks havoc on healthcare systems all across the world. In pandemic scenarios like COVID-19, the applicability of diagnostic modalities is crucial in medical diagnosis, where non-invasive ultrasound imaging has the potential to be a useful biomarker. This research develops a computer-assisted intelligent methodology for ultrasound lung image classification by utilizing a fuzzy pooling-based convolutional neural network FP-CNN with underlying evidence of particular decisions. The fuzzy-pooling method finds better representative features for ultrasound image classification. The FPCNN model categorizes ultrasound images into one of three classes: covid, disease-free (normal), and pneumonia. Explanations of diagnostic decisions are crucial to ensure the fairness of an intelligent system. This research has used Shapley Additive Explanation (SHAP) to explain the prediction of the FP-CNN models. The prediction of the black-box model is illustrated using the SHAP explanation of the intermediate layers of the black-box model. To determine the most effective model, we have tested different state-of-the-art convolutional neural network architectures with various training strategies, including fine-tuned models, single-layer fuzzy pooling models, and fuzzy pooling at all pooling layers. Among different architectures, the Xception model with all pooling layers having fuzzy pooling achieves the best classification results of 97.2% accuracy. We hope our proposed method will be helpful for the clinical diagnosis of covid-19 from lung ultrasound (LUS) images.

WheatSpikeNet: an improved wheat spike segmentation model for accurate estimation from field imaging.

Phenotyping is used in plant breeding to identify genotypes with desirable characteristics, such as drought tolerance, disease resistance, and high-yield potentials. It may also be used to evaluate the effect of environmental circumstances, such as drought, heat, and salt, on plant growth and development. Wheat spike density measure is one of the most important agronomic factors relating to wheat phenotyping. Nonetheless, due to the diversity of wheat field environments, fast and accurate identification for counting wheat spikes remains one of the challenges. This study proposes a meticulously curated and annotated dataset, named as SPIKE-segm, taken from the publicly accessible SPIKE dataset, and an optimal instance segmentation approach named as WheatSpikeNet for segmenting and counting wheat spikes from field imagery. The proposed method is based on the well-known Cascade Mask RCNN architecture with model enhancements and hyperparameter tuning to provide state-of-the-art detection and segmentation performance. A comprehensive ablation analysis incorporating many architectural components of the model was performed to determine the most efficient version. In addition, the model's hyperparameters were fine-tuned by conducting several empirical tests. ResNet50 with Deformable Convolution Network (DCN) as the backbone architecture for feature extraction, Generic RoI Extractor (GRoIE) for RoI pooling, and Side Aware Boundary Localization (SABL) for wheat spike localization comprises the final instance segmentation model. With bbox and mask mean average precision (mAP) scores of 0.9303 and 0.9416, respectively, on the test set, the proposed model achieved superior performance on the challenging SPIKE datasets. Furthermore, in comparison with other existing state-of-the-art methods, the proposed model achieved up to a 0.41% improvement of mAP in spike detection and a significant improvement of 3.46% of mAP in the segmentation tasks that will lead us to an appropriate yield estimation from wheat plants.

An Up-to-Date Review on the Remediation of Dyes and Phenolic Compounds from Wastewaters Using Enzymes Immobilized on Emerging and Nanostructured Materials: Promises and Challenges.

Addressing the critical issue of water pollution, this review article emphasizes the need to remove hazardous dyes and phenolic compounds from wastewater. These pollutants pose severe risks due to their toxic, mutagenic, and carcinogenic properties. The study explores various techniques for the remediation of organic contaminants from wastewater, including an enzymatic approach. A significant challenge in enzymatic wastewater treatment is the loss of enzyme activity and difficulty in recovery post-treatment. To mitigate these issues, this review examines the strategy of immobilizing enzymes on newly developed nanostructured materials like graphene, carbon nanotubes (CNTs), and metal-organic frameworks (MOFs). These materials offer high surface areas, excellent porosity, and ample anchoring sites for effective enzyme immobilization. The review evaluates recent research on enzyme immobilization on these supports and their applications in biocatalytic nanoparticles. It also analyzes the impact of operational factors (e.g., time, pH, and temperature) on dye and phenolic compound removal from wastewater using these enzymes. Despite promising outcomes, this review acknowledges the challenges for large-scale implementation and offers recommendations for future research to tackle these obstacles. This review concludes by suggesting that enzyme immobilization on these emerging materials could present a sustainable, environmentally friendly solution to the escalating water pollution crisis.

Effect of the molar ratio of (Ni2+ and Fe3+) on the magnetic, optical and antibacterial properties of ternary metal oxide CdO-NiO-Fe2O3 nanocomposites.

In this work, the effect of the molar ratio of (Ni2+ and Fe3+) on the properties of CdO-NiO-Fe2O3 nanocomposites was investigated. The synthesis of CdO-NiO-Fe2O3 nanocomposites was carried out by self-combustion. XRD, UV-Vis, PL and VSM were used to describe the physical properties of the materials. The results showed significant progress in structural and optical properties supporting antibacterial activity. For all samples, the particle size decreased from 28.96 to 24.95 nm with increasing Ni2+ content and decreasing Fe3+ content, as shown by the XRD pattern, which also shows the crystal structure of cubic CdO, cubic NiO, and cubic γ-Fe2O3 spinel. The Ni2+ and Fe3+ contents in the CdO-NiO-Fe2O3 nanocomposites have also been shown to enhance the ferromagnetic properties. Due to the significant coupling between Fe2O3 and NiO, the coercivity Hc values of the samples increase from 66.4 to 266 Oe. The potential of the nanocomposites for antibacterial activity was investigated against Gram-positive (Staphylococcus aureus) and Gram-negative (Pseudomonas aeruginosa, Escherichia coli, and Moraxella catarrhalis) bacteria. Comparison of P. aeruginosa with E. coli, S. aureus and M. catarrhalis showed that it has a stronger antibacterial activity with a ZOI of 25 mm.

Stem Cell-Based Tissue Engineering for Cleft Defects: Systematic Review and Meta-Analysis.

This study aimed to analyze the efficacy of stem cell-based tissue engineering for the treatment of alveolar cleft (AC) and cleft palate (CP) defects in animal models.Systematic review and meta-analysis.Preclinical studies on alveolar cleft repair in maxillofacial practice.Electronic search was performed using PubMed, Embase, and Cochrane databases. Pre-clinical studies, where stem cell-based tissue engineering was used in the reconstruction of AC and CP in animal models were included. Quality of the selected articles was evaluated using SYRCLE (SYstematic Review Centre for Laboratory animal Experimentation).Review of alveolar cleft bone augmentation interventions in preclinical models.Outcome parameters registered were new bone formation (NBF) and/or bone mineral density (BMD).Thirteen large and twelve small animal studies on AC (21) and CP (4) reconstructions were included. Studies had an unclear-to-high risk of bias. Bone marrow mesenchymal stem cells were the most widely used cell source. Meta-analyses for AC indicated non-significant benefits in favor of: (1) scaffold + cells over scaffold-only (NBF P = .13); and (2) scaffold + cells over empty control (NBF P = .66; BMD P = .31). Interestingly, dog studies using regenerative grafts showed similar to superior bone formation compared to autografts. Meta analysis for the CP group was not possible.AC and CP reconstructions are enhanced by addition of osteogenic cells to biomaterials. Directions and estimates of treatment effect are useful to predict therapeutic efficacy and guide future clinical trials of bone tissue engineering.