Biomedical Promise of Aspergillus Flavus-Biosynthesized Selenium Nanoparticles: A Green Synthesis Approach to Antiviral, Anticancer, Anti-Biofilm, and Antibacterial Applications.

This study utilized Aspergillus flavus to produce selenium nanoparticles (Se-NPs) in an environmentally friendly and ecologically sustainable manner, targeting several medicinal applications. These biosynthesized Se-NPs were meticulously characterized using X-ray diffraction (XRD), Fourier-transform infrared (FT-IR) spectroscopy, transmission electron microscope (TEM), and UV-visible spectroscopy (UV), revealing their spherical shape and size ranging between 28 and 78 nm. We conducted further testing of Se-NPs to evaluate their potential for biological applications, including antiviral, anticancer, antibacterial, antioxidant, and antibiofilm activities. The results indicate that biosynthesized Se-NPs could be effective against various pathogens, including Salmonella typhimurium (ATCC 14028), Bacillus pumilus (ATCC 14884), Staphylococcus aureus (ATCC 6538), Clostridium sporogenes (ATCC 19404), Escherichia coli (ATCC 8739), and Bacillus subtilis (ATCC 6633). Additionally, the biosynthesized Se-NPs exhibited anticancer activity against three cell lines: pancreatic carcinoma (PANC1), cervical cancer (Hela), and colorectal adenocarcinoma (Caco-2), with IC50 values of 177, 208, and 216 µg/mL, respectively. The nanoparticles demonstrated antiviral activity against HSV-1 and HAV, achieving inhibition rates of 66.4% and 15.1%, respectively, at the maximum non-toxic concentration, while also displaying antibiofilm and antioxidant properties. In conclusion, the biosynthesized Se-NPs by A. flavus present a promising avenue for various biomedical applications with safe usage.

Advanced OCTA imaging segmentation: Unsupervised, non-linear retinal vessel detection using modified self-organizing maps and joint MGRF modeling.

BACKGROUND AND OBJECTIVE: This paper proposes a fully automated and unsupervised stochastic segmentation approach using two-level joint Markov-Gibbs Random Field (MGRF) to detect the vascular system from retinal Optical Coherence Tomography Angiography (OCTA) images, which is a critical step in developing Computer-Aided Diagnosis (CAD) systems for detecting retinal diseases. METHODS: Using a new probabilistic model based on a Linear Combination of Discrete Gaussian (LCDG), the first level models the appearance of OCTA images and their spatially smoothed images. The parameters of the LCDG model are estimated using a modified Expectation Maximization (EM) algorithm. The second level models the maps of OCTA images, including the vascular system and other retina tissues, using MGRF with analytically estimated parameters from the input images. The proposed segmentation approach employs modified self-organizing maps as a MAP-based optimizer maximizing the joint likelihood and handles the Joint MGRF model in a new, unsupervised way. This approach deviates from traditional stochastic optimization approaches and leverages non-linear optimization to achieve more accurate segmentation results. RESULTS: The proposed segmentation framework is evaluated quantitatively on a dataset of 204 subjects. Achieving 0.92 ± 0.03 Dice similarity coefficient, 0.69 ± 0.25 95-percentile bidirectional Hausdorff distance, and 0.93 ± 0.03 accuracy, confirms the superior performance of the proposed approach. CONCLUSIONS: The conclusions drawn from the study highlight the superior performance of the proposed unsupervised and fully automated segmentation approach in detecting the vascular system from OCTA images. This approach not only deviates from traditional methods but also achieves more accurate segmentation results, demonstrating its potential in aiding the development of CAD systems for detecting retinal diseases.

Precise Prostate Cancer Assessment Using IVIM-Based Parametric Estimation of Blood Diffusion from DW-MRI.

Prostate cancer is a significant health concern with high mortality rates and substantial economic impact. Early detection plays a crucial role in improving patient outcomes. This study introduces a non-invasive computer-aided diagnosis (CAD) system that leverages intravoxel incoherent motion (IVIM) parameters for the detection and diagnosis of prostate cancer (PCa). IVIM imaging enables the differentiation of water molecule diffusion within capillaries and outside vessels, offering valuable insights into tumor characteristics. The proposed approach utilizes a two-step segmentation approach through the use of three U-Net architectures for extracting tumor-containing regions of interest (ROIs) from the segmented images. The performance of the CAD system is thoroughly evaluated, considering the optimal classifier and IVIM parameters for differentiation and comparing the diagnostic value of IVIM parameters with the commonly used apparent diffusion coefficient (ADC). The results demonstrate that the combination of central zone (CZ) and peripheral zone (PZ) features with the Random Forest Classifier (RFC) yields the best performance. The CAD system achieves an accuracy of 84.08% and a balanced accuracy of 82.60%. This combination showcases high sensitivity (93.24%) and reasonable specificity (71.96%), along with good precision (81.48%) and F1 score (86.96%). These findings highlight the effectiveness of the proposed CAD system in accurately segmenting and diagnosing PCa. This study represents a significant advancement in non-invasive methods for early detection and diagnosis of PCa, showcasing the potential of IVIM parameters in combination with machine learning techniques. This developed solution has the potential to revolutionize PCa diagnosis, leading to improved patient outcomes and reduced healthcare costs.

Assessing the ecological security of the Three Gorges reservoir complex ecosystem based on the improved three-dimensional emergy ecological footprint model.

The ecological security (ES) of the reservoir complex ecosystem (RCE) is one of the critical components of watershed water security and sustainable development. Hence, accurately assessing the ES of the RCE is of utmost importance. This study proposed a novel ecological security assessment model based on the improved three-dimensional emergy ecological footprint (ESM-IEEF3D), which integrated various emergy flows during the RCE's construction and operation into a three-dimensional emergy ecological footprint (EEF3D) calculation account. The Three Gorges Project (TGP) is selected as a case study to evaluate the ES from 1993 to 2022 comprehensively. The results showed that the Three Gorges RCE mainly showed an ecological remainder state, and the inflow runoff enormously promoted the TGP's sustainability. The EEF3D indicated a fluctuation decrease trend with a mean value of 7.18 × 102 ha, illustrating that TGP's ecological security and sustainability levels are gradually improving. Regarding the ES evaluation indicators, the TGP's resource dependency and ecological pressure on the natural ecosystem and the external socio-economic system are steadily relieved. Furthermore, the Three Gorges RCE's resource utilization condition is safe, the structural characteristics are healthy, and the eco-economic coordination degree is continuously enlightening. Finally, applicable policy implications for improving the ecological security of Three Gorges RCE were provided. This study helps to understand the complex relationship between humans and ecosystems. It provides a novel framework to be used as an evaluation index and policy insights for hydropower ecological security and sustainable development.

The efficacy of simultaneous successive classic and variant infectious bronchitis virus vaccines versus circulating variant II Egyptian field virus.

Background: Being a ubiquitous, highly contagious virus with a continuous mutation and a large number of evolutions worldwide, the infectious bronchitis virus (IBV) continues to wreak problems among Egyptian chickens and generate economic losses. The commonly applied IBV vaccination protocols in broilers include alternatives to classic and/or variant attenuated live virus vaccines. Aim: The current study targeted to assess the protective efficacy of concurrent and successive Ma5 and 4/91 vaccine strain regimens against the field variant II IBV strain (IBV-EGY-ZU/Ck-127/2021) in chickens. Methods: Commercial broiler chickens were vaccinated with Ma5 and 4/91 strains simultaneously at 1 and 14 days of age. The evaluation parameters included clinical protection and humoral and early innate immunity aspects in the renal tissues of vaccinated and infected birds. Results: The vaccine regimen ameliorated the clinical and histopathological lesions against variant II IBV and enhanced body gain as well as succeeded in preventing tracheal shedding and minimizing cloacal shedding of the field virus. The IL-1ß mRNA gene expression was evident as early as 24 hours, with highly significant upregulation at 48 hours post vaccination and 24 hours post challenge (PC) in vaccinated birds. Remarkable upregulation was observed in oligoadenylate synthetases (OAS) expression 48 hours PC in vaccinated and unvaccinated infected birds. The vaccinated birds developed a significant antibody titer of 704.0 ± 111.98 at 28 days of age, with a consistent antibody titer increase after the challenge. Conclusion: Overall, a combination of heterologous protectotype commercial vaccines achieved good protection against the Egyptian variant II IBV strain. This vaccine program could be an effective protocol against the threat posed by IBV viruses circulating in the Egyptian field.

Evaluating the Effect of Claytone-EM on the Performance of Oil-Based Drilling Fluids.

This study provides a detailed characterization and evaluation of Claytone-EM as a rheological additive to enhance the performance of oil-based drilling fluids (OBDFs) under high-pressure, high-temperature (HPHT) conditions. It also offers a comparative evaluation of the effectiveness of Claytone-EM with an existing organoclay, analyzing their mineral and chemical compositions, morphologies, and particle sizes. A series of experiments are performed to evaluate Claytone-EM's influence on crucial drilling mud properties, such as mud density, electrical stability, sagging tendency, rheology, viscoelastic properties, and filtration properties, to formulate a stable and high-performing OBDF. Results indicated that Claytone-EM had no significant impact on mud density but remarkably enhanced emulsion stability. Claytone-EM effectively mitigated sagging issues under both static and dynamic conditions, leading to improvements in the plastic viscosity (PV), yield point (YP), apparent viscosity (AV), and YP/PV ratio. The PV, YP, AV, and YP/PV ratios were improved by 11, 85, 28, and 66% increments, respectively, compared with those of the drilling fluid formulated with MC-TONE. The addition of Claytone-EM resulted in enhancing gel strength and improving the filtration properties of the drilling fluid. The filtration volume was reduced by 2% from 5.0 to 4.9 cm3, and the filter cake thickness had a 13% reduction from 2.60 to 2.26 mm. These findings highlight Claytone-EM as a valuable additive for enhancing OBDF performance, particularly under challenging HPHT conditions. Its ability to provide emulsion stability, reduce static and dynamic sag, and control filtration holds the potential to enhance drilling operations, minimize downtime, and bolster wellbore stability. This study acknowledges certain limitations, including its temperature range, which could benefit from exploration at extreme temperatures. Additionally, the absence of flow experiments limits a comprehensive understanding of sag effects, and further research and field-scale evaluations are recommended to validate and optimize the application of Claytone-EM in OBDFs.

Unravelling the Antimicrobial, Antibiofilm, Suppressing Fibronectin Binding Protein A (fnba) and cna Virulence Genes, Anti-Inflammatory and Antioxidant Potential of Biosynthesized Solanum lycopersicum Silver Nanoparticles.

Background and Objectives: Urinary tract infections [UTIs] are considered the third most known risk of infection in human health around the world. There is increasing appreciation for the pathogenicity of Gram-positive and Gram-negative strains in UTIs, aside from fungal infection, as they have numerous virulence factors. Materials and Methods: In this study, fifty urine samples were collected from patients suffering from UTI. Among the isolates of UTI microbes, six isolates were described as MDR isolates after an antibiotic susceptibility test carried out using ten different antibiotics. An alternative treatment for microbial elimination involved the use of biosynthesized silver nanoparticles (AgNPs) derived from Solanum lycopersicum [S. cumin]. Results: The sizes and shapes of AgNPs were characterized through TEM imaging, which showed spherical particles in a size range of 35-80 nm, of which the average size was 53 nm. Additionally, the silver nanoparticles (AgNPs) demonstrated inhibitory activity against Staphylococcus aureus (OR648079), exhibiting a 31 mm zone of inhibition at a minimum inhibitory concentration (MIC) of 4 mg/mL and a minimum bactericidal concentration (MBC) of 8 mg/mL. This was followed by Aspergillus niger (OR648075), which showed a 30 mm inhibition zone at an MIC of 16 mg/mL and a minimum fungicidal concentration (MFC) of 32 mg/mL. Then, Enterococcus faecalis (OR648078), Klebsiella pneumoniae (OR648081), and Acinetobacter baumannii (OR648080) each displayed a 29 mm zone of inhibition at an MIC of 8 mg/mL and an MBC of 16 mg/mL. The least inhibition was observed against Candida auris (OR648076), with a 25 mm inhibition zone at an MIC of 16 mg/mL and an MFC of 32 mg/mL. Furthermore, AgNPs at different concentrations removed DPPH and H2O2 at an IC50 value of 13.54 µg/mL. Also, AgNPs at 3 mg/mL showed remarkable DNA fragmentation in all bacterial strains except Enterococcus faecalis. The phytochemical analysis showed the presence of different active organic components in the plant extract, which concluded that rutin was 88.3 mg/g, garlic acid was 70.4 mg/g, and tannic acid was 23.7 mg/g. Finally, AgNPs concentrations in the range of 3-6 mg/mL showed decreased expression of two of the fundamental genes necessary for biofilm formation within Staphylococcus aureus, fnbA (6 folds), and Cna (12.5 folds) when compared with the RecA gene, which decreased by one-fold when compared with the control sample. These two genes were submitted with NCBI accession numbers [OR682119] and [OR682118], respectively. Conclusions: The findings from this study indicate that biosynthesized AgNPs from Solanum lycopersicum exhibit promising antimicrobial and antioxidant properties against UTI pathogens, including strains resistant to multiple antibiotics. This suggests their potential as an effective alternative treatment for UTIs. Further research is warranted to fully understand the mechanisms of action and to explore the therapeutic applications of these nanoparticles in combating UTIs.

Investigating the relationship between nurses' workplace behaviour and perceived levels of ethical leadership in managers.

BACKGROUND: There is increasing research interest in the relationship between ethical leadership and deviant workplace behaviour. Ethical leadership encompasses altruism, courage, ethical orientation, integrity and fairness. Examples of deviant workplace behaviours include theft, fraud, sabotage, assault, abuse, manipulation and bullying. It appears that when leaders are fair and emphasise ethical conduct, followers are less inclined to engage in deviant workplace behaviour. AIM: To investigate the relationship between nurses' self-rated levels of deviant workplace behaviour and perceived levels of ethical leadership in managers. METHOD: For this descriptive correlational study, 355 nurses from one university hospital in Egypt responded to an online questionnaire comprising the Ethical Leadership Scale and the Workplace Deviance Behavior Scale. Descriptive and inferential statistics were used to explore results and examine the relationships between study variables. RESULTS: There was a statistically significant negative relationship between respondents' self-rated levels of deviant workplace behaviour and their perceptions of levels of ethical leadership in managers. The results appeared to confirm previous research. Nurses who feel that they are treated fairly by their managers tend to have positive attitudes towards work, colleagues and management. CONCLUSION: Ethical leadership on the part of managers is a significant determinant of nurses' behaviour in the workplace and should therefore be fostered by healthcare organisations.

Investigating the efficacy of novel organoclay as a rheological additive for enhancing the performance of oil-based drilling fluids.

Oil-based drilling fluids (OBDFs) are extensively used in the drilling industry due to their superior performance in challenging drilling conditions. These fluids control wellbore stability, lubricate the drill bit, and transport drill cuttings to the surface. One important component of oil-based drilling fluids is the viscosifier, which provides rheological properties to enhance drilling operations. This study evaluates the effectiveness of Claytone-IMG 400, a novel rheological agent, in enhancing the performance of OBDFs under high-pressure and high-temperature (HPHT) conditions. A comparative analysis was conducted with a pre-existing organoclay (OC) to assess the improvements achieved by Claytone-IMG 400. The OCs were analyzed using X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM), and particle size distribution (PSD) to identify their mineral and chemical compositions, morphologies, and particle sizes. The drilling fluid density, electrical stability, sagging tendency, rheological properties, viscoelastic properties, and filtration properties were studied to formulate a stable and high-performance drilling fluid. The results confirmed that the novel OC does not affect the drilling fluid density but enhances the emulsion stability with a 9% increment compared with the drilling fluid formulated with MC-TONE. The sagging experiments showed that Claytone-IMG 400 prevented the sagging issues in both static and dynamic conditions. Also, Claytone-IMG 400 improved the plastic viscosity (PV), yield point (YP), and apparent viscosity (AV). The PV, YP, and AV were improved by 30%, 38%, and 33% increments respectively compared with the drilling fluid formulated with MC-TONE. The YP/PV ratio increased with a 6% increment from 1.12 to 1.19. Moreover, the gel strength (GS) was significantly increased, and the filtration properties were enhanced. The filtration volume was reduced by 10% from 5.0 to 4.5 cm3, and the filter cake thickness had a 37.5% reduction from 2.60 to 1.89 mm. The novelty of this study is highlighted by the introduction and evaluation of Claytone-IMG 400 as a new rheological additive for safe, efficient, and cost-effective drilling operations. The results indicate that Claytone-IMG 400 significantly improves the stability and performance of OBDFs, thereby reducing wellbore instability and drilling-related problems.

Novel Dual-Acting Hybrids Targeting Type-2 Cannabinoid Receptors and Cholinesterase Activity Show Neuroprotective Effects In Vitro and Amelioration of Cognitive Impairment In Vivo.

Alzheimer's disease (AD) is a neurodegenerative form of dementia characterized by the loss of synapses and a progressive decline in cognitive abilities. Among current treatments for AD, acetylcholinesterase (AChE) inhibitors have efficacy limited to symptom relief, with significant side effects and poor compliance. Pharmacological agents that modulate the activity of type-2 cannabinoid receptors (CB2R) of the endocannabinoid system by activating or blocking them have also been shown to be effective against neuroinflammation. Herein, we describe the design, synthesis, and pharmacological effects in vitro and in vivo of dual-acting compounds that inhibit AChE and butyrylcholinesterase (BChE) and target CB2R. Within the investigated series, compound 4g proved to be the most promising. It achieved IC50 values in the low micromolar to submicromolar range against both human cholinesterase isoforms while antagonizing CB2R with Ki of 31 nM. Interestingly, 4g showed neuroprotective effects on the SH-SY5Y cell line thanks to its ability to prevent oxidative stress-induced cell toxicity and reverse scopolamine-induced amnesia in the Y-maze forced alternation test in vivo.

Tuberculosis (TB) treatment challenges in TB-diabetes comorbid patients: a systematic review and meta-analysis.

BACKGROUND: The Directly Observed Treatment-Short Course (DOTS) Programme was implemented by WHO and includes a combination of four anti-tuberculosis (TB) drugs (isoniazid, pyrazinamide, ethambutol and rifampicin) for a period of six months to eradicate the TB infection completely. Diabetes mellitus (DM) is recognized as one of a strong contributor of TB according to World Health Organization (WHO). The presence of diabetes mellitus type 2 (DM type 2) makes TB treatment complicated. Thus, the objective of the current meta-analysis was to identify and quantify the impact of type 2 DM on treatment outcomes of TB patients treated under the DOTS Programme. METHODS: This meta-analysis was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Through a systematic review of relevant literature, we focused on studies investigating treatment outcomes including extended treatment duration and recurrence for individuals with both TB and DM undergoing DOTS therapy. The extracted information included study designs, sample sizes, patient characteristics and reported treatment results. RESULTS: In 44 studies from different parts of the world, the pooled HR for the impact of DM on extended treatment duration and reoccurrence were HR 0.72, 95% CI 0.56-0.83, p < .01 and HR 0.93, 95% CI 0.70-1.04, p = .08, respectively. The pooled HR for impact of DM on composite TB treatment outcomes was calculated as 0.76 (95% CI 0.60-0.87), p < .01 with an effect size of 41.18. The heterogeneity observed among the included studies was moderate (I2 = 55.79%). CONCLUSIONS: A negative impact of DM was found on recurrence and extended treatment duration in TB patients treated with DOTS therapy. DM type 2 is responsible for the TB treatment prolongation and TB recurrence rates. By implementing effective management strategies and advancing research, the challenges can be mitigated, arising due to the complex interaction between DM and TB.

Diagnostic value of PET imaging in clinically unresponsive patients.

Rapid advancements in the critical care management of acute brain injuries have facilitated the survival of numerous patients who may have otherwise succumbed to their injuries. The probability of conscious recovery hinges on the extent of structural brain damage and the level of metabolic and functional cerebral impairment, which remain challenging to assess via laboratory, clinical, or functional tests. Current research settings and guidelines highlight the potential value of fluorodeoxyglucose-PET (FDG-PET) for diagnostic and prognostic purposes, emphasizing its capacity to consistently illustrate a metabolic reduction in cerebral glucose uptake across various disorders of consciousness. Crucially, FDG-PET might be a pivotal tool for differentiating between patients in the minimally conscious state and those in the unresponsive wakefulness syndrome, a persistent clinical challenge. In patients with disorders of consciousness, PET offers utility in evaluating the degree and spread of functional disruption, as well as identifying irreversible neural damage. Further, studies that capture responses to external stimuli can shed light on residual or revived brain functioning. Nevertheless, the validity of these findings in predicting clinical outcomes calls for additional long-term studies with larger patient cohorts suffering from consciousness impairment. Misdiagnosis of conscious illnesses during bedside clinical assessments remains a significant concern. Based on the clinical research settings, current clinical guidelines recommend PET for diagnostic and/or prognostic purposes. This review article discusses the clinical categories of conscious disorders and the diagnostic and prognostic value of PET imaging in clinically unresponsive patients, considering the known limitations of PET imaging in such contexts.

An AI-based novel system for predicting respiratory support in COVID-19 patients through CT imaging analysis.

The proposed AI-based diagnostic system aims to predict the respiratory support required for COVID-19 patients by analyzing the correlation between COVID-19 lesions and the level of respiratory support provided to the patients. Computed tomography (CT) imaging will be used to analyze the three levels of respiratory support received by the patient: Level 0 (minimum support), Level 1 (non-invasive support such as soft oxygen), and Level 2 (invasive support such as mechanical ventilation). The system will begin by segmenting the COVID-19 lesions from the CT images and creating an appearance model for each lesion using a 2D, rotation-invariant, Markov-Gibbs random field (MGRF) model. Three MGRF-based models will be created, one for each level of respiratory support. This suggests that the system will be able to differentiate between different levels of severity in COVID-19 patients. The system will decide for each patient using a neural network-based fusion system, which combines the estimates of the Gibbs energy from the three MGRF-based models. The proposed system were assessed using 307 COVID-19-infected patients, achieving an accuracy of [Formula: see text], a sensitivity of [Formula: see text], and a specificity of [Formula: see text], indicating a high level of prediction accuracy.

Examining generational differences as a moderator of extreme-context perception and its impact on work alienation organizational outcomes: Implications for the workplace and remote work transformation.

There is no doubt that extreme contexts (e.g., war zones and pandemics) represent substantial disruptions that force many companies to rethink the way they do business. With so much of the workforce now working remotely and concerns about resulting work alienation, we must ask this question: How can this be translated into the generational divide in workplaces based in extreme contexts? Using COVID-19 as an example trigger of extreme-context experience, therefore, we investigate generation as a moderator of the effects of extreme-context perception upon anxiety leading to alienation with subsequent behavioral outcomes on job insecurity, job satisfaction, and organizational citizenship behavior (OCB). A time-lagged survey procedure yielded 219 valid responses from a three-generation sample of employees working in multiple service organizations. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). Our analysis suggested that intense extreme-context perception led to elevated anxiety and alienation, which, in turn, heightened job insecurity and worsened job satisfaction and OCB outcomes. Finally, during the experience of extreme-context times, generation was found to moderate our model, such that both Generation Y and Generation Z experienced higher anxiety due to extreme-context perception and hence higher job insecurity due to alienation compared with Generation X respondents. Our results endorse the criticality of implementing agile and generationally non-sectarian management for effectively functioning generationally diverse workforces in pandemic times.

Impact of Imaging Biomarkers and AI on Breast Cancer Management: A Brief Review.

Breast cancer stands out as the most frequently identified malignancy, ranking as the fifth leading cause of global cancer-related deaths. The American College of Radiology (ACR) introduced the Breast Imaging Reporting and Data System (BI-RADS) as a standard terminology facilitating communication between radiologists and clinicians; however, an update is now imperative to encompass the latest imaging modalities developed subsequent to the 5th edition of BI-RADS. Within this review article, we provide a concise history of BI-RADS, delve into advanced mammography techniques, ultrasonography (US), magnetic resonance imaging (MRI), PET/CT images, and microwave breast imaging, and subsequently furnish comprehensive, updated insights into Molecular Breast Imaging (MBI), diagnostic imaging biomarkers, and the assessment of treatment responses. This endeavor aims to enhance radiologists' proficiency in catering to the personalized needs of breast cancer patients. Lastly, we explore the augmented benefits of artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications in segmenting, detecting, and diagnosing breast cancer, as well as the early prediction of the response of tumors to neoadjuvant chemotherapy (NAC). By assimilating state-of-the-art computer algorithms capable of deciphering intricate imaging data and aiding radiologists in rendering precise and effective diagnoses, AI has profoundly revolutionized the landscape of breast cancer radiology. Its vast potential holds the promise of bolstering radiologists' capabilities and ameliorating patient outcomes in the realm of breast cancer management.

Exploring Neoadjuvant Chemotherapy, Predictive Models, Radiomic, and Pathological Markers in Breast Cancer: A Comprehensive Review.

Breast cancer retains its position as the most prevalent form of malignancy among females on a global scale. The careful selection of appropriate treatment for each patient holds paramount importance in effectively managing breast cancer. Neoadjuvant chemotherapy (NACT) plays a pivotal role in the comprehensive treatment of this disease. Administering chemotherapy before surgery, NACT becomes a powerful tool in reducing tumor size, potentially enabling fewer invasive surgical procedures and even rendering initially inoperable tumors amenable to surgery. However, a significant challenge lies in the varying responses exhibited by different patients towards NACT. To address this challenge, researchers have focused on developing prediction models that can identify those who would benefit from NACT and those who would not. Such models have the potential to reduce treatment costs and contribute to a more efficient and accurate management of breast cancer. Therefore, this review has two objectives: first, to identify the most effective radiomic markers correlated with NACT response, and second, to explore whether integrating radiomic markers extracted from radiological images with pathological markers can enhance the predictive accuracy of NACT response. This review will delve into addressing these research questions and also shed light on the emerging research direction of leveraging artificial intelligence techniques for predicting NACT response, thereby shaping the future landscape of breast cancer treatment.

Nurses Job Crafting: Correlation Between Organizational Identification and Workplace Attachment Among Nurses.

AIM: The aim of this study was to investigate the relationship between nurses' job crafting, organizational identification, and work attachment. BACKGROUND: Job crafting is a proactive activity in which nurses adapt the physical, cognitive, or social aspects of their jobs to make them more meaningful. Nurses are considered fundamental healthcare stakeholders who are able to transform initiatives implemented by the healthcare organization into valuable work outcomes. Nurses' perceptions of their jobs shape the community's opinion toward an organization. METHODS: This is a descriptive correlational study. Two hundred seventy nurses were recruited from 1 governmental hospital in Egypt. Respondents completed the self-administered, printed questionnaires. Measures included job crafting, organizational identification, and work attachment questionnaires. Findings were investigated via descriptive and inferential statistics. RESULTS: Over half of the nurses reported a moderate level of job crafting, whereas none of the nurses reported a high level of organizational identification. More than half of the nurses reported low levels of work attachment. CONCLUSION: Job crafting is significantly related to nurses' organizational identification and work attachment.

Ribosomal dysregulation: A conserved pathophysiological mechanism in human depression and mouse chronic stress.

The underlying biological mechanisms that contribute to the heterogeneity of major depressive disorder (MDD) presentation remain poorly understood, highlighting the need for a conceptual framework that can explain this variability and bridge the gap between animal models and clinical endpoints. Here, we hypothesize that comparative analysis of molecular data from different experimental systems of chronic stress, and MDD has the potential to provide insight into these mechanisms and address this gap. Thus, we compared transcriptomic profiles of brain tissue from postmortem MDD subjects and from mice exposed to chronic variable stress (CVS) to identify orthologous genes. Ribosomal protein genes (RPGs) were down-regulated, and associated ribosomal protein (RP) pseudogenes were up-regulated in both conditions. A seeded gene co-expression analysis using altered RPGs common between the MDD and CVS groups revealed that down-regulated RPGs homeostatically regulated the synaptic changes in both groups through a RP-pseudogene-driven mechanism. In vitro analysis demonstrated that the RPG dysregulation was a glucocorticoid-driven endocrine response to stress. In silico analysis further demonstrated that the dysregulation was reversed during remission from MDD and selectively responded to ketamine but not to imipramine. This study provides the first evidence that ribosomal dysregulation during stress is a conserved phenotype in human MDD and chronic stress-exposed mouse. Our results establish a foundation for the hypothesis that stress-induced alterations in RPGs and, consequently, ribosomes contribute to the synaptic dysregulation underlying MDD and chronic stress-related mood disorders. We discuss the role of ribosomal heterogeneity in the variable presentations of depression and other mood disorders.

Fatal pulmonary embolism following injectable gluteal filler usage: a case report.

BACKGROUND: Despite the fact that injectable filler usage in the gluteal region has not been recommended in formal medical institutions, illegal procedures are performed in many clinics and beauty centers across Egypt. This case report illustrates the illegal practice culminating in a fatal complication. CASE PRESENTATION: A 26-year-old female with no relevant medical history presented to the ER with acute onset shortness of breath. The complaint started 16 h before, with a rapidly progressive course, shortly after undergoing a gluteal filler injection at a center in Cairo. At ER, the patient was severely distressed, yet fully conscious and oriented. She was shocked (BP 70/40 mmHg), tachycardic (130 BPM), and tachypneic (30/min) with normal temperature. She had congested pulsating neck veins with positive Kussmaul sign. Chest auscultation revealed normal vesicular breathing with equal air entry and no adventitious sounds. Her O2 saturation was 60% on room air that improved to 85% on O2 mask. ECG showed sinus tachycardia. Echocardiography showed dilated right side, D-shaped septum with systolic flattening, dilated IVC, mild tricuspid regurgitation and estimated RV systolic pressure 53 mmHg. Her ABG showed compensated metabolic acidosis with elevated lactate level. At the ICU, CVP was 18 mmHg. Saline infusion was continued along with noradrenaline infusion initiation. A provisional diagnosis of high-risk pulmonary embolism was made, though CT pulmonary angiography was not available. Accordingly, thrombolytic therapy was initiated with alteplase (100 mg) over 2 h. Also, a dose of pulse steroids (methylprednisolone 200 mg) was given. Chest X-ray showed bilateral heterogenous opacity and ABG showed deteriorating hypoxia and combined metabolic and respiratory acidosis. The patient was intubated upon deterioration of conscious level and was put on mechanical ventilation. Her ET tube showed frequent blood-tinged secretions. Echocardiography showed more right-side dilatation that was consistent with deterioration of clinical status. Three hours after admission the patient developed cardiac arrest and died 2 h later. CONCLUSIONS: This case report highlights the dangers associated with injectable filler usage in the gluteal region. Physicians and patients should be aware of the possible complications and how to avoid it.

A personalized classification of behavioral severity of autism spectrum disorder using a comprehensive machine learning framework.

Autism Spectrum Disorder (ASD) is characterized as a neurodevelopmental disorder with a heterogeneous nature, influenced by genetics and exhibiting diverse clinical presentations. In this study, we dissect Autism Spectrum Disorder (ASD) into its behavioral components, mirroring the diagnostic process used in clinical settings. Morphological features are extracted from magnetic resonance imaging (MRI) scans, found in the publicly available dataset ABIDE II, identifying the most discriminative features that differentiate ASD within various behavioral domains. Then, each subject is categorized as having severe, moderate, or mild ASD, or typical neurodevelopment (TD), based on the behavioral domains of the Social Responsiveness Scale (SRS). Through this study, multiple artificial intelligence (AI) models are utilized for feature selection and classifying each ASD severity and behavioural group. A multivariate feature selection algorithm, investigating four different classifiers with linear and non-linear hypotheses, is applied iteratively while shuffling the training-validation subjects to find the set of cortical regions with statistically significant association with ASD. A set of six classifiers are optimized and trained on the selected set of features using 5-fold cross-validation for the purpose of severity classification for each behavioural group. Our AI-based model achieved an average accuracy of 96%, computed as the mean accuracy across the top-performing AI models for feature selection and severity classification across the different behavioral groups. The proposed AI model has the ability to accurately differentiate between the functionalities of specific brain regions, such as the left and right caudal middle frontal regions. We propose an AI-based model that dissects ASD into behavioral components. For each behavioral component, the AI-based model is capable of identifying the brain regions which are associated with ASD as well as utilizing those regions for diagnosis. The proposed system can increase the speed and accuracy of the diagnostic process and result in improved outcomes for individuals with ASD, highlighting the potential of AI in this area.