Search

Efficient and targeted delivery of impermeable exogenous material such as small molecules, proteins, and plasmids into cells in culture as well as in vivo is of great importance for drug, vaccine and gene delivery for different therapeutic strategies. Though advent of optoporation by ultrafast laser microbeam has allowed spatial targeting in cells, the requirement of high peak power to create holes on the cell membrane is not practical and also challenging in vivo. Here, we report development and use of uniquely non-reactive crystalline magnetic carbon nanoparticles (CMCNPs) for photothermal delivery (PTD) of impermeable dyes and plasmids encoding light-sensitive proteins into cells using low power continuous wave near-infrared (NIR) laser beam. Further, we utilized the magnetic nature of these CMCNPs to localize them in desired region by external magnetic field, thus minimizing the required number of nanoparticles. We discovered that irradiation of the CMCNPs near the desired cell(s) with NIR laser beam leads to temperature rise that not only stretch the cell-membrane to ease delivery, it also creates fluid flow to allow mobilization of exogenous substances to the delivery. Due to significant absorption properties of the CMCNPs in the NIR therapeutic window, PTD under in vivo condition is highly possible. [ABSTRACT FROM AUTHOR]

Abstract Nash equilibrium is a key concept in game theory fundamental for elucidating the equilibrium state of strategic interactions, with applications in diverse fields such as economics, political science, and biology. However, the Nash equilibrium may not always align with desired outcomes within the broader system. This article introduces a novel game engineering framework that tweaks strategic payoffs within a game to achieve a pre-defined desired Nash equilibrium while averting undesired ones. Leveraging mixed-integer linear programming, this framework identifies intricate combinations of players and strategies and optimal perturbations to their payoffs that enable the shift from undesirable Nash equilibria to more favorable ones. We demonstrate the effectiveness and scalability of our approach on games of varying complexity, ranging from simple prototype games such as the Prisoner’s Dilemma and Snowdrift games with two or more players to complex game configurations with up to $${10}^{6}$$ 10 6 entries in the payoff matrix. These studies showcase the capability of this framework in efficiently identifying the alternative ways of reshaping strategic payoffs to secure desired Nash equilibria and preclude undesired equilibrium states. Our game engineering framework offers a versatile toolkit for precision strategic decision-making with far-reaching implications across diverse domains.

Abstract Reduced functional connectivity of physiological systems is associated with poor prognosis in critically ill patients. However, physiological network analysis is not commonly used in clinical practice and awaits quantitative evidence. Acute liver failure (ALF) is associated with multiorgan failure and mortality. Prognostication in ALF is highly important for clinical management but is currently dependent on models that do not consider the interaction between organ systems. This study aims to examine whether physiological network analysis can predict survival in patients with ALF. Data from 640 adult patients admitted to the ICU for paracetamol-induced ALF were extracted from the MIMIC-III database. Parenclitic network analysis was performed on the routine biomarkers using 28-day survivors as reference population and network clusters were identified for survivors and non-survivors using k-clique percolation method. Network analysis showed that liver function biomarkers were more clustered in survivors than in non-survivors. Arterial pH was also found to cluster with serum creatinine and bicarbonate in survivors compared with non-survivors, where it clustered with respiratory nodes indicating physiologically distinctive compensatory mechanism. Deviation along the pH-bicarbonate and pH-creatinine axes significantly predicts mortality independent of current prognostic indicators. These results demonstrate that network analysis can provide pathophysiologic insight and predict survival in critically ill patients with ALF.

Abstract The availability of target cells expressing the HIV receptors CD4 and CCR5 in genital tissue is a critical determinant of HIV susceptibility during sexual transmission. Quantification of immune cells in genital tissue is therefore an important outcome for studies on HIV susceptibility and prevention. Immunofluorescence microscopy allows for precise visualization of immune cells in mucosal tissues; however, this technique is limited in clinical studies by the lack of an accurate, unbiased, high-throughput image analysis method. Current pixel-based thresholding methods for cell counting struggle in tissue regions with high cell density and autofluorescence, both of which are common features in genital tissue. We describe a deep-learning approach using the publicly available StarDist method to count cells in immunofluorescence microscopy images of foreskin stained for nuclei, CD3, CD4, and CCR5. The accuracy of the model was comparable to manual counting (gold standard) and surpassed the capability of a previously described pixel-based cell counting method. We show that the performance of our deep-learning model is robust in tissue regions with high cell density and high autofluorescence. Moreover, we show that this deep-learning analysis method is both easy to implement and to adapt for the identification of other cell types in genital mucosal tissue.

Abstract Infectious keratitis (IK) is a major cause of corneal opacity. IK can be caused by a variety of microorganisms. Typically, fungal ulcers carry the worst prognosis. Fungal cases can be subdivided into filamentous and yeasts, which shows fundamental differences. Delays in diagnosis or initiation of treatment increase the risk of ocular complications. Currently, the diagnosis of IK is mainly based on slit-lamp examination and corneal scrapings. Notably, these diagnostic methods have their drawbacks, including experience-dependency, tissue damage, and time consumption. Artificial intelligence (AI) is designed to mimic and enhance human decision-making. An increasing number of studies have utilized AI in the diagnosis of IK. In this paper, we propose to use AI to diagnose IK (model 1), differentiate between bacterial keratitis and fungal keratitis (model 2), and discriminate the filamentous type from the yeast type of fungal cases (model 3). Overall, 9329 slit-lamp photographs gathered from 977 patients were enrolled in the study. The models exhibited remarkable accuracy, with model 1 achieving 99.3%, model 2 at 84%, and model 3 reaching 77.5%. In conclusion, our study offers valuable support in the early identification of potential fungal and bacterial keratitis cases and helps enable timely management.

Abstract Neuroprosthetics that combine a brain computer interface (BCI) with functional electrical stimulation (FES) can restore voluntary control of a patients’ own paralyzed limbs. To date, human studies have demonstrated an “all-or-none” type of control for a fixed number of pre-determined states, like hand-open and hand-closed. To be practical for everyday use, a BCI-FES system should enable smooth control of limb movements through a continuum of states and generate situationally appropriate, graded muscle contractions. Crucially, this functionality will allow users of BCI-FES neuroprosthetics to manipulate objects of different sizes and weights without dropping or crushing them. In this study, we present the first evidence that using a BCI-FES system, a human with tetraplegia can regain volitional, graded control of muscle contraction in his paralyzed limb. In addition, we show the critical ability of the system to generalize beyond training states and accurately generate wrist flexion states that are intermediate to training levels. These innovations provide the groundwork for enabling enhanced and more natural fine motor control of paralyzed limbs by BCI-FES neuroprosthetics.

Abstract Long non-coding RNAs (lncRNAs) play key roles in human diseases, including cancer. Functional studies of the lncRNA HOTAIR (HOX transcript antisense RNA) provide compelling evidence for therapeutic targeting of HOTAIR in cancer, but targeting lncRNAs in vivo has proven to be difficult. In the current study, we describe a peptide nucleic acids (PNA)-based approach to block the ability of HOTAIR to interact with EZH2 and subsequently inhibit HOTAIR-EZH2 activity and resensitize resistant ovarian tumors to platinum. Treatment of HOTAIR-overexpressing ovarian and breast cancer cell lines with PNAs decreased invasion and increased chemotherapy sensitivity. Furthermore, the mechanism of action correlated with reduced nuclear factor-kappaB (NF-κB) activation and decreased expression of NF-κB target genes matrix metalloprotease 9 and interleukin 6. To deliver the anti-lncRNA to the acidic (pH approximately 6) tumor microenvironment, PNAs were conjugated to pH-low insertion peptide (pHLIP). Treatment of mice harboring platinum-resistant ovarian tumor xenografts with pHLIP-PNA constructs suppressed HOTAIR activity, reduced tumor formation and improved survival. This first report on pHLIP-PNA lncRNA targeting solid tumors in vivo suggests a novel cancer therapeutic approach.

Most of published research on magnetic hyperthermia focused on iron oxides, ferrites, and binary alloy nanostructures, while the ternary alloys attracted much limited interest. Herein, we prepared NiCuCo ternary alloy nanocomposites with variable compositions by mechanical alloying. Physical properties were fully characterized by XRD, Rietveld analysis, XPS, SEM/EDX, TEM, ZFC/FC and H-M loops. DFT calculations were used to confirm the experimental results in terms of structure and magnetism. The results showed that the fabricated nanoalloys are face centered cubic (FCC) with average core sizes of 9-40 nm and behave as superparamagnetic with saturation in the range 4.67-42.63 emu/g. Langevin fitting corroborated the superparamagnetic behavior, while law of approach to saturation (LAS) was used to calculate the magnetic anisotropy constants. Heating effciencies were performed under an alternating magnetic field (AMF, H 0  = 170 Oe and f = 332.5 kHz), and specific absorption rate (SAR) values were determined. The highest magnetic saturation (M s ), heating potentials, and SAR values were attained for Ni 35 Cu 30 Co 35 containing the lowest Cu but highest Ni and Co percentages, and the least for Ni 15 Cu 70 Co 15 . Importantly, the nanoalloys reached the required temperatures for magnetic hyperthermia (42 °C) in relatively short times. We also showed that heat dissipiation can be simply tuned by changing many parameters such as concentration, field amplitude, and frequency. Finally, cytotoxicity viability assays against two different breast cancer cell lines treated with Ni 25 Cu 50 Co 25 nanoalloy in the presence and absence of AMF were investigated. No significant decrease in cancer cell viability was observed in the absence of AMF. When tested against tumorigenic KAIMRC2 breast cancer cells under AMF, the NiCuCo nanoalloy was found to be highly potent to the cells (~ 2-fold enhancement), killing almost all the cells in short times (20 min) and clinically-safe AC magnetic fields. These findings strongly suggest that the as-prepared ternary NiCuCo nanoalloys hold great promise for potential magnetically-triggered cancer hyperthermia., (© 2024. The Author(s).)

The role of efficient fuel mixing and a stable flame holder is crucial in enhancing the performance and capabilities of scramjet engines for high-speed flight. The present research paper has tried to disclose the fuel mixing efficiency of 3-lobe annular nozzle on the mixing mechanism of the fuel jet behind the strut. In addition, using internal air jet flow for increasing the circulation strength and fuel mixing behind the strut is also examined in this study. Numerical simulation of the flow and fuel jet behind the strut is done to reveal the main physics related to the mechanism of fuel mixing inside the combustor with the proposed injection system. The results of our simulation show that using annular 3-lobe fuel jet improve the fuel mixing via production of the multiple vortex pairs within the combustor behind the strut. The use of internal air jet also enhances the fuel mixing efficiency up to 90% in combustor of scramjet engine., (© 2024. The Author(s).)

This study aimed to evaluate the effects of oral contraceptive (OC) use, khat chewing, and their combined effect on telomerase level and tumor suppressor genes, p53 and p21 in breast cancer (BC) patients and normal volunteers. 140 Yemeni women aged 25-40 years old enrolled, 60 newly diagnosed pretreated BC patients, and 80 control subjects. Venous blood (5 ml) was collected and the results showed BC patients to have significantly raised levels of telomerase, p53, and p21 compared to the control group. The use of OCs significantly raised telomerase in control group with no effect in BC patients; whereas p53 and p21 were significantly increased in BC patients. On the other hand, khat chewing significantly increased p53 in controls and BC patients, whereas p21 was significantly raised in BC patients. The combined use of OCs and khat chewing significantly increased telomerase and p53 in control group, and significantly increased p53 and p21 in BC patients. Telomerase was shown to be a risk factor (OR 4.4) for BC, and the use of OCs was a high-risk factor for increasing telomerase (OR 27.8) in normal subjects. In contrast, khat chewing was shown to be protective (OR 0.142), and the combined use of OCs and khat chewing decreased the risk factor of telomerase from OR 27.8 to 2.1., (© 2024. The Author(s).)

Myelodysplastic syndrome (MDS) is a heterogeneous spectrum of clonal hematopoietic disorders with varying degrees of cytopenia and morphologic dysplasia. The hemoglobin, albumin, lymphocyte, and platelet (HALP) score is a prognostic marker in several types of malignant tumors. Prognostic value of HALP score remains unclear for MDS. To determine the prognostic value of baseline HALP score in MDS. We retrospectively analyzed data from 130 newly diagnosed MDS patients evaluated and classified under HALP score. By the receiver operating characteristic (ROC) analysis, the optimal cut-off value of HALP was > 67.5 in predicting mortality. Patients were divided into two groups: with low and high HALP scores, and the characteristics were compared between both groups. Patients' median age was 68 (19-84) years, and 79 (60.8%) were male. Higher HALP score was detected in MDS patients with intermediate-risk under IPSS score, and at high and very high risks under IPSS-R score, and those receiving azacitidine (AZA) treatment. The survival rates of those with a HALP score > 67.5 were significantly lower than those with low HALP score at 17.77 ± 3.98 (median ± SE) (p < 0.001). The 3-, 5- and 10-years survival rates of individuals with HALP scores > 67.5 were found as 25, 18, and 11%, respectively. Median overall survival (OS) was also determined as 33.10 (95% CI 16.34-49.88) months by the Kaplan-Meier method. HALP score has shown an ability to be a useful prognostic biomarker in various cancers, including MDS. The meaningful cut-off value of HALP is disease-specific and largely study-specific. High HALP score is associated with unfavorable clinicopathological characteristics. Also, it may be useful in predicting OS and mortality of MDS., (© 2024. The Author(s).)

Evaluate the impact of extracts from the Lens culinaris plant on a number of physiological and biochemical parameters in squash leaves infected with ZYMV in this work. Compared to the untreated leaves, ZYMV infected leaves showed a range of symptoms, such as severe mosaic, size reduction, stunting, and deformation. Analysis of physiological data revealed that L. culinaris extract lectin therapies and viral infections had an impact on metabolism. Protein, carbohydrate, and pigment levels were all lowered by viral infection. However, phenolic compounds, total protein, total carbohydrates, total amino acids, proline, total chlorophyll and peroxidases levels are considerably elevated with all extract therapies. The other biochemical parameters also displayed a variety of changes. Moreover shoot length, number of leaves and number of flowers was significantly increased compared to viral control in all treatments. The L. culinaris extract treatment increases the plant's ZYMV resistance. This is detectable through reduction of the plants treated with lentil lectin pre and post virus inoculation, reduction in disease severity and viral concentration, and percentage of the infected plants has a virus. All findings demonstrate significant metabolic alterations brought by viral infections or L. culinaris extract treatments, and they also suggest that exogenous extract treatments is essential for activating the body's defences against ZYMV infection., (© 2024. The Author(s).)

Skin cancer is the most prevalent kind of cancer in people. It is estimated that more than 1 million people get skin cancer every year in the world. The effectiveness of the disease's therapy is significantly impacted by early identification of this illness. Preprocessing is the initial detecting stage in enhancing the quality of skin images by removing undesired background noise and objects. This study aims is to compile preprocessing techniques for skin cancer imaging that are currently accessible. Researchers looking into automated skin cancer diagnosis might use this article as an excellent place to start. The fully convolutional encoder-decoder network and Sparrow search algorithm (FCEDN-SpaSA) are proposed in this study for the segmentation of dermoscopic images. The individual wolf method and the ensemble ghosting technique are integrated to generate a neighbour-based search strategy in SpaSA for stressing the correct balance between navigation and exploitation. The classification procedure is accomplished by using an adaptive CNN technique to discriminate between normal skin and malignant skin lesions suggestive of disease. Our method provides classification accuracies comparable to commonly used incremental learning techniques while using less energy, storage space, memory access, and training time (only network updates with new training samples, no network sharing). In a simulation, the segmentation performance of the proposed technique on the ISBI 2017, ISIC 2018, and PH2 datasets reached accuracies of 95.28%, 95.89%, 92.70%, and 98.78%, respectively, on the same dataset and assessed the classification performance. It is accurate 91.67% of the time. The efficiency of the suggested strategy is demonstrated through comparisons with cutting-edge methodologies., (© 2024. The Author(s).)

Cancer is responsible for approximately 10 million deaths worldwide, with 70% of the deaths occurring in low- and middle-income countries; as such safer and more effective anti-cancer drugs are required. Therefore, the potential benefits of Ziziphus nummularia and Ziziphus spina-christi as sources of anti-cancer agents were investigated. Z. nummularia and Z. spina-christi extracts were prepared using chloroform, ethanol, ethyl acetate, and water. The extracts' anti-cancer properties were determined using the MTT Cell Viability Assay in four cancer cell lines: breast (KAIMRC2 and MDA-MB-231), colorectal (HCT8), and liver (HepG2). The ApoTox-Glo Triplex Assay and high-content imaging (HCI)-Apoptosis Assay were used to assess KAIMRC2 and HCT8 cells further. In addition, KAIMRC2 cells were tested for microtubule staining, and AKT/mTOR protein expression was determined by western blot analysis. Liquid chromatography-mass spectrometry (LC-MS) was performed to identify the secondary metabolites in the ethanol and ethyl acetate extracts, followed by in silico techniques to predict molecular targets and interactions, safety, and pharmacokinetic profile for identified metabolites. Out of the eight extracts, the ethanolic extract of Z. nummularia, exhibited the most potent activity against KAIMRC2 cells with an IC 50 value of 29.2 μg/ml. Cancer cell treatment with the ethanolic extract of Z. nummularia resulted in a dose-dependent decrease in cell viability with increased apoptosis and cytotoxic effects. Microtubule staining showed a disrupted microtubular network. The ethanolic extract treatment of KAIMRC2 cells led to upregulated expression of pAKT and pmTOR. In silico studies predicted luteolin-7-O-glucoside to be a ligand for tubulin with the highest docking score (- 7.686) and similar binding interactions relative to the native ligand. Further computational analysis of the metabolites showed acceptable pharmacokinetic and safety profiles, although ethanolic extract metabolites were predicted to have cardiotoxic effects. Ethanolic extraction is optimal for solubilizing active anticancer metabolites from Z. nummularia, which may act by causing M-phase arrest via inhibition of tubulin polymerization. Luteolin-7-O-glucoside is the lead candidate for further research and development as an anti-cancer agent. In addition, this study suggests that herbal treatment could switch on mechanisms of adaptation and survival in cancer cells., (© 2024. The Author(s).)

In this paper, we investigate a fractal-fractional-order mathematical model with the influence of hospitalized patients and the impact of vaccination with fractal-fractional operators. The respective derivatives are considered in the Caputo, Caputo Fabrizio, and Atangana-Baleanu senses of fractional order α and fractal dimension τ . For the proposed problem, some results regarding basic reproduction number and stability are given. Using the next-generation matrix approach, we have investigated the global and local stability of several types of equilibrium points. We provide a detailed analysis of the existence and uniqueness of the solution. Moreover, we fit the model with the real data of Pakistan from June 01, 2020, till March 24, 2021. Then, we use the fractal-fractional derivative to find a numerical solution for the model. MATLAB software is used for numerical illustration. Graphical presentations corresponding to different parameteric values are given as well., (© 2024. The Author(s).)

This study explores the impact of Internet addiction (IA), age, and essential and non-essential technology usage time on the physical and mental fatigue of adolescents. The research surveyed 477 adolescents from Qatar and employed the Internet Addiction Diagnostic Questionnaire (IADQ) and Chalder's Fatigue Scale for data collection. Multiple linear regression and Mann-Whitney U tests were utilized for analysis. The findings indicate that IA, non-essential usage time, and age are positively associated with overall fatigue among adolescents. IA and non-essential usage time are positively linked to physical fatigue, while IA, non-essential usage time, and age are positive predictors of mental fatigue. However, essential usage time is negatively associated with mental fatigue. These results highlight the importance of distinguishing technology usage based on intent and necessity, as well as differentiating between physical and mental fatigue when examining problematic technology usage. This study is among the few conducted in the Middle Eastern context., (© 2024. The Author(s).)

We analyzed 5 years (2016-2020) of nested Canadian data from the Study for Monitoring Antimicrobial Resistance Trends (SMART) to identify pathogen predominance and antimicrobial resistance (AMR) patterns of adult Gram-negative infections in Canadian health care and to complement other public surveillance programs and studies in Canada. A total of 6853 isolates were analyzed from medical (44%), surgical (18%), intensive care (22%) and emergency units (15%) and from respiratory tract (36%), intra-abdominal (25%), urinary tract (24%) and bloodstream (15%) infections. Overall, E. coli (36%), P. aeruginosa (18%) and K. pneumoniae (12%) were the most frequent isolates and P. aeruginosa was the most common respiratory pathogen. 18% of Enterobacterales species were ESBL positive. Collective susceptibility profiles showed that P. aeruginosa isolates were highly susceptible (> 95%) to ceftolozane/tazobactam and colistin, though markedly less susceptible (58-74%) to other antimicrobials tested. Multi-drug resistance (MDR) was present in 10% of P. aeruginosa isolates and was more frequent in those from respiratory infections and from ICU than non-ICU locations. Of P. aeruginosa isolates that were resistant to combinations of ceftazidime, piperacillin/tazobactam and meropenem, 73-96% were susceptible to ceftolozane/tazobactam over the period of the study. These national data can now be combined with clinical prediction rules and genomic data to enable expert antimicrobial stewardship applications and guide treatment policies to optimize adult patient care., (© 2023. Springer Nature Limited.)