This work tackles the problem of image restoration, a crucial task in many fields of applied sciences, focusing on removing degradation caused by blur and noise during the acquisition process. Drawing inspiration from the multi-penalty approach based on the Uniform Penalty principle introduced in [Bortolotti et al. arXiv.math.NA/2309.14163], we develop here a new image restoration model and an iterative algorithm for its effective solution. The model incorporates pixel-wise regularization terms and establishes a rule for parameters selection, aiming to restore images through the solution of a sequence of constrained optimization problems. To achieve this, we present a modified version of the Newton Projection method, adapted to multi-penalty scenarios, and prove its convergence. Numerical experiments demonstrate the efficacy of the method in eliminating noise and blur while preserving the image edges.

Machine learning offers advanced tools for efficient management of radio resources in modern wireless networks. In this study, we leverage a multi-agent deep reinforcement learning (DRL) approach, specifically the Parameterized Deep Q-Network (DQN), to address the challenging problem of power allocation and user association in massive multiple-input multiple-output (M-MIMO) communication networks. Our approach tackles a multi-objective optimization problem aiming to maximize network utility while meeting stringent quality of service requirements in M-MIMO networks. To address the non-convex and nonlinear nature of this problem, we introduce a novel multi-agent DQN framework. This framework defines a large action space, state space, and reward functions, enabling us to learn a near-optimal policy. Simulation results demonstrate the superiority of our Parameterized Deep DQN (PD-DQN) approach when compared to traditional DQN and RL methods. Specifically, we show that our approach outperforms traditional DQN methods in terms of convergence speed and final performance. Additionally, our approach shows 72.2 % and 108.5 % improvement over DQN methods and RL method respectively in handling large-scale multi-agent problems in M-MIMO networks.

This study proposes a method for image matching between infrared(IR)-RGB images using a deep learning network to estimate the deformation field. We propose a deformation field generator (DFG) that estimates the deformation field of the transformation matrix to match each pixel or IR image to the RGB image. DFG is a network that receives IR and RGB images as input; the output size is two channels and has the sample resolution as the input image. By warping the IR image through a grid-sampler that warps the image according to the value of the deformation field, we can obtain a warped IR image that matches the RGB image. Additionally, to check whether the warped IR image matched the RGB image, the masking images detecting the segmentation of objects were photographed in two images. Without directly comparing IR and RGB images, we proposed mask loss that warps the IR mask image through the deformation field and grid sampler and then compares the warped IR mask image with the RGB mask image. Mask loss solves the spatial similarity comparison problem with multi-modality images, such as IR and RGB images, by comparing the mask image with the same modality image as the mask image.

This paper proposes a position recognition method for the receiver coil by the secondary coil current. Based on the practical value of the current of the receiver coil, the position recognition of the receiver coil in the WPT system is realized. This paper proposes a 3×3 array multi-transmitter coil grouping and control logic. The mathematical model of mutual inductance between the receiver and transmitter coil at different positions on the X-Y plane is established. A method for identifying the position of the receiver coil according to the current of the receiver coil is proposed. Compared with the traditional position recognition method of the receiver coil, this method does not need to add a detection coil and position sensor and can realize the position recognition of the receiver coil on the 2D plane.

With a high proportion of distributed photovoltaic and lower fossil energy integrated into the distribution network, it is very difficult to ensure the reliability of power supply. The distributed photovoltaic planning model based on big data is proposed. According to the impact stochastic photovoltaics and loads on reliability planning, the static and dynamic capacity-load ratios are proposed. The big data analysis model of distributed photovoltaic planning is established. The big data multi-scenario generation and reduction algorithm of stochastic distributed photovoltaic and load planning is studied, and a source-load big data scenario matching model is proposed. Ac-cording to the source load big data scenario, the dynamic capacity-load ratio of the distribution network is obtained. The static capacity-load ratio calculation method in distribution network planning is studied to ensure the reliability of power supply. Finally, the IEEE 33-bus system is used as an example. The results show that distributed photovoltaic planning based on big data and multi-scenario methods can improve photovoltaic utilization and power supply reliability.

Reading is a complex cognitive task involving processes from different systems. The present work aims to identify some points of divergence reported in the reading literature and discuss them in a new experimental paradigm framework. Inspired by the paradigms of perceptual identification and rapid parallel presentation (RPVP), we emphasize that the originality of our experimental paradigm lies in the recruitment of multi-stable Arabic percepts within the region where low-level processing occurs (i.e., the visual span area). With good flexibility, the current paradigm has reached higher-order processing levels. In agreement with previous works highlighting the parafoveal-on-foveal effect, results suggest parallel word processing. Furthermore, they suggest a rapid extraction of syntactic and semantic information from words in sentences while attributing an advantage to semantic processing in the emergence of the sentence superiority effect.

The effects of various drawing parameters and annealing processes on the structure and properties of Cu-Ag wires, containing 1 wt% silver, were investigated using specialized equipment including fine wire drawing machines, very fine wire drawing machines, heat treatment equipment, tensile testing machines, microcomputer-controlled electronic universal testers, resistance testers, and scanning electron microscopes. The results revealed that continuous drawing of Cu-1%Ag alloy wires led to elongation of the grains, resulting in a uniform and tightly fibrous microstructure. Moreover, the tensile strength of the alloy wire increased from 670 MPa to 783.9 MPa after a single-pass with a deformation of 14%. Subsequently, when the wire was drawn at a speed of 500 m/min, the tensile strength further increased to 820.1 MPa. After annealing the Փ0.08 mm Cu-1% Ag alloy wire, an increase in annealing temperature up to 500°C resulted in the wire's tensile strength decreasing from 820.1 MPa to 377.5 MPa. Simultaneously, the elongation increased from 1.94% to 15.21%, and the resistivity decreased from 1.931×10-8Ω·m to 1.723×10-8Ω·m. Additionally, when annealing was conducted at a rate of 80 m/min, the wire resistivity dropped to 1.635×10-8Ω·m.

Buildings are responsible for approximately 40% of the world’s energy consumption and 36% of the total carbon dioxide emissions. Building occupancy is essential, enabling Occupant-Centric Control for zero emissions and decarbonization. Although existing machine learning and deep learning methods for building occupancy prediction have achieved remarked progress, their analyses remain limited when applied to complex real-world scenarios. Besides, there is a high expectation for Transformer algorithms to predict building occupancy accurately. Therefore, this paper presents an Occupancy Prediction Transformer network (OPTnet). We fuse and feed multi-sensor data (building occupancy, indoor environmental conditions, HVAC operations) into a Transformer model to forecast the future occupancy presence in multiple zones. We perform experimental analysis and compare it to different occupancy prediction methods (e.g., Decision Tree, Long Short-Term Memory networks, Multi-layer perceptron) and diverse time horizons (1,2,3,5,10,20,30mins). The performance metrics (e.g., Accuracy and Mean Squared Error) are employed to evaluate the effectiveness of prediction algorithms. Our OPTnet method achieves superior performance on our experimental two-week data compared to existing methods. The improved performance signifies its potential to enhance HVAC control systems and energy optimization strategies. We will make the code publicly available at https://github.com/kailaisun/occupancy-prediction-binary to promote transparency and reproducibility.

Current effort with light field displays is mainly concentrated on the widest possible viewing angle, while a single viewer only needs to view the display in a specific viewing direction. To make light field display a practical practice, a super multi-view light field display is proposed to compress the information in the viewing zone of a single user by reducing the redundant viewpoints. A quasi-directional backlight is proposed and a lenticular lens array is applied to achieve the restricted viewing zone. Eye-tracking technique is applied to extend the viewing area. Experimental results show that the proposed scheme can present vivid 3D scene with smooth motion parallax. Only 16.7% conventional light field display data are required to achieve 3D display. Furthermore, an illumination power of 3.5 watt is sufficient to lighten a 31.5-inch light field display，which takes up 1.5% of the illumination power required for planar display of similar configuration.

In this paper, we extend the Merton model of investment in discrete time to the cases when there is a finite number of investors and the market is with frictions represented by convex penalty functions defined for each investor. In the main result of this paper, we proved the existence of optimal strategy of investment by using a new approach based on the formulation of an equivalent general equilibrium economy model.

For the ground-state properties of gas-phase nanomolecules with multi-reference character, thermally-assisted-occupation density functional theory (TAO-DFT) has been recently found to outperform the widely used Kohn-Sham density functional theory, when the conventional exchange-correlation energy functionals are employed. Aiming to explore solvation effects on the ground-state properties of nanomolecules with multi-reference character at a minimal computational cost, we combine TAO-DFT with the polarizable continuum model (PCM). To show its usefulness, TAO-DFT-based PCM (TAO-PCM) is employed to study the electronic properties of linear acenes in three different solvents (toluene, chlorobenzene, and water). According to TAO-PCM, in the presence of these solvents, the smaller acenes should have nonradical nature, and the larger acenes should have increasing polyradical nature, showing remarkable similarities to the past findings in the gas phase.

Given the importance of menstrual blood in the pathogenesis of endometriosis and the multifunctional roles of menstrual mesenchymal stem cells (MenSCs) in regenerative medicine, this issue has gained prominence in the scientific community. Moreover, recent reviews highlight how robust the integrated assessment of omics data is for endometriosis. To our knowledge, no study has applied the multi-omics approaches to endometriosis MenSCs. It is a case-control study at a university-affiliated hospital. MenSCs transcriptome and proteome data were obtained by RNA-seq and UHPLC-MS/MS detection. Among the differentially expressed proteins and genes, we emphasize ATF3, ID1, ID3, FOSB, SNAI1, NR4A1, EGR1, LAMC3, and ZFP36 genes and MT2A, TYMP, COL1A1, COL6A2, and NID2 proteins that were already reported in the endometriosis. Our functional enrichment analysis reveals integrated modulating signaling pathways such as epithelial-mesenchymal transition (↑) and PI3K signaling via AKT to mTORC1 (↓in proteome), mTORC1 signaling, TGF beta signaling, TNFA signaling via NFkB, and response to hypoxia via HIF1A targets (↑in transcriptome). Our findings highlight primary changes in the endometriosis MenSCs, suggesting that the chronic inflammatory endometrial microenvironment can modulate these cells, providing opportunities for endometriosis etiopathogenesis. Moreover, they identify challenges for future research leveraging knowledge for regenerative and precision medicine in endometriosis.

Land cover mapping provides spatial information on the physical properties of the Earth’s surface, for various classes of wetlands, artificial surface and constructions, vineyards, water bodies, etc. Having reliable information on land cover is crucial to developing solutions to a variety of environmental problems such as destruction of important wetlands/forests, and loss of fish and wildlife habitats. This has made land cover mapping one of the most widespread application areas in remote sensing computational imaging. However, due to the differences between modalities in terms of resolutions, content, and sensors, integrating complementary information that multi-modal remote sensing imagery exhibits into a robust and accurate system still remains challenging, and classical segmentation approaches generally do not give satisfactory results for land cover mapping. In this paper, we propose a novel dynamic deep network architecture, AMM-FuseNet, that promotes the use of multi-modal remote sensing images for the purpose of land cover mapping. The proposed network exploits the hybrid approach of the Channel Attention mechanism and Densely Connected Atrous Spatial Pyramid Pooling (DenseASPP). In the experimental analysis, in order to to verify the validity of the proposed method, we test AMM-FuseNet applied to four datasets whilst comparing it to the 6 state-of-the-art models of DeepLabV3+, PSPNet, UNet, SegNet, DenseASPP, and DANet. In addition, we also demonstrate the capability of AMM-FuseNet under minimal training supervision (reduced number of training samples) compared to the state-of-the-art, achieving less accuracy loss even for the case with 1/20 of the training samples.

Pedestrian multi-target tracking technology plays an important role in artificial intelligence, driverless, virtual reality and other fields. The pedestrian multi-target tracking algorithm DeepSORT based on detection is widely used in industry. It mainly tracks multiple pedestrian targets continuously and keeps their ID unchanged. In order to improve the applicability and tracking accuracy of DeepSORT algorithm, this paper improved the IOU distance measurement in the matching process. At the same time, ResNet50 is used as the feature extraction backbone network, and combined with FPN (Feature Pyramid Network), the appearance features of multi-layer pedestrians are fused to improve the tracking accuracy of DeepSORT algorithm. The proposed algorithm is verified on the public data set MOT-16 and it’s tracking accuracy is enhanced to 4.1%.

The present paper is concerned with the study of the quality of life index. Such an index has become an important index for measuring the well-being of individuals. However, the quality of life index is always a subjective, intangible, and often hard to quantify with precision due to the lack of quantitative models dealing with. The main goal of the present paper is thus to propose a mathematical, quantitative model for the measurement of a quality of life index. The main novelty is firstly the construction of a wavelet dynamic multiscale model to quantify and investigate the effect of time scale on the quality of life index measuring. The proposed procedure is acted empirically on a sample corresponding to Saudi Arabia as a case of study during the period from 2003 to 2020 as part of the 2030-vision plan. Saudi Arabia has implemented the so-called 2030-vision plan where the quality of life improvement is one of the main goals to be attempted. The findings show that wavelets are capable to localize the time-wise behavior of the index contrarily to classical studies which estimate a global view of the index. Moreover, the study shows the link between the quality of life behavior and many other indices.

In this study, a new method for synthesizing Au-NaYF4:Yb3+/Er3+-DSPE-PEG2K nanocomposites was introduced. Using a hydrothermal method, the synthesized Yb3+- and Er3+-codoped NaYF4 upconversion luminescent materials and Au nanoparticles were doped into upconversion nanomaterials and modified with DSPE-PEG2k up-conversion nanomaterials. This material is known as Ag-UCNPs-DSPE-PEG2k, it improves both the luminous intensity because of the doped Au nanoparticles and has low cytotoxicity because of the DSPE-PEG2k modified. Exciting UCNPs with a wavelength of 980nm near-infrared light will emit light with a wavelength of 520nm to further excite gold nanoparticles to convert light energy into heat. Successful synthesized gold nanoparticles was confirmed using transmission electron microscopy (TEM). The morphology of UCNPs was observed using scanning electron microscopy (SEM), and the mapping confirmed the successful doping of Au nanoparticles. Fluorescence spectra were used to compare changes in luminescence intensity before and after doping Au nanoparticles. The cytotoxicity of Au-UCNPs-DSPE-PEG2K was tested via the cell counting kit-8 (CCK-8) method, and its imaging ability was characterized using the Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) method.

Background: The COVID-19 pandemic has disproportionately affected people from more deprived communities. The experience of Long Covid is similarly distributed but very few investigations have concentrated on the needs of this population. The aim of this project was to co-produce an acceptable intervention for people with Long Covid, living in communities recognised as more deprived. Methods: The intervention was based on a multi-disciplinary team using approaches from sport and exercise medicine and functional rehabilitation. The co-production process was undertaken with a stakeholder advisory group and patient public involvement representation. This study identified participants by postcode and the indices of multiple deprivation (IMD); recruitment and engagement were supported by an existing health and wellbeing service. A virtual ‘clinic’ was offered with a team of professional practitioners who met participants three times each; to directly consider their needs and offer structured advice. The acceptability of the intervention was based on the individual’s participation and their completion of the intervention. Results: Ten participants were recruited with eight completing the intervention. The partnership with an existing community health and wellbeing service was deemed to be an important way of reaching participants. Two men and six women ages ranging from 38 to 73 were involved and their needs were commonly associated with fatigue, anxiety and depression with overall de-conditioning. None reported serious hardship associated with the pandemic although most were in self-employment/part-time employment or were not working due to retirement or ill-health. Two older participants lived alone, and others were single parents and had considerable challenges associated with managing a household alongside their Long Covid difficulties. Conclusions: This paper presents the needs and perspectives of eight individuals involved in the process and discusses the needs and preferences of the group in relation to their support for self- managed recovery from Long Covid.

A graph based path planning method consisting of off-line part and on-line part for multi-UAV system in windy condition is proposed. In the off-line part, the task area is divided into grids. When two nodes is close enough, they are connected and weighted by the cost, obtained by solving an optimization problem based on difference method, between them. In order to ensure the accuracy of the difference method, the adjacent radius is set to be small enough. In order to ensure the generated paths close to analytical solution, the grid size is set to be much smaller than the adjacent radius. The shortest path algorithm is used to update the adjacent matrix and path matrix. In the on-line part, the target position assignment and optimal velocity can be obtained by accessing the adjacent matrix and path matrix. At the end of this paper, some numerical examples are taken to illustrate the validity of our method and the influence of the parameters.

To realize precise control of the quantum dots (Qdots) device, multi-channel precision bias source plays the key role. In this paper, the 16-channel high precision bias source with 18-bit resolution for Qdots device was designed. The prototype was made and its performance was tested. The short time fluctuations can reach 50μV. The step response time is less than 3μs. The resolution, stability, linearity and dynamic range of the bias source exhibits good performance. What's more, the bias source can be controlled locally and online. The results show that it is one effective and feasible topology for experiments in Qdots device application.

Identifying cracks in the incipient state is essential to prevent the failure of engineering structures. Detection methods relying on the analysis of the changes in modal parameters are widely used because of the advantages they present. In our previous research, we have found that eigenfrequencies were capable of indicating the position and depth of damage when sufficient vibration modes were considered. The damage indicator we developed was based on the relative frequency shifts (RFS). To calculate the RFSs for various positions and depths of a crack, we established a mathematical relation that involved the squared modal curvatures in the healthy state and the deflection of the healthy and damaged beam under dead mass, respectively. In this study, we propose to calculate the RFS for beams with several cracks by applying the superposition principle. We demonstrate that this is possible if the cracks are far enough from each other. In fact, if the cracks are close to each other, the superposition method does not work and we distinguish two cases: (i) when the cracks affect the same beam face, the frequency drop is less than the sum of the individual frequency drops, and (ii) on the contrary, cracks on opposite sides cause a decrease in frequency, which is greater than the sum of the frequency drop due to individual damage. When the RFS curves are known, crack assessment becomes an optimization problem, the cost function being the distance between the measured RFSs and all possible RFSs for several vibration modes. Thus, the RFS constitutes a benchmark that characterizes damage using only the eigenfrequencies. We can accurately locate multiple cracks and estimate their severity trough experiments and thus prove the reliability of the proposed method.

The paper describes problems with the current additive manufacturing chain before considering additive manufacturing as part of a modern manufacturing chain. Additive manufacturing can be used for near net-shape for finishing, for repair or for adding special features which cannot be made with traditional manufacturing. This paper describes how STEP-NC deals with these different scenarios in terms of accuracy, multi-material and variation of slice direction. The possibilities of multi-material objects also raises questions about the design of such objects and how these need to be handled by an advanced controller. The paper also describes non-planar slicing. Curved direction and cylindrical direction are shown to improve the accuracy of curved structure additive manufacturing. STEP-NC using boundary representation has better capability of depicting complex internal structures for additive processes. By using exact model of the final product represented by STEP-NC, the paper demonstrates improvements in data size reduction, slicing accuracy, and precise manipulation of internal structure.

Multi-criteria decision-making (MCDM) methods and techniques have been applied to many real-world problems in different fields of engineering science and technology. The evaluation based on distance from average solution (EDAS) method is a new and efficient MCDM method. The aim of this study is to propose a modification to address two exceptional cases in which the EDAS method fails to solve an MCDM problem.

Hydraulic conductivity is the key and one of the most uncertain parameters in groundwater modeling. The grid based numerical simulation require spatial distribution of sampled hydraulic conductivity at un-sampled locations in the study area. This spatial interpolation has been routinely performed using variogram based models (two-point geostatistics methods). These traditional techniques fail to capture the complex geological structures, provides smoothing effects and ignore the higher order moments of subsurface heterogeneities. In this work, a multiple-point geostatistics (MPS) method is applied to interpolate hydraulic conductivity data which will be further used in WASH123D numerical groundwater simulation model for regional smart groundwater management. To do this, MPS need ‘training images (TIs) as a key input. TI is a conceptual model of subsurface geological heterogeneity which was developed by using concept of ages, topographic slope as an index criteria and knowledge of geologist. After considerations of full physics of study area, an example shows the advantages of using multiple-point geostatistics compared with the traditional two-point geostatistics methods (such as Kriging) for the interpolation of hydraulic conductivity data in a complex geological formation.

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used to define the building blocks to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources.

The proportion of area under various crops at a given point in time, known as a cropping pattern, plays an essential role in determining the level of agricultural production. In this study, cropping patterns of three sub-counties in Murang’a County, a typical African smallholder farming area in Kenya, were mapped. Specifically, we compared the performance of eight classification scenarios for mapping cropping patterns; namely using (i) only Sentinel-2 reflectance bands (S2), (ii) S2 and S2 derived vegetation indices (VIs); (iii) S2 and S2 vegetation phenology (VP); (iv) S2 and Sentinel-1 radar backscatter data (S1); (v) S2, VIs, and S1; (vi) S2, VP, and S1; (vii) S2, VIs and VP, and (viii) S2, VIs, VP and S1. Reference data of the dominant cropping patterns and non-croplands were collected. The guided regularized random forest (GRRF) algorithm was used to select the optimum variables and to perform the respective classification for each scenario. The most accurate result of the overall accuracy of 93.16% was attained from the scenario (viii) S2, VIs, VP, and S1. The McNemar’s test of significance did not show significant differences (p≤0.05) among the tested scenarios. Our study demonstrated the strength of GRRF and the synergetic advantage of S2 and S1 derivatives to map cropping patterns in a heterogeneous landscape where high resolution imagery are inaccessible. Our cropping pattern mapping approach can be used in other sites of relatively similar agro-ecological conditions.

In research applications across several areas, noise removal is indispensable for accuracy of final results. Noise is caused due to physical principals, such as background electronic noise, quantum effect, and wave rebound effect to name a few. Noise removal can help improve results in medical, astronomy, defense, and numerous other fields. Addressing this limitation would result in potentially low cost, automatic, and reliable systems. In this paper, a generalized new approach i.e. Multi-Frame Noise Removal (MFNR) is proposed for noise removal. Given any type of data, the probability density function (PDF) of the noise can be determined. Herein, we extracted the noise PDF parameters using KDE (Kernel Density Estimation). Because the data is corrupted by “deterministic” noise, hence can be cleaned. This could be used as a general purpose noise removal tool. The data point with same position in multiple frames helps us determine the noise PDF characteristics and hence making it possible to remove noise. The conventional wisdom which states that noise removal and detail preservation are contrary to each other is not true for MFNR. Experimental results validate our proposed method which showed practically complete noise reduction based on number of frames used, as compared to existing benchmark methods.

The interaction between single or a fixed number of photons with a single absorber is of fundamental interest in quantum technology. The harnessing of light matter interactions at the single particle limit has several potential applications ranging from quantum communication and quantum metrology to quantum imaging. In this letter, a setup for heralded two-photon absorption at the single absorber level is proposed. The setup is based on a heralded two-photon source utilizing spontaneous parametric down-conversion, entanglement swapping and sum frequency generation for joint detection. The feasibility of the scheme is discussed by reviewing recent achievements in utilizing entangled and correlated photons for two-photon absorption as well as single photon absorption experiments at the limit of single absorbers in the context of applications in imaging (here mainly microscopy) and spectroscopy.

Changes in land-use have been observed in banana-based systems in the African Great Lakes region affected by Xanthomonas wilt disease (XW) of banana. Through participatory focus group discussions (FGDs) and the 4-cell method, changes in land-use were retrospectively assessed in 13 XW-affected landscapes/villages along a 230 km transect from Masisi (XW arrived in 2001) to Bukavu (XW arrived around 2014) in eastern Democratic Republic of Congo during 2015. The four-cell chart ranked land-use by mapping the area under production and the number of households involved in production. Farmers’ perceptions on the sustainability of new land-uses were also documented. Soil nutrient content and erosion levels were measured for five major land-use options/ trajectories on 147 fields across 55 farms in three landscapes along the transect. From being ranked the most important crop (92% of landscapes i.e. produced on large areas of land and by many households) before XW outbreaks, its importance had declined with most households in 36% of the landscapes growing it on smaller farms while in 64% of cases by few households on smaller pots. Farmers uprooted entire banana mats or fields, expanding land under other crops, mainly beans, taro, sweet potato, cassava, maize, coffee and eucalyptus. Species richness did not change at landscape level, though 21 crops were introduced at farm level. Land-use for banana is however still perceived to be more sustainable due to its multi-functional roles. Soils under banana plots were found in general to be better in their chemical attributes while high erosion levels (Mg ha-1 year-1) were observed under cassava (1.7-148.9) compared with banana (0.3-10.7) and trees (0.3-5.9). The current shift away from banana could thus have profound effects on supply of key services and sustainability of the production systems. This study offers a good basis/entry point for interventions in the XW-affected landscapes.

Accurate channel estimation is of utmost importance for massive MIMO systems that allow providing significant improvements in spectral and energy efficiency. In this work, we investigate the spectral efficiency performance and present a channel estimator for multi-cell massive MIMO systems subjected to pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without prior knowledge of the inter-cell large-scale channel coefficients and noise power. The estimator approximates the performance of a linear Minimum Mean Square Error (MMSE) as the number of antennas increases. Following, we derive a lower bound closed-form spectral efficiency of the Maximum Ratio Combining (MRC) detector in the proposed channel estimator. The simulation results highlight that the proposed estimator performance approaches the linear minimum mean square error (LMMSE) channel estimator asymptotically.

Accurate channel estimation is of utmost importance for massive MIMO systems to provide significant improvements in spectral and energy efficiency. In this work, we present a study on the distribution of a simple but yet effective and practical channel estimator for multi-cell massive MIMO systems suffering from pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without previous knowledge of the inter-cell large-scale channel coefficients and noise power, asymptotically approximating the performance of the linear MMSE estimator as the number of antennas increases. We prove that the distribution of the proposed channel estimator can be accurately approximated by the circularly-symmetric complex normal distribution, when the number of antennas, M, deployed at the base station is greater than 10.

Existing methods for detecting magnetic leakage signals from damaged wire ropes require axial saturation magnetisation, and the accuracy of the detection equipment depends on the saturation degree of magnetisation. Moreover, the expected magnetisation effect is usually difficult to achieve owing to the special characteristics of the rope structure, diameter, and operating environment of the wire rope. Consequently, in addition to other issues, the detection accuracy and versatility of the equipment are low. In this study, a method based on spatial multidimensional orthogonal array loop magnetisation for detecting mine wire rope defects is proposed. Firstly, a new sensor excitation structure model is developed. Then a method of radiant magnetic flux of permanent magnet array is analysed, and the influence law of the number of permanent radiant magnetic blocks on the magnetisation effect is studied. In addition, a method of wire rope detection based on the principle of clustering is investigated, according to which the influence law of the shape, structure, and size of the polyurethane device on the effect of magnetisation is discussed. Finally, through laboratory experiments, the test model and proposed method are verified. The results show that the magnetisation effect is better and more cost-effective when the number of permanent magnet radiation magnetic block is n=8, and the proposed detection method can effectively distinguish damaged wire rope joints. Furthermore, the proposed equipment achieved signal-to-noise ratio of the signals, improving the reliability of damage detection.

Negative corona discharges occur widely in high voltage transmission lines and charged aircraft, which can cause strong electromagnetic interference. Negative corona discharge is typically performed simultaneously at multiple discharge points. In this study, the current and its EM radiation characteristics of single-needle and multi-needle negative corona discharge in different conditions were tested. The current and electromagnetic radiation characteristics of the two discharge structures were compared. The dipole radiation model was established to analyze the EM radiation characteristics of the negative corona discharge.The results show that, It is only when the voltage reaches a certain threshold that the current and electromagnetic radiation fields of the multi-needle discharge structure will be superimposed and their amplitudes will increase significantly. The frequency of electromagnetic radiation signal does not change with the number of needles, cathode geometry and applied voltage, but only depends on ambient pressure. It provides a basis for detecting corona discharge sources under different conditions.

In the oil palm industry, stands age is an important parameter to monitor the sustainability of cultivation, to develop the growth yield model, to identify the disease or stressed area, and to estimate the carbon storage capacity. This research is focused to estimate and distinguish oil palm stands age based on crown/ canopy density obtained using Forest Canopy Density (FCD) model derived from four indices as follows; Advanced Vegetation Index, Bare Soil Index, Shadow Index, and Thermal Index. FCD model employs multi temporal image analysis resulting four classes of oil palm stands age categorized as seed with FCD value of 29–56% (0 years), young with FCD value of 56–63% (1–9 years), teen with FCD value of 63–80% (10–15 years), and mature with FCD value of >80% (>15 years). Minimum canopy density value is 29% even in the zero years old indicates incomplete land clearance or the type of seed planted in the land.

With quick improvement in the field of network, everything becomes online. Remote user authentication is a mechanism in which remote server verify the correctness of user over common or public channel. Remote user authentication can be Single server authentication or Multi server authentication. The disadvantage of single server authentication is that the user needs to recall user id and password for each service, he/she need to utilize, however it can overcome by Multi-server authentication in which user needs to register himself with Registration Center (RC) for the first run through and after that onwards he can utilize each service (which are given by servers, associated with RC) by recollecting only one user id and password. In this paper, we analyze Chen's authentication scheme (based on multi server authentication) and show that this scheme is vulnerable to password guessing attack, replay attack, RC spoofing attack, session key verification attack and perfect forward secrecy attack. In this Paper, we propose a biometric based remote user authentication scheme in multi-server environment. Proposed scheme is more secure and efficient as compared to chen's scheme\cite{23}.

UAS-based multi-spectral imagery is becoming increasingly popular for the improved monitoring and managing of various horticultural crops. However, for UAS data to be used as an industry standard for assessing tree structure and condition as well as production parameters, it is imperative that the appropriate data collection and pre-processing protocols are established to enable multi-temporal comparison. There are several UAS-based radiometric correction methods commonly used for precision agricultural purposes. However, their relative accuracies have not been assessed for data acquired in complex horticultural environments. This study assessed the variations in estimated surface reflectance values of different radiometric corrections applied to multi-spectral UAS imagery acquired in both avocado and banana orchards. We found that inaccurate calibration panel measurements, inaccurate signal-to-reflectance conversion, and high variation in geometry between illumination, surface, and sensor viewing produced significant radiometric variations in at-surface reflectance estimates. Potential solutions to address these limitations included appropriate panel deployment, site-specific sensor calibration, and appropriate BRDF correction. Future UAS based horticultural crop monitoring can benefit from the proposed solutions to radiometric corrections to ensure they are using comparable image-based maps of multi-temporal biophysical properties.

There is an ongoing global pandemic of human respiratory syncytial virus (RSV) infection that results in substantial annual morbidity and mortality. In Australia, RSV is the major cause of acute lower respiratory tract infections (ALRI). Nevertheless, little is known about the extent and origins of genetic diversity of RSV in Australia, nor the factors that shape this diversity. We conducted a genome-scale analysis of RSV infections in New South Wales (NSW). RSV genomes were successfully sequenced for 144 specimens collected between 2010-2016. Of these, 64 belonged to the RSVA and 80 to the RSVB subtype. Phylogenetic analysis revealed a wide diversity of RSV lineages within NSW and that both subtypes evolved rapidly in a strongly clock-like manner, with mean rates of approximately 6-8 x 10^-4 nucleotide substitutions per site per year. There was only weak evidence for geographic clustering of sequences, indicative of fluid patterns of transmission within the infected population, and no evidence of any clustering by patient age such that viruses in the same lineages circulate through the entire host population. Importantly, we show that both subtypes circulated concurrently in NSW with multiple introductions into the Australian population in each year, and only limited evidence for multi-year persistence.

We describe a multi-resolution approach for audio classification and illustrate its application to the open data set for environmental sound classification. The proposed approach utilizes a multi-resolution based ensemble consisting of targeted feature extraction of approximation (coarse scale) and detail (fine scale) portions of the signal under the action of multiple transforms. This is paired with an automatic machine learning engine for algorithm and parameter selection and the LSTM algorithm, capable of mapping several sequences of features to a predicted class membership probability distribution. Initial results show an improvement in multi-class classification accuracy.

Abstract: Comparing outcrop data to laboratory results is important to verify and validate experiments of analogue and reservoir materials especially regarding conditions for deformation experiments. This is important better understand highly complex carbonate reservoir strata and their response to changes in subsurface conditions, reducing subsurface uncertainty. This study develops methods to allow for a more straightforward comparison of outcrop data (m-scale) with experimentally created fracture arrays developed in cylindrical samples (cm-scale). The main objective is to assess usefulness of experimentally-produced fracture networks as analogues for subsurface structures, typically at the meter and above scale by developing new techniques to use the lab deformation. It analyses key characteristics of laboratory-induced fracture networks by adapting scanline methods to use with x-ray tomography (XRT) images to allow for comparison with outcrop and field data. To test and verify these new methods two low permeability carbonate samples were used for deformation testing and analysis. Applying the different scanline methods we show that they can be used to analyse lab induced fractures (mm to cm-scale) identified in XRT images for comparison with outcrop data (m-scale). In addition, these methods also allow for quantification of fracture network attributes e.g. fracture spacing, fracture apertures, orientation. This new data bridges the gap between micro-scanlines using thin sections and outcrop scanlines.

The RPL protocol is a routing protocol for low power and lossy networks. In such a network, energy is a very scarce resource; so many studies are focused on minimizing global energy consumption. End-to-end latency is another important performance indicator of the network, but existing research tends to focus more on energy consumption and ignore the end-to-end delay of data transmission. In this paper, we propose a kind of energy equalization routing protocol to maximize the surviving time of the restricted nodes so that the energy consumed by each node is close to each other. At the same time, a multi-path forwarding route is proposed based on the cache utilization. The data is sent to the sink node through different parent nodes at a certain probability, not only by selecting the preferred parent node, thus avoiding buffer overflow and reducing end-to-end delay. Finally, the two algorithms are combined to accommodate different application scenarios. The experimental results show that the proposed three improved schemes improve the reliability of the routing, extend the lifetime of the network, reduce the end-to-end delay, and reduce the number of DAG reconfiguration.

Recent analyses of cosmic microwave background surveys have revealed hints that there may be a non-trivial running of the running of the spectral index. If future experiments were to confirm these hints, it would prove a powerful discriminator of inflationary models, ruling out simple single field models. We discuss how isocurvature perturbations in multi-field models can be invoked to generate large runnings in a non-standard hierarchy, and find that a minimal model capable of practically realising this would be a two-field model with a non-canonical kinetic structure. We also consider alternative scenarios such as variable speed of light models and canonical quantum gravity effects and their implications for runnings of the spectral index.

The weight coefficients of the diaphragm spring depend on experiences in the traditional optimization. However, this method not only cannot guarantee the optimal solution but it is also not universal. Therefore, a new optimization target function is proposed. The new function takes the minimum of average compress force changing of the spring and the minimum force of the separation as total objectives. Based on the optimization function, the result of the clutch diaphragm spring in a car is analyzed by the non-dominated sorting genetic algorithm (NSGA-II) and the solution set of Pareto is obtained. The results show that the pressing force of the diaphragm spring is improved by 4.09%by the new algorithmand the steering separation force is improved by 6.55%, which has better stability and steering portability. The problem of the weight coefficient in the traditional empirical design is solved. The pressing force of the optimized diaphragm spring varied slightly during the abrasion range of the friction film, and the manipulation became remarkably light.

The airport ground handling service (AGHS) equipment vendor selection (AGHSEVS) problem is critical for ramp work safety management, because AGHS equipment malfunctions affect airport ramp work safety. Appropriate vendor selection can prevent aircraft damage and delays in airlines schedules, and ensure reliable and high-quality ground handling service. The AGHSEVS problem is a time-consuming and complex process that requires professional knowledge and experience to make judgments. Specifically, AGHSEVS is a multi-criteria decision-making (MCDM) problem. Previous research has seldom integrated MCDM methods with linear and goal programming to solve the AGHSEVS problem. The objective of this study was to develop a new system evaluation model for AGHSEVS by considering both qualitative and quantitative methods. We test the proposed approach on an AGHS company in Taiwan.

We conducted a retrospective analysis of the immunohistochemical (IHC) staining GRP94, an ER stress protein on large B-cell lymphoma (LBCL) cells, intracellular p53, and 15 factors involved in the metabolism of CHOP regimen :AKR1C3 (HO-metabolism), CYP3A4 (CHOP-metabolism) and HO efflux pumps (MDR1, MRP1). The study subjects were 42 patients with LBCL at our hospital. IHC staining using antibodies against the 17 factors. The odds ratios by logistic regression analysis using a dichotomous variable of CR, non-CR/relapse were statistically significant: for MDR1, MRP1, and AKR1C3. The overall survival (OS) after R-CHOP was compared by the log-rank test. The four groups showed that Very good (5-year OS, 100%) consisted of 4 patients showed negative IHC staining for both GRP94 and CYP3A4. Very poor (1-year OS, 0%), consisted of 3 patients who showed positive results of IHC for both GRP94 and CYP3A4. The remaining 35 patients comprised two subgroups: Good (5-year OS 60-80%.): 15 patients who showed negative staining for both MDR1 and AKR1C3, Poor: 5-year OS, 10-20%) :20 patients who showed positive staining for either MDR, AKR1C3,,MRP1 or p53. The Histological Prognostic Index (HPI) (The four groups: Very poor, Poor, Good, and Very pood) is a breakthrough method for stratifying patients based on factors involved in the development of treatment resistance.

We conducted a retrospective evaluation of the clinical outcomes and prognostic factors in patients with non-metastatic castration-resistant prostate cancer (nmCRPC) treated with first-line androgen receptor signaling inhibitors (ARSI) in real-world clinical practice in Japan. Between 2012 and 2023, a total of 127 consecutive patients with nmCRPC received ARSI treatment. Overall survival (OS), metastatic-free survival (MFS), and prostate-specific antigen progression–free survival (PSA-PFS) from ARSI initiation were assessed using Kaplan–Meier methodology. Clinical factors associated with OS in nmCRPC were analyzed using the Cox proportional hazards model. Among the patients, 72, 26, 12, and 17 received enzalutamide (ENZ), abiraterone (ABI), apalutamide (APA), and darolutamide (DARO) as first-line therapy. The median OS and MFS for all patients were 79.0 and 42.0 months, respectively. Median PSA-PFS was 27.0, 20.0, 10.0, and 14.0 months for patients treated with ENZ, ABI, APA, and DARO, respectively (p = 0.33). Multivariate analysis revealed that a baseline PSA level ≥3.67 ng/ml at ARSI initiation was significantly associated with poorer OS (p = 0.002). ARSI demonstrated favorable efficacy in nmCRPC patients. There were no significant differences in clinical outcomes among different types of ARSI therapy for nmCRP. Elevated baseline PSA at ARSI initiation was significantly associated with poorer OS.

The prevalence of multidrug-resistant Gram-negative infections, particularly carbapenem-resistant strains, has become a significant global health concern. Ceftazidime-avibactam (CZA) has emerged as a promising treatment option. However, data on its efficacy and safety in children are scarce, necessitating further investigation. We conducted a retrospective study at a tertiary hospital in Spain from February 2019 to January 2022. Pediatric patients (<16 years) treated with CZA for confirmed or suspected multidrug-resistant Gram-negative infections were included. Clinical and microbiological characteristics, treatment approaches, and outcomes were examined. Eighteen children received CZA treatment. All had complex chronic conditions, with the most frequent underlying main diseases being liver transplantation (n=8) and biliary atresia (n=4). The predominant type of infection for which they received CZA was intra-abdominal infections caused or suspected to be caused by OXA-48-producing Klebsiella pneumoniae. CZA was generally well tolerated. Within the first month of starting CZA therapy, 2 patients died, with one case directly linked to the infection’s fatal outcome. Some patients needed repeated courses of therapy due to recurrent infections, yet no resistance development was noted. In summary, the use of CZA showed effectiveness and safety, while the lack of resistance development highlights CZA’s potential as a primary treatment option against OXA-48-producing infections.

The current globally dominant SARS-CoV-2 variants are showing immune escape and reduced susceptibility to antiviral drugs. Therefore, agencies responsible for drug evaluation and regula-tion such as the FDA and EMA are revising their emergency authorization use of several COVID-19 neutralizing antibodies. These NAbs proved to be unlikely effective against new variants espe-cially Omicron descendants and several pharmaceutical companies are pursuing the development of more potent neutralizing antibodies. To address the issue of using in silico prediction for the rapid assessment of anti-SARS-CoV-2 MAbs neutralization power, we used a computational method we developed previously, to evaluate 10 SARS-CoV-2 antibodies propensity to neutralize the new Omicron’s subvariants Eris (EG.5) and Pirola (BA.2.86) based on comparative binding affinity and previous experimental and clinical observations. Nine of these MAbs were once granted emergency use authorization, and one is currently under clinical investigation. The rapid, cost-effective in silico evaluation provided reliable predictions consistent with published clinical and experimental data. Furthermore, our data showed new potential therapeutic MAbs combi-nation that could be effective for the treatment countermeasure of the new Omicron’s subvariants Eris (EG.5) and Pirola (BA.2.86).

The demand for efficient processes through a comprehensive understanding and optimization of welding conditions continues to grow in the manufacturing industry. This study involves heat-resistant 2.25 Cr-1 Mo V-groove steel welding using the square-waveform alternating cur-rent. Experiments were conducted to build the relationship between input variables—such as current, frequency, electrode negativity ratio, and welding speed—and process performance, such as penetration, bay area, deposition rate, melting efficiency, percentage dilution, flux–wire ratio, and heat input. The process was analyzed in light of the defect-free high-deposition weld groove weld, the sensitivity to process parameters, and the optimization and development of the process map. The study proposes an innovative approach to reducing the cost and time of optimizing the one-pass-each-layer V-groove welding process using bead-on-plate welds. Square waveform welding creates a metallurgical notch in the form of a bay at the fusion boundary that can be minimized by selecting appropriate welding conditions. The square waveform submerged arc welding is more sensitive towards changes in current and welding speed than the frequency and electrode negativity ratio; however, the electrode negativity ratio and frequency are minor but helpful parameters to achieve optimal results. The proximity of the planned and experimental results to within 3% confirms the validity of the proposed approach. The investigation shows that 90% of the maximum deposition rate is possible for one-pass-each-layer V-groove welds within heat input and weld width constraints.

The purpose of this study is to examine the relationship between the institutional investors which can affect financial performance for corporate sustainability on the income smoothing. Therefore, this study focus on the connection between the nature of stock rights and income smoothing in China. For this study, hypotheses were established on the relationship each state-controlled companies, income smoothing, and information equilibrium of individual investors, and empirical analysis was conducted through related variables. The analysis results are summarized in three categories as follows. First, this research finds that state-controlled firms (CONTs) prefer income smoothing activities compared to non-state-controlled firms for the long-term sustainable development of firms using data from 2011 to 2019. Second, this study found out that Institutional investors support the behavior of CONTs to smooth their earnings because this behavior is seen as an attempt by CONTs to convey valuable private information to other investors. Third, we was able to discover that institutional investors' monitoring effect is predominantly driven by pressure-resistant institutional investors. This research complements the lack of empirical research on income smoothing and enable to give a guideline that the type of stock rights is a critical key determinant of participation in income smoothing activities for stable growth and sustainability in the future.

This review critically evaluates the role of Antibody-drug conjugates (ADCs) in the treatment of urothelial cancer, exploring their therapeutic potential and addressing the scientific and clinical challenges encountered in the development of these agents. It also discusses the recent approvals and clinical trials that are shaping the future of ADC therapy in this field. Through a detailed examination of the mechanism of action of ADCs, including the bystander effect, this paper aims to highlight both the successes and the limitations of these drugs in clinical settings. The main objective of this work is to provide a thorough overview of the current state of ADCs in urothelial cancer treatment, elucidating how these drugs can offer improved outcomes for patients. By discussing the broader implications of ADC technology and its integration into existing treatment paradigms, this review outlines the next steps in research and application necessary to overcome the existing challenges and harness the full potential of ADCs in cancer therapy.

Curcumin is a nutraceutical known to have numerous medicinal effects including anticancer activity. However, due to its poor water solubility and bioavailability, the therapeutic impact of curcumin against cancer, especially breast cancer, has been constrained. Encapsulating curcumin into chitosan nanoparticles (CHNPs) is an effective method to increase its bioavailability as well as antitumorigenic activity. In the present study, the effect of curcumin encapsulated CHNPs (Cur-CHNPs) on cell migration, targeted homing and tumour growth was examined using in vitro and in vivo breast cancer models. Cur-CHNPs possessed monodispersed nature with long term colloidal stability, and demonstrated significant inhibition of cell viability in vitro, which was potentiated by 5-fluorouracil (5-FU). Outcomes of the in vivo imaging studies confirmed effective tumour targeting and retention ability of Cur-CHNPs, thereby suppressing breast tumour growth in mice models. Overall, the results demonstrated that Cur-CHNPs, could be an effective candidate drug formulation for management of breast cancer.

Carbon nanodots (CNDs) have garnered significant attention as viable drug delivery vehicles in recent years, especially in the field of phytomedicine. Although there is much promise for therapeutic applications with phytomedicine, its effectiveness is frequently restricted by its low solubility, stability, and bioavailability. This paper offers a thorough synopsis of the developing field of phytomedicine drug delivery based on CND. It explores CND synthesis processes, surface functionalization strategies, and structural and optical characteristics. Additionally, the advantages and difficulties of phytomedicine are examined, with a focus on the contribution of drug delivery methods to the increased effectiveness of phytomedicine. The applications of CNDs in drug delivery are also included in the review, along with the mechanisms that underlie their improved drug delivery capabilities. Additionally, it looks at controlled release methods, stability augmentation, and phytomedicine loading tactics onto CNDs. The potential of polymeric carbon nanodots in drug delivery is also covered, along with difficulties and prospective directions going forward, such as resolving toxicity and biocompatibility issues. In summary, the present review highlights the encouraging contribution of CNDs to the field of drug delivery, specifically in enhancing the potential of phytomedicine for therapeutic purposes.

In this work, we report the synthesis of a new thiosemicarbazone-based drug of N'-(di(pyridin-2-yl)methylene)-4-(thiazol-2-yl)piperazine-1-carbothiohydrazide (HL) featuring a thiazole spectator for the efficient coordination with Cu(II) to give [CuCl(L)]2 (1) and [Cu(NO3)(L)]2 (2). Both 1 and 2 exhibit dimeric structures ascribed to the presence of di-2-pyridylketone moieties that demonstrate dual functions of chelation and intermolecular bridging. HL, 1 and 2 are highly toxic against hepatocellular carcinoma cell lines Hep-G2, PLC/PRF/5, and HuH-7, with half maximal inhibitory concentration (IC50) values as low as 3.26 nmol/mL (HL), 2.18 nmol/mL (1), and 2.54 × 10−5 nmol/mL (2) for PLC/PRF/5. While the free ligand HL may elicit its anticancer effect via sequestration of bio-relevant metal ions (i.e. Fe3+ and Cu2+), 1 and 2 are also capable of generating cytotoxic reactive oxygen species (ROS) to inhibit cancer cell proliferation. Our preliminary pharmacokinetic studies revealed that oral administration (per os, PO) of HL has a significantly longer half-life t1/2 of 21.61 ± 9.4 h, nearly doubled as compared to that of the intravenous (i.v.) administration of 11.88 ± 1.66 h, certifying HL as an effective chemotherapeutic drug via PO administration.

Preventing or treating infections at implantation sites where the risk of bacterial contamination is high requires the development of intelligent drug delivery systems. In this work, honeycomb structures as a potential drug carrier were obtained for the first time in a fast, one-step anodization process of titanium grade 4, lasting only 60 seconds. Fourth generation oxide nanotube layers were obtained from an aqueous solution of 0.5% AgNO3 in the voltage range from 50 to 80 at 15(1) °C. The FE-SEM method showed the length of the oxide nanotubes from 1.02(2) µm at 50 V to 230(8) nm at 80 V. The EDS analysis revealed that during anodizing, silver particles are deposited on the Ti G4 up to 2.2(5) wt.%. Electrochemical measurements by open circuit potential and anodic polarization curves methods proved the improvement of in vitro corrosion resistance as a result of Ti G4 anodizing. Assessment of the anodized Ti G4 as gentamicin sulfate carrier carried out using ATR-FTIR and UV-VIS absorption spectroscopy revealed that the obtained oxide nanotube layers can be used for application of drugs directly to the tissue around the implant. This method of application allows full use of the therapeutic dose of the antibiotic used.

Diabetes is one of the metabolic syndromes that demands the great concern affecting millions of people all over the world. Viral infections were also considered as responsible for diabetes. Though, variety of medications for prevention and treatment of diabetes are available, numerous limitations are also prevailing that cannot be neglected. Precise drug-targetability, controlled drug-release, oral bioavailability, minimizing side effects are a few to consider. To address most of these shortcomings of traditional drug-delivery models, nanoformulation has been employed therein a wide range of nanoformulation models are developed. The pharmacology of a drug can be greatly enhanced through nanoformulation models in diabetes treatment in terms of enhanced bioavailability, prolonged and sustained drug-lease, maintain maximum drug concentration in serum, higher intestinal absorption, and protection from enzymatic degradation. In this review work, recently designed nanoformulation models for efficient insulin delivery and the other properties concerning diabetes such as reducing blood glucose level, total cholesterol, triglycerides, lipid profile, wound healing, elevating antioxidant enzymes etc. are discussed. Classification of the nanoformulation models is done based on the nature of the fabricating material employed in nanoformulation. This review may be helpful in designing a more efficient nanoformulation model for diabetes treatment.

Mississippi youth are demographically unique compared to that of the nation. The purpose of this study was to determine the trend of drug use among adolescents of the United States and Mississippi, and to estimate the differences of drug use prevalence as a whole, and by gender and by race. National and Mississippi YRBSS data from 2001 to 2021 were obtained for analysis. Summary statistics, prevalence ratio, and survey Chi-squared tests of independence statistics were generated for the comparison for all students, and by gender and race separately. Trend analysis was conducted using logistic regression combined with joinpoint regression. Six survey questions being studied were: have you ever used marijuana, inhalant, heroin, methamphetamines, injected drugs, and were you offered, sold, or given an illegal drug on school property during the last 12 months. Survey packages in R were used to account for the complex sampling design of YRBSS data. On the national level, all six drug related risk behaviors being studied showed significant decrease from 2001 to 2021. In Mississippi however, only “ever used marijuana” showed a trend of decrease, while three remain unchanged, and two increased. 2021 YRBSS data shows that Mississippi adolescents exhibited significantly higher prevalence of drug use, and are more likely to be offered, sold or given an illegal drug on school property. Our study suggests an urgent need for drug use intervention among Mississippi adolescents. More concerted actions at the community, school and government level are needed for reducing youth drug use and controlling the drug traffic on school property.

M184V is a single-base mutation in the YMDD domain of reverse transcriptase (RT). The M184V resistance-associated mutation is related to virological unresponsiveness to lamivudine (3TC) and emtricitabine (FTC) and induces high-level resistance to these two antiretroviral agents. M184V is rapidly selected in the setting of non-suppressive antiretroviral therapy (ART) and accumulates in the HIV reservoir. There were continuous efforts to evaluate the impact of M184V mutation on the treatment outcomes in people with HIV (PWH). Since lamivudine remains an extensively used part of recommended antiretroviral combinations, M184V is commonly detected in patients with virological failure. ART guidelines do not recommend the use of drugs impacted by resistance-associated mutations as they have been confirmed to comprise a risk factor for virological failure. However, previous authors suggest that 3TC/FTC can remain active even in the presence of M184V. Obtaining the viral resistance profile for each individual both treated or ART-naïve is a key challenge for lifelong treatment management.Given the potential benefits of lamivudine in the ART combinations, the investigation of M184V remains of high interest for clinicians and researchers. This is a review of literature for the challenges in treating both naïve and experienced individuals carrying the M184V resistance mutation, including virological failure, virological suppression, and resistance to ART.

Neurologic symptoms associated with Long COVID result from the persistent infection of SARS-CoV-2 in the nasal neuroepithelial cells, leading to inflammation in the central nervous sys-tem (CNS). As of today, there is no evidence that vaccines or medications can clear the persistent viral infection in the olfactory mucosa. Recently published clinical data demonstrate that only 5% of Long COVID anosmia patients have fully recovered during the past 2 years and 10.4% of COVID patients are still symptomatic 18 months post infection. Our group demonstrated that ep-igallocatechin-3-gallate-monopalmitate (EC16m) nanoformulations possess strong antiviral activ-ity against human coronavirus, suggesting this green tea-derived compound in nanoparticle for-mulations could be developed as an intranasally delivered new drug targeting the persistent SARS-CoV-2 infection, as well as inflammation and oxidative stress in the CNS, leading to resto-ration of neurologic functions. The objective of the current study is to evaluate the mucociliary safety of the EC16m nasal nanoformulations and the efficacy against human coronavirus. Meth-ods: nanoparticle size and Zeta potential were measured using the ZetaView Nanoparticle Tracking Analysis system; mucociliary safety was determined using MucilAir Human Nasal Epi-thelium Model; contact antiviral activity and post-infection inhibition against OC43 viral strain were assessed by TCID50 assay for cytopathic effect on MRC-5 cells. Results: the saline-based EC16 mucoadhesive nanoformulations containing 0.005 to 0.02% w/v EC16m have no significant difference in comparison to saline (0.9% NaCl) on tissue integrity, cytotoxicity, and cilia beat fre-quency. A 5-minute contact inactivated 99.9% of the β-coronavirus OC43. OC43 viral replication was inhibited by >99% after infected MAR-5 cells were treated with one of the formulations. Con-clusion: the saline-based novel EC16m mucoadhesive nasal nanoformulations rapidly inactivated human coronavirus with mucociliary safety measurements comparable to saline, a solution widely used for nasal applications.

Fungal infections caused by Candida spp. are responsible for high hospital morbidity and mortality rates. Therefore, there is a continuous search for new antifungal medicines, particularly ones with anti-Candida activity. This review analyzed articles published between 2002 and 2023 considering the anti-Candida activity of chemical compounds identified or isolated in plants of the Anacardiaceae family. In addition, the in-silico prediction of the isolated compounds described was performed. The analysis of 35 studies showed that extracts, essential oils, and compounds from the anti-Candida activity were frequently determined in vitro using the minimum inhibitory concentration (MIC). The most commonly tested species were Candida albicans, C. tropicalis, C. parapsilosis, C. glabrata, C. krusei, and C. guilliermondii, respectively. Essential oils were the most used form (37% of the studies). The isolated compounds with antifungal effects include cardanol, estragole, trans-anethole, β-caryophyllene, myrcene, catechin-3-o-rhamnoside, β-sitosterol-3-O-glucoside, 24Z-isomasticadienolic acid, oleanolic acid, and oleanolic aldehyde. The in-silico evaluation of those isolated compounds revealed the compounds' drug-likeness and possible antifungal activity. However, some of them showed high toxicity. In conclusion, compounds from the Anacardiaceae family show promise for developing new therapeutic antifungal drugs, especially in combination with conventional antifungals.

Abstract: Lung cancer, characterized by its heterogeneity, presents a significant challenge in ther-apeutic management, primarily due to the development of resistance to conventional drugs. This resistance is often compounded by the tumour’s ability to reprogram its metabolic pathways, a survival strategy that enables cancer cells to thrive in adverse conditions. This review article ex-plores the complex link between drug resistance and metabolic reprogramming in lung cancer, offering a detailed analysis of the molecular mechanisms and treatment strategies. It emphasizes the interplay between drug resistance and changes in metabolic pathways, crucial for developing effective lung cancer therapies. The review examines the impact of current treatments on metabolic pathways and the significance of considering metabolic factors to combat drug resistance. It highlights the different challenges and metabolic alterations in non-small cell lung cancer and small cell lung cancer, underlining the need for subtype-specific treatments. Key signalling pathways, including PI3K/AKT/mTOR, MAPK, and AMPK, have been discussed for their roles in promoting drug resistance and metabolic changes, alongside the complex regulatory networks involved. The article evaluates emerging treatments targeting metabolism, such as metabolic inhibitors, dietary management, and combination therapies, assessing their potential and challenges. It concludes with insights into the role of precision medicine and metabolic biomarkers in crafting personalized lung cancer treatments, advocating for metabolic targeting as a promising approach to enhance treatment efficacy and overcome drug resistance. The review underscores ongoing advancements and hurdles in integrating metabolic considerations into lung cancer therapy strategies.

Hiccups can significantly reduce the quality of life of patients and can occur as a drug side effect. Previous report using the Drug Adverse Event Database revealed sex-specific differences in the incidence of drug-induced hiccups. However, the pathogenesis of drug-induced hiccups remains unknown, and there is limited evidence on its treatment or prevention. This study examined molecular initiating events (MIEs), which are the starting point of adverse events, to investigate the drug-induced pathways of hiccups. We extracted drugs suspected to cause hiccups using FDA Adverse Event Reporting System, a large database on adverse drug reactions. Information on drugs suspected to be associated with hiccups were extracted from the overall population and sex-specific subgroups divided. In each data table, the predicted activity values of nuclear receptors (NRs) and stress response pathways (SPs) for each drug were calculated using the toxicity predictor, a machine-learning model. Univariate analysis extracted NRs and SPs associated with hiccups, and a multivariate analysis was performed to evaluate independent factors. Transforming growth factor-beta and antioxidant response element were considered an independent factor for hiccups in the male and female subgroups, respectively. This report first examined one of the mechanisms of drug-induced hiccups and identified MIEs associated with drug-induced hiccups.

The aberrant glycosylation is a hallmark of cancer progression and chemoresistance. It is also an immune therapeutic target for various cancers. Tunicamycin (TM) is one of the potent nucleo-side antibiotics and an inhibitor of aberrant glycosylation in various cancer cells, including breast cancer, gastric cancer, and pancreatic cancer, parallel with inhibition of cancer cell growth and progression of tumors. Thus, TM can be considered a potent antitumor drug in various cancers and may promote chemosensitivity. Mechanistically, TM impedes the role of the UDP-HexNAc enzyme in the biosynthesis of oligosaccharides, specialized macromolecules instrumental in N-linked glycosylation. Further, like chemotherapies such as doxorubicin (DOX), 5'fluorouracil, etoposide, and Cisplatin, TM induces the unfolded protein response (UPR) by blocking aberrant glycosylation. Despite TM's antitumor effectiveness, its lack of cell-type specific cytotoxicity impedes its anticancer efficacy. Thus, various nanoencapsulation techniques and materials have been considered for use in experiments to reduce TM's cytotoxicity and improve efficacy as a targeted therapy. The current review is a profound audit of the benefits and pitfalls of TM in various cancers, focusing on breast, colon, and pancreatic cancers. Additional progressive studies have also discussed the use of TM in immune checkpoints and other unique pathways. Cytotoxicity and other possibly adverse effects of TM are highlighted based on the data from in vitro and in vivo assays. In addition, the recent advances in nano-based drug delivery systems regarding TM have been emphasized. However, the potential of this nucleoside inhibitor re-quires thorough investigation and research to determine its likeliness as a viable chemotherapeutic.

The active form of fingolimod (FTY720; FT) is a sphingosine-1-phosphate receptor agonist with potential ocular applications. The goal of the present study was to develop an FT-loaded nanoemulsion (NE; FT-NE) formulation for the efficient and prolonged delivery of FT to the posterior segment of the eye through the topical route. FT-NE formulations were prepared with homogenization followed by probe sonication method. The lead FT-NE formulation (0.15% and 0.3% w/v loading), comprising soybean oil as lipid and Tween® 80 and Poloxamer 188 as surfactants, was further evaluated for in vitro release, surface morphology, filtration sterilization, and stability at refrigerated temperature. The formulation, at both dose levels, showed desirable physicochemical characteristics, a nearly spherical shape with homogenous nanometric size distribution, and was stable for 180 days (last time point checked) at refrigerated temperature post-filtration through polyethersulfone (0.22 µm) membrane. In vitro release studies showed prolonged release, compared with the control FT solution (FT-S), over 24 h. The results from these studies demonstrate that the FT-NE formulation can serve as a viable platform for the ocular delivery of FT through the topical route.

Cenobamate is approved by the European Medicine Agency for the treatment of adult patients with epilepsy (PWEs) who suffer from ongoing focal-onset seizures despite appropriate treatment with at least two established antiseizure medications. Pivotal trials and post-marketing real-world observational studies have suggested a high efficacy with unusually high seizure-free rates. We sought to investigate the serum trough levels of cenobamate under steady-state conditions in seizure-free versus non-responding PWEs, and in PWEs who experienced adverse events versus those who did not. We analyzed samples from 101 PWEs treated with adjunct cenobamate under steady-state conditions. In all, 36 PWEs were seizure-free and 65 were non-responders. In 31 PWEs, adverse events were apparent, whereas in the remaining 70, no tolerability issues were reported. We found a linear correlation between the daily doses (range: 100 mg – 400 mg) and the plasma levels (3.8 mg/l – 54.6 mg/l). Neither the daily doses nor the plasma levels differed significantly between seizure-free and non-responding PWEs or between PWEs with a satisfactory tolerability and those who experienced adverse events. The main reason for this result was that the individual therapeutic ranges varied widely: seizure freedom and adverse effects were observed alongside low doses and plasma levels in some PWEs. Conversely, there were examples of PWEs who did not respond or who reported no tolerability issues at high doses or plasma levels. Still, to evaluate the individual therapeutic range and to better understand the influence of other drugs in cases where concomitant medications are used, the therapeutic drug monitoring of cenobamate may be useful.

Persons who inject drugs (PWIDs) represent an important reservoir of hepatitis C virus (HCV) infection, hence therapeutic communities (TCs) are promising points of care for the identification and treatment of HCV-infected PWIDs. We evaluated the effectiveness and efficacy of an HCV micro-elimination program targeting PWIDs in the context of a drug-free TC applying Cascade of Care (CoC) evaluation by calculating frequencies of infection diagnosis, confirmation, treatment and achievement of a sustained virological response (SVR). We also evaluated the risk of reinfection of PWIDs achieving HCV eradication, by collecting follow-up virologic information of previously recovered individuals and eventual relapse in drug use, assuming the latter as a potential source of reinfection. We considered all PWIDs (aged 18+ years) residing in the San Patrignano TC at the beginning of the observation period (Jan/2018–Mar/2022) or admitted thereafter, assessing for HCV and HIV serology and viral load by standard laboratory procedures. Ongoing infections were treated with direct acting antivirals (DAA), according to the current national guidelines. Out of the 792 individuals tested on admission, 503 (63.5%) were found to be seropositive for antibodies against HCV. 481 of these 503 individuals (95.6%) underwent HCV-RNA testing. Out of the 331 participants positive for HCV-RNA, 225 were ultimately prescribed a DAA treatment with a Sustained Viral Response (SVR), which was achieved by 222 PWIDs (98.7%). 186 of 222 PWIDs (83.8%) with SVR remained HCV-free on follow-up (with a median follow-up of 2.73 years after SVR ascertainment). The CoC model in our TC proved efficient in implementing HCV micro-elimination, as well as in preventing reinfection and promoting retention in care of individuals, which aligns with the therapeutic goals of addiction treatment.

The reproductive health of women is governed by an optimal balance between the host-microbiota interaction. Depletion in the beneficial vaginal microflora caused by depletion of Lactobacillus species and increased proliferation of pathogens results in gynecological infections. Among women of reproductive age, vaginal infections are increasingly prevalent. Attaining therapeutic efficacy using conventional formulations remains a challenge as vaginal fluids quickly remove or dilute the therapeutic formulations. Hydrogels have been widely exploited for targeted delivery of therapeutics directly into the vaginal mucus. With careful choice of polymers (natural, synthetic or semi-synthetic) hydrogels with specific properties such as stimuli-responsiveness, antimicrobial, and muco-adhesiveness can be tailored for higher therapeutic efficacy. In this review, the advnances in hydrogel strategies for the treatment of vaginal infections is presented with emphasis on the types and properties that play a significant role in vaginal drug delivery systems.

Progress in understanding the pathogenesis and treatment of Alzheimer's disease (AD) is based on the recognition of the primary causes of the disease, which can be deduced from the knowledge of risk factors and biomarkers measurable in the early stages of the disease. Insights into risk factors and the time course of biomarker abnormalities point to a role for mitochondrial dysfunction and oxidative stress in the onset and development of AD. Coenzyme Q10 (CoQ10) is a lipid antioxidant and electron transporter in the mitochondrial electron transport system. The availability and activity of CoQ10 is crucial for proper mitochondrial function and cellular bioenergetics. Based on the mitochondrial hypothesis of AD and the hypothesis of oxidative stress, the regulation of the efficiency of the oxidative phosphorylation system by means of CoQ10 can be considered promising in restoring the mitochondrial function impaired in AD, or in preventing the onset of mitochondrial dysfunction and the development of amyloid and tau pathology in AD.

This review centers on the pivotal role of the oncoprotein FOSL1, within the dimeric AP-1 transcription factor consisting of FOS-related elements. FOSL1 emerges as a key regulator governing invasion and metastatic dissemination, therefore making it a promising target for therapeutic intervention in cancer patients. The review provides a comprehensive survey of the regulatory mechanisms that exert influence over FOSL1. These encompass a spectrum of transcriptional and post-translational modifications. Notably, we unveiled the intricate involvement of diverse non-coding RNAs, specifically microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in the modulation of FOSL1 expression through targeted interactions with its mRNA transcripts. Furthermore, an exploration into the functional dimensions of FOSL1 unfolds, encompassing apoptosis, proliferation, and migration. This investigation is accompanied by a thorough examination of the elaborate signaling pathways that underpin these multifaced roles. Additionally, emphasis is placed on the role of FOSL1 in orchestrating the stimulation of various cytokines, including TGF-beta, and the initiation of IL-6 and VEGF production in tumor-associated macrophages (TAMs) that transverse into the tumor microenvironment. A distinct focus is dedicated to appraising the prognostic implications associated with FOSL1. Finally, insights emerge into the evolving roles of FOSL1 in the context of mechanisms governing resistance and dependency on targeted therapeutic modalities.

Polyelectrolyte multilayers (PEMs) deposited on porous composite polylactic acid/poly(ε-caprolactone) substrates were studied. The substrates were previously charged in a corona discharge. Time dependences of the normalized surface potential for positively and negatively charged electrets were investigated. The morphology of the obtained porous substrates was examined by means of scanning electron microscopy (SEM). The chitosan and the casein polyelectrolytes were deposited on the substrates using the layer-by-layer (LbL) technique. A drug loading efficiency and the release kinetics were determined spectrophotometrically.

Over the few decades, cancer-associated mortalities and morbidities were continuously increased worldwide despite sophisticated technological advancements. Pharmaceutical interventions associated with drugs exhibit a high degree of side effects and toxicities in addition to very high costs. Subsequently, to reduce or to vanish the side effects and high costs, researchers are now exploring natural bioactive compounds such as quercetin in its nanoformulations along with biologics as cargo delivery vehicles. Quercetin along with mesenchymal stromal lineage-derived extracellular vesicles (EVs) possesses an anti-cancer potential that can be explored to treat hepatocellular carcinoma (HCC). Exerting enhanced effect, nano quercetin synergistically with EVs triggers the anti-cancer mechanisms by regulating and dysregulating several signalling mechanisms including NF-κB, p53, JAK/STAT, MAPK, Wnt/β-catenin and PI3K/AKT, in addition to PBX3/ERK1/2/CDK2, and miRNAs modulation. In addition, findings regarding the potential checkpoints of anti-cancer signalling pathways were investigated that offer opportunities to develop engineered EVs incorporated with nano quercetin for the development of novel therapeutics to treat HCC in future. In this present mechanistic review, we abridged the regulation of such signalling mechanisms synergetic approach of nano quercetin and EVs. The regulatory role of EVs in the manifestation of innumerable miRNAs has also been tailed with special context to HCC.

Although conventional chemotherapeutic drugs are the first line of treatment for cancer, they have numerous side effects. One of the emerging challenges in cancer treatment is drug resistance. Nat-ural compounds have proven effective against various hallmarks of cancer for their multi-target inhibition properties, but especially for their ability to synergistically bypass low bioavailability. Methods: The present study investigated the in vivo antitumor effects of a combination of two natural dietary agents, epigallocatechin-3-gallate (EGCG) from Camelia Sinensis and curcumin, a component of turmeric (Curcuma longa). We aimed to compare, for the first time in vivo, the antiangiogenic and antitumor effects of sunitinib with the combination of curcumin and EGCG in a mouse model of renal cell carcinoma (ccRCC). It was shown that they are able to inhibit cell survival, proliferation of several type of cancer, including renal cell carcinoma (ccRCC), by mod-ulating different signaling pathways and that their combination respect to single compound syn-ergistically decreased angiogenesis. Results: Herein, we highlighted that these compounds inhib-ited the growth of xenografted renal cancer in nude mice by significant inhibition of tumor vol-ume, tumor weight and CD31 expression with no signs of hepatic toxicity. Moreover, mice treated with these natural compounds showed a significant reduction in angiogenesis and an improve-ment in survival rate with p<0.05. Finally, pretreatment of mice with a diet containing 0.6% curcumin before injection of tumor cells showed a significant inhibition of tumor engraftment in 60% of mice with respect to controls and other groups. Conclusions: Taken together, our data in-dicate, for the first time, that the combination of curcumin and EGCG acts in a synergistic manner to inhibit the growth and angiogenesis of ccRCC and with less toxicity than sunitinib and provide an important rationale for future clinical development for chemoprevention and treatment of re-nal cancer.

Zika Virus (ZIKV) is a pathogenic member of the flavivirus family, with several unique charac-teristics. Unlike any other arbovirus, ZIKV can be transmitted sexually and maternally, and thus produce congenital syndromes (CZS) due to its neurotropism. This challenges the search for safe active molecules that can protect pregnant women and their fetuses. In this context, and in the ab-sence of any existing treatment, it seemed worthwhile to test whether the known cytoprotective properties of adiponectin and its pharmacological analog, AdipoRon, could influence the outcome of ZIKV infection. We showed that both AdipoRon and adiponectin could significantly reduce in vitro infection of A549 epithelial cells, a well-known cell model for flaviviruses infection studies. This effect was particularly observed when a pre-treatment was carried out. Conversely, ZIKV revealed an ability to down-regulate adiponectin receptor expression and thereby limit adi-ponectin signaling.

The integration of bioinformatics in drug discovery has revolutionized the field of pharmaceutical research. The use of computational tools and techniques has enabled researchers to analyze vast amounts of data, identify potential drug targets, and design new drugs with greater precision and efficiency. The integration of bioinformatics has also facilitated the development of personalized medicine, where drugs can be tailored to individual patients based on their genetic makeup. However, there are still challenges that need to be addressed, such as the need for more accurate predictive models and the ethical considerations surrounding the use of patient data. Overall, the integration of bioinformatics in drug discovery holds great promise for improving human health and advancing our understanding of disease mechanisms. In this mini-review, we discuss how Bioinformatics plays a crucial role in each step of drug discovery by providing tools and techniques to analyze large amounts of data generated from various sources, as well as the challenges and the opportunities offered by bioinformatics.

(1) Background: The incidence of vancomycin-induced neutropenia in hospitalized patients is estimated to be around 2 to 8 percent [1,2]. Data surrounding vancomycin-induced neutropenia is limited as it is based on a small number of observational case reports. Additionally, it is difficult to provide generalized conclusions since patient characteristics and indications for treatment vary between reports. (2) Case Reports: We present two cases of vancomycin-induced neutropenia that occurred at our facility; a 50-year-old male who developed neutropenia after treatment with vancomycin for a gluteal abscess and a 51-year-old female who developed neutropenia after treatment with vancomycin for lumbar osteomyelitis. In both cases, neutropenia resolved within 2 days of discontinuation of vancomycin. (3) Conclusion: The risk of developing neutropenia increases with age, prolonged drug exposure, decreased renal clearance, and in those of female sex. Treatment involves discontinuation of vancomycin with or without administration of granulocyte colony-stimulating factor (G-CSF). Additional studies are needed to better understand the true incidence of this adverse drug reaction and to identify risk factors that may predispose patients to vancomycin-induced neutropenia.

The number of people affected by eye conditions is growing every year, due to the popularity of electronic devices and an aging population. In the world of medicine, accomplishing eye medication administration has always been a difficult task. Despite the fact that there are many eye drops on the market, most of them have important limitations due to quick clearance mechanisms and ocular barriers. One solution with tremendous potential is the contact lens used as medication delivery vehicle to bypass this constraint. Therapeutic contact lenses for ocular medication delivery have attracted a lot of attention because they have the potential to improve ocular bioavailability, patient compliance, and reduce side effects. However, it is essential not to compromise essential features such as water content, optical transparency, and modulus in order to target successful in vitro and in vivo sustained drug delivery profile from impregnated contact lenses. Aside from difficulties like drug stability and burst release, the changing of lens physical and chemical properties caused by therapeutic or non-therapeutic components can limit the commercialization potential of pharmaceutical-loaded lenses. Research has progressed towards bioinspired techniques and smart materials to improve the efficacy of drug-eluting contact lenses. The bioinspired method uses bioinspired polymeric materials to improve biocompatibility, a specialized molecule recognition technique called molecular imprinting, or a stimuli-responsive system to improve biocompatibility and support drug delivery efficacy of drug-eluting contact lenses. This review encompasses strategies of material design, lens manufacturing and drug impregnation under the current auspices in ophthalmic therapies and projects an outlook onto future opportunities in the field of eye conditions management by means of active principles-eluting contact lens.

Hydrogels prepared from natural polymer have attracted extensive attentions in biomedical fields such as drug delivery, wound healing, and regenerative medicine due to their good biocompatibility, degradability and flexibility. This review outlines the commonly used natural polymer in hydrogel preparation, including cellulose, chitosan, collagen/gelatin, alginate, hyaluronic acid and starch. The polymeric structure and process/synthesis of natural polymers are illustrated, and natural polymer-based hydrogels including the hydrogel formation and properties are elaborated. Subsequently, the biomedical application of hydrogels based on natural polymer in drug delivery, tissue regeneration, wound healing and other biomedical field is summarized. Finally, the future perspectives of natural polymers and hydrogels based on them are discussed. For natural polymer, novel technologies such as enzymatic and biological methods are developed to improve the structural properties and the development of new natural based polymers or natural polymer derivatives with high performance is still very important and challenging. For natural polymer-based hydrogels, novel hydrogel materials, like double-network hydrogel, multifunctional composite hydrogels and hydrogel microrobots are designed to meet the advanced requirements in biomedical application, and new strategies such as dual-crosslinking, microfluidic chip, micropatterning and 3D/4D bioprinting, have been explored to fabricate advanced hydrogel materials with designed properties for biomedical application. Overall, natural polymeric hydrogels have attracted increasing interests in biomedical application, and the development of novel natural polymer-based materials and new strategies/methods for hydrogel fabrication is badly desirable and still challenging.

Since the first published genome sequence of Trypanosoma cruzi in 2005, there has been tremendous technological advance in genomics, reverse genetics, and assay development for this elusive pathogen. However, there is still an unmet need for new and better drugs to treat Chagas disease. Here we introduce a T. cruzi assay strain that is useful for drug research as well as basic studies in host-pathogen interaction. Trypanosoma cruzi STIB980 is a strain of discrete typing unit TcI that grows well in culture as axenic epimastigotes or intracellular amastigotes. We have evaluated the optimal parameters for genetic transfection and constructed derivatives of T. cruzi STIB980 that express reporter genes for fluorescence- or bioluminescence-based drug efficacy testing, as well as a Cas9-expressing line for CRISPR/Cas9-mediated gene editing. The genome of T. cruzi STIB980 was sequenced by combining short-read Illumina with long-read Oxford Nanopore technologies. The latter served for the primary assembly, the former to correct mistakes and fill the gaps. This resulted in a high-quality nuclear haplotype assembly of 28 Mb in 400 contigs, containing 10,043 open-reading frames with a median length of 1077 bp. We believe that T. cruzi STIB980 is a useful addition to the antichagasic toolbox, and propose that it can serve as a DTU TcI reference strain for drug efficacy testing.

Primary central nervous system and brain tumors are one of the global burdens that are continuously increasing in cases and requiring more treatment options. Surgery has been the leading treatment option for tumors, however, the localization of the tumor and its infiltrating nature make this option challenging. DNA microarray expression profiles of different CNS tumors provide insight into potential biomarkers for identifying different tumor types and subtypes. Here, we utilized the differentially expressed genes common in four expression profiles, GSE66354, GSE68848, GSE74195, and GSE43290 to reconstruct the gene co-expression network. In this study, we were able to identify preserved cluster genes, hub genes, co-regulating transcription factors, miRNA families, and candidate repurposed drugs. Fourteen identified hub genes, which were, CACNA1A, DNM1, GABRA1, GRIA2, MAPT, SLC17A7, SNAP25, SNAP91, STXBP1, SYT1, COL1A1, COL6A2, FBN2, and FN1 appeared to play a role in tumor progression and may serve as drug targets. We also reported the DEGs in each tumor type, which were ATRT, EPN, PA, MED, PNET, MEN, ACM, ODG, and GBM. Five identified miRNA families, which were, let-7 family, mir-124 family, mir-1 family, mir-103 family, and mir-27 family described in the literature to have tumor-suppressing characteristics. Drug-gene and drug-transcription factor network revealed 32 candidate repurposed drugs and 13 were validated through connectivity map analysis. Here, two main repurposed drugs fit the regulatory requirement for gene interaction, these were, quercetin and vorinostat. Future validation in experimental studies may utilize the future use of the candidate repurposed drugs. Our study provides insights into drug repurposing prospects and understanding tumor expressions.

Non-systemic oral drugs, which do not get absorbed through the gastrointestinal membrane, are an important group of compounds for targeting diseases residing within the gastrointestinal lumen. However, they require a set of design principles not sufficiently covered by traditional druglikeness metrics, such as Lipinski’s Rule of 5. These druglikeness metrics fail to accurately identify true negative outcomes; such is the requirement for novel cheminformatic based approaches for the discovery of non-systemic small molecules. One such example of these newer metrics is the fraction of SP3-hybridised carbon atoms (fSP3) which has shown promising application as an identifier of poor oral-bioavailability. Herein, we discuss the application of fSP3 in the drug discovery process in a number of case studies, including our own work discovering non-systemic fructose scavengers for the treatment of fructose malabsorption.

Introduction: Type 2 Diabetes mellitus (T2DM) is a common disease burdened with significant morbidity and mortality. Despite the substantial number of new available drug treatments, adherence to therapy and adverse drug reactions (ADRs) are the major constrain in the management of this disease. We evaluated the use, the adherence and the dsaftey of antidiabetic drugs in patients with T2DM. Methods: we performed an observational, retrospective, multicenter study on medical records of outpatients referred to general practitioners. Drug adherence was measured in agreement to the European Society for Patient Adherence, Compliance and Persistence Medication Adherence Reporting Guideline. ADRs were evaluated using the Naranjo probability scale. Collected data were analyzed using the Statistical Package for the Social Sciences. Results: During the study we evaluated 12,170 medical records of 7 general practitioners. The most prescribed drug was metformin alone (28.4%) or with other oral antidiabetics (19.6%) and then insulin (n: 354; men 190, women 164). Enrolled patients were stratified as high (35%), medium (41%) and low (24%) adherence. Logistic regression showed an association between T2DM less than or equal to 5 years and low adherence (P = 0.023). During the study we recorded 26 ADRs that was correlated with sex (women) and insulin treatment. Conclusion: this real-life study shows that patients with T2DM have high adherence probably related dto a low number of ADRs

In this work, alkylammonium-functionalized hollow mesoporous silica as nonocarrier of drugs was synthesized to realize enhanced cancer therapy by pH stimuli for sustained drug release. First, functionalized hollow mesoporous silica nanoparticles (Hollow MSNs) were synthesized using dodecyl dimethyl(3-sulfopropyl)ammonium hydroxide (DDAPS), sodium dodecyl sulfate (SDS), and triethanolamine as structure-directing agents, and tetraethyl orthosilicate (TEOS) and N-trimethoxysilypropyl-N,N,N-trimethylammonium chloride (TMAPS) as silica sources under basic condition via the sol-gel process. The structure and morphology of the alkylammonium-functionalized hollow mesoporous silica nanoparticles (Hollow MSN-N+CH3) were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), N2 adsorption-desorption analysis, and Fourier-transform infrared (FT-IR) spectroscopy. The functionalized hollow MSNs had a particle size of about 450 nm and a shell thickness of about 60 nm with uniform size. The nanoparticle had a surface area of 408 m2g-1, pore volume of 0.8 cm3g-1 and a uniform pore diameter of 45.9 Å. In the cancer cell viability test with MCF-7 cell, fludarabine-incorporated and alkylammonium-functionalized hollow mesoporous silica nanoparticles (Flu/Hollow MSN-N+CH3) showed excellent cancer cell death comparable with pure fludarabine drug with the controlled drug release by pH stimuli. It is considered that our current materials have the potential applicability as pH-responsive nanocarriers in the field of cancer therapy.

Microfluidic technology has become a powerful tool for several applications in chemistry, physics, biology, and engineering. Benefiting from the advantages of flowing fluids in the laminar regime, droplet-based microfluidics enable the development of various delivery systems based on food-grade emulsions, such as multiple emulsions, microgels, microcapsules, solid lipid micro-particles, and giant liposomes. Besides, by manipulating fluids on a micrometer scale with low-energy demand, it is possible to control the size, shape, and dispersity of droplets generated, which makes microfluidic emulsification an excellent strategy to modulate delivery system properties depending on the entrapped compound type. Thus, this review points out the most current advances in droplet-based microfluidic processes, in which food-grade materials were successfully utilized to develop simple and complex delivery systems. In that context, we sum-marized the principles of droplet-based microfluidics, introducing the most common microde-vices geometries, manufacturing materials, and forces involved in the different droplet generation processes within the microchannels. Subsequently, the encapsulated compound type, classified as lipophilic or hydrophilic functional compounds, was used as a starting point to present current advances in delivery systems based on food-grade emulsions and assembly using microfluidic technologies. Finally, we discuss the limitations and perspectives of scale-up in droplet-based microfluidic approaches, including the challenges that have limited the transition of microfluidic processes from lab-scale to industrial-scale.

Due to their distinct physical, chemical, and biological characteristics, biopolymers, in particular Poly Ethylene Glycol (PEG) and Cellulose, are frequently used in biomedical medicine as drug or vaccine delivery systems. In this study, we have done a systematic review and a meta-analysis to compare current developments in many PEG and cellulose-based hydrogels, including double network hydrogels, injectable hydrogels, sliding hydrogels, conductive hydrogels, responsive hydrogels, and nanocomposite hydrogels. The pharmacokinetic properties, including physicochemical properties, biocompatibility, biodegradability, temperature, and pH, have been studied as these critical factors are to be considered for deciding the suitability of the drug for delivery. Moreover, the study has evaluated the controlled-release parameters such as half-life, circulation time, maximum release percentage of loaded drug released, burst release, maximum release, and drug-release kinetics. Finally, the efficacy and immune response of hydrogel was studied for future choice, including the cellulose hydrogel system in COVID-related long-term vaccine delivery. The finding revealed that cellulose-based hydrogel is effective for vaccine delivery.

The Bcl-2 family plays a crucial role in regulating cell apoptosis, making it an attractive target for cancer therapy. In this study, a series of indole-based compounds, U1-6, were designed, synthesized, and evaluated for their anticancer activity against BCL-2-expressing cancer cell lines. The binding affinity, safety profile, cell cycle arrest, and apoptosis effects of the compounds were tested. The designed compounds exhibited potent inhibitory activity at sub-micromolar IC50 concentrations against MCF-7, MDA-MB-231, and A549 cell lines. Notably, U2 and U3 demonstrated the highest activity, particularly against MCF-7 cells. Respectively, both U2 and U3 showed potential Bcl-2 inhibition activity with IC50 values of 1.2 ± 0.02 and 11.10 ± 0.07 µM using an ELISA binding assay compared to 0.62 ± 0.01 µM for gossypol, employed as positive control. Molecular docking analysis suggested stable interactions of compound U2 at the Bcl-2 binding site through hydrogen bonding, pi-pi stacking, and hydrophobic interactions. Furthermore, U2 demonstrated significant induction of apoptosis and cell cycle arrest at G1/S phase. Importantly, U2 displayed a favorable safety profile on HDF human dermal normal fibroblast cells at 10-fold greater IC50 compared to MDA-MB-231 cells. These findings underscore the therapeutic potential of compound U2 as a Bcl-2 inhibitor and provide insights into its molecular mechanisms of action.

Polymeric microparticles of polyethyleneglycol-polylactic acid-co-glycolic acid (PEG-PLGA) are widely used as drug carriers for a variety of applications due to their unique characteristics. Herein, we developed a novel method for the synthesis of uniformly sized microparticles via coaxial flow-phase separation. The study evaluated the effect of various process parameters on microparticle size and polydispersity including polymer concentration, stirring rate, surfactant concentration, and the organic/aqueous phase flow rate and volume ratio. The results demonstrated that stirring rate and polymer concentration had the most significant impact on the mean particle size and distribution whereas surfactant concentration had the most substantial impact on the morphology of particles. Several microparticle formulations yielding particle sizes in the range of (5-50 µm), morphology, and concentration were synthesized as a demonstration of the tunability and scalability of this method. Notably, by controlling the process parameters microparticles of less than ~ 7 μm could be made using polymer concentrations varying by an order of magnitude. Finally, we demonstrated the tunability and scalability of this method by showing a 10-fold increase in encapsulation efficiency, a 3-fold increase in drug loading of a model hydrophilic drug, and modified release kinetics in microparticle formulations of comparable sizes but different polymer concentrations.

Breast cancer is one of the most common types of malignant tumors worldwide and the leading cause of cancer-related deaths in women. According to the latest report from the World Health Organization, breast cancer has surpassed lung cancer, becoming the most diagnosed cancer globally. Herein, a systematic, quantitative, and visual analysis of the scientific achievements in natural products research and development for breast cancer over the past 30 years is presented. The study utilizes bibliometric and knowledge graph visualization techniques to analyze the trends, co-occurrence of keywords, cooperative networks, cited literature, and research hotspots in the field. The analysis shows that breast cancer natural drug development involves mutual cooperation between multiple countries, with China, the United States, and India being the most active players. Pharmacology is the discipline with the largest number of articles published in nearly 30 years. The study also reveals that the extraction of drugs from organisms and their metabolites is an important direction in the current development of anticancer drugs. The development of natural medicines for breast cancer together with the mining of genetic knowledge play an important role in treating human breast cancer. The research presented here provides insights into the current state of natural product research and development for breast cancer, and highlights the need for strengthening mutual communication and cooperation between countries and scientific research institutions to enhance the development of breast cancer treatment technologies and natural medicines.

Polymeric hydrogels are promising polymeric functional materials that have been widely used in the biomedical field as an emerging carrier of various therapeutic agents. Polymeric hydrogels as a carrier of therapeutics can leverage therapeutically beneficial outcomes of drug delivery than systemic chemotherapy and can provide spatial and temporal control over the release of various therapeutic agents. Polymeric hydrogels are cross-linked three-dimensional networks constructed by hydrophilic polymers and they are capable of absorbing and re-taining a large amount of water. Polymeric hydrogels share many physiochemical features with natural tissues due to their water abundance, biomimetic microstructure, and intrinsic flexibility. Polymeric hydrogels have excellent biocompatibility, biodegradability, and lower toxicity. Polymeric hydrogels enhance the convenience and efficiency of drug delivery by assisting in situ gelation and controlling drug release by changing their volume and other properties when it encounters some stimuli (e.g., heat, pH, light, and ultrasound). This review aims to outline the overview of polymeric hydrogels, properties, types, advantage, disadvantages, characteri-zation, and their application with present status and future perspective used for the delivery of therapeutics in pharmaceutical and biomedical sciences.

Management of chronic inflammation and wounds has always been a key issue in the pharmaceutical and healthcare sector. Curcumin (CCM) is an active ingredient extracted from turmeric rhizomes that has antioxidant, anti-inflammatory, and antibacterial activities, thus showing significant effectiveness toward wound healing. However, its shortcomings such as poor water solubility, poor chemical stability and fast metabolic rate limit its bioavailability and long-term use. In this context, hydrogels appear to be a versatile matrix for carrying and stabilizing drugs due to the biomimetic structure, soft porous microarchitecture, and pleasant biomechanical properties. The drug loading/releasing efficiencies can also be controlled by use of highly crystalline and porous metal organic frameworks (MOFs). Here, a flexible hydrogel composed of sodium alginate (SA) matrix and CCM-loaded MOFs was constructed for long-term drug release and antibacterial activity. The morphology and physicochemical properties of composite hydrogels were analyzed by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), ultraviolet visible spectroscopy (UV-Vis), Raman spectroscopy and mechanical property tests. The results showed that the composite hydrogel was highly twistable and bendable to mechanically comply with human skin. The as-prepared hydrogel could capture efficient CCM for slow drug release as well as effective killing of bacteria. Therefore, such composite hydrogel is expected to provide a new management system for chronic wound dressings.

The supramolecular based macrocyclic amphiphiles have attracted great attention in the field of drug delivery due to their unique self-assembling nature. Therefore, these macrocycles are used as nanocarriers for the delivery of poor water soluble drugs, and also for those which have lower permeability, and cannot cross the barrier to reach the desired site. Herein, we design and synthesized a new supramolecular amphiphilic macrocycle to overcome these problems. The macrocycle was synthesized in two steps. In first step 4-hydroxybenzaldehyde was treated with 1-bromotetradecane to obtain a derivatized product which was then treated with resorcinol to cyclize and get calix(4)resorcinarene based supramolecular amphiphilic macrocycle. The synthesized macrocycle and intermediate products were characterized by Mass spectrometry, IR and 1H-NMR spectroscopic techniques. The amphiphile was screened for biocompatibility studies, vesicles formation, and then Amphotericin-B was loaded in the supramolecular amphiphile based vesicles and was characterized for shape, size, homogeneity, surface charge, drug entrapment, in-vitro release profile and stability through atomic force microscopy (AFM), Zetasizer, HPLC and FT-IR. Amp-B loaded macrocycle based vesicles were investigated for in-vivo bioavailability in rabbits. The synthesized macrocycle was nontoxic in cancer cells, hemo-compatible and safe in mice. The drug-loaded macrocycle based vesicles appeared spherical, nano-ranged, and homogeneous in size with negative surface charge and were able to load an increased amount of drug. The vesicles are stable upon storage and when incubated with gastric simulated fluid. Amp-B increased oral bioavailability was achieved when delivered in synthesized macrocycle based vesicles. These results point out that the synthesized supramolecular amphiphile is an efficient nanocarrier to enhance the oral bioavailability of lipophilic drugs

Acinetobacter baumannii (AB) is a bacterium that causes infections, particularly in immunocompromised patients. Treatment is challenging due to biofilm formation by AB strains, which hinders antibiotic effec-tiveness and promotes drug resistance. The aim of our study was to analyze the biofilm-producing capacity of AB isolates from various forms of infections in relation to biofilm-related genes and their drug resistance. We tested one hundred isolates for biofilm formation using the crystal violet microplate method. Drug re-sistance analyses were performed based on EUCAST and CLSI guidelines, and biofilm genes were detected using PCR. All tested strains were found to form biofilms, with 50% being ICU strains and 72% classified as strong biofilm-producers. Among these, 87% were extensively drug-resistant (XDR) and 2% were extra extensively drug-resistant (E-XDR). The most common gene set was bap, bfmS, csuE, and ompA, found in 57% of all isolates. Our research has shown that, regardless of the form of infection, biofilm-forming strains can be expected among AB isolates. The emergence of E-XDR and XDR strains among non-ICU infections highlights the necessity for the rational use of antibiotics to stop or limit the further acquisition of drug re-sistance by A. baumannii.

Nanomaterials such as pH-responsive polymers are promising for targeted drug delivery systems, due to the difference in pH between tumor and healthy regions. However, there is a significant concern about the application of these materials in this field due to their low mechanical resistance, which can be mitigated by combining these polymers with mechanically resistant inorganic materials such as mesoporous silica nanoparticles (MSN) and hydroxyapatite (HA). Mesoporous silica has interesting properties such as high surface area and hydroxyapatite has been widely studied to aid in bone regeneration, providing special properties adding multifunctionality to the system. Furthermore, fields of medicine involving luminescent elements such as rare earth are an interesting option in cancer treatment. The present work aims to obtain a pH-sensitive hybrid system based on silica and hydroxyapatite with photoluminescent and magnetic properties. The nanocomposites were characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), nitrogen adsorption methods, CHN elemental analysis, Zeta Potential, scanning electron microscopy (SEM), and transmission electron microscopy (TEM), vibrational sample magnetometry (VSM), and photoluminescence analysis. Incorporation and release studies of the antitumor drug doxorubicin were performed to evaluate the potential use of these systems in targeted drug delivery. The results showed the luminescent and magnetic properties of the materials and showed suitable characteristics for application in the release of pH-sensitive drugs.

Rottlerin(R) is a natural extract from Mallotus philippensis with antiviral properties. Feline Infectious Peritonitis (FIP) is a fatal disease characterized by systemic granulomatous inflammation and high mortality, with no established prevention or cure. We investigated antiviral effect of liposome loaded R, Rottlerin-liposome(RL) against Feline infectious peritonitis virus (FIPV), the causative agent. We demonstrated that R and RL inhibited FIPV replication in dose dependently with a PKCδ related manner, not only in the early endocytosis step but also in the late step of replication. RL resolved the low solubility issue of rottlerin and improved its inhibition efficacy at the cellular level. Based on these findings, we suggest that RL has a value for further research as a potential antiviral agent against FIPV.

Hydrogel microneedles are a promising technology for the delivery of different types of medicines locally and painlessly, as well as ISF extraction. As the hydrogel microneedles are inserted into the tissue, they swell and release drugs. To improve the effectiveness of this technology in delivering medicine at controlled and desirable doses and intervals, a deep understanding of the mechanism of drug delivery inside the microneedles is required. In this work, drug diffusion inside a tapered microneedle is investigated using numerical simulation. The microneedle is divided into many small elements, and the mass transfer equation of meloxicam is solved in each element over time. The skin is simulated as the sink in the microneedle surface for drug absorption. Simulations are performed for different sizes of microneedles. For a microneedle with a height of 500 µm and a base diameter of 250 µm, the drug completely penetrates the skin within 3.2 seconds. The rate of drug diffusion from the tip of the microneedle is higher than diffusion from the side area near the microneedle base. The obtained data demonstrate that in addition to the height and the base diameter, the microneedle’s aspect ratio, h/d, also affects the time of drug diffusion. We present a nonlinear equation to predict the time of complete drug diffusion as a function of the microneedle geometrical parameter, including the height and base diameter. The proposed equation calculates the total drug diffusion time with an error of less than 7% for all studied cases. Predicting drug diffusion patterns inside microneedles can be helpful in the biomedical field, especially in the drug-controlled release system for the optimization of drug delivery.

The mechanistic target of rapamycin (mTOR) kinase is one of the top drug targets for promoting health and lifespan extension. Besides rapamycin, only a few other mTOR inhibitors have been developed and shown their ability to slow aging. We used machine learning to predict novel small molecules targeting mTOR. We selected one small molecule, TKA001, based on in-silico predictions of a high on-target probability, low toxicity, favorable physicochemical properties, and preferable ADMET profile. We confirmed TKA001 binding in silico by molecular docking. TKA001 potently inhibits both TOR complex 1 and 2 downstream signaling in vitro. Furthermore, TKA001 inhibits human cancer cell proliferation in vitro and extended the lifespan of C. elegans, suggesting that TKA001 can slow aging in vivo.

Calcium signaling and lipid metabolism are crucial in the infection processes of Apicomplexans parasites. Thus, enzymes involved in these processes can be drug targets against Apicomplexans. For example, in malaria infection, in-depth research into lipid metabolic pathways is crucial in understanding the parasite's infection cycle, particularly during its erythrocytic infection cycle, which has been demonstrated to be a critical stage during the disease progression. Most enzymes that play critical roles in lipid synthesis and calcium signaling have been extensively studied; nonetheless, a vast knowledge gap still exists, especially on specific enzymes and their roles in the transmission and progression of the Apicomplexan parasites. Many types of infections caused by Apicomplexans are life-threatening and hard to treat. These intracellular parasites proliferate within parasitophorous vacuoles in their host cells. As the parasites multiply, they need to meet their high demand for nutrients such as amino acids and lipids. They can acquire nutrients through scavenging and biosynthesis. This review summarizes a few interesting, unique pathways in selected Apicomplexa and how such unique pathways can be targets for drugs.

The emergence of drug-resistant tuberculosis forced the development of new drugs and screnning of more effective or less toxic analogs. Mycolic acids biosynthesis is targeted by several antituberculosis drugs toped by the isoniazid being one of the most important in tuberculosis therapy. Recently, perchlozone, acting on another step in FAS-II cycle, received official approval and was included in the Russian national clinical guidelines. Using the serial dilution method on agar 7H10 plates for perchlozone and Sensititre MYCOTB microdilution plate we analyzed the phenotypic properties of primary M. tuberculosis clinical isolates and analyzed the molecular determinants of resistance to isoniazid, ethionamide and perchlozone. We found a wide variation in the MIC of perchlozone from 2 to 64 mg/L, correlating with the overall resistance profile: the MIC was higher for MDR and pre-XDR isolates. The cross-resistance between the ethionamide and the perchlozone was driven by mutations in ethA gene encoding monooxygenase responsible for activation of both drugs. Presumably susceptible to perchlozone wild-type strains had MICs ranged 2–4 mg/L, and the breakpoint estimated to be at 4 or 8 mg/L. In conclusion, susceptibility to perchlozone retained for a part of MDR strains, as does suceptibility to ethionamide, providing the possibility of therapy for such cases based on phenotypic or molecular analysis.

The proportion of human cells to the microbial cell is 1:1. These procaryotes use efflux pumps and enzymes to prevent cellular intoxication of ions and compounds respectively. There is promising evidence on the role of the gut microbiome and its enzymes in metabolizing xenobiotics. The genetic potential of oral bacteria in drug and xenobiotic metabolism is yet to be unveiled. This study aimed to characterize the bacteriome associated with oral fibroepithelial polyps (FEP) and to predict the genetic potential. A representative sub-sample of 22 clinically diagnosed oral FEP (the control group) was selected from a main case-control study. Amplification of nucleotides of extracted DNA from frozen tissues was performed for the V1 to V3 region and sequencing of the amplicon with Illumina’s 2 X 300–bp chemistry. Classification of high-quality nonchimeric merged reads was done to the species level with a prioritized BLASTN-based algorithm. Downstream compositional analysis was performed with QIIME (Quantitative Insights into Microbial Ecology). Functional prediction of bacteriome was obtained by PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States). Rothia mucilaginosa, Streptococcus mitis, Gamella haemolysans, Streptococcus sp. oral taxon 431, and Rothia dentocariosa accounted for the top five taxa among 810 bacterial species according to the percentage of average relative abundance. Rothia mucilaginosa was elevated statistically significantly (p< 0.05). The genetic potential of xenobiotics and drug metabolism catalyzed by the P450 enzymes was observed for the first time as an attribute of bacteriome associated with oral FEP tissues dominated by R. mucilaginosa. This finding needs further investigation.

Nanomedicine holds great potential to devise better drug delivery systems (DDSs). However, many reported nanomedicines still fall short of commercial requirements including specific targetability, scale-up manufacturing and safety. Cell/tissue based carriers, including cell membrane vehicle and exosome, are biocompatible and targeting platforms but usually suffered from low yields and unstable reproducibility. Here in this study, we proposed the concept and preparation of reconstituted lipid nanoparticles (rLNPs) to develop highly reproducible cell/tissue based lipid nanoparticles (LNPs) for drug delivery, which holds the potential as a versatile drug delivery platform. The whole lipids of cell or tissue were firstly extracted and then prepared into rLNPs using solvent diffusion method. In this way, the preparation of ultra-small (~20 nm) rLNPs can be easily applied to both cell (mouse breast cancer cell line, 4T1) and tissue (mouse liver tissue). Our results demonstrated that mouse liver tissue derived rLNPs can be further labeled/modified with imaging, targeting or other functional moieties. Furthermore, rLNPs were highly biocompatible and capable of loading different drugs including doxorubicin hydrochloride (Dox) and curcumin (Cur). Most importantly, Dox loaded rLNPs (rLNPs/Dox) showed preferable in vitro and in vivo anticancer performance. Therefore, rLNPs might be a versatile drug delivery platform for future application in the treatment of a variety of diseases.

The study is based on wide international research, the International Self-report Delinquency Study 3 (ISRD-3) and it analyses the relationship between parental presence, juvenile delinquency, and the consumption of psychotropic substances in adolescents. The data have been collected by a questionnaire ISRD-3 administered to 6021 students from 7th to 9th grade from 24 countries. The results confirmed the protective effect of dual-parent families on alcohol and drug use and committing illicit behaviours. Monoparental families and families without parents are associated with higher levels of alcohol, drug use, and deviant behaviors by young people.

Mycobacterium tuberculosis is a leading cause of human mortality worldwide and the emergence of drug-resistantstrains, demands the discovery of new classes of antimycobacterials that can be employed in the therapeutic pipeline. Previously, a secondary metabolite Chrysomycin A, isolated from Streptomyces sp. OA161 was shown to have potent bactericidal activity against drug-resistant clinical isolates of M. tuberculosis and different species of mycobacteria. The antibiotic inhibits the mycobacterial topoisomerase I and DNA gyrase leading to bacterial death, but the mechanisms that could cause resistance are currently unknown. To further understand the resistance mechanism, spontaneous resistance mutants were isolated and subjected to whole-genome sequencing. Mutation in a Tet^R family transcriptional regulator MSMEG_1380 was identified in the resistant isolates and was close to an operon encoding membrane protein MSMEG_1381 and MSMEG_1382. Sequence analysis and modeling studies indicated that they are components of the Mmp family of efflux pumps and over-expression of either the operon or individual genes conferred resistance to chrysomycin A, isoniazid, and ethambutol that are in TB therapy. Our study highlights the role of membrane transporter proteins in conferring multiple drug resistance and the utility of recombinant strains overexpressing membrane transporters in the drug screening pipeline.

Background: Worldwide, microbes are becoming more dangerous by acquiring virulent skills to adapt and develop antimicrobial resistance (AMR). This is a concern as this increases morbidity, mortality, and costs. Consequently, physicians need to be trained inappropriate prescribing, starting with medical students. Objective: Evaluate medical students' confidence in antimicrobial agent prescribing and drug resistance Methods: Cross-sectional study assessing medical students' knowledge, perception, and confidence in prescribing antimicrobial agents and drug resistance in a Malaysian University. A universal sampling method was used. Results: Most respondents believe that educational input regarding overall prescribing was sufficient. Regarding the principle of appropriate and accurate prescriptions, female medical students had less knowledge [Odds Ratio (OR)=0.51; 95% Confidence Interval (CI) 0.25-0.99; p=0.050]. Year-IV and Year-V students had more excellent knowledge than Year-III students regarding confidence in antibiotic prescribing. Year-V students also showed appreciably higher confidence in the broad principles of prescribing, including infectious diseases, compared to those in other years. Conclusion: Overall, medical students, gain more excellent knowledge and confidence regarding prescribing, including antimicrobials, as their academic careers progress.