Evolution of natural myocardial shear wave behavior in young hearts: determinant factors and reproducibility analysis.

BACKGROUND: Myocardial diastolic function assessment in children by conventional echocardiography is challenging. Recent high frame rate (HFR) echocardiography facilitates the assessment of myocardial stiffness (MS) -a key factor of diastolic function- by measuring the propagation velocities of myocardial shear waves (SWs). However, normal values of natural SWs in children are currently lacking. OBJECTIVES: To explore the behavior of natural SW among children and adolescents, their reproducibility, and the factors affecting SW velocities from childhood into adulthood. METHODS: 106 healthy children (2-18 years) and 62 adults (19-80 years) were recruited. HFR images were acquired using a modified commercial scanner. An anatomical M-mode was drawn along the ventricular septum, and propagation velocities of natural SWs after mitral valve closure (MVC) were measured in the tissue acceleration coded M-mode display. RESULTS: Throughout life, SW velocities after MVC exhibited pronounced age dependency (r= 0.73; P<0.001). Among the pediatric population, SW velocities correlated significantly with measures of cardiac geometry (septal thickness and left ventricular end-diastolic dimension), local hemodynamics (systolic blood pressure), as well as with echocardiographic parameters of systolic and diastolic function (global longitudinal strain (GLS), mitral E/e', isovolumetric relaxation time and mitral deceleration time) (P <0.001). In a multivariate analysis including all these factors, the predictors of SW velocities were age, mitral E/e', and GLS (r= 0.81). CONCLUSIONS: Natural myocardial SW velocities in children can be detected and measured. SW velocities showed significant dependence on age and diastolic function. Natural SWs could be a promising additive tool for assessment of diastolic function among children.

Layer-By-Layer Designed Spark-Type AuCuPt Alloy with Robust Broadband Absorption to Enhance Sensitivity in Flexible Detection of Estriol by a Lateral Flow Immunoassay.

Excessive intake of estrogen poses significant health risks to the human body; hence, there is a necessity to develop rapid detection methods to monitor its levels of addition. Gold nanoparticles (AuNPs), commonly utilized as colorimetric signal labels, find extensive application in lateral flow immunoassay (LFIA). However, the detection sensitivity of traditional AuNPs-LFIA is typically constrained by low molar extinction coefficients and reliance on a single signal. Herein, in this work, unique spark-type AuCuPt nanoflowers modified with tannic acid (AuCuPt@TA) were precisely designed by reasonable layer-by-layer element composition and green modification. The obtained AuCuPt displays robust broadband absorption spanning the visible to near-infrared spectrum, showcasing a notable molar extinction coefficient of 2.38 × 1012 M-1 cm-1 and a photothermal conversion efficiency of 48.5%. Based on this, selecting estriol (E3) as a model analyte, colorimetric/photothermal dual-signal LFIA (CLFIA and PLFIA) was developed. Limits of detection (LOD) of the CLFIA and PLFIA were achieved at 0.033 ng mL-1 and 0.021 ng mL-1, respectively, which represent a 9.3- and 14.6-fold improvement compared to the visual LOD of AuNPs-LFIA. Moreover, the application feasibility of the immunoassay was further evaluated in the milk and pork with satisfactory recoveries ranging from 86.21% to 117.91%. Thus, this work has enhanced the performance of LFIA for E3 detection and exhibited enormous potential for other sensing platform construction.

Enhancement of biomass productivity and biochemical composition of alkaliphilic microalgae by mixotrophic cultivation using cheese whey for biofuel production.

The growth of microalgae under alkaline conditions ensures an ample supply of CO2 from the atmosphere, with a low risk of crashing due to contamination and predators. The present study investigated the mixotrophic cultivation of two alkaliphilic microalgae (Tetradesmus obliquus and Cyanothece sp.) using cheese whey as an organic carbon source. The variation in cheese whey concentration (0.5-4.5% (v/v)), culture pH (7-11), and NaNO3 concentrations (0-2 gL-1) was evaluated using central composite design in response to biomass productivity and the contents of lipids, total proteins, and soluble carbohydrates. Both investigated microalgae effectively utilized cheese whey as an organic carbon source. The optimum conditions for simultaneously maximizing biomass and lipid productivity in T. obliquus were 3.5% (v/v) whey, pH 10.0, and 0.5 g L-1 NaNO3. Under these conditions, the biomass, lipid, soluble carbohydrate, and protein productivities were 48.69, 20.64, 7.02, and 10.97 mg L-1 day-1, respectively. Meanwhile, Cyanothece produced 52.78, 11.42, 4.31, and 7.89 mg L-1 day-1 of biomass, lipid, carbohydrate, and protein, respectively, at 4.5% (v/v) whey, pH 9.0, and 1.0 g L-1 NaNO3. The lipids produced under these conditions were rich in saturated fatty acids (FAs) and monounsaturated FAs, with no polyunsaturated FAs in both microalgae. Moreover, several biodiesel characteristics were estimated, and results fell within the ranges specified by international standards. These findings indicate that the mixotrophic cultivation of alkaliphilic microalgae could open new avenues for promoting microalgae productivity through low-cost biofuel production.

Polymer-Based Terbium Complex as a Fluorescent Probe for Cancer Antigen 125 Detection: A Promising Tool for Early Diagnosis of Ovarian Cancer.

A novel photoprobe, Tb-acetylacetone (Tb-ACAC) doped within a modified epoxy cellulose polymer immobilized with CA-125 monoclonal antibody, offers an accurate and highly selective method for early ovarian cancer (OC) diagnosis by detecting cancer antigen 125 (CA-125) in serum samples. This approach leverages quenching of the Tb-ACAC luminescence upon binding to CA-125. Characterization of the photoprobe film through UV-vis and fluorescence measurements confirmed the presence of Tb-ACAC within the polymer matrix. In aqueous solution (pH 6.8, λex = 365 nm), the characteristic emission band of Tb-ACAC at λem = 546.2 nm exhibited significant quenching upon CA-125 binding. This quenching effect enabled the sensitive and specific detection of CA-125 in diverse serum samples from OC patients, demonstrating the applicability, simplicity, and effectiveness of this novel approach.

Copper/Tin Nanocomposites-Loaded Exosomes Induce Apoptosis and Cell Cycle Arrest at G0/G1 Phase in Skin Cancer Cell Line.

This study aims to explore the efficacy of Copper/Tin (CuS/SnS) nanocomposites loaded into exosomes against skin cancer A431 cell line. CuS/SnS nanocomposites (S1, S2, S3) were synthesized and characterized, then loaded into exosomes (Exo) (S1-Exo, S2-Exo and S3-Exo) and characterized. After that, the loaded samples were investigated in vitro against A431 using cytotoxicity, apoptosis, and cell cycle assays. CuS/SnS nanocomposites were indexed to hexagonal CuS structure and orthorhombic α-SnS phase and showed nano-rode shape. The exosomes loaded with nanocomposites were regular and rounded within the size of 120 nm, with no signs of broken exosomes or leakage of their contents. The cytotoxicity assay indicated the enhanced cytotoxic of S1-Exo versus the free nano-form S1 on A431. Interestingly, S1-Exo recorded 1.109 times more than DOX in its anti-skin cancer capacity. Moreover, S1-Exo recorded 40.2% for early apoptosis and 22.1% for late apoptosis. Furthermore, it displayed impact in arresting the cancer cell cycle at G0/G1 phase and reducing G2/M phase. Noteworthy, loaded nanocomposites were safe against normal HSF skin cells. In conclusion, the loaded CuS/SnS nanocomposites into the exosomes could be of great potential as anti-skin cancer candidates through induction of apoptosis and promotion of the cell cycle arrest at G0/G1 phase.

Preparation and characterization of pectin/hydroxyethyl cellulose/clay/TiO2 bionanocomposite films for microbial pathogen removal from contaminated water.

Some of conventional wastewater disinfectants can have a harmful influence on the environment as well as human health. The aim of this investigation was synthesis and characterizes ecofriendly pectin/hydroxyethyl cellulose (HEC)/clay and pectin/HEC/clay incorporated with titanium dioxide nanoparticles (TiO2NPs) and use the prepared bionanocomposite as microbial disinfectants for real wastewater. Pectin/HEC/clay and pectin/HEC/clay/TiO2 bionanocomposite were characterized by various methods including X-ray diffraction (XRD), scanning electron microscope (SEM), and Fourier-transform infrared spectroscopy (FTIR), thermal gravimetric analysis (TGA). Mechanical properties and water vapor permeability (WVP) were carried out. The results of SEM showed that, the prepared bionanocomposite had a smooth surface. Additionally, TiO2 nanoparticles to the pectin/HEC/clay composites may lead to changes in the FTIR spectrum. The intensity of XRD peaks indicated that, TiO2NPs was small size crystallite. TGA illustrated that pectin has moderate thermal stability, while HEC generally exhibits good thermal stability. The TEM showed that, TiO2 nanoparticles have diameters <25 nm. On the other hand, antimicrobial activities of pectin/HEC/clay against Escherichia coli (E. coli), Staphylococcus aureus and Candida albicans have been enhanced by adding TiO2NPs. The minimum inhibitory concentration (MIC) of pectin/HEC/clay/TiO2 against E. coli was 200 mg/mL. Moreover, complete eradication of E. coli, Salmonella and Candida spp. from real wastewater was observed by using pectin/HEC/clay/TiO2 bionanocomposite. Finally, it can be concluded that, the synthesized bionanocomposite is environmentally friendly and considered an excellent disinfectant matter for removal of the microbial pathogens from wastewater to safely reuse.

Phyto- and biochemical study on cape gooseberry (physalis peruviana L.) extract incorporated with metal nanoparticles against hepatic injury induced in rats.

The study aimed to investigate the role of metal nanoparticles (M-NPs) in improving the efficiency of Physalis peruviana (Cape gooseberry) juice, which is rich in numerous important therapeutic phytochemicals. Therefore, it was subsequently studied against chemically-induced toxicity in rats. The present study demonstrated that C. gooseberry juice was used for the biosynthesis of silver (Ag-NPs) and zinc oxide nanoparticles (ZnO-NPs). The ZnO-C. gooseberry nano-extract exhibited higher in vitro biological activities compared to the other extracts. It was also found to be safer when administered orally. Moreover, it demonstrated a greater ameliorative effect against hepatotoxicity induced by carbon tetrachloride (CCl4) in rats. It restored the integrity of the liver tissue by increasing levels of antioxidant enzymes and reducing the inflammatory markers significantly (p ≤ 0.05). The study found that the ZnO-C. gooseberry nano-extract demonstrated greater efficacy in combating CCl4-induced hepatotoxicity compared to the other extracts.

Sequential graph convolutional network and DeepRNN based hybrid framework for epileptic seizure detection from EEG signal.

Automated epileptic seizure detection from ectroencephalogram (EEG) signals has attracted significant attention in the recent health informatics field. The serious brain condition known as epilepsy, which is characterized by recurrent seizures, is typically described as a sudden change in behavior caused by a momentary shift in the excessive electrical discharges in a group of brain cells, and EEG signal is primarily used in most cases to identify seizure to revitalize the close loop brain. The development of various deep learning (DL) algorithms for epileptic seizure diagnosis has been driven by the EEG's non-invasiveness and capacity to provide repetitive patterns of seizure-related electrophysiological information. Existing DL models, especially in clinical contexts where irregular and unordered structures of physiological recordings make it difficult to think of them as a matrix; this has been a key disadvantage to producing a consistent and appropriate diagnosis outcome due to EEG's low amplitude and nonstationary nature. Graph neural networks have drawn significant improvement by exploiting implicit information that is present in a brain anatomical system, whereas inter-acting nodes are connected by edges whose weights can be determined by either temporal associations or anatomical connections. Considering all these aspects, a novel hybrid framework is proposed for epileptic seizure detection by combined with a sequential graph convolutional network (SGCN) and deep recurrent neural network (DeepRNN). Here, DepRNN is developed by fusing a gated recurrent unit (GRU) with a traditional RNN; its key benefit is that it solves the vanishing gradient problem and achieve this hybrid framework greater sophistication. The line length feature, auto-covariance, auto-correlation, and periodogram are applied as a feature from the raw EEG signal and then grouped the resulting matrix into time-frequency domain as inputs for the SGCN to use for seizure classification. This model extracts both spatial and temporal information, resulting in improved accuracy, precision, and recall for seizure detection. Extensive experiments conducted on the CHB-MIT and TUH datasets showed that the SGCN-DeepRNN model outperforms other deep learning models for seizure detection, achieving an accuracy of 99.007%, with high sensitivity and specificity.

Optimizing AVR system performance via a novel cascaded RPIDD2-FOPI controller and QWGBO approach.

Maintaining stable voltage levels is essential for power systems' efficiency and reliability. Voltage fluctuations during load changes can lead to equipment damage and costly disruptions. Automatic voltage regulators (AVRs) are traditionally used to address this issue, regulating generator terminal voltage. Despite progress in control methodologies, challenges persist, including robustness and response time limitations. Therefore, this study introduces a novel approach to AVR control, aiming to enhance robustness and efficiency. A custom optimizer, the quadratic wavelet-enhanced gradient-based optimization (QWGBO) algorithm, is developed. QWGBO refines the gradient-based optimization (GBO) by introducing exploration and exploitation improvements. The algorithm integrates quadratic interpolation mutation and wavelet mutation strategy to enhance search efficiency. Extensive tests using benchmark functions demonstrate the QWGBO's effectiveness in optimization. Comparative assessments against existing optimization algorithms and recent techniques confirm QWGBO's superior performance. In AVR control, QWGBO is coupled with a cascaded real proportional-integral-derivative with second order derivative (RPIDD2) and fractional-order proportional-integral (FOPI) controller, aiming for precision, stability, and quick response. The algorithm's performance is verified through rigorous simulations, emphasizing its effectiveness in optimizing complex engineering problems. Comparative analyses highlight QWGBO's superiority over existing algorithms, positioning it as a promising solution for optimizing power system control and contributing to the advancement of robust and efficient power systems.

Formulation and In Vitro-Ex vivo Evaluation of Cannabidiol and Cannabidiol-Valine-Hemisuccinate Loaded Lipid-Based Nanoformulations for Ocular Applications.

The goal of this investigation is to develop stable ophthalmic nanoformulations containing cannabidiol (CBD) and its analog cannabidiol-valine-hemisuccinate (CBD-VHS) for improved ocular delivery. Two nanoformulations, nanoemulsion (NE) and nanomicelles (NMC), were developed and evaluated for physicochemical characteristics, drug-excipient compatibility, sterilization, thermal analysis, surface morphology, ex-vivo transcorneal permeation, corneal deposition, and stability. The saturation solubility studies revealed that among the surfactants tested, Cremophor EL had the highest solubilizing capacity for CBD (23.3 ± 0.1 mg/mL) and CBD-VHS (11.2 ± 0.2 mg/mL). The globule size for the lead CBD formulations (NE and NMC) ranged between 205 and 270 nm while CBD-VHS-NMC formulation had a particle size of about 78 nm. The sterilized formulations, except for CBD-VHS-NMC at 40 °C, were stable for three months of storage (last time point tested). Release, in terms of CBD, in the in-vitro release/diffusion studies over 18 h, were faster from the CBD-VHS nanomicelles (38 %) compared to that from the CBD nanoemulsion (16 %) and nanomicelles (33 %). Transcorneal permeation studies revealed improvement in CBD permeability and flux with both formulations; however, a greater improvement was observed with the NMC formulation compared to the NE formulation. In conclusion, the nanoformulations prepared could serve as efficient topical ocular drug delivery platforms for CBD and its analog.

Valorization of edible films based on chitosan/hydroxyethyl cellulose/olive leaf extract and TiO2-NPs for preserving sour cream.

Biodegradable edible films for sour cream packaging were developed based on chitosan (CS), hydroxyethyl cellulose (HEC), Olive leaf extract (OE), and titanium dioxide nanoparticles (TiO2-NPs). The prepared CS/HEC/TiO2-OE bionanocomposite films were evaluated for their antimicrobial and antioxidant activities as well as using FT-IR, mechanical, permeability, and contact angle. The effect of developed films on the lipid oxidation, microbiological load, and chemical properties of sour cream was investigated. The fabricated films had an antimicrobial impact against all tested strains. The film containing 8 % OE showed effective protection against fat oxidation, with a peroxide value of 3.21 meq O2/kg, a para-anisidine value 5.40, and free fatty acids of 0.82 mg KOH/kg. The films with OE 4 % and 8 % have a good effect on the microbiological load of sour cream for 90 days. These films did not influence the chemical composition of sour cream and therefore can be used in this sort of dairy product.

Immediate effect of physical activity on the autonomic nervous system in individuals with autism spectrum disorders of different age groups: a randomised trial.

Background: Autism spectrum disorder (ASD) is one of the most complex neurodevelopmental disorders. It affects almost all human physiological systems. Individuals with ASD often display dysregulation in their autonomic nervous system (ANS), which may elicit differing effects across age groups. Also, studying the ANS missed several important parameters related to ANS. Studying the ANS is crucial in developing adaptive behavioural strategies and maintaining communication abilities and social behaviours. Thus, this study compared the immediate effect of physical activity on the ANS in individuals with ASD in different age groups. Methods: 200 participants (106 males and 94 females) took part in a double-blinded randomised design. All participants were divided into four groups according to their age (4-7, 7-10, 10-13 and 14-18 years old). Participants performed a 60 min treadmill walk. The main outcome measurements were heart rate (HR), saturation of peripheral oxygen (SpO2), respiratory rate (RR) and end-tidal carbon dioxide (etCO2). Results: Before the study, there were non-significant differences between groups in their physical characteristics (body mass index, Childhood Autism Rating Scale, physical activity level, both parents' existence, aerobic capacity and gender) (p>0.05). At baseline measurements, there were non-significant differences between all groups for all outcome measurements (p>0.05). Immediately after physical activity, there was significant difference between group 1 and other groups (p<0.05), while all other differences were non-significant (p>0.05). At the follow-up (after 15 min of rest), group 1 maintained significant differences with the other groups for all outcome measurements (p<0.05), while there were non-significant differences between the other three groups (p>0.05). Conclusion: This study revealed that the SpO2 significantly decreased immediately after the physical activity, while HR, RR and etCO2 significantly increased immediately after physical activity in comparison to the baseline measurements. Contrary to other ANS parameters (SpO2, RR and etCO2), HR in early ages (4-7 years old) was higher after physical activity and remained elevated longer than other ages. The early ages (4-7 years old) take more time to return to the normal status of ANS parameters including SpO2, HR, RR and etCO2. Trial registration number: NCT05725733.

A novel visible and near-infrared hyperspectral imaging platform for automated breast-cancer detection.

BACKGROUND: Breast cancer is a leading cause of cancer-related deaths among women worldwide. Early and accurate detection is crucial for improving patient outcomes. Our study utilizes Visible and Near-Infrared Hyperspectral Imaging (VIS-NIR HSI), a promising non-invasive technique, to detect cancerous regions in ex-vivo breast specimens based on their hyperspectral response. METHODS: In this paper, we present a novel HSI platform integrated with fuzzy c-means clustering for automated breast cancer detection. We acquire hyperspectral data from breast tissue samples, and preprocess it to reduce noise and enhance hyperspectral features. Fuzzy c-means clustering is then applied to segment cancerous regions based on their spectral characteristics. RESULTS: Our approach demonstrates promising results. We evaluated the quality of the clustering using metrics like Silhouette Index (SI), Davies-Bouldin Index (DBI), and Calinski-Harabasz Index (CHI). The clustering metrics results revealed an optimal number of 6 clusters for breast tissue classification, and the SI values ranged from 0.68 to 0.72, indicating well-separated clusters. Moreover, the CHI values showed that the clusters were well-defined, and the DBI values demonstrated low cluster dispersion. Additionally, the sensitivity, specificity, and accuracy of our system were evaluated on a dataset of breast tissue samples. We achieved an average sensitivity of 96.83%, specificity of 93.39%, and accuracy of 95.12%. These results indicate the effectiveness of our HSI-based approach in distinguishing cancerous and non-cancerous regions. CONCLUSIONS: The paper introduces a robust hyperspectral imaging platform coupled with fuzzy c-means clustering for automated breast cancer detection. The clustering metrics results support the reliability of our approach in effectively segmenting breast tissue samples. In addition, the system shows high sensitivity and specificity, making it a valuable tool for early-stage breast cancer diagnosis. This innovative approach holds great potential for improving breast cancer screening and, thereby, enhancing our understanding of the disease and its detection patterns.

Formulation Development of Solid Self-Nanoemulsifying Drug Delivery Systems of Quetiapine Fumarate via Hot-Melt Extrusion Technology: Optimization Using Central Composite Design.

Quetiapine fumarate (QTF) was approved for the treatment of schizophrenia and acute manic episodes. QTF can also be used as an adjunctive treatment for major depressive disorders. QTF oral bioavailability is limited due to its poor aqueous solubility and pre-systemic metabolism. The objective of the current investigation was the formulation development and manufacturing of solid self-nanoemulsifying drug delivery system (S-SNEDDS) formulation through a single-step continuous hot-melt extrusion (HME) process to address these drawbacks. In this study, Capmul® MCM, Gelucire® 48/16, and propylene glycol were selected as oil, surfactant, and co-surfactant, respectively, for the preparation of S-SNEDDS. Soluplus® and Klucel™ EF (1:1) were selected as the solid carrier. Response surface methodology in the form of central composite design (CCD) was utilized in the current experimental design to develop the S-SNEDDS formulations via a continuous HME technology. The developed formulations were evaluated for self-emulsifying properties, particle size distribution, thermal behavior, crystallinity, morphology, physicochemical incompatibility, accelerated stability, and in vitro drug release studies. The globule size and emulsification time of the optimized SNEDDS formulation was 92.27 ± 3.4 nm and 3.4 ± 3.38 min. The differential scanning calorimetry (DSC) and powder X-ray diffraction (PXRD) studies revealed the amorphous nature of the drug within the formulation. There were no drug-excipient incompatibilities observed following the Fourier transform infrared (FTIR) spectroscopy. The optimized formulation showed an extended-release profile for 24 h. The optimized formulation was stable for three months (last time-point tested) at 40 °C/75% RH. Therefore, the developed S-SNEDDS formulation could be an effective oral delivery platform for QTF and could lead to better therapeutic outcomes.

DESP demixes cell-state profiles from dynamic bulk molecular measurements.

Understanding the dynamic expression of proteins and other key molecules driving phenotypic remodeling in development and pathobiology has garnered widespread interest, yet the exploration of these systems at the foundational resolution of the underlying cell states has been significantly limited by technical constraints. Here, we present DESP, an algorithm designed to leverage independent estimates of cell-state proportions, such as from single-cell RNA sequencing, to resolve the relative contributions of cell states to bulk molecular measurements, most notably quantitative proteomics, recorded in parallel. We applied DESP to an in vitro model of the epithelial-to-mesenchymal transition and demonstrated its ability to accurately reconstruct cell-state signatures from bulk-level measurements of both the proteome and transcriptome, providing insights into transient regulatory mechanisms. DESP provides a generalizable computational framework for modeling the relationship between bulk and single-cell molecular measurements, enabling the study of proteomes and other molecular profiles at the cell-state level using established bulk-level workflows.

Formulation and evaluation of inhaled Sildenafil-loaded PLGA microparticles for treatment of pulmonary arterial hypertension (PAH): A novel high drug loaded formulation and scalable process via hot melt extrusion technology (Part â ).

In recent years, several techniques were employed to develop a local sustained pulmonary delivery of sildenafil citrate (SC) as an alternative for the intravenous and oral treatment of pulmonary arterial hypertension (PAH). Most of these methods, however, need to be improved due to limitations of scalability, low yield production, low drug loading, and stability issues. In this study, we report the use of hot-melt extrusion (HME) as a scalable process for making Poly (lactic-co-glycolic acid) (PLGA) microparticles with high SC load. The prepared particles were tested in vitro for local drug delivery to the lungs by inhalation. Sodium bicarbonate was included as a porogen in the formulation to make the particles more brittle and to impart favorable aerodynamic properties. Six formulations were prepared with different formulation compositions. Laser diffraction analysis was used to estimate the geometric particle size distribution of the microparticles. In-vitro aerodynamic performance was evaluated by the next-generation cascade impactor (NGI). It was reported in terms of an emitted dose (ED), an emitted fraction (EF%), a respirable fraction (RF%), a fine particle fraction (FPF%), a mass median aerodynamic diameter (MMAD), and geometric standard deviation (GSD). The formulations have also been characterized for surface morphology, entrapment efficiency, drug load, and in-vitro drug release. The results demonstrated that PLGA microparticles have a mean geometric particle size between 6 and 14 µm, entrapment efficiency of 77 to 89 %, and SC load between 17 and 33 % w/w. Fifteen percent of entrapped sildenafil was released over 24 h from the PLGA microparticles, and seventy percent over 7 days. The aerodynamic properties included fine particle fraction ranging between 19 and 33 % and an average mass median aerodynamic diameter of 6-13 µm.

Shock wave lithotripsy in the era of COVID-19.

Objective: The objective of the study y was to evaluate factors which can improve shock wave lithotripsy (SWL) results to keep up with COVID-19 pandemic. Methods: Between June 2020 and June 2021, patients with radio-opaque or faint radio-opaque upper urinary tract stones, stone attenuation value ≤1200 HU, and stones size <2.5 cm were treated by electrohydraulic SWL. Patients with respiratory tract symptoms elevated temperature, contact with COVID-19 patients, or positive COVID-19 swab 2 weeks preoperatively, skin-to-stone distance >11 cm, and body mass index >30 kg/m2 were excluded from the study. Patients were prospectively enrolled in SWL done at a rate of 40-50 SWs/min under combined ultrasound and fluoroscopy-guided, ramped into high power in the 1st 300 shocks. Success rate and complications were recorded. Results: Five hundred and ninety patients completed the study. The success rate after 1st session was 408/590 patients (69.15%) which was augmented by 2nd session to reach 527/590 patients 89.3%. The success rate was 96.2% at 3 months postoperatively. Most complications were mild (Grade 1 or 2). Conclusions: SWL results improved using slow rate high power from the start of the session under combined fluoroscopy and ultrasound guidance. SWL may be a preferred option during a pandemic.

Non-Surgical Approaches to the Management of Lumbar Disc Herniation Associated with Radiculopathy: A Narrative Review.

Lumbar disc herniation associated with radiculopathy (LDHR) is among the most frequent causes of spine-related disorders. This condition is triggered by irritation of the nerve root caused by a herniated disc. Many non-surgical and surgical approaches are available for managing this prevalent disorder. Non-surgical treatment approaches are considered the preferred initial management methods as they are proven to be efficient in reducing both pain and disability in the absence of any red flags. The methodology employed in this review involves an extensive exploration of recent clinical research, focusing on various non-surgical approaches for LDHR. By exploring the effectiveness and patient-related outcomes of various conservative approaches, including physical therapy modalities and alternative therapies, therapists gain valuable insights that can inform clinical decision-making, ultimately contributing to enhanced patient care and improved outcomes in the treatment of LDHR. The objective of this article is to introduce advanced and new treatment techniques, supplementing existing knowledge on various conservative treatments. It provides a comprehensive overview of the current therapeutic landscape, thereby suggesting pathways for future research to fill the gaps in knowledge. Specific to our detailed review, we identified the following interventions to yield moderate evidence (Level B) of effectiveness for the conservative treatment of LDHR: patient education and self-management, McKenzie method, mobilization and manipulation, exercise therapy, traction (short-term outcomes), neural mobilization, and epidural injections. Two interventions were identified to have weak evidence of effectiveness (Level C): traction for long-term outcomes and dry needling. Three interventions were identified to have conflicting or no evidence (Level D) of effectiveness: electro-diagnostic-based management, laser and ultrasound, and electrotherapy.

3D printing in vaginal drug delivery: a revolution in pharmaceutical manufacturing.

INTRODUCTION: The Food and Drug Administration's approval of the first three-dimensional (3D) printed tablet, Spritam®, led to a burgeoning interest in using 3D printing to fabricate numerous drug delivery systems for different routes of administration. The high degree of manufacturing flexibility achieved through 3D printing facilitates the preparation of dosage forms with many actives with complex and tailored release profiles that can address individual patient needs. AREAS COVERED: This comprehensive review provides an in-depth look into the several 3D printing technologies currently utilized in pharmaceutical research. Additionally, the review delves into vaginal anatomy and physiology, 3D-printed drug delivery systems for vaginal applications, the latest research studies, and the challenges of 3D printing technology and future possibilities. EXPERT OPINION: 3D printing technology can produce drug-delivery devices or implants optimized for vaginal applications, including vaginal rings, intra-vaginal inserts, or biodegradable microdevices loaded with drugs, all custom-tailored to deliver specific medications with controlled release profiles. However, though the potential of 3D printing in vaginal drug delivery is promising, there are still challenges and regulatory hurdles to overcome before these technologies can be widely adopted and approved for clinical use. Extensive research and testing are necessary to ensure safety, effectiveness, and biocompatibility.