Explore the vast range of titles available.

Optimal mitochondrial function determined by mitochondrial dynamics, morphology and activity is coupled to stem cell differentiation and organism development. However, the mechanisms of interaction of signaling pathways with mitochondrial morphology and activity are not completely understood. We assessed the role of mitochondrial fusion and fission in the differentiation of neural stem cells called neuroblasts (NB) in the Drosophila brain. Depleting mitochondrial inner membrane fusion protein Opa1 and mitochondrial outer membrane fusion protein Marf in the Drosophila type II NB lineage led to mitochondrial fragmentation and loss of activity. Opa1 and Marf depletion did not affect the numbers of type II NBs but led to a decrease in differentiated progeny. Opa1 depletion decreased the mature intermediate precursor cells (INPs), ganglion mother cells (GMCs) and neurons by the decreased proliferation of the type II NBs and mature INPs. Marf depletion led to a decrease in neurons by a depletion of proliferation of GMCs. On the contrary, loss of mitochondrial fission protein Drp1 led to mitochondrial clustering but did not show defects in differentiation. Depletion of Drp1 along with Opa1 or Marf also led to mitochondrial clustering and suppressed the loss of mitochondrial activity and defects in proliferation and differentiation in the type II NB lineage. Opa1 depletion led to decreased Notch signaling in the type II NB lineage. Further, Notch signaling depletion via the canonical pathway showed mitochondrial fragmentation and loss of differentiation similar to Opa1 depletion. An increase in Notch signaling showed mitochondrial clustering similar to Drp1 mutants. Further, Drp1 mutant overexpression combined with Notch depletion showed mitochondrial fusion and drove differentiation in the lineage, suggesting that fused mitochondria can influence differentiation in the type II NB lineage. Our results implicate crosstalk between proliferation, Notch signaling, mitochondrial activity and fusion as an essential step in differentiation in the type II NB lineage.

Autophagy is a degradative process that makes rapid turnover of old and impaired proteins and organelles possible. It is highly instigated by stress signals, like starvation, and contributes to the cell’s homeostasis. Autophagy performs a crucial function in keeping cell genomic integrity stable. Impaired autophagic flux is implicated in neurodegenerative diseases, abnormal ageing, and cancerous diseases. In diseases like cancer, autophagy performs a dualistic function; it can have both a tumor-suppressive and supportive role. Autophagy in the initial phases of tumorigenesis maintains the integrity of the genome and, if it fails, leads to cell death, thus having a tumor-suppressive role. Meanwhile, autophagy also imparts the function of the pro-survival mechanism in the latter stages of tumorigenesis and supports the cancerous cells in surviving conditions like hypoxia and increased oxidative stress. Autophagy also helps cancerous cells develop drug resistance in some cases. Thus, modulation of the autophagic mechanism is a possible therapeutic strategy in cancer therapy as its inhibition can sensitise cancer cells to anti-cancerous drugs. The promotion of autophagy, in some cases, can also safeguard cells from toxic protein aggregation and enhanced oxidative stress. Excessive autophagy can result in autophagic cell death. Autophagy also regulates several cellular processes and cell death pathways, like apoptosis. Therefore, an in-depth knowledge of the autophagy process and its regulating molecules is critically important. Pharmaceutical small molecules or cellular target modulation can help modulate the cellular autophagy process in the context of specific disease conditions.

Background Vildagliptin (VLG), an antidiabetic agent, presents a potential solution to this widespread affliction. It exhibits notable attributes, such as a high solubility and a shorter elimination half-life. The current study uses a microreactor to fabricate sustained-release VLG-encapsulated cross-linked chitosan–dextran sulfate nanoparticles (VLG-CDNPs). The fabrication was systematically optimized using the design of experiment approach. Results The optimized VLG-CDNPs had an average particle size of 217.4 ± 12.3 nm and an encapsulation efficiency of 78.25 ± 3.0%. Scanning electron microscopy revealed that the nanoparticles had a smooth spherical shape. Spray drying was used for drying, and the reconstitution ability was close to ideal (~ 1.33). In vitro studies revealed sustained VLG release over 12 h, with ~ 58% in acidic and ~ 83% in basic conditions. Cell viability remained at 80% even at 100 μg/mL, and glucose uptake in L6 cells was significantly enhanced with VLG-CDNPs (78.34%) compared to pure VLG (60.91%). VLG-CDNPs also showed moderate inhibitory activity against α-amylase (41.57%) and α-glucosidase (63.48%) compared to pure VLG, which had higher inhibition levels. Conclusion The study’s outcome suggested that the optimized VLG-CDNPs  may serve as an effective and promising nanoformulation for managing diabetes mellitus.

Machine failures during the manufacturing process can have severe consequences, causing extensive downtime and financial losses. Hence, predictive maintenance (PdM) plays a crucial role within the Industrial Internet of Things (IIoT) by estimating the remaining useful life (RUL) of machines so that proactive maintenance measures can be taken to mitigate potential failures and minimize disruptions. RUL estimation is enabled by gathering and processing the data sensed by sensors mounted on and around the machines at the central server (base station or cloud) after analyzing the failure patterns. However, this approach imposes a significant load on network bandwidth and leads to poor response time for the monitoring system because a large volume of sensed data has to be transmitted to the central server for processing. Moreover, due to the singularity of the computing resource, many problems, such as inefficient resource utilization, frequent offloading, single-point failure, etc., have become major challenges. To address these issues, this article proposes an edge computing-enabled predictive maintenance framework called “Collaborative Predictive Maintenance Framework\" ( CollabRULe ), which first identifies the optimal locations for edge server placement in the deployment region by considering the QoS parameters, such as energy, delay and connectivity. Then, it uses federated learning for predictive maintenance by estimating the RUL of the machines. Simulation results show that the proposed mechanism effectively minimizes the overall network energy consumption and end-to-end delay by ≈ 60 % and ≈ 35 % , respectively, as compared to state-of-the-art approaches. Furthermore, it shows significant improvement in the accuracy of RUL prediction as compared to its counterparts.

Data acquisition using mobile sink in wireless sensor networks (WSNs) has shown significant advantages, especially in large-scale networks. Unlike the acquisition of sensor data by static sink through multi-hop forwarding, mobile sink travels across the sensing field to acquire data, which significantly reduces the energy consumption of sensor nodes. However, deciding sojourning locations for mobile sink in sensing field and designing a delay efficient trajectory path for its movement are very challenging. This paper takes up this issue and proposes an energy and delay efficient data acquisition technique, named as EDEDA . It divides the sensor field into virtual grids and identifies a certain number of grid cells, termed as visiting points (VPs), in such a way that mobile sink sojourns in them and acquires data from nine adjacent grid cell heads in single-hop. Furthermore, the mobility pattern of mobile sink is modelled as Hamiltonian cycle starting and ending at the base station (BS) after visiting all the VPs. Mobile sink offloads collected data at BS after each cycle. Simulations are performed on NS-2 to evaluate the performance of EDEDA at varying number of sensor nodes and found that it outperforms existing routing protocols in terms of energy consumption and throughput. Moreover, EDEDA results in 25.72%, 25.72%, 19.54%, 14.57% improvement in data acquisition latency for varying number of sensor nodes when compared with TCBDGA, PSOBS, RkM, VGRSS, respectively.

Chain-based routing protocols play a vital role in enabling energy-efficient communication in wireless sensor networks (WSNs). Building upon the foundational principles established by power efficient gathering in sensor information systems (PEGASIS), researchers have proposed several modified versions and novel chain-based routing protocols. This paper surveys the evolution of chain-based routing protocols, classifying them into hybrid and non-hybrid categories. Hybrid protocols combine chain topology with other virtual structures---such as clusters, grids or trees---to enhance overall network performance. Our findings highlight that hybrid chain-based routing protocols achieve up to 30% improvement in energy efficiency and 25% reduction in latency compared to non-hybrid chain-based routing protocols. Each protocol is examined comprehensively in this paper, providing in-depth insights into their design and trade-offs, including the balance between scalability and energy consumption.

Dry powder inhalers (DPIs) are state-of-the-art pulmonary drug delivery systems. This article explores the transformative impact of nanotechnology on DPIs, emphasizing the Quality Target Product Profile (QTPP) with a focus on aerodynamic performance and particle characteristics. It navigates global regulatory frameworks, underscoring the need for safety and efficacy standards. Additionally, it highlights the emerging field of nanoparticulate dry powder inhalers, showcasing their potential to enhance targeted drug delivery in respiratory medicine. This concise overview is a valuable resource for researchers, physicians, and pharmaceutical developers, providing insights into the development and commercialization of advanced inhalation systems. Graphical Abstract

The changing and diverse nature of the environment presents challenges in predicting natural disasters, which are further exacerbated by human interventions such as road and dam constructions, tunnelling, and hydropower projects in mountainous regions, along with changing climate conditions. Landslides, common in mountainous terrain, pose risks to both travellers and residents. The susceptibility of mountain slopes to landslides increases during the monsoon season from June to September in the study area, as water infiltration saturates rock masses, increasing their weight and reducing friction angles. Additionally, the capacity of the drainage system to carry loads rises during this period. This study uses field-based data and various methodologies along the Bhowali–Lohali section of the National Highway-109 (NH-109) to assess slope stability and suggest landslide risk mitigation measures. A comparative analysis of slope stability was conducted using methods such as kinematic analysis, slope mass rating (SMR), continuous slope mass rating (CSMR), the chart method, and the landslide possibility index (LPI). According to the SMR, three locations (S3, S5, S7) are completely unstable, while only one location (S3) is completely unstable, according to the CSMR. Based on the LPI, two locations (S6, S9) have a very high possibility of failure, and the chart method indicates that four locations (S3, S4, S5, S8) are unstable. The study suggested necessary support systems such as rock bolting, shotcrete, wire meshing, ditch catchment and drainage systems at the suitability with site-specific in instability-prone localities to mitigate the landslide activities.

Niclosamide (NIC), an anthelminthic drug, is found to be promising in overcoming the problem of various types of drug-resistant cancer. In spite of strong anti-proliferative effect, NIC shows low aqueous solubility, leading to poor bioavailability. To overcome this limitation, and enhance its physicochemical properties and pharmacokinetic profile, we used co-crystallization technique as a promising strategy. In this work, we brought together the crystal and particle engineering at a time using spray drying to enhance physicochemical and aerodynamic properties of co-crystal particle for inhalation purpose. We investigated the formation and evaluation of pharmaceutical co-crystals of niclosamide-nicotinamide (NIC-NCT) prepared by rapid, continuous and scalable spray drying method and compared with conventional solvent evaporation technique. The newly formed co-crystal was evaluated by XRPD, FTIR, Raman spectroscopy and DSC, which showed an indication of formation of H bonds between drug (NIC) and co-former (NCT) as a major binding force in co-crystal development. The particle geometry of co-crystals including spherical shape, size 1–5 μm and aerodynamic properties (ED, 97.1 ± 8.9%; MMAD, 3.61 ± 0.87 μm; FPF, 71.74 ± 6.9% and GSD 1.46) attributes suitable for inhalation. For spray-dried co-crystal systems, an improvement in solubility characteristics (≥ 14.8-fold) was observed, relative to pure drug. To investigate the anti-proliferative activity, NIC-NCT co-crystals were investigated on A549 human lung adenomas cells, which showed a superior cytotoxic activity compared with pure drug. Mechanistically, NIC-NCT co-crystals enhanced autophagic flux in cancer cell which demonstrates autophagy-mediated cell death as shown by confocal microscopy. This technique could help in improving bioavailability of drug, hence reducing the need for high dosages and signifying a novel paradigm for future clinical applications.

Changes in the transition metal homeostasis in the brain are closely linked with Alzheimer’s disease (AD), including intraneuronal iron accumulation and extracellular copper and zinc pooling in the amyloid plague. The brain copper, zinc, and iron surplus are commonly acknowledged characteristics of AD, despite disagreements among some. This has led to the theory that oxidative stress resulting from abnormal homeostasis of these transition metals may be a causative explanation behind AD. In the nervous system, the interaction of metals with proteins appears to be an essential variable in the development or suppression of neurodegeneration. Chelation treatment may be an option for treating neurodegeneration induced by transition metal ion dyshomeostasis. Some clinicians even recommend using chelating agents as an adjunct therapy for AD. The current review also looks at the therapeutic strategies that have been attempted, primarily with metal-chelating drugs. Metal buildup in the nervous system, as reported in the AD, could be the result of compensatory mechanisms designed to improve metal availability for physiological functions.