Search

The classical pathway of the complement system is activated by the binding of C1q in the C1 complex to the target activator, including immune complexes. Factor H is regarded as the key downregulatory protein of the complement alternative pathway. However, both C1q and factor H bind to target surfaces via charge distribution patterns. For a few targets, C1q and factor H compete for binding to common or overlapping sites. Factor H, therefore, can effectively regulate the classical pathway activation through such targets, in addition to its previously characterized role in the alternative pathway. Both C1q and factor H are known to recognize foreign or altered-self materials, e.g., bacteria, viruses, and apoptotic/necrotic cells. Clots, formed by the coagulation system, are an example of altered self. Factor H is present abundantly in platelets and is a well-known substrate for FXIIIa. Here, we investigated whether clots activate the complement classical pathway and whether this is regulated by factor H. We show here that both C1q and factor H bind to the fibrin formed in microtiter plates and the fibrin clots formed under in vitro physiological conditions. Both C1q and factor H become covalently bound to fibrin clots, and this is mediated via FXIIIa. We also show that fibrin clots activate the classical pathway of complement, as demonstrated by C4 consumption and membrane attack complex detection assays. Thus, factor H downregulates the activation of the classical pathway induced by fibrin clots. These results elucidate the intricate molecular mechanisms through which the complement and coagulation pathways intersect and have regulatory consequences.

This research explores the effects of wear on a 6063 aluminum alloy matrix combined with silicon carbide (SiC) and tungsten disulfide (WS2) particulates. Dry friction wear tests were conducted on three materials: pure 6063 aluminum alloy, a composite with 4 wt% SiC and 4 wt% WS2 reinforcement, and another composite with 6 wt% SiC and 4 wt% WS2 reinforcement. These materials were tested against AISI410 stainless steel discs under varying loads (10N, 20N, and 30N) and sliding rates (0.5, 1.0, and 1.5 ms−1) following a Taguchi L27 orthogonal experimental plan. Main effect graphs (S/N ratios) and ANOVA analysis were utilized to determine optimal parameter combinations, and confirmation tests were carried out to validate the Taguchi results. Scanning electron microscope (SEM) images of wear areas showed that incorporating SiC and WS2 significantly enhanced the wear resistance of the aluminum alloy. This indicates that incorporating SiC and WS2 reinforcement has the potential to enhance the wear resistance of aluminum alloys, making them suitable for applications such as piston rings in internal combustion engines, which is in line with the requirements of engine performance. Furthermore, potentiodynamic polarization studies evaluated the corrosion resistance of the Metal Matrix Composites AA6063 in 3.5% NaCl. Results indicated that the AA6063 + 6 wt% SiC + 4 wt% WS2 composite exhibited superior corrosion resistance compared to AA6063 alone.

By cultivating more sustainable, effective, and efficient corporate practices, artificial intelligence (AI) reinvents financial management. Contemporary finance includes AI as an existential component. The cornerstone technology of the industrial revolution and technological revolution is artificial intelligence. The rise of artificial intelligence (AI) is reshaping financial management by transforming how firms make choices, allocate resources and control risk. As companies face increasing pressure to integrate sustainability into their operations artificial intelligence (AI) has emerged as a key tool for resolving complex environmental concerns and improving financial performance. AI-powered analytics can help businesses detect and assess ecological issues, optimize resource allocation, and speed up financial processes like forecasting, auditing, and budgeting. This strengthens decision-making and increases operational efficiency by providing real-time insights on ESG (Environmental, Social, and Governance) factors. AI also helps businesses, investors, and creditors. This research paper explores the literature on the transformative Power of AI in financial management, examining its role, applications, benefits, and challenges. It investigates AI’s impact on financial forecasting, portfolio optimization, risk management and compliance.

In the past, the perspective of training programs has been used to understand employee motivation. However, there is a lack of normative and perceptive support that can guide the development of online training programs. Therefore, there is a need to understand employee motivation from the perspective of online training. This study aims to understand employee motivation and its relationship with online training in an organizational setting. The study adopted empirical research to investigate the relationship between training goals and trainee intentions to undergo online training, the role of self-efficacy in this relationship, and the expectancy of the learners from online training programs. The study tests the factors identified from the literature review for model validation. A total of 15 items were used in a survey of 812 randomly selected respondents from the organization in Belagavi, Karnataka, India. The structural equation modeling techniques were applied to explore and validate the model. The results show that factors such as learning goals, social interaction, time management and personalization have a great role to play in building training intention in the online environment, and the successful realization of the training goals. [ABSTRACT FROM AUTHOR]

Binary transition metal chalcogenides and reduced graphene oxide exhibit significant potential for energy storage devices due to their superior electronic conductivity and capacity, surpassing that of single-metal sulfides, owing to their more extensive redox reactions. In this report, we introduce a novel synthesis method for producing a mixed-phase MnSe2/CoSe2 nanocomposite wrapped with reduced graphene oxide (rGO) sheets, designed specifically for supercapacitor applications. The MnSe2/CoSe2 hybrid material was synthesized using an ultrasonic assisted hydrothermal technique, followed by the preparation of the rGO/MnSe2/CoSe2 hybrid composite. The structural characterization was conducted employing x-ray diffraction (XRD), scanning electron microscopy (SEM), x-ray photoelectron spectroscopy (XPS) and Raman techniques. Brunauer–Emmett–Teller (BET) analysis demonstrated a significant specific surface area (66.5 m2/g) and a pore size distribution of 28.4 nm in rGO-MnSe2/CoSe2. The interconnected ultrathin rGO nanosheets and conductive carbon layer contributed to the exceptional conductivity and stability achieved by the rGO/MnSe2/CoSe2 composite electrode. The electrochemical performance was assessed using a three-electrode setup in a 3 M KOH solution, with nickel foam as the current collector. The working electrode, consisting of rGO/MnSe2/CoSe2, acetylene black and PVDF in an 80:15:5 weight ratio, demonstrated specific capacitance of 1214 F g−1 and cycling stability of 88% retention after 5000 cycles at 1 A g−1. An asymmetric supercapacitor, constructed using a tailored electrode composition, achieved energy density of 28.6 Wh kg−1 at 2100 W kg−1 and high power density of 888 W kg−1 at 49.7 Wh kg−1. [ABSTRACT FROM AUTHOR]

This study describes using carbon fibers coated with magnetic material as a filler in polyethylene for EMI shielding. It investigates how to utilize barium ferrite (BaFeO3) as a conducting filler in a polyethylene matrix by optimizing the conditions for its electroless deposition onto carbon fibers. Various polymer nanocomposite samples were prepared using varying concentrations of BFO@CF. Scanning electron microscopy is used to assess the surface appearance of the composite and the distribution of BFO@CF within the polymer matrix. Including MWCNT/graphene nanoplatelets exhibit superior shielding properties, and the polymer composite with the BFO@CF demonstrates enhanced mechanical properties. The 8.2 to 12.4 GHz frequency range is used to study the EMI shielding properties. For the composition ratio of LDPE: MWCNT: GNP: BFO@CF (50 : 5 : 47.5 : 2.5), a maximum shielding of 67 dB was attained. After BFO@CF was added to the matrix, the absorption mechanism rather than the reflection mechanism dominated the shielding mechanism. A thorough evaluation and discussion of the shielding mechanism and parameters are presented. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is a very famous network because of its many applications. IoT network has an integration of large-scale IoT devices that generate data. These IoT devices are very low power computing devices due to which they have a low level of communication. These devices construct data and transmit the data to the base station via intermediate IoT devices. The base station gathers and integrates the data and sends it to the administrator for further processing. The data attains the base station using various routing algorithms with the goal of low power consumption. When discussing low power IoT devices, power efficiency is an important performance measurement when creating a routing algorithm. This paper proposes a Minimum Power Consumption Routing (MPCR) algorithm using Hierarchical Fuzzy Logic Clustering (HFLC) algorithm for IoT networks. The MPCR with HFLC algorithm is an energy-efficient algorithm because of its lower power consumption for the cluster by aggregating the data within the cluster head and decreasing the number of data transmissions to the base station. In this paper, the cluster formation and cluster-head selection are explained, and a simulation has been conducted. In addition, the proposed algorithm is compared with the existing algorithms based on different metrics such as throughput, packet delivery ratio, and energy consumption of the network. The experimental results show that the proposed MPCR with the HFLC algorithm provides high throughput and packet delivery ratio and reduces energy consumption more efficiently than other existing algorithms. [ABSTRACT FROM AUTHOR]

Distributed processing systems play a crucial role in query search operations, where large-scale data are partitioned across multiple nodes using shard selection algorithms. However, the existing shard selection algorithms pose significant challenges, such as shard ranking, shard cut-off estimation, high latency, low throughput, and high processing costs. These limitations become more pronounced as the data size increases, affecting the efficiency and effectiveness of search operations. To address these challenges, the novel Hybrid Shard Selection Algorithm (HSSA) is proposed as a solution in this paper, designed specifically to enhance the effectiveness and efficiency of search operations within distributed processing systems. HSSA employs an advanced sharding approach that adeptly navigates and targets pertinent shards based on specific queries. This not only curtails search-related overhead but also enhances operational efficiency. Through rigorous testing using the Gov2 dataset, the HSSA algorithm has proven its merits. When set against well-established algorithms like CORI, Rank-S, and SHiRE, HSSA stands out, registering remarkable gains in average throughput by 21%, 16%, and 12%, while also slashing latency by 14.2%, 9.4%, and 8.2%, respectively. The insights gained from this research underscore HSSA's capability to effectively bridge the gaps inherent in traditional shard selection strategies. Furthermore, its exemplary efficacy with datasets of varied sizes amplifies its relevance for practical integration within distributed processing landscapes. [ABSTRACT FROM AUTHOR]

Dacomitinib, a quinazoline compound, exhibits antineoplastic activity against brain metastasis activities in non‐small cell lung cancer and the central nervous system. In this study, the liquid–liquid extraction method with high‐performance liquid chromatography and tandem mass spectrometry detection method was established and validated for the determination of Dacomitinib in human plasma. Plasma samples were prepared and chromatographic separation was achieved on analytical column Discovery C18 (10 cm × 4.6 mm, 5 μm) with gradient elutes at a flow rate of 0.8 mL/min, using a mobile phase consisting of acetonitrile and ammonium formate. Dacomitinib and dacomitinib D10 (internal standard) were detected by multiple reactions. The method was fully validated according to the United States Food and Drug Administration guidelines. The calibration curve was linear with an excellent correlation coefficient (r2 ˂ 0.99). The method validation steps such as carry‐over, matrix effect, extraction recovery, dilution effect, intra‐inter accuracy, and precision were found within acceptable limits. The method was then applied to a pharmacokinetic study in human plasma. After oral administration, the plasma concentration in different volunteers reached 0.5–250.01 ng/mL. The result established can be applied to the estimation of drugs in human plasma. [ABSTRACT FROM AUTHOR]

Background and Objectives: The knowledge of various blood group antigen and phenotype frequencies in a population is important in selecting compatible blood in alloimmunized patients. Such information in Indian population is very limited. Hence this study was carried out to determine the frequency of clinically significant antigens. Such information in Indian population is very limited. Methods: This study was carried out to determine the frequencies of the D, C, c, E, e, K, k, Fya, Fyb, Jka, and Jkb antigens in 1024 blood donors at our department. Samples were collected for extended antigen typing during March 2016-February 2017 for D, C, c, E, e, K, k, Fya, Fyb, Jka, and Jkb antigens using monoclonal antisera by column agglutination technology. Antigenic and phenotypic frequencies were expressed as percentages. Results: Among the Rh system, "e" antigen was found in 98.6% of donors, followed by D (92%), C (89%), c (56%), and E (17%) with DCe/DCe (R1 R1, 41.4%) as the most common phenotype. "k" was found to be positive in 97% of donors, and K+k- phenotype was found in 0.1% of donors. For Kidd and Duffy blood group system, Jk(a+b+) and Fy(a+b+) were the most common phenotypes with frequency of 56.2% and 47.5%, respectively. MNS antigens were not included on account of financial constraints. Conclusion: Database for antigen frequency of various blood group systems in native donors helps provide antigen-negative compatible blood units to patients with multiple antibodies in order to formulate in-house red cells for antibody detection and identification and for preparing donor registry for rare blood groups. [ABSTRACT FROM AUTHOR]

The C-band SAR on-board EOS-04 mission provides unique opportunities to characterize forest vegetation through its sensitiveness to vegetation structure and allweather imaging capability over regions of perpetual cloud cover. The present study has brought out the applications of EOS-04 data for estimation of aboveground biomass (AGB) of tropical deciduous forests and scrublands, mapping of forest cover and delineation of mangroves vegetation. The study suggested that EOS04 data can be used for mapping AGB of tropical scrublands and low density forests of AGB ≤ 80 t/ha. The overall RMSE for all vegetation with AGB ≤ 80 t/ha was 15.3 t/ha (R² – 0.49). It was shown that the integration of EOS-04 and Sentinel-2 data improved AGB estimates across biomass ranges of 0–245 t/ha (RMSE – 21.60 t/ha and 0.81). EOS-04 data was also found to be useful for the delineation of mangroves and forest vegetation using machine-learning algorithms. The study supports operational use of EOS-04 data for estimation of AGB over low biomass tropical forests and scrublands. [ABSTRACT FROM AUTHOR]

Background and Aims: The objective of the study was to evaluate the performances of qCON and qNOX indices in pediatric populations undergoing surgery under general anesthesia (GA), focusing on the induction and recovery periods. Both the indices are derived from electroencephalogram (EEG) and implemented in the CONOX monitor (Fresenius Kabi, Germany)., Material and Methods: After approval of the institutional ethics committee, this prospective observational study was conducted in pediatric patients of either sex in the age group of 1-12 years belonging to the American Society of Anesthesiology (ASA) grade I and II undergoing elective surgery under GA. Anesthetic technique was GA with or without regional analgesia (RA). All patients underwent inhalation induction and maintenance using sevoflurane. Patients were monitored with the use of a CONOX monitoring system (Fresenius Kabi, Germany), connected via a set of electrodes placed over the forehead. qCON and qNOX scores were recorded during awake (on operating table premedicated with oral midazolam 0.5 mg/kg), at induction, at loss of eyelash reflex, intubation/laryngeal mask airway (LMA) insertion, before and after regional anesthesia, surgical incision, at cessation of anesthesia, emergence, extubation, and eye-opening. Registered results were also analyzed compared with the minimum alveolar concentration of sevoflurane (MAC)., Results: A total of 46 pediatric patients were enrolled in the study with a mean age of 5.6 years. All the patients were either ASA I or II. There was a simultaneous fall and rise of qCON and qNOX upon induction and recovery, respectively. There was a rise in qNOX with surgical incision irrespective of RA. However, there was a greater rise in qNOX following surgical incision in those who did not receive RA ( P = 0.33) Also both qCON ( P = 0.06) and qNOX ( P = 0.41) were poorly correlated with MAC values of sevoflurane during GA in the pediatric population., Conclusions: Both qCON and qNOX values change predictably with changes in the conscious level and with different noxious stimuli. Further studies are required to confirm the findings taking into account the postoperative assessment of delirium and recall of intraoperative events., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Journal of Anaesthesiology Clinical Pharmacology.)

This study presents a novel approach to synthesizing silver nanoparticles (Ag NPs) using a solution combustion synthesis (SCS) method with Catharanthus roseus (C. roseus) leaf extract. The NPs were thoroughly characterized through X-ray diffraction (XRD), Scanning electron microscopy (SEM), Energy dispersive X-ray (EDX), Transmission electron microscopy (TEM), and Selected area electron diffraction (SAED), elucidating their crystal structure. Notably, the synthesized Ag NPs exhibited a significant dose-dependent decline in viability of the MDA-MB 231 breast cancer cell line, with an IC50 value of 13.3 μg/mL, underscoring their potential as potent anticancer agent. Beyond cytotoxicity, the study pioneers an investigation into the biocompatibility of Ag NPs by blood hemolsysis, providing critical insights into their safety and biomedical applicability. Furthermore, this research uncovers a distinctive facet of Ag NPs, revealing their inhibitory effects on the inflammatory enzyme secretory phospholipase A2 (sPLA2), a recognized biomarker for breast cancer. The demonstrated in vitro and in vivo inhibition of sPLA2 highlights the multifaceted potential of Ag NPs in not only targeting cancer cells but also modulating inflammatory responses associated with breast cancer, positioning the study at the forefront of advancements in nanomedicine and cancer therapeutics., (© 2023 Wiley-VHCA AG, Zurich, Switzerland.)

Potentilla nepalensis belongs to the Rosaceae family and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in earlier studies. However, the PCs affecting human genes and their roles in the body have not previously been disclosed. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDSs), and MMGBSA methodologies. The SMILES format of PCs from the PubChem was used as input to DIGEP-Pred, with 764 identified as the inducing genes. Their enrichment studies have shown inducing genes' gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analyzing parameters performed in Cytoscape v3.10 revealed three therapeutic targets: TP53 from MS-, NR-, and NS-induced genes; HSPCB and Nf-kB1 from MR-induced genes. From 40 PCs, two PCs, 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6 and -8.0, and three PCs, 3a, (NR) 4a, and 4c (NS), with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Therapeutic targets identified in this study have a prominent role in numerous cancers. Thus, further investigations such as in vivo and in vitro studies should be carried out to find the molecular functions and interlaying mechanism of the identified therapeutic targets on numerous cancer cell lines in considering the PCs of P . nepalensis.