Reversible Covalent Inhibition─Desired Covalent Adduct Formation by Mass Action.

Covalent inhibition has seen a resurgence in the last several years. Although long-plagued by concerns of off-target effects due to nonspecific reactions leading to covalent adducts, there has been success in developing covalent inhibitors, especially within the field of anticancer therapy. Covalent inhibitors can have an advantage over noncovalent inhibitors since the formation of a covalent adduct may serve as an additional mode of selectivity due to the intrinsic reactivity of the target protein that is absent in many other proteins.

Using the artificial bee colony technique to optimize machine learning algorithms in estimating the mature weight of camels.

This paper aims to predict male and female camels' mature weight (MW) through various morphological traits using hybrid machine learning (ML) algorithms. For this aim, biometrical measurements such as birth weight (BW), length of face (FL), length of the neck (NL), a girth of the heart (HG), body length (BL), withers height (WH), and hind leg length (HLL) were used to estimate the mature weight for eight camel breeds of Pakistan. In this study, multivariate adaptive regression splines (MARS), random forest (RF), and support vector machine (SVM) were applied to develop prediction models.

Physicians' Response and Preparedness of Terrorism-Related Disaster Events in Quetta City, Pakistan: A Qualitative Inquiry.

Background: Besides catastrophes, infrastructural damages, and psychosocial distress, terrorism also imposes an unexpected burden on healthcare services. Considerably, adequately-prepared and responsive healthcare professionals affirms effective management of terrorism-related incidences. Accordingly, the present study aimed to evaluate physicians' preparedness and response toward terrorism-related disaster events in Quetta city, Pakistan.

Preferences for Mobile-Supported e-Cigarette Cessation Interventions Among Young Adults: Qualitative Descriptive Study.

Background: Despite the steady rise in electronic cigarette (e-cigarette) uptake among young adults, increasingly more young people want to quit. Given the popularity of smartphones among young adults, mobile-based e-cigarette cessation interventions hold significant promise. Smartphone apps are particularly promising due to their varied and complex capabilities to engage end users.

Laryngeal Embryonal Rhabdomyosarcoma: A rare adult neoplasm.

The embryonal subtype of rhabdomyosarcoma is the most frequent, commonly seen in children. However, it is uncommon to discover this subtype in adults, especially in the larynx. We presented a rare case of a 63 years old man who presented with worsening hoarseness, dysphagia for solids, and dyspnea and was later diagnosed with embryonal rhabdomyosarcoma of the larynx.

HDL-IDS: A Hybrid Deep Learning Architecture for Intrusion Detection in the Internet of Vehicles.

Internet of Vehicles (IoV) is an application of the Internet of Things (IoT) network that connects smart vehicles to the internet, and vehicles with each other. With the emergence of IoV technology, customers have placed great attention on smart vehicles. However, the rapid growth of IoV has also caused many security and privacy challenges that can lead to fatal accidents.

Profile and Predictors of Maternal Quality of Life During Physiological Pregnancy: A Cross-Sectional Analysis.

Background: Quality of Life (QoL) and its determinants are significant in all stages of life, including pregnancy. The physical and emotional changes during pregnancy affect the QoL of pregnant women, affecting both maternal and infant health. Hence, assessing the QoL of pregnant women is gaining interest in literature.

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions.

The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices generate large amounts of data, and thus IIoT frameworks require intelligent, robust techniques for big data analysis. Artificial intelligence (AI) and deep learning (DL) techniques produce promising results in IIoT networks due to their intelligent learning and processing capabilities.

Modeling and predicting the growth of indigenous Harnai sheep in Pakistan: non-linear functions and MARS algorithm.

Five non-linear functions, i.e. Gompertz, Logistic, Negative exponential, Brody and Bertalanffy, and multivariate adaptive regression splines (MARS) data mining algorithm were implemented with the objective to describe the body weight-age relationship of Harnai sheep of Balochistan, Pakistan.

Nanosilver Mitigates Biofilm Formation via FapC Amyloidosis Inhibition.

Multidrug resistance of bacteria is a major challenge due to the wide-spread use of antibiotics. While a range of strategies have been developed in recent years, suppression of bacterial activity and virulence via their network of extracellular amyloid has rarely been explored, especially with nanomaterials. Here, silver nanoparticles and nanoclusters (AgNPs and AgNCs) capped with cationic branched polyethylenimine polymer are synthesized, and their antimicrobial potentials are determined at concentrations safe to mammalian cells.

Cationic Silver Nanoclusters as Potent Antimicrobials against Multidrug-Resistant Bacteria.

Bacterial multidrug resistance (MDR) is a serious healthcare issue caused by the long-term subtherapeutic clinical treatment of infectious diseases. Nanoscale engineering of metal nanoparticles has great potential to address this issue by tuning the nano-bio interface to target bacteria. Herein, we report the use of branched polyethylenimine-functionalized silver nanoclusters (bPEI-Ag NCs) to selectively kill MDR pathogenic bacteria by combining the antimicrobial activity of silver with the selective toxicity of bPEI toward bacteria.

Evaluation and extension of the two-site, two-step model for binding and activation of the chemokine receptor CCR1.

Interactions between secreted immune proteins called chemokines and their cognate G protein-coupled receptors regulate the trafficking of leukocytes in inflammatory responses. The two-site, two-step model describes these interactions. It involves initial binding of the chemokine N-loop/β3 region to the receptor's N-terminal region and subsequent insertion of the chemokine N-terminal region into the transmembrane helical bundle of the receptor concurrent with receptor activation.

Polymeric nanocapsules embedded with ultra-small silver nanoclusters for synergistic pharmacology and improved oral delivery of Docetaxel.

Despite of the remarkable cytotoxic and imaging potential of ultra-small metal nanoclusters, their toxicity-free and targeted delivery to cancerous cells remains a substantial challenge that hinders their clinical applications. In this study, a polymeric scaffold was first synthesized by grafting folic acid and thiol groups to chitosan (CS) for cancer cell targeting and improved gastric permeation. Furthermore, silver nanocluster (Ag NCs) were synthesized in situ, within CS scaffold by microwave irradiation and core-shell nanocapsules (NCPs) were prepared with hydrophobic docetaxel (DTX) in the core and Ag NCs embedded CS in the shell.

Key determinants of selective binding and activation by the monocyte chemoattractant proteins at the chemokine receptor CCR2.

Chemokines and their receptors collectively orchestrate the trafficking of leukocytes in normal immune function and inflammatory diseases. Different chemokines can induce distinct responses at the same receptor. In comparison to monocyte chemoattractant protein-1 (MCP-1; also known as CCL2), the chemokines MCP-2 (CCL8) and MCP-3 (CCL7) are partial agonists of their shared receptor CCR2, a key regulator of the trafficking of monocytes and macrophages that contribute to the pathology of atherosclerosis, obesity, and type 2 diabetes.

Mechanisms of Regulation of the Chemokine-Receptor Network.

The interactions of chemokines with their G protein-coupled receptors promote the migration of leukocytes during normal immune function and as a key aspect of the inflammatory response to tissue injury or infection. This review summarizes the major cellular and biochemical mechanisms by which the interactions of chemokines with chemokine receptors are regulated, including: selective and competitive binding interactions; genetic polymorphisms; mRNA splice variation; variation of expression, degradation and localization; down-regulation by atypical (decoy) receptors; interactions with cell-surface glycosaminoglycans; post-translational modifications; oligomerization; alternative signaling responses; and binding to natural or pharmacological inhibitors.