Recent Developments Research Articles

Methodological Considerations on the Use of Cohort Designs in Drug-Drug Interaction Studies in Pharmacoepidemiology

Abstract Purpose of Review The evidence regarding the clinical effects of drug-drug interactions (DDIs) is scarce and limited. Pharmacoepidemiologic studies could help fill in this important knowledge gap. Here, we review the pharmacoepidemiology of DDIs with a focus on cohort designs. We also highlight the decision-making process with respect to different aspects of cohort study design, potential biases that may arise during this decision process, and mitigation strategies. Recent Findings Considering the pharmacologic mechanism of the DDI of interest as well as of the object drug and the precipitant drug separately at the design stage of cohort studies for DDIs will help minimize major biases such as prevalent user bias and confounding by indication. Confounding by indication could also be mitigated by using control precipitants. Further, the correct assignment of the cohort entry date via the application of a time-varying exposure definition can help minimize immortal time bias and prevalent user bias. Minimization of these biases may also potentially be achieved with recently developed tools such as target trial emulation and the prevalent new-user design; however, more research is needed in the area. Summary Careful consideration of the underlying pharmacology and the specifics of study design will help minimize major biases in cohort studies that aim to assess the clinical effects of DDIs. Recent methodological developments from other areas of pharmacoepidemiology could further improve the internal validity of DDI studies.

Editorial: Recent development in energy conversion systems

Editorial: Recent development in energy conversion systems

Growth Processing and Strategies: A Way to Improve the Gas Sensing Performance of Nickel Oxide-Based Devices

The review paper provides a comprehensive analysis of nickel oxide (NiO) as an emerging material in environmental monitoring by surveying recent developments primarily within the last three years and reports the growth processing and strategies employed to enhance NiO sensing performance. It covers synthesis methods for pristine NiO, including vapor-phase, liquid-phase, and solution-processing techniques, highlighting advantages and limitations. The growth mechanisms of NiO nanostructures are explored, with a focus on the most recent research studies. Additionally, different strategies to improve the gas sensing performance of NiO are discussed (i.e., surface functionalization by metallic nanoparticles, heterostructure formation, carbon-based nanomaterials, and conducting polymers). The influence of these strategies on selectivity, sensitivity, response time, and stability of NiO-based sensors is thoroughly examined. Finally, the challenges and future directions that may lead to the successful development of highly efficient NiO-based gas sensors for environmental monitoring are introduced in this review.

DNA Logic Gates Integrated on DNA Substrates in Molecular Computing.

Due to nucleic acid's programmability, it is possible to realize DNA structures with computing functions, and thus a new generation of molecular computers is evolving to solve biological and medical problems. Pioneered by Milan Stojanovic, Boolean DNA logic gates created the foundation for the development of DNA computers. Similar to electronic computers, the field is evolving towards integrating DNA logic gates and circuits by positioning them on substrates to increase circuit density and minimize gate distance and undesired crosstalk. In this minireview, we summarize recent developments in the integration of DNA logic gates into circuits localized on DNA substrates. This approach of all-DNA integrated circuits (DNA ICs) offers the advantages of biocompatibility, increased circuit response, increased circuit density, reduced unit concentration, facilitated circuit isolation, and facilitated cell uptake. DNA ICs can face similar challenges as their equivalent circuits operating in bulk solution (bulk circuits), and new physical challenges inherent in spatial localization. We discuss possible avenues to overcome these obstacles.

Design and Control of the Magnetically Actuated Micro/Nanorobot Swarm toward Biomedical Applications.

Recently, magnetically actuated micro/nanorobots hold extensive promises in biomedical applications due to their advantages of noninvasiveness, fuel-free operation, and programmable nature. While effectively promised in various fields such as targeted delivery, most past investigations are mainly displayed in magnetic control of individual micro/nanorobots. Facing practical medical use, the micro/nanorobots are required for the development of swarm control in a closed-loop control manner. This review outlines the recent developments in magnetic micro/nanorobot swarms, including their actuating fundamentals, designs, controls, and biomedical applications. The fundamental principles and interactions involved in the formation of magnetic micro/nanorobot swarms are discussed first. The recent advances in the design of artificial and biohybrid micro/nanorobot swarms, along with the control devices and methods used for swarm manipulation, are presented. Furthermore, biomedical applications that have the potential to achieve clinical application are introduced, such as imaging-guided therapy, targeted delivery, embolization, and biofilm eradication. By addressing the potential challenges discussed toward the end of this review, magnetic micro/nanorobot swarms hold promise for clinical treatments in the future.

Overview of the population genetics and connectivity of sea turtles in the East Asia Region and their conservation implications

Understanding the current status and recent development of the population genetics and connectivity of sea turtles is crucial for effective conservation management of the species. Five sea turtle species, green turtle (Chelonia mydas), loggerhead turtle (Caretta caretta), hawksbill turtle (Eretmochelys imbricata), olive ridley turtle (Lepidochelys olivacea) and leatherback turtle (Dermochelys coriacea), are recorded in the East Asia Region situated in the western side of the North Pacific Ocean. We compiled information from 35 published genetic studies on the five sea turtle species, with a focus on green turtle and loggerhead turtle, which are the most studied species (in 30 studies) in view of their commonness and occurrence of nesting populations. We provided an overview of the key methods and findings of these previous studies, addressing two main objectives on genetic structure of the rookeries and their differences compared to other populations, and connectivity of the rookeries and foraging aggregations. By identifying information gaps and conservation needs, we discussed future developments for sea turtle genetic studies and conservation implications in the region.

Anti-Calcitonin Gene-Related Peptide Monoclonal Antibodies in Migraine: Focus on Drug Interactions.

Calcitonin gene-related peptide neurotransmission was the target for recent development of monoclonal antibodies that effectively prevent attacks of both episodic and chronic migraine. The aim of this narrative review was to offer deeper insight into drug-drug, drug-food and drug-disease interactions of monoclonal antibodies approved for prevention of migraine attacks. For this narrative review, relevant literature was searched for in MEDLINE and Google Scholar databases, covering the 1966-2023 and 2006-2023 periods, respectively. The ClinicalTrials.gov database was also searched for relevant clinical studies whose results had not been published previously in medical journals, covering 2000-2023. Monoclonal antibodies (erenumab, fremanezumab, galcanezumab and eptinezumab) augment prophylactic action of gepants and onabotulinumtoxin A and somewhat increase efficacy of triptans used to abort migraine attacks; however, their adverse reactions may also be augmented. Pharmacokinetic interactions and interactions in general with drugs used for other indications except migraine are negligible, as are drug-food interactions. However, monoclonal antibodies may worsen diseases with already weakened CGRP neurotransmission, Raynaud phenomenon and constipation. Monoclonal antibodies used for prevention of migraine do not engage in significant pharmacokinetic interactions with other drugs; however, they do engage in pharmacodynamic interactions with other anti-migraine drugs, additively augmenting their prophylactic action, but also increasing frequency and severity of adverse reactions, which are a consequence of the CGRP neurotransmission interruption.

Highly Conductive Imidazolate Covalent Organic Frameworks with Ether Chains as Solid Electrolytes for Lithium Metal Batteries.

Poly(ethylene oxide) (PEO)-based electrolytes are often used for Li+ conduction as they can dissociate the Li salts efficiently. However, high entanglement of the chains and lack of pathways for rapid ion diffusion limit their applications in advanced batteries. Recent developments in ionic covalent organic frameworks (iCOFs) showed that their highly ordered structures provide efficient pathways for Li+ transport, solving the limitations of traditional PEO-based electrolytes. Here, we present imidazolate COFs, PI-TMEFB-COFs, having methoxyethoxy chains, synthesized by Debus-Radziszewski multicomponent reactions and their ionized form, Li+ @PI-TMEFB-COFs, showing a high Li+ conductivity of 8.81 mS cm-1 and a transference number of 0.974. The mechanism for such excellent electrochemical properties is that methoxyethoxy chains dissociate LiClO4 , making free Li+ , then those Li+ are transported through the imidazolate COFs' pores. The synthesized Li+ @PI-TMEFB-COFs formed a stable interface with Li metal. Thus, employing Li+ @PI-TMEFB-COFs as the solid electrolyte to assemble LiFePO4 batteries showed an initial discharge capacity of 119.2 mAh g-1 at 0.5 C, and 82.0 % capacity and 99.9 % Coulombic efficiency were maintained after 400 cycles. These results show that iCOFs with ether chains synthesized via multicomponent reactions can create a new chapter for making solid electrolytes for advanced rechargeable batteries.

Space partitioning within groups of social coral reef fish

AbstractSite-attached fish that form social groups may face a trade-off between the advantages of group living and the disadvantages related to intra-group competition for food. A possible solution for the latter is space partitioning among group members. Technological limitations related to individual tagging and underwater tracking hindered such spatial studies in grouping fishes. Here, using underwater video cameras and recent developments in deep learning tools, we successfully tracked the 3D movements of individually tagged fish in 4 groups of the damselfish Dascyllus marginatus in the coral reef of Eilat, Red Sea. Our findings, based on tracking sessions lasting 3–11 min that were recorded during a period of > 1 month, show that the individual fish kept separate foraging spaces with minimal overlap and that this separation was stable in time. When the tidally driven current reversed, the separation was kept, and a corresponding reversal was found in the positions of each fish relative to the coral and its neighbors. We propose that the stable spatial partitioning observed in our study is a primary mechanism through which site-attached species can organize themselves in order to reduce intra-group competition.

A Slicing‐Free Perspective to Sufficient Dimension Reduction: Selective Review and Recent Developments

SummarySince the pioneering work of sliced inverse regression, sufficient dimension reduction has been growing into a mature field in statistics and it has broad applications to regression diagnostics, data visualisation, image processing and machine learning. In this paper, we provide a review of several popular inverse regression methods, including sliced inverse regression (SIR) method and principal hessian directions (PHD) method. In addition, we adopt a conditional characteristic function approach and develop a new class of slicing‐free methods, which are parallel to the classical SIR and PHD, and are named weighted inverse regression ensemble (WIRE) and weighted PHD (WPHD), respectively. Relationship with recently developed martingale difference divergence matrix is also revealed. Numerical studies and a real data example show that the proposed slicing‐free alternatives have superior performance than SIR and PHD.

Highly Conductive Imidazolate Covalent Organic Frameworks with Ether Chains as Solid Electrolytes for Lithium Metal Batteries

AbstractPoly(ethylene oxide) (PEO)‐based electrolytes are often used for Li+ conduction as they can dissociate the Li salts efficiently. However, high entanglement of the chains and lack of pathways for rapid ion diffusion limit their applications in advanced batteries. Recent developments in ionic covalent organic frameworks (iCOFs) showed that their highly ordered structures provide efficient pathways for Li+ transport, solving the limitations of traditional PEO‐based electrolytes. Here, we present imidazolate COFs, PI‐TMEFB‐COFs, having methoxyethoxy chains, synthesized by Debus–Radziszewski multicomponent reactions and their ionized form, Li+@PI‐TMEFB‐COFs, showing a high Li+ conductivity of 8.81 mS cm−1 and a transference number of 0.974. The mechanism for such excellent electrochemical properties is that methoxyethoxy chains dissociate LiClO4, making free Li+, then those Li+ are transported through the imidazolate COFs’ pores. The synthesized Li+@PI‐TMEFB‐COFs formed a stable interface with Li metal. Thus, employing Li+@PI‐TMEFB‐COFs as the solid electrolyte to assemble LiFePO4 batteries showed an initial discharge capacity of 119.2 mAh g−1 at 0.5 C, and 82.0 % capacity and 99.9 % Coulombic efficiency were maintained after 400 cycles. These results show that iCOFs with ether chains synthesized via multicomponent reactions can create a new chapter for making solid electrolytes for advanced rechargeable batteries.

Artificial neural network (ANN) modelling to estimate bubble size from macroscopic image and object features

Bubble size measurements in aerated systems such as froth flotation cells are critical for controlling gas dispersion. Commonly, bubbles are measured by obtaining representative photographs, which are then analyzed using segmentation and identification software tools. Recent developments have focused on enhancing these segmentation tools. However, the main challenges around complex bubble cluster segmentation remain unresolved, while the tools to tackle these challenges have become increasingly complex and computationally expensive. In this work, we propose an alternative solution, circumventing the need for image segmentation and bubble identification. An Artificial Neural Network (ANN) was trained to estimate the Sauter mean bubble size (D<sub>32</sub>) based on macroscopic image features obtained with simple and inexpensive image analysis. The results showed excellent prediction accuracy, with a correlation coefficient, R, over 0.998 in the testing stage, and without bias in its error distribution. This machine learning tool paves the way for robust and fast estimation of bubble size under complex bubble images, without the need of image segmentation.

A Review and Comparative Study of Works that Care is Monitoring Detection and Therapy of Children with Autism Spectrum Disorder

Recognizing human activity from video sequences and sensor data is one of the major challenges in human-computer interaction and computer vision. Health care is a rapidly developing field of technology and services. The latest development in this field is remote patient monitoring, which has many advantages in a rapidly evolving world. With relatively simple applications for monitoring patients within hospital rooms, technology has advanced to the point where a patient can be allowed to carry out normal daily activities at home while still being monitored using modern communication technologies and sensors. These new technologies can monitor patients based on their disease or condition. The technology varies from sensors attached to the body to peripheral sensors connected to the environment, and innovations show contactless monitoring that only requires the patient to be within a few meters of the sensor. Nowadays, the Internet of Things, wearable devices, mobile technologies, and improved communication and computing capabilities have given rise to innovative mobile health solutions, and several research efforts have recently been made in the field of autism spectrum disorders (ASD). This technology may be particularly useful for some rapidly changing emotional states, especially people with ASD. Children with ASD have some disturbing activities, and usually cannot speak fluently. Instead, they use signs and words to establish rapport, so understanding their needs is one of the most challenging tasks for healthcare providers, but monitoring the disease can make it much easier. We study in this work more than 50 collected articles that have made a significant contribution to the field were selected. Indeed, the current paper reviews the literature to identify current trends, expectations, and potential gaps related to the latest portable, smart, and wearable technologies in the field of ASD. This study also provides a review of recent developments in health care and monitoring of people with autism.

Reflections on Sikh Dharma at Fifty

ABSTRACT Our panel on Sikh Dharma at Fifty, organized for the May 2023 Sikh studies conference at the University of California-Riverside, allowed me to update what I have previously written on 3HO/Sikh Dharma in light of recent developments affecting the organization. Here I reflect further upon (1) the internal evolution of Sikh Dharma and the self-identities of its followers, (2) the impact of Sikh Dharma – both the organization and its followers – on other Sikhs and Sikhi in North America, and (3) ways in which Sikh studies scholars have written about 3HO/Sikh Dharma positioning for the wider Sikh Panth.

Ground air pollutants explanation based on multiple visibility graph of complex network by temporal community division.

In air pollution studies, the correlation analysis of environmental variables has usually been challenged by parametric diversity. Such variable variations are not only from the extrinsic meteorological conditions and industrial activities but also from the interactive influences between the multiple parameters. A promising solution has been motivated by the recent development of visibility graph (VG) on multi-variable data analysis, especially for the characterization of pollutants' correlation in the temporal domain, the multiple visibility graph (MVG) for nonlinear multivariate time series analysis has been verified effectively in different realistic scenarios. To comprehensively study the correlation between pollutant data and season, in this work, we propose a multi-layer complex network with a community division strategy based on the joint analysis of the atmospheric pollutants. Compared to the single-layer-based complex networks, our proposed method can integrate multiple different atmospheric pollutants for analysis, and combine them with multivariate time series data to obtain higher temporary community division for ground air pollutants interpretation. Substantial experiments have shown that this method effectively utilizes air pollution data from multiple representative indicators. By mining community information in the data, it successfully achieves reasonable and strong interpretive analysis of air pollution data.

Unveiling Nanogranular Advancements in Nickel-Doped Tungsten Oxide for Superior Electrochromic Performance

Electrochromic materials allow for precise control of their optical properties by applying an electric field, which has led to recent developments in energy-saving and indoor temperature control systems like smart windows. The selective incorporation of metal dopants is an effective technique for generating highly advanced semiconducting metal oxides with precisely customized physicochemical characteristics. In this report, we employed a one-step electrodeposition process to fabricate nickel-doped tungsten oxide (W–Ni) thin films, systematically probing the impact of nickel (Ni) doping on the collective material characteristics. Comprehensive X-ray diffraction research revealed significant changes in diffraction patterns, suggesting slight modifications in the structure caused by Ni doping. The scanning electron microscopy showed complex differences in the microstructure of the film, such as a dense surface, porosity, and clustering of nanogranules. The WNi-3% thin film doped at 3 wt. % exhibited excellent electrochromic performance by efficiently handling lithium ions and displaying favorable electrochromic properties. The improved electrode, WNi-3%, showed a maximum optical modulation of 81.90%, exceptional reversibility of 99.4%, and a high coloration efficiency of 75.12 cm2/C. These findings underscore the efficacy of Ni-doping in tailoring the electrochromic properties of nickel-doped tungsten oxide thin films, thereby advancing the frontiers of high-performance electrochromic materials for energy-efficient applications.

“On the Side of the Good”: Political Alliances of Religious Zionists and Israeli Conservatism in the Quest to Hegemony

This article discusses the recent political alliance between IC and the “Hardal” (acronym for Haredi-Dati-Leumi, meaning Ultra-Orthodox-Religious-Zionists) followers of Rabbi Zvi Thau. This new cooperation is surprising, due to Thau’s tendency to criticize groups that do not adhere to his strict interpretation of Judaism. In this article we analyze the recent developments within Thau’s circle, and determine that this cooperation is a consequence of a unique interpretation of a spiritual state of emergency. We conclude by analyzing the circumstances in which IC was formed, as a lesson religious Zionists took from the 2005 disengagement from Gaza plan. The article demonstrates that IC intentionally intended to enable the creation of this sort of political alliance.

New functions and roles of the Na+-H+-exchanger NHE3.

The sodium/proton exchanger isoform 3 (NHE3) is expressed in the intestine and the kidney, where it contributes to hydrogen secretion and sodium (re)absorption. The roles of this transporter have been studied by the use of the respective knockout mice and by using pharmacological inhibitors. Whole-body NHE3 knockout mice suffer from a high mortality rate (with only ∼30% of mice surviving into adulthood), and based on the expression of NHE3 in both intestine and kidney, some conclusions that were originally derived were based on this rather complex phenotype. In the last decade, more refined models have been developed that added temporal and spatial control of NHE3 expression. For example, novel mouse models have been developed with a knockout of NHE3 in intestinal epithelial cells, tubule/collecting duct of the kidney, proximal tubule of the kidney, and thick ascending limb of the kidney. These refined models have significantly contributed to our understanding of the role of NHE3 in a tissue/cell type-specific manner. In addition, tenapanor was developed, which is a non-absorbable, intestine-specific NHE3 inhibitor. In rat and human studies, tenapanor lowered intestinal Pi uptake and was effective in lowering plasma Pi levels in patients on hemodialysis. Of note, diarrhea is seen as a side effect of tenapanor (with its indication for the treatment of constipation) and in intestine-specific NHE3 knockout mice; however, effects on plasma Pi were not supported by this mouse model which showed enhanced and not reduced intestinal Pi uptake. Further studies indicated that the gut microbiome in mice lacking intestinal NHE3 resembles an intestinal environment favoring the competitive advantage of inflammophilic over anti-inflammatory species, something similar seen in patients with inflammatory bowel disease. This review will highlight recent developments and summarize newly gained insight from these refined models.

Polar low research: recent developments and promising courses of research

Polar lows (PLs) are intense maritime mesoscale weather systems that develop during marine cold air outbreaks at high latitudes. The objective of this review is to describe the advances in polar low research since the last literature review—published 3 years ago—, indicate the knowledge gaps that remain, and suggest promising courses of research. Among the breakthroughs identified here are the first climatology of PLs obtained with a global atmospheric model, and increased evidence showing that baroclinic instability is the main mechanism leading to PL development. Despite these advances, many challenges persist such as the lack of conventional observations of PLs and the need to better understand coupled atmosphere-ocean processes involved in PL development. With the rapid advances in deep learning, this method has the potential to be used for PL forecasting.

Advancements in Serum Biomarkers for Early Diagnosis and Prognostic Assessment of Aortic Dissection.

Aortic dissection (AD) is a potentially fatal cardiovascular issue that needs to be diagnosed and treated very away. While early detection is essential for bettering patient outcomes, there are substantial obstacles with the diagnostic techniques used today. Promising pathways for improving AD prognosis evaluation and early detection are presented by recent developments in serum biomarkers. The most recent research on serum biomarkers for AD is reviewed here, with an emphasis on the prognostic and diagnostic utility of these indicators. A number of biomarkers, including as matrix metalloproteinases, soluble elastin fragments, smooth muscle myosin heavy chain, and D-dimer, have been identified as putative markers of AD. These indicators are indicative of multiple pathophysiological mechanisms associated with AD, including inflammation, extracellular matrix remodeling, and vascular damage. Research has indicated that they are useful in differentiating AD from other acute cardiovascular diseases, facilitating prompt diagnosis and risk assessment.