Perspectives For Applications Research Articles

Improving selection procedures in health professions education from the applicant perspective: an interview study

IntroductionApplicant perceptions of selection impact motivation and performance during selection, and student diversity. However, in-depth insight into which values underly these perceptions is lacking, creating challenges for aligning selection procedures with applicant perceptions. This qualitative interview study aimed to identify values applicants believe should underlie selection, and how, according to applicants, these values should be used to make specific improvements to selection procedures in undergraduate health professions education (HPE).MethodsThirty-one applicants to five undergraduate HPE programs in the Netherlands participated in semi-structured interviews using Appreciative Inquiry, an approach that focuses on what goes well to create vision for improvement, to guide the interviews. Transcriptions were analyzed using thematic analysis, adopting a constructivist approach.ResultsApplicants’ values related to the aims of selection, the content of selection, and the treatment of applicants. Applicants believed that selection procedures should aim to identify students who best fit the training and profession, and generate diverse student populations to fulfill societal needs. According to applicants, the content of selection should be relevant for the curriculum and profession, assess a comprehensive set of attributes, be of high quality, allow applicants to show who they are, and be adapted to applicants’ current developmental state. Regarding treatment, applicants believed that selection should be a two-way process that fosters reflection on study choice, be transparent about what applicants can expect, safeguard applicants’ well-being, treat all applicants equally, and employ an equitable approach by taking personal circumstances into account. Applicants mentioned specific improvements regarding each value.DiscussionApplicants’ values offer novel insights into what they consider important preconditions for the design of selection procedures. Their suggested improvements can support selection committees in better meeting applicants’ needs.

Da Vinci single-port robotic system current application and future perspective in general surgery: A scoping review.

The da Vinci Single-Port Robot System (DVSP) allows three robotic instruments and an articulated scope to be inserted through a single small incision. It received FDA approval in 2014 and was first introduced in 2018. The aim of this new system was to overcome the limitations of single-incision laparoscopic and robotic surgery. Since then, it has been approved for use only for urologic and transoral surgeries in some countries. It has been used as part of experimental protocols in general surgery. By obtaining the CE mark at the end of January 2024, DVSP will soon enter the European market. This review aims to comprehensively describe the applications of DVSP in general surgery. A search of PubMed, Embase, and Ebsco databases up to March 2024 was conducted, with registration in PROSPERO (CRD42024536430), following the preferred reporting items for Systematic reviews and Meta-analyses for scoping review (PRISMA-Scr) guidelines. All the studies about the use of DVSP in general surgery were included. Fifty-six studies were included. The following surgical areas of use were identified: transabdominal and transanal colorectal, cholecystectomy, abdominal wall repair, upper gastroesophageal tract, liver, pancreas, breast, and thyroid surgery. The reported surgical and short-term outcomes are promising; a wide range of procedures have been performed safely. Some groups have found advantages, such as faster discharge, shorter operative time, and less postoperative pain compared to multiport robotic surgery. Five years after its initial clinical applications, the use of the DVSP in general surgery procedures has demonstrated feasibility and safety. Hernia repair, cholecystectomy, and colorectal surgery emerge as the most frequently conducted interventions with this robotic system. Nevertheless, there is anticipation for further studies with larger sample sizes and extended follow-up periods to provide more comprehensive insights and data on the long-term outcomes, including the incidence of incisional hernia.

Single-cell RNA sequencing in tuberculosis: Application and future perspectives.

Tuberculosis (TB) has one of the highest mortality rates among infectious diseases worldwide. The immune response in the host after infection is proposed to contribute significantly to the progression of TB, but the specific mechanisms involved remain to be elucidated. Single-cell RNA sequencing (scRNA-seq) provides unbiased transcriptome sequencing of large quantities of individual cells, thereby defining biological comprehension of cellular heterogeneity and dynamic transcriptome state of cell populations in the field of immunology and is therefore increasingly applied to lung disease research. Here, we first briefly introduce the concept of scRNA-seq, followed by a summarization on the application of scRNA-seq to TB. Furthermore, we underscore the potential of scRNA-seq for clinical biomarker exploration, host-directed therapy, and precision therapy research in TB and discuss the bottlenecks that need to be overcome for the broad application of scRNA-seq to TB-related research.

Emerging toolkits for decoding the co-occurrence of modified histones and chromatin proteins.

In eukaryotes, DNA is packaged into chromatin with the help of highly conserved histone proteins. Together with DNA-binding proteins, posttranslational modifications (PTMs) on these histones play crucial roles in regulating genome function, cell fate determination, inheritance of acquired traits, cellular states, and diseases. While most studies have focused on individual DNA-binding proteins, chromatin proteins, or histone PTMs in bulk cell populations, suchchromatin features co-occur and potentially act cooperatively to accomplish specific functions in a given cell. This review discusses state-of-the-art techniques for the simultaneous profiling of multiple chromatin features in low-input samples and single cells, focusing on histone PTMs, DNA-binding, and chromatin proteins. We cover the origins of the currently available toolkits, compare and contrast their characteristic features, and discuss challenges and perspectives for future applications. Studying the co-occurrence of histone PTMs, DNA-binding proteins, and chromatin proteins in single cells will be central for a better understanding of the biological relevance of combinatorial chromatin features, their impact on genomic output, and cellular heterogeneity.

Transforming Hospital Quality Improvement Through Harnessing the Power of Artificial Intelligence.

This policy analysis focuses on harnessing the power of artificial intelligence (AI) in hospital quality improvement to transform quality and patient safety. It examines the application of AI at the two following fundamental levels: (1) diagnostic and treatment and (2) clinical operations. AI applications in diagnostics directly impact patient care and safety. At the same time, AI indirectly influences patient safety at the clinical operations level by streamlining (1) operational efficiency, (2) risk assessment, (3) predictive analytics, (4) quality indicators reporting, and (5) staff training and education. The challenges and future perspectives of AI application in healthcare, encompassing technological, ethical, and other considerations, are also critically analyzed.

Novel bamboo-raft-type floating structure (BRT-FS) assembled by FRP reinforced concrete tubes: Conceptual design and analysis

To improve construction efficiency in offshore engineering and extend service life of offshore platforms, a novel bamboo-raft-type floating structure (BRT-FS) assembled by FRP reinforced concrete tubes is proposed. It comprises four fundamental components: concrete tube, carbon fiber-reinforced polymer (CFRP) cable, holding beam, and bellow. This paper presents the structure system and structure design of BRT-FS. Separating load-bearing and buoyant functions ensures structural safety and ease of design. It has broad application perspectives in offshore construction due to its high corrosion resistance, designability, construction efficiency, and low crack control requirement. Furthermore, to obtain the operation conditions of BRT-FS, the mechanical performance is analyzed from two levels, which are hydroelastic analysis and structural analysis. Hydroelastic analysis is conducted under different wave directions, wave periods, water depths, and structural dimensions using a new finite element-boundary element (FE-BE) method. In a specify study case, a sensitive period around 11 s for head sea, around 7 s for oblique wave, around 5 s for beam sea are noted. The hydroelastic response is not significantly affected by water depth or transverse dimension. Structural analysis indicates that the structure can work in clam harbour sea with breakwater protection. Even after concrete tubes crack in higher waves, this new structure can still float with the inside bellows in theory. These preliminary findings confirm the feasibility of this novel structure. Structural details such as tube-tube joints, tube-beam joints, CFRP cable anchorages, and other connections will be further designed and tested in the future.

A Review on Biocontrol Agents as Sustainable Approach for Crop Disease Management: Applications, Production, and Future Perspectives

Horticultural crops are vulnerable to diverse microbial infections, which have a detrimental impact on their growth, fruit quality, and productivity. Currently, chemical pesticides are widely employed to manage diseases in horticultural crops, but they have negative effects on the environment, human health, soil physiochemical properties, and biodiversity. Additionally, the use of pesticides has facilitated the development and spread of resistant pathovars, which have emerged as a serious concern in contemporary agriculture. Nonetheless, the adverse consequences of chemical pesticides on the environment and public health have worried scientists greatly in recent years, which has led to a switch to the use of biocontrol agents such as bacteria, fungi, and insects to control plant pathogens. Biocontrol agents (BCAs) form an integral part of organic farming, which is regarded as the future of sustainable agriculture. Hence, harnessing the potential of BCAs is an important viable strategy to control microbial disease in horticultural crops in a way that is also ecofriendly and can improve the soil health. Here, we discuss the role of the biological control of microbial diseases in crops. We also discuss different microbial-based BCAs such as fungal, bacterial, and viral and their role in disease management. Next, we discuss the factors that affect the performance of the BCAs under field conditions. This review also highlights the genetic engineering of BCAs to enhance their biocontrol efficiency and other growth traits. Finally, we highlight the challenges and opportunities of biocontrol-based disease management in horticulture crops and future research directions to boost their efficacy and applications.

Enhancing Sustainability in Health Tourism through an Ontology-Based Booking Application for Personalized Packages

Currently, health tourists primarily rely on independent facilitators to manage and book their medical appointments and vacation plans. There is a notable absence of dedicated booking applications for health tourism packages. This paper proposes HealthTourismHub, an application designed to provide personalized packages that include medical appointments, accommodation options, and recommended tourism activities. It also serves as a platform for medical experts and accommodation providers, allowing health tourists to discover and connect with them, promoting local resources, and contributing to the sustainable growth of health tourism destinations. To incorporate personalization, HealthTourismHub uses an ontology that organizes medical and tourism data, along with a reasoner that generates new knowledge. This approach enables the application to offer customized packages and identify the most suitable providers for each user. Providers are strategically paired and located in close proximity, encouraging shorter travel distances and more efficient travel planning, with the package also including personalized tourism recommendations that benefit the local economy and contribute to a conscious tourism industry. A survey was conducted to assess the usability of the application and general perspectives towards health tourism, including motivations, concerns, and preferences. The results revealed an above-average SUS score, indicating that users found the application user-friendly and effective. Some areas for improvement were identified, such as error handling and additional functionalities. Nonetheless, HealthTourismHub shows great potential as a pioneer in the field of sustainable health tourism applications.

Neutrophil extracellular traps - an a-list-actor in a variety of diseases.

Neutrophil extracellular traps (NETs) represent a response mechanism in which activated neutrophils release DNA-based webs, adorned with histones and neutrophil proteases, to capture and eliminate invasive microorganisms. However, when these neutrophils become excessively activated, much more proteases associated with NETs are liberated into surrounding tissues or bloodstreams, thereby altering the cellular milieu and causing tissue damage. Recent research has revealed that NETs may play significant roles in the emergence and progression of various diseases, spanning from infections, inflammation to autoimmune disorders and cancers. In this review, we delve deeply into the intricate and complex mechanisms that underlie the formation of NETs and their profound interplay with various clinical pathologies. We aim to describe the application perspectives of NETs related proteins in specific disease diagnosis and treatment.

Isoreticular Metal-Organic Framework-3 (IRMOF-3): From Experimental Preparation, Functionalized Modification to Practical Applications

Isoreticular metal-organic framework-3 (IRMOF-3), a porous coordination polymer, is an MOF material with the characteristics of a large specific surface area and adjustable pore size. Due to the existence of the active amino group (-NH2) on the organic ligand, IRMOF-3 has more extensive research and application potential. Herein, the main preparation methods of IRMOF-3 in existing research were compared and discussed first. Second, we classified and summarized the functionalization modification of IRMOF-3 based on different reaction mechanisms. In addition, the expanded research and progress of IRMOF-3 and their derivatives in catalysis, hydrogen storage, material adsorption and separation, carrier materials, and fluorescence detection were discussed from an application perspective. Moreover, the industrialization prospect of IRMOF-3 and the pressing problems in its practical application were analyzed and prospected. This review is expected to provide a reference for the design and application of more new nanomaterials based on IRMOF-3 to develop more advanced functional materials in industrial production and engineering applications.

A Perspective of Fabrication and Applications of MXene–Metal Hybrids

Abstract2D materials with ultrathin structure, high specific areas, and excellent mechanical properties provide potentials to enhance the electrical, mechanical, and chemical properties of metals. In particular, MXene with different compositions, abundant surface terminations, high electrical conductivity has good affinity with some metals such as Al, Li, Na as well as can be uniformly dispersed in the metals. Moreover, the above unique features enable the MXene–metal hybrids with diversified functions. In this review, the current advanced studies in the topic of MXene–metal hybrids are summarized. The properties of MXenes such as mechanical properties, electrical conductivity, wettability, and surface properties of MXenes are first reviewed. Subsequently, different synthetic approaches including physical, metallurgy, electrochemical, and wet‐chemical routes are screened. By harnessing the above unique features, MXene could enhance the electrical, mechanical, and chemical properties of the hybrids, and their application such as energy storage devices, anticorrosion coating, functional structural materials, electromagnetic wave absorption are highlighted. Finally, an outlook on the in‐operando characterization techniques is provided to clarify the strengthening mechanism of MXenes in metals, tailoration of interface between MXenes and metals, and urgent need for industrial‐scale manufacture of MXene–metal hybrids.

A Case Study of 2D Bi2O2Se Nanoplate Near‐Infrared Photodetectors from the Perspective of Practical Applications

AbstractOver the past several decades infrared (IR) photodetectors have received wide attention due to their important applications. 2D materials, distinguished by their unique electronic structures, ultimate dimensional confinement, and robust light‐matter interactions, provide a promising candidate for fabricating future IR photodetectors. However, there is a lack of reports concerning the practical industrial applications of these 2D photodetectors, despite that some of these 2D photodetectors have demonstrated performance exceeding that of commercial photodetectors. In this work, a case study on 2D Bi2O2Se nanoplate near‐infrared photodetectors from the perspective of practical applications is presented. With the characterization method used for nano detectors, the 2D Bi2O2Se photodetector exhibits a responsivity of 212.5 A W−1, a specific detectivity of 4.99 × 1011 Jones and an external quantum efficiency of 26 887.68% at wavelength of 980 nm, while with the traditional characterization method the photodetector shows a responsivity of 0.13 A W−1 and a specific detectivity of 2.26 × 106 Jones and an external quantum efficiency of 17.87% at wavelength of 900 nm. The Bi2O2Se nanoplate photodetector also presents good passive imaging quality in the near‐infrared wavelength region. These results suggest the great potential of Bi2O2Se nanoplate photodetectors for practical applications.

Chitosan-Based Hydrogels as Antibacterial/Antioxidant/Anti-Inflammation Multifunctional Dressings for Chronic Wound Healing.

Due to repeated microbial infection, persistent inflammation, excessive oxidative stress, and cell dysfunction, chronic wounds are difficult to heal, posing a serious threat to public health. Therefore, developing multifunctional wound dressings that can regulate the complex microenvironment of chronic wounds and enhance cellular function holds great significance. Recently, chitosan has emerged as a promising biopolymer for wound healing due to its excellent biocompatibility, biodegradability, and versatile bioactivity. The aim of this review is to provide a comprehensive understanding of the mechanisms of delayed chronic wound healing and discuss the healing-promoting properties of chitosan and its derivatives, such as good biocompatibility, antibacterial activity, hemostatic capacity, and the ability to promote tissue regeneration. On this basis, the potential applications of chitosan-based hydrogels are summarized in chronic wound healing, including providing a suitable microenvironment, eliminating bacterial infections, promoting hemostasis, inhibiting chronic inflammation, alleviating oxidative stress, and promoting tissue regeneration. In addition, the concerns and perspectives for the clinical application of chitosan-based hydrogels are also discussed.

Coriolopsis trogii MUT3379: A Novel Cell Factory for High-Yield Laccase Production

Coriolopsis trogii is a basidiomycete fungus which utilizes a large array of lignin-modifying enzymes to colonize and decompose dead wood. Its extracellular enzymatic arsenal includes laccases, i.e., polyphenol oxidases of relevant interest for different industrial applications thanks to their ability to oxidize a diverse range of natural and synthetic compounds. In this work, the production of laccases in C. trogii MUT3379 was explored and improved. From an initial production of ca. 10,000 U L−1, the fermentation process was gradually optimized, reaching a final yield of ca. 200,000 U L−1. An SDS-PAGE analysis of the secretome highlighted the presence of a main protein of ca. 60 kDa showing laccase activity, which was designated as Lac3379-1 once its primary sequence was established by tandem mass spectrometry. The characterization of Lac3379-1 revealed a remarkable enzymatic stability in the presence of surfactants and solvents and a diversified activity on a broad range of substrates, positioning it as an interesting tool for diverse biotechnological applications. The high-yield and robust production process indicates C. trogii MUT3379 as a promising cell factory for laccases, offering new perspectives for industrial applications of lignin-modifying enzymes.

Evaluating the performance of spherical, hemispherical, and tubular solar stills with various configurations - A detailed review

Solving global water shortages has become an urgent challenge, hindering sustainable development. Therefore, comparing different solar still designs from application and economic perspectives is necessary. Solar distillation is considered a major innovation in the alternative energy sector for purifying brackish or brine water into clean water. Despite the extensive literature on improved solar stills, determining the most efficient designs for residential and industrial applications remains difficult. This review compares the productivity of spherical, hemispherical, and tubular solar still designs. The aim is to study the factors that influence the efficiency of each type and to analyze recent research and results obtained under different conditions. The results show that innovations in solar distillation design can take many forms to improve efficiency and productivity. For example, adding parabolic mirrors can increase productivity in spherical, hemispherical, and tubular stills by 35 to 70%. Likewise, innovative designs such as rotating spheres and changing bowl shapes significantly increased the productivity of spherical and hemispherical stills. Likewise, retrofitting a still with vacuum generation technology can significantly increase yields by 50 to 70%. In addition, using nanomaterials, especially nanophase change materials (NPCM), has increased the efficiency of the spherical and tubular stills by 116.5%, producing 7.62 kg/m2 per day. Therefore, the NPCM-equipped model was still the most efficient option among the three designs.

Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics.

Data from multiple organizations are crucial for advancing learning health systems. However, ethical, legal, and social concerns may restrict the use of standard statistical methods that rely on pooling data. Although distributed algorithms offer alternatives, they may not always be suitable for health frameworks. This paper aims to support researchers and data custodians in three ways: (1) providing a concise overview of the literature on statistical inference methods for horizontally partitioned data; (2) describing the methods applicable to generalized linear models (GLM) and assessing their underlying distributional assumptions; (3) adapting existing methods to make them fully usable in health settings. A scoping review methodology was employed for the literature mapping, from which methods presenting a methodological framework for GLM analyses with horizontally partitioned data were identified and assessed from the perspective of applicability in health settings. Statistical theory was used to adapt methods and to derive the properties of the resulting estimators. From the review, 41 articles were selected, and six approaches were extracted for conducting standard GLM-based statistical analysis. However, these approaches assumed evenly and identically distributed data across nodes. Consequently, statistical procedures were derived to accommodate uneven node sample sizes and heterogeneous data distributions across nodes. Workflows and detailed algorithms were developed to highlight information-sharing requirements and operational complexity. This paper contributes to the field of health analytics by providing an overview of the methods that can be used with horizontally partitioned data, by adapting these methods to the context of heterogeneous health data and by clarifying the workflows and quantities exchanged by the methods discussed. Further analysis of the confidentiality preserved by these methods is needed to fully understand the risk associated with the sharing of summary statistics.

Optogenetics and Targeted Gene Therapy for Retinal Diseases: Unravelling the Fundamentals, Applications, and Future Perspectives.

With a common aim of restoring physiological function of defective cells, optogenetics and targeted gene therapies have shown great clinical potential and novelty in the branch of personalized medicine and inherited retinal diseases (IRDs). The basis of optogenetics aims to bypass defective photoreceptors by introducing opsins with light-sensing capabilities. In contrast, targeted gene therapies, such as methods based on CRISPR-Cas9 and RNA interference with noncoding RNAs (i.e., microRNA, small interfering RNA, short hairpin RNA), consists of inducing normal gene or protein expression into affected cells. Having partially leveraged the challenges limiting their prompt introduction into the clinical practice (i.e., engineering, cell or tissue delivery capabilities), it is crucial to deepen the fields of knowledge applied to optogenetics and targeted gene therapy. The aim of this in-depth and novel literature review is to explain the fundamentals and applications of optogenetics and targeted gene therapies, while providing decision-making arguments for ophthalmologists. First, we review the biomolecular principles and engineering steps involved in optogenetics and the targeted gene therapies mentioned above by bringing a focus on the specific vectors and molecules for cell signalization. The importance of vector choice and engineering methods are discussed. Second, we summarize the ongoing clinical trials and most recent discoveries for optogenetics and targeted gene therapies for IRDs. Finally, we then discuss the limits and current challenges of each novel therapy. We aim to provide for the first time scientific-based explanations for clinicians to justify the specificity of each therapy for one disease, which can help improve clinical decision-making tasks.

Fungal Proteins: Sources, Production and Purification Methods, Industrial Applications, and Future Perspectives

Fungal Proteins: Sources, Production and Purification Methods, Industrial Applications, and Future Perspectives

Least Squares Estimation of Multifactor Uncertain Differential Equations with Applications to the Stock Market

Multifactor uncertain differential equations are powerful tools for studying dynamic systems under multi-source noise. A key challenge in this study is how to accurately estimate unknown parameters based on the framework of uncertainty theory in multi-source noise environments. To address this core problem, this paper innovatively proposes a least-squares estimation method. The essence of this method lies in constructing statistical invariants with a symmetric uncertainty distribution based on observational data and determining specific parameters by minimizing the distance between the population distribution and the empirical distribution of the statistical invariant. Additionally, two numerical examples are provided to help readers better understand the practical operation and effectiveness of this method. In addition, we also provide a case study of JD.com’s stock prices to illustrate the advantages of the method proposed in this paper, which not only provides a new idea and method for addressing the problem of dynamic system parameter estimation but also provides a new perspective and tool for research and application in related fields.

Transferability and explainability of deep learning emulators for regional climate model projections: Perspectives for future applications

Abstract Regional climate models (RCMs) are essential tools for simulating and studying regional climate variability and change. However, their high computational cost limits the production of comprehensive ensembles of regional climate projections covering multiple scenarios and driving Global Climate Models (GCMs) across regions. RCM emulators based on deep learning models have recently been introduced as a cost-effective and promising alternative that requires only short RCM simulations to train the models. Therefore, evaluating their transferability to different periods, scenarios, and GCMs becomes a pivotal and complex task in which the inherent biases of both GCMs and RCMs play a significant role. Here we focus on this problem by considering the two different emulation approaches introduced in the literature as perfect and imperfect, that we here refer to as Perfect Prognosis (PP) and Model Output Statistics (MOS), respectively, following the well-established downscaling terminology. In addition to standard evaluation techniques, we expand the analysis with methods from the field of eXplainable Artificial Intelligence (XAI), to assess the physical consistency of the empirical links learnt by the models. We find that both approaches are able to emulate certain climatological properties of RCMs for different periods and scenarios (soft transferability), but the consistency of the emulation functions differ between approaches. Whereas PP learns robust and physically meaningful patterns, MOS results are GCM-dependent and lack physical consistency in some cases. Both approaches face problems when transferring the emulation function to other GCMs (hard transferability), due to the existence of GCM-dependent biases. This limits their applicability to build RCM ensembles. We conclude by giving prospects for future applications.