RESUMEN
Federated learning (FL) has become a popular mode of learning, allowing model training without the need to share data. Unfortunately, it remains vulnerable to privacy leakage and poisoning attacks, which compromise user data security and degrade model quality. Therefore, numerous privacy-preserving frameworks have been proposed, among which mask-based framework has certain advantages in terms of efficiency and functionality. However, it is more susceptible to poisoning attacks from malicious users, and current works lack practical means to detect such attacks within this framework. To overcome this challenge, we present DefendFL, an efficient, privacy-preserving, and poisoning-detectable mask-based FL scheme. We first leverage collinearity mask to protect users' gradient privacy. Then, cosine similarity is utilized to detect masked gradients to identify poisonous gradients. Meanwhile, a verification mechanism is designed to detect the mask, ensuring the mask's validity in aggregation and preventing poisoning attacks by intentionally changing the mask. Finally, we resist poisoning attacks by removing malicious gradients or lowering their weights in aggregation. Through security analysis and experimental evaluation, DefendFL can effectively detect and mitigate poisoning attacks while outperforming existing privacy-preserving detection works in efficiency.
RESUMEN
Ginkgo biloba is abundant in secondary metabolites, including flavonoids and terpenoids. While the majority of research has focused on the role of these compounds in disease resistance, their specific contribution to pathogen defense has been rarely explored. In this study, we collected root exudates from hydroponically cultivated ginkgo seedlings and conducted a metabolomic analysis. We identified several primary metabolites mainly comprising amino acids and nucleotides, while secondary metabolites consisted of various compounds, including bioactive compounds such as flavonoids and terpenoids. Focusing on the secondary metabolites with relatively higher abundance in the exudates, we selected a mixture of flavonoids and terpenoids for in vitro inhibition experiments against two soil-borne fungal pathogens, Fusarium oxysporum f. sp. cucumerinum that causes cucumber wilt and Rhizoctonia solani AG-8 that causes wheat root rot. The results indicated that the growth rate of both fungus cells was significantly reduced with the increasing concentration of the flavonoid and terpenoid mixture extracted from ginkgo and was completely inhibited at a concentration of 5 mg/mL. Further experiments revealed that this mixture of flavonoids and terpenoids had a destructive effect on the cellular structure of both fungi, thereby reducing cell viability and achieving an antifungal effect. These findings provide a foundation for further research into the use of ginkgo extracts in biological control.
RESUMEN
Ficus carica is an economically important horticultural plant. Due to its abundant secondary metabolites, F. carica has gained interest for its applications in medicine and as a nutritional supplement. Both external and internal factors affect the accumulation of secondary metabolites in F. carica. The assembly of the F. carica genome has facilitated functional analysis of key genes and transcription factors associated with the biosynthesis of secondary metabolites, particularly anthocyanin. In this review, we summarize the various types and functions of secondary metabolites, with a particular focus on flavonoids, coumarins, and terpenes. We also explore the factors influencing their biosynthesis and accumulation, including varieties, tissue, environmental factors (e.g., light), stresses (e.g., high temperature, low temperature, drought, nutrient deficiencies, salinity), hormonal treatments, and developmental factors. Furthermore, we discuss the involvement of structural genes and transcription factors in the biosynthesis of secondary metabolites, specifically anthocyanin and furanocoumarins, knowledge of which will promote the breeding and genetic engineering of novel F. carica varieties.
RESUMEN
Although hierarchically porous zeolitic imidazolate frameworks (HPZIFs) not only inherit the intrinsic architectural and chemical stabilities of their microporous counterparts but also afford open space for the efficient mass diffusion of the macromolecules involved, their rational design and construction are still challenging. Herein, HPZIFs with tailorable pore sizes ranging from 18 to 54 nm were successfully fabricated by using a newly developed soft-template-directed strategy. Our success rooted in the fact that the screened PS81-PVP44-PEO113 triblock copolymer could effectively coordinate with the metal precursor for the directed crystallization of ZIFs along surfactant assemblies. The advantages of continuous large pores and open structures in such HPZIFs were fully taken into account to serve as a bioreactor for the efficient immunoassay. The expanded large pores provided not only a significantly vast surface area to enhance the density of capture antibodies but also enough space for accommodating multiple conjugated biomolecules in one pore channel. In combination with a cascade enzyme cycle amplification strategy, a model biomarker of prostate-specific antigen (PSA) at the femtomolar level was checked with a limit of detection of 92 fM using the developed immunosensor. Specific screening on patients with prostate cancer or even benign prostatic hyperplasia was exemplified through accurately quantifying small changes of PSA concentration in clinical serum samples, prefiguring the great potential of the developed HPZIF-8 immunosensor platform for the early monitoring and diagnostics of diseases.
Asunto(s)
Imidazoles , Antígeno Prostático Específico , Zeolitas , Zeolitas/química , Inmunoensayo/métodos , Porosidad , Imidazoles/química , Humanos , Antígeno Prostático Específico/sangre , Estructuras Metalorgánicas/química , Estructuras Metalorgánicas/síntesis química , Técnicas Biosensibles/métodos , Límite de DetecciónRESUMEN
Alloy-type materials are attractive for anodes in sodium-ion batteries (SIBs) owing to their high theoretical capacities and overall performance. However, the accumulation of stress/strain during repeated cycling results in electrode pulverization, leading to rapid capacity decay and eventual disintegration, thus hindering their practical applications. Herein, we report a 3D coral-like Sb-Cu alloy nanoarray with gradient distribution of both elements. The array features a Sb-rich bottom and a Cu-rich top with increasing Sb and decreasing Cu concentrations from top to bottom. The former is the active component that provides the high capacity, whereas the latter serves as an inert additive that acts against volume variation. The gradual transition in composition within the electrode introduces a ladder-type volume expansion effect, facilitating a smooth distribution and effective release of stress, thereby ensuring the wanted mechanical stability and structural integrity. The as-developed nanoarray affords a high reversible capacity (460 mAh g-1 at 0.5 C), stable cycling (89% retention over 120 cycles at 1.0 C), and superior rate capability (354 mAh g-1 at 10 C). The concentration dual-gradient strategy paves a new pathway of designing alloy-type materials for SIBs.
RESUMEN
Various hazardous volatile organic compounds (VOCs) are frequently released into environments during accidental events that cause many hazards to ecosystems and humans. Therefore, rapid, sensitive, and on-site detection of hazardous VOCs is crucial to understand their compositions, characteristics, and distributions in complex environments. However, manual handling of hazardous VOCs remains a challenging task, because of the inaccessible environments and health risk. In this work, we designed a quadruped robotic sampler to reach different complex environments for capturing trace hazardous VOCs using a needle trap device (NTD) by remote manipulation. The captured samples were rapidly identified by portable mass spectrometry (MS) within minutes. Rapid detection of various hazardous VOCs including toxicants, chemical warfare agents, and burning materials from different environments was successfully achieved using this robot-MS system. On-site detection of 83 typical hazardous VOCs was examined. Acceptable analytical performances including low detection limits (at subng/mL level), good reproducibility (relative standard deviation (RSD) < 20%, n = 6), excellent quantitative ability (R2 > 0.99), and detection speed (within minutes) were also obtained. Our results show that the robot-MS system has excellent performance including safety, controllability, applicability, and robustness under dangerous chemical conditions.
Asunto(s)
Espectrometría de Masas , Robótica , Compuestos Orgánicos Volátiles , Compuestos Orgánicos Volátiles/análisis , Espectrometría de Masas/métodos , Sustancias Peligrosas/análisis , Sustancias Peligrosas/aislamiento & purificación , Monitoreo del Ambiente/métodos , Monitoreo del Ambiente/instrumentación , Límite de DetecciónRESUMEN
OBJECTIVE: The purpose was to explore the effects of traditional and non-traditional lipid parameters on Sudden Sensorineural Hearing Loss (SSNHL). METHODS: The study included 452 patients diagnosed with SSNHL, among whom 206 patients had a level of hearing improvement ≥10â¯dB after one month of follow-up. A propensity score-matched (2:1) control group was used. Conditional and unconditional logistic regression were used to analyze the risk factors for SSNHL. RESULTS: Patients with SSNHL had a higher risk of concomitant hypertension and elevated atherosclerogenic lipid levels, with apolipoprotein B and apolipoprotein E identified as independent risk factors for the onset of SSNHL. Additionally, the Lipid Comprehensive Index (LCI) was an independent risk factor for the degree of hearing loss. A positive linear correlation was revealed between triglyceride, non-high-density lipoprotein cholesterol, atherogenic index, Castelli risk index, atherogenic index of plasma, LCI and hearing loss. However, no linear relationship was observed between hearing gain and any lipid parameters. When Total Cholesterol (TC) was in the range of borderline high, the treatment effect was the best. However, the statistical significance disappeared upon adjusting for confounding factors. CONCLUSION: Patients with SSNHL exhibited markedly dysregulated lipid metabolism. Elevated serum lipid levels may be a causative factor in auditory impairment and can influence the extent of hearing loss. Promptly improving cochlear microcirculation may benefit patients with borderline elevated TC.
Asunto(s)
Pérdida Auditiva Sensorineural , Pérdida Auditiva Súbita , Lípidos , Humanos , Masculino , Factores de Riesgo , Femenino , Pérdida Auditiva Súbita/sangre , Pérdida Auditiva Súbita/etiología , Pérdida Auditiva Sensorineural/sangre , Pérdida Auditiva Sensorineural/etiología , Persona de Mediana Edad , Lípidos/sangre , Adulto , Anciano , Estudios de Casos y Controles , Puntaje de Propensión , Metabolismo de los LípidosRESUMEN
Single Atoms Catalysts (SACs) have emerged as a class of highly promising heterogeneous catalysts, where the traditional bottom-up synthesis approaches often encounter considerable challenges in relation to aggregation issues and poor stability. Consequently, achieving densely dispersed atomic species in a reliable and efficient manner remains a key focus in the field. Herein, we report a new facile electrochemical knock-down strategy for the formation of SACs, whereby the metal Zn clusters are transformed into single atoms. While a defect-rich substrate plays a pivotal role in capturing and stabilizing isolated Zn atoms, the feasibility of this novel strategy is demonstrated through a comprehensive investigation, combining experimental and theoretical studies. Furthermore, when studied in exploring for potential applications, the material prepared shows a remarkable improvement of 58.21% for the Li+ storage and delivers a capacity over 300 Wh kg-1 after 500 cycles upon the transformation of Zn clusters into single atoms.
RESUMEN
Metal-organic framework (MOF) and covalent organic framework (COF) are a huge group of advanced porous materials exhibiting attractive and tunable microstructural features, such as large surface area, tunable pore size, and functional surfaces, which have significant values in various application areas. The emerging 3D printing technology further provides MOF and COFs (M/COFs) with higher designability of their macrostructure and demonstrates large achievements in their performance by shaping them into advanced 3D monoliths. However, the currently available 3D printing M/COFs strategy faces a major challenge of severe destruction of M/COFs' microstructural features, both during and after 3D printing. It is envisioned that preserving the microstructure of M/COFs in the 3D-printed monolith will bring a great improvement to the related applications. In this overview, the 3D-printed M/COFs are categorized into M/COF-mixed monoliths and M/COF-covered monoliths. Their differences in the properties, applications, and current research states are discussed. The up-to-date advancements in paste/scaffold composition and printing/covering methods to preserve the superior M/COF microstructure during 3D printing are further discussed for the two types of 3D-printed M/COF. Throughout the analysis of the current states of 3D-printed M/COFs, the expected future research direction to achieve a highly preserved microstructure in the 3D monolith is proposed.
RESUMEN
Microbial cell factories, renowned for their economic and environmental benefits, have emerged as a key trend in academic and industrial areas, particularly in the fermentation of natural compounds. Among these, plant-derived terpenes stand out as a significant class of bioactive natural products. The large-scale production of such terpenes, exemplified by artemisinic acid-a crucial precursor to artemisinin-is now feasible through microbial cell factories. In the fermentation of terpenes, two-phase fermentation technology has been widely applied due to its unique advantages. It facilitates in situ product extraction or adsorption, effectively mitigating the detrimental impact of product accumulation on microbial cells, thereby significantly bolstering the efficiency of microbial production of plant-derived terpenes. This paper reviews the latest developments in two-phase fermentation system applications, focusing on microbial fermentation of plant-derived terpenes. It also discusses the mechanisms influencing microbial biosynthesis of terpenes. Moreover, we introduce some new two-phase fermentation techniques, currently unexplored in terpene fermentation, with the aim of providing more thoughts and explorations on the future applications of two-phase fermentation technology. Lastly, we discuss several challenges in the industrial application of two-phase fermentation systems, especially in downstream processing.
Asunto(s)
Productos Biológicos , Terpenos , FermentaciónRESUMEN
Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer an elegant way to handle combinatorial optimization problems (COPs). However, limited by expertise and resources, most users lack the capability to implement EAs for solving COPs. An intuitive and promising solution is to outsource evolutionary operations to a cloud server, however, it poses privacy concerns. To this end, this article proposes a novel computing paradigm called evolutionary computation as a service (ECaaS), where a cloud server renders evolutionary computation services for users while ensuring their privacy. Following the concept of ECaaS, this article presents privacy-preserving genetic algorithm (PEGA), a privacy-preserving GA designed specifically for COPs. PEGA enables users, regardless of their domain expertise or resource availability, to outsource COPs to the cloud server that holds a competitive GA and approximates the optimal solution while safeguarding privacy. Notably, PEGA features the following characteristics. First, PEGA empowers users without domain expertise or sufficient resources to solve COPs effectively. Second, PEGA protects the privacy of users by preventing the leakage of optimization problem details. Third, PEGA performs comparably to the conventional GA when approximating the optimal solution. To realize its functionality, we implement PEGA falling in a twin-server architecture and evaluate it on two widely known COPs: 1) the traveling Salesman problem (TSP) and 2) the 0/1 knapsack problem (KP). Particularly, we utilize encryption cryptography to protect users' privacy and carefully design a suite of secure computing protocols to support evolutionary operators of GA on encrypted chromosomes. Privacy analysis demonstrates that PEGA successfully preserves the confidentiality of COP contents. Experimental evaluation results on several TSP datasets and KP datasets reveal that PEGA performs equivalently to the conventional GA in approximating the optimal solution.
RESUMEN
As cost-effective catalysts, platinum (Pt) single-atom catalysts (SACs) have attracted substantial attention. However, most studies indicate that Pt SACs in acidic hydrogen evolution reaction (HER) follow the slow Volmer-Heyrovsky (VH) mechanism instead of the fast kinetic Volmer-Tafel (VT) pathway. Here, this work propose that the VH mechanism in Pt SACs can be switched to the faster VT pathway for efficient HER by correlating Pt single atoms (SAs) with Pt clusters (Cs). Our calculations reveal that the correlation between Pt SAs and Cs significantly impacts the electronic structure of exposed Pt atoms, lowering the adsorption barrier for atomic hydrogen and enabling a faster VT mechanism. To validate these findings, this work purposely synthesize three catalysts: l-Pt@MoS2, m-Pt@MoS2 and h-Pt@MoS2 with low, moderate, and high Pt-loading, having different distributions of Pt SAs and Cs. The m-Pt@MoS2 catalyst with properly correlating Pt SAs and Cs exhibits outstanding performance with an overpotential of 47 mV and Tafel slope of 32 mV dec-1. Further analysis of the Tafel values confirms that the m-Pt@MoS2 sample indeed follows the VT reaction mechanism, aligning with the theoretical findings. This study offers a deep understanding of the synergistic mechanism, paving a way for designing novel-advanced catalysts.
RESUMEN
Efficient catalyst design is crucial for addressing the sluggish multi-step sulfur redox reaction (SRR) in lithium-sulfur batteries (LiSBs), which are among the promising candidates for the next-generation high-energy-density storage systems. However, the limited understanding of the underlying catalytic kinetic mechanisms and the lack of precise control over catalyst structures pose challenges in designing highly efficient catalysts, which hinder the LiSBs' practical application. Here, drawing inspiration from the theoretical calculations, the concept of precisely controlled pre-lithiation SRR electrocatalysts is proposed. The dual roles of channel and surface lithium in pre-lithiated 1T'-MoS2 are revealed, referred to as the "electronic modulation effect" and "drifting effect", respectively, both of which contribute to accelerating the SRR kinetics. As a result, the thus-designed 1T'-Lix MoS2 /CS cathode obtained by epitaxial growth of pre-lithiated 1T'-MoS2 on cubic Co9 S8 exhibits impressive performance with a high initial specific capacity of 1049.8 mAh g-1 , excellent rate-capability, and remarkable long-term cycling stability with a decay rate of only 0.019% per cycle over 1000 cycles at 3 C. This work highlights the importance of precise control in pre-lithiation parameters and the synergistic effects of channel and surface lithium, providing new valuable insights into the design and optimization of SRR electrocatalysts for high-performance LiSBs.
RESUMEN
A rational design of sulfur host is the key to conquering the"polysulfide shuttle effects" by accelerating the polysulfide conversion. Since the process involves solid-liquid-solid multistep phase transitions, purposely-engineered heterostructure catalysts with various active regions for catalyzing conversion steps correspondingly are beneficial to promote the overall conversion process. However, the functionalities of the materials surface and interface in heterostructure catalysts remain unclear. In this work, an Mo2C/MoC catalyst with abundant Mo2C surface-interface-MoC surface tri-active-region is developed by in situ converting the MoZn-metal organic framework. The experimental and simulation studies demonstrate the interface can catch long-chain polysulfides and promote their conversion. Instead, the Mo2C and MoC tend to accommodate the short-chain polysulfide and accelerate their conversion and the Li2S dissociation. Benefitting from the high catalytic ability, the Li-S battery assembled with the Mo2C/MoC-S cathode shows more discrete redox reactions and delivers a high initial capacity of 1603.6 mAh g-1 at 1 C charging-discharging rate, which is over twofolds of the one assembled using individual hosts, and 80.4% capacity can be maintained after 1000 cycles at 3 C rate. This work has demonstrated a novel synergy between the interface and material surface, which will help the future design of high-performance Li-S batteries.
RESUMEN
Enhancing electrocatalytic performance through structural and compositional engineering attracts considerable attention. However, most materials only function as pre-catalysts and convert into "real catalysts" during electrochemical reactions. Such transition involves dramatic structural and compositional changes and disrupts their designed properties. Herein, for the first time, a laser-ironing (LI) approach capable of in-situ forming a laser-ironing capping layer (LICL) on the Co-ZIF-L flakes is developed. During the oxygen evolution reaction (OER) process, the LICL sustains the leaf-like morphology and promotes the formation of OER-active Co3 O4 nanoclusters with the highest activity and stability. In contrast, the pristine and conventional heat-treated Co-ZIF-Ls both collapse and transform to less active CoOOH. The density functional theory (DFT) calculations pinpoint the importance of the high spin (HS) states of Co ions and the narrowed band gap in Co3 O4 nanoclusters. They enhance the OER activity by promoting spin-selected electron transport, effectively lowering the energy barrier and realizing a spontaneous O2 -releasing step that is the potential determining step (pds) in CoOOH. This study presents an innovative approach for modulating both structural and compositional evolutions of electrocatalysts during the reaction, sustaining stability with high performance during dynamic electrochemical reactions, and providing new pathways for facile and high-precision surface microstructure control.
RESUMEN
Severe brain damage usually leads to disorders of consciousness (DOC), which include coma, unresponsive wakefulness syndrome (UWS) and a minimally conscious state (MCS). Visual stimulation is widely used, especially in the diagnosis and treatment and treatment of DOC. Researchers have indicated that tests based on visual stimulation including visual pursuit, when used in conjunction with the Coma Recovery Scale-Revised, are able to differentiate between UWS from an MCS. Recently, targeting patients' circadian rhythms has been proposed to be a possible treatment target for DOC. Indeed, light therapy has been applied in some other fields, including treating seasonal affective disorder, sleep problems, and Parkinson's disease. However, at present, although visual stimulation and light therapy are frequently used in DOC, there is still no international unified standard. Therefore, we recommend the development of an international consensus in regard to the definitions, operational criteria and assessment procedures of visual stimulation and light therapy. This review combines visual stimulation, circadian rhythm recovery, and light therapy in DOC patients and presents the mechanisms and current advances in applications related to light therapy and visual stimulation in an attempt to provide additional ideas for future research and treatment of DOC.
RESUMEN
As the atmospheric carbon dioxide (CO2 ) level keeps hitting the new record, humanity is facing an ever-daunting challenge to efficiently mitigate CO2 from the atmosphere. Though electrochemical CO2 reduction presents a promising pathway to convert CO2 to valuable fuels and chemicals, the general lack of suitable electrocatalysts with high activity and selectivity severely constrains this approach. Herein, a novel class of electrocatalysts is investigated, the quasi-copper-mers, in which the CuN4 rather than Cu atom itself serve as the basic building block. The respective quasi-copper-monomers, -dimers, and -trimers hosted in a graphene-like substrate are first synthesized and then performed both experimental characterization and density functional theory (DFT) calculations to examine their atomic structures, evaluate their electrocatalytical performance and understand their underlying mechanisms. The experimental results show that the quasi-copper-trimers not only outperform the quasi-copper-dimer and quasi-copper-monomer when catalyzing CO2 to CO, it also shows a superior selectivity against the competing hydrogen evolution reaction (HER). The DFT calculations not only support the experimental observations, but also reveal the volcano curve and the physical origin for the qausi-copper-trimer superiority. The present work thus presents a new strategy in the design of high-performance electrocatalysts with high activity and selectivity.
RESUMEN
The Cyber-Physical System and even the Metaverse will become the second space in which human beings live. While bringing convenience to human beings, it also brings many security threats. These threats may come from software or hardware. There has been a lot of research on managing malware, and there are many mature commercial products, such as antivirus software, firewalls, etc. In stark contrast, the research community on governing malicious hardware is still in its infancy. Chips are the core component of hardware, and hardware Trojans are the primary and complex security issue faced by chips. Detection of hardware Trojans is the first step for dealing with malicious circuits. Due to the limitation of the golden chip and the computational consumption, the existing traditional detection methods are not applicable to very large-scale integration. The performances of traditional machine-learning-based methods depend on the accuracy of the multi-feature representation, and most of the methods may lead to instability because of the difficulty of extracting features manually. In this paper, employing deep learning, a multiscale detection model for automatic feature extraction is proposed. The model is called MHTtext and provides two strategies to balance the accuracy and computational consumption. After selecting a strategy according to the actual situations and requirements, the MHTtext generates the corresponding path sentences from the netlist and employs TextCNN for identification. Further, it can also obtain non-repeated hardware Trojan component information to improve its stability performance. Moreover, a new evaluation metric is established to intuitively measure the model's effectiveness and balance: the stabilization efficiency index (SEI). In the experimental results for the benchmark netlists, the average accuracy (ACC) in the TextCNN of the global strategy is as high as 99.26%, and one of its stabilization efficiency index values ranks first with a score of 71.21 in all comparison classifiers. The local strategy also achieved an excellent effect, according to the SEI. The results show that the proposed MHTtext model has high stability, flexibility, and accuracy, in general.
Asunto(s)
Aprendizaje Profundo , Humanos , Computadores , Programas Informáticos , BenchmarkingRESUMEN
Huanglongbing (HLB) is one of the most serious citrus diseases in the world. Rapid, onsite, and accurate field detection of HLB is a challenging task in analytical science for a long time. Herein, we have developed a novel HLB detection method that combines headspace solid phase microextraction with portable gas chromatography-mass spectrometry (PGC-MS) approach for onsite field detection of volatile metabolites of citrus leaves. Detectability and characteristics of HLB-affected metabolites from leaves were validated, and the important biomarkers were verified by authentic compounds. A machine learning approach based on random forest algorithm is established to model the volatile metabolites from healthy, symptomatic, and asymptomatic citrus leaves. In this work, a total of 147 citrus leaf samples were analyzed. Analytical performances of this newly developed method were investigated by in-field detection of various volatile metabolites. Results demonstrated limits of detection and quantification of 0.04-0.12 and 0.17-0.44 ng/mL for different metabolites, respectively. Linear calibration curves of various metabolites were established over a concentration dynamic range of at least three orders (R2 > 0.96). Good reproducibility was obtained for intraday (3.0-17.5%, n = 6) and interday precision (8.7-18.2%, n = 7). This new HLB field detection method provides a rapid detection with 6 min for each sample via a simple optimized procedure, including onsite sampling, PGC-MS analysis, and data process and provides a high accuracy (93.3%) for simultaneous identification of healthy, symptomatic, and asymptomatic trees. These data support the use of this new method for reliable field detection of HLB. Furthermore, metabolic pathways of HLB-affected metabolites were also proposed. Overall, our results not only provide a rapid and onsite field HLB detection method but also provide valuable information for understanding metabolic change of HLB infection.
Asunto(s)
Citrus , Rhizobiaceae , Reproducibilidad de los Resultados , Enfermedades de las Plantas , Espectrometría de Masas , Citrus/química , Citrus/metabolismoRESUMEN
PURPOSE: Real-world data on antibiotic management of nontuberculous mycobacterial lung disease (NTM-LD) is limited for many countries. This study aimed to evaluate real-world treatment practices of NTM-LD in the Netherlands using medication dispensing data. METHODS: A retrospective longitudinal real-world study was conducted using IQVIA's Dutch pharmaceutical dispensing database. The data are collected monthly and include approximately 70% of all outpatient prescriptions in the Netherlands. Patients initiated on specific NTM-LD treatment regimens between October 2015 and September 2020 were included. The main areas of investigation were initial treatment regimens, persistence on treatment, treatment switching, treatment compliance in terms of medication possession rate (MPR) and restarts of treatment. RESULTS: The database included 465 unique patients initiated on triple- or dual-drug regimens for the treatment of NTM-LD. Treatment switches were common and occurred approximately 1.6 per quarter throughout the treatment period. The average MPR of patients initiated on triple-drug therapy was 90%. The median time on therapy for these patients was 119 days; after six months and one year, 47% and 20% of the patients, respectively, were still on antibiotic therapy. Of 187 patients initiated on triple-drug therapy, 33 (18%) patients restarted antibiotic therapy after the initial treatment had been stopped. CONCLUSION: When on therapy, patients were compliant with the NTM-LD treatment; however, many patients stopped their therapy prematurely, treatment switches often occurred, and part of patients had to restart their therapy after a longer treatment gap. NTM-LD management should be improved through greater guideline adherence and appropriate involvement of expert centers.