Microlife. 2024 Dec 5;6:uqae024. doi: 10.1093/femsml/uqae024. eCollection 2025.

ABSTRACT

The polyene antimycotic amphotericin B (AmB) and its liposomal formulation AmBisome belong to the treatment options of invasive aspergillosis caused by Aspergillus fumigatus. Increasing resistance to AmB in clinical isolates of Aspergillus species is a growing concern, but mechanisms of AmB resistance remain unclear. In this study, we conducted a proteomic analysis of A. fumigatus exposed to sublethal concentrations of AmB and AmBisome. Both antifungals induced significantly increased levels of proteins involved in aromatic acid metabolism, transmembrane transport, and secondary metabolite biosynthesis. One of the most upregulated proteins was RtaA, a member of the RTA-like protein family, which includes conserved fungal membrane proteins with putative functions as transporters or translocases. Accordingly, we found that RtaA is mainly located in the cytoplasmic membrane and to a minor extent in vacuolar-like structures. Deletion of rtaA led to increased polyene sensitivity and its overexpression resulted in modest resistance. Interestingly, rtaA expression was only induced by exposure to the polyenes AmB and nystatin, but not by itraconazole and caspofungin. Orthologues of rtaA were also induced by AmB exposure in A. lentulus and A. terreus. Deletion of rtaA did not significantly change the ergosterol content of A. fumigatus, but decreased fluorescence intensity of the sterol-binding stain filipin. This suggests that RtaA is involved in sterol and lipid trafficking, possibly by transporting the target ergosterol to or from lipid droplets. These findings reveal the contribution of RtaA to polyene resistance in A. fumigatus, and thus provide a new putative target for antifungal drug development.

PMID:39790482 | PMC:PMC11707875 | DOI:10.1093/femsml/uqae024

HCA Healthc J Med. 2024 Dec 1;5(6):739-743. doi: 10.36518/2689-0216.1738. eCollection 2024.

ABSTRACT

BACKGROUND: Nitrofurantoin is a prevalent antibiotic used to treat urinary tract infections. Despite nitrofurantoin's general safety, it can cause serious side effects, including acute pulmonary toxicity, fulminant hepatitis, and severe systemic inflammatory responses, which may mimic conditions such as ischemia and infection. However, reports of acute systemic inflammatory response syndrome after nitrofurantoin ingestion are uncommon in medical literature.

CASE PRESENTATION: This case describes a severe systemic inflammatory response syndrome in an 85-year-old woman presenting with hypoxia, altered mental status, and profound leukocytosis after exposure to a single dose of nitrofurantoin.

CONCLUSION: Herein we report on a patient with suspected bacteremia and urosepsis. Who was treated with broad-spectrum antibiotics. However, the antibiotic used to treat the patient's urinary tract infection caused an altered mental status and systemic inflammatory response. Therefore, it is crucial for clinicians to consider iatrogenic and medication-induced etiologies for altered mental status.

PMID:39790693 | PMC:PMC11708924 | DOI:10.36518/2689-0216.1738

Funding Opportunity PAR-25-090 from the NIH Guide for Grants and Contracts. NIDDK supports investigator-initiated, high-risk multi-center (more than one center) clinical studies through a two-part process that may include an implementation planning cooperative agreement (U34). The U34 is designed to: 1) Permit early peer review of the rationale for the proposed clinical study; 2) Permit assessment of the design and protocol of the proposed study; 3) Provide support for the development of documents needed for the conduct of the study, including a manual of operations; and 4) Support the development of other essential elements required for the conduct of the clinical study. The proposed clinical study should be hypothesis-driven and focus on a disease in the mission of NIDDK. Consultation with NIDDK scientific staff is strongly encouraged prior to the submission of the U34 application.

Funding Opportunity PAR-25-312 from the NIH Guide for Grants and Contracts. This Notice of Funding Opportunity (NOFO) establishes an accelerated review/award process to support time-sensitive research to evaluate a new policy or program that is likely to influence obesity related behaviors (e.g., dietary intake, physical activity, or sedentary behavior) and/or weight outcomes in an effort to prevent or reduce obesity. This NOFO is intended to support research where opportunities for empirical study are, by their very nature, only available through expedited review and funding. All applications to this NOFO must demonstrate that the evaluation of an obesity related policy and /or program offers an uncommon and scientifically compelling research opportunity that will only be available if the research is initiated with minimum delay. For these reasons, applications in response to this time-sensitive NOFO are not eligible for re-submission. It is intended that eligible applications selected for funding will be awarded within 4 months of the application due date. However, administrative requirements and other unforeseen circumstances may delay issuance dates beyond that timeline.

Funding Opportunity RFA-HS-25-001 from the NIH Guide for Grants and Contracts. The purpose of this is NOFO is to disseminate patient-centered outcomes (PCOR) evidence for Long COVID care into clinical practice through clinical decision support (CDS) that is consistently updated as best practices and new evidence emerge.

Int J Technol Assess Health Care. 2025 Jan 9;41(1):e6. doi: 10.1017/S0266462324004835.

ABSTRACT

OBJECTIVE: The aim of this study is to propose and validate a value assessment framework for Health Technology Assessment (HTA) for rare diseases drugs in Brazil.

METHODS: A scoping review was performed to identify criteria used by HTA agencies in countries with public healthcare systems when evaluating orphan drugs. Based on the findings, a criteria framework for rare disease drugs was proposed for Brazil. Content validity was conducted over three rounds using Delphi technique and content validity ratio (CVR) approach was employed to evaluate the ratings from the eighteen stakeholders (experts and patients).

RESULTS: Twenty-nine HTA criteria for rare disease drugs were identified to compose the Brazilian framework. After three Delphi rounds, the final value framework comprised fifteen criteria categorized into four domains: disease-related factors, treatment-related factors, social and political factors, and economic factors. Among the most well-rated criteria by the CVR, considering the relevance attribute, were "relevance of outcomes for a rare disease," "impact on patient's quality of life," "price negotiation," and "adjusted cost-effectiveness threshold." On the other hand, "budget impact threshold," "innovative nature of treatment," and "willingness to accept greater uncertainty in clinical evidence" received negative evaluations and were excluded from the final framework.

CONCLUSIONS: A value assessment framework validated by key stakeholders of rare diseases in Brazil could contribute to improve HTA transparency, decision making, and efficiency of the healthcare system, and inspire the development of a local guidance for rare-disease HTA.

PMID:39783027 | DOI:10.1017/S0266462324004835

BMC Pulm Med. 2025 Jan 9;25(1):11. doi: 10.1186/s12890-024-03433-8.

ABSTRACT

BACKGROUND: This study aims to compare Lung Ultrasound (LUS) findings with High-Resolution Computerized Tomography (HRCT) and Pulmonary Function Tests (PFTs) to detect the severity of lung involvement in patients with Usual Interstitial Pneumonia (UIP) and Non-Specific Interstitial Pneumonia (NSIP).

METHODS: A cross-sectional study was conducted on 35 UIP and 30 NSIP patients at a referral hospital. All patients underwent LUS, HRCT, and PFT. LUS findings such as B-lines, pleural fragmentation, and pleural thickening were compared with HRCT-based lung involvement and PFT parameters.

RESULTS: In UIP patients, B-lines > 18 and pleural fragmentation significantly differentiated between < 50% and > 50% HRCT involvement. A logistic regression model showed that B-lines > 18 (OR = 39, p = 0.04) and pleural fragmentation (OR = 22, p = 0.037) independently predicted > 50% HRCT involvement. ROC analysis of the model revealed 84.2% sensitivity and 84.5% specificity. Furthermore, the crude number of B-lines (OR = 1.2, p = 0.038) and > 50% HRCT involvement (OR = 9.5, p = 0.045) independently predicted severe DLCO impairment, with a sensitivity of 94.7% and specificity of 84.5%. Linear regression showed that each additional B-line was associated with a 0.4% decrease in DLCO (Beta = -0.377, p = 0.043), independent of patient diagnosis. In NSIP patients, no significant correlation was observed between LUS findings and > 50% HRCT involvement (p > 0.05), though B-line numbers and pleural thickening increased in cases with severe DLCO impairment (p < 0.05).

CONCLUSIONS: LUS shows promise as a sensitive, radiation-free alternative to HRCT in monitoring the severity of UIP. It is particularly valuable in predicting the extent of lung involvement and severe DLCO impairment in UIP patients but has limited application in NSIP.

PMID:39789530 | DOI:10.1186/s12890-024-03433-8

AJNR Am J Neuroradiol. 2025 Jan 9:ajnr.A8645. doi: 10.3174/ajnr.A8645. Online ahead of print.

ABSTRACT

BACKGROUND AND PURPOSE: Diagnosis of tumefactive demyelination can be challenging. The diagnosis of indeterminate brain lesions on MRI often requires tissue confirmation via brain biopsy. Noninvasive methods for accurate diagnosis of tumor and non-tumor etiologies allows for tailored therapy, optimal tumor control, and a reduced risk of iatrogenic morbidity and mortality. Tumefactive demyelination has imaging features that mimic isocitrate dehydrogenase-wildtype glioblastoma (IDHwt GBM). We hypothesized that deep learning applied to postcontrast T1-weighted (T1C) and T2-weighted (T2) MRI images can discriminate tumefactive demyelination from IDHwt GBM.

MATERIALS AND METHODS: Patients with tumefactive demyelination (n=144) and IDHwt GBM (n=455) were identified by clinical registries. A 3D DenseNet121 architecture was used to develop models to differentiate tumefactive demyelination and IDHwt GBM using both T1C and T2 MRI images, as well as only T1C and only T2 images. A three-stage design was used: (i) model development and internal validation via five-fold cross validation using a sex-, age-, and MRI technology-matched set of tumefactive demyelination and IDHwt GBM, (ii) validation of model specificity on independent IDHwt GBM, and (iii) prospective validation on tumefactive demyelination and IDHwt GBM. Stratified AUCs were used to evaluate model performance stratified by sex, age at diagnosis, MRI scanner strength, and MRI acquisition.

RESULTS: The deep learning model developed using both T1C and T2 images had a prospective validation area under the receiver operator characteristic curve (AUC) of 88% (95% CI: 0.82 - 0.95). In the prospective validation stage, a model score threshold of 0.28 resulted in 91% sensitivity of correctly classifying tumefactive demyelination and 80% specificity (correctly classifying IDHwt GBM). Stratified AUCs demonstrated that model performance may be improved if thresholds were chosen stratified by age and MRI acquisition.

CONCLUSIONS: MRI images can provide the basis for applying deep learning models to aid in the differential diagnosis of brain lesions. Further validation is needed to evaluate how well the model generalizes across institutions, patient populations, and technology, and to evaluate optimal thresholds for classification. Next steps also should incorporate additional tumor etiologies such as CNS lymphoma and brain metastases.

ABBREVIATIONS: AUC = area under the receiver operator characteristic curve; CNS = central nervous system; CNSIDD = central nervous system inflammatory demyelinating disease; FeTS = federated tumor segmentation; GBM = glioblastoma; IDHwt = isocitrate dehydrogenase wildtype; IHC = immunohistochemistry; MOGAD = myelin oligodendrocyte glycoprotein antibody associated disorder; MS = multiple sclerosis; NMOSD = neuromyelitis optica spectrum disorder; wt = wildtype.

PMID:39788628 | DOI:10.3174/ajnr.A8645

J Pathol. 2025 Feb;265(2):198-210. doi: 10.1002/path.6378.

ABSTRACT

Colorectal cancer (CRC) is a histologically heterogeneous disease with variable clinical outcome. The role the tumour microenvironment (TME) plays in determining tumour progression is complex and not fully understood. To improve our understanding, it is critical that the TME is studied systematically within clinically annotated patient cohorts with long-term follow-up. Here we studied the TME in three clinical cohorts of metastatic CRC with diverse molecular subtype and treatment history. The MISSONI cohort included cases with microsatellite instability that received immunotherapy (n = 59, 24 months median follow-up). The BRAF cohort included BRAF V600E mutant microsatellite stable (MSS) cancers (n = 141, 24 months median follow-up). The VALENTINO cohort included RAS/RAF WT MSS cases who received chemotherapy and anti-EGFR therapy (n = 175, 32 months median follow-up). Using a Deep learning cell classifier, trained upon >38,000 pathologist annotations, to detect eight cell types within H&E-stained sections of CRC, we quantified the spatial tissue organisation and colocalisation of cell types across these cohorts. We found that the ratio of infiltrating endothelial cells to cancer cells, a possible marker of vascular invasion, was an independent predictor of progression-free survival (PFS) in the BRAF+MISSONI cohort (p = 0.033, HR = 1.44, CI = 1.029-2.01). In the VALENTINO cohort, this pattern was also an independent PFS predictor in TP53 mutant patients (p = 0.009, HR = 0.59, CI = 0.40-0.88). Tumour-infiltrating lymphocytes were an independent predictor of PFS in BRAF+MISSONI (p = 0.016, HR = 0.36, CI = 0.153-0.83). Elevated tumour-infiltrating macrophages were predictive of improved PFS in the MISSONI cohort (p = 0.031). We validated our cell classification using highly multiplexed immunofluorescence for 17 markers applied to the same sections that were analysed by the classifier (n = 26 cases). These findings uncovered important microenvironmental factors that underpin treatment response across and within CRC molecular subtypes, while providing an atlas of the distribution of 180 million cells in 375 clinically annotated CRC patients. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

PMID:39788558 | DOI:10.1002/path.6378

Magn Reson Imaging. 2025 Jan 7:110325. doi: 10.1016/j.mri.2025.110325. Online ahead of print.

ABSTRACT

OBJECTIVE: To explore the application value of MRI-based imaging histology and deep learning model in the identification and classification of breast phyllodes tumors.

METHODS: Seventy-seven patients diagnosed as breast phyllodes tumors and fibroadenomas by pathological examination were retrospectively analyzed, and traditional radiomics features, subregion radiomics features, and deep learning features were extracted from MRI images, respectively. The features were screened and modeled using variance selection method, statistical test, random forest importance ranking method, Spearman correlation analysis, least absolute shrinkage and selection operator (LASSO). The efficacy of each model was assessed using the subject operating characteristic (ROC) curve, The DeLong test was used to assess the differences in the AUC values of the different models, and the clinical benefit of each model was assessed using the decision curve (DCA), and the predictive accuracy of the model was assessed using the calibration curve (CCA).

RESULTS: Among the constructed models for classification of breast phyllodes tumors, the fusion model (AUC: 0.97) had the best diagnostic efficacy and highest clinical benefit. The traditional radiomics model (AUC: 0.81) had better diagnostic efficacy compared with subregion radiomics model (AUC: 0.70). De-Long test, there is a statistical difference between the fusion model traditional radiomics model, and subregion radiomics model in the training group. Among the models constructed to distinguish phyllodes tumors from fibroadenomas in the breast, the TDT_CIDL model (AUC: 0.974) had the best predictive efficacy and the highest clinical benefit. De-Long test, the TDT_CI combination model was statistically different from the remaining five models in the training group.

CONCLUSION: Traditional radiomics models, subregion radiomics models and deep learning models based on MRI sequences can help to differentiate benign from junctional phyllodes tumors, phyllodes tumors from fibroadenomas, and provide personalized treatment for patients.

PMID:39788394 | DOI:10.1016/j.mri.2025.110325

J Appl Microbiol. 2025 Jan 9:lxaf012. doi: 10.1093/jambio/lxaf012. Online ahead of print.

ABSTRACT

AIMS: To investigate the effects of simvastatin as an antimicrobial, considering its influence on the mevalonate pathway and on the bacterial cell wall of Staphylococcus aureus.

METHODS AND RESULTS: S. aureus ATCC 29213 and 33591 were exposed to simvastatin in the presence of exogenous mevalonate to determine whether mevalonate could reverse the inhibition. S. aureus was also treated with simvastatin and gene expression analysis assays were performed to evaluate genes associated with the mevalonate pathway (mvaA, mvaS, mvaK1, and mvaK2), peptidoglycan synthesis (uppS, uppP, and murG), and cell wall stress (vraX, sgtB, and tcaA). Transmission electron microscopy was used to identify the presence of morphological changes. The data were compared using two-way ANOVA and Bonferroni post-test, or the Mann-Whitney test. Addition of exogenous mevalonate was able to partially or completely reverse the inhibition caused by simvastatin. A significant increase of the vraX gene and a reduction of the mvaA gene were observed, together with changes in bacterial morphology.

CONCLUSION: Simvastatin can exert its antimicrobial effect by means of changes in the cell wall associated with the mevalonate pathway.

PMID:39788721 | DOI:10.1093/jambio/lxaf012

Int J Biol Macromol. 2025 Jan 7:139590. doi: 10.1016/j.ijbiomac.2025.139590. Online ahead of print.

ABSTRACT

SARS-CoV-2 encodes a 3C-like protease (3CLpro) that is essential for viral replication. This cysteine protease cleaves viral polyproteins to release functional nonstructural proteins, making it a prime target for antiviral drug development. We investigated the inhibitory effects of halicin, a known c-Jun N-terminal kinase inhibitor, on 3CLpro. Mass spectrometry and crystallographic analysis revealed that halicin covalently binds to several cysteine residues in 3CLpro. As expected, Cys145, the catalytic residue, was found to be the most targeted residue by halicin. Secondly, Cys44 was found to be modified, suggesting a potential inhibitory role of this residue. A mutant protease (Cys44Ala) was generated to further understand the function of Cys44. In silico and enzymatic assays showed that the mutation significantly reduced the stability and activity of 3CLpro, indicating the importance of Cys44 in maintaining the active conformation of the protease. Differential scanning fluorimetry assays confirmed this evidence, showing a reduced thermal stability of the mutant compared to the wild-type protease. Our results highlight the potential of halicin as a multi-target inhibitor of 3CLpro and underline the importance of Cys44 in the function of the protease. These findings contribute to the development of effective antiviral therapies against COVID-19 by targeting critical residues in 3CLpro.

PMID:39788258 | DOI:10.1016/j.ijbiomac.2025.139590

Sci Rep. 2025 Jan 9;15(1):1521. doi: 10.1038/s41598-024-84192-8.

ABSTRACT

Aripiprazole (ARI) is an atypical antipsychotic which is a substrate of P-glycoprotein (P-gp), a transmembrane glycoprotein that plays a crucial role in eliminating potentially harmful compounds from the organism. ARI once-monthly (AOM) is a long-acting injectable form which improves treatment compliance. Genetic polymorphisms in ABCB1 may lead to changes in P-gp function, leading to individual differences in drug disposition. The present study aims to determine how the different variants of the three most prevalent SNPs of the ABCB1 gene affect plasma concentrations of ARI, of its active metabolite dehydroaripiprazole (DHA) and ARI/DHA ratio in patients under AOM treatment. The metabolizing state of the two main aripiprazole metabolizing enzymes (CYP2D6 and CYP3A4) were considered to specifically study the effect of P-gp on plasma concentrations of the parent compound and its active metabolite. The study found a clear relationship between the genotypes found for the different ABCB1 SNPs and the ARI/DHA ratio. Specifically, patients with GG genotype in G2677T have almost twice the ratio compared to TT genotype. Similarly, this increase is also found in C3435T with 1.4-fold and in C1236T with 1.6-fold for the same genotypes. Regarding haplotypes, significant differences were obtained between CC-GG-CC and TT-TT-TT patients, with an 87.9% higher ratio in patients with the CC-GG-CC haplotype. There was a clear trend towards lower ARI concentrations and higher DHA concentrations when the presence of mutated T alleles increases. The ABCB1 gene could be a good partner along with CYP2D6 and CYP3A4 genotyping in conjunction with monitoring ARI plasma concentrations.

PMID:39789135 | DOI:10.1038/s41598-024-84192-8

Nat Commun. 2025 Jan 9;16(1):538. doi: 10.1038/s41467-025-55864-4.

NO ABSTRACT

PMID:39788999 | DOI:10.1038/s41467-025-55864-4

Eur Psychiatry. 2025 Jan 10:1-13. doi: 10.1192/j.eurpsy.2024.1816. Online ahead of print.

NO ABSTRACT

PMID:39788917 | DOI:10.1192/j.eurpsy.2024.1816

Therapie. 2024 Dec 20:S0040-5957(24)00215-4. doi: 10.1016/j.therap.2024.11.010. Online ahead of print.

ABSTRACT

4P medicine (personalized, preventive, predictive, and participatory) is experiencing a remarkable rise, and pharmacogenetics is an essential part of it. However, several obstacles are hindering its deployment. This round table brought together a group of experts to take stock of the situation, reflecting on ways to facilitate the prescription of these tests and the dissemination of the results on a national scale. The experts looked at the methods of prescribing and communicating pharmacogenetic data in the current situation as well as in the coming years, with the arrival of artificial intelligence software. The questions relating to the reimbursement of tests - as topical as ever - were also discussed, as this is a way to allow all patients to access these tests. Numerous recommendations have been formulated on these various points, aimed at facilitating prescription management for healthcare professionals, and ensuring the retention and use of the results throughout the patient's life. Finally, better patient information was recommended, as well as strengthening the involvement of healthcare professionals and industry stakeholders in this process, with insistence on the necessary training and commitment to ensure its success.

PMID:39788802 | DOI:10.1016/j.therap.2024.11.010

BMC Pediatr. 2025 Jan 9;25(1):22. doi: 10.1186/s12887-024-05369-8.

ABSTRACT

Preterm infants are at high risk of developing respiratory distress syndrome (RDS). Mutations in the genes encoding for surfactant proteins B and C or the ATP-binding cassette transporter A3 (ABCA3) are rare but known to be associated with severe RDS and interstitial lung diseases. The exact prevalence of these mutations in the general population is difficult to determine, as they are usually studied in connection with clinical symptoms. Most cases are not captured due to variability in expression or diagnosis. It is estimated that they affect a small percentage of the population, with mutations in ABCA3 most commonly identified in association with severe lung diseases in newborns. Even heterozygous ABCA3-mutations can increase the risk and severity of RDS in neonates. The expression of these proteins is developmentally regulated, increases with gestational age, and is crucial for the function of pulmonary surfactant at birth. Additional lung stressors, such as meconium aspiration syndrome or pulmonary infections, can lead to a complex clinical picture associated with severe courses. This case report describes an extremely preterm female infant with suspected meconium aspiration syndrome, severe RDS, Mycoplasma pneumoniae infection, and a heterozygous ABCA3-mutation. The report discusses the clinical presentation, diagnostic evaluation, and therapeutic interventions, emphasizing the complexities associated with multiple pulmonary conditions in the context of extreme prematurity. At the limits of viability, therapeutic options for severe respiratory insufficiency are limited compared to older children. The developmental neurological prognosis following prolonged relative hypoxia is a crucial factor to consider in discussions about changing treatment goals. Particularly in severe cases, pulmonary infections and genetic changes in surfactant metabolism must be considered in newborns with RDS.

PMID:39789505 | DOI:10.1186/s12887-024-05369-8

Transplant Proc. 2025 Jan 8:S0041-1345(24)00687-0. doi: 10.1016/j.transproceed.2024.12.024. Online ahead of print.

ABSTRACT

Infectious complications significantly impact morbidity and mortality following lung transplantation (LuTx), with over 25% of post-transplant deaths attributed to infections. Antibiotic prophylaxis during the surgical procedure is crucial for reducing early infections, though the current use of wide-spectrum antibiotics, especially in cases of multidrug-resistant organisms (MDROs), is contentious and varies widely across centre. This practice raises concerns about antimicrobial resistance (AMR), particularly in immunosuppressed patients requiring lifelong healthcare access. Syndromic multiplex polymerase chain reaction (mPCR) tests, which detect multiple pathogens simultaneously, have shown promise in quickly identifying pathogens and resistance mechanisms, thus enabling targeted treatments. However, their application in LuTx has been limited.

PMID:39788793 | DOI:10.1016/j.transproceed.2024.12.024

J Med Internet Res. 2025 Jan 9;27:e60689. doi: 10.2196/60689.

ABSTRACT

BACKGROUND: Home spirometers have been widely implemented in the treatment of people with cystic fibrosis (CF). Frequent spirometry measurements at home could lead to earlier detection of exacerbations. However, previous research indicates that the long-term use of home spirometry is not well maintained by people with CF.

OBJECTIVE: We aimed to gain insight into the long-term uptake of home spirometry in regular multicenter CF care.

METHODS: Home spirometers combined with a remote monitoring platform were introduced in the treatment of people with CF in 5 Dutch CF centers starting in April 2020. Usage data from April 2020 to December 2022 were analyzed retrospectively. Survival analyses were conducted to assess use consistency over time, and t tests were used to evaluate the impact of increased pulmonary symptoms on home spirometry frequency. The effect of the initiation of a new treatment, Elexacaftor/Tezacaftor/Ivacaftor, on use frequency over time was assessed in a subgroup of participants with repeated measures ANOVA.

RESULTS: During the observation period, a total of 604 people with CF were enrolled in the remote monitoring platform and 9930 home spirometry measurements were performed. After the initiation of home spirometry use, the number of users declined rapidly. One year after the initiation, 232 (54.2%) people with CF stopped using home spirometry. During the observation period, 67 (11.1%) users performed more than 20 measurements. Furthermore, the number of consistent home spirometry users decreased over time. After 600 days, only 1% of users had measured their lung function consistently every 31 days. Use frequency slightly increased during periods with increased pulmonary symptoms (ΔMean=0.45, t497.278=-4,197; P<.001) and showed an initial rise followed by a decrease after starting treatment with Elexacaftor/Tezacaftor/Ivacaftor (ΔMean=0.45, t497.278=-4,197; P<.001).

CONCLUSIONS: Consistent uptake of home spirometry in people with CF is low but increases around periods of changing symptoms. A clear strategy for the organization of remote care seemed to improve the long-term uptake of home spirometry. Nevertheless, home spirometry and its intensity are not a goal on their own but should be used as a tool to reach individual goals within local contexts.

PMID:39788554 | DOI:10.2196/60689

Plant Methods. 2025 Jan 9;21(1):4. doi: 10.1186/s13007-025-01324-5.

ABSTRACT

Apricot trees, serving as critical agricultural resources, hold a significant role within the agricultural domain. Conventional methods for detecting pests and diseases in these trees are notably labor-intensive. Many conditions affecting apricot trees manifest distinct visual symptoms that are ideally suited for precise identification and classification via deep learning techniques. Despite this, the academic realm currently lacks extensive, realistic datasets and deep learning strategies specifically crafted for apricot trees. This study introduces ATZD01, a publicly accessible dataset encompassing 11 categories of apricot tree pests and diseases, meticulously compiled under genuine field conditions. Furthermore, we introduce an innovative detection algorithm founded on convolutional neural networks, specifically devised for the management of apricot tree pests and diseases. To enhance the accuracy of detection, we have developed a novel object detection framework, APNet, alongside a dedicated module, the Adaptive Thresholding Algorithm (ATA), tailored for the detection of apricot tree afflictions. Experimental evaluations reveal that our proposed algorithm attains an accuracy rate of 87.1% on ATZD01, surpassing the performance of all other leading algorithms tested, thereby affirming the effectiveness of our dataset and model. The code and dataset will be made available at https://github.com/meanlang/ATZD01 .

PMID:39789617 | DOI:10.1186/s13007-025-01324-5