Iran J Parasitol. 2025 Jan-Mar;20(1):21-31. doi: 10.18502/ijpa.v20i1.18102.

ABSTRACT

BACKGROUND: We aimed to determine the genotypes of Echinococcus granulosus sensu lato (s.l.) using DNA regions within the NADH dehydrogenase subunit-1 (nad1) mitochondrial genes in formalin-fixed paraffin-embedded (FFPE) isolates of human cystic echinococcosis cysts (CE cysts) and compare their histopathologic alterations.

METHODS: Out of 135 samples, 21 high-quality PCR positive samples were selected for sequencing and were deposited into GenBank database. Moreover, histopathological changes of E. granulosus sensu stricto (G1 genotype) and E. canadensis (G6 genotype) cases were also compared.

RESULTS: Based on the sequencing results, 16 cases were diagnosed as E. granulosus s.s. (G1-G3 genotype) and 5 cases as E. canadensis (G6 genotype). Five haplotypes of E. granulosus were identified from 21 nad1 sequences. The histopathological alterations in both genotypes showed laminated layer of CE without inflammatory cells. In a few cases of the G6 genotype, neutrophils in the outer cuticular layer with mild vascular and congestion were observed. Cell debris with multiple areas of necrosis, as well as scanty lymphoplasma cells in the outer cuticular layer were observed in G1-G3 genotype cases. So, the histopathological differences between the two genotypes are not noticeable enough to be differentiated by microscopical observations.

CONCLUSION: E. granulosus s.s. (G1-G3) and E. canadensis (G6 genotype) are prevalent among CE patients. In general, five haplotypes were identified by nad1 genes analysis. The histopathological differences between the two genotypes have not been so big to be differentiated by microscopic observations.

PMID:40206365 | PMC:PMC11978209 | DOI:10.18502/ijpa.v20i1.18102

Front Pharmacol. 2025 Mar 26;16:1593164. doi: 10.3389/fphar.2025.1593164. eCollection 2025.

NO ABSTRACT

PMID:40206057 | PMC:PMC11979609 | DOI:10.3389/fphar.2025.1593164

Dis Model Mech. 2025 Apr 10:dmm.052282. doi: 10.1242/dmm.052282. Online ahead of print.

ABSTRACT

While progressive striatal gene expression changes and epigenetic alterations are a prominent feature of Huntington's disease (HD), the mechanistic basis remains poorly understood. Using chromatin immunoprecipitation and sequencing (ChIP-seq), we show that the huntingtin protein (HTT) reproducibly occupies specific locations in the mouse genome. Striatal HTT ChIP-seq peaks were enriched in coding regions of spiny projection neuron identity genes, which are found to have reduced expression in HD patients and mouse models, and had reduced occupancy in expanded polyglutamine HTT knock-in mice (HttQ111/Q111). Conversely, HTT occupancy was depleted near genes that are up-regulated in HD. ChIP-seq of striatal histone modifications revealed genotype-specific colocalization of HTT with active chromatin marks and enhancer of zeste homolog 2 (EZH2), a key enzymatic component of the PRC2 complex. Near genes that are differentially regulated in HD, greater HTT occupancy in HttQ111/Q111 vs. wildtype mice was associated with increased EZH2 binding, increased H3K4me3, and decreased H3K27me3. Our study suggests that huntingtin-chromatin interactions may play a role in organizing chromatin and promoting cell type-specific gene expression, with HTT occupancy predicting transcriptional dysregulation in HD.

PMID:40205980 | DOI:10.1242/dmm.052282

CNS Neurosci Ther. 2025 Apr;31(4):e70292. doi: 10.1111/cns.70292.

ABSTRACT

AIMS: This randomized controlled trial evaluated the efficacy of a psychoeducational program in enhancing telomerase activity (TA) among patients with bipolar disorder (BD), with a specific focus on gender differences.

METHODS: A total of 62 participants were assigned to either the psychoeducation (PE) group or the control (CTR) group, with TA measured both before and after the intervention.

RESULTS: Results demonstrated a significant increase in TA in the PE group compared to the controls at the conclusion of the study. Notably, gender-specific analyses revealed that female participants showed significant increases in both TA and delta TA (ΔTA), with ΔTA PE = 0.586 ± 0.273 and ΔTA CTR = -0.251 ± 0.177. In contrast, male participants exhibited significant changes only in ΔTA, with ΔTA PE = 0.257 ± 0.138 and ΔTA CTR = -0.144 ± 0.1194.

CONCLUSION: These findings suggest that psychoeducational interventions have differential gender-specific effects, underscoring the importance of personalized approaches in the treatment of BD.

PMID:40205817 | DOI:10.1111/cns.70292

Rev Panam Salud Publica. 2025 Apr 9;49:e27. doi: 10.26633/RPSP.2025.27. eCollection 2025.

ABSTRACT

OBJECTIVE: To quantify the occurrence of vaccine-associated paralytic poliomyelitis (VAPP) cases in Brazil from January 2013 to May 2023.

METHODS: A descriptive study was conducted on VAPP cases reported as events supposedly attributable to vaccination or immunization (ESAVI) following oral poliovirus vaccine (OPV) administration. VAPP cases were defined as acute flaccid paralysis (AFP) with isolation of vaccine-derived poliovirus in stool samples and persistence of motor deficits after 60 days.

RESULTS: A total of 200 suspected cases were identified, with two confirmed as VAPP (<1 case per 10 million doses administered) based on the isolation of the vaccine virus. Risk factors associated with VAPP included incomplete vaccination schedules, malnutrition, and/or immunodeficiency.

CONCLUSIONS: VAPP occurrence was rare and aligned with expected values. Continued surveillance of ESAVI and suspected VAPP cases is essential to support poliomyelitis eradication efforts and ensure vaccine safety.

PMID:40206565 | PMC:PMC11980524 | DOI:10.26633/RPSP.2025.27

Res Pract Thromb Haemost. 2025 Mar 3;9(2):102721. doi: 10.1016/j.rpth.2025.102721. eCollection 2025 Feb.

ABSTRACT

BACKGROUND: Factor X (FX) deficiency (FXD) significantly disrupts coagulation, potentially leading to severe bleeding. While inherited FXD is rare, with a prevalence of 1 in 500,000, acquired FXD is also uncommon and frequently linked to conditions such as light-chain amyloidosis. In rare cases, certain medications can cause FXD.

KEY CLINICAL QUESTION: Here, we present a rare case of acquired FXD induced by valproic acid (VPA). This deficiency is associated with the presence of anti-FX antibodies.

CLINICAL APPROACH: A 65-year-old man undergoing treatment for various conditions, including chronic kidney disease and type 2 diabetes, developed severe FXD (activity <2 U/L) following VPA administration for epilepsy. During FXD, the patient experienced significant bleeding episodes, necessitating FX replacement with prothrombin complex concentrate. Upon discontinuation of VPA, FX activity improved in 9 days, possibly suggesting a role of the drug in FXD. Interestingly, antibodies directed against FX have been identified.

CONCLUSION: This case emphasizes the necessity for clinicians to be vigilant of hemostasis disorders associated with VPA, even though such occurrences are rare.

PMID:40206323 | PMC:PMC11981724 | DOI:10.1016/j.rpth.2025.102721

Cancer Innov. 2025 Apr 9;4(3):e70008. doi: 10.1002/cai2.70008. eCollection 2025 Jun.

ABSTRACT

BACKGROUND: The phosphoinositide 3-kinase (PI3K)/protein kinase B (PKB or AKT)/mammalian target of rapamycin (mTOR) signaling pathway (PAM pathway) plays a critical role in breast cancer pathogenesis and progression, and is closely linked with resistance to endocrine therapy in advanced breast cancer. Randomized clinical trials have shown that PI3K/AKT/mTOR inhibitors deliver significant clinical benefits, particularly for patients with advanced hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative breast cancer.

METHODS: In 2022, the Breast Cancer Expert Committee of the National Cancer Quality Control Center convened specialists in related fields to draft the "Expert Consensus on the Clinical Application of PI3K/AKT/mTOR Inhibitors in the Treatment of Advanced Breast Cancer." This consensus raised awareness of these inhibitors among oncologists in China and improved the precision of clinical decision-making. In recent years, growing evidence has emphasized the importance of targeting the PAM pathway, reflected in the approval of several innovative agents. This consensus is an updated 2025 edition that retains the foundational structure of the 2022 edition while incorporating notable updates.

RESULTS: Updates to the consensus include the introduction of newly approved PAM pathway inhibitors, updated data from recent clinical trials, and expanded therapeutic applications. The revised guidance also offers updated recommendations for genetic testing to detect alterations in relevant pathways. The section on managing drug-related adverse events has been significantly expanded, providing detailed insights into different types of adverse events and their management. These updates aim to enhance the clinical application of PAM pathway inhibitors, promote precision medicine, and ultimately, improve survival outcomes for patients with breast cancer.

PMID:40206206 | PMC:PMC11981814 | DOI:10.1002/cai2.70008

Front Pharmacol. 2025 Mar 26;16:1565480. doi: 10.3389/fphar.2025.1565480. eCollection 2025.

ABSTRACT

BACKGROUND: Herpes zoster severely impacts patients' quality of life and therapeutic results. This research utilized data from the FDA Adverse Event Reporting System (FAERS) to examine the prevalence and attributes of drug-induced herpes zoster.

METHODS: We analyzed FAERS reports about zoster from Q1 2004 to Q3 2024 and developed a list of possible pathogenic agents. Ranked the 30 medicines with the greatest incidence of reported herpes zoster cases. Statistical disproportionality analysis was employed to identify an elevated reporting frequency of herpes zoster linked to a particular medication.

RESULTS: Herpes zoster was referenced in 50,164 FAERS reports from 2004 to 2024. The majority of the implicated drugs were immunosuppressants. Anifrolumab exhibited the greatest ROR and PRR ratings among the drugs evaluated. Furthermore, rozanolixizumab, tozinameran, elapegademase, and other medications not indicated for inducing herpes zoster were recognized, underscoring the necessity for increased clinical vigilance and awareness. Nonetheless, these correlations should be regarded with caution, as they do not establish a direct causative relationship.

CONCLUSION: This study underscores the need of pharmacovigilance in recognizing and comprehending drug-induced herpes zoster. Additional research is required to validate these findings and to design strategies for risk management and reduction to enhance treatment outcomes in patients.

PMID:40206093 | PMC:PMC11979123 | DOI:10.3389/fphar.2025.1565480

Front Pharmacol. 2025 Mar 26;16:1508290. doi: 10.3389/fphar.2025.1508290. eCollection 2025.

ABSTRACT

BACKGROUND: Drug-induced liver injury (DILI) is the most common cause of acute liver injury. Anoectochilus roxburghii (Wall.) Lindl. (AR) and its polysaccharide fractions (ARPs) have been shown to have effective therapeutic effects with minimal side effects on a wide range of diseases including hepatopathy. This study aims to determine the therapeutic effects of ARPs on acetaminophen (APAP)-induced liver injury and to explore the mechanistic pathways involved.

METHODS: C57BL/6J male mice at 8 weeks were used to construct a model of APAP-induced liver injury. The acute hepatic injury was induced by oral administration of APAP (300 mg/kg) before 16 h fasting. For therapeutic experiment, mice were gavaged with the water extract of AR (AR.WE) or the purified ARPs before and after APAP administration. Biochemical analyses, ELISA analyses, H&E staining, RT-PCR, and Quantitative proteomic analysis were used to investigate the effects and mechanisms of AR on DILI.

RESULTS: Both AR.WE. and the purified ARPs treatment reduced APAP-induced liver injury, decreased hepatic glutathione and TNF-α levels, alleviated oxidative stress and inflammation. Quantitative proteomic analysis revealed that ARPs downregulated the protein levels involved in apoptosis, inflammation, oxidative stress, necroptosis, while upregulated the protein levels involved in autophagy. These protective effects of ARPs are possibly related to the downregulation of vATPase activity and thus participating in the autophagic process and ferroptosis.

CONCLUSION: ARPs can protect mice against APAP-induced liver injury, alleviate oxidative stress and inflammation. Our study reveals a potential therapeutic effect for ARPs in protecting APAP-induced liver injury.

PMID:40206085 | PMC:PMC11979217 | DOI:10.3389/fphar.2025.1508290

Orphanet J Rare Dis. 2025 Apr 10;20(1):169. doi: 10.1186/s13023-025-03673-9.

ABSTRACT

BACKGROUND: Individuals living with rare congenital malformations and/or intellectual disability often face challenges in accessing appropriate healthcare. Clinical practice guidelines (CPGs) may serve as a tool to provide evidence-based care for rare diseases, but their development is complex, and the views of affected individuals and families often remain unknown.

METHODS: Patient advocates of the European Reference Network ITHACA (Intellectual disability, TeleHealth, Autism and Congenital Anomalies) participated in focus groups in which their experiences with and perspectives on CPG use and development were discussed.

RESULTS: Patient advocates considered CPGs relevant to address information and care needs and support advocacy efforts. Important characteristics included representation of heterogeneity within conditions, a holistic approach in which and how topics are addressed, user-friendly availability for individuals and families, and reliability of information. Guideline development and implementation were described as challenging, iterative processes in which effective partnership between clinicians, patient advocates, and other stakeholders is essential.

CONCLUSIONS: Understanding the perspectives of patient advocates is essential to develop CPGs that meet the life-long and complex care needs of individuals and families living with rare conditions. Identified challenges include balancing the urgency of information needs with thorough guideline development processes, as well as the integration and interpretation of different types of knowledge.

PMID:40205602 | DOI:10.1186/s13023-025-03673-9

Breast Cancer Res. 2025 Apr 9;27(1):54. doi: 10.1186/s13058-025-02013-w.

ABSTRACT

OBJECTIVE: There are three categories of drugs that treat human epidermal growth factor receptor type 2 (HER-2) positive breast cancer: monoclonal antibodies (mAbs), antibody-drug conjugates (ADCs), and tyrosine kinase inhibitors (TKIs). The purpose of this study is to analyze and compare the adverse reactions of three classes of anti-HER-2 drugs to various body systems in patients based on the FDA Adverse Event Reporting System (FAERS).

METHODS: All data reports were extracted from the FAERS between 2004 and 2024. Data mining of adverse events associated with anti-HER-2 drugs was carried out using disproportionality analysis. A multivariate logistic regression analysis was conducted to explore the risk factors associated with AEs leading to hospitalization.

RESULTS: A total of 47,799 patients were screened for the three classes of drugs, among which ADC drugs caused the largest proportion of deaths. MAb has the strongest ADR signals associated with "cardiac disorders". Moreover, trastuzumab was associated with a greater risk of cardiotoxicity. Logistic regression analysis revealed that the treatment with mAbs should be wary of serious adverse reactions in "infections and infestations" and "metabolism and nutrition disorders". Moreover, "endocrine disorders" were the factor associated with the highest risk of prolonged hospitalization due to trastuzumab deruxtecan (T-DXd). The safety of tucatinib among TKI drugs is greater than that of other drugs.

CONCLUSION: In general, from the perspective of the effects of the three classes of drugs on the various body systems of patients, we should focus on mAb-associated "cardiac disorders", ADC-associated "hepatobiliary disorders", "respiratory, thoracic and mediastinal disorders", and TKI-associated "gastrointestinal disorders.

PMID:40205546 | DOI:10.1186/s13058-025-02013-w

Sci Rep. 2025 Apr 9;15(1):12089. doi: 10.1038/s41598-025-96618-y.

ABSTRACT

To explore the value of applying the MRI-based radiomic nomogram for predicting lymph node metastasis (LNM) in rectal cancer (RC). This retrospective analysis used data from 430 patients with RC from two medical centers. The patients were categorized into the LNM negative (LNM-) and LNM positive (LNM+) according to their surgical pathology results. We developed a physician model by selecting clinical independent predictors through physician assessments. Additionally, we developed deep learning radscore (DLRS) models by extracting deep features from multiparametric MRI (mpMRI) images. A nomogram model was constructed by combining the physician model and DLRS models. Among the patients, 192 (44.65%, 192/430) experienced LNM+. Six prediction models were developed, namely the physician model, three sequence models, the DLRS, and the nomogram. The physician model achieved AUC of the receiver operating characteristic (ROC) values of 0.78, 0.79, and 0.7, whereas the sequence models, DLRS model, and nomogram model achieved AUC values ranging from 0.83 to 0.99. The predictive performance of the DLRS and nomogram models was superior to that of the physician model. DLRS and nomogram models based on mpMRI provided higher accuracy in predicting LNM status in patients with RC than the other models.

PMID:40204902 | DOI:10.1038/s41598-025-96618-y

Sci Rep. 2025 Apr 9;15(1):12204. doi: 10.1038/s41598-025-95767-4.

ABSTRACT

Transcranial Magnetic Stimulation (TMS) is a non-invasive method to modulate neural activity by inducing an electric field in the human brain. Computational models are an important tool for informing TMS targeting and dosing. State-of-the-art modeling techniques use numerical methods, such as the finite element method (FEM), to produce highly accurate simulation results. However, these methods operate at a high computational cost, limiting real-time integration and high throughput applications. Deep learning (DL) methods, particularly U-Nets, are being investigated for TMS electric field estimations. However, their performance across large datasets and whole-head stimulation conditions has not been systematically evaluated. Here, we develop a DL framework to estimate TMS-induced electric fields directly from an anatomical magnetic resonance image (MRI) and TMS coil parameters. We perform a comprehensive evaluation of the performance of our U-Net approach compared to the FEM gold standard. We selected a dataset of 100 MRI scans from a diverse population demographic (ethnic, gender, age) made available by the Human Connectome Project. For each MRI, we generated a FEM head model and simulated the electric fields for 13 TMS coil orientations and 1206 positions (a total of 15,678 coil configurations per participant). We trained a modified U-Net architecture to predict individual TMS-induced electric fields in the brain based on an input T1-weighted MRI scan and stimulation parameters. We characterized the model's performance according to computational efficiency and simulation accuracy compared to FEM using an independent testing dataset. The U-Net results demonstrated an accelerated electric field modeling speed at 0.8 s per simulation (×97,000 times acceleration over the FEM-based approach). Sampling stimulation conditions across the whole brain yielded an average DICE coefficient of 0.71 ± 0.06 mm and an average center of gravity deviation of 7.52 ± 4.06 mm from the FEM-based approach. Our findings indicate that while deep learning has the potential to significantly accelerate electric field predictions, the precision it achieves needs to be evaluated for the specific TMS application.

PMID:40204769 | DOI:10.1038/s41598-025-95767-4

Neuroscience. 2025 Apr 7:S0306-4522(25)00287-8. doi: 10.1016/j.neuroscience.2025.04.010. Online ahead of print.

ABSTRACT

Cerebral vascular occlusion is a serious condition that can lead to stroke and permanent neurological damage due to insufficient oxygen and nutrients reaching brain tissue. Early diagnosis and accurate segmentation are critical for effective treatment planning. Due to its high soft tissue contrast, Magnetic Resonance Imaging (MRI) is commonly used for detecting these occlusions such as ischemic stroke. However, challenges such as low contrast, noise, and heterogeneous lesion structures in MRI images complicate manual segmentation and often lead to misinterpretations. As a result, deep learning-based Computer-Aided Diagnosis (CAD) systems are essential for faster and more accurate diagnosis and treatment methods, although they can sometimes face challenges such as high computational costs and difficulties in segmenting small or irregular lesions. This study proposes a novel U-Net architecture enhanced with ConvNeXtV2 blocks and GRN-based Multi-Layer Perceptrons (MLP) to address these challenges in cerebral vascular occlusion segmentation. This is the first application of ConvNeXtV2 in this domain. The proposed model significantly improves segmentation accuracy, even in low-contrast regions, while maintaining high computational efficiency, which is crucial for real-world clinical applications. To reduce false positives and improve overall accuracy, small lesions (≤5 pixels) were removed in the preprocessing step with the support of expert clinicians. Experimental results on the ISLES 2022 dataset showed superior performance with an Intersection over Union (IoU) of 0.8015 and a Dice coefficient of 0.8894. Comparative analyses indicate that the proposed model achieves higher segmentation accuracy than existing U-Net variants and other methods, offering a promising solution for clinical use.

PMID:40204150 | DOI:10.1016/j.neuroscience.2025.04.010

Pharmacogenomics J. 2025 Apr 9;25(3):8. doi: 10.1038/s41397-025-00368-z.

ABSTRACT

This review offers an overview of advanced in silico methods crucial for drug discovery, emphasizing their integration with data science, and investigates the effectiveness of data science, machine learning, and artificial intelligence via a thorough meta-analysis of existing technologies. This meta-analysis aims to rank these technologies based on their applications and accessibility of knowledge. Initially, a search strategy yielded 900 papers, which were then refined into two subsets: the top 300 most-cited papers since 2000 and papers selected for systematic review based on high impact. From these, 97 articles were identified for discussion, categorized by their influence on society. The focus remains on the qualitative impact of these disciplines rather than solely on metrics like new drug approvals. Ultimately, the review underscores the role of big data in enhancing our comprehension of drug candidate trajectories from development to commercialization, utilizing information stored in publicly available databases to chemical space. Graphical extrapolation of some keywords (Drug Discovery; Big Data; Database; Metadata) discussed in this article and their evolution (in terms of absolute items that are available) by time.

PMID:40204715 | DOI:10.1038/s41397-025-00368-z

Mol Metab. 2025 Apr 7:102136. doi: 10.1016/j.molmet.2025.102136. Online ahead of print.

ABSTRACT

Recent modifications to glucagon-like peptide 1 (GLP-1), known for its insulinotropic and satiety-inducing effects, have focused on conjugating small molecules to enable selective delivery into GLP-1R+ tissues to achieve targeted synergy and improved metabolic outcomes. Despite continued advancements in GLP-1/small molecule conjugate strategies, the intracellular mechanisms facilitating concurrent GLP-1R signaling and small molecule cargo release remain poorly understood. We evaluate an estradiol (E2)-conjugated GLP-1 (GLP-1-CEX/E2) for relative differences in GLP-1R signaling and trafficking, and elucidate endolysosomal dynamics that lead to estrogenic activity using various live-cell, reporter, imaging, and mass-spectrometry techniques. We find GLP-1-CEX/E2 does not differentially activate or traffic the GLP-1R relative to its unconjugated GLP-1 backbone (GLP-1-CEX), but uniquely internalizes the E2 moiety and stimulates estrogenic signaling. Endolysosomal pH-dependent proteolytic activity likely mediates E2 moiety liberation, as evidenced by clear amplification in estrogenic activity following co-administration with lysosomal VATPase activator EN6. The hypothesized liberated metabolite from GLP-1-CEX/E2, E2-3-ether, exhibits partial estrogenic efficacy through ERα, and is predisposed toward estrone-3-sulfate conversion. Finally, we identify relative increases in intracellular E2, estrone, and estrone-3-sulfate following GLP-1-CEX/E2 incubation in GLP-1R+ cells, demonstrating proof-of-principle for desired cargo release. Together, our data suggest that GLP-1-CEX/E2 depends on GLP-1R trafficking and lysosome acidification for estrogenic efficacy, with a likely conversion of the liberated E2-3-ether metabolite into estrone-3-sulfate, resulting in residual downstream flux into active estradiol. Our current findings aim to improve the understanding of small molecule targeting and the efficacy behind GLP-1/small molecule conjugates.

PMID:40204014 | DOI:10.1016/j.molmet.2025.102136

BMC Microbiol. 2025 Apr 9;25(1):203. doi: 10.1186/s12866-025-03920-w.

ABSTRACT

BACKGROUND: Pseudomonas aeruginosa is a major pathogen in cystic fibrosis (CF), where chronic and intermittent infections significantly affect patient outcomes. This study aimed to investigate the molecular epidemiology of P. aeruginosa in CF patients from the Brazilian Amazon, focusing on genotypic diversity, resistance profiles, and virulence factors.

METHODS: A cross-sectional study included 72 P. aeruginosa isolates from 44 CF patients treated at a regional reference center between 2018 and 2019. Antimicrobial susceptibility patterns were determined using VITEK-2 system and Kirby-Bauer disk diffusion. Virulotypes were defined by molecular detection of exoS, exoU, exoT, exoY, algU, and algD genes. Genetic diversity was assessed using multilocus sequence typing (MLST). Demographic data, clinical severity, and spirometry results were also collected.

RESULTS: Among the patients, 54.55% experienced intermittent infections, while 45.45% had chronic infections. Chronic infections were associated with older age, lower FEV1, and reduced Shwachman-Kulczycki scores. Multidrug resistance was observed in 15.3% of isolates, particularly against ciprofloxacin and piperacillin/tazobactam. The exoU gene was present in 55.56% of isolates, an uncommon finding in CF populations. High genetic diversity was evident, with 37 sequence types (STs), including 14 novel STs. High-risk clones (HRCs) constituted 25% of isolates, with ST274 being the most prevalent (12.5%). Longitudinal analysis revealed transient colonization in intermittent infections, while chronic infections were dominated by stable clones.

CONCLUSION: This study highlights the molecular and clinical dynamics of P. aeruginosa in CF patients from the Brazilian Amazon. Chronic infections were linked to severe lung impairment , while intermittent infections were dominated by HRCs. These findings underscore the need for robust genotypic surveillance to mitigate the burden of P. aeruginosa in CF populations.

PMID:40205346 | DOI:10.1186/s12866-025-03920-w

Respir Med. 2025 Apr 7:108086. doi: 10.1016/j.rmed.2025.108086. Online ahead of print.

ABSTRACT

This study evaluates the clinical impact of transitioning from the GLI 2012 to the race-neutral GLI 2022 spirometry equations in people with cystic fibrosis (pwCF). Spirometry data from a large adult CF centre showed an increase in average ppFEV1 (71.1% to 75%, p<0.01), with White patients showing the greatest change (4.56%). Fewer patients met lung transplantation thresholds, and 1.7% became newly eligible for clinical trials, while 7% became ineligible. These findings suggest the need for further research on the long-term implications of GLI 2022 across respiratory conditions.

PMID:40204244 | DOI:10.1016/j.rmed.2025.108086

J Transl Med. 2025 Apr 9;23(1):412. doi: 10.1186/s12967-025-06428-z.

ABSTRACT

BACKGROUND: Malignant digestive tract tumors are highly prevalent and fatal tumor types globally, often diagnosed at advanced stages due to atypical early symptoms, causing patients to miss optimal treatment opportunities. Traditional endoscopic and pathological diagnostic processes are highly dependent on expert experience, facing problems such as high misdiagnosis rates and significant inter-observer variations. With the development of artificial intelligence (AI) technologies such as deep learning, real-time lesion detection with endoscopic assistance and automated pathological image analysis have shown potential in improving diagnostic accuracy and efficiency. However, relevant applications still face challenges including insufficient data standardization, inadequate interpretability, and weak clinical validation.

OBJECTIVE: This study aims to systematically review the current applications of artificial intelligence in diagnosing malignant digestive tract tumors, focusing on the progress and bottlenecks in two key areas: endoscopic examination and pathological diagnosis, and to provide feasible ideas and suggestions for subsequent research and clinical translation.

METHODS: A systematic literature search strategy was adopted to screen relevant studies published between 2017 and 2024 from databases including PubMed, Web of Science, Scopus, and IEEE Xplore, supplemented with searches of early classical literature. Inclusion criteria included studies on malignant digestive tract tumors such as esophageal cancer, gastric cancer, or colorectal cancer, involving the application of artificial intelligence technology in endoscopic diagnosis or pathological analysis. The effects and main limitations of AI diagnosis were summarized through comprehensive analysis of research design, algorithmic methods, and experimental results from relevant literature.

RESULTS: In the field of endoscopy, multiple deep learning models have significantly improved detection rates in real-time polyp detection, early gastric cancer, and esophageal cancer screening, with some commercialized systems successfully entering clinical trials. However, the scale and quality of data across different studies vary widely, and the generalizability of models to multi-center, multi-device environments remains to be verified. In pathological analysis, using convolutional neural networks, multimodal pre-training models, etc., automatic tissue segmentation, tumor grading, and assisted diagnosis can be achieved, showing good scalability in interactive question-answering. Nevertheless, clinical implementation still faces obstacles such as non-uniform data standards, lack of large-scale prospective validation, and insufficient model interpretability and continuous learning mechanisms.

CONCLUSION: Artificial intelligence provides new technological opportunities for endoscopic and pathological diagnosis of malignant digestive tract tumors, achieving positive results in early lesion identification and assisted decision-making. However, to achieve the transition from research to widespread clinical application, data standardization, model reliability, and interpretability still need to be improved through multi-center joint research, and a complete regulatory and ethical system needs to be established. In the future, artificial intelligence will play a more important role in the standardization and precision management of diagnosis and treatment of digestive tract tumors.

PMID:40205603 | DOI:10.1186/s12967-025-06428-z

Br J Radiol. 2025 Apr 9:tqaf077. doi: 10.1093/bjr/tqaf077. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the radiation and contrast dose reduction potential of combining 70 kV with deep learning image reconstruction(DLIR) in coronary computed tomography angiography(CCTA) for slender patients with body-mass-index (BMI)≤25kg/m2.

METHODS: Sixty patients for CCTA were randomly divided into two groups: group A with 120 kV and contrast agent dose of 0.8 ml/kg, and group B with 70 kV and contrast agent dose of 0.5 ml/kg.Group A used adaptive statistical iterative reconstruction-V(ASIR-V) with 50% strength level(50%ASIR-V) while group B used 50%ASIR-V, DLIR of low level(DLIR-L),DLIR of medium level(DLIR-M) and DLIR of high level(DLIR-H) for image reconstruction. The CT values and SD values of coronary arteries and pericardial fat were measured, and signal-to-noise ratio(SNR) and contrast-to-noise ratio(CNR) were calculated. The image quality was subjectively evaluated by two radiologists using a five-point scoring system. The effective radiation dose(ED) and contrast dose were calculated and compared.

RESULTS: Group B significantly reduced radiation dose by 75.6% and contrast dose by 32.9% compared to group A. Group B exhibited higher CT values of coronary arteries than group A, and DLIR-L, DLIR-M and DLIR-H in group B provided higher SNR values and CNR values and subjective scores, among which DLIR-H had the lowest noise and highest subjective scores.

CONCLUSION: Using 70 kV combined with DLIR significantly reduces radiation and contrast dose while improving image quality in CCTA for slender patients with DLIR-H having the best effect on improving image quality.

ADVANCES IN KNOWLEDGE: The 70 kV and DLIR-H may be used in CCTA for slender patients to significantly reduce radiation dose and contrast dose while improving image quality.

PMID:40205479 | DOI:10.1093/bjr/tqaf077