Standard Sequence Research Articles

Whole Brain MRI Assessment of Age and Sex-Related R2* Changes in the Human Fetal Brain.

Iron in the brain is essential to neurodevelopmental processes, as it supports neural functions, including processes of oxygen delivery, electron transport, and enzymatic activity. However, the development of brain iron before birth is scarcely understood. By estimating R2* (1/T2*) relaxometry from a sizable sample of fetal multiecho echo-planar imaging (EPI) scans, which is the standard sequence for functional magnetic resonance imaging (fMRI), across gestation, this study investigates age and sex-related changes in iron, across regions and tissue segments. Our findings reveal that brain R2* levels significantly increase throughout gestation spanning many different regions, except the frontal lobe. Furthermore, females exhibit a faster rate of R2* increase compared to males, in both gray matter and white matter. This sex effect is particularly notable within the left insula. This work represents the first MRI examination of iron accumulation and sex differences in developing fetal brains. This is also the first study to establish R2* estimation methodology in fetal multiecho functional MRI.

P-2129. Analytical Validation of a Next-Generation Sequencing Assay for the Detection of Microbial Pathogens in Human Plasma

Abstract Background Fungal and acid-fast bacteria (AFB) infections can be a serious complication for immunosuppressed patients. Identification of the pathogen involved in invasive fungal/AFB infections (IFIs) can allow for reduced time to initiation of the appropriate targeted therapy through elimination of ineffective therapies. Current fungal/AFB diagnostics suffer from low sensitivity/specificity, invasiveness (e.g., biopsy or antigen), have long turnaround times (e.g., culture), and/or require an a priori hypothesis regarding the causative pathogen (e.g., PCR based methods). To overcome shortcomings in fungal/AFB diagnostics, an unbiased next-generation sequencing (NGS) approach can be utilized to characterize pathogen cfDNA present in a patient blood sample. Methods Sequencing of IFIs through hybrid capture has the potential to detect a broad range of pathogens yet can still specifically target the most clinically relevant. Compared to standard whole-genome sequencing methods, hybrid capture followed by NGS can be more specific and sensitive due to an enrichment step using probes specific to cfDNA targets of interest. This additional enrichment step can result in more sequencing reads being dedicated to cfDNA derived from pathogens of interest rather than to cfDNA derived from non-relevant organisms. Here is described a hybrid capture assay that uses >30,000 probes to detect >600 Fungal and select AFB species in plasma. Results Cutoffs for target coverage and kmers/million were established through ROC analysis of 170 contrived plasma samples resulting in an analytical specificity of ∼96% and a sensitivity of ∼1,200 molecules/mL. 98% of the 40 contrived samples used for accuracy were correctly identified while 100% intra- and 93%-inter assay precision was achieved. In silico validation demonstrated the assay’s ability to detect closely related species unable to be tested at the bench. Several species have been detected in the initial clinical samples received thus far, however, all have been below the reportable cutoff values. Conclusion The analytical validation described here demonstrates the analytical performance of hybrid capture in human plasma. Disclosures Curtis Bacon, PhD, Eurofins Viracor: employee Ellis Bixler, n/a, Eurofins Viracor: Employee Scott Cowden, n/a, Eurofins Viracor: Employee Jamie Nutt, n/a, Eurofins Viracor: Employee Steve Kleiboeker, PhD, Eurofins: employee|Eurofins: Stocks/Bonds (Public Company)

A sequencing-based method for quantifying gene-deletion mutants of bacteria in the intracellular environment

Advancements in next-generation sequencing (NGS) have significantly accelerated the development of innovative methodologies in microbiological research. In this study, we present a novel method to quantify the net survival of gene-deletion mutants within the intracellular environment. Based on standardized Illumina short-read sequencing of genomic DNA, the method eliminates the need for specific selective markers on each deletion mutant. For validation, the method was shown to accurately quantify mutants in spiked pools of mixed mutants, showing no statistically significant differences compared to the expected values based on CFU determination (p > 0.05). Further, the method was used to quantify mutants of S. Gallinarum in macrophages. Six mutants and one control strain were mixed in a pool and allowed to infect HD11 cells for 2 h. The results align with prior research results, providing evidence of the feasibility of mixed mutant infections in functional gene identification. Notably, the simplicity and standardization of the method, rooted in standard whole-genome sequencing protocols, make it easily implementable across various laboratories.

Fast and reliable quantitative measures of white matter development with magnetic resonance fingerprinting

Abstract Developmental cognitive neuroscience aims to shed light on evolving relationships between brain structure and cognitive development. To this end, quantitative methods that reliably measure individual differences in brain tissue properties are fundamental. Standard qualitative MRI sequences are influenced by scan parameters and hardware-related biases, and also lack physical units, making the analysis of individual differences problematic. In contrast, quantitative MRI can measure physical properties of the tissue but with the cost of long scan durations and sensitivity to motion. This poses a critical limitation for studying young children. Here, we examine the reliability of an efficient quantitative multiparameter mapping method - Magnetic Resonance Fingerprinting (MRF) - in children scanned longitudinally. We focus on T1 values in white matter, since quantitative T1 values are known to primarily reflect myelin content, a key factor in brain development. Forty-nine children aged 8-13y (mean 10.3y ±1.4) completed two scanning sessions 2-4 months apart. In each session, two 2-minute 3D-MRF scans at 1mm isotropic resolution were collected to evaluate the effect of scan duration on image quality and scan-rescan reliability. A separate calibration scan was used to measure B0 inhomogeneity and correct for bias. We examined the impact of scan time and B0 inhomogeneity correction on scan-rescan reliability of values in white matter, by comparing single 2-min and combined two 2-min scans, with and without B0-correction. Whole-brain voxel-based reliability analysis showed that combining two 2-min MRF scans improved reliability (pearson’s r=0.87) compared with a single 2-min scan (r=0.84), while B0-correction had no effect on reliability in white matter (r=0.86 and 0.83 4-min vs 2-min). Using diffusion tractography, we segmented major white matter fiber tracts and examined the profiles of MRF-derived T1 values along each tract. We found that T1 values from MRF showed similar or greater reliability compared with diffusion parameters. Lastly, we found that R1 (1/T1) values in multiple white matter tracts were significantly correlated with age. In sum, MRF-derived T1 values were highly reliable in a longitudinal sample of children and replicated known age effects. Reliability in white matter was improved by longer scan duration but was not affected by B0-correction, making it a quick and straightforward scan to collect. We propose that MRF provides a promising avenue for acquiring quantitative brain metrics in children and patient populations where scan time and motion are of particular concern.

Machine learning reveals the dynamic importance of accessory sequences for Salmonella outbreak clustering.

Gene-by-gene typing is widely used to detect clusters of foodborne illnesses that share a common origin. It remains actively debated whether the inclusion of accessory sequences in bacterial typing schema is informative or deleterious for cluster definitions in outbreak investigations due to the potential confounding effects of horizontal gene transfer. By training machine learning models on a curated set of historical Salmonella outbreaks, we revealed an enriched presence of outbreak distinguishing features in a wide range of mobile genetic elements. Systematic comparison of the efficacy of clustering different accessory elements against standard sequence typing methods led to our cataloging of scenarios where accessory sequence variations were beneficial and uninformative to resolving outbreak clusters. The presented work underscores the complexity of the molecular trends in enteric outbreaks and seeks to inspire novel computational ways to exploit whole-genome sequencing data in enteric disease surveillance and management.

Deep learning classification of MGMT status of glioblastomas using multiparametric MRI with a novel domain knowledge augmented mask fusion approach

We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used. A comprehensive mask fusion approach was developed to select relevant image crops of diseased tissue. These fusion masks, which were guided by multiple sequences, helped collect information from the regions that seem disease-free to radiologists in standard MRI sequences while harboring pathology. Integrating the information in different MRI sequences and leveraging the high entropic capacity of deep neural networks, we built a 3D ROI-based custom CNN classifier for the automatic prediction of MGMT methylation status of glioblastoma in multi-parametric MRI. Single sequence-based classifiers reached intermediate predictive performance with 0.65, 0.71, 0.77, and 0.82 accuracy for T1W, T2W, T1 contrast-enhanced, and FLAIR sequences, respectively. The multiparametric classifier using T1 contrast-enhanced and FLAIR images reached 0.88 accuracy. The accuracy of the four-input model that used all sequences was 0.81. The best model reached 0.90 ROC AUC value. Integrating human knowledge in the form of relevant target selection was a useful approach in MGMT methylation status prediction in MRI. Exploration of means to integrate radiology knowledge into the models and achieve human-machine collaboration may help to develop better models. MGMT methylation status of glioblastoma is an important prognostic marker and is also important for treatment decisions. The preoperative non-invasive predictive ability and the explanation tools of the developed model may help clinicians to better understand imaging phenotypes of MGMT methylation status of glial tumors.

Perivascular and parenchymal brain fluid diffusivity in patients with a recent small subcortical infarct.

Fluid exchanges between perivascular spaces (PVS) and interstitium may contribute to the pathophysiology of small vessel disease (SVD). We aimed to analyze water diffusivity measures and their relationship with PVS and other SVD imaging markers. We enrolled 50 consecutive patients with a recent small subcortical infarct. We collected clinical variables, including vascular risk factors and sleep quality scales. All patients underwent a 3-Tesla MRI with standard structural sequences and multishell-diffusion images to obtain extracellular free water content (FW) and water diffusivity along the perivascular space (ALPS) index. We obtained volumetric measurements of white matter hyperintensities (WMH) and PVS, and the number of lacunes and microbleeds. To analyze the association between PVS, ALPS index, FW, and SVD imaging features, we utilized linear regression models including age, sex, history of hypertension and diabetes, Pittsburgh Sleep Quality Index, WMH, and brain volume. All patients (mean age 70 years, 36% women) had usable data. FW and PVS were strongly associated in all models (0.008 < Beta < 0.054; P < 0.045). Higher FW was related to the other SVD features in univariable models and remained significant for WMH (1.175 < Beta < 1.262; P < 0.001) and brain volume (Beta < 0.0001; P < 0.002) in multivariable models. ALPS index was not associated with FW, PVS, or any other SVD markers. The increased extracellular water in SVD suggests that impaired brain fluid exchanges, PVS dilation, and other SVD features are linked. Further investigation is needed to determine the specificity of the ALPS index to PVS diffusion.

Improved detection of brain metastases using contrast-enhanced 3D black-blood TSE sequences compared to post-contrast 3D T1 GRE: a comparative study on 1.5-T MRI.

Brain metastases are the most common intracranial malignancy in adults, and their detection is crucial for treatment planning. Post-contrast 3D T1 gradient-recalled echo (GRE) sequences are commonly used for this purpose, but contrast-enhanced 3D T1 turbo spin-echo (TSE) sequences with motion-sensitized driven-equilibrium (MSDE) technique ("black blood") may offer improved detection. This study aimed to compare the effectiveness of contrast-enhanced 3D black blood sequences to standard 3D T1 GRE sequences in detecting brain metastases on a 1.5-T MRI. A retrospective analysis of 183 patients with suspected or follow-up brain metastases between May 2022 and September 2023 was conducted. Among these patients, 107 were included in the final analysis. Both post-contrast 3D T1 GRE and 3D black blood sequences were acquired on the same scanner with similar acquisition times. Two neuroradiologists independently evaluated the images for the number, size, and location of metastases. Interobserver variability and statistical analysis were performed. Among the 107 patients (mean age 60.8 years ± 13.2 years; 55 males, 52 females), 3D black blood sequences detected a significantly higher number of brain metastases, particularly small lesions (< 5 mm), compared to 3D T1 GRE sequences (p < 0.05). There was no significant difference in detecting large metastases (≥ 5 mm) between the sequences. In addition, the black blood sequences provided better conspicuity of metastases in the majority of patients (85%). Contrast-enhanced 3D T1 TSE with MSDE ("black blood") sequences offer improved detection of brain metastases, especially small lesions, on 1.5-T MRI compared to standard 3D T1 GRE sequences. Question Accurate identification of the number and location of brain metastases using MRI is essential for planning and managing effective treatment. Findings Contrast-enhanced 3D T1 TSE black blood sequences detected significantly more small brain metastases than standard 3D T1 GRE sequences on 1.5-T MRI. Clinical relevance The use of 3D black blood sequences on 1.5-T MRI may have the potential to improve the accuracy of detection of brain metastases, leading to better treatment planning and potentially improved patient outcomes.

The origin and transmission of HIV-1 CRF80_0107 among two major first-tier cities in China

BackgroundCRF01_AE and CRF07_BC are the two most prevalent HIV-1 genotypes in China, and the co-circulation of these two genotypes has led to the continuous generation of CRF_0107 viruses in recent years. However, little is known about the origin and spread of CRF_0107 viruses thus far. This study focused on HIV-1 CRF80_0107, which we previously identified among the MSM population in Beijing and Hebei Province, to explore the demographic distribution, transmission links, and temporal-spatial evolutionary features of the HIV-1 CRF80_0107 strain in China.MethodsWith the partial pol region fragment of the HIV-1 CRF80_0107 subtype standard sequence as a reference, BLAST was used to search for highly similar sequences in the Los Alamos HIV Sequence Database, followed by preliminary subtype identification via COMET. Further phylogenetic and recombination breakpoint analyses were conducted to verify the subtypes and recombination patterns. We also performed a distance-based molecular network analysis to identify potential relationships among different HIV-positive individuals. In addition, spatiotemporal evolutionary dynamics analysis of the candidate CRF80_0107 sequences was performed via a Bayesian approach.ResultsA total of 36 partial pol gene sequences of HIV-1 CRF80_0107 were identified from 2009 to 2018 from 5 provinces in China. Phylogenetic and spatial-temporal dynamics analyses indicated that CRF80_0107 likely originated in Beijing around 2009 and spread to Guangdong Province around 2012. Population dynamics analysis revealed that CRF80_0107 experienced a significant increase in population size from 2009 to 2011 and then stabilized. The study also found that the number of cases in Guangdong Province was second only to that in Beijing and formed 2 relatively independent transmission clusters in the MSM population in Shenzhen, Guangdong Province.ConclusionsThe HIV-1 CRF80_0107 strain has spread to cities beyond its origin, particularly the MSM population in Shenzhen city, Guangdong Province, which is an area with a high incidence of HIV. This highlights the importance of continuous monitoring for the emergence and dynamic changes of novel HIV-1 recombinant viruses and the necessity of implementing effective preventive measures targeting specific populations in particular regions.

Improved Image Quality Through Deep Learning Acceleration of Gradient-Echo Acquisitions in Uterine MRI: First Application with the Female Pelvis.

The aim of this study was to compare the image quality of a deep learning (DL)-accelerated volumetric interpolated breath-hold examination (VIBE) sequence with a standard (ST) VIBE sequence in assessing the uterus. Between April and December 2023, a total of 61 female patients (aged 41 ± 14 years) who were referred for anmagnetic resonance imaging (MRI) of the pelvis were included in this prospective study, after providing informed consent. All examinations were performed with a 1.5T MRI scanner. The DL VIBE and ST VIBE were acquired before (noncontrast [NC]) and after (contrast-enhanced [CE]) contrast administration in the sagittal orientation. Three readers independently evaluated the following aspects of the images' quality using 4-point Likert scales (1 = nondiagnostic; 4 = excellent): global image quality, anatomy delineation, and lesion detection/demarcation. Motion artifacts and noise were also assessed (1 = no artifacts; 4 = severe artifacts). In addition, all three readers selected their preferred sequence and the sequence in which they had the highest diagnostic confidence. After exclusions, the data for 54 patients were analyzed. The DL VIBE was preferred by all three readers in almost all cases (NC: 99%; CE: 96%) and rated highest for diagnostic confidence (NC: 98%; CE: 90%). The image quality of the DL VIBE was rated statistically significantly better than that of the ST VIBE, with simultaneously reduced noise and motion artifacts (p < 0.01). The image quality of the DL VIBE was predominantly rated with a score of 4 (NC: 54%; CE: 78%), while the image quality of the ST VIBE was mostly rated with a score of 3 (NC: 53%; CE: 80%). The anatomy of the female pelvis was significantly better delineated by the DL VIBE (p < 0.01; log[OR] = 5.3; 95% CI: 3.7-6.8), and lesions were more clearly demarcated (p < 0.01; log[OR] = 6.7; 95% CI: 4.5-8.8). The DL VIBE sequence showed a significant overall improvement in all image quality characteristics for all readers and was preferred in most cases. The clinical implementation of DL VIBE in MRI of the female pelvis could improve the diagnostic value of the examination.

Photoluminescence and Photocurrent from InGaN/GaN Diodes with Quantum Wells of Different Widths and Polarities.

We compare the optical properties of four pin diode samples differing by built-in field direction and width of the In0.17Ga0.83N quantum well in the active layer: two diodes with standard nip layer sequences and 2.6 and 15 nm well widths and two diodes with inverted pin layer ordering (due to the tunnel junction grown before the pin structure) also with 2.6 and 15 nm widths. We study photoluminescence and photocurrent in those samples (as a function of excitation power and applied voltage), revealing very different properties due to the interplay of built-in fields and screening by injected carriers. Out of the four types of diodes, the highest photocurrent efficiency was obtained (at reverse voltage) for the wide-well, inverted polarity diode. This diode also showed the highest PL intensity (at positive voltages) of our four samples. Diodes with wide wells have stable emission wavelengths (almost independent of bias and excitation power).

Impact of Subarachnoid Hemorrhage on Human Glymphatic Function: A Time-Evolution Magnetic Resonance Imaging Study.

Subarachnoid hemorrhage (SAH) is associated with significant mortality and morbidity. The impact of SAH on human glymphatic function remains unknown. This prospective, controlled study investigated whether human glymphatic function is altered after SAH, how it differs over time, and possible underlying mechanisms. Glymphatic enrichment was examined by intrathecal contrast-enhanced magnetic resonance imaging (MRI, glymphatic MRI), utilizing the MRI contrast agent gadobutrol (Gadovist, Bayer AG, GE; 0.50 mmol) as a cerebrospinal fluid (CSF) tracer. The distribution of the tracer in the brain and the subarachnoid and ventricular CSF spaces was assessed using standardized multi-phase MRI T1 sequences, and between-group differences in percentage change of standardized T1 signal unit ratios over time were analyzed by linear mixed models. The study comprised 27 patients with SAH (19 female/8 male; 59.3±10.2 years) who were examined <3 months (n=5), 3 to 6 months (n=10), 6 to 12 months (n=5), or >12 months (n=7) after bleed. A sex- and age-matched control group of 22 individuals (15 female/7 male; 55.5±10.5 years) underwent the same glymphatic MRI protocol but had no neurological or CSF disease. The patients with SAH showed a marked impairment of glymphatic enrichment throughout the brain (particularly addressing the cerebral cortex and subcortical white matter), especially after 24 hours. The glymphatic impairment was accompanied by redistribution of CSF tracer from subarachnoid spaces toward ventricles. These alterations were most pronounced after 3 to 6 months and less after 12 months, though with interindividual variation. CSF tracer transport within perivascular subarachnoid spaces was impaired and coincided with impaired glymphatic enrichment. Human glymphatic function is severely impaired by SAH, particularly shortly after the event. Glymphatic failure is associated with redistribution of CSF from subarachnoid spaces toward ventricles. SAH-related impairment of fluid transport within perivascular subarachnoid spaces may contribute to reduced glymphatic influx. Since patient groups are small, care should be made when concluding about the impact of time on glymphatic function.

Accelerated High-resolution T1- and T2-weighted Breast MRI with Deep Learning Super-resolution Reconstruction.

To assess the performance of an industry-developed deep learning (DL) algorithm to reconstruct low-resolution Cartesian T1-weighted dynamic contrast-enhanced (T1w) and T2-weighted turbo-spin-echo (T2w) sequences and compare them to standard sequences. Female patients with indications for breast MRI were included in this prospective study. The study protocol at 1.5 Tesla MRI included T1w and T2w. Both sequences were acquired in standard resolution (T1S and T2S) and in low-resolution with following DL reconstructions (T1DL and T2DL). For DL reconstruction, two convolutional networks were used: (1) Adaptive-CS-Net for denoising with compressed sensing, and (2) Precise-Image-Net for resolution upscaling of previously downscaled images. Overall image quality was assessed using 5-point-Likert scale (from 1=non-diagnostic to 5=excellent). Apparent signal-to-noise (aSNR) and contrast-to-noise (aCNR) ratios were calculated. Breast Imaging Reporting and Data System (BI-RADS) agreement between different sequence types was assessed. A total of 47 patients were included (mean age, 58±11 years). Acquisition time for T1DL and T2DL were reduced by 51% (44 vs. 90s per dynamic phase) and 46% (102 vs. 192s), respectively. T1DL and T2DL showed higher overall image quality (e.g., 4 [IQR, 4-4] for T1S vs. 5 [IQR, 5-5] for T1DL, P<0.001). Both, T1DL and T2DL revealed higher aSNR and aCNR than T1S and T2S (e.g., aSNR: 32.35±10.23 for T2S vs. 27.88±6.86 for T2DL, P=0.014). Cohen k agreement by BI-RADS assessment was excellent (0.962, P<0.001). DL for denoising and resolution upscaling reduces acquisition time and improves image quality for T1w and T2w breast MRI.

Exploring local microbial communities in adenoids through 16S rRNA gene sequencing

Objective:To explore the hypothesis of "pathogen storage pool" by analyzing the local microbial community of adenoids. Methods:Under the guidance of a 70° nasal endoscope, sterile swabs were used to collect secretions from the adenoid crypts of the subjects. The samples were sent to the laboratory for DNA extraction and standard bacterial 16S full-length sequencing analysis. Results:At the species level, the top three microbial communities in adenoid crypts were Bacillus subtilis（18.78%）, Fusobacterium pyogenes（11.42%）, and Streptococcus pneumoniae（9.38%）. Conclusion:The local microbial community of adenoids exhibits a high degree of diversity, including microbial communities from the oral cavity and gastrointestinal tract. Our research results support the hypothesis that adenoids act as a " pathogen reservoir".

Integration of MRI radiomics and clinical data for preoperative prediction of vascular invasion in breast cancer: A deep learning approach.

Accurate preoperative prediction of vascular invasion in breast cancer is crucial for surgical planning and patient management. MRI radiomics has shown promise in enhancing diagnostic precision. This study aims to evaluate the effectiveness of integrating MRI radiomic features with clinical data using a deep learning approach to predict vascular invasion in breast cancer patients. A retrospective analysis was conducted on 102 patients with invasive breast cancer confirmed by surgical pathology. Using the MR750 3.0 T as the examination device, the subject underwent the examination in standard breast positions and sequences. Diffusion-weighted imaging (DWI) was performed with two selected b-values, specifically 0 and 1000 s/mm2. Following the injection of the contrast agent, dynamic scans were conducted across six phases, and delayed phase sagittal images were acquired using the VIBRANT sequence. Texture features were extracted from MRI images, and key radiomic and clinical features were selected using variance thresholding, correlation filtering, and logistic regression. A predictive model was developed combining these features, and its performance was evaluated through sensitivity, specificity, and area under the curve (AUC) metrics. The univariate models based on individual MRI sequences or clinical data demonstrated variable diagnostic performance. In contrast, the multifactorial model that combined radiomic features with clinical data achieved significantly higher accuracy, with an AUC of 0.829, sensitivity of 76.9 %, and specificity of 83.3 %. Integrating MRI radiomics and clinical data enhances the preoperative prediction of vascular invasion in breast cancer. This approach can improve diagnostic accuracy, providing valuable insights for clinical decision-making and personalized treatment strategies.

Does intervention sequence impact self-regulatory and behavioral outcomes in an adaptive trial among adults with prediabetes?

ABSTRACT Background: Lifestyle interventions can promote improvement in dietary intake and physical activity (PA), on average, by strengthening motivation, self-regulatory efforts, and commitment to behavioral change. However, maintenance of behavioral change is challenging, and slow responders during treatment often experience less overall success. Adaptive intervention sequences tailored to treatment response may be more effective in sustaining behavioral change. Methods: Adults ≥ 21 years old with prediabetes (n = 187) were stratified at week five to the standard Group Lifestyle Balance (GLB) intervention, if they achieved > 2.5% weight loss, or to the augmented intervention GLB Plus (GLB+) at week five, if they did not. At month five, each person in a matched pair was randomly assigned to GLB or GLB + for the extended intervention phase (months 5-12) followed by no study conduct (months 13-18). The primary comparison of interest was the change in outcomes between the standard (GLB followed by GLB) and augmented (GLB + followed by GLB+) intervention sequences post-intervention at 12 – and 18-months using linear mixed effect models. Results: The augmented GLB + intervention sequence reported a decline in the change in self-efficacy for reducing fat intake, self-efficacy for ‘sticking to’ healthy eating and exercise, and hopeful thought and planning compared to the standard GLB intervention sequence (all P < 0.0167) at 18-months. However, there were no significant differences between these intervention sequences at 18-months in the change in dietary intake or minutes of PA (all P > 0.05). Conclusions: No significant change in behavioral measures across intervention sequences occurred at study end. An 18-month decline in self-efficacy regarding diet and PA and hopeful thought and planning among slow responders following no intervention for six months indicates greater extended care is likely needed. The type of extended care that is most effective for slow treatment responders requires additional research.

Population genetics and molecular xenomonitoring of Biomphalaria freshwater snails along the southern shoreline of Lake Malawi, Malawi

BackgroundIntestinal schistosomiasis was confirmed endemic in Mangochi District, Malawi, in May of 2018 following an unexpected encounter with discreet populations of Biomphalaria spp. freshwater snails during routine malacological surveillance activities. Since then, only limited malacological surveillance of Biomphalaria has been carried out, and so the distribution of Biomphalaria populations in this area is currently unclear. Additionally, sites of active Schistosoma mansoni transmission in this area are also unknown. In the present study, through extensive malacological surveillance, we aimed to formally document the distribution of Biomphalaria in Mangochi District. We also aimed to identify active intestinal schistosomiasis transmission sites in this area through subjecting all collected Biomphalaria to a recently developed S. mansoni-specific molecular xenomonitoring PCR.MethodsThree malacological surveys were carried out along the southern shoreline of Lake Malawi, Mangochi District, Malawi, in November 2021, July 2022 and October/November 2022. All collected Biomphalaria were subjected to cercarial shedding analysis to identify active Schistosoma infections. Shed cercariae were then genotyped to species level using a standard multi-locus PCR and Sanger sequencing protocol. Following this, a subset of Biomphalaria from each collection site were also genotyped to species level using a standard PCR and Sanger sequencing protocol. All collected Biomphalaria were then subjected to a recently developed S. mansoni-specific molecular xenomonitoring PCR to identify infected, but non-shedding, Biomphalaria.ResultsA total of 589 Biomphalaria were collected across all three surveys. One single Biomphalaria (0.17%) specimen was found to be actively shedding Schistosoma cercariae, which were molecularly confirmed as S. mansoni. All genotyped Biomphalaria (n = 42) were molecularly identified as B. pfeifferi. A further 19 Biomphalaria specimens, collected from four different surveillance sites, were found to be infected with S. mansoni through molecular xenomonitoring. Intestinal schistosomiasis transmission was therefore identified at four different foci in Mangochi District.ConclusionsOur study highlights the importance of molecular approaches to investigate Biomphalaria populations and monitor Biomphalaria-associated intestinal schistosomiasis transmission in endemic areas. As such, the continued development and use of such approaches, in particular the development and use of molecular xenomonitoring assays that can be carried out in resource-poor schistosomiasis-endemic settings, is encouraged. The revision of ongoing schistosomiasis control programmes in Mangochi District, in line with WHO recommendations, is also encouraged.Graphical abstract

Robustness assessment of regressions using cluster analysis typologies: a bootstrap procedure with application in state sequence analysis

BackgroundIn standard Sequence Analysis, similar trajectories are clustered together to create a typology of trajectories, which is then often used to evaluate the association between sequence patterns and covariates inside regression models. The sampling uncertainty, which affects both the derivation of the typology and the associated regressions, is typically ignored in this analysis, an oversight that may lead to wrong statistical conclusions. We propose utilising sampling variation to derive new estimates that further inform on the association of interest.MethodsWe introduce a novel procedure to assess the robustness of regression results obtained from the standard analysis. Bootstrap samples are drawn from the data, and for each bootstrap, a new typology replicating the original one is constructed, followed by the estimation of the corresponding regression models. The bootstrap estimates are then combined using a multilevel modelling framework that mimics a meta-analysis. The fitted values from this multilevel model allow to account for the sampling uncertainty in the inferential analysis. We illustrate the methodology by applying it to the study of healthcare utilisation trajectories in a Swiss cohort of diabetic patients.ResultsThe procedure provides robust estimates for an association of interest, along with 95% prediction intervals, representing the range of expected values if the clustering and associated regressions were performed on a new sample from the same underlying distribution. It also identifies central and borderline trajectories within each cluster. Regarding the illustrative application, while there was evidence of an association between regular lipid testing and subsequent healthcare utilisation patterns in the original analysis, this is not supported in the robustness assessment.ConclusionsInvestigating the relationship between trajectory patterns and covariates is of interest in many situations. However, it is a challenging task with potential pitfalls. Our Robustness Assessment of Regression using Cluster Analysis Typologies (RARCAT) may assist in ensuring the robustness of such association studies. The method is applicable wherever clustering is combined with regression analysis, so its relevance goes beyond State Sequence Analysis.

Altered amino and fatty acids metabolism in Sudanese prostate cancer patients: insights from metabolic analysis.

Prostate cancer (PCa) management presents a multifaceted clinical challenge, intricately linking oncological considerations with cardiovascular health. Despite the recognized importance of lipid metabolism and hypertension in this interwoven relationship, their involvement in PCa development remains partially understood. This study aimed to explore variations in plasma metabolome among Sudanese PCa patients and their associated comorbidities. Plasma samples were collected from 50 patients across four hospitals in Sudan and profiled by nuclear magnetic resonance (NMR) spectroscopy. One-dimensional proton NMR spectra were acquired for each sample using standard nuclear Overhauser effect spectroscopy pulse sequence presat on a 500 MHz Bruker Avance III HD NMR spectrometer. Metabolite concentrations were quantified using R scripts developed in-house. Univariate and multivariate analyses were generated in the R software. Patients were categorized into four distinct metabotypes based on their metabolic profiles, and statistical analyses were conducted to evaluate the significance of observed differences. Our findings revealed high levels of fatty acids, phospholipids, cholesterol, valine, leucine, and isoleucine associated with non-hypertensive patients. In contrast, hypertensive patients were associated with high GlycA and GlycB levels and altered amino acid metabolism. These findings underscore the intricate interplay between metabolic dysregulation and hypertension in PCa patients. Further research is warranted to elucidate the precise molecular pathways underlying lipid metabolism in PCa and to explore the therapeutic potential of targeting these pathways. In conclusion, our study contributes to a deeper understanding of the metabolic landscape of PCa in Sudanese patients, emphasizing the importance of personalized approaches in cancer management.

Exploring brain perfusion in dogs with meningoencephalitis of unknown origin: A promising role for arterial spin labeling imaging.

Arterial spin labeling (ASL) is a noninvasive brain perfusion magnetic resonance imaging (MRI) technique that has not been assessed in dogs with meningoencephalitis of unknown origin (MUO). Assess brain perfusion changes characteristics before and after medical treatment, and investigate the role of ASL perfusion in the diagnosis and prognosis of MUO in dogs. Thirty-one dogs with presumed MUO. Prospective study. Each animal had brain MRI including standard and ASL perfusion sequences at presentation and after treatment of 3 months or longer. Brain perfusion characteristics were assessed visually and by cerebral blood flow (CBF) measurements. Perfusion characteristics were compared pre- and post-treatment. Dogs with MUO had preferential localization of lesions in optic nerves (ONs) and brainstem. At presentation, one third of the dogs with MUO had focal brain perfusion alterations and two-thirds had global brain hypoperfusion. Both focal and global brain perfusion changes resolved after treatment in all surviving dogs. Arterial spin labeling failed to predict prognosis. Brain ASL perfusion in dogs with MUO demonstrated the value of ASL in the diagnosis and follow-up of the condition, suggesting the value of adding ASL to the clinical evaluation in dogs with suspected MUO. Preferential lesion localization in ON and brainstem resembled findings in the central nervous system of human patients with inflammatory demyelinating diseases. Future studies with histopathological confirmation are needed to better characterize the benefits of ASL in the different subtypes of non-infectious encephalomyelitis in dogs.