Dosimetric impact of variable air cavity within PTV for rectum cancer.

PURPOSE: The aim of this study is to determine the impact of rectal air volume changes on treatment plan quality, and subsequently inform daily cone-beam computed tomography (CBCT) evaluation constraints, in terms of acceptable rectal air volume during treatment. METHODS: Twelve rectal cancer patients who exhibited rectal air within the PTV on their planning CT were selected. A study was conducted to evaluate the deterioration in plan quality due to expanding air volume. For each case, the air cavity volume was isotropically expanded in three dimensions using predefined margins of 3, 5, 7, and 10 mm, while deforming bladder and rectum contours. A constraint was applied to the bony anatomy to restrict the deformation. Treatment plans were then generated for all twelve patients by recalculating the reference plan with the expanded air cavity volume. RESULTS: As the air cavity expanded, the maximum relative change in D98% coverage, compared to the reference plan, decreased by 10.8% ± 3.5%, while the D2% increased by 3.5% ± 0.9%. The positioning of the air cavity notably influenced the D98% variability with the 3 mm expansion. D98% coverage falls below 95% when the air cavity volume exceeds 17 cm3. On average, D2% coverage increased by 0.5% with each expansion. At the largest expansion, extensive coverage of 102% and 105% isodoses was observed compared to the reference plan. CONCLUSION: Air cavity volumes above 17 cm3 can potentially degrade the high-dose PTV coverage while increasing the regions covered by the 102% and 105% isodoses. Clinical CBCT guidelines were deduced, recommending a maximum threshold of 3.2 cm in diameter in any direction.

Association Between Hip Translation and Hip Rotation and Anatomy: A Pilot Quasi-static MRI Study.

Background: There is little known about translation of the hip and the relationship with hip rotation and morphology in asymptomatic patients. Hypotheses: (1) Femoral head would exhibit significant translations in asymptomatic hips, (2) femoral head translations would correlate to femoral rotations, and (3) range of femoral head translations would correlate to hip morphology. Study Design: Cross-sectional study; Level of evidence, 3. Methods: A total of 11 individuals (age, 23-47 years; 64% female) with asymptomatic hips underwent hip magnetic resonance imaging (MRI) in the following postures: neutral (supine), midflexion, maximum-flexion, internal rotation, internal rotation + midflexion, internal rotation + maximum-flexion, adduction, flexion-abduction-external rotation (FABER), extension, and lateral abduction. All rotations were passive. MRI-generated 3-dimensional hip models were used to quantify femoral rotations and translations. Femoral head diameter, acetabular diameter, lateral center-edge angle, alpha angle, femoral anteversion, acetabular version and inclination, and neck-shaft angle were measured from MRI. A t test was used if measured translations were statistically significant. Linear regression was used to assess the associations between translation and rotation. Pearson correlation was used to assess the relationships between hip anatomy and range of femoral head translations. Results: In all tested positions, the femoral head translated anteriorly by 2 ± 1 mm (maximum 5 mm, P < .001), posteriorly by 1 ± 1 mm (maximum 6 mm, P < .001), superiorly by 2 ± 2 mm (maximum 7 mm, P < .001), inferiorly by 2 ± 2 mm (maximum 6 mm, P < .001), laterally by 1 ± 1 mm (maximum 4 mm, P < .001), and medially by 2 ± 1 mm (maximum 5 mm, P < .001), relative to the rested supine position. Femoral flexion was associated with posterior translation of the femoral head (P = .038). Femoral abduction was associated with medial translation of the femoral head (P = .042). Higher femoral anteversion and smaller alpha angle were associated with a higher total magnitude of femoral head translation in the anterior-posterior direction (P < .04). Smaller femoral anteversion, higher acetabular inclination, smaller lateral center-edge angle, and lower neck-shaft angle were associated with a higher total magnitude of femoral head translation in the superior-inferior direction (P ≤ .03). Conclusion: Our study demonstrated that, during passive physiologic movement, asymptomatic hips on average translated up to 2 mm (with up to 7 mm maximum translation in some positions), which is potentially related to hip rotations and morphology. Further investigations are warranted to understand the normal and pathologic hip translations and their impact on hip function (ie, instability and impingement).

Emergence and Rapid Diagnosis of Talaromyces marneffei Infections in Renal Transplant Recipients by Next-Generation Sequencing.

In the last few years, next-generation sequencing (NGS) has emerged as a technology for laboratory diagnosis of many culture-negative infections and slow-growing microorganisms. In this study, we describe the use of metagenomic NGS (mNGS) for rapid diagnosis of T. marneffei infection in a 37-year-old renal transplant recipient who presented with chronic pneumonia syndrome. Bronchoalveolar lavage for mNGS was positive for T. marneffei sequence reads. Prolonged incubation of the bronchoalveolar lavage revealed T. marneffei colonies after 6 days of incubation. Analysis of 23 cases of T. marneffei infections in renal transplant recipients from the literature revealed that the number of cases ranged from 1 to 4 cases per five years from 1990 to 2020; but increased rapidly to 9 cases from 2021 to 2023, with 7 of them diagnosed by NGS. Twenty of the 23 cases were from T. marneffei-endemic areas [southern part of mainland China (n = 9); Hong Kong (n = 4); northeastern India (n = 2); Indonesia (n = 1) and Taiwan (n = 4)]. For the 3 patients from non-T. marneffei-endemic areas [United Kingdom (n = 2) and Australia (n = 1)], they had travel histories to China and Vietnam respectively. The time taken for diagnosis by mNGS [median 1 (range 1 to 2) day] was significantly shorter than that for fungal culture [median 6 (range 3 to 15) days] (P = 0.002). mNGS is useful for picking up more cases of T. marneffei infections in renal transplant recipients as well as providing a rapid diagnosis. Talaromycosis is an emerging fungal infection in renal transplant recipients.

Usefulness of next-generation sequencing for laboratory diagnosis of rickettsiosis.

Rickettsiosis includes a diversity of culture-negative non-specific systemic infections. Laboratory diagnosis of rickettsiosis is often not easy. In this 12-month study, six patients with a variety of rickettsia infections of the spotted fever group, typhus group and scrub typhus were diagnosed directly or indirectly by metagenomic next-generation sequencing (mNGS). The patient with Japanese spotted fever was rapidly made when mNGS analysis of the patient's blood revealed Rickettsia japonica sequences. For the two patients with Rickettsia felis chest infections, the bacterium was detected in the bronchoalveolar lavage of one case and lung biopsy of the other. Both patients had underlying malignancies, carcinoma of the breast and carcinoma of the lung respectively, and were on chemotherapy with immunosuppressive effect. For the remaining three patients who presented over a period of 13 weeks, all had fever, headache and the typical eschar. They also had increased serum transaminases and responded promptly to doxycycline. However, the Weil-Felix test results of all three patients were negative. Since we considered the three cases typical of rickettsiosis, we submitted their serum samples for mNGS analysis. Results showed that Orientia tsutsugamushi sequences were present in the serum of one case. In view of the positive mNGS results, we repeated the Weil-Felix test for the residual sera of all three patients and it revealed that those of the other two cases showed OX-19 titers of 1:640 and 1:160 respectively, inferring that these two patients probably had rickettsiosis of the typhus group. As for the patient positive for O. tsutsugamushi sequences, we also detected IgM for O. tsutsugamushi in the serum, which double confirmed that it was a case of scrub typhus. mNGS is an important molecular tool and can complement serology for laboratory diagnosis of rickettsiosis.

Detailed delineation of the fetal brain in diffusion MRI via multi-task learning.

Diffusion-weighted MRI is increasingly used to study the normal and abnormal development of fetal brain inutero. Recent studies have shown that dMRI can offer invaluable insights into the neurodevelopmental processes in the fetal stage. However, because of the low data quality and rapid brain development, reliable analysis of fetal dMRI data requires dedicated computational methods that are currently unavailable. The lack of automated methods for fast, accurate, and reproducible data analysis has seriously limited our ability to tap the potential of fetal brain dMRI for medical and scientific applications. In this work, we developed and validated a unified computational framework to (1) segment the brain tissue into white matter, cortical/subcortical gray matter, and cerebrospinal fluid, (2) segment 31 distinct white matter tracts, and (3) parcellate the brain's cortex and delineate the deep gray nuclei and white matter structures into 96 anatomically meaningful regions. We utilized a set of manual, semi-automatic, and automatic approaches to annotate 97 fetal brains. Using these labels, we developed and validated a multi-task deep learning method to perform the three computations. Our evaluations show that the new method can accurately carry out all three tasks, achieving a mean Dice similarity coefficient of 0.865 on tissue segmentation, 0.825 on white matter tract segmentation, and 0.819 on parcellation. The proposed method can greatly advance the field of fetal neuroimaging as it can lead to substantial improvements in fetal brain tractography, tract-specific analysis, and structural connectivity assessment.

Assessment of health technology acceptability for remote monitoring of patients with COVID-19: A measurement model for user perceptions of pulse oximeters.

Objective: This study aims to develop a measurement model for health technology acceptability using a theoretical framework and a range of validated instruments to measure user experience, acceptance, usability, health and digital health literacy. Methods: A cross-sectional evaluation study using a mixed-methods approach was conducted. An online survey was administered to patients who used a pulse oximeter in a virtual hospital setting during COVID-19. The model development was conducted in three steps: (1) exploratory factor analysis for conceptual model development, (2) measurement model confirmation through confirmatory factor analysis followed by structural equation modelling and (3) test of model external validity on four outcome measures. Finally, the different constructs of the developed model were used to compare two types of pulse oximeters by measuring the standardised scores. Results: Two hundred and two participants were included in the analysis, 37.6% were female and the average age was 53 years (SD:15.38). A four-construct model comprising Task Load, Affective Attitude, Self-Efficacy and Value of Use (0.636-0.857 factor loadings) with 12 items resulted from the exploratory factor analysis and yielded a good fit (RMSEA = .026). Health and digital health literacy did not affect the overall reliability of the model. Frustration, performance, trust and satisfaction were identified as outcomes of the model. No significant differences were observed in the acceptability constructs when comparing the two pulse oximeter devices. Conclusions: This article proposes a model for the measurement of the acceptability of health technologies used by patients in a remote care setting based on the use of a pulse oximeter in COVID-19 remote monitoring.

Recent and forecasted increases in coccidioidomycosis incidence in California linked to hydroclimatic swings.

Coccidioidomycosis, or Valley fever, is an infectious disease caused by inhalation of Coccidioides spp., fungi found primarily in soils of the southwestern United States. Prior work showed that coccidioidomycosis cases in California sharply increase by nearly 2-fold following wet winters that occur one- and two-years following drought. Statewide drought between 2020-2022 followed by heavy precipitation during the 2022-2023 winter raised concerns over potential increases in coccidioidomycosis cases in the fall of 2023, prompting California Department of Public Health (CDPH) to issue public health alerts. As anticipated, California saw a near record number of cases in 2023, with 9,054 provisional cases reported. During the 2023-2024 California wet season, precipitation was 115% the long-term average, furthering concerns about continued high coccidioidomycosis risk. We developed an ensemble model to forecast coccidioidomycosis cases in California in 2024-2025. Using this model, we predicted a total of 11,846 cases (90% PI: 10,056-14,094) in California between April 1, 2023, and March 31, 2024, encompassing the preliminary state report of 10,593. Our model forecasted 12,244 cases statewide between April 1, 2024, and March 31, 2025 - a 62% increase over the cases reported during the same period two years prior, and on par with the high incidence seen in 2023. The Southern San Joaquin Valley (5,398 cases, 90% PI: 4,556-6,442), Southern Coast (3,322, 90% PI: 2,694-3,961), and Central Coast (1,207 cases, 90% PI: 867-1,585) regions are expected to see the largest number of infections. Our model forecasts that disease incidence will exhibit pronounced seasonality, particularly in endemic regions, with cases rising in June and peaking in November at 1,411 (90% PI: 815-2,172) cases statewide - 98% higher than the peak two years prior (714) and nearly as high as the peak in 2023 (1,462). Near-term forecasts have the potential to inform public health messaging to enhance provider and patient awareness, encourage risk reduction practices, and improve recognition and management of coccidioidomycosis.

The interactions of macrophages, lymphocytes, and mesenchymal stem cells during bone regeneration.

Bone regeneration and repair are crucial to ambulation and quality of life. Factors such as poor general health, serious medical comorbidities, chronic inflammation, and ageing can lead to delayed healing and nonunion of fractures, and persistent bone defects. Bioengineering strategies to heal bone often involve grafting of autologous bone marrow aspirate concentrate (BMAC) or mesenchymal stem cells (MSCs) with biocompatible scaffolds. While BMAC shows promise, variability in its efficacy exists due to discrepancies in MSC concentration and robustness, and immune cell composition. Understanding the mechanisms by which macrophages and lymphocytes - the main cellular components in BMAC - interact with MSCs could suggest novel strategies to enhance bone healing. Macrophages are polarized into pro-inflammatory (M1) or anti-inflammatory (M2) phenotypes, and influence cell metabolism and tissue regeneration via the secretion of cytokines and other factors. T cells, especially helper T1 (Th1) and Th17, promote inflammation and osteoclastogenesis, whereas Th2 and regulatory T (Treg) cells have anti-inflammatory pro-reconstructive effects, thereby supporting osteogenesis. Crosstalk among macrophages, T cells, and MSCs affects the bone microenvironment and regulates the local immune response. Manipulating the proportion and interactions of these cells presents an opportunity to alter the local regenerative capacity of bone, which potentially could enhance clinical outcomes.

Streamline tractography of the fetal brain in utero with machine learning.

Diffusion-weighted magnetic resonance imaging (dMRI) is the only non-invasive tool for studying white matter tracts and structural connectivity of the brain. These assessments rely heavily on tractography techniques, which reconstruct virtual streamlines representing white matter fibers. Much effort has been devoted to improving tractography methodology for adult brains, while tractography of the fetal brain has been largely neglected. Fetal tractography faces unique difficulties due to low dMRI signal quality, immature and rapidly developing brain structures, and paucity of reference data. To address these challenges, this work presents the first machine learning model, based on a deep neural network, for fetal tractography. The model input consists of five different sources of information: (1) Voxel-wise fiber orientation, inferred from a diffusion tensor fit to the dMRI signal; (2) Directions of recent propagation steps; (3) Global spatial information, encoded as normalized distances to keypoints in the brain cortex; (4) Tissue segmentation information; and (5) Prior information about the expected local fiber orientations supplied with an atlas. In order to mitigate the local tensor estimation error, a large spatial context around the current point in the diffusion tensor image is encoded using convolutional and attention neural network modules. Moreover, the diffusion tensor information at a hypothetical next point is included in the model input. Filtering rules based on anatomically constrained tractography are applied to prune implausible streamlines. We trained the model on manually-refined whole-brain fetal tractograms and validated the trained model on an independent set of 11 test scans with gestational ages between 23 and 36 weeks. Results show that our proposed method achieves superior performance across all evaluated tracts. The new method can significantly advance the capabilities of dMRI for studying normal and abnormal brain development in utero.

Detailed delineation of the fetal brain in diffusion MRI via multi-task learning.

Diffusion-weighted MRI is increasingly used to study the normal and abnormal development of fetal brain inutero. Recent studies have shown that dMRI can offer invaluable insights into the neurodevelopmental processes in the fetal stage. However, because of the low data quality and rapid brain development, reliable analysis of fetal dMRI data requires dedicated computational methods that are currently unavailable. The lack of automated methods for fast, accurate, and reproducible data analysis has seriously limited our ability to tap the potential of fetal brain dMRI for medical and scientific applications. In this work, we developed and validated a unified computational framework to (1) segment the brain tissue into white matter, cortical/subcortical gray matter, and cerebrospinal fluid, (2) segment 31 distinct white matter tracts, and (3) parcellate the brain's cortex and delineate the deep gray nuclei and white matter structures into 96 anatomically meaningful regions. We utilized a set of manual, semi-automatic, and automatic approaches to annotate 97 fetal brains. Using these labels, we developed and validated a multi-task deep learning method to perform the three computations. Our evaluations show that the new method can accurately carry out all three tasks, achieving a mean Dice similarity coefficient of 0.865 on tissue segmentation, 0.825 on white matter tract segmentation, and 0.819 on parcellation. The proposed method can greatly advance the field of fetal neuroimaging as it can lead to substantial improvements in fetal brain tractography, tract-specific analysis, and structural connectivity assessment.

Accuracy of Clinical Staging in Early-Stage Pancreatic Ductal Adenocarcinoma.

This study evaluates the accuracy of clinical staging in early-stage pancreatic ductal adenocarcinoma.

Towards tunable exciton delocalization in DNA Holliday junction-templated indodicarbocyanine 5 (Cy5) dye derivative heterodimers.

We studied the exciton delocalization of indodicarbocyanine 5 dye derivative (Cy5-R) heterodimers templated by a DNA Holliday junction (HJ), which was quantified by the exciton hopping parameter Jm,n. These dyes were modified at the 5 and 5' positions of indole rings with substituent (R) H, Cl, tBu, Peg, and hexyloxy (Hex) groups that exhibit different bulkiness and electron-withdrawing/donating capacities. The substituents tune the physical properties of the dyes, such as hydrophobicity (log P) and solvent-accessible surface area (SASA). We tuned the Jm,n of heterodimers by attaching two Cy5-Rs in adjacent and transverse positions along the DNA-HJ. Adjacent heterodimers exhibited smaller Jm,n compared to transverse heterodimers, and some adjacent heterodimers displayed a mixture of H- and J-like aggregates. Most heterodimers exhibited Jm,n values within the ranges of the corresponding homodimers, but some heterodimers displayed synergistic exciton delocalization that resulted in larger Jm,n compared to their homodimers. We then investigated how chemically distinct Cy5-R conjugated to DNA can interact to create delocalized excitons. We determined that heterodimers involving Cy5-H and Cy5-Cl and a dye with larger substituents (bulky substituents and large SASA) such as Cy5-Peg, Cy5-Hex, and Cy5-tBu resulted in larger Jm,n. The combination provides steric hindrance that optimizes co-facial packing (bulky Cy5-R) with a smaller footprint (small SASA) that maximizes proximity. The results of this study lay a groundwork for rationally optimizing the exciton delocalization in dye aggregates for developing next-generation technologies based on optimized exciton transfer efficiency such as quantum information systems and biomedicine.

Air quality and mental illness: role of bioaerosols, causal mechanisms and research priorities.

BACKGROUND: Poor air quality can both trigger and aggravate lung and heart conditions, as well as affecting child development. It can even lead to neurological and mental health problems. However, the precise mechanisms by which air pollution affect human health are not well understood. AIMS: To promote interdisciplinary dialogue and better research based on a critical summary of evidence on air quality and health, with an emphasis on mental health, and to do so with a special focus on bioaerosols as a common but neglected air constituent. METHOD: A rapid narrative review and interdisciplinary expert consultation, as is recommended for a complex and rapidly changing field of research. RESULTS: The research methods used to assess exposures and outcomes vary across different fields of study, resulting in a disconnect in bioaerosol and health research. We make recommendations to enhance the evidence base by standardising measures of exposure to both particulate matter in general and bioaerosols specifically. We present methods for assessing mental health and ideal designs. There is less research on bioaerosols, and we provide specific ways of measuring exposure to these. We suggest research designs for investigating causal mechanisms as important intermediate steps before undertaking larger-scale and definitive studies. CONCLUSIONS: We propose methods for exposure and outcome measurement, as well as optimal research designs to inform the development of standards for undertaking and reporting research and for future policy.

A Holistic Way to Understand the Determinants of Physical Activity in Urban New South Wales, Australia: A Codesigned Systems Mapping Project.

BACKGROUND: To meet the World Health Organization goal of reducing physical inactivity by 15% by 2030, a multisectoral system approach is urgently needed to promote physical activity (PA). We report the process of and findings from a codesigned systems mapping project to present determinants of PA in the context of urban New South Wales, Australia. METHODS: A participatory conceptual mapping workshop was held in May 2023 with 19 participants working in education, transportation, urban planning, community, health, and sport and recreation. Initial maps were developed and refined using online feedback from the participants. Interviews were conducted with 10 additional policymakers from relevant sectors to further refine the maps. RESULTS: Two systems maps were cocreated, identifying over 100 variables influencing PA and their interconnections. Five settings emerged from the adults' map-social and community, policy, built environment and transportation, health care, and workplace-and 4 for the young people's map-family, school, transportation, and community and environment. The maps share similarities, such as regarding potential drivers within the transportation, community, and built environment sectors; however, the young people's map has a specific focus on the school setting and the adults' map on workplace and health care settings. Interviews with policymakers provided further unique insights into understanding and intervening in the PA system. CONCLUSIONS: This codesigned participatory systems mapping process, supplemented by stakeholder interviews, provided a unique opportunity to bring together stakeholders across sectors to understand the complexity within the PA system and begin to identify leverage points for tackling physical inactivity in New South Wales.

Coccidioidomycosis seasonality in California: a longitudinal surveillance study of the climate determinants and spatiotemporal variability of seasonal dynamics, 2000-2021.

Background: Coccidioidomycosis, an emerging fungal disease in the western USA, exhibits seasonal patterns that are poorly understood, including periods of strong cyclicity, aseasonal intervals, and variation in seasonal timing that have been minimally characterized, and unexplained as to their causal factors. Coccidioidomycosis incidence has increased markedly in recent years, and our limited understanding of intra- and inter-annual seasonality has hindered the identification of important drivers of disease transmission, including climate conditions. In this study, we aim to characterize coccidioidomycosis seasonality in endemic regions of California and to estimate the relationship between drought conditions and coccidioidomycosis seasonal periodicity and timing. Methods: We analysed data on all reported incident cases of coccidioidomycosis in California from 2000 to 2021 to characterize seasonal patterns in incidence, and conducted wavelet analyses to assess the dominant periodicity, power, and timing of incidence for 17 counties with consistently high incidence rates. We assessed associations between seasonality parameters and measures of drought in California using a distributed lag nonlinear modelling framework. Findings: All counties exhibited annual cyclicity in incidence (i.e., a dominant wavelet periodicity of 12 months), but there was considerable heterogeneity in seasonal strength and timing across regions and years. On average, 12-month periodicity was most pronounced in the Southern San Joaquin Valley and Central Coast. Further, the annual seasonal cycles in the Southern San Joaquin Valley and the Southern Inland regions occurred earlier than those in coastal and northern counties, yet the timing of annual cycles became more aligned among counties by the end of the study period. Drought conditions were associated with a strong attenuation of the annual seasonal cycle, and seasonal peaks became more pronounced in the 1-2 years after a drought ended. Interpretation: We conclude that drought conditions do not increase the risk of coccidioidomycosis onset uniformly across the year, but instead promote increased risk concentrated within a specific calendar period (September to December). The findings have important implications for public health preparedness, and for how future shifts in seasonal climate patterns and extreme events may impact spatial and temporal coccidioidomycosis risk. Funding: National Institutes of Health.

Genetic findings in people with schwannomas who do not meet clinical diagnostic criteria for NF2-related schwannomatosis.

BACKGROUND: Most schwannomas are isolated tumours occurring in otherwise healthy people. However, bilateral vestibular schwannomas (BVS) or multiple non-vestibular schwannomas indicate an underlying genetic predisposition. This is most commonly NF2-related schwannomatosis (SWN), but when BVS are absent, this can also indicate SMARCB1-related or LZTR1-related SWN. METHODS: We assessed the variant detection rates for the three major SWN genes (NF2, LZTR1 and SMARCB1) in 154 people, from 150 families, who had at least one non-vestibular schwannoma, but who did not meet clinical criteria for NF2-related SWN at the time of genetic testing. RESULTS: We found that 17 (11%) people from 13 families had a germline SMARCB1 variant and 19 (12%) unrelated individuals had a germline LZTR1 variant. 19 people had an NF2 variant, but 18 of these were mosaic and 17 were only detected when 2 tumours were available for testing. The overall detection rate was 25% using blood alone, but increased to 36% when tumour analysis was included. Another 12 people had a germline variant of uncertain significance (VUS). CONCLUSIONS: There were similar proportions of LZTR1, SMARCB1 or mosaic NF2. However, since an NF2 variant was detected in tumours from 103 people, it is likely that further cases of mosaicism would be detected if more people had additional tumours available for analysis. In addition, if further evidence becomes available to show that the VUSs are pathogenic, this would significantly increase the proportion of people with a genetic diagnosis. Our results indicate the importance of comprehensive genetic testing and improved variant classification.

Comparison of Retinal Nerve Fiber Layer and Ganglion Cell Complex Rates of Change in Patients With Moderate to Advanced Glaucoma.

PURPOSE: To compare ganglion cell complex (GCC) and retinal nerve fiber layer (RNFL) rates of change (RoC) in eyes with central or moderate to advanced glaucoma. DESIGN: Prospective cohort study. PARTICIPANTS: A total of 918 matched macular and RNFL OCT scan pairs from 109 eyes (109 patients) enrolled in the Advanced Glaucoma Progression Study with ≥2 years of follow-up and ≥4 OCT scans. METHODS: We exported GCC and RNFL thickness measurements in 49 central macular superpixels and 12 RNFL clock-hour sectors, respectively. We applied our latest Bayesian hierarchical longitudinal model to estimate population and subject-specific baseline thickness (intercepts) and rates of change (RoC) in macular superpixels and RNFL sectors. Global RNFL and GCC RoC were analyzed in a single bivariate longitudinal model to properly compare them accounting for the correlation between their RoC. MAIN OUTCOME MEASURES: Proportion of significant negative (deteriorating) and positive (improving) RoC expressed in µm/year. Standardized RoC were calculated by dividing RoC by the corresponding population SD. Analyses were repeated in eyes with visual field mean deviation (MD) ≤-6 and > -6 dB. RESULTS: Average (SD) 24-2 visual field MD and follow-up length were -8.6 (6.3) dB and 4.2 (0.5) years, respectively. Global RNFL RoC (-0.70 µm/year) were faster than GCC (-0.44 µm/year) (P < .001); corresponding normalized RoC were not significantly different (P = .052). In bivariate analysis, patients with a significant negative global RNFL RoC (n = 63, 57%) or GCC (n = 56, 51%) frequently did so for both outcomes (n = 49, 45%). The average proportion of significantly decreasing RNFL sectors within an eye was 30.7% in eyes with MD > -6 dB compared to 20.5% in those with MD ≤ -6 dB (P = .014); the proportions for GCC superpixels were 21.1% versus 18.7%, respectively (P = .63). CONCLUSIONS: Both GCC and RNFL measures can detect structural progression in glaucoma patients with central damage or moderate to advanced glaucoma. The clinical utility of RNFL imaging decreases with worsening severity of glaucoma.

Extraction, Characterization, and Antioxidant Activity of Pectin from Lemon Peels.

Pectin is a natural polymer that is found in the cell walls of higher plants. This study presents a comprehensive analysis of pectin extracted from lemon in two different geographic regions (Peddie and Fort Beaufort) in two consecutive years (2023 and 2024) named PP 2023, PP 2024, FBP 2023, and FBP 2024. The dried lemon peels were ground into a powder, sifted to obtain particles of 500 µm, and then subjected to pectin extraction using a conventional method involving mixing lemon peel powder with distilled water, adjusting the pH level to 2.0 with HCl, heating the mixture at 70 °C for 45 min, filtering the acidic extract, and precipitating pectin with ethanol. The yield of these pectin samples was statistically significant, as FBP 2024 had a maximum yield of 12.2 ± 0.02%, PP 2024 had a maximum yield of 13.0 ± 0.02%, FBP 2023 had a maximum yield of 12.2 ± 0.03%, and PP 2023 had a maximum yield of 13.1 ± 0.03%, The variation in yield could be due to the differences in the growing conditions, such as the climate and soil, which could have affected the pectin content in the lemons. The physicochemical characterization of all samples proved that our pectin samples could be used in the pharmaceutical and food industries, with anhydrouronic acid content which was greater than 65%, as suggested by the FAO. The scanning electron microscope analysis of all extracted pectin was rough and jagged, while the commercial pectin displayed a smooth surface morphology with a consistent size. FTIR confirmed the functional groups which were present in our samples. Thermogravimetric analysis was employed to investigate the thermal behavior of the extracted pectin in comparison with commercial pectin. It was found that the extracted pectin had three-step degradation while the commercial pectin had four-step degradation. Additionally, pectin samples have been shown to have antioxidants, as the IC50 of PP 2024, PP 2023, FBP 2023, FBP 2024, and Commercial P was 1062.5 ± 20.0, 1201.3 ± 22.0, 1304.6 ± 19.0, 1382.6 ± 29.9, and 1019.4 ± 17.1 mg/L, respectively. These findings indicate that lemon pectin has promising characteristics as a biopolymer for use in biomedical applications.

Implementation of PET/CT in radiation oncology-a patterns-of-care analysis of the German Society of Nuclear Medicine and the German Society of Radiation Oncology.

BACKGROUND: The use of positron-emission tomography (PET)/computed tomography (CT) in radiation therapy (RT) has increased. Radiation oncologists (RadOncs) have access to PET/CT with a variety of tracers for different tumor entities and use it for target volume definition. The German Society of Nuclear Medicine (DGN) and the German Society of Radiation Oncology (DEGRO) aimed to identify current patterns of care in order to improve interdisciplinary collaboration. METHODS: We created an online survey on participating RadOncs' use of PET tracers for different tumor entities and how they affect RT indication, dose prescription, and target volume definition. Further topics were reimbursement of PET/CT and organizational information (fixed timeslots and use of PET with an immobilization device [planning/RT-PET]). The survey contained 31 questions in German language (yes/no questions, multiple choice [MC] questions, multiple select [MS] questions, and free-text entry options). The survey was distributed twice via the DEGRO member mailing list. RESULTS: During the survey period (May 22-August 7, 2023) a total of 156 RadOncs (13% of respondents) answered the survey. Among these, 59% reported access to diagnostic PET/CT within their organization/clinic and 24% have fixed timeslots for their patients. 37% of survey participants can perform RT-PET and 29% have the option of providing a dedicated RT technician for planning PET. Besides [18F]-fluorodeoxyglucose (FDG; mainly used in lung cancer: 95%), diagnostic prostate-specific membrane antigen (PSMA)-PET/CT for RT of prostate cancer is routinely used by 44% of participants (by 64% in salvage RT). Use of amino acid PET in brain tumors and somatostatin receptor PET in meningioma is low (19 and 25%, respectively). Scans are reimbursed through private (75%) or compulsory (55%) health insurance or as part of indications approved by the German Joint Federal Committee (Gemeinsamer Bundesausschuss; 59%). 98% of RadOncs agree that PET impacts target volume definition and 62% think that it impacts RT dose prescription. DISCUSSION: This is the first nationwide survey on the role of PET/CT for RT planning among RadOncs in Germany. We find high acceptance of PET results for treatment decisions and target volume definition. Planning PET comes with logistic challenges for different healthcare settings (e.g., private practices vs. university hospitals). The decision to request PET/CT is often based on the possibility of reimbursement. CONCLUSION: PET/CT has become an important tool for RadOncs, with several indications. However, access is still limited at several sites, especially for dedicated RT-PET. This study aims to improve interdisciplinary cooperation and adequate implementation of current guidelines for the treatment of various tumor entities.

White matter tract crossing and bottleneck regions in the fetal brain.

There is a growing interest in using diffusion MRI to study the white matter tracts and structural connectivity of the fetal brain. Recent progress in data acquisition and processing suggests that this imaging modality has a unique role in elucidating the normal and abnormal patterns of neurodevelopment in utero. However, there have been no efforts to quantify the prevalence of crossing tracts and bottleneck regions, important issues that have been extensively researched for adult brains. In this work, we determined the brain regions with crossing tracts and bottlenecks between 23 and 36 gestational weeks. We performed probabilistic tractography on 59 fetal brain scans and extracted a set of 51 distinct white tracts, which we grouped into 10 major tract bundle groups. We analyzed the results to determine the patterns of tract crossings and bottlenecks. Our results showed that 20-25% of the white matter voxels included two or three crossing tracts. Bottlenecks were more prevalent. Between 75-80% of the voxels were characterized as bottlenecks, with more than 40% of the voxels involving four or more tracts. The results of this study highlight the challenge of fetal brain tractography and structural connectivity assessment and call for innovative image acquisition and analysis methods to mitigate these problems.