Correction: Towards control of excitonic coupling in DNA-templated Cy5 aggregates: the principal role of chemical substituent hydrophobicity and steric interactions.

Correction for 'Towards control of excitonic coupling in DNA-templated Cy5 aggregates: the principal role of chemical substituent hydrophobicity and steric interactions' by Sebastián A. Díaz et al., Nanoscale, 2023, 15, 3284-3299. https://doi.org/10.1039/D2NR05544A.

Optimizing Upconversion Quantum Yield via Structural Tuning of Dipyrrolonaphthyridinedione Annihilators.

Triplet-triplet annihilation upconversion (TTA-UC) is a photophysical process in which two low-energy photons are converted into one higher-energy photon. This type of upconversion requires two species: a sensitizer that absorbs low-energy light and transfers its energy to an annihilator, which emits higher-energy light after TTA. In spite of the multitude of applications of TTA-UC, few families of annihilators have been explored. In this work, we show dipyrrolonaphthyridinediones (DPNDs) can act as annihilators in TTA-UC. We found that structural changes to DPND dramatically increase its upconversion quantum yield (UCQY). Our optimized DPND annihilator demonstrates a high maximum internal UCQY of 9.4%, outperforming the UCQY of commonly used near-infrared-to-visible annihilator rubrene by almost double.

Proteomes of native and non-native symbionts reveal responses underpinning host-symbiont specificity in the cnidarian-dinoflagellate symbiosis.

Cellular mechanisms responsible for the regulation of nutrient exchange, immune responses, and symbiont population growth in the cnidarian-dinoflagellate symbiosis are poorly resolved, particularly with respect to the dinoflagellate symbiont. Here, we characterised proteomic changes in the native symbiont Breviolum minutum during colonisation of its host sea anemone Exaiptasia diaphana ("Aiptasia"). We also compared the proteome of this native symbiont in the established symbiotic state with that of a non-native symbiont, Durusdinium trenchii. The onset of symbiosis between Aiptasia and Branchioglossum minutum increased accumulation of symbiont proteins associated with acquisition of inorganic carbon and photosynthesis, nitrogen metabolism, micro- and macronutrient starvation, suppression of host immune responses, tolerance to low pH, and management of oxidative stress. Such responses are consistent with a functional, persistent symbiosis. In contrast, D. trenchii predominantly showed elevated levels of immunosuppressive proteins, consistent with the view that this symbiont is an opportunist that forms a less beneficial, less well-integrated symbiosis with this model anemone. By adding symbiont analysis to the already known responses of the host proteome, our results provide a more holistic view of cellular processes that determine host-symbiont specificity and how differences in symbiont partners (i.e., native versus non-native symbionts) may impact the fitness of the cnidarian-dinoflagellate symbiosis.

A systematic search for RNA structural switches across the human transcriptome.

RNA structural switches are key regulators of gene expression in bacteria, but their characterization in Metazoa remains limited. Here, we present SwitchSeeker, a comprehensive computational and experimental approach for systematic identification of functional RNA structural switches. We applied SwitchSeeker to the human transcriptome and identified 245 putative RNA switches. To validate our approach, we characterized a previously unknown RNA switch in the 3' untranslated region of the RORC (RAR-related orphan receptor C) transcript. In vivo dimethyl sulfate (DMS) mutational profiling with sequencing (DMS-MaPseq), coupled with cryogenic electron microscopy, confirmed its existence as two alternative structural conformations. Furthermore, we used genome-scale CRISPR screens to identify trans factors that regulate gene expression through this RNA structural switch. We found that nonsense-mediated messenger RNA decay acts on this element in a conformation-specific manner. SwitchSeeker provides an unbiased, experimentally driven method for discovering RNA structural switches that shape the eukaryotic gene expression landscape.

Anatomically constrained tractography of the fetal brain.

Diffusion-weighted Magnetic Resonance Imaging (dMRI) is increasingly used to study the fetal brain in utero. An important computation enabled by dMRI is streamline tractography, which has unique applications such as tract-specific analysis of the brain white matter and structural connectivity assessment. However, due to the low fetal dMRI data quality and the challenging nature of tractography, existing methods tend to produce highly inaccurate results. They generate many false streamlines while failing to reconstruct the streamlines that constitute the major white matter tracts. In this paper, we advocate for anatomically constrained tractography based on an accurate segmentation of the fetal brain tissue directly in the dMRI space. We develop a deep learning method to compute the segmentation automatically. Experiments on independent test data show that this method can accurately segment the fetal brain tissue and drastically improve the tractography results. It enables the reconstruction of highly curved tracts such as optic radiations. Importantly, our method infers the tissue segmentation and streamline propagation direction from a diffusion tensor fit to the dMRI data, making it applicable to routine fetal dMRI scans. The proposed method can facilitate the study of fetal brain white matter tracts with dMRI.

Integrated image-based deep learning and language models for primary diabetes care.

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P < 0.05). For patients with referral DR, those in the PCP+DeepDR-LLM arm were more likely to adhere to DR referrals (P < 0.01). Additionally, DeepDR-LLM deployment improved the quality and empathy level of management recommendations. Given its multifaceted performance, DeepDR-LLM holds promise as a digital solution for enhancing primary diabetes care and DR screening.

Protein stability prediction by fine-tuning a protein language model on a mega-scale dataset.

Protein stability plays a crucial role in a variety of applications, such as food processing, therapeutics, and the identification of pathogenic mutations. Engineering campaigns commonly seek to improve protein stability, and there is a strong interest in streamlining these processes to enable rapid optimization of highly stabilized proteins with fewer iterations. In this work, we explore utilizing a mega-scale dataset to develop a protein language model optimized for stability prediction. ESMtherm is trained on the folding stability of 528k natural and de novo sequences derived from 461 protein domains and can accommodate deletions, insertions, and multiple-point mutations. We show that a protein language model can be fine-tuned to predict folding stability. ESMtherm performs reasonably on small protein domains and generalizes to sequences distal from the training set. Lastly, we discuss our model's limitations compared to other state-of-the-art methods in generalizing to larger protein scaffolds. Our results highlight the need for large-scale stability measurements on a diverse dataset that mirrors the distribution of sequence lengths commonly observed in nature.

Deep learning-based image quality assessment for optical coherence tomography macular scans: a multicentre study.

AIMS: To develop and externally test deep learning (DL) models for assessing the image quality of three-dimensional (3D) macular scans from Cirrus and Spectralis optical coherence tomography devices. METHODS: We retrospectively collected two data sets including 2277 Cirrus 3D scans and 1557 Spectralis 3D scans, respectively, for training (70%), fine-tuning (10%) and internal validation (20%) from electronic medical and research records at The Chinese University of Hong Kong Eye Centre and the Hong Kong Eye Hospital. Scans with various eye diseases (eg, diabetic macular oedema, age-related macular degeneration, polypoidal choroidal vasculopathy and pathological myopia), and scans of normal eyes from adults and children were included. Two graders labelled each 3D scan as gradable or ungradable, according to standardised criteria. We used a 3D version of the residual network (ResNet)-18 for Cirrus 3D scans and a multiple-instance learning pipline with ResNet-18 for Spectralis 3D scans. Two deep learning (DL) models were further tested via three unseen Cirrus data sets from Singapore and five unseen Spectralis data sets from India, Australia and Hong Kong, respectively. RESULTS: In the internal validation, the models achieved the area under curves (AUCs) of 0.930 (0.885-0.976) and 0.906 (0.863-0.948) for assessing the Cirrus 3D scans and Spectralis 3D scans, respectively. In the external testing, the models showed robust performance with AUCs ranging from 0.832 (0.730-0.934) to 0.930 (0.906-0.953) and 0.891 (0.836-0.945) to 0.962 (0.918-1.000), respectively. CONCLUSIONS: Our models could be used for filtering out ungradable 3D scans and further incorporated with a disease-detection DL model, allowing a fully automated eye disease detection workflow.

Esophageal Self-Expandable Metal Stents Can Fracture in the Distal Third When Used for Post-Bariatric Surgery Complications: A Single Center Experience and Review of the Literature with Video.

Background: Esophageal self-expandable metal stents (SEMS) are an important endoscopic tool. These stents have now been adapted successfully to manage post-bariatric surgery complications such as anastomotic leaks and strictures. In centers of expertise, this has become the primary standard-of-care treatment given its minimally invasive nature, and that it results in early oral feeding, decreased hospitalization, and overall favorable outcomes. Self-expandable metal stents (SEMS) fractures are a rare complication of unknown etiology. We aimed to investigate possible causes of SEMS fractures and highlight a unique endoscopic approach utilized to manage a fractured and impaled SEMS. Methods: This is a retrospective study of consecutive patients who underwent esophageal SEMS placement between 2015-2021 at a tertiary referral center to identify fractured SEMS. Patient demographics, stent characteristics, and possible etiologies of fractured SEMS were identified. A comprehensive literature review was also conducted to evaluate all prior cases of fractured SEMS and to hypothesize fracture theories. Results: There were seven fractured esophageal SEMS, of which six were used to manage post-bariatric surgery complications. Five SEMS were deployed with their distal ends in the gastric antrum and proximal ends in the distal esophagus. All stents fractured within 9 weeks of deployment. Most stents (5/7) were at least 10 cm in length with fractures commonly occurring in the distal third of the stents (6/7). The wires of a fractured SEMS were embedded within the esophagogastric junction in one case, prompting the use of an overtube that was synchronously advanced while steadily extracting the stent. Discussion: We suggest the following four etiologies of SEMS fractures: anatomical, physiological, mechanical, and chemical. Stent curvature at the stomach incisura can lead to strain- and stress-related fatigue due to mechanical bending with exacerbation from respiratory movements. Physiologic factors (gastric body contractions) can result in repetitive squeezing of the stent, adding to metal fatigue. Intrinsic properties (long length and low axial force) may be contributing factors. Lastly, the stomach acidic environment may cause nitinol-induced chemical weakness. Despite the aforementioned theories, SEMS fracture etiology remains unclear. Until more data become available, it may be advisable to remove these stents within 6 weeks.

The IDH paradox: Meta-analysis of alkylating chemotherapy in IDH-wildtype and -mutant lower grade gliomas.

BACKGROUND: IDH-wildtype (-wt) status is a pre-requisite for the diagnosis of glioblastoma (GBM); however, IDH-wt gliomas with low grade or anaplastic morphology have historically been excluded from GBM trials and may represent a distinct prognostic entity. While alkylating agent chemotherapy improves overall survival (OS) and progression-free survival (PFS) for IDH-wt GBM and also IDH-mutant gliomas, irrespective of grade, the benefit for IDH-wt diffuse histologic lower grade gliomas is unclear. METHODS: We performed a meta-analysis of randomized clinical trials for World Health Organization (WHO) grade 2-3 gliomas (2009 to present) to determine the effect of alkylating chemotherapy on IDH-wt and -mutant gliomas using a random-effects model with inverse-variance pooling. RESULTS: We identified six trials with 1,204 patients (430 IDH-wt, 774 IDH-mutant) that evaluated alkylating chemoradiotherapy versus radiotherapy alone, allowing us to perform an analysis focused on the value of adding alkylating chemotherapy to radiotherapy. For patients with IDH-wt tumors, alkylating chemotherapy added to radiotherapy was associated with improved PFS (HR:0.77 [95%CI 0.62-0.97], P=.03) but not OS (HR:0.87 [95%CI 0.64-1.18], P=.17). For patients with IDH-mutant tumors, alkylating chemotherapy added to radiotherapy improved both OS (HR:0.52 [95%CI 0.42-0.64], P<.001) and PFS (HR=0.47 [95%CI 0.39-0.57], P<.001) compared to radiotherapy alone. The magnitude of benefit was similar for IDH-mutant gliomas with or without 1p19q-codeletion. CONCLUSIONS: Alkylating chemotherapy reduces mortality by 48% and progression by 53% for patients with IDH-mutant gliomas. Optimal management of IDH-wt diffuse histologic lower grade gliomas remains to be determined, as there is little evidence supporting an OS benefit from alkylating chemotherapy.

Whole pelvis vs. hemi pelvis elective nodal radiotherapy in patients with PSMA-positive nodal recurrence after radical prostatectomy - a retrospective multi-institutional propensity score analysis.

PURPOSE: Despite growing evidence for bilateral pelvic radiotherapy (whole pelvis RT, WPRT) there is almost no data on unilateral RT (hemi pelvis RT, HPRT) in patients with nodal recurrent prostate cancer after prostatectomy. Nevertheless, in clinical practice HPRT is sometimes used with the intention to reduce side effects compared to WPRT. Prostate-specific membrane antigen positron emission tomography / computed tomography (PSMA-PET/CT) is currently the best imaging modality in this clinical situation. This analysis compares PSMA-PET/CT based WPRT and HPRT. METHODS: A propensity score matching was performed in a multi-institutional retrospective dataset of 273 patients treated with pelvic RT due to nodal recurrence (214 WPRT, 59 HPRT). In total, 102 patients (51 in each group) were included in the final analysis. Biochemical recurrence-free survival (BRFS) defined as prostate specific antigen (PSA) < post-RT nadir + 0.2ng/ml, metastasis-free survival (MFS) and nodal recurrence-free survival (NRFS) were calculated using the Kaplan-Meier method and compared using the log rank test. RESULTS: Median follow-up was 29 months. After propensity matching, both groups were mostly well balanced. However, in the WPRT group there were still significantly more patients with additional local recurrences and biochemical persistence after prostatectomy. There were no significant differences between both groups in BRFS (p = .97), MFS (p = .43) and NRFS (p = .43). After two years, BRFS, MFS and NRFS were 61%, 86% and 88% in the WPRT group and 57%, 90% and 82% in the HPRT group, respectively. Application of a boost to lymph node metastases, a higher RT dose to the lymphatic pathways (> 50 Gy EQD2α/ß=1.5 Gy) and concomitant androgen deprivation therapy (ADT) were significantly associated with longer BRFS in uni- and multivariate analysis. CONCLUSIONS: Overall, this analysis presents the outcome of HPRT in nodal recurrent prostate cancer patients and shows that it can result in a similar oncologic outcome compared to WPRT. Nevertheless, patients in the WPRT may have been at a higher risk for progression due to some persistent imbalances between the groups. Therefore, further research should prospectively evaluate which subgroups of patients are suitable for HPRT and if HPRT leads to a clinically significant reduction in toxicity.

Free-Breathing High-Resolution, Swap-Free, and Motion-Corrected Water/Fat Separation in Pediatric Abdominal MRI.

OBJECTIVES: The T1-weighted GRE (gradient recalled echo) sequence with the Dixon technique for water/fat separation is an essential component of abdominal MRI (magnetic resonance imaging), useful in detecting tumors and characterizing hemorrhage/fat content. Unfortunately, the current implementation of this sequence suffers from several problems: (1) low resolution to maintain high pixel bandwidth and minimize chemical shift; (2) image blurring due to respiratory motion; (3) water/fat swapping due to the natural ambiguity between fat and water peaks; and (4) off-resonance fat blurring due to the multipeak nature of the fat spectrum. The goal of this study was to evaluate the image quality of water/fat separation using a high-resolution 3-point Dixon golden angle radial acquisition with retrospective motion compensation and multipeak fat modeling in children undergoing abdominal MRI. MATERIALS AND METHODS: Twenty-two pediatric patients (4.2 ± 2.3 years) underwent abdominal MRI on a 3 T scanner with routine abdominal protocol and with a 3-point Dixon radial-VIBE (volumetric interpolated breath-hold examination) sequence. Field maps were calculated using 3D graph-cut optimization followed by fat and water calculation from k-space data by iteratively solving an optimization problem. A 6-peak fat model was used to model chemical shifts in k-space. Residual respiratory motion was corrected through soft-gating by weighting each projection based on the estimated respiratory motion from the center of the k-space. Reconstructed images were reviewed by 3 pediatric radiologists on a PACS (picture archiving and communication systems) workstation. Subjective image quality and water/fat swapping artifact were scored by each pediatric radiologist using a 5-point Likert scale. The VoL (variance of Laplacian) of the reconstructed images was used to objectively quantify image sharpness. RESULTS: Based on the overall Likert scores, the images generated using the described method were significantly superior to those reconstructed by the conventional 2-point Dixon technique (P < 0.05). Water/fat swapping artifact was observed in 14 of 22 patients using 2-point Dixon, and this artifact was not present when using the proposed method. Image sharpness was significantly improved using the proposed framework. CONCLUSIONS: In smaller patients, a high-quality water/fat separation with sharp visualization of fine details is critical for diagnostic accuracy. High-resolution golden angle radial-VIBE 3-point Dixon acquisition with 6-peak fat model and soft-gated motion correction offers improved image quality at the expense of an additional ~1-minute acquisition time. Thus, this technique offers the potential to replace the conventional 2-point Dixon technique.

Systematic under-ascertainment of anaplastic large cell lymphoma cases in cancer registries: report from a comprehensive cancer center.

INTRODUCTION: Breast implant-associated anaplastic large cell lymphoma (ALCL) has been rapidly rising in the US and around the world, leading to a mandated "black-box" label on all silicone- and saline-filled implants by the Food and Drug Administration (FDA). Because regulatory decisions in the US and around the world have been influenced primarily by risk estimates derived from cancer registries, it is important to determine their validity in identifying cases of ALCL. METHOD: We reviewed all cases of ALCL submitted to the New York State Cancer Registry from a large comprehensive cancer center in New York City from 2007 to 2019. To determine the possibility of misdiagnosis or under-diagnosis of ALCL cases reported to cancer registries, we accessed the sensitivity and specificity of the ICD-O-3 codes 9714 (ALCL) and 9702 (Mature T-cell lymphoma, not otherwise specified [T-NOS]) to identify pathologically-proven ALCL. RESULTS: We reviewed 2286,164 pathology reports from 47,466 unique patients with primary cancers. Twenty-eight cases of histologically-proven ALCL were identified. The sensitivity and specificity of the ICD-O-3 code 9714 (ALCL) were 82% and 100%, respectively. The sensitivity of the combined codes 9714/9702 (ALCL/T-NOS) was 96% and the specificity was 44%. CONCLUSION: Previous epidemiological studies that influenced regulatory decisions by the FDA may have systematically underestimated the risk of ALCL by at least 20%. We encourage updated global risk estimates of breast ALCL using methods that ensure adequate case ascertainment.

Abnormality of Early White Matter Development in Tuberous Sclerosis Complex and Autism Spectrum Disorder: Longitudinal Analysis of Diffusion Tensor Imaging Measures.

Background: Abnormalities in white matter development may influence development of autism spectrum disorder in tuberous sclerosis complex (TSC). Our goals for this study were as follows: (1) use data from a longitudinal neuroimaging study of tuberous sclerosis complex (TACERN) to develop optimized linear mixed effects models for analyzing longitudinal, repeated diffusion tensor imaging metrics (fractional anisotropy, mean diffusivity) pertaining to select white matter tracts, in relation to positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months, and (2) perform an exploratory analysis using optimized models applied to all white matter tracts from these data. Methods: Eligible participants (3-12 months) underwent brain magnetic resonance imaging (MRI) at repeated time points from ages 3 to 36 months. Positive Autism Diagnostic Observation Schedule-Second Edition classification at 36 months was used. Linear mixed effects models were fine-tuned separately for fractional anisotropy values (using fractional anisotropy corpus callosum as test outcome) and mean diffusivity values (using mean diffusivity right posterior limb internal capsule as test outcome). Fixed effects included participant age, within-participant longitudinal age, and autism spectrum disorder diagnosis. Results: Analysis included data from n = 78. After selecting separate optimal models for fractional anisotropy and mean diffusivity values, we applied these models to fractional anisotropy and mean diffusivity of all 27 white matter tracts. Fractional anisotropy corpus callosum was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = 0.0093, P = .0612), and mean diffusivity right inferior cerebellar peduncle was related to positive Autism Diagnostic Observation Schedule-Second Edition classification (coefficient = -0.00002071, P = .0445), though these findings were not statistically significant after multiple comparisons correction. Conclusion: These optimized linear mixed effects models possibly implicate corpus callosum and cerebellar pathology in development of autism spectrum disorder in tuberous sclerosis complex, but future studies are needed to replicate these findings and explore contributors of heterogeneity in these models.

Rapid Diagnosis of Pneumocystis jirovecii Pneumonia and Respiratory Tract Colonization by Next-Generation Sequencing.

OBJECTIVES: To describe the epidemiology of Pneumocystis jirovecii pneumonia and colonization diagnosed by next-generation sequencing (NGS) and explore the usefulness of the number of P. jirovecii sequence reads for the diagnosis of P. jirovecii pneumonia. METHODS: We examined the NGS results for P. jirovecii in respiratory samples collected from patients and analysed their clinical, radiological and microbiological characteristics. RESULTS: Among 285 respiratory samples collected over a 12-month period (January to December 2022), P. jirovecii sequences were detected in 56 samples from 53 patients. Fifty (94.3%) of the 53 patients were HIV-negative. Following our case definitions, 37 (69.8%) and 16 (30.2%) of the 53 patients had P. jirovecii infection and colonization respectively. P. jirovecii infection was associated with presence of underlying disease with immunosuppression (94.6% vs 18.8%, P < 0.05), positive serum 1,3-ß-D-glucan (41.2% vs 0%, P < 0.01) and higher number of P. jirovecii sequence reads (P < 0.005). In contrast, P. jirovecii colonization was associated with the male sex (93.8% vs 54.1%, P < 0.01), another definitive infectious disease diagnosis of the respiratory tract (43.8% vs 2.7%, P < 0.001) and higher survival (100% vs 67.6%, P < 0.01). Although P. jirovecii pneumonia was associated with higher number of P. jirovecii reads in respiratory samples, only a sensitivity of 82.14% and a specificity of 68.75% could be achieved. CONCLUSION: Detection of P. jirovecii sequences in respiratory samples has to be interpreted discreetly. A combination of clinical, radiological and laboratory findings is still the most crucial in determining whether a particular case is genuine P. jirovecii pneumonia.

A detailed spatio-temporal atlas of the white matter tracts for the fetal brain.

This study presents the construction of a comprehensive spatiotemporal atlas detailing the development of white matter tracts in the fetal brain using diffusion magnetic resonance imaging (dMRI). Our research leverages data collected from fetal MRI scans conducted between 22 and 37 weeks of gestation, capturing the dynamic changes in the brain's microstructure during this critical period. The atlas includes 60 distinct white matter tracts, including commissural, projection, and association fibers. We employed advanced fetal dMRI processing techniques and tractography to map and characterize the developmental trajectories of these tracts. Our findings reveal that the development of these tracts is characterized by complex patterns of fractional anisotropy (FA) and mean diffusivity (MD), reflecting key neurodevelopmental processes such as axonal growth, involution of the radial-glial scaffolding, and synaptic pruning. This atlas can serve as a useful resource for neuroscience research and clinical practice, improving our understanding of the fetal brain and potentially aiding in the early diagnosis of neurodevelopmental disorders. By detailing the normal progression of white matter tract development, the atlas can be used as a benchmark for identifying deviations that may indicate neurological anomalies or predispositions to disorders.

Acute Kidney Injury Duration and 20-Year Risks of CKD and Cardiovascular Disease.

Introduction: Acute kidney injury (AKI) is associated with chronic kidney disease (CKD) and cardiovascular disease (CVD); however, it is unclear whether AKI duration affects the long-term risks of CKD and CVD. Therefore, we performed a population-based cohort study examining the associations between AKI duration and CKD and CVD. Methods: We identified patients with laboratory-recorded AKI in Denmark from 1990 through 2018. AKIs were categorized as rapid reversal AKI (≤48 hours), persistent AKI (2-7 days), and acute kidney disease (AKD) (>7 days). We estimated 20-year risks and adjusted hazard ratios (aHRs) of incident CKD and CVD. Results: The study comprised 169,582 patients with AKI, with 100,478 and 76,838 included in the analysis of CKD and CVD, respectively. The 20-year risks of CKD were 26.3%, 29.5%, and 28.7% for rapid reversal AKI, persistent AKI, and AKD, respectively. Compared with rapid reversal AKI, aHRs were 1.13 (95% confidence interval [CI], 1.08-1.19) for persistent AKI and 1.36 (95% CI, 1.30-1.41) for AKD. Risks and rates of overall CVD were similar for rapid reversal AKI, persistent AKI, and AKD. However, persistent AKI was associated with a slightly increased aHR of heart failure (1.09; 95% CI, 1.02-1.16), and aHRs of heart failure, ischemic heart disease, and peripheral artery disease were slightly increased for AKD (1.09 [95% CI, 1.03-1.15], 1.11 [95% CI, 1.03-1.19], and 1.10 [95% CI, 1.02-1.17], respectively). Conclusion: AKI duration was associated with development of CKD, but not overall CVD; however, rates of heart failure, ischemic heart disease, and peripheral artery disease increased slightly with AKI duration.

Generalization of Odd Ramos-Louzada generated family of distributions: Properties, characterizations, and applications to diabetes and cancer survival datasets.

Probability distributions offer the best description of survival data and as a result, various lifetime models have been proposed. However, some of these survival datasets are not followed or sufficiently fitted by the existing proposed probability distributions. This paper presents a novel Kumaraswamy Odd Ramos-Louzada-G (KumORL-G) family of distributions together with its statistical features, including the quantile function, moments, probability-weighted moments, order statistics, and entropy measures. Some relevant characterizations were obtained using the hazard rate function and the ratio of two truncated moments. In light of the proposed KumORL-G family, a five-parameter sub-model, the Kumaraswamy Odd Ramos-Louzada Burr XII (KumORLBXII) distribution was introduced and its parameters were determined with the maximum likelihood estimation (MLE) technique. Monte Carlo simulation was performed and the numerical results were used to evaluate the MLE technique. The proposed probability distribution's significance and applicability were empirically demonstrated using various complete and censored datasets on the survival times of cancer and diabetes patients. The analytical results showed that the KumORLBXII distribution performed well in practice in comparison to its sub-models and several other competing distributions. The new KumORL-G for diabetes and cancer survival data is found extremely efficient and offers an enhanced and novel technique for modeling survival datasets.

Genotypic analysis of RTS,S/AS01E malaria vaccine efficacy against parasite infection as a function of dosage regimen and baseline malaria infection status in children aged 5-17 months in Ghana and Kenya: a longitudinal phase 2b randomised controlled trial.

BACKGROUND: The first licensed malaria vaccine, RTS,S/AS01E, confers moderate protection against symptomatic disease. Because many malaria infections are asymptomatic, we conducted a large-scale longitudinal parasite genotyping study of samples from a clinical trial exploring how vaccine dosing regimen affects vaccine efficacy. METHODS: Between Sept 28, 2017, and Sept 25, 2018, 1500 children aged 5-17 months were randomly assigned (1:1:1:1:1) to receive four different RTS,S/AS01E regimens or a rabies control vaccine in a phase 2b open-label clinical trial in Ghana and Kenya. Participants in the four RTS,S groups received two full doses at month 0 and month 1 and either full doses at month 2 and month 20 (group R012-20); full doses at month 2, month 14, month 26, and month 38 (group R012-14); fractional doses at month 2, month 14, month 26, and month 38 (group Fx012-14; early fourth dose); or fractional doses at month 7, month 20, and month 32 (group Fx017-20; delayed third dose). We evaluated the time to the first new genotypically detected infection and the total number of new infections during two follow-up periods (12 months and 20 months) in more than 36 000 dried blood spot specimens from 1500 participants. To study vaccine effects on time to the first new infection, we defined vaccine efficacy as one minus the hazard ratio (HR; RTS,S vs control) of the first new infection. We performed a post-hoc analysis of vaccine efficacy based on malaria infection status at first vaccination and force of infection by month 2. This trial (MAL-095) is registered with ClinicalTrials.gov, NCT03281291. FINDINGS: We observed significant and similar vaccine efficacy (25-43%; 95% CI union 9-53) against first new infection for all four RTS,S/AS01E regimens across both follow-up periods (12 months and 20 months). Each RTS,S/AS01E regimen significantly reduced the mean number of new infections in the 20-month follow-up period by 1·1-1·6 infections (95% CI union 0·6-2·1). Vaccine efficacy against first new infection was significantly higher in participants who were infected with malaria (68%; 95% CI 50-80) than in those who were uninfected (37%; 23-48) at the first vaccination (p=0·0053). INTERPRETATION: All tested dosing regimens blocked some infections to a similar degree. Improved vaccine efficacy in participants infected during vaccination could suggest new strategies for highly efficacious malaria vaccine development and implementation. FUNDING: GlaxoSmithKline Biologicals SA, PATH, Bill & Melinda Gates Foundation, and the German Federal Ministry of Education and Research.