Different metazoan parasites, different transcriptomic responses, with new insights on parasitic castration by digenetic trematodes in the schistosome vector snail Biomphalaria glabrata.

BACKGROUND: Gastropods of the genus Biomphalaria (Family Planorbidae) are exploited as vectors by Schistosoma mansoni, the most common causative agent of human intestinal schistosomiasis. Using improved genomic resources, overviews of how Biomphalaria responds to S. mansoni and other metazoan parasites can provide unique insights into the reproductive, immune, and other systems of invertebrate hosts, and their responses to parasite challenges. RESULTS: Using Illumina-based RNA-Seq, we compared the responses of iM line B. glabrata at 2, 8, and 40 days post-infection (dpi) to single infections with S. mansoni, Echinostoma paraensei (both digenetic trematodes) or Daubaylia potomaca (a nematode parasite of planorbid snails). Responses were compared to unexposed time-matched control snails. We observed: (1) each parasite provoked a distinctive response with a predominance of down-regulated snail genes at all time points following exposure to either trematode, and of up-regulated genes at 8 and especially 40dpi following nematode exposure; (2) At 2 and 8dpi with either trematode, several snail genes associated with gametogenesis (particularly spermatogenesis) were down-regulated. Regarding the phenomenon of trematode-mediated parasitic castration in molluscs, we define for the first time a complement of host genes that are targeted, as early as 2dpi when trematode larvae are still small; (3) Differential gene expression of snails with trematode infection at 40dpi, when snails were shedding cercariae, was unexpectedly modest and revealed down-regulation of genes involved in the production of egg mass proteins and peptide processing; and (4) surprisingly, D. potomaca provoked up-regulation at 40dpi of many of the reproduction-related snail genes noted to be down-regulated at 2 and 8dpi following trematode infection. Happening at a time when B. glabrata began to succumb to D. potomaca, we hypothesize this response represents an unexpected form of fecundity compensation. We also document expression patterns for other Biomphalaria gene families, including fibrinogen domain-containing proteins (FReDs), C-type lectins, G-protein coupled receptors, biomphalysins, and protease and protease inhibitors. CONCLUSIONS: Our study is relevant in identifying several genes involved in reproduction that are targeted by parasites in the vector snail B. glabrata and that might be amenable to manipulation to minimize their ability to serve as vectors of schistosomes.

The genome and transcriptome of the snail Biomphalaria sudanica s.l.: immune gene diversification and highly polymorphic genomic regions in an important African vector of Schistosoma mansoni.

BACKGROUND: Control and elimination of schistosomiasis is an arduous task, with current strategies proving inadequate to break transmission. Exploration of genetic approaches to interrupt Schistosoma mansoni transmission, the causative agent for human intestinal schistosomiasis in sub-Saharan Africa and South America, has led to genomic research of the snail vector hosts of the genus Biomphalaria. Few complete genomic resources exist, with African Biomphalaria species being particularly underrepresented despite this being where the majority of S. mansoni infections occur. Here we generate and annotate the first genome assembly of Biomphalaria sudanica sensu lato, a species responsible for S. mansoni transmission in lake and marsh habitats of the African Rift Valley. Supported by whole-genome diversity data among five inbred lines, we describe orthologs of immune-relevant gene regions in the South American vector B. glabrata and present a bioinformatic pipeline to identify candidate novel pathogen recognition receptors (PRRs). RESULTS: De novo genome and transcriptome assembly of inbred B. sudanica originating from the shoreline of Lake Victoria (Kisumu, Kenya) resulted in a haploid genome size of ~ 944.2 Mb (6,728 fragments, N50 = 1.067 Mb), comprising 23,598 genes (BUSCO = 93.6% complete). The B. sudanica genome contains orthologues to all described immune genes/regions tied to protection against S. mansoni in B. glabrata, including the polymorphic transmembrane clusters (PTC1 and PTC2), RADres, and other loci. The B. sudanica PTC2 candidate immune genomic region contained many PRR-like genes across a much wider genomic region than has been shown in B. glabrata, as well as a large inversion between species. High levels of intra-species nucleotide diversity were seen in PTC2, as well as in regions linked to PTC1 and RADres orthologues. Immune related and putative PRR gene families were significantly over-represented in the sub-set of B. sudanica genes determined as hyperdiverse, including high extracellular diversity in transmembrane genes, which could be under pathogen-mediated balancing selection. However, no overall expansion in immunity related genes was seen in African compared to South American lineages. CONCLUSIONS: The B. sudanica genome and analyses presented here will facilitate future research in vector immune defense mechanisms against pathogens. This genomic/transcriptomic resource provides necessary data for the future development of molecular snail vector control/surveillance tools, facilitating schistosome transmission interruption mechanisms in Africa.

Multiscale Anion-Hybrid in Atomic Ni Sites for High-Rate Water Electrolysis: Insights into the Charge Accumulation Mechanism.

Single-atom catalysts, characterized by transition metal-(N/O)4 units on nanocarbon (M-(N/O)4-C), have emerged as efficient performers in water electrolysis. However, there are few guiding principles for accurately controlling the ligand fields of single atoms to further stimulate the catalyst activities. Herein, using the Ni-(N/O)4-C unit as a model, we develop a further modification of the P anion on the outer shells to modulate the morphology of the ligand. The catalyst thus prepared possesses high activity and excellent long-term durability, surpassing commercial Pt/C, RuO2, and currently reported single-atom catalysts. Notably, mechanistic studies demonstrated that the pseudocapacitive feature of multiscale anion-hybrid nanocarbon is considerable at accumulating enough positive charge [Q], contributing to the high oxygen evolution reaction (OER) order (ß) through the rate formula. DFT calculations also indicate that the catalytic activity is decided by the suitable barrier energy of the intermediates due to charge accumulation. This work reveals the activity origin of single atoms on multihybrid nanocarbon, providing a clear experiential formula for designing the electronic configuration of single-atom catalysts to boost electrocatalytic performance.

Associating Knee Osteoarthritis Progression with Temporal-Regional Graph Convolutional Network Analysis on MR Images.

BACKGROUND: Artificial intelligence shows promise in assessing knee osteoarthritis (OA) progression on MR images, but faces challenges in accuracy and interpretability. PURPOSE: To introduce a temporal-regional graph convolutional network (TRGCN) on MR images to study the association between knee OA progression status and network outcome. STUDY TYPE: Retrospective. POPULATION: 194 OA progressors (mean age, 62 ± 9 years) and 406 controls (mean age, 61 ± 9 years) from the OA Initiative were randomly divided into training (80%) and testing (20%) cohorts. FIELD STRENGTH/SEQUENCE: Sagittal 2D IW-TSE-FS (IW) and 3D-DESS-WE (DESS) at 3T. ASSESSMENT: Anatomical subregions of cartilage, subchondral bone, meniscus, and the infrapatellar fat pad at baseline, 12-month, and 24-month were automatically segmented and served as inputs to form compartment-based graphs for a TRGCN model, which containing both regional and temporal information. The performance of models based on (i) clinical variables alone, (ii) radiologist score alone, (iii) combined features (containing i and ii), (iv) composite TRGCN (combining TRGCN, i and ii), (v) radiomics features, (vi) convolutional neural network based on Densenet-169 were compared. STATISTICAL TESTS: DeLong test was performed to compare the areas under the ROC curve (AUC) of all models. Additionally, interpretability analysis was done to evaluate the contributions of individual regions. A P value <0.05 was considered significant. RESULTS: The composite TRGCN outperformed all other models with AUCs of 0.841 (DESS) and 0.856 (IW) in the testing cohort (all P < 0.05). Interpretability analysis highlighted cartilage's importance over other structures (42%-45%), tibiofemoral joint's (TFJ) dominance over patellofemoral joint (PFJ) (58%-67% vs. 12%-37%), and importance scores changes in compartments over time (TFJ vs. PFJ: baseline: 44% vs. 43%, 12-month: 52% vs. 39%, 24-month: 31% vs. 48%). DATA CONCLUSION: The composite TRGCN, capturing temporal and regional information, demonstrated superior discriminative ability compared with other methods, providing interpretable insights for identifying knee OA progression. TECHNICAL EFFICACY: Stage 2.

Interpretation of SPECT wall motion with deep learning.

OBJECTIVES: We sought to develop a novel deep learning (DL) workflow to interpret single-photon emission computed tomography (SPECT) wall motion. BACKGROUND: Wall motion assessment with SPECT is limited by image temporal and spatial resolution. Visual interpretation of wall motion can be subjective and prone to error. Artificial intelligence (AI) may improve accuracy of wall motion assessment. METHODS: A total of 1038 patients undergoing rest electrocardiogram (ECG)-gated SPECT and echocardiography were included. Using echocardiography as truth, a DL-model (DL-model 1) was trained to predict the probability of abnormal wall motion. Of the 1038 patients, 317 were used to train a DL-model (DL-model 2) to assess regional wall motion. A 10-fold cross-validation was adopted. Diagnostic performance of DL was compared with human readers and quantitative parameters. RESULTS: The area under the receiver operating characteristic curve (AUC) and accuracy (ACC) of DL model (AUC: .82 [95% CI: .79-.85]; ACC: .88) were higher than human (AUC: .77 [95% CI: .73-.81]; ACC: .82; P < .001) and quantitative parameter (AUC: .74 [95% CI: .66-.81]; ACC: .78; P < .05). The net reclassification index (NRI) was 7.7%. The AUC and accuracy of DL model for per-segment and per-vessel territory diagnosis were also higher than human reader. The DL model generated results within 30 seconds with operable guided user interface (GUI) and therefore could provide preliminary interpretation. CONCLUSIONS: DL can be used to improve interpretation of rest SPECT wall motion as compared with current human readers and quantitative parameter diagnosis.

Efficacy and safety of hyperbaric oxygen therapy in acute ischaemic stroke: a systematic review and meta-analysis.

OBJECTIVE: This study aims to evaluate the efficacy and safety of adjunctive hyperbaric oxygen therapy (HBOT) in acute ischaemic stroke (AIS) based on existing evidence. METHODS: We conducted a comprehensive search through April 15, 2023, of seven major databases for randomized controlled trials (RCTs) comparing adjunctive hyperbaric HBOT with non-HBOT (no HBOT or sham HBOT) treatments for AIS. Data extraction and assessment were independently performed by two researchers. The quality of included studies was evaluated using the tool provided by the Cochrane Collaboration. Meta-analysis was conducted using Rev Man 5.3. RESULTS: A total of 8 studies involving 493 patients were included. The meta-analysis showed no statistically significant differences between HBOT and the control group in terms of NIHSS score (MD = -1.41, 95%CI = -7.41 to 4.58), Barthel index (MD = 8.85, 95%CI = -5.84 to 23.54), TNF-α (MD = -5.78, 95%CI = -19.93 to 8.36), sICAM (MD = -308.47, 95%CI = -844.13 to 13227.19), sVCAM (MD = -122.84, 95%CI = -728.26 to 482.58), sE-selectin (MD = 0.11, 95%CI = -21.86 to 22.08), CRP (MD = -5.76, 95%CI = -15.02 to 3.51), adverse event incidence within ≤ 6 months of follow-up (OR = 0.98, 95%CI = 0.25 to 3.79). However, HBOT showed significant improvement in modified Rankin score (MD = 0.10, 95%CI = 0.03 to 0.17), and adverse event incidence at the end of treatment (OR = 0.42, 95%CI = 0.19 to 0.94) compared to the control group. CONCLUSION: While our findings do not support the routine use of HBOT for improving clinical outcomes in AIS, further research is needed to explore its potential efficacy within specific therapeutic windows and for different cerebral occlusion scenarios. Therefore, the possibility of HBOT offering clinical benefits for AIS cannot be entirely ruled out.

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep learning features to radiomics models for predicting 5-year OS status. METHODS: Two hundred twenty cases from The Cancer Imaging Archive public dataset were included in this study; 2212 radiomics features and 304 deep features were extracted from each case. The features were selected by univariate analysis and the least absolute shrinkage and selection operator, and then grouped into a radiomics model containing Positron Emission Tomography /Computed Tomography (PET/CT) radiomics features score, a deep model containing deep features score, and a combined model containing PET/CT radiomics features score +3D deep features score. TumorStage model was also constructed using initial patient tumor node metastasis stage to compare the performance of the combined model. A nomogram was constructed to analyze the influence of deep features on the performance of the model. The 10-fold cross-validation of the average area under the receiver operating characteristic curve and calibration curve were used to evaluate performance, and Shapley Additive exPlanations (SHAP) was developed for interpretation. RESULTS: The TumorStage model, radiomics model, deep model, and the combined model achieved areas under the receiver operating characteristic curve of 0.604, 0.851, 0.840, and 0.895 on the train set and 0.571, 0.849, 0.832, and 0.900 on the test set. The combined model showed better performance of predicting the 5-year OS status of HNC patients than the radiomics model and deep model. The combined model was shown to provide a favorable fit in calibration curves and be clinically useful in decision curve analysis. SHAP summary plot and SHAP The SHAP summary plot and SHAP force plot visually interpreted the influence of deep features and radiomics features on the model results. CONCLUSIONS: In predicting 5-year OS status in patients with HNC, 3D deep features could provide richer features for combined model, which showed outperformance compared with the radiomics model and deep model.

Unraveling the Structure and Reactivity Patterns of the Indole Radical Cation in Regioselective Electrochemical Oxidative Annulations.

Oxidation-induced strategy for inert chemical bond activation through highly active radical cation intermediate has exhibited unique reactivity. Understanding the structure and reactivity patterns of radical cation intermediates is crucial in the mechanistic study and will be beneficial for developing new reactions. In this work, the structure and properties of indole radical cations have been revealed using time-resolved transient absorption spectroscopy, in situ electrochemical UV-vis, and in situ electrochemical electron paramagnetic resonance (EPR) technique. Density functional theory (DFT) calculations were used to explain and predict the regioselectivity of several electrochemical oxidative indole annulations. Based on the understanding of the inherent properties of several indole radical cations, two different regioselective annulations of indoles have been successfully developed under electrochemical oxidation conditions. Varieties of furo[2,3-b]indolines and furo[3,2-b]indolines were synthesized in good yields with high regioselectivities. Our mechanistic insights into indole radical cations will promote the further development of oxidation-induced indole functionalizations.

Radiomics prognostic analysis of PET/CT images in a multicenter head and neck cancer cohort: investigating ComBat strategies, sub-volume characterization, and automatic segmentation.

PURPOSE: This study aimed to investigate the impact of several ComBat harmonization strategies, intra-tumoral sub-volume characterization, and automatic segmentations for progression-free survival (PFS) prediction through radiomics modeling for patients with head and neck cancer (HNC) in PET/CT images. METHODS: The HECKTOR MICCAI 2021 challenge set containing PET/CT images and clinical data of 325 oropharynx HNC patients was exploited. A total of 346 IBSI-compliant radiomic features were extracted for each patient's primary tumor volume defined by the reference manual contours. Modeling relied on least absolute shrinkage Cox regression (Lasso-Cox) for feature selection (FS) and Cox proportional-hazards (CoxPH) models were built to predict PFS. Within this methodological framework, 8 different strategies for ComBat harmonization were compared, including before or after FS, in feature groups separately or all features directly, and with center or clustering-determined labels. Features extracted from tumor sub-volume clustering were also investigated for their prognostic additional value. Finally, 3 automatic segmentations (2 threshold-based and a 3D U-Net) were also compared. All results were evaluated with the concordance index (C-index). RESULTS: Radiomics features without harmonization, combined with clinical factors, led to models with C-index values of 0.69 in the testing set. The best version of ComBat harmonization, i.e., after FS, for feature groups separately and relying on clustering-determined labels, achieved a C-index of 0.71. The use of features extracted from tumor sub-volumes further improved the C-index to 0.72. Models that relied on the automatic segmentations yielded close but slightly lower prognostic performance (0.67-0.70) compared to reference contours. CONCLUSION: A standard radiomics pipeline allowed for prediction of PFS in a multicenter HNC cohort. Applying a specific strategy of ComBat harmonization improved the performance. The extraction of intra-tumoral sub-volume features and automatic segmentation could contribute to the improvement and automation of prognosis modeling, respectively.

Transfer learning-based attenuation correction for static and dynamic cardiac PET using a generative adversarial network.

PURPOSE: The goal of this work is to demonstrate the feasibility of directly generating attenuation-corrected PET images from non-attenuation-corrected (NAC) PET images for both rest and stress-state static or dynamic [13N]ammonia MP PET based on a generative adversarial network. METHODS: We recruited 60 subjects for rest-only scans and 14 subjects for rest-stress scans, all of whom underwent [13N]ammonia cardiac PET/CT examinations to acquire static and dynamic frames with both 3D NAC and CT-based AC (CTAC) PET images. We developed a 3D pix2pix deep learning AC (DLAC) framework via a U-net + ResNet-based generator and a convolutional neural network-based discriminator. Paired static or dynamic NAC and CTAC PET images from 60 rest-only subjects were used as network inputs and labels for static (S-DLAC) and dynamic (D-DLAC) training, respectively. The pre-trained S-DLAC network was then fine-tuned by paired dynamic NAC and CTAC PET frames of 60 rest-only subjects to derive an improved D-DLAC-FT for dynamic PET images. The 14 rest-stress subjects were used as an internal testing dataset and separately tested on different network models without training. The proposed methods were evaluated using visual quality and quantitative metrics. RESULTS: The proposed S-DLAC, D-DLAC, and D-DLAC-FT methods were consistent with clinical CTAC in terms of various images and quantitative metrics. The S-DLAC (slope = 0.9423, R2 = 0.947) showed a higher correlation with the reference static CTAC as compared to static NAC (slope = 0.0992, R2 = 0.654). D-DLAC-FT yielded lower myocardial blood flow (MBF) errors in the whole left ventricular myocardium than D-DLAC, but with no significant difference, both for the 60 rest-state subjects (6.63 ± 5.05% vs. 7.00 ± 6.84%, p = 0.7593) and the 14 stress-state subjects (1.97 ± 2.28% vs. 3.21 ± 3.89%, p = 0.8595). CONCLUSION: The proposed S-DLAC, D-DLAC, and D-DLAC-FT methods achieve comparable performance with clinical CTAC. Transfer learning shows promising potential for dynamic MP PET.

Deep learning-based harmonization of CT reconstruction kernels towards improved clinical task performance.

OBJECTIVES: To develop a deep learning-based harmonization framework, assessing whether it can improve performance of radiomics models given different kernels in different clinical tasks and additionally generalize to mitigate the effects of new/unobserved kernels on radiomics features. METHODS: Patient data with 2 reconstruction kernels and phantom data with 22 reconstruction kernels were included. Eighty-five patients were studied for lymph node metastasis (LNM) prediction, and 164 patients for differential diagnosis between lung cancer (LC) and pulmonary tuberculosis (TB). Two convolutional neural network (CNN) models were developed to convert images (i) from B70f to B30f (CNNa) and (ii) from B30f to B70f (CNNb). Model performance between the two kernels was evaluated using AUC and compared with other well-known harmonization methods. Patient-normalized feature difference (PNFD) was used to identify the incompatible kernels (i.e., kernel with median PNFD > 1) with baseline (B30f/B70f), and measure the ability of the CNN models to convert the non-comparable kernels. RESULTS: For LC versus pulmonary TB diagnosis, AUCs of CNNa vs. others were 0.85 vs. 0.54-0.74 (p = 0.0001-0.0003), and for CNNb vs. others: 0.87 vs. 0.54-0.86 (p = 0.0001-0.55). For LNM prediction, AUCs of CNNa vs. others were 0.68 vs. 0.56-0.61 (p = 0.10-0.39), and for CNNb vs. others: 0.78 vs. 0.70-0.73 (p = 0.07-0.40). After CNN harmonization, 17 of 20 (85%) of investigated unknown kernels produced comparable radiomics feature values relative to baseline (median PNFD from 1.10-2.31 to 0.23-1.13). CONCLUSION: The CNN harmonization effectively improved performance of radiomics models between reconstruction kernels in different clinical tasks, and reduced feature differences between unknown kernels vs. baseline. KEY POINTS: • The soft (B30f) and sharp (B70f) kernels strongly affect radiomics reproducibility and generalizability. • The convolutional neural network (CNN) harmonization methods performed better than location-scale (ComBat and centering-scaling) and matrix factorization harmonization methods (based on singular value decomposition (SVD) and independent component analysis (ICA)) in both clinical tasks. • The CNN harmonization methods improve feature reproducibility not only between specific kernels (B30f and B70f) from the same scanner, but also between unobserved kernels from different scanners of different vendors.

Multimodality radiomics analysis based on [18F]FDG PET/CT imaging and multisequence MRI: application to nasopharyngeal carcinoma prognosis.

OBJECTIVES: To determine whether radiomics models developed from 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) PET/CT combined with multisequence MRI could contribute to predicting the progression-free survival (PFS) of nasopharyngeal carcinoma (NPC) patients. METHODS: One hundred thirty-two NPC patients who underwent both PET/CT and MRI scanning were retrospectively enrolled (88 vs. 44 for training vs. testing). For each modality/sequence (i.e., PET, CT, T1, T1C, and T2), 1906 radiomics features were extracted from the primary tumor volume. Univariate Cox model and correlation analysis were used for feature selection. A multivariate Cox model was used to establish radiomics signature. Prognostic performances of 5 individual modality models and 12 multimodality models (3 integrations × 4 fusion strategies) were assessed by the concordance index (C-index) and log-rank test. A clinical-radiomics nomogram was built to explore the clinical utilities of radiomics signature, which was evaluated by discrimination, calibration curve, and decision curve analysis (DCA). RESULTS: The radiomics signatures of individual modalities showed limited prognostic efficacy with a C-index of 0.539-0.664 in the testing cohort. Different fusion strategies exhibited a slight difference in predictive performance. The PET/CT and MRI integrated model achieved the best performance with a C-index of 0.745 (95% CI, 0.619-0.865) in the testing cohort (log-rank test, p < 0.05). Clinical-radiomics nomogram further improved the prognosis, which also showed satisfactory discrimination, calibration, and net benefit. CONCLUSIONS: Multimodality radiomics analysis by combining PET/CT with multisequence MRI could potentially improve the efficacy of PFS prediction for NPC patients. KEY POINTS: • Individual modality radiomics models showed limited performance in prognosis evaluation for NPC patients. • Combined PET, CT and multisequence MRI radiomics signature could improve the prognostic efficacy. • Multilevel fusion strategies exhibit comparable performance but feature-level fusion deserves more attention.

Recurrent Cerebellar Infarction Caused by Rare Thyroid Steal Syndrome: A Patient Report.

Thyroid steal syndrome is an extremely rare condition characterized by recurrent transient ischemic attacks. It is usually detected by the presence of an enlarged thyroid gland or thyroid dysfunction on examination. Herein, the authors reported a case of a severe patient with recurrent cerebellar infarction due to thyroid steal syndrome, which was initially considered to be due to intracranial arterial stenosis based on the patient's computed tomography angiogram but was later found to be due to circulation shunt caused by goiter.

Pinitol Protects Against Ox-Low-Density Lipoprotein-Induced Endothelial Inflammation and Monocytes Attachment.

ABSTRACT: Atherosclerosis is a cardiovascular disease that affects a majority of people around the world at old age. Atherosclerosis is slow to develop and challenging to treat. Endothelial dysfunction caused by oxidative stress, inflammation, and other pathological factors drives the process of atherogenesis. LOX-1 is one of the main scavenging receptors for oxidized low-density lipoprotein (ox-LDL) and contributes to atherogenesis by inducing overproduction of reactive oxygen species, increased expression of proinflammatory cytokines, and secretion of cellular adhesion molecules. In addition, activation of LOX-1 inhibits the expression of KLF2, a key protective factor against atherosclerosis. In this study, we investigated the effects of pinitol, and naturally occurring cyclic polyol, on endothelial dysfunction induced by ox-LDL. Our findings show that pinitol revealed a good safety profile, as evidenced by reducing lactate dehydrogenase release in human aortic endothelial cells. In our experiments, pinitol reduced the production of reactive oxygen species and expression of IL-6 and monocyte chemoattractant protein-1 induced by ox-LDL. Pinitol also significantly reduced the attachment of THP-1 monocytes to endothelial cells via downregulation of vascular cellular adhesion molecule-1 and E-selectin. Importantly, we found that pinitol reduced the expression of LOX-1 induced by ox-LDL and rescued the expression of KLF2, which is dependent on ERK5 expression. Together, our findings provide notable evidence that pinitol may have potential implication in the prevention and treatment of atherosclerosis.

Efficacy of Individualized Preventive Treatment of Patients with Severe Hemophilia A Guided by Multiple Clinical Parameters and Pharmacokinetics.

OBJECTIVE: The objective of the study was to investigate the effect of multiple clinical parameters (age, weight, blood types, and bleeding types) on FVIII pharmacokinetic parameters (PK parameters) in adult patients with severe hemophilia A (SHA), draw up individualized preventive treatment plans, and observe clinical efficacy. METHODS: Forty SHA patients treated in our hospital from January 2018 to May 2019 were enrolled, with their age, weight, blood types, bleeding types, and PK parameters measured to analyze the effects of clinical parameters on PK parameters. Individualized preventive treatment was developed, and patients were followed up for 1 year. The annual bleeding rate (ABR), annual joint bleeding rate (AJBR), and annual FVIII dosage were observed and compared before and after treatment. RESULTS: Weight, blood types, and bleeding types could affect the PK parameters of FVIII. A prophylaxis plan was formulated under the guidance of FVIII half-life. After 1 year of follow-up, the mean ABR dropped from 36.54 to 4.06, decreased by 88.9%, the mean AJBR dropped from 28.36 to 2.75, decreased by 90%, and annual FVIII dosage increased by 47%. The dosage of FVIII in 8 patients after was less than that before prophylaxis, and the average half-life time of these 8 patients was 13.32 h. CONCLUSIONS: (1) Weight, blood types, and bleeding types of adult SHA patients could affect FVIII half-life. As body mass index increased, FVIII half-life was significantly prolonged. The FVIII half-life of patients with type O blood was significantly shorter than those with other blood types, and the FVIII half-life of knee joint bleeding was conspicuously shorter than those of elbow joint bleeding. (2) Individualized preventive treatment could markedly reduce the number of bleeds. For patients with a long half-life period, the total annual FVIII dosage could be reduced to achieve bleeding prevention.

Destructing surfactant network in nanoemulsions by positively charged magnetic nanorods to enhance oil-water separation.

The separation of ultrafine oil droplets from wasted nanoemulsions stabilized with high concentration of surfactants is precondition for oil reuse and the safe discharge of effluent. However, the double barriers of the interfacial film and network structures formed by surfactants in nanoemulsions significantly impede the oil-water separation. To destroy these surfactant protective layers, we proposed a newly-developed polyethyleneimine micelle template approach to achieve simultaneous surface charge manipulation and morphology transformation of magnetic nanospheres to magnetic nanorods. The results revealed that positively charged magnetic nanospheres exhibited limited separation performance of nanoemulsions, with a maximum chemical oxygen demand (COD) removal of 50%, whereas magnetic nanorods achieved more than 95% COD removal in less than 30 s. The magnetic nanorods were also applicable to wasted nanoemulsions from different sources and exhibited excellent resistance to wide pH changes. Owing to their unique one-dimensional structure, the interfacial dispersion of magnetic nanorods was significantly promoted, leading to the efficient capture of surfactants and widespread destruction of both the interfacial film and network structure, which facilitated droplet merging into the oil phase. The easy-to-prepare and easy-to-tune strategy in this study paves a feasible avenue to simultaneously tailor surface charge and morphology of magnetic nanoparticles, and reveals the huge potential of morphology manipulation for producing high-performance nanomaterials to be applied in complex interfacial interaction process. We believe that the newly-developed magnetic-nanorods significantly contribute to hazardous oily waste remediation and advances technology evolution toward problematic oil-pollution control.

Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomic Model for Discrimination of Pathological Subtypes of Craniopharyngioma.

BACKGROUND: Preoperative, noninvasive discrimination of the craniopharyngioma subtypes is important because it influences the treatment strategy. PURPOSE: To develop a radiomic model based on multiparametric magnetic resonance imaging for noninvasive discrimination of pathological subtypes of craniopharyngioma. STUDY TYPE: Retrospective. POPULATION: A total of 164 patients from two medical centers were enrolled in this study. Patients from the first medical center were divided into a training cohort (N = 99) and an internal validation cohort (N = 33). Patients from the second medical center were used as the external independent validation cohort (N = 32). FIELD STRENGTH/SEQUENCE: Axial T1 -weighted (T1 -w), T2 -weighted (T2 -w), contrast-enhanced T1 -weighted (CET1 -w) on 3.0 T or 1.5 T magnetic resonance scanners. ASSESSMENT: Pathological subtypes (squamous papillary craniopharyngioma and adamantinomatous craniopharyngioma) were confirmed by surgery and hematoxylin and eosin staining. Optimal radiomic feature selection was performed by SelectKBest, the least absolute shrinkage and selection operator algorithm, and support vector machine (SVM) with a recursive feature elimination algorithm. Models based on each sequence or combinations of sequences were built using a SVM classifier and used to differentiate pathological subtypes of craniopharyngioma in the training cohort, internal validation, and external validation cohorts. STATISTICAL TESTS: The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic performance of the radiomic models. RESULTS: Seven texture features, three from T1 -w, two from T2 -w, and two from CET1 -w, were selected and used to construct the radiomic model. The AUC values of the radiomic model were 0.899, 0.810, and 0.920 in the training cohort, internal and external validation cohorts, respectively. The AUC values of the clinicoradiological model were 0.677, 0.655, and 0.671 in the training cohort, internal and external validation cohorts, respectively. DATA CONCLUSION: The model based on radiomic features from T1 -w, T2 -w, and CET1 -w has a high discriminatory ability for pathological subtypes of craniopharyngioma. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: 2.

Evaluation of the diagnostic value of joint PET myocardial perfusion and metabolic imaging for vascular stenosis in patients with obstructive coronary artery disease.

BACKGROUND: To investigate the diagnostic value of joint PET myocardial perfusion and metabolic imaging for vascular stenosis in patients with suspected obstructive coronary artery disease (CAD). METHODS: Eighty-eight patients (53 and 35 applied for training and validation, respectively) with suspected obstructive CAD were referred to 13N-NH3 PET/CT myocardial perfusion imaging (MPI) and 18F-FDG PET/CT myocardial metabolic imaging (MMI) with available coronary angiography for analysis. One semi-quantitative indicator summed rest score (SRS) and five quantitative indicators, namely, perfusion defect extent (EXT), total perfusion deficit (TPD), myocardial blood flow (MBF), scar degree (SCR), and metabolism-perfusion mismatch (MIS), were extracted from the PET rest MPI and MMI scans. Different combinations of indicators and seven machine learning methods were used to construct diagnostic models. Diagnostic performance was evaluated using the sum of four metrics (noted as sumScore), namely, area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTS: In univariate analysis, MIS outperformed other individual indicators in terms of sumScore (2.816-3.042 vs 2.138-2.908). In multivariate analysis, support vector machine (SVM) consisting of three indicators (MBF, SCR, and MIS) achieved the best performance (AUC 0.856, accuracy 0.810, sensitivity 0.838, specificity 0.757, and sumScore 3.261). This model consistently achieved significantly higher AUC compared with the SRS method for four specific subgroups (0.897, 0.839, 0.875, and 0.949 vs 0.775, 0.606, 0.713, and 0.744; P = 0.041, 0.005, 0.034 0.003, respectively). CONCLUSIONS: The joint evaluation of PET rest MPI and MMI could improve the diagnostic performance for obstructive CAD. The multivariate model (MBF, SCR, and MIS) combined with SVM outperformed other methods.

Coupling magnetic particles with flocculants to enhance demulsification and separation of waste cutting emulsion for engineering applications.

Magnetic particles were coupled with a flocculant to enhance the demulsification and separation of waste cutting emulsions. The optimal magnetic particle size and critical magnetic field conditions were investigated to achieve large-scale engineering application of magnetic demulsification separation for waste cutting emulsion treatment. The micro-scale magnetic particles were found to show comparable effects to nano-scale magnetic particles on enhancing the demulsification and separation of cutting emulsions, which are beneficial for broadening the selectivity of low-cost magnetic particles. The critical magnetic separation region was determined to be an area 40 mm from the magnetic field source. Compared to the flocculant demulsification, the magnetic demulsification separation exhibited a significant advantage in accelerating flocs-water separation by decreasing the separation time of flocs from 180-240 min to less than 15 min, compressing the flocs by reducing the floc volume ratio from 60%-90% to lower than 20%, and showing excellent adaptability to the variable properties of waste cutting emulsions. Coupled with the design of the magnetic disk separator, continuous demulsification separation of the waste cutting emulsion was achieved at 1.0 t/hr for at least 10 hr to obtain clear effluent with 81% chemical oxygen demand removal and 89% turbidity reduction. This study demonstrates the feasibility of applying magnetic demulsification separation to large-scale continuous treatment of waste emulsion. Moreover, it addresses the flocs-water separation problems that occur in practical flocculant demulsification engineering applications.

Genome-wide discovery, and computational and transcriptional characterization of an AIG gene family in the freshwater snail Biomphalaria glabrata, a vector for Schistosoma mansoni.

BACKGROUND: The AIG (avrRpt2-induced gene) family of GTPases, characterized by the presence of a distinctive AIG1 domain, is mysterious in having a peculiar phylogenetic distribution, a predilection for undergoing expansion and loss, and an uncertain functional role, especially in invertebrates. AIGs are frequently represented as GIMAPs (GTPase of the immunity associated protein family), characterized by presence of the AIG1 domain along with coiled-coil domains. Here we provide an overview of the remarkably expanded AIG repertoire of the freshwater gastropod Biomphalaria glabrata, compare it with AIGs in other organisms, and detail patterns of expression in B. glabrata susceptible or resistant to infection with Schistosoma mansoni, responsible for the neglected tropical disease of intestinal schistosomiasis. RESULTS: We define the 7 conserved motifs that comprise the AIG1 domain in B. glabrata and detail its association with at least 7 other domains, indicative of functional versatility of B. glabrata AIGs. AIG genes were usually found in tandem arrays in the B. glabrata genome, suggestive of an origin by segmental gene duplication. We found 91 genes with complete AIG1 domains, including 64 GIMAPs and 27 AIG genes without coiled-coils, more than known for any other organism except Danio (with > 100). We defined expression patterns of AIG genes in 12 different B. glabrata organs and characterized whole-body AIG responses to microbial PAMPs, and of schistosome-resistant or -susceptible strains of B. glabrata to S. mansoni exposure. Biomphalaria glabrata AIG genes clustered with expansions of AIG genes from other heterobranch gastropods yet showed unique lineage-specific subclusters. Other gastropods and bivalves had separate but also diverse expansions of AIG genes, whereas cephalopods seem to lack AIG genes. CONCLUSIONS: The AIG genes of B. glabrata exhibit expansion in both numbers and potential functions, differ markedly in expression between strains varying in susceptibility to schistosomes, and are responsive to immune challenge. These features provide strong impetus to further explore the functional role of AIG genes in the defense responses of B. glabrata, including to suppress or support the development of medically relevant S. mansoni parasites.