Comparative analysis of brain age prediction using structural and diffusion MRIs in neonates.

Using machine learning techniques to predict brain age from multimodal data has become a crucial biomarker for assessing brain development. Among various types of brain imaging data, structural magnetic resonance imaging (sMRI) and diffusion magnetic resonance imaging (dMRI) are the most commonly used modalities. sMRI focuses on depicting macrostructural features of the brain, while dMRI reveals the orientation of major white matter fibers and changes in tissue microstructure. However, their differential capabilities in reflecting newborn age and clinical implications have not been systematically studied. This study aims to explore the impact of sMRI and dMRI on brain age prediction. Comparing predictions based on T2-weighted(T2w) and fractional anisotropy (FA) images, we found their mean absolute errors (MAE) in predicting infant age to be similar. Exploratory analysis revealed for T2w images, areas such as the cerebral cortex and ventricles contribute most significantly to age prediction, whereas FA images highlight the cerebral cortex and regions of the main white matter tracts. Despite both modalities focusing on the cerebral cortex, they exhibit significant region-wise differences, reflecting developmental disparities in macro- and microstructural aspects of the cortex. Additionally, we examined the effects of prematurity, gender, and hemispherical asymmetry of the brain on age prediction for both modalities. Results showed significant differences (p<0.05) in age prediction biases based on FA images across gender and hemispherical asymmetry, whereas no significant differences were observed with T2w images. This study underscores the differences between T2w and FA images in predicting infant brain age, offering new perspectives for studying infant brain development and aiding more effective assessment and tracking of infant development.

The effect of preterm birth on thalamic development based on shape and structural covariance analysis.

Acting as a central hub in regulating brain functions, the thalamus plays a pivotal role in controlling high-order brain functions. Considering the impact of preterm birth on infant brain development, traditional studies focused on the overall development of thalamus other than its subregions. In this study, we compared the volumetric growth and shape development of the thalamic hemispheres between the infants born preterm and full-term (Left volume: P = 0.027, Left normalized volume: P < 0.0001; Right volume: P = 0.070, Right normalized volume: P < 0.0001). The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus exhibit higher vulnerability to alterations induced by preterm birth. The structural covariance (SC) between the thickness of thalamus and insula in preterm infants (Left: corrected P = 0.0091, Right: corrected P = 0.0119) showed significant increase as compared to full-term controls. Current findings suggest that preterm birth affects the development of the thalamus and has differential effects on its subregions. The ventral nucleus region, dorsomedial nucleus region, and posterior nucleus region of the thalamus are more susceptible to the impacts of preterm birth.

Thirty-Day Readmissions Are Largely Not Preventable in Patients With Cirrhosis.

INTRODUCTION: Hospital readmissions are common in patients with cirrhosis, but there are few studies describing readmission preventability. We aimed to describe the incidence, causes, and risk factors for preventable readmission in this population. METHODS: We performed a prospective cohort study of patients with cirrhosis hospitalized at a single center between June 2014 and March 2020 and followed up for 30 days postdischarge. Demographic, clinical, and socioeconomic data, functional status, and quality of life were collected. Readmission preventability was independently and systematically adjudicated by 3 reviewers. Multinomial logistic regression was used to compare those with (i) preventable readmission, (ii) nonpreventable readmission/death, and (iii) no readmission. RESULTS: Of 654 patients, 246 (38%) were readmitted, and 29 (12%) were preventable readmissions. Reviewers agreed on preventability for 70% of readmissions. Twenty-two (including 2 with preventable readmission) died. The most common reasons for readmission were hepatic encephalopathy (22%), gastrointestinal bleeding (13%), acute kidney injury (13%), and ascites (6%), and these reasons were similar between preventable and nonpreventable readmissions. Preventable readmission was often related to paracentesis timeliness, diuretic adjustment monitoring, and hepatic encephalopathy treatment. Compared with nonreadmitted patients, preventable readmission was independently associated with racial and ethnic minoritized individuals (odds ratio [OR] 5.80; 95% CI, 1.96-17.13), nonmarried marital status (OR 2.88; 95% CI, 1.18-7.05), and admission in the prior 30 days (OR 3.45; 95% CI, 1.48-8.04). DISCUSSION: For patients with cirrhosis, readmission is common, but most are not preventable. Preventable readmissions are often related to ascites and hepatic encephalopathy and are associated with racial and ethnic minorities, nonmarried status, and prior admissions.

A Coculture of Photoautotrophs and Hydrolytic Heterotrophs Enables Efficient Upcycling of Starch from Wastewater toward Biomass-Derived Products: Synergistic Interactions Impacting Metabolism of the Consortium.

Even with particular interest in sustainable development, due to the limited types of bioavailable carbon sources that could support heterotrophic/mixotrophic growth, microalgae-derived products still suffer from inconsistent yield and high costs. This study demonstrates a successful cocultivation of the photoautotroph Chlorella vulgaris with a hydrolytic-enzyme-abundant heterotroph, Saccharomycopsis fibuligera, enabling efficient starch upcycling from water/wastewater toward enhancing microalgae-dominant biomass and lipid production. The enzymatic activities of S. fibuligera contributed to the hydrolysis of starch into glucose, generating a 7-fold higher biomass through mixotrophic/heterotrophic growth of C. vulgaris. Further, scanning transmission electron microscopy (STEM) and quantitative analysis suggested a significantly induced accumulation of lipids in C. vulgaris. Results of meta-transcriptomics revealed the critical regulatory role of illumination in interaction shifting. Gene expression for glycolysis and lipid biosynthesis of C. vulgaris were highly activated during dark periods. Meanwhile, during illumination periods, genes coding for glucoamylase and the sulfur-related activities in S. fibuligera were significantly upregulated, leading to induced starch hydrolysis and potential increased competition for sulfur utilization, respectively. This study indicates that hydrolytic organisms could collaborate to make starch bioavailable for nonhydrolytic microalgae, thus broadening the substrate spectrum and making starch a novel biotechnological feedstock for microalgae-derived products, e.g., biofuels or single-cell protein.

Deep-learning-based segmentation of perivascular spaces on T2-Weighted 3T magnetic resonance images.

Purpose: Studying perivascular spaces (PVSs) is important for understanding the pathogenesis and pathological changes of neurological disorders. Although some methods for automated segmentation of PVSs have been proposed, most of them were based on 7T MR images that were majorly acquired in healthy young people. Notably, 7T MR imaging is rarely used in clinical practice. Herein, we propose a deep-learning-based method that enables automatic segmentation of PVSs on T2-weighted 3T MR images. Method: Twenty patients with Parkinson's disease (age range, 42-79 years) participated in this study. Specifically, we introduced a multi-scale supervised dense nested attention network designed to segment the PVSs. This model fosters progressive interactions between high-level and low-level features. Simultaneously, it utilizes multi-scale foreground content for deep supervision, aiding in refining segmentation results at various levels. Result: Our method achieved the best segmentation results compared with the four other deep-learning-based methods, achieving a dice similarity coefficient (DSC) of 0.702. The results of the visual count of the PVSs in our model correlated extremely well with the expert scoring results on the T2-weighted images (basal ganglia: rs = 0.845, P < 0.001; rs = 0.868, P < 0.001; centrum semiovale: rs = 0.845, P < 0.001; rs = 0.823, P < 0.001 for raters 1 and 2, respectively). Experimental results show that the proposed method performs well in the segmentation of PVSs. Conclusion: The proposed method can accurately segment PVSs; it will facilitate practical clinical applications and is expected to replace the method of visual counting directly on T1-weighted images or T2-weighted images.

Enhanced biofuel production by co-pyrolysis of distiller's grains and waste plastics: A quantitative appraisal of kinetic behaviors and product characteristics.

Pyrolysis of biomass feedstocks can produce valuable biofuel, however, the final products may present excessive corrosion and poor stability due to the lack of hydrogen content. Co-pyrolysis with hydrogen-rich substances such as waste plastics may compensate for these shortcomings. In this study, the co-pyrolysis of a common biomass, i.e. distiller's grains (DG), and waste polypropylene plastic (PP) were investigated towards increasing the quantity and quality of the production of biofuel. Results from the thermogravimetric analyses showed that the reaction interval of individual pyrolysis of DG and PP was 124-471 °C and 260-461 °C, respectively. Conversely, an interaction effect between DG and PP was observed during co-pyrolysis, resulting in a slower rate of weight loss, a longer temperature range for the pyrolysis reaction, and an increase in the temperature difference between the evolution of products. Likewise, the Coats-Redfern model showed that the activation energies of DG, PP and an equal mixture of both were 42.90, 130.27 and 47.74 kJ mol-1, respectively. It thus follows that co-pyrolysis of DG and PP can effectively reduce the activation energy of the reaction system and promote the degree of pyrolysis. Synergistic effects essentially promoted the free radical reaction of the PP during co-pyrolysis, thereby reducing the activation energy of the process. Moreover, due to this synergistic effect in the co-pyrolysis of DG and PP, the ratio of elements was effectively optimized, especially the content of oxygen-containing species was reduced, and the hydrocarbon content of products was increased. These results will not only advance our understanding of the characteristics of co-pyrolysis of DG and PP, but will also support further research toward improving an efficient co-pyrolysis reactor system and the pyrolysis process itself.

Improving Alzheimer Diagnoses With An Interpretable Deep Learning Framework: Including Neuropsychiatric Symptoms.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder characterized by the progressive cognitive decline. Among the various clinical symptoms, neuropsychiatric symptoms (NPS) commonly occur during the course of AD. Previous researches have demonstrated a strong association between NPS and severity of AD, while the research methods are not sufficiently intuitive. Here, we report a hybrid deep learning framework for AD diagnosis using multimodal inputs such as structural MRI, behavioral scores, age, and gender information. The framework uses a 3D convolutional neural network to automatically extract features from MRI. The imaging features are passed to the Principal Component Analysis for dimensionality reduction, which fuse with non-imaging information to improve the diagnosis of AD. According to the experimental results, our model achieves an accuracy of 0.91 and an area under the curve of 0.97 in the task of classifying AD and cognitively normal individuals. SHapley Additive exPlanations are used to visually exhibit the contribution of specific NPS in the proposed model. Among all behavioral symptoms, apathy plays a particularly important role in the diagnosis of AD, which can be considered a valuable factor in further studies, as well as clinical trials.

Indiana Palliative Excellence in Alzheimer's Care Efforts (IN-PEACE): Protocol for a randomized controlled trial in persons with advanced dementia.

BACKGROUND: Dementia affects 6.5 million persons in the U.S., a number which is expected to double by 2060. More than half of persons with dementia die at home, creating an enormous burden for both patients and caregivers. However, there is a paucity of research on community-based palliative care interventions for advanced dementia. OBJECTIVES: The Indiana Palliative Excellence in Alzheimer's Care Efforts (IN-PEACE) study is a randomized trial to test the effectiveness of a collaborative predominantly telehealth home-based intervention for persons with advanced dementia residing in the community and their primary, informal caregivers. The primary aim is to determine if this palliative care focused supportive intervention is superior to usual care in reducing neuropsychiatric symptoms of dementia. Secondarily, intervention effects on other patient symptoms (e.g., pain), caregiver distress and depression, and emergency department (ED)/hospitalization events are examined. METHODS: The study population consists of participant pairs comprising a person with dementia and their primary, informal caregiver. The person with dementia must be ≥65 years old, with a clinical diagnosis of moderate to severe dementia. A total of 201 demographically and socioeconomically diverse participant pairs have been randomized to the IN-PEACE care coordination intervention (n = 99) or usual care (n = 102). Outcome assessments are conducted at baseline, and quarterly for up to 2 years (3, 6, 9, 12, 15, 18, 21, and 24 months). DISCUSSION: IN-PEACE results will inform care for the large number of individuals with advanced dementia residing in the community and enable informal caregivers to provide effective home-based care. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT03773757.

Enhancing Bioenergy Production from the Raw and Defatted Microalgal Biomass Using Wastewater as the Cultivation Medium.

Improving the efficiency of using energy and decreasing impacts on the environment will be an inevitable choice for future development. Based on this direction, three kinds of medium (modified anaerobic digestion wastewater, anaerobic digestion wastewater and a standard growth medium BG11) were used to culture microalgae towards achieving high-quality biodiesel products. The results showed that microalgae culturing with anaerobic digestate wastewater could increase lipid content (21.8%); however, the modified anaerobic digestion wastewater can boost the microalgal biomass production to 0.78 ± 0.01 g/L when compared with (0.35-0.54 g/L) the other two groups. Besides the first step lipid extraction, the elemental composition, thermogravimetric and pyrolysis products of the defatted microalgal residues were also analysed to delve into the utilisation potential of microalgae biomass. Defatted microalgae from modified wastewater by pyrolysis at 650 °C resulted in an increase in the total content of valuable products (39.47%) with no significant difference in the content of toxic compounds compared to other groups. Moreover, the results of the life cycle assessment showed that the environmental impact (388.9 mPET2000) was lower than that of raw wastewater (418.1 mPET2000) and standard medium (497.3 mPET2000)-cultivated groups. Consequently, the method of culturing microalgae in modified wastewater and pyrolyzing algal residues has a potential to increase renewable energy production and reduce environmental impact.

Integrated valorization system for simultaneous high strength organic wastewater treatment and astaxanthin production from Haematococcus pluvialis.

High-strength organic wastewater, e.g., potato juice wastewater, exerts high stress on the environment. This study proposes an integrated system for simultaneous high-strength organic wastewater treatment and nutrients upcycling for astaxanthin production by the combination of anaerobic processes and microalgae (Haematococcus pluvialis) cultivation. The potato juice wastewater was pretreated by either acidification or methanation. The effluents of both pretreatments achieved higher biomass yields of H. pluvialis compared to cultivation in standard culture media (control). The high acetate and potassium concentrations of the acidification effluents resulted in significantly higher astaxanthin production (24.5-27.9 mg g-1, 3 days) compared to the control (14.7 mg g-1, 12 days) in a shorter period. The integrated system contributed to a final removal efficiency of 51.3-75.8%, 86.5-98.3%, and 69.4-83.4% for COD, phosphorus, and ammonia, respectively. This study presents a promising two-stage process for simultaneous efficient methane and astaxanthin production, as well as remediation of high-strength organic wastewater.

Mitigating antibiotic pollution using cyanobacteria: Removal efficiency, pathways and metabolism.

The occurrence of pharmaceuticals and personal care products (PPCPs) in wastewater poses huge environmental threats, even at trace concentrations, and novel approaches are urged due to the inefficiencies of conventional wastewater treatment plants, especially when processing contaminants at high concentrations. Meanwhile, another widespread problem in the aquatic domain is the occurrence of harmful algal blooms (HABs) which cause serious damage to the ecosystem, but have rarely been investigated for possible valorization. This study investigated the possibilities, mechanisms, and effects of toxin release of using a harmful cyanobacterial species, Microcystis aeruginosa (M. aeruginosa), in order to remove the widely used drug, tetracycline, at high concentration. The results were compared with the performance obtained by the use of the hitherto generally-selected chlorophyte alga Chlorella pyrenoidosa (C. pyrenoidosa) for tetracycline concentrations of 10-100 mg L-1. M. aeruginosa exhibited a much more effective and rapid tetracycline removal (over 98.0% removal in 2 days) than did C. pyrenoidosa (36.7%-93.9% in 2 days). A comprehensive kinetic investigation into probable removal pathways indicated that, theoretically, bio-remediation dominated the process by M. aeruginosa (71.6%), while only accounting for 20.5% by C. pyrenoidosa. Both microalgae promoted the hydrolysis of tetracycline under conditions of increased pH and inhibited abiotic photolytic reactions by the shading effect to the water column, when compared with control experiments. Although identical degradation by-products were identified from treatments by both microalgal species, distinct by-products were also confirmed, unique to each treatment. Moreover, the growth of M. aeruginosa biomass exhibited strong tolerance to tetracycline exposure and released significantly lower levels of microcystin-LR, compared with the control systems. This study supports the possibility of reusing HABs species for the effective remediation of antibiotics at high concentrations. We have further suggested possible mechanisms for remediation and demonstrated control of toxin release.

Preparation of Sludge-Derived Activated Carbon by Fenton Activation and the Adsorption of Eriochrome Black T.

Sludge-derived activated carbon (SAC) was prepared by Fenton activation and calcination, and used as adsorbent to eliminate Eriochrome Black T (EBT) dye from aqueous media. The characterization results indicated that the produced SAC had a porous structure, high specific surface area, and abundant functional groups on its surface. The adsorption process was affected by pH, adsorbent dosage, time, and temperature. The adsorption capacity increased with temperature, and the highest adsorption capacity reached 178.2 mg·g-1 in 48 h at 318 K and pH 6. The results of the adsorption isotherm, kinetic, and thermodynamic analyses revealed that the adsorption of EBT onto SAC was naturally endothermic and spontaneous, involved both physical and chemical processes, and belonged mostly to the multilayer type of adsorption.

The miR-143/145 cluster reverses the regulation effect of KLF5 in smooth muscle cells with proliferation and contractility in intracranial aneurysm.

Alterations in vascular smooth muscle cells (VSMCs) contribute to the pathogenesis of intracranial aneurysms (IAs), but the molecular mechanisms of these alterations are unclear. The aim of this study was therefore to identify the molecular mechanism of VSMC-mediated IAs at clinical and cellular levels. We used bioinformatic and biochemical analyses to show that the microRNA (miR)-143/145 cluster was involved in various biological processes related to aneurysm formation. Clinical studies showed that the miR-143/145 cluster was downregulated in IA patients when compared with healthy subjects. However, KLF5 expression was upregulated in IA patients. In vitro experiments showed that overexpression of the miR-143/145 cluster inhibited proliferation and migration of VSMCs, but increased contractile protein expression and decreased matrix metalloproteinase-2 and -3. KLF5 overexpression had the opposite effect, even reversing the protective effect of the miR-143/145 cluster on IAs. Bifluorescein report experiments further confirmed that both miR-143 and miR-145 interacted with the 3'-UTR of KLF5 and inhibited post-transcriptional expression of KLF5. Taken together, the results showed that VSMC phenotypic modulation with upregulation of KLF5 by downregulation of the miR-143/145 cluster played an important role in formation and growth of IAs. The process of IA formation was reversed by overexpression of the miR-143/145 cluster. Together, the results provided a theoretical basis for further investigation of the potential clinical prevention and treatment of IAs.

Effective removal of sulfur from high-sulfur coal prior to use by dry chlorination at low temperature.

Desulfurization of high-sulfur coal prior to use by dry chlorination under various conditions was investigated. The contents of total carbon, total sulfur, pyritic sulfur, sulfate and organic sulfur of the coal were 72.48, 5.95, 1.08, 0.66 and 4.22 wt.%, respectively. It was found that the chlorination temperature and particle size had a great influence on sulfur removal. The optimal chlorination temperature and particle size for sulfur removal was 350°C and 48-75 µm, respectively. Under optimal conditions, sulfur content in the chlorinated coal was 1.12 wt.%. The removal percentages of total sulfur, pyritic sulfur, sulfate and organic sulfur were 67.7, 93.0, 65.6 and 61.6, respectively, indicating that a high proportion of organic sulfur, pyritic sulfur and inorganic sulfur were removed by dry chlorination. Meanwhile, the fixed carbon did not lose appreciably. It was speculated that the removal of organic sulfur by dry chlorination at 350°C proceeded mainly based on the equation 2RS+Cl(2)=2RCl+S(2)Cl(2). The chlorinated coal thus obtained could be used in production of various carbon-containing materials such as metallurgical coke after a complete dechlorination pretreatment at 500-600°C.