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IntroductionPike perch (Sander Lucioperca) is a predatory freshwater fish, which is highly popular amongst consumers, owing to its white flesh with a delicate structure and mild flavor. Compared to wild pike perch, the diet of farmed ones has shifted from natural food to artificial feeds. These changes would affect the gut flora of the pike perch. Endogenous metabolites of the intestinal flora are transferred through the gut-liver axis, which affects the physiological functions of the host. By studying wild and farmed individuals of the pike perch, novel insights into the stability of the intestinal flora can be provided.Methods and resultsIn this study, we measured various immune parameters in the blood, liver and intestine of wild and farmed pike perch using enzyme activity assays and real-time fluorescence quantitative PCR. Gut microbes were also collected for 16S rRNA gene sequencing. Our results showed that the serum low-density lipoprotein cholesterol (LDL-C) levels were twice as high in the wild group as in the farmed group. Furthermore, the activities of glutamate pyruvate transaminase (GPT) and glutamate oxaloacetate transaminase (GOT) in the intestinal tissues of the wild group were 733.91 U/g and 375.35 U/g, which were significantly higher than those of the farmed group. Expression of IL10 in the liver of farmed pike perch was also 4-fold higher than that of wild pike perch. The expression of genes related to the p53-BAX/Bcl2 signaling pathway was higher in both intestinal and liver tissues of wild pike perch compared with farmed. 16S rRNA gene analysis of the gut microflora showed a high relative abundance of Cetobacterium in the gut of farmed pike perch.ConclusionAs a result, our study indicates that dietary differences affect the diversity, composition and relative abundance of the gut flora of the pike perch. Meanwhile, it affects the glycolipid metabolism and immunomodulation of pike perch.

BackgroundMultiple sclerosis (MS) and Cerebral Small Vessel Disease (CSVD) exhibit some similarities in Magnetic resonance imaging (MRI), potentially leading to misdiagnosis and delaying effective treatment windows. It is unclear whether CSVD can be detected with Paramagnetic Rim Lesions (PRL), which is special in MS.ObjectiveWe aimed to investigate whether PRL can serve as a neuroimaging marker for discriminating between MS and CSVD.MethodsIn this retrospective study, 49 MS and 104 CSVD patients underwent 3.0 T Magnetic resonance imaging (MRI). Visual assessment of 37 MS patients and 89 CSVD patients with or without lacunes, cerebral microbleeds (CMBs), enlarged perivascular spaces (EPVS), white matter hyperintensity (WMH), central vein sign (CVS), and PRL. The distribution and number of PRL were then counted.ResultsOur study found that PRL was detected in over half of the MS patients but was entirely absent in CSVD patients (78.38 vs. 0%, p

When the battery or supercapacitor is connected to the output of a PV system, the conventional voltage equation expressing its mathematical model usually must be replaced by the current relationship to study the maximum power point tracking (MPPT) control theory. However, hitherto, there is a lack of an attempt to disclose the current constraint relationships at the maximum power point (MPP), which leads to the potential risk of MPPT failure. To solve this problem, in this paper, the MPPT constraint conditions on the basis of currents are built and then a new MPPT control strategy is proposed. In this strategy, a linearized model parameter of a PV cell is used as the bridge to find the current relationships. On the basis of them, some expressions involving the duty cycle are built to directly calculate the control signal of the MPPT controller. Meanwhile, an implementation method is designed to match this proposed MPPT strategy. Finally, some simulation experiments are conducted. The simulation results verify that the proposed MPPT constraint expressions are accurate and workable and that the proposed MPPT strategy and its implementation process are feasible and available. In addition, the simulation results also show that the proposed MPPT strategy has a better MPPT speed and the same MPPT accuracy when the P&O method and fuzzy algorithm are compared. By this work, the MPPT constraint conditions based on current relationships are first found, representing a breakthrough in disclosing the inherent relationships between different currents when the PV system is operating around the MPP.

In 2023, Rana dybowskii exhibiting characteristic skin ulcers were found on a farm in northeastern China. Subsequently, two dominant bacteria, Aeromonas hydrophila Rd001 and Acinetobacter johnsonii Rd002, were isolated from naturally infected R. dybowskii. Experimental infection confirmed that Rd001 was the primary pathogen responsible for the disease in R. dybowskii, with a mean lethal dose (LD50) of 6.25 × 102 CFU/g. The virulence genotype of Rd001 was identified as ser+/aha+/lip+/nuc+/hlyA+/aer+/alt+/ast+/act+. Antimicrobial susceptibility testing indicated that Rd001 was sensitive to enrofloxacin, flumequine, and neomycin. MLST analysis showed that Rd001 belonged to a new sequence type of A. hydrophila, named ST2378. This study offered the first comprehensive investigation into the pathogenicity, virulence genotypes, antimicrobial resistance, and genetic traits of A. hydrophila isolated from R. dybowskii, providing a theoretical foundation for preventing and controlling A. hydrophila infections.

The rainbow trout (Oncorhynchus mykiss) is an important commercial fish. Studies have shown that probiotics can promote the healthy growth of fish. In this study, we assessed the impact of an endogenous Bacillus subtilis strain (RT-BS07) on the growth, survival and immunological response of juvenile rainbow trout. Additionally, the morphology of rainbow trout’s intestinal tissue was measured. Control (CT) and experimental groups (B) were fed with conventional and probiotic-supplemented diets (1.0 × 108 CFU per gram) for 42 days, respectively. Following feeding, a challenge experiment was carried out with Aeromonas hydrophila at 1.0 × 107 CFU/mL to determine the experimental fish’s tolerance to the bacteria. The results showed that the weight gain rate (WGR) in group B was 118.2%, which was significantly higher than that in group CT (54.86%) after 42 days. The height of intestinal villi and the number of goblet cells increased in group B, thus increasing the resistance of rainbow trout to pathogenic bacteria. The alkaline phosphatase (AKP) activity (U/mg prot) in the liver, spleen and intestinal tissues of group B was significantly higher than that in the CT group. The expression of interleukin-1β (IL-1β) in the intestinal tissue of group B was 6-fold higher than that in group CT. Furthermore, the expression of growth hormone-2 (GH-2) in the spleen was 3-fold higher than that in group CT. After 12 days of A. hydrophila injection, the survival rate was 40% and 70% in group CT and group B, respectively. Collectively, the present study demonstrated that the addition of endogenous B. subtilis strain (1.0 × 108 CFU per gram) to the feed can effectively promote the growth of rainbow trout and enhance immunity, which is beneficial to rainbow trout culture.

The energy efficiency of the photovoltaic (PV) panel is greatly influenced by the dust deposition, especially in a PV plant covering a wide area. However, hitherto there has been a lack of a real-time measurement technique for the dust deposition degree. To solve this problem, in this paper, some evaluation indicators are defined, and then a real-time evaluation strategy is proposed. In order to calculate these indicators, a method and three simplification methods based on some established equations (or equation sets) are proposed to obtain the equation solution for the irradiance. This solved data is compared with the irradiance directly measured by the sensor, so the dust deposition degree can be successfully evaluated. Finally, some simulations and experiments verify the feasibility, availability and workability of the proposed irradiance solution methods and the designed evaluation strategy. The simulation and experiment results show that the errors of the solved irradiance values are always less than 2.5%. Meanwhile, these results also show that the real-time dust deposition degree can be successfully characterized by the defined indicators in this evaluation strategy, even if it is compared with other work. Therefore, this work is very beneficial to judge the energy efficiency of the PV system and plan the cleaning schedule of the PV panel.

Abstract Objective There is evidence showing both heterozygous HTRA1 and homozygous HTRA1 mutations as causal for familial cerebral small vessel disease (CSVD). The clinical and neuroimaging signs of heterozygous HTRA1‐related CSVD can mimic cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). We aimed to characterize the genotypic and phenotypic features of HTRA1‐related CSVD, and we compared the features of heterozygous HTRA1‐related CSVD and CADASIL. Methods We carried out genetic sequencing in a series of unrelated patients with suspected familial CSVD from China. Clinical and imaging characteristics of heterozygous HTRA1‐related CSVD and CADASIL were compared. Results We identified nine heterozygous HTRA1 mutations and one homozygous HTRA1 mutation, seven of which are novel. Compared with CADASIL, patients with heterozygous HTRA1‐related CSVD had a higher proportion of spine disorders and a lower proportion of white matter hyperintensities involving the anterior temporal lobe (p

Multiple sclerosis (MS) is a condition that affects the veins and small blood vessels. Previous research suggests that individuals with MS have an increased risk of vascular events and higher mortality rates. However, the relationship between MS and cerebral small vessel disease (CSVD) remains uncertain. This study aims to investigate the association between MS and lacunes. A prospective observational study was conducted, including a total of 112 participants, of which 46 had MS and 66 had CSVD. All participants underwent an MRI scan and a battery of neurological functional assessments. The presence of definite lacunes and black holes was determined through the analysis of T2-weighted, T1-weighted, and FLAIR images. The occurrence of lacunes in MS patients was found to be 19.6%. Notably, the duration of MS was identified as the sole risk factor for the development of lacune lesions in MS patients [odds ratio (OR) = 1.3, 95% confidence interval (CI) = 1.1–1.6, p = 0.008]. Comparatively, MS patients with lacunes exhibited a higher frequency of attacks and larger volumes of T2 lesions compared to MS patients without lacunes. Further analysis using receiver operating characteristic (ROC) curves showed that lacune lesions had limited ability to discriminate between MS and CSVD when disease duration exceeded 6 years. The presence of small arterial lesions in the brain of individuals with MS, along with the duration of the disease, contributes to the development of lacunes in MS patients.

Flavobacterium psychrophilum is the causative agent of rainbow trout fry syndrome and bacterial cold-water disease in salmonid fish worldwide. As an important fish pathogen, F. psychrophilum is frequently exposed to multiple invading genetic elements in natural environments. Endonuclease Cas9 provides bacteria with adaptive interference against invading genetic elements. Previous studies revealed that several F. psychrophilum strains harbored a type II-C Cas9 called Fp1Cas9, but little is known about the potential role of this endonuclease against invading genetic elements. In this work, we identified a gene encoding a novel type II-C Cas9 called Fp2Cas9 from F. psychrophilum strain CN46. Through bacterial RNA sequencing, we demonstrated active transcription of both Fp2Cas9 and pre-crRNAs in strain CN46. Bioinformatics analysis further revealed that the transcription of Fp2Cas9 and pre-crRNAs was driven by a newly integrated promoter sequence and a promoter element embedded within each CRISPR repeat, respectively. To formally demonstrate that Fp2Cas9 and associated crRNAs yielded functional interference in strain CN46, a plasmid interference assay was performed, resulting in adaptive immunity to target DNA sequences in Flavobacterium bacteriophages. Phylogenetic analysis demonstrated that Fp2Cas9 was present only in several F. psychrophilum isolates. Phylogenetic analysis revealed that this novel endonuclease was probably acquired through horizontal gene transfer from the CRISPR-Cas9 system in an unidentified Flavobacterium species. Comparative genomics analysis further showed that the Fp2Cas9 was integrated into the type II-C CRISPR-Cas locus in strain CN38 instead of the original Fp1Cas9. Taken together, our results shed light on the origin and evolution of Fp2Cas9 gene and demonstrated that this novel endonuclease provided adaptive interference against bacteriophage infections.

Flavobacterium psychrophilum, the etiological agent of bacterial coldwater disease and rainbow trout fry syndrome, causes considerable losses in salmonid aquaculture globally. Systemic F. psychrophilum infections in rainbow trout (Oncorhynchus mykiss) lead to a range of clinical signs, including ulcerative lesions in the skin and muscle and splenitis. Previous studies offered an integrative analysis of the skeletal muscle response to F. psychrophilum infection in rainbow trout. However, little is known about the molecular mechanism of immune response in the spleen, which is an important immune organ of rainbow trout. Here, we investigated the time-course splenic transcriptome profiles in uninfected rainbow trout (CK) and F. psychrophilum–infected rainbow trout at day 3 and day 7 (D3, D7) by RNA-seq analyses. Among the 7,170 differentially expressed genes (DEGs) in the three comparisons (D3 vs. CK, D7 vs. CK, D3 vs. D7), 1,286 DEGs showed consistent upregulation or downregulation at D3 and D7 and were associated with pattern recognition, acute-phase response, complement cascade, chemokine and cytokine signaling, and apoptosis. The Real time quantitative PCR (RT-qPCR) analysis of eight DEGs confirmed the accuracy of the RNA-Sequencing (RNA-seq) data. Our results reflected a general process from pathogen recognition to inflammatory cytokine generation and delineated a putative Toll-like receptor signaling pathway in rainbow trout spleen, following F. psychrophilum infection. Taken together, these results provide new insights into the molecular mechanism of the immune response to F. psychrophilum infection and are a valuable resource for future research on the prevention and control of bacterial coldwater disease during salmon culture.

Abstract Background Yersinia ruckeri is a pathogen that can cause enteric redmouth disease in salmonid species, damaging global production of economically important fish including rainbow trout (Oncorhynchus mykiss). Herein, we conducted the transcriptomic profiling of spleen samples from rainbow trout at 24 h post-Y. ruckeri infection via RNA-seq in an effort to more fully understand their immunological responses. Results We identified 2498 differentially expressed genes (DEGs), of which 2083 and 415 were up- and down-regulated, respectively. We then conducted a more in-depth assessment of 78 DEGs associated with the immune system including CCR9, CXCL11, IL-1β, CARD9, IFN, TNF, CASP8, NF-κB, NOD1, TLR8α2, HSP90, and MAPK11, revealing these genes to be associated with 20 different immunological KEGG pathways including the Cytokine-cytokine receptor interaction, Toll-like receptor signaling, RIG-I-like receptor signaling, NOD-like receptor signaling, and MAPK signaling pathways. Additionally, the differential expression of 8 of these DEGs was validated by a qRT-PCR approach and their immunological importance was then discussed. Conclusions Our findings provide preliminary insight on molecular mechanism underlying the immune responses of rainbow trout following Y. ruckeri infection and the base for future studies of host-pathogen interactions in rainbow trout.

There are some significant nonlinearity and delay issues in photovoltaic (PV) system circuits. Therefore, it is very difficult for the existing classic linear control theories to be used in PV systems; this hinders the design of the optimal energy dispatch by considering real-time generation power forecasting methods. To solve this problem, an overall linearized model with variable weather parameters (OLM-VWP) of the PV system is proposed on the basis of small-signal modeling. Meanwhile, a corresponding simplified overall linearized model with variable weather parameters (SOLM-VWP) is presented. The SOLM-VWP avoids analyzing delay characteristics of the complex high-order PV system. Moreover, it can reduce hardware cost and computation time, which makes analysis of the transient performance index of the PV system more convenient. In addition, on the basis of the OLM-VWP and SOLM-VWP, a delay-time model with variable weather parameters (DTM-VWP) of the PV system is also proposed. The delay time of the system can be accurately calculated using the DTM-VWP, and it provides a preliminary theoretical basis for carrying out real-time energy scheduling of the PV system. Finally, simulations are implemented using the MATLAB tool, and experiments are conducted. The results verify that the proposed linearization model of the PV system is accurate and reasonable under varying irradiance and temperature conditions. Meanwhile, the results also verify that the proposed SOLM-VWP and DTM-VWP of the PV system are feasible. Additionally, the results show that some transient performance indexes (delay time, rise time, settling time, and peak time) can be solved by means of equations when the circuit parameters and real-time weather parameters are given.

PurposeThe majority of solitary brain metastases appear similar to glioblastomas (GBMs) on magnetic resonance imaging (MRI). This study aimed to develop and validate an MRI-based model to differentiate intracranial metastases from GBMs using automated machine learning.Materials and MethodsRadiomics features from 354 patients with brain metastases and 354 with GBMs were used to build prediction algorithms based on T2-weighted images, contrast-enhanced (CE) T1-weighted images, or both. The data of these subjects were subjected to a nested 10-fold split in the training and testing groups to build the best algorithms using the tree-based pipeline optimization tool (TPOT). The algorithms were independently validated using data from 124 institutional patients with solitary brain metastases and 103 patients with GBMs from the cancer genome atlas.ResultsThree groups of models were developed. The average areas under the receiver operating characteristic curve (AUCs) were 0.856 for CE T1-weighted images, 0.976 for T2-weighted images, and 0.988 for a combination in the testing groups, and the AUCs of the groups of models in the independent validation were 0.687, 0.831, and 0.867, respectively. A total of 149 radiomics features were considered as the most valuable features for the differential diagnosis of GBMs and metastases.ConclusionThe models established by TPOT can distinguish glioblastoma from solitary brain metastases well, and its non-invasiveness, convenience, and robustness make it potentially useful for clinical applications.

Background and PurposeA variety of hereditary diseases overlap with neurological phenotypes or even share genes with hereditary spastic paraplegia (HSP). The aim of this study was to determine the clinical features and genetic spectrum of patients with clinically suspected HSPs.MethodsA total of 52 patients with clinically suspected HSPs were enrolled in this study. All the patients underwent next-generation sequencing (NGS) and triplet repeat primed PCR to screen for the dynamic mutations typical of spinocerebellar ataxia (SCA). Multiplex ligation-dependent probe amplification (MLPA) was further conducted in patients with no causative genetic mutations detected to examine for large deletions and duplications in genes of SPAST, ATL1, REEP1, PGN, and SPG11. Clinical characteristics and findings of brain MRI were analyzed in patients with definite diagnoses.ResultsThe mean age of the patients studied was 36.90 ± 14.57 years. 75% (39/52) of patients manifested a phenotype of complex form of HSPs. A genetic diagnosis was made in 51.9% (27/52) of patients, of whom 40.3% (21/52) of patients had mutations in HSPs genes (SPG4/SPG6/SPG8/SPG11/SPG15/SPG78/SPG5A) and 11.5% (6/52) of patients had mutations in SCAs genes (SCA3/SCA17/SCA28). SPG4 and SPG11 were the most common cause of pure form of HSPs (5/6, 83.3%) and complex form of HSPs (5/15, 33.3%), respectively. Gait disturbance was the most common initial symptom in both the patients with HSPs (15/21) and in patients with SCAs (5/6). Dysarthria and cerebellar ataxia were detected in 28.5% (6/21) and 23.8% (5/21) of patients with HSPs, respectively, and were the most common symptoms in addition to progressive weakness and spasticity of the lower limbs. Cerebellar atrophy was seen on the brain MRI of patients with SPG5A, SCA3, and SCA28.ConclusionCausative genetic mutations were identified in 51.9% of patients with clinically suspected HSPs by NGS and triplet repeat primed PCR. A final diagnosis of HSPs or SCAs was made in 40.3% and 11.5% of patients, respectively. The clinical manifestations and neuroimaging findings overlapped between patients with HSPs and patients with SCAs. Dynamic mutations should be screened in patients with clinically suspected HSPs, especially in those with phenotypes of complex form of HSPs.

Nowadays, with the high development of photovoltaic (PV) technique and tourist industry, PV system is used in remote tourist area more and more widely. However, in practical application, the design, planning and layout involved in them are usually very difficult because the direct relationship between them is absent. To solve this problem, in this paper, some mathematical expressions and their constraint conditions are proposed by analyzing the power relationships between PV system and tourism facilities. By them, the power coupling characteristics between PV system and remote tourist area can be clearly shown. Finally, some simulation experiments are done to analyze the tourism facilities installed in two areas where the degree of difficulty in constructing the electricity grid is different. Meanwhile, a simulation experiment for a whole tourist area is also conducted. The simulation results not only show that the presented power coupling characteristics is accurate and reasonable, but also illustrate that the real-time simulation analysis based on them is feasible and available regardless of a single tourism facility or a whole tourist area.

For the conventional four-parameter model of photovoltaic (PV) cell, to simplify the number of its mathematical equations, in this paper, a variable-weather-parameter cell model (VWP model) is proposed. Furthermore, to decrease the number of its model parameters, a simplified variable-weather-parameter cell model (SVWP model) is also proposed. Based on them, the model parameters of linear equivalent models can be replaced by the conventional four-parameter model parameters, which finds the direct relationships between linear equivalent cell model and four-parameter cell model. Finally, some simulation experiments are done by comparing the proposed VWP and SVWP models with conventional four-parameter model of PV cell. The results show that, on the one hand, their output characteristics almost correspond with each other. On the other hand, these proposed cell models are very accurate under varying irradiance or temperature conditions. Meanwhile, some simulation experiments also verify that the linear equivalent models expressed by the VWP model and SVWP model are feasible, available and reasonable. By this work, both the conventional four-parameter model and linear equivalent models are greatly evolved and improved. On the one hand, the conventional four-parameter model can be greatly simplified, which makes its modeling and application easier. On the other hand, the bridge between it and linear equivalent models can be built successfully, which makes these linear models more standard and practical.

ObjectiveSimilar white matter hyperintensities (WMH) might have different impact on the cognitive outcomes in patients with cerebral small vessel disease (CSVD). This study is to assess the possible factors related to the heterogeneity of WMH in cognitively impaired patients with CVSD.MethodsWe analyzed data from a cohort of patients with CVSD who were recruited consecutively from the Beijing Tiantan Hospital from 2015 to 2020. WMH, lacunes, enlarged perivascular space (ePVS), microbleeds and lacunar infarcts were rated on brain MRI. A score of

ABSTRACT Flavobacterium psychrophilum, the etiological agent of bacterial coldwater disease (BCWD) and rainbow trout fry syndrome, causes great economic losses in salmonid aquaculture worldwide. Recent molecular studies have uncovered important epidemiological and ecological aspects of this pathogen; however, such data are lacking for F. psychrophilum populations affecting aquaculture in China. Herein, F. psychrophilum phenotype, genotype, and virulence were characterized for isolates recovered from epizootics in multiple salmonid aquaculture facilities across China. Thirty-one F. psychrophilum isolates, originating from four provinces and three host fish species, were predominantly homogeneous biochemically but represented 5 sequence types (STs) according to multilocus sequence typing (MLST) that belonged to clonal complex CC-ST10 or 3 newly recognized singleton STs. PCR-based serotyping classified 19 and 12 F. psychrophilum isolates into molecular serotypes 1 and 0, respectively, showing an obvious relationship with host species. Antimicrobial susceptibility analysis via broth microdilution revealed reduced susceptibility to enrofloxacin, flumequine, and oxolinic acid, moderate susceptibility to gentamicin, erythromycin, and florfenicol, and variable susceptibility to ampicillin and oxytetracycline. In vivo challenge experiments confirmed the ability of two representative Chinese F. psychrophilum isolates to induce typical signs of BCWD and mortality in 1-year-old rainbow trout (Oncorhynchus mykiss). Findings collectively demonstrate (i) that BCWD outbreaks in China studied thus far are caused by F. psychrophilum lineages that are common on other continents (e.g., CC-ST10) and others that have not been reported elsewhere (e.g., ST355, ST356, ST357), (ii) that F. psychrophilum molecular serotypes distinguish isolates from different host fish species, even within STs, and (iii) reduced F. psychrophilum antimicrobial susceptibility against compounds used for BCWD control in China. IMPORTANCE Flavobacterium psychrophilum causes substantial economic losses in salmonid aquaculture worldwide. Although this bacterium is also believed to be a disease source in China, published reports of its presence do not yet exist. Herein, F. psychrophilum was linked to multiple disease outbreaks in several salmonid aquaculture facilities within four Chinese provinces, and polyphasic characterization revealed that most isolates were genetically distinct from strains recovered on other continents. Analyses further revealed the predominating molecular serotypes, antimicrobial susceptibility profiles, and pathogenic potential of two representative recovered isolates. Collectively, the results presented here provide important data on the epidemiology and disease ecology of F. psychrophilum in China and pave the way for targeted prevention and control methods to be pursued in the future.

The control signals of the variable-weather-parameter (VWP) methods need to be calculated by the real-time measured data of the irradiance and temperature (I&T) sensors, which leads to the high hardware cost of the sensors. To solve this problem, the PV system with a DC bus is selected as the research subject and a novel maximum power point tracking (MPPT) method is proposed. It is named the VWP MPPT method based on the equation solution (ES-VWP method). Its control signal is directly calculated by the solution of an established equation set rather than data measured by the I&T sensors. This equation set consists of two integrated mathematical equations, which represent two different operating points of the PV system. Meanwhile, when the bus voltage is varying or unknown, a calculation method that can estimate the real-time value of the DC bus voltage is proposed. In addition, an implementation method corresponding to the ES-VWP method is also designed. Finally, some simulation experiments are carried out to verify the availability and feasibility of the ES-VWP method. Meanwhile, some simulation experiments show that the error of the equation solution is less than 0.0001. In addition, some simulation experiments illustrate that the MPPT settling times of the ES-VWP method are always less than one-tenth of the P&O method (or one-sixth of the FLC method). Compared with the existing VWP methods, it can be implemented without the use of I&T sensors or external I&T data. Meanwhile, compared with other existing MPPT methods, its better MPPT rapidity originating from the advantage of the VWP methods is inherited. This work is the first attempt to design a novel MPPT method by obtaining the real-time equation solutions of Voc and Isc. Meanwhile, this work is also the first attempt to solve the real-time equation of Vbus by the solved Voc and Isc. In addition, this work is also the first attempt to design an implementation method for establishing an equation set by sampling two operating points of a PV system at the same time.

PurposeThe present study aimed to preoperatively predict the status of 1p/19q based on radiomics analysis in patients with World Health Organization (WHO) grade II gliomas.MethodsThis retrospective study enrolled 157 patients with WHO grade II gliomas (76 patients with astrocytomas with mutant IDH, 16 patients with astrocytomas with wild-type IDH, and 65 patients with oligodendrogliomas with mutant IDH and 1p/19q codeletion). Radiomic features were extracted from magnetic resonance images, including T1-weighted, T2-weighted, and contrast T1-weighted images. Elastic net and support vector machines with radial basis function kernel were applied in nested 10-fold cross-validation loops to predict the 1p/19q status. Receiver operating characteristic analysis and precision-recall analysis were used to evaluate the model performance. Student’s t-tests were then used to compare the posterior probabilities of 1p/19q co-deletion prediction in the group with different 1p/19q status.ResultsSix valuable radiomic features, along with age, were selected with the nested 10-fold cross-validation loops. Five features showed significant difference in patients with different 1p/19q status. The area under curve and accuracy of the predictive model were 0.8079 (95% confidence interval, 0.733–0.8755) and 0.758 (0.6879–0.8217), respectively, and the F1-score of the precision-recall curve achieved 0.6667 (0.5201–0.7705). The posterior probabilities in the 1p/19q co-deletion group were significantly different from the non-deletion group.ConclusionCombined radiomics analysis and machine learning showed potential clinical utility in the preoperative prediction of 1p/19q status, which can aid in making customized neurosurgery plans and glioma management strategies before postoperative pathology.

Abstract Objective To predict vascular endothelial growth factor (VEGF) expression in patients with diffuse gliomas using radiomic analysis. Materials and methods Preoperative magnetic resonance images were retrospectively obtained from 239 patients with diffuse gliomas (World Health Organization grades II–IV). The patients were randomly assigned to a training group (n = 160) or a validation group (n = 79) at a 2:1 ratio. For each patient, a total of 431 radiomic features were extracted. The minimum redundancy maximum relevance (mRMR) algorithm was used for feature selection. A machine-learning model for predicting VEGF status was then developed using the selected features and a support vector machine classifier. The predictive performance of the model was evaluated in both groups using receiver operating characteristic curve analysis, and correlations between selected features were assessed. Results Nine radiomic features were selected to generate a VEGF-associated radiomic signature of diffuse gliomas based on the mRMR algorithm. This radiomic signature consisted of two first-order statistics or related wavelet features (Entropy and Minimum) and seven textural features or related wavelet features (including Cluster Tendency and Long Run Low Gray Level Emphasis). The predictive efficiencies measured by the area under the curve were 74.1% in the training group and 70.2% in the validation group. The overall correlations between the 9 radiomic features were low in both groups. Conclusions Radiomic analysis facilitated efficient prediction of VEGF status in diffuse gliomas, suggesting that using tumor-derived radiomic features for predicting genomic information is feasible.

The detection of mutations in telomerase reverse transcriptase promoter (pTERT) is important since preoperative diagnosis of pTERT status helps with evaluating prognosis and determining the surgical strategy. Here, we aimed to establish a radiomics-based machine-learning algorithm and evaluated its performance with regard to the prediction of mutations in pTERT in patients with World Health Organization (WHO) grade II gliomas. In total, 164 patients with WHO grade II gliomas were enrolled in this retrospective study. We extracted a total of 1,293 radiomics features from multi-parametric magnetic resonance imaging scans. Elastic net (used for feature selection) and support vector machine with linear kernel were applied in nested 10-fold cross-validation loops. The predictive model was evaluated by receiver operating characteristic and precision-recall analyses. We performed an unpaired t-test to compare the posterior predictive probabilities among patients with differing pTERT statuses. We selected 12 valuable radiomics features using nested 10-fold cross-validation loops. The area under the curve (AUC) was 0.8446 (95% confidence interval [CI], 0.7735–0.9065) with an optimal summed value of sensitivity of 0.9355 (95% CI, 0.8802–0.9788) and specificity of 0.6197 (95% CI, 0.5071–0.7371). The overall accuracy was 0.7988 (95% CI, 0.7378–0.8598). The F1-score was 0.8406 (95% CI, 0.7684–0.902) with an optimal precision of 0.7632 (95% CI, 0.6818–0.8364) and recall of 0.9355 (95% CI, 0.8802–0.9788). Posterior probabilities of pTERT mutations were significantly different between patients with wild-type and mutant TERT promoters. Our findings suggest that a radiomics analysis with a machine-learning algorithm can be useful for predicting pTERT status in patients with WHO grade II glioma and may aid in glioma management.

Background and objective: Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is an inherited systemic arteriopathy, the classic feature of which is small vessel lesions. Studies on intracranial large arteries in CADASIL are not common. We aim to evaluate intracranial large arteries, describing the characteristics of large arteries in CADASIL and their association with cerebral small vessel associated lesions.Methods: Consecutive CADASIL patients from a single-center prospective cohort were analyzed. Brain magnetic resonance imaging and magnetic resonance angiography were performed to assess the intracranial large arteries and cerebral small vessels associated lesions' neuroimaging.Results: The study included 37 CADASIL patients. Of the patients, 28 of them (75.7%) had intracranial large artery abnormalities. Eighteen (48.6%) had congenital variations such as fenestration, vertebral artery (VA) hypoplasia and agenesis, or common trunk and fetus posterior cerebral artery. Seventeen (45.9%) had acquired anomalies such as arterial stenosis, prolongation, or tortuosity (seven of them had both congenital and acquired anomalies). CADASIL patients with anterior circulation middle cerebral artery (MCA) or internal cerebral artery (ICA) severe stenosis were more likely to have ipsilateral asymmetric white matter hyper-density (WMH) distribution. Patients with posterior circulation VA hypoplasia had a higher prevalence of posterior subcortical zone dominant WMH distribution.Conclusion: CADASIL patients can demonstrate various intracranial large artery abnormalities which might influence the development of microangiopathy. Assessment of great vessels seems essential in CADASIL.

Abstract The presence of contrast enhancement (CE) on magnetic resonance (MR) imaging is conventionally regarded as an indicator for tumor malignancy. However, the biological behaviors and molecular mechanism of enhanced tumor are not well illustrated. The aim of this study was to investigate the molecular profiles associated with anaplastic gliomas (AGs) presenting CE on postcontrast T1‐weighted MR imaging. In this retrospective database study, RNA sequencing and MR imaging data of 91 AGs from the Cancer Genome Atlas (TCGA) and 64 from the Chinese Glioma Genome Atlas (CGGA) were collected. Gene set enrichment analysis (GSEA), significant analysis of microarray, generalized linear models, and Least absolute shrinkage and selection operator algorithm were used to explore radiogenomic and prognostic signatures of AG patients. GSEA indicated that angiogenesis and epithelial‐mesenchymal transition were significantly associated with post‐CE. Genes driving immune system response, cell proliferation, and focal adhesions were also significantly enriched. Gene ontology of 237 differential genes indicated consistent results. A 48‐gene signature for CE was identified in TCGA and validated in CGGA dataset (area under the curve = 0.9787). Furthermore, seven genes derived from the CE‐specific signature could stratify AG patients into two subgroups based on overall survival time according to corresponding risk score. Comprehensive analysis of post‐CE and genomic characteristics leads to a better understanding of radiology‐pathology correlations. Our gene signature helps interpret the occurrence of radiological traits and predict clinical outcomes. Additionally, we found nine prognostic quantitative radiomic features of CE and investigated the underlying biological processes of them.

The white matter disease spectrum is associated with many genetic diseases, including AARS2, CADASIL, ALD, and others. In this study, to determine the novel alanyl-tRNA synthetase 2 mutation implicated in white matter disease, several families with an autosomal recessive inheritance pattern of white matter disease were analyzed by whole-exome sequencing. Variants were prioritized according to their rarity and pathogenic variants in genes already known to be associated with leukodystrophies and were confirmed by Sanger sequencing using standard protocols. We identified 5 rare variants (c.452T>C chr6:44279256 p.M151T, c.1871G>A chr6:44272054 p.W624X, c.802A>G chr6:44278128 p.M268V, c.1703-1704del chr6:-44272430-44272431 p.Q568fs, and c.179C>A chr6-44280882 p.P60H) with varying expression in 4 independent Chinese families with leukodystrophy. These single nucleotide variants (SNVs), or deletion mutations, each induced a frameshift, causing a missense mutation in alanyl-tRNA synthetase 2. These findings suggested that all mutations might contribute to the development of leukodystrophy in the examined family members. Combined with previous findings, our data confirmed that the novel mutations are located in leukodystrophy-related risk genes. We also summarized all the alanyl-tRNA synthetase 2 mutations related to the onset of leukodystrophies in adults.

Objective: The aim of this study was to develop a radiomics signature for prediction of progression-free survival (PFS) in lower-grade gliomas and to investigate the genetic background behind the radiomics signature. Methods: In this retrospective study, training (n = 216) and validation (n = 84) cohorts were collected from the Chinese Glioma Genome Atlas and the Cancer Genome Atlas, respectively. For each patient, a total of 431 radiomics features were extracted from preoperative T2-weighted magnetic resonance images. A radiomics signature was generated in the training cohort, and its prognostic value was evaluated in both the training and validation cohorts. The genetic characteristics of the group with high-risk scores were identified by radiogenomic analysis, and a nomogram was established for prediction of PFS. Results: There was a significant association between the radiomics signature (including 9 screened radiomics features) and PFS, which was independent of other clinicopathologic factors in both the training (P

Background: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images. Methods: Preoperative MR images were retrospectively obtained from 272 patients with primary grade II/III gliomas. The patients were randomly allocated in a 2:1 ratio to a training (n=180) or validation (n=92) set. A total of 431 radiomic features were extracted from each patient. The lest absolute shrinkage and selection operator (LASSO) method was used for feature selection and radiomic signature construction. Subsequently, a machine-learning model to predict p53 status was established using the selected features and a Support Vector Machine classifier. The predictive performance of all individual features and the model was calculated using receiver operating characteristic curves in both the training and validation sets. Results: The p53-related radiomic signature was built using the LASSO algorithm; this procedure consisted of four first-order statistics or related wavelet features (including Maximum, Median, Minimum, and Uniformity), a shape and size-based feature (Spherical Disproportion), and ten textural features or related wavelet features (including Correlation, Run Percentage, and Sum Entropy). The prediction accuracies based on the area under the curve were 89.6% in the training set and 76.3% in the validation set, which were better than individual features. Conclusions: These results demonstrate that MR image texture features are predictive of p53 mutation status in lower-grade gliomas. Thus, our procedure can be conveniently used to facilitate presurgical molecular pathological diagnosis. Keywords: p53, Lower-grade gliomas, Radiogenomics, Prediction, Machine learning

The real-time linearization of a photovoltaic (PV) cell has been implemented well by the proposition of two maximum power point (MPP) linear models (MPP Thevenin cell model and MPP Norton cell model). However, there is no work to specially analyze the circuit parameter range (CPR) to correctly use them, which seriously impedes the development of the linear control theory involving them. To deal with this problem, in this paper, PV systems with three usual outputs are analyzed and the expressions of their CPR are proposed under ideal conditions. Meanwhile, these expressions are improved to match the practical application. They disclose the relationships between load (or bus voltage) and model parameters of the MPP Thevenin cell model (MPP-TCM) when the MPP of PV system always exists. They also reveal the constraints of load (or bus voltage) when the MPP-TCM is always available. Finally, by some simulation experiments, the accuracy of the expressions of the CPR is verified, the regular patterns of the CPR changing with weather are disclosed, and the comparison of the CPR for different PV systems are made. In this work, the relationships between MPP-TCM and circuit parameters are successfully found, disclosing the constraints among parameters when the MPP-TCM is used to implement the overall linearization of a PV system.

Abstract Necrosis is a hallmark feature of glioblastoma (GBM). This study investigated the prognostic role of necrotic patterns in GBM using fractal dimension (FD) and lacunarity analyses of magnetic resonance imaging (MRI) data and evaluated the role of lacunarity in the biological processes leading to necrosis. We retrospectively reviewed clinical and MRI data of 95 patients with GBM. FD and lacunarity of the necrosis on MRI were calculated by fractal analysis and subjected to survival analysis. We also performed gene ontology analysis in 32 patients with available RNA-seq data. Univariate analysis revealed that FD 0.46 significantly correlated with poor progression-free survival (p = 0.006 and p = 0.012, respectively) and overall survival (p = 0.008 and p = 0.005, respectively). Multivariate analysis revealed that both parameters were independent factors for unfavorable progression-free survival (p = 0.001 and p = 0.015, respectively) and overall survival (p = 0.002 and p = 0.007, respectively). Gene ontology analysis revealed that genes positively correlated with lacunarity were involved in the suppression of apoptosis and necrosis-associated biological processes. We demonstrate that the fractal parameters of necrosis in GBM can predict patient survival and are associated with the biological processes of tumor necrosis.

Background Ivermectin (IVM) has been widely used in the aquaculture industry since its efficacy against parasites. However, the degradation of IVM was very slow in aquatic environments and the environmental fate of IVM in a complete aquatic system was still not clear. Therefore, comparable studies in a complete aquatic system were merited and helped to elucidate the environmental fate and effects of IVM. Methods An aquatic micro-ecological system containing an aquatic environment (water and sediment) and aquatic organisms (invertebrates, aquatic plants and fish) was built to simulate the natural rearing conditions. A single dose of 0.3 mg kg−1 body weight of IVM was given to the fish by oral gavage. Water, sediment, the roots and leaves of the aquatic plants, the soft tissue of the invertebrates and the visceral mass and muscle of fish samples were collected at 0.5 hours, 1 day, 7 days, 15 days, 30 days, 45 days, 60 days and 70 days after the treatment. IVM concentration in each sample was determined using ELISA method. Results IVM was quickly and widely distributed into the whole aquatic system in one day, and then was highly accumulated in organisms resulting in long-term residues. IVM was exchanged multiple times between the different media, which caused continuous fluctuations in the concentration of IVM in the water and sediment. It was worth noting that there was a second peak value of IVM in the fish and invertebrates after 30 days. The environmental fate of the IVM in the aquatic micro-ecological system showed that the drug was transferred from the fish to aquatic plants in the first seven days, and then gathered in the water and sediment, finally accumulating in the invertebrates. Our results indicated that an effective aquatic micro-ecological system was successfully established, and it could be applied to the study the environmental fate of IVM, which will aid the scientific use of this anti-parasitic agent during aquaculture.

Abstrct: Objectives: To investigate the association between proton magnetic resonance spectroscopy (1H-MRS) metabolic features and the grade of gliomas, and to establish a machine-learning model to predict the glioma grade. Methods: This study included 112 glioma patients who were divided into the training (n = 74) and validation (n = 38) sets based on the time of hospitalization. Twenty-six metabolic features were extracted from the preoperative 1H-MRS image. The Student's t-test was conducted to screen for differentially expressed features between low- and high-grade gliomas (WHO grades II and III/IV, respectively). Next, the minimum Redundancy Maximum Relevance (mRMR) algorithm was performed to further select features for a support vector machine (SVM) classifier building. Performance of the predictive model was evaluated both in the training and validation sets using ROC curve analysis. Results: Among the extracted 1H-MRS metabolic features, thirteen features were differentially expressed. Four features were further selected as grade-predictive imaging signatures using the mRMR algorithm. The predictive performance of the machine-learning model measured by the AUC was 0.825 and 0.820 in the training and validation sets, respectively. This was better than the predictive performances of individual metabolic features, the best of which was 0.812. Conclusions: 1H-MRS metabolic features could help in predicting the grade of gliomas. The machine-learning model achieved a better prediction performance in grading gliomas than individual features, indicating that it could complement the traditionally used metabolic features. Keywords: Proton magnetic resonance spectroscopy, Machine learning, Glioma grading, Support vector machine

Background and objective: Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the best known and the most common monogenic small vessel disease (SVD). Cognitive impairment is an inevitable feature of CADASIL. Total SVD score and global cortical atrophy (GCA) scale were found to be good predictors of poor cognitive performance in community-dwelling adults. We aimed to estimate the association between the total SVD score, GCA scale and the cognitive performance in patients with CADASIL.Methods: We enrolled 20 genetically confirmed CADASIL patients and 20 controls matched by age, gender, and years of education. All participants underwent cognitive assessments to rate the global cognition and individual domain of executive function, information processing speed, memory, language, and visuospatial function. The total SVD score and GCA scale were rated.Results: The CADASIL group performed worse than the controls on all cognition measures. Neither global cognition nor any separate domain of cognition was significantly different among patients grouped by total SVD score. Negative correlations between the GCA score and cognitive performance were observed. Approximately 40% of the variance was explained by the total GCA score in the domains of executive function, information processing speed, and language. The superficial atrophy score was associated with poor performance in most of the domains of cognition. Adding the superficial atrophy score decreased the prediction power of the deep atrophy score on cognitive impairment alone.Conclusions: The GCA score, not the total SVD score, was significantly associated with poor cognitive performance in patients with CADASIL. Adding the superficial atrophy score attenuated the prediction power of the deep atrophy score on cognitive impairment alone.

In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the movement velocity of the buoy using the Doppler frequency shift of satellite GPS signals, and then to calculate the wave parameters from the movement velocity according to ocean wave theory. The shortage of the GPS wave buoy is the occasional occurrence of some unusual values in the movement velocity. This is mainly due to the fact that the GPS antenna is occasionally covered by sea water and cannot normally receive high-quality satellite GPS signals. The traditional solution is to remove these unusual movement velocity values from the records, which requires furthering extend the acquisition time of satellite GPS signals to ensure there is a large enough quantity of effective movement velocity values. Based on the traditional GPS wave measurement technology, this paper presents the algorithmic flow and proposes two improvement measures. On the one hand, the neural network algorithm is used to correct the unusual movement velocity data so that extending the acquisition time of satellite GPS signals is not necessary and battery power is saved. On the other hand, the Gaussian low-pass filter is used to correct the raw directional wave spectrum, which can further eliminate the influence of noise spectrum energy and improve the measurement accuracy. The on-site sea test of the SBF7-1A GPS wave buoy, developed by the National Ocean Technology Center in China, and the gravity-acceleration-type DWR-MKIII Waverider buoy are highlighted in this article. The wave data acquired by the two buoys are analyzed and processed. It can be seen from the processed results that the ocean wave parameters from the two kinds of wave buoys, such as wave height, wave period, wave direction, wave frequency spectrum, and directional wave spectrum, are in good consistency, indicating that the SBF7-1A GPS wave buoy is comparable to the traditional gravity-acceleration-type wave buoy in terms of its accuracy. Therefore, the feasibility and validity of the two improvement measures proposed in this paper are confirmed.

Induced neural stem cells (iNSCs) can be directly transdifferentiated from somatic cells. One potential clinical application of the iNSCs is for nerve regeneration. However, it is unknown whether iNSCs function in disease models. We produced transdifferentiated iNSCs by conditional overexpressing Oct4, Sox2, Klf4, c-Mycin mouse embryonic fibroblasts. They expanded readily in vitro and expressed NSC mRNA profile and protein markers. These iNSCs differentiated into mature astrocytes, neurons and oligodendrocytes in vitro. Importantly, they reduced lesion size, promoted the recovery of motor and sensory function as well as metabolism status in middle cerebral artery stroke rats. These iNSCs secreted nerve growth factors, which was associated with observed protection of neurons from apoptosis. Furthermore, iNSCs migrated to and passed through the lesion in the cerebral cortex, where Tuj1+ neurons were detected. These findings have revealed the function of transdifferentiated iNSCs in vivo, and thus provide experimental evidence to support the development of personalized regenerative therapy for CNS diseases by using genetically engineered autologous somatic cells.

Magnetic Resonance Spectroscopy (MRS) can measure in vivo brain tissue metabolism that exhibits unique biochemical characteristics in brain tumors. For clinical application, an efficient and versatile quantification method of MRS would be an important tool for medical research, particularly for exploring the scientific problem of tumor monitoring. The objective of our study is to propose an automated MRS quantitative approach and assess the feasibility of this approach for glioma grading, prognosis and boundary detection.An automated quantitative approach based on a convex envelope (AQoCE) is proposed in this paper, including preprocessing, convex-envelope based baseline fitting, bias correction, sectional baseline removal, and peak detection, in a total of 5 steps. Some metabolic ratios acquired by this quantification are selected for statistical analysis. An independent sample t-test and the Kruskal-Wallis test are used for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and for detecting the tumor, peritumoral and contralateral areas, respectively. Seventy-eight cases of pre-operative brain gliomas with pathological reports are included in this study.Cho/NAA, Cho/Cr and Lip-Lac/Cr (LL/Cr) calculated by AQoCE in the tumor area differ significantly between LGG and HGG, with p≤0.005. Using logistic regression combining Cho/NAA, Cho/Cr and LL/Cr to generate a ROC curve, AQoCE achieves a sensitivity of 92.9%, a specificity of 72.2%, and an area under ROC curve (AUC) of 0.860. Moreover, both Cho/NAA and Cho/Cr in the AQoCE approach show a significant difference (p≤0.019) between tumoral, peritumoral, and contralateral areas. The comparison between the results of AQoCE and Siemens MRS processing software are also discussed in this paper.The AQoCE approach is an automated method of residual water removal and metabolite quantification. It can be applied to multi-voxel 1H-MRS for evaluating brain glioma grading and demonstrating characteristics of brain glioma metabolism. It can also detect infiltration in the peritumoral area. Under the limited clinical data used, AQoCE is significantly more versatile and efficient compared to the reference approach of Siemens.

OBJECTIVES: Seizure is a common presenting symptom of primary brain tumors. There are no published studies regarding the roles of MicroRNA (miRNA) in tumor-related epilepsy. The authors set out to correlate miR-196b expression in low-grade glioma patients with pre-operative seizures and post-operative seizure control. METHODS: Twenty-three patients with WHO grade II astrocytomas and 83 similar patients for independent validation were included. Follow-up visits regarding seizure prognosis were scheduled at 6 months. MiRNA profiling was used to identify differentially expressed miRNAs. The most important miRNA was determined by quantitative reverse-transcriptase polymerase chain reaction (q-PCR) in the validation cohort. Gene ontology (GO) analysis and whole genome mRNA profiling was performed to investigate the underlying biological processes. RESULTS: Array results showed that 30 miRNAs were overexpressed and 10 miRNAs were underexpressed (with more than 2 fold change) in patients with pre-operative seizures. MiR-196b was validated in the independent validation cohort. Patients with good seizure prognosis exhibited low levels of miR-196b expression compared with those who had poor seizure prognosis in the group without pre-operative seizures. Biological processes that relate to transcription and cell cycles were over-represented in the miR-196b-associated gene expression signature. MiR-196b-associated gene expression profiling was characterized by enrichment of genes usually involved in cell proliferation. CONCLUSIONS: We have provided the first evidence that expression of miR-196b was associated with the occurrence of pre-operative seizures in low-grade gliomas, and may predict seizure prognosis in patients without pre-operative seizures. Targeted treatments that decrease endogenous levels of miR-196b might represent novel therapeutic strategies.