bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on force model and characteristics of large wind turbine pitch system based on SCADA data
Authors: Li Mimi , Dai Juchuan , Zhang Fan , Liu Deshun
Published: June 2023

In large-scale wind turbines, the force state of the pitch system greatly influences safe operation and service life. This paper provides a novel method to estimate blade pitch load, bearing friction torque, and motor pitch torque. In this method, the force equilibrium equations are established by investigating the force of the pitch system under multiple operating conditions. The multidimensional BIN method is employed to classify the supervisory control and data acquisition (SCADA) data of wind turbines into several intervals. The multidimensional scatter data is processed in a single-valued way. Then, the estimating model of the pitch system forces is established by combining the obtained data and the equilibrium equations. Taking a 2 MW wind turbine as an example, the variation characteristics of blade pitch load, bearing friction torque, and motor pitch torque under multiple operating conditions are analyzed. Some interesting and valuable conclusions are obtained. For example, when the wind speed increases, the blade pitch load increases significantly in the maximum wind energy tracking region, but there is no obvious change in the observed constant power output region. The wind speed and azimuth have little effect on the bearing friction torque. The variation trend of motor pitch torque is consistent with that of blade pitch load in the maximum wind energy tracking region.
Experimental study on friction pressure drop and circumferential heat transfer characteristics in helical tubes
Authors: Zheng Xiong , Lu Xianghui , Gao Yaxin , Jin Desheng , Hu Yisong , Hu Yousen , Mao Yulong
Published: June 2023

Helical tubes are widely used in nuclear plants, heat recovery process, and refrigeration technology. The fluid is influenced by centrifugal force flow through the helical tube, accompanied by secondary flow which is conducive to the enhancement of heat transfer. However, the uneven circumferential heat transfer caused by the secondary flow was seldom reported, while the pressure drops and heat transfer characteristics of helical tubes under single-phase and two-phase flow conditions need to be supplemented. This paper investigated the friction pressure drop and circumferential heat transfer characteristics based on the experiments on helical tubes with the coil diameter to the tube diameter varying from 28.5 to 128.5 and lift angle varying from 3° to 10°. The results showed that the coil diameter was the key parameter affecting the pressure drop and non-uniform circumferential heat transfer, compared with the lift angle. At the same cross section, the heat transfer coefficient at the outside tube wall was the highest, which was more obvious under small coil diameter conditions. Correlations of flow resistance and heat transfer were proposed for the single-phase and saturated boiling two-phase flow, respectively, and the predicted values were improved compared with the prediction results of correlations in the existing literature.
Based on the difference of Newton’s method integrated energy system distributed collaborative optimization
Authors: Liu Xinying , Chen Xu , Ke Xinyu
Published: June 2023

With the integration of renewable energy into the grid, the traditional power system stability faced by huge challenges, and the development of integrated energy system, it is of essence to improve the coupling of multiple integrated energy systems of different types, management in the integrated energy system and reduce the pressure of communication and computing, in this paper, we construct a distributed Newton algorithm based on Newton’s method to accelerate the solving speed, which decreases the times of iterations to reduce the pressure of communication and calculation, saving the cost of operation. Besides, privacy protection is particularly important for a distributed control system, under the premise that calculation speed is guaranteed, meanwhile, privacy protection of all agents in an integrated energy system is also critical. This study uses annular directed distributed algorithm to enhance the privacy of integrated distributed energy systems in the intelligent body, so as to fully ensure the privacy safety of all agents in the system. Moreover, the forementioned difference Newton algorithm in this study avoid the behavior of Zeno, greatly accelerating the speed of iteration and finding the best energy market price,. At the same time, the privacy safety of all agentsin the distributed energy system are ensured. Finally, a distributed integrated energy system based on the algorithm proposed by this study has went through theoretical proof and simulation experiment, whose result shows the validity of the algorithm.
Determining sources of reactive mercury compounds in Reno, Nevada, United States
Authors: Gustin Mae Sexauer , Dunham-Cheatham Sarrah M. , Choma Nicole , Shoemaker Kevin T. , Allen Natalie
Published: June 2023

There is much uncertainty regarding the sources of reactive mercury (RM) compounds and atmospheric chemistry driving their formation. This work focused on assessing the chemistry and potential sources of reactive mercury measured in Reno, Nevada, United States, using 1 year of data collected using Reactive Mercury Active System. In addition, ancillary meteorology and criteria air pollutant data, Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) analyses, and a generalized linear model were applied to better understand reactive mercury observations. During the year of sampling, a fire event impacted the sampling site, and gaseous elemental Hg and particulate-bound mercury concentrations increased, as did HgII-S compounds. Data collected on a peak above Reno showed that reactive mercury concentrations were higher at higher elevation, and compounds found in Reno were the same as those measured on the peak. HYSPLIT results demonstrated RM compounds were generated inside and outside of the basin housing Reno. Compounds were sourced from San Francisco, Sacramento, and Reno in the fall and winter, and from long-range transport and the marine boundary layer during the spring and summer. The generalized linear model produced correlations that could be explained; however, when applying the model to similar data collected at two other locations, the Reno model did not predict the observations, suggesting that sampling location chemistry and concentration cannot be generalized.
Contribution of the Fenton reaction to the degradation of carbon nanotubes by enzymes
Authors: Takahashi Seira , Taguchi Fumiko , Hori Katsutoshi
Published: June 2023

The widespread use of carbon nanotubes (CNTs) has raised concerns about the human health and ecological effects of CNTs released into the environment. Bacteria play an important role in bioremediation and waste treatment, and their enzymes are mostly responsible for the degradation of contaminants. However, there are still only a few reports about the bacterial degradation of CNTs, and evidence showing the involvement of bacterial enzymes in CNT degradation with their mechanisms has never been reported. The purpose of this study is to clarify whether CNTs can be degraded by bacterial enzymes. In this study, the degradation of oxidized (carboxylated) single-walled CNTs (O-SWCNTs) by mt2DyP, a dye-decolorizing peroxidase of Pseudomonas putida mt-2, a common soil bacterium, was investigated. After incubation of O-SWCNTs with recombinant mt2DyP and its substrate H2O2 for 30 d, the optical absorbance and Raman spectra revealed the degradation of O-SWCNTs. However, inactivation of the enzyme was observed within 60 min of the start of incubation, suggesting that the degradation of O-SWCNTs occurred nonenzymatically. The inactivation of mt2DyP was accompanied by the release of iron, the active center metal, and degradation of O-SWCNTs was significantly inhibited in the presence of diethylenetriamine pentaacetic acid, a chelating agent, indicating that O-SWCNTs were degraded by the Fenton reaction with iron released from mt2DyP and H2O2. The same phenomenon was observed with P450, which is also a heme enzyme. Furthermore, we investigated the contribution of the Fenton reaction to the O-SWCNT degradation by horseradish peroxidase (HRP), which was reported to enzymatically and rapidly degrade O-SWCNTs. Our results revealed that the degradation of O-SWCNTs in the presence of HRP is also mainly due to the Fenton reaction, with negligible enzymatic degradation. This contradicts the report showing enzymatic degradation of O-SWCNTs by HRP but supports the subsequent report quantitatively showing very slow transformation of O-SWCNTs by HRP. The current results emphasize that the Fenton reaction, which has received little attention in CNT degradation by heme enzymes, must be taken into consideration and will contribute to the development of a simple disposal method for CNTs, utilizing the Fenton reaction with bacteria/bacterial enzymes and H2O2.
Spatiotemporal trends and factors influencing online attention for China’s tea industry
Authors: Shu Rentian , Xiao Jingyi , Su Zhucheng
Published: June 2023

In the context of the “Internet plus” era, the study of tea industry online attention is a new perspective in research on the tea industry and an opportunity for the sustainable and high-quality development of this industry. Based on the Baidu index, this paper obtains web attention data from 2012 to 2021, analyzes the spatial and temporal evolution characteristics of online attention using the seasonal concentration index and geographic concentration index, and quantitatively discusses the influencing factors using correlation analysis and GeoDetector. The results show the following: The interannual change in China’s tea industry online attention shows “rapid growth, high level of stability, slow decline,” the monthly distribution has an intense concentration, mainly in March-April and October, and the interday distribution of attention peaks on weekdays. The spatial distribution shows an intense geographical concentration, with an overall trend of “light concentration first, then light dispersion.” The migration trajectory of the center of attention is tilted toward the southwest. Economic development status, residents’ income, the natural environment of tea growing, the leisure time of followers, and the price level of tea are the essential factors affecting the of the tea industry online attention. In contrast, the other factors we have chosen have a weaker impact on online attention compared to the few factors just mentioned.
Impact of 30 years precipitation regime differences on forest soil physiology and microbial assemblages
Authors: Chakraborty Amrita , Zádrapová Dagmar , Dvořák Jakub , Faltinová Zuzana , Žáček Petr , Cajthaml Tomáš , Korecký Jiří , Roy Amit
Published: June 2023

Anthropogenic disturbances and climate change affect abiotic and biotic environmental drivers in forest ecosystems. Global warming impacts the soil moisture content, thus influencing the diversity, abundance and functioning of soil microfauna. However, limited studies have been conducted to evaluate the impact of long-term variation in precipitation on soil microfauna. A better understanding of soil microfauna functioning under various precipitation regimes can aid in formulating better prediction models for assessing future climate change impacts. The present study uses a multi-omics approach to capture the variability in the total organic carbon (TOC), total nitrogen (TN), pH, metabolites, microbial biomass and function due to the difference in soil water content mediated by long-term precipitation (30 years) and soil texture differences in two Norway spruce seed orchards. Results showed a positive correlation between TOC, TN, extracellular enzyme activities (EEAs) and phospholipid fatty acids (PLFA) content with higher precipitation, whereas microbial diversity showed an opposite trend. A distinct metabolic profile was observed between the two forest soils. Furthermore, variance partitioning canonical correspondence analysis (VPA) revealed a higher contribution of TOC and TN in shaping the microbial communities than soil pH and conductivity in Norway spruce seed orchards. Our study generates field data for modeling the impact of long-term precipitation variance supplemented by soil texture on soil microbial assemblage and function in Norway spruce stands.
BCG vaccination policy, natural boosting and pediatric brain and CNS tumor incidences
Authors: Singh Samer , Diwakar Amita , Singh Rakesh K.
Published: June 2023

Bacille Calmette-Guérin (BCG) vaccination supposedly imparts and augments “trained immunity” that cross-protects against multiple unrelated pathogens and enhances general immune surveillance. Gradual reductions in tuberculosis burden over the last 3–5 decades have resulted in the withdrawal of BCG vaccination mandates from developed industrialized countries while reducing to a single neonatal shot in the rest. Concurrently, a steady increase in early childhood Brain and CNS (BCNS) tumors has occurred. Though immunological causes of pediatric BCNS cancer are suspected, the identification of a causal protective variable with intervention potential has remained elusive. An examination of the countries with contrasting vaccination policies indicates significantly lower BCNS cancer incidence in 0–4-year-olds (per hundredthousand) of countries following neonatal BCG inoculations (n=146) vs. non-BCG countries (n=33) [Mean: 1.26 vs. 2.64; Median: 0.985 vs. 2.8; IQR: 0.31–2.0 vs. 2.4–3.2; P=<0.0001 (two-tailed)]. Remarkably, natural Mycobacterium spp. reexposure likelihood is negatively correlated with BCNS cancer incidence in 0-4-year-olds of all affected countries [r(154): −0.6085, P=<0.0001]. Seemingly, neonatal BCG vaccination and natural “boosting” are associated with a 15–20-fold lower BCNS cancer incidence. In this opinion article, we attempt to synthesize existing evidence implying the immunological basis of early childhood BCNS cancer incidence and briefly indicate possible causes that could have precluded objective analysis of the existing data in the past. We draw the attention of the stakeholders to consider the comprehensive evaluation of immune training as a potential protective variable through well-designed controlled clinical trials or registry-based studies as feasible for its potential applications in reducing childhood BCNS cancer incidence.
Immune profiling in multiple sclerosis: a single-center study of 65 cytokines, chemokines, and related molecules in cerebrospinal fluid and serum
Authors: Berek Klaus , Bauer Angelika , Rudzki Dagmar , Auer Michael , Barket Robert , Zinganell Anne , Lerch Magdalena , Hofer Livia , Grams Astrid , Poskaite Paulina , Wurth Sebastian , Berger Thomas , Di Pauli Franziska , Deisenhammer Florian , Hegen Harald , Reindl Markus
Published: June 2023

Introduction

The understanding of the pathophysiology of multiple sclerosis (MS) has evolved alongside the characterization of cytokines and chemokines in cerebrospinal fluid (CSF) and serum. However, the complex interplay of pro- and anti-inflammatory cytokines and chemokines in different body fluids in people with MS (pwMS) and their association with disease progression is still not well understood and needs further investigation. Therefore, the aim of this study was to profile a total of 65 cytokines, chemokines, and related molecules in paired serum and CSF samples of pwMS at disease onset.

Methods

Multiplex bead-based assays were performed and baseline routine laboratory diagnostics, magnetic resonance imaging (MRI), and clinical characteristics were assessed. Of 44 participants included, 40 had a relapsing–remitting disease course and four a primary progressive MS.

Results

There were 29 cytokines and chemokines that were significantly higher in CSF and 15 in serum. Statistically significant associations with moderate effect sizes were found for 34 of 65 analytes with sex, age, CSF, and MRI parameters and disease progression.

Discussion

In conclusion, this study provides data on the distribution of 65 different cytokines, chemokines, and related molecules in CSF and serum in newly diagnosed pwMS.
Infection with hypervirulent Mycobacterium tuberculosis triggers emergency myelopoiesis but not trained immunity
Authors: Maceiras Ana Raquel , Silvério Diogo , Gonçalves Rute , Cardoso Marcos S. , Saraiva Margarida
Published: June 2023

Introduction

During infection, bone marrow (BM) hematopoiesis is reprogrammed toward myeloid cell production, a mechanism named emergency myelopoiesis. In addition to replenishing myeloid cells, emergency myelopoiesis has been linked to trained immunity, a process that allows enhanced innate immune responses to secondary challenges. Although hematopoietic alterations during tuberculosis (TB) have been described and Mycobacterium tuberculosis may colonize the BM, studies using the mouse model of infection and the laboratory reference strain M. tuberculosis H37Rv have demonstrated limited emergency myelopoiesis and trained immunity.

Methods

To further address this issue, we aerosol- infected C57BL/6 mice with high doses of the hypervirulent M. tuberculosis isolate HN878 and monitored alterations to the BM. This experimental model better resembles the human blood immune signature of TB.

Results and discussion

We found increased frequencies of lineage-Sca-1+cKit+ (LSK) cells and the granulocyte/macrophage progenitor (GMP) population. At the mature cell level, we observed an increase of monocytes and neutrophils in the blood and lung, likely reflecting the increased BM myeloid output. Monocytes or monocyte-derived macrophages recovered from the BM of M. tuberculosis HN878-infected mice did not show signs of trained immunity, suggesting an uncoupling of emergency myelopoiesis and trained immunity in the BM. Surprisingly, M. tuberculosis HN878-induced emergency myelopoiesis was not fully dependent on IFNγ, as mice lacking this cytokine and infected under the same conditions as wild-type mice still presented BM alterations. These data expand our understanding of the immune response to M. tuberculosis and raise awareness of pathogen strain-imposed differences to host responses.
Understanding torquetenovirus (TTV) as an immune marker
Authors: Gore Edmund J. , Gard Lilli , Niesters Hubert G. M. , Van Leer Buter Coretta C.
Published: June 2023

Torquetenovirus (TTV), a small, single stranded anellovirus, is currently being explored as a marker of immunocompetence in patients with immunological impairment and inflammatory disorders. TTV has an extremely high prevalence and is regarded as a part of the human virome, the replication of which is controlled by a functioning immune system. The viral load of TTV in plasma of individuals is thought to reflect the degree of immunosuppression. Measuring and quantifying this viral load is especially promising in organ transplantation, as many studies have shown a strong correlation between high TTV loads and increased risk of infection on one side, and low TTV loads and an increased risk of rejection on the other side. As clinical studies are underway, investigating if TTV viral load measurement is superior for gauging antirejection therapy compared to medication-levels, some aspects nevertheless have to be considered. In contrast with medication levels, TTV loads have to be interpreted bearing in mind that viruses have properties including transmission, tropism, genotypes and mutations. This narrative review describes the potential pitfalls of TTV measurement in the follow-up of solid organ transplant recipients and addresses the questions which remain to be answered.
Role of gC1qR as a modulator of endothelial cell permeability and contributor to post-stroke inflammation and edema formation
Authors: Delgardo Mychael , Tang Anthony J. , Tudor Thilan , Pascual-Leone Andrés , Connolly E. Sander
Published: June 2023

Ischemic stroke is a leading cause of death and disability worldwide. A serious risk of acute ischemic stroke (AIS) arises after the stroke event, due to inflammation and edema formation. Inflammation and edema in the brain are mediated by bradykinin, the formation of which is dependent upon a multi-ligand receptor protein called gC1qR. There are currently no preventive treatments for the secondary damage of AIS produced by inflammation and edema. This review aims to summarize recent research regarding the role of gC1qR in bradykinin formation, its role in inflammation and edema following ischemic injury, and potential therapeutic approaches to preventing post-stroke inflammation and edema formation.
Stroke severity mediates the effect of socioeconomic disadvantage on poor outcomes among patients with intracerebral hemorrhage
Authors: Potter Thomas B. H. , Tannous Jonika , Pan Alan P. , Bako Abdulaziz , Johnson Carnayla , Baig Eman , Kelly Hannah , McCane Charles D. , Garg Tanu , Gadhia Rajan , Misra Vivek , Volpi John , Britz Gavin , Chiu David , Vahidy Farhaan S.
Published: June 2023

Background

Socioeconomic deprivation drives poor functional outcomes after intracerebral hemorrhage (ICH). Stroke severity and background cerebral small vessel disease (CSVD) burden have each been linked to socioeconomic status and independently contribute to worse outcomes after ICH, providing distinct, plausible pathways for the effects of deprivation. We investigate whether admission stroke severity or cerebral small vessel disease (CSVD) mediates the effect of socioeconomic deprivation on 90-day functional outcomes.

Methods

Electronic medical record data, including demographics, treatments, comorbidities, and physiological data, were analyzed. CSVD burden was graded from 0 to 4, with severe CSVD categorized as ≥3. High deprivation was assessed for patients in the top 30% of state-level area deprivation index scores. Severe disability or death was defined as a 90-day modified Rankin Scale score of 4–6. Stroke severity (NIH stroke scale (NIHSS)) was classified as: none (0), minor (1–4), moderate (5–15), moderate–severe (16–20), and severe (21+). Univariate and multivariate associations with severe disability or death were determined, with mediation evaluated through structural equation modelling.

Results

A total of 677 patients were included (46.8% female; 43.9% White, 27.0% Black, 20.7% Hispanic, 6.1% Asian, 2.4% Other). In univariable modelling, high deprivation (odds ratio: 1.54; 95% confidence interval: [1.06–2.23]; p = 0.024), severe CSVD (2.14 [1.42–3.21]; p < 0.001), moderate (8.03 [2.76–17.15]; p < 0.001), moderate–severe (32.79 [11.52–93.29]; p < 0.001), and severe stroke (104.19 [37.66–288.12]; p < 0.001) were associated with severe disability or death. In multivariable modelling, severe CSVD (3.42 [1.75–6.69]; p < 0.001) and moderate (5.84 [2.27–15.01], p < 0.001), moderate–severe (27.59 [7.34–103.69], p < 0.001), and severe stroke (36.41 [9.90–133.85]; p < 0.001) independently increased odds of severe disability or death; high deprivation did not. Stroke severity mediated 94.1% of deprivation’s effect on severe disability or death (p = 0.005), while CSVD accounted for 4.9% (p = 0.524).

Conclusion

CSVD contributed to poor functional outcome independent of socioeconomic deprivation, while stroke severity mediated the effects of deprivation. Improving awareness and trust among disadvantaged communities may reduce admission stroke severity and improve outcomes.
Case report: Mitochondrial trifunctional protein deficiency caused by HADHB gene mutation (c.1175C>T) characterized by higher brain dysfunction followed by neuropathy, presented gadolinium enhancement on brain imaging in an adult patient
Authors: Ishikawa Ruoyi , Nakamori Masahiro , Takenaka Megumi , Aoki Shiro , Yamazaki Yu , Hashiguchi Akihiro , Takashima Hiroshi , Maruyama Hirofumi
Published: June 2023

Mitochondrial trifunctional protein (MTP) deficiency is an autosomal recessive disorder caused by impaired metabolism of long-chain fatty acids (LCFAs). Childhood and late-onset MTP deficiency is characterized by myopathy/rhabdomyolysis and peripheral neuropathy; however, the features are unclear. A 44-year-old woman was clinically diagnosed with Charcot-Marie-Tooth disease at 3 years of age due to gait disturbance. Her activity and voluntary speech gradually decreased in her 40s. Cognitive function was evaluated and brain imaging tests were performed. The Mini-Mental State Examination and frontal assessment battery scores were 25/30 and 10/18, respectively, suggesting higher brain dysfunction. Peripheral nerve conduction studies revealed axonal impairments. Brain computed tomography showed significant calcification. Magnetic resonance imaging revealed an increased gadolinium contrast-enhanced signal in the white matter, suggesting demyelination of the central nervous system (CNS) due to LCFAs. The diagnosis of MTP deficiency was confirmed through genetic examination. Administration of L-carnitine and a medium-chain fatty triglyceride diet was initiated, and the progression of higher brain dysfunction was retarded within 1 year. This patient's presentation was suggestive of CNS demyelination. The presence of brain calcification, higher brain dysfunction, or gadolinium enhancement in the white matter in patients with peripheral neuropathy may be suggestive of MTP deficiency.
Correlation analysis between 18F-fluorodeoxyglucose positron emission tomography and cognitive function in first diagnosed Parkinson’s disease patients
Authors: Zhihui Sun , Yinghua Li , Hongguang Zhao , Yuyin Dai , Xiaoxiao Du , Lulu Gao , Yi Li , Kangli Fan , Ying Zhang
Published: June 2023

Objective

Evaluation of the correlation between 18F-fluorodeoxyglucose-positron emission tomography (18F-FDG PET) and cognitive function in first-diagnosed and untreated Parkinson’s disease (PD) patients.

Materials and method

This cross-sectional study included 84 first diagnosed and untreated PD patients. The individuals were diagnosed by movement disorder experts based on the 2015 MDS Parkinson’s disease diagnostic criteria. The patients also underwent 18F-FDG PET scans and clinical feature assessments including the Montreal Cognitive Assessment (MoCA) scale. Glucose metabolism rates were measured in 26 brain regions using region of interest (ROI) and pixel-wise analyses with displayed Z scores. The cognitive function was assessed by professionals using the MoCA scale, which covers five cognitive domains. Spearman’s linear correlation and linear regression models were used to compare the correlations between 18F-FDG metabolism in each brain region and cognitive domain, using SPSS 25.0 software.

Result

The results indicated a positive correlation between executive function and glucose metabolism in the lateral prefrontal cortex of the left hemisphere (p = 0.041). Additionally, a positive correlation between memory function and glucose metabolism in the right precuneus (p = 0.014), right lateral occipital cortex (p = 0.017), left lateral occipital cortex (p = 0.031), left primary visual cortex (p = 0.008), and right medial temporal cortex (p = 0.046). Further regression analysis showed that for every one-point decrease in the memory score, the glucose metabolism in the right precuneus would decrease by 0.3 (B = 0.30, p = 0.005), the glucose metabolism in the left primary visual cortex would decrease by 0.25 (B = 0.25, p = 0.040), the glucose metabolism in the right lateral occipital cortex would decrease by 0.38 (B = 0.38, p = 0.012), and the glucose metabolism in the left lateral occipital cortex would decrease by 0.32 (B = 0.32, p = 0.045).

Conclusion

This study indicated that cognitive impairment in PD patients mainly manifests as changes in executive function, visual-spatial function and memory functions, while glucose metabolism mainly decreases in the frontal and posterior cortex. Further analysis shows that executive function is related to glucose metabolism in the left lateral prefrontal cortex. On the other hand, memory ability involves changes in glucose metabolism in a more extensive brain region. This suggests that cognitive function assessment can indirectly reflect the level of glucose metabolism in the relevant brain regions.
Quantitative susceptibility mapping using multi-channel convolutional neural networks with dipole-adaptive multi-frequency inputs
Authors: Si Wenbin , Guo Yihao , Zhang Qianqian , Zhang Jinwei , Wang Yi , Feng Yanqiu
Published: June 2023

Quantitative susceptibility mapping (QSM) quantifies the distribution of magnetic susceptibility and shows great potential in assessing tissue contents such as iron, myelin, and calcium in numerous brain diseases. The accuracy of QSM reconstruction was challenged by an ill-posed field-to-susceptibility inversion problem, which is related to the impaired information near the zero-frequency response of the dipole kernel. Recently, deep learning methods demonstrated great capability in improving the accuracy and efficiency of QSM reconstruction. However, the construction of neural networks in most deep learning-based QSM methods did not take the intrinsic nature of the dipole kernel into account. In this study, we propose a dipole kernel-adaptive multi-channel convolutional neural network (DIAM-CNN) method for the dipole inversion problem in QSM. DIAM-CNN first divided the original tissue field into high-fidelity and low-fidelity components by thresholding the dipole kernel in the frequency domain, and it then inputs the two components as additional channels into a multichannel 3D Unet. QSM maps from the calculation of susceptibility through multiple orientation sampling (COSMOS) were used as training labels and evaluation reference. DIAM-CNN was compared with two conventional model-based methods [morphology enabled dipole inversion (MEDI) and improved sparse linear equation and least squares (iLSQR) and one deep learning method (QSMnet)]. High-frequency error norm (HFEN), peak signal-to-noise-ratio (PSNR), normalized root mean squared error (NRMSE), and the structural similarity index (SSIM) were reported for quantitative comparisons. Experiments on healthy volunteers demonstrated that the DIAM-CNN results had superior image quality to those of the MEDI, iLSQR, or QSMnet results. Experiments on data with simulated hemorrhagic lesions demonstrated that DIAM-CNN produced fewer shadow artifacts around the bleeding lesion than the compared methods. This study demonstrates that the incorporation of dipole-related knowledge into the network construction has a potential to improve deep learning-based QSM reconstruction.
Behavioral paradigm for the evaluation of stimulation-evoked somatosensory perception thresholds in rats
Authors: Smith Thomas J. , Wu Yupeng , Cheon Claire , Khan Arlin A. , Srinivasan Hari , Capadona Jeffrey R. , Cogan Stuart F. , Pancrazio Joseph J. , Engineer Crystal T. , Hernandez-Reynoso Ana G.
Published: June 2023

Intracortical microstimulation (ICMS) of the somatosensory cortex via penetrating microelectrode arrays (MEAs) can evoke cutaneous and proprioceptive sensations for restoration of perception in individuals with spinal cord injuries. However, ICMS current amplitudes needed to evoke these sensory percepts tend to change over time following implantation. Animal models have been used to investigate the mechanisms by which these changes occur and aid in the development of new engineering strategies to mitigate such changes. Non-human primates are commonly the animal of choice for investigating ICMS, but ethical concerns exist regarding their use. Rodents are a preferred animal model due to their availability, affordability, and ease of handling, but there are limited choices of behavioral tasks for investigating ICMS. In this study, we investigated the application of an innovative behavioral go/no-go paradigm capable of estimating ICMS-evoked sensory perception thresholds in freely moving rats. We divided animals into two groups, one receiving ICMS and a control group receiving auditory tones. Then, we trained the animals to nose-poke – a well-established behavioral task for rats – following either a suprathreshold ICMS current-controlled pulse train or frequency-controlled auditory tone. Animals received a sugar pellet reward when nose-poking correctly. When nose-poking incorrectly, animals received a mild air puff. After animals became proficient in this task, as defined by accuracy, precision, and other performance metrics, they continued to the next phase for perception threshold detection, where we varied the ICMS amplitude using a modified staircase method. Finally, we used non-linear regression to estimate perception thresholds. Results indicated that our behavioral protocol could estimate ICMS perception thresholds based on ~95% accuracy of rat nose-poke responses to the conditioned stimulus. This behavioral paradigm provides a robust methodology for evaluating stimulation-evoked somatosensory percepts in rats comparable to the evaluation of auditory percepts. In future studies, this validated methodology can be used to study the performance of novel MEA device technologies on ICMS-evoked perception threshold stability using freely moving rats or to investigate information processing principles in neural circuits related to sensory perception discrimination.
Independent effect of fat-to-muscle mass ratio at bioimpedance analysis on long-term survival in patients receiving surgery for pancreatic cancer
Authors: Sandini Marta , Paiella Salvatore , Cereda Marco , Angrisani Marco , Capretti Giovanni , Famularo Simone , Giani Alessandro , Roccamatisi Linda , Fontani Andrea , Malleo Giuseppe , Salvia Roberto , Roviello Franco , Zerbi Alessandro , Bassi Claudio , Gianotti Luca
Published: June 2023

Introduction

Malnutrition and alteration of body composition are early features in pancreatic cancer and appear to be predictors of advanced stages and dismal overall survival. Whether specific patient characteristics measured at the preoperative bioimpedance analysis (BIA) could be associated with long-term outcomes following curative resection has not been yet described.

Methods

In a prospective multicenter study, all histologically proven resected pancreatic cancer patients were included in the analysis. BIA was measured for all patients on the day before surgery. Demographics, perioperative data, and postoperative outcomes were prospectively collected. Patients who experienced 90-day mortality were excluded from the analysis. Survival data were obtained through follow-up visits and phone interviews. Bioimpedance variables were analyzed according to the overall survival using the Kaplan–Meier curves and the univariate and multivariate Cox regression model.

Results

Overall, 161 pancreatic cancer patients were included. The median age was 66 (60–74) years, and 27.3% received systemic neoadjuvant treatment. There were 23 (14.3%) patients malnourished in the preoperative evaluation. Median OS was 34.0 (25.7–42.3) months. Several bioimpedance variables were associated with OS at the univariate analysis, namely the phase angle [HR 0.85, 95% CI 0.74–0.98)], standardized phase angle [HR 0.91, 95% CI 0.82–0.99)], and an increased ratio between the fat and lean mass (FM/FFM) [HR 4.27, 95% CI 1.10–16.64)]. At the multivariate analysis, the FM/FFM ratio was a confirmed independent predictor of OS following radical resection, together with a positive lymph nodal status.

Conclusion

Alteration of body composition at the preoperative bioimpedance vector analysis (BIVA) can predict dismal oncologic outcomes following pancreatic resection for cancer.
Clinical trial of a probiotic and herbal supplement for lung health
Authors: Wenger Nancy M. , Qiao Luhua , Nicola Teodora , Nizami Zoha , Martin Isaac , Halloran Brian A. , Tanaka Kosuke , Evans Michael , Xu Xin , Dinan Timothy G. , Kakilla Charles , DunnGalvin Gillian , Ambalavanan Namasivayam , Willis Kent A. , Gaggar Amit , Lal Charitharth Vivek
Published: June 2023

Introduction

Dysbiosis of the gut microbiome may augment lung disease via the gut-lung axis. Proteobacteria may contribute to tissue proteolysis followed by neutrophil recruitment, lung tissue injury, and perpetuation of chronic inflammation. To study the effects of probiotics across the gut-lung axis, we sought to determine if a Lactobacillus probiotic and herbal blend was safe and well-tolerated in healthy volunteers and asthmatic patients.

Methods

We conducted a 1-month randomized, open-label clinical trial in Cork, Ireland with healthy and asthmatic patients who took the blend twice a day. The primary endpoint was safety with exploratory endpoints including quality of life, lung function, gut microbiome ecology, and inflammatory biomarkers.

Results

All subjects tolerated the blend without adverse events. Asthmatic subjects who took the blend showed significant improvements in lung function as measured by forced expiratory volume and serum short chain fatty acid levels from baseline to Week 4. The gut microbiome of asthmatic subjects differed significantly from controls, with the most prominent difference in the relative abundance of the proteobacteria Escherichia coli. Administration of the probiotic maintained overall microbial community architecture with the only significant difference being an increase in absolute abundance of the probiotic strains measured by strain-specific PCR.

Conclusion

This study supports the safety and efficacy potential of a Lactobacillus probiotic plus herbal blend to act on the gut-lung axis. However, due to the lack of a control group, a longer blinded, placebo-controlled study will be warranted to confirm the efficacy improvements observed in this trial.

Clinical trial registration

https://clinicaltrials.gov/, identifier NCT05173168.
A Bayesian optimization tunning integrated multi-stacking classifier framework for the prediction of radiodermatitis from 4D-CT of patients underwent breast cancer radiotherapy
Authors: Wu Kuan , Miu Xiaoyan , Wang Hui , Li Xiadong
Published: June 2023

Purpose

In this study, we aimed to develop a novel Bayesian optimization based multi-stacking deep learning platform for the prediction of radiation-induced dermatitis (grade ≥ two) (RD 2+) before radiotherapy, by using multi-region dose-gradient-related radiomics features extracted from pre-treatment planning four-dimensional computed tomography (4D-CT) images, as well as clinical and dosimetric characteristics of breast cancer patients who underwent radiotherapy.

Materials and methods

The study retrospectively included 214 patients with breast cancer who received radiotherapy after breast surgeries. Six regions of interest (ROIs) were delineated based on three PTV dose -gradient-related and three skin dose-gradient-related parameters (i.e., isodose). A total of 4309 radiomics features extracted from these six ROIs, as well as clinical and dosimetric characteristics, were used to train and validate the prediction model using nine mainstream deep machine learning algorithms and three stacking classifiers (i.e., meta-learners). To achieve the best prediction performance, a Bayesian optimization based multi-parameter tuning technology was adopted for the AdaBoost, random forest (RF), decision tree (DT), gradient boosting (GB) and extra tree (XTree) five machine learning models. The five parameter -tuned learners and the other four learners (i.e., logistic regression (LR), K-nearest neighbors (KNN), linear discriminant analysis (LDA), Bagging) whose parameters cannot be tuned, all as the primary week learners, were fed into the subsequent meta-learners for training and learning the final prediction model.

Results

The final prediction model included 20 radiomics features and eight clinical and dosimetric characteristics. At the primary learner level, on base of Bayesian parameter tuning optimization, the RF, XGBoost, AdaBoost, GBDT, and LGBM models with the best parameter combinations achieved AUC of 0.82, 0.82, 0.77, 0.80, and 0.80 prediction performance in the verification data set, respectively. In the secondary meta-learner lever, compared with LR and MLP meta-learner, the best predictor of symptomatic RD 2+ for stacked classifiers was the GB meta-learner with an area under the curve (AUC) of 0.97 [95% CI: 0.91-1.0] and an AUC of 0.93 [95% CI: 0.87-0.97] in the training and validation datasets, respectively and the 10 top predictive characteristics were identified.

Conclusion

A novel multi-region dose-gradient-based Bayesian optimization tunning integrated multi-stacking classifier framework can achieve a high-accuracy prediction of symptomatic RD 2+ in breast cancer patients than any other single deep machine learning algorithm.
Research progress on deep learning in magnetic resonance imaging–based diagnosis and treatment of prostate cancer: a review on the current status and perspectives
Authors: He Mingze , Cao Yu , Chi Changliang , Yang Xinyi , Ramin Rzayev , Wang Shuowen , Yang Guodong , Mukhtorov Otabek , Zhang Liqun , Kazantsev Anton , Enikeev Mikhail , Hu Kebang
Published: June 2023

Multiparametric magnetic resonance imaging (mpMRI) has emerged as a first-line screening and diagnostic tool for prostate cancer, aiding in treatment selection and noninvasive radiotherapy guidance. However, the manual interpretation of MRI data is challenging and time-consuming, which may impact sensitivity and specificity. With recent technological advances, artificial intelligence (AI) in the form of computer-aided diagnosis (CAD) based on MRI data has been applied to prostate cancer diagnosis and treatment. Among AI techniques, deep learning involving convolutional neural networks contributes to detection, segmentation, scoring, grading, and prognostic evaluation of prostate cancer. CAD systems have automatic operation, rapid processing, and accuracy, incorporating multiple sequences of multiparametric MRI data of the prostate gland into the deep learning model. Thus, they have become a research direction of great interest, especially in smart healthcare. This review highlights the current progress of deep learning technology in MRI-based diagnosis and treatment of prostate cancer. The key elements of deep learning-based MRI image processing in CAD systems and radiotherapy of prostate cancer are briefly described, making it understandable not only for radiologists but also for general physicians without specialized imaging interpretation training. Deep learning technology enables lesion identification, detection, and segmentation, grading and scoring of prostate cancer, and prediction of postoperative recurrence and prognostic outcomes. The diagnostic accuracy of deep learning can be improved by optimizing models and algorithms, expanding medical database resources, and combining multi-omics data and comprehensive analysis of various morphological data. Deep learning has the potential to become the key diagnostic method in prostate cancer diagnosis and treatment in the future.
Myopia among children and adolescents: an epidemiological study in Fuzhou City
Authors: Zhu Mei-hong , Lin Tai-nan , Lin Jing-hua , Wen Qian
Published: June 2023

Objective

To provide a reference for the prevention and control of myopia by analyzing and discussing the findings of an epidemiological survey of the prevalence of myopia among children and adolescents in Fuzhou City from 2019 to 2021.

Methods

Participants for this cross-sectional study were drawn from Gulou District and Minqing County in Fuzhou City using cluster random sampling to account for differences in population density, economic development, and other environmental variables.

Results

Myopia was more prevalent in 2020 than in 2019, but by 2021 it had dropped to about the same level as in 2019. Myopia was more prevalent among girls than boys during the course of the study period, with a three-year prevalence of 44.72% for boys and 52.16% for girls. Mild myopia accounted for 24.14% of all cases, followed by moderate myopia at 19.62%, and severe myopia at 4.58%. Students in urban regions had a prevalence of myopia equivalent to that of students in the suburbs, and this prevalence rose with age.

Conclusion

Myopia was quite prevalent among children and adolescents in Fuzhou City, and was shown to be steadily rising as students progressed through the school system. This suggests that all levels of government, educational institutions, medical facilities, and concerned parents in Fujian Province should focus on the issue of myopia and collaborate to reduce the risk factors for the development of myopia in school-aged participants.
Risk of diabetic ketoacidosis of SGLT2 inhibitors in patients with type 2 diabetes: a systematic review and network meta-analysis of randomized controlled trials
Authors: Yang Shiwen , Liu Ying , Zhang Shengzhao , Wu Fengbo , Liu Dan , Wu Qingfang , Zheng Hanrui , Fan Ping , Su Na
Published: June 2023

Background: Sodium–glucose cotransporter-2 (SGLT2) inhibitors have proven to be effective in improving glycemic control in patients with type 2 diabetes mellitus (T2DM). However, the risk of diabetic ketoacidosis (DKA) in patients remains unclear. The purpose of this study is to conduct this systematic review and network meta-analysis for the risk of DKA of SGLT2 inhibitors in patients with T2DM.

Methods: We searched for randomized controlled trials (RCTs) concerning SGLT2 inhibitors in patients with T2DM in PubMed, EMBASE (Ovid SP), Cochrane Central Register of Controlled Trials (Ovid SP), and ClinicalTrials.gov from inception to January 2022. The primary outcomes were the risk of DKA. We assessed the sparse network with a fixed-effect model and consistency model in a frequentist framework with a graph-theoretical method by the netmeta package in R. We assessed the evidence quality of evidence of outcomes according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE).

Results: In total, 36 studies involving 52,264 patients were included. The network showed that there was no significant difference observed among SGLT2 inhibitors, other active antidiabetic drugs, and placebo in the risk of DKA. There was no significant difference in the DKA risk between different doses of SGLT2 inhibitors. The certainty of the evidence ranged from very low to moderate. The probabilities of rankings and P-score showed that compared to placebo, SGLT2 inhibitors might increase the risk of DKA (P-score = 0.5298). Canagliflozin might have a higher DKA risk than other SGLT2 inhibitors (P-score = 0.7388).

Conclusion: Neither SGLT2 inhibitors nor other active antidiabetic drugs were associated with an increased risk of DKA compared to placebo, and the risk of DKA with SGLT2 inhibitors was not found to be dose-dependent. In addition, the use of canagliflozin was less advisable than other SGLT2 inhibitors according to the rankings and P-score.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier PROSPERO, CRD42021297081.