bluuebunny/crossref_metadata_2025 huggingface dataset:
Case report: Safety and efficacy of voxelotor in a patient with sickle cell disease and stage IV chronic kidney disease
Authors: Alshurafa Awni , Yassin Mohamed A.
Published: September 2022

Sickle cell disease (SCD) is a heterogeneous group of inherited disorders characterized by the production of sickle hemoglobin which is less soluble than an adult or fetal hemoglobin. Voxelotor is a hemoglobin S polymerization inhibitor that has been approved for sickle cell disease treatment in the adult and adolescent populations. It acts as a hemoglobin modulator by increasing its affinity to oxygen which prevents red blood cells from sickling. Chronic kidney disease is a common but under-reported complication of SCD and it is a leading cause of morbidity and mortality. The data about the safety and efficacy of voxelotor use in chronic kidney disease is limited. Herein we report a 49-year-old man, with sickle cell disease and stage IV chronic kidney disease, who was managed successfully with voxelotor and resulted in decreasing transfusion requirement and vaso-occlusive painful crisis without affecting kidney function.
Is high intensity laser therapy more effective than other physical therapy modalities for treating knee osteoarthritis? A systematic review and network meta-analysis
Authors: Wu Menglai , Luan Lijiang , Pranata Adrian , Witchalls Jeremy , Adams Roger , Bousie Jaquelin , Han Jia
Published: September 2022

Background

The use of physical therapy modalities, especially high intensity laser therapy (HILT), for individuals with knee osteoarthritis (KOA) is still controversial.

Objective

To compare the effects of HILT to other physical therapy modalities on symptoms and function in individuals with KOA.

Methods

Six databases (PubMed, Embase, Cochrane Library, Web of Science, EBSCO, and PEDro) were searched in March 2022. Included studies were randomized controlled trials involving HILT conducted on individuals with KOA. The end-trial weighted mean difference (WMD) and standard deviations (SD) with 95% confidence intervals (CI) were analyzed.

Results

Ten studies with 580 participants were obtained, of which nine were included in the final network meta-analysis. In terms of relieving pain, HILT demonstrated the highest probability of being among the most effective treatments, with surface under the cumulative ranking (SUCRA) = 100%, and compared to a control (placebo laser or exercise or a combination of both) on the visual analog scale (VAS) for pain it demonstrated significant benefits (WMD 1.66, 95% CI 1.48–1.84). For improving self-reported function, as measured by the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total scores, the HILT SUCRA value led with 98.9%. When individuals with KOA were treated by HILT, the improvement in stiffness was statistically significant (WMD 0.78, 95% CI 0.52–1.04) but the amount of improvement was smaller than the minimal clinically important difference (MCID).

Conclusion

The current evidence suggests that HILT may be more effective than other physical therapy modalities for improving pain and function in individuals with KOA. For improving stiffness, however, it may not be clinically effective.

Systematic review registration

[https://www.researchregistry.com], identifier [1148].
High—throughput and automated screening for COVID-19
Authors: Jonguitud-Borrego Nestor , Malcı Koray , Anand Mihir , Baluku Erikan , Webb Calum , Liang Lungang , Barba-Ostria Carlos , Guaman Linda P. , Hui Liu , Rios-Solis Leonardo
Published: September 2022

The COVID-19 pandemic has become a global challenge for the healthcare systems of many countries with 6 million people having lost their lives and 530 million more having tested positive for the virus. Robust testing and a comprehensive track and trace process for positive patients are essential for effective pandemic control, leading to high demand for diagnostic testing. In order to comply with demand and increase testing capacity worldwide, automated workflows have come into prominence as they enable high-throughput screening, faster processing, exclusion of human error, repeatability, reproducibility and diagnostic precision. The gold standard for COVID-19 testing so far has been RT-qPCR, however, different SARS-CoV-2 testing methods have been developed to be combined with high throughput testing to improve diagnosis. Case studies in China, Spain and the United Kingdom have been reviewed and automation has been proven to be promising for mass testing. Free and Open Source scientific and medical Hardware (FOSH) plays a vital role in this matter but there are some challenges to be overcome before automation can be fully implemented. This review discusses the importance of automated high-throughput testing, the different equipment available, the bottlenecks of its implementation and key selected case studies that due to their high effectiveness are already in use in hospitals and research centres.
Spatio-temporal spread and evolution of influenza A (H7N9) viruses
Authors: Shi Zhibin , Wei Lili , Wang Pengfei , Wang Shida , Liu Zaisi , Jiang Yongping , Wang Jingfei
Published: September 2022

The influenza A (H7N9) virus has been seriously concerned for its potential to cause an influenza pandemic. To understand the spread and evolution process of the virus, a spatial and temporal Bayesian evolutionary analysis was conducted on 2,052 H7N9 viruses isolated during 2013 and 2018. It revealed that the H7N9 virus was probably emerged in a border area of Anhui Province in August 2012, approximately 6 months earlier than the first human case reported. Two major epicenters had been developed in the Yangtze River Delta and Peral River Delta regions by the end of 2013, and from where the viruses have also spread to other regions at an average speed of 6.57 km/d. At least 24 genotypes showing have been developed and each of them showed a distinct spatio-temporal distribution pattern. Furthermore, A random forest algorithm-based model has been developed to predict the occurrence risk of H7N9 virus. The model has a high overall forecasting precision (> 97%) and the monthly H7N9 occurrence risk for each county of China was predicted. These findings provide new insights for a comprehensive understanding of the origin, evolution, and occurrence risk of H7N9 virus. Moreover, our study also lays a theoretical basis for conducting risk-based surveillance and prevention of the disease.
Microbes-mediated integrated nutrient management for improved rhizo-modulation, pigeonpea productivity, and soil bio-fertility in a semi-arid agro-ecology
Authors: Gupta Gaurendra , Dhar Shiva , Kumar Adarsh , Choudhary Anil K. , Dass Anchal , Sharma V. K. , Shukla Livleen , Upadhyay P. K. , Das Anup , Jinger Dinesh , Rajpoot Sudhir Kumar , Sannagoudar Manjanagouda S. , Kumar Amit , Bhupenchandra Ingudam , Tyagi Vishal , Joshi Ekta , Kumar Kamlesh , Dwivedi Padmanabh , Rajawat Mahendra Vikram Singh
Published: September 2022

Excessive dependence on chemical fertilizers and ignorance to organic and microbial inputs under intensive cropping systems are the basic components of contemporary agriculture, which evolves several sustainability issues, such as degraded soil health and sub-optimal crop productivity. This scenario urges for integrated nutrient management approaches, such as microbes-mediated integrated plant nutrition for curtailing the high doses as chemical fertilizers. Rationally, experiment has been conducted in pigeonpea at ICAR-IARI, New Delhi, with the aim of identifying the appropriate nutrient management technique involving microbial and organic nutrient sources for improved rhizo-modulation, crop productivity, and soil bio-fertility. The randomized block-designed experiment consisted nine treatmentsviz. Control, Recommended dose of fertilizers (RDF), RDF+ Microbial inoculants (MI), Vermicompost (VC), Farm Yard Manure (FYM), Leaf Compost (LC), VC + MI, FYM + MI, and LC + MI.Rhizobiumspp.,Pseudomonasspp.,Bacillusspp., andFrateuria aurantiawere used as seed-inoculating microbes. The results indicated the significant response of integration following the trend VC + MI > FYM + MI > LC + MI > RDF + MI for various plant shoot-root growth attributes and soil microbial and enzymatic properties. FYM + MI significantly improved the water-stable aggregates (22%), mean weight diameter (1.13 mm), and geometric mean diameter (0.93 mm), soil organic carbon (SOC), SOC stock, and SOC sequestration. The chemical propertiesviz. available N, P, and K were significantly improved with VC + MI. The study summarizes that FYM + MI could result in better soil physico-chemical and biological properties and shoot-root development; however; VC + MI could improve available nutrients in the soil and may enhance the growth of pigeonpea more effectively. The outcomes of the study are postulated as a viable and alternative solution for excessive chemical fertilizer-based nutrient management and would also promote the microbial consortia and organic manures-based agro-industries. This would add to the goal of sustainable agricultural development by producing quality crop produce, maintaining agro-biodiversity and making the soils fertile and healthy that would be a “gift to the society.”
Using deep learning for gene detection and classification in raw nanopore signals
Authors: Nykrynova Marketa , Jakubicek Roman , Barton Vojtech , Bezdicek Matej , Lengerova Martina , Skutkova Helena
Published: September 2022

Recently, nanopore sequencing has come to the fore as library preparation is rapid and simple, sequencing can be done almost anywhere, and longer reads are obtained than with next-generation sequencing. The main bottleneck still lies in data postprocessing which consists of basecalling, genome assembly, and localizing significant sequences, which is time consuming and computationally demanding, thus prolonging delivery of crucial results for clinical practice. Here, we present a neural network-based method capable of detecting and classifying specific genomic regions already in raw nanopore signals—squiggles. Therefore, the basecalling process can be omitted entirely as the raw signals of significant genes, or intergenic regions can be directly analyzed, or if the nucleotide sequences are required, the identified squiggles can be basecalled, preferably to others. The proposed neural network could be included directly in the sequencing run, allowing real-time squiggle processing.
Evaluation of phages and liposomes as combination therapy to counteract Pseudomonas aeruginosa infection in wild-type and CFTR-null models
Authors: Cafora Marco , Poerio Noemi , Forti Francesca , Loberto Nicoletta , Pin Davide , Bassi Rosaria , Aureli Massimo , Briani Federica , Pistocchi Anna , Fraziano Maurizio
Published: September 2022

Multi drug resistant (MDR) bacteria are insensitive to the most common antibiotics currently in use. The spread of antibiotic-resistant bacteria, if not contained, will represent the main cause of death for humanity in 2050. The situation is even more worrying when considering patients with chronic bacterial infections, such as those with Cystic Fibrosis (CF). The development of alternative approaches is essential and novel therapies that combine exogenous and host-mediated antimicrobial action are promising. In this work, we demonstrate that asymmetric phosphatidylserine/phosphatidic acid (PS/PA) liposomes administrated both in prophylactic and therapeutic treatments, induced a reduction in the bacterial burden both in wild-type and cftr-loss-of-function (cftr-LOF) zebrafish embryos infected with Pseudomonas aeruginosa (Pa) PAO1 strain (PAO1). These effects are elicited through the enhancement of phagocytic activity of macrophages. Moreover, the combined use of liposomes and a phage-cocktail (CKΦ), already validated as a PAO1 “eater”, improves the antimicrobial effects of single treatments, and it is effective also against CKΦ-resistant bacteria. We also address the translational potential of the research, by evaluating the safety of CKΦ and PS/PA liposomes administrations in in vitro model of human bronchial epithelial cells, carrying the homozygous F508del-CFTR mutation, and in THP-1 cells differentiated into a macrophage-like phenotype with pharmacologically inhibited CFTR. Our results open the way to the development of novel pharmacological formulations composed of both phages and liposomes to counteract more efficiently the infections caused by Pa or other bacteria, especially in patients with chronic infections such those with CF.
Biochemical characterization of a novel acidophilic β-xylanase from Trichoderma asperellum ND-1 and its synergistic hydrolysis of beechwood xylan
Authors: Zheng Fengzhen , Basit Abdul , Zhuang Huan , Chen Jun , Zhang Jianfen , Chen Weiqing
Published: September 2022

Acidophilic β-xylanases have attracted considerable attention due to their excellent activity under extreme acidic environments and potential industrial utilizations. In this study, a novel β-xylanase gene (Xyl11) of glycoside hydrolase family 11, was cloned from Trichoderma asperellum ND-1 and efficiently expressed in Pichia pastoris (a 2.0-fold increase). Xyl11 displayed a maximum activity of 121.99 U/ml at pH 3.0 and 50°C, and exhibited strict substrate specificity toward beechwood xylan (Km = 9.06 mg/ml, Vmax = 608.65 μmol/min/mg). The Xyl11 retained over 80% activity at pH 2.0–5.0 after pretreatment at 4°C for 1 h. Analysis of the hydrolytic pattern revealed that Xyl11 could rapidly convert xylan to xylobiose via hydrolysis activity as well as transglycosylation. Moreover, the results of site-directed mutagenesis suggested that the Xyl11 residues, Glu127, Glu164, and Glu216, are essential catalytic sites, with Asp138 having an auxiliary function. Additionally, a high degree of synergy (15.02) was observed when Xyl11 was used in association with commercial β-xylosidase. This study provided a novel acidophilic β-xylanase that exhibits excellent characteristics and can, therefore, be considered a suitable candidate for extensive applications, especially in food and animal feed industries.
Screening of interferon-stimulated genes against avian reovirus infection and mechanistic exploration of the antiviral activity of IFIT5
Authors: Wang Sheng , Wan Lijun , Ren Hongyu , Xie Zhixun , Xie Liji , Huang Jiaoling , Deng Xianwen , Xie Zhiqin , Luo Sisi , Li Meng , Zeng Tingting , Zhang Yanfang , Zhang Minxiu
Published: September 2022

Avian reovirus (ARV) infection can lead to severe immunosuppression, complications, and secondary diseases, causing immense economic losses to the poultry industry. In-depth study of the mechanism by which the innate immune system combats ARV infection, especially the antiviral effect mediated by interferon, is needed to prevent and contain ARV infection. In this study, ARV strain S1133 was used to artificially infect 7-day-old specific pathogen–free chickens. The results indicated that ARV rapidly proliferated in the immune organs, including the spleen, bursa of Fabricius, and thymus. The viral load peaked early in the infection and led to varying degrees of pathological damage to tissues and organs. Real-time quantitative PCR revealed that the mRNA levels of interferon and multiple interferon-stimulated genes (ISGs) in the spleen, bursa of Fabricius, and thymus were upregulated to varying degrees in the early stage of infection. Among the ISGs, IFIT5, and Mx were the most upregulated in various tissues and organs, suggesting that they are important ISGs for host resistance to ARV infection. Further investigation of the role of IFIT5 in ARV infection showed that overexpression of the IFIT5 gene inhibited ARV replication, whereas inhibition of the endogenously expressed IFIT5 gene by siRNA promoted ARV replication. IFIT5 may be a positive feedback regulator of the innate immune signaling pathways during ARV infection and may induce IFN-α production by promoting the expression of MAD5 and MAVS to exert its antiviral effect. The results of this study help explain the innate immune regulatory mechanism of ARV infection and reveal the important role of IFIT5 in inhibiting ARV replication, which has important theoretical significance and practical application value for the prevention and control of ARV infection.
Prediction value of the genetic risk of type 2 diabetes on the amnestic mild cognitive impairment conversion to Alzheimer’s disease
Authors: Yang Jiayang , Wang Zirui , Fu Yumeng , Xu Jiayuan , Zhang Yang , Qin Wen , Zhang Quan
Published: September 2022

Amnestic mild cognitive impairment (aMCI) and Type 2 diabetes mellitus (T2DM) are both important risk factors for Alzheimer’s disease (AD). We aimed to investigate whether a T2DM-specific polygenic risk score (PRSsT2DM) can predict the conversion of aMCI to AD and further explore the underlying neurological mechanism. All aMCI patients were from the Alzheimer’s disease Neuroimaging Initiative (ADNI) database and were divided into conversion (aMCI-C, n = 164) and stable (aMCI-S, n = 222) groups. PRSsT2DM was calculated by PRSice-2 software to explore the predictive efficacy of the aMCI conversion to AD. We found that PRSsT2DM could independently predict the aMCI conversion to AD after removing the common variants of these two diseases. PRSsT2DM was significantly negatively correlated with gray matter volume (GMV) of the right superior frontal gyrus in the aMCI-C group. In all aMCI patients, PRSsT2DM was significantly negatively correlated with the cortical volume of the right superior occipital gyrus. The cortical volume of the right superior occipital gyrus could significantly mediate the association between PRSsT2DM and aMCI conversion. Gene-based analysis showed that T2DM-specific genes are highly expressed in cortical neurons and involved in ion and protein binding, neural development and generation, cell junction and projection, and PI3K-Akt and MAPK signaling pathway, which might increase the aMCI conversion by affecting the Tau phosphorylation and amyloid-beta (Aβ) accumulation. Therefore, the PRSsT2DM could be used as a measure to predict the conversion of aMCI to AD.
Targeting autonomic nervous system as a biomarker of well-ageing in the prevention of stroke
Authors: Barthelemy Jean-Claude , Pichot Vincent , Hupin David , Berger Mathieu , Celle Sébastien , Mouhli Lytissia , Bäck Magnus , Lacour Jean-René , Roche Frederic
Published: September 2022

Stroke prediction is a key health issue for preventive medicine. Atrial fibrillation (AF) detection is well established and the importance of obstructive sleep apneas (OSA) has emerged in recent years. Although autonomic nervous system (ANS) appears strongly implicated in stroke occurrence, this factor is more rarely considered. However, the consequences of decreased parasympathetic activity explored in large cohort studies through measurement of ANS activity indicate that an ability to improve its activity level and equilibrium may prevent stroke. In support of these observations, a compensatory neurostimulation has already proved beneficial on endothelium function. The available data on stroke predictions from ANS is based on many long-term stroke cohorts. These data underline the need of repeated ANS evaluation for the general population, in a medical environment, and remotely by emerging telemedicine digital tools. This would help uncovering the reasons behind the ANS imbalance that would need to be medically adjusted to decrease the risk of stroke. This ANS unbalance help to draw attention on clinical or non-clinical evidence, disclosing the vascular risk, as ANS activity integrates the cumulated risk from many factors of which most are modifiable, such as metabolic inadaptation in diabetes and obesity, sleep ventilatory disorders, hypertension, inflammation, and lack of physical activity. Treating these factors may determine ANS recovery through the appropriate management of these conditions. Natural aging also decreases ANS activity. ANS recovery will decrease global circulating inflammation, which will reinforce endothelial function and thus protect the vessels and the associated organs. ANS is the whistle-blower of vascular risk and the actor of vascular health. Such as, ANS should be regularly checked to help draw attention on vascular risk and help follow the improvements in response to our interventions. While today prediction of stroke relies on classical cardiovascular risk factors, adding autonomic biomarkers as HRV parameters may significantly increase the prediction of stroke.
A nomogram incorporating red blood cell indices to predict post-stroke cognitive impairment in the intracerebral hemorrhage population
Authors: Gu Yongzhe , Wang Fang , Gong Li , Fang Min , Liu Xueyuan
Published: September 2022

Background

Post-stroke cognitive impairment (PSCI) plagues 20–80% of stroke survivors worldwide. There is a lack of an easy and effective scoring tool to predict the risk of PSCI in intracerebral hemorrhage (ICH) patients. We aimed to develop a risk prediction model incorporating red blood cell (RBC) indices to identify ICH populations at risk of PSCI.

Methods

Patients diagnosed with ICH at the stroke center were consecutively enrolled in the study as part of the development cohort from July 2017 to December 2018, and of the validation cohort from July 2019 to February 2020. Univariable and multivariable analyses were applied in the development cohort to screen the patients for PSCI risk factors. Then, a nomogram based on RBC indices and other risk factors was developed and validated to evaluate its performance in predicting PSCI occurrence.

Results

A total of 123 patients were enrolled in the development cohort, of which 69 (56.1%) were identified as PSCI, while 38 (63.3%) of 60 patients in the validation cohort were identified as PSCI. According to the multivariate analysis, seven independent risk factors, including three RBC indices (hemoglobin, mean corpuscular volume, RBC distribution width), as well as age, education level, hematoma volume, and dominant-hemisphere hemorrhage were incorporated into the model. The nomogram incorporating RBC indices displayed good discrimination and calibration. The area under the receiver operating characteristic curve was 0.940 for the development cohort and 0.914 for the validation cohort. Decision curve analysis and clinical impact curve showed that the nomogram was clinically useful.

Conclusion

RBC indices are independent and important predictors of PSCI. A nomogram incorporating RBC indices can be used as a reasonable and reliable graphic tool to help clinicians identify high cognition impairment-risk patients and adjust individualized therapy.
Pyroptosis as a candidate therapeutic target for Alzheimer’s disease
Authors: Huang Yuehua , Li Xiaoyu , Luo Guifei , Wang Junli , Li Ranhui , Zhou Chuyi , Wan Teng , Yang Fenglian
Published: September 2022

Pyroptosis is a form of cell death mediated by inflammasomes and gasdermins, and the relevance of pyroptosis to neurodegenerative diseases is currently receiving increasing attention. Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that is closely associated with neuroinflammation. Its main pathological features include β-amyloid (Aβ) deposition, Tau protein hyperphosphorylation and neuronal loss. Aβ, tau-induced microglia pyroptosis and polarization leading to neuroinflammation play an important role in the pathogenesis of AD. Studying the pathogenesis and treatment of AD based on cellular pyroptosis has become a new direction in AD research. In this paper, we review the research progress of pyroptosis and will focus on the pathogenic roles of pyroptosis in AD and the role of targeted inhibition of inflammasome-dependent pyroptosis in AD treatment. These results deepen our understanding of the pathogenesis of AD and provide ideas for the development of new drugs based on the regulation of pyroptosis in AD patients.
An efficient approach for textual data classification using deep learning
Authors: Alqahtani Abdullah , Ullah Khan Habib , Alsubai Shtwai , Sha Mohemmed , Almadhor Ahmad , Iqbal Tayyab , Abbas Sidra
Published: September 2022

Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. Similarly, deep learning offers enormous benefits for text classification since they execute highly accurately with lower-level engineering and processing. This paper employs machine and deep learning techniques to classify textual data. Textual data contains much useless information that must be pre-processed. We clean the data, impute missing values, and eliminate the repeated columns. Next, we employ machine learning algorithms: logistic regression, random forest, K-nearest neighbors (KNN), and deep learning algorithms: long short-term memory (LSTM), artificial neural network (ANN), and gated recurrent unit (GRU) for classification. Results reveal that LSTM achieves 92% accuracy outperforming all other model and baseline studies.
A bibliometric of research trends in acupuncture for spinal cord injury: Quantitative and qualitative analyses
Authors: Huang Yi , He Kelin , Fang Dandan , Ni Fengjia , Qiu Bei , Liang Kang , Ma Ruijie
Published: September 2022

Introduction

Spinal cord injury (SCI) is a severe disease of the central nervous system with a very high disability rate that seriously affects the daily life of patients. Acupuncture is one of the rehabilitation therapies that has shown significant efficacy in treating post-SCI complications such as motor disorders, neuropathic pain, and neurogenic bladder. Current studies have focused on the effectiveness and mechanisms of acupuncture for SCI, but no studies are available to analyze the bibliometrics of publications related to this area.

Methods

Publications related to acupuncture for SCI were retrieved from the Web of Science Core Collection for quantitative and qualitative analyses. The quantitative analysis was unfolded in the following six main areas: annual publications, countries, institutions, authors, sources, and keywords. The qualitative analysis section screened out publications with high annual citation rates and categorized them according to the study content.

Results

There were 213 relevant publications, more than half of which were journal articles. The number of publications showed a fluctuating upward trend. China and the United States were hub countries for related publications and had extensive cooperation with other countries. The most relevant author was Yuanshan Zeng from Sun Yat-sen University, China. The efficacy and mechanism of acupuncture for neuropathic pain after SCI was the first research hotspot in this field, and electroacupuncture was the most widely used technique. In the past 5 years, the mechanism of acupuncture to improve the local microenvironment of SCI and promote nerve regeneration had become a new research trend. At the same time, acupuncture had been gradually applied to various complications after SCI and in veterinary medicine.

Conclusion

The findings suggest that research on acupuncture for SCI is still flourishing, and more research on electroacupuncture for promoting nerve repair and regeneration after SCI will be available in the future.
Predictors of futile recanalization in patients with acute ischemic stroke undergoing mechanical thrombectomy in late time windows
Authors: Ni Heng , Liu Xinglong , Hang Yu , Jia Zhenyu , Cao Yuezhou , Shi Haibin , Liu Sheng , Zhao Linbo
Published: September 2022

Background and purpose

Futile recanalization (FR), defined as functional dependence despite successful reperfusion, is common in patients who experience an acute stroke after thrombectomy. We aimed to determine the predictors of FR in patients who underwent thrombectomy in late time windows (6 h or more after symptom onset).

Methods

This retrospective review included patients who underwent thrombectomy for acute anterior circulation large vessel occlusion from October 2019 to June 2021. Successful reperfusion was defined as a modified Thrombolysis in Cerebral Infarction (mTICI) score of 2b/3. Functional dependence at 90 days was defined as a modified Rankin scale score of 3–6. Multivariate analysis and a receiver operating characteristic (ROC) curve were used to identify the predictors of FR in patients treated in delayed time windows.

Results

Of the 99 patients included, FR was observed in 51 (51.5%). In the multivariate analysis, older age (OR, 1.12; 95% CI, 1.04–1.22; P = 0.005), female sex (OR, 3.79; 95% CI, 1.08–13.40; P = 0.038), a higher National Institutes of Health Stroke Score (NIHSS) score upon admission (OR, 1.11; 95% CI, 1.02–1.22; P = 0.023), and an increased number of passes per procedure (OR, 2.07; 95% CI, 1.11–3.86; P = 0.023) were independently associated with FR after thrombectomy. The ROC curve indicated that the model that combined age, female sex, baseline NIHSS score, and the number of passes per procedure (area under the curve, 0.84; 95% CI, 0.75–0.90, P < 0.001) was able to predict FR accurately.

Conclusions

Older age, female sex, higher NIHSS score upon admission, and an increased number of passes per procedure were independent predictors of FR in patients who experienced acute ischemic strokes after thrombectomy in late time windows.
Alteration of network connectivity in stroke patients with apraxia of speech after tDCS: A randomized controlled study
Authors: Zhao Jiayi , Li Yuanyuan , Zhang Xu , Yuan Ying , Cheng Yinan , Hou Jun , Duan Guoping , Liu Baohu , Wang Jie , Wu Dongyu
Published: September 2022

Objective

This study aimed to examine the changes in the functional connectivity of the cortical speech articulation network after anodal transcranial direct current stimulation (A-tDCS) over the left lip region of the primary motor cortex (M1) in subacute post-stroke patients with apraxia of speech (AoS), and the effect of A-tDCS on AoS.

Methods

A total of 24 patients with post-stroke AoS were randomized into two groups and received A-tDCS over the left lip region of M1 (tDCS group)/ sham tDCS (control group) as well as speech and language therapy two times per day for 5 days. Before and after the treatment, the AoS assessments and electroencephalogram (EEG) were evaluated. The cortical interconnections were measured using the EEG non-linear index of cross approximate entropy (C-ApEn).

Results

The analysis of EEG showed that, after the treatment, the activated connectivity was all in the left hemisphere, and not only regions in the speech articulation network but also in the dorsal lateral prefrontal cortex (DLPFC) in the domain-general network were activated in the tDCS group. In contrast, the connectivity was confined to the right hemisphere and between bilateral DLPFC and bilateral inferior frontal gyrus (IFG) in the control group. In AoS assessments, the tDCS group improved significantly more than the control group in four of the five subtests. The results of multivariate linear regression analyses showed that only the group was significantly associated with the improvement of word repetition (P = 0.002).

Conclusion

A-tDCS over the left lip region of M1 coupled with speech therapy could upregulate the connectivity of both speech-specific and domain-general networks in the left hemisphere. The improved articulation performance in patients with post-stroke AoS might be related to the enhanced connectivity of networks in the left hemisphere induced by tDCS.

Clinical trial registration

ChiCTR-TRC-14005072.
Endovascular thrombectomy in acute ischemic stroke patients with prestroke disability (mRS ≥2): A systematic review and meta-analysis
Authors: Yang Jin-Cai , Bao Qiang-Ji , Guo Yu , Chen Shu-Jun , Zhang Jin-Tao , Zhang Qiang , Zhou Ping , Yang Ming-Fei
Published: September 2022

Objective

The effect of endovascular thrombectomy (EVT) in acute ischemic stroke patients with prestroke disability (modified Rankin Scale score, mRS) ≥2) has not been well-studied. This study aimed to assess the safety and benefit of EVT in patients with prestroke disability.

Methods

According to PRISMA guidelines, literature searching was performed using PubMed, Embase, and Cochrane databases, for a series of acute ischemic stroke patients with prestroke mRS ≥2 treated by EVT. Random-effects meta-analysis was used to pool the rate of return to prestroke mRS and mortality at 3-month follow-up.

Results

In total, 13 observational studies, with 2,625 patients, were analyzed. The rates of return to prestroke mRS in patients with prestroke mRS of 2–4 were 20% (120/588), 27% (218/827), and 31% (34/108), respectively. Patients with prestroke disability treated by EVT had a higher likelihood of return to prestroke mRS (relative risk, RR, 1.86; 95% CI 1.28–2.70) and a lower likelihood of mortality (RR 0.75; 95%CI 0.58–0.97) compared with patients with standard medical treatment. Successful recanalization (Thrombolysis in Cerebral Infarction grade 2b-3) after EVT gave a higher likelihood of return to prestroke mRS (RR 2.04; 95% CI 1.17–3.55) and lower mortality (RR 0.72; 95% CI 0.62–0.84) compared with unsuccessful reperfusion.

Conclusions

Acute ischemic stroke patients with prestroke disability may benefit from EVT. Withholding EVT on the sole ground of prestroke disabilities may not be justified.

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/.
A medical image segmentation method based on multi-dimensional statistical features
Authors: Xu Yang , He Xianyu , Xu Guofeng , Qi Guanqiu , Yu Kun , Yin Li , Yang Pan , Yin Yuehui , Chen Hao
Published: September 2022

Medical image segmentation has important auxiliary significance for clinical diagnosis and treatment. Most of existing medical image segmentation solutions adopt convolutional neural networks (CNNs). Althought these existing solutions can achieve good image segmentation performance, CNNs focus on local information and ignore global image information. Since Transformer can encode the whole image, it has good global modeling ability and is effective for the extraction of global information. Therefore, this paper proposes a hybrid feature extraction network, into which CNNs and Transformer are integrated to utilize their advantages in feature extraction. To enhance low-dimensional texture features, this paper also proposes a multi-dimensional statistical feature extraction module to fully fuse the features extracted by CNNs and Transformer and enhance the segmentation performance of medical images. The experimental results confirm that the proposed method achieves better results in brain tumor segmentation and ventricle segmentation than state-of-the-art solutions.
Brain and brain-heart Granger causality during wakefulness and sleep
Authors: Abdalbari Helmi , Durrani Mohammad , Pancholi Shivam , Patel Nikhil , Nasuto Slawomir J. , Nicolaou Nicoletta
Published: September 2022

In this exploratory study we apply Granger Causality (GC) to investigate the brain-brain and brain-heart interactions during wakefulness and sleep. Our analysis includes electroencephalogram (EEG) and electrocardiogram (ECG) data during all-night polysomnographic recordings from volunteers with apnea, available from the Massachusetts General Hospital’s Computational Clinical Neurophysiology Laboratory and the Clinical Data Animation Laboratory. The data is manually annotated by clinical staff at the MGH in 30 second contiguous intervals (wakefulness and sleep stages 1, 2, 3, and rapid eye movement (REM). We applied GC to 4-s non-overlapping segments of available EEG and ECG across all-night recordings of 50 randomly chosen patients. To identify differences in GC between the different sleep stages, the GC for each sleep stage was subtracted from the GC during wakefulness. Positive (negative) differences indicated that GC was greater (lower) during wakefulness compared to the specific sleep stage. The application of GC to study brain-brain and brain-heart bidirectional connections during wakefulness and sleep confirmed the importance of fronto-posterior connectivity during these two states, but has also revealed differences in ipsilateral and contralateral mechanisms of these connections. It has also confirmed the existence of bidirectional brain-heart connections that are more prominent in the direction from brain to heart. Our exploratory study has shown that GC can be successfully applied to sleep data analysis and captures the varying physiological mechanisms that are related to wakefulness and different sleep stages.
Ensemble learning via supervision augmentation for white matter hyperintensity segmentation
Authors: Guo Xutao , Ye Chenfei , Yang Yanwu , Zhang Li , Liang Li , Lu Shang , Lv Haiyan , Guo Chunjie , Ma Ting
Published: September 2022

Since the ambiguous boundary of the lesion and inter-observer variability, white matter hyperintensity segmentation annotations are inherently noisy and uncertain. On the other hand, the high capacity of deep neural networks (DNN) enables them to overfit labels with noise and uncertainty, which may lead to biased models with weak generalization ability. This challenge has been addressed by leveraging multiple annotations per image. However, multiple annotations are often not available in a real-world scenario. To mitigate the issue, this paper proposes a supervision augmentation method (SA) and combines it with ensemble learning (SA-EN) to improve the generalization ability of the model. SA can obtain diverse supervision information by estimating the uncertainty of annotation in a real-world scenario that per image have only one ambiguous annotation. Then different base learners in EN are trained with diverse supervision information. The experimental results on two white matter hyperintensity segmentation datasets demonstrate that SA-EN gets the optimal accuracy compared with other state-of-the-art ensemble methods. SA-EN is more effective on small datasets, which is more suitable for medical image segmentation with few annotations. A quantitative study is presented to show the effect of ensemble size and the effectiveness of the ensemble model. Furthermore, SA-EN can capture two types of uncertainty, aleatoric uncertainty modeled in SA and epistemic uncertainty modeled in EN.
Regional brain atrophy in patients with chronic ankle instability: A voxel-based morphometry study
Authors: Xie Hui-Min , Xing Zhen-Tong , Chen Zhi-Ye , Zhang Xiao-Tan , Qiu Xiao-Juan , Jia Zi-Shan , Zhang Li-Ning , Yu Xin-Guang
Published: September 2022

The objective of this study was to investigate whether brain volume changes occur in patients with chronic ankle instability (CAI) using voxel-based morphometry and assessing correlations with clinical tests. Structural magnetic resonance imaging data were prospectively acquired in 24 patients with CAI and 34 healthy controls. CAI symptoms and pain intensity were assessed using the Foot and Ankle Ability Measure (FAAM), Cumberland Ankle Instability Tool (CAIT), American Orthopedic Foot and Ankle Society (AOFAS) ankle-hindfoot score, and visual analog scale (VAS). The gray matter volume (GMV) of each voxel was compared between the two groups while controlling for age, sex, weight, and education level. Correlation analysis was performed to identify associations between abnormal GMV regions and the FAAM score, AOFAS score, VAS score, disease duration, and body mass index. Patients with CAI exhibited reduced GMV in the right precentral and postcentral areas, right parahippocampal area, left thalamus, left parahippocampal area, and left postcentral area compared to that of healthy controls. Furthermore, the right parahippocampal (r = 0.642, p = 0.001), left parahippocampal (r = 0.486, p = 0.016), and left postcentral areas (r = 0.521, p = 0.009) were positively correlated with disease duration. The left thalamus was positively correlated with the CAIT score and FAAM activities of daily living score (r = 0.463, p = 0.023 and r = 0.561, p = 0.004, respectively). A significant positive correlation was found between the local GMV of the right and left parahippocampal areas (r = 0.487, p = 0.016 and r = 0.763, p < 0.001, respectively) and the AOFAS score. Neural plasticity may occur in the precentral and postcentral areas, parahippocampal area, and thalamus in patients with CAI. The patterns of structural reorganization in patients with CAI may provide useful information on the neuropathological mechanisms of CAI.
Mast cell stabilizer disodium cromoglycate improves long-term cognitive impairment after general anesthesia exposure in neonatal mice
Authors: Zhang Xiaojun , Wu Wensi , Zheng Zhenzhen , Li Liang , Chen Junjun , Zhong Junying , Zhao Le , Chen Jiawei , Wang Zhi , Meng Fanqing
Published: September 2022

Background

Prolonged exposure to general anesthesia (GA) results in long-lasting cognitive impairment, especially during critical stages of brain development. An exaggerated neuroinflammation induced by anesthesia is generally considered to be a key cause of cognitive impairment.

Materials and methods

Postnatal day 7 (PND 7) mice were exposed to GA by isoflurane inhalation for 6 h or mock anesthesia. Disodium cromoglycate (DSCG) was intraperitoneally injected daily for 2 weeks, beginning from 30 min before anesthesia. The post-anesthesia evaluation included behavioral tests, toluidine blue staining, immunofluorescence and western blot.

Results

Our results demonstrated the long-term cognition were impaired after 6 h GA exposure in neonatal mice. DSCG treatment ameliorated early mast cells (MCs) degranulation and mast cell tryptase (MCT) expression, which helps to attenuate subsequent neuroinflammation, activation of microglia and astrocytes, and damage to oligodendrocytes and synapses to improve cognitive impairment.

Conclusion

Disodium cromoglycate could effectively improve long-term cognitive impairment after GA exposure in neonatal mice.
Pathological mechanisms of connexin26-related hearing loss: Potassium recycling, ATP-calcium signaling, or energy supply?
Authors: Chen Penghui , Wu Wenjin , Zhang Jifang , Chen Junmin , Li Yue , Sun Lianhua , Hou Shule , Yang Jun
Published: September 2022

Hereditary deafness is one of the most common human birth defects. GJB2 gene mutation is the most genetic etiology. Gap junction protein 26 (connexin26, Cx26) encoded by the GJB2 gene, which is responsible for intercellular substance transfer and signal communication, plays a critical role in hearing acquisition and maintenance. The auditory character of different Connexin26 transgenic mice models can be classified into two types: profound congenital deafness and late-onset progressive hearing loss. Recent studies demonstrated that there are pathological changes including endocochlear potential reduction, active cochlear amplification impairment, cochlear developmental disorders, and so on, in connexin26 deficiency mice. Here, this review summarizes three main hypotheses to explain pathological mechanisms of connexin26-related hearing loss: potassium recycling disruption, adenosine-triphosphate-calcium signaling propagation disruption, and energy supply dysfunction. Elucidating pathological mechanisms underlying connexin26-related hearing loss can help develop new protective and therapeutic strategies for this common deafness. It is worthy of further study on the detailed cellular and molecular upstream mechanisms to modify connexin (channel) function.
The otolith vermis: A systems neuroscience theory of the Nodulus and Uvula
Authors: Laurens Jean
Published: September 2022

The Nodulus and Uvula (NU) (lobules X and IX of the cerebellar vermis) form a prominent center of vestibular information processing. Over decades, fundamental and clinical research on the NU has uncovered many aspects of its function. Those include the resolution of a sensory ambiguity inherent to inertial sensors in the inner ear, the otolith organs; the use of gravity signals to sense head rotations; and the differential processing of self-generated and externally imposed head motion. Here, I review these works in the context of a theoretical framework of information processing called the internal model hypothesis. I propose that the NU implements a forward internal model to predict the activation of the otoliths, and outputs sensory predictions errors to correct internal estimates of self-motion or to drive learning. I show that a Kalman filter based on this framework accounts for various functions of the NU, neurophysiological findings, as well as the clinical consequences of NU lesions. This highlights the role of the NU in processing information from the otoliths and supports its denomination as the “otolith” vermis.
Concepts and methods for the dosimetry of radioembolisation of the liver with Y-90-loaded microspheres
Authors: Dieudonné Arnaud , Sanchez-Garcia Manuel , Bando-Delaunay Aurélie , Lebtahi Rachida
Published: September 2022

This article aims at presenting in a didactic way, dosimetry concepts and methods that are relevant for radio-embolization of the liver with 90Y-microspheres. The application of the medical internal radiation dose formalism to radio-embolization is introduced. This formalism enables a simplified dosimetry, where the absorbed dose in a given tissue depends on only its mass and initial activity. This is applied in the single-compartment method, partition model, for the liver, tumour and lung dosimetry, and multi-compartment method, allowing identification of multiple tumours. Voxel-based dosimetry approaches are also discussed. This allows taking into account the non-uniform uptake within a compartment, which translates into a non-uniform dose distribution, represented as a dose–volume histogram. For this purpose, dose–kernel convolution allows propagating the energy deposition around voxel-sources in a computationally efficient manner. Alternatively, local-energy deposition is preferable when the spatial resolution is comparable or larger than the beta-particle path. Statistical tools may be relevant in establishing dose–effect relationships in a given population. These include tools such as the logistic regression or receiver operator characteristic analysis. Examples are given for illustration purpose. Moreover, tumour control probability modelling can be assessed through the linear-quadratic model of Lea and Catcheside and its counterpart, the normal-tissue complication probability model of Lyman, which is suitable to the parallel structure of the liver. The selectivity of microsphere administration allows tissue sparing, which can be considered with the concept of equivalent uniform dose, for which examples are also given. The implication of microscopic deposition of microspheres is also illustrated through a liver toxicity model, even though it is not clinically validated. Finally, we propose a reflection around the concept of therapeutic index (TI), which could help tailor treatment planning by determining the treatment safety through the evaluation of TI based on treatment-specific parameters.