bluuebunny/crossref_metadata_2025 huggingface dataset:
Factors that influence outcomes and device use for pediatric cochlear implant recipients with unilateral hearing loss
Authors: Park Lisa R. , Gagnon Erika B. , Dillon Margaret T.
Published: May 2023

Introduction

Candidacy criteria for cochlear implantation in the United States has expanded to include children with single-sided deafness (SSD) who are at least 5 years of age. Pediatric cochlear implant (CI) users with SSD experience improved speech recognition with increased daily device use. There are few studies that report the hearing hour percentage (HHP) or the incidence of non-use for pediatric CI recipients with SSD. The aim of this study was to investigate factors that impact outcomes in children with SSD who use CIs. A secondary aim was to identify factors that impact daily device use in this population.

Methods

A clinical database query revealed 97 pediatric CI recipients with SSD who underwent implantation between 2014 and 2022 and had records of datalogs. The clinical test battery included speech recognition assessment for CNC words with the CI-alone and BKB-SIN with the CI plus the normal-hearing ear (combined condition). The target and masker for the BKB-SIN were presented in collocated and spatially separated conditions to evaluate spatial release from masking (SRM). Linear mixed-effects models evaluated the influence of time since activation, duration of deafness, HHP, and age at activation on performance (CNC and SRM). A separate linear mixed-effects model evaluated the main effects of age at testing, time since activation, duration of deafness, and onset of deafness (stable, progressive, or sudden) on HHP.

Results

Longer time since activation, shorter duration of deafness, and higher HHP were significantly correlated with better CNC word scores. Younger age at device activation was not found to be a significant predictor of CNC outcomes. There was a significant relationship between HHP and SRM, with children who had higher HHP experiencing greater SRM. There was a significant negative correlation between time since activation and age at test with HHP. Children with sudden hearing loss had a higher HHP than children with progressive and congenital hearing losses.

Conclusion

The present data presented here do not support a cut-off age or duration of deafness for pediatric cochlear implantation in cases of SSD. Instead, they expand on our understanding of the benefits of CI use in this population by reviewing the factors that influence outcomes in this growing patient population. Higher HHP, or greater percentage of time spent each day using bilateral input, was associated with better outcomes in the CI-alone and in the combined condition. Younger children and those within the first months of use had higher HHP. Clinicians should discuss these factors and how they may influence CI outcomes with potential candidates with SSD and their families. Ongoing work is investigating the long-term outcomes in this patient population, including whether increasing HHP after a period of limited CI use results in improved outcomes.
When proprioceptive feedback enhances visual perception of self-body movement: rehabilitation perspectives
Authors: Schlienger Raphaëlle , De Giovanni Claire , Guerraz Michel , Kavounoudias Anne
Published: May 2023

Introduction

Rehabilitation approaches take advantage of vision’s important role in kinesthesia, using the mirror paradigm as a means to reduce phantom limb pain or to promote recovery from hemiparesis. Notably, it is currently applied to provide a visual reafferentation of the missing limb to relieve amputees’ pain. However, the efficiency of this method is still debated, possibly due to the absence of concomitant coherent proprioceptive feedback. We know that combining congruent visuo-proprioceptive signals at the hand level enhances movement perception in healthy people. However, much less is known about lower limbs, for which actions are far less visually controlled in everyday life than upper limbs. Therefore, the present study aimed to explore, with the mirror paradigm, the benefit of combined visuo-proprioceptive feedback from the lower limbs of healthy participants.

Methods

We compared the movement illusions driven by visual or proprioceptive afferents and tested the extent to which adding proprioceptive input to the visual reflection of the leg improved the resulting movement illusion. To this end, 23 healthy adults were exposed to mirror or proprioceptive stimulation and concomitant visuo-proprioceptive stimulation. In the visual conditions, participants were asked to voluntarily move their left leg in extension and look at its reflection in the mirror. In the proprioceptive conditions, a mechanical vibration was applied to the hamstring muscle of the leg hidden behind the mirror to simulate an extension of the leg, either exclusively or concomitantly, to the visual reflection of the leg in the mirror.

Results

(i) Visual stimulation evoked leg movement illusions but with a lower velocity than the actual movement reflection on the mirror; (ii) proprioceptive stimulation alone provided more salient illusions than the mirror illusion; and (iii) adding a congruent proprioceptive stimulation improved the saliency, amplitude, and velocity of the illusion.

Conclusion

The present findings confirm that visuo-proprioceptive integration occurs efficiently when the mirror paradigm is coupled with mechanical vibration at the lower limbs, thus providing promising new perspectives for rehabilitation.
AI-driven and automated MRI sequence optimization in scanner-independent MRI sequences formulated by a domain-specific language
Authors: Hoinkiss Daniel Christopher , Huber Jörn , Plump Christina , Lüth Christoph , Drechsler Rolf , Günther Matthias
Published: May 2023

Introduction

The complexity of Magnetic Resonance Imaging (MRI) sequences requires expert knowledge about the underlying contrast mechanisms to select from the wide range of available applications and protocols. Automation of this process using machine learning (ML) can support the radiologists and MR technicians by complementing their experience and finding the optimal MRI sequence and protocol for certain applications.

Methods

We define domain-specific languages (DSL) both for describing MRI sequences and for formulating clinical demands for sequence optimization. By using various abstraction levels, we allow different key users exact definitions of MRI sequences and make them more accessible to ML. We use a vendor-independent MRI framework (gammaSTAR) to build sequences that are formulated by the DSL and export them using the generic file format introduced by the Pulseq framework, making it possible to simulate phantom data using the open-source MR simulation framework JEMRIS to build a training database that relates input MRI sequences to output sets of metrics. Utilizing ML techniques, we learn this correspondence to allow efficient optimization of MRI sequences meeting the clinical demands formulated as a starting point.

Results

ML methods are capable of capturing the relation of input and simulated output parameters. Evolutionary algorithms show promising results in finding optimal MRI sequences with regards to the training data. Simulated and acquired MRI data show high correspondence to the initial set of requirements.

Discussion

This work has the potential to offer optimal solutions for different clinical scenarios, potentially reducing exam times by preventing suboptimal MRI protocol settings. Future work needs to cover additional DSL layers of higher flexibility as well as an optimization of the underlying MRI simulation process together with an extension of the optimization method.
Decreased gray matter volume in the right middle temporal gyrus associated with cognitive dysfunction in preeclampsia superimposed on chronic hypertension
Authors: Sui Chaofan , Wen Hongwei , Han Jingchao , Chen Tao , Gao Yian , Wang Yuanyuan , Yang Linfeng , Guo Lingfei
Published: May 2023

Introduction

The effects of preeclampsia superimposed on chronic hypertension (CHTN-PE) on the structure and function of the human brain are mostly unknown. The purpose of this study was to examine altered gray matter volume (GMV) and its correlation with cognitive function in pregnant healthy women, healthy non-pregnant individuals, and CHTN-PE patients.

Methods

Twenty-five CHTN-PE patients, thirty-five pregnant healthy controls (PHC) and thirty-five non-pregnant healthy controls (NPHC) were included in this study and underwent cognitive assessment testing. A voxel-based morphometry (VBM) approach was applied to investigate variations in brain GMV among the three groups. Pearson’s correlations between mean GMV and the Stroop color-word test (SCWT) scores were calculated.

Results

Compared with the NPHC group, the PHC and CHTN-PE groups showed significantly decreased GMV in a cluster of the right middle temporal gyrus (MTG), and the GMV decrease was more significant in the CHTN-PE group. There were significant differences in the Montreal Cognitive Assessment (MoCA) and Stroop word scores among the three groups. Notably, the mean GMV values in the right MTG cluster were not only significantly negatively correlated with Stroop word and Stroop color scores but also significantly distinguished CHTN-PE patients from the NPHC and PHC groups in receiver operating characteristic curve analysis.

Discussion

Pregnancy may cause a decrease in local GMV in the right MTG, and the GMV decrease is more significant in CHTN-PE patients. The right MTG affects multiple cognitive functions, and combined with the SCWT scores, it may explain the decline in speech motor function and cognitive flexibility in CHTN-PE patients.
Test and re-test reliability of optimal stimulation targets and parameters for personalized neuromodulation
Authors: Fang Feng , Cammon Jared , Li Rihui , Zhang Yingchun
Published: May 2023

Protocols have been proposed to optimize neuromodulation targets and parameters to increase treatment efficacies for different neuropsychiatric diseases. However, no study has investigated the temporal effects of optimal neuromodulation targets and parameters simultaneously via exploring the test–retest reliability of the optimal neuromodulation protocols. In this study, we employed a publicly available structural and resting-state functional magnetic resonance imaging (fMRI) dataset to investigate the temporal effects of the optimal neuromodulation targets and parameters inferred from our customized neuromodulation protocol and examine the test–retest reliability over scanning time. 57 healthy young subjects were included in this study. Each subject underwent a repeated structural and resting state fMRI scan in two visits with an interval of 6 weeks between two scanning visits. Brain controllability analysis was performed to determine the optimal neuromodulation targets and optimal control analysis was further applied to calculate the optimal neuromodulation parameters for specific brain states transition. Intra-class correlation (ICC) measure was utilized to examine the test–retest reliability. Our results demonstrated that the optimal neuromodulation targets and parameters had excellent test–retest reliability (both ICCs > 0.80). The test–retest reliability of model fitting accuracies between the actual final state and the simulated final state also showed a good test–retest reliability (ICC > 0.65). Our results indicated the validity of our customized neuromodulation protocol to reliably identify the optimal neuromodulation targets and parameters between visits, which may be reliably extended to optimize the neuromodulation protocols to efficiently treat different neuropsychiatric disorders.
Intranasally delivered mesenchymal stromal cells decrease glial inflammation early in prion disease
Authors: Hay Arielle J. D. , Latham Amanda S. , Mumford Genova , Hines Amelia D. , Risen Sydney , Gordon Elizabeth , Siebenaler Connor , Gilberto Vincenzo S. , Zabel Mark D. , Moreno Julie A.
Published: May 2023

Mesenchymal stromal cells (MSCs) are an intriguing avenue for the treatment of neurological disorders due to their ability to migrate to sites of neuroinflammation and respond to paracrine signaling in those sites by secreting cytokines, growth factors, and other neuromodulators. We potentiated this ability by stimulating MSCs with inflammatory molecules, improving their migratory and secretory properties. We investigated the use of intranasally delivered adipose-derived MSCs (AdMSCs) in combating prion disease in a mouse model. Prion disease is a rare, lethal neurodegenerative disease that results from the misfolding and aggregation of the prion protein. Early signs of this disease include neuroinflammation, activation of microglia, and development of reactive astrocytes. Later stages of disease include development of vacuoles, neuronal loss, abundant aggregated prions, and astrogliosis. We demonstrate the ability of AdMSCs to upregulate anti-inflammatory genes and growth factors when stimulated with tumor necrosis factor alpha (TNFα) or prion-infected brain homogenates. We stimulated AdMSCs with TNFα and performed biweekly intranasal deliveries of AdMSCs on mice that had been intracranially inoculated with mouse-adapted prions. At early stages in disease, animals treated with AdMSCs showed decreased vacuolization throughout the brain. Expression of genes associated with Nuclear Factor-kappa B (NF-κB) and Nod-Like Receptor family pyrin domain containing 3 (NLRP3) inflammasome signaling were decreased in the hippocampus. AdMSC treatment promoted a quiescent state in hippocampal microglia by inducing changes in both number and morphology. Animals that received AdMSCs showed a decrease in both overall and reactive astrocyte number, and morphological changes indicative of homeostatic astrocytes. Although this treatment did not prolong survival or rescue neurons, it demonstrates the benefits of MSCs in combatting neuroinflammation and astrogliosis.
Molecular analysis and prenatal diagnosis of seven Chinese families with genetic epilepsy
Authors: Mao Bin , Lin Na , Guo Danhua , He Deqin , Xue Huili , Chen Lingji , He Qianqian , Zhang Min , Chen Meihuan , Huang Hailong , Xu Liangpu
Published: May 2023

Introduction

Genetic epilepsy is a large group of clinically and genetically heterogeneous neurological disorders characterized by recurrent seizures, which have a clear association with genetic defects. In this study, we have recruited seven families from China with neurodevelopmental abnormalities in which epilepsy was a predominant manifestation, aiming to elucidate the underlying causes and make a precise diagnosis for the cases.

Methods

Whole-exome sequencing (WES) combined with Sanger sequencing was used to identify the causative variants associated with the diseases in addition to essential imaging and biomedical examination.

Results

A gross intragenic deletion detected in MFSD8 was investigated via gap-polymerase chain reaction (PCR), real-time quantitative PCR (qPCR), and mRNA sequence analysis. We identified 11 variants in seven genes (ALDH7A1, CDKL5, PCDH19, QARS1, POLG, GRIN2A, and MFSD8) responsible for genetic epilepsy in the seven families, respectively. A total of six variants (c.1408T>G in ALDH7A1, c.1994_1997del in CDKL5, c.794G>A in QARS1, c.2453C>T in GRIN2A, and c.217dup and c.863+995_998+1480del in MFSD8) have not yet been reported to be associated with diseases and were all evaluated to be pathogenic or likely pathogenic according to the American College of Medical Genetics and Genomics (ACMG) guidelines.

Methods

Based on the molecular findings, we have associated the intragenic deletion in MFSD8 with the mutagenesis mechanism of Alu-mediated genomic rearrangements for the first time and provided genetic counseling, medical suggestions, and prenatal diagnosis for the families. In conclusion, molecular diagnosis is crucial to obtain improved medical outcomes and recurrence risk evaluation for genetic epilepsy.
Recent progress of the genetics of amyotrophic lateral sclerosis and challenges of gene therapy
Authors: Wang Hui , Guan LiPing , Deng Min
Published: May 2023

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by the degeneration of motor neurons in the brain and spinal cord. The causes of ALS are not fully understood. About 10% of ALS cases were associated with genetic factors. Since the discovery of the first familial ALS pathogenic gene SOD1 in 1993 and with the technology advancement, now over 40 ALS genes have been found. Recent studies have identified ALS related genes including ANXA11, ARPP21, CAV1, C21ORF2, CCNF, DNAJC7, GLT8D1, KIF5A, NEK1, SPTLC1, TIA1, and WDR7. These genetic discoveries contribute to a better understanding of ALS and show the potential to aid the development of better ALS treatments. Besides, several genes appear to be associated with other neurological disorders, such as CCNF and ANXA11 linked to FTD. With the deepening understanding of the classic ALS genes, rapid progress has been made in gene therapies. In this review, we summarize the latest progress on classical ALS genes and clinical trials for these gene therapies, as well as recent findings on newly discovered ALS genes.
Dominant aminoacyl-tRNA synthetase disorders: lessons learned from in vivo disease models
Authors: Kalotay Elizabeth , Klugmann Matthias , Housley Gary D. , Fröhlich Dominik
Published: May 2023

Aminoacyl-tRNA synthetases (ARSs) play an essential role in protein synthesis, being responsible for ligating tRNA molecules to their corresponding amino acids in a reaction known as ‘tRNA aminoacylation’. Separate ARSs carry out the aminoacylation reaction in the cytosol and in mitochondria, and mutations in almost all ARS genes cause pathophysiology most evident in the nervous system. Dominant mutations in multiple cytosolic ARSs have been linked to forms of peripheral neuropathy including Charcot-Marie-Tooth disease, distal hereditary motor neuropathy, and spinal muscular atrophy. This review provides an overview of approaches that have been employed to model each of these diseases in vivo, followed by a discussion of the existing animal models of dominant ARS disorders and key mechanistic insights that they have provided. In summary, ARS disease models have demonstrated that loss of canonical ARS function alone cannot fully account for the observed disease phenotypes, and that pathogenic ARS variants cause developmental defects within the peripheral nervous system, despite a typically later onset of disease in humans. In addition, aberrant interactions between mutant ARSs and other proteins have been shown to contribute to the disease phenotypes. These findings provide a strong foundation for future research into this group of diseases, providing methodological guidance for studies on ARS disorders that currently lack in vivo models, as well as identifying candidate therapeutic targets.
Meta-SpikePropamine: learning to learn with synaptic plasticity in spiking neural networks
Authors: Schmidgall Samuel , Hays Joe
Published: May 2023

We propose that in order to harness our understanding of neuroscience toward machine learning, we must first have powerful tools for training brain-like models of learning. Although substantial progress has been made toward understanding the dynamics of learning in the brain, neuroscience-derived models of learning have yet to demonstrate the same performance capabilities as methods in deep learning such as gradient descent. Inspired by the successes of machine learning using gradient descent, we introduce a bi-level optimization framework that seeks to both solve online learning tasks and improve the ability to learn online using models of plasticity from neuroscience. We demonstrate that models of three-factor learning with synaptic plasticity taken from the neuroscience literature can be trained in Spiking Neural Networks (SNNs) with gradient descent via a framework of learning-to-learn to address challenging online learning problems. This framework opens a new path toward developing neuroscience inspired online learning algorithms.
Focal cross transformer: multi-view brain tumor segmentation model based on cross window and focal self-attention
Authors: Zongren Li , Silamu Wushouer , Shurui Feng , Guanghui Yan
Published: May 2023

Introduction

Recently, the Transformer model and its variants have been a great success in terms of computer vision, and have surpassed the performance of convolutional neural networks (CNN). The key to the success of Transformer vision is the acquisition of short-term and long-term visual dependencies through self-attention mechanisms; this technology can efficiently learn global and remote semantic information interactions. However, there are certain challenges associated with the use of Transformers. The computational cost of the global self-attention mechanism increases quadratically, thus hindering the application of Transformers for high-resolution images.

Methods

In view of this, this paper proposes a multi-view brain tumor segmentation model based on cross windows and focal self-attention which represents a novel mechanism to enlarge the receptive field by parallel cross windows and improve global dependence by using local fine-grained and global coarse-grained interactions. First, the receiving field is increased by parallelizing the self-attention of horizontal and vertical fringes in the cross window, thus achieving strong modeling capability while limiting the computational cost. Second, the focus on self-attention with regards to local fine-grained and global coarse-grained interactions enables the model to capture short-term and long-term visual dependencies in an efficient manner.

Results

Finally, the performance of the model on Brats2021 verification set is as follows: dice Similarity Score of 87.28, 87.35 and 93.28%; Hausdorff Distance (95%) of 4.58 mm, 5.26 mm, 3.78 mm for the enhancing tumor, tumor core and whole tumor, respectively.

Discussion

In summary, the model proposed in this paper has achieved excellent performance while limiting the computational cost.
Golgi_DF: Golgi proteins classification with deep forest
Authors: Bao Wenzheng , Gu Yujian , Chen Baitong , Yu Huiping
Published: May 2023

Introduction

Golgi is one of the components of the inner membrane system in eukaryotic cells. Its main function is to send the proteins involved in the synthesis of endoplasmic reticulum to specific parts of cells or secrete them outside cells. It can be seen that Golgi is an important organelle for eukaryotic cells to synthesize proteins. Golgi disorders can cause various neurodegenerative and genetic diseases, and the accurate classification of Golgi proteins is helpful to develop corresponding therapeutic drugs.

Methods

This paper proposed a novel Golgi proteins classification method, which is Golgi_DF with the deep forest algorithm. Firstly, the classified proteins method can be converted the vector features containing various information. Secondly, the synthetic minority oversampling technique (SMOTE) is utilized to deal with the classified samples. Next, the Light GBM method is utilized to feature reduction. Meanwhile, the features can be utilized in the penultimate dense layer. Therefore, the reconstructed features can be classified with the deep forest algorithm.

Results

In Golgi_DF, this method can be utilized to select the important features and identify Golgi proteins. Experiments show that the well-performance than the other art-of-the state methods. Golgi_DF as a standalone tools, all its source codes publicly available at https://github.com/baowz12345/golgiDF.

Discussion

Golgi_DF employed reconstructed feature to classify the Golgi proteins. Such method may achieve more available features among the UniRep features.
Synaptic properties of mouse tecto-parabigeminal pathways
Authors: Whyland Kyle L. , Masterson Sean P. , Slusarczyk Arkadiusz S. , Bickford Martha E.
Published: May 2023

The superior colliculus (SC) is a critical hub for the generation of visually-evoked orienting and defensive behaviors. Among the SC’s myriad downstream targets is the parabigeminal nucleus (PBG), the mammalian homolog of the nucleus isthmi, which has been implicated in motion processing and the production of defensive behaviors. The inputs to the PBG are thought to arise exclusively from the SC but little is known regarding the precise synaptic relationships linking the SC to the PBG. In the current study, we use optogenetics as well as viral tracing and electron microscopy in mice to better characterize the anatomical and functional properties of the SC-PBG circuit, as well as the morphological and ultrastructural characteristics of neurons residing in the PBG. We characterized GABAergic SC-PBG projections (that do not contain parvalbumin) and glutamatergic SC-PBG projections (which include neurons that contain parvalbumin). These two terminal populations were found to converge on different morphological populations of PBG neurons and elicit opposing postsynaptic effects. Additionally, we identified a population of non-tectal GABAergic terminals in the PBG that partially arise from neurons in the surrounding tegmentum, as well as several organizing principles that divide the nucleus into anatomically distinct regions and preserve a coarse retinotopy inherited from its SC-derived inputs. These studies provide an essential first step toward understanding how PBG circuits contribute to the initiation of behavior in response to visual signals.
Nutritional status of a group of polish children with FASD: A retrospective study
Authors: Domin Agnieszka , Mazur Artur
Published: May 2023

Introduction

Fetal alcohol spectrum disorders (FASDs) are a leading preventable cause of developmental and psychosocial disorders. Prenatal alcohol exposure can be a cause of growth impairment and metabolic problems. In this study, we analyzed data on the growth, weight, and nutritional status of children with FASD.

Methods

Patients were recruited from the Department of Pediatrics, Pediatric Endocrinology and Diabetology, and the Outpatient Endocrinology Clinic in Rzeszów, Poland. Each person referred for evaluation had a diagnosis of FASD based on the recommendations of Polish experts. The population consisted of 59 subjects with measurements of weight and height, and the IGF-1 level test was performed.

Results

Children with FAS had consistently lower height and weight measurements than children with ND-PAE. In the FAS group, children (<3 percentile) accounted for 42.31%, and in the ND-PAE group – 18.18%. The analysis of the whole group showed the highest prevalence of low body weight (below the third percentile) among subjects with FAS – 53.85%. The prevalence of low body weight and short stature (both parameters <3rd centile) was found to be 27.11% in the whole group. Lower mean BMI values were related to the FAS group (21.71 kg/m2) compared to the ND-PAE group (39.62 kg/m2). In the study group, BMI below the fifth percentile was found in 28.81% of the children, normal weight (5th-85th percentile) in 67.80%.

Discussion

During the care of children with FASD, a continuous evaluation of nutritional status, height, and weight is necessary. This group of patients is often affected by low birth weight, short stature and weight deficiency, which require differential diagnosis and appropriate dietary and therapeutic management.
Prevalence and mortality risk of low skeletal muscle mass in critically ill patients: an updated systematic review and meta-analysis
Authors: Yang Hui , Wan Xi-Xi , Ma Hui , Li Zhen , Weng Li , Xia Ying , Zhang Xiao-Ming
Published: May 2023

Background

Patients with critical illness often develop low skeletal muscle mass (LSMM) for multiple reasons. Numerous studies have explored the association between LSMM and mortality. The prevalence of LSMM and its association with mortality are unclear. This systematic review and meta-analysis was performed to examine the prevalence and mortality risk of LSMM among critically ill patients.

Methods

Three internet databases (Embase, PubMed, and Web of Science) were searched by two independent investigators to identify relevant studies. A random-effects model was used to pool the prevalence of LSMM and its association with mortality. The GRADE assessment tool was used to assess the overall quality of evidence.

Results

In total, 1,582 records were initially identified in our search, and 38 studies involving 6,891 patients were included in the final quantitative analysis. The pooled prevalence of LSMM was 51.0% [95% confidence interval (CI), 44.5–57.5%]. The subgroup analysis showed that the prevalence of LSMM in patients with and without mechanical ventilation was 53.4% (95% CI, 43.2–63.6%) and 48.9% (95% CI, 39.7–58.1%), respectively (P-value for difference = 0.44). The pooled results showed that critically ill patients with LSMM had a higher risk of mortality than those without LSMM, with a pooled odds ratio of 2.35 (95% CI, 1.91–2.89). The subgroup analysis based on the muscle mass assessment tool showed that critically ill patients with LSMM had a higher risk of mortality than those with normal skeletal muscle mass regardless of the different assessment tools used. In addition, the association between LSMM and mortality was statistically significant, independent of the different types of mortality.

Conclusion

Our study revealed that critically ill patients had a high prevalence of LSMM and that critically ill patients with LSMM had a higher risk of mortality than those without LSMM. However, large-scale and high-quality prospective cohort studies, especially those based on muscle ultrasound, are required to validate these findings.

Systematic review registration

http://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022379200.
Case report: An asymptomatic mother with an inborn error of cobalamin metabolism (cblC) detected through high homocysteine levels during prenatal diagnosis
Authors: Liu Yu-Peng , He Ru-Xuan , Chen Zhe-Hui , Kang Lu-Lu , Song Jin-Qing , Liu Yi , Shi Chun-Yan , Chen Jun-Ya , Dong Hui , Zhang Yao , Li Meng-Qiu , Jin Ying , Qin Jiong , Yang Yan-Ling
Published: May 2023

Background

The most common disorder of the intracellular cobalamin metabolism pathway is the combined methylmalonic acidemia and homocysteinemia, cblC type (cblC). There is a variation in its clinical spectrum ranging from severe neonatal-onset forms that are highly fatal to later-onset forms which are milder. In this study, the first case of an asymptomatic Chinese woman with a defect in congenital cobalamin (cblC type) metabolism at prenatal diagnosis due to elevated homocysteine level is identified.

Case presentation

The proband, a male child born to a 29-year-old G1P0 mother, admitted to local hospital with feeding disorder, intellectual disability, seizures, microcephaly, as well as heterophthalmos. The level of the urine methylmalonic was elevated. Equally found were increased blood propionylcarnitine (C3) and propionylcarnitine/free carnitine ratio (C3/C0) and decreased methionine levels. The plasma total homocysteine level was elevated at 101.04 μmol/L (normal < 15 μmol/L). The clinical diagnosis of combined methylmalonic acidemia and homocysteinemia was supported. Four years later, the mother of the boy married again and came to us for prenatal diagnosis exactly 15 weeks after her last menstrual period. Subsequently, there is an increase in the amniotic fluid methylmalonate. The level of the amniotic fluid total homocysteine was marginally high. A considerably elevated amniotic fluid C3 was equally observed. In addition, there is a respective significant increase in the plasma and urine total homocysteine at 31.96 and 39.35 μmol/L. After the sequencing of MMACHC genes, it is found that the boy, a proband carried a homozygous mutation of the MMACHC at c.658_660delAAG. While the boy's mother, she carries two mutations in MMACHC: c.658_660delAAG and c.617G>A. The fetus is a carrier of the MMACHC gene. Following the administration of routine treatment, the mother remained symptom-free in the course of pregnancy, and she gave birth to a healthy boy.

Conclusion

Variable and nonspecific symptoms characterized the cblC type of methylmalonic acidemia combined with homocysteinemia. Both biochemical assays and mutation analysis are recommended as crucial complementary techniques.
Phytochemical screening of Prunus avium for its antioxidative and anti-mutagenic potential against DMBA-induced hepatocarcinogenesis
Authors: Saeed Raakia Anam , Khan Muhammad Issa , Butt Masood Sadiq , Faisal Muhammad Naeem
Published: May 2023

Scope

Prunus avium fruit is the richer source of phenolics known to exert anticancer and anti-invasive activities. The study aimed at elucidating antiproliferative and chemo-preventive potential of sweet cherries (P. avium) against the in vivo hepatocarcinoma model.

Methods and results

The quantification of ultrasound-assisted extract (UAE) of P. avium depicted anthocyanins, ferulic acid, gallic acid, quercetin, syringic acid and p- and m-coumaric acids as major phytochemicals. The hepatocarcinoma (HCC) was induced in rats through intraperitoneal administration of DMBA (20 mg/kg B.W) once a week for the period of eight weeks. The intragastric administration of P. avium UAE, as cotreatment (500 mg/Kg B.W) to treatment group, significantly (p < 0.01) attenuated the raised serum alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH) as well as total oxidative stress (TOS) and enhanced total antioxidant capacity TAOC in contrast to diseased rats. Moreover, microscopic examination of hepatic tissues confirmed the pleomorphism, nests of neoplastic hepatocytes and necrosis in HCC-bearing rats as compared to extract-fed rats, where these necrotic changes were suppressed. Besides, qRT-PCR analysis of hepatic tissues demonstrated the higher mRNA expression of CHEK1, CHEK2 and P21/CDKN1α genes, while downexpression of ATM gene in extract fed rats, further denoting the anti-mutagenic potential.

Conclusion

Consequently, the polyphenol-rich sweet cherries UAE exhibited antiproliferative and chemo-preventive potential by reducing tumor biomarkers, serum transaminases and oxidative stress, as well as enhancing antioxidant status. It further upregulated the downstream targets of ATM signaling cascade.
Development and internal validation of a nomogram for predicting survival of nonoperative EGFR-positive locally advanced elderly esophageal cancers
Authors: Wang Jiayang , Peng Jin , Luo Honglei , Song Yaqi
Published: May 2023

Purpose

This study aims to develop and validate a prediction model for non-operative, epidermal growth factor receptor (EGFR)-positive, locally advanced elderly esophageal cancer (LAEEC).

Methods

A total of 80 EGFR-positive LAEEC patients were included in the study. All patients underwent radiotherapy, while 41 cases received icotinib concurrent systemic therapy. A nomogram was established using univariable and multivariable Cox analyses. The model’s efficacy was assessed through area under curve (AUC) values, receiver operating characteristic (ROC) curves at different time points, time-dependent AUC (tAUC), calibration curves, and clinical decision curves. Bootstrap resampling and out-of-bag (OOB) cross-validation methods were employed to verify the model’s robustness. Subgroup survival analysis was also conducted.

Results

Univariable and multivariable Cox analyses revealed that icotinib, stage, and ECOG score were independent prognostic factors for LAEEC patients. The AUCs of model-based prediction scoring (PS) for 1-, 2-, and 3-year overall survival (OS) were 0.852, 0.827, and 0.792, respectively. Calibration curves demonstrated that the predicted mortality was consistent with the actual mortality. The time-dependent AUC of the model exceeded 0.75, and the internal cross-validation calibration curves showed good agreement between predicted and actual mortality. Clinical decision curves indicated that the model had a substantial net clinical benefit within a threshold probability range of 0.2 to 0.8. Model-based risk stratification analysis demonstrated the model’s excellent ability to distinguish survival risk. Further subgroup analyses showed that icotinib significantly improved survival in patients with stage III and ECOG score of 1 (HR 0.122, P<0.001).

Conclusions

Our nomogram model effectively predicts the overall survival of LAEEC patients, and the benefits of icotinib were found in the clinical stage III population with good ECOG scores.
Sociodemographic disparities in targeted therapy in ovarian cancer in a national sample
Authors: Amin Saber A. , Collin Lindsay J. , Kavecansky Juraj , Setoguchi Soko , Satagopan Jaya M. , Bandera Elisa V.
Published: May 2023

Background

The treatment landscape for ovarian cancer has changed in recent years with the introduction of targeted therapies to treat patients with advanced disease. We investigated patient demographic and clinical factors associated with use of targeted therapies as a part of the first-line treatment for ovarian cancer.

Methods

This study included patients diagnosed with stage I–IV ovarian cancer between 2012 and 2019 from the National Cancer Database. Information on demographic and clinical characteristics were collected and described using frequency and percent across receipt of targeted therapy. Logistic regression was used to compute the odds ratios (ORs) and 95% confidence intervals (CI) associating patient demographic and clinical factors with receipt of targeted therapy.

Results

Among 99,286 ovarian cancer patients (mean age 62 years), 4.1% received targeted therapy. The rate of targeted therapy receipt across racial and ethnic groups over the study period was fairly similar; however, non-Hispanic Black women were less likely to receive targeted therapy than their non-Hispanic White counterparts (OR=0.87, 95% CI: 0.76–1.00). Patients who received neoadjuvant chemotherapy were more likely to receive targeted therapy than those who received adjuvant chemotherapy (OR=1.26; 95% CI: 1.15–1.38). Moreover, among patients who received targeted therapy, 28% received neoadjuvant targeted therapy, with non-Hispanic Black women being most likely to receive neoadjuvant targeted therapy (34%) compared with other racial and ethnic groups.

Conclusions

We observed differences in receipt of targeted therapy by factors such as age at diagnosis, stage, and comorbidities present at diagnosis, as well as factors related to healthcare access—including neighborhood education level and health insurance status. Approximately 28% of patients received targeted therapy in the neoadjuvant setting, which could negatively impact treatment outcomes and survival due to the increased risk of complications associated with targeted therapies that may delay or prevent surgery. These results warrant further evaluation in a cohort of patients with more comprehensive treatment information.
A nomogram based on cuproptosis-related genes predicts 7-year relapse-free survival in patients with estrogen receptor-positive early breast cancer
Authors: Fan Yu , Luo Chuanxu , Wang Yu , Wang Zhu , Wang Chengshi , Zhong Xiaorong , Hu Kejia , Wang Yanping , Lu Donghao , Zheng Hong
Published: May 2023

Introduction

Excess copper induces cell death by binding to lipoylated components of the tricarboxylic acid cycle. Although a few studies have examined the relationship between cuproptosis-related genes (CRGs) and breast cancer prognosis, reports on estrogen receptor-positive (ER+) breast cancer are lacking. Herein, we aimed to analyze the relationship between CRGs and outcomes in patients with ER+ early breast cancer (EBC).

Methods

We conducted a case-control study among patients with ER+ EBC presenting poor and favorable invasive disease-free survival (iDFS) at West China Hospital. Logistic regression analysis was performed to establish the association between CRG expression and iDFS. A cohort study was performed using pooled data from three publicly available microarray datasets in the Gene Expression Omnibus database. Subsequently, we constructed a CRG score model and a nomogram to predict relapse-free survival (RFS). Finally, the prediction performance of the two models was verified using training and validation sets.

Results

In this case-control study, high expression of LIAS, LIPT1, and ATP7B and low CDKN2A expression were associated with favorable iDFS. In the cohort study, high expression of FDX1, LIAS, LIPT1, DLD, PDHB, and ATP7B and low CDKN2A expression were associated with favorable RFS. Using LASSO-Cox analysis, a CRG score was developed using the seven identified CRGs. Patients in the low CRG score group had a reduced risk of relapse in both training and validation sets. The nomogram included the CRG score, lymph node status, and age. The area under the receiver operating characteristic (ROC) curve (AUC) of the nomogram was significantly higher than the AUC of the CRG score at 7 years.

Conclusions

The CRG score, combined with other clinical features, could afford a practical long-term outcome predictor in patients with ER+ EBC.
Delta-radiomics based on CT predicts pathologic complete response in ESCC treated with neoadjuvant immunochemotherapy and surgery
Authors: Li Kaiyuan , Li Yuetong , Wang Zhulin , Huang Chunyao , Sun Shaowu , Liu Xu , Fan Wenbo , Zhang Guoqing , Li Xiangnan
Published: May 2023

Background and purpose

Unnecessary surgery can be avoided, and more appropriate treatment plans can be developed for patients if the efficacy of neoadjuvant immunochemotherapy for esophageal cancer (EC) can be predicted before surgery. The purpose of this study was to evaluate the ability of machine learning models based on delta features of immunochemotherapy CT images to predict the efficacy of neoadjuvant immunochemotherapy in patients with esophageal squamous cell carcinoma (ESCC) compared with machine learning models based solely on postimmunochemotherapy CT images.

Materials and methods

A total of 95 patients were enrolled in our study and randomly divided into a training group (n = 66) and test group (n = 29). We extracted preimmunochemotherapy radiomics features from preimmunochemotherapy enhanced CT images in the preimmunochemotherapy group (pregroup) and postimmunochemotherapy radiomics features from postimmunochemotherapy enhanced CT images in the postimmunochemotherapy group (postgroup). We then subtracted the preimmunochemotherapy features from the postimmunochemotherapy features and obtained a series of new radiomics features that were included in the delta group. The reduction and screening of radiomics features were carried out by using the Mann-Whitney U test and LASSO regression. Five pairwise machine learning models were established, the performance of which was evaluated by receiver operating characteristic (ROC) curve and decision curve analyses.

Results

The radiomics signature of the postgroup was composed of 6 radiomics features; that of the delta-group was composed of 8 radiomics features. The area under the ROC curve (AUC) of the machine learning model with the best efficacy was 0.824 (0.706-0.917) in the postgroup and 0.848 (0.765-0.917) in the delta group. The decision curve showed that our machine learning models had good predictive performance. The delta group performed better than the postgroup for each corresponding machine learning model.

Conclusion

We established machine learning models that have good predictive efficacy and can provide certain reference values for clinical treatment decision-making. Our machine learning models based on delta imaging features performed better than those based on single time-stage postimmunochemotherapy imaging features.
Direct attenuation correction for 99mTc-3PRGD2 chest SPECT lung cancer images using deep learning
Authors: Xing Haiqun , Wang Tong , Jin Xiaona , Tian Jian , Ba Jiantao , Jing Hongli , Li Fang
Published: May 2023

Introduction

The attenuation correction technique of single photon emission computed tomography (SPECT) images is essential for early diagnosis, therapeutic evaluation, and pharmacokinetic studies of lung cancer. 99mTc-3PRGD2 is a novel radiotracer for the early diagnosis and evaluation of treatment effects of lung cancer. This study preliminary discusses the deep learning method to directly correct the attenuation of 99mTc-3PRGD2 chest SPECT images.

Methods

Retrospective analysis was performed on 53 patients with pathological diagnosis of lung cancer who received 99mTc-3PRGD2 chest SPECT/CT. All patients’ SPECT/CT images were reconstructed with CT attenuation correction (CT-AC) and without attenuation correction (NAC). The CT-AC image was used as the reference standard (Ground Truth) to train the attenuation correction (DL-AC) SPECT image model using deep learning. A total of 48 of 53 cases were divided randomly into the training set, the remaining 5 were divided into the testing set. Using 3D Unet neural network, the mean square error loss function (MSELoss) of 0.0001 was selected. A testing set is used to evaluate the model quality, using the SPECT image quality evaluation and quantitative analysis of lung lesions tumor-to-background (T/B).

Results

SPECT imaging quality metrics between DL-AC and CT-AC including mean absolute error (MAE), mean-square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity (SSIM), normalized root mean square error (NRMSE), and normalized Mutual Information (NMI) of the testing set are 2.62 ± 0.45, 58.5 ± 14.85, 45.67 ± 2.80, 0.82 ± 0.02, 0.07 ± 0.04, and 1.58 ± 0.06, respectively. These results indicate PSNR > 42, SSIM > 0.8, and NRMSE < 0.11. Lung lesions T/B (maximum) of CT-AC and DL-AC groups are 4.36 ± 3.52 and 4.33 ± 3.09, respectively (p = 0.81). There are no significant differences between two attenuation correction methods.

Conclusion

Our preliminary research results indicate that using the DL-AC method to directly correct 99mTc-3PRGD2 chest SPECT images is highly accurate and feasible for SPECT without configuration with CT or treatment effect evaluation using multiple SPECT/CT scans.
The genomic landscape of sensitivity to arsenic trioxide uncovered by genome-wide CRISPR-Cas9 screening
Authors: Chen Jun-Zhu , Wang Li-Na , Luo Xue-Qun , Tang Yan-Lai
Published: May 2023

Introduction

Arsenic trioxide (ATO) is a promising anticancer drug for hematological malignancy. Given the dramatic efficacy of acute promyelocytic leukemia (APL), ATO has been utilized in other types of cancers, including solid tumors. Unfortunately, the results were not comparable with the effects on APL, and the resistance mechanism has not been clarified yet. This study intends to identify relevant genes and pathways affecting ATO drug sensitivity through genome-wide CRISPR-Cas9 knockdown screening to provide a panoramic view for further study of ATO targets and improved clinical outcomes.

Methods

A genome-wide CRISPR-Cas9 knockdown screening system was constructed for ATO screening. The screening results were processed with MAGeCK, and the results were subjected to pathway enrichment analysis using WebGestalt and KOBAS. We also performed protein-protein interaction (PPI) network analysis using String and Cytoscape, followed by expression profiling and survival curve analysis of critical genes. Virtual screening was used to recognize drugs that may interact with the hub gene.

Results

We applied enrichment analysis and identified vital ATO-related pathways such as metabolism, chemokines and cytokines production and signaling, and immune system responses. In addition, we identified KEAP1 as the top gene relating to ATO resistance. We found that KEAP1 expression was higher in the pan-cancer, including ALL, than in normal tissue. Patients with acute myeloid leukemia (AML) with higher KEAP1 expression had worse overall survival (OS). A virtual screen showed that etoposide and eltrombopag could bind to KEAP1 and potentially interact with ATO.

Discussion

ATO is a multi-target anticancer drug, and the key pathways regulating its sensitivity include oxidative stress, metabolism, chemokines and cytokines, and the immune system. KEAP1 is the most critical gene regulating ATO drug sensitivity, which is related to AML prognosis and may bind to some clinical drugs leading to an interaction with ATO. These integrated results provided new insights into the pharmacological mechanism of ATO and potentiate for further applications in cancer treatments.