bluuebunny/crossref_metadata_2025 huggingface dataset:
Longitudinal Brain Changes After Stroke and the Association With Cognitive Decline
Authors: Aamodt Eva B. , Lydersen Stian , Alnæs Dag , Schellhorn Till , Saltvedt Ingvild , Beyer Mona K. , Håberg Asta
Published: June 2022

Background

Cognitive impairment is common after stroke. So is cortical- and subcortical atrophy, with studies reporting more atrophy in the ipsilesional hemisphere than the contralesional hemisphere. The current study aimed to investigate the longitudinal associations between (I) lateralization of brain atrophy and stroke hemisphere, and (II) cognitive impairment and brain atrophy after stroke. We expected to find that (I) cortical thickness and hippocampal-, thalamic-, and caudate nucleus volumes declined more in the ipsilesional than the contralesional hemisphere up to 36 months after stroke. Furthermore, we predicted that (II) cognitive decline was associated with greater stroke volumes, and with greater cortical thickness and subcortical structural volume atrophy across the 36 months.

Methods

Stroke survivors from five Norwegian hospitals were included from the multisite-prospective “Norwegian Cognitive Impairment After Stroke” (Nor-COAST) study. Analyses were run with clinical, neuropsychological and structural magnetic resonance imaging (MRI) data from baseline, 18- and 36 months. Cortical thicknesses and subcortical volumes were obtained via FreeSurfer segmentations and stroke lesion volumes were semi-automatically derived using ITK-SNAP. Cognition was measured using MoCA.

Results

Findings from 244 stroke survivors [age = 72.2 (11.3) years, women = 55.7%, stroke severity NIHSS = 4.9 (5.0)] were included at baseline. Of these, 145 (59.4%) had an MRI scan at 18 months and 72 (49.7% of 18 months) at 36 months. Most cortices and subcortices showed a higher ipsi- compared to contralesional atrophy rate, with the effect being more prominent in the right hemisphere. Next, greater degrees of atrophy particularly in the medial temporal lobe after left-sided strokes and larger stroke lesion volumes after right-sided strokes were associated with cognitive decline over time.

Conclusion

Atrophy in the ipsilesional hemisphere was greater than in the contralesional hemisphere over time. This effect was found to be more prominent in the right hemisphere, pointing to a possible higher resilience to stroke of the left hemisphere. Lastly, greater atrophy of the cortex and subcortex, as well as larger stroke volume, were associated with worse cognition over time and should be included in risk assessments of cognitive decline after stroke.
Altered Effective Connectivity of Resting-State Networks by Tai Chi Chuan in Chronic Fatigue Syndrome Patients: A Multivariate Granger Causality Study
Authors: Li Yuanyuan , Wu Kang , Hu Xiaojie , Xu Tianjiao , Li Zongheng , Zhang Yong , Li Kuangshi
Published: June 2022

Numerous evidence has shown that patients with chronic fatigue syndrome (CFS) have changes in resting brain functional connectivity, but there is no study on the brain network effect of Tai Chi Chuan intervention in CFS. To explore the influence of Tai Chi Chuan exercise on the causal relationship between brain functional networks in patients with CFS, 21 patients with CFS and 19 healthy controls were recruited for resting-state functional magnetic resonance imaging (rs-fMRI) scanning and 36-item Short-Form Health Survey (SF-36) scale assessment before and after 1month-long training in Tai Chi Chuan. We extracted the resting brain networks using the independent component analysis (ICA) method, analyzed the changes of FC in these networks, conducted Granger causality analysis (GCA) on it, and analyzed the correlation between the difference causality value and the SF-36 scale. Compared to the healthy control group, the SF-36 scale scores of patients with CFS were lower at baseline. Meanwhile, the causal relationship between sensorimotor network (SMN) and default mode network (DMN) was weakened. The above abnormalities could be improved by Tai Chi Chuan training for 1 month. In addition, the correlation analyses showed that the causal relationship between SMN and DMN was positively correlated with the scores of Role Physical (RP) and Bodily Pain (BP) in CFS patients, and the change of causal relationship between SMN and DMN before and after training was positively correlated with the change of BP score. The findings suggest that Tai Chi Chuan is helpful to improve the quality of life for patients with CFS. The change of Granger causality between SMN and DMN may be a readout parameter of CFS. Tai Chi Chuan may promote the functional plasticity of brain networks in patients with CFS by regulating the information transmission between them.
Neuroplasticity Mechanisms in Frontal Brain Gliomas: A Preliminary Study
Authors: Mitolo Micaela , Zoli Matteo , Testa Claudia , Morandi Luca , Rochat Magali Jane , Zaccagna Fulvio , Martinoni Matteo , Santoro Francesca , Asioli Sofia , Badaloni Filippo , Conti Alfredo , Sturiale Carmelo , Lodi Raffaele , Mazzatenta Diego , Tonon Caterina
Published: June 2022

Background

Pathological brain processes may induce adaptive cortical reorganization, however, the mechanisms underlying neuroplasticity that occurs in the presence of lesions in eloquent areas are not fully explained. The aim of this study was to evaluate functional compensatory cortical activations in patients with frontal brain gliomas during a phonemic fluency task and to explore correlations with cognitive performance, white matter tracts microstructural alterations, and tumor histopathological and molecular characterization.

Methods

Fifteen patients with frontal glioma were preoperatively investigated with an MRI study on a 3T scanner and a subgroup underwent an extensive neuropsychological assessment. The hemispheric laterality index (LI) was calculated through phonemic fluency task functional MRI (fMRI) activations in the frontal, parietal, and temporal lobe parcellations. Diffusion-weighted images were acquired for all patients and for a group of 24 matched healthy volunteers. Arcuate Fasciculus (AF) and Frontal Aslant Tract (FAT) tractography was performed using constrained spherical deconvolution diffusivity modeling and probabilistic fiber tracking. All patients were operated on with a resective aim and underwent adjuvant therapies, depending on the final diagnosis.

Results

All patients during the phonemic fluency task fMRI showed left hemispheric dominance in temporal and parietal regions. Regarding frontal regions (i.e., frontal operculum) we found right hemispheric dominance that increases when considering only those patients with tumors located on the left side. These latter activations positively correlate with verbal and visuo-spatial short-term memory, and executive functions. No correlations were found between the left frontal operculum and cognitive performance. Furthermore, patients with IDH-1 mutation and without TERT mutation, showed higher rightward frontal operculum fMRI activations and better cognitive performance in tests measuring general cognitive abilities, semantic fluency, verbal short-term memory, and executive functions. As for white matter tracts, we found left and right AF and FAT microstructural alterations in patients with, respectively, left-sided and right-side glioma compared to controls.

Conclusions

Compensatory cortical activation of the corresponding region in the non-dominant hemisphere and its association with better cognitive performance and more favorable histopathological and molecular tumor characteristics shed light on the neuroplasticity mechanisms that occur in the presence of a tumor, helping to predict the rate of post-operative deficit, with the final goal of improving patients'quality of life.
Ventral Attention Network Correlates With High Traits of Emotion Dysregulation in Community Women — A Resting-State EEG Study
Authors: Fusina Francesca , Marino Marco , Spironelli Chiara , Angrilli Alessandro
Published: June 2022

In recent years, many studies have focused on resting-state brain activity, and especially on functional connectivity (FC), an approach that typically describes the statistical interdependence of activity in distant brain regions through specific networks. Our aim was to study the neurophysiological correlates of emotion dysregulation. Therefore, we expected that both the Default Mode Network (DMN), and the Ventral Attention Network (VAN) would have been involved. Indeed, the latter plays a role in the automatic orienting of attention towards biologically salient stimuli and includes key regions for emotion control and modulation. Starting from a community sample of 422 female students, we selected 25 women with high traits of emotion dysregulation (HD group) and 25 with low traits (LD group). They underwent a 64-channel EEG recording during a five-minute resting state with eyes open. Seed-based FC was computed on the EEG Alpha band (8–13 Hz) as a control band, and on EEG Gamma power (30–50 Hz) as the relevant measure. The power within each network and inter-network connectivity (Inter-NC) was also calculated. Analysis of the EEG Gamma band revealed, in the HD group, higher levels of Inter-NC between the VAN and all other resting-state networks as compared with the LD group, while no differences emerged in the Alpha band. Concerning correlations, Alpha power in the VAN was negatively correlated in the HD group with affective lability (ALS-18 questionnaire), both for total score (ρ = –0.52, pFDR < 0.01) and the Depression/Elation subscale) ρ = −0.45, pFDR < 0.05). Consistent with this, in the Gamma band, a positive correlation was found between VAN spectral power and the Depression/Elation subscale of ALS-18, again in the HD group only (ρ = 0.47, pFDR < 0.05). In conclusion, both resting state FC and network power in the VAN were found to be related to high emotion dysregulation, even in our non-clinical sample with high traits. Emotion dysregulation was characterized, in the EEG gamma band, by a VAN strongly connected to all other networks, a result that points, in women prone to emotion dysregulation, to a strong automatic orienting of attention towards their internal state, bodily sensations, and emotionally intense related thoughts.
APOE ε4 Allele Distribution and Association With Scores of Subjective Cognitive Decline Questionnaire 9 in a Large Chinese Memory Clinic Cohort
Authors: Hao Lixiao , Jia Jianguo , Xing Yue , Han Ying
Published: June 2022

Background

Previous reports on APOE ε4 allele distribution in different populations have been inconclusive. The Subjective Cognitive Decline-Questionnaire 9 (SCD-Q9) was developed to identify those at risk of objective cognitive impairment [OCI; including mild cognitive impairment (MCI) and dementia groups), but its association with APOE ε4 and discriminatory powers for SCDwith subtle cognitive decline (SCDs) and OCI in memory clinics are unclear.

Objectives

To investigate demographic distribution of APOE ε4, its association with SCD-Q9 scores, and its ability to discriminate SCDs and OCI groups from normal control (NC).

Methods

A total of 632 participants were recruited (NC = 243, SCDs = 298, OCI = 91). APOE ε4 allele distribution and association with SCD-Q9 scores were calculated and the effects on cognitive impairment were analyzed. Receiver operating characteristic (ROC) analysis was applied to identify discriminatory powers for NC, SCDs, and OCI.

Results

Total APOE ε4 frequency was 13.1%. This did not vary by demography but was higher in patients with OCI. The SCD-Q9 scores were higher in APOE ε4 carriers than non-carriers in the OCI group. The area under the curve (AUC) for discriminating from OCI using APOE ε4 were 0.587 and 0.575, using SCD-Q9 scores were 0.738 and 0.571 for NC and SCDs groups, respectively. When we combined APOE ε4 and SCD-Q9 scores into the model, the AUC increased to 0.747 for discriminating OCI from NC. However, when OCI group was split into MCI and dementia groups, only total SCD-Q9 score was the independent affecting factor of MCI.

Conclusion

This study demonstrated that the distribution of APOE ε4 alleles did not vary with different demographic characteristics in a large-scale cohort from a memory clinic. APOE ε4 alleles may be associated with scores of SCD-Q9 reflecting the degree of cognitive complaints but their additional contribution to SCD-Q9 scores is marginal in discriminating between NC, SCDs, and OCI.
Circadian Sensitivity of Noise Trauma-Induced Hearing Loss and Tinnitus in Mongolian Gerbils
Authors: Grimm Jannik , Schulze Holger , Tziridis Konstantin
Published: June 2022

Noise-induced hearing loss (HL) has a circadian component: In nocturnal mice, hearing thresholds (HT) have a significantly stronger effect to acoustic trauma when induced during the night compared to rather mild effects on hearing when induced during daytime. Here, we investigate whether such effects are also present in diurnal Mongolian gerbils and determined whether trauma-induced HL correlated with the development of a tinnitus percept in these animals. In particular, we investigated the effects of acoustic trauma (2 kHz, 115 dB SPL, 75 min) on HT and tinnitus development in 34 male gerbils exposed either at 9 AM, 1 PM, 5 PM, or 12 PM. HT was measured by acoustic brainstem response audiometry at defined times 1 day before and 1 week after the trauma. Possible tinnitus percepts were assessed behaviorally by the gap prepulse inhibition of the acoustic startle response at defined times 1 day before and 1 week after the trauma. We found daytime-dependent changes due to trauma in mean HT in a frequency-dependent manner comparable to the results in mice, but the results temporally shifted according to respective activity profiles. Additionally, we found linear correlations of these threshold changes with the strength of the tinnitus percept, with the most prominent correlations in the 5 PM trauma group. Taken together, circadian sensitivity of the HT to noise trauma can also be found in gerbils, and tinnitus strength correlates most strongly with HL only when the trauma is applied at the most sensitive times, which seem to be the evening.
The Coupled Representation of Hierarchical Features for Mild Cognitive Impairment and Alzheimer's Disease Classification
Authors: Liu Ke , Li Qing , Yao Li , Guo Xiaojuan
Published: June 2022

Structural magnetic resonance imaging (MRI) features have played an increasingly crucial role in discriminating patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) from normal controls (NC). However, the large number of structural MRI studies only extracted low-level neuroimaging features or simply concatenated multitudinous features while ignoring the interregional covariate information. The appropriate representation and integration of multilevel features will be preferable for the precise discrimination in the progression of AD. In this study, we proposed a novel inter-coupled feature representation method and built an integration model considering the two-level (the regions of interest (ROI) level and the network level) coupled features based on structural MRI data. For the intra-coupled interactions about the network-level features, we performed the ROI-level (intra- and inter-) coupled interaction within each network by feature expansion and coupling learning. For the inter-coupled interaction of the network-level features, we measured the coupled relationships among different networks via Canonical correlation analysis. We evaluated the classification performance using coupled feature representations on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Results showed that the coupled integration model with hierarchical features achieved the optimal classification performance with an accuracy of 90.44% for AD and NC groups, with an accuracy of 87.72% for the MCI converter (MCI-c) and MCI non-converter (MCI-nc) groups. These findings suggested that our two-level coupled interaction representation of hierarchical features has been the effective means for the precise discrimination of MCI-c from MCI-nc groups and, therefore, helpful in the characterization of different AD courses.
CAU-Net: A Deep Learning Method for Deep Gray Matter Nuclei Segmentation
Authors: Chai Chao , Wu Mengran , Wang Huiying , Cheng Yue , Zhang Shengtong , Zhang Kun , Shen Wen , Liu Zhiyang , Xia Shuang
Published: June 2022

The abnormal iron deposition of the deep gray matter nuclei is related to many neurological diseases. With the quantitative susceptibility mapping (QSM) technique, it is possible to quantitatively measure the brain iron content in vivo. To assess the magnetic susceptibility of the deep gray matter nuclei in the QSM, it is mandatory to segment the nuclei of interest first, and many automatic methods have been proposed in the literature. This study proposed a contrast attention U-Net for nuclei segmentation and evaluated its performance on two datasets acquired using different sequences with different parameters from different MRI devices. Experimental results revealed that our proposed method was superior on both datasets over other commonly adopted network structures. The impacts of training and inference strategies were also discussed, which showed that adopting test time augmentation during the inference stage can impose an obvious improvement. At the training stage, our results indicated that sufficient data augmentation, deep supervision, and nonuniform patch sampling contributed significantly to improving the segmentation accuracy, which indicated that appropriate choices of training and inference strategies were at least as important as designing more advanced network structures.
Metformin in the Treatment of Amisulpride-Induced Hyperprolactinemia: A Clinical Trial
Authors: Zhu Cuifang , Li Ruofan , Ju Mingliang , Xiao Xudong , Yuan Ti-Fei , Jin Zhixing , Zhao Jing
Published: June 2022

Objective

To evaluate the efficacy and safety of metformin in the treatment of amisulpride-induced hyperprolactinemia.

Methods

A total of 86 schizophrenic patients who developed hyperprolactinemia after taking amisulpride were screened and randomly assigned to the metformin group (42 patients) and placebo group (44 patients) and followed up for eight weeks. The patients’ serum prolactin levels, blood glucose and lipids were measured at the baseline and the end of the intervention. The treatment emergent symptom scale (TESS) was also assessed.

Results

After eight weeks of intervention, serum prolactin levels in the metformin group decreased from (1737.360 ± 626.918) mIU/L at baseline to (1618.625 ± 640.865) mIU/L, whereas serum prolactin levels in the placebo group increased from (2676.470 ± 1269.234) mIU/L at baseline to (2860.933 ± 1317.376) mIU/L. There was a significant difference in prolactin changes (Fcovariance = 9.982, P = 0.002) between the two groups. There was no significant difference in the incidence of adverse drug reactions (P > 0.05) between the two groups.

Conclusion

Metformin is able to improve amisulpride-induced hyperprolactinemia with its safety.
DSNN: A DenseNet-Based SNN for Explainable Brain Disease Classification
Authors: Zhu Ziquan , Lu Siyuan , Wang Shui-Hua , Gorriz Juan Manuel , Zhang Yu-Dong
Published: June 2022

Aims: Brain diseases refer to intracranial tissue and organ inflammation, vascular diseases, tumors, degeneration, malformations, genetic diseases, immune diseases, nutritional and metabolic diseases, poisoning, trauma, parasitic diseases, etc. Taking Alzheimer’s disease (AD) as an example, the number of patients dramatically increases in developed countries. By 2025, the number of elderly patients with AD aged 65 and over will reach 7.1 million, an increase of nearly 29% over the 5.5 million patients of the same age in 2018. Unless medical breakthroughs are made, AD patients may increase from 5.5 million to 13.8 million by 2050, almost three times the original. Researchers have focused on developing complex machine learning (ML) algorithms, i.e., convolutional neural networks (CNNs), containing millions of parameters. However, CNN models need many training samples. A small number of training samples in CNN models may lead to overfitting problems. With the continuous research of CNN, other networks have been proposed, such as randomized neural networks (RNNs). Schmidt neural network (SNN), random vector functional link (RVFL), and extreme learning machine (ELM) are three types of RNNs.

Methods: We propose three novel models to classify brain diseases to cope with these problems. The proposed models are DenseNet-based SNN (DSNN), DenseNet-based RVFL (DRVFL), and DenseNet-based ELM (DELM). The backbone of the three proposed models is the pre-trained “customize” DenseNet. The modified DenseNet is fine-tuned on the empirical dataset. Finally, the last five layers of the fine-tuned DenseNet are substituted by SNN, ELM, and RVFL, respectively.

Results: Overall, the DSNN gets the best performance among the three proposed models in classification performance. We evaluate the proposed DSNN by five-fold cross-validation. The accuracy, sensitivity, specificity, precision, and F1-score of the proposed DSNN on the test set are 98.46% ± 2.05%, 100.00% ± 0.00%, 85.00% ± 20.00%, 98.36% ± 2.17%, and 99.16% ± 1.11%, respectively. The proposed DSNN is compared with restricted DenseNet, spiking neural network, and other state-of-the-art methods. Finally, our model obtains the best results among all models.

Conclusions: DSNN is an effective model for classifying brain diseases.
Poor Nutritional Status and Dynapenia Are Highly Prevalent in Post-Acute COVID-19
Authors: de Blasio Francesco , Scalfi Luca , Castellucci Bianca , Sacco Anna Maria , Berlingieri Giulia Miracco , Capitelli Ludovica , Alicante Paola , Sanduzzi Alessandro , Bocchino Marialuisa
Published: June 2022

Poor nutritional status is common (estimated prevalence 5–69%) in acute coronavirus disease-2019 (COVID-19), and has been associated with hospitalization, the need for intensive care, and mortality. Body composition (BC) and muscle function have also been related in such patients to poor disease outcomes.

As the evidence in the literature is limited, a cross-sectional study was carried out to determine the frequency of malnutrition in a cohort of post-acute COVID-19 patients referred to a rehabilitation center after hospital discharge. BC and muscle strength were assessed and the differences between bedridden and not bedridden patients were specifically evaluated.

The study sample was composed of 144 post-acute COVID-19 patients (mean age 64.8 years; males = 95), 37% of whom were bedridden (males = 60%). Nutritional status was evaluated with Mini-Nutritional Assessment (MNA) and Controlling Nutritional status (CONUT). Fat-free mass (FFM) and skeletal muscle mass (SM) were estimated using bioelectrical impedance analysis (BIA). Raw BIA variables (phase angle = PhA and impedance ratios = IRs) were also determined and handgrip strength (HGS) was measured. Dynapenia was identified according to the 2019 EWGSOP criteria.

According to MNA, 18% (n. 26) of patients were malnourished and 62% (n. 89) were at risk of malnutrition. As for CONUT, 21% (n. 31) of cases had moderate–severe malnutrition and 58% (n. 83) had light malnutrition. Abnormalities of raw BIA variables (low PhA and high IRs) and low HGS were more common in bedridden patients, in those who were malnourished, or had low FFM or SM. Dynapenic patients were 65% men and 47% women.

In conclusion, malnutrition, BC alterations, and low HGS occur in post-acute COVID-19 patients and are more common in bedridden patients. Further studies are needed to identify reliable algorithms for assessing nutritional status in post-acute COVID-19 patients undergoing rehabilitation.
Daily Intake of a Phaseolus vulgaris L. Snack Bar Attenuates Hypertriglyceridemia and Improves Lipid Metabolism-Associated Plasma Proteins in Mexican Women: A Randomized Clinical Trial
Authors: Ramírez-Jiménez Aurea K. , Luzardo-Ocampo Ivan , Cuellar-Nuñez M. Liceth , Anaya-Loyola Miriam Aracely , León-Galván Ma. Fabiola , Loarca-Piña Guadalupe
Published: June 2022

Current efforts to prevent dyslipidemia are focused on the development of functional products as an alternative for hypertriglyceridemia management. This study assessed the metabolic effect of the daily consumption of a bean and oats snack bar (BOSB) on hypertriglyceridemia biomarkers among Mexican women. An 8-weeks randomized parallel clinical trial (ID: NCT0496694, https://clinicaltrials.gov/ct2/show/NCT04966494) was conducted with 26 hypertriglyceridemic women allocated to BOSB group (TG = 208.18 ± 56.97 mg/dL) and control group (TG = 182.28 ± 51.39 mg/dL). Only the BOSB group consumed 50 g of the product per day. Fasting blood samples were taken from women with an adherence ≥ 90%. A targeted proteomic analysis with plasma samples of control and BOSB groups were conducted using a human obesity antibody array kit and bioinformatic tools provided by the Ingenuity Pathways Analysis (IPA) software. Serum TG levels in the BOSB group decreased by 37.80% (132.04 ± 27.83 mg/dL) compared with the control group (178.87 ± 32.01 mg/dL); glucose levels decreased by 5.69% in the BOSB group (87.55 ± 3.36 mg/dL). A modest body weight (5%) reduction was also found. Forty proteins were differentially modulated by the BOSB consumption (fold change > 1.2). The proteomic analysis revealed the involvement of BOSB bioactives in prevention of monocytes recruitment and localized inflammatory response, inhibition of pre-adipocyte maturation and adipogenesis, inhibition of hepatic b-oxidation, and potential satiety regulation. These results are promising since the mere intervention with the BOSB reduced serum TG without diet restriction, giving insights for further research in prevention of hypertriglyceridemia.
Modification of Ovalbumin by Maillard Reaction: Effect of Heating Temperature and Different Monosaccharides
Authors: Yan Yujie , Hang Fangxue , Wei Tiantian , Xie Caifeng , Niu Debao
Published: June 2022

Glycosylation is considered to be an effective way to improve the performance of protein emulsification. This study focused on the effects of the molecular structure and emulsifying properties of ovalbumin (OVA) by wet heating Maillard reaction with three types of monosaccharides (i.e., xylose, glucose, and galactose). Results showed that increasing reaction temperature from 55°C to 95°C could significantly improve the degree of grafting (DG), while glycosylated OVA conjugate with xylose at 95°C processed the highest DG of 28.46%. This reaction was further confirmed by the browning intensity determination. Analysis of Fourier transform infrared spectrophotometer, circular dichroism, and fluorescence spectra indicated that there were slight changes in the subunits and the conversion of α-helices to β-sheets, as well as the unfolded structures, thereby increasing the surface hydrophobicity and absolute zeta potential of obtained glycosylated OVA. Glycosylation endowed OVA with better emulsifying properties, especially the xylose glycosylated OVA was superior to that of glucose and galactose glycosylated OVA, which was mainly due to its shorter molecular chains with smaller steric hindrance for reaction. Furthermore, the enhancement of emulsifying properties may be attributed to the synergistic effect of stronger electrostatic repulsion of larger absolute zeta potential and the steric hindrance from thicker adsorbed layer, thereby inhibiting aggregation and flocculation of emulsion droplet.
Structural Characterization, Antioxidant and Antibacterial Activities of a Novel Polysaccharide From Zingiber officinale and Its Application in Synthesis of Silver Nanoparticles
Authors: Jing Yongshuai , Cheng Wenjing , Ma Yunfeng , Zhang Yameng , Li Mingsong , Zheng Yuguang , Zhang Danshen , Wu Lanfang
Published: June 2022

A novel polysaccharide (ZOP) was extracted from Zingiber officinale with ultrasonic assisted extraction method. ZOP monosaccharide composition and mole ratio is GlcA: GalA: Glc: Gal: Ara = 1.97:1.15:94.33:1.48:1.07. Then, the particle size of ZOP-NPs prepared by nano-precipitation method was 230.5 nm, and the polydispersity index (PDI) was 0.260. Using ZOP and ZOP-NPs as reductants and stabilizers, ZOP-AgNPs and ZOP-NPs-AgNPs were prepared. They were characterized by ultraviolet-visible spectrophotometer (UV-Vis), fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), transmission electron microscope (TEM), and X-ray diffraction (XRD). The silver chelation rate of polysaccharide silver nanoparticles (AgNPs) ranged from 68.70 to 82.12%. ZOP-AgNPs (0.5%, w/v; 1%, w/v) and ZOP-NPs-AgNPs (0.5%, w/v; 1%, w/v) exhibited a narrow particle size distribution of 31.1, 34.6, 25.1 and 27.6 nm, respectively. And the zeta potential values of them were−19.4,−21.6,−19.7,−23.8mV, respectively. The antioxidant and antibacterial activities of ZOP-NPs-AgNPs were superior to those of ZOP, ZOP-NPs and ZOP-AgNPs.
FOXP4-AS1 May be a Potential Prognostic Biomarker in Human Cancers: A Meta−Analysis and Bioinformatics Analysis
Authors: Zhang Guangming , Wang Yongfeng , Han Xiaoyong , Lu Tingting , Fu Liangyin , Jin Haojie , Yang Kehu , Cai Hui
Published: June 2022

Background

Cancer is one of the leading causes of death worldwide. Early diagnosis can significantly lower cancer-related mortality. Studies have shown that the lncRNA Forkhead box P4 antisense RNA 1 (FOXP4-AS1) is aberrantly expressed in various solid tumors. A meta-analysis was performed to evaluate the correlation of FOXP4-AS1 with the prognosis of cancer patients and determine the clinical value of FOXP4-AS1 as a potential diagnostic marker.

Methods

Correlational studies from the Web of Science, Embase, OVID, Cochrane and PubMed databases were screened (up to April 1, 2021). Meta-analysis was performed using Stata SE12.0 software.

Results

Eleven original studies with 1,332 patients who were diagnosed with a solid cancer (nasopharyngeal carcinoma, hepatocellular carcinoma, colorectal cancer, gastric cancer, osteosarcoma, mantle cell lymphoma, prostate cancer, and pancreatic ductal adenocarcinoma) were included in the meta-analysis. High expression of FOXP4-AS1 was correlated with poor overall survival (OS) (HR = 1.77, 95% CI 1.29–2.44, P < 0.001) and shorter disease−free survival (DFS) (HR = 1.66, 95% CI 1.01–2.72, P = 0.044). Subgroup analysis based on sample size, follow-up time and Newcastle-Ottawa Scale (NOS) score revealed significant differences between FOXP4-AS1 levels and OS (P < 0.05). However, the expression level of FOXP4-AS1 was not significantly correlated with the OS of gastric cancer patients (P = 0.381). High expression of FOXP4-AS1 was predictive of a larger tumor size (OR = 3.82, 95% CI 2.3–6.3, P < 0.001).

Conclusions

Overexpression of FOXP4-AS1 correlates with poor prognosis of cancer patients, and is a potential prognostic biomarker and therapeutic target.

Systematic Review Registration

PROSPERO, identifier CRD42021245267.
Molecular Typing of Gastric Cancer Based on Invasion-Related Genes and Prognosis-Related Features
Authors: Guo Haonan , Tang Hui , Zhao Yang , Zhao Qianwen , Hou Xianliang , Ren Lei
Published: June 2022

Background

This study aimed to construct a prognostic stratification system for gastric cancer (GC) using tumour invasion-related genes to more accurately predict the clinical prognosis of GC.

Methodology

Tumour invasion-related genes were downloaded from CancerSEA, and their expression data in the TCGA-STAD dataset were used to cluster samples via non-negative matrix factorisation (NMF). Differentially expressed genes (DEGs) between subtypes were identified using the limma package. KEGG pathway and GO functional enrichment analyses were conducted using the WebGestaltR package (v0.4.2). The immune scores of molecular subtypes were evaluated using the R package ESTIMATE, MCPcounter and the ssGSEA function of the GSVA package. Univariate, multivariate and lasso regression analyses of DEGs were performed using the coxph function of the survival package and the glmnet package to construct a RiskScore model. The robustness of the model was validated using internal and external datasets, and a nomogram was constructed based on the model.

Results

Based on 97 tumour invasion-related genes, 353 GC samples from TCGA were categorised into two subtypes, thereby indicating the presence of inter-subtype differences in prognosis. A total of 569 DEGs were identified between the two subtypes; of which, four genes were selected to construct the risk model. This four-gene signature was robust and exhibited stable predictive performance in different platform datasets (GSE26942 and GSE66229), indicating that the established model performed better than other existing models.

Conclusion

A prognostic stratification system based on a four-gene signature was developed with a desirable area under the curve in the training and independent validation sets. Therefore, the use of this system as a molecular diagnostic test is recommended to assess the prognostic risk of patients with GC.
Detachment of Hexokinase II From Mitochondria Promotes Collateral Sensitivity in Multidrug Resistant Chronic Myeloid Leukemia Cells
Authors: Oliveira Thaís , Lemos Douglas , Jean Louise , Kawashima Jéssica M. , de Azevedo Vitória R. , Salustiano Eduardo J. , Rumjanek Vivian M. , Monteiro Robson Q.
Published: June 2022

Chronic Myeloid Leukemia is a neoplastic disease characterized by the abnormal expansion of hematopoietic cells with compromised functions. Leukemic cells often display a multidrug resistance phenotype, enabling them to evade a number of structurally unrelated cytotoxic compounds. One of those mechanisms relies on the high expression of efflux transporters, such as the ABC proteins, whose activity depends on the hydrolysis of ATP to reduce intracellular drug accumulation. In the present work, we employed a well-known erythroleukemia cell line, K562, and a multidrug resistant derivative cell, FEPS, to evaluate how hexokinase II, a key regulator for the rate-limiting step glycolysis, contributes to the establishment of the multidrug resistance phenotype. We found that multidrug resistant cells primarily resort to glycolysis to generate ATP. Clotrimazole reduced the expression of mitochondrial hexokinase II, which destabilized bioenergetic parameters such as reactive oxygen species production, ATP, and glutathione levels on multidrug resistant cells. This impaired the activity of ABCC1, leading to increased drug accumulation and cell death. In summary, we propose that decoupling of hexokinase II from the mitochondria emerges as a promising strategy to generate collateral sensitivity and aid in the management of chronic myeloid leukemia in chemotherapy-refractory patients.
Changes in Pulmonary Microenvironment Aids Lung Metastasis of Breast Cancer
Authors: Wu Meimei , Liang Yanfang , Zhang Xin
Published: June 2022

Breast cancer has become the most common malignant disease in the world according to the International Agency for Research on Cancer (IARC), and the most critical cause of death is distant metastasis. The lung is the extremely common visceral site for breast cancer metastasis. Lung metastasis of breast cancer is not only dependent on the invasive ability of the tumor itself, but also closely relates to the pulmonary microenvironment. In the progression of breast cancer, the formation of specific microenvironment in lungs can provide suitable conditions for the metastasis of breast cancer. Pulmonary inflammatory response, angiogenesis, extracellular matrix remodeling, some chemotherapeutic agents and so on all play important roles in the formation of the pulmonary microenvironment. This review highlights recent findings regarding the alterations of pulmonary microenvironment in lung metastasis of breast cancer, with a focus on various cells and acellular components.
Deep Learning for Approaching Hepatocellular Carcinoma Ultrasound Screening Dilemma: Identification of α-Fetoprotein-Negative Hepatocellular Carcinoma From Focal Liver Lesion Found in High-Risk Patients
Authors: Zhang Wei-bin , Hou Si-ze , Chen Yan-ling , Mao Feng , Dong Yi , Chen Jian-gang , Wang Wen-ping
Published: June 2022

Background

First-line surveillance on hepatitis B virus (HBV)-infected populations with B-mode ultrasound is relatively limited to identifying hepatocellular carcinoma (HCC) without elevated α-fetoprotein (AFP). To improve the present HCC surveillance strategy, the state of the art of artificial intelligence (AI), a deep learning (DL) approach, is proposed to assist in the diagnosis of a focal liver lesion (FLL) in HBV-infected liver background.

Methods

Our proposed deep learning model was based on B-mode ultrasound images of surgery that proved 209 HCC and 198 focal nodular hyperplasia (FNH) cases with 413 lesions. The model cohort and test cohort were set at a ratio of 3:1, in which the test cohort was composed of AFP-negative HBV-infected cases. Four additional deep learning models (MobileNet, Resnet50, DenseNet121, and InceptionV3) were also constructed as comparative baselines. To evaluate the models in terms of diagnostic power, sensitivity, specificity, accuracy, confusion matrix, F1-score, and area under the receiver operating characteristic curve (AUC) were calculated in the test cohort.

Results

The AUC of our model, Xception, achieved 93.68% in the test cohort, superior to other baselines (89.06%, 85.67%, 83.94%, and 78.13% respectively for MobileNet, Resnet50, DenseNet121, and InceptionV3). In terms of diagnostic power, our model showed sensitivity, specificity, accuracy, and F1-score of 96.08%, 76.92%, 86.41%, and 87.50%, respectively, and PPV, NPV, FPR, and FNR calculated from the confusion matrix were respectively 80.33%, 95.24%, 23.08%, and 3.92% in identifying AFP-negative HCC from HBV-infected FLL cases. Satisfactory robustness of our proposed model was shown based on 5-fold cross-validation performed among the models above.

Conclusions

Our DL approach has great potential to assist B-mode ultrasound in identifying AFP-negative HCC from FLL found in surveillance of HBV-infected patients.
Fibroblast-Induced Paradoxical PI3K Pathway Activation in PTEN-Competent Colorectal Cancer: Implications for Therapeutic PI3K/mTOR Inhibition
Authors: Conciatori Fabiana , Salvati Erica , Ciuffreda Ludovica , Shirasawa Senji , Falcone Italia , Cognetti Francesco , Ferretti Gianluigi , Zeuli Massimo , Del Bufalo Donatella , Bazzichetto Chiara , Milella Michele
Published: June 2022

Purpose

Tumor-microenvironment interactions are important determinants of drug resistance in colorectal cancer (CRC). We, therefore, set out to understand how interactions between genetically characterized CRC cells and stromal fibroblasts might influence response to molecularly targeted inhibitors.

Techniques

Sensitivity to PI3K/AKT/mTOR pathway inhibitors of CRC cell lines, with known genetic background, was investigated under different culture conditions [serum-free medium, fibroblasts’ conditioned medium (CM), direct co-culture]. Molecular pathway activation was monitored using Western Blot analysis. Immunoprecipitation was used to detect specific mTOR complex activation. Immunofluorescence was used to analyze cellular PTEN distribution, while different mutant PTEN plasmids were used to map the observed function to specific PTEN protein domains.

Results

Exposure to fibroblast-CM resulted in increased growth-inhibitory response to double PI3K/mTOR inhibitors in PTEN-competent CRC cell lines harboring KRAS and PI3K mutations. Such functional effect was attributable to fibroblast-CM induced paradoxical PI3K/mTORC1 pathway activation, occurring in the presence of a functional PTEN protein. At a molecular level, fibroblast-CM induced C-tail phosphorylation and cytoplasmic redistribution of the PTEN protein, thereby impairing its lipid phosphatase function and favored the formation of active, RAPTOR-containing, mTORC1 complexes. However, PTEN’s lipid phosphatase function appeared to be dispensable, while complex protein-protein interactions, also involving PTEN/mTOR co-localization and subcellular distribution, were crucial for both mTORC1 activation and sensitivity to double PI3K/mTOR inhibitors.

Data Interpretation

Microenvironmental cues, in particular soluble factors produced by stromal fibroblasts, profoundly influence PI3K pathway signaling and functional response to specific inhibitors in CRC cells, depending on their mutational background and PTEN status.
The Molecular Role of IL-35 in Non-Small Cell Lung Cancer
Authors: Hao Yuqiu , Dong Hongna , Li Wei , Lv Xuejiao , Shi Bingqing , Gao Peng
Published: June 2022

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer and a common cause of cancer-related death. Better understanding of the molecular mechanisms, pathogenesis, and treatment of NSCLC can help improve patient outcomes. Significant progress has been made in the treatment of NSCLC, and immunotherapy can prolong patient survival. However, the overall cure and survival rates are low, especially in patients with advanced metastases. Interleukin-35 (IL-35), an immunosuppressive factor, is associated with the onset and prognosis of various cancers. Studies have shown that IL-35 expression is elevated in NSCLC, and it is closely related to the progression and prognosis of NSCLC. However, there are few studies on the mechanism of IL-35 in NSCLC. This study discusses the role of IL-35 and its downstream signaling pathways in the pathogenesis of NSCLC and provides new insights into its therapeutic potential.
MRI-Based Radiomics and Urine Creatinine for the Differentiation of Renal Angiomyolipoma With Minimal Fat From Renal Cell Carcinoma: A Preliminary Study
Authors: Jian Lian , Liu Yan , Xie Yu , Jiang Shusuan , Ye Mingji , Lin Huashan
Published: June 2022

Objectives

Standard magnetic resonance imaging (MRI) techniques are different to distinguish minimal fat angiomyolipoma (mf-AML) with minimal fat from renal cell carcinoma (RCC). Here we aimed to evaluate the diagnostic performance of MRI-based radiomics in the differentiation of fat-poor AMLs from other renal neoplasms.

Methods

A total of 69 patients with solid renal tumors without macroscopic fat and with a pathologic diagnosis of RCC (n=50) or mf-AML (n=19) who underwent conventional MRI and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) were included. Clinical data including age, sex, tumor location, urine creatinine, and urea nitrogen were collected from medical records. The apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were measured from renal tumors. We used the ITK-SNAP software to manually delineate the regions of interest on T2-weighted imaging (T2WI) and IVIM-DWI from the largest cross-sectional area of the tumor. We extracted 396 radiomics features by the Analysis Kit software for each MR sequence. The hand-crafted features were selected by using the Pearson correlation analysis and least absolute shrinkage and selection operator (LASSO). Diagnostic models were built by logistic regression analysis. Receiver operating characteristic curve analysis was performed using five-fold cross-validation and the mean area under the curve (AUC) values were calculated and compared between the models to obtain the optimal model for the differentiation of mf-AML and RCC. Decision curve analysis (DCA) was used to evaluate the clinical utility of the models.

Results

Clinical model based on urine creatinine achieved an AUC of 0.802 (95%CI: 0.761-0.843). IVIM-based model based on f value achieved an AUC of 0.692 (95%CI: 0.627-0.757). T2WI-radiomics model achieved an AUC of 0.883 (95%CI: 0.852-0.914). IVIM-radiomics model achieved an AUC of 0.874 (95%CI: 0.841-0.907). Combined radiomics model achieved an AUC of 0.919 (95%CI: 0.894-0.944). Clinical-radiomics model yielded the best performance, with an AUC of 0.931 (95%CI: 0.907-0.955). The calibration curve and DCA confirmed that the clinical-radiomics model had a good consistency and clinical usefulness.

Conclusion

The clinical-radiomics model may be served as a noninvasive diagnostic tool to differentiate mf-AML with RCC, which might facilitate the clinical decision-making process.
Pretreatment Metabolic Parameters Measured by 18F-FDG PET to Predict the Pathological Treatment Response of HCC Patients Treated With PD-1 Inhibitors and Lenvatinib as a Conversion Therapy in BCLC Stage C
Authors: Wang Guanyun , Zhang Wenwen , Chen Jiaxin , Luan Xiaohui , Wang Zhanbo , Wang Yanmei , Xu Xiaodan , Yao Shulin , Guan Zhiwei , Tian Jiahe , Lu Shichun , Xu Baixuan , Ma Guangyu
Published: June 2022

Objectives

This study aimed to assess the pretreatment 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) as a predictor of the pathological treatment response (PTR) of hepatocellular carcinoma (HCC) patients treated with PD-1 inhibitors and lenvatinib as a conversion therapy in BCLC stage C.

Methods

All patients (n=20) underwent pretreatment 18F-FDG PET/CT and were treated with conversion therapy and surgery. Patients were categorized into responders (n=9) and non-responders (n=11) according to PTR. The parameters of PET/CT, including lesion size, SUVmean (mean standard uptake value), MTV (metabolic tumor volume), TLG (total lesion glycolysis), SUVpeak (peak standard uptake value), and TLR (tumor-to-normal liver standardized uptake value ratio), were calculated. The diagnostic efficacy was evaluated by receiver operating characteristic analysis (ROC). PTR was compared with pretreatment PET/CT parameters by using Spearman correlation analysis. The patients were followed up.

Results

There was significant difference in TLR (5.59 ± 1.90 vs. 2.84 ± 1.70, respectively; P=0.003) between responders and non-responders, with the largest area under the curve (sensitivity=100%, specificity=72.7%, AUC=0.899, 95%CI: 0.759-1.000, optimal diagnostic threshold of 3.09). The relationship between 18F-FDG PET/CT parameters and PTR indicated TLR was moderately and positively correlated with pathological treatment response, with correlation coefficients (rs) of 0.69 (P<0.01). During the follow-up, no patients died, and tumor recurrence was found in one of the responders (11.1%). In all 11 non-responders, tumor recurrence was found in six patients (54.5%) and four patients (36.4%) died.

Conclusions

TLR may be a powerful marker to predict PTR of HCC patients with BCLC stage C who were treated with conversion therapy.
Smart Nanoparticles for Breast Cancer Treatment Based on the Tumor Microenvironment
Authors: Luo Xiao , Zhang Qi , Chen Hongbo , Hou Kai , Zeng Ning , Wu Yiping
Published: June 2022

Breast cancer (BC) is the most common malignant tumor in women. There are different risk characteristics and treatment strategies for different subtypes of BC. The tumor microenvironment (TME) is of great significance for understanding the occurrence, development, and metastasis of tumors. The TME plays an important role in all stages of BC metastasis, immune monitoring, immune response avoidance, and drug resistance, and also plays an important role in the diagnosis, prevention, and prognosis of BC. Smart nanosystems have broad development prospect in the regulation of the BC drug delivery based on the response of the TME. In particular, TME-responsive nanoparticles cleverly utilize the abnormal features of BC tissues and cells to achieve targeted transport, stable release, and improved efficacy. We here present a review of the mechanisms underlying the response of the TME to BC to provide potential nanostrategies for future BC treatment.