bluuebunny/crossref_metadata_2025 huggingface dataset:
Accurate Machine Learning Model to Diagnose Chronic Autoimmune Diseases Utilizing Information From B Cells and Monocytes
Authors: Ma Yuanchen , Chen Jieying , Wang Tao , Zhang Liting , Xu Xinhao , Qiu Yuxuan , Xiang Andy Peng , Huang Weijun
Published: April 2022

Heterogeneity and limited comprehension of chronic autoimmune disease pathophysiology cause accurate diagnosis a challenging process. With the increasing resources of single-cell sequencing data, a reasonable way could be found to address this issue. In our study, with the use of large-scale public single-cell RNA sequencing (scRNA-seq) data, analysis of dataset integration (3.1 × 105 PBMCs from fifteen SLE patients and eight healthy donors) and cellular cross talking (3.8 × 105 PBMCs from twenty-eight SLE patients and eight healthy donors) were performed to identify the most crucial information characterizing SLE. Our findings revealed that the interactions among the PBMC subpopulations of SLE patients may be weakened under the inflammatory microenvironment, which could result in abnormal emergences or variations in signaling patterns within PBMCs. In particular, the alterations of B cells and monocytes may be the most significant findings. Utilizing this powerful information, an efficient mathematical model of unbiased random forest machine learning was established to distinguish SLE patients from healthy donors via not only scRNA-seq data but also bulk RNA-seq data. Surprisingly, our mathematical model could also accurately identify patients with rheumatoid arthritis and multiple sclerosis, not just SLE, via bulk RNA-seq data (derived from 688 samples). Since the variations in PBMCs should predate the clinical manifestations of these diseases, our machine learning model may be feasible to develop into an efficient tool for accurate diagnosis of chronic autoimmune diseases.
Microbiome Analysis of Malacopathogenic Nematodes Suggests No Evidence of a Single Bacterial Symbiont Responsible for Gastropod Mortality
Authors: Sheehy Laura , Cutler James , Weedall Gareth D. , Rae Robbie
Published: April 2022

Nematodes and bacteria are prevalent in soil ecosystems, and some have evolved symbiotic relationships. In some cases, symbionts carry out highly specialized functions: a prime example being entomopathogenic nematodes (EPNs), which vector bacteria (Xenorhabdus or Photorhabdus) into insect hosts, killing them to provide a food source for the nematodes. It is thought that the commercially available malacopathogenic (kills slugs and snails) biocontrol nematode Phasmarhabditis hermaphrodita vectors a bacterium (Moraxella osloensis) into slugs to kill them. To investigate this further we used a metagenomic approach to profile the bacteria present in the commercial strain of P. hermaphrodita, a wild strain of P. hermaphrodita and two other Phasmarhabditis species (P. californica and P. neopapillosa), after they had killed their slug host (Deroceras invadens). We show that these nematodes do not exclusively associate with one bacterium but a range of species, with members of the phyla Pseudomonadota, Bacillota, Actinobacteriota and Bacteroidota the most prevalent. The commercial strain of P. hermaphrodita had the least diverse bacterial community. Furthermore, we found that the bacterium P. hermaphrodita has been cultured on for 25 years is not the expected species M. osloensis but is Psychrobacter spp. and the only strain of the Phasmarhabditis species to associate with Psychrobacter spp. was the commercial strain of P. hermaphrodita. In summary, we found no evidence to show that P. hermaphrodita rely exclusively on one bacterium to cause host mortality but found variable and diverse bacterial communities associated with these nematodes in their slug hosts.
Case Report: Therapeutic Use of Ibrutinib in a Patient With Schnitzler Syndrome
Authors: Huang Yuehua , Wang Yanying , Yu Fan , Mao Xuehan , Wang Bianhong , Li Jingxian , Li Lihong
Published: April 2022

Schnitzler syndrome is a rare adult-onset acquired autoinflammatory disorder typically characterized by chronic urticarial rash and immunoglobulin M (IgM) (rarely IgG) monoclonal gammopathy. Its clinical symptoms usually respond well to interleukin-1 blockade therapy, which, however, does not impact the underlying monoclonal gammopathy. Herein, we described a female patient who presented with urticarial rash, recurrent fevers, and fatigue for 7 years. Laboratory investigations revealed IgMκ monoclonal protein and MYD88 L265P mutation, but no lymphoplasmacytic lymphoma on bone marrow examination. She fulfilled the diagnosis of Schnitzler syndrome and was treated with the Bruton tyrosine kinase inhibitor ibrutinib in combination with prednisone. Her symptoms improved dramatically, and the level of IgMκ monoclonal protein also declined. She tolerated the treatment well. This case highlights the potential therapeutic role of Bruton tyrosine kinase inhibitors in Schnitzler syndrome.
Alternative Splicing of the Lobster (Homarus americanus) Crustacean Hyperglycemic Hormone A and B Genes Produce 2 Protein Variants Involved in Vitellogenin Inhibition
Authors: Wang Cheng Gui , Wang Wei , Shi Li Li , Shen Yu Chun , Chan Siuming F.
Published: April 2022

Current BLASTP search analysis results suggested that the lobster (Homarus americanus) HaCHH-A and HaCHH-B may be derived from two different four-exon genes. Repeated tissue expression studies have revealed much different expression patterns of these two genes from those reported in the past. With RT-PCR, rapid amplification of complementary DNA (cDNA) ends (RACE), and genomic DNA cloning, we confirmed that the HaCHH-A and HaCHH-B transcripts were derived from two different four-exon CHH genes. By an alternative splicing mechanism, each gene can produce different but larger transcript variants (i.e., sHaCHH-A and sHaCHH-B) mainly in different non-eyestalk tissues of the females. The larger and unspliced transcripts can be detected in the hepatopancreas, gill, heart, nerve cord, brain, ovary, and thoracic ganglion of the reproductive females. The expression patterns of sHaCHH-A and sHaCHH-B in other non-eyestalk tissues suggest that these transcripts have a wide spectrum of expressions during the female reproductive cycle. An in vitro organ explant culture system was developed to investigate the reproductive function of these cDNAs. The results showed that the recombinant proteins for sHaCHH-A and sHaCHH-B inhibited the gene expression of vitellogenin, whereas the double-stranded RNA (dsRNA) for sHaCHH-A and sHaCHH-B stimulated the expression of the vitellogenin gene in vitro. The results of the study may provide insights for the development of techniques to induce gonad development without using eyestalk ablation operation. This is the first in-depth report of the characterization of two four-exon CHH genes in a crustacean.
Grazing and Recovery of Kelp Gametophytes Under Ocean Warming
Authors: Veenhof Reina J. , Dworjanyn Symon A. , Champion Curtis , Coleman Melinda Ann
Published: April 2022

Kelp forests are economically important ecosystems that support a wealth of biodiversity but are declining globally. They are often replaced by biologically depauperate alternate stable states dominated by turfing algae. Hysteresis maintains algal turfs by inhibiting kelp recruitment, preventing the reestablishment of kelp forests. The mechanisms inhibiting kelp recruitment remain poorly understood as microscopic stages of kelp are difficult to study in situ. A potential mechanism contributing to the suppression of recruitment may be turf-facilitated grazing of kelp gametophytes, the haploid free-living reproductive life stage. Here we assess the resilience of kelp gametophytes to grazing pressure from a gastropod micrograzer commonly present in turf under current and future ocean warming scenarios. Gametophyte coverage and abundance were significantly reduced following grazing under all temperatures, however there was no significant effect of temperature on grazing rates. Once grazing pressure was removed, gametophyte abundance recovered to control levels, but the total coverage and length of gametophytes continued to decline in all treatments. Gametophytes were found to survive micrograzer ingestion and continued to grow in aggregations in the gastropod’s mucus trail and faeces, even producing sporophytes. Gametophyte survival post-ingestion may positively contribute to dispersal and sporophyte recruitment, however the lack of gametophyte recovery at elevated temperatures may counteract this effect under future ocean warming. Taken together, this study demonstrates complex interactions that take place in the turf micro-habitat of kelp gametophytes and highlights biotic factors influencing transitions between kelp forests and algal turfs.
NeuroPack: An Algorithm-Level Python-Based Simulator for Memristor-Empowered Neuro-Inspired Computing
Authors: Huang Jinqi , Stathopoulos Spyros , Serb Alexantrou , Prodromakis Themis
Published: April 2022

Emerging two-terminal nanoscale memory devices, known as memristors, have demonstrated great potential for implementing energy-efficient neuro-inspired computing architectures over the past decade. As a result, a wide range of technologies have been developed that, in turn, are described via distinct empirical models. This diversity of technologies requires the establishment of versatile tools that can enable designers to translate memristors’ attributes in novel neuro-inspired topologies. In this study, we present NeuroPack, a modular, algorithm-level Python-based simulation platform that can support studies of memristor neuro-inspired architectures for performing online learning or offline classification. The NeuroPack environment is designed with versatility being central, allowing the user to choose from a variety of neuron models, learning rules, and memristor models. Its hierarchical structure empowers NeuroPack to predict any memristor state changes and the corresponding neural network behavior across a variety of design decisions and user parameter options. The use of NeuroPack is demonstrated herein via an application example of performing handwritten digit classification with the MNIST dataset and an existing empirical model for metal-oxide memristors.
Molecular and Brain Volume Changes Following Aerobic Exercise, Cognitive and Combined Training in Physically Inactive Healthy Late-Middle-Aged Adults: The Projecte Moviment Randomized Controlled Trial
Authors: Castells-Sánchez Alba , Roig-Coll Francesca , Dacosta-Aguayo Rosalía , Lamonja-Vicente Noemí , Torán-Monserrat Pere , Pera Guillem , García-Molina Alberto , Tormos José Maria , Montero-Alía Pilar , Heras-Tébar Antonio , Soriano-Raya Juan José , Cáceres Cynthia , Domènech Sira , Via Marc , Erickson Kirk I. , Mataró Maria
Published: April 2022

Behavioral interventions have shown promising neuroprotective effects, but the cascade of molecular, brain and behavioral changes involved in these benefits remains poorly understood. Projecte Moviment is a 12-week (5 days per week—45 min per day) multi-domain, single-blind, proof-of-concept randomized controlled trial examining the cognitive effect and underlying mechanisms of an aerobic exercise (AE), computerized cognitive training (CCT) and a combined (COMB) groups compared to a waitlist control group. Adherence was > 80% for 82/109 participants recruited (62% female; age = 58.38 ± 5.47). In this study we report intervention-related changes in plasma biomarkers (BDNF, TNF-α, HGF, ICAM-1, SDF1-α) and structural-MRI (brain volume) and how they related to changes in physical activity and individual variables (age and sex) and their potential role as mediators in the cognitive changes. Our results show that although there were no significant changes in molecular biomarker concentrations in any intervention group, changes in ICAM-1 and SDF1-α were negatively associated with changes in physical activity outcomes in AE and COMB groups. Brain volume changes were found in the CCT showing a significant increase in precuneus volume. Sex moderated the brain volume change in the AE and COMB groups, suggesting that men may benefit more than women. Changes in molecular biomarkers and brain volumes did not significantly mediate the cognitive-related benefits found previously for any group. This study shows crucial initial molecular and brain volume changes related to lifestyle interventions at early stages and highlights the value of examining activity parameters, individual difference characteristics and using a multi-level analysis approach to address these questions.
Function Over Mass: A Meta-Analysis on the Importance of Skeletal Muscle Quality in COVID-19 Patients
Authors: Pinto Flaydson Clayton Silva , Andrade Márcia Fábia , Gatti da Silva Guilherme Henrique , Faiad Jaline Zandonato , Barrére Ana Paula Noronha , Gonçalves Renata de Castro , de Castro Gabriela Salim , Seelaender Marília
Published: April 2022

COVID-19 caused by SARS-CoV-2 infection is a highly contagious disease affecting both the higher and lower portions of the respiratory tract. This disease reached over 265 million people and has been responsible for over 5.25 million deaths worldwide. Skeletal muscle quality and total mass seem to be predictive of COVID-19 outcome. This systematic review aimed at providing a critical analysis of the studies published so far reporting on skeletal muscle mass in patients with COVID-19, with the intent of examining the eventual association between muscle status and disease severity. A meta-analysis was performed to evaluate whether skeletal muscle quantity, quality and function were related to disease severity. Systematic reviews and meta-analyses were conducted according to the guidelines of the Cochrane Handbook for Systematic Reviews of Interventions and reported according to the guidelines of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guide. From a total of 1,056 references found, 480 were selected after removing duplicates. Finally, only 7 met the specified inclusion criteria. The results of this meta-analysis showed that skeletal muscle quality, rather than quantity, was associated with COVID-19 severity, as confirmed by lower skeletal muscle density and lower handgrip strength in patients with severe disease. Muscle function assessment can thus be a valuable tool with prognostic value in COVID-19.
Ultra-Processed Food Availability and Sociodemographic Associated Factors in a Brazilian Municipality
Authors: Serafim Patricia , Borges Camila Aparecida , Cabral-Miranda William , Jaime Patricia Constante
Published: April 2022

The availability of ultra-processed foods in a municipality tends to be related to different types of food retailers and their location in the territory, besides social, economic, and demographic factors. The aim of this study was to evaluate the availability of ultra-processed foods according to different types of food retailers and sociodemographic factors. This is a cross-sectional observational study carried out with audit data from food retailers in the municipality of Jundiaí, SP. Using a validated instrument, data on the availability of 18 types of ultra-processed foods were used to create a score of ultra-processed foods, ranging from 0 to 100 points, and five subscores referring to the ultra-processed food subgroups. Descriptive statistics and means comparison tests were performed to verify differences in the ultra-processed food availability score, according to the food retail type, household income, number of household members, and percentage of people of the color population in the census tract in which food retailers were located. Geo-referenced maps were used to characterize the score of ultra-processed in the territory, according to sociodemographic variables. A total of 649 food retailers were analyzed, most of which were classified as neighborhood markets (25.4%). The supermarkets were the category with the highest ultra-processed food availability score. Among the subgroups of ultra-processed foods analyzed, candies, soft drinks, and snacks were available in 60% of the food retailers. Higher ultra-processed food availability score was observed in regions with lower income, higher percentage of people of color population, and higher number of members per household. The findings show that the greater availability of ultra-processed foods is related to supermarkets and markets and regions of greater social vulnerability, which can put this population at nutritional risk.
Perspective: The Glycemic Index Falls Short as a Carbohydrate Food Quality Indicator to Improve Diet Quality
Authors: Nicholls Jill
Published: April 2022

This perspective examines the utility of the glycemic index (GI) as a carbohydrate quality indicator to improve Dietary Guidelines for Americans (DGA) adherence and diet quality. Achieving affordable, high-quality dietary patterns can address multiple nutrition and health priorities. Carbohydrate-containing foods make important energy, macronutrient, micronutrient, phytochemical, and bioactive contributions to dietary patterns, thus improving carbohydrate food quality may improve diet quality. Following DGA guidance helps meet nutrient needs, achieve good health, and reduce risk for diet-related non-communicable diseases in healthy people, yet adherence by Americans is low. A simple indicator that identifies high-quality carbohydrate foods and improves food choice may improve DGA adherence, but there is no consensus on a definition. The GI is a measure of the ability of the available carbohydrate in a food to increase blood glucose. The GI is well established in research literature and popular resources, and some have called for including the GI on food labels and in food-based dietary guidelines. The GI has increased understanding about physiological responses to carbohydrate-containing foods, yet its role in food-based dietary guidance and diet quality is unresolved. A one-dimensional indicator like the GI runs the risk of being interpreted to mean foods are “good” or “bad,” and it does not characterize the multiple contributions of carbohydrate-containing foods to diet quality, including nutrient density, a core concept in the DGA. New ways to define and communicate carbohydrate food quality shown to help improve adherence to high-quality dietary patterns such as described in the DGA would benefit public health.
Machine Learning-Based Prediction of Lymph Node Metastasis Among Osteosarcoma Patients
Authors: Li Wenle , Liu Yafeng , Liu Wencai , Tang Zhi-Ri , Dong Shengtao , Li Wanying , Zhang Kai , Xu Chan , Hu Zhaohui , Wang Haosheng , Lei Zhi , Liu Qiang , Guo Chunxue , Yin Chengliang
Published: April 2022

Background

Regional lymph node metastasis is a contributor for poor prognosis in osteosarcoma. However, studies on risk factors for predicting regional lymph node metastasis in osteosarcoma are scarce. This study aimed to develop and validate a model based on machine learning (ML) algorithms.

Methods

A total of 1201 patients, with 1094 cases from the surveillance epidemiology and end results (SEER) (the training set) and 107 cases (the external validation set) admitted from four medical centers in China, was included in this study. Independent risk factors for the risk of lymph node metastasis were screened by the multifactorial logistic regression models. Six ML algorithms, including the logistic regression (LR), the gradient boosting machine (GBM), the extreme gradient boosting (XGBoost), the random forest (RF), the decision tree (DT), and the multilayer perceptron (MLP), were used to evaluate the risk of lymph node metastasis. The prediction model was developed based on the bestpredictive performance of ML algorithm and the performance of the model was evaluatedby the area under curve (AUC), prediction accuracy, sensitivity and specificity. A homemade online calculator was capable of estimating the probability of lymph node metastasis in individuals.

Results

Of all included patients, 9.41% (113/1201) patients developed regional lymph node metastasis. ML prediction models were developed based on nine variables: age, tumor (T) stage, metastasis (M) stage, laterality, surgery, radiation, chemotherapy, bone metastases, and lung metastases. In multivariate logistic regression analysis, T and M stage, surgery, and chemotherapy were significantly associated with lymph node metastasis. In the six ML algorithms, XGB had the highest AUC (0.882) and was utilized to develop as prediction model. A homemade online calculator was capable of estimating the probability of CLNM in individuals.

Conclusions

T and M stage, surgery and Chemotherapy are independent risk factors for predicting lymph node metastasis among osteosarcoma patients. XGB algorithm has the best predictive performance, and the online risk calculator can help clinicians to identify the risk probability of lymph node metastasis among osteosarcoma patients.
Identification of Cell Subpopulations and Interactive Signaling Pathways From a Single-Cell RNA Sequencing Dataset in Osteosarcoma: A Comprehensive Bioinformatics Analysis
Authors: Wu Rong , Dou Xiaojie , Li Haidong , Sun Zhenguo , Li Heng , Shen Yuxin , Weng Wei , Min Jikang
Published: April 2022

Osteosarcoma is a type of highly aggressive bone tumor arising from primitive cells of mesenchymal origin in adults and is associated with a high rate of tumor relapse. However, there is an urgent need to clarify the molecular mechanisms underlying osteosarcoma development. The present study performed integrated bioinformatics analysis in a single-cell RNA sequencing dataset and explored the potential interactive signaling pathways associated with osteosarcoma development. Single-cell transcriptomic analysis of osteosarcoma tissues was performed by using the Seurat R package, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes was performed by using the clusterProfiler R package, and the cell–cell interaction analysis was performed by using the CellPhoneDB package. Our results showed that 11 clustered cell types were identified across 11 osteosarcoma tissues, with cell types including “osteoblastic”, “myeloid”, “osteoblastic_proli”, “osteoclast”, and “tumor-infiltrating lymphocytes (TILs)” as the main types. The DEGs between different cell types from primary, metastatic, and recurrent osteosarcomas were mainly enriched in the GO terms including “negative regulation of hydrolase activity”, “regulation of peptidase activity”, “regulation of binding”, “negative regulation of proteolysis”, and “negative regulation of peptidase activity” and in the KEGG pathways including “transcriptional misregulation in cancer”, “cellular senescence”, “apoptosis”, “FoxO signaling pathway”, “cell cycle”, “NF-kappa B signaling pathway”, “p53 signaling pathway”, “pentose phosphate pathway”, and “protein export”. For the cell–cell communication network analysis, the different interaction profiles between cell types were detected among primary, metastatic, and recurrent osteosarcomas. Further exploration of the KEGG pathway revealed that these ligand/receptor interactions may be associated with the NF-κB signaling pathway and its interacted mediators. In conclusion, the present study for the first time explored the scRNA-seq dataset in osteosarcoma, and our results revealed the 11 clustered cell types and demonstrated the novel cell–cell interactions among different cell types in primary, metastatic, and recurrent osteosarcomas. The NF-κB signaling pathway may play a key role in regulating the TME of osteosarcoma. The present study may provide new insights into understanding the molecular mechanisms of osteosarcoma pathophysiology.
New Studies of the Aberrant Alterations in Fibrillin-1 Methylation During Colorectal Cancer Development
Authors: Lv Ling , Ma Jianzhong , Wu Lina , Zhang Chao , Wang Yueping , Wang Guang
Published: April 2022

Background

Fibrillin-1 (FBN1) methylation risk from control to colorectal cancer (CRC), the variation regularities of FBN1 methylation, and DNA methyltransferase (DNMT) catalyzed with FBN1 methylation had not been reported yet; these were all studied in this paper.

Methods

FBN1 methylation roles were investigated with big data and meta-analysis.

Results

The 6 independent studies were searched including 702 tissue and 448 feces. FBN1 methylation frequencies of CRC, adenoma or polyp, and control in tissue were 79.1%, 69.4%, and 2.7%, respectively; those in feces were 74.6%, 50.7%, and 10.8%, respectively. FBN1 methylation of control samples was used as a standard reference; this study showed that ORs (95% CI) of FBN1 methylation in CRC and control tissues were 124.79 (62.86–248.35); those in feces were detected to be 30.87 (16.48–57.85). FBN1 methylation risk in tissue was higher than that in feces; there was a quadratic equation between the methylation rate of tissue and that of feces. There was another quadratic curve in the variation process of FBN1 methylation; this curve reflected the overall metabolism regularity of DNMT.

Conclusions

The transcriptional inactivation of FBN1 gene might start from normal colonic epithelium; the quadratic curve of FBN1 methylation catalyzed by DNMT can gradually produce powerful strength, accelerate expansion, and eventually lead to CRC. The overall metabolism regularity of DNMT maintains the changing process of FBN1 methylation; it has the changing feature of the same quadratic curve. FBN1 methylation is a promising biomarker. FBN1 methylation risk size in feces reflects that in tissue in non-invasive detection.
Lipophilic Constituents in Salvia miltiorrhiza Inhibit Activation of the Hepatic Stellate Cells by Suppressing the JAK1/STAT3 Signaling Pathway: A Network Pharmacology Study and Experimental Validation
Authors: Tang Ya-Xin , Liu Mingming , Liu Long , Zhen Bo-Rui , Wang Tian-Tian , Li Na , Lv Nanning , Zhu Zhenyu , Sun Guoquan , Wang Xiaobo , Chen Si
Published: April 2022

Liver fibrosis is currently a global health challenge with no approved therapy, with the activation of hepatic stellate cells being a principal factor. Lipophilic constituents in Salvia miltiorrhiza (LS) have been reported to improve liver function and reduce the indicators of liver fibrosis for patients with chronic hepatitis B induced hepatic fibrosis. However, the pharmacological mechanisms of LS on liver fibrosis have not been clarified. In this study, 71 active compounds, 342 potential target proteins and 22 signaling pathways of LS were identified through a network pharmacology strategy. Through text mining and data analysis, the JAK1/STAT3 signaling pathway was representatively selected for further experimental validation. We firstly confirmed the protective effect of LS on liver fibrosis in vivo by animal experiments. Hepatic stellate cells, which proliferated and displayed a fibroblast-like morphology similar to activated primary stellate cells, were applied to evaluate its underlying mechanisms. The results showed that LS could inhibit the cell viability, promote the cell apoptosis, decrease the expression of liver fibrosis markers, and downregulate the JAK1/STAT3 signaling pathway. These results demonstrated that LS could exert anti-liver-fibrosis effects by inhibiting the activation of HSCs and regulating the JAK1/STAT3 signaling pathway, which is expected to benefit its clinical application.
Treatment Resistance in Severe Asthma Patients With a Combination of High Fraction of Exhaled Nitric Oxide and Low Blood Eosinophil Counts
Authors: Hoshino Yuki , Soma Tomoyuki , Uchida Yoshitaka , Shiko Yuki , Nakagome Kazuyuki , Nagata Makoto
Published: April 2022

Background: Combining a fraction of exhaled nitric oxide (FeNO) and blood eosinophil count (B-EOS) may be a useful strategy for administration of biologics such as anti-IgE or anti-IL-5 to patients with type 2 inflammatory-predominant severe asthma and is important to be elucidated considering the increasing use of biologics.

Methods: This cross-sectional study analyzed the clinical data from 114 adult patients with severe asthma, who were treated at Saitama Medical University Hospital. The eligible patients were stratified into four subgroups defined by thresholds of FeNO and blood eosinophil (B-EOS) counts to detect sputum eosinophilia, using the receiver operating characteristic curve analysis. A total of 75 patients with optimal samples were stratified into four subtypes defined by thresholds of sputum eosinophilia and neutrophilia. Clinical characteristics, pattern of biologics, and distribution of sputum subtypes were analyzed in the stratified subclasses according to the FeNO and B-EOS thresholds. The asthma exacerbation (AE)-free time of the FeNO/B-EOS subgroups and any biologics treatment including anti-IgE or anti-IL-5 use were examined using the Kaplan–Meier method. The hazard ratios (HRs) for AE-free time were examined using the Cox proportional hazard model.

Results: The optimal cutoff values for prediction of sputum eosinophilia were defined as ≥2.7% wherein for FeNO as ≥27 ppb and B-EOS as ≥265/µL were considered. The high-FeNO subgroups showed significant high total IgE, compared with the low FeNO. The high-FeNO/high-B-EOS and the high-FeNO/low-B-EOS subgroups showed the largest prevalence of mepolizumab and benralizumab use among the other FeNO/B-EOS, respectively. The high-FeNO/low-B-EOS showed the largest frequency of AEs, high HR, and the shortest AE-free time, among the other FeNO/B-EOS. The sputum eosinophil-predominant subtype was the great majority in the high FeNO/high B-EOS. A diverse distribution of sputum leukocyte-predominant subtype was observed in the other FeNO/B-EOS. The subsequent AE-free time and its HR were comparable among the biologics use groups.

Conclusion: The strategy of classifying severe asthma based on the combination of FeNO and B-EOS proposes particular refractory type 2 severe asthma and underlying airway inflammation as a feasible trait for optimal biologics use.
CXCR2 Small-Molecule Antagonist Combats Chemoresistance and Enhances Immunotherapy in Triple-Negative Breast Cancer
Authors: Ghallab Alaa M. , Eissa Reda A. , El Tayebi Hend M.
Published: April 2022

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer as the absence of cell surface receptors renders it more difficult to be therapeutically targeted. Chemokine receptor 2 (CXCR2) has been suggested not only to promote therapy resistance and suppress immunotherapy but it also to possess a positive cross-talk with the multifunctional cytokine transforming growth factor beta (TGF-β). Here, we showed that CXCR2 and TGF-β signaling were both upregulated in human TNBC biopsies. CXCR2 inhibition abrogated doxorubicin-mediated TGF-β upregulation in 3D in vitro TNBC coculture with PBMCs and eliminated drug resistance in TNBC mammospheres, suggesting a vital role for CXCR2 in TNBC doxorubicin-resistance via TGF-β signaling regulation. Moreover, CXCR2 inhibition improved the efficacy of the immunotherapeutic drug “atezolizumab” where the combined inhibition of CXCR2 and PDL1 in TNBC in vitro coculture showed an additive effect in cytotoxicity. Altogether, the current study suggests CXCR2 inhibitors as a promising approach to improve TNBC treatment if used in combination with chemotherapy and/or immunotherapy.
Activation of the PPARγ Prevents Ferroptosis-Induced Neuronal Loss in Response to Intracerebral Hemorrhage Through Synergistic Actions With the Nrf2
Authors: Duan Chenyang , Jiao Dian , Wang Hanbin , Wu Qiaoli , Men Weidong , Yan Hua , Li Chunhui
Published: April 2022

Intracerebral hemorrhage (ICH) is a subtype of stroke characterized by high mortality and disability rates. The long-term effects of ICH-induced intracranial hematoma on patients’ neurological function are unclear. Currently, an effective treatment that significantly reduces the rates of death and disability in patients with ICH is not available. Based on accumulating evidence, ferroptosis may be the leading factor contributing to the neurological impairment caused by ICH injury. Peroxisome proliferator-activated receptor γ (PPARγ) is a ligand-activated receptor in the nuclear hormone receptor family that synergistically interacts with the nuclear factor erythrocyte 2-related factor 2 (Nrf2) pathway to promote the expression of related genes and inhibit ferroptosis. Primary rat hippocampal neurons were treated with heme (50 μM) and erastin (50 μM) to induce ferroptosis, followed by the PPARγ agonist pioglitazone (PDZ, 10 μM) to verify the inhibitory effect of PPARγ activation on ferroptosis. ML385 (2 μM), a novel and specific NRF2 inhibitor, was administered to the inhibitor group, followed by an analysis of cellular activity and immunofluorescence staining. In vivo Assays, ICH rats injected with autologous striatum were treated with 30 mg/kg/d pioglitazone, and the inhibitor group was injected with ML385 (30 mg/kg). The results showed that PDZ inhibited ferroptosis in neurons by increasing the expression of PPARγ, Nrf2 and Gpx4 in vitro, while PDZ reduced ferroptosis in neurons after ICH and promoted the recovery of neural function in vivo. Our results suggest that PDZ, a PPARγ agonist, promotes Gpx4 expression through the interaction between PPARγ and the Nrf2 pathway, inhibits ferroptosis of neurons after ICH, and promotes the recovery of neural function.
Targeting Mutant Kirsten Rat Sarcoma Viral Oncogene Homolog in Non-Small Cell Lung Cancer: Current Difficulties, Integrative Treatments and Future Perspectives
Authors: Li Jia-Xin , Li Run-Ze , Ma Lin-Rui , Wang Peng , Xu Dong-Han , Huang Jie , Li Li-Qi , Tang Ling , Xie Ying , Leung Elaine Lai-Han , Yan Pei-Yu
Published: April 2022

In the past few decades, several gene mutations, including the anaplastic lymphoma kinase, epidermal growth factor receptor, ROS proto-oncogene 1 and rat sarcoma viral oncogene homolog (RAS), have been discovered in non-small cell lung cancer (NSCLC). Kirsten rat sarcoma viral oncogene homolog (KRAS) is the isoform most frequently altered in RAS-mutated NSCLC cases. Due to the structural and biochemical characteristics of the KRAS protein, effective approaches to treating KRAS-mutant NSCLC still remain elusive. Extensive recent research on KRAS-mutant inhibitors has made a breakthrough in identifying the covalent KRASG12C inhibitor as an effective agent for the treatment of NSCLC. This review mainly concentrated on introducing new covalent KRASG12C inhibitors like sotorasib (AMG 510) and adagrasib (MRTX 849); summarizing inhibitors targeting the KRAS-related upstream and downstream effectors in RAF/MEK/ERK pathway and PI3K/AKT/mTOR pathway; exploring the efficacy of immunotherapy and certain emerging immune-related therapeutics such as adoptive cell therapy and cancer vaccines. These inhibitors are being investigated in clinical trials and have exhibited promising effects. On the other hand, naturally extracted compounds, which have exhibited safe and effective properties in treating KRAS-mutant NSCLC through suppressing the MAPK and PI3K/AKT/mTOR signaling pathways, as well as through decreasing PD-L1 expression in preclinical studies, could be expected to enter into clinical studies. Finally, in order to confront the matter of drug resistance, the ongoing clinical trials in combination treatment strategies were summarized herein.
Association of TGF-β Canonical Signaling-Related Core Genes With Aortic Aneurysms and Aortic Dissections
Authors: Chen Jicheng , Chang Rong
Published: April 2022

Transforming growth factor-beta (TGF-β) signaling is essential for the maintenance of the normal structure and function of the aorta. It includes SMAD-dependent canonical pathways and noncanonical signaling pathways. Accumulated genetic evidence has shown that TGF-β canonical signaling-related genes have key roles in aortic aneurysms (AAs) and aortic dissections and many gene mutations have been identified in patients, such as those for transforming growth factor-beta receptor one TGFBR1, TGFBR2, SMAD2, SMAD3, SMAD4, and SMAD6. Aortic specimens from patients with these mutations often show paradoxically enhanced TGF-β signaling. Some hypotheses have been proposed and new AA models in mice have been constructed to reveal new mechanisms, but the role of TGF-β signaling in AAs is controversial. In this review, we focus mainly on the role of canonical signaling-related core genes in diseases of the aorta, as well as recent advances in gene-mutation detection, animal models, and in vitro studies.
Surfactant Treatment Shows Higher Correlation Between Ventilator and EIT Tidal Volumes in an RDS Animal Model
Authors: Kim Yoon Zi , Choi Hee Yoon , Choi Yong Sung , Kim Chae Young , Lee Young Joo , Chung Sung Hoon
Published: April 2022

Neonatal respiratory distress syndrome (RDS) is a condition of pulmonary surfactant insufficiency in the premature newborn. As such, artificial pulmonary surfactant administration is a key treatment. Despite continued improvement in the clinical outcomes of RDS, there are currently no established bedside tools to monitor whether pulmonary surfactant is effectively instilled throughout the lungs. Electrical impedance tomography (EIT) is an emerging technique in which physiological functions are monitored on the basis of temporal changes in conductivity of different tissues in the body. In this preliminary study, we aimed to assess how EIT tidal volumes correlate with ventilator tidal volumes in an RDS animal model, namely untreated, surfactant-treated, and normal control rabbit pups. Tidal volumes were measured simultaneously on an EIT system and a mechanical ventilator and compared at different peak inspiratory pressures. The linear correlation between tidal volumes measured by EIT and by ventilator had an R2 of 0.71, 0.76 and 0.86 in the untreated, surfactant-treated, and normal control groups, respectively. Bland–Altman analysis showed a good correlation between the measurements obtained with these two modalities. The intraclass correlation coefficients (ICC) between ventilator tidal volume and EIT tidal volume were 0.83, 0.87, and 0.93 (all p < 0.001) in the untreated, surfactant-treated, and normal control groups, respectively, indicating that the higher ICC value, the better inflated status of the lung. In conclusion, we demonstrated that EIT tidal volume correlated with ventilator tidal volume. ICC was higher in the surfactant treated group.
Improvement of Sympathovagal Balance by Regular Exercise May Counteract the Ageing Process. A Study by the Analysis of QT Variability
Authors: De Maria Beatrice , Lucini Daniela , Gois Mariana de Oliveira , Catai Aparecida Maria , Perego Francesca , Malacarne Mara , Pagani Massimo , Porta Alberto , Dalla Vecchia Laura Adelaide
Published: April 2022

QT interval (QT) variability analysis provides pathophysiological and prognostic information utilized in cardiac and non-cardiac diseases, complementary to those obtained from the analysis of heart period (HP) variability. An increased QT variability has been associated to a higher risk for cardiac events and poorest prognosis. Autonomic cardiovascular adaptation to internal and external challenges, such those occurring in athletes exposed to high levels of physical stress and in ageing could also be deepen by analyzing QT variability, searching for early prognostic signatures. The aim of the study was to analyze the QT variability and cardiac control complexity in a group of middle-aged half-marathon runners at baseline (B) and at a 10-year follow-up (FU). We found that the overall QT variability decreased at FU, despite the inescapable increase in age (52.3 ± 8.0 years at FU). This change was accompanied by an increase of the HP variability complexity without changes of the QT variability complexity. Of notice, over the years, the group of athletes maintained their regular physical activity by switching to a moderate intensity rather than strenuous. In conclusion, regular and moderate exercise over the years was beneficial for this group of athletes, as reflected by the decreased overall QT variability that is known to be associated to lower cardiovascular risk. The concomitant enhanced cardiac control complexity also suggests a trend opposite to what usually occurs with ageing, resulting in a more flexible cardiac control, typical of younger people.
Shared Multimodal Input Through Social Coordination: Infants With Monolingual and Bilingual Learning Experiences
Authors: Sun Lichao , Griep Christina D. , Yoshida Hanako
Published: April 2022

A growing number of children in the United States are exposed to multiple languages at home from birth. However, relatively little is known about the early process of word learning—how words are mapped to the referent in their child-centered learning experiences. The present study defined parental input operationally as the integrated and multimodal learning experiences as an infant engages with his/her parent in an interactive play session with objects. By using a head-mounted eye tracking device, we recorded visual scenes from the infant’s point of view, along with the parent’s social input with respect to gaze, labeling, and actions of object handling. Fifty-one infants and toddlers (aged 6–18 months) from an English monolingual or a diverse bilingual household were recruited to observe the early multimodal learning experiences in an object play session. Despite that monolingual parents spoke more and labeled more frequently relative to bilingual parents, infants from both language groups benefit from a comparable amount of socially coordinated experiences where parents name the object while the object is looked at by the infant. Also, a sequential path analysis reveals multiple social coordinated pathways that facilitate infant object looking. Specifically, young children’s attention to the referent objects is directly influenced by parent’s object handling. These findings point to the new approach to early language input and how multimodal learning experiences are coordinated socially for young children growing up with monolingual and bilingual learning contexts.
Organizational Emotional Capability Perspective: Research on the Impact of Psychological Capital on Enterprise Safety Performance
Authors: Peng Cheng , Xue Ke , Tian Yue , Zhang Xuezhou , Jing Xi , Luo Haolun
Published: April 2022

Theoretical researchers of manager psychology have excellent potential to extend its research framework to more enterprise application areas, such as innovation, performance, and safety in production. Research in these areas has also been increasing in the past 10 years. Psychological capital is composed of four aspects: self-efficacy, hope, optimism, and tenacity. It plays an essential role in stimulating organizational growth and improving organizational performance. In safety management work, managers, as the core members of the organization, have a relationship between their psychological capital and employees’ safety performance. Nevertheless, the closeness of the relationship between psychological capital and employee safety performance has not been fully demonstrated by academic circles. Based on positive psychology theory, this paper conducts a questionnaire survey of 157 managers and 314 employees related to safety work in manufacturing enterprises. From the new perspective of organizational emotional capability, this paper investigates the complex and extensive social-psychological role in organizations and combs, analyzes, and integrates relevant psychological research to construct the influence mechanism of managers’ psychological capital and employee safety performance. Finally, the three important issues found based on data analysis were: (1) Managers’ psychological capital has a significant positive impact both on employee safety performance and organizational emotional capability; (2) Organizational emotional capability has a significant positive impact on employee safety performance; (3) organizational emotional capability plays a partial mediating role in the relationship between managers’ psychological capital and employee safety performance.
Comparison of Students' Mental Wellbeing, Anxiety, Depression, and Quality of Life During COVID-19's Full and Partial (Smart) Lockdowns: A Follow-Up Study at a 5-Month Interval
Authors: Aqeel Muhammad , Rehna Tasnim , Shuja Kanwar Hamza , Abbas Jaffar
Published: April 2022

Objective

Scholars have debated the COVID-19's full and partial lockdowns' effectivity to control the transmission of the new case. They emphasized the provision of required economic and social resources worldwide. Past literature related to COVID-19 has contributed little evidence to examine the efficacy of full and partial lockdown measures with experimental perspectives at different intervals. This study bridges this literature gap and explores the full and smart lockdowns' impacts on Pakistani students' mental health, depression, quality of life, and anxiety symptoms, during the various waves of the COVID-19 pandemic.

Method

This pretest and posttest experimental designed web-based survey recruited 40 students from March 23 to August 23, 2020, and recorded their responses. The study incorporated four standardized psychological instruments to receive the desired datasets related to students' mental health, quality of life, anxiety, and depression. Researchers shared data links with the participants via social media, WhatsApp. The study applied one-way and multivariate ANOVA tests (analysis of variance) to draw the desired results.

Results

This study's findings suggest that both full and partial COVID-19 lockdowns effectively improve students' mental health and quality of life. These measures help reduce anxiety and depressive symptoms among university students. The study results exhibit that partial lockdown (PL) is more effective in improving quality of life. Besides, PL helps reduce anxiety symptoms than complete lockdown among Pakistani students.

Conclusion

The present study's findings suggest that students are vulnerable. They need particular interventions and preventive measures to protect and improve their mental health and quality of life during a global pandemic. As the stressful experience of the epidemic persists in Pakistan. It will also be interesting to examine the psychological impact of the successive waves of the COVID-19 pandemic.
Does Deep Learning-Based Super-Resolution Help Humans With Face Recognition?
Authors: Velan Erik , Fontani Marco , Carrato Sergio , Jerian Martino
Published: April 2022

The last decade witnessed a renaissance of machine learning for image processing. Super-resolution (SR) is one of the areas where deep learning techniques have achieved impressive results, with a specific focus on the SR of facial images. Examining and comparing facial images is one of the critical activities in forensic video analysis; a compelling question is thus whether recent SR techniques could help face recognition (FR) made by a human operator, especially in the challenging scenario where very low resolution images are available, which is typical of surveillance recordings. This paper addresses such a question through a simple yet insightful experiment: we used two state-of-the-art deep learning-based SR algorithms to enhance some very low-resolution faces of 30 worldwide celebrities. We then asked a heterogeneous group of more than 130 individuals to recognize them and compared the recognition accuracy against the one achieved by presenting a simple bicubic-interpolated version of the same faces. Results are somehow surprising: despite an undisputed general superiority of SR-enhanced images in terms of visual appearance, SR techniques brought no considerable advantage in overall recognition accuracy.