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Kaidi Zhao,1,* Yang Zhao,2,* Ao Guo,1 Shengxiang Xiao,1 Chen Tu1 1Department of Dermatology, Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, 710004, People’s Republic of China; 2National & Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, 710004, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chen Tu; Shengxiang Xiao, Email tuchen2023@126.com; xiao_sx@163.comBackground: Psoriasis is a chronic inflammatory skin disease, and its etiology is still unclear. There is increasing evidence suggesting that microorganisms may trigger psoriasis. However, the relationship between psoriasis and oral microbiota remains poorly understood. Our aim is to identify differences in the composition and diversity of the oral microbiota between patients with psoriasis and healthy controls, and to discover oral microbial markers for assessing the severity of psoriasis.Methods: This study recruited 20 psoriasis patients and 20 healthy individuals, collecting their saliva to analyze the composition of the oral microbiota in psoriasis patients. We employed 16S rRNA sequencing technology and utilized various methods for oral microbiome analysis, including the Shannon Index, Gini-Simpson Index, Principal Coordinates Analysis (PCoA), non-metric multidimensional scaling (NMDS), Linear discriminant analysis Effect Size (LEfSe), Wilcoxon test, and Spearman’s rank correlation.Results: The results showed that the alpha diversity of oral microbiota was higher in psoriasis patients. The relative abundances of certain bacterial taxa differed between psoriasis and healthy individuals, including Prevotella, Prevotella 7 and Porphyromonas gingivalis, which are increased in psoriasis. We also found a positive correlation between Alloprevotella, Porphyromonas, and Neisseria with the severity of psoriasis, while Veillonella showed a negative correlation.Conclusion: In summary, this study found significant changes in the composition of the oral microbiota in patients with psoriasis. Some oral bacteria are associated with psoriasis severity. It provides a new perspective on the relationship between the oral microbiota and psoriasis.Keywords: psoriasis, oral microbiota, dysbiosis, comorbidity, 16s rRNA

Fangyuan Kuang,1,2 Yang Gao,3 Qingyun Zhou,4 Chenying Lu,3 Qiaomei Lin,4 Abdullah Al Mamun,5 Junle Pan,6 Shuibo Shi,7 Chaoyong Tu,4,* Chuxiao Shao2,* 1School of Medicine, Shaoxing University, Shaoxing, Zhejiang, 312000, People’s Republic of China; 2Department of Hepatopancreatobiliary Surgery, People Hospital of Lishui, The Sixth Affiliated Hospital of Wenzhou Medical University, The First Affiliated Hospital of Lishui University, Lishui, Zhejiang, 323000, People’s Republic of China; 3Department of Radiology, the Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, 323000, People’s Republic of China; 4Department of Hepatopancreatobiliary Surgery, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, 323000, People’s Republic of China; 5Key Laboratory of Joint Diagnosis and Treatment of Chronic Liver Disease and Liver Cancer of Lishui, The Sixth Affiliated Hospital of Wenzhou Medical University, Lishui People’s Hospital, Lishui, Zhejiang, 323000, People’s Republic of China; 6First Academy of Clinical Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, 325000, People’s Republic of China; 7The First Clinical Medical College of Nanchang University, Nanchang City, Jiangxi, 330000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chaoyong Tu, Department of Hepatopancreatobiliary Surgery, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui, Zhejiang, 323000, People’s Republic of China, Email tcy7409@163.comBackground: A limited number of studies have examined the use of radiomics to predict 3-year overall survival (OS) after hepatectomy in patients with hepatocellular carcinoma (HCC). This study develops 3-year OS prediction models for HCC patients after liver resection using MRI radiomics and clinicopathological factors.Materials and Methods: A retrospective analysis of 141 patients who underwent surgical resection of HCC was performed. Patients were randomized into two set: the training set (n=98) and the validation set (n=43) including the survival groups (n=111) and non-survival groups (n=30) based on 3-year survival after hepatectomy. Furthermore, x2 or Fisher’s exact test, univariate and multivariate logistic regression analyses were conducted to determine independent clinicopathological risk factors associated with 3-year OS. 1688 quantitative imaging features were extracted from preoperative T2-weighted imaging (T2WI) and contrast-enhanced magnetic resonance imaging (CE-MRI) of arterial phase (AP), portal venous phases (PVP)and delay period (DP). The features were selected using the variance threshold method, the select K best method and the least absolute shrinkage and selection operator (LASSO) algorithm. By using Bernoulli Naive Bayes (BernoulliNB) and Multinomial Naive Bayes (MultinomialNB) classifiers, we constructed models based on the independent clinicopathological factors and Rad-scores. To determine the best model, receiver operating characteristics (ROC) and Delong’s test were used. Moreover, calibration curves were used to determine the calibration ability of the model, while decision curve analysis (DCA) was implemented to evaluate its clinical benefit.Results: The fusion model showed excellent prediction precision with AUC of 0.910 and 0.846 in training and validation set and revealed significant diagnostic accuracy and value in the calibration curve and DCA analysis.Conclusion: Nomograms based on MRI radiomics and clinicopathological factors have significant predictive value for 3-year OS after hepatectomy and can be used for risk classification.Keywords: hepatocellular carcinoma, hepatectomy, MRI radiomics

Abstract Metal-Organic frameworks (MOFs) have been considered for various gas storage and separation applications. Theoretically, there are an infinite number of MOFs that can be created; however, a finite amount of resources are available to evaluate each one. Computational methods can be adapted to expedite the process of evaluation. In the context of CO2 capture, this paper investigates the method of screening MOFs using machine learning trained on molecular simulation data. New descriptors are introduced to aid this process. Using all descriptors, it is shown that machine learning can predict the CO2 adsorption, with an R2 of above 0.9. The introduced Effective Point Charge (EPoCh) descriptors, which assign values to frameworks’ partial charges based on the expected CO2 uptake of an equivalent point charge in isolation, are shown to be the second most important group of descriptors, behind the Henry coefficient. Furthermore, the EPoCh descriptors are hundreds of thousands of times faster to obtain compared with the Henry coefficient, and they achieve similar results when identifying top candidates for CO2 capture using pseudo-classification predictions.

Rong Liu,1,* Min Zhu,2,* Jiaojiao Chen,3 Junwei Gai,2 Jing Huang,2 Yingqun Zhou,1 Yakun Wan,2 Chuantao Tu4 1Department of Gastroenterology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, 200072, People’s Republic of China; 2Shanghai Novamab Biopharmaceuticals Co., Ltd, Shanghai, 201318, People’s Republic of China; 3Department of Gastroenterology, Shanghai Fourth People’s Hospital, Tongji University School of Medicine, Shanghai, 200434, People’s Republic of China; 4Department of Gastroenterology, Shanghai Public Health Clinical Center, Fudan University, Shanghai, 201508, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chuantao Tu; Yakun Wan, Email tuchuantao@hotmail.com; ykwan@novamab.comBackground: No agents are currently available for the treatment or reversal of liver fibrosis. Novel antifibrotic therapies for chronic liver diseases are thus urgently needed. Connective tissue growth factor (CTGF) has been shown to contributes profoundly to liver fibrogenesis, which makes CTGF as a promising target for developing antifibrotic agents.Methods: In this study, we identified a novel nanobody (Nb) against human CTGF (anti-CTGF Nb) by phage display using an immunized camel, which showed high affinity and specificity in vitro. LX-2 cells, the immortalized human hepatic stellate cells, were induced by transforming growth factor beta1 (TGFβ 1) as an in vitro model of liver fibrosis to verify the antifibrotic activity of the anti-CTGF Nb.Results: Our data demonstrated that anti-CTGF Nb effectively alleviated TGFβ 1-induced LX-2 cell proliferation, activation, and migration, and promoted the apoptosis of activated LX-2 cells in response to TGFβ 1. Moreover, the anti-CTGF Nb remarkably reduced the levels of TGFβ 1, Smad2, and Smad3 expression in LX-2 stellate cells stimulated by TGFβ 1.Conclusion: Taken together, we successfully identified a novel Nb against human CTGF, which exhibited antifibrotic effects in vitro by regulating the biological functions of human stellate cells LX-2.Graphical Abstract: Keywords: nanobody, connective tissue growth factor, liver fibrosis, hepatic stellate cells

Abstract Zein, which accounts for around 80% of the total protein composition in corn, is a biocompatible and biodegradable substance derived from renewable sources. Although insoluble in water, its amphiphilic characteristics are utilized to generate nanoparticles, nanofibers, microparticles, and even films. Numerous recent studies have demonstrated the potential of zein as a prospective biomaterial to develop fibrous scaffolds for biomedical functions owing to its biocompatibility, fibrous formation, and encapsulating qualities. Fabrication of zein‐based fibrous scaffolds for biomedical applications is achieved by a wide variety of techniques, including electrospinning, wet spinning, freeze drying, and additive manufacturing. This article overviews current advancements in manufacturing techniques for zein‐based fibrous scaffolds. In addition, it summarizes the most recent biomedical applications and research activities utilizing zein‐based fibrous scaffolds. Overall, zein is proposed as a potential biomaterial for the production of fibrous scaffolds that stimulate cell adhesion and proliferation in a number of exciting biomedical applications due to its biodegradability, biocompatibility, and other unique features related to its structure.

Lan Wei,1 Yuanyuan Han,2 Chao Tu1 1Department of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, People’s Republic of China; 2Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Yunnan Key Laboratory of Vaccine Research and Development on Severe Infectious Diseases, Kunming, People’s Republic of ChinaCorrespondence: Chao Tu, Department of Internal Medicine, The Third Affiliated Hospital of Soochow University, 185 Juqian Road, Changzhou, 213000, People’s Republic of China, Email tcmedical21@czfph.comAbstract: Diabetic kidney disease (DKD) affects an estimated 20– 40% of type 2 diabetes patients and is among the most prevalent microvascular complications in this patient population, contributing to high morbidity and mortality rates. Currently, changes in albuminuria status are thought to be a primary indicator of the onset or progression of DKD, yet progressive nephropathy and renal impairment can occur in certain diabetic individuals who exhibit normal urinary albumin levels, emphasizing the lack of sensitivity and specificity associated with the use of albuminuria as a biomarker for detecting diabetic kidney disease and predicting DKD risk. According to the study, a non-invasive method for early detection or prediction of DKD may involve combining proteomic analytical techniques such second generation sequencing, mass spectrometry, two-dimensional gel electrophoresis, and other advanced system biology algorithms. Another category of proteins of relevance may now be provided by renal tissue biomarkers. The establishment of reliable proteomic biomarkers of DKD represents a novel approach to improving the diagnosis, prognostic evaluation, and treatment of affected patients. In the present review, a series of protein biomarkers that have been characterized to date are discussed, offering a theoretical foundation for future efforts to aid patients suffering from this debilitating microvascular complication.Keywords: diabetic kidney disease, proteomics, diagnostic biomarkers, therapeutic targets

Qi You,1,2,* Minxun Lu,1,2,* Zhuangzhuang Li,1,2 Yong Zhou,1,2 Chongqi Tu1,2 1Orthopedic Research Institute, Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, Sichuan Province, People’s Republic of China; 2Sichuan Model Worker and Craftsman Talent Innovation Research Studio, Chengdu, Sichuan Province, People’s Republic of China*These authors contributed equally to this workCorrespondence: Chongqi Tu; Yong Zhou, Department of Orthopedics, West China Hospital, Sichuan University, No. 37, Guoxuexiang, Chengdu, 610041, Sichuan Province, People’s Republic of China, Email Tucq@scu.edu.cn; zhouyonggk@163.comAbstract: Bone defects that are congenital or the result of infection, malignancy, or trauma represent a challenge to the global healthcare system. To address this issue, multiple research groups have been developing novel cell sheet technology (CST)-based approaches to promote bone regeneration. These methods hold promise for use in regenerative medicine because they preserve cell-cell contacts, cell-extracellular matrix interactions, and the protein makeup of cell membranes. This review introduces the concept and preparation system of the cell sheet (CS), explores the application of CST in bone regeneration, highlights the current states of the bone regeneration via CST, and offers perspectives on the challenges and future research direction of translating current knowledge from the lab to the clinic.Keywords: bone defect, cell sheet technology, bone regeneration, bone tissue engineering

Light-matter interaction can induce changes to the properties of the system by creating hybrid collective states of light and molecular excitations, the so called polaritons. Here the authors use femtosecond pump-probe spectroscopy to explore exciton-polariton dynamics in a photosynthetic protein, light harvesting 2 complexes, and find evidence for rapid energy transfer to dark polariton states.

Rongxin Zhang,1,2 Zhao Hou,2 Kexin Liao,2 Chao Yu,2 Rongrong Jing,1,2 Caixia Tu1,2 1Institute of Integrative Medicine, Dalian Medical University, Dalian, 116044, People’s Republic of China; 2Department of Dermatology, The Second Hospital of Dalian Medical University, Dalian, 116027, People’s Republic of ChinaCorrespondence: Caixia Tu, Department of Dermatology, The Second Hospital of Dalian Medical University, No. 467 Zhongshan Road, Dalian, 116027, People’s Republic of China, Tel +8617709872288, Fax +86 411 84672130, Email tucx2010@sina.comPurpose: Circular RNAs (circRNAs) are abundant, stable, and evolutionarily conserved noncoding RNAs with impacts on cell proliferation, differentiation, invasion, apoptosis, and immunity by acting as an miRNA sponge. This study aimed to investigate the expression of circRNAs in vitiligo and analyze the differentially expressed circRNAs (DEcircRNAs) bioinformatically.Patients and Methods: Biopsies of five lesional and five nonlesional skins of patients with vitiligo and five healthy skins (control) were harvested in this study. The expression profiles of circRNAs and DEcircRNAs were determined by microarray analysis and qRT-PCR. Bioinformatics analysis was used to predict target genes of DEcircRNAs binding to miRNAs and their underlying functions. Meanwhile, a competing endogenous RNA (ceRNA) network was constructed using Cytoscape.Results: A total of 817 and 508 DEcircRNAs were identified in lesional and nonlesional skins of patients with vitiligo, respectively. The results of hsa_circRNA_000957 and hsa_circRNA_101798 validation were consistent with our microarray analysis. Furthermore, 32 miRNA response elements (MREs) and related target genes of DEcircRNAs were identified, whose main functions were involved in the pathogenesis of vitiligo. Hsa_circRNA_000957 and hsa_circRNA_101798 might be candidate biomarkers for vitiligo.Conclusion: This study provides scientific clues for understanding the mechanism of vitiligo.Keywords: vitiligo, circular RNAs, microRNAs, miRNA response element, ceRNA

Hongfeng Wu,1,2 Shuo Liu,1,2 Siyu Chen,1,2 Yuchen Hua,1,2 Xiangfeng Li,1,2 Qin Zeng,1– 3 Yong Zhou,4 Xiao Yang,1,2 Xiangdong Zhu,1,2 Chongqi Tu,4 Xingdong Zhang1– 3 1National Engineering Research Center for Biomaterials, Sichuan University, Chengdu, 610064, People’s Republic of China; 2College of Biomedical Engineering, Sichuan University, Chengdu, 610064, People’s Republic of China; 3NMPA Key Laboratory for Quality Research and Control of Tissue Regenerative Biomaterials & Institute of Regulatory Science for Medical Devices & NMPA Research Base of Regulatory Science for Medical Devices, Sichuan University, Chengdu, 610064, People’s Republic of China; 4Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of ChinaCorrespondence: Qin Zeng; Xiangdong Zhu, National Engineering Research Center for Biomaterials, Sichuan University, NO. 29 Wangjiang Road, Chengdu, 610064, People’s Republic of China, Email qzeng8156@scu.edu.cn; zhu_xd1973@scu.edu.cnBackground: In recent years, using hydroxyapatite nanoparticles (HANPs) for tumor therapy attracted increasing attention because HANPs were found to selectively suppress the growth of tumor cells but exhibit ignorable toxicity to normal cells.Purpose: This study aimed to investigate the capacities of HANPs with different morphologies and particle sizes against two kinds of osteosarcoma (OS) cells, human OS 143B cells and rat OS UMR106 cells.Methods: Six kinds of HANPs with different morphologies and particle sizes were prepared by wet chemical method. Then, the antitumor effect of these nanoparticles was characterized by means of in vitro cell experiments and in vivo tumor-bearing mice model. The underlying antitumor mechanism involving mitochondrial apoptosis was also investigated by analysis of intracellular calcium, expression of apoptosis-related genes, reactive oxygen species (ROS), and the endocytosis efficiency of the particles in tumor cells.Results: Both in vitro cell experiments and in vivo mice model evaluation revealed the anti-OS performance of HANPs depended on the concentration, morphology, and particle size of the nanoparticles, as well as the OS cell lines. Among the six HANPs, rod-like HANPs (R-HANPs) showed the best inhibitory activity on 143B cells, while needle-like HANPs (N-HANPs) inhibited the growth of UMR106 cells most efficiently. We further demonstrated that HANPs induced mitochondrial apoptosis by selectively raising intracellular Ca2+ and the gene expression levels of mitochondrial apoptosis-related molecules, and depolarizing mitochondrial membrane potential in tumor cells but not in MC3T3-E1, a mouse pre-osteoblast line. Additionally, the anti-OS activity of HANPs also linked with the endocytosis efficiency of the particles in the tumor cells, and their ability to drive oxidative damage and immunogenic cell death (ICD).Conclusion: The current study provides an effective strategy for OS therapy where the effectiveness was associated with the particle morphology and cell line.Keywords: hydroxyapatite nanoparticles, osteosarcoma, material features, cell line, mitochondrial apoptosis

Chao Tu, Liangzhi Wang, Lan Wei Department of Internal Medicine, the Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213000, People’s Republic of ChinaCorrespondence: Lan Wei, Department of Internal Medicine, the Third Affiliated Hospital of Soochow University, 185 Juqian Road, Changzhou, Jiangsu, 213000, People’s Republic of China, Tel +86 0519 68871132, Email weilan06082021@163.comAbstract: Diabetic microangiopathy is among the most common complications affecting patients with diabetes, and includes both diabetic retinopathy (DR) and diabetic nephropathy (DKD). Diabetic microangiopathy remains a persistent threat to the health and quality of life of affected patients. Mechanistically, the severity of DR and DKD is tied to mitochondrial and glucose metabolism abnormalities, with the activation of the glycolytic enzyme pyruvate kinase M2 (PKM2) contributing to mitochondrial and glomerular dysfunction, abnormal renal hemodynamics, and retinopathy. PKM2 can activate inflammatory bodies in macrophages to promote the release of inflammatory mediators, and serves as a key regulator of inflammatory factors, chemokines and adhesion molecules. As such, there is sufficient evidence that PKM2 can be used as a biomarker for the diagnosis of diabetes and diabetic microangiopathy. Here, we survey the mechanisms whereby PKM2 contributes to diabetes-related microvascular diseases, associated regulatory roles, post-translational modifications, and the potential utility of PKM2 as a therapeutic target. Through this literature review, we have determined that PKM2 offers promise as both a diagnostic marker and therapeutic target with direct relevance to research pertaining to diabetic microangiopathy.Keywords: pyruvate kinase M2, inflammation, diabetic retinopathy, diabetic nephropathy, diabetic microangiopathy

Chao Tu,1 Lan Wei,1 Liangzhi Wang,1 Ying Tang2 1Department of Internal Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, People’s Republic of China; 2Department of Rehabilitation Medicine, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213000, People’s Republic of ChinaCorrespondence: Ying Tang, Department of Rehabilitation Medicine, The Third Affiliated Hospital of Soochow University, 185 Juqian Road, Changzhou, Jiangsu, 213000, People’s Republic of China, Tel +86 0519 68872146, Email tyczfph@yeah.netBackground: Diabetic nephropathy (DN) is the common cause of renal diseases such as end-stage renal disease (ESRD) and chronic kidney disease (CKD). Various diagnostic applications and treatment methods are used for clinical but remain some prognosis issues. To avoid morbidity and mortality related to DN, early detection of disease complications as well as targeted therapeutic strategies is essential. Considerable evidence indicates that non-coding RNA plays a vital role in the biological processes of various diseases, used as biomarkers and therapeutic targets. And the most known ncRNAs are the microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs).Materials and Methods: Our study aimed to identify potential prognostic ncRNAs involved in DN by bioinformatics analysis and validated expression levels through quantitative polymerase chain reaction (qPCR) and GEO database. Our research focuses on differential expression miRNAs (DEmiRNAs) in DN and their interactions with critical genes.Results: We identified 8 up-regulated DEmiRNAs, including miR-103a-2-5p, miR-297, miR-548x-3p, miR-604, miR-644a, miR-1256, miR-3911 and miR-5047 finally. We further validated these miRNAs in a murine model.Conclusion: Identifying these up-regulated genes and elucidating these miRNAs regulatory network will contribute to a better understanding of the molecular mechanism of DN and how they can be used as new biomarkers and potential therapeutic targets for DN.Graphical Abstract: Keywords: diabetic nephropathy, microRNAs, bioinformatics, biomarkers

Lu Wan,1,2 Wenchao Zhang,1,2 Zhongyue Liu,1,2 Zhimin Yang,1,2 Chao Tu,1,2 Zhihong Li1,2 1Key Laboratory of Tumor Models and Individualized Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Orthopedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of ChinaCorrespondence: Chao Tu; Zhihong Li, Tel +86 15974290117; +86 13975112458, Email tuchao@csu.edu.cn; lizhihong@csu.edu.cnPurpose: Metabolic reprogramming, as one of the hallmarks of cancer, shows promising translational potential for cancer diagnosis, treatment and prognostic prediction. This study aims to construct and validate a prognostic prediction model for osteosarcoma based on glutamine metabolism-related genes.Materials and Methods: A group of glutamine metabolism-related genes was identified from a public database and intersected with a list of osteosarcoma survival-related genes, and a risk score model based on sixteen glutamine metabolism-related genes was developed by using LASSO penalized Cox regression analysis.Results: The prognosis of patients in the high-risk group was significantly worse than that of patients in the low-risk group in the training dataset (high- vs low-risk, 5-year overall survival: 11% vs 88%, p < 0.0001) and in two other external validation cohorts (high- vs low-risk, 5-year overall survival: 39% vs 81%, p = 0.015; 50% vs 94%, p = 0.011).In addition, a novel nomogram was constructed by integrating the risk score and clinical characteristics, including age, sex, metastasis status and chemotherapy response. This nomogram had superior predictive power compared with a nomogram composed of only conventional factors. Gene set enrichment analysis indicated that several well-known malignancy-associated gene sets, including MYC targets V1, DNA repair, and unfolded protein response, were enriched in the high-risk subgroup.Conclusion: A novel glutamine metabolism-related prognostic prediction model and nomogram for osteosarcoma was developed and validated in the present study, which could predict the survival of patients with osteosarcoma and may facilitate individualized clinical decision-making for patients.Keywords: bone tumor, survivorship, amino acid metabolism, nomogram

The present work aimed to develop a type of bread rich in dietary fibre (DF), and to investigate the effects of different amounts of steam-exploded apple pomace (AP) on the physicochemical properties of wheat flour and bread quality. The content of soluble dietary fibre (SDF) in apple pomace treated with steam explosion (SE-AP) increased, which could improve the quality of flour products and supplement dietary fibre. Adding 12% apple pomace powder resulted in maximum solubility (10.23 ± 0.25%) and swelling power (3.97 ± 0.14%). The relative viscosity of the mixed powder decreased with increasing SE-AP content. Moreover, the coagulation value of the mixed powder increased with the increase in SE-AP content. Based on the textural characteristics and sensory evaluation analysis of the bread, the quality of bread made with mixed powder was the best when 10% SE-AP was added to high-gluten flour. SE-AP can be utilised to produce bread rich in DF. The addition of 10% SE-AP resulted in the highest overall acceptance. [ABSTRACT FROM AUTHOR]

Yingjian Liang, Xiaobin Zheng, Meizhu Chen, Changli Tu, Cuiyan Tan, Yiying Huang, Zhenguo Wang, Jian Wu, Jing Liu Department of Pulmonary and Critical Care Medicine (PCCM), The Fifth Affiliated Hospital of Sun Yat-sen University, Zhuhai, People’s Republic of ChinaCorrespondence: Jing Liu; Xiaobin ZhengDepartment of Pulmonary and Critical Care Medicine (PCCM), The Fifth Affiliated Hospital of Sun Yat-sen University, 52 East Meihua Road, Zhuhai City, 519000, People’s Republic of ChinaTel/Fax +867562528733Email liujing25@mail.sysu.edu.cn; zhxbin@mail.sysu.edu.cnPurpose: The main objective of this study was to decipher the general epidemiology, clinical characteristic, laboratory finding and chest computed tomography (CT) imaging features of the novel coronavirus disease (COVID-19) patients whose initial detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)is negative.Methods: Nearly 100 confirmed cases admitted to The Fifth Affiliated Hospital of Sun Yat-sen University from 18th January to 26th February, 2020, were screened. Clinical records, laboratory results and CT images were reviewed for nine COVID-19 patients with initially negative RT-PCR detection.Results: Fever and cough were common, and one patient merely present gastrointestinal symptoms. Increasing CRP and decreasing ALB were showed in nearly half of the patients among negative detection and return to normal level after real time polymerase chain reaction (RT-PCR) results converted from positive to negative. Left lower lobe was affected nearly in all the patients. A patient received oxygen support timely according his high Mulbsta score.Conclusion: Our study elucidated on the clinical features of hospitalized patients with initially negative detection of SARS-CoV nucleic acid. Patient merely with symptoms associated with digestive system should be screened for COVID-19. CT scan and repeated RT-PCR are two powerful diagnostic tools. Mulbsta score assessing in the early stage enhances the confidence of severity evaluation in physician.Keywords: COVID-19, negative detection, clinical characteristic, laboratory finding, CT images features

Abstract Addressing climate change challenges by reducing greenhouse gas levels requires innovative adsorbent materials for clean energy applications. Recent progress in machine learning has stimulated technological breakthroughs in the discovery, design, and deployment of materials with potential for high‐performance and low‐cost clean energy applications. This review summarizes basic machine learning methods—data collection, featurization, model generation, and model evaluation—and reviews their use in the development of robust adsorbent materials. Key case studies are provided where these methods are used to accelerate adsorbent materials design and discovery, optimize synthesis conditions, and understand complex feature–property relationships. The review provides a concise resource for researchers wishing to use machine learning methods to rapidly develop effective adsorbent materials with a positive impact on the environment.