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One of the most widely used measures of scientific impact is the number of citations. However, due to its heavy-tailed distribution, citations are fundamentally difficult to predict but can be improved. This study was aimed at investigating the factors and parts influencing the citation number of a scientific paper in the otology field. Therefore, this work proposes a new solution that utilizes machine learning and natural language processing to process English text and provides a paper citation as the predicted results. Different algorithms are implemented in this solution, such as linear regression, boosted decision tree, decision forest, and neural networks. The application of neural network regression revealed that papers' abstracts have more influence on the citation numbers of otological articles. This new solution has been developed in visual programming using Microsoft Azure machine learning at the back end and Programming Without Coding Technology at the front end. We recommend using machine learning models to improve the abstracts of research articles to get more citations. [ABSTRACT FROM AUTHOR]

Objectives. To evaluate the usefulness of a novel acoustic uroflowmetry- (UFM-) based mobile application (app) voiding diary (VD) focusing on the (1) compliance and (2) correlation with a conventional paper-based VD. Materials and Methods. A total of 78 patients were included between December 2019 and June 2020, and a subsequent review of all data was performed. The analyzed data were as follows: (1) survey of convenience/satisfaction/preference comparing the two methods, (2) compliance regarding the completeness of both methods, and (3) correlation of each metric (24-hour urine volume, nocturnal urine volume, nocturnal polyuria index, total number of voids, number of daytime voids, number of nocturnal voids, and maximal bladder capacity) between the two methods. Results. The survey results of convenience, satisfaction, and preference were as follows. With regard to convenience and satisfaction area, higher scores are reported in the mobile app VD (mean ± standard deviation (SD); convenience: 7.47 ± 2.19 [app] vs. 4.20 ± 2.49 [paper]; satisfaction: 7.36 ± 2.17 [app] vs. 5.07 ± 2.65 [paper]). The median score of the overall preference for using the mobile app instead of the paper-based VD was 9 out of 10 (mean ± SD 7.82 ± 2.68). We also found a good correlation between the two methods for nocturnal urine volume (r = 0.55 , p = 0.04), nocturnal polyuria index (r = 0.66 , p = 0.23), total number of voids (r = 0.9 , p = 0.02), number of nocturnal voids (r = 0.83 , p = 0.02), and maximal bladder capacity (r = 0.89 , p = 0.04). Conclusion. The acoustic UFM-based mobile app VD demonstrated favorable findings compared to the conventional paper-based VD. [ABSTRACT FROM AUTHOR]

Worldwide, iron deficiency is a common form of micronutrient deficiency with a high individual and societal cost. There are considerable knowledge and practice gaps in the diagnosis and treatment of iron deficiency. Bibliometric analysis examines the published body of knowledge of a subject in an objective fashion. The Web of Science Core Collection was searched to retrieve the 100 most cited papers on the topic of iron deficiency, and the key metrics of each paper were extracted. A keyword study was performed using VOSviewer 1.6.10 software, which provided a visual mapping of the network of keyword cooccurrences. The papers were published between 1964 and 2017 and were cited an average of 636 times. They were contributed by authors from 119 different countries/regions, with the largest contributing country being the United States. 29 institutions contributed at least 6 publications each, and 4 researchers authored or coauthored at least 5 papers. Keyword analysis suggests that the most cited topics could be grouped into 4 categories: (1) epidemiologic research of the global burden of iron deficiency, (2) clinical aspects of iron deficiency anemia, (3) iron metabolism, and (4) the impact of iron deficiency on children. Identification of the most impactful studies in the field of iron deficiency may be helpful to practitioners interested in improving their knowledge base. Compared to bibliometric studies performed on other topics, the medical literature of iron deficiency is mature, as evidenced by the high citation rate of the top 100 papers. Despite the high worldwide prevalence of iron deficiency, the top cited papers are dominated by a relatively small number of countries and institutions. Interestingly, however, the most cited authors in this study do not overlap with the most cited institutions. [ABSTRACT FROM AUTHOR]

Aim. To evaluate in vitro the antibacterial effect of a paper made of silver phosphate cellulose fibers (SPCF) on Staphylococcus aureus, the most common diabetic foot ulceration (DFU) pathogen when compared with other common commercial products. Methods. The antibacterial activity of SPCF samples was evaluated through time with cell counting on agar plates. SPCF samples were then compared with commercial wound care products currently in use in DFU treatments (Silvercel™, Acticoat 7, and Aquacel Ag ExtraTM) through time on agar plates (growth inhibition zones). Results. After 6 hours, there was no viable bacterial cell detected on either plate (p < 0.05). There was a net growth inhibition zone for SPCF samples but no significant difference between the two silver concentrations. Compared with common commercial products, SPCF paper provides results equal to Acticoat 7 (p < 0.05) and superior to Aquacel AG ExtraTM and Silvercel™ at lower silver concentrations (p < 0.001). Conclusions. These results have shown the efficiency of SPCF paper to eliminate Staphylococcus aureus in these conditions. SPCF papers are effective when compared with other common commercial products and could have an industrial potential in wound care. Infected DFU could benefit from the antibacterial effectiveness of SPCF, but more relevant experimentations related to foot ulcers are needed. [ABSTRACT FROM AUTHOR]

The paper mulberry (Broussonetia papyrifera) leaf is rich in alkaloids and flavonoids, which has high medicinal and feeding value. We aimed to analyze the effects of B. papyrifera leaf extract on growth performance, antioxidant capacity, immune functions, and fecal microflora of weaned piglets. Thirty healthy, 28-day-old piglets were randomly assigned to three groups and fed with a basal diet supplemented with 0, 150, and 300 g/t B. papyrifera leaf extract for 42 days (control group, group I, and group II) separately. The result revealed that the final weight of piglets in group II was higher than the other groups, and the diarrhea rate in this group was 62.9% lower than in the control group. The feed conversion ratio in group I was significantly lower than the other two groups. Higher blood urine nitrogen concentration was noted in group II, higher glutathione peroxidase and catalase in group II, higher superoxide dismutase in the control group, and higher immune globulins (Ig) IgG, IgA, and IgM in group II. There was no significant difference in community richness and community diversity among the three groups of fecal samples. The relative level of Roseburia was higher in groups I and II, while Lactobacillus was higher in the control group. In conclusion, supplementation with B. papyrifera leaf extract at a certain dosage can increase growth performance and antioxidant capacity of weaned piglets, reduce the occurrence of diarrhea, enhance immune functions and disease resistance, and affect the composition of fecal microflora. [ABSTRACT FROM AUTHOR]

The paper mulberry (Broussonetia papyrifera) leaf is rich in alkaloids and flavonoids, which has high medicinal and feeding value. We aimed to analyze the effects of B. papyrifera leaf extract on growth performance, antioxidant capacity, immune functions, and fecal microflora of weaned piglets. Thirty healthy, 28-day-old piglets were randomly assigned to three groups and fed with a basal diet supplemented with 0, 150, and 300 g/t B. papyrifera leaf extract for 42 days (control group, group I, and group II) separately. The result revealed that the final weight of piglets in group II was higher than the other groups, and the diarrhea rate in this group was 62.9% lower than in the control group. The feed conversion ratio in group I was significantly lower than the other two groups. Higher blood urine nitrogen concentration was noted in group II, higher glutathione peroxidase and catalase in group II, higher superoxide dismutase in the control group, and higher immune globulins (Ig) IgG, IgA, and IgM in group II. There was no significant difference in community richness and community diversity among the three groups of fecal samples. The relative level of Roseburia was higher in groups I and II, while Lactobacillus was higher in the control group. In conclusion, supplementation with B. papyrifera leaf extract at a certain dosage can increase growth performance and antioxidant capacity of weaned piglets, reduce the occurrence of diarrhea, enhance immune functions and disease resistance, and affect the composition of fecal microflora. [ABSTRACT FROM AUTHOR]

Citation classics represent the highest impact work in a given field. We aim to identify and analyze the most frequently cited papers on brucellosis. We used the databases Scopus and Web of Science to determine the most frequently cited papers. The most cited fifty papers in each database were identified. We then ranked the papers according to the highest citation count recorded from any of the two databases. The most frequently cited paper received 964 citations and was by DelVecchio VG et al. reporting the complete genomic sequencing of Brucella melitensis. The papers were published in 30 journals led by the “Infection and Immunity” journal and the “Veterinary Microbiology” journal (each had 7 papers). Citation classics in brucellosis were all in English except one in French and were mostly of basic science type. In addition, we noticed that 12 articles that were identified among the highest fifty articles in one database were missed by the other database and vice versa. Therefore, we suggest that searching in more than one database would detect additional citation classics. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this is to examine the visualization, dynamicity, and collaborative networking of scientific production on visible light (VL) and skin aging through scientometric analysis. Materials and Methods: This research consisted of a cross‐sectional and descriptive design with a scientometric approach that examined the publication trends and collaborative patterns among authors and institutions from 2018 to 2023. A comprehensive search strategy was also employed by using specific keywords related to VL and skin aging. In this case, several indicators were employed, including scholarly output, view count, field‐weighted citation impact (FWCI), and citation count. The analyses were performed by using SciVal software and R Studio version 4.3.2. Results: A total of 180 sources were identified, with 280 documents generated, indicating an annual growth rate of 6.72%. The documents, averaging 3.25 years in age, received an average of 12.14 citations, revealing their impact. Additionally, collaborations were evident, with a ratio of 5.6 coauthors per paper and 25.71% consisting of international collaborations. In terms of institutions, there were notable disparities in scholarly activities and impact metrics, highlighting the diversity of the research landscape. Meanwhile, journals, such as Photodermatology, Photoimmunology and Photomedicine, revealed a substantial impact (FWCI 2.05). Overall, the impact of the journals showed a general upward trend, reflecting dynamicity and variability over time. Conclusion: An annual growth rate of 6.72% was found, with 180 sources and 280 papers on VL and skin aging. Moreover, international collaborations, the positive impact in leading journals, and the distribution patterns identified through scientometric laws underscored the vitality and complexity of the field. These results offer valuable insights into guiding future research in this multidisciplinary field. [ABSTRACT FROM AUTHOR]

Mass production of vermicompost using suitable species of earthworms and selecting target organic waste materials has appeared to be a great development in the realm of biotechnological research for the sustainable eco-management. Although, for the bioconversion of organic wastes to vermicompost, suitable earthworm species play major roles, a hoard of bacterial assemblages by virtue of production of different enzymes facilitate the process of vermicomposting. The present study has documented the roles of vermicompost associated bacteria in combating, preventing, and controlling of cancer so as to open a new vista not only in the field of vermitechnology but also on biomedical research. Earthworms’ associated bacterial metabolic products having their unique physicochemical excellence have gained importance due to their roles as a facilitator of apoptosis (programed cell death in a MCF-7 cell line). The antioxidant and anticancer activities of ethyl acetate extracts’ of vermicompost associated bacterium Bacillus anthracis were undertaken by antioxidant assay which revealed maximum DPPH radical scavenging effect (75.79 ± 5.41%) of the extracts’ at 9 00 μg ml-1. Furthermore, the crude extracts obtained from the same bacteria were found to decrease the activity of SOD (superoxide dismutase) with the increase in doses. MTT assay showed potent cytotoxic activity against human breast adenocarcinoma cells (MCF-7) with the IC50 value of 46.64 ± 0.79 μg ml-1. It was further confirmed through Hoechst 33258 staining of nuclear fragmentation assay and DNA fragmentation analysis. Western blotting test has confirmed a downregulation of Akt upon application of crude extracts. Increase of SOD activity along with decrease of Akt level reflects that the mode of action is entirely PI-3K dependent. This study tends to indicate that B. anthracis isolated from vermicompost could be potentially explored for the development of new therapeutic agents, especially against cancer. [ABSTRACT FROM AUTHOR]

Objective. The aim of this study was to examine the characteristics of scientific production related to the use of filtered water in the field of dentistry. Material and Methods. A quantitative and descriptive observational study was carried out with a scientometric approach. Data were collected from the Web of Science (WOS) database during the period January 1991 to December 2023. A search strategy incorporating a combination of MeSH terms, including terms and thesauri related to "filtered water" and "dentistry", was used. R Studio version 4.3.2 and CiteSpace 6.2.R7 were used for data analysis. Results. Over the 32-year study period, 227 scholarly papers from 134 different sources were reviewed. The literature in this field has shown an annual growth rate of 10.44%. During the year 2010, a steady movement in the number of publications and authors was observed, with considerable collaborative interaction. In the year 2020, a large interaction between publications and their citations was found. The "Citation Burst" graph identified three references that have experienced the largest "burst" of citations in an evaluated period. Lotka's law described the productivity of authors, finding that most authors have published only one paper, while a smaller number of authors have published two papers. Most authors contributed a small number of articles, while a few authors contributed a large amount of the existing literature. Conclusion. A comprehensive overview of the scientific production related to the use of filtered water in dentistry over a span of 32 years is provided. The results highlight the growing interdisciplinarity and international collaboration in this field. Finally, the importance of filtered water in dentistry and its growing relevance in the scientific literature are emphasized. [ABSTRACT FROM AUTHOR]

The plate-like graphene shells (GS) produced by an original methane pyrolysis method and their derivatives graphene oxide (GO) and graphene oxide paper (GO-P) were evaluated with luminescent Escherichia coli biotests and additional bacterial-based assays which together revealed the graphene-family nanomaterials’ toxicity and bioactivity mechanisms. Bioluminescence inhibition assay, fluorescent two-component staining to evaluate cell membrane permeability, and atomic force microscopy data showed GO expressed bioactivity in aqueous suspension, whereas GS suspensions and the GO-P surface were assessed as nontoxic materials. The mechanism of toxicity of GO was shown not to be associated with oxidative stress in the targeted soxS::lux and katG::lux reporter cells; also, GO did not lead to significant mechanical disruption of treated bacteria with the release of intracellular DNA contents into the environment. The well-coordinated time- and dose-dependent surface charge neutralization and transport and energetic disorders in the Escherichia coli cells suggest direct membrane interaction, internalization, and perturbation (i.e., “membrane stress”) as a clue to graphene oxide’s mechanism of toxicity. [ABSTRACT FROM AUTHOR]

Objective: The objective of the study is to explore the scientific literature between ultraprocessed foods (UPFs) and cancer using a scientometric mapping. Materials and Methods: A Scopus search was conducted on February 4, 2024, limited to papers published between 2018 and 2023. We found 662 articles, 189 reviews, 68 book chapters, 13 conference papers, and 9 notes. The whole analysis included the evaluation of scholarly output by country/region, the number of scholarly papers produced (scholarly output), the number of views (view count), the field‐weighted citation impact (FWCI). Results: In the analysis conducted for the period 2018–2023, a dataset was examined where the annual growth rate was 5.96%, indicating a sustained expansion of the literature. The average number of citations per paper was 18.56, underlining the impact and relevance of the publications. Sixty‐six single‐authored papers were identified, and international collaborations accounted for 27.23% of the collaborative efforts. The most prominent authors were Inge Huybrechts, Marc J.R. Gunter, and Edward Luciano Giovannucci. In terms of impact and visibility, Harvard University leads with 52 contributions and a field‐weighted impact of 3.39. Conclusions: The literature in the field of UPFs and cancer has experienced a sustained expansion. The scientometric indicators reveal a high activity of recent academic contributions with significant impact. [ABSTRACT FROM AUTHOR]

Background. Lactobacillus acidophilus is lactic acid bacteria that produce bacteriocins. Bacteriocins are antimicrobial peptides or proteins that exhibit activity against closely related bacteria. The aim of this study was to determine the effect of L. acidophilus ATCC 4356 bacteriocin against Staphylococcus aureus. Material and Methods. We used four different phenotypic methods for antimicrobial activities against two standard strains: methicillin-resistant S. aureus (MRSA) ATCC 33591 and methicillin-susceptible S. aureus (MSSA) ATCC 25923. The methods were (1) agar well diffusion, (2) overlay soft agar, (3) paper disk, and (4) modification of punch hole. The ammonium sulfate method was used to concentrate crude bacteriocin, and ultrafiltration and dialysis tubes were used to remove ammonium sulfate from the bacteriocins. Each method was repeated in triplicate. Result. L. acidophilus ATCC 4356 showed antimicrobial activity against both MRSA and MSSA standard strains only by the overlay soft agar method and not by the agar well diffusion, punch hole modification, and paper disk methods. No antimicrobial effects were observed in crude bacteriocins concentrated. Conclusion. The growth inhibition of S. aureus in overlay soft agar method may be due to the production of bacteriocin-like substances. The overlay soft agar method is a qualitative test, so there is a need for further study to optimize the conditions for the production of bacteriocin-like substances in the culture supernatant and precise comparison between the inhibitory activity and pheromone secretion of different strains. [ABSTRACT FROM AUTHOR]

Telephone triage services are becoming increasingly commonplace in modern healthcare. Despite this widespread adoption, health researchers and practitioners seeking to understand evidence-based best practice face several challenges. Firstly, the few systematic reviews available yield small sample sizes, suggesting a small amount of research. Secondly, the rapid pace of development of telephone triage technologies means that there may be temporal validity issues with the available research, given some of this research is relatively old. Thirdly, researchers use different terminologies to describe telephone triage, meaning evidence may be more difficult to find than if consistent terminology was used. This bibliometric analysis therefore is aimed at providing a macroscopic overview of telephone triage, to understand the scale and scope of the available evidence (i.e., where, when, and by whom research is conducted), for interested researchers and practitioners. Additionally, it is aimed at quantifying the prevalence of terms used to describe telephone triage, to recommend consistent terminology for future use, and to improve accessibility of research. To address these aims, literature searches using three different key terms: "telephone triage," "remote triage," and "teletriage" were conducted in Scopus and PubMed. Corresponding bibliometric data was visualised and analysed using VOSviewer. This bibliometric review identified 784 papers since the term "telephone triage" first appears in 1980, confirming a paucity of literature in the field. An overview of telephone triage research up to 2021 is provided, which should serve as a useful foundation for future research and application of evidence-based practice. Gaps in telephone triage research are identified, and the use of consistent terminology is encouraged, with the aim of supporting telephone triage researchers in determining research priorities and improving the impact of future studies. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) and single nucleotide polymorphisms (SNPs) play important roles in disease risk and development, especially cancer. Importantly, when SNPs are located in pre-miRNAs, they affect their splicing mechanism and change the function of miRNAs. To improve disease risk assessment, we propose an approach and developed a software tool, IsomiR_Find, to identify disease/phenotype-related SNPs and isomiRs in individuals. Our approach is based on the individual's samples, with SNP information extracted from the 1000 Genomes Project. SNPs were mapped to pre-miRNAs based on whole-genome coordinates and then SNP-pre-miRNA sequences were constructed. Moreover, we developed matpred2, a software tool to identify the four splicing sites of mature miRNAs. Using matpred2, we identified isomiRs and then verified them by searching within individual miRNA sequencing data. Our approach yielded biomarkers for biological experiments, mined functions of miRNAs and SNPs, improved disease risk assessment, and provided a way to achieve individualized precision medicine. [ABSTRACT FROM AUTHOR]

Next generation sequencing is an emerging technology that has been widely used in the detection of genomic variants. However, since its depth of coverage, a main signature used for variant calling, is affected greatly by biases such as GC content and mappability, some callings are false positives. In this study, we utilized paired-end read mapping, another signature that is not affected by the aforementioned biases, to detect false-positive deletions in the database of genomic variants. We first identified 1923 suspicious variants that may be false positives and then conducted validation studies on each suspicious variant, which detected 583 false-positive deletions. Finally we analysed the distribution of these false positives by chromosome, sample, and size. Hopefully, incorrect documentation and annotations in downstream studies can be avoided by correcting these false positives in public repositories. [ABSTRACT FROM AUTHOR]

Purpose. As a scientific field, bioinformatics has drawn remarkable attention from various fields, such as information technology, mathematics, and modern biological sciences, in recent years. The topic models originating from the field of natural language processing have become the focus of attention with the rapid accumulation of biological datasets. Thus, this research is aimed at modeling the topic content of the bioinformatics literature presented by Iranian researchers in the Scopus Citation Database. Methodology. This research was a descriptive-exploratory study, and the studied population included 3899 papers indexed in the Scopus database, which had been indexed in this database until March 9, 2022. The topic modeling was then performed on the abstracts and titles of the papers. A combination of LDA and TF-IDF was utilized for topic modeling. Findings. The data analysis with topic modeling resulted in identifying seven main topics "Molecular Modeling," "Gene Expression," "Biomarker," "Coronavirus," "Immunoinformatics," "Cancer Bioinformatics," and "Systems Biology." Moreover, "Systems Biology" and "Coronavirus" had the largest and smallest clusters, respectively. Conclusion. The present investigation demonstrated an acceptable performance for the LDA algorithm in classifying the topics included in this field. The extracted topic clusters indicated excellent consistency and topic connection with each other. [ABSTRACT FROM AUTHOR]

Objective. To perform a bibliometric analysis of scientific production related to gut microbiota and Parkinson's disease between 2011 and 2020. Methods. A descriptive, retrospective, cross-sectional, and bibliometric study was carried out. The Scopus database was used as a source to evaluate the worldwide scientific production on intestinal microbiota and its relationship with Parkinson's disease. Data were extracted from Scopus using a formula developed with thesaurus terms MeSH (Medline) and Emtree (Embase). Results. A total of 591 documents were found. The retrieved manuscripts received an average of 41.9 citations per document. Four of the 10 most productive authors were Italian. The University of Helsinki (Finland) was the institution with the highest scientific production (19 papers) and the highest impact (5921 citations). In terms of productivity and impact, Movement Disorders ranked first with 38 papers and 2782 citations, and those papers published in Q1 quartile journals exceeded the sum of the remaining quartiles. Papers with international collaboration were the most cited. Keyword analysis showed that the terms Parkinson Disease, Disease, and Intestine Flora were the most frequent. Conclusion. The number of papers on Parkinson's disease and gut microbiota has been increasing; however, high-quality journals maintain the same high publication rate. International collaboration from high-income countries played an important role in the impact generated by the publications. [ABSTRACT FROM AUTHOR]

The rapid development of antibiotic resistance in K. pneumonia has led to a major concern. In order to analyze the hotspots and develop trends in this field through visual the analysis, this study used CiteSpace software to summarize the available data in the literature to provide insights. A total of 9366 research articles were retrieved from the Web of Science Core Collection, and the number of published papers is increasing year by year. The country with the most articles was the USA, followed by China and India. The institution with the highest number of publications was LERU. The author with the highest number of articles was Li. The journal with the highest citation rate was Antimicrobial Agents and Chemotherapy. In addition, based on keyword coword analysis and cited literature prominence analysis by CiteSpace, the current research focus in the field was therapy, CRKP, and resistance genes. This paper provides a new quantitative visualization way for the development of the field in the recent ten years. The results show global trends that researchers can use to determine future directions. [ABSTRACT FROM AUTHOR]

An epidemic can cause enormous damage through financial and economic losses in addition to impaired health and loss of life. Good epidemic models can provide insights into ongoing waves that may facilitate public health responses and other readiness. Epidemic systems can undergo or consist of more than two driving forces; actually, they involve several. This paper deals with the modeling epidemics with two wave dynamics. We present a mathematical model with three driving forces, which is more compatible with the biology of the epidemic than conventional bilogistic and bi‐Richards ones, which have two driving forces. Simulation results show that our proposed model can predict turning points (waves) and cumulative case numbers during the two waves of epidemics satisfactorily. As a sample examination of our proposed model against real data, we show that the second phase of a typical epidemic can be detected by using less case data past the beginning of the epidemic than the bi‐Richards model. [ABSTRACT FROM AUTHOR]

In recent years the T-Scan system has introduced the possibility of importing digitization of dental arches to its registrations. This is a remarkable advance, which allows an intuitive display of the location of the gathered dynamic data on the denture. Nevertheless, today’s usual method of manually positioning the arch in relation to the T-Scan’s force registration gives rise to the possibility of human error. In order to guarantee a good alignment between the dynamic registration and 3D digital casts, a specific method was developed. The aim of this study is to evaluate the accuracy of this alignment method. For this purpose, it was compared with the most common procedure for detecting occlusal contacts, the articulating paper method. The comparison comprised overlapping digital models of both methods. Contacts of casts of 11 adults were registered, both with articulating paper and the T-Scan system. For one method, articulating paper marks were scanned in color; for the second method, the previously mentioned alignment was carried out with the T-Scan registrations. The results of both methods were overlapped in 3D digital casts, quantifying occlusal data matches. Statistical analyses were made to measure the quality of this alignment method. The study revealed a mean matching percentage of 79.02%, confirming the high reliability of the method. [ABSTRACT FROM AUTHOR]

N-lined glycosylation is one of the critical quality attributes (CQA) for biotherapeutics impacting the safety and activity of drug product. Changes in pattern and level of glycosylation can significantly alter the intrinsic properties of the product and, therefore, have to be monitored throughout its lifecycle. Therefore fast, precise, and unbiased N-glycan mapping assay is desired. To ensure these qualities, using analytical methods that evaluate completeness of deglycosylation is necessary. For quantification of deglycosylation yield, methods such as reduced liquid chromatography–mass spectrometry (LC-MS) and reduced capillary gel electrophoresis (CGE) have been commonly used. Here we present development of two additional methods to evaluate deglycosylation yield: one based on LC using reverse phase (RP) column and one based on reduced sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE gel) with offline software (GelAnalyzer). With the advent of rapid deglycosylation workflows in the market for N-glycan profiling replacing overnight incubation, we have aimed to quantify the level of deglycosylation in a selected rapid deglycosylation workflow. Our results have shown well resolved peaks of glycosylated and deglycosylated protein species with RP-LC method allowing simple quantification of deglycosylation yield of protein with high confidence. Additionally a good correlation, ≥0.94, was found between deglycosylation yields estimated by RP-LC method and that of reduced SDS-PAGE gel method with offline software. Evaluation of rapid deglycosylation protocol from GlycanAssure™ HyPerformance assay kit performed on fetuin and RNase B has shown complete deglycosylation within the recommended protocol time when evaluated with these techniques. Using this kit, N-glycans from NIST mAb were prepared in 1.4 hr and analyzed by hydrophilic interaction chromatography (HILIC) ultrahigh performance LC (UHPLC) equipped with a fluorescence detector (FLD). 37 peaks were resolved with good resolution. Excellent sample preparation repeatability was found with relative standard deviation (RSD) of <5% for peaks with >0.5% relative area. [ABSTRACT FROM AUTHOR]

Aptamers, synthetic single-stranded DNA or RNA molecules, can be regarded as a valuable improvement to develop novel ad hoc sensors to diagnose several clinical pathologies. Their intrinsic potential is related to the high specificity and sensitivity to the selected target biomarkers, being capable of detecting very low concentrations and thus allowing an early diagnosis of a possible disease. This kind of probe can be usefully integrated into a number of different devices in order to provide a reliable acquisition of the analyte and properly elaborate the related signal. The study presents the fabrication and characterization of a label-free aptamer sensor designed using a gold-coated silicon nanostructured substrate to map the target molecule by means of surface-enhanced Raman spectroscopy (SERS). As a proof, thrombin was used as a model at four different concentrations (i.e., 0.0873, 0.873, 8.73, and 87.3 nM). SERS mapping analysis was carried out considering each representative band of the aptamer-thrombin complex (centered at 822, 1140, and 1558 cm−1) and then combining them in order to acquire a comprehensive and unambiguous measure of the target. In both cases, a valuable correlation was evaluated, even if the first approach can suffer from some limitations in the third band related to lower definition of the characteristic peak compared to those in the other two bands. [ABSTRACT FROM AUTHOR]

The incidence of oral cancer is still increasing. It has become very common in patients with malignant tumors, which has forced medical personnel to continuously explore its treatment methods. What kind of method can effectively and correctly diagnose the disease in the early stage and improve the survival rate has become one of the research topics that have attracted much attention. Aiming at this problem, it has great research significance for the field of oral precancerous lesions diagnosis. With the in-depth research on oral precancerous diagnosis, the research on artificial neural network (ANN) in medical diagnosis is gradually carried out. Its performance advantage is of great significance to solve the problem of early and correct disease diagnosis. This paper aimed to investigate the application of ANN-assisted cancer risk prediction method in risk prediction of oral precancerous lesions. Through the analysis and research of ANN and oral cancer, the construction of oral cancer risk prediction model was applied to solve the problem of improving the survival rate of oral cancer patients. In this paper, ANN and oral precancerous lesions were analyzed, the performance of the algorithm was experimentally analyzed, and the relevant theoretical formulas were used to explain. The results showed that the method had higher accuracy than traditional forecasting methods. When N = 2 , the output accuracy was above 90%. It can be seen that the algorithm can meet the needs of the diagnosis of high-risk groups of oral cancer lesions, and the diagnosis efficiency and patient survival rate has been greatly improved. [ABSTRACT FROM AUTHOR]

Introduction. The function of the masticatory apparatus is complete when the dentition is intact with contact between the individual teeth and proper occlusion with the antagonists. For years, occlusal contacts have been studied to determine their exact location and describing various materials and methods for their registration such as paper foil, silk, and Shimstock foil. For years, occlusal contacts have been studied to determine their exact location and describe various materials and methods for their registration such as paper foil, silk, shim stock foil, the T-Scan system, and more recently the OccluSense system. The primary aim of the study was at evaluating which of the occlusal indicators is the most commonly used in practice, and the secondary aim was whether dentists are willing to use digital methods to examine occlusion. Materials and Methods. The main primary information of the survey was collected by sending electronically anonymous questionnaires to 2014 dentists, randomly selected from all regions of the country. 228 questionnaires were filled in and returned. To achieve the goal of the study, the self-developed questionnaire was created and tested to survey the opinion about the use of occlusal indicators in dental practice. Each questionnaire contains questions about the sociodemographic and professional status of the people in the group and their opinion about the positives and negatives and the effectiveness of occlusal indicators. Results. The obtained results confirm the statement that the most frequently used occlusal indicator in dental practice is the articulation paper. Articulation foil and silk are used less frequently than articulation paper. Of the listed quality indicators, Shimstock foil is rarely used in practice. Of the indicated quantitative indicators, the T-Scan system is more used than the OccluSense system. In the era of rapid technology development, the opinion and desire of dentists to increasingly want to introduce in their clinical practice quantitative methods are the digital diagnosis of occlusion. Conclusion. In any dental practice, if technically possible, digital methods would be used, giving more accurate and reliable data on the registered occlusal contacts. [ABSTRACT FROM AUTHOR]

Objective. Aging is a growing public health concern for people, organizations, and governments. The current study was undertaken to provide insights into the global research output on geriatric nursing. Methods. A bibliometric study was implemented using the WoS database for the period from 1900 to 2020. Various tools and measures were used to analyze and visualized. Results. The search strategy found 4923 papers. The oldest paper was written by Beverly C. Andre in 1953. As team size increases, so does the number of citations. The USA was the active country and the highest number of coauthors. New York University was an active institution. Stig Karlsson was the most active author in Geriatric Nursing with 28 articles from Sweden, followed by Koen Milisen and Sandman, with 26 articles each from Sweden and Belgium. The most frequent words in this field were depression, malnutrition, education, Alzheimer's disease, and dementia. The latest research themes in this field were COVID-19, interprofessional locomotive syndrome, emergency nursing, and public health. The most influential papers were specified. Journal of the American Geriatrics Society was the most active journal. Conclusions. Geriatric nursing is a rooted field and has received special attention in the last decade. Policymakers, especially in developing countries, should pay attention to geriatric nursing as a specialty of nursing to solve aging issues they would face considering the increasing elderly population. [ABSTRACT FROM AUTHOR]

Introduction. The wide variety of methods for recording occlusal contacts and the contradictory data on the interpretation of the obtained markings provoked us to make a comparative laboratory study between different occlusal indicators. Purpose. Evaluation of a qualitative and quantitative method for registration of occlusal contacts in static occlusion in laboratory conditions. Materials and Methods. In completion of the objective, we designed an apparatus for registration of the occlusal contacts (AROC) in static occlusion which is used, corresponding to the MIP in clinical conditions. The occlusal indicators that were included in the study were articulating paper 100 μ, articulating foil 12 μ, and T-Scan Novus system with a sensor thickness of 100 μ. The collected primary statistical information was entered and processed with the statistical package SPSS Statistics 19.0, and the graphs were prepared using Microsoft Office 2019. We performed descriptive statistical analysis in this study. Comparisons were performed using one-way analysis of variance (ANOVA), Student's t -test, and Pearson coefficient method. For a significance level, p < 0.05 was chosen. Result and Discussion. With quality occlusal indicators, it is possible only to visually determine the size, number, and intensity of the marked contacts. After the statistical processing of the obtained data on the number of registered contacts, a significant difference is found in the number of contacts of certain teeth (18, 24, 25, 28, 38, 35, 34, 33, 44, 45, and 48) registered with articulating paper and articulating foil. The maximum force that is reported during the study with the T-Scan system is 93.72% and the forces in the right half of the dentition are 51.7% and in the left 48.9%. To visualize the location of the registered occlusal contacts with the system, it is intraoral to use a quality indicator and we recommend the use of articulating foil. Conclusion. Based on findings from the current in vitro simulation, we can conclude that the type of occlusal indicator influences the registration of contacts, and therefore, we propose as a method of choice to achieve a balanced occlusion in clinical practice to combine the use of one conventional and one quantitative method. [ABSTRACT FROM AUTHOR]

Objective. To sort out the literature related to conjunctival bacteria and summarize research hotspots and trends of this field. Materials and Methods. The relevant literature data from 1900 to 2019 was retrieved from the Web of Science Core Collection database. After manual selection, each document record includes title, author, keywords, abstract, year, organization, and citation. We imported the downloaded data into CiteSpace V (version 5.5R2) to draw the knowledge map and conduct cooperative network analysis, discipline and journal analysis, cluster analysis, and burst keyword analysis. Results. After manual screening, there were 285 relevant papers published in the last 28 years (from 1991 to 2019), and the number is increasing year by year. The publications of conjunctival bacteria were dedicated by 1381 authors of 451 institutions in 56 countries/regions. The United States dominates this field (82 literatures), followed by Germany (23 literatures) and Japan (23 literatures). Overall, most cited papers were published with a focus on molecular biology, genetics, nursing, and toxicology. Most papers fall into the category of ophthalmology, veterinary sciences, and pharmacology and pharmacy. The only organized cluster is the "postantibiotic effect," and the top 5 keywords with the strongest citation bursts include "postoperative endophthalmiti(s)," "infectious keratoconjunctiviti(s)," "conjunctiviti(s)," "resistance," and "diversity". Conclusion. The global field of conjunctival bacteria has expanded in the last 28 years. The United States contributes most. However, there are little cooperation among authors and institutions. Overall, this bibliometric study organized one cluster, "postantibiotic effect", and identified the top 5 hotspots in conjunctival bacteria research: "postoperative endophthalmiti(s)," "infectious keratoconjunctiviti(s)," "conjunctiviti(s)," "resistance," and "diversity". Thus, further research focuses on these topics that may be more helpful to prevent ocular infection and improve prophylaxis strategies to bring a benefit to patients in the near future. [ABSTRACT FROM AUTHOR]

Introduction. Ethiopia has made significant efforts to enhance family planning services despite variations in the community's use of modern contraception in different parts of the country. Various studies have reported the proportion and determinant factors of adolescents' contraceptive uptake in Ethiopia. These studies are not consistent in terms of size, scope, and geographic coverage, and the results need to be systematically collated to inform policies. Therefore, this review was aimed at analyzing the findings of those primary studies to obtain more representative evidence of adolescents' contraceptive uptake in Ethiopia. Methods. Five databases (MEDLINE via PubMed, Google Scholar, Scopus, ScienceDirect, and CINAHL) were searched for papers published from January 2000 up to June 2022 in English. Of thirty eligible studies, eight papers were included in this meta-analysis. Between-study heterogeneity was evaluated by the forest plot and inconsistency index ( I 2 ). A random-effects model was used to calculate the pooled estimates of adolescents' contraceptive uptake. Results. The overall pooled proportion of adolescents' contraceptive uptake was 40% ( I 2 = 99.70 , p ≤ 0.001 ; 95 % CI = 19 , 61). Adolescents' usage of contraception was influenced by a number of factors: individual-, sociocultural-, knowledge- (about contraceptive methods), and healthcare service-related factors. Individual-related factors include the educational status of adolescents, being of young age, and the income status of adolescents' families. Sociocultural-related factors comprise discussion with the family/relatives, parent disapproval and pressure from partners, and being married or having a partner. Healthcare service-related factors include the availability of youth clubs and inconvenient service hours for SRH services. Knowing contraceptive methods and SRH services was also positively associated with adolescents' contraceptive utilization. Conclusions. The proportion of adolescents who used contraception in Ethiopia was 40%. Adolescents' use of contraceptives was influenced by a variety of factors: individual-, sociocultural-, healthcare-, and knowledge-related factors. Hence, integrated interventions targeted at tackling barriers to contraceptive uptake may be helpful to improve adolescents' contraceptive utilization in Ethiopia. [ABSTRACT FROM AUTHOR]

Different from traditional images, light field images record not only spatial information but also angle information. Due to the large volume of light field data brings great difficulties to storage and compression, light field compression technology has attracted much attention. The epipolar plane image (EPI) contains a lot of low rank information, which is suitable for recovering the complete EPI from a part of EPI. In this paper, a light field image coding framework based on EPI restoration neural network has been proposed. Compared with previous algorithms, the proposed algorithm further takes advantage of the inherent similarity in light field images, and the proposed framework has higher performance and robustness. Experimental results show that the proposed method has superior performance compared to the state-of-the-art both in quantitatively and qualitatively. [ABSTRACT FROM AUTHOR]

Chlamydia trachomatis imposes serious health problems and causes infertility. Because of asymptomatic onset, it often escapes antibiotic treatment. Therefore, vaccines offer a better option for the prevention of unwanted inflammatory sequelae. The existence of serologically distinct serovars of C. trachomatis suggests that a vaccine will need to provide protection against multiple serovars. Chlamydia spp. use a highly conserved type III secretion system (T3SS) composed of structural and effector proteins which is an essential virulence factor. In this study, we expressed the T3SS needle protein of Chlamydia muridarum, TC_0037, an ortholog of C. trachomatis CdsF, in a replication-defective adenoviral vector (AdTC_0037) and evaluated its protective efficacy in an intravaginal Chlamydia muridarum model. For better immune responses, we employed a heterologous prime-boost immunization protocol in which mice were intranasally primed with AdTC_0037 and subcutaneously boosted with recombinant TC_0037 and Toll-like receptor 4 agonist monophosphoryl lipid A mixed in a squalene nanoscale emulsion. We found that immunization with TC_0037 antigen induced specific humoral and T cell responses, decreased Chlamydia loads in the genital tract, and abrogated pathology of upper genital organs. Together, our results suggest that TC_0037, a highly conserved chlamydial T3SS protein, is a good candidate for inclusion in a Chlamydia vaccine. [ABSTRACT FROM AUTHOR]

Purpose. Artificial intelligence (AI) techniques are used in precision medicine to explore novel genotypes and phenotypes data. The main aims of precision medicine include early diagnosis, screening, and personalized treatment regime for a patient based on genetic-oriented features and characteristics. The main objective of this study was to review AI techniques and their effectiveness in neoplasm precision medicine. Materials and Methods. A comprehensive search was performed in Medline (through PubMed), Scopus, ISI Web of Science, IEEE Xplore, Embase, and Cochrane databases from inception to December 29, 2021, in order to identify the studies that used AI methods for cancer precision medicine and evaluate outcomes of the models. Results. Sixty-three studies were included in this systematic review. The main AI approaches in 17 papers (26.9%) were linear and nonlinear categories (random forest or decision trees), and in 21 citations, rule-based systems and deep learning models were used. Notably, 62% of the articles were done in the United States and China. R package was the most frequent software, and breast and lung cancer were the most selected neoplasms in the papers. Out of 63 papers, in 34 articles, genomic data like gene expression, somatic mutation data, phenotype data, and proteomics with drug-response which is functional data was used as input in AI methods; in 16 papers' (25.3%) drug response, functional data was utilized in personalization of treatment. The maximum values of the assessment indicators such as accuracy, sensitivity, specificity, precision, recall, and area under the curve (AUC) in included studies were 0.99, 1.00, 0.96, 0.98, 0.99, and 0.9929, respectively. Conclusion. The findings showed that in many cases, the use of artificial intelligence methods had effective application in personalized medicine. [ABSTRACT FROM AUTHOR]

The elbow joint is prone to stiffness and adhesion after trauma or surgery. High-energy trauma easily led to loss of mobility of the elbow joint. Mild trauma can also cause stiffness in the elbow joint. In order to investigate the pathogenesis of stiffness and adhesion in elbow joint, a feedback-type elbow joint control system based on network is proposed in this paper. The simulation results show that it has significant differences in elbow bioelectrical impedance in patients with elbow trauma, and this new method realizes the control strategy of converting the patient's elbow joint pathological information into elbow joint orthosis control information. [ABSTRACT FROM AUTHOR]

Introduction. Candida auris is a relatively novel pathogen first described in 2009 in Japan. It has increased its presence worldwide, becoming a public health concern due to its innate resistance to antifungals and outbreak potential. Methods. We performed a query using the word "Candida auris" from the Scopus database, further performing a bibliometric analysis with the open-source R package Bibliometrix. Results. 907 original articles were retrieved, allowing us to map the principal authors, papers, journals, and countries involved in this yeast research, as well as analyze current and future trends and the number of published articles. Conclusion. C. auris will continue to be a pivotal point in fungal resistance research, either for a better understanding of its resistance and pathogenic mechanisms or for developing novel drugs. [ABSTRACT FROM AUTHOR]

This paper has reviewed the global research on the pandemic critical care research during the COVID-19 from 2020 to 2022. To this end, a bibliometric and cluster analysis by full counting has been carried out using VOSviewer software and bibliographic data extracted from the Scopus database. The research found and studied 2778 documents. The types of research documents were limited to an article (81.46%), a letter (9.43%), an editorial (3.92%), a note (3.92%), a conference paper (0.90), and a short survey (0.04%). The results show an incessant increase in the number of research documents published and citations received during the COVID-19 pandemic. The U.S., U.K., Italy, and France have been shown to be the most productive countries, and there is a predominance of European institutions supporting and fostering research on pandemic critical care. Cecconi, M. (Italy) and Shankar-Hari, M. (U.K.) produced the highest number of research documents. Mapping of citation, co-citation, co-authorship, and keyword cooccurrence highlighted the hotspot, knowledge structure, and important themes. Citation dynamics for the top-cited research documents revealed static discourse. By reviewing the evolutionary trends of pandemic critical care research investigated factors, such as the influential works, main research topics, and the research frontiers, this paper reveals the scientific literature production's main research objectives and directions that could be addressed and explored in future studies. This paper reveals the scientific literature production's main research objectives and directions that could be addressed and explored in future studies after reviewing the evolutionary trends of pandemic critical care research during the COVID-19 and the investigated factors, such as influential works, main research topics, and research frontiers. [ABSTRACT FROM AUTHOR]

The incidence of liver cancer is increasing year by year, and how to effectively diagnose early-stage liver cancer and improve the survival rate of liver cancer patients has become one of the current research topics of concern. Aiming at this problem, it is of great significance for the diagnosis of early liver cancer. With the in-depth research on the diagnosis of early-stage liver cancer, the research on growth differentiation factor 15 is gradually carried out, and its performance advantages are of great significance to solve the problem of detection and diagnosis of early-stage liver cancer. This study can improve the accuracy of early diagnosis of liver cancer. The purpose of this paper is to study the application of data mining in the study of clinical value of growth and differentiation factor 15 detection and diagnosis of early liver cancer. In this paper, the data mining algorithm is analyzed, the performance of the algorithm is experimentally analyzed, and the relevant theoretical formulas are used to explain. The results showed that the expression level of GDF-15 was significant in early primary liver cancer (tumor diameter <2.5 cm). Different from normal liver tissue (P < 0.01), there was a significant difference (P < 0.01) compared with adjacent tissue (P < 0.01). Serum GDF-15 can be used as a tumor marker for predicting early stage liver cancer. The high expression of GDF-15 in early stage liver cancer is an independent risk factor affecting the prognosis of liver cancer patients. [ABSTRACT FROM AUTHOR]

Tissue adhesives as a physical barrier to microorganism penetration provide an alternative method with many advantages for wound closure in surgical settings compared to the clinical standard. This raises the need of developing and conducting in vitro methods that are sensitive and reproducible to assess their microbial barrier properties. In this study, three different polyurethane-based tissue adhesives with different physicochemical properties were evaluated in comparison to Dermabond® as a clinical gold standard for topical wound closure. Here, physicochemical properties varied in lactide concentration, viscosity, processing, and the full polymerization time. To evaluate the microbial barrier function, a 5 μl aliquot of E. coli Lux inoculum containing at least 1 × 10 9 CFU / ml was applied to the surface of each test adhesive and sterile filter paper as the control that was placed on an agar plate and incubated at 37°C. Plates were observed for bacterial growth (morphology), the adhesion of the adhesive/filter paper, and bioluminescence after 24, 48, and 72 hours. The data presented in this in vitro model indicated that polyurethane-based tissue adhesives with lactide concentration ≥ 5 % provided a suitable barrier against microbial penetration with 95% confidence of 99% efficacy for 72 h along with Dermabond®. Interestingly, the here described method was able to discriminate between the different physicochemical properties showing a better microbial barrier function with increasing lactide concentration of the adhesive. Overall, the results of this study showed the noninferiority between Dermabond® and the two abovementioned polyurethane-based tissue adhesives. [ABSTRACT FROM AUTHOR]

Traditional Chinese medicine (TCM) is a summary of the diagnosis and treatment experience formed by the working people in the long-term struggle against diseases, so it is very important to protect the intangible cultural heritage of TCM. How to extract valuable knowledge accurately and conveniently from the massive medical records of TCM is one of the important issues in the current research on the development of TCM. Due to the large amount of data of TCM medical records, many feature attributes, and diverse patterns, the existing classification technology has high computational complexity, low mining efficiency, and poor universality. Therefore, this paper proposed to quantify the medical records of TCM and obtained the main symptoms according to the improved hierarchical clustering feature selection algorithm. This paper also proposed a support vector machine (SVM) classification method using improved particle swarm algorithm to classify TCM information, which not only improves the efficiency and accuracy of TCM information classification but also discovers the potential dialectical and symptom patterns in diagnosis and treatment, so that the intangible cultural heritage protection of TCM can be developed sustainably. This paper showed that the information acquisition accuracy of the improved algorithm was very high. Before the improved algorithm was used, the accuracy of information mining for TCM was 67.90% at the highest and 65.53% at the lowest, but after using the improved algorithm, the accuracy rate of information mining for TCM was 88.02% at the highest and 82.45% at the lowest. It can be seen that using the improved algorithm to mine TCM information can quickly process effective information. [ABSTRACT FROM AUTHOR]

Fourteen Ganoderma lucidum strains from different geographic regions were identified using ITS region sequencing. Based on the sequences obtained, the genomic relationship between the analyzed strains was determined. All G. lucidum strains were also genetically characterized using the AFLP technique. G. lucidum strains included in the analysis displayed an AFLP profile similarity level in the range from 9.6 to 33.9%. Biolog FF MicroPlates were applied to obtain data on utilization of 95 carbon sources and mitochondrial activity. The analysis allowed comparison of functional diversity of the fungal strains. The substrate utilization profiles for the isolates tested revealed a broad variability within the analyzed G. lucidum species and proved to be a good profiling technology for studying the diversity in fungi. Significant differences have been demonstrated in substrate richness values. Interestingly, the analysis of growth and biomass production also differentiated the strains based on the growth rate on the agar and sawdust substrate. In general, the mycelial growth on the sawdust substrate was more balanced and the fastest fungal growth was observed for GRE3 and FCL192. [ABSTRACT FROM AUTHOR]

This study showed the prevalence of human papillomavirus (HPV) variants as well as nucleotide changes within L1 gene and LCR of the HPV16, HPV31, and HPV58 found in cervical lesions of women from North-East Brazil. [ABSTRACT FROM AUTHOR]

Background. Among the surgical methods for lumbar disc herniation, open lumbar microdiscectomy is considered the gold standard. Recently, percutaneous endoscopic lumbar discectomy is also commonly performed for lumbar disc herniation for its various strong points. Objectives. The present study aims to examine whether percutaneous endoscopic lumbar discectomy and open lumbar microdiscectomy show better results as surgical treatments for lumbar disc herniation in the Korean population. Methods. In the present meta-analysis, papers on Korean patients who underwent open lumbar microdiscectomy and percutaneous endoscopic lumbar discectomy were searched, both of which are surgical methods to treat lumbar disc herniation. The papers from 1973, when percutaneous endoscopic lumbar discectomy was first introduced, to March 2018 were searched at the databases of MEDLINE, EMBASE, PubMed, and Cochrane Library. Results. Seven papers with 1254 patients were selected. A comparison study revealed that percutaneous endoscopic lumbar discectomy had significantly better results than open lumbar microdiscectomy in the visual analogue pain scale at the final follow-up (leg: mean difference [MD]=-0.35; 95% confidence interval [CI]=-0.61, -0.09; p=0.009; back: MD=-0.79; 95% confidence interval [CI]=-1.42, -0.17; p=0.01), Oswestry Disability Index (MD=-2.12; 95% CI=-4.25, 0.01; p=0.05), operation time (MD=-23.06; 95% CI=-32.42, -13.70; p<0.00001), and hospital stay (MD=-4.64; 95% CI=-6.37, -2.90; p<0.00001). There were no statistical differences in the MacNab classification (odds ratio [OR]=1.02; 95% CI=0.71, 1.49; p=0.90), complication rate (OR=0.72; 95% CI=0.20, 2.62; p=0.62), recurrence rate (OR=0.83; 95% CI=0.50, 1.38; p=0.47), and reoperation rate (OR=1.45; 95% CI=0.89, 2.35; p=0.13). Limitations. All 7 papers used for the meta-analysis were non-RCTs. Some differences (type of surgery (primary or revisional), treatment options before the operation, follow-up period, etc.) existed depending on the selected paper, and the sample size was small as well. Conclusion. While percutaneous endoscopic lumbar discectomy showed better results than open lumbar microdiscectomy in some items, open lumbar microdiscectomy still showed good clinical results, and it is therefore reckoned that a randomized controlled trial with a large sample size would be required in the future to compare these two surgical methods. [ABSTRACT FROM AUTHOR]

Gastric cancer is a common and deadly cancer in the world. The gold standard for the detection of gastric cancer is the histological examination by pathologists, where Gastric Histopathological Image Analysis (GHIA) contributes significant diagnostic information. The histopathological images of gastric cancer contain sufficient characterization information, which plays a crucial role in the diagnosis and treatment of gastric cancer. In order to improve the accuracy and objectivity of GHIA, Computer-Aided Diagnosis (CAD) has been widely used in histological image analysis of gastric cancer. In this review, the CAD technique on pathological images of gastric cancer is summarized. Firstly, the paper summarizes the image preprocessing methods, then introduces the methods of feature extraction, and then generalizes the existing segmentation and classification techniques. Finally, these techniques are systematically introduced and analyzed for the convenience of future researchers. [ABSTRACT FROM AUTHOR]

In recent years, due to the increase in the incidence of traffic accidents, the number of people with limb injuries has also increased. At the same time, among the aging population, neurological diseases or cardiovascular and cerebrovascular diseases have caused many people to have limb hemiplegia. It has been clinically proven that the use of rehabilitation equipment can help patients with limb injuries to restore limb motor function. This paper takes wearable lower limb rehabilitation exoskeleton as the research object, and its main contents are mechanical structure design, kinematics analysis, gait planning, virtual prototype simulation, and experimental verification and analysis. Based on the physiological characteristics of human body and the principle of comfortable and reliable wearing, this paper designs wearable exoskeleton for lower limb rehabilitation. Firstly, the physiological structure characteristics and movement mechanism of human lower limbs were studied and analyzed. By referring to the rotation range and height and size of each joint of human lower limbs, the overall scheme of wearable lower limb rehabilitation exoskeleton was designed and the degree of freedom was allocated. At the same time, Solidworks was used to establish a three-dimensional model. On the basis of a 3D model, a kinematics model was established, and the forward kinematics solution was obtained by using homogeneous coordinate transformation. Since the inverse kinematics solution was relatively complicated, the inverse kinematics solution was conducted in this paper according to the geometric relations of the joints of the lower limbs. Kinematics analysis of the exoskeleton structure of wearable lower limb rehabilitation was carried out to lay a theoretical foundation for gait planning. The off-line gait planning was carried out by using the method based on ZMP stability criterion, and the gait planning was divided into five stages: squat, start, middle step, stop and rise, and the motion trajectory of the center of mass and ankle joint was planned. Based on the inverse kinematics formula, the function of the change of joint angle with time in walking process is derived. The virtual prototype is established in ADAMS, and the simulation of virtual prototype is carried out by using the function of gait planning's joint angle and time. The correctness of structural design and gait planning was verified by measuring the trajectories of the centroid and ankle joints in each gait stage and the functional relationship between the rotation angle of each joint and time. Then, using a 3D dynamic capture system to capture the human lower limb motion trajectory of each joint, each joint trajectory data output, using the MATLAB software to output data, gets the joint trajectory change over time function curve and is used to verify feasibility and applicability of human gait planning. Through the research and analysis of the joints of the lower limbs of the human body, it can be concluded that the hip joint and the knee joint have 3 degrees of freedom, respectively, and the knee joint has 1 degree of freedom. [ABSTRACT FROM AUTHOR]

Predicting the polyproline type II (PPII) helix structure is crucial important in many research areas, such as the protein folding mechanisms, the drug targets, and the protein functions. However, many existing PPII helix prediction algorithms encode the protein sequence information in a single way, which causes the insufficient learning of protein sequence feature information. To improve the protein sequence encoding performance, this paper proposes a BERT-based PPII helix structure prediction algorithm (BERT-PPII), which learns the protein sequence information based on the BERT model. The BERT model's CLS vector can fairly fuse sample's each amino acid residue information. Thus, we utilize the CLS vector as the global feature to represent the sample's global contextual information. As the interactions among the protein chains' local amino acid residues have an important influence on the formation of PPII helix, we utilize the CNN to extract local amino acid residues' features which can further enhance the information expression of protein sequence samples. In this paper, we fuse the CLS vectors with CNN local features to improve the performance of predicting PPII structure. Compared to the state-of-the-art PPIIPRED method, the experimental results on the unbalanced dataset show that the proposed method improves the accuracy value by 1% on the strict dataset and 2% on the less strict dataset. Correspondingly, the results on the balanced dataset show that the AUCs of the proposed method are 0.826 on the strict dataset and 0.785 on less strict datasets, respectively. For the independent test set, the proposed method has the AUC value of 0.827 on the strict dataset and 0.783 on the less strict dataset. The above experimental results have proved that the proposed BERT-PPII method can achieve a superior performance of predicting the PPII helix. [ABSTRACT FROM AUTHOR]

Purpose. Single-period segmentation is one of the important steps in time-domain analysis of pulse signals, which is the basis of time-domain feature extraction. The existing single-period segmentation methods have the disadvantages of generalization, reliability, and robustness. Method. This paper proposed a period segmentation method of pulse signals based on long short-term memory (LSTM) network. The preprocessing was performed to remove noises and baseline drift of pulse signals. Thus, LabelMe was used to label each period of the pulse signals into two parts according to the location of the starting point of main wave and the dicrotic notch, and the dataset of the pulse signal period segmentation was established. Consequently, the labeled dataset was input into the LSTM for training and testing, and the results were compared with sum slope function method. Result. The remarkable result with the whole period segmentation accuracy of 92.8% was achieved for the segmentation of seven types of pulse signals. And the segmentation accuracies of the systolic phase, diastolic phase, and whole period using this method were higher than those of the sum slope function method. Conclusion. LSTM-based pulse signal segmentation method can achieve outstanding, robust, and reliable segmentation effects of the systolic phase, diastolic phase, and whole period of pulse signals. The research provides a new idea and method for the segmentation of pulse signals. [ABSTRACT FROM AUTHOR]

Breast cancer is the most prevalent form of cancer that can strike at any age; the higher the age, the greater the risk. The presence of malignant tissue has become more frequent in women. Although medical therapy has improved breast cancer diagnostic and treatment methods, still the death rate remains high due to failure of diagnosing breast cancer in its early stages. A classification approach for mammography images based on nonsubsampled contourlet transform (NSCT) is proposed in order to investigate it. The proposed method uses multiresolution NSCT decomposition to the region of interest (ROI) of mammography images and then uses Z-moments for extracting features from the NSCT-decomposed images. The matrix is formed by the components that are extracted from the region of interest and are then subjected to singular value decomposition (SVD) in order to remove the essential features that can generalize globally. The method employs a support vector machine (SVM) classification algorithm to categorize mammography pictures into normal, benign, and malignant and to identify and classify the breast lesions. The accuracy of the proposed model is 96.76 percent, and the training time is greatly decreased, as evident from the experiments performed. The paper also focuses on conducting the feature extraction experiments using morphological spectroscopy. The experiment combines 16 different algorithms with 4 classification methods for achieving exceptional accuracy and time efficiency outcomes as compared to other existing state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

In recent years, people's living standards are getting higher and higher, and life pressure is also increasing, and there are also many problems in eating habits. This is also the direct cause of colon cancer. The aim of this paper was to investigate whether anesthetic drugs could positively affect the proliferation and apoptosis of colon cancer cells. In this paper, the significance of anesthetic drugs is proposed, and an artificial neural network algorithm based on artificial intelligence is proposed. It is well known that artificial neural networks play an important role in medicine. The experimental results of this paper show that the incidence of colon cancer in 2020 will be in the range of 5%-35%, and the incidence of colon cancer in 2021 will be in the range of 7%-30%. While colon cancer rates in 2021 do not appear to be as high as colon cancer rates in 2020, they are generally much higher than colon cancer rates in 2020. It can be seen that as the population ages, the number of colon cancer patients is increasing due to the lack of emphasis on health. This also means that the incidence of colon cancer is getting higher and higher, and traditional drug chemotherapy has been unable to play a good role in inhibiting the proliferation of colon cancer cells. Therefore, this paper investigated the effects of anesthetic drugs on the proliferation and apoptosis of human colon cancer cells. [ABSTRACT FROM AUTHOR]

With the gradual expansion of the development of sports, the level of sports has been rapidly improved. Athletes have to carry out high-intensity and systemic technical movements in training and competition. Some sports have the greatest burden on the shoulder joint. From the observation and investigation of the injured parts of athletes, it is found that the shoulder joint is the most common sports injury, which is the most typical sports injury. Based on the problem of insufficient strength and endurance reserve after rehabilitation of shoulder external rotator injury, it will cause muscle tension and poor extensibility. To prove the improvement effect of functional training and posture index calibration on the poor posture of the shoulder, considering the measurement of global passive torque, this paper uses a limited set of joint angles and corresponding passive torque data in the upper arm lifting trajectory to train the neural network and uses the trained network to predict the passive torque in other upper arm trajectories. The kinematics model of the shoulder joint is established, and the human-computer interaction experiment is designed on the platform of the gesture index manipulator. The passive and active torque components of the shoulder joint in the human-computer interaction process are calculated by measuring the man-machine interaction force of the subjects in the motion state, which is used as the basis for evaluating the active motion intention of the subjects. Surface electromyography (SEMG) was used to calibrate and verify the attitude index of shoulder active torque. The method proposed in this paper is helpful to achieve more efficient on-demand assisted rehabilitation training exercises, which is of great significance to improve the level of rehabilitation training. [ABSTRACT FROM AUTHOR]

Aiming at the current problem of insufficient extraction of small retinal blood vessels, we propose a retinal blood vessel segmentation algorithm that combines supervised learning and unsupervised learning algorithms. In this study, we use a multiscale matched filter with vessel enhancement capability and a U-Net model with a coding and decoding network structure. Three channels are used to extract vessel features separately, and finally, the segmentation results of the three channels are merged. The algorithm proposed in this paper has been verified and evaluated on the DRIVE, STARE, and CHASE_DB1 datasets. The experimental results show that the proposed algorithm can segment small blood vessels better than most other methods. We conclude that our algorithm has reached 0.8745, 0.8903, and 0.8916 on the three datasets in the sensitivity metric, respectively, which is nearly 0.1 higher than other existing methods. [ABSTRACT FROM AUTHOR]

The maintenance and sharing of electronic medical records are one of the essential tasks in the medical treatment combination. Traditional cloud-based electronic medical record storage system is difficult to realize data security sharing. The tamper resistance and traceability of blockchain technology provide the possibility for the sharing of highly sensitive medical data. This paper proposes a safe sharing scheme of stroke electronic medical records based on the consortium blockchain. The scheme adopts the storage method of ciphertext of medical records stored in the cloud and index of medical records stored on the blockchain. The privacy protection mechanism proposed in this paper innovatively combines proxy reencryption and searchable encryption which supports patient pseudoidentity search. The mechanism could achieve controllable sharing of medical records and precise search. According to the organizational characteristics of the stroke medical treatment combination, this paper proposes an improved Practical Byzantine Fault Tolerance mechanism to reach a consensus between consensus nodes. Then, the proposed scheme is analyzed and evaluated from three aspects of medical record integrity, user privacy, and data security. The results show that the scheme can not only ensure the privacy of patient identity information and private key data but also resist the tampering and deletion attacks of internal and external malicious nodes on the medical record data. Therefore, the proposed scheme is conducive to the improvement of the timeliness of stroke treatment and the safe sharing of electronic medical records in stroke medical treatment combination. [ABSTRACT FROM AUTHOR]