bluuebunny/crossref_metadata_2025 huggingface dataset:
Substantial adaptive artificial bee colony algorithm implementation for glioblastoma detection
Authors: Ibrahim Shafaf , Fariza Abu Samah Khyrina Airin , Hamzah Raseeda , Mohd Ali Nurul Amira , Aminuddin Raihah
Published: October 2022

Glioblastoma multiforme (GBM) is a high-grade brain tumor that is extremely dangerous and aggressive. Due to its rapid development rate, high-grade cancers require early detection and treatment, and early detection may possibly increase the chances of survival. The current practice of GBM detection is performed by a radiologist; due to the enormous number of cases, it is nevertheless tedious, intrusive, and error-prone. Thus, this study attempted a substantial adaptive artificial bee colony (a-ABC) algorithm implementation in providing a non-invasive approach for GBM detection. The basic statistical intensity-based analysis of minimum (minGL), maximum (maxGL), and mean (meanGL) of grey level data was employed to investigate the GBM's feature properties. The a-ABC's performance for adaptive GBM detection identification was evaluated using T1-weighted (T1), T2-weighted (T2), fluid attenuated inversion recovery (FLAIR), and T1-contrast (T1C) which are four different magnetic resonance imaging (MRI) imaging sequences. Hundred and twenty MRI of GBM images were assessed in total, with 30 images per imaging sequence. The overall mean of GBM detection accuracy percentage was 93.67%, implying that the proposed a-ABC algorithm is capable of detecting GBM brain tumors. Other feature extraction strategies, on the other hand, may be added in the future to enhancee the performance of feature extraction. 
A novel automated deep learning approach for Alzheimer's disease classification
Authors: Aparna Mudiyala , Rao Battula Srinivasa
Published: October 2022

Alzheimer's disease is a degenerative brain illness, incurable and progressive. Globally for every two seconds, someone is affected by Alzheimer's disease. Alzheimer's disease in the elderly is difficult to diagnose due to the complexity of the brain structure. Its pixel intensity is similar and systematic distinction is necessary. Deep learning has inspired a lot of interest in recent years in tackling challenges in a variety of fields, including medical imaging. One of the drawbacks of deep learning approach is the inability to detect changes in functional connectivity in MCI (mild cognitive impairment) patients' functional brain networks. In this paper, we utilize deep features extracted from two pre-trained deep learning models to tackle this issue. The proposed models DenseNet121 and MobileNetV2 is used to perform the task of Alzheimer's disease multi-class classification. In this method, initially we increased 70 % of dataset and generated images by using CycleGAN (generative adversarial networks). We achieved 98.82% of accuracy with proposed models. It gives best results compared to existing models.
Comparative evaluation for detection of brain tumor using machine learning algorithms
Authors: Kareem Shahab Wahhab , Abdulrahman Bikhtiyar Friyad , Hawezi Roojwan Sc. , Khoshaba Farah Sami , Askar Shavan , Muheden Karwan Muhammed , Abdulkhaleq Ibrahim Shamal
Published: October 2022

Automated flaw identification has become more important in medical imaging. For patient preparation, unaided prediction of tumor (brain) detection in the magnetic resonance imaging process (MRI) is critical. Traditional ways of recognizing z are intended to make radiologists' jobs easier. The size and variety of molecular structures in brain tumors is one of the issues with MRI brain tumor diagnosis. Deep learning (DL) techniques (artificial neural network (ANN), naive Bayes (NB), multi-layer perceptron (MLP)) are used in this article to detect brain cancers in MRI data. The preprocessing techniques are used to eliminate textural features from the brain MRI images. These characteristics are then utilized to train a machine-learning system.
Performance analysis of cooperative spectrum sensing using double dynamic threshold
Authors: Chaudhary Neha , Mahajan Rashima
Published: October 2022

Increased use of wireless technologies and in turn more utilization of available spectrum is subsequently leading to the increasing demand for wireless spectrum. This research work incorporates spectrum sensing detection consisting of a double dynamic threshold followed by cooperative type spectrum sensing. The performance has been analyzed using two modulation schemes, quadrature-amplitude-modulation (QAM) & binary-phase-shift-keying (BPSK). Improved probability of detection has been witnessed using the double dynamic threshold where a comparison of average values of local decision (LD) and the observed value of energy (EO) has been considered instead of using direct values of local decisions and energy. Further, the probability-of-detection ( ) is found to be better with QAM as compared to the BPSK. From the results, it has been observed that the detection of primary users is also affected by the number of samples. The simulation environment considered for this work is MATLAB and the performance of cooperative spectrum sensing for 500 and 1000 samples with -9db and -12 SNR by considering different false alarm values i. e 0.1,0.3 and 0.5 has been analyzed. The further scope shall be to enhance the primary user detection by considering different QAM schemes and different SNRs.
Improvement of transformer dissolved gas analysis interpretation using j48 decision tree model
Authors: Bakar Norazhar Abu , Chairul Imran Sutan , Ghani Sharin Ab , Ahmad Khiar Mohd Shahril , Che Wanik Mohd Zamri
Published: October 2022

Dissolved gas analysis (DGA) is widely accepted as an effective method to detect incipient faults within power transformers. Gases such as hydrogen, methane, acetylene, ethylene and ethane are normally utilized to identify the transformer fault conditions. Several techniques have been developed to interpret DGA results such as the key gas method, Doernenburg, Rogers, IEC ratio-based methods, Duval Triangles, and the latest Duval Pentagon methods. However, each of these approaches depends on the experts' shared knowledge and experience rather than quantitative scientific methods, therefore different diagnoses may be reported for the same oil sample. To overcome these shortcomings, this paper proposed the use of decision tree method to interpret the transformer health condition based on DGA results. The proposed decision tree model employed three main fault gases; methane, acetylene, ethylene as inputs, and classified the transformer into eight fault conditions. The J48 algorithm is used to train and developed the decision tree model. The performance of the proposed model is validated with the pre-known condition of transformers and compared with the Duval Triangle method. Results show that the proposed model delivers better precision and accuracy in predicting transformer fault conditions compared to DTM with 81% and 69% respectively.
Automated COVID-19 misinformation checking system using encoder representation with deep learning models
Authors: Taha Mohamed , Zayed Hala H. , Azer Marina , Gadallah Mahmoud
Published: October 2022

Social media impacts society whether these impacts are positive or negative, or even both. It has become a key component of our lives and a vital news resource. The crisis of covid-19 has impacted the lives of all people. The spread of misinformation causes confusion among individuals. So automated methods are vital to detect the wrong arguments to prevent misinformation spread. The covid-19 news can be classified into two categories: false or real. This paper provides an automated misinformation checking system for the covid-19 news. Five machine learning algorithms and deep learning models are evaluated. The proposed system uses the bidirectional encoder representations from transformers (BERT) with deep learning models. detecting fake news using BERT is a fine-tuning. BERT achieved accuracy (98.83%) as a pre-trained and a classifier on the covid-19 dataset. Better results are obtained using BERT with deep learning models (LSTM), which achieved accuracy (99.1%). The results achieved improvements in the area of fake news detection. Another contribution of the proposed system allows users to detect claims' credibility. It finds the most related real news from experts to the fake claims and answers any question about covid-19 using the universal-sentence-encoder model.
Forecasting the number of dengue fever based on weather conditions using ensemble forecasting method
Authors: Nabilah Mursyidatun , Tyasnurita Raras , Mahananto Faizal , Anggraeni Wiwik , Vinarti Retno Aulia , Muklason Ahmad
Published: October 2022

Dengue fever is still a crucial public health problem in Indonesia, with the highest fatality rate (CFR) is 1.01% in East Java, Malang Regency. One of the solutions to control the death rate and cases is to forecast the cases number. This study proposed ensemble forecasting that build from several penalized regressions. Penalized regressions are able to overcome linear regression analysis’ shortcomings by using penalty values, that will affect regression’s coefficient, resulting on regression model with a slight bias in order to reduce parameter estimations and prediction values' variances. Penalized regressions are evaluated and built as ensemble forecasting method to minimize the shortcomings of other existing model, so it could produce more accurate values comparing to single penalized regression model. The result showed that the ensemble model `consists of smoothly clipped absolute deviation (SCAD) and Elastic-net is sufficient to capture data patterns with root mean squared error (RMSE) 6.38. 
K-nearest neighbor based facial emotion recognition using effective features
Authors: Subudhiray Swapna , Palo Hemanta Kumar , Das Niva
Published: October 2022

In this paper, an experiment has been carried out based on a simple k-nearest neighbor (kNN) classifier to investigate the capabilities of three extracted facial features for the better recognition of facial emotions. The feature extraction techniques used are histogram of oriented gradient (HOG), Gabor, and local binary pattern (LBP). A comparison has been made using performance indices such as average recognition accuracy, overall recognition accuracy, precision, recall, kappa coefficient, and computation time. Two databases, i.e., Cohn-Kanade (CK+) and Japanese female facial expression (JAFFE) have been used here. Different training to testing data division ratios is explored to find out the best one from the performance point of view of the three extracted features, Gabor produced 94.8%, which is the best among all in terms of average accuracy though the computational time required is the highest. LBP showed 88.2% average accuracy with a computational time less than that of Gabor while HOG showed minimum average accuracy of 55.2% with the lowest computation time.
Neural network-based parking system object detection and predictive modeling
Authors: El Khatib Ziad , Mnaouer Adel Ben , Moussa Sherif , Mashaal Omar , Ismail Nor Azman , Bin Abas Mohd Azman , Abdulgaleel Fuad
Published: October 2022

A neural network-based parking system with real-time license plate detection and vacant space detection using hyper parameter optimization is presented. When number of epochs increased from 30, 50 to 80 and learning rate tuned to 0.001, the validation loss improved to 0.017 and training object loss improved to 0.040. The model mean average precision mAP_0.5 is improved to 0.988 and the precision is improved to 99%. The proposed neural network-based parking system also uses a regularization technique for effective predictive modeling. The proposed modified lasso ridge elastic (LRE) regularization technique provides a 5.21 root mean square error (RMSE) and an R-square of 0.71 with a 4.22 mean absolute error (MAE) indicative of higher accuracy performance compared to other regularization regression models. The advantage of the proposed modified LRE is that it enables effective regularization via modified penalty with the feature selection characteristics of both lasso and ridge.
Human emotion detection and classification using modified viola-jones and convolution neural network
Authors: Karilingappa Komala , Jayadevappa Devappa , Ganganna Shivaprakash
Published: October 2022

Facial expression is a kind of nonverbal communication that conveys information about a person's emotional state. Human emotion detection and recognition remains a major task in computer vision (CV) and artificial intelligence (AI). To recognize and identify the many sorts of emotions, several algorithms are proposed in the literature. In this paper, the modified Viola-Jones method is introduced to provide a robust approach capable of detecting and identifying human feelings such as angerness,sadness, desire, surprise, anxiety, disgust, and neutrality in real-time. This technique captures real-time pictures and then extracts the characteristics of the facial image to identify emotions very accurately. In this method, many feature extraction techniques like gray-level co-occurrence matrix (GLCM), linear binary pattern (LBP) and robust principal components analysis (RPCA) are applied to identify the distinct mood states and they are categorized using a convolution neural network (CNN) classifier. The obtained outcome demonstrates that the proposed method outperforms in terms of determining the rate of emotion recognition as compared to the current human emotion recognition techniques.
A deep learning based stereo matching model for autonomous vehicle
Authors: Deepa Deepa , Kupparu Jyothi
Published: October 2022

Autonomous vehicle is one the prominent area of research in computer vision. In today’s AI world, the concept of autonomous vehicles has become popular largely to avoid accidents due to negligence of driver. Perceiving the depth of the surrounding region accurately is a challenging task in autonomous vehicles. Sensors like light detection and ranging can be used for depth estimation but these sensors are expensive. Hence stereo matching is an alternate solution to estimate the depth. The main difficulties observed in stereo matching is to minimize mismatches in the ill-posed regions, like occluded, texture less and discontinuous regions. This paper presents an efficient deep stereo matching technique for estimating disparity map from stereo images in ill-posed regions. The images from Middlebury stereo data set are used to assess the efficacy of the model proposed. The experimental outcome dipicts that the proposed model generates reliable results in the occluded, texture less and discontinuous regions as compared to the existing techniques.
Boosting auxiliary task guidance: a probabilistic approach
Authors: Al Hasib Irfan Mohammad , Sultana Sumaiya Saima , Nyeen Imrad Zulkar , Sabur Muhammad Abdus
Published: October 2022

This work aims to introduce a novel approach for auxiliary task guidance (ATG). In this approach, our goal is to achieve effective guidance from a suitable auxiliary task by utilizing the uncertainty in calculated gradients for a mini-batch of samples. Our method calculates a probabilistic fitness factor of the auxiliary task gradient for each of the shared weights to guide the main task at every training step of mini-batch gradient descent. We have shown that this proposed factor incorporates task specific confidence of learning to manipulate ATG in an effective manner. For studying the potency of the method, monocular visual odometry (VO) has been chosen as an application. Substantial experiments have been done on the KITTI VO dataset for solving monocular VO with a simple convolutional neural network (CNN) architecture. Corresponding results show that our ATG method significantly boosts the performance of supervised learning for VO. It also out performs state-of-the-art (SOTA) auxiliary guided methods we applied for VO. The proposed method is able to achieve decent scores (in some cases competitive)compared to existing SOTA supervised monocular VO algorithms, while keeping an exceptionally low parameter space in supervised regime.
Pseudophaeocytostroma bambusicola gen. et sp. nov. (Diaporthaceae) from bamboo in Yunnan, P.R. China
Authors: MONKAI JUTAMART , PHOOKAMSAK RUNGTIWA , XU SHENG , XU JIANCHU , MORTIMER PETER E. , KARUNARATHNA SAMANTHA C. , SUWANNARACH NAKARIN , LUMYONG SAISAMORN
Published: November 2022

Phaeocytostroma species (Diaporthaceae, Diaporthales, Sordariomycetes) are mainly associated with grasses (Poaceae) and are considered important pathogens of maize and sugarcane. In the present study, a phaeocytostroma-like taxon was collected from bamboo culms in Yunnan, China and characterized using morphological and multigene phylogenetic analyses. The fungus was characterized by uni- to bi-locular conidiomata, papillate ostioles, septate, filiform paraphyses and brown, oblong to ellipsoid, aseptate, conidia, with obtuse ends. Phylogenetic analyses inferred from the combined dataset of ITS, LSU, and TEF1-α regions showed that the phaeocytostroma-like taxon constituted an independent lineage clustered with P. sacchari distant from Phaeocytostroma sensu stricto. Hence, the novel genus Pseudophaeocytostroma is introduced to accommodate the new species Ps. bambusicola. Pseudophaeocytostroma bambusicola clustered with P. sacchari strains CBS 275.34, km-1, UMICH-1, 135 in the present phylogenetic analyses. However, these strains are not the ex-type strains of P. sacchari and some of them lack morphological descriptions and remain unpublished. Therefore, we treat these strains as Ps. “sacchari” herein until the type strain of P. sacchari is verified. The pairwise nucleotide comparison of ITS and TEF1-α sequence data and a pairwise homoplasy index test between Ps. bambusicola and Ps. “sacchari” provided further evidence to support Ps. bambusicola as a distinct species. The morphological characteristics and phylogenetic relationship of Ps. bambusicola and other related Phaeocytostroma species are also compared and discussed.
Two new species, Parabathylaimus gracilis sp. nov. and Belbolla sinica sp. nov. (Nematoda: Enoplida), from Yangma Island of the Yellow Sea, China
Authors: WANG MENGNA , GUO WEN , WANG CHUNMING
Published: October 2022

Two new species Parabathylaimus gracilis sp. nov. and Belbolla sinica sp. nov. are described from Yangma Island, Yellow Sea. Parabathylaimus gracilis sp. nov. is characterized by six outer labial setae three-jointed, inner labial setae and cephalic setae unjointed, amphidial fovea unispiral with circular aperture and positioned at middle of buccal cavity, spicules paired and slightly curved, gubernaculum kidney-like and distal end heavily cuticularized with a pointed projection, tail conical without long subterminal setae. Belbolla sinica sp. nov. is characterized by short body length, posterior pharynx region with seven bulbs, spicules straight with proximal and distal end tapered and middle part thickened, gubernaculum short without apophysis, two small wing-shaped precloacal supplements well developed, tail conico-cylindrical with cylindrical portion short.
Description of a new species of the Anthaxia (Anthaxia) glabrifrons species-group from Morocco (Coleoptera: Buprestidae: Anthaxiini)
Authors: OBOŘIL MARTIN , BAŇAŘ PETR
Published: October 2022

Anthaxia (Anthaxia) rejzeki sp. nov. belonging to the Anthaxia (Anthaxia) glabrifrons species-group from Morocco is described, illustrated and compared to other species of the group.
Immature stages, new host plant records and shelter structures of Troyus phyllides (Röber, 1925) and Thoon ponka Evans, 1955 in the Peruvian Amazon (Lepidoptera: Hesperiidae: Hesperiinae: Hesperiini)
Authors: DUERR NATHAN , CORAHUA-ESPINOZA THALIA , BAINE QUINLYN , TEJEIRA RAFAEL , CCAHUANA RODRIGO , CASTILLO ESPINOZA MARÍA MERCEDES DEL , PERLETT ERIC , CERVANTES-MARTÍNEZ JOSELIN NIDIA , SANTILLANA ALEXANDRA LIZA , SEE JOSEPH , SOTO-QUISPE YULISA SARI , WOOD HALLE , ARTEAGA ZUNILDA ESCALANTE , GALLICE GEOFFREY
Published: October 2022

We describe here for the first time the complete immature life cycles and shelter structures of two Neotropical skipper butterflies in the subtribe Moncina, Troyus phyllides (Röber, 1925) and Thoon ponka Evans 1955, along with new natural host plant records for these species at Finca Las Piedras, Madre de Dios, Peru. Four eggs and a preantepenultimate larva of T. phyllides, as well as three eggs of Thoon ponka were collected in nature and each passed through five larval instars to adulthood. Troyus phyllides fed on a herbaceous species, Lasiacis ligulata Hitchcock & Chase (Poaceae: Panicoideae: Paniceae), while T. ponka fed on two congeneric herbaceous bamboo species, Pariana lunata Nees and Pariana sp. (Poaceae: Bambusoideae: Olyreae). We present photos of all immature stages and host plants, as well as illustrations of the shelter structures and the head capsules for each of these two species.
New genus and new combination of Deltocephalinae (Insecta: Hemiptera: Cicadellidae)
Authors: CAMISÃO BEATRIZ M. , DIETRICH CHRISTOPHER H.
Published: October 2022

Based on study of the holotype of Scaphytopius (Tumeus) rubidus DeLong, 1980, it was determined that this species does not belong in any genus of the subfamily Deltocephalinae described so far. To accommodate this species, we describe and illustrate a new genus in the tribe Bahitini, Anavilhanas gen. nov., and propose the new combination, Anavilhanas rubida (DeLong) comb. nov.
Integrative redescription of the enigmatic monotypic alpine pill millipede genus Simplomeris Verhoeff, 1936 (Glomerida, Glomeridae, Haploglomerinae)
Authors: WESENER THOMAS
Published: November 2022

The European pill millipedes (Glomerida) are especially rich in species and genera of enigmatic status, which have been neither reviewed nor revised since more than 70 years. One of these genera is Simplomeris Verhoeff, 1936 with its single species S. montivaga (Faës, 1902), a high-altitude endemic only known from <5 collection events in the Simplon Valley and the Aletsch Glacier, southern Switzerland. Being one of only a handful of genera in the subfamily Haploglomerinae, distributed in Europe and SE Asia, its morphology is of greater interest in a future phylogenetic sorting of the Glomerida. Fresh material, which was encountered by the author 10 years ago from both known localities, allows here a redescription of this rarely encountered genus. Aside from the first photograph of a living specimen, scanning electron microscopy and genetic barcoding of the COI gene have been conducted. Morphologically, the telopods of Simplomeris resemble those of Haploglomeris Verhoeff, 1906 from the eastern Alps and confirm the present position in the Haploglomerinae. Genetically, Simplomeris belongs to the Glomeris klugii Brandt, 1833 species-group and is particularly close to high-altitude endemics from the southwestern and Bergamasque Alps, especially G. primordialis Verhoeff, 1930, G. transalpina Koch, 1836, and G. oropensis Verhoeff, 1934. Genetic barcoding data confirm the three colour varieties of S. montivaga, S. montivaga var. montivaga Verhoeff, 1936 syn. nov., S. montivaga var. simplonensis Verhoeff, 1936: syn. nov., S. montivaga var. berisalensis Verhoeff, 1936 syn. nov. to be just that, and all three are formally synonymized under S. montivaga.
Improving plasmonic photodetector based on ITO/TiO2/Ag configuration and roughened interface
Authors: Xiao Long , Yan Shancheng , Chen Tianhong , Wang Junzhuan , Shi Yi
Published: October 2022

In this work, plasmonic photodetector based on ITO/TiO2/Ag grating configuration specially with nano-scale roughened interface is proposed to achieve high photoresponsivity, in which hot-electron are effectively excited by taking advantages of the narrow distribution of excitation
energy in Ag and the high density of states in TiO2 conduction band. Simultaneously, a roughened structure is introduced at Ag/TiO2 interface to alleviate the momentum mismatch of hot-electron. The influences of the grating structures on incident light absorption and
hot-electron excitation are simulated by using finite-difference time-domain method. The thicknesses of both metallic Ag and spacer layers modulate the absorption characteristics, and the introduction of the nano-scale roughened interface does not have effect obviously on the absorptivity
and response wavelength. The present work provides a valuable guidance in the fields of interface design and structure optimization of high-efficiency plasmonic photodetectors.
Synthesis, anti-inflammatory and analgesia activities of diclofenac and their derivatives
Authors: Li Guiying , Kim Thaesong , Huang Runxia , Hu Dingyuan , Shi Shucong , Wang Han
Published: October 2022

Diclofenac potassium was synthesized from aniline and chloroacetyl chloride. The reaction of diclofenac potassium with calcium sulphate dihydrate and ammonium sulphate yielded diclofenac calcium and diclofenac ammonium, respectively. After diclofenac potassium was acidized with hydrochloride,
the esterification of attained diclofenac with absolute methanol and absolute ethanol yielded compounds diclofenac methyl ester and diclofenac ethyl ester, respectively. Among the five compounds, diclofenac calcium and diclofenac ammonium are new compounds, and their synthetic methods have
not been reported in the world. Every synthesized compound and intermediate were measured their 1H-NMR, 13C-NMR spectra. Analgesic activity of the target compounds was screened using acetic acid writhing test of mice and anti-inflammatory activity of the compounds was
tested by xylene-induced ear swelling of mice. The results showed that all the 5 compounds had strong analgesic activity and anti-inflammatory activity. Among them, diclofenac methyl ester is the strongest, its analgesic and anti-inflammatory effects were stronger than the clinical use of
diclofenac potassium.
Molecular mechanism of new type of lipid nanoparticles on gastric carcinoma by autophagy and apoptosis of caspase family being targeted with miR-199a-3p
Authors: Chen Lu , Wan Lu , Cao Yan , Cheng Si , Cha Huolong
Published: October 2022

This study assesses the molecular mechanism of new type of lipid nanoparticles on gastric carcinoma by autophagy and apoptosis of Caspase family being targeted with miR-199a-3p. Gastric carcinoma tissue was set as observation group while tissue from two centimeters of gastric carcinoma
was set as control group. miR-199a-3p and Caspase3 expression was detected with RT-PCR. Proliferative and apoptotic activity was detected with 3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide (MTT) and flow cytometry (FCM), while the quantity of invasion and migration were detected
with Transwell. The presentation quantity of miR-199a-3p in test group was elevated notably compared with control group. There was a negative regulation between and Caspase 3. The cellular infiltration of gastric carcinoma was notably reduced with Caspase3 nanoparticles being targeted by transfection
of miR-199a-3p. Gastric carcinoma growth rate in test group was reduced when miR-199a-3p level was interfered with si-RNA. The apoptosis could be reduced if there was over presentation of miR-199a-3p. Cell invasive and metastatic activity was notably reduced by the Caspase3 nanoparticles being
targeted by transfection of si-miR-199a-3p. The invasive and metastatic activity of gastric carcinoma was prompted with increased expression of Caspase3 and reduced miR-199a-3p expression. Cell behaviors were effectively enhanced by directed nanoparticles.
A simple label-free electrochemical aptamer sensor for detection of Hg2+ based on black phosphorus
Authors: Zhou Jie , Wei Dan , Hu Changchun , Li Shuo , Ma Liang , Chen Zhu , Deng Yan
Published: October 2022

In this work, a simple label-free aptamer-based electrochemical sensor was developed for determination of mercury ions (Hg2+) by polylysine (PLL) modified black phosphorus nanosheets (BP) and gold nanoparticles (AuNPs) as signal amplification strategy. The PLL-BP composite
materials greatly improved electron transfer speed and electrochemical behavior of electrode in the detection of analytes. AuNPs can amplify the electrochemical signal and facilitate the binding of aptamers to the electrode. The selected aptamer (Apt) can bind specifically to Hg2+
to form a T-Hg2+-T structure, which we used to detect Hg2+. Experimental results showed that the prepared electrochemical aptamer sensor exhibited wide linear range from 1.0–500 nM, along with a low detection limit of 0.14 nM. Moreover, the electrochemical aptamer
sensor has good specificity, stability, and repeatability. Therefore, this proposed electrochemical aptamer sensor provide a simple and sensitive method for the detection of Hg2+, which is expected to be used for the detection of trace amounts of Hg2+ in actual samples.
Isolation, culture and identification of SD rat bone marrow mesenchymal stem cells in tissue engineering
Authors: Ni Xiaohui , Zhao Quanming , Zhou Feng , Pan Xiaoyun , Zhao Gang , Zhu Xingyuan , Ren Liubao , Yu Jiong , Cai Baisheng , Mi Jingyi
Published: October 2022

Seed cells are an important part of bone tissue engineering. In this study, we investigated methods for the isolation, culture and identification of rat bone marrow mesenchymal stem cells (BMSCs) in vitro. BMSCs from SD rats were isolated and cultured using the whole bone marrow
adherent method. Morphological observation and flow cytometry were used for the detection of cell surface markers. The osteogenic and adipogenic differentiation of cultured cells was induced and evaluated. BMSCs could be effectively isolated and purified using the whole bone marrow adherent
method. The primary BMSCs cultured in vitro formed spindle-shaped, spiral and vigorous cell colonies. The flow cytometry results showed that CD90 was highly expressed on the cell surface, but CD34 and CD45 were not expressed. After culture in osteogenic and adipogenic induction medium,
positive Alizarin Red and Oil Red O staining was observed, indicating the potential for multidirectional differentiation. The whole bone marrow adherent method is simple and practical, which makes the isolation, culture and amplification of BMSCs in vitro easy, and the method has little
effect on cell activity and is an effective method for obtaining high-purity BMSCs.
Effect of astragalus polysaccharide nanoliposomes on lipid metabolism and insulin resistance in pregnant rats with gestational diabetes by regulating AMPK pathway via protein-tyrosine phosphatase 1B inhibition
Authors: Xu Wen , Shen Haichuan , Chen Haixia , Chu Chu , Zhao Mingliang , Meng Qian
Published: October 2022

Gestational diabetes mechanism is related to lipid metabolism and insulin resistance, but its mechanism of action still needs to be explored. Whether the mechanism for astragalus polysaccharides in the treatment of gestational diabetes is related to the above factors is worth studying.
100 SD rats were in this study selected, in which 10 were set in the control group, and the rest were separated into groups, namely; positive control group, model group, low-dose group, middle-dose group, and high-dose group with 10 rats each. AMP-activated protein kinase (AMPK) pathway inhibitor
group (inhibitor group) and AMPK pathway agonist group (agonist group) were then set respectively. In the model group, Adiponectin (APN), superoxide dismutase (SOD), insulin resistance index (ISI), high-density lipoprotein (HDL) and p-AMPK were lowest, and TNF-a, Leptin, MDA, TG, TC, LDL,
FBG, FINS, IS, IRI, and protein-tyrosine Phosphatase 1B (PTP1B) expressions were highest. The APN, SOD, HDL levels, ISI index, and p-AMPK from the control group were highest, while the positive control group had lower p-AMPK expression. TNF-a, Leptin, MDA, TG, TC, LDL levels, FBG, and expressions
of FINS, IS index, IRI index, and PTP1B were lowest (p < 0.05). The model group, agonist p-AMPK expression, HDL level, ISI index were lowest. PTP1B, TG, TC, LDL level, IS, IRI index expressions were the highest; while the control group, inhibitor group p-AMPK expression, HDL level,
ISI index were highest. The PTP1B expression, TG, TC, LDL levels, IS, and IRI index were the lowest, while the positive control group had low expression of p-AMPK. Astragalus polysaccharides can therefore promote AMPK phosphorylation by inhibiting the expression of PTP1B protein to reduce
insulin resistance and improve lipid metabolism.
Neither Withdrawal nor Resistance: Adapting to Increased Repression in China
Authors: O’Brien Kevin J.
Published: October 2022

As repression grows in China, some pastors, lawyers, and nongovernmental organizations (NGOs) are neither resisting it nor withdrawing from the public sphere, but instead are finding ways to adapt. Coping strategies include the following: being transparent about their activities and maintaining close communication with the authorities; cultivating allies in the government and giving credit to officials for their achievements; keeping the size of their organizations nonthreatening and consenting to a heightened party presence; staying a safe distance from “red lines” and focusing on less controversial issues; encouraging their constituents to accept compromises and government priorities; distancing themselves from activists who speak out against restrictions; shedding connections with foreign countries; and arguing that loyalty and moderation are the best means to make progress. The hope is that cooperation and exhibiting an understanding view of the Chinese Communist Party’s motives will preserve space to operate and suggest a path toward long-term coexistence. Accommodating pastors, lawyers, and NGOs take the regime as a given and work with the state rather than against it. By doing so, they retain some agency, even as deepening authoritarianism blurs the line between accommodation and co-optation. Potentially restive professionals are directed away from activities and ways of thinking that the authorities do not like and toward organizing themselves and acting in a manner that is deemed acceptable. They learn to avoid confrontation while they are steered to a safe place and rewarded (or at least tolerated) if they stay there.
Genome-wide analysis of polyamine biosynthesis genes in wheat reveals gene expression specificity and involvement of STRE and MYB-elements in regulating polyamines under drought
Authors: Ebeed Heba Talat
Published: October 2022

Background

Polyamines (PAs) are considered promising biostimulants that have diverse key roles during growth and stress responses in plants. Nevertheless, the molecular basis of these roles by PAs has not been completely realized even now, and unfortunately, the transcriptional analyses of the biosynthesis pathway in various wheat tissues have not been investigated under normal or stress conditions. In this research, the findings of genome-wide analyses of genes implicated in the PAs biosynthesis in wheat (ADC, Arginine decarboxylase; ODC, ornithine decarboxylase; AIH, agmatine iminohydrolase; NPL1, Nitrlase like protein 1; SAMDC, S-adenosylmethionine decarboxylase; SPDS, spermidine synthase; SPMS, spermine synthase and ACL5, thermospermine synthase) are shown.

Results

In total, thirty PAs biosynthesis genes were identified. Analysis of gene structure, subcellular compartmentation and promoters were discussed. Furthermore, experimental gene expression analyses in roots, shoot axis, leaves, and spike tissues were investigated in adult wheat plants under control and drought conditions. Results revealed structural similarity within each gene family and revealed the identity of two new motifs that were conserved in SPDS, SPMS and ACL5. Analysis of the promoter elements revealed the incidence of conserved elements (STRE, CAAT-box, TATA-box, and MYB TF) in all promoters and highly conserved CREs in >80% of promoters (G-Box, ABRE, TGACG-motif, CGTCA-motif, as1, and MYC). The results of the quantification of PAs revealed higher levels of putrescine (Put) in the leaves and higher spermidine (Spd) in the other tissues. However, no spermine (Spm) was detected in the roots. Drought stress elevated Put level in the roots and the Spm in the leaves, shoots and roots, while decreased Put in spikes and elevated the total PAs levels in all tissues. Interestingly, PA biosynthesis genes showed tissue-specificity and some homoeologs of the same gene family showed differential gene expression during wheat development. Additionally, gene expression analysis showed that ODC is the Put biosynthesis path under drought stress in roots.

Conclusion

The information gained by this research offers important insights into the transcriptional regulation of PA biosynthesis in wheat that would result in more successful and consistent plant production.
Population genetic analyses inferred a limited genetic diversity across the pvama-1 DI domain among Plasmodium vivax isolates from Khyber Pakhtunkhwa regions of Pakistan
Authors: Ullah Ibrar , Afridi Sahib Gul , Israr Muhammad , Khan Hizbullah , Shams Sulaiman , Zaib Komal , Le Huong Giang , Kang Jung-Mi , Na Byoung-Kuk , Khan Asifullah
Published: October 2022

Background

Plasmodium vivax apical membrane antigen-1 (pvama-1) is an important vaccine candidate against Malaria. The genetic composition assessment of pvama-1 from wide-range geography is vital to plan the antigen based vaccine designing against Malaria.

Methods

The blood samples were collected from 84 P. vivax positive malaria patients from different districts of Khyber Pakhtunkhwa (KP) province of Pakistan. The highly polymorphic and immunogenic domain-I (DI) region of pvama-1 was PCR amplified and DNA sequenced. The QC based sequences raw data filtration was done using DNASTAR package. The downstream population genetic analyses were performed using MEGA4, DnaSP, Arlequin v3.5 and Network.5 resources.

Results

The analyses unveiled total 57 haplotypes of pvama-1 (DI) in KP samples with majorly prevalent H-14 and H-5 haplotypes. Pairwise comparative population genetics analyses identified limited to moderate genetic distinctions among the samples collected from different districts of KP, Pakistan. In context of worldwide available data, the KP samples depicted major genetic differentiation against the Korean samples with Fst = 0.40915 (P-value = 0.0001), while least distinction was observed against Indian and Iranian samples. The statistically significant negative values of Fu and Li’s D* and F* tests indicate the evidence of population expansion and directional positive selection signature. The slow LD decay across the nucleotide distance in KP isolates indicates low nucleotide diversity. In context of reference pvama-1 sequence, the KP samples were identified to have 09 novel non-synonymous single nucleotide polymorphisms (nsSNPs), including several trimorphic and tetramorphic substitutions. Few of these nsSNPs are mapped within the B-cell predicted epitopic motifs of the pvama-1, and possibly modulate the immune response mechanism.

Conclusion

Low genetic differentiation was observed across the pvama-1 DI among the P. vivax isolates acquired from widespread regions of KP province of Pakistan. The information may implicate in future vaccine designing strategies based on antigenic features of pvama-1.
Tertiary lymphoid structures associate with improved survival in early oral tongue cancer
Authors: Almangush Alhadi , Bello Ibrahim O. , Elseragy Amr , Hagström Jaana , Haglund Caj , Kowalski Luiz Paulo , Nieminen Pentti , Coletta Ricardo D. , Mäkitie Antti A. , Salo Tuula , Leivo Ilmo
Published: October 2022

Background

The clinical significance of tertiary lymphoid structures (TLSs) is not well-documented in early oral tongue squamous cell carcinoma (OTSCC).

Methods

A total of 310 cases of early (cT1-2N0) OTSCC were included in this multicenter study. Assessment of TLSs was conducted on hematoxylin and eosin-stained sections. TLSs were assessed both in the central part of the tumor and at the invasive front area.

Results

The presence of TLSs associated with improved survival of early OTSCC as presented by Kaplan–Meier survival analyses for disease-specific survival (P = 0.01) and overall survival (P = 0.006). In multivariable analyses, which included conventional prognostic factors, the absence of TLSs associated with worse disease-specific survival with a hazard ratio (HR) of 1.96 (95% CI 1.09–3.54; P = 0.025) and poor overall survival (HR 1.66, 95% CI 1.11–2.48; P = 0.014).

Conclusion

Histological evaluation of TLSs predicts survival in early OTSCC. TLSs showed superior prognostic power independent of routine WHO grading and TNM staging system.
The temporal trend of cause-specific mortality: comparing Estonia and Lithuania, 2001 – 2019
Authors: Tran Alexander , Stoppel Relika , Jiang Huan , Kim Kawon Victoria , Lange Shannon , Petkevičienė Janina , Radišauskas Ričardas , Štelemėkas Mindaugas , Telksnys Tadas , Zafar Anush , Rehm Jürgen
Published: October 2022

Background

Despite being two Baltic countries with similar histories, Estonia and Lithuania have diverged in life expectancy trends in recent years. We investigated this divergence by comparing cause-specific mortality trends.

Methods

We obtained yearly mortality data for individuals 20 + years of age from 2001–2019 (19 years worth of data) through Statistics Lithuania, the Lithuanian Institute for Hygiene, and the National Institute for Health Development (Estonia). Using ICD-10 codes, we analyzed all-cause mortality rates and created eight major disease categories: ischemic heart disease, cerebrovascular disease, all other cardiovascular disease, cancers (neoplasms), digestive diseases, self-harm and interpersonal violence, unintentional injuries and related conditions, and other mortality (deaths per 100,000 population). We used joinpoint regression analysis, and analyzed the proportional contribution of each category to all-cause mortality.

Results

There was a steeper decline in all-cause mortality in Estonia (average annual percent change, AAPC = -2.55%, 95% CI: [-2.91%, -2.20%], P < .001) as compared to Lithuania (AAPC = -1.26%, 95% CI: [-2.18%, -0.57%], P = .001). For ischemic heart disease mortality Estonia exhibited a relatively larger decline over the 19-year period (AAPC = -6.61%, 95% CI: [-7.02%, -6.21%], P < .001) as compared to Lithuania (AAPC = -2.23%, 95% CI: [-3.40%, -1.04%], P < .001).

Conclusion

Estonia and Lithuania showed distinct mortality trends and distributions of major disease categories. Our findings highlight the role of ischemic heart disease mortality. Differences in public health care, management and prevention of ischemic heart disease, alcohol control policies may explain these differences.
Evaluating and rating HIV/AIDS mobile apps using the feature-based application rating method and mobile app rating scale
Authors: Raeesi Ahmad , Khajouei Reza , Ahmadian Leila
Published: October 2022

Background

The purpose of this study was to evaluate HIV/AIDS mobile applications using the Mobile App Rating Scale (MARS) and rate the features of these applications using the new tool called the Feature-based Application Rating Method (FARM).

Methods

In this study, all available HIV/AIDS apps in Iran from Cafe Bazaar and Google Play Store due to inclusion criteria were studied. The evaluation of the quality of applications was done using the MARS tool and the FARM tool. The FARM, which was developed in this study, was applied to rank the features of the applications.

Results

In this study, 79 applications were included. The mean score of all apps using both tools was 3.58 (SD = 0.95) out of 5. The overall mean quality score based on the MARS was 3.14 (SD = 0.84), and the mean score of features based on FARM was 3.81 (SD = 1.23). This study showed a higher than moderate correlation between the scores assigned to apps based on the MARS and FARM tools (r > 0.4).

Conclusions

The HIV/AIDS mobile applications available in Iran had the "acceptable" ranking. Also, our study results showed that to evaluate mobile apps, using a single tool may not provide good insight to evaluators about the assessed apps. However, using more than one tool may provide more details about the evaluated apps. To improve the quality of mobile health apps and help users select the most desirable app, we suggested using tools like FARM for ranking apps based on the features of each app in the app stores.
An electronic pillbox intervention designed to improve medication safety during care transitions: challenges and lessons learned regarding implementation and evaluation
Authors: Shahani Amrita , Nieva Harry Reyes , Czado Katie , Shannon Evan , Gaetani Raquel , Gresham Marcus , Garcia Jose Cruz , Ganesan Hareesh , Cerciello Emily , Dave Janan , Jain Rahul , Schnipper Jeffrey L.
Published: October 2022

Background

Adverse drug events are common during transitions of care. As part of the Smart Pillbox study, a cluster-randomized controlled trial of an electronic pillbox designed to reduce medication discrepancies and improve medication adherence after hospital discharge, we explored barriers to successful implementation and evaluation of this intervention.

Methods

Eligible patients were those admitted to a medicine service of a large teaching hospital with a plan to be discharged home on five or more chronic medications. The intervention consisted of an electronic pillbox with pre-filled weekly blister pack medication trays given to patients prior to discharge. Pillbox features included alarms to take medications, detection of pill removal from each well, alerts to patients or caregivers by phone, email, or text if medications were not taken, and adherence reports accessible by providers. Greater than 20% missed doses for three days in a row triggered outreach from a pharmacist. To identify barriers to implementation and evaluation of the intervention, we reviewed patient exit surveys, including quantitative data on satisfaction and free-text responses regarding their experiences; technical issue logs; and team meeting minutes. Themes were derived by consensus among the study authors and organized using the Consolidated Framework for Implementation Research.

Results

Barriers to implementation included intervention characteristics such as perceived portability issues with the pillbox and time required by pharmacists to enter medication information into the software; external policies such as lack of insurance coverage for early refills and regulatory prohibitions on repackaging medications; implementation climate issues such as the incompatibility between the rushed nature of hospital discharge with the time required to deploy the intervention; and patient issues such as denial of previous problems with medication adherence. We founds several obstacles to conducting the study, including patients declining study enrollment and limited attempts by the hospital to streamline logistics by building the intervention into usual care. Several solutions to address many of these challenges were implemented or planned. Despite these challenges, many patients with the pillbox were pleased with the service and believed the intervention worked well for them.

Conclusions

In this evaluation, several barriers to implementing and conducting a study of the effectiveness of the intervention were identified. Our findings provide lessons learned for others wishing to implement and evaluate HIT-related interventions designed to improve medication safety during care transitions.

Trial registration

Clinicaltrials.gov NCT03475030