Novel homozygous missense variants in MED27 associated with neurodevelopmental disorder: Clinical and pathogenetic research.

Background: Neurodevelopmental disorder with spasticity, cataracts, and cerebellar hypoplasia (NEDSCAC), induced by MED27 gene, is an autosomal recessive rare disorder characterized by widespread developmental delay with varying degrees of intellectual impairment. Other symptoms include limb spasticity, cataracts, and cerebellar hypoplasia. So far there have been limited reports on NEDSCAC. Methods: In this study, we conducted genetic testing on a child presenting with developmental delay as the primary clinical feature. The genetic test results indicated the presence of novel homozygous missense variants c.74G > A, p.(Arg25His) in the MED27 gene. In vitro functional validation experiments, including plasmid construction and cell transfection, Western blotting, and molecular dynamics structural modeling, were performed on the MED27 Arg25His variant. Results: The results demonstrated a significant reduction in protein expression of MED27 Arg25His and indicated may weaken the interaction force between the MED27 subunit and MED14 subunit. Conclusions: This study expands our understanding of MED27 gene variants and their associated clinical phenotypes. Additionally, it contributes to the investigation of the potential pathogenesis of NEDSCAC caused by MED27 gene variants.

Label-free ratiometric fluorescence detection of Pb2+via structure-specific fluorescent dyes and dual signal amplification.

Lead ions (Pb2+) are a widely distributed and highly toxic heavy metal pollutant, which seriously threatens the environment, economy and human safety. Here, a label-free ratiometric fluorescent biosensor was constructed for Pb2+ detection using DNAzyme-driven target cycling and exonuclease III (Exo III)-mediated DNA cycling as a dual signal amplification strategy. The SYBR Green I (SGI) and N-methyl mesoporphyrin IX (NMM) used in this study are characterized by low cost, storage resistance, and short preparation time compared with conventional signaling probes labeled with fluorescent groups. Unlike the single-emission fluorescence strategy, monitoring the fluorescence intensity ratio of SGI and NMM can effectively reduce external interference to achieve accurate detection of Pb2+. DNAzyme structures on the surface of magnetic beads (MBs) can recognize Pb2+ and activate the target circulatory system to cleave single-stranded DNA (ssDNA). The ssDNA further initiated the Exo III-assisted DNA circulatory system to digest double-stranded DNA (dsDNA) and release guanine-rich G1. Finally, the fluorescence signals of SGI and NMM were weakened and enhanced, respectively. The sensing strategy achieved a wide linear range from 0.5 to 500 nM and a low limit of detection (LOD) of 26.4 pM. Furthermore, its anti-interference ability and potential applicability for Pb2+ detection in actual samples were verified. This work ingeniously combines the dual signal amplification strategy with the ratiometric sensing strategy constructed by structure-specific fluorescent dyes, which provides a promising method for constructing sensitive and accurate fluorescent biosensors.

Application of medical-nurse integration health education in aged patients undergoing percutaneous vertebroplasty.

This study was designed to explore the effect of medical-nurse integration health education in aged patients undergoing percutaneous vertebroplasty. A total of 72 aged patients with osteoporotic vertebral compression fractures, who obtained percutaneous vertebroplasty from June 2019 to May 2022 were selected in this study. Patients were divided into control group (n = 36) and experimental group (n = 36) according to the time of hospitalization. The patients in control group received routine health education, while the patients in the experimental group received medical-nurse integration health education. We evaluated participants on 4 key aspects, their understanding of relevant knowledge, compliance with functional exercise, residual lower back pain rate, and satisfaction with the health education received. Our study found that patients in the experimental group had a significantly higher mastery rate of health education knowledge compared to those in the control group (88.89% vs 50.00%, P < .001). Additionally, compliance with the functional exercise program was higher in the experimental group, with over 80% of patients fully compliant, compared to only about 44.4% in the control group (P = .001). The average Japanese Orthopaedic Association score of the observation group 1 week after operation was higher than that of the control group (P < .05). Moreover, most patients in the experimental group were very satisfied with the medical-nurse integration health education, while most patients in the control group were only satisfied (P < .001). For aged patients with osteoporotic vertebral compression fractures treated by percutaneous vertebroplasty, medical-nurse integration health education could be an effective method to improve the ability of patients to obtain relevant education, enhance the compliance of patients for functional exercise and increase patient satisfaction to the education, and reduce residual low back pain in patients.

A convenient paper-based fluorescent aptasensor for high-throughput detection of Pb2+ in multiple real samples (water-soil-food).

Lead ion (Pb2+) is one of the most toxic and widely polluted heavy metal ions. Given the potential health risks and economic losses associated with Pb2+, the rapid detection of Pb2+ using fluorescent aptasensors is of significant importance in evaluating food safety. A rapid, facile and economic fluorescent aptasensor using convenient paper as the sensing substrate was designed to high-throughput detect Pb2+ in complex samples within about 45 min. The Pb2+ changed the conformation of FAM-modified Apt from a random coil to a stable G-quadruplex structure. And then Dabcyl-labeled cDNA was added to form double-stranded DNA with the Apt that did not form a G-quadruplex structure, resulting in a weak fluorescence due to the fluorescence resonance energy transfer (FRET). The fluorescent aptasensor showed a positive correlation with Pb2+ concentration, and a linear relationship was obtained in the range of 0.01-10 µM with LOD of 6.1 nM. In addition, this method has been successfully used for the determination of Pb2+ in water, soil and various foods containing complex substrates. Meanwhile, the high-throughput detection of Pb2+ has also reached an acceptable level. Therefore, this convenient strategy has potential application value for on-site rapid detection of Pb2+.

Assessing the export trade risk of bluetongue virus serotypes 4 and 8 in France.

Bluetongue (BT) causes an economic loss of $3 billion every year in the world. After two serious occurrences of BT (bluetongue virus [BTV] occurrence in 2006 and 2015), France has been controlling for decades, but it has not been eradicated. As the largest live cattle export market in the world, France is also one of the major exporters of breeding animals and genetic materials in the world. The biosafety of its exported cattle and products has always been a concern. The scenario tree quantitative model was used to analyze the risk of BTV release from French exported live cattle and bovine semen. The results showed that with the increase in vaccination coverage rates, the risk decreased. If the vaccine coverage is 0%, the areas with the highest average risk probability of BTV-4 and BTV-8 release from exported live cattle were Haute-Savoie and Puy-de-Dôme, and the risk was 2.96 × 10-4 and 4.25 × 10-4 , respectively. When the vaccine coverage was 90%, the risk probability of BTV-4 and BTV-8 release from exported live cattle was 2.96 × 10-5 and 4.24 × 10-5 , respectively. The average probability of BTV-8 release from bovine semen was 1.09 × 10-10 . Sensitivity analysis showed that the probability of false negative polymerase chain reaction (PCR) test and the probability of BT infection in the bull breeding station had an impact on the model. The identification of high-risk areas and the discovery of key control measures provide a reference for decision makers to assess the risk of French exports of live cattle and bovine semen.

Epidemiologic and import risk analysis of Peste des petits ruminants between 2010 and 2018 in India.

BACKGROUND: Peste des petits ruminants (PPR) is a serious disease that affects goats, sheep and other small ruminants. As one of the earliest and most serious countries, PPR has seriously threatened India's animal husbandry economy. RESULTS: In this study, the spatiotemporal characteristics of the PPR in India outbreaks were analyzed. Between 2010 and 2018, the epidemic in India broke out all over the country in a cluster distribution. Epidemic clusters in northern and southern India are at higher risk, and the outbreak time of PPR has significant seasonality. The results of the analysis of the development and transmission of PPR under the natural infection conditions showed that the PPR outbreak in India reached a peak within 15 days. Finally, the quantitative risk analysis results based on scenario tree show showed that the average probability of infecting PPRV in live sheep exported from India was 1.45 × 10-4. CONCLUSIONS: This study analyzed the prevalence of PPR in India. The analysis of transmission dynamics on the development of the epidemic provides a reference for the prevention and control of the epidemic. At the same time, it provides risk analysis and suggestions on trade measures for the trading countries of India.

Spatiotemporal characteristics analysis and potential distribution prediction of peste des petits ruminants (PPR) in China from 2007-2018.

Peste des petits ruminants (PPR) is a highly infectious disease that mainly infects small ruminants. To date, PPR has been confirmed in more than 70 countries. In China, PPR has occurred in more than 20 provinces and cities. In this study, based on geographic information system (GIS), spatial analysis was used to examine the occurrence of PPR in China from 2007 to 2018. The results showed that PPR first occurred in Tibet and gradually spread to other provinces. The outbreaks of PPR were concentrated in 2014, 2015 and 2018. Combining climate factors with the maximum entropy (MaxEnt), the results also suggested that the potential risk areas of PPR outbreaks in China were mainly Jiangsu, Yunnan and Anhui in Southeast China. Finally, a phylogenetic tree was used to analyse the evolutionary relationship between the peste des petits ruminants virus (PPRV) in China and the global ones, and it was found that the one in China had a close genetic relationship with the one in Mongolia, India and Bangladesh. Understanding and forecasting the distribution of PPR in China will help policymakers develop targeted monitoring plans. Likewise, analysing the global PPRV epidemic trends will play an important role in the elimination and prevention of PPR.

Risk assessment and integrated surveillance of foot-and-mouth disease outbreaks in Russia based on Monte Carlo simulation.

BACKGROUND: Foot-and-mouth disease (FMD) is a highly contagious disease of livestock worldwide. Russia is a big agricultural country with a wide geographical area where FMD outbreaks have become an obstacle for the development of the animal and animal products trade. In this study, we aimed to assess the export risk of FMD from Russia. RESULTS: After simulation by Monte Carlo, the results showed that the probability of cattle infected with FMD in the surveillance zone (Surrounding the areas where no epidemic disease has occurred within the prescribed time limit, the construction of buffer areas is called surveillance zone.) of Russia was 1.29 × 10- 6. The probability that at least one FMD positive case was exported from Russia per year in the surveillance zone was 6 %. The predicted number of positive cattle of the 39,530 - 50,576 exported from Russia per year was 0.06. A key node in the impact model was the probability of occurrence of FMD outbreaks in the Russian surveillance zone. By semi-quantitative model calculation, the risk probability of FMD defense system defects was 1.84 × 10- 5, indicating that there was a potential risk in the prevention and control measures of FMD in Russia. The spatial time scan model found that the most likely FMD cluster (P < 0.01) was in the Eastern and Siberian Central regions. CONCLUSIONS: There was a risk of FMDV among cattle exported from Russia, and the infection rate of cattle in the monitored area was the key factor. Understanding the export risk of FMD in Russia and relevant epidemic prevention measures will help policymakers to develop targeted surveillance plans.

Prevalence of Antibiotic Resistance Genes, Heavy Metal Resistance Genes and the Class 1 Integron Gene in Well Water and Tap Water Samples from Four Cities in Henan Province, China.

The presence of multi-resistance to both antibiotics and heavy metals in drinking water poses a significant risk to human health. Herein, we utilized qPCR to assess patterns of antibiotic resistance genes (ARGs), heavy metal resistance genes (HMRGs), and class 1 integron (intI1) gene expression levels in well and tap water samples from four cities in Henan Province, China. The relative abundance of most index values was higher in well water relative to tap water, or was highest in Shangqiu City and lowest in Puyang City on average. The expression of ARG was closely correlated with that of intI1 and HMRG in both well and tap water. Overall, our data highlighted the health threat posed by ARGs in the drinking water supply and underscore the potential for the transfer of these genes between bacteria with the aid of intI1 under selective pressure associated with human activity and heavy metal stress.

Epidemic analysis of COVID-19 in Italy based on spatiotemporal geographic information and Google Trends.

Since the first two novel coronavirus cases appeared in January of 2020, the outbreak of the COVID-19 epidemic seriously threatens the public health of Italy. In this article, the distribution characteristics and spreading of COVID-19 in various regions of Italy were analysed by heat maps. Meanwhile, spatial autocorrelation, spatiotemporal clustering analysis and kernel density method were also applied to analyse the spatial clustering of COVID-19. The results showed that the Italian epidemic has a temporal trend and spatial aggregation. The epidemic was concentrated in northern Italy and gradually spread to other regions. Finally, the Google Trends index of the COVID-19 epidemic was further employed to build a prediction model combined with machine learning algorithms. By using Adaboost algorithm for single-factor modelling,the results show that the AUC of these six features (mask, pneumonia, thermometer, ISS, disinfection and disposable gloves) are all >0.9, indicating that these features have a large contribution to the prediction model. It is also implied that the public's attention to the epidemic is increasing as well as the awareness of the need for protective measures. This increased awareness of the epidemic will prompt the public to pay more attention to protective measures, thereby reducing the risk of coronavirus infection.

Prediction for global African swine fever outbreaks based on a combination of random forest algorithms and meteorological data.

African swine fever (ASF) is a virulent infectious disease of pigs. As there is no effective vaccine and treatment method at present, it poses a great threat to the pig industry once it breaks out. In this paper, we used ASF outbreak data and the WorldClim database meteorological data and selected the CfsSubset Evaluator-Best First feature selection method combined with the random forest algorithms to construct an African swine fever outbreak prediction model. Subsequently, we also established a test set for data other than modelling, and the accuracy accuracy value range of the model on the independent test set was 76.02%-84.64%, which indicated that the modelling effect was better and the prediction accuracy was higher than previous estimates. In addition, logistic regression analysis was conducted on 12 features used for modelling and the ROC curves were drawn. The results showed that the bio14 features (precipitation of driest month) had the largest contribution to the outbreak of ASF, and it was speculated that the outbreak of the epidemic was significantly related to precipitation. Finally, we used this qualitative prediction model to build a global online prediction system for ASF outbreaks, in the hope that this study will help to decision-makers who can then take the relevant prevention and control measures in order to prevent the further spread of future epidemics of the disease.

Progress in Target Drug Molecules for Alzheimer's Disease.

Alzheimer's disease (AD) is a chronic neurodegenerative disease that 4 widespread in the elderly. The etiology of AD is complicated, and its pathogenesis is still unclear. Although there are many researches on anti-AD drugs, they are limited to reverse relief symptoms and cannot treat diseases. Therefore, the development of high-efficiency anti-AD drugs with no side effects has become an urgent need. Based on the published literature, this paper summarizes the main targets of AD and their drugs, and focuses on the research and development progress of these drugs in recent years.

Prediction for Global Peste des Petits Ruminants Outbreaks Based on a Combination of Random Forest Algorithms and Meteorological Data.

Peste des Petits Ruminants (PPR) is an acute and highly contagious transboundary disease caused by the PPR virus (PPRV). The virus infects goats, sheep and some wild relatives of small domestic ruminants, such as antelopes. PPR is listed by the World Organization for Animal Health as an animal disease that must be reported promptly. In this paper, PPR outbreak data combined with WorldClim database meteorological data were used to build a PPR prediction model. Using feature selection methods, eight sets of features were selected: bio3, bio10, bio15, bio18, prec7, prec8, prec12, and alt for modeling. Then different machine learning algorithms were used to build models, among which the random forest (RF) algorithm was found to have the best modeling effect. The ACC value of prediction accuracy for the model on the training set can reach 99.10%, while the ACC on the test sets was 99.10%. Therefore, RF algorithms and eight features were finally selected to build the model in order to build the online prediction system. In addition, we adopt single-factor modeling and correlation analysis of modeling variables to explore the impact of each variable on modeling results. It was found that bio18 (the warmest quarterly precipitation), prec7 (the precipitation in July), and prec8 (the precipitation in August) contributed significantly to the model, and the outbreak of the epidemic may have an important relationship with precipitation. Eventually, we used the final qualitative prediction model to establish a global online prediction system for the PPR epidemic.

A Study of the Mechanism of Binding between Neratinib and MAD2L1 Based on Molecular Simulation and Multi-spectroscopy Methods.

BACKGROUND: Nilatinib is an irreversible tyrosine kinase inhibitor, which is used in the treatment of some kinds of cancer. To study the interaction between Neratinib and MAD2L1, a potential tumor target, is of guiding significance for enriching the medicinal value of Neratinib. METHOD: The binding mechanism between Mitotic arrest deficient 2-like protein 1 (MAD2L1) and Neratinib under simulative physiological conditions was investigated by molecule simulation and multi-spectroscopy approaches. RESULTS: Molecular docking showed the most possible binding mode of Neratinib-MAD2L1 and the potential binding sites and interaction forces of the interaction between MAD2L1 and Neratinib. Fluorescence spectroscopy experiments manifested that Neratinib could interact with MAD2L1 and form a complex by hydrogen bond and van der Waals interaction. These results were consistent with the conclusions obtained from molecular docking. In addition, according to Synchronous fluorescence and three-dimensional fluorescence results, Neratinib might lead to the conformational change of MAD2L1, which may affect the biological functions of MAD2L1. CONCLUSION: This study indicated that Neratinib could interact with MAD2L1 and lead to the conformational change of MAD2L1. These works provide helpful insights for the further study of biological function of MAD2L1 and novel pharmacological utility of Neratinib.

Identifying Cancer Targets Based on Machine Learning Methods via Chou's 5-steps Rule and General Pseudo Components.

In recent years, the successful implementation of human genome project has made people realize that genetic, environmental and lifestyle factors should be combined together to study cancer due to the complexity and various forms of the disease. The increasing availability and growth rate of 'big data' derived from various omics, opens a new window for study and therapy of cancer. In this paper, we will introduce the application of machine learning methods in handling cancer big data including the use of artificial neural networks, support vector machines, ensemble learning and naïve Bayes classifiers.

Retrospect and Risk Analysis of Foot-and-Mouth Disease in China Based on Integrated Surveillance and Spatial Analysis Tools.

Foot-and-mouth disease (FMD) is a highly contagious disease of livestock and seriously affects the development of animal husbandry. It is necessary to defend the spread of FMD. To explore the distribution characteristics and transmission of FMD between 2010 and 2017 in China, Global Moran's I test and Getis-Ord Gi index were used to analyze the spatial cluster. A space-time permutation scan statistic was applied to analyze the spatio-temporal pattern. GIS-based method was employed to create a map representing the distribution pattern, directional trend, and hotspots for each outbreak. The number of cases was defined as the number of animals with FMD for the above analysis. We also constructed a phylogenetic tree to compare the homology and variation of FMD virus (FMDV) to provide a clue for the potential development of an effective vaccine. The results indicated that the FMD outbreaks in China had obvious time patterns and clusters in space and space-time, with the outbreaks concentrated in the first half of each year. The outbreaks of FMD decreased each year from 2010 with an obvious downward trend of hotspots. Spatial analysis revealed that the distribution of FMD outbreaks in 2010, 2015, and 2017 exhibited a clustered pattern. Space-time scanning revealed that the spatio-temporal clusters were centered in Guangdong, Tibet and the junction of Wuhan, Jiangxi, Anhui. Comparison of the spatial analysis and space-time analysis of FMD outbreaks revealed that Guangdong was the same cluster of the two in 2010. In addition, the directional trend analysis indicated that the FMD transmission was oriented northwest-southeast. The findings demonstrated that FMDV in China can be divided into three pedigrees and the homology of these strains is very high while comparing the first FMDV strain with the others. The data provide a basis for the effective monitoring and prevention of FMD, and for the development of an FMD vaccine in China.