The emergence of CRISPR/Cas system allows for precise and efficient alteration of genetic sequences in almost any kind of living cells. Several studies have attempted to modify human hepatocytes with plasmids that encodes immortalized genes, such as hepatocytes derived from stem cells or cell lines produced by an organism. Most strategies are time consuming and requires high technical expertise, especially for the use of drug metabolism studies. This study shows that there is a possibility to develop a hepatocyte cell line for functional expression studies with modifiable CYP2C9 expression. Two CRISPR/Cas9 systems were successfully assembled to specifically target the CYP2C9 gene and reduce the expression down. The efficiency of this method was validated using standardised experimental guidelines, to confirm target selection, cleavage efficiency and an analysis of target activity. Both systems managed to reduce CYP2C9 expression by at least 5 folds in Huh-7 cell line and 2 folds in HepG2 cell line. The successful knocking down of CYP2C9 regulation may open a path to a cheaper, time saving, and modifiable hepatocyte drug metabolism assays that can be grown in a lab.

We developed a multi-enzyme system to enhance the biosynthesis of inositol by covalently immobilizing four purified enzymes on the polyacrylamide hydrogel microparticles. The four purified enzymes form an in vitro enzymatic pathway that converts starch to inositol. Employing a continuous flow column reactor, inositol was produced steadily for 360 hours with the continuous supply of maltodextrin. To examine the effect of the enzyme immobilization on biosynthesis of inositol, the four-enzyme system, either immobilized in hydrogel microparticles or in solution phase, was encapsulated in a continuous flow membrane reactor and continuously catalyzed the conversion of maltodextrin to inositol. The conversion reaction using the multi-enzyme system in the hydrogel lasted for 72 hours longer than the reaction in solution phase. The results showed that immobilization of the multi-enzyme system on the hydrogel polymer backbone substantially improved the function lifetime and the tolerance of enzymes to different pH and high temperature. We expect the immobilized multi-enzyme system combined with the continuous flow reactor provides an economical approach for biosynthesis.

Environmental and biotic factors drive species richness patterns, but the nature of this relationship can vary with sampling grain. Understanding the scale-dependent effects of these factors is crucial for interpreting species richness patterns in ecosystems experiencing rapid environmental change. We investigated the effects of local environmental drivers on plant species richness at small (1 x 1 m) and large (3 x 3 m) sampling grains, and the factors correlated with differences in richness between the two grains, on a sub-Antarctic island. Broadly, richness was higher in warmer (i.e., lower altitude, north-facing) and wetter (i.e., higher topographic wetness index, lower distance from drainage line) sites, and in more topographically heterogenous (i.e., steeper slopes) sites. Additionally, there was some evidence of competition with a keystone plant limiting species richness, though this was only evident at low elevations. However, the effects of several drivers on richness depended on spatial grain. Differences in species richness between large and small grain sizes were more pronounced at low elevations, indicating that there is more compositional heterogeneity at low altitudes at both grains. Richness was positively related to northness at large grain size but not at small grain size, suggesting that higher northness increases local turnover at a grain size > 1 m2. On the other hand, TWI boosted richness at small but not large grains, implying that competition limited coexistence at low TWI, and that higher TWI only resulted in more species coexisting at a grain of 1 m2, while having no effect on richness at large grains. Our study therefore highlights that drivers of plant species richness can vary with sampling grain, suggesting that environmental effects on local species turnover affect richness patterns at different grains. Assessing how the influence of such drivers differ with grain size provides insight into local patterns of species assemblage.

We conducted a comprehensive investigation of the interrelationships among the species diversity, productivity, community structure, and soil nutrients of vegetation communities of an alpine meadow ecosystem on the eastern Qinghai–Tibet Plateau. We performed biodiversity manipulation experiments to examine the effects of removing plant functional groups (Gramineae, Cyperaceae, Legumes, and other Forbs) for 3 and 10 years at a research station in Haibei. Interannual variation in the species richness and above- and belowground biomass of the community gradually decreased over time. Species richness and productivity were positively correlated, and this correlation became increasingly significant over time. Removal of the plant functional groups resulted in fewer Gramineae species within the community. However, soil total nitrogen, phosphorus, organic matter, and moisture contents increased significantly in the Legume removal treatment. The removal of other Forbs led to the lowest negative cohesion values, suggesting that this community may have had difficulty recovering its previous equilibrium state within a short period of time. The effects of species removal on the ecosystem were likely influenced by the species structure and composition within the community. Changes in the number of Gramineae species indicated that they were more sensitive and less resistant to plant functional group removal. Legume removal may also have indirectly caused distinct community responses through starvation and compensation effects. In summary, species loss at the community level led to extensive species niche shifts, which caused community resource redistribution and significant changes in community structure.

Adjacent tissue skip metastasis of keratoacanthoma on the nose tip: A case report

Cancer is one of the main causes of death in the world. Resistance to anticancer treatments in patients with advanced solid tumors leads to new treatments. Therefore, more alternative anticancer methods have been found over time with greater specificity against tumor cells and with less or no adverse effects on normal cells. In the microbial environment, pathogens such as Staphylococcus aureus, Bacillus cereus, or Streptococcus pyogenes produce hemolysin. This protein is used as an anti-cancer protein. To identify the production of hemolysin by bacteria, which can destroy cancer cells more effectively, different bacterial strains were first cultured in blood agar culture medium. The strains capable of complete hemolysis of red blood cells created a transparent zone in this environment and were selected for the next stages of the research. Then, to find out which strains have more ability to lyse red blood cells, the qualitative method of halo diameter measurement was used. Also, using quantitative methods, hemolysin strength in microtubes was determined compared to control samples. The results of the hemolysis in the microtube and the good test results showed similar results. knows Then, the cell viability test was performed with the partially purified proteins. Then, bioinformatics studies such as secondary structure investigation, physicochemical properties, pseudo amino acid composition, and molecular docking were performed.

Kadir Uludag PhD.aShanghai Mental Health Center, Shanghai Jiao Tong University, School of Medicine, China*Corresponding Authors:Kadir Uludag; Shanghai Mental Health Center, Shanghai Jiao Tong University China Tel: +86-18401653162, Email: kadiruludag@mails.ucas.ac.cn&kadiruludag@protonmail.com& kadiruludag233@gmail.comFunding: There is no funding associated with this study.Competing interests: No potential competing interest was reported by the authors.Ethical approval: Not required.Patient Consent: Not required.Acknowledgment: Not required.Author Statement: K.U. wrote the manuscript and is the only author.

Wintering birds serve as vital climate sentinels, yet they are often underrepresented in comprehensive surveys and overlooked in studies of avian diversity change. Here, we provide a continental-scale characterization of change in multiple facets of wintering avifauna and examine the effects of climate change on these dynamics. We reveal a strong functional reorganization of wintering bird communities marked by a distinct east-west gradient in functional diversity change, along with a superimposed north-south gradient in trait composition change. Assemblages in the eastern US saw an expansion of the functional space and increases in functional originality, evenness, and divergence, while the western US saw contractions of the functional space. Shifts in functional diversity were underlined by significant reshuffling in trait composition, particularly pronounced in the northern US. Finally, we find strong contributions of climate change to this functional reorganization, underscoring the importance of wintering birds in tracking climate change impacts on biodiversity.

Wildlife conservation involves making management decisions with incomplete knowledge of biological and ecological relationships. Efforts to augment foraging resources for the endangered Mexican long-nosed bat (Leptonycteris nivalis) are progressing despite limited knowledge about the species’ foraging behavior and requirements. This study sought to fill knowledge gaps about L. nivalis responses to floral resource availability by addressing individual plant and local-scale (30 m) characteristics that influence visitation rates to flowering agaves. We observed bat visitation at 62 flowering agaves around two roosting caves in northeast Mexico on 46 nights in summers 2017 and 2018. We found visitation rate had positive relationships with two agave-scale characteristics: the number of umbels (flower clusters) with open flowers and earlier phenological stages of plants. A negative interaction between the significant predictors indicated that direction of the relationship between visitation and either characteristic depended on the level of the other characteristic. We also found relationships between visitation rate and two local-scale characteristics: negative for the density of flowering conspecifics within 30 m of the focal plant and positive for the density of dead standing stalks within 30 m. Our findings suggest opportunities to augment foraging resources for L. nivalis in ways that are consistent with the bats’ foraging behavior, including: planting larger agave species with more flowers, planting multiple species of agaves with different flowering times to ensure nectar availability when L. nivalis is present in northeast Mexico, planting agaves in clusters, and keeping dead standing stalks on the landscape. Our study highlights important considerations for management actions, which will ultimately aid the development of ongoing conservation efforts.

Ctenostomes are a group of gymnolaemate bryozoans with an uncalcified chitinous body wall having few external, skeletal characters. Hence, species identification is challenging and their systematics remain poorly understood, even more so when they exhibit an endolithic (boring) lifestyle. Currently, there are four Recent families of endolithic bryozoans that live inside in mineralized substrates like mollusk shells. In particular, Penetrantiidae Silén, 1946 has received considerable attention and its systematic affinity to either cheilostomes or ctenostomes has been debated. Species delimitation of penetrantiids remains difficult, owing to a high degree of colonial and zooidal plasticity. Consequently, an additional molecular approach is essential to unravel the systematics of penetrantiids, their phylogenetic placement and their species diversity. We therefore sequenced the mitochondrial (mt) genomes and two nuclear markers of 27 ctenostome species including nine penetrantiids. Our phylogeny supports the Penetrantiidae as a monophyletic group placed as sister taxa to the remaining ctenostomes alongside paludicellids and arachnoidids. Our results also suggest that the endolithic lifestyle evolved at least twice independently within ctenostomes, since the boring families Terebriporidae d’Orbigny, 1847 and Penetrantiidae are well separated. Ctenostome paraphyly is supported by our data, as the cheilostomes nest within them. A Multiporata clade is also well supported, including the former victorelloid genus Sundanella. Altogether, this study provides new insights into ctenostome systematics, assists with species delimitation and contributes to our understanding of the bryozoan tree of life.

Background Coronavirus disease (COVID-19) is an emerging infectious disease affecting people of all ages, races, and countries, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV-2). The disease has been shown to be more lethal in select individuals with existing comorbidities and inflammation. Although the disease occurs in people of all ages, a milder course has been observed in pediatric patients. Evidence suggests that the burden of COVID-19 infection is lower in hospitalized children than in their adult counterparts. To date, there are few reports describing the factors responsible for acute COVID-19 severity in young adults and their differences in the elderly. In this work, we aimed to review the factors responsible for determining the most severe cases with chronic clinical manifestations by evaluating their clinical presentations to close the gap and provide a potential basis to address this relationship between severity and age. The lower severity in young adults could be due to a variety of reasons, ranging from immunologic factors to genetic composition. Our work helps classify some of these factors, which appear to play a role in a small number of critical cases. The characteristic ability of the younger human body to fight this deadly disease may be a striking feature when trying to manage patients belonging to the older age group. Setting All settings, including hospitalized and community settings. Patients Children and young people (CYP) under 20 years of age with PCR and other laboratory tests COVID -19 affected patients. Main results: Prevalence of symptoms and signs of COVID -19. Purpose There are limited data on the demographics and clinical features of SAR -CoV-2 infection in children. Therefore, with this literature review, we aim to uncover various factors responsible for the different severities in pediatric patients. This will help us to better understand COVID -19 in different age groups.

Malware growth has accelerated due to the widespread use of Android applications. Android smartphone attacks have increased due to the widespread use of these devices. While deep learning models offer high efficiency and accuracy, training them on large and complex data sets is computationally expensive. Hence, a method that effectively detects new malware variants at a low computational cost is required. A transfer learning method to detect Android malware is proposed in this research. Because of transferring known features from a source model that has been trained to a target model, the transfer learning approach reduces the need for new training data and minimizes the need for huge amounts of computational power. We performed many experiments on 1.2 million Android application samples for performance evaluation. In addition, we evaluated how well our framework performed in comparison to traditional deep learning and standard machine learning models. In comparison to state-of-the-art Android malware detection methods, the proposed framework offers improved classification accuracy of 98.87%, a precision of 99.55%, recall of 97.30%, f1 measure of 99.42%, and a quicker detection rate of 5.14 ms by utilizing the transfer learning strategy.

Objectives: To evaluate the effects of local radiotherapy (RT) on growth, we evaluated the chronological growth profiles and vertebral features of children with high-risk neuroblastoma. Materials and Methods: Thirty-eight children who received local photon or proton beam therapy to the abdomen or retroperitoneum between January 2014 and September 2019 were included. Simple radiography of the thoracolumbar spine was performed before and every year after RT. The height and vertical length of the irradiated vertebral bodies (VBs) compared with the unirradiated VBs (vertebral body ratio, VBR) were analyzed using the linear mixed model. Shape feature analysis was performed to compare the irradiated and unirradiated vertebrae. Results: The follow-up was a median of 53.5 months (range, 21-81­ months) after RT. A decline in height z-scores was mainly found in the early phase after treatment. In the linear mixed model with height, the initial height (fixed, p < .001), sex (time interaction, p = .008), endocrine dysfunction (time interaction, 0.019), and age at diagnosis (fixed and time interaction, both p = .002) were significant. Unlike the trend in height, the change in VBR (ΔVBR) decreased gradually ( p < .001). The ΔVBR in the group that received more than 30 Gy decreased more than in the group that received smaller doses. In the shape feature analysis, the irradiated VBs changed to a more irregular surface that were neither round nor rectangular. Conclusion: The irradiated VBs in children were gradually restricted compared to the unirradiated VBs in long-term follow-up, and higher RT doses were significantly affected. Radiation-induced irregular features of VBs were observed.

Arthropod-eating birds comprise a diverse group with varying degrees of sensitivity to environmental changes and distinct responses to habitat degradation. In our study, we investigated the impact of landscape and habitat characteristics on the functional diversity of insectivorous birds in the Brazilian Atlantic Forest. Our hypotheses are focused on (I) how species composition and functional diversity respond to habitat turnover and nestedness and (II) whether an increase in native forest cover positively influences bird species richness and functional diversity. Our research encompasses 22 different landscapes within the Cantareira-Mantiqueira region, southeastern Brazil, including native forests, pastures, and marshes, within 1 km radius buffers. To assess functional diversity, we employed beta pair and beta multi-function indices for each environment type. Generalized mixed linear models were calculated to examine the effects of the native forest cover gradient and environment type on functional diversity. Our findings indicated negative effects of increased native forest cover on functional diversity indices. Bird communities were susceptibility to turnover in pasturelands, to nestedness in marshes, and both species nestedness and turnover in native forests. These results may be partially due to the predominantly second-growth, small-sized, and early successional stages of the native forest fragments in the region. These findings underscore the intricate interplay between landscape characteristics, habitat types, and bird functional diversity within the Brazilian Atlantic Forest. They also highlight the significance of considering habitat quality and succession stages in conservation efforts in this region.

The defences of aposematic animals are characterised by diversity and variability of secondary metabolites. Here we examine the nature and function of chemical defence diversity in large milkweed bugs, Oncopeltus fasciatus, testing the hypothesis that different chemical defence compounds have evolved in response to different enemies. We profiled and quantified the cardenolides sequestered by large milkweed bugs in their defensive secretions and their bodies, and measured the inhibitory properties of a subset of isolated milkweed cardenolides in the insect’s defence against the Na+/K+—ATPase target site of vertebrate and invertebrate predators, using porcine Na+/K+—ATPase data as a reference. We show that highly concentrated coroglaucigenin cardenolides in the insect’s defence (glucopyranosyl frugoside and frugoside) are toxic for both resistant and sensitive predators, whereas corotoxigenin and calotropagenin cardenolides have varying degrees of enzyme inhibition among various predators. Overall, O. fasciatus is well defended against a range of enemies due to the differential effect of these compounds´ target sites. Our results suggest that the compounds the insect sequester have evolved in response to predation pressure.

Computing protein structure from amino acid sequence information has been a long-standing grand challenge. CASP (Critical Assessment of Structure Prediction) conducts community experiments aimed at advancing solutions to this and related problems. Experiments are conducted every two years. The 2020 experiment (CASP14) saw major progress, with the second generation of deep learning methods delivering accuracy comparable with experiment for many single proteins. There is an expectation that these methods will have much wider application in computational structural biology. Here we summarize results from the most recent experiment, CASP15, in 2022, with an emphasis on new deep learning-driven progress. Other papers in this special issue of Proteins provide more detailed analysis. For single protein structures, the AlphaFold2 deep learning method is still superior to other approaches, but there are two points of note. First, although AlphaFold2 was the core of all the most successful methods, there was a wide variety of implementation and combination with other methods. Second, using the standard AlphaFold2 protocol and default parameters only produces the highest quality result for about two thirds of the targets, and more extensive sampling is required for the others. The major advance in this CASP is the enormous increase in the accuracy of computed protein complexes, achieved by the use of deep learning methods, although overall these do not fully match the performance for single proteins. Here too, AlphaFold2 based method perform best, and again more extensive sampling than the defaults is often required. Also of note are the encouraging early results on the use of deep learning to compute ensembles of macromolecular structures. Critically for the usability of computed structures, for both single proteins and protein complexes, deep learning derived estimates of both local and global accuracy are of high quality, however the estimates in interface regions are slightly less reliable. CASP15 also included computation of RNA structures for the first time. Here, the classical approaches produced better agreement with experiment than the new deep learning ones, and accuracy is limited. Also, for the first time, CASP included the computation of protein-ligand complexes, an area of special interest for drug design. Here too, classical methods were still superior to deep learning ones. Many new approaches were discussed at the CASP conference, and it is clear methods will continue to advance.

This article examines the real potential of smart cities to offer a better experience to residents as people with more than just basic needs. This is done through a lens of design, urban encounters and on-site sensations. The topic is presented and discussed in four main themes; Facilitating the Making of Livable City and Quality Experience, Mental Associations of the City, The Unique Intimacy of the Night Experience, Emotional Responses: Safety, Stress and Discomfort, and the Taste of the City: Character, Wayfinding and Monotony. This is done to facilitate analysis and communication. Nevertheless, the topics presented here should not be separated from one another. Various qualitative methods were used in the analysis of the Milton Keynes case study. This includes interviews, field observations and visual comparisons with other cases, allowing for a deeper understanding of the different capabilities of the different approaches. The results help to further fill the knowledge gap in the literature on the overlooked aspects of smart cities and provide better information for smart city design. 

Land systems are closely related to various factors, including social issues, national economies, natural environments, etc. However, the dynamic evolution simulation of land systems is quite complex. There are many problems in terms of land use in China, such as extensive development, significant regional differences, and imbalanced development. From this perspective, it is imperative to study systematic land use evolution according to local contexts. In this study, two methods that are commonly used to solve complexity issues— “top-down” system dynamics and “bottom-up” cellular automata—were combined to investigate the land use evolutionary trend in Ya’an City. Firstly, a system dynamics model of land resource use was constructed based on the causal relationship between land and macroscopic elements, and the quantitative future predictions of land use structures in Ya’an were obtained. Next, an ANN-CA model containing three steps—artificial neural network training, optimization of cellular automata parameters, and model calibration—was constructed. The land use scenario in Ya’an City in 2018 was simulated and the quantity and space accuracy verification were conducted. Finally, the spatial layout of land use in Ya’an City in 2028 and 2038 was predicted, and the land use evolution trend was studied using the model under the constraint of the quantitative prediction results of system dynamics. The results demonstrated the good simulation effect of the ANN-CA model under the SD constraint. The overall simulation accuracy of the model is the highest (93.93%) when the threshold of transformation is 0.8 and the diffusion coefficient is 1. In the future, the spatial distribution of different land types in Ya’an City will change slightly, and construction land presents an expansion law from the center to surrounding areas.

Forest degradation is increasingly recognized as a major threat to global biodiversity and ecosystems’ capacity to provide ecosystem services. This study examined the impacts of forest degradation on soil quality and function in a seasonally dry tropical forest (SDTF) of Ecuador. We compared soil physical-chemical properties, enzymatic activity, particulate organic carbon (POC) and mineral-associated organic carbon (MAOC) along a gradient of SDTF degradation in the dry and rainy season. Our findings showed a consistent and steady reduction in soil quality (total C and N) and function (dehydrogenase and β-glucosidase activity) that paralleled the loss of vegetative structure and diversity along the degradation gradient. Soil physical-chemical properties were less variable and enzymatic activity was generally higher in the dry season compared to the rainy season. We also showed for the first time a significant and uniform decrease in POC and MAOC with ecosystem degradation in a SDTF. The relative proportion of these two components was constant along the gradient except for the most degraded state (arid land), where POC was higher in proportion to MAOC, suggesting that a functional tipping point may be crossed with extreme forest degradation. These findings address an important knowledge gap for SDTFs by showing a consistent loss of soil quality and functionality with degradation and suggest that extreme degradation can result in an alternate state with compromised resilience.

Introduction: The clinical spectrum of SARS-CoV-2 infection is well-established. However, understanding its long-term implications, especially in infants, remains limited. We aimed to evaluate pulmonary function tests in infants (iPFT) several months after a documented SARS-CoV-2 infection. Methods: An observational case-control study was performed. iPFT results in infants with persistent respiratory complaints several months after a SARS-CoV-2 infection were compared to a registry of patients assessed at our center between 2008 and 2019 using the Mann–Whitney U and Fisher’s exact tests. Excluded from the study were infants with chronic diseases and extreme prematurity. Results: iPFT data from sixteen infants with respiratory complaints and a history of SARS-CoV-2 infection and 475 controls were evaluated in the study. The median time between the SARS-CoV-2 infection and iPFT evaluation was 5.5 months (IQR=2.8-8.0). There were no differences between cases and controls in clinical characteristics and reason for iPFT evaluation. iPFT results showed no significant differences between cases and controls in lung volumes, compliance, or resistance. Expiratory airflow limitation was observed in both groups, with better low lung volume flows in the SARS-CoV-2 group. Categorization according to iPFT physiologic alteration and bronchodilator responsiveness were similar in the two groups. Conclusion: This study provides the first comprehensive iPFT data in infants following a SARS-CoV-2 infection. The findings suggest that SARS-CoV-2 infection does not cause unique long-term effects on pulmonary function in infants with chronic respiratory symptoms. Further studies in larger cohorts, particularly in infants with severe acute SARS-CoV-2 infection, are warranted to validate these findings.

The widespread use of Internet of Things technology has made it now a popular topic subject. It’s full with all kinds of devices that are all linked to the internet and to one other. The limited processing power, storage space, and energy supply of IoT devices impose severe limitations on their overall functionality. Because of these limitations, implementing effective security measures on such devices is challenging. This makes them simple targets for fraudsters who are looking for vulnerable areas to exploit. TCP_SYN flooding assault is an effort to interrupt regular service by flooding a server with a large number of SYN packets without completing the handshake. The new networking paradigm known as Software Defined Networking (SDN) separates the forwarding devices from the control actions. It’s supposed to make managing networks easier and pave the way for new developments. In this paper, SDN model was proposed to detect and prevent TCP_SYN flooding attack in IoT based on the traffic’s anomalous behavior in real time. It has the ability to swiftly identify and mitigate attacks within a two-second time. The CPU utilization remains stable at around 19.1% during the process of mitigating attacks by discarding all malicious packets, rather than redirecting them to the controller for examination. A bout 6487795 packets dropped through TCP_SYN attack.

Objective: This study aims to determine the impact of maternal gestational diabetes mellitus (GDM) on peripubertal growth of offspring. Design: Population-based prospective cohort study. Setting: University Hospital. Population: 478 mother-offspring pairs from cohort Taiwan Birth Panel Study II (TBPS II). Methods: Maternal GDM status was tested at gestational weeks 24-28 using two-step or one-step oral glucose tolerance test. Offspring received follow-up questionnaire, physical examination, and bone age study at the age of 6 to 8. Associations between maternal GDM and offspring outcomes were analyzed using multiple linear or logistic regression models to adjust for maternal pre-gravid BMI, household income, maternal age at delivery, and maternal menarche age. Main Outcome Measures: Offspring bone age, serum sex hormone levels, Tanner stage for breast and testes, and penile length. Results: There were 43 (9.0%) children born from mothers with GDM, and 435 (91.0%) in the control group. In girls, there was a more advanced bone age in the GDM group (n=19) than the control group (n=203) after adjusting for potential confounding factors (0.48-year, 95% CI=0.002-0.97-year). For boys, the GDM group (n=24) showed no advancement in the bone age compared with the control group (n=232) (-0.13-year, 95% CI= -0.66-0.40). The serum sex hormone levels and secondary sexual characteristics of children in the GDM group were comparable to those in the control group. Conclusions: Girls born from GDM mothers had more advanced bone age at peripubertal stage than the control group. This phenomenon was not observed in boys, nor were other secondary sexual characteristics and serum sex hormone levels.

Objective: To explore the potential factors that contribute to the occurrence of medical abortion(MA) through a Mendelian randomization(MR) study. Design: Univariate MR(UVMR) and multivariate MR(MVMR) analyses. Setting: Genetic variants from European populations. Population or Sample: Instrumental variants for MA were obtained from FinnGen with 36,232 cases and 149,622 controls. Methods: The inverse variance weighting method was adopted as the primary analysis. Main outcome measures: The associations of MA with household income(HI), education attainment(EA), cognitive performance(CP), risky behaviors: smoking behavior(SB), alcohol consumption(AC), and reproductive traits: age at first sexual intercourse(AFS), lifetime number of sexual partners(LNSP), age at first birth(AFB), age at last birth(ALB). Results: In the UVMR, increasing HI, EA, AFS and AFB appeared to reduce MA risk(HI, OR=0.569, P = 7.93E-08; EA, OR=0.875, P = 6.02E-21; AFS, OR=0.439, P = 5.17E-25; AFB, OR=0.815, P = 5.46E-12), whereas SB and LNSP appeared to add to MA risk((SB, OR=1.424, P =8.32E-11; LNSP, OR=2.777, P =2.14E-11). In the MVMR, EA, SB, LNSP and AFS seems to be the predominant risk factor for MA risk with the independent effect, while HI had no effect after controlling EA(HI in model 1, OR=0.890, P = 5.78E-01). AFB functioned as mediators in the causal chain of MA risk reduction by EA, with the mediated proportion of AFS and AFB being 57.8%. Conclusions: Our MR study demonstrated the causal potential of the associations of HI, EA, SB, LNSP, AFS and AFB with medical abortion.

The progressive improvement of lithium-ion batteries (LIBs) leads to subsequent electrolyte design and electrode modification processes. The spinel lithium nickel manganese oxide (LiNi0.5Mn1.5O4, LNMO) is one of the potential candidates for the next generation of LIBs applied for electric vehicles due to its high working potential (4.75 V vs. Li+/Li), reasonable price, and environmental friendliness. Nevertheless, the degradation of cycling performance at high potential induces massive challenges for LNMO-based batteries commercialization. This study investigated the impact of Succinonitrile (SN) and electrode processing to strengthen and maximize the LNMO electrode and graphite||LNMO full-cell performance. According to the performance in half-cell, the sample contained 85 wt.% LNMO: 7.5 wt.% C65: 7.5 wt.% PVDF/NMP combining with the electrolyte 1.5 M LiPF6 in EC: EMC: DMC (2:1:7 – v/v) at 0.5 wt.% SN seems to be the optimal condition for further full-cell. Indeed, the promising full-cell with N/P=1.3 displays a remarkable initial capacity of 118.75 mAh.g-1 with a Coulombic efficiency of 91.64%. Moreover, it maintains a capacity retention of around 58% at the current density of 0.1C after 100 cycles.