Using repeatability of performance within and across contexts to validate measures of behavioral flexibility
Research into animal cognitive abilities is increasing quickly and often uses methods where behavioral performance on a task is assumed to represent variation in the underlying cognitive trait. However, because these methods rely on behavioral responses as a proxy for cognitive ability, it is important to validate that the task structure does, in fact, target the cognitive trait of interest rather than non-target cognitive, personality, or motivational traits (construct validity). Although it can be difficult, or impossible, to definitively assign performance to one cognitive trait, one way to validate that task structure is more likely to elicit performance based on the target cognitive trait is to assess the temporal and contextual repeatability of performance. In other words, individual performance is likely to represent an inherent trait when it is consistent across time and across similar or different tasks that theoretically test the same trait. Here, we assessed the temporal and contextual repeatability of performance on tasks intended to test the cognitive trait behavioral flexibility in great-tailed grackles (Quiscalus mexicanus). For temporal repeatability, we quantified the number of trials to form a color preference after each of multiple color reversals on a serial reversal learning task. For contextual repeatability, we then compared performance on the serial color reversal task to the latency to switch among solutions on each of two different multi-access boxes. We found that the number of trials to form a preference in reversal learning was repeatable across serial color reversals and the latency to switch a preference was repeatable across color reversal learning and the multi-access box contexts. This supports the idea that the reversal learning task structure elicits performance reflective of an inherent trait, and that reversal learning and solution switching on multi-access boxes similarly reflect the inherent trait of behavioral flexibility.
McCune et al. (2023) Using repeatability of performance within and across contexts to validate measures of behavioral flexibility. PeerJ 11:e15773 https://doi.org/10.7717/peerj.15773
Review of knockout technology approaches in bacterial drug resistance research
Gene knockout is a widely used method in biology for investigating gene function. Several technologies are available for gene knockout, including zinc-finger nuclease technology (ZFN), suicide plasmid vector systems, transcription activator-like effector protein nuclease technology (TALEN), Red homologous recombination technology, CRISPR/Cas, and others. Of these, Red homologous recombination technology, CRISPR/Cas9 technology, and suicide plasmid vector systems have been the most extensively used for knocking out bacterial drug resistance genes. These three technologies have been shown to yield significant results in researching bacterial gene functions in numerous studies. This study provides an overview of current gene knockout methods that are effective for genetic drug resistance testing in bacteria. The study aims to serve as a reference for selecting appropriate techniques.
Tong et al. (2023) Review of knockout technology approaches in bacterial drug resistance research. PeerJ 11:e15790 https://doi.org/10.7717/peerj.15790
Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives database
We built the Curcumin Chalcone Derivatives Database (CCDD) to enable the effective virtual screening of highly potent curcumin and its analogs. The two-dimensional (2D) structures were drawn using the ChemBioOffice package and converted to 3D structures using Discovery Studio Visualizer V 2021 (DS). The database was built using different Python modules. For the 3D structures, different Python packages were used to obtain the data frame of compounds. This framework is also used to visualize the compounds. The webserver enables the users to screen the compounds according to Lipinski’s rule of five. The structures can be downloaded in .sdf and .mol format. The data frame (df) can be downloaded in .csv format. Our webserver can help computational drug discovery researchers find new therapeutics and build new webservers. The CCDD is freely available at: https://srampogu-ccdd-ccdd-8uldk8.streamlit.app/.
Rampogu et al. (2023) Curcumin Chalcone Derivatives Database (CCDD): a Python framework for natural compound derivatives database. PeerJ 11:e15885 https://doi.org/10.7717/peerj.15885
MMP12 serves as an immune cell–related marker of disease status and prognosis in lung squamous cell carcinoma
Background Worldwide, lung squamous cell carcinoma (LUSC) has wreaked havoc on humanity. Matrix metallopeptidase 12 (MMP12) plays an essential role in a variety of cancers. This study aimed to reveal the expression, clinical significance, and potential molecular mechanisms of MMP12 in LUSC. Methods There were 2,738 messenger RNA (mRNA) samples from several multicenter databases used to detect MMP12 expression in LUSC, and 125 tissue samples were validated by immunohistochemistry (IHC) experiments. Receiver operator characteristic (ROC) curves, Kaplan–Meier curves, and univariate and multivariate Cox regression analyses were used to assess the clinical value of MMP12 in LUSC. The potential molecular mechanisms of MMP12 were explored by gene enrichment analysis and immune correlation analysis. Furthermore, single-cell sequencing was used to determine the distribution of MMP12 in multiple tumor microenvironment cells. Results MMP12 was significantly overexpressed at the mRNA level (p < 0.05, SMD = 3.13, 95% CI [2.51–3.75]), which was verified at the protein level (p < 0.001) by internal IHC experiments. MMP12 expression could be used to differentiate LUSC samples from normal samples, and overexpression of MMP12 itself implied a worse clinical prognosis and higher levels of immune cell infiltration in LUSC patients. MMP12 was involved in cancer development and progression through two immune-related signaling pathways. The high expression of MMP12 in LUSC might act as an antigen-presenting cell–associated tumor neoantigen and activate the body’s immune response. Conclusions MMP12 expression is upregulated in LUSC and high expression of MMP12 serves as a risk factor for LUSC patients. MMP12 may be involved in cancer development by participating in immune-related signaling pathways and elevating the level of immune cell infiltration.
Zhang et al. (2023) MMP12 serves as an immune cell–related marker of disease status and prognosis in lung squamous cell carcinoma. PeerJ 11:e15598 https://doi.org/10.7717/peerj.15598
Hub gene associated with prognosis in bladder cancer is a novel therapeutic target
Objective Bladder cancer is a clinical and social conundrum due to its high incidence and recurrence rate. It is urgent to find new targets for the diagnosis and treatment of bladder cancer and improve the prognosis and survival rate of bladder cancer patients. We sought a prognosis-related gene, built related models of evaluated bladder cancer and identified the function of the hub gene in bladder cancer. Methods We downloaded the data of bladder cancer patients from the TCGA database, and used differentially expressed genes (DEGs), copy number variation (CNV) and survival analysis to scan the hub genes associated with prognosis in bladder cancer. Then, multi-factor cox regression was used to obtain the bladder cancer prognosis correlation model. Then, we analyzed the relationship between the expression of hub gene and immune microenvironment of bladder cancer. The relationship between the expression of hub gene and prognosis in bladder cancer patients was verified by immunohistochemistry. Cell proliferation assay and drug sensitivity test in vivo were used to verify the inhibition of bladder cancer by targeted inhibitors. Results In bladder cancer, we screened seven hub genes (ACLY, CNP, NKIRAS2, P3H4, PDIA6, VPS25 and XPO1) associated with survival. Moreover, the multifactor regression model constructed with hub gene can well distinguish the prognosis of bladder cancer. Hub gene is mostly associated with immune microenvironment. Immunohistochemical results basically confirmed the importance of XPO1 in bladder cancer. Selinexor (an inhibitor of XPO1) could effectively inhibit the proliferation of bladder cancer in the cell proliferation experiments by CCK-8 assays and it could suppress the growth of bladder cancer in mouse bladder cancer model. Conclusions In this study, a prognostic model with seven hub genes has provided great help for the prognosis prediction of bladder cancer patients. And XPO1 is an important target affecting the prognosis of bladder cancer, and inhibition of XPO1 can effectively inhibit bladder cancer proliferation and growth.
Fang et al. (2023) Hub gene associated with prognosis in bladder cancer is a novel therapeutic target. PeerJ 11:e15670 https://doi.org/10.7717/peerj.15670
Antifungal effects of eugenol on Candida albicans adherence to denture polymers
Background The study’s objective is to assess the adherence of C. albicans in different types of denture polymers and the effectiveness of eugenol and commercialized denture cleansers in the removal of C. albicans. Three types of denture base polymers (Lucitone® 199 (High-Impact PMMA), Impact® (conventional PMMA) and Eclipse® (UDMA)) and two hard denture reline materials (Kooliner® and Tokuyama® Rebase II Fast) were used in this study. Methods Three hundred samples were prepared (6 × 2 mm disc shape) and divided into five groups of denture polymers (n = 60) and further subjected into five treatment groups (Polident®, Steradent, distilled water, eugenol 5-minutes, and eugenol 10-min). Three samples were extracted from each treatment group for baseline data (n = 12). Baseline data were used to calculate the initial number of C. albicans adherence. A 0.5 ml immersion solution from each specimen was cultured on YPD agar and incubated for 48 h at 37 °C. Visible colonies were counted using a colony counter machine (ROCKER Galaxy 230). Results The result showed that the denture base polymer significantly affected the initial adherence (p = 0.007). The removal of C. albicans was also considerably affected by the denture base polymers and denture cleansers (p < 0.05). Lucitone®, Tokuyama®, and Kooliner® denture base polymers immersed for 3 min in eugenol showed the best results of removal. Discussion This study’s overall results showed that all denture polymers used as denture bases had an effect on C. albicans initial adherence and removal from the denture base, and eugenol is comparable to commercialised denture cleansers in reducing the number of attached C. albicans on denture base polymers.
Zanul Abidin et al. (2023) Antifungal effects of eugenol on Candida albicans adherence to denture polymers. PeerJ 11:e15750 https://doi.org/10.7717/peerj.15750
Life-expectancy changes during the COVID-19 pandemic from 2019–2021: estimates from Japan, a country with low pandemic impact
Background The COVID-19 pandemic had a low impact on Japan in 2020, but the size of the epidemic increased considerably there in 2021. This study made a statistical analysis of life expectancy changes up to the end of 2021 in Japan. Objective We aimed to estimate changes in life expectancy from 2019 to 2021 associated with the COVID-19 pandemic. To do so, we decomposed the life expectancy changes from 2020–2021 into age-specific and cause of death-specific contributions. Methods We used the absolute number of deaths by age and prefecture in Japan to calculate life expectancy from 2019–21 at both national and prefectural levels, and also examined the correlation between life expectancy gap and annual number of COVID-19 cases, total person-days spent in intensive care, and documented deaths due to COVID-19. We used the Arriaga decomposition method to decompose national life expectancy changes from 2020 to 2021 into age and cause of death components. Results From 2019–2020, Japan’s national level life expectancy across the entire population was extended by 0.24 years. From 2020–2021, it shortened by 0.15 years. The life expectancy shortened more among women (0.15 years) than men (0.12 years). There was significant heterogeneity in life expectancy changes from 2020–2021 by prefecture. It ranged from the maximum shortening of 0.57 years in Tottori prefecture to the maximum extension of 0.23 years in Fukui. The regression analysis revealed the negative correlation between the life expectancy change and burden of COVID-19 at prefectural level. The decomposition of life expectancy changes at birth from 2020–2021 showed that losses in life expectancy were largely attributable to the mortality of the population over 70 years old. Changes in life expectancy among infants and working-age adults mostly contributed to lengthening overall life expectancy. Among leading major causes of death, deaths due to neoplastic tumor and cardiovascular diseases contributed to shortening life expectancy, whereas respiratory diseases did not. Conclusion The decades-long increasing trend in life expectancy was suspended by the COVID-19 pandemic. However, life expectancy changes from 2019–2020 and 2020–2021 were small in Japan. This may be attributable to the small epidemiological impact of COVID-19 during this time period, but nonetheless, the negative impact of COVID-19 on life expectancy was indicated in the present study. The chance of death accelerated in older people in 2021, but a smaller number of deaths than usual among infants and working age adults contributed to extended life expectancy, and the change in the cause of death structure under the COVID-19 pandemic also significantly contributed to shortening life expectancy.
Munira et al. (2023) Life-expectancy changes during the COVID-19 pandemic from 2019–2021: estimates from Japan, a country with low pandemic impact. PeerJ 11:e15784 https://doi.org/10.7717/peerj.15784
Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies
Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.
Rollin et al. (2023) Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies. PeerJ 11:e15816 https://doi.org/10.7717/peerj.15816
LIDER: cell embedding based deep neural network classifier for supervised cell type identification
Background Automatic cell type identification has been an urgent task for the rapid development of single-cell RNA-seq techniques. Generally, the current approach for cell type identification is to generate cell clusters by unsupervised clustering and later assign labels to each cell cluster with manual annotation. Methods Here, we introduce LIDER (celL embeddIng based Deep nEural netwoRk classifier), a deep supervised learning method that combines cell embedding and deep neural network classifier for automatic cell type identification. Based on a stacked denoising autoencoder with a tailored and reconstructed loss function, LIDER identifies cell embedding and predicts cell types with a deep neural network classifier. LIDER was developed upon a stacked denoising autoencoder to learn encoder-decoder structures for identifying cell embedding. Results LIDER accurately identifies cell types by using stacked denoising autoencoder. Benchmarking against state-of-the-art methods across eight types of single-cell data, LIDER achieves comparable or even superior enhancement performance. Moreover, LIDER suggests comparable robust to batch effects. Our results show a potential in deep supervised learning for automatic cell type identification of single-cell RNA-seq data. The LIDER codes are available at https://github.com/ShiMGLab/LIDER.
Tang et al. (2023) LIDER: cell embedding based deep neural network classifier for supervised cell type identification. PeerJ 11:e15862 https://doi.org/10.7717/peerj.15862
Effects of post-activation protocols based on slow tempo bodyweight squat and isometric activity on vertical jump height enhancement in trained males: a randomized controlled trial
This study aimed to establish the effectiveness of slow tempo bodyweight squat combined with an isometric squat (ST-ISO), and an isometric squat alone (ISO), as a post-activation performance enhancement protocol (PAPE) for jump height improvement. The study sample consisted of 41 trained men aged 18–24. The ST-ISO group (n = 17) performed three five-second sets of the maximal voluntary back squat while pushing on an immovable bar and two sets of five repetitions of a slow-tempo (5-0-5-0) body squat immediately after isometry with a 2-m rest interval. The ISO (n = 14) group only performed isometric squats, and the control group (CG; n = 10) performed a 5-min treadmill run at 6 km/h. The countermovement jump (CMJ) height results were analyzed from the baseline and then at 3, 5, 7, and 9 min after the PAPE protocols. The statistical significance was set at p < 0.05. RM-ANOVA revealed differences in the group-minute interaction (F = 2.70; p = 0.0083; η2 = 0.1243), and post-hoc tests demonstrated a significant decrease in CMJ after 5 min in the ISO group (p < 0.0446). The performance of the ST-ISO group markedly decreased in the 3rd and 7th min after PAPE (p = 0.0137; p = 0.0424, respectively), though it improved significantly in the final minute (p < 0.0030). Chi-squared analysis revealed that the ST-ISO group peaked more frequently in the 9th min (X2 = 17.97; p = 0.0214). However, CMJ height improvement did not differ between the PAPE protocols, thus it was close to statistical significance (t = −1.82; p = 0.07; ES = 0.7). The ST-ISO protocol provided jump enhancement, though the deterioration observed in the first minutes after the protocols suggest the rest period after activity requires attention, and the methods need to be individualized.
Koźlenia et al. (2023) Effects of post-activation protocols based on slow tempo bodyweight squat and isometric activity on vertical jump height enhancement in trained males: a randomized controlled trial. PeerJ 11:e15753 https://doi.org/10.7717/peerj.15753