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Cancer is one of the most deadly diseases that annually kills millions of people worldwide. The investigation on anticancer medicines has never ceased to seek better and more adaptive agents with fewer side effects. Besides chemically synthetic anticancer compounds, natural products are scientifically proved as a highly potential alternative source for anticancer drug discovery. Along with experimental approaches being used to find anticancer drug candidates, computational approaches have been developed to virtually screen for potential anticancer compounds. In this study, we construct an ensemble computational framework, called iANP-EC, using machine learning approaches incorporated with evolutionary computation. Four learning algorithms (

Peristaltic movement of the intestine propels food down the length of the gastrointestinal tract to promote nutrient absorption. Interactions between intestinal macrophages and the enteric nervous system regulate gastrointestinal motility, yet we have an incomplete understanding of the molecular mediators of this crosstalk. Here we identify complement component 1q (C1q) as a macrophage product that regulates gut motility. Macrophages were the predominant source of C1q in the mouse intestine and most extraintestinal tissues. Although C1q mediates complement-mediated killing of bacteria in the bloodstream, we found that C1q was not essential for immune defense of the intestine. Instead, C1q-expressing macrophages were localized to the intestinal submucosal plexus where they closely associated with enteric neurons and expressed surface markers characteristic of nerve-adjacent macrophages in other tissues. Mice with a macrophage-specific deletion ofC1qashowed changes in enteric neuronal gene expression, increased peristaltic activity, and accelerated intestinal transit. Our findings identify C1q as a key regulator of gastrointestinal motility and provide enhanced insight into the crosstalk between macrophages and the enteric nervous system.

Additional file 1: Supplementary Table 1: Model performance of iPromoter-Seqvec and DeePromoter on the validation sets. Supplementary Figure 1: ROC curves of iPromoter-Seqvec and iPro-EL on different independent test sets. Supplementary Figure 2: PR curves of iPromoter-Seqvec and iPro-EL on different independent test sets.

Background The evaluation of nutrient variability plays a crucial role in accessing soil potentials and practical intervention responses in rice production systems. Synthetic fertilizer applications and cultivation practices are considered key factors affecting nutrient dynamics and availability. Here, we assessed the nutrient dynamics in surface, subsurface water and soil under local water management and conventional rice cultivation practices in the Vietnamese Mekong Delta. Methods We implemented a field experiment (200 m 2) in the 2018 wet season and the 2019 dry season in a triple rice-cropping field. Eight samples of surface water, subsurface water (30–45 cm), and topsoil (0–20 cm) were collected and analysed during the rice-growing seasons. Results The results showed that N-NH 4+, P-PO 43- and total P peaks were achieved after fertilizing. Irrespective of seasons, the nutrient content in surface water was always greater than that of subsurface water (P<0.001), with the exception of N-NO 3-, which was insignificant (P>0.05). When comparing the wet and dry seasons, nutrient concentrations exhibited minor differences (P>0.05). Under conventional rice cultivation, the effects of synthetic fertilizer topdressing on the total N, soil organic matter (SOM), and total P were negligible in the soil. Higher rates of N fertilizer application did not significantly increase soil N-NH 4+, total N, yet larger P fertilizer amounts substantially enhanced soil total P (P<0.001). Conclusions Under conventional rice cultivation, N-NH 4+, P-PO 43- and total P losses mainly occur through runoff rather than leaching. While N-NO 3- loss is similar in surface water and subsurface water. Notably, nutrient content in soil was high; whilst SOM was seen to be low-to-medium between seasons. Future work should consider the nutrient balance and dynamic simulation in the lowland soil of the Vietnamese Mekong Delta’s paddy fields.

Background Since protein-DNA interactions are highly essential to diverse biological events, accurately positioning the location of the DNA-binding residues is necessary. This biological issue, however, is currently a challenging task in the age of post-genomic where data on protein sequences have expanded very fast. In this study, we propose iProDNA-CapsNet – a new prediction model identifying protein-DNA binding residues using an ensemble of capsule neural networks (CapsNets) on position specific scoring matrix (PSMM) profiles. The use of CapsNets promises an innovative approach to determine the location of DNA-binding residues. In this study, the benchmark datasets introduced by Hu et al. (2017), i.e., PDNA-543 and PDNA-TEST, were used to train and evaluate the model, respectively. To fairly assess the model performance, comparative analysis between iProDNA-CapsNet and existing state-of-the-art methods was done. Results Under the decision threshold corresponding to false positive rate (FPR) ≈ 5%, the accuracy, sensitivity, precision, and Matthews’s correlation coefficient (MCC) of our model is increased by about 2.0%, 2.0%, 14.0%, and 5.0% with respect to TargetDNA (Hu et al., 2017) and 1.0%, 75.0%, 45.0%, and 77.0% with respect to BindN+ (Wang et al., 2010), respectively. With regards to other methods not reporting their threshold settings, iProDNA-CapsNet also shows a significant improvement in performance based on most of the evaluation metrics. Even with different patterns of change among the models, iProDNA-CapsNets remains to be the best model having top performance in most of the metrics, especially MCC which is boosted from about 8.0% to 220.0%. Conclusions According to all evaluation metrics under various decision thresholds, iProDNA-CapsNet shows better performance compared to the two current best models (BindN and TargetDNA). Our proposed approach also shows that CapsNet can potentially be used and adopted in other biological applications.

This research aims to compare the performance of ARIMA as a linear model with that of the combination of ARIMA and GARCH family models to forecast S&P500 log returns in order to construct algorithmic investment strategies on this index. We used the data collected from Yahoo Finance with daily frequency for the period from 1 January 2000 to 31 December 2019. By using a rolling window approach, we compared ARIMA with the hybrid models to examine whether hybrid ARIMA-SGARCH and ARIMA-EGARCH can really reflect the specific time-series characteristics and have better predictive power than the simple ARIMA model. In order to assess the precision and quality of these models in forecasting, we compared their equity lines, their forecasting error metrics (MAE, MAPE, RMSE, MAPE), and their performance metrics (annualized return compounded, annualized standard deviation, maximum drawdown, information ratio, and adjusted information ratio). The main contribution of this research is to show that the hybrid models outperform ARIMA and the benchmark (Buy&Hold strategy on S&P500 index) over the long term. These results are not sensitive to varying window sizes, the type of distribution, and the type of the GARCH model.

This study presented an overview of current developments in optical micro-electromechanical systems in biomedical applications. Optical micro-electromechanical system (MEMS) is a particular class of MEMS technology. It combines micro-optics, mechanical elements, and electronics, called the micro-opto electromechanical system (MOEMS). Optical MEMS comprises sensing and influencing optical signals on micron-level by incorporating mechanical, electrical, and optical systems. Optical MEMS devices are widely used in inertial navigation, accelerometers, gyroscope application, and many industrial and biomedical applications. Due to its miniaturised size, insensitivity to electromagnetic interference, affordability, and lightweight characteristic, it can be easily integrated into the human body with a suitable design. This study presented a comprehensive review of 140 research articles published on photonic MEMS in biomedical applications that used the qualitative method to find the recent advancement, challenges, and issues. The paper also identified the critical success factors applied to design the optimum photonic MEMS devices in biomedical applications. With the systematic literature review approach, the results showed that the key design factors could significantly impact design, application, and future scope of work. The literature of this paper suggested that due to the flexibility, accuracy, design factors efficiency of the Fibre Bragg Grating (FBG) sensors, the demand has been increasing for various photonic devices. Except for FBG sensing devices, other sensing systems such as optical ring resonator, Mach-Zehnder interferometer (MZI), and photonic crystals are used, which still show experimental stages in the application of biosensing. Due to the requirement of sophisticated fabrication facilities and integrated systems, it is a tough choice to consider the other photonic system. Miniaturisation of complete FBG device for biomedical applications is the future scope of work. Even though there is a lot of experimental work considered with an FBG sensing system, commercialisation of the final FBG device for a specific application has not been seen noticeable progress in the past.

The research into and production of hematological reference samples used to implement an external quality assessment (EQA) to check the quality of hematology tests are necessary for hematology laboratories in Vietnam. In this research, the study team determined the assessment values of blood cell count (human RBCs, pseudo-leucocytes, and pseudo-platelets) by the impedance method used in hematology EQA programs. The hematological reference samples were controlled at three concentration levels: low, normal, and high. Determination of the assigned value (mean ± 2SD) was performed for the following hematology analyzer series by impedance method: ABX Micros 60, Celldyn 1700, and Mindray BC 2000. Each device was sent to 10 different laboratories for evaluation. Research results for assigned values of each model (ABX Micros 60, Celldyn 1700, and Mindray BC 2000) were determined at the three concentrations. For the ABX Micros 60 and Celldyn 1700 series, 80% of laboratories had analytical results within assigned values. For the Mindray BC 2000 series, 100% of laboratories had analytical results within assigned values. The measurement results for the number of human RBCs, pseudo-leucocytes, and pseudo-platelets on each analyzer were similar between the 10 laboratories; the results of the three hematology analyzer series using the impedance method were different and the difference was statistically significant (p < 0.05). Thus, hematological reference samples for measuring the number of blood cells meeting the standards so that they can evaluate the results of laboratories using the impedance method: ABX, Celldyn 1700, Mindray BC 2000.

This paper examines the impact of the dike systems on river flows in the Vietnamese Mekong Delta (VMD). The study combined a hydrological change index method and the Mann–Kendall test to assess the temporal dynamics of both discharge and water levels along the main rivers of the VMD. Results highlight that the system of rivers and canals helps facilitate waterway traffic and drainage during the flood season. However, the low elevation of the delta has created conditions suitable for saline water to increasingly penetrate upstream during the dry season. Observed changes in the hydrological indicators at the upstream stations of Tan Chau (Mekong River) and Chau Doc (Bassac River) are not only due to the dike system but also upstream alterations to the flow regime. More research is needed to consider the various drivers of flow-regime change associated with natural and human activities both inside and outside of the study area.

Groundwater is among the Nation’s most important natural resources. It provides drinking water to urban and rural communities, supports irrigation and industry, sustains the flow of streams and rivers, and maintains riparian and wetland ecosystems. In many areas of the Nation, the future sustainability of groundwater resources is at risk from overuse and contamination. Groundwater extraction not only regulates the shape of the ground surface and but also has a significant influence on human life. However, the occurrence of estimating the settlement of ground surface is still not well-studied. The objective of this study is to assess relation between groundwater pumping and land subsidence in Cai Rang district, Can Tho city. It is carried out by following steps: (1) Collecting geological prospecting data;(2) Conducting the method of ground water pumping test; (3) Processing the collected data; (4) Using Riley, Lohman and Poland methods in estimating the settlement of ground surface; (5) Using Finite element method to stimulate land subsidence. The result shows that the hydro-geological parameters, K is of 18.05 m/h; S is of 0.0083; T is of 299.608 m2/d. The cumulative land subsidence varies in the range of from 0 to 0.66 cm. Consequence of the land subsidence does not considerably affect construction work in the area. The analytical and interpretive methods described in this study will be useful to scientists involved in studies of ground-water hydraulics and aquifersystem deformation.

3-Hydroxypropionic acid (3-HP) is a platform chemical which has potential applications in cosmetic and polymer industries. Microbial production of 3-HP is hampered by its toxic effect when its concentration is high (300 mM). In this study, the effect of yohJK overexpression (via yieP deletion or episomal overexpression) on 3-HP tolerance was investigated in Klebsiella pneumoniae, Pseudomonas denitrificans and P. asiatica. The deletion of yieP homolog could improve 3-HP tolerance in K. pneumoniae. Transcriptional analysis suggested that, among the two yohJK homologs of K. pneumoniae, expression of yohJK1, not yohJK2, was under the negative control of YieP. Furthermore, deletion of yieP significantly reduced cytoplasmic 3-HP concentration when determined by 3-HP biosensor and enhanced 3-HP tolerance and 3-HP production. This study demonstrates that the YohJK1 functions as 3-HP transporter in K. pneumoniae and their overexpression by the yieP deletion is a good strategy to enhance 3-HP tolerance and its production.

There is a growing body of literature supporting the utilization of machine learning (ML) to improve diagnosis and prognosis tools of cardiovascular disease. The current study was to investigate the impact that the ML framework may have on the sensitivity of predicting the presence or absence of congenital heart disease (CHD) using fetal echocardiography. A comprehensive fetal echocardiogram including 2D cardiac chamber quantification, valvar assessments, assessment of great vessel morphology, and Doppler-derived blood flow interrogation was recorded. The postnatal echocardiogram was used to ascertain the diagnosis of CHD. A random forest (RF) algorithm with a nested tenfold cross-validation was used to train models for assessing the presence of CHD. The study population was derived from a database of 3910 singleton fetuses with maternal age of 28.8 ± 5.2 years and gestational age at the time of fetal echocardiography of 22.0 weeks (IQR 21-24). The proportion of CHD was 14.1% for the studied cohort confirmed by post-natal echocardiograms. Our proposed RF-based framework provided a sensitivity of 0.85, a specificity of 0.88, a positive predictive value of 0.55 and a negative predictive value of 0.97 to detect the CHD with the mean of mean ROC curves of 0.94 and the mean of mean PR curves of 0.84. Additionally, six first features, including cardiac axis, peak velocity of blood flow across the pulmonic valve, cardiothoracic ratio, pulmonary valvar annulus diameter, right ventricular end-diastolic diameter, and aortic valvar annulus diameter, are essential features that play crucial roles in adding more predictive values to the model in detecting patients with CHD. ML using RF can provide increased sensitivity in prenatal CHD screening with very good performance. The incorporation of ML algorithms into fetal echocardiography may further standardize the assessment for CHD.

When users in virtual reality cannot physically walk and self-motions are instead only visually simulated, spatial updating is often impaired. In this paper, we report on a study that investigated if HeadJoystick, an embodied leaning-based flying interface, could improve performance in a 3D navigational search task that relies on maintaining situational awareness and spatial updating in VR. We compared it to Gamepad, a standard flying interface. For both interfaces, participants were seated on a swivel chair and controlled simulated rotations by physically rotating. They either leaned (forward/backward, right/left, up/down) or used the Gamepad thumbsticks for simulated translation. In a gamified 3D navigational search task, participants had to find eight balls within 5 min. Those balls were hidden amongst 16 randomly positioned boxes in a dark environment devoid of any landmarks. Compared to the Gamepad, participants collected more balls using the HeadJoystick. It also minimized the distance travelled, motion sickness, and mental task demand. Moreover, the HeadJoystick was rated better in terms of ease of use, controllability, learnability, overall usability, and self-motion perception. However, participants rated HeadJoystick could be more physically fatiguing after a long use. Overall, participants felt more engaged with HeadJoystick, enjoyed it more, and preferred it. Together, this provides evidence that leaning-based interfaces like HeadJoystick can provide an affordable and effective alternative for flying in VR and potentially telepresence drones.

Hematological reference samples for external quality assessment (EQA) in hematology are essential for many laboratories in Vietnam, however, the prices are high along with short storing time. This study attempted to establish an optimal formula for the manufacture of hematological reference samples for hematological EQA programs. Human red blood cells (RBCs) were mixed with goose RBCs (pseudo-leucocytes) and goat RBCs (pseudo-platelets) as alternatives for white blood cells (WBCs) and platelets (PLTs), respectively, in different formulas of storage media. The optimal formula was obtained using response surface methodology–central composite design (RSM-CCD). Three main factors affecting the concentrations of RBCs were determined by Plackett–Burmann matrix. The optimal concentrations determined by RSM-CCD were 46% serum, 0.44 g/L neomycin sulfate, and 2.5% glycerol. The model predicted that the maximum number of human RBCs was 4.1 × 1012 cells/L, pseudo-leucocytes was 6.4 × 109 cells/L, and pseudo-platelets was 188 × 109 cells/L. The practical concentrations of RBCs, pseudo-leucocytes, and pseudo-platelets were 4.21 × 1012 cells/L, 6.4 × 109 cells/L, and 187 × 109 cells/L, respectively, which showed 98.93% similarity with theoretical data. This result could be a premise for further study to improve manufacturing of hematological reference samples for hematology EQA programs.

Due to stringent regulatory norms, waste processing faces confrontations and challenges in adapting technology for effective management through a convenient and economical system. At the global level, attempts are underway to achieve a green and sustainable treatment for the valorization of lignocellulosic biomass as well as organic contaminants in wastewater. Enzymatic treatment in the environmental aspect thrived on being the promising rapid strategy that appeased the aforementioned predicament. On that account, coimmobilization of various enzymes on single support enhances the catalytic activity ensuing operational stability with industrial applications. This review pivoted towards the coimmobilization of enzymes on diverse supports and their applications in biomass conversion to industrial value-added products and removal of contaminants in wastewater. The limelight of this study chronicles the unique breakthroughs in biotechnology for the production of reusable biocatalysts, which inculcating various enzymes towards the scope of environment application.

Pollution due to heavy metals is a global issue in recent years. Initially, there were fewer contaminants, which has increased exponentially owing to rapid industrialization and various anthropogenic activities. Toxicity due to heavy metals causes a lot of health problems and organ system failure in human beings. It also affects other forms of living beings such as plants, animals and even the microbiota. This has been reported by various press reports and research findings. In this review, the production of heavy metals, associated effects on the environment and the technologies employed for detecting these heavy metals are comprehensively discussed. The analytical instruments, including biosensors, have been found to be more beneficial than other techniques. Biosensor exhibits numerous special features, such as reproducibility, reusability, linearity, sensitivity, selectivity, and stability. Over the last three years, biosensors have also had a detection limit of 65.36 ng/mL for heavy metals. The design of biosensors, features and types were also explained in detail. The limit of detection for the heavy metals in wastewater using biosensors was also included with recent references up to the last five years.

Bullous pemphigoid is the most common autoimmune blistering skin disease. Pathogenesis involves autoantibodies that attack the basement membrane, resulting in blisters and intense pruritus. We present a case of bullous pemphigoid with concurrent excoriation disorder in a woman in her 50s. The suspected diagnosis of bullous pemphigoid was confirmed through direct immunofluorescence testing on a specimen obtained via punch biopsy, then treated with vancomycin and steroids. In addition, cross tapering from duloxetine to fluoxetine was used to treat the patient’s excoriation disorder. The concurrent dermatological and psychiatric components, as well as the severity, made this case unique.

Patient experience is being widely considered in evaluating the quality of health care services. This is a cross-sectional study with 860 inpatients hospitalized in 4 clinical departments (General Internal Medicine; Cardiology; General Surgery; Surgery, and Orthopedic Trauma) of the Kien Giang General Hospital, from April to June 2020. Data was collected through a two-part questionnaire used to evaluate the inpatient experience during hospital treatment, using the Likert scale 5 points. The patient’s experience is classified into 3 aspects (environment—facilities, healthcare staff's care, treatment information). In total, 815 participants responded to the interview (94.8%). The rates of patients having a positive experience on the environment and facilities, the care of health workers, and treatment information are 31.7%, 85.9%, and 74.2%, respectively. The patient’s positive overall experience rate is 65.5%. Factors related to the patient's overall experience are the department of treatment, residential area, age, and employment status ( P