Recent progress in machine learning approaches for predicting carcinogenicity in drug development.

INTRODUCTION: This review explores the transformative impact of machine learning (ML) on carcinogenicity prediction within drug development. It discusses the historical context and recent advancements, emphasizing the significance of ML methodologies in overcoming challenges related to data interpretation, ethical considerations, and regulatory acceptance. AREAS COVERED: The review comprehensively examines the integration of ML, deep learning, and diverse artificial intelligence (AI) approaches in various aspects of drug development safety assessments. It explores applications ranging from early-phase compound screening to clinical trial optimization, highlighting the versatility of ML in enhancing predictive accuracy and efficiency. EXPERT OPINION: Through the analysis of traditional approaches such as in vivo rodent bioassays and in vitro assays, the review underscores the limitations and resource intensity associated with these methods. It provides expert insights into how ML offers innovative solutions to address these challenges, revolutionizing safety assessments in drug development.

A highly selective KIT inhibitor MOD000001 suppresses IgE-mediated mast cell activation.

Background: The KIT receptor tyrosine kinase and its ligand, stem cell factor (SCF), control proliferation and survival of mast cells. Thus, targeting KIT signaling may show promise for the treatment of allergic diseases involving mast cells. Recently, we discovered a new compound, MOD000001, as a potential small-molecule KIT kinase inhibitor by using an in silico approach. Objective: We sought to determine whether MOD000001 is highly selective to KIT, inhibits KIT signaling in mast cells, and affects IgE-mediated mast cell activation. Methods: The interaction of MOD000001 with 468 human kinases and its inhibitory activity against KIT were profiled and evaluated by using KINOMEscan (Discover X/Eurofins Corporation, Fremont, Calif) and cell-free kinase assays, respectively. The effects of MOD000001 on SCF-dependent signaling were examined by using primary mouse and human mast cells. The effects of MOD000001 on SCF-induced degranulation and passive cutaneous anaphylaxis reaction were examined in mice. Results: MOD000001 interacted with KIT and inhibited KIT kinase activity with high selectivity. MOD000001 suppressed SCF-induced KIT signaling in mouse and human mast cells and in mice. Passive cutaneous anaphylaxis reaction was suppressed in mice treated with MOD000001 both for a short-term (1 week) and for a long-term (7 weeks). Mice treated with MOD000001 for a long-term, but not for a short-term, showed skin mast cell reduction. Conclusions: MOD000001 is a highly selective KIT inhibitor that can suppress IgE-mediated mast cell activation in vivo. MOD000001 may do so by reducing tissue mast cell numbers or by other unknown mechanisms. The findings suggest potential benefits of MOD000001 for allergic diseases involving IgE-mediated mast cell activation.

Influence of purple non-sulfur bacterial augmentation on soil nutrient dynamics and rice (Oryza sativa) growth in acidic saline-stressed environments.

The aim of the current study was to assess the potency of the exopolymeric substances (EPS)-secreting purple non-sulfur bacteria (PNSB) on rice plants on acidic salt-affected soil under greenhouse conditions. A two-factor experiment was conducted following a completely randomized block design. The first factor was the salinity of the irrigation, and the other factor was the application of the EPS producing PNSB (Luteovulum sphaeroides EPS18, EPS37, and EPS54), with four replicates. The result illustrated that irrigation of salt water at 3-4‰ resulted in an increase in the Na+ accumulation in soil, resulting in a lower rice grain yield by 12.9-22.2% in comparison with the 0‰ salinity case. Supplying the mixture of L. sphaeroides EPS18, EPS37, and EPS54 increased pH by 0.13, NH4+ by 2.30 mg NH4+ kg-1, and available P by 8.80 mg P kg-1, and decreased Na+ by 0.348 meq Na+ 100 g-1, resulting in improvements in N, P, and K uptake and reductions in Na uptake, in comparison with the treatment without bacteria. Thus, the treatments supplied with the mixture of L. sphaeroides EPS18, EPS37, and EPS54 resulted in greater yield by 27.7% than the control treatment.

Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains.

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR.

Oral hygiene status and oral care motivation in children aged 7-9 years in a Vietnam primary school: A cross-sectional study.

INTRODUCTION: Oral hygiene is a crucial factor in oral health, especially in children. To increase the awareness of oral care behaviour among children, oral care motivation plays a critical role in daily dental practices. Therefore, this cross-sectional study was conducted to investigate the current oral hygiene status and evaluate the association between oral care motivation and oral hygiene index in 7-9-year-old children at Primary School in Hanoi, Vietnam. METHODS: Clinical examinations were performed on 200 randomly selected children to assess the Simplified Oral Hygiene Index (OHI-S). Face-to-face interviews were applied to record students' intrinsic and extrinsic motivation for oral care through a questionnaire, which consisted of questions regarding demographic characteristics and oral care motivation. Data were analyzed using STATA 15.0 software and a p-value < 0.05 was statistically significant. RESULTS: The mean OHI-S score was 2.48 ± 0.72. Good and fair oral hygiene were observed in 7.5 % and 66 % of participants, respectively. Students' motivation for dental care was predominantly extrinsic, with a mean score of 15.87 ± 1.322. Higher motivation in dental care is statistically significantly associated with oral hygiene index score (Coef=-0.27). CONCLUSION: These results indicate that students with intrinsic motivation exhibit better oral hygiene practices. Consequently, strengthening oral health educational programs in primary schools based on intrinsic motivation could be helped improve the oral hygiene status and oral care behaviours of children.

Constructing B─N─P Bonds in Ultrathin Holey g-C3N4 for Regulating the Local Chemical Environment in Photocatalytic CO2 Reduction to CO.

The lack of intrinsic active sites for photocatalytic CO2 reduction reaction (CO2RR) and fast recombination rate of charge carriers are the main obstacles to achieving high photocatalytic activity. In this work, a novel phosphorus and boron binary-doped graphitic carbon nitride, highly porous material that exhibits powerful photocatalytic CO2 reduction activity, specifically toward selective CO generation, is disclosed. The coexistence of Lewis-acidic and Lewis-basic sites plays a key role in tuning the electronic structure, promoting charge distribution, extending light-harvesting ability, and promoting dissociation of excitons into active carriers. Porosity and dual dopants create local chemical environments that activate the pyridinic nitrogen atom between the phosphorus and boron atoms on the exposed surface, enabling it to function as an active site for CO2RR. The P-N-B triad is found to lower the activation barrier for reduction of CO2 by stabilizing the COOH reaction intermediate and altering the rate-determining step. As a result, CO yield increased to 22.45 µmol g-1 h-1 under visible light irradiation, which is ≈12 times larger than that of pristine graphitic carbon nitride. This study provides insights into the mechanism of charge carrier dynamics and active site determination, contributing to the understanding of the photocatalytic CO2RR mechanism.

Lattice dynamics and self-trapped excitons in the Cs2SnBr6double perovskites.

Our study delved into the detailed investigation of Cs2SnBr6double perovskites, focusing on their electrical properties, lattice dynamics, and stability. The direct bandgap for Cs2SnBr6was estimated to be at 2.93 eV. One external translational mode of the Cs+lattice withT2gsymmetry and three internal modes of the octahedral withA1g,Eg, andT2gsymmetries are defined by calculated lattice dynamics, experimental micro-Raman scattering. We show a correlation with first-principles calculations, validating using a band-structured electronic approach to understanding the behavior of charge carriers, and electron-phonon interactions in Cs2SnBr6. We propose that electron-vibration interactions result in self-trapped excitons (STEs) displaying significant Stokes shifts (0.508 eV) and broad-spectrum emission. Understanding the behavior of STEs is fundamental for their optoelectronic applications.

Enhanced photocatalytic performance of ZnO under visible light by co-doping of Ta and C using hydrothermal method.

This study attempted to improve the photocatalytic activity of zinc oxide (ZnO) semiconductors in the visible light region by introducing the co-doping of carbon (C) and tantalum (Ta) to ZnO (ZTC) using a simple hydrothermal method with the respective precursors. The obtained uniform ZTC nanoparticles with an average crystal size of 29.30 nm (according to Scherrer's equation) revealed a redshift with a decrease in bandgap (Eg) from 3.04 eV to 2.88 eV, allowing the obtained photocatalyst to absorb the energy of the visible light for photocatalysis. Furthermore, the Zn 2p and Ta 4f core level spectra confirmed the presence of Zn2+ and Ta5+ in the ZTC sample. In addition, the infrared spectra identified hydrogen-related defects (HRDs), while the O 1s spectra indicated the existence of oxygen vacancies (VO). Electrochemical tests revealed improvement in the electron conductivity and charge separation of the obtained materials. To follow, the photocatalytic performance assessment was conducted by varying the C/Zn2+ ratios (5, 10, and 15 mol%) in ZTC samples, the initial RhB concentration (7, 15, and 30 ppm), and the pH of the RhB solution (3.0-10.0). The photodegradation on ZTC samples showed the most effectiveness for a 7 ppm RhB solution with a C/Zn2+ ratio of 10 mol% in the slightly alkaline medium (pH 9.0). Additionally, ZTC also exhibited commendable durability after being reused several times. The nature of RhB photodegradation was proposed and discussed via a mechanism at the end of this work.

Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing.

Accurately predicting tumor T-cell antigen (TTCA) sequences is a crucial task in the development of cancer vaccines and immunotherapies. TTCAs derived from tumor cells, are presented to immune cells (T cells) through major histocompatibility complex (MHC), via the recognition of specific portions of their structure known as epitopes. More specifically, MHC class I introduces TTCAs to T-cell receptors (TCR) which are located on the surface of CD8+ T cells. However, TTCA sequences are varied and lead to struggles in vaccine design. Recently, Machine learning (ML) models have been developed to predict TTCA sequences which could aid in fast and correct TTCA identification. During the construction of the TTCA predictor, the peptide encoding strategy is an important step. Previous studies have used biological descriptors for encoding TTCA sequences. However, there have been no studies that use natural language processing (NLP), a potential approach for this purpose. As sentences have their own words with diverse properties, biological sequences also hold unique characteristics that reflect evolutionary information, physicochemical values, and structural information. We hypothesized that NLP methods would benefit the prediction of TTCA. To develop a new identifying TTCA model, we first constructed a based model with widely used ML algorithms and extracted features from biological descriptors. Then, to improve our model performance, we added extracted features from biological language models (BLMs) based on NLP methods. Besides, we conducted feature selection by using Chi-square and Pearson Correlation Coefficient techniques. Then, SMOTE, Up-sampling, and Near-Miss were used to treat unbalanced data. Finally, we optimized Sa-TTCA by the SVM algorithm to the four most effective feature groups. The best performance of Sa-TTCA showed a competitive balanced accuracy of 87.5% on a training set, and 72.0% on an independent testing set. Our results suggest that integrating biological descriptors with natural language processing has the potential to improve the precision of predicting protein/peptide functionality, which could be beneficial for developing cancer vaccines.

Long-term weight gain in children with craniopharyngioma.

OBJECTIVE: Adamantinomatous craniopharyngioma mainly affects children. Excessive weight gain is a major long-term complication. The primary objective of this study was to assess long-term weight changes in children treated for craniopharyngioma. The secondary objectives were to identify risk factors for excessive weight gain and to look for associations with hypothalamic damage by the tumour or treatment. DESIGN: Single-centre retrospective cohort study. METHOD: Children managed for craniopharyngioma at our centre between 1990 and 2019 were included. The body mass index (BMI) standard deviation scores (SDS) at baseline and at last follow-up were compared. Univariate and multivariate analyses were performed in order to identify variables associated with the long-term BMI-SDS variation. RESULTS: The 108 patients had a mean follow-up of 10.4 years. The mean BMI-SDS increase over time was 2.11 (P < .001) overall, 1.21 (P < .001) in the group without hypothalamic involvement by the tumour, and 1.95 (P < .001) in the group managed using intended hypothalamus-sparing surgery. The absence of hypothalamic involvement by the tumour or treatment was significantly associated with less weight gain (P = .046 and P < .01, respectively). After adjustment, factors associated with a BMI-SDS change greater than 2 were female sex (P = .023), tumour involving the hypothalamus (P = .04), and higher baseline BMI (P < .001). CONCLUSION: Clinically significant weight gain occurred in nearly all children treated for craniopharyngioma, including those whose hypothalamus was spared by the tumour and intentionally by treatment. However, hypothalamus integrity was associated with less weight gain. Despite hypothalamus-sparing strategies, hypothalamic obesity remains a major concern, indicating a need for novel treatment approaches.

Acute Kidney Injury After Percutaneous Coronary Intervention Guided by Intravascular Ultrasound.

Purpose We investigated the impact of intravascular ultrasound guidance on reducing the incidence of contrast-induced acute kidney injury (CI-AKI) in patients undergoing percutaneous coronary intervention (PCI). Methods Ninety-nine patients were enrolled in this prospective cohort who were not randomly assigned to angiography-guided percutaneous coronary intervention or intravascular ultrasound-guided percutaneous coronary intervention. The patients were hospitalized at the Vietnam National Heart Institute - Bach Mai Hospital between 2019 and 2020. Acute kidney injury incidence during hospitalization was the primary endpoint. Results A total of 99 patients were divided into two groups: the intravascular ultrasound-guided group (33 participants) and the angiography-guided group (66 participants). The mean ± SD contrast volume of each group was 95.2 ± 37.1 mL and 133.0 ± 36.0 mL for the ultrasound-guided and angiography-guided groups, with P < 0.0001. Intravascular imaging-guided percutaneous coronary intervention (IVUS-guided PCI) was associated with reduced acute kidney injury incidence during hospitalization: 0.0% vs. 12.12% and P = 0.049. Conclusions Intravascular ultrasound is a safe imaging tool that guides percutaneous coronary intervention and significantly reduces the rate of acute kidney injury compared to angiography alone. Patients who have a high chance of experiencing acute kidney injury benefit from using intravascular ultrasound.

Enhancing Nasopharyngeal Carcinoma Survival Prediction: Integrating Pre- and Post-Treatment MRI Radiomics with Clinical Data.

Recurrences are frequent in nasopharyngeal carcinoma (NPC) despite high remission rates with treatment, leading to considerable morbidity. This study aimed to develop a prediction model for NPC survival by harnessing both pre- and post-treatment magnetic resonance imaging (MRI) radiomics in conjunction with clinical data, focusing on 3-year progression-free survival (PFS) as the primary outcome. Our comprehensive approach involved retrospective clinical and MRI data collection of 276 eligible NPC patients from three independent hospitals (180 in the training cohort, 46 in the validation cohort, and 50 in the external cohort) who underwent MRI scans twice, once within 2 months prior to treatment and once within 10 months after treatment. From the contrast-enhanced T1-weighted images before and after treatment, 3404 radiomics features were extracted. These features were not only derived from the primary lesion but also from the adjacent lymph nodes surrounding the tumor. We conducted appropriate feature selection pipelines, followed by Cox proportional hazards models for survival analysis. Model evaluation was performed using receiver operating characteristic (ROC) analysis, the Kaplan-Meier method, and nomogram construction. Our study unveiled several crucial predictors of NPC survival, notably highlighting the synergistic combination of pre- and post-treatment data in both clinical and radiomics assessments. Our prediction model demonstrated robust performance, with an accuracy of AUCs of 0.66 (95% CI: 0.536-0.779) in the training cohort, 0.717 (95% CI: 0.536-0.883) in the testing cohort, and 0.827 (95% CI: 0.684-0.948) in validation cohort in prognosticating patient outcomes. Our study presented a novel and effective prediction model for NPC survival, leveraging both pre- and post-treatment clinical data in conjunction with MRI features. Its constructed nomogram provides potentially significant implications for NPC research, offering clinicians a valuable tool for individualized treatment planning and patient counseling.

Prevalence and determinants of constipation in children in Asia: a systematic review and meta-analysis.

Background: Constipation is prevalent worldwide, significantly increasing healthcare costs and diminishing the quality of life in children affected. Current studies have yielded mixed results regarding the factors associated with constipation, and mainly focusing on patients outside of Asia. Moreover, most of these studies lack focus on the paediatric population. This study aimed to identify the prevalence and associated factors of constipation among children in Asia. Methods: In this systematic review and meta-analysis, we systematically searched PubMed, Scopus, and Cochrane for cohort and cross-sectional studies published from database inception up to October 12, 2022, and continued with manual searching until September 2, 2023. Eligible studies were those that included children in Asia aged 0-18 years old suffering from idiopathic constipation, with prevalence value provided in the English abstract. The analysis included clinical and general population. Children with organic constipation, who had undergone gastrointestinal surgery, or with congenital defects were excluded, as these factors affect the incidence of constipation. Data included in the analysis were extracted from published reports only. The extracted data were pooled using random-effects model to analyse the prevalence of constipation in children in Asia. This study is registered with PROSPERO, CRD42022367122. Findings: Out of 4410 systematically searched studies and 36 manually searched ones, a total of 50 studies were included in the final analysis, encompassing data from 311,660 children residing in Asia. The pooled prevalence of constipation was 12.0% (95% CI 9.3-14.6%, I2 = 99.8%). There was no significant difference in constipation prevalence observed by sex and geographical location. Nonetheless, adolescents and children aged 1-9 years exhibited a significantly higher prevalence constipation compared to infants (p < 0.0001) Additionally, significant differences in constipation rates were observed across various diagnostic methods, population sources, and mental health conditions. Interpretation: Despite the high heterogeneity resulting from varying diagnostic tools or definitions used among studies, our review adds to the literature on constipation among children in Asia. It reveals a notably high prevalence of constipation in this demographic. Diagnostic methods, age, and compromised mental health emerged as significant influencers of constipation among children in Asia, highlighting potential strategies to mitigate constipation prevalence in children in Asia. Funding: The National Science and Technology Council, Taiwan.

Impact of aerobic granular sludge sizes and dissolved oxygen concentration on greenhouse gas N2O emission.

Aerobic granular sludge (AGS) at wastewater treatment plants (WWTPs) are known to produce nitrous oxide (N2O), a greenhouse gas which has a ∼300 times higher global warming potential than carbon dioxide. In this research, we studied N2O emissions from different sizes of AGS developed at a dissolved oxygen (DO) level of 2 mgO2/L while exposing them to disturbances at various DO concentrations ranging from 1 to 4 mgO2/L. Five different AGS size classes were studied: 212-600 µm, 600-1000 µm, 1000-1400 µm, 1400-2000 µm, and > 2000 µm. Metagenomic data showed N2O reductase genes (nosZ) were more abundant in the smaller AGS sizes which aligned with the observation of higher N2O reduction rates in small AGS under anaerobic conditions. However, when oxygen was present, the activity measurements of N2O emission showed an opposite trend compared to metagenomic data, smaller AGS (212 to 1000 µm) emitted significantly higher N2O (p < 0.05) than larger AGS (1000 µm to >2000 µm) at DO of 2, 3, and 4 mgO2/L. The N2O emission rate showed positive correlation with both oxygen levels and nitrification rate. This pattern indicates a connection between N2O emission and nitrification. In addition, the data suggested the penetration of oxygen into the anoxic zone of granules might have hindered nitrous oxide reduction, resulting in incomplete denitrification stopping at N2O and consequently contributing to an increase in N2O emissions. This work sets the stage to better understand the impacts of AGS size on N2O emissions in WWTPs under different disturbance of DO conditions, and thus ensure that wastewater treatment will comply with possible future regulations demanding lowering greenhouse gas emissions in an effort to combat climate change.

Multi-Omics Analysis Reveals the IFI6 Gene as a Prognostic Indicator and Therapeutic Target in Esophageal Cancer.

The role of the IFI6 gene has been described in several cancers, but its involvement in esophageal cancer (ESCA) remains unclear. This study aimed to identify novel prognostic indicators for ESCA-targeted therapy by investigating IFI6's expression, epigenetic mechanisms, and signaling activities. We utilized public data from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) to analyze IFI6's expression, clinical characteristics, gene function, pathways, and correlation with different immune cells in ESCA. The TIMER2.0 database was employed to assess the pan-cancer expression of IFI6, while UALCAN was used to examine its expression across tumor stages and histology subtypes. Additionally, the KEGG database helped identify related pathways. Our findings revealed 95 genes positively correlated and 15 genes negatively correlated with IFI6 in ESCA. IFI6 was over-expressed in ESCA and other cancers, impacting patient survival and showing higher expression in tumor tissues than normal tissues. IFI6 was also correlated with CD4+ T cells and B cell receptors (BCRs), both essential in immune response. GO Biological Process (GO BP) enrichment analysis indicated that IFI6 was primarily associated with the Type I interferon signaling pathway and the defense response to viruses. Intriguingly, KEGG pathway analysis demonstrated that IFI6 and its positively correlated genes in ESCA were mostly linked to the Cytosolic DNA-sensing pathway, which plays a crucial role in innate immunity and viral defense, and the RIG-I-like receptor (RLR) signaling pathway, which detects viral infections and activates immune responses. Pathways related to various viral infections were also identified. It is important to note that our study relied on online databases. Given that ESCA consists of two distinct subgroups (ESCC and EAC), most databases combine them into a single category. Future research should focus on evaluating IFI6 expression and its impact on each subgroup to gain more specific insights. In conclusion, inhibiting IFI6 using targeted therapy could be an effective strategy for treating ESCA considering its potential as a biomarker and correlation with immune cell factors.

Evaluation of Anti-Obesity and Antidiabetic Activities of Orostachys japonicus in Cell and Animal Models.

Orostachys japonicus is a popular traditional medicinal herb used in Asian countries. This study is focused on evaluating its role in lipid and glucose metabolism in cell and animal models to establish the plant as an anti-obesity and antidiabetic herb. A butanol fraction of O. japonicus was used in the study. The lipid production was evaluated by the Oil Red O technique while the expression of adipogenic markers by Western blotting and RT-PCR using 3T3-L1 preadipocyte. The effect on glucose uptake activity was evaluated in C2C12 myoblast cells. The animal study was carried out in C57BL mice to evaluate anti-obesity activity using the high-fat diet model. The evaluation of serum lipid, blood glucose, adipogenic and fibrosis markers in the liver, and fat deposition in the liver and adipose tissue (by histology) of mice was conducted. Butanol fraction of O. japonicus significantly inhibited the lipid production in the 3T3-L1 cells and reduced the expression of PPARγ, C/EBPα, SREBP-1c and aP2. It enhanced glucose uptake in insulin-resistant C2C12 myoblast cells. It reduced body weight, triglycerides, and blood glucose in the obese mice. It significantly inhibited lipid accumulation in the liver and adipose tissue of obese mice along with suppression of expression of adipogenic and fibrosis markers in the liver. In summary, supporting the previous results, this study helped to establish the potent anti-obesity, antidiabetic, and liver-protecting effect of the butanol fraction of O. japonicus.

Improving nitrogen content in soil and lemon balm (Melissa officinalis L.) yield by purple nonsulfur bacteria Rhodopseudomonas palustris in two consecutive seasons.

The study was conducted to assess the effects of nitrogen (N)-fixing purple nonsulfur bacteria (PNSB) Rhodopseudomonas palustris TLS06, VNW02, VNW64, and VNS89 on soil fertility, N uptake, essential oil (EO) content, growth, and yield of lemon balm. The experiment followed a completely randomized block design with 9 treatments and 3 replications. The treatments consisted of (i) applying 100% N as the recommended fertilizer rate (RFR), (ii) applying 85% N as RFR, (iii) applying 70% N as RFR, (iv) applying 55% N as RFR, (v) the treatment ii combined with N-PNSB, (vi) the treatment iii combined with N-PNSB, (vii) the treatment iv combined with N-PNSB, (viii) 0% as RFR combined with N-PNSB, and (ix) 0% N as RFR. The results showed that applying N-PNSB increased the plant height, and the number of primary branches in both seasons. In addition, the treatment without N fertilizer combined with N-PNSB increased stem leaf biomass by 41.2 and 50.3% in both seasons as compared with the treatment without neither N fertilizer nor N-PNSB. For soil properties, among treatments without N fertilizer, the treatment with N-PNSB increased concentrations of NH4+, soluble P, and exchangeable K+ by 41.3, 41.4, and 26.8%, respectively, as compared with the treatment without N-PNSB at the end of the second season. Applying 85% N as RFR combined with N-PNSB had a greater yield by 5.78-11.8% as compared with the treatment with 100% N as RFR, and a greater EO content by 23% as compared with the treatment with 85% N as RFR.

Comparative effects of dietary herbal mixture or guanidinoacetic acid supplementation on growth performance, cecal microbiota, blood profile, excreta gas emission, and meat quality in Hanhyup-3-ho chicken.

Phytogenic feed additives are renowned for their growth promotion, gut health enhancement, and disease prevention properties, which is important factors for sustaining prolonged poultry rearing. The study aimed to evaluate the effect of herbal mixture (mixture of ginseng and artichoke) or guanidinoacetic acid (GAA) on growth performance, cecal microbiota, excretal gas emission, blood profile, and meat quality in Hanhyup-3-ho chicken. A total of 360 one-day-old chickens (half males and half females) were allocated into one of 3 dietary treatments (12 replicate cages/treatment; 10 broilers/replicate cage) for 100 d of age. Experimental diets were CON: basal diet; TRT1: basal diet combined with 0.05% herbal mixture; and TRT2: basal diet combined with 0.06% GAA. All birds received a basal diet during the first 30 d, but from d 31 to 100, an experimental diet was supplied. The addition of 0.05% herbal mixture improved the average body weight gain and feed conversion ratio from d 31 to 100 as well as the overall experimental period. The cecal Lactobacillus, Escherichia coli, and Salmonella count remained consistent across all dietary treatments. Blood albumin and Superoxide Dismutase (SOD) levels increased in the herbal mixture supplemented diet. Additionally, there was a notable reduction in excretal NH3 and H2S emissions in the herbal mixture group. Furthermore, the herbal mixture group exhibited increased breast muscle weight, improved breast muscle color, improved water holding capacity, and a decrease in abdominal fat compared to the control group. Additionally, the supplementation of 0.06% GAA did not demonstrate any statistically significant impact on any evaluated parameter throughout the experiment. The results from the present investigation underscore the potential of ginseng together with artichoke extract supplementation as a viable feed additive, conferring improvements in growth performance, feed efficiency, excreta gas emission, meat quality parameters, and defense mechanism against oxidative stress in Hanhyup-3-ho chicken.