Testosterone and aging male, a perspective from a developing country.

PURPOSE: Hypogonadism is associated with a wide range of physical and psychological symptoms that can affect the overall health of men. However, in a developing country, there are several imposing challenges in the diagnosis and treatment of hypogonadism, including a lack of awareness and understanding of the condition among healthcare providers and patients, limited resources and the high cost of treatment. This review aimed to examine the potential benefits and risks of testosterone replacement therapy (TRT) and provides a perspective of a developing country on the topic. MATERIALS AND METHODS: A comprehensive literature review was conducted to gather relevant information on the impact of testosterone deficiency on ageing males and the effectiveness of TRT for treating hypogonadism. Published peer-reviewed articles were analyzed to evaluate the benefits and risks of TRT. Additionally, the unique challenges faced in the diagnosis and treatment of hypogonadism in a developing country were considered. RESULTS: Testosterone replacement therapy has been shown to be an effective treatment for hypogonadism, particularly in symptomatic men with low testosterone levels. It offers potential benefits such as improvements in symptoms and overall quality of life. However, there are associated risks and side effects that need to be considered. In a developing country, challenges such as limited awareness and understanding of hypogonadism, resource constraints, and high treatment costs pose additional barriers to accessing TRT and comprehensive care. CONCLUSION: In conclusion, TRT holds promise as a treatment for hypogonadism, but its implementation and accessibility face significant challenges in a developing country. Addressing these challenges, including raising awareness, allocating resources, and finding cost-effective solutions, is crucial for ensuring that men with hypogonadism in such settings receive appropriate diagnosis and treatment. Further research and efforts are needed to improve the management of hypogonadism in developing countries and optimize the potential benefits of TRT for affected individuals.

Machine learning combines atomistic simulations to predict SARS-CoV-2 Mpro inhibitors from natural compounds.

To date, the COVID-19 pandemic has still been infectious around the world, continuously causing social and economic damage on a global scale. One of the most important therapeutic targets for the treatment of COVID-19 is the main protease (Mpro) of SARS-CoV-2. In this study, we combined machine-learning (ML) model with atomistic simulations to computationally search for highly promising SARS-CoV-2 Mpro inhibitors from the representative natural compounds of the National Cancer Institute (NCI) Database. First, the trained ML model was used to scan the library quickly and reliably for possible Mpro inhibitors. The ML output was then confirmed using atomistic simulations integrating molecular docking and molecular dynamic simulations with the linear interaction energy scheme. The results turned out to show that there was evidently good agreement between ML and atomistic simulations. Ten substances were proposed to be able to inhibit SARS-CoV-2 Mpro. Seven of them have high-nanomolar affinity and are very potential inhibitors. The strategy has been proven to be reliable and appropriate for fast prediction of SARS-CoV-2 Mpro inhibitors, benefiting for new emerging SARS-CoV-2 variants in the future accordingly.

Improving ligand-ranking of AutoDock Vina by changing the empirical parameters.

AutoDock Vina (Vina) achieved a very high docking-success rate, p^ , but give a rather low correlation coefficient, R , for binding affinity with respect to experiments. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is the main objective of docking simulations. In this context, we evaluated the dependence of Vina R coefficient upon its empirical parameters. R is affected more by changing the gauss2 and rotation than other terms. The docking-success rate p^ is sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Based on our benchmarks, the parameter set1 has been suggested to be the most optimal. The testing study over 800 complexes indicated that the modified Vina provided higher correlation with experiment Rset1=0.556±0.025 compared with RDefault=0.493±0.028 obtained by the original Vina and RVina1.2=0.503±0.029 by Vina version 1.2. Besides, the modified Vina can be also applied more widely, giving R≥0.500 for 32/48 targets, compared with the default package, giving R≥0.500 for 31/48 targets. In addition, validation calculations for 1036 complexes obtained from version 2019 of PDBbind refined structures showed that the set1 of parameters gave higher correlation coefficient ( Rset1=0.617±0.017 ) than the default package ( RDefault=0.543±0.020 ) and Vina version 1.2 ( RVina1.2=0.540±0.020 ). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes would enhance the ranking of ligand-binding affinity using Autodock Vina.

Correction: Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches.

Correction for 'Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches' by Son Tung Ngo et al., Phys. Chem. Chem. Phys., 2022, https://doi.org/10.1039/d2cp04476e.

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches.

Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.

Benchmark of Popular Free Energy Approaches Revealing the Inhibitors Binding to SARS-CoV-2 Mpro.

The COVID-19 pandemic has killed millions of people worldwide since its outbreak in December 2019. The pandemic is caused by the SARS-CoV-2 virus whose main protease (Mpro) is a promising drug target since it plays a key role in viral proliferation and replication. Currently, developing an effective therapy is an urgent task, which requires accurately estimating the ligand-binding free energy to SARS-CoV-2 Mpro. However, it should be noted that the accuracy of a free energy method probably depends on the protein target. A highly accurate approach for some targets may fail to produce a reasonable correlation with the experiment when a novel enzyme is considered as a drug target. Therefore, in this context, the ligand-binding affinity to SARS-CoV-2 Mpro was calculated via various approaches. The molecular docking approach was manipulated using Autodock Vina (Vina) and Autodock4 (AD4) protocols to preliminarily investigate the ligand-binding affinity and pose to SARS-CoV-2 Mpro. The binding free energy was then refined using the fast pulling of ligand (FPL), linear interaction energy (LIE), molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA), and free energy perturbation (FEP) methods. The benchmark results indicated that for docking calculations, Vina is more accurate than AD4, and for free energy methods, FEP is the most accurate method, followed by LIE, FPL, and MM-PBSA (FEP > LIE ≈ FPL > MM-PBSA). Moreover, atomistic simulations revealed that the van der Waals interaction is the dominant factor. The residues Thr26, His41, Ser46, Asn142, Gly143, Cys145, His164, Glu166, and Gln189 are essential elements affecting the binding process. Our benchmark provides guidelines for further investigations using computational approaches.

Antiproliferative and antiinflammatory coxib-combretastatin hybrids suppress cell cycle progression and induce apoptosis of MCF7 breast cancer cells.

In our study, some newly synthesized aryl-substituted pyrazole derivatives mimicking cis-diphenylethylene scaffold of two apoptotic inducing agents celecoxib and combretastatin A-4 were found to have strong antiproliferative as well as antiinflammatory activities. Among these coxib-combretastatin hybrids, two lead compounds 8 and 6c simultaneously inhibited prostaglandin E2 (PGE2) production in LPS-activated murine macrophage RAW 264.7 cells and suppressed cell cycle progression of MCF7 cells at G2/M or G0/G1 phases, but only compound 8 induced apoptosis via caspase-3 activation. Both the lead compounds showed good docking energies with both protein targets COX-2 and tubulin in the molecule interaction modeling. The cis-diphenylethylene scaffold of celecoxib or combretastatin A-4 as well as functional groups such as the ethyl ester group and the sulfonamide could be considered as potential key features for the dual activity of studied compounds meanwhile the trimethoxybenzene remained the crucial characterization of the newly derived compounds of combretastatins.

Antioxidant and Anticancer Properties of Functionalized Ferrocene with Hydroxycinnamate Derivatives-An Integrated Experimental and Theoretical Study.

Two ferrocenyl derivatives, Fc-CA and Fc-FA, were synthesized by a condensation reaction between the amino ferrocene and hydroxycinnamic acids, that is, caffeic acid (CA) and ferulic acid (FA). The structures and purity of all compounds were characterized by 1H- and 13C NMR spectroscopies, Mass spectrometry (MS), and elemental analysis. The antioxidant properties of Fc-CA and Fc-FA and of its ligand were studied for free radical scavenging activity toward DPPH•, superoxide anion (O2•-), NO•, and ABTS•+ by UV-vis and electron spin resonance spectroscopies. The cytotoxicity of Fc-CA and Fc-FA against MCF-7 and MDA-MB-231 breast cancer cells and MRC-5 human lung fibroblasts cell was higher than that of cisplatin. The geometry and electronic structures of all compounds were then simulated using density functional theory at M05-2X/6-311+G(d,p) level of theory. Thermodynamics of the free radical quenching reactions by common mechanisms reveal the higher antioxidant properties of the Fc-CA and Fc-FA in comparison to their ligands. An in-depth study of the free radical scavenging activity against HOO• and HO• radicals was performed for two of the most favorable and competitive mechanisms, the hydrogen transfer (either hydrogen atom transfer or proton-coupled electron transfer mechanisms) and the radical adduct formation. The in silico studies indicated that ferrocenyl derivatives exhibited prominent binding affinity to protein models in comparison to CA and FA. Their dock scores were notable at ligand binding sites of ERα, Erß, and JAK2 proteins. Dock pose analysis also shed light into the possible mechanism of action for the studied compounds.

Autodock Vina Adopts More Accurate Binding Poses but Autodock4 Forms Better Binding Affinity.

The binding pose and affinity between a ligand and enzyme are very important pieces of information for computer-aided drug design. In the initial stage of a drug discovery project, this information is often obtained by using molecular docking methods. Autodock4 and Autodock Vina are two commonly used open-source and free software tools to perform this task, and each has been cited more than 6000 times in the last ten years. It is of great interest to compare the success rate of the two docking software programs for a large and diverse set of protein-ligand complexes. In this study, we selected 800 protein-ligand complexes for which both PDB structures and experimental binding affinity are available. Docking calculations were performed for these complexes using both Autodock4 and Autodock Vina with different docking options related to computing resource consumption and accuracy. Our calculation results are in good agreement with a previous study that the Vina approach converges much faster than AD4 one. However, interestingly, AD4 shows a better performance than Vina over 21 considered targets, whereas the Vina protocol is better than the AD4 package for 10 other targets. There are 16 complexes for which both the AD4 and Vina protocols fail to produce a reasonable correlation with respected experiments so both are not suitable to use to estimate binding free energies for these cases. In addition, the best docking option for performing the AD4 approach is the long option. However, the short option is the best solution for carrying out Vina docking. The obtained results probably will be useful for future docking studies in deciding which program to use.

Fatty Acid, Lipid Classes and Phospholipid Molecular Species Composition of the Marine Clam Meretrix lyrata (Sowerby 1851) from Cua Lo Beach, Nghe An Province, Vietnam.

This study aims to analyze compositions of fatty acids and phospholipid molecular species in the hard clams Meretrix lyrata (Sowerby, 1851) harvested from Cua Lo beach, Nghe An province, Viet Nam. Total lipid of hard clams Meretrix lyrata occupied 1.7 ± 0.2% of wet weight and contained six classes: hydrocarbon and wax (HW), triacylglycerol (TAG), free fatty acids (FFA), sterol (ST), polar lipid (PoL), and monoalkyl diacylglycerol (MADAG). Among the constituents, the proportion of PoL accounted was highest, at 45.7%. In contrast, the figures for MADAG were lowest, at 1.3%. Twenty-six fatty acids were identified with the ratios of USAFA/SAFA was 2. The percentage of n-3 PUFA (ω-3) and n-6 PUFA (ω-6) was high, occupying 38.4% of total FA. Among PUFAs, arachidonic acid (AA, 20:4n-6), eicosapentaenoic acid (EPA, 20:5n-3), docosapentaenoic acid (DPA, 22:5n-3), and docosahexaenoic acid (DHA, 22:6n-3) accounted for 3.8%, 7.8%, 2.2% and 12.0% of total lipid of the clam respectively. Phospholipid molecular species were identified in polar lipids of the clams consisting six types: phosphatidylethalnolamine (PE, with 28 molecular species), phosphatidylcholine (PC, with 26 molecular species), phosphatidylserine (PS, with 18 molecular species), phosphatidylinositol (PI, with 10 molecular species), phosphatidylglycerol (PG, with only one molecular species), and ceramide aminoethylphosphonate (CAEP, with 15 molecular species). This is the first time that the molecular species of sphingophospholipid were determined, in Meretrix lyrata in particular, and for clams in general. Phospholipid formula species of PE and PS were revealed to comprise two kinds: Alkenyl acyl glycerophosphoethanolamine and Alkenyl acyl glycerophosphoserine occupy 80.3% and 81.0% of total PE and PS species, respectively. In contrast, the percentage of diacyl glycero phosphatidylcholine was twice as high as that of PakCho in total PC, at 69.3, in comparison with 30.7%. In addition, phospholipid formula species of PI and PG comprised only diacyl glycoro phospholipids. PE 36:1 (p18:0/18:1), PC 38:6 (16:0/22:6), PS 38:1 (p18:0/20:1), PI 40:5 (20:1/20:4), PG 32:0 (16:0/16:0) and CAEP 34:2 (16:2/d18:0) were the major molecular species.

Gambogic acid induces apoptotic cell death in T98G glioma cells.

Gambogic acid (GA), a natural product with a xanthone structure, has a broad range of anti-proliferative effects on cancer cell lines. We evaluated GA for its cytotoxic effects on T98G glioblastoma cells. GA exhibited potent anti-proliferative activity and induced apoptosis in T98G glioblastoma cells in a dose-dependent manner. Incubation of cells with GA revealed apoptotic features including increased Bax and AIF expression, cytochrome c release, and cleavage of caspase-3, -8, -9, and PARP, while Bcl-2 expression was downregulated. Furthermore, GA induced reactive oxygen species (ROS) generation in T98G cells. Our results indicate that GA increases Bax- and AIF-associated apoptotic signaling in glioblastoma cells.

Perceived intravaginal ejaculation latency time: The diagnosis of premature ejaculation among Vietnamese men.

INTRODUCTION: Premature ejaculation (PE) is a prevalent sexual dysfunction in men that greatly affects their quality of life. In PE, the duration of sexual performance is considered an important aspect. However, a self-estimated value of intravaginal ejaculation latency time (perceived IELT, PIELT) as a criterion for diagnosis has not been specified. AIM: This study aimed to determine the validity and a threshold value for PIELT in PE diagnosis. METHOD: In our cross-sectional study, we recruited 550 men from March 2019 to January 2020 and interviewed them regarding their general demographic characteristics, sexual habits, PIELT and completed a premature ejaculation diagnostic tool (PEDT) questionnaire. Eventually, a combination of a clinical diagnosis and PEDT score was used, in which those with PEDT ≥ 11 and diagnosed with possible PE were assigned to the final PE(+) group; those with PEDT score ≤ 8 and diagnosed with no PE were included in the final PE(-) group. RESULTS: Men PE(-) had more frequent sexual intercourse (9.74 ± 5.38 vs. 6.69 ± 5.38 episodes per month, p < 0.001) and had higher marriage rate (72.7% vs. 60.4%, p = 0.002) than PE(+) patients. No significant difference was noted regarding age, smoking habit, age of first sexual experience, and number of sexual partners between the two groups. The mean PIELT of control subjects and PE(+) patients were 11.69 ± 6.83 min and 2.01 ± 1.21 min, respectively. On receiver operating characteristic curve analysis, the cut-off value of PIELT of 3.75 min can be used to distinguish PE men (area under the curve = 0.982, sensitivity/specificity = 0.961/0.909), which means that men with a PIELT ≤ 3.5 min is suggestive of PE. CONCLUSION: The impact of PE is dramatic both from a social and a personal perspective. PE(+) patients married significantly less and have significantly lower sexual activity compared to a PE(-) population. Furthermore, a PIELT of ≤ 3.5 min predicts PE demonstrating the need to revise its taxonomy and definition.

Silver nanoparticles alter the dimerization of Aß42 studied by REMD simulations.

The aggregation of amyloid beta (Aß) peptides is associated with the development of Alzheimer's disease (AD). However, there has been a growing belief that the oligomerization of Aß species in different environments has a neurotoxic effect on the patient's brain, causing damage. It is necessary to comprehend the compositions of Aß oligomers in order to develop medications that may effectively inhibit these neurotoxic forms that affect the nervous system of AD patients. Thus, dissociation or inhibition of Aß aggregation may be able to prevent AD. To date, the search for traditional agents and biomolecules has largely been unsuccessful. In this context, nanoparticles have emerged as potential candidates to directly inhibit the formation of Aß oligomers. The oligomerization of the dimeric Aß peptides with or without the influence of a silver nanoparticle was thus investigated using temperature replica-exchange molecular dynamics (REMD) simulations. The physical insights into the dimeric Aß oligomerization were clarified by analyzing intermolecular contact maps, the free energy landscape of the dimeric oligomer, secondary structure terms, etc. The difference in obtained metrics between Aß with or without a silver nanoparticle provides a picture of the influence of silver nanoparticles on the oligomerization process. The underlying mechanisms that are involved in altering Aß oligomerization will be discussed. The obtained results may play an important role in searching for Aß inhibitor pathways.

MedChemExpress compounds prevent neuraminidase N1 via physics- and knowledge-based methods.

Influenza A viruses spread out worldwide, causing several global concerns. Hence, discovering neuraminidase inhibitors to prevent the influenza A virus is of great interest. In this work, a machine learning model was employed to evaluate the ligand-binding affinity of ca. 10 000 compounds from the MedChemExpress (MCE) database for inhibiting neuraminidase. Atomistic simulations, including molecular docking and molecular dynamics simulations, then confirmed the ligand-binding affinity. Furthermore, we clarified the physical insights into the binding process of ligands to neuraminidase. It was found that five compounds, including micronomicin, didesmethyl cariprazine, argatroban, Kgp-IN-1, and AY 9944, are able to inhibit neuraminidase N1 of the influenza A virus. Ten residues, including Glu119, Asp151, Arg152, Trp179, Gln228, Glu277, Glu278, Arg293, Asn295, and Tyr402, may be very important in controlling the ligand-binding process to N1.

Calculation of binding affinity of JAK1 inhibitors via accurately computational estimation.

Janus kinase 1 (JAK1) is a tyrosine kinase that is involved in the initiation of responses to a number of different cytokine receptor families. The JAK1-dependent pathway is a therapeutic target, and several JAK inhibitors have been developed thanks to intensive research. However, since the ATP binding sites of JAK family members are quite alike, JAK1 inhibitors can thus be less selective, resulting in unanticipated adverse effects. Despite this, minor variations in the ATP-binding site have been extensively used to find a variety of small compounds with different inhibitory properties. Stronger binding affinity of JAK1 inhibitors is believed to be able to reduce the negative effects, leading to better treatment results. Therefore, a thorough computational search that can effectively identify ligands with extremely high binding affinity for JAK1 to serve as promising inhibitors is required. Here, a method combining steered-molecular dynamic (SMD) simulations with a modified linear interaction energy (LIE) model has been developed to evaluate the binding affinities of known JAK1 inhibitors. The correlation coefficient between the estimated and experimental values was 0.72 and a root-mean-square error was 0.97 kcal•mol-1, revealing that the SMD/LIE method can precisely and quickly predict the binding free energies of JAK1 inhibitors. Furthermore, three marine fungus-derived compounds, namely hansforesters E, hansforesters G and tetroazolemycins B, were identified to be particularly promising JAK1 inhibitors, accordingly. These findings show that the SMD/LIE method has a lot of promise for in silico screening of possible JAK1 inhibitors from a vast number of compounds that are now accessible.Communicated by Ramaswamy H. Sarma.

Upgrading nirmatrelvir to inhibit SARS-CoV-2 Mpro via DeepFrag and free energy calculations.

The first oral drug for the treatment of COVID-19, Paxlovid, has been authorized; however, nirmatrelvir, a major component of the drug, is reported to be associated with some side effects. Moreover, the appearance of many novel variants raises concerns about drug resistance, and designing new potent inhibitors to prevent viral replication is thus urgent. In this context, using a hybrid approach combining machine learning (ML) and free energy simulations, 6 compounds obtained by modifying nirmatrelvir were proposed to bind strongly to SARS-CoV-2 Mpro. The structural modification of nirmatrelvir significantly enhances the electrostatic interaction free energy between the protein and ligand and slightly decreases the vdW term. However, the vdW term is the most important factor in controlling the ligand-binding affinity. In addition, the modified nirmatrelvir might be less toxic to the human body than the original inhibitor.

Plant Secondary Metabolites on Efflux-Mediated Antibiotic Resistant Stenotrophomonas Maltophilia: Potential of Herbal-Derived Efflux Pump Inhibitors.

During the process of adapting to metal contamination, plants produce secondary metabolites that have the potential to modulate multidrug-resistant (MDR) phenotypes; this is achieved by inhibiting the activity of efflux pumps to reduce the minimum inhibitory concentrations (MICs) of antimicrobial substrates. Our study evaluated the effect of secondary metabolites of belowground parts of Pteris vittata L. and Fallopia japonica, two metal-tolerant plants from northern Vietnam, on six antibiotic-resistant Stenotrophomonas maltophilia strains possessing efflux pump resistance mechanisms that were isolated from soil and clinical samples. The chemical composition of aqueous and dichloromethane (DCM) fractions extracted from P. vittata and F. japonica was determined using UHPLC-DAD-ESI/QTOF analysis. The antibacterial and efflux pump inhibitory activities of the four fractions were evaluated for the six strains (K279a, 0366, BurA1, BurE1, PierC1, and 502) using a microdilution assay at fraction concentrations of 62.5, 125, and 250 µg/mL. The DCM fraction of F. japonica exhibited remarkable antibacterial activity against strain 0366, with a MIC of 31.25 µg/mL. Furthermore, this fraction also significantly decreased gentamicin MIC: four-fold and eight-fold reductions for BurA1 and BurE1 strains, respectively (when tested at 250 µg/mL), and two-fold and eight-fold reductions for K279a and BurE1 strains, respectively (when tested at 125 µg/mL). Pure emodin, the main component identified in the DCM fraction of F. japonica, and sennidine A&B only reduced by half the MIC of gentamicin (when tested at 30 µg/mL). Our results suggest that the DCM fraction components of F. japonica underground parts may be potential candidates for new bacterial efflux pump inhibitors (EPIs).

Umbrella Sampling-Based Method to Compute Ligand-Binding Affinity.

Many proteins have a solvent-exposed binding cleft, which permits their inhibitors to bind and unbind without significant protein conformation transforms. The binding/unbinding pathways of these protein-inhibitor complexes can be rather straightforwardly sampled by using umbrella sampling (US) simulation methods. During a US simulation, the Cα atoms of the protein are restrained via a harmonic force. The potential of mean force (PMF) along the binding pathway can be estimated by using the weighted histogram analysis method (WHAM). The binding affinity is then computed as the difference in PMF between the binding and unbinding states.

Searching for AChE inhibitors from natural compounds by using machine learning and atomistic simulations.

Acetylcholinesterase (AChE) is one of the most important drug targets for Alzheimer's disease treatment. In this work, a combined approach involving machine-learning (ML) model and atomistic simulations was established to predict the ligand-binding affinity to AChE of the natural compounds from VIETHERB database. The trained ML model was first utilized to rapidly and accurately screen the natural compound database for potential AChE inhibitors. Atomistic simulations including molecular docking and steered-molecular dynamics simulations were then used to confirm the ML outcome. Good agreement between ML and atomistic simulations was observed. Twenty compounds were suggested to be able to inhibit AChE. Especially, four of them including geranylgeranyl diphosphate, 2-phosphoglyceric acid, and 2-carboxy-d-arabinitol 1-phosphate, and farnesyl diphosphate are highly potent inhibitors with sub-nanomolar affinities.

Effects of antibiotics on Vietnam koi, Anabas testudineus, exposed to Aeromonas dhakensis as a co-infection.

The dietary effects of antibiotics on aquatic disease is circumstantial and has not been investigated under infections. the efficacy of erythromycin, after 10 days in use and 10 days off, on the survival and infection rate of (Anabas testudineus) after co-infection with antibiotic-resistant Aeromonas dhakensis (isolate NV5M or V7L). The mortality rate observed in non-medicated groups of co-infected fish (93.3 and 100%) was significantly higher (p < 0.05) than that in the medicated group of naturally infected fish (NIF) (53.3%) but not significantly different to that in medicated groups of co-infected fish (66.6% and 86.6%). In particular, the loads of invasive erythromycin-resistant bacteria (ERB) were markedly higher (p < 0.05, 3.5-4.8 times) in the kidney of co-infected fish medicated for 5 days than those in NIF. The measure of ERB in the kidney of fish co-infected with isolate V7L, whether medicated or not for 10 days, was significantly higher (p < 0.05) than that in non-medicated NIF and also that in the medicated group of fish co-infected with isolate NV5M. In addition to the elevation of gut-derived ERB invasion and colonization in the kidney, synergistic effects of the competition between mixed pathogens caused by co-infection and medication might result in a high fish mortality rate. Further investigation of antibiograms and/or new strategies for aquatic disease control should be undertaken with mixed infections and interaction of pathogens to achieve the optimal treatment effect.