Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis.

Complete coding sequence of an Aedes flavivirus strain isolated from Aedes albopictus collected in Northern Italy.

Complete genome data for the globally distributed Aedes flavivirus (AEFV) is scarce. We analyzed a new Italian AEFV strain isolated from Aedes albopictus. The results demonstrated genetic diversity among Italian AEFVs. The high similarity between AEFV genomes across geographically distant regions suggests long distance spreading via invasive host mosquito species.

Time-course cross-species transcriptomics reveals conserved hepatotoxicity pathways induced by repeated administration of cyclosporine A.

Cyclosporine A (CsA) has shown efficacy against immunity-related diseases despite its toxicity in various organs, including the liver, emphasizing the need to elucidate its underlying hepatotoxicity mechanism. This study aimed to capture the alterations in genome-wide expression over time and the subsequent perturbations of corresponding pathways across species. Six data from humans, mice, and rats, including animal liver tissue, human liver microtissues, and two liver cell lines exposed to CsA toxic dose, were used. The microtissue exposed to CsA for 10 d was analyzed to obtain dynamically differentially expressed genes (DEGs). Single-time points data at 1, 3, 5, 7, and 28 d of different species were used to provide additional evidence. Using liver microtissue-based longitudinal design, DEGs that were consistently up- or down-regulated over time were captured, and the well-known mechanism involved in CsA toxicity was elucidated. Thirty DEGs that consistently changed in longitudinal data were also altered in 28-d rat in-house data with concordant expression. Some genes (e.g. TUBB2A, PLIN2, APOB) showed good concordance with identified DEGs in 1-d and 7-d mouse data. Pathway analysis revealed up-regulations of protein processing, asparagine N-linked glycosylation, and cargo concentration in the endoplasmic reticulum. Furthermore, the down-regulations of pathways related to biological oxidations and metabolite and lipid metabolism were elucidated. These pathways were also enriched in single-time-point data and conserved across species, implying their biological significance and generalizability. Overall, the human organoids-based longitudinal design coupled with cross-species validation provides temporal molecular change tracking, aiding mechanistic elucidation and biologically relevant biomarker discovery.

Physicochemical Characterization, Antioxidant and Tyrosinase Inhibitory Activities of Coffea Robusta Monofloral Honey from Dak Lak Province, Vietnam.

Robusta coffee blossom honey stands as a key regional product in Dak Lak province, Vietnam. Despite its significance, there exists a dearth of scientific data for assessing its quality. This study aims to fill this gap by characterizing the physicochemical properties and biological activities of coffee blossom honeys from three distinct sub-regions within Dak Lak province, Vietnam. These activities include ferric reducing power (FRP), DPPH and ABTS radical scavenging, as well as tyrosinase inhibitory activities. Moreover, the study compares these honey samples with other popular varieties in Vietnam, such as Lychee and Longan honeys. The physicochemical parameters of the honey samples meet the standards set by Codex Alimentarius 2001. Through UPLC analysis, eleven compounds were identified, with caffeine serving as a marker for coffee honey. Furthermore, by employing multiple factor analysis (MFA), it was observed that certain physicochemical properties correlate positively with tyrosinase inhibitory, DPPH, ABTS free radicals scavenging activities, and FRP. Notably, tyrosinase inhibitory activity exhibited a positive correlation with antioxidant activity. These findings underscore the high quality of Coffea robusta honey, showcasing its potent antioxidant and tyrosinase inhibitory activities.

Distracted on duty: A theory-based exploration of influences leading to mobile phone distracted riding among food delivery workers.

Using mobile phones while riding is a form of distracted riding that significantly elevates crash risk. Regrettably, the factors contributing to mobile phone use while riding (MPUWR) among food delivery riders remain under-researched. Addressing this literature gap, the current study employs the Job Demands-Resources (JD-R) model and various socio-economic factors to examine the determinants of MPUWR. The research incorporates data from 558 delivery workers in Hanoi and Ho Chi Minh City, Vietnam. The study utilizes two analytical methods to empirically test the hypotheses, considering non-linear relationships between variables: Partial Least Square Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN). The results reveal mixed impacts of factors connected to job resources. Although social support appears to deter MPUWR, work autonomy and rewards seemingly encourage it. Furthermore, a predisposition towards risk-taking behaviour significantly impacts the frequency of mobile phone usage among delivery riders. Interestingly, riders with higher incomes and those who have previously been fined by the police exhibit more frequent mobile phone use. The findings of this study present valuable insights into the crucial factors to be addressed when designing interventions aimed at reducing phone use among food delivery riders.

Novel machine learning approach toward classification model of HIV-1 integrase inhibitors.

HIV-1 (human immunodeficiency virus-1) has been causing severe pandemics by attacking the immune system of its host. Left untreated, it can lead to AIDS (acquired immunodeficiency syndrome), where death is inevitable due to opportunistic diseases. Therefore, discovering new antiviral drugs against HIV-1 is crucial. This study aimed to explore a novel machine learning approach to classify compounds that inhibit HIV-1 integrase and screen the dataset of repurposing compounds. The present study had two main stages: selecting the best type of fingerprint or molecular descriptor using the Wilcoxon signed-rank test and building a computational model based on machine learning. In the first stage, we calculated 16 different types of fingerprint or molecular descriptors from the dataset and used each of them as input features for 10 machine-learning models, which were evaluated through cross-validation. Then, a meta-analysis was performed with the Wilcoxon signed-rank test to select the optimal fingerprint or molecular descriptor types. In the second stage, we constructed a model based on the optimal fingerprint or molecular descriptor type. This data followed the machine learning procedure, including data preprocessing, outlier handling, normalization, feature selection, model selection, external validation, and model optimization. In the end, an XGBoost model and RDK7 fingerprint were identified as the most suitable. The model achieved promising results, with an average precision of 0.928 ± 0.027 and an F1-score of 0.848 ± 0.041 in cross-validation. The model achieved an average precision of 0.921 and an F1-score of 0.889 in external validation. Molecular docking was performed and validated by redocking for docking power and retrospective control for screening power, with the AUC metrics being 0.876 and the threshold being identified at -9.71 kcal mol-1. Finally, 44 compounds from DrugBank repurposing data were selected from the QSAR model, then three candidates were identified as potential compounds from molecular docking, and PSI-697 was detected as the most promising molecule, with in vitro experiment being not performed (docking score: -17.14 kcal mol-1, HIV integrase inhibitory probability: 69.81%).

Application of short tandem repeats (STRs) in the preimplantation genetic diagnosis (PGD) of α-thalassemia.

OBJECTIVES: α-thalassemia is an autosomal recessive monogenic blood disorder, affecting up to 5% of the world's population. The occurrence rate of the disease in Vietnam varies up to up to 51.5%, with high rate of mutation carriers, of couples consisting of two carriers at risk of bearing a child with fetal Hb Bart, which can develop into hydrops fetalis syndrome, threatening the well-being of the mother and the child. Our study aims to facilitate birth of healthy/asymptomatic children of α-thalassemia carrier couples who received reproductive service at our centre during the period of 2019-2022. MATERIALS AND METHODS: 89 couples at risks of having α-thalassemia offsprings requested IVF procedures and PGD at Post Hospital during 2019-2022 were recruited for investigation. Couple and additional family members' peripheral blood samples of couples and additional family members were subjected to haemoglobin electrophoresis, DNA extraction for α-thalassemia gene mutation detection and STRs linkage analysis. Data were observed and analysed on GeneMarker software. RESULTS: 91 cycles of PGD for α-thalassemia were carried out for 89 couples. α-thalassemia large deletion (--SEA/αα) was the most common mutation identified in 88 couples, in which 4 cases also carried ß-thalassemia point mutations. Combining results of PGS and PGD, 278/424 amplified embryos were transferable (HBA-mutation free or carriers of single heterozygous HBA mutation, without chromosomal abnormality). 64/89 couples have been transferred with the embryos (prioritizing mutation free ones over carriers), resulting in the birth of 36 α-thalassemia disease-free children, 17 ongoing pregnancies, and 11 with miscarriages. CONCLUSION: Successful application of microsatellite-based method in PGD facilitated the birth of 36 healthy children and 17 ongoing pregnancies for 53/64 couples with embryo-transferred. All resulted clinical births displayed confirmation results in line with the PGD results, thus demonstrating the feasibility and credibility of the use of STR markers in PGD.

Sex Differences in Clustering Unhealthy Lifestyles Among Survivors of COVID-19: Latent Class Analysis.

BACKGROUND: The COVID-19 pandemic has underscored the significance of adopting healthy lifestyles to mitigate the risk of severe outcomes and long-term consequences. OBJECTIVE: This study focuses on assessing the prevalence and clustering of 5 unhealthy lifestyle behaviors among Vietnamese adults after recovering from COVID-19, with a specific emphasis on sex differences. METHODS: The cross-sectional data of 5890 survivors of COVID-19 in Vietnam were analyzed from December 2021 to October 2022. To examine the sex differences in 5 unhealthy lifestyle behaviors (smoking, drinking, unhealthy diet, physical inactivity, and sedentary behavior), the percentages were plotted along with their corresponding 95% CI for each behavior. Latent class analysis was used to identify 2 distinct classes of individuals based on the clustering of these behaviors: the "less unhealthy" group and the "more unhealthy" group. We examined the sociodemographic characteristics associated with each identified class and used logistic regression to investigate the factors related to the "more unhealthy" group. RESULTS: The majority of individuals (male participants: 2432/2447, 99.4% and female participants: 3411/3443, 99.1%) exhibited at least 1 unhealthy behavior, with male participants being more susceptible to multiple unhealthy behaviors. The male-to-female ratio for having a single behavior was 1.003, but it escalated to 25 for individuals displaying all 5 behaviors. Male participants demonstrated a higher prevalence of combining alcohol intake with sedentary behavior (949/2447, 38.8%) or an unhealthy diet (861/2447, 35.2%), whereas female participants tended to exhibit physical inactivity combined with sedentary behavior (1305/3443, 37.9%) or an unhealthy diet (1260/3443, 36.6%). Married male participants had increased odds of falling into the "more unhealthy" group compared to their single counterparts (odds ratio [OR] 1.45, 95% CI 1.14-1.85), while female participants exhibited lower odds (OR 0.65, 95% CI 0.51-0.83). Female participants who are underweight showed a higher likelihood of belonging to the "more unhealthy" group (OR 1.11, 95% CI 0.89-1.39), but this was not observed among male participants (OR 0.6, 95% CI 0.41-0.89). In both sexes, older age, dependent employment, high education, and obesity were associated with higher odds of being in the "more unhealthy" group. CONCLUSIONS: The study identified notable sex differences in unhealthy lifestyle behaviors among survivors of COVID-19. Male survivors are more likely to engage in unhealthy behaviors compared to female survivors. These findings emphasize the importance of tailored public health interventions targeting sex-specific unhealthy behaviors. Specifically, addressing unhealthy habits is crucial for promoting post-COVID-19 health and well-being.

Omics analysis unveils changes in the metabolome and lipidome of Caenorhabditis elegans upon polydopamine exposure.

Polydopamine (PDA) is an insoluble biopolymer with a dark brown-black color that forms through the autoxidation of dopamine. Because of its outstanding biocompatibility and durability, PDA holds enormous promise for various applications, both in the biomedical and non-medical domains. To ensure human safety, protect health, and minimize environmental impacts, the assessment of PDA toxicity is important. In this study, metabolomics and lipidomics assessed the impact of acute PDA exposure on Caenorhabditis elegans (C. elegans). The findings revealed a pronounced perturbation in the metabolome and lipidome of C. elegans at the L4 stage following 24 hours of exposure to 100 µg/mL PDA. The changes in lipid composition varied based on lipid classes. Increased lipid classes included lysophosphatidylethanolamine, triacylglycerides, and fatty acids, while decreased species involved in several sub-classes of glycerophospholipids and sphingolipids. Besides, we detected 37 significantly affected metabolites in the positive and 8 in the negative ion modes due to exposure to PDA in C. elegans. The metabolites most impacted by PDA exposure were associated with purine metabolism, biosynthesis of valine, leucine, and isoleucine; aminoacyl-tRNA biosynthesis; and cysteine and methionine metabolism, along with pantothenate and CoA biosynthesis; the citrate cycle (TCA cycle); and beta-alanine metabolism. In conclusion, PDA exposure may intricately influence the metabolome and lipidome of C. elegans. The combined application of metabolomics and lipidomics offers additional insights into the metabolic perturbations involved in PDA-induced biological effects and presents potential biomarkers for the assessment of PDA safety.

Three cases of vulvovaginal candidiasis due to Candida nivariensis.

Candida nivariensis is emerging as a highly resistant species of the Candida glabrata complex causing invasive and mucocutaneous infections. In this study, three cases of vulvovaginal candidiasis caused by C. nivariensis are described and identified by Internal Transcribed Spacer 1-2 sequencing. All isolates were susceptible in vitro to anidulafungin, micafungin, caspofungin, 5-flucytosine, posaconazole, voriconazole, itraconazole, amphotericin B, and showed dose-dependent susceptibility to fluconazole. In two patients, three doses of oral fluconazole were effective, while one patient developed clinical fluconazole resistance with a new relapse after 6 months. Increasing the weekly dose of fluconazole showed to be effective in this patient.

Impact of long COVID-19 on posttraumatic stress disorder as modified by health literacy: an observational study in Vietnam.

BACKGROUND: The prevalence of posttraumatic stress disorder (PTSD) has increased, particularly among individuals who have recovered from coronavirus disease 2019 (COVID-19) infection. Health literacy is considered a "social vaccine" that helps people respond effectively to the pandemic. We aimed to investigate the association between long COVID-19 and PTSD, and to examine the modifying role of health literacy in this association. METHODS: A cross-sectional study was conducted at 18 hospitals and health centers in Vietnam from December 2021 to October 2022. We recruited 4,463 individuals who had recovered from COVID-19 infection for at least 4 weeks. Participants provided information about their sociodemographics, clinical parameters, health-related behaviors, health literacy (using the 12-item short-form health literacy scale), long COVID-19 symptoms and PTSD (Impact Event Scale-Revised score of 33 or higher). Logistic regression models were used to examine associations and interactions. RESULTS: Out of the study sample, 55.9% had long COVID-19 symptoms, and 49.6% had PTSD. Individuals with long COVID-19 symptoms had a higher likelihood of PTSD (odds ratio [OR], 1.86; 95% confidence interval [CI], 1.63-2.12; p<0.001). Higher health literacy was associated with a lower likelihood of PTSD (OR, 0.98; 95% CI, 0.97-0.99; p=0.001). Compared to those without long COVID-19 symptoms and the lowest health literacy score, those with long COVID-19 symptoms and a 1-point health literacy increment had a 3% lower likelihood of PTSD (OR, 0.97; 95% CI, 0.96-0.99; p=0.001). CONCLUSION: Health literacy was found to be a protective factor against PTSD and modified the negative impact of long COVID-19 symptoms on PTSD.

OSBP-mediated PI(4)P-cholesterol exchange at endoplasmic reticulum-secretory granule contact sites controls insulin secretion.

Insulin is packaged into secretory granules that depart the Golgi and undergo a maturation process that involves changes in the protein and lipid composition of the granules. Here, we show that insulin secretory granules form physical contacts with the endoplasmic reticulum and that the lipid exchange protein oxysterol-binding protein (OSBP) is recruited to these sites in a Ca2+-dependent manner. OSBP binding to insulin granules is positively regulated by phosphatidylinositol-4 (PI4)-kinases and negatively regulated by the PI4 phosphate (PI(4)P) phosphatase Sac2. Loss of Sac2 results in excess accumulation of cholesterol on insulin granules that is normalized when OSBP expression is reduced, and both acute inhibition and small interfering RNA (siRNA)-mediated knockdown of OSBP suppress glucose-stimulated insulin secretion without affecting insulin production or intracellular Ca2+ signaling. In conclusion, we show that lipid exchange at endoplasmic reticulum (ER)-granule contact sites is involved in the exocytic process and propose that these contacts act as reaction centers with multimodal functions during insulin granule maturation.

Cyclosporine A-induced systemic metabolic perturbations in rats: A comprehensive metabolome analysis.

A better understanding of cyclosporine A (CsA)-induced nephro- and hepatotoxicity at the molecular level is necessary for safe and effective use. Utilizing a sophisticated study design, this study explored metabolic alterations after long-term CsA treatment in vivo. Rats were exposed to CsA with 4, 10, and 25 mg/kg for 4 weeks and then sacrificed to obtain liver, kidney, urine, and serum for untargeted metabolomics analysis. Differential network analysis was conducted to explore the biological relevance of metabolites significantly altered by toxicity-induced disturbance. Dose-dependent toxicity was observed in all biospecimens. The toxic effects were characterized by alterations of metabolites related to energy metabolism and cellular membrane composition, which could lead to the cholestasis-induced accumulation of bile acids in the tissues. The unfavorable impacts were also demonstrated in the serum and urine. Intriguingly, phenylacetylglycine was increased in the kidney, urine, and serum treated with high doses versus controls. Differential correlation network analysis revealed the strong correlations of deoxycytidine and guanosine with other metabolites in the network, which highlighted the influence of repeated CsA exposure on DNA synthesis. Overall, prolonged CsA administration had system-level dose-dependent effects on the metabolome in treated rats, suggesting the need for careful usage and dose adjustment.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management.

The spread of tuberculosis (TB), especially multidrug-resistant TB and extensively drug-resistant TB, has strongly motivated the research and development of new anti-TB drugs. New strategies to facilitate drug combinations, including pharmacokinetics-guided dose optimization and toxicology studies of first- and second-line anti-TB drugs have also been introduced and recommended. Liquid chromatography-mass spectrometry (LC-MS) has arguably become the gold standard in the analysis of both endo- and exo-genous compounds. This technique has been applied successfully not only for therapeutic drug monitoring (TDM) but also for pharmacometabolomics analysis. TDM improves the effectiveness of treatment, reduces adverse drug reactions, and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window. Based on TDM, the dose would be optimized individually to achieve favorable outcomes. Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs, aiding in the discovery of potential biomarkers for TB diagnostics, treatment monitoring, and outcome evaluation. This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades. Besides, we discussed the advantages and disadvantages of this technique in practical use. The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted. Lastly, we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies (pharmacometrics, drug and vaccine developments, machine learning/artificial intelligence, among others) to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

Response surface methodology for aqueous two-phase system extraction: An unprecedented approach for the specific flavonoid-rich extraction of Houttuynia cordata Thunb. leaves towards acne treatment.

Background: Houttuynia cordata Thunb. has long been widely used as a daily vegetable and traditional medicine. The flavonoid component of H. cordata has plenty of pharmacological effects, such as antibacterial, anti-inflammatory, and antioxidant. In this study, we applied the aqueous two-phase system (ATPS) combined with ultrasonic extraction for extracting H. cordata leaves. Methods: We optimized the extraction process to improve the extraction efficiency of the two flavonoids, hyperin and quercitrin, by Surface Method Response - Central Composite Design (RSM-CCD). Next, we investigated the antibacterial ability of H. cordata ATPS extract from optimal conditions against two bacterial strains, Cutibacterium acnes and Staphylococcus epidermidis. Results: The results showed that using 10% (NH4)2SO4 and 35% ethanol for ATPS extraction resulted in the highest hyperin and quercitrin contents. From the RSM-CCD results, the optimal extraction conditions were determined to be ultrasonic extraction at 50 °C for 30 min, giving results consistent with the predicted model and obtaining hyperin and quercitrin contents at 1.5681 ± 0.0114 and 4.6225 ± 0.0327 mg/g, respectively.Furthermore, ATPS extract has excellent antibacterial activity with a minimum inhibitory concentration (MIC) value of 250 µg/mL on both C. acnes and S. epidermidis. This MIC is significantly lower than the H. cordata ultrasound-assisted (UA) extract, with MICs of 1500.00 and 156.25 µg/mL on C. acnes and S. epidermidis, respectively. In addition, the results from the disk diffusion assay also showed that ATPS extraction has superior internal antibacterial activity with a zone of inhibition diameter at 250 µg/mL of 8.67 ± 1.15 and 5.00 ± 2.00 mm. Meanwhile, those of UA extract on C. acnes is 5.67 ± 1.53 mm (at 1500 µg/mL), and on S. epidermidis is 1.34 ± 0.58 mm (at 156.25 µg/mL). Conclusion: To sum up, our research highlights the potential of H. cordata ATPS extracts as the starting material for topical preparations for effectively treating acne.

Metabolic phenotyping and global functional analysis facilitate metabolic signature discovery for tuberculosis treatment monitoring.

Tracking alterations in polar metabolite and lipid levels during anti-tuberculosis (TB) interventions is an emerging biomarker discovery and validation approach due to its sensitivity in capturing changes and reflecting on the host status. Here, we employed deep plasma metabolic phenotyping to explore the TB patient metabolome during three phases of treatment: at baseline, during intensive phase treatment, and upon treatment completion. Differential metabolites (DMs) in each period were determined, and the pathway-level biological alterations were explored by untargeted metabolomics-guided functional interpretations that bypassed identification. We identified 41 DMs and 39 pathways that changed during intensive phase completion. Notably, levels of certain amino acids including histidine, bile acids, and metabolites of purine metabolism were dramatically increased. The altered pathways included those involved in the metabolism of amino acids, glycerophospholipids, and purine. At the end of treatment, 44 DMs were discovered. The levels of glutamine, bile acids, and lysophosphatidylinositol significantly increased compared to baseline; the levels of carboxylates and hypotaurine declined. In addition, 37 pathways principally associated with the metabolism of amino acids, carbohydrates, and glycan altered at treatment completion. The potential of each DM for diagnosing TB was examined using a cohort consisting of TB patients, those with latent infections, and controls. Logistic regression revealed four biomarkers (taurine, methionine, glutamine, and acetyl-carnitine) that exhibited excellent performance in differential diagnosis. In conclusion, we identified metabolites that could serve as useful metabolic signatures for TB management and elucidated underlying biological processes affected by the crosstalk between host and TB pathogen during treatment.

Prevalence and drug susceptibility of clinical Candida species in nasopharyngeal cancer patients in Vietnam.

In the nature, Candida species are normal inhabitants and can be observed in a wide variety of vertebrates. In humans, especially for cancer patients who fall prey to opportunistic pathogens, this group of susceptible multi-drug resistant and biofilm-forming yeasts, are among the commonest ones. In this study, Candida species in 76 oral lesion samples from Vietnamese nasopharyngeal-cancer patients were isolated, morphologically identified using CHROMagar™, germ tube formation, and chlamydospore formation tests, and molecularly confirmed by PCR-RFLP. The drug susceptibility of these isolates was then tested, and the gene ERG11 was DNA sequenced to investigate the mechanism of resistance. The results showed that Candida albicans remained the most prevalent species (63.16% of the cases), followed by Candida glabrata, Candida tropicalis, and Candida krusei. The rates of resistance of non-albicans Candida for tested drugs were 85.71%, 53.57%, and 57.14% to fluconazole, clotrimazole, and miconazole, respectively. Although the drug-resistance rate of Candida albicans was lower than that of non-albicans Candida, it was higher than expected, suggesting an emerging drug-resistance phenomenon. Furthermore, ERG11 DNA sequencing revealed different mutations (especially K128T), implying the presence of multiple resistance mechanisms. Altogether, the results indicate an alarming drug-resistance situation in Candida species in Vietnamese cancer patients and emphasize the importance of species identification and their drug susceptibility prior to treatment.

Effect of Pharmacist-Led Training on Adherence and Practice of Inhaler Use: A Pre-Post Interventional Study in Outpatients With Asthma at Hue University Hospital.

Objective This study aimed to evaluate the impact of a pharmacist-led intervention on improving adherence and practice of inhaler use in outpatients with asthma at a hospital in Vietnam. Methods A pre-post interventional study was conducted at Hue University Hospital. An adapted checklist for both metered-dose inhalers and/or dry powder inhalers was used to evaluate the inhaler technique. Adherence was assessed by using the Test of Adherence to Inhalers questionnaire. The means of interventions comprised "Face-to-face training," "Creating the leaflet for patients," and "Watching guidance video." Results The number of participants with complete data was 79. Before the intervention, 54.4% of patients had misused inhalers, especially inappropriate posture when using devices (70.2%) and not exhaling before inhalation (46.8%). Non-adherence accounted for 55.7% of patients, and the erratic pattern was the highest, with 83.5%. The intervention had remarkably raised the number of good practice and good adherence patients after three months (P < 0.001). Conclusion Pharmacist-led intervention has a positive impact on improving the adherence to inhalers and inhalation techniques of patients with asthma. Practice Implications The pharmacist-led education model could be considered as an effective and feasible solution for asthma management in outpatients and better medication use. Key Points (1) The most frequently observed mistakes in this study were inappropriate posture and inhalation skill when using devices. (2) Pharmacist-led training remarkably improved patients' practice of inhaler use as well as medication adherence.

Process and outcomes from systemization of a longitudinal advanced pharmacy practice experience (LAPPE) program.

PURPOSE: Longitudinal models for completing advanced pharmacy practice experiences were implemented to enhance experiential training efficiency through extracurricular experiences and to offer high-quality learning continuously. Through multihospital expansion of an established single-site longitudinal advanced pharmacy practice experience (LAPPE) program, the expanded collaborative opportunities support the development of new concepts that enhance integrated learning. METHODS: An observational study was designed to describe the approach for constructing a LAPPE program integrated across a multihospital system, to assess the professional skills gained by the program graduates, and to evaluate program impact on graduates' professional career. A questionnaire was developed for current students to assess the program's impact across 5 domains. Value-added benefits for the health system and challenges to implementation of a systemized program were reviewed as guidance for institutions interested in implementing such a model. RESULTS: Expansion of a single-site LAPPE program across a multihospital health system requires significant coordination from leadership, especially during the recruitment and interview process. Additionally, integration of preceptors across sites bolsters student experiences for various professional activities offered in a LAPPE program. This program's questionnaire results pointed toward an increase in students' knowledge and skills in preparation for postgraduate training. For students entering the ASHP Resident Matching Program, there was a 100% residency match rate before and after program systemization. CONCLUSION: The expansion of a LAPPE program across a multihospital system offers intangible benefits to an institution, expands self-reported competencies, and establishes a foundation for postgraduate success. This model may be utilized at institutions with similar interest to implement, expand, or systemize a LAPPE program.