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Background Plasmodium malariae , a causative agent of human quartan malaria, has been largely overlooked due to its mild clinical manifestations and low prevalence. Genetic information of the parasite is also very limited, particularly for clinical isolates. In this study, we analyzed the genetic nature of apical membrane antigen-1 (AMA-1) in Vietnam P. malariae isolates to expand knowledge on the genetic nature of the vaccine candidate protein. Method The gene encoding AMA-1 of P. malariae ( pmama-1 ) was amplified from 95 Vietnam P. malariae isolates and sequenced. Polymorphic patterns and natural selection of the pmama-1 were examined with programs such as BioEdit, MEGA4, and DnaSP. Comparative analysis of genetic polymorphisms and natural selection in pmama-1 from other Southeast Asia countries was also conducted. Results A total of 117 Vietnam pmama-1 sequences were obtained from 95 Vietnam P. malariae isolates. The majority of amino acid polymorphisms were identified in domains I and II, grouping Vietnam pmama-1 into 19 distinct haplotypes. Although overall profiles of amino acid polymorphisms in Vietnam pmama-1 mirrored those from other Southeast Asia countries, positions and frequencies of amino acid changes varied by countries. Most amino acid changes detected in pmama-1 were predicted to be positioned on the surface of the protein. Evidences of natural selection and evolutionary trend of the gene were also observed. Conclusions This study highlights a substantial genetic heterogeneity of pmama-1 in P. malariae population and expands our knowledge on genetic nature of this gene. To understand the genetic nature and evolution of global pmama-1 , further studies with larger numbers of P. malariae isolates from other global regions are necessary.

, a causative agent of quartan malaria, is prevalent across tropical and subtropical regions, but global cases have been usually very rare and sporadic. However, a significant outbreak of quartan malaria caused by occurred in Khanh Vinh District, Khanh Hoa Province, Vietnam in 2023 and the outbreak persists. In this report, we present the epidemiological and clinical characteristics of this unprecedented outbreak of quartan malaria in Vietnam.

Background Late detection of hepatocellular carcinoma (HCC) results in an overall 5-year survival rate of less than 16%. Liquid biopsy (LB) assays based on detecting circulating tumor DNA (ctDNA) might provide an opportunity to detect HCC early noninvasively. Increasing evidence indicates that ctDNA detection using mutation-based assays is significantly challenged by the abundance of white blood cell-derived mutations, non-tumor tissue-derived somatic mutations in plasma, and the mutational tumor heterogeneity. Methods Here, we employed concurrent analysis of cancer-related mutations, and their fragment length profiles to differentiate mutations from different sources. To distinguish persons with HCC (PwHCC) from healthy participants, we built a classification model using three fragmentomic features of ctDNA through deep sequencing of thirteen genes associated with HCC. Results Our model achieved an area under the curve (AUC) of 0.88, a sensitivity of 89%, and a specificity of 82% in the discovery cohort consisting of 55 PwHCC and 55 healthy participants. In an independent validation cohort of 54 PwHCC and 53 healthy participants, the established model achieved comparable classification performance with an AUC of 0.86 and yielded a sensitivity and specificity of 81%. Conclusions Our study provides a rationale for subsequent clinical evaluation of our assay performance in a large-scale prospective study.

Antiretroviral therapy (ART) retention and 5 early-warning indicators (EWIs) of HIV drug resistance (HIVDR) were abstracted at 27 adult and 4 pediatric clinics in Vietnam in 2009. Of 4531 adults and 313 children, 81.2% and 84.4% respectively were still on ART at 12 months. More than 90% of the clinics monitored achieved the World Health Organization (WHO) targets for lost-to-follow-up (LTFU), ART prescribing practices, and ARV supply continuity. Only 83.9% of the clinics met the target for first-line ART retention and 79.3% met the target for clinic appointment-keeping. Clinic factors (i.e. number of patients, administrative level, and geographical region) were associated with ART retention and LFTU. Data were useful in guiding public health action to optimize ART services.

Despite their promise, circulating tumor DNA (ctDNA)-based assays for multi-cancer early detection face challenges in test performance, due mostly to the limited abundance of ctDNA and its inherent variability. To address these challenges, published assays to date demanded a very high-depth sequencing, resulting in an elevated price of test. Herein, we developed a multimodal assay called SPOT-MAS (screening for the presence of tumor by methylation and size) to simultaneously profile methylomics, fragmentomics, copy number, and end motifs in a single workflow using targeted and shallow genome-wide sequencing (~0.55×) of cell-free DNA. We applied SPOT-MAS to 738 non-metastatic patients with breast, colorectal, gastric, lung, and liver cancer, and 1550 healthy controls. We then employed machine learning to extract multiple cancer and tissue-specific signatures for detecting and locating cancer. SPOT-MAS successfully detected the five cancer types with a sensitivity of 72.4% at 97.0% specificity. The sensitivities for detecting early-stage cancers were 73.9% and 62.3% for stages I and II, respectively, increasing to 88.3% for non-metastatic stage IIIA. For tumor-of-origin, our assay achieved an accuracy of 0.7. Our study demonstrates comparable performance to other ctDNA-based assays while requiring significantly lower sequencing depth, making it economically feasible for population-wide screening.

Background Interpreting point-of-care lung ultrasound (LUS) images from intensive care unit (ICU) patients can be challenging, especially in low- and middle- income countries (LMICs) where there is limited training available. Despite recent advances in the use of Artificial Intelligence (AI) to automate many ultrasound imaging analysis tasks, no AI-enabled LUS solutions have been proven to be clinically useful in ICUs, and specifically in LMICs. Therefore, we developed an AI solution that assists LUS practitioners and assessed its usefulness in  a low resource ICU. Methods This was a three-phase prospective study. In the first phase, the performance of four different clinical user groups in interpreting LUS clips was assessed. In the second phase, the performance of 57 non-expert clinicians with and without the aid of a bespoke AI tool for LUS interpretation was assessed in retrospective offline clips. In the third phase, we conducted a prospective study in the ICU where 14 clinicians were asked to carry out LUS examinations in 7 patients with and without our AI tool and we interviewed the clinicians regarding the usability of the AI tool. Results The average accuracy of beginners’ LUS interpretation was 68.7% [95% CI 66.8–70.7%] compared to 72.2% [95% CI 70.0–75.6%] in intermediate, and 73.4% [95% CI 62.2–87.8%] in advanced users. Experts had an average accuracy of 95.0% [95% CI 88.2–100.0%], which was significantly better than beginners, intermediate and advanced users ( p  < 0.001). When supported by our AI tool for interpreting retrospectively acquired clips, the non-expert clinicians improved their performance from an average of 68.9% [95% CI 65.6–73.9%] to 82.9% [95% CI 79.1–86.7%], ( p  < 0.001). In prospective real-time testing, non-expert clinicians improved their baseline performance from 68.1% [95% CI 57.9–78.2%] to 93.4% [95% CI 89.0–97.8%], ( p  < 0.001) when using our AI tool. The time-to-interpret clips improved from a median of 12.1 s (IQR 8.5–20.6) to 5.0 s (IQR 3.5–8.8), ( p  < 0.001) and clinicians’ median confidence level improved from 3 out of 4 to 4 out of 4 when using our AI tool. Conclusions AI-assisted LUS can help non-expert clinicians in an LMIC ICU improve their performance in interpreting LUS features more accurately, more quickly and more confidently.

Vietnam features extensive ethnolinguistic diversity and occupies a key position in Mainland Southeast Asia. Yet, the genetic diversity of Vietnam remains relatively unexplored, especially with genome-wide data, because previous studies have focused mainly on the majority Kinh group. Here, we analyze newly generated genome-wide single-nucleotide polymorphism data for the Kinh and 21 additional ethnic groups in Vietnam, encompassing all five major language families in Mainland Southeast Asia. In addition to analyzing the allele and haplotype sharing within the Vietnamese groups, we incorporate published data from both nearby modern populations and ancient samples for comparison. In contrast to previous studies that suggested a largely indigenous origin for Vietnamese genetic diversity, we find that Vietnamese ethnolinguistic groups harbor multiple sources of genetic diversity that likely reflect different sources for the ancestry associated with each language family. However, linguistic diversity does not completely match genetic diversity: There have been extensive interactions between the Hmong-Mien and Tai-Kadai groups; different Austro-Asiatic groups show different affinities with other ethnolinguistic groups; and we identified a likely case of cultural diffusion in which some Austro-Asiatic groups shifted to Austronesian languages during the past 2,500 years. Overall, our results highlight the importance of genome-wide data from dense sampling of ethnolinguistic groups in providing new insights into the genetic diversity and history of an ethnolinguistically diverse region, such as Vietnam.

Vietnam is an important crossroads within Mainland Southeast Asia (MSEA) and a gateway to Island Southeast Asia, and as such exhibits high levels of ethnolinguistic diversity. However, comparatively few studies have been undertaken of the genetic diversity of Vietnamese populations. In order to gain comprehensive insights into MSEA mtDNA phylogeography, we sequenced 609 complete mtDNA genomes from individuals belonging to five language families (Austroasiatic, Tai-Kadai, Hmong-Mien, Sino-Tibetan and Austronesian) and analyzed them in comparison with sequences from other MSEA countries and Taiwan. Within Vietnam, we identified 399 haplotypes belonging to 135 haplogroups; among the five language families, the sequences from Austronesian groups differ the most from the other groups. Phylogenetic analysis revealed 111 novel Vietnamese mtDNA lineages. Bayesian estimates of coalescence times and associated 95% HPD for these show a peak of mtDNA diversification around 2.5–3 kya, which coincides with the Dong Son culture, and thus may be associated with the agriculturally-driven expansion of this culture. Networks of major MSEA haplogroups emphasize the overall distinctiveness of sequences from Taiwan, in keeping with previous studies that suggested at most a minor impact of the Austronesian expansion from Taiwan on MSEA. We also see evidence for population expansions across MSEA geographic regions and language families.

BackgroundVietnam possesses a vast diversity of rice landraces due to its geographical situation, latitudinal range, and a variety of ecosystems. This genetic diversity constitutes a highly valuable resource at a time when the highest rice production areas in the low-lying Mekong and Red River Deltas are enduring increasing threats from climate changes, particularly in rainfall and temperature patterns.ResultsWe analysed 672 Vietnamese rice genomes, 616 newly sequenced, that encompass the range of rice varieties grown in the diverse ecosystems found throughout Vietnam. We described four Japonica and five Indica subpopulations within Vietnam likely adapted to the region of origin. We compared the population structure and genetic diversity of these Vietnamese rice genomes to the 3000 genomes of Asian cultivated rice. The named Indica-5 (I5) subpopulation was expanded in Vietnam and contained lowland Indica accessions, which had very low shared ancestry with accessions from any other subpopulation and were previously overlooked as admixtures. We scored phenotypic measurements for nineteen traits and identified 453 unique genotype-phenotype significant associations comprising twenty-one QTLs (quantitative trait loci). The strongest associations were observed for grain size traits, while weaker associations were observed for a range of characteristics, including panicle length, heading date and leaf width.ConclusionsWe showed how the rice diversity within Vietnam relates to the wider Asian rice diversity by using a number of approaches to provide a clear picture of the novel diversity present within Vietnam, mainly around the Indica-5 subpopulation. Our results highlight differences in genome composition and trait associations among traditional Vietnamese rice accessions, which are likely the product of adaption to multiple environmental conditions and regional preferences in a very diverse country. Our results highlighted traits and their associated genomic regions that are a potential source of novel loci and alleles to breed a new generation of low input sustainable and climate resilient rice.

Drug-related problems (DRPs) are common in clinical practice and occur at all stages of the medication process. The major factor contributing to DRPs is prescription, although patients' poor adherence to treatment is also a significant factor. This study evaluated type 2 diabetes outpatients in a hospital in Vietnam for drug-related problems (DRPs) and related variables. A cross-sectional descriptive study was conducted on 495 outpatients who met the criteria and 157 people agreed to participate in the interview. Medication order review and medication adherence review were used to identify DRPs. The types of DRP were based on the Pharmaceutical Care Network Europe (PCNE) categories version 9.0. The identification and assessment DRPs were carried out by clinical pharmacists and get agreed upon by physicians who had not directly prescribed patients who participated in the study. A total of 762 DRPs were identified via prescribing review process, the average number of DRP on each prescription was 1.54±1.07, while 412 DRPs were determined through patient interviewing. The most frequent DRPs were \"ADR (Adverse Drug Reaction) occurring\" (68.8%). The main causes were \"patient is unable to understand instructions properly\" or \"patient is not properly instructed\", \"patient stores insulin inappropriately\", \"patient decides to use unnecessary drugs\" and \"patient intentionally uses/takes less drug than prescribed or does not take the drug at all for whatever reason\" which accounted for 65.0%, 41.4%, 38.2%, and 28.7%, respectively. From the prescribing review, the most observed DRPs were \"Inappropriate drug according to guidelines/formulary\" and \"No or incomplete drug treatment in spite of existing indication\", accounting for 45.0% and 42.9%, respectively. There was a significant association between age (OR 3.38, 95% CI: 1.01-11.30), duration of diabetes (OR 3.61, 95%CI: 1.11-11.74), presence of comorbidity (OR 5.31, 95%CI: 1.97-14.30), polypharmacy (OR: 2.95, 95%CI: 1.01-8.72) and DRPs. In patients, poor knowledge of antidiabetic agents was the main reason to lack adherence and occurring ADR (OR 2.73, 95%CI: 1.32-5.66, p = 0.007 and OR 2.49, 95%CI: 1.54-4.03, p = 0.001 respectively). DRPs occurred in the prescribing stage and relating to patient's behavior of drug administration was high. Clear identification of DRPs and the associated factors are essential for building the intervention process to improve effectiveness and safety in the treatment of type 2 diabetes mellitus patients.