Background: Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples. Methods: We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples. Results: We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5. Conclusions We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Background: Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples. Methods: We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples. Results: We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5. Conclusions We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Background: Although the criteria for follicular-pattern thyroid tumors are well-established, diagnosing these lesions remains challenging in some cases. In the recent World Health Organization Classification of Endocrine and Neuroendocrine Tumors (5th edition), the invasive encapsulated follicular variant of papillary thyroid carcinoma was reclassified as its own entity. It is crucial to differentiate this variant of papillary thyroid carcinoma from low-risk follicular pattern tumors due to their shared morphological characteristics. Proteomics holds significant promise for detecting and quantifying protein biomarkers. We investigated the potential value of a protein biomarker panel defined by machine learning for identifying the invasive encapsulated follicular variant of papillary thyroid carcinoma, initially using formalin- fixed paraffin-embedded samples. Methods: We developed a supervised machine-learning model and tested its performance using proteomics data from 46 thyroid tissue samples. Results: We applied a random forest classifier utilizing five protein biomarkers (ZEB1, NUP98, C2C2L, NPAP1, and KCNJ3). This classifier achieved areas under the curve (AUCs) of 1.00 and accuracy rates of 1.00 in training samples for distinguishing the invasive encapsulated follicular variant of papillary thyroid carcinoma from non-malignant samples. Additionally, we analyzed the performance of single-protein/gene receiver operating characteristic in differentiating the invasive encapsulated follicular variant of papillary thyroid carcinoma from others within The Cancer Genome Atlas projects, which yielded an AUC >0.5. Conclusions We demonstrated that integration of high-throughput proteomics with machine learning can effectively differentiate the invasive encapsulated follicular variant of papillary thyroid carcinoma from other follicular pattern thyroid tumors.

Objective: To investigate the cause of a foodborne outbreak that occurred in Dong Nai province, Viet Nam, in 2024, and implement control measures. Methods: An initial investigation was conducted to confirm the outbreak, which was followed by epidemiological and environmental investigations to find the plausible causative food item. Clinical specimens and food samples were tested to identify the pathogen. Results: A total of 547 symptomatic cases were recorded, of whom two were in severe condition requiring extracorporeal membrane oxygenation and ventilation, one of whom died. Among 99 interviewed cases, the mean incubation time was 9 hours (range 2–24 hours), with the main symptoms being fever, abdominal pain, diarrhoea and vomiting. All patients had eaten banh mi from a local bakery. Salmonella spp. were identified in food samples and clinical specimens. The bakery halted production, and the outbreak ended after 1 week. Discussion: All the patients were exposed to only one food in common, which facilitated the investigation process. This outbreak is a reminder to small retailers and take-away shops of the importance of food safety management in preventing similar future outbreaks. All food handlers must comply with food hygiene principles, especially in hot temperatures, which boosts bacterial growth.

Background: Anaplastic lymphoma kinase (ALK) mutations have been identified as a prominent cause of some familial and sporadic neuroblastoma (NB). ALK expression in NB and its relationship with clinical and histopathological features remains controversial. This study investigated ALK expression and its potential relations with these features in NB. Methods: Ninety cases of NB at the Department of Pathology, University of Medicine and Pharmacy at Ho Chi Minh City, Viet Nam from 01/01/2018 to 12/31/2021, were immunohistochemically stained with ALK (D5F3) antibody. The ALK expression and its relations with some clinical and histopathological features were investigated. Results: The rate of ALK expression in NB was 91.1%. High ALK expression (over 50% of tumor cells were positive with moderate-strong intensity) accounted for 65.6%, and low ALK expression accounted for 34.4%. All the MYCN-amplified NB patients had ALK immunohistochemistry positivity, most cases had high ALK protein expression. The undifferentiated subtype of NB had a lower ALK-positive rate than the poorly differentiated and differentiated subtype. The percentages of ALK positivity were significantly higher in more differentiated histological types of NB (p = .024). There was no relation between ALK expression and: age group, sex, primary tumor location, tumor stage, MYCN status, clinical risk, Mitotic-Karyorrhectic Index, prognostic group, necrosis, and calcification. Conclusions ALK was highly expressed in NB. ALK expression was not related to several clinical and histopathological features. More studies are needed to elucidate the association between ALK expression and ALK gene status and to investigate disease progression, especially the oncogenesis of ALK-positive NB.

Background: The identification of idiopathic inflammatory myopathies (IIMs) requires a comprehensive analysis involving clinical manifestations and histological findings. This study aims to provide insights into the histopathological and immunohistochemical aspects of IIMs. Methods: This retrospective case series involved 56 patients diagnosed with IIMs at the Department of Pathology, University of Medicine and Pharmacy at Ho Chi Minh City, from 2019 to 2023. The histology and immunohistochemical expression of HLA-ABC, HLA-DR, C5b-9, Mx1/2/3, and p62 were detected. Results: We examined six categories of inflammatory myopathy, including immunemediated necrotizing myopathy (58.9%), dermatomyositis (DM; 23.2%), overlap myositis (8.9%), antisynthetase syndrome (5.4%), inclusion body myositis (IBM; 1.8%), and polymyositis (1.8%). The average age of the patients was 49.7 ± 16.1 years, with a female-to-male ratio of 3:1. Inflammatory cell infiltration in the endomysium was present in 62.5% of cases, perifascicular atrophy was found in 17.8%, and fiber necrosis was observed in 42 cases (75.0%). Rimmed vacuoles were present in 100% of cases in the IBM group. Immunohistochemistry showed the following positivity rates: HLA-ABC (89.2%), HLA-DR (19.6%), C5b-9 (57.1%), and Mx1/2/3 (10.7%). Mx1/2/3 expression was high in DM cases. p62 vacuole deposits were noted in the IBM case. The combination of membrane attack complex and major histocompatibility complex I helped detect IIMs in 96% of cases. Conclusions The diagnosis of IIMs and their subtypes should be based on clinical features and histopathological characteristics. Immunohistochemistry plays a crucial role in the diagnosis and differentiation of these subgroups.

Objectives: The objective of this study was to characterize mental health issues among Vietnamese healthcare workers (HCWs) and to identify related factors. Methods: A cross-sectional study was conducted with 990 HCWs in 2021. Their mental health status was measured using the Depression, Anxiety, and Stress Scale. Results: In total, 49.9%, 52.3%, and 29.8% of respondents were found to have depression, anxiety, and stress, respectively. The multivariable linear regression model revealed that factors associated with increased anxiety scores included depression scores (β, 0.45; 95% confidence interval [CI], 0.39 to 0.51) and stress scores (β, 0.46; 95% CI, 0.41 to 0.52). Factors associated with increased depression scores included being frontline HCWs (β, 0.57; 95% CI, 0.10 to 1.10), stress scores (β, 0.50; 95% CI, 0.45 to 0.56), and anxiety scores (β, 0.41; 95% CI, 0.36 to 0.47), while working experience was associated with reduced depression scores (β, -0.08; 95% CI, -0.16 to -0.01). Factors associated with increased stress scores included working experience (β, 0.08; 95% CI, 0.00 to 0.16), personal protective equipment interference with daily activities (β, 0.55; 95% CI, 0.07 to 1.00), depression scores (β, 0.54; 95% CI, 0.48 to 0.59), and anxiety scores (β, 0.45; 95% CI, 0.39 to 0.50), while age was associated with reduced stress scores (β, -0.12; 95% CI, -0.20 to -0.05). Conclusions Specific interventions are necessary to enhance and promote the mental health of HCWs so they can successfully cope with the circumstances of the pandemic.

Purpose: This study aimed to determine the occurrence rate of gestational trophoblastic neoplasia (GTN) and its related factors in aged women with hydatidiform mole (HM) in Tu Du Hospital, Vietnam. Materials and Methods: This retrospective cohort study included 372 women aged ≥40 years with HM diagnosed through postabortion histopathological assessment in Tu Du Hospital from January 2016 to March 2019. Survival analysis was used for GTN cumulative rate estimation, log-rank test for group comparison, and Cox regression model for determining GTN-related factors. Results: After a 2-year follow-up, 123 patients were found to have GTN at a rate of 33.06% [95% confidence interval (CI): 28.30– 38.10]. GTN occurrence meant that the time was 4.15±2.93 weeks with peaks at week 2 and 3 after curettage abortion. The GTN rate was remarkably higher in the ≥46-year age group than in the 40-to-45-year age group [hazard ratio (HR)=1.63; 95%CI: 1.09– 2.44], as was the vaginal bleeding group compared to the non-bleeding group (HR=1.85; 95%CI: 1.16–2.96). Preventive hysterectomy and preventive chemotherapy plus hysterectomy in the intervention group reduced the GTN risk compared to the no intervention group at HRs of 0.16 (95%CI: 0.09–0.30) and 0.09 (95%CI: 0.04–0.21), respectively. Chemoprophylaxis failed to decrease the GTN risk when comparing the two groups. Conclusion Post-molar pregnancy GTN rate in aged patients was 33.06%, much higher than that of the general population. Preventive hysterectomy or chemoprophylaxis plus hysterectomy are effective treatment methods to support GTN risk reduction.

Objectives: The coronavirus disease 2019 (COVID-19) pandemic has increased the workload of healthcare workers (HCWs), impacting their health. This study aimed to assess sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and identify factors associated with poor sleep among HCWs in Vietnam during the COVID-19 pandemic. Methods: In this cross-sectional study, 1000 frontline HCWs were recruited from various healthcare facilities in Vietnam between October 2021 and November 2021. Data were collected using a 3-part self-administered questionnaire, which covered demographics, sleep quality, and factors related to poor sleep. Poor sleep quality was defined as a total PSQI score of 5 or higher. Results: Participants’ mean age was 33.20±6.81 years (range, 20.0-61.0), and 63.0% were women. The median work experience was 8.54±6.30 years. Approximately 6.3% had chronic comorbidities, such as hypertension and diabetes mellitus. About 59.5% were directly responsible for patient care and treatment, while 7.1% worked in tracing and sampling. A total of 73.8% reported poor sleep quality. Multivariate logistic regression revealed significant associations between poor sleep quality and the presence of chronic comorbidities (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.17 to 5.24), being a frontline HCW directly involved in patient care and treatment (OR, 1.59; 95% CI, 1.16 to 2.16), increased working hours (OR, 1.84; 95% CI,1.37 to 2.48), and a higher frequency of encountering critically ill and dying patients (OR, 1.42; 95% CI, 1.03 to 1.95). Conclusions The high prevalence of poor sleep among HCWs in Vietnam during the COVID-19 pandemic was similar to that in other countries. Working conditions should be adjusted to improve sleep quality among this population.

Objectives: Tuberculosis (TB) and drug-resistant TB (DR-TB) are national health burdens in Vietnam. In this study, we investigated the prevalence of rifampicin (RIF) and/or isoniazid (isonicotinic acid hydrazide, INH) resistance in patients with suspected TB, and applied appropriate techniques to help rapidly target DR-TB. Methods: In total, 1,547 clinical specimens were collected and cultured using the BACTEC MGIT system (Becton Dickinson and Co.). A resazurin microtiter assay (REMA) was used to determine the proportions of RIF and/or INH resistance. A real-time polymerase chain reaction panel with TaqMan probes was employed to identify the mutations of rpoB and katG associated with DR-TB in clinical isolates. Genotyping of the identified mutations was also performed. Results: A total of 468 Mycobacterium tuberculosis isolates were identified using the REMA. Of these isolates, 106 (22.6%) were found to be resistant to 1 or both antibiotics. Of the resistant isolates, 74 isolates (69.8%) were resistant to isoniazid (INH) only, while 1 isolate (0.94%) was resistant to RIF only. Notably, 31 isolates (29.24%) were resistant to both antibiotics. Of the 41 phenotypically INH-resistant isolates, 19 (46.3%) had the Ser315Thr mutation. There were 8 different rpoB mutations in 22 (68.8%) of the RIF-resistant isolates. The most frequently detected mutations were at codons 531 (37.5%), 526 (18.8%), and 516 (6.3%). Conclusion To help prevent new cases of DR-TB in Vietnam, it is crucial to gain a comprehensive understanding of the genotypic DR-TB isolates.