Factors associated with shame and stigma among head and neck cancer patients: a cross-sectional study.

PURPOSE: Head and neck cancer (HNC) patients often suffer from shame and stigma due to treatment limitations or due to societal factors. The purpose of this study was to assess perceived body image, depression, physical and psychosocial function, and self-stigma, as well as to identify factors that predicted shame and stigma in patients with HNC. METHODS: This cross-sectional study recruited 178 HNC patients from the outpatient radiation department of a medical center in Northern Taiwan. Patients were assessed for patient reported outcomes using the Body Image Scale (BIS), the Hospital Anxiety and Depression Scale-Depression Subscale (HADS-Depression Subscale), the University of Washington Quality of Life Scale (UW-QOL) version 4.0, and the Shame and Stigma Scale (SSS). Data were analyzed by descriptive analysis, Pearson's product-moment correlation, and multiple regression. RESULTS: The two top-ranked subscales of shame and stigma were: "speech and social concerns" and "regret". Shame and stigma were positively correlated with a longer time since completion of treatment, more body image concerns, and higher levels of depression. They were negatively correlated with being male and having lower physical function. Multiple regression analysis showed that female gender, a longer time since completing treatment, higher levels of body image concern, greater depression, and less physical function predicted greater shame and stigma. These factors explained 74.7% of the variance in shame and stigma. CONCLUSION: Patients' body image concerns, depression, time since completing treatment, and physical function are associated with shame and stigma. Oncology nurses should assess and record psychological status, provide available resources, and refer appropriate HNC patients to counselling.

Can predictive factors determine the time to treatment initiation for oral and oropharyngeal cancer? A classification and regression tree analysis.

This ecological study aimed to identify the factors with the greatest power to discriminate the proportion of oral and oropharyngeal cancer (OOC) records with time to treatment initiation (TTI) within 30 days of diagnosis in Brazilian municipalities. A descriptive analysis was performed on the variables grouped into five dimensions related to patient characteristics, access to health services, support for cancer diagnosis, human resources, and socioeconomic characteristics of 3,218 Brazilian municipalities that registered at least one case of OOC in 2019. The Classification and Regression Trees (CART) technique was adopted to identify the explanatory variables with greater discriminatory power for the TTI response variable. There was a higher median percentage of records in the age group of 60 years or older. The median percentage of records with stage III and IV of the disease was 46.97%, and of records with chemotherapy, radiation, or both as the first treatment was 50%. The median percentage of people with private dental and health insurance was low. Up to 75% had no cancer diagnostic support services, and up to 50% of the municipalities had no specialist dentists. Most municipalities (49.4%) started treatment after more than 30 days. In the CART analysis, treatment with chemotherapy, radiotherapy, or both explained the highest TTI in all municipalities, and it was the most relevant for predicting TTI. The final model also included anatomical sites in the oral cavity and oropharynx and the number of computed tomography services per 100,000. There is a need to expand the availability of oncology services and human resources specialized in diagnosing and treating OOC in Brazilian municipalities for a timely TTI of OOC.

Out-of-Pocket Costs and Payments in Autologous and Implant-Based Breast Reconstruction: A Nationwide Analysis.

BACKGROUND: Many factors influence a patient's decision to undergo autologous versus implant-based breast reconstruction, including medical, social, and financial considerations. This study aims to investigate differences in out-of-pocket and total spending for patients undergoing autologous and implant-based breast reconstruction. METHODS: The IBM MarketScan Commercial Databases were queried to extract all patients who underwent inpatient autologous or implant-based breast reconstruction from 2017 to 2021. Financial variables included gross payments to the provider (facility and/or physician) and out-of-pocket costs (total of coinsurance, deductible, and copayments). Univariate regressions assessed differences between autologous and implant-based reconstruction procedures. Mixed-effects linear regression was used to analyze parametric contributions to total gross and out-of-pocket costs. RESULTS: The sample identified 2079 autologous breast reconstruction and 1475 implant-based breast reconstruction episodes. Median out-of-pocket costs were significantly higher for autologous reconstruction than implant-based reconstruction ($597 vs $250, P < 0.001) as were total payments ($63,667 vs $31,472, P < 0.001). Type of insurance plan and region contributed to variable out-of-pocket costs (P < 0.001). Regression analysis revealed that autologous reconstruction contributes significantly to increasing out-of-pocket costs (B = $597, P = 0.025) and increasing total costs (B = $74,507, P = 0.006). CONCLUSION: The US national data demonstrate that autologous breast reconstruction has higher out-of-pocket costs and higher gross payments than implant-based reconstruction. More study is needed to determine the extent to which these financial differences affect patient decision-making.

HE4-based nomogram for predicting overall survival in patients with idiopathic pulmonary fibrosis: construction and validation.

Idiopathic pulmonary fibrosis (IPF) is a life-threatening interstitial lung disease. Identifying biomarkers for early diagnosis is of great clinical importance. The epididymis protein 4 (HE4) is important in the process of inflammation and fibrosis in the epididymis. Its prognostic value in IPF, however, has not been studied. The mRNA and protein levels of HE4 were used to determine the prognostic value in different patient cohorts. In this study, prognostic nomograms were generated based on the results of the cox regression analysis. We identified the HE4 protein level increased in IPF patients, but not the HE4 gene expression. The increased expression of HE4 correlated positively with a poor prognosis for patients with IPF. The HR and 95% CI were 2.62 (1.61-4.24) (p < 0.001) in the training set. We constructed a model based on the risk-score = 0.16222182 * HE4 + 0/0.37580659/1.05003609 (for GAP index 0-3/4-5/6-8) + (- 1.1183375). In both training and validation sets, high-risk patients had poor prognoses (HR: 3.49, 95%CI 2.10-5.80, p = 0.001) and higher likelihood of dying (HR: 6.00, 95%CI 2.04-17.67, p = 0.001). Analyses of calibration curves and decision curves suggest that the method is effective in predicting outcomes. Furthermore, a similar formulation was used in a protein-based model based on HE4 that also showed prognostic value when applied to IPF patients. Accordingly, HE4 is an independent poor prognosis factor, and it has the potential to predict IPF patient survival.

Effects of taxane-induced peripheral neuropathy on hand dexterity impairment: evaluation of quantitative and subjective assessments.

PURPOSE: Chemotherapy-induced peripheral neuropathy (CIPN) commonly involves hand dexterity impairment. However, the factors affecting hand dexterity impairment are unknown and there is currently no established treatment. The purpose of the current study was to clarify factors influencing hand dexterity impairment in taxane-induced peripheral neuropathy using subjective and objective assessments. METHODS: We assessed patient characteristics, treatment-related factors, subjective symptoms of CIPN (Patient Neurotoxicity Questionnaire [PNQ]), psychological symptoms, and upper limb dysfunction (Quick Disabilities of the Arm, Shoulder and Hand [Quick DASH]). Quantitative assessments were pinch strength, sensory threshold, hand dexterity impairment, and grip force control. Multiple regression analysis was performed using hand dexterity impairment as the dependent variable and age and PNQ, Quick DASH, and control of grip force as independent variables. RESULTS: Forty-three breast cancer patients were included in the analysis. Hand dexterity impairment in taxane-induced peripheral neuropathy patients was significantly correlated with age, grip force control, and PNQ sensory scores (p < 0.008). Multiple regression analysis demonstrated that PNQ sensory scores and grip force control were significantly associated with hand dexterity impairment (p < 0.01). CONCLUSION: Subjective symptoms (numbness and pain) and grip force control contributed to impaired hand dexterity in taxane-induced peripheral neuropathy.

m6Aexpress-enet: Predicting the regulatory expression m6A sites by an enet-regularization negative binomial regression model.

As the most abundant mRNA modification, m6A controls and influences many aspects of mRNA metabolism including the mRNA stability and degradation. However, the role of specific m6A sites in regulating gene expression still remains unclear. In additional, the multicollinearity problem caused by the correlation of methylation level of multiple m6A sites in each gene could influence the prediction performance. To address the above challenges, we propose an elastic-net regularized negative binomial regression model (called m6Aexpress-enet) to predict which m6A site could potentially regulate its gene expression. Comprehensive evaluations on simulated datasets demonstrate that m6Aexpress-enet could achieve the top prediction performance. Applying m6Aexpress-enet on real MeRIP-seq data from human lymphoblastoid cell lines, we have uncovered the complex regulatory pattern of predicted m6A sites and their unique enrichment pathway of the constructed co-methylation modules. m6Aexpress-enet proves itself as a powerful tool to enable biologists to discover the mechanism of m6A regulatory gene expression. Furthermore, the source code and the step-by-step implementation of m6Aexpress-enet is freely accessed at https://github.com/tengzhangs/m6Aexpress-enet.

Prediction of excess cement residues using a regression model to avoid peri-implant diseases: An in vitro study.

Dental implant restorations attached to cement can potentially result in peri-implant mucositis and peri-implantitis if cement residues are present. Effectively predicting and eliminating such dental cement residues is crucial for preventing complications. This study focuses on creating a regression model using the pixel values to predict the Excess Cement Residues (ECR) by employing an octagonal surface imaging approach. A model featuring gingival imitation, ten abutments, and ten crowns was created, and the cemented implants underwent thorough photographic and analytical assessment. The ECR was determined through two distinct approaches: the Computerized Planimetric Method (CPM) and the weighing method. Across ten implants in this in vitro study, ECR varied from 0.3 to 21 mg, with an average of 5.69 mg. The findings reveal a higher amount of ECR on the distal, mesiobuccal, and mesial sides. Utilizing Pearson's correlation, a coefficient value of r = 0.786 signifies a strong correlation between CPM and the weighing method. The regression model further aids in predicting ECR based on pixel values. The octagonal surface imaging approach not only vividly captures information about ECR in the implant cementation region but also emphasizes the feasibility of ImageJ as an effective tool for detecting ECR. The congruence between CPM and the weighing method results supports the application of the regression model for precise ECR prediction.

A multiple linear regression analysis identifies factors associated with fear of cancer recurrence in postoperative patients with gastric cancer.

To investigate the risk factors of fear of cancer recurrence (FCR) in postoperative patients with gastric cancer (GC) and provide references for targeted nursing intervention development. A total of 84 patients who underwent GC surgery were included in this study. The fear of progression questionnaire-short form and social support rating scale were conducted, and multiple linear regression was performed to identify risk factors of FCR. The score of the fear of progression questionnaire-short form in patients with GC surgery was 39.1 ±â€…7.6. The results of multiple linear regression showed that age, education level, occupational status, course of the disease, Tumor node metastasis staging, and social support were the influencing factors of FCR in patients with GC (P < .05). The current situation of FCR in patients with GC surgery is not optimistic. The medical staff should pay more attention to patients with low age, low education level, unemployment, short course, high tumor node metastasis staging, low social support level, and other high-risk groups, and provide social support resources to reduce the level of FCR.

A population-based urinary and plasma metabolomics study of environmental exposure to cadmium.

BACKGROUND: The application of metabolomics-based profiles in environmental epidemiological studies is a promising approach to refine the process of health risk assessment. We aimed to identify potential metabolomics-based profiles in urine and plasma for the detection of relatively low-level cadmium (Cd) exposure in large population-based studies. METHOD: We analyzed 123 urinary metabolites and 94 plasma metabolites detected in fasting urine and plasma samples collected from 1,412 men and 2,022 women involved in the Tsuruoka Metabolomics Cohort Study. Regression analysis was performed for urinary N-acetyl-beta-D-glucosaminidase (NAG), plasma, and urinary metabolites as dependent variables, and urinary Cd (U-Cd, quartile) as an independent variable. The multivariable regression model included age, gender, systolic blood pressure, smoking, rice intake, BMI, glycated hemoglobin, low-density lipoprotein cholesterol, alcohol consumption, physical activity, educational history, dietary energy intake, urinary Na/K ratio, and uric acid. Pathway-network analysis was carried out to visualize the metabolite networks linked to Cd exposure. RESULT: Urinary NAG was positively associated with U-Cd, but not at lower concentrations (Q2). Among urinary metabolites in the total population, 45 metabolites showed associations with U-Cd in the unadjusted and adjusted models after adjusting for the multiplicity of comparison with FDR. There were 12 urinary metabolites which showed consistent associations between Cd exposure from Q2 to Q4. Among plasma metabolites, six cations and one anion were positively associated with U-Cd, whereas alanine, creatinine, and isoleucine were negatively associated with U-Cd. Our results were robust by statistical adjustment of various confounders. Pathway-network analysis revealed metabolites and upstream regulator changes associated with mitochondria (ACACB, UCP2, and metabolites related to the TCA cycle). CONCLUSION: These results suggested that U-Cd was associated with metabolites related to upstream mitochondrial dysfunction in a dose-dependent manner. Our data will help develop environmental Cd exposure profiles for human populations.

Differential network connectivity analysis for microbiome data adjusted for clinical covariates using jackknife pseudo-values.

BACKGROUND: A recent breakthrough in differential network (DN) analysis of microbiome data has been realized with the advent of next-generation sequencing technologies. The DN analysis disentangles the microbial co-abundance among taxa by comparing the network properties between two or more graphs under different biological conditions. However, the existing methods to the DN analysis for microbiome data do not adjust for other clinical differences between subjects. RESULTS: We propose a Statistical Approach via Pseudo-value Information and Estimation for Differential Network Analysis (SOHPIE-DNA) that incorporates additional covariates such as continuous age and categorical BMI. SOHPIE-DNA is a regression technique adopting jackknife pseudo-values that can be implemented readily for the analysis. We demonstrate through simulations that SOHPIE-DNA consistently reaches higher recall and F1-score, while maintaining similar precision and accuracy to existing methods (NetCoMi and MDiNE). Lastly, we apply SOHPIE-DNA on two real datasets from the American Gut Project and the Diet Exchange Study to showcase the utility. The analysis of the Diet Exchange Study is to showcase that SOHPIE-DNA can also be used to incorporate the temporal change of connectivity of taxa with the inclusion of additional covariates. As a result, our method has found taxa that are related to the prevention of intestinal inflammation and severity of fatigue in advanced metastatic cancer patients. CONCLUSION: SOHPIE-DNA is the first attempt of introducing the regression framework for the DN analysis in microbiome data. This enables the prediction of characteristics of a connectivity of a network with the presence of additional covariate information in the regression. The R package with a vignette of our methodology is available through the CRAN repository ( https://CRAN.R-project.org/package=SOHPIE ), named SOHPIE (pronounced as Sofie). The source code and user manual can be found at https://github.com/sjahnn/SOHPIE-DNA .

Effect of metformin on anti-mullerian hormone levels in women with polycystic ovarian syndrome: a systematic review and meta-regression analysis of randomized controlled trials with.

BACKGROUND: Several interventional studies have evaluated the potential anti-Mullerian hormone (AMH)-reduction effect of metformin. However, the results are still contradictory. In order to obtain a better viewpoint from them, this study aimed to comprehensively investigate the effects of metformin on AMH in the women with with polycystic ovarian syndrome (PCOS). METHODS: Scopus, PubMed/Medline, Web of Science, Cochrane, and Embase databases were searched using standard keywords to identify all controlled trials investigating the AMH levels following metformin administration. Pooled weighted mean difference and 95% confidence intervals were achieved by random-effects model analysis for the best estimation of outcomes. RESULTS: Sixteen studies with 484 participants' were included in this article. The pooled findings showed that AMH levels in the single arm clinical trials were significantly reduced (pooled WMD of -3.06 ng/ml; 95% confidence interval [CI] -4.03 to -2.10; P < 0.001) after use of metformin. Furthermore, compared to the control group, in randomized clinical trials, a reduced significant effect on AMH levels was observed following use of metformin (pooled WMD of -3.47 ng/ml; 95% CI -7.14 to -0.19; P = 0.047). Furthermore, higher reduction in the AMH levels with a metformin dosage ≤ 1500 mg/day and duration of treatment ≤ 12 weeks when compared to higher dosages and duration of intervention, observed in this meta-analysis. CONCLUSIONS: In conclusion, results this meta-analysis of clinical trials confirms the beneficial effect of the treatment with metformin in the reduction of the AMH levels in women.

Effects of physical and psychological symptoms on cancer-related fatigue among esophageal cancer patients.

BACKGROUND: Cancer-related fatigue (CRF) is considered one of the most prevalent and distressing symptoms among cancer patients and may vary among patients with different cancer types. However, few studies have explored the influence of physical and psychological symptoms on CRF among esophageal cancer (EC) patients without esophagectomy. Therefore, this study aimed to examine the effects of physical and psychological symptoms on CRF among EC patients without esophagectomy. METHODS: In the present study, a cross-sectional study was conducted from February 2021 to March 2022 in Liaoning Province, China. Among the 112 included participants, 97 completed our investigation. The questionnaires used consisted of the Brief Fatigue Inventory (BFI), the MD Anderson Symptom Inventory Gastrointestinal Cancer Module (MDASI-GI), the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder-7 (GAD-7), and demographic and clinical information. Multivariate linear regression was conducted to test the relationships between physical and psychological symptoms and CRF. RESULTS: Of the 97 EC patients, 60.8% reported CRF (BFI ≥ 4). The mean age of the participants was 64.92 years (SD = 8.67). According to the regression model, all the variables explained 74.5% of the variance in CRF. Regression analysis indicated that physical symptoms, including constipation, diarrhoea, and difficulty swallowing, contributed to CRF. On the other hand, depressive symptoms increased the level of CRF among EC patients without esophagectomy. CONCLUSIONS: Given the high prevalence of CRF among EC patients without esophagectomy, it is urgent to emphasize the importance of fatigue management interventions based on physical and psychological symptoms to alleviate CRF in EC patients.

Nursing-care for family caregivers of terminally ill cancer patients to enhance preparedness for death.

Family caregivers of terminally ill cancer patients prepare for a patient's death. Nursing-care for preparedness is effective for their psychological health. This study aims to structuralize nursing-care for preparedness and extract related factors while presenting the implications for improved quality of care. Data from a cross-sectional survey of general ward and palliative care unit nurses in designated cancer care hospitals (n=561) was analyzed with exploratory factor analysis and multiple regression analyses. The results of the analysis, the structure was classified into "Nurse-centered support" and "Support through inter-professional work." Both supports were practiced significantly more frequently in palliative care units than general wards. Related factors in general wards were; communication skills, cooperation with doctors, the existence of certified nurse/certified nurse specialists as consultants, attitudes toward care of the dying, frequency of death conferences, and cooperation with specialist cancer counselors. Therefore, the results can help improve the quality of family care in palliative care, especially in general wards.

Creation of a machine learning-based prognostic prediction model for various subtypes of laryngeal cancer.

Depending on the source of the blastophore, there are various subtypes of laryngeal cancer, each with a unique metastatic risk and prognosis. The forecasting of their prognosis is a pressing issue that needs to be resolved. This study comprised 5953 patients with glottic carcinoma and 4465 individuals with non-glottic type (supraglottic and subglottic). Five clinicopathological characteristics of glottic and non-glottic carcinoma were screened using univariate and multivariate regression for CoxPH (Cox proportional hazards); for other models, 10 (glottic) and 11 (non-glottic) clinicopathological characteristics were selected using least absolute shrinkage and selection operator (LASSO) regression analysis, respectively; the corresponding survival models were established; and the best model was evaluated. We discovered that RSF (Random survival forest) was a superior model for both glottic and non-glottic carcinoma, with a projected concordance index (C-index) of 0.687 for glottic and 0.657 for non-glottic, respectively. The integrated Brier score (IBS) of their 1-year, 3-year, and 5-year time points is, respectively, 0.116, 0.182, 0.195 (glottic), and 0.130, 0.215, 0.220 (non-glottic), demonstrating the model's effective correction. We represented significant variables in a Shapley Additive Explanations (SHAP) plot. The two models are then combined to predict the prognosis for two distinct individuals, which has some effectiveness in predicting prognosis. For our investigation, we established separate models for glottic carcinoma and non-glottic carcinoma that were most effective at predicting survival. RSF is used to evaluate both glottic and non-glottic cancer, and it has a considerable impact on patient prognosis and risk factor prediction.

The association between quality of life and diabetes: the Bushehr Elderly Health Program.

BACKGROUND AND OBJECTIVE: Considering the importance of diabetes and its increased prevalence with aging, this study aimed to evaluate the association between diabetes status and quality of life (QOL) and the determining factors in individuals over 60. METHODS: Two thousand three hundred seventy-five individuals including 819 (34.5%) with diabetes, aged 69.4 ± 6.4, from Bushehr Elderly Health Program (BEHP) were enrolled. We categorized the participants as non-diabetic, controlled diabetic, and poorly controlled diabetic. The QOL was assessed using the SF-12 questionnaire. The physical (PCS) and mental (MCS) component summaries of QOL were estimated. We compared the SF-12 domains and components between the categories using ANOVA. Further, the association of diabetes status with PCS and MCS was assessed after adjustment for possible confounders including age, sex, depression, cognitive impairment, physical activity, and other relevant factors using linear regression analysis. RESULTS: Individuals with diabetes had lower PCS (40.9 ± 8.8 vs. 42.7 ± 8.6, p-value < 0.001), and MCS scores (45.0 ± 10.2 vs. 46.4 ± 9.4, p-value < 0.001) compared to participants without diabetes. No significant differences were observed in PCS or MCS scores between controlled or poorly controlled individuals with diabetes. Diabetes status was associated with PCS and MCS scores in univariable analysis. Regarding physical component of QOL, after adjusting for other confounders, poorly controlled diabetes was significantly associated with PCS [beta: -1.27 (-2.02, -0.52)]; some other determinants include depression [-7.66 (-8.51, -6.80)], male sex [3.90 (3.24,4.57)], and good physical activity [1.87 (1.17,2.57)]. As for the mental component, controlled diabetes was significantly associated with MCS [-1.17 (-2.13, -0.22)]; other contributing factors include depression [-14.35 (-15.34, -13.37)], male sex [1.97 (1.20,2.73)], good physical activity [-1.55 (-2.35, -0.75)], and smoking [-1.42 (-2.24, -0.59)]. BMI had an inverse association with PCS [-0.19 (-0.26, -0.13)] and a direct association with MCS [0.14 (0.07,0.21)]. CONCLUSION: Individuals with diabetes exhibited reduced QOL scores. Upon adjusting for other variables, it was found that uncontrolled diabetes correlated with decreased PCS scores, whereas controlled diabetes was linked to lower MCS scores. Factors such as depression and being female were identified as contributors to diminished QOL in both physical and mental aspects. These results have the potential to guide healthcare decision-making, facilitating the creation of tailored interventions aimed at improving the QOL for individuals with diabetes, with a specific focus on women and depression.

Will coronal alignment postoperatively be deteriorating in adult spinal deformity after long-fusion surgery?

BACKGROUND: To investigate whether the coronal alignment (CA) will deteriorate, and identify the risk factors for coronal malalignment (CM) developing in adult spinal deformity (ASD) after long-fusion surgery. METHODS: A multi-center retrospective study was performed, which included a total of 161 ASD patients who had undergone the surgical procedure of long-fusion (≥ 5 vertebras) with instrumentations in three medical centers. All of the participants were retrospectively reviewed, and subsequently assigned into the consistency group (C7 plumb line (C7PL) shifting towards the convex side of the main curve), and the opposition group (C7PL shifting towards the concave side). CM was considered if the coronal balance distance (CBD) being over 30 mm. A Kaplan-Meier curve and log-rank test were used to analyze the differences in CM-free survival during follow-up. Multivariate analysis via a Cox proportional hazards test was used to analyze the risk factors. RESULTS: Patients showing CM equaled 35 (21.7%) at the pre-operation, and that increased significantly up to 51 (31.7%) at the final follow-up (P = 0.04). In the consistency group, the incidence of CM at the final follow-up was much higher than that preoperatively (35:16, P = 0.002). CM-free survival time decreased significantly in patients with larger CBD correction, pelvic fixation and more instrumented segments, respectively, during follow-up (P < 0.05, log-rank test). Age ≥ 60 years, the consistency CA, pelvic fixation, CBD-correction ≥ 30 mm and fixed-vertebra ≥ 8 were risk factors for CM happening after surgery using multivariate regression analysis (P < 0.05). CONCLUSIONS: The coronal alignments in ASD patients underwent long-fusion surgeries may deteriorate during follow-up, for which the risk factors include the consistency CA, age ≥ 60, fixed-vertebra ≥ 8, CBD-correction ≥ 30 mm and pelvic fixation.

Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements.

Based on the data of the State of Global Air (2020), air quality deterioration in Thailand has caused ~32,000 premature deaths, while the World Health Organization evaluated that air pollutants can decrease the life expectancy in the country by two years. PM2.5 was collected at three air quality observatory sites in Chiang-Mai, Bangkok, and Phuket, Thailand, from July 2020 to June 2021. The concentrations of 25 elements (Na, Mg, Al, Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Br, Sr, Ba, and Pb) were quantitatively characterised using energy-dispersive X-ray fluorescence spectrometry. Potential adverse health impacts of some element exposures from inhaling PM2.5 were estimated by employing the hazard quotient and excess lifetime cancer risk. Higher cancer risks were detected in PM2.5 samples collected at the sampling site in Bangkok, indicating that vehicle exhaust adversely impacts human health. Principal component analysis suggests that traffic emissions, crustal inputs coupled with maritime aerosols, and construction dust were the three main potential sources of PM2.5. Artificial neural networks underlined agricultural waste burning and relative humidity as two major factors controlling the air quality of Thailand.

Time trends in liver cancer mortality rates in Montenegro from 1990 to 2018.

OBJECTIVE: Liver cancer is the third most common cause of cancer-related deaths worldwide. Hepatitis B and C infections are the main factors affecting mortality. During recent years, Montenegro conducted activities on eradication of viral hepatitis according to the global strategy for the primary prevention of liver cancer mortality. The objective of this study was to assess the liver cancer mortality trend in Montenegro for the period of 1990-2018 using regression techniques. METHODS: liver cancer mortality data in Montenegro from 1990 to 2018 were collected. Mortality rates were age standardized to the World Standard Population. The joinpoint, linear and Poisson regressions were used to assess liver cancer mortality trends both overall and gender specific. RESULTS: The mortality trend was constant, with no significant increase or decrease in mortality rates both at the overall level and by gender. The number of cases, however, increases significantly at the overall level by an average of 1.4% per year [average annual percentage change (AAPC) (95% confidence interval, CI): 1.4 (0.5-2.3); P  = 0.004] and in women by 1.9% per year [AAPC (95% CI): 1.9 (0.8-3.1); P  = 0.002]. In men, there was no change in the number of cases. The three age groups most burdened by mortality from liver cancer were 65-74 (34.9%), 75-84 (26.6%) and 55-64 (25.8%). CONCLUSION: The consistent implementation of prevention measures and hepatitis virus infection treatment has played a role in partially favorable liver cancer mortality trends in Montenegro. It is crucial to closely monitor guidelines for this cancer and give particular attention to the elderly population as the most affected.