PeerJ最新文献

Background: Vicks VapoRub (VVR) is a globally popular over-the-counter remedy marketed for use as a topical antitussive and analgesic. This review seeks to provide health professionals and care providers with a thorough summary of the benefits and complications associated with VVR use reported in the medical literature, identify off-label consumer behaviors that might increase the risk of health complications, and encourage further research into over-the-counter (OTC) medications.

Methods: Three databases-PubMed, Web of Science, and Embase-aided in creating a pool of 220 studies. For inclusion, studies had to discuss the therapeutic application of VVR in humans or a complication arising from its use.

Findings: Thirty-seven articles were found to meet inclusion criteria. Nine synthesis groups were created: three groups concern the product's efficacy in regard to upper respiratory tract infection (URTI) symptom treatment (n = 7), onychomycosis treatment (n = 2), and in the context of wound care (n = 2). Six groups collate case reports that describe VVR-related complications, including VVR-associated lipid pneumonia (n = 11), ocular injury (n = 5), camphor toxicity (n = 5), dermatological conditions (n = 3), psychosis (n = 1), and respiratory distress (n = 1). The evidence around the use of VVR for the treatment of URTI symptoms and onychomycosis is limited and inconclusive. Even more limited cross-sectional data concerns its use in wound care. Many of the complications described in our study (e.g., multi-organ failure, ocular evisceration, severe pneumonia) involve product misuse. This review was designed to help guide patients on the safe and appropriate use of VVR (e.g., advising patients to avoid heating, ingesting, or intranasal/intrabuccal/ocular application of the product). In general, the severity of complications associated with misuse of VVR highlights the importance of complementary and alternative medicine disclosure and discussion.

Background: Because of illegal logging, habitat fragmentation, and high value timber Andean montane forest Cedrela species (such as Cedrela angustifolia), is endangered in Central and South America. Studying the effects of climate change and tree cover loss on the distribution of C. angustifolia will help us to understand the climatic and ecological sensitivity of this species and suggest conservation and restoration strategies.

Methods: Using ecological niche modeling with two algorithms (maximum entropy (MaxEnt) and Random Forest) under the ecological niche conservatism approach, we generated 16,920 models with different combinations of variables and parameters. We identified suitable areas for C. angustifolia trees under present and future climate scenarios (2040, 2070, and 2100 with SSP 3-7.0 and SSP 5-8.5), tree cover loss, and variables linked to soil and topography.

Results: Our results demonstrated 10 environmental variables with high percentage contributions and permutation importance; for example, precipitation seasonality exhibited the highest contribution to the current and future distribution of Cedrela angustifolia. The potential present distribution was estimated as 13,080 km²with tree cover loss and 16,148.5 km²without tree cover loss. From 2040 to 2100 the species distribution will decrease (from 22.16% to 36.88% with tree cover loss variation). The results indicated that Bolivia displayed higher habitat suitability than Ecuador, Peru, and Argentina. Finally, we recommend developing conservation management strategies that consider both protected and unprotected areas as well as the impact of land-use changes to improve the persistence of C. angustifolia in the future.

Background: Nicotinamide (NAM) metabolism fulfills crucial functions in tumor progression. The present study aims to establish a NAM metabolism-correlated gene (NMRG) signature to assess the immunotherapy response and prognosis of lung adenocarcinoma (LUAD).

Methods: The training set and validation set (the GSE31210 dataset) were collected The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. Molecular subtypes of LUAD were classified by consensus clustering. Mutation landscape of the top 20 somatic genes was visualized by maftools package. Subsequently, differential expression analysis was conducted using the limma package, and univariate, multivariate and LASSO regression analyses were performed on the screened genes to construct a risk model for LUAD. Next, the MCP-counter, TIMER and ESTIMATE algorithms were utilized to comprehensively assess the immune microenvironmental profile of LUAD patients in different risk groups. The efficacy of immunotherapy and chemotherapy drugs was evaluated by TIDE score and pRRophetic package. A nomogram was created by integrating RiskScore and clinical features. The mRNA expressions of independent prognostic NMRGs and the migration and invasion of LUAD cells were measured by carrying out cellular assays.

Results: Two subtypes (C1 and C2) of LUAD were classified, with C1 subtype showing a worse prognosis than C2. The top three genes with a high mutation frequency in C1 and C2 subtypes were TTN (45.25%), FLG (25.25%), and ZNF536 (19.8%). Four independent prognostic NMRGs (GJB3, CPA3, DKK1, KRT6A) were screened and used to construct a RiskScore model, which exhibited a strong predictive performance. High-risk group showed low immune cell infiltration, high TIDE score, and worse prognosis, and the patients in this group exhibited a high drug sensitivity to Cisplatin, Erlotinib, Paclitaxel, Saracatini, and CGP_082996. A nomogram was established with an accurate predictive and diagnostic performance. GJB3, DKK1, CPA3, and KRT6A were all high- expressed in LUAD cells, and silencing GJB3 inhibited the migration and invasion of LUAD cells.

Conclusion: A novel NMRG signature was developed, contributing to the prognostic evaluation and personalized treatment for LUAD patients.

Objective: Multidrug-resistant tuberculosis (MDR-TB) is a global health threat. Our study aimed to develop and externally validate a nomogram to estimate the probability of MDR-TB in patients with TB.

Methods: A total of 453 patients with TB in Anhui Chest Hospital between January 2019 and December 2020 were included in the training cohort. In addition, 116 patients with TB from Anhui Provincial Hospital Infection District between January 2015 and November 2023 were included in the validation cohort. Multivariable logistic regression analysis was applied to build a predictive model by combining the feature selected in the least absolute shrinkage and selection operator regression model. The C-index, calibration plot, and decision curve analysis were implemented to evaluate the predictive model's discrimination, calibration, and clinical practicality. Then, logistic regression and least absolute shrinkage and selection operator (LASSO) models were constructed using R software, and the accuracy, goodness of fit, and stability of the models were verified using the validation cohort.

Results: Eight variables of patients with TB were selected using the best penalization parameter of the LASSO regression method, and the nomogram was established. The model displayed good discrimination with a C-index of 0.752 and good calibration. A high C-index value of 0.825 could still be reached in the validation cohort. The decision curve analysis demonstrated the clinical value of the model.

Conclusion: In this study, we constructed the LASSO regression model based on eight clinical traits and outcomes of laboratory tests, providing a novel insight for evaluating MDR-TB.

Drought is one of the most environmental stressors, significantly affecting wheat production, particularly in the face of accelerating climate change. Therefore, developing drought-resistant, high-yielding wheat varieties is essential to ensure sustainable production and maintain global food security as the world population rapidly grows. This study aimed to evaluate the genetic variation of local and imported bread wheat genotypes through simple sequence repeat (SSR) markers and assess their combining ability to identify top-performing genotypes under both normal and drought-stress environments. SSR markers revealed significant genetic diversity among the parental genotypes, which were utilized to develop 28 F1 crosses utilizing diallel mating design. Field trials under well-watered and drought-stressed environments demonstrated that drought significantly reduced all measured agronomic traits. The genotypes were categorized into five clusters based on their drought tolerance, ranging from highly sensitive (group-E) to robustly drought-resistant (group-A). The local variety Sids-12 (P2) was identified as an excellent combiner for breeding shorter and early-maturing cultivars and Line-117 (P3), Line-144 (P4), and Line-123 (P5) for improving grain yield and related traits under drought conditions. The crosses P1×P5, P3×P8, P4×P5, and P6×P7 possessed superior performance under both conditions. Key traits, including plant height, grains per spike, 1,000-grain weight, and spikes per plant, displayed strong correlations with grain yield, providing an effective approach for indirect selection in drought-prone environments.

Background: Previous research has shown a correlation between high visceral fat levels and hyperuricemia incidence. The Chinese Visceral Adiposity Index (CVAI) assessed visceral fat status in the Chinese population. Our study investigates the correlation between CVAI and asymptomatic hyperuricemia in type 2 diabetes patients.

Methods: This cross-sectional study analyzed 1,588 hospitalized type 2 diabetes patients to investigate the association between CVAI and hyperuricemia. CVAI was included in the logistic regression analysis as both a continuous and categorical variable, and restricted cubic splines were used to assess the dose-response relationship. Additionally, subgroup analyses were performed to investigate potential interactions among variables. The predictive capability of CVAI was assessed using the receiver operating characteristic (ROC) curve based on the basic model.

Results: The CVAI quartile group analysis revealed a higher prevalence of hyperuricemia with increasing CVAI levels. CVAI is significantly associated with hyperuricemia, as identified through multifactorial logistic regression analysis. After adjusting for all covariates, the odds ratios for CVAI in the second, third, and fourth quartiles were significantly higher than in the lowest quartile, with values of 2.688 (95% CI [1.301-5.554], p = 0.008), 2.752 (95% CI [1.320-5.739], p = 0.007), and 4.990 (95% CI [2.392-10.409], p < 0.001), respectively. No significant interactions were observed in the subgroup analysis. Incorporating CVAI into the basic model increased the ROC curve's area under the curve to 0.714.

Conclusion: This study found a positive correlation between CVAI and hyperuricemia incidence in type 2 diabetes patients. Consequently, CVAI may reliably indicate hyperuricemia in this patient population.

Background: Sepsis is a life-threatening disease causing millions of deaths every year. It has been reported that programmed cell death (PCD) plays a critical role in the development and progression of sepsis, which has the potential to be a diagnosis and prognosis indicator for patient with sepsis.

Methods: Fourteen PCD patterns were analyzed for model construction. Seven transcriptome datasets and a single cell sequencing dataset were collected from the Gene Expression Omnibus database.

Results: A total of 289 PCD-related differentially expressed genes were identified between sepsis patients and healthy individuals. The machine learning algorithm screened three PCD-related genes, NLRC4, TXN and S100A9, as potential biomarkers for sepsis. The area under curve of the diagnostic model reached 100.0% in the training set and 100.0%, 99.9%, 98.9%, 99.5% and 98.6% in five validation sets. Furthermore, we verified the diagnostic genes in sepsis patients from our center via qPCR experiment. Single cell sequencing analysis revealed that NLRC4, TXN and S100A9 were mainly expressed on myeloid/monocytes and dendritic cells. Immune infiltration analysis revealed that multiple immune cells involved in the development of sepsis. Correlation and gene set enrichment analysis (GSEA) analysis revealed that the three biomarkers were significantly associated with immune cells infiltration.

Conclusions: We developed and validated a diagnostic model for sepsis based on three PCD-related genes. Our study might provide potential peripheral blood diagnostic candidate biomarkers for patients with sepsis.

Background: Exposure to fine particulate matter (PM2.5) is known to increase oxidative stress, impacting health adversely. This study examines the relationship between PM2.5 exposure and oxidative stress biomarkers in Chiang Mai, Thailand.

Methods: A pilot prospective observational study was conducted in Samoeng District, Chiang Mai, including 25 healthy participants (age 25-60 years). Urine samples were collected during high (March-April 2023) and low (May-July 2023) PM2.5 seasons. PM2.5 concentrations were monitored daily from the Northern Thailand Air Quality Health Index (NTAQHI) system. Biomarkers analyzed included 1-hydroxypyrene (1-OHP) using high-performance liquid chromatography (HPLC), malondialdehyde (MDA) via Spectrophotometry, and 8-epi-prostaglandin F2α (8-epi-PGF2α) with Enzyme-linked Immunosorbent Assay (ELISA). Statistical analysis was performed using IBM SPSS Statistics 22.0.

Results: Significant increases in urinary 1-OHP, MDA, and 8-epi-PGF2α were observed during the high PM2.5 season compared to the low season. The mean concentration of PM2.5 was 67 µg/m³ during high pollution and 7 µg/m³ during low pollution. Elevated levels of these biomarkers indicate increased oxidative stress associated with higher PM2.5 exposure.

Conclusions: This study highlights a significant association between elevated PM2.5 levels and increased oxidative stress biomarkers in Chiang Mai, Thailand. The findings suggest that exposure to higher concentrations of PM2.5 contributes to oxidative stress, potentially leading to adverse health outcomes.