Diagnostic value of 18F-PSMA-1007 PET/CT for predicting the pathological grade of prostate cancer

This study was designed to evaluate the diagnostic efficacy of relevant parameters of 18F-prostate-specific membrane antigen (PSMA)-1007 PET/CT in predicting the pathological grade of primary prostate cancer. Briefly, a prospective analysis was performed on 53 patients diagnosed with prostate cancer by systematic puncture biopsy, followed by 18F-PSMA-1007 PET/CT examination prior to treatment within 10 d. The patients were grouped in accordance with the Gleason grading system revised by the International Association of Urology Pathology (ISUP). They were divided into high-grade group (ISUP 4-5 group) and low-grade group (ISUP 1-3 group). The differences in maximum standardized uptake value (SUVmax), tumor-to-background ratio (TBR), intraprostatic PSMA-derived tumor volume (iPSMA-TV), and intraprostatic total lesion PSMA (iTL-PSMA) between the high- and low-grade group were statistically significant (p < .001). No significant difference was found for mean standardized uptake value (SUVmean) between the high- and low-grade groups (Z =  -1.131, p = .258). Besides, binary multivariate logistic regression analysis showed that only iPSMA-TV and iTL-PSMA were independent predictors of the pathological grading, for which the odds ratios were 18.821 [95% confidence interval (CI): 2.040-173.614, p = .010] and 0.758 (95% CI: 0.613-0.938, p = .011), respectively. The area under the ROC of this regression model was 0.983 (95% CI: 0.958-1.00, p < .001). Only iTL-PSMA was a significant parameter for distinguishing ISUP-4 and ISUP-5 groups (Z =  -2.043, p = .041). In a nutshell, 18F-PSMA-1007 PET/CT has good application value in predicting the histopathological grade of primary prostate cancer. Three-dimensional volume metabolism parameters iPSMA-TV and iTL-PSMA were found to be independent predictors for pathological grade.

Severe and continuous immunoparesis during induction or maintenance therapy in nontransplant patients with multiple myeloma is a sign of poor prognosis

OBJECTIVE

Multiple myeloma (MM) varies in clinical behavior, response to treatment and prognosis due to the heterogeneity of the disease. Data on the association between the immunoparesis status during treatment and prognosis in nontransplant MM patients are limited.

METHODS

In a retrospective analysis of 142 patients with MM, we examined the relationship between immunoparesis status and prognosis during treatment. All patients received novel agent-based therapy and did not undergo autologous stem cell transplantation. One, two, or three uninvolved immunoglobulins (Igs) below the lowest thresholds of normalcy were used to identify immunoparesis.

RESULTS

Patients with a greater degree of immunoparesis during treatment had shorter progression-free survival (PFS) and overall survival (OS). A total of 46.5% of the patients had severe and continuous immunoparesis (at least two uninvolved Igs suppressed continuously during treatment), representing a worse prognosis than those with complete or partial normalization of Igs during treatment. Among patients who achieved at least complete remission, PFS was poor in patients with severe and continuous immunoparesis. Furthermore, severe and continuous immunoparesis during treatment was a poor prognostic factor for PFS and OS according to multivariate analyses.

CONCLUSION

The degree of immunoparesis during treatment is a follow-up indicator for survival in nontransplant myeloma patients, and severe and continuous immunoparesis in nontransplant myeloma patients might be a sign of poor prognosis.

Longitudinal non-targeted metabolomic profiling of urine samples for monitoring of kidney transplantation patients

The assessment of kidney function within the first year following transplantation is crucial for predicting long-term graft survival. This study aimed to develop a robust and accurate model using metabolite profiles to predict early long-term outcomes in patient groups at the highest risk of early graft loss. A group of 61 kidney transplant recipients underwent thorough monitoring during a one-year follow-up period, which included a one-week hospital stay and follow-up assessments at three and six months. Based on their 12-month follow-up serum creatinine levels: Group 2 had levels exceeding 1.5 mg/dl, while Group 1 had levels below 1.5 mg/dl. Metabolites were detected by mass spectrometer and first pre-processed. Univariate and multivariate statistical analyses were employed to identify significant differences between the two groups. Nineteen metabolites were found to differ significantly in the 1st week, and seventeen metabolites in the 3rd month (adjusted p-value < 0.05, quality control (QC) < 30, a fold change (FC) > 1.1 or a FC < 0.91, Variable Influence on Projection (VIP) > 1). However, no significant differences were observed in the 6th month. These distinctive metabolites mainly belonged to lipid, fatty acid, and amino acid categories. Ten models were constructed using a backward conditional approach, with the best performance seen in model 5 for Group 2 at the 1st-week mark (AUC 0.900) and model 3 at the 3rd-month mark (AUC 0.924). In conclusion, the models developed in the early stages may offer potential benefits in the management of kidney transplant patients.

Identification of provenance of Basmati rice grown in different regions of Punjab through multivariate analysis

High-priced Basmati rice is vulnerable to deliberate mislabeling to increase profits. This type of fraud may lower consumers' confidence as inferior products can affect brand reputation. To address this problem, there is a need to devise a method that can efficiently distinguish Basmati rice grown in regions that are famous versus the regions that are not suitable for their production. Therefore, in this investigation, thirty-six samples of Basmati rice were collected from two zones of Punjab province (one known for Basmati rice) of Pakistan which is the major producer of Basmati rice. The elemental composition of rice samples was assessed using inductively coupled plasma-optical emission spectrometry and an organic elemental analyzer, whereas data on δ13C was acquired using isotopic ratio-mass spectrometry. Regional clustering of samples based on their respective cultivation zones was observed using multivariate data analysis techniques. Partial least squares-discriminant analysis was found to be effective in grouping rice samples from the different locations and identifying unknown samples belonging to these two regions. Further recommendations are presented to develop a better model for tracing the origin of unidentified rice samples.

Rapid and green discrimination of bovine milk according to fat content, thermal treatment, brand and manufacturer via colloidal fingerprinting

Addressing food safety and detecting food fraud while fulfilling greenness requisites for analysis is a challenging but necessary task. The use of sustainable techniques, with limited pretreatment, non-toxic chemicals, high throughput results, is recommended. A combination of Field Flow Fractionation (FFF), working in saline carrier and with minimal preprocessing, and chemometrics was for the first time applied to bovine milk grouping. A set of 47 bovine milk samples was analyzed: a single analysis yielded a characteristic multidimensional colloidal dataset, that once processed with multivariate tools allowed simultaneously for different discriminations: fat content, thermal treatment, brand and manufacturing plant. The analytical methodology is fast, green, simple, and inexpensive and could offer great help in the field of quality control and frauds identification. This work represents also the first attempt to identify milk sub-typologies based on colloidal profiles, and the most complete study concerning multivariate analysis of FFF fingerprint.

Therapeutic implications of dapagliflozin on the metabolomics profile of diabetic rats: A GC-MS investigation coupled with multivariate analysis

BACKGROUND

Diabetes mellitus is a complex metabolic disorder with systemic implications, necessitating the search for reliable biomarkers and therapeutic strategies. This study investigates the metabolomics profile alterations in diabetic rats, with a focus on the therapeutic effects of Dapagliflozin, a drug known to inhibit renal glucose reabsorption, using Gas Chromatography-Mass Spectrometry analysis.

METHODS

A GC-MS based metabolomics approach combined with multivariate and univariate statistical analyses was utilized to study serum samples from a diabetic model of Wistar rats, treated with dapagliflozin. Metabolomics pathways analysis was also performed to identify the altered metabolic pathways associated with the disease and the intervention.

RESULTS

Dapagliflozin treatment in diabetic rats resulted in normalized levels of metabolites associated with insulin resistance, notably branched-chain and aromatic amino acids. Improvements in glycine metabolism were observed, suggesting a modulatory role of the drug. Additionally, reduced palmitic acid levels indicated an alleviation of lipotoxic effects. The metabolic changes indicate a restorative effect of dapagliflozin on diabetes-induced metabolic perturbations.

CONCLUSIONS

The comprehensive metabolomics analysis demonstrated the potential of GC-MS in revealing significant metabolic pathway alterations due to dapagliflozin treatment in diabetic model rats. The therapy induced normalization of key metabolic disturbances, providing insights that could advance personalized diabetes mellitus management and therapeutic monitoring, highlighting the utility of metabolomics in understanding drug mechanisms and effects.

Classification of asbestos and their nonasbestiform analogues using FTIR and multivariate data analysis

This study presents a possible application of Fourier transform infrared (FTIR) spectrometry and multivariate data analysis, principal component analysis (PCA), and partial least squares-discriminant analysis (PLS-DA) for classifying asbestos and their nonasbestiform analogues. The objectives of the study are: 1) to classify six regulated asbestos types and 2) to classify between asbestos types and their nonasbestiform analogues. The respirable fraction of six regulated asbestos types and their nonasbestiform analogues were prepared in potassium bromide pellets and collected on polyvinyl chloride membrane filters for FTIR measurement. Both PCA and PLS-DA classified asbestos types and their nonasbestiform analogues on the score plots showed a very distinct clustering of samples between the serpentine (chrysotile) and amphibole groups. The PLS-DA model provided ∼95% correct prediction with a single asbestos type in the sample, although it did not provide all correct predictions for all the challenge samples due to their inherent complexity and the limited sample number. Further studies are necessary for a better prediction level in real samples and standardization of sampling and analysis procedures.

Impact of travel distance on receipt of indicated adjuvant therapy in resected non-small cell lung cancer

OBJECTIVE

We have previously demonstrated the negative impact of travel distance on adherence to surveillance imaging guidelines for resected non-small cell lung cancer (NSCLC). The influence of patient residential location on adherence to recommended postoperative treatment plans remains unclear. We sought to characterize the impact of travel distance on receipt of indicated adjuvant therapy in resected NSCLC.

METHODS

We performed a single-institution, retrospective review of patients with stage II-III NSCLC who underwent upfront pulmonary resection, 2012-2016. Clinicopathologic and operative/perioperative details of treatment were collected. Travel distance was measured from patients' homes to the operative hospital. Our primary outcome was receipt of adjuvant systemic or radiotherapy. Travel distance was stratified as <100 or >100 miles. Multivariable logistic regression was performed.

RESULTS

In total, 391 patients met inclusion criteria, with mean age of 65.9 years and fairly even sex distribution (182 women, 49.2%). Most patients were Non-Hispanic White (n = 309, 83.5%), and most frequent clinical stage was II (n = 254, 64.9%). Indicated adjuvant therapy was received by 266 (71.9%), and median distance traveled was 209 miles (interquartile range, 50.7-617). Multivariate analysis revealed that longer travel distance was inversely associated with receipt of indicated adjuvant therapy (odds ratio, 0.13; 95% confidence interval, 0.06-0.26; P < .001). In addition, Black patients were less likely to receive appropriate treatment (odds ratio, 0.05; 95% confidence interval, 0.02-0.15; P < .001).

CONCLUSIONS

Travel distance >100 miles negatively impacts the likelihood of receiving indicated adjuvant therapy in NSCLC. Indications for systemic therapy in earlier staged disease are rapidly expanding, and these findings bear heightened relevance as we aim to provide equitable access to all patients.

Mixtures of t $$ t $$ factor analysers with censored responses and external covariates: An application to educational data from Peru

Analysing data from educational tests allows governments to make decisions for improving the quality of life of individuals in a society. One of the key responsibilities of statisticians is to develop models that provide decision-makers with pertinent information about the latent process that educational tests seek to represent. Mixtures oft $$ t $$ factor analysers (MtFA) have emerged as a powerful device for model-based clustering and classification of high-dimensional data containing one or several groups of observations with fatter tails or anomalous outliers. This paper considers an extension of MtFA for robust clustering of censored data, referred to as the MtFAC model, by incorporating external covariates. The enhanced flexibility of including covariates in MtFAC enables cluster-specific multivariate regression analysis of dependent variables with censored responses arising from upper and/or lower detection limits of experimental equipment. An alternating expectation conditional maximization (AECM) algorithm is developed for maximum likelihood estimation of the proposed model. Two simulation experiments are conducted to examine the effectiveness of the techniques presented. Furthermore, the proposed methodology is applied to Peruvian data from the 2007 Early Grade Reading Assessment, and the results obtained from the analysis provide new insights regarding the reading skills of Peruvian students.

Long-term skeletodental changes with early and late treatment using modified C-palatal plates in hyperdivergent Class II adolescents

OBJECTIVES

To compare skeletodental changes between early and late treatment groups using modified C-palatal plates (MCPP) and long-term retention outcomes in hyperdivergent Class II adolescents.

MATERIALS AND METHODS

Seventy-one hyperdivergent Class II patients were divided into four groups according to treatment modality and treatment timing: group 1, early treatment with MCPP (n = 16; 9.9 ± 0.9 years); group 2, late treatment with MCPP (n = 19; 12.3 ± 0.8 years); group 3, early treatment with headgear (HG; n = 18; 9.6 ± 0.8 years); and group 4, late treatment with HG (n = 18; 12.1 ± 1.2 years). Lateral cephalograms were taken and skeletal and dental variables were measured. For statistical analysis, paired t-tests, independent t-tests, and multiple regression were performed.

RESULTS

The early MCPP group showed a more significant decrease in mandibular plane angle than the late MCPP group did, and vertical control was more efficient in the early group than in the late group. In the MCPP groups, both FMA and SN-GoGn were increased with late treatment but decreased with early treatment, and the difference was statistically significant (P < .01). The early-treatment MCPP group had a significant decrease in SN-GoGn of 0.6° compared with an increase of 1.7° in the early treatment HG group (P < .01). Posttreatment stability of both the early and late MCPP groups was maintained in long-term retention.

CONCLUSIONS

Early MCPP showed more significant vertical control than late MCPP. However, there was no difference in long-term stability between early and late groups.

Post-operative complications affect survival in surgically treated metastatic spinal cord compression

PURPOSE

The prevalence of metastatic epidural spinal cord compression (MESCC) is increasing globally due to advancements in cancer diagnosis and treatment. Whilst surgery can benefit specific patients, the complication rate can reach up to 34%, with limited reporting on their impact in the literature. This study aims to analyse the influence of major complications on the survival of surgically treated MESCC patients.

METHODS

Consecutive MESCC patients undergoing surgery and meeting inclusion criteria were selected. Survival duration from decompressive surgery to death was recorded. Perioperative factors influencing survival were documented and analysed. Kaplan-Meier survival analysis at one year compared these factors. Univariate and multivariate Cox proportional hazard regression analyses were performed. Additionally, univariate analysis compared complicated and uncomplicated groups.

RESULTS

Seventy-five patients were analysed. Median survival for this cohort was 229 days (95% CI 174-365). Surgical complications, low patient performance, and rapid primary tumour growth were significant perioperative variables for survival in multivariate analyses (p < 0.001, p = 0.003, and p = 0.02, respectively) with a hazard ratio of 3.2, 3.6, and 2.1, respectively. Univariate analysis showed no variables associated with complication occurrence.

CONCLUSION

In this cohort, major surgical complications, patient performance, and primary tumour growth rate were found to be independent factors affecting one year survival. Thus, prioritizing complication prevention and appropriate patient selection is crucial for optimizing survival in this population.

GOLPH3 promotes tumor malignancy via inhibition of ferroptosis by upregulating SLC7A11 in cholangiocarcinoma

Golgi phosphoprotein 3 (GOLPH3) has been reported as an oncogene in various tumors; however, the role and function of GOLPH3 and its relevant molecular mechanism in cholangiocarcinoma (CCA) are unclear. Herein, GOLPH3 expression in CCA tissues was observed to be significantly higher than that in paired adjacent noncancerous tissues. Clinicopathological analysis showed that GOLPH3 expression correlated positively with the tumor-node-metastasis stage. In addition, GOLPH3 expression correlated inversely with the overall survival of patients with CCA. Multivariate analysis showed that GOLPH3 was an independent prognostic factor for patients with CCA. Transcriptome analysis (RNA sequencing) of GOLPH3 knockdown cells showed that the expression levels of nine ferroptosis-related genes were significantly changed, indicating the important biological function of GOLPH3 in ferroptosis in CCA cells. Furthermore, GOLPH3 knockdown could significantly promote Erastin-induced ferroptosis in vitro and suppress tumor growth in vivo. Overexpression of GOLPH3 had the opposite effect on this phenotype. Further studies revealed that GOLPH3 knockdown was significantly associated with a decrease in cysteine content, an accumulation of the lipid peroxidation product malondialdehyde, an increase in reactive oxygen species, and sensitized CCA cells to Erastin-induced ferroptosis. Moreover, changes in GOLPH3 expression were found to be consistent with the expression of light chain subunit solute carrier family 7 member 11 (SLC7A11). Thus, our study suggested that GOLPH3 functions as an oncoprotein in CCA and may suppress ferroptosis by facilitating SLC7A11 expression, suggesting that GOLPH3 could serve as a therapeutic target for CCA treatment.

Relationship between night work and health-related quality of life: an analysis based on profiles and cumulative duration of exposure to night work among French workers in the CONSTANCES cohort

OBJECTIVE

The aim of this study is to estimate the association between night work and health-related quality of life (HRQoL) among French workers. The association between cumulative duration of night work and HRQoL was also investigated.

METHODS

Three career-long night work exposure groups were defined at inclusion in the CONSTANCES cohort: permanent night workers, rotating night workers and former night workers. Day workers with no experience of night work were the reference group. HRQoL was assessed using the Short Form Health Survey (SF-12), in particular the physical component summary (PCS) and mental component summary (MCS) scores, with a higher score indicating better HRQoL. Several linear regression models were built to test the association between night work exposure and HRQoL. The relationship between cumulative duration of night work and HRQoL scores was analyzed using generalised additive models.

RESULTS

The sample consisted of 10,372 participants. Former night workers had a significantly lower PCS score than day workers (β [95% CI]: - 1.09 [- 1.73; - 0.45], p = 0.001), whereas permanent night workers had a significantly higher MCS score (β [95% CI]: 1.19 [0.009; 2.36], p = 0.048). A significant decrease in PCS score from 5 to 20 years of cumulative night work was observed among former night workers.

CONCLUSIONS

Former night workers had poorer physical HRQoL in contrast to permanent and rotating night workers who had similar or even better HRQoL than day workers, suggesting the well-known healthy worker survivor effect. Consequently, both current and former night workers require regular and specific follow-up focused on the physical components of their health.

Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets

Machine vision systems have emerged for quality assessment of solid dosage forms in the pharmaceutical industry. These can offer a versatile tool for continuous manufacturing while supporting the framework of process analytical technology, quality-by-design, and real-time release testing. The aim of this work is to develop a digital UV/VIS imaging-based system for predicting the in vitro dissolution of meloxicam-containing tablets. The alteration of the dissolution profiles of the samples required different levels of the critical process parameters, including compression force, particle size and content of the API. These process parameters were predicted non-destructively by multivariate analysis of UV/VIS images taken from the tablets. The dissolution profile prediction was also executed using solely the image data and applying artificial neural networks. The prediction error (RMSE) of the dissolution profile points was less than 5%. The alteration of the API content directly affected the maximum concentrations observed at the end of the dissolution tests. This parameter was predicted with a relative error of less than 10% by PLS models that are based on the color components of UV and VIS images. In conclusion, this paper presents a modern, non-destructive PAT solution for real-time testing of the dissolution of tablets.

Low surgical weight associated with ETV failure in pediatric hydrocephalus patients

The use of endoscopic third ventriculostomy (ETV) for treatment of pediatric hydrocephalus has higher failure rates in younger patients. Here we investigate the impact of select perioperative variables, specifically gestational age, chronological age, birth weight, and surgical weight, on ETV failure rates. A retrospective review was performed on patients treated with ETV - with or without choroid plexus cauterization (CPC) - from 2010 to 2021 at a large academic center. Analyses included Cox regression for independent predictors and Kaplan-Meier survival curves for time to-event outcomes. In total, 47 patients were treated with ETV; of these, 31 received adjunctive CPC. Overall, 66% of the cohort experienced ETV failure with a median failure of 36 days postoperatively. Patients aged < 6 months at time of surgery experienced 80% failure rate, and those > 6 months at time of surgery experienced a 41% failure rate. Univariate Cox regression analysis showed weight at the time of ETV surgery was significantly inversely associated with ETV failure with a hazard ratio of 0.92 (95% CI 0.82, 0.99). Multivariate analysis redemonstrated the inverse association of weight at time of surgery with ETV failure with hazard ratio of 0.76 (95% CI 0.60, 0.92), and sensitivity analysis showed < 4.9 kg as the optimal cutoff predicting ETV/CPC failure. Neither chronologic age nor gestational age were found to be significantly associated with ETV failure.In this study, younger patients experienced higher ETV failure rates, but multivariate regression found that weight was a more robust predictor of ETV failure than chronologic age or gestational age, with an optimal cutoff of 4.9 kg in our small cohort. Given the limited sample size, further study is needed to elucidate the independent role of weight as a peri-operative variable in determining ETV candidacy in young infants. Previous presentations: Poster Presentation, Congress of Neurological Surgeons.

Sociodemographic and clinical characteristics of people with ostomy and the adaptive domains of Roy's theory: A cross-sectional study

INTRODUCTION

The adaptation of people with ostomies may be associated with and affected by sociodemographic and clinical factors. The present study aimed to investigate the association between the sociodemographic and clinical characteristics and the adaptation of people with an intestinal stoma.

METHOD

An analytical study, carried out through an interview with 200 patients with ostomy for five months. For that, it was applied to scale for the level of adaptation of ostomy patients to measure the physiological domains, self-concept, role function and interdependence and a questionnaire was used in which sociodemographic and clinical information. Descriptive and multivariate analyses were performed to test the study hypothesis.

RESULTS

The study pointed out statistically significant associations with male sex, age group below 60, low education level, Stoma time less than one year, below one minimum wage, temporary permanence criteria and presence of complications relation to low scores of adaptation.

CONCLUSIONS

The association of sociodemographic and clinical factors with the measured adaptive modes provides important information for the planning of nursing care and other care providers, since it directs actions to the aspects that give greater adaptive difficulty to people with stomas and which are the focus of care nursing to this clientele.

Beyond visual integration: sensitivity of the temporal-parietal junction for objects, places, and faces

One important role of the TPJ is the contribution to perception of the global gist in hierarchically organized stimuli where individual elements create a global visual percept. However, the link between clinical findings in simultanagnosia and neuroimaging in healthy subjects is missing for real-world global stimuli, like visual scenes. It is well-known that hierarchical, global stimuli activate TPJ regions and that simultanagnosia patients show deficits during the recognition of hierarchical stimuli and real-world visual scenes. However, the role of the TPJ in real-world scene processing is entirely unexplored. In the present study, we first localized TPJ regions significantly responding to the global gist of hierarchical stimuli and then investigated the responses to visual scenes, as well as single objects and faces as control stimuli. All three stimulus classes evoked significantly positive univariate responses in the previously localized TPJ regions. In a multivariate analysis, we were able to demonstrate that voxel patterns of the TPJ were classified significantly above chance level for all three stimulus classes. These results demonstrate a significant involvement of the TPJ in processing of complex visual stimuli that is not restricted to visual scenes and that the TPJ is sensitive to different classes of visual stimuli with a specific signature of neuronal activations.

Noninvasive Assessment of Chicken Egg Fertility during Incubation Using HSSE-GC-MS VOC Profiling

Volatile organic compounds (VOCs) carry crucial information about chicken egg fertility. Assessing the fertility before incubation holds immense potential for poultry industry efficiency. Our study used headspace sorptive extraction-gas chromatography-mass spectrometry to analyze egg VOCs before and during the initial 12 incubation days. A total of 162 VOCs were identified. Hexanal was significantly higher in unfertilized eggs, whereas compounds such as propan-2-ol, propan-2-one, and carboxylic acids were higher in fertilized eggs. Furthermore, the obtained multiple logistic regression model outperformed the partial least-squares-discriminant analysis (PLS-DA) model, demonstrating lower complexity and superior performance. Fertile eggs were accurately identified in the validation set in 68-75% of the cases during the initial 4 days, to 85 and 100% on days 6 and 8. Finally, hierarchical cluster analysis in fertilized eggs revealed the clustering of VOCs of the same chemical class, indicative of their shared biochemical origin. This suggests a promising direction for future research aimed at understanding the biological information embedded in VOCs and their relationship to biochemical processes during embryo development.

Chemokine expression in sera of patients with microscopic polyangiitis and granulomatosis with polyangiitis

We evaluated chemokine expression and its correlation with disease activity in patients with microscopic polyangiitis (MPA) and granulomatosis with polyangiitis (GPA) (MPA/GPA). Serum CCL2, CCL4, CCL19, CXCL1, CXCL2, and CX3CL1 level in 80 patients were analysed using multiple enzyme-linked immunosorbent assays. Correlations between variables were investigated using Pearson's correlation analysis, and receiver operator curve analysis was performed to identify optimal CX3CL1 values in determining active disease. Multivariate logistic regression analysis was done to evaluate predictors of active disease. CCL4 (r = 0.251, p = 0.025), CXCL1 (r = 0.270, p = 0.015), and CX3CL1 (r = 0.295, p = 0.008) significantly correlated with BVAS, while CX3CL1 was associated with five-factor score (r =  - 0.290, p = 0.009). Correlations were revealed between CCL2 and CCL4 (r = 0.267, p = 0.017), CCL4 and CXCL1 (r = 0.368, p < 0.001), CCL4 and CXCL2 (r = 0.436, p < 0.001), and CXCL1 and CXCL2 (r = 0.518, p < 0.001). Multivariate analysis revealed serum CX3CL1 levels > 2408.92 pg/mL could predict active disease (odds ratio, 27.401, p < 0.001). Serum chemokine levels of CCL4, CXCL1, and CX3CL1 showed association with disease activity and especially, CX3CL1 > 2408.92 pg/mL showed potential in predicting active MPA/GPA.

Quantitative measurement of internal quality of carrots using hyperspectral imaging and multivariate analysis

The study aimed to measure the carotenoid (Car) and pH contents of carrots using hyperspectral imaging. A total of 300 images were collected using a hyperspectral imaging system, covering 472 wavebands from 400 to 1000 nm. Regions of interest (ROIs) were defined to extract average spectra from the hyperspectral images (HIS). We developed two models: least squares support vector machine (LS-SVM) and partial least squares regression (PLSR) to establish a quantitative analysis between the pigment amounts and spectra. The spectra and pigment contents were predicted and correlated using these models. The selection of EWs for modeling was done using the Successive Projections Algorithm (SPA), regression coefficients (RC) from PLSR models, and LS-SVM. The results demonstrated that hyperspectral imaging could effectively evaluate the internal attributes of carrot cortex and xylem. Moreover, these models accurately predicted the Car and pH contents of the carrot parts. This study provides a valuable approach for variable selection and modeling in hyperspectral imaging studies of carrots.

Study of association between corneal shape parameters and axial length elongation during orthokeratology using image-pro plus software

BACKGROUND

The aim was to validate the correlation between corneal shape parameters and axial length growth (ALG) during orthokeratology using Image-Pro Plus (IPP) 6.0 software.

METHODS

This retrospective study used medical records of myopic children aged 8-13 years (n = 104) undergoing orthokeratology. Their corneal topography and axial length were measured at baseline and subsequent follow-ups after lens wear. Corneal shape parameters, including the treatment zone (TZ) area, TZ diameter, TZ fractal dimension, TZ radius ratio, eccentric distance, pupil area, and pupillary peripheral steepened zone(PSZ) area, were measured using IPP software. The impact of corneal shape parameters at 3 months post-orthokeratology visit on 1.5-year ALG was evaluated using multivariate linear regression analysis.

RESULTS

ALG exhibited significant associations with age, TZ area, TZ diameter, TZ fractal dimension, and eccentric distance on univariate linear regression analysis. Multivariate regression analysis identified age, TZ area, and eccentric distance as significantly correlated with ALG (all P < 0.01), with eccentric distance showing the strongest correlation (β = -0.370). The regressive equation was y = 1.870 - 0.235a + 0.276b - 0.370c, where y represents ALG, a represents age, b represents TZ area, and c represents eccentric distance; R2 = 0.27). No significant relationships were observed between the TZ radius ratio, pupillary PSZ area, and ALG.

CONCLUSIONS

IPP software proves effective in capturing precise corneal shape parameters after orthokeratology. Eccentric distance, rather than age or the TZ area, significantly influences ALG retardation.

Preoperative anaemia in distal pancreatectomy: a propensity-score matched analysis

BACKGROUND

Preoperative anaemia is a prevalent morbidity predictor that adversely affects short- and long-term outcomes of patients undergoing surgery. This analysis aimed to investigate preoperative anaemia and its detrimental effects on patients after distal pancreatectomy.

MATERIAL AND METHODS

The present study was a propensity-score match analysis of 286 consecutive patients undergoing distal pancreatectomy. Patients were screened for preoperative anaemia and classified according to WHO recommendations. The primary outcome measure was overall morbidity. The secondary endpoints were in-hospital mortality and rehospitalization.

RESULTS

The preoperative anaemia rate before matching was 34.3% (98 patients), and after matching a total of 127 patients (non-anaemic 42 vs. anaemic 85) were included. Anaemic patients had significantly more postoperative major complications (54.1% vs. 23.8%; p < 0.01), a higher comprehensive complication index (26.2 vs. 4.3; p < 0.01), and higher in-hospital mortality rate (14.1% vs. 2.4%; p = 0.04). Multivariate regression analysis confirmed these findings and identified preoperative anaemia as a strong independent risk factor for postoperative major morbidity (OR 4.047; 95% CI: 1.587-10.320; p < 0.01).

CONCLUSION

The current propensity-score matched analysis strongly considered preoperative anaemia as a risk factor for major complications following distal pancreatectomy. Therefore, an intense preoperative anaemia workup should be increasingly prioritised.

A mobile app to challenge obsessional beliefs in adolescents: a protocol of a two-armed, parallel randomized controlled trial

BACKGROUND

Adolescence is a crucial stage for the development of OCD symptoms that, in most cases, persist into adulthood. This requires designing preventive strategies tailored to this population. Therefore, we aim to describe the study protocol that will be used to examine the effectiveness of a mobile health application to challenge obsessional beliefs in adolescents.

METHODS

A two-armed randomized controlled trial will be conducted on an adolescent sample from the general population. The experimental group will use the intervention module (GGOC-AD) of a mobile app on the GGtude platform for 14 days whereas the control group will use a non-active module (GGN-AD) of said app. Primary outcome measures will be obsessional beliefs and obsessive-compulsive symptoms, and secondary measures will be self-esteem and emotional symptoms. Three assessment points will be conducted at baseline, post-intervention, and one-month follow-up. A linear multiple regression model with an intention to treat approach will be used. The expected total sample size will be 55 participants.

DISCUSSION

We expect that the intervention group will show a reduction in obsessional beliefs and OCD-symptoms at post and follow-up in comparison with the control group. Additionally, we expect that the app will improve participants' self-esteem. This study could provide an accessible mobile health tool to prevent OCD-related symptoms in adolescents.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT06033391 . Registered September 4, 2023.

Peripapillary atrophy area predicts the decrease of macular choroidal thickness in young adults during myopia progression

OBJECTIVE

This study aimed to investigate the influence of peripapillary atrophy (PPA) area and axial elongation on the longitudinal changes in macular choroidal thickness (ChT) in young individuals with myopia.

METHODS AND ANALYSIS

In this longitudinal investigation, 431 eyes-342 categorised as non-high myopia (non-HM) and 89 as HM-were examined for 2 years. Participants were examined with swept-source optical coherence tomography. The macular ChT, PPA area and axial length (AL) were measured at baseline and follow-up visits. Multiple regression analysis was performed to identify factors associated with ChT changes. The areas under the receiver operating characteristic curves were analysed to ascertain the predictive capacity of the PPA area and axial elongation for the reduction in macular ChT.

RESULTS

Initial measurements revealed that the average macular ChT was 240.35±56.15 µm in the non-HM group and 198.43±50.27 µm in the HM group (p<0.001). It was observed that the HM group experienced a significantly greater reduction in average macular ChT (-7.35±11.70 µm) than the non-HM group (-1.85±16.95 µm, p=0.004). Multivariate regression analysis showed that a greater reduction of ChT was associated with baseline PPA area (β=-26.646, p<0.001) and the change in AL (β=-35.230, p<0.001). The combination of the baseline PPA area with the change in AL was found to be effective in predicting the decrease in macular ChT, with an area under the curve of 0.741 (95% CI 0.694 to 0.787).

CONCLUSION

Over 2 years, eyes with HM exhibit a more significant decrease in ChT than those without HM. Combining the baseline PPA area with the change in AL could be used to predict the decrease of macular ChT.

Early diagnosis of thyroid-associated ophthalmopathy using label-free Raman spectroscopy and multivariate analysis

Thyroid-associated ophthalmopathy (TAO) is the most common orbital disease in adults, with complex clinical manifestations and significant impacts on the life quality of patients. The current diagnosis of TAO lacks reliable biomarkers for early and non-invasive screening and detection, easily leading to poor prognosis. Therefore, it is essential to explore new methods for accurately predicting TAO development in its early stage. In this study, Raman spectroscopy, with non-destructive, label-free, and high-sensitivity characteristics, was used to analyze the differences in biochemical components of orbital adipocyte and tear samples between TAO and control groups. Furthermore, a multivariate analysis method (i.e., Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA)) was applied for data processing and analysis. Compared with controls, PCA-LDA yielded TAO diagnostic accuracies of 72.7% and 75.0% using orbital adipocytes and tears, respectively. Our proof-of-concept results suggest that Raman spectroscopy holds potential for exploring the underlying pathogenesis of TAO, and its potential application in early screening of other thyroid-associated diseases can be further expanded.

Quantitative and qualitative analysis of cell culture media powders for mammalian cells by Raman microscopy

Cell culture media are essential for large-scale recombinant protein production using mammalian cell cultures. The composition and quality of media significantly impact cell growth and product formation. Analyzing media poses challenges due to complex compositions and undisclosed exact compositions. Traditional methods like NMR and chromatography offer sensitivity but require time-consuming sample preparation and lack spatial information. Raman chemical mapping characterizes solids, but its use in cell culture media analysis is limited so far. We present a chemometric evaluation for Raman maps to qualify and quantify media components, evaluate powder homogeneity, and perform lot-to-lot comparisons. Three lots of a marketed cell culture media powder were measured with Raman mapping technique. Chemometrics techniques have outlined a strategy to extract information from complex data. First, a spectral library has been structured. In addition to the 23 spectra for presumed ingredients, we obtained another 9 pure components with Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS). Then the Spectral Angle Mapper-Orthogonal Projection (SAM-OP) algorithm revealed whether references actually occur in the mapped media powders. Finally, a quantification was provided by Classical Least Squares (CLS) modelling. Quantities of 18 significant amino acids mostly correlated with the reference method. The proposed method can be generally applied even for such complicated samples. Leveraging Raman mapping and innovative chemometric methods enhance recombinant protein production by improving the understanding of the spatial distribution and composition of cell culture media in mammalian cell cultivations.

Prediction of 1-year change in knee extension strength by neuromuscular properties in older adults

Improving muscle strength and preventing muscle weakness are important for older adults. The change in strength can be effectively explained by skeletal muscle mass and neural factors. Neural factors are important for older adults because the variation of neural components is greater in older than in young adults, and any decline in strength cannot solely be explained by a decrease in skeletal muscle mass. The purpose of the present study was to investigate whether skeletal muscle mass or motor unit firing properties could explain the change in muscle strength after 1 year. Thirty-eight older adults (75.0 ± 4.7 years, 156.6 ± 7.7 cm, 55.5 ± 9.4 kg, 26 women) performed maximum voluntary knee extension and their skeletal muscle mass was measured using a bioimpedance device. During a submaximal contraction task, high-density surface electromyography was recorded and the signals were decomposed into individual motor unit firing. As an index of motor unit firing properties, the slope and y-intercept (MU intercept) were calculated from the regression line between recruitment thresholds and firing rates in each participant. After 1 year, their maximum knee extension torque was evaluated again. A stepwise multiple regression linear model with sex and age as covariates indicated that MU intercept was a significant explanation with a negative association for the 1-year change in muscle strength (β =  - 0.493, p = 0.004), but not skeletal muscle mass (p = 0.364). The results suggest that neural components might be predictors of increasing and decreasing muscle strength rather than skeletal muscle mass.

Serum Raman spectroscopy: Evaluation of tumour load variations in experimental carcinogenesis

Several serum Raman spectroscopy (RS) studies have demonstrated its potential as an oral cancer screening tool. This study investigates influence of low tumour load (LTL) and high tumour load (HTL) on serum RS using hamster buccal pouch model of experimental oral carcinogenesis. Sera of untreated control, LTL, and HTL groups at week intervals during malignant transformation were employed. Serum Raman spectra were subjected to multivariate analyses-principal component analysis, principal component-based linear discriminant analysis (for stratification of study groups), and multivariate curve resolution-alternating least squares (MCR-ALS) (to comprehend biomolecular differences). Multivariate analysis revealed misclassifications between LTL and HTL at all week intervals. MCR-ALS components showed statistically significant abundances between control versus LTL and control versus HTL, but could not discern LTL and HTL. MCR-ALS components exhibited spectral mixtures of proteins, lipids, heme and nucleic acids. Thus, these findings support use of serum RS as a screening tool as varying tumour load is not a confounding factor influencing the technique.

rMATS-turbo: an efficient and flexible computational tool for alternative splicing analysis of large-scale RNA-seq data

Pre-mRNA alternative splicing is a prevalent mechanism for diversifying eukaryotic transcriptomes and proteomes. Regulated alternative splicing plays a role in many biological processes, and dysregulated alternative splicing is a feature of many human diseases. Short-read RNA sequencing (RNA-seq) is now the standard approach for transcriptome-wide analysis of alternative splicing. Since 2011, our laboratory has developed and maintained Replicate Multivariate Analysis of Transcript Splicing (rMATS), a computational tool for discovering and quantifying alternative splicing events from RNA-seq data. Here we provide a protocol for the contemporary version of rMATS, rMATS-turbo, a fast and scalable re-implementation that maintains the statistical framework and user interface of the original rMATS software, while incorporating a revamped computational workflow with a substantial improvement in speed and data storage efficiency. The rMATS-turbo software scales up to massive RNA-seq datasets with tens of thousands of samples. To illustrate the utility of rMATS-turbo, we describe two representative application scenarios. First, we describe a broadly applicable two-group comparison to identify differential alternative splicing events between two sample groups, including both annotated and novel alternative splicing events. Second, we describe a quantitative analysis of alternative splicing in a large-scale RNA-seq dataset (~1,000 samples), including the discovery of alternative splicing events associated with distinct cell states. We detail the workflow and features of rMATS-turbo that enable efficient parallel processing and analysis of large-scale RNA-seq datasets on a compute cluster. We anticipate that this protocol will help the broad user base of rMATS-turbo make the best use of this software for studying alternative splicing in diverse biological systems.

Grouping of unused agricultural by-product biomass for fuel conversion in South Korea through multivariate analysis

While biomass holds significance as a resource, its abundance in South Korea is limited. Therefore, in this study analyzed the chemical characteristics of agricultural by-products produced and evaluated their fuel potentiality. To achieve this objective, multivariate analysis was utilized to create biomass clusters with diverse feature. All investigated biomass types showed heating values of at least 12.6 MJ/kg, adhering to South Korea's Bio-solid recovered fuel (SRF) standard, once the moisture content was reduced to 20 % or less. However, the biomasses only met the heating value of Level 3 of the European standard for SRF, which is at least 15 MJ/kg. Groups were formed based on a multivariate analysis using four variables: the high heating value, and carbon, nitrogen, and ash contents. The groups were centered around wood chips and hog fuel, with a cluster of lignocellulosic biomass materials surrounding them. The clusters formed around four groups. When the biomasses in each group were mixed, the combustion characteristics were compared to the ignition, maximum, and burn-out temperatures. Utilizing biomass grouping, by-products from agriculture and livestock in South Korea can be effectively employed as energy sources.

Prognostic significance of serum monoclonal proteins based on immunofixation electrophoresis in B-cell non-Hodgkin lymphoma

The presence of serum monoclonal components has been associated with poor outcomes in various hematological malignancies. The current study focused on exploring its prognostic role in B-cell non-Hodgkin lymphoma. Our study represented 314 patients with information on serum immunofixation electrophoresis at diagnosis that were available with B-cell non-Hodgkin lymphoma. IFE was positive in 61 patients (19%). Baseline features were comparable between pairs of groups, poor ECOG PS, B symptoms, advanced stage, and high-risk IPI score were significantly more frequent in the + IFE group. Shorter PFS and OS of B-NHL patients were observed in patients who presented at diagnosis with a + IFE, and IFE was the independent predictor of PFS and OS in multivariate analysis. Moreover, integrating IFE into the IPI-M1, IPI-M2, and IPI-M3 models improved the area under the curve for more accurate survival prediction and prognosis. Serum monoclonal proteins are significant prognostic indicators for newly diagnosed B-cell non-Hodgkin lymphoma that can early identify patients with poor prognosis and guide clinical treatment decisions.

Women's Social Mobility and Attitudinal Acceptance of Wife Abuse: A Cross-Sectional Study Among Bengali, Santal, and Garo Ethnic Communities in Rural Bangladesh

Previous studies exploring the influential factors associated with attitudinal acceptance of wife abuse (AAWA) did not widely focus on the relation between women's social mobility (WSM) and different dimensions of AAWA in rural Bangladesh. This current study examined the association between WSM and different dimensions of AAWA in the context of socio-cultural differences among the Bengali, the Santal, and the Garo ethnic communities in rural Bangladesh. Adopting a cross-sectional design, 1,929 married men and women were randomly included in the study from 8 Bengali, 8 Santal, and 8 Garo villages where 50.2% were women and 49.8% were men. Of the sample, 33.2% Garo, 33.2% Santal, and 33.6% Bengali participants were included in this study. Data revealed that 45.5% of women had low social mobility and the prevalence of different dimensions of AAWA was high and varied among the study communities. We used descriptive statistics, chi-square, and binary logistic regression analysis to estimate the association. The multivariate binary logistic regression analysis results revealed that the likelihood of attitudinal acceptance of overall abuse, psychological abuse, physical abuse, abuse on disobeying family obligation, and abuse on challenging male authority were significantly lower for the respondents who belonged to families where women enjoyed high mobility compared to those who belonged to families where WSM was low. This study also showed that the Bengali and the Santal participants were more likely to accept different dimensions of AAWA compared to the Garos. This study suggests that WSM should be considered in policy-making and implementing interventions to reduce the different dimensions of AAWA in rural Bangladesh.

Multivariate analysis of alveolar bone dehiscence and fenestration in anterior teeth after orthodontic treatment: A retrospective study

OBJECTIVE

To compare the prevalence of fenestration and dehiscence between pre- and post-orthodontic treatment and to explore the factors related to fenestration and dehiscence in the anterior teeth after treatment.

METHODS

This study included 1000 cone-beam computed tomography (CBCT) scans of 500 patients before (T1) and after (T2) orthodontic treatment. These images were imported into Dolphin 11.9 software to detect alveolar fenestration and dehiscence in the anterior teeth area. The chi-square test and Fisher's exact test were performed to compare the prevalence of alveolar bone defects between time points T1 and T2. A total of 499 patients were selected for logistic regression analysis to examine the correlation among age, sex, crowding, sagittal facial type, extraction, miniscrew use and fenestration or dehiscence post-treatment.

RESULTS

Except for the maxillary lingual fenestration and labial fenestration of mandibular canines, a significant change in the prevalence of fenestration and dehiscence was noted between time points T1 and T2 (P < .025). Multinomial logistic regression showed that age, miniscrew use and extraction highly influenced the prevalence of anterior lingual dehiscence (P < .05). Dehiscence of the mandibular labial side (skeletal Class III vs. I, OR = 2.368, P = .000) and fenestration of the mandibular lingual side (skeletal Class II vs. I, OR = 2.344, P = .044) were strongly correlated with the sagittal facial type. Dehiscence of the maxillary labial side (moderate vs. mild, OR = 1.468, P = .017) was significantly associated with crowding.

CONCLUSIONS

Older age, maxillary moderate crowding, skeletal Class III, extraction and miniscrew potentially significantly affect the prevalence of anterior teeth dehiscence. Adult females, skeletal Class III patients on the mandibular labial side and skeletal Class II patients on the mandibular lingual side should be monitored for anterior teeth fenestration.

The neural dynamics of conflict adaptation induced by conflict observation: Evidence from univariate and multivariate analysis

Conflict adaptation can be expressed as greater performance (shorter response time and lower error rate) after incongruent trials when compared to congruent trials. It has been observed in designs that minimize confounding factors, i.e., feature integration, contingency learning, and temporal learning. Our current study aimed to further elucidate the temporal evolution mechanisms of conflict adaptation. To address this issue, the current study employed a combination of behavioral, univariate, and multivariate analysis (MVPA) methods in a modified color-word Stroop task, where half of the trials required button presses (DO trials), and the other half only required observation (LOOK trials). Both behavioral and the ERP results (N450 and SP) in the LOOK-DO transition trials revealed significant conflict adaptation without feature integration, contingency learning, and temporal learning, providing support for the conflict monitoring theory. Furthermore, during the LOOK trials, significant Stroop effect in the N450 and SP components were observed, indicating that conflict monitoring occurred at the stimulus level and triggered reactive control adjustments. The MVPA results decoded the congruent-incongruent and incongruent-incongruent conditions during the conflict adjustment phase but not during the conflict monitoring phase, emphasizing the unique contribution of conflict adjustment to conflict adaptation. The current research findings provided more compelling supporting evidence for the conflict monitoring theory, while also indicating that future studies should employ the present design to elucidate the specific processes of conflict adaptation.

A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG

The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns.

Characterization, multivariate analysis and bioactivity evaluation of coumarins in the bark of Fraxinus mandshurica

The bark of Fraxinus mandshurica is a traditional folk herb used to clear heat and dry dampness. To investigate the differences in coumarins content in the bark of F. mandshurica, 24 batches of samples from four origins were collected and analyzed. Eight coumarins were obtained by traditional natural product extraction, isolation and identification techniques and quantified by high performance liquid chromatography-photodiode array (HPLC-DAD). The quantitative results showed that the overall content of compound 30 (Fraxinol) was higher at 100.23 mg/g, while the overall content of compound 23 (Cichoriin) was lower, which may be related to environmental factors in different regions. The method validation showed that the linear range of the eight standards was between 10 and 2500 μg/mL with correlation coefficient (R2) values >0.9991; the relative standard deviation (RSD, %) values of intra-day precision were between 0.35 and 1.38, while the RSD values of inter-day precision were between 0. 29-1.78; the RSD (%) values for the reproducibility experiments ranged from 0.29 to 1.87, while the RSD (%) values for the stability experiments ranged from 0.22 to 2.33; the spiked recovery of the samples ranged from 98.65 to 101.34%, and the RSD (%) values ranged from 0.22 to 1.96. The method validation results showed that the instrument used for the analysis had good precision, the reproducibility and stability of the samples were good, and the accuracy of the experimental method was high. In addition, a total of 54 chemical components were identified from F. mandshurica bark by ultra performance liquid chromatography-electrospray quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS). Based on this, fingerprinting, heatmap and multivariate analysis, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA), were established for 24 batches of samples, and four marker compounds that could be used to distinguish different origins of F. mandshurica were screened. To further investigate the bioactivities of the eight coumarins, in vitro enzyme activity inhibition studies were performed, and the results showed that they all exhibited different degrees of inhibition of acetylcholinesterase, tyrosinase and α-glucosidase, thus having potential applications in the treatment of Alzheimer's disease, blemish whitening and anti-diabetes, and becoming a new source of natural enzyme activity inhibitors. This study established an identification and evaluation method applicable to plants of different origins, which provides a strong reference for quality control, origin evaluation and clinical application of traditional medicinal plants.

FT-Raman spectra in combination with machine learning and multivariate analyses as a diagnostic tool in brain tumors

Brain tumors are one of the most dangerous, because the position of these are in the organ that governs all life processes. Moreover, a lot of brain tumor types were observed, but only one main diagnostic method was used - histopathology, for which preparation of sample was long. Consequently, a new, quicker diagnostic method is needed. In this paper, FT-Raman spectra of brain tissues were analyzed by Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), four different machine learning (ML) algorithms to show possibility of differentiating between glioblastoma G4 and meningiomas, as well as two different types of meningiomas (atypical and angiomatous). Obtained results showed that in meningiomas additional peak around 1503 cm-1 and higher level of amides was noticed in comparison with glioblastoma G4. In the case of meningiomas differentiation, in angiomatous meningiomas tissues lower level of lipids and polysaccharides were visible than in atypical meningiomas. Moreover, PCA analyses showed higher distinction between glioblastoma G4 and meningiomas in the FT-Raman range between 800 cm-1 and 1800 cm-1 and between two types of meningiomas in the range between 2700 cm-1 and 3000 cm-1. Decision trees showed, that the most important peaks to differentiate glioblastoma and meningiomas were at 1151 cm-1 and 2836 cm-1 while for angiomatous and atypical meningiomas - 1514 cm-1 and 2875 cm-1. Furthermore, the accuracy of obtained results for glioblastoma G4 and meningiomas was 88 %, while for meningiomas - 92 %. Consequently, obtained data showed possibility of using FT-Raman spectroscopy in diagnosis of different types of brain tumors.

Current Applications of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) in Pharmaceutical Analysis: Review

The present review encompasses various applications of multivariate curve resolution- alternating least squares (MCR-ALS) as a promising data handling, which is issued by analytical techniques in pharmaceutics. It involves different sections starting from a concise theory of MCR-ALS and four detailed applications in drugs analysis. Dissolution, stability, polymorphism, and quantification are the main four detailed applications. The data generated by analytical techniques associated with MCR-ALS deals accurately with different challenges compared to other chemometric tools. For each reviewed purpose, it was explained how MCR-ALS was applied and detailed information was given. Different approaches were introduced to overcome challenges that limit the use of MCR-ALS efficiently in pharmaceutical mixture were also discussed.

Transition readiness of adolescents with cancer: A cross-sectional study based on self-determination theory

PURPOSE

This study aimed to assess the transition readiness of adolescents with cancer in central China and to explore the paths associated with transition readiness based on self-determination theory (SDT).

METHODS

Self-management and transition to adulthood with Rx = treatment questionnaire, patient activation measure, perceived social support scale and general self-efficacy scale were used to measure transition readiness as well as constructs pertaining to SDT (competence, relatedness and autonomy). The factors influencing transition readiness were evaluated using multiple linear regression. Models 4 and 6 in PROCESS Macro 3.3 were used to test the mediating effects and chain mediating effects, respectively.

RESULTS

A total of 217 adolescents with cancer were included; their mean transition readiness score was 59.95 (11.34). Age (t = 6.086, p < 0.000), duration of diagnosis (t = 2.218, p = 0.028), completion of treatment (t = -2.036, p = 0.043), insurance, and competence (t = 11.149, p < 0.000) were significantly associated with transition readiness. The direct effects of self-efficacy and perceived social support on transition readiness were not significant. However, two chain mediating paths were observed: perceived social support - self-efficacy - patient activation - transition readiness and self-efficacy - perceived social support - patient activation - transition readiness; the effect values of these paths were 0.0678 and 0.0703, respectively.

CONCLUSIONS

The findings of this study add to the evidence supporting the use of SDT-related constructs to promote transition readiness among adolescents with cancer, highlight the importance of encouraging patient activation, and clarify the ancillary roles of social support and self-efficacy in patient activation development during transitional period.

Determinants of health and mortality in undiagnosed diabetes: A nationally representative US adult, 2011-2020

AIM

This study examines the determinants of health and mortality associated with undiagnosed diabetes among a nationally representative sample of US adults.

METHODS

Data are from the National Health and Nutrition Examination Survey between 2011 and 2012 and 2019-2020. Diabetes status is categorized into three groups: undiagnosed diabetes, diagnosed diabetes, and no diabetes. Multiple logistic regression is used to estimate the association between undiagnosed diabetes and three domains of risk factors, including sociodemographic and health behavioral and clinical factors. Cox proportional hazards models are performed to compare excess mortality risk between the three groups.

RESULTS

Young adults, racial minorities, the foreign-born, and individuals with limited access to health care are more likely to be unaware of their diabetes. Moreover, adults without a family history of diabetes and chronic conditions have a higher chance of undiagnosed diabetes. No health behavioral factors are found to be associated with undiagnosed diabetes. Adults with undiagnosed diabetes have a lower risk of all-cause and cardiovascular disease mortality compared to those with diagnosed diabetes, but a higher risk of all-cause mortality than those with no diabetes.

CONCLUSION

Targeted public health approaches should address sociodemographic and clinical factors to reduce the burden of undiagnosed diabetes.

[Parental strain, inattention/hyperactivity symptoms and parent-reported ADHD in children and adolescents: results of the KiGGS study]

BACKGROUND

A child's attention deficit hyperactivity disorder (ADHD) is associated with strain for the parents. In turn, psychosocial parental strain is associated with higher probabilities for the occurrence of inattention/hyperactivity symptoms (IHS) in their children. The aim of this paper is to assess the association between parental strain, IHS, and a parent-reported ADHD diagnosis of the children.

METHODOLOGY

Based on data from n = 4596 participants of the KiGGS cohort (wave 2: 2014-2017), the type and extent of parental strain was set in relation to IHS and an ADHD diagnosis of the child in cross-sectional analysis. Frequencies, means, beta coefficients, and odds ratios adjusted for sex, age, socioeconomic status, and migration background are reported.

RESULTS

In individual consideration, a greater number of parental strains were associated with IHS than with an ADHD diagnosis. In a multivariate analysis, financial worries and parenting problems/conflicts with the children were significant predictors of IHS and an ADHD diagnosis, respectively. In addition, four or more types of parental strain were associated with a higher likelihood of both IHS and an ADHD diagnosis.

DISCUSSION

Financial and child-rearing strain are relevant to parents of children with IHS and an ADHD diagnosis. Interrelationships between parental stress and a child's IHS or an ADHD diagnosis can be assumed. To relieve their burden, prevention can either aim at improving the situation of ADHD-affected families or at improving the family's handling of the child's ADHD.

Time is the enemy: Negative symptoms are related to even slight differences in the duration of untreated psychosis

BACKGROUND

Negative symptoms (NS) represent a detrimental symptomatic domain in schizophrenia affecting social and occupational outcomes.

AIMS

We aimed to identify factors from the baseline visit (V1) - with a mean illness duration of 0.47 years (SD = 0.45) - that predict the magnitude of NS at the follow-up visit (V3), occurring 4.4 years later (mean +/- 0.45).

METHOD

Using longitudinal data from 77 first-episode schizophrenia spectrum patients, we analysed eight predictors of NS severity at V3: (1) the age at disease onset, (2) age at V1, (3) sex, (4) diagnosis, (5) NS severity at V1, (6) the dose of antipsychotic medication at V3, (7) hospitalisation days before V1 and; (8) the duration of untreated psychosis /DUP/). Secondly, using a multiple linear regression model, we studied the longitudinal relationship between such identified predictors and NS severity at V3 using a multiple linear regression model.

RESULTS

DUP (Pearson's r = 0.37, p = 0.001) and NS severity at V1 (Pearson's r = 0.49, p < 0.001) survived correction for multiple comparisons. The logarithmic-like relationship between DUP and NS was responsible for the initial stunning incremental contribution of DUP to the severity of NS. For DUP < 6 months, with the sharpest DUP/NS correlation, prolonging DUP by five days resulted in a measurable one-point increase in the 6-item negative symptoms PANSS domain assessed 4.9 (+/- 0.6) years after the illness onset. Prolongation of DUP to 14.7 days doubled this NS gain, whereas 39 days longer DUP tripled NS increase.

CONCLUSION

The results suggest the petrification of NS during the early stages of the schizophrenia spectrum and a crucial dependence of this symptom domain on DUP. These findings are clinically significant and highlight the need for primary preventive actions.

Label-Free SERS of Urine Components: A Powerful Tool for Discriminating Renal Cell Carcinoma through Multivariate Analysis and Machine Learning Techniques

The advent of Surface-Enhanced Raman Scattering (SERS) has enabled the exploration and detection of small molecules, particularly in biological fluids such as serum, blood plasma, urine, saliva, and tears. SERS has been proposed as a simple diagnostic technique for various diseases, including cancer. Renal cell carcinoma (RCC) ranks as the sixth most commonly diagnosed cancer in men and is often asymptomatic, with detection occurring incidentally. The onset of symptoms typically aligns with advanced disease, aggressive histology, and unfavorable prognosis, and therefore new methods for an early diagnosis are needed. In this study, we investigated the utility of label-free SERS in urine, coupled with two multivariate analysis approaches: Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) and Support Vector Machine (SVM), to discriminate between 50 RCC patients and 44 healthy donors. Employing LDA-PCA, we achieved a discrimination accuracy of 100% using 13 principal components, and an 88% accuracy in discriminating between different RCC stages. The SVM approach yielded a training accuracy of 100%, a validation accuracy of 99% for discriminating between RCC and controls, and an 80% accuracy for discriminating between stages. The comparative analysis of raw and normalized SERS spectral data shows that while raw data disclose relative concentration variations in urine metabolites between the two classes, the normalization of spectral data significantly improves the accuracy of discrimination. Moreover, the selection of principal components with markedly distinct scores between the two classes serves to alleviate overfitting risks and reduces the number of components employed for discrimination. We obtained the accuracy of the discrimination between the RCC patients cases and healthy donors of 90% for three PCs and a linear discrimination function, and a 88% accuracy of discrimination between stages using six PCs, mitigating practically the risk of overfitting and increasing the robustness of our analysis. Our findings underscore the potential of label-free SERS of urine in conjunction with chemometrics for non-invasive and early RCC detection.

Changes in profiles of volatile compounds and prediction of the storage year of organic green tea during the long-term storage

In the present study, the volatile compounds in organic green tea with a continuous storage period (ranging from 1 to 16 years) were comprehensively analyzed and compared through SDE-GC-MS and chemometrics. The results revealed that the total of 124 volatiles were identified, and their total amount was increased with the prolongation of the storage years. Ketones, alcohols, esters, and aromatic hydrocarbons were the main types of volatiles in organic green tea, among which 26 volatile compounds were significantly correlated with storage years, and six volatile compounds that were most seriously affected by the storage years. The results of the support vector machine classification combined with multiple linear regression analysis showed that the content-period prediction model for the six volatile compounds can accurately predict the storage years of organic green tea. Therefore, this study offers novel insights into volatile compounds changes during the storage of green tea.

Personalized analysis of pain-weather associations: a pilot study

Background and purpose

It is a wellknown belief that weather can influence human health, including pain sensation. However, the current data are controversial, which might be due to the wide range of interindividual differences. The present study aimed to characterize the individual pain–weather associations during chronic pain by utilizing several data analytical methods.

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Methods

The study included 3-3 patients with (P1, P3, and P4) or without (P2, P5, P6) diabetes mellitus and signs of trigeminal neuralgia or low back pain. Subjective pain scores (0–10) and 12 weather parameters (terrestrial, geomagnetic, and solar) were recorded for one month repeated three times daily. Nonparametric Spearman’s correlation (Sp), multiple regression (Mx), and principal component (PCA) analyses were performed to evaluate associations between pain and meteorological factors obtained at the day of recorded pain value, 2 days before and 2 days after the recorded pain, and the changes in these parameters (5 × 12 parameters). Complex scores were calculated based on the results of these analyses.

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Results

While the temperature had the highest effects on the pain levels in most of the participants, huge interindividual dif­ferences in the degree and the direction of the associations between pain and weather parameters could be obtained. The analytic methods also revealed subjectspecific results, and the synthesis of different statistical methods as total scores provided a personalized map for each patient, which showed disparate patterns across the study participants. Thus, Participants 2 and 5 had higher scores for Mx compared to Sp; furthermore, certain factors showed opposite direction in their associations with the pain level depending on the type of analysis (Sp vs Mx). In contrast, P3 had a lower score for Mx compared to Sp, which might suggest a low level of weather sensitivity on the association between the different weather parameters in this subject. Furthermore, participants P4 and P6 had a very high level of weather sensitivity, while P1 had an opposite pattern. Regarding the time point-related effects on the pain level, most patients were sensitive to parameters obtained at the same day or two days before, except the P1 subject, who had the highest sensitivity to weather parameters detected two days after.

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Conclusion

The present study highlights the importance of integrating different data analysis approaches to elucidate the individual connections between pain and most of the weather parameters. In conclusion, complex personalized profiling should be considered for the characterization of pain–weather associations by applying different data analytical approaches, which may provide feedback to physicians and patients. 

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Development and validation of a novel prognostic nomogram for advanced diffuse large B cell lymphoma

Advanced diffuse large B cell lymphoma (DLBCL) is a common malignant tumor with aggressive clinical features and poor prognosis. At present, there is lack of effective prognostic tool for patients with advanced (stage III/IV) DLBCL. The aim of this study is to identify prognostic indicators that affect survival and response and establish the first survival prediction nomogram for advanced DLBCL. A total of 402 patients with advanced DLBCL were enrolled in this study. COX multivariate analysis was used to obtain independent prognostic factors. The independent prognostic factors were included in the nomogram, and the nomogram to predict the performance of the model was established by R rms package, C-index (consistency index), AUC curve and calibration curve. The training and validation cohorts included 281 and 121 patients. In the training cohort, multivariate analysis showed that Ki-67 (70% (high expression) vs ≤ 70% (low expression), p < 0.001), LDH (lactate dehydrogenase) (elevated vs normal, p = 0.05), FER (ferritin) (elevated vs normal, p < 0.001), and β2-microglobulin (elevated vs normal, p < 0.001) were independent predictors and the nomogram was constructed. The nomogram showed that there was a significant difference in OS among the low-risk, intermediate-risk and high-risk groups, with 5-year survival rates of 81.6%, 44% and 6%, respectively. The C-index of the nomogram in the training group was 0.76. The internal validation of the training group showed good consistency. In the internal validation cohort of the training group, the AUC was 0.828, and similar results were obtained in the validation group, with a C-index of 0.74 and an AUC of 0.803. The proposed nomogram provided a valuable individualized risk assessment of OS in advanced DLBCL patients.

Treatment patterns and survival outcomes in patients with non-metastatic early-onset pancreatic cancer

BACKGROUND

The incidence of patients with early-onset pancreatic cancer (EOPC; age ≤ 50 years at diagnosis) is on the rise, placing a heavy burden on individuals, families, and society. The role of combination therapy including surgery, radiotherapy, and chemotherapy in non-metastatic EOPC is not well-defined.

AIM

To investigate the treatment patterns and survival outcomes in patients with non-metastatic EOPC.

METHODS

A total of 277 patients with non-metastatic EOPC who were treated at our institution between 2017 and 2021 were investigated retrospectively. Overall survival (OS), disease-free survival, and progression-free survival were estimated using the Kaplan-Meier method. Univariate and multivariate analyses with the Cox proportional hazards model were used to identify prognostic factors.

RESULTS

With a median follow-up time of 34.6 months, the 1-year, 2-year, and 3-year OS rates for the entire cohort were 84.3%, 51.5%, and 27.6%, respectively. The median OS of patients with localized disease who received surgery alone and adjuvant therapy (AT) were 21.2 months and 28.8 months, respectively (P = 0.007). The median OS of patients with locally advanced disease who received radiotherapy-based combination therapy (RCT), surgery after neoadjuvant therapy (NAT), and chemotherapy were 28.5 months, 25.6 months, and 14.0 months, respectively (P = 0.002). The median OS after regional recurrence were 16.0 months, 13.4 months, and 8.9 months in the RCT, chemotherapy, and supportive therapy groups, respectively (P = 0.035). Multivariate analysis demonstrated that carbohydrate antigen 19-9 level, pathological grade, T-stage, N-stage, and resection were independent prognostic factors for non-metastatic EOPC.

CONCLUSION

AT improves postoperative survival in localized patients. Surgery after NAT and RCT are the preferred therapeutic options for patients with locally advanced EOPC.

Comparative analysis and evaluation of wild and cultivated Radix Fici Simplicissimae using an UHPLC-Q-Orbitrap mass spectrometry-based metabolomics approach

Radix Fici Simplicissimae (RFS) is widely studied, and is in demand for its value in medicines and food products, with increased scientific focus on its cultivation and breeding. We used ultra-high-performance liquid chromatography quadrupole-orbitrap mass spectrometry-based metabolomics to elucidate the similarities and differences in phytochemical compositions of wild Radix Fici Simplicissimae (WRFS) and cultivated Radix Fici Simplicissimae (CRFS). Untargeted metabolomic analysis was performed with multivariate statistical analysis and heat maps to identify the differences. Eighty one compounds were identified from WRFS and CRFS samples. Principal component analysis and orthogonal partial least squares discrimination analysis indicated that mass spectrometry could effectively distinguish WRFS from CRFS. Among these, 17 potential biomarkers with high metabolic contents could distinguish between the two varieties, including seven phenylpropanoids, three flavonoids, one flavonol, one alkaloid, one glycoside, and four organic acids. Notably, psoralen, apigenin, and bergapten, essential metabolites that play a substantial pharmacological role in RFS, are upregulated in WRFS. WRFS and CRFS are rich in phytochemicals and are similar in terms of the compounds they contain. These findings highlight the effects of different growth environments and drug varieties on secondary metabolite compositions and provide support for targeted breeding for improved CRFS varieties.

Multivariate Analysis of Light-Activated SMOX Gas Sensors

Chemoresistive gas sensors made from SnO2, ZnO, WO3, and In2O3 have been prepared by flame spray pyrolysis. The sensors' response to CO and NO2 in darkness and under illumination at different wavelengths, using commercially available LEDs, was investigated. Operation at room temperature turned out to be impractical due to the condensation of water inside the porous sensing layers and the irreversible changes it caused. Accordingly, for sensors operated at 70 °C, a characterization procedure was developed and proven to deliver consistent data. The resulting data set was so complex that usual univariate data analysis was intricate and, consequently, was investigated by correlation and principal component analysis. The results show that light of different wavelengths affects not only the resistance of each material, both under exposure to the target gases in humidity and in its absence, but also the sensor response to humidity and the target gases. It was found that each of the materials behaves differently under light exposure, and it was possible to identify conditions that need further investigations.