Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer.

Cervical cancer (CC) is a major global health problem with 570,000 new cases and 266,000 deaths annually. Prognosis is poor for advanced stage disease, and few effective treatments exist. Preoperative diagnostic imaging is common in high-income countries and MRI measured tumor size routinely guides treatment allocation of cervical cancer patients. Recently, the role of MRI radiomics has been recognized. However, its potential to independently predict survival and treatment response requires further clarification. This retrospective cohort study demonstrates how non-invasive, preoperative, MRI radiomic profiling may improve prognostication and tailoring of treatments and follow-ups for cervical cancer patients. By unsupervised clustering based on 293 radiomic features from 132 patients, we identify three distinct clusters comprising patients with significantly different risk profiles, also when adjusting for FIGO stage and age. By linking their radiomic profiles to genomic alterations, we identify putative treatment targets for the different patient clusters (e.g., immunotherapy, CDK4/6 and YAP-TEAD inhibitors and p53 pathway targeting treatments).

The influence of drying and storage conditions on the volatilome and cannabinoid content of Cannabis sativa L. inflorescences.

The increasing interest in hemp and cannabis poses new questions about the influence of drying and storage conditions on the overall aroma and cannabinoids profile of these products. Cannabis inflorescences are subjected to drying shortly after harvest and then to storage in different containers. These steps may cause a process of rapid deterioration with consequent changes in precious secondary metabolite content, negatively impacting on the product quality and potency. In this context, in this work, the investigation of the effects of freeze vs tray drying and three storage conditions on the preservation of cannabis compounds has been performed. A multi-trait approach, combining both solid-phase microextraction (SPME) two-dimensional gas chromatography coupled to mass spectrometry (SPME-GC × GC-MS) and high-performance liquid chromatography (HPLC), is presented for the first time. This approach has permitted to obtain the detailed characterisation of the whole cannabis matrix in terms of volatile compounds and cannabinoids. Moreover, multivariate statistical analyses were performed on the obtained data, helping to show that freeze drying conditions is useful to preserve cannabinoid content, preventing decarboxylation of acid cannabinoids, but leads to a loss of volatile compounds which are responsible for the cannabis aroma. Furthermore, among storage conditions, storage in glass bottle seems more beneficial for the retention of the initial VOC profile compared to open to air dry tray and closed high-density polyethylene box. However, the glass bottle storage condition causes formation of neutral cannabinoids at the expenses of the highly priced acid forms. This work will contribute to help define optimal storage conditions useful to produce highly valuable and high-quality products.

Lifestyle-based subtypes of childhood obesity and their association with cardiometabolic factors: A cluster analysis.

BACKGROUND: Lifestyle factors play an important role in the development and management of childhood obesity and its related cardiometabolic complications. OBJECTIVE/METHODS: We aimed to explore childhood obesity subtypes based on lifestyle factors and examine their association with cardiometabolic health. We included 1550 children with obesity from the National Health and Nutrition Examination Survey. Cluster analysis identified obesity subtypes based on four lifestyle factors (physical activity, diet quality, sedentary time and smoking). Multiple linear regression assessed their association with cardiometabolic factors. RESULTS: Five subtypes of childhood obesity were identified: unhealthy subtype (n = 571; 36.8%), physically active subtype (n = 185; 21.1%), healthy diet subtype (n = 404; 26.1%), smoking subtype (n = 125; 8.1%) and non-sedentary subtype (n = 265; 17.1%). Compared with the unhealthy subtype, the physically active subtype had lower insulin and HOMA-IR levels, and smoking subtype was associated with lower HDL levels. When compared with children with normal weight, all obesity subtypes had worse cardiometabolic profile, except the physically active subtype who had similar DBP, HbA1c and TC levels; smoking subtype who had similar TC levels; and healthy diet and non-sedentary subtypes who had similar DBP levels. CONCLUSION: Children of different lifestyle-based obesity subtypes might have different cardiometabolic risks. Our new classification system might help personalize assessment of childhood obesity.

Cluster analysis of patients with alcohol use disorder featuring alexithymia, depression, and diverse drinking behavior.

AIM: This study aimed to identify subgroups of alcohol use disorder (AUD) based on a multidimensional combination of alexithymia, depression, and diverse drinking behavior. METHOD: We recruited 176 patients with AUD, which were initially divided into non-alexithymic (n = 130) and alexithymic (n = 46) groups using a cutoff score of 61 on the Toronto Alexithymia Scale (TAS-20). Subsequently, the profiles of the two groups were compared. Thereafter, a two-stage cluster analysis using hierarchical and K-means methods was performed with the Z-scores from the TAS-20, the Quick Inventory of Depressive Symptomatology Self-Report Japanese Version, the 12-item questionnaire for quantitative assessment of depressive mixed state, and the 20-item questionnaire for drinking behavior pattern. RESULTS: In the first analysis, Alexithymic patients with AUD showed greater depressive symptoms and more pathological drinking behavior patterns than those without alexithymia. Cluster analysis featuring alexithymia, depression, and drinking behavior identified three subtypes: Cluster 1 (core AUD type) manifesting pathological drinking behavior highlighting automaticity; Cluster 2 (late-onset type) showing relatively late-onset alcohol use and fewer depressive symptoms or pathological drinking behavior; and Cluster 3 (alexithymic type) characterized by alexithymia, depression, and pathological drinking behavior featuring greater coping with negative affect. CONCLUSION: The multidimensional model with alexithymia, depression, and diverse drinking behavior provided possible practical classification of AUD. The alexithymic subtype may require more caution, and additional support for negative affect may be necessary due to accompanying mood problems and various maladaptive drinking behaviors.

Peripheral Blood Lymphocyte Subsets and Heterogeneity of B Cell Subsets in Patients of Idiopathic Inflammatory Myositis with Different Myositis-specific Autoantibodies.

Idiopathic inflammatory myopathies (IIM) are a group of myopathies that present with muscle weakness and multiple extra-muscular manifestations, in which lymphocytes play central roles in myositis pathogenesis. This study aimed to explore the clinical characteristics of lymphocyte subsets, especially B cell subsets, in patients with IIM. Our study included 176 patients with active IIM and 210 gender/age-matched healthy controls (HCs). Compared to HCs, patients have reduced counts of T cells, B cells, and natural killer cells. In addition, B cell subsets from 153 patients with IIM and 92 HCs were characterized. Patients had a lower percentage of memory B cells and translational memory B cells, while those patients were with an elevated percentage of CD19+ B cells, plasmablast and naïve B cells compared with HCs. Moreover, to further explore the heterogeneity of B cells in IIM, patients were categorized into three clusters based on clustering analysis. Cluster 1 was dominated by CD19+ B cells, Bregs and naïve B cells, cluster 3 was dominated by memory B cells and plasmablast, and cluster 2 had the highest proportion of translational memory B cells. Notably, patients in cluster 1 presented with higher CK levels, indicating muscle damage, whereas patients in cluster 3 showed a higher incidence of chest tightness. Our study indicated that lymphopenia is a common manifestation in patients with IIM. B cell subsets are abnormally expressed and showed high heterogeneity in patients with IIM. The patients with IIM were divided into three different clusters with different percentages of chest tightness and distinct CK levels.

Classification of congenital cataracts based on multidimensional phenotypes and its association with visual outcomes.

AIM: To establish a classification for congenital cataracts that can facilitate individualized treatment and help identify individuals with a high likelihood of different visual outcomes. METHODS: Consecutive patients diagnosed with congenital cataracts and undergoing surgery between January 2005 and November 2021 were recruited. Data on visual outcomes and the phenotypic characteristics of ocular biometry and the anterior and posterior segments were extracted from the patients' medical records. A hierarchical cluster analysis was performed. The main outcome measure was the identification of distinct clusters of eyes with congenital cataracts. RESULTS: A total of 164 children (299 eyes) were divided into two clusters based on their ocular features. Cluster 1 (96 eyes) had a shorter axial length (mean±SD, 19.44±1.68 mm), a low prevalence of macular abnormalities (1.04%), and no retinal abnormalities or posterior cataracts. Cluster 2 (203 eyes) had a greater axial length (mean±SD, 20.42±2.10 mm) and a higher prevalence of macular abnormalities (8.37%), retinal abnormalities (98.52%), and posterior cataracts (4.93%). Compared with the eyes in Cluster 2 (57.14%), those in Cluster 1 (71.88%) had a 2.2 times higher chance of good best-corrected visual acuity [<0.7 logMAR; OR (95%CI), 2.20 (1.25-3.81); P=0.006]. CONCLUSION: This retrospective study categorizes congenital cataracts into two distinct clusters, each associated with a different likelihood of visual outcomes. This innovative classification may enable the personalization and prioritization of early interventions for patients who may gain the greatest benefit, thereby making strides toward precision medicine in the field of congenital cataracts.

Using Cluster Analysis to Identify Metabolic Syndrome Components and Physical Fitness in Patients with Metabolic Syndrome.

Background: Metabolic syndrome (MetS) comprises a cluster of cardiovascular risk factors. Physical inactivity and reduced physical fitness are associated with one or more components of MetS. However, MetS has many components, and the unclear relationship between the components and physical fitness parameters can provide a plain and straightforward understanding of the clustering method. Aim: To identify the relationship between physical fitness parameters, physical activity levels, and components of MetS using hierarchical cluster analysis. Methods: One hundred twenty-one patients (mean age = 51.4 ± 7.1/years, F:90, M:31) who were diagnosed as having MetS according to the National Cholesterol Education Program-Adult Treatment Panel III (NCEP-ATP III) criteria were included in the study. Fasting plasma glucose (FPG), high-density lipoprotein cholesterol (HDL-C), and triglyceride (TG) were analyzed. Systolic and diastolic blood pressures, (SBP and DBP), were evaluated. Body composition (waist and hip circumference, (WC and HC), waist-to-hip ratio (WHR), body mass index (BMI), percent body fat, and visceral fat), upper and lower extremity muscle strength (dynamometer), and functional exercise capacity [6-minute walk test (6MWT)] were assessed as physical fitness parameters. Physical activity levels were assessed using a pedometer and number of steps (NS) was determined. Results: Of the patients, 45.5% were diagnosed as having MetS based on four components. The dendrogram consisted of two main clusters and four subclusters. The main cluster I composed of BMI, HC, WC, visceral fat, HDL-C, percent fat, SBP, DBP, and percent quadriceps. The main cluster II comprised FPG, TG, WHR, handgrip strength, 6MWT, and NS. Conclusion: MetS components clustered with different physical fitness parameters. The clusters in the dendrogram can provide substantial implications for heterogeneous MetS components and physical fitness parameters. Future studies are needed to elucidate the effectiveness of dendrogram-derived exercise programs in MetS.

Pre-crash scenarios for safety testing of autonomous vehicles: A clustering method for in-depth crash data.

Autonomous vehicles (AVs) provide an opportunity to enhance traffic safety. However, AVs market penetration is still restricted due to their safety concerns and dependability. For widespread adoption, it is crucial to thoroughly assess the safety response of AVs in various high-risk scenarios. To achieve this objective, a clustering method was used to construct typical testing scenarios based on the China In-depth Mobility Safety Study-Traffic Accident (CIMSS-TA) database. Initially, 222 car-to-powered two-wheelers (PTWs) crashes and 180 car-to-car crashes were reconstructed from CIMSS-TA database. Second, six variables were extracted and analyzed, including the motion of the two vehicles involved, relative movement, lighting condition, road condition, and visual obstruction. Third, these variables were clustered using the k-medoids algorithm, identifying five typical pre-crash scenarios for car-to-PTWs and seven for car-to-car. Additionally, we extracted the velocities and surrounding environmental information of the crash-involved parties to enrich the scenario description. The approach used in this study used in-depth case review and thus provided more insightful information for identifying and quantifying representative high-risk scenarios than prior studies that analyzed overall descriptive variables from Chinese crash databases. Furthermore, it is crucial to separately test car-to-car scenarios and car-to-PTWs scenarios due to their distinct motion characteristics, which significantly affect the resulting typical scenarios.

Analysing district-level climate vulnerability pattern in Madhya Pradesh, India, based on agricultural and socio-economic indicators.

Indian agriculture transitioned from a food deficit sector to a food surplus following the Green Revolution. However, the continued progress of Indian agriculture has been hampered by climate change. This research explores the district-wise vulnerability in Madhya Pradesh, India, to climate change by assessing the composite vulnerability index using the agricultural vulnerability index (AVI) and socio-economic vulnerability index (SEVI). The study seeks to understand how agricultural and socio-economic factors lead to variations in vulnerability across districts and influence targeted adaptation and mitigation strategies. The trend analysis results present declining rainfall and inclining temperature from 1951 to 2021 in Madhya Pradesh, directly affecting the agricultural sector and human livelihood. The composite vulnerability index (CVI) results revealed that districts with low values (< 0.394), such as Burhanpur and Balaghat, demonstrate reduced susceptibility due to limited cultivation, low reliance on rainfall, lower drought susceptibility, and decreased population density. Districts such as Panna and Bhopal show moderate vulnerability (0.394-0.423), with lower fallow land, reduced rainfed agriculture, and socio-economic vulnerability. Extensive agriculture and marginalised workers' presence influence high vulnerability (0.423 to 0.456) in districts such as Tikamgarh and Indore. Districts like Barwani and Jhabua have the highest CVI values (> 0.456), indicating substantial susceptibility to climate impacts. The cluster analysis validates the results of the vulnerability index. The findings highlight the urgent need for tailored adaptation strategies to address the diverse agricultural and socio-economic indicators creating vulnerability in Madhya Pradesh. The study helps understand regional vulnerability patterns and provides evidence-based policy approaches for resilience to climate change effects.

Clinical phenotypes of adult-onset Behçet's syndrome: a comprehensive cross-sectional study in China.

Behçet's syndrome (BS) is a variant vasculitis that can involve multiple organs with inflammatory manifestations. This study aimed to provide a more comprehensive analysis of the clinical phenotypes and characteristics of BS patients. We enrolled 2792 BS patients referred from China nationwide to Huadong Hospital Affiliated to Fudan University from October 2012 to December 2022. Detailed assessments of demographic information, clinical manifestations, laboratory results, gastroscopy, and medical imaging were conducted. Cluster analysis was performed based on 13 variables to determine the clinical phenotypes, and each phenotype was characterized according to the features of BS patients. A total of 1834 BS patients were included, while 958 invalid patients were excluded. The median age at onset was 31 years (IQR, 24-40 years), and the median disease duration was 10 years (IQR, 5-15 years). Eight clusters were identified, including mucocutaneous (n = 655, 35.7%), gastrointestinal (n = 363, 19.8%), articular (n = 184, 10%), ocular (n = 223, 12.2%), cardiovascular (n = 119, 6.5%), neurological (n = 118, 6.4%), vascular (n = 114, 6.2%), and hematological phenotype (n = 58, 3.2%). Ocular (RR = 1.672 (95% CI, 1.327-2.106); P < 0.001), gastrointestinal (RR = = 1.194 (95% CI, 1.031-1.383); P = 0.018), cardiovascular (RR = = 2.582 (95% CI, 1.842-3.620); P < 0.001), and vascular (RR = = 2.288 (95% CI, 1.600-3.272); P < 0.001) involvement were more prevalent in male BS patients, while the hematological (RR = 0.528 (95% CI, 0.360-0.776); P = 0.001) involvement was more common among female patients. BS presents significant heterogeneity and gender differences. The eight phenotypes of BS patients we propose hold the potential to assist clinicians in devising more personalized treatment and follow-up strategies. Key Points • This cluster analysis divided adult-onset BS into eight clinical phenotypes. • BS demonstrates a high level of clinical heterogeneity and gender differences. • Hematologic phenotypes of BS present distinctive clinical characteristics.

Classification of Healthy Family Indicators in Indonesia Based on a K-Means Cluster Analysis.

Objectives: Health development is a key element of national development. The goal of improving health development at the societal level will be readily achieved if it is directed from the smallest social unit, namely the family. This was the goal of the Healthy Indonesia Program with a Family Approach. The objective of the study was to analyze variables of family health indicators across all provinces in Indonesia to identify provincial disparities based on the status of healthy families. Methods: This study examined secondary data for 2021 from the Indonesia Health Profile, provided by the Ministry of Health of the Republic of Indonesia, and from the 2021 welfare statistics by Statistics Indonesia (BPS). From these sources, we identified 10 variables for analysis using the k-means method, a non-hierarchical method of cluster analysis. Results: The results of the cluster analysis of healthy family indicators yielded 5 clusters. In general, cluster 1 (Papua and West Papua Provinces) had the lowest average achievements for healthy family indicators, while cluster 5 (Jakarta Province) had the highest indicator scores. Conclusions: In Indonesia, disparities in healthy family indicators persist. Nutrition, maternal health, and child health are among the indicators that require government attention.

Characterization of CKD illness representation profiles using patient-level factors.

BACKGROUND: Illness perceptions are the unique perspective individuals have on their illness, based on their context and experiences, and are associated with patient outcomes including coping and adherence. The purpose of this study was to explore characteristics that may be driving membership in illness perceptions cluster groups for adults with chronic kidney disease (CKD). METHODS: This study was conducted within the multicenter longitudinal Chronic Renal Insufficiency Cohort (CRIC) Study. Cross-sectional data were collected and combined with CRIC data. Illness perceptions were measured using the Revised Illness Perception Questionnaire. Clustering analysis was conducted in R, and bivariate analysis including linear regression was performed in STATA 16. RESULTS: The sample (n = 197) had a mean age of 68, was 52% women, 53% non-White, and mean estimated glomerular filtration rate (eGFR) 56 ml/min/1.73 m2. Three cluster groups were identified, labeled as "Disengaged" (n = 20), "Well-Resourced" (n = 108), and "Distressed" (n = 69). The "Disengaged" group was characterized by low CKD knowledge, many recent hospitalization days, and the lowest perceived CKD burden. The "Well-Resourced" group was characterized by the highest levels of education, CKD knowledge, optimism, and medication adherence. The "Distressed" group was characterized by the highest levels of depression scores, comorbidity burden, CKD burden, CKD symptoms, and lowest optimism. Group membership significantly predicted the number of hospitalization days in adjusted analyses. CONCLUSIONS: Illness perceptions groups are associated with number of hospitalization days but are independent of many patient characteristics. Illness perceptions data could be used to tailor care for specific patients at risk for poor health outcomes.

Clinical phenotyping in patients with anti-synthetase antibodies using cluster analysis.

Objectives: To characterize clinically distinct subgroups among unselected patients with anti-synthetase antibodies using cluster analysis. Methods: This study evaluated patients with anti-synthetase antibodies registered to two independent cohorts; 106 consecutive patients from a prospective, single-centre cohort of the Scleroderma/Myositis Centre of Excellence (SMCE) were used as a derivation cohort and 125 patients from the Multicentre Retrospective Cohort of Japanese Patients with Myositis-Associated Interstitial Lung Disease (JAMI) were used as a validation cohort. Anti-synthetase antibodies were identified by RNA immunoprecipitation. A multiple correspondence analysis followed by hierarchical clustering was performed to aggregate the patients into homogeneous subgroups. Subsequently, a simple-to-use classification tree was generated using classification and regression tree analysis. Results: Three clusters were identified in the SMCE cohort: cluster 1 (n = 48), the interstitial pneumonia with autoimmune features/amyopathic dermatomyositis cluster, associated with older age at diagnosis and a higher frequency of malignancy; cluster 2 (n = 46), the DM cluster, corresponded to a younger age at diagnosis with a higher prevalence of myositis, arthritis, DM pathognomonic rashes, mechanic's hands and fever; and cluster 3 (n = 12), the SSc cluster, characterized by chronic interstitial lung disease. There was no significant difference in overall survival or progression-free survival between the clusters. A simple classification tree using myositis and RP was created in the SMCE cohort. Clusters 1 and 2 were successfully reproduced and the classification tree demonstrated favourable performance in the JAMI cohort. Conclusion: Patients with anti-synthetase antibodies were classified into three distinct phenotypes, indicating substantial heterogeneity within this patient group.

OneFlowTraX: a user-friendly software for super-resolution analysis of single-molecule dynamics and nanoscale organization.

Super-resolution microscopy (SRM) approaches revolutionize cell biology by providing insights into the nanoscale organization and dynamics of macromolecular assemblies and single molecules in living cells. A major hurdle limiting SRM democratization is post-acquisition data analysis which is often complex and time-consuming. Here, we present OneFlowTraX, a user-friendly and open-source software dedicated to the analysis of single-molecule localization microscopy (SMLM) approaches such as single-particle tracking photoactivated localization microscopy (sptPALM). Through an intuitive graphical user interface, OneFlowTraX provides an automated all-in-one solution for single-molecule localization, tracking, as well as mobility and clustering analyses. OneFlowTraX allows the extraction of diffusion and clustering parameters of millions of molecules in a few minutes. Finally, OneFlowTraX greatly simplifies data management following the FAIR (Findable, Accessible, Interoperable, Reusable) principles. We provide a detailed step-by-step manual and guidelines to assess the quality of single-molecule analyses. Applying different fluorophores including mEos3.2, PA-GFP, and PATagRFP, we exemplarily used OneFlowTraX to analyze the dynamics of plant plasma membrane-localized proteins including an aquaporin, the brassinosteroid receptor Brassinosteroid Insensitive 1 (BRI1) and the Receptor-Like Protein 44 (RLP44).

Influence of psychometric and sleep quality features on painful mechanical sensitivity and pain modulation in patients with temporomandibular disorders.

Investigating the collective impact of psychometric properties and sleep quality on pain sensitivity in temporomandibular disorder (TMD) patients could improve clinical management strategies. OBJECTIVE: Assessing whether combined psychometric properties and sleep quality impact painful mechanical sensitivity and pain modulation in TMD patients. MATERIALS AND METHODS: A cross-sectional study using secondary data analysis of 77 TMD patients and 101 controls. All participants completed questionnaires characterizing their psychometric profile (anxiety, depression, stress and catastrophizing) and sleep quality, alongside psychophysical tests for painful mechanical sensory (mechanical pain threshold (MPT), pressure pain threshold (PPT), and wind-up ratio (WUR)) and conditioned pain modulation (CPM). Participants were grouped into "High distress" or "Low distress" categories based on psychometric properties and sleep quality using hierarchical cluster and k-means analyses. Multiple linear regression evaluated the influence of TMD, age, and the distress cluster on MPT, WUR, PPT, and CPM in masseter and thenar muscles. Differences were statistically significant when p < 0.05. RESULTS: The presence of TMD was the strongest predictor of mechanical painful sensitivity in the trigeminal region (MPT[F(3,174) = 51.902;p < .001;R2 = .463]; TMD presence (ß = -.682) / PPT[F(3,174) = 15.573;p < .001;R2 = .198] TMD presence (ß = -.452), and extra-trigeminal (MPT[F(3,174) = 35.897;p < .001;R2 = .382] TMD (ß = -.647) / CPM [F(3,174) = 4.106;p < .05;R2 = .050] TMD presence (ß = .197). Furthermore, neither the high distress group nor the low distress group were able to significantly influence the variation of the values of any of the psychophysical variables evaluated (p > .05). CONCLUSIONS: There is not a significant influence of impairment clusters based on psychological variables and sleep quality on painful mechanical sensitivity and pain modulation, regardless of the presence of TMD. CLINICAL RELEVANCE: This outcome suggests that psychosocial factors and sleep quality may not play a decisive role in the sensory-discriminative aspect of pain, particularly concerning painful TMD.

Cluster analysis of medical students' attitudes regarding people who use drugs: a first step to design a tailored education program.

INTRODUCTION: People with substance use disorder (SUD) deal with stigmatization in various areas of life, including healthcare system. In this study, we investigated the attitudes of final-year medical students towards SUD people and attempted to understand their influence. METHODS: We conducted a two-stage cluster analysis (hierarchical ascending classification followed by K-means clustering) based on the "beSAAS". We administrated this 23-item questionnaire to 923 final-year medical students in Belgium (response rate = 71,1%). Sociodemographic characteristics were compared between the clusters. RESULTS: Four clusters of students with specific characteristics were identified in this study. The first, "The Inclusives" (including 27,9% of respondents) had the least negative attitudes; they wanted to specialize mainly in psychiatry and gynecology. The second, "The Centrists" (23,6%) consisted mainly of male students. They had many private and professional experiences with substance use and considered themselves less healthy than others did. Most wanted to specialize in pediatrics and general practice. Their attitudes were slightly negative towards people with SUD. The third, "The Moralists" (27,6%), were mainly older, from non-European countries, had the least experience with substance use (or contact mainly in hospitals), had the less high mother's level of education and reported excellent health. They were heading toward other specialties. They had the most stereotypes and moralism, and less treatment optimism. The fourth, "The Specialist care-oriented" (20,8%), were the most in favor of specialized treatment. This group had a higher proportion of Belgian, females, and students who had specific contact with this population. They especially intended to specialize in internal medicine. CONCLUSION: This study revealed 4 profiles of medical students with different attitudes towards SUD people. "The Moralists", including more than a quarter of the respondents, were characterized by strong stereotypes and moralism and little treatment optimism. These clusters could contribute to the design of a learner-centered program aimed at addressing stigma within the main curriculum.

Clustering evaluation of water quality for various classes of in-flow rivers in connected brackish lakes.

Brackish waters and estuaries at the lower reaches of rivers accumulate organic matter and nutrients from various sources in the watershed. Sufficient light and shallow water depth stimulate phytoplankton growth, resulting in a more diversified ecosystem with higher trophic levels. For effective watershed management, it is crucial to characterize the water quality of all rivers, including small and medium-sized ones. Our field survey assessed water quality parameters in 26 inflow rivers surrounding Lakes Shinji and Nakaumi, two consolidated brackish lakes in Japan. The parameters included water temperature, salinity, chlorophyll-a, and nutrients. The study used hierarchical clustering. The Silhouette Index was used to assess clustering outcomes and identify any difficulties in dispersion across clusters. The 26 rivers surrounding Lakes Shinji and Nakaumi were classified into six groups based on their water quality characteristics. This classification distinguishes itself from earlier subjective methods that relied on geographical factors. The new approach identifies a need for improved management of river water quality. The results of the cluster analysis provide valuable insights for future management initiatives. It is important to consider these findings alongside established watershed criteria.

Chemical Characterization of the Essential Oil Compositions of Mentha spicata and M. longifolia ssp. cyprica from the Mediterranean Basin and Multivariate Statistical Analyses.

This present study aims to characterize the essential oil compositions of the aerial parts of M. spicata L. and endemic M. longifolia ssp. cyprica (Heinr. Braun) Harley by using GC-FID and GC/MS analyses simultaneously. In addition, it aims to perform multivariate statistical analysis by comparing with the existing literature, emphasizing the literature published within the last two decades, conducted on both species growing within the Mediterranean Basin. The major essential oil components of M. spicata were determined as carvone (67.8%) and limonene (10.6%), while the major compounds of M. longifolia ssp. cyprica essential oil were pulegone (64.8%) and 1,8-cineole (10.0%). As a result of statistical analysis, three clades were determined for M. spicata: a carvone-rich chemotype, a carvone/trans-carveol chemotype, and a pulegone/menthone chemotype, with the present study result belonging to the carvone-rich chemotype. Carvone was a primary determinant of chemotype, along with menthone, pulegone, and trans-carveol. In M. longifolia, the primary determinants of chemotype were identified as pulegone and menthone, with three chemotype clades being pulegone-rich, combined menthone/pulegone, and combined menthone/pulegone with caryophyllene enrichment. The primary determinants of chemotype were menthone, pulegone, and caryophyllene. The present study result belongs to pulegone-rich chemotype.

Intrauterine twin environment and genetic factors subliminally affecting general movements in preterm infants.

BACKGROUND: Understanding background factors is beneficial for interpreting general movements (GMs). This study examines the factors involved in preterm-writhing GMs by comparing twins and singletons. METHOD: The subjects were 107 infants cared for at Oita University. The cohort consisted of very-low-birth-weight infants, including twins with a birth weight < 2000 g. The median gestational age (GA) was 29 weeks 1 day. The subjects consisted of 75 singletons, 32 twins (16 pairs), 20 monochorionic twins (M-twins), and 12 dichorionic twins (D-twins). GMs were scored according to the GMs optimality score (GMOS) and integrated into 6 items: the quality, neck-trunk and space, amplitude-speed, rotation, onset-offset and cramped, and tremulous score at 32-34 weeks, 35-36 weeks, and 37-42 weeks' GA. A hierarchical cluster analysis was performed using integrated GMOS, and the characteristics of clusters were examined according to clinical backgrounds. RESULTS: Three clusters were identified. Cluster 1 was characterized by good-quality GMs, cluster 2 by a poor repertoire but optimal space and rotatory components, and cluster 3 by overall poor-quality GMs, respectively. The mean GMOSs were 36.6, 31.8 and 24.3 in clusters 1, 2, and 3, respectively. There were no marked differences in proportions within clusters with respect to sex and twins. Small-for-gestational age (SGA) was significantly more frequent in cluster 3 at 32-34 weeks' GA than in other clusters. Perinatal brain injury had a significantly lower proportion in cluster 1 and a higher proportion in cluster 3 at 35-36 weeks' GA and 37-42 weeks' GA. M-twin pairs tended to belong to the same clusters at 35-36 weeks' GA. CONCLUSION: Preterm writhing GMs are associated with SGA and perinatal brain injury. Cluster matching in M-twins suggests that certain genetic factors may substantially influence GMs.

Multivariate analysis applied to X-ray fluorescence to assess soil contamination pathways: case studies of mass magnetic susceptibility in soils near abandoned coal and W/Sn mines.

Determining the origin and pathways of contaminants in the natural environment is key to informing any mitigation process. The mass magnetic susceptibility of soils allows a rapid method to measure the concentration of magnetic minerals, derived from anthropogenic activities such as mining or industrial processes, i.e., smelting metals (technogenic origin), or from the local bedrock (of geogenic origin). This is especially effective when combined with rapid geochemical analyses of soils. The use of multivariate analysis (MVA) elucidates complex multiple-component relationships between soil geochemistry and magnetic susceptibility. In the case of soil mining sites, X-ray fluorescence (XRF) spectroscopic data of soils contaminated by mine waste shows statistically significant relationships between magnetic susceptibility and some base metal species (e.g., Fe, Pb, Zn, etc.). Here, we show how qualitative and quantitative MVA methodologies can be used to assess soil contamination pathways using mass magnetic susceptibility and XRF spectra of soils near abandoned coal and W/Sn mines (NW Portugal). Principal component analysis (PCA) showed how the first two primary components (PC-1 + PC-2) explained 94% of the sample variability, grouped them according to their geochemistry and magnetic susceptibility in to geogenic and technogenic groups. Regression analyses showed a strong positive correlation (R2 > 0.95) between soil geochemistry and magnetic properties at the local scale. These parameters provided an insight into the multi-element variables that control magnetic susceptibility and indicated the possibility of efficient assessment of potentially contaminated sites through mass-specific soil magnetism.