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Managing patients with kidney allografts largely depends on biopsy diagnosis which is based on semiquantitative assessments of rejection features and extent of acute and chronic changes within the renal parenchyma. Current methods lack reproducibility while digital image data-driven computational models enable comprehensive and quantitative assays. In this study we aimed to develop a computational method for automated assessment of histopathology transformations within the tubulointerstitial compartment of the renal cortex. Whole slide images of modified Picrosirius red-stained biopsy slides were used for the training (n = 852) and both internal (n = 172) and external (n = 94) tests datasets. The pipeline utilizes deep learning segmentations of renal tubules, interstitium, and peritubular capillaries from which morphometry features were extracted. Seven indicators were selected for exploring the intrinsic spatial interactions within the tubulointerstitial compartment. A principal component analysis revealed two independent factors which can be interpreted as representing chronic and acute tubulointerstitial injury. A K-means clustering classified biopsies according to potential phenotypes of combined acute and chronic transformations of various degrees. We conclude that multivariate analyses of tubulointerstitial morphometry transformations enable extraction of and quantification of acute and chronic components of injury. The method is developed for renal allograft biopsies; however, the principle can be applied more broadly for kidney pathology assessment.

This is a prospective case-control study investigated the factors influencing ultra-early visual acuity and quality after Small Incision Lenticule Extraction (SMILE) surgery, with a specific focus on the morphology and distribution of "black clefts" observed in posterior lenticule laser scanning images. A total of 174 patients who underwent SMILE surgery were included, and their preoperative ocular clinical parameters, visual quality indicators, and posterior lenticule laser scanning images were analyzed. The morphological features of black clefts were calculated using image processing techniques. Univariate and multivariate logistic analyses were conducted to identify factors impacting ultra-early visual acuity recovery, while correlation analysis was used to explore the association between black cleft morphology and postoperative visual quality. The results showed that although patients experienced significant visual acuity improvement one day after surgery, 26% had poor early recovery. Postoperative visual quality parameters were significantly lower, while the Object Scatter Index (OSI) was higher compared to preoperative values. Patients with poor visual recovery had a higher number of irregular black clefts in their laser scanning images. Logistic regression analysis revealed that intraoperative morphological parameters of black clefts were independent factors influencing early postoperative visual acuity recovery. Additionally, correlation analysis demonstrated a negative correlation between black cleft morphology and postoperative visual quality parameters, and a positive correlation with OSI. In conclusion, the morphology and distribution of black clefts during SMILE surgery significantly affect ultra-early postoperative visual acuity and quality, with increased variability in black cleft area leading to higher OSI, thereby impacting visual quality recovery. [ABSTRACT FROM AUTHOR]

Pilocytic astrocytoma (PA) is classified as a Grade I benign neuroglial tumor. The extent of surgical resection is a critical factor influencing the prognosis for patients with PA. In prior researches of PA, the extent of surgical resection is generally categorized into GTR, STR and biopsy. In some researches on brain tumor surgeries, the extent of resection also includes GTL. There is no existing research specifically comparing the efficacy of GTR versus GTL in PA treatment. In this study, the data we used are from the SEER database. We categorized the extent of resection into GTL, GTR, STL, STR, biopsy, and no surgery based on SEER classification of surgical procedures, to investigate the impact of extent of resection on PA patient survival. A multivariate logistic regression model was utilized to acquire odds ratios (OR) for different extent of resection. Survival outcomes across different extent of resection (GTL, GTR, STL, STR, biopsy, no surgery) were assessed using Kaplan–Meier survival curve analysis, with curve comparisons conducted via log-rank tests. The impact of various risk factors on survival was assessed using the Cox proportional hazards model. The hazard ratio (HR) was employed to quantify the influence of one or more factors on overall survival throughout the follow-up period. Multivariate Cox analysis revealed that age, tumor location, extent of resection, as well as the application of radiotherapy and chemotherapy, all significantly impacted prognosis. Compared to GTL, GTR did not significantly increase the risk of mortality (HR 1.17; 95% CI 0.73–1.86, p = 0.5). Furthermore, there was no statistically significant difference between the Kaplan–Meier survival curves of the two groups (p = 0.18). We employed propensity score matching (PSM) to balance the differences in baseline characteristics of patients receiving chemotherapy or radiotherapy. A total of 4429 patients were included in this study. Age, diagnosis period, race, tumor size, and tumor location as influential on the extent of resection. Age, tumor location, extent of resection, and application of radiotherapy and chemotherapy influenced the survival of PA patients. The Kaplan–Meier survival curves revealed that the long-term survival rate for GTR is slightly higher than that for GTL. The PSM analysis revealed that the application of radiotherapy and chemotherapy was associated with the reduction of overall survival in PA patients. In conclusion, there was no significant difference in survival between GTR and GTL, so GTR with less damage was preferred. The application of radiotherapy and chemotherapy can reduce overall survival of patients with PA. [ABSTRACT FROM AUTHOR]

This study evaluates the efficacy of photodynamic therapy (PDT) in treating central serous chorioretinopathy (CSC) based on the number of engorged vortex vein draining macula visualized on ultra-widefield (UWF) indocyanine green angiography (ICGA). Thirty-six eyes of 36 patients with treatment-naïve CSC were included. Macula-draining vortex veins were assessed in each quadrant using UWF ICGA. The resolution of subretinal fluid (SRF), pigment epithelial detachment (PED), ellipsoid zone (EZ) disintegrity, and retinal pigment epithelium (RPE) irregularity were evaluated at 3 months after PDT. Visual and anatomical improvements were monitored for 12 months. Logistic regression analysis was performed to identify factors associated with poor visual outcomes. A higher number of macula-draining vortex vein was associated to persistent SRF (p = 0.004), PED (p = 0.001), EZ disintegrity (p = 0.011), and RPE irregularity (p = 0.001). Macula-draining vortex veins were also correlated with poor EZ restoration and limited best corrected visual acuity (BCVA) improvements. In multivariate analysis, the number of macula-draining vortex vein (B = 0.197, p = 0.047) was a risk factor for worse BCVA at 12 months. Increased macula-draining vortex vein was related with unfavorable anatomical and poor visual outcomes after PDT in CSC patients. [ABSTRACT FROM AUTHOR]

Explicit identification of hydrochemical processes and their controlling factors within groundwater systems is critical for the sustainable utilization of water resources in coastal urban areas. This study was undertaken in the North Coastal Region of Jiaozhou Bay (NCRJB), located in the eastern part of Shandong Province, China, an area grappling with significant issues of groundwater quality degradation and water scarcity. A total of 105 groundwater samples and 34 surface water samples, collected from 2020 to 2024, were analyzed and studied using various hydrogeological tools, multivariate statistical analyses, and water quality assessment methods. These include the Piper diagram, hydrochemical facies evolution diagram (HFE-D), Principal Components Analysis (PCA), correlation analysis, stable isotope analysis, Water Quality Index (WQI), and USSL diagrams. The results indicated that all surface water and pore groundwater samples were categorized as Na-Cl type, exhibiting high Total Dissolved Solids (TDS) and Electrical Conductivity (EC) values, characteristics that render them poor to unsuitable for drinking and irrigation purposes. The fracture groundwater is predominantly of the Ca-Na-Cl mixed type, with average suitability for irrigation and a limited proportion (22.5%) deemed suitable for drinking. Seawater intrusion, primarily through the surface water system, and the impact of human activities were identified as the predominant controlling factors con-tributing to the degradation of the local groundwater environment. Field empirical investigations further validated the results derived from hydrogeological assessments, multivariate statistical analyses, and isotopic approaches. The long-term shifts in hydrochemical properties, along with the latent threat of seawater intrusion, exhibit an upward trend during the dry season and show a certain degree of mitigation during the wet season. This study highlights that field investigations, in conjunction with hydrochemical tools, multivariate statistical analyses, and stable isotope analysis, can successfully furnish reliable insights into the predominant mechanisms governing regional groundwater evolution within the context of long-term and intricate envi-ronmental settings. [ABSTRACT FROM AUTHOR]

Angiogenesis, metastasis, and resistance to therapy are all facilitated by cancer-associated fibroblasts (CAFs). A CAF-based risk signature can be used to predict patients' prognoses for Lung adenocarcinoma (LUAD) based on CAF characteristics. The Gene Expression Omnibus (GEO) database was used to gather signal-cell RNA sequencing (scRNA-seq) data for this investigation. The GEO and TCGA databases were used to gather bulk RNA-seq and microarray data for LUAD. The scRNA-seq data were analyzed using the Seurat R program based on the CAF markers. Our goal was to use differential expression analysis to discover differentially expressed genes (DEGs) across normal and tumor samples in the TCGA dataset. Pearson correlation analysis was utilized to discover prognostic genes related with CAF, followed by univariate Cox regression analysis. Using Lasso regression, a risk signature based on CAF-related prognostic genes was created. A nomogram model was created based on the clinical and pathological aspects. 5 CAF clusters were identified in LUAD, 4 of which were associated with prognosis. From 2811 DEGs, 1002 genes were found to be significantly correlated with CAF clusters, which led to the creation of a risk signature with 8 genes. These 8 genes were primarily connected with 41 pathways, such as antigen paocessing and presentation, apoptosis, and cell cycle. Meanwhile, the risk signature was significantly associated with stromal and immune scores, as well as some immune cells. Multivariate analysis revealed that risk signature was an independent prognostic factor for LUAD, and its value in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the stage and CAF-based risk signature was constructed, which exhibited favorable predictability and reliability in the prognosis prediction of LUAD. CAF-based risk signatures can be effective in predicting the prognosis of LUAD, and they may provide new strategies for cancer treatments by interpreting the response of LUAD to immunotherapy. [ABSTRACT FROM AUTHOR]

Intracranial pressure (ICP) is a physiological parameter that conventionally requires invasive monitoring for accurate measurement. Utilising multivariate predictive models, we sought to evaluate the utility of non-invasive, widely accessible MRI biomarkers in predicting ICP and their reversibility following cerebrospinal fluid (CSF) diversion. The retrospective study included 325 adult patients with suspected CSF dynamic disorders who underwent brain MRI scans within three months of elective 24-h ICP monitoring. Five MRI biomarkers were assessed: Yuh sella grade, optic nerve vertical tortuosity (VT), optic nerve sheath distension, posterior globe flattening and optic disc protrusion (ODP). The association between individual biomarkers and 24-h ICP was examined and reversibility of each following CSF diversion was assessed. Multivariate models incorporating these radiological biomarkers were utilised to predict 24-h median intracranial pressure. All five biomarkers were significantly associated with median 24-h ICP (p < 0.0001). Using a pair-wise approach, the presence of each abnormal biomarker was significantly associated with higher median 24-h ICP (p < 0.0001). On multivariate analysis, ICP was significantly and positively associated with Yuh sella grade (p < 0.0001), VT (p < 0.0001) and ODP (p = 0.003), after accounting for age and suspected diagnosis. The Bayesian multiple linear regression model predicted 24-h median ICP with a mean absolute error of 2.71 mmHg. Following CSF diversion, we found pituitary sella grade to show significant pairwise reversibility (p < 0.001). ICP was predicted with clinically useful precision utilising a compact Bayesian model, offering an easily interpretable tool using non-invasive MRI data. Brain MRI biomarkers are anticipated to play a more significant role in the screening, triaging, and referral of patients with suspected CSF dynamic disorders. [ABSTRACT FROM AUTHOR]

To investigate the incidence and risk factors for neovascular glaucoma (NVG) after vitrectomy in patients with proliferative diabetic retinopathy (PDR). Patients were categorized into two subgroups based on their treatment regimen: one group received vitrectomy only (Group 1), while the other received combined phacovitrectomy (Group 2). A comparative analysis was conducted to evaluate the distinguishing characteristics of the two groups. Kaplan-Meier survival analysis was used to determine the incidence of NVG following surgery. Furthermore, multivariate analysis using the Cox proportional hazards model was conducted to identify the risk factors associated with the development of NVG after surgery. A total of 484 eyes of 484 patients were included in the study. When comparing Group 1 with Group 2, a significant difference was observed in the occurrence of NVG. In Group 1, there were 10 cases of NVG (3.9%), whereas 29 cases of NVG occurred in Group 2 (12.71%). Male sex, high preoperative intraocular pressure (IOP), and combined phacovitrectomy were found to be associated with the occurrence of NVG following phacovitrectomy. Higher creatinine levels had a protective effect in preventing the development of NVG. Male sex, high preoperative IOP, and combined phacovitrectomy were associated with a high incidence of NVG. Explore strategies to prevent NVG is important when performing combined phacovitrectomy in patients with PDR. [ABSTRACT FROM AUTHOR]

Sorghum is the world’s fifth-largest cereal crop, and anthracnose (Colletotrichum sublineola) is the main disease affecting sorghum. However, systematic research on the cellular structure, physiological and biochemical, and genes related to anthracnose resistance and disease resistance evaluation in sorghum is lacking in the field. Upon inoculation with anthracnose (C. sublineola) spores, disease-resistant sorghum (gz93) developed a relative lesion area (RLA) that was significantly smaller than that of the disease-susceptible sorghum (gz234). The leaf thickness, length and profile area of leaf mesophyll cells, upper and lower epidermal cells decreased in the lesion area, with a greater reduction observed in gz234 than in gz93. The damage caused by C. sublineola resulted in a greater decrease in the net photosynthetic rate (Pn) in gz234 than in gz93, with early-stage reduction due to stomatal limitation and late-stage reduction caused by lesions. Overall, the activities of superoxide dismutase (SOD) and catalase (CAT), the content of proline (Pro), abscisic acid (ABA), jasmonic acid (JA), salicylic acid (SA), and gibberellic acid (GA3), are higher in gz93 than in gz234 and may be positively correlated with disease resistance. While malondialdehyde (MDA) may be negatively correlated with disease resistance. Disease-resistant genes are significantly overexpressed in gz93, with significant expression changes in gz234, which is related to disease resistance in sorghum. Correlation analysis indicates that GA3, MDA, peroxidase (POD), and disease-resistance genes can serve as reference indicators for disease severity. The regression equation RLA = 0.029 + 8.02 × 10−6 JA–0.016 GA3 can predict and explain RLA. Principal component analysis (PCA), with the top 5 principal components for physiological and biochemical indicators and the top 2 principal components for disease-resistant genes, can explain 82.37% and 89.11% of their total variance, reducing the number of evaluation indicators. This study provides a basis for research on the mechanisms and breeding of sorghum with resistance to anthracnose. [ABSTRACT FROM AUTHOR]

Goal-directed memory reactivation involves retrieving the most relevant information for the current behavioral goal. Previous research has linked this process to activations in the fronto-parietal network, but the underlying neurocognitive mechanism remains poorly understood. The current electroencephalogram (EEG) study explores attentional selection as a possible mechanism supporting goal-directed retrieval. We designed a long-term memory experiment containing three phases. First, participants learned associations between objects and two screen locations. In a following phase, we changed the relevance of some locations (selective cue condition) to simulate goal-directed retrieval. We also introduced a control condition, in which the original associations remained unchanged (neutral cue condition). Behavior performance measured during the final retrieval phase revealed faster and more confident responses in the selective vs. neutral condition. At the EEG level, we found significant differences in decoding accuracy, with above-chance effects in the selective cue condition but not in the neutral cue condition. Additionally, we observed a stronger posterior contralateral negativity and lateralized alpha power in the selective cue condition. Overall, these results suggest that attentional selection enhances task-relevant information accessibility, emphasizing its role in goal-directed memory retrieval. [ABSTRACT FROM AUTHOR]

This study was intended to investigate the macular vascular and photoreceptor changes for diabetic macular edema (DME) at the early stage. A total of 255 eyes of 134 diabetes mellitus patients were enrolled and underwent an ophthalmological and systemic evaluation in this cross-sectional study. Early DME was characterized by central subfoveal thickness (CST) value between 250 and 325 μm, intact ellipsoid zone, and an external limiting membrane. While non-DME was characterized by CST < 250 μm with normal retinal morphology and structure. Foveal avascular zone (FAZ) area ≤ 0.3 mm2 (P < 0.001, OR = 0.41, 95% CI 0.26–0.67 in the multivariate analysis) and HbA1c level ≤ 8% (P = 0.005, OR = 0.37, 95% CI 0.19–0.74 in multivariate analysis) were significantly associated with a higher risk of early DME. Meanwhile, no significant differences exist in cone parameters between non-DME and early DME eyes. Compared with non-DME eyes, vessel diameter, vessel wall thickness, wall-to-lumen ratio, the cross-sectional area of the vascular wall in the upper side were significantly decreased in the early DME eyes (P = 0.001, P < 0.001, P = 0.005, P = 0.003 respectively). This study suggested a vasospasm or vasoconstriction with limited further photoreceptor impairment at the early stage of DME formation. CST ≥ 250 μm and FAZ ≤ 0.3 mm2 may be the indicator for early DME detection. [ABSTRACT FROM AUTHOR]

Abstract In this study, a comprehensive methodology combining machine learning and statistical analysis was employed to investigate alterations in the metabolite profiles, including lipids, of breast cancer tissues and their subtypes. By integrating biological and machine learning feature selection techniques, along with univariate and multivariate analyses, a notable lipid signature was identified in breast cancer tissues. The results revealed elevated levels of saturated and monounsaturated phospholipids in breast cancer tissues, consistent with external validation findings. Additionally, lipidomics analysis in both the original and validation datasets indicated lower levels of most triacylglycerols compared to non-cancerous tissues, suggesting potential alterations in lipid storage and metabolism within cancer cells. Analysis of cancer subtypes revealed that levels of PC 30:0 were relatively reduced in HER2(−) samples that were ER(+) and PR(+) compared to those that were ER(−) and PR(−). Conversely, HER2(+) tumors, which were ER(−) and PR(−), exhibited increased concentrations of PC 30:0. This increase could potentially be linked to the role of Stearoyl-CoA-Desaturase 1 in breast cancer. Comprehensive metabolomic analyses of breast cancer can offer crucial insights into cancer development, aiding in early detection and treatment evaluation of this devastating disease.

Abstract Sorghum is the world’s fifth-largest cereal crop, and anthracnose (Colletotrichum sublineola) is the main disease affecting sorghum. However, systematic research on the cellular structure, physiological and biochemical, and genes related to anthracnose resistance and disease resistance evaluation in sorghum is lacking in the field. Upon inoculation with anthracnose (C. sublineola) spores, disease-resistant sorghum (gz93) developed a relative lesion area (RLA) that was significantly smaller than that of the disease-susceptible sorghum (gz234). The leaf thickness, length and profile area of leaf mesophyll cells, upper and lower epidermal cells decreased in the lesion area, with a greater reduction observed in gz234 than in gz93. The damage caused by C. sublineola resulted in a greater decrease in the net photosynthetic rate (Pn) in gz234 than in gz93, with early-stage reduction due to stomatal limitation and late-stage reduction caused by lesions. Overall, the activities of superoxide dismutase (SOD) and catalase (CAT), the content of proline (Pro), abscisic acid (ABA), jasmonic acid (JA), salicylic acid (SA), and gibberellic acid (GA3), are higher in gz93 than in gz234 and may be positively correlated with disease resistance. While malondialdehyde (MDA) may be negatively correlated with disease resistance. Disease-resistant genes are significantly overexpressed in gz93, with significant expression changes in gz234, which is related to disease resistance in sorghum. Correlation analysis indicates that GA3, MDA, peroxidase (POD), and disease-resistance genes can serve as reference indicators for disease severity. The regression equation RLA = 0.029 + 8.02 × 10−6 JA–0.016 GA3 can predict and explain RLA. Principal component analysis (PCA), with the top 5 principal components for physiological and biochemical indicators and the top 2 principal components for disease-resistant genes, can explain 82.37% and 89.11% of their total variance, reducing the number of evaluation indicators. This study provides a basis for research on the mechanisms and breeding of sorghum with resistance to anthracnose.

Abstract The interpretation of emotional facial expressions is crucial in everyday social interactions, and rapid processing of these expressions is necessary. Although extensive research has shed light on the mechanisms involved in facial expression processing, there is limited research on the potential role of the state of neural activity that directly precedes the occurrence of a face. Here, we investigated the potential modulatory role of pre-stimulus oscillatory activity in emotional facial expression processing. We tested emotional facial processing in two experiments, one utilizing artificial and the other natural facial expressions. The participants had to evaluate the emotional valence of the presented ambiguous facial expressions. In a univariate analysis, differences in the oscillation activity of the later rated valence of the faces were observed in both experiments, and these differences were observed even before the presentation of the facial expressions. Importantly, two different multivariate approaches directly supported the relevance of pre-stimulus oscillatory activity by exclusively using pre-stimulus oscillatory data to predict the perceived valence of the latter rated facial expression across the two experiments within as well as across subjects. The behavioral data shows the often observed negativity bias, i.e. ambiguous faces resulted in the tendency to rate them as negative. This negativity bias was related to neural activity modulations in the pre-stimulus period and also within post-stimulus processing related activity. These findings underscore the significance of pre-stimulus oscillatory activity in facial expression processing, indicating a functional role of ongoing neural states that affects the processing of facial expressions and constitute a basis for the well described negativity bias.

Abstract High and low pathogenicity avian influenza viruses (HPAIV, LPAIV) are the primary causes of poultry diseases worldwide. HPAIV and LPAIV constitute a major threat to the global poultry industry. Therefore, early detection and well-adapted surveillance strategies are of the utmost importance to control the spread of these viruses. Volatile Organic Compounds (VOCs) released from living organisms have been investigated over the last decades as a diagnostic strategy. Mass spectrometry instruments can analyze VOCs emitted upon viral infection. Selected ion flow tube mass spectrometry (SIFT-MS) enables direct analysis of cell headspace in less than 20 min. As a proof-of-concept study, we investigated the ability of a SIFT-MS coupled sparse Partial Least Square-Discriminant Analysis analytical workflow to discriminate IAV-infected cells. Supernatants of HPAIV, LPAIV, and control cells were collected from 1 to 72 h post-infection and analyzed using our analytical workflow. At each collection point, VOCs' signatures were first identified based on four independent experiments and then used to discriminate the infectious status of external samples. Our results indicate that the identified VOCs signatures successfully discriminate, as early as 1-h post-infection, infected cells from the control cells and differentiated the HPAIV from the LPAIV infection. These results suggest a virus-dependent VOCs signature. Overall, the external samples' status was identified with 96.67% sensitivity, 100% specificity, and 97.78% general accuracy.

Abstract Understanding the distribution of the plant species of an unexplored area is the utmost need of the present-day. In order to collect vegetation data, Quadrat method was used having size of 1 m2. The composite soil samples from each site were tested for various edaphic properties. PC-ORD v.5 was used for the classification of the vegetation while CANOCO v.5.1 was used for ordination of the data and to find out the complex relationship between plants and environment. Survey was conducted during summer season and a total of 216 herbaceous species were recorded from forty different sites of District Kohat, Pakistan. Cluster Analysis (CA) and Two-Way Cluster Analysis (TWCA) classified the vegetation of forty sites into six major plant groups i.e., 1. Paspalum paspalodes, Alternanthera sessilis, Typha domingensis, 2. Cynodon dactylon, Parthenium hysterophorus, Brachiaria ramosa, 3. Cynodon dactylon, Eragrostis minor, Cymbopogon jwarancusa, 4. Cymbopogon jwarancusa, Aristida adscensionis, Boerhavia procumbens, 5. Cymbopogon jwarancusa, Aristida adscensionis, Pennisetum orientale and 6. Heteropogon contortus, Bothriochloa ischaemum, Chrysopogon serrulatus. They were named after the dominant species based on their Importance Value (IV). The detrended correspondence analysis (DCA) analysis further confirmed the vegetation classification. Canonical correspondence analysis (CCA) indicated that the species distribution in the area was strongly affected by various environmental factors including status, soil characteristics, topography and altitude.

Abstract This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980–81 to 2020–21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices.

Eucalyptus species play an important role in the global carbon cycle, especially in reducing the greenhouse effect as well as storing atmospheric CO₂. Thus, assessing the amount of CO₂ released by the soil in forest areas can generate important information for environmental monitoring. This study aims to verify the relation between soil carbon dioxide (CO₂) flux (FCO₂), spectral bands, and vegetation indices (VIs) derived from a UAV-based multispectral camera over an area of eucalyptus species. Multispectral imageries (green, red-edge, and near-infrared) from the Parrot Sequoia sensor, derived vegetation indices, and the FCO₂ data from a LI-COR 8100 analyzer, combined with soil moisture and temperature data, were collected and related. The vegetation indices ATSAVI (Adjusted Transformed Soil-Adjusted VI), GSAVI (Green Soil Adjusted Vegetation Index), and SAVI (Soil-Adjusted Vegetation Index), which use soil correction factors, exhibited a strong negative correlation with FCO₂ for the species E. camaldulensis, E. saligna, and E. urophylla species. A Multivariate Analysis of Variance showed significance (p < 0.01) for the species factor, which indicates that there are differences when considering all variables simultaneously. The results achieved in this study show a specific correlation between the data of soil CO₂ emission and the eucalypt species, providing a distinction of values between the species in the statistical data. [ABSTRACT FROM AUTHOR]

This retrospective cohort study describes the real-world incidence and maintenance of clinically meaningful intraocular pressure (IOP) reduction ("response") following stand-alone phacoemulsification for 667,987 eyes with suspected or confirmed glaucoma in the IRIS Registry (Intelligent Research in Sight) from 1/1/2013–9/30/2019. Intraocular pressure responders had ≥ 20% IOP reduction in daily mean IOP from baseline on two consecutive postoperative visits. We declared failure if a responder no longer maintained ≥ 20% IOP reduction. The estimated IOP responder rate was 41.3% by Kaplan–Meier analysis. Multivariate analysis demonstrated relationships between IOP response and baseline IOP (hazard ratio (HR) (95% confidence interval)) 1.48 (1.48–1.49), per 3 mmHg, P < 0.0001), age (HR 1.14 (1.13–1.14), per 10 years, P < 0.0001), male sex (HR 1.13 (1.12–1.15), P < 0.0001), prostaglandin analogue (HR 0.88 (0.87–0.90), P < 0.0001), and Rho-kinase inhibitor use (HR 1.50 (1.32–1.70), P = 0.01). Fifty percent of IOP responders failed at a median time of 14.3 months. Multivariate analysis demonstrated relationships between failure and baseline IOP (HR 0.75 (0.75–0.76), per 3 mmHg, P < 0.0001), nitric oxide donating prostaglandin (HR 1.78 (1.46–2.18), P < 0.0001) and Rho-kinase inhibitor use (HR 1.73 (1.43–2.09), P < 0.0001). Clinicians may counsel glaucoma patients with risk factors on whether to anticipate an IOP response and its expected duration after stand-alone phacoemulsification. [ABSTRACT FROM AUTHOR]

Large White and Meishan sows differ in maternal ability and early piglet growth. We investigated the relationships between 100 maternal traits, grouped into 11 blocks according to the biological function they describe and litter growth over three successive periods after birth (D0–D1, D1–D3 and D3–D7; D0 starting at the onset of farrowing), as a measure of sow investment in early piglet production. Within- and between-breed variation was exploited to cover a maximum of the variability existing in pig maternal populations. The objective was to quantify the contribution of maternal traits, including functional traits and behavioural traits, to early litter growth. Multivariate analyses were used to depict correlations among traits. A partial least square multiblock analysis allowed quantifying the effect of maternal traits on early growth traits. Partial triadic analyses highlighted how sow behaviour changed with days, and whether it resulted in changes in litter growth. Several behavioural traits (standing activity, reactivity to different stimuli, postural activity) and functional traits (body reserves, udder quality) at farrowing contributed substantially to litter growth from D0 to D7. Sow aggression towards piglets and time spent standing at D0 were unfavourably correlated to D1–D3 litter growth. Time spent lying with udder exposed at D0 was favourably correlated to D1–D3 litter growth. The farrowing duration was negatively correlated to D0–D1 and D1–D3 litter growth. Furthermore, D3–D7 litter growth was positively correlated to feed intake in the same period. Several behavioural traits and some functional traits influence early litter growth. The contribution of sow behaviour was greater in the critical period around farrowing than in later days. [ABSTRACT FROM AUTHOR]

The current study aimed to evaluate the effect of lymph node ratio (LNR) on the short-term and long-term outcomes of colorectal cancer (CRC) patients who underwent radical CRC surgery. We retrospectively collected CRC patients who underwent radical surgery from Jan 2011 to Jan 2020 in a single-center hospital. The patients were divided into the high LNR group and the low group according to the median. The baseline information and the short-term outcomes were compared between the high group and the low group. Univariate and multivariate logistic regression was performed to analyze the independent predictors for overall survival (OS) and disease-free survival (DFS). A 1:1 proportional propensity score matching (PSM) was used to reduce the selection bias between the two groups. Kaplan–Meier method was used to estimate the OS and DFS between the two groups in different T stages. A total of 1434 CRC patients undergoing radical surgery were enrolled in this study, and there were 730 (50.9%) patients in the low LNR group and 704 (49.1%) patients in the high LNR group. After the PSM, there were 618 patients in both groups, the baseline characteristics between the two groups had no significant difference (p > 0.05). After comparing the Surgery-related information and The Short-term outcomes, the high LNR group had a longer hospital stay (after PSM, p < 0.01). In univariate and multivariate logistic regression analyses, age (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), tumor location (univariate analysis, p = 0.020; multivariate analysis, p = 0.024), lymph-vascular space invasion (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), cancer nodules (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), tumor size (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), LNR (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), and overall complications (univariate analysis, p < 0.01; multivariate analysis, p < 0.01) were independent risk factors for OS, and age (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), tumor location (univariate analysis, p = 0.032; multivariate analysis, p = 0.031), T stage (univariate analysis, p < 0.01; multivariate analysis, p = 0.014), lymph-vascular space invasion (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), cancer nodules (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), LNR (univariate analysis, p < 0.01; multivariate analysis, p < 0.01), and overall complications (univariate analysis, p < 0.01; multivariate analysis, p < 0.01) were identified as independent risk factors for DFS. The high LNR group had a worse OS in T3 (p < 0.01) and T4 (p < 0.01) as well as a worse DFS in T3 (p < 0.01) and T4 (p < 0.01). No association was found between LNR and postoperative complications, but the high LNR group had a longer hospital stay. LNR was identified as an independent predictor for OS and DFS. Furthermore, high LNR had a worse OS and DFS under T3 and T4 stages. Therefore, LNR was more prognostically significant for CRC patients under T3 and T4 stages. [ABSTRACT FROM AUTHOR]

Currently, there is no consensus regarding the extent of surgery for stage I pulmonary carcinoid (PC) tumors, which encompass typical carcinoid (TC) and atypical carcinoid (AC) tumors. Sublobar resection includes segmental resection and wedge resection; the former is regarded as a type of anatomical resection that is better suited for tumor treatment. Therefore, it needs to be further verified whether differences exist in the effects of the two surgical methods on the survival time of patients. Propensity score matching (PSM) was used. The primary endpoints were cancer-specific survival (CSS) and overall survival (OS) time. Survival differences were analyzed via the Kaplan–Meier method and the log-rank test. There was no significant difference in survival between the sublobar resection and lobectomy groups after PSM in either the TC or AC tumor groups (all p > 0.05). A total of 1680 patients underwent pulmonary wedge resection (TC: n = 1547, AC: n = 133), and 398 patients underwent segmental resection (TC: n = 365, AC: n = 33). After PSM, there were no statistically significant differences in survival, regardless of whether OS or CSS was considered the primary endpoint (OS: p = 0.337; CSS: p = 0.470). Furthermore, segmental resection did not prolong patient survival time compared with wedge resection in different subgroup analyses on the basis of histology, age, and tumor size (all p > 0.05). Finally, the same results were obtained via multivariate Cox analysis (OS: p = 0.153; HR = 1.21; CSS: p = 0.351, HR = 1.32). Sublobar resection could be considered for patients with early-stage typical or atypical pulmonary carcinoid, provided that a rigorous lymph node evaluation is conducted. If the tumor is distant from the pulmonary hilum, either segmentectomy or wedge resection may be performed depending on the specific location of the tumor and the clinical condition of the patient. [ABSTRACT FROM AUTHOR]

We investigated the association of CA125 response with prognosis and RECIST response/progressive disease (PD) criteria in recurrent high grade serous ovarian cancer (HGSOC) patients treated with a cell cycle checkpoint kinase 1 inhibitor (CHK1i), prexasertib. 81 patients had measurable disease per RECISTv1.1, of which 72 and 70 were measurable by Gynecologic Cancer InterGroup (GCIG) CA125 response and PD criteria, respectively. Univariate and multivariate analyses showed that GCIG CA125 response (n = 32) is associated with improved progression-free survival (PFS) and overall survival (OS) compared to no GCIG CA125 response (n = 40) (median PFS 8.0 vs. 3.5 months [HR: 0.30, 95% CI: 0.18–0.51, p < 0.0001]; median OS 19.8 vs. 10.0 months [HR: 0.38, 95% CI: 0.23–0.64, p < 0.001]) independent of BRCA mutation status, platinum-sensitivity, previous PARP inhibitor therapy, ECOG performance status, and FIGO stage. Notably, GCIG CA125 response had a high negative predictive value (NPV: 93%, 95% CI: 80–98), but poor positive predictive value (PPV: 53%, 95% CI: 35–71) in predicting RECIST response. CA125 PD criteria also showed poor concordance with RECIST PD (PPV 56%, 95% CI: 40–71; NPV 33%, 95% CI: 17–54). Therefore, serum CA125 may be useful as a highly accessible prognostic and predictive biomarker to CHK1i therapy in recurrent HGSOC. [ABSTRACT FROM AUTHOR]

In this work, a multivariate analysis was carried out, using a Plackett–Burman (PB) design involving seventeen growth parameters, on carotenoids production of Pavlova gyrans (p < 0.10). Each assay was analysed regarding its content (mg g−1) of fucoxanthin (Fx), diatoxanthin, diadinoxanthin, β-carotene (βCar), α-carotene, and the sum of all carotenoids analysed individually (TCar). According to the statistical analysis, modified medium formulations were developed for the particular cases of Fx, βCar, and TCar. The study showed that Fx content was positively affected by nitrogen supplementation and lower light intensities. Higher concentrations of nitrogen and iron increased the final content of βCar as well. Similarly, salinity, light intensity, nitrogen, iron, and cobalt were identified as key factors in TCar production. The PB-based formulations showed significant improvements (p < 0.05) for TCar (11.794 mg g−1) and Fx (6.153 mg g−1) when compared to the control conditions (Walne's medium—2.010 mg g−1). Furthermore, effective control of key variables (e.g., light intensity) throughout P. gyrans growth proved successful (p < 0.05), increasing the productivity of Fx (0.759 mg L−1 d−1) and TCar (1.615 mg L−1 d−1). [ABSTRACT FROM AUTHOR]

High and low pathogenicity avian influenza viruses (HPAIV, LPAIV) are the primary causes of poultry diseases worldwide. HPAIV and LPAIV constitute a major threat to the global poultry industry. Therefore, early detection and well-adapted surveillance strategies are of the utmost importance to control the spread of these viruses. Volatile Organic Compounds (VOCs) released from living organisms have been investigated over the last decades as a diagnostic strategy. Mass spectrometry instruments can analyze VOCs emitted upon viral infection. Selected ion flow tube mass spectrometry (SIFT-MS) enables direct analysis of cell headspace in less than 20 min. As a proof-of-concept study, we investigated the ability of a SIFT-MS coupled sparse Partial Least Square-Discriminant Analysis analytical workflow to discriminate IAV-infected cells. Supernatants of HPAIV, LPAIV, and control cells were collected from 1 to 72 h post-infection and analyzed using our analytical workflow. At each collection point, VOCs' signatures were first identified based on four independent experiments and then used to discriminate the infectious status of external samples. Our results indicate that the identified VOCs signatures successfully discriminate, as early as 1-h post-infection, infected cells from the control cells and differentiated the HPAIV from the LPAIV infection. These results suggest a virus-dependent VOCs signature. Overall, the external samples' status was identified with 96.67% sensitivity, 100% specificity, and 97.78% general accuracy. [ABSTRACT FROM AUTHOR]

A growing body of evidence indicates the emergence of overweight/obesity in developing countries before the battle against undernutrition has been won. We conducted this study to quantify the reduction of underweight and the emergence of overweight among Ethiopian women from 2000 to 2016 and evaluate factors explaining the progress. We used the four Ethiopian Demographic and Health Surveys (2000–2016) to analyze body mass index (BMI) trends among women. Data from 43,815 non-pregnant, non-puerperal reproductive-age women was used to evaluate the linear change in BMI and changes in the percentage of overweight and underweight over time. Using multivariate decomposition analysis of change in underweight and overweight percentages, we identified sources of change in BMI in the past 16 years of the survey periods. The BMI of Ethiopian reproductive-age women increased by 0.88 kg/m2 from 2000 to 2016. The increment was pronounced in urban areas with 1.46 kg/m2. There has been a significant reduction in underweight women since 2000 (p-value < 0.001), and 87.62% of the changes were attributed to behavioral changes toward weight management. And there was a significant upswing in overweight women from 2000 to 2016 (p-value < 0.001) as well. A compositional change of factors including region, women's age, women's educational status, religion, type of place of residence, and use of contraceptives contributed to 57.51% of the observed increment in the percentage of overweight women. A relatively slow decrease in underweight and an increment in overweight have been observed. This progress can be disaggregated into persistent underweight in the rural and poorest, and swift development of overweight in the urban and richest communities. Targeted nutrition interventions for both underweight and overweight women are mandatory. Nutritional interventions in Ethiopia should focus on behavioral change to reduce hunger and malnutrition as well as to avert the emergence of overweight or obesity in the affected communities. [ABSTRACT FROM AUTHOR]

Understanding the distribution of the plant species of an unexplored area is the utmost need of the present-day. In order to collect vegetation data, Quadrat method was used having size of 1 m2. The composite soil samples from each site were tested for various edaphic properties. PC-ORD v.5 was used for the classification of the vegetation while CANOCO v.5.1 was used for ordination of the data and to find out the complex relationship between plants and environment. Survey was conducted during summer season and a total of 216 herbaceous species were recorded from forty different sites of District Kohat, Pakistan. Cluster Analysis (CA) and Two-Way Cluster Analysis (TWCA) classified the vegetation of forty sites into six major plant groups i.e., 1. Paspalum paspalodes, Alternanthera sessilis, Typha domingensis, 2. Cynodon dactylon, Parthenium hysterophorus, Brachiaria ramosa, 3. Cynodon dactylon, Eragrostis minor, Cymbopogon jwarancusa, 4. Cymbopogon jwarancusa, Aristida adscensionis, Boerhavia procumbens, 5. Cymbopogon jwarancusa, Aristida adscensionis, Pennisetum orientale and 6. Heteropogon contortus, Bothriochloa ischaemum, Chrysopogon serrulatus. They were named after the dominant species based on their Importance Value (IV). The detrended correspondence analysis (DCA) analysis further confirmed the vegetation classification. Canonical correspondence analysis (CCA) indicated that the species distribution in the area was strongly affected by various environmental factors including status, soil characteristics, topography and altitude. [ABSTRACT FROM AUTHOR]

This study aims to investigate the factors effective in predicting the persistence of reflux after the first subureteric transurethral injection (STING) of dextranomer/hyaluronic acid copolymer in pediatric patients with vesicoureteral reflux. The data of patients without a previous history of surgery to treat vesicoureteral reflux and who underwent STING for the first time between September 2011 and November 2020 were investigated retrospectively. After considering exclusion criteria, of 199 patients, 127 patients and 180 renal units were suitable for inclusion. A renal unit-based evaluation was made. Age < 61 months (univariate: p = 0.001, multivariate: p = 0.015, HR: 2.352 (1.181–4.686), OR (95% CI)), moderate reflux level (grade 3) (univariate: p < 0.001, multivariate: p = 0.019, HR: 2.703 (1.177–6.209), OR (95% CI)), DRF (differential renal function) < 45 (univariate: p = 0.020, multivariate: p = 0.047, HR: 1.992 (1.009–3.935), OR (95% CI)), and UDR (ureteral diameter ratio) > 0.15 (univariate: p < 0.001, multivariate: p = 0.005, HR: 2.786 (1.368–5.672), OR (95% CI)) were found predictors of reflux persistence after STING surgery both univariate and multivariate analysis. High reflux level (grade 4–5) was statistically significant in univariate analysis (p < 0.001) but not statistically significant in multivariate analysis (p = 0.215). In our study, UDR and DRF were found to be factors affecting reflux persistence. UDR and DRF should be considered in order to predict reflux resolution in patients who will undergo STING. [ABSTRACT FROM AUTHOR]

The current study aimed to identify the indications for manual reduction in incarcerated obturator hernias (OH). Further, whether time to symptom onset and manual reduction outcomes can be predictors of bowel viability and the need for bowel resection in incarcerated OH were examined. This retrospective study included 26 patients with incarcerated OH who underwent surgery. All patients underwent manual reduction, and computed tomography scan after manual reduction confirmed hernia release. Multivariate analyses were performed to determine the predictors of bowel resection. The bowel resection group had a significantly longer average time to symptom onset than the nonbowel resection group (88 vs 36 h). Further, the bowel resection group was more likely to have failed manual reduction than the nonbowel resection group. A time to symptom onset of ≥ 72 h and failed manual reduction were significant predictors of bowel viability. Age, sex, hernia localization, American Society of Anesthesiologists physical status score, and laboratory findings did not differ significantly between the bowel resection and nonbowel resection groups. Time to symptom onset and manual reduction outcomes are significant predictors of bowel viability in incarcerated OH. Patients with a time to symptom onset of ≥ 72 h and failed manual reduction require surgical evaluation due to a high risk of bowel nonviability. Therefore, a cautious approach is required in the management of OH, and further research on optimized treatment protocols should be conducted. [ABSTRACT FROM AUTHOR]

Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis. [ABSTRACT FROM AUTHOR]

This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980–81 to 2020–21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices. [ABSTRACT FROM AUTHOR]

Abstract Clinical depression is characterized by multiple concurrent symptoms, manifesting as a complex heterogeneous condition. Although some well-established classical behavioral assessments are widespread in rodent models, it remains uncertain whether rats also display stress-induced depression-related phenotypes in a multidimensional manner, i.e., simultaneous alterations in multiple behavioral tests. Here, we investigated multivariate patterns and profiles of depression-related behavioral traits in male Wistar rats subjected to inescapable footshocks (IS) or no-shocks (NS), followed by a comprehensive battery of behavioral tests and ethological characterization. We observed generalized stronger intra-test but weaker inter-test correlations. However, feature clustering of behavioral measures successfully delineated variables linked to resilience and susceptibility to stress. Accordingly, a noteworthy covariation pattern emerged, characterized by increased open field locomotion, reduced time in the elevated plus maze open arms, lower sucrose preference, and increased shuttle box escape failures that consistently differentiated IS from NS. Surprisingly there is little contribution from forced swim. In addition, individual clustering revealed a diversity of behavioral profiles, naturally separating NS and IS, including subpopulations entirely characterized by resilience or susceptibility. In conclusion, our study elucidates intricate relationships among classical depression-related behavioral measures, highlighting multidimensional individual variability. Our work emphasizes the importance of a multivariate framework for behavioral assessment in animal models to understand stress-related neuropsychiatric disorders.

Abstract Potassium testing is an essential test in emergency medicine. Turnaround time (TAT) is the time between specimen receipt by the laboratory and the release of the test report. A brief in-laboratory TAT increases emergency department effectiveness. Optimizing processes to shorten TAT using other tools requires extensive time, resources, training, and support. Therefore, we aimed to find a convenient way to shorten TAT, identify risk factors affecting the timeliness of emergency potassium test reporting, and verify the intervention’s effects. The dependent variable was emergency potassium reporting time > 30 or

Abstract Managing patients with kidney allografts largely depends on biopsy diagnosis which is based on semiquantitative assessments of rejection features and extent of acute and chronic changes within the renal parenchyma. Current methods lack reproducibility while digital image data-driven computational models enable comprehensive and quantitative assays. In this study we aimed to develop a computational method for automated assessment of histopathology transformations within the tubulointerstitial compartment of the renal cortex. Whole slide images of modified Picrosirius red-stained biopsy slides were used for the training (n = 852) and both internal (n = 172) and external (n = 94) tests datasets. The pipeline utilizes deep learning segmentations of renal tubules, interstitium, and peritubular capillaries from which morphometry features were extracted. Seven indicators were selected for exploring the intrinsic spatial interactions within the tubulointerstitial compartment. A principal component analysis revealed two independent factors which can be interpreted as representing chronic and acute tubulointerstitial injury. A K-means clustering classified biopsies according to potential phenotypes of combined acute and chronic transformations of various degrees. We conclude that multivariate analyses of tubulointerstitial morphometry transformations enable extraction of and quantification of acute and chronic components of injury. The method is developed for renal allograft biopsies; however, the principle can be applied more broadly for kidney pathology assessment.

The biology underlying proton minibeam radiation therapy (pMBRT) is not fully understood. Here we aim to elucidate the biological effects of pMBRT using Fourier Transform Infrared Microspectroscopy (FTIRM). In vitro (CTX-TNA2 astrocytes and F98 glioma rat cell lines) and in vivo (healthy and F98-bearing Fischer rats) irradiations were conducted, with conventional proton radiotherapy and pMBRT. FTIRM measurements were performed at ALBA Synchrotron, and multivariate data analysis methods were employed to assess spectral differences between irradiation configurations and doses. For astrocytes, the spectral regions related to proteins and nucleic acids were highly affected by conventional irradiations and the high-dose regions of pMBRT, suggesting important modifications on these biomolecules. For glioma, pMBRT had a great effect on the nucleic acids and carbohydrates. In animals, conventional radiotherapy had a remarkable impact on the proteins and nucleic acids of healthy rats; analysis of tumour regions in glioma-bearing rats suggested major nucleic acid modifications due to pMBRT. [ABSTRACT FROM AUTHOR]

Metacognitive systematic bias impairs human learning efficiency, which is characterized by the inconsistency between predicted and actual memory performance. However, the underlying mechanism of metacognitive systematic bias remains unclear in existing studies. In this study, we utilized judgments of learning task in human participants to compare the neural mechanism difference in metacognitive systematic bias. Participants encoded words in fMRI sessions that would be tested later. Immediately after encoding each item, participants predicted how likely they would remember it. Multivariate analyses on fMRI data demonstrated that working memory and uncertainty decisions are represented in patterns of neural activity in metacognitive systematic bias. The available information participants used led to overestimated bias and underestimated bias. Effective connectivity analyses further indicate that information about the metacognitive systematic bias is represented in the dorsolateral prefrontal cortex and inferior parietal cortex. Different neural patterns were found underlying overestimated bias and underestimated bias. Specifically, connectivity regions with the dorsolateral prefrontal cortex, anterior cingulate cortex, and supramarginal gyrus form overestimated bias, while less regional connectivity forms underestimated bias. These findings provide a mechanistic account for the construction of metacognitive systematic bias. [ABSTRACT FROM AUTHOR]

This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. Twenty (19 patients) and 31 MRI scans (30 patients) of femurs with PFI and normal femurs, respectively, were used. Bone and cartilage segmentation of the distal femurs was performed and subsequently converted into 3D reconstructed models. The pointwise distance map showed anterior elevation of the trochlea, particularly at the central floor of the proximal trochlea, in the PFI models compared with the normal models. Principal component analysis examined shape variations in the PFI group, and several principal components exhibited shape variations in the trochlear floor and intercondylar width. Multivariate analysis showed that these shape components were significantly correlated with the PFI/non-PFI distinction after adjusting for age and sex. Our ML-based prediction model for PFI achieved a strong predictive performance with an accuracy of 0.909 ± 0.015, and an area under the curve of 0.939 ± 0.009 when using a support vector machine with a linear kernel. This study demonstrated that 3D MRI-based SSA can realistically visualize statistical results on surface models and may facilitate the understanding of complex shape features. [ABSTRACT FROM AUTHOR]

This study presents a thorough investigation into the concentration of heavy metals and mineral composition within four distinct coastal flora species: Cyperus conglomeratus, Halopyrum mucronatum, Sericostem pauciflorum, and Salvadora persica. Employing rigorous statistical methodologies such as Pearson coefficient correlation, principal component analysis (PCA), analysis of variance (ANOVA), and interclass correlation (ICC), we aimed to elucidate the bioavailability of heavy metals, minerals, and relevant physical characteristics. The analysis focused on essential elements including copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), magnesium (Mg2+), calcium (Ca2+), sodium (Na+), potassium (K+), and chloride (Cl–), all of which are known to play pivotal roles in the ecological dynamics of coastal ecosystems. Through PCA, we discerned distinctive patterns within PC1 to PC4, collectively explaining an impressive 99.65% of the variance observed in heavy metal composition across the studied flora species. These results underscore the profound influence of environmental factors on the mineral composition of coastal flora, offering critical insights into the ecological processes shaping these vital ecosystems. Furthermore, significant correlations among mineral contents in H. mucronatum; K+ with content of Na+ (r = 0.989) and Mg2+ (r = 0.984); as revealed by ICC analyses, contributed to a nuanced understanding of variations in electrical conductivity (EC), pH levels, and ash content among the diverse coastal flora species. By shedding light on heavy metal and mineral dynamics in coastal flora, this study not only advances our scientific understanding but also provides a foundation for the development of targeted environmental monitoring and management strategies aimed at promoting the ecological sustainability and resilience of coastal ecosystems in the face of ongoing environmental challenges. [ABSTRACT FROM AUTHOR]

Gut microbiome dysbiosis contributes to the pathophysiology of both gestational diabetes mellitus (GDM) and its associated adverse outcomes in the woman and offspring. Even though GDM prevalence, complications, and outcomes vary among different ethnic groups, limited information is available about the influence of ethnicity on gut microbiome dysbiosis in pregnancies complicated by GDM. This pilot prospective cohort study examined the impact of ethnicity on gut dysbiosis in GDM among three Asian ethnic groups (Chinese, Malay, Indian) living in Singapore, and investigated the potential modulatory roles of diet and lifestyle modifications on gut microbiome post-GDM diagnosis. Women with GDM (n = 53) and without GDM (n = 16) were recruited. Fecal samples were collected at 24–28- and 36–40-weeks' gestation and analyzed by targeted 16S rRNA gene-based amplicon sequencing. Permutational multivariate analysis of variance (PERMANOVA) analysis was performed to evaluate differences between groups. Differentially abundant taxa were identified by DeSeq2 based analysis. Functional prediction was performed using the phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt2). Among women with GDM, gut microbiome from different ethnicities harbored common microbial features. However, among those without GDM, there was contrasting microbiome composition between ethnic groups. Microbial members such as Collinsella, Blautia, Ruminococcus, Ruminococcus gnavus, Ruminococcus torques, and Eubacterium hallii groups were differentially enriched (p < 0.05) in women with GDM compared to those without. Among women with GDM, no differences in alpha- and beta- diversity were observed when comparing 24–28 weeks' samples with 36–40 weeks' samples, a period covering intense dietary and lifestyle modification, suggesting an inability to modulate gut microbiota through classic GDM management. Women with GDM have a distinct gut microbiome profile which harbours common features across different Asian ethnic groups, consistent with the notion that specific microbes are involved in the pathogenesis of insulin resistance, pro-inflammatory conditions, and other metabolic dysregulation known to be present in GDM. [ABSTRACT FROM AUTHOR]

Clinical depression is characterized by multiple concurrent symptoms, manifesting as a complex heterogeneous condition. Although some well-established classical behavioral assessments are widespread in rodent models, it remains uncertain whether rats also display stress-induced depression-related phenotypes in a multidimensional manner, i.e., simultaneous alterations in multiple behavioral tests. Here, we investigated multivariate patterns and profiles of depression-related behavioral traits in male Wistar rats subjected to inescapable footshocks (IS) or no-shocks (NS), followed by a comprehensive battery of behavioral tests and ethological characterization. We observed generalized stronger intra-test but weaker inter-test correlations. However, feature clustering of behavioral measures successfully delineated variables linked to resilience and susceptibility to stress. Accordingly, a noteworthy covariation pattern emerged, characterized by increased open field locomotion, reduced time in the elevated plus maze open arms, lower sucrose preference, and increased shuttle box escape failures that consistently differentiated IS from NS. Surprisingly there is little contribution from forced swim. In addition, individual clustering revealed a diversity of behavioral profiles, naturally separating NS and IS, including subpopulations entirely characterized by resilience or susceptibility. In conclusion, our study elucidates intricate relationships among classical depression-related behavioral measures, highlighting multidimensional individual variability. Our work emphasizes the importance of a multivariate framework for behavioral assessment in animal models to understand stress-related neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]

We compared survival outcomes of high-dose concomitant boost radiotherapy (HDCBRT) and conventional dose radiotherapy (CRT) for newly diagnosed glioblastoma (GB). Patients treated with intensity-modulated radiation therapy for newly diagnosed GB were included. In HDCBRT, specific targets received 69, 60, and 51 Gy in 30 fractions, while 60 Gy in 30 fractions was administered with a standard radiotherapy method in CRT. Overall survival (OS) and progression-free survival (PFS) were compared using the Log-rank test, followed by multivariate Cox analysis. The inverse probability of treatment weighting (IPTW) method was also applied to each analysis. Among 102 eligible patients, 45 received HDCBRT and 57 received CRT. With a median follow-up of 16 months, the median survival times of OS and PFS were 21 and 9 months, respectively. No significant differences were observed in OS or PFS in the Kaplan–Meier analyses. In the multivariate analysis, HDCBRT correlated with improved OS (hazard ratio, 0.49; 95% confidence interval, 0.27–0.90; P = 0.021), and this result remained consistent after IPTW adjustments (P = 0.028). Conversely, dose suppression due to the proximity of normal tissues and IMRT field correlated with worse OS and PFS (P = 0.008 and 0.049, respectively). A prospective study with a stricter protocol is warranted to validate the efficacy of HDCBRT for GB. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

To investigate the associations between corneal curvature (CC) and other anterior segment biometrics in young myopic adults. In this retrospective multi-center study, 7893 young myopic adults were included. CC and other anterior segment biometrics were measured by Scheimpflug imaging (Pentacam). CC was defined as SimK at central 3 mm area, and other anterior segment biometrics included white-to-white corneal diameter (WTW), central corneal thickness (CCT), corneal volume (CV) at 3 mm, 5 mm, and 7 mm area, anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA), anterior corneal eccentricity (ACE) and asphericity (ACAP), posterior corneal eccentricity (PCE) and asphericity (PCAP), anterior chamber depth (ACD), and anterior chamber volume (ACV). Univariate regression analyses were used to assess the associations between CC and other anterior segment biometrics, and multivariate regression analyses were further performed to adjusted for age, gender and spherical equivalent. CC was higher in patients of female gender and higher myopia (all P < 0.05). Eyes in higher CC quartiles had lower WTW, thinner CCT, lower CV at 3 mm and 5 mm, lower ACD, and lower ACV (all P < 0.001), but had larger ACA, larger PCA, less PCE and less PCAP (all P < 0.001), compared to eyes in lower CC quartiles. The trends of CV at 7 mm, ACE and ACAP were inconsistent in different CC quartiles. After adjusting for age, gender and spherical equivalent with multivariate linear regression, CC was positively correlated to CV at 7 mm (βs = 0.069), ACA (βs = 0.194), PCA (βs = 0.187), ACE (βs = 0.072), PCAP (βs = 0.087), and ACD (βs = 0.027) (all P < 0.05), but was negatively correlated to WTW (βs = − 0.432), CCT (βs = − 0.087), CV-3 mm (βs = − 0.066), ACAP (βs = − 0.043), PCE (βs = − 0.062), and ACV (βs = − 0.188) (all P < 0.05). CC was associated with most of the other anterior segment biometrics in young myopic adults. These associations are important for better understanding of the interactions between different anterior segment structures in young myopic patients, and are also useful for the exploration of the pathogenesis of myopia. [ABSTRACT FROM AUTHOR]

A total of 739 patients underwent RARP as initial treatment for PCa from November 2011 to October 2018. Data on BCR status, clinical and pathological parameters were collected from the clinical records. After excluding cases with neoadjuvant and/or adjuvant therapies, presence of lymph node or distant metastasis, and positive SM, a total of 537 cases were eligible for the final analysis. The median follow-up of experimental cohort was 28.0 (interquartile: 18.0–43.0) months. We identified the presence of International Society of Urological Pathology grade group (ISUP-GG) ≥ 4 (Hazard ratio (HR) 3.20, 95% Confidence Interval (95% CI) 1.70–6.03, P < 0.001), lymphovascular invasion (HR 2.03, 95% CI 1.00–4.12, P = 0.049), perineural invasion (HR 10.7, 95% CI 1.45–79.9, P = 0.020), and maximum tumor diameter (MTD) > 20 mm (HR 1.9, 95% CI 1.01–3.70, P = 0.047) as significant factors of BCR in the multivariate analysis. We further developed a risk model according to these factors. Based on this model, 1-year, 3-year, and 5-year BCR-free survival were 100%, 98.9%, 98.9% in the low-risk group; 99.1%, 94.1%, 86.5% in the intermediate-risk group; 93.9%, 84.6%, 58.1% in the high-risk group. Internal validation using the bootstrap method showed a c-index of 0.742 and an optimism-corrected c-index level of 0.731. External validation was also carried out using an integrated database derived from 3 other independent institutions including a total of 387 patients for the final analysis. External validation showed a c-index of 0.655. In conclusion, we identified risk factors of biochemical failure in patients showing negative surgical margin after RARP and further developed a risk model using these risk factors. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This study aimed to identify the factors affecting hip−knee−ankle (HKA) angle following Oxford medial unicompartmental knee arthroplasty (MUKA). A retrospective analysis of 200 patients who underwent Oxford MUKA from June 2018 to October 2020 was conducted. Univariate and multivariate analyses were performed to investigate the impact of surgical and radiographic characteristics on the postoperative HKA angle. The mean HKA angle was 9.5 ± 4.3° before surgery and 3.6 ± 3.7° after surgery (p < 0.001). The postoperative HKA angle significantly correlated with the preoperative HKA angle, bearing size, tibial component alignment angle, and BMI (r = 0.71, p < 0.001; r = − 0.24, p = 0.001; r = 0.21, p = 0.004; r = − 0.18, p = 0.011). Multiple linear regression analysis revealed that the preoperative HKA angle (β = 0.68, p < 0.001), bearing size (β = − 0.31, p < 0.001), tibial component alignment angle (β = 0.14, p = 0.003), and BMI (β = − 0.09, p = 0.047) significantly affected the postoperative HKA angle. In conclusion, larger preoperative varus deformity, smaller bearing size, greater varus alignment of the tibial component, and lower BMI lead to greater postoperative varus alignment of the lower limb in Oxford MUKA. With this concept, surgeons can more accurately predict postoperative lower limb alignment and avoid malalignment in Oxford MUKA. [ABSTRACT FROM AUTHOR]

Abstract Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging.

Pleomorphic xanthoastrocytomas (PXA) are rare, accounting for < 1% of all astrocytomas. Literature on the clinical course and treatment outcomes of PXAs is limited. The study aimed to determine prognosis and treatment strategies for PXAs. Patients who had PXAs surgery between 2000–2021 were retrospectively analyzed for demographics and radiological characteristics. Initial and salvage treatment outcomes were recorded. Overall, 40 and 9 patients had grade 2 and 3 PXAs; their 5-year progression-free survival (PFS) rates were 75.8% and 37.0%, respectively (p = 0.003). Univariate analysis revealed that strong T1 enhancement (p = 0.036), infiltrative tumor margins (p < 0.001), peritumoral edema (p = 0.003), WHO grade (p = 0.005), and gross total resection (p = 0.005) affected the PFS. Multivariate analysis revealed that the WHO grade (p = 0.010) and infiltrative tumor margins (p = 0.008) influenced the PFS. The WHO grade (p = 0.027) and infiltrative tumor margins (p = 0.027) also affected the overall survival (OS). Subgroup analysis for grade 2 PXAs revealed no significant associations between adjuvant radiation therapy and the PFS and OS. This study highlighted the heterogeneous nature of PXAs and its impact on patient prognosis. Infiltrative tumor margins emerged as a key prognostic factor. Our findings have emphasized the prognostic relevance of radiological features and the need for larger studies on comprehensive management. [ABSTRACT FROM AUTHOR]

Alterations in the default mode network (DMN) are associated with aging. We assessed age-dependent changes of DMN interactions and correlations with a battery of neuropsychological tests, to understand the differences of DMN directed connectivity between young and older subjects. Using a novel multivariate analysis method on resting-state functional MRI data from fifty young and thirty-one healthy older subjects, we calculated intra- and inter-DMN 4-nodes directed pathways. For the old subject group, we calculated the partial correlations of inter-DMN pathways with: psychomotor speed and working memory, executive function, language, long-term memory and visuospatial function. Pathways connecting the DMN with visual and limbic regions in older subjects engaged at BOLD low frequency and involved the dorsal posterior cingulate cortex (PCC), whereas in young subjects, they were at high frequency and involved the ventral PCC. Pathways combining the sensorimotor (SM) cortex and the DMN, were SM efferent in the young subjects and SM afferent in the older subjects. Most DMN efferent pathways correlated with reduced speed and working memory. We suggest that the reduced sensorimotor efferent and the increased need to control such activities, cause a higher dependency on external versus internal cues thus suggesting how physical activity might slow aging. [ABSTRACT FROM AUTHOR]

Forearm rotation restriction (FRR) is common after surgery for distal radius fractures (DRFs). The aim of the current study was to investigate the effect of DRFs on forearm rotation. This retrospective study reviewed patients with DRFs who underwent surgical treatment from January 2019 to December 2021. The patients' basic data and radiographic parameters were analyzed. Forearm rotation, including pronation and supination, was assessed using a standard goniometer. The Patient-Rated Wrist Evaluation (PRWE) score was evaluated, and the incidence of FRR at the 6-month follow-up was recorded. Univariate and multivariate logistic regression analyses were performed to identify risk factors correlated with FRR. A total of 127 patients with DRFs were included in this study. After surgery, 46 cases were considered to have FRR, with a rate of 36.2%, while the remaining 81 cases (63.8%) did not have FRR. The PRWE scores were 22.8 ± 5.2 and 17.9 ± 4.2 in the FRR group and non-FRR group, respectively, and the difference was statistically significant (P < 0.05). Multivariate analysis showed that the involvement of the sigmoid notch (OR, 2.88; 95% CI 1.49–5.56), post-operative volar tilt < 0° (OR, 2.16; 95% CI 1.34–3.50), and post-operative ulnar variance > 0 mm (OR, 1.37; 95% CI 1.06–1.78) were independently associated with the incidence of FRR. The FRR is associated with an increased PRWE score and may have had some impact on the patient's daily life. Fractures involving the sigmoid notch, dorsal angulation, and radial shortening deformity were found to be correlated with the incidence of FRR. Preoperative risk notification and intraoperative preventive measures are necessary for these patients. [ABSTRACT FROM AUTHOR]