Development and validation of prognostic nomograms for adult with papillary renal cell carcinoma: A retrospective study.

OBJECTIVE: The aim of the study was to create two consensus nomograms for predicting Overall Survival (OS) and Cancer-Specific Survival (CSS) in adults with papillary Renal Cell Carcinoma (pRCC). METHODS: Using the Surveillance, Epidemiology, and End Results databases, a retrospective analysis of 1,074 adults with pRCC from 2004 to 2015 was performed. These patients were then randomly divided into two independent cohorts with a ratio of 7:3 (training cohort: 752; validation cohort: 322). In a retrospective analysis of 752 patients from the training cohort, independent prognostic variables affecting OS and CSS were found. R software was used to create prognostic nomograms based on the findings of Cox regression analysis. The performance of the nomograms was assessed using the Concordance Index (C-index), the Area Under Curve (AUC), a calibration curve, and Decision Curve Analysis (DCA). Data from the 107 postoperative pRCC patients at the Affiliated Hospital of Xuzhou Medical University were used for external validation of the nomogram. RESULTS: For OS and CSS, the C-indices and AUCs of the training cohort and the validation cohort indicated that the model had excellent discrimination. The DCA demonstrated that the model was clinically applicable, and the calibration curves in the internal and external validations showed that the model's accuracy was high. CONCLUSION: The authors developed and validated a prognostic nomogram that accurately predicted the 3-, 5-, and 8-year OS and CSS of adults with pRCC. Clinicians can use this knowledge to direct the clinical management and counseling of patients with pRCC.

Deep-Learning Models for Abdominal CT Organ Segmentation in Children: Development and Validation in Internal and Heterogeneous Public Datasets.

Background: Deep-learning abdominal organ segmentation algorithms have shown excellent results in adults; validation in children is sparse. Objective: To develop and validate deep-learning models for liver, spleen, and pancreas segmentation on pediatric CT examinations. Methods: This retrospective study developed and validated deep-learning models for liver, spleen, and pancreas segmentation using 1731 CT examinations (1504 training, 221 testing), derived from three internal institutional pediatric (age ≤18) datasets (n=483) and three public datasets comprising pediatric and adult examinations with various pathologies (n=1248). Three deep-learning model architectures (SegResNet, DynUNet, and SwinUNETR) from the Medical Open Network for AI (MONAI) framework underwent training using native training (NT), relying solely on institutional datasets, and transfer learning (TL), incorporating pre-training on public datasets. For comparison, TotalSegmentator (TS), a publicly available segmentation model, was applied to test data without further training. Segmentation performance was evaluated using mean Dice similarity coefficient (DSC), with manual segmentations as reference. Results: For internal pediatric data, DSC for normal liver was 0.953 (TS), 0.964-0.965 (NT models), and 0.965-0.966 (TL models); normal spleen, 0.914 (TS), 0.942-0.945 (NT models), and 0.937-0.945 (TL models); normal pancreas, 0.733 (TS), 0.774-0.785 (NT models), and 0.775-0.786 (TL models); pancreas with pancreatitis, 0.703 (TS), 0.590-0.640 (NT models), and 0.667-0.711 (TL models). For public pediatric data, DSC for liver was 0.952 (TS), 0.876-0.908 (NT models), and 0.941-0.946 (TL models); spleen, 0.905 (TS), 0.771-0.827 (NT models), and 0.897-0.926 (TL models); pancreas, 0.700 (TS), 0.577-0.648 (NT models), and 0.693-0.736 (TL models). For public primarily adult data, DSC for liver was 0.991 (TS), 0.633-0.750 (NT models), and 0.926-0.952 (TL models); spleen, 0.983 (TS), 0.569-0.604 (NT models), and 0.923-0.947 (TL models); pancreas, 0.909 (TS), 0.148-0.241 (NT models), and 0.699-0.775 (TL models). DynUNet-TL was selected as the best-performing NT or TL model and was made available as an opensource MONAI bundle (https://github.com/cchmc-dll/pediatric_abdominal_segmentation_bundle.git). Conclusion: TL models trained on heterogeneous public datasets and fine-tuned using institutional pediatric data outperformed internal NT models and TotalSegmentator across internal and external pediatric test data. Segmentation performance was better in liver and spleen than in pancreas. Clinical Impact: The selected model may be used for various volumetry applications in pediatric imaging.

Baicalin enhances the chemotherapy sensitivity of oxaliplatin-resistant gastric cancer cells by activating p53-mediated ferroptosis.

Gastric cancer is one of the most common malignant tumors, and chemotherapy is the main treatment for advanced gastric cancer. However, chemotherapy resistance leads to treatment failure and poor prognosis in patients with gastric cancer. Multidrug resistance (MDR) is a major challenge that needs to be overcome in chemotherapy. According to recent research, ferroptosis activation is crucial for tumor therapeutic strategies. In this work, we explored the solution to chemoresistance in gastric cancer by investigating the effects of the Chinese medicine monomer baicalin on ferroptosis. Baicalin with different concentrations was used to treat the parent HGC27 and drug-resistant HGC27/L cells of gastric cancer. Cell viability was measured by CCK8, and synergistic effects of baicalin combined with oxaliplatin were evaluated using Synergy Finder software. The effects of baicalin on organelles and cell morphology were investigated using projective electron microscopy. Iron concentration, MDA production and GSH inhibition rate were measured by colorimetry. ROS accumulation was detected by flow cytometry. The ferroptosis-related genes (IREB2, TfR, GPX4, FTH1), P53, and SLC7A11 were analysed by Western blot, and the expression differences of the above proteins between pretreatment and pretreatment of different concentrations of baicalin, were assayed in both parental HGC27 cells and Oxaliplatin-resistant HGC27/L cells. Mechanically, Baicalin disrupted iron homeostasis and inhibits antioxidant defense, resulting in iron accumulation, lipid peroxide aggregation, and specifically targeted and activated ferroptosis by upregulating the expression of tumor suppressor gene p53, thereby activating the SLC7A11/GPX4/ROS pathway mediated by it. Baicalin activates ferroptosis through multiple pathways and targets, thereby inhibiting the viability of oxaliplatin-resistant gastric cancer HGC27/L cells and enhancing the sensitivity to oxaliplatin chemotherapy.

Exosomal miR-423-5p Derived from Cerebrospinal Fluid Pulsation Stress-Stimulated Osteoblasts Improves Angiogenesis of Endothelial Cells via DUSP8/ERK1/2 Signaling Pathway.

Exosomes secreted from osteoblasts (OBs) can regulate the angiogenesis of endothelial cells (ECs); however, whether cerebrospinal fluid pulsation (CSFP) stress, a special mechanical stimulation, can influence the cell's communication in the context of angiogenesis remains unknown. In this study, the effect of exosomes derived from CSFP stress-stimulated OBs on facilitating the angiogenesis of ECs was investigated. First, OBs were cultured in a CSFP bioreactor, and exosomes derived from OBs were isolated and identified. Cell Counting Kit 8 assay, transwell migration assay, wound healing migration assay, and tube formation assay were conducted to assess the effects of CSFP stress-stimulated OBs-derived exosomes (CSFP-Exos) on the angiogenesis of ECs. Then high-throughput RNA sequencing was used to determine the miRNA profiles of Non-CSFP stress-stimulated OBs-derived exosomes (NCSFP-Exos) and CSFP-Exos, and the luciferase reporter gene assay was performed to confirm the binging of miR-423-5p to DUSP8. In addition, the Matrigel plug assay was performed to explore whether exosomal miR-423-5p has the same effects in vivo. Our results suggested that CSFP-Exos can promote the angiogenesis of ECs, and miR-423-5p was enriched in CSFP-Exos. Moreover, miR-423-5p could promote the effect of angiogenesis via directly targeting dual-specificity phosphatase 8 (DUSP8), which inhibited the ERK1/2 signaling pathway. In conclusion, exosomal miR-423-5p derived from CSFP stress-stimulated OBs could promote the angiogenesis of ECs by the DUSP8/ERK1/2 signaling pathway.

Negative family and interpersonal relationship are associated with centromedial amygdala functional connectivity alterations in adolescent depression.

The amygdala, known for its functional heterogeneity, plays a critical role in the neural mechanism of adolescent major depressive disorder (aMDD). However, changes in its subregional functional networks in relation to stressful factors remain unclear. We recruited 78 comorbidity-free, medication-naive aMDD patients and 40 matched healthy controls (HC) to explore changes in resting-state functional connectivity (FC) across four amygdala subregions: the centromedial nucleus (CM), the basolateral nucleus (LB), the superficial nucleus (SF), and the amygdalostriatal transition area (Astr). Then, we performed partial correlation analysis to investigate the relationship between amygdala subregional FC and stressful factors as measured by the Chinese Version of Family Environment Scale (FES-CV) and the Adolescent Self-Rated Life Events Scale (ASLEC). Compared to HC, aMDD patients demonstrated significantly decreased functional connectivity between the left CM and left precentral gyrus, as well as between left SF and left precentral gyrus, and between left LB and posterior cingulate gyrus (PCC)/precuneus. In aMDD group, left CM-precentral gyrus FC exhibited negative correlation with interpersonal relationship and punishment, and positive correlation with family cohesion and expressiveness. This study reveals distinct patterns of abnormal functional connectivity among amygdala subregions in aMDD. Our findings suggest that the CM network, in particular, may be involved in stress-related factors in aMDD, which provide a potential target for the prevention and treatment of adolescent depression.

Physicochemical Characterization, Antioxidant and Anticancer Activity Evaluation of an Acidic Polysaccharide from Alpinia officinarum Hance.

AHP-3a, a triple-helix acidic polysaccharide isolated from Alpinia officinarum Hance, was evaluated for its anticancer and antioxidant activities. The physicochemical properties and structure of AHP-3a were investigated through gel permeation chromatography, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy. The weight-average molecular weight of AHP-3a was 484 kDa, with the molar percentages of GalA, Gal, Ara, Xyl, Rha, Glc, GlcA, and Fuc being 35.4%, 21.4%, 16.9%, 11.8%, 8.9%, 3.1%, 2.0%, and 0.5%, respectively. Based on the results of the monosaccharide composition analysis, methylation analysis, and NMR spectroscopy, the main chain of AHP-3a was presumed to consist of (1→4)-α-D-GalpA and (1→2)-α-L-Rhap residues, which is a pectic polysaccharide with homogalacturonan (HG) and rhamnogalacturonan-I (RG-I) structural domains containing side chains. In addition, the results of the antioxidant activity assay revealed that the ability of AHP-3a to scavenge DPPH, ABTS, and OH free radicals increased with an increase in its concentration. Moreover, according to the results from the EdU, wound healing, and Transwell assays, AHP-3a can control the proliferation, migration, and invasion of HepG2 and Huh7 hepatocellular carcinoma cells without causing any damage to healthy cells. Thus, AHP-3a may be a natural antioxidant and anticancer component.

Prescribed-time distributed optimization problem with constraints.

In recent years, distributed optimization problem have a wide range of applications in various fields. This paper considers the prescribed-time distributed optimization problem with/without constraints. Firstly, we assume the state of each agent is constrained, and the prescribed-time distributed optimization algorithm with constraints is designed on the basis of gradient projection algorithm and consensus algorithm. Secondly, the constrained distributed optimization problem is transformed into the unconstrained distributed optimization problem, and according to the gradient descent algorithm and consensus algorithm, we also propose the prescribed-time distributed optimization algorithm without constraints. By designing the appropriate objective functions, we prove the multi-agent system can converge to the optimal solution within any prescribed-time, and the convergence time is fully independent of the initial conditions and system parameters. Finally, three simulation examples are provided to verify the validity of the designed algorithms.

A systematic review of automated methods to perform white matter tract segmentation.

White matter tract segmentation is a pivotal research area that leverages diffusion-weighted magnetic resonance imaging (dMRI) for the identification and mapping of individual white matter tracts and their trajectories. This study aims to provide a comprehensive systematic literature review on automated methods for white matter tract segmentation in brain dMRI scans. Articles on PubMed, ScienceDirect [NeuroImage, NeuroImage (Clinical), Medical Image Analysis], Scopus and IEEEXplore databases and Conference proceedings of Medical Imaging Computing and Computer Assisted Intervention Society (MICCAI) and International Symposium on Biomedical Imaging (ISBI), were searched in the range from January 2013 until September 2023. This systematic search and review identified 619 articles. Adhering to the specified search criteria using the query, "white matter tract segmentation OR fiber tract identification OR fiber bundle segmentation OR tractography dissection OR white matter parcellation OR tract segmentation," 59 published studies were selected. Among these, 27% employed direct voxel-based methods, 25% applied streamline-based clustering methods, 20% used streamline-based classification methods, 14% implemented atlas-based methods, and 14% utilized hybrid approaches. The paper delves into the research gaps and challenges associated with each of these categories. Additionally, this review paper illuminates the most frequently utilized public datasets for tract segmentation along with their specific characteristics. Furthermore, it presents evaluation strategies and their key attributes. The review concludes with a detailed discussion of the challenges and future directions in this field.

Multivariate association between psychosocial environment, behaviors, and brain functional networks in adolescent depression.

BACKGROUND: Adolescent depression shows high clinical heterogeneity. Brain functional networks serve as a powerful tool for investigating neural mechanisms underlying depression profiles. A key challenge is to characterize how variation in brain functional organization links to behavioral features and psychosocial environmental influences. METHODS: We recruited 80 adolescents with major depressive disorder (MDD) and 42 healthy controls (HCs). First, we estimated the differences in functional connectivity of resting-state networks (RSN) between the two groups. Then, we used sparse canonical correlation analysis to characterize patterns of associations between RSN connectivity and symptoms, cognition, and psychosocial environmental factors in MDD adolescents. Clustering analysis was applied to stratify patients into homogenous subtypes according to these brain-behavior-environment associations. RESULTS: MDD adolescents showed significantly hyperconnectivity between the ventral attention and cingulo-opercular networks compared with HCs. We identified one reliable pattern of covariation between RSN connectivity and clinical/environmental features in MDD adolescents. In this pattern, psychosocial factors, especially the interpersonal and family relationships, were major contributors to variation in connectivity of salience, cingulo-opercular, ventral attention, subcortical and somatosensory-motor networks. Based on this association, we categorized patients into two subgroups which showed different environment and symptoms characteristics, and distinct connectivity alterations. These differences were covered up when the patients were taken as a whole group. CONCLUSION: This study identified the environmental exposures associated with specific functional networks in MDD youths. Our findings emphasize the importance of the psychosocial context in assessing brain function alterations in adolescent depression and have the potential to promote targeted treatment and precise prevention.

Study on coupling effect of soil structure and overconsolidation on mechanical properties of loess.

Soil structure and overconsolidation are two important factors that affect soil strength. Current research studies have primarily focused on the influence of single factors, and relatively few studies have studied the coupling effect of the two. In this paper, the effects of structure and overconsolidation on the mechanical properties of loess under certain conditions have been studied by compression tests and direct shear tests. Undisturbed loess, remolded loess, overconsolidated undisturbed loess, and overconsolidated remolded loess were investigated in this work. The results indicate that structure and overconsolidation can enhance the overall strength of the soil, but the effects of these two factors also interfere and weaken each other. The combined effect of structure and overconsolidation can lead to higher soil shear strength. Compared with remolded normally consolidated soil, when the vertical pressure is 50kPa, 100kPa, and 200kPa, the structure increases the strength of the original normally consolidated soil by 35%, 21%, and 7%, respectively. Overconsolidation increases the strength of the remolded overconsolidated soil by 51.3%, 40.9%, and 17.7%, respectively. The combined effect of structure and overconsolidation increases the strength of the original overconsolidated soil by 89%, 72.5%, and 32.7%, respectively. The increase in soil strength caused by the coupling effect is smaller than the sum of the strength increase caused by the two factors. The main reason is that the soil structure can reduces the compaction effect of overconsolidation, and the compaction load applied during the process of overconsolidation can also damage the soil structure, and the scanning electron microscopy observation is consistent with the experimental results and analysis. Finally, an empirical relation was developed for the effect of overconsolidation, structural properties, and their coupling on soil strength. The calculated results of the formula are highly consistent with the experimental data, and have good rationality and accuracy.

Reevaluation of the adhesion between cellulose materials using macro spherical beads and flat model surfaces.

Interactions between dry cellulose were studied using model systems, cellulose beads, and cellulose films, using custom-built contact adhesion testing equipment. Depending on the configuration of the substrates in contact, Polydimethylsiloxane (PDMS) film, cellulose films spin-coated either on PDMS or glass, the interaction shows three distinct processes. Firstly, molecular interlocking is formed between cellulose and cellulose when there is a soft PDMS thin film backing the cellulose film. Secondly, without backing, no initial attraction force between the surfaces is observed. Thirdly, a significant force increase, ∆F, is observed during the retraction process for cellulose on glass, and there is a maximum in ∆F when the retraction rate is increased. This is due to the kinetics of a contacting process occurring in the interaction zone between the surfaces caused by an interdigitation of a fine fibrillar structure at the nano-scale, whereas, for the spin-coated cellulose surfaces on the PDMS backing, there is a more direct adhesive failure. The results have generated understanding of the interaction between cellulose-rich materials, which helps design new, advanced cellulose-based materials. The results also show the complexity of the interaction between these surfaces and that earlier mechanisms, based on macroscopic material testing, are simply not adequate for molecular tailoring.

Supervised contrastive learning enhances graph convolutional networks for predicting neurodevelopmental deficits in very preterm infants using brain structural connectome.

Very preterm (VPT) infants (born at less than 32 weeks gestational age) are at high risk for various adverse neurodevelopmental deficits. Unfortunately, most of these deficits cannot be accurately diagnosed until the age of 2-5 years old. Given the benefits of early interventions, accurate diagnosis and prediction soon after birth are urgently needed for VPT infants. Previous studies have applied deep learning models to learn the brain structural connectome (SC) to predict neurodevelopmental deficits in the preterm population. However, none of these models are specifically designed for graph-structured data, and thus may potentially miss certain topological information conveyed in the brain SC. In this study, we aim to develop deep learning models to learn the SC acquired at term-equivalent age for early prediction of neurodevelopmental deficits at 2 years corrected age in VPT infants. We directly treated the brain SC as a graph, and applied graph convolutional network (GCN) models to capture complex topological information of the SC. In addition, we applied the supervised contrastive learning (SCL) technique to mitigate the effects of the data scarcity problem, and enable robust training of GCN models. We hypothesize that SCL will enhance GCN models for early prediction of neurodevelopmental deficits in VPT infants using the SC. We used a regional prospective cohort of ∼280 VPT infants who underwent MRI examinations at term-equivalent age from the Cincinnati Infant Neurodevelopment Early Prediction Study (CINEPS). These VPT infants completed neurodevelopmental assessment at 2 years corrected age to evaluate cognition, language, and motor skills. Using the SCL technique, the GCN model achieved mean areas under the receiver operating characteristic curve (AUCs) in the range of 0.72∼0.75 for predicting three neurodevelopmental deficits, outperforming several competing models. Our results support our hypothesis that the SCL technique is able to enhance the GCN model in our prediction tasks.

Emergent energy dissipation in quantum limit.

Energy dissipation is of fundamental interest and crucial importance in quantum systems. However, whether energy dissipation can emerge without backscattering inside topological systems remains a question. As a hallmark, we propose a microscopic picture that illustrates energy dissipation in the quantum Hall (QH) plateau regime of graphene. Despite the quantization of Hall, longitudinal, and two-probe resistances (dubbed as the quantum limit), we find that the energy dissipation emerges in the form of Joule heat. It is demonstrated that the non-equilibrium energy distribution of carriers plays much more essential roles than the resistance on energy dissipation. Eventually, we suggest probing the phenomenon by measuring local temperature increases in experiments and reconsidering the dissipation typically ignored in realistic topological circuits.

Sarcopenia is associated with leukopenia in urothelial carcinoma patients who receive tislelizumab combined with gemcitabine and cisplatin therapy.

BACKGROUND: In the era of combination therapy, there has been limited research on body composition. Specific body composition, such as sarcopenia, possesses the potential to serve as a predictive biomarker for toxic effects and clinical response in patients with urothelial carcinoma (UC) undergoing tislelizumab combined with gemcitabine and cisplatin (T + GC). MATERIALS AND METHODS: A total of 112 UC patients who received T + GC were selected at the Affiliated Hospital of Xuzhou Medical University from April 2020 to January 2023. Baseline patient characteristics and detailed hematological parameters were collected using the electronic medical system and laboratory examinations. The computed tomography images of patients were analyzed to calculate psoas muscle mass index (PMI). We evaluated the association between sarcopenia (PMI < 4.5 cm2/m2 in men; PMI < 3.3 cm2/m2 in women) and both hematological toxicity and tumor response. RESULTS: Overall, of the 112 patients (65.2% male, median age 56 years), 43 (38.4%) were defined as sarcopenia. Patients with sarcopenia were notably older (p = 0.037), more likely to have hypertension (p = 0.009), and had poorer ECOG-PS (p = 0.027). Patients with sarcopenia were more likely to develop leukopenia (OR 2.969, 95% CI 1.028-8.575, p = 0.044) after receiving at least two cycles of T + GC. However, these significant differences were not observed in thrombocytopenia and anemia. There were no significant differences in the tumor response and grade 3-4 hematological toxicity between patients with sarcopenia and those without sarcopenia. CONCLUSIONS: Patients with sarcopenia were more likely to develop leukopenia after receiving T + GC. There were no notable alterations observed in relation to anemia or thrombocytopenia. No significant difference was found between the sarcopenia group and non-sarcopenia group in terms of tumor response and grade 3-4 hematological toxicity.

A dual diffusion model enables 3D molecule generation and lead optimization based on target pockets.

Structure-based generative chemistry is essential in computer-aided drug discovery by exploring a vast chemical space to design ligands with high binding affinity for targets. However, traditional in silico methods are limited by computational inefficiency, while machine learning approaches face bottlenecks due to auto-regressive sampling. To address these concerns, we have developed a conditional deep generative model, PMDM, for 3D molecule generation fitting specified targets. PMDM consists of a conditional equivariant diffusion model with both local and global molecular dynamics, enabling PMDM to consider the conditioned protein information to generate molecules efficiently. The comprehensive experiments indicate that PMDM outperforms baseline models across multiple evaluation metrics. To evaluate the applications of PMDM under real drug design scenarios, we conduct lead compound optimization for SARS-CoV-2 main protease (Mpro) and Cyclin-dependent Kinase 2 (CDK2), respectively. The selected lead optimization molecules are synthesized and evaluated for their in-vitro activities against CDK2, displaying improved CDK2 activity.

Divergent effects of sex on hippocampal subfield alterations in drug-naive patients with major depressive disorder.

BACKGROUND: The hippocampus is a crucial brain structure in etiological models of major depressive disorder (MDD). It remains unclear whether sex differences in the incidence and symptoms of MDD are related to differential illness-associated brain alterations, including alterations in the hippocampus. This study investigated divergent the effects of sex on hippocampal subfield alterations in drug-naive patients with MDD. METHODS: High-resolution structural MR images were obtained from 144 drug-naive individuals with MDD early in their illness course and 135 age- and sex-matched healthy controls (HCs). Hippocampal subfields were segmented using FreeSurfer software and analyzed in terms of both histological subfields (CA1-4, dentate gyrus, etc.) and more integrative larger functional subregions (head, body and tail). RESULTS: We observed a significant overall reduction in hippocampal volume in MDD patients, with deficits more prominent deficits in the posterior hippocampus. Differences in anatomic alterations between male and female patients were observed in the CA1-head, presubiculum-body and fimbria in the left hemisphere. Exploratory analyses revealed different patterns of clinical and memory function correlations with histological subfields and functional subregions between male and female patients primarily in the hippocampal head and body. LIMITATIONS: This cross-sectional study cannot clarify the causality of hippocampal alterations or their association with illness risk or onset. CONCLUSIONS: These findings represent the first reported sex-specific alterations in hippocampal histological subfields in patients with MDD early in the illness course prior to treatment. Sex-specific hippocampal alterations may contribute to diverse sex differences in the clinical presentation of MDD.

The changing nature of groundwater in the global water cycle.

In recent decades, climate change and other anthropogenic activities have substantially affected groundwater systems worldwide. These impacts include changes in groundwater recharge, discharge, flow, storage, and distribution. Climate-induced shifts are evident in altered recharge rates, greater groundwater contribution to streamflow in glacierized catchments, and enhanced groundwater flow in permafrost areas. Direct anthropogenic changes include groundwater withdrawal and injection, regional flow regime modification, water table and storage alterations, and redistribution of embedded groundwater in foods globally. Notably, groundwater extraction contributes to sea level rise, increasing the risk of groundwater inundation in coastal areas. The role of groundwater in the global water cycle is becoming more dynamic and complex. Quantifying these changes is essential to ensure sustainable supply of fresh groundwater resources for people and ecosystems.

Anemia and Low Body Mass Index in Axial Spondyloarthritis: Results from ChinaSpA, the Chinese Spondyloarthritis Registry.

INTRODUCTION: Anemia and malnutrition are recognized indicators of suboptimal physical condition in chronic inflammatory diseases. This study aimed to examine the association between anemia, low body mass index (BMI), and clinical outcomes in axial spondyloarthritis (axSpA). METHOD: This cross-sectional analysis utilized data from the multicenter ChinaSpA cohort. A total of 4146 participants with axSpA were categorized into four groups based on BMI and hemoglobin levels: those with both anemia and low BMI, those with anemia only, those with low BMI only, and those with neither condition. Logistic regression analyses were performed to analyze the association between anemia, low BMI, inflammation status, functional impairment, and disease activity. RESULTS: Anemia was present in 13.94%, low BMI in 11.99%, and both conditions in 2.15% of axSpA participants. Those with both anemia and low BMI showed significantly higher levels of inflammation (hypersensitive C-reactive protein [hsCRP] 30.60 mg/L vs. 8.44 mg/L), functional impairment (Bath Ankylosing Spondylitis Functional Index [BASFI] 3.80 vs. 2.10), and disease activity (Bath Ankylosing Spondylitis Disease Activity Index [BASDAI] 4.52 ± 2.04 vs. 3.67 ± 2.21; Ankylosing Spondylitis Disease Activity Score calculated with C-reactive protein [ASDAS_CRP] 3.51 ± 1.10 vs. 2.62 ± 1.21) compared to those without these conditions. After adjusting for sex and age, significant associations were observed between elevated hsCRP levels and the presence of low BMI (odds ratio [OR] 1.44, 95% CI 1.17-1.78), anemia (OR 1.91, 95% CI 1.56-2.32), and their concurrent presence (OR 3.59, 95% CI 2.22-5.80). Similarly, increased BASFI was significantly associated with low BMI (OR 1.57, 95% CI 1.25-1.97), anemia (OR 1.47, 95% CI 1.19-1.80), and their combination (OR 3.11, 95% CI 2.02-4.78). CONCLUSION: All-cause anemia and low BMI are prevalent complications in patients with axSpA, exhibiting a significant correlation with elevated inflammation status and functional impairment. The simultaneous occurrence of anemia and low BMI particularly exacerbates clinical outcomes, emphasizing the critical role of comprehensive nutritional assessment and management in the therapeutic strategy for axSpA.

Distinctive intrinsic functional connectivity alterations of anterior cingulate cortex subdivisions in major depressive disorder: A systematic review and meta-analysis.

Evidence of whether the intrinsic functional connectivity of anterior cingulate cortex (ACC) and its subregions is altered in major depressive disorder (MDD) remains inconclusive. A systematic review and meta-analysis were therefore performed on the whole-brain resting-state functional connectivity (rsFC) studies using the ACC and its subregions as seed regions in MDD, in order to draw more reliable conclusions. Forty-four ACC-based rsFC studies were included, comprising 25 subgenual ACC-based studies, 11 pregenual ACC-based studies, and 17 dorsal ACC-based studies. Specific alterations of rsFC were identified for each ACC subregion in patients with MDD, with altered rsFC of subgenual ACC in emotion-related brain regions, of pregenual ACC in sensorimotor-related regions, and of dorsal ACC in cognition-related regions. Furthermore, meta-regression analysis revealed a significant negative correlation between the pgACC-caudate hypoconnectivity and percentage of female patients in the study cohort. This meta-analysis provides robust evidence of altered intrinsic functional connectivity of the ACC subregions in MDD, which may hold relevance to understanding the origin of, and treating, the emotional, sensorimotor and cognitive dysfunctions that are often observed in these patients.