Different levels of prepulse inhibition among patients with first-episode schizophrenia, bipolar disorder and major depressive disorder.

BACKGROUND: Deficits in prepulse inhibition may be a common feature in first-episode schizophrenia, bipolar disorder (BD) and major depressive disorder (MDD). We sought to explore the levels and viability of prepulse inhibition to differentiate first-episode schizophrenia, BD and MDD in patient populations. METHODS: We tested patients with first-episode schizophrenia, BD or MDD and healthy controls using prepulse inhibition paradigms, namely perceived spatial co-location (PSC-PPI) and perceived spatial separation (PSS-PPI). RESULTS: We included 53 patients with first-episode schizophrenia, 30 with BD and 25 with MDD, as well as 82 healthy controls. The PSS-PPI indicated that the levels of prepulse inhibition were smallest to largest, respectively, in the first-episode schizophrenia, BD, MDD and control groups. Relative to the healthy controls, the prepulse inhibition deficits in the first-episode schizophrenia group were significant (p < 0.001), but the prepulse inhibitions were similar between patients with BD and healthy controls, and between patients with MDD and healthy controls. The receiver operating characteristic curve analysis showed that PSS-PPI (area under the curve [AUC] 0.73, p < 0.001) and latency (AUC 0.72, p < 0.001) were significant for differentiating patients with first-episode schizophrenia or BD from healthy controls. LIMITATIONS: The demographics of the 4 groups were not ideally matched. We did not perform cognitive assessments. The possible confounding effect of medications on prepulse inhibition could not be eliminated. CONCLUSION: The level of prepulse inhibition among patients with first-episode schizophrenia was the lowest, with levels among patients with BD, patients with MDD and healthy controls increasingly higher. The PSS-PPI paradigm was more effective than PSC-PPI to recognize deficits in prepulse inhibition. These results provide a basis for further research on biological indicators that can assist differential diagnoses in psychosis.

Vitamin D deficiency and the risk of diabetic retinopathy in patients with type 2 diabetes in Tibet: a cross-sectional analysis.

BACKGROUND: Diabetic retinopathy (DR) is one of the most common complications of diabetes worldwide. The aim of this study was to assess the prevalence of DR in hospitalized patients with type 2 diabetes (T2DM) in Tibet and to identify risk factors that may influence the occurrence of DR. METHODS: This was a cross-sectional study conducted in a third-class hospital in the Tibet Autonomous Region. The prevalence of DR in hospitalized patients with T2DM was measured. Univariate and multivariate logistic regression, restricted cubic spline (RCS) analysis and receiver-operating characteristic curve analysis were used to investigate the risk factors for DR. RESULTS: The prevalence of DR was 29.3%. The duration of diabetes; concentrations of 25-OH-VitD3, hemoglobin, fasting insulin, alanine aminotransferase, total bilirubin, and creatinine; and HOMA-IR were significantly different between DR patients and non-DR patients (all P < 0.05). Univariate and multivariate logistic regression revealed that a longer duration of diabetes and lower 25-OH-VitD3 levels were associated with increased DR risk. RCS analysis suggested overall positive associations of the duration of diabetes and 25-OH-VitD3 concentrations with DR risk (P nonlinearity < 0.05). The turning points for the duration of diabetes and 25-OH-VitD3 concentrations were 5.1 years and 10.6 ng/mL, respectively. The sensitivity, specificity, and area under the receiver-operating characteristic curve for the combination of the duration of diabetes and 25-OH-VitD3 levels were 79.4%, 69.4% and 0.764, respectively. CONCLUSIONS: Given the high prevalence of DR in hospitalized patients with T2DM in Tibet, vitamin D supplementation seems to be important in the prevention of DR to some degree.

Osteosarcoma-targeted Cu and Ce based oxide nanoplatform for NIR II fluorescence/magnetic resonance dual-mode imaging and ros cascade amplification along with immunotherapy.

BACKGROUND: As the lethal bone tumor, osteosarcoma often frequently occurs in children and adolescents with locally destructive and high metastasis. Distinctive kinds of nanoplatform with high therapeutical effect and precise diagnosis for osteosarcoma are urgently required. Multimodal optical imaging and programmed treatment, including synergistic photothermal-chemodynamic therapy (PTT-CDT) elicits immunogenetic cell death (ICD) is a promising strategy that possesses high bio-imaging sensitivity for accurate osteosarcoma delineating as well as appreciable therapeutic efficacy with ignorable side-effects. METHODS AND RESULTS: In this study, mesoporous Cu and Ce based oxide nanoplatform with Arg-Gly-Asp (RGD) anchoring is designed and successfully constructed. After loading with indocyanine green, this nanoplatform can be utilized for precisely targeting and efficaciously ablating against osteosarcoma via PTT boosted CDT and the closely following ICD stimulation both in vitro and in vivo. Besides, it provides off-peak fluorescence bio-imaging in the second window of near-infrared region (NIR II, 1000-1700 nm) and Magnetic resonance signal, serves as the dual-mode contrast agents for osteosarcoma tissue discrimination. CONCLUSION: Tumor targeted Cu&Ce based mesoporous nanoplatform permits efficient osteosarcoma suppression and dual-mode bio-imaging that opens new possibility for effectively diagnosing and inhibiting the clinical malignant osteosarcoma.

Targeting the glutamine-arginine-proline metabolism axis in cancer.

Metabolic abnormalities are an important feature of tumours. The glutamine-arginine-proline axis is an important node of cancer metabolism and plays a major role in amino acid metabolism. This axis also acts as a scaffold for the synthesis of other nonessential amino acids and essential metabolites. In this paper, we briefly review (1) the glutamine addiction exhibited by tumour cells with accelerated glutamine transport and metabolism; (2) the methods regulating extracellular glutamine entry, intracellular glutamine synthesis and the fate of intracellular glutamine; (3) the glutamine, proline and arginine metabolic pathways and their interaction; and (4) the research progress in tumour therapy targeting the glutamine-arginine-proline metabolic system, with a focus on summarising the therapeutic research progress of strategies targeting of one of the key enzymes of this metabolic system, P5CS (ALDH18A1). This review provides a new basis for treatments targeting the metabolic characteristics of tumours.

Association of urinary and seminal plasma vanadium concentrations with semen quality: A repeated-measures study of 1135 healthy men.

Although animal studies have shown the reproductive toxicity of vanadium, less is known about its effects on semen quality in humans. Among 1135 healthy men who were screened as potential semen donors, we investigated the relationships of semen quality with urinary and seminal plasma vanadium levels via inductively coupled plasma-mass spectrometry (ICP-MS). Spearman rank correlation tests and linear regression models were used to assess the correlations between average urinary and within-individual pooled seminal plasma vanadium concentrations (n = 1135). We utilized linear mixed-effects models to evaluate the associations of urinary and seminal plasma vanadium levels (n = 1135) with repeated sperm quality parameters (n = 5576). Seminal plasma vanadium concentrations were not significantly correlated with urinary vanadium concentrations (r = 0.03). After adjusting for possible confounders, we observed inverse relationships of within-individual pooled seminal plasma vanadium levels with total count, semen volume, and sperm concentration (all P values for trend < 0.05). Specifically, subjects in the highest (vs. lowest) tertile of seminal plasma vanadium concentrations had - 11.3% (-16.4%, -5.9%), - 11.1% (-19.1%, -2.4%), and - 20.9% (-29.0%, -11.8%) lower sperm volume, concentration, and total count, respectively; moreover, urinary vanadium levels appeared to be negatively associated with sperm motility. These relationships showed monotonically decreasing dose-response patterns in the restricted cubic spline analyses. Our results demonstrated a poor correlation between urinary and seminal plasma levels of vanadium, and elevated vanadium concentrations in urine and seminal plasma may be adversely related to male semen quality.

Melittin Treats Periprosthetic Osteolysis in a Rat Model by Inhibiting the NF-kB Pathway and Regulating the Ratio of Receptor Activator of Nuclear Factor Kappa B Ligand/Osteoprotegerin.

BACKGROUND: Aseptic loosening around the prosthesis is a common cause of failure in total joint arthroplasty. Polyethylene wear particles trigger the release of inflammatory factors by macrophages. Key mediators involved in osteoclastogenesis include interleukin-6, tumor necrosis factor-α, receptor activator of nuclear factor kappa B (RANK), RANK ligand (RANKL), and bone protection hormone (Osteoprotegerin [OPG]). The purpose of our experiment was to see whether melittin can slow down the release of inflammatory mediators through the NF-kB pathway, regulate the RANKL/OPG ratio, reduce osteoclast formation, and delay the onset of arthritis in rats. METHODS: A total of 20 male Sprague-Dawley rats (10 months, Specific Pathogen Free, 350 g ± 20 g) were randomly divided into 5 groups: sham group, model group, melittin concentration 1 group (0.2 mg/kg), concentration 2 group (0.4 mg/kg), and concentration 3 group (0.6 mg/kg). All rats were implanted with TA2 high-purity titanium rods. A drill was used to create a bone canal along the long axis of the femur in the intercondylar notch. The model group and experimental groups were exposed to polyethylene particles, while the sham group did not receive any particles. RESULTS: The melittin group exhibited significantly increased serum levels of serum P, calcium-phosphorus product, OPG, PINP, PINP/CTX-I, and OPG/RANKKL (P < .05). In the experimental group, micro computed tomography scanning results revealed a decrease in the amount of bone defect around the prosthesis. Immunofluorescence analysis demonstrated a decrease in the expression of IKKα and P65, while the expression of OPG showed an upward trend. Both Hematoxylin-Eosin and Tartrate-Resistant Acid Phosphatase staining revealed less osteoclast and inflammatory cell infiltration in bone resorption pits. CONCLUSIONS: Our study demonstrates that melittin has the ability to inhibit the NF-kB pathway in a rat model, and reduce the impact of RANKL/OPG, thereby delaying osteoclast activity and alleviating periprosthetic osteolysis.

Design and properties of ternary alkali-activated binder based on blast furnace slag, recycled powder and waste glass powder.

Ternary alkali-activated binder was prepared by blast furnace slag (GGBS), recycled powder (RP) and waste glass powder (WGP) using simplex centroid design method. By measuring the fluidity, setting time, drying shrinkage and mechanical property of specimen, the complementary effect of GGBS, RP and WGP was discussed. The reaction mechanism and microstructure were explored by X-ray diffraction and scanning electron microscopy. The results reveal that the addition of RP could significantly reduce the fluidity and setting time of paste, while WGP can obviously improve the rheological property and play a retarding role. The workability of paste can be effectively regulated by mixing RP and WGP together. Whether added alone or in combination, RP and WGP can effectively improve the shrinkage performance. In the ternary system, GGBS can be rapidly activated and form a skeleton structure. The fine RP particles can play a good role in filling the structure, and the pozzolanic reaction of WGP gradually occurs, which makes the microstructure more compact. The incorporation of GGBS, RP and WGP can promote the growth of hydration products, improve the density of microstructure, and form a certain complementary effect.

Revealing the Antiperspirant Components of Floating Wheat and Their Mechanisms of Action through Metabolomics and Network Pharmacology.

Floating wheat is a classical herbal with potential efficacy in the treatment of hyperhidrosis. Aiming at revealing the main components and potential mechanisms of floating wheat, a comprehensive and unique phytopharmacology profile study was carried out. First, common wheat was used as a control to look for chemical markers of floating wheat. In the screening analysis, a total of 180 shared compounds were characterized in common wheat and floating wheat, respectively. The results showed that floating wheat and common wheat contain similar types of compounds. In addition, in non-targeted metabolomic analysis, when taking the contents of the constituents into account, it was found that there indeed existed quite a difference between floating wheat and common wheat and 17 potential biomarkers for floating wheat. Meanwhile, a total of seven components targeted for hyperhidrosis were screened out based on network pharmacology. Seven key differential components were screened, among which kaempferol, asiatic acid, sclareol, enoxolone, and secoisolariciresinol had higher degree values than the others. The analysis of interacting genes revealed three key genes, namely, MAP2K1, ESR1, and ESR2. The Kyoto Encyclopaedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses showed that various signaling pathways were involved. Prolactin signaling, thyroid cancer, endocrine resistance, gonadotropin secretion, and estrogen signaling pathways were the main pathways of the intervention of floating wheat in excessive sweating, which was associated with the estrogenic response, hormone receptor binding, androgen metabolism, apoptosis, cancer, and many other biological processes. Molecular docking showed that the screened key components could form good bindings with the target proteins through intermolecular forces. This study reveals the active ingredients and potential molecular mechanism of floating wheat in the treatment of hyperhidrosis and provides a reference for subsequent basic research.

Virtual water flows and drivers in the international trade of agricultural products of the regional comprehensive economic partnership.

The regional comprehensive economic partnership (RCEP) is today the largest free trade area in the world. This paper examines agricultural trade in the RCEP from 2010 to 2019 through the perspective of virtual water. And the drivers of the virtual water flow between China and the RCEP are also explored. The results are as follows: the virtual water flow during the study period was 2,576.51 billion m3. From a temporal perspective, the annual virtual water flow over the study period is characterized by a slow rise-significant fall-slow rise. It has the characteristics of concentration in spatial distribution and water resources and product structure. However, the concentration degree showed a downward trend during the study period. Then, we have divided the major trading into four categories based on whether there is a shortage of water on both sides of the trade. In terms of the drivers of virtual water flows between China and the RCEP, we have used the gravity model to arrive at the following findings: crop yields, bilateral economic scale, and agricultural labor resources are the main drivers. Our research results have reference values for adjusting bilateral agricultural trade and water conservation.

[Multi-index evaluation of different parts of Amomum villosum].

To investigate the quality differences between the seeds and husks of Amomum villosum and explore the rationality of using the seeds without husks, this study determined the content of protocatechuic acid, vanillic acid, epicatechin, quercitrin, volatile oil, water extract, and ethanol extract. The 2,2-diphenyl-1-picrylhydrazyl(DPPH), 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)(ABTS), and hydroxyl radical scavenging activities were determined to evaluate the antioxidant activities of seeds and husks. The quality differences between the seeds and husks were assessed through orthogonal partial least squares-discriminant analysis(OPLS-DA) and analytic hierarchy process(AHP) combined with the entropy weight method(EWM). Significant differences(P<0.05) were observed in all 10 indicators between the seeds and husks. The levels of epicatechin, quercetin, and volatile oil were higher in the seeds, whereas those of protocatechuic acid, vanillic acid, water extract, and ethanol extract were higher in the husks. The seeds showed stronger scavenging ability against DPPH and ABTS radicals, while the husks showed a stronger scavenging effect on hydroxyl radicals. OPLS-DA significantly discriminated between the seeds and husks. Furthermore, volatile oil, water extract, DPPH radical scavenging rate, quercitrin, ABTS radical scavenging rate, hydroxyl radical scavenging rate, and vanillic acid were selected as the main differential indicators by variable importance in projection(VIP). Comprehensive scores calculated by AHP combined with EWM indicated that the seeds were superior to husks in terms of overall quality. However, there are still some dominant components and a certain antioxidant effect in the husks. Therefore, it is suggested to using Amomi Fructus with a certain amount of husks or utilizing the husks for other purposes.

SAE3D: Set Abstraction Enhancement Network for 3D Object Detection Based Distance Features.

With the increasing demand from unmanned driving and robotics, more attention has been paid to point-cloud-based 3D object accurate detection technology. However, due to the sparseness and irregularity of the point cloud, the most critical problem is how to utilize the relevant features more efficiently. In this paper, we proposed a point-based object detection enhancement network to improve the detection accuracy in the 3D scenes understanding based on the distance features. Firstly, the distance features are extracted from the raw point sets and fused with the raw features regarding reflectivity of the point cloud to maximize the use of information in the point cloud. Secondly, we enhanced the distance features and raw features, which we collectively refer to as self-features of the key points, in set abstraction (SA) layers with the self-attention mechanism, so that the foreground points can be better distinguished from the background points. Finally, we revised the group aggregation module in SA layers to enhance the feature aggregation effect of key points. We conducted experiments on the KITTI dataset and nuScenes dataset and the results show that the enhancement method proposed in this paper has excellent performance.

Generation, division and training: A promising method for source-free unsupervised domain adaptation.

Conventional unsupervised domain adaptation (UDA) methods often presuppose the existence of labeled source domain samples while adapting the source model to the target domain. Nevertheless, this premise is not always tenable in the context of source-free UDA (SFUDA) attributed to data privacy considerations. Some existing methods address this challenging SFUDA problem by self-supervised learning. But inaccurate pseudo-labels are always unavoidable to degrade the performance of the target model among these methods. Therefore, we propose a promising SFUDA method, namely Generation, Division and Training (GDT) which aims to promote the reliability of pseudo-labels for self-supervised learning and encourage similar features to have closer predictions than dissimilar ones by contrastive learning. Specifically in our GDT method, we first refine pseudo-labels with deep clustering for target samples and then split them into reliable samples and unreliable samples. After that, we adopt self-supervised learning and information maximization for reliable samples training. And for unreliable samples, we conduct contrastive learning via the perspective of similarity and disparity to attract similar samples and repulse dissimilar samples, which helps pull the similar features closed and push the dissimilar features away, leading to efficient feature clustering. Thorough experimentation on three benchmark datasets substantiates the excellence of our proposed approach.

SpyGlass guided PDT for advanced intraductal papillary mucinous neoplasm of the bile tract: A case report and literature review.

Intraductal papillary mucinous neoplasm of the bile tract is a rare biliary tumor characterized by mucin growth within the bile duct. In the early stages, it often presents without significant obstruction, this often leads to its discovery in the advanced stages. We report a case of a 63-year-old female with an intraductal papillary mucinous neoplasm of the bile duct (IPMN-B). The patient had a history of intrahepatic bile duct stones and biliary ascariasis. She gradually developed symptoms such as jaundice and intermittent fever before admission, and a bile duct biopsy confirmed the diagnosis of IPMN-B. Currently, endoscopic photodynamic therapy (PDT) is considered an effective treatment for bile duct cancer. In this case, we performed two sessions of PDT guided by SpyGlass. The patient experienced complete remission postoperatively, and there has been no evidence of tumor recurrence or metastasis in the three years following the procedure.

Research progress on the association between glycemic variability index derived from CGM and cardiovascular disease complications.

Currently, glycated hemoglobin A1c (HbA1c) has been widely used to assess the glycemic control of patients with diabetes. However, HbA1c has certain limitations in describing both short-term and long-term glycemic control. To more accurately evaluate the glycemic control of diabetes patients, the continuous glucose monitoring (CGM) technology has emerged. CGM technology can provide robust data on short-term glycemic control and introduce new monitoring parameters such as time in range, time above range, and time below range as indicators of glycemic fluctuation. These indicators are used to describe the changes in glycemic control after interventions in clinical research or treatment modifications in diabetes patient care. Recent studies both domestically and internationally have shown that these indicators are not only associated with microvascular complications of diabetes mellitus but also closely related to cardiovascular disease complications and prognosis. Therefore, this article aims to comprehensively review the association between CGM-based glycemic parameters and cardiovascular disease complications by analyzing a large number of domestic and international literature. The purpose is to provide scientific evidence and guidance for the standardized application of these indicators in clinical practice, in order to better evaluate the glycemic control of diabetes patients and prevent the occurrence of cardiovascular disease complications. This research will contribute to improving the quality of life for diabetes patients and provide important references for clinical decision-making.

Photodynamic therapy inhibits cancer progression and induces ferroptosis and apoptosis by targeting P53/GPX4/SLC7A11 signaling pathways in cholangiocarcinoma.

BACKGROUND: Cholangiocarcinoma (CCA) is a malignant tumor with a poor prognosis. The specific mechanism of photodynamic therapy (PDT) in treating CCA remains unclear. This study aims to investigate the mechanisms of PDT in the treatment of CCA and try to improve the therapeutic effect of PDT by intervening associated signaling pathways. METHODS: The Cell Counting Kit-8 (CCK-8) was used to examine the cytotoxicity of CCA cell lines following PDT. Apoptosis and reactive oxygen species (ROS) levels were measured by flow cytometry. A transmission electron microscope was used to study the changes in cell mitochondria after PDT. The levels of glutathione (GSH), malondialdehyde (MDA), ferrous iron (Fe2+), lactate dehydrogenase (LDH), and lipid peroxide (LPO) were determined. Changes in the expression of apoptosis and ferroptosis-related proteins were determined using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. Xenograft tumor models were developed to investigate the effects of PDT on tumor proliferation, apoptosis, and ferroptosis in vivo. RESULTS: PDT inhibited tumor proliferation and induced apoptosis both in vivo and in vitro. This treatment led to swelling and damage of the mitochondria in affected cells. Furthermore, ROS levels rose, accompanied by an increase in the proportion of apoptotic-positive cells. The expressions of Bax and Caspase-3 were upregulated, while the Bcl-2 was downregulated. Meanwhile, PDT triggered ferroptosis, marked by decreased expressions of GPX4 and SLC7A11, and reduced GSH levels. This was accompanied by upregulation of P53 expression and heightened levels of Fe2+, LPO, MDA, and LDH. After inducing the ferroptosis pathway, the therapeutic effect of PDT was enhanced, the tumor tissue was further reduced, and the degree of malignancy was reduced. CONCLUSION: PDT promotes apoptosis and ferroptosis of cholangiocarcinoma cells by activating the P53/SLC7A11/GPX4 signaling pathway and inhibits the growth of cholangiocarcinoma. Inducing ferroptosis can enhance the effectiveness of photodynamic therapy.

Quasi-MOF-Engineered MnOx/CeBTC Multinanozyme as a Robust Self-Cascade ROS Generator toward Antibacterial Face Mask.

It is of great importance to endow personal protective equipments with bactericidal property combating against infected pathogens. Nanozyme that can generate reactive oxygen species (ROS) in an enzyme-catalytic manner is regarded as a novel and promising nanobactericide. But until now, very rare of them is designed specifically for personal protective equipments. In this study, a multinanozyme of manganese oxide supported on Ce-containing MOF (CeBTC) is constructed with post-engineering via a quasi-metal-organic framework (MOF) strategy (denoted as MnOx/q-CeBTC). The strategy enables a full exposure of the metal cluster nodes, introduction of new active Mn─O─Ce bonds and strengthens interaction between the metal nodes and the guest oxide. As an advanced multinanozyme, the MnOx/q-CeBTC exhibits excellent multiple enzymatic activities at low temperature, and enables abundant and self-cascade ROS generation without H2O2 addition. This empowers it with high efficiency in bacteria killing, which is also reflected when incorporated into face mask to combat against pathogen invasion even at low temperature. The results achieved in this work provide guidance for rational design of effective bactericide based on nanozyme and broaden their application in personal protective equipment and other fields.

Effect of plant-soil system on the restoration of community stability after wildfire in the northeast margin of Qinghai-Tibet plateau.

Wildfires, as an environmental filter, are pivotal ecological disturbances that reshape plant communities and soil dynamics, playing a crucial role in regulating biogeographic patterns and ecosystem services. In this study, we aim to explore the effects of wildfires on forest ecosystems, specifically focusing on the plant-soil feedback mechanisms within the northeastern margin of the Qinghai-Tibet Plateau (QTP). Utilizing Partial Least Squares Path Modeling (PLS-PM), we investigated the interrelationships among soil physicochemical properties, enzyme activities, species diversity, and community stability at varying post-fire recovery stages (5, 15, and 23 years). Results indicated that in the early recovery stages, rapid changes in soil properties such as decreased pH (p < 0.001) and increased nutrient availability facilitate the emergence of early successional species with high resource utilization traits. As the ecosystem evolved toward a climax community, the soil and vegetation exhibit increased stability. Furthermore, soil enzyme activities displayed dynamic patterns that corresponded with changes in soil nutrient content, directly influencing the regeneration and diversity of plant communities. Importantly, our study documented a transition in the influence of soil properties on community stability from direct positive effects in initial recovery phases to negative impacts in later stages, while indirect benefits accrue through increased species diversity and enzyme activity. Vegetation composition and structure changed dynamically with recovery time during community succession. Plant nutrient absorption and accumulation affected nutrient dynamics in the soil, influencing plant regeneration, distribution, and diversity. Our results underscore the complex interactions between soil and vegetation that drive the recovery dynamics post-wildfire, highlighting the resilience of forest ecosystems to fire disturbances. This study contributes to the understanding of post-fire recovery processes and offers valuable insights for the management and restoration of fire-affected forest ecosystems.

Dynamic restoration mechanism of plant community in the burned area of northeastern margin of Qinghai-Tibet Plateau.

Forest fires play a pivotal role in influencing ecosystem evolution, exerting a profound impact on plant diversity and community stability. Understanding post-fire recovery strategies holds significant scientific importance for the ecological succession and restoration of forest ecosystems. This study utilized Partial Least Squares Path Modeling (PLS-PM) to investigate dynamic relationships among plant species diversity, phylogenetic diversity, soil properties, and community stability during various recovery stages (5-year, 15-year, and 23-year) following wildfires on the northeastern margin of the Qinghai-Tibet Plateau. The findings revealed: (1) Over time, species richness significantly decreased (p< 0.05 or p< 0.01), while species diversity and dominance increased, resulting in uniform species distribution. Community stability progressively improved, with increased species compositional similarity. (2) Throughout succession, phylogenetic diversity (PD) significantly decreased (p< 0.01), accompanied by rising Mean Pairwise Distance (MPD) and Mean Nearest Taxon Distance (MNTD). Net Relatedness Index (NRI) shifted from positive to negative, indicating an increasing aggregation and dominance of plants with similar evolutionary traits in burned areas. Early succession witnessed simultaneous environmental filtering and competitive exclusion, shifting predominantly to competitive exclusion in later stages. (3) PLS-PM revealed that in the early recovery stage, soil properties mainly affected community stability, while species diversity metamorphosed into the primary factor in the mid-to-late stages. In summary, this study showed that plant diversity and phylogenetic variation were successful in revealing changes in community structure during the succession process. Soil characteristics functioned as selective barriers for plant communities during succession, and community stability underwent a multi-faceted and dynamic process. The soil-plant dynamic feedback continuously enhanced soil conditions and community vegetation structure thereby augmenting stability. Post-fire vegetation gradually transitioned towards the original native state, demonstrating inherent ecological self-recovery capabilities in the absence of secondary disturbances.

Developing and comparing deep learning and machine learning algorithms for osteoporosis risk prediction.

Introduction: Osteoporosis, characterized by low bone mineral density (BMD), is an increasingly serious public health issue. So far, several traditional regression models and machine learning (ML) algorithms have been proposed for predicting osteoporosis risk. However, these models have shown relatively low accuracy in clinical implementation. Recently proposed deep learning (DL) approaches, such as deep neural network (DNN), which can discover knowledge from complex hidden interactions, offer a new opportunity to improve predictive performance. In this study, we aimed to assess whether DNN can achieve a better performance in osteoporosis risk prediction. Methods: By utilizing hip BMD and extensive demographic and routine clinical data of 8,134 subjects with age more than 40 from the Louisiana Osteoporosis Study (LOS), we developed and constructed a novel DNN framework for predicting osteoporosis risk and compared its performance in osteoporosis risk prediction with four conventional ML models, namely random forest (RF), artificial neural network (ANN), k-nearest neighbor (KNN), and support vector machine (SVM), as well as a traditional regression model termed osteoporosis self-assessment tool (OST). Model performance was assessed by area under 'receiver operating curve' (AUC) and accuracy. Results: By using 16 discriminative variables, we observed that the DNN approach achieved the best predictive performance (AUC = 0.848) in classifying osteoporosis (hip BMD T-score ≤ -1.0) and non-osteoporosis risk (hip BMD T-score > -1.0) subjects, compared to the other approaches. Feature importance analysis showed that the top 10 most important variables identified by the DNN model were weight, age, gender, grip strength, height, beer drinking, diastolic pressure, alcohol drinking, smoke years, and economic level. Furthermore, we performed subsampling analysis to assess the effects of varying number of sample size and variables on the predictive performance of these tested models. Notably, we observed that the DNN model performed equally well (AUC = 0.846) even by utilizing only the top 10 most important variables for osteoporosis risk prediction. Meanwhile, the DNN model can still achieve a high predictive performance (AUC = 0.826) when sample size was reduced to 50% of the original dataset. Conclusion: In conclusion, we developed a novel DNN model which was considered to be an effective algorithm for early diagnosis and intervention of osteoporosis in the aging population.

Celastrol regulates the oligomeric state and chaperone activity of αB-crystallin linked with protein homeostasis in the lens.

Protein misfolding and aggregation are crucial pathogenic factors for cataracts, which are the leading cause of visual impairment worldwide. α-crystallin, as a small molecular chaperone, is involved in preventing protein misfolding and maintaining lens transparency. The chaperone activity of α-crystallin depends on its oligomeric state. Our previous work identified a natural compound, celastrol, which could regulate the oligomeric state of αB-crystallin. In this work, based on the UNcle and SEC analysis, we found that celastrol induced αB-crystallin to form large oligomers. Large oligomer formation enhanced the chaperone activity of αB-crystallin and prevented aggregation of the cataract-causing mutant ßA3-G91del. The interactions between αB-crystallin and celastrol were detected by the FRET (Fluorescence Resonance Energy Transfer) technique, and verified by molecular docking. At least 9 binding patterns were recognized, and some binding sites covered the groove structure of αB-crystallin. Interestingly, αB-R120G, a cataract-causing mutation located at the groove structure, and celastrol can decrease the aggregates of αB-R120G. Overall, our results suggested celastrol not only promoted the formation of large αB-crystallin oligomers, which enhanced its chaperone activity, but also bound to the groove structure of its α-crystallin domain to maintain its structural stability. Celastrol might serve as a chemical and pharmacological chaperone for cataract treatment.