Plant-derived inducers in tumor differentiation therapy:A systematic review.

BACKGROUND: Differentiation therapy, a highly regarded treatment method in tumor research, aims to induce tumor cells to differentiate back to normal cells, deviating from the malignant pathway and returning to a benign state. Its development relies on the continuous discovery of efficient and low-toxic differentiation inducers, including plant-derived active components that offer significant biological utilization and therapeutic potential. For this reason, the exploration of plant-derived inducers, particularly in their application in differentiation therapy, holds great promise in advancing cancer treatment strategies toward more effective and safer alternatives. PURPOSE: This paper aims to provide a valuable reference for researchers seeking to identify natural, efficient, and low-toxic differentiation inducers from plants and highlights a promising research direction for the application of differentiation therapy in malignant tumor treatment. METHODS: For the collection of pertinent information, an extensive search was conducted across diverse literature and electronic databases, including PubMed, ScienceDirect, Wiley, ACS, CNKI, Springer, Taylor & Francis, Web of Science, Google Scholar, and Baidu Scholar. This comprehensive approach aimed to retrieve and include all relevant literature from 1985 to 2023. Primary keywords such as "Natural medicinal plant," "Differentiation therapy," and "Differentiation inducer" were utilized, supplemented by secondary search terms including "Cancer," "Tumor," "Herbal medicine," "Induced differentiation," and "Cancer treatment." RESULTS: This study systematically evaluated the application of plant-derived inducers in tumor-induced differentiation therapy. Through extensive literature review, specific plant components with confirmed differentiation-inducing properties were identified. Furthermore, potential molecular mechanisms underlying this process were outlined, shedding light on the future development of differentiation therapy in cancer treatment. CONCLUSION: Plant-derived active components exhibit substantial biological utility and therapeutic potential. Delving deeper into the research on these components as differentiation inducers holds promise for the selection of novel cancer drugs and the unveiling of novel pathways for cancer treatment. These results emphasize the importance of continued exploration and in-depth research into natural, efficient, and low-toxic differentiation inducers from plants, which could significantly advance cancer treatment strategies. Moreover, the highlighted research direction underscores the relevance of differentiation therapy in the context of malignant tumor treatment, indicating its potential as a safer and more effective alternative in cancer therapy.

Three-dimensional spatio-angular fluorescence microscopy with a polarized dual-view inverted selective-plane illumination microscope (pol-diSPIM).

Polarized fluorescence microscopy is a valuable tool for measuring molecular orientations, but techniques for recovering three-dimensional orientations and positions of fluorescent ensembles are limited. We report a polarized dual-view light-sheet system for determining the three-dimensional orientations and diffraction-limited positions of ensembles of fluorescent dipoles that label biological structures, and we share a set of visualization, histogram, and profiling tools for interpreting these positions and orientations. We model our samples, their excitation, and their detection using coarse-grained representations we call orientation distribution functions (ODFs). We apply ODFs to create physics-informed models of image formation with spatio-angular point-spread and transfer functions. We use theory and experiment to conclude that light-sheet tilting is a necessary part of our design for recovering all three-dimensional orientations. We use our system to extend known two-dimensional results to three dimensions in FM1-43-labelled giant unilamellar vesicles, fast-scarlet-labelled cellulose in xylem cells, and phalloidin-labelled actin in U2OS cells. Additionally, we observe phalloidin-labelled actin in mouse fibroblasts grown on grids of labelled nanowires and identify correlations between local actin alignment and global cell-scale orientation, indicating cellular coordination across length scales.

Multiple serum anti-glutamate receptor antibody levels in clozapine-treated/naïve patients with treatment-resistant schizophrenia.

BACKGROUND: Glutamatergic function abnormalities have been implicated in the etiology of treatment-resistant schizophrenia (TRS), and the efficacy of clozapine may be attributed to its impact on the glutamate system. Recently, evidence has emerged suggesting the involvement of immune processes and increased prevalence of antineuronal antibodies in TRS. This current study aimed to investigate the levels of multiple anti-glutamate receptor antibodies in TRS and explore the effects of clozapine on these antibody levels. METHODS: Enzyme linked immunosorbent assay (ELISA) was used to measure and compare the levels of anti-glutamate receptor antibodies (NMDAR, AMPAR, mGlur3, mGluR5) in clozapine-treated TRS patients (TRS-C, n = 37), clozapine-naïve TRS patients (TRS-NC, n = 39), and non-TRS patients (nTRS, n = 35). Clinical symptom severity was assessed using the Positive and Negative Symptom Scale (PANSS), while cognitive function was evaluated using the MATRICS Consensus Cognitive Battery (MCCB). RESULT: The levels of all four glutamate receptor antibodies in TRS-NC were significantly higher than those in nTRS (p < 0.001) and in TRS-C (p < 0.001), and the antibody levels in TRS-C were comparable to those in nTRS. However, no significant associations were observed between antibody levels and symptom severity or cognitive function across all three groups after FDR correction. CONCLUSION: Our findings suggest that TRS may related to increased anti-glutamate receptor antibody levels and provide further evidence that glutamatergic dysfunction and immune processes may contribute to the pathogenesis of TRS. The impact of clozapine on anti-glutamate receptor antibody levels may be a pharmacological mechanism underlying its therapeutic effects.

Updated Progress on Polysaccharides with Anti-Diabetic Effects through the Regulation of Gut Microbiota: Sources, Mechanisms, and Structure-Activity Relationships.

Diabetes mellitus (DM) is a common chronic metabolic disease worldwide. The disturbance of the gut microbiota has a complex influence on the development of DM. Polysaccharides are one type of the most important natural components with anti-diabetic effects. Gut microbiota can participate in the fermentation of polysaccharides, and through this, polysaccharides regulate the gut microbiota and improve DM. This review begins by a summary of the sources, anti-diabetic effects and the gut microbiota regulation functions of natural polysaccharides. Then, the mechanisms of polysaccharides in regulating the gut microbiota to exert anti-diabetic effects and the structure-activity relationship are summarized. It is found that polysaccharides from plants, fungi, and marine organisms show great hypoglycemic activities and the gut microbiota regulation functions. The mechanisms mainly include repairing the gut burrier, reshaping gut microbiota composition, changing the metabolites, regulating anti-inflammatory activity and immune function, and regulating the signal pathways. Structural characteristics of polysaccharides, such as monosaccharide composition, molecular weight, and type of glycosidic linkage, show great influence on the anti-diabetic activity of polysaccharides. This review provides a reference for the exploration and development of the anti-diabetic effects of polysaccharides.

Mulberry leaf and its effects against obesity: A systematic review of phytochemistry, molecular mechanisms and applications.

BACKGROUND: Obesity and hyperlipidemia can induce a variety of diseases, and have become major health problems worldwide. How to effectively prevent and control obesity has become one of the hot-spots of contemporary research. Mulberry leaf is the dried leaf of Morus alba L., which is approved by the Ministry of Health as a "homology of medicine and food", rich in diverse active constituents and with a variety of health effects including anti-obesity and anti-hyperlipidemia activities. PURPOSE: The review attempts to summarize and provide the molecular basis, mechanism, safety and products for further exploration and application of mulberry leaf on the treatment on the control of weight gain and obesity. METHODS: This review is conducted by using ScienceDirect, PubMed, CNKI and Web of Science databases following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). RESULTS: Based on the research progress of domestic and foreign scholars, the effective phytochemicals, molecular mechanisms and product applications of mulberry leaf in the prevention and treatment of obesity and related metabolic diseases were summarized. CONCLUSION: Mulberry leaf has excellent medicinal and health care value in obesity treatment. However, its pharmacodynamic substance basis and molecular mechanisms need to be further studied.

A Study of the Friction Characteristics of Rubber Thermo-Mechanical Coupling.

The friction performance of tread rubber is related to the safety of the vehicle during driving, especially in terms of shifting speeds, cornering, and changing environmental factors. The experimental design used in this paper employed a self-developed automatic multi-working-condition friction tester to investigate the correlation between the friction coefficient of three tread formulations and various factors, including speed, pressure, temperature, side deflection angle, and lateral camber. This experimental study demonstrates that the coefficient of friction decreases with increasing load and increases with increasing sliding velocities due to changes in adhesion friction. Due to the increasing and decreasing changes in rubber adhesion and hysteresis friction caused by temperature, the coefficient of friction shows a tendency to increase and then decrease with the increase in temperature; thus, temperature has an important effect on the coefficient of friction. Based on the basic theory of friction and experimental research, the Dorsch friction model was modified in terms of temperature, and the analytical relationship between the rubber friction coefficient and the combined variables of contact pressure, slip velocity, and temperature was established, which is more in line with the actual situation of rubber friction. The model predictions were compared with the experimental results, and the error accuracy was controlled within 5%. This verifies the accuracy of the model and provides a theoretical basis for the study of rubber friction.

Beyond MD17: the reactive xxMD dataset.

System specific neural force fields (NFFs) have gained popularity in computational chemistry. One of the most popular datasets as a bencharmk to develop NFF models is the MD17 dataset and its subsequent extension. These datasets comprise geometries from the equilibrium region of the ground electronic state potential energy surface, sampled from direct adiabatic dynamics. However, many chemical reactions involve significant molecular geometrical deformations, for example, bond breaking. Therefore, MD17 is inadequate to represent a chemical reaction. To address this limitation in MD17, we introduce a new dataset, called Extended Excited-state Molecular Dynamics (xxMD) dataset. The xxMD dataset involves geometries sampled from direct nonadiabatic dynamics, and the energies are computed at both multireference wavefunction theory and density functional theory. We show that the xxMD dataset involves diverse geometries which represent chemical reactions. Assessment of NFF models on xxMD dataset reveals significantly higher predictive errors than those reported for MD17 and its variants. This work underscores the challenges faced in crafting a generalizable NFF model with extrapolation capability.

Screening of Associated Factors for Erectile Dysfunction after Radical Prostatectomy and Construction of a Clinical Risk Assessment Model: A Retrospective Study.

OBJECTIVE: In this article, the associated factors for erectile dysfunction (ED) after radical prostatectomy (RP) were explored, and a clinical risk assessment model was constructed. METHODS: A total of 155 patients who underwent RP in People's Hospital of Hunan Province from November 2020, to November 2021, were selected as the study group. In accordance with the results of International Index of Erectile Function (IIEF-5) at 6 months after surgery, 88 patients were included in the ED group (IIEF-5 <22), and 67 patients were included in the non-ED group (IIEF-5 ≥22). Univariate and multivariate logistic regression analyses were conducted to screen the risk factors for ED after RP, and a risk model was constructed on this basis. In addition, 43 patients with ED after RP and 41 patients with non-ED after RP from January 2022, to January 2023, were included in the test group to evaluate the predictive efficacy of the clinical risk assessment model on the basis of the receiver operating characteristic curve. RESULTS: The study group had a lower postoperative IIEF-5 score than before surgery (p < 0.001). The incidence of ED after RP in the study group was 56.77% (88/155). Multivariate analysis showed that advanced age (odds ratio (OR) = 1.155), large prostate volume (OR = 1.077), smoking (OR = 5.676), drinking (OR = 3.495), hypertension (OR = 8.079), diabetes (OR = 6.082), low preoperative serum testosterone (T) level (OR = 0.684) and high preoperative serum endothelin-1 (ET-1) level (OR = 1.192) were risk factors for ED after RP (p < 0.05). A risk model was constructed as follows: Z = 0.144 × (age) + 0.074 × (prostate volume) + 1.736 × (smoking) + 1.251 × (drinking) + 2.089 × (hypertension) + 1.805 × (diabetes) - 0.380 × (preoperative serum T) + 0.175 × (preoperative serum ET-1). The area under curve (AUC), sensitivity, specificity and 95% CI of this model were 0.906, 97.70%, 73.20%, and 0.848-0.964, respectively (p < 0.001). CONCLUSIONS: The clinical risk assessment model constructed on the basis of the above factors provides some references for the scientific prevention and treatment of ED after RP.

3D printed high-precision porous scaffolds prepared by fused deposition modeling induce macrophage polarization to promote bone regeneration.

Macrophage-mediated bone immune responses significantly influence the repair of bone defects when utilizing tissue-engineered scaffolds. Notably, the scaffolds' physical structure critically impacts macrophage polarization. The optimal pore size for facilitating bone repair remains a topic of debate due to the imprecision of traditional methods in controlling scaffold pore dimensions and spatial architecture. In this investigation, we utilized fused deposition modeling (FDM) technology to fabricate high-precision porous polycaprolactone (PCL) scaffolds, aiming to elucidate the impact of pore size on macrophage polarization. We assessed the scaffolds' mechanical attributes and biocompatibility. Real-time quantitative reverse transcription polymerase chain reaction was used to detect the expression levels of macrophage-related genes, and enzyme linked immunosorbent assay for cytokine secretion levels.In vitroosteogenic capacity was determined through alkaline phosphatase and alizarin red staining. Our findings indicated that macroporous scaffolds enhanced macrophage adhesion and drove their differentiation towards the M2 phenotype. This led to the increased production of anti-inflammatory factors and a reduction in pro-inflammatory agents, highlighting the scaffolds' immunomodulatory capabilities. Moreover, conditioned media from macrophages cultured on these macroporous scaffolds bolstered the osteogenic differentiation of bone marrow mesenchymal stem cells, exhibiting superior osteogenic differentiation potential. Consequently, FDM-fabricated PCL scaffolds, with precision-controlled pore sizes, present promising prospects as superior materials for bone tissue engineering, leveraging the regulation of macrophage polarization.

Screening of Associated Factors for Erectile Dysfunction after Radical Prostatectomy and Construction of a Clinical Risk Assessment Model: A Retrospective Study

Objective: In this article, the associated factors for erectile dysfunction (ED) after radical prostatectomy (RP) were explored, and a clinical risk assessment model was constructed. Methods: A total of 155 patients who underwent RP in People’s Hospital of Hunan Province from November 2020, to November 2021, were selected as the study group. In accordance with the results of International Index of Erectile Function (IIEF-5) at 6 months after surgery, 88 patients were included in the ED group (IIEF-5 <22), and 67 patients were included in the non-ED group (IIEF-5 ≥22). Univariate and multivariate logistic regression analyses were conducted to screen the risk factors for ED after RP, and a risk model was constructed on this basis. In addition, 43 patients with ED after RP and 41 patients with non-ED after RP from January 2022, to January 2023, were included in the test group to evaluate the predictive efficacy of the clinical risk assessment model on the basis of the receiver operating characteristic curve. Results: The study group had a lower postoperative IIEF-5 score than before surgery (p < 0.001). The incidence of ED after RP in the study group was 56.77% (88/155). Multivariate analysis showed that advanced age (odds ratio (OR) = 1.155), large prostate volume (OR = 1.077), smoking (OR = 5.676), drinking (OR = 3.495), hypertension (OR = 8.079), diabetes (OR = 6.082), low preoperative serum testosterone (T) level (OR = 0.684) and high preoperative serum endothelin-1 (ET-1) level (OR = 1.192) were risk factors for ED after RP (p < 0.05). A risk model was constructed as follows: Z = 0.144 × (age) + 0.074 × (prostate volume) + 1.736 × (smoking) + 1.251 × (drinking) + 2.089 × (hypertension) + 1.805 × (diabetes) − 0.380 × (preoperative serum T) + 0.175 × (preoperative serum ET-1). The area under curve (AUC), sensitivity, specificity and 95% CI of this model were 0.906, 97.70%, 73.20%, and 0.848–0.964, respectively (p < 0.001)(AU)

Towards provably efficient quantum algorithms for large-scale machine-learning models.

Large machine learning models are revolutionary technologies of artificial intelligence whose bottlenecks include huge computational expenses, power, and time used both in the pre-training and fine-tuning process. In this work, we show that fault-tolerant quantum computing could possibly provide provably efficient resolutions for generic (stochastic) gradient descent algorithms, scaling as [Formula: see text], where n is the size of the models and T is the number of iterations in the training, as long as the models are both sufficiently dissipative and sparse, with small learning rates. Based on earlier efficient quantum algorithms for dissipative differential equations, we find and prove that similar algorithms work for (stochastic) gradient descent, the primary algorithm for machine learning. In practice, we benchmark instances of large machine learning models from 7 million to 103 million parameters. We find that, in the context of sparse training, a quantum enhancement is possible at the early stage of learning after model pruning, motivating a sparse parameter download and re-upload scheme. Our work shows solidly that fault-tolerant quantum algorithms could potentially contribute to most state-of-the-art, large-scale machine-learning problems.

Updated Progress on Mass Spectrometry Imaging and its Application in Cancer Treatment and Drug Discovery.

BACKGROUND: Mass spectrometry imaging (MSI) is an imaging method based on mass spectrometry technology that can simultaneously visualize the spatial distribution of various biological molecules. The use of MSI in cancer detection and drug discovery has been extensively investigated in recent years. OBJECTIVE: This review aims to summarize the latest advances of MSI and its specific applications in cancer detection and drug discovery, providing a basic understanding of the development and application of MSI in the past five years and offering references for the further application of MSI in cancer detection and drug discovery. METHODS: In the database, "mass spectrometry imaging", "cancer treatment", and "drug discovery" were used as keywords for literature retrieval, and the time range was limited to "2018- 2023". After organizing and analyzing the literature and patents, a review was conducted. RESULTS: Based on the literature, it was found that the updated progress of MSI in the past five years mostly focused on concrete methods, operation procedures, facilities, and composite applications. The patents of MSI were mainly correlated with the mass spectrometry imaging system and its application in cancer treatment. MSI is conducive to investigating the therapeutic schedule of cancer and searching for new drugs. CONCLUSION: MSI is a convenient, fast and powerful technology that has made great progress in sample preparation, instrumentation, quantitation, and multimodal imaging. MSI has emerged as a powerful technique in various biomedical applications, which has strong potential in cancer detection, treatment, formation mechanism research, discovery of biomarkers, and drug discovery process.

Flow-diverter stents in intracranial aneurysm treatment: impact on covered cerebral artery branches.

OBJECTIVE: Flow diverter stents (FDSs) have attracted interest for intracranial aneurysm (IA) treatment; however, occlusion of side branches and related complications have been reported. This study aimed to investigate the effects of FDSs in IA management when different branches of intracranial arteries are covered. MATERIALS AND METHODS: A cross-sectional study was conducted using PUBMED, Embase, Web of Science, and Cochrane databases to include randomized or nonrandomized comparative-designed studies from January 2000 to August 2022 which reported outcomes of occlusion/narrowing of branches after IA treatment using FDSs. The PRISMA guidelines were used for our report. A random-effects meta-analysis was conducted to pool the outcomes, which included incidence rates of occlusion/narrowing of FDS-covered branches, branch occlusion-related symptoms, obliteration of IAs, and ideal clinical outcomes (modified Rankin Scale score ≤2). RESULTS: The authors identified 57 studies involving 3789 patients with IA managed by FDSs covering different branches. During the median imaging follow-up at 12 months, the IA obliteration rate was satisfactory (>70%) when covering the ophthalmic artery (OA), posterior communicating artery (PComA), anterior choroidal artery (AChoA) or anterior cerebral artery (ACA), but not the middle cerebral artery-M2 segment (MCA-M2; 69.5%; 95% CI: 60.8-77.5%) and posterior inferior cerebellar artery (PICA; 59.1%, 13/22). The overall ideal clinical outcome was observed in 97.4% of patients (95% CI: 95.5-98.9%). Higher rates of occlusion/narrowing of branches were identified when FDSs covered the ACA (66.6%; 95% CI: 45.1-85.3%), PComA (44.3%; 95% CI: 34.2-54.6%), or MCA-M2 (39.2%; 95% CI: 24.5-54.7%); the risks were lower when covering the OA (11.8%; 95% CI: 8.8-15.1%), PICA (6.8%; 95% CI: 1.5-14.5%), and AchoA (0.5%; 95% CI: 0.0-2.9%). The risk of branch occlusion-related complications was low (incidence rate <5%) for each of the six evaluated branches. CONCLUSIONS: Acceptable outcomes were identified following treatment of IAs when FDSs were placed across each of the six studied cerebral arteries. Treatment decisions regarding FDS placement across branch arteries should be made with the risk of complications from branch occlusion in mind.

Cathepsin V is correlated with the prognosis and tumor microenvironment in liver cancer.

Recent studies have shown that high cell cycle activity negatively correlates with antitumor immunity in certain cancer types. However, a similar correlation has not been proven in liver cancer. We downloaded transcriptomic profiles of the cancer genome atlas-liver hepatocellular carcinoma (TCGA-LIHC) and assessed the cell cycle distribution of samples using single sample gene set enrichment analysis (ssGSEA), termed the cell cycle score (CCS). We obtained cell cycle-related differentially expressed prognostic genes and identified CENPA, CDC20, and CTSV using LASSO regression. We studied the effect of CTSV on clinical features and immune alterations in liver cancer based on TCGA-LIHC data. In vitro and in vivo experiments were performed to validate the role of CTSV in liver cancer using liver cancer cell lines and tissues. We found that the CCS closely correlated with the clinical features and prognosis of patients in TCGA-LIHC. Analysis of differentially expressed genes (DEGs), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression identified cathepsin V (CTSV) with prognostic significance in LIHC. Importantly, single-gene survival analysis of CTSV using microarray and sequencing data indicated that high levels of CTSV expression correlated with an unfavorable prognosis in various cancers. Gene set enrichment analysis revealed that high CTSV expression closely correlated with decreased expression of metabolic genes and increased expression of cell cycle genes. Furthermore, difference and correlation analyses of the relationship between CTSV expression and immune infiltrates, determined using CIBERSORT and TIMER algorithms, revealed that CTSV expression correlated with macrophages and CD4+ T cells. In vitro and in vivo experiments revealed that knockdown of CTSV inhibited liver cancer cells proliferation. Immunohistochemical staining showed that high CTSV expression correlated with macrophage infiltration in liver cancer tissues, predicted a poor prognosis, and is associated with the effectiveness of hepatocellular carcinoma treatment. In couclusion, CTSV is a novel cell cycle-associated gene with clinical significance in HCC.

Natural products in traditional Chinese medicine: molecular mechanisms and therapeutic targets of renal fibrosis and state-of-the-art drug delivery systems.

Renal fibrosis (RF) is the end stage of several chronic kidney diseases. Its series of changes include excessive accumulation of extracellular matrix, epithelial-mesenchymal transition (EMT) of renal tubular cells, fibroblast activation, immune cell infiltration, and renal cell apoptosis. RF can eventually lead to renal dysfunction or even renal failure. A large body of evidence suggests that natural products in traditional Chinese medicine (TCM) have great potential for treating RF. In this article, we first describe the recent advances in RF treatment by several natural products and clarify their mechanisms of action. They can ameliorate the RF disease phenotype, which includes apoptosis, endoplasmic reticulum stress, and EMT, by affecting relevant signaling pathways and molecular targets, thereby delaying or reversing fibrosis. We also present the roles of nanodrug delivery systems, which have been explored to address the drawback of low oral bioavailability of natural products. This may provide new ideas for using natural products for RF treatment. Finally, we provide new insights into the clinical prospects of herbal natural products.

Moderate static magnetic field promotes fracture healing and regulates iron metabolism in mice.

BACKGROUND: Fractures are the most common orthopedic diseases. It is known that static magnetic fields (SMFs) can contribute to the maintenance of bone health. However, the effect and mechanism of SMFs on fracture is still unclear. This study is aim to investigate the effect of moderate static magnetic fields (MMFs) on bone structure and metabolism during fracture healing. METHODS: Eight-week-old male C57BL/6J mice were subjected to a unilateral open transverse tibial fracture, and following treatment under geomagnetic field (GMF) or MMF. The micro-computed tomography (Micro-CT) and three-point bending were employed to evaluate the microarchitecture and mechanical properties. Endochondral ossification and bone remodeling were evaluated by bone histomorphometric and serum biochemical assay. In addition, the atomic absorption spectroscopy and ELISA were utilized to examine the influence of MMF exposure on iron metabolism in mice. RESULTS: MMF exposure increased bone mineral density (BMD), bone volume per tissue volume (BV/TV), mechanical properties, and proportion of mineralized bone matrix of the callus during fracture healing. MMF exposure reduced the proportion of cartilage in the callus area during fracture healing. Meanwhile, MMF exposure increased the number of osteoblasts in callus on the 14th day, and reduced the number of osteoclasts on the 28th day of fracture healing. Furthermore, MMF exposure increased PINP and OCN levels, and reduced the TRAP-5b and ß-CTX levels in serum. It was also observed that MMF exposure reduced the iron content in the liver and callus, as well as serum ferritin levels while elevating the serum hepcidin concentration. CONCLUSIONS: MMF exposure could accelerate fracture healing via promote the endochondral ossification and bone formation while regulating systemic iron metabolism during fracture healing. This study suggests that MMF may have the potential to become a form of physical therapy for fractures.

Effect of dietary patterns on dental caries among 12-15 years-old adolescents: a cross-sectional survey.

BACKGROUND: Several factors can influence the risk of dental caries, among which dietary factors have a significance impact on the occurrence of dental caries. The limitation of current studies is that they only focus on the influence of individual foods on the risk of dental caries. This study use cluster analysis to examine the relationship between dietary patterns and dental caries experience among adolescents aged 12-15. METHODS: Based on data from the first oral epidemic survey in Shanxi Province, a cross-sectional study was conducted among 11,351 adolescents aged 12-15 in Shanxi Province through oral examination and questionnaires. The questionnaire included the intake frequency of seven types of food. Descriptive statistics, cluster analysis, and multinomial logistic regression were used to analyze the association between dietary patterns and dental caries experience. RESULTS: The prevalence rate of caries was 44.57% and the mean DMFT score was 0.98 ± 1.49 in adolescents aged 12-15 in Shanxi Province. The caries rate was higher in females than males (X2 = 103.59, P < 0.001). Adolescents who grow up in one-child families have a lower caries risk than those who grow up in families with more than one child (OR:0.91; 95%CI:0.84-0.97). The dietary patterns of adolescents aged 12-15 can be divided into eight types, among which refreshments-rich diet (OR:1.47; 95%CI,1.22-1.77) can increase the risk of caries, while the coarse-grains-rich dietery pattern (OR:0.90; 95%CI, 0.79-0.97) has a lower caries risk. CONCLUSIONS: Social determinants of health such as sex, family size and dietary patterns influence the risk of dental caries. Certain dietary patterns could increase or decrease the risk of caries. The government, school canteens and news media should take dietary pattern factors seriously.

Clinical characteristics, treatment, and outcome of low-risk non-HIV-associated cryptococcal meningitis: A retrospective cohort study.

Although non-human immunodeficiency virus (HIV)-associated cryptococcal meningitis (CM) is a severe disease, there are still some non-HIV CM patients with a low risk of therapeutic failure. Recognizing clinical characteristics of low-risk non-HIV-associated CM may enable clinicians to treat non-HIV-associated CM more reasonably. According to the definition of low-risk non-HIV-associated CM in the 2010 Infectious Diseases Society of America guideline, a total of 220 non-HIV CM patients were divided into two groups (Group 1: 35 low-risk patients and Group 2: 185 non-low-risk patients). Clinical characteristics, treatment, and outcome were compared between the two groups. Compared with non-low-risk patients, low-risk patients had a lower rate of headache (82.9% vs. 95.7%, P = .012), cerebrospinal fluid (CSF) opening pressure (OP) at baseline (CSF OP < 250-mm H2O, 60.0% vs. 32.4%, P = .001), and baseline CSF cryptococcal count (median, 0 vs. 2376, P < .001), higher baseline CSF white blood cell (median, 130 vs. 90, P = .029) and CSF protein (median, 0.87 vs. 0.73, P = .011). Multivariate analysis showed that baseline CSF OP <250-mm H2O (OR: 2.545, 95% CI 1.168, 5.545, P = .019) was independently associated with low-risk for non-HIV-associated CM. The lengths of AMB-d-based induction therapy of low-risk patients (median, 20 days) were shorter (P < .001) than that of non-low-risk patients (median, 38 days). The successful outcome rate of low-risk patients was higher than non-low-risk patients (97.1% vs. 54.6%, P < .001). We demonstrated that non-HIV-associated CM patients with baseline CSF OP < 250-mm H2O were prone to the low-risk status.

This was a retrospective cohort study to find the features of low-risk non-human immunodeficiency virus (HIV)-associated cryptococcal meningitis (CM). We found that non-HIV-associated CM patients with baseline cerebrospinal fluid opening pressure <250-mm H2O were prone to low-risk status.

Short-term environmental triggers of hemorrhagic stroke.

Hemorrhagic stroke (HS) is associated with severe morbidity and high mortality. Identifying the trigger factors for HS is critical for disease prevention. This study aimed to assess the associations between short-term environmental triggers (STETs) and HS risk. We systematically searched six databases for articles published up to September 9, 2022. Pooled odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using random-effect models to evaluate the associations between STETs and the risk of HS. Heterogeneity was assessed using Cochran Q and I2 tests. A total of 63 studies were included for analysis. Of these, 40 focused on air pollutants and 23 on meteorological factors. Pooling results showed that exposure to particulate matter 2.5 (PM2.5; OR, 1.003 per 10 µg/m3; 95% CI, 1.001-1.007), sulfur dioxide (SO2; OR, 1.022 per 10 ppb; 95% CI, 1.005-1.040), and nitrogen dioxide (NO2; OR, 1.026 per 10 ppb; 95% CI, 1.004-1.047) was associated with an increase in HS risk. Moreover, exposure to PM2.5 (OR, 1.018 per 10 µg/m3; 95% CI, 1.009-1.027) and SO2 (OR, 1.102 per 10 ppb; 95% CI, 1.010-1.204) was positively associated with the risk of intracerebral hemorrhage. In addition, extreme temperature, high pressures, high and low relative humidity were potentially associated with HS risk. Targeted preventive measures to limit the effect of these air pollutants and extreme meteorological factors should be taken to reduce the HS disease burden. Further studies are warranted to verify these findings.

Development and validation of a machine learning model to predict prognosis in HIV-negative cryptococcal meningitis patients: a multicenter study.

PURPOSE: To predict prognosis in HIV-negative cryptococcal meningitis (CM) patients by developing and validating a machine learning (ML) model. METHODS: This study involved 523 HIV-negative CM patients diagnosed between January 1, 1998, and August 31, 2022, by neurologists from 3 tertiary Chinese centers. Prognosis was evaluated at 10 weeks after the initiation of antifungal therapy. RESULTS: The final prediction model for HIV-negative CM patients comprised 8 variables: Cerebrospinal fluid (CSF) cryptococcal count, CSF white blood cell (WBC), altered mental status, hearing impairment, CSF chloride levels, CSF opening pressure (OP), aspartate aminotransferase levels at admission, and decreased rate of CSF cryptococcal count within 2 weeks after admission. The areas under the curve (AUCs) in the internal, temporal, and external validation sets were 0.87 (95% CI 0.794-0.944), 0.92 (95% CI 0.795-1.000), and 0.86 (95% CI 0.744-0.975), respectively. An artificial intelligence (AI) model was trained to detect and count cryptococci, and the mean average precision (mAP) was 0.993. CONCLUSION: A ML model for predicting prognosis in HIV-negative CM patients was built and validated, and the model might provide a reference for personalized treatment of HIV-negative CM patients. The change in the CSF cryptococcal count in the early phase of HIV-negative CM treatment can reflect the prognosis of the disease. In addition, utilizing AI to detect and count CSF cryptococci in HIV-negative CM patients can eliminate the interference of human factors in detecting cryptococci in CSF samples and reduce the workload of the examiner.