Unveiling Novel Structural Biomarkers for the Diagnosis of Glaucoma.

Glaucoma, a leading cause of irreversible blindness, poses a significant global health burden. Early detection is crucial for effective management and prevention of vision loss. This study presents a collection of novel structural biomarkers in glaucoma diagnosis. By employing advanced imaging techniques and data analysis algorithms, we now can recognize indicators of glaucomatous progression. Many research studies have revealed a correlation between the structural changes in the eye or brain, particularly in the optic nerve head and retinal nerve fiber layer, and the progression of glaucoma. These biomarkers demonstrate value in distinguishing glaucomatous eyes from healthy ones, even in the early stages of the disease. By facilitating timely detection and monitoring, they hold the potential to mitigate vision impairment and improve patient outcomes. This study marks an advancement in the field of glaucoma, offering a promising avenue for enhancing the diagnosis and possible management.

IL-4 attenuates myocardial infarction injury by promoting M2 macrophage polarization.

IL-4, an immunoregulatory cytokine, plays a role in various cellular pathways and is known to regulate M2 macrophage polarization. Numerous studies have suggested that promoting the polarization of macrophages toward the M2 phenotype is beneficial for myocardial infarction (MI) recovery. However, whether IL-4 can achieve therapeutic effects in MI by regulating M2 macrophage polarization remains unclear. In this study, the authors observed that IL-4 increased the proportion of M2 macrophages in the ischemic myocardium compared to the PBS group. Additionally, IL-4 reduced the infiltration of inflammatory cells and the expression of proinflammatory-related proteins, while enhancing the expression of genes associated with tissue repair. Furthermore, IL-4 facilitated the recovery of cardiac function and reduced fibrosis in the post-MI phase. Importantly, when macrophages were depleted, the therapeutic benefits of IL-4 mentioned above were attenuated. These findings provide evidence for the effectiveness of IL-4 in treating MI through the regulation of M2 macrophage polarization, thereby encouraging further development of this therapeutic approach.

The Application of Rho Kinase Inhibitors in the Management of Glaucoma.

Glaucoma is a chronic neurodegenerative disease that poses a significant threat of irreversible blindness worldwide. Current treatments for glaucoma focus on reducing intraocular pressure (IOP), which is the only modifiable risk factor. Traditional anti-glaucomatous agents, including carbonic anhydrase inhibitors, beta-blockers, alpha-2 agonists, and prostaglandin analogs, work by either improving uveoscleral outflow or reducing aqueous humor production. Rho kinase (ROCK) inhibitors represent a novel class of anti-glaucomatous drugs that have emerged from bench to bedside in the past decade, offering multifunctional characteristics. Unlike conventional medications, ROCK inhibitors directly target the trabecular meshwork outflow pathway. This review aims to discuss the mechanism of ROCK inhibitors in reducing IOP, providing neuroprotection, and preventing fibrosis. We also highlight recent studies and clinical trials evaluating the efficacy and safety of ROCK inhibitors, compare them with other clinical anti-glaucomatous medications, and outline future prospects for ROCK inhibitors in glaucoma treatment.

Association between pathologic complete response and biochemical indicators after neoadjuvant therapy for HER2-positive breast cancer.

PURPOSE: This study investigated the changes in the fasting blood glucose (FBG), fasting triglyceride (FTG), and fasting total cholesterol (FTC) levels during neoadjuvant therapy (NAT) for human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC) and the association with pathologic complete response (pCR). METHODS: Relevant data from Sichuan Cancer Hospital from June 2019 to June 2022 were collected and analyzed, and FBG, FTG, and FTC were divided into baseline, change, and process groups, which were grouped to analyze the changes after receiving NAT and the association with pCR. RESULTS: In the estrogen receptor (ER)-negative subgroup, patients with low levels of FTG in the process group were more likely to achieve pCR compared to high levels, and in the progesterone receptor (PR)-negative subgroup, patients with lower FTG compared to higher FTG after receiving NAT was more likely to achieve pCR. CONCLUSIONS: Patients with HER2-positive BC undergoing NAT develop varying degrees of abnormalities (elevated or decreased) in FBG, FTG, and FTC; moreover, the status of FTG levels during NAT may predict pCR in ER-negative or PR-negative HER2-positive BC.Early monitoring and timely intervention for FTG abnormalities may enable this subset of patients to increase the likelihood of obtaining a pCR along with management of abnormal markers.

Mimicking bacterial infection in male mice changes sperm small RNA profiles and multigenerationally alters offspring behavior and physiology.

Paternal pre-conceptual exposures, including stress, diet, substance abuse, parasite infection, and viral immune activation via Poly I:C, have been reported to influence the brains and behavior of offspring through sperm epigenetic changes. However, the effects of paternal (F0) pre-conceptual exposure to bacterial-induced immune activation on the behavior and physiology of F1 and F2 generations remain unexplored. We examined this using C57BL/6J mice. Eight-week-old males (F0) received a single intraperitoneal injection of the bacterial mimetic lipopolysaccharide (LPS: 5 mg/kg) or 0.9 % saline (vehicle control) before mating with naïve females at four weeks post-injection. Comprehensive behavioral assessments were conducted to investigate anxiety, social behaviors, depressive-like behaviors and cognition in both the F1 and F2 generations within the age range of 8 to 14 weeks. Results demonstrated that only female offspring of LPS-exposed fathers exhibited reduced anxiety levels in the light/dark box, large open field, and novelty-suppressed feeding test. These F1 female offspring also exhibited heightened sociability in the 3-chambered social interaction test and a reduced preference for saccharin in the saccharin preference test. Additionally, the F1 male offspring of LPS-challenged males demonstrated an increased total distance traveled in the light/dark box and a longer distance covered in the light zone. They also exhibited diminished preference for social novelty in the 3-chambered social interaction test and an elevated novel arm preference index in the Y-maze. In the F2 generation, male descendants of LPS-treated fathers showed reduced latency to feed in the novelty-suppressed feeding test. Additionally, the F2 generation of LPS-challenged fathers, but not the F1 generation, displayed enhanced immune response in both sexes after an acute LPS immune challenge (5 mg/kg). Analysis of sperm small noncoding RNA profiles from LPS-treated F0 mice revealed significant changes at 4 weeks after administration of LPS. These changes included three microRNAs, eight PIWI-interacting RNAs, and two transfer RNAs, exhibiting significant upregulation (mmu-miR-146a-5p, mmu-piR-27082 and mmu-piR-29102) or downregulation (mmu-miR-5110, mmu-miR-467e-3p, mmu-piR-22583, mmu-piR-23548, mmu-piR-36341, mmu-piR-50293, mmu-piR-16583, mmu-piR-36507, Mus_musculus_tRNA-Ile-AAT-2-1 and Mus_musculus_tRNA-Tyr-GTA-1-1). Additionally, we detected 52 upregulated small noncoding RNAs (including 9 miRNAs, 41 piRNAs, and 2 tRNAs) and 7 downregulated small noncoding RNAs (3 miRNAs, 3 piRNAs, and 1 tRNA) in the sperm of F1 offspring from LPS-treated males. These findings provide compelling evidence for the involvement of epigenetic mechanisms in the modulation of brain function and immunity, and associated behavioral and immunological traits, across generations, in response to bacterial infection.

[Effect of Intensive Insulin Therapy on Prognosis in Patients With Acute Myocardial Infarction].

Objective To evaluate the clinical efficacy and safety of intensive insulin therapy in the patients with acute myocardial infarction and provide guidance for improving the prognosis. Methods The articles involving the randomized controlled trials(RCT)focusing on the effects of intensive versus conventional insulin therapy on the clinical outcomes of the patients with acute myocardial infarction were retrieved from Cochrane,Embase,PubMed,CNKI,Wanfang Data,VIP,and CBM with the time interval from inception to October 2022.The data of each RCT were extracted and used for meta-analysis in RevMan5.4. Results A total of 8 articles were included in this study,involving 726 patients(372 in the intensive insulin group and 354 in the normal insulin group).The meta-analysis results showed that the intensive insulin group had lower incidence of major cardiovascular adverse events (RR=0.53, 95%CI=0.44-0.64, P<0.001), lower all-cause mortality (RR=0.51, 95%CI=0.33-0.78, P=0.002),lower high-sensitivity C-reactive protein level on day 7(WMD=-2.00,95%CI=-2.17- -1.83,P<0.001),higher left ventricular ejection fraction on day 30 (WMD=3.94, 95%CI=2.45-5.43,P<0.001), and higher incidence of hypoglycemia events (RR=2.96, 95%CI=1.12-7.83,P=0.030) than the normal insulin group.There was no significant difference between the two groups in terms of no-reflow event after percutaneous coronary intervention(RR=0.39,95%CI=0.14-1.13,P=0.080). Conclusion Intensive insulin therapy might be associated with more clinical benefits in the patients with acute myocardial infarction,while the conclusion remains to be confirmed by more studies.

Prevalence of depressive symptoms in patients with advanced schistosomiasis in China: A systematic review and meta-analysis.

BACKGROUND: Advanced schistosomiasis is the most serious outcome of infection and has a negative impact on both physical fitness and mental health of patients, the latter of which has long been overlooked. Therefore, we performed this systematic review and meta-analysis to estimate the overall prevalence of depressive symptoms, one of the most common mental problems, in patients with advanced schistosomiasis in China. METHODS: Six electronic databases were searched for studies reporting the prevalence of depressive symptoms in the targeted patients. Assessments were pooled using a fixed- or random-effects model based on heterogeneity test. Subgroup analyses were further performed and differences between/among groups were examined using the chi-squared test. The protocol had previously been registered in PROSPERO (CRD42023406708). RESULTS: A total of 11 studies with 1,673 participants were included. The pooled prevalence of depressive symptoms in advanced schistosomiasis in China was 62.01% (95% CI: 51.30% - 72.72%), with a significant heterogeneity among studies. Depressive symptoms were more prevalent in patients with complications and more than half of the patients suffered a mild- or moderate-level of depression. No publication bias was found, and sensitivity analysis showed a stable result. CONCLUSIONS: The overall prevalence of depressive symptoms in advanced schistosomiasis in China was high enough to warrant psychotherapeutic interventions, especially for patients with complications. This would greatly prevent or/and reduce depression and improve their quality of life.

Classification of recurrent major depressive disorder using a residual denoising autoencoder framework: Insights from large-scale multisite fMRI data.

BACKGROUND AND OBJECTIVE: Recurrent major depressive disorder (rMDD) has a high recurrence rate, and symptoms often worsen with each episode. Classifying rMDD using functional magnetic resonance imaging (fMRI) can enhance understanding of brain activity and aid diagnosis and treatment of this disorder. METHODS: We developed a Residual Denoising Autoencoder (Res-DAE) framework for the classification of rMDD. The functional connectivity (FC) was extracted from fMRI data as features. The framework addresses site heterogeneity by employing the Combat method to harmonize feature distribution differences. A feature selection method based on Fisher scores was used to reduce redundant information in the features. A data augmentation strategy using a Synthetic Minority Over-sampling Technique algorithm based on Extended Frobenius Norm measure was incorporated to increase the sample size. Furthermore, a residual module was integrated into the autoencoder network to preserve important features and improve the classification accuracy. RESULTS: We tested our framework on a large-scale, multisite fMRI dataset, which includes 189 rMDD patients and 427 healthy controls. The Res-DAE achieved an average accuracy of 75.1 % (sensitivity = 69 %, specificity = 77.8 %) in cross-validation, thereby outperforming comparison methods. In a larger dataset that also includes first-episode depression (comprising 832 MDD patients and 779 healthy controls), the accuracy reached 70 %. CONCLUSIONS: We proposed a deep learning framework that can effectively classify rMDD and 33 identify the altered FC associated with rMDD. Our study may reveal changes in brain function 34 associated with rMDD and provide assistance for the diagnosis and treatment of rMDD.

BDM: An Assessment Metric for Protein Complex Structure Models Based on Distance Difference Matrix.

Protein complex structure prediction is an important problem in computational biology. While significant progress has been made for protein monomers, accurate evaluation of protein complexes remains challenging. Existing assessment methods in CASP, lack dedicated metrics for evaluating complexes. DockQ, a widely used metric, has some limitations. In this study, we propose a novel metric called BDM (Based on Distance difference Matrix) for assessing protein complex prediction structures. Our approach utilizes a distance difference matrix derived from comparing real and predicted protein structures, establishing a linear correlation with Root Mean Square Deviation (RMSD). BDM overcomes limitations associated with receptor-ligand differentiation and eliminates the requirement for structure alignment, making it a more effective and efficient metric. Evaluation of BDM using CASP14 and CASP15 test sets demonstrates superior performance compared to the official CASP scoring. BDM provides accurate and reasonable assessments of predicted protein complexes, wide adoption of BDM has the potential to advance protein complex structure prediction and facilitate related researches across scientific domains. Code is available at http://mialab.ruc.edu.cn/BDMServer/ .

A multi-label transformer-based deep learning approach to predict focal visual field progression.

PURPOSE: Tracking functional changes in visual fields (VFs) through standard automated perimetry remains a clinical standard for glaucoma diagnosis. This study aims to develop and evaluate a deep learning (DL) model to predict regional VF progression, which has not been explored in prior studies. METHODS: The study included 2430 eyes of 1283 patients with four or more consecutive VF examinations from the baseline. A multi-label transformer-based network (MTN) using longitudinal VF data was developed to predict progression in six VF regions mapped to the optic disc. Progression was defined using the mean deviation (MD) slope and calculated for all six VF regions, referred to as clusters. Separate MTN models, trained for focal progression detection and forecasting on various numbers of VFs as model input, were tested on a held-out test set. RESULTS: The MTNs overall demonstrated excellent macro-average AUCs above 0.884 in detecting focal VF progression given five or more VFs. With a minimum of 6 VFs, the model demonstrated superior and more stable overall and per-cluster performance, compared to 5 VFs. The MTN given 6 VFs achieved a macro-average AUC of 0.848 for forecasting progression across 8 VF tests. The MTN also achieved excellent performance (AUCs ≥ 0.86, 1.0 sensitivity, and specificity ≥ 0.70) in four out of six clusters for the eyes already with severe VF loss (baseline MD ≤ - 12 dB). CONCLUSION: The high prediction accuracy suggested that multi-label DL networks trained with longitudinal VF results may assist in identifying and forecasting progression in VF regions.

Spatial and temporal characteristics, spatial clustering and governance strategies for regional development of social enterprises in China.

Social enterprises are a powerful starting point for achieving Common Prosperity. Expanding the scale of social enterprises in China is conducive to promoting sustainable social development. This study uses exploratory spatial data analysis methods to systematically analyze the spatio-temporal pattern, clustering characteristics and impact mechanism of the development of social enterprises in provincial administrative regions in China. The research has found that provincial social enterprises in China showed a random distribution pattern from 2015 to 2018, and showed significant negative spatial correlation from 2019 to 2022, forming a local spatial pattern of "low ones consistently low, high ones consistently high", with obvious path and spatial dependencies as well as regional isolation effects; From 2015 to 2022, the core density of provincial social enterprises showed a significant "unipolar" phenomenon, exhibiting significant spatial imbalance. Based on the TOE framework, each province and city can be divided into three clusters: demonstration provinces and cities for the development of social enterprises, starting provinces and cities for social enterprises, and lagging provinces and cities for the development of social enterprises. The first classification presents characteristics of dispersion and cross domain, while the other two categories have strong regional continuity. The core driving factors that affect the spatial differentiation of social enterprise development have regional differences, among which the decisive factor is government policy support, and the interaction factor has an enhanced effect on provincial spatial differentiation compared to a single factor. Sorting out the development characteristics of social enterprises is conducive to promoting the large-scale development of social enterprises and promoting cooperation and dialogue with other countries.

Timely assessment of 5-year relative survival for patients with thyroid cancer from Taizhou, eastern China: a period analysis.

BACKGROUND: While timely assessment of long-term survival in thyroid cancer patients is critical for assessing early detection and screening programs for thyroid cancer, those data are sorely lacking in China. We aimed to timely and accurately assess the long-term survival of thyroid cancer patients in eastern China. METHODS: Patients diagnosed with thyroid cancer during 2004-2018 from four cancer registries in Taizhou, eastern China were included. The 5-year relative survival was estimated by period analysis and stratified by sex, age at diagnosis, and region. The 5-year RS of thyroid cancer patients during 2019-2023 was also predicted using the model-based period analysis. RESULTS: During 2014-2018, the overall 5-year relative survival of thyroid cancer patients was 87.7%, 91.2% for women and 79.4% for men. The 5-year RS decreased along with increasing age at diagnosis, decreasing from 94.9% for age <45 years to 81.3% for age >74 years, while 5-year RS was higher in urban areas than in rural areas (93.2% vs. 86.1%). The 5-year RS for thyroid cancer patients improved greatly between 2004-2008 to 2014-2018. The predicted overall 5-year RS could reach 91.4% over the upcoming 2019-2023 period. CONCLUSION: We provided, for the first time in China using period analysis, the most up-to-date 5-year RS for thyroid cancer patients from Taizhou, eastern China, which has important implications for timely evaluation on early detection and screening programs for patients with thyroid cancer in eastern China.

Startup of a large height-diameter ratio bioreactor by alternate feeding: performance of partial nitrification and enrichment of ammonia-oxidizing bacteria (AOB).

In order to solve the complicated control of dissolved oxygen (DO) for partial nitrification in bioreactors treating high NH4+-N wastewater, a large height-diameter ratio anammox pre-reactor system was developed. And in this reactor, NO2--N accumulation rate can reach 85.76% by alternate feeding with high NH4+-N wastewater (150 mg NH4+-N/L) and low NH4+-N wastewater (50 mg c) with low DO (0.19 mg/L-0.62 mg/L). Based on 16S rRNA identification technology, it was found that Nitrosomonas had a significant effect on NH4+-N oxidization in this study. And when the reactor treated higher concentration wastewater (250 mg NH4+-N/L), the growth rate of Nitrosomonas was higher than that of Nitrospira (nitrite-oxidizing bacteria, NOB), which was conducive to improving the NO2--N accumulation rate and realizing partial nitrification stably. It was also found that the material exchange frequency of the microbial flora during alternate feeding with different NH4+-N concentration wastewaters was higher than that during feeding with higher NH4+-N concentration wastewater (250 mg/L) by Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolism pathways analysis. This study can provide valuable insights and lay the foundation for building anammox pre-reactors.

Classification of MDD using a Transformer classifier with large-scale multisite resting-state fMRI data.

Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide with high recurrence rate. Identifying MDD patients, particularly those with recurrent episodes with resting-state fMRI, may reveal the relationship between MDD and brain function. We proposed a Transformer-Encoder model, which utilized functional connectivity extracted from large-scale multisite rs-fMRI datasets to classify MDD and HC. The model discarded the Transformer's Decoder part, reducing the model's complexity and decreasing the number of parameters to adapt to the limited sample size and it does not require a complex feature selection process and achieves end-to-end classification. Additionally, our model is suitable for classifying data combined from multiple brain atlases and has an optional unsupervised pre-training module to acquire optimal initial parameters and speed up the training process. The model's performance was tested on a large-scale multisite dataset and identified brain regions affected by MDD using the Grad-CAM method. After conducting five-fold cross-validation, our model achieved an average classification accuracy of 68.61% on a dataset consisting of 1611 samples. For the selected recurrent MDD dataset, the model reached an average classification accuracy of 78.11%. Abnormalities were detected in the frontal gyri and cerebral cortex of MDD patients in both datasets. Furthermore, the identified brain regions in the recurrent MDD dataset generally exhibited a higher contribution to the model's performance.

Orthopedic mechanism analysis of growing rod distraction for early-onset scoliosis based on 3D morphological parameters.

Traditional growing rod (TGR) provides a corrective moment for deformed segments to straighten the spine, whose clinical efficacy has proven positive and growth-friendly. However, an insufficient understanding of orthopedic mechanisms can affect the development of clinical strategies. This research attempts to analyze the spine that has undergone four distraction operations: exploring the spinal orthopedic mechanism, including alignment, growth, and morphology. In this study, the spinal morphology curves were illustrated in three human planes to exhibit the changes in spinal alignment. The spinal growth characteristics were measured to discuss the unsynchronized and diminishing growth rate. The spinal deformations were evaluated to indicate asymmetric growth. As a result, the spinal alignment changes indicated the orthopedic process improved, but the re-unbalance occurred after multiple distractions. Then, unsynchronized growth existed in the superior and inferior segments, and the growth rate over every distraction diminished. Finally, asymmetric growth was indicated as the axial/circumferential growth ratio getting greater and the cuneate level approaching normal. Accordingly, a TGR is growth-friendly, but combining the osteotomy fusion of lumbar segments for severe early-onset scoliosis may be an excellent choice to solve the insufficient corrective stimulation. Regarding the distraction process, reshaping before the final fusion can fix the balance loss, and a prolonged distraction frequency fits the law of diminishing return. In conclusion, studying orthopedic mechanisms based on morphological measurement can guide clinical strategy optimization.

Genetic difference between two Schistosoma japonicum isolates with contrasting cercarial shedding patterns revealed by whole genome sequencing.

Schistosoma japonicum is one of the major infectious agents of human schistosomiasis, mainly endemic in China and the Philippines. We have previously reported the finding of two schistosome isolates, each with a different cercarial emergence pattern adapted to their different hosts. However, there are currently no whole-genome sequencing studies to investigate the underlining genetics of the adaptive traits. We sampled schistosomes in 2013 and 2020 from a hilly area Shitai (ST) and a marshland area Hexian (HX) of Anhui, China. Ten to 15 male or female adult worms from each site/year were sent for whole genome sequencing. Genetics were analyzed, and selection signals along genomes were detected. Gene enrichment analysis was performed for the genome regions under selection. The results revealed considerable genetic differentiation between the two isolates. The genome "windows" affected by natural selection were fewer in ST (64 windows containing 78 genes) than in HX (318 windows containing 276 genes). Twelve significantly enriched genes were identified in ST, but none in HX. These genes were mainly related to specific DNA binding and intercellular signaling transduction. Some functional region changes identified along the genome of the hilly schistosome may be related to its unique late afternoon cercarial emergence.

Title: Différence génétique entre deux isolats de Schistosoma japonicum présentant des schémas contrastés d'émergence de cercaires, révélés par séquençage du génome entier. Abstract: Schistosoma japonicum est l'un des principaux agents infectieux de la schistosomiase humaine, principalement endémique en Chine et aux Philippines. Nous avons précédemment rapporté la découverte de deux isolats de schistosomes, chacun présentant un schéma différent d'émergence de cercaires, adapté à leurs différents hôtes. Cependant, il n'existe actuellement aucune étude de séquençage du génome entier pour comprendre la génétique sous-jacente aux traits adaptatifs. Nous avons échantillonné des schistosomes en 2013 et 2020 dans une zone de collines de Shitai (ST) et une zone marécageuse de Hexian (HX) de l'Anhui, en Chine. Dix à 15 vers adultes mâles ou femelles de chaque site/année ont été envoyés pour séquençage du génome entier. La génétique a été analysée et des signaux de sélection le long des génomes ont été détectés. Une analyse d'enrichissement génétique a été réalisée pour les régions du génome sélectionnées. Les résultats ont révélé une différenciation génétique considérable entre deux isolats. Les « fenêtres ¼ du génome affectées par la sélection naturelle étaient moins nombreuses dans ST (64 fenêtres contenant 78 gènes) que dans HX (318 fenêtres contenant 276 gènes). Douze gènes significativement enrichis ont été identifiés dans ST mais aucun dans HX. Ces gènes étaient principalement liés à la liaison spécifique à l'ADN et à la transduction de la signalisation intercellulaire. Certains changements de régions fonctionnelles identifiés le long du génome du schistosome des collines peuvent être liés à son émergence cercarienne exceptionnelle en fin d'après-midi.

The Role of Retinal Ganglion Cell Structure and Function in Glaucoma.

Glaucoma, a leading cause of irreversible blindness globally, primarily affects retinal ganglion cells (RGCs). This review dives into the anatomy of RGC subtypes, covering the different underlying theoretical mechanisms that lead to RGC susceptibility in glaucoma, including mechanical, vascular, excitotoxicity, and neurotrophic factor deficiency, as well as oxidative stress and inflammation. Furthermore, we examined numerous imaging methods and functional assessments to gain insight into RGC health. Finally, we investigated the current possible neuroprotective targets for RGCs that could help with future glaucoma research and management.

Cinobufotalin prevents bone loss induced by ovariectomy in mice through the BMPs/SMAD and Wnt/ß-catenin signaling pathways.

BACKGROUND: Osteoporosis is a chronic bone disease characterized by bone loss and decreased bone strength. However, current anti-resorptive drugs carry a risk of various complications. The deep learning-based efficacy prediction system (DLEPS) is a forecasting tool that can effectively compete in drug screening and prediction based on gene expression changes. This study aimed to explore the protective effect and potential mechanisms of cinobufotalin (CB), a traditional Chinese medicine (TCM), on bone loss. METHODS: DLEPS was employed for screening anti-osteoporotic agents according to gene profile changes in primary osteoporosis. Micro-CT, histological and morphological analysis were applied for the bone protective detection of CB, and the osteogenic differentiation/function in human bone marrow mesenchymal stem cells (hBMMSCs) were also investigated. The underlying mechanism was verified using qRT-PCR, Western blot (WB), immunofluorescence (IF), etc. RESULTS: A safe concentration (0.25 mg/kg in vivo, 0.05 µM in vitro) of CB could effectively preserve bone mass in estrogen deficiency-induced bone loss and promote osteogenic differentiation/function of hBMMSCs. Both BMPs/SMAD and Wnt/ß-catenin signaling pathways participated in CB-induced osteogenic differentiation, further regulating the expression of osteogenesis-associated factors, and ultimately promoting osteogenesis. CONCLUSION: Our study demonstrated that CB could significantly reverse estrogen deficiency-induced bone loss, further promoting osteogenic differentiation/function of hBMMSCs, with BMPs/SMAD and Wnt/ß-catenin signaling pathways involved.

Computational methods for in situ structural studies with cryogenic electron tomography.

Cryo-electron tomography (cryo-ET) plays a critical role in imaging microorganisms in situ in terms of further analyzing the working mechanisms of viruses and drug exploitation, among others. A data processing workflow for cryo-ET has been developed to reconstruct three-dimensional density maps and further build atomic models from a tilt series of two-dimensional projections. Low signal-to-noise ratio (SNR) and missing wedge are two major factors that make the reconstruction procedure challenging. Because only few near-atomic resolution structures have been reconstructed in cryo-ET, there is still much room to design new approaches to improve universal reconstruction resolutions. This review summarizes classical mathematical models and deep learning methods among general reconstruction steps. Moreover, we also discuss current limitations and prospects. This review can provide software and methods for each step of the entire procedure from tilt series by cryo-ET to 3D atomic structures. In addition, it can also help more experts in various fields comprehend a recent research trend in cryo-ET. Furthermore, we hope that more researchers can collaborate in developing computational methods and mathematical models for high-resolution three-dimensional structures from cryo-ET datasets.