Search

Osteoporosis, a systemic skeletal disorder marked by diminished bone mass and compromised bone microarchitecture, is becoming increasingly prevalent due to an aging population. The underlying pathophysiology of osteoporosis is attributed to an imbalance between osteoclast-mediated bone resorption and osteoblast-mediated bone formation. Osteoclasts play a crucial role in the development of osteoporosis through various molecular pathways, including the RANK/RANKL/OPG signaling axis, cytokines, and integrins. Notably, the calcium signaling pathway is pivotal in regulating osteoclast activation and function, influencing bone resorption activity. Disruption in calcium signaling can lead to increased osteoclast-mediated bone resorption, contributing to the progression of osteoporosis. Emerging research indicates that calcium-permeable channels on the cellular membrane play a critical role in bone metabolism by modulating these intracellular calcium pathways. Here, we provide an overview of current literature on the regulation of plasma membrane calcium channels in relation to bone metabolism with particular emphasis on their dysregulation during the progression of osteoporosis. Targeting these calcium channels may represent a potential therapeutic strategy for treating osteoporosis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Hao, Yang, Sun, Yang and Chen.)

Gene expression profiling of new or modified cell lines becomes routine today; however, obtaining comprehensive molecular characterization and cellular responses for a variety of cell lines, including those derived from underrepresented groups, is not trivial when resources are minimal. Using gene expression to predict other measurements has been actively explored; however, systematic investigation of its predictive power in various measurements has not been well studied. Here, we evaluated commonly used machine learning methods and presented TransCell, a two-step deep transfer learning framework that utilized the knowledge derived from pan-cancer tumor samples to predict molecular features and responses. Among these models, TransCell had the best performance in predicting metabolite, gene effect score (or genetic dependency), and drug sensitivity, and had comparable performance in predicting mutation, copy number variation, and protein expression. Notably, TransCell improved the performance by over 50% in drug sensitivity prediction and achieved a correlation of 0.7 in gene effect score prediction. Furthermore, predicted drug sensitivities revealed potential repurposing candidates for new 100 pediatric cancer cell lines, and predicted gene effect scores reflected BRAF resistance in melanoma cell lines. Together, we investigated the predictive power of gene expression in six molecular measurement types and developed a web portal (http://apps.octad.org/transcell/) that enables the prediction of 352,000 genomic and cellular response features solely from gene expression profiles., (© The Author(s) 2024. Published by Oxford University Press and Science Press on behalf of the Beijing Institute of Genomics, Chinese Academy of Sciences / China National Center for Bioinformation and Genetics Society of China.)

A proactive mobile network (PMN) is a novel architecture enabling extremely low-latency communication. This architecture employs an open-loop transmission mode that prohibits all real-time control feedback processes and employs virtual cell technology to allocate resources non-exclusively to users. However, such a design also results in significant potential user interference and worsens the communication's reliability. In this paper, we propose introducing multi-reconfigurable intelligent surface (RIS) technology into the downlink process of the PMN to increase the network's capacity against interference. Since the PMN environment is complex and time varying and accurate channel state information cannot be acquired in real time, it is challenging to manage RISs to service the PMN effectively. We begin by formulating an optimization problem for RIS phase shifts and reflection coefficients. Furthermore, motivated by recent developments in deep reinforcement learning (DRL), we propose an asynchronous advantage actor-critic (A3C)-based method for solving the problem by appropriately designing the action space, state space, and reward function. Simulation results indicate that deploying RISs within a region can significantly facilitate interference suppression. The proposed A3C-based scheme can achieve a higher capacity than baseline schemes and approach the upper limit as the number of RISs increases.

Purpose: To review and critically evaluate currently available risk prediction models for breast cancer-related lymphedema (BCRL)., Methods: PubMed, Embase, CINAHL, Scopus, Web of Science, the Cochrane Library, CNKI, SinoMed, WangFang Data, VIP Database were searched from inception to April 1, 2022, and updated on November 8, 2022. Study selection, data extraction and quality assessment were conducted by two independent reviewers. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability. Meta-analysis of AUC values of model external validations was performed using Stata 17.0., Results: Twenty-one studies were included, reporting twenty-two prediction models, with the AUC or C-index ranging from 0.601 to 0.965. Only two models were externally validated, with the pooled AUC of 0.70 (n = 3, 95%CI: 0.67 to 0.74), and 0.80 (n = 3, 95%CI: 0.75 to 0.86), respectively. Most models were developed using classical regression methods, with two studies using machine learning. Predictors most frequently used in included models were radiotherapy, body mass index before surgery, number of lymph nodes dissected, and chemotherapy. All studies were judged as high overall risk of bias and poorly reported., Conclusions: Current models for predicting BCRL showed moderate to good predictive performance. However, all models were at high risk of bias and poorly reported, and their performance is probably optimistic. None of these models is suitable for recommendation in clinical practice. Future research should focus on validating, optimizing, or developing new models in well-designed and reported studies, following the methodology guidance and reporting guidelines., Competing Interests: Declaration of competing interest The authors have no relevant financial or non-financial interests to disclose., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

BACKGROUND The role of nutritional parameter prealbumin in predicting the incidence of hepatic encephalopathy (HE) remains unclear. This study was designed to assess the diagnostic performance of prealbumin in predicting the incidence of HE in hepatitis B virus (HBV)-related decompensated liver cirrhosis patients. MATERIAL AND METHODS A retrospective cohort of 262 patients with HBV-related decompensated liver cirrhosis was involved in this study. Prealbumin, albumin, and other indicators were collected at admission, and independent factors were identified by logistic regression analysis. The Mann-Whitney U test and receiver operating characteristic (ROC) curves were used to compare the groups and indicators. RESULTS A total of 262 patients were enrolled in the study, including 197 men and 65 women. In patients with HBV-related decompensated liver cirrhosis accompanied by HE, the model for end-stage liver disease (MELD) scores, and prothrombin time (PT) and international normalized ratio (INR) values were significantly increased, while prealbumin and albumin levels were significantly decreased. Multivariate analysis showed that only serum prealbumin level (P=0.014) was independently related to the incidence of HE. Moreover, prealbumin level was negatively correlated with MELD (r=-0.63, P<0.001) and Child-Turcotte-Pugh (r=-0.35, P<0.001) scores. ROC curves were performed, and prealbumin showed the highest area under the ROC curve (0.781) compared with MELD and Child-Turcotte-Pugh scores. CONCLUSIONS Low prealbumin levels were associated with increased frequency of hepatic encephalopathy in HBV-related decompensated cirrhosis, which showed better performance than traditional models.

Leveraging computational methods to generate small molecules with desired properties has been an active research area in the drug discovery field. Towards real-world applications, however, efficient generation of molecules that satisfy multiple property requirements simultaneously remains a key challenge. In this paper, we tackle this challenge using a search-based approach and propose a simple yet effective framework called MolSearch for multi-objective molecular generation (optimization). We show that given proper design and sufficient information, search-based methods can achieve performance comparable or even better than deep learning methods while being computationally efficient. Such efficiency enables massive exploration of chemical space given constrained computational resources. In particular, MolSearch starts with existing molecules and uses a two-stage search strategy to gradually modify them into new ones, based on transformation rules derived systematically and exhaustively from large compound libraries. We evaluate MolSearch in multiple benchmark generation settings and demonstrate its effectiveness and efficiency.

Kruppel-associated box (KRAB) zinc-finger proteins (KRAB-ZFPs) are the largest transcriptional/transcription-regulatory factor family in mammalian cells. The amino-terminal KRAB domain, which recruits other transcription-regulating proteins, and the carboxyl-terminal C2H2 zinc-finger motifs, which bind to specific DNA sequences, are the typical structural characteristics of KRAB-ZFPs. Many KRAB-ZFPs are abnormally expressed in several cancer types and involved in many cancer-related signaling pathways and bioprocesses, including cell proliferation, apoptosis, migration, invasion, and metastasis. In this review, we summarize the protein structure and mechanisms involved in transcriptional regulation, and focus on multiple key signaling pathways regulated by KRAB-ZFPs, including the p53, Wnt/β-catenin, and NF-κB pathways, highlighting the oncogenic and tumor-suppressive roles of KRAB-ZFPs in different cancers. We also discuss the mechanisms regulating KRAB-ZFP expression. The further elucidation of the oncogenic and tumor-suppressive roles of KRAB-ZFPs and their targeting for multiple synergistic signaling pathways may be valuable for effective cancer therapy., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Mg doped Ni(OH) 2 was synthesized and investigated as an efficient material to activate persulfate (PS) for phenol degradation. The property of the Ni(OH) 2 material was enhanced by Mg doping as the removal efficiency of phenol was increased from 74.82 % in Ni(OH) 2 /PS system to 89.53 % in Mg-doped Ni(OH) 2 /PS system within 20 min. Such a high removal efficiency revealed that doping Mg into Ni(OH) 2 brings about more defects (oxygen vacancies), which facilitated the formation of more active species in the degradation process. The removal efficiencies of phenol increased with the increase of the initial pH from 3 to 11. The influences of Cl - , NO 3 - and HCO 3 - on the stability of the system were also studied and the results showed that removal rates of all systems in the presence of these different inorganic anions could reached about 90 % within 20 min. Based on the electron spin resonance (ESR) experiments, 1 O 2 , O 2 ·- , ·OH and SO 4 •- were identified as the active species in Mg-doped Ni(OH) 2 /PS system for phenol degradation and a degradation mechanism was proposed for this system. In addition, the as-prepared material retained its activation performance even after 3 repeated cycles., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Hyperoside has a variety of pharmacological activities, including anti-liver injury, anti-depression, anti-inflammatory, and anti-cancer activities. However, the effect of hyperoside on Parkinson's disease (PD) is still unclear. Therefore, we tried to study the therapeutic effect and mechanism of hyperoside on PD in vivo and in vitro models. Rotenone was used to induce PD rat model and SH-SY5Y cell injury model, and hyperoside was used for intervention. Immunohistochemistry, animal behavior assays, TUNEL and Western blot were constructed to observe the protective effect and related mechanisms of hyperoside in vivo. Cell counting kit-8 (CCK-8), flow cytometry, Rh123 staining and Western blot were used for in vitro assays. Rapamycin (RAP) pretreatment was used in rescue experiments to verify the relationship between hyperoside and autophagy in rotenone-induced SH-SY5Y cells. Hyperoside promoted the number of tyrosine hydroxylase (TH)-positive cells, improved the behavioral defects of rats, and inhibited cell apoptosis in vivo. Different concentrations of hyperoside had no significant effect on SH-SY5Y cell viability, but dramatically reversed the rotenone-induced decrease in cell viability, increased apoptosis and loss of cell mitochondrial membrane potential in vitro. Additionally, hyperoside reversed the regulation of rotenone on the Beclin1, LC3II, Bax, cleaved caspase 3, Cyc and Bcl-2 expressions in rat SNpc tissues and SH-SY5Y cells, while promoted the regulation of rotenone on the P62 and α-synuclcin. Furthermore, RAP reversed the effect of hyperoside on rotenone-induced SH-SY5Y cells. Hyperoside may play a neuroprotective effect in rotenone-induced PD rat model and SH-SY5Y cell model by affecting autophagy., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Recent years have seen a rapid growth of utilizing graph neural networks (GNNs) in the biomedical domain for tackling drug-related problems. However, like any other deep architectures, GNNs are data hungry. While requiring labels in real world is often expensive, pretraining GNNs in an unsupervised manner has been actively explored. Among them, graph contrastive learning, by maximizing the mutual information between paired graph augmentations, has been shown to be effective on various downstream tasks. However, the current graph contrastive learning framework has two limitations. First, the augmentations are designed for general graphs and thus may not be suitable or powerful enough for certain domains. Second, the contrastive scheme only learns representations that are invariant to local perturbations and thus does not consider the global structure of the dataset, which may also be useful for downstream tasks. In this paper, we study graph contrastive learning designed specifically for the biomedical domain, where molecular graphs are present. We propose a novel framework called MoCL, which utilizes domain knowledge at both local- and global-level to assist representation learning. The local-level domain knowledge guides the augmentation process such that variation is introduced without changing graph semantics. The global-level knowledge encodes the similarity information between graphs in the entire dataset and helps to learn representations with richer semantics. The entire model is learned through a double contrast objective. We evaluate MoCL on various molecular datasets under both linear and semi-supervised settings and results show that MoCL achieves state-of-the-art performance.

Training deep neural models in the presence of corrupted supervision is challenging as the corrupted data points may significantly impact the generalization performance. To alleviate this problem, we present an efficient robust algorithm that achieves strong guarantees without any assumption on the type of corruption, and provides a unified framework for both classification and regression problems. Unlike many existing approaches that quantify the quality of the data points (e.g., based on their individual loss values), and filter them accordingly, the proposed algorithm focuses on controlling the collective impact of data points on the average gradient. Even when a corrupted data point failed to be excluded by our algorithm, the data point will have very limited impact on the overall loss, as compared with state-of-the-art filtering methods based on loss values. Extensive experiments on multiple benchmark datasets have demonstrated the robustness of our algorithm under different types of corruptions.

The exopolysaccharide (EPS) of some Lactobacillus strains has been reported to exert anti-cancer activities. In this study, the effects of crude EPSs produced by four Lactobacillus plantarum strains (Lactobacillus plantarum-12, L. plantarum-14, L. plantarum-32, and L. plantarum-37) on HT-29 cell proliferation and apoptosis were studied. The results showed that the inhibition rate of the crude EPS produced by L. plantarum-12 on HT-29 cell proliferation was significantly higher than that of the EPS produced by the other three strains. L. plantarum-12 crude EPS (50, 100, 250, 500 μg/ml) exerted inhibitory effects on the expression of proliferating cell nuclear antigen (PCNA) in HT-29 cells in a positive dose-dependent manner. The reactive oxygen species (ROS) level and apoptosis rate were also increased in HT-29 cells treated with different concentrations of L. plantarum-12 crude EPS compared with control cells. Further studies found that the expression of the pro-apoptotic proteins Bax, Cyt C, caspase-3, caspase-8 and caspase-9 was upregulated and that the expression of the anti-apoptosis protein Bcl-2 was decreased in HT-29 cells treated with L. plantarum-12 crude EPS compared with control cells. The results suggested that the EPS produced by L. plantarum-12 could inhibit the proliferation of the human colon cancer cell line HT-29 through the mitochondrial pathway.

Our previous study demonstrated that Lactobacillus plantarum Y44 exhibited antioxidant activity. However, the physiological characteristics of L. plantarum Y44 exposure to oxidative stress was not clear. In this research, the differentially expressed proteins and genes in L. plantarum Y44 under 2,2-azobis(2-methylpropionamidine) dihydrochloride (AAPH) stress at different concentrations were studied by using integrated transcriptomic and proteomic methods. Under 100 mM AAPH stress condition, 1139 differentially expressed genes (DEGs, 546 up-regulated and 593 down-regulated) and 329 differentially expressed proteins (DEPs, 127 up-regulated and 202 down-regulated) were observed. Under 200 mM AAPH stress condition, 1526 DEGs (751 up-regulated and 775 down-regulated) and 382 DEPs (139 up-regulated and 243 down-regulated) were observed. Overall, we found that L. plantarum Y44 fought against AAPH induced oxidative stress by up-regulating antioxidant enzymes and DNA repair proteins, such as ATP-dependent DNA helicase RuvA, adenine DNA glycosylase, single-strand DNA-binding protein SSB, DNA-binding ferritin-like protein DPS, thioredoxin reductase, protein-methionine-S-oxide reductase and glutathione peroxidase. Additionally, cell envelope composition of L. plantarum Y44 was highly remodeled by accelerating peptidoglycan and teichoic-acid (LTA) biosynthesis and modulating the fatty acids (FA) composition to achieve a higher ratio of unsaturated/saturated fatty acids (UFAs/SFAs) against AAPH stress. Moreover, metabolism processes including carbohydrate metabolism, amino acid biosynthesis, and nucleotide metabolism altered to respond to AAPH-induced damage. Altogether, our findings allow us to facilitate a better understanding of L. plantarum Y44 against oxidative stress. SIGNIFICANCE: This study represents an integrated proteomic and transcriptomic analysis of Lactobacillus plantarum Y44 response to 2,2-azobis(2-methylpropionamidine) dihydrochloride (AAPH) stress. Differentially expressed proteins and genes were identified between the proteome and transcriptome of L. plantarum Y44 under different AAPH stress. AAPH-induced response of L. plantarum Y44 appears to be primarily based on ROS scavenging, DNA repair, highly remodeled cell surface and specific metabolic processes. The knowledge about these proteomes and transcriptomes provides significant insights into the oxidative stress response of Lactobacillus plantarum., Competing Interests: Declaration of Competing Interest All authors declare no competing financial interest., (Copyright © 2020. Published by Elsevier B.V.)

Fe@Fe 2 O 3 core shell nanomaterials with different Fe 2 O 3 shell thickness were synthesized and the Fe@Fe 2 O 3 /NaHSO 3 Fenton-like system was used for the decomposition of Orange II. The consequences are compared with traditional Fenton Fe@Fe 2 O 3 /H 2 O 2 system. The Fe@Fe 2 O 3 /NaHSO 3 system showed extremely good applicability under both strongly acidic and alkaline conditions. The new Fe@Fe 2 O 3 -(2)/NaHSO 3 system led to more than 99% degradation in 30 s when the pH was 3, which indicated that the Fe@Fe 2 O 3 material was not corroded during the process even under strongly acidic condition. The above Fe@Fe 2 O 3 -(2) material was prepared from nano-zero-valent iron aged in solution for 2 h to synthesize the Fe 2 O 3 shell. The reaction mechanism of Fe@Fe 2 O 3 /NaHSO 3 Fenton-like system was also concluded. The oxidation efficiency was highly improved due to rapid electron transfer between Fe core and Fe 2 O 3 shell, which promoted the direct recycling of ≡Fe 3+ and ≡Fe 2+ and thus accelerated the generation of SO 4 - and OH radicals., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

The homogeneous Fe(VI)/Na 2 SO 3 system has been proposed for highly efficient degradation of recalcitrant contaminants, in which sulfite could significantly enhance the transformation of organic substrate by Fe(VI). Also, the Fe(VI)/NaHSO 3 system could show high efficiency across a wide range of pH conditions. The degradation rates reached up to 80% within 2 min and 70% within 5 min in strongly acidic and alkaline conditions, respectively. Unexpectedly, a faster removal rate was obtained in Fe(VI)/NaHSO 3 system than that in Fe(VI)/Na 2 SO 3 system for the degradation of methylene blue (MB). A reasonable dye degradation mechanism was proposed and verified by a series of experiments. The high oxidation potential of Fe(VI) and other species such as sulfate and hydroxyl radicals were responsible for the outstanding capabilities of Fe(VI)/NaHSO 3 system, which could significantly improve the treatment of organics in wastewater under a very wide range of pH conditions., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Regorafenib (RG) was an oral multi-kinase inhibitor with poor water solubility. In order to enhance the drug's solubility, dissolution and bioavailability, the binary molecular chaperone drug between RG and β-cyclodetrin (β-CD) had prepared by co-crystallization. The structure of RG-β-CD was characterized by thermal analysis, powder X-ray diffraction, infrared spectroscopy and nuclear magnetic resonance. Phase-solubility study revealed the higher solubility and complexing ability of β-CDwith RG.The solubility and dissolution of RG-β-CD was significantly enhanced in pH 1.2 medium, pH 6.8 PBS buffer solution and distilled water compared to RG. In vivo distribution and antitumor studies revealed that the bioavailability of RG-β-CD was increased when β-CD mated with RG. Therefore, these findings could provide a suitable pharmaceutical dosage to enhanced therapeutic activity., (Copyright © 2017 Elsevier B.V. All rights reserved.)