Aromatherapy refers to the method of using the aromatic components of plants in appropriate forms to act on the entire body or a specific area to prevent and treat diseases. Essential oils used in aromatherapy are hydrophobic liquids containing volatile aromatic molecules， such as limonene， linalool， linalool acetate， geraniol， and citronellol. These chemicals have been extensively studied and shown to have a variety of functions， including reducing anxiety， relieving depression， promoting sleep， and providing pain relief. Terpenoids are a class of organic molecules with relatively low lipid solubility. After being inhaled， they can pass through the nasal mucosa for transfer or penetrate the skin and enter the bloodstream upon local application. Some of these substances also have the ability to cross the blood-brain barrier， thereby exerting effects on the central nervous system. Currently， the academic community generally agrees that products such as essential oils and aromatherapy from aromatic plants have certain health benefits. However， the process of extracting a single component from it and successfully developing it into a drug still faces many challenges. Its safety and efficacy still need to be further verified through more rigorous and systematic experiments. This article systematically elaborated on the efficacy of aromatic substances， including plant extracts and natural small molecule compounds， in antibacterial and antiviral fields and the regulation of nervous system activity. As a result， a deeper understanding of aromatherapy was achieved. At the same time， the potential of these aromatic substances for drug development was thoroughly explored， providing important references and insights for possible future drug research and application.

Periodontitis is a common oral disease characterized by progressive alveolar bone resorption and inflammation of the periodontal tissues. Dimethyl fumarate (DMF) has been used in the treatment of various immune-inflammatory diseases due to its excellent anti-inflammatory and antioxidant functions. Here, we investigated for the first time the therapeutic effect of DMF on periodontitis. In vivo studies showed that DMF significantly inhibited periodontal destruction, enhanced mitophagy, and decreased the M1/M2 macrophage ratio. In vitro studies showed that DMF inhibited macrophage polarization toward M1 macrophages and promoted polarization toward M2 macrophages, with improved mitochondrial function, inhibited oxidative stress, and increased mitophagy in RAW 264.7 cells. Furthermore, DMF increased intracellular mitochondrial Tu translation elongation factor (TUFM) levels to maintain mitochondrial homeostasis, promoted mitophagy, and modulated macrophage polarization, whereas TUFM knockdown decreased the protective effect of DMF. Finally, mechanistic studies showed that DMF increased intracellular TUFM levels by protecting TUFM from degradation via the ubiquitin-proteasomal degradation pathway. Our results demonstrate for the first time that DMF protects mitochondrial function and inhibits oxidative stress through TUFM-mediated mitophagy in macrophages, resulting in a shift in the balance of macrophage polarization, thereby attenuating periodontitis. Importantly, this study provides new insights into the prevention of periodontitis.
Dimethyl Fumarate/pharmacology* ; Mitophagy/drug effects* ; Animals ; Mice ; Macrophages/metabolism* ; Periodontitis/prevention & control* ; RAW 264.7 Cells ; Oxidative Stress/drug effects* ; Peptide Elongation Factor Tu/metabolism* ; Mice, Inbred C57BL ; Male ; Mitochondria/drug effects*

Advancements in artificial intelligence (AI) and emerging technologies are rapidly expanding the exploration of chemical space, facilitating innovative drug discovery. However, the transformation of novel compounds into safe and effective drugs remains a lengthy, high-risk, and costly process. Comprehensive early-stage evaluation is essential for reducing costs and improving the success rate of drug development. Despite this need, no comprehensive tool currently supports systematic evaluation and efficient screening. Here, we present druglikeFilter, a deep learning-based framework designed to assess drug-likeness across four critical dimensions: 1) physicochemical rule evaluated by systematic determination, 2) toxicity alert investigated from multiple perspectives, 3) binding affinity measured by dual-path analysis, and 4) compound synthesizability assessed by retro-route prediction. By enabling automated, multidimensional filtering of compound libraries, druglikeFilter not only streamlines the drug development process but also plays a crucial role in advancing research efforts towards viable drug candidates, which can be freely accessed at https://idrblab.org/drugfilter/.

Objective: To explore the effects of sleep on subsequent day physical activity (PA) in children and adolescents, so as to provide a reference for refining PA intervention strategies and further investigating their underlying mechanisms. Methods: Through searching databases including Web of Science Core Collection, PubMed, EBSCOhost, ScienceDirect, Cochrane Library, CNKI, Wanfang and VIP cross sectional, cohort and experimental studies on sleep and subsequent day PA among children and adolescents were identified, with the searching period spanning from database inception to June, 2025. Based on the characteristics of the included literature, two sleep variables[sleep duration (SD) and sleep efficiency (SE)] and three physical activity variables[moderate to vigorous physical activity (MVPA), light physical activity (LPA), and total physical activity (TPA)] were selected. The relationship between these two types of variables was analyzed for pooled effect sizes using Stata 17.0. Results: A total of 14 studies were included, with 64.3% published in 2018 or later, involving 11 361 children and adolescents from 17 countries. Meta analysis results showed that both SD ( ES=0.04, 95%CI =0.01-0.07) and SE ( ES=0.24, 95%CI =0.01-0.47) were positively correlated with subsequent day MVPA (both P <0.05). However, no statistically significant associations were found with LPA ( ES=-0.04, 95%CI =-0.13 to 0.06; ES=-0.02, 95%CI =-0.15 to 0.11) or TPA( ES=0.09, 95%CI =-0.02 to 0.20; ES=0.02, 95%CI = -0.03 to 0.06)(all P >0.05). Subgroup analysis revealed that in the "≤6 years" subgroup, SD and SE were positively correlated with TPA ( ES=0.22, 95%CI =0.09-0.35) and MVPA ( ES=1.19, 95%CI =1.06-1.32), respectively; in the "6-12 years" subgroup, SD was positively correlated with MVPA ( ES=0.05, 95%CI =0.02-0.08); in the "≥12 years" subgroup, SE was positively correlated with LPA ( ES=0.08, 95%CI =0.00-0.16), while SD was negatively correlated with LPA ( ES=-0.23, 95%CI = -0.31 to -0.16) (all P <0.05). Conclusion Adequate SD and good SE can effectively enhance subsequent day MVPA among children and adolescents, although these sleep effects vary by age group.

Purpose: Explore the causal relationship between the gut microbiota and erectile dysfunction (ED) at phylum, class, order, family, and genus levels, and identify specific pathogenic bacteria that may be associated with the onset and progression of ED. Materials and Methods: The genetic variation data of 196 human gut microbiota incorporated in our study came from the human gut microbiome Genome Wide Association Studies (GWAS) dataset released by the MiBioGen Consortium. The GWAS statistics for ED were extracted from one study by Bovijn et al., which included 223,805 participants of European ancestry, of whom 6,175 were diagnosed with ED. Subsequently, Mendelian randomization (MR) analysis was carried out to explore whether a causal relationship exists between the gut microbiota and ED. Additionally, bidirectional MR analysis was performed to examine the directionality of the causal relationship. Results: Through MR analysis, we found that family Lachnospiraceae (odds ratio [OR]: 1.27, 95% confidence interval [CI]: 1.05–1.52, p=0.01) and its subclass genus LachnospiraceaeNC2004 group (OR: 1.17, 95% CI: 1.01–1.37, p=0.04) are associated with a higher risk of ED. In addition, genus Oscillibacter (OR: 1.17, 95% CI: 1.02–1.35, p=0.03), genus Senegalimassilia (OR: 1.32, 95% CI: 1.06–1.64, p=0.01) and genus Tyzzerella3 (OR: 1.14, 95% CI: 1.02–1.27, p=0.02) also increase the risk of ED. In contrast, the inverse variance weighted estimate of genus RuminococcaceaeUCG013 (OR: 0.77, 95% CI: 0.61–0.96, p=0.02) suggests that it has a protective effect against the occurrence of ED. Conclusions This study preliminarily identified 6 bacterial taxa that may have a causal relationship with ED, including family Lachnospiraceae, genus Lachnospiraceae NC2004 group, Oscillibacter, Senegalimassilia, Tyzzerella 3 and Ruminococcaceae UCG013. These identified important bacterial taxa may serve as candidates for microbiome intervention in future ED clinical trials.

Purpose: Explore the causal relationship between the gut microbiota and erectile dysfunction (ED) at phylum, class, order, family, and genus levels, and identify specific pathogenic bacteria that may be associated with the onset and progression of ED. Materials and Methods: The genetic variation data of 196 human gut microbiota incorporated in our study came from the human gut microbiome Genome Wide Association Studies (GWAS) dataset released by the MiBioGen Consortium. The GWAS statistics for ED were extracted from one study by Bovijn et al., which included 223,805 participants of European ancestry, of whom 6,175 were diagnosed with ED. Subsequently, Mendelian randomization (MR) analysis was carried out to explore whether a causal relationship exists between the gut microbiota and ED. Additionally, bidirectional MR analysis was performed to examine the directionality of the causal relationship. Results: Through MR analysis, we found that family Lachnospiraceae (odds ratio [OR]: 1.27, 95% confidence interval [CI]: 1.05–1.52, p=0.01) and its subclass genus LachnospiraceaeNC2004 group (OR: 1.17, 95% CI: 1.01–1.37, p=0.04) are associated with a higher risk of ED. In addition, genus Oscillibacter (OR: 1.17, 95% CI: 1.02–1.35, p=0.03), genus Senegalimassilia (OR: 1.32, 95% CI: 1.06–1.64, p=0.01) and genus Tyzzerella3 (OR: 1.14, 95% CI: 1.02–1.27, p=0.02) also increase the risk of ED. In contrast, the inverse variance weighted estimate of genus RuminococcaceaeUCG013 (OR: 0.77, 95% CI: 0.61–0.96, p=0.02) suggests that it has a protective effect against the occurrence of ED. Conclusions This study preliminarily identified 6 bacterial taxa that may have a causal relationship with ED, including family Lachnospiraceae, genus Lachnospiraceae NC2004 group, Oscillibacter, Senegalimassilia, Tyzzerella 3 and Ruminococcaceae UCG013. These identified important bacterial taxa may serve as candidates for microbiome intervention in future ED clinical trials.

Purpose: Explore the causal relationship between the gut microbiota and erectile dysfunction (ED) at phylum, class, order, family, and genus levels, and identify specific pathogenic bacteria that may be associated with the onset and progression of ED. Materials and Methods: The genetic variation data of 196 human gut microbiota incorporated in our study came from the human gut microbiome Genome Wide Association Studies (GWAS) dataset released by the MiBioGen Consortium. The GWAS statistics for ED were extracted from one study by Bovijn et al., which included 223,805 participants of European ancestry, of whom 6,175 were diagnosed with ED. Subsequently, Mendelian randomization (MR) analysis was carried out to explore whether a causal relationship exists between the gut microbiota and ED. Additionally, bidirectional MR analysis was performed to examine the directionality of the causal relationship. Results: Through MR analysis, we found that family Lachnospiraceae (odds ratio [OR]: 1.27, 95% confidence interval [CI]: 1.05–1.52, p=0.01) and its subclass genus LachnospiraceaeNC2004 group (OR: 1.17, 95% CI: 1.01–1.37, p=0.04) are associated with a higher risk of ED. In addition, genus Oscillibacter (OR: 1.17, 95% CI: 1.02–1.35, p=0.03), genus Senegalimassilia (OR: 1.32, 95% CI: 1.06–1.64, p=0.01) and genus Tyzzerella3 (OR: 1.14, 95% CI: 1.02–1.27, p=0.02) also increase the risk of ED. In contrast, the inverse variance weighted estimate of genus RuminococcaceaeUCG013 (OR: 0.77, 95% CI: 0.61–0.96, p=0.02) suggests that it has a protective effect against the occurrence of ED. Conclusions This study preliminarily identified 6 bacterial taxa that may have a causal relationship with ED, including family Lachnospiraceae, genus Lachnospiraceae NC2004 group, Oscillibacter, Senegalimassilia, Tyzzerella 3 and Ruminococcaceae UCG013. These identified important bacterial taxa may serve as candidates for microbiome intervention in future ED clinical trials.

Purpose: Explore the causal relationship between the gut microbiota and erectile dysfunction (ED) at phylum, class, order, family, and genus levels, and identify specific pathogenic bacteria that may be associated with the onset and progression of ED. Materials and Methods: The genetic variation data of 196 human gut microbiota incorporated in our study came from the human gut microbiome Genome Wide Association Studies (GWAS) dataset released by the MiBioGen Consortium. The GWAS statistics for ED were extracted from one study by Bovijn et al., which included 223,805 participants of European ancestry, of whom 6,175 were diagnosed with ED. Subsequently, Mendelian randomization (MR) analysis was carried out to explore whether a causal relationship exists between the gut microbiota and ED. Additionally, bidirectional MR analysis was performed to examine the directionality of the causal relationship. Results: Through MR analysis, we found that family Lachnospiraceae (odds ratio [OR]: 1.27, 95% confidence interval [CI]: 1.05–1.52, p=0.01) and its subclass genus LachnospiraceaeNC2004 group (OR: 1.17, 95% CI: 1.01–1.37, p=0.04) are associated with a higher risk of ED. In addition, genus Oscillibacter (OR: 1.17, 95% CI: 1.02–1.35, p=0.03), genus Senegalimassilia (OR: 1.32, 95% CI: 1.06–1.64, p=0.01) and genus Tyzzerella3 (OR: 1.14, 95% CI: 1.02–1.27, p=0.02) also increase the risk of ED. In contrast, the inverse variance weighted estimate of genus RuminococcaceaeUCG013 (OR: 0.77, 95% CI: 0.61–0.96, p=0.02) suggests that it has a protective effect against the occurrence of ED. Conclusions This study preliminarily identified 6 bacterial taxa that may have a causal relationship with ED, including family Lachnospiraceae, genus Lachnospiraceae NC2004 group, Oscillibacter, Senegalimassilia, Tyzzerella 3 and Ruminococcaceae UCG013. These identified important bacterial taxa may serve as candidates for microbiome intervention in future ED clinical trials.

Purpose: Explore the causal relationship between the gut microbiota and erectile dysfunction (ED) at phylum, class, order, family, and genus levels, and identify specific pathogenic bacteria that may be associated with the onset and progression of ED. Materials and Methods: The genetic variation data of 196 human gut microbiota incorporated in our study came from the human gut microbiome Genome Wide Association Studies (GWAS) dataset released by the MiBioGen Consortium. The GWAS statistics for ED were extracted from one study by Bovijn et al., which included 223,805 participants of European ancestry, of whom 6,175 were diagnosed with ED. Subsequently, Mendelian randomization (MR) analysis was carried out to explore whether a causal relationship exists between the gut microbiota and ED. Additionally, bidirectional MR analysis was performed to examine the directionality of the causal relationship. Results: Through MR analysis, we found that family Lachnospiraceae (odds ratio [OR]: 1.27, 95% confidence interval [CI]: 1.05–1.52, p=0.01) and its subclass genus LachnospiraceaeNC2004 group (OR: 1.17, 95% CI: 1.01–1.37, p=0.04) are associated with a higher risk of ED. In addition, genus Oscillibacter (OR: 1.17, 95% CI: 1.02–1.35, p=0.03), genus Senegalimassilia (OR: 1.32, 95% CI: 1.06–1.64, p=0.01) and genus Tyzzerella3 (OR: 1.14, 95% CI: 1.02–1.27, p=0.02) also increase the risk of ED. In contrast, the inverse variance weighted estimate of genus RuminococcaceaeUCG013 (OR: 0.77, 95% CI: 0.61–0.96, p=0.02) suggests that it has a protective effect against the occurrence of ED. Conclusions This study preliminarily identified 6 bacterial taxa that may have a causal relationship with ED, including family Lachnospiraceae, genus Lachnospiraceae NC2004 group, Oscillibacter, Senegalimassilia, Tyzzerella 3 and Ruminococcaceae UCG013. These identified important bacterial taxa may serve as candidates for microbiome intervention in future ED clinical trials.

Objective: Based on physical activity (PA) and sedentary behavior (SB) variables on weekdays and weekends, the study aims to cluster the physical activities inside and outside kindergartens and to explore the cluster characteristics of different children using physical fitness indicators, so as to provide new strategies and methods for early childhood education and health. Methods: From March to June 2019, 291 children aged 3-6 years from 6 kindergartens in Nanchang were recruited by a stratified cluster random sampling method. The ActiGraph GT3X-BT triaxial accelerometer was used to measure and analyze the PA and SB levels inside and outside the kindergarten. A twostep clustering algorithm model was employed for cluster analysis. Physical fitness were measured and evaluated according to the "National Physical Fitness Measurement Standard Manual (Preschool Section)". Differences in physical fitness among different clusters of children were compared, and the cluster characteristics of different children were analyzed. Results: The clustering algorithm model indicated that based on six indicators, including PA and SB inside the kindergarten on weekdays, and PA and SB outside the kindergarten on both weekdays and weekends, children could be divided into three categories:active inside (high PA, low SB inside), active outside (high PA outside), and inactive (low PA, high SB both inside and outside). The average silhouette coefficient of the model was 0.3, indicating good clustering results. Both the active inside and active outside children showed significantly higher PA inside on weekdays, PA outside on weekdays and weekends, daily low intensity physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) than the inactive children ( F=157.91, 80.79 , 95.86, 95.52, 124.74, P <0.05). After adjusting for gender and age, the physical fitness scores of both active outside ( 19.03 ±0.47) and active inside (19.11±0.40) were significantly higher than those of the inactive children (17.94±0.31). Additionally, active inside children (3.91±0.14) also showed significantly better performance in continuous double-leg jumps, compared to inactive children (3.45±0.11) ( P <0.05). Conclusion Children active inside and those active outside perform well in PA. Future research should focus on the proportion of structured and unstructured PA time to enhance the overall physical fitness of children.