Identification of candidate plasma miRNA biomarkers for the diagnosis of head and neck squamous cell carcinoma.

Aim: Current head and neck squamous cell carcinoma (HNSCC) diagnostic tools are limited, so this study aimed to identify diagnostic microRNA (miRNA) biomarkers from plasma. Materials & methods: A total of 76 HNSCC and 76 noncancerous control (NC) plasma samples underwent microarray analysis and quantitative reverse transcription PCR to screen for diagnostic plasma miRNAs. The diagnostic potential of the miRNAs was evaluated by the receiver operating characteristic curve. Results: miR-95-3p and miR-579-5p expression was shown to be significantly upregulated, and that of miR-1298-3p to be downregulated in HNSCC patients compared with controls. The final diagnostic panel included miR-95-3p, miR-579-5p and miR-1298-3p with an area under the curve of 0.83. Conclusion: This three-miRNA panel has potential for the diagnosis of HNSCC.

Early detection of head and neck cancer is crucial. In this study, we established a diagnostic model based on blood samples. This is a convenient diagnostic and screening tool that can help people early detect head and neck cancer.

Long-term nitrogen input reduces soil bacterial network complexity by shifts in life history strategy in temperate grassland.

We investigated soil bacterial and fungal communities, constructed co-occurrence networks, and estimated bacterial traits along a gradient of nitrogen (N) input. The results showed that soil bacterial co-occurrence networks complexity decreased with increasing N input. The ratio of negative to positive cohesion decreased with increasing N input, suggesting the declined competitive but strengthened cooperative interactions. However, soil fungal network complexity did not change under N enrichment. In addition, N input stimulated the copiotroph/oligotroph ratio, ribosomal RNA operon (rrn) copy number, and guanine-cytosine (GC) content of soil bacteria, shifting bacterial life history strategy toward copiotroph with increased r-/K-strategy ratio. Piecewise structural equation modeling results further revealed that the reduction in bacterial co-occurrence network complexity was directly regulated by the increased bacterial r-/K-strategy ratio, rather than reduced bacterial richness. Our study reveals the mechanisms through which microbial traits regulate interactions and shape co-occurrence networks under global changes.

Construction and validation of "WCH-nomogram" for predicting the prognosis after resection of colorectal liver metastases.

BACKGROUND: The prognostic predictive tool for patients with colorectal liver metastasis (CRLM) is limited and the criteria for administering preoperative neoadjuvant chemotherapy in CRLM patients remain controversial. METHODS: This study enrolled 532 CRLM patients at West China Hospital (WCH) from January 2009 to December 2019. Prognostic factors were identified from the training cohort to construct a WCH-nomogram and evaluating accuracy in the validation cohort. Receiver operating characteristic (ROC) curve analysis was used to compare the prediction accuracy with other existing prediction tools. RESULTS: From the analysis of the training cohort, four independent prognostic risk factors, namely tumor marker score, KRAS mutation, primary lymph node metastasis, and tumor burden score were identified on which a WCH-nomogram was constructed. The C-index of the two cohorts were 0.674 (95% CI: 0.634-0.713) and 0.655 (95% CI: 0.586-0.723), respectively, which was better than the previously reported predication scores (CRS, m-CS and GAME score). ROC curves showed AUCs for predicting 1-, 3-, and 5-year overall survival (OS) of 0.758, 0.709, and 0.717 in the training cohort, and 0.860, 0.669, and 0.692 in the validation cohort, respectively. A cutoff value of 114.5 points was obtained for the WCH-nomogram total score based on the maximum Youden index of the ROC curve of 5-year OS. Risk stratification showed significantly better prognosis in the low-risk group, however, the high-risk group was more likely to benefit from neoadjuvant chemotherapy. CONCLUSIONS: The WCH-nomogram demonstrates superior prognostic stratification compared to prior scoring systems, effectively identifying CRLM patients who may benefit the most from neoadjuvant chemotherapy.

Application of hybrid multi-criteria decision-making approach to analyze wastewater microalgae culture systems for bioenergy production.

Bioenergy generation from microalgae can significantly contribute to climate mitigation and renewable energy production. In this regard, several multi-criteria decision-making method were employed to prioritize appropriate microalgae culture system for bioenergy production. Entropy weight, Criteria Importance Through Intercriteria Correlation (CRITIC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were the employed MCDA method. Fourteen microalgae culture systems were selected as a case study, which contain teen monoculture and four dual-culture. Initially, through ans in-depth review of the literature and expert views, four categories total eight indicators were selected as the evaluation indices of the study, namely 1) Proliferation: Half growth cycle and Max growth rate,2) Biomass output: Bio-crude yield and Lipid yield, 3) Nutrient utilization: residual concentration of total Nitrogen and total Phosphorus, and, 4) Stability: coefficient of variation of Bio-crude yield and Lipid yield. The result indicated that "Pediastrum sp. & Micractinium sp." was identified as the most bioenergy potential microalgae culture system, and the evaluation results of entropy weight method and CRITIC method are similar. It is pertinent to note that 1)the entropy weight method exhibits lower sample size requirements, 2) the critic method excels when dealing with larger sample sizes, and 3) the TOPSIS method necessitates the incorporation of appropriate weighting methods to ensure credible results. In the application stage, the key indicators related to cost can be further included in the evaluation indices.

A novel photoelectrochemical self-screening aptamer biosensor based on CAU-17-derived Bi2WO6/Bi2S3 for rapid detection of quorum sensing signal molecules.

Quorum sensing signal molecule is an important biomarker released by some microorganisms, which can regulate the adhesion and aggregation of marine microorganisms on the surface of engineering facilities. Thus, it is significant to exploit a convenient method that can effectively monitor the formation and development of marine biofouling. In this work, an advanced photoelectrochemical (PEC) aptamer biosensing platform was established and firstly applied for the rapid and ultrasensitive determination of N-(3-Oxodecanoyl)-l-homoserine lactone (3-O-C10-HL) released from marine fouling microorganism Ponticoccus sp. PD-2. The visible-light-driven Bi2WO6/Bi2S3 heterojunction derived from metal-organic frameworks (MOFs) CAU-17 and self-screened aptamer were employed as the photoactive materials and bioidentification elements, respectively. Appropriate amount of MoS2 quantum dots (QDs) conjugated with single-stranded DNA were introduced by hybridization to enhance the photocurrent response of the PEC biosensor. The self-screening aptamer can specifically recognize 3-O-C10-HL, accompanied by increasing the steric hindrance and forcing MoS2 QDs to leave the electrode surface, resulting in an obvious reduction of photocurrent and achieving a dual-inhibition signal amplification effect. Under the optimized conditions, the photocurrent response of PEC aptasensor was linear with 3-O-C10-HL concentration from 1 nM to 10 µM, and the detection limit was as low as 0.26 nM. The detection strategy also showed a high reproducibility, superior specificity and good stability. This work not only provides a simple, rapid and ultrasensitive PEC aptamer biosensing strategy for monitoring quorum sensing signal molecules in marine biofouling, but also broadens the application of MOFs-based heterojunctions in PEC sensors.

Study of Iron Complex Photosensitizer with Hollow Double-Shell Nano Structure Used to Enhance Ferroptosis and Photodynamic Therapy.

Ferroptosis therapy, which uses ferroptosis inducers to produce lethal lipid peroxides and induce tumor cell death, is considered a promising cancer treatment strategy. However, challenges remain regarding how to increase the accumulation of reactive oxygen species (ROS) in the tumor microenvironment (TME) to enhance antitumor efficacy. In this study, a hyaluronic acid (HA) encapsulated hollow mesoporous manganese dioxide (H-MnO2 ) with double-shell nanostructure is designed to contain iron coordinated cyanine near-infrared dye IR783 (IR783-Fe) for synergistic ferroptosis photodynamic therapy against tumors. The nano photosensitizer IR783-Fe@MnO2 -HA, in which HA actively targets the CD44 receptor, subsequently dissociates and releases Fe3+ and IR783 in acidic TME. First, Fe3+ consumes glutathione to produce Fe2+ , which promotes the Fenton reaction in cells to produce hydroxyl free radicals (·OH) and induce ferroptosis of tumor cells. In addition, MnO2 catalyzes the production of O2 from H2 O2 and enhances the production of singlet oxygen (1 O2 ) by IR783 under laser irradiation, thus increasing the production and accumulation of ROS to provide photodynamic therapy. The highly biocompatible IR783-Fe@MnO2 -HA nano-photosensitizers have exhibited tumor-targeting ability and efficient tumor inhibition in vivo due to the synergistic effect of photodynamic and ferroptosis antitumor therapies.

Causal association of serum biomarkers with oral cavity and oropharyngeal cancer: a mendelian randomization study.

BACKGROUND: Observational epidemiological studies revealed that multiple serum biomarkers can be associated with the risk of oral and oropharyngeal cancer (OC/OPC). However, the causal relationship between them remains largely unknown. This study aimed to investigate the causal relationship between potential serum biomarkers and (OC/OPC). METHODS: A two-sample Mendelian randomization (MR) approach was performed to assess the causal association of 10 serum biomarkers with the risk of OC / OPC. Summary data on OC/OPC were obtained from a GWAS meta-analysis that included 2497 cases and 2928 controls. The TwoSampleMR package in R was used to perform MR analyzes. Inverse-variance weighted (IVW), Weighted median and MR-Egger methods were used to assess causal effects. RESULTS: Suggestive associations with increased risk of C-reactive protein (CRP) (OR 1.52, 95% CI 1.14 to 2.02), using the IVW method. MR-Egger regression suggested that directional pleiotropy was unlikely to bias the result (P = 0.19). The findings were robust to sensitivity analyzes. The risk of OC/OPC was not associated with serum 25-hydroxyvitamin D, HDL cholesterol, LDL cholesterol, total cholesterol, triglycerides, adiponectin, leptin, HbA1C and Insulin-like growth factor 1 (IGF 1). CONCLUSIONS: This study supports that CRP was causally associated with an increased risk of oral and oropharyngeal cancer.

Deepened snow cover increases grassland soil carbon stocks by incorporating carbon inputs into deep soil layers.

Climate-induced changes in snow cover can greatly impact winter soil microclimate and spring water supply. These effects, in turn, can influence plant and microbial activity and the strength of leaching processes, potentially altering the distribution and storage of soil organic carbon (SOC) across different soil depths. However, few studies have examined how changes in snow cover will affect SOC stocks, and even less is known about the impact of snow cover on SOC dynamics along soil profiles. By selecting 11 snow fences along a 570 km climate gradient in Inner Mongolia, covering arid, temperate, and meadow steppes, we measured plant and microbial biomass, community composition, SOC content, and other soil parameters from topsoil to a depth of 60 cm. We found that deepened snow increased aboveground and belowground plant biomass, as well as microbial biomass. Plant and microbial carbon input were positively correlated with grassland SOC stocks. More importantly, we found that deepened snow altered SOC distribution along vertical soil profiles. The increase in SOC caused by deepened snow was much greater in the subsoil (+74.7%; 40-60 cm) than that in the topsoil (+19.0%; 0-5 cm). Additionally, the controls on SOC content under deepened snow differed between the topsoil and subsoil layers. The increase in microbial and root biomass jointly enhanced topsoil C accumulation, while the increase in leaching processes became critical in promoting subsoil C accumulation. We conclude that under deepened snow, the subsoil had a high capacity to sink C by incorporating C leached from the topsoil, suggesting that the subsoil, originally thought to be climate insensitive, could have a higher response to precipitation changes due to vertical C transport. Our study highlights the importance of considering soil depth when assessing the impacts of snow cover changes on SOC dynamics.

Foliar nutrient resorption stoichiometry and microbial phosphatase catalytic efficiency together alleviate the relative phosphorus limitation in forest ecosystems.

Understanding how plants adapt to spatially heterogeneous phosphorus (P) supply is important to elucidate the effect of environmental changes on ecosystem productivity. Plant P supply is concurrently controlled by plant internal conservation and external acquisition. However, it is unclear how climate, soil, and microbes influence the contributions and interactions of the internal and external pathways for plant P supply. Here, we measured P and nitrogen (N) resorption efficiency, litter and soil acid phosphatase (AP) catalytic parameters (Vmax(s) and Km ), and soil physicochemical properties at four sites spanning from cold temperate to tropical forests. We found that the relative P limitation to plants was generally higher in tropical forests than temperate forests, but varied greatly among species and within sites. In P-impoverished habitats, plants resorbed more P than N during litterfall to maintain their N : P stoichiometric balance. In addition, once ecosystems shifted from N-limited to P-limited, litter- and soil-specific AP catalytic efficiency (Vmax(s) /Km ) increased rapidly, thereby enhancing organic P mineralization. Our findings suggested that ecosystems develop a coupled aboveground-belowground strategy to maintain P supply and N : P stoichiometric balance under P-limitation. We also highlighted that N cycle moderates P cycles and together shape plant P acquisition in forest ecosystems.

The grassland carbon cycle: Mechanisms, responses to global changes, and potential contribution to carbon neutrality.

Grassland is one of the largest terrestrial biomes, providing critical ecosystem services such as food production, biodiversity conservation, and climate change mitigation. Global climate change and land-use intensification have been causing grassland degradation and desertification worldwide. As one of the primary medium for ecosystem energy flow and biogeochemical cycling, grassland carbon (C) cycling is the most fundamental process for maintaining ecosystem services. In this review, we first summarize recent advances in our understanding of the mechanisms underpinning spatial and temporal patterns of the grassland C cycle, discuss the importance of grasslands in regulating inter- and intra-annual variations in global C fluxes, and explore the previously unappreciated complexity in abiotic processes controlling the grassland C balance, including soil inorganic C accumulation, photochemical and thermal degradation, and wind erosion. We also discuss how climate and land-use changes could alter the grassland C balance by modifying the water budget, nutrient cycling and additional plant and soil processes. Further, we examine why and how increasing aridity and improper land use may induce significant losses in grassland C stocks. Finally, we identify several priorities for future grassland C research, including improving understanding of abiotic processes in the grassland C cycle, strengthening monitoring of grassland C dynamics by integrating ground inventory, flux monitoring, and modern remote sensing techniques, and selecting appropriate plant species combinations with suitable traits and strong resistance to climate fluctuations, which would help design sustainable grassland restoration strategies in a changing climate.

Work stress, mental health, and employee performance.

The COVID-19 pandemic outbreak-as a typical emergency event-significantly has impacted employees' psychological status and thus has negatively affected their performance. Hence, along with focusing on the mechanisms and solutions to alleviate the impact of work stress on employee performance, we also examine the relationship between work stress, mental health, and employee performance. Furthermore, we analyzed the moderating role of servant leadership in the relationship between work stress and mental health, but the result was not significant. The results contribute to providing practical guidance for enterprises to improve employee performance in the context of major emergencies.

Antitumor effects of new glycoconjugated PtII agents dual-targeting GLUT1 and Pgp proteins.

A novel and highly efficient dual-targeting PtII system was designed to improve the drug delivery capacity and selectivity in cancer treatment. The dual-targeting monofunctional PtII complexes (1-8) having glycosylated pendants as tridentated ligand were achieved by introducing glycosylation modification in the thioaminocarbazone compounds with potential lysosomal targeting ability. The structures and stability of 1-8 were further established by various techniques. Molecular docking studies showed that 2 was efficiently docked into glucose transporters protein 1 (GLUT1) and P-glycoprotein (Pgp) proteins with the optimal CDocker-interaction-energy of -64.84 and -48.85 kcal mol-1. Complex 2 with higher protein binding capacity demonstrated significant and broad-spectrum antitumor efficacy in vitro, even exhibiting a half maximal inhibitory concentration (IC50) value (∼10 µM) than cisplatin (∼17 µM) against human lung adenocarcinoma cells (A549). The inhibitor experiment revealed GLUT-mediated uptake of 2, and the subcellular localization experiment in A549 also proved that 2 could be localized in the lysosome, thereby causing cell apoptosis. Moreover, cellular thermal shift assay (CETSA) confirmed the binding of 2 with the target proteins of GLUT1 and Pgp. The above results indicated that 2 represents a potential anticancer candidate with dual-targeting functions.

Childhood asthma and type 1 diabetes mellitus: A meta-analysis and bidirectional Mendelian randomization study.

BACKGROUND: Worldwide incidence and prevalence of both asthma and type 1 diabetes mellitus (T1DM) in children have been increasing in past decades. Association between the two diseases has been found in some but not in other studies. OBJECTIVE: We conducted a meta-analysis to verify such an association, and bidirectional Mendelian randomization analysis to examine the potential cause-effect relationships. METHODS: Three databases (PubMed, Embase, and Web of Science) were searched from their inception to February 1, 2021. Pooled hazard ratios (HR) or odds ratios (OR), and 95% confidence intervals, were calculated. Associations between single-nucleotide polymorphisms with childhood asthma and T1DM were selected based on genome-wide association studies. The outcome datasets were obtained from FinnGen study. We used the inverse-variance-weighted (IVW), weighted median and MR-Egger methods to estimate causal effects. To assess robustness and horizontal pleiotropy, MR-Egger regression and MR pleiotropy residual sum and outlier test were conducted. RESULTS: In meta-analysis, childhood asthma was associated with an increased risk of T1DM (HR = 1.30, 95% CI 1.05-1.61, P = .014), whereas T1DM was not associated with the risk of asthma (HR = 0.98, 95% CI 0.64-1.51, P = .941; OR = 0.84, 95% CI 0.65-1.08, P = .168). MR analysis indicated increased genetic risk of T1DM in children with asthma (OR = 1.308; 95% CI 1.030-1.661; P = .028). Analysis using the IVW method indicated no association between T1DM and genetic risk of asthma (OR = 1.027, 95%CI 0.970-1.089, P = .358). CONCLUSION: Both meta-analysis and MR study suggested that childhood asthma was a risk factor for T1DM. No epidemiological or genetic evidence was found for an association of T1DM with asthma incidence. Further studies could be carried out to leverage this newfound insight into better clinical and experimental research in asthma and T1DM.

Partitioning of beta-diversity reveals distinct assembly mechanisms of plant and soil microbial communities in response to nitrogen enrichment.

Nitrogen (N) deposition poses a serious threat to terrestrial biodiversity and alters plant and soil microbial community composition. Species turnover and nestedness reflect the underlying mechanisms of variations in community composition. However, it remains unclear how species turnover and nestedness contribute to different responses of taxonomic groups (plants and soil microbes) to N enrichment. Here, based on a 13-year consecutive multi-level N addition experiment in a semiarid steppe, we partitioned community ß-diversity into species turnover and nestedness components and explored how and why plant and microbial communities reorganize via these two processes following N enrichment. We found that plant, soil bacterial, and fungal ß-diversity increased, but their two components showed different patterns with increasing N input. Plant ß-diversity was mainly driven by species turnover under lower N input but by nestedness under higher N input, which may be due to a reduction in forb species, with low tolerance to soil Mn2+, with increasing N input. However, turnover was the main contributor to differences in soil bacterial and fungal communities with increasing N input, indicating the phenomenon of microbial taxa replacement. The turnover of bacteria increased greatly whereas that of fungi remained within a narrow range with increasing N input. We further found that the increased soil Mn2+ concentration was the best predictor for increasing nestedness of plant communities under higher N input, whereas increasing N availability and acidification together contributed to the turnover of bacterial communities. However, environmental factors could explain neither fungal turnover nor nestedness. Our findings reflect two different pathways of community changes in plants, soil bacteria, and fungi, as well as their distinct community assembly in response to N enrichment. Disentangling the turnover and nestedness of plant and microbial ß-diversity would have important implications for understanding plant-soil microbe interactions and seeking conservation strategies for maintaining regional diversity.

Performance Evaluation and Mechanism Study of Seawater-Based Circulatory Fracturing Fluid Based on pH-Regulated WormLike Micelles.

In this article, a novel salt-resistant pH-sensitive surfactant N-carboxystearamido methanesulfonic acid (MSA) was designed and synthesized. The rheological properties of the MSA/CTAB mixed system prepared using seawater were evaluated, and the variation laws of the related rheological parameters were discussed. The relevant fracturing technical parameters of the MSA/CTAB mixed system were comprehensively evaluated. The wormlike micelles formed by the non-covalent binding of MSA and CTAB molecules can resist the electrostatic effect of inorganic salts in the seawater. Meanwhile, the MSA/CTAB mixed system has an excellent pH response and revealed that the change from wormlike micelles to spherical micelles leads to the decrease of the apparent viscosity and the transition from Maxwell fluid to Newton-type fluid. Furthermore, the MSA/CTAB mixed system has excellent cyclic fracturing performance, which can meet the dual requirements of fracturing fluid cost and performance of offshore oilfield, and has a good application prospect.

Deepened snow loosens temporal coupling between plant and microbial N utilization and induces ecosystem N losses.

Seasonal differences in plant and microbial nitrogen (N) acquisition are believed to be a major mechanism that maximizes ecosystem N retention. There is also a concern that climate change may interrupt the delicate balance in N allocation between plants and microbes. Yet, convincing experimental evidence is still lacking. Using a 15 N tracer, we assessed how deepened snow affects the temporal coupling between plant and microbial N utilization in a temperate Mongolian grassland. We found that microbial 15 N recovery peaked in winter, accounting for 22% of the total ecosystem 15 N recovery, and then rapidly declined during the spring thaw. By stimulating N loss via N2 O emission and leaching, deepened snow reduced the total ecosystem 15 N recovery by 42% during the spring thaw. As the growing season progresses, the 15 N released from microbial biomass was taken up by plants, and the competitive advantage for N shifted from microbes to plants. Plant 15 N recovery reached its peak in August, accounting for 17% of the total ecosystem 15 N recovery. The Granger causality test showed that the temporal dynamics of plant 15 N recovery can be predicted by microbial 15 N recovery under ambient snow but not under deepened snow. In addition, plant 15 N recovery in August was positively correlated with and best explained by microbial 15 N recovery in March. The lower microbial 15 N recovery under deepened snow in March reduced plant 15 N recovery by 73% in August. Together, our results provide direct evidence of seasonal differences in plant and microbial N utilization that are conducive to ecosystem N retention; however, deepened snow disrupted the temporal coupling between plant-microbial N use and turnover. These findings suggest that changes in snowfall patterns may significantly alter ecosystem N cycling and N-based greenhouse gas emissions under future climate change. We highlight the importance of better representing winter processes and their response to winter climate change in biogeochemical models when assessing N cycling under global change.

A Model Study on Raw Material Chemical Composition to Predict Sinter Quality Based on GA-RNN.

The quality control process for sintered ore is cumbersome and time- and money-consuming. When the assay results come out and the ratios are found to be faulty, the ratios cannot be changed in time, which will produce sintered ore of substandard quality, resulting in a waste of resources and environmental pollution. For the problem of lagging sinter detection results, Long Short-Term Memory and Genetic Algorithm-Recurrent Neural Networks prediction algorithms were used for comparative analysis, and the article used GA-RNN quality prediction model for prediction. Through correlation analysis, the chemical composition of the sintered raw material was determined as the input parameter and the physical and metallurgical properties of the sintered ore were determined as the output parameters, thus successfully establishing a GA-RNN-based sinter quality prediction model. Based on 150 sets of original data, 105 sets of data were selected as the training sample set and 45 sets of data were selected as the test sample set. The results obtained were compared to the real value with an average prediction error of 1.24% for the drum index, 0.92% for the low-temperature reduction chalking index (RDI), 0.95% for the reduction index (RI), 0.40% for the load softening temperature T10%, and 0.43% for the load softening temperature T40%, with all within the running time thresholds. The study of this model enables the prediction of the quality of sintered ore prior to sintering, thus improving the yield of sintered ore, increasing corporate efficiency, saving energy, and reducing environmental pollution.

Association between depression and sleep apnoea: a Mendelian randomisation study.

BACKGROUND: Studies have reported a close relationship between depression and sleep apnoea, yet it is unknown whether these are causally related. Thus, we aimed to determine whether depression is associated with the aetiology of sleep apnoea. METHODS: We used publicly available genetic summary data from two large consortia: the Psychiatric Genomics Consortium, with data from 36 single-nucleotide polymorphisms (SNPs) closely associated with major depressive disorder (MDD), and the UK Biobank, including 456 736 patients with sleep apnoea and 766 964 controls. For Mendelian randomisation (MR) analysis, we used the inverse-variance weighted method, weighted median method, MR-Egger regression, MR pleiotropy residual sum and outlier test to retrieve summary data. Analyses were performed using the "TwoSampleMR" package in R. RESULTS: Out of the 36 SNPs associated with MDD, we found statistically significant evidence of a potential causal effect of MDD on the risk of sleep apnoea (OR 1.004, 95% CI 1.001-1.006; p=0.001). Similar results were obtained using the MR-Egger and weighted median methods. Additionally, we found no heterogeneity or pleiotropy. CONCLUSIONS: Our findings suggest that depression slightly increases the risk of sleep apnoea. Further investigation of the potential biological mechanisms is necessary.