Trophic Transfer and Toxic Potency of Rare Earth Elements along a Terrestrial Plant-Herbivore Food Chain.

Extensive rare earth element (REE) mining activities have caused REE contamination of ambient agricultural soils, posing threats to associated food webs. Here, a simulated lettuce-snail food chain was conducted to evaluate the trophic transfer characteristics and the consequent effects of REEs on consumers. After 50-day exposure to soil, lettuce roots dose-dependently accumulated 9.4-76 mg kg-1 REEs and translocated 3.7-20 mg kg-1 REEs to shoots. Snails feeding on REE-contaminated shoots accumulated 3.0-6.7 mg kg-1 REEs with trophic transfer factors of 0.20-0.98, indicating trophic dilution in the lettuce-snail system. REE profiles in lettuce and snails indicated light REE (LREE) enrichment only in snails and the varied REE profiles along the food chain. This was corroborated by toxicokinetics. Estimated uptake (Ku) and elimination (Ke) parameters were 0.010-2.9 kgshoot kgsnail-1 day-1 and 0.010-1.8 day-1, respectively, with higher Ku values for LREE and HREE. The relatively high Ke, compared to Ku, indicating a fast REE elimination, supports the trophic dilution. Dietary exposure to REEs dose-dependently affected gut microbiota and metabolites in snails. These effects are mainly related to oxidative damage and energy expenditure, which are further substantiated by targeted analysis. Our study provides essential information about REE bioaccumulation characteristics and its associated risks to terrestrial food chains near REE mining areas.

An Intelligent DNA Nanoreactor for Easy-to-Read In Vivo Tumor Imaging and Precise Therapy.

Nanomaterial-based in vivo tumor imaging and therapy have attracted extensive attention; however, they suffer from the unintelligent "always ON" or single-parameter responsive signal output, substantial off-target effects, and high cost. Therefore, achieving in vivo easy-to-read tumor imaging and precise therapy in a multi-parameter responsive and intelligent manner remains challenging. Herein, an intelligent DNA nanoreactor (iDNR) was constructed following the "AND" Boolean logic algorithm to address these issues. iDNR-mediated in situ deposition of photothermal substance polydopamine (PDA) can only be satisfied in tumor tissues with abundant membrane protein biomarkers "AND" hydrogen peroxide (H2 O2 ). Therefore, intelligent temperature-based in vivo easy-to-read tumor imaging is realized without expensive instrumentation, and its diagnostic performance matches with that of flow cytometry, and photoacoustic imaging. Moreover, precise photothermal therapy (PTT) of tumors could be achieved via intelligent heating of tumor tissues. The precise PTT of primary tumors in combination with immune checkpoint blockade (ICB) therapy suppresses the growth of distant tumors and inhibits tumor recurrence. Therefore, highly programmable iDNR is a powerful tool for intelligent biomedical applications.

Screening of key functional components of Taohong Siwu Decoction on ischemic stroke treatment based on multiobjective optimization approach and experimental validation.

BACKGROUND: Taohong Siwu Decoction (THSWD) is a widely used traditional Chinese medicine (TCM) prescription in the treatment of ischemic stroke. There are thousands of chemical components in THSWD. However, the key functional components are still poorly understood. This study aimed to construct a mathematical model for screening of active ingredients in TCM prescriptions and apply it to THSWD on ischemic stroke. METHODS: Botanical drugs and compounds in THSWD were acquired from multiple public TCM databases. All compounds were initially screened by ADMET properties. SEA, HitPick, and Swiss Target Prediction were used for target prediction of the filtered compounds. Ischemic stroke pathological genes were acquired from the DisGeNet database. The compound-target-pathogenic gene (C-T-P) network of THSWD was constructed and then optimized using the multiobjective optimization (MOO) algorithm. We calculated the cumulative target coverage score of each compound and screened the top compounds with 90% coverage. Finally, verification of the neuroprotective effect of these compounds was performed with the oxygen-glucose deprivation and reoxygenation (OGD/R) model. RESULTS: The optimized C-T-P network contains 167 compounds, 1,467 predicted targets, and 1,758 stroke pathological genes. And the MOO model showed better optimization performance than the degree model, closeness model, and betweenness model. Then, we calculated the cumulative target coverage score of the above compounds, and the cumulative effect of 39 compounds on pathogenic genes reached 90% of all compounds. Furthermore, the experimental results showed that decanoic acid, butylphthalide, chrysophanol, and sinapic acid significantly increased cell viability. Finally, the docking results showed the binding modes of these four compounds and their target proteins. CONCLUSION: This study provides a methodological reference for the screening of potential therapeutic compounds of TCM. In addition, decanoic acid and sinapic acid screened from THSWD were found having potential neuroprotective effects first and verified with cell experiments, however, further in vitro and in vivo studies are needed to explore the precise mechanisms involved.

Differential Evolution Optimization of Microwave Focused Hyperthermia Phased Array Excitation for Targeted Breast Cancer Heating.

Microwave hyperthermia using the phased array applicator is a non-invasive treatment modality for breast cancer. Hyperthermia treatment planning (HTP) is critical to accurately treating breast cancer and avoiding damage to the patient's healthy tissue. A global optimization algorithm, differential evolution (DE) algorithm, has been applied to optimize HTP for breast cancer and its ability to improve the treatment effect was proved by electromagnetic (EM) and thermal simulation results. DE algorithm is compared to time reversal (TR) technology, particle swarm optimization (PSO) algorithm, and genetic algorithm (GA) in HTP for breast cancer in terms of convergence rate and treatment results, such as treatment indicators and temperature parameters. The current approaches in breast cancer microwave hyperthermia still have the problem of hotspots in healthy tissue. DE enhances focused microwave energy absorption into the tumor and reduces the relative energy of healthy tissue during hyperthermia treatment. By comparing the treatment results of each objective function used in DE, the DE algorithm with hotspot to target quotient (HTQ) as the objective function has outstanding performance in HTP for breast cancer, which can increase the focused microwave energy of the tumor and decrease the damage to healthy tissue.

Design of Ultra-Wideband Phased Array Applicator for Breast Cancer Hyperthermia Therapy.

Focused microwave-hyperthermia therapy has recently emerged as a key technology in the treatment of breast cancer due to non-invasive treatment. An applicator of a three-ring phased array consisting of ultra-wideband (UWB) microstrip antennas was designed for breast cancer therapy and operates at 0.915 GHz and 2.45 GHz. The proposed antenna has an ultra-wideband from 0.7 GHz to 5.5 GHz with resonant frequencies of 0.915 GHz and 2.45 GHz and dimensions of 15 × 43.5 × 1.575 mm3. The number of each ring was chosen to be 12 based on the SAR distribution and the performance indicators of tumor off-center focusing results for four different numbers of single-ring arrays. The homogeneous breast model is applied to a three-ring phased array consisting of 36 elements for focused simulation, and 1 cm3 and 2 cm3 tumors are placed in three different locations in the breast. The simulation results show that the proposed phased array has good performance and the capability to raise the temperature of different volumes of breast cancer above 42.5 °C after choosing a suitable operating frequency. The proposed applicator allows for precise treatment of tumors by selecting the appropriate operating frequency based on the size of the malignant tumor.

Elucidating the Synergistic Effect of Multiple Chinese Herbal Prescriptions in the Treatment of Post-stroke Neurological Damage.

Background: Traditional Chinese medicine (TCM) has been widely used in the treatment of human diseases. However, the synergistic effects of multiple TCM prescriptions in the treatment of stroke have not been thoroughly studied. Objective of the study: This study aimed to reveal the mechanisms underlying the synergistic effects of these TCM prescriptions in stroke treatment and identify the active compounds. Methods: Herbs and compounds in the Di-Tan Decoction (DTD), Xue-Fu Zhu-Yu Decoction (XFZYD), and Xiao-Xu-Ming Decoction (XXMD) were acquired from the TCMSP database. SEA, HitPick, and TargetNet web servers were used for target prediction. The compound-target (C-T) networks of three prescriptions were constructed and then filtered using the collaborative filtering algorithm. We combined KEGG enrichment analysis, molecular docking, and network analysis approaches to identify active compounds, followed by verification of these compounds with an oxygen-glucose deprivation and reoxygenation (OGD/R) model. Results: The filtered DTD network contained 39 compounds and 534 targets, the filtered XFZYD network contained 40 compounds and 508 targets, and the filtered XXMD network contained 55 compounds and 599 targets. The filtered C-T networks retained approximately 80% of the biological functions of the original networks. Based on the enriched pathways, molecular docking, and network analysis results, we constructed a complex network containing 3 prescriptions, 14 botanical drugs, 26 compounds, 13 targets, and 5 pathways. By calculating the synergy score, we identified the top 5 candidate compounds. The experimental results showed that quercetin, baicalin, and ginsenoside Rg1 independently and synergistically increased cell viability. Conclusion: By integrating pharmacological and chemoinformatic approaches, our study provides a new method for identifying the effective synergistic compounds of TCM prescriptions. The filtered compounds and their synergistic effects on stroke require further research.

Intensive phototherapy vs. exchange transfusion for the treatment of neonatal hyperbilirubinemia: a multicenter retrospective cohort study.

BACKGROUND: Intensive phototherapy (IPT) and exchange transfusion (ET) are the main treatments for extreme hyperbilirubinemia. However, there is no reliable evidence on determining the thresholds for these treatments. This multicenter study compared the effectiveness and complications of IPT and ET in the treatment of extreme hyperbilirubinemia. METHODS: This retrospective cohort study was conducted in seven centers from January 2015 to January 2018. Patients with extreme hyperbilirubinemia that met the criteria of ET were included. Patients were divided into three subgroups (low-, medium-, and high- risk) according to gestational week and risk factors. Propensity score matching (PSM) was performed to balance the data before treatment. Study outcomes included the development of bilirubin encephalopathy, duration of hospitalization, expenses, and complications. Mortality, auditory complications, seizures, enamel dysplasia, ocular motility disorders, athetosis, motor, and language development were evaluated during follow-up at age of 3 years. RESULTS: A total of 1164 patients were included in this study. After PSM, 296 patients in the IPT only group and 296 patients in the IPT plus ET group were further divided into the low-, medium-, and high-risk subgroups with 188, 364, and 40 matched patients, respectively. No significant differences were found between the IPT only and IPT plus ET groups in terms of morbidity, complications, and sequelae. Hospitalization duration and expenses were lower in the low- and medium-risk subgroups in the IPT only group. CONCLUSIONS: In this study, our results suggest that IPT is a safe and effective treatment for extreme hyperbilirubinemia. The indication of ET for patients with hyperbilirubinemia could be stricter. However, it is necessary to have a contingency plan for emergency ET as soon as IPT is commenced especially for infants with risk factors. If IPT can be guaranteed and proved to be therapeutic, ET should be avoided as much as possible.

Commonwealth of Soil Health: How Do Earthworms Modify the Soil Microbial Responses to CeO2 Nanoparticles?

Soil ecotoxicological assays on nanoparticles (NPs) have mainly investigated single components (e.g., plants, fauna, and microbes) within the ecosystem, neglecting possible effects resulting from the disturbance of the interactions between these components. Here, we investigated soil microbial responses to CeO2 NPs in the presence and absence of earthworms from the perspectives of microbial functions (i.e., enzyme activities), the community structure, and soil metabolite profiles. Exposure to CeO2 NPs (50, 500 mg/kg) alone decreased the activities of enzymes (i.e., acid protease and acid phosphatase) participating in soil N and P cycles, while the presence of earthworms ameliorated these inhibitory effects. After the CeO2 NP exposure, the earthworms significantly altered the relative abundance of some microbes associated with the soil N and P cycles (Flavobacterium, Pedobacter, Streptomyces, Bacillus, Bacteroidota, Actinobacteria, and Firmicutes). This was consistent with the pattern found in the significantly changed metabolites which were also involved in the microbial N and P metabolism. Both CeO2 NPs and earthworms changed the soil bacterial community and soil metabolite profiles. Larger alterations of soil bacteria and metabolites were found under CeO2 NP exposure with earthworms. Overall, our study indicates that the top-down control of earthworms can drastically modify the microbial responses to CeO2 NPs from all studied biological aspects. This clearly shows the importance of the holistic consideration of all soil ecological components to assess the environmental risks of NPs to soil health.

A strategy to find novel candidate anti-Alzheimer's disease drugs by constructing interaction networks between drug targets and natural compounds in medical plants.

BACKGROUND: Alzheimer' disease (AD) is an ultimately fatal degenerative brain disorder that has an increasingly large burden on health and social care systems. There are only five drugs for AD on the market, and no new effective medicines have been discovered for many years. Chinese medicinal plants have been used to treat diseases for thousands of years, and screening herbal remedies is a way to develop new drugs. METHODS: We used molecular docking to screen 30,438 compounds from Traditional Chinese Medicine (TCM) against a comprehensive list of AD target proteins. TCM compounds in the top 0.5% of binding affinity scores for each target protein were selected as our research objects. Structural similarities between existing drugs from DrugBank database and selected TCM compounds as well as the druggability of our candidate compounds were studied. Finally, we searched the CNKI database to obtain studies on anti-AD Chinese plants from 2007 to 2017, and only clinical studies were included. RESULTS: A total of 1,476 compounds (top 0.5%) were selected as drug candidates. Most of these compounds are abundantly found in plants used for treating AD in China, especially the plants from two genera Panax and Morus. We classified the compounds by single target and multiple targets and analyzed the interactions between target proteins and compounds. Analysis of structural similarity revealed that 17 candidate anti-AD compounds were structurally identical to 14 existing approved drugs. Most of them have been reported to have a positive effect in AD. After filtering for compound druggability, we identified 11 anti-AD compounds with favorable properties, seven of which are found in anti-AD Chinese plants. Of 11 anti-AD compounds, four compounds 5,862, 5,863, 5,868, 5,869 have anti-inflammatory activity. The compound 28,814 mainly has immunoregulatory activity. The other six compounds have not yet been reported for any biology activity at present. DISCUSSION: Natural compounds from TCM provide a broad prospect for the screening of anti-AD drugs. In this work, we established networks to systematically study the connections among natural compounds, approved drugs, TCM plants and AD target proteins with the goal of identifying promising drug candidates. We hope that our study will facilitate in-depth research for the treatment of AD in Chinese medicine.

The identification and molecular mechanism of anti-stroke traditional Chinese medicinal compounds.

Stroke is a worldwide epidemic disease with high morbidity and mortality. The continuously exploration of anti-stroke medicines and molecular mechanism has a long way to go. In this study, in order to screen candidate anti-stroke compounds, more than 60000 compounds from traditional Chinese medicine (TCM) database were computationally analyzed then docked to the 15 known anti-stroke targets. 192 anti-stroke plants for clinical therapy and 51 current anti-stroke drugs were used to validate docking results. Totally 2355 candidate anti-stroke compounds were obtained. Among these compounds, 19 compounds are structurally identical with 16 existing drugs in which part of them have been used for anti-stroke treatment. Furthermore, these candidate compounds were significantly enriched in anti-stroke plants. Based on the above results, the compound-target-plant network was constructed. The network reveals the potential molecular mechanism of anti-stroke for these compounds. Most of candidate compounds and anti-stroke plants are tended to interact with target NOS3, PSD-95 and PDE5A. Finally, using ADMET filter, we identified 35 anti-stroke compounds with favorable properties. The 35 candidate anti-stroke compounds offer an opportunity to develop new anti-stroke drugs and will improve the research on molecular mechanism of anti-stroke.

In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database.

There is a constant demand to develop new, effective, and affordable anti-cancer drugs. The traditional Chinese medicine (TCM) is a valuable and alternative resource for identifying novel anti-cancer agents. In this study, we aim to identify the anti-cancer compounds and plants from the TCM database by using cheminformatics. We first predicted 5278 anti-cancer compounds from TCM database. The top 346 compounds were highly potent active in the 60 cell lines test. Similarity analysis revealed that 75% of the 5278 compounds are highly similar to the approved anti-cancer drugs. Based on the predicted anti-cancer compounds, we identified 57 anti-cancer plants by activity enrichment. The identified plants are widely distributed in 46 genera and 28 families, which broadens the scope of the anti-cancer drug screening. Finally, we constructed a network of predicted anti-cancer plants and approved drugs based on the above results. The network highlighted the supportive role of the predicted plant in the development of anti-cancer drug and suggested different molecular anti-cancer mechanisms of the plants. Our study suggests that the predicted compounds and plants from TCM database offer an attractive starting point and a broader scope to mine for potential anti-cancer agents.