Prediction and Structure–Activity Relationship Analysis on Ready Biodegradability of Chemical Using Machine Learning Method

Persistent contaminants from different industries have already caused significant risks to the environment and public health. In this study, a data set containing 1306 not readily biodegradable (NRB) and 622 readily biodegradable (RB) chemicals was collected and characterized by CORINA descriptors, MACCS fingerprints, and ECFP_4 fingerprints. We utilized decision tree (DT), support vector machine (SVM), random forest (RF), and deep neural network (DNN) to construct 34 classification models that could predict the biodegradability of compounds. The best model (model 5F) built using a Transformer-CNN algorithm had a balanced accuracy of 86.29% and a Matthews correlation coefficient of 0.71 on the test set. By analyzing the top 10 CORINA descriptors used for modeling, the properties containing solubility, π/σ atom charges, rotatable bonds number, lone pair/π/σ atom electronegativities, molecular weight, and number of nitrogen atom based hydrogen bonding acceptors were determined to be critical for biodegradability. The substructure investigations confirmed earlier studies that the presence of aromatic rings and nitrogen or halogen substitutions in a molecule will hinder the biodegradation of the compound, while the ester groups and carboxyl groups promote biodegradability. We also identified the representative fragments affecting biodegradability by analyzing the frequency differences of substructural fragments between the NRB and RB compounds. The results of the study can provide excellent guidance for the discovery and design of compounds with good chemical biodegradability

Additional file 4: of Revealing the dominant long noncoding RNAs responding to the infection with Colletotrichum gloeosporioides in Hevea brasiliensis

Figure S3. The relative expressions by real-time quantitative reverse transcription PCR (qRT-PCR) in re-sampled non-inoculated control (CK) and inoculated samples (INF) of (A) lncRNA11254, (B) lncRNA11041 and (C) lncRNA11205. Values were presented as the mean ± SE of three independent experiments and * indicated significant differences. (P < 0.05) (PDF 15 kb

Image1_Functional inference of long non-coding RNAs through exploration of highly conserved regions.JPEG

Background: Long non-coding RNAs (lncRNAs), which are generally less functionally characterized or less annotated, evolve more rapidly than mRNAs and substantially possess fewer sequence conservation patterns than protein-coding genes across divergent species. People assume that the functional inference could be conducted on the evolutionarily conserved long non-coding RNAs as they are most likely to be functional. In the past decades, substantial progress has been made in discussions on the evolutionary conservation of non-coding genomic regions from multiple perspectives. However, understanding their conservation and the functions associated with sequence conservation in relation to further corresponding phenotypic variability or disorders still remains incomplete.Results: Accordingly, we determined a highly conserved region (HCR) to verify the sequence conservation among long non-coding RNAs and systematically profiled homologous long non-coding RNA clusters in humans and mice based on the detection of highly conserved regions. Moreover, according to homolog clustering, we explored the potential function inference via highly conserved regions on representative long non-coding RNAs. On lncRNA XACT, we investigated the potential functional competence between XACT and lncRNA XIST by recruiting miRNA-29a, regulating the downstream target genes. In addition, on lncRNA LINC00461, we examined the interaction relationship between LINC00461 and SND1. This interaction or association may be perturbed during the progression of glioma. In addition, we have constructed a website with user-friendly web interfaces for searching, analyzing, and downloading to present the homologous clusters of humans and mice.Conclusion: Collectively, homolog clustering via the highly conserved region definition and detection on long non-coding RNAs, as well as the functional explorations on representative sequences in our research, would provide new evidence for the potential function of long non-coding RNAs. Our results on the remarkable roles of long non-coding RNAs would presumably provide a new theoretical basis and candidate diagnostic indicators for tumors.</p

Study on essential drug use status and its influencing factors among cerebral infarction inpatients in county level hospitals of Anhui Province, China

<div><p>Background and purpose</p><p>Drug costs is one of the main components of hospitalization expenditure for cerebral infarction inpatients. In China, the National Essential Medicine System (NEMS) was created to relieve the heavy drug-cost burden for patients. The objective of this study was to investigate essential drug-use status and its influencing factors among cerebral infarction inpatients in county-level hospitals of Anhui province, China.</p><p>Methods</p><p>Three county-level hospitals were selected through a multi-stage cluster random sampling method. The hospitalization cost data of cerebral infarction inpatients in the three hospitals were extracted from the Anhui provincial information platform of the New Rural Cooperative Insurance System (NCMS), and whether the proportion of essential drug cost in the total drug cost reached the median value of 33.05% which was set as the evaluation index for essential drug-use status. Questionnaires for hospitals and physicians were designed and given to them to assess influencing factors.</p><p>Results</p><p>We retrieved the cost data of 2,189 inpatients from the NCMS platform and investigated 51 corresponding physicians in total. The drug costs accounted for 52.6% of the total hospitalization cost, and essential drug costs alone accounted for 37.0% of the total drug costs. The essential drug-cost proportion was high among physicians with a higher recognition degree on NEMS, older age, lower final academic degree, longer work experience and lower professional title. Married physicians and those with tight organizational affiliation also prescribed more essential drugs.</p><p>Conclusions</p><p>Increasing the proportion of essential drugs was an effective way to reduce the disease burden for cerebral infarction patients. Perfecting the NEMS, increasing government investment, reinforcing education and propaganda, and formulating relevant incentive and restrictive mechanisms were all effective ways to promote and increase the number of essential drug prescriptions written by physicians.</p></div

Image2_Functional inference of long non-coding RNAs through exploration of highly conserved regions.JPEG

Background: Long non-coding RNAs (lncRNAs), which are generally less functionally characterized or less annotated, evolve more rapidly than mRNAs and substantially possess fewer sequence conservation patterns than protein-coding genes across divergent species. People assume that the functional inference could be conducted on the evolutionarily conserved long non-coding RNAs as they are most likely to be functional. In the past decades, substantial progress has been made in discussions on the evolutionary conservation of non-coding genomic regions from multiple perspectives. However, understanding their conservation and the functions associated with sequence conservation in relation to further corresponding phenotypic variability or disorders still remains incomplete.Results: Accordingly, we determined a highly conserved region (HCR) to verify the sequence conservation among long non-coding RNAs and systematically profiled homologous long non-coding RNA clusters in humans and mice based on the detection of highly conserved regions. Moreover, according to homolog clustering, we explored the potential function inference via highly conserved regions on representative long non-coding RNAs. On lncRNA XACT, we investigated the potential functional competence between XACT and lncRNA XIST by recruiting miRNA-29a, regulating the downstream target genes. In addition, on lncRNA LINC00461, we examined the interaction relationship between LINC00461 and SND1. This interaction or association may be perturbed during the progression of glioma. In addition, we have constructed a website with user-friendly web interfaces for searching, analyzing, and downloading to present the homologous clusters of humans and mice.Conclusion: Collectively, homolog clustering via the highly conserved region definition and detection on long non-coding RNAs, as well as the functional explorations on representative sequences in our research, would provide new evidence for the potential function of long non-coding RNAs. Our results on the remarkable roles of long non-coding RNAs would presumably provide a new theoretical basis and candidate diagnostic indicators for tumors.</p

Hospitalization cost (USD) data for the 2,189 cerebral infarction patients.

Hospitalization cost (USD) data for the 2,189 cerebral infarction patients.</p

Additional file 5: of Revealing the dominant long noncoding RNAs responding to the infection with Colletotrichum gloeosporioides in Hevea brasiliensis

Figure S4. The relative expressions of miRNAs in rubber tree mesophyll protoplasts. (A) The relative expressions of miRNA397 in rubber tree mesophyll protoplasts overexpressing lncRNA11041 (lnc11041+) and control (ctl). (B) The relative expressions of miRNA395 in rubber tree mesophyll protoplasts overexpressing lncRNA11205 (lnc11205+) and control. (PDF 12 kb

Multifactor analysis of the elements that affected essential drug cost proportion.

<p>Multifactor analysis of the elements that affected essential drug cost proportion.</p

General and relevant business data of the three hospitals in 2015.

<p>General and relevant business data of the three hospitals in 2015.</p

Additional file 2: of Revealing the dominant long noncoding RNAs responding to the infection with Colletotrichum gloeosporioides in Hevea brasiliensis

Figure S1. Density plot for average expressions of coding transcripts and ncRNAs in control group samples (Methods). (JPG 9 kb