Risk factors and predictive model of cerebral edema after road traffic accidents-related traumatic brain injury.

PURPOSE: Cerebral edema (CE) is the main secondary injury following traumatic brain injury (TBI) caused by road traffic accidents (RTAs). It is challenging to be predicted timely. In this study, we aimed to develop a prediction model for CE by identifying its risk factors and comparing the timing of edema occurrence in TBI patients with varying levels of injuries. METHODS: This case-control study included 218 patients with TBI caused by RTAs. The cohort was divided into CE and non-CE groups, according to CT results within 7 days. Demographic data, imaging data, and clinical data were collected and analyzed. Quantitative variables that follow normal distribution were presented as mean ± standard deviation, those that do not follow normal distribution were presented as median (Q1, Q3). Categorical variables were expressed as percentages. The Chi-square test and logistic regression analysis were used to identify risk factors for CE. Logistic curve fitting was performed to predict the time to secondary CE in TBI patients with different levels of injuries. The efficacy of the model was evaluated using the receiver operator characteristic curve. RESULTS: According to the study, almost half (47.3%) of the patients were found to have CE. The risk factors associated with CE were bilateral frontal lobe contusion, unilateral frontal lobe contusion, cerebral contusion, subarachnoid hemorrhage, and abbreviated injury scale (AIS). The odds ratio values for these factors were 7.27 (95% confidence interval (CI): 2.08 - 25.42, p = 0.002), 2.85 (95% CI: 1.11 - 7.31, p = 0.030), 2.62 (95% CI: 1.12 - 6.13, p = 0.027), 2.44 (95% CI: 1.25 - 4.76, p = 0.009), and 1.5 (95% CI: 1.10 - 2.04, p = 0.009), respectively. We also observed that patients with mild/moderate TBI (AIS ≤ 3) had a 50% probability of developing CE 19.7 h after injury (χ2 = 13.82, adjusted R2 = 0.51), while patients with severe TBI (AIS > 3) developed CE after 12.5 h (χ2 = 18.48, adjusted R2 = 0.54). Finally, we conducted a receiver operator characteristic curve analysis of CE time, which showed an area under the curve of 0.744 and 0.672 for severe and mild/moderate TBI, respectively. CONCLUSION: Our study found that the onset of CE in individuals with TBI resulting from RTAs was correlated with the severity of the injury. Specifically, those with more severe injuries experienced an earlier onset of CE. These findings suggest that there is a critical time window for clinical intervention in cases of CE secondary to TBI.

Blast injuries with contrasting outcomes treated by military surgery strategies: A case report.

The treatment strategy for blast injuries is closely linked to the clinical outcome of blast injury casualties. However, the application of military surgery experience to blast injuries caused by production safety accidents is relatively uncommon. In this study, the authors present 2 cases of blast injuries caused by one gas explosion, both cases involved individuals of the same age and gender and experienced similar degree of injury. The authors highlight the importance of using a military surgery treatment strategy, specifically emphasizing the need to understand the concept of damage control and disposal. It is recommended that relevant training in this area should be strengthened to improve the clinical treatment of such injuries. This study provides a valuable reference for healthcare professionals dealing with blast injuries.

Investigating neuropathological changes and underlying neurobiological mechanisms in the early stages of primary blast-induced traumatic brain injury: Insights from a rat model.

The utilization of explosives and chemicals has resulted in a rise in blast-induced traumatic brain injury (bTBI) in recent times. However, there is a dearth of diagnostic biomarkers and therapeutic targets for bTBI due to a limited understanding of biological mechanisms, particularly in the early stages. The objective of this study was to examine the early neuropathological characteristics and underlying biological mechanisms of primary bTBI. A total of 83 Sprague Dawley rats were employed, with their heads subjected to a blast shockwave of peak overpressure ranging from 172 to 421 kPa in the GI, GII, and GIII groups within a closed shock tube, while the body was shielded. Neuromotor dysfunctions, morphological changes, and neuropathological alterations were detected through modified neurologic severity scores, brain water content analysis, MRI scans, histological, TUNEL, and caspase-3 immunohistochemical staining. In addition, label-free quantitative (LFQ)-proteomics was utilized to investigate the biological mechanisms associated with the observed neuropathology. Notably, no evident damage was discernible in the GII and GI groups, whereas mild brain injury was observed in the GIII group. Neuropathological features of bTBI were characterized by morphologic changes, including neuronal injury and apoptosis, cerebral edema, and cerebrovascular injury in the shockwave's path. Subsequently, 3153 proteins were identified and quantified in the GIII group, with subsequent enriched neurological responses consistent with pathological findings. Further analysis revealed that signaling pathways such as relaxin signaling, hippo signaling, gap junction, chemokine signaling, and sphingolipid signaling, as well as hub proteins including Prkacb, Adcy5, and various G-protein subunits (Gnai2, Gnai3, Gnao1, Gnb1, Gnb2, Gnb4, and Gnb5), were closely associated with the observed neuropathology. The expression of hub proteins was confirmed via Western blotting. Accordingly, this study proposes signaling pathways and key proteins that exhibit sensitivity to brain injury and are correlated with the early pathologies of bTBI. Furthermore, it highlights the significance of G-protein subunits in bTBI pathophysiology, thereby establishing a theoretical foundation for early diagnosis and treatment strategies for primary bTBI.

Different acupuncture and moxibustion therapies for mild cognitive impairment: a network meta-analysis.

OBJECTIVE: To investigate the effectiveness of different acupuncture and moxibustion therapies in improving cognitive function in patients with mild cognitive impairment (MCI) to determine the optimal approach. This study aims to provide insights into the treatment of MCI patients for future randomized controlled trials (RCTs) and clinical decision-making. MATERIALS AND METHODS: RCT studies were retrieved from databases including PubMed, Embase, Cochrane Library, Web of Science, CNKI, WANFANG, VIP, and SinoMed. The Cochrane risk of bias tool was used to assess the risk of bias for eligible trials. Bayesian network meta-analysis was conducted using R4.2.3 software. RESULTS: A total of 46 RCTs with 3641 participants were included. The network meta-analysis showed that acupoint pressing + cognitive training + auricular point sticking, massage + western medicine treatment, and electroacupuncture + western medicine treatment ranked first, second, and third in improving MMSE score, respectively. Acupoint pressing + cognitive training, cognitive training + scalp acupuncture, and cognitive training + moxibustion ranked first, second, and third in improving MoCA score, respectively. CONCLUSION: This study showed that acupoint pressing alone or acupoint pressing + auricular point sticking may improve cognitive function in MCI patients and possibly be the most effective acupuncture interventions for the treatment of MCI.

Effects of different preservation on the mechanical properties of cortical bone under quasi-static and dynamic compression.

Introduction: Mechanical properties of biological tissue are important for numerical simulations. Preservative treatments are necessary for disinfection and long-term storage when conducting biomechanical experimentation on materials. However, few studies have been focused on the effect of preservation on the mechanical properties of bone in a wide strain rate. The purpose of this study was to evaluate the influence of formalin and dehydration on the intrinsic mechanical properties of cortical bone from quasi-static to dynamic compression. Methods: Cube specimens were prepared from pig femur and divided into three groups (fresh, formalin, and dehydration). All samples underwent static and dynamic compression at a strain rate from 10-3 s-1 to 103 s-1. The ultimate stress, ultimate strain, elastic modulus, and strain-rate sensitivity exponent were calculated. A one-way ANOVA test was performed to determine if the preservation method showed significant differences in mechanical properties under at different strain rates. The morphology of the macroscopic and microscopic structure of bones was observed. Results: The results show that ultimate stress and ultimate strain increased as the strain rate increased, while the elastic modulus decreased. Formalin fixation and dehydration did not affect elastic modulus significantly whereas significantly increased the ultimate strain and ultimate stress. The strain-rate sensitivity exponent was the highest in the fresh group, followed by the formalin group and dehydration group. Different fracture mechanisms were observed on the fractured surface, with fresh and preserved bone tending to fracture along the oblique direction, and dried bone tending to fracture along the axial direction. Discussion: In conclusion, preservation with both formalin and dehydration showed an influence on mechanical properties. The influence of the preservation method on material properties should be fully considered in developing a numerical simulation model, especially for high strain rate simulation.

Research on skeletal muscle impact injury using a new rat model from a bioimpact machine.

Introduction: Skeletal muscle impact injury occurs frequently during sports, falls, and road traffic accidents. From the reported studies on skeletal muscle injury, it is difficult to determine the injury parameters. Therefore, we developed a new model of gastrocnemius impact injury in rats with a bioimpact machine, with which the experimental operation could be conducted in feasibility from the recorded parameters. Through this novel model, we study the skeletal muscle impact injury mechanisms by combining temporal and spatial variation. Methods: The gastrocnemius of anesthetized rats was injured by a small pneumatic-driven bioimpact machine; the moving speed and impact force were determined, and the whole impact process was captured by a high-speed camera. We observed the general condition of rats and measured the changes in injured calf circumference, evaluating calf injuries using MRI, gait analysis system, and pathology at different times after the injury. Results: The gastrocnemius was injured at an impact speed of 6.63 m/s ± 0.25 m/s and a peak force of 1,556.80 N ± 110.79 N. The gait analysis system showed that the footprint area of the RH limb decreased significantly on the first day and then increased. The calf circumference of the injured limb increased rapidly on the first day post-injury and then decreased in the next few days. MRI showed edema of subcutaneous and gastrocnemius on the first day, and the area of edema decreased over the following days. HE staining showed edema of cells, extensive hyperemia of blood vessels, and infiltration of inflammatory cells on the first day. Cell edema was alleviated day by day, but inflammatory cell infiltration was the most on the third day. TEM showed that the sarcoplasmic reticulum was dilated on the first day, the mitochondrial vacuolation was obvious on the second day, and the glycogen deposition was prominent on the fifth day. Conclusion: In our experiment, we developed a new and effective experimental animal model that was feasible to operate; the injured area of the gastrocnemius began to show "map-like" changes in the light microscope on the third day. Meanwhile, the gastrocnemius showed a trend of "edema-mitochondrial vacuolation-inflammatory cell aggregation" after impact injury.

Characterization of Bitter Compounds in Shaoxing Huangjiu by Quantitative Measurements, Taste Recombination, and Omission Experiments.

Excessive and uncoordinated bitterness of Shaoxing Huangjiu, a traditional Chinese rice wine, reduces its acceptance by consumers. To determine the compounds responsible for this bitterness, gas chromatography-mass spectrometry and high-performance liquid chromatography were performed on four types of Shaoxing Huangjiu (Yuanhong, Huadiao, Shanniang, and Xiangxue wine) for targeted quantitation of candidate compounds known to contribute to bitterness. Calculations of dose-over-threshold factors revealed that isoamyl alcohol, 1-hexanol, phenylethanol, ethyl butyrate, ethyl lactate, furfural, histidine, and arginine were important bitter compounds. Taste recombination experiments demonstrated that a recombination model constructed using the screened known bitter compounds showed good similarity with the original sample in bitter taste. Furthermore, omission experiments revealed that isobutanol, isoamyl alcohol, 1-hexanol, phenylethanol, ethyl acetate, ethyl butyrate, ethyl lactate, furfural, arginine, and valine were the compounds affecting the bitter taste perception. This study provides a certain guiding effect on the bitterness control and taste improvement of Shaoxing Huangjiu.

Isolation and identification of bitter-tasting peptides in Shaoxing rice wine using ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with taste orientation strategy.

The content of peptides in Shaoxing rice wine is high; however, their potential taste properties have not yet been studied. To isolate and identify bitter-tasting peptides in a popular Chinese rice wine, Shaoxing rice wine, a series of purification steps including ultrafiltration and gel filtration chromatography (GFC), combined with a taste orientation strategy, were used. According to the evaluation results of taste dilution analysis, a bitter peptide with the highest taste efficacy was isolated, and its purity was verified by high-performance liquid chromatography (HPLC). The amino acid sequence of peptide components was analyzed by ultra-performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-Q-TOF-MS). The bitter peptide Leu-Pro-Thr-Leu (LPTL) was successfully identified from Shaoxing rice wine. Then, taste addition experiments highlighted the bitter impacts of LPTL on sensory descriptors in Shaoxing rice wine. The LPTL peptide can contribute to bitterness in Shaoxing rice wine.

Comprehensive two-dimensional gas chromatography mass spectrometry-based untargeted metabolomics to clarify the dynamic variations in the volatile composition of Huangjiu of different ages.

Aging plays an important role in the formation of aroma characteristics of Huangjiu, a traditional Chinese alcoholic beverage. Comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-qMS)-based untargeted metabolomics combined with a multivariate analysis was used to investigate the dynamic variations in the aroma profile of Huangjiu during aging process and to establish the relationship between the changing volatile metabolite profiles and the age-dependent sensory attributes. A total of 144 volatile metabolites were identified by GC×GC-qMS and 63 were selected as critical metabolites based on variable importance in projection values and p-values. Based on the results of principal component analysis, orthogonal partial least-squares discriminant analysis, and hierarchical clustering analysis, the samples of six different ages were divided into three groups: 1Y and 3Y samples, 5Y and 8Y samples, and 10Y and 15Y samples. The partial least-squares analysis results further revealed the relationship between the aromas attributes and variations of these volatile compounds. The high esters, aldehydes, and lactones contents contributed to the high intensities of the sweet and ester aroma attributes of the aged Huangjiu, while the high alcohols and ethyl esters contents contributed to the alcoholic and fruity aroma attributes of the newly brewed Huangjiu. These results improve our understanding of the chemical nature of the aroma characteristics of aged Huangjiu. PRACTICAL APPLICATION: Huangjiu is often labeled with its age as a measure of quality, which influences consumers' choice. Dynamic variations in volatile compounds of Huangjiu during aging and its contribution to the aroma characteristics of Huangjiu were figured out, which will assist the industry to produce better quality aged Huangjiu for consumers.

Retraction of "Porous Organic Polymer-Derived Fe2P@N,P-Codoped Porous Carbon as Efficient Electrocatalysts for pH Universal ORR".

[This retracts the article DOI: 10.1021/acsomega.9b03851.].

Biomechanical analysis of thorax-abdomen response of vehicle occupant under seat belt load considering different frontal crash pulses.

PURPOSE: The purpose of this work was to understand the biomechanical response and injury risk of thorax and abdomen of vehicle front seat occupants caused by seat belt load under different frontal crash pulses. METHODS: A vehicle-seat-occupant subsystem finite element (FE) model was developed using the a assembly of vehicle front seat and seat belt together with the THUMS (Total Human body Model for Safety) AM50 (50th% Adult Male) occupant model. Then the typical vehicle frontal crash pulses from different impact scenarios were applied to the vehicle-seat-occupant subsystem FE model, and the predictions from the occupant model were analyzed. RESULTS: The modeling results indicate that the maximum sternal compression of the occupant caused by seat belt load is not sensitive to the peek of the crash pulse but sensitive to the energy contained by the crash pulse in the phrase before seat belt load reaching its limit. Injury risk analysis implies that seat belt load of the four crash scenarios considered in the current work could induce a high thorax AIS2+ injury risk (>80%) to the occupants older than 70 years, and a potential injury risk to the spleen. CONCLUSIONS: The findings suggest that control of the energy in the first 75 ms of the crash pulse is crucial for vehicle safety design, and thorax tolerance of the older population and spleen injury prevention are the key considerations in developing of seat belt system.

Mining for Ligandable Cavities in RNA.

Identifying potential ligand binding cavities is a critical step in structure-based screening of biomolecular targets. Cavity mapping methods can detect such binding cavities; however, for ribonucleic acid (RNA) targets, determining which of the detected cavities are "ligandable" remains an unsolved challenge. In this study, we trained a set of machine learning classifiers to distinguish ligandable RNA cavities from decoy cavities. Application of our classifiers to two independent test sets demonstrated that we could recover ligandable cavities from decoys with an AUC > 0.83. Interestingly, when we applied our classifiers to a library of modeled structures of the HIV-1 transactivation response (TAR) element RNA, we found that several of the conformers that harbored cavities with high ligandability scores resembled known holo-TAR structures. On the basis of our results, we envision that our classifiers could find utility as a tool to parse RNA structures and prospectively mine for ligandable binding cavities and, in so doing, facilitate structure-based virtual screening efforts against RNA drug targets.

RNA Ensembles from Solvent Accessibility Data: Application to the SAM-I Riboswitch Aptamer Domain.

Riboswitches are regulatory ribonucleic acid (RNA) elements that act as ligand-dependent conformational switches that recognize their cognate ligand via a binding pocket located in their aptamer domain. In the apo form, the aptamer domain is dynamic, requiring an ensemble representation of its structure. Here, as a proof-of-concept, we used solvent accessibility information to construct a pair of dynamical ensembles of the aptamer domain of the well-studied S-adenosylmethionine (SAM) class-I riboswitch in the absence (-SAM) and presence (+SAM) of SAM. To achieve this, we first generated a large conformational library and then reweighted conformers in the library using solvent-accessible surface area (SASA) data derived from recently reported light-activated structural examination of RNA (LASER) reactivities measured in the -SAM and +SAM states of the riboswitch. The differences in the resulting -SAM and +SAM ensembles are consistent with a SAM-dependent reshaping of the free-energy landscape of the aptamer domain. Within our -SAM ensemble, we identified a "transient" state that is missing a critical long-range contact, leading us to speculate that it may be representative of a folding intermediate. Further structural analysis also revealed that the transient state harbors a hidden binding pocket that is distinct from the SAM-binding pocket and is predicted by docking calculations to selectively bind small-molecule ligands. The SASA-based method we applied to the SAM-I riboswitch aptamer domain is general and could be used to construct dynamical ensembles for other riboswitch aptamer domains and, more broadly, other classes of structured RNAs.

RNAPosers: Machine Learning Classifiers for Ribonucleic Acid-Ligand Poses.

Determining the three-dimensional (3D) structures of ribonucleic acid (RNA)-small molecule ligand complexes is critical to understanding molecular recognition in RNA. Computer docking can, in principle, be used to predict the 3D structure of RNA-small molecule complexes. Unfortunately, retrospective analysis has shown that the scoring functions that are typically used for pose prediction tend to misclassify non-native poses as native and vice versa. Here, we use machine learning to train a set of pose classifiers that estimate the relative "nativeness" of a set of RNA-ligand poses. At the heart of our approach is the use of a pose "fingerprint" (FP) that is a composite of a set of atomic FPs, which individually encode the local "RNA environment" around ligand atoms. We found that by ranking poses based on classification scores from our machine learning classifiers, we were able to recover native-like poses better than when we ranked poses based on their docking scores. With a leave-one-out training and testing approach, we found that one of our classifiers could recover poses that were within 2.5 Šof the native poses in ∼80% of the 80 cases we examined, and, on two separate validation sets, we could recover such poses in ∼60% of the cases. Our set of classifiers, which we refer to as RNAPosers, should find utility as a tool to aid in RNA-ligand pose prediction, and so we make RNAPosers open to the academic community via https://github.com/atfrank/RNAPosers.

Preliminary injury risk estimation for occupants involved in frontal crashes by combining computer simulations and real crashes.

The fatality rate can be dramatically reduced with the help of emergency medical services. The purpose of this study was to establish a computational algorithm to predict the injury severity, so as to improve the timeliness, appropriateness, and efficacy of medical care provided. The computer simulations of full-frontal crashes with rigid wall were carried out using LS-DYNA and MADYMO under different collision speeds, airbag deployment time, and seatbelt wearing condition, in which a total of 84 times simulation was conducted. Then an artificial neural network is adopted to construct relevance between head and chest injuries and the injury risk factors; 37 accident cases with Event Data Recorder data and information on occupant injury were collected to validate the model accuracy through receiver operating characteristic analysis. The results showed that delta-v, seatbelt wearing condition, and airbag deployment time were important factors in the occupant's head and chest injuries. When delta-v increased, the occupant had significantly higher level of severe injury on the head and chest; there is a significant difference of Head Injury Criterion and Combined Thoracic Index whether the occupant wore seatbelt. When the airbag deployment time was less than 20 ms, the severity of head and chest injuries did not significantly vary with the increase of deployment time. However, when the deployment time exceeded 20 ms, the severity of head and chest injuries significantly increased with increase in deployment time. The validation result of the algorithm showed that area under the curve = 0.747, p < 0.05, indicating a medium level of accuracy, nearly to previous model. The computer simulation and artificial neural network have a great potential for developing injury risk estimation algorithms suitable for Advanced Automatic Crash Notification applications, which could assist in medical decision-making and medical care.

Porous Organic Polymer-Derived Fe2P@N,P-Codoped Porous Carbon as Efficient Electrocatalysts for pH Universal ORR.

A new porous organic polymer (CP-CMP) was designed and synthesized via the direct polymerization of pyrrole and hexakis(4-formyl-phenoxy)cyclotriphosphazene, skipping the tedious synthetic procedure of porphyrin-monomers containing special groups. This special porous organic polymer (POP) serves as an "all in one" precursor for C, N, P, and Fe. Direct carbonization of this special POP afforded Fe2P@N,P-codoped porous carbons with hierarchical pore structure and high graphitization. Finally, the optimal catalyst (CP-CMP-900) prepared by carbonization of CP-CMP at 900 °C exhibited high efficiency for oxygen electroreduction. Typically, CP-CMP-900 presented an oxygen reduction reaction half-wave potential (E 1/2) of 0.85, 0.73, and 0.65 V, respectively, in alkaline, neutral, and acidic media, close to those of commercial Pt/C in the same electrolyte (0.843, 0.71, and 0.74 V). Furthermore, it also displayed excellent methanol immunity and long-time stability in various electrolytes better than commercial Pt/C (20%).

Aroma perceptual interactions of benzaldehyde, furfural, and vanillin and their effects on the descriptor intensities of Huangjiu.

Aldehydes are important in the aroma of Huangjiu and contribute the almond and sweet aromas to Huangjiu. The perceptual interactions of 3 important aldehyde compounds were investigated using S-curves. Three volatiles, benzaldehyde, furfural, and vanillin, reduced the "olfactory threshold" of an aromatic reconstitution (AR) from 24.2 mL/L to 11.0, 14.8 and 9.00 mL/L (AR/matrix, mL/L), respectively. Furthermore, synergistic effects were observed in a benzaldehyde and furfural mixture (71:29, m/m) wherein the overall olfactory threshold value was reduced from 17.0 mL/L to 2.60 mL/L. In addition, these compounds could increase or decrease the intensity of sensory descriptors even at subthreshold concentrations, and the profiles confirmed that they had synergistic effects with other compounds in Huangjiu. In particular, when benzaldehyde and furfural were present in the actual concentration ratio determined in Huangjiu (71:29, m/m), the enhancement of the Qu and sweet aromas became significant, which indirectly indicated synergy between them.

PyShifts: A PyMOL Plugin for Chemical Shift-Based Analysis of Biomolecular Ensembles.

Here, we present PyShifts-a PyMOL plugin for chemical shift-based analysis of biomolecular ensembles. With PyShifts, users can compare and visualize differences between experimentally measured and computationally predicted chemical shifts. When analyzing multiple conformations of a biomolecule with PyShifts, users can also sort a set of conformations based on chemical shift differences and identify the conformers that exhibit the best agreement between measured and predicted chemical shifts. Although we have integrated PyShifts with the chemical shift predictors LARMORD and LARMORCα, PyShifts can read in chemical shifts from any source, and so, users can employ PyShifts to analyze biomolecular structures using chemical shifts computed by any chemical shift predictor. We envision, therefore, that PyShifts (https://github.com/atfrank/PyShifts) will find utility as a general-purpose tool for exploring chemical shift-structure relationships in biomolecular ensembles.

Characterization of key aroma compounds in Chinese rice wine using gas chromatography-mass spectrometry and gas chromatography-olfactometry.

To determine the key aroma compounds in Chinese rice wine (CRW), four types of CRW (YH, JF, SN, and XX) were analyzed by gas chromatography-mass spectrometry (GC-MS), gas chromatography-olfactometry (GC-O), and sensory evaluation. The contributions of the key aroma compounds to the flavor characteristics were determined by partial least squares regression. Sixty-one aroma compounds were detected. Twenty-five components were identified as odor-active compounds. On the basis of their odor active values, 18 odor-active compounds were determined as key aroma compounds. Ethyl isovalerate, ethyl butyrate, ethyl acetate, ethyl hexanoate, and phenylethyl alcohol were key aroma compounds in all four types of wine. The unique key aroma compounds of JF wine were isovaleraldehyde and isoamyl acetate; those of XX wine were 1-butanol, benzaldehyde, ethyl benzoate, ethyl phenylacetate, 2-octanone, and furfural; that of YH wine was ethyl 2-methylbutyrate; and those of SN wine were 1-butanol, 1-hexanol, 2-butenoic acid ethyl ester, and 3-methyl-1-butanol.

MicroRNA array analysis of the regulation of microRNAs in rats exhibiting hyperplasia of mammary glands.

Hyperplasia of mammary glands (HMG) is also termed mammary dysplasia. In China, the number of patients suffering from breast hyperplasia is increasing annually. MicroRNAs (miRNAs; length, 19-24 nucleotides), a group of small endogenous non-coding RNAs, post-transcriptionally regulate gene expression via RNA interference and gene silencing pathways. The cause of disease of HMG because remains unclear. Thus, the aim of the present study was to establish comprehensive profile of drug treatments following at different time intervals on rat models of differentially expressed miRNAs, using miRNA microarray data. After scanning the chip, 13 up-regulated and 20 down-regulated miRNAs were identified. MiR-31 and miR-30 exhibited different expression levels between rats exhibiting mammary gland hyperplasia treated with or without Jiedu Capsule water solution once a day for 4 weeks, and the two demonstrated a strong association with HMG and breast cancer. Therefore, the functions of these miRNAs may provide the basis for further investigation of HMG.