Seasonal mouse cadaver microbial study: rupture time and postmortem interval estimation model construction.

The estimation of postmortem interval (PMI) has long been a focal point in the field of forensic science. Following the death of an organism, microorganisms exhibit a clock-like proliferation pattern during the course of cadaver decomposition, forming the foundation for utilizing microbiology in PMI estimation. The establishment of PMI estimation models based on datasets from different seasons is of great practical significance. In this experiment, we conducted microbiota sequencing and analysis on gravesoil and mouse intestinal contents collected during both the winter and summer seasons and constructed a PMI estimation model using the Random Forest algorithm. The results showed that the MAE of the gut microbiota model in summer was 0.47 ± 0.26 d, R2 = 0.991, and the MAE of the gravesoil model in winter was 1.04 ± 0.22 d, R2 = 0.998. We propose that, in practical applications, it is advantageous to selectively build PMI estimation models based on seasonal variations. Additionally, through a combination of morphological observations, gravesoil microbiota sequencing results, and soil physicochemical data, we identified the time of cadaveric rupture for mouse cadavers, occurring at around days 24-27 in winter and days 6-9 in summer. This study not only confirms previous research findings but also introduces novel insights, contributing to the foundational knowledge necessary to advance the utilization of microbiota for PMI estimation.

Combining spectrum and machine learning algorithms to predict the weathering time of empty puparia of Sarcophaga peregrine (Diptera: Sarcophagidae).

The weathering time of empty puparia could be important in predicting the minimum postmortem interval (PMImin). As corpse decomposition progresses to the skeletal stage, empty puparia often remain the sole evidence of fly activity at the scene. In this study, we used empty puparia of Sarcophaga peregrina (Diptera: Sarcophagidae) collected at ten different time points between January 2019 and February 2023 as our samples. Initially, we used the scanning electron microscope (SEM) to observe the surface of the empty puparia, but it was challenging to identify significant markers to estimate weathering time. We then utilized attenuated total internal reflectance Fourier transform infrared spectroscopy (ATR-FTIR) to detect the puparia spectrogram. Absorption peaks were observed at 1064 cm-1, 1236 cm-1, 1381 cm-1, 1538 cm-1, 1636 cm-1, 2852 cm-1, 2920 cm-1. Three machine learning models were used to regress the spectral data after dimensionality reduction using principal component analysis (PCA). Among them, eXtreme Gradient Boosting regression (XGBR) showed the best performance in the wavenumber range of 1800-600 cm-1, with a mean absolute error (MAE) of 1.20. This study highlights the value of refining these techniques for forensic applications involving entomological specimens and underscores the considerable potential of combining FTIR and machine learning in forensic practice.

The gut bacterial composition across life stages of Sarcophaga peregrina (Diptera: Sarcophagidae) and the effects of amikacin on their development.

Insects and microorganisms, ubiquitous organisms in the natural world, have developed intricate relationships throughout their evolutionary histories. However, most studies have concentrated on specific time points or life stages, but some limited studies have investigated the dynamics of microbial diversity within insects across life stages. Here, 16S rDNA sequencing technology was used to investigate the gut bacterial community across the life stages of Sarcophaga peregrina (Robineau-Desvoidy) (Diptera: Sarcophagidae). The results revealed that the gut bacterial diversity of S. peregrina varied with life stage and showed similarity in the nearby life stages. Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes were the dominant phyla in S. peregrina. Genera such as Providencia, Ignatzschineria, and Myroides are implicated in potentially pivotal roles during the developmental processes of this flesh fly. Furthermore, the effects of amikacin on the growth and development of S. peregrina were not statistically significant. However, we did observe significant changes at the protein level, which suggests a close association between protein-level alterations and growth and development. Additionally, we speculate that S. peregrina regulates its nutritional status during nonfeeding stages to meet the demands of eclosion. This study represents the first comprehensive examination of the intestinal bacterial composition across various life stages of S. peregrina. Our findings deepen our understanding of the gut microbiota in this flesh fly and lay the groundwork for further exploration into the intricate interactions between microorganisms and insects.

Emission and optical characteristics of brown carbon in size-segregated particles from three types of Chinese ships.

Brown carbon (BrC) is one of the important light absorption substances that have high light absorption ability under short wavelength light. However, limit studies have focused on the BrC emission from ships. In this study, size-segregated particulate matters (PM) were collected from three different types of ships, light absorption characteristics and size distribution of methanol-soluble BrC and water-soluble BrC in PM from ship exhausts were investigated. Results showed that four-stroke low-power diesel fishing boat (4-LDF) had the highest mass concentrations of methanol-soluble organic carbon (MSOC) and water-soluble organic carbon (WSOC), followed by 2-stroke high-power heavy-fuel-oil vessel (2-HHV), and four-stroke high-power marine-diesel vessel (4-HMV). While 2-HHV had obviously higher light absorption coefficients of methanol-soluble BrC (Abs365,M) and water-soluble BrC (Abs365,W) in unit weight of PM than the other two types of ships. The tested ships presented comparable or higher absorption efficiency of BrC in water extracts (MAE365,W) compared with other BrC emission sources. Majority of BrC was concentrated in fine particles, and the particle size distributions of both Abs365,M and Abs365,W showed bimodal patterns, peaking at 0.43-0.65 µm and 4.7-5.8 µm, respectively. However, different particle size distributions were found for MAE365,M between diesel and heavy fuel oil ships. Besides, different wavelength dependence in particles with different size were also detected. Ship exhaust could be confirmed as a non-ignorable BrC emission source, and complex influencing factor could affect the light absorption characteristics of ship emissions. Particle size should also be considered when light absorption ability of BrC was evaluated.

Age Determination of Chrysomya megacephala Pupae through Reflectance and Machine Learning Analysis.

Estimating the age of pupa during the development time of the blow fly Chrysomya megacephala (Diptera: Calliphoridae) is of forensic significance as it assists in determining the time of colonization (TOC), which could help to determine the postmortem interval (PMI). However, establishing an objective, accurate, and efficient method for pupa age inference is still a leading matter of concern among forensic entomologists. In this study, we utilized hyperspectral imaging (HSI) technology to analyze the reflectance changes of pupa development under different temperatures (15 °C, 20 °C, 25 °C, and 30 °C). The spectrograms showed a downtrend under all temperatures. We used PCA to reduce the dimensionality of the spectral data, and then machine learning models (RF, SVR-RBF, SVR-POLY, XGBR, and Lasso) were built. RF, SVR with RBF kernel, and XGBR could show promise in accurate developmental time estimation using accumulated degree days. Among these, the XGBR model consistently exhibited the most minor errors, ranging between 3.9156 and 7.3951 (MAE). This study has identified the value of further refinement of HSI in forensic applications involving entomological specimens, and identified the considerable potential of HSI in forensic practice.

Identification of sudden cardiac death from human blood using ATR-FTIR spectroscopy and machine learning.

OBJECTIVE: The aim of this study is to identify a rapid, sensitive, and non-destructive auxiliary approach for postmortem diagnosis of SCD, addressing the challenges faced in forensic practice. METHODS: ATR-FTIR spectroscopy was employed to collect spectral features of blood samples from different cases, combined with pathological changes. Mixed datasets were analyzed using ANN, KNN, RF, and SVM algorithms. Evaluation metrics such as accuracy, precision, recall, F1-score and confusion matrix were used to select the optimal algorithm and construct the postmortem diagnosis model for SCD. RESULTS: A total of 77 cases were collected, including 43 cases in the SCD group and 34 cases in the non-SCD group. A total of 693 spectrogram were obtained. Compared to other algorithms, the SVM algorithm demonstrated the highest accuracy, reaching 95.83% based on spectral biomarkers. Furthermore, by combing spectral biomarkers with age, gender, and cardiac histopathological changes, the accuracy of the SVM model could get 100%. CONCLUSION: Integrating artificial intelligence technology, pathology, and physical chemistry analysis of blood components can serve as an effective auxiliary method for postmortem diagnosis of SCD.

Analysis and comparison of machine learning methods for species identification utilizing ATR-FTIR spectroscopy.

Accurate identification of insect species holds paramount significance in diverse fields as it facilitates a comprehensive understanding of their ecological habits, distribution range, and impact on both the environment and humans. While morphological characteristics have traditionally been employed for species identification, the utilization of empty pupariums for this purpose remains relatively limited. In this study, ATR-FTIR was employed to acquire spectral information from empty pupariums of five fly species, subjecting the data to spectral pre-processing to obtain average spectra for preliminary analysis. Subsequently, PCA and OPLS-DA were utilized for clustering and classification. Notably, two wavebands (3000-2800 cm-1 and 1800-1300 cm-1) were found to be significant in distinguishing A. grahami. Further, we established three machine learning models, including SVM, KNN, and RF, to analyze spectra from different waveband groups. The biological fingerprint region (1800-1300 cm-1) demonstrated a substantial advantage in identifying empty puparium species. Remarkably, the SVM model exhibited an impressive accuracy of 100 % in identifying all five fly species. This study represents the first instance of employing infrared spectroscopy and machine learning methods for identifying insect species using empty pupariums, providing a robust research foundation for future investigations in this area.

Age determination of Chrysomya megacephala (Diptera: Calliphoridae) using lifespan patterns, gene expression, and pteridine concentration under constant and variable temperatures.

Chrysomya megacephala (Fabricius, 1794) (Diptera: Calliphoridae), is a blowfly species widely studied in medical, veterinary, and entomological research. Our study examined the impact of constant (15, 20, 25, 30, and 35 °C) and variable (ranging from 21.0 to 25.4 °C, with an average of 23.31 °C) temperatures on the development and larval body length of C. megacephala. Additionally, we analyzed the age of the adult C. megacephala through pteridine content and related metabolic genes analysis. Our findings revealed three distinct growth patterns: isomorphen diagram, isomegalen diagram, and thermal accumulated models. At constant temperatures of 15, 20, 25, 30, and 35 °C, egg-hatching times were 44.5 ± 8.9, 26.7 ± 4.6, 12.6 ± 1.1, 11.0 ± 1.0, and 9.9 ± 1.9 h, respectively, while it was 15.3 ± 5.9 h at variable temperatures. The total development times from oviposition to adult eclosion in C. megacephala required 858.1 ± 69.2, 362.3 ± 5.9, 289.6 ± 17.8, 207.3 ± 9.3, and 184.7 ± 12.1 h at constant temperatures of 15, 20, 25, 30, and 35 °C, respectively. This duration was extended to 282.0 ± 64.1 h under variable temperatures. However, no significant differences were found in hatching times and the total developmental durations between 25 °C and variable temperatures. A developmental threshold temperature (D0) of 9.90 ± 0.77 °C and a thermal summation constant (K) of 4244.0 ± 347.0° hours were ascertained. Pteridine content patterns varied significantly across constant temperatures, but not between 25 °C and variable temperatures. Sex and temperature were identified as the primary factors influencing pteridine levels in the head of C. megacephala. Gene expression associated with pteridine metabolism decreased following adult eclosion, matching with increased pteridine concentration. Further investigations are needed to explore the use of pteridine cofactors for age-grading adult necrophagous flies. These findings provide valuable insights into the lifespan of C. megacephala, thereby offering valuable groundwork for forthcoming investigations and PMImin determination.

Effect of Ciprofloxacin on the Composition of Intestinal Microbiota in Sarcophaga peregrina (Diptera: Sarcophagidae).

The intestinal bacteria of insects are crucial to the growth and development of the host. It has been found that various physiological processes of insects, such as immune response, metabolism, reproductive ability, and growth and development, involve the gastrointestinal flora. However, many external factors affect the composition of insects' intestinal microorganisms, such as the type of dietary substrate. Sarcophaga peregrina (Robineau-Desvoidy, 1830) (Diptera: Sarcophagidae) is of great significance in medicine and forensic science. In this study, we investigated the effects of ciprofloxacin on the growth and gut microbiota of S. peregrina. The results demonstrated that the maximum body length of larvae was not affected by ciprofloxacin, while the growth rate of body length quickened as the concentration of the drug increased. The weight of the pupa and adult was reduced significantly due to the effect of ciprofloxacin. After analyzing the gut microbiota composition of S. peregrina in different drug groups, it was indicated that Ignatzschineria, Providencia, Wohlfahrtiimonas, Proteus, Myroides, and Bacteroides play important roles in the growth of S. peregrina. However, they still need to be further studied. In general, ciprofloxacin can affect the gut microbial community structure, which in turn affects the fitness of the host.

Molecular identification and functional analysis of chitinase genes reveal their importance in the metamorphosis of Sarcophaga peregrina (Diptera: Sarcophagidae).

Chitinases play a crucial role in insect metamorphosis by facilitating chitin degradation. Sarcophaga peregrina (Robineau-Desvoidy, 1830) (Diptera: Sarcophagidae) is a typical holometabolous insect and an important hygiene pest that causes myiasis in humans and other mammals and acts as a vector for various parasitic agents, including bacteria, viruses, and parasites. Enhancing the understanding of the metamorphosis in this species has significance for vector control. In this study, we identified a total of 12 chitinase genes in S. peregrina using bioinformatic analysis methods. Based on transcriptome data, SpIDGF2 and SpCht10 were selected for further functional investigation. The down-regulation of these genes by RNA interference led to developmental delays, disruptions in molting, and differences in cuticle composition during the pupal stage. These findings underscore the pivotal role of chitinase genes in the metamorphic process and offer valuable insights for effective control strategies.

Effects of heat tolerance on the gut microbiota of Sarcophaga peregrina (Diptera: Sarcophagidae) and impacts on the life history traits.

BACKGROUND: Heat tolerance is a distinct abiotic factor affecting the distribution and abundance of insects. Gut microbiota can contribute to host fitness, thereby increasing resistance to abiotic stress conditions. In this study, Sarcophaga peregrina is closely associated with human life in ecological habits and shows remarkable adaptability to daily and seasonal temperature fluctuations. To date, the role of gut microbiota in S. peregrina response to heat stress and its influence on the host phenotypic variability remain poorly studied. METHODS: We exposed S. peregrina to heat stress at 40 °C for 3 h every day throughout the developmental stages from newly hatched larva to adult, after which gut DNA was extracted from third-instar larvae, early pupal stage, late pupal stage, and newly emerged adults, respectively. Then, 16S rRNA microbial community analyses were performed. RESULTS: Firstly, we analyzed whether heat stress could have an impact on the life history traits of S. peregrina and showed that the growth rate of larvae was higher and the developmental time was significantly shorter after heat stress. We then proposed the role of the gut microbiota in the heat tolerance of S. peregrina, which indicated that the bacterial abundance and community structure changed significantly after heat tolerance. In particular, the relative abundance of Wohlfahrtiimonas and Ignatzschineria was higher in the third-instar larval larvae; the former increased and the latter decreased significantly after heat stress. To further explore the effect of disturbing the microbial community on thermotolerant phenotype, newly hatched larvae were fed with amikacin under heat stress, which indicated that the larval length and the whole developmental cycle was significantly shorter. CONCLUSION: This study indicated that Wohlfahrtiimonas and Ignatzschineria should play an important role in the post-feeding stage under heat stress, but further study is still needed. In general, heat tolerance can affect the gut microbial community structure, which in turn affects the fitness of the host.

Analysis of the Influence of Changing and Fixed Temperatures on the Growth and Pteridine Content in the Head of Adults Sarcophaga crassipalpis (Diptera: Sarcophagidae).

Flesh flies (Diptera: Sarcophagidae) are regarded as significant in medical and veterinary entomology, and their development models can be utilized as considerable markers to ascertain the minimum postmortem interval (PMImin). In this research, we explored the growth cycle and larval body length of Sarcophaga crassipalpis Macquart 1839 (Diptera: Sarcophagidae) reared under variable temperatures ranging from 15.7 to 31.1 °C, with an average of 24.55 °C and relative humidity ranges from 31.4 to 82.8% and at six fixed temperatures of 15, 20, 25, 30, 32, and then 35 °C. Moreover, pteridine from the head was used to assess adult age grading. Our results allowed us to provide three development models: the isomorphen chart, the isomegalen chart, and the thermal summation models. The time taken for S. crassipalpis to complete its development from larviposition to adult emergence at constant temperatures of 15, 20, 25, 30, 32, and 35 °C was 1256.3 ± 124.2, 698.6 ± 15.1, 481.8 ± 35.7, 366.0 ± 13.5, and 295.8 ± 20.5 h, respectively, except 35 °C, where all pupae were unable to attain adulthood. They lasted 485.8 ± 5.4 h under variable temperatures. The minimum developmental limit (D0) temperature and the thermal summation constant (K) of S. crassipalpis were 9.31 ± 0.55 °C and 7290.0 ± 388.4 degree hours, respectively. The increase in pteridine content exhibited variations across different temperatures. There was quite a considerable distinction in the pteridine contents of male and female S. crassipalpis at 15 °C (p = 0.0075) and 25 °C (p = 0.0213). At 32 °C and variable temperatures, the pteridine content between female and male S. crassipalpis was not statistically divergent. However, temperature and gender remain the main factors influencing the pteridine content in the head of S. crassipalpis. We aim to provide detailed developmental data on S. crassipalpis that can be used as a valuable resource for future research and PMI estimation.

Genome-wide analysis of long noncoding RNAs and their association in regulating the metamorphosis of the Sarcophaga peregrina (Diptera: Sarcophagidae).

BACKGROUND: The flesh fly, Sarcophaga peregrina (Diptera: Sarcophagidae), is an important hygiene pest, that causes myiasis in humans and other mammals, typically livestock, and as a vector for various parasitic agents, including bacteria, viruses, and parasites. The role of long non-coding RNAs (lncRNAs) in regulating gene expression during metamorphosis of the flesh fly has not been well established. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we performed genome-wide identification and characterization of lncRNAs from the early pupal stage (1-days pupae), mid-term pupal stage (5-days pupae), and late pupal stage (9-days pupae) of S. peregrina by RNA-seq, and a total of 6921 lncRNAs transcripts were identified. RT-qPCR and enrichment analyses revealed the differentially expressed lncRNAs (DE lncRNAs) that might be associated with insect metamorphosis development. Furthermore, functional analysis revealed that the DE lncRNA (SP_lnc5000) could potentially be involved in regulating the metamorphosis of S. peregrina. RNA interference of SP_lnc5000 caused reduced expression of metamorphosis-related genes in 20-hydroxyecdysone (20E) signaling (Br-c, Ftz-F1), cuticle tanning pathway (TH, DOPA), and chitin related pathway (Cht5). Injection of dsSP_lnc5000 in 3rd instar larvae of S. peregrina resulted in deformed pupae, stagnation of pupal-adult metamorphosis, and a decrease in development time of pupal, pupariation rates and eclosion rates. Hematoxylin-eosin staining (H&E), scanning electron microscope (SEM) observation and cuticle hydrocarbons (CHCs) analysis indicated that SP_lnc5000 had crucial roles in the metamorphosis developmental by modulating pupal cuticular development. CONCLUSIONS/SIGNIFICANCE: We established that the lncRNA SP_lnc5000 potentially regulates the metamorphosis of S. peregrina by putatively affecting the structure and composition of the pupal cuticle. This study enhances our understanding of lncRNAs as regulators of metamorphosis in S. peregrina, and provide valuable insights into the identification of potential targets for vector control and the development of effective strategies for controlling the spread of myiasis and parasitic diseases.

Development of Forensically Important Sarcophaga peregrina (Diptera: Sarcophagidae) and Intra-Puparial Age Estimation Utilizing Multiple Methods at Constant and Fluctuating Temperatures.

Sarcophaga peregrina (Robineau-Desvoidy, 1830) has the potential to estimate the minimum postmortem interval (PMImin). Development data and intra-puparial age estimation are significant for PMImin estimation. Previous research has focused on constant temperatures, although fluctuating temperatures are a more real scenario at a crime scene. The current study examined the growth patterns of S. peregrina under constant (25.75 °C) and fluctuating temperatures (18-36 °C; 22-30 °C). Furthermore, differentially expressed genes, attenuated total reflectance Fourier-transform infrared spectroscopy, and cuticular hydrocarbons of S. peregrina during the intra-puparial period were used to estimate age. The results indicated that S. peregrina at fluctuating temperatures took longer to develop and had a lower pupariation rate, eclosion rate, and pupal weight than the group at constant temperatures did. Moreover, we found that six DEG expression profiles and ATR-FTIR technology, CHCs detection methods, and chemometrics can potentially estimate the intra-puparial age of S. peregrina at both constant and fluctuating temperatures. The findings of the study support the use of S. peregrina for PMImin estimation and encourage the use of entomological evidence in forensic practice.

Pupal Age Estimation of Sarcophaga peregrina (Diptera: Sarcophagidae) at Different Constant Temperatures Utilizing ATR-FTIR Spectroscopy and Cuticular Hydrocarbons.

Sarcophaga peregrina (Robineau-Desvoidy, 1830) (Diptera: Sarcophagidae) is a forensically important flesh fly that has potential value in estimating the PMImin. The precise pupal age estimation has great implications for PMImin estimation. During larval development, the age determination is straightforward by the morphological changes and variation of length and weight, however, the pupal age estimation is more difficult due to anatomical and morphological changes not being visible. Thus, it is necessary to find new techniques and methods that can be implemented by standard experiments for accurate pupal age estimation. In this study, we first investigated the potential of attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and cuticular hydrocarbons (CHCs) for the age estimations of S. peregrina pupae at different constant temperatures (20 °C, 25 °C, and 30 °C). The orthogonal projections latent structure discrimination analysis (OPLS-DA) classification model was used to distinguish the pupae samples of different developmental ages. Then, a multivariate statistical regression model, partial least squares (PLS), was established with the spectroscopic and hydrocarbon data for pupal age estimations. We identified 37 CHCs with a carbon chain length between 11 and 35 in the pupae of S. peregrina. The results of the OPLS-DA model show a significant separation between different developmental ages of pupae (R2X > 0.928, R2Y > 0.899, Q2 > 0.863). The PLS model had a satisfactory prediction with a good fit between the actual and predicted ages of the pupae (R2 > 0.927, RMSECV < 1.268). The results demonstrate that the variation tendencies of spectroscopy and hydrocarbons were time-dependent, and ATR-FTIR and CHCs may be optimal for the age estimations of pupae of forensically important flies with implications for PMImin estimation in forensic practice.

Multimethod combination for age estimation of Sarcophaga peregrina (Diptera: Sarcophagidae) with implications for estimation of the postmortem interval.

Sarcophaga peregrina (Robineau-Desvoidy, 1830) (Diptera: Sarcophagidae) is a forensically important flesh fly with potential value for estimating the minimum postmortem interval (PMImin). Here, the developmental patterns of S. peregrina were investigated at 5 constant temperatures (15-35 °C). Morphological changes at different developmental stages of the pupa were observed at 4 constant temperatures (15-30 °C) by removing the puparium and staining the pupa with hematoxylin and eosin. Furthermore, differentially expressed genes (DEGs) were analyzed at 25 °C in the intrapuparial period to estimate the age of S. peregrina during the intrapuparial stage. S. peregrina completed development from larviposition to adult eclosion at 15 °C, 20 °C, 25 °C, and 30 °C; the developmental durations were 1090.3 ± 30.6 h, 566.6 ± 21.9 h, 404.6 ± 13.01 h, and 280.3 ± 4.5 h, respectively, while the development could not be completed at 35 °C. The intrapuparial period of S. peregrina was divided into 12 sub-stages on the basis of the overall external morphological changes; 6 sub-stages on the basis of individual morphological structures such as the compound eyes, antennae, thorax, legs, wings, and abdomen; and 10 sub-stages on the basis of internal morphological changes detected using histological analysis. The period of each sub-stage or structure that appeared was determined. Moreover, we found that 6 genes (NDUFS2, CPAMD8, NDUFV2, Hsp27, Hsp23, and TPP) with differential expression can be used for the precise age estimation of S. peregrina during the intrapuparial period. This study provided basic developmental data for the use of S. peregrina in PMImin estimation, and we successfully estimated PMImin in a real forensic case by using a multimethod combination.

Impacts of Chinese spring festival on household PM2.5 pollution and blood pressure of rural residents.

BACKGROUND: Household air pollution (HAP) from residential combustion considerably affects human health in rural China. Large-scale population migration and rural lifestyle changes during the Spring Festival are supposed to change the household air pollution and health risks; however, limited field study has determined its impacts on HAP and short-term health outcomes. METHODS: A field study was conducted in rural areas of Southern China before and during the Spring Festival to explore the associations between HAP and blood pressure considering different factors such as cooking fuel, heating fuel, and smoking. Stationary real-time PM2.5 monitors were used to measure PM2.5 concentrations of the kitchen, living room, and yard of 156 randomly selected households. Personal exposure to PM2.5 was calculated based on the results of stationary samplers and corresponding time local residents spent in different microenvironments, and one adult resident was recruited of each family for the blood pressure measurement. RESULTS: Both personal exposure to PM2.5 and blood pressures of local residents increased during Spring Festival compared to the days before the holiday. Based on generalized linear model coupled with dominance analysis approach, it was found that personal PM2.5 exposure was positively associated with the factors of population size and the types of cooking and heating fuels with the relative contributions of approximately 82%, and systolic blood pressure (SBP, 100-120 mmHg as normal range for adults) was positively and significantly associated with personal PM2.5 exposures with the relative contribution of 11%. CONCLUSION: The findings in this study demonstrated that Spring Festival can give rise to increase of HAP and hypertension risks, also related to tremendous solid fuel use, suggesting further policy making on promoting cleaner energy in rural areas and more attention on large population migration during national holidays.

Relevance popularity: A term event model based feature selection scheme for text classification.

Feature selection is a practical approach for improving the performance of text classification methods by optimizing the feature subsets input to classifiers. In traditional feature selection methods such as information gain and chi-square, the number of documents that contain a particular term (i.e. the document frequency) is often used. However, the frequency of a given term appearing in each document has not been fully investigated, even though it is a promising feature to produce accurate classifications. In this paper, we propose a new feature selection scheme based on a term event Multinomial naive Bayes probabilistic model. According to the model assumptions, the matching score function, which is based on the prediction probability ratio, can be factorized. Finally, we derive a feature selection measurement for each term after replacing inner parameters by their estimators. On a benchmark English text datasets (20 Newsgroups) and a Chinese text dataset (MPH-20), our numerical experiment results obtained from using two widely used text classifiers (naive Bayes and support vector machine) demonstrate that our method outperformed the representative feature selection methods.

Antifungal activity of 40 TCMs used individually and in combination for treatment of superficial fungal infections.

ETHNOPHARMACOLOGICAL RELEVANCE: A series of 40 important Traditional Chinese Medicines (TCMs), which were reported effective in treating superficial fungal infections of the skin in Chinese clinical trial publications and Chinese Herbal Classics, were chosen for the investigation of the individual and combination antifungal properties against 8 superficial fungal strains in vitro. MATERIALS AND METHODS: Plant preparations were followed the theory of TCM by using sterile water boiled with plant material at 100°C to produce water decoction of the tested sample. The minimum inhibitory concentration (MIC) of each plant for each fungus was determined. For the compatibility investigation, both invariable (same amounts of each tested TCM) and variable (different amounts of each tested TCM) combinations were evaluated. RESULTS: All the tested TCMs demonstrated varying degrees of antifungal activities against one or more of the tested superficial fungi, and 16 of which were effective on all of the fungi. Strong antifungal activities were exhibited by water decoction of 7 TCMs with MIC at about 100µg/ml, and among these effective antifungal extracts, 4 TCMs including Melaphis chinensis, Polygonum cuspidatum, Punica granatum and Schisandra chinensis showed the significantly inhibitory activities against all of the fungi with MICs among 50µg/ml. Most of the invariable combinations of the above-mentioned 4 TCMs showed synergic effects against 4 of the least susceptible fungi strains, especially the invariable combination of Punica granatum, Melaphis chinensis and Schisandra chinensis, with the MIC at 23.4µg/ml. However, their further variable combinations investigation demonstrated that only the combination of 7.5g Punica granatum with 10g Melaphis chinensis and 7.5g Schisandra chinensis showed synergic effect with the MIC at19.5µg/ml. CONCLUSIONS: The present study aimed the discovery of therapeutically useful agents for treatment of superficial fungal infections. Findings suggested that the combination of 3 TCMs including Punica granatum, Melaphis chinensis and Schisandra chinensis showed potential antifungal activity and thus appeared to be promising agents in preventing superficial fungal skin infectious in a natural way through herbal resources. The synergic effects of invariable and variable combinations of the tested TCMs threw a light on our further animal model and clinical practice as well as the bio-guided isolation and identification of the antifungal compounds.

Synthesis and secretory expression of hybrid antimicrobial peptide CecA-mag and its mutants in Pichia pastoris.

The hybrid peptide CA(1-7)-M(2-12) gene was designed according to the N-terminal 1-7 amino acid sequence of the antimicrobial peptide cecropin A (CA) and the N-terminal 2-12 amino acid sequence of maganin (M) and synthesized using Pichia pastoris preferred codons. The gene was cloned into pPICZαA and transformed into the P. pastoris recipient bacterium SMD1168, regulated by the alcohol oxidase (AOX). Expression of the cecA-mag hybrid antimicrobial peptide (MW, 1.9 kDa) revealed broad-spectrum antibiotic activity and to the ability to inhibit growth of most G(-) and G(+) bacteria. Three mutants of cecA-mag were designed and synthesized by recombination polymerase chain reaction site-directed mutagenesis to investigate the relationship between the structure and function of this antimicrobial peptide. The inhibition titers of these mutants against Staphylococcus aureus were evaluated using the agar diffusion method. Under the conditions of the same concentration and volume, the bacteriostatic diameters of three cecA-mag mutants were 1.2, 1.2 and 1.5 times, respectively, compared with the diameters of wild-type cecA-mag.