Efficient biodegradation of chlorobenzene via monooxygenation pathways by Pandoraea sp. XJJ-1 with high potential for groundwater bioremediation.

Chlorobenzene (CB), extensively used in industrial processes, has emerged as a significant contaminant in soil and groundwater. The eco-friendly and cost-effective microbial remediation has been increasingly favored to address this environmental challenge. In this study, a degrading bacterium was isolated from CB-contaminated soil at a pesticide plant, identified as Pandoraea sp. XJJ-1 (CCTCC M 2021057). This strain completely degraded 100 mg·L-1 CB and showed extensive degradability across a range of pH (5.0-9.0), temperature (10-37 °C), and CB concentrations (100-600 mg·L-1). Notably, the degradation efficiency was 85.2% at 15 °C, and the strain could also degrade six other aromatic hydrocarbons, including benzene, toluene, ethylbenzene, and xylene (o-, m-, p-). The metabolic pathway of CB was inferred using ultraperformance liquid chromatography, gas chromatography-mass spectrometry, and genomic analysis. In strain XJJ-1, CB was metabolized to o-chlorophenol and 3-chloroxychol by CB monooxygenase, followed by ortho-cleavage by the action of 3-chlorocatechol 1,2-dioxygenase. Moreover, the presence of the chlorobenzene monooxygenation pathway metabolism in strain XJJ-1 is reported for the first time in Pandoraea. As a bacterium with low-temperature resistance and composite pollutant degradation capacity, strain XJJ-1 has the potential application prospects in the in-situ bioremediation of CB-contaminated sites.

Serum concentrations of bisphenol A and its alternatives in elderly population living around e-waste recycling facilities in China: Associations with fasting blood glucose.

In the present study, concentrations of bisphenol A (BPA) and its six alternatives were quantified in serum samples collected from elder population living around an e-waste recycling facilities as well as an reference area in China. BPA, bisphenol AF (BPAF), and bisphenol F (BPF) were frequently detected (detection rates: > 65%) in serum samples collected from residents living near e-waste dismantling facilities, with geometric mean (GM) concentrations of 3.2, 0.0074, and 0.062 ng/mL, respectively. The detection frequencies of other four bisphenols (BPs) in serum samples were lower than 25%, regardless of the sampling areas. Significant difference (Mann-Whitney U-test, p < 0.05) was observed in the serum concentration of BPA, but not BPAF and BPF, between the e-waste recycling and reference areas. This finding indicated e-waste dismantling activities are correlated with human BPA exposure. Significant higher (p < 0.05) detection rates of donors who had abnormal fasting blood glucose (FBG) levels were found in e-waste recycling areas (45%) than those found in reference area. Our results suggested BPA and BPAF exposure might associated with abnormal FBG in participants living in e-waste sites. To our knowledge, this study is first determination of BPs in serum samples and assessment of health risk of elderly people from BPs exposure in e-waste dismantling area.

Shenfu injection improves isoproterenol-induced heart failure in rats by modulating co-metabolism and regulating the trimethylamine-N-oxide - inflammation axis.

Heart failure (HF) is a chronic condition that progressively worsens and continues to be a major financial burden and public health concern. The "gut-heart" axis provides an innovative perspective and therapeutic strategy for preventing and treating heart failure. Shenfu injection (SFI) is a Traditional Chinese Medicine-based treatment demonstrating potential as a therapeutic strategy for heart failure. However, the precise therapeutic mechanisms of SFI in heart failure are not completely characterized. In this study, HF models were established utilizing subcutaneous multipoint injection of isoproterenol (ISO) at a dosage of 5 mg kg-1·d-1 for 7 days. Serum levels of inflammatory biomarkers were quantified using protein microarrays. Rat feces were analyzed using untargeted metabolomics research and 16S rRNA sequencing. The link between gut microbiota and metabolites was examined using a MetOrigin and Spearman correlation analysis. Our results show that Shenfu injection effectively enhances cardiac function in rats with ISO-induced heart failure by potentially modulating pro-/anti-inflammatory imbalance and reducing serum and urine Trimethylamine-N-oxide (TMAO) levels. Moreover, SFI significantly increases the abundance of Bacteroidota at the phylum level, thereby improving disrupted gut microbiota composition. Additionally, SFI supplementation enriches specific genera known for their capacity to produce short-chain fatty acids. SFI was found to be associated with three key metabolic pathways, as revealed by fecal metabonomics analysis, including the pentose phosphate pathway, pyrimidine metabolism, and purine metabolism. Metabolite tracing analysis revealed that Taurine and hypotaurine metabolism was found to be specific to the microbial community. The biosynthesis of Pyrimidine metabolism, Purine metabolism, beta-alanine metabolism, Naphthalene degradation, Pantothenate, and CoA biosynthesis were identified as co-metabolic pathways between microbes and host. The Spearman correlation analysis was also significantly correlated to differentially expressed metabolites regulated by SFI and the gut microbiota. These results suggest that SFI improves ISO-induced heart failure by modulating co-metabolism and regulating the TMAO-inflammation axis.

[Spectroscopic diagnosis of striation in hollow cathode discharge].

The characteristics of striations in cylindrical hollow cathode discharge were investigated experimentally. The emission intensity and spectra of striations were measured, and the spatial characteristics of electron excitation temperature and relative electron density were calculated. It is shown that the emission intensity, the electron excitation temperature and the electron density appear as a periodic structure. The electrons have higher excitation temperature but lower density in the bright regions compared with the dark regions. The electron excitation temperature in the bright regions decreases from the cathode to the anode. It is also shown that the electron excitation temperature increases with increasing current.

A Novel Low-Cost Wireless Footwear System for Monitoring Diabetic Foot Patients.

Diabetic foot is one of the main complications of diabetes with the characteristics of high incidence and difficulty in treatment. Diabetic patients with peripheral neuropathy may develop foot ulcers, and in severe cases amputations are required and some may even die. Plantar pressure can be used to assess the risk of developing diabetic foot, but the existing plantar pressure monitoring methods are not suitable for long-term monitoring in daily life. This study presents a novel low-cost shoe system for daily monitoring of plantar pressure in diabetics. It includes an insole with pressure sensor array, which can dynamically monitor the plantar pressure and display the changes of plantar pressure in real time in the mobile phone to provide early warning for patients with high risk of diabetic foot. As for the sensor, copper and carbon black were adopted as the electrode and conductive filler respectively, enabling a mass production with low price. It was soft and bendable, meeting the performance needs of daily plantar pressure monitoring. All devices were encapsulated in shoes, and the data was transmitted wirelessly through Bluetooth, which did not affect the user's walking. After using random forest for feature selection, five classifiers were used to classify the plantar pressure of healthy people, diabetic patients without peripheral neuropathy, and diabetic patients with peripheral neuropathy collected by this system. The experimental results showed that the accuracy of the random forest classifier was the highest, reaching 94.7%, which indicated that the system could be useful for daily plantar pressure monitoring of diabetic patients.

Water-Stable Silver-Based Metal-Organic Frameworks of Quaternized Carboxylates and Their Antimicrobial Activity.

Three-dimensional (3D) and two-dimensional (2D) Ag-based zwitterionic metal-organic frameworks (MOFs) [Ag2(Cedcp)]n (1, 3D, H3CedcpBr denotes N-(carboxyethyl)-(3,5-dicarboxyl)-pyridinium bromide) and {[Ag4(Cmdcp)2(H2O)4]·4H2O}n (2, 2D, H3CmdcpBr denotes N-(carboxymethyl)-(3,5-dicarboxyl)-pyridinium bromide) have been prepared and investigated for antimicrobial activity via minimal inhibition concentration (MIC) test and killing kinetic assay. Both MOFs 1 and 2 show good water stability and solubility ascribed to their characteristic aromatic rings and positively charged pyridinium of the ligands, as well as the presence of Ag+ on their surface, leading to strong antimicrobial activity and a wide antimicrobial spectrum toward Gram-negative and positive bacteria. The results indicated that MOF 2 possesses a faster antibacterial activity (60 min) than MOF 1 (120 min). Scanning electron microscopy analysis further suggests that the Ag-based MOFs are capable of rupturing the bacterial membrane, leading to cell death. Moreover, both MOFs exhibit little hemolytic activity against mouse erythrocytes and show good biocompatibility in vitro, rendering MOFs 1 and 2 potential therapeutic agents for diseases caused by bacteria.

A pilot study of metabolites of organophosphorus flame retardants in paired maternal urine and amniotic fluid samples: potential exposure risks of tributyl phosphate to pregnant women.

Organophosphorus flame retardants (OPs) are of wide concern due to their presence in human urine and their considerable endocrine disruption and neuro-development toxicity. It has been confirmed that electronic waste (e-waste) dismantling activities have contributed to human exposure to OPs. However, assessments of OP exposure and the health risks for pregnant women and fetuses living in areas associated with e-waste dismantling have been impeded by a lack of data. In this study, six OP metabolites (mOPs) were measured in paired maternal urine and amniotic fluid samples collected from an e-waste dismantling area in Guangdong Province, China. All mOPs were detectable in maternal urine, whereas two were found in amniotic fluid. Dibutyl phosphate (DBP) was the predominant mOP in both maternal urine (geometric mean (GM): 2.9 ng ml-1) and amniotic fluid (1.3 ng ml-1); and diphenyl phosphate (DPHP) was the secondary one found (0.94 ng ml-1 in maternal urine, 0.12 ng ml-1 in amniotic fluid). The GM urinary concentrations of DBP and DPHP were two and seven times higher than those in amniotic fluid, respectively. The estimated daily intakes (EDIs) of triphenyl phosphate (TPHP) and tributyl phosphate (TnBP) by pregnant women were calculated from their daily urine excretion rate as fractions of OP metabolized to the corresponding metabolite (FUE). Our results showed high exposure levels to TPHP (median: 273 or 613 ng per kg bw per day) and TnBP (404 ng per kg bw per day) for pregnant women living in the e-waste associated area. Most importantly, 13% of mothers had EDITnBP levels that exceeded the reference dose (RfD: 2400 ng per kg bw per day), suggesting potential health risks from TnBP exposure for pregnant women living in areas associated with e-waste dismantling. This study, as a pilot study, presents the first measurements of mOPs in human amniotic fluid.

Urinary metabolites of organophosphate flame retardants in China: Health risk from tris(2-chloroethyl) phosphate (TCEP) exposure.

Organophosphate esters (OPs) are substitutes for polybrominated diphenyl ether (PBDE) flame retardants. China is the largest producer of OPs globally, with the production rate increasing at 15% annually. Since some OPs are neurodevelopmental and/or carcinogenic toxicants, human exposure is a concern. In this study, concentrations of eight OP metabolites (mOPs) were measured in human urine samples collected from 13 cities located in Northern, Eastern, Southern, and Southwestern China. All target mOPs were frequently detected with detection rates of 50% to 100%, indicating widespread human exposure to OPs. Bis(2-chloroethyl) phosphate (BCEP; median: 0.68 ng/mL), bis(1-chloro-2-propyl) phosphate (BCIPP; 0.30 ng/mL), diphenyl phosphate (DPHP; 0.30 ng/mL), and dibutyl phosphate (DBP; 0.29 ng/mL) were the dominant mOPs across all participants. Regional differences in concentrations (ΣmOPs varied from 0.86 to 3.7 ng/mL) and composition profiles (contribution of chlorinated mOPs to ΣmOPs varied from 35% to 95%) of mOPs were observed within China. In comparison to the concentrations reported worldwide, urinary DPHP and bis(1,3-dichloro-2-propyl) phosphate (BDCIPP) levels in China were lower, whereas BCEP and DBP levels were comparable or higher. The total daily intake (TDI) of tris(2-chloroethyl) phosphate (TCEP), tris(1,3-dichloro-2-propyl) phosphate (TDCIPP) and triphenyl phosphate (TPHP) were estimated from daily urine excretion rate and the fraction of OP metabolized in human liver microsomes (TDIHLM) or S9 fraction (TDIS9). The intake estimates showed that Chinese residents were exposed to TCEP from 96.9 to 46,700 (or 52.2 to 25,200) ng/kg bw/day. Depending on the reference dose, we found that approximately 5% of the individuals exceeded the limit (i.e., 2200 ng/kg bw/day) for TCEP intake. To our knowledge, this is the first nationwide baseline survey to determine urinary levels of mOPs in Chinese residents.

A computer aided diagnosis system for thyroid disease using extreme learning machine.

In this paper, we present an effective and efficient computer aided diagnosis (CAD) system based on principle component analysis (PCA) and extreme learning machine (ELM) to assist the task of thyroid disease diagnosis. The CAD system is comprised of three stages. Focusing on dimension reduction, the first stage applies PCA to construct the most discriminative new feature set. After then, the system switches to the second stage whose target is model construction. ELM classifier is explored to train an optimal predictive model whose parameters are optimized. As we known, the number of hidden neurons has an important role in the performance of ELM, so we propose an experimental method to hunt for the optimal value. Finally, the obtained optimal ELM model proceeds to perform the thyroid disease diagnosis tasks using the most discriminative new feature set and the optimal parameters. The effectiveness of the resultant CAD system (PCA-ELM) has been rigorously estimated on a thyroid disease dataset which is taken from UCI machine learning repository. We compare it with other related methods in terms of their classification accuracy. Experimental results demonstrate that PCA-ELM outperforms other ones reported so far by 10-fold cross-validation method, with the mean accuracy of 97.73% and with the maximum accuracy of 98.1%. Besides, PCA-ELM performs much faster than support vector machines (SVM) based CAD system. Consequently, the proposed method PCA-ELM can be considered as a new powerful tools for diagnosing thyroid disease with excellent performance and less time.