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Estrogens, particularly 17β-estradiol, are prevalent endocrine-disrupting chemicals in aquatic environments, posing risks to ecosystems and human health. Biodegradation is considered one of the most effective and environmentally friendly methods for removing estrogen. In this study, a novel bacterial strain, Microbacterium proteolyticum ZJSU01, was isolated from pig manure. It completely degraded 5 mg/L of 17β-estradiol (E2) within 4 h, as well as its major transformation product, estrone (E1). The strain ZJSU01 displayed strong adaptability to high temperatures (37℃, 42℃) and a broad pH range (6–11), E2 (5 mg/L) could be completely removed by the strain under these conditions. Transformation intermediates were analyzed using UHPLC and HPLC-Q-TOF–MS to identify key metabolites and trace the degradation pathways. Four potential degradation pathways were identified, including the 4,5-seco pathway, which is widely conserved in most E2-degrading bacteria. Whole-genome sequencing predicted a chromosome with a size of 3,828,432 bp, and a series of functional genes, and transcriptomics analysis identified several genes involved in E2 degradation. The budC gene, a member of the short-chain dehydrogenases/reductases (SDRs) family, was identified as critical for E2 degradation and exhibited a nearly 170-fold upregulation. Meanwhile, genes such as fdeE and catA were associated with downstream degradation. Microbacterium proteolyticum ZJSU01 demonstrated strong acid–base and high-temperature resilience, highlighting its strong potential for practical applications due to its degradation capability and adaptability. This strain could be applied in wastewater treatment to effectively remove estrogenic pollutants from contaminated water. Key points • Microbacterium proteolyticum ZJSU01 removed 100% of E2 (10、5、1 mg/L) within 4 h. • Strain ZJSU01 showed great tolerance to high temperature and acid–base conditions. • A novel gene, budC , was identified as the primary driver of E2 degradation by ZJSU01.

To support dual-carbon objectives and enhance the accuracy of rooftop distributed photovoltaic (PV) planning, this study proposes a multidimensional coupled evaluation framework that integrates an improved rooftop segmentation network (CESW-TransUNet), a residual-fusion ensemble, and physics-based shading and performance simulations, thereby correcting the bias of conventional 2-D area–based methods. First, CESW-TransUNet, equipped with convolution-enhanced modules, achieves robust multi-scale rooftop extraction and reaches an IoU of 78.50% on the INRIA benchmark, representing a 2.27 percentage point improvement over TransUNet. Second, the proposed residual fusion strategy adaptively integrates multiple models, including DeepLabV3+ and PSPNet, further improving the IoU to 79.85%. Finally, by coupling Ecotect-based shadow analysis with PVsyst performance modeling, the framework systematically quantifies dynamic inter-building shading, rooftop equipment occupancy, and installation suitability. A case study demonstrates that the method reduces the systematic overestimation of annual generation by 27.7% compared with traditional 2-D assessments. The framework thereby offers a quantitative, end-to-end decision tool for urban rooftop PV planning, enabling more reliable evaluation of generation and carbon-mitigation potential.

We identified an individual who was coinfected with two SARS-CoV-2 variants of concern, the Beta and Delta variants. The ratio of the relative abundance between the two variants was maintained at 1:9 (Beta:Delta) in 14 days. Furthermore, possible evidence of recombinations in the Orf1ab and Spike genes was found.

Background Serological test is helpful in confirming and tracking infectious diseases in large population with the advantage of fast and convenience. Using the specific epitope peptides identified from the whole antigen as the detection antigen is sensitive and relatively economical. The development of epitope peptide-based detection kits for COVID-19 patients requires comprehensive information about epitope peptides. But the data on B cell epitope of SARS-CoV-2 spike protein is still limited. More importantly, there is a lack of serological data on the peptides in the population. In this study, we aimed to identify the B cell epitope peptides of spike protein and detect the reactivity in serum samples, for further providing data support for their subsequent serological applications. Results Two B cell linear epitopes, P104 and P82, located in non-RBD region of SARS-CoV-2 S protein were identified by indirect ELISA screening of an overlapping peptide library of the S protein with COVID-19 patients’ convalescent serum. And the peptides were verified by testing with 165 serum samples. P104 has not been reported previously; P82 is contained in peptide S21P2 reported before. The positive reaction rates of epitope peptides S14P5 and S21P2, the two non-RBD region epitopes identified by Poh et al., and P82 and P104 were 77.0%, 73.9%, 61.2% and 30.3%, respectively, for 165 convalescent sera, including 30 asymptomatic patients. Although P104 had the lowest positive rate for total patients (30.3%), it exhibited slight advantage for detection of asymptomatic infections (36.7%). Combination of epitopes significantly improved the positive reaction rate. Among all combination patterns, (S14P5 + S21P2 + P104) pattern exhibited the highest positive reaction rate for all patients (92.7%), as well as for asymptomatic infections (86.7%), confirming the feasibility of P104 as supplementary antigen for serological detection. In addition, we analyzed the correlation between epitopes with neutralizing antibody, but only S14P5 had a medium positive correlation with neutralizing antibody titre (r s  = 0.510, P  < 0.01). Conclusion Our research proved that epitopes on non-RBD region are of value in serological detection especially when combination more than one epitope, thus providing serological reaction information about the four epitopes, which has valuable references for their usage.

Guillain-Barré Syndrome (GBS) is a severe paralytic neuropathy associated with virus infections such as Zika virus and Chikungunya virus. There were also case reports of dengue fever preceding GBS. With the aim to understand the mechanisms of GBS and dengue outbreaks, this ecological study investigates the relationships between GBS, dengue, meteorological factors in Hong Kong and global climatic factors from January 2000 to June 2016. The correlations between GBS, dengue, Multivariate El Niño Southern Oscillation Index (MEI) and local meteorological data were explored by Spearman's Rank correlations and cross-correlations. Three Poisson regression models were fitted to identify non-linear associations among GBS, dengue and MEI. Cross wavelet analyses were applied to infer potential non-stationary oscillating associations among GBS, dengue and MEI. We report a substantial increasing of local GBS and dengue cases (mainly imported) in recent year in Hong Kong. The seasonalities of GBS and dengue are different, in particular, GBS is low while dengue is high in the summer. We found weak but significant correlations between GBS and local meteorological factors. MEI could explain over 17% of dengue's variations based on Poisson regression analyses. We report a possible non-stationary oscillating association between dengue fever and GBS cases in Hong Kong. This study has led to an improved understanding about the timing and ecological relationships between MEI, GBS and dengue.

Varicella (chickenpox) is a highly transmissible childhood disease. Between 2010 and 2015, it displayed two epidemic waves annually among school populations in Shenzhen, China. However, their transmission dynamics remain unclear and there is no school-based vaccination programme in Shenzhen to-date. In this study, we developed a mathematical model to compare a school-based vaccination intervention scenario with a baseline (i.e. no intervention) scenario. Data on varicella reported cases were downloaded from the Infectious Disease Reporting Information Management System. We obtained the population size, age structure of children aged 15 or under, the class and school distribution from Shenzhen Education Bureau. We developed an Agent-Based Susceptible-Exposed-Infectious-Recovered (ABM-SEIR) Model that considered within-class, class-to-class and out-of-school transmission modes. The intervention scenario was that school-wide vaccination intervention occurred when an outbreak threshold was reached within a school. We varied this threshold level from five to ten cases. We compared the reduction of disease outbreak size and estimated the key epidemiological parameters under the intervention strategy. Our ABM-SEIR model provided a good model fit to the two annual varicella epidemic waves from 2013 to 2015. The transmission dynamics displayed strong seasonality. Our results suggested that a school-based vaccination strategy could effectively prevent large outbreaks at different thresholds. There was a considerable increase in reported varicella cases from 2013 to 2015 in Shenzhen. Our modelling study provided important theoretical support for disease control decision making during school outbreaks and the development of a school-based vaccination programme.

To investigate the characteristics of polycyclic aromatic hydrocarbons (PAHs) during haze episodes in warm seasons, daily PM 2.5 and gaseous samples were collected from March to September 2015 in Hangzhou, China. Daily samples were further divided into four groups by the definition of haze according to visibility and relative humidity (RH), including non-haze (visibility, >10 km), light haze (visibility, 8–10 km, RH <90 %), medium haze (visibility, 5–8 km, RH <90 %), and heavy haze (visibility, <5 km, RH <90 %). Significantly higher concentrations of PM 2.5 -bound PAHs were found in haze days, but the mean PM 2.5 -bound PAH concentrations obviously decreased with the aggravation of haze pollution from light to heavy. The gas/particle partitioning coefficients of PAHs decreased from light-haze to heavy-haze episodes, which indicated that PM 2.5 -bound PAHs were restricted to adhere to the particulate phase with the aggravation of haze pollution. Absorption was considered the main mechanism of gas/particle partitioning of PAHs from gaseous to particulate phase. Analysis of air mass transport indicated that the PM 2.5 -bound PAH pollution in haze days was largely from regional sources but also significantly affected by long-range air mass transport. The inhalation cancer risk associated with PAHs exceeded the acceptable risk level markedly in both haze and non-haze days.

A series of organic-inorganic composite catalysts were prepared by modifying tungstophosphoric acid (H PW ) and propyl sulfonic acid-functionalized ionic complex. The obtained water-soluble catalysts were well characterized by Fourier transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, and nuclear magnetic resonance, and investigated for their performance as homogeneous catalysts for selective oxidation of benzyl alcohol (BzOH) with hydrogen peroxide (H ) in water. Among them, the [DMBPSH]H PW catalyst exhibited the best oxidative activity with a desirable benzaldehyde (BzH) selectivity of 97.0% and an excellent BzOH conversion of 98.5%. Further kinetic studies and model analysis by response surface methodology revealed that alcohols’ oxidation reaction followed an apparent order of 2.2 with an activation energy of 36.18 kJ/mol. And the optimal reaction conditions were established as follows: BzOH/H molar ratio of 1:1.7, amount of catalyst 5.4 wt%, reaction time 3.9 h, amount of water 24 ml, and a maximum yield of BzH of 95.8%. Under optimum conditions, [DMBPSH]H PW catalyst showed a superior catalytic efficiency and reusability due to strong acidity and excellent surface activity.

Managing recovered COVID-19 patients with recurrent-positive SARS-CoV-2 RNA test results is challenging. We performed a population-based observational study to characterize the viral RNA level and serum antibody responses in recurrent-positive patients and evaluate their viral transmission risk. Of 479 recovered COVID-19 patients, 93 (19%) recurrent-positive patients were identified, characterized by younger age, with a median discharge-to-recurrent-positive length of 8 days. After readmission, recurrent-positive patients exhibited mild (28%) or absent (72%) symptoms, with no disease progression. The viral RNA level in recurrent-positive patients ranged from 1.8 to 5.7 log10 copies/mL (median: 3.2), which was significantly lower than the corresponding values at disease onset. There are generally no significant differences in antibody levels between recurrent-positive and non-recurrent-positive patients, or in recurrent-positive patients over time (before, during, or after recurrent-positive detection). Virus isolation of nine representative specimens returned negative results. Whole genome sequencing of six specimens yielded only genomic fragments. 96 close contacts and 1,200 candidate contacts of 23 recurrent-positive patients showed no clinical symptoms; their viral RNA (1,296/1,296) and antibody (20/20) tests were negative. After full recovery (no longer/never recurrent-positive), 60% (98/162) patients had neutralizing antibody titers of ≥1:32. Our findings suggested that an intermittent, non-stable excretion of low-level viral RNA may result in recurrent-positive occurrence, rather than re-infection. Recurrent-positive patients pose a low transmission risk, a relatively relaxed management of recovered COVID-19 patients is recommended.

Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, prompted heightened surveillance in Shenzhen, China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control measures. From Jan 14 to Feb 12, 2020, the Shenzhen Center for Disease Control and Prevention identified 391 SARS-CoV-2 cases and 1286 close contacts. We compared cases identified through symptomatic surveillance and contact tracing, and estimated the time from symptom onset to confirmation, isolation, and admission to hospital. We estimated metrics of disease transmission and analysed factors influencing transmission risk. Cases were older than the general population (mean age 45 years) and balanced between males (n=187) and females (n=204). 356 (91%) of 391 cases had mild or moderate clinical severity at initial assessment. As of Feb 22, 2020, three cases had died and 225 had recovered (median time to recovery 21 days; 95% CI 20–22). Cases were isolated on average 4·6 days (95% CI 4·1–5·0) after developing symptoms; contact tracing reduced this by 1·9 days (95% CI 1·1–2·7). Household contacts and those travelling with a case were at higher risk of infection (odds ratio 6·27 [95% CI 1·49–26·33] for household contacts and 7·06 [1·43–34·91] for those travelling with a case) than other close contacts. The household secondary attack rate was 11·2% (95% CI 9·1–13·8), and children were as likely to be infected as adults (infection rate 7·4% in children <10 years vs population average of 6·6%). The observed reproductive number (R) was 0·4 (95% CI 0·3–0·5), with a mean serial interval of 6·3 days (95% CI 5·2–7·6). Our data on cases as well as their infected and uninfected close contacts provide key insights into the epidemiology of SARS-CoV-2. This analysis shows that isolation and contact tracing reduce the time during which cases are infectious in the community, thereby reducing the R. The overall impact of isolation and contact tracing, however, is uncertain and highly dependent on the number of asymptomatic cases. Moreover, children are at a similar risk of infection to the general population, although less likely to have severe symptoms; hence they should be considered in analyses of transmission and control. Emergency Response Program of Harbin Institute of Technology, Emergency Response Program of Peng Cheng Laboratory, US Centers for Disease Control and Prevention.