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Poly(ethylene terephthalate) (PET), extensively employed in bottles, film, and fiber manufacture, has generated persistent environmental contamination due to its non-degradable nature. The resolution of this issue requires the conversion of waste PET into valuable products, often achieved through depolymerization into monomers. However, the laborious purification procedures involved in the extraction of monomers pose challenges and constraints on the complete utilization of PET. Herein, a strategy is demonstrated for the polymer-to-polymer upcycling of waste PET into high-value biodegradable and programmable materials named PEXT. This process involves reversible transesterifications dependent on ester bonds, wherein commercially available X-monomers from aliphatic diacids and diols are introduced, utilizing existing industrial equipment for complete PET utilization. PEXT features a programmable molecular structure, delivering tailored mechanical, thermal, and biodegradation performance. Notably, PEXT exhibits superior mechanical performance, with a maximal elongation at break of 3419.2 % and a toughness of 270.79 MJ m -3 . These characteristics make PEXT suitable for numerous applications, including shape-memory materials, transparent films, and fracture-resistant stretchable components. Significantly, PEXT allows closed-loop recycling within specific biodegradable analogs by reprograming PET or X-monomers. This strategy not only offers cost-effective advantages in large-scale upcycling of waste PET into advanced materials but also demonstrates its enormous prospect in environmental conservation., (© 2024 Wiley-VCH GmbH.)

The development of photocatalysts plays a pivotal role in facilitating the production of green hydrogen energy through water splitting. In this study, one-dimensional (1D) organic-inorganic ZnCdS(EDA)/Ni@NiO (EDA: ethylenediamine) nanorods were prepared by combining organic molecules of EDA into ZnCdS. The EDA molecule possesses two amino functional groups with strong electron-donating capacity, thereby facilitating electron transfer to ZnCdS(EDA)/Ni@NiO and enabling efficient hydrogen evolution through photocatalytic water splitting. The H 2 evolution rate of ZnCdS(EDA)/Ni@NiO was 159 μmol g -1 h -1 in the absence of sacrificial agents, and its H 2 evolution rate in the system with EDA as the sacrificial agent can reach 5760 μmol g -1 h -1 . The combination of EDA, a S vacancy, and heterojunction was proved to be the main factor for improving the separation and transfer rate of photogenerated carriers. The incorporation of ZnCdS(EDA)/Ni@NiO enhances the participation of photogenerated electrons in the photocatalytic hydrogen evolution reaction, thereby improving the overall photocatalytic activity. The synthesis of this one-dimensional composite catalyst holds great potential for advancing the development of efficient photocatalytic materials.

Unsupervised image segmentation is a technique that divides an image into distinct regions or objects without prior labeling. This approach offers flexibility and adaptability to various types of image data. Particularly for large datasets, it eliminates the need for manual labeling, thereby it presents advantages in terms of time and labor costs. However, when applied to retinal image segmentation, challenges arise due to variations in data, presence of noise, and manual threshold adjustments, which can lead to over-segmentation or under-segmentation of small blood vessel boundaries and endpoints. In order to enhance the precision and accuracy of retinal image segmentation, we propose a novel image supervised segmentation network based on three-path Unet model.Firstly, the Haar wavelet transform is employed to extract high-frequency image information, which forms the foundation for the proposed HaarNet, a Unet-inspired architecture. Next, the HaarNet is integrated with the Unet and SegNet frameworks to develop a three-path Unet model, referred to as TP-Unet. Finally, the model is further refined into TP-Unet+AE+DSL by incorporating the advantages of auto-encoding (AE) and deep supervised learning (DSL) techniques, thereby enhancing the overall performance of the system. To evaluate the effectiveness of our proposed model, we conduct experiments using the DRIVE and CHASE public datasets. On the DRIVE dataset, our recommended model achieves a Dice coefficient of 0.8291 and a sensitivity index of 0.8184. These results significantly outperform the Unet model by [Formula: see text] and [Formula: see text], respectively. Furthermore, our model demonstrates excellent performance on the CHASE dataset, with a Dice coefficient of 0.8162, a sensitivity of 0.8242, and an accuracy of 0.9664. These metrics surpass the Unet model by [Formula: see text], [Formula: see text], and [Formula: see text], respectively. Our proposed model provides more accurate and reliable results for retinal vessel segmentation, which holds significant potential for assisting doctors in their diagnosis., (© 2023. The Author(s).)

Liver cancer is one of the leading causes of cancer-related deaths worldwide. Automatic liver and tumor segmentation are of great value in clinical practice as they can reduce surgeons' workload and increase the probability of success in surgery. Liver and tumor segmentation is a challenging task because of the different sizes, shapes, blurred boundaries of livers and lesions, and low-intensity contrast between organs within patients. To address the problem of fuzzy livers and small tumors, we propose a novel Residual Multi-scale Attention U-Net (RMAU-Net) for liver and tumor segmentation by introducing two modules, i.e., Res-SE-Block and MAB. The Res-SE-Block can mitigate the problem of gradient disappearance by residual connection and enhance the quality of representations by explicitly modeling the interdependencies and feature recalibration between the channels of features. The MAB can exploit rich multi-scale feature information and capture inter-channel and inter-spatial relationships of features simultaneously. In addition, a hybrid loss function, that combines focal loss and dice loss, is designed to improve segmentation accuracy and speed up convergence. We evaluated the proposed method on two publicly available datasets, i.e., LiTS and 3D-IRCADb. Our proposed method achieved better performance than the other state-of-the-art methods, with dice scores of 0.9552 and 0.9697 for LiTS and 3D-IRCABb liver segmentation, and dice scores of 0.7616 and 0.8307 for LiTS and 3D-IRCABb liver tumor segmentation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Wastewater-based epidemiology (WBE) has drawn great attention since the Coronavirus disease 2019 (COVID-19) pandemic, not only due to its capability to circumvent the limitations of traditional clinical surveillance, but also due to its potential to forewarn fluctuations of disease incidences in communities. One critical application of WBE is to provide "early warnings" for upcoming fluctuations of disease incidences in communities which traditional clinical testing is incapable to achieve. While intricate models have been developed to determine early warnings based on wastewater surveillance data, there is an exigent need for straightforward, rapid, broadly applicable methods for health departments and partner agencies to implement. Our purpose in this study is to develop and evaluate such early-warning methods and clinical-case peak-detection methods based on WBE data to mount an informed public health response. Throughout an extended wastewater surveillance period across Detroit, MI metropolitan area (the entire study period is from September 2020 to May 2022) we designed eight early-warning methods (three real-time and five post-factum). Additionally, we designed three peak-detection methods based on clinical epidemiological data. We demonstrated the utility of these methods for providing early warnings for COVID-19 incidences, with their counterpart accuracies evaluated by hit rates. "Hit rates" were defined as the number of early warning dates (using wastewater surveillance data) that captured defined peaks (using clinical epidemiological data) divided by the total number of early warning dates. Hit rates demonstrated that the accuracy of both real-time and post-factum methods could reach 100 %. Furthermore, the results indicate that the accuracy was influenced by approaches to defining peaks of disease incidence. The proposed methods herein can assist health departments capitalizing on WBE data to assess trends and implement quick public health responses to future epidemics. Besides, this study elucidated critical factors affecting early warnings based on WBE amid the COVID-19 pandemic., Competing Interests: Declaration of competing interest All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 10 2 genomic copies/L to 6.87 × 10 3 gc/L and N2 values ranging from 1.91 × 10 2 gc/L to 6.45 × 10 3 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Wastewater-based epidemiology (WBE) is useful in predicting temporal fluctuations of COVID-19 incidence in communities and providing early warnings of pending outbreaks. To investigate the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in communities, a 12-month study between September 1, 2020, and August 31, 2021, prior to the Omicron surge, was conducted. 407 untreated wastewater samples were collected from the Great Lakes Water Authority (GLWA) in southeastern Michigan. N1 and N2 genes of SARS-CoV-2 were quantified using RT-ddPCR. Daily confirmed COVID-19 cases for the City of Detroit, and Wayne, Macomb, Oakland counties between September 1, 2020, and October 4, 2021, were collected from a public data source. The total concentrations of N1 and N2 genes ranged from 714.85 to 7145.98 gc/L and 820.47 to 6219.05 gc/L, respectively, which were strongly correlated with the 7-day moving average of total daily COVID-19 cases in the associated areas, after 5 weeks of the viral measurement. The results indicate a potential 5-week lag time of wastewater surveillance preceding COVID-19 incidence for the Detroit metropolitan area. Four statistical models were established to analyze the relationship between SARS-CoV-2 concentrations in wastewater and COVID-19 incidence in the study areas. Under a 5-week lag time scenario with both N1 and N2 genes, the autoregression model with seasonal patterns and vector autoregression model were more effective in predicting COVID-19 cases during the study period. To investigate the impact of flow parameters on the correlation, the original N1 and N2 gene concentrations were normalized by wastewater flow parameters. The statistical results indicated the optimum models were consistent for both normalized and non-normalized data. In addition, we discussed parameters that explain the observed lag time. Furthermore, we evaluated the impact of the omicron surge that followed, and the impact of different sampling methods on the estimation of lag time., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

A synchronous multi-angle scattered light field measurement system is constructed in this study to overcome issues with current systems in the field of multi-angle remote sensing. A mathematical model of the scattered light field measurement was established. An off-axis catadioptric optical system was designed to satisfy hemispheric spatial scattered light field measurements in a zenith angle range of 68°. The off-axis calibration model was established, and the spatial relationship was calibrated. The measurement accuracy was calibrated via an integrating sphere light source, and the maximum measurement relative error was -3.71 % . The scattered light field of the reference diffuse reflective target plate Labsphere Permaflect-50 and 304 stainless steel was simulated under an incident light irradiation range within the zenith angle of -23.5 ∘ to +23.5 ∘ , and synchronous measurement of the multi-angle scattered light field of the sample was realized. The measurement system could provide technical support for building the complex model of multi-angle reflection/radiation from the earth's surface, multi-angle sensor radiation calibration, and improvement of the physical parameter inversion accuracy of observation targets.

The bidirectional reflection distribution function (BRDF) is among the most effective means to study the phenomenon of light-object interaction. It can precisely describe the characteristics of spatial reflection of the target surface, and has been applied to aerial remote sensing, imaging technology, materials analysis, and computer rendering technology. This study provides a comprehensive review of the development of devices to measure the BRDF. We gathered research in the area by using the Web of Science Core Collection, and show that work on the BDRF has been ongoing in the last 30 years. We also describe some typical measurement devices for the BRDF proposed in the literature. Finally, we summarise outstanding problems related to BRDF measurement and propose directions of future research in the area.

Background: Ivabradine selectively inhibits the If current, reducing the heart rate and protecting against myocardial ischemia/reperfusion injury. We investigated the effects of ivabradine on post-resuscitation myocardial function in a porcine model of cardiopulmonary resuscitation., Methods and Results: Ventricular fibrillation was induced and untreated for 8 min while defibrillation was attempted after 6 min of cardiopulmonary resuscitation in anesthetized domestic swine. Then the animals were randomized into ivabradine and placebo groups (n = 5 each). Ivabradine and saline were administered at the same volume 5 min after Return of Spontaneous Circulation, followed by continuous intravenous infusion at 0.5 mg/kg for 480 min. Hemodynamic parameters were continuously recorded. Myocardial function was assessed by echocardiography at baseline and at 60, 120, 240, 480 min and 24 h after resuscitation. The serum levels of N-terminal pro-brain natriuretic peptide (NT-proBNP) and cardiac troponin I (cTnI) were measured by commercial enzyme-linked immunosorbent assay kits. Animals were killed 24 h after resuscitation, and all myocardial tissue was removed for histopathological analysis. The heart rate was significantly reduced from 1 h after resuscitation in the ivabradine group (all P < 0.05). The post-resuscitation mitral E/A and E/e' velocity ratios and left ventricular ejection fraction were significantly better in the ivabradine than placebo group (P < 0.05). The serum levels of myocardial injury biomarkers (NT-proBNP, cTnI) and the myocardial biopsy scores were significantly lower in the ivabradine than placebo group (P < 0.05). Neurological deficit scores were lower in the IVA group at PR 24 h (P < 0.05)., Conclusions: Ivabradine improved post-resuscitation myocardial dysfunction, myocardial injury, and post-resuscitation cerebral function, and also slowed the heart rate in this porcine model.

Low-cost airborne particle sensors are gaining attention for monitoring human exposure to indoor particulate matter. This study aimed to establish the concentrations at which these commercially available sensors can be expected to report accurate concentrations. We exposed five types of commercial integrated devices and three types of "bare" low-cost particle sensors to a range of concentrations generated by three different sources. We propose definitions of upper and lower bounds of functional range based on the relationship between a given sensor's output and that of a reference instrument during a laboratory experiment. Experiments show that the lower bound can range from approximately 3 to 15 μg/m 3 . At greater concentrations, sensor output deviates from linearity at approximately 300-3000 μg/m 3 . We also conducted a simulation campaign to analyze the effect of this limitation on functional range on the accuracy of exposure readings given by these devices. We estimate that the upper bound results in minimal inaccuracy in exposure quantification, and the lower bound can result in as much as a 50% error in approximately 10% of US homes., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Purpose: We investigated the protective effects and the underlying mechanisms through which recombinant human brain natriuretic peptide (rhBNP) acts on postresuscitation myocardial dysfunction (PRMD) in the cardiac arrest (CA) model., Methods: Ventricular fibrillation was induced and untreated for 6 min. And the time of cardiopulmonary resuscitation was 8 min, after which defibrillation was attempted in this rat model. 24 Sprague Dawley rats (450-550g) were randomized into cardiopulmonary resuscitation (CPR) + rhBNP and CPR + placebo groups after restoration of spontaneous circulation (ROSC). rhBNP was infused at PR 30 min (loading dose: 1.5  µ g/kg, 3 min; maintenance dose: 0.01  µ g/kg, 3 min; maintenance dose: 0.01  α (TNF- α (TNF- α (TNF- κ B (NF- κ B (NF., Results: The administration of rhBNP attenuated the severity of PRMD and myocardial tissue injuries, with improvement of MAP (mean arterial blood pressure), ETCO 2 (end-tidal CO 2 ), serum level of NT-proBNP, EF, CO, and MPI values. The serum levels and protein expression levels in myocardial tissue of IL-6 and TNF- α (TNF- κ B (NF., Conclusion: Our research demonstrated that the administration of rhBNP attenuated the severity of PRMD and myocardial tissue injuries and increased the 24 h survival rate in this CA model. rhBNP administration also reduced the serum and myocardial tissue levels of IL-6 and TNF- α after ROSC, likely due to the suppression of the TLR4/NF- κ B signaling pathway and the regulation of inflammatory mediator secretion. α (TNF- κ B (NF., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2020 Min Yang et al.)

Objective: To investigate the protective function of endovascular cooling method on post-resuscitation syndrome (PRS) in porcine cardiac arrest (CA) model and its mechanism., Methods: Ventricular fibrillation (VF) was electrically induced and untreated for 8 minutes in 15 healthy male porcines, cardiopulmonary resuscitation (CPR) was then initiated. All successful recovery animals were randomly divided into two groups by random number table. In normal temperature group, the core temperature was maintained at (38.0±0.5) centigrade for 12 hours. In mild hypothermia group, the mild hypothermia treatment was initiated at 5 minutes after successful resuscitation, the treatment of rapid endovascular cooling was performed to reach the target cooling temperature of (33.0±1.0) centigrade, and then maintained until 6 hours after resuscitation. Rewarming was implemented at the rate of 0.7 centigrade/h until the body temperature reached (38.0±0.5) centigrade. Hemodynamic parameters including heart rate (HR), mean arterial blood pressure (MAP), cardiac output (CO) were continually monitored. Right femoral vein blood was collected before VF and 1, 2, 4, 6, 12 and 24 hours after resuscitation, respectively, and the serum concentrations of E-selectin, soluble thrombomodulin (sTM), and interleukin-1β (IL-1β) were determined with enzyme linked immunosorbent assay (ELISA). The survival of porcines at 24 hours after resuscitation was observed, and the neurological deficit score (NDS) was calculated for the surviving porcines. All animals were sacrificed, and brain, heart and lung tissues were collected, after hematoxylin and eosin (HE) staining, the histopathology changes were evaluated under a light microscopy., Results: After 8-minute VF, 14 porcines were resuscitated successfully, 7 porcines in normal temperature group and 7 in mild hypothermia group respectively, with the resuscitation success rate of 93.3%. There was no significant difference in body weigh, core temperature, hemodynamics, or blood lactate as well as duration of CPR and the number of defibrillations between the two groups. The core temperature of normal temperature group was maintained at (38.0±0.5) centigrade, while in mild hypothermia group, the hypothermia was reduced to the hypothermia range (33.0±1.0) centigrade until 6 hours, then rewarmed to normothermia gradually [(38.0±0.5) centigrade]. Compared with those before VF, HR was significantly increased after resuscitation in both groups, and MAP and CO were decreased, then they tended to normal. There was no significant difference in hemodynamic parameter at all time points between the two groups. Compared with those before VF, the levels of E-selectin and sTM in serum of the two groups were increased significantly at 1 hour after resuscitation, and they were decreased gradually after reaching the peak at 6 hours, and IL-1β was increased continuously with time. There was no significant difference in E-selectin (μg/L: 1.34±0.52 vs. 1.60±0.61), sTM (μg/L: 19.13±0.34 vs. 19.24±0.73), or IL-1β (ng/L: 25.73±0.87 vs. 25.32±0.25) before VF between normal temperature group and mild hypothermia group (all P > 0.05). The levels of E-selection, sTM and IL-1β in mild hypothermia group were significantly lower than those in normal temperature group from 2 hours after resuscitation [E-selection (μg/L): 11.15±2.73 vs. 16.04±3.23, sTM (μg/L): 49.67±3.32 vs. 62.22±1.85, IL-1β (ng/L): 140.51±6.66 vs. 176.29±18.51, all P < 0.05], and E-selection decreased to the baseline level at 12 hours (μg/L: 1.17±0.65 vs. 1.60±0.61, P > 0.05). The 24-hour survival rates of two groups were both 100%. The NDS score of mild hypothermia group was obviously lower than that of normal temperature group (150.0±6.6 vs. 326.4±12.3, P < 0.05). In normal temperature group, neuronal cell necrosis was observed in the cerebral cortex at 24 hours after resuscitation, and nucleus was deeply stained. The myocardial necrosis and alveolar collapse was found. Meanwhile the infiltration of inflammatory cell could be found in the myocardium and alveolar. The brain, lung and myocardium injury were significantly milder in mild hypothermia group as compared with those in normal temperature group., Conclusions: The intravascular cooling therapy was a safe and effective method for inducing mild hypothermia after resuscitation. This cooling effect was fast and reliable, and the rewarming speed was controllable and stable. The protective mechanism of mild hypothermia on PRS may be related to inhibiting systemic inflammatory response and reducing vascular endothelial cell injury.

Moxibustion at Guanyuan (CV 4) can produce biological effects, mainly including local effects, targeting organ effects, systemic effects. The biological effects of moxibustion at Guanyuan (CV 4) are related to stimulation parameters and health or pathological nature of the objects, and the effects show acupoint specificity. Its research of local effects should be attached importance to and the acupoint specificity needs to be ascertained, as well as the relationships between the biological effects and stimulation parameters, and between the effects and health or pathological nature of the objects.

In order to optimize acupuncture treatment protocol for functional defecation disorders, literature during past 20 years is reviewed, and factors which influences acupuncture therapeutic effect are analyzed from aspects of acupoint, acupuncture technique, etc. As for the selection of acupoint, more attention should be paid on the use of Baliao, especially Zhongliao (BL 33) and Xialiao (BL 34); when Baliao is deeply needled, it is essential to acquire scientific technique. The relationship between acupuncture parameter (including electroacupuncture waveform and frequency), acupuncture techniques (including reinforcing and reducing technique, quantity of stimulation, etc. ) and acupuncture efficacy is complicated, and the scientific values of present research conclusion are in need, of further improvement. The diagnosis and treatment awareness on types of functional defecation should be strengthened, and the mental health of the constipation patients should be concerned. The combination of acupuncture and biofeedback training can have a synergistic effect, which is benefit to achieve a better long-term effect. Based on this, acupuncture treatment protocol for functional defecation disorders can be optimized to further improve the efficacy.

Background. Electroacupuncture (EA) has been reported to treat functional constipation (FC). The aim of this study was to investigate the efficacy and safety of EA with different needle insertion method for FC. Methods. Sixty-seven participants were randomly assigned to control (EA with shallow puncture) and EA (with deep puncture) groups. Every patient received 5 treatments per week in the first two weeks, then 3 treatments per week during the following six weeks. Complete spontaneous bowel movements (CSBM), spontaneous bowel movements (SBM), Bristol stool scores (BSS), and Patient Assessment of Constipation Quality of Life (PAC-QOL) were assessed. Results. Both shallow and deep EA significantly increased CSBM frequency compared to the baseline. CSBM was increased from 0.50 ± 0.59/wk to 2.00 ± 1.67/wk with deep EA and from 0.48 ± 0.59/wk to 1.33 ± 1.09/wk with shallow EA (P < 0.05, resp.). Similar finding was noted in SBM. Deep EA was more potent than shallow EA (P < 0.05) during the treatment period. No difference was found on BSS and PAC-QOL between two groups. Conclusion. It is effective and safe with EA to treat FC. Studies with large sample size and long-term observation are needed for further investigation.