Application of a single-cell-RNA-based biological-inspired graph neural network in diagnosis of primary liver tumors.

Single-cell technology depicts integrated tumor profiles including both tumor cells and tumor microenvironments, which theoretically enables more robust diagnosis than traditional diagnostic standards based on only pathology. However, the inherent challenges of single-cell RNA sequencing (scRNA-seq) data, such as high dimensionality, low signal-to-noise ratio (SNR), sparse and non-Euclidean nature, pose significant obstacles for traditional diagnostic approaches. The diagnostic value of single-cell technology has been largely unexplored despite the potential advantages. Here, we present a graph neural network-based framework tailored for molecular diagnosis of primary liver tumors using scRNA-seq data. Our approach capitalizes on the biological plausibility inherent in the intercellular communication networks within tumor samples. By integrating pathway activation features within cell clusters and modeling unidirectional inter-cellular communication, we achieve robust discrimination between malignant tumors (including hepatocellular carcinoma, HCC, and intrahepatic cholangiocarcinoma, iCCA) and benign tumors (focal nodular hyperplasia, FNH) by scRNA data of all tissue cells and immunocytes only. The efficacy to distinguish iCCA from HCC was further validated on public datasets. Through extending the application of high-throughput scRNA-seq data into diagnosis approaches focusing on integrated tumor microenvironment profiles rather than a few tumor markers, this framework also sheds light on minimal-invasive diagnostic methods based on migrating/circulating immunocytes.

Relationship between vaginal microbiota and chorioamnionitis: A prospective cohort study.

OBJECTIVE: This study aimed to determine the association between vaginal microbiota and chorioamnionitis and its predictive value. METHODS: Thirty pregnant women in their third trimester were prospectively recruited. The participants were categorized into three groups based on their clinical manifestations and placental pathology: the clinical chorioamnionitis group (IP group), the asymptomatic histological chorioamnionitis group (CP group), and the healthy control group (CN group). Basic data and medical history were collected from each participant. Vaginal samples were collected before delivery and analyzed using microbial diversity sequencing. RESULTS: No significant differences were observed in age, body mass index, and education among the groups (P > 0.05). However, the IP group exhibited higher rates of low birth weight (60 % vs 20 % vs 0 %, P = 0.008) and respiratory distress syndrome (50 % vs 20 % vs 0 %, P = 0.003) compared with the CP and CN groups. The Shannon index [2.09 (1.16-3.86) vs 0.84 (0.19-1.11) vs 0.44 (0.25-0.85), P = 0.009] and Simpson index [0.70 (0.41-0.81) vs 0.26 (0.04-0.39) vs 0.11 (0.05-0.29), P = 0.010] in the IP group were higher than those in the CN and CP groups. ß diversity analysis indicated that the microbial community structure differed among the three groups, with a 14.1 % variation associated with group differences (P = 0.002). At the genus level, the random forest model revealed that Lactobacillus, Dialister, Prevotella, Ligilactobacillus, and Anaerococcus had Gini indexes higher than 1. Further, linear discriminant analysis (LDA) demonstrated that the abundance of Lactobacillus crispatus in the IP group was lower than in the CN group (LDA >4.0, mean relative abundance 9.19 % vs 54.40 %, P = 0.031). The logistic regression analysis indicated that a decreased abundance of L. crispatus was associated with an increased risk of clinical chorioamnionitis. CONCLUSIONS: The reduction of L. crispatus and increasing trend of specific anaerobic groups are associated with the onset of chorioamnionitis, suggesting their potential value in chorioamnionitis identification. The vaginal microbiota could serve as a useful biomarker for predicting future disease and tailoring surveillance efforts. Additionally, it may present a viable target for developing prevention and therapeutic strategies.

Old people's preference for nursing homes in East China: a discrete choice experiment.

BACKGROUND: The aged people who live in nursing home are predicted to keep growing in the following decades. There are both quantitative imbalance and structural imbalance in the utilization of nursing homes in China. This study aimed to analyze old people's preference for nursing homes and help the government optimize resource allocation. METHODS: A discrete choice experiment (DCE) was conducted and six attributes of nursing homes including monthly fee, distance from home, geographical location, medical facilities, environment of nursing homes and nursing staff were determined. Respondents were recruited from Nantong and Yangzhou city, China. In each city, two communities or villages were randomly selected. In each community/village, about 65 old people were randomly selected. Analysis was conducted using mixed logit regression models to determine preferences for potential attributes. RESULTS: A total of 233 old people were included in the analysis. The findings indicated that all six attributes were statistically significant factors for participants. "Professional nursing staff" was the most important characteristic to participants, followed by "Medical facilities". Compared with female, the males preferred professional nursing staff (ß = 2.939 vs. ß = 2.643, P < 0.001), medical facilities (ß = 1.890 vs. ß = 1.498, P < 0.001), and the environment (ß = 0.752, P < 0.01). For different age groups, participants aged 60-69 didn't pay attention to distance and location, while those aged 80 and above only paid attention to professional nursing staff and medical facilities. CONCLUSIONS: The present study provides important insights into the characteristics of nursing home that are most preferred by old people. Authorities should take into account old people's preference in the planning, design and evaluation of nursing homes.

Multi-Group Polymer Coating on Zn Anode for High Overall Conversion Efficiency Photorechargeable Zinc-Ion Batteries.

The solar-driven photorechargeable zinc-ion batteries have emerged as a promising power solution for smart electronic devices and equipment. However, the subpar cyclic stability of the Zn anode remains a significant impediment to their practical application. Herein, poly(diethynylbenzene-1,3,5-triimine-2,4,6-trione) (PDPTT) was designed as a functional polymer coating of Zn. Theoretical calculations demonstrate that the PDPTT coating not only significantly homogenizes the electric field distribution on the Zn surface, but also promotes the ion-accessible surface of Zn. With multiple N and C=O groups exhibiting strong adsorption energies, this polymer coating reduces the nucleation overpotential of Zn, alters the diffusion pathway of Zn2+ at the anode interface, and decreases the corrosion current and hydrogen evolution current. Leveraging these advantages, Zn-PDPTT//Zn-PDPTT exhibits an exceptionally long cycling time (≥4300 h, 1 mA cm-2). Zn-PDPTT//AC zinc-ion hybrid capacitors can withstand 50,000 cycles at 5 A/g. Zn-PDPTT//NVO zinc-ion battery exhibits a faster charge storage rate, higher capacity, and excellent cycling stability. Coupling Zn-PDPTT//NVO with high-performance perovskite solar cells results in a 13.12 % overall conversion efficiency for the photorechargeable zinc-ion battery, showcasing significant value in advancing the efficiency and upgrading conversion of renewable energy utilization.

Research on layout model and construction planning of aged care institutions for disabled elders in China: based on Nanjing city data.

BACKGROUND: To meet the needs of diversified pension services and the construction of aged care institutions is one of the urgent livelihood issues in China. Under the major national needs of pension and care for the elderly, it is necessary to optimize the allocation of pension and care for the elderly resources, and formulate operational coping strategies and optimization plans. It is of great significance to deal with the urgent problem of population aging in a timely and scientific way. METHODS: The economic benefits and social costs of aged care institutions are regarded as objective functions. To satisfy the economic benefits, it is necessary to reduce the social costs, and its construction quantity can only be an integer. The multi-objective genetic algorithm is improved with integer programming, and the global optimal solution is achieved after several times of searching. Under the multi-objective optimization model, the improved genetic algorithm was combined with the superior and inferior solution distance method to solve the genetic algorithm, and the corresponding objective function value was obtained after rounding. Finally, Pareto optimal solution set is selected by multi-objective decision, and the result of construction planning is obtained. RESULTS: Based on multi-attribute decision analysis and taking three years as the construction cycle, the planning scheme of aged care institutions construction in each district of Nanjing in the next 15 years was proposed. In addition, considering the intelligent trend of future pension, the proportion of home-based pension is increasing year by year, and the model is promoted to meet the needs of diversified pension services. With the gradual increase of the elderly population in Nanjing, the proportion of intelligent home-based care has been increasing year by year since 2027, and the construction demand of aged care institutions has also increased. The number of construction at all levels rises gradually in each cycle, and the increase is more obvious after 2027. CONCLUSIONS: The layout and planning of aged care institutions proposed in this paper not only considers economic and environmental benefits, but also combines the current situation of aged care institutions in various districts of Nanjing. The model is reasonable and effective, and has practical application value. It will help China optimize the allocation of elderly care resources under the target of active aging, and scientifically and comprehensively deal with the problem of population aging.

Predicting of elderly population structure and density by a novel grey fractional-order model with theta residual optimization: a case study of Shanghai City, China.

BACKGROUND: Accurately predicting the future development trend of population aging is conducive to accelerating the development of the elderly care industry. This study constructed a combined optimization grey prediction model to predict the structure and density of elderly population. METHODS: In this paper, a GT-FGM model is proposed, which combines Theta residual optimization with fractional-order accumulation operator. Fractional-order accumulation can effectively weaken the randomness of the original data sequence. Meanwhile, Theta residual optimization can adjust parameter by minimizing the mean absolute error. And the population statistics of Shanghai city from 2006 to 2020 were selected for prediction analysis. By comparing with the other traditional grey prediction methods, three representative error indexes (MAE, MAPE, RMSE) were conducting for error analysis. RESULTS: Compared with the FGM model, GM (1,1) model, Verhulst model, Logistic model, SES and other classical prediction methods, the GT-FGM model shows significant forecasting advantages, and its multi-step rolling prediction accuracy is superior to other prediction methods. The results show that the elderly population density in nine districts in Shanghai will exceed 0.5 by 2030, among which Huangpu District has the highest elderly population density, reaching 0.6825. There has been a steady increase in the elderly population over the age of 60. CONCLUSIONS: The GT-FGM model can improve the prediction accuracy effectively. The elderly population in Shanghai shows a steady growth trend on the whole, and the differences between districts are obvious. The government should build a modern pension industry system according to the aging degree of the population in each region, and promote the balanced development of each region.

Research Hotspots and Trends in the Diagnosis of Chorioamnionitis: Based on Bibliometric Analysis from 2010 to 2022.

OBJECTIVE: This study aimed to conduct a bibliometric analysis of literature related to the diagnosis of chorioamnionitis (CAM) and to point out the current research progress, hotspots, and development trends of CAM research. STUDY DESIGN: Literature on the diagnosis of CAM from the Web of Science Core Collection (WoSCC) between 2010 and 2022 was retrieved. CiteSpace, VOSviewer, and Online Analysis Platform (OALM) were used to draw maps of authors, articles, journals, institutions, countries/regions, and keywords. RESULTS: A total of 312 articles were included, and the number of articles gradually increased over the study period. The author with the largest number of articles was Roberto Romero. The institution with the largest number of articles was Wayne State University School of Medicine, and the United States was the country that produced the largest number of articles. Analysis of keywords and outbreak words suggested that future research hotspots and trends may focus on early treatment of CAM and more precise, noninvasive, and more sensitive diagnoses. CONCLUSION: In this study, visualization software and data information mining were innovatively used to conduct a bibliometric analysis of articles in the field of CAM diagnosis, and the current status, hotspots, and development of this field were obtained. Future research hotspots may be the precision diagnosis and treatment of CAM. KEY POINTS: · There is no bibliometric study on CAM diagnosis in the existing literature.. · The prediction of CAM diagnosis is an important topic to improve maternal and infant prognosis.. · Bibliometrics can effectively guide the direction of future research..

Treatment of Post-Stroke Dysphagia with Repetitive Transcranial Magnetic Stimulation Based on the Bimodal Balance Recovery Model: A Pilot Study.

BACKGROUND: Brain plasticity and functional reorganization are the main mechanisms of stroke rehabilitation and the theoretical basis for transcranial magnetic therapy. Bimodal balance recovery model suggests that the structural integrity of neural pathways affects the functional reorganization mode of brain recovery after stroke. The principal neural pathway that innervates swallowing is the corticobulbar tract (CBT). The goal is to investigate the impact of corticobulbar tract integrity on swallowing function recovery in post-stroke dysphagia (PSD) patients treated with repetitive transcranial magnetic stimulation (rTMS). METHODS: Thirty-five patients with high CBT integrity (relative fractional anisotropy (rFA) >0.5) and 32 patients with low CBT integrity (rFA ≤0.5) were respectively assigned to three subgroups through a random number table: 5 Hz frequency rTMS group, 1 Hz frequency rTMS group, and Sham rTMS group. The Standardized Swallowing Assessment (SSA), Penetration Aspiration Scale (PAS), and Dysphagia Outcome Severity Scale (DOSS) were analyzed before and after therapy. RESULTS: Significant improvements in SSA (p < 0.05), PAS (p < 0.05), and DOSS scores (p < 0.05) were seen in the high frequency (HF) and low frequency (LF) groups compared with the Sham group for patients with high CBT integrity. Increased SSA (p < 0.05), PAS (p < 0.05), and DOSS scores (p < 0.05) demonstrated that the HF group achieved greater remediation than the LF and Sham groups for patients with low CBT integrity. CONCLUSIONS: Both 5 Hz and 1 Hz rTMS over the contralateral hemisphere are effective for the treatment of swallowing disorders for patients with high CBT integrity after stroke; 5 Hz rTMS over the contralateral hemisphere is more effective than 1 Hz and sham stimulation for patients with low CBT integrity.

A Visual Color Response Test Paper for the Detection of Hydrogen Sulfide Gas in the Air.

Hydrogen sulfide (H2S) is widely found in oil and natural gas wells and industrial wastewater tanks. Owing to its high toxicity, the monitoring and detection of H2S in the air is essential. However, recent techniques for the quantitative detection of H2S gas suffer from limitations such as high cost, complicated operation, and insufficient sensitivity, preventing their practical application in industry. Thus, we have developed a portable test paper for real-time and inexpensive monitoring of H2S gas by color changes. The test paper had a significantly low H2S detection limit of 200 ppb, which is considered safe for humans. Moreover, the color of the test paper did not change noticeably when exposed to CO2, N2, O2, and air environments, indicating that the test paper is selective for H2S gas and can be stored for a long time. In addition, we fitted a color difference linear model between the color difference values (ΔE) and the concentrations of H2S gas. The establishment of the linear model substantiates that the test paper can provide accurate intensity information when detecting H2S gas leakage.

Stable Lead-Free Tin Halide Perovskite with Operational Stability >1200 h by Suppressing Tin(II) Oxidation.

Sn-based perovskites are the most promising alternative materials for Pb-based perovskites to address the toxicity problem of lead. However, the development of SnII -based perovskites has been hindered by their extreme instability. Here, we synthesized efficient and stable lead-free Cs4 SnBr6 perovskite by using SnF2 as tin source instead of easily oxidized SnBr2 . The SnF2 configures a fluorine-rich environment, which can not only suppress the oxidation of Sn2+ in the synthesis, but also construct chemically stable Sn-F coordination to hinder the electron transfer from Sn2+ to oxygen within the long-term operation process. The SnF2 -derived Cs4 SnBr6 perovskite shows a high photoluminescence quantum yield of 62.8 %, and excellent stability against oxygen, moisture, and light radiation for 1200 h, representing one of the most stable lead-free perovskites. The results pave a new pathway to enhance the optical properties and stability of lead-free perovskite for high-performance light emitters.

Quality-adjusted survival in patients with metastatic colorectal cancer treated with fruquintinib in the FRESCO trial.

Aim: To assess whether the survival benefit of fruquintinib is quality-adjusted. Materials & methods: Data of 416 metastatic colorectal cancer patients from the Phase III FRESCO trial were used. The Quality-adjusted Time Without Symptoms or Toxicity (Q-TWiST) analysis assessed the quality-adjusted survival benefit of fruquintinib versus placebo, accounting for freedom from symptomatic disease and from severe side effects of treatment. Results: Fruquintinib significantly improved patients' Q-TWiST (difference: 2.23 [1.41, 3.04] months) versus placebo. The Q-TWiST gain was 28.3% in the base case and ranged from 16.7 to 39.9% in the threshold analysis, favoring fruquintinib. The Q-TWiST benefit was observed in fruquintinib-treated patients regardless of prior targeted therapy. Conclusion: Fruquintinib provides a clinically meaningful quality-adjusted survival benefit versus placebo as a third-line treatment for metastatic colorectal cancer patients.

Lay abstract The objective of the study was to assess the benefit of fruqintinib, a chemotherapy drug for patients with metastatic colorectal cancer (mCRC) who do not respond well to previous chemotherapy. The study considered both the time of survival and the quality of life after patients received fruqintinib. In measuring patients' quality of life, the study assessed the time that was free from cancer symptoms and any severe side effects from treatment. The study used data obtained from a Phase III clinical trial, FRESCO, which included 416 mCRC patients receiving fruqintinib or placebo. The results showed that fruqintinib significantly extended patients' symptom-free and side effects-free survival time by approximately 2 months and 5 days. Fruqintinib was 16.7­39.9% more effective than placebo in extending mCRC patients' high-quality life, regardless of prior targeted therapy.

Subgroup analysis by prior anti-VEGF or anti-EGFR target therapy in FRESCO, a randomized, double-blind, Phase III trial.

Background: FRESCO study demonstrated efficacy and safety of fruquintinib in metastatic colorectal cancer patients. Impact of prior targeted therapy (PTT) on efficacy and safety of fruquintinib was evaluated. Materials & methods: In this subgroup analysis of FRESCO trial, patients were divided into PTT and non-PTT subgroups, and efficacy and safety of fruquintinib were assessed, respectively. Results: In non-PTT subgroup, fruquintinib significantly prolonged overall survival (OS) and progression-free survival (PFS) of patients compared with placebo. In PTT subgroup, the median OS and PFS of patients in fruquintinib arm was significantly higher than those in placebo. Treatment-emergent adverse events (TEAEs) rates were similar in both subgroups. Conclusion: Fruquintinib demonstrated clinically meaningful improvement in OS, PFS, objective response rate, and disease control rate with manageable TEAEs in both subgroups. Clinical trial registration: NCT02314819 (ClinicalTrials.gov).

Lay abstract In this analysis of the FRESCO trial, we evaluated the efficacy and safety of fruquintinib in two different groups of patients (subgroups) with metastatic colorectal cancer - patients who received prior targeted therapy (PTT) and patients who did not (non-PTT). Of the 278 patients treated with fruquintinib, 111 patients received PTT. Patients treated with fruquintinib had longer overall survival and it took longer for their disease to worsen in both PTT and non-PTT subgroups compared with placebo. Patients in both subgroups treated with fruquintinib showed measurable reduction in their tumor size and disease control with similar side effects in patients of both the subgroups. These results suggest that fruquintinib is safe and effective in patients with metastatic colorectal cancer in both subgroups.

Predicting the trend of infectious diseases using grey self-memory system model: a case study of the incidence of tuberculosis.

OBJECTIVES: The prediction and early warning of infectious diseases is an important work in the field of public health. This study constructed the grey self-memory system model to predict the incidence trend of infectious diseases affected by many uncertain factors. STUDY DESIGN: The design of this study is a combination of the prediction method and empirical analysis. METHODS: By organically coupling the self-memory algorithm with the mean GM(1,1) model, the tuberculosis incidence statistics of China from 2004 to 2018 were selected for prediction analysis. Meanwhile, by comparing with the other traditional prediction methods, three representative accuracy check indexes (MSE, AME, MAPE) were conducting for error analysis. RESULTS: Owing to the multiple time-points initial fields, which replace the single time-points, the limitation of the traditional grey prediction model, which is sensitive to the initial value, is overcome in the self-memory equation. Consequently, compared with the mean GM model and other statistical methods, the grey self-memory model shows significant forecasting advantages, and its single-step rolling prediction accuracy is superior to other prediction methods. Therefore, the incidence of tuberculosis in China in the next year can be predicted as 55.30 (unit: 1/105). CONCLUSIONS: The grey self-memory system model can closely capture the individual random fluctuation in the whole evolution trend of the uncertain system. It is appropriate for predicting the future incidence trend of infectious diseases and is worth popularizing to other similar public health prediction problems.

Cancer cell-derived exosomal circUHRF1 induces natural killer cell exhaustion and may cause resistance to anti-PD1 therapy in hepatocellular carcinoma.

OBJECTIVE: Natural killer (NK) cells play a critical role in the innate antitumor immune response. Recently, NK cell dysfunction has been verified in various malignant tumors, including hepatocellular carcinoma (HCC). However, the molecular biological mechanisms of NK cell dysfunction in human HCC are still obscure. METHODS: The expression of circular ubiquitin-like with PHD and ring finger domain 1 RNA (circUHRF1) in HCC tissues, exosomes, and cell lines was detected by qRT-PCR. Exosomes were isolated from the culture medium of HCC cells and plasma of HCC patients using an ultracentrifugation method and the ExoQuick Exosome Precipitation Solution kit and then characterized by transmission electronic microscopy, NanoSight and western blotting. The role of circUHRF1 in NK cell dysfunction was assessed by ELISA. In vivo circRNA precipitation, RNA immunoprecipitation, and luciferase reporter assays were performed to explore the molecular mechanisms of circUHRF1 in NK cells. In a retrospective study, the clinical characteristics and prognostic significance of circUHRF1 were determined in HCC tissues. RESULTS: Here, we report that the expression of circUHRF1 is higher in human HCC tissues than in matched adjacent nontumor tissues. Increased levels of circUHRF1 indicate poor clinical prognosis and NK cell dysfunction in patients with HCC. In HCC patient plasma, circUHRF1 is predominantly secreted by HCC cells in an exosomal manner, and circUHRF1 inhibits NK cell-derived IFN-γ and TNF-α secretion. A high level of plasma exosomal circUHRF1 is associated with a decreased NK cell proportion and decreased NK cell tumor infiltration. Moreover, circUHRF1 inhibits NK cell function by upregulating the expression of TIM-3 via degradation of miR-449c-5p. Finally, we show that circUHRF1 may drive resistance to anti-PD1 immunotherapy in HCC patients. CONCLUSIONS: Exosomal circUHRF1 is predominantly secreted by HCC cells and contributes to immunosuppression by inducing NK cell dysfunction in HCC. CircUHRF1 may drive resistance to anti-PD1 immunotherapy, providing a potential therapeutic strategy for patients with HCC.

Isolation, heterologous expression, and purification of a novel antifungal protein from Bacillus subtilis strain Z-14.

BACKGROUND: Wheat sheath blight, a soil borne fungal disease caused by Rhizoctonia cerealis, is considered as one of the most serious threats to wheat worldwide. Bacillus subtilis Z-14 was isolated from soil sampled from a wheat rhizosphere and was confirmed to have strong antifungal activity against R. cerealis. RESULTS: An antifungal protein, termed F2, was isolated from the culture supernatant of Z-14 strain using precipitation with ammonium sulfate, anion exchange chromatography, and reverse phase chromatography. Purified F2 had a molecular mass of approximately 8 kDa, as assessed using sodium dodecyl sulfate polyacrylamide gel electrophoresis. Edman degradation was used to determine the amino acid sequence of the N-terminus, which was NH2ASGGTVGIYGANMRS. This sequence is identical to a hypothetical protein RBAM_004680 (YP_001420098.1) synthesized by B. amyloliquefaciens FZB42. The recombinant F2 protein (rF2) was heterologously expressed in the yeast host Pichia pastoris, purified using a Niaffinity column, and demonstrated significant antifungal activity against R. cerealis. The purified rF2 demonstrated broad spectrum antifungal activity against different varieties of fungi such as Fusarium oxysporum, Verticillium dahliae, Bipolaris papendorfii, and Fusarium proliferatum. rF2 was thermostable, retaining 91.5% of its activity when incubated for 30 min at 100 °C. Meanwhile, rF2 maintained its activity under treatment by proteinase K and trypsin and over a wide pH range from 5 to 10. CONCLUSIONS: A novel antifungal protein, F2, was purified from biocontrol Bacillus subtilis Z-14 strain fermentation supernatant and heterologously expressed in Pichia pastoris to verify its antifungal activity against R. cerealis and the validity of the gene encoding F2. Considering its significant antifungal activity and stable characteristics, protein F2 presents an alternative compound to resist fungal infections caused by R. cerealis.

Modulation Classification Using Compressed Sensing and Decision Tree-Support Vector Machine in Cognitive Radio System.

In this paper, a blind modulation classification method based on compressed sensing using a high-order cumulant and cyclic spectrum combined with the decision tree-support vector machine classifier is proposed to solve the problem of low identification accuracy under single-feature parameters and reduce the performance requirements of the sampling system. Through calculating the fourth-order, eighth-order cumulant and cyclic spectrum feature parameters by breaking through the traditional Nyquist sampling law in the compressed sensing framework, six different cognitive radio signals are effectively classified. Moreover, the influences of symbol length and compression ratio on the classification accuracy are simulated and the classification performance is improved, which achieves the purpose of identifying more signals when fewer feature parameters are used. The results indicate that accurate and effective modulation classification can be achieved, which provides the theoretical basis and technical accumulation for the field of optical-fiber signal detection.

Efficient photocatalytic removal of orange II by a Mn3O4-FeS2/Fe2O3 heterogeneous catalyst.

Elemental doping has been proven to be an effective strategy for increasing the catalytic activity and structural stability of Fenton catalysts. Therefore, this work reports that Mn-doped FeS2/Fe2O3 (Mn3O4-FeS2/Fe2O3) has excellent catalytic performance for the degradation of Orange II under simulated solar energy. Degradation experiment results showed that the sample with a manganese-iron molar ratio of 1:2 exhibited higher activity than others. The degradation rate of 20 mg/L OII reached 99.0% in 18 min under the conditions of 0.3 g/L Mn3O4-FeS2/Fe2O3, 5 mM H2O2 and pH = 2.8. In addition to, the Mn3O4-FeS2/Fe2O3 catalyst shows good reusability for Orange II and high activity for other dyes (MB, MG, Rh B and MO) under optimal conditions. Degradation mechanism study indicated that the heterogeneous Fenton reaction was promoted by retarding the recombination of photogenerated charge carriers and accelerating the cycle between Fe3+/Mn2+ and Fe2+/Mn3+, which improved photo-Fenton-like catalytic performance, resulting in the enhanced degradation of organic pollutant. Finally, a possible degradation pathway was proposed according to the results of liquid chromatography-mass spectrometry (LC-MS). In short, the catalyst has potential application value in wastewater treatment.

Homolytic versus Heterolytic Hydrogen Evolution Reaction Steered by a Steric Effect.

Several H-H bond forming pathways have been proposed for the hydrogen evolution reaction (HER). Revealing these HER mechanisms is of fundamental importance for the rational design of catalysts and is also extremely challenging. Now, an unparalleled example of switching between homolytic and heterolytic HER mechanisms is reported. Three nickel(II) porphyrins were designed and synthesized with distinct steric effects by introducing bulky amido moieties to ortho- or para-positions of the meso-phenyl groups. These porphyrins exhibited different catalytic HER behaviors. For these Ni porphyrins, although their 1e-reduced forms are active to reduce trifluoroacetic acid, the resulting Ni hydrides (depending on the steric effects of porphyrin rings) have different pathways to make H2 . Understanding HER processes, especially controllable switching between homolytic and heterolytic H-H bond formation pathways through molecular engineering, is unprecedented in electrocatalysis.

A Flexible Acetylcholinesterase-Modified Graphene for Chiral Pesticide Sensor.

Sensors based on graphene are promising devices for chemical and biological detection owing to their high sensitivity, biocompatibility, and low costs. However, for chiral recognition, which is very important in biological systems, graphene sensors remain unable to discriminate enantiomers. Here, using chiral pesticide molecules as an example, we realized a highly sensitive graphene chiral sensor by modification with acetylcholinesterase (AChE). Quantum chemical simulations indicate that the inhibition effect of the enantiomer on AChE was transferred to graphene, which allowed for the electrical detection of chiral molecules. Under an operating voltage of 1 V, the sensitivity of the device reached 0.34 µg/L and 0.32 µg/L for (+)/(-)-methamidophos, respectively, which is much higher than by circular dichroism (6.90 mg/L and 5.16 mg/L, respectively). Furthermore, real-time, rapid detection was realized by combining with smartphones and wireless transmission.

Efficacy of acupressure on quality of recovery after surgery: Randomised controlled trial.

BACKGROUND: Acupressure therapy is associated with favourable efficacies on postoperative nausea, pain and sleep disturbance, although the quality of the evidence is generally low. No randomised clinical trial has yet assessed the effect of acupressure on postoperative quality of recovery (QoR). OBJECTIVE: The objective was to study acupressure efficacy on patient-reported postoperative recovery. DESIGN: We conducted a single centre, three-group, blind, randomised controlled, pragmatic trial assessing acupressure therapy on the PC6, LI4 and HT7 acupoints. PATIENTS: Postoperative patients expected to stay in hospital at least 2 days after surgery. INTERVENTIONS: In the acupressure group, pressure was applied for 6 min (2 min per acupoint), three times a day after surgery for a maximum of 2 postoperative days during the hospital stay. In the sham group, extremely light touch was applied to the acupoints. The third group did not receive any touch. MAIN OUTCOME MEASURES: The primary outcome was the change in the QoR, using the QoR-15 questionnaire, between postoperative days 1 and 3. Key secondary outcomes included patients' satisfaction, postoperative nausea and vomiting, pain score and opioid (morphine equivalent) consumption. Assessors for the primary and secondary endpoints were blind to the group allocation. RESULTS: Overall, 163 patients were randomised (acupressure n=55, sham n=53, no intervention n=55). The mean (SD) postoperative change in QoR-15 did not differ statistically (P = 0.27) between the acupressure, sham and no intervention groups: 15.2 (17.8), 14.2 (21.9), 9.2 (21.7), respectively. Patient satisfaction (on a 0 to 10 scale) was statistically different (P = 0.01) among these three groups: 9.1 (1.5), 8.4 (1.6) and 8.2 (2.2), respectively. Changes in pain score and morphine equivalent consumption were not significantly different between the groups. CONCLUSION: Two days of postoperative acupressure therapy (up to six treatments) did not significantly improve patient QoR, postoperative nausea and vomiting, pain score or opioid consumption. Acupressure, however, was associated with improved patient satisfaction. TRIAL REGISTRATION: ClinicalTrials.gov, identifier: NCT02762435.