Synthesis of δ-MnO2 via ozonation routine for low temperature formaldehyde removal.

Nowadays, it is still a challenge to prepared high efficiency and low cost formaldehyde (HCHO) removal catalysts in order to tackle the long-living indoor air pollution. Herein, δ-MnO2 is successfully synthesized by a facile ozonation strategy, where Mn2+ is oxidized by ozone (O3) bubble in an alkaline solution. It presents one of the best catalytic properties with a low 100% conversion temperature of 85°C for 50 ppm of HCHO under a GHSV of 48,000 mL/(g·hr). As a comparison, more than 6 times far longer oxidation time is needed if O3 is replaced by O2. Characterizations show that ozonation process generates a different intermediate of tetragonal ß-HMnO2, which would favor the quick transformation into the final product δ-MnO2, as compared with the relatively more thermodynamically stable monoclinic γ-HMnO2 in the O2 process. Finally, HCHO is found to be decomposed into CO2 via formate, dioxymethylene and carbonate species as identified by room temperature in-situ diffuse reflectance infrared fourier transform spectroscopy. All these results show great potency of this facile ozonation routine for the highly active δ-MnO2 synthesis in order to remove the HCHO contamination.

Synthesis of a Metalla[2]catenane, Metallarectangles and Polynuclear Assemblies from Di(N-Heterocyclic Carbene) Ligands.

The 2,7-fluorenone-linked bis(6-imidazo[1,5-a]pyridinium) salt H2-1(PF6)2 reacts with Ag2O in CH3CN to yield the [2]catenane [Ag4(1)4](PF6)4. The [2]catenane rearranges in DMF to yield two metallamacrocycles [Ag2(1)2](PF6)2. 2,7-Fluorenone-bridged bis-(imidazolium) salt H2-L(PF6)2 (L = 2a, 2b) react with Ag2O in CH3CN to yield metallamacrocycles [Ag2(L)2](PF6)2 with interplanar distances between the fluorenone rings too small for [2]catenane formation. Intra- and intermolecular p···p interactions between the fluorenone groups were observed by X-ray crystallography. The strongly kinked 2,7-fluorenone bridged bis(5-imidazo[1,5-a]pyridinium) salt H2-4(PF6)2 reacts with Ag2O to yield [Ag2(4)(CN)](PF6) while the tetranuclear assembly [Ag4(4)2(CO3)](PF6)2 was obtained in the presence of K2CO3.

Gut microbiota modulating intestinal stem cell differentiation.

Proliferation and differentiation of intestinal stem cell (ISC) to replace damaged gut mucosal epithelial cells in inflammatory states is a critical step in ameliorating gut inflammation. However, when this disordered proliferation continues, it induces the ISC to enter a cancerous state. The gut microbiota on the free surface of the gut mucosal barrier is able to interact with ISC on a sustained basis. Microbiota metabolites are able to regulate the proliferation of gut stem and progenitor cells through transcription factors, while in steady state, differentiated colonocytes are able to break down such metabolites, thereby protecting stem cells at the gut crypt. In the future, the gut flora and its metabolites mediating the regulation of ISC differentiation will be a potential treatment for enteropathies.

A Novel Combination Strategy of Ultrasound-Guided Percutaneous Radiofrequency Ablation and Corticosteroid Injection for Treating Recalcitrant Plantar Fasciitis: A Retrospective Comparison Study.

INTRODUCTION: The best treatment yielding clinical benefits was still equivocal and controversial for the treatment of recalcitrant plantar fasciitis (PF). This study aimed to propose a novel combination strategy of ultrasound-guided percutaneous radiofrequency ablation (RFA) and corticosteroid injection (CI) for recalcitrant PF, and to compare its therapeutic effects with CI alone and continued conservative management. METHODS: We retrospectively reviewed consecutive patients with recalcitrant PF who underwent combined strategy (RFA + CI), CI alone, and continue conservative treatment at our institution between October 2021 and February 2023. The technical pearls were described elaborately. A comparison of demographic data and clinical outcomes, including visual analog scale (VAS), Ankle-Hindfoot Scale (AOFAS-AHS), and plantar fascia thickness, were conducted among the three groups. RESULTS: Seventy-one eligible patients were enrolled in this study, with 17 in the combined strategy group, 25 in the CI group, and 29 in the continued conservative treatment group. Both the combined strategy group and the CI group showed significant improvements in VAS scores, AOFAS-AHS scores, and significant reductions in plantar fascia thickness during the 12-month follow-up period compared to those preoperatively (P < 0.05). The combined strategy group achieved comparable immediate pain relief to the CI group after the intervention ([25.7 ± 15.7] vs. [20.6 ± 17.6], P = 0.850). However, the combined strategy group demonstrated superior improvement in symptom and function compared to the CI group at the 3-month (VAS: [21.9 ± 13.5] vs. [39.6 ± 20.4]; AOFAS-AHS: [77.9 ± 12.4] vs. [60.5 ± 17.4], P < 0.05) and 12-month follow-up (VAS: [15.7 ± 12.0] vs. [56.8 ± 17.5]; AOFAS-AHS: [84.5 ± 10.7] vs. [53.8 ± 12.4], P < 0.05). Obvious adverse effects or complications were not identified in either group, while two cases (11.8%) in the combined strategy group and five cases (20.0%) in the CI group experienced unsatisfactory symptom remission. CONCLUSIONS: We introduced and detailed a novel combination strategy involving ultrasound-guided percutaneous RFA and CI for treating recalcitrant PF. The strategy is both effective and safe in alleviating pain and enhancing function throughout the entire treatment course.

Development and Validation of a Community-Based Prediction Model for Depression in Elderly Patients with Diabetes: A Cross-Sectional Study.

Background: In elderly diabetic patients, depression is often overlooked because professional evaluation requires psychiatrists, but such specialists are lacking in the community. Therefore, we aimed to create a simple depression screening model that allows earlier detection of depressive disorders in elderly diabetic patients by community health workers. Methods: The prediction model was developed in a primary cohort that consisted of 210 patients with diabetes, and data were gathered from December 2022 to February 2023. The independent validation cohort included 99 consecutive patients from February 2023 to March 2023. Multivariable logistic regression analysis was used to develop the predictive model. We incorporated common demographic characteristics, diabetes-specific factors, family structure characteristics, the self-perceived burden scale (SPBS) score, and the family APGAR (adaptation, partnership, growth, affection, resolution) score. The performance of the nomogram was assessed with respect to its calibration (calibration curve, the Hosmer-Lemeshow test), discrimination (the area under the curve (AUC)), and clinical usefulness (Decision curve analysis (DCA)). Results: The prediction nomogram incorporated 5 crucial factors such as glucose monitoring status, exercise status, monthly income, sleep disorder status, and the SPBS score. The model demonstrated strong discrimination in the primary cohort, with an AUC of 0.839 (95% CI, 0.781-0.897). This discriminative ability was further validated in the validation cohort, with an AUC of 0.857 (95% CI, 0.779-0.935). Moreover, the nomogram exhibited satisfactory calibration. DCA suggested that the prediction of depression in elderly patients with diabetes mellitus was of great clinical value. Conclusion: The prediction model provides precise and user-friendly guidance for community health workers in preliminary screenings for depression among elderly patients with diabetes.

Evaluating anemia in HIV-infected patients using chest CT.

Objective: The aim of this study was to investigate the role of the Hounsfield unit value of chest CT non-contrast enhanced scan in evaluating the severity of anemia in HIV-infected patients. Methods: Patients with HIV infection combined with anemia admitted to the Kunming Third People's Hospital were retrospectively collected and divided into mild anemia, moderate anemia, and severe anemia groups by peripheral hemoglobin (HB) content and calculated the ratio of ventricular septum density (VSD) to left ventricular density (LVD) and VSD to right ventricular density (RVD); then, the above patients were divided into the critical value group and the non-critical value group according to HB and compared the differences of LVD, RVD, VSD/LVD, and VSD/RVD in the two groups of patients. Results: A total of 126 patients were included, with a mean age of 47.9 ± 11.1 years; 43 cases were in the mild anemia group, 59 cases were in the moderate anemia group, and 24 cases were in the severe anemia group; the differences in LVD, RVD, VSD/LVD, and VSD/RVD were significant in the three groups; VSD/LVD was an independent predictor for the diagnosis of anemia critical value in the non-critical value group vs critical value group by multifactorial binary logistic regression analysis, and the ROC was plotted using VSD/LVD with an area under the curve of 0.731. Conclusions: The measurement of cardiac cavity density and ventricular septal density under CT plain film scan has a high accuracy in evaluating the severity of anemia in patients with HIV infection and can quickly determine the severity of HIV infection in the early stage and treat it as soon as possible.

Performance improvement of reflective phosphor film via adjusting the thickness realizing bright and efficient laser lighting.

Phosphor-in-glass-film (PiG-F) has been extensively investigated, showing great potential for use in laser lighting technique. Thickness is apparently a key parameter for PiG-F, affecting the heat dissipation, absorption, and reabsorption, thus determining the luminous efficacy and luminescence saturation threshold (LST). Conventional studies suggest that thinner films often have lower thermal load than that of the thicker ones. Unexpectedly, we found that the Lu3Al5O12:Ce (LuAG:Ce)-based PiG-F with a moderate thickness (78 µm) yielded the optimal LST of 31.9 W (14.2 W·mm-2, rather than 28.0 W (12.3 W·mm-2) for the thinnest one (56 µm). This unexpected result was further verified by thermal simulations. With the high saturation threshold together with a high luminous efficacy (∼296 lm·W-1), an ultrahigh luminous flux of 7178 lm with a luminous exitance of 2930 lm·mm-2 was thus attained. We believe the new, to the best of our knowledge, findings in this study will substantially impact the design principles of phosphors for laser lighting.

Rules of acupoint selection in treatment of cancer-related insomnia with acupuncture and moxibustion based on data mining technology. / åŸºäºŽæ•°æ®æŒ–æŽ˜æŠ€æœ¯æŽ¢æžé’ˆç¸æ²»ç–—è‚¿ç˜¤ç›¸å ³æ€§å¤±çœ çš„é€‰ç©´è§„å¾‹.

OBJECTIVES: To analyze the rules of acupoint selection in treatment of cancer-related insomnia with acupuncture and moxibustion by data mining technology. METHODS: The articles of cancer-related insomnia treated with acupuncture and moxibustion were searched from CNKI, Wanfang, VIP, SinoMed, PubMed, WOS, Cochrane, and Embase databases, from the inception of each database to January 5, 2024. The prescription database of acupuncture and moxibustion for cancer-related insomnia was established. The descriptive analysis was conducted on the use frequency, meridian tropism and distribution of acupoints. Using SPSS Modeler 18.0 Apriori algorithm, the association rules of acupoint prescriptions were analyzed. With Cytoscape3.9.1 software used, the complex network diagram was plotted, and the cluster analysis of high-frequency acupoints was performed by SPSS26.0 software. RESULTS: Forty-one articles were included, and 67 prescriptions were extracted with 89 acupoints involved, and the total use frequency was 447 times. The top 4 acupoints of the high use frequency were Baihui (GV20), Sanyinjiao (SP6), Shenmen (HT7) and Shenting (GV24). The included meridians were the governor vessel, the spleen meridian, the bladder meridian, the conception vessel, the heart meridian and the stomach meridian. The selected acupoints were mostly distributed on the head, the neck and and the upper and lower limbs. The special acupoints of the high use frequency included the five-Shu points, the crossing points and yuan-primordial points. Regarding acupoint combination, GV24, SP6, HT7, and GV20 were highly correlated. The three effective clusters were categorized among the top 12 acupoints of the high use frequency. CONCLUSIONS: In treatment of cancer-related insomnia with acupuncture and moxibustion, the principle focuses on supporting the healthy qi, eliminating pathogens, regulating yin and yang, promoting the circulation of the governor vessel for regulating the spirit, and tranquilizing the mind. The core acupoint prescription may includes GV24, SP6, HT7 and GV20；combined with Zusanli (ST36) and Yintang (GV4+) to enhance the therapeutic effect.

Six-Cyclic Crown Ether-Type Pillar[5]arene: Enhanced Binding Ability to Bispyridinium Derivatives.

A six-cyclic crown ether-type pillar[5]arene was synthesized, and the five ethylene oxide loops were located outside the cavity and not affected by temperature changes which was confirmed by variable-temperature NMR experiment in DMSO-d6 and CDCl3 and 2D 1H-1H NOESY experiment in CDCl3. The six-cyclic pillar[5]-crown also showed greater binding ability of host-guest with bis(pyridinium) derivatives than conventional alkoxy pillar[5]arenes that illustrated through 1H NMR titration spectroscopic experiment in acetone-d6/CDCl3 (1:1) and UV-vis titration experiments in CHCl3 at room temperature. The five benzocrown ethers at the periphery were able to bind metal cations by 1H NMR titration spectroscopic experiment in CD2Cl2/methanol-d4(9:1).

Preadmission metformin use increased the incidence of hyperlactatemia at admission and 30-day in-hospital mortality among T2D patients with heart disease at high risk of hypoxia.

BACKGROUND: Surprisingly, despite the high prevalence of metformin use in type 2 diabetes (T2D) patients with heart disease, limited safety data is available regarding metformin use in patients with acute and critical heart disease. METHODS: In this single-center retrospective study, patients admitted to the cardiology department for heart failure (HF) or acute coronary syndrome (ACS) between December 2013 and December 2021 and who underwent arterial blood gas analysis at admission with an estimated glomerular clearance rate of ≥45 ml/min/1.73 m2 were identified. The incidences of hyperlactatemia, acidosis, and 30-day in-hospital mortality were compared between preadmission metformin users and nonusers. RESULTS: Of 526 admissions, 193/193 metformin users/nonusers were selected in a propensity score-matched model. Metformin users had greater lactate levels (2.55 ± 2.07 mmol/l vs. 2.00 ± 1.80 mmol/l P < 0.01), a greater incidence of hyperlactatemia [odds ratio (OR) = 2.55; 95% confidence interval (CI), 1.63-3.98; P < 0.01] and acidosis (OR = 1.78; 95% CI, 1.00-3.16; P < 0.05) at admission and a greater incidence of in-hospital mortality (OR = 3.83; 95% CI, 1.05-13.94; P < 0.05), especially those with HF/acute myocardial infarction, elderly age, or without preadmission insulin use. CONCLUSIONS: Our results suggest that, compared to metformin nonusers, preadmission use of metformin may be associated with a greater incidence of hyperlactatemia and acidosis at admission and greater 30-day in-hospital mortality among T2D patients with HF or ACS at high risk of hypoxia, particularly those without preadmission insulin use. The safety of metformin in this population needs to be confirmed in prospective controlled trials.

The value of deep learning-based X-ray techniques in detecting and classifying K-L grades of knee osteoarthritis: a systematic review and meta-analysis.

OBJECTIVES: Knee osteoarthritis (KOA), a prevalent degenerative joint disease, is primarily diagnosed through X-ray imaging. The Kellgren-Lawrence grading system (K-L) is the gold standard for evaluating KOA severity through X-ray analysis. However, this method is highly subjective and non-quantifiable, limiting its effectiveness in detecting subtle joint changes on X-rays. Recent researchers have been directed towards developing deep-learning (DL) techniques for a more accurate diagnosis of KOA using X-ray images. Despite advancements in these intelligent methods, the debate over their diagnostic sensitivity continues. Hence, we conducted the current meta-analysis. METHODS: A comprehensive search was conducted in PubMed, Cochrane, Embase, Web of Science, and IEEE up to July 11, 2023. The QUADAS-2 tool was employed to assess the risk of bias in the included studies. Given the multi-classification nature of DL tasks, the sensitivity of DL across different K-L grades was meta-analyzed. RESULTS: A total of 19 studies were included, encompassing 62,158 images. These images consisted of 22,388 for K-L0, 13,415 for K-L1, 15,597 for K-L2, 7768 for K-L3, and 2990 for K-L4. The meta-analysis demonstrated that the sensitivity of DL was 86.74% for K-L0 (95% CI: 80.01%-92.28%), 64.00% for K-L1 (95% CI: 51.81%-75.35%), 75.03% for K-L2 (95% CI: 66.00%-83.09%), 84.76% for K-L3 (95% CI: 78.34%-90.25%), and 90.32% for K-L4 (95% CI: 85.39%-94.40%). CONCLUSIONS: The DL multi-classification methods based on X-ray imaging generally demonstrate a favorable sensitivity rate (over 50%) in distinguishing between K-L0-K-L4. Specifically, for K-L4, the sensitivity is highly satisfactory at 90.32%. In contrast, the sensitivity rates for K-L1-2 still need improvement. CLINICAL RELEVANCE STATEMENT: Deep-learning methods have been useful to some extent in assessing the effectiveness of X-rays for osteoarthritis of the knee. However, this requires further research and reliable data to provide specific recommendations for clinical practice. KEY POINTS: X-ray deep-learning (DL) methods are debatable for evaluating knee osteoarthritis (KOA) under The Kellgren-Lawrence system (K-L). Multi-classification deep-learning methods are more clinically relevant for assessing K-L grading than dichotomous results. For K-L3 and K-L4, X-ray-based DL has high diagnostic performance; early KOA needs to be further improved.

Precision control and parameter optimization in screw extrusion 3D printing of polypropylene materials.

Fused Deposition Modeling (FDM), a widely-utilized additive manufacturing (AM) technology, has found significant favor among automotive manufacturers. Polypropylene (PP) compound is extensively employed in the production of automotive parts due to its superior mechanical properties and formability. However, aiming at the problem of poor dimensional accuracy of pure PP parts, the quality of products can be enhanced by optimizing the combination of processing parameters. In this paper, the dimensional accuracy of 3D-printed components made from pure PP material is investigated. Key influencing factors such as infill percentage, infill pattern, layer thickness, and extrusion temperature are considered. To gain a deeper understanding, fluid simulation is conducted, and mathematical models are established to correlate processing parameters with dimensional accuracy. Furthermore, the Taguchi's experiments are designed and the experimental data are subjected to rigorous Signal-to-Noise ratio and ANOVA analyses. Within the experimental range, the lower extrusion temperature, infill percentage and layer thickness yield the best dimensional accuracy. Considering the influence factors of X, Y and Z directions, the optimal processing parameters for PP prints using screw extrusion 3D printers are determined as follows: an extrusion temperature of 210 °C, an infill percentage of 40 %, a layer thickness of 0.3 mm, and a concentric circle infill pattern. This study provides reference value for the subsequent improvement of the dimensional accuracy of the printed parts.

[A quality improvement project on reducing antibiotic use duration in very low birth weight preterm infants in the neonatal intensive care unit]. / é™ä½Žæ–°ç”Ÿå„¿é‡ç—‡ç›‘æŠ¤å®¤æžä½Žå‡ºç”Ÿä½“é‡æ—©äº§å„¿æŠ—ç”Ÿç´ ä½¿ç”¨æ—¶é—´çš„è´¨é‡æ”¹è¿›ç ”ç©¶.

OBJECTIVES: To develop effective measures to reduce antibiotic use duration in very low birth weight (VLBW) preterm infants in the neonatal intensive care unit through quality improvement methods. METHODS: The study population consisted of hospitalized VLBW preterm infants, with the percentage of hospitalization time during which antibiotics were used from November 2020 to June 2021 serving as the baseline. The specific quality improvement goal was to reduce the duration of antibiotic use. Factors affecting antibiotic use duration in preterm infants were analyzed using Pareto charts. Key drivers were identified, and specific interventions were formulated based on the stages of antibiotic use. Changes in the percentage of antibiotic use duration were monitored with run charts until the quality improvement target was achieved. RESULTS: From November 2020 to June 2021, the baseline antibiotic use duration percentage was 49%, with a quality improvement target to reduce this by 10% within 12 months. The Pareto analysis indicated that major factors influencing antibiotic duration included non-standard antibiotic use; delayed cessation of antibiotics when no infection evidence was present; prolonged central venous catheter placement; insufficient application of kangaroo care; and delayed progress in enteral nutrition. The interventions implemented included: (1) establishing sepsis evaluation and management standards; (2) educating medical staff on the rational use of antibiotics for preterm infants; (3) supervising the enforcement of antibiotic use standards during ward rounds; (4) for those without clear signs of infection and with negative blood cultures, discontinued the use of antibiotics 36 hours after initiation; (5) reducing the duration of central venous catheterization and parenteral nutrition to lower the risk of infection in preterm infants. The control chart showed that with continuous implementation of interventions, the percentage of antibiotic use duration was reduced from 49% to 32%, a statistically significant decrease. CONCLUSIONS: The application of quality improvement tools based on statistical principles and process control may significantly reduce the antibiotic use duration in VLBW preterm infants. Citation:Chinese Journal of Contemporary Pediatrics, 2024, 26(7): 736-742.

Machine learning based on metabolomics unveils neutrophil extracellular trap-related metabolic signatures in non-small cell lung cancer patients undergoing chemoimmunotherapy.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the primary form of lung cancer, and the combination of chemotherapy with immunotherapy offers promising treatment options for patients suffering from this disease. However, the emergence of drug resistance significantly limits the effectiveness of these therapeutic strategies. Consequently, it is imperative to devise methods for accurately detecting and evaluating the efficacy of these treatments. AIM: To identify the metabolic signatures associated with neutrophil extracellular traps (NETs) and chemoimmunotherapy efficacy in NSCLC patients. METHODS: In total, 159 NSCLC patients undergoing first-line chemoimmunotherapy were enrolled. We first investigated the characteristics influencing clinical efficacy. Circulating levels of NETs and cytokines were measured by commercial kits. Liquid chromatography tandem mass spectrometry quantified plasma metabolites, and differential metabolites were identified. Least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and random forest algorithms were employed. By using plasma metabolic profiles and machine learning algorithms, predictive metabolic signatures were established. RESULTS: First, the levels of circulating interleukin-8, neutrophil-to-lymphocyte ratio, and NETs were closely related to poor efficacy of first-line chemoimmunotherapy. Patients were classed into a low NET group or a high NET group. A total of 54 differential plasma metabolites were identified. These metabolites were primarily involved in arachidonic acid and purine metabolism. Three key metabolites were identified as crucial variables, including 8,9-epoxyeicosatrienoic acid, L-malate, and bis(monoacylglycerol)phosphate (18:1/16:0). Using metabolomic sequencing data and machine learning methods, key metabolic signatures were screened to predict NET level as well as chemoimmunotherapy efficacy. CONCLUSION: The identified metabolic signatures may effectively distinguish NET levels and predict clinical benefit from chemoimmunotherapy in NSCLC patients.

Comparison of the diagnostic significance of cerebrospinal fluid metagenomic next-generation sequencing copy number variation analysis and cytology in leptomeningeal malignancy.

BACKGROUND: Diagnosis and monitoring of leptomeningeal malignancy remain challenging, and are usually based on neurological, radiological, cerebrospinal fluid (CSF) and pathological findings. This study aimed to investigate the diagnostic performance of CSF metagenomic next-generation sequencing (mNGS) and chromosome copy number variations (CNVs) analysis in the detection of leptomeningeal malignancy. METHODS: Of the 51 patients included in the study, 34 patients were diagnosed with leptomeningeal malignancies, and 17 patients were diagnosed with central nervous system (CNS) inflammatory diseases. The Sayk's spontaneous cell sedimentation technique was employed for CSF cytology. And a well-designed approach utilizing the CSF mNGS-CNVs technique was explored for early diagnosis of leptomeningeal malignancy. RESULTS: In the tumor group, 28 patients were positive for CSF cytology, and 24 patients were positive for CSF mNGS-CNVs. Sensitivity and specificity of CSF cytology were 82.35% (95% CI: 66.83-92.61%) and 94.12% (95% CI: 69.24-99.69%). In comparison, sensitivity and specificity of CSF mNGS-CNV were 70.59% (95% CI: 52.33-84.29%) and 100% (95% CI: 77.08-100%). There was no significant difference in diagnostic consistency between CSF cytology and mNGS-CNVs (p = 0.18, kappa = 0.650). CONCLUSIONS: CSF mNGS-CNVs tend to have higher specificity compared with traditional cytology and can be used as a complementary diagnostic method for patients with leptomeningeal malignancies.

Organic nano carbon source inducing 3D silica nanoparticles-graphene nanosheet layer on Cu current collector for high-performance anode-free lithium metal batteries.

Anode-free lithium metal batteries (AFLBs) have attracted considerable attention due to their high theoretical specific capacity and absence of Li. However, the heterogeneous Li deposition and stripping on the lithiophobic Cu collector hamper AFLBs in practice. To achieve a uniform and reversible Li deposition, a carbon-based layer on the Cu collector has attracted intense interest due to its high conductivity. However, the 2D single-component carbon-based interface is inadequate lithiophilic for obtaining the homogeneous Li deposition and preventing the lithium dendrite from piercing the separator. Herein, we present a 3D embedded lithiophilic SiO2 nanoparticles-graphene nanosheet matrix (SiO2@G-M) on the Cu collector by organic nano carbon source. In this structure, the lithiophilic SiO2 nanoparticles as active points promote the homogeneous lithium nucleation and the 3D graphene nanosheet matrix offers homogenous electron distribution and voids to prevent the piercing. Finally, SiO2@G-M/Li cell shows a high coulombic efficiency of 98.62 % after 100 cycles at a high current density of 2 mA cm-2 with an areal capacity of 1 mAh cm-2.

Wavelength-modulated photoacoustic spectroscopic instrumentation system for multiple greenhouse gas detection and in-field application in the Qinling mountainous region of China.

We present a sensitive and compact quantum cascade laser-based photoacoustic greenhouse gas sensor for the detection of CO2, CH4 and CO and discuss its applicability toward on-line real-time trace greenhouse gas analysis. Differential photoacoustic resonators with different dimensions were used and optimized to balance sensitivity with signal saturation. The effects of ambient parameters, gas flow rate, pressure and humidity on the photoacoustic signal and the spectral cross-interference were investigated. Thanks to the combined operation of in-house designed laser control and lock-in amplifier, the gas detection sensitivities achieved were 5.6 ppb for CH4, 0.8 ppb for CO and 17.2 ppb for CO2, signal averaging time 1 s and an excellent dynamic range beyond 6 orders of magnitude. A continuous outdoor five-day test was performed in an observation station in China's Qinling National Botanical Garden (E longitude 108°29', N latitude 33°43') which demonstrated the stability and reliability of the greenhouse gas sensor.

The Association of Infant Birth Sizes and Anemia under Five Years Old: A Population-Based Prospective Cohort Study in China.

Infant birth sizes are vital clinical parameters to predict poor growth and micronutrient deficiency in early life. However, their effects on childhood anemia remain unclear. We aimed to explore the associations between birth weight, crown-heel length, and head circumference with anemia in early childhood, as well as potential modification factors. This population-based prospective cohort study included 204,556 participants with singleton live births delivered at gestational ages of 28-42 weeks. A logistic regression model was used to estimate the associations of the measures of infant birth size and their Z-score with anemia under five years old. There were 26,802 (13.10%) children under five years old who were diagnosed has having anemia. Compared with children who did not have anemia, children who had anemia had a lower birth weight and smaller head circumference and a longer crown-heel length (all p-values < 0.05). After adjusting for confounders, not only birth weight (ß coefficient, -0.008; 95% CI, -0.011--0.004; p < 0.001) and head circumference (ß coefficient, -0.004; 95% CI, -0.007--0.001; p = 0.009), but also the related Z-scores were negatively associated with childhood anemia, while the trends for crown-heel length were the opposite. We further found significant interactions of folic acid use and maternal occupation with infant birth sizes. In conclusion, infants having abnormal sizes at birth are significantly associated with the risk for childhood anemia, which can be modified by folic acid use during pregnancy and maternal occupation.

Imaging Neurotransmitters with Small-Molecule Fluorescent Probes.

Neurotransmitters play a crucial role in regulating communication between neurons within the brain and central nervous system. Thus, imaging neurotransmitters has become a high priority in neuroscience. This minireview focuses on recent advancements in the development of fluorescent small-molecule fluorescent probes for neurotransmitter imaging and applications of these probes in neuroscience. Innovative approaches for probe design are highlighted as well as attributes which are necessary for practical utility, with a view to inspiring new probe development capable of visualizing neurotransmitters.