Preparation of Aluminum-Based Superhydrophobic Surfaces for Fog Collection by Bioinspired Sarracenia Microstructures.

Freshwater shortage is a growing problem. Inspired by the Sarracenia trichome fog-trapping and ultrafast water-transport structure, a series of hierarchical textured surfaces with high-low ribs with different wettabilities was prepared based on laser processing combined with dip modification. Through fog-collection performance tests, it was found that the samples with superhydrophobicity and low adhesion had the best fog-collection effect. In addition, it was observed that the fog-collection process of different microstructured samples was significantly different, and it was analysed that the fog-collection process was composed of two aspects: directional condensation and directional transport of droplets, which were affected by the low ribs number and rib height ratio. A design parameter was given to create the Sarracenia trichome-like structure to achieve a fast water transport mode. This study provides a good reference for the development and preparation of fog-collection surfaces.

A modified sampling method for the precise detection of prostate cancer tissues using a three-dimensional stereotaxic location technique.

Background: The rapid and accurate acquisition of prostate cancer pathological tissue is critical to prostate cancer research but has traditionally proven challenging. However, the gradual application of three-dimensional (3D) modeling in medical practice has overcome many of the related limitations. This cohort study aimed to compare the difference between a 3D stereotaxic sampling method and traditional cognitive sampling method to clarify the factors affecting sampling. Methods: An analysis of 111 men who received radical prostatectomy for prostate cancer at The First Affiliated Hospital of Soochow University between November 2020 and April 2022 was conducted. The positive rate of the cognitive sampling method and the 3D stereotaxic sampling method and their respective influencing factors, such as age, body mass index (BMI), prostate-specific antigen (PSA), PSA density (PSAD), International Society of Urological Pathology (ISUP) grade, tumor volume, number of positive needles from perineal puncture, clinical T stage, and tumor image location, were compared and analyzed, and a cohort study was conducted. Results: Among the 111 patients, there were 57 cases of cognitive sampling and 54 cases of 3D stereotaxic sampling. In this study, the positive rate of cognitive sampling was 29.82% (17/57,), and the positive rate of 3D stereotaxic sampling was 61.11% (33/54), with the positive rate of 3D stereotaxic sampling being significantly higher than that of cognitive sampling (P=0.001). In cognitive sampling, tumor volume [odds ratio (OR) =1.10; 95% confidence interval (CI): 1.02-1.20], number of positive biopsy cores (OR =1.30; 95% CI: 1.06-1.60), Prostate Imaging Report and Data System (PI-RADS) score (OR =5.54; 95% CI: 1.60-19.12), and clinical T stage (OR =2.36; 95% CI: 1.31-4.25) were identified as influencing factors; in 3D stereotaxic sampling, these influencing factors were eliminated, with ORs of 1.22 (95% CI: 0.78-1.90), 0.88 (95% CI: 0.72-1.09), 1.09 (95% CI: 0.62-1.92), and 1.51 (95% CI: 0.86-2.65), respectively, representing a statistically significant difference (P<0.05). Conclusions: The 3D stereotaxic sampling method can accurately obtain the required prostate cancer tissue from the prostate in vitro within a short time, and the factors affecting the positive rate of sampling can be eliminated.

Comparison of characteristics of children hospitalized for respiratory syncytial virus infection during the pre- and post-COVID-19 eras: a multicenter retrospective study.

BACKGROUND: Respiratory syncytial virus (RSV), a leading cause of lower respiratory tract infection (LRTI) among children, has resurged in the form of endemic or even pandemic in many countries and areas after the easing of COVID-19 containment measures. This study aimed to investigate the differences in epidemiological and clinical characteristics of children hospitalized for RSV infection during pre- and post-COVID-19 eras in Yunnan, China. METHODS: A total of 2553 pediatric RSV inpatients from eight hospitals in Yunnan were retrospectively enrolled in this study, including 1451 patients admitted in 2018-2019 (pre-COVID-19 group) and 1102 patients admitted in 2023 (post-COVID-19 group). According to the presence or absence of severe LRTI (SLRTI), patients in the pre- and post-COVID-19 groups were further divided into the respective severe or non-severe subgroups, thus analyzing the risk factors for RSV-associated SLRTI in the two eras. Demographic, epidemiological, clinical, and laboratory data of the patients were collected for the final analysis. RESULTS: A shift in the seasonal pattern of RSV activity was observed between the pre-and post-COVID-19 groups. The peak period of RSV hospitalizations in the pre-COVID-19 group was during January-April and October-December in both 2018 and 2019, whereas that in the post-COVID-19 group was from April to September in 2023. Older age, more frequent clinical manifestations (fever, acute otitis media, seizures), and elevated laboratory indicators [neutrophil-to-lymphocyte ratio (NLR), c-reactive protein (CRP), interleukin 6 (IL-6), co-infection rate] were identified in the post-COVID-19 group than those in the pre-COVID-19 group (all P < 0.05). Furthermore, compared to the pre-COVID-19 group, the post-COVID-19 group displayed higher rates of SLRTI and mechanical ventilation, with a longer length of hospital stay (all P < 0.05). Age, low birthweight, preterm birth, personal history of atopy, underlying condition, NLR, IL-6 were the shared independent risk factors for RSV-related SLRTI in both pre- and post-COVID-19 groups, whereas seizures and co-infection were independently associated with SLRTI only in the post-COVID-19 group. CONCLUSIONS: An off-season RSV endemic was observed in Yunnan during the post-COVID-19 era, with changed clinical features and increased severity. Age, low birthweight, preterm birth, personal history of atopy, underlying condition, NLR, IL-6, seizures, and co-infection were the risk factors for RSV-related SLRTI in the post-COVID-19 era.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Responses of lettuce (Lactuca sativa L.) growth and soil properties to conventional non-biodegradable and new biodegradable microplastics.

Residual plastic films in soils are posing a potential threat to agricultural ecosystem. However, little is known about the impacts of microplastics (MPs) derived from biodegradable and non-biodegradable plastic films on plant-soil systems. Here, we carried out a pot experiment using soil-cultivated lettuce treated by two types of MPs, degradable poly(butylene adipate-co-terephthalate) (PBAT-MPs) and non-biodegradable polyethylene (PE-MPs). MPs resulted in different degrees of reduction in shoot biomass, chlorophyll content, photosynthetic parameters, and leaf contents of nitrogen (N), phosphorus (P), and potassium (K), accelerated accumulation of hydrogen peroxide and superoxide, and increased malondialdehyde content in lettuce leaves. Moreover, MPs obviously decreased contents of total N, nitrate, ammonium, and available K in soils, and increased available P, thus altering soil nutrient availability. MPs also significantly decreased proportions of macroaggregates, and decreased soil electrical conductivity and microbial activity. PBAT-MPs had significantly greater impacts on oxidative damage, photosynthetic rate, soil aggregation, microbial activity, and soil ammonium than those of PE-MPs. Our results suggested that MPs caused oxidative damages, nutrient uptake inhibition, soil properties alteration, ultimately leading to growth reduction, and PBAT-MPs exhibited stronger impacts. Therefore, it is urgent to further study the ecological effects of MPs, especially biodegradable MPs, on soil-plant systems.

Preparation of 2D Materials and Their Application in Oil-Water Separation.

The problems of environmental pollution are increasingly severe. Among them, industrial wastewater is one of the primary sources of pollution, so it is essential to deal with wastewater, especially oil and water mixtures. At present, biomimetic materials with special wettability have been proven to be effective in oil-water separation. Compared with three-dimensional (3D) materials, two-dimensional (2D) materials show unique advantages in the preparation of special wettable materials due to their high specific surface area, high porosity, controlled structure, and rich functional group rich on the surface. In this review, we first introduce oil-water mixtures and the common oil-water separation mechanism. Then, the research progress of 2D materials in oil-water separation is presented, including but not limited to their structure, types, preparation principles, and methods. In addition, it is still impossible to prepare 2D materials with large sizes because they are powder-like, which greatly limits the application in oil-water separation. Therefore, we provide here a review of several ways to transform 2D materials into 3D materials. In the end, the challenges encountered by 2D materials in separating oil-water are also clarified to promote future applications.

Kimesurface Representation and Tensor Linear Modeling of Longitudinal Data.

Many modern techniques for analyzing time-varying longitudinal data rely on parametric models to interrogate the time-courses of univariate or multivariate processes. Typical analytic objectives include utilizing retrospective observations to model current trends, predict prospective trajectories, derive categorical traits, or characterize various relations. Among the many mathematical, statistical, and computational strategies for analyzing longitudinal data, tensor-based linear modeling offers a unique algebraic approach that encodes different characterizations of the observed measurements in terms of state indices. This paper introduces a new method of representing, modeling, and analyzing repeated-measurement longitudinal data using a generalization of event order from the positive reals to the complex plane. Using complex time (kime), we transform classical time-varying signals as 2D manifolds called kimesurfaces. This kime characterization extends the classical protocols for analyzing time-series data and offers unique opportunities to design novel inference, prediction, classification, and regression techniques based on the corresponding kimesurface manifolds. We define complex time and illustrate alternative time-series to kimesurface transformations. Using the Laplace transform and its inverse, we demonstrate the bijective mapping between time-series and kimesurfaces. A proposed general tensor regression based linear model is validated using functional Magnetic Resonance Imaging (fMRI) data. This kimesurface representation method can be used with a wide range of machine learning algorithms, artificial intelligence tools, analytical approaches, and inferential techniques to interrogate multivariate, complex-domain, and complex-range longitudinal processes.

Translation, Cultural Adaptation, and Reliability and Validity Testing of a Chinese Version of the Freezing of Gait Questionnaire (FOGQ-CH).

Freezing of gait is a disabling symptom with a complex episodic nature that is frequently experienced by people with Parkinson's disease (PD). Although China has the largest population with PD in the world, no Chinese version of the freezing of gait questionnaire (FOGQ), the instrument that has been most widely used to assess FOG, has yet been developed. This study aimed to translate and adapt the original version of FOGQ to create a Chinese version, the FOGQ-CH, then assess its reliability, calculate the Minimal Detectable Change (MDC) and investigate its validity. The forward-backwards translation model was adopted, and cultural adaptation included expert review and pretesting. For the reliability study, 31 Chinese native speaking patients with PD were assessed two times in a 7-10 days interval. Internal consistency and test-retest reliability of the FOGQ-CH were measured by Cronbach's alpha (Cα) and the Intraclass Correlation Coefficient (ICC). For the validity study, 34 native speakers of Chinese with PD were included. To explore the convergent validity, relationships between the FOGQ-CH and the Unified Parkinson's Disease Rating Scale Part II (UPDRS II) and Part III (UPDRS III), Timed Up and Go Test (TUGT), Timed Up and Go Test in cognitive task (TUGT-Cog), walking speed (10 MWT speed), and step length (10 MWT step length) in a 10-m Walk Test were tested. To explore predictive validity, the number of falls followed up for 6 months were assessed. The area under the ROC curve (AUC) was employed to test the capacity of FOGQ-CH to discriminate those with falls. From the reliability study, Cα = 0.823, ICC = 0.786. The MDC0.90 = 4.538. From the validity study, the FOGQ-CH showed moderate correlations with UPDRS II (rho = 0.560, p = 0.001), UPDRS III (rho = 0.451, p = 0.007), TUGT (rho = 0.556, p = 0.007), TUGT-Cog (rho = 0.557, p = 0.001), 10MWT-speed (rho = -0.478, p = 0.004), 10MWT-step length (rho = -0.419, p = 0.014), and the number of falls followed up for 6 months (rho = 0.356, p = 0.045). The AUC = 0.777 (p = 0.036) for predicting whether the participants will have multiple falls (two or more) in the following 6 months. The FOGQ-CH showed good reliability and validity for assessing Chinese native speaking patients with PD. In addition, the FOGQ-CH showed good efficacy for predicting multiple falls in the following 6 months.

Electrochemical Alkoxysulfonylation Difunctionalization of Styrene Derivatives Using Sodium Sulfinates as Sulfonyl Sources.

An eco-friendly method for the synthesis of ß-alkoxy sulfones via electrochemical alkoxysulfonylation reaction of styrenes with sodium sulfinates as sulfonyl sources has been established. The reaction is conducted in an undivided cell at room temperature and tolerates a wide scope of styrenes, sodium sulfinates, and alcohols. The reaction does not need any chemical oxidants and transition-metal catalysts, which provides a new and green access to ß-alkoxy sulfones.

Design and verification of halogen-bonding system at the complex interface of human fertilization-related MUP PDZ5 domain with CAMK's C-terminal peptide.

Calmodulin-dependent protein kinase (CAMK) is physiologically activated in fertilized human oocytes and is involved in the Ca2+ response pathways that link the fertilization calmodulin signal to meiosis resumption and cortical granule exocytosis. The kinase has an unstructured C-terminal tail that can be recognized and bound by the PDZ5 domain of its cognate partner, the multi-PDZ domain protein (MUP). In the current study, we reported a rational biomolecular design of halogen-bonding system at the complex interface of CAMK's C-terminal peptide with MUP PDZ5 domain by using high-level computational approaches. Four organic halogens were employed as atom probes to explore the structural geometry and energetic property of designed halogen bonds in the PDZ5-peptide complex. It was found that the heavier halogen elements such as bromine Br and iodine I can confer stronger halogen bond but would cause bad atomic contacts and overlaps at the complex interface, while fluorine F cannot form effective halogen bond in the complex. In addition, the halogen substitution at different positions of peptide's aromatic ring would result in distinct effects on the halogen-bonding system. The computational findings were then verified by using fluorescence analysis; it is indicated that the halogen type and substitution position play critical role in the interaction strength of halogen bonds, and thus the PDZ5-peptide binding affinity can be improved considerably by optimizing their combination.

[Analysis of microRNA in drug-resistant breast cancer cell line MCF-7/ADR].

OBJECTIVE: To analyze the difference in microRNAs expression between MCF-7 and MCF-7/ADR cells and explore the association between microRNA and drug resistance of breast cancer. METHODS: The drug resistance of MCF-7/ADR cells was evaluated using MTT assay and flow cytometry. Microarray technique and RT-PCR were used to analyze the differential expressions of the microRNA between MCF-7 and MCF-7/ADR cells. RESULTS: The drug resistance index of MCF-7/ADR cells relative to the parental MCF-7 cells was 33.2. The percentages of the side population in MCF-7/ADR and MCF-7 cells were (9.50-/+0.9)% and (0.85-/+0.2)%, respectively. Microarray analysis of MCF-7 to MCF-7/ADR cells identified 36 differentially expressed genes, including 16 up-regulated and 20 down-regulated genes in MCF-7/ADR cells. RT-PCR identified 14 microRNAs that were differentially expressed between MCF-7 and MCF-7/ADR cells, including 7 up-regulated and 7 down-regulated ones in MCF-7/ADR cells. Of these differentially expressed microRNAs, mir-221, mir222, mir-130a, and mir-155 showed significantly increased expression, and mir200a, mir-200b, mir-200c, and mir-421 showed significantly lowered expression in MCF-7/ADR cells as indicated by the results of microarray analysis and RT-PCR. CONCLUSION: MCF-7/ADR cells show a different microRNA expression profile from its parental MCF-7 cells, suggesting the involvement of microRNAs in tumor cell drug resistance. This finding provides a experimental basis for further study of mechanism underlying the drug resistance of breast cancer.