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Abstract Purpose To investigate the current status of medication adherence among peritoneal dialysis (PD) patients in a primary hospital and to explore the influencing factors of medication adherence among PD patients. Methods The author used the Chinese version of the Morisky Medication Compliance Scale to evaluate the medication compliance of 226 PD patients in a single centre. Univariate analysis and logistic regression were used to analyse the factors influencing medication compliance in patients. Results Among 226 PD patients, 196 had moderate/high drug adherence (86.73%), and 36 had low medication adherence (15.93%). Univariate analysis showed that there was a statistically significant difference between groups in age (χ2 = 3.990, P = 0.020), PD vintage (t = 2.068, P = 0.040), presence of anaemia (t = -2.750, P = 0.006), PD operator (χ2 = 3.110, P = 0.047), SDS scores (t = 2.818, P = 0.005). Binary logistic regression analysis demonstrated that age (OR = 1.037, 95% CI: 1.005–1.070; P = 0.037), SDS scores (OR = 0.940, 95% CI: 0.900–0.982; P = 0.005) are factors affecting patient drug compliance. Conclusions In summary, this study found that age and depressive symptoms were the main factors affecting drug compliance in PD patients, providing a basis for specifying specific measures to improve patient medication adherence. With the help of information technology and a novel exercise method, the medical staff could carry out various forms of health education and activity to improve the medication compliance of PD patients.

Abstract Background The molecular complexity of colorectal cancer poses a significant challenge to the clinical implementation of accurate risk stratification. There is still an urgent need to find better biomarkers to enhance established risk stratification and guide risk-adapted treatment decisions. Methods we systematically analyzed cancer dependencies of 17 colorectal cancer cells and 513 other cancer cells based on genome-scale CRISPR-Cas9 knockout screens to identify colorectal cancer-specific fitness genes. A regression model was built using colorectal cancer-specific fitness genes, which was validated in other three independent cohorts. 30 published gene expression signatures were also retrieved. Findings We defined a total of 1828 genes that were colorectal cancer-specific fitness genes and identified a 22 colorectal cancer-specific fitness gene (CFG22) score. A high CFG22 score represented unfavorable recurrence and mortality rates, which was validated in three independent cohorts. Combined with age, and TNM stage, the CFG22 model can provide guidance for the prognosis of colorectal cancer patients. Analysis of genomic abnormalities and infiltrating immune cells in the CFG22 risk stratification revealed molecular pathological difference between the subgroups. Besides, drug analysis found that CFG22 high patients were more sensitive to clofibrate. Interpretation The CFG22 model provided a powerful auxiliary prediction tool for identifying colorectal cancer patients with high recurrence risk and poor prognosis, optimizing precise treatment and improving clinical efficacy.

Abstract Background Sex difference in the incidence rate of idiopathic pulmonary fibrosis (IPF) indicates that estrogen has a certain protective effect on the disease. Nevertheless, there is a dearth of study investigating the association between factors pertaining to endogenous estrogen exposure level, such as age at menarche (AAM) in women, and IPF. Our study intended to employ Mendelian randomization (MR) method to elucidate the causal association between AAM and IPF. Methods Our study utilized AAM as a measure of endogenous estrogen exposure and investigated its causal effect on the risk of IPF through MR. We employed the inverse variance weighted (IVW) method to assess the causal relationship between AAM and IPF risk, with supplementary analyses conducted using the weighted median estimator (WME) and MR-Egger method. Several sensitivity analyses were performed to assess the dependability of MR estimates. Results A total of 9 selected single nucleotide polymorphisms (SNPs) significantly associated with AAM were selected as instrumental variables. The IVW method showed that genetically later AAM was associated with an increased risk of IPF (odds ratio [OR] = 1.0014, 95%confidence interval [CI] = 1.0005–1.0023, p = 0.001). The median weighting method and the MR-Egger method obtained similar estimates, and no heterogeneity or pleiotropy was found, indicating that the results were robust. Conclusions Our MR study suggested a causal relationship between a later onset of menarche and a heightened susceptibility to IPF.

BackgroundThe purpose of this study was to investigate the diagnostic value of IL-17 detection in bronchoalveolar lavage fluid (BALF) and plasma samples from nonneutropenic patients with invasive pulmonary aspergillosis.MethodsWe retrospectively collected data on non-neutropenic patients who were suspected to have IPA admitted to the Third Affiliated Hospital of Soochow University between March 2020 to January 2023. IL-17 and GM were measured using enzyme-linked immunosorbent assays.ResultsA total of 281 patients were enrolled in this study, of which 62 had proven or probable IPA and the remaining 219 patients were controls. The plasma and BALF IL-17 levels were significantly higher in the IPA group compared with the control group. The plasma GM, plasma IL17, BALF GM, and BALF IL17 assays had sensitivities of 56.5%, 72.6%, 68.7%, and 81.2%, respectively, and specificities of 87.7%, 69.4%, 91.9%, and 72.6%, respectively. The sensitivity of IL17 in plasma and BALF was higher than that of GM. Plasma GM in combination with IL-17 increases the sensitivity but does not decrease the diagnostic specificity of GM testing. The diagnostic sensitivity and specificity of BALF GM combined with IL-17 for IPA in non-neutropenic patients were greater than 80% and there was a significant increase in sensitivity compared with BALF GM.ConclusionsPlasma and BALF IL-17 levels were significantly higher in non-neutropenic patients with IPA. The sensitivity of plasma and BLAF IL-17 for diagnosing IPA in non-neutropenic patients was superior to that of GM. Combined detection of lavage fluid GM and IL17 significantly improves the diagnosis of IPA in non-neutropenic patients. The combined detection of GM and IL-17 in plasma also contributes to the diagnosis of IPA in patients who cannot tolerate invasive procedures.

IntroductionThis study was conducted to evaluate the effects of dietary galacto-oligosaccharides (GOS) and hyocholic acids (HCA) during late gestation and lactation on reproductive performance, colostrum quality, antioxidant capacity and gut microbiota in multiparous sows.MethodsA total of 60 healthy multiparous cross-bred sows (Landrace × Yorkshire) were randomly fed 4 groups diets as follows: the basal diets (CTRL group), or the basal diets containing only 600 mg/kg GOS (GOS group), 600 mg/kg GOS + 100 mg/kg HCA (GOS + Low HCA group), and 600 mg/kg + 200 mg/kg HCA (GOS + High HCA group) from d 85 of gestation to weaning. Multiple parameters of sows were determined.ResultsThere was a trend of shortening the labor process of sows (p = 0.07) in the GOS group and GOS + Low/High HCA group. Compared with the CTRL group, the GOS + Low/High HCA group increased the average piglets weight at birth (p

Abstract Exploiting thin Li metal anode is essential for high-energy-density battery, but is severely plagued by the poor processability of Li, as well as the uncontrollable Li plating/stripping behaviors and Li/electrolyte interface. Herein, a thickness/capacity-adjustable thin alloy-type Li/LiZn@Cu anode is fabricated for high-energy-density Li metal batteries. The as-formed lithophilic LiZn alloy in Li/LiZn@Cu anode can effectively regulate Li plating/stripping and stabilize the Li/electrolyte interface to deliver the hierarchical Li electrochemistry. Upon charging, the Li/LiZn@Cu anode firstly acts as Li source for homogeneous Li extraction. At the end of charging, the de-alloy of LiZn nanostructures further supplements the Li extraction, actually playing the Li compensation role in battery cycling. While upon discharging, the LiZn alloy forms just at the beginning, thereby regulating the following Li homogeneous deposition. The reversibility of such an interesting process is undoubtedly verified from the electrochemistry and in-situ XRD characterization. This work sheds light on the facile fabrication of practical Li metal anodes and useful Li compensation materials for high-energy-density Li metal batteries.

Abstract Nitrate is a primary nitrogen source for plant growth, and previous studies have indicated a correlation between nitrogen and browning. Nitrate transporters (NRTs) are crucial in nitrate allocation. Here, we utilized a genome-wide approach to identify and analyze the expression pattern of 74 potential GbNRTs under nitrate treatments during calluses browning in Ginkgo, including 68 NITRATE TRANSPORTER 1 (NRT1)/PEPTIDE TRANSPORTER (PTR) (NPF), 4 NRT2 and 2 NRT3. Conserved domains, motifs, phylogeny, and cis-acting elements (CREs) were analyzed to demonstrate the evolutionary conservation and functional diversity of GbNRTs. Our analysis showed that the NPF family was divided into eight branches, with the GbNPF2 and GbNPF6 subfamilies split into three groups. Each GbNRT contained 108–214 CREs of 19–36 types, especially with binding sites of auxin and transcription factors v-myb avian myeloblastosis viral oncogene homolog (MYB) and basic helix-loop-helix (bHLH). The E1X1X2E2R motif had significant variations in GbNPFs, indicating changes in the potential dynamic proton transporting ability. The expression profiles of GbNRTs indicated that they may function in regulating nitrate uptake and modulating the signaling of auxin and polyphenols biosynthesis, thereby affecting browning in Ginkgo callus induction. These findings provide a better understanding of the role of NRTs during NO3 − uptake and utilization in vitro culture, which is crucial to prevent browning and develop an efficient regeneration and suspension production system in Ginkgo.

We present the design of a Single Polarization Single Mode (SPSM) Terahertz Hollow-Core Anti-Resonant Waveguide (THz HC-ARW) by using multi-size semi-elliptical tubes (SETs) and high-resistance silicon layer. High single mode performance can be achieved by optimizing the structural parameters in the structure of the THz HC-ARW with multi-size SETs in the cladding. Numerical results indicate that the single mode bandwidth with High Order Mode Extinction Ratio (HOMER) above 100 reaches up to 420 GHz covering the frequency range from 0.82 THz to 1.24 THz, in which the loss of Fundamental Mode (FM) remains below 0.05 dB/m. To the best of our knowledge, this is the first instance of achieving low loss of FM under 0.05 dB/m and HOMER exceeding 100 within an exceptionally wide frequency bandwidth for a THz HC-ARW. On the basis of the above structure, a modified structure is proposed to further obtain single polarization characteristics by selectively coating a high-resistance silicon layer on the inner surface of one SET. When a high-resistance silicon layer with the thickness of 0.258 mm is coating on the inner surface of the biggest SET, a high polarization extinction ratio of 371 and a HOMER of 106 can be attained simultaneously at a frequency of 1 THz, thus only the X-polarization FM with low loss of 0.04 dB/m can propagate through the waveguide. This means SPSM can be achieved in the proposed modified structure.

Abstract Objectives The aim of this study is to evaluate the diagnostic value of rapid on‐site evaluation (ROSE) combined with computed tomography‐guided percutaneous needle biopsy (CT‐PNB) or radial endobronchial ultrasound‐guided transbronchial lung biopsy (EBUS‐TBLB) for pulmonary cryptococcosis (PC). Methods Clinical data of 33 patients diagnosed with PC at the Third Affiliated Hospital of Soochow University between February 2018 and June 2023 were retrospectively analysed. Patients were divided into the CT‐PNB and EBUS‐TBLB groups based on the intervention method, and the diagnostic positivity rate and incidence of complications were compared between the two groups. Results Compared with the final diagnosis, the positive diagnostic rates of ROSE, histopathology and serum CrAg of all patients were 81.8% (27/33), 72.7% (24/33) and 63.6% (21/33), respectively. The average turnaround times of the three methods were 0.1 (0.1–0.2) h, 96.0 (48.0–120.0) h and 7.8 (4.5–13.6) h, respectively (P

A Hot Disk thermal constant analyzer was used to obtain the thermal parameters of composite boards, solid wood floor, and ceramic tiles (CT). FLUENT software was used for the model establishment and the temperature field simulation, and the effects caused by different surface materials were analyzed. A 2D unsteady model was constructed to analyze floor surface temperature and indoor temperature fields in an enclosure space. Comparison of temperature fields caused by different materials showed that both steady indoor temperature and surface temperature of CTwerethe highest, which is due to its good thermal properties. Thermal conductivity and thermal capacity are the two main factors affecting floor thermal performance in the initial hours, while thermal conductivity is the key factor in the steady period. For the compared floor materials, CT and Sindora glabra (SG) are the optimal choices from the perspective of thermal performance, while composite boards are almost the same in thermal performance.

Various graphics applications use multibody collision detection, a critical technology in computer graphics, system simulations, and virtual reality. In these simulation environments, broad-phase collision detection, as part of collision detection, plays a critical role in ensuring that rejecting disjoint objects and collision detection is accelerated. Few existing methods implement collision detection of millions of objects in a general-purpose environment on the CPU. This paper proposes a broad-phase collision detection algorithm based on KD-Tree spatial subdivision and sweep-and-prune, which optimizes and accelerates broad-phase collision detection using a pre-sorting and temporal inference solution. Our method enables broad-phase collision detection for coherent and non-coherent settings for uniformly and non-uniformly sized objects respectively. Based on our proposed solution is tested in the context of complex scenarios and compared with other solutions available in the literature and in the industry. The experimental results show that our approach has a 1X to 2X performance improvement in virtual environments with up to $1024 \times 10^{3}$ objects, reaching the fastest collision detection speed of 119.45 milliseconds per frame in the test environment.

Industrial structure markedly affects the level of carbon emissions generated in a region. It is imperative to study the industrial structure of the Chengdu-Chongqing region to obtain information to achieve regional high-quality development by promoting low-carbon development. We selected 16 cities in Chengdu-Chongqing area as the research object in this study. The total carbon emissions (CE), carbon intensity (CI) and per capita carbon emissions (PCE) were calculated for each city. The green industry development (GI) evaluation indexes were then extracted, and the comprehensive evaluation value was determined using the entropy weight-TOPSIS model (EWM-TOPSIS). The green industry development was used as the core explanatory variable to construct a system representing the dynamic relationship between green industry development and carbon intensity using the quantile regression (QR) model. The results of the study showed that: (1) the total carbon emissions of Chengdu-Chongqing region increased whereas the carbon intensity decreased from 2010 to 2020. (2) The green industry development evaluation results showed that Chengdu-Chongqing had unevenly distributed green industry development during the study period, and Chengdu and Chongqing cities had higher green industry development values than other cities. (3) The green industry development of the region had a significant negative effect on carbon intensity at low quantile and a significant positive effect on carbon intensity at high quantile. Energy supply (ES) was positively correlated with the carbon intensity of the region at 1 % level of significance, whereas urbanization rate (U) and power consumption (PEC) were negatively correlated with the carbon intensity at 1 % level of significance. We comprehensively evaluated the development of green industry and introduced it as a core explanatory variable into the quantile regression model to explore the relationship between regional carbon emission intensity and industrial development. The results provide a reference for designing strategies to promote high-quality development in the cities in the Chengdu-Chongqing region.

BackgroundAmong immunocompetent patients, patients with bronchiectasis are considered to be a high-risk group for invasive pulmonary aspergillosis (IPA). Early diagnosis and treatment can improve the prognosis of patients.ObjectivesWe aimed to investigate the diagnostic value of Dectin-1 and IL-17 for diagnosing IPA with bronchiectasis.MethodsWe retrospectively collected data on patients with bronchiectasis who had been hospitalized in the Third Affiliated Hospital of Soochow University between September 2018 to December 2021. Dectin-1, IL-17 and GM were measured by enzyme-linked immunosorbent assays.ResultsA total of 129 patients were analyzed in the study, of whom 33 had proven or probable IPA with bronchiectasis. The remaining 96 patients served as controls. The plasma Dectin-1 and IL-17 levels in the IPA group were significantly higher than that in the control group (P=0.005; P

An omni-azimuth angle sensor for tilt measuring based on fiber Bragg grating (FBG) array is proposed. It is designed based on the sensitivity of FBG to axial traction. The sensor consists of a mass block and a cube frame connected by an FBG array. The FBG array consists of four FBGs. When the sensor is tilted at different angles, the axial traction of each FBG will change due to the pull of the mass block. The tilt angle of the sensing unit can be obtained by calculating the magnitude and direction of the resultant traction of the four FBGs. The array design and measurement theory of the sensor are introduced, and the sensitivity of the sensor is discussed. Experimental results show that the FBG array can be used to measure the omni-azimuth angle. The angle sensitivity varies unevenly with the tilt angle and the range of variation is 0.08 nm/° to 0.4593 nm/°. Using the spectrometer with an accuracy of 0.01 nm, the angle resolution ranges from 0.125° to 0.0218°. The array effectively extends the measurement range of the tilt sensor, and reduces the number of FBGs as much as possible on the basis of achieving omni-azimuth angle measurement.

Abstract Lithium (Li) has garnered considerable attention as an alternative anodes of next‐generation high‐performance batteries owing to its prominent theoretical specific capacity. However, the commercialization of Li metal anodes (LMAs) is significantly compromised by non‐uniform Li deposition and inferior electrolyte–anode interfaces, particularly at high currents and capacities. Herein, a hierarchical three‐dimentional structure with CoSe2‐nanoparticle‐anchored nitrogen‐doped carbon nanoflake arrays is developed on a carbon fiber cloth (CoSe2–NC@CFC) to regulate the Li nucleation/plating process and stabilize the electrolyte–anode interface. Owing to the enhanced lithiophilicity endowed by CoSe2–NC, in situ‐formed Li2Se and Co nanoparticles during initial Li nucleation, and large void space, CoSe2–NC@CFC can induce homogeneous Li nucleation/plating, optimize the solid electrolyte interface, and mitigate volume change. Consequently, the CoSe2–NC@CFC can accommodate Li with a high areal capacity of up to 40 mAh cm–2. Moreover, the Li/CoSe2–NC@CFC anodes possess outstanding cycling stability and lifespan in symmetric cells, particularly under ultrahigh currents and capacities (1600 h at 10 mA cm−2/10 mAh cm−2 and 5 mA cm−2/20 mAh cm−2). The Li/CoSe2–NC@CFC//LiFePO4 full cell delivers impressive long‐term performance and favorable flexibility. The developed CoSe2–NC@CFC provides insights into the development of advanced Li hosts for flexible and stable LMAs.

In order to solve the problem of low recognition rate and low real-time performance of vehicle detection in complex road environment, a data-driven forward vehicle detection algorithm based on improved tiny-YOLOv3 is proposed. Based on tiny-YOLOv3, the context feature information is combined to increase the two scale detections of tiny-YOLOv3 to three. The spatial pyramid pooling (SPP) module is added to increase the number of feature channels to improve the network feature extraction ability. According to the dense arrangement of vehicles on the horizontal axis in the road image ahead, we change the grid size of tiny-YOLOv3 and increase the number of candidate boxes on the horizontal axis. In addition, combined with the characteristics of the vehicle size in the road image ahead, K-means clustering method is used to select the appropriate number and size of target candidate boxes. We obtain the optimal detection model by multi-scale training of the improved network. The experimental results show that the average accuracy of the improved algorithm on the KITTI datasets is 91.03%, which is 7.12% higher than that of tiny-YOLOv3. And the detection speed of improved network is 144 frames/s, which meets the real-time requirements.

The ultra-dense network (UDN) has been widely accepted as a promising technology to improve the network performance. However, the severe co-channel interference (CCI) generated due to the densely deployed femtocells greatly limits the network throughput. Different from most conventional methods that model the inter-user interference intensities based on the accurate geographical distance information, which is usually hard to obtain in reality, a more practical machine learning based relative interference intensity modeling method is proposed. The proposed method models the relative interference intensities by mining the resource block (RB) allocation data, the new data indicator (NDI) data, the acknowledgement (ACK) and negative acknowledgement (NACK) data collected from the network, which could achieve an extremely high accuracy that is validated by the simulation results. In addition, we propose a load-aware resource allocation approach which calculates each user's boundary of reusing the common RBs and allocating the orthogonal RBs with its interfering sources based on the relative interference intensities modeled above and the network load in each transmission time interval (TTI). The orthogonal interfering source set of each user is generated based on its time-varying boundary. Simulation results show that the proposed load-aware resource allocation approach outperforms all the benchmark algorithms under most network densities and network loads especially when the network load is heavy and the network is ultra-dense.

Abstract The hepatitis B virus (HBV) causes acute and chronic liver infection, which may lead to liver cirrhosis and hepatocellular carcinoma. Current treatments including interferons and nucleotide analogs, have limited therapeutic effects, underscoring the need to identify effective therapeutic options to inhibit HBV replication and prevent complications. Previous animal models mimicking chronic HBV infection do not faithfully reflect disease progression in humans. Here, we used our established HBV-persistent mouse line with liver fibrosis to evaluate the efficacy of novel therapies. The combination of two short hairpin RNAs (dual-shRNA) against different coding regions of HBV delivered by a self-complementary AAV vector showed better antiviral effects than single shRNA both in vitro and in HBV-persistent mice. The dual-shRNA also exhibited stronger antifibrotic activity in vivo. Vector carrying shRNA against TGF-β, though did not inhibit HBV replication alone, enhanced the antiviral and antifibrotic activities of single and dual HBV shRNAs. Co-administration of TGF-β shRNA and HBV dual-shRNA decreased HBV DNA, HBV RNA, HBsAg, HBeAg, and liver fibrosis markers in serum and tissues, and improved liver morphology more effectively than single treatments. Our results suggest that the combination of shRNAs against HBV and TGF-β could be developed into a viable treatment for human HBV infection.

Dengue virus (DENV), a single-stranded RNA virus and Flaviviridae family member, is transmitted by Aedes aegypti and Aedes albopictus mosquitoes. DENV causes dengue fever, which may progress to severe dengue. Hospital-based surveillance was performed in two Chinese regions, Guangzhou and Xishuangbanna, during the dengue epidemics in 2014 and 2015, respectively. Acute-phase serum was obtained from 133 patients with suspected dengue infections during the peak season for dengue cases. Viremia levels, virus sero-positivity, serotype distribution, infection type, clinical manifestations and virus phylogenetics were investigated. Of the 112 DENV-confirmed cases, 92(82.14%) were IgM antibody-positive for DENV, and 69(51.88%) were positive for DENV RNA. From these cases, 47(41.96%) were classified as primary infections, 39(34.82%) as secondary infections and 26 (23.21%) as undetermined infections. The viremia levels were negatively correlated with IgM presence, but had no relationship with the infection type. DENV-1 genotype V dominated in Guangzhou, whereas the DENV-2 Cosmopolitan genotype dominated in Xishuangbanna, where fewer DENV-1 genotype I cases occurred. DENV-2 is associated with severe dengue illness with more serious clinical issues. The strains isolated during 2014-2015 are closely related to the isolates obtained from other Chinese regions and to those isolated recently in Southeast Asian countries. Our results indicate that DENV is no longer an imported virus and is now endemic in China. An extensive seroepidemiological study of DENV and the implementation of vector control measures against it are now warranted in China.

Triple-negative breast cancer (TNBC) is the most aggressive, prevalent, and distinct subtype of breast cancer characterized by high recurrence rates and poor clinical prognosis, devoid of both predictive markers and potential therapeutic targets. MicroRNAs (miRNA/miR) are a family of small, endogenous, non-coding, single-stranded regulatory RNAs that bind to the 3’-untranslated region (3’-UTR) complementary sequences and downregulate the translation of target mRNAs as post-transcriptional regulators. Dysregulation miRNAs are involved in broad spectrum cellular processes of TNBC, exerting their function as oncogenes or tumor suppressors depending on their cellular target involved in tumor initiation, promotion, malignant conversion, and metastasis. In this review, we emphasize on masses of miRNAs that act as oncogenes or tumor suppressors involved in epithelial−mesenchymal transition (EMT), maintenance of stemness, tumor invasion and metastasis, cell proliferation, and apoptosis. We also discuss miRNAs as the targets or as the regulators of dysregulation epigenetic modulation in the carcinogenesis process of TNBC. Furthermore, we show that miRNAs used as potential classification, prognostic, chemotherapy and radiotherapy resistance markers in TNBC. Finally, we present the perspective on miRNA therapeutics with mimics or antagonists, and focus on the challenges of miRNA therapy. This study offers an insight into the role of miRNA in pathology progression of TNBC.