Nanofluidic Membrane-Assisted Organic Electrochemical Transistors for Bioinspired Gustatory Sensation Based on Selective Cation Transport.

Natural organisms have evolved precise sensing systems relying on unique ion channels, which can efficiently perceive various physical/chemical stimuli based on ionic signal transmission in biological fluid environments. However, it is still a huge challenge to achieve extensive applications of the artificial counterparts as an efficient wet sensing platform due to the fluidity of the working medium. Herein, nanofluidic membranes with selective cation transport properties and solid-state organic electrochemical transistors (OECTs) with amplified signals are integrated together to mimic human gustatory sensation, achieving ionic gustatory reagent recognition and a portable configuration. Cu-HHTP nanofluidic membranes with selective cation transport through their uniform micropores are constructed first, followed by assembly with OECTs to form the designed nanofluidic membrane-assisted OECTs (nanofluidic OECTs). As a result, they can distinguish typically ionic gustatory reagents, and even ionic liquids (ILs), demonstrating enhanced gustatory perception performance under a wide concentration range (10-7-10-1 m) compared with those of conventional OECTs. The linear correlations between the response and the reagent concentration further indicate the promising potential for practical application as a next-generation sensing platform. It is suggested that nanofluidic membranes mediated intramembrane cation transport based on the steric hindrance effect, resulting in distinguishable and improved response to multiple ions.

Design and Development of Metasurface Materials for Enhancing Photodetector Properties.

Recently, metasurface-based photodetectors (metaphotodetectors) have been developed and applied in various fields. Metasurfaces are artificial materials with unique properties that have emerged over the past decade, and photodetectors are powerful tools used to quantify incident electromagnetic wave information by measuring changes in the conductivity of irradiated materials. Through an efficient microstructural design, metasurfaces can effectively regulate numerous characteristics of electromagnetic waves and have demonstrated unique advantages in various fields, including holographic projection, stealth, biological image enhancement, biological sensing, and energy absorption applications. Photodetectors play a crucial role in military and civilian applications; therefore, efficient photodetectors are essential for optical communications, imaging technology, and spectral analysis. Metaphotodetectors have considerably improved sensitivity and noise-equivalent power and miniaturization over conventional photodetectors. This review summarizes the advantages of metaphotodetectors based on five aspects. Furthermore, the applications of metaphotodetectors in various fields including military and civil applications, are systematically discussed. It highlights the potential future applications and developmental trends of metasurfaces in metaphotodetectors, provides systematic guidance for their development, and establishes metasurfaces as a promising technology.

Spatial distribution of metabolites in processing Ziziphi Spinosae Semen as revealed by matrix-assisted laser desorption/ionization mass spectrometry imaging.

Ziziphi Spinosae Semen (ZSS) is the first choice for the treatment of insomnia. This research aimed to reveal the spatial distribution of identifying quality markers of ZSS and to illustrate the metabolite quality characteristics of this herbal medicine. Here, we performed a matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) in situ to detect and image 33 metabolites in ZSS, including three saponins, six flavonoids, four alkaloids, eight fatty acids, and 12 amino acids. The MALDI images of the metabolites clearly showed the heterogeneous spatial distribution in different regions of ZSS tissues, such as the cotyledon, endosperm, and radicle. The distribution area of two saponins, six flavonoids, and three alkaloids increased significantly after the fried processing of ZSS. Based on the ion images, samples with different processing technologies were distinguished unambiguously by the pattern recognition method of orthogonal partial least squares discrimination analysis (OPLS-DA). Simultaneously, 23 major influencing components exerting higher ion intensities were identified as the potential quality markers of ZSS. Results obtained in the current research demonstrate that the processing of ZSS changes its content and distribution of the medicinal components. The analysis of MALDI-MSI provides a novel MS-based molecular imaging approach to investigate and monitor traditional medicinal plants.

Access to essential and innovative anti-cancer medicines: a longitudinal study in Nanjing, China.

PURPOSE: To evaluate the availability, cost, affordability of anti-cancer medicines in Nanjing, Jiangsu. METHODS: A longitudinal tracking investigation study was performed to collect information about 24 essential anti-cancer medicines (EAMs) and 17 innovative anti-cancer medicines (IAMs) in 26 healthcare institutions in Nanjing from 2016 to 2020. The availability, cost, drug utilization and affordability of EAMs and IAMs were investigated. RESULTS: The availability of EAMs showed no significant changes in Nanjing, but the availability of IAMs showed a significant increase in 2018 and 2019 and tended to stabilize in 2020. For EAMs, the DDDc(Defined Daily Dose cost) of LPGs (Lowest-Priced Generics) showed no significant changes, and the DDDc of OBs (Originator Brands) and IAMs significantly decreased. The DDDs(Defined Daily Doses) of EAMs (LPGs) showed a decreasing trend since 2016 and rose again in 2019. Overall, the DDDs of EAMs (LPGs) decreased by 25.18% between 2016 and 2020, but the proportion selected for clinical treatment remained at 67.35% in 2020. The DDDs of EAMs (OBs) and IAMs both showed an increasing trend year by year, with a proportional increase of 207.72% and 652.68%, respectively; but the proportion selected for clinical treatment was only 16.09% and 16.56% respectively in 2020. EAMs (LPGs) had good affordability for urban residents but poor affordability for rural residents; the affordability of EAMs (OBs) and IAMs was poor for both urban and rural residents. CONCLUSIONS: There were no significant changes in the availability and cost of EAMs (LPGs), whose lower prices showed better affordability. Although their relative change in drug utilization showed a decreasing trend, they still dominated clinical treatment. Driven by the national drug price negotiation (NDPN) policy, the availability of IAMs was on the rise. It is necessary to further develop and strengthen policies for essential medicines procurement assessment to improve the accessibility of EAMs.

Prediction of pathological complete response and prognosis in locally advanced rectal cancer.

BACKGROUND: Colorectal cancer is currently the third most common malignant tumor and the second leading cause of cancer-related death worldwide. Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer (LARC). Except for pathological examination after resection, it is not known exactly whether LARC patients have achieved pathological complete response (pCR) before surgery. To date, there are no clear clinical indicators that can predict the efficacy of nCRT and patient outcomes. AIM: To investigate the indicators that can predict pCR and long-term outcomes following nCRT in patients with LARC. METHODS: Clinical data of 128 LARC patients admitted to our hospital between September 2013 and November 2022 were retrospectively analyzed. Patients were categorized into pCR and non-pCR groups. Univariate analysis (using the χ 2 test or Fisher's exact test) and logistic multivariate regression analysis were used to study clinical predictors affecting pCR. The 5-year disease-free survival (DFS) and overall survival (OS) rates were calculated using Kaplan-Meier analysis, and differences in survival curves were assessed with the log-rank test. RESULTS: Univariate analysis showed that pretreatment carcinoembryonic antigen (CEA) level, lymphocyte-monocyte ratio (LMR), time interval between neoadjuvant therapy completion and total mesorectal excision, and tumor size were correlated with pCR. Multivariate results showed that CEA ≤ 5 ng/mL (P = 0.039), LMR > 2.73 (P = 0.023), and time interval > 10 wk (P = 0.039) were independent predictors for pCR. Survival analysis demonstrated that patients in the pCR group had significantly higher 5-year DFS rates (94.7% vs 59.7%, P = 0.002) and 5-year OS rates (95.8% vs 80.1%, P = 0.019) compared to the non-pCR group. Tumor deposits (TDs) were significantly correlated with shorter DFS (P = 0.002) and OS (P < 0.001). CONCLUSION: Pretreatment CEA, LMR, and time interval contribute to predicting nCRT efficacy in LARC patients. Achieving pCR demonstrates longer DFS and OS. TDs correlate with poor prognosis.

Improved efficacy of cisplatin delivery by peanut agglutinin­modified liposomes in non­small cell lung cancer.

Globally, non­small cell lung cancer (NSCLC) is a significant threat to human health, and constitutes >80% of lung cancer cases. Cisplatin (CDDP), a commonly used drug in clinical treatment, has been the focus of research aiming to mitigate its potent toxicity through encapsulation within liposomes. However, challenges, such as a reduced drug loading efficiency and nonspecific release, have emerged as obstacles. The present study aimed to improve the encapsulation efficiency of CDDP within liposomes by pre­preparation of CDDP and modifying the liposome surface through the incorporation of peanut agglutinin (PNA) as a ligand [CDDP­loaded PNA­modified liposomes (CDDP­PNA­Lip)]. This strategy was designed to enhance the delivery of CDDP to tumour tissues, thereby reducing associated side effects. The effect of CDDP­PNA­Lip on the proliferation and migration of NSCLC cell lines with high MUC1 expression was elucidated through in vitro studies. Additionally, the capacity of PNA modification to augment the targeted anti­tumour efficacy of liposomes was assessed through xenograft tumour experiments. The results indicated that in an in vitro uptake assay Rhodamine B (RhB)­loaded PNA­modified liposomes were taken up by cells with ~50% higher efficiency compared with free RhB. In addition, CDDP­PNA­Lip resulted in a 2.65­fold enhancement of tumour suppression in vivo compared with free CDDP. These findings suggested that the encapsulation of CDDP within ligand­modified liposomes may significantly improve its tumour­targeting capabilities, providing valuable insights for clinical drug development.

Semi-supervised urban haze pollution prediction based on multi-source heterogeneous data.

Particulate matter (PM) is defined by the Texas Commission on Environmental Quality (TCEQ) as "a mixture of solid particles and liquid droplets found in the air". These particles vary widely in size. Those particles that are less than 2.5 µm in aerodynamic diameter are known as Particulate Matter 2.5 or PM2.5. Urban haze pollution represented by PM2.5 is becoming serious, so air pollution monitoring is very important. However, due to high cost, the number of air monitoring stations is limited. Our work focuses on integrating multi-source heterogeneous data of Nanchang, China, which includes Taxi track, human mobility, Road networks, Points of Interest (POIs), Meteorology (e.g., temperature, dew point, humidity, wind speed, wind direction, atmospheric pressure, weather activity, weather conditions) and PM2.5 forecast data of air monitoring stations. This research presents an innovative approach to air quality prediction by integrating the above data sets from various sources and utilizing diverse architectures in Nanchang City, China. So for that, semi-supervised learning techniques will be used, namely collaborative training algorithm Co-Training (Co-T), who further adjusting algorithm Tri-Training (Tri-T). The objective is to accurately estimate haze pollution by integrating and using these multi-source heterogeneous data. We achieved this for the first time by employing a semi-supervised co-training strategy to accurately estimate pollution levels after applying the U-air system to environmental data. In particular, the algorithm of U-Air system is reproduced on these highly diverse heterogeneous data of Nanchang City, and the semi-supervised learning Co-T and Tri-T are used to conduct more detailed urban haze pollution prediction. Compared with Co-T, which train time classifier (TC) and subspace classifier (SC) respectively from the separated spatio-temporal perspective, the Tri-T is more accurate with a and faster because of its testing accuracy up to 85.62 %. The forecast results also present the potential of the city multi-source heterogeneous data and the effectiveness of the semi-supervised learning. We hope that this synthesis will motivate atmospheric environmental officials, scientists, and environmentalists in China to explore machine learning technology for controlling the discharge of pollutants and environmental management.

Pharmacokinetics and safety of mavacamten in healthy Chinese participants with different CYP2C19 phenotypes.

Obstructive hypertrophic cardiomyopathy (oHCM) is a subtype of HCM characterized by left ventricular outflow tract obstruction resulting from cardiac muscle hypertrophy and anatomic alterations in the mitral valve and apparatus. Mavacamten, a cardiac myosin inhibitor metabolized primarily by CYP2C19 in the liver, is the first and only targeted medication approved for the treatment of symptomatic New York Heart Association (NYHA) class II-III oHCM. Previous pharmacokinetic (PK) results of mavacamten in healthy Caucasian, Japanese, and Asian participants demonstrated that mavacamten exposure was affected by CYP2C19 metabolism status. This open-label, parallel-group, phase I trial aimed to determine the PK and safety of mavacamten in healthy Chinese participants with different CYP2C19 genotypes. The primary outcome was to define the PK of mavacamten in healthy Chinese participants; the secondary outcome was to examine safety and tolerability. After a single oral dose of 15 or 25 mg mavacamten in fasted healthy adult Chinese individuals, Cmax was reached within a median Tmax of 0.6-1.5 h, indicating rapid absorption. Inter-individual variability was moderate, and individuals carrying non-functional CYP2C19 alleles (*2/*2, *3/*3, or *2/*3) exhibited longer half-life and increased total exposure. After stratification of CYP2C19 genotypes, total mavacamten exposures were similar among different ethnic groups when compared with prior PK studies. No significant adverse events were observed in this study. Single oral administration of mavacamten at 15 mg was well tolerated across all CYP2C19 genotypes, and 25 mg dose was well tolerated in healthy participants with CYP2C19 genotypes UM/RM/NM. The PK profile of mavacamten in the healthy Chinese population was consistent with that in other healthy populations.

Integrated aerobic-anaerobic digestion of highly solids-loaded corn stover and swine manure under dynamic aeration: Temperature rise, physicochemical characteristics, and methane production.

This research aimed to design an integrated aerobic-anaerobic reactor with dynamic aeration that was automatically regulated based on real-time oxygen concentration and investigate the aerobic pretreatment and subsequent dry co-anaerobic digestion (co-AD) characteristics of highly solids-loaded corn stover and swine manure in terms of temperature rise, physiochemical characteristics, and methane production. The high-temperature feedstocks from the aerobic pretreatment phase rapidly entered the AD phase without transportation and effectively improved the start-up and methane production of the co-AD. Oxygen concentration range, aeration rate, and pretreatment time affected the cumulative aeration time, temperature rise, and organic matter removal interactively during aerobic pretreatment, and a low aeration rate was relatively preferable. Although the lignocellulose removal increased with the increase in pretreatment duration, the maximal lignin elimination efficiency only reached 1.30%. The inoculum injection in the transition phase from aerobic pretreatment to co-AD and the leachate reflux during co-AD were also critical for producing methane steadily apart from aerobic pretreatment. The cold air weakened the temperature rise of aerobic pretreatment, and the low-temperature leachate reduced the methane production in the co-AD process. An oxygen concentration range of 13%-17%, aeration rate of 0.10 m3/(min·m3), pretreatment time of 84 h, inoculum loading of 40%, leachate refluxing thrice per day, and double-layer inoculation were optimum for improving the integrated aerobic-anaerobic digestion system's ability to resist low temperatures and achieving high methane production. The maximal cumulative and volatile solids (VS) methane yields of corn stover and swine manure reached 444.58 L and 266.30 L/kg VS.

Research progresses of imaging studies on preoperative prediction of microvascular invasion of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is the predominant form of primary liver cancer, accounting for approximately 90% of liver cancer cases. It currently ranks as the fifth most prevalent cancer worldwide and represents the third leading cause of cancer-related mortality. As a malignant disease with surgical resection and ablative therapy being the sole curative options available, it is disheartening that most HCC patients who undergo liver resection experience relapse within five years. Microvascular invasion (MVI), defined as the presence of micrometastatic HCC emboli within liver vessels, serves as an important histopathological feature and indicative factor for both disease-free survival and overall survival in HCC patients. Therefore, achieving accurate preoperative noninvasive prediction of MVI holds vital significance in selecting appropriate clinical treatments and improving patient prognosis. Currently, there are no universally recognized criteria for preoperative diagnosis of MVI in clinical practice. Consequently, extensive research efforts have been directed towards preoperative imaging prediction of MVI to address this problem and the relative research progresses were reviewed in this article to summarize its current limitations and future research prospects.

Infectious viruses and neurodegenerative diseases: The mitochondrial defect hypothesis.

Global attention is riveted on neurodegenerative diseases due to their unresolved aetiologies and lack of efficacious therapies. Two key factors implicated include mitochondrial impairment and microglial ageing. Several viral infections, including Herpes simplex virus-1 (HSV-1), human immunodeficiency virus (HIV) and Epstein-Barr virus, are linked to heightened risk of these disorders. Surprisingly, numerous studies indicate viruses induce these aforementioned precipitating events. Epstein-Barr virus, Hepatitis C Virus, HIV, respiratory syncytial virus, HSV-1, Japanese Encephalitis Virus, Zika virus and Enterovirus 71 specifically impact mitochondrial function, leading to mitochondrial malfunction. These vital organelles govern various cell activities and, under specific circumstances, trigger microglial ageing. This article explores the role of viral infections in elucidating the pathogenesis of neurodegenerative ailments. Various viruses instigate microglial ageing via mitochondrial destruction, causing senescent microglia to exhibit activated behaviour, thereby inducing neuroinflammation and contributing to neurodegeneration.

Assessment of inflammatory biomarkers to identify surgical/death necrotizing enterocolitis in preterm infants without pneumoperitoneum.

BACKGROUND: Necrotizing enterocolitis (NEC) is a life-threatening disease that affects premature infants. However, the role of inflammatory biomarkers in identifying surgical/death NEC without pneumoperitoneum remains elusive. PURPOSE: We aimed to verify the value of platelet-to-lymphocyte ratio (PLR) and the combination of white blood cell (WBC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), neutrophil lymphocyte ratio (NLR), PLR, C reactive protein (CRP) and procalcitonin (PCT) in predicting the severity of NEC, and to construct a model to differ surgically NEC from non-surgically NEC. METHODS: A retrospective analysis was performed on 191 premature infants with NEC. Based on the inclusion and exclusion criteria, 90 infants with Stage II and IIIA NEC were enrolled in this study, including surgical/death NEC (n = 38) and medical NEC (n = 52). The values of inflammatory biomarkers were collected within 24 h of onset. RESULTS: The univariate analysis revealed that the values of WBC (p = 0.040), ANC (p = 0.048), PLR (p = 0.009), CRP (p = 0.016) and PCT (p < 0.01) in surgical/death NEC cohort were significantly higher than medical NEC cohort. Binary multivariate logistic regression analysis indicates that ANC, PLR, CRP, and PCT are capable of distinguishing infants with surgical/death NEC, and the AUC of the regression equation was 0.79 (95% CI 0.64-0.89; sensitivity 0.63; specificity 0.88), suggesting the equation has a good discrimination. IMPLICATIONS FOR PRACTICE AND RESEARCH: Elevated PLR is associated with severe inflammation in surgical/death NEC patients. The prediction modelling of combination of ANC, PLR, CRP and PCT can differentiate surgical/death NEC from infants with medical NEC, which may improve risk awareness and facilitate effective communication between nurses and clinicians. However, multicentre research is needed to verify these findings for better clinical management of NEC.

Association of both depressive symptoms scores and specific depressive symptoms with all-cause and cardiovascular disease mortality.

BACKGROUND: The presence of depression related to an increased risk of all-cause and cardiovascular disease (CVD) mortality has been reported. However, studies conducted on certain specific depressive symptoms are scarce. Our purpose was to assess the effect of both depressive symptoms scores and certain specific depressive symptoms on all-cause and CVD mortality. METHODS: In the present cohort study, all participants, aged 18 years or older, were enrolled in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2014. Depressive symptoms score was assessed using the validated 9-item Patient Health Questionnaire Depression Scale (PHQ-9), which ranges from 0 to 27, with a PHQ-9 score ≥ 10 diagnosed as depression. The outcome events were all-cause and CVD mortality, which were followed up from 2005 to 2014. The associations of both depressive symptoms score and certain specific depressive symptoms with all-cause and CVD mortality were examined by weighted multivariable proportional hazards models. RESULTS: A total of 26,028 participants aged ≥ 18 years were included in the statistical analysis, including 12,813 (49.2%) males and 13,215 (50.8%) females, with a mean (SD) age of 47.34 (18.86) years. During the 9.32 (3.20) years of mean (SD) follow-up, 3261 deaths were recorded, of which 826 were cardiovascular deaths. All-cause mortality was 16.87/1000 person-years in subjects with depression. In terms of CVD mortality, these figures were 4.53/1000 person-years. In the full model (model 3), elevated depressive symptoms scores were independently associated with an increased risk of all-cause mortality (Highest depression symptom score group: adjusted hazard ratio, 1.63; 95% CI 1.44-1.85) and CVD mortality (Highest depression symptom score group: adjusted hazard ratio, 1.73; 95% CI 1.34-2.24). All 9 specific depressive symptoms that make up the PHQ-9 were related to an increased risk of all-cause mortality. However, only 3 symptoms, including trouble sleeping or sleeping too much, poor appetite or overeating, and suicidal ideation, were no significantly associated with an increased risk of CVD mortality. CONCLUSIONS: The elevated depressive symptoms scores were strongly associated with an increased risk of all-cause and CVD mortality in US adults. Furthermore, all 9 specific depressive symptoms were associated with high all-cause mortality. However, trouble sleeping or sleeping too much, poor appetite or overeating, and suicidal ideation might not increase the risk of CVD mortality.

Clinical features and multiomics profiles indicate coagulation and platelet dysfunction in COVID-19 viral sepsis.

Increased cases of sepsis during COVID-19 in the absence of known bacterial pathogens highlighted role of viruses as causative agents of sepsis. In this study, we investigated clinical, laboratory, proteomic, and metabolomic characteristics of viral sepsis patients (n = 45) and compared them to non-sepsis patients with COVID-19 (n = 186) to identify molecular mechanisms underlying the pathology of viral sepsis in COVID-19. We identified unique metabolomic and proteomic signatures that suggest a substantial perturbation in the coagulation, complement, and platelet activation pathways in viral sepsis. Our proteomic data indicated elevated coagulation pathway protein (fibrinogen), whereas a decrease in many of the complement proteins was observed. These alterations were associated with the functional consequences such as susceptibility to secondary bacterial infections and potentially contributing to both local and systemic disease phenotypes. Our data provide novel aspect of COVID-19 pathology that is centered around presence of sepsis phenotype in COVID-19.

A novel bispecific peptide targeting PD-1 and PD-L1 with combined antitumor activity of T-cells derived from the patients with TSCC.

Programmed death-1 (PD-1) and programmed death ligand-1 (PD-L1) are key immune checkpoints (ICs) that critically influence immunotherapy. Tumor resistance to single IC-targeting drugs has increased interest in dual-target drugs, which have shown feasibility for cancer treatment. In this study, we aimed to develop dual-target peptide drugs targeting the PD-1/PD-L1 pathway and to evaluate their efficacy compared to functional antibodies in enhancing the cytotoxicity of human T cells against tongue squamous carcinoma cell lines. Through sequence analysis and peptide truncation, we modified a pre-existing peptide named nABPD-1 targeting PD-1. Subsequently, we obtained two novel peptides named nABPD-2 and nABPD-3, with nABPD-2 showing an enhanced affinity for human PD-1 protein compared to nABPD-1. Importantly, nABPD-2 exhibited dual-targeting capability, possessing a high affinity for both PD-L1 and PD-1. Furthermore, nABPD-2 effectively promoted the cytotoxicity of human T cells against tongue squamous carcinoma cell lines, surpassing the efficacy of anti-PD-1 or anti-PD-L1 functional antibodies alone. Considering that nABPD-2 has lower production costs and dose requirements, it can potentially be used in therapeutic applications.

Scene-aware Foveated Neural Radiance Fields.

Foveated rendering provides an idea for improving the image synthesis performance of neural radiance fields (NeRF) methods. In this paper, we propose a scene-aware foveated neural radiance fields method to synthesize high-quality foveated images in complex VR scenes at high frame rates. Firstly, we construct a multi-ellipsoidal neural representation to enhance the neural radiance field's representation capability in salient regions of complex VR scenes based on the scene content. Then, we introduce a uniform sampling based foveated neural radiance field framework to improve the foveated image synthesis performance with one-pass color inference, and improve the synthesis quality by leveraging the foveated scene-aware objective function. Our method synthesizes high-quality binocular foveated images at the average frame rate of 66 frames per second (FPS) in complex scenes with high occlusion, intricate textures, and sophisticated geometries. Compared with the state-of-the-art foveated NeRF method, our method achieves significantly higher synthesis quality in both the foveal and peripheral regions with 1.41-1.46× speedup. We also conduct a user study to prove that the perceived quality of our method has a high visual similarity with the ground truth.

Organofluorosilicon Modified Polyacrylate with the Unidirectional Migration Promotion of Disperse Dyes toward Polyester Fabric for Wash-Free Digital Inkjet Dyeing.

The printing and dyeing industry is currently accelerating toward a direction of high efficiency, energy conservation, environmental protection, and integration with digitalization. Disperse dye wash-free digital inkjet dyeing is a revolutionary breakthrough for cleaning and coloring polyester fabric. Based on the solubility parameters and the hot-melt dyeing characteristics of disperse dyes, soft, hard, and functional monomers of acrylate were used as the main body. Moreover, single-vinyl fluorinated polysiloxane and divinyl polysiloxane with low solubility parameters were used as modified monomers. A modified polyacrylate (PFSMA) adhesive containing silicon in the main chain and fluorine silicon in the side chain was prepared via miniemulsion polymerization. Using disperse digital inkjet dyeing of polyester fabric without washing can realize energy saving, emission reduction, and carbon reduction. Results showed that the optimum preparation conditions of PFSMA were as follows: DVFS molecular weight of 957 g/mol and DVFS content of 2.5 wt %. Compared with that of polyacrylate (PA), the glass-transition temperature of PFSMA film decreased, and its water resistance, toughness, and adhesion enhanced. When the PFSMA content in the wash-free disperse red ink was 8 wt %, the color yields of the front and back of the PFSMA jet-dyed polyester fabric were 18.86 and 13.28, respectively. Moreover, the color yield of the front of PFSMA jet-dyed polyester fabric was 39.9% higher than that of the pure liquid disperse red jet-dyed fabric. The simulated fixation rate was 87.9%, approximately 2.9 times higher than that of the PA wash-free jet-dyed fabric. The color fastness to dry rubbing reached level 4 and the color fastness to wet rubbing reached level 3-4, which was one level higher than that of pure liquid disperse red jet-dyed fabrics. The color fastness to soaping reached grade 5 and the color fastness to heat compression reached grades 4-5 and above. The fabric was a little firmer but smoother. The color properties, color fastness, and hand feeling of the PFSMA wash-free jet-dyed polyester fabric exceeded the levels of commercially available adhesives.

[Chest computed tomography manifestations in neonates with chronic granulomatous disease]. / æ–°ç”Ÿå„¿æ ¢æ€§è‚‰èŠ½è‚¿ç— èƒ¸éƒ¨è®¡ç®—æœºæ–­å±‚æ‰«æçš„ç‰¹å¾åˆ†æž.

OBJECTIVES: To study chest computed tomography (CT) manifestations in neonates with chronic granulomatous disease (CGD) to provide clues for early diagnosis of this disease. METHODS: A retrospective analysis was conducted on the clinical data and chest CT scan results of neonates diagnosed with CGD from January 2015 to December 2022 at Anhui Provincial Children's Hospital. RESULTS: Nine neonates with CGD were included, with eight presenting respiratory symptoms as the initial sign. Chest CT findings included: consolidation in all 9 cases; nodules in all 9 cases, characterized by multiple, variably sized scattered nodules in both lungs; masses in 4 cases; cavities in 3 cases; abscesses in 6 cases; bronchial stenosis in 2 cases; pleural effusion, interstitial changes, and mediastinal lymphadenopathy each in 1 case. CT enhancement scans showed nodules and masses with uneven or ring-shaped enhancement; no signs of pulmonary emphysema, lung calcification, halo signs, crescent signs, bronchiectasis, or scar lesions were observed. There was no evidence of rib or vertebral bone destruction. Fungal infections were present in 8 of the 9 cases, including 6 with Aspergillus infections; three of these involved mixed infections with Aspergillus, with masses most commonly associated with mixed Aspergillus infections (3/4). CONCLUSIONS: The primary manifestations of neonatal CGD on chest CT are consolidation, nodules, and/or masses, with Aspergillus as a common pathogen. These features can serve as early diagnostic clues for neonatal CGD.

The influence of psychological change factors of tennis training strategy using optimized recurrent neural network and artificial intelligence.

Due to the specialization of tennis technical training, the teaching focus of tennis teaching has gradually shifted to the psychological skills training of tennis players. This work addresses the impact of psychological factors on tennis players' insufficient concentration in teaching and training on match results. It discusses the psychological changes' influencing factors in tennis training strategies and analyzes the current psychological changes that are easy to occur in tennis teaching. The Recurrent Neural Network (RNN) can simulate the human brain's information processing and learning process to establish models to study human psychological changes. To explore the influence of psychological changes on tennis training, artificial intelligence technology is combined to optimize the performance of RNN, and a prediction model of psychological distress in tennis training is constructed. Additionally, a questionnaire is applied to compare the sports state of tennis players before and after the psychological regulation intervention. The findings demonstrate that following psychological regulation, 73 % of players perform as usual, 20 % present exceptionally well, and 7 % do not perform as well as usual. These results indicate an improvement compared to previous performances, highlighting the efficacy of psychological regulation supported by optimized RNN under AI assistance. This study aims to foster a consistently positive psychological state among tennis players during daily training and competitions, ensuring that their competitive performance levels remain normal or even exceed their usual standards.

Polyploid giant cancer cells induced by Docetaxel exhibit a senescence phenotype with the expression of stem cell markers in ovarian cancer cells.

Docetaxel (Doc) plays a crucial role in clinical antineoplastic practice. However, it is continuously documented that tumors frequently develop chemoresistance and relapse, which may be related to polyploid giant cancer cells (PGCCs). The aim of this study was investigate the formation mechanism and biological behavior of PGCCs induced by Doc. Ovarian cancer cells were treated with Doc, and then the effect of Doc on cellular viability was evaluated by MTT assay and microscopic imaging analysis. The biological properties of PGCCs were further evaluated by Hoechst 33342 staining, cell cycle and DNA content assay, DNA damage response (DDR) signaling detection, ß-galactosidase staining, mitochondrial membrane potential detection, and reverse transcription-quantitative polymerase chain reaction. The results indicated that Doc reduced cellular viability; however, many cells were still alive, and were giant and polyploid. Doc increased the proportion of cells stayed in the G2/M phase and reduced the number of cells. In addition, the expression of γ-H2A.X was constantly increased after Doc treatment. PGCCs showed senescence-associated ß-galactosidase activity and an increase in the monomeric form of JC-1. The mRNA level of octamer-binding transcription factor 4 (OCT4) and krüppel-like factor 4 (KLF4) was significantly increased in PGCCs. Taken together, our results suggest that Doc induces G2/M cell cycle arrest, inhibits the proliferation and activates persistent DDR signaling to promote the formation of PGCCs. Importantly, PGCCs exhibit a senescence phenotype and express stem cell markers.