Gaming self-consistent field theory: Generative block polymer phase discovery.

Block polymers are an attractive platform for uncovering the factors that give rise to self-assembly in soft matter owing to their relatively simple thermodynamic description, as captured in self-consistent field theory (SCFT). SCFT historically has found great success explaining experimental data, allowing one to construct phase diagrams from a set of candidate phases, and there is now strong interest in deploying SCFT as a screening tool to guide experimental design. However, using SCFT for phase discovery leads to a conundrum: How does one discover a new morphology if the set of candidate phases needs to be specified in advance? This long-standing challenge was surmounted by training a deep convolutional generative adversarial network (GAN) with trajectories from converged SCFT solutions, and then deploying the GAN to generate input fields for subsequent SCFT calculations. The power of this approach is demonstrated for network phase formation in neat diblock copolymer melts via SCFT. A training set of only five networks produced 349 candidate phases spanning known and previously unexplored morphologies, including a chiral network. This computational pipeline, constructed here entirely from open-source codes, should find widespread application in block polymer phase discovery and other forms of soft matter.

Circadian rhythm regulation in the immune system.

Circadian rhythms are a ubiquitous feature in nearly all living organisms, representing oscillatory patterns with a 24-h cycle that are widespread across various physiological processes. Circadian rhythms regulate a multitude of physiological systems, including the immune system. At the molecular level, most immune cells autonomously express clock-regulating genes, which play critical roles in regulating immune cell functions. These functions encompass migration, phagocytic activity, immune cell metabolism (such as mitochondrial structural function and metabolism), signalling pathway activation, inflammatory responses, innate immune recognition, and adaptive immune processes (including vaccine responses and pathogen clearance). The endogenous circadian clock orchestrates multifaceted rhythmicity within the immune system, optimizing immune surveillance and responsiveness; this bears significant implications for maintaining immune homeostasis and resilience against diseases. This work provides an overview of circadian rhythm regulation within the immune system.

Unlocking the Potential of Oxidative Asymmetric Catalysis with Continuous Flow Electrochemistry.

In the field of catalytic asymmetric synthesis, the less-treated path lies in oxidative catalytic asymmetric transformations. The hurdles of pinpointing the appropriate chemical oxidants and addressing their compatibility issues with catalysts and functionalities present significant challenges. Organic electrochemistry, employing traceless electrons for redox reactions, is underscored as a promising solution. However, the commonly used electrolysis in batch cells introduces its own set of challenges, hindering the advancement of electrochemical asymmetric catalysis. Here we introduce a microfluidic electrochemistry platform with single-pass continuous flow reactors that exhibits a wide-ranging applicability to various oxidative asymmetric catalytic transformations. This is exemplified through the sulfenylation of 1,3-dicarbonyls, dehydrogenative C-C coupling, and dehydrogenative alkene annulation processes. The unique properties of microfluidic electrochemical reactors not only eliminate the need for chemical oxidants but also enhance reaction efficiency and reduce the use of additives and electrolytes. These salient features of microfluidic electrochemistry expedite the discovery and development of oxidative asymmetric transformations. In addition, the continuous production facilitated by parallel single-pass reactors ensures straightforward reaction upscaling, removing the necessity for reoptimization across various scales, as evidenced by direct translation from milligram screening to hectogram asymmetric synthesis.

Adaptive Ion Channels Formed in Ultrathin and Semicrystalline Polymer Interphases for Stable Aqueous Batteries.

Aqueous Zn batteries have recently emerged as promising candidates for large-scale energy storage, driven by the need for a safe and cost-effective technology with sufficient energy density and readily accessible electrode materials. However, the energy density and cycle life of Zn batteries have been limited by inherent chemical, morphological, and mechanical instabilities at the electrode-electrolyte interface where uncontrolled reactions occur. To suppress the uncontrolled reactions, we designed a crystalline polymer interphase for both electrodes, which simultaneously promotes electrode reversibility via fast and selective Zn transport through the adaptive formation of ion channels. The interphase comprises an ultrathin layer of crystalline poly(1H,1H,2H,2H-perfluorodecyl acrylate), synthesized and applied as a conformal coating in a single step using initiated chemical vapor deposition (iCVD). Crystallinity is optimized to improve interphase stability and Zn-ion transport. The optimized interphase enables a cycle life of 9500 for Zn symmetric cells and over 11,000 for Zn-MnO2 full-cell batteries. We further demonstrate the generalizability of this interphase design using Cu and Li as examples, improving their stability and achieving reversible cycling in both. The iCVD method and molecular design unlock the potential of highly reversible and cost-effective aqueous batteries using earth-abundant Zn anode materials, pointing to grid-scale energy storage.

Embracing the era of antimicrobial peptides with marine organisms.

Covering: 2018 to Jun of 2023The efficiency of traditional antibiotics has been undermined by the proliferation of antibiotic-resistant pathogenic microorganisms, necessitating the pursuit of innovative therapeutic agents. Antimicrobial peptides (AMPs), which are part of host defence peptides found ubiquitously in nature, exhibiting a wide range of activity towards bacteria, fungi, and viruses, offer a highly promising candidate solution. The efficacy of AMPs can frequently be augmented via alterations to their amino acid sequences or structural adjustments. Given the vast reservoir of marine life forms and their distinctive ecosystems, marine AMPs stand as a burgeoning focal point in the quest for alternative peptide templates extracted from natural sources. Advances in identification and characterization techniques have accelerated the discoveries of marine AMPs, thereby stimulating AMP customization, optimization, and synthesis research endeavours. This review presents an overview of recent discoveries related to the intriguing qualities of marine AMPs. Emphasis will be placed upon post-translational modifications (PTMs) of marine AMPs and how they may impact functionality and potency. Additionally, this review considers ways in which marine PTM might support larger-scale, heterologous AMP manufacturing initiatives, providing insights into translational applications of these important biomolecules.

Construction and validation of a novel tumor morphology immune inflammatory nutritional score (TIIN score) for intrahepatic cholangiocarcinoma: a multicenter study.

BACKGROUND: Tumor morphology, immune function, inflammatory levels, and nutritional status play critical roles in the progression of intrahepatic cholangiocarcinoma (ICC). This multicenter study aimed to investigate the association between markers related to tumor morphology, immune function, inflammatory levels, and nutritional status with the prognosis of ICC patients. Additionally, a novel tumor morphology immune inflammatory nutritional score (TIIN score), integrating these factors was constructed. METHODS: A retrospective analysis was performed on 418 patients who underwent radical surgical resection and had postoperative pathological confirmation of ICC between January 2016 and January 2020 at three medical centers. The cohort was divided into a training set (n = 272) and a validation set (n = 146). The prognostic significance of 16 relevant markers was assessed, and the TIIN score was derived using LASSO regression. Subsequently, the TIIN-nomogram models for OS and RFS were developed based on the TIIN score and the results of multivariate analysis. The predictive performance of the TIIN-nomogram models was evaluated using ROC survival curves, calibration curves, and clinical decision curve analysis (DCA). RESULTS: The TIIN score, derived from albumin-to-alkaline phosphatase ratio (AAPR), albumin-globulin ratio (AGR), monocyte-to-lymphocyte ratio (MLR), and tumor burden score (TBS), effectively categorized patients into high-risk and low-risk groups using the optimal cutoff value. Compared to individual metrics, the TIIN score demonstrated superior predictive value for both OS and RFS. Furthermore, the TIIN score exhibited strong associations with clinical indicators including obstructive jaundice, CEA, CA19-9, Child-pugh grade, perineural invasion, and 8th edition AJCC N stage. Univariate and multivariate analysis confirmed the TIIN score as an independent risk factor for postoperative OS and RFS in ICC patients (p < 0.05). Notably, the TIIN-nomogram models for OS and RFS, constructed based on the multivariate analysis and incorporating the TIIN score, demonstrated excellent predictive ability for postoperative survival in ICC patients. CONCLUSION: The development and validation of the TIIN score, a comprehensive composite index incorporating tumor morphology, immune function, inflammatory level, and nutritional status, significantly contribute to the prognostic assessment of ICC patients. Furthermore, the successful application of the TIIN-nomogram prediction model underscores its potential as a valuable tool in guiding individualized treatment strategies for ICC patients. These findings emphasize the importance of personalized approaches in improving the clinical management and outcomes of ICC.

Development and Application of a Multidimensional Database for the Detection of Quaternary Ammonium Compounds and Their Phase I Hepatic Metabolites in Humans.

The COVID-19 pandemic has led to significantly increased human exposure to the widely used disinfectants quaternary ammonium compounds (QACs). Xenobiotic metabolism serves a critical role in the clearance of environmental molecules, yet limited data are available on the routes of QAC metabolism or metabolite levels in humans. To address this gap and to advance QAC biomonitoring capabilities, we analyzed 19 commonly used QACs and their phase I metabolites by liquid chromatography-ion mobility-tandem mass spectrometry (LC-IM-MS/MS). In vitro generation of QAC metabolites by human liver microsomes produced a series of oxidized metabolites, with metabolism generally occurring on the alkyl chain group, as supported by MS/MS fragmentation. Discernible trends were observed in the gas-phase IM behavior of QAC metabolites, which, despite their increased mass, displayed smaller collision cross-section (CCS) values than those of their respective parent compounds. We then constructed a multidimensional reference SQLite database consisting of m/z, CCS, retention time (rt), and MS/MS spectra for 19 parent QACs and 81 QAC metabolites. Using this database, we confidently identified 13 parent QACs and 35 metabolites in de-identified human fecal samples. This is the first study to integrate in vitro metabolite biosynthesis with LC-IM-MS/MS for the simultaneous monitoring of parent QACs and their metabolites in humans.

Predictive value of HTS grade in patients with intrahepatic cholangiocarcinoma undergoing radical resection: a multicenter study from China.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICC) is a highly malignant tumor with a poor prognosis. This study aimed to investigate whether Hemoglobin, Albumin, Lymphocytes, and Platelets (HALP) score and Tumor Burden Score (TBS) serves as independent influencing factors following radical resection in patients with ICC. Furthermore, we sought to evaluate the predictive capacity of the combined HALP and TBS grade, referred to as HTS grade, and to develop a prognostic prediction model. METHODS: Clinical data for ICC patients who underwent radical resection were retrospectively analyzed. Univariate and multivariate Cox regression analyses were first used to find influencing factors of prognosis for ICC. Receiver operating characteristic (ROC) curves were then used to find the optimal cut-off values for HALP score and TBS and to compare the predictive ability of HALP, TBS, and HTS grade using the area under these curves (AUC). Nomogram prediction models were constructed and validated based on the results of the multivariate analysis. RESULTS: Among 423 patients, 234 (55.3%) were male and 202 (47.8) were aged ≥ 60 years. The cut-off value of HALP was found to be 37.1 and for TBS to be 6.3. Our univariate results showed that HALP, TBS, and HTS grade were prognostic factors of ICC patients (all P < 0.05), and ROC results showed that HTS had the best predictive value. The Kaplan-Meier curve showed that the prognosis of ICC patients was worse with increasing HTS grade. Additionally, multivariate regression analysis showed that HTS grade, carbohydrate antigen 19-9 (CA19-9), tumor differentiation, and vascular invasion were independent influencing factors for Overall survival (OS) and that HTS grade, CA19-9, CEA, vascular invasion and lymph node invasion were independent influencing factors for recurrence-free survival (RFS) (all P < 0.05). In the first, second, and third years of the training group, the AUCs for OS were 0.867, 0.902, and 0.881, and the AUCs for RFS were 0.849, 0.841, and 0.899, respectively. In the first, second, and third years of the validation group, the AUCs for OS were 0.727, 0.771, and 0.763, and the AUCs for RFS were 0.733, 0.746, and 0.801, respectively. Through the examination of calibration curves and using decision curve analysis (DCA), nomograms based on HTS grade showed excellent predictive performance. CONCLUSIONS: Our nomograms based on HTS grade had excellent predictive effects and may thus be able to help clinicians provide individualized clinical decision for ICC patients.

A nomogram for predicting risk factors of testicular salvage after testicular torsion in children.

OBJECTIVES: This study aimed to establish a nomogram for predicting the probability of testicular salvage after testicular torsion in children. METHODS: We retrospectively collected data of children with testicular torsion who were treated at Shenzhen Children's Hospital between September 2005 and August 2022. Of the training cohort, 113 patients who underwent orchiectomy and five with testicular atrophy after orchiopexy were included in the failed testicular salvage group. Additionally, 37 patients who underwent orchiopexy without postoperative testicular atrophy were included in the successful testicular salvage group. The predictive factors affecting testicular salvage were determined using univariate and multivariate logistic regression analyses; a nomogram was constructed. The nomogram was verified using data from the validation group. RESULTS: Using multivariate logistic regression analysis, the independent risk factors of testicular salvage after testicular torsion were symptom duration (p = 0.034), intratesticular blood flow (p = 0.003), spermatic cord torsion degree (p = 0.037), and monocyte count (odds ratio: 0.012, p = 0.036). A nomogram was established based on these four risk factors. In the training cohort, the area under the receiver operating characteristic curve was 0.969. The area under the receiver operating characteristic curve of the verification cohort was 0.965, indicating good discrimination ability of the nomogram. Increased symptom duration without intratesticular blood flow increased the monocyte count and spermatic cord torsion degree and decreased the success rate of testicular salvage. CONCLUSION: This prediction model could obtain the corresponding probability of testicular salvage according to the clinical characteristics of different patients with testicular torsion, providing reference for clinicians and parents.

Advantages of single-site laparoscopic orchiopexy for palpable undescended testes in children: a prospective comparison study.

PURPOSE: To evaluate the feasibility of single-site laparoscopic orchiopexy for palpable undescended testes in children. METHODS: We prospectively studied patients with undescended testes between July 2021 and June 2022. In total, 223 patients were included in our study: 105 underwent single-site laparoscopic orchiopexy and 118 underwent conventional laparoscopic orchiopexy. During single-site laparoscopic orchiopexy, 3 ports were inserted within the umbilicus. RESULTS: No differences were observed between the groups in terms of age and laterality. For unilateral undescended testes, the operating time was longer in the single site group than in the conventional group at the early stages (55.31 ± 12.04 min vs. 48.14 ± 14.39 min, P = 0.007), but it was similar to the conventional group at the later stages (48.82 ± 13.49 min vs. 48.14 ± 14.39 min, P = 0.78). Testicular ascent occurred in one patient from each group. There was no significant difference in the success rate between the single-site group and the conventional group (99.0% vs. 99.2%, P = 0.93). In the single-site group, no visible abdominal scarring was observed, while in the conventional group, there were two noticeable scars on the abdomen. CONCLUSION: Single-site laparoscopic orchiopexy offers superior cosmetic results and comparable success rates compared to conventional laparoscopic orchiopexy for palpable undescended testes.

Unlocking policy effects: Water resources management plans and urban water pollution.

Water resource management, as a foundation for supporting sustainable urban development, has garnered increasing attention from scholars. Developing effective water resource management plans is a major challenge faced by countries worldwide. This study uses the 2015 Water Pollution Control and Prevention Action Plan (WPCAP) in China as a natural experiment and employs a Difference-in-Differences (DID) model to estimate the relationship between WPCAP and urban water pollution from 2010 to 2021. The findings are as follows: 1) WPCAP reduces water pollution. 2) WPCAP decreases water pollution in high-policy-pressure cities but increases water pollution in low-policy-pressure cities within a 60 km radius, particularly having a significantly negative impact on water pollution in low-policy-pressure cities with low altitude. 3) optimizing industrial and domestic water use, as well as enhancing sewage treatment capabilities, are crucial pathways through which WPCAP reduces water pollution. Additionally, WPCAP significantly improves water pollution control capabilities in cities with abundant water resources, large cities, and industrialized cities. 4) although WPCAP's ability to control water pollution increases management costs, it also raises residential income and promotes population growth. These findings have important implications for the sustainable development of water resources in emerging countries, including China.

Other's shoes also fit well: AI technologies contribute to China's blue skies as well as carbon reduction.

Artificial intelligence (AI) technology represents a disruptive innovation that has garnered significant interest among researchers for its potential applications in ecological and environmental management. While many studies have investigated the impact of AI on carbon emissions, relatively few have delved into its relationship with air pollution. This study sets out to explore the causal mechanisms and constraints linking AI technologies and air pollution, using provincial panel data collected from 2007 to 2020 in China. Furthermore, this study examines the distinct pathways through which AI technology can ameliorate air pollution and reduce carbon emissions. The findings reveal the following key insights: (1) AI technologies have the capacity to significantly reduce air pollution, particularly in terms of PM2.5 and SO2 levels. (2) AI technologies contribute to enhanced air quality by facilitating adjustments in energy structures, improving energy efficiency, and strengthening digital infrastructure. Nonetheless, it is important to note that adjusting the energy structure remains the most practical approach for reducing carbon emissions. (3) The efficacy of AI in controlling air pollution is influenced by geographical location, economic development level, level of information technology development, resource dependence, and public attention. In conclusion, this study proposes novel policy recommendations to offer fresh perspectives to countries interested in leveraging AI for the advancement of ecological and environmental governance.

Revolutionizing energy practices: Unleashing the power of artificial intelligence in corporate energy transition.

Corporate energy transition is crucial for long-term sustainable development. The widely discussed Artificial Intelligence (AI), as a disruptive technological innovation, is highly potential for enhancing environment performance. However, the specific impact of AI on the process of corporate energy transition and its underlying mechanisms have not been fully explored. This study focuses on A-share listed corporates in Shanghai and Shenzhen stock markets in China spanning from 2011 to 2021. Based on corporate annual report information and information from over 200,000 patent application texts, we innovatively construct indicators for corporate energy transition and AI technology application. Furthermore, we empirically investigate the impact of AI technology on corporate energy transition and its potential mechanisms through combining information asymmetry theory and institutional theory. The empirical results indicate that: 1) AI can drive corporate energy transition and the promoting effect of AI collaborative innovation on corporate energy transition should not be ignored. 2) AI can help corporates achieve energy transition through pathways such as mitigating information asymmetry, reducing financing constraints, adjusting sustainable development concepts and practices. 3) The driving effect of AI on corporate energy transition varies depending on the characteristics of different types of corporates, industries, and regions. This study provides strategic guidance and decision support for business managers and policymakers, assisting both corporates and governments in better utilizing AI technology during the social energy transition process to achieve a dual optimization of environmental and economic goals.

Effectiveness of Electroencephalography Neurofeedback for Improving Working Memory and Episodic Memory in the Elderly: A Meta-Analysis.

Background and Objective: Existing evidence indicates the potential benefits of electroencephalography neurofeedback (NFB) training for cognitive function. This study aims to comprehensively review all available evidence investigating the effectiveness of NFB on working memory (WM) and episodic memory (EM) in the elderly population. Material and Methods: A systematic search was conducted across five databases to identify clinical trials examining the impact of NFB on memory function in healthy elderly individuals or those with mild cognitive impairment (MCI). The co-primary outcomes focused on changes in WM and EM. Data synthesis was performed using a random-effects meta-analysis. Results: Fourteen clinical trials (n = 284) were included in the analysis. The findings revealed that NFB was associated with improved WM (k = 11, reported as Hedges' g = 0.665, 95% confidence [CI] = 0.473 to 0.858, p < 0.001) and EM (k = 12, 0.595, 0.333 to 0.856, p < 0.001) in the elderly, with moderate effect sizes. Subgroup analyses demonstrated that NFB had a positive impact on both WM and EM, not only in the healthy population (WM: k = 7, 0.495, 0.213 to 0.778, p = 0.001; EM: k = 6, 0.729, 0.483 to 0.976, p < 0.001) but also in those with MCI (WM: k = 6, 0.812, 0.549 to 1.074, p < 0.001; EM: k = 6, 0.503, 0.088 to 0.919, p = 0.018). Additionally, sufficient training time (totaling more than 300 min) was associated with a significant improvement in WM (k = 6, 0.743, 0.510 to 0.976, p < 0.001) and EM (k = 7, 0.516, 0.156 to 0.876, p = 0.005); however, such benefits were not observed in groups with inadequate training time. Conclusions: The results suggest that NFB is associated with enhancement of both WM and EM in both healthy and MCI elderly individuals, particularly when adequate training time (exceeding 300 min) is provided. These findings underscore the potential of NFB in dementia prevention or rehabilitation.

Phage-Displayed Nanobody as a Sensitive Nanoprobe to Enhance Chemiluminescent Immunoassay for Cronobacter sakazakii Detection in Dairy Products.

The exploitation of stable, high-affinity, and low-cost nanoprobes is essential to develop immunoassays for real-time monitoring of foodborne pathogens, so as to safeguard human health. The possible interaction of the Fc fragment of antibodies with spA protein on Staphylococcus aureus will result in unexpected interference. To address this consideration, we described herein for the first time the development of nanobodies that by definition are devoid of the Fc fraction. These nanobodies directed against Cronobacter sakazakii (C. sakazakii) were retrieved from a dedicated immune phage-displayed nanobody library. The binders showed superiority of low cost, strong stability, high binding affinity, and adequate load capacity. Thereafter, a phage-mediated sandwich enzyme-linked immunosorbent assay (ELISA) was constructed by using Cs-Nb2 as an antigen-capturing antibody and phage-displayed Cs-Nb1 as a detection probe. To further enhance the sensitivity, a chemiluminescent enzyme immunoassay (CISA) was established by replacing the substrate from 3,3',5,5'-tetramethylbenzidine (TMB) to luminol, providing a limit of detection of 1.04 × 104 CFU/mL, with a recovery of 98.15-114.63% for the detection of C. sakazakii in dairy products. The proposed nanobody-based phage-mediated sandwich CLISA shows various advantages, including high sensitivity, cost effectiveness, enhanced loading capacity of the enzyme, and high resistance to the matrix effect, providing a strategy for the design of immunoassays toward foodborne pathogens.

Enhancing Oriented Immobilization Efficiency: A One-for-Two Organism-Bispecific Nanobody Scaffold for Highly Sensitive Detection of Foodborne Pathogens.

Nanobodies have gained widespread application in immunoassays. However, their small size presents a significant challenge in achieving effective immobilization and optimal sensitivity. Here, we present a novel "one-for-two"-oriented immobilization platform based on an organism-bispecific nanobody (O-BsNb) scaffold, enabling highly sensitive detection of two bacterial pathogens. Through genetic engineering, a bispecific nanobody (BsNb) was engineered, targeting Salmonella spp. and Vibrio parahaemolyticus. The O-BsNb scaffold allowed one nanobody to bind specifically to inactivated bacteria, forming an organism-oriented immobilization platform, while the other served as the capture antibody. Consequently, the O-BsNb bioscaffold-based ELISA (O-ELISA) for individual detection of S. enteritidis and V. parahaemolyticus was established. When compared to the sandwich ELISA utilizing passive immobilization of monovalent nanobodies, the O-ELISA exhibited a remarkable 13.4- and 13.7-fold improvement in LOD for S. enteritidis and V. parahaemolyticus, respectively, highlighting the enhanced immobilization efficacy of the O-ELISA. Furthermore, the feasibility and reproducibility of the assay in practical samples were meticulously evaluated, revealing exemplary performance in terms of recovery precision and assay stability. These findings demonstrate the significant potential of the O-ELISA platform for the sensitive detection of macromolecules, opening new avenues for efficient pathogen identification in foodborne safety and clinical diagnostics.

Microalgae are not an umbrella solution for power industry waste abatement but could play a role in their valorization.

Microalgae have long been regarded as a promising solution for biological carbon abatement from the power industry, offering renewable biomass without competing for land or water resources used for food crops. In this study, we extensively examined the application of photosynthetic microorganisms for closing carbon, nitrogen, and micronutrient loops in the power industry. Subsequently, we explored the bottom-up integration of algal biorefineries into power industry waste streams for increased economic benefits and reduced environmental impacts. Analysis of the available data indicated that microalgae integration with the power industry is primarily performed using flue-gas-assisted cultivation. This approach allows for carbon sequestration typically below one gram per liter per day, too low to significantly impact carbon abatement at achievable scales of microalgae cultivation. Alternative approaches are also being explored. For example, soluble bicarbonate platforms allow for higher biomass productivity and temporary carbon storage. Meanwhile, the use of ashes and waste heat and thermophilic strains can result in lower cultivation costs and better control of cultivation conditions. These approaches offer further incremental improvement to microalgae-based carbon abatement systems in the power industry but are unlikely to be an umbrella solution for carbon reduction. Consequently, in the near term, microalgae-based carbon valorization systems are likely to be limited to niche applications involving the synthesis of high-value products. For microalgae to truly transform carbon abatement processes radical improvements in both biology and engineering approaches are urgently needed.

Diethyldithiocarbamate copper nanoparticle overcomes resistance in cancer therapy without inhibiting P-glycoprotein.

Copper diethyldithiocarbamate [Cu(DDC)2] is a promising anticancer agent. However, its poor water solubility is a significant obstacle to clinical application. In previous studies, we developed a stabilized metal ion ligand complex (SMILE) method to prepare Cu(DDC)2 nanoparticle (NP) to address the drug delivery challenge. In the current study, we investigate the use of Cu(DDC)2 NP for treating P-glycoprotein (P-gp) mediated drug-resistant cancers. We tested its anticancer efficacy with extensive in vitro cell-based assays and in vivo xenograft tumor model. We also explored the mechanism of overcoming drug resistance by Cu(DDC)2 NP. Our results indicate that Cu(DDC)2 NP is not a substrate of P-gp and thus can avoid P-gp mediated drug efflux. Further, the Cu(DDC)2 NP does not inhibit the activity or the expression of P-gp.

Genetic diversity of 23 STR loci of the Guizhou Tujia ethnic minority and the phylogenetic relationships with 22 other populations.

BACKGROUND: Short tandem repeats (STR) are highly polymorphic DNA markers utilised in forensic personal identification and human population genetic research. Guizhou Tujia is one of the ancient minority groups in southwest China, however, the population has not been studied using the highly discriminating 23 STR Huaxia Platinum Kit. AIM: To obtain genetic data from 23 autosomal STRs in Guizhou Tujia and examine the population's relationship with others. SUBJECTS AND METHODS: A total of 480 individuals from the Guizhou Tujia population were analysed using 23 STR loci of Huaxia Platinum Kit. Allele frequencies and forensic parameters were estimated. Population genetic relationships were calculated by Nei's genetic distances and visualised using a variety of biostatistical methods. RESULTS: A total of 264 alleles were found, with allelic frequencies ranging from 0.0010 to 0.5104. The combined discrimination power (CDP) and the combined probability of paternity (CPE) of 23 STR loci were 0.9999999999999999999999999996 and 0.999999999710422, respectively. Guizhou Tujia showed closer genetic relationships with Hubei Tujia, Guizhou Gelao, and Guizhou Miao than with other populations. CONCLUSION: We first obtained the population genetic data of Guizhou Tujia using the 23 STR system and demonstrated its value in forensic applications. Comprehensive population comparisons showed an evident genetic affinity pattern between populations that are geographically, ethnically and linguistically related.

Gill structure and respiratory ability of Euchiloglanis kishinouyei (Osteichthyes: Siluriformes: Sisoridae).

Glyptosternoid fishes are distributed in the torrent environment of alpine canyons, where they often leave the water to climb rocky cliffs. As one of the most primitive species of glyptosternoid fishes, Euchiloglanis kishinouyei was examined in the current study to analyse its gill microstructure and respiratory ability. We first found that the oxygen consumption rate was relatively high and negatively correlated with body mass and that the average oxygen consumption at night was higher than during the day. The asphyxiation point of E. kishinouyei (5.05 ± 0.22 g) was c. 1.93 mg/L. Subsequently, the surface morphology, gross gill tissue structure, and ultra-microstructure of gill lamellae were investigated using optical microscopy and SEM. The gills showed an overall trend of regression, with five pairs of gill arches in each gill cavity. The adjacent gill filaments had large gaps, and the gill lamellae were thick. The gill filaments were closely arranged on the gill arches, their folded respiratory surface was highly vascularized with no tiny crest, and there were obvious tiny crests, grooves, pits, and pores on the nonrespiratory surface. The gill lamellae were closely embedded on both sides of gill filaments, which were composed of flat epithelial cells, basement membrane, pillar cells, and mucous cells. The gill total respiratory area correlated positively with body mass and length, whereas the gill relative respiratory area correlated negatively with body mass. We comprehensively analysed the gill microstructure and respiratory capacity of E. kishinouyei to provide fundamental data for the adaptive evolution of the gill structures of bimodally respiring fishes and offer insights into further study on the accessory air-breathing function of skin.