Nanoparticle/Engineered Bacteria Based Triple-Strategy Delivery System for Enhanced Hepatocellular Carcinoma Cancer Therapy.

Background: New treatment modalities for hepatocellular carcinoma (HCC) are desperately critically needed, given the lack of specificity, severe side effects, and drug resistance with single chemotherapy. Engineered bacteria can target and accumulate in tumor tissues, induce an immune response, and act as drug delivery vehicles. However, conventional bacterial therapy has limitations, such as drug loading capacity and difficult cargo release, resulting in inadequate therapeutic outcomes. Synthetic biotechnology can enhance the precision and efficacy of bacteria-based delivery systems. This enables the selective release of therapeutic payloads in vivo. Methods: In this study, we constructed a non-pathogenic Escherichia coli (E. coli) with a synchronized lysis circuit as both a drug/gene delivery vehicle and an in-situ (hepatitis B surface antigen) Ag (ASEc) producer. Polyethylene glycol (CHO-PEG2000-CHO)-poly(ethyleneimine) (PEI25k)-citraconic anhydride (CA)-doxorubicin (DOX) nanoparticles loaded with plasmid encoded human sulfatase 1 (hsulf-1) enzyme (PNPs) were anchored on the surface of ASEc (ASEc@PNPs). The composites were synthesized and characterized. The in vitro and in vivo anti-tumor effect of ASEc@PNPs was tested in HepG2 cell lines and a mouse subcutaneous tumor model. Results: The results demonstrated that upon intravenous injection into tumor-bearing mice, ASEc can actively target and colonise tumor sites. The lytic genes to achieve blast and concentrated release of Ag significantly increased cytokine secretion and the intratumoral infiltration of CD4/CD8+T cells, initiated a specific immune response. Simultaneously, the PNPs system releases hsulf-1 and DOX into the tumor cell resulting in rapid tumor regression and metastasis prevention. Conclusion: The novel drug delivery system significantly suppressed HCC in vivo with reduced side effects, indicating a potential strategy for clinical HCC therapy.

Quality of life analysis in patients with retinitis pigmentosa.

INTRODUCTION: Retinitis pigmentosa (RP) is a chronic progressive disease causing loss of visual acuity and ultimately blindness. This visual impairment can contribute to psychiatric comorbidity and worse overall quality of life (QOL). Our goal was to assess the relationship between the severity of disease for people with RP and QOL as it pertains to mental health, social support, disability resources, and financial factors. METHODS: This was a survey study conducted from June 2021 to February 2022 including 38 people with RP. Quality of life was assessed through a survey questionnaire focusing specifically on demographics, visual function, family, employment, social support, and mental health/well-being. Statistical analysis was conducted using a Chi-squared test for significance. RESULTS: A best-corrected visual acuity (BCVA) of less than 20/200 (p= 0.0285) and living alone (p=0.0358) were both statistically significant independent risk factors for experiencing depressive symptoms. Highest education level attained and unemployment rate were not found to be related to the development of depressive symptoms. Subjects had a higher unemployment rate (64% vs. US rate of 3.6%) and a high likelihood of reporting depressive symptoms (47.4%). CONCLUSIONS: People with RP are more likely to be unemployed and to develop depressive symptoms when compared to the general population. Similar to previous studies' findings, those with a BCVA of less than 20/200 were statistically more likely to experience depressive symptoms; living alone is a novel risk factor that is also associated with the presence of depressive symptoms. Contrary to prior findings, highest education level and unemployment status were found not to be related to the development of depressive symptoms. These patients may benefit from regular depression screenings and optional establishment of care with a psychiatrist or psychologist if they live alone or their BCVA is 20/200 or worse.

Chemo-photodynamic antitumour therapy based on Er-doped upconversion nanoparticles coated with hypocrellin B and MnO2.

An antitumour chemo-photodynamic therapy nanoplatform was constructed based on phospholipid-coated NaYF4: Yb/Er upconversion nanoparticles (UCNPs). In this work, the amphiphilic block copolymer DSPE-PEG2000 was combined with the surface ligand oleic acid of the UCNPs through hydrophobic interaction to form liposomes with a dense hydrophobic layer in which the photosensitizer hypocrellin B (HB) was assembled. The coated HB formed J-aggregates, which caused a large redshift in the absorption spectrum and improved the quantum efficiency of energy transfer. Furthermore, MnO2 nanosheets grew in-situ on the liposomes through OMn coordination. Therefore, a multifunctional tumour microenvironment (TME)-responsive theranostic nanoplatform integrating photodynamic therapy (PDT) and chemodynamic therapy (CDT) was successfully developed. The results showed that this NIR-mediated chemo-photodynamic therapy nanoplatform was highly efficient for oncotherapy.

Personalized Prediction of Postoperative Complication and Survival Among Colorectal Liver Metastases Patients Receiving Simultaneous Resection Using Machine Learning Approaches: A Multi-center Study.

BACKGROUND: To predict clinical important outcomes for colorectal liver metastases (CRLM) patients receiving colorectal resection with simultaneous liver resection by integrating demographic, clinical, laboratory, and genetic data. METHODS: Random forest (RF) models were developed to predict postoperative complications and major complications (binary outcomes), as well as progression-free survival (PFS) and overall survival (OS) (time-to-event outcomes) of the CRLM patients based on data from two hospitals. The models were validated on an external dataset from an independent hospital. The clinical utility of the models was assessed via decision curve analyses (DCA). RESULTS: There were 1067 patients included in survival prediction analyses and 1070 patients included in postoperative complication prediction analyses. The RF models provided an assessment of the model contributions of features for outcomes and suggested KRAS, BRAF, and MMR status were salient for the PFS or OS predictions. RF model of PFS showed that the Brier scores at 1-, 3-, and 5-year PFS were 0.213, 0.202 and 0.188; and the AUCs of 1-, 3- and 5-year PFS were 0.702, 0.720 and 0.743. RF model of OS revealed that Brier scores of 1-,3-, and 5-year OS were 0.040, 0.183 and 0.211; and the AUCs of 1-, 3- and 5-year OS were 0.737, 0.706 and 0.719. RF model for postoperative complication resulted in an AUC of 0.716 and a Brier score of 0.196. DCA curves clearly demonstrated that the RF models for these outcomes exhibited a superior net benefit across a wide range of threshold probabilities, signifying their favorable clinical utility. The RF models consistently exhibited robust performance in both internal cross-validation and external validation. The individualized risk profile predicted by the models closely aligned with the actual survival outcomes observed for the patients. A web-based tool (https://kanli.shinyapps.io/CRLMRF/) was provided to demonstrate the practical use of the prediction models for new patients in the clinical setting. CONCLUSION: The predictive models and a web-based tool for personalized prediction demonstrated a moderate predictive performance and favorable clinical utilities on several key clinical outcomes of CRLM patients receiving simultaneous resection, which could facilitate the clinical decision-making and inform future interventions for CRLM patients.

Neuron-level explainable AI for Alzheimer's Disease assessment from fundus images.

Alzheimer's Disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia. Early diagnosis is critical for patients to benefit from potential intervention and treatment. The retina has emerged as a plausible diagnostic site for AD detection owing to its anatomical connection with the brain. However, existing AI models for this purpose have yet to provide a rational explanation behind their decisions and have not been able to infer the stage of the disease's progression. Along this direction, we propose a novel model-agnostic explainable-AI framework, called Granu la ̲ r Neuron-le v ̲ el Expl a ̲ iner (LAVA), an interpretation prototype that probes into intermediate layers of the Convolutional Neural Network (CNN) models to directly assess the continuum of AD from the retinal imaging without the need for longitudinal or clinical evaluations. This innovative approach aims to validate retinal vasculature as a biomarker and diagnostic modality for evaluating Alzheimer's Disease. Leveraged UK Biobank cognitive tests and vascular morphological features demonstrate significant promise and effectiveness of LAVA in identifying AD stages across the progression continuum.

Sulfated glyco-based hydrogels as self-healing, adhesive, and anti-inflammatory dressings for wound healing.

Hydrogels have emerged as a new type of wound dressing materials that involved in different stages of the healing processes. However, most of the existing wound dressings mainly offer a protective and moisturizing layer to prevent cross-infection, while the anti-inflammatory and anti-oxidative properties are frequently induced by extra addition of other bioactive molecules. Here, a novel type of sulfated glyco-functionalized hydrogels for wound dressing was prepared through the hybrid supramolecular co-assembly of carbohydrate segments (FG, FGS and FG3S), fluorenylmethoxycarbonyl-diphenylalanine (Fmoc-FF), and diphenylalanine-dopamine (FFD). Implanting sulfated carbohydrates can mimic the structure of glycosaminoglycans (GAGs), promoting cell proliferation and migration, along with anti-inflammatory effects. In situ polymerization of FFD introduced a secondary covalent network to the hydrogel, meanwhile, providing anti-oxidation and adhesion properties to wound surfaces. Furthermore, the dynamic supramolecular interactions within the hydrogels also confer self-healing capabilities to the wound dressing materials. In vivo experiments further demonstrated significantly accelerated healing rates with the multifunctional hydrogel FG3S-FFD, indicating high application potential.

Precise Capture and Dynamic Release of Circulating Liver Cancer Cells with Dual-Histidine-Based Cell Imprinted Hydrogels.

Circulating tumor cells (CTCs) detection presents significant advantages in diagnosing liver cancer due to its noninvasiveness, real-time monitoring, and dynamic tracking. However, the clinical application of CTCs-based diagnosis is largely limited by the challenges of capturing low-abundance CTCs within a complex blood environment while ensuring them alive. Here, an ultrastrong ligand, l-histidine-l-histidine (HH), specifically targeting sialylated glycans on the surface of CTCs, is designed. Furthermore, HH is integrated into a cell-imprinted polymer, constructing a hydrogel with precise CTCs imprinting, high elasticity, satisfactory blood compatibility, and robust anti-interference capacities. These features endow the hydrogel with excellent capture efficiency (>95%) for CTCs in peripheral blood, as well as the ability to release CTCs controllably and alive. Clinical tests substantiate the accurate differentiation between liver cancer, cirrhosis, and healthy groups using this method. The remarkable diagnostic accuracy (94%), lossless release of CTCs, material reversibility, and cost-effectiveness ($6.68 per sample) make the HH-based hydrogel a potentially revolutionary technology for liver cancer diagnosis and single-cell analysis.

Association of preoperative aspartate aminotransferase to platelet ratio index with outcomes and tumour microenvironment among colorectal cancer with liver metastases.

This study aims to investigate applicable robust biomarkers that can improve prognostic predictions for colorectal liver metastasis (CRLM) patients receiving simultaneous resection. A total of 1323 CRLM patients from multiple centres were included. The preoperative aspartate aminotransferase to platelet ratio index (APRI) level from blood of patients were obtained. Patients were stratified into a high APRI group and a low APRI group, and comparisons were conducted by analyzing progression-free survival (PFS), overall survival (OS) and postoperative early recurrence. Tumour samples of CRLM were collected to perform single-cell RNA sequencing and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) to investigate the association of APRI levels and the tumour microenvironment of CRLM. Compared with APRI <0.33, PFS disadvantage (IPTW-adjusted HR = 1.240, P = 0.015) and OS disadvantage (IPTW- adjusted HR = 1.507, P = 0.002) of APRI ≥0.33 were preserved in the IPTW-adjusted Cox hazards regression analyses. An APRI ≥0.25 was associated with a significantly increased risk of postoperative early recurrence after adjustment (IPTW-adjusted OR = 1.486, P = 0.001). The external validation showed consistent results with the training cohort. In the high APRI group, the single-cell RNA sequencing results revealed a heightened malignancy of epithelial cells, the enrichment of inflammatory-like cancer-associated fibroblasts and SPP1+ macrophages associated with activation of malignant cells and fibrotic microenvironment, and a more suppressed-function T cells; mIHC/IF showed that PD1+ CD4+ T cells, FOXP3+ CD4+ T cells, PD1+ CD8+ T cells, FOXP3+ CD8+ T cells, SPP1+ macrophages and iCAFs were significantly increased in the intratumoral region and peritumoral region. This study contributed valuable evidence regarding preoperative APRI for predicting prognoses among CRLM patients receiving simultaneous resection and provided underlying clues supporting the association between APRI and clinical outcomes by single-cell sequencing bioinformatics analysis and mIHC/IF.

A Novel CaCu-Metal-Organic-Framework Based Multimodal Treatment Platform for Enhanced Synergistic Therapy of Hepatocellular Carcinoma.

Metal ions have attracted a lot of interest in antitumor therapy due to their unique mechanism of action. However, multiple death mechanisms associate with metal ions to synergistic antitumors have few studies mainly due to the serious challenges in designing and building metal-associated multimodal treatment platforms. Hence, a series of glutathione-activatable CaCu-based metal-organic-frameworks loaded with doxorubicin and ovalbumin are successfully designed and synthesized with an "all in one" strategy, which is modified by galactosamine-linked hyaluronic acid to prepare multimodal treatment platform (SCC/DOX@OVA-HG) for targeted delivery and synergistic antitumor therapy. SCC/DOX@OVA-HG can be rapidly degraded by the overexpressed glutathione and then releases the "cargoes" in the tumor microenvironment. The released Cu+ efficiently catalyzes H2O2 to produce highly toxic ROS for CDT, and the up-regulation of calcium ion concentration in tumor cells induced by the released Ca2+ enables calcium overload therapy, which synergically enhances the metal-related death pattern. Meanwhile, OVA combined with Ca2+/Cu2+ further activates macrophages into an M1-like phenotype to accelerate tumor cell death through immunotherapy. Besides, the released DOX can also insert into the DNA double helix for chemotherapy. Consequently, the developed SCC/DOX@OVA-HG reveals significantly improved antitumor efficacy through a multimodal synergistic therapy of chemotherapy, chemodynamic therapy, calcium overload, and immunotherapy.

Structure of a unique PSII-Pcb tetrameric megacomplex in a chlorophyll d-containing cyanobacterium.

Acaryochloris marina is a unique cyanobacterium using chlorophyll d (Chl d) as its major pigment and thus can use far-red light for photosynthesis. Photosystem II (PSII) of A. marina associates with a number of prochlorophyte Chl-binding (Pcb) proteins to act as the light-harvesting system. We report here the cryo-electron microscopic structure of a PSII-Pcb megacomplex from A. marina at a 3.6-angstrom overall resolution and a 3.3-angstrom local resolution. The megacomplex is organized as a tetramer consisting of two PSII core dimers flanked by sixteen symmetrically related Pcb proteins, with a total molecular weight of 1.9 megadaltons. The structure reveals the detailed organization of PSII core consisting of 15 known protein subunits and an unknown subunit, the assembly of 4 Pcb antennas within each PSII monomer, and possible pathways of energy transfer within the megacomplex, providing deep insights into energy transfer and dissipation mechanisms within the PSII-Pcb megacomplex involved in far-red light utilization.

Deep learning predicts prevalent and incident Parkinson's disease from UK Biobank fundus imaging.

Parkinson's disease is the world's fastest-growing neurological disorder. Research to elucidate the mechanisms of Parkinson's disease and automate diagnostics would greatly improve the treatment of patients with Parkinson's disease. Current diagnostic methods are expensive and have limited availability. Considering the insidious and preclinical onset and progression of the disease, a desirable screening should be diagnostically accurate even before the onset of symptoms to allow medical interventions. We highlight retinal fundus imaging, often termed a window to the brain, as a diagnostic screening modality for Parkinson's disease. We conducted a systematic evaluation of conventional machine learning and deep learning techniques to classify Parkinson's disease from UK Biobank fundus imaging. Our results suggest Parkinson's disease individuals can be differentiated from age and gender-matched healthy subjects with 68% accuracy. This accuracy is maintained when predicting either prevalent or incident Parkinson's disease. Explainability and trustworthiness are enhanced by visual attribution maps of localized biomarkers and quantified metrics of model robustness to data perturbations.

Impacts of the aerosol mixing state and new particle formation on CCN in summer at the summit of Mount Tai (1534m) in Central East China.

In this study, the aerosol size distributions, cloud condensation nuclei (CCN) number concentration (NCCN), single-particle chemical composition and meteorological data were collected from May 12 to June 8, 2017, at the summit of Mt. Tai. The effects of new particle formation (NPF) events and aerosol chemical components on CCN at Mt. Tai were analyzed in detail. The results showed that, NPF events significantly enhanced the CCN population, and the enhancement effect increased with increasing supersaturation (SS) value at Mt.Tai. NCCN at SS ranging from 0.1 to 0.9 % on NPF days was 10.9 %, 36.5 %, 44.6 %, 53.5 % and 51.5 % higher than that on non-NPF days from 10:00-13:00 as NPF events progressed. The effect of chemical components on CCN activation under the influence of NPF events was greater than that in the absence of NPF events. The correlation coefficients of EC-Nitrate particles (EC-Sulfate particles) and CCN at all SS levels on NPF days were 1.31-1.59 times (1.17-1.35 times) higher than those on non-NPF days. Nitrate particles promoted CCN activation but sulfate particles inhibited activation at Mt. Tai. There are differences or even opposite effects of the same group of particles on CCN activation under the influence of NPF events in different air masses. EC-Sulfate particles inhibited CCN activation at all SS levels for type I but weakly promoted activation at lower SS ranging from 0.1 to 0.3 % and weakly inhibited it at higher 0.9 % SS for type II. OCEC particles significantly inhibited CCN activation for type II, and this effect decreased with increasing SS. OCEC particles only weakly inhibited activation at SS ranging from 0.5 to 0.7 % for type I. OCEC particles only weakly inhibited this process at 0.1 % SS, while they very weakly promoted activation for SS > 0.1 %. This reveals that the CCN activity is not only related to the chemical composition of the particles, but the mixing state also has an important effect on the CCN activity.

Naphthalimide-based Functional Glycopolymeric Nanoparticles as Fluorescent Probes for Selective Imaging of Tumor Cells.

A series of functional glycopolymer nanoparticles with 1,8-naphthalimide motif was designed, synthesized and applied for tumor cell imaging. With the pH-sensitive and aggregation-induced emission (AIE) effect of the 1,8-naphthalimide fluorescent probe, the presence of glucose-based glycopolymers enhanced its water-solubility and biocompatibility. Owing to the dual tumor-targeting effects of the dense glucose part and the boronic ester modification, the obtained glycopolymers showed high affinity to tumor cells, with a much faster staining rate than normal cells, indicating a great potential for diagnosis and treatments of cancers.

Shikonin improves the effectiveness of PD-1 blockade in colorectal cancer by enhancing immunogenicity via Hsp70 upregulation.

BACKGROUND: PD-1 blockade has shown impressive clinical outcomes in colorectal cancers patients with high microsatellite instability (MSI-H). However, the majority of patients with colorectal cancer who present low microsatellite instability (MSI-L) or stable microsatellites (MSS) show little response to PD-1 blockade therapy. Here, we have demonstrated that Shikonin (SK) could induce cell death of CT26 cells via classically programmed and immunogenic pathways. METHODS AND RESULTS: SK promoted the membrane exposure of calreticulin and upregulated the expression of heat shock protein 70 (Hsp70). The upregulation of Hsp70 was dependent on ROS induced by SK and silencing of PKM2 in CT26 cells reverts ROS upregulation. Besides, SK synergizes with PD-1 blockade in CT26 tumor mice model, with the increase of intramural DC cells and CD8+ T cells. The expression of Hsp70 in tumor tissue was also increased in combinational SK plus αPD-1 therapy group. CONCLUSIONS: Our study elucidated the potential role of 'Shikonin-PKM2-ROS-Hsp70' axis in the promotion of efficacy of PD-1 blockade in CRC treatments, providing a potential strategy and targets for improving the efficacy of PD-1 blockade in colorectal cancer.

Quantitative parameters of dual-layer spectral detector computed tomography for evaluating Ki-67 and human epidermal growth factor receptor 2 expression in colorectal adenocarcinoma.

Background: Ki-67 and human epidermal growth factor receptor 2 (HER2) are key biomarkers in evaluating the prognosis of colorectal adenocarcinoma (CRAC). The purpose of this study was to investigate the value of quantitative parameters in dual-layer spectral detector computed tomography (SDCT) for evaluating the expression of Ki-67 and HER2 in CRAC. Methods: In this retrospective, cross-sectional study, 88 eligible patients with pathologically confirmed CRAC were selected from Taicang Hospital of Traditional Chinese Medicine between May 2021 and April 2023. The study participants underwent enhanced SDCT of the whole abdomen within 2 weeks before to surgery, did not receive antitumor therapy, and had complete immunohistochemical (IHC) indexes. Patients with nonadenocarcinoma pathologic types, poor quality of spectral CT images, or no complete immunohistochemistry results were excluded. Spectral parameters including CT values at 40 and 100 keV, effective atomic number, iodine concentration (IC), the slope of the spectral Hounsfield unit (HU) curve (λHU), and normalized iodine concentration (NIC) in the arterial phase (AP) and venous phase (VP) were analyzed for their value in distinguishing between the high and low expression of Ki-67 and HER2-positive and -negative status in CRAC. The statistical significance of the SDCT parameters between the different groups of Ki-67 expression and those of HER2 status was assessed with the Mann-Whitney test. Spearman correlation analysis was used to analyze the correlation between the SDCT parameters and the extent of Ki-67 expression and HER2 expression status. The receiver operating characteristic (ROC) curve was used, and the area under the curve (AUC) was calculated. Results: The SDCT parameters of CT values at 40 keV, effective atomic number, IC, and the λHU in the VP showed significant differences between the Ki-67 high- and low-expression groups in CRAC (P=0.035, P=0.041, P=0.036, and P=0.044, respectively), with AUCs of 0.639 [95% confidence interval (CI): 0.512-0.766], 0.634 (95% CI: 0.508-0.761), 0.638 (95% CI: 0.510-0.766), and 0.633 (95% CI: 0.504-0.762), respectively. The expression of CRAC Ki-67 was positively correlated with CT values at 40 keV (r=0.227; P=0.034), effective atomic number (r=0.219; P=0.040), IC (r=0.225; P=0.035), and the λHU in VP (r=0.216; P=0.043). SDCT parameter values showed no statistical difference between negative and positive expression in HER2 (all P values >0.05). There was no significant correlation between SDCT parameters and the expression of HER2 in CRAC (all P values >0.05). Conclusions: The quantitative parameters of SDCT in the VP provide valuable information for distinguishing between the low expression and high expression of Ki-67 in CRAC.

More enhanced non-growing season methane exchanges under warming on the Qinghai-Tibetan Plateau.

Uncertainty in methane (CH4) exchanges across wetlands and grasslands in the Qinghai-Tibetan Plateau (QTP) is projected to increase due to continuous permafrost degradation and asymmetrical seasonal warming. Temperature plays a vital role in regulating CH4 exchange, yet the seasonal patterns of temperature dependencies for CH4 fluxes over the wetlands and grasslands on the QTP remain poorly understood. Here, we demonstrated a stronger warming response of CH4 exchanges during the non-growing season compared to the growing season on the QTP. Analyzing 9745 daily observations and employing four methods -regression fitting of temperature-CH4 flux, temperature dependence calculations, field-based and model-based control experiments-we found that warming intensified CH4 emissions in wetlands and uptakes in grasslands. Specifically, the average reaction intensity in the non-growing season surpasses that in the growing season by 1.89 and 4.80 times, respectively. This stronger warming response of CH4 exchanges during the non-growing season significantly increases the regional CH4 exchange on the QTP. Our research reveals that CH4 exchanges in the QTP have a higher warming sensitivity in non-growing seasons, which meanwhile are dominated by a larger warming rate than the annual average. The combined effects of these two factors will significantly alter the CH4 source/sink on the QTP. Neglecting these impacts would lead to inaccurate estimations of CH4 source/sink over the QTP under climate warming.

Pretreatment prediction for IVF outcomes: generalized applicable model or centre-specific model?

STUDY QUESTION: What was the performance of different pretreatment prediction models for IVF, which were developed based on UK/US population (McLernon 2016 model, Luke model, Dhillon model, and McLernon 2022 model), in wider populations? SUMMARY ANSWER: For a patient in China, the published pretreatment prediction models based on the UK/US population provide similar discriminatory power with reasonable AUCs and underestimated predictions. WHAT IS KNOWN ALREADY: Several pretreatment prediction models for IVF allow patients and clinicians to estimate the cumulative probability of live birth in a cycle before the treatment, but they are mostly based on the population of Europe or the USA, and their performance and applicability in the countries and regions beyond these regions are largely unknown. STUDY DESIGN, SIZE, DURATION: A total of 26 382 Chinese patients underwent oocyte pick-up cycles between January 2013 and December 2020. PARTICIPANTS/MATERIALS, SETTING, METHODS: UK/US model performance was externally validated according to the coefficients and intercepts they provided. Centre-specific models were established with XGboost, Lasso, and generalized linear model algorithms. Discriminatory power and calibration of the models were compared as the forms of the AUC of the Receiver Operator Characteristic and calibration curves. MAIN RESULTS AND THE ROLE OF CHANCE: The AUCs for McLernon 2016 model, Luke model, Dhillon model, and McLernon 2022 model were 0.69 (95% CI 0.68-0.69), 0.67 (95% CI 0.67-0.68), 0.69 (95% CI 0.68-0.69), and 0.67 (95% CI 0.67-0.68), respectively. The centre-specific yielded an AUC of 0.71 (95% CI 0.71-0.72) with key predictors including age, duration of infertility, and endocrine parameters. All external models suggested underestimation. Among the external models, the rescaled McLernon 2022 model demonstrated the best calibration (Slope 1.12, intercept 0.06). LIMITATIONS, REASONS FOR CAUTION: The study is limited by its single-centre design and may not be representative elsewhere. Only per-complete cycle validation was carried out to provide a similar framework to compare different models in the sample population. Newer predictors, such as AMH, were not used. WIDER IMPLICATIONS OF THE FINDINGS: Existing pretreatment prediction models for IVF may be used to provide useful discriminatory power in populations different from those on which they were developed. However, models based on newer more relevant datasets may provide better calibrations. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the National Natural Science Foundation of China [grant number 22176159], the Xiamen Medical Advantage Subspecialty Construction Project [grant number 2018296], and the Special Fund for Clinical and Scientific Research of Chinese Medical Association [grant number 18010360765]. TRIAL REGISTRATION NUMBER: N/A.

Glycogen for lysosome-targeted CpG ODNs delivery and enhanced cancer immunotherapy.

CpG oligodeoxynucleotides (ODNs) strongly activate the immune system after binding to toll-like receptor 9 (TLR9) in lysosome, which demonstrated significant potential in cancer immunotherapy. However, their therapeutic efficacy is limited by drawbacks such as rapid degradation and poor cellular uptake. Although encouraging progress have been made on developing various delivery systems for CpG ODNs, safety risks of the synthetic nanocarriers as well as the deficient CpG ODNs release within lysosome remain big obstacles. Herein, we developed a novel nanovector for lysosome-targeted CpG ODNs delivery and enhanced cancer immunotherapy. Natural glycogen was simply aminated (NH2-Gly) through grafting with diethylenetriamine (DETA), which was spherical in shape with diameter of approximately 40 nm. NH2-Gly possessed good biocompatibility. Cationic NH2-Gly complexed CpG ODNs well and protected them from nuclease digestion. NH2-Gly significantly enhanced the cellular uptake of CpG ODNs. Efficient CpG ODNs release was observed in the presence of α-glucosidase that mimicking the environment of lysosome. Consequently, NH2-Gly/CpG complexes triggered potent antitumor immunity and effectively inhibit the tumor growth without causing any toxic effect or tissue damages. This work highlights the promise of glycogen for lysosome-targeted on-command delivery of CpG ODNs, which brings new hope for precision cancer immunotherapy.

Cyclometalated gold(III)-hydride under oriented external electric fields: a new strategy to modulate its reactivity?

Selected gold complexes have been regarded as promising anti-cancer agents because they can bind with protein targets containing thiol or selenol moieties, but their clinical applications were hindered by the unbiased binding towards off-target thiol-proteins. Recently, a novel gold(III)-hydride complex (abbreviated as 1) with visible light-induced thiol reactivity has been reported as potent photo-activated anticancer agents (Angew. Chem. Int. Ed., 2020, 132, 11139). To explore new strategies to stimuli this potential antitumor drug, the effect of oriented external electric fields (OEEFs) on its geometric structure, electronic properties, and chemical reactivity was systematically investigated. Results reveal that imposing external electric fields along the Au-H bond of 1 can effectively activate this bond, which is conducive to its dissociation and the binding of Au site to potential targets. Hence, this study provides a new OEEF-strategy to activate this reported gold(III)-hydride, revealing its potential application in electrochemical therapy. We anticipate this work could promote the development of more electric field-activated anticancer agents. However, further experimental research should be conducted to verify the conclusions obtained in this work.

Does cleavage stage morphology increase the discriminatory power of prediction in blastocyst transfer outcome?

PURPOSE: To evaluate the contribution of the cleavage stage morphological parameters to the prediction of blastocyst transfer outcomes. METHODS: A retrospective study was conducted on 8383 single-blastocyst transfer cycles including 2246 fresh and 6137 vitrified-warmed cycles. XGboost, LASSO, and GLM algorithms were employed to establish models for assessing the predictive value of the cleavage stage morphological parameters in transfer outcomes. Four models were developed using each algorithm: all-in model with or without day 3 morphology and embryo quality-only model with or without day 3 morphology. RESULTS: The live birth rate was 48.04% in the overall cohort. The AUCs of the models with the algorithm of XGboost were 0.83, 0.82, 0.63, and 0.60; with LASSO were 0.66, 0.66, 0.61, and 0.60; and with GLM were 0.66, 0.66, 0.61, and 0.60 respectively. In models 1 and 2, female age, basal FSH, peak E2, endometrial thickness, and female BMI were the top five critical features for predicting live birth; In models 3 and 4, the most crucial factor was blastocyst formation on D5 rather than D6. In model 3, incorporating cleavage stage morphology, including early cleavage, D3 cell number, and fragmentation, was significantly associated with successful live birth. Additionally, the live birth rates for blastocysts derived from on-time, slow, and fast D3 embryos were 49.7%, 39.5%, and 52%, respectively. CONCLUSIONS: The value of cleavage stage morphological parameters in predicting the live birth outcome of single blastocyst transfer is limited.