A simple predictor for donor-specific anti-HLA antibody desensitisation in haploidentical haematopoietic stem cell transplantation.

Donor-specific HLA antibody (DSA) has been recognised as an independent risk factor for graft failure in patients undergoing haploidentical haematopoietic stem cell transplantation (HID HSCT). Therapeutic plasma exchange (TPE), as a first-line strategy for DSA desensitisation, can promptly reduce serum DSA levels. This study aimed to investigate DSA characteristics and identify a biomarker predicting the efficacy of DSA desensitisation in patients proceeding to HID HSCT. We retrospectively enrolled 32 patients with DSA from April 2021 to January 2024, and analysed the mean fluorescence intensity (MFI) value of DSA at the different time points of desensitisation treatment. Compared with baseline DSA level before TPE, the median MFI of HLA class I DSA was reduced from 8178.6 to 795.3 (p < 0.001), and HLA class II DSA decreased from 6210.9 to 808.8 (p < 0.001) after TPE. The DSA level in 1:16 diluted pre-TPE serum correlated well with DSA value in post-TPE serum (class I, r = 0.85, p < 0.0001; class II, r = 0.94, p < 0.0001), predicting TPE efficacy in 84.4% of patients. Based on the degree of DSA reduction after TPE, patients were divided into complete responders (decreased by >70%), partial responders (decreased by 30 to 70%) and non-responders (decreased by <30%) and the percentages were 43.8%, 25% and 31.2%, respectively. Non-responders receiving aggressive immunotherapy had longer overall survival compared to those receiving standard strategies (p < 0.05). The 1:16 diluted pre-TPE serum may predict the efficacy of TPE and allow for more rational immunotherapy strategy for patients with DSA proceeding to HID HSCT.

Preparation and Performance Evaluation of Self-Cementing Nanoscale Polymeric Microspheres with Salt and Temperature Tolerance.

Polymer microspheres with temperature and salt resistance were synthesized using the anti-suspension polymerization method, incorporating the functional monomers AMPS, AM, and AA. To enhance their self-gelling properties, the microspheres were designed with a core-shell structure. The shell is composed of a polymeric surfactant, fatty alcohol polyoxyethylene ether methacrylate (AEOMA), which serves as a thermosensitive crosslinking agent, enabling self-crosslinking upon shell decomposition, addressing compatibility with reservoir pore throat dimensions. Comprehensive characterizations including infrared spectroscopy, scanning electron microscopy, optical microscopy, and laser particle size analysis were conducted. The microspheres exhibited successful synthesis, a nanoscale size, and regular spherical morphology. They demonstrated excellent temperature and salt resistance, making them suitable for high-temperature, high-salinity reservoir profile control. With a stable three-dimensional network structure, the microspheres displayed good expansion behavior due to hydrophilic groups along the polymer chains, resulting in favorable water affinity. Even after aging, the microspheres maintained their gelling state with a distinct and stable microscopic network skeleton. They exhibited superior plugging performance in low-permeability reservoirs, while effectively improving water absorption profiles in reservoirs with permeability contrasts of 10 to 80, thereby enhancing oil recovery.

A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer research.

Owing to their distinct physical and chemical properties, inorganic nanoparticles (NPs) have shown promising results in preclinical cancer therapy, but designing and engineering them for effective therapeutic purposes remains a challenge. Although a comprehensive database of inorganic NP research is not currently available, it is crucial for developing effective cancer therapies. In this context, machine learning (ML) has emerged as a transformative tool, but its adaptation to nanomedicine is hindered by inexistent or small datasets. Here we assembled a large database of inorganic NPs, comprising experimental datasets from 745 preclinical studies in cancer nanomedicine. Using descriptive statistics and explainable ML models we mined this database to gain knowledge of inorganic NP design patterns and inform future NP research for cancer treatment. Our analyses suggest that NP shape and therapy type are prominent features in determining in vivo efficacy, measured as a percentage of tumour reduction. Moreover, our database provides a large-scale open-access resource for discriminative ML that the broader nanotechnology community can utilize. Our work blueprints data mining for translational cancer research and offers evidence for standardizing NP reporting to accelerate and de-risk inorganic NP-based drug delivery, which may help to improve patient outcomes in clinical settings.

Characterization of the complete chloroplast genome of Eutrema deltoideum (Brassicaceae).

Eutrema deltoideum (Hook. f. et Thoms.) has been recognized as a potentially important vegetable and medicinal resource. In this study, we present the complete chloroplast genome of E. deltoideum and conduct a phylogenetic analysis. The chloroplast genome is 154,051 bp long and consists of a large single-copy (LSC) region of 84,149 bp, two inverted repeat (IR) regions of 26,065 bp each, and a small single-copy (SSC) region of 17,772 bp. It contains 132 complete genes, including 87 protein-coding genes, 8 ribosomal RNA genes, and 37 tRNA genes. Additionally, we identified 78 simple sequence repeats (SSRs). The phylogenetic tree reveals that E. deltoideum is closely related to E. heterophyllum, and the Eutrema genus is monophyletic. This study provides valuable information about E. deltoideum and enhances our understanding of its taxonomic classification.

Activating plant immunity: the hidden dance of intracellular Ca2+ stores.

Calcium ion (Ca2+) serves as a versatile and conserved second messenger in orchestrating immune responses. In plants, plasma membrane-localized Ca2+-permeable channels can be activated to induce Ca2+ influx from extracellular space to cytosol upon pathogen infection. Notably, different immune elicitors can induce dynamic Ca2+ signatures in the cytosol. During pattern-triggered immunity, there is a rapid and transient increase in cytosolic Ca2+, whereas in effector-triggered immunity, the elevation of cytosolic Ca2+ is strong and sustained. Numerous Ca2+ sensors are localized in the cytosol or different intracellular organelles, which are responsible for detecting and converting Ca2+ signals. In fact, Ca2+ signaling coordinated by cytosol and subcellular compartments plays a crucial role in activating plant immune responses. However, the complete Ca2+ signaling network in plant cells is still largely ambiguous. This review offers a comprehensive insight into the collaborative role of intracellular Ca2+ stores in shaping the Ca2+ signaling network during plant immunity, and several intriguing questions for future research are highlighted.

Visual Gustation via Regulable Elastic Photonic Crystals.

The unique structural sensitivity of photonic crystals (PCs) endows them with stretchable or elastic tunability for light propagation and spontaneous emission modulation. Hydrogel PCs have been demonstrated to have biocompatibility and flexibility for potential human health detection and environmental security monitoring. However, current elastic PCs still possess a fixed elastic modulus and uncontrollable structural colors based on a tunable elastic modulus, posing considerable challenges for in situ detection, particularly in wearable or portable sensing devices. In this work, we introduced a novel chemo-mechanical transduction mechanism embedded within a photonic crystal nanomatrix, leading to the creation of structural colors and giving rise to a visual gustation sensing experience. By utilizing the captivating structural colors generated by the hydrogel PC, we employ abundant optical information to identify various analytes. The finite element analysis proved the electric field distribution in the PC matrix during stretch operations. The elastic-optical behaviors with various chemical cosolvents, including cations, anions, saccharides, or organic acids, were investigated. The mechanism of the Hofmeister effect regulating the elasticity of hydrogels was demonstrated with the network nanostructure of the hydrogels. The hydrogel PC matrix demonstrates remarkable capability in efficiently distinguishing a wide range of cations, anions, saccharides, and organic acids across various concentrations, mixtures, and even real food samples, such as tastes and soups. Through comprehensive research, a precise relationship between the structural colors and the elastic modulus of hydrogel PCs has been established, contributing to the biomatching elastic-optics platform for wearable devices, a dynamic environment, and clinical or health monitoring auxiliary.

Screening oral drugs for their interactions with the intestinal transportome via porcine tissue explants and machine learning.

In vitro systems that accurately model in vivo conditions in the gastrointestinal tract may aid the development of oral drugs with greater bioavailability. Here we show that the interaction profiles between drugs and intestinal drug transporters can be obtained by modulating transporter expression in intact porcine tissue explants via the ultrasound-mediated delivery of small interfering RNAs and that the interaction profiles can be classified via a random forest model trained on the drug-transporter relationships. For 24 drugs with well-characterized drug-transporter interactions, the model achieved 100% concordance. For 28 clinical drugs and 22 investigational drugs, the model identified 58 unknown drug-transporter interactions, 7 of which (out of 8 tested) corresponded to drug-pharmacokinetic measurements in mice. We also validated the model's predictions for interactions between doxycycline and four drugs (warfarin, tacrolimus, digoxin and levetiracetam) through an ex vivo perfusion assay and the analysis of pharmacologic data from patients. Screening drugs for their interactions with the intestinal transportome via tissue explants and machine learning may help to expedite drug development and the evaluation of drug safety.

Early T-cell reconstitution predicts risk of EBV reactivation after allogeneic hematopoietic stem cell transplantation.

The quality of immune reconstitution (IR) is crucial for the outcome of patients who received allogeneic hematopoietic stem cell transplantation (allo-HSCT), and is closely connected with infection, relapse and graft-versus-host disease (GvHD) which are the most important causes for transplantation failure. However, the IR pattern in the early stage after allo-HSCT, particularly haploidentical (HID) HSCT, remains unclear. In this retrospective study, we examined the T cell reconstitution of patients within the initial 30 days (n = 173) and 100 days (n = 122) after allo-HSCT with myeloablative condition (MAC), of which > 70% were HID HSCT, to assess the influence of IR on the transplant outcomes. By comparing 78 patients with good IR (GIR) to 44 patients with poor IR (PIR), we observed that GIR was associated with lower risk for Epstein-Barr virus (EBV) reactivation and cytomegalovirus (CMV) reactivation, but had no significant impacts on the survival outcomes (i.e., overall survival, event-free survival) and cumulative incidences of GvHD. Importantly, we found lymphocyte reconstitution pattern at day 30 after allo-HSCT would be a surrogate for IR evaluated at day 100. In the Cox proportional hazard model, early reconstitution of CD4+, CD4+CD25+, CD4+CD45RO+, CD4+CD25+CD27low, and CD8+ T cells at day 30 was reversely correlated with risk of EBV reactivation. Finally, we constructed a predictive model for EBV reactivation with CD8+ and CD4+CD45RO+ T cell proportions of the training cohort (n = 102), which was validated with a validation cohort (n = 37). In summary, our study found that the quality of IR at day 30 had a predictive value for the risk of EBV reactivation, and might provide guidance for close monitoring for EBV reactivation.

COVID-19 in immunocompromised patients after hematopoietic stem cell transplantation: a pilot study.

Data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in patients at early stage of immune reconstitution after hematopoietic stem cell transplantation (HSCT) are limited. In the present study, we retrospectively investigated the incidence and clinical features of SARS-CoV-2 infection in patients who underwent HSCT in 2022. Patients (allo-HSCT, n = 80; auto-HSCT, n = 37) were consecutively included in the study. The SARS-CoV-2 infection rate was 59.8%, and the median interval of HSCT to coronavirus disease 2019 (COVID-19) was 4.8 (range: 0.5-12) months. Most patients were categorized as mild (41.4%) or moderate (38.6%), and 20% as severe/critical. No deaths were attributable to COVID-19. Further analysis showed that lower circulating CD8+ T-cell counts and calcineurin inhibitor administration increased the risk of SARS-CoV-2 infection. Exposure to rituximab significantly increased the probability of severe or critical COVID-19 compared with that of mild/moderate illness (P < .001). In the multivariate analysis, rituximab use was associated with severe COVID-19. Additionally, COVID-19 had no significant effect on immune reconstitution. Furthermore, it was found that Epstein-Barr virus infection and rituximab administration possibly increase the risk of developing severe illness. Our study provides preliminary insights into the effect of SARS-CoV-2 on immune reconstitution and the outcomes of allo-HSCT recipients.