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Cell-membrane-coated nanoparticles (CCNPs) that integrate the biophysiological advantages of cell membranes with the multifunctionalities of synthetic materials hold great promise in cancer immunotherapy. However, strategies have yet to be revealed to further improve their immunotherapeutic efficacy. Herein, a polymer multicellular nanoengager (SPNE) for synergistic second-near-infrared-window (NIR-II) photothermal immunotherapy is reported. The nanoengager consists of an NIR-II absorbing polymer as the photothermal core, which is camouflaged with fused membranes derived from immunologically engineered tumor cells and dendritic cells (DCs) as the cancer vaccine shell. In association with the high accumulation in lymph nodes and tumors, the multicellular engagement ability of the SPNE enables effective cross-interactions among tumor cells, DCs, and T cells, leading to augmented T cell activation relative to bare or tumor-cell-coated nanoparticles. Upon deep-tissue penetrating NIR-II photoirradiation, SPNE eradicates the tumor and induces immunogenic cell death, further eliciting anti-tumor T cell immunity. Such a synergistic photothermal immunotherapeutic effect eventually inhibits tumor growth, prevents metastasis and procures immunological memory. Thus, this study presents a general cell-membrane-coating approach to develop photo-immunotherapeutic agents for cancer therapy.The BRCA2 tumor suppressor is a DNA double-strand break (DSB) repair factor essential for maintaining genome integrity. BRCA2-deficient cells spontaneously accumulate DNA-RNA hybrids, a known source of genome instability. However, the specific role of BRCA2 on these structures remains poorly understood. Here we identified the DEAD-box RNA helicase DDX5 as a BRCA2-interacting protein. DDX5 associates with DNA-RNA hybrids that form in the vicinity of DSBs, and this association is enhanced by BRCA2. Notably, BRCA2 stimulates the DNA-RNA hybrid-unwinding activity of DDX5 helicase. An impaired BRCA2-DDX5 interaction, as observed in cells expressing the breast cancer variant BRCA2-T207A, reduces the association of DDX5 with DNA-RNA hybrids, decreases the number of RPA foci, and alters the kinetics of appearance of RAD51 foci upon irradiation. Nigericin sodium datasheet Our findings are consistent with DNA-RNA hybrids constituting an impediment for the repair of DSBs by homologous recombination and reveal BRCA2 and DDX5 as active players in their removal.Solid-state NMR (SSNMR) spectroscopy of integer-spin quadrupolar nuclei is important for the molecular-level characterization of a variety of materials and biological solids; of the integer spins, 2 H (S = 1) is by far the most widely studied, due to its usefulness in probing dynamical motions. SSNMR spectra of integer-spin nuclei often feature very broad powder patterns that arise largely from the effects of the first-order quadrupolar interaction; as such, the acquisition of high-quality spectra continues to remain a challenge. The broadband adiabatic inversion cross-polarization (BRAIN-CP) pulse sequence, which is capable of cross-polarization (CP) enhancement over large bandwidths, has found success for the acquisition of SSNMR spectra of integer-spin nuclei, including 14 N (S = 1), especially when coupled with Carr-Purcell/Meiboom-Gill pulse sequences featuring frequency-swept WURST pulses (WURST-CPMG) for T2 -based signal enhancement. However, to date, there has not been a systematic investigation of the spin dynamics underlying BRAIN-CP, nor any concrete theoretical models to aid in its parameterization for applications to integer-spin nuclei. In addition, the BRAIN-CP/WURST-CPMG scheme has not been demonstrated for generalized application to wideline or ultra-wideline (UW) 2 H SSNMR. Herein, we provide a theoretical description of the BRAIN-CP pulse sequence for spin-1/2 → spin-1 CP under static conditions, featuring a set of analytical equations describing Hartmann-Hahn matching conditions and numerical simulations that elucidate a CP mechanism involving polarization transfer, coherence exchange, and adiabatic inversion. Several experimental examples are presented for comparison with theoretical models and previously developed integer-spin CP methods, demonstrating rapid acquisition of 2 H NMR spectra from efficient broadband CP.The explosive growth in medical devices, imaging and diagnostics, computing, and communication and information technologies in drug development and healthcare has created an ever-expanding data landscape that the pharmacometrics (PMX) research community must now traverse. The tools of machine learning (ML) have emerged as a powerful computational approach in other data-rich disciplines but its effective utilization in the pharmaceutical sciences and PMX modelling is in its infancy. ML-based methods can complement PMX modelling by enabling the information in diverse sources of big data, e.g. population-based public databases and disease-specific clinical registries, to be harnessed because they are capable of efficiently identifying salient variables associated with outcomes and delineating their interdependencies. ML algorithms are computationally efficient, have strong predictive capabilities and can enable learning in the big data setting. ML algorithms can be viewed as providing a computational bridge from big data to complement PMX modelling. This review provides an overview of the strengths and weaknesses of ML approaches vis-à-vis population methods, assesses current research into ML applications in the pharmaceutical sciences and provides perspective for potential opportunities and strategies for the successful integration and utilization of ML in PMX.Mindfulness is a meditation practice frequently associated with changes in subjective evaluation of cognitive and sensorial experience, as well as with modifications of brain activity and morphometry. Aside from the anatomical localization of functional changes induced by mindfulness practice, little is known about changes in functional and effective functional magnetic resonance imaging (fMRI) connectivity. Here we performed a connectivity fMRI analysis in a group of healthy individuals participating in an 8-week mindfulness-based stress reduction (MBSR) training program. Data from both a "mind-wandering" and a "meditation" state were acquired before and after the MBSR course. Results highlighted decreased local connectivity after training in the right anterior putamen and insula during spontaneous mind-wandering and the right cerebellum during the meditative state. A further effective connectivity analysis revealed (a) decreased modulation by the anterior cingulate cortex over the anterior portion of the putamen, and (b) a change in left and right posterior putamen excitatory input and inhibitory output with the cerebellum, respectively.