Moderating Role of Religiosity and the Determinants to Attitude, Willingness to Donate and Willingness to Communicate Posthumous Organ Donation Decisions among University Students in Pakistan.

Organ transplantation is considered an alternative treatment to save lives or to improve the quality of life and is a successful method for the treatment of patients with end-stage organ diseases. The main objective of the current study was to explore the determinants of the attitudes and willingness to communicate the posthumous organ donation decisions to the families. Questionnaires were used to test the hypothesized relationships. The results confirmed altruism, knowledge, empathy, and self-identity as the antecedents to attitude. We also found perceived behavioral control, moral norms, and attitude as significant antecedents to the willingness to donate organs after death. The results of the study also indicated that those who were willing to sign the donor card were also willing to communicate their decision to their families. Religiosity moderated the relationship between willingness to donate and signing the donor card, and it strengthened the relationship. The findings of this study would provide insight into the factors which can influence posthumous organ donation among university students in Pakistan.

Computational design of ultra-robust strain sensors for soft robot perception and autonomy.

Compliant strain sensors are crucial for soft robots' perception and autonomy. However, their deformable bodies and dynamic actuation pose challenges in predictive sensor manufacturing and long-term robustness. This necessitates accurate sensor modelling and well-controlled sensor structural changes under strain. Here, we present a computational sensor design featuring a programmed crack array within micro-crumples strategy. By controlling the user-defined structure, the sensing performance becomes highly tunable and can be accurately modelled by physical models. Moreover, they maintain robust responsiveness under various demanding conditions including noise interruptions (50% strain), intermittent cyclic loadings (100,000 cycles), and dynamic frequencies (0-23 Hz), satisfying soft robots of diverse scaling from macro to micro. Finally, machine intelligence is applied to a sensor-integrated origami robot, enabling robotic trajectory prediction (<4% error) and topographical altitude awareness (<10% error). This strategy holds promise for advancing soft robotic capabilities in exploration, rescue operations, and swarming behaviors in complex environments.

Dynamic nano-imaging via a microsphere compound lens integrated microfluidic device with a 10× objective lens.

Optical microscopic imaging techniques are essential in biology and chemistry fields to observe and extract dynamic information of micro/nano-scale samples in microfluidic devices. However, the current microfluidic optical imaging schemes encounter dilemmas in simultaneously possessing high spatial and temporal resolutions. Recently, microsphere nanoscope has emerged as a competitive nano-imaging tool due to its merits like high spatial resolution, real-time imaging abilities, and cost-effectiveness, which make it a potential solution to address the aforementioned challenges. Here, a microsphere compound lens (MCL) integrated microfluidic imaging device is proposed for real-time super-resolution imaging. The MCL consists of two vertically stacked microspheres, which can resolve nano-objects with size beyond the optical diffraction limit and generate an image of the object with a magnification up to 10×. Exploiting the extraordinary nano-imaging and magnification ability of the MCL, optically transparent 100 nm polystyrene particles in flowing fluid can be discerned in real time by the microfluidic device under a 10× objective lens. Contrary to this, the single microsphere and the conventional optical microscope are incompetent in this case regardless of the magnification of objective lenses used, which demonstrates the superiority of the MCL imaging scheme. Besides, applications of the microfluidic device in nanoparticle tracing and live-cell monitoring are also experimentally demonstrated. The MCL integrated microfluidic imaging device can thus be a competent technique for diverse biology and chemistry applications.

Development and Validation of Blood-Based Predictive Biomarkers for Response to PD-1/PD-L1 Checkpoint Inhibitors: Evidence of a Universal Systemic Core of 3D Immunogenetic Profiling across Multiple Oncological Indications.

BACKGROUND: Unprecedented advantages in cancer treatment with immune checkpoint inhibitors (ICIs) remain limited to only a subset of patients. Systemic analyses of the regulatory 3D genome architecture linked to individual epigenetic and immunogenetic controls associated with tumour immune evasion mechanisms and immune checkpoint pathways reveal a highly prevalent molecular profile predictive of response to PD-1/PD-L1 ICIs. A clinical blood test based on a set of eight (8) 3D genomic biomarkers has been developed and validated on the basis of an observational trial to predict response to ICI therapy. METHODS: The predictive eight biomarker set is derived from prospective observational clinical trials, representing 280 treatments with Pembrolizumab, Atezolizumab, Durvalumab, Nivolumab, and Avelumab in a broad range of indications: melanoma, lung, hepatocellular, renal, breast, bladder, colon, head and neck, bone, brain, lymphoma, prostate, vulvar, and cervical cancers. RESULTS: The 3D genomic eight biomarker panel for response to immune checkpoint therapy achieved a high accuracy of 85%, sensitivity of 93%, and specificity of 82%. CONCLUSIONS: This study demonstrates that a 3D genomic approach can be used to develop a predictive clinical assay for response to PD-1/PD-L1 checkpoint inhibition in cancer patients.

Macromolecule conformational shaping for extreme mechanical programming of polymorphic hydrogel fibers.

Mechanical properties of hydrogels are crucial to emerging devices and machines for wearables, robotics and energy harvesters. Various polymer network architectures and interactions have been explored for achieving specific mechanical characteristics, however, extreme mechanical property tuning of single-composition hydrogel material and deployment in integrated devices remain challenging. Here, we introduce a macromolecule conformational shaping strategy that enables mechanical programming of polymorphic hydrogel fiber based devices. Conformation of the single-composition polyelectrolyte macromolecule is controlled to evolve from coiling to extending states via a pH-dependent antisolvent phase separation process. The resulting structured hydrogel microfibers reveal extreme mechanical integrity, including modulus spanning four orders of magnitude, brittleness to ultrastretchability, and plasticity to anelasticity and elasticity. Our approach yields hydrogel microfibers of varied macromolecule conformations that can be built-in layered formats, enabling the translation of extraordinary, realistic hydrogel electronic applications, i.e., large strain (1000%) and ultrafast responsive (~30 ms) fiber sensors in a robotic bird, large deformations (6000%) and antifreezing helical electronic conductors, and large strain (700%) capable Janus springs energy harvesters in wearables.