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Conventional solid lubricants such as MoS2, graphite, or diamond-like carbon films demonstrate excellent tribological performance but only in specific environments due to their inherent materials properties. This limitation prohibits using these solid lubricants in environments that change dynamically. This study presents the results of a novel solid lubricant that was developed using a combination of solution-processed 2D-molybdenum disulfide and graphene-oxide (GO) that can be deposited on to stainless steel substrates using a simple spray-coating technique and show exceptional performance in multifarious environments namely, ambient (humid) atmosphere, dry nitrogen, and vacuum. The tribological performance of the coatings was evaluated using a ball-on-disc sliding test and demonstrated an excellent wear/friction performance in all environments and coating survived even after 44 km of linear sliding. Transmission electron microscopy and Raman spectroscopy analysis of the tribolayers suggested in-operando friction-induced re-orientation of MoS2 layers that were protected by GO layers and, an absence of MoOx peaks indicate a strong resistance to intercalation with moisture and oxygen. The simplicity and robustness of the hybrid MoS2–GO solid lubricant in mitigating wear-friction behavior of steel-on-steel tribopair in a multifarious environment is a game-changing and is promising for various applications.

Mutations in the Membrane-type frizzled related protein (Mfrp) gene results in an early-onset retinal degeneration associated with retinitis pigmentosa, microphthalmia, optic disc drusen and foveal schisis. In the current study, a previously characterized mouse model of human retinal degeneration carrying homozygous c.498_499insC mutations in Mfrp (MfrpKI/KI) was used. Patients carrying this mutation have retinal degeneration at an early age. The model demonstrates subretinal deposits and develops early-onset photoreceptor degeneration. We observed large subretinal deposits in MfrpKI/KI mice which were strongly CD68 positive and co-localized with autofluorescent spots. Single cell RNA sequencing of MfrpKI/KI mice retinal microglia showed a significantly higher number of pan-macrophage marker Iba-1 and F4/80 positive cells with increased expression of activation marker (CD68) and lowered microglial homeostatic markers (TMEM119, P2ry13, P2ry13, Siglech) compared with wild type mice confirming microglial activation as observed in retinal immunostaining showing microglia activation in subretinal region. Trajectory analysis identified a small cluster of microglial cells with activation transcriptomic signatures that could represent a subretinal microglia population in MfrpKI/KI mice expressing higher levels of APOE. We validated these findings using immunofluorescence staining of retinal cryosections and found a significantly higher number of subretinal Iba-1/ApoE positive microglia in MfrpKI/KI mice with some subretinal microglia also expressing lowered levels of microglial homeostatic marker TMEM119, confirming microglial origin. In summary, we confirm that MfrpKI/KI mice carrying the c.498_499insC mutation had a significantly higher population of activated microglia in their retina with distinct subsets of subretinal microglia. Further, studies are required to confirm whether the association of increased subretinal microglia in MfrpKI/KI mice are causal in degeneration.

In-vitro fertilization (IVF) is a popular method of resolving complications such as endometriosis, poor egg quality, a genetic disease of mother or father, problems with ovulation, antibody problems that harm sperm or eggs, the inability of sperm to penetrate or survive in the cervical mucus and low sperm counts, resulting human infertility. Nevertheless, IVF does not guarantee success in the fertilization. Choosing IVF is burdensome for the reason of high cost and uncertainty in the result. As the complications and fertilization factors are numerous in the IVF process, it is a cumbersome task for fertility doctors to give an accurate prediction of a successful birth. Artificial Intelligence (AI) has been employed in this study for predicting the live-birth occurrence. This work mainly focuses on making predictions of live-birth occurrence when an embryo forms from a couple and not a donor. Here, we compare various AI algorithms, including both classical Machine Learning, deep learning architecture, and an ensemble of algorithms on the publicly available dataset provided by Human Fertilisation and Embryology Authority (HFEA). Insights on data and metrics such as confusion matrices, F1-score, precision, recall, receiver operating characteristic (ROC) curves are demonstrated in the subsequent sections. The training process has two settings Without feature selection and With feature selection to train classifier models. Machine Learning, Deep learning, ensemble models classification paradigms have been trained in both settings. The Random Forest model achieves the highest F1-score of 76.49% in without feature selection setting. For the same model, the precision, recall, and area under the ROC Curve (ROC AUC) scores are 77%, 76%, and 84.60%, respectively. The success of the pregnancy depends on both male and female traits and living conditions. This study predicts a successful pregnancy through the clinically relevant parameters in In-vitro fertilization. Thus artificial intelligence plays a promising role in decision making process to support the diagnosis, prognosis, treatment etc.

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system’s use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications.

The combination of high strength and good ductility are very desirable for advanced structural and functional applications. However, measures to enhance strength typically lead to ductility reduction due to their inverse correlation, nano-grained structures for an instance. Bi-modal grain structure is promising in this regard, but its realization is limited by multiple complex processing steps. Here, we demonstrate a facile single-step processing route for the development of bimodal grain structure in austenitic stainless steel, SS316L. The bimodal structure comprised of fine martensite grains (

Metallic glass composites represent a unique alloy design strategy comprising of in situ crystalline dendrites in an amorphous matrix to achieve damage tolerance unseen in conventional structural materials. They are promising for a range of advanced applications including spacecraft gears, high-performance sporting goods and bio-implants, all of which demand high surface degradation resistance. Here, we evaluated the phase-specific electrochemical and friction characteristics of a Zr-based metallic glass composite, Zr56.2Ti13.8Nb5.0Cu6.9Ni5.6Be12.5, which comprised roughly of 40% by volume crystalline dendrites in an amorphous matrix. The amorphous matrix showed higher hardness and friction coefficient compared to the crystalline dendrites. But sliding reciprocating tests for the composite revealed inter-phase delamination rather than preferred wearing of one phase. Pitting during potentiodynamic polarization in NaCl solution was prevalent at the inter-phase boundary, confirming that galvanic coupling was the predominant corrosion mechanism. Scanning vibration electrode technique demonstrated that the amorphous matrix corroded much faster than the crystalline dendrites due to its unfavorable chemistry. Relative work function values measured using scanning kelvin probe showed the amorphous matrix to be more electropositive, which explain its preferred corrosion over the crystalline dendrites as well as its characteristic friction behavior. This study paves the way for careful partitioning of elements between the two phases in a metallic glass composite to tune its surface degradation behavior for a range of advanced applications.

Alpha-synuclein (α-Syn) aggregation into oligomers and fibrils is associated with dopaminergic neuron loss occurring in Parkinson’s disease (PD) pathogenesis. Compounds that modulate α-Syn aggregation and interact with preformed fibrils/oligomers and convert them to less toxic species could have promising applications in the drug development efforts against PD. Curcumin is one of the Asian food ingredient which showed promising role as therapeutic agent against many neurological disorders including PD. However, the instability and low solubility makes it less attractive for the drug development. In this work, we selected various curcumin analogs and studied their toxicity, stability and efficacy to interact with different α-Syn species and modulation of their toxicity. We found a subset of curcumin analogs with higher stability and showed that curcumin and its various analogs interact with preformed fibrils and oligomers and accelerate α-Syn aggregation to produce morphologically different amyloid fibrils in vitro. Furthermore, these curcumin analogs showed differential binding with the preformed α-Syn aggregates. The present data suggest the potential role of curcumin analogs in modulating α-Syn aggregation.