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The growing phenomenon of transnational families where the mothers work abroad has reinvigorated the debate on the fluidity of contemporary families. Family is no longer defined as household-bound, and family obligations are constantly negotiated. Research shows migrant mothers utilize communication technologies, most recently smartphones, to (re)constitute family intimacy and maternal identity from afar through everyday family practices. However, most research has focused on the material reconfiguration of family practices, essentially sidelining the discursive workings of intimacy and identity via mobile media. To address this gap, this ethnographic study draws on the narrative theories, particularly the small stories approach, to examine the narratives of Indonesian mothers in Hong Kong as embedded in their smartphone communication. The participant observation and narrative interviews with 25 migrant mothers revealed that maternal storytelling on smartphones is routine, eclectic, and personalized. These enable migrant mothers to craft and tell family stories to (1) rationalize distance and (2) bolster family resilience. This article concludes by reflecting upon the authorial privilege in constructing family narratives on mobile media. The implications on our understanding of the contextualizing power of narrative and power dynamics underlying mediated family communication are discussed.

Transgalactosylation reaction is the penultimate step in the production of galactooligosaccharides (GOSs) which has prominent applications in the treatment of disorders. In the present study, partially purified β-galactosidase from Enterobacter aerogenes KCTC2190 was used for the synthesis of prebiotic GOSs. GOSs were produced using lactose as substrate. Structural elucidation of collected fractions of GOSs by liquid chromatography electrospray ionization mass spectrometry exhibited the appearance of major peaks of produced GOSs at m/z 241.20, 481.39, 365.11, 527.17, and 701.51 respectively. GOSs facilitated the growth of potential probiotic strains (Lactobacillus delbrueckii ssp. helveticus, Bifidobacterium bifidum, and Lactiplantibacillus plantarum) and liberated propionate and butyrate as principal short-chain fatty acids which established its prebiotic potency. Synbiotic combinations exhibited good antioxidant activities. Synbiotic combinations also exhibited antimicrobial activities against pathogenic microorganisms namely Staphylococcus aureus and Escherichia coli. Synbiotic combinations of GOSs and the respective probiotic microorganisms were able to decrease viable human bone cancer cells (MG-63).

Pancreatic cancer is a devastating disease that is largely refractory to currently available treatment strategies. Therapeutic resistance is partially attributed to the dense stromal reaction of pancreatic ductal adenocarcinoma tumors that includes a pervasive infiltration of immunosuppressive (M2) macrophages. Nab-paclitaxel (trade name Abraxane) is a nanoparticle albumin-bound formulation of paclitaxel that, in combination with gemcitabine, is currently the first-line treatment for pancreatic cancer. Here, we show that macrophages internalized nab-paclitaxel via macropinocytosis. The macropinocytic uptake of nab-paclitaxel induced macrophage immunostimulatory (M1) cytokine expression and synergized with IFNγ to promote inducible nitric oxide synthase expression in a TLR4-dependent manner. Nab-paclitaxel was internalized by tumor-associated macrophages in vivo, and therapeutic doses of nab-paclitaxel alone, and in combination with gemcitabine, increased the MHCII+CD80+CD86+ M1 macrophage population. These data revealed an unanticipated role for nab-paclitaxel in macrophage activation and rationalized its potential use to target immune evasion in pancreatic cancer. Cancer Immunol Res; 5(3); 182–90. ©2017 AACR.

Nab-paclitaxel induces M1 activation in pancreatic tumor-associated macrophages in vivo

Figure legends for supplementary figures 1-3

LPS induces M1 cytokine expression in a TLR4-dependent manner

Statistical agencies often publish microdata or synthetic data to protect confidentiality of survey respondents. This is more prevalent in case of income data. In this paper, we develop likelihood-based finite sample inferential methods for a singly imputed synthetic data using plug-in sampling and posterior predictive sampling techniques under Pareto distribution, a well known income distribution. The estimators are constructed based on sufficient statistics and the estimation methods possess desirable properties. For example, the estimators are unbiased and confidence intervals developed are exact. An extensive simulation study is carried out to analyze the performance of the proposed methods., REVSTAT-Statistical Journal, Vol. 20 No. 5 (2022): REVSTAT-Statistical Journal

Nanoparticles (NPs) have been used in drug delivery therapies, medical diagnostic strategies, and as current Covid-19 vaccine carriers. Many microscope-based imaging systems have been introduced to facilitate detection and visualization of NPs. Unfortunately, none can differentiate the core and the shell of NPs. Spectral imaging has been used to distinguish a drug molecule and its metabolite. We have recently integrated this technology to a resolution of 9 nm by using artificial intelligence-driven analyses. Such a resolution allowed us to collect many robust datapoints for each pixel of an image. Our analyses could recognize 45 spectral points within a pixel to detect unlabeled Ag-NPs and Au-NPs in single live cells and tissues (liver, heart, spleen and kidneys). The improved resolution and software provided a more specific fingerprinting for each single molecule, allowing simultaneous analyses of 990 complex interactions from the 45 points for each molecule within a pixel of an image. This in turn allowed us to detect surface-functionalization of Ag-NPs to distinguish the core from the shell of Ag-NPs for the first time. Our studies were validated using various laborious and time-consuming conventional techniques. We propose that spectral imaging has tremendous potential to study NP localization and identification in biological samples at a high temporal and spatial resolution, based primarily on spectral identity information.

The response of cytoskeleton to mechanical cues plays a pivotal role in understanding several aspects of cellular growth, migration, and cell–cell and cell–matrix interactions under normal and diseased conditions. Finite element analysis (FEA) has become a powerful computational technique to study the response of cytoskeleton in the maintenance of overall cellular mechanics. With the revelation of role of external mechanical microenvironment on cell mechanics, FEA models have also been developed to simulate the effect of substrate stiffness on the mechanical properties of cancer cells. However, the models developed so far model cellular response under static mode, whereas in physiological condition, cells always experience dynamic loading conditions. To develop a more accurate model of cell-extracellular matrix (ECM) interactions, this paper models the cytoskeleton and other parts of the cell by beam and solid elements respectively, assuming spherical morphology of the cell. The stiffness and roughness of extracellular matrix were varied. Furthermore, static and dynamic sinusoidal loads were applied through a flat plate indenter on the cell along with providing sinusoidal strain at the substrate. It is observed that due to axial loading, cell reaches a plastic region, and when the sinusoidal loading is added to the axial load, the cell experiences permanent deformation. Degradation of the cytoskeleton elements and a physiologically more relevant spherical cap shape of the cell were also considered during the analysis. This study suggests that asperity topology of the substrate and indirect cyclic load can play a significant role in the shape alterations and motion of a cell.

A field experiment was conducted to study the effect of organic manures and growth regulators on the growth and yield of two varieties of strawberry namely ‘Sweet Charlie’ and ‘Winter Dawn’. Six treatments were taken combining three organic manures viz. Vermicompost @ 3.0 t/ha, Mustard oil cake @ 1.0 t/ha and Neem cake @ 1.0 t/ha and two concentrations of gibberellic acid (GA3) viz. 75 ppm and 100 ppm along with a control. Foliar application of GA3 was carried out at 40 and 60 days after planting whereas organic manures were applied as basal dose. Results of the study suggested that higher doses i.e. 100 ppm of GA3 along with vermicompost exhibited more vegetative growth whereas 75 ppm GA3 resulted in higher fruit set and yield in both the varieties. It was found that vermicompost @ 3.0 t/ha combined with 100 ppm GA3 recorded the highest plant height (24.7 cm and 21.4 cm) and numbers of leaves per plant (46.0 and 68.7) in both Sweet Charlie and Winter Dawn varieties, respectively. Whereas, highest fruit diameter (3.3cm and 3.4cm), fruit length (4.6cm and 4.8cm), fruit weight (18.2 g and 17.9 g), number of fruits per plant (24.6 and 32.0), yield per plant (447.8 g and 572.1 g) and yield per hectare (18.80 t and 24.03 t) were recorded under vermicompost @ 3.0 t/ha in combination with 75 ppm GA3 in both Sweet Charlie and Winter Dawn varieties, respectively. It was observed that Winter Dawn variety produced a 28.0% higher yield as compared to Sweet Charlie under the best treatment i.e. vermicompost @ 3.0 t/ha in combination with 75 ppm GA3.

Despite quantum leaps, the biomimetic regeneration of cartilage and osteochondral regeneration remains a major challenge, owing to the complex and hierarchical nature of compositional, structural and functional properties. In this review, an account of the prevailing challenges in biomimicking the gradients in porous microstructure, cells and extracellular matrix (ECM) orientation is presented. Further, the spatial arrangement of the cues in inducing vascularization in the subchondral bone region while maintaining the avascular nature of the adjacent cartilage layer is highlighted. With rapid advancement in biomaterials science, biofabrication tools and strategies, the state-of-the-art in osteochondral regeneration since the last decade has expansively elaborated. This includes conventional and additive manufacturing of synthetic/natural/ECM-based biomaterials, tissue-specific/mesenchymal/progenitor cells, growth factors and/or signaling biomolecules. Beyond the laboratory-based research and development, the underlying challenges in translational research are also provided in a dedicated section. A new generation of biomaterial-based acellular scaffold systems with uncompromised biocompatibility and osteochondral regenerative capability is necessary to bridge the clinical demand and commercial supply. Encompassing the basic elements of osteochondral research, this review is believed to serve as a standalone guide for early career researchers, in expanding the research horizon to improve the quality of life of osteoarthritic patients affordably.

Clinical success of regenerative medicine for treating deep-tissue skin injuries depends on the availability of skin grafts. Though bioengineered constructs are tested clinically, lack of neovascularization provide only superficial healing. Thus constructs, which promotes wound healing and supports vascularization has gained priority in tissue engineering. In this study, chitosan-collagen-fibrinogen (CCF) scaffold was fabricated using freeze-drying method without using any chemical crosslinkers. CCF scaffolds proved cytocompatibility and faster healing in in vitro scratch assay of primary human adult dermal fibroblasts cells with progressively increasing vascular endothelial growth factor-A and reducing vascular endothelial growth factor receptor 1 expressions. Skin regeneration evaluated on in vivo full thickness wound model confirmed faster remodeling with angiogenic signatures in CCF scaffold-implanted mice. Histopathological observations corroborated with stereo-zoom and SS-optical coherence tomography images of wound sites to prove the maturation of healing-bed, after 12 days of CCF implantation. Therefore, it is concluded that CCF scaffolds are promising for skin tissue regeneration and demonstrates pro-angiogenic potential.

Despite different nanomaterials were developed so far against cancer, their potential drawbacks are still scarcely considered. The off-target delivery of a therapeutic compound, as well as the non-specific uptake of these nanomaterials by healthy tissues or organs, and their potential immunogenicity are some of the major issues that still have to be faced prior to a successful clinical translation. This work aims to develop an innovative theranostic, biocompatible, and drug-loaded nanoconstruct based on Gadolinium-doped Zinc Oxide (ZnO-Gd) nanocrystals (NCs), focusing on one of the most lethal diseases, i.e., pancreatic cancer. The use of zinc oxide is motivated by the huge potential of this nanomaterial already demonstrated for in vitro and in vivo applications, while the Gadolinium doping confers magnetic properties useful for diagnostics. Furthermore, an innovative biomimetic shell is here used to coat the NCs: it is composed of a lipid bilayer made from extracellular vesicles (EVs) combined with other synthetic lipids and a peptide targeting the pancreatic tumor microenvironment. To complete the nanoconstruct therapeutic function, Gemcitabine, a first-line drug for pancreatic cancer treatment, was adsorbed on the ZnO-Gd NCs prior to the coating with the above-mentioned lipidic shell. The aim of this work is thus to strongly enhance the therapeutic capability of the final nanoconstruct, providing it with high biocompatibility, colloidal stability in biological media, efficient cargo loading and release properties, as well as active targeting for site-selective drug delivery. Furthermore, the magnetic properties of the ZnO-Gd NCs core can in future allow efficient in situ bioimaging capabilities based on Magnetic Resonance Imaging technique. The obtained nanoconstructs were tested on two different pancreatic cancer cell lines, i.e., BxPC-3 and the metastatic AsPC-1, proving high cell internalization levels, mediated by the targeting peptide exposed on the nanoconstruct. Cellular cytotoxicity assay performed on both cell lines dictated ~ 20% increased cell killing efficacy of Gemcitabine when delivered through the nanoconstruct rather than as a free drug. Taken together, our designed theranostic nanoconstruct can have a significant impact on the standard treatment of pancreatic cancer.

Congenital granular cell epulis (CGCE) is a rare tumor of gingiva that is exclusive to newborns, has marked female predominance, and is rarely associated with other abnormalities. Although benign in behavior, CGCE can be lethal by obstruction of respiration and/or deglutition and can require a multidisciplinary team of specialist at birth for survival of an otherwise normal infant. Histologically, CGCE resembles granular cell tumor (GCT), but unlike GCT, which is Schwannian-derived, derivation of CGCE remains an enigma, largely because of its low prevalence. This study presents 24 new cases of CGCE, the largest series since the original description 150 years ago and permits detailed study of homogeneity of cases diagnosed as CGCE as well as detailed comparisons of CGCE with GCT by clinical, morphological, immunohistochemical, and ultrastructural studies. The data show homogeneity within the CGCE cases, more differences than similarities between CGCE and GCT, and no immunohistochemical staining for common placental proteins/hormones in CGCE. The findings support a primitive mesenchymal cell origin, and a progressive degenerative process in CGCE, rather than neoplasia. Prenatal detection of this lesion is important to facilitate adequate preparations for support of these infants during labor and delivery.

In clinical studies, survival analysis is a well known technique to analyze time to event data with the assumption that every subject in the study will encounter the event of interest. With recent advancements in the drug development industry, a fraction of subjects may not face the event and are considered as immune or cured. However, due to the finite study period, full knowledge of subjects who are immune is usually not known and hence, can be considered as missing. We develop a novel semi-parametric algorithm to address this problem by minimizing a suitable loss function, which incorporates the missing data and generates cure indicators for the censored individuals. We prove the existence of a global minimizer for the loss function and establish some asymptotic properties, demonstrate via numerical experiments that under appropriate circumstances, our approach performs better than simpler alternatives, and use this algorithm to estimate lifetime parameters and the overall survivor function.

Since aptamers were first reported in the early 2000s, research on their use for the detection of health-relevant analytical targets has exploded. This review article provides a brief overview of the most recent developments in the field of aptamer-based biosensors for global health applications. The review provides a description of general aptasensing principles and follows up with examples of recent reports of diagnostics-related applications. These applications include detection of proteins and small molecules, circulating cancer cells, whole-cell pathogens, extracellular vesicles, and tissue diagnostics. The review also discusses the main challenges that this growing technology faces in the quest of bringing these new devices from the laboratory to the market.

Kalighat’s paintings originated in West Bengal, India in the 19th century, near Kalighat Kali Temple, in Calcutta, India, and and from being souvenir pieces taken by visitors to the Kali Temple, the paintings developed over a period of time as a distinct Indian form of painting and art. The Kalighat Paintings developed to depict a range of themes ranging from mythological characters to depictions of the social scene. The paintings served as a kind of mirror of the society in which they worked. Under the influence of an increasingly growing European society, they underwent a transformation. They were able to rapidly adapt the interests of then popular interest and reflect different contemporary themes., and to represent different contemporary themes. The charm of the Kalighat paintings lies in the fact that they captured the essence of everyday life and have inspired contemporary artists like the late Jamini Roy even to this day. Experts find the brushwork on these paintings to be precise, flawless, elegant and one of India’s smoothest art types.

Deep neural networks (DNNs) have shown success in image classification, with high accuracy in recognition of everyday objects. Performance of DNNs has traditionally been measured assuming human accuracy is perfect. In specific problem domains, however, human accuracy is less than perfect and a comparison between humans and machine learning (ML) models can be performed. In recognising everyday objects, humans have the advantage of a lifetime of experience, whereas DNN models are trained only with a limited image dataset. We have tried to compare performance of human learners and two DNN models on an image dataset which is novel to both, i.e. histological images. We thus aim to eliminate the advantage of prior experience that humans have over DNN models in image classification. Ten classes of tissues were randomly selected from the undergraduate first year histology curriculum of a Medical School in North India. Two machine learning (ML) models were developed based on the VGG16 (VML) and Inception V2 (IML) DNNs, using transfer learning, to produce a 10-class classifier. One thousand (1000) images belonging to the ten classes (i.e. 100 images from each class) were split into training (700) and validation (300) sets. After training, the VML and IML model achieved 85.67 and 89% accuracy on the validation set, respectively. The training set was also circulated to medical students (MS) of the college for a week. An online quiz, consisting of a random selection of 100 images from the validation set, was conducted on students (after obtaining informed consent) who volunteered for the study. 66 students participated in the quiz, providing 6557 responses. In addition, we prepared a set of 10 images which belonged to different classes of tissue, not present in training set (i.e. out of training scope or OTS images). A second quiz was conducted on medical students with OTS images, and the ML models were also run on these OTS images. The overall accuracy of MS in the first quiz was 55.14%. The two ML models were also run on the first quiz questionnaire, producing accuracy between 91 and 93%. The ML models scored more than 80% of medical students. Analysis of confusion matrices of both ML models and all medical students showed dissimilar error profiles. However, when comparing the subset of students who achieved similar accuracy as the ML models, the error profile was also similar. Recognition of ‘stomach’ proved difficult for both humans and ML models. In 04 images in the first quiz set, both VML model and medical students produced highly equivocal responses. Within these images, a pattern of bias was uncovered–the tendency of medical students to misclassify ‘liver’ tissue. The ‘stomach’ class proved most difficult for both MS and VML, producing 34.84% of all errors of MS, and 41.17% of all errors of VML model; however, the IML model committed most errors in recognising the ‘skin’ class (27.5% of all errors). Analysis of the convolution layers of the DNN outlined features in the original image which might have led to misclassification by the VML model. In OTS images, however, the medical students produced better overall score than both ML models, i.e. they successfully recognised patterns of similarity between tissues and could generalise their training to a novel dataset. Our findings suggest that within the scope of training, ML models perform better than 80% medical students with a distinct error profile. However, students who have reached accuracy close to the ML models, tend to replicate the error profile as that of the ML models. This suggests a degree of similarity between how machines and humans extract features from an image. If asked to recognise images outside the scope of training, humans perform better at recognising patterns and likeness between tissues. This suggests that ‘training’ is not the same as ‘learning’, and humans can extend their pattern-based learning to different domains outside of the training set.

Inkjet printing is extremely precise in terms of the ejected microdroplets (picoliter volume), contributing an unparalleled lateral resolution. Additionally, the benefits of high-speed deposition, contactless ink delivery, and the use of a range of ink materials endorse this technique as suitable for high-throughput 3D manufacturing. This article provides an overview of inkjet 3D printing (also referred to as 3D inkjetting). It then highlights the major components and accessories used in commercial and laboratory-based 3D inkjet printers. Next, the article describes the process physics of the transient phenomena involved in both binder-jetting- and direct-inkjetting-based 3D printing. It then discusses the scope and advantages of 3D inkjetting in the manufacturing of metallic, ceramic, and polymer-based biomaterials. The article also discusses several approaches and methodologies to examine the in vitro cytocompatibility and in vivo biocompatibility of both binder-jetted and direct-inkjetted scaffolds for biomedical applications. Finally, it discusses the challenges and troubleshooting methodologies in 3D inkjetting of biomaterials.

The effect of gibberellic acid concentrations on fruit characters and yield of strawberry was studied on two varieties, namely ‘Sweet Charlie’ and ‘Winter Dawn’ during November, 2018 to March, 2019. Foliar application of three different concentration of GA3 viz. 50 ppm, 75 ppm and 100 ppm were done at 40 days and 60 days after planting. Experimental results showed that GA3 @ 75 ppm had the best effect to increase yield components and yield of both the varieties. Under GA3 @ 75 ppm, Winter Dawn exhibited higher fruit diameter (3.38cm) and fruit length (4.74cm) as compared to Sweet Charlie (3.28cm fruit diameter and 4.60cm fruit length). Though the fruit weight was slightly higher in Sweet Charlie (18.36g) as against Winter Dawn (17.90g) under the best treatment i.e. 75 ppm GA3 the yield recorded was higher in Winter Dawn (573.62g/plant and 24.04t/ha) as against Sweet Charlie (445.43g/plant and18.73t/ ha) due to higher number of fruits (32.44/plant) produced by Winter Dawn as compared to Sweet Charlie (24.94/plant). So, Winter Dawn variety produced 28.35% higher yield as compared to Sweet Charlie under GA3 @ 75 ppm treatment.

Aim: Histomorphological study of urothelial carcinoma on TRBT and Cystectomy specimen and its categorization on the basis of WHO grading & pTNM staging and to nd out the correlation between CK20 and CD44 exprression with tumour grade, pTNM staging. Material And Method: This descriptive cross sectional prospective study was conducted in the Department of Pathology, R G Kar Medical College & Hospital Kolkata in collaboration with Department of Urosurgery, R G Kar Medical College & Hospital, Kolkata, West Bengal. The present study is intended to nd out over expression of CD44 & CK20 in Urothelial Carcinoma of Bladder and correlate with tumour grade and clinical features. Result: There is strong association between CD44, CK20 expression and Stage of Urothelial Carcinoma cases and had a strong association between CD44 expressions and grade Urothelial Carcinoma cases. Conclusion: CK20 overexpression was seen more signicantly in High Grade tumours HGPUC (p < 0.05) as well as advanced stage pT2 and CD44 overexpression was more signicantly in lower grade tumours LGPUC (p