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Background: Anxiety is a significant psychological challenge for patients newly diagnosed with cancer and scheduled for chemotherapy, potentially affecting their treatment adherence. This study aimed to evaluate the impact of watching the Tom and Jerry cartoon on reducing anxiety in individuals undergoing chemotherapy for the first time.Method: This pilot study employed a prospective, non-randomized, observational, two-arm, pre-and post-test design involving literate English-speaking patients (test group) and non-literate patients (control group) who were about to receive cytotoxic chemotherapy for their cancer. The test group viewed Tom and Jerry cartoons via video systems, whereas the control group was exposed to Kannada movies. An 11-point Likert scale featuring facial expressions assessed patients' anxiety levels three times: 20 minutes before, 30 minutes after, and following the chemotherapy session. Data analysis included frequency, percentage, chi-square tests for patient and treatment data, and repeated measures ANOVA with Bonferroni correction for anxiety scores at three-time intervals. A P-value of

Summary: Geometrically controlled stem cell differentiation promotes reproducible pattern formation. Here, we present a protocol to fabricate elastomeric stencils for patterned stem cell differentiation. We describe procedures for using photolithography to produce molds, followed by molding polydimethylsiloxane (PDMS) to obtain stencils with through holes. We then provide instructions for culturing cells on stencils and, finally, removing stencils to allow colony growth and cell migration. This approach yields reproducible two-dimensional organoids tailored for quantitative studies of growth and pattern formation.For complete details on the use and execution of this protocol, please refer to Lehr et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract A smart home energy management system plays an important role in improving the efficiency of an energy distribution system and also helps to reduce the carbon footprint of the power utility company. For a developing country like India, one of the main challenges faced while integrating an energy management system and renewable energy technology is the migration cost faced by the user from the existing system. The existing energy policy of the nation or the community should be reformed in such a way that the user who is willing to adapt to an energy management system should be properly rewarded. Smart appliances and IoT-enabled devices reduce wiring complexity in any conventional home and the smart metering facility aids in the bidirectional communication between consumers and utility companies. But how does it take care of user privacy? What are the reasons behind the user’s negligence on-demand response schemes in India? Through a case study, it was observed that the power consumption of domestic consumers in India increased over the years. It was also observed through an energy survey of 200 low-tension domestic consumers that a simple reengineering of lighting loads can save up to 4.68 Megawatt-hour of energy in a year. The paper also identified the negative impact of the inclining block rate billing scheme by comparing the bimonthly energy consumption pattern of consumers and also proposed a new billing scheme. The paper also reviews the types of optimization methods available for load scheduling. This paper is an attempt to enlighten readers on the importance of adopting a sustainable home energy management system, as a socio-economic commitment towards a green future.

Background and Aims: Ventilator-associated pneumonia (VAP) is a nosocomial infection associated with high morbidity and mortality. This study was undertaken to monitor the trend of the demographical details, comorbid conditions, bacterial etiological agents, and their antibiogram causing VAP in adults in the year 2008, 2013 and 2018. Material and Methods: A retrospective study conducted at the Department of Microbiology, Hospital Infection control and Quality Control at a tertiary care teaching hospital. All the adult patients with more than 48 h of the mechanical ventilator with endotracheal intubation with Clinical Pulmonary infection Score >6 with suspicion of VAP were included in the study at a difference of 5 years, i.e., 2008, 2013, and 2018. Results: A total of 338 patients were included in the study, of which males accounted for more than two-third of the patients studied. Nearly 45% of the patients belonged to geriatric (>60 years) age group. The most common comorbid conditions were chronic obstructive pulmonary disease, hypertension and diabetes mellitus. Among the gram-negative isolates, Klebsiella pneumoniae, Acinetobacter species, and Pseudomonas aeruginosa were the most common. There is an emergence of resistance to most commonly administered antimicrobial agents like aminoglycosides, levofloxacin, piperacillin/tazobactum, and carbapenems during the study period. Conclusion: This is a ten-year study on the antibiotic resistance pattern of organisms causing VAP. As far as the authors are aware, this is the first study addressing the pattern of change in drug resistance in the organisms causing VAP over a decade. The emergence of multi-drug resistant (MDR) MDR pathogens, especially in intensive care unit (ICU), is a great concern for the intensivist and infection control physicians. Preventive measures need to be undertaken to control the spread of these pathogens to the patients in the ICU.

Predicting the consequences of the agent’s actions on its environment is a pivotal challenge in robotic learning, which plays a key role in developing higher cognitive skills for intelligent robots. While current methods have predominantly relied on vision and motion data to generate the predicted videos, more comprehensive sensory perception is required for complex physical interactions such as contact-rich manipulation or highly dynamic tasks. In this work, we investigate the interdependence between vision and tactile sensation in the scenario of dynamic robotic interaction. A multi-modal fusion mechanism is introduced to the action-conditioned video prediction model to forecast future scenes, which enriches the single-modality prototype with a compressed latent representation of multiple sensory inputs. Additionally, to accomplish the interactive setting, we built a robotic interaction system that is equipped with both web cameras and vision-based tactile sensors to collect the dataset of vision-tactile sequences and the corresponding robot action data. Finally, through a series of qualitative and quantitative comparative study of different prediction architecture and tasks, we present insightful analysis of the cross-modality influence between vision, tactile and action, revealing the asymmetrical impact that exists between the sensations when contributing to interpreting the environment information. This opens possibilities for more adaptive and efficient robotic control in complex environments, with implications for dexterous manipulation and human-robot interaction.

Introduction: Tuberculosis (TB) is a disease that causes severe mortality and morbidity worldwide, including India. Endobronchial Tuberculosis (EBTB) is an uncommon form of TB, which is often underdiagnosed due to the difficulty in diagnosis. This form of TB often has a poor prognosis and long-lasting sequelae. Aim: To study the proportion of EBTB in clinically diagnosed pulmonary TB and to study the clinicoradiological and bronchoscopic profile of EBTB. Materials and Methods: This study was a hospital-based record-based cross-sectional study that included patients with sputum smear negative for Acid-Fast Bacilli (AFB) and Mycobacterium tuberculosis (M. tuberculosis) not detected on Nucleic Acid Amplification Test (NAAT), who were clinically diagnosed with TB. Bronchoscopy was performed on such patients, and samples were sent for investigations, including histopathology and NAAT. Demographic characteristics, bronchoscopy and radiology findings , and microbiology results were documented. Quantitative variables were summarised as means, and categorical variables were presented as percentages. Results: A total of 198 underwent bronchoscopy, of which 20 (10%) were diagnosed with EBTB. The mean age was 22 years, and 65% were females. The most common clinical feature in these patients was fever, the most common radiological presentation was lobar collapse, and the most common bronchoscopy feature was a tumorous lesion. NAAT detected M. tuberculosis in the bronchial wash in 50% of patients diagnosed with EBTB. A total of 45% of patients had TB which was diagnosed on histopathology. Conclusion: EBTB was diagnosed in 10% of smear-negative, NAAT-negative cases. The use of NAAT on bronchoscopy wash samples resulted in a high yield in diagnosis.

Soft robots exhibit complex nonlinear dynamics with large degrees of freedom, making their modelling and control challenging. Typically, reduced-order models in time or space are used in addressing these challenges, but the resulting simplification limits soft robot control accuracy and restricts their range of motion. In this work, we introduce an end-to-end learning-based approach for fully dynamic modelling of any general robotic system that does not rely on predefined structures, learning dynamic models of the robot directly in the visual space. The generated models possess identical dimensionality to the observation space, resulting in models whose complexity is determined by the sensory system without explicitly decomposing the problem. To validate the effectiveness of our proposed method, we apply it to a fully soft robotic manipulator, and we demonstrate its applicability in controller development through an open-loop optimization-based controller. We achieve a wide range of dynamic control tasks including shape control, trajectory tracking and obstacle avoidance using a model derived from just 90 min of real-world data. Our work thus far provides the most comprehensive strategy for controlling a general soft robotic system, without constraints on the shape, properties, or dimensionality of the system.

Abstract We reported exciton binding-energy determination using tunneling-current spectroscopy of Germanium (Ge) quantum dot (QD) single-hole transistors (SHTs) operating in the few-hole regime, under 405–1550 nm wavelength (λ) illumination. When the photon energy is smaller than the bandgap energy (1.46 eV) of a 20 nm Ge QD (for instance, λ = 1310 nm and 1550 nm illuminations), there is no change in the peak voltages of tunneling current spectroscopy even when the irradiation power density reaches as high as 10 µW/µm2. In contrast, a considerable shift in the first hole-tunneling current peak towards positive VG is induced (ΔVG ≈ 0.08 V at 0.33 nW/µm2 and 0.15 V at 1.4 nW/µm2) and even additional photocurrent peaks are created at higher positive VG values (ΔVG ≈ 0.2 V at 10 nW/µm2 irradiation) by illumination at λ = 850 nm (where the photon energy matches the bandgap energy of the 20 nm Ge QD). These experimental observations were further strengthened when Ge-QD SHTs were illuminated by λ = 405 nm lasers at much lower optical-power conditions. The newly-photogenerated current peaks are attributed to the contribution of exciton, biexciton, and positive trion complexes. Furthermore, the exciton binding energy can be determined by analyzing the tunneling current spectra.

Soft sensing technologies provide a novel alternative for state estimation in wearables and robotic systems. They allow one to capture intrinsic state parameters in a highly conformable manner. However, due to the nonlinearities in the materials that make up a soft sensor, it is difficult to develop accurate models of these systems. Consequently, design of these soft sensors is largely user defined or based on trial and error. Since these sensors conform and take the shape of the sensing body, these issues are further exacerbated when they are installed. Herein, a framework for the automated design optimization of soft sensors using closed‐loop 3D printing of a recyclable hydrogel‐based sensing material is presented. The framework allows direct printing of the sensor on the sensing body using visual feedback, evaluates the sensor performance, and iteratively improves the sensor design. Following preliminary investigations into the material and morphology parameters, this is demonstrated through the optimization of a sensorized glove which can be matched to specific tasks and individual hand shapes. The glove's sensors are tuned to respond only to particular hand poses, including distinguishing between two similar tennis racket grip techniques.

Abstract Tactility in biological organisms is a faculty that relies on a variety of specialized receptors. The bimodal sensorized skin, featured in this study, combines soft resistive composites that attribute the skin with mechano‐ and thermoreceptive capabilities. Mimicking the position of the different natural receptors in different depths of the skin layers, a multi‐layer arrangement of the soft resistive composites is achieved. However, the magnitude of the signal response and the localization ability of the stimulus change with lighter presses of the bimodal skin. Hence, a learning‐based approach is employed that can help achieve predictions about the stimulus using 4500 probes. Similar to the cognitive functions in the human brain, the cross‐talk of sensory information between the two types of sensory information allows the learning architecture to make more accurate predictions of localization, depth, and temperature of the stimulus contiguously. Localization accuracies of 1.8 mm, depth errors of 0.22 mm, and temperature errors of 8.2 °C using 8 mechanoreceptive and 8 thermoreceptive sensing elements are achieved for the smaller inter‐element distances. Combining the bimodal sensing multilayer skins with the neural network learning approach brings the artificial tactile interface one step closer to imitating the sensory capabilities of biological skin.

The medical sub-specialty of Oncology presents diverse ethical dilemmas, often challenging cancer healthcare workers with difficult-to-handle clinical scenarios that are tough from a personal and professional perspective. Making decisions on patient care in various circumstances is a defining obligation of an oncologist and those duty-based judgments entail more than just selecting the best treatment or solution. Ethics is an essential and inseparable aspect of clinical medicine and the oncologists as well as the allied health care workers are ethically committed to helping the patient, avoiding or minimizing harm, and respecting the patient’s values and choices. This review provides an overview of ethics and clinical ethics and the four main ethical principles of autonomy, beneficence, non-maleficence, and justice are stated and explained. At times there are frequently contradictions between ethical principles in patient care scenarios, especially between beneficence and autonomy. In addition, truth-telling, professionalism, empathy, and cultural competence; which are recently considered important in cancer care, are also addressed from an Indian perspective.

Background: Radiation dermatitis is known to be a major side-effect occurring following cancer treatment. We conducted the present study to understand whether salivary lactate dehydrogenase (LDH) could be conducive to predict the development of radiation-dermatitis in the head and neck cancer (HNC) patients undergoing curative radiotherapy (60-70 Gy).Method: This was a prospective study performed on HNC patients requiring curative radiotherapy. Saliva was collected at two points from the willing volunteers. The first time point was prior to the first fraction of 2 Gy radiation and the second one was 24 hours after the first fraction and before exposure to the second fraction. The saliva collected at the both time points were analyzed for the levels of salivary LDH using standard procedure. The patients were provided with the standard care throughout the treatment period and the incidence and severity of radiation dermatitis was noted down using a proforma sheet throughout the 7-week treatment period.Results: The results suggested that with exposure to 2 Gy fraction, there was an increase in the level of salivary LDH (387.11 ± 18.98 IU/L vs. 368. 13 ± 19.56IU/L); this increase was significant (t = 20.06 and P < 0.001). The LDH data was stratified based on the severity of dermatitis [mild (grades 1 and 2) vs. severe (grades 3 and 4)] in accordance to the Radiation Therapy Oncology Group/European Organization for Research and Treatment Cancer (RTOG) grading. The LDH values were subjected to Karl Pearson’s correlation analysis with the grade of dermatitis and the results indicated a P value of 0.019 and R value of 0.24.Conclusion: For the first time, our study revealed that salivary LDH could be a useful marker to understand the development of radiation-induced dermatitis in HNC patients undergoing curative radiotherapy. The most advantageous aspect herewith is that the collection of saliva does not require skilled people or special equipment; it cou ld be done at repeated intervals and without causing any invasive process.

Introduction The Florida-California Cancer Research, Education, and Engagement (CaRE 2 ) Health Equity Center is a triad partnership committed to increasing institutional capacity for cancer disparity research, the diversity of the cancer workforce, and community empowerment. This article provides an overview of the structure, process innovations, and initial outcomes from the first 4 years of the CaRE 2 triad partnership. Methods CaRE 2 serves diverse populations in Florida and California using a “molecule to the community and back” model. We prioritize research on the complex intersection of biological, environmental, and social determinants health, working together with scientific and health disparities communities, sharing expertise across institutions, bidirectional training, and community outreach. Partnership progress and outcomes were assessed using mixed methods and four Program Steering Committee meetings. Results Research capacity was increased through development of a Living Repository of 81 cancer model systems from minority patients for novel cancer drug development. CaRE 2 funded 15 scientific projects resulting in 38 publications. Workforce diversity entailed supporting 94 cancer trainees (92 URM) and 34 ESIs (32 URM) who coauthored 313 CaRE 2 -related publications and received 48 grants. Community empowerment was promoted via outreaching to more than 3000 individuals, training 145 community cancer advocates (including 28 Community Scientist Advocates), and publishing 10 community reports. CaRE 2 members and trainees together have published 639 articles, received 61 grants, and 57 awards. Conclusion The CaRE 2 partnership has achieved its initial aims. Infrastructure for translational cancer research was expanded at one partner institution, and cancer disparities research was expanded at the two cancer centers.

Manipulation strategies based on the passive dynamics of soft‐bodied interactions provide robust performances with limited sensory information. They utilize the kinematic structure and passive dynamics of the body to adapt to objects of varying shapes and properties. However, these soft passive interactions make the state of the robotic device influenced by the environment, making control generation and state estimation difficult. This work presents a closed‐loop framework for dynamic interaction‐based grasping that relies on two novelties: 1) a wrist‐driven passive soft anthropomorphic hand that can generate robust grasp strategies using one‐step kinaesthetic teaching and 2) a learning‐based perception system that uses temporal data from sparse tactile sensors to predict and adapt to failures before it happens. With the anthropomorphic soft design and wrist‐driven control, it is shown that controllers can be generated robust to novel objects and location uncertainty. With the learning‐based high‐level perception system and 32 sensing receptors, it is shown that failures can be predicted in advance, further improving the robustness of the entire system by more than doubling the grasping success rate. From over 1000 real‐world grasping trials, both the control and perception framework are also seen to be transferable to novel objects and conditions. An interactive preprint version of the article can be found here: https://doi.org/10.22541/au.167687985.55182112/v1.

Objective: To assess the effectiveness of platelet-rich fibrin (PRF) with decalcified freeze-dried bone allograft (DFDBA) compared to DFDBA alone in mandibular grade–II furcation defects. Material and Methods: A quasi-experimental study was conducted on nine patients with chronic periodontitis, each having two almost identical mandibular grade II furcation defects. Test sites (left mandibular first molars) were treated with open flap debridement (OFD), DFDBA, and PRF, whereas control sites (right mandibular first molars) received OFD and DFDBA alone. Clinical parameters (plaque index (PI), gingival index (GI), vertical clinical attachment level (VCAL) and horizontal clinical attachment level (HCAL) into the furcation defect) and radiographic measurements (mean alveolar bone defect) were done at baseline and after six months postoperatively. Results: The gain in relative horizontal clinical attachment level (RHCAL) in the test sites was 2.94±0.52 mm compared to 1.33±0.35 mm in control sites (p=0.01). Improvement in mean alveolar bone defect (MABD) (was 1.21±0.5 mm2 at test sites compared to 1.15±0.7 mm2 at control sites) probing pocket depth (PPD), recession, relative vertical attachment level (RVCAL), and percentage of bone fill was found in the test sites compared to control, which statistically insignificant. Conclusion: The test sites had better outcomes than control sites, which was significant for the parameter RHCAL. Therefore, combining the biological benefits of autologous PRF with DFDBA is an efficient and economical treatment modality for the management of mandibular grade II furcation defects.

Abstract Background Angular cheilitis, an infection mainly caused by Candida yeasts, is featured by the appearance of inflammatory lesions at the bilateral corners of the mouth, particularly in patients with poor oral hygiene, ill-fitting dentures and old age. The first isolation of an atypical yeast, Cystobasidium calyptogenae, from oral samples of a patient presenting with angular cheilitis is discussed in this study. Case presentation Angular cheilitis was diagnosed in a 60-year-old denture-wearing woman who presented with an irritation fibroma on her right lower buccal sulcus over the premolar region. Primary cultures of her oral swab and oral rinse samples grew a pure culture of an uncommon yeast strain resembling Rhodotorula sp. Sequence analysis of the yeast internal transcribed spacer (ITS) gene region and D1D2 domain showed highest similarity (99.6% and 100%, respectively) to C. calyptogenae CBS 9125 type strain. Following 2 weeks of treatment with miconazole/fusidic acid and mouthwash, the oral lesion showed improvement with less erythema. C. calyptogenae was not isolated from the patient’s oral samples upon repeat sampling. Conclusion This is the first report on the isolation of C. calyptogenae from human oral samples. The ability of C. calyptogenae to grow at 37 °C and the fact that it was the only yeast species isolated from the patient’s oral samples suggests its pathogenic potential and possible involvement in angular cheilitis. The ubiquitous nature of the Cystobasidium yeast is believed to increase the likelihood of opportunistic infections among immunocompromised individuals. As Cystobasidium is phenotypically indistinguishable from Rhodotorula, an emerging opportunistic pathogen, surveillance using molecular identification in clinical settings is essential in providing accurate diagnosis and treatment of uncommon yeast infections.

Abstract The ability to remotely control a free-floating object through surface flows on a fluid medium can facilitate numerous applications. Current studies on this problem have been limited to uni-directional motion control due to the challenging nature of the control problem. Analytical modelling of the object dynamics is difficult due to the high-dimensionality and mixing of the surface flows while the control problem is hard due to the nonlinear slow dynamics of the fluid medium, underactuation, and chaotic regions. This study presents a methodology for manipulation of free-floating objects using large-scale physical experimentation and recent advances in deep reinforcement learning. We demonstrate our methodology through the open-loop control of a free-floating object in water using a robotic arm. Our learned control policy is relatively quick to obtain, highly data efficient, and easily scalable to a higher-dimensional parameter space and/or experimental scenarios. Our results show the potential of data-driven approaches for solving and analyzing highly complex nonlinear control problems.

Road infrastructure is one of the most vital assets of any country. Keeping the road infrastructure clean and unpolluted is important for ensuring road safety and reducing environmental risk. However, roadside litter picking is an extremely laborious, expensive, monotonous and hazardous task. Automating the process would save taxpayers money and reduce the risk for road users and the maintenance crew. This work presents LitterBot, an autonomous robotic system capable of detecting, localizing and classifying common roadside litter. We use a learning-based object detection and segmentation algorithm trained on the TACO dataset for identifying and classifying garbage. We develop a robust modular manipulation framework by using soft robotic grippers and a real-time visual-servoing strategy. This enables the manipulator to pick up objects of variable sizes and shapes even in dynamic environments. The robot achieves greater than 80% classified picking and binning success rates for all experiments; which was validated on a wide variety of test litter objects in static single and cluttered configurations and with dynamically moving test objects. Our results showcase how a deep model trained on an online dataset can be deployed in real-world applications with high accuracy by the appropriate design of a control framework around it.

Natural agents display various adaptation strategies to damages, including damage assessment, localization, healing, and recalibration. This work investigates strategies by which a soft electronic skin can similarly preserve its sensitivity after multiple damages, combining material‐level healing with software‐level adaptation. Being manufactured entirely from self‐healing Diels–Alder matrix and composite fibers, the skin is capable of physically recovering from macroscopic damages. However, the simultaneous shifts in sensor fiber signals cannot be modeled using analytical approaches because the materials viscoelasticity and healing processes introduce significant nonlinearities and time‐variance into the skin's response. It is shown that machine learning of five‐layer networks after 5000 probes leads to highly sensitive models for touch localization with 2.3 mm position and 95% depth accuracy. Through health monitoring via probing, damage and partial recovery are localized. Although healing is often successful, insufficient recontact leads to limited recovery or complete loss of a fiber. In these cases, complete resampling and retraining recovers the networks’ full performance, regaining sensitivity, and further increasing the system's robustness. Transfer learning with a single frozen layer provides the ability to rapidly adapt with fewer than 200 probes.

Oral potentially malignant disorders (OPMD) are precursors of oral squamous cell carcinoma (OSCC), and the presence of oral epithelial dysplasia (OED) in OPMD confers an increased risk of malignant transformation. Emerging evidence has indicated a role for the immune system in OPMD disease progression; however, the underlying immune mechanisms remain elusive. In this study, we used immune signatures established from cancer to delineate the immune profiles of moderate and severe OED, which are considered high-risk OPMD. We demonstrated that moderate and severe OEDs exhibit high lymphocyte infiltration and upregulation of genes involved in both immune surveillance (major histocompatibility complex-I, T cells, B cells and cytolytic activity) and immune suppression (immune checkpoints, T regulatory cells, and tumor-associated macrophages). Notably, we identified three distinct subtypes of moderate and severe OED: immune cytotoxic, non-cytotoxic and non-immune reactive. Active immune surveillance is present in the immune cytotoxic subtype, whereas the non-cytotoxic subtype lacks CD8 immune cytotoxic response. The non-immune reactive subtype showed upregulation of genes involved in the stromal microenvironment and cell cycle. The lack of T cell infiltration and activation in the non-immune reactive subtype is due to the dysregulation of CTNNB1, PTEN and JAK2. This work suggests that moderate and severe OED that harbor the non-cytotoxic or non-immune reactive subtype are likely to progress to cancer. Overall, we showed that distinct immune responses are present in high-risk OPMD, and revealed targetable pathways that could lead to potential new approaches for non-surgical management of OED.

Abstract Background It is unclear whether faster progression of atherosclerosis explains the higher risk of cardiovascular events in CKD. The objectives of this study were to 1. Characterize the associations of CKD with presence and morphology of atherosclerotic plaques on carotid magnetic resonance imaging (MRI) and 2. Examine the associations of baseline CKD and carotid atherosclerotic plaques with subsequent cardiovascular events. Methods In a subgroup (N = 465) of Systolic Blood Pressure Intervention Trial. (SPRINT) participants, we measured carotid plaque presence and morphology at baseline and after 30-months with MRI. We examined the associations of CKD (baseline eGFR

Abstract The demand for purified water has been increasing day by day. More feasible technologies, including membrane filtration, adsorbents, and so forth have emerged out to be more efficient and cheaper over conventional industrial methods. Nanocellulose, being biodegradable, nontoxic, and sustainable nanofiller exhibits excellent mechanical properties, high aspect ratio, high surface area, and more importantly tunable surface chemistry; is a potential candidate to be employed for water purification. Composite membranes and films for water filtration, constituting of biopolymers have gathered immense interest lately. Compared with its unmodified form, the functionalized NC enhances the compatibility with the matrix and readily forming strong network structures; essential for the formation of channels for better adsorption of impurities and higher water flux. This review highlights some of the recent studies dedicated to making and testing of nanofiltration membranes prepared using nanocellulose and its different functionalized derivatives.

Purpose Development of cancer chemotherapy treatment-induced hyperglycemia/ diabetes (secondary diabetes) is a major problem and has never been reported from India. The present study was planned to ascertain this in women undergoing curative chemotherapy for their breast cancer. Materials and Methods This was a retrospective chart-based study and was conducted in a cancer specialty hospital. The information on women who were nondiabetic at the start of the treatment was collected from the files. Details on cancer diagnosis, domicile, body mass index (BMI), type of diet, marital status, number of children, and previous history of diabetes if any were considered. The blood glucose levels before surgery and after the completion of radiotherapy were considered. World Health Organization (WHO) guidelines for diabetes were considered. The data were subjected to frequency and percentage and analyzed using Chi-square test. Association between the demographic details and development of Hyperglycemia or secondary diabetes or prediabetes was done using the Pearson’s correlation analysis. p < 0.05 was considered as statistically significant. Results A total of 474 cases were included in accordance with the inclusion criteria. The results indicated that by the end of the radiation treatment, 24.89% were prediabetic, 10.97% were diabetic after being in prediabetic stage, 8.22% became diabetic without going through a prediabetic stage, and that 55.91% did not develop either prediabetic or diabetic condition. Analysis of development of secondary diabetes and prediabetes with BMI (p < 0.0001) and age (p < 0.024) showed a strong correlation and was significant. Conclusion To the best of the authors’ knowledge, this is the first study from India, and the results indicate that the development of secondary diabetes in women undergoing curative chemotherapy is high. Attempts are underway to ascertain the cause for the development and how it can be mitigated.

A rare subset of Coronavirus Disease-2019 (COVID-19) positive patients has musculoskeletal manifestations including arthritis, arthralgia, myalgia and non specific bodyaches. Moreover, postviral Reactive Arthritis (ReA) has been reported following COVID-19 infection. This article reports the characteristic joint manifestations of Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) infection in 6 out of 211 consecutive patients with laboratory-confirmed diagnosis of COVID-19 and treated at dedicated hospital. One 49-year-old female patient developed arthritis while having active COVID-19 infection, one 54-year-old male had post COVID-19 ReA, and one 48-year-old female was found to have undifferentiated arthritis. One 58-year-old female patient was initially thought to have ReA the diagnosis was reconsidered later when her symptoms resolved without any disease modifying agents. Two patients 37-year-old male and 63-year-old female, developed arthralgia following COVID-19 infection. Non Steroidal Anti-Inflammatory Drugs (NSAIDs) and steroids were found to be beneficial in the series of patients. The key point to be noted is that not all arthritis or arthralgia following COVID-19 is ReA.

BackgroundIntelectin (ITLN) is an adipokine with two homologs—ITLN1 and ITLN2—that has various physiological functions. Studies analyzing the relationship between ITLN and cancer are focused on ITLN1; the available literature on ITLN2 and cancer is limited. This review aims to evaluate the role of ITLN1 in cancer without imposing any inclusion criteria, to examine pro- and anticancer roles for ITLN1 and to discuss whether the relationship between ITLN and cancer is mediated by obesity.FindingsOverall, ITLN1 level was highly variable in cancer patients but different from healthy individuals. Compared with control groups, patients with gastrointestinal and prostate cancer showed increased concentrations of circulating ITLN1, while patients with gynecological, breast, bladder, and renal cancer had lower ITLN1 levels. Several studies also evaluated tissue and tumor expression of ITLN1. In gastrointestinal cancer, ITLN1 was increased in tumor tissue compared with adjacent healthy tissue and elevated in the visceral adipose tissue of patients compared with controls. Consequently, the high levels of circulating ITLN1 might be determined by the tumor and by the cancer-associated weight loss in gastrointestinal cancer. ITLN1 can activate the phosphoinositide-3-kinase-protein kinase B/Akt (PI3K/Akt) pathway. The improper regulation of this pathway may contribute to a series of cellular events that favor tumor development and progression. Obesity has been linked with an increased risk of developing some cancers. Indeed, low circulating ITLN1 levels may be a marker of the metabolic effects of obesity, rather than obesity per se, and might contribute to a deregulation of the PI3K/Akt pathway.ConclusionsITLN1 could be associated with cancer formation and progression. Since circulating ITLN1 levels are highly variable and differ between cancer types, the local tumor production of ITLN1 could be more relevant in determining malignant behavior. Future research should aim to identify the source of ITLN1 variability, to understand the differences in ITLN1 between distinct tumor types, and to further explore the signaling pathways through which this adipokine influences cancer biology.

HPV-independent head and neck squamous cell carcinoma (HNSCC) is a common cancer globally. The overall response rate to anti-PD1 checkpoint inhibitors (CPIs) in HNSCC is ~16%. One major factor influencing the effectiveness of CPI is the level of tumor infiltrating T cells (TILs). Converting TILlow tumors to TILhigh tumors is thus critical to improve clinical outcome. Here we describe a novel DNA vaccines to facilitate the T-cell infiltration and control tumor growth. We evaluated the expression of target antigens and their respective immunogenicity in HNSCC patients. The efficacy of DNA vaccines targeting two novel antigens were evaluated with or without CPI using a syngeneic model. Most HNSCC patients (43/44) co-expressed MAGED4B and FJX1 and their respective tetramer-specific T cells were in the range of 0.06-0.12%. In a preclinical model, antigen-specific T cells were induced by DNA vaccines and increased T cell infiltration into the tumor, but not MDSC or regulatory T cells. The vaccines inhibited tumor growth and improved the outcome alone and upon combination with anti-PD1 and resulted in tumor clearance in approximately 75% of mice. Pre-existence of MAGED4B and FJX1-reactive T cells in HNSCC patients suggests that these widely expressed antigens are highly immunogenic and could be further expanded by vaccination. The DNA vaccines targeting these antigens induced robust T cell responses and with the anti-PD1 antibody conferring excellent tumor control. This opens up an opportunity for combination immunotherapy that might benefit a wider population of HNSCC patients in an antigen-specific manner.

As-transformed and hot-deformed samples of MnAl-C alloys with Ti or Zr additions have been produced and characterized using magnetometry, X-ray diffraction, scanning electron microscopy and transmission electron microscopy. Both Ti and Zr additions in MnAl-C alloys form carbide primary phases, TiC and ZrC, which consume the carbon meant to be dissolved in the metastable τ-phase to stabilize it against decomposition. With these two additions, the Curie temperature of τ-phase increases while its stability against decomposition decreases. After hot deformation, the MnAl-C alloys with Ti or Zr additions have lower polarisation and remanence due to the reduced stability of the τ-phase. Adding extra carbon along with Ti to a MnAl-C alloy in order to compensate for the C lost on formation of TiC restored the original stability of the τ-phase. After hot-deformation, this alloy exhibited a lower polarisation and remanence owing to the unexpected formation of the γ2-phase.

One of the key challenges in the practical realization of industrial internet of things (IoT) is overcoming Faraday shielding of free space electromagnetic waves emanating from the antennas of wireless systems used for power and data transfer. Metallic structures, machinery, pipeline, etc., cause interference resulting in the loss of signal connectivity among sensor network. Currently available techniques based on ultrasonic-electromagnetic transducers pose severe limitations on frequency, efficiency, and alignment. Here we demonstrate exciting Zenneck type interface waves propagating as localized charge oscillations (modes) along the metal profile, which overcomes the restrictions on frequency, metal obstacles, partial enclosures, and alignment. A finite element methods (FEM) model developed to predict the signal reception and power transfer efficiency across metal infrastructure shows excellent agreement with the experimental results. Electrical power transfer using Zenneck, under open conditions, show 4% drop for distance of 1 to 8 meters (68 to 64%), and 9% drop under shielded conditions for the same range (66 to 57%). For data transmission results, we demonstrate a feasibility, for an input power of 0dBm with several metallic pipelines as obstacles show received power of -11.8 dBm and -19.01 dBm at 6 and 25 meters, respectively.

Oral cancer is a major global health issue accounting for 177,384 deaths in 2018 and it is most prevalent in low- and middle-income countries. Enabling automation in the identification of potentially malignant and malignant lesions in the oral cavity would potentially lead to low-cost and early diagnosis of the disease. Building a large library of well-annotated oral lesions is key. As part of the MeMoSA®(Mobile Mouth Screening Anywhere) project, images are currently in the process of being gathered from clinical experts from across the world, who have been provided with an annotation tool to produce rich labels. A novel strategy to combine bounding box annotations from multiple clinicians is provided in this paper. Further to this, deep neural networks were used to build automated systems, in which complex patterns were derived for tackling this difficult task. Using the initial data gathered in this study, two deep learning based computer vision approaches were assessed for the automated detection and classification of oral lesions for the early detection of oral cancer, these were image classification with ResNet-101 and object detection with the Faster R-CNN. Image classification achieved an F1 score of 87.07% for identification of images that contained lesions and 78.30% for the identification of images that required referral. Object detection achieved an F1 score of 41.18% for the detection of lesions that required referral. Further performances are reported with respect to classifying according to the type of referral decision. Our initial results demonstrate deep learning has the potential to tackle this challenging task.

BACKGROUND: Scrub typhus, an acute febrile illness, is one of the emerging and re-emerging infectious diseases in India. This study was undertaken to assess the clinicohematological, treatment, and outcome profile of the patients diagnosed with scrub typhus at the clinical microbiology department of a tertiary care teaching hospital in Coastal Karnataka, India. MATERIALS AND METHODS: This was a retrospective study conducted with patients diagnosed as scrub typhus between January 2014 and December 2017. The demographic, clinical, laboratory, treatment, and outcome profile of these patients were noted and analyzed by Student's t-test. A P < 0.5 was considered statistically significant. RESULTS: A total of 146 patients were included in the study. The males were more infected than females, and people in the age group of 51–60 years were affected the most. Fever (139, 95.2%) was the most common symptom. Eschar was seen in only 52 (34.89%) patients. Anemia, leukocytosis, neutrophilia, lymphocytopenia, eosinophilia, monocytosis, thrombocytopenia, and raised erythrocyte sedimentation rate were statistically significant in scrub patients. The hepatic and renal indicators were also deranged. All patients were treated with doxycycline, and platelet was transfused in 7 (4.8%) patients. Among the seven dead patients, there were significant eosinopenia and deranged renal parameters compared to the survived patients. CONCLUSION: In endemic area, when a middle-aged individual presents with fever and leukocytosis with thrombocytopenia with or without eschar, scrub typhus should be considered as a differential diagnosis and empirical therapy started.

BACKGROUND: Leptospirosis is a neglected tropical disease caused by spirochete Leptospira interrogans. It is one of the notifiable diseases. It is under-reported and under-diagnosed in tropical countries, including India. AIM: The aim of this study is to compare the clinico-laboratory profile of leptospirosis patients with healthy individuals and survived with dead patients. MATERIAL AND METHODS: This was a retrospective study carried out in people diagnosed with leptospirosis. All the clinical features and laboratory parameters were studied and analyzed as per the Student's t-test. RESULTS: A total of 467 patients were diagnosed with leptospirosis during the study period 2013–2018. Males were majority, and most of the patients belonged to the age group of 31–45 years. Seventy-two patients (15.41%) succumbed to leptospirosis. Fever, vomiting, abdominal pain, jaundice were common symptoms. Leptospirosis patients had significant anemia, leukocytosis, thrombocytopenia, elevated liver, and renal parameters. Among the dead patients, significant neutrophilia, lymphocytopenia, hyperbilirubinemia, hyperuremia, and raised creatinine were observed compared with alive patients. CONCLUSION: Leptospirosis should be strongly suspected in male, working-age groups presenting with fever and jaundice. Anemia, leukocytosis, thrombocytosis were hematological changes in leptospirosis patients. Hepatic and renal dysfunctions with neutrophilia are the risk factors with increased mortality in patients with leptospirosis.

Background: Ethical problems routinely arise in the healthcare profession and more so in hospitals providing cancer diagnosis and care. Literature study indicates that almost all studies addressing ethical issues in cancer have been qualitative and reported from the developed countries, while there has been no study reported from developing countries. For the first time, we performed a questionnaire study to quantify the ethical issues plaguing the healthcare fraternity in the diagnosis and care of people with cancer. Method: This prospective study was conducted under the aegis of UNESCO Bioethics Education and Research Unit of the UNESCO Chair in Bioethics, Haifa at Mangalore Institute of Oncology Mangalore, India. The investigators approached the healthcare professionals involved in diagnosis, treating, and caring for patients with cancer and ascertained various ethical issues they faced. Data were tabulated and subjected to frequency and percentage. Result: The results indicated that discussing end-of-life issues with the patient and breaking bad news were the two most difficult ones while discussing end of life issues with family caregivers was the least. Conclusion: According to this study, oncology treatment involves a series of dilemmatic issues and breaking bad news. Based on the detailed studies and emphasis on handling these issues, it is possible to develop a teaching module for training the health care professionals and workers for managing the ethical issues effectively.

Background: In this study, we sought to understand the usefulness of salivary lactatedehydrogenase as a predictive marker for the development of radiation-inducedmucositis.Methods: This was a prospective study with head and neck cancer patients whorequired curative radiotherapy (>60Gy). We collected patients’ saliva before the onsetof radiation and after 2 Gy of radiation to assess lactate dehydrogenase levels. The patientsreceived the stipulated oral and dental care. Data on incidence and severity of mucositiswas collected using a preform sheet and oral mucositis assessment scale published bythe Radiation Therapy Oncology Group throughout the 7-week treatment period.Results: Salivary lactate dehydrogenase increased with exposure to radiation(Pr = 0.515).Conclusion: The present results have established, for the first time, that salivarylactate dehydrogenase could be a useful predictive marker to understand the developmentof radiation-induced mucositis in patients with head and neck cancer. The proximityof the oral cavity for regular observation and saliva collection is an added advantage.

Objectives: The aim of this descriptive study was to characterise anthropometric variables, aerobic capacity, running performance and energy intake and expenditure of hill runners in free-living conditions, and to investigate the relationship between age, anthropometric variables, aerobic capacity and running performance.Methods: Twenty-eight hill runners participated in this study (17 males and 11 females; aged 18–65 years). Body fat percentage estimate, sum of eight skinfolds (triceps, subscapular, biceps, iliac crest, supraspinale, abdominal, front thigh and medial calf) and maximal oxygen capacity (VO2max) were assessed in a laboratory setting. Participants also completed a timed hill run (Dumyat Hill, Scotland, ascent: 420 m, distance: 8 km) while wearing a portable gas analyzer to assess oxygen consumption (VO2). Energy intake and energy expenditure were assessed in free-living conditions over three consecutive days different from the testing days through self-reported food diaries and accelerometers.Results: VO2max assessed in the lab (51.2 ± 7.6 ml·min−1·kg−1) showed a weak negative relationship with age [rs(23) = −0.38, p = 0.08]. Neither body fat percentage (median 12.4; IQR 10.1–17.1) nor the sum of skinfolds (median 81.8; IQR 62.4–97.8 mm) correlated with age [rs(28) = 0.001, p = 0.10 and 26 rs(28) = −0.02, p = 0.94, respectively]. The observed intensity of the hill run was 89 ± 6% of the age predicted maximum heart rate and 87 ± 9% of the VO2max observed in the lab. Hill running performance correlated with VO2max [r(21) = 0.76, p < 0.001], age [rs(26) = −0.44, p = 0.02] and with estimated body fat percentage and sum of skinfolds [rs(26) = −0.66, p < 0.001 and rs(26) = −0.49, p = 0.01, respectively]. Energy intake negatively correlated with age [rs(26) = −0.43, p = 0.03], with the overall energy intake being significantly lower than the total energy expenditure (2273 ± 550 vs. 2879 ± 510 kcal·day−1; p < 0.001; d = 1.05).Conclusion: This study demonstrated that hill running performance is positively associated with greater aerobic capacity and negatively associated with increases in adiposity and age. Further, the study highlights that hill runners are at risk of negative energy balance.

Abstract Autonomous dishwasher loading is a benchmark problem in robotics that highlights the challenges of robotic perception, planning, and manipulation in an unstructured environment. Current approaches resort to a specialized solution, however, these technologies are not viable in a domestic setting. Learning‐based solutions seem promising for a general purpose solutions; however, they require large amounts of catered data to be applied in real‐world scenarios. This article presents a novel learning‐based solution without a training phase using pre‐trained object detection networks. By developing a perception, planning, and manipulation framework around an off‐the‐shelf object detection network, we are able to develop robust pick‐and‐place solutions that are easy to develop and general purpose requiring only a RGB feedback and a pinch gripper. Analysis of a real‐world canteen tray data is first performed and used for developing our in‐lab experimental setup. Our results obtained from real‐world scenarios indicate that such approaches are highly desirable for plug‐and‐play domestic applications with limited calibration. All the associated data and code of this work are shared in a public repository.

Evolutionary studies have unequivocally proven the transition of living organisms from water to land. Consequently, it can be deduced that locomotion strategies must have evolved from one environment to the other. However, the mechanism by which this transition happened and its implications on bio-mechanical studies and robotics research have not been explored in detail. This paper presents a unifying control strategy for locomotion in varying environments based on the principle of ‘learning to stop’. Using a common reinforcement learning framework, deep deterministic policy gradient, we show that our proposed learning strategy facilitates a fast and safe methodology for transferring learned controllers from the facile water environment to the harsh land environment. Our results not only propose a plausible mechanism for safe and quick transition of locomotion strategies from a water to land environment but also provide a novel alternative for safer and faster training of robots.

The human tactile system is composed of multi-functional mechanoreceptors distributed in an optimized manner. Having the ability to design and optimize multi-modal soft sensory systems can further enhance the capabilities of current soft robotic systems. This work presents a complete framework for the fabrication of soft sensory fiber networks for contact localization, using pellet-based 3D printing of piezoresistive elastomers to manufacture flexible sensory networks with precise and repeatable performances. Given a desirable soft sensor property, our methodology can design and fabricate optimized sensor morphologies without human intervention. Extensive simulation and experimental studies are performed on two printed networks, comparing a baseline network to one optimized via an existing information theory based approach. Machine learning is used for contact localization based on the sensor responses. The sensor responses match simulations with tunable performances and good localization accuracy, even in the presence of damage and nonlinear material properties. The potential of the networks to function as capacitive sensors is also demonstrated.

BackgroundLocal relapse of oral squamous cell carcinoma in non-involved mucosal surgical margins indicated possibility of field alteration in the margins, which could be predicted with certain biomarkers. The objectives were to evaluate the expression of Ki-67, Cornulin and ISG15 in non-involved mucosal surgical margins and the association of clinicopathological prognosticators with local relapse in oral squamous cell carcinoma.MethodsSurgical margins from the study (relapse) group (n = 23), control (non-relapse) group (n = 32) and normal oral mucosa (n = 5) were immunohistochemically stained using Ki-67, Cornulin and ISG15 antibodies. Association between expression of markers and clinicopathological prognosticators with local relapse in oral squamous cell carcinoma was analyzed statistically.ResultsThe study group surgical margins demonstrated significantly decreased Cornulin expression (p = 0.032). Low Cornulin expression was significantly associated with local relapse (p = 0.004) and non-tongue primary tumor (p = 0.013). Although not significantly associated with local relapse, expression of Ki-67 was significantly reduced in female patients (p = 0.041). Age above 57.5 years, Chinese & Indian ethnicity, alcohol consumption, epithelial dysplasia in surgical margins, and type III and IV patterns of invasion of tumor were also significantly related to local relapse. Regression analysis showed low expression of Cornulin (p = 0.018), and increased patient's age (p = 0.008) were predictors of local relapse in oral squamous cell carcinoma, with 34-fold risk and 18-fold risk, respectively. Expression of Ki-67 and ISG15 did not show significant association with local relapse in oral squamous cell carcinoma.ConclusionLow expression of Cornulin is an independent predictor of relapse in oral squamous cell carcinoma.

Cabbage, one of the most popular vegetables in the world is infested by several insect-pests and diseases. Novaluron, a chitin synthesis inhibitor and lambda-cyhalothrin, a synthetic pyrethroid group insecticide are used to manage insect-pests on cabbage. The dissipation kinetics and risk assessment of combination formulation (novaluron 9.45% + lambda-cyhalothrin 1.9%) with different modes of action has not yet been investigated in cabbage. Multi–location supervised field trials were therefore, conducted in different agro-climatic regions of India for safety evaluation of the combination product. The co-formulation at the recommended (novaluron 750 g a.i. ha−1 + lambda-cyhalothrin 750 g a.i. ha−1) and double the recommended (novaluron 1500 g a.i. ha−1 + lambda-cyhalothrin 1500 g a.i. ha−1) dose was sprayed on the cabbage crop. The samples were extracted and cleaned up using a modified QuEChERS method, and the residues analyzed by GC–ECD and GC–MS. The half-life (t1/2) varied between 1.77 and 2.51 and 2.00–3.38 days for novaluron and 1.36–2.24 and 1.69–3.82 days for lambda-cyhalothrin in cabbage at respective doses. The Food Safety and Standards Authority of India (FSSAI) has set the MRL of 0.7 mg kg−1 for novaluron at PHI of 5 days, and no MRL is set for lambda-cyhalothrin in cabbage. On the basis of OECD MRL calculator, the MRLs of 0.6 and 1.5 mg kg−1 for novaluron and lambda-cyhalothrin, respectively were calculated at the respective doses at PHI of 3 days. Hazard quotient (HQ)

Modeling of soft robots is typically performed at the static level or at a second-order fully dynamic level. Controllers developed upon these models have several advantages and disadvantages. Static controllers, based on the kinematic relations tend to be the easiest to develop, but by sacrificing accuracy, efficiency and the natural dynamics. Controllers developed using second-order dynamic models tend to be computationally expensive, but allow optimal control. Here we propose that the dynamic model of a soft robot can be reduced to first-order dynamical equation owing to their high damping and low inertial properties, as typically observed in nature, with minimal loss in accuracy. This paper investigates the validity of this assumption and the advantages it provides to the modeling and control of soft robots. Our results demonstrate that this model approximation is a powerful tool for developing closed-loop task-space dynamic controllers for soft robots by simplifying the planning and sensory feedback process with minimal effects on the controller accuracy.