Impact of Transforming Interface Geometry on Edge States in Valley Photonic Crystals

We investigate how altering the interface geometry from a zigzag to a glide plane interface between two topologically distinct valley Hall emulating photonic crystals (VPC), profoundly affects edge states. We experimentally observe a transition from gapless to gapped edge states, accompanied by the occurrence of slow light within the Brillouin zone, rather than at its edge. We numerically simulate the propagation and measure the transmittance of the modified edge states through a specially designed valley-conserving defect. The robustness to backscattering gradually decreases, suggesting a disruption of valley-dependent transport. We demonstrate the significance of interface geometry to gapless edge states in a VPC.

Is Quadriceps-Strengthening Exercises (QSE) in Medial-Compartment Knee Osteoarthritis with Neutral and Varus Malalignment a Paradox? - A Risk-Appraisal of Strength-Training on Disease Progression

Introduction

The present inquiry seeks to investigate whether the current regimens of QSEs (Quadriceps-Strengthening Exercises) aggravate the disease while mitigating symptoms.

Materials and methods

A comparative study was conducted on 32 patients with medial compartment osteoarthritis of knees. While the neutral group of 16 patients was constituted of those with an anatomical-lateral-femoro-tibial-angle (aFTA) 176-180º, varus group comprised an equal number of patients with an aFTA >180º. A home-based 12-week strength-training program involving weekly visits to hospital for supervised sessions was administered. The outcome measures were visual-analog-scale (VAS), medial patello-femoral joint tenderness (MPFJT), time-up-and-go-test (TUGT), stair-climb test, step test, WOMAC, IKDC scores, aFTA, hip-knee-ankle (HKA) angle, lateral-tibio-femoral-joint-separation (LTFJS), and horizontal-distance-from-centre-of-knee-to-Mikulicz-line.

Results

There was a significant increase in quadriceps strength (p<0.01) in both groups. Values for neutral group with VAS score (p=0.01), MPFJT (p=0.01), TUGT (p=0.01), timing of the stair climb test (p=0.01), WOMAC (p<0.01), and IKDC (p=0.03) were better compared to varus group with VAS score (p=0.13), MPFJT (p=0.03), TUGT (p=0.90), timing of stair climb test (p=0.68), WOMAC (p<0.02), and IKDC (p=0.05). Varus group also showed an increase in aFTA and LTFJS in 12 patients, increase in HKA in 11, and increase in horizontal distance from the centre of knee to the Mikulicz line in 7 patients.

Conclusion

The present study brings to the fore the paradoxical role played by QSEs in management of medial knee OA. While there is a radiological progression of the disease in both neutral and varus mal-aligned knees more so in the latter than the former.

Unlocking The Mysteries of DNA Adducts with Artificial Intelligence

Cellular genome is considered a dynamic blueprint of a cell since it encodes genetic information that gets temporally altered due to various endogenous and exogenous insults. Largely, the extent of genomic dynamicity is controlled by the trade-off between DNA repair processes and the genotoxic potential of the causative agent (genotoxins or potential carcinogens). A subset of genotoxins form DNA adducts by covalently binding to the cellular DNA, triggering structural or functional changes that lead to significant alterations in cellular processes via genetic (e. g., mutations) or non-genetic (e. g., epigenome) routes. Identification, quantification, and characterization of DNA adducts are indispensable for their comprehensive understanding and could expedite the ongoing efforts in predicting carcinogenicity and their mode of action. In this review, we elaborate on using Artificial Intelligence (AI)-based modeling in adducts biology and present multiple computational strategies to gain advancements in decoding DNA adducts. The proposed AI-based strategies encompass predictive modeling for adduct formation via metabolic activation, novel adducts' identification, prediction of biochemical routes for adduct formation, adducts' half-life predictions within biological ecosystems, and, establishing methods to predict the link between adducts chemistry and its location within the genomic DNA. In summary, we discuss some futuristic AI-based approaches in DNA adduct biology.

Cost-effectiveness of a real-time spatiotemporal mapping surveillance system for meticillin-resistant Staphylococcus aureus prevention

OBJECTIVES

An infection surveillance system based on a hospital's digital twin [4D-Disease Outbreak Surveillance System (4D-DOSS)] is being developed in Singapore. It offers near-real-time infection surveillance and mapping capabilities. This early economic modelling study was conducted, using meticillin-resistant Staphylococcus aureus (MRSA) as the pathogen of interest, to assess the potential cost-effectiveness of 4D-DOSS.

METHODS

A Markov model that simulates the likelihood of MRSA colonization and infection was developed to evaluate the cost-effectiveness of adopting 4D-DOSS for MRSA surveillance from the hospital perspective, compared with current practice. The cycle duration was 1 day, and the model horizon was 30 days. Probabilistic sensitivity analysis was conducted, and the probability of cost-effectiveness was reported. Scenario analyses and a value of information analysis were performed.

RESULTS

In the base-case scenario, with 10-year implementation/maintenance costs of 4D-DOSS of $0, there was 68.6% chance that 4D-DOSS would be cost-effective. In a more pessimistic but plausible scenario where the effectiveness of 4D-DOSS in reducing MRSA transmission was one-quarter of the base-case scenario with 10-year implementation/maintenance costs of $1 million, there was 47.7% chance that adoption of 4D-DOSS would be cost-effective. The value of information analysis showed that uncertainty in MRSA costs made the greatest contribution to model uncertainty.

CONCLUSIONS

This early-stage modelling study revealed the circumstances for which 4D-DOSS is likely to be cost-effective at the current willingness-to-pay threshold, and identified the parameters for which further research will be worthwhile to reduce model uncertainty. Inclusion of other drug-resistant organisms will provide a more thorough assessment of the cost-effectiveness of 4D-DOSS.

Curriculum-based Faculty Training in Networking: Knowledge and Self-efficacy Outcomes

Although the advantages of developmental networks are well-known, most faculty do not know how to participate in such networks actively. Additionally, institutions face challenges in teaching faculty the best practices of networking. This deficiency constitutes a critical gap in the literature, which may slow career advancement for faculty, particularly from underrepresented groups. The study's purpose was to examine the effectiveness of a curriculum-based faculty training in developmental networks, utilizing the Extension for Community Health Outcomes (ECHO) platform. In this pre-post study, 33 faculty members participated in the intervention utilizing eight modules involving four competencies. Each module followed a standard format, including a short didactic, two facilitated case study discussions based on real-life scenarios, and self-reading of selected literature. Outcomes included (i) change in knowledge scores obtained from two questions per module and (ii) self-efficacy scores measured on a scale of 0-100. Paired student's t-test and mixed model regression analyses were used. A significant increase in knowledge score was documented using mixed model regression for 4 of the eight modules (mean change score 0.4-0.8, p≤0.03 for all analyses). The proportion of faculty participants reporting correct knowledge items for all modules increased from 49.8% (pre) to 64.3% (post), which was statistically significant (p<0.001). Significant increases in paired self-efficacy scores were reported for each of the eight modules (mean change score 17-37, p<0.05 for all analyses). This study highlights the importance of curriculum-based training in networking. Participants showed a significant increase in pre-post networking self-efficacy and knowledge scores. Our ECHO-based curriculum, facilitator training, and manual enable easy implementation in other institutions, ensuring scalability and adaptability. Our analysis provides the evidence basis for examining the impact of a developmental network intervention in enhancing individual career networks.

Inhibition of EphA3 Expression in Tumour Stromal Cells Suppresses Tumour Growth and Progression

Tumour progression relies on interactions with untransformed cells in the tumour microenvironment (TME), including cancer-associated fibroblasts (CAFs), which promote blood supply, tumour progression, and immune evasion. Eph receptor tyrosine kinases are cell guidance receptors that are most active during development but re-emerge in cancer and are recognised drug targets. EphA3 is overexpressed in a wide range of tumour types, and we previously found expression particularly in stromal and vascular tissues of the TME. To investigate its role in the TME, we generated transgenic mice with inducible shRNA-mediated knockdown of EphA3 expression. EphA3 knockdown was confirmed in aortic mesenchymal stem cells (MSCs), which displayed reduced angiogenic capacity. In mice with syngeneic lung tumours, EphA3 knockdown reduced vasculature and CAF/MSC-like cells in tumours, and inhibited tumour growth, which was confirmed also in a melanoma model. Single cell RNA sequencing analysis of multiple human tumour types confirmed EphA3 expression in CAFs, including in breast cancer, where EphA3 was particularly prominent in perivascular- and myofibroblast-like CAFs. Our results thus indicate expression of the cell guidance receptor EphA3 in distinct CAF subpopulations is important in supporting tumour angiogenesis and tumour growth, highlighting its potential as a therapeutic target.

Coordination of floral and fiber development in cotton (Gossypium) by hormone- and flavonoid-signalling associated regulatory miRNAs

Various plant development activities and stress responses are tightly regulated by various microRNAs (miRNA) and their target genes, or transcription factors in a spatiotemporal manner. Here, to exemplify how flowering-associated regulatory miRNAs synchronize their expression dynamics during floral and fiber development in cotton, constitutive expression diminution transgenic lines of auxin-signaling regulatory Gh-miR167 (35S-MIM167) were developed through target mimicry approach. 'Moderate' (58% to 80%)- and 'high' (> 80%)-Gh-miR167 diminution mimic lines showed dosage-dependent developmental deformities in anther development, pollen maturation, and fruit (= boll) formation. Cross pollination of 'moderate' 35S-MIM167 mimic lines with wild type (WT) plant partially restored boll formation and emergence of fiber initials on the ovule surface. Gh-miR167 diminution favored organ-specific transcription biases in miR159, miR166 as well as miR160, miR164, and miR172 along with their target genes during anther and petal development, respectively. Similarly, accumulative effect of percent Gh-miR167 diminution, cross regulation of its target ARF6/8 genes, and temporal mis-expression of hormone signaling- and flavonoid biosynthesis-associated regulatory miRNAs at early fiber initiation stage caused irregular fiber formation. Spatial and temporal transcription proportions of regulatory miRNAs were also found crucial for the execution of hormone- and flavonoid-dependent progression of floral and fiber development. These observations discover how assorted regulatory genetic circuits get organized in response to Gh-miR167 diminution and converge upon ensuing episodes of floral and fiber development in cotton.

Production and characterization of sustainable vermimanure derived from poultry litter and rice straw using tiger worm Eisenia fetida

Poultry litter (PL) and rice straw (RS), commonly available waste materials, pose severe threat to environment, if not properly managed. As viable waste treatment method, vermi-transformation of PL into enriched vermimanure was done using RS and cow dung (CD) with different feedstocks (FS) combinations like FS0_{(CD without earthworm),} FS1_(CD), FS2_{(1CD: 1RS)}, FS3_{(1CD: 1PL)} and FS4_{(1CD: 1RS: 1PL)} for 110 days. Increased growth performance (P < 0.05) of Eisenia fetida, macronutrient levels, and a consistently lower carbon-to-nitrogen ratio (C/N) emphasize the importance of RS and PL in the vermimanuring process. Several analytical techniques have revealed the presence of functional groups, nitrate (NO₃^-), phosphate (PO₄^3-), and potassium ions (K⁺) as well as the high porosity of the matured vermimanures. Therefore, using earthworms, the feedstock FS4_{(1CD: 1RS: 1PL)} could be successfully biotransformed into sustainable manure lowering the usage of chemical fertilizers and rice straw burning.

Performance analysis of U-Net with hybrid loss for foreground detection

With the latest developments in deep neural networks, the convolutional neural network (CNN) has made considerable progress in the area of foreground detection. However, the top-rank background subtraction algorithms for foreground detection still have many shortcomings. It is challenging to extract the true foreground against complex background. To tackle the bottleneck, we propose a hybrid loss-assisted U-Net framework for foreground detection. A proposed deep learning model integrates transfer learning and hybrid loss for better feature representation and faster model convergence. The core idea is to incorporate reference background image and change detection mask in the learning network. Furthermore, we empirically investigate the potential of hybrid loss over single loss function. The advantages of two significant loss functions are combined to tackle the class imbalance problem in foreground detection. The proposed technique demonstrates its effectiveness on standard datasets and performs better than the top-rank methods in challenging environment. Moreover, experiments on unseen videos also confirm the efficacy of proposed method.

Physical Therapy Interventions of an Electrical Burn Injury-Afflicted Patient: A Case Report

Electrical injuries are uncommon but not completely rare. It is most prevalent in the male population, although females are also affected in the workplace or household-related activities. These injuries usually occur in situations where proper precautions are not taken by the individual and also appropriate safety drills and education for personnel are not carried out. Electrical burns affecting children are very rare, but when they do occur, it is usually due to accidental contact with exposed electrical sources. In this patient, there were severe levels of secondary complications following the burn injury. The patient developed blood infections and also was hampered in doing a variety of activities of daily living. The patient was diagnosed with 45%-50% body surface area (BSA) covered with burns, which suggests its severe nature. Treatment focuses on preventing wound infection, managing the excruciating amount of pain, preventing complications of immobility, promoting mobility as much as the patient can, and also educating the patient and the family members.

Healthcare use by children in North West London 2015-2019 by deprivation and integrated care access

Background

England has a health system offering universal coverage, but disparities in healthcare use are increasing. Between 2007-2017, children living in more deprived areas had higher rates of unplanned care (Emergency Department (ED) attendance and hospital admissions), whereas children from less deprived areas had higher rates of planned care (General Practitioner (GP) contact and outpatient appointments). More detailed research to find solutions for this divergent pattern is required.

Aim

To assess the rates of GP contact, outpatient appointments, hospital admissions and ED attendance in North West London, by Index of Multiple Deprivation (IMD) decile of home postcode and access to an integrated care service providing linked care between multiple child health professionals ‘Connecting Care for Children (CC4C)', for children aged 0-18 years between 2015-2019.

Methods

Retrospective analysis of a de-identified database of integrated care records for 495,357 children.

Results

Children from the most deprived decile had higher rates of emergency admissions (0.070 per child per year vs. overall mean 0.040), elective admissions (0.076 vs. 0.032), ED attendances (0.754 vs. 0.358) and outpatient appointments (1.702 vs. 0.756) between 01.01.2015- 31.12.2019. Children from the least deprived decile had the second highest rates of outpatient appointments (0.911 vs. 0.756) and GP contact (8.192 vs. 5.390) between 01.01.2015- 31.12.2019. Children with access to the CC4C service, despite being from more deprived backgrounds, had lower rates of emergency admissions (0.028 vs. 0.037) compared to patients with access to usual care. P values &lt;0.001 in all cases.

Conclusions

Greater deprivation was linked to higher rates of emergency admissions, but this was partially mitigated by access to more integrated healthcare models. Children from the least deprived decile continued to have disproportionately higher use of planned care.

Key messages

• Despite universal health coverage, children from more deprived areas continue to have disproportionately higher use of unplanned care.

• Further research is required to explore whether integrated care solutions can reduce the burden on unplanned health services and inequalities in access to care.

A systematic survey of advances in retinal imaging modalities for Alzheimer's disease diagnosis

Recent advances in retinal imaging pathophysiology have shown a new function for biomarkers in Alzheimer's disease diagnosis and prognosis. The significant improvements in Optical coherence tomography (OCT) retinal imaging have led to significant clinical translation, particularly in Alzheimer's disease detection. This systematic review will provide a comprehensive overview of retinal imaging in clinical applications, with a special focus on biomarker analysis for use in Alzheimer's disease detection. Articles on OCT retinal imaging in Alzheimer's disease diagnosis were identified in PubMed, Google Scholar, IEEE Xplore, and Research Gate databases until March 2021. Those studies using simultaneous retinal imaging acquisition were chosen, while those using sequential techniques were rejected. "Alzheimer's disease" and "Dementia" were searched alone and in combination with "OCT" and "retinal imaging". Approximately 1000 publications were searched, and after deleting duplicate articles, 145 relevant studies focused on the diagnosis of Alzheimer's disease utilizing retinal imaging were chosen for study. OCT has recently been demonstrated to be a valuable technique in clinical practice as according to this survey, 57% of the researchers employed optical coherence tomography, 19% used ocular fundus imaging, 13% used scanning laser ophthalmoscopy, and 11% have used multimodal imaging to diagnose Alzheimer disease. Retinal imaging has become an important diagnostic technique for Alzheimer's disease. Given the scarcity of available literature, it is clear that future prospective trials involving larger and more homogeneous groups are necessary, and the work can be expanded by evaluating its significance utilizing a machine-learning platform rather than simply using statistical methodologies.

Osteoporosis diagnosis in knee X-rays by transfer learning based on convolution neural network

Osteoporosis degrades the quality of bones and is the primary cause of fractures in the elderly and women after menopause. The high diagnostic and treatment costs urge the researchers to find a cost-effective diagnostic system to diagnose osteoporosis in the early stages. X-ray imaging is the cheapest and most common imaging technique to detect bone pathologies butmanual interpretation of x-rays for osteoporosis is difficult and extraction of required features and selection of high-performance classifiers is a very challenging task. Deep learning systems have gained the popularity in image analysis field over the last few decades. This paper proposes a convolution neural network (CNN) based approach to detect osteoporosis from x-rays. In our study, we have used the transfer learning of deep learning-based CNNs namely AlexNet, VggNet-16, ResNet, and VggNet -19 to classify the x-ray images of knee joints into normal, osteopenia, and osteoporosis disease groups. The main objectives of the current study are: (i) to present a dataset of 381 knee x-rays medically validated by the T-scores obtained from the Quantitative Ultrasound System, and (ii) to propose a deep learning approach using transfer learning to classify different stages of the disease. The performance of these classifiers is compared and the best accuracy of 91.1% is achieved by pretrained Alexnet architecture on the presented dataset with an error rate of 0.09 and validation loss of 0.54 as compared to the accuracy of 79%, an error rate of 0.21, and validation loss of 0.544 when pretrained network was not used.. The results of the study suggest that a deep learning system with transfer learning can help clinicians to detect osteoporosis in its early stages hence reducing the risk of fractures.

Implication and utility of DAS-28 squeeze in rheumatoid arthritis: an Indian experience

The purpose of this study was to compare and correlate disease activity score including 28 joints counts (DAS-28) Squeeze with DAS-28 and clinical disease activity index (CDAI) to assess disease activity (DA) in rheumatoid arthritis (RA) patients. A total of 100 RA patients were included in the study. All subjects were evaluated for disease activity using the DAS-28 Squeeze, DAS-28, and CDAI. Spearman’s rho (ρ) was calculated to determine the correlation between DAS-28 Squeeze, DAS-28, and CDAI. Cross-tabulation was performed to compare and calculate the kappa coefficient for the link between two indices. For each scale, Cronbach’s alpha was also calculated to test dependability. The average age of the study group was 43.9±11.3. The mean scores on the DAS-28 Squeeze, DAS-28, and CDAI were, respectively, 3.58±1.06, 5.06±1.56, and 22.81±14.92. p=0.001 indicated a significant correlation between DAS-28 Squeeze and DAS-28 (ρ=0.986) and CDAI (ρ=0.939) for DAS-28 Squeeze. There was a considerable correlation between all three measures at various DA levels. Cronbach’s alpha for DAS-28 Squeeze, DAS-28, and CDAI were respectively 0.716, 0.663, and 0.734. DAS-28 Squeeze exhibited a substantial positive association with DAS-28 and CDAI for assessing disease activity and appears to be a more useful and reliable method than DAS-28 and CDAI for monitoring disease activity in RA patients.

Artificial intelligence uncovers carcinogenic human metabolites

The genome of a eukaryotic cell is often vulnerable to both intrinsic and extrinsic threats owing to its constant exposure to a myriad of heterogeneous compounds. Despite the availability of innate DNA damage responses, some genomic lesions trigger malignant transformation of cells. Accurate prediction of carcinogens is an ever-challenging task owing to the limited information about bona fide (non-)carcinogens. We developed Metabokiller, an ensemble classifier that accurately recognizes carcinogens by quantitatively assessing their electrophilicity, their potential to induce proliferation, oxidative stress, genomic instability, epigenome alterations, and anti-apoptotic response. Concomitant with the carcinogenicity prediction, Metabokiller is fully interpretable and outperforms existing best-practice methods for carcinogenicity prediction. Metabokiller unraveled potential carcinogenic human metabolites. To cross-validate Metabokiller predictions, we performed multiple functional assays using Saccharomyces cerevisiae and human cells with two Metabokiller-flagged human metabolites, namely 4-nitrocatechol and 3,4-dihydroxyphenylacetic acid, and observed high synergy between Metabokiller predictions and experimental validations.

deepGraphh: AI-driven web service for graph-based quantitative structure-activity relationship analysis

Artificial intelligence (AI)-based computational techniques allow rapid exploration of the chemical space. However, representation of the compounds into computational-compatible and detailed features is one of the crucial steps for quantitative structure-activity relationship (QSAR) analysis. Recently, graph-based methods are emerging as a powerful alternative to chemistry-restricted fingerprints or descriptors for modeling. Although graph-based modeling offers multiple advantages, its implementation demands in-depth domain knowledge and programming skills. Here we introduce deepGraphh, an end-to-end web service featuring a conglomerate of established graph-based methods for model generation for classification or regression tasks. The graphical user interface of deepGraphh supports highly configurable parameter support for model parameter tuning, model generation, cross-validation and testing of the user-supplied query molecules. deepGraphh supports four widely adopted methods for QSAR analysis, namely, graph convolution network, graph attention network, directed acyclic graph and Attentive FP. Comparative analysis revealed that deepGraphh supported methods are comparable to the descriptors-based machine learning techniques. Finally, we used deepGraphh models to predict the blood-brain barrier permeability of human and microbiome-generated metabolites. In summary, deepGraphh offers a one-stop web service for graph-based methods for chemoinformatics.

Breakdown of Spin-to-Helicity Locking at the Nanoscale in Topological Photonic Crystal Edge States

We measure the local near-field spin in topological edge state waveguides that emulate the quantum spin Hall effect. We reveal a highly structured spin density distribution that is not linked to a unique pseudospin value. From experimental near-field real-space maps and numerical calculations, we confirm that this local structure is essential in understanding the properties of optical edge states and light-matter interactions. The global spin is reduced by a factor of 30 in the near field and, for certain frequencies, flipped compared to the pseudospin measured in the far field. We experimentally reveal the influence of higher-order Bloch harmonics in spin inhomogeneity, leading to a breakdown in the coupling between local helicity and global spin.

INFLUENCE OF THE DURATION OF DIABETES AND VIBRATION PERCEPTION THRESHOLD ON THE SEVERITY OF ERECTILE DYSFUNCTION IN PATIENTS WITH TYPE 2 DIABETES MELLITUS

BACKGROUND

Erectile dysfunction(ED) in men is a frequent under-reported complication of diabetes mellitus, which is becoming significant health problem worldwide.

AIMS

The study aims to determine the prevalence and risk factors for development of ED in North Indian patients with type 2 diabetes mellitus.

METHODS

We used international index of erectile function (IIEF-5) for the assessment of ED in 796 patients with type 2 diabetes mellitus. We recorded the age, duration of diabetes, glycemic status, body mass index, diabetes medications, microvascular and macrovascular complications.

RESULTS

The mean age of patients in the study was 49.38 ± 9.52 years. The prevalence of ED in patients with type 2 diabetes mellitus was 79.4%. Logistic regression analysis revealed that age, body mass index, glycemic control, insulin therapy, retinopathy and nephropathy was not significantly associated with erectile dysfunction in patients with type 2 diabetes mellitus. Duration of diabetes (OR = 1.054, 95% CI 1.007 to 1.102, P=0.023) and vibration perception threshold (OR = 1.071, 95% CI 1.042 to 1.102, P=0.000) were identified as key risk factors for development of ED.

CONCLUSION

Duration of diabetes and peripheral neuropathy emerged as significant risk factors for development of severe erectile dysfunction.

Airway Complications After Lung Transplant for Post Coronaviral Disease (COVID-19) Acute Respiratory Distress Syndrome (ARDS) Related End Stage Lung Disease: Single Centre Experience

Purpose

Severe COVID-19 ARDS related end stage lung fibrosis with irreversible changes is a newer indication for lung transplantation with acceptable survival rate. Airway complication post lung transplant is a major source of morbidity and mortality with incidence as high as 25 to 49 percent. Patients with end stage COVID-19 fibrosis are likely to be clinically deconditioned with long duration of extracorporeal oxygenator (ECMO) support, high burden of sepsis and prolonged respiratory support which may affect the airways post lung transplantation.

Methods

This is a retrospective observational study after obtaining institutional ethical clearance. We reviewed electronic medical data of patients who underwent lung transplantation for post COVID-19 ARDS related fibrosis. We evaluated the incidence and type of airway complications and the various therapeutic interventions applied for its management.

Results

Between May 2020 and September 2021 our centre performed 23 bilateral lung transplants for end stage COVID-19 ARDS related fibrosis. 22 patients were on ECMO support with mean duration of 50.9 days before transplantation. All patients underwent lung transplantation with central Veno-Arterial ECMO support with mean organ ischaemia time of 360±154 minutes. The incidence of airway complication in our study group was 56%. We observed anastomotic narrowing in 3(13%), distal airway narrowing in 4(17%) and sloughing/coating of anastomotic site in 5(22%) patients. Nonspecific inflammatory polypi around the bronchial anastomotic site were noticed in 4(17%) and mild airway anastomotic dehiscence in 2 subjects. 8(34%) patients required serial bronchoscopy and balloon dilatation; 2 among them mandated additional cautery usage. 2 cases underwent polypectomy, further 4 subjects needed bronchial stent placement. 5 (21%) recipients were discharged with Tracheostomy while rest were successfully decannulated in the ward.

Conclusion

We observed a high incidence of airway complications in post lung transplant for COVID-19 ARDS related fibrosis. Early detection, timely management and serial follow up is of paramount importance in this subset of patients.

Effect of virtual reality and haptic feedback on upper extremity function and functional independence in children with hemiplegic cerebral palsy: a research protocol

Hemiplegic cerebral palsy (CP) is a subcategory of CP which is characterized by sensory motor deficits primarily on one side of the body that adversely affects functionality. Virtual reality (VR) systems have been advanced in the recent past for the use in rehabilitation of patients with neurological conditions. Virtual reality has an inherent motivational component that provides the much-needed compliance for active participation by children. The rationale of the proposed study is to investigate the effect of VR and haptic feedback for improvement of upper extremity function of children with hemiplegic cerebral palsy. This comparative experimental study will be recruiting 36 children with hemiplegic CP and will be treating them by VR and haptic feedback along with conventional physiotherapy in group A and by conventional physiotherapy only in group B. The children will undergo the treatment for six weeks (five days/week) with each session extending for 60 minutes/day. The primary outcome measures including `nine-hole peg test´ (9HPT) and `box and block test´ (BBT) will assess the manual dexterity and secondary outcome measures including `ABILHAND-kids´ and `WeeFIM (self-care)´ will assess the functional independence that are hypothesized to be gained by haptic enhanced VR intervention when combined with the conventional therapy.

A comparative simulation of normalization methods for machine learning-based intrusion detection systems using KDD Cup’99 dataset

Network Intrusion detection systems (NIDS) detect malicious and intrusive information in computer networks. Presently, commercial NIDS is based on machine learning approaches that have complex algorithms and increase intrusion detection efficiency and efficacy. These machine learning-based NIDS use high dimensional network traffic data from which intrusive information is to be detected. This high-dimensional network traffic data in NIDS needs to be preprocessed and normalized to make it suitable for machine learning tools. A machine learning approach with appropriate normalization and prepossessing increases NIDS performance. This paper presents an empirical study on various normalization methods implemented on a benchmark network traffic dataset, KDD Cup’99, that has been used to evaluate the NIDS model. The present study shows decimal normalization has a better prediction performance than non-normalized traffic data categorized into ‘normal’ or ‘intrusive’ classes.

Assessment of prescribing pattern of drugs and completeness of prescriptions as per the World Health Organization prescribing indicators in various Indian tertiary care centers: A multicentric study by Rational Use of Medicines Centers-Indian Council of Medical Research network under National Virtual Centre Clinical Pharmacology activity

OBJECTIVE

The rational use of medicines as per the World Health Organization (WHO) should be practiced globally. However, data regarding the completeness of the prescriptions and their rational use is lacking from developing countries like India. Thus, the aim of this study was to assess the prescribing patterns of drugs and completeness of prescriptions as per WHO core drug use and complementary indicators to provide real-life examples for the Indian Council of Medical Research (ICMR) online prescribing skill course for medical graduates.

METHODS

Prescriptions of the patients, fulfilling inclusion criteria, attending Outpatient Departments of various specialties of tertiary care hospitals, were collected by thirteen ICMR Rational use of medicines centers located in tertiary care hospitals, throughout India. Prescriptions were evaluated for rational use of medicines according to the WHO guidelines and for appropriateness as per standard treatment guidelines using a common protocol approved by local Ethics committees.

RESULTS

Among 4838 prescriptions, an average of about three drugs (3.34) was prescribed to the patients per prescription. Polypharmacy was noted in 83.05% of prescriptions. Generic drugs were prescribed in 47.58% of the prescriptions. Further, antimicrobials were prescribed in 17.63% of the prescriptions and only 4.98% of prescriptions were with injectables. During the prescription evaluation, 38.65% of the prescriptions were incomplete due to multiple omissions such as dose, duration, and formulation.

CONCLUSION

Most of the parameters in the present study were out of the range of WHO-recommended prescribing indicators. Therefore, effective intervention program, like training, for the promotion of rational drug use practice was recommended to improve the prescribing pattern of drugs and the quality of prescriptions all over the country.

Fibrosis assessment in patients with nonalcoholic fatty liver disease: Adherence to proposed algorithms and barriers to complying with them

INTRODUCTION AND AIMS

Fibrosis staging in patients with nonalcoholic fatty liver disease (NAFLD) is carried out through the application of stepwise algorithms but there is little real-world data on their use. Our aim was to calculate the number of patients with NAFLD and indeterminate or high risk for fibrosis, assessed through noninvasive scores, that consequently underwent further staging evaluation.

MATERIALS AND METHODS

A cross-sectional multicenter cohort study was conducted on patients with NAFLD evaluated by hepatologists within the time frame of June 1 and July 31, 2018. The FIB-4 and NAFLD fibrosis scores were calculated in all the patients, and if at least one of the scores suggested indeterminate or high risk for fibrosis, we believed the patient should have undergone additional fibrosis staging assessment.

RESULTS

The study included 238 patients. The median time interval from NAFLD diagnosis and inclusion in the analysis was 12.2 months (IQR 3.0-36.5). A total of 128 (54%) patients had at least one noninvasive score that suggested indeterminate or high risk for fibrosis but studies to confirm the fibrosis grade (elastography, biopsy, etc.) were performed on only 72 (56%). The main barriers encountered by the physicians for applying the staging algorithms were related to health insurance coverage and imaging study costs.

CONCLUSIONS

A high percentage of patients with NAFLD were at indeterminate or high risk for fibrosis, according to noninvasive scores, but additional studies were carried out on only half of them, showing low adherence to current recommendations.

Expanding Indications of Primary Arthrodesis in Selected Individuals for Managing Complex Hindfoot Trauma During COVID-19 Pandemic

BACKGROUND

During the COVID-19 pandemic, public health measures to encourage social distancing have been implemented, including cancellation of outdoor activities, organized sports, and schools/colleges. Neglected hindfoot fractures have emerged as a consequence with increased frequency. Similarly, complex ankle and pilon fractures that require staged management, prolonged hospital stay, and soft-tissue care have emerged as a potential concern as prolonged exposure to healthcare setting adds to risk of acquiring as well as transmitting COVID-19 infection. The authors present their experience with expanding these indications for hindfoot arthrodesis as they encounter a greater number of neglected ankle and hindfoot trauma.

METHODS

This was a retrospective observational study of collected data from the trauma unit of our hospital. Inclusion criteria included all trauma classified by the AO/OTA as occurring at locations 43, and who underwent subtalar and ankle arthrodesis. This included distal tibia, malleolar, talus, and calcaneus fractures. These patients were followed up to at least 6 months till complete fracture union.

RESULTS

A total of 18 patients underwent arthrodesis of either the ankle or subtalar joint between March and October 2020. Mean age of patients undergoing arthrodesis of the hindfoot was 69.2 years (43-84 years). Indications for the procedure included Displaced and comminuted intra-articular distal tibia fractures in elderly (6 patients), Malunited ankle fractures (2 patients), Neglected Ankle fractures managed conservatively (3 patients), Calcaneus fractures (5 patients), and neglected Talus body fracture (2 patients). All patients were followed up to at least 6 months and everyone went onto successful painless union between 3 and 6 months of the arthrodesis procedure without any significant complications.

CONCLUSION

In summary, COVID-19 pandemic has led to a change in paradigm of trauma management and foot and ankle management is no different than other musculoskeletal trauma systems. The authors propose an expansion of indications for hindfoot arthrodesis in managing complex hindfoot trauma in pandemic situation.

Prognostic significance of polyvascular disease in patients admitted with acute decompensated heart failure: the ARIC Study Community Surveillance

Introduction

The prevalence and outcomes of polyvascular disease (PVD) in patients admitted with acute decompensated heart failure (ADHF) have not been previously reported, nor is it known whether associations differ for heart failure (HF) with reduced vs. preserved ejection fraction (HFrEF vs HFpEF, respectively).

Purpose

To investigate the relationship between atherosclerotic involvement of multiple arterial territories and mortality in patients hospitalized with ADHF.

Methods

The Atherosclerosis Risk in Communities (ARIC) study conducted hospital surveillance of adjudicated heart failure in 4 US areas from 2005–2014, with events verified by physician review. Medical histories were abstracted from the hospital record. PVD was defined by coexisting disease in ≥2 arterial beds, identified by prevalent coronary artery disease, peripheral arterial disease, and cerebrovascular disease. Mortality hazards of PVD vs. no PVD were analyzed separately for HFpEF and HFrEF, with adjustment for age, race, sex, year of admission and geographic region. All analyses were weighted by the inverse of the sampling probability.

Results

Of 24,936 ADHF hospitalizations (52% female, 32% Black, mean age 75 years), 19% had PVD (22% among HFrEF hospitalizations, 17% among HFpEF hospitalizations), Figure 1. There was an increasing trend in 1-year mortality with 0, 1 and ≥2 arterial bed involvement, both for patients with HFrEF (29% to 32% to 38%; P-trend=0.0006) and HFpEF (26% to 32% to 37%; P-trend &lt;0.0001). After adjustments, PVD was associated with a 20% higher hazard of 1-year mortality in patients with HFrEF (HR=1.23; 95% CI: 1.06–1.44) and a 30% higher hazard in patients with HFpEF (HR=1.33; 95% CI: 1.09–1.63), with no significant interaction by HF type (P-interaction = 0.5).

Conclusion

Patients hospitalized with ADHF and coexisting PVD have an increased risk of death, irrespective of HF type. Clinical attention should be directed toward PVD, with secondary prevention strategies enacted to improve the prognosis of this vulnerable population.

Funding Acknowledgement

Type of funding sources: Public Institution(s). Main funding source(s): National Institutes of Health Distributions of arterial diseaseTrends in 1-year mortality outcomes

The morphological and morphometric analysis of the variant patterns of the tricipital aponeurosis: a new anatomical classification with possible clinical implications

BACKGROUND

Tricipital aponeurosis (TA) has gained attraction as a constant and reliable landmark to identify the location of radial nerve in the setting of fracture distal humeri. The aponeurosis itself shows variant anatomical patterns. In this study, we intend to provide a comprehensive description and functional classification of observed anatomical variations with possible clinical implications.

MATERIALS AND METHODS

Sixty arms belonging to 30 adult cadavers were studied. TA was examined grossly to document variations in its shape and classified accordingly. Subsequently, length and breadth of TA were measured. The distance of the radial nerve (RN) from the point of confluence and from the lateral border of TA was also measured (tricepso-radial distance [TRD]). These distances were correlated with the different patterns of TA obtained.

RESULTS

Based on the shape of the proximal apex of TA or point of confluence and frequency of their occurrence, we propose a new classification of 4 patterns for the TA anatomy. Pattern I: classically seen as the triangular proximal apex (76.67%); pattern II: tongue shaped or blunt proximal apex (18.33%); pattern III: bifurcated or dual proximal apex (3.33%); pattern IV: as the absence of TA (1.67%). The mean of length and breadth of TA was 16.58 ± 2.05 cm and 3.61 ± 0.61 cm, respectively. The mean distance of RN from point of confluence and lateral border of TA was 3.57 ± 0.19 cm and 2.04 ± 0.56 cm, respectively. The length, breadth of TA and TRD differs amongst the different patterns of TA.

CONCLUSIONS

Anatomical variations in the shape and size of TA are frequently encountered. The proposed, hitherto undescribed, classification may make operating surgeon aware of these morphological variations and help prevent iatrogenic injury to RN. Such classification is simple and unique; however, its success relies upon universal acceptance.

Global expression dynamics and miRNA evolution profile govern floral/fiber architecture in the modern cotton (Gossypium)

Majority of differentially expressed miRNAs with functional attributes have been recruited independently and parallelly during allopolyploidy followed by the millennia of human selection of both domesticated G. hirsutum and G. barbadense. The genus Gossypium is a marvelous evolutionary model for studying allopolyploidy and morpho-evolution of long-spinnable fibers from the ancestral wild-fuzz. Many genes, transcription factors, and notably, the regulatory miRNAs essentially govern such remarkable modern fiber phenotypes. To comprehend the impact of allopolyploidy on the evolutionary selection of transcriptional dynamicity of key miRNAs, comparative transcriptome profiling of vegetative and fiber tissues of domesticated diploid G. arboreum (A₂) and allopolyploid cotton species G. hirsutum (AD₁), and G. barbadense (AD₂) identified > 300 differentially expressed miRNAs (DEmiRs) within or between corresponding tissues of A₂, AD₁ and AD₂ species. Up to 49% and 32% DEmiRs were up- and down-regulated at fiber initiation stage of AD₁ and AD₂ species, respectively, whereas 50% and 18% DEmiRs were up- and down-regulated at fiber elongation stage of both the allopolyploid species. Interestingly, A-subgenome-specific DEmiRs exhibit expression dominance in the allopolyploid genetic backgrounds. Comparative spatio-temporal expression analyses of AD₁ and AD₂ species discovered that a majority of DEmiRs were recruited independently under millennia of human selection during domestication. Functional annotations of these DEmiRs revealed selection of associated molecular functions such as hormone-signaling, calcium-signaling and reactive oxygen species (ROS) signaling during fiber initiation and elongation. To validate the functional attributes of annotated DEmiRs, we demonstrated for the first time that the target-mimicry-based constitutive diminution of auxin-signaling associated miR167 directly affected the differentiation of floral and fiber tissues of transgenic cotton. These results strongly suggested that the evolutionarily favored DEmiRs including miR167 were involved in the transcriptional regulation of numerous genes during cotton evolution for enhanced fiber-associated agronomic traits.