Debiasing Multimodal Models via Causal Information Minimization

Most existing debiasing methods for multimodal models, including causal intervention and inference methods, utilize approximate heuristics to represent the biases, such as shallow features from early stages of training or unimodal features for multimodal tasks like VQA, etc., which may not be accurate. In this paper, we study bias arising from confounders in a causal graph for multimodal data and examine a novel approach that leverages causally-motivated information minimization to learn the confounder representations. Robust predictive features contain diverse information that helps a model generalize to out-of-distribution data. Hence, minimizing the information content of features obtained from a pretrained biased model helps learn the simplest predictive features that capture the underlying data distribution. We treat these features as confounder representations and use them via methods motivated by causal theory to remove bias from models. We find that the learned confounder representations indeed capture dataset biases, and the proposed debiasing methods improve out-of-distribution (OOD) performance on multiple multimodal datasets without sacrificing in-distribution performance. Additionally, we introduce a novel metric to quantify the sufficiency of spurious features in models' predictions that further demonstrates the effectiveness of our proposed methods. Our code is available at: https://github.com/Vaidehi99/CausalInfoMinComment: EMNLP 2023 Findings (16 pages

Identifying molecular and functional similarities and differences between human primary cardiac valve interstitial cells and ventricular fibroblasts

Introduction: Fibroblasts are mesenchymal cells that predominantly produce and maintain the extracellular matrix (ECM) and are critical mediators of injury response. In the heart, valve interstitial cells (VICs) are a population of fibroblasts responsible for maintaining the structure and function of heart valves. These cells are regionally distinct from myocardial fibroblasts, including left ventricular cardiac fibroblasts (LVCFBs), which are located in the myocardium in close vicinity to cardiomyocytes. Here, we hypothesize these subpopulations of fibroblasts are transcriptionally and functionally distinct.Methods: To compare these fibroblast subtypes, we collected patient-matched samples of human primary VICs and LVCFBs and performed bulk RNA sequencing, extracellular matrix profiling, and functional contraction and calcification assays.Results: Here, we identified combined expression of SUSD2 on a protein-level, and MEOX2, EBF2 and RHOU at a transcript-level to be differentially expressed in VICs compared to LVCFBs and demonstrated that expression of these genes can be used to distinguish between the two subpopulations. We found both VICs and LVCFBs expressed similar activation and contraction potential in vitro, but VICs showed an increase in ALP activity when activated and higher expression in matricellular proteins, including cartilage oligomeric protein and alpha 2-Heremans-Schmid glycoprotein, both of which are reported to be linked to calcification, compared to LVCFBs.Conclusion: These comparative transcriptomic, proteomic, and functional studies shed novel insight into the similarities and differences between valve interstitial cells and left ventricular cardiac fibroblasts and will aid in understanding region-specific cardiac pathologies, distinguishing between primary subpopulations of fibroblasts, and generating region-specific stem-cell derived cardiac fibroblasts

Engineered Collagen Matrices

Collagen is the most abundant protein in mammals, accounting for approximately one-third of the total protein in the human body. Thus, it is a logical choice for the creation of biomimetic environments, and there is a long history of using collagen matrices for various tissue engineering applications. However, from a biomaterial perspective, the use of collagen-only scaffolds is associated with many challenges. Namely, the mechanical properties of collagen matrices can be difficult to tune across a wide range of values, and collagen itself is not highly amenable to direct chemical modification without affecting its architecture or bioactivity. Thus, many approaches have been pursued to design scaffold environments that display critical features of collagen but enable improved tunability of physical and biological characteristics. This paper provides a brief overview of approaches that have been employed to create such engineered collagen matrices. Specifically, these approaches include blending of collagen with other natural or synthetic polymers, chemical modifications of denatured collagen, de novo creation of collagen-mimetic chains, and reductionist methods to incorporate collagen moieties into other materials. These advancements in the creation of tunable, engineered collagen matrices will continue to enable the interrogation of novel and increasingly complex biological questions

A Case Study of Scalp Psoriasis managed with Ayurvedic principles

Psoriasis is a persistent, visible skin disorder that has a significant impact on a person's physical and psychological well-being. It is one of the most pressing concerns of social significance. Skin disorders are widespread as a result of a changed lifestyle, lack of physical activity, unsanitary habits, mental stress, and overeating. It is tough to treat because of its high recurrence; it is an auto-immune, non-contagious condition that is extremely difficult to cure, according to modern medicine. According to Ayurveda, all skin disorders are grouped together under the term 'Kushtha'. Despite the fact that the heading is the same for all skin disorders, there is further division and naming of skin diseases based on the doshas involved, which play an important part in determining the disease's treatment path. Scalp psoriasis is clinically similar to Eka Kushtha, which is referenced in the Samhitas. A case study of Scalp Psoriasis managed with Ayurvedic principles Shodhana Chikitsa is presented in this paper. In this study, a 25-year-old male patient with scalp psoriasis was treated, who presented with symptoms of dandruff like flaking, silvery white scales, reddish plaque, and severe itching. Ekakushtha (Scalp psoriasis) was diagnosed, and the patient was treated with both external and internal drugs, including Vaman (therapeutic vomiting) and Shamanachikitsa (palliative treatment). During treatment, the patient noticed a significant reduction in symptoms. In this case study, Vaman karma followed by palliative treatment was found to be a more effective treatment choice for Scalp Psoriasis.

Clinicopathological study of acute myeloid leukemia in a tertiary care hospital

Background- The diagnosis of acute myeloid leukemia is based on peripheral blood smear and bone marrow examination. Immunophenotyping characteristics and cytogenetics have clinical relevance besides morphological features in these cases. Present study aims at clinicohematological evaluation of cases of acute myeloid leukemia diagnosed at hematology unit of our tertiary care hospital. Objectives –Present study aimed to diagnose and classify cases of acute myeloid leukemia with clinicohematological correlation. Material and methods- newly diagnosed cases of acute myeloid leukemia within a period of 1 year from May 2020 to May 2021 were included in this cross sectional and prospective study. In addition to hematological work up, flow cytometry, cytogenetics and molecular studies were taken into consideration for clinicohematological evaluation.Result- The study included 14 cases of acute myeloid leukemia which were classified as per FAB classification as AML M1- 7 cases, M3 – 3 cases and M4 and M5 – 2 cases each

Characterization of a Meso-Scale Wearable Robot for Bathing Assistance

Robotic bathing assistance has long been considered an important and practical task in healthcare. Yet, achieving flexible and efficient cleaning tasks on the human body is challenging, since washing the body involves direct human-robot physical contact and simple, safe, and effective devices are needed for bathing and hygiene. In this paper, we present a meso-scale wearable robot that can locomote along the human body to provide bathing and skin care assistance. We evaluated the cleaning performance of the robot system under different scenarios. The experiments on the pipe show that the robot can achieve cleaning percentage over 92% with two types of stretchable fabrics. The robot removed most of the debris with average values of 94% on a human arm and 93% on a manikin torso. The results demonstrate that the robot exhibits high performance in cleaning tasks

Deciphering Microbial Shifts in the Gut and Lung Microbiomes of COVID-19 Patients

COVID-19, caused by SARS-CoV-2, results in respiratory and cardiopulmonary infections. There is an urgent need to understand not just the pathogenic mechanisms of this disease but also its impact on the physiology of different organs and microbiomes. Multiple studies have reported the effects of COVID-19 on the gastrointestinal microbiota, such as promoting dysbiosis (imbalances in the microbiome) following the disease’s progression. Deconstructing the dynamic changes in microbiome composition that are specifically correlated with COVID-19 patients remains a challenge. Motivated by this problem, we implemented a biomarker discovery pipeline to identify candidate microbes specific to COVID-19. This involved a meta-analysis of large-scale COVID-19 metagenomic data to decipher the impact of COVID-19 on the human gut and respiratory microbiomes. Metagenomic studies of the gut and respiratory microbiomes of COVID-19 patients and of microbiomes from other respiratory diseases with symptoms similar to or overlapping with COVID-19 revealed 1169 and 131 differentially abundant microbes in the human gut and respiratory microbiomes, respectively, that uniquely associate with COVID-19. Furthermore, by utilizing machine learning models (LASSO and XGBoost), we demonstrated the power of microbial features in separating COVID-19 samples from metagenomic samples representing other respiratory diseases and controls (healthy individuals), achieving an overall accuracy of over 80%. Overall, our study provides insights into the microbiome shifts occurring in COVID-19 patients, shining a new light on the compositional changes

Clinicopathological Study of Acute Myeloid Leukemia in A Tertiary Care Hospital

Background- The diagnosis of acute myeloid leukemia is based on peripheral blood smear and bone marrow examination. Immunophenotyping characteristics and cytogenetics have clinical relevance besides morphological features in these cases. Present study aims at clinicohematological evaluation of cases of acute myeloid leukemia diagnosed at hematology unit of our tertiary care hospital. Objectives –Present study aimed to diagnose and classify cases of acute myeloid leukemia with clinicohematological correlation. Material and methods- newly diagnosed cases of acute myeloid leukemia within a period of 1 year from May 2020 to May 2021 were included in this cross sectional and prospective study. In addition to hematological work up, flow cytometry, cytogenetics and molecular studies were taken into consideration for clinicohematological evaluation.Result- The study included 14 cases of acute myeloid leukemia which were classified as per FAB classification as AML M1- 7 cases, M3 – 3 cases and M4 and M5 – 2 cases each