Successful outcome of pregnancy in a case of Guillain Barre syndrome-report of a rare case and review of literature

Guillain Barre syndrome (GBS) is a rare autoimmune neurological disorder that has been reported to carry a high maternal risk and maternal mortality risk of >10% if occurred during pregnancy. It is characterized by acute onset of symmetrical ascending paralysis with or without respiratory depression and autonomic dysfunction secondary to gastrointestinal or respiratory infection. This is case report of 30 years old multigravida who presented at 19 weeks period of gestation with sudden onset back pain and bilateral lower limb weakness that progressed to involve bilateral upper limbs with respiratory insufficiency.  Based on clinical presentation and relevant investigations like serum electrolyte, arterial blood gas analysis and nerve conduction studies, provisional diagnosis of GBS was made. In collaboration with the physician, she was managed with ventilator support for 12 days, intravenous immunoglobulin and supportive therapy. This was followed by complete and rapid recovery as she was extubated on 12th day and discharged on day 16. Patient was followed by strict maternal and fetal surveillance. She successfully delivered a healthy boy at 38 weeks of period of gestation by caesarean section done in view of meconium-stained liquor grade 3 in early labour and she was discharged on day 3 of LSCS.

Study of vertical transmission of COVID-19 infection in COVID-19 positive obstetrical patients by comparing amniotic fluid and immediate neonatal COVID-19 RT-PCR

Background: The objective of this study was to estimate the incidence of vertical transmission COVID-19 by RT-PCR.Methods: In this hospital based prospective study, all COVID-19 positive pregnant women admitted in COVID ward in Muzaffarnagar medical college and hospital from April 2020 to January 2021 were included. A detailed history and examination was done and all routine investigations were done as per protocol. Samples were taken from amniotic fluid during vaginal delivery or caesarean section and collected in viral transport medium. Sample were also collected as nasal and oropharyngeal swab from neonate immediately after birth and sent for COVID 19 RT-PCR.Results: Out of total 50 cases; 43 (86%) neonates were delivered via LSCS and 7 (14%) by normal delivery, out of these 41 (82%) neonates were normal; 4 (8%) were IUGR, 2 (4%) were IUD, 2 (4%) were pre-term and 1 (2%) neonatal death. All 50 amniotic fluid as well as nasal and oropharyngeal samples of all neonates were negative by RT-PCR.Conclusions: Low vertical transmission may be due to the fact that antibodies are produced by mother that crosses the placenta and saves the fetus or there are highly specific immunological mediators in the placenta that do not allow the infection to pass to the fetus

DALE: Generative Data Augmentation for Low-Resource Legal NLP

We present DALE, a novel and effective generative Data Augmentation framework for low-resource LEgal NLP. DALE addresses the challenges existing frameworks pose in generating effective data augmentations of legal documents - legal language, with its specialized vocabulary and complex semantics, morphology, and syntax, does not benefit from data augmentations that merely rephrase the source sentence. To address this, DALE, built on an Encoder-Decoder Language Model, is pre-trained on a novel unsupervised text denoising objective based on selective masking - our masking strategy exploits the domain-specific language characteristics of templatized legal documents to mask collocated spans of text. Denoising these spans helps DALE acquire knowledge about legal concepts, principles, and language usage. Consequently, it develops the ability to generate coherent and diverse augmentations with novel contexts. Finally, DALE performs conditional generation to generate synthetic augmentations for low-resource Legal NLP tasks. We demonstrate the effectiveness of DALE on 13 datasets spanning 6 tasks and 4 low-resource settings. DALE outperforms all our baselines, including LLMs, qualitatively and quantitatively, with improvements of 1%-50%.Comment: Accepted to EMNLP 2023 Main Conference. Code: https://github.com/Sreyan88/DAL

ASPIRE: Language-Guided Augmentation for Robust Image Classification

Neural image classifiers can often learn to make predictions by overly relying on non-predictive features that are spuriously correlated with the class labels in the training data. This leads to poor performance in real-world atypical scenarios where such features are absent. Supplementing the training dataset with images without such spurious features can aid robust learning against spurious correlations via better generalization. This paper presents ASPIRE (Language-guided data Augmentation for SPurIous correlation REmoval), a simple yet effective solution for expanding the training dataset with synthetic images without spurious features. ASPIRE, guided by language, generates these images without requiring any form of additional supervision or existing examples. Precisely, we employ LLMs to first extract foreground and background features from textual descriptions of an image, followed by advanced language-guided image editing to discover the features that are spuriously correlated with the class label. Finally, we personalize a text-to-image generation model to generate diverse in-domain images without spurious features. We demonstrate the effectiveness of ASPIRE on 4 datasets, including the very challenging Hard ImageNet dataset, and 9 baselines and show that ASPIRE improves the classification accuracy of prior methods by 1% - 38%. Code soon at: https://github.com/Sreyan88/ASPIRE.Comment: Pre-print Under Revie

CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models

A fundamental characteristic of audio is its compositional nature. Audio-language models (ALMs) trained using a contrastive approach (e.g., CLAP) that learns a shared representation between audio and language modalities have improved performance in many downstream applications, including zero-shot audio classification, audio retrieval, etc. However, the ability of these models to effectively perform compositional reasoning remains largely unexplored and necessitates additional research. In this paper, we propose CompA, a collection of two expert-annotated benchmarks with a majority of real-world audio samples, to evaluate compositional reasoning in ALMs. Our proposed CompA-order evaluates how well an ALM understands the order or occurrence of acoustic events in audio, and CompA-attribute evaluates attribute binding of acoustic events. An instance from either benchmark consists of two audio-caption pairs, where both audios have the same acoustic events but with different compositions. An ALM is evaluated on how well it matches the right audio to the right caption. Using this benchmark, we first show that current ALMs perform only marginally better than random chance, thereby struggling with compositional reasoning. Next, we propose CompA-CLAP, where we fine-tune CLAP using a novel learning method to improve its compositional reasoning abilities. To train CompA-CLAP, we first propose improvements to contrastive training with composition-aware hard negatives, allowing for more focused training. Next, we propose a novel modular contrastive loss that helps the model learn fine-grained compositional understanding and overcomes the acute scarcity of openly available compositional audios. CompA-CLAP significantly improves over all our baseline models on the CompA benchmark, indicating its superior compositional reasoning capabilities.Comment: Pre-print under revie

Mycobacterium tuberculosis Transcriptional Adaptation, Growth Arrest and Dormancy Phenotype Development Is Triggered by Vitamin C

BACKGROUND: Tubercle bacilli are thought to persist in a dormant state during latent tuberculosis (TB) infection. Although little is known about the host factors that induce and maintain Mycobacterium tuberculosis (M. tb) within latent lesions, O(2) depletion, nutrient limitation and acidification are some of the stresses implicated in bacterial dormancy development/growth arrest. Adaptation to hypoxia and exposure to NO/CO is implemented through the DevRS/DosT two-component system which induces the dormancy regulon. METHODOLOGY/PRINCIPAL FINDINGS: Here we show that vitamin C (ascorbic acid/AA) can serve as an additional signal to induce the DevR regulon. Physiological levels of AA scavenge O(2) and rapidly induce the DevR regulon at an estimated O(2) saturation of <30%. The kinetics and magnitude of the response suggests an initial involvement of DosT and a sustained DevS-mediated response during bacterial adaptation to increasing hypoxia. In addition to inducing DevR regulon mechanisms, vitamin C induces the expression of selected genes previously shown to be responsive to low pH and oxidative stress, triggers bacterial growth arrest and promotes dormancy phenotype development in M. tb grown in axenic culture and intracellularly in THP-1 cells. CONCLUSIONS/SIGNIFICANCE: Vitamin C mimics multiple intracellular stresses and has wide-ranging regulatory effects on gene expression and physiology of M. tb which leads to growth arrest and a 'dormant' drug-tolerant phenotype, but in a manner independent of the DevRS/DosT system. The 'AA-dormancy infection model' offers a potential alternative to other models of non-replicating persistence of M. tb and may be useful for investigating host-'dormant' M. tb interactions. Our findings offer a new perspective on the role of nutritional factors in TB and suggest a possible role for vitamin C in TB

Appropriate DevR (DosR)-Mediated Signaling Determines Transcriptional Response, Hypoxic Viability and Virulence of Mycobacterium tuberculosis

Background: The DevR(DosR) regulon is implicated in hypoxic adaptation and virulence of Mycobacterium tuberculosis. The present study was designed to decipher the impact of perturbation in DevR-mediated signaling on these properties. Methodology/Principal Findings: M. tb complemented (Comp) strains expressing different levels of DevR were constructed in Mut1 * background (expressing DevR N-terminal domain in fusion with AphI (DevRN-Kan) and in Mut2DdevR background (deletion mutant). They were compared for their hypoxia adaptation and virulence properties. Diverse phenotypes were noted; basal level expression (,5.362.3 mM) when induced to levels equivalent to WT levels (,25.869.3 mM) was associated with robust DevR regulon induction and hypoxic adaptation (Comp 9 * and 10*), whereas low-level expression (detectable at transcript level) as in Comp 11 * and Comp15 was associated with an adaptation defect. Intermediate-level expression (,3.361.2 mM) partially restored hypoxic adaptation functions in Comp2, but not in Comp1 * bacteria that coexpressed DevRN-Kan. Comp * strains in Mut1 * background also exhibited diverse virulence phenotypes; high/very low-level DevR expression was associated with virulence whereas intermediate-level expression was associated with low virulence. Transcription profiling and gene expression analysis revealed up-regulation of the phosphate starvation response (PSR) in Mut1 * and Comp11 * bacteria, but not in WT/Mut2DdevR/other Comp strains, indicating a plasticity in expression pathways that is determined by the magnitude of signaling perturbation through DevRN-Kan

Effect of Musta (Cyperus Rotundus) and Pathya-Apathya in Sthaulya

Sthaulya (obesity) is so profound disease spreading worldwide and is associated with various systematic diseases. Sthaulya is mainly a lifestyle disorder occurring due to our eating habits of preserved and processed food items or it may have some genetic aetiology. Aim: To assess the efficacy of drug Musta along with Pathya-Apathya for 90 days. Material and Method: The subject has been selected from OPD with symptoms of Sthaulya and regular assessment has been done every 15 days at Ayurvedic and Unani Tibbia College and Hospital Karol Bagh. Drug Musta Churna (Cyperus rotundus) is administered orally with Pathya-Apathya for 90 days. At the end of the study, all data information related to the subject before and after treatment like weight, height, BMI measurement, and skin fold thickness of various regions and Lipid profile has been documented. Discussion: Before and after the treatment of the study subjective and objective parameters are thoroughly analysed and it has been found that there are practical changes in various parameters with no side effects. Conclusion: It has been concluded that single Musta churna is highly effective in Sthaulya along with Pathya-Apathya

Pharmacological Actions of Valeriana Wallichii (Tagara): A Fundamental Analysis Supporting Traditional Benefits

Valeriana wallichii referred to as Indian Valeriana has a family circle Valerianaceae commonly known as "Tagara". India, Nepal, and China are home to the important variety of the Valeriana genus. It is indigenous to India and can be found between 8000-10000 feet altitudes in the Himalayan region. Valeriana is a popular ethnobotanical remedy throughout Europe for relieving stress and improving sleep. Vital Central nervous system (CNS) activity is mirrored in the genuine Ayurvedic text-based content and declared as&nbsp;one of the&nbsp;handiest&nbsp;treatments&nbsp;with inside the&nbsp;remedy&nbsp;of neurosis and is&nbsp;powerful&nbsp;in pacifying the&nbsp;body ache&nbsp;(Vedanasathpana), chills (Sheetprashmana), and headaches (Shirah shoolprshmana). Additionally, it has been addressed in the Charaka Samhita as a remedy for snake poisoning. The rhizome and supporting tissues of valerian are used to treat insomnia, epilepsy, hypertension, and psychosomatic disorders. Important phytochemicals can reduce pain, manage stress, protect the brain from radiation, and fight off microbes. Hesperidin, the statutory potent flavonoid, 6-methylapigenin, and four new varieties of the iridoids Valeriotetrates B and C, 8-methylvalepotriate, and 1,5-dihydroxy-3,8-epoxyvalechlorine A are just a few of the naturally occurring active phytochemicals in the Valeriana wallichii