Evolutionary and functional insights into Leishmania META1: evidence for lateral gene transfer and a role for META1 in secretion.

BACKGROUND: Leishmania META1 has for long been a candidate molecule for involvement in virulence: META1 transcript and protein are up-regulated in metacyclic Leishmania. Yet, how META1 contributes to virulence remains unclear. We sought insights into the possible functions of META1 by studying its evolutionary origins. RESULTS: Using multiple criteria including sequence similarity, nucleotide composition, phylogenetic analysis and selection pressure on gene sequence, we present evidence that META1 originated in trypanosomatids as a result of a lateral gene transfer of a bacterial heat-inducible protein, HslJ. Furthermore, within the Leishmania genome, META1 sequence is under negative selection pressure against change/substitution. Using homology modeling of Leishmania META1 based on solved NMR structure of HslJ, we show that META1 and HslJ share a similar structural fold. The best hit for other proteins with similar fold is MxiM, a protein involved in the type III secretion system in Shigella. The striking structural similarity shared by META1, HslJ and MxiM suggests a possibility of shared functions. Upon structural superposition with MxiM, we have observed a putative hydrophobic cavity in META1. Mutagenesis of select hydrophobic residues in this cavity affects the secretion of the secreted acid phosphatase (SAP), indicating META1's involvement in secretory processes in Leishmania. CONCLUSIONS: Overall, this work uses an evolutionary biology approach, 3D-modeling and site-directed mutagenesis to arrive at new insights into functions of Leishmania META1

Adapter Pruning using Tropical Characterization

Adapters are widely popular parameter-efficient transfer learning approaches in natural language processing that insert trainable modules in between layers of a pre-trained language model. Apart from several heuristics, however, there has been a lack of studies analyzing the optimal number of adapter parameters needed for downstream applications. In this paper, we propose an adapter pruning approach by studying the tropical characteristics of trainable modules. We cast it as an optimization problem that aims to prune parameters from the adapter layers without changing the orientation of underlying tropical hypersurfaces. Our experiments on five NLP datasets show that tropical geometry tends to identify more relevant parameters to prune when compared with the magnitude-based baseline, while a combined approach works best across the tasks.Comment: Accepted at EMNLP 2023, Finding

KNOT: Knowledge Distillation using Optimal Transport for Solving NLP Tasks

We propose a new approach, Knowledge Distillation using Optimal Transport (KNOT), to distill the natural language semantic knowledge from multiple teacher networks to a student network. KNOT aims to train a (global) student model by learning to minimize the optimal transport cost of its assigned probability distribution over the labels to the weighted sum of probabilities predicted by the (local) teacher models, under the constraints, that the student model does not have access to teacher models' parameters or training data. To evaluate the quality of knowledge transfer, we introduce a new metric, Semantic Distance (SD), that measures semantic closeness between the predicted and ground truth label distributions. The proposed method shows improvements in the global model's SD performance over the baseline across three NLP tasks while performing on par with Entropy-based distillation on standard accuracy and F1 metrics. The implementation pertaining to this work is publicly available at: https://github.com/declare-lab/KNOT.Comment: COLING 202

Quantum Algorithms for the Pathwise Lasso

We present a novel quantum high-dimensional linear regression algorithm with an $\ell_1$-penalty based on the classical LARS (Least Angle Regression) pathwise algorithm. Similarly to available classical algorithms for Lasso, our quantum algorithm provides the full regularisation path as the penalty term varies, but quadratically faster per iteration under specific conditions. A quadratic speedup on the number of features $d$ is possible by using the quantum minimum-finding routine from D\"urr and Hoyer (arXiv'96) in order to obtain the joining time at each iteration. We then improve upon this simple quantum algorithm and obtain a quadratic speedup both in the number of features $d$ and the number of observations $n$ by using the approximate quantum minimum-finding routine from Chen and de Wolf (ICALP'23). As one of our main contributions, we construct a quantum unitary to approximately compute the joining times to be searched over by the approximate quantum minimum finding. Since the joining times are no longer exactly computed, it is no longer clear that the resulting approximate quantum algorithm obtains a good solution. As our second main contribution, we prove, via an approximate version of the KKT conditions and a duality gap, that the LARS algorithm (and thus our quantum algorithm) is robust to errors. This means that it still outputs a path that minimises the Lasso cost function up to a small error if the joining times are approximately computed. Moreover, we show that, when the observations are sampled from a Gaussian distribution, our quantum algorithm's complexity only depends polylogarithmically on $n$, exponentially better than the classical LARS algorithm, while keeping the quadratic improvement on $d$. Finally, we propose a dequantised algorithm that also retains the polylogarithmic dependence on $n$, albeit with the linear scaling on $d$ from the standard LARS algorithm.Comment: 48 pages. v2: several improvements, typos fixed, references added, fixed a bug in Theorem 28, exponentially improved the complexity dependence on the number of observations $n$ for a random Gaussian input matri

Unraveling Prostaglandin and NLRP3 Inflammasomemediated Pathways of Primary Dysmenorrhea and the Role of Mefenamic Acid and Its Combinations

Painful menstrual cramps during or around the time of the monthly cycle are known as dysmenorrhea. The estimated global prevalence in women of reproductive age ranges from 45% to 95%. It has a significant negative impact on regular activities and productivity at work. However, despite the severe consequences on quality of life, primary dysmenorrhea (PD) is underdiagnosed. Dysmenorrhea has complex pathogenesis. It involves the release of prostaglandins and activation of the nucleotide-binding oligomerization domain-like receptor protein 3 (NLRP3) inflammasome and also includes the involvement of other mediators such as bradykinin, histamine and acetylcholine. Even though nonsteroidal anti-inflammatory drugs (NSAIDs) remain the most common type of pain medication, the question of which one should be the most preferred is still open to debate. The current review examines the existing evidence for the pathogenesis of PD and makes evidence based and clinical experience based recommendations for the use of mefenamic acid and its combination in the treatment of dysmenorrhea. Mefenamic acid alleviates PD by inhibiting endometrial prostaglandin formation, restoring normal uterine activity, and reducing the inflammatory response by inhibiting the NLRP3 inflammasome and reducing the release of cytokines such as interleukin (IL)-1β. It is also known to have bradykinin antagonist activity. Dicyclomine has a dual action of blocking the muscarinic action of acetylcholine in postganglionic parasympathetic effect or regions and acting directly on uterine smooth muscle by blocking bradykinin and histamine receptors to relieve spasms. According to the experts, mefenamic acid and dicyclomine act synergistically by acting on the different pathways of dysmenorrhea by blocking multifactorial agents attributed to the cause of dysmenorrhea. Hence, the combination of mefenamic acid and dicyclomine should be the preferred treatment option for dysmenorrhea

Chitohexaose Activates Macrophages by Alternate Pathway through TLR4 and Blocks Endotoxemia

Sepsis is a consequence of systemic bacterial infections leading to hyper activation of immune cells by bacterial products resulting in enhanced release of mediators of inflammation. Endotoxin (LPS) is a major component of the outer membrane of Gram negative bacteria and a critical factor in pathogenesis of sepsis. Development of antagonists that inhibit the storm of inflammatory molecules by blocking Toll like receptors (TLR) has been the main stay of research efforts. We report here that a filarial glycoprotein binds to murine macrophages and human monocytes through TLR4 and activates them through alternate pathway and in the process inhibits LPS mediated classical activation which leads to inflammation associated with endotoxemia. The active component of the nematode glycoprotein mediating alternate activation of macrophages was found to be a carbohydrate residue, Chitohexaose. Murine macrophages and human monocytes up regulated Arginase-1 and released high levels of IL-10 when incubated with chitohexaose. Macrophages of C3H/HeJ mice (non-responsive to LPS) failed to get activated by chitohexaose suggesting that a functional TLR4 is critical for alternate activation of macrophages also. Chitohexaose inhibited LPS induced production of inflammatory molecules TNF-α, IL-1β and IL-6 by macropahges in vitro and in vivo in mice. Intraperitoneal injection of chitohexaose completely protected mice against endotoxemia when challenged with a lethal dose of LPS. Furthermore, Chitohexaose was found to reverse LPS induced endotoxemia in mice even 6/24/48 hrs after its onset. Monocytes of subjects with active filarial infection displayed characteristic alternate activation markers and were refractory to LPS mediated inflammatory activation suggesting an interesting possibility of subjects with filarial infections being less prone to develop of endotoxemia. These observations that innate activation of alternate pathway of macrophages by chtx through TLR4 has offered novel opportunities to cell biologists to study two mutually exclusive activation pathways of macrophages being mediated through a single receptor