Probing LLMs for Joint Encoding of Linguistic Categories

Large Language Models (LLMs) exhibit impressive performance on a range of NLP tasks, due to the general-purpose linguistic knowledge acquired during pretraining. Existing model interpretability research (Tenney et al., 2019) suggests that a linguistic hierarchy emerges in the LLM layers, with lower layers better suited to solving syntactic tasks and higher layers employed for semantic processing. Yet, little is known about how encodings of different linguistic phenomena interact within the models and to what extent processing of linguistically-related categories relies on the same, shared model representations. In this paper, we propose a framework for testing the joint encoding of linguistic categories in LLMs. Focusing on syntax, we find evidence of joint encoding both at the same (related part-of-speech (POS) classes) and different (POS classes and related syntactic dependency relations) levels of linguistic hierarchy. Our cross-lingual experiments show that the same patterns hold across languages in multilingual LLMs.</p

Finding the association of mRNA and miRNA using Next Generation Sequencing data of Kidney renal cell carcinoma

MicroRNAs (miRNAs) are a class of 22-nucleotide endogenous noncod- ing RNAs, plays important role in regulating target gene expression via repress- ing translation or promoting messenger RNAs (mRNA) degradation. Numerous re- searchers have found that miRNAs have serious effects on cancer. Therefore, study of mRNAs and miRNAs together through the integrated analysis of mRNA and miRNA expression profiling could help us in getting a deeper insight into the can- cer research. In this regards, High-Throughput Sequencing data of Kidney renal cell carcinoma is used here. The proposed method focuses on identifying mRNA- miRNA pair that has a signature in kidney tumor sample. For this analysis, Ran- dom Forests, Particle Swarm Optimization and Support Vector Machine classifier is used to have best sets of mRNAs-miRNA pairs. Additionally, the significance of selected mRNA-miRNA pairs is tested using gene ontology and pathway analysis tools. Moreover, the selected mRNA-miRNA pairs are searched based on changes in expression values of the used mRNA and miRNA dataset

Oxaliplatin-dacarbazine combination chemotherapy for the treatment of advanced soft tissue sarcoma of the limbs

<p>Abstract</p> <p>Background</p> <p>This study was designed to explore the feasibility, safety, and outcomes of pre-operative oxaliplatin-dacarbazine combination therapy for the treatment of advanced soft tissue sarcoma (STS) of the limb.</p> <p>Patients and Methods</p> <p>Between November 2005 and November 2008, 31 patients with advanced limb STS classified with stage IV STS were randomly assigned into experimental or control groups, and both were given 2 cycles of chemotherapy before undergoing surgery. The regimen for the experimental group was oxaliplatin (120 mg/m², d₁) in combination with dacarbazine (175 mg/m², d₁₃), while that for the control group was a standard vincristine, epirubicin, cyclophosphamide therapy. Operations were carried out four weeks after the second chemotherapy cycle, followed by another 24 more chemotherapy cycles of the previous regimen.</p> <p>Results</p> <p>Following preoperative chemotherapy, the experimental group exhibited a significant improvement in tumor regression compared to controls. Both regimens were well-tolerated, and no significant differences in adverse reactions were noted. At a median follow-up of 24 months, 28 patients were still alive and had normal limb function. The progression free survival rate of the experimental group was significantly higher than that of the control group (10/15 vs. 4/16, <it>p </it>< 0.05).</p> <p>Conclusion</p> <p>Oxaliplatin- dacarbazine neoadjuvant/adjuvant chemotherapy improved the prognosis of patients with advanced limb STS in comparison with vincristine, epirubicin, cyclophosphamide combination therapy.</p

New insights into the Tyrolean Iceman's origin and phenotype as inferred by whole-genome sequencing

The Tyrolean Iceman, a 5,300-year-old Copper age individual, was discovered in 1991 on the Tisenjoch Pass in the Italian part of the Otztal Alps. Here we report the complete genome sequence of the Iceman and show 100% concordance between the previously reported mitochondrial genome sequence and the consensus sequence generated from our genomic data. We present indications for recent common ancestry between the Iceman and present-day inhabitants of the Tyrrhenian Sea, that the Iceman probably had brown eyes, belonged to blood group O and was lactose intolerant. His genetic predisposition shows an increased risk for coronary heart disease and may have contributed to the development of previously reported vascular calcifications. Sequences corresponding to similar to 60% of the genome of Borrelia burgdorferi are indicative of the earliest human case of infection with the pathogen for Lyme borreliosis

Multiple Sclerosis: MicroRNA Expression Profiles Accurately Differentiate Patients with Relapsing-Remitting Disease from Healthy Controls

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS