Orca 2: Teaching Small Language Models How to Reason

Orca 1 learns from rich signals, such as explanation traces, allowing it to outperform conventional instruction-tuned models on benchmarks like BigBench Hard and AGIEval. In Orca 2, we continue exploring how improved training signals can enhance smaller LMs' reasoning abilities. Research on training small LMs has often relied on imitation learning to replicate the output of more capable models. We contend that excessive emphasis on imitation may restrict the potential of smaller models. We seek to teach small LMs to employ different solution strategies for different tasks, potentially different from the one used by the larger model. For example, while larger models might provide a direct answer to a complex task, smaller models may not have the same capacity. In Orca 2, we teach the model various reasoning techniques (step-by-step, recall then generate, recall-reason-generate, direct answer, etc.). More crucially, we aim to help the model learn to determine the most effective solution strategy for each task. We evaluate Orca 2 using a comprehensive set of 15 diverse benchmarks (corresponding to approximately 100 tasks and over 36,000 unique prompts). Orca 2 significantly surpasses models of similar size and attains performance levels similar or better to those of models 5-10x larger, as assessed on complex tasks that test advanced reasoning abilities in zero-shot settings. make Orca 2 weights publicly available at aka.ms/orca-lm to support research on the development, evaluation, and alignment of smaller LMsComment: Added url to model weights fixed typo in Author nam

Root coverage using epithelial embossed connective tissue graft

In periodontal practice, root coverage after marginal soft tissue recession requires daily clinical decisions. Numerous longitudinal human studies have been presented to support the efficacy and predictability of different mucogingival surgical techniques for root coverage. Over the years, root coverage procedure using the subepithelial connective tissue graft with variations has emerged as the favorite surgical technique. In the case presented in this report, subepithelial connective tissue graft with embossed epithelium was used to cover Miller′s class II gingival recession in the upper right canine. The design is such that embossed epithelium exactly fits the recession site and the connective tissue portion is tucked below the gingival margin of the recipient site. In this technique, coronal advancement of flap is not needed. Wider zone of attached gingiva at the recipient site was achieved by this technique

Comprehensive overview of biomarkers to predict response to immune checkpoint therapy in lung cancer

Immune checkpoint (IC) therapy has brought a huge revolution in the field of lung cancer treatment over the past decade. It has also revolutionised treatment paradigm and has tremendously improved patient prognosis. IC inhibitors (ICIs) targeting Programmed Cell Death Protein 1/Programmed cell death Ligand 1 (PD1/PD-L1) have shown remarkable success and are now being used as first-line therapies in metastatic disease, adjuvant therapy following surgical resection and chemotherapy in resectable disease. Despite this remarkable success, only a subset of patients obtains complete benefit and most patients do not respond or develop progressive disease during treatment. ICIs are relatively expensive and some patients suffer from significant immune-related adverse toxicities. Hence, the identification and discovery of new predictive and prognostic immunotherapy biomarkers remains the present crucial need for patient selection, stratification and also for guiding therapeutic decisions. Currently established biomarkers such as PD-L1 determined by immunohistochemistry and tumour mutation burden determined by next-generation sequencing are non-specific and possess limitations. At present, several other biomarkers using peripheral blood, liquid biopsies along with gene expression signatures, and tumour infiltrating lymphocytes are being researched globally which have demonstrated predictive potential to characterise ICIs responders. In this review, we provide a comprehensive overview of the current biomarkers, highlighting the main clinical challenges and possible novel potential biomarkers to better predict responders to ICIs

Analysis & prognosis of sustainable development goals using big data-based approach during COVID-19 pandemic

The world has changed considerably in the previous two decades. Today, people are facing extreme poverty, global warming, and unwanted climate changes. The economic gap between countries is continuously growing. Moreover, with the expanding influence of technology, governance is getting more difficult. To address these issues, the UN announced Sustainable Development Goals (SDGs), also called Global Goals, in 2015. These goals fill in as an overall source of inspiration to annihilate poverty, protect the environment, and guarantee that all individuals live in harmony and thrive by 2030. The 17 SDGs are interconnected in that they recognize that activities in a single region sway result in others and that improvement should adjust to social, monetary, and natural sustainability. The SDGs intend to kill poverty, hunger, AIDS, and gender discrimination against women and girls. The COVID-19 epidemic, on the other hand, has hampered attempts to accomplish the 2030 Agenda for Sustainable Development. As a result, the impact of these SDGs must be thoroughly studied and analyzed. As a result, the purpose of this research is to examine the SDG before and after Covid-19, as well as how they have influenced various national and international markets. The research also assesses the 17 SDGs in each of India's 29 states in depth. Since SDGs have a larger scope, this paper predicts the SDG-9 scores of few countries like UAE, New Zealand, Japan, India, Germany, China, Bhutan, and USA

<i>Plasmodium vivax</i> Tryptophan Rich Antigen PvTRAg36.6 Interacts with PvETRAMP and PvTRAg56.6 Interacts with PvMSP7 during Erythrocytic Stages of the Parasite

<div><p><i>Plasmodium vivax</i> is most wide spread and a neglected malaria parasite. There is a lack of information on parasite biology of this species. Genome of this parasite encodes for the largest number of tryptophan-rich proteins belonging to ‘Pv-fam-a’ family and some of them are potential drug/vaccine targets but their functional role(s) largely remains unexplored. Using bacterial and yeast two hybrid systems, we have identified the interacting partners for two of the <i>P</i>. <i>vivax</i> tryptophan-rich antigens called PvTRAg36.6 and PvTRAg56.2. The PvTRAg36.6 interacts with early transcribed membrane protein (ETRAMP) of <i>P</i>.<i>vivax</i>. It is apically localized in merozoites but in early stages it is seen in parasite periphery suggesting its likely involvement in parasitophorous vacuole membrane (PVM) development or maintenance. On the other hand, PvTRAg56.2 interacts with <i>P</i>.<i>vivax</i> merozoite surface protein7 (PvMSP7) and is localized on merozoite surface. Co-localization of PvTRAg56.2 with PvMSP1 and its molecular interaction with PvMSP7 probably suggest that, PvTRAg56.2 is part of MSP-complex, and might assist or stabilize the protein complex at the merozoite surface. In conclusion, the PvTRAg proteins have different sub cellular localizations and specific associated functions during intra-erythrocytic developmental cycle.</p></div

Non-Fermenting Gram Negative Bacteria as Uropathogens in Causing Urinary Tract Infection and its Antimicrobial Susceptibility Pattern at A Tertiary Care Centre of South India

Non fermenting gram-negative bacilli (NFGNB) are recently striving as uropathogens. The present study was conducted to isolate the common species of bacteria in NFGNB causing urinary tract infection (UTI) and its correlation with comorbid conditions and to study the antibacterial susceptibility pattern. This retrospective study was done at the diagnostic Microbiology laboratory of a tertiary care hospital. Urine samples were collected for the period of six months. These samples were plated on blood agar and MacConkey agar and incubated at 37°C for 18–24 hr under aerobic conditions. Identification of NFGNB was done by Gram staining and MALDI-TOF (Matrix- Assisted Laser Desorption/ Ionization- Time of Flight, Biomerieux- Diagnostics). Antibiotic sensitivity testing was done by Vitek® 2 system (Biomerieux- Diagnostics) using N 281 card. Data was analyzed using SPSS IBM version 16. Out of the total 16,413 non repetitive urine samples that were received in the laboratory, 318 had significant bacteriuria. NFGNB were identified in 108 (33.9%) of all the urine samples with significant bacteriuria. Prevalence of non-fermenters in our study was 0.6%. NFGNB were more frequently isolated in the females and also in the age group of more than 50 years. Eighty five (78.70%) had comorbid conditions. P. aeruginosa and A. baumannii were the most common organism isolated among NFGNB. Pseudomonas aeruginosa isolates showed high susceptibility to imipenem (80.2%) and amikacin (66.6%). NFGNB although seen frequently in females and in age group of 50 years and above, clinical correlation with comorbid condition is essential to label it as uropathogens. Amikacin or imipenem may be the empirical drug of choice

Sub cellular localization of PvTRAg36.6 in <i>P</i>.<i>vivax</i> natural infections.

<p>Immunofluorescence images of <i>P</i>.<i>vivax</i> infected red cells. Parasites were labeled with anti- PvTRAg36.6 (green) antibody and DAPI for nuclear staining (blue). Fluorescence pattern observed in ring (<b>R</b>, double infection), trophozoite <b>(T),</b> Schizont <b>(S)</b> stages and in free merozoites <b>(M)</b> are shown. Overlay shows the images merged with bright field.</p

Co-localization studies of PvTRAg36.6 in <i>P</i>.<i>vivax</i>.

<p>Co-localization images of PvTRAg36.6 with apicoplast, rhoptry and micronemal markers in <i>P</i>.<i>vivax</i> natural infections. <b>(A)</b> Fluorescence pattern observed after co-immuno staining of <i>P</i>.<i>vivax</i> parasite with anti-PvTRAg36.6 (green) and anti-PfClpP (red) recognizing apicoplast in schizont (<b>A</b>, upper panel) as well as in free merozites (<b>A</b>, lower panel). <b>(B)</b> Co-immunostaining of anti-PvTRAg36.6 (green) with anti-PvRII (red) recognizing microneme in a schizont, and <b>(C)</b> Co-immunostaining of anti-PvTRAg36.6 (green) with anti-PvAARP (red) recognizing rhoptry neck in a schizont. The parasite nuclei were stained with DAPI (blue). Overlay shows the images merged with bright field.</p

Putative interacting protein partners of PvTRAg36.6 and PvTRAg56.2 identified by bacterial two hybrid assay.

<p>Putative interacting protein partners of PvTRAg36.6 and PvTRAg56.2 identified by bacterial two hybrid assay.</p

Sub cellular localization of PvTRAg36.6 in <i>P</i>.<i>falciparum</i> transgenic parasites expressing GFP fusion protein.

<p>GFP fluorescence images showing localization of PvTRAg36.6-GFP in trophozoite stages of transgenic parasite line 3D7_ PvTRAg36.6-GFP, B. Images of co-immunostaining between anti-GFP antibody (green) and anti-SBP1 antibody (red). Parasite nuclei were labeled with DAPI (blue). Overlay shows images merged with bright field.</p