Over the past few years, radiopharmaceutical therapy has emerged as a groundbreaking therapeutic modality, taking advantage of the unique properties of radionuclides to deliver molecularly targeted therapy with high precision and transforming the landscape of precision oncology and personalized medicine. Its development reflects decades of advances in nuclear medicine, chemistry, and cancer biology. However, until recently, definitive clinical evidence was lacking to establish it into treatment plans, with few large randomized controlled clinical studies. The last two decades witnessed a paradigm shift, with three successful phase 3 studies which shed light on radiopharmaceutical therapy. This paper offers a brief overview of currently active phase 3 studies to highlight the dynamism and promise of this clinical domain, as well as the large variety of cancers being treated.

The global market is expected to enjoy a valuation of US$ 9.3 Billion by the end of the year 2023, and further expand at a CAGR of 12.1% to reach a valuation of ~US$ 29.1 Billion by the year 2033. According to the recent study by Future Market Insights, clinical data management systems (CDMS) are leading the market with an expected share of about 22.6% in the year 2023, within the global market.

H1-H2 Update

Country-wise Insights

The data files are too large to host on Dataverse. Data and programs which replicate tables and figures from "Representation and Extrapolation: Evidence from Clinical Trials", by Alsan, Durvasula, Gupta, Schwartzstein, and Williams can be downloaded here: https://hu.sharepoint.com/:f:/s/HarvardEconomicsDatasets/EgEIycYhhzdFjP9PKzXXnWwB1OwMF-e7maN5LNzMz_Jhgw?e=EexDiz Please see the README file for additional details.

The size of the Virtual Clinical Trials Industry market was valued at USD 9.52 Million in 2023 and is projected to reach USD 17.79 Million by 2032, with an expected CAGR of 9.34% during the forecast period. The virtual clinical trials sector is moving very fast because of the recognition of a more efficient and adaptable way of conducting clinical research in recent times. Virtual clinical trials use digital technologies to conduct studies from remote settings; participants can thus participate from their homes using telemedicine, mobile health apps, and wearable devices to collect data. The method has improved on patient recruitment, retention, and compliance, especially among patients who would otherwise be discouraged from participating in traditional trials. The main drivers of growth in this sector are a continued focus on patient-centric trial designs, technology advancements, as well as the COVID-19 pandemic, which previously accelerated the spread of remote trial design. Regulatory bodies have also started to embrace virtual approaches that can offer the potential for more cost-effective and efficient trials for some time now. The market includes various stakeholders, like pharma companies, CROs, and technology providers. Those players are investing in innovative solutions to streamline the processes under a trial, data management, and regulatory compliance. Geographical Areas: North America is leading in the market based on the present healthcare infrastructure and technological advancement. However, the Asian Pacific is accelerating rapidly, which gets driven by increasing investments in the clinical research area along with a rise in focus on digital health solutions. Overall, virtual clinical trials is going to continue seeing growth because that is an element of this systemic shift toward more accessible, efficient, and patient-centered approaches in clinical research. Key drivers for this market are: Growing Digitization in Healthcare Sector, Technological Advancements in Virtual Clinical Trials; Prevalence of Chronic Disease. Potential restraints include: Challenges Associated with the Virtual Clinical Trials. Notable trends are: The Oncology Segment is Expected to Occupy a Significant Share of the Market Over the Forecast Period.

Questionnaire of the French Society of Sport Medicine (QSFMS). (DOC)

This dataset underlies AfriDx D6.7 report on Clinical study of NAT in COVID-19.

Summary of Project

The AfriDx Project comprises nucleic acid testing (NAT) for COVID-19 using the PATHPOD system and compared with the RT-qPCR as the gold standard. KNUST, KCCR and NMIMR received PATHPOD and cartridges from the DTU (see D2.2). The cartridges for the testing were shipped in two (2) batches. Training on PATHPOD usage was done and used for testing covid-19 samples. Data obtained was compared with the gold standard RT-PCR.

The overall the testing against RT-LAMP was circa 60% sensitive, but the specificity dropped from 80.0% in the first batch to 24% in the second batch. Analysis of the factors causing the drop in specificity is on-going.

In the first batch a total of 1,947 tests were conducted, with 531 positive and 1416 negative results, producing 302 samples returning a false positive (FP) 133 samples giving a false negative (FN). The data showed that the FNs could be related to the copy number of virus in the sample, with a strong correlation with RT-PCR C_T value and true positive/false negative LAMP outcome. The second batch of nucleic acid testing recorded a total of 1,612 test for N-gene in Ghana with 1208 positive and 404 negative tests. This showed an exceptionally high occurrence of false positive test results: 1134 (76.2%) samples returned a false positive (FP) compared with the RT-PCR and 49 (3.9%) samples gave a false negative (FN). Nevertheless, the correlation with C_T remained, suggesting that the PATHPOD was functioning correctly and that the results were revealing some contamination or deterioration of reagents or sample.

Some initial analysis of the raw data from PATHPOD revealed some characteristics of sample and/or reagent contamination as well as the outcome of a poorly sealed cartridge, that would result in an erroneous signal. Further analysis is needed to fully understand any design modifications that might be beneficial. The impact of shipping and storage on the cartridges also has potential impact and it is particularly noteworthy that the second batch of testing, using cartridges from the same manufacturing run as the first batch, performed less well.

Methodology

The PATHPOD equipment was placed on a clean and flat surface and switch on with the knob located at the back of equipment to turn on the equipment. The oropharyngeal sample in 300ul of PBS was heated at 95 ⁰C for 5min to inactivate virus. The master mix room table was disinfected with suitable disinfectant against DNA/RNA contamination. Wearing appropriate gloves, the Pathpod cartridge was removed from the refrigerator and allow 15-30 min at room temperature for the cartridge to acclimatize, and place in the chip holder. The attached temporary sealer film covering the wells was removed and discarded.

After short vortex of sample, 6 µl of sample and/or controls were added directly into the center of the well. the yellow paper from the PCR film was removed and placed over the film chip. The film was sealed properly to the chip using a soft roller ready for processing in the PATHPOD system.

Using the Pathpod keyboard, sample ID was entered and COV assay was selected. The start bottom was pressed to heat the machine, thereafter the cartridge was inserted and start bottom was pressed again to run the program. When the assay was completed, result was read from both the screen and the LEDs next to the keyboard. Ensuring that the position on the machine matches the position on the chip. The following interpretation was inferred as results:

GREEN LIGHT: NEGATIVE BLINKING RED LIGHT: POSITIVE YELLOW LIGHT: RE-TEST THE SAMPLE

Datasets

Marker genes for the lymphocyte subpopulations identified in Supplementary Figure 6. Only genes with adjusted p-value < 0.01 and average log fold-change > 0.3 were included. gene, gene name; p_val, p-value calculated based on Wilcoxon test; avg_logFC, log fold-change of the average expression between the given cluster and all other clusters; pct.1, fraction of gene-expressing cells in the given cluster; pct.2, fraction of gene-expressing cells in all other clusters; pct.diff, Difference between the percentage of gene-expressing cells in the given cluster and all other clusters; p_val_adj, Bonferroni adjusted p-value; cluster, cluster annotation based on the gene markers identified; resolution, clustering resolution parameter used in Seurat.

Chronic obstructive pulmonary disease (COPD) is a progressive incurable disease associated with smoking and advanced age, ranking as the third leading cause of death worldwide. DNA damage and loss of the central metabolite nicotinamide adenine dinucleotide (NAD) may contribute to both aging and COPD, presenting a potential avenue for interventions. In this randomized, double-blinded, placebo-controlled clinical trial, we treated patients with stable COPD (n = 40) with the NAD precursor nicotinamide riboside (NR) for 6 weeks and followed up 12 weeks after. The primary outcome was change in sputum interleukin-8 (IL-8) from baseline to week 6. The estimated treatment difference between NR and placebo in IL-8 after 6 weeks was -52.6% (95% confidence interval (CI), -75.7 to -7.6%; P = 0.030). This effect persisted until the follow-up twelve weeks after the end of treatment (-63.7%: 95% CI, -85.7 to -7.8%; P = 0.034). For secondary outcomes, NR treatment increased NAD levels by more than two-fold in whole-blood while IL-6 levels in plasma remained unchanged. In exploratory analyses, treatment with NR showed indications of upregulated gene pathways related to genomic integrity in the airways and reduced epigenetic aging–possibly through a reduction in cellular senescence. These exploratory analyses need to be confirmed in future trials. ClinicalTrials.gov identifier NCT04990869. Methods Data collection Study participants Forty patients with a diagnosis of COPD (post-bronchodilator FEV1/FVC < 0.7) were enrolled in this study (Table 1). Inclusion criteria included age ≥ 60 years, BMI between 18.5-40.0 kg·m-2 and a weight ≥ 40 kg at enrolment, a smoking history of at least 10 pack years but currently ex-smokers within six months, no use of inhalation corticosteroids (ICS), reported experiencing worsening of symptoms in relation to respiratory infections and a blood eosinophil count of < 0.3 x 109 cells/L. Exclusion criteria included having had an exacerbation of COPD or severe airway infection within the last two months, chronic use of supplements containing NR or vitamin B prior to and throughout the trial or a cancer diagnosis within 5 years. Furthermore, we enrolled a convenience sample of lung-healthy controls that were comparable with the patients with COPD in terms of age, sex, and body mass index (BMI) but who reported being never-smokers with no history of lung disease (Table 1). Two lung-healthy control participants were randomized to the placebo group but were later diagnosed with asthma and were therefore excluded from further analyses. Study design, randomization, and intervention This was a single-center, double blind, placebo-controlled clinical trial, with a 6-week intervention phase and a 12-week follow-up period. The intervention consisted of ingesting 2 g NR or placebo for 6 weeks (four 250 mg capsules consumed with meals in the morning and evening). Participants attended a screening visit and were randomized only if all inclusion criteria and none of the exclusion criteria were fulfilled. All participants were allocated 1:1 to receive NR or placebo using permuted block randomization with a block size of four. Independent blocks were generated for COPD and controls, and patients with COPD were additionally randomized stratified by CAT score (0-15 and 16-40). Randomization was performed by a member of the study team not involved in the assessment of outcomes. The study participants and members of the study team involved in the collection and analysis of the outcomes were blinded to the treatment condition. The placebo capsules had the same size, color, smell and appearance as the active drug tablets. The study visits included pre- (week 1), post- (week 6), and follow-up (week 18) assessments, for which participants arrived in the morning following an overnight fast. Participants took the last dose of NR/placebo 12-14 h prior to the post-intervention assessments. During each of the study visits, venous blood, sputum, and nasal brush samples were collected. Lung function was measured using spirometry according to standards set by the ATS/ERS 1 Venous blood samples were collected into Vacutainer tubes. Leukocyte count was analyzed using standardized clinical assays at Bispebjerg Hospital. Blood for NAD+ quantification was collected into sodium citrate tubes and immediately placed on wet ice. Aliquots of 0.1 mL blood were added to cryotubes containing 1 mL of 0.5 M perchloric acid, gently resuspended and stored at -80°C for later NAD+ quantification. Adverse events were recorded during the post-intervention and follow-up assessments. Nasal brushes After participants cleaned their nose with isotonic saline, nasal brush samples were collected by inserting a brush (Gynobrush, Heinz Herenz Hamburg, Germany) ~4 cm into the left nostril towards concha media and rotating six times. The same procedure was repeated for the right nostril, and the brushes were put into a 15 mL falcon tube containing 4 mL PBS. The tube was vortexed for 20 s and centrifuged at 600 g for 10 min at 4°C after discarding the brushes. The supernatant was discarded, and the cell pellet was lysed in 350 µL RLT buffer (Qiagen, Hilden, Germany) containing dithiothreitol (20 µL 2 M DTT per 1 mL RLT). RNA was extracted using the QIAcube (Qiagen, Hilden, Germany) following the manufacturer’s instructions and samples were stored at -80°C. RNA sequencing in nasal epithelial cells. RNA sequencing was performed on 151 nasal epithelial cell samples collected by nasal brush as indicated above by BGI genomics using whole RNA sequencing analysis on samples with a RIN mean 8.0, range 5.2-9.5. Paired-end reads were aligned to mm9 using bowtie2 2..Differential expression analysis was performed using Salmon, tximeta and, DESeq2 3. Gene set enrichment analysis was performed on DESeq2 normalized counts and comparisons were made against baseline values and between COPD and controls. The gene set used was based on Gene Ontology (GO) terms. Terms were filtered for false-discovery rate (FDR) < 0.05 and sorted by Normalized Enrichment Score. Gene sets with FDR>0.05 that were differentially expressed following treatment with NR (pre to post) and did not overlap with placebo were visualized using EnrichmentMap in Cytoscape (v. 3.9.1). Similar gene sets were clustered together into functional groups using AutoAnnotate. References Miller, M. R. et al. Standardisation of spirometry. Eur Respir J 26, 319–338 (2005). Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat Methods 9, 357–359 (2012). Patro, R., Duggal, G., Love, M. I., Irizarry, R. A. & Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 14, 417–419 (2017).

Supporting information, figures, and tables. Figure S1, 2004 global disability-adjusted life years (DALYs) and 2005 reviews, clinical trials and animal studies categorized by 19 broad WHO disease and disability categories. This correspondence the loose relationship between burden of disease and health knowledge (see Figure 1). Figure S2, Relationship between national disease burden and wealth. Scatterplots of national DALY rate (DALYs per 1000 people) and GNI per capita for each of 96 specific health conditions, where each point is a country. Also shown is the estimated influence (or regression slope) of logged DALY rate on logged GNI per capita, by condition, computed using ordinary least-squares (OLS) regression. Figure S3, Relationship between the national GDP per capita in 2004 and the quantity of reviews, clinical trials and animal studies published by researchers in 2005, by country, plotted on a logarithmic scale (to spread out countries for visual inspection). Each three character string corresponds to the unique ISO 3166-1 alpha-3 code associated with each country (see Figure 3 and Table S4 in File S1 for complete list). Table S1, Complete list of WHO Global Burden of Disease Categories. Table S2, Estimated Change in Global Number of Biomedical Articles with Changes in Global Health Burden (1990, 2004). Table S3, Estimated Change in Regional Number of Biomedical Articles with Changes in Regional Health Burden (1990, 2004). Table S4, Disease or Disease Category exacting the most DALYs. Table S5, Countries and their 3-Character Codes from Figure 3. (DOCX)

The global microscope table market is experiencing robust growth, driven by advancements in microscopy techniques and the increasing adoption of these technologies across diverse sectors like medical research, biological sciences, and industrial quality control. The market, estimated at $250 million in 2025, is projected to exhibit a healthy Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is fueled by several key factors: the rising demand for high-precision and stable platforms for advanced microscopy applications, including live-cell imaging and super-resolution microscopy; the increasing investments in research and development across various scientific domains; and the expanding adoption of automated and electrically controlled microscope tables offering enhanced precision and ease of use. The market segmentation reveals significant contributions from both the medical and biological application segments, with electric microscope tables holding a larger share compared to their manual counterparts due to the advantages in speed, accuracy, and repeatability. North America and Europe currently dominate the market, but the Asia-Pacific region is anticipated to witness significant growth over the forecast period driven by increased research spending and expanding industrial infrastructure. Despite the positive outlook, certain restraints might impede market expansion. These include the high initial investment cost associated with advanced microscope tables, particularly for electrically controlled models; the availability of limited skilled workforce proficient in operating and maintaining sophisticated equipment; and the presence of alternative, albeit less precise, methods for sample manipulation. However, continuous technological innovations, along with the introduction of cost-effective solutions and comprehensive training programs, are anticipated to mitigate these challenges. Major players in the market include established scientific instrument manufacturers as well as specialized companies focusing on precision engineering. Competitive strategies will likely include product innovation, strategic partnerships, and geographic expansion to maintain market share and capitalize on the growth opportunities. The market is expected to witness a significant shift towards advanced functionalities and higher automation levels in the coming years.

Market Overview:

The 7 major cervix lesion markets are expected to exhibit a CAGR of 3.92% during 2024-2034.

The cervix lesion market has been comprehensively analyzed in IMARC's new report titled "Cervix Lesion Market: Epidemiology, Industry Trends, Share, Size, Growth, Opportunity, and Forecast 2024-2034". Cervix lesion refers to an abnormal area of tissue growth or change on the cervix, which is the lower section of the uterus connecting to the vagina. These lesions can vary in nature, ranging from benign (non-cancerous) to pre-cancerous or cancerous. The symptoms of this ailment might not be immediately apparent, especially in the early stages. However, as the lesion progresses, some patients may experience abnormal vaginal bleeding, unusual discharge, pain during sexual intercourse, or pelvic discomfort. Diagnosing cervix lesions involves a series of steps. Initial screenings, like Pap smears or human papillomavirus (HPV) tests, can identify abnormalities in the cervix's cells or determine the presence of high-risk HPV strains. If these tests yield concerning results, further diagnostic procedures, such as colposcopy and biopsy, are conducted to detect the extent and nature of the lesion. Timely diagnosis and appropriate medical management are crucial to addressing cervix lesions and preventing their potential progression to more serious conditions.

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The escalating incidence of persistent infections with high-risk strains of HPV that can cause interference in the normal process of cell cycle control, leading to uncontrolled cell growth, is primarily driving the cervix lesion market. In addition to this, the inflating utilization of laser ablation procedures, to remove precancerous tissue and preserve the majority of the cervix's structural and functional integrity is also creating a positive outlook for the market. Moreover, the widespread adoption of innovative techniques, such as photodynamic therapy, which utilizes light-activated compounds to selectively destroy abnormal cells, is further bolstering the market growth. This approach helps in targeting and treating cervix lesions while minimizing harm to healthy surrounding tissue. Additionally, the rising usage of advanced diagnostic modalities, like liquid-based cytology, since it offers superior accuracy and reduced false negatives, thereby enhancing treatment outcomes for individuals suffering from the illness, is acting as another significant growth-inducing factor. Apart from this, the emerging popularity of HPV vaccines, that act as a prophylactic measure against the most common cancer-causing strains, is also augmenting the market growth. Furthermore, the increasing application of loop electrosurgical excision procedures (LEEP) on account of their several advantages, like a high success rate and minimal disruption to daily life, is expected to drive the cervix lesion market during the forecast period.

IMARC Group's new report provides an exhaustive analysis of the cervix lesion market in the United States, EU5 (Germany, Spain, Italy, France, and United Kingdom) and Japan. This includes treatment practices, in-market, and pipeline drugs, share of individual therapies, market performance across the seven major markets, market performance of key companies and their drugs, etc. The report also provides the current and future patient pool across the seven major markets. According to the report the United States has the largest patient pool for cervix lesion and also represents the largest market for its treatment. Furthermore, the current treatment practice/algorithm, market drivers, challenges, opportunities, reimbursement scenario and unmet medical needs, etc. have also been provided in the report. This report is a must-read for manufacturers, investors, business strategists, researchers, consultants, and all those who have any kind of stake or are planning to foray into the cervix lesion market in any manner.

Time Period of the Study

• Base Year: 2023
• Historical Period: 2018-2023
• Market Forecast: 2024-2034
  

Countries Covered

• United States
• Germany
• France
• United Kingdom
• Italy
• Spain
• Japan
  

Analysis Covered Across Each Country

• Historical, current, and future epidemiology scenario
• Historical, current, and future performance of the cervix lesion market
• Historical, current, and future performance of various therapeutic categories in the market
• Sales of various drugs across the cervix lesion market
• Reimbursement scenario in the market
• In-market and pipeline drugs

Competitive Landscape:

This report also provides a detailed analysis of the current cervix lesion marketed drugs and late-stage pipeline drugs.

In-Market Drugs

• Drug Overview
• Mechanism of Action
• Regulatory Status
• Clinical Trial Results
• Drug Uptake and Market Performance
  

Late-Stage Pipeline Drugs

• Drug Overview
• Mechanism of Action
• Regulatory Status
• Clinical Trial Results
• Drug Uptake and Market Performance
  

*Kindly note that the drugs in the above table only represent a partial list of marketed/pipeline drugs, and the complete list has been provided in the report.

Key Questions Answered in this Report:

Market Insights

• How has the cervix lesion market performed so far and how will it perform in the coming years?
• What are the markets shares of various therapeutic segments in 2023 and how are they expected to perform till 2034?
• What was the country-wise size of the cervix lesion market across the seven major markets in 2023 and what will it look like in 2034?
• What is the growth rate of the cervix lesion market across the seven major markets and what will be the expected growth over the next ten years?
• What are the key unmet needs in the market?
  

Epidemiology Insights

• What is the number of prevalent cases (2018-2034) of cervix lesion across the seven major markets?
• What is the number of prevalent cases (2018-2034) of cervix lesion by age across the seven major markets?
• What is the number of prevalent cases (2018-2034) of cervix lesion by gender across the seven major markets?
• How many patients are diagnosed (2018-2034) with cervix lesion across the seven major markets?
• What is the size of the cervix lesion patient pool (2018-2023) across the seven major markets?
• What would be the forecasted patient pool (2024-2034) across the seven major markets?
• What are the key factors driving the epidemiological trend of cervix lesion?
• What will be the growth rate of patients across the seven major markets?
  

Cervix Lesion: Current Treatment Scenario, Marketed Drugs and Emerging Therapies

• What are the current marketed drugs and what are their market performance?
• What are the key pipeline drugs and how are they expected to perform in the coming years?
• How safe are the current marketed drugs and what are their efficacies?
• How safe are the late-stage pipeline drugs and what are their efficacies?
• What are the current treatment guidelines for cervix lesion drugs across the seven major markets?
• Who are the key companies in the market and what are their market shares?
• What are the key mergers and acquisitions, licensing activities, collaborations, etc. related to the cervix lesion market?
• What are the key regulatory events related to the cervix lesion

a: No further information was identified in results registries of manufacturers.b: The designation of the primary outcome in the SR does not necessarily correspond to the operationalization of this outcome in the trials included in the systematic review (outcome in the trial included in the SR: recurrence of any affective episode; listed in Table 3).c: If information on clinical outcomes was unavailable, the SR considered surrogate outcomes.CGI: clinical global impression; HAM-D: Hamilton rating scale for depression; LDL-C: low-density lipoprotein cholesterol; MADRS: Montgomery–Åsberg Depression Rating Scale; SR: systematic review.

Annotated corpora for MESINESP2 shared-task (Spanish BioASQ track, see https://temu.bsc.es/mesinesp2). BioASQ 2021 will be held at CLEF 2021 (scheduled in Bucharest, Romania in September) http://clef2021.clef-initiative.eu/

Introduction: These corpora contain the data for each of the subtracks of MESINESP2 shared-task:

[Subtrack 1] MESINESP-L – Scientific Literature :

Training set: It contains all spanish records from LILACS and IBECS databases at the Virtual Health Library (VHL) with non-empty abstract written in Spanish. We have filtered out empty abstracts and non-Spanish abstracts. We have built the training dataset with the data crawled on 01/29/2021. This means that the data is a snapshot of that moment and that may change over time since LILACS and IBECS usually add or modify indexes after the first inclusion in the database. We distribute two different datasets:

Articles training set: This corpus contains the set of 237574 Spanish scientific papers in VHL that have at least one DeCS code assigned to them.

Full training set: This corpus contains the whole set of 249474 Spanish documents from VHL that have at leas one DeCS code assigned to them.

Development set: We provide a development set manually indexed by expert annotators. This dataset includes 1065 articles annotated with DeCS by three expert indexers in this controlled vocabulary. The articles were initially indexed by 7 annotators, after analyzing the Inter-Annotator Agreement among their annotations we decided to select the 3 best ones, considering their annotations the valid ones to build the test set. From those 1065 records:

213 articles were annotated by more than one annotator. We have selected de union between annotations.

852 articles were annotated by only one of the three selected annotators with better performance.

Test set: We provide a test set containing 10179 abstract without DeCS codes (not annotated) from LILACS and IBECS. Participants will have to predict the DecS codes for each of the abstracts in the entire dataset. However, the evaluation of the systems will only be made on the set of 500 expert-annotated abstracts that will be published as Gold Standard after finishing the evaluation period.

[Subtrack 2] MESINESP-T- Clinical Trials:

Training set: The training dataset contains records from Registro Español de Estudios Clínicos (REEC). REEC doesn't provide documents with the structure title/abstract needed in BioASQ, for that reason we have built artificial abstracts based on the content available in the data crawled using the REEC API. Clinical trials are not indexed with DeCS terminology, we have used as training data a set of 3560 clinical trials that were automatically annotated in the first edition of MESINESP and that were published as a Silver Standard outcome. Because the performance of the models used by the participants was variable, we have only selected predictions from runs with a MiF higher than 0.41, which corresponds with the submission of the best team.

Development set: We provide a development set manually indexed by expert annotators. This dataset includes 147 clinical trials annotated with DeCS by seven expert indexers in this controlled vocabulary.

Test set: The test dataset contains a collection of 8919 items. Out of this subset, there are 461 clinical trials coming from REEC and 8458 clinical trials artificially constructed from drug datasheets that have a similar structure to REEC documents. The evaluation of the systems will be performed on a set of 250 items annotated by DeCS experts following the same protocol as in subtrack 1. Similarly, these items will be published as Gold Standard after completion of the task.

[Subtrack 3] MESINESP-P – Patents:

Development set: We provide a Development set manually indexed by expert annotators. This dataset includes 115 patents in Spanish extracted from Google Patents which have the IPC code “A61P” and “A61K31”. We have selected these patents based on semantic similarity to the MESINESP-L training set to facilitate model generation and to try to improve model performance.

Test set: We provide a test set containing 68404 records that correspond to the total number of patents published in Spanish with the IPC codes “A61P” and “A61K31”. From this set, 150 will be selected and indexed by DeCS experts under the protocol defined in subtask 1, which will be used to evaluate the quality of the developed systems. Similarly to the development set, we selected these 150 records based on semantic similarity to the MESINESP-L training set.

Additional data:

We provide this information to the participants as additional data in the “Additional Data” folder. For each training, development, and test set there is an additional JSON file with the structure shown here. Each file contains entities related to medications, diseases, symptoms, and medical procedures extrated with the BSC NERs.

Files structure:

Subtrack1-Scientific_Literature.zip contains the corpora generated for subtrack 1. Content:

Subtrack1:

Train

training_set_track1_all.json: Full training set for subtrack 1.

training_set_track1_only_articles.json: Articles training set for subtrack 1.

Development

development_set_subtrack1.json: Manually annotated development set for subtrack 1.

Test

test_set_subtrack1.json: Test set for subtrack 1.

Subtrack2-Clinical_Trials.zip contains the corpora generated for subtrack 2. Content:

Subtrack2:

Train

training_set_subtrack2.json: Training set for subtrack 2.

Development

development_set_subtrack2.json: Manually annotated development set for subtrack 2.

Test

test_set_subtrack2.json: Test set for subtrack 2.

Subtrack3-Patents.zip contains the corpora generated for subtrack 3. Content:

Subtrack3:

Development

development_set_subtrack3.json: Manually annotated development set for subtrack 3.

Test

test_set_subtrack3.json: Test set for subtrack 3.

Additional data.zip contains the corpora with additional data for each subtrack of MESINESP2.

DeCS2020.tsv contains a DeCS table with the following structure:

DeCS code

Preferred descriptor (the preferred label in the Latin Spanish DeCS 2020 set)

List of synonyms (the descriptors and synonyms from Latin Spanish DeCS 2020 set, separated by pipes.

DeCS2020.obo contains the *.obo file with the hierarchical relationships between DeCS descriptors.

*Note: The obo and tsv files with DeCS2020 descriptors contain some additional COVID19 descriptors that will be included in future versions of DeCS. These items were provided by the Pan American Health Organization (PAHO), which has kindly shared this content to improve the results of the task by taking these descriptors into account.

For further information, please visit https://temu.bsc.es/mesinesp2/ or email us at lgasco@bsc.es

GLP-1 receptor agonists (GLP-1RAs) are effective anti-obesity drugs. However, the precise central mechanisms of GLP-1RAs remain elusive. We administered GLP-1RAs to obese patients and observed heightened sense of pre-ingestive satiation. Analysis of human and mouse brain samples pinpointed GLP-1R neurons in the dorsomedial hypothalamus (DMH) as candidates for encoding pre-ingestive satiation. Optogenetic manipulation of DMHGLP-1R neurons caused satiation. Calcium imaging demonstrated that these neurons are actively involved in encoding pre-ingestive satiation. GLP-1RA administration increased the activity of DMHGLP-1R neurons selectively during eating behavior. We further identified an intricate interplay between DMHGLP-1R neurons and arcuate NPY/AgRP neurons (ARCNPY/AgRP), to regulate food intake. Our findings reveal a hypothalamic mechanism through which GLP-1RAs control pre-ingestive satiation, offering novel neural targets for obesity and metabolic diseases. Methods Analysis Analysis was done using custom MATLAB code otherwise stated. Clinical trials 72 patients were assessed for eligibility, and 44 patients were screened, with 4 patients meeting the exclusion criteria. 40 obese individuals were enrolled, who were allocated randomly into two groups (Group A n=20, Group B n=20). The participants were prescribed liraglutide and received a weekly escalating dose of 0.6mg, 1.2mg, 1.8mg, 2.4mg daily over a four-weeks period. Patients were asked to write a diary to record the dose and date daily. Group A participants underwent control clinical tests prior to liraglutide injection, got 4 weeks of injection, and performed the same structured test scheme. Group B participants got 4 weeks of injection and underwent clinical tests, and after 2 weeks of washout period they performed the control clinical tests. A total of 28 patients were analyzed for study. (Withdrawn from trial: Group A n=0, Group B n=2. Excluded from analysis: Group A n=5, Group B n=5) Individual characteristics have been reported in Table S3. Clinical tests were performed as previously described as a structured test scheme, broken down into four distinct phases with a survey at the end of each phase. The survey was reconstructed based on the following questionnaires: VAS (34), RISE-Q (35), RED-13 (36), PFS-K (37), DEBQ (38). Missing values were omitted for analysis. This study was approved by the institutional review board (IRB) of Seoul National University College of Medicine/Seoul National University Hospital (IRB No. 2208-049-1349). Written informed consent was obtained from participants. Inclusion, exclusion, withdrawal, exclusion from analysis criteria have been reported in Table S2. Optogenetics Laser stimulation (473 nm for activation and 532 nm for inhibition, Shanghai DPSS Laser) was delivered through an FC-FC fiber patch cord (Doric Lenses) connected to the rotary joint, followed by the FC-ZF 1.25 fiber patch cord delivered stimulation to the cannula (200 µm core, NA 0.37, Doric Lenses or Inper). The laser intensity was approximately 10 mW at the tip. For open-loop stimulation, mice received 10-minute or 2-minute intervals of lasers at wavelengths of 473nm at 10hz, 50ms for neural activation or 532nm continuously for neural inhibition experiments. For closed-loop stimulation, mice received manual laser stimulation when they started to eat a high-fat diet (D12492, Research diets). Fiber photometry Fiber photometry signal data were acquired using the Doric Studio software. 465 nm calcium and 405 nm isosbestic signals (for artifact correction), were obtained. 405 nm signals were linearly fitted to 465 signals. △F/F0 signals were corrected as follows to minimize artifact recordings △F/F0 = (465 nm signal − fitted 405 nm signal)/fitted 405 nm signal. Signals were decimated to obtain approximately 20, 25 or 30 data points in 1 s. The mean of the baseline (m) and standard deviation (σ) of the baseline were computed to normalize the corrected signals into Z-scores (Z = (corrected 465 nm − m)/σ). The behavior time points for each test were manually annotated. For the heatmap visualization, Z-Score was used or each trial was normalized as follows: normalized Z = (Z − minimum Z)/(maximum Z − minimum Z). In the GLP-1RAs injection test baseline was designated before injection of drugs to account for the stable state of mice (Fig. 4). To account for signal changes near initiation of the first behavior, when the dosage effect was strongest, mean △F/F0 signals were quantified regarding the initial 5% of time between the initiation of behavior (Food Accessibility, Seeking Start, Consumption Start) and the next behavior (Seeking Start, Consumption Start, Consumption End, respectively) and was compared with baseline. Cumulative probability was quantified by first extracting a section of the Z-score from the behavior moment of interest to the next behavior moment. The section was divided into bins of 1 second and averaged. The averaged values were used for further quantification. Rate of change was quantified by computing the gradient at each behavior moment. Z-scored signals were smoothed using moving average function in MATLAB (movmean) by a sliding window of 1 second (Fig. 4K and R). Afterwards, the gradient of two moments near a behavior moment (before and after 1 second of a behavior moment) was computed. Micro-endoscope The raw signal output was preprocessed and computed into calcium dynamics (craw) using CNMF-E by using Inscopix Data Acquisition Software (IDAS ver.1.8). Afterwards, craw was computed into Z-scores (Z = (Craw − m)/σ), according to the mean (m) and standard deviation (σ) of the baseline for each trial (Start of mouse going into shelter until food accessibility). Tuning of each cell was computed using choice probability (CP), defined as how well a single cell’s neural activity could predictively discriminate between two behavioral phases as described from previous reports (44). All frames from the pre-consumption and consumption behavior bouts were used to compute the histogram for each cell. These distributions are computed into a cumulative distribution which are integrated to generate a ROC (receiver operating characteristics) curve. The area under the curve is then computed for each unit regarding the two behavior conditions. The significance of a cell’s CP was determined using shuffled bout timings. Shuffling was repeated 100 times in which the mean and standard deviation was acquired. CP that had a value of over 2 standard deviations above the mean was considered significant and used for analysis (Fig. 3 and fig. S7). To account for visualization, quantification and the responsive cells in different contexts, Z-score was acquired for each trial from each cell (baseline -10 ~ -5 from behavior of interest) (fig. S7 and S9). Representative traces were smoothed using movmean function in MATLAB with a sliding window of 1 second (Fig. 3S). For responsive cell analysis, cells were determined responsive if Z-score surpassed a value of 4 or -4 after behavior of interest (fig. S10). Heatmap visualization was done as stated above (Fig. 3O, T, fig. S10). For visualization of the whole population recordings from all mice, the whole trace of the individual cell itself was used as the baseline (fig. S6). Statistical Analysis Statistical data were analyzed using MATLAB, Graphpad Prism 8.0 software and figures were visualized using MATLAB or CorelDrawC8 (64bit). Paired t-tests or unpaired t-tests were used to compare data between two groups. One-way or two-way repeated-measures analyses of variance (ANOVA) were used for multiple comparisons. P-values for comparisons across multiple groups were corrected using the Greenhouse–Geisser, the Tukey, and the Sidak method. Cumulative probability distribution was analyzed with two sample Kolmogorov-Smirnov tests. Results are reported as mean ± SEM, including shades, unless indicated otherwise. Levels of significance were as follows: *p < 0.05. **p < 0.01, ***p < 0.001, ****p < 0.0001. Statistic methods are listed in Table S1. Electrophysiology studies Slice preparation Brain slices were prepared from mice as previously described (13, 14). Briefly, male mice were deeply anesthetized with i.p. injection of 7% chloral hydrate and transcardially perfused with a modified ice-cold artificial CSF (ACSF) (described below). The mice were then decapitated, and the entire brain was removed and immediately submerged in ice-cold, carbogen-saturated (95% O2 and 5% CO2) ACSF (126 mM NaCl, 2.8 mM KCl, 1.2 mM MgCl2, 2.5 mM CaCl2, 1.25 mM NaH2PO4, 26 mM NaHCO3, and 5 mM glucose). Coronal sections (250 μm) were cut with a Leica VT1000S Vibratome and then incubated in oxygenated ACSF (32 °C–34 °C) for at least 1 h before recording. The slices were bathed in oxygenated ACSF (32 °C–34 °C) at a flow rate of ∼2 ml/min. All electrophysiology recordings were performed at room temperature. Whole-cell recordings The pipette solution for whole-cell recording was modified to include an intracellular dye (Alexa Fluor 350 hydrazide dye) for whole-cell recording: 120 mM K-gluconate, 10 mM KCl, 10 mM HEPES, 5 mM EGTA, 1 mM CaCl2, 1 mM MgCl2, and 2 mM MgATP, 0.03 mM Alexa Fluor 350 hydrazide dye (pH 7.3). K-gluconate was replaced with equimolar Cs-gluconate for recording of spontaneous inhibitory postsynaptic currents (IPSCs) in response to photostimulation (2 pulses 50ms interval) upon the ARC. Epifluorescence was used to target fluorescent cells, at which time the light source was switched to infrared differential interference contrast imaging to obtain the whole-cell recording (Zeiss Axioskop FS2 Plus equipped with a fixed stage and a QuantEM:512SC electron-multiplying charge-coupled device camera). Electrophysiological signals were recorded using an Axopatch 700B amplifier (Molecular Devices); low-pass filtered at 2–5 kHz and

1. Supplemental Materials including: Supplementary Figure 1: Flow diagram of study; Supplementary Figure 2: Numbers of AD patients achieving EASI 25/50/75 at week 2, 4, 8 and week 12. Supplementary Figure 3: Numbers of AD patients achieving SCORAD 25/50/75 at week 2, 4, 8 and week 12. Supplementary Figure 4: Clinical photographs and the EASI score of two typical patients during the follow-up. Supplemental Table 1: Demographic and clinical characteristics of 16 patients. Supplemental Table 2: Laboratory parameters before and during abrocitinib treatment. 2.Supplemental Methods

Summary table of the data and metadata used in this study, including: Ella protein concentrations (in pg/ml), sample information (sample type and study time point), and selected subject information (sex, race, age, study site and COVID-19 status at the time of sampling). (XLSX)

Supplementary Table 1Supplementary Table 1 – this table lists the change scores for clinical outcome measures and strength tests over 1 year in mildly, moderately and severely affected ambulant patients and non-ambulant patientssupplementary table 1.docx

In 2023, research and development spending in the pharmaceutical industry exceeded 300 billion U.S. dollars globally. For comparison, R&D expenditures totaled 137 billion dollars in 2012. Pharmaceutical R&D includes all steps from the initial research of disease processes, the compound testing over pre-clinical, and all clinical trial stages. At a certain point in the process – mostly during the pre-clinical phase – a governmental authority is involved to overview, regulate, and ultimately approve the drug. In the United States, the Food and Drug Administration is the principal agency associated with processes. The pressure to innovate In comparison to other industries, pharmaceutical companies are more driven by the imperative to manufacture innovative products, and thus to spend significant amounts on research and development. This is largely due to the time-limited patent protection of drugs and the following threat of sales erosion through generic and biosimilar competition. Two major effects of patent expirations for the pharma industry are a specific high R&D intensity and a growing focus on specialty drugs to diversify their product portfolio. The latest trends For the last several years, major developments in pharmaceutical research and development have begun to change the R&D landscape. A growing number of drug manufacturers are outsourcing large parts of R&D, mostly to clinical research organizations (also contract research organizations), with the main aim to reduce costs. Another important development is the use of big data in clinical research. Thus, a predictive modeling is possible which uses clinical and molecular data to develop safer and more efficient drugs. Particularly, real-time or real-world evidence (RWE) is becoming a greater interest. This makes cooperation with technology companies necessary and includes data gathered from various sources, even that of social media.