Through 2022, the changes in the producer price index (PPI) were at a high rate across all regions, before falling through the last quarter of 2022 and the first months of 2023. In the Euro Area, the monthly change was over 40 percent in August 2022, but has been negative since mid-2023. Meanwhile, China had a negative index rate of 2.8 percent in September 2024, struggling with producer price deflation through 2023. The Producer Price Index (PPI) measures the average change over time in the selling prices received by domestic producers for their output.

An extensive dataset of binary physical protein-protein interaction extracted from STRING 12.0 (>12,000 organisms) with artificially generated negatives. The dataset includes 72M positive pairs with STRING confidence scores> 0.9 and 720M negative pairs. The corresponding protein sequences are located in the .fasta files. The generation of the negatives was derived from https://doi.org/10.1016/j.isci.2024.110371

Protein–protein interactions (PPIs) are extremely important for gaining mechanistic insights into the functional organization of the proteome. The resolution of PPI functions can help in the identification of novel diagnostic and therapeutic targets with medical utility, thus facilitating the development of new medications. However, the traditional methods for resolving PPI functions are mainly experimental methods, such as co-immunoprecipitation, pull-down assays, cross-linking, label transfer, and far-Western blot analysis, that are not only expensive but also time-consuming. In this study, we constructed an integrated feature selection scheme for the large-scale selection of the relevant functions of PPIs by using the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotations of PPI participants. First, we encoded the proteins in each PPI with their gene ontologies and KEGG pathways. Then, the encoded protein features were refined as features of both positive and negative PPIs. Subsequently, Boruta was used for the initial filtering of features to obtain 5684 features. Three feature ranking algorithms, namely, least absolute shrinkage and selection operator, light gradient boosting machine, and max-relevance and min-redundancy, were applied to evaluate feature importance. Finally, the top-ranked features derived from multiple datasets were comprehensively evaluated, and the intersection of results mined by three feature ranking algorithms was taken to identify the features with high correlation with PPIs. Some functional terms were identified in our study, including cytokine–cytokine receptor interaction (hsa04060), intrinsic component of membrane (GO:0031224), and protein-binding biological process (GO:0005515). Our newly proposed integrated computational approach offers a novel perspective of the large-scale mining of biological functions linked to PPI.

The inter-annual variation of the producer price index (PPI) in Spain stood at 1.9 as of April 2025. By the October 2024 the annual variation was negative.

Data for RAPPPID, a method for the Regularised Automative Prediction of Protein-Protein Interactions using Deep Learning.

These datasets are in a format that RAPPPID is ready to read.

Comparatives Dataset
These datasets were derived from the STRING v11 H. sapiens dataset, according to the C1, C2, and C3 procedures outlined by Park and Marcotte, 2012. Negative samples are sampled randomly from the space of proteins not known to interact. See Szymborski & Emad for details.

Repeatability Datasets
The following datasets are all derived from STRING in the manner as the comparatives dataset, but three different random seeds are used for drawing proteins.

References
Park,Y. and Marcotte,E.M. (2012) Flaws in evaluation schemes for pair-input computational predictions. Nat Methods, 9, 1134–1136.

Szklarczyk, D., Gable, A. L., Lyon, D., Junge, A., Wyder, S., Huerta-Cepas, J., Simonovic, M., Doncheva, N. T., Morris, J. H., Bork, P., Jensen, L. J., and Mering, C. (2019). String v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Research, 47(D1), D607–D613.

Szymborski,J. and Emad,A. (2021) RAPPPID: Towards Generalisable Protein Interaction Prediction with AWD-LSTM Twin Networks. bioRxiv https://doi.org/10.1101/2021.08.13.456309

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Proton Pump Inhibitors (PPIs) Market Size 2025-2029

The proton pump inhibitors market size is forecast to increase by USD 819.5 million, at a CAGR of 4.7% between 2024 and 2029.

The market is characterized by significant growth drivers and trends, as well as notable challenges. The expanding geriatric population is a key growth driver, as this demographic is more susceptible to gastroesophageal reflux disease and other conditions requiring long-term PPI therapy. Additionally, the increasing prevalence of gastric ulcers and other gastrointestinal disorders contributes to market expansion. However, the market faces challenges, including the rising number of lawsuits against PPIs due to potential side effects, such as kidney damage and increased risk of heart attacks. These lawsuits may lead to increased regulatory scrutiny and potential restrictions on PPI use, posing a significant threat to market growth.
Companies operating in the PPI market must navigate these challenges by investing in research and development of safer alternatives, as well as implementing robust regulatory compliance strategies. By capitalizing on the growing demand for effective gastrointestinal treatments while addressing regulatory and legal hurdles, market participants can successfully capitalize on the opportunities and challenges presented in the PPI market.

What will be the Size of the Proton Pump Inhibitors (PPIs) Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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Proton pump inhibitors (PPIs) continue to play a significant role in the gastrointestinal therapeutics market due to their efficacy in treating various conditions, including peptic ulcer disease, gastroesophageal reflux disease (GERD), and Zollinger-Ellison syndrome. The market dynamics for PPIs are continually evolving, with ongoing research and development efforts focusing on addressing unmet needs and improving patient outcomes. In the realm of disease management, PPIs are increasingly being used in the context of smoking cessation and alcohol reduction to mitigate the negative effects of these habits on the gastrointestinal tract. Furthermore, the role of PPIs in managing conditions such as c difficile infection, elevated intra-abdominal pressure, and chronic kidney disease is a growing area of interest.

Brand-name PPIs dominate the market, but the introduction of generic alternatives and over-the-counter (OTC) medications has increased competition and driven down costs. Health technology assessment and cost-effectiveness analysis are crucial factors influencing market dynamics, with healthcare providers and primary care physicians seeking to optimize treatment algorithms and improve patient satisfaction. Clinical trials and treatment guidelines continue to shape the market, with a focus on addressing adverse events, drug interactions, and disease resistance. Patient education and lifestyle modifications, such as dietary changes and weight management, are essential components of effective PPI therapy. Quality of life and safety and efficacy remain key considerations in the PPI market, with ongoing efforts to improve patient adherence and address healthcare costs.

Healthcare providers and medical guidelines emphasize the importance of proper diagnosis and individualized treatment plans to ensure optimal outcomes for patients. The ongoing evolution of the PPI market is driven by a complex interplay of factors, including patient needs, healthcare costs, regulatory requirements, and technological advancements. The landscape is continually unfolding, with new developments and trends shaping the future of this dynamic market.

How is this Proton Pump Inhibitors (PPIs) Industry segmented?

The proton pump inhibitors (ppis) industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  OTC PPIs
  Prescription PPIs


Route Of Administration

  Oral
  Injectable


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

.

By Product Insights

The otc ppis segment is estimated to witness significant growth during the forecast period.

The market encompasses both prescription medications and over-the-counter (OTC) drugs, with the latter category gaining significant traction due to ease of access and affordability. OTC PPIs, such as PREVACID, NEXIUM, PRILOSEC, and Zegerid, are commonly used for treating frequent heartburn by decreasing stomach acid secretion. The US Food and Drug Administration (FDA

Between January 2022 and October 2024, the monthly Producer Price Index (PPI) of macaroni, noodles, couscous and similar farinaceous products in Italy showed an overall increase up until February 2023. Since then the trend has generally developed negatively. The monthly PPI is here calculated using the year 2021 as the base, thus equal to 100. The output price index of pasta products manufactured in the country reached ***** in October 2024.

In the first quarter of 2025, the Producer Price Index (PPI) of agricultural products in China ranged at 98.4 index points (same quarter of previous year = 100). After a considerable price decrease between the first quarter of 2020 and the third quarter of 2021, inflation picked up in the second and third quarter of 2022, mainly driven by rising pork prices, but also supported by a price increase of farm crops. Agricultural prices decreased again in 2023 and stabilized in 2024. The Producer Prices Index The Producer Price Index (PPI) measures the average change in selling prices received by domestic producers for their output. In combination with the Consumer Price Index (CPI), the PPI is used as an indicator to identify economic inflation or deflation. In contrast to CPI, which measures price levels of end consumers, the PPI measures the output price change from the perspective of sellers. In this sense, the Producer Price Index of agricultural products reflects changes in selling price received by farmers. Agricultural producer prices in China According to the graph at hand, producer prices for agricultural products picked up considerably in the second quarter of 2019. Inflation peaked in the first quarter of 2020 and fell back to a normal level in the fourth quarter of 2020. This development was mainly caused by an increase of Chinese producer prices for livestock, which were driven by the outbreak of the swine fever in 2019. The PPI for fishery in China fluctuated only slightely at around 100 index points during the same period, while producer prices for forestry products in China even saw a partially negative price development. During the third quarter of 2022, however, prices for livestock products grew considerably, while prices for farm crops in China indicated a moderate price increase.

PPI maps for task switch > repeat (local switch cost) bilateral dorsal caudate seed region negatively regressed with behavioral switch cost.

Collection description

Dopaminergic signaling in striatum is strongly implicated in executive functions including cognitive flexibility. However, there is a paucity of multimodal research in humans defining the nature of relationships between endogenous dopamine, striatal network activity, and cognition. Here, we measured dopamine synthesis capacity in young and older adults using the PET tracer 6-[18F]fluoro-L-m-tyrosine, and examined its relationship with cognitive performance and functional connectivity during an fMRI study of task switching. Aging is associated with alteration in dopamine function including profound losses in dopamine receptors, but an apparent elevation in dopamine synthesis. A compensatory benefit of upregulated dopamine synthesis in aging has not been established. Across young and older adults, we found that cognitive flexibility (low behavioral switch cost) was associated with stronger task-related functional connectivity within canonical fronto-striato-thalamic circuits connecting left inferior frontal gyrus, dorsal caudate nucleus (DCA) and ventral lateral/ventral anterior thalamic nuclei. In young adults, functional connectivity mediated the influence of DCA dopamine synthesis capacity on switch cost. For older adults, these relationships were modified such that DCA synthesis capacity and connectivity interacted to influence switch cost. Older adults with most elevated synthesis capacity maintained the pattern of connectivity-cognition relationships observed in youth, whereas these relationships were not evident for low synthesis older adults. Together, these findings suggest a role of dopamine in tuning striatal circuits to benefit executive function in young adults, and clarify the functional impact of elevated dopamine synthesis capacity in aging.

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

task-switching

Map type

T

In the second quarter of 2025, the Producer Price Index (PPI) of agricultural products in China ranged at **** index points (same quarter of previous year = 100). After a considerable price decrease between the first quarter of 2020 and the third quarter of 2021, inflation picked up in the second and third quarter of 2022, mainly driven by rising pork prices, but also supported by a price increase of farm crops. Agricultural prices decreased again in 2023 and stabilized in 2024. The Producer Prices Index The Producer Price Index (PPI) measures the average change in selling prices received by domestic producers for their output. In combination with the Consumer Price Index (CPI), the PPI is used as an indicator to identify economic inflation or deflation. In contrast to CPI, which measures price levels of end consumers, the PPI measures the output price change from the perspective of sellers. In this sense, the Producer Price Index of agricultural products reflects changes in selling price received by farmers. Agricultural producer prices in China According to the graph at hand, producer prices for agricultural products picked up considerably in the second quarter of 2019. Inflation peaked in the first quarter of 2020 and fell back to a normal level in the fourth quarter of 2020. This development was mainly caused by an increase of Chinese producer prices for livestock, which were driven by the outbreak of the swine fever in 2019. The PPI for fishery in China fluctuated only slightely at around 100 index points during the same period, while producer prices for forestry products in China even saw a partially negative price development. During the third quarter of 2022, however, prices for livestock products grew considerably, while prices for farm crops in China indicated a moderate price increase.

Benchmark data sets of AF2Complex, input features for application to E. coli proteome, and predicted structural models of E. coli Ccm I as described in

Predicting direct physical interactions in multimeric proteins with deep learning

Mu Gao, Davi Nakajima An, Jerry M. Parks, Jeffrey Skolnick

1. af2complex_bench.tar.gz: Benchmark data sets CP17, Dimer1193 and Oligomer562, including input features for AF2Complex/AF-Multimer, both paired and unpaired MSAs, as well as sequences, experimental structures, and results presented in the AF2Complex work (~90GB de-compressed size)
2. ecoli_Ccm_I.tar.gz: Computational models of the E. coli Ccm I system
3. ecoli_sets.tar.gz: Lists of benchmark sets of positive and negative PPIs from E. coli
4. ecoli_af_fea.tar.gz: Pre-generated input features of E. coli proteome for protein complex prediction and modeling by AF2Complex (4,429 proteins, ~800 GB de-compressed size). This data set can be used with AF2Complex to probe the interactions of any combinations among the 4,429 proteins of E. coli.

Proton pump inhibitors (PPIs) such as omeprazole and pantoprazole are commonly prescribed for the management of acid-related gastrointestinal (GI) disorders. Ranked among the 10 most frequently prescribed drugs in the United States, PPIs are used to treat a variety of conditions, including gastroesophageal reflux disease, peptic ulcers, Helicobacter pylori infection, Barrett's esophagus, as well as to treat patients who might be at higher risk for those conditions, such as patients on long-term nonsteroidal anti-inflammatory (NSAIDS) or antiplatelet therapies. PPIs inhibit the H+/K+ adenosine triphosphatase proton pump in gastric parietal cells, inhibiting the secretion of gastric acid into the stomach. Typically, gastric parietal cells secrete hydrochloric acid when stimulated, and a negative feedback inhibitory mechanism initiated in response to elevated intragastric acidity depresses further acid secretion. Interruption of that mechanism by drugs such as PPIs results in hypergastrinemia. Chronic low-acid states have been implicated in the reduced absorption of fats, minerals, and vitamins. In addition to aiding in digestion and activating pepsin, gastric acid limits the survival of pH-sensitive microorganisms implicated in GI tract infections. Accordingly, an association has been found between the composition of the microbiome and PPI use. PPIs increase stomach pH, which decreases the number of indigenous bacteria and encourages alternative bacterial species to survive and colonize. Changes in the GI microbiota with PPI use also has been related to an increased risk of bacterial peritonitis, pneumonia, and enteric infections. Achlorhydria induced by acid-inhibitory drugs can lead to bacterial overgrowth, consisting primarily of Gram-positive organisms that more closely resemble the oral and oropharyngeal microflora. Evidence suggests that PPI administration might have a deleterious effect on developing bone among pediatric patients, and lead to decreased bone mineralization and development of osteoporosis in adult or elderly individuals. However, the precise mechanism by which PPIs impact bone metabolism is unclear. One theory suggests that PPIs might reduce intestinal calcium absorption by increasing the gastric pH, thereby affecting the solubility of calcium salts obtained from the diet. Decreased calcium absorption results in increased risk of bone resorption and secondary hyperparathyroidism, leading to a negative calcium balance. Another theory suggests that suppression of gastric acid by PPIs leads to hypergastrinemia, which has a stimulatory effect on parathyroid glands. Parathyroid hormone (PTH) has been reported to play a pivotal role in calcium and bone metabolism, and increased levels of PTH stimulates bone resorption to maintain the serum calcium concentration. Indeed, long-term elevated PTH levels have been associated with decreased bone strength and quality. Yet another hypothesized mechanism by which PPIs impact bone metabolism is through direct inhibition of bone-specific proton pumps that are present in osteoclasts. Osteoclasts resorb bone by lowering the pH at their external ruffled border area. Tuukkanen et al., in an in vitro study, found many similarities between gastric acid production and osteoclast-mediated bone resorption, an observation that supports the concept that the basic cellular event in osteoclast-mediated bone resorption occurs by active H+ production at the site of active resorption. Periodontitis is characterized by microbe-associated host mediated inflammation that results in loss of periodontal attachment. The pathogenesis of periodontitis can be significantly influenced by the host response, which facilitates the subsequent loss of periodontal attachment initiated by bacteria. Once the immunoinflammatory processes begin, the connective tissue attachment and alveolar bone are destroyed, and the junctional epithelium migrates apically. Bone destruction by osteoclastic resorption, in addition to inflammation, tissue destruction, and detachment of junctional epithelium, often results in formation of periodontal pockets and, ultimately, tooth loss.

SPM{T_[47.0]} - contrast 1: PPI_interaction (Up neg > maintain neg [old, no cov]

A 1 sample t test across sleep condition for the PPI_interaction term (Upregulate negative > maintain negative*Amygdala BOLD signal). Left amygdala connectivity. Old only.

Collection description

This collection contains data from the so called "Stockholm Sleepy Brain Study". The specific study investigates the effect of sleep restriction on networks underlying cognitive reappraisal. The fMRI paradigm consisted of 45 negative pictures with an instruction to upregulate, downregulate or maintain the emotional response and 15 neutral pictures with the instruction to maintain.

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

emotional regulation task

Map type

T

This repository contains pre-processed data required to reproduce the results of the paper "Identification of transcription factor co-binding patterns with non-negative matrix factorization". The repository with the code can be found here: https://bitbucket.org/CBGR/cobind_manuscript/src/master/. Data include transcription factor binding sites (TFBSs) for 7 species from UniBind 2021 database, joined motif collection from CIS-BP and JASPAR 2022 databases and corresponding physical protein-protein interaction (PPI) data from STRING database.

Immunoprecipitation coupled to tandem mass spectrometry (IP-MS/MS) methods are often used to identify protein–protein interactions (PPIs). While these approaches are prone to false positive identifications through contamination and antibody nonspecific binding, their results can be filtered using negative controls and computational modeling. However, such filtering does not effectively detect false-positive interactions when IP-MS/MS is performed on human plasma samples. Therein, proteins cannot be overexpressed or inhibited, and existing modeling algorithms are not adapted for execution without such controls. Hence, we introduce MAGPIE, a novel machine learning-based approach for identifying PPIs in human plasma using IP-MS/MS, which leverages negative controls that include antibodies targeting proteins not expected to be present in human plasma. A set of negative controls used for false positive interaction modeling is first constructed. MAGPIE then assesses the reliability of PPIs detected in IP-MS/MS experiments using antibodies that target known plasma proteins. When applied to five IP-MS/MS experiments as a proof of concept, our algorithm identified 68 PPIs with an FDR of 20.77%. MAGPIE significantly outperformed a state-of-the-art PPI discovery tool and identified known and predicted PPIs. Our approach provides an unprecedented ability to detect human plasma PPIs, which enables a better understanding of biological processes in plasma.

Reducing carbon emissions is critical for addressing the challenges of climate change and represents an important step toward achieving the United Nations Sustainable Development Goals (SDGs). How to minimize disruptions to price levels within the economic system during the process of carbon reduction is an urgent issue that requires systematic investigation. In this paper, the nonlinear impact of carbon emissions on PPI (Producer Price Index) and CPI (Consumer Price Index) is deeply explored by using the Quantile-on-Quantile approach. In addition, the dynamic characteristics of this impact in the short-, middle- and long-term are systematically investigated through wavelet decomposition. It is found that, in general, there is significant heterogeneity in the impact of carbon emissions on PPI with the movement of the quantiles of the two factors. From a dynamic perspective, the impact of carbon emissions on PPI is not obvious in the short-term, shows a negative effect in the middle-term, and exhibits volatile effects in the-long term across different quantiles of PPI. In contrast, the effect of carbon emissions on CPI is relatively insignificant. However, in the middle-term and long-term, carbon emissions have negative effects on CPI within certain quantile intervals. Further analysis reveals that PPI exerts a positive impact on CPI, with this positive effect becoming more pronounced over time. These findings offer valuable insights for mitigating the disruptions caused by carbon reduction measures on production and consumer prices.

Protein-Protein, Genetic, and Chemical Interactions for Trepte P (2015):DULIP: A Dual Luminescence-Based Co-Immunoprecipitation Assay for Interactome Mapping in Mammalian Cells. curated by BioGRID (https://thebiogrid.org); ABSTRACT: Mapping of protein-protein interactions (PPIs) is critical for understanding protein function and complex biological processes. Here, we present DULIP, a dual luminescence-based co-immunoprecipitation assay, for systematic PPI mapping in mammalian cells. DULIP is a second-generation luminescence-based PPI screening method for the systematic and quantitative analysis of co-immunoprecipitations using two different luciferase tags. Benchmarking studies with positive and negative PPI reference sets revealed that DULIP allows the detection of interactions with high sensitivity and specificity. Furthermore, the analysis of a PPI reference set with known binding affinities demonstrated that both low- and high-affinity interactions can be detected with DULIP assays. Finally, using the well-characterized interaction between Syntaxin-1 and Munc18, we found that DULIP is capable of detecting the effects of point mutations on interaction strength. Taken together, our studies demonstrate that DULIP is a sensitive and reliable method of great utility for systematic interactome research. It can be applied for interaction screening and validation of PPIs in mammalian cells. Moreover, DULIP permits the specific analysis of mutation-dependent binding patterns.

Collection description

Subject species

homo sapiens

Modality

fMRI-BOLD

Analysis level

group

Cognitive paradigm (task)

face matching task

Map type

T

Producer Prices in China decreased 3.60 percent in June of 2025 over the same month in the previous year. This dataset provides the latest reported value for - China Producer Prices Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Cross-cultural investigation of psychopathy measures is important for clarifying the nomological network surrounding the psychopathy construct. The Psychopathic Personality Inventory-Revised (PPI-R) is one of the most extensively researched self-report measures of psychopathic traits in adults. To date however, it has been examined primarily in North American criminal or student samples. To address this gap in the literature, we examined PPI-R’s reliability, construct validity and factor structure in non-criminal individuals (N = 227) in Sweden, using a multimethod approach including psychophysiological correlates of empathy for pain. PPI-R construct validity was investigated in subgroups of participants by exploring its degree of overlap with (i) the Psychopathy Checklist: Screening Version (PCL:SV), (ii) self-rated empathy and behavioral and physiological responses in an experiment on empathy for pain, and (iii) additional self-report measures of alexithymia and trait anxiety. The PPI-R total score was significantly associated with PCL:SV total and factor scores. The PPI-R Coldheartedness scale demonstrated significant negative associations with all empathy subscales and with rated unpleasantness and skin conductance responses in the empathy experiment. The PPI-R higher order Self-Centered Impulsivity and Fearless Dominance dimensions were associated with trait anxiety in opposite directions (positively and negatively, respectively). Overall, the results demonstrated solid reliability (test-retest and internal consistency) and promising but somewhat mixed construct validity for the Swedish translation of the PPI-R.