Business Confidence in the United States decreased to 48.20 points in November from 48.70 points in October of 2025. This dataset provides the latest reported value for - United States ISM Purchasing Managers Index (PMI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset provides values for MANUFACTURING PMI reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

The QIF PMI Report (QPR) software generates a spreadsheet from a QIF (Quality Information Framework) file containing Product and Manufacturing Information (PMI). QIF is a unified XML framework standard for computer-aided quality QIF systems, available free to all implementers. QIF enables the capture, use, and re-use of metrology-related information throughout the Product Lifecycle Management (PLM) and Product Data Management (PDM) domains. QIF was created by the Digital Metrology Standards Consortium. PMI consists of annotations and attributes that define product geometry and product specifications. PMI includes annotations to specify Geometric Dimensioning and Tolerancing (GD&T), as well as non-geometric data such as surface texture specifications, finish requirements, process notes, material specifications, and welding symbols. GD&T is a symbolic language used to communicate tolerances on manufactured parts. PMI in QIF is defined by the QIF MBD (Model-based Definition). The spreadsheet that QPR generates creates a visual presentation of the PMI from its semantic definition in the QIF file. Measurements and QPids are also reported. QPR does not consider any of the graphical PMI in a QIF file.

China PMI: Mfg: Producer Price Index data was reported at 48.200 % in Nov 2025. This records an increase from the previous number of 47.500 % for Oct 2025. China PMI: Mfg: Producer Price Index data is updated monthly, averaging 58.900 % from Jan 2016 (Median) to Nov 2025, with 119 observations. The data reached an all-time high of 61.100 % in Oct 2021 and a record low of 40.100 % in Jul 2022. China PMI: Mfg: Producer Price Index data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Business and Economic Survey – Table CN.OP: Purchasing Managers' Index: Manufacturing.

Business Confidence in China increased to 49.20 points in November from 49 points in October of 2025. This dataset provides - China Business Confidence - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Neuronal information can be coded in different temporal and spatial scales. Cross-frequency coupling of neuronal oscillations, especially phase-amplitude coupling (PAC), plays a critical functional role in neuronal communication and large scale neuronal encoding. Several approaches have been developed to assess PAC intensity. It is generally agreed that the PAC intensity relates to the uneven distribution of the fast oscillation amplitude conditioned on the slow oscillation phase. However, it is still not clear what the PAC intensity exactly means. In the present study, it was found that there were three types of interferential signals taking part in PAC phenomenon. Based on the classification of interferential signals, the conception of PAC intensity is theoretically annotated as the proportion of slow or fast oscillation that is involved in a related PAC phenomenon. In order to make sure that the annotation is proper to some content, simulation data are constructed and then analyzed by three PAC approaches. These approaches are the mean vector length (MVL), the modulation index (MI), and a new permutation mutual information (PMI) method in which the permutation entropy and the information theory are applied. Results show positive correlations between PAC values derived from all three methods and the suggested intensity. Finally, the amplitude distributions, i.e. the phase-amplitude plots, obtained from different PAC intensities show that the annotation proposed in the study is in line with the previous understandings.

Verbs of seeing in Akkadian

This repository contains scripts and data for the paper "Language Technology Approach to Seeing in Akkadian".

/data

aug18-nolex.txt Lemmatized dataset from Oracc

results-pmi2-top50.log Script parameters for pmizer (see https://github.com/asahala/Pmizer)

results-pmi2-top50.tsv Results in .tsv format. Fields in the file:

keyword

translation from Oracc

collocate

translation from Oracc

period distribution

genre distribution

period and genre distribution

keyword freq

collocate freq

co-occurrence freq

PMI2 score

average distance between keyword and collocate (in words)

url to Korp (all links may not return results, as Korp Oracc had a major update in 2019: see https://www.kielipankki.fi/corpora/oracc/ for more info and user guide). Note that the co-occurrence of words (a, b) is symmetric, meaning that (a, b) == (b, a). Thus, if you search results in Korp using the links and do not get any results, you may have to switch the search boxes in reverse order.

period/genre-distribution-matrix.tsv Distribution of seeing verbs in different genres and periods as a matrix representation

Microbial succession has been suggested to supplement established postmortem interval (PMI) estimation methods for human remains. Due to limitations of entomological and morphological PMI methods, microbes are an intriguing target for forensic applications as they are present at all stages of decomposition. Previous machine learning models from soil necrobiome data have produced PMI error rates from two and a half to six days; however, these models are built solely on amplicon sequencing of biomarkers (e.g., 16S, 18S rRNA genes) and do not consider environmental factors that influence the presence and abundance of microbial decomposers. This study builds upon current research by evaluating the inclusion of environmental data on microbial-based PMI estimates from decomposition soil samples. Random forest regression models were built to predict PMI using relative taxon abundances obtained from different biological markers (bacterial 16S, fungal ITS, 16S-ITS combined) and taxonomic levels (phylum, class, order, OTU), both with and without environmental predictors (ambient temperature, soil pH, soil conductivity, and enzyme activities) from 19 deceased human individuals that decomposed on the soil surface (Tennessee, USA). Model performance was evaluated by calculating the mean absolute error (MAE). MAE ranged from 804 to 997 accumulated degree hours (ADH) across all models. 16S models outperformed ITS models (p = 0.006), while combining 16S and ITS did not improve upon 16S models alone (p = 0.47). Inclusion of environmental data in PMI prediction models had varied effects on MAE depending on the biological marker and taxonomic level conserved. Specifically, inclusion of the measured environmental features reduced MAE for all ITS models, but improved 16S models at higher taxonomic levels (phylum and class). Overall, we demonstrated some level of predictability in soil microbial succession during human decomposition, however error rates were high when considering a moderate population of donors.

Skeletal muscle index (SMI) is a promising predictor of clinical outcomes in patients with malignant diseases. As a simpler surrogate of sarcopenia-psoas muscle index (PMI), its predict value for overall survival (OS) after transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) has not been reported. To determine if changes in the PMI predicted OS in individuals with HCC treated with TACE. A retrospective analysis was performed in HCC patients treated with TACE between January 2018 and March 2019. The survival curve according to PMI was estimated by the Kaplan–Meier method and then compared by the log-rank test. Cox proportional hazards models were conducted to identify the prognostic factors for OS. Furthermore, the predictive abilities of PMI and SMI were compared by using Harrell’s concordance index (C-index). Two hundred and twenty-eight patients (175 men, mean age 59 ± 11 years) were analysed. The OS was less in patients with low PMI than those with high PMI (median OS: 16.9 vs. 38.5 months, p < .001). Multivariate analysis found that either PMI (hazard ratio [HR] = 0.64; 95% confidence interval [CI], 0.45–0.91; p < .001) or SMI (HR = 0.51; 95% CI, 0.36–0.72; p < .001) was significantly associated with OS. In the multivariate analysis, the C-index for PMI was 0.78 and 0.79 for SMI (p = .985). PMI is a simple tool to predict OS in HCC patients treated with TACE. The predictive ability of PMI is comparable to that of SMI. Key messagesLow psoas-muscle index is associated with decreased overall survival in hepatocellular carcinoma treated with transarterial chemoembolization (TACE).Psoas-muscle index has advantages of being faster and easier to acquire, which thus makes it more likely to achieve widespread clinical application. Low psoas-muscle index is associated with decreased overall survival in hepatocellular carcinoma treated with transarterial chemoembolization (TACE). Psoas-muscle index has advantages of being faster and easier to acquire, which thus makes it more likely to achieve widespread clinical application.

CODE.PY OUTPUT

Institutional Benchmarking and Regression Results

To contextualize institutional performance, we first compare India and Pakistan against the global mean of common-law economies on three governance indicators: Protecting Minority Investors (PMI), Enforcing Contracts (EC), and a composite index of the Legal-Political Environment. The global averages for common-law countries are:

• PMI: 18.6

• EC: 37.9

• Legal-Political Environment: 7.44 (on a 0–10 scale)

Relative to these benchmarks:

• India outperforms the PMI average by 5.6 ranks, but underperforms EC by 125.1 ranks and legal-political environment by 2.74 points.

• Pakistan underperforms on all three: +9.4 ranks in PMI (worse), +118.1 ranks in EC, and –4.24 points on legal-political environment.

These gaps suggest that formal investor protections (PMI) are stronger in India, but contract enforcement and broader institutional trust lag significantly in both countries.

Regression Analysis: Institutional Predictors of Governance Outcomes

We ran robust Ordinary Least Squares (OLS) regressions with Control of Corruption (cc), Rule of Law (rl), and Political Stability (pv) (from the Worldwide Governance Indicators) as predictors of country performance in both PMI and EC.

✅ Protecting Minority Investors (PMI)

• Model Fit: R² = 0.364; F(3, 182) = 46.91; p < 0.001

• Significant predictors:

  • Rule of Law (β = –62.74, p < 0.001): Strong negative relationship, consistent with countries with weaker rule of law having higher PMI ranks (i.e., worse protections).

  • Political Stability (β = +22.28, p < 0.001): Higher stability is associated with better (lower) PMI rank.

  • Control of Corruption (β = +15.91, p = 0.078): Marginally significant.

✅ Enforcing Contracts (EC)

• Model Fit: R² = 0.389; F(3, 182) = 52.32; p < 0.001

• Significant predictors:

  • Rule of Law (β = –47.55, p < 0.001): Again, weak rule of law predicts poor performance.

  • Political Stability (β = +11.27, p = 0.029): More stable environments enforce contracts more efficiently.

  • Control of Corruption was not significant (p = 0.61).

These results underscore the salience of Rule of Law and Political Stability in explaining variation in corporate governance effectiveness across countries.

Peer-Adjusted Z-Scores: Rule of Law and Judicial Independence

To further refine the comparison, we standardized India and Pakistan’s scores relative to global peers using z-scores:

• India: Judicial Independence z = +1.39, Rule of Law z = +1.28

• Pakistan: Judicial Independence z = +0.25, Rule of Law z = –0.95

This highlights India’s relative institutional strength in legal capacity, while Pakistan falls below global norms, particularly on rule of law.

CODE2.PY OUTPUT

Summary Statistics and Cross-National Comparison

We begin by comparing key governance indicators for India and Pakistan over the 1996–2020 period using data from the V-Dem dataset. Table X reports descriptive statistics for six core institutional quality variables:

• v2x_rule: Rule of Law

• v2x_jucon: Judicial Constraints on the Executive

• v2xlg_legcon: Legislative Constraints

• v2x_freexp: Freedom of Expression

• v2x_polyarchy: Electoral Democracy Index

• v2x_corr: Control of Corruption

Key Observations from the 23-year panel:

• Rule of Law (v2x_rule): India displays a high mean score of 0.579 (SD = 0.029), while Pakistan lags significantly behind at 0.237 (SD = 0.023).

• Judicial Constraints (v2x_jucon): India again leads with a mean of 0.814, compared to 0.537 for Pakistan.

• Control of Corruption (v2x_corr): Interestingly, Pakistan scores higher (0.868) than India (0.566), suggesting a potential data artifact or performative anti-corruption signaling.

These descriptive statistics show a consistent pattern of stronger rule-of-law institutions in India. However, India’s governance edge does not hold across all indicators—especially corruption control, which exhibits counterintuitive results.

T-Test Results: India vs. Pakistan

We formally test whether the differences in means between India and Pakistan are statistically significant using two-sample t-tests:

The highly significant differences in nearly all variables confirm that India and Pakistan follow distinct institutional trajectories—though India’s relative weakness in corruption control invites further scrutiny under the CMF framework.

Structural Breaks in India’s Democratic Governance

Using the ruptures package and a rolling t-test approach, we detect structural breakpoints in India’s democratic trajectory:

• Based on v2x_polyarchy, break years are identified at 2011, 2016, and 2021.

• The rolling t-test method suggests more granular shifts starting as early as 2001, with notable accelerations around 2011–2019.

These breakpoints align with major political and constitutional developments in India and support the CMF argument that formal continuity in legal benchmarks may obscure deeper institutional volatility.

CODE3.PY OUTPUT

Summary Statistics and Institutional Quality Comparison: India vs. Pakistan

We begin by reporting descriptive statistics for two core institutional variables—Control of Corruption (v2x_corr) and Judicial Constraints on the Executive (v2x_jucon)—drawn from the V-Dem dataset for the years 1996–2020:

• Control of Corruption (v2x_corr):

  • India: Mean = 0.566, SD = 0.027, indicating relatively consistent performance with moderate corruption control.

  • Pakistan: Mean = 0.868, SD = 0.051, suggesting surprisingly strong corruption scores, but with greater variability. This may reflect methodological distortions or performative anti-corruption institutions that lack substantive checks—a key focus of our Critical Macro-Finance (CMF) interpretation.

• Judicial Constraints (v2x_jucon):

  • India: Mean = 0.814, SD = 0.013, indicating strong and stable judicial oversight over executive actions.

  • Pakistan: Mean = 0.537, SD = 0.140, reflecting weaker, more volatile institutional constraints.

T-Test Results: Are India and Pakistan Statistically Different?

Two-sample t-tests confirm that these differences are highly statistically significant:

These results validate the hypothesis that India and Pakistan exhibit substantially divergent institutional trajectories—though not always in expected directions. India shows stronger judicial oversight, while Pakistan appears to outperform in corruption metrics, warranting

This paper brings together the concepts of molecular complexity and crowdsourcing. An exercise was done at Merck where 386 chemists voted on the molecular complexity (on a scale of 1–5) of 2681 molecules taken from various sources: public, licensed, and in-house. The meanComplexity of a molecule is the average over all votes for that molecule. As long as enough votes are cast per molecule, we find meanComplexity is quite easy to model with QSAR methods using only a handful of physical descriptors (e.g., number of chiral centers, number of unique topological torsions, a Wiener index, etc.). The high level of self-consistency of the model (cross-validated R2 ∼0.88) is remarkable given that our chemists do not agree with each other strongly about the complexity of any given molecule. Thus, the power of crowdsourcing is clearly demonstrated in this case. The meanComplexity appears to be correlated with at least one metric of synthetic complexity from the literature derived in a different way and is correlated with values of process mass intensity (PMI) from the literature and from in-house studies. Complexity can be used to differentiate between in-house programs and to follow a program over time.

■Application Instructions This grant and the following application form are for Small and Medium-Sized Enterprises Productivity Revolution Project Business Succession M& A This report was prepared for the “Types of Utilization of PMI Experts in the PMI Promotion Framework ” by grant (12 public offering). When applying in conjunction with the exit/rechallenge window, apply under the PMI Promotion Window Expert Utilization Type.

[Recommendation of Applications by 5 Business Days Prior to the Application Date] In this grant, it is expected that applications will be concentrated on the day before and the day of the application date due to the tendency of the application timing of the past public offering. In this public offering, due to examination schedule, there is a possibility that the application may not be accepted if the secretariat fails to point out deficiencies and return corrections several times for applications filed before the deadline, and if deficiencies are not resolved. To increase the likelihood of adoption, applicants who wish to have their applications pointed out or remanded should consider submitting their applications no later than 5 business days prior to the filing date (September 11, 2025).

■ Objectives and Overview Small and Medium-Sized Enterprises Productivity Revolution Project Business Succession M& A grant (Hereinafter referred to as "grant".) are persons from Small and Medium-Sized Enterprises and sole proprietors (Hereinafter, persons in Small and Medium-Sized Enterprises and sole proprietors are collectively referred to as "persons in Small and Medium-Sized Enterprises, etc.".). Business, etc., in which new initiatives are taken in the wake of Business Succession, business restructuring and business integration (Hereinafter referred to as the "Project".) Business Succession, business restructuring and business integration, and revitalize our country economy through productivity improvement.

■ Underlying Laws Law on the Proper Enforcement of budget for grants in Relation to grant, etc. Basic Law of Small and Medium-Sized Enterprises

■ Eligibility Individuals eligible for this grant must meet the following requirements of (1) - (14), and also Small and Medium-Sized Enterprises meet the requirement of "6. Subsidized Projects" as stated in the Public Offering Guidelines. In addition, in the case of the "Type of Utilization of PMI Experts (simultaneous application)," it is necessary to be a person in Small and Medium-Sized Enterprises, etc. who satisfies the requirements described in the separately published guidelines for the quota for utilization of experts.

• For the requirements for persons in Small and Medium-Sized Enterprises, refer to "Eligible Persons in Small and Medium-Sized Enterprises" in the Guidelines for Public Offering. *For joint applications, please refer to "7. See Application Unit.

  (1) Persons Eligible for the Assistance must have a base or residence in Japan and must carry on business in Japan. *In the case of a corporation, the registration of incorporation and the settlement and filing of accounts for 3 period are completed at the time of application. *The sole proprietor must be able to submit a copy of the tax return form B and the income tax blue return settlement form submitted to the tax office, as 5 years have passed since the date of submission of the "notification of opening of sole proprietorship" and the "application for approval of income tax blue return" to the tax office. (If tax filing and filing are done electronically, submit additional "details of mail" or "notice of receipt" (acceptance result) to confirm acceptance. If there is no "Mail details" or "Receipt notification" (acceptance result), "Tax payment certificate (2) Certificate of the amount of income" or "Taxation certificate (with the amount of income)" must also be submitted) * For foreign nationals, attach a certificate of residence clearly stating the items of "nationality/region," "Period of stay, etc.," "Status of residence," "Expiration date of period of stay, etc.," and "Classification under Article 30, 45." (2) Subsidy recipients must be people in Small and Medium-Sized Enterprises who contribute to the local economy. A person in Small and Medium-Sized Enterprises, etc. who is contributing (or plans to contribute) to the regional economy by, for example, maintaining or creating jobs in the region or supporting the region with technology or specialty products that are the region's strength. •It contributes to the regional economy by maintaining and creating jobs in the region. •There are many purchases from the region where they are located or neighboring regions (intra-regional purchases). •Utilization of regional strengths (Technology, specialty products, tourism, sports, etc.) is being addressed. •Sales to regions other than the region in which the company is located or neighboring regions (sales outside the region) are large (including sales resulting from an increase in demand in the region due to inbound travel, etc.). •It plays a central role in projects that challenge new businesses and contribute to the local economy. •Regardless of the above, Others is making efforts to revitalize the regional economy by bringing ripple effects to the regional economy from the growth of the enterprises concerned. (3) The recipient of the subsidy or the director of the corporation is not an anti-social force such as an organized crime group. They should not have any relationship with antisocial forces. Incidentally, those who receive funds such as investment from anti-social forces are also excluded from the scope. (4) The subsidized person must not have a compliance problem. (5) Subsidy recipients must submit a feasibility report, etc. after completion of the Subsidy Project by the deadline. (6) Subsidy recipients must not violate the Public Offering Guidelines, etc. (7) Persons eligible for assistance shall respond appropriately to questions and requests for additional materials from the Secretariat. (8) The grantee agrees that the secretariat shall, when it deems necessary, notify grant, as amended, of matters relating to the adoption and issuance of the grantee and other approvals and notifications of results by the various secretariats. (9) That the grantee agrees that under no circumstances shall the Secretariat bear the various expenses incurred in delivering Others grant Application in the event of an event such as the return of grant. (10) Suspension of designation or suspension of designation for grant has not been implemented by the the Ministry of Economy, Trade and Industry or Small and Medium-Sized Enterprises Regional Innovation Agency. (11) grant All information including personal information provided at the time of application, use, submission of project report, etc. may be provided by the secretariat to the State and Small and Medium-Sized Enterprises Regional Innovation Agency for the purpose of project implementation, effective policy formulation, management support, etc. (provision of various information to applicants, etc.), and then disclosed by statistical processing, etc. while ensuring anonymity, or utilized as described in this Others Public Offering Guidelines. By filing this application, consent to use this data shall be given. In examination of grant, information on applications, issuance, etc. in other grant pertaining to the applicant held by grant Secretariat under the jurisdiction of the SME Agency will be used. In addition, for the efficient execution of grant, the parties agree to share information regarding the application and issuance of grant with other grant bureaus under the jurisdiction of the SME Agency. (12) Please make an application to grant *, which is under the jurisdiction of the Small and Medium Enterprise Agency, with the understanding that if you fail to meet the requirements for additional Wage Increases points, etc., within the past 18 months from the time of application, you will receive a significant deduction unless a justifiable reason is found. *As of July 2025, there were: grant for Promoting Productivity Improvement in Manufacturing, Commerce and Services (after the 17 public offering); IT Introduction Support Program for Improving Productivity in Services (after the 2024 public offering of grant for IT Introduction); grant for Sustaining Small Enterprises (after the 15 public offering); Business Succession M& A grant (after 8 Public Offering), Growth-oriented Small and Medium-Sized Enterprises R & D Support Project (r&d support program for growth-oriented technology smes Project) (after the 2024 Public Offering), grant for Business Reconstruction (after the 12 Public Offering), (including the Labor Saving Investment Subsidy Project in Small and Medium-Sized Enterprises (after 1 Public Offering)) (13) You must be able to cooperate with surveys, questionnaires, etc. related to subsidized projects requested by the secretariat. (14) grant beneficiaries of past Resource Takeover grant or Business Succession Takeover grant that properly performed commercialization reports by the due date (Those who have failed to submit a feasibility report despite the obligation to do so are excluded from the scope.).

  [Eligible Small and Medium-Sized Enterprises Persons] Pursuant to Article 2 of the Basic Law for Small and Medium-Sized Enterprises, Small and Medium-Sized Enterprises Persons in this grant are defined as follows: Industry Classification Definition Manufacturing Others (Note 1) Companies with less than 300 million JPY in capital or total contributions, or companies with less than 300 regular employees and sole proprietors Wholesale Trade Companies with less than 100 million JPY in capital or total contributions, or companies with less than 100 regular employees and sole proprietors Retail Trade Companies with

Mean values are represented by shades of color, with darker indicating more relative abundance among the taxa within a body site or soil. (XLSX)

ISM Manufacturing New Orders in the United States decreased to 47.40 points in November from 49.40 points in October of 2025. This dataset includes a chart with historical data for the United States ISM Manufacturing New Orders.

AimEarly childhood caries is the most common chronic infectious disease in children in the United States. This study, which is part of a larger, longitudinal study exploring oral microbiological components of caries development in children, reports on the impact of total mutans streptococci (MS), total acid tolerant bacteria and Candida species on the development of dental caries in a subset of these children. Of particular interest was the relationship between caries development and co-colonization of mutans streptococci and Candida species.MethodsChildren between the ages of 12 and 47 months displaying no evidence of dental caries were recruited for a longitudinal study (n = 130). Twelve age- and gender-matched pairs were selected. In each pair, one child developed caries during the study, and one did not. Whole mouth plaque samples were collected by swab at baseline and every 6 months thereafter for a duration of 18 months and spiral plated for microbial counts (CFU/ml). Cut-offs based on percent of total cultivable flora were designated for all microbial measures. A scoring system designated the Plaque Microbial Index (PMI) was developed for use in statistical analyses to assess potential predictive factors for caries risk assessment.ResultsChildren who developed caries were significantly more likely to harbor higher percentages of acid tolerant bacteria (p = 0.003), MS (p < 0.001) and have Candida species present (p < 0.001) at ≥1 visit leading up to caries onset. Mean PMI scores derived from the aforementioned microbial measures, were higher for caries active children than caries free children (p = 0.000147). Co-colonization of MS and Candida species was significantly associated with caries development (p < 0.001) and detection of both at the same visit had a 100% positive predictive value and 60% negative predictive value for caries development.ConclusionIn children who developed caries, there was a statistically significant association with the percent of total flora that was acid tolerant, the percent of MS, the presence of Candida and co-colonization of MS and Candida species. Combining these microbial measures into PMI scores further delineated children who developed caries from those who remained caries-free. These microbiological measures show potential as predictive factors and risk assessment tools for caries development.

The combined use of multiple omics methods to answer complex system biology questions is growing in biological and medical sciences, as the importance of studying interrelated biological processes in their entirety is increasingly recognized. We applied a combination of metabolomics, lipidomics and proteomics to human bone to investigate the potential of this multi-omics approach to estimate the time elapsed since death (i.e., the post-mortem interval, PMI). This “ForensOMICS” approach has the potential to improve accuracy and precision of PMI estimation of skeletonized human remains, thereby helping forensic investigators to establish the timeline of events surrounding death. Anterior midshaft tibial bone was collected from four female body donors in a fresh stage of decomposition before placement of the bodies to decompose outdoors at the human taphonomy facility managed by the Forensic Anthropological Center at Texas State (FACTS). Bone samples were again collected at selected PMIs (219, 790, 834 and 872 days). Liquid chromatography mass spectrometry (LC-MS) was used to obtain untargeted metabolomic, lipidomic and proteomic profiles from the pre- and post-placement bone samples. Multivariate analysis was used to investigate the three omics blocks by means of Data Integration Analysis for Biomarker discovery using Latent variable approaches for Omics studies (DIABLO), to identify the reduced number of markers that could effectively describe post-mortem changes and classify the individuals based on their PMI. The resulting model showed that pre-placement bone metabolome, lipidome and proteome profiles were clearly distinguishable from post-placement profiles. Metabolites associated with the pre-placement samples, suggested an extinction of the energetic metabolism and a switch towards another source of fuelling (e.g., structural proteins). We were able to identify certain biomolecules from the three groups that show excellent potential for estimation of the PMI, predominantly the biomolecules from the metabolomics block. Our findings suggest that, by targeting a combination of compounds with different post-mortem stability, in future studies we could be able to estimate both short PMIs, by using metabolites and lipids, and longer PMIs, by including more stable proteins.

26 circonscriptions de PMI recouvre chacune un territoire géographique d'une à plusieurs villes, selon leur taille. Elles sont animées par un responsable de circonscription (médecin, puéricultrice ou sage-femme). Chaque responsable de circonscription (RC) se situe en interface entre le service central de PMI et les directrices de centres de PMI et les équipes de terrain. Il est garant de la mise en œuvre des missions, dispositifs et procédures (protection de l’enfance, agrément des assistantes maternelles…) et coordonne l’activité de PMI, de planification familiale et des modes d’accueil sur sa circonscription. Le RC anime des projets et est également garant du partenariat institutionnel avec l’ensemble des acteurs locaux intervenant dans le champ large des compétences de la PMI.

Attributs :

• id_circons_pmi int4
• nom_circons_pmi varchar : Nom de la circonscription de PMI
• nom_equipement varchar : nom de l'équipement
• adresse varchar : adresse
• code_postal int4 : code postal
• ville varchar : ville
• tel bpchar : Téléphone
• fax bpchar
• code_insee int4
• observation varchar : Observations
• geom geometry

Origine

Géocodage de listing DEF (centres PMI et Circonscription de PMI) et fusion des communes de la BDTOPO IGN pour constitution des zonages d'intervention des circonscriptions de PMI

Organisations partenaires

Département de la Seine-Saint-Denis

Liens annexes

• Voir sur Géoportail93

Discover the booming Single Sideband Modulator market! This in-depth analysis reveals key trends, drivers, restraints, and forecasts (2025-2033), including market size, CAGR, and regional breakdowns. Explore the competitive landscape and understand the future of this technology in 5G, aerospace, and defense sectors.

ISM Manufacturing Prices in the United States increased to 58.50 points in November from 58 points in October of 2025. This dataset includes a chart with historical data for the United States ISM Manufacturing Prices Paid.

Mean values are represented by shades of color, with darker indicating more relative abundance among the taxa within a body site or soil. (XLSX)