It was not related to the profession (p = 0.163), gender (p = 0.103), or years of service (p = 0.610). Conclusions: This paper outlines the prevalence of MD in care settings and describes its relationship with profession, gender, and seniority. There is no patient care without the care of health professionals: knowing and fighting MD improves the safety of the treatments provided and the quality perceived by patients.Background: The oncology setting is characterized by various complexities, and healthcare professionals may experience stressful conditions associated with ethical decisions during daily clinical practice. Moral distress (MD) is a condition of distress that is generated when an individual would like to take action in line with their ethical beliefs but in conflict with the healthcare facility’s customs and/or organization. This study aims to describe the MD of oncology health professionals in different care settings. Methods: Descriptive quantitative study was conducted in the Operating Units of the Istituti Fisioterapici Ospitalieri in Rome between January and March 2022. The investigated sample consisted of the medical and nursing staff on duty at the facility, who were given a questionnaire through a web survey. Besides a brief sociodemographic form, the MD Scale-Revised questionnaire was used for data collection. Results: The sample consisted of nurses (51%) and physicians (49%), predominantly working in surgeries (48%), and having 20–30 years of service (30%). MD was higher among healthcare professionals, in medicine than that ing in corporate organizations, surgeries, or outpatient clinics ( Oncology is considered one of the largest areas and encompasses many competencies that healthcare professionals can and should perform in an increasingly complex and ever-changing environment . MoreoveMD was first defined by Jameton (1984) , who desThe various studies conducted over time have shown that other factors, in addition to organizational factors, are sources of MD: powerlessness or lack of adequate knowledge, clinical situations such as aggressive treatments given to terminally ill patients, pain management patterns, maintenance of the appropriate patient quality of life standards, and conflicts between staff, patient and family members ,7,8,9,10MD can be expressed as psychological distress, fatigue, disengagement, or alienation from the profession .It is a complex phenomenon frequently experienced in departments where ethical conflicts are linked to technological progress and high-intensity work environments, or when operators are involved in decisions concerning the end of life. It can, on the one hand, be defined as healthcare personnel being required to have ever greater competence about the ability to make ethically valid decisions aimed at greater patient protection, and on the other hand, as these staff themselves maybe lack both resources and individuals, as well as lacking adequate coordination within the staff and organizational resources. MD has implications not only for the well-being of the individual, but also for care outcomes and, more generally, for the entire social and healthcare system; it is not uncommon for healthcare professionals experiencing a situation of stress and emotional exhaustion to express their anger at a colleague or patient, and even to adopt an attitude of “avoidance” toward the conflict situation, denying all care provision and nurturing the idea of leaving the profession . In someAccordingly, the literature reports how human resources play a strategic role because they can influence the outcome of the care process; therefore, an institute needs to identify the phenomenon of MD among healthcare providers at an early stage through specific rating scales. Among all healthcare professionals, the nurse appears to be the most at risk of developing MD, mainly when employed in critical areas . FurtherTo date, most of the quantitative studies in the literature have been conducted in intensive care units and on nursing staff. Studies investigating the prevalence of MD in medical staff involved in the care of oncology patients are still few. Therefore, this study aims to describe the MD of healthcare professionals (physicians and nurses) working in oncology in different clinical settings. Evaluating this aspect is essential for understanding the problem and taking proper corrective measures based on a more elastic organizational management view.This quantitative descriptive study was conducted in the Operating Units of the Istituti Fisioterapici Ospitalieri (IFO) in Rome between 18 January and 24 March 2022. The investigated sample consisted of the medical and nursing staff on duty at the facility, who were given a questionnaire through a web survey. Inclusion criteria for recruitment were as follows: being healthcare professionals (physicians and nurses) employed at the IFO and adhering to the present study by completing informed consent forms. Within the IFO, other medical and nursing healthcare operators deal with non-cancer patients, are there in training but only for a short time, or belong to outsourcing companies that do not have an institutional email, a factor which would not permit the photographing of the figures involved in their daily professional activity for the focus of our attention. Therefore, the criteria for excluding the sample were precise: physicians and nurses employed in the care of non-oncology patients; physicians and nurses in specialty training at the IFO; healthcare professionals from outsourcing companies or freelancers who did not have an institutional email address, such as students. Before the start of the study, the IFO Central Committee’s approval was obtained , and the study’s purpose and participation were explained to participants via email.For organizational reasons, excluding a priori healthcare professionals not directly involved in oncology patient care was not possible, although they did not meet the study criteria. This part of the population was excluded retrospectively when responses were received.In addition to the administration of the questionnaire, the following data were collected: unit of service, gender, and years of service: .The MD Scale-Revised questionnaire (MDS-R) , adminisThe MDS-R is a questionnaire with 14 items investigating four components: the futility of care, perception of unethical behavior, communication between staff and families, and poor teamwork . Using ap-value < 0.05 was considered statistically significant. All statistical analyses were performed with SPSS software .Descriptive statistics were produced for all variables of interest. Categorical variables were summarized using frequencies and percentage values, and continuous variables by median values and their range. Nonparametric Kruskal–Wallis or Mann–Whitney tests were applied to analyze potential differences between groups when appropriate. A The questionnaire was sent to a total of 677 healthcare professionals. Overall, 299 healthcare professionals (44%) joined the study and completed the questionnaire upon acceptance of informed consent. Out of the total number of questionnaires collected, 29  were not analyzed for the study because they were filled out by healthcare providers not directly involved in the care of oncology patients. The total number of questionnaires surveyed was 270. The sample consisted of nurses (51%) and physicians (49%), predominantly female (66%), working in surgeries (48%), and with 20–30 years of service (30%) .p = 0.001) among the different affiliation facilities. In the specific comparison between individual facilities, a significant difference in the global score at MSD-R emerged between medicine and corporate organizations (p = 0.034) for which the level of MD was higher among healthcare providers working in medicine than in corporate organizations; between medicine and outpatient clinics (p = 0.007), the level of MD was higher among healthcare professionals working in medicine than in outpatient clinics; between medicine and surgeries (p = 0.010), the level of MD was higher among healthcare professionals working in medicine than in surgeries. We measured MD in the different facilities by grouping the operating units into five main categories: outpatient clinics, medicine, surgeries, diagnostics, and corporate organization. The results showed a significant difference in the overall score at the MSD-R (p = 0.037), no significant difference emerged in the pairwise subscales. Regarding Deceptive Communication, an overall significant difference resulted between the different facilities (p = 0.008) and in the sub-comparison between surgeries and outpatient clinics (p = 0.024) and between medicine and outpatient clinics (p = 0.006). In Deceptive Communication, surgeries and medicine had higher MD levels than in outpatient clinics. p = 0.169).Based on the rating scale items analysis, a significant difference was found between the affiliated facilities in the Futility Rate and Deceptive Communication subscales. Regarding the Futility Rate, it was found that the five units had a different distribution of scores; however, while we obtained a significant difference overall (p = 0.163) or the individual scales: Futility Rate (p = 0.105), Ethical Misconduct (p = 0.122), Deceptive Communication (p = 0.168), Poor Teamwork (p = 0.061). No significant differences arose either between males and females in the overall MDS-R score (p = 0.103) or the individual scales: Futility Rate (p = 0.821), Ethical Misconduct (p = 0.221), Deceptive Communication (p = 0.076), and Poor Teamwork (p = 0.245).We compared the MD scores of male and female physicians and nurses and their years of seniority. The results showed no significant differences between physicians and nurses in the overall MDS-R score (p = 0.610) and the individual scales showed no statistically significant differences: Futility Rate (p = 0.513), Ethical Misconduct (p = 0.430), Deceptive Communication (p = 0.828), and Poor Teamwork (p = 0.585)  .p = 0.018) than those who had never thought about leaving their employment. In the subscale analysis, significant differences resulted between these two groups regarding Ethical Misconduct (p = 0.008) and Poor Teamwork (p < 0.001). In the difference between genders, males reflected the same trend as the total sample ; among females, there was no difference in the score on the overall scale, but a significant difference was found in Poor Teamwork (p < 0.001). When we compared physicians and nurses, it emerged that physicians who in the past had thought of leaving or had left their job had higher scores on the overall scale (p = 0.049) in the Ethical Misconduct (p = 0.018) and Poor Teamwork (p = 0.019) subscales. A significant difference was found only among nurses in the Poor Teamwork subscale (p = 0.001). When we related job position to years of seniority, it emerged that those with 0–10 years of service had a higher score in the Poor Teamwork subscale (p = 0.031), those who have worked 10–20 years had a higher score in the Deceptive Communication subscale (p = 0.030), and those who have worked 20–30 years had higher scores in Ethical Misconduct (p = 0.005), in Deceptive Communication (p = 0.047), and Poor Teamwork (p = 0.013). Finally, those working for more than 30 years had higher values in Poor Teamwork (p = 0.006).In analyzing the relationship between MD and job position, to the question, “Have you ever thought about leaving your job because of the ethical distress experienced in your work environment?”, it was found that those who had thought about leaving or had left their jobs in the past had a significantly higher score on the overall scale (p = 0.007), Ethical Misconduct (p = 0.001), Deceptive Communication (p = 0.018), and Poor Teamwork (p = 0.001). In medicine, differences appeared in Ethical Misconduct (p = 0.021) and Poor Teamwork (p = 0.002). Regarding the question “Are you currently thinking of leaving your job?”, the only notable finding resulted in diagnostics, where those thinking of leaving their employment had higher scores in Ethical Misconduct (p = 0.043) (Data upon request.)In the relation between job positions and different facilities, significant differences resulted between those who thought about leaving or quitting their job and those who never thought about leaving diagnostics or medicine. In diagnostics, differences were found in the overall score  [017 [2], The second relevant item is Ethical Misconduct, which achieved significantly higher scores in the overall difference between those who had decided to leave or had left their jobs and those who had not thought of doing so or done so, specifically for the following categories: physicians, males, those working in their 20s to 30s, and those working in medicine. This is a factor that has already been explored in the literature in terms of its various constituent components: the burden of inadequate care provided by other healthcare professionals, the weight of the decision-making hierarchy , and theThe study’s limitations concern being single-center and the lack of comparison between the sample of 44% who answered the questionnaire and the remaining 66%who did not join the study. Given that the study was conducted on the institution’s in-house staff, we maintained a tremendous focus on privacy, and their demographic age is not even available; therefore, we do not have data that would allow us to make a comparison between the two groups.The purpose of this study was to describe the MD of healthcare professionals (physicians and nurses) working in oncology in different clinical settings. The results showed that levels of MD increased in healthcare professionals working in medical units. MD does not change based on the type of profession practiced, gender, or years of seniority, while Poor Teamwork leads to job abandonment. The data that emerges on Poor Teamwork deserves attention because, in some ways, it represents one of the key elements of the problem: when a professional take an ethically relevant decision, even if judged formally consistent with presumed professional duties, this does not mean that it does not involve any cost in terms of emotions and feelings about oneself or the other subjects involved. In this sense, the decision-making process should be conceived and carried out within an open communication and coordination system. This figure deserves more in-depth investigations of the medical and nursing staff and adequate support interventions.Despite the need for further investigation, the data acquired from the investigated Italian population may help us to better understand the problem and help the oncology team.


This study aimed to investigate the state of the immune system and liver function of affected turkey hens and to determine a possible nutritional influence on the pathogenesis. Hematological analyses, clinical chemistry analyses, and determination of vitamin E and selenium liver concentrations at 2 examination dates  as well as feed analyses throughout the whole fattening period were performed. The results indicate a subacute inflammatory process in flocks with the occurrence of green livers at the early fattening stage and acute inflammation in individuals with green livers at the late fattening stage. It is suspected that an inadequate nutrient supply contributes to the development of green liver discoloration, but further research under experimental conditions is needed.Previous studies indicate that green liver discoloration in fattening turkeys, which has occurred with a high prevalence in organically reared turkeys, is not caused by a certain pathogen but by a variety of factors weakening the immune system. Other than vitamin D3 concentrations were analyzed in feed samples for each of the five feeding phases during each trial. The results of the hematological analyses, clinical chemistry analyses, and determination of vitamin E and selenium liver concentrations were statistically evaluated between: (i) individuals with and without GL, and (ii) individuals from flocks with and without turkeys with GL. At both fattening stages, the occurrence of GL was characterized by an inflammatory reaction. A subacute inflammatory reaction was detected in the early fattening stage, indicating a viral cause of the disease. In the late fattening stage, acute inflammation indicated a bacterial cause of the disease. The results of the feed sample analyses of the different flocks were generally quite homogeneous. However, the nutrient and energy content of the feed likely contribute to GL pathogenesis.Green liver discoloration (GL) in fattening turkeys is suspected to be a multifactorial disease complex with a compromised immune system as the key factor. This study aimed to identify the formal pathogenesis of GL and to investigate possible nutritional influences. A total of 360 Bronze turkey hens out of 10 flocks from 5 fattening farms were necropsied for detection of GL during 2 consecutive trials on 2 examination dates each . At each examination date, hematological and clinical chemistry analyses, as well as determination of vitamin E and selenium concentrations in the liver, were carried out in 6 hens with (if applicable) and 6 hens without GL, representing a total of 130 individuals. Raw nutrient, energy, amino acid, bulk and trace element, and vitamin E and D The occurrence of green livers (GL) in turkeys has been observed for decades, especially in association with arthritis, osteomyelitis, or both, and was first described as green liver syndrome or turkey green-liver osteomyelitis complex (TOC) in the United States ,2,3,4. IBayyari et al.  found tuHuff et al.  found thThe aim of this study was to identify a possible systemic inflammatory process in the pathogenesis of GL and to determine if the liver function of affected Bronze turkey hens is compromised. In order to work out the formal pathogenesis of GL on flock level, in addition to examining differences between individual turkey hens with and without GL, it was aimed to investigate if significant differences occurred between turkeys from flock samples in which GL was present in at least one hen as opposed to flocks without GL at the respective time point of examination. It was attempted to clarify the possible influence of feed nutrient contents on Bronze turkeys’ immune systems and as such, on the development of GL.The examinations did not require notification or approval, as in accordance with the German Animal Welfare Act .n = 16 for each examination, trial, and flock was required to detect green discolored livers in organically reared hens. Taking into consideration that, on the one hand, a sufficient number of carriers in each sample had to be obtained, and, on the other hand, all turkeys had to be purchased and taken from the food chain, 20 randomly sampled individuals were taken from each flock at each examination date . In some flocks, male turkeys were falsely integrated within the hen flocks (and only noticed during postmortem examination); as with young age, sex is not easily identifiable on the farms. If toms were included in the random sample, these were not further examined and not included in the study. The turkeys were taken to the Clinic for Birds and Reptiles at the University of Leipzig, housed overnight, and provided with feed and water. The next day, stunning  and euthanasia by exsanguination through a unilateral neck cut severing the carotid artery and the jugular vein were performed. All turkeys were examined for GL and six hens without and (if applicable) six hens with GL were chosen for further examination, which included hematological and clinical chemistry analyses as well as determination of hepatic vitamin E and Se concentrations. Overall, samples were taken from 130 Bronze turkey hens, of which 67 animals were examined at the early and 63 animals at the late fattening stage. Based on the selection criteria of a high prevalence of GL within the flocks during the predecessor study ,7, five 9 per liter. The EDTA blood was used for the determination of packed cell volume (PCV) and Hb concentration. PCV was determined using a hematocrit centrifuge . The determination of Hb followed the method described by Kyaw et al. [During the turkeys’ bleeding, blood was collected in EDTA tubes , heparin tubes (Sarstedt AG & Co.), and Eppendorf tubes without coagulant . The blood in the EDTA and heparin tubes was stored in a cooling box. Blood smears were prepared from native blood and fixed and stained using DiffQuik . A total leucocyte count was carried out using the estimation method . Differew et al. . Eight sAlbumin (ALB), AP, aspartate aminotransferase (AST), bilirubin (BIL), Ca, cholesterol (CHOL), creatine kinase (CK), GGT, GLDH, urea, lactate dehydrogenase (LDH), LDL, magnesium (Mg), inorganic phosphate (Pi), triglycerides (TG), TP, and UA were analyzed photometrically using the analyzing system Cobas C311  and the associated reagents. The reliability of the measured parameters was tested daily using the intended controls (Roche Diagnostics Deutschland GmbH). Bile acids were determined using the same analyzing system and an appropriate reagents kit . Analysis of GPX concentration was performed using the Cobas C311 and appropriate test kit (Ransel Randox), as well as the intended controls . Given that GPX is located in the membrane of erythrocytes, the results are presented related to PCV and Hb in order to compensate for possible changes in erythrocyte numbers or dehydration effects. Eight samples were not eligible for PCV and Hb analysis due to coagulation and were therefore not used for GPX determination. One sample was not suitable for Mg and Ca determination. One sample was not suitable for any clinical chemistry analysis. The globulin concentration (TP minus ALB concentration), A:G ratio, and calcium to phosphate ratio (Ca:Pi) were calculated using the presented results. Liver tissue samples were taken and stored in a polystyrene box filled with dry ice. At the end of each examination day, the samples were stored at −80 °C until further processing. Determination of the vitamin E liver concentration was achieved by solvent extraction with ethanol, followed by hexane extraction and separation by reversed-phase high-performance liquid chromatography using δ-tocopherol as an internal standard ,47. For In total, 59 feed samples were collected and analyzed. These 59 samples were made up of one sample from every flock for each of the five phase feeds applied  and some additional samples: one more starter feed and phase 1 sample were collected. In the appropriate two trials, feeds with different textures (granulated and pelletized) were offered in one of the phases each, and both types were analyzed. Furthermore, a retention sample from the manufacturer was analyzed for one starter feed in addition to the sample taken directly from the farm, as some of the first analytical results varied greatly from the other samples. The results from the original and retention samples were very similar; only those from the retention sample were used for statistical analyses. Two farms combined the complete diet with greater amounts of grains in both trials, so the grains were analyzed as well (five samples of oat and one sample of wheat).3 and E were analyzed or calculated. This was achieved according to the official methods of the Association of German Agricultural Inspection and Research Institutes (VDLUFA) in the latest updated version [Dry matter (DM), crude ash (ASH), CP, crude fat (CFAT), crude fiber (CF), nitrogen-free extracts (NFE), starch, sugar (SU), apparent metabolizable energy corrected by nitrogen (AMEn), amino acids, aspartic acid (Asp), taurine (Tau), threonine (Thr), serine (Ser), glutamic acid (Glu), glycine (Gly), alanine (Ala), valine , Cys, Met, isoleucine (Ile), leucine (Leu), tyrosine (Tyr), phenylalanine (Phe), histidine (His), Lys, arginine (Arg), OH-proline and proline (Pro), bulk elements Ca and P, and trace elements Zn, Mn, and Se as well as vitamins D version  at the I version , except  version . The vit version .In each flock, the five different diets were offered during differing time periods throughout the fattening period. In order to be able to compare the offered nutrient contents with feed recommendations, the fattening period was divided into six supply phases (with some flocks going into a seventh phase) according to the feed recommendation periods by the GfE , which ip-value was less or equal to 0.05. Data were examined for normal distribution using the Shapiro–Wilk test. When two groups were compared, the Student’s t-test for independent samples was performed in case of a normal distribution and the Mann–Whitney U test if data did not follow a normal distribution. When correlations were calculated, Pearson’s correlation coefficient  or Spearman’s rank correlation coefficient  were calculated. GGT and bilirubin were not included in the statistical analyses because the concentration of only 7 and 46 (out of 130) samples were above the detection limit, respectively. As age-dependent differences for several parameters have been described [Statistical data analysis was performed using IBM SPSS Statistics for Windows, version 28.0 . Results were considered significant if the double-sided escribed ,17,18, aGL amongst the examined Bronze turkey hens occurred with an overall prevalence of 8.7% during the early fattening stage (with a range of 0.0% to 68.4% within the different flock samples) and 9.4% in the late fattening stage . Lymphocyte counts were higher in the early fattening stage (p = 0.048), whereas higher heterophil counts (p = 0.025) and higher H:L ratios (p = 0.030) were detected in turkeys with versus those without GL in the late fattening stage (Bronze turkey hens with GL showed higher WBC numbers at both examination times as opposed to those without (ng stage . 9/L) with heterophilia (>30 × 109/L), of which five had GL. At the early fattening stage, Bronze turkeys from flock samples with GL showed higher numbers of WBC (p = 0.003), heterophil (p = 0.010), and basophil granulocytes (p ≤ 0.001) as well as monocytes (p = 0.034), whereas in the late fattening stage, basophil granulocytes were higher (p = 0.041) in turkeys from flock samples with the occurrence of GL compared to those without . As ALB concentration gradually decreases in infectious and inflammatory diseases [p ≤ 0.001 for individuals; p = 0.004 for flocks). A high globulin concentration can indicate an acute inflammatory process in which especially α-globulins increase rapidly [A decrease in the A:G ratio is considered indicative of acute or chronic inflammation resulting from a rise in alpha-, beta-, and/or gamma-globulins, and often a fall in ALB concentration ,59. Besidiseases , the res rapidly . To the  rapidly ,58.p = 0.004 for individuals; p = 0.028 for flocks; Higher GPX activities (relative to the PCV) were measured in individuals with GL and in hens from flocks with the occurrence of GL versus those without in the early fattening stage . On the contrary, at days 70 to 75 of fattening, a more chronic inflammation process seems to take place in flocks affected by GL . These results complement the findings by Cuta et al. [p = 0.026; p = 0.022), AST (p = 0.028), CK , or LDH (p = 0.001) values were determined for individuals or flocks or both without GL at variable examination dates  and LDL (p = 0.049) plasma levels were lower in the turkeys from flocks with than from flocks without the occurrence of GL  and a higher Ca:Pi ratio . No toxic levels were reached, and no negative effects could be identified . A general feature of feed from all flocks was the energy level dropping progressively  below the recommended level in the late phases of the fattening period [The results of the feed sample analysis were generally quite homogeneous . Variatig period ,55, starg period ,68,69. Ag period ,71,72. Ag period ,73. Threg period ,75.Some of the results of the feed analysis in this study differ significantly from the results of the feed analysis of organically reared turkeys by Krautwald-Junghanns et al. . In thisp ≤ 0.05 for all correlations; To find a possible relation between the prevalence of GL within a turkey flock and the analyzed feed energy and nutrient content, the concentration offered within each feeding phase was checked for correlation with GL prevalence on both examination dates . A negative correlation between GL prevalence and the supply of several amino acids was striking for both examination dates (p ≤ 0.05), but not Met and Thr [p ≤ 0.05). It is known that vitamin D₃ is involved in the immune response and can increase disease resistance [As mentioned before, the amino acid supply was lower than recommended, especially in the late fattening period. Of the amino acids that are regarded as most important for the avian immune system, Arg and Lys showed a negative correlation with GL prevalence .Overall, the homogeneity of the results of the feed analyses leaves the calculation of correlations difficult. For example, the amino acid supply was deficient for all examined flocks in some phases, so there is no control group with a sufficient supply that could be compared. The evaluation of energy and nutrient supply in each phase was carried out with reservation because only the time periods in which certain feeds were offered could be calculated, but not the actual feed intake, as this had not been documented in sufficient detail on the farms. Additionally, only one batch of each phase feed was analyzed per trial and flock, while several batches were fed during each phase, especially towards the end of fattening. Furthermore, grains, dietary supplements which were additionally fed in most of the flocks, and—in one flock—vegetables could not be considered when calculating the turkeys’ supply within the different phases, because the fed amounts were not documented in detail. The examined grains differed greatly from the complete feed samples  and hints at a correlation with the development of GL and therefore suggests approaches for improvement. However, due to the limitations of the study, no direct influence of certain nutrients on the pathogenesis of GL can be proven with certainty, and further research under experimental conditions is recommended.


In January 2023, the derogation loophole was closed on “emergency authorisations” for the use of three out of five neonicotinoids in all EU states. In this study, we analysed the sorption/desorption behaviour and kinetic parameters of acetamiprid and thiacloprid, the two neonicotinoids that are still approved for use, either regularly or under emergency authorisations in the EU, and widely used worldwide. Sorption and desorption curves in four soils with different organic matter content were analysed using four kinetic models, namely, Lagergren’s pseudo first-order model, two-site model (TSM), Weber–Morris intraparticle diffusion model and Elovich’s model. Kinetic parameters were correlated to soil physico-chemical characteristics. To determine the mutual influence of soil characteristics and sorption/desorption parameters in the analysed soils, a factor analysis based on principal component analysis (PCA) was performed. Even though the two insecticides are very similar in size and chemical structure, the results showed different sorption/desorption kinetics. The model that best fits the experimental data was TSM. Thiacloprid showed a more rapid sorption compared to acetamiprid, and, in all soils, a higher proportion sorbed at equilibrium. Intra-particle diffusion seemed to be a relevant process in acetamiprid sorption, but not for thiacloprid. Desorption results showed that acetamiprid is more easily and more thoroughly desorbed than thiacloprid, in all soils. The kinetic behaviour differences stem from variations in molecular structure, causing disparate water solubility, lipophilicity, and acid–base properties.  Nowadays, global agriculture has emerged as one of the most important branches of industry, representing the basis of the development of each country. However, modern agriculture tends to utilize all the constituents of the soil, considering only economic profitability, without maintaining the quality of arable soil ,2,3. TheHowever, the toxicity of some of the members of the neonics family to non-target organisms, both vertebrates and mammals, is now well established ,11,12,13Kd when the isotherms are linear, or Kf when the isotherms are described by the conventional Freundlich model. The parameter KOC is obtained when respective sorption constants are normalized to organic carbon content (OC), KOC = K/OC. The use of this parameter is justified when the sorption is taking place exclusively in the soil organic fraction, which is assumed to have the same thermodynamic characteristics in different soils, and the sorption isotherms are linear  and 1/Y represent the sorbed insecticide amount (mg/kg) during the fast phase (approximately until the 1. h of the reaction), and the amount in the slow sorption/desorption reaction, respectively.The desorption process can be expressed by Equation (16):t = 0, the linear form of Equation (16) was obtained:Integrating Equation (16) at the boundary conditions ® V.12.0 . As a measure of the goodness of fit of the experimental results and the results obtained by modelling, the following parameters were used: coefficient of multiple determination (R2), the scaled root mean squared error (SRMSE), and the minimum error level of χ2 test (err-%). The χ2 test can be used as the best parameter to test the goodness of fit, since it includes freedom degrees for each kinetic model at the desired level (5%) and compares the calculated χ2 value with the χ2 standard value [χ2 < χ2tabulated at the chosen level of significance. The minimum error (err-%) at which the χ2 test is passed can be calculated by Equation (17):All experimental data were presented as a mean of three determinations with standard deviation. Sorption/desorption experimental results were tested using the application of non-linear regression models available with the software Wolfram Research Mathematicard value . A suitaMexp and Mpred are the experimental and predicted data, χ2tab is tabulated χ2 value for appropriate degrees of freedom at p = 0.05.The model with the smallest error (err-%) can be used as the most appropriate, since it describes the experimental data in the most robust way . In Equa® software V.14.0.  at a significance level of p < 0.05. The effect of physico-chemical soil characteristics on the insecticide sorption/desorption parameters obtained by mathematical modelling were tested by correlation matrix. Furthermore, to determine the mutual influence of soil characteristics and sorption/desorption parameters in the analysed soils, as well as similarities and correlations between variables, a factor analysis based on principal component analysis (PCA) was performed on the pooled analytical data.Descriptive statistics and all other statistical analyses were performed by the StatisticaOut of the four tested mathematical models , the two-site model showed the best fit to our experimental data. The data showed that, even though the two insecticides are very similar in size and chemical structure, their sorption/desorption kinetic behaviours differ. Thiacloprid showed more rapid sorption compared to acetamiprid, and a higher proportion sorbed at equilibrium, in all soils. Intra-particle diffusion seemed to be a relevant process in acetamiprid sorption, but not for thiacloprid. Desorption results showed that acetamiprid is more easily and more thoroughly desorbed than thiacloprid, in all soils. These differences in the kinetic behaviour can be attributed to variations in molecular structure, namely, the presence of the sulphur-containing thiazolidine ring in thiacloprid, which leads to disparities in water solubility, acid–base properties, lipophilicity, and, consequently, the interactions with soil constituents.


The increasing Cesarean Section (CS) rates may be attributed to women’s increasing requests for elective CS. High Fear of Childbirth (FOC), especially among nulliparous women, may be significantly associated with CS preference without medical indications. The current study aims to investigate the impact of childbirth fear on the mode of delivery preference among nulliparous women.A cross-sectional correlational study was performed in the Maternal and Children Hospital (MCH) from the beginning of October 2022 to the end of February 2023 and incorporated a convenience sample of 342 nulliparous women. The data was collected using a self-reported questionnaire comprising participants’ demographic and obstetrics characteristics and the FOC questionnaire. A logistic regression model examined the relationship between CS preference and the other independent variables.p < 0.05). Moreover, the participants who had increased fear of harming or distressing the infant, fear from pain, fear from the body’s ability to give birth, fear from not being involved in decision-making, and overall FOC had a higher probability of choosing CS as the preferred delivery mode compared to the participants who had lower fear (p < 0.05).The results indicated that 74.3% of the nulliparous women preferred vaginal delivery, while 25.7% preferred Cesarean Section. Concerning childbirth-related fear, the highest mean scores were related to fear of clinical procedures, fear of harming or distressing the infant, and fear of pain 5.19 ± 1.13, 5.12 ± 1.27, and 5.09 ± 1.22, respectively. High FOC was present among 74.6%, moderate in 17.3%, and severe in 6.7% of the participants. Logistic regression analysis showed maternal age and monthly income were the significant sociodemographic determinants of choosing CS as the preferred delivery mode (Having high FOC increases the CS preference among nulliparous women. Increased fear of harming or distressing the infant, fear from pain, fear from the body’s ability to give birth, and fear from not being involved in decision- making seem to be significant dimensions of childbirth fear associated with CS preference among nulliparous women. Childbirth is often seen as an important milestone and is a life-affirming event for numerous women. Pregnancy and childbirth are unique experiences for each woman. They can trigger various emotions, such as happiness, hope, anxiety, and fear, making such experiences subjective, multidimensional, and complex . It is cFear of childbirth is described as a collection of anxious feelings and thoughts related to a woman’s experience of childbirth . SeveralFOC can lead to psychological consequences such as anxiety, traumatic stress symptoms, and postpartum depression . In addiA recent study indicated that nulliparous women experience higher FOC than multiparous women . If suchAlthough previous research has demonstrated the relationship between a woman’s FOC and elective CS on maternal request , no prio2.2.1.The current study is a cross-sectional correlational study performed in the Maternal and Children Hospital (MCH) affiliated to the Ministry of Health in Najran City, Saudia Arabia. MCH is the only large hospital specializing in maternal and children services in the Najran region; therefore, it serves a large number of the population. The data was collected from the four outpatient clinics that provide antenatal services in MCH hospital.2.2.The study incorporated a convenience sample of 342 nulliparous women. The inclusion criteria were nulliparous, free from pregnancy-related complications and diagnosed mental illness , singleton pregnancy, the third trimester of pregnancy, aged 18 to 40 years, not advised by a physician for CS, and agreed to participate in the study.The sample size was calculated based on the Cocharane formula Where z = 1.96 for a 95% confidence interval; P = cesarean section rate in Saudi Arabia from a previous study 41%; , d is thThe following chart illustrates the participants’ distribution .2.3.The data collection instrument is a self-reported questionnaire composed of four parts.Part I: Participants’ demographic and obstetrics characteristics. This part collects data such as age, residence, occupation, educational level, and satisfaction with monthly income. Obstetric history includes gestational age, regularity of antenatal care (Irregularity of ANC was considered based on whether a participant missed two or more ANC visits), and the number of abortions. Part II: the mode of delivery preference, assessed by one dichotomous question to evaluate whether the woman prefers vaginal birth delivery or CS. Part III is the FOC questionnaire: It was developed by Slade et al. to assess pregnant women’s FOC and composed of 20 items rated on a 4-point Likert scale: strongly disagree (0), disagrees (1), agrees (2), and strongly agree (3). The scoring system was inverted in negative items numbers 1, 3, 5, 8, 10, 14, 17, and 20. The scale was designed to evaluate 10 dimensions related to childbirth fear (each dimension contains two items), namely fear of inability to identify and plan for emergency events, fear of infant harm or distress, fear of pain, fear of the body’s capability to give birth, fear from intranatal or postnatal self-harm, fear from clinical procedures, fear from not being involved in decision making, fear from being alone, fear from the loss of control, and fear from unknown. The total scale score ranged from 0 to 60, with a higher score indicating higher fear. The woman was considered to have low (0–15), moderate (16–30), high (31–45), and severe fear (46–60) based on her score , 2022. T2.4.Data collection started from October 2022 to February 2023. The data collection team was present in the antenatal clinic waiting areas from 9 a.m. until 2 p.m. twice weekly for 5 months. Because the study participants were nulliparous women with low-risk pregnancies, randomization was not applicable. Therefore, any participants who fit the inclusion criteria were included in the study using convenience sampling. At the beginning of each data collection session, the data collector explained the study purpose to the participants and then got informed consent. Then, she was given the self-reported questionnaire. The data collection team was present to answer any questions and make required clarifications. If the participant was excluded or refused participation, she was replaced by another one until the required sample size was reached.2.5.The data collection team was composed of two researchers and two data collectors with bachelor’s degrees in nursing and previous experience in data collection. Before data collection, two meetings were held to explain the study proposal, instrument of data collection, research ethics, and data collection procedures. The data collectors discussed any needed clarifications with the researchers. Any questionnaire containing missing data was excluded during the data quality check before data entry to IBM; therefore, 16 questionnaires were excluded from the analysis.2.6.The study proposal was approved by the Deanship of Scientific Research and then by the Najran Health Affairs Ethical Committee (IRB Log Number 2022-02 E). Additionally, permission for data collection was granted by the MCH administration. Before each data collection session, the data collector provided a detailed explanation of the study’s purpose and obtained informed consent from each participant. All data collected was anonymous, and participants were assured that their information would remain confidential and that they had the right to refuse participation without any repercussions on their service. The collected data was treated with the utmost confidentiality and used only for research purposes.2.7.p < 0.05. Before regression, the data was checked for multi-correlations, and the total regression model was checked with the Cox and Snell R Square goodness of fit test.After completing data collection, data were entered into IBM version 23. The data were described using descriptive statistics such as frequencies, percentages, means, and standard deviation (SD). Among the analyzed data, residence, occupation, level of education, satisfaction with monthly income, regularity of antenatal care, and preferred mode of delivery were categorical variables. While age, gestational age, number of abortions, and FOC were numerical. The total FOC and subscales were obtained by summing items. Binary logistic regression was utilized to determine the CS preference predictors, and the significant level was considered at 3.p = 0.000] and , respectively. Similarly, Women with unsatisfied family income  had a lower probability of choosing CS as the preferred delivery mode when taking satisfied family income as a reference , eference .p = 0.029], , , and , respectively. Moreover, the women who had increased fear from the loss of control, fear from the unknown, and overall FOC had a higher probability of choosing CS as the preferred delivery mode than the participants who had lower fear , , and , respectively.As shown in 4.The decision regarding the mode of delivery is difficult and affected by numerous factors. These factors include women’s health and obstetric conditions. In the absence of medical indication, the mode of delivery decision requires months and long discussions to be made and is strongly affected by the woman’s preferences and FOC, especially in nulliparous women . FOC is In the present study, the deepest concern of the nulliparous woman regarding FOC was related to fear of clinical procedures, harming or distressing the infant, and pain. In addition, a significant proportion of the women were afraid of self-harm intra-natal or postnatal, fear from the loss of control, and fear of the unknown. High total FOC was present in around three-quarters of the nulliparous women, moderate in 17.3%, and severe fear in only 6.7% of the participants. In the same line, Mortazavi et al. found that FOC was moderate to high among nearly two-thirds of their participants, while severe fear was present among only one-tenth. They added that FOC was strongly associated with old maternal age and lower satisfaction with pregnancy. The major concern regarding FOC among their participants was the loss of control and loneliness, and these two concerns were also present among the current study participants .On the contrary  reportedRegarding the mode of delivery, one-quarter of the current study participants preferred CS. A similar rate of CS preference was reported in Hong Kong, where 22.9% of their participants considered CS as safer and more controllable compared to vaginal delivery; however, they did not ignore the benefits of vaginal birth . In SaudOn the contrary, a study conducted in the United Arab Emirates reported that only 9.4% of their participants preferred CS compared to 25% in the current study . This diIn the current study, maternal age and monthly income were the significant sociodemographic determinants of choosing CS as the preferred delivery mode. Younger women aged less than 20 years have a higher probability of CS preference when compared to older women. Similarly, Women with an unsatisfied family income had a lower probability of choosing CS as the preferred delivery mode. Young women were reported to prefer CS delivery in the United Arab Emirates because they may have little knowledge regarding the serious CS consequences . TherefoA logistic regression analysis clarified that the participants who had increased fear of harming or distressing the infant, fear from pain, fear from the body’s ability to give birth, and fear from not being involved in decision-making had a higher probability of choosing CS as the preferred delivery mode eight times than the participants who had lower fear. Moreover, the women who had increased fear from the loss of control, fear from the unknown, and overall FOC had a higher probability of choosing CS as the preferred delivery mode than the participants who had lower fear. In Sutherland, Sluijs et al. tried to explain the relationship between FOC and the preferred mode of delivery. They stated that high FOC was associated with CS preference, and women who preferred vaginal birth and delivered with CS had significant postpartum FOC. On the other hand, women who preferred CS and delivered vaginally had low postpartum FOC . Further4.1.Our study has numerous strengths: It is the first study conducted in Saudi Arabia to investigate the impact of FOC on the mode of delivery preference among nulliparous women. Our study used recent, reliable, and valid instruments to evaluate FOC. The sample size was calculated using a standardized equation with a 95% confidence level. However, the current study did not evaluate some CS-associated factors or previous history of infertility. In addition, the current study randomization was not applicable; therefore, we used a convenience sample.5.High FOC was present in around three-quarters of the participants, and severe fear in 6.7% of the participants. One-quarter of the nulliparous women preferred CS as the mode of childbirth. Having high FOC increases the CS preference among nulliparous women. Increased fear of harming or distressing the infant, fear of pain, fear of the body’s ability to give birth, and fear of not being involved in decision-making seem to be significant dimensions of FOC associated with CS preference. In addition, maternal age and monthly income were the significant sociodemographic determinants of choosing CS as the preferred delivery mode.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving humans were approved by the Najran Health Affairs Ethical Committee, Najran Health Affairs. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.WE and HI conceived and designed the study. WE, HI, and MA gathered the data. HI conducted the statistical analysis. WE and HI wrote the first draft. WE, HI, and MA contributed essentially with result analysis and in the revision of the manuscript. All authors contributed to the article and approved the submitted version.


The logopenic variant of primary progressive aphasia (lvPPA) shows different features from the non-fluent (nfvPPA) and semantic (svPPA) variants of PPA. Although language impairments remain the core symptoms, studies have highlighted the presence of executive disorders at the onset of the disease. Nevertheless, the results are contradictory, particularly in lvPPA. The aim of this study was to explore the executive profile of lvPPA. We compared executive functioning in lvPPA with the other two variants of PPA, Alzheimer’s disease (AD) and a cognitively healthy group. In total, 70 patients with PPA, 32 patients with AD, and 41 healthy controls were included. They underwent a comprehensive executive battery assessing short-term and working memory, inhibition, flexibility, planning, and initiation. The analyses showed significant differences between the lvPPA group and the control group, except on visuospatial spans and the Stroop test, and between the lvPPA group and the other PPA groups and the AD group for several tasks. Thus, this research highlighted the existence of an executive dysfunction from the onset of the disease in lvPPA but also in the other two variants of PPA. Primary progressive aphasia (PPA) identifies a clinical neurodegenerative syndrome, with the earliest symptom being a decline in speech and language. Knowledge of the clinical profile of PPA continues to evolve and become more accurate.A progressive disorder of language associated with the atrophy of the frontal and temporal regions of the left hemisphere was first described by Pick in 1892 ,4,5. DurReferring to the clinical syndrome, AD is the most common neurodegenerative disease, accounting for an estimated 60% of all neurodegenerative pathologies . RegardiEFs are defined as high-level cognitive abilities . In thisAt the onset of PPA, EFs are believed to remain relatively unaffected ,21. HoweHowever, these studies are difficult to compare as the authors did not always use the same tasks to investigate the assessed functions. Thus, the results of these studies are often contradictory . MoreoveIf we now compare lvPPA to AD, as Rahul and Ponniah  remind uThe objectives of our study were twofold. First, we sought to provide new insights into EF impairment or preservation in lvPPA, i.e., the variant that has been least often studied in the literature . Indeed,To carry out this research, five groups with a total of 143 participants were included. First, over a three-year period, a sample of individuals with PPA was recruited, especially at the Research, Resources, and Memory Center at the North University Hospital Center, Saint-Etienne, France. A few participants were also recruited at Purpan Hospital, Toulouse, and Beauvais Hospital. In total, 22 patients with lvPPA, 22 patients with nfvPPA, and 26 patients with svPPA were recruited.Inclusion criteria for the study were a clinical diagnosis of PPA, a consultation by a neurologist at an investigation center for cognitive difficulties, a magnetic resonance image within six months of initial evaluation, and agreement to participate in the study after reading the information letter.All PPA participants met the criteria for PPA . They unThe mean age was 68.95 (±9.3) for patients with lvPPA, 69.55 (±4.8) for those with nfvPPA, and 66.27 (±10.2) for those with svPPA. The mean durations of education in years were 11.59 (±2.5), 11.68 (±2.8), and 12.42 (±2.7) for the three groups, respectively. Statistical analyses showed no significant difference between groups for age and education level. The duration of the disease at the time of testing varied from 23 to 31 months for all PPA groups. We also recruited 32 individuals with early-stage AD (MMSE scores above 20 out of 30) at the Research, Resources, and Memory Center in North University Hospital Center. Their mean age was 65.66 (±9.5) and the mean education duration was 11.69 (±2.7) years.Forty-one education- and age-matched healthy volunteers were recruited. Their mean age was 65.73 (±10.1) and the mean education duration was 12.07 (±3.7) years. To be included, they had to present no history of neurological or psychiatric disorder and no cognitive complaints.Three patients and two control participants were left-handed.Demographic data on the participants and their scores on the Mini-Mental State Examination (MMSE) , a widelThe study was conducted according to the guidelines of the Declaration of Helsinki and approved by the University of Mons ethics committee. All participants (patients and controls) gave written informed consent for their participation. All of them agreed to take part in the study. Data were anonymized before the statistical analyses were completed.All participants underwent neuropsychological testing with a comprehensive battery of executive function tasks, which included the verbal forward and backward digit span subtest from the WAIS-IV  and the p value of < 0.05 was adopted to determine the statistical significance.Statistical analyses were conducted using IBM SPSS version 25.0. Prior to conducting these analyses, all variables were checked for normality of distribution using Shapiro–Wilk test. Since variables were non-normally distributed, group comparisons of demographic data were carried out with nonparametric tests and chi-squared test for gender. Group comparisons on neuropsychological measures were investigated using Kruskal–Wallis tests and Mann–Whitney tests. A Group comparisons of the demographic data revealed no significant difference between groups regarding age, gender, laterality, and years of education.Scores for each group and between-group differences in EF measures are presented in p < 0.05), except the forward visuospatial span , backward visuospatial span , and Stroop interference tasks . Patients in the nfvPPA and AD groups had significantly lower scores for all the tasks than controls (p < 0.0001). The svPPA group scored significantly lower than controls only on the RFFT design fluency task .Relative to healthy controls, the lvPPA group showed significantly poorer scores than the control group for most tasks , forward visuospatial span , backward visuospatial span , Stroop interference , and RFFT design fluency . The forward digit span, TMT A and B, and Tower of London tasks did not distinguish between the two groups (p > 0.05). The svPPA group performed significantly better than the lvPPA group on the TMT A , TMT B , forward digit span , and backward digit span  tests. Analyses did not reveal any significant difference for the other tasks. Finally, patients with AD performed significantly worse on only the forward visuospatial span  and backward visuospatial span  tasks. The other tasks did not differentiate the two groups (p > 0.05).In comparing the lvPPA group to other clinical groups, patients with nfvPPA showed significantly poorer scores for the following tasks: backward digit span  and backward digit span  tests. The analyses did not show any significant difference between the two groups for the other tasks (p < 0.05). The AD group scored significantly lower than the svPPA group on all tasks (p < 0.05). Finally, the analyses showed a significant difference between the nfvPPA and svPPA groups for all tasks (p < 0.05). Participants in the nfvPPA group performed significantly worse than participants in the svPPA group. As for other between-group differences, participants in the nfvPPA group performed significantly worse than participants in the AD group on the forward digit span . Patients did not score much lower than the control group in inhibition levels, as described in the literature [p = 0.010), and lvPPA patients performed poorly on initiation, which has not been reported in other studies [In the comparison of the lvPPA and control groups, the analyses showed a deficit in verbal working memory, as the lvPPA group scored significantly lower than the control group . The literature indicates that svPPA patients present few executive difficulties at the onset of the disease [p = 0.030). Indeed, some patients had difficulties with this task, which however does not involve language or semantic memory, unlike a verbal fluency test. These results indicate that patients may exhibit a mild initiation deficit, linked to frontal lobe dysfunction [Our results show only one significant difference between these two groups for RFFT design fluency  and backward (p = 0.020) visual spans, results on which were lower for the nfvPPA group. Thus, few of the EFs that were assessed differed between the nfvPPA and lvPPA groups. These results support recent studies by identifying few tasks that significantly differentiate between these two groups [p > 0.0001) is similarly impaired in both groups, as described in the literature [p = 0.21) between the two groups, with lower scores for the nfvPPA group, as described in another recent study [The lvPPA and nfvPPA groups’ results were significantly different for visuospatial short-term and working memory, evaluated by the forward , verbal short-term memory (p = 0.007), verbal working memory (p = 0.010), and cognitive flexibility (TMT B) (p = 0.005) differentiated the two groups. These results corroborate recent studies that found a significant difference between these two PPA variants, specifically for short-term and auditory–verbal working memory [Processing speed (TMT A) . Moreover, it is interesting to note that this study highlighted preserved verbal short-term memory (assessed by the forward digit span) in AD but an impairment in lvPPA, which may contribute to the differential diagnosis of these disorders. Integrating visuospatial span tests into assessments would be relevant since they make it possible to distinguish between patients with lvPPA and those not only with AD but also with nfvPPA [In comparison to the lvPPA and AD groups, only visuospatial short-term and working memory, evaluated by forward and backward visual spans, respectively, distinguished between the lvPPA and AD groups (h nfvPPA . The path nfvPPA . It woulh nfvPPA .p < 0.05). These results are in line with the literature, which states that EFs are relatively preserved in svPPA and impaired in nfvPPA [A comparison of the nfvPPA and svPPA groups demonstrated significant differences between these two groups for all the tests assessing EFs, with the nfvPPA group scoring lower (n nfvPPA . Recent n nfvPPA ,24,27,36n nfvPPA . Contrarn nfvPPA ,36, and n nfvPPA ,32,40. TRegarding the nfvPPA and AD groups, on the forward and backward digit spans, which assess verbal short-term and working memory, respectively, the nfvPPA group scored significantly lower than the AD group. A recent study showed a significant difference between these two groups for verbal short-term memory . These rFinally, analyses of the svPPA and AD groups showed significantly lower performance in the AD group than the svPPA group for all EFs, except verbal short-term memory. Thus, these results provide additional information to help differential diagnosis and support the data from the literature. For instance, verbal working memory, flexibility, inhibition, initiation, and planning are all less efficient in AD than in the semantic form of PPA ,73,75,76Overall, for the in-between group analyses, the nfvPPA and svPPA patients differed the most on EF tests, followed by the svPPA and lvPPA groups. The nfvPPA and lvPPA groups did not differ significantly on the EF tests. Although patients essentially express a complaint related to language, executive disorders are observed from the onset of PPA ,41. ReceOur study has some limitations. The main limitation was the small sample size in each group, which could explain that the findings are at odds with some studies, especially for executive functioning in nfvPPA and lvPPA groups. Other factors including disease severity, language contamination, and the inherent variation at the individual level account for the varying findings across studies. The statistical analysis containing non-parametric tests has restricted the generalization of our results. Another limitation was the lack of qualitative analyses. It would have been interesting to study the types of errors made in the tests and compare them in the different groups. We plan to conduct this qualitative analysis. Another limitation is that only the cognitive domain was studied. An evaluation of the behavioral and social components would have provided additional information. Finally, a longitudinal study would have been valuable. Future research is warranted to provide qualitative analyses.This study has provided new insights and led to a better characterization of lvPPA. Patients evaluated at the early stage of the disease showed the moderate impairment of EFs, with the preservation of inhibition and visuospatial short-term and working memory. In comparison with the lvPPA and AD groups, only the forward and backward visual spans distinguished the groups. Visuospatial span task performance is preserved in lvPPA patients, unlike the AD group, which showed a deficit. Moreover, the preservation of forward digit span performance in AD and impairment in lvPPA were also observed, which may contribute to the differential diagnosis of these two disorders. Integrating visuospatial span tests in the cognitive assessment of PPA would be relevant since they make it possible to distinguish lvPPA patients from both AD and nfvPPA patients. To conclude, the findings support other recent studies and suggest that, although language deficits remain the core symptoms of PPA, executive dysfunction is also observed at the early stages, even though some studies have described EFs as remaining relatively unaffected, and they are currently excluded from the consensual diagnostic criteria ,41. DysfFinally, our research highlights a need for standardized tools that can be used for studying the complex aspects of EFs, so that disorders that may go unnoticed at the onset of the disease can be accurately diagnosed ,81.


Data from 882 children and adolescents were analyzed . In females, Fmax/BW values were higher in younger age but remained constant in adolescence. vmax, hmax and Pmax/mass increased in childhood, reaching a plateau in adolescence. In males, vmax, hmax and Pmax/mass showed a constant increase and the Fmax/BW remained lower. Children with obesity showed lower Fmax/BW, hmax, vmax and the NMI, hence, lower velocity per relative force unit and less efficient jump. The centiles should be used to monitor motor development in childhood. The NMI is a surrogate for motor efficiency.Jumping mechanography provides robust motor function indicators among children. The study aim was to develop centiles for the single 2-leg jump (S2LJ) in German children and adolescents and to identify differences in children with obesity. Data were collected in 2004–2021 through the German DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study. All participants  performed annually an S2LJ aiming for maximum height on a Ground Reaction Force Platform. LMS (lambda-mu-sigma), including resampling, was used to develop centiles for velocity (v Evaluation of muscle function is crucial in childhood, e.g., to understand the muscle–bone relationship and/or monitor the motor development of the child ,2. Musclmax/Bodyweight), relative power (Pmax/mass), speed and maximum jump height (hmax) are common parameters assessed during the measurement. Thus, this test could allow a rather simple examination of various domains of physical fitness, such as strength, power or coordination, in a differentiated manner.Jumping mechanography is valid and reliable to measure ground reaction forces associated with a standardized jump in children ,5. Such EFI was defined as In the previous literature, there have also been some attempts to quantify the efficiency of the jump by combining individual measurement parameters  developing of age-dependent centile curves for the kinetic parameters of an S2LJ among healthy boys and girls from the 6th to the 18th year of age in Germany using data from the open cohort DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study; (ii) introducing a new mechanography-related parameter to quantify jump efficiency; (iii) evaluating jumping performance during childhood development; and (iv) identifying differences in the jump characteristics of children with obesity, implementing the presented centiles and parameters, hypothesizing a probably differently coordinated jump in children with obesity. Ideally, the presented tools can help monitor motor development in children.Every year since 1985, a small group of infants from the metropolitan Dortmund area are recruited in the open cohort DONALD study. These children participate in observational study visits throughout infancy, childhood and adolescence, until adulthood. Within the framework of the DONALD study, detailed data on nutritional intake, growth, development, metabolism and health status are collected at regular, usually annual, intervals. These data can be used to examine the diet–health or growth–health relationships, but also to create reference data from healthy children and adolescents . The staAnthropometric data were collected at all visits at the study center. Body height has been recorded with an approximation of 0.1 cm using a digital telescopic wall-mounted stadiometer . Body weight has been measured with an electronic scale  at an approximation of 0.1 kg . We used®, NOVOTEC Medical GmbH, Pforzheim, Germany). According to the study protocol, the children, only wearing underwear and no shoes, performed a single two-leg jump (S2LJ), aiming for maximum height. The children stood on the GRFP with each foot placed on one section of the GRFP. The GRFP consists of two individual smaller platforms, which have the capacity to record vertical force separately for the left and right leg. The counter-movement jump was performed allowing free movement of arms and without any other restrictions. The children were instructed to jump as high as possible using both feet and landing on both feet  = 0Thus, the correlation coefficient r depends on the age of the child and the time interval between two S2LJ measures. With the dataset of n = 1445 measurements performed by girls and 1617 measurements by boys, the correlation coefficients r were calculated for all above defined intersections for the ages between 6 and 18 years. Since the Z-scores have a standard normal distribution, the Z-scores for their change is equal to the effect size of the size and can interpreted similar to Cohen’s d.p value significance < 0.05) for non-normally distributed data, and to measure the effect size of the differences we calculated Cohen’s d. Since we compared Z-scores, no further adjustment for age or sex was needed. In addition, mixed effect linear models were used to confirm the results of the above-mentioned analysis, since these models can handle better the hierarchical structure of the data .To analyze the relationship between obesity and the jumping characteristics of healthy children, jump parameters of participants with obesity were compared with their values from the non-obese participants . For the2 for girls and 18.8 kg/m2 for boys. To investigate the relationship between increased bodyweight and the S2LJ parameters, we compared the measurements in participants with obesity (BMI ≥ 97th centile) at the time of measurement  and 847 normal weight children (3005 measurements).Study sample characteristics are presented in max, hmax, Pmax/mass, Fmax/BW, the NMI and side-difference of the impulse for girls and boys, truncated to three decimal places, are presented in max, hmax and Pmax/mass showed a significant increase in both females and males, until late childhood. This trend continued in males until adulthood, but showed a plateau in females, starting from the 13th year of age. On the other hand, the Fmax/BW, as well as the side-difference, remained very stable, especially after the age of 8 to 9 years for both sexes. Thus, the NMI showed an evolution according to the one of Pmax/mass, showing a continuous increase during childhood and adolescence in boys, but reaching a plateau in adolescent girls.The detailed centiles for the vmax/mass and the NMI in the interceptions of measurements performed at different age classes for females and males. We summarized the results in Further, we calculated the correlation coefficient r for the Z-scores of the Pmax/BW (p < 0.001) as well as for hmax (p < 0.001), Pmax/mass (p < 0.001) and vmax (p < 0.001), in comparison to the S2LJs of their non-obese peers  in comparison to their non-obese peers. The effect size was highest for vmax with a Cohen’s d of 1.3 and least for Fmax/BW with a Cohen’s d of 0.51  with obesity (BMI Z-score ≥ 1.88). The study of their jump characteristics showed significantly lower Z-scores for F of 0.51 .max/mass, vmax, Fmax/BW and the NMI is also graphically demonstrated, using a non-linear LOESS regression, in max and Pmax/mass scores, compared to their obese peers.The association of the BMI and the Z-scores for Pmax , Pmax/mass , Fmax/BW  and the NMI  and showing no correlations with the DIMP Z-scores .To confirm our findings, we also performed a mixed effect linear regression to investigate if the Z-scores of BMI are correlated with the Z-scores of the jump parameters. The results were comparable with the aforementioned analysis, with BMI Z-scores significantly negatively correlating with the Z-scores for vIn the current study, we presented the first sex-specific and age-related reference centiles based on longitudinal data for jumping mechanography outcomes in German children and adolescents from 6 to 18 years of age (using the S2LJ with free swinging arms). Our findings complement previously published data of cross-sectional studies for the S2LJ assessment, but also other jumping assessments in healthy children ,9,10,19.max, vmax and Pmax/mass, as well as for the newly defined Nerve–Muscle Index (NMI) for younger children, in comparison to those in adolescence. In females, hmax, vmax, Pmax/mass and the NMI reached a plateau in adolescence, around the 15th year. In males, the increase was steeper, and the plateau was reached around the 18th year. The Fmax/BW was higher in females during childhood than in males but declined with age, faster during childhood and slower during adolescence. In males, the Fmax/BW was, in general, lower than that of females of the same age and remained constant throughout childhood and puberty. Thus, boys reached the same S2LJ results  using less force, following a similar pattern to that which has been shown in previous studies [max/mass, vmax and the NMI, though.Our data showed, both in females and males, lower values for h studies ,9,10. Th studies . Males dThe process we recommend to evaluate the S2LJ of an individual child would be as follows:max/mass with the reference population.Step 1: Compare the child’s Pmax (parameter depicting neuromuscular coordination), by the Fmax (muscular strength) or by both.Step 2: Whether the child’s performance is influenced primarily by differences in the vStep 3: Evaluate the jump efficiency by using the NMI.max may also be evaluated, using the curves presented in the Step 4: In special cases, such as in children with unilateral paresis, unilateral spasticity, jump symmetry and, less probably, hmax, Pmax/mass, Fmax/BW and vmax [Our results are consistent with those proposed by other cross-sectional studies, which also show similar differences between the two sexes in hand vmax ,9,10,19.and vmax  and the and vmax ,21,22. Tmax/mass, as summarized in In the following, we have presented a detailed implementation of the tool to calculate changes in the Z-scores for the Pmax/mass of 0.1 at the age of 10 years and Z-score of −0.5 at 16 years. The question is if this deterioration is relevant or a frequent age-related fluctuation, as seen in the reference population. For the Pmax of the boy we are studying, Formula (5) can be transformed as follows:Let us assume a boy who had a Z-score for PThus, the boy showed a deterioration in these six years. The aforementioned calculated value also represents the effect size for the change for this boy between 10 and 16 years, which is moderate, according to Cohen (0.5 to 0.8) . We woulIn this study, we introduced the Nerve–Muscle Index. We chose to use the term “Nerve” referring to the phenomenon of coordinated interaction of muscles, while the term “Muscle” refers to pure muscular strength, and “Index” hints that the quotient of these two parameters can be used as an efficiency parameter for jumping, in this case, but probably also to quantify motor efficiency in general.max/BW) were significantly decreased, which is a finding that is consistent with already-published cross-sectional data [max in comparison with their non-obese peers. Thus, these children shower higher Fmax/BW in relation to the reached vmax (which leads to a reduction in the NMI), indicating that the movement concept has changed. The reason might be associated with lower movement efficacy due to lack of muscle coordination, lower flexibility and/or poorer ability to store energy (stretch-shortening cycle) [max/mass is reduced and Fmax/BW seems to be proportionally less reduced than vmax. The NMI was also significantly lower in children with increased weight, indicating that the lower number of vmax units are developed per Fmax/BW unit.The meaning of this parameter is clearer, when we study the S2LJ pattern in a subpopulation of our cohort, such as the group of physically healthy, but children with obesity (BMI Z-score ≥ 1.88) . The stug cycle) . Hence, max/mass and NMI values and, thus, a less efficient jump. The jump pattern of children in children with cystic fibrosis, as well as young adults with congenital heart disease, showed also increased absolute forces and relative low power [Achieving the highest power with the smallest amount of force, while storing—and saving—the maximum energy is ideal for locomotion coordination and efficiency . Obese cow power ,26. The Our study cohort presents a convenience sample of boys and girls from the metropolitan area of Dortmund, which probably may not qualify to represent the totality of German children. To address selection bias and the dependent character of the data, we used the LMS method combined with resampling . The assIn our cohort, we found a lower Esslinger Fitness Index (EFI)  in compamax values in both males and females in comparison to theirs [Further, a variant for the execution of the S2LJ has been proposed, arguing that the hands-on-waist method is associated with a less variable jump performance due to the effects of the upward swing of arms, as well as with a lower jump height . This vao theirs . No concmax/mass and the NMI can be also used to monitor motor development and efficiency of children and could be used to counsel for promotion of physical activity, not only in healthy children and adolescents, but also in those suffering from chronic conditions. Children with obesity showed lower jump efficiency and performance at the S2LJ when compared to their non-obese peers. The ratio of the Nerve–Muscle Index, which was introduced and validated in the present study, could be used as a surrogate for jump efficiency, as well as other types of motor efficiency, giving new insights into the evaluation of motor functions and differentiation between the relevant components of muscle force and jump coordination.The presented sex-specific, age-related reference centiles for the single two-leg jump of healthy boys and girls aged 6–18 years provide a valid data basis for assessing jump performance in German children and adolescents (and probably comparable populations). The presented centiles for P


We re-analyzed the data from a recent large-scale study that reported strong correlations between microbial organisms and 33 different cancer types, and that created machine learning predictors with near-perfect accuracy at distinguishing among cancers. We found at least two fundamental flaws in the reported data and in the methods: (1) errors in the genome database and the associated computational methods led to millions of false positive findings of bacterial reads across all samples, largely because most of the sequences identified as bacteria were instead human; and (2) errors in transformation of the raw data created an artificial signature, even for microbes with no reads detected, tagging each tumor type with a distinct signal that the machine learning programs then used to create an apparently accurate classifier. Each of these problems invalidates the results, leading to the conclusion that the microbiome-based classifiers for identifying cancer presented in the study are entirely wrong. These flaws have subsequently affected more than a dozen additional published studies that used the same data and whose results are likely invalid as well. Helicobacter pylori for stomach cancer  with large numbers of mis-labeled sequences. The biggest problem, as reported in one study , is thatet al. reported  by matching them against a curated, publicly available Kraken database  that conet al. study for BLCA, compared to the read counts found in our analysis. As shown in the figure, the top genera from Poore et al. were Streptococcus, Mycobacterium, and Staphylococcus, with average read counts per sample of 560K, 411K, and 241K respectively. In our re-analysis of the same samples, we found far fewer reads in these genera: an average of 36, 6, and 282 reads respectively, values that are 16,000, 67,000, and 854 times smaller. et al. study were apparently due to human reads in the filtered data that were incorrectly labeled as bacterial. Because filtering the raw reads only against GRCh37 or GRCh38 did not remove all human reads, the input to their metagenomics pipeline included 1.4–3.3 million human reads per sample, and these reads explain the dramatic over-counts shown on the left side of As we describe below, the vast majority of the excessive counts in the Poore et al. Campylobacter). Nearly half of the top-weighted genera had average read counts below 10 in the Poore et al. data as well, although several had counts in the thousands. Below we explain how genera with raw counts near zero were selected by the machine learning models.We also compared the read counts for the genera that were given the highest weights in the machine learning models created by Poore We conducted the same re-analysis on 334 HNSC samples and 238 BRCA samples see . As withet al., contrasted with our read counts for the same genera in the same samples. As with the bladder cancer results shown in et al. in both cancer types were consistently hundreds or thousands of times higher than found in our analysis. For most of these putatively abundant genera in all three cancer types, we found average read counts near zero, while Poore et al. reported read counts ranging from tens of thousands to over one million. As we demonstrate below, the vast majority of these over-counts are human reads that were erroneously assigned to bacteria.et al. Note that in the original raw data matrix, 21,074,259 (60%) of the entries were zero and 14,071,985 (40%) were non-zero. Each cell in the matrix represents a sample/genus pair; i.e., the count of the number of reads from a given sample that were assigned to a given genus.We then looked more broadly at all of the read counts, for all genera, for the BLCA, HNSC, and BRCA whole-genome samples, focusing on the non-zero counts reported by Poore et al. to the number we found in our analysis. The table focuses on sample/genus pairs where the read counts were at least 10, on the assumption that smaller values likely represent noise or contamination.et al. was at least 10 times larger than our results for 98.5% of the data entries. If we looked only at samples and genera where Poore et al. found ≥100 reads, their value was more than 10 times too large in 99.4% of all cases. The results were similar for HNSC, where 97.9% of values were at least 10 times too high, and in BRCA where 97.9% of the read counts were inflated at least 10-fold.As shown in the table, in the BLCA samples the number of reads reported by Poore et al.–the data upon which all of their results were based–appears to be wrong, by very large amounts.We also computed how many of the non-zero read counts were at least approximately the same as the value as determined in our re-analysis. In the BLCA samples, only 90 out of 37,723 (0.02%) were within 50% of the counts that we found in the same samples. Equivalently, fewer than 1 in 400 non-zero values in the bladder cancer data were within 50% of the value found upon re-analysis. The HNSC and BRCA read counts were only marginally better, with just 1.9% and 0.4% respectively within 50% of the correct value. Thus the vast majority of the non-zero data in the original data matrix of Poore et al. The number of human reads matching bacteria was unrelated to the actual presence of bacteria in the tumor sample; instead, it was determined by the database itself, in which many draft bacterial genomes contained mis-labeled human sequences.The likely reason for these vast over-counts is that human reads were erroneously categorized as bacterial by Poore Streptococcus and Waddlia, in one primary tumor sample, s2707 (case ID TCGA-DK-A1AB), from the BLCA data. We chose these genera because they were reported to be among the most abundant in Poore et al., as shown in et al. to have 327,985 Streptococcus reads and 20,673 Waddlia reads. When we aligned s2707 to our Kraken database, which only contains complete bacterial genomes, we found just 1 read labeled as Streptococcus and none labeled as Waddlia.To illustrate how such high read counts can appear when few or even no reads from a bacterial genus are present, we did a deep analysis of two genera, Streptococcus genomes available in GenBank as of 2016. , to find large numbers of reads from each of these genera when aligning against a database built entirely from bacterial genomes, as long as that database does not contain the human genome.We then extracted all reads from s2707 that did not match the human genome in the TCGA BAM file, which comprised 11,997,726 unmapped reads. Next we built a custom Kraken database containing all 10,270  of 2016 .) We buiStreptococcus or Waddlia in the Kraken analyses above and aligned them to the CHM13 human genome using Bowtie2 . All of the ACC cancer samples had raw read counts of zero for this virus, but during normalization, 71 of the 79 samples (90%) were assigned the value 3.078874655 by Poore et al. Out of all 17,625 samples across all cancer types , only 77 other samples had a value equal to or smaller than this value in the normalized data. In the raw data, however, 17,624 samples had zero Hepandensovirus reads, and one sample had 2 reads.First, consider the values for Hepandensovirus value HN, then if the model splits the samples using the simple rule HN>3.078874655, it will label 71/79 (90%) of the positive samples correctly, and only make 77/17,625 (0.4%) errors (Hepandensovirus was the highest-weighted feature for the machine learning model distinguishing ACC from other cancers in the most stringent decontamination (MSD) data set, despite the fact that only 1/17,624 samples had any reads at all matching this virus.As illustrated in ) errors . This exThiorhodospira, for the Kidney chromophobe (KICH) tumor samples  dataset, and the “all putative contaminants removed” (APCR) dataset). The TCGA-KICH data contained 51 tumor samples and 41 normal tissue samples, and in the raw data, 85 samples had read counts of zero, and 7 samples  had counts of 1 for Thiorhodospira, meaning that it had almost no utility as a discriminating feature. In the normalized data, though, the cancer samples were assigned an almost perfectly disjoint set of values from the normal tissues, as shown in We observed a similar pattern in the normalized values of another genus,  samples . ThiorhoNitrospira, which was a highly-weighted genus for the machine learning models in 13 different cancer types in Poore et al., including lung squamous cell cancer (LUSC) where it was the top-ranked genus. Nitrospira reads, after Voom-SNM normalization, in the LUSC samples compared to all other cancer types. In the figure, the frequencies of Nitrospira in LUSC are shifted to the right; i.e., they have larger values on average than other cancers. This explains why the machine learning model gave Nitrospira the highest weight; however, in the raw data there is no such shift to the right. Thus the Voom-SNM normalization process created a signature of lung cancer even though no such signature was present in the original read counts.Another example is Mulikevirus. This genus had the highest weight both for distinguishing tumor from normal tissue, and for distinguishing HNSC from all other cancers. All 906 HNSC samples, including tumor, blood, and normal tissue, had zero reads in the raw data for Mulikevirus, making this virus useless at discriminating between tumor and normal samples.We observed this phenomenon again in HNSC, where the genus with the highest weight in the MSD dataset was Mulikevirus, despite the fact that all the raw read counts were zero.However, in the Voom-SNM normalized data, values for the 70 normal samples were set to lower values than any of the tumor samples, as shown in Hepandensovirus were erroneously tagged with tumor-type specific values, we wanted to explore how this tagging would affect the performance of machine learning classifiers on a larger selection of tumor types and taxa. To investigate this question, we extracted a completely empty microbial-sample matrix  from the raw Kraken classification data provided in the Poore et al. study. To obtain the empty matrix, we filtered the data to retain only genera present in fewer than 50 samples, and then removed any samples with non-zero values for any genus. This produced a matrix containing 16,567 samples and 170 genera in which all values were zero. No machine learning classifier can use such data to discriminate among cancer types, because every entry in the matrix is identical.Given that individual genera such as N=12,803) so that we could attempt to build classifiers discriminating each cancer type from all others.We then populated each cell in the empty matrix with its corresponding value from the Voom-SNM normalized data. For this experiment, we used the Voom-SNM data from the “most stringent decontamination” (MSD) dataset, which included only 66 of the 170 taxa in our initial empty matrix. We then filtered to retain only primary tumor samples  that are unlikely to be present in human samples.A 2023 study by Parida et al.  reportedet al.  that in the raw data had zero discriminative power. This error seems to have involved every tumor type and many genera that had zero or near-zero read counts across all of the human samples.et al. study and of the other studies that relied upon the same data. The original data matrix of raw read counts contained millions of wildly inaccurate values, and the normalized data compounded this error by tagging the cancer types with distinctive normalized values. Our conclusion after re-analysis is that the near-perfect association between microbes and cancer types reported in the study is, simply put, a fiction.Either of these two errors suffices to invalidate the conclusions of the Poore We downloaded raw reads from the Genome Data Commons at the U.S. National Cancer Institute (gdc.cancer.gov) for three types of cancer from the TCGA project: bladder cancer, head and neck cancer, and breast cancer. For TCGA-BLCA  we downloaded read data from 683 samples, which included 277 whole-genome shotgun (WGS) samples and 406 RNA-seq samples . We focuFor TCGA-HNSC (Head and Neck Squamous Cell carcinoma), we downloaded the raw reads from 334 WGS samples, which included 24 solid-tissue normal, 140 blood-derived normal, and 170 primary tumor samples. As with BLCA, we focused the analysis on WGS samples. For TCGA-BRCA (Breast Invasive Carcinoma) we downloaded the unmapped reads from all 238 available WGS samples in TCGA , which ihttps://www.ncbi.nlm.nih.gov/tools/vecscreen/univec/), and the GRCh38 human genome. This 384GB KrakenUniq database is available for download from https://benlangmead.github.io/aws-indexes/k2. Files containing lists of all species, genera, and NCBI accession numbers in this database are available as Supplementary data files 1–3. All supplemental files and tables from this study are available at https://github.com/yge15/Cancer_Microbiome_Reanalyzed.Using these two-pass filtered files, for all samples in the BLCA, HNSC, and BRCA data, we ran KrakenUniq  against et al., they likely still contain some false positives and should be regarded as upper bounds on the actual number of reads from each genus. et al. study, downloaded from http://cancermicrobiome.ucsd.edu/CancerMicrobiome_DataBrowser. These include all the classifiers for the APCR and MSD datasets (separate classifiers were created for each dataset, and for those datasets, the table includes the top genera used for classifying one cancer type versus all others and for distinguishing tumor from normal tissue,Supplement 1Supplement 2Supplement 3Supplement 4Supplement 5