Opuntia, where several of its species have been an important plant resource for people in arid and semiarid zones. Opuntia streptacantha is widely distributed in Mexico; however, precise aspects of its geographic distribution and ecological status are still unknown. Here, we modeled its potential distribution under paleoclimatic, current, and future conditions through maximum entropy and predictions from 824 records and seven environmental variables. Potential distribution of O. streptacantha in the interglacial period was contracted and slightly north than current distribution, with 44,773 km2 of optimal habitat. In other past periods, the central location of potential distribution coincides with the actual current distribution, but the period of the last glacial maximum was characterized by 201 km2 of very suitable habitat, absent in interglacial, current, and future periods. The future model suggests that potential distribution will move toward the south of the Mexican territory. Synthesis and applications. The potential distribution of O. streptacantha can be applied for the conservation and management of the species, and also in the selection of areas with crassicaule scrubs for protection, conservation, and reproduction of species resistant to the hostile conditions of arid and semiarid zones of Mexican territory, where the structure and composition of the vegetation will be affected in the next 100 years.Mexican territory is one of the centers of origin and dispersion of the genus  Opuntia streptacantha. In the interglacial period, its distribution was contracted and slightly north than current, with 42,850 km2 of optimal habitat including 27 km2 of very suitable habitat.Potential distribution under paleoclimatic, current, and future conditions through maximum entropy and predictions was modeled for  Current climate data include averages for the years 1970–2000. Paleoclimatic data, including the Last Interglacial  and Last Glacial Maximum , are derived from Community Climate System Model version 4 (CCSM4) and Model for Interdisciplinary Research on Climate version 6 (MIROC)  were eliminated from further analyses  analysis was carried out to evaluate the performance of MaxEnt. This curve originates the area under receiver‐operating characteristic curve (AUC) statistic. The area under receiver‐operating characteristic curve values range from 0.5 (random) to 1.0 (perfect discrimination), where 0.5 to 0.7 model reliability is low, 0.7 to 0.9 signals a useful application of the model, and values above 0.9 are high reliability , increases with relatively low temperature seasonality values (Bio4)  indicate that the occurrence of ) Figure  with the) Figure  and the ) Figure , the pro) Figure . Finally) Figure .3.2O. streptacantha at present were predicted in central Mexico  predictions reveal a larger and continuous distribution area for on Table . Moreove2 in the predicted distribution compared with the last interglacial period (LIG), but closer to the area and location predicted for the current climate scenario, including a great part of Tlaxcala and Puebla  showed a significant change in area extension with a large increase of 5402 kma Figure . The MIRa Figure . The CCS3.42 (12.8% higher than current), 50,712 km2 (7.1% higher than current), and 52,138 km2 (10.2% higher than current), respectively  and precipitation . Ranges of most determining variables for optimal habitats like the seasonality of temperature , precipitation in the warmest quarter , and precipitation in the coldest quarter , are consistent with the current habitat requirements for the genus Opuntia, which grows well at 27–30°C and whose roots and stems are sensitive to temperature changes , thus ensuring their survival during the winter season in the arid and semiarid zones of Mexico , ONGs, and people living in the region. All the maps generated in this study can be downloaded via ZENODO https://doi.org/10.5281/zenodo.7796359.This research projected the potential distribution of Israel Cruz‐Jiménez: Conceptualization ; data curation ; formal analysis ; investigation ; methodology ; visualization (lead); writing – original draft ; writing – review and editing . Pablo Delgado‐Sánchez: Conceptualization ; funding acquisition (lead); project administration (lead); resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Maria de la Luz Guerrero‐González: Conceptualization ; investigation ; writing – original draft ; writing – review and editing . Raul Puente‐Martínez: Conceptualization ; investigation ; supervision ; writing – original draft ; writing – review and editing . Joel Flores: Conceptualization ; investigation ; methodology ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . José Arturo De‐Nova: Conceptualization ; investigation ; methodology ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing .We declare no conflict of interest.


Adopting a low‐ or very low‐carbohydrate (LCD or VLCD) diet in type 1 diabetes mellitus (T1D) is a controversial intervention. The main fear is that these diets may increase the risk of diabetic ketoacidosis. However, there is little data about the ketoacidosis risk and the level of physiological nutritional ketosis in individuals following these diets. We aimed to define the level of ketosis in those with T1D following carbohydrate restricted diets in a real‐world observational study.Patients with T1D who had self‐selected dietary carbohydrate restriction were enrolled from local clinics and were compared to those following an unrestricted regular carbohydrate control diet (RCCD). Participants completed a 3‐day diary, documenting food intake, ketones, and blood/interstitial glucose concentrations.n = 6, LCD (50–130 g carbohydrates/day) n = 6, and RCCD (>130 g carbohydrates/day) n = 3. Mean beta‐hydroxybutyrate (BOHB) concentrations were 1.2 mmol/l (SD 0.14), 0.3 mmol/l (SD 0.12) and 0.1mmol/l (SD 0.05) in the VLCD, LCD and RCCD groups, respectively (p = 0.02). Post hoc Dunn test demonstrated this reached statistical significance between the VLCD and RCCD groups (p = 0.02).Participants were divided into three groups according to mean carbohydrate intake: VLCD (<50 g carbohydrates/day) Carbohydrate restricted diets, in particular VLCDs, are associated with a higher BOHB level. However, the degree of ketosis seen is much lower than we expected, and significantly lower than the level typically associated with diabetic ketoacidosis. This may suggest the risk of ketoacidosis is lower than feared, although safety will need to be evaluated further in large scale randomised trials.  Dietary carbohydrate restriction has become an increasingly popular, and contentious, approach selected by patients living with type 1 diabetes.A key question that remains is whether adherence to a low‐ or very low‐ carbohydrate diet in type 1 diabetes is associated with a dangerous, supraphysiological ketonaemia?Carbohydrate restriction may offer therapeutic benefit and a much‐needed alternative approach to the management of type 1 diabetes.Adopting a low‐ or very low‐carbohydrate (LCD or VLCD) diet in type 1 diabetes mellitus (T1D) is a controversial intervention. Proponents of LCD/VLCDs report improvements in glycaemic control, decreased glycaemic variability and insulin requirements. However, the use of LCD/VLCDs by people with T1D is not recommended by professional organisations, mainly due to paucity of adequately controlled studies to examine their efficacy and safety. There is concern that physiological nutritional ketosis seen in LCD/VLCDs may translate into an increased risk of pathological ketoacidosis.n = 6), LCD (n = 6) and RCCD (n = 3). Mean diurnal BOHB (beta‐hydroxy butyrate) concentrations for each individual was calculated using an area under the curve (AUC) method. The non‐parametric independent samples Kruskal‐Wallis test and post‐hoc Dunn's test were used to test for significance.To better define the diurnal changes in nutritional ketosis in T1D, we performed a real‐world observational study in a single tertiary diabetes centre in England, comparing ketone levels in those following an LCD/VLCD to those following an unrestricted carbohydrate counting diet. Adult participants with T1D of at least 3 years duration, who had either self‐selected an LCD/VLCD or were following an unrestricted regular carbohydrate control diet (RCCD) were enrolled from outpatient diabetes clinics at the Oxford Centre for Diabetes, Endocrinology and Metabolism from May to September 2022. Baseline anthropometric data, daily insulin use, HbA1c, GOLD score and history of admissions with ketoacidosis or severe hypoglycaemia in the preceding 2 years were collected from self‐reported questionnaires and electronic patient records. Repetitive ANOVA test with post hoc Tukey HSD was used to assess for between group differences in these characteristics. Participants completed a 3‐day diary, documenting diurnal capillary ketone and blood/interstitial glucose concentrations using home glucose and ketone meters at the following time points: fasting, pre‐meal, 2‐h post meals and pre‐bedtime. Participants also completed a food diary, including weights and photographs of food where possible, which was subsequently analysed with nutritics software to define macronutrient composition. Participants were divided into three groups according to their mean carbohydrate intake: VLCD (p = 0.02). A post‐hoc Dunn test revealed that this difference reached statistical significance between the VLCD and RCCD groups (p = 0.02) but not between the VLCD and LCD (p = 0.06) or LCD and RCCD groups (p = 0.56) , 57 g  and 256 g . There were no statistically significant differences between the groups in age, total daily insulin dose, BMI or GOLD score. There were no reported admissions for ketoacidosis or severe hypoglycaemia in the preceding 2 years in any participants in the groups. The mean diurnal BOHB concentrations were 1.2 mmol/L (SD 0.14), 0.3 mmol/L (SD 0.12) and 0.1 mmol/L (SD 0.05) in the VLCD, LCD and RCCD groups, respectively  in 2019/2020,H.O. and F.K. researched data, contributed to discussion and wrote, reviewed and edited the manuscript. M.M. reviewed and edited the manuscript. P.D provided diet and nutrient evaluations and both G.T. and P.D. contributed to discussion and reviewed and edited the manuscript. All authors approved the final version of the manuscript.The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.Hakan Ozoran and Fredrik Karpe are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.FK and GT are supported by the National institute for Health Reasearch (NIHR) Oxford. FK, GT and PD are also supported by the Biomedical Research Centre (BRC). FK is supported by the BHF RG17/1/32663.


We estimated the secondary attack rate of SARS‐CoV‐2 among household contacts of PCR‐confirmed cases of COVID‐19 in rural Kenya and analysed risk factors for transmission.We enrolled incident PCR‐confirmed cases and their household members. At baseline, a questionnaire, a blood sample, and naso‐oropharyngeal swabs were collected. Household members were followed 4, 7, 10, 14, 21 and 28 days after the date of the first PCR‐positive in the household; naso‐oropharyngeal swabs were collected at each visit and used to define secondary cases. Blood samples were collected every 1–2 weeks. Symptoms were collected in a daily symptom diary. We used binomial regression to estimate secondary attack rates and survival analysis to analyse risk factors for transmission.A total of 119 households with at least one positive household member were enrolled between October 2020 and September 2022, comprising 503 household members; 226 remained in follow‐up at day 14 (45%). A total of 43 secondary cases arose within 14 days of identification of the primary case, and 81 household members remained negative. The 7‐day secondary attack rate was 4% (95% CI 1%–10%), the 14‐day secondary attack rate was 28% (95% CI 17%–40%). Of 38 secondary cases with data, eight reported symptoms . Antibody to SARS‐CoV‐2 spike protein at enrolment was not associated with risk of becoming a secondary case.Households in our setting experienced a lower 7‐day attack rate than a recent meta‐analysis indicated as the global average (23%–43% depending on variant), and infection is mostly asymptomatic in our setting. Primary cases who were children, had high viral load, and had Beta or Delta viral variants (compared with Alpha) were more likely to be the source of onwards transmission. In total, 85% of infections were asymptomatic.A recent systematic review of six studies in the African region estimated 47% (95% CI 22%–74%) of infections were asymptomatic, in contrast to 24% in Europe (95% CI 17%–33%).Further data on the epidemiology in the African region are needed, and we aimed to estimate the secondary attack rate of SARS‐CoV‐2, the prevalence of symptoms, and identify risk factors for transmission among household contacts of PCR‐confirmed cases in rural Kenya.22.1The study took place within the Kilifi Health and Demographic Surveillance System (KHDSS), Kilifi County, Kenya.2.2The protocol was adapted from the World Health Organization UNITY household study protocols.2.3At baseline, a questionnaire, a blood sample (3–5 mL), and naso‐oropharyngeal swabs were collected from all consenting household members (regardless of symptoms). Subsequent study visits were dependent on whether household member(s) were confirmed positive for SARS‐CoV‐2 at baseline Figure . Househo2.4The KEMRI‐Wellcome Trust Research Programme Kilifi laboratory was the designated laboratory for testing SARS‐CoV‐2 suspect cases across the coastal region.All serums were separated within 48 h of sample collection and stored at −80°C at the KWTRP laboratories in accordance with Standard Operating Procedures. An in‐house two‐step Enzyme Linked Immunosorbent Assay (ELISA) adapted from the Krammer assay2.5Among households with at least one SARS‐CoV‐2 positive member, participants were defined into three groups: primary cases, secondary cases, and those who remained negative. Primary cases were the earliest confirmed PCR‐positive case(s) within a household at the time of study; secondary cases were household members who were PCR‐negative at the timepoint the primary case(s) in the household were identified but had at least one subsequent PCR‐positive test result during follow‐up; persistently negative household members were defined as those who returned negative PCR results throughout follow‐up . Cox regression was used to identify risk factors associated with acquisition, comparing secondary cases with those remaining negative, with robust standard errors to account for clustering by household. Characteristics of participants who were lost to follow‐up were compared with those in the analytical dataset using a generalised linear model with complementary log–log link function with random effects to control for clustering by household.Secondary attack rates were calculated using the number of secondary cases (defined above) within 7 and 14 days of the identification of the primary case(s), and the number of susceptibles in each household. Susceptibles were household members who were not primary cases, who remained in follow‐up at the timepoint of interest, as we could not be sure that the other susceptibles enrolled, but lost to follow‐up were not cases by this timepoint. Household‐specific attack rates were pooled using binomial regression with a random effect for household (Metaprop).3The protocol and study forms were approved by the KEMRI Scientific & Ethics Review Unit , The University of Warwick's Humanities and Social Sciences Research Ethics Committee (BSREC 150/19‐20) and the London School of Hygiene & Tropical Medicine observational research ethics committee (28160).44.1A total of 214 households consented to participate out of 250 visited. At least one household member in 119 households had a confirmed PCR‐positive result at enrolment, or on day 4 or day 7; these households were therefore followed up intensively for 28 days following the positive test Figure .4.2Across the 119 households that entered intensive follow‐up, 30% (36/119) were enrolled during the third wave of SARS‐CoV‐2 infection in Kenya (dominated by the Alpha and Beta variants in March–June 2021), another 30% (34/119) were enrolled during wave 4 , and 40% (48/119) were enrolled in December 2021 to August 2022 during two Omicron variant waves Table . Of 535 4.3The 7‐day attack rate was restricted to 174 unvaccinated household members who were not defined as primary cases and remained in the study 7 days post‐identification of the primary case . Accounting for clustering by household, 7 days after identification of the primary case(s), 4% of the unvaccinated household members who had been negative at enrolment had tested positive (95% CI 1%–11%). The 14‐day secondary attack rate was restricted to 113 unvaccinated household members who were not primary cases and remained in the study 14 days post identification of the primary case(s) . This did not differ when restricted to 30 unvaccinated primary and secondary case pairs .4.5Over a third of primary cases (46%) only tested positive once Table . SecondaHalf of all the primary and secondary cases were seropositive for IgG to SARS‐CoV‐2 at enrolment Table . Among pJust over half of primary cases 56%, 114/204) reported symptoms. A fifth  of secondary cases reported symptoms within 7 days of becoming PCR‐positive, 79% remained asymptomatic (95% CI 66%–92%). Six of the symptomatic secondary cases only reported symptoms at one timepoint, one reported symptoms for 3 days, and one reported symptoms for 6 days. A similar proportion of household members who remained PCR‐negative also reported symptoms  of participants at day 14, we analysed differences in participant characteristics among those who were included in the risk factor and secondary attack rate analyses and those whose data were missing. Young people and adults (10–45 year olds), participants with reported pre‐existing conditions and unvaccinated individuals were more likely to drop out of follow‐up compared with young children or adults over 45, participants without pre‐existing conditions and the small number of vaccinated participants Table .5We report a low, 4%, 7‐day attack rate within households in rural, coastal Kenya, lower than those reported in other settings in a recent systematic review, although the follow‐up time of other studies is not always apparent.The 14‐day attack rate of 33% was closer to the global average (30%–43%)Our findings that households had a high number of co‐primary cases and high seroprevalence at enrolment, low 7‐day secondary attack rate, and multiple introductions of new genomic variants from outside the household indicate the observed SARS‐CoV‐2 transmission was predominantly community spread, rather than within‐households. Low secondary attack rates within households may be plausible in our context with high seroprevalence after natural exposure to the virus,Natural, vaccine‐induced and hybrid immunity have been shown to both directly protect individualsThere were too few participants reporting any one symptom to disaggregate the attack rate by symptom of the primary case. We also could not disaggregate the attack rate by vaccination status as so few of the participants had been vaccinated. This is representative of our context; COVID‐19 vaccination started in Kenya in March 2021, but half of the participants were enrolled before July 2021 when the vaccine coverage with one dose in Kilifi was <5%.Contrary to a previous review,A total of 30 secondary cases  were completely asymptomatic; this is higher than the 53% estimated in a recent systematic review of studies in Africa.6Households in our setting experienced a lower 7‐day attack rate than a recent meta‐analysis (to March 2022) indicated as the global average. Observed households had a high number of co‐primary cases, high seroprevalence, and high 14‐day attack rate indicating a substantial force of infection in Kilifi, but this may be predominantly via community spread rather than within household transmission. Approximately 80% of secondary cases were asymptomatic.Katherine E. Gallagher: Conceptualization; data curation; formal analysis; writing—original draft. Joyce U. Nyiro: Conceptualization; investigation; project administration; writing—review and editing. Charles N. Agoti: Conceptualization; investigation; writing—review and editing. Eric Maitha: Investigation. James Nyagwange: Investigation; writing—review and editing. Angela Karani: Investigation; writing—review and editing. Christian Bottomley: Formal analysis; validation; writing—review and editing. Nickson Murunga: Data curation; writing—review and editing. George Githinji: Investigation; writing—review and editing. Martin Mutunga: Data curation; investigation; writing—review and editing. Lynette Isabella Ochola‐Oyier: Supervision; writing—review and editing. Ivy Kombe: Writing—review and editing. Amek Nyaguara: Investigation; writing—review and editing. E Wangeci Kagucia: Writing—review and editing. George Warimwe: Supervision; writing—review and editing. Ambrose Agweyu: Writing—review and editing. Benjamin Tsofa: Writing—review and editing. Philip Bejon: Writing—review and editing. J Anthony G Scott: Writing—review and editing. David James Nokes: Supervision; writing—review and editing.All authors report no conflicts of interest.https://www.webofscience.com/api/gateway/wos/peer‐review/10.1111/irv.13185.The peer review history for this article is available at The protocol and study forms were approved by the KEMRI Scientific & Ethics Review Unit , The University of Warwick's Humanities and Social Sciences Research Ethics Committee  and the London School of Hygiene & Tropical Medicine observational research ethics committee (ref 28 160).Written permission to involve the household in the study was sought from the household head. Individual written informed consent was obtained from every household member prior to engagement with any study procedure. Consent for children under the legal age of consent (18 years) was obtained from a parent or legal guardian. Informed assent was obtained from adolescents aged 13–17 years.Agnes Mutiso, Alfred Mwanzu, Angela Karani, Bonface M. Gichuki, Boniface Karia, Brian Bartilol, Brian Tawa, Calleb Odundo, Caroline Ngetsa, Clement Lewa, Daisy Mugo, David Amadi, David Ireri, Debra Riako, Domtila Kimani, Donwilliams Omuoyo, Edwin Machanja, Elijah Gicheru, Elisha Omer, Faith Gambo, Horace Gumba, Isaac Musungu, James Chemweno, Janet Thoya, Jedida Mwacharo, Jennifer Musyoki, John Gitonga, Johnstone Makale, Justine Getonto, Kelly Ominde, Kelvias Keter, Lydia Nyamako, Margaret Nunah, Martin Mutunga, Metrine Tendwa, Moses Mosobo, Nelson Ouma, Nicole Achieng, Patience Kiyuka, Perpetual Wanjiku, Peter Mwaura, Rita Warui, Robinson Cheruiyot, Salim Mwarumba, Shaban Mwangi, Shadrack Mutua, Susan Njuguna, Victor Osoti, Wesley Cheruiyot, Wilfred Nyamu, Wilson Gumbi, and Yiakon Sein.Table S1: Visit schedule, including naso‐oropharyngeal swabs and blood draws.Table S2: Household characteristics for the whole study population.Table S3: Household member characteristics across the whole study population, in households that remained negative, and those with at least 1 positive PCR test and therefore followed up intensively for 28 days.Table S4: Secondary Attack Rates additional tables.Table S5: Analysis of whether those lost to follow up differed from those who remained in follow up at day 14 post‐primary case identification.Click here for additional data file.


Invasive micropapillary carcinoma (IMPC) is one of the rare subtypes of breast cancer. This study aimed to explore a predictive nomogram model for IMPC prognosis.A total of 1855 IMPC patients diagnosed after surgery between 2004 and 2014 were identified from the Surveillance, Epidemiology and End Results (SEER) database to build and validate nomogram. A nomogram was created based on univariate and multivariate Cox proportional hazards regression analysis. Receiver operating characteristic (ROC) curves were used to demonstrate the accuracy of the prognostic model. Decision curve analysis (DCA) was performed to evaluate the safety of the model in the range of clinical applications, while calibration curves were used to validate the prediction consistency.Cox regression analysis indicated that age ≥62 at diagnosis, negative ER status, and tumor stage were considered adverse independent factors for overall survival (OS), while patients who were married, white or of other races, received chemotherapy or radiotherapy, had a better postoperative prognosis. The nomogram accurately predicted OS with high internal and external validation consistency index (C index) . The areas under the ROC curve (AUCs) of the training group were 0.787, 0.774 and 0.764 for 3, 5 and 10 years, respectively, while those of the validation group were 0.756, 0.766 and 0.762, respectively. The results of both DCA and calibration curves demonstrated the good performance of the model.A nomogram for IMPC of the breast patients after surgery was developed to estimate 3, 5 and 10 years—OS based on independent risk factors. This model has good accuracy and consistency in predicting prognosis and has clinical application value. In this study, we aimed to develop a nomogram to identify factors associated with improved survival in patients with IMPC.22.1IMPC after surgery was identified by SEER*Stat (version 8.3.9) from 18 population‐based cancer registries. Patients were eligible for enrollment according to the following inclusion criteria: (1) histology ICD‐O‐3 (8507), (2) surgery performed, (3) patients with primary site, (4) known ER, PR status and adjusted AJCC 6th stage. The exclusion criteria were as follows: (1) detailed information lacking age, race, grade or marital status and (2) unknown T, N, M classification and breast subtype.2.2Patient characteristics included basic information, histological type, grade, breast subtype, primary site, tumor size, positive regional nodes and treatments. The patient's age was cut off at 62 years, while the tumor size was reclassified as ≤20, 20–50 and >50 mm. Surgery information was categorized as breast‐conserving surgery (BCS) or mastectomy. Primary sites of tumors were divided into central portion of breast or nipple, lower‐inner/lower‐outer/upper‐inner/upper‐outer quadrant of breast and others. The subtypes of tumors were classified as HR+/HER2− , HR+/HER2+ , HR−/HER2+ (HER2 enriched) and HR−/HER2− (triple negative).2.3p < 0.05 in univariate analysis were included in Cox proportional risk regression models to identify risk factors associated with IMPC prognosis.The baseline characteristics of IMPC patients after surgery were first described statistically. OS was defined as the date of diagnosis to the date of death from any cause or the date of the last follow‐up visit. The data were divided into training and validation sets in a 7:3 ratio using the “caret” package in R version 4.1.1. Survival analysis was performed using SPSS version 25.0. Kaplan–Meier survival curves were constructed for each variable with a log‐rank test. Variables with Nomograms were built based on multifactor analysis using the “rms” package. The performance of the nomogram was measured by the C index to judge the accuracy of the prediction results. The total score of patients in the validation set was calculated based on the corresponding column line graphs and included as a new factor in the Cox regression model. In addition, the area under the ROC curve (AUC) was also calculated to assess the performance of the prognostic model, while the “stdca” function was used in decision curve analysis (DCA) to determine the suitability of the model. Moreover, calibration curves were plotted to compare the difference between predicted survival and actual survival determined using Kaplan–Meier analysis.33.1n = 1300) for nomogram building, and a validation set (n = 555) for model validation. Next, the clinical and pathological characteristics of the patients in the training set were described in detail. The median age of primary diagnosis for the entire population was 62 (22–96) years old. The majority of patients were white (78.2%), and 98.5% were female. The breast cancer subtype was HR+/HER2−  in 52.7% of patients, HR+/HER2+  in 11.2%, HR−/HER2+ (HER2 enriched) in 2.8% and HR−/HER2− (triple negative) in 2.7%. Since the Seer database has only recorded HER2 status since 2010, the HER2 status was not known for patients (30.6%) before that date. A total of 41.4% of screened patients after surgery were stage I, 37.3% were stage II, 20% were stage III, and 1.3% were stage IV. A total of 52.4% of the patients received breast‐conserving surgery (BCS), and the rest underwent mastectomy. The majority of patients developed breast cancer that was located on the upper‐outer region (29.5%), and most tumors were ≤20 mm (58.4%). The proportions of patients who underwent chemotherapy and radiotherapy were 48.9% and 55.1%, respectively. The demographic and clinical characteristics of the study participants based on dataset classification are shown in Table A total of 1855 patients diagnosed with IMPC after surgery were included in this study. Patients were randomly divided via a 7:3 ratio into two sets: a training set (3.2p < 0.001), negative ER (p = 0.004), stage III (p = 0.044), and stage IV (p < 0.001) were related to a significantly increased risk of IMPC patients after surgery. In contrast, marital status (p < 0.001), white or other race (p = 0.002), chemotherapy (p < 0.001) and radiotherapy (p = 0.002) were associated with a significant reduction in risk. Kaplan–Meier analysis with the log rank test was performed for the above factors using the “survival” package of R software, and the same statistical results were obtained  for the 3‐, 5‐, and 10‐year OS were plotted for the training and validation sets. The generation of DCA curves validated the safety of the nomogram and has value for clinical application Figure . The res3.4p < 0.001) ; data curation ; formal analysis ; funding acquisition ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Caixian Yu: Conceptualization ; data curation ; formal analysis ; funding acquisition ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Dedian Chen: Conceptualization ; data curation ; formal analysis ; funding acquisition ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Yiyin Tang: Conceptualization ; data curation ; formal analysis ; investigation ; methodology ; project administration . Keying Zhu: Software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Rong Guo: Resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Sheng Huang: Conceptualization (lead); data curation ; formal analysis ; funding acquisition ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Zheng Li: Conceptualization ; data curation ; formal analysis ; funding acquisition ; investigation ; methodology ; project administration ; resources ; software ; supervision ; validation ; visualization ; writing – original draft ; writing – review and editing . Lvjun Cen: Conceptualization ; writing – review and editing .This work was supported by the National Natural Science Foundation of China (81860465 and 8216110588).The authors declare that there are no potential conflicts of interest disclosed.This article does not contain any studies with human participants or animals performed by any of the authors.


Saccharomyces cerevisiae yeast culture product influenced growth performance, feed efficiency, and hepatic trace mineral concentration in newly weaned steers. Crossbred steers  were used in a 49-day receiving phase experiment. Within 36 hours of weaning, steers were weighed, allotted to 24 pens , and randomly assigned to treatments: 1) a traditional receiving diet (CON), 2) a traditional receiving diet plus the “stress-pack” directly in the diet (FORCE), and 3) a traditional receiving diet plus a low-moisture, cooked molasses block fortified with the “stress-pack” (TUB). The “stress-pack” was offered the first 28 day of the 49-day receiving period. Due to adverse weather conditions forecasted on day 1, biopsy samples were collected from a subsample of steers (n = 14 steers) on day 1 to establish hepatic trace mineral concentration baseline. Steers were selected based on the mean body weight (BW) from allotment (day −1) of the pen for collection of subsequent samples (n = 1 steer/pen) on days 14, 28, and 49 for hepatic trace mineral concentration determination. Cumulative dry matter intake (DMI) (P = 0.01) was greater for FORCE compared to CON and TUB. Final BW and average daily gain (ADG) tended (P ≤ 0.10) to be greater for FORCE compared to TUB and CON by 5.4% and 9.4%, respectively. Feed efficiency did not differ between treatments (P = 0.28). A treatment × day interaction (P ≤ 0.01) for hepatic Cu concentration was noted. The FORCE treatment had greater hepatic Cu compared to TUB and CON for the entire period. The steers that received TUB had greater hepatic Cu compared to CON on days 14 and 28, but similar to CON on day 49. The addition of a “stress-pack” to diets offered to newly weaned cattle enhanced hepatic trace mineral concentration, and delivery method influences DMI and daily gain.The objective of this study was to determine if supplementation and delivery method of a “stress pack” composed of organic trace minerals and  The present study was conducted to evaluate the effects of delivery method of oragnic trace minerals and yeast culture product(“stress-pack”) has on production efficiency and hepatic trace mineral status and demonstrated that method of delivery alters intake and hepatic trace mineral status. TM) status of cattle  have positive effects on growth performance, rumen, intestinal health, and immune responses. In addition, cattle-fed YCP also exhibited improved fiber digestibility, mineral retention, and flow of microbial protein to the small intestine  fed in combination (stress-pack) affect growth performance and hepatic trace mineral concentration upon feedlot introduction in newly weaned beef steer calves. We hypothesized that additional TM and YCP would increase daily intake and gain, and method of supplementation would have no influence on production outcomes.Supplementation of TM and YCP in combination has led to greater performance and greater hepatic TM content compared to nontreated steers . HoweverAll procedures involving the use of animals in this experiment were approved by the South Dakota State University Institutional Animal Care and Use Committee .n = 192; 256 ± 14.0 kg) from a single source were transported (515 km) to the Ruminant Nutrition Center in Brookings, SD. Upon arrival (6.5 hours transport from the ranch), steers were offered long-stem grass hay and ad libitum access to water. The following day (day −1), steers were weighed, tagged, and vaccinated , administered a dose of pour-on moxidectin , and sorted into study pens the afternoon following initial processing . Steers were individually weighed again on day 1. Initial BW was the average of the two BW measures collected on day −1 and day 1. Live BW measures, excluding initial BW, were shrunk 4% to account for digestive tract fill. Initial BW was not shrunk to accommodate for transportation shrink on day −1.Charolais × Angus steers calves (n = 64 steers/treatment). Each pen was assigned to one of three dietary treatments in a randomized complete block design (RCBD), where location in the feedlot was considered the blocking factor. Dietary treatments included: 1) a traditional receiving diet (CON), 2) a traditional receiving diet plus the “stress-pack” directly in the diet  t FORCE; .The traditional receiving diet  consisteAll steers were fed twice daily (0800 hours and 1400 hours) in equal proportions. On day 1, 2 kg/steer of the diet (DM basis) was offered to the steers and increased by 0.5 kg/steer (DM basis) until day 7. Bunks were managed using a slick bunk approach from days 8 to 49 such that bunks were managed to be devoid of feed by 0730 hours. Pens were 7.6 × 7.6 m concrete surface pens with 7.6 m of linear bunk space and equipped with a heated, continuous flow concrete waterer.n = 1 tub/pen) were placed in the opposite corner of the feed bunk and waterer, tubs were replaced when 90% of the tub was consumed. Tubs were cleaned and weighed daily, and consumption was determined from daily disappearance. Individual consumption was calculated by dividing daily tub disappearance by the number of steers in the pen. Steers were provided access to the tubs through day 28 of the experiment. Force-fed supplement and Stress Tub nutritional values are presented in −1. To facilitate the mixing process, a soybean hull carrier was used to ensure uniform distribution throughout the diet. The FORCE supplement was designed so that TM and YCP intake would be equivalent to tub assuming a targeted tub intake of 0.22 kg/steer·d−1. The FORCE supplements were included in the diet from day 1 to day 28.Treatments were introduced approximately 36 hours following arrival to the RNC. Tubs  using AOAC procedures. Actual diet formulation based upon weekly DM determination and feed batching records along with tabular energy values  are presSteers were weighed before feeding, and on day −1, 1, 14, 28, and 49. Growth performance data were summarized from initial to d 49. Initial BW was not shrunk, while BW from day 49 was shrunk 4% to account for digestive tract fill. Average daily gain was determined using the difference in BW divided by days on feed. Efficiency of weight gain (G:F) was calculated by dividing the ADG by DMI.n = 14 steers) on day −1 to establish hepatic trace mineral concentration baseline. Steers were selected based on the mean BW from allotment of the pen for collection of subsequent samples (n = 1 steer/pen) on days 14, 28, and 49 for hepatic trace mineral concentration determination. Briefly, steers were secured in a hydraulic squeeze chute. The biopsy was collected through an incision in the 11th intercostal space on a line from the tuber coxae to the point of the scapula-humoral joint. Hair was clipped from an area approximately 10.16 cm × 10.16 cm around the biopsy site. The surgical site was prepared with iodine and 70% isopropyl alcohol. A solution composed of lidocaine hydrochloride and bicarbonate  was applied in the muscle layer and injected (1 mL) as the needle was withdrawn from the biopsy location The surgical site was prepared with iodine and 70% isopropyl alcohol. A solution composed of lidocaine hydrochloride and bicarbonate  was applied in the muscle layer and injected (1 mL) as the needle was withdrawn from the biopsy location. After 15 seconds, a 6.35 mm incision was made by inserting a scalpel blade through the skin and intercostal muscle. Surgical tubing was applied to the biopsy needle , which was inserted into the incision site to reach the liver. The hepatic tissue was collected by using back pressure on a 10 mL syringe. Contents were emptied from surgical tub into a wire mesh screen, and blood was rinsed-off using 0.01M of phosphate buffered saline . Treatment was included as a fixed effect and block (location) was considered a random effect in the statistical model. Hepatic trace mineral content was analyzed via repeated measures and included the fixed effects of treatment, day, and their interaction, the covariance structure with the best fit (lowest Akaike information criterion) was autoregressive 1 (AR-1). Least squares means were generated and separated using pairwise comparisons. An Tub disappearance and DMI are depicted in P = 0.01) for FORCE compared to CON and TUB. Final BW and ADG tended (P ≤ 0.10) to be greater for FORCE compared to TUB and CON by 5.4% and 9.4%, respectively, G:F did not differ by treatment (P = 0.28). In the study conducted by −1·d−1. Furthermore, the administration of YCP at 28.4 g·steer−1·d−1 had no effect on growth performance of shipping-stressed calves , for hepatic concentrations of Co and Cu was noted (P ≤ 0.05) compared to TUB and CON on day 14, 28, and 49. However, hepatic Co concentration was greater for TUB compared to CON on day 14 but did not differ on day 28 and day 49. P ≤ 0.01) when supplemented early weaned calves with a molasses block at the concentration of 0.15, 550, 1,650, and 2,200 mg/kg of Co, Cu, Zn, and Mn, respectively. P < 0.05), but hepatic Co content was similar to CON on days 28 and 49 (P > 0.10).In the present study, a treatment × day interaction (as noted  and 3. TP ≤ 0.05) compared to TUB and CON on days 14, 28, and 49. This is likely driven by greater DMI consumed by the FORCE treatment compared to the other treatments thus leading to greater overall daily Cu intake. As observed when an organic source of TM was fed, P < 0.05), but hepatic Cu content was similar to CON on day 49 (P > 0.10). This trend is consistent with the findings of Steers from FORCE treatment had greater hepatic Cu (P = 0.07) and Zn (P = 0.09). In addition, a day effect was noted  for Mn and Zn hepatic concentration, respectively (In the present study, a tendency for a treatment × day interaction was observed for hepatic concentration of Mn (ectively  and 5. Dectively . HoweverProviding TM supplementation for calves through limit-fed creep feeding, injectable trace minerals, or low moisture cooked molasses blocks improves trace mineral status of cattle .Using the cooked-molasses based block to provide additional TM and YCP has the benefit of labor savings compared to other supplementation methods . However


Nickel‐induced proliferation or cytokine release by peripheral blood mononuclear cells may be used for in vitro diagnosis of nickel allergy.Aim of this study was to explore the nickel‐specific cytokine profile to further elucidate the pathogenesis of nickel allergic contact dermatitis (ACD) and to identify potential new biomarkers for nickel ACD.Peripheral blood mononuclear cells from patients and controls were cultured with T‐cell skewing cytokine cocktails and/or nickel. Cytokine and chemokine concentrations were assessed in culture supernatants using validated multiplex assays. Specific cytokine production was related to history of nickel allergy and patch‐test results.Twenty‐one of the 33 analytes included in the analysis were associated with nickel allergy and included type1 , type 2 , type 1/2 , type 9 (IL‐9), type 17/1  and type 22 (IL‐22) derived cytokines as well as the T‐cell/antigen presentation cell derived factors Thymus and activation regulated chemokine (TARC), IL‐27 and IP‐10. Receiver operator characteristics (ROC) analysis showed that IL‐5 was the strongest biomarker for nickel allergy.A broad spectrum of 33 cytokines and chemokines is involved in the allergen‐specific immune response in nickel allergic patients. IL‐5 remains, next to the lymphocyte proliferation test, the strongest biomarker for nickel allergy. PBMC from nickel allergic patients and controls were stimulated with nickel under type 1, 2 and 17 skewing culture conditions; levels of 33 cyto‐ /chemokines were analysed and related to medical history of nickel contact dermatitis and nickel patch test result.A broad spectrum of 21 type 1, 2, 9,17, 22 and antigen presenting cell related factors was associated with nickel allergy.IL‐5 production under type 2 skewing conditions and lymphocyte proliferation are most potent biomarkers for nickel allergy. To study whether sensitivity of the cyto‐/chemokine release assay can be enhanced, cytokine cocktails skewing lymphocytes towards type‐1, ‐2 or ‐17 function were added. A wide range of 33 different chemokines, cytokines and growth factors was analysed, most of which, to our knowledge, have not previously been examined in an in vitro assay in response to nickel. The aim of this study was to identify novel cytokines in the inflammatory mediator profile induced by nickel and to investigate whether existing proliferation and type2 cytokine production diagnostic tests can be improved.Using multiplex assays, a broad range of inflammatory mediators can be determined in a small volume sample. In this study, peripheral blood mononuclear cells (PBMC) of in total 52 nickel allergic patients and controls were stimulated in vitro with nickel sulfate  jewellery, coins, metal tools, scissors or metals in clothing such as belts and buttons, was recorded, enabling us to divide the participants into four groups: true positives (positive patch test and history), true negatives (negative patch test and history) and two groups in which the patch test did not confirm the history. The subjects were without systemic immunosuppression or UV radiation therapy. Patient characteristics have been previously described, (6) and are listed in Table The study followed the Declaration of Helsinki Principles. All participants gave written informed consent, and the study was approved by the medical ethical committee of VU University Medical Centre . Patient inclusion was as described previously.2.24 was 5% in petrolatum as recommended in the European baseline test Series. Allergens were tested in square chambers  mounted on Fixomull stretch from Beiersdorf .Patch testing was performed according to the guidelines of the International Contact Dermatitis Research Group (ICDRG) criteria. All included patients were tested with at least the 30 allergens of the European baseline contact allergen series, on their back with an application time of 48 h. Allergens were purchased from Van der Bend . The patch test concentration of NiSOReadings were performed at 48, 72 and 168 h (7 days). Positive reactions were rated as +, ++ or +++.2.3l‐glutamine  and 50 μM β‐mercapto‐ethanol) containing 10% autologous serum. The final cell density was 7.5 × 105 cells/ml/well. The PBMC were cultivated with or without 50 μM NiSO4 (Merck), the same salt as used in the patch test, for 7 days in duplicate. We have previously shown 50 μM NiSO4 to be the optimal non‐toxic concentration.The lymphocyte cytokine production test (LCPT) was performed in the laboratory of the Oral Cell Biology department of the Academic Centre for Dentistry Amsterdam (ACTA), cultures were set up as previously described.2.4Cytokine production was determined by collecting supernatants at Day 7 of culture. The analysis of mediators in the supernatants was performed using the mesoscale platform and V‐PLEX validated immunoassays from MSD . The following kits were used: Cytokine panels 1 and 2, Pro‐inflammatory panel 1, Chemokine panel 1 and Th17 panel. See for details on individual analytes in these kits and analytes excluded from analysis Table S2.5p < 0.05.SPSS , MedCalc  and GraphPad Prism  were used for statistical analyses. Supervised and unsupervised clustering and heatmap generation was performed using R. To better interpret the heat map cluster results, the top 10% of the SI's were lowered, resulting in a top SI of 44.2. To determine optimal SI cut‐off values to distinguish positive from negative patients, receiver operator characteristics (ROC)‐curve analyses were performed for each in vitro parameter. Statistical significance was defined as 3n = 10) or a positive patch test without a clinical history of nickel allergy .A summary of the patient characteristics are listed in Table Five different optimized V‐plex kits were used to analyse 44 analytes. Eight of these were excluded from analysis because baseline production (medium) exceeded the upper limit of the standard curve and thus the upper limit of detection of the assay, these were predominantly chemokines .IL‐1α, VEGF‐A, IL‐16, IL‐1β, IL‐12p70, Eotaxin‐1 and Eotaxin‐2, were produced but the mean SI was <1.5 in all culture conditions.All remaining analytes were included in the supervised cluster analysis shown in Figure The supervised cluster analysis in Figure p‐values for the different culture conditions, see Table SIn Figure Figure p < 0.0001, see Table SWe have previously shown in this patient group that specific proliferation to nickel is associated with nickel allergy. We therefore analysed the correlation between the LPT and the LCPT for the cytokines with an AUC ≥ 0.90 under non‐skewed and type 2 skewed conditions. Indeed, the LPT and cytokine production under non‐skewed conditions  and type 2 skewing conditions  all correlated well , demonstrating that the T‐cell response to nickel shows a broad spectrum of type 1 , type 2 , type 1/2 , type 9 , type 17/1  and type 22 (IL‐22) derived cytokines. The types 9 and 22 cytokines in particular are to our knowledge not previously described in this context. In addition, we show some cyto‐/chemokines  which are predominantly produced by antigen presenting cells rather than T‐cells, to be associated with nickel allergy.+ T‐cells, CD4+ T‐cells) cells and non‐haematopoietic  cells and is a chemoattractant for CD4+ cells.+ T‐cells.Of the tested T‐cell derived factors only IL‐16, Eotaxin‐1 and IL‐31 were not associated with nickel allergy. IL‐16 is produced by a variety of haematopoietic , IL‐27  and IP‐10  were also associated with nickel allergy  after in vitro PBMC stimulation, which can most accurately predict nickel allergy and could be used as a diagnostic test. In the ROC analyses, there were 7 cytokines with an AUC of more than 0.90 with a Summer et al. described a lower production of IL‐8 in nickel allergic patients as compared to controls and reported IL‐5/IL‐8 ratio as the strongest diagnostic parameter for nickel allergy.Our previously described LPT and the IL‐5 LCPT are both more accurate than the patch test in this patient group, if nickel allergic contact history is used as a reference.In conclusion, nickel allergic contact allergy is characterized by a broad cytokine response with cytokines related to type 1, type 2, type 9, type 17 and type 22 cells; type 2 cytokines showed the strongest correlation. The type 2 cytokine IL‐5 is the best biomarker for nickel allergy.Investigation: de Graaf NPJ, Rustemeyer T, Roffel S; Formal Analysis: de Graaf NPJ, Roffel S, Gibbs S, Lopez Gonzalez M and Bontkes HJ; Conceptualization: Feilzer AJ, Gibbs, S., Kleverlaan CJ, Bontkes HJ; Funding Acquisition and Supervision: Feilzer AJ, Gibbs, S. Writing‐Original Draft Preparation: Bontkes HJ, de Graaf NPJ; Writing‐review & editing: all authors.None of the authors have a conflict of interest.The study was approved by the medical ethical committee of VU University Medical Centre, Central Committee on Research Involving Human Subjects protocol number: NL52668.029.15.Table S1 patient characteristicsTable S2. MSD V‐plex kits used for mesoscale analysisTable S3. Receiver operator characteristics (ROC) data, part 1Table S3. Receiver operator characteristics (ROC) data, part 2Table S4. Raw data (pg/ml) of top 10 analyte/culture condtition combinationsTable S5. Correlation lymphocyte proliferation and cytokine production testsClick here for additional data file.Figure S1 Unsupervised cluster analysis: Dark blue colours represent low SI's, white colours represent average SI's, and dark red represent high SI's.Click here for additional data file.


Antisocial personality disorder (ASPD) and conduct disorder (CD) are characterized by a persistent pattern of violations of societal norms and others' rights. Ample evidence shows that the pathophysiology of these disorders is contributed by orbitofrontal cortex (OFC) alterations, yet the underlying molecular mechanisms remain elusive. To address this knowledge gap, we performed the first‐ever RNA sequencing study of postmortem OFC samples from subjects with a lifetime diagnosis of ASPD and/or CD.n = 9/group).The transcriptomic profiles of OFC samples from subjects with ASPD and/or CD were compared to those of unaffected age‐matched controls  and/or conduct disorder (CD). Our results indicate that ASPD and/or CD are characterized by dysfunctions of synaptic regulation and neurotransmission in the pyramidal neurons of the orbitofrontal cortex. These findings point to molecular and functional substrates that may explain the connectivity deficits exhibited by the orbitofrontal cortex of antisocial subjects. The analysis was performed in postmortem OFC tissue (21.68 ± 3.80 mg/sample) and associated clinical data, including age, sex, brain pH, and postmortem interval (PMI) for age‐ and sex‐matched cohorts of nine individuals receiving lifetime diagnoses of ASPD and/or CD , and nine individuals with no history of psychiatric disease  using the RNeasy Lipid Tissue Mini Kit (Qiagen) in an elution volume of 40 μL of RNase‐free water. RNA purity was assessed by the A260/A280 absorbance ratio using a NanoDrop™ spectrophotometer (ThermoFisher Scientific). RNA extracted from OFC samples was sequenced using NovaSeq Reagent Kit v1.5_150 × 150 bp (100 M read‐pairs) Sequencing (Illumina Inc), and sequencing libraries were prepared using Illumina TruSeq Stranded Total RNA Library Prep Ribo‐Zero Gold kit (Illumina).2.3STAR v2.7.5b,featureCounts, as implemented in the R‐package subread.MultiQC v1.12,DESeq2.r. Raw counts were normalized using DESeq2, and differential expression analysis was performed between ASPD+CD and unaffected controls (CTL), including the covariates sex, RIN, and PMI. P values were adjusted for multiple testing using the False Discovery Rate (FDR) method.p < 0.05 were considered statistically significant differentially expressed genes (DEGs). Pathway analysis was conducted on the DEGs using clusterProfiler R‐package,p‐values with the FDR method.Raw reads were aligned using p‐values (FDR) were p < 0.05, and (2) the regression coefficient of the enriched cell type exhibited a ratio ≥1.76 compared to the second enriched cell type. The cutoff was established by testing coefficient ratios ranging from 1 to 5 until the variation in the number of unclassified genes stabilized below 0.5%. A list of 5399 cell‐specific genes, identified by HGNC symbols, was obtained.A list of cell‐specific markers was generated using a brain single‐nuclei sequencing dataset from the prefrontal cortex (BA10).enrichment from the R‐package bc3net.voom method.MEGENA R‐packageFDR level . Significantly correlated gene pairs (FDR <0.05) were ranked and iteratively tested for planarity to grow a Planar Filtered Network using the Planar Maximally Filtered Graph (PMFG) technique . Finally, we conducted a multiscale clustering analysis to identify coexpression modules at different network scale topology, as well as their hub genes (function: do.MEGENA). Significant coexpression modules (permuted p < 0.05) were retained for downstream analysis. We extracted module eigengenes  using the function moduleEigengenes from the WGCNA R‐package,limma R‐package,ggnet.The enrichment test was conducted by hypergeometric statistics using the function 33.1p‐values >0.097), with correlation coefficients (|r|) ranging from 0.118 to 0.416 , suggesting that these factors could have a meaningful impact on expression patterns even though they were not statistically significant at our chosen threshold.All subjects were males, with an average age of 43.2 years . The average PMI was 17.18 h , and the average RIN was 8.05 . Sixteen samples (88.9%) had a RIN >7, and seventeen samples (94.4%) had a RIN >6. All samples were sequenced for a total of 504.1 M reads . The average percentage mapping rate (uniquely mapped reads) was 70.2% (range: 45.3%–78.7%) Figure . Eleven  Figures . Despite3.2n = 315; 96%). In ASPD+CD samples, astrocyte genes (n = 33) were significantly enriched among upregulated genes (FDR = 1.21E‐16), while excitatory neuron genes were significantly enriched among downregulated genes (FDR = 1.84E‐07)  Table . Of thes7) Table .As shown in Figure CALM3, encoding the protein calmodulin 3)   Figure . Another) Tables .4To the best of our knowledge, this is the first unbiased and comprehensive characterization of gene‐expression alterations in postmortem OFC samples from subjects with ASPD and CD. Consistent with epidemiological evidence showing an extremely high prevalence of SUD in individuals with lifetime diagnoses of ASPD and CD, all subjects in this group had used substances, including alcohol. Additionally, five of the subjects had comorbid mood disorders such as depressive disorders or dysthymia.FOXP2, MAOA, and other serotonin‐related genes. The top downregulated DEG, COPS7A, is a component of the COP9 signalosome (CSN), a master regulator of the ubiquitin conjugation pathway.UBQLN4 (ubiquitin 4), UBA1 , RAD23A (which delivers ubiquitinated proteins to the proteasome), and PSMC3 (a regulator subunit of the 26S proteasome).The comparison of postmortem OFC samples from individuals with ASPD+CD and age‐matched unaffected controls identified 328 differentially expressed genes (DEGs). Notably, this set did not include key genes associated with antisocial or externalizing behavior  and associated transporters (dynactin subunits DCTN1 and DCTN3). In line with these findings, the largest module identified by coexpression network analyses (M7) featured the downregulation of transcripts related to synaptic and dendritic modulations. The hub of this module, CALM3 , encodes calmodulin 3, a key regulator of microtubule functions.SLC1A2, encoding excitatory amino acid transporter 2, the major glutamate transporter in the brain, which is expressed predominantly in astrocytesGLUD1 (glutamate dehydrogenase 1), which catalyzes the degradation of glutamate into α‐ketoglutarate in both astrocytes and neurons, which is also essential to sustain oxidative energy metabolism.GO analyses revealed significant downregulation of several gene clusters related to excitatory neurons of the OFC, namely glutamatergic pyramidal cells. This reduction was observed across key functional domains, namely vesicle and neurotransmitter transport, synaptic organization, ATP biosynthesis, and aerobic respiration. In line with these alterations, most differences were related to neuronal cell body, axon, mitochondria, and glutamatergic synapse/postsynaptic density. Notably, a marked downregulation was found in genes encoding microtubule‐associated molecules, such as tubulin chains (Finally, our analyses documented the upregulation of Wnt pathways. Wnt proteins are cysteine‐rich glycoproteins associated with different signaling pathways.Ample evidence has shown that OFC functional deficits lead to disinhibition, impulsivity, lack of insight, lack of concern with the consequences of one's actions, irresponsibility, social inappropriateness, and deficits in social behavior interpretations.Several limitations of this study should be acknowledged. Firstly, our analyses were conducted on a limited number of brain samples from individuals diagnosed with CD and ASPD. Three of these subjects had a CD, but not ASPD, diagnosis. Notably, their mean age of death was 50.67 years, suggesting that their sociopathic tendencies may have subsided in adulthood, and they had not engaged in pervasive antisocial behavior for more than 30 years. However, the limited power of our analyses does not allow us to verify whether the transcriptomic profile of these individuals may significantly diverge from the others in the same group. Secondly, all subjects were males, reflecting the high sex disproportion observed in ASPD and CD. Thus, it remains unclear whether our results may be generalizable to both genders. Thirdly, all subjects with ASPD and/or CD had a history of drug use, and most had a lifetime diagnosis of mood disorders, reflecting the high comorbidity rates observed in these conditions. Because of this substantial overlap, we cannot exclude that some of the transcriptomic alterations in the OFC may be linked to these comorbid psychiatric entities, rather than ASPD and CD itself. At the same time, it is worth noting that the relationship between ASPD/CD and drug use is complex, and each condition worsens the other in a downward spiral. In addition, these disorders share common vulnerability factors. From this perspective, our data may provide insight into the alterations of the OFC in relation to the comorbidity of ASPD and SUD within the externalizing spectrum.All these limitations stem primarily from the scarcity of available postmortem brain samples from individuals with diagnoses of ASPD and CD. Although the acquisition of these samples has been made possible by the recent establishment of large brain bank networks, such as the NBB repository in the US, concerted efforts are required to obtain more specimens for targeted analyses on these diagnostic groups. As more postmortem specimens become available, future studies on larger numbers of samples will be needed to corroborate and expand upon the preliminary findings presented in this study.In conclusion, this study presents the first transcriptomic profiles of the right OFCs in ASPD and CD. Our results suggest that these psychiatric disorders may be characterized by a complex array of functional deficits in the pyramidal neurons of this brain region, including dysfunctional synaptic regulation, microtubule organization, and bioenergetic deficits in pyramidal neurons. The development of novel animal models that may reproduce some of these deficits may prove particularly useful in establishing how these molecular alterations contribute to the ontogeny of antisocial behavior. Such insights could ultimately help establish new leads for the development of more targeted and effective treatments for individuals with ASPD and CD.Ignazio S. Piras: Bioinformatic analyses, Data Curation, Writing of the first draft of the manuscript. Giulia Braccagni: Tissue processing, RNA extraction and sequencing, Data Curation, Editorial Assistance. Matthew J Huentelman: Methodology, Data Curation, Editing. Marco Bortolato: Conceptualization, Obtainment of tissues, Writing of the manuscript, Editing, Supervision, Supervision, Funding acquisition, Project administration.The authors declare no conflict of interest.Figures S1–S5.Click here for additional data file.Tables S1–S6.Click here for additional data file.


Head and neck squamous cell carcinoma (HNSCC) is one of the most common histological types of head and neck cancer. Epiberberine is a potent antitumour agent for several types of cancer. This study is aimed at investigating the regulatory and molecular mechanism of epiberberine on HNSSC cell metastasis. The results showed that epiberberine inhibited the motility of Ca9‐22 and FaDu cell lines at nontoxicity doses. Moreover, the epithelial‐mesenchymal transition (EMT)‐related proteins, vimentin, snail and slug, were found suppressing after epiberberine treatments. In addition, the JNK signalling cascade and the metalloproteinase 13 (MMP‐13) expression were also found downregulated by epiberberine. In conclusion, the present study demonstrates that epiberberine suppresses cell migration and invasion by regulating the JNK pathway and MMP‐13. These results suggest that epiberberine could be a potential antimetastatic agent in HNSCC cells. The most common histological type of head and neck cancer is referred to as squamous cell carcinoma (SCC), also called head and neck squamous cell carcinoma (HNSCC), which accounts for more than 90% of cases.Cancer metastasis is involved by multiple complex processes, including extracellular matrix (ECM) remodelling, epithelial‐mesenchymal transition (EMT), extravasation, intravasation, mesenchymal‐epithelial transition (MET) and colonization.Sinomenium acutum, Corydalis turtschaninovii and Coptis chinensis. It has been discovered in multitherapeutic effect, such as anticancer, antioxidant, antiadipogenesis, antidyslipidemia and antibacterial.Epiberberine is a protoberberine alkaloid found in 22.12. Epiberberine . The Ca9‐22 cell line was derived from a patient with gingival carcinoma,2.24 cells/well of Ca9‐22 or FaDu in a 96‐well plate, different doses of epiberberine  were treated for 24 h. 0.1% DMSO was treated as vehicle group (0 μM). Subsequently, the supernatant was removed from the cells, and the MTT reagent/culture medium mixer (1:10) was incubated with cells for 3 h. Purple formazan was dissolved in DMSO and then measured using a microplate reader (BioTek) at the absorbance of 570 nm.3‐‐2,5‐diphenyltetrazolium bromide  was used for detecting cell viability. Briefly, after seeding 1 × 102.33 cells in the reservoirs. After cell attached, the inserts were removed and then the cells were treated with different doses of epiberberine  for 24 h. The cell migrated ability of each group was recorded by micrography. According to the rate of migratory cells, the Ca9‐22 cell groups were recorded for 0, 6 and 24 h, while the FaDu cell groups were recorded for 0, 24 and 48 h.The wound‐healing assay is a method that measures directional cell migration in vitro.2.45 cells/mL and seeded in the upper chamber of the transwells. For the transwell invasion assay, matrigel (BD Biosciences) was added to the upper chamber of the transwells before cell seeding. The transwells for the migration and invasion assay were collected at 24 h, which were then fixed and stained with 10% Giemsa stain solution (Sigma‐Aldrich). The capacity of cell migration and invasion of each group was recorded using micrography.The transwell migration and invasion assay is used to measure the capacity of cell motility and invasiveness in vitro.2.5To determine protein expression in epiberberine‐treated HNSCC cells, a western blotting assay was performed. Cells treated with different doses of epiberberine  for 24 h were collected and lysed with RIPA buffer (MilliporeSigma) that contained protease and phosphatase inhibitors. An equally amount of samples were separated by 10% polyacrylamide gel and then transferred to polyvinylidene fluoride (PVDF) membranes (MilliporeSigma). After blocking with 5% skim milk, membranes were incubated with the indicated primary antibody at 4°C overnight. Primary antibodies against vimentin, slug, snail, matrix metalloproteinase‐13 (MMP‐13), phosphorylated extracellular signal‐related kinase (p‐ERK), ERK, phosphorylated c‐Jun N‐terminal kinase (p‐JNK), JNK, phosphorylated p38 (p‐p38) and p38 were purchased from Cell Signaling Technology; primary antibody against β‐actin was purchased from Novus Biologicals. Subsequently, secondary antibody against rabbit or mouse with peroxidase was incubated with membrane for 1 h at room temperature. The membranes were measured using a chemiluminescence photometer .2.6The human protease array kit  was conducted to analyse the relative level of selected proteases. According to the manual, cell lysates were collected and incubated with membranes from the human protease array kit at 4°C overnight. After being washed with wash buffer and incubated with streptavidin–HRP solution, membranes were measured using a chemiluminescence photometer .2.7MMP‐13; for the GEO database, the 22 pairs of HNSCC samples  of GSE6631MMP‐13.The information from Cancer Genome Atlas (TCGA) data and the Gene Expression Omnibus (GEO) database was analysed using GraphPad Prism V6.0 . For TCGA data, the 42 pairs of HNSCC samples  were included to determine the expression level of 2.8MMP‐13 were purchased from Cohesion Biosciences. Ca9‐22 and FaDu cells were transfected with each siRNA using Turbofect reagent (Thermo Fisher Scientific) for 24 h. The effects of siRNA were detected by western blotting assay.For investigating gene function, RNA interference (RNAi) is used to knock down the level of a particular protein.2.9anova followed by Tukey's multiple comparison test is used to compare multiple groups. The Student's t‐test is used for comparison of two groups. A p‐value less than 0.05 is considered significant.The statistical analysis in the present experiments was measured using GraphPad Prism V6.0 . One‐way 33.1After treatment with different doses of epiberberine, the cell viability of HNSCC cell lines was not affected at a dose of 10 μM and slightly reduced at doses of 20 and 40 μM Figure . Cell to3.2EMT markers such as E‐cadherin, N‐cadherin, vimentin, fibronectin, claudin‐1 and related transcription factors  have been found to correlate with the promotion or inhibition of cell mobility. As shown in Figure 3.3MMP‐13 for 48 h and following with epiberberine treatment for 24 h, the level of MMP‐13 protein was downregulated compared with the epiberberine‐alone group and the siMMP‐13 group, respectively, in both Ca9‐22 and FaDu cell lines , including the inactive form and catalytically phosphorylated forms, are signal‐transducted kinases that are involved in cellular response. The protein levels of ERK, JNK and p38 were detected using a western blot assay. As shown in Figure 4MMP‐13 siRNA with epiberberine also confirmed the role of the MMP‐13 and JNK pathway in cell motility. Epiberberine has been indicated as a low‐toxicity small molecule with multiple targets on several activities. Choi et al.50 value of epiberberine in gastric cancer cell line MKN‐45 and the hepatocellular carcinoma cell line HepG2 is 39.7 μM and 120.58 μg/mL, respectively.The present study is designed to investigate the regulatory and molecular mechanisms of epiberberine on cell motility of HNSCC cells. The results indicate that epiberberine inhibited cell motility at nontoxicity doses in Ca9‐22 and FaDu cell lines. The EMT markers and related transcription factors were regulated by epiberberine. The combination of JNK inhibitor or EMT is a preserved development programme involved in carcinogenesis that enhances the movement, invasion and resistance of apoptotic stimuli and confers metastatic properties in cancer cells.MMPs belong to a family of zinc‐dependent proteinases that are capable of promoting metastasis by remodelling surrounding ECM proteins during tumour progression.The MAPK cascade is known to correlate highly with tumour metastasis.5The present study demonstrates that epiberberine reduced Ca9‐22 and FaDu cell metastasis by inhibiting the JNK signalling cascade, EMT‐related proteins and MMP‐13 expression. Based on this study, we have first documented that epiberberine inhibits metastasis by targeting MMP‐13 in head and neck cancer cells. These findings provide new insights into the therapeutic activity of epiberberine in metastatic head and neck cancer.Hsin‐Yu Ho: Methodology ; software ; writing – original draft (lead). Mu‐Kuan Chen: Conceptualization . Chia‐Chieh Lin: Methodology ; software . Yu‐Sheng Lo: Methodology ; software . Yi‐Ching Chuang: Methodology ; software . Ming‐Ju Hsieh: Conceptualization ; writing – review and editing (lead).The authors declare that there are no conflicts of interest.


Cellular senescence has been listed as a hallmark of cancer, but its role in colorectal cancer (CRC) remains unclear. We comprehensively evaluated the transcriptome, genome, digital pathology, and clinical data from multiple datasets of CRC patients and proposed a novel senescence subtype for CRC. Multi‐omics data was used to analyze the biological features, tumor microenvironment, and mutation landscape of senescence subtypes, as well as drug sensitivity and immunotherapy response. The senescence score was constructed to better quantify senescence in each patient for clinical use. Unsupervised learning revealed three transcriptome‐based senescence subtypes. Cluster 1, characterized by low senescence and activated proliferative pathways, was sensitive to chemotherapeutic drugs. Cluster 2, characterized by intermediate senescence and high immune infiltration, exhibited significant immunotherapeutic advantages. Cluster 3, characterized by high senescence, high immune, and stroma infiltration, had a worse prognosis and maybe benefit from targeted therapy. We further constructed a senescence scoring system based on seven senescent genes through machine learning. Lower senescence scores were highly predictive of longer disease‐free survival, and patients with low senescence scores may benefit from immunotherapy. We proposed the senescence subtypes of CRC and our findings provide potential treatment interventions for each CRC senescence subtype to promote precision treatment. Schema flow chart of the study. The analysis included multi‐omics data from transcriptomic, genomic, and whole slide images of more than 2500 colorectal cancer (CRC) patients. Senescence subtypes were established by unsupervised clustering, and multi‐omics data were utilized to further analyze the biological characteristics, tumor microenvironment, mutational landscape, and drug sensitivity of the senescence subtypes. Finally, the senescence scoring system senescore was developed and its clinical prognosis and therapeutic efficacy were validated in multiple CRC cohorts. In recent years, researchers have found that tumor heterogeneity can promote the evolution and adaptation of tumors and hinder the effectiveness of individualized drug strategies,It is known that cancer cells are characterized by a series of hallmarks different from non‐neoplastic cells.n = 587) and multiple public datasets. We identified three distinct senescence subtypes with significantly different biological characteristics, prognosis, and treatment response. We further constructed a senescent scoring system and assessed whether senescent scores can be used as prognostic biomarkers to guide clinical treatment decisions. Our research proposed CRC senescence subtypes which have good applicability in the Chinese population, as well as universality and reliability in other populations. Overall, our study contributed to the role of senescence in CRC and provided a foundation for the development of precision medicine strategies for CRC patients.To address these critical problems, we comprehensively analyzed the senescent heterogeneity in CRC through a large in‐house RNA‐seq cohort (22.1https://www.gsea‐msigdb.org/gsea/msigdb) using the keywords “senescence”, “senescent” and “aging”  between CRC and paired adjacent normal tissue. We also conducted univariate Cox analysis on all CRC genes from the ICGC‐ARGO dataset and obtained 12,000 survival genes related to disease‐free survival (DFS). In addition, we obtained 1,409 senescence genes from Peters et al.’s study.2.2MYC and other cell cycle‐related pathways. Cluster 2 displayed significantly higher activation in interferon, inflammation response and other immune‐related pathways. Cluster 3 was highly enriched in tumor development and signaling pathways such as the epithelial‐mesenchymal transition (EMT), NOTCH and PI3K , and cluster 3 presented the worst prognosis . In cluster 2, there were significant co‐mutations between OBSCN and TTN, RYR2 and FAT4, and ZFHX4 and MUC16 (p < 0.05). In cluster 3, there were significant co‐mutations between OBSCN and MUC16, and FAT3 and SYNE1 (p < 0.05)  and cluster 3 had the highest stromal score (p < 0.0001) by the ESTIMATE algorithm , PDCD1(PD‐1), CTLA4, and LAG3 were higher in cluster 2, while myeloid‐derived suppressor cells (MDSC), cancer‐associated fibroblasts (CAFs), EMT, T cell exhaustion and other immune suppression/exclusion/exhaustion related signatures were most expressed in cluster 3  was used as the training cohort. 20 top expressed genes were screened out from 77 CSGs to further construct the LASSO model. Finally, 7 CSGs were selected and weighted sum for the construction of senescence scoring model  + (0.0288 × IGFBP7) + (0.0168 × BHLHE40) + (0.106 × TTYH3) + (0.0077 × TIMP1) + (0.119 × TAGLN) + (0.0277 × PLOD3).To accurately quantify the senescent characteristics of individual patients, we constructed a senescence scoring model to quantify the level of senescence in individual CRC patients. The ICGC‐ARGO  in the ICGC‐ARGO cohort  , and a greater proportion of patients in the low group responded to immunotherapy (p = 0.0159)  Figure . In addi) Figure . For bet) Figure . The cal) Figure . We demo) Figure . In addie Figure . Besidese Figure . The hise Figure . Immunohs Figure . Notablys Figure . Hallmars Figure . The sens Figure . Besides) Figure . These r3More and more studies have shown that the accumulation of senescent cells in tissues and organs with aging and at sites of various pathologies was largely detrimental.MYC, and other pathways. We, therefore, defined it as a proliferative/senescence low subtype. By utilizing the GDSC database, we found that cluster 1 was more sensitive to the VE‐822, which reduced tumor cell survival by attenuating the ATR signaling pathway.CD274 (PD‐L1), PDCD1 (PD‐1), CTLA4, and LAG3. So we defined cluster 2 as an immunosensitive/senescence intermediate subtype, and the validation in the IMvigor210 dataset further confirmed the better benefit of immunotherapy for PD‐L1 in cluster 2 CRC patients. Cluster 3 was characterized by the highest senescence, higher stromal infiltration, and poor survival prognosis. Cluster 3 was highly enriched in tumor development pathways such as EMT, WNT, HIPPO, and molecules such as MDSC, CAFs, and T cell exhaustion were most expressed in cluster 3. We defined cluster 3 as a stromal/senescence high subtype, for which conventional chemotherapeutic agents and immunotherapy had low therapeutic effects on it. In the GDSC database, cluster 3 only had a significant therapeutic effect on the drug Sepantronium‐bromide (YM‐155), which was an effective inhibitor of survivin‐targeting DNA topoisomerases.In addition, we identified three senescence subtypes in patients with CRC. The three senescence subtypes differed significantly in biological features, TME, and mutation landscape. Cluster1 with low senescence was highly enriched in the cell cycle, The CMS classification system provides a more accurate way of classifying CRC based on gene expression profiles.CDKN1A, CDKN2A, and CBX7 protein expression was significantly higher in the high senescence group compared to the low senescence group. However, there was no statistically significant difference in SIRT1 protein expression between the two groups, possibly due to its relatively low expression level and the influence of post‐transcriptional modifications, post‐translational modifications, and metabolic homeostasis. Besides, we observed that a high senescence score correlated with a high stromal score, high EMT, and high content of CAFs. Also, some studies found that high stromal infiltration was closely associated with senescence.In addition, we developed a senescence score model consisting of seven CSGs to assess the level of senescence in CRC, which was easier to translate into clinical practice. Our comprehensive analysis showed that the senescence score had an important clinical correlation and it was a robust prognostic biomarker. More importantly, the senescence score was proven to be an independent factor for DFS. In the IHC results, we found that Moreover, CRC patients with low senescence scores were more likely to benefit from immunotherapy. Therefore, the senescence score model was also a candidate biomarker to evaluate the therapeutic benefit of PD‐L1, and patients with high senescence scores may not be suitable for immunotherapy due to potential drug resistance and immune‐related adverse event.Our research had some limitations. First, this is a retrospective study, although we validated the senescence subtypes and senescence scores in multiple independent datasets. Future validation of senescence subtypes and senescence scoring system should be performed in a prospective multicenter cohort. In addition, clinical evaluation of drug sensitivity tests is needed. We look forward to conducting clinical trials and transforming our results into clinical practice.In conclusion, we proposed senescence subtypes for CRC patients. Our analysis showed that the three senescence subtypes had their prominent characteristics and were appropriate for different therapeutic strategies. The proposed senescence subtypes provide a new basis for precise diagnosis and treatment of CRC patients, paving the way for developing more rational treatment recommendations and facilitating personalized cancer therapy.44.1https://www.icgc‐argo.org/page/89/project‐list). The ICGC‐ARGO cohort was selected as the discovery cohort, while TCGA‐CRC, GSE17538, GSE14333, GSE33113, GSE37892, and GSE39582 were used for validation (Table https://www.ncbi.nlm.nih.gov/geo/) and the Cancer Genome Atlas .The workflow of this study was shown in Figure For RNA‐seq data of ICGC‐ARGO, HISAT4.2P < 0.05 and the |log fold change| > 1. We also performed a univariate Cox analysis with all genes in CRC from the ICGC‐ARGO dataset and obtained survival genes associated with DFS. Besides, we obtained 1,499 senescent genes from Peters, et.al.’ s research.The differentially expressed genes (DEGs) between CRC and normal colorectal tissues were screened via the “DESeq2” package. The significant criteria for determining DEGs were set as the 4.3Unsupervised clustering analysis was applied to identify distinct senescence subtypes based on the expression of CSGs. This process was performed in R using the “ConsensusClusterPlus” package (CCP)4.4Single‐sample gene set enrichment analysis (ssGSEA) was employed to quantify the relative abundance of each cell infiltration. Analysis of the gene set of each TME infiltrating immune cell type was obtained from the study of Charoentong et al.4.5The somatic mutation data were acquired by the “TCGAbiolinks4.6To further explore the clinical application of the CRC senescence subtypes and our model, we used GDSC4.7To better quantify and translate cellular senescence into clinical practice, we developed a senescence scoring system using the least absolute shrinkage and selection operator (LASSO) algorithm. A total of 77 CSGs were included to narrow down and further develop the senescence scoring system. The penalty parameter λ value of the LASSO model was selected based on tenfold cross‐validation, and lambda.1se was used to avoid overfitting. By weighted summation of the expression value of feature genes and their corresponding coefficients obtained from the model, the senescence score was generated. The optimal cut‐off value calculated by the “survminer” package4.8https://doi.org/10.5281/zenodo.1214456.https://openslide.org/). Each tile was normalized with the Macenko methodIn this study, we retrieved 581 H&E slides of 581 CRC patients from the TCGA cohort (COAD and READ) and use a pathological tile tissue classification algorithm to explore their composition ratio in different senescence subtypes. The classification model was trained and validated on the two public datasets, NCT‐CRC‐HE‐100k and CRC‐VAL‐HE‐7K from 4.9Tissue sections from CRC specimens were deparaffinized in xylene, rehydrated through graded ethanol, and subjected to antigen retrieval by heating in sodium citrate (pH 6.0) in a microwave oven for 15 min. Endogenous peroxidase activity was blocked by incubation in 3% hydrogen peroxide. After blocking with 20% goat serum for 30 min at room temperature, the sections were incubated overnight at 4°C with the primary antibodies Table . The EnV4.10p‐value of less than 0.05 was considered statistically significant. All processing was done in the R 4.1.1 software.For the comparison of continuous variables between two groups, the statistical significance of variables was analyzed using the Wilcoxon rank sum test, while the Kruskal Wallis test was used to assess the significant difference for more than two group comparisons. The chi‐square test was used to compare categorical variables. Cox regression and Kaplan‐Meier analysis were conducted by the “survival” R package. The “survminer” R package was performed to determine the optimal cut‐off value. A M.Y.L., D.C., C.H.L., and J.G.C. contributed equally to this study. M.Y.L., D.C., C.H.L, J.G.C., P.L., X.J.W., X.S.H., and F.G. contributed to the study concept and design, the acquisition, analysis, and interpretation of data, and the drafting of the manuscript. G.M.L., C.L.H., B.W.G., and J.X.L. contributed to the data collection and manuscript reviews. All authors have read and approved the final manuscript.The authors declare no conflict of interest.The research scheme was approved by the Ethics Review Committee of the Sixth Affiliated Hospital, Sun Yat‐sen University (2022ZSLYEC‐362).Supporting InformationClick here for additional data file.


Vitamin D is important for bone and cartilage metabolism. Changes in vitamin D blood level may be related to pathological disorders such as rheumatoid arthritis (RA). The main aim of this study is to investigate the association between RA and the vitamin D receptor (VDR) genes FokI and TaqI polymorphisms. One hundred RA patients and fifty healthy matched controls were assessed for VDR FokI and TaqI genotyping. Intact parathyroid hormone (PTH) and calcium (Ca) levels were measured, categorized, and compared between the cases and control groups.We found that the FokI genotype frequencies for the RA cases and control groups were FF:Ff:ff = 46%:52%:2% and 50%:50%:0%, respectively (P = 0.76). The TaqI genotype frequencies for the RA cases and control groups were TT:Tt:tt = 45%:44%:11% and 42%:42%:16%, respectively (P = 0.69). A statistically significant high serum PTH level was associated with the ff genotype (p = 0.03), and a significantly low serum Ca level was associated with the TT genotype (p = 0.003). In comparison with controls, no influence of VDR FokI and TaqI genotypes on RA susceptibility or risk was demonstrated. Persistent symmetric polyarthritis (synovitis) is the defining characteristic of rheumatoid arthritis (RA), a chronic multisystem inflammatory illness. Any joint can be affected, though an extra-articular association of organs such as the skin, heart, lungs, and eyes can occur. Rheumatoid arthritis (RA) affects the joints, causing them to become warm, swollen, and painful. Pain and stiffness often worsen after periods of inactivity .The vitamin D receptors (VDR) act as ligand-activated, transcriptional-controlling proteins. They selectively bind the 1,25-dihydroxyvitamin D3  hormone and control the expression of selected genes in target cells .The VDR FokI gene rs2228570) has a unique role in immunity 70 has a .The VDR TaqI gene rs731236) resulted in a T-to-C substitution at codon 352 within exon 9 31236 res. It has Parathyroid hormone (PTH) is secreted by four parathyroid glands. Normally, its production is increased when calcium (Ca) levels in the blood are low. PTH sends a signal to the bones to release Ca into the blood and to the kidneys to reabsorb Ca and excrete phosphorus. Additionally, PTH plays an important role in intestinal absorption by causing the conversion of vitamin D into its active form. PTH increases the activation of 25-hydroxy vitamin D to 1,25-dihydroxy vitamin D in the kidneys, which then motivates the intestines to absorb both calcium and phosphorus . The norThe aim of this study is to compare the VDR genes FokI and TaqI in RA cases and controls and to evaluate their relationship to PTH and Ca levels.This case–control study was carried out at special rheumatology clinics, where all medical assessments were performed.Adults aged over 30 years were divided into two groups: the first group (cases) included 100 previously diagnosed rheumatoid arthritis patients who met the 2010 “American College of Rheumatology/European League against Rheumatism classification criteria for RA patients”. . The secSamples for both the cases and control groups were selected by consecutive sampling. All patients underwent a complete history-taking, medical examination, laboratory, and radiological investigations. Figure For all cases and controls, we measured serum intact PTH levels, calcium (Ca), and assessed for VDR gene FokI and TaqI genotypes.The Calbiotech intact PTH ELISA Kit was used for the quantitative determination of intact PTH in human serum or plasma. The intact PTH level normal range is 10–65 pg/mL; we categorized them as ≤ 65 pg/mL and > 65 pg/mL.The Spinreact Kit was used for the quantitative determination of calcium in human serum or plasma. The normal calcium level range is (8.5–10.5 mg/dL); we categorized it into (≥ 8.5 mg/dL) and (< 8.5 mg/dL).Relationships between FokI and TaqI genotypes, PTH levels, and Ca levels were compared between cases and controls.The FokI (rs2228570), and TaqI rs731236) polymorphisms were analyzed using polymerase chain reaction—restriction fragment length polymorphism (RFLP). Genomic DNA was extracted from peripheral white blood cells using the salting out method  for continuous variables. Chi-Square and Fisher’s exact tests were used for comparing categorical data. An independent t-test was used in the case of two unrelated groups. One-way analysis of variance (ANOVA) was used to compare the means of three or more independent groups. A p-value of 0.05 was set as the threshold of statistical significance. MedCalc version 20 software was used to analyze the receiver operating characteristic (ROC) curve.This study included one hundred rheumatoid arthritis patients and fifty healthy controls. 32 were male and 118 were female.Table Figure Table FokI genotype frequencies for the RA cases and control groups were FF:Ff:ff = 46%:52%:2% and 50%:50%:0%, respectively (P = 0.76). In addition, the frequencies of the F and f alleles in RA cases were 72%:28% and 75%:25% in the control group.TaqI genotype frequencies for the RA cases and control groups were TT:Tt:tt = 45%:44%:11% and 42%:42%:16%, respectively (P = 0.69). In addition, the frequencies of the T and t alleles in RA cases were 67%:33% and 63%:37% in the control group.We noticed that having any of the FokI genotypes  had no higher risk of being an RA patient, and likewise for TaqI genotypes .So, there is no contribution of the vitamin D receptor genes FokI and TaqI genotypes to the development of RA.Table The M ± SD serum Ca levels in FF, Ff, and ff genotypes were 8.43 ± 1.14, 8.56 ± 1.21, and 7.8 ± 0.42, respectively, with no statistically significant difference among these values (p = 0.62). The M ± SD serum Ca levels between FF + Ff and ff genotypes were 8.5 ± 1.17 and 7.8 ± 0.42, respectively, with no statistically significant difference between these values (p = 0.41). The M ± SD serum Ca levels between ff + Ff and FF genotypes were 8.53 ± 1.19 and 8.43 ± 1.14, respectively, with no statistically significant difference between these values (p = 0.68).Figure Table The M ± SD serum Ca levels in TT, Tt, and tt genotypes were 8.08 ± 1.16, 8.91 ± 1.15, and 8.43 ± 0.55, respectively, with a statistically significant difference among these values (p = 0.003). Multiple comparisons revealed significantly lower serum Ca levels associated with the TT genotype than the Tt genotype (p = 0.001).The M ± SD serum Ca levels between TT + Tt and tt genotypes were 8.49 ± 1.22 and 8.43 ± 0.55, respectively, with no statistically significant difference between these values (p = 0.87). The M ± SD serum Ca levels between tt + Tt and TT genotypes were 8.82 ± 1.07 and 8.08 ± 1.16, respectively, with a statistically significant difference between these values (p = 0.001), Thus significantly low serum Ca levels were associated with the TT genotype.Figure Figure In this study, we compared RA patients and a healthy control group regarding the vitamin D receptor genes FokI and TaqI polymorphisms, PTH level, and Ca level. FokI and TaqI genotypes were detected using the PCR–RFLP technique, and the results showed that there were no significant differences in genotype or allele frequency observed between the two groups. This suggests that there is no association between the FokI and TaqI genes and the prevalence of RA disease.Many previous studies have supported these findings. A study in the Lithuanian population found that none of the four VDR gene polymorphisms  were associated with a genetic predisposition to RA. . An IndiIn contrast to previous studies, a case–control study was conducted to test for polymorphisms associated with RA  and other genes by genotyping 105 RA patients and 80 controls. The conclusion was that all the studied single nucleotide polymorphisms (SNPs) may contribute to the susceptibility of RA disease, except for the FokI SNP . AnotherIn this study, we found no statistically significant difference between RA cases and control groups regarding age, gender, and PTH level, but a statistically significant difference was found between the two groups regarding Ca level (p < 0.001).The relationship between rheumatoid arthritis (RA) and parathyroid hormone (PTH) levels is ambiguous and unclear. Therefore, the role of RA disease in PTH levels is not the main aim or focus of this study. Many patients with active RA exhibited biochemical features suggestive of hyperparathyroidism, despite having normal serum PTH levels . PTH andAgreeing with these results, a study revealed that serum PTH levels were in the normal range in 81.6% of patients with active RA and in 88.7% of patients with silent RA (p = 0.331). The serum level of PTH was also not affected by patients’ gender, age, or duration of the disease . AnotherIn contrast to these findings, a study found that the presence of bone erosion in RA is associated with low bone mineral density levels and high PTH levels. These associations in people with RA are independent of other common factors of bone mass and mineral metabolism and the severity of functional impairment .We found a significant difference between the RA and control groups regarding Ca level (p < 0.001) in this study. In a cross-sectional study of 394 patients with rheumatoid arthritis investigating the total serum calcium levels, Ca levels were lower in RA than in healthy adults . CalciumIn this study, patients with the ff genotype had significantly high serum PTH levels. However, in a cross-sectional study of 50 hemodialysis patients and 30 healthy adults as a control group, the FF genotype of the FokI gene was more frequent in hemodialysis patients with higher intact PTH levels .Against the study results, another study found that between the VDR genotypes determined by PCR, there was no detectable variation in serum PTH levels for diabetic patients in a study analyzed by PCR–RFLP of the VDR gene in 877 Japanese hemodialysis patients . Also, tThis study has some limitations. First, the results cannot be generalized to all populations because the study was limited to participants from one country without including different ethnicities. Similar studies are needed in multiple countries to generalize the results. Second, the study biomarkers were assessed only once, so longitudinal data are not available.There is no contribution from the vitamin D receptor genes FokI and TaqI genotypes to the development of RA. Parathyroid hormone levels are not affected by RA disease; on the contrary, blood Ca levels decrease in RA patients. Rheumatoid arthritis may cause hypocalcemia but may not affect PTH secretion because of other controlling factors.Regarding FokI and TaqI genotypes, significantly high serum PTH levels are associated with ff genotypes and significantly low serum Ca levels are associated with TT genotypes. There is a possible role of FokI and TaqI genes in controlling the levels of PTH hormone and calcium. Intact serum PTH levels were effective in predicting hypocalcemia in RA patients.