Robson's Ten Group Classification System (TGCS) creates clinically relevant sub‐groups for monitoring caesarean birth rates. This study assesses whether this classification can be derived from routine data in Europe and uses it to analyse national caesarean rates.Observational study using routine data.Twenty‐seven EU member states plus Iceland, Norway, Switzerland and the UK.All births at ≥22 weeks of gestational age in 2015.National statistical offices and medical birth registers derived numbers of caesarean births in TGCS groups.Overall caesarean rate, prevalence and caesarean rates in each of the TGCS groups.P = 0.04). Countries with higher caesarean rates tended to have higher rates in all TGCS groups. Substantial heterogeneity was observed, however, especially for groups 5 (previous caesarean section), 6, 7 (nulliparous/multiparous breech) and 10 . The differences in percentages of abnormal lies, group 9, illustrate potential misclassification arising from unstandardised definitions.Of 31 countries, 18 were able to provide data on the TGCS groups, with UK data available only from Northern Ireland. Caesarean birth rates ranged from 16.1 to 56.9%. Countries providing TGCS data had lower caesarean rates than countries without data (25.8% versus 32.9%, Although further validation of data quality is needed, using TGCS in Europe provides valuable comparator and baseline data for benchmarking and surveillance. Higher caesarean rates in countries unable to construct the TGCS suggest that effective routine information systems may be an indicator of a country's investment in implementing evidence‐based caesarean policies.Many European countries can provide Robson's Ten‐Group Classification to improve caesarean rate comparisons. Many European countries can provide Robson's Ten‐Group Classification to improve caesarean rate comparisons. Caesarean birth rates differ by a factor of three in European countries from just over 15% to over 45%, as shown in recent data from the Euro‐Peristat project.As the overall caesarean rate conflates multiple groups with differing levels of risk, subdividing it by risk group is an important first step for comparative analyses. The Ten‐Group Classification System (TGCS), proposed in 2001 by Michael Robson, provides a clinically relevant framework for assessing differences in the caesarean rate and, as stated by Robson, ‘serves as the initial structure within which additional epidemiological variables, processes, perinatal events and outcomes in addition to caesarean sections can be analysed.’The Euro‐Peristat project, which aims to monitor perinatal health indicators in Europe, recommends the presentation of the caesarean rate by selected risk groups, which include those in the TGCS, but up to now, these have been collected and presented separately.Data come from the most recent collection of data, on births in 2015, by the Euro‐Peristat project.Euro‐Peristat requests data for all stillbirths and live births at 22 or more weeks of gestation, or weighing 500 g or more if gestational age is missing. When countries cannot provide data using this recommended inclusion threshold, they are asked to provide data using their national inclusion criteria along with a description of these criteria. Most provided data using the 22‐week threshold for live births, but other thresholds exist for stillbirths in some countries, such as a 500‐g limit or a 24‐week threshold.Mode of delivery is one of Euro‐Peristat's core indicators and is compiled separately by risk sub‐groups based on parity, plurality, fetal presentation, previous caesarean section and gestational age.Box 1+0 weeks) births in spontaneous labour;(1) Nulliparous, singleton, cephalic, term (≥37(2) Nulliparous, singleton, cephalic, term births with (2a) induced labour or (2b) prelabour caesarean section;(3) Multiparous, singleton, cephalic, term births without previous caesarean section in spontaneous labour;(4) Multiparous, singleton, cephalic, term births without previous caesarean section with (4a) induced labour or (4b) prelabour caesarean section;(5) Previous caesarean section, singleton, cephalic, term births;(6) Nulliparous singleton breech births;(7) Multiparous singleton breech births, including previous caesarean section;(8) Multiple pregnancies, including previous caesarean section;(9) Transverse and oblique lies, including previous caesarean section;+0 weeks), singleton, cephalic births, including previous caesarean section.(10) Preterm .t‐test. Greece does not have national data on the caesarean rate, so its rate was estimated from a WHO working group report (www.euro.who.int/en/countries/greece/news/news/2016/11/greece‐commits‐to‐addressing‐excessive‐reliance‐on‐caesarean‐sections).We described the overall caesarean birth rate for each country as calculated by Euro‐Peristat in its reports and assessed countries' capacity to provide data using the TGCS groups. We then compared caesarean birth rates by ability to provide data on TGCS using an independent sample two‐sided To compare the groups between countries, we produced graphs for each dimension of the recommended tables: the size of each group as a percentage of the total population of women having a live birth or stillbirth, the caesarean rate in each group and the absolute contribution of each group to the overall caesarean rate. To simplify the interpretation of this information, we ordered countries by their overall caesarean section rate from low to high. Because of the large numbers of countries and categories, it was not considered appropriate to use significance tests for comparisons between groups and countries. However, we drew attention to countries where denominators fell below 100 women for some groups . Spearman rank correlations were used to show associations between the TGCS groups.Euro‐Peristat received authorisations for its 2015 core database from the French Advisory Committee on Use of Health Data in Medical Research  and the French National Commission for Data Protection and Liberties .This analysis did not involve patients or patient groups.The TGCS is part of core outcome sets.Euro‐Peristat receives support as part of the InfAct Joint Action (Grant no. 801553) and data collection was partially funded as part of the BridgeHealth Project (Grant no. 665691), Public Health Programme, Consumers, Health, Agriculture and Food Executive Agency (CHAFEA). The funding agency was not involved in analysis or interpretation of results.P = 0.04).Caesarean rates in 2015, based on total births, ranged from 16.1% (Iceland) to 56.9% (Cyprus) as shown in Table Figure The proportion of childbearing women with a previous caesarean section varied from a low of 6.4% (Slovenia) to a high of 19.1% (Cyprus). In general, the percentage of women with a previous caesarean section was higher when overall rates were higher (ρ = 0.55). Higher overall caesarean rates were also correlated with a higher proportion of births in groups 6 and 7 (breech combined) (ρ = 0.53) and 10  (ρ = 0.69); we explored the hypothesis that a higher percentage of preterm births was related with groups 6 and 7 combined  as preterm births are more often breech; this was confirmed (ρ = 0.63). Finally, abnormal lies constituted a small proportion of births (<0.5%), except in Finland, Latvia, Estonia and Switzerland. In the first three countries this was accompanied by relatively low proportion of breeches (<2.5%), whereas in Switzerland both proportion were high.Figure In all countries, caesarean sections for women with previous caesarean sections contributed more than all other groups to the overall rate. In general, the contribution of all groups was greater in countries with higher caesarean rates, confirming the patterns observed in group‐specific caesarean rates Figure . HoweverMore than half of the European countries participating in the Euro‐Peristat project could classify caesarean births into the TGCS, illustrating the feasibility of using it to carry out routine monitoring of maternal and perinatal health at a national level. In general, countries with higher overall caesarean rates had higher rates in all TGCS groups. Substantial heterogeneity was also observed among countries with similar caesarean rates, however, especially for groups 5 (previous caesarean section), 6, 7 (nulliparous and multiparous breech) and 10 . On average, countries that could not provide data on the TGCS groups had higher caesarean rates, suggesting that having more comprehensive caesarean data in routine systems might contribute to implementing evidence‐based practice.The strengths of this study are the inclusion of a large number of countries, use of a common data collection protocol, crosschecks with other Euro‐Peristat indicators and the engagement of our network of experts and data providers in checking and interpreting the data. We also collected information on births with missing data, as recommended by previous reviews.Limitations primarily relate to misclassification due to unstandardised definitions and underreporting in routine data sources. These are most problematic for mode of onset of delivery, fetal presentation and previous caesarean section. For delivery onset, some countries classify caesarean sections as elective or emergency, which imperfectly maps onto whether labour did or did not begin before the caesarean section (elective caesarean sections can be carried out after labour begins and emergency caesarean sections can occur without labour). Similarly, for induction, there are inconsistencies linked to oxytocin use for induction or augmentation of labour and inclusions of amniotomy.Countries with higher caesarean rates overall tended to have higher caesarean rates in all TGCS groups and a higher absolute contribution from all groups. For instance, caesarean section for multiple births ranged from under 45% in countries with low overall rates to over 95% in countries with the highest overall rates. Caesarean rates for women with a previous caesarean section were also lower (under 60%) in countries with lower caesarean rates.Another heterogeneous group was breech deliveries. Most countries with high caesarean rates had breech delivery caesarean rates of 90% and over, as also reported in the USA,While the TGCS was primarily conceived as a tool to assess clinical practice at the facility level, it is useful for national and international reporting because it facilitates comparisons between homogeneous clinical groups and accentuates how caesarean sections in first pregnancies contribute to increasing caesarean rates. However, although these analyses constitute a first step towards investigating differences in caesarean rates,How care is organised, including the financial and time management incentives for obstetricians to perform caesarean sections as well as the availability of midwives and the nature of their roles within maternity services, is likely to be a central reason for many of these differences.Unfortunately, we could not include many of the countries in Europe with the highest caesarean rates in this study because they were unable to construct the TGCS. In the 2015 Euro‐Peristat report, these countries accounted for most of those with a caesarean birth rate of over 30% and had increases over 10% between 2010 and 2015.We were able to construct the TGCS for over half of European countries. Future work should continue to harmonise data definitions, and this classification constitutes an important comparator for individual countries and hospitals within these countries, baseline data for future surveillance and an impetus for countries to improve the quality and scope of their data systems.The authors have no interests to disclose. Completed disclosure of interests forms are available to view online as supporting information.JZ, MD, AM, SA, GH, ML, JN, HSO, EM, MG and BB conceived the study. JZ, MD and BB drafted the first draft and were responsible for the analysis. AM, GH, ML, JN, HSO, EM and MG contributed to analysis and interpretation of data. JZ, MD, AM, SA, GH, ML, JN, HSO, EM, MG, BB and the Euro‐Peristat Network critically reviewed and revised the manuscript. JZ, MD, AM, SA, GH, ML, JN, HSO, EM, MG, BB and the Euro‐Peristat Network provided data for the study and participated in interpretation. JZ, MD, AM, SA, GH, ML, JN, HSO, EM, MG, BB and the Euro‐Peristat Network approved the final manuscript.Euro‐Peristat received authorisations for its 2015 core database from the French Advisory Committee on Use of Health Data in Medical Research  and the French National Commission for Data Protection and Liberties .InfAct Joint Action (Grant no. 801553) and Bridge Health Project (Grant no. 665691), Public Health Programme, Consumers, Health, Agriculture and Food Executive Agency (CHAFEA).Table S1. Robson's Ten‐Group Classification System, including sub‐groups, in Belgium 2015.Table S2. Robson's Ten‐Group Classification System, including sub‐groups, in Cyprus 2015.Table S3. Robson's Ten‐Group Classification System, including sub‐groups, in Denmark 2015.Table S4. Robson's Ten‐Group Classification System, including sub‐groups, in Estonia 2015.Table S5. Robson's Ten‐Group Classification System, including sub‐groups, in Finland 2015.Table S6. Robson's Ten‐Group Classification System, including sub‐groups, in France 2016.Table S7. Robson's Ten‐Group Classification System, including sub‐groups, in Germany 2015.Table S8. Robson's Ten‐Group Classification System, including sub‐groups, in Iceland 2015.Table S9. Robson's Ten‐Group Classification System, including sub‐groups, in Italy 2015.Table S10. Robson's Ten‐Group Classification System, including sub‐groups, in Latvia 2015.Table S11. Robson's Ten‐Group Classification System, including sub‐groups, in Luxembourg 2015.Table S12. Robson's Ten‐Group Classification System, including sub‐groups, in Malta 2015.Table S13. Robson's Ten‐Group Classification System, including sub‐groups, in the Netherlands 2015.Table S14. Robson's Ten‐Group Classification System, including sub‐groups, in Northern Ireland 2015.Table S15. Robson's Ten‐Group Classification System, including sub‐groups, in Norway 2015.Table S16. Robson's Ten‐Group Classification System, including sub‐groups, in Slovenia 2015.Table S17. Robson's Ten‐Group Classification System, including sub‐groups, in Sweden 2015.Table S18. Robson's Ten‐Group Classification System, including sub‐groups, in Switzerland 2014.Click here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.


Primary tumor resection (PTR) as a treatment option for patients with stage IV pancreatic cancer (PC) is controversial.Stage IV PC patients, with treatment data from the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER), were screened. The main outcomes were overall survival (OS) and cancer‐specific survival (CSS).OS]: 13 vs. 9 months, p = 0.024; MSTCSS: 14 vs. 10 months, p = 0.035), and chemoradiotherapy plus PTR versus chemoradiotherapy . Multivariate adjusted analyses further confirmed these results. Stratified with different metastatic modalities, multivariate analyses suggested that PTR significantly improved the OS and CSS among patients with ≤1 metastatic organ, and that patients with brain metastasis might not benefit from chemotherapy treatment.We enrolled 15,836 stage IV PC patients in this study. Propensity score‐matched analyses revealed improved OS and CSS of patients receiving chemotherapy plus PTR versus chemotherapy (median survival time [MSTPTR improves the OS and CSS of stage IV PC patients on the basis of chemotherapy or chemoradiotherapy, provided that the metastases involve ≤1 organ. Chemotherapy, however, should be carefully considered in patients with metastases involving the brain. Primary site resection should be recommended for stage IV pancreatic cancer patients, provided that synchronous chemotherapy/chemoradiotherapy was administrated. Chemotherapy, however, may not bring survival benefits for those with brain metastases. The caliper was set to 0.05, with a matching ratio of 1:1. The matched covariates are presented in the corresponding tables.As timing of the enrollment relative to surgical resection differed, sequential landmark analyses were implemented to evaluate survival in varied settings for patients surviving a minimum of 0.5, 1, 2, and 3 years from diagnosis, to eliminate “time‐to‐treatment” bias.A forest plot was generated to evaluate the effect of PTR‐combined therapy on OS by subgroups including age, race, sex, grade, T/N stage, tumor location, metastatic site, and number of involved organs, and further, to explore the potential candidates suitable for PTR.p value of less than 0.05 was considered to be statistically significant.Statistical analyses were performed using SPSS version 26, and R version 3.6.3. Normally distributed continuous variables are displayed as average , while non‐normally distributed continuous variables are presented as median (Q1–Q3). The Kolmogorov–Smirnov test was used for normality testing of continuous variables. The Wilcoxon (Mann–Whitney) and Kruskal–Wallis tests were used to evaluate continuous variables. Categorical variables are presented as percentages and analyzed using Pearson's test. A two‐sided 3OS], 4 months; MSTCSS, 5 months). According to the different treatment types, patients were categorized into three groups: chemotherapy with or without PTR , chemoradiation with or without PTR (N = 699), and no treatment versus PTR only . All patient characteristics are presented in Table Among the 15,836 stage IV PC patients, the median follow‐up was 33 months .After adjusting for confounding covariates, PTR also significantly improved the OS and CSS in different comparison patterns. Figure , Table 2To eliminate time‐to‐treatment bias, sequential landmark analyses with landmarks set as 0, 0.5, 1, and 2 years after diagnosis, were performed. Figure  Chemothep < 0.001) except for that between primary site plus distant/regional site and primary site only . Additionally, in multivariate analyses, PTR increased the OS and CSS more significantly than distant/regional resection did . On the basis of primary site resection, distant/regional resection might not result in additional OS/CSS improvements. .Except for the primary site, the outcomes of patients receiving distant/regional site resections were also evaluated Table . The MSTA forest plot was constructed to verify whether the OS improvement seen with PTR existed in different subcategories. Figure  It was rFor different organ involvement modalities, we compared the OS and CSS using log‐rank analyses. Table  Stratifi4The majority of patients with PC (approximately 60%) were diagnosed with metastatic disease (stage IV).In our study, additional PTR significantly increased the OS and CSS, compared with PTR‐absent treatments in multivariable risk adjustment analyses, based on chemotherapy/chemoradiotherapy. PSM analyses were performed serving as the sensitivity analysis and the complementary verification.“Time‐to‐treatment” bias arises in comparative research, when survival time is measured from enrollment , and the receipt of treatment occurs during follow‐up. Patients with poor performance status or significantly aggressive disease, might die too early (before undergoing PTR), which creates an apparent survival disadvantage for patients who do not receive PTR. The time interval between the date of initial diagnosis and the date of surgery, was unknown in the SEER data. The longer the deferral, the greater the “time‐to‐treatment” bias is in favor of PTR. We speculated that “time‐to‐treatment” bias could partially explain the treatment effect estimate in previous studies. In our study, we used the landmark analysis, one of the recommended corrective approaches, to eliminate “time‐to‐treatment” bias, after which PTR with synchronous chemotherapy/chemoradiotherapy was still associated with improved OS and CSS.As suggested by Drs. Shi, Liu, and Shrikhande, the population for PTR should be carefully selected.To treat metastatic loci, Dünschede et al. recommended metachronous resection, while Tachezy et al. recommended synchronous resection for liver metastases. Dr. Liu, however, believed that both metachronous and synchronous metastatic resection, improved survival in lung metastases. However, some researchers have recommended nonsurgical treatment options.Due to the insufficiency of studies on metastatic patterns, stratified with different metastatic organ involvement modalities, we verified the impact of different treatments. PTR should be considered only if a single organ is involved, which corresponds to the discoveries in the forest plot analysis. Distant/regional site resection can be applied when only the liver is involved. If the brain is involved, the administration of chemotherapy should be carefully considered. Radiotherapy, however, was not beneficial for patients with stage IV PC; it could be considered as a last complementary choice. The survival prognoses of different metastatic organ modalities varied slightly (MST range ≤8 months). Therefore, the subgroup of metastatic behavior was of no use. In summary, patients with multiorgan or liver involvement were observed to have worse prognoses compared to those with brain, bone, or lung involvement.This study had some limitations. First, its retrospective nature limited the evidence value of our work. However, our discoveries provide more grounds for ethical committees to approve clinical trials on the subject matter. Second, due to the limitations of the database, details about the treatments, such as the treatment time, chemotherapy regimen, surgery details, and so on were not designed and recorded. These findings should be taken into consideration in future prospective studies. Third, information on the total tumor burden , as well as the response to treatment was lacking. Fourth, selection bias existed because of preference for surgery, for individuals whose general condition was more “acceptable.” Good performance status and personal habits may influence the OS, even though the NCCN guidelines bifurcated the strategies for stage IV PC patients based on performance status, while SEER lacked this information.Ultimately, “time‐to‐treatment” bias, the metastatic pattern analyses, and combined treatment analyses, which most previous studies neglected, were taken into consideration with a satisfactory sample size. In conclusion, we demonstrated improvements in OS and CSS in patients with stage IV PC. If only one organ is involved, surgery should be performed on the basis of chemotherapy or chemoradiotherapy. The use of chemotherapy as a treatment option in patients with brain metastasis, should be carefully considered due to the lack of significant improvement in OS and CSS in our studies.The authors report no conflict of interest.This study was exempt from institutional review board approval due to the nature of the study. Because all data were deidentified, patient consent was waived.Fig S1Click here for additional data file.Fig S2Click here for additional data file.Table S1Click here for additional data file.Table S2Click here for additional data file.Table S3Click here for additional data file.Table S4Click here for additional data file.Table S5Click here for additional data file.


To analyze the clinical characteristics and controllable risk factors of osteoporosis in elderly men with type‐2 diabetes mellitus (T2DM).A total of 250 elderly OP patients with T2DM were included in the present study. Patients with one or more common chronic diseases , and a course of more than 3 years were defined as complicated with chronic diseases. Blood glucose, cholesterol, triglyceride, low‐density lipoprotein, high‐density lipoprotein, calcium, phosphorus, glycosylated hemoglobin, urea nitrogen, creatinine, fasting insulin, liver function, and 25‐hydroxy vitamin D3 levels were measured. Bone mineral density was also measured.A total of 16 patients (6.4%) had severe osteoporosis. Furthermore, 66 patients (26.4%) had blood glucose control that reached the standard, while 176 patients (70.4%) used more than two anti‐diabetic drugs. The serum testosterone level was lower than the median in 87 patients (34.8%) and in 56 smokers (22.4%). Furthermore, 138 patients (55.2%) were overweight and obese, six patients (2.4%) were underweight, 197 patients (78.8%) had chronic diseases, 88 patients (35.2%) were sticking to exercise, and 117 patients (46.8%) had less exercise. In addition, 92 patients (36.8%) were treated with osteotrophy‐protective agents, and 24 patients (9.6%) received anti‐osteoporosis therapy. Smoking, poor glycemic control, low testosterone levels, less exercise, and complications with chronic diseases were the most relevant controllable risk factors.For elderly male osteoporosis patients with type‐2 diabetes, smoking cessation, blood sugar control up to the standard, regular exercise, active prevention and treatment of complications, and appropriate testosterone supplementation are necessary for preventing and curing osteoporosis. Technology roadmap Osteoporosis is a kind of systemic bone disease characterized by decreased bone mass and damaged microstructure of the bone, which results in increased osteopsathyrosis and vulnerability to fracture. This disease can be divided into two categories: primary osteoporosis and secondary osteoporosisT2DM is a chronic metabolic disease and an age‐related disease. It is also one of the risk factors for OPThe inclusion criteria for this study are as follows: (i) people who were diagnosed with T2DM in accordance with the World Health Organization (WHO 1999) definitionThe exclusion criteria for this study are as follows: (i) patients with acute diabetic complications; (ii) patients with severe hepatic and renal insufficiency, abnormal endocrine and metabolic disorders, digestive tract diseases and malignant tumors; (iii) patients who received adrenal glucocorticoids and androgens, and drugs that could affect bone metabolism; (v) patients with mobility difficulties, infirmity of age and communication barriers, and those unable to cooperate with the completion of all examinations; (iv) patients who were unwilling to cooperate with the completion of the questionnaire.A total of 250 elderly OP patients with T2DM were included in the present study. These patients were treated in the endocrine ward from the first affifiliated hospital of Xinjiang medical university January 2018 to November 2019, had a mean age of 72.3 ± 8.4 years old, and a course of T2DM of 8.7 ± 3.2 years. The following data were measured to analyze the clinical characteristics and controllable risk factors of osteoporosis in elderly men with T2DM: (i) the clinical characteristics and (ii) controllable risk factors of osteoporosis in elderly men with type‐2 diabetes mellitus. Smoking was defined as more than three cigarettes per day, which lasted for over 3 months. Exercise for less than 150 min per week was considered as less, while exercise not less than three times a week, not less than 30 min each time was considered as regular exercise. Patients with one or more common chronic diseases and a course of more than 3 years were defined as complicated with chronic diseases. Common chronic diseases mainly included hypertension, coronary heart disease, heart failure, chronic bronchitis, chronic nephrosis, and cirrhosis. The diagnostic criteria were all referred to the relevant guidelines recommended by the Chinese Medical Association. The diagnosis of patients being overweight and/or obese was based on the criteria recommended in the Guidelines for the Prevention and Treatment of Type‐2 Diabetes formulated by Diabetes Branch of the Chinese Medical Association.The present study protocol was approved by the hospital medical science ethics committee, and patients provided signed informed consent.The height, weight, blood pressure, and body mass index (BMI) were measured by specially trained medical staff using unified standards under fasting in the morning. A questionnaire was made to collect the smoking history, past history, and other related information. The information was collected from uniform questionnaires.Venous blood was drawn from all the subjects in the morning after fasting for 12 h. The blood samples were measured for blood glucose, cholesterol, triglyceride, low‐density lipoprotein, high‐density lipoprotein, calcium, phosphorus, glycosylated hemoglobin, urea nitrogen, creatinine, fasting insulin, liver function, and 25‐hydroxy vitamin D3 levels using the automatic biochemical instrument in the hospital clinical laboratory on the same day.2, with a coefficient of variation <1%. The diagnosis report for the test results was uniformly issued by the operation technician.The bone densitometry was carried out at the hospital's bone mineral density (BMD) laboratory. This was performed by specialists using dual‐energy X‐ray absorptiometry, in order to measure the lumbar and femoral neck BMD in g/cmP < 0.05 was considered statistically significant.The statistical analysis was conducted using the SPSS 21.0 statistical software. Normally distributed data were measured using the normality test, and expressed as mean ± standard deviation (SD). The risk factors were analyzed by logistic regression analysis, and The baseline data stratified by age are presented in Table P < 0.01), poor glycemic control (OR = 2.21. P < 0.01), low testosterone levels (OR = 1.56. P < 0.01), less exercise (OR = 1.42. P < 0.01), and complications with chronic diseases (OR = 1.44. P < 0.01) .We have no competing interests.


To investigate the therapeutic effect of lenvatinib (LEN) in liver disease etiology, especially nonviral hepatocellular carcinoma (HCC).P < 0.01). Similarly, median overall survival (OS) was significantly longer in the nonviral group than in the viral group . Multivariate analysis revealed that portal vein invasion , treatment line , and etiology  were significant independent factors associated with OS in u‐HCC patients treated with LEN.Sixty‐seven patients with unresectable advanced HCC (u‐HCC) treated with LEN and consisting of 26 hepatitis C virus (HCV), 19 hepatitis B virus (HBV), 11 alcohol, and 11 nonalcoholic steatohepatitis (NASH) cases were retrospectively recruited. Univariate and multivariate Cox proportional hazard models were used to determine predictive factors for survival. The objective response rate in the nonviral  group was higher than that in the viral group (59.1% [13/22] vs. 46.7% [21/45]). Progression‐free survival was significantly longer in the nonviral group than in the viral group (13.7 vs. 6.6 months; hazard ratio [HR] 0.324; 95% confidence interval [CI] 0.174–0.602; Our results suggest that LEN is more effective against nonviral u‐HCC than against viral u‐HCC. Kaplan–Meier analysis of progression‐free survival among patients with unresectable advanced hepatocellular carcinoma treated with lenvatinib according to etiology. The PFS in the non‐viral group was significantly longer than that in the viral group. Our results suggest that LEN is more effective against non‐viral u‐HCC than against viral u‐HCC. Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the third most common cause of cancer‐related death worldwide.More recently, the Phase III IMbrave150 trial reported that the combination of atezolizumab and bevacizumab was superior to SOR as the first‐line therapy for u‐HCC .However, the IMbrave150 trial did not show a sufficient survival benefit, with an HR of 0.91 in patients with nonviral etiology.Although LEN was noninferior to SOR in terms of survival benefit, it is a highly effective antitumor agent.Therefore, we aimed to reveal the efficacy of LEN by etiology, such as its effectiveness against NASH‐, alcohol‐, and viral hepatitis‐associated HCC.2 and type 2 diabetes were diagnosed with burn‐out NASH.This retrospective, observational study evaluated the efficacy and safety of LEN  monotherapy in patients with u‐HCC at Tokushima University Hospital between March 2018 and January 2021. This study was approved by the Ethics Committee of Tokushima University Hospital . Written informed consent was obtained from all patients. The inclusion and exclusion criteria were based on those of the REFLECT trial. Further, Vp4, tumor volume > 50%, and non‐first‐line cases were considered as eligibility criteria. Patients with Child–Pugh class B, with performance status (PS) of ≥2, and without contrast‐enhanced computed tomography (CT) or magnetic resonance imaging (MRI) due to renal impairment or allergy were excluded. Briefly, eligible patients had target lesions defined as measurable based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST),The initial daily oral doses of LEN administered to patients weighing ≥60, <60, and <40 kg were 12, 8, and 4 mg/day, respectively. The initial daily oral doses of LEN provided to patients weighing ≥60 and <60 kg were 12 and 8 mg/day, respectively. For HCC patients weighing <40 kg, we started with the initial LEN dose of 4 mg/day and confirmed its safety for 1 week, which was followed by dosing up to 8 mg/day since there were no reports showing the appropriate starting dose for patients weighing <40 kg. When serious adverse events (AEs) were observed, LEN administration was discontinued. Dose interruptions were in accordance with medical package inserts for administering LEN. Briefly, when grade 3 AEs or unacceptable grade 2 AEs developed, LEN was discontinued until AEs resolved and reverted to a lower grade.10 bilirubin [μmol/L] × 0.66) + ]. It was defined by the following scores: ≤−2.60 = grade 1, >−2.60 to ≤−2.27 = grade 2a, >−2.27 to ≤−1.39 = grade 2b, and > −1.39 = grade 3.Hepatic reserve function was assessed according to modified albumin–bilirubin (mALBI) grading and Child–Pugh classification. The mALBI grade was calculated based on the serum albumin and total bilirubin values using the following formula: [ALBI score =  was defined as the sum of complete response (CR) and partial response (PR) rates. DCR was defined as the sum of CR, PR, and stable disease (SD) rates. Progression‐free survival (PFS) was defined as the time from the first day of administering LEN until the day of radiological progression or death from any cause.P‐value of <0.05. Kaplan–Meier plots of medians (with 95% CI) were used to estimate the PFS and OS. Univariate and multivariate Cox proportional hazard models were used to determine predictive factors for survival. We performed multivariate analysis using covariates such as age, sex, HCC etiology, ECOG PS, mALBI grade, number of tumors, maximum tumor size, portal vein invasion, extrahepatic metastasis, and treatment line, which are known from prior research to affect treatment outcomes in patients with HCC.All statistical analyses were performed using Easy R version 1.29 .Table The results of the therapeutic response according to mRECIST are presented in Table Among these 67 patients, 2 exhibited CR , 32 had PR , 31 had SD , and 2 had progressive disease (PD) . The ORR and DCR were 50.8% (34/67) and 97% (65/67), respectively.P = 0.31). The PFS of all patients was 7.8 (95% CI = 6.2–9.8) months  and the HBV and HCV groups  showed no significant differences  and the HBV and HCV groups   Fig. .P < 0.05; Fig. P < 0.01; Fig. Furthermore, we analyzed both the NAFLD and non‐NAFLD groups. PFS in the NAFLD group was significantly longer than that in the non‐NAFLD group , portal vein invasion , and etiology  were significant independent factors associated with PFS in u‐HCC patients treated with LEN  were prognostic factors for u‐HCC patients treated with LEN , treatment line , and etiology  were significant independent factors associated with OS in u‐HCC patients treated with LEN  were prognostic factors for u‐HCC patients treated with LEN  and etiology  were significant independent factors associated with PFS in u‐HCC patients treated with LEN  were prognostic factors for u‐HCC patients treated with LEN  and etiology  were significant independent factors associated with OS in u‐HCC patients treated with LEN  were prognostic factors for u‐HCC patients treated with LEN , fatigue , proteinuria , decreased appetite , and palmar‐plantar erythrodysesthesia . The most common grade 3 drug‐related AEs were proteinuria , hypertension , fatigue , decreased platelet count , and diarrhea . There were no significant differences in LEN‐related AEs between the viral and nonviral groups .In this study, LEN showed significantly better PFS and OS in the nonviral HCC group than in the viral HCC group. In multivariate analysis, first‐line, portal vein invasion and nonviral etiology were independent prognostic factors. Furthermore, the analysis of the first‐line group also showed that portal vein invasion and nonviral etiology were independent prognostic factors. These results suggest that LEN is an effective therapeutic option against u‐HCC associated with nonviral etiology. Therefore, the present findings suggest that LEN could be an alternative to atezolizumab and bevacizumab in nonviral HCC.HCC has distinct etiologic factors. Common etiologies of HCC include HBV, HCV, NASH, and alcoholic liver disease. Due to these various etiologies, the carcinogenic process differs from tumor biological characteristics. These differences may affect the efficacy of targeted therapies.Recently, Tsuchiya et al. reported no significant difference in PFS and OS between viral and nonviral u‐HCC patients treated with LEN in a multicenter study.Recent progress in pharmacotherapy for u‐HCC has been remarkable, and although several drugs have shown efficacy, atezolizumab plus bevacizumab is currently recommended as the first‐line treatment.In fact, our study showed that the PFS of LEN in alcohol‐associated u‐HCC (13.7 months) was favorably comparable to the PFS of LEN in the REFLECT trial Fig. b.Although the reasons for the high efficacy of LEN against nonviral HCC are not evident in our study, this high efficacy was observed in alcohol‐associated u‐HCC and NASH‐associated u‐HCC Fig. . When coHepatic reserve function and portal vein invasion at treatment initiation are general prognostic factors for u‐HCC treatment with MTAs,The main limitations of our study are its retrospective nature, small sample size, and short observation period. Although analysis of the first‐line treatment also showed that LEN resulted in better survival in the nonviral HCC group than in the viral HCC group, the number of these cases may be insufficient to show the efficacy of LEN as the first‐line treatment against nonviral u‐HCC. Therefore, a large‐scale prospective study is required to confirm the present findings and to conduct more detailed analyses, such as a prospective comparison of LEN and ICIs in patients with nonviral hepatitis‐derived u‐HCC.Our results suggest that LEN treatment showed better clinical efficacy in nonviral hepatitis‐associated u‐HCC than in viral hepatitis‐associated u‐HCC, indicating that we should consider etiology when treating u‐HCC. However, further studies are required to confirm the effect of LEN on u‐HCC based on etiology.Tetsu Tomonari, study concept and design, acquisition of data, statistical analysis, and drafting of the manuscript. Yasushi Sato, statistical analysis and revision of the manuscript. Hironori Tanaka, acquisition of data. Takahiro Tanaka, acquisition of data. Tatsuya Taniguchi, acquisition of data. Koichi Okamoto, acquisition of data. Masahiro Sogabe, acquisition of data. Hiroshi Miyamoto, acquisition of data. Naoki Muguruma, acquisition of data. Tetsuji Takayama, revision of the manuscript. All authors had access to the data and participated in the writing of this manuscript.Figure S1. Kaplan–Meier analysis of progression‐free survival among patients with advanced hepatocellular carcinoma treated with lenvatinib as the first‐line treatment according to etiology. (a) The PFS in the non‐NAFLD group was significantly longer than NAFLD group. Kaplan–Meier analysis of overall survival among patients with advanced hepatocellular carcinoma treated with lenvatinib as the first‐line treatment according to etiology. (b) The OS in the nonviral group was significantly longer than that in the viral group. NAFLD, nonalcoholic fatty liver disease; OS, overall survival.Click here for additional data file.Figure S2. Kaplan–Meier analysis of progression‐free survival among patients with advanced hepatocellular carcinoma treated with lenvatinib as the first‐line treatment according to etiology. (a) The PFS in the nonviral group was significantly longer than that in the viral group. (b) The PFS among alcohol, NASH, HBV, and HCV groups. NASH, nonalcoholic steatohepatitis; HBV, hepatitis B virus; HCV, hepatitis C virus; PFS, progression‐free survival.Click here for additional data file.Figure S3. Kaplan–Meier analysis of overall survival among patients with advanced hepatocellular carcinoma treated with lenvatinib as the first‐line treatment according to etiology. (a) The OS in the nonviral group was significantly longer than that in the viral group. (b) The OS among alcohol, NASH, HBV, and HCV groups. HBV, hepatitis B virus; HCV, hepatitis C virus; OS, overall survival.Click here for additional data file.Table S1. Characteristics of patients with unresectable advanced hepatocellular carcinoma treated with lenvatinib.Table S2. Univariate and multivariate analyses of the factors influencing progression‐free survival in first line.Table S3. Univariate and multivariate analyses of the factors influencing overall survival in first line.Table S4. Adverse events associated with lenvatinib treatment.Click here for additional data file.


Warfarin remains the most widely prescribed oral anticoagulant in sub‐Saharan Africa. However, because of its narrow therapeutic index, dosing can be challenging. We have therefore (a) evaluated and compared the performance of 21 machine‐learning techniques in predicting stable warfarin dose in sub‐Saharan Black‐African patients and (b) externally validated a previously developed Warfarin Anticoagulation in Patients in Sub‐Saharan Africa (War‐PATH) clinical dose–initiation algorithm. The development cohort included 364 patients recruited from eight outpatient clinics and hospital departments in Uganda and South Africa (June 2018–July 2019). Validation was conducted using an external validation cohort . Based on the mean absolute error , random forest regression  was the best performing machine‐learning technique in the external validation cohort, whereas the worst performing technique was model trees . By comparison, the simple, commonly used regression technique (ordinary least squares) performed similarly to more complex supervised machine‐learning techniques and achieved an MAE of 13.01 mg/week . In summary, we have demonstrated that simpler regression techniques perform similarly to more complex supervised machine‐learning techniques. We have also externally validated our previously developed clinical dose–initiation algorithm, which is being prospectively tested for clinical utility. WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?WHAT QUESTION DID THIS STUDY ADDRESS?To improve warfarin dose prediction, numerous algorithms, including our previously reported clinical dose–initiation algorithm, have been developed using several techniques. WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?Do simpler regression techniques perform similarly to more complex supervised machine‐learning techniques, and what is the external validity of our previously developed clinical dose–initiation model? HOW MIGHT THIS CHANGE DRUG DISCOVERY, DEVELOPMENT, AND/OR THERAPEUTICS?We have shown that simpler regression techniques perform similarly to more complex supervised machine‐learning techniques and also externally validated our previously developed clinical dose–initiation algorithm. Our short‐term aim is to evaluate the utility of our externally validated clinical dose–initiation algorithm to facilitate dose prediction in sub‐Saharan African patients. In the longer term, simple regression techniques will be used to develop a pharmacogenetic model to further improve the quality of anticoagulation with warfarin.Warfarin remains the most commonly prescribed oral anticoagulant in sub‐Saharan Africa.To optimize dosing, numerous algorithms have been developed. For example, our recently conducted systematic review identified 433 dosing algorithms, of which 86% were for dose initiation.The mathematical backgrounds, strengths, and weaknesses of various machine‐learning techniques have been extensively exploredThis report follows the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) statementn = 270) recruited using the same eligibility criteria between August 2019 and March 2020 formed the external validation cohort  being in therapeutic range at each of those visits.During the development of the War‐PATH clinical dose–initiation algorithm and based on expert guidance and literature review, we selected seven predictors  for use during the modeling process.All available data were used during algorithm development and external validation to maximize the power and generalizability of the results. With eight candidate predictor parameters (HIV status had three factor levels), the study participant‐per‐candidate predictor parameter was 46 (War‐PATH development cohort). The War‐PATH external validation cohort included data from more than 100 individuals, the currently recommended sample size for validation.We used multivariate imputation by chained equations in RAll analyses were conducted in R version 4.0.2To model a proportional/multiplicative scale that is clinically relevant and easy to interpret,We neither transformed nor categorized predictor variables. Nonlinearity between continuous predictors and stable dose was previously assessed using restricted cubic splines.We used 21 machine‐learning techniques as detailed in Table As described previously, we used the seven predictors that were previously selected based on expert guidance and literature review.Except for the techniques such as least absolute shrinkage and selection operator regression, elastic net, multivariate adaptive regression splines, and tree‐based methods that perform automatic predictor selection during parameter tuning or model fitting, we did not perform predictor selection during modeling.For some techniques and to prevent overfitting, the out‐of‐bag bootstrap approach (in which the test performance was computed using the samples not included in each bootstrap iteration)n = 270).Algorithms produced by the 21 machine‐learning techniques, the War‐PATH clinical dose–initiation algorithmDuring both model development and validation, we computed prediction accuracy based on the mean absolute error (MAE) and the “unbiased” mean absolute percentage error (“unbiased” MAPE).Characteristics of the War‐PATH external validation cohort are presented in Table The performances of the various algorithms in the War‐PATH development and external validation cohorts are summarized in Figure In the development data set and in terms of the MAE, bagged trees  and Cubist  were the top performing techniques, with the other techniques having similar performances, which ranged from 10.58 mg/week  for random forest regression to 11.91 mg/week  for k‐nearest neighbors. In the external validation data set, random forest regression had the lowest MAE , although this was not very different from most of the other techniques, with the exception of model trees . The simple, commonly used, ordinary least squares regression  was the 15th best performing technique , although its performance was similar to that of random forest regression , all other techniques were unbiased in the development data set. In the external validation set, all techniques overpredicted doses, but only bagged trees, cubist, model trees, support vector regression, quantile regression, and robust regression systematically overpredicted  and Cubist  were the top performing models in the development cohort. Other models performed similarly, ranging from 46.61%  patients with ideal dose for Bayesian additive regression trees to 41.12%  patients with ideal dose for ordinary least squares/principal components regression. In the external validation cohort, elastic net regression  and k‐nearest neigbors  were the top performers, although this was similar to the performance of other models. Bagged trees and model trees, however, performed poorly  again had a lower performance than fixed‐dose initiation , but the difference  was not statistically significant. With a fixed dose of 35 mg/week, 30/270 and 54/270 patients, respectively, required 40% less warfarin (≤21 mg/week) and 40% more warfarin (≥49 mg/week), which translated into 11.11% and 20.00% of the patients being at high risk of overdosing and underdosing. This implied that 68.89% of the patients were at low risk of suboptimal dosing as shown in Figure In this study, we compared the performances of 21 machine‐learning techniques with regard to predicting stable warfarin dose in sub‐Saharan Black‐African patients. As previously observed, simple multiple regression techniques such as ordinary least squares regression performed similarly or even better than more complex machine‐learning techniques.Our second objective involved externally validating our previous clinical dose–initiation algorithm.In Tables Our study had several limitations. For example, despite basing on our recent systematic review,In conclusion, the simpler and more widely known multiple linear regression techniques such as ordinary least squares performed similarly to more complex supervised machine‐learning techniques in the War‐PATH cohorts. These simpler techniques were previously used to develop a War‐PATH clinical dose–initiation algorithm, which we have externally validated in this study . Given that simple techniques can get the job done, we will be using them in achieving our long‐term aim of evaluating the importance of clinical and genetic predictors in improving warfarin dosing in Ugandan and South African patients.www.ardat.org). C.W. is supported by a Wellcome Clinical Research Career Development Fellowship 222075/Z/20/Z. None of these of funding sources have been used for the current article. All other authors declared no competing interests for this work.M.P. has received partnership funding for the following: Medical Research Council (MRC) Clinical Pharmacology Training Scheme ; a PhD studentship jointly funded by Engineering and Physical Sciences Research Council and Astra Zeneca; and grant funding from Vistagen Therapeutics. He has also unrestricted educational grant support for the UK Pharmacogenetics and Stratified Medicine Network from Bristol‐Myers Squibb and UCB. He has developed a human leukocyte antigen genotyping panel with MC Diagnostics, but does not benefit financially from this. He is part of the Innovative Medicines Initiative Consortium Accelerating Research and Development for Advanced Therapies (All authors wrote the manuscript and performed the research. I.G.A., M.B., K.C., C.H., M.L., J.P.M., C.S.‐W., J.R.S., C.W., E.J.Z., A.L.J., and M.P. designed the research. I.G.A. analyzed the data. M.B., K.C., C.C., C.H., B.J., M.L., J.M., J.P.M., D.N., E.O., E.S., C.S.‐W., J.R.S., and C.W. contributed new reagents/analytical tools.Supplementary MaterialClick here for additional data file.


To report an adolescent with infantile‐onset carnitine palmitoyltransferase 2 (CPT2) deficiency and cerebral malformations and to review the occurrence of brain malformations in CPT2 deficiency. The patient presented clinically at age 5 months with dehydration and hepatomegaly. He also has an unrelated condition, X‐linked nephrogenic diabetes insipidus. He had recurrent rhabdomyolysis but normal psychomotor development. At age 17 years, he developed spontaneous focal seizures. Cerebral magnetic resonance imaging revealed extensive left temporo‐parieto‐occipital polymicrogyria, white matter heterotopias, and schizencephaly. Neuronal migration defects were previously reported in lethal neonatal CPT2 deficiency but not in later‐onset forms.We searched PubMed, Google Scholar, and the bibliographies of the articles found by these searches, for cerebral malformations in CPT2 deficiency. All antenatal, neonatal, infantile, and adult‐onset cases were included. Exclusion criteria included insufficient information about age of clinical onset and lack of confirmation of CPT2 deficiency by enzymatic assay or genetic testing. For each report, we noted the presence of cerebral malformations on brain imaging or pathological examination.Of 26 neonatal‐onset CPT2‐deficient patients who met the inclusion criteria, brain malformations were reported in 16 (61.5%). In 19 infantile‐onset cases, brain malformations were not reported, but only 3 of the 19 reports (15.8%) include brain imaging or neuropathology data. In 276 adult‐onset cases, no brain malformations were reported.To the best of our knowledge, this is the first report of cerebral malformations in an infantile onset CPT2‐deficient patient. Brain imaging should be considered in patients with CPTII deficiency and neurological manifestations, even in those with later clinical onset. CPTcarnitine palmitoyltransferase (EC 2.3.1.21)CPT2carnitine palmitoyltransferase 21lethal neonatal form , an early‐onset infantile form , and a late‐onset (adult) form .The hereditary deficiency of carnitine palmitoyltransferase 2  is an autosomal recessive inborn error of carnitine and long‐chain fatty acid metabolism.lethal neonatal/antenatal subtype of CPT2 deficiency is the most severe form. Classically, it presents with acute metabolic signs in the first days of life, accompanied by respiratory distress, hypoglycemia, seizures, hepatomegaly, cardiomegaly, arrhythmias and abnormalities of cardiac conduction, and often mild facial dysmorphic features, cystic renal dysplasia, and brain malformations, including neuronal migration defects (pachygyria), defects of cortical organization (polymicrogyria), brain calcifications or cystic dysplasia, and posterior fossa anomalies , often with co‐existing hydrocephalus.The Infantile CPT2 deficiency shares the metabolic features of the neonatal form,Late‐onset (adult) CPT2 deficiency is the commonest form and usually the least severe. It is characterized by episodes of rhabdomyolysis precipitated by prolonged exercise, fasting, high fat intake, exposure to cold, infections, fever, emotional stress and drugs such as ibuprofen, diazepam, and valproic acid.infantile form and about 300 patients with the adult form of CPT2 deficiency have been described.To date about 30 patients with the We report a CPT2‐deficient patient with an infantile age of clinical onset in whom an extensive cortical malformation was discovered following a focal seizure at 17 years of age.2We reviewed the patient's medical records from birth until 17 years of age. To test whether other patients with post‐neonatal clinical onset of CPT2 deficiency and cerebral malformations had been reported, we searched PubMed using keywords, as follows:  AND . We also traced the references cited in the articles found by these searches as necessary.Exclusion criteria for case histories of neonatal and infantile forms included insufficient information about age of clinical onset and lack of confirmation of CPT2 deficiency by enzymatic assay or genetic testing.For adult‐onset patients, we did not apply exclusion criteria. The majority of these patients are described in review articles of genotype‐phenotype correlations. Often, only limited clinical data are available. It is not possible to determine from these publications whether some patients are described in more than one study.Each phenotypic description was analyzed for the presence or absence of documented cerebral malformations by imaging or neuropathology.33.1The patient is the first child of healthy, unrelated individuals of Italian descent. The pregnancy was uneventful. He was born at term by spontaneous vaginal delivery. Pediatric visits during the first 5 months showed normal growth and development for his age. The family history revealed no other instances of epilepsy, brain malformations, or metabolic diseases. At 5 months of age, he was admitted because of 2 days of recurrent vomiting and restlessness, with dehydration and a liver edge palpable 4 cm below the costal margin.Laboratory studies revealed normal blood glucose and lactate and mild‐to‐moderate ketonuria. Plasma aspartate aminotransferase was 500 U/L ; alanine aminotransferase, 341 U/L (5‐25 U/L); total bilirubin, 27 μmol/L (0‐14 μmol/L); direct bilirubin, 14 μmol/L (0‐4 μmol/L); gamma glutamyl transferase (GGT), 96 U/L (3‐43 U/L); serum sodium 150 mmol/L (130‐142 mmol/L). Urine density was persistently below 1.005. Creatine kinase was not measured.Abdominal ultrasound revealed hepatomegaly with an echotexture suggesting fatty infiltration. The kidneys appeared normal. Severe hepatic steatosis with hepatomegaly was confirmed on abdominal CT‐scan. Hepatic biopsy showed isolated macrovesicular steatosis. Cardiac ultrasound demonstrated mild septal and left ventricular hypertrophy with normal myocardial function.Urine organic acids showed acetoacetic acid, 340 μmol/mmol creat.  and 3‐hydroxybutyric acid, 66 μmol/mmol creat.  and were otherwise normal.3.2The first determination of plasma free carnitine level was normal, with elevated esterified carnitine, 58.4 μmol/L . Plasma acylcarnitines showed levels of C16 and C18 species more than 10‐fold above the upper reference value, with lesser elevations of C12, C14 and C2 acylcarnitines.Fatty acid oxidation studies in cultured fibroblasts showed low oxidation of palmitate and myristate . CPT2 assay in fibroblasts showed CPT2 activity <2.7% of control activity .CPT2 exons and surrounding intronic regions revealed compound heterozygosity for two previously reported pathogenic variants, c.887G > A (p.Arg296Gln)Sequencing of all 3.3AVPR2 (c.541C > T in NM_000054 (p.Arg181Cys).Hypernatremia and low urine density persisted. He was found to have a second condition, X‐linked nephrogenic diabetes insipidus, caused by a de novo known pathogenic variant in He was initially treated by glucose‐containing intravenous fluids then transitioned to frequent nasogastric tube feeding with a low fat, high carbohydrate formula. Plasma aminotransferase levels normalized within days. He had severe gastroesophageal reflux. The treatments of CPT2 deficiency and of nephrogenic diabetes insipidus both require frequent feeds and/or hydration, and therefore gastrostomy was performed at 7 months of age. He received nocturnal gavages until 10 years of age. Subsequently, the gastrostomy was closed and oral hydration at night was prescribed.l‐carnitine. Serial abdominal and cardiac ultrasounds showed complete normalization of hepatic morphology at age of 3 years and persistently normal heart function after 13 months of age. He was hospitalized 12 times between 5 and 17 years of age for episodes of rhabdomyolysis precipitated by fever, fasting or intense exercise. He recovered quickly and completely from each episode. Developmental milestones were normal. He had average performance in regular school. A generalized anxiety disorder appeared during adolescence.After his first hospitalization, intake of long‐chain fatty acids was restricted and he received supplements of medium chain fatty acids and At age 17 years, he experienced two brief focal seizures with secondary generalization . Right‐sided hyperreflexia was present. Brain magnetic resonance imaging (MRI) revealed extensive left parietal, temporal, and occipital polymicrogyria with closed lip schizencephaly, subcortical grey matter heterotopias and a dysplastic left hippocampus Figure . Three e3.43.4.1Twenty six of 27 reports of neonatal  CPT2 deficiency met the inclusion criteria Table . Sixteen3.4.2Twenty‐six infantile‐onset patients were identified in the literature Table . For sev3.4.3The search identified 276 patients with the adult muscular form of CPT2 deficiency Table . Brain m4The clinical spectrum of CPT2 deficiency ranges from congenital malformations with early death to isolated intermittent skeletal muscle involvement in adults. Here, we confirm that cerebral malformations are common (62%) in the neonatal  form of CPT2 deficiency and can be present in patients with later clinical presentation.To the best of our knowledge, this is the first report of a cortical malformation in a CPT2‐deficient patient with clinical onset after the neonatal period. Ohtani et alRemarkably, the patient remained neurologically asymptomatic for 17 years despite having a large and complex malformation including extensive polymicrogyria, closed lip schizencephaly, subcortical grey matter heterotopias and hippocampal dysplasia. Among 101 patients with malformations of cortical development, aged 1 month to 19 years,CPT2, c.1102G > A  and c.1939A > G .Both mutations of our patient have previously been reported. c.887G > A (p.Arg296Gln) was reported in trans with a complex allele that produces an in‐frame deletion.The mechanisms underlying the occurrence of cerebral malformations in CPT2 deficiency are unknown. Patients may also have renal cysts.The classification of CPT2 deficiency based on age of clinical onset is convenient and often useful, but as this patient shows, the age of clinical onset does not define biologically distinct categories. The patient presented as an infant, evolved to have a classical “adult” course dominated by recurrent episodes of rhabdomyolysis, yet in late adolescence, was found to have a cerebral malformation of prenatal onset.In practice, clinical descriptions of infantile‐onset CPT2 deficiency are few and are often incomplete. It is not possible to conclude upon the incidence of brain malformations in this form of CPT2 deficiency, but this patient shows that they can occur. Presumably, in most patients, brain malformations cause detectable neurological signs if present, and the decision to perform cerebral imaging depends upon clinical indications. Conversely, the observation of a complex, extensive cerebral malformation that was clinically asymptomatic until adolescence, suggests that cerebral malformation should be considered in any CPT2‐deficient patient who develops unexplained seizures or other neurological signs, regardless of the age of clinical onset.Ivan Shelihan, Elsa Rossignol, Jean‐Claude Décarie, Jean‐Paul Bonnefont, Michèle Brivet, Catherine Brunel‐Guitton, and Grant A. Mitchell declare that they have no conflict of interest.Ethics approval was not required for all research studies.The patient and his parents provided informed consent for publication of this case report. This article does not contain any studies with human or animal subjects performed by the any of the authors.Ivan Shelihan: Data analysis and interpretation and planning and drafting most of the article. Elsa Rossignol: Article contribution and revision. Jean‐Claude Décarie: Article contribution and revision. Jean‐Paul Bonnefont: Article contribution and revision. Michèle Brivet: Article contribution and revision. Catherine Brunel‐Guitton: Article contribution and revision. Grant A. Mitchell: Data analysis and interpretation and planning and drafting of article.5References for supplementary tables”References 19‐53 are cited only in Supporting Information, where they are numbered according to the accompanying list, “Table S1‐S3 Reports of neonatal  form of CPT2 deficiencyClick here for additional data file.


Estimates of the disease burden associated with different respiratory viruses are severely limited in low‐ and middle‐income countries, especially in Africa.We estimated age‐specific numbers and rates of medically and non‐medically attended influenza‐like illness (ILI) and severe respiratory illness (SRI) that were associated with influenza, respiratory syncytial virus (RSV), rhinovirus, human metapneumovirus, adenovirus, enterovirus and parainfluenza virus types 1–3 after adjusting for the attributable fraction (AF) of virus detection to illness in South Africa during 2013–2015. The base rates were estimated from five surveillance sites and extrapolated nationally.The mean annual rates per 100,000 population were 51,383 and 4196 for ILI and SRI, respectively. Of these, 26% (for ILI) and 46% (for SRI) were medically attended. Among outpatients with ILI, rhinovirus had the highest AF‐adjusted rate (7221), followed by influenza (6443) and adenovirus (1364); whereas, among inpatients with SRI, rhinovirus had the highest AF‐adjusted rate (400), followed by RSV (247) and influenza (130). Rhinovirus (9424) and RSV (2026) had the highest AF‐adjusted rates among children aged <5 years with ILI or SRI, respectively, whereas rhinovirus (757) and influenza (306) had the highest AF‐adjusted rates among individuals aged ≥65 years with ILI or SRI, respectively.There was a substantial burden of ILI and SRI in South Africa during 2013–2015. Rhinovirus and influenza had a prominent disease burden among patients with ILI. RSV and influenza were the most prominent causes of SRI in children and the elderly, respectively. A case of SRI was defined as a hospitalized person with symptoms of any duration who met age‐specific clinical inclusion criteria. A case in children aged 2 days to <3 months included any hospitalized patient with diagnosis of suspected sepsis or physician‐diagnosed acute lower respiratory tract infection irrespective of signs and symptoms. A case in children aged 3 months to <5 years included any hospitalized patient with physician‐diagnosed acute lower respiratory tract infection, including bronchitis, bronchiolitis, pneumonia, and pleural effusion. A case in individuals aged ≥5 years included any hospitalized patient presenting with manifestation of acute lower respiratory tract infection with fever (≥38°C) or history of fever and cough.In addition, we conducted prospective surveillance for patients presenting with ILI at two outpatient clinics  located in the same catchment area as the abovementioned hospitals over the same study period. An ILI case was defined as an outpatient of any age presenting with either temperature ≥38°C or history of fever and cough of duration of ≤10 days.We also enrolled persons presenting at the same outpatient clinics with no history of fever, respiratory, or gastrointestinal symptoms during the 14 days preceding the visit (hereafter referred to as controls). These individuals commonly presented to the clinics for visits such as dental procedures, family planning, well baby visits, voluntary HIV counseling and testing, or acute care for non‐febrile illnesses. We aimed to enroll one HIV‐infected and one HIV‐uninfected control every week in each clinic within each of the following age categories: <1, 1–4, 5–24, 25–44, 45–64, and ≥65 years.The procedures of these surveillance programs have been previously described.Respiratory specimens  were collected from all enrolled individuals (controls and ILI and SRI cases), placed in universal transport medium , stored at 4–8°C, and transported to the National Institute for Communicable Diseases (NICD) for testing within 72 h of collection. Specimens were tested for the presence of 10 respiratory viruses  using a multiplex real‐time reverse transcription polymerase chain reaction (PCR) assay.○Data source 2: Healthcare utilization surveys (HUSs)We obtained data on actual healthcare‐seeking behavior  among individuals with reported ILI and SRI from three HUSs conducted in South Africa.○Data source 3: Prevalence of risk factors for pneumonia and healthcare‐seeking behavior for ARIWe obtained the provincial‐level prevalence of known risk factors for pneumonia and the provincial data on healthcare‐seeking behavior among cases with ARI from the 2016 South Africa Demographic and Health Survey (DHS)○Data source 4: Population denominatorsWe obtained age‐ and year‐specific population denominators for the catchment area of the surveillance sites described in Data source 1 from projections of 2011 census data for South Africa.HIV results were obtained from a combination of two sources: (i) patient clinical records when available and (ii) for consenting patients, a dried blood spot was tested at NICD. Testing included HIV enzyme‐linked immunosorbent assay (ELISA) for patients aged ≥18 months and PCR for children aged <18 months if the ELISA was reactive.2.2InflDetectRateIll) from the observed detection rate (InflDetectRateObs) as follows:We used unconditional logistic regression to estimate the attributable fraction (AF) of respiratory viruses‐associated hospitalization and outpatient consultation by comparing the respiratory viruses detection rate among ILI or SRI cases with those of controls (outcome variables in the models). The AF was estimated from the virus specific odds ratio (OR) obtained from the multivariable regression models as follows:2.3We reported mean annual estimates over the study period for any SRI and ILI as well as those associated with the respiratory viruses investigated in this study. Estimates were obtained overall and within the following age categories: <1, 1–4, 5–24, 25–44, 45–64, ≥65, <5, and ≥5 years of age. Rates were reported per 100,000 population. The details of the estimation approach are provided in Supporting Information and summarized below.2.3.1To estimate the national number of respiratory viruses‐associated SRI hospitalizations, we used a four‐step approach. In Step 1, we estimated the SRI hospitalizations rates at the two hospitals mentioned above (Data source 1) during 2013–2015 as previously described,To estimate the national number of respiratory viruses‐associated ILI outpatient consultations, we used an approach similar to that used for SRI cases, but we did not adjust for the provincial level risk factors for pneumonia.2.3.2To estimate the national number and rates of respiratory viruses‐associated non‐medically attended ILI and SRI, we used the four‐step approach described above in conjunction with HUS data (Data source 2).2.4th and 97.5th percentiles of the estimated values obtained from the 1000 resampled datasets, respectively.We obtained the 95% confidence intervals (CIs) for medically and non‐medically attended respiratory viruses‐associated illness using bootstrap resampling over 1000 replications for all parameters included in the calculations.33.1During January 2013–December 2015 we enrolled 10,602 individuals of which 10,149 (95.7%) had available data on age and underlying medical conditions as well as respiratory viruses and HIV results and were thus included for further analyses. Of these 10,602 individuals, 2119 (20.9%) were controls, 3672 (36.2%) were outpatients with ILI, and 4358 (42.9%) were inpatients with SRI. Children aged <5 years accounted for 38.0% (806/2119) of controls, 35.5% (1134/3672) of patients with ILI, and 37.5% (1632/4358) of patients with SRI. The HIV prevalence was 41.3% (874/2119) among controls (due to enrolment criteria), 25.1% (923/3672) among patients with ILI, and 50.1% (2183/4358) among patients with SRI.3.2Among individuals of any age, the detection of the nine respiratory viruses investigated in this study ranged between 0.2% and 16.7% among controls, 0.6% and 26.2% among patients with ILI, and 0.6% and 22.1% among patients with SRI. Rhinovirus was the most detected virus among controls  and patients with ILI  or SRI  Tables . Among c3.3Among individuals of any age, the AF of the nine respiratory viruses investigated in this study ranged between 20.7% and 90.8% among patients with ILI Table  and 26.4Among patients of any age with ILI, rhinovirus 13.9%) had the highest AF‐adjusted prevalence followed by influenza (11.9%) and RSV (3.8%)  Table  of which3.5During 2013–2015, among individuals of any age, the estimated mean annual number of SRI episodes was 2,268,125  Table  of which4We estimated the AF of nine respiratory viruses among patients with ILI and SRI as well as the mean annual number and rates of these syndromes and that associated with respiratory viruses after adjusting for the estimated AF in South Africa during 2013–2015. The burden of ILI  and SRI  was substantial. Twenty six percent of ILI and 46% of SRI episodes were medically attended, indicating a heavy burden of these syndromes on the healthcare system.Estimates of the burden of ILI in Africa are scarce. Our estimated rates of medically attended ILI  are similar to those reported in a study conducted in the Democratic Republic of Congo (DRC) .In our study, among patients with ILI, the most commonly detected virus was rhinovirus, followed by influenza and adenovirus. These viruses were detected at high frequencies also in other studies conducted in Africa among outpatients with respiratory illness.Among patient with ILI the AF of influenza, RSV, HMPV, and PIV Types 1–3 were generally high (range: 68.7–91.9%), whereas those of adenovirus and enterovirus were generally low (range: 16.4–46.9%). A similar pattern was observed among patients with SRI, and this has been reported in other studies.Rhinovirus was the most detected virus among patients with ILI and SRI, but its AF was moderate . The AF of rhinovirus found in this study was similar to those reported in other studies (range: 39.8–59.2%).Among patients with ILI, the rates associated with the different viruses evaluated in this study were highest among children aged <1 and 1–4 years, with the exception of influenza and adenovirus, where the highest rates were among individuals aged 5–24 years and PIV Type 2 where the highest rates were among individuals aged ≥65 years. Young children have been described to be particularly susceptible to viral respiratory infections,This study has limitations that warrant discussion. First, the base incidence estimates were obtained from five surveillance sites and extrapolated nationally. Whereas the extrapolation approach used in this study has been used in several other similar studies,In conclusion, there was a substantial burden of ILI and SRI in South Africa before the COVID‐19 pandemic. Our study suggests that, among the investigated viruses, influenza and rhinovirus had a prominent disease burden among patients with ILI. The results of our study support the results of other studies that identified RSV as the most prominent cause of SRI in children,Stefano Tempia: Conceptualization; data curation; formal analysis; investigation; methodology; validation; visualization. Jocelyn Moyes: Conceptualization; investigation; methodology. Adam Cohen: Conceptualization; investigation; methodology. Sibongile Walaza: Conceptualization; data curation; investigation; methodology. Meredith McMorrow: Conceptualization; investigation; methodology. Florette Treurnicht: Conceptualization; investigation; methodology. Orienka Hellferscee: Conceptualization; investigation; methodology. Nicole Wolter: Conceptualization; investigation; methodology. Anne von Gottberg: Conceptualization; investigation; methodology. Halima Dawood: Conceptualization; investigation; methodology. Ebrahim Variava: Conceptualization; investigation; methodology. Cheryl Cohen: Conceptualization; investigation; methodology.The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the US Centers for Disease Control and Prevention, USA or the National Institute for Communicable Diseases, South Africa.https://publons.com/publon/10.1111/irv.12949.The peer review history for this article is available at Data S1: Supporting InformationClick here for additional data file.


In silico deconvolution of invasive immune cell infiltration in bulk breast tumors helps characterize immunophenotype, expands treatment options, and influences survival endpoints. In this study, we identify the differential expression (DE) of the LM22 signature to classify immune‐rich and ‐poor breast tumors and evaluate immune infiltration by receptor subtype and lymph node metastasis.Using publicly available data, we applied the CIBERSORT algorithm to estimate immune cells infiltrating the tumor into immune‐rich and immune‐poor groups. We then tested the association of receptor subtype and nodal status with immune‐rich/poor phenotype. We used DE to test individual signature genes and over‐representation analysis for related pathways.CCL19 and CXCL9 expression differed between rich/poor signature groups regardless of subtype. Overexpression of CHI3L2 and FES was observed in triple negative breast cancers (TNBCs) relative to other subtypes in immune‐rich tumors. Non‐signature genes, LYZ, C1QB, CORO1A, EVI2B, GBP1, PSMB9, and CD52 were consistently overexpressed in immune‐rich tumors, and SCUBE2 and GRIA2 were associated with immune‐poor tumors. Immune‐rich tumors had significant upregulation of genes/pathways while none were identified in immune‐poor tumors.Overall, the proportion of immune‐rich/poor tumors differed by subtype; however, a subset of 10 LM22 genes that marked immune‐rich status remained the same across subtype. Non‐LM22 genes differentially expressed between the phenotypes suggest that the biologic processes responsible for immune‐poor phenotype are not yet well characterized. Our approach classified 2369 patients into two groups  using an immune cell expression signature. The overall frequency of immune‐rich versus immune‐poor tumors differed by receptor subtype, however the specific signature genes remained the same, suggesting that signature expression is a stronger determinant of immune infiltration than receptor subtype. Clinical trials evaluating adjuvant therapy and immune invasiveness found that the presence of TILs in TNBC and Her2+ receptor subtypes is associated with improved treatment response and survival.There is no gold standard for the measure of lymphocytes and other tumor invasive immune cell types. In clinical settings, the recommended methodology for classifying tumors into immune‐poor/rich remains hematoxylin and eosin (H&E) staining of tumor sections.The goal of this research study is to use three independent sets of data to create a validated, standard signature of tumor invasive immune cells genes. We aim to better understand how the presence/lack of immune cell infiltration in a primary tumor relates to distinct molecular/pathologic features of disease, specifically receptor subtype, and lymph node metastasis. Rather than focus on the relative abundance of each invasive immune cell type in tumors, we use a standard gene expression array‐based signature of 547 genes to create a binary (immune‐rich or immune‐poor) variable of immune invasion status across three large breast cancer cohorts. Among patients with immune‐rich tumors, we further identify the specific signature genes on each subtype. Lastly, we apply pathway analysis to identify important molecular mechanisms behind both immune‐rich and immune‐poor tumor groups.22.1n = 774). GEO data had no information regarding histologic tissue type, yet all patients were confirmed non‐DCIS using size and grading information.We evaluated patient data from three independent publicly available data sources, final data for analysis includes: 650 patients from The Cancer Genome Atlas (TCGA),2.2http://www.ncbi.nlm.nih.gov/geo) and Array Express (http://www.ebi.ac.uk/arrayexpress) accession numbers are: E‐TABM‐158,METABRIC used the Illumina HT‐12v3 platform in gene expression analysis.2.3We estimated immune cells abundance in the tumor sample, derived from the LM22 signature employing the immune cell expression profiling using CIBERSORT algorithm.p‐value. Samples under the p = 0.05 threshold were termed immune‐rich.CIBERSORT, based on the LM22 gene signature, was used to estimate immune cells infiltrating the tumor.2.4http://www.genome.jp/kegg/) pathways and the limma “kegga” function.Both METABRIC and TCGA had 0.3% and 8% missing subtype information, respectively. Differential expression analysis, for immune‐rich/poor phenotype, was conducted with linear models using the R package limma.2.4.1p < 0.05 and log fold change in the same direction were considered. Since LM22 is used to identify primarily immune‐rich tumors, we conducted a secondary, genome‐wide, DE analysis excluding LM22 (non‐LM22) genes in order to identify any shared genes expressed in immune‐poor groups, and to check for additionally over expressed non‐LM22 genes in immune‐rich tumors. All LM22 genes were excluded in this testing, and results were filtered/validated according to FDR adjusted p < 0.05 and log fold change in the same direction.We first tested if there were genes with differential expression in the following categories: immune‐rich and immune‐poor and nodal metastasis status and breast cancer receptor subtype. We then evaluated if expression in LM22 signature genes was changed in immune‐rich samples across the conditions of subtype or nodal status. Differential expression (DE) among immune‐rich and ‐poor tumors was assessed within each subtype and compared against all other subtypes . Results lists from each source of patient data  were compared against one another for validation, and only intersecting genes with association FDR‐adjusted 2.52.6). In addition, no definitive connection between NM and immune‐cell signature was identified in LM22 signature gene analysis (data not shown).Receptor subtype was associated with both nodal status and immune‐rich/poor tumors. Approximately 61% (1454/2369) of tumors in all datasets were Luminal type. Luminal patient tumors were more frequently immune‐poor in all data. Conversely, TNBC and Her2+ patients consistently had more immune‐rich tumors across all datasets , several of the TNBC only genes were not significant, most likely due to lack of power. TNBC receptor subtype showed no unique differences in genes associated with immune‐rich status when compared to all receptor subtypes. Presence of lymph node metastasis had no consistent effect upon tumor immune‐rich/poor status across datasets .While overall immune‐rich/poor status differed significantly across receptor subtype, individual signature genes seemed to be the same across the three subtypes, suggesting that the same genes responsible for immune infiltration do not differ across subtype. There were 10 total LM22 signature genes with consistently higher expression in immune‐rich tumors (FDR 2.7.1p < 0.05) and consistent direction of log fold change across the three datasets, . Both KYNU and EPHA1 transcripts were significantly decreased in the Luminal immune‐rich tumor group. In TNBC patients with immune‐rich samples, expression of CHI3L2 and FES was significantly upregulated relative to all other subtypes. Decreases of expression in TRPM, ABCB9, and EPHA1 were unique to the TNBC immune‐rich set of patients  between the 2 immune phenotypes consistently across the three datasets  has been identified as a marker of M2 tumor associated macrophages, yet its effect on tumor progression in breast cancer is not fully known.Our approach classified 2369 patients into two groups  using an immune cell expression signature. The overall frequency of immune‐rich versus immune‐poor tumors differed by receptor subtype; however, the specific signature genes remained the same, suggesting that signature expression is a stronger determinant of immune infiltration than receptor subtype. Common to both TNBC and Luminal patients, the genes for C‐C motif chemokine ligand genes of LYZ, C1QB, CORO1A, EVI2B, GBP1, PSMB9, and CD52 in immune‐rich tumors independent of receptor subtype or nodal metastasis. Likewise, overexpression of both SCUBE2 and GRIA2 was consistently associated with immune‐poor status across datasets. Interestingly, SCUBE2 has been associated with ER/PR positive tumors GRIA2 is a member of a family of glutamate receptors, and its expression has been linked to the modulation of both tumor and immune cell function.CD52) is expressed in mature lymphocytes. It is the target of the monoclonal antibody therapy alemtuzumab in several diseases including chronic lymphocytic leukemia, cutaneous T‐cell lymphoma (CTCL), and multiple sclerosis (MS).CD52 has been linked to an expression signature of poor outcome,We also observed several new relationships between non‐LM22 genes and immune‐rich tumors, specifically overexpression of LYZ). Whether increased lysozyme production originates from normal or cancerous breast cells or from invasive immune cells, or both, is less clear. Lysozyme is secreted by neutrophils and macrophages in inflammatory response,LYZ.GBP1, GBP4, and GBP5. GBP‐1 has been associated with various antimicrobial activities as well as paclitaxel resistance in cell lines of some tumors with the notable exception of breast.GBP1 has been associated with improved survival in breast cancer.One of the genes most differentially expressed between immune‐rich and immune‐poor tumors was lysozyme : M. Behring, S. Shrestha, A.I. Vazquez, Writing, review, and/or revision of the manuscript: M. Behring, Y. Ye, A. Elkholy, P. Bajpai, S. Agarwal, H. Kim, H. W. Wiener, A. I. Ojesina, S. Shrestha, U. Manne, A.I. Vazquez, Study supervision: S. Shrestha, U. Manne, A.I. Vazquez.


Mechanistic understanding of how living systems sense, transduce, and respond to mechanical cues has important implications in development, physiology, and therapy. Here, the authors use an integrated atomic force microscope (AFM) and brightfield/epifluorescent microscope platform to precisely simulate living single cells or groups of cells under physiological conditions, in real time, concomitantly measuring the single‐cell autophagic response and its transmission to neighboring cells. Dual‐color fluorescence monitoring of the cellular autophagic response reveals the dynamics of autophagosome formation, degradation, and induction in neighboring contacting and noncontacting cells. Autophagosome formation is dependent on both the applied force and contact area of the AFM tip. More importantly, the enhancement of the autophagic responses in neighboring cells via a gap junction‐dependent mechanism is observed. This AFM‐based nanoacupuncture platform can serve as a tool for elucidating the primary mechanism underlying mechanical stimulation of living systems and other biomechanical therapeutics. An integrated atomic force microscope and brightfield/epifluorescent microscope platform is employed to quantify real‐time force application at the single cell level, which reveals the dynamics of autophagosome formation, degradation, and induction in neighboring contacting and noncontacting cells. Therefore, it is of great importance to well understand the correlation between mechanical stimulation on cells and cellular autophagy response. Being able to describe a relationship of nanoscale mechanical force on the response of autophagy at the single‐cell level is of particular interest, because it will shed light on the quantitative data that would be hidden in measurements involving a large number of cells. However, there is a lack of investigation platform that is capable of both precise generation and modulation of mechanical forces and real‐time monitoring of autophagy.Biomechanical stimulation is known to play key roles in biological processes, such as cell growth, differentiation, and communication.1 Rece in terms of spatial precision (nanometers) and force sensitivity (piconewtons). Under the premise that compressive force is the driving stimulus to account for mechanical autophagic response we have developed a two‐component system to determine the biological effects of nanoscale compression. The system is composed of: 1) a precise and nondestructive spatiotemporal compressive force applicator based on AFM; and 2) a fluorescent optical readout of cellular responses. By applying such defined force to cells and recording the generation of autophagosomes via the fluorescent cell reporter, we can use the dual modality epifluorescent/AFM to investigate in real time the cellular response. We thus aim to quantify force application at the single cell level (dubbed nanoacupuncture) using AFM.Atomic force microscopy (AFM) provides an ideal actuator and recorder of mechanical forces on cells,4 in tTraditional acupuncture may be one of the best model systems to study the correlation between mechanical force and autophagy, since at the most basic level, acupuncture is the application of mechanical forces or electrical stimulation to cells. The most commonly practiced acupuncture uses mechanical stimulation, which requires needle insertion/penetration of the skin. The compressing force on the cells exerted by the needle is the most critical because a common procedure is performed for all the acupuncture treatments during which needle compresses cells. Although acupuncture‐induced autophagy is a common response at the animal level, it is not clear whether it is a direct or indirect consequence of local mechanical stimulation at the single cell level. To quantitate the compressive force aspects of acupuncture, more accurate information about the mechanical force necessary to induce autophagy is important. with excellent spatial precision (nanometers‐nm) and force sensitivity (piconewtons‐pN). Through the application of defined mechanical forces and recording the autophagosomes via the fluorescent reporters, we have examined the relationship between mechanical stimulation and autophagy to understand the cellular response in a quantitative manner. In this study, we selected three different tissue culture cell lines, that is, HeLa , N2A , and PC12 , as test models. This integrated approach provides a new single‐cell platform to study the mechanism of nanoacupuncture in a quantitative manner.In this study, we focused on autophagy as a cellular response to understand the underlying mechanism of acupuncture at the single‐cell level in a quantitative manner under physiological conditions. Using an AFM integrated with a fluorescence microscope, we modeled acupuncture conditions on single cells by applying well‐defined compressive forces to a cell for defined time periods using AFM probes of known shape and size, a process we have termed nanoacupuncture. The autophagic response was determined by recording the optical output of the fluorescent reporter of cellular autophagy, that is, GFP‐fused LC3 protein (GFP‐LC3). The AFM tip serves as an actuator and detector of mechanical forces on cells,4 with22.1−1) were used for force indentation as well as for imaging.To establish and refine the experimental setup of nanoacupuncture at the single‐cell level, AFM tips were modeled as acupuncture needles. Nanomechanical stimulation was carried out using AFM tips of varying tip diameters (20 nm–2.5 µm) and shapes   and PC12  cells were selected to evaluate their response to mechanical stimulation and compared that to epithelial cells.To exclude the possibility that the observed relationship between mechanical stimulation and autophagy is limited to specific cell line, three cell lines, that is, HeLa, N2A, and PC12, were selected to conduct investigation. HeLa  cells stably expressing GFP‐LC3 and mCherry‐GFP‐LC3 have long been utilized for real‐time observation of autophagy.5 It i The number of fluorescent puncta (autophagosomes) correlates well with the level of autophagy. To confirm this basic assumption, we determined the increase in the number of fluorescent puncta with interventions previously identified as causing increased cell autophagy in HeLa cells, that is, either chloroquine or serum starvation treatments  curves , the average number of GFP puncta in responsive cells was ≈18 compared to ≈24 of mCherry puncta  to GFP‐LC3 to make a dual‐labeled LC3 autophagosome reporter (mCherry‐GFP‐LC3). The relative abundance of GFP and mCherry populations enables us to differentiate the newly formed population from autophagosomes undergoing degradation through the lysosomal pathway. The green fluorescence of GFP will decrease as it enters the acidic lysosome since it is pH‐sensitive, while the red fluorescence of mCherry will be retained as it is pH insensitive Figure 3a.[8a Figure . 30 min 2.4Figure To understand whether nanoacupuncture could affect the physiology of adjoining contacting cells, we examined the autophagic response of cells surrounding the stimulated cell  through the endogenous connexin. To ascertain the role of GJIC on the transfer of autophagy signals between contacting cells, we examined cells with such low levels of endogenous connexin expression (N2A cells) and compared their responses following connexin transfection , the appearance of puncta was recorded in contacting but unstimulated cells with and without transfection of Cx43‐mCherry , defined force application , defined deformation (indentation), physical measurements of compliance (Young's modulus), and direct individual cell nano‐surgery‐manipulation. The combination of the AFM with varying expression constructs including multiple fluorescent reporter constructs GFP‐LC3, mCherry‐GFP‐LC3, and Connexin 43‐mCherry demonstrates that with the appropriate excitation and emission subsystems a range of wavelengths can be imaged. It is applied in the safe and effective management of a broad spectrum of ailments, including pain, Parkinson's disease, stress, asthma, and depression. Acupuncture relies on applying mechanical stimulation using fine‐tipped  cells were purchased from Stem Cell Bank/Stem Cell Core Facility . HeLa and N2A cells were maintained in Modified Eagle's Medium (Thermo Fisher Scientific), while PC12 cells were maintained in Dulbecco's Modified Eagle's Medium (Thermo Fisher Scientific), containing 10% fetal bovine serum , 1% L‐glutamine (Thermo Fisher Scientific), and 1% penicillin/streptomycin (Thermo Fisher Scientific) at 37 °C in a humidified atmosphere containing 5% CO and FUW mCherry‐GFP‐LC3 from Anne Brunet (Addgene plasmid #110060). Cx43‐mCherry was constructed on pLPCX‐Cx43‐IRES‐GFP from Trond Aasen (Addgene plasmid #65433). Transfection of HeLa, PC12, and N2A cells with indicated plasmids was performed with Lipofectamine 3000 (Invitrogen) according to the manufacturer's instructions. Transduced cells were grown in the medium as described above. Selection of transduced cells was performed with 1 mg mL−1 Geneticin (G418) (Thermo Fisher Scientific) for about 15 days. High‐expressing cell clones were identified using fluorescence microscopy. Following selection, stably transfected HeLa and PC12 cells were cultured and supplemented with 500 µg mL−1 G418, and N2A cells were cultured with 800 µg mL−1 G418.The following plasmids were obtained from Addgene: pBABEpuro GFP‐LC3 from Jayanta Debnath (Addgene plasmid #22405)16 and−1. A PeakForce loading on cell samples was within 25 pN–5 nN during 45–75 min nanoacupuncture.A Bioscope Resolve AFM  and fluorescence microscopy  were used in the present study. Probes with various tip diameters of 20–25000 nm were used in AFM experiments. The nominal spring constant of probes was ranged within 0.1–0.35 N mThe fluorescence images were analyzed using ImageJ and AFM images were analyzed with Nanoscope Analysis 2.0 .Needle diameters were evaluated using a scanning electron microscope (SEM) . SEM was operated at 10 kV with magnification of 50–37 000.t‐test with GraphPad Prism 7.0 . Details of data presentation, sample size (n), statistical analysis, and significance of differences were provided in the figure legends.All the data were collected from at least three independent experiments, and analyzed without preprocessing. Statistical evaluation was conducted using Student's two‐tailed The authors declare no conflict of interest.B.L., Y.W. (Wei), and Q.L. contributed equally to this work. J.H. and C.F. directed the research; B.L., J.H., Z.S., and C.F. conceived and planned the study; B.L., L.W., J.H., Z.S., and C.F. designed experiments; Y.W. (Wei) carried out AFM experiments under the supervision of B.L., Q.L., N.C., and Y.W. (Wang); L.L. performed cell culture and plasmid transfection under the supervision of N.C.; L.W. and J.L. constructed plasmids; J.Z., Y.W. (Wang), and Y.S. assisted plasmid construction and cell transfection; B.L., Y.W. (Wei), Q.L., N.C., Y.W. (Wang), L.L., J.H., and C.F. analyzed data; J.S., L.W., and Z.S. contributed to discussions and overall impact of the work; B.L., Q.L., J.H., and C.F. cowrote the paper with input from all the authors.Supporting InformationClick here for additional data file.