The Japanese Society of Medical Oncology published a guideline (GL) on febrile neutropenia (FN) in 2017. The study’s purpose is to reveal how widely GL penetrated among physicians and surgeons providing chemotherapy.A questionnaire survey was conducted with SurveyMonkey™ for members of the Japanese Association of Supportive Care in Cancer and relevant academic organizations. Each question had four options  and a free description form. Responses were analyzed with statistical text-analytics.A total of 800 responses were retrieved. Major respondents were experts with more than 10-year experience, physicians 54%, and surgeons 46%. Eighty-seven percent of respondents knew and used GL. Forty-eight percent assessed FN with Multinational Association of Supportive Care in Cancer (MASCC) score “always” or “more than half.” Eighty-one percent chose beta-lactam monotherapy as primary treatment in high-risk patients. Seventy-seven percent did oral antibacterial therapy in low-risk patients ambulatorily. Seventy-eight percent administered primary prophylactic G-CSF (ppG-CSF) in FN frequency ≥ 20% regimen. Fifty-nine percent did ppG-CSF for high-risk patients in FN frequency 10–20% regimen. Ninety-seven percent did not use ppG-CSF in FN frequency < 10% regimen. The medians of complete and complete plus partial compliance rates were 46.4% (range 7.0–92.8) and 77.8% (range 35.4–98.7). The complete compliance rates were less than 30% in seven recommendations, including the MASCC score assessment.GL is estimated to be widely utilized, but some recommendations were not followed, presumably due to a mismatch with actual clinical practices in Japan. Febrile neutropenia (FN) is a potentially fatal infectious complication in cancer chemotherapy. Various guidelines were published abroad –5, some A questionnaire consisting of 21 questions on GL and seven on attributes of respondents was surveyed through SurveyMonkey™ for the members of the Japanese Association of Supportive Care in Cancer, the Japanese Society of Medical Oncology, the Japanese Society of Hematology, and the Japanese Breast Cancer Society  score (MS) to assess the risk of FN “always” or “more than half.” Eighty-nine comments were posted as to why “less than half” or “not at all” and categorized into seven groups: exclusively see high-risk patients, who will be hospitalized when FN occurs, 15 comments; do not calculate the score but refer to the evaluation criteria to roughly assess the risk, 14; judge the risk according to the unique criteria including patient conditions and clinical experience, 14; feel cumbersome, complicated, and unnecessary, 11; see only low risk or do not experience FN, 11; do not know MS, 9; others 15.A total of 71.4% and 85.9% took two sets of blood cultures at the onset of FN “always” or “more than half” in outpatient clinics and in-hospital care, respectively. Seventy-six comments on “less than half” and “not at all” in the outpatient setting were categorized into eight: FN patients will be hospitalized and be collected two sets of blood cultures in-hospital care, 13; two sets collection imposes a heavy burden on doctors and medical staffs, 11; when FN occurs, patients will take oral antibacterial at home prescribed in advance, 10; no encounter of FN, 9; do not take blood culture in low-risk patients even if FN occurs, 8; two sets is a heavy burden on patients, especially children, 8; do not implement it as antibacterial treatment is prioritized, 5; others 12. In the case of in-hospital care, 27 posted comments were summarized as follows: a heavy burden on doctors and nurses, 6; no encounter of FN, 5; a heavy burden on pediatric patients, 5; do not take blood culture in low risk, 4; others 7.A total of 74.4% collected one set of blood cultures from each of the central venous catheter (CVC) and the peripheral vein “always” or “more than half.” Sixty-seven posted comments on “less than half” and “not at all” were categorized into eight: no encounter of the applicable cases, 22; blood drawing from CVC is considered meaningless, 10; collect blood cultures only from the peripheral vein (unspecified reasons), 9; CVC will be removed in suspicion of catheter-related infection, 6; as a central venous port is installed if necessary, it is hard to draw blood from the port, 5; collect blood cultures only from CVC (unspecified reasons), 4; two sets collection is a heavy burden on adult patients as well as pediatric, 3; others 8.A total of 81.3% administered intravenous beta-lactam monotherapy for the high-risk FN patients “always” or “more than half” as the first-line therapy. Twenty-six comments on “less than half” or “not at all” were summarized as follows: no encounter of applicable cases, 8; use fluoroquinolone, 5; practice combination therapy (unspecified), 2; others 11 including four “use carbapenem” due to misunderstanding.A total of 77.2% administered oral antibacterial for the low-risk FN patients, and 77.0% saw those patients ambulatorily “always” or “more than half”. Forty-one and 43 comments on Q7 and Q8 for “less than half” and “not at all” were divided into three groups with the same titles each: an FN patient needs to admit and to take intravenous antibacterial in-hospital care, 30 and 37; intravenous antibacterial is administered in-hospital care because it is difficult for pediatric patients to take oral antibacterial, 4 and 2; others 7 and 4, respectively.A total of 69.1% “always” or “more than half” switched the initial intravenous antibacterial to oral agents or discontinued it when fever resolved with initial treatment despite persisting neutropenia. Forty comments on “less than half” and “not at all” were categorized into five: continue intravenous antibiotic until neutrophil recovery (unspecified reasons), 21; do not encounter applicable patients, 8; neutrophils usually recovered concurrently with defervescence, 4; decide to either continue primary therapy or cease it or shift to oral antibacterial according to the patient’s condition, 4; oral antibacterial is improper in pediatric FN patients for insufficient evidence or poor adherence, 3.Staphylococcus aureus agent or antifungal to the first-line therapy in consideration of treatment failure, 73; decide to either continue the primary treatment or change it based on scrutiny, 9; no encounter of applicable patients, 7; others 7.If the patient’s general condition is stable despite the persistence of FN over 3–4 days after the initiation of the first-line therapy, 66.9% continued it. Ninety-six comments on “less than half” and “not at all” were categorized into four: shift to another antibacterial or add an anti-methicillin-resistant Only 35.4% did not use G-CSF for therapeutic purposes in an FN patient, or “less than half” use G-CSF, as GL does not recommend using it. Thirty-eight comments on “always” and “more than half” were categorized into seven: expect recovering from neutropenia as soon as possible to shorten hospital stay and reduce patient burden, 10; use G-CSF in the high-risk FN patients, 7; use G-CSF for solid tumors and lymphoid tumors but not for acute myeloid leukemia, 5; prevent deteriorating of FN, 4; use G-CSF in the case of profound neutropenia, 4; others 8.A total of 94.3% did not use or “less than half” use intravenous gamma-globulin in the high-risk FN patients, as GL does not recommend it. Twelve comments on using it “always,” “more than half,” and “less than half” were summarized as follows: use it in the FN patients with severe conditions, 5; administer it to the patients with hypogammaglobulinemia, 4; others 3.Staphylococcus aureus, Pseudomonas aeruginosa, Bacillus species, and Candida species. Twenty-one comments on “less than half” and “not at all” were summarized as follows: it is hard to remove the central venous port, 4; re-insertion of CVC is challenging, 3; CVC is retained in the patients with the difficulty of intravenous catheterization, 3; no encounter of applicable patients, 6; others 5.A total of 92.3% “always” or “more than half” removed CVC when patients had FN accompanied by either thrombophlebitis, infectious endocarditis, or positive blood cultures of Pneumocystis pneumonia.”A total of 91.5% did not practice, or “less than half” practiced oral antibacterial prophylaxis in patients with low-grade neutropenia because GL does not recommend it. Seven comments on “always” and “more than half” varied but included one “Sulfamethoxazole/trimethoprim tablet is used to prevent A total of 78.2% used G-CSF as primary prophylaxis (ppG-CSF) “always” or “more than half” in the regimens of FN occurrence of more than 20%. Forty-four comments on “less than half” and “not at all” were categorized into seven: apply ppG-CSF in consideration with the chemotherapeutic regimen and patient’s condition, 11; examine whether prophylactic G-CSF is needed based on neutrophil counts during the first course of chemotherapy, 10; do not need to use ppG-CSF because of no encounter of applicable patients, 9; use G-CSF prophylactically from the following course if FN develops, 4; it is not profitable to use pegfilgrastim in-hospital care due to the diagnosis procedure combination (DPC)-based payment system, 3; reduce the doses of antineoplastic agents instead of administering prophylactic G-CSF, 2; others 5.A total of 58.5% used ppG-CSF “always” or “more than half” to the high-risk patients for FN in the regimens of FN occurrence of 10–20%. Fifty-four comments on “less than half” and “not at all” were categorized into eight: examine whether prophylactic G-CSF is needed based on neutrophil counts during the first course of chemotherapy, 14; do not use ppG-CSF due to unprofitability in DPC, 9; use G-CSF prophylactically from the following course if FN develops, 8; do not need to use ppG-CSF because of no encounter of applicable patients, 6; apply ppG-CSF in consideration with patient’s condition, 6; reduce the doses of antineoplastic agents or change regimen instead of administering prophylactic G-CSF, 2; administer prophylactic oral antibacterial, 2; others 7.A total of 96.6% did not use or “less than half” use ppG-CSF in the regimens of FN occurrence of less than 10% because of no recommendation in GL. Twelve comments on “always” and “more than half” were summarized as follows: consider to use it up to the patient’s conditions, 8; use it in the patients with a history of severe FN, 2; others 2.A total of 98.7% “always” or “more than half” screened HBV infection, including the examination of HBs antigen, anti-HBs antibody, and anti-HBc antibody before the initiation of chemotherapy.A total of 76.0% “always” or “more than half” screened tuberculosis, including chest X-ray examination and taking a history of the previous infection and recent contact with a patient with tuberculosis before the initiation of chemotherapy. Twenty-eight comments on “less than half” and “not at all” were summarized as follows: examine chest X-ray or CT but do not take the history of recent contact with a tuberculosis patient, 19; others 9.A total of 82.2% practiced “always” or “more than half” influenza vaccination for patients receiving chemotherapy. Forty-eight comments on “less than half” and “not at all” were categorized into five: the efficacy of vaccination does not look promising during chemotherapy, in particular including immunosuppressants like rituximab and corticosteroids, 16; it is up to the patient to decide whether or not to get the vaccination, 13; vaccination is recommended but is not provided in the hospital, 6; chemotherapy is prioritized to vaccination, 3; others 10.Streptococcus pneumoniae for patients receiving chemotherapy when they are either between 2 months and 6 years of age or older than 65 years old. GL recommends 13 valent and 23 valent vaccines for the former and the latter, respectively. Seventy-four comments on “less than half” and “not at all” were categorized into eight: it is up to a patient to decide whether or not to get the vaccination, 20; let the family doctor determine whether or not to provide the vaccination, 13; vaccination is given after recovering from the immunosuppression caused by chemotherapy, 7; the efficacy of vaccination does not look promising during chemotherapy, 7; vaccinate if a patient gets a public subsidy, 6; have never been aware of it, 6; chemotherapy is prioritized to the vaccination, 3; others 12.A total of 61.0% practice “always” or “more than half” vaccination of Each question is about what GL recommends, except for Q11, 12, 14, and 17. The responses to those questions represent the degree of compliance with GL. “Always do” and “do in more than half of patients” suggest complete and partial compliance, respectively. In contrast, so do “do not at all” and “do in less than half of the patients” in Q11, 12, 14, and 17. The medians of the complete and complete plus partial compliance rates were 46.4% (range 7.0–92.8) and 77.8% (range 35.4–98.7), respectively. The complete compliance rates were less than 30% in seven recommendations .The cumulative total numbers of the doctor members of each academic society were 21,252 consisting of 510 in the Japanese Association of Supportive Care in Cancer, 6900 in the Japanese Society of Medical Oncology, 6180 in the Japanese Society of Hematology, and 7662 in the Japanese Breast Cancer Society. Since some of the respondents belong to two or more societies, the estimated number is considered more than actual persons. Even if the number of target population is 100,000, sample size is calculated as 383 under the condition of a 5% margin of error and 95% confidence level . TherefoIt has become evident that GL is well known and used in daily clinical practices. Concerning that 95.8% knew GL, however, it cannot be ruled out that the respondents may have been biased toward who were familiar with GL, as they voluntarily participated in this survey. The state of complying with GL is considered acceptable, as the complete plus partial compliance rate was just under 80% in the majority of the recommendations. However, the complete compliance rates were lower than expected, and those in some of the recommendations were less than 30%. Through this survey, major four problems responsible for the quality of FN management have been identified: risk assessment of FN (Q2), primary therapy for FN in low-risk FN patients (Q7 & 8), management of FN (Q9 & 10), usage of G-CSF .GL weakly recommends estimating FN risk with MS at the onset. It was inherently designed to identify low-risk patients . Risk asOn the other hand, MS has been pointed out to have a couple of problems as about 10% of patients who are identified as low risk will develop severely ill. The American Society of Clinical Oncology and Infectious Disease Society of America guidelines for the outpatient management of FN advocate combining it with the Clinical Index of Stable Febrile Neutropenia (CISNE) score to increase the determination accuracy . It is cGL strongly recommends intravenous beta-lactam monotherapy for high-risk FN patients. The overall compliance rate, meaning as complete plus partial compliance rate, of 81.3% was deemed adequate. GL weakly recommends both oral antibacterial therapy and management in the outpatient setting for low-risk FN patients. The overall compliance rates for these two recommendations were just below 80% and considered reasonable. However, the primary therapy’s complete compliance rates in high- and low-risk patients were considerably low, 49.2% and 39.7%, respectively. A survey of 25,231 admitted FN cases in the USA revealed that 79% received guideline-based antibiotics . Two surThe GL weakly recommends switching from the initial intravenous antimicrobial to an oral agent or discontinuing it if the fever subsides after the initial treatment despite persistent neutropenia. Besides, if the patient’s general condition is stable regardless of persistent FN for more than 3–4 days after initiation of therapy, it is weakly recommended to continue the primary treatment. Although the overall compliance rates were good, the complete compliance rates, 22.1% and 17.9%, were substantially low. Many respondents probably thought that intravenous antimicrobials should be continued until neutrophil recuperate because discontinuation may cause a resurgence of infection, and that persistent fever, even in stable condition, was deemed to be treatment failure. To comply with these recommendations presumably depends on multifactor, including patient condition, local healthcare-providing system, the evidence level, and healthcare economy. According to the questionnaire survey on antimicrobial practice for FN across European and Asian blood and marrow transplantation centers, about half of the centers responded to de-escalate or discontinue the first-line therapy when the fever of unknown origin with an uncomplicated presentation resolved by the treatment [GL does not recommend therapeutic G-CSF administration, which means starting G-CSF after FN onset, and advises to consider its application in case of deterioration. The rates of therapeutic G-CSF “always” and “more than half” were 33.6% and 31.0%, respectively. A case-based survey disclosed that 63% of hospitalized FN patients were administered therapeutic G-CSF in the USA , 14.Although GL strongly recommends using ppG-CSF in the regimens with FN occurrence of more than 20%, the complete compliance rate was low as 32.8%. Besides, regarding the use of ppG-CSF in patients at high risk for developing FN in regimens with FN incidence of 10–20%, the overall and complete compliance rates were also low as 58.5 and 14.6%, respectively. These results indicate that the ppG-CSF was discouraged by several disincentives, including low profitability in the DPC. A questionnaire survey of oncologist’s perceptions and opinions regarding the use of G-CSF in the USA demonstrated that 65% agreed using ppG-CSF in all of the patients with high risk for developing FN . It alsoThe present study clarified the discrepancy between GL recommendations and daily practice perception in the doctors engaging in chemotherapy. Due to the study’s limitations, these results could deviate from the actual practices when analyzing the patients’ files. To promote evidence-based FN management, further research will be needed, including prospective or retrospective cohort studies to disclose GL compliance state and questionnaire to identify inhibitory factors causing the gaps.


Monitoring aging parents' daily life is an essential task for adult children to ensure their parents’ health and safety. The current study examined domains of parents' lives that adult children monitored as caregivers. Based on social domain theory , we hypothesized that adult children would monitor parents’ health and safety issues as respecting parents’ autonomy in other issues. The study also examined how adult children’s belief in need for monitoring and their perception of having actual knowledge of their parents’ behaviors and thoughts would relate to the intensity of their intergenerational ambivalence. Adults who had at least one living parent  participated in online surveys. Issues of parents' lives that adult children monitored were categorized into four domains by factor analysis: parents' financial safety, health and physical safety, substance use, and plans with other adult children. A series of regression analyses revealed that adult children's sense of need to know about parents' financial safety was associated with lower ambivalence, B=-.60, SE=.18, β=-.23, p=.001, whereas parents’ physical safety was associated with greater ambivalence, B=.42, SE=.19, β =.17, p=.03. Adult children's perception of their knowledge about parents' financial safety was positively associated with their ambivalence, B=.58, SE=.20, β=.22, p=.004, whereas adult children's perception of parents' physical safety was negatively associated with their ambivalence, B=-.42, SE=.21, β=-.14, p=.05. Different meanings of different types of parents' safety issues for adult children as their caregivers and suggestions for future research will be discussed.


N, of myosin heads move an actin filament at a rate that is influenced by actin–myosin attachment and detachment kinetics is accounted for neither experimentally nor theoretically. To better understand the emergent mechanics of actin–myosin mechanochemistry, we use an in vitro motility assay to measure and correlate the N-dependence of actin sliding velocities, actin-activated ATPase activity, force generation against a mechanical load, and the calcium sensitivity of thin filament velocities. Our results show that both velocity and ATPase activity are strain dependent and that velocity becomes maximized with the saturation of myosin-binding sites on actin at a value that is 40% dependent on attachment kinetics and 60% dependent on detachment kinetics. These results support a chemical thermodynamic model for ensemble motor mechanochemistry and imply molecularly explicit mechanisms within this framework, challenging the assumption of independent force generation.Molecular motors such as kinesin and myosin often work in groups to generate the directed movements and forces critical for many biological processes. Although much is known about how individual motors generate force and movement, surprisingly, little is known about the mechanisms underlying the macroscopic mechanics generated by multiple motors. For example, the observation that a saturating number,  Molecular motors such as myosin and kinesin often work in groups to perform diverse biological functions such as vesicle transport, cell division, wound healing, and muscle contraction , 2, 3. Tin vitro motility experiments have been used to study how force and motion generation change with increasing numbers, N, of motors , at which actin filaments slide over a bed of myosin molecules increases with increasing numbers, N, of myosin molecules, saturating at a maximum velocity, Vmax, through a mechanism that continues to be disputed. For decades, it has widely been assumed that—in accord with independent force models—Vmax is limited by what are effectively molecular mechanical barriers to force transmission between independent force generators , that N myosin heads stall actin movement by myosin working steps. According to the independent force model, P(N) is simply the probability that at least one myosin head is bound to actin (P(N) is the probability that at least one myosin head is bound to actin and has reached the end of its mechanical tether (P(N) is the probability that an ensemble of myosin heads collectively reaches an internal stall force. Of importance, P(N) in the latter two models is clearly less than that in the independent force model. In all models, when P(N) = 1, actin movement can only occur with the detachment of the resistive head(s) (see V(N) saturates at a Vmax that is limited by actin–myosin detachment kinetics. Although this solid-state, detachment limit is theoretically possible within any of the above models, here we show that experimentally it is never reached (P(N) is always less than one) by myosin ensembles under physiological conditions.To describe this hypothetical mechanical limit to to actin . Accordil tether . Here wed(s) see , at whicV(N), P(N), and Vmax using an in vitro motility assay to directly measure and correlate, under nearly identical conditions, the N-dependence of actin sliding velocities, V(N); actin-activated ATPase activity, v(N); small molecule inhibition of ATPase activity; force generation against a mechanical load, F(N); and calcium sensitivity of thin filaments, pCa50(N). In all cases, we observe that these N-dependent measurements saturate at an N similar to that at which v(N) saturates, consistent with saturation of myosin-binding sites on actin.We determine the chemical kinetics underlying N, there is an insufficient number of myosin heads for processive movement (P(N) < 1). Here we show that, according to a thermodynamic force model, a peak V is reached well before the detachment limit (P(N) < 1) with at least one myosin head strongly bound to actin.According to an independent force model this means that, at saturating V(N) and how their relative contributions change with changes in N, linker compliance, and actin–myosin kinetics and energetics. These chemical thermodynamic mechanisms are broadly applicable to any molecular motor ensemble and account for our observations that both V(N) and v(N) are influenced by the strain-dependent kinetics of the myosin working step and that V(N) saturates at a Vmax that is influenced 40% by attachment kinetics and 60% by detachment kinetics.Our data and analysis support a classic chemical thermodynamic framework for describing motor ensemble mechanochemistry, demonstrating that force generation is thermally equilibrated within ensemble motor systems. Here, within this formal framework, we continue to develop the first molecularly explicit models for how myosin working steps, resistive myosin heads, and external loads influence A is a kinetic scheme of the actin–myosin ATPase reaction showing that the working step of a myosin head displaces an actin filament a distance d, upon strong actin binding at a rate katt, and a myosin head detaches from actin at a rate kdet.Figure 1B, top) actin sliding velocities are described in terms of the kinetics and mechanics of an individual myosin head, Vmax = d·kdet. According to this model, Vmax is fully determined by the displacement, d, generated by a single myosin head and by a single rate constant, kdet (C), and thus Vmax is inherently detachment limited. The N-dependence of V is determined by the probability that at least one myosin head is strongly bound to actin .In an independent force model B, top acnt, kdet C, and thB, bottom) multiple myosin heads collectively move an actin filament at Vatt = d·v (D) where v is the bulk (N-dependent) ATPase rate. A myosin head strongly bound to an actin filament imposes a resistive but nonarresting load against actin movement, and with increasing N a detachment limited Vdet = L·kdet is approached when a stall force is reached at the bulk (N-dependent) average maximum displacement, L. Movement resumes when myosin heads detach from actin at a bulk (N-dependent) rate (D). Figure 1D shows that, according to a thermodynamic model, actin sliding velocities are influenced by both attachment and detachment kinetics.In a chemical thermodynamic model B, bottomtt = d·v D where vnt) rate D. FigureN-dependent velocities, V(N), predicted by these two models are fundamentally different. A–C show the effects of attachment kinetics  on V(N) predicted by three models (see N is increased without bound (no saturation of binding sites), V(N) eventually saturates at a Vdet that is independent of N and katt and decreasing katt increases the myosin KM  without affecting Vmax = Vdet.The dels see : indepenin vitro motility assay to directly test whether decreasing katt increases KM without affecting Vmax = Vdet. Counter to predictions of all three models, Figure 2D shows that blebbistatin inhibition of katt  and indicate that V(N) saturates before a detachment limit is reached (when P(N) < 1). Here we test an alternative hypothesis that V(N) saturates not at the detachment limit but with the saturation of myosin-binding sites on actin.We use an  of katt  inhibits by katt . These rV(N) and the actin–myosin ATPase rate, v(N), should exhibit similar saturation kinetics (KM) and correlated maximal activities (Vmax and vmax)  nor v(N). studies . This su studies  have shov signal, we used higher concentrations of actin in this assay than typically used in a motility assay, and we confirmed that the majority of actin filaments were still moving under these conditions. Assuming an actin-activated ATPase activity of 40 s−1 (20-fold over 2 s−1), the ∼4-fold actin activation of ATPase activity observed at low N in To maximize the v(N) and V(N) measurements obtained in a motility assay at two different ionic strengths fit to hyperbolas. These data show that increasing KCl from 50 to 100 mM results in similar decreases in both Vmax and vmax , consistent with Vatt influencing Vmax (Equation Vmax with increasing KCl at high ionic strength is consistent with previous studies (V(N) and v(N) exhibit similar saturation kinetics with KM values of 16 ± 8 and 46 ± 32, respectively, at 50 mM KCl and 17 ± 9 and 23 ± 13, respectively, at 100 mM KCl. studies . Both V against a mechanical load. Force generation by myosin molecules along an actin filament increases linearly with the number, N, of myosin available to bind that actin filament. Thus, according to our hypothesis, the KM for myosin force generation in a motility assay should resemble that of both V(N) and v(N) determined above. We tested this prediction by measuring the N-dependence of myosin force generation against a mechanical load imposed by α-actinin in a motility assay.To further test the saturation kinetic hypothesis and its implications for the models in Figure 2V. Assuming that the force, F(N), collectively generated by myosin molecules against this load increases with N as F(N) = Funi·N⋅r  the N-dependence of V(N) is described by Equation Funi is the average force generated per myosin head and γ is a frictional coefficient that, according to a molecular model for friction , which at relatively high Vatt approaches the α-actinin equivalent of Equation Alpha-actinin binds to actin and when adhered to a motility surface imposes a mechanical load against actin movement by weakly linking actin to the surface. In effect, α-actinin acts as a frictional load  that slofriction , equals ing step , 17. EquV(N) against a mechanical load (Equation F(N), in external compliant linkages such as alpha-actinin , it follows that V determines −Funi⋅N⋅r, which is simply not true. Myosin working steps actively generate Funi⋅N⋅r (and the opposing Ff) against alpha-actinin linkages, and Funi⋅N⋅r determines V as described by Equation Fig. 1D), not the other way around.The collective force formalism provides a clear working-step influenced mechanism for Equation . This isinin see ; insteadmines Ff , and becA is a graph of V(N) measured in an in vitro motility assay with and without α-actinin on the motility surface. These data show that, at subsaturating myosin (N < 50), V(N) slowed by an α-actinin load (increasing γ) can be recovered by increasing N, consistent with Equation N values above those at which V(N) and v(N) saturate, V(N) inhibited by α-actinin cannot be recovered by further increasing N, implying that F(N) saturates with V(N) and v(N). Fits of the α-actinin data to a hyperbolic function give KM values for F(N) (16 ± 7 at 0.5 μg/ml α-actinin and 38 ± 13 at 1.0 μg/ml α-actinin) that are not significantly different from the KM values for V(N) and v(N)  , furtherkws, can in theory only be a function of local strain, independent of the external alpha-actinin load. In contrast, we previously showed that working step energetics are a function of an external muscle load (kws = kws°⋅exp(−w/kBT), where w is the work performed in collectively stretching external compliant linkages like those introduced by alpha-actin , suggesting that α-actinin decreases katt by decreasing the rate-limiting kws. This interpretation is supported by the data in Figure 5B. We measure the actin-activated ATPase activity with and without α-actinin during a motility assay at low N (= 5), conditions under which V is primarily limited by katt. We observe that the load imposed by 1.0 μg/ml α-actinin inhibited actin-activated ATPase activity by 55% (B), consistent with the external α-actinin load inhibiting kws, as predicted by collective force models.According to Equation e by 73% A, suggesy by 55% B, consisN-dependence of myosin activation of thin filaments. In 2010 we developed and tested experimentally a simple two-state model for thin filament activation of thin filament motility by calcium and myosin , N, and the actin–myosin duty ratio, r (the fraction of time myosin spends strongly bound to an actin filament). Specifically, we showed that pCa50 is proportional to Nˑr. Previously we showed that pCa50 increases linearly with N (N = 100 (100 μg/ml myosin incubation), but we never measured pCa50 at N > 100. Here, using an in vitro motility assay, we measured the calcium dependence of V at both 50 and 100 mM KCl and obtained pCa50 values from Hill fits to pCa–V curves , v(N), and F(N).To further test the kinetic saturation hypothesis, we consider the d myosin , 40, 41.V curves , inset a50 for calcium binding to TnC in the absence of myosin and the slope is proportional to the actin–myosin duty ratio  is half the N at saturation. Using this approach, the pseudo KM for pCa50 is 24 for 50 mM KCl and 26 for 100 mM KCl, similar to KM values for V(N), v(N), and F(N)  where according to our model the y-intercept is the pCaty ratio . The horand F(N) .K. In Figure 7A, simulations of V(N) at different katt values are compared with the blebbistatin data from Figure 2D. Figure 7B shows simulations of F(N). Although these results suggest that in a standard motility assay actin–myosin binding saturates at a Vmax prior to P(N) saturating at 1, P(N) is not zero at Vmax. In other words, detachment kinetics still contributes to Vmax. This is supported by numerous studies that have demonstrated a correlation between Vmax and kdet . For example, we have previously shown that Vmax is influenced more by Vdet in a myosin monomer–based motility assay than in a myosin filament–based motility assay  when actin–myosin binding saturates—in a standard motility assay. At P(N) = 0, V = Vatt is attachment limited (Equation V has a KM(ATP)  of katt/kT, where kT is the second-order ATP binding constant. V measured in an in vitro motility assay at low N (= 5) and low P(N). A hyperbolic fit to these data gives a KM(ATP) = katt/kT of 0.01 mM. At P(N) = 1, V = Vdet is detachment limited (V has a KM(ATP) of k−D/kT, which is (k−D/katt)-fold greater than the KM(ATP) at P(N) = 0. Here k−D is the rate constant for ADP release. Assuming a duty ratio of katt/k−D = 0.1, we expect the KM(ATP) for Vdet to be 10-fold greater than the KM(ATP) for Vatt. V obtained at saturating N (= 100) fitted to a hyperbola with a KM(ATP) of 0.04 mM. This is 40% of the KM(ATP) predicted for Vdet, implying that P(N) = 0.4 at saturating N.Here we estimate the extent to which Equation  and the  limited  and the V(N) and F(N) within this classical framework.Many biological processes rely on collections of molecular motors to generate macroscopic forces and movement , 2, 3. Tin vitro motility assay, myosin-generated actin sliding velocities, V(N), increase with increasing N, saturating at a Vmax that is influenced by both actin–myosin attachment and detachment kinetics. The conventional assumption of a detachment-limited Vmax is based more on adherence to the formal constraints of the independent force model than on experimental data, as the influence of v on Vmax was long ago demonstrated —that a single actin-bound myosin head prevents actin movement and force transmission—is the purported mechanism by which myosin heads are thermally isolated in shortening muscle despite there being no known molecular mechanisms for such a barrier to thermal force. Within this framework, motor kinetics and energetics are only influenced by the work individual motors perform locally and are uncoupled from any work performed on external compliant elements through subsequent actin movement. Thus, unique to this model is the definition of molecular stress-strain curves, a characteristic feature that identifies most models of muscle contraction to date as independent force generator models   , 43, conThe Gibbs’ chemical thermodynamic and Hill’s molecular mechanics formalisms are fundamentally different. They are based on fundamentally different assumptions with fundamentally different formal constraints, resulting in fundamentally different predictions. The data and analysis herein highlight some of those differences and further demonstrate that motor ensemble mechanochemistry is consistent with Gibbs’ chemical thermodynamics not Hill’s molecular mechanics.kws contributes to Vmax implies that myosin working steps directly contribute to actin movement and perform work on all external compliant elements stretched by that movement, challenging the independent force generator formalism. The observation that myosin-binding sites on actin saturate before a detachment limit is reached implies that kws contributes to Vmax in any actin–myosin system, including muscle. The data and analyses herein infer explicit mechanisms for a classical chemical thermodynamic model. Equations P(N) and L  against a load (Equation The observation that nd L see  provide Equation  as opposEquation .V(N) (limited by katt at low N) and v(N) (limited by katt) implies that the work performed by myosin working steps in stretching α-actinin linkages slows kws. Although we cannot rule out that the α-actinin load diminishes to some extent d and/or kdet, the observation that it decreases kws by more than 50% (B) is inconsistent with the independent force model, whereas this external strain dependence is predicted by a collective force model  is then the probability that a stall force is reached by N myosin heads, which occurs when many myosin heads are strongly bound to actin (C).In the same way that the independent force model formally precludes myosin working steps from collectively performing work against an external load  and streFig. 1to actin C.L and P(N), including the Gibbs free energy for the working step (L (L) from which we developed an analytical expression for P(N). In general, however, a more realistic model requires strain-dependent kinetics and collective force generation in stretching compliant linkages. Here we have developed the simplest possible discrete state collective force model (see C). It is worth noting that our computer simulations of collective force in Figure 2C resemble our mathematical model of collective displacements plotted in Figure 2B. We continue to refine and test this model through experiments like those presented here.We have previously shown that many factors influence ing step , the numing step , and theing step . Our rec step  = 0.4 when myosin-binding sites on actin are saturated (P(N). Assuming that there are 28 myosin-binding sites on actin along the pseudo repeat of a 1-μm actin filament and a duty ratio of 0.1, we would expect on average 2.8 strongly bound myosin heads not 0.4 as inferred by the independent force model. In muscle, this discrepancy is even greater considering the myosin S2 tether further decreases P(N) (P(N) is the probability that at least one myosin head is strongly bound to actin, the fraction of time no myosin heads are strongly bound to actin is [1 − P(N)]. This would imply that a 1-μm actin filament sliding at Vmax in a motility assay spends 60% of its time with no myosin heads strongly bound and even more time with no heads strongly bound in muscle, which is inconsistent with sustained muscle contractions. Clearly, the probability that actin-bound myosin heads stall actin movement, P(N), is much smaller than the probability that at least one myosin head is strongly bound to actin, which is to say that a strongly bound myosin head does not prevent actin movement or force transmission; myosin working steps directly move actin filaments and generate force in external elements; and multiple myosin heads collectively generate force against common actin-bound myosin heads, compliant linkages, and external loads that resist that movement, inconsistent with independent force generation.Our observation that aturated  is also ses P(N) . In addiVmax has mechanistic significance. For example, near the attachment limit [P(N) << 1], muscle shortens at a maximum velocity per myosin head with minimal energy lost to myosin head–head interactions and internal force generation, whereas near the detachment limit [P(N) = 1] myosin head–head interactions generate internal strain during shortening that can provide functionally significant cooperative mechanisms involving strain-dependent kinetics  and v(N) are both strain dependent and that V(N) saturates at a Vmax that is influenced 40% by attachment kinetics and 60% by detachment kinetics, filling an important gap in our basic understanding of ensemble actin–myosin mechanics. The observation that myosin-binding sites on actin saturate prior to a detachment limit precludes a detachment-limited Vmax in any actin–myosin system, including muscle. The impact of these results extends well beyond this basic observation, however. These results inform our continuing development of the first explicit models for V(N) and F(N) within a classical chemical thermodynamic framework that is broadly applicable to any molecular motor ensemble, providing insights into how motor working steps, resistive motors, and other resistive external loads all influence and contribute to V(N) and how the relative contributions of these mechanisms change with changes in N, motor kinetics and energetics, and linker compliance.The data and analysis reported herein provide explicit mechanisms for our observations that in vitro motility assays, actin (1 μM in actin buffer) was incubated with 1 μM tetramethyl-rhodamine isothiocyanate (TRITC)-phalloidin (Sigma) overnight at 4 °C prior to dilution to the experimental concentration (see below). Skeletal tropomyosin and troponin (Tm-Tn) were purified as described , 2 mM EGTA, 8 mM MgCl2, and 10 mM DTT. Motility buffer contained 50 mM imidazole (pH 7.4), 2 mM EGTA, 8 mM MgCl2, 10 mM DTT, 0.5% methylcellulose and KCl, and 1 mM ATP. Motility buffer also contained an oxygen scavenger system  that was added immediately prior to imaging , 1 mM EGTA, 4 mM MgCl imaging .−1 bovine serum albumin in actin buffer, 10 nM TRITC-actin in actin buffer prepared as described above, actin buffer, and motility buffer. Each solution was incubated in the flow cell for 1 min before adding the next. Blebbistatin experiments were performed using 10 and 50 μM (-)-blebbistatin (Sigma-Aldrich) in the motility buffer . Myosin solutions of different concentrations in myosin buffer were applied to the flow cell followed by 2 × 50-μl aliquots in sequence of 5 mg mly buffer . For loay buffer . A totalV values are averages of at least three (n = 3) independent experiments with standard error reported with error bars.MetaMorph software (Molecular Devices) was used for image acquisition. For each flow cell, 30-s image sequences from three different fields were recorded. Actin velocities were manually tracked using the MTrackJ plug-in for ImageJ (NIH). Only smoothly moving filaments with trajectories greater than 3 μm were selected for analysis. An average velocity for a given trajectory meeting the above criteria was determined using ImageJ. For a given experiment (one flow cell) 45 to 100 trajectories were recorded and analyzed (n = 1). Reported v, was measured in a motility flow cell having the geometry described above with three minor differences: (i) tape was added to only one side of the flow cell to allow access to the solution within, (ii) higher concentrations of TRITC-actin  were used to increase the ATPase signal, and (iii) ATPase measurements were made over longer periods than motility measurements. Specifically, solutions and proteins were added as described above for the motility assay, but instead of mounting the slide on a microscope, slides were placed on a slide warmer set to 30 °C. At 5, 10, 15, 30, 35, 45, and 60 min time points, an individual flow cell was opened (side without the tape was lifted) and 25 μl of solution was removed and added to 250 μl of malachite green  and mixed with a positive displacement pipette. The reaction was quenched with 30 μl of 34% sodium citrate solution, and absorbance was read at 650 nm in a 96-well plate reader using Gen5 (Biotek) software. In all experiments, the time course of absorbance was well fit to a line with the slope being a proportional measure of the total ATPase activity in that flow cell. Because the total ATPase activity is the sum of the ATPase activity of myosin heads interacting with actin (actin-activated ATPase) and the activity of myosin heads not interacting with actin , we subtract the basal ATPase from the total ATPase to obtain the actin-activated ATPase activity. We measured the basal (myosin) ATPase activity for each experimental condition by repeating all of the steps above except no TRITC-actin was added. Because we were unable to quantitate the amount of actin interacting with myosin in these experiments, we were only able to measure relative changes in actin-activated ATPase activity not absolute values. One-hour time courses obtained both in the presence and absence of actin constitute one experiment (n = 1), and a total of three experiments (N = 3) were averaged per data point.Actin-activated ATPase activity, N, of myosin available to bind a unit length (1 μm) of actin is proportional to the myosin surface density. To calculate N, we multiply [M] by a conversion factor 1 (myosin per μm actin) (ml/μg) consistent with estimates in Harris and Warshaw  moves an actin filament a distance, d, with a working step every time it completes one actin–myosin ATPase reaction cycle (A and B). In theory, the speed at which one myosin head can move an actin filament is V = d∙v, where v is the actin–myosin ATPase rate  is limited by katt . At low N, v(N) increases linearly as N·katt, and at sufficiently high N, v(N) saturates at Nactin·kws, where Nactin is the number of myosin-binding sites per 1 μm actin filament. We use 1 μm because it is roughly the length above which segmental actin movements become redundant, a length beyond which the force generated by a given myosin head is not transmitted (Vatt(N) saturates at a maximum velocity, Vmax, of kws·Nactin·d.At saturating [ATP],  by katt , and so  limited   does not take into consideration the mechanical effects of actin-bound myosin heads that impose mechanical loads against actin sliding at high N. The probability, P(N), that actin-bound myosin heads stall actin sliding increases with increasing N, and when P(N) = 1, actin movement can only occur with the detachment of resistive myosin heads at which point V reaches a detachment limit  at a rate kdet  to detach from actin is 1/kdet. Thus the detachment-limited V is B)  B 33), w, wV(N) dN-dependence of the relative contributions of attachment (Equation P(N) and L are model dependent, achieving this goal requires discriminating between two fundamentally different models: the independent force generator model and the collective force model  is then the probability that at least one myosin head is strongly bound to actin, and L = d (B). Equation A) and the N-dependence of V is V(N) = Vdet·P(N)  .C) actin movement stalls when the compliant linkages associated with myosin heads strongly bound to actin are collectively displaced a distance L by the working steps of N myosin heads before reaching a stall force, F(N), which increases linearly with N (P(N) is the probability that a collectively generated internal stall force is reached, and L = F(N)/κ, where κ is the effective stiffness of the compliant linkages associated with strongly bound heads. According to this model, V(N) = Vdet·P(N) + Vatt·(1 − P(N)) (C). Based on our recent observation that the myosin S2 tether significantly increases L in a myosin filament motility assay, we previously developed an idealized model in which the compliant linkage was infinitely compliant with a hard stop when stretched a distance L (the length of the tether) from which we developed an analytical expression (B) for P(N) ) C. Based pression B for P(Nfor P(N) . We refeA with forward and reverse rate constants set to values consistent with those measured in skeletal muscle myosin. A single elastic element of stiffness κ is collectively displaced by myosin heads a distance 8 nm with each actin–myosin weak-to-strong binding step and 2 nm with each ADP release step. Strain-dependent kinetics are incorporated by multiplying the rate constants for each of the two mechanochemical steps by exp(−w/kBT), where w is the work performed displacing the elastic element. Here, kB is Boltzmann’s constant and T is temperature. Monte Carlo simulations were run with 1-μs time steps. Simulations were run either without saturation kinetics  or with saturation kinetics .Our collective force model is based on the ATPase kinetic scheme in Figure 1All data are contained within the article.The authors declare that they have no conflicts of interest with the contents of this article.


Recent studies on fertility awareness among the reproductive population have reported the lack of accurate knowledge about fertility and assisted reproductive technologies. However, there has been little information regarding women trying to get pregnant at home. The aim of this study was to explore the prevalence of subclinical infertility among women trying to get pregnant at home, and to evaluate awareness regarding infertility and reasons for not visiting infertility clinics among women who use pregnancy-assist mobile applications to help them conceive.A total of 2084 Japanese women responded to this online survey. We selected 1541 women according to the study criteria. Based on the results of 61 questions, we evaluated knowledge regarding fertility, prevalence of subclinical infertility, and reasons for not visiting the clinic among the participants.Despite the desire to conceive, the participants had an apparent tendency to overestimate the age limit for childbearing. A total of 338 (21.9%) women answered that in general women aged > 45 years could get pregnant. Approximately 40% of the women had possible subclinical infertility and were unaware of the fact. Additionally, about 70% of the women considered themselves to have infertility problems. Women who were aware of the possibility of infertility hesitated to visit the clinic due to unfamiliarity with a gynecologist or clinic, and apprehensions about the gynecologic examination.In our study, some women required treatment for infertility. Nonetheless, they hesitated to visit an infertility clinic. Sexual health education, together with proper accessibility to gynecology clinics, are necessary to reduce involuntary childlessness. The average age of first pregnancy has increased in most countries since the 1980s –4. AlthoMoreover, recent studies on fertility awareness in the reproductive population have reported the lack of accurate knowledge about fertility and assisted reproductive technologies (ART) among women who are trying to conceive , 9–22. TThus, women have been able to access fertility information more easily than before. However, the number of infertile patients has been increasing in Japan . The afoThe majority of previous studies on fertility-related knowledge have been conducted among university students , 26, 27.There have been some studies regarding fertility knowledge among the general population , 28, 29.We conducted the study on a smartphone application  that comprised user information, including women’s health, fertility, and ovulation prediction  in September 2018 . We chosA total of 2084 women responded to this survey. We selected 1541 women according to the inclusion criterion, that is women who wanted to have children at that time, and two exclusion criteria, that is (1) women receiving infertility treatment and (2) women receiving hormone therapy The first question was, ‘Do you want to have children now?’ (Yes/No). Only participants who answered ‘Yes’ proceed with the following questions: ‘Are you receiving infertility treatment?’(Yes/No) and ‘Are you receiving hormone therapy?’(Yes/No).Participant’s demographic information (31 items)Participants were asked to state their age, body weight, height, smoking status (Never or Former/Current), medical history (open response), social status (Full-time/Part-time/Housewife or Unemployed/Student), marital status (Yes/No), and personal experience of reproduction .Menstrual information (10 items)Participants were asked to state their age of menarche and pattern of menstrual cycle . The answer to the menstrual cycle was defined according to the criteria of the Stage of Reproductive Aging Workshop . Next, pKnowledge about age-related decline in fertility (1 item)The question was, ‘In general, until what age do you think women can get pregnant?’.Attitude and behavior towards trying to get pregnant (4 items)Participants were asked the following questions: ‘Since how long are you having intercourse without contraception?’, ‘How frequent do you have intercourse?’(open response), ‘Do you feel any difficulties while having intercourse?’ (Yes/No), and ‘What are you doing to become pregnant? (Self-timing therapy with application service/Self-timing therapy without application service/Nothing in particular)’. We chose the following question: ‘What are you doing to become pregnant?’ to clarify the number of women who used the application service of self-timing therapy because it would be an important participants’ characteristic for this study.Awareness and attitude regarding infertility (4 items)At first, participants were asked the question, ‘Have you ever had an infertility examination?’(Yes/No). Only participants who answered ‘Yes’ proceed with the following questions: ‘What is the likelihood of your infertility?’  , ‘Do youWith regard to the last question; ‘Why haven’t you visited a clinic for infertility examination?’, we presented several likely answers for the participants to choose from, including the option “other” as it allowed respondents to answer the question freely.Partner’s demographic information (9 items)Participants were requested to state their partner’s age, body weight, height, and medical history (open response).Based on previous research, the questionnaire was designed for this study by three gynaecologists, including one reproductive medicine specialists , 21, 24.P value < 0.05 was considered statistically significant.We performed logistic regression analysis to assess the risk factors for subclinical infertility among women trying to get pregnant at home. We defined subclinical infertility among women who failed to conceive successfully after ≥ 12 months of regular, unprotected intercourse (or ≥ 6 months if the women over age 35 years), according to the Practice Committee of the American Society for Reproductive Medicine, 2013 . We calc2 (67.6%), respectively. Regarding their partner, the largest age and BMI group were 30–39 years (52.0%) and 18.5–24.9 kg/m2 (64.9%), respectively. 234 (15.2%) participants and 636 their partners (41.3%) were current smokers.Table Nearly 80% of the women had a job . Of 1541, 1,247 (80.9%) women were married and 582 (37.8%) women had children.A total of 41 women (2.7%) had gynecologic disease: Endometriosis 12 (0.8%), Myoma 8 (0.5%), Ovarian cyst 5 (0.3%), and Dysplasia of uterine cervix 9 (0.6%). There were no women who had medical history which leads infertility necessarily, for example bilateral oophorectomy or hysterectomy.Regarding to menstrual cycle, regular, variable-length; persistent ≥ 7-day difference in the length of consecutive cycles, and interval of amenorrhea of ≥ 60 days were 76.9%, 10.2%, 4.7%, respectively. 652 (42.3%) out of all participants suffered with dysmenorrhea.Table Approximately 338 (21.9%) women believed that women aged > 45 years could have children. Additionally, 47.7% of the participants selected the 40–44 years category as the upper age limit to have children. These results highlight the apparent tendency of most participants to overestimate the possible age of childbearing.About three-quarters (74.4%) of the women used the ovulation prediction service included in the application. The number of women whose sterile period was < 1 year, 1 year, 2 years, 3 years, and ≥ 4 years was 746 (48.4%), 267 (17.3%), 159 (10.3%), 94 (6.1%), and 222 (14.4%), respectively.Regarding infertility awareness, about 70% of women thought the following about the possibility of infertility: (1) highly unlikely (7.9%), 2) unlikely (22.2%), (3) possibly (42.2%), (4) likely (19.9%), and (5) highly likely (7.7%). Among these five groups divided by the likelihood of their infertility, the prevalence of subclinical infertility was calculated as shown in Fig.  unlikelyOver half of the 1,362 women, who had never been examined for infertility, were aware of the necessity for an infertility examination. The primary reasons for not visiting the clinic were as follows: (i) “no time” (22.5%), (ii) “hesitation to know the truth” (22.4%), and (iii) “an absence of a familiar gynecologist or clinic (22.3%).” Other reasons behind this hesitancy included the following: (1) “the fear of gynecologic examination” (12.7%), (2) “an uncooperative partner” (7.9%), and (3) “the hesitation to let another person know about their infertility (6.5%).” Among the potential answers, the most common subjective reason given for the “other” option was “I do not think myself infertility because of experience of giving birth ”, and the second was “financial reason ”.P = 0.001) and 40–44 years  and women whose partners were aged 40–49 years , had a significantly higher risk of infertility, compared to the youngest group. On the other hand, women’s BMI, smoking history, incidence of abortion or miscarriage, and BMI of male partners were not significant risk factors for infertility.Table Several previous studies have highlighted the poor knowledge regarding fertility among women of reproductive age , 26–29. The number of women who need infertility treatment has been recently increasing in several countries , 35. AmoIn this study, the apparent tendency to overestimate the age limitation for childbearing was consistent with those in previously published results , 9–22. OPasset-Wittin, J. identified five categories of determinants of medical help-seeking for infertility: socio-demographic variables, socio-economic factors, reproductive history, attitudes, and psychological factors . AlthougThe multivariate analysis in our study indicated “multipara” as a significant risk factor for infertility. Such women may lack sufficient awareness on secondary infertility due to a previous pregnancy. Despite being overlooked for secondary infertility, such women should be aware of infertility in case of a long period of sterility.Our study has several limitations. First, the participants were selected from among those who used a particular application, thus, raising the possibility of a selection bias. The aforementioned application presented information about pregnancy and was aimed at helping the users conceive. Thus, the participants might have had a stronger desire to bear a child, compared to ordinary women. In addition, there were 10 university students in this study. In general, it is rare for university students to try to get pregnant. However, the number was so small  that including university students would have little influence on our results. Second, we conducted the study among Japanese women who often harbor negative and sensitive ideas about infertility. This tendency of more women hesitating to go to the clinic for infertility examination or women not wanting to know the truth that they are infertile may have influenced our results. Third, our investigation lacked information about the selected participants’ place of residence. There are several infertility clinics in a city, compared to the few in the countryside. This uneven distribution of infertility clinics might have also influenced the choice to seek infertility treatment. Thus, the differences in this study could not be clarified. Fourth, as there had been no research about medical help-seeking for infertility in Japan, we designed some of the questions about “awareness and attitude regarding infertility” for this study. However, the information might be biased.According to our investigation, there may be a significant number of women with subclinical infertility among those trying to get pregnant at home. Furthermore, these women generally hesitate to visit the clinic for several reasons, namely, being unfamiliar with seeing a gynecologic doctor and feeling afraid of discovering the truth. Additionally, our results also indicate that prior experience of childbirth might be a possible risk factor for secondary infertility.The dissemination of correct knowledge regarding fertility and infertility is insufficient. The presence of a gynecologist who could provide medical advice at an appropriate time might effectively resolve the problem that some subclinical infertility patients encounter, namely; hesitant to go to a clinic because of an unfamiliar gynecologic doctor or clinic. Our study had a small sample size with limited participants. This calls for the need for large-scale studies in various countries.


Background and Objectives: Barefoot peak plantar pressures (PPPs) are elevated in diabetes patients with neuropathic foot ulcer (DFU) history; however, there is limited reported evidence for a causative link between high barefoot PPP and DFU risk. We aimed to determine, using a simple mat-based methodology, the site-specific, barefoot PPP critical threshold that will identify a plantar site with a previous DFU. Materials and Methods: In a cross-sectional study, barefoot, site-specific PPPs were measured with normal gait for patients with DFU history (n = 21) and healthy controls (n = 12), using a validated carbon footprint system. For each participant, PPP was recorded at twelve distinct plantar sites , midfoot and heel), per right and left foot, resulting in the analysis of n = 504 distinct plantar sites in the diabetes group, and n = 288 sites in the control group. Receiver operator characteristic curve analysis determined the optimal critical threshold for sites with DFU history. Results: Median PPPs for the groups were: diabetes sites with DFU history (n = 32) = 5.0 (3.25–7.5) kg/cm2, diabetes sites without DFU history (n = 472) = 3.25 (2.0–5.0) kg/cm2, control sites (n = 288) = 2.0 (2.0–3.25) kg/cm2; (p < 0.0001). Diabetes sites with elevated PPP (>6 kg/cm2) were six times more likely to have had DFU than diabetes sites with PPP ≤ 6 kg/cm2 , p < 0.0001). PPP > 4.1 kg/cm2 was determined as the optimal critical threshold for identifying DFU at a specific plantar site, with sensitivity/specificity = 100%/79% at midfoot; 80%/65% at 5th metatarsal head; 73%/62% at combined midfoot/metatarsal head areas. Conclusions: We have demonstrated, for the first time, a strong, site-specific relationship between elevated barefoot PPP and previous DFU. We have determined a critical, highly-sensitive, barefoot PPP threshold value of >4.1 kg/cm2, which may be easily used to identify sites of previous DFU occurrence and, therefore, increased risk of re-ulceration. This site-specific approach may have implications for how high PPPs should be investigated in future trials. The aetiology of plantar foot ulceration for people with diabetes is underpinned by the presence of peripheral neuropathy, leading to a loss of protective sensation, deformities in the bony architecture of the foot and soft tissue changes, culminating in elevated weight-bearing plantar pressures and tissue breakdown ,2. The cAlthough current guidelines advise diabetes patients with neuropathy to use adequately off-loading therapeutic footwear on a daily basis to reduce elevated plantar pressures and DFU risk , the lifThere are, to date, no DFU risk reports of the distribution of barefoot PPP at distinct plantar sites, the site-specific relationship between barefoot PPP with DFU or barefoot PPP critical thresholds above which DFU develop. Maintaining PPP below a threshold of 200 kPa has been recommended as the target in-shoe pressure threshold in footwear prescription for patients with prior ulcers . This isPlantar DFU location is discrete and site-specific, occurring predominantly at forefoot sites—often at the great toe and metatarsal heads (MTHs)—with mid-foot sites commonly affected in Charcot patients ,18,19. WIn a cross-sectional analysis of a cohort of ‘high-risk’ people with diabetes with a previous history of plantar DFU, we aimed to: (1) determine the prevalence and distribution of individual plantar sites with critically high barefoot PPP; (2) determine whether previously ulcerated sites remain under high PPP (and therefore explain the high-risk of DFU recurrence); (3) determine a site-specific, critical threshold of barefoot PPP for DFU history, in order to help the footcare team identify and target occasional ‘high-risk’ plantar areas.This study was a cross-sectional cohort study of a sub-cohort of 21 people with diabetes with a previous history of plantar DFU, participating in a randomised, proof-of-concept trial of an intelligent insole system for DFU prevention . ParticiThe study was approved by local research ethics committees on 24 October 2013 and other relevant governance bodies in the UK .n = 21), who had been previously referred by their general practitioner to a secondary care, multi-disciplinary outpatient diabetes foot clinic in central Manchester, UK, for their foot ulcer assessment and management, were recruited to the study. Inclusion criteria were age ≥ 18 years, Type 1 or Type 2 diabetes, history of previous ulceration on the weight-bearing surfaces of the foot, presence of diabetic polyneuropathy as defined by any loss of sensation, ability to walk independently for 30 steps. Main exclusion criteria included: active foot ulceration, severe vascular disease, lower limb amputation above the level of the ankle, BMI > 40 kg/m2 [n = 12) who had never received a clinical diagnosis of diabetes, and who were staff at Manchester Royal Infirmary, were also consented and recruited into the study.Participants with diabetes  classified patients with neuropathy. Callus severity was scored at 12 distinct plantar sites per foot, as previously described .n = 12 healthy, age-matched controls without diabetes underwent the same procedure.Barefoot peak plantar pressures during normal gait were measured using the simple, validated carbon footprint system, PressureStat™ , formerly known as Podotrack  . At the Following data collection, three researchers trained in PressureStat™ assessment  independp < 0.001) and the diabetes group ; therefore, one analyser’s results alone was randomly selected for all further data analyses. Focal plantar pressure of ≥ 6 kg/cm2  was used as the initial standard definition for critically ‘high’ pressure during barefoot walking [The intraclass correlation coefficient (ICC) for inter-observer reliability for PPP recordings was high for both the control group . All data were checked for normality of distribution by examining histograms and comparison of mean/median values. Baseline data were compared between groups of participants with diabetes versus healthy controls using an independent Student’s For the inter-observer reliability analysis, a two-way mixed-effects consistency multiple-observers/measurements ICC model was used.n = 288), (b) all diabetes sites without DFU history (n = 472), and (c) all diabetes sites with DFU history (n = 32) were compared between the groups using a Kruskal-Wallis one-way ANOVA.The frequency distribution of PPP recordings for (a) all control sites  control sites, (b) diabetes sites without DFU history and (c) diabetes sites with DFU history were compared between groups using a one-way ANOVA and subsequent post-hoc Scheffé test.Logistic regression analysis models were constructed to assess the predictive value of PPP cut-off values for identifying DFU history for diabetes plantar sites only (odds ratios equate to relative risks when outcomes are < 10%). Receiver operator characteristic (ROC) curves were used to generate performance thresholds for PPP and examine the sensitivity/specificity of these thresholds at different plantar sites. All individual plantar sites were considered to be independent of sites on the same or other foot for each participant, based on evidence from prior research  and the n = 21) and the age-matched healthy controls (n = 12) are in n = 12, (38%)) and the hallux ), with other sites being at the toes 2–5 ), midfoot ) and heel ). The mean duration since the previous ulcers had healed was 5.5 ± 3.9 years.The baseline characteristics of those with diabetes (2) was 41, i.e., just 8.1% of all plantar sites assessed. The total number of sites with PPP ≥9 kg/cm2 (‘very high’ PPP) was 5/504, i.e., <1% of all plantar sites assessed. In the control group, the total number of plantar sites assessed for PPP was 288 (12 plantar sites × 2 feet × 12 patients = 288). The number of sites with PPP ≥6 kg/cm2 (‘high’ PPP) was 0/288 (0%).In the diabetes cohort, PPP was assessed at 504 individual plantar sites (12 plantar sites × 2 feet × 21 patients = 504). The total number of sites with ‘high’ PPP (≥6 kg/cmn = 19) had zero ‘high’ PPP sites (≥6 kg/cm2), 36% (n = 15) had 1 high PPP site, and 19% (n = 8) had two or more high PPP sites. There was an average of just 1 high PPP site per foot.Analysis of the 42 individual feet in the diabetes cohort showed that 45% feet (n = 42) were highest at the 5th MTH (4.6 ± 2.5 kg/cm2), 2nd MTH (4.3 ± 2.2 kg/cm2), great toe (4.3 ± 1.6 kg/cm2), 1st MTH (4.2 ± 2.0 kg/cm2) and 4th MTH (4.1 ± 1.5 kg/cm2). All other plantar sites had mean PPP < 4 kg/cm2(data not shown). Mean PPP at the great toe was significantly higher in feet with general toe deformities (claw/hammer toes) , than feet without toe deformities .Mean PPP levels at specific plantar areas in all individual diabetes feet (n = 792) recorded at specific plantar sites for all (n = 33) study participants, split into 3 sub-groups for analysis: (A) healthy control sites (n = 288); (B) diabetes sites without DFU history (n = 472); (C) diabetes sites with DFU history (n = 32). Median (IQR) PPP for the groups were: healthy control sites = 2 kg/cm2 (2–3.25); diabetes sites without DFU history = 3.25 kg/cm2 (2–5); diabetes sites with DFU history = 5 kg/cm2 (3.25–7.5), and all 3 groups were significantly different (p < 0.0001). Curves for control sites and diabetes sites without DFU history were normally distributed/moderately skewed ; whereas the curve for diabetes sites with DFU history was moderately/highly skewed towards the right (skewness = 0.97).n = 288), diabetes sites without DFU history (n = 472) and diabetes sites with DFU history (n = 32), is given in p < 0.0001). Furthermore, specific, individual sites with DFU history  had significantly higher PPP  than their equivalent sites without DFU history . In contrast, there was no difference at the great toe for PPP when comparing DFU history sites vs. no DFU history sites; furthermore, across all conditions, PPPs were generally lower at the hallux than other plantar sites. All healthy control sites had lower mean PPP compared to all diabetes group sites without a history of DFU (p < 0.0001). Similarly, the control group mean PPP was consistently lower at each individual site between these two groups: at the great toe, 1st–5th MTHs, midfoot and heel (p < 0.05).A comparison of mean PPP levels between the three groups of plantar sites  PPP for identifying DFU history. The model was DFU site history vs. no DFU site history, using a PPP threshold of ≥ 6 kg/cm2 at that site (n = 504 sites included). The odds ratio for this model was 6.4 , p < 0.0001, indicating that any plantar sites with PPP ≥ 6 kg/cm2 were six times more likely to have a history of DFU than sites with PPP below this threshold. This ‘site-specific’ model showed a much stronger and predictive OR compared to an alternative ‘whole foot’ model, i.e., DFU site history vs. no DFU site history, with high PPP threshold of (≥ 6 kg/cm2) at any plantar site on the foot (n = 504). In the latter ‘whole foot’ model, the OR showed no association between DFU site history and high whole-foot PPP (OR = 1.4 (0.67–2.93), p = 0.37).For all diabetes sites (with and without a DFU history), a logistic regression analysis model was constructed to assess the predictive value of site-specific ‘high’ (≥ 6 kg/cmn = 504 sites); (B) great toe only (n = 42 sites); (C) combined metatarsal and mid-foot sites (n = 252 sites); (D) mid-foot only (n = 42 sites). The area under the ROC curves (A), (C) and (D) were large and significantly different from a value of 0.5 (2 (402 kPa) was the most reliable prediction method of DFU history at a specific plantar site and was significantly better than the established > 6 kg/cm2 threshold . At midfoot alone (p = 0.026) sensitivity was 80% and specificity was 65%. Conversely, however, the ROC curve for PPP at the great toe site was not significantly different from 0.5 and had no diagnostic ability.e of 0.5 , and curhreshold . The 4.1tar site A, with aoot only C, the diot alone D, sensit2 (>402 kPa), with optimal sensitivity for predicting these ‘high-risk’ plantar sites. The methodology for this, using a single-use carbon footprint mat, could be adopted very easily into the clinical setting.This study has demonstrated, for the first time, a strong, site-specific relationship between ‘elevated’ barefoot PPP and DFU history for ‘high-risk’ patients. Furthermore, we found surprisingly low numbers of discrete areas of high pressure across the plantar surface of ‘high-risk’ feet , despite the general current assumption that ‘high-risk’ feet are at risk of re-ulceration across the plantar surface because of generally higher PPPs. We have also determined a critical barefoot peak plantar pressure threshold value of >4.1 kg/cm2 ) were six times more likely to have a history of DFU than sites with barefoot PPP below this threshold; (b) however, there was no relationship between DFU sites and ‘high’ barefoot PPP (>6 kg/cm2) recorded more generally across the plantar surface of the foot; (c) ‘high’ barefoot PPP (>6 kg/cm2) sites were infrequent across the whole plantar surface, averaging just one ‘high’ PPP site per foot; (d) ROC curve coordinates showed that PPP critical threshold of 4.1 kg/cm2 (402 kPa) was the most reliable prediction method of DFU history at any plantar site, and significantly better than the established >6 kg/cm2 threshold; (e) sensitivity (the ability to correctly identify the DFU site) of the 4.1 kg/cm2 threshold was highest at the metatarsal heads and midfoot sites (73%) and peaked at 100% at midfoot alone . All of this evidence indicates that there is a very strong relationship between barefoot PPP and DFU history occurring at discrete plantar sites per foot. These sites are very easily identifiable in the clinical setting using a single-use carbon footprint mat, with a highly sensitive threshold for capturing the DFU risk at the metatarsal heads and midfoot regions, enabling a simple, cost-effective, site-specific, targeted approach for off-loading foot management.Our evidence was (a) plantar sites with established ‘high’ barefoot PPP ) as ‘high-risk’ for barefoot walking [2 ) [The very strong association of DFU history when PPP is above the 4.1 kg/cmpressure . Althougpressure , we showkg/cm2)) .2 range for PressureStat™. Of note, their model examining ‘all DFU recurrences per foot’ showed that barefoot PPP at ‘plantar foot distal to the heel’ was not independently significant in the multivariate model; conversely, PPP was independently significant in their site-specific model. This is important data, highlighting a site-specific relationship between PPP and DFU; unfortunately, information regarding actual locations on the plantar foot was not included in their study. Elsewhere, mean PPP at the ‘forefoot’ during barefoot walking in patients with previous DFU (mean = 566 kPa (range =107–1192 kPa) [2) in diabetic patients with neuropathy has previously been considered as a ‘region of interest’ [2 provides optimal sensitivity and specificity for identifying risk of DFU site validate this proposed cut-off value.The barefoot PPP range for our cohort is highly comparable to barefoot PPP ranges observed in similar populations ,16,29. WThe above studies, in which in-shoe plantar pressures are reduced compared to equivalent barefoot pressures (up to a 4-fold reduction) ,16,29, sThe number of discrete areas of high pressure across the plantar surface of ‘high-risk’ feet were scarce , despite the general current assumption that ‘high-risk’ feet are at risk of re-ulceration across the plantar surface because of generally higher PPPs. This novel finding has been enabled by the ability to capture an instant ‘snapshot’ plantar image of all barefoot PPPs using the carbon mat PressureStat™ system.2) for identifying new DFU. The model indicated that any plantar sites with PPP > 9 kg/cm2 were 60-fold more likely to develop a new DFU than sites with PPP below this critical threshold (p < 0.0001); however, because of the low number of events, the effect estimate was very large, and the model was considered unstable. Predictive analyses of this kind may prove to be successful with a larger participant sample size.The PressureStat™ system used for our analyses is an inexpensive, validated, highly sensitive, quick and simple alternative device for measuring barefoot PPP foot pressures in the clinical setting , contrasWe recommend the use of this inexpensive (approximately $2 per footprint), robust screening tool in the annual review clinic, ideally at the point when patients’ shoes and socks have already been removed for foot examination and neuropathy screening, to capture evidence of high-risk barefoot plantar pressures. The carbon footprint provides an immediate visual image for the patient and physician to view and discuss together, acting as an educational tool for the patient and enabling the physician to immediately target specific, problem plantar areas for off-loading therapy. Furthermore, as we have shown for the first time, areas of high pressure on the ‘at-risk’ foot are very scarce; we suggest that this may have implications for how high PPPs should be investigated in future clinical trials.2 to identify specific plantar sites of previous DFU occurrence, using an inexpensive, simple carbon footprint screening tool. We can recommend the use of this threshold value for ‘high-risk’ patients in daily clinical practice  to identify which individual plantar sites are at higher risk of DFU recurrence, enabling immediate, targeted DFU prevention strategies.To conclude, we have determined and validated a robust, highly sensitive, critical plantar pressure threshold value of >4.1 kg/cm