16 overshot ct brands

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It appears that once evolution set jerboa bones on the path toward fusing together, they overshot the optimum amount of fusing—the structure that best dissipated stresses from jumping and landing—to become fully bonded.

"We wanted to explore why we are seeing these fused bones in only larger jerboas," said Carla Nathaly Villacís Núñez, U-M doctoral candidate in mechanical engineering and first author of the study in Proceedings of the Royal Society B.

To study the bone performance across species, the researchers performed micro-CT scans of museum specimens and built 3D models of the jerboa metatarsals in software, then scaled them to equal sizes and stress tested them as they hit, flexed and hopped off of a surface.

The smaller jerboas have three separate metatarsal bones, which are capable of supporting the rodent"s small stature even if used for high-impact jumping. The more recent, larger jerboa species have completely fused these three bones into one. The intermediate weight species have something in-between: a metatarsal with interior remnants of bone where it has partially fused together, like a bundle of sticks.

"Through similar analysis, we could simulate how the foot bones of extinct human ancestors might have experienced stresses during walking, running or other locomotion."

An additional author is Kimberly Cooper, professor of developmental biology at the University of California, San Diego, who formulated the idea for the project with Moore during a separate study tracing the evolution and development of metatarsal fusion in jerboas. Cooper"s expertise was key to understanding the evolutionary implications of the findings.

Partnerships with powerhouse internet celebs such as Jeffree Star and James Charles helped revenue top $400 million in 2019, according to a company presentation from December 2021 reviewed by Bloomberg. But Morphe severed ties with them after Star was accused of using racist language in 2020 and allegations of sexual misconduct plagued Charles in 2021.

In October, Women’s Wear Daily reported the company was considering bankruptcy. As part of a buyout by private equity firm General Atlantic in 2019, the company took on $650 million in debt.

Seeking to diversify away from influencers, Morphe rebranded itself as Forma, an incubator focused on acquiring and building out smaller lines. But the company’s strategy floundered. In the document reviewed by Bloomberg, Forma said that in 2022 it planned to pause development and investment in new products for several of its brands.

But four years later, that Morphe store is gone after the company, according to court records, was evicted for owing more than $300,000 in unpaid rent.

(Update adds company statements in second, ninth and 16th paragraphs. An earlier version of this story was updated with details throughout on company’s results and strategy.)

Post will pay with $700 million in cash and about 5.4 million of its shares, according to a statement. J.M. Smucker estimates the brands, which also consist of 9Lives, Nature’s Recipe, Gravy Train and a private-label business, will generate about $1.5 billion in sales the fiscal year that concludes April 30. The transaction is expected to close in the quarter that ends the same date.

In a separate statement, Post Holdings estimated the sales for the fiscal year would be about $1.4 billion. Post will issue new shares to J.M. Smucker for the transaction, while the other portion will be funded with cash on hand and proceeds from a revolving-credit facility.

“This is bold in magnitude, as we had expected smaller divestitures over time, but it’s unsurprising. Dog food is the biggest category in the pet segment, but Smucker isn’t a leader, trailing Nestlé, General Mills and Mars significantly.”

The transaction includes manufacturing and distribution facilities in Bloomsburg, Pennsylvania, as well as plants in Meadville, Pennsylvania, and Lawrence, Kansas.

(Updates with Post statement in third paragraph, shares in final paragraph. A previous version corrected the name of a pet-food brand in the first paragraph.)

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Soon after the introduction of the first commercial instrument in 1987 (Perkin-Elmer Cetus DNA thermal cycler), other suppliers offered similar devices. Today the thermocycler market is dominated by a few major manufacturers. Thermocyclers of the previous generations differ widely from the contemporary models. Developments of heating/cooling systems (circulating water versus Peltier technology), internal temperature control options (block control versus in-sample probe control and calculated temperature control), and evaporation control concepts (oil overlay versus heated lid) have been changing the technical architecture of the cyclers completely (15, 16). Accurate thermocyclers are a prerequisite for advanced applications such as cycling sequencing, in situ PCR, and real-time quantitative PCR in sample formats of up to 384 block positions. All these techniques rely on (i) an efficient heating and cooling system, (ii) an efficient heat transfer from the block to the sample liquid, and (iii) a sophisticated steering algorithm which allows the reproducibility of a given set temperature profile as stringent as possible.

The performance studies on thermal cyclers published so far lack relevance (5, 8, 14, 21). On the one hand, the studies refer to the older generation of thermocyclers, or processors from only one or two manufacturers were tested (5, 8, 21). Interlaboratory trials, on the other hand, compared only the amplification efficiency of used cyclers of various makes and models (16). The physical functionality of the machines was not determined.

This study focused on brand-new cyclers of the last generation. By embedding a fast-response microthermocouple inside the PCR tube, it was possible to determine the temperature uniformity within the sample block and to study the thermodynamic process from the block via the tube to the PCR sample in more detail. If available, the calculated temperature control mode, which is known to bring the samples more easily to the programmed temperatures (16), and each maximum heating rate had been chosen. By performing a PCR assay (PCR ListStand), the amplification efficiency of each model was determined.

Both physical testing using a static protocol and PCR testing allowed us to distinguish accurate (A, B, D, and E) from less-accurate (C and F) cyclers. This was also shown using a dynamic three-level protocol in a recent study (19). The most obvious irregularities of the machines were premature timing, followed by under- and overshooting and spatial irregularities of heat transfer. These results indicated that a difference in the cycler performance is not only a matter of abrasion after years of use, as suggested by previous studies (7, 16). It is an outcome of the variable technical architecture of the cyclers, which differs in the number, size, and quality of the Peltier elements, the location and number of the thermosensors steering the Peltier elements, and the underlying algorithm. A difference in the ITT from the block temperature might also result from poor heat transfer from the block to the PCR sample. In particular, the models which were notable for high heating and cooling rates seemed to be “susceptible” to premature timing.

The short denaturation step of PCR ListStand was seen to be the critical point. The cyclers C and F failed to amplify the target DNA. The physical testing of cyclers C and F showed a significant tendency for undershooting and premature timing. Usually the optimum denaturation temperature is between 91 and 94°C (11). Referring to the PCR ListStand protocol (94°C/15 s, 68°C/30 s, and 72°C/60 s), cylers C and F performed the effective temperature level only for 5 s (33%) or 7 s (47%), respectively (data not shown). Consequently, we concluded that the lack of amplification of cyclers C and F was most likely caused by the insufficient melting of the template DNA. This hypothesis could be proved by modifying the original denaturation step by increasing the temperature (PCR Listmod1), time (PCR Listmod2) or both (PCR Listmod3). The amplification efficiencies of cyclers C and F could be improved significantly. The best results could be obtained by expanding the denaturation time from 15 to 60 s (PCR Listmod2). This was seen as a proof that premature timing was the main reason for the lack of amplification of cyclers C and F.

By increasing and expanding the denaturation step up to 96°C and 60 s (PCR Listmod3), the tendency of cycler E for overshooting became most evident. Its amplification efficiency decreased dramatically, perhaps due to polymerase inactivation or deoxynucleoside triphosphate breakdowns (3, 22, 23, 24).

Each PCR user should have an effective and simple tool to test the performance of in-house cyclers. Several cycler companies developed end-user-friendly temperature validation systems, such as the Temperature Verification system (Applied Biosystems, Foster City, CA) or the Temperature Validation system (Eppendorf Netheler-Hinz GmbH, Hamburg, Germany). These single-sensor test systems allow static temperature measurement only within the block wells. Our study could show that static temperature procedures, on condition that they are done in-tube, are appropriate to detect some of the main weak points of thermocyclers (19). Another approach could be a cycler performance test using a standardized temperature-sensitive PCR system, such as SureCycle (Congen, Berlin, Germany), which was recently developed and introduced into the market (9). Cycler performance testing should regularly be carried out and become a part of any accreditation of an expert or an end-user lab devoted to PCR diagnostics. New PCR strategies should demonstrate the robustness of a temperature protocol, and validation of PCR protocols must include the testing of a PCR assay on several thermocyclers.

Poor understanding of the pharmacokinetics of target-controlled infusion (TCI)/TIVA practice has contributed to accidental anaesthetic awareness as reported by NAP5.

All models incorporate assumptions and elements of inaccuracy in the prediction of plasma and effect-site targets. However, inter-individual variability in pharmacodynamic response represents a more challenging aspect of using TIVA.

After an i.v. bolus, the plasma concentration of a typical drug follows an exponential decline in three distinct phases (Fig. 1). These observations are explained by distribution of drug between a central compartment (V1, principally plasma) and two compartments which equilibrate rapidly (V2, well-perfused tissue like muscle) and slowly (V3, mainly fatty tissue) (Fig. 2). Mathematical analysis allows the compartment volumes and rate constants for drug transfer between them to be calculated.

Plasma concentration vs time curve demonstrating tri-exponential decline after a bolus injection. In conventional pharmacokinetic terminology, these are phases A–C. The plasma concentration at time t(Ct) may be derived from C(t)=Ae−αt+Be−βt+Ce−γt⁠, where t is time since i.v. bolus. C, concentration after a bolus dose. A–C represent the phase coefficients which sum to the plasma concentration after an i.v. bolus. α, β, and γ represent phase rate constants. e, natural logarithm.

Three-compartment model showing the various compartments and their associated rate constants. V1−3 represents the compartment volumes. K12 represents the rate constant between V1 and V2, K21 between V2 and V1, etc. K10 represents the rate constant for drug elimination from the central compartment. ke0 is the rate constant for equilibration between plasma and effect-site concentrations.

Adequacy of TIVA depends on the maintenance of brain propofol and remifentanil concentrations which are clinically appropriate and in equilibrium with levels in the plasma. The best way to achieve this state is by TCI from dedicated pharmacokinetic pumps. These devices solve the complex equations which describe the distribution of agents between compartments and allow for rapid adjustments in targets to achieve the desired clinical effect. Manual infusion regimes are prone to errors in the calculation and implementation of the required changes in infusion rate as reported by NAP5.

A bolus/elimination/transfer (BET) principle is used to approximate a constant plasma level of drug (however, the algorithms in pharmacokinetic pumps use more exacting analytical solutions). Once compartment V1 is filled by the bolus, the subsequent infusion rate compensates for rapid and slow transfer of drug to V2 and V3, and drug elimination from V1 as described by the rate constant K10 (rate constant for drug elimination from the central compartment in a pharmacokinetic model). When the three compartments reach steady-state concentration (>20 h for propofol), the infusion rate slows to match elimination only. Without an appropriate bolus, a constant propofol infusion at 10 mg kg−1 h−1 requires 40–90 min (dependent upon which kinetic model is used for calculation) to achieve a clinically useful plasma concentration of 4 μg ml−1 in an 85 kg adult male. It is likely that an inadequate clinical effect would be observed in the interim as was reported by NAP5.

The differences in published models for propofol and remifentanil result from methodological aspects and limitations of the original studies. Relatively few of these solutions are implemented in commercial infusion devices (Table 2). Currently, there is no evidence to support the use of one model in preference to another and all have proved reliable in clinical practice. All have similar performance in terms of the accuracy and stability of predicted plasma (Cp) and effect-site (Ce) concentrations.

Comparison of the pharmacokinetic parameters for the main TCI models implemented in commercial infusion devices. V1, central compartment; V2, rapidly equilibrating compartment; V3, slowly equilibrating compartment; K10, rate constant for drug elimination from the central compartment in a pharmacokinetic model; Kxy and Kyx, rate constants for drug transfer from compartment x to compartment y or the reverse direction; LBM, lean body mass

Comparison of the pharmacokinetic parameters for the main TCI models implemented in commercial infusion devices. V1, central compartment; V2, rapidly equilibrating compartment; V3, slowly equilibrating compartment; K10, rate constant for drug elimination from the central compartment in a pharmacokinetic model; Kxy and Kyx, rate constants for drug transfer from compartment x to compartment y or the reverse direction; LBM, lean body mass

Comparison of propofol concentrations predicted for a 40-yr-old male, 178 cm tall, and weighing 85 kg by the Marsh (upper panels) and Schnider (lower panels) models using Tivatrainer 9 software (www.eurosiva.eu). Left-hand panels show plasma targeting (Cpt) mode; right-hand panels show effect-site targeting (Cet). The target was set at 4 μg ml−1 and all diagrams have the same time scale in minutes on the x-axis. Note the major difference in plasma concentration predicted in Cet modes—this is largely due to the difference in the volume of the central compartment V1 assumed by each model. Differences in the time to equilibration of the plasma and effect-site concentrations for the Marsh model are due to the different ke0 utilised in each calculation. The ke0s used in the effect-site models are based on a TTPE of 1.6 min after the bolus dose. Red line, plasma concentration; orange line, chosen target level; green line, effect-site concentration; vertical white lines represent the infusion rate of TCI pump.

The Marsh model ignores age and scales the volumes of V1−3 linearly to patient weight. An identical bolus dose is administered to all patients of a given body mass for any chosen Cpt. This delivery contrasts with non-TIVA practice where the anaesthetist usually adjusts dosage for patient age and likely pharmacodynamic response. Age is input to the TCI pump only to ensure that the patient is ≥16 yr and that the use of this model is appropriate. For less robust patients, it is better to start the pump at a lower Cpt and increase the target incrementally until a desired clinical effect is obtained.

Although the Schnider model adjusts some of the pharmacokinetic parameters for age (Table 2), this does not necessarily constrain the patient"s pharmacodynamic response. A sex-specific lean body mass (LBM) is calculated and used to adjust the elimination rate constant K10. Because a small fixed volume for V1 is used, lower doses of propofol are required to achieve a given Cpt compared with Marsh (Table 3). In many instances, this bolus is inappropriately small and results in an inadequate clinical effect. Consequently, the Schnider model can only be recommended for use in effect-site targeting mode (see below) as larger bolus doses are utilised.

Comparison of the dose of propofol administered to a 40-yr-old male, 178 cm tall, and 85 kg in weight when a 4 μg ml−1 target concentration is set. The table shows the initial bolus dose, the time to equilibration of plasma and effect-site concentrations, and the cumulative doses at two time points. Time to equilibration is equivalent to TTPE with effect-site targeting. Data derived from Tivatrainer 9 software (www.eurosiva.eu). Greyed areas show non-applicable data

Comparison of the dose of propofol administered to a 40-yr-old male, 178 cm tall, and 85 kg in weight when a 4 μg ml−1 target concentration is set. The table shows the initial bolus dose, the time to equilibration of plasma and effect-site concentrations, and the cumulative doses at two time points. Time to equilibration is equivalent to TTPE with effect-site targeting. Data derived from Tivatrainer 9 software (www.eurosiva.eu). Greyed areas show non-applicable data

Small differences between the Paedfusor and Kataria paediatric models are shown in Table 2. Both use weight as the key patient characteristic for scaling the volumes of V1−3. The Kataria model is validated for use in patients aged 3–16 yr with a minimum weight of 15 kg. The Paedfusor model is a variant of the Marsh kinetics for patients 1–16 yr of age, and also uses weight to calculate the elimination constant K10. It features non-linear scaling of V1 volume as age exceeds 12 yr. Extrapolation of these models to patients outside of the described patient characteristics is not recommended due to increased pharmacokinetic differences, but is commonly practised.

A recently described allometric scaling model promises improved utility in propofol administration.V2 and V3 which in turn are the primary determinants of their associated rate constants, not absolute body mass. This complex analysis allows the model to be used for patients aged 3 months to 88 yr and weighing 5–160 kg, but needs further clinical validation before it becomes commercially available.

The Minto model for remifentanil is popular because it is applicable to a wide range of patient characteristics. Age is used for calculation of pharmacokinetic parameters (Table 2) but in common with the Schnider model, this adjustment does not influence pharmacodynamic response. A sex-specific LBM is calculated and used to fine tune some of the parameters to the patient.

Clinicians regularly but unintentionally use effect-site targeting in non-TIVA practice to rapidly achieve unconsciousness. The high plasma concentration generated by a large bolus of propofol causes fast diffusion of drug into the brain and rapid onset of the desired effect. However, propofol diffusion continues until the brain concentration has equilibrated with the diminishing plasma level (Fig. 3, right-hand panels). This occurs 1.6–3.9 min after injection irrespective of the size of the bolus dose

However, brain propofol concentrations cannot be measured in vivo and the rate constant required for direct calculation of plasma overshoot is unknowable. Instead, drug concentration in a theoretical surrogate called the effect-site is used for mathematical analysis of effect and prediction of plasma overshoot.V1 and causes little perturbation in plasma concentration at equilibrium. A rate constant called ke0 (Fig. 2) describes equilibration of effect-site concentration with plasma propofol levels but has to be derived indirectly in experimental studies.

A measure of dynamic anaesthetic effect, typically a processed EEG signal, is recorded simultaneously with measured plasma propofol concentrations in volunteer subjects. A numeric value for ke0 can then be derived to match the timing of the calculated peak Ce to the observed maximum EEG effect. This ke0 is linked to rate of decay of drug concentration in V1 and hence to the specific pharmacokinetic model used to administer the agent. Once established, ke0 allows manipulation of plasma overshoot to achieve a particular Cet.

For any given pharmacokinetic model, a large numeric value of ke0 will predict a more rapid increase in Ce and allow a smaller initial bolus dose to be given. Similarly, the decline in Ce to a level representing recovery from anaesthesia will be predicted to occur more quickly.

Effect-site targeting is the only approach recommended for the Schnider model as larger bolus doses are required to achieve plasma overshoot (Table 3). Because this model incorporates more patient characteristics, it has been recommended for use in the elderly and less robust patient. However, it is always better to start at a low Cet in frail individuals and increase the target incrementally until the desired response is obtained.

The original ‘Diprifusor’ Marsh Cpt model did not have a ke0 and could not be used in the Cet mode. Subsequently, a ke0 was assigned to allow calculation of Ce for information only, and the selected value predicts a TTPE of 3.9–4.5 min after a typical 2–3 mg kg−1 bolus. This timing may seem lengthy, but the prediction of Ce by this model has been validated in a patient study.ke0 for enabling the Marsh model in the Cet mode, and a variety of solutions have been published. A method using a TTPE of 1.6 min to derive ke0 has been implemented in some commercial TCI devices as the ‘Modified Marsh’ model.

For both Marsh and Schnider models, larger bolus doses of propofol are used in the Cet mode at any given numeric target compared with the same model in the Cpt mode. Marsh always administers a larger bolus dose than Schnider in either mode principally due to the significant difference in the volume of V1 used in calculations. However, the absolute mass of agent may seem small compared with that used in non-TIVA practice (Table 3) where unwanted effect overshoot is common. The propofol TCI models described above prove highly effective in combination with remifentanil TCI.

The Minto model for remifentanil can be used in the Cet mode, but the ke0 used is derived from studies of EEG parameters as a measure of effect. It must be remembered that an EEG parameter does not necessarily equate with the onset of analgesic action. The increased plasma remifentanil concentrations required in the Cet mode can be associated with a higher likelihood of chest wall rigidity and severe bradycardia via non-vagal mechanisms, so an incremental approach to remifentanil Cet may be a reasonable technique.

Currently, there is no ‘best’ TCI model for propofol. The clinician should become familiar with the model which matches the patient characteristics of their usual patient population. All pharmacokinetic models have inherent assumptions which generate elements of inaccuracy in prediction. However, inter-individual variability in pharmacodynamic response represents a more challenging aspect of using TIVA. Close clinical monitoring of the patient remains an important part of the anaesthetist"s role.

Bispectral index monitoring prevents awareness during total intravenous anesthesia: a prospective, randomized, double-blinded, multi-center controlled trial.

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