Category: Uncategorized

An imaging difference that becomes less apparent during early infancy is encouraging evidence about that measured trajectory. It is not proof that every developmental consequence has resolved. Chang and colleagues’ 2016 study of prenatal methamphetamine and tobacco exposure illustrates why “normalization” must remain tied to the brain region, measurement and follow-up period actually examined.

How many infants contributed to the imaging analysis?

The investigators screened 752 mother–infant pairs and clinically evaluated 139 infants: 36 in the methamphetamine/tobacco group, 32 in the tobacco group and 71 unexposed controls. The prospective observational study recruited between 2008 and 2015 and scheduled assessments approximately one week, one to two months and two to four months after birth.

The final diffusion-tensor-imaging analysis was smaller: 223 usable scans from 109 infants, comprising 32 methamphetamine/tobacco-exposed, 30 tobacco-exposed and 47 unexposed infants. Of 325 attempted scans, 102 were excluded because of sleep, movement or scanning-parameter issues. Repeated scans are observations within infants, not additional independent infants. Quoting 139 as the imaging denominator would overstate that analysis.

Was this a methamphetamine-only exposure experiment?

No. The groups reflected naturally occurring maternal substance use rather than randomly assigned prenatal exposure. In the clinically evaluated methamphetamine group, 35 of 36 mothers reported tobacco use. That group also reported more cigarettes overall than the tobacco-only group, as well as differences in alcohol and marijuana exposure and social characteristics.

Maternal methamphetamine amounts varied widely by self-report: the reported median total during pregnancy was 47 g, with a range of 0.15–388 g. These are retrospective estimates across pregnancy, not standardized administered doses, measured fetal concentrations or a validated dose–injury relationship. The study did not isolate methamphetamine from otherwise identical tobacco exposure.

What did the scans measure?

Diffusion tensor imaging estimates properties of water diffusion. The researchers examined fractional anisotropy and axial, radial and mean diffusivity in selected white-matter tracts and subcortical regions. These imaging measures can inform hypotheses about maturation and tissue organization. They are not direct histological measurements of myelin, neuron counts or individual cognitive ability.

The infants were scanned during natural sleep without sedation. Age was important: baseline postmenstrual age differed across groups, and the models accounted for developmental timing. Postmenstrual age incorporates gestational age and time since birth; it should not be confused with the number of months since delivery.

Which trajectories appeared to converge?

The authors described lower fractional anisotropy and higher diffusivity early in some corona-radiata measurements among methamphetamine/tobacco-exposed boys, with later convergence during the first three to four months. Active muscle-tone and total neurological-examination scores also showed early differences followed by apparent normalization.

These findings concerned particular endpoints over a short developmental period. They did not show that every tract behaved identically, that girls shared the same trajectory, or that a later school-age outcome was normal. A group curve approaching another group curve is not the same as demonstrating recovery in every individual infant.

Why must nominal and corrected findings be distinguished?

The methods specified a Bonferroni threshold of p<0.005 for ten regional comparisons per imaging metric, while describing p<0.05 findings as trends. Some superior-corona-radiata interaction results met the stricter threshold, including a reported group-by-age-by-sex p-value of 0.002. Other reported regional findings had p-values such as 0.01, 0.02 or 0.04.

A summary that calls every result equally established would erase the paper’s stated multiplicity rule. The anterior-corona-radiata findings in exposed girls, for example, should retain their nominal statistical status rather than being promoted into definitive proof of permanent injury. Null results in other sex-and-region comparisons must also remain visible.

What else limits a causal or prognostic interpretation?

Not every infant completed every follow-up, potentially influencing the later portions of the modeled curves. The study primarily included healthy infants and excluded important maternal conditions, including clinical depression; the authors cautioned against generalizing to infants whose mothers also had depression during or after pregnancy. Unmeasured prenatal stress, social circumstances and other exposures remained potential contributors.

The proposed biological explanations, including delayed myelination and epigenetic effects, were interpretations of the imaging and prior research. The human study did not directly demonstrate those molecular mechanisms. Nor did a tobacco comparator remove every difference between exposure groups.

How should “normalization” be explained to a client?

Describe early convergence as a bounded observation: which metric, which tract, which subgroup and through what age. Avoid turning it into either a guarantee of permanent recovery or a claim that every exposed child has lasting injury. Individual developmental assessment and longer follow-up answer questions that an exposure label and an early group MRI pattern cannot resolve.

Scientific source

Chang L, Oishi K, Skranes J, et al. Sex-specific alterations of white matter developmental trajectories in infants with prenatal exposure to methamphetamine and tobacco. JAMA Psychiatry. 2016;73(12):1217–1227. doi:10.1001/jamapsychiatry.2016.2794. Historical prospective observational human study; full text recovered for the paper identified in the supplied research collection.

Norfentanyl should not be treated as pharmacologically interchangeable with fentanyl merely because both are detected in a toxicology investigation. A 1986 experimental study found very different activity in an isolated-tissue opioid bioassay. Those results support distinguishing the compounds, but they do not supply a human fatal concentration, a blood-concentration conversion or a numerical measure of impairment.

What the researchers were trying to explain

Schneider and Brune investigated whether fentanyl metabolites could help explain delayed respiratory depression after anesthesia, sometimes called fentanyl rebound. Their work combined an isolated guinea-pig ileum bioassay with a rat distribution experiment. It did not study human autopsies or compare concentrations in people who died with concentrations in survivors.

The biological assay measured how strongly compounds inhibited electrically induced contraction of isolated ileum segments. Naloxone was used to check that the inhibitory response reflected opioid activity. The investigators used this model because direct measurement of respiratory depression was difficult. An intestinal contraction endpoint is nevertheless not a direct measurement of human breathing or consciousness.

The reported activity differences

The paper’s Table 1 reported these concentrations producing half-maximal inhibition, or IC50 values, in the guinea-pig ileum assay:

Compound	Reported IC50
Fentanyl	4 nM
Morphine	50 nM
Pethidine	1,300 nM
Norfentanyl	3,800 nM
Despropionyl-fentanyl	12,000 nM
4-Anilinopiperidine	120,000 nM

A larger IC50 here means that more compound was required to produce the specified inhibition in that preparation. Norfentanyl’s activity was therefore much lower than fentanyl’s in this assay. The norfentanyl concentration–response series had four experiments; other metabolite series had different counts. The study was not one uniformly sized experiment for every compound.

The researchers also tested hydroxylated and hypothetical metabolites. One synthetic hydroxylated compound produced a differently shaped response curve, limiting simple potency comparisons. A hypothetical N-methyl-norfentanyl compound showed activity in the bioassay but was not detected in the rat specimens. A proposed metabolite’s laboratory activity does not establish that it occurs at a relevant concentration in a person.

The rat experiment tested a different question

Female Wistar rats weighing approximately 200 ±10 g received radiolabeled fentanyl through a femoral venous catheter over nine minutes. The two label preparations delivered approximately 5.96 or 6 µg per 100 g body weight. Animals were sampled at 0, 10, 30, 90 and 270 minutes after the infusion ended. Organs were removed immediately and stored at −30°C.

These intervals describe time after drug administration in an antemortem distribution experiment. They are not intervals during which a human body decomposed after death. The article did not provide a clearly consolidated total animal count for the full distribution series.

High-performance thin-layer chromatography, radioactive scanning and scintillation counting separated and measured labeled components. Recovery after extraction and separation was reported as 80%–99% of organ radioactivity; repeated analysis of an organ sample five times gave a standard deviation no greater than 8%. Some proposed structures remained uncertain because reference material was unavailable. These measurements were not a modern validated human postmortem blood assay.

The negative finding is important too

The distribution experiment did not show secondary accumulation of fentanyl or its active metabolites in the brain sufficient to explain rebound after a single dose. That result did not rule out every explanation for delayed respiratory depression. The authors specifically retained questions about repeated dosing and interactions with other anesthetic or tranquilizing drugs.

It would therefore be inaccurate to cite the paper as proof that a metabolite accumulated in brain and caused delayed death. It would also be inaccurate to turn its single-dose rat result into proof that delayed toxicity cannot occur under other conditions.

Applying the distinction to a postmortem report

A forensic report should retain separate identities and measurements for parent drug and metabolites. A norfentanyl finding is not an equal concentration of fentanyl, and the nanomolar bioassay values above are not blood thresholds in ng/mL or µg/L. Translating one into the other would require evidence this study did not provide.

The study explains why chemical detection and biological effect are separate questions. It does not establish an ingested dose, impairment at a particular time or cause of death. For a related analytical distinction, see why fentanyl radioactivity does not necessarily represent unchanged parent drug. The additional limits of postmortem specimen ratios concern yet another question: where the measured compound was collected.

Primary source

Schneider E, Brune K. Opioid activity and distribution of fentanyl metabolites. Naunyn-Schmiedeberg’s Archives of Pharmacology. 1986;334:267–274. https://doi.org/10.1007/BF00508781.

An opiate screen can miss fentanyl when fentanyl is outside the assay’s target scope. The 2016 New Haven outbreak provides a concrete example: the urine immunoassay used in the investigation could not detect fentanyl or its analogs, while later mass-spectrometric testing and medical examiner testing identified fentanyl exposure. That is a limitation of the particular screening approach, not evidence that every current opioid assay has the same scope.

Twelve cases did not mean twelve identical toxicology workups

Tomassoni and colleagues described 12 people brought to Yale New Haven Hospital during an outbreak on June 23, 2016, after a white powder had been sold as cocaine. The route was unknown but presumed to be intranasal in most cases. Nine patients were admitted; four received intensive care. Two arrived dead, and another died three days later in hospital.

The case definition combined clinical opioid toxicity and response to naloxone with either laboratory evidence of fentanyl or its metabolites, or a direct association with a laboratory-confirmed exposure. This was an outbreak investigation, not a blinded diagnostic-accuracy study of an opiate immunoassay.

Qualitative urine immunoassays were performed in nine patients. The authors explicitly stated that those tests could not detect fentanyl and its analogs. Eight of the nine urine screens were cocaine-positive. These cocaine findings were a separate part of the panel and did not show that fentanyl had been tested and excluded.

What later testing added

Serum and urine were subsequently investigated at the University of California, San Francisco using liquid chromatography–high-resolution mass spectrometry. The report described screening for 215 common drugs and metabolites, followed by additional searching for 7,038 novel drugs and metabolites. Fentanyl, cocaine, benzoylecgonine and levamisole were quantified; additional compounds were reported qualitatively.

Nine hospitalized patients had fentanyl detected in blood collected during hospitalization. One associated patient left before the outbreak was fully recognized and did not receive confirmatory toxicology testing. The medical examiner separately tested postmortem specimens from the two people who died before arrival. These different pathways should remain visible when reading the total of 12 cases.

The article did not provide a complete matrix-specific validation dataset for the outbreak measurements, including all detection limits, quantitation limits and uncertainty estimates. A large searchable library is not equivalent to demonstrated uniform sensitivity for every listed compound.

Hospital serum and postmortem specimens answer different questions

Fentanyl concentrations in the hospitalized group were 0.5–9.5 ng/mL. The two deaths before arrival had reported postmortem concentrations of 11 and 13 ng/mL. The postmortem specimens were identified in a table footnote as medical examiner specimens; the report did not establish their anatomical collection sites or precise death-to-collection intervals.

These values are not paired before-and-after measurements from the same people. They cannot quantify a redistribution factor or establish a concentration separating survival from death. The patient with the 9.5-ng/mL hospital result later died, further emphasizing the importance of when a specimen was obtained and what subsequent outcome is being compared.

Norfentanyl was reported in the serum of nine patients but not in the two early deaths’ postmortem testing. The authors proposed rapid death before substantial metabolism as an explanation. They did not validate absent norfentanyl as a precise exposure clock. Sampling, analytical scope and reporting limits must be considered before turning a metabolite pattern into a timing conclusion.

Evidence about the powder was a separate specimen

A 32-mg sample of illicit material collected by law enforcement contained 6.6% ±0.8% fentanyl by weight, with trace cocaine and an inert adulterant. This supported the outbreak investigation, but it did not measure the amount consumed by any patient. Product composition, a blood concentration and the dose taken are different measurements.

The two postmortem investigations identified fentanyl as a cause of death in their case context. That conclusion was not derived solely from the absence of a positive opiate screen. Clinical findings, circumstances and targeted toxicological evidence supplied different pieces of the investigation.

What to establish when reviewing a negative result

The central question is whether the actual assay could detect the substance at issue in the submitted matrix and at its reporting threshold. The label “opiates” alone does not answer it. A report should distinguish the initial class screen, later analyte identification, quantitative results and postmortem interpretation.

Our article on negative autopsy drug screens discusses broader coverage limitations. For the separate problem of comparing living and deceased groups, see postmortem and antemortem fentanyl comparisons.

Primary source

Tomassoni AJ, Hawk KF, Jubanyik K, et al. Multiple Fentanyl Overdoses—New Haven, Connecticut, June 23, 2016. MMWR Morbidity and Mortality Weekly Report. 2017;66:107–111. https://doi.org/10.15585/mm6604a4.

Accurate mass alone cannot distinguish drugs that share the same molecular formula and exact molecular-ion mass. A postmortem blood method developed by Rosano and colleagues separated morphine from hydromorphone and codeine from hydrocodone chromatographically before quantitation. Its good overall performance depended on the complete analytical method, including separation, internal standards and identification criteria.

The study behind the distinction

The 2014 study developed a UPLC–MS^E/time-of-flight method for 16 drugs and metabolites in postmortem blood and compared it with a routine UPLC–MS/MS method using nominal-mass detection. The panel included opioids and their metabolites, cocaine-related compounds, citalopram, dextromethorphan and diphenhydramine. It was a defined quantitative panel, not validation for every compound that might appear in a general drug screen.

For the casework comparison, discarded extracts from 159 medical examiner cases were de-identified and reanalyzed. The cases had initially screened positive for relevant analytes and undergone routine quantitative confirmation. Thus, the comparison used previously prepared extracts rather than two independent collections of blood. The paper did not provide a uniform anatomical collection site, death-to-collection interval or decomposition classification for this case series.

Two pairs that exact mass cannot resolve

The reported molecular ions for morphine and hydromorphone were both m/z 286.1443. Codeine and hydrocodone both had a reported molecular ion of m/z 300.1600. A narrower mass window cannot distinguish the members of either pair on that molecular ion alone.

The investigators optimized chromatographic conditions to separate these pairs because they also share some fragment-ion masses. For high-resolution quantitation, molecular-ion data were extracted within ±5 parts per million of exact mass. Identification incorporated retention time within 0.3 minutes of reference analysis, molecular and isotope information, and available diagnostic fragments. Low collision energy was 6 eV; the higher-energy acquisition ramped from 10 to 40 eV.

The implication for reviewing a report is specific: “high resolution” describes a useful measurement capability, but does not identify which combination of evidence distinguished the reported analyte from an isomer or interference.

What quantitative validation demonstrated

The validated calibration range was 25–3,000 ng/mL for all 16 analytes, with calibration R² above 0.99. The detection threshold was administratively defined at 10 ng/mL and checked in 12 analytical batches. The lower quantitation limit was 25 ng/mL. A detection between those limits therefore did not become a fully quantified result merely because the instrument supplied a numerical signal.

Extraction recovery exceeded 60% in the abstract’s summary, and matrix suppression or enhancement remained within 20%. Precision and bias were tested with 16 replicate measurements of control material at 40, 125, 1,600 and 2,500 ng/mL. Both methods met the study’s precision criterion of CV below 15% and bias criterion below 20%, although the high-resolution method showed greater variation for several analytes at low and high concentrations.

The comparison reported concordant findings for 253 positive and 2,269 negative analyte results in the 159 cases. These are analyte findings, not 2,522 separate decedents. The pooled quantitative regression was y = 1.002x + 1.523, with R² = 0.993. The authors reported no significant between-method quantitative difference. Twenty-two comparisons included a concentration between detection and quantitation limits, reported as below 25 ng/mL for at least one method.

Internal standards can complicate identification ions

Analyte-matched deuterated standards supported quantitation, but some lost their deuterium labels during fragmentation and produced ions shared with the corresponding drug. The authors identified this issue for several standards, including codeine-D3 and hydrocodone-D3. Testing D6 alternatives for those two analytes made the listed fragment ions available as distinct identifiers.

This was not evidence that internal standards should be omitted routinely. It showed why the laboratory must understand which ions remain independent identifiers under its chosen acquisition conditions. The proposed use of additional molecular-ion ratios also required further investigation and standardization, according to the authors.

Analytical agreement does not answer the biological question

Agreement supports measurement performance for this panel and workflow. It does not show that a measured postmortem concentration equals its antemortem value, or that a detected drug caused impairment or death. Those questions require specimen and case interpretation beyond analytical validation.

For related distinctions, see why authentic specimens matter in assay validation and what a negative autopsy screen can exclude.

Primary source

Rosano TG, Na S, Ihenetu K, Swift TA, Wood M. Multi-drug and Metabolite Quantification in Postmortem Blood by Liquid Chromatography–High-Resolution Mass Spectrometry: Comparison with Nominal Mass Technology. Journal of Analytical Toxicology. 2014;38:495–506. https://doi.org/10.1093/jat/bku066.

A drug’s volume of distribution can inform concern about postmortem redistribution, but it cannot reliably rank the change expected in an individual death. In a 129-case study, drugs with relatively small reported distribution volumes sometimes had larger central-to-peripheral concentration ratios than drugs with much larger volumes. The study measured differences between sampling sites; it did not measure each person’s change from life to death.

What the study actually compared

Han and colleagues examined 129 selected drug-related cases investigated by South Korea’s National Forensic Service during 2006–2009. One to six drugs were detected per case, and the study reported results for 76 drugs. This was not a series of 129 observations for every drug. Thirty-three drugs had results from at least two cases; the remaining drugs had only one case each.

The collection details matter. Femoral venous blood was obtained after ligation to reduce drawing blood from central vessels. The specimen called “cardiac blood” in the article was collected from the inferior vena cava after the chest and abdomen were opened. Paired specimens were stored in 50-mL plastic tubes at −20°C until analysis. The reported average interval from arrival at the facility to collection was approximately three hours, which is not the interval from death to collection.

Drugs were quantified by GC–MS or LC–MS/MS. The authors referred to earlier publications and laboratory procedures for method validation. The paper does not supply a complete analyte-specific validation dataset that would allow a reader to assign one analytical uncertainty to all 76 drugs.

The exceptions to a simple ranking rule

Volume of distribution describes the relationship between the amount of drug in the body and its blood or plasma concentration under the relevant pharmacokinetic conditions. It is not a direct measurement of how much drug will move after death. The authors discussed a distribution volume above approximately 3–4 L/kg as a reason for concern, but their observations showed why that cannot function as a universal dividing line.

Drug	Distribution volume discussed in the paper	Mean central/femoral ratio in this series	Cases
Codeine	2.2 L/kg	4.90; range 1.14–8.67	2
Zolpidem	0.6 L/kg	3.74; range 0.67–13.25	17
Nortriptyline	20 L/kg	2.01; range 0.40–5.63	12
Sertraline	20 L/kg	1.73; range 1.00–2.53	4
Amitriptyline	12 L/kg	1.36; range 0.73–2.50	13

These are descriptive comparisons, not a statistically validated ranking model. The distribution-volume values were discussed as drug properties, not measured separately in these decedents. Codeine’s apparently large average rests on just two cases. Zolpidem’s range includes a ratio below one and a value above thirteen. Neither average is a dependable multiplier for a new case.

A site ratio is not an antemortem correction

The numerator and denominator were both postmortem measurements. No antemortem drug concentrations were available for any case, and the death-to-collection interval was unavailable for most cases. There were no earlier serial specimens with which to establish the direction or speed of change.

Accordingly, dividing a central result by the published mean ratio would estimate neither a validated femoral concentration for that person nor the concentration during life. A ratio near one also cannot show that both sites remained unchanged. This distinction is illustrated further in our discussion of fentanyl specimen ratios near one.

How the findings help a case review

The practical value is to identify an assumption that needs evidence. A low distribution volume does not justify treating a central specimen as unaffected by postmortem processes. A high volume does not supply a numerical correction. The actual collection site, ligation technique, specimen history, analyte and available comparison specimens remain necessary parts of interpretation.

Detection establishes an analytical finding in the tested specimen. Even a well-measured concentration and a plausible redistribution mechanism do not independently establish impairment, the ingested dose or cause of death. A separate hydrocodone study with an influential outlier illustrates why individual observations should remain visible behind summary statistics.

Primary source

Han E, Kim E, Hong H, Jeong S, Kim J, In S, Chung H, Lee S. Evaluation of postmortem redistribution phenomena for commonly encountered drugs. Forensic Science International. 2012;219:265–271. https://doi.org/10.1016/j.forsciint.2012.01.016.

“Methamphetamine increases dopamine” does not answer every question about dopamine after repeated exposure. A measurement taken at rest during withdrawal differs from a measurement after a new dose. Lominac and colleagues’ 2014 mouse experiments illustrate how enhanced drug-evoked release can coexist with a lower resting estimate in a particular brain region.

Which experiment supports that distinction?

The repeated-exposure arm used adult male C57BL/6J mice assigned to methamphetamine or saline. Methamphetamine was administered intraperitoneally at 2 mg/kg once daily for ten consecutive days. Neurochemical or protein measurements were obtained after one or 21 days of withdrawal. A separate challenge experiment used another 2 mg/kg methamphetamine injection to examine the subsequent dopamine response.

This was controlled animal research, not a human dosing trial or an observational comparison of motorists. The authors described the regimen as relatively low and subtoxic in their experimental framework. Those descriptors do not establish a human safe dose or show that the regimen lacked every possible adverse effect.

What happened after a new methamphetamine challenge?

The challenge increased extracellular dopamine, and the response was sensitized in mice with the repeated methamphetamine history. The researchers detected this effect in both the nucleus accumbens and medial prefrontal cortex. The response’s magnitude and time course differed by region.

The statistical analysis did not detect a main or interaction effect of the withdrawal factor for this sensitization, with reported p-values above 0.20. That is a nonsignificant comparison between the tested withdrawal conditions, not proof that the response is permanently unchanged or identical at every intervening time.

What did the resting measurements show?

Using conventional microdialysis, the investigators did not detect significant treatment or withdrawal effects on basal extracellular dopamine in either region; the reported p-values were above 0.06. They then used quantitative no-net-flux microdialysis to address the influence of probe recovery on the estimate.

In the nucleus accumbens, that approach identified a lower resting dopamine estimate after 21 days of withdrawal, while the one-day comparison did not show a significant group difference. This resting observation and the amplified response after a fresh challenge concern different physiological conditions. Neither should replace the other in a summary of the experiment.

Why can the measurement method matter?

A microdialysis probe samples extracellular fluid through a membrane. The amount recovered in the collected dialysate can depend on the probe and local exchange conditions as well as the biological concentration being investigated. Conventional measurements therefore require care when comparing absolute recovered amounts across animals.

For the quantitative procedure, the researchers perfused increasing dopamine concentrations of 0, 2.5, 5 and 10 nM and modeled net exchange to estimate the point of no net flux. That procedure provides a different basis for estimating baseline extracellular content. The contrast between methods does not mean the conventional null result was fabricated or that the quantitative result establishes an individual diagnostic cutoff. It means the measurement process is part of the scientific inference.

Were every protein and functional outcome changed?

No. The study separately measured dopamine-transporter protein and responses to a transporter inhibitor. Repeated exposure reduced transporter protein in the nucleus accumbens core, while comparable changes were not detected in the shell or medial prefrontal cortex. The capacity of the inhibitor GBR-12909 to increase extracellular dopamine did not show a significant effect of repeated methamphetamine history in either tested region.

Protein abundance, drug-evoked response and resting neurotransmitter content are related but distinct endpoints. A change in one cannot be generalized into a claim that every component of dopamine function changed in the same direction. Nor does an unchanged functional comparison establish the absence of all biological adaptation.

Which limitations affect translation?

Final sample sizes differed across assays because of technical problems, probe placement and incomplete sampling. The paper reports obtaining both planned microdialysis sessions for approximately 70% of animals tested. The repeated-exposure arm used male inbred mice; a separate selectively bred high- versus low-drinking comparison used females with a different genetic background. Those designs should not be combined as though they were interchangeable replications or a randomized test of sex differences.

The paper also contains inconsistent descriptions of the direction of the resting medial-prefrontal dopamine change between its results narrative and discussion summary. This article therefore does not assign a firm direction to that particular result. The nucleus-accumbens distinction between resting content and challenge responsiveness can be discussed without silently resolving that reporting inconsistency.

What can a client safely take from the study?

The central lesson is to specify the state, region, timing and method behind a dopamine claim. Controlled exposure can support causation within this mouse model, but the experiment did not establish neuronal death, a human impairment threshold or an individual’s addiction prognosis. A lower resting estimate and an enhanced response to another dose describe separate outcomes, not a contradiction that requires one finding to be discarded.

Scientific source

Lominac KD, McKenna CL, Schwartz LM, et al. Mesocorticolimbic monoamine correlates of methamphetamine sensitization and motivation. Frontiers in Systems Neuroscience. 2014;8:70. doi:10.3389/fnsys.2014.00070. Historical controlled mouse experiments; original commentary focused on the repeated-exposure and measurement findings.

A larger amount of drug on positive sweat patches does not necessarily mean a larger percentage of patches will be positive. Barnes and colleagues’ historical controlled methamphetamine study illustrates this distinction: the higher-dose phase produced greater methamphetamine mass on positive weekly patches, but a smaller proportion of the available weekly patches tested positive. The apparent contradiction disappears when the denominators, missing data and reporting rules stay attached to the results.

Who received which drug?

Eight volunteers lived on a secure research unit during a ten-week protocol that included a two-week washout. All eight received four oral 10 mg doses of sustained-release S-(+)-methamphetamine hydrochloride within one week. Five later received four oral 20 mg doses after an interval of at least three weeks that included placebo administration. Two participants did not proceed for medical reasons and one for personal reasons.

These were cumulative dosing-week totals of 40 mg and 80 mg of the administered formulation, rather than single 40 mg or 80 mg doses. Some doses were not on consecutive days because of baseline heart rate or scheduling. The findings concern this oral sustained-release regimen; they should not be silently reassigned to smoked, injected or intranasal methamphetamine.

Were 682 patches equivalent to 682 independent participants?

No. The researchers analyzed 682 sweat patches from eight people. Short-term patches covered intervals from two hours upward, while weekly patches accumulated material over a longer period. Duplicate weekly patches were placed on the back and abdomen, and their results were reported individually.

Thus repeated and duplicate patches are observations within participants, not additional independent volunteers. A patch-level percentage cannot be described as the percentage of all people who would be detected after a particular dose. Available observations were also affected by missing patches, skin irritation, collection issues and analytical exclusions. The paper reports that 48 short-term and 20 weekly patches were lost between collection and analysis.

What did the weekly dose comparison show?

Available dosing-week patches in the controlled study; methamphetamine mass summaries describe positive patches.

Measure	Four 10 mg doses	Four 20 mg doses
Methamphetamine at or above the assay quantification limit	13/14 patches: 92.9%	5/8 patches: 62.5%
Median methamphetamine on positive patches	63.0 ng/patch	307 ng/patch
Range on positive patches	16.8–175 ng/patch	199–607 ng/patch
Methamphetamine-positive under the historical proposed reporting rule	12/14 patches: 85.7%	5/8 patches: 62.5%

The higher-dose median was larger, but fewer available weekly patches were positive. The percentage difference was not statistically significant, with the authors reporting p>0.05. Small patch counts, different participant availability, missing data and individual variation limit interpretation. These figures do not establish that a larger dose generally makes methamphetamine harder to detect.

Why did the reporting cutoff change the answer?

The GC-MS method quantified methamphetamine and amphetamine at 2.5 ng/patch. The investigators also applied a proposed SAMHSA rule discussed at the time: a methamphetamine result of at least 25 ng/patch with amphetamine present at or above the method’s detection limit. This was a historical proposed criterion, not a statement of current law or present laboratory policy.

After the first 10 mg dose, 12 of 32 short-term patches had measurable methamphetamine, but none met that reporting rule because amphetamine was not detected in those patches. An analytically measurable parent drug and a reportable positive under a rule requiring its metabolite are therefore different classifications.

Can a later positive patch date a new exposure?

At the assay quantification limit, some patches applied after the dosing week still contained drug. During the first postdose week, methamphetamine was measurable in eight of 13 available patches after the lower doses and seven of seven after the higher doses. One patch collected during the second postdose week after the higher doses contained 15.2 ng methamphetamine. No postdose weekly patch met the historical proposed methamphetamine-positive rule.

Those observations show why patch application and removal dates, wear duration and the actual reporting criterion matter. They do not create a universal detection window or establish that a positive patch necessarily represents a new dose taken during that wear interval.

What does the measured unit mean?

Nanograms per patch express accumulated analyte mass on the collector. They are not nanograms per milliliter of blood or a measured administered dose. The study also found that summed short-term patch amounts often exceeded corresponding weekly amounts, raising questions about losses during longer wear. It did not establish a universal recovery factor that could convert one patch result into total intake.

The evidence supports careful exposure monitoring under the conditions tested. It does not establish an individual’s time of ingestion, dose, current impairment or driving ability from patch mass alone.

Scientific source

Barnes AJ, Smith ML, Kacinko SL, Schwilke EW, Cone EJ, Moolchan ET, Huestis MA. Excretion of methamphetamine and amphetamine in human sweat following controlled oral methamphetamine administration. Clinical Chemistry. 2008;54(1):172–180; published online November 2, 2007. doi:10.1373/clinchem.2007.092304. Historical controlled human administration study; full text recovered for the paper identified in the supplied research collection.

A bacterial ethanol model developed in nutrient broth did not retain the same performance in every human blood or plasma culture. Boumba and colleagues showed that changing the matrix could alter both ethanol production and the relationship with other alcohols, even when the starting glucose concentration was matched. A successful broth model was not a universal correction for a postmortem specimen.

What the researchers cultured

The study used four reference bacterial strains: Escherichia coli, Clostridium perfringens, Clostridium sporogenes and Enterococcus faecalis. They were cultured separately under controlled anaerobic conditions for 30 days, principally at 25°C, in brain-heart-infusion broth. Starting bacterial concentration was approximately 10⁴ cells/mL. No growth was observed in the 4°C comparison cultures.

Alcohol concentrations were tracked during incubation. Three species produced usable alcohol patterns; E. faecalis produced negligible ethanol and other alcohols under these conditions, so it did not supply a practical regression model.

The human-matrix work used blood from healthy living donors, not blood removed from decomposed bodies. The methods described sets of 16 tubes for sampling in pairs at eight time points through day 15. Sixteen tubes should not be described as sixteen independent donors; a donor count was not clearly reported.

Changing the medium changed the outcome

C. sporogenes produced the largest ethanol amounts in broth, but produced no ethanol or other measured alcohols in the tested plasma cultures during 15 days. Adding glucose to achieve 200 mg/dL did not restore that production.

E. coli produced more ethanol in glucose-supplemented plasma than in unsupplemented plasma, yet less than in broth with the same initial glucose concentration of 200 mg/dL. Glucose alone therefore did not account for the matrix effect.

The blood anticoagulant also mattered. In citrate-containing blood inoculated with C. perfringens, ethanol appeared after day five without detectable production of the other measured alcohols. The EDTA-blood experiment behaved differently. These observations concern defined inoculated cultures, not every preserved forensic sample.

Analytical measurement and model performance were separate

The laboratory quantified ethanol and other volatiles by headspace GC–FID. For ethanol, the reported detection limit was 0.01 mg/dL, quantification limit 0.03 mg/dL and calibration range 0.03–400 mg/dL. The validation reported precision below 6% relative standard deviation and accuracy errors from −1.0% to 2.5% across the tested analytes and controls.

These analytical characteristics did not guarantee that a regression fitted in one medium predicted another medium correctly. In EDTA whole blood inoculated with C. perfringens, the broth-derived model did not successfully predict the experimental values; a second-degree polynomial provided a better fit, R² = 0.79.

Other transfers performed better under particular conditions. The authors reported average prediction errors of approximately 16% for one C. perfringens plasma application and 22% for glucose-supplemented E. coli plasma. Those percentages were conditional experimental results, not universal uncertainty limits for casework.

What did the forty postmortem cases establish?

The investigators also applied models retrospectively to 40 selected case chromatograms with co-detected alcohols. Thirty-nine cases showed marked putrefaction; one had extensive trauma. This selected series was not a random validation cohort.

Critically, the amount of ethanol truly formed after death was not independently known. Comparison with the measured total ethanol could not separate predeath ingestion from microbial formation. The authors acknowledged that limitation, the small number of modeled microbes and the need for further work before routine extrapolation.

What follows for a case review?

Identify the model’s organism, medium, temperature, additives and validation population before applying it to blood. Accurate ethanol quantitation and accurate attribution of ethanol origin are separate achievements. Neither a fitted model nor detection alone establishes drinking, impairment or cause of death.

For the related measurement distinction, see analytical uncertainty versus postmortem ethanol formation.

Primary source

Boumba VA, Economou V, Kourkoumelis N, Gousia P, Papadopoulou C, Vougiouklakis T. Microbial ethanol production: Experimental study and multivariate evaluation. Forensic Science International. 2012;215:189–198. doi:10.1016/j.forsciint.2011.03.003.

An autoradiograph tracks a radioactive label, which may be present in unchanged fentanyl or in its metabolites. It also does not automatically measure postmortem redistribution. Schneider and Brune’s rat study is useful precisely because it separated these questions using different labels and additional chemical analysis.

What was the experiment designed to investigate?

The 1985 study addressed a proposed explanation for delayed respiratory depression after anesthesia: fentanyl might accumulate in the stomach and later be reabsorbed, causing a second rise in brain concentration. It was a pharmacological distribution experiment, not a human death-investigation series.

Female Wistar rats weighing approximately 200 ± 10 g received fentanyl labeled either in the phenethyl portion with tritium or in the aniline portion with carbon-14. Intravenous administration through a femoral-vein catheter lasted nine minutes. Doses were approximately 6 µg per 100 g body weight. A separate experiment used intragastric administration.

The paper described two labeling series and their sampling schedules but did not give a clear total number of animals. A total sample size should therefore not be inferred simply by counting displayed images.

The sampling clock ran before death

Autoradiographic specimens were obtained at specified times up to 270 minutes after intravenous dosing, with a separate intragastric assessment at 320 minutes. Animals were killed and immediately frozen for sectioning.

Those intervals were times after administration in living animals. They were not intervals during which a corpse was allowed to undergo redistribution or decomposition. The study therefore cannot supply a numerical correction for fentanyl movement between death and a later human autopsy.

Why the radioactive label was not the parent drug

Radioactivity distribution depended partly on which portion of the fentanyl molecule carried the label. Metabolism could leave label-bearing products in tissues after unchanged fentanyl had diminished. The investigators discussed differences between the two label patterns in that context.

They used high-performance thin-layer chromatography to separate parent drug from labeled metabolites in organ extracts. At 320 minutes after intragastric administration, 87% of the label in stomach contents was attributed to unchanged fentanyl, compared with only 40% in small-intestinal contents. Total recovered radioactivity therefore did not represent the same proportion of unchanged drug in every compartment.

For whole-blood measurements, the procedure included hexane extraction. Chromatographic analysis indicated that those extracts contained parent drug. This added chemical selectivity should not be assumed for every autoradiographic tissue signal. The paper did not provide numerical detection or quantification limits for the tissue autoradiographs. Blood results and tissue radioactivity were also expressed using different quantities, including pmol/mL and radioactivity-derived pmol/g equivalents.

What did the investigators find?

They observed early brain radioactivity followed by distribution to other compartments. Neither labeling series demonstrated secondary brain accumulation, and the measured blood curve did not show the predicted second rise. The estimated intragastric bioavailability was 1.5% over the study’s specified comparison period.

These findings did not support the proposed gastrointestinal recirculation explanation under the tested conditions. They did not establish that delayed respiratory depression is impossible. The authors left questions about multiple dosing, metabolite accumulation and interactions with other anesthetic drugs unresolved.

What the study can contribute to forensic interpretation

When a distribution paper is used to explain a postmortem result, identify whether its signal measured parent drug, metabolites or both, and whether its time course occurred before or after death. An image showing drug-related material in a tissue is not an independently validated concentration of unchanged fentanyl.

This animal experiment established neither a human impairment threshold nor a cause-of-death criterion. Compare the distinct evidentiary limits of the rabbit marrow methanol experiment, which actually included specified postmortem sampling delays.

Primary source

Schneider E, Brune K. Distribution of fentanyl in rats: an autoradiographic study. Naunyn-Schmiedeberg’s Archives of Pharmacology. 1985;331:359–363. doi:10.1007/BF00500820.

A published 44-drug redistribution table was not validated by paired antemortem and postmortem measurements for all 44 drugs. McIntyre’s 2016 study compared theoretical factors with 13 observations involving nine drugs from nine cases. The statistically significant relationship supported further investigation, but did not establish precise individual reconstruction across the entire table.

The model and the measured factor were different

The measured factor, F, was the postmortem peripheral whole-blood concentration divided by the corresponding antemortem whole-blood concentration. The theoretical factor, F_t, was calculated from a drug’s characteristic liver/peripheral-blood ratio.

The source dataset summarized median liver/peripheral ratios for 44 drugs from 867 cases. Those 867 cases supplied reference distribution information; they were not 867 people with paired blood specimens collected during life and after death.

The proposed use was to estimate an earlier whole-blood concentration by dividing the postmortem peripheral result by the factor. That proposed calculation must not be mistaken for a directly measured earlier concentration.

What did the thirteen examples show?

The paired comparison involved 13 drug observations from nine cases. Some people supplied more than one drug observation, so the dataset was not thirteen independent decedents. Antemortem specimens were collected one to 36 minutes before death. The death-to-autopsy interval was 5.2–42 hours, averaging 17 hours.

The relationship between measured and theoretical factors was statistically significant: R² = 0.7006, p = 0.001. That association was not a case-specific prediction interval or a demonstration of equivalent accuracy for every drug.

For example, the fentanyl observation had antemortem and postmortem concentrations of 0.0014 and 0.0016 mg/L, respectively. The table reported a measured factor of 1.1 and theoretical factor of 1.5. A quetiapine observation was 0.15 mg/L before death and 0.24 mg/L afterward, giving a measured factor of 1.6 versus theoretical 2.0. The factors did not match exactly even in these closely timed cases.

Collection conditions restricted the application

The study excluded obvious decomposition. Its described collection procedure used right-lobe liver tissue and peripheral blood from the visually identified common iliac vein. The upper iliac vein was usually not clamped, allowing potential contribution from more proximal blood. It should not be silently relabeled as an isolated femoral-vein specimen.

Blood was collected into fluoride/oxalate tubes; liver had no preservative, and specimens were stored at 4°C. Screening included immunoassay and chromatographic procedures, followed by specific confirmation and quantitation. Different drugs required different analytical methods. The article did not provide one common numerical detection limit, quantification limit or precision value for all nine paired analytes.

What remained unverified?

The author explicitly stated that the same relationship lacked direct evidence for the other 35 drugs. Their theoretical entries were hypotheses requiring further verification, not observed before-and-after changes.

The paper also cautioned against extension to prolonged postmortem intervals, decomposition, incomplete drug distribution in acute overdose, and incompatible blood or liver collection sites. It found no obvious effect of interval within its small comparison but acknowledged inadequate numbers to resolve that question.

A drug ranking can assist interpretation without supplying an exact correction for every individual. Before applying any factor, reviewers need to examine independent validation, sample comparability, prediction uncertainty and the clinical interval before death. Neither the factor nor a reconstructed number establishes impairment or cause of death.

The importance of preserving individual exceptions is illustrated by the repeated hydrocodone liver-to-blood outlier.

Primary source

McIntyre IM. Analytical data supporting the “theoretical” postmortem redistribution factor (F_t): a new model to evaluate postmortem redistribution. Forensic Sciences Research. 2016;1(1):33–37. doi:10.1080/20961790.2016.1253255.