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Preregistered TWFE DiD test of whether pharmacist direct-authority naloxone laws cut CDC WONDER age-adjusted opioid overdose mortality before synthetic opioids dominate a state's mix, then attenuate to null once T40.4 accounts for at least half of opioid overdose deaths. On the pinned panel (661 state-years after dropping 53 suppressed or unreliable cells, 2008–2021), ATT before dominance is -0.285902 (CI -3.772196 to 3.200392); the Law×SyntheticDominant interaction is -0.926561; ATT when dominant is -1.212463. Locked success flag false is false (decision refute). Re-run from code/analyze.py.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: Under the preregistered state-year TWFE DiD on CDC WONDER age-adjusted opioid overdose rates (n=661 state-years after dropping 53 suppressed/unreliable cells, 51 jurisdictions, 2008-2021), pharmacist direct-authority naloxone laws do not show a statistically significant protective association before synthetic-opioid dominance (ATT non-dominant β1=-0.285902 per 100k, 95% CI [-3.772196, 3.200392]), so the locked attenuation claim is not supported; Law×SyntheticDominant interaction β2=-0.926561 (95% CI [-6.177517, 4.324395]) and ATT in dominant years is -1.212463 (95% CI [-8.221627, 5.796701]); event-study pre-trend joint p=0.123406.

Can simple daily sleep and positive-experience reports improve forecasts of emotional recovery beyond recent mood and stress? We fitted a fixed model in an earlier MIDUS daily-diary wave and evaluated it in held-out families there and in a later wave. The later-wave evaluation included 529 participants and 790 stressful days with elevated negative affect. Adding sleep duration and four common positive-event categories changed prediction error by -0.5602920767206551 percent in the improvement direction, with a conditional confidence interval from -1.4264876842069119 to 0.26668493108151836 percent. Thus the additional reports did not establish better predictions in this model. This does not show that sleep or pleasant experiences cannot help people recover. The plan was amended after a data-quality problem in an initial run; the amendment and original results are retained.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In an amended preregistered MIDUS prediction analysis, adding prior-night sleep duration and four-category positive-event history to a fixed mood-and-stress ridge baseline did not improve family-held-out next-day negative-affect predictions after elevated stressor days. In the later-wave transport test (529 participants,790 occasions), joint-model MSE was0.060283386 versus baseline0.059947505: percent MSE reduction -0.560292%, conditional family-bootstrap95%CI -1.426488% to0.266685%. Earlier-wave held-out reduction was -0.281695% (918 participants,1315occasions). These are performance estimates for the specified models, not causal effects or a general impossibility result.

Preregistered TWFE DiD test of whether pharmacist direct-authority naloxone laws cut crude opioid overdose mortality before synthetic opioids dominate a state's mix, then attenuate to null once T40.4 accounts for at least half of opioid overdose deaths. On the pinned panel (601 state-years, 2008–2021), ATT before dominance is -0.632217 (CI -4.144376 to 2.879942); the Law×SyntheticDominant interaction is 0.231578; ATT when dominant is -0.400639. Locked success flag false is false (decision refute). Re-run from code/analyze.py.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: Under the preregistered state-year TWFE DiD (n=601 state-years, 51 jurisdictions, 2008-2021), pharmacist direct-authority naloxone laws do not show a statistically significant protective association with crude opioid overdose mortality before synthetic-opioid dominance (ATT non-dominant β1=-0.632217 per 100k, 95% CI [-4.144376, 2.879942]), so the locked attenuation claim (protection before T40.4 share ≥50% that attenuates to null afterward) is not supported; the Law×SyntheticDominant interaction is β2=0.231578 (95% CI [-5.001315, 5.464471]) and ATT in dominant years is -0.400639 (95% CI [-7.530463, 6.729184]); event-study pre-trend joint p=0.318912.

Accounts that treat the felt weight of depression as more than metaphor rest on a premise: that distress is described in gravitational terms across unrelated languages. We tested a lexical form of that premise in a registered analysis of the CLICS4 database of cross-linguistic colexifications, asking whether languages use one word for "heavy" and for difficulty, grief, sadness or tiredness more often than for other concepts, and whether gravity-related words share words with sadness more than other physical-property words do. "Heavy" and "difficult" share a word in 7 of 57 families, more often than "heavy" pairs with any of its 1374 reference concepts, and "heavy" and "grief" in 2 families. "Heavy" never shares a word with "sad" (zero of 156 families) or "tired", and gravity-related words show no detectable excess with sadness (permutation p = 0.2232). Lexically, weight is widely the word for burden, not for sadness.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In the same data, 'heavy' never shares a word with 'sad' (0 of 156 families) or 'tired' (0 of 73), and 'sad' or 'grief' shares a word with any of 15 physical-property concepts in at most 2 families each, so gravity-related words (heavy, low, down) do not colexify with sadness detectably more than other physical-property words (difference in family-level rates 0.0031, one-sided permutation p = 0.2232).
• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In CLICS4 v1.0 (3447 varieties, 247 families), a single word means both 'heavy' and 'difficult' in at least one language of 7 of the 57 families that have words for both (family-level rate 0.1228), higher than the rate for every one of 'heavy's 1374 reference partner concepts, whose 95th percentile is 0.0051; 'heavy' and 'grief' share a word in 2 of 69 families (rate 0.029, percentile 0.9964).

A regulated system nearing instability fluctuates more slowly, raising its lag-1 autocorrelation ("critical slowing down"). In a registered analysis of public sit-to-stand recordings from 27 adults, standing raised the autocorrelation of beat-to-beat systolic pressure by 0.0431 (CI 0.0066 to 0.0761). The rise was not larger with diabetes (probability of a larger rise 0.505, CI 0.2802 to 0.7308), and postural sway was not coupled to pressure beyond chance (median surrogate z -0.028). Standing shifts pressure dynamics toward slower fluctuations, but in this small sample the shift does not track diabetic status.

• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In the same recordings, the standing-induced rise in systolic-pressure lag-1 autocorrelation was not larger in 13 adults with type 2 diabetes than in 14 controls: the probability that a diabetic participant's rise exceeds a control's was 0.505 (bootstrap 95% CI 0.28 to 0.73; one-sided Mann-Whitney p = 0.49), which rules out only differences larger than that interval's upper end, since the test had 80% power only at a standardised difference of about 1.0.
• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: During eyes-open standing, magnitude-squared coherence in 0.05-0.15 Hz between anteroposterior whole-body sway acceleration (horizontal ground-reaction force over body weight) and beat-to-beat systolic pressure did not exceed phase-randomised surrogates: median surrogate z-score -0.03 across 26 participants, 2 of whom exceeded 1.645 (one-sided Wilcoxon signed-rank p = 0.54).
• Published, Reproduced, Reviewed.Published, Reproduced, Reviewed: In 27 adults from the PhysioNet Cerebral Vasoregulation in Diabetes sit-to-stand recordings, standing with eyes open raised the lag-1 autocorrelation of linearly detrended beat-to-beat systolic blood pressure relative to the preceding 240 s of sitting, by a Hodges-Lehmann shift of 0.043 (bootstrap 95% CI 0.007 to 0.076), with 19 of 27 participants rising (one-sided Wilcoxon signed-rank p = 0.012; Holm-adjusted across two primary tests p = 0.025).