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opencc-by-4.0Aug 2021View details →

Sex-specific tuning of modular muscle activation patterns for locomotion in young and older adults

There is increasing evidence that including sex as a biological variable is of crucial importance to promote rigorous, repeatable and reproducible science. In spite of this, the body of literature that accounts for the sex of participants in human locomotion studies is small and often produces controversial results. Here, we investigated the modular organization of muscle activation patterns for human locomotion using the concept of muscle synergies with a double purpose: i) uncover possible sex-specific characteristics of motor control and ii) assess whether these are maintained in older age. We recorded electromyographic activities from 13 ipsilateral muscles of the lower limb in young and older adults of both sexes walking (young and old) and running (young) on a treadmill. The data set obtained from the 215 participants was elaborated through non-negative matrix factorization to extract the time-independent (i.e., motor modules) and time-dependent (i.e., motor primitives) coefficients of muscle synergies. We found sparse sex-specific modulations of motor control. Motor modules showed a different contribution of hip extensors, knee extensors and foot dorsiflexors in various synergies. Motor primitives were wider (i.e., lasted longer) in males in the propulsion synergy for walking (but only in young and not in older adults) and in the weight acceptance synergy for running. Moreover, the complexity of motor primitives was similar in younger adults of both sexes, but lower in older females as compared to older males. In essence, our results revealed the existence of small but defined sex-specific differences in the way humans control locomotion and that these strategies are not entirely maintained in older age. In this supplementary data set we made available: a) the metadata with anonymized participant information; b) the raw EMG, already concatenated for the overground trials; c) the touchdown and lift-off timings of the recorded limb, d) the code to process the data. In total, 520 trials from 215 participants are included in the supplementary data set. The file “metadata.dat” is available in ASCII format and contains: <ul> <li>Code: the participant’s code</li> <li>Group: the participant's group (G1=young adults, walking; G2=old adults, walking; G3=young adults, running)</li> <li>Sex: the participant’s sex (M or F)</li> <li>Locomotion: the type of locomotion (walking or running)</li> <li>Speed: the speed at which the recordings were conducted in [m/s]</li> <li>Speed_type: the distinction between fixed (decided by the researchers) or preferred (selected by the participant) speed</li> <li>Age: the participant’s age in years</li> <li>Height: the participant’s height in [cm]</li> <li>Mass: the participant’s body mass in [kg].</li> </ul> The "RAW_DATA.RData" R list consists of elements of S3 class "EMG", each of which is a human locomotion trial containing cycle segmentation timings and raw electromyographic (EMG) data from 13 muscles of the right-side leg. Cycle times are structured as data frames containing two columns that correspond to touchdown (first column) and lift-off (second column). Raw EMG data sets are also structured as data frames with one row for each recorded data point and 14 columns. The first column contains the incremental time in seconds. The remaining 13 columns contain the raw EMG data, named with the following muscle abbreviations: ME = gluteus medius, MA = gluteus maximus, FL = tensor fasciæ latæ, RF = rectus femoris, VM = vastus medialis, VL = vastus lateralis, ST = semitendinosus, BF = biceps femoris, TA = tibialis anterior, PL = peroneus longus, GM = gastrocnemius medialis, GL = gastrocnemius lateralis, SO = soleus. Trials are named like “ID0020_M_YOUNG_TW_01,” where the characters “ID0020” indicate the participant number (in this example the 20th), the character “M” indicates the sex, the characters “YOUNG” indicate the age group, the characters “TW” indicate the locomotion type and environment (T=treadmill, W=walking, R=running), and the numbers “01” indicate the trial number. Old versions not compatible with the R package <a href="https://CRAN.R-project.org/package=musclesyneRgies">musclesyneRgies</a> The files containing the gait cycle breakdown are available in RData format, in the file named “CYCLE_TIMES.RData”. The files are structured as data frames with one row for each gait cycle and two columns. The first column contains the touchdown incremental times in seconds. The second column contains the duration of each stance phase in seconds. Each trial is saved as an element of a single R list. Trials are named like “CYCLE_TIMES_ID0020_M_YOUNG_TW_01,” where the characters “CYCLE_TIMES” indicate that the trial contains the gait cycle breakdown times, the characters “ID0020” indicate the participant number (in this example the 20th), the character “M” indicates the sex, the characters “YOUNG” indicate the age group, the characters “TW” indicate the locomotion type and environment (T=treadmill, W=walking, R=running), and the numbers “01” indicate the trial number. The files containing the raw, filtered, and the normalized EMG data are available in RData format, in the files named “RAW_EMG.RData” and “FILT_EMG.RData”. The raw EMG files are structured as data frames with one row for each recorded data point and 14 columns. The first column contains the incremental time in seconds. The remaining 13 columns contain the raw EMG data, named with the following muscle abbreviations: ME = gluteus medius, MA = gluteus maximus, FL = tensor fasciæ latæ, RF = rectus femoris, VM = vastus medialis, VL = vastus lateralis, ST = semitendinosus, BF = biceps femoris, TA = tibialis anterior, PL = peroneus longus, GM = gastrocnemius medialis, GL = gastrocnemius lateralis, SO = soleus. Each trial is saved as an element of a single R list. Trials are named like “RAW_EMG_ID0003_F_OLD_TW_01”, where the characters “RAW_EMG” indicate that the trial contains raw emg data, the characters “ID0003” indicate the participant number (in this example the 3rd), the character “F” indicates the sex, the characters “OLD” indicate the age group, the characters “TW” indicate the locomotion type and environment (see above), and the numbers “01” indicate the trial number. All the code used for the pre-processing of EMG data and the extraction of muscle synergies is available in R format. Explanatory comments are profusely present throughout the script “muscle_synergies.R”. The latest version of this code can be found at https://github.com/alesantuz/musclesyneRgies.

opencc-by-4.0Jul 2020View details →

Muscle activation patterns are more constrained and regular in treadmill than in overground human locomotion

The use of motorized treadmills as convenient tools for the study of locomotion has been in vogue for many decades. However, despite the widespread presence of these devices in many scientific and clinical environments, a full consensus on their validity to faithfully substitute free overground locomotion is still missing. Specifically, little information is available on whether and how the neural control of movement is affected when humans walk and run on a treadmill as compared to overground. Here, we made use of linear and nonlinear analysis tools to extract information from electromyographic recordings during walking and running overground and on an instrumented treadmill. We extracted synergistic activation patterns from the muscles of the lower limb via non-negative matrix factorization. We then investigated how the motor modules (or time-invariant muscle weightings) were used in the two locomotion environments. Subsequently, we examined the timing of motor primitives (or time-dependent coefficients of muscle synergies) by calculating their duration, the time of main activation, and their Hurst exponent, a nonlinear metric derived from fractal analysis. We found that motor modules were not influenced by the locomotion environment, while motor primitives resulted overall more regular in treadmill than in overground locomotion, with the main activity of the primitive for propulsion shifted earlier in time. Our results suggest that the spatial and sensory constraints imposed by the treadmill environment forced the central nervous system to adopt a different neural control strategy than that used for free overground locomotion. A data-driven indication that treadmills induce perturbations to the neural control of locomotion.   In this supplementary data set we made available: a) the metadata with anonymized participant information; b) the raw EMG, already concatenated for the overground trials; c) the touchdown and lift-off timings of the recorded limb, d) the filtered and time-normalized EMG; e) the muscle synergies extracted via NMF; f) the code to process the data. In total, 120 trials from 30 participants are included in the supplementary data set. The file “metadata.dat” is available in ASCII and RData format and contains: <ul> <li>Code: the participant’s code</li> <li>Sex: the participant’s sex (M or F)</li> <li>Locomotion: the type of locomotion (W=walking, R=running)</li> <li>Environment: to distinguish between overground (O) and treadmill (T)</li> <li>Speed: the speed at which the recordings were conducted in [m/s] (1.4 m/s for walking, 2.8 m/s for running)</li> <li>Age: the participant’s age in years</li> <li>Height: the participant’s height in [cm]</li> <li>Mass: the participant’s body mass in [kg].</li> </ul> The "RAW_DATA.RData" R list consists of elements of S3 class "EMG", each of which is a human locomotion trial containing cycle segmentation timings and raw electromyographic (EMG) data from 13 muscles of the right-side leg. Cycle times are structured as data frames containing two columns that correspond to touchdown (first column) and lift-off (second column). Raw EMG data sets are also structured as data frames with one row for each recorded data point and 14 columns. The first column contains the incremental time in seconds. The remaining 13 columns contain the raw EMG data, named with the following muscle abbreviations: ME = gluteus medius, MA = gluteus maximus, FL = tensor fasciæ latæ, RF = rectus femoris, VM = vastus medialis, VL = vastus lateralis, ST = semitendinosus, BF = biceps femoris, TA = tibialis anterior, PL = peroneus longus, GM = gastrocnemius medialis, GL = gastrocnemius lateralis, SO = soleus. Please note that the running overground trials of participants P0001, P0007, P0008 and P0009 consist of 21, 29, 29 and 26 cycles, respectively. All the other trials consist of 30 gait cycles. Trials are named like “P0003_OR_01”, where the characters “P0003” indicate the participant number (in this example the 3rd), the characters “OR” indicate the locomotion type and environment (see above), and the numbers “01” indicate the trial number. The filtered and time-normalized emg data are named, following the same rules, like “FILT_EMG_P0003_OR_01”. Old versions not compatible with the R package <a href="https://CRAN.R-project.org/package=musclesyneRgies">musclesyneRgies</a> The files containing the gait cycle breakdown are available in RData format, in the file named “CYCLE_TIMES.RData”. The files are structured as data frames with 30 rows (one for each gait cycle) and two columns. The first column contains the touchdown incremental times in seconds. The second column contains the duration of each stance phase in seconds. Each trial is saved as an element of a single R list. Trials are named like “CYCLE_TIMES_P0020_TW_01,” where the characters “CYCLE_TIMES” indicate that the trial contains the gait cycle breakdown times, the characters “P0020” indicate the participant number (in this example the 20th), the characters “TW” indicate the locomotion type and environment (O=overground, T=treadmill, W=walking, R=running), and the numbers “01” indicate the trial number. Please note that the running overground trials of participants P0001, P0007, P0008 and P0009 only contain 21, 29, 29 and 26 cycles, respectively. The files containing the raw, filtered, and the normalized EMG data are available in RData format, in the files named “RAW_EMG.RData” and “FILT_EMG.RData”. The raw EMG files are structured as data frames with 30000 rows (one for each recorded data point) and 14 columns. The first column contains the incremental time in seconds. The remaining 13 columns contain the raw EMG data, named with muscle abbreviations that follow those reported above. Each trial is saved as an element of a single R list. Trials are named like “RAW_EMG_P0003_OR_01”, where the characters “RAW_EMG” indicate that the trial contains raw emg data, the characters “P0003” indicate the participant number (in this example the 3rd), the characters “OR” indicate the locomotion type and environment (see above), and the numbers “01” indicate the trial number. The filtered and time-normalized emg data is named, following the same rules, like “FILT_EMG_P0003_OR_01”. The files containing the muscle synergies extracted from the filtered and normalized EMG data are available in RData format, in the file named “SYNS.RData”. Each element of this R list represents one trial and contains the factorization rank (list element named “synsR2”), the motor modules (list element named “M”), the motor primitives (list element named “P”), the reconstructed EMG (list element named “Vr”), the number of iterations needed by the NMF algorithm to converge (list element named “iterations”), and the reconstruction quality measured as the coefficient of determination (list element named “R2”). The motor modules and motor primitives are presented as direct output of the factorization and not in any functional order. Motor modules are data frames with 13 rows (number of recorded muscles) and a number of columns equal to the number of synergies (which might differ from trial to trial). The rows, named with muscle abbreviations that follow those reported above, contain the time-independent coefficients (motor modules M), one for each synergy and for each muscle. Motor primitives are data frames with 6000 rows and a number of columns equal to the number of synergies (which might differ from trial to trial) plus one. The rows contain the time-dependent coefficients (motor primitives P), one column for each synergy plus the time points (columns are named e.g. “time, Syn1, Syn2, Syn3”, where “Syn” is the abbreviation for “synergy”). Each gait cycle contains 200 data points, 100 for the stance and 100 for the swing phase which, multiplied by the 30 recorded cycles, result in 6000 data points distributed in as many rows. This output is transposed as compared to the one discussed in the methods section to improve user readability. Trials are named like “SYNS_ P0012_OW_01”, where the characters “SYNS” indicate that the trial contains muscle synergy data, the characters “P0012” indicate the participant number (in this example the 12th), the characters “OW” indicate the locomotion type and environment (see above), and the numbers “01” indicate the trial number. Given the nature of the NMF algorithm for the extraction of muscle synergies, the supplementary data set might show non-significant differences as compared to the one used for obtaining the results of this paper. All the code used for the pre-processing of EMG data and the extraction of muscle synergies is available in R format. Explanatory comments are profusely present throughout the script “muscle_synergies.R”.

dryad40/100

Tutorial video for: A toolbox for the retrodeformation and muscle reconstruction of fossil specimens in Blender

Accurate muscle reconstructions can offer new information on the anatomy of fossil organisms and are also important for biomechanical analysis (multibody dynamics and finite element analysis). For the sake of simplicity, muscles are often modeled as point-to-point strands or frustra (cut off cones) in biomechanical models. However, there are cases in which it is useful to model the muscle morphology in 3D, to better examine the effects of muscle shape and size. This is especially important for fossil analyses, where muscle force is estimated from the reconstructed muscle morphology (rather than based on data collected in vivo). The two main aims of this paper are as follows. First, we created a new interactive tool in the free open access software Blender to enable interactive 3D modeling of muscles. This approach can be applied to both palaeontological and human biomechanics research to generate muscle force magnitudes and lines of action for finite element analysis. Second, we provide a guide on how to use existing Blender tools to reconstruct distorted or incomplete specimens. This guide is aimed at palaeontologists but can also be used by anatomists working with damaged specimens or to test functional implication of hypothetical morphologies.

opencc-zeroAug 2022View details →

opencc-by-4.0Sep 2022View details →

Dataset for "Quantification of Muscle Fiber Malformations Using Edge Detection to Investigate Chronic Wound Healing"

Primary images, spreadsheets and files for "Quantification of Muscle Fiber Malformations Using Edge Detection to Investigate Chronic Wound Healing"

opencc-by-3.0Sep 2022View details →

Survival, wet weight and muscle cellular stress responses of Palaemon varians shrimps exposed to combined temperature and salinity variations

Shrimps were exposed to a full factorial experiment combining different temperatures (20, 23 and 26 ºC) and salinities (20, 40). Cellular stress response biomarkers were assessed in the shrimps muscle at several time-points, namely the 7th, 14th, 21st and 28th days of exposure. Wet weight (as proxy for growth) and survival were also assessed during the experiment. These datasets refer to the publication of an article in STOTEN (<a href="https://doi.org/10.1016/j.scitotenv.2022.158732">https://doi.org/10.1016/j.scitotenv.2022.158732</a>). Note: the biomarker dataset contained 3.2% of missing values, which were replaced by group averages for the purpose of the statistical analyses in the article.

opencc-by-4.0Dec 2019View details →

Рис. 1. Раковины Mya truncata (А–Г) (Белое море) и Laternula elliptica (А'–Г') (Зал. Прюдс): А, А' – обЩий вид; Б, Г' – внутреннЯЯ поверхность левых створок; В, В' – вид хондрофора со стороны дорсального краЯ; Г, Б' – внутреннЯЯ поверхность правых створок. ОбоЗначениЯ: пК – передний край раковины; ЗК – Задний край; дК – дорсальный край; м – макушка; мщ – макушечнаЯ (умбональнаЯ) Щель; Кс – концентрическаЯ скульптура; сКп – складки периостракума; хр – хондрофор; ппЛ – поддерживаюЩаЯ пластинка; син – синус; ОмЗ – отпечаток мускула-ЗамыкателЯ. Fig. 1. Shells of Mya truncata (А–Г) (White Sea) and Laternula elliptica (А'–Г') (Prydz Bay): A, A' – general view; Б, Г' – internal view of left valves; В, В' – dorsal view on chondrophores; Г, Б' – internal view of right valves. Notes: пК – anterior margin; ЗК – posterior margin; дК – dorsal margin; м – umbo; мщ – umbonal crack; Кс – concentric sculpture; сКп – periostracal wrinkles; хр – chondrophore; ппЛ – buttress; син – sinus; ОмЗ – trace of retractor muscle. in Species of warm-water origin Laternula elliptica (King, 1832) (Mollusca: Bivalvia: Laternulidae), a widespread mollusk in recent Antarctica

Рис. 1. Раковины Mya truncata (А–Г) (Белое море) и Laternula elliptica (А'–Г') (Зал. Прюдс): А, А' – обЩий вид; Б, Г' – внутреннЯЯ поверхность левых створок; В, В' – вид хондрофора со стороны дорсального краЯ; Г, Б' – внутреннЯЯ поверхность правых створок. ОбоЗначениЯ: пК – передний край раковины; ЗК – Задний край; дК – дорсальный край; м – макушка; мщ – макушечнаЯ (умбональнаЯ) Щель; Кс – концентрическаЯ скульптура; сКп – складки периостракума; хр – хондрофор; ппЛ – поддерживаюЩаЯ пластинка; син – синус; ОмЗ – отпечаток мускула-ЗамыкателЯ. Fig. 1. Shells of Mya truncata (А–Г) (White Sea) and Laternula elliptica (А'–Г') (Prydz Bay): A, A' – general view; Б, Г' – internal view of left valves; В, В' – dorsal view on chondrophores; Г, Б' – internal view of right valves. Notes: пК – anterior margin; ЗК – posterior margin; дК – dorsal margin; м – umbo; мщ – umbonal crack; Кс – concentric sculpture; сКп – periostracal wrinkles; хр – chondrophore; ппЛ – buttress; син – sinus; ОмЗ – trace of retractor muscle.

Fig. 9 in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 9. Muscle scars on internal mould of the rostroconch Ribeiria Sharpe, 1853, in lateral view. Both the anterior and posterior median muscle scars lie across the median dorsal plane of symmetry, the former attached to the transverse pegma preserved as a deep cleft on the internal mould. The posterior scar is a uniform attachment area, often ornamented with transverse growth lines, unlike the multiple small scars of Eotebenna (based on Pojeta and Runnegar 1976; Polechova 2015).

Fig. 7 in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 7. Muscle scars on internal moulds of Palaeozoic bivalves. A. Left valve of Babinka Barrande, 1881, from the Lower Ordovician of Öland, Sweden (after Soot-Ryen 1969, length of specimen about 20 mm). B. Left valve of Palaeoneilo musculosa (Knod, 1908) from the Devonian of Bolivia (after Babin and Farjat 1994, length of specimens about 20 mm). C, D. Sketches in apical view showing asymmetry between pedal muscle scars (black) on internal molds of Palaeoneilo musculosa between left and right valves, and variation in pattern of pedal muscle between specimens (after Babin and Farjat 1994). Abbreviation: am, anterior adductor muscle scar.

Fig. 8 in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 8. Muscle scars on internal moulds of helcionelloids. All sketches oriented in lateral view with the apex to the right. A. Vendrascospira frykmani Peel and Kouchinsky, 2022 (after Peel 2023). B. Anhuiconus microtuberus Zhou and Xiao, 1984 (after Parkhaev 2002). C. Hensoniconus siku (Peel and Kouchinsky, 2022) (after Peel 2023). D. Bemella communis Parkhaev, 2001 showing three pairs of muscle scars (black, after Parkhaev 2014b); Li et al. 2021) considered the two pairs of scars on the supra-apical surface (joined by grey) to be traces of a single pair of scars. E. Yochelcionella (based on outline of Yochelcionella ostentata Runnegar and Jell, 1974) showing pair of apical muscle scars described by Vendrasco et al. (2010) in Yochelcionella snorkorum Vendrasco, Porter, Kouchinsky, Li, and Fernandez, 2010. F. Eotebenna danica sp. nov., with multiple scars forming a muscle attachment area at the apex.

Fig. 6 in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 6. Surface textures on internal mould of a helcionelloid mollusc Vendrascospira frykmani Peel and Kouchinsky, 2022, PMU 39208 from GGU sample 271492, Henson Gletscher Formation, Løndal, Peary Land, North Greenland, Miaolingian, middle Cambrian. A1. Lateral view with one muscle attachment scar from each of the two pairs of muscle scars (arrows). A2. Dorsal view showing pair of symmetrically placed muscle scars (arrows) on the supra-apical surface (right side of A1). The muscle scars lie on each side of the median area with botryoidal surface texture. A3. Detail of muscle scar (left scar in A1). A4. Detail of finely imbricate shell structure from the median area of A2.

Fig. 3. Helcionelloid mollusc Eotebenna viviannae Peel, 1991a in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 3. Helcionelloid mollusc Eotebenna viviannae Peel, 1991a, internal moulds, Andrarum Limestone, Bornholm, Denmark, Guzhangian, Miaolingian, middle Cambrian. A. MGUH 19565, paratype, lateral view (A1) with detail of apex (A2). B. MGUH 34273, lateral (B1) and apico-lateral views showing impression of comarginal ornamentation and cylindrical form of median sub-apical area (B2). C. Specimen lost, lateral view (C1) with detail of apex (C2), arrow locates detail of shell structure (C3). D. MGUH 34274, lateral view with detail of radial fibrous structure and overlying imbricated lamellae (D2), and patch of ornamented outer shell (D1, arrow). E. MGUH 34275, lateral view with detail of apex (E2) with muscle scars; arrows locate possible muscle scar. F. MGUH 34276, lateral view (F1) with detail of possible muscle scar (F2) located by arrows.

Fig. 2. Helcionelloid mollusc Eotebenna viviannae Peel, 1991a, MGUH 19564 in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 2. Helcionelloid mollusc Eotebenna viviannae Peel, 1991a, MGUH 19564, holotype, internal mould, Andrarum Limestone, Bornholm, Denmark, Guzhangian, Miaolingian, middle Cambrian. A1. Oblique lateral view showing margin of shell (arrow) along the narrow slit joining the sub-apical and supra-apical apertures. A2. Oblique apico-lateral view. A3. Lateral view. A4. Oblique view showing inverted teardrop-shaped sub-apical aperture and irregular area (arrow) of possible muscle scar. A5. Lateral view of apex. A6. Oblique lateral view of apex showing radial fibrous structure beneath smooth outer layer.

Fig. 1. Geological and geographical background. A in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 1. Geological and geographical background. A. Cambrian stratigraphy of southern Bornholm, Denmark (based on Nielsen and Schovsbo 2007). B. Map of the Baltic area showing location of Bornholm, with location of studied locality (asterisk) on the rivulet Øleå (C), and the Lake Vänern area in southern Sweden (D), with collection locality on the western slopes of the hill Kinnekulle (asterisk).

Fig. 4 in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 4. Helcionelloid mollusc Eotebenna danica sp. nov., internal moulds, Andrarum Limestone, Bornholm, Denmark, Guzhangian, Miaolingian, middle Cambrian. A. MGUH 34277, lateral view (A1) with rectangles indicating location of Fig. 5B1, B2, and B3. Muscle scars at apex illustrated in different orientations (A2–A6), with arrow in A2 indicating slight diagenetic compression or deformation along edge of muscle field. Arrow in A3 indicating imbricated lamellar structure shown in detail in A4. B. MGUH 34278, apex in lateral view. C. MGUH 34279, lateral view. D. MGUH 34280, holotype, lateral (D1) and apico-lateral (D2) views, the latter showing the laterally compressed shell form, with detail of apical muscle scars (D3). E. MGUH 34281, lateral view. F. MGUH 34282, apex in lateral view. pontifex Runnegar and Jell, 1976, from the Currant Bush southern Freuchen Land, North Greenland is more strongly Limestone (Miaolingian) of Queensland, Australia, is also coiled than Eotebenna danica, with a convex supra-apical much more elongate than Eotebenna danica but the massive surface, in lateral view, and the apex strongly overhanging snorkel is circular in cross-section compared to the inverted the sub-apical surface (Peel 1989, 1991b). teardrop-shape in the two Bornholm species. Eotebenna arctica Peel, 1989, from the Henson Gletscher Stratigraphic and geographic range.—Drumian of Sweden Formation (uppermost Series 2, Stage 4, lower Cambrian) of and Guzhangian of Denmark (both middle Cambrian).

Fig. 5 in Muscle attachment scars in helcionelloids from Denmark cast light on mollusc evolution in the Cambrian

Fig. 5. Helcionelloid mollusc Eotebenna danica sp. nov. from Miaolingian, middle Cambrian A. MGUH 34283, internal mould with traces of comarginal ornamentation and rugae (arrow), western slopes of Kinnekulle, southern Sweden, Drumian. B. MGUH 34277, details of shell structure, Andrarum Limestone, Bornholm, Denmark, Guzhangian (general view of the specimen in Fig. 4A). Surface of internal mould (B1) digitally inverted and mirrored here (B2) to depict shell structure on the interior surface of the shell. Detail of imbricate lamellae on internal mould (B3).

FIGURE 1. Translucent 3D in Calcite precipitation forms crystal clusters and muscle mineralization during the decomposition of Cambarellus diminutus (Decapoda: Cambaridae) in freshwater

FIGURE 1. Translucent 3D-models of Cambarellus diminutus sample C7tank in combination with 3D-models of calcite clusters, which precipitated inside the carcass during its decomposition in freshwater. 1.1 3D-model without calcite clusters on day 1. 1.2 3D-model on day 2 showing a small amount of calcite clusters inside the cephalothorax and the first tergite. 1.3 3D-model on day 4 showing a lot of calcite clusters inside the antennules, the left major propodus, the rostrum, the cephalothorax, the tergites, the uropods, and the telson. 1.4 3D-model on day 7, showing widespread calcite clusters at the inner side of the carapace of the carcass except the dorsal side of the cephalothorax and the tergites (see also Figure.4.1). 3D-models were reconstructed based on µ-CT data.

FIGURE 6. 3D in Calcite precipitation forms crystal clusters and muscle mineralization during the decomposition of Cambarellus diminutus (Decapoda: Cambaridae) in freshwater

FIGURE 6. 3D-models and SEM-images of sample C3tank. 6.1 3D-model of the whole crayfish in dorso-lateral view. 6.2 3D-model of the chela of the first left pereiopod in combination with a SEM-image of the calcified muscle of the dactyl. 6.3 SEM-image of a calcified muscle from the inside of the dactyl of the chela of the first left pereiopod. 3Dmodels were reconstructed based on µ-CT data.

FIGURE 5 in Calcite precipitation forms crystal clusters and muscle mineralization during the decomposition of Cambarellus diminutus (Decapoda: Cambaridae) in freshwater

FIGURE 5. SEM-images of several diverse calcite structures which precipitated inside the carcasses. 5.1 Bispherical structure with mineralized setae and a part of the cuticle layers. 5.2 and 5.3 Spherical structures. 5.4 Elliptical structure which is tapering at the left side. 5.5 Complex structure. 5.6 Bispherical structure with mineralized setae and a part of the cuticle layers.

FIGURE 8 in Calcite precipitation forms crystal clusters and muscle mineralization during the decomposition of Cambarellus diminutus (Decapoda: Cambaridae) in freshwater

FIGURE 8. Hypothetical scenarios of calcium dissolution and precipitation of calcite clusters inside decomposing crayfish without (8.1-2) and with gastroliths in tank water (8.3-4). 8.1 Low pH-values around and inside the carcass caused by an enzymatic self-digestion (autolysis) and bacterial activity release dissolved calcium ions which migrate out of the carapace into the body cavity and into the environment (red arrows). 8.2 Increase of the pH-value inside the carcass caused by microbial activities during the putrefaction result in a precipitation of calcite clusters at the inner side of the carapace, consisting of previously dissolved calcium ions out of the cuticle layers. 8.3 Low pH-values around and inside the carcass caused by enzymatic self-digestion (autolysis) and bacterial activity resulted in an accumulation of dissolved calcium ions (red arrows). In addition, low pH conditions inside the stomach and decay of the "gastrolith-cavity-membrane" resulted in dissolving calcium ions from the gastroliths. 8.4 An increase of the pHvalue inside the carcass, along the inner side of the carapace, caused by microbial activities during the putrefaction resulted in a precipitation of calcite clusters by previously dissolved calcium ions out of the cuticle layers and gastroliths.

FIGURE 7 in Calcite precipitation forms crystal clusters and muscle mineralization during the decomposition of Cambarellus diminutus (Decapoda: Cambaridae) in freshwater

FIGURE 7. Representative Raman spectra of a mineralized muscle of Cambarellus diminutus (sample C3tank) and observed crystal clusters compared to Raman reference spectra of crystalline calcite and apatite, taken from the RRUFF Raman data base (*R040170, #R060070, Laetsch and Downs, 2006). Raman spectra of the mineralized muscle as well as of the crystal cluster exhibit all main Raman bands typically observed in well crystallized calcite, including the lattice modes, which are absent in amorphous calcium carbonate (Wang et al., 2011).