The crystal structure of nylon 6 (NH (CH2)5CO)p has been determined by interpretation of the x‐ray diffraction patterns given by drawn, rolled fibers. The determination was part of a program to investigate the relation between structure and physical properties, in particular melting point. Nylon 6 melts 50°C. lower than its isomer nylon 66 (NH (CH2)6NH·CO (CH2)4CO)p; it had been suggested that this was due to deficient hydrogen‐bond formation in nylon 6 crystallites. The unit cell contains eight chemical units (NH (CH2)5CO) and is monoclinic with a = 9.56 A., b = 17.24 A., c = 8.01 A., and β = 671/2°. Calculated density = 1.23. Observed density for a drawn monofilament = 1.16. The structure consists of planar chains of CH2 groups and amide groups tilted 7° from the (001) plane. Alternate chains in this plane are oppositely directed, an arrangement which allows all hydrogen bonds to be made perfectly. The hydrogen‐bonded sheets of atoms are packed in an “up‐and‐down” staggered configuration along the c‐axis. Distances between atoms in neighboring molecules are all normal van der Waals contact distances. It appears, from a general survey of polyamide melting points published elsewhere, that the determining factor is the number of CH2 groups between the amide “anchor points”—polymers with odd numbers of CH2 groups melt lower than those with even numbers. The present work shows that the odd number of CH2 groups in this polymer does not lead to deficient hydrogenbond formation, and that the lower melting point of nylon 6 as compared with nylon 66 must be ascribed to some other cause, possibly connected with the propagation of vibrations along odd‐numbered chain segments.

Mammalian spermatozoa motility is a subject of growing importance because of rising human infertility and the possibility of improving animal breeding. We highlight opportunities for fluid and continuum dynamics to provide novel insights concerning the mechanics of these specialized cells, especially during their remarkable journey to the egg. The biological structure of the motile sperm appendage, the flagellum, is described and placed in the context of the mechanics underlying the migration of mammalian sperm through the numerous environments of the female reproductive tract. This process demands certain specific changes to flagellar movement and motility for which further mechanical insight would be valuable, although this requires improved modeling capabilities, particularly to increase our understanding of sperm progression in vivo. We summarize current theoretical studies, highlighting the synergistic combination of imaging and theory in exploring sperm motility, and discuss the challenges for future observational and theoretical studies in understanding the underlying mechanics.

Context:Adrenal tumors have a prevalence of around 2% in the general population. Adrenocortical carcinoma (ACC) is rare but accounts for 2–11% of incidentally discovered adrenal masses. Differentiating ACC from adrenocortical adenoma (ACA) represents a diagnostic challenge in patients with adrenal incidentalomas, with tumor size, imaging, and even histology all providing unsatisfactory predictive values.Objective:Here we developed a novel steroid metabolomic approach, mass spectrometry-based steroid profiling followed by machine learning analysis, and examined its diagnostic value for the detection of adrenal malignancy.Design:Quantification of 32 distinct adrenal derived steroids was carried out by gas chromatography/mass spectrometry in 24-h urine samples from 102 ACA patients (age range 19–84 yr) and 45 ACC patients (20–80 yr). Underlying diagnosis was ascertained by histology and metastasis in ACC and by clinical follow-up [median duration 52 (range 26–201) months] without evidence of metastasis in ACA. Steroid excretion data were subjected to generalized matrix learning vector quantization (GMLVQ) to identify the most discriminative steroids.Results:Steroid profiling revealed a pattern of predominantly immature, early-stage steroidogenesis in ACC. GMLVQ analysis identified a subset of nine steroids that performed best in differentiating ACA from ACC. Receiver-operating characteristics analysis of GMLVQ results demonstrated sensitivity = specificity = 90% (area under the curve = 0.97) employing all 32 steroids and sensitivity = specificity = 88% (area under the curve = 0.96) when using only the nine most differentiating markers.Conclusions:Urine steroid metabolomics is a novel, highly sensitive, and specific biomarker tool for discriminating benign from malignant adrenal tumors, with obvious promise for the diagnostic work-up of patients with adrenal incidentalomas.