118 research outputs found
Comparative anatomy of nitrergic intrinsic choroidal neurons (ICN) in various avian species
No full textIntrinsic choroidal neurons (ICN) represent a peculiar feature of eyes in higher primates and birds. They account for up to 2000 in human and duck eyes but are virtually absent or rare in all other mammalian species investigated so far. It has been suggested that ICN are involved in regulation of ocular blood supply, hence influencing intraocular pressure, and changes in choroidal thickness, thus influencing accommodation. The present study was undertaken in order to compare differences in various avian species with respect to ICN as well as to provide data on some avian species relevant for experimental ophthalmic research, i.e. chicken and quail. Choroids from 12 avian species were processed for NADPH-diaphorase histochemistry or, in some cases, neuronal nitric oxide synthase immunocytochemistry. ICN were quantified and normalized to mean choroidal area. Three choroids of each galliformes (i.e. chicken, quail, turkey) and anseriformes (i.e. Muscovy duck, Mallard duck, goose) were rastered in squares of 1 mm(2) and x/y coordinates were transferred into a 3D-diagram with the amount of ICN represented in the z-axis. ICN were detected in all species investigated. They were predominantly small cells with soma diameters of 20-30 mum. In turkey, and to a lesser amount in chicken, a subpopulation of ICN with somal diameters of up to 70 mum was observed. Highest mean cell counts were found in goose (6195(.)4; turkey 3558(.)4; chicken 1681(.)4; Muscovy duck 785(.)4; Mallard duck 640(.)8; quail 440(.)2). Normalized to choroidal area, highest mean cell counts were (per mm(2)): 12(.)62 in goose, 4(.)42 in both chicken and turkey, 2(.)86 in quail, 2(.)66 in Mallard duck and 1(.)89 in Muscovy duck. In galliformes, ICN were found to be accumulated temporo-cranial, while in anseriformes they were arranged in a more belt-like fashion, passing from cranio-nasal to temporo-caudal. Our results show that besides Muscovy duck, other avian species appear as suitable models for further functional experiments on ICN. The temporo-cranial accumulation of ICN in galliformes and the belt-like arrangement in anseriformes may reflect special functional requirements in regions of high visual acuity. (C) 2003 Elsevier Ltd. All rights reserved
Somatostatin immunoreactivity in quail pterygopalatine ganglion
No full textIn the ciliary ganglion of the chicken and quail, somatostatin (SOM) is an exclusive marker for parasympathetic postganglionic neurons innervating the choroid. A second parasympathetic pathway projecting to the choroid originates from the pterygopalatine ganglion. The aim of this study was to investigate SOM immunoreactivity in the pterygopalatine ganglion of the Japanese quail (Coturnix coturnix japonica) and on neurons within the choroid, the intrinsic choroidal neurons (ICN). We did so using immunohistochemistry and subsequent light, electron and confocal laser scanning microscopy. Pterygopalatine neurons were characterized by nNOS-immunohistochemistry or NADPH-diaphorase cytochemistry. SOM immunoreactivity was absent in the perikarya, but neurons were densely surrounded by SOM-positive nerve fibres. Electron microscopy revealed that these fibres formed contacts with and without membrane specializations on pterygopalatine neurons. In the choroid, neuronal nitric-oxide synthase (nNOS)-immunoreactive ICN were likewise closely apposed by SOM-immunoreactive nerve fibres, as revealed by confocal microscopy. There was no detectable co-localization of the markers. In the absence of tracing studies, it is open to speculation whether SOM immunoreactivity originates from preganglionic fibres of the superior salivatory nucleus, postganglionic fibres of the ciliary ganglion or fibres of the brainstem via as yet unknown pathways. SOM may regulate the production of NO in pterygopalatine neurons and ICN, respectively, and is therefore involved in neuronal circuits regulating ocular homeostasis
Calbindin D28k-Immunoreactivity in Human Enteric Neurons
No full textCalbindin (CALB) is well established as immunohistochemical marker for intrinsic primary
afferent neurons in the guinea pig gut. Its expression by numerous human enteric neurons has
been demonstrated but little is known about particular types of neurons immunoreactive for CALB.
Here we investigated small and large intestinal wholemount sets of 26 tumor patients in order to
evaluate (1) the proportion of CALB+ neurons in the total neuron population, (2) the colocalization
of CALB with calretinin (CALR), somatostatin (SOM) and vasoactive intestinal peptide (VIP) and
(3) the morphology of CALB+ neurons. CALB+ neurons represented a minority of myenteric neurons
(small intestine: 31%; large intestine: 25%) and the majority of submucosal neurons (between 72
and 95%). In the submucosa, most CALB+ neurons co-stained for CALR and VIP (between 69 and
80%) or for SOM (between 20 and 3%). In the myenteric plexus, 85% of CALB+ neurons did not
co-stain with the other markers investigated. An unequivocal correlation between CALB reactivity
and neuronal morphology was found for myenteric type III neurons in the small intestine: uniaxonal
neurons with long, slender and branched dendrites were generally positive for CALB. Since also
other neurons displayed occasional CALB reactivity, this protein is not suited as an exclusive marker
for type III neurons
Morphological and Immunohistochemical Characterization of Human Intrinsic Gastric Neurons
No full textOur knowledge about human gastric enteric neuron types is even more limited than that of human intestinal types. Here, we immunohistochemically stained wholemounts and sec-
tions of gastric specimens obtained from 18 tumor-resected patients. Myenteric wholemounts were labeled for choline acetyl transferase (ChAT), neuronal nitric oxide synthase (NOS), and the human neuronal protein HuC/D (as panneuronal marker for quantitative analysis) or alternatively for neurofilament (for morphological evaluation). ChAT-positive neurons outnumbered NOS-positive neurons (56 vs. 27%), and neurons negative for both markers accounted for 17%. Two larger groups of neurons (each between 12 and 14%) costained for ChAT and vasoactive intestinal peptide (VIP) or for NOS and VIP, respectively. Clear morphochemical
correlation was found for uniaxonal stubby type I neurons (ChAT+; putative excitatory inter- or motor neurons), for uniaxonal spiny type I neurons (NOS+/VIP+; putative inhibitory motor or interneurons), and for multiaxonal type II neurons
(ChAT+; putative afferent neurons; immunostaining of ad-
ditional wholemounts revealed their coreactivity for soma-
tostatin). Whereas these latter neuron types were already known from the human intestine, the morphology of gastric myenteric neurons coreactive for ChAT and VIP was newly described: they had numerous short, extremely thin dendrites and resembled, together with their cell bodies, a “hairy” head. In our sections, nerve fibers coreactive for ChAT and VIP were commonly found only in the mucosa. We suggest these myenteric ChAT+/VIP+/hairy neurons to be mucosal effector neurons. In contrast to myenteric neurons, the much less common submucosal neurons were not embedded in a continuous plexus and did not display any clear morphochemical phenotypes
Immunhistochemische und morphologische Klassifizierung submuköser Neuronen im menschlichen Darm
No full textZusammenfassung
Hintergrund und Ziele
Das Enterische Nervensystem (ENS) des Menschen setzt sich aus mehreren ganglionären Nervengeflechten, dem Plexus myentericus und den beiden Plexus submucosus, zusammen. Zum besseren Verständnis von Funktion und Pathologie des ENS ist es essenziell, immunhistochemisch und morphologisch unterscheidbare Subpopulationen von Neuronen zu charakterisieren. Im Plexus myentericus sind entsprechende Untersuchungen fortgeschritten. Hier sollen dagegen neuronale Subpopulationen im Plexus submucosus untersucht werden. Es werden hierzu unsere eigenen Studienergebnisse (Beyer et al., 2013) vorgestellt und mit denen von späteren Arbeiten anderer Autoren in einem aktuellen Kontext diskutiert.
Methoden
Wir untersuchten submuköse Häutchen- und Schnittpräparate aller Segmente des Dünn- und Dickdarms von 23 Körperspendern oder Patienten post operationem. Diese wurden 4-fach immunhistochemisch gefärbt für Calretinin (CALR), Somatostatin (SOM), Cholin-Acetyltransferase (ChAT) und Substanz P (SP) sowie für Peripherin (PER; morphologische Analyse). In späteren Studien wurde zudem auf Immunoreaktivität für vasoaktives Peptid (VIP) und neuronale Stickstoffmonoxid-Synthase (NOS) getestet.
Ergebnisse und Beobachtungen
In der Submukosa des menschlichen Darmes existieren mindestens zwei Hauptgruppen von Neuronen: SOM- und CALR- Neuronen sowie vermutlich mindestens eine weitere, kleinere, nitrerge Population.
SOM-Neuronen sind ko-immunoreaktiv für ChAT sowie fakultativ für SP, sie sind morphologisch unipolar, d.h. nicht-dendritisch und (pseudo-)uniaxonal, ihre Axone projizieren in die Mukosa, sie sind möglicherweise afferente Neuronen.
CALR-Neuronen sind ko-immunoreaktiv für VIP sowie fakultativ für ChAT, sie sind multidendritisch und uniaxonal und projizieren vornehmlich in die Mukosa. Sie scheinen eine wichtige Rolle bei der Aufrechterhaltung der mukösen Barriere zu spielen.
Eine dritte, sehr kleine Population ist NOS-immunoreaktiv, sie war jedoch nicht in allen Präparaten nachweisbar und wurde bislang nicht näher untersucht. Weitere, nicht-cholinerge Subpopulationen werden vermutet.
Schlussfolgerung
Wie auch myenterische Neuronen können humane submuköse Nervenzellen morphochemisch differenziert werden. Vierfach-Immunfärbungen erlaubten es, mindestens zwei verschiedene Neuronenpopulationen in der menschlichen Mukosa zu charakterisieren. Die eine ist ko-immunoreaktiv für SOM, ChAT und (teils) für SP, diese Neuronen sind non-dendritisch und (pseudo-)uniaxonal. Die andere Population ist ko-reaktiv für CALR, VIP und ChAT, die Zellen sind multidendritisch und uniaxonal. Mögliche weitere Populationen bleiben zu differenzieren, um ein besseres Verständnis sowohl der physiologischen als auch der pathologisch veränderten nervalen Steuerung muköser Funktionen zu erlangen
Therapieentscheidung bei Bandscheibenvorfällen der Lendenwirbelsäule mit künstlicher Intelligenz
No full textHintergrund und Ziele
Für Patienten im Graubereich zwischen konservativer und operativer Behandlung ist
die Studienlage nicht eindeutig. Sehr viele Patienten fallen in eben diesen Bereich: Einerseits
sind in der Frühphase nach ihrem Bandscheibenvorfall die Beschwerden nicht
so stark, dass eine eindeutige OP Indikation vorliegt. Andererseits sind die vorliegenden
Beeinträchtigungen zu schwerwiegend, als dass der Erfolg einer konservativen
Therapie zuverlässig vorhergesehen werden kann. Unser Ziel ist in diesen Fällen einen
frühzeitigen Hinweis auf die richtige Therapiemöglichkeit zu erhalten. Deshalb wurde
untersucht, ob Deep Learning Algorithmen helfen können, eine Entscheidung für die
erfolgreiche Behandlung frühzeitig zu treffen.
Methodik
Die Daten von 139 Patienten wurden in einer laufenden Beobachtungsstudie erhoben.
Diese wurden genutzt, um ein state-of-the-art Deep learning Algorithmus zu implementieren.
Es wurde ein Ansatz von überwachtem Lernen geschaffen. Dabei wurden mehrere
Möglichkeiten der Feature Selection getestet, um das bestmögliche Ergebnis zu
erzielen. Ziel hierbei war die Vorhersage des ODI in Abhängigkeit der Behandlung im
Zeitverlauf. Ein niedriger ODI spricht für einen guten Behandlungserfolg.
Ergebnisse und Beobachtungen
Unsere Ansätze waren von unterschiedlichem Erfolg. Der Beste mithilfe der K-Best Selektion
der Daten performte mit mittleren absoluten Abweichungen von sieben bis zehn
für jeden der Untersuchungswerte. Die ausgewählte Behandlungsoption des Testpatienten
konnte mit der entsprechend gegensätzlichen verglichen werden.
Diskussion und Schlussfolgerung
Deep learning kann auch im Bereich der Wirbelsäulenchirurgie verwendet werden, um
unnötig lange Schmerzverläufe für zunächst konservativ behandelte Patienten zu vermeiden.
Gleichzeitig können überflüssige Operationen vermieden werden. Für die Zukunft
bestehen noch ausreichend Möglichkeiten, den Algorithmus mit mehr Informationen
zu versorgen, um eine weitere Verbesserung zu erreichen. Durch die Arbeit wurde
eine Möglichkeit geschaffen, eine Entscheidung zwischen zwei Behandlungsmethoden
besser treffen zu können. Dies kann in Zukunft auch auf andere Felder der Medizin
übertragen werden.Purpose
For patients in the gray area between conservative and surgical treatment, the study
situation is not finally resolved. Many patients fall into this category: On the one hand, in
the early phase after their herniated disc, the symptoms are not so severe that there is a
clear indication for surgery. On the other hand, the existing impairments are too severe
for the success of conservative therapy to be reliably predicted. Our goal in these cases
is to obtain an early indication of the best therapy option. Therefore, we investigated
whether deep learning algorithms can help to make an early decision for successful
treatment.
Methods
Data from 139 patients were collected in an ongoing observational study. These were
used to implement a state-of-the-art deep learning algorithm. An approach of supervised
learning was chosen. We tested several possibilities to train a model. The goal was
to predict the Oswestry Disability Index (ODI) as a function of treatment over time. A low
ODI indicates a good treatment success.
Results and Observations
Our approaches were of variable success. Our best approach using K-best selection
of the data performed with mean absolute error of seven to ten for each of the study
values. The selected treatment option of the test patient could be compared with the
corresponding opposite one.
Discussion and Conclusion
Deep learning can also be used in the field of spine surgery to avoid unnecessarily long
pain courses for conservatively treated patients. At the same time unnecessary surgeries
can be avoided. For the future there are still possibilities to provide our algorithm
with more information in order to achieve a further improvement. Our work has created
a possibility to make a better decision between two treatment methods. This can be
transferred to other fields of medicine in the future
Classification of human enteric neurons
No full textMajor advances in our understanding of the functional heterogeneity of enteric neurons are driven by the application of newly developed, innovative methods. In contrast to this progress, both animal and human enteric neurons are usually divided into only two morphological subpopulations, “Dogiel type II” neurons (with several long processes) and “Dogiel type I” neurons (with several short processes). This implies no more than the distinction of intrinsic primary afferent from all other enteric neurons. The well-known chemical and functional diversity of enteric neurons is not reflected by this restrictive dichotomy of morphological data. Recent structural investigations of human enteric neurons were performed by different groups which mainly used two methodical approaches, namely detecting the architecture of their processes and target-specific tracing of their axonal courses. Both methods were combined with multiple immunohistochemistry in order to decipher neurochemical codes. This review integrates these morphological and immunohistological data and presents a classification of human enteric neurons which we believe is not yet complete but provides an essential foundation for the further development of human gastrointestinal neuropathology
Classification of human enteric neurons
No full textMajor advances in our understanding of the functional heterogeneity of enteric neurons are driven by the application of newly developed, innovative methods. In contrast to this progress, both animal and human enteric neurons are usually divided into only two morphological subpopulations, 'Dogiel type II' neurons (with several long processes) and 'Dogiel type I' neurons (with several short processes). This implies no more than the distinction of intrinsic primary afferent from all other enteric neurons. The well-known chemical and functional diversity of enteric neurons is not reflected by this restrictive dichotomy of morphological data. Recent structural investigations of human enteric neurons were performed by different groups which mainly used two methodical approaches, namely detecting the architecture of their processes and target-specific tracing of their axonal courses. Both methods were combined with multiple immunohistochemistry in order to decipher neurochemical codes. This review integrates these morphological and immunohistological data and presents a classification of human enteric neurons which we believe is not yet complete but provides an essential foundation for the further development of human gastrointestinal neuropathology
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