Optimal cut-point of RBCadjusted (determined at day 1 after bleeding) was > 3667/µl to identify SAH patients with a 97% sensitivity and 94% specificity. Combination of low RBC and clear CSF supernatant was found in none of SAH patients. Combined CSF RBC count and CSF supernatant reliably distinguished traumatic LP from SAH.Lumbar puncture (LP) is recommended in patients with thunderclap headache and negative computed tomography to rule out spontaneous subarachnoid haemorrhage (SAH). Blood contamination of cerebrospinal fluid (CSF) due to traumatic LP poses a diagnostic dilemma. Therefore, routine CSF parameters were investigated to distinguish between SAH and a traumatic LP. CSF red blood cell (RBC), white blood cell (WBC) count, total protein, CSF colour and supernatant were used for group comparisons of patients with SAH and ‘symptomatic controls’. Due to variable time intervals between bleeding onset and LP in SAH patients in contrast to patients with traumatic LP, where blood contamination of CSF occurs at the time of LP, CSF variables were adjusted for decay in time to allow comparability. Logistic regression analysis identified bloody CSF [odds ratio (OR) 32.6], xanthochromic supernatant [OR 15.5] and WBC Cerebral computed tomography (CT) scan is the first investigation if SAH is suspected. Its diagnostic sensitivity is high in the first hours after the bleeding, but sharply decreases thereafter4. As patients frequently present hours or even days after symptom onset, lumbar puncture (LP) should be performed in case of normal CT scans to detect the low but clinically significant percentage of CT negative SAH patients5. Under physiological conditions, cerebrospinal fluid (CSF) does not contain red blood cells (RBC) and, thus, can rule out SAH. However, RBC are artificially introduced into the CSF in up to one third of patients as a result of needle trauma mostly due to puncturing spinal venous plexus6. This hampers the differentiation between patients with SAH and traumatic LP.Spontaneous subarachnoid haemorrhage (SAH) is a severe life-threating neurological disease which accounts for approximately 5–10% of all strokes and bears the risk of significant morbidity and mortality7. Furthermore, some of these biomarkers are not in wide clinical use. While different temporal dynamics of CSF biomarkers in SAH patients have been acknowledged and certain time frames defined for their detection, e.g., bilirubin > 12 h after the bleeding7, none of these studies considered that the magnitude of CSF changes might also depend on disease duration.Prior studies have investigated various CSF biomarkers to identify SAH patients, e.g., RBC count, xanthochromia, oxyhaemoglobin, methaemoglobin, ferritin or siderophages, but reported only moderate diagnostic value due to various reasonsThe objective of this study was to investigate the diagnostic value of widely available CSF parameters to discriminate patients with SAH from patients with diseases other than SAH but with traumatic LP applying a multivariable approach and considering disease duration as a covariate in particular. In addition, a literature review was conducted to provide an overview of current knowledge on the ability of CSF parameters to differentiate between SAH and traumatic LP.We have stored the results of CSF and serum sample analyses performed for routine diagnostic purposes in the Innsbruck CSF Database from patients with mainly neurological diseases. We screened for samples applying the following criteria: CSF collection by LP and sample processing within 24 h after withdrawal . Medical records of the remaining patients were studied and patients classified into a spontaneous SAH group and control group. The authors had access to information that could identify individual participants during or after data collection.Patients with spontaneous SAH were subdivided into patients with evidence of subarachnoid blood on the CT scan (termed ‘SAH’) and patients without evidence of intrathecal blood on the CT scan (termed ‘CT negative SAH’). Within the SAH and CT negative SAH group, patients with re-bleeding or ventriculitis before LP were excluded to ensure that adjustment for disease duration (see below) is not biased by these complications, which might lead to changes in RBC, WBC count and CSF total protein Fig. .Figure 18 or patients without any neurological disease were used as control group. These patients should show normal routine CSF findings . Diagnoses of the control group are given in Table Patients fulfilling the definition of ‘symptomatic controls’ according to a recent consensusPatients classified as ‘CT negative SAH’ had typical clinical presentation (thunderclap headache), normal CT scan, but further clinical/ paraclinical findings, which led to the diagnosis of ‘CT negative SAH’ by the treating physicians, e.g., MRI with evidence of bleeding, signs of erythrophagocytosis in the CSF .9. Division by 3.2 allowed reporting of cell counts per μL according to International System of units (SI). CSF total protein concentration was measured by spectrophotometry after incubation of centrifuged CSF with 3% trichloroacetic acid10. CSF colour  and CSF supernatant (clear vs. xanthochromic) were classified by visual inspection.CSF WBC and CSF RBC were counted within a Fuchs-Rosenthal chamber, which has a volume of 3.2 μLData were displayed as mean ± standard deviation (SD) or as median, interquartile range (IQR), 5th-95th percentile, as appropriate.11.11. The 11. E.g., a patient with a RBC count of 2000/μl determined in CSF collected three days after SAH onset has an RBCadjusted of 3508/μl, calculated asAs CSF of patients with SAH is usually taken hours or days after the bleeding, in contrast to patients with traumatic LP, where blood contamination of CSF occurs at the time of LP, the variables RBC count, WBC count and CSF total protein were corrected for their decay in time to make them comparable between patients. They were adjusted according to the decay law previously publishedadjusted, WBCadjusted, CSF total proteinadjusted, CSF supernatant, CSF colour, sex and age as independent variables. As sample size was small a likelihood ratio test was used to test for statistical significance of each variable.With a binary logistic regression model the probability for both SAH & CT negative SAH was modelled using RBCadjusted, using the sum of specificity and sensitivity as optimization criterion.We calculated the optimal cut-off point in the logistic regression of the probability of both SAH & CT negative SAH dependent on RBC13.The significance level was 5%. All computations were done with R Core Team (2017) and the package cutpointThe conduct of the study was approved by the Ethics Committee of the Medical University of Innsbruck . Informed consent was not needed because this was a retrospective analysis of existing data that were obtained in routine diagnostic procedures.A literature search in PubMed using the search terms “cerebrospinal fluid” AND “subarachnoid haemorrhage” AND “traumatic tap” or “red blood cell count” or “white blood cell count” or “total protein” or “opening pressure” or “three tube test” or “xanthochromia” or “colour” or “supernatant” or “ferritin” or “oxyhaemoglobin” or “bilirubin” or “methaemoglobin” limited to August 1st, 2022 offered 18, 39, 35, 80, 32, 7, 92, 25, 17, 24, 70, 119, and 17 references. Abstracts that did not primarily deal with the use of CSF to differentiate between SAH and traumatic LP were excluded. In addition, articles identified in reference lists of individual papers were selected if considered appropriate. Only original articles written in English were considered.A total of 471 samples comprising 27 patients with SAH, 5 patients with CT negative SAH and 439 controls were included in the study. For inclusion criteria see Fig. The median disease duration, i.e. the time interval from symptom onset to LP, in patients with SAH was 9 days and in patients with CT negative SAH 6 days. We adjusted RBC, WBC count and CSF total protein for the individual disease duration, i.e. the time interval from symptom onset until LP. For comparison of the measured and adjusted values, please refer to Table adjusted, WBCadjusted as well as CSF total proteinadjusted were significantly higher in SAH patients and CT negative SAH patients compared to controls. SAH patients compared to controls showed more frequently bloody CSF (97% vs. 29%) and xanthochromic CSF supernatant (84% vs. 3%) , p < 0.001] as predictors, while age, sex and CSF total proteinadjusted were not statistically significant predictors , p < 0.001] (Table adjusted count to identify SAH (both SAH and CT negative SAH) was obtained at 3667/µl , while 413 (94.1%) of 439 controls had low RBCadjusted (≤ 3667/µl). The negative predictive value (NPV) of low RBC count was 99.8% in controls, while the positive predictive value (PPV) of high RBC was 54.4% considering all SAH patients  32.6, p = 0.013], xanthochromic CSF supernatant  and WBCAH Table . In univ1] Table . An optits Table . Overallts Table .Table 2Radjusted (i.e. RBC counts adjusted for disease duration) instead of RBCmeasured resulted in an improved classification of SAH patients versus controls of 11 percentage points (Table adjusted cut-point with a previously suggested cut-point (for RBCmeasured of 2000/μl) showed an increase in this classification by 15 percentage points  and after 6 days in patients with CT negative SAH. This is in contrast to patients with traumatic LP, where blood contamination of CSF occurs at the time of LP. In patients with SAH and CT negative SAH, RBC count at the time of the bleeding was estimated from the RBC count determined at the time of LP, using the previously published decay law11 and the respective time from symptom onset, i.e. adjusting for the in vivo cell degradation over time. Indeed, the measured and adjusted variables showed considerable differences  had RBC counts above 2000/μl and/or xanthochromia15. Perry et al. included 15 CT negative SAH patients, which had LP up to 5 days after symptom onset and identified a RBC cut-off of 2450/μl14. However, both studies did not consider the different disease duration and, thus, used non-adjusted, potentially false-low RBC counts. In our study, when we used RBCadjusted or RBCmeasured as predictor of SAH versus controls, an improved classification was achieved by the RBCadjusted approach.We identified an adjusted RBC cut point of approximately 3600/μl which was higher than previously suggested cut pointsIn clinical practice, our approach would allow first to adjust the RBC count for the patient’s individual disease duration (i.e. time since symptom onset) and then to assess whether it is above or below the cut-off , instead of uncritically applying non-adjusted RBC counts, i.e. independent of disease duration, to a fixed cut-off. Despite of the obvious advantages of our approach, prospective studies are required to validate these results and to show superiority.11. However, we assume that cell degradation, which occurred in a non-linear manner, should be independent of the exact location within the CSF space and the site of the sample obtainment. Thirdly, we included CSF samples processed within 24 h after LP. Longer intervals to laboratory processing might result in decreased RBC and WBC count9. This means that shorter processing time would have led to higher RBC cut-off values. As the main conclusion of our study is that patients with RBC count below the cut-off are most likely traumatic LP, higher RBC cut-off would not impair the negative predictive values. Furthermore, we were not able to consider other CSF parameters such as bilirubin, or the “three-tube test” in our multivariable analysis, as we did not routinely perform or document these measurements. Also, some of the patients had an intervention (i.e. either coiling or clipping) before CSF withdrawal. It cannot be excluded that this had an influence on CSF parameters. We have to state that we adjusted CSF parameters in our analyses for a fixed disease duration of one day in SAH patients; an earlier time point would not be valid, as we also considered CSF supernatant, and colour change (into xanthochromia) needs at least 12 h as bilirubin has to be formed in vivo. Considering the disease duration within the SAH group of median 7.5 days (3. quartile: 16 days), it might be that at a different (earlier) time point of LP, a higher percentage of SAH patients would have shown CSF xanthochromia. However, it is not possible to adjust the variable “CSF xanthochromia” for disease duration, as in case of a negative status, a positive status before cannot be extrapolated. This means that the diagnostic value of CSF supernatant might have been underestimated. Another limitation of our study is that we could only include 5 patients with CT-negative SAH, therefore, the results on CT-negative SAH patients  need to be replicated by further studies.There are some limitations to our study. First, this was a retrospective study with all inherent limitations. Secondly, the decay rates used to adjust CSF parameters for individual disease duration were estimated in longitudinally collected CSF obtained by ventricular drainage53 cannot be excluded, the herein applied criterion (of an adjusted RBC count of less than 3667/μl combined with clear CSF supernatant) identified only patients with traumatic LP and none of the SAH patients. It has to be clearly stated that in case of high RBC counts and/ or xanthochromia, the differentiation between SAH and traumatic LP is still not reliable. Altogether, we think that the results of our study contribute to further understanding. Correct interpretation of CSF findings is of utmost importance, as SAH—if misdiagnosed—is a severe neurological disease with significant morbidity and mortality.Altogether, we present a tool, which has the potential to be widely used in clinical practice, to identify patients with traumatic LP by RBC count and inspection of CSF supernatant. Even though assessment of CSF supernatant is rater-dependent and anecdotal reports of SAH in patients with very low RBC countsSupplementary Tables.


In this study, we investigated whether predation pressures in the early life history of frogs can result in an anuran-affect behavior response in the later stages of their life history. Tadpoles that undergo predation pressure possess smaller body sizes, slower development rates, and broader caudal fins. In particular, juvenile frogs that undergo predation pressure from the tadpole stage also metamorphosize later, develop longer limbs, narrower skulls, and demonstrate other finer changes in the skeleton of the lower body. On this note, we predicted that this would change the locomotory performance of such juvenile frogs in terms of their swimming and jumping speed, but such an eventuality did not take place. It appears, then, that predation pressure in the early life history of frogs does not alter their jumping and swimming speed abilities. Moreover, such a fact suggests that this morphological change may not be a predator-adaptive response.Anax parthenope) on the phenotypical change of tadpoles into juvenile frogs , and also analyzed the impact of morphological changes on locomotory performance after metamorphosis. The experiments on predator impact were conducted in the laboratory. Body length, weight, development timing, and metamorphosis timing in the presence of dragonfly nymphs were measured in both tadpoles and juvenile frogs. The body and tail shapes of the tadpoles, as well as the skeletal shape of the juvenile frogs, were analyzed using landmark-based geometric morphometrics. Furthermore, the locomotory performance of the juvenile frogs was tested by measuring their jumping and swimming speeds. Tadpoles that had grown with predators possessed smaller bodies, deeper tail fins, and slower development rates, and they waited longer periods of time before commencing metamorphosis. Having said this, however, the effect of predator cues on the body length and weight of juvenile frogs was not found to be significant. These juvenile frogs possessed longer limbs and narrower skulls, with subtle morphological changes in the pelvis and ilium, but there was no subsequent difference in their swimming and jumping speeds. Our results showed that the changes in anatomical traits that can affect locomotor performance are so subtle that they do not affect the jumping or swimming speeds. Therefore, we support the view that these morphological changes are thus by-products of an altered tadpole period, rather than an adaptive response to predator-escape ability or to post-metamorphosis life history. On the other hand, delayed metamorphosis, without an increase in body size, may still be disadvantageous to the reproduction, growth, and survival of frogs in their life history following metamorphosis.Anuran species can respond to environmental changes via phenotypic plasticity, which can also result in ecological impacts across the life history of such species. We investigated the effects of predation pressure  from the dragonfly larva ( Phenotypic plasticity is the ability of an organism to produce a suitable phenotype in response to the environmental variability that is present in their habitats; furthermore, such a response can influence the survival or reproduction of a species . Among tPhenotypic plasticity does not occur within only one stage of the life cycle. A plastic response can be induced and combined at multiple ontogenetic stages of development; in addition, it can also result in either a temporary or lasting effect. For example, the loss of tail tissue in tadpoles can lead to smaller frogs after their metamorphosis . AdditioThe plastic responses may be more complicated due to the fact that, unlike other vertebrates, most anurans experience metamorphosis when maturing from tadpoles into adult frogs. Among the various plastic responses, the most important source of variability in tadpoles is the difference in the rate of metamorphosis with respect to environmental factors. The rate of metamorphosis can be changed by various environmental factors or stressors, such as the source of variability in water level, the protein composition of food, intra- or interspecific competition, the presence of predators, and chemical contamination  that alter the metamorphosis period of the black-spotted pond frog (Pelophylax nigromaculatus). The dragonfly larva persists usually alongside the tadpoles of black-spotted pond frogs from South Korea; moreover, the dragonfly larva is a predator that directly consumes tadpoles. We assumed that juvenile frogs, who were subjected to predation pressure in their respective tadpole periods, would experience changes in their skeletal morphology, as well as changes in their locomotory performance after metamorphosis. As such, we identified the differences in metamorphosis and growth speed that took place under the influence of predation pressure, and quantified the tail shape of a tadpole, as well as the skeletal shape of a juvenile frog by utilizing landmark-based geometric morphometrics, in order to compare the morphology. The jumping and swimming speeds of frogs were also analyzed in order to determine the difference in locomotor performance.We investigated whether the changes in locomotor performance, mediated by modifications in anatomical features post metamorphosis, are influenced by the presence of predators  is a semiaquatic pond frog, widely distributed in Korea, China, Japan, and far-eastern Russia [The black-spotted pond frog ; in addition, the number of masses per site was five a. It wasi by the process of confirming that certain genetic material is derived from a common ancestor K. Each analysis consisted of 100,000 simulations, following the burn-in of 100,000 simulations. The STRUCTURE Harvester [The genome DNA of the toe samples was extracted using DNeasy Blood and Tissue kits , according to the manufacturer’s protocol. In total, seven primers  were used in order to amplify the microsatellite loci of the frogs, according to previously reported procedures . In addiarvester  was usedarvester  for the The frog egg clutches were transported to the laboratory in plastic boxes. They were then raised in clear water for 15 days. Tadpoles from the five egg clutches in each collection site were raised together in a single container. After hatching, we randomly extracted 60 tadpoles per collection site that had hatched on the same day; further, they were kept in separate cages. A total of 360 tadpoles were used in the experiment. Until the end of the experiment, all tadpoles were bred in a container (460 mm × 300 mm × 170 mm) with 10 L of water and air generators that operated under a 12 h/12 h light/dark regime, with 3 W LED light; lastly, the air temperature was maintained at 23 ± 1 °C. Dog food  was used to feed the tadpoles, and an amount equivalent to about 3% of the tadpole weight was supplied every 3 days. Leftover food was removed the next day and the water was only half changed once a week. The water level was checked daily and kept constant until the end of the experiment. When we found that the tail of the tadpoles was absorbed , we placed a floating piece of plastic in each container. The experimental procedures and animal maintenance were performed in accordance with the regulations and approval of the Experimental Animal Ethics Committee of Kongju National University (KNU_2019-01).When the external gills of hatchlings disappeared and the internal gills of tadpoles began to appear , 60 tadpoles were divided into two groups of 30 individuals each (a set); furthermore, one group was indirectly  exposed to the predator (predation group), whereas the other group was not exposed to the predator (control group). A total of six sets were made, four sets of which were used for the experiment, and two sets were left as spare sets for the purposes of supplement when tadpoles died in the experiment sets.Anax parthenope). The tadpoles were separated from the dragonfly larva area by a segregation compartment. However, this was a segregation compartment that still allowed the flow of chemical and visual cues by the dragonfly larva. Further, the dragonfly larvae were fed separately reared tadpoles of the same species, supplied every other day. In order to minimize the spatial impact, a separate compartment (where there were no predators) was also placed in the container of the control group.The plastic container had a separation compartment that contained the dragonfly larva (t-test.We collected five tadpoles from each container in order to confirm that there was no difference in the length and weight of tadpoles between the predation group and control group at the start of the experiment (Gosner stage 26). We tapped the collected tadpoles with a piece of gauze in order to remove moisture. The side of the tadpole was photographed for the purposes of length measurement. The body length of the collected tadpoles was measured from snout to tail tip by using the ImageJ software . The weiWe assessed the developmental condition of the tadpoles daily, removed the tadpoles that reached Gosner stage 39, photographed the side of the tadpole by following the same methodology described, and measured their weights. The collected tadpoles were removed from the containers, and the length, weight, and time to reach Gosner stage 39 were calculated in order to determine the growth status and development rate of the tadpoles. Five tadpoles (Gosner stage 39) were collected from each container . Then, we analyzed for side photos, length, and the weight of collected tadpoles in the same process as mentioned above. Further, it must be noted that the analyzed tadpoles were not returned to the container.In addition to the above, we measured the length, weight, and the rate of metamorphosis regarding the juvenile frogs after metamorphosis. Five juvenile frogs (Gosner stage 46) were collected in each container . The juvenile frogs were removed under the following conditions: frogs that died if maintained for two days after metamorphosis; frogs that did not exhibit a clear skeletal shape on an X-ray film. Thus, 13 juvenile frogs per group were used for the purposes of data analysis. The length of the juvenile frogs was measured according to a snout–vent length, to the nearest 0.01 mm, by using a digital caliper. In addition, the weight of the frogs was measured, to the nearest 0.001 g, by utilizing a digital balance. After the length and weight measurements, the juvenile frogs were transferred to separate containers (460 mm × 300 mm × 170 mm), which contained both land and clear water. Furthermore, these containers were maintained for 48 h and then used in experiments in order to compare locomotor performance. We then summarized the process of this experiment graphically .We prepared two glass tanks (600 mm × 500 mm × 450 mm) for the purposes of measuring the jumping and swimming performances. One glass tank was used in order to observe the jumping of the frogs. Further, the other glass tank was used to observe the swimming of the frogs. The two glass tanks were all covered with white paper, except for the top. Furthermore, a styrofoam land was fixed on one side in a glass tank that was designed to observe swimming. The water was filled to a water level of about 10 cm. The lighting was manufactured using 3 W LED light. A digital camera  was used to film the jumping and swimming of the frogs from a top-down view. As the efficiency or maximum ability of locomotory performance may vary depending on temperature , the expIn the jumping video, the frogs commenced jumping from one side of the tank. Via utilizing a thin paint brush, we tapped the urostyle of the frogs in order to induce a strong jump. The experiment was repeated three times for each individual, and there was a break of 5 min among each experiment. In the case of consecutive jumps in one experiment, the jumping action with the highest speed was selected. In the swimming video shoot, the frog was placed on styrofoam land at the end of a glass tank. After that, a thin paint brush was used to allow the individual to enter the water from land. Swimming behavior immediately after drowning was excluded, and only the subsequent swimming behavior was used for the purposes of analysis. Similarly, three swimming experiments were repeated and a 5 min break between each experiment was implemented. In the case of a consecutive swim in one experiment, the swimming action with the highest speed was selected.We split the video into 30 frames per second and performed the analysis using ImageJ . First, Landmark-based geometric morphometrics were used to analyze the morphological changes in tadpoles and juvenile frogs. The left-side image of the tadpole was used in order to analyze the shape of the tadpole tail. Furthermore, the skeletal shape of juvenile frogs was analyzed in order to identify the shape of the skull, pelvis, ilium, and urostyle. Further, 2D skeleton images were captured from the dorsal direction by using an X-ray imaging system . We then digitized the landmark points in respect to the shape of the tadpole tail by using the TpsDig software . Nineteet-test was used in order to compare the length and weight in both the tadpoles and juvenile frogs. The developmental rate of the tadpoles and the metamorphosis timing of the juvenile frogs were compared by utilizing an unpaired t-test. We also analyzed the difference in respect to the length of the bones in the limbs and urostyle of the subjects. In addition, the jumping speed and the swimming speed of juvenile frogs between the predation group and control group was analyzed by an unpaired t-test. The assumptions of the unpaired t-test were confirmed by a Levene’s equal variances test and the Shapiro–Wilk normality test. Statistical differences were significant at p < 0.05. In respect to this, GraphPad Prism version 8.0 for Windows  was used in order to perform the statistical analyses.An unpaired (38) = 0.755, p > 0.05) and weight (t (38) = 0.049, p > 0.05) of the tadpoles did not appear to have resulted in a difference between the predation group  or the control group . In respect to this, it must be noted that the tadpoles that were used for length and weight measurements were excluded from the experiment.The initial (Gosner stage 26) length (t (38) = 3.285, p = 0.002) and weight (t (38) = 3.664, p = 0.001) than the tadpoles of the predation group  who were in Gosner stage 39 ((38) = 2.781, p = 0.008) than the time in which the control group (time = 58.30 ± 2.62 days) was able to reach Gosner stage 39  that were in Gosner stage 39 possessed a higher body length  was used in order to analyze the body and tail shape of the tadpoles (Gosner stage 39) between both the predation and control groups. The canonical variate 1 (CV1) axis explained the 100% morphological variation of the bodies and tails of the tadpoles. The higher the CV1 was represented, the smaller the body became; in addition, the tail also became longer and the caudal fin narrower d,e. The (24) = 4.378, p < 0.001) than the time that was required in the control group (time = 109.61 ± 4.98 days) ((24) = 0.399, p = 0.693) and weight (t (24) = 0.466, p = 0.646) were not significantly different between the predation group  and the control group  in Gosner stage 46 (The period of time to metamorphosis (Gosner stage 46) in the predation group (time = 126.15 ± 11.90 days) in respect to the juvenile frog was longer (t 98 days) a. Moreovstage 46 b,c.(24) = 2.073, p = 0.049) that combines the humerus, radio–ulna, and the hindlimb (t (24) = 2.077, p = 0.049), as well as that which combines the femur and tibio–fibula, was longer in the frogs of the predation group  than in the frogs of the control group  in Gosner stage 46 ((24) = 1.251, p = 0.223) between the predation group (3.55 ± 0.43 mm) and the control group (3.37 ± 0.45 mm) in Gosner stage 46 . The higher the CV1 was represented, the more the skull widened; likewise, the higher the CV1, the pelvis also was noted to have slightly widened g,h. The (24) = 1.075, p = 0.293) between the predation group (78.92 ± 11.03 cm/s) and the control group (74.11 ± 11.78 cm/s) in Gosner stage 46 ((24) = 0.383, p = 0.705) between the predation group (8.26 ± 2.25 cm/s) and the control group (7.95 ± 1.91 cm/s) in Gosner stage 46 . However, our expectations were wrong. There was no difference in the jumping and swimming speed between the two groups. Indeed, certain researchers have also studied the change in locomotory performance via the change in metamorphosis periods in tadpoles, but the results were different. Tadpoles grown at a low density were larger in body size and demonstrated a further jumping performance than tadpoles at a high density; having said this, however, there was no difference found in the hind limb length . TadpolePrevious researchers have predicted that the intensity of change in the hind limbs is likely to be too weak to affect functional traits ,26,61. IIn spite of targeting the same factors in this study, the results from several previous studies, including ours, were concluded with disparate results in terms of different traits among the anuran species, different developmental stages that are exposed to certain factors, and the strength of the factors whereby the subjects responded to environmental pressures. However, the responses to changes in body size, body weight, and morphology according to the rate of development, appears to be similar. Even frogs that have experienced delayed or accelerated metamorphosis, including predation pressure, will not find an increase in locomotory performance due to the subtle changes in limb length and body shape, unless there is also a change in body size. Although altered morphology may have an ecological role that we have not thus far detected, our results still support the notion that delayed metamorphosis in tadpoles may be detrimental to their later life-history.


We examined changes in barbell velocity and surface electromyographic activity (sEMG) during the concentric (CON) and eccentric (ECC) phases of a bench press set. Ten men executed a set to instant exhaustion as fast as possible, against a low (40% 1-RM) and a heavy load (80% 1-RM), one week apart. The reduction in mean barbell velocity was lower in the ECC compared with the CON phase for both loads . Under both loading conditions, sEMG activity of the pectoralis major increased in the last compared to the first repetitions only in the CON phase . Similarly, triceps brachii sEMG increased by 15.7% (p = 0.02) and by 21.0% (p < 0.001) during the CON phase in the 40% and 80%1-RM conditions, respectively. However, during the ECC phase, sEMG remained unchanged in the last part of the set for both muscles and loads except for 80%1-RM in the pectoralis major muscle. It was concluded that fatigue measured by velocity loss was lower during the ECC than the CON phase of the bench press movement, when the exercise was performed with maximum velocity to failure, irrespective of the load. sEMG was lower in the ECC than the CON phase for all loads, and increased at the end of the set only during the CON phase, while it remained relatively unchanged in the ECC phase, with the exception of the pectoralis muscle when the load was heavier. Eccentric (ECC) muscle actions are characterized by different mechanical and surface electromyographic (sEMG) responses and have lower energy requirements compared with concentric (CON) muscle actions . PreviouPrevious studies conducted on an isokinetic dynamometer, demonstrated that during a fatigue test there was a greater rate of decline in force (−31.6% vs. −23.8%) and sEMG activity (−26.4% vs. −17.5%) when using CON compared with ECC muscle actions . HoweverIn addition to lower fatigue during isolated ECC muscle actions, the number of repetitions to failure in the bench press is higher than isolated CON muscle actions or a combination of ECC and CON muscle actions . MoreovePower analysis indicated a minimum sample size of eight participants (effect size: 0.67). This value was taken from a relevant paper on the effects of the bench press exercise to failure on sEMG and mean or peak velocity variables . Power a−1 body mass. Participants were informed of the potential risks and the right to withdraw from the study at any stage and signed an informed consent form. The Ethics Committee of the School of P.E. and Sport Science of the National & Kapodistrian University of Athens approved the study which was a part of a larger project , and the procedures were in accordance with the Code of Ethics of the World Medical Association .Ten strength-trained men participated in the study . Participants were: (a) involved in strength-power sports for over 3 years, (b) free from taking any nutritional supplements or drugs, and (c) injury-free for at least one year prior to the study. Their maximum bench press strength (1-RM) was 99.0 ± 15.6 kg, and their relative strength (per kg body mass) was 1.26 ± 0.18 kg•kgThis study used a repeated measures experimental design to compare changes in barbell velocity and sEMG activity in the ECC and CON phases in one set of the bench press executed as fast as possible  to instaParticipants took part in two preliminary sessions. Anthropometric measurements were taken, and the maximum bench press (1-RM) was evaluated during the first preliminary visit. During the second familiarization visit, participants performed a general warm-up, followed by a specific warm-up. Then, they performed a familiarization set of 20 repetitions against 40% 1-RM and a set of 5 repetitions against 80% 1-RM, with 5 min of recovery in between. All repetitions were executed as fast as possible from the start of the exercise, and these sets served to familiarize the participants with the main test conditions.A standardized general warm-up was performed before all preliminary and main sessions. This included five minutes of light exercise on a cycle ergometer (50–60 W) followed by five minutes of dynamic stretching of the upper limb muscles . SubsequA stadiometer was used to measure body height (Charder HM-200P Portstad) and a scale for the assessment of body mass . A Harpenden skinfold caliper  was used for the estimation of body fat .o) and the feet rested flat on the floor. The barbell was grasped slightly wider than shoulder-width with a pronated grip. Two experienced strength and conditioning coaches acted as spotters. Participants completed one set of 3–5 repetitions at 50–60% of the predicted 1-RM, one set of 2–3 repetitions at 75–80% of the predicted 1-RM and 3 to 5 sets of one repetition to determine the 1-RM (p < 0.01).Maximum bench press strength or one-repetition maximum (1-RM) was evaluated on a Smith machine . Particithe 1-RM . The intA linear position transducer  was used to measure barbell velocity. The device was placed vertically to the movement of the barbell. Mean barbell velocity during the upward (concentric) and downward (eccentric) movement of the barbell was measured for every repetition. The ICC for mean barbell velocity in our laboratory is 0.983 (95%CI: 0.962–0.995) , 2021a.o. Each repetition lasted 3 s and the two repetitions were separated by 3 min rest intervals  was recorded throughout the bench press exercise using appropriate instrumentation  and software . Bipolar electrodes (Ag/AgCl) were placed on the pectoralis major and triceps brachii of the dominant side  accordinntervals . This prntervals . Eccentrp = 0.89). This process was carried out because each repetition had different duration when exercising against 40% 1-RM and 80% 1-RM loads. Data were similarly averaged at the end of each set, i.e., the last 2 and 4 repetitions of the set for 80% and 40%-1-RM, respectively. Velocity loss from the initial to the last part of each set was calculated as a percentage decrease in mean barbell velocity, as defined above.Volume load (kg) was determined as the product of the lifted load and the number of repetitions. sEMG and mean barbell velocity data were matched by averaging a specific number of repetitions at the first part of each set , so that the partial time under tension (pTUT) was the same for the two loads at the initial part  was used as a measure of effect size in ANOVAs , while Hedges’ g was used to calculate effect size for pairwise comparisons . Statistical significance was accepted at p < 0.05. All analyses were performed using the SPSS Statistical package v. 23 .All measured variables presented a normal distribution (Shapiro-Wilk test) and sphericity was verified (Mauchly’s test of sphericity). Data are presented as means and standard deviations (SD). Changes in sEMG and barbell mean velocity were compared using a 3-way repeated measures analysis of variance (ANOVA) . When appropriate, a follow-up 2-way ANOVA was also conducted. A Tukey’s post-hoc test was performed when a significant main effect or interaction was observed. Differences between conditions in the lifted load (kg), the number of repetitions performed, and the volume load were examined using dependent p < 0.001, Hedges’ g = 3.84). In contrast, the volume load and total number of repetitions were higher in the 40% 1-RM compared with the 80% 1-RM condition .The lifted load was significantly greater under the 80% 1-RM condition compared to the 40% 1-RM . Tukey post-hoc tests showed that pTUT at 40% 1-RM and 80% 1-RM was similar under the two conditions at the initial part . However, pTUT was longer in the last part at the 40% 1-RM condition compared with the 80% 1-RM condition .The two-way ANOVA revealed a significant interaction for pTUT . Mean ECC and CON velocities were significantly higher in the initial compared with the last part for both conditions . Also, ECC mean velocity was higher at the initial part and the last part under 80% 1-RM condition compared with the CON mean velocity (p < 0.05). Under 40% 1-RM condition, ECC mean velocity was equal with CON mean velocity at the initial part and higher than CON mean velocity at the last part (p < 0.01).ANOVA showed a significant three-way interaction (load x muscle action x part) for mean barbell velocity (p = 0.022 η2 = 0.46) and post-hoc tests showed that velocity loss was lower in the ECC compared with the CON phase for both loads .p = 0.012; η2 = 0.52) and triceps brachii muscles . sEMG activity during both phases (CON and ECC) was higher during the 80% 1-RM than during the 40% 1-RM (p < 0.05) for both muscles (p < 0.001) and by 24.8% under the 80% 1-RM condition . Similarly, sEMG of the triceps brachii during the CON phase increased under the 40% 1-RM condition by 15.7%  and by 21.0% under the 80%1-RM condition . During the ECC phase, there was no change in sEMG in the last part of the set for both muscles and both loads (p = 0.262 to 0.107) with the exception of the sEMG of the pectoralis major muscle under the 80% 1-RM condition (p < 0.01).Three-way ANOVAs revealed significant three-way interactions (load x muscle action x part) for sEMG of the pectoralis major  and high loads (80% 1-RM). One main finding was that barbell velocity loss was less in the ECC than the CON phase of the movement for both loads, and thus fatigue was greater in the CON compared with the ECC phase. In addition, sEMG in the ECC phase was lower than in the CON phase for both muscles, while sEMG during the ECC phase did not increase at the end of the set except for 80%1-RM in the pectoralis major muscle. sEMG during the CON phase was greater at the end of the set in both muscles and loads. Thus, fatigue and sEMG were lower during the ECC compared with the CON phase of the movement. Also, ECC mean barbell velocity was higher compared with CON mean velocity in both loads and parts of the set except the initial part under the 40% 1-RM condition.Previous studies  have shoIn the present study, velocity loss was higher in the CON compared with the ECC phase of the movement. One possible explanation may be that the relative load, i.e., the load expressed as a percentage of maximum strength, was lower in the ECC than in the CON phase, since ECC muscle strength is higher than CON strength . A previAnother possible cause for greater fatigue in the CON phase may be the higher energy requirement of CON compared with ECC muscle actions . Researc−1 vs. 0.43 ± 0.02 m·s−1, respectively  and may not be generalizable to experts who present different kinetic and kinematic characteristics during this exercise . Also, sEMG was lower in the ECC than the CON phase for all loads, and increased at the end of the set only during the CON phase, while it remained unchanged in the ECC phase, except for the pectoralis major when the heavier load was applied. These findings confirm that in the bench press exercise, the ECC muscle action is less prone to fatigue although the ECC mean velocity is higher. These differences in fatigue during the CON and ECC phases of the bench press exercise using free weights, should be considered when designing resistance training protocols for sports requiring upper body strength. For example, to maximize the training stimulus, strength and conditioning coaches may use eccentric overload methods  to take advantage of the differences in fatigue between the ECC and CON phases of the movement, or they may require the athlete to continue with ECC only movements when CON fatigue is reached.


Cervical vertebral compressive myelopathy (CVCM) and equine neuroaxonal dystrophy/degenerative myeloencephalopathy (eNAD/EDM) are leading causes of spinal ataxia in horses. The conditions can be difficult to differentiate, and there is currently no diagnostic modality that offers a definitive antemortem diagnosis.Evaluate novel proteomic techniques and machine learning algorithms to predict biomarkers that can aid in the antemortem diagnosis of noninfectious spinal ataxia in horses.Banked serum and cerebrospinal fluid (CSF) samples from necropsy‐confirmed adult eNAD/EDM (n = 47) and CVCM (n = 25) horses and neurologically normal adult horses (n = 45).. A subset of serum and CSF samples from eNAD/EDM (n = 5) and normal (n = 5) horses was used to evaluate the proximity extension assay (PEA). All samples were assayed by PEA for 368 neurologically relevant proteins. Data were analyzed using machine learning algorithms to define potential diagnostic biomarkers.Of the 368 proteins, 84 were detected in CSF and 146 in serum. Eighteen of 84 proteins in CSF and 30/146 in serum were differentially abundant among the 3 groups, after correction for multiple testing. Modeling indicated that a 2‐protein test using CSF had the highest accuracy for discriminating among all 3 groups. Cerebrospinal fluid R‐spondin 1 (RSPO1) and neurofilament‐light (NEFL), in parallel, predicted normal horses with an accuracy of 87.18%, CVCM with 84.62%, and eNAD/EDM with 73.5%.Cross‐species platform. Uneven sample size.Proximity extension assay technology allows for rapid screening of equine biologic matrices for potential protein biomarkers. Machine learning analysis allows for unbiased selection of highly accurate biomarkers from high‐dimensional data. CALB2calretininCOVcoefficient of variationCSFcerebrospinal fluidCVCMcervical vertebral compressive myelopathyDKK1dikkoph‐1eNAD/EDMequine neuroaxonal dystrophy/degenerative myeloencephalopathyNEFLneurofilament‐lightNPXnormalized expression unitsPCAprincipal component analysisPEAproximity extension assaypNfHphosphorylated neurofilament heavyRSPO1r‐spondin 1SOD2superoxide dismutase‐2WFKKN1WAP, follistatin/kazal, immunoglobulin, kunitz and neutrin domain containing 11Spinal ataxia is a frequently encountered neurologic problem in racing and sport horses. Spinal ataxia has several underlying causes, including congenital and acquired cervical vertebral compressive myelopathy (CVCM), equine neuroaxonal dystrophy (eNAD)/equine degenerative myeloencephalopathy (EDM), and equine protozoal myeloencephalitis (EPM). Apart from EPM, definitively diagnosing the underlying cause of spinal ataxia antemortem is challenging.Next‐generation proteomic technologies, coupled with detailed phenotyping, provide the opportunity to enhance diagnostic modalities. Spinal ataxia in horses is well‐positioned to benefit from these technologies and improve antemortem diagnosis. The application of such techniques to degenerative neurologic disease in humans already has yielded several highly sensitive and specific biomarkers.22.1Samples of CSF and serum from age‐ and sex‐matched American Quarter Horses were used to validate the Olink proximity extension assay technology (PEA). Samples were derived from necropsy‐confirmed eNAD (n = 5) and neurologically normal horses (n = 5). Samples were evaluated using the Olink Target 92 Neuro‐Exploratory assay. This assay simultaneously evaluates the relative concentration of 92 curated proteins in serum and CSF without the need for additional sample preparation. Olink selects proteins to encompass both potential biomarker targets and representative proteins of important biologic pathways. All assays were performed at Olink , with samples run on a single plate. Internal plate standardization and quality control were performed by Olink.2.2s. All samples were collected as previously describedPreviously collected paired serum and CSF samples from neurologically normal horses (n = 45) formed the control cohort. Paired serum and CSF samples from CVCM (n = 25) and eNAD/EDM (n = 47) horses that all were examined for spinal ataxia and later confirmed by necropsy formed the case populationSample size was calculated according to the National Cancer Institute's guidelines for classifier development for high‐dimensional data.2.3www.olink.com) according to the manufacturer's instructions and as described previously.Study samples were quantified using Olink multiplex PEA panels . Data were first inspected by principal component analysis (PCA). Analysis of covariance (ANCOVA) was performed for serum and CSF samples, with phenotype  considered a fixed effect and age, breed, and sex introduced as covariates. A Bonferroni correction was used to correct for multiple comparisons. A corrected Proteins that were significantly differentially abundant in serum and CSF were used to train random forest models. Random forest analysis was performed in R using the randomForest package with default parameters. A randomly selected subset of cases and controls (80%) was used to train the model. The model subsequently was tested on the remaining cases and controls (20%). Models were constructed for serum alone, CSF alone and a merged serum and CSF dataset. Results are reported as class error (proportion of incorrect decisions), mean decrease in accuracy and mean decrease in Gini index. The Gini index gives the probability of a feature , selected randomly, that is incorrectly classified.P‐value of <.05 was used to define binary classification with accuracy and precision of prediction for each group reported.To determine the minimum biomarker set needed to achieve accurate group assignment, conditional inference models were constructed in R using the Partykit package. Default parameters were used for the 3 classifiers, with the model having the same set of proteins introduced as the random forest model for serum, CSF and merged data. A 33.1All CSF samples and 9/10 serum samples fully passed quality control, with intra‐assay coefficients of variation of 3% and 8%, respectively. In serum, 36/92 proteins were detected in ≥50% samples and in CSF 15/92 proteins were detected in ≥50% of samples  of 12%. In >50% of samples, 148 of 368 proteins (40%) were detected. Of those proteins detected in >50% samples, 37 (25%) were differentially abundant among the 3 groups  were detected. Of those proteins detected in >50% samples, 18 (21%) were differentially abundant among the 3 groups  and Dickkoph‐1 (DKK1). In serum, this modeling offered diagnostic accuracies of 67.5% for eNAD/EDM, 87.2% for CVCM and 76.9% for normal horses  approach.Although the PEA assay has probes for 368 proteins, neither CSF nor serum approached the total number of possible detectable proteins. This result, in part, may be attributed to the cross‐species platform. All probes in this platform were developed for human‐derived proteins. Pilot data generated from our laboratory indicated that highly conserved proteins (>80% protein‐protein identity) performed well using this platform. The technology has been used previously for equine synovial samples, where it was able to accurately discriminate among various cyto‐ and chemokines.Machine learning models offer an unbiased and tractable technique to distill high‐dimensional data into useful diagnostic sets. Random forest and conditional inference, although similar, have some fundamental differences. Namely, random forest takes an ensemble approach, with predictions averaged among the sample parameters.Neurofilament light (NEFL) was identified as an important protein for group classification in our study, with relative amounts in CSF and serum highest for CVCM. Neurofilament light is part of the neurofilament family of proteins important for the cytoskeletal structure of the axon.In addition to NEFL, other proteins that are under evaluation as biomarkers in neurologic diseases of humans were detected. These included Dickkoph‐1 (DDK1), an important inhibitor of WNT signaling.Additional potential biomarkers of interest were detected our study, including CSF calretinin (CALB2) and serum superoxide dismutase‐2 (SOD2). Calretinin previously has been used to define the tracts that undergo degeneration in eNAD/EDM.Our findings highlight several potential biomarkers for neurodegenerative disease in horses. However, our study had some limitations. First, unequal distribution of disease groups may have affected our machine learning algorithms, particularly with the smaller CVCM sample set. Because of the strict disease category approach that was taken , the available pool of samples was decreased. Despite the smaller size, the effect magnitude was higher and somewhat more homogeneous compared to both the normal and eNAD/EDM groups, allowing for partial abrogation of the sample size deficit. The second limitation is that our study does not include infectious, inflammatory, or traumatic causes of spinal ataxia. Validation of these potential biomarkers will require evaluation of these additional causes of spinal ataxia to ensure the diagnostic specificity for the intended neurodegenerative disease. However, diagnostic tests currently exist for many of the infectious causes of spinal ataxia in horses. The final limitation is that our study represents only a snapshot in time for both disease groups. Temporal dynamics of these biomarkers may play a role in their diagnostic value, and therefore prospective repeated sampling studies evaluating these markers will be valuable to increase confidence in our current findings.In conclusion, ours is the first study to report on the use of PEA proteomic technology for equine serum and CSF samples. This technology, in tandem with machine learning algorithms, defines highly accurate dual‐ and triplex biomarkers for diagnosis of CVCM and eNAD/EDM in horses. Future studies to validate these markers by development of quantitative assay panels in larger replication cohorts are required before clinical adoption of these biomarkers.Authors declare no conflict of interest.Authors declare no off‐label use of antimicrobials.Authors declare no IACUC or other approval was needed.Authors declare human ethics approval was not needed for this study.Data S1: Supporting InformationClick here for additional data file.


The early differential diagnosis between bacterial meningitis (BM) and tuberculous meningitis (TBM) or cryptococcal meningitis (CM) remains a significant clinical challenge. Neutrophil Gelatinase-Associated Lipocalin (NGAL) has been reported as a novel inflammatory biomarker in the early stages of infection. This study aimed to investigate whether cerebrospinal fluid (CSF) NGAL can serve as a potential biomarker for distinguishing between BM and TBM or CM.We prospectively enrolled the patients with suspected CNS infections at admission and divided them into three case groups: BM (n = 67), TBM (n = 55), CM (n = 51), and an age- and sex-matched hospitalized control . Detected the CSF NGAL and assessed its diagnostic accuracy in distinguishing between BM and TBM or CM. Additionally, longitudinally measured the CSF NGAL levels in patients with BM to evaluate its potential as a monitoring tool for antibacterial treatment. P < 0.05), while the serum NGAL did not show significant differences among the three case groups. The ROC analysis demonstrated that CSF NGAL presented a good diagnostic performance with an AUC of 0.834 (0.770–0.886) and at the optimal cutoff value of 74.27 ng/mL with 70.15% sensitivity and 77.36% specificity for discriminating BM with TBM and CM. Additionally, the CSF NGAL in the convalescent period of BM was significantly lower than in the acute period (P < 0.05).The concentration of CSF NGAL in BM was significantly higher than in TBM, CM, and HC (allCSF NGAL may serve as a potential biomarker for distinguishing between acute BM and TBM or CM. Additionally, it holds clinical significance in monitoring the effectiveness of antibiotic therapy for BM.The online version contains supplementary material available at 10.1186/s12967-023-04485-w. Central nervous system (CNS) infection, commonly presenting as meningitis or encephalitis, is a serious medical condition with high mortality and morbidity. Even survivors may experience significant disability due to neurological deficits , 2. As dConventional diagnostic technologies for CNS infections, such as the cerebrospinal fluid (CSF) routine examination, CSF chemistry tests, and immunological tests, have low specificity or sensitivity. While, microbiological culture is considered the reference standard, it is time-consuming and has low sensitivity . CSF molNeutrophil Gelatinase-Associated Lipocalin (NGAL), also known as human neutrophil lipocalin (HNL) or lipocalin 2, was initially discovered and purified from neutrophils . NGAL isIn the present study, we prospectively enrolled CNS infection patients, including BM, TBM, CM, and hospitalized controls (HC) with no CNS infection and normal CSF examination findings, to detect CSF NGAL levels and evaluate the value of CSF NGAL in distinguishing BM from two other clinically common types of meningitis (TBM and CM), as well as its significance in monitoring antibiotic therapy for BM.In the current study, we prospectively enrolled patients with suspected CNS infections, in the First Affiliated Hospital of Fujian Medical University  from May 2019 to June 2022. The study protocol was approved by the Institutional Review Board of the First Affiliated Hospital of Fujian Medical University . Written informed consent was obtained from participants or their surrogates prior to the study.The case inclusion criteria were as follows: (1) clinical features were characterized by headache, fever, vomiting, neck stiffness, or meningeal irritation signs; (2) The presence of abnormalities in routine CSF examinations and CSF chemistry tests (such as elevated white blood cells and proteins) suggests the presence of intracranial infection. (3) Patients who cooperated with the study and were willing to sign informed consent. Ultimately, these patients were categorized into four groups: BM, TBM, CM, and others, based on the final diagnosis made by at least two experienced neurologists at the time of discharge. The diagnosis of BM, TBM, and CM was based on the following criteria: (1) Confirmed BM was diagnosed based on the positive results for at least one of the following tests: culture of pathogenic bacteria, PCR, or mNGS analysis from CSF. Probable BM was diagnosed based on clinical symptoms, typically abnormal CSF findings, and a good response to antibiotics. The criteria for the convalescent period of BM were as follows: After antibiotic treatment for more than 7 days, the clinical symptoms of BM patients significantly improved, and the levels of the CSF white blood cells and proteins decreased significantly or have returned normal levels compared to the initial period of the onset of the disease. (2) The definite TBM was diagnosed by the culture-positive presence of M.tb or the positive acid-fast staining in the CSF. The probable TBM was diagnosed based on clinical manifestations and CSF findings, including the following changes: a history of or exposure to tuberculosis; positive interferon gamma release assays in the blood; effective anti-TB treatment; and the exclusion of alternative diagnoses . (3) TheProspectively collected baseline data on demographics, clinical signs and symptoms at the time of admission, and general examination, including blood routine tests, CSF common examinations, and serum white blood counts (WBC) and C reactive protein (CRP).All enrolled patients underwent lumbar punctures at the L4 and L5 levels by the physicians after admission, and 3 mL of CSF were extracted into a sterile tube. After centrifugation at 2000 g for 5 min, CSF supernatant samples were collected and stored at −80 °C until analysis. The paired serum specimens from each subject were collected simultaneously, centrifuged at 1,500 g for 10 min, and stored at −80 °C until used. Furthermore, in order to observe the dynamic change of CSF NGAL, the CSF and paired serum specimens collected during the convalescent period of some BM patients (from March 2021 to June 2022) were also collected.The CSF and serum NGAL were measured by an automatic biochemistry analyzer , using a commercialized kit (the Latex enhanced immunoturbidimetry methods), which have been approved by the CFDA, from Wuhan Life Origin Biotech Joint Stock Co., Ltd.P < 0.05 was considered statistically significant.Data analysis was performed with SPSS 18.0 software . Continuous variables that did not have a normal distribution were expressed as medians and interquartile ranges (IQR). The non-parametric test  was used to compare outcomes. Categorical variables were expressed as the number (%) and compared using the Chi-square test. For paired comparisons, Wilcoxon’s non-parametric test for paired samples was used. The diagnostic accuracy of the biochemical markers was assessed by receiver operating characteristic (ROC) curve analysis. The Spearman correlation coefficient was employed to evaluate the correlations. All tests of significance were two-tailed, and In the current study, we prospectively obtained 439 patients with suspected CNS infections at admission Fig. . After tP > 0.05). The most common symptoms presented in three case groups were fever and headache, and some patients also presented with vomiting and altered consciousness. The ratio of fever in the TBM was 85.4%, higher than the BM (73.1%) and CM (66.7%), and the ratio of headache in the CM was 100%, which was higher than the TBM (92.7%) and BM (83.6%); however, there were no significant differences (P > 0.05). On physical examination, the positive rate of meningeal irritation  was highest in the TBM (70.9%), followed by the BM (61.2%) and the CM (56.8%), which also had no significant differences (P > 0.05). The intracranial pressure (IP) in the CM was highest, followed by the BM and the TBM, which were significantly higher than the HC.The demographic and clinical characteristics of subjects at admission are summarized in Table P < 0.01), however, there were no significant differences among the three case groups , but there were also no significant differences among the three case groups , however, there was no significant difference among the three case groups. In addition, the serum CRP in the three case groups was not significantly different from the HC group  and serum WBC and CRP in patients in four groups at admission. As shown in Table P < 0.05). Later, we also detected the serum NGAL. We found that the serum NGAL in three case groups: BM (median and IQR: 180.93 (83.90–378.81) ng/mL), TBM (median and IQR: 141.61 (92.29–207.61) ng/mL), and CM (median and IQR: 109.38 (74.27–172.38) ng/mL) were higher than HC (median and IQR: 46.01 (34.75–63.01) ng/mL); however, there were no significant differences among BM, TBM, and CM .Next, we examined the levels of CSF and serum NGAL among the BM, TBM, CM and HC in the acute period (at admission). The CSF NGAL in BM (median and IQR: 253.36 (79.81–535.49) ng/mL) was significantly higher than TBM (median and IQR: 35.89 (17.27–80.61) ng/mL), CM (median and IQR: 21.25 (10.91–62.58) ng/mL), and HC (median and IQR: 9.28 (6.11–18.84) ng/mL), as shown in Fig. P > 0.05). Similarly, no significant differences were found in serum NGAL between males and females in BM, TBM, CM, and HC .To evaluate the effects of gender on NGAL levels, we compared CSF and serum NGAL levels in males and females in the BM, TBM, CM, and HC groups, respectively. As shown in Fig. P < 0.001) than the serum NGAL, in which the AUC was 0.724 and the 95% CI was 0.587 to 0.861. At a CSF NGAL cutoff value of 31.03 ng/mL, there was the optimal sensitivity (88.06%) and specificity (93.01%) for distinguishing the BM and HC , cutoff value, sensitivity, and specificity, respectively. Our results showed that the CSF NGAL exhibited a larger AUC (0.955), with a 95% confidence interval [CI] of 0.903 to 0.984 (P < 0.05); however, it was significantly better than CSF chloride, glucose, and protein . We also focused on comparing the diagnostic efficacy of CSF NGAL in discriminating BM from TBM and CM. Our results demonstrated that the diagnostic efficacy of CSF NGAL in this differential diagnosis was significantly better than that of the traditional CSF assays , and CSF NGAL exhibited superior AUC, sensitivity, and specificity compared to the above four assays .To further analyze the superiority of CSF NGAL in diagnosing BM compared to traditional CSF assays, we conducted ROC curve analysis to compare the accuracy of CSF NGAL with CSF WBC, CSF chloride, glucose, and protein for distinguishing BM and HC. Our findings showed that CSF NGAL was slightly less accurate than CSF WBC in differentiating BM from healthy controls  and a hospitalized control group (HC). Firstly, we preliminary compared the common CSF laboratory parameters among the patients with BM, TBM, and CM to evaluate their differential diagnosis value. Our results showed that compared with HC, increased counts of WBC, low glucose, and high protein concentrations of CSF were observed in three case groups; however, there were no significant differences among BM, TBM, and CM. These results indicated the common CSF laboratory tests can preliminary differentiate the CNS infection from non-infection but cannot differentiate the BM from TBM or CM, which was consistent with the previous studies .NGAL was initially identified in neutrophils and is primarily produced by damaged nephron epithelia, although it is also generated by macrophages, active leukocytes, the choroid plexus, and a variety of other tissues , 29. ApaSerum NGAL has been utilized as a biomarker for clinical acute kidney injury patients. Per Venge et al. have proposed that serum NGAL can also be employed for the timely and early diagnosis of bacterial infections, similar to CRP . Common Moreover, previous studies have reported gender-dependent signatures for NGAL, with its expression being linked to metabolic and cardiovascular problems in males , 32. In The exact regulatory mechanisms of NGAL are still insufficiently understood. As a component of the innate immune response during acute neuroinflammation, NGAL is produced at the blood brain barrier by the choroid plexus epithelial cells and the endothelial cells of blood vessels . To explApart from the differential diagnosis of BM in the acute period, the monitoring of antibiotic treatment is also an important clinical challenge. To further evaluate whether the CSF NGAL would be a useful monitor of the antibacterial treatment, we longitudinally measured the CSF NGAL of BM in the acute and convalescent periods. We found the CSF NGAL in the convalescent period of BM was significantly decreased compared to the acute period. Our study’s findings are consistent with those of other studies of serum NGAL . Thus, CAlthough previous studies have reported the significance of CSF NGAL in BM , 36, theHowever, there were some limitations that should be pointed out. First, due to the limitations of diagnostic technologies, not all of the patients in the current study had an etiological diagnosis, which would cause an incorporation bias. Second, because most of the patients in our study were transferred from a primary health care setting where they had accepted empirical antibiotic therapy before admission, we could not get data on the CSF NGAL before antibiotic therapy. Third, according to previous studies, the monomeric form and, to some extent, the heterodimeric forms of NGAL are mainly produced by tubular epithelial cells, while the homodimeric forms are specific to neutrophils , 38. HowIn conclusion, our study has suggested that CSF NGAL might be used as an early diagnostic biomarker of BM, especially for differential diagnosis with patients with TBM or CM during the acute periods, and it also might have some important clinical value for monitoring antibiotic therapy for BM. Further research is required to identify the origin of increased CSF NGAL and to determine whether it has a bacteriostatic properties or is merely a marker during the pathogenesis of BM. This will contribute to a more precise understanding of NGAL's role in the pathogenesis of BM and its potential clinical applications.Additional file 1: Figure S1. The levels of traditional CSF assays  among the four groups. A, the levels of CSF WBC among the patients with BM, TBM, CM, and HC; B, the levels of CSF chloride among the patients with BM, TBM, CM, and HC; C, the levels of CSF glucose among the patients with BM, TBM, CM, and HC; D, the levels of CSF protein among the patients with BM, TBM, CM, and HC. WBC, White blood count; NGAL, Neutrophil Gelatinase-Associated Lipocalin; BM, bacterial meningitis; TBM, tuberculous meningitis; CM, cryptococcal meningitis; HC, hospitalized controls. ** P < 0.01, *** P < 0.001, compared with the HC group. n.s, not significant.


It was revealed that up to 81% of our cohort met the criteria for cognitive impairment. Additionally, we observed that the addition of a CSF volumetric analysis improved the identification of VPS responders (accuracy of 93%), thus enhancing the management and prognosis of long-term cancer survivors.Up to 50–90% of long-term cancer survivors will exhibit moderate to severe cognitive impairment following cranial radiotherapy (RT). It is common in this population to observe a ventricular dilatation disproportionate to the cerebral atrophy, which clinically manifests similar to normal pressure hydrocephalus (NPH). Previous studies demonstrated that early placement of a ventriculoperitoneal shunt (VPS) may be beneficial. Our study aimed to describe the cognitive, neuroimaging-MRI , and lumbar infusion test features of a cohort of cancer survivors (n = 36). For those in whom VPS was placed (n = 14), we explored whether adding a CSF volumetric analysis to classical MRI and LIT (Tap Test) features would better identify VPS responders. Results: Nearly 80% exhibited cognitive impairment. The CSF volume at NPH diagnoses was significantly larger in the group of VPS responders (p = 0.04). The addition of CSF volume to NPH diagnoses increased accuracy to 93%, with a positive and negative predictive value of 91% and 100%, respectively. Conclusion: The addition of a quantitative MRI analysis of CSF volume to classical MRI and LIT NPH criteria, along with a high clinical suspicion of NPH, may help to identify VPS responders, thus improving the clinical management and prognosis of long-term survivors. Background: We examined cognitive, brain MRI, and lumbar infusion test (LIT) features to identify predictors of response to ventriculoperitoneal shunting (VPS) in long-term cancer survivors with suspected normal pressure hydrocephalus (NPH) following cranial radiotherapy (RT). Methods: Patients who completed cranial RT at least 2 years before with clinically suspected NPH and an Evans’ index (EI) ≥ 0.30 underwent a cognitive and a cerebrospinal fluid (CSF) volumetric (MRI) analysis ( Nowadays, cranial radiotherapy (RT), is still one of the mainstay treatments for brain tumour patients. Despite the poor prognosis of this population, some patients will achieve long-term overall survival. These include patients with low-grade or even high-grade primary brain tumours and patients with brain metastases with favourable clinical and molecular prognostic factors.However, 50–90% of them will experience long-term cognitive deficits induced by cranial RT, impairing functional independence and quality of life ,5,6,7,8.Typically, it has been considered that RT-induced neurotoxicity results from direct damage to neurons or glia or from disruption of the normal cerebral vasculature . Radiolon = 30). They found that more than half of their patients experienced a favorable functional response after VPS, although only urinary incontinence achieved a statistically significant difference. Cognitive impairment showed minimal improvement, but it is important to note that only one third received formal neuropsychological testing  ,31, a viCognitive impairment was defined as subjective memory complaints accompanied by an impairment in one or more cognitive domains that are greater than would be expected for the patient’s age and educational level (one test scored ≥2 standard deviations (SD) below the sample mean or two tests scored ≥1.5 SD below the sample means) ,34 and/oop). After that, through another lumbar cannula, following the constant infusion method, an artificial CSF  is infused at a rate of 1.6 mL/min for about 20 min, until pressure reaches a plateau level (Pp) [p minus Pop divided by infusion rate (Rout = Pp − Pop/infusion rate). The duration of the register is between 40–60 min. If the baseline pressure exceeds 50 mmHg or if the patient experiences headaches or neurological symptoms, the infusion test is interrupted. Following the infusion test, a CSF tap test is performed. It consists of removing 20–30 mL of CSF and after an interval of time (less than 72 h) evaluating improvement of gait, urinary incontinence, or cognitive symptoms [LIT is a method used to measure the resistance of CSF outflow (Rout). It consists of inserting a lumbar cannula into the CSF space while the patient is lying horizontally on the left side, and then the examiner determines the opening CSF pressure (Pvel (Pp) . Rout issymptoms . Prior tsymptoms  Table 1op. AfterThe MRI (1.5 Tesla) closer to the infusion test date was examined. Brain morphology was assessed, including: (a) EI , for which measurements greater than 0.30 are considered hydrocephalus; (b) other features of DESH, that include tight high convexity or midline surfaces, an enlarged sylvian fissure associated with ventriculomegaly, and focal dilatation of sulci not attributable to atrophy ,23,24,39http://www.mccauslandcenter.sc.edu/mricro/mricron (accessed on 2 September 2019)). Then, a morphometric analysis was carried out using the SPM8 software package  running on MATLAB . Specifically, first, Unified Segmentation with medium regularization and cost function masking were applied to segment gray matter (GM), WM and CSF images and normalize the T1 image and the tumour mask for each patient into the Montreal Neurological Institute (MNI) space [We used the Fazekas scale to grade WM changes or leukoencephalopathy in both periventricular and deep WM areas . AdditioI) space . After sp threshold of 0.05. Additionally, a receiver operating characteristic (ROC) curve analysis was conducted to determine a cutoff of CSF volume with desirable levels of sensitivity and specificity to predict VPS responses.All statistical analyses were conducted using SPSS 27.0 software . We used U-Mann-Whitney, Chi-square, Student-t and log-rank tests to assess for group differences, depending on the nature of the variables, with a critical A total of 50 patients  were screened: 36 patients (72%) had an EI ≥ 0.30 and 14 patients (28%) had an EI < 0.30 which were excluded from further analysis. All patients underwent a cytological examination of the CSF during LIT, which ruled out leptomeningeal carcinomatosis. Overall, 26 out of 32 patients (81%) met the criteria for cognitive impairment, specially focused on executive functioning (Trail making test B) but also on processing speed (Trail making test A) and verbal fluency.n = 4) or recurrence/disease progression (n = 2). As a result, a total of 14 out of 36 patients included (39%) underwent VPS placement.Patients with NPH suspicion who showed more than one of the clinical triad symptoms, an EI ≥ 0.30 and a pathological Rout value > 12 mmHg/mL/min, a criterion used by the neurosurgeons of our institution, were eligible for VPS placement. Twenty patients of our cohort met these criteria , but VPS was eventually ruled out in six patients due to either patient refusal (p = 0.11). Concerning neuroimaging features, neither the EI value nor the presence of DESH showed significant differences between groups. In contrast, CSF volume at NPH diagnoses was significantly larger in the improvement group than in the non-improvement (p = 0.04)  showed clinical improvement after VPS . There were no differences regarding demographic, clinical, and LIT features between those who improved or not following VPS. Only RT doses resulted in significant differences between groups. This is explained by the fact that in the non-improvement group, there was one patient who had received more than 60 Gy of RT . When we repeated the analysis without this outlier, RT doses resulted in no significant differences (.04) See . See Tabp < 0.001). In fact, during the 6-month follow-up evaluation, 14 out of 21 (67%) patients experienced a worsening of their NPH symptoms. One patient could not be evaluated because he died from pneumonia prior to the clinical follow-up.Patients with post-RT NPH who did not undergo VPS, failed to show any clinical improvement compared to the VPS group  resulted in the only significant differential factor between groups  we added this variable to the analysis. After applying a ROC curve analysis to the variable CSF volume [area under the curve (AUC) = 0.88, to 92.9% B. IntereFinally, it is also worth pointing out that 29% of the patients (4/14) experienced complications after VPS placement. Three patients developed subdural collections ; two of whom required neurosurgical drainage and revision of the VPS. The other patient required a VPS repositioning due to poor abdominal position. However, all complications were successfully resolved.The present study describes the cognitive, neuroimaging, and CSF characteristics of the largest published series of cancer patients with suspected post-RT NPH, highlighting the use of CSF volumetrics to identify potential VPS responders.n = 26/32) of our cohort met the criteria for cognitive impairment, with more pronounced deficits focused on executive functioning, accompanied in most cases by severe leukoencephalopathy . These findings are consistent with previous studies of radiation-induced cognitive toxicity, including the retrospective study by Thiessen and DeAngelis [Our work revealed that up to 81% , we explored whether the addition of a quantitative MRI analysis of CSF volume to the classical NPH MRI criteria and tap test result might improve the identification of VPS responders. Specifically, we showed that CSF volumetric analysis, as add-on variable but also by itself, achieves a 92.9% accuracy in differentiating VPS responders from non-responders. Interestingly and in line with our results, several studies focusing on quantitative MRI CSF volumetric analysis in idiopathic NPH patients have been published in the past decade [Bearing this in mind and considering that in our cohort VPS responders had a significantly higher CSF volume than non-responders  may have impeded the achievement of significant differences between responders and non-responders, limiting the generalizability of the results obtained. Additionally, while the number of patients who developed complications after VPS appeared considerable (29%), all of them were successfully managed with a favourable outcome. Our study presents some limitations. Firstly, it was a single-centre study; thus, multicentre and randomized studies are required to validate the results. Secondly, due to its retrospective nature, longitudinal cognitive testing was not performed following VPS, thus hampering the assessment of objective cognitive improvement after VPS. Additionally, the small number of NPH patients undergoing VPS placement (In conclusion, our study has shown that the addition of a quantitative CSF MRI analysis in the study of patients with clinical suspicion of post-RT NPH could aid in identifying those who may benefit from VPS, thus improving the clinical management and prognosis of long-term cancer survivors. However, larger multicentre studies are needed to confirm the usefulness, accuracy, and applicability of this approach.


Most cases of IIH occur in obese women of childbearing age, though age, BMI, and female sex do not encompass all aspects of IIH pathophysiology. Systemic metabolic dysregulation has been identified in IIH with a profile of androgen excess. However, the mechanistic coupling between obesity/hormonal perturbations and cerebrospinal fluid dynamics remains unresolvedFemale Wistar rats were either fed a high fat diet (HFD) for 21 weeks or exposed to adjuvant testosterone treatment for 28 days to recapitulate IIH causal drivers. Cerebrospinal fluid (CSF) and blood testosterone levels were determined with mass spectrometry, ICP and CSF dynamics with in vivo experimentation, and the choroid plexus function revealed with transcriptomics and ex vivo isotope-based flux assays.+,K+,2Cl− cotransporter, NKCC1.HFD-fed rats presented with increased ICP (65%), which was accompanied by increased CSF outflow resistance (50%) without altered CSF secretion rate or choroid plexus gene expression. Chronic adjuvant testosterone treatment of lean rats caused elevated ICP (55%) and CSF secretion rate (85%), in association with increased activity of the choroid plexus NaHFD-induced ICP elevation in experimental rats occurred with decreased CSF drainage capacity. Adjuvant testosterone, mimicking the androgen excess observed in female IIH patients, elevated the CSF secretion rate and thus ICP. Obesity-induced androgen dysregulation may thus contribute to the disease mechanism of IIH.The online version contains supplementary material available at 10.1186/s12987-023-00436-1. Idiopathic intracranial hypertension (IIH) is characterized by an unexplained increase in intracranial pressure (ICP) resulting in life-altering symptoms. These include severe, persistent headache and optic nerve swelling (papilloedema) that can lead to permanent visual loss and cognitive impairment –6. ObeseThe elevated ICP in IIH has been attributed to multiple factors, including increased venous pressure , 19, asp+/K+-ATPase and the Na+/K+/2Cl− cotransporter (NKCC1) during the washing procedure), followed by transfer to scintillation vials containing 100 µl Solvable  to dissolve the choroid plexus. For efflux, the choroid plexus was swiftly rinsed in 37 °C isotope-free HEPES-aCSF, then transferred into new wells containing 37 °C isotope-free HEPES-aCSF with or without 20 µM bumetanide, at 10 s intervals. For each time point, 200 µl of the surrounding HEPES-aCSF was collected into a scintillation vial. At the end of the experiment, the choroid plexus was placed into a scintillation vial containing 200 µl Solvable to dissolve the choroid plexus. Isotope content was determined in 2 ml Ultima Gold™ XR scintillation liquid  using the Tri-Carb 2900TR Liquid Scintillation Analyzer (Packard). The 86Rb+ activity was corrected for extracellular background using 3H-mannitol [86Rb+ activity at each time point (AT) normalized to the initial 86Rb+ activity (A0) as a function of time. The slope from linear regression analysis was used to determine the 86Rb+ efflux rate constant [Lateral choroid plexus was isolated from control and testosterone-treated rat brains and placed in 37 °C HEPES-aCSF for a 5–10 min recovery period followed by 2 min (influx) or 8 min  or vehicle) of incubation in an isotope solution containing rubidium . All data were tested for normality of distribution using Shapiro–Wilk test prior to statistical analysis with Student's unpaired t-test, one-way ANOVA with Sidaks multiple comparisons test, and simple linear regression, as stated in figure legends. Data are displayed as the mean and standard error of the mean (SEM) with a p-value < 0.05 employed to define statistical significance. Outliers were determined with Grubbs’ test, when indicated in figure legend.2, n = 22 vs control: 0.66 ± 0.01 g/cm2 n = 19, p < 0.001, Fig. 2 = 0.34, p < 0.05, Fig. 2 = 0.40, p < 0.05, Fig. Obesity in humans is commonly attributed to myriad factors including genetic predisposition, macro- and micro-environmental factors, and lack of physical activity, but the primary recognized feature is consumption of energy rich diet . In ordeout) detected in most IIH patients [out was significantly elevated in HFD-fed rats relative to controls , both known to contribute to CSF secretion [+/K+-ATPase to the increased CSF production observed in the testosterone-treated rats, its transport activity was determined in acutely excised choroid plexus from testosterone-treated rats and their control counterparts by influx assays with the radioisotope 86Rb+, as a congener of K+, in the absence and presence of the Na+/K+-ATPase inhibitor ouabain , we observed increased CSF secretion rates. We therefore speculate that CSF testosterone excess is a relevant contributing causal driver in IIH etiology.Here, we demonstrate that mimicking of IIH patient characteristics  in a rat model, led to elevated ICP and RAlthough IIH has been acknowledged as a recognized pathology for more than a century , 74, theout, indicating reduced efficiency of CSF drainage similar to that observed in IIH patients [out observed in HFD-fed rats provide a compelling animal model for approximating several aspects of human IIH clinical presentation. Increased resistance to CSF drainage, as well as reduced compliance of the cerebrovascular system could be secondary to changes in venous pressure, which has been observed to increase in IIH patients [HFD-fed rats exhibited increased ICP as a function of their bodyweight, as previously demonstrated in a study using young female rats on a shorter duration obesogenic HFD program with similar weight gain, displaying similar increases in ICP, as well as indications of other IIH symptoms including reduced cerebrovascular compliance, papilledema, and headache  and aligpatients . Combinepatients , though patients , indicatpatients , 87 and patients , 85. Howpatients . Therefopatients  and/or tpatients ). Similapatients . At 27 wpatients .Elevated CSF secretion has been proposed to be associated with the elevated ICP in IIH patients , 27, alt+/K+-ATPase activity [While female sex and obesity are two of the cardinal characteristics of most IIH patients, the great majority of obese females do not have IIH. Striking among biomarkers distinguishing IIH patients from unaffected obese females is elevation of testosterone , 41, whiactivity , which wactivity . Howeveractivity –47, likeactivity , 46, whiactivity . The andactivity , is alsoactivity , 99, 100activity  and moduactivity  which, tactivity , 46, 103out) that together recapitulate IIH symptoms and allow mechanistic insight into IIH etiology. When mimicking the elevated testosterone environment, as observed in patients with IIH, we observed elevated ICP and CSF hypersecretion in the experimental rats. Synergistic effects of obesity and hyperandrogenism may thus, if sustained for prolonged time and potentially associated with other IIH-promoting factors [In conclusion, we here demonstrate that although HFD-fed rats gained weight and displayed elevated ICP, their weight gain and ICP increase did not fully reach levels observed in IIH patients. The ICP elevation could not be accounted for by CSF hypersecretion but, at least in part, by a decreased CSF drainage capacity  together with the Gene (gene symbol). The ‘‘Control diet’’ and ‘‘High fat diet’’ are the mean values, in transcript per million (TPM), of five wistar rats on either control diet or high fat diet. Together with the mean values arestandard error of the mean (SEM) of the five ‘‘Control diet’’ and ‘‘High fat diet’’, also in TPM. All values have been rounded to closest integer, and values under one are annotated as ‘‘< 1’’.Additional file 3: Table S3.of all the differentially expressed genes in the choroid plexus of Wistar rats fed control diet or high fat diet. Differentially expressed genes are all genes with an adjusted P < 0.05. The table contains the Ensembl ID (Rnor_6.0) together with the Gene (gene symbol). The MeanBase (DEseq2) is the mean of the normalized transcript count values, divided by size factors, taken across all samples. Log2FC represents the log2 fold change from control diet to high fat diet. A positive Log2FC value thus indicates an upregulation of gene expression in the high fat diet fed rats. Adjusted P value is calculated by the Benjamini–Hochberg procedure (see methods).Additional file 4: Mass spectrometry analysis of CSF and blood hormones.Additional file 5: Testosterone treatment does not affect CSF flow or choroid plexus transport rate.