Breakthroughs, discoveries, and DIY tips sent every weekday. No responsibilities and little to do but enjoy yourself. Yet somehow, after a whole day of blissful nothing, you find yourself completely zonked. If taking in the sea air is supposed to be restorative, why can a restful day at the beach end up feeling so tiring? There's no one certain answer, but science offers a few possibilities.

Malnutrition and dehydration are strongly associated with increased cognitive and functional decline in people living with dementia (PLWD), as well as an increased rate of hospitalisations in comparison to their healthy counterparts. Extreme changes in eating and drinking behaviours can often lead to malnutrition and dehydration, accelerating the progression of cognitive and functional decline and resulting in a marked reduction in quality of life. Unfortunately, there are currently no established methods by which to objectively detect such changes. Here, we present the findings of an extensive quantitative analysis conducted on in-home monitoring data collected from 73 households of PLWD using Internet of Things technologies. The Coronavirus 2019 (COVID-19) pandemic has previously been shown to have dramatically altered the behavioural habits, particularly the eating and drinking habits, of PLWD. Using the COVID-19 pandemic as a natural experiment, we conducted linear mixed-effects modelling to examine changes in mean kitchen activity within a subset of 21 households of PLWD that were continuously monitored for 499 days. We report an observable increase in day-time kitchen activity and a significant decrease in night-time kitchen activity (t(147) = -2.90, p < 0.001). We further propose a novel analytical approach to detecting changes in behaviours of PLWD using Markov modelling applied to remote monitoring data as a proxy for behaviours that cannot be directly measured. Together, these results pave the way to introduce improvements into the monitoring of PLWD in naturalistic settings and for shifting from reactive to proactive care.

Child dehydration is a significant health concern, especially among children under 5 years of age who are more susceptible to diarrhea and vomiting. In Afghanistan, severe diarrhea contributes to child mortality due to dehydration. However, there is no evidence of research exploring the potential of machine learning techniques in diagnosing dehydration in Afghan children under five. To fill this gap, this study leveraged various classifiers such as Random Forest, Multilayer Perceptron, Support Vector Machine, J48, and Logistic Regression to develop a predictive model using a dataset of sick children retrieved from the Afghanistan Demographic and Health Survey (ADHS). The primary objective was to determine the dehydration status of children under 5 years. Among all the classifiers, Random Forest proved to be the most effective, achieving an accuracy of 91.46%, precision of 91%, and AUC of 94%. This model can potentially assist healthcare professionals in promptly and accurately identifying dehydration in under five children, leading to timely interventions, and reducing the risk of severe health complications. Our study demonstrates the potential of machine learning techniques in improving the early diagnosis of dehydration in Afghan children.

In a world where unmanned spacecraft have landed on Mars and artificial intelligence can read your mind, one would think someone would have figured out a precise way to measure how much athletes should drink while exercising. Hydrating, or replacing body fluids lost through sweating, exhaling, and eliminating waste, is essential. When 2 or more percent of body mass is lost through dehydration, the body can go haywire, with elevated cardiovascular strain, reduced aerobic exercise performance, and impaired thermoregulatory function. After losing 12 percent of body mass to dehydration, a human will die. It's rare for an athlete to exercise to the point of death by dehydration.

We experience thirst every day, but where does this sensation come from? In the 1950s, Bengt Andersson proposed a tantalizing answer: Our brains might contain an “osmosensor” ([ 1 ][1]) that governs thirst, which consists of a group of cells that sense when we are dehydrated by directly monitoring the osmolarity of the blood. In a series of pioneering experiments , Andersson systematically infused salt into the brains of goats in an attempt to locate this osmosensor ([ 2 ][2], [ 3 ][3]). He ultimately discovered a small area within the hypothalamus where even minute amounts of salt triggered immediate, voracious drinking. Subsequent studies established that Andersson's osmosensor encompasses the subfornical organ (SFO), a brain region that is distinctively suited to detecting blood osmolarity because it lies outside the blood-brain barrier ([ 4 ][4]). The osmosensor model is powerful because it explains how dehydration generates thirst, but it has a crucial shortcoming: Drinking behavior is regulated on a fast, moment-by-moment basis that cannot be explained by slow changes in blood osmolarity. Consider that drinking immediately satiates thirst, even though the water imbibed is not absorbed for many minutes ([ 5 ][5], [ 6 ][6]), and that eating stimulates prandial drinking long before the ingested food enters the bloodstream ([ 7 ][7], [ 8 ][8]). How does the brain bridge these disparate time scales to dynamically adjust our sense of thirst? I reasoned that we might gain new insight into this longstanding question by recording the activity of thirst-promoting neurons in living animals. My colleagues and I thus began by genetically labeling the SFO neurons that comprise Andersson's osmosensor and confirming that these cells are essential for dehydration-induced drinking ([ 9 ][9]). We then set out to observe the neural dynamics underlying thirst in behaving mice ([ 10 ][10], [ 11 ][11]). If SFO neurons are genuine osmosensors, then we would expect them to simply encode an animal's dehydration level. Consistent with this idea, our initial fiber photometry recordings demonstrated that these neurons are dose-dependently activated by increases in blood osmolarity ([ 10 ][10]). It was therefore surprising to discover that SFO neurons are also rapidly regulated during eating and drinking, well in advance of any impact food and drink might have on the blood ([ 10 ][10]). For example, their activity decreases every time a mouse licks from a water bottle and increases with every bite of food. This counterintuitive finding indicated that SFO neurons—long viewed as merely passive sensors of dehydration—must receive a second class of signals that operate on the fast time scale of behavior. To pinpoint the origin of these signals, we traced the flow of water through the digestive tract of the mouse. We found that fluid detection in the mouth triggers a near-instantaneous inhibitory signal that closely tracks the volume ingested ([ 10 ][10]). Temperature sensing contributes to this process—SFO neurons are most efficiently inhibited by drinking cold water, a phenomenon that could be reproduced through isolated oral cooling. This may explain why we experience cold drinks as especially thirstquenching and pleasurable ([ 12 ][12], [ 13 ][13]). Using an intragastric infusion paradigm, we next discovered that the osmolarity of ingested fluids is precisely measured in the gastrointestinal tract and then rapidly transmitted to the brain by the vagus nerve ([ 11 ][11]). This gut-to-brain osmolarity signal sustains the inhibition of SFO neurons produced by oral volume signals and satiates thirst if pure water is drunk. By contrast, detection of hypertonic fluids in the gut causes SFO activity to rebound to the “thirsty” state. Thus, drinking generates layers of signals that enable thirst neurons to predict how ingested fluids will affect hydration in the future and then adjust drinking preemptively. This simple model explains how drinking can rapidly quench thirst yet also be properly calibrated to match an animal's level of dehydration ([ 5 ][5], [ 6 ][6]). Does the body notify the thirst system about other behaviors that affect hydration? We found that eating triggers additional signals that activate SFO neurons in anticipation of food absorption ([ 10 ][10]). This activation drives prandial drinking or, if water is unavailable, suppresses further feeding. This suggests a neural basis for the widespread coordination of eating and drinking ([ 7 ][7], [ 8 ][8]). To test the causal role of the body-tobrain signals identified by our recording experiments, we used optogenetics to precisely manipulate each of them during behavior. This allowed us to confirm that these signals are necessary for thirst satiation, prandial thirst, and dehydration-induced anorexia ([ 10 ][10], [ 11 ][11]), and thus account for most normal drinking behavior. The discovery of diverse inputs to SFO neurons raises the fundamental question of how signals are processed by the individual cells that comprise the thirst system. Do they flow in segregated “streams” or do they interact? To answer this question, we used microendoscopic imaging to track the activity of single neurons during dehydration, drinking, and intragastric infusion ([ 11 ][11]). This revealed a simple processing logic : The signals arising from the mouth, gut, and blood converge onto the same individual thirst neurons, thereby enabling every cell to continuously integrate information about current hydration status with the predicted consequences of ongoing ingestion. In a parallel series of experiments, we showed that downstream brain regions use this integrated representation to coordinate the various components of the body's response to dehydration, including not only drinking but also cardiovascular adjustments, hormone secretion, and changes to emotional valence ([ 11 ][11], [ 14 ][14]). Thirst is governed by a sensory system, analogous to vision or hearing. Unlike these exterosensory systems, however, the neural dynamics underlying thirst were previously unknown. Our recordings revealed that thirst is regulated by layers of signals that arise throughout the body and converge onto individual neurons in the forebrain. This convergence occurs at the first node in the thirst system—the SFO—and generates a real-time estimate of the body's need for water that downstream nodes use to dynamically adjust drinking, valence, and cardiovascular physiology ([ 10 ][10], [ 11 ][11], [ 14 ][14]). Our findings reveal fundamental principles that govern ingestive behavior ([ 15 ][15], [ 16 ][16]) and provide neural mechanisms that can potentially explain long-enigmatic elements of everyday human experience, including the speed of thirst satiation, the prevalence of drinking during meals, and the thirst-quenching power of oral cooling. GRAND PRIZE WINNER Christopher Zimmerman Christopher Zimmerman received his undergraduate degrees from the University of Pittsburgh and a Ph.D. from the University of California, San Francisco. His thesis research focused on the neural mechanisms that govern thirst and drinking behavior. Zimmerman is currently a postdoctoral fellow at the Princeton Neuroscience Institute, where he continues to study the neural processes underlying motivated behaviors. FINALIST Tara LeGates Tara LeGates received her B.S. in Biopsychology from Rider University and a Ph.D. from Johns Hopkins University. She completed a postdoctoral fellowship at the University of Maryland School of Medicine, where she established the importance of the strength and plasticity of hippocampus-nucleus accumbens synapses and reward behavior. LeGates is now an assistant professor at the University of Maryland, Baltimore County (UMBC). Her lab studies how neuronal circuits integrate information to regulate behavior and their alterations in psychiatric disorders. [www.sciencemag.org/content/370/6512/46.1][17] FINALIST Riccardo Beltramo Riccardo Beltramo received his undergraduate degree from the University of Turin and a Ph.D. from the Italian Institute of Technology. After his doctoral training, Beltramo joined the Howard Hughes Medical Institute at the University of California, San Diego and the University of California, San Francisco, where he is completing his postdoctoral work. He studies sensory perception in the mouse visual system, focusing on understanding how cortical and subcortical neural circuits process visual information to drive behavior. [www.sciencemag.org/content/370/6512/46.2][18] 1. [↵][19]1. E. B. Verney , Proc. R. Soc. London Ser. B 135, 25 (1947). [OpenUrl][20][CrossRef][21] 2. [↵][22]1. B. Andersson , Acta Physiol. Scand. 28, 188 (1953). [OpenUrl][23][CrossRef][24][PubMed][25][Web of Science][26] 3. [↵][27]1. B. Andersson, 2. S. M. McCann , Acta Physiol. Scand. 33, 333 (1955). [OpenUrl][28][CrossRef][29][PubMed][30][Web of Science][31] 4. [↵][32]1. M. J. McKinley et al ., The Sensory Circumventricular Organs of the Mammalian Brain (Springer, 2003). 5. [↵][33]1. R. T. Bellows , Am. J. Physiol. 125, 87 (1938). [OpenUrl][34] 6. [↵][35]1. B. J. Rolls et al ., Am. J. Physiol. Regul. Integr. Comp. Physiol. 239, R476 (1980). [OpenUrl][36][PubMed][37] 7. [↵][38]1. T. J. Fitzsimons, 2. J. Le Magnen , J. Comp. Physiol. Psychol. 67, 273 (1969). [OpenUrl][39][CrossRef][40][PubMed][41][Web of Science][42] 8. [↵][43]1. F. Bellisle, 2. J. Le Magnen , Physiol. Behav. 27, 649 (1981). [OpenUrl][44][CrossRef][45][PubMed][46][Web of Science][47] 9. [↵][48]1. C. A. Zimmerman, 2. D. E. Leib, 3. Z. A. Knight , Nat. Rev. Neurosci. 18, 459 (2017). [OpenUrl][49][CrossRef][50][PubMed][51] 10. [↵][52]1. C. A. Zimmerman et al ., Nature 537, 680 (2016). [OpenUrl][53][CrossRef][54][PubMed][55] 11. [↵][56]1. C. A. Zimmerman et al ., Nature 568, 98 (2019). [OpenUrl][57][PubMed][58] 12. [↵][59]1. G. Kapatos, 2. R. M. Gold , Science 176, 685 (1972). [OpenUrl][60][Abstract/FREE Full Text][61] 13. [↵][62]1. D. Boulze, 2. P. Montastruc, 3. M. Cabanac , Physiol. Behav. 30, 97 (1983). [OpenUrl][63][CrossRef][64][PubMed][65] 14. [↵][66]1. D. E. Leib et al ., Neuron 96, 1272 (2017). [OpenUrl][67][CrossRef][68][PubMed][69] 15. [↵][70]1. B. B. Lowell , N. Engl. J. Med. 380, 459 (2019). [OpenUrl][71][CrossRef][72][PubMed][73] 16. [↵][74]1. C. A. Zimmerman, 2. Z. A. Knight , Curr. Opin. Neurobiol. 64, 79 (2020). [OpenUrl][75] [1]: #ref-1 [2]: #ref-2 [3]: #ref-3 [4]: #ref-4 [5]: #ref-5 [6]: #ref-6 [7]: #ref-7 [8]: #ref-8 [9]: #ref-9 [10]: #ref-10 [11]: #ref-11 [12]: #ref-12 [13]: #ref-13 [14]: #ref-14 [15]: #ref-15 [16]: #ref-16 [17]: http://www.sciencemag.org/content/370/6512/46.1 [18]: http://www.sciencemag.org/content/370/6512/46.2 [19]: #xref-ref-1-1 "View reference 1 in text" [20]: {openurl}?query=rft.jtitle%253DProc.%2BR.%2BSoc.%2BLondon%2BSer.%2BB%26rft_id%253Dinfo%253Adoi%252F10.1098%252Frspb.1947.0037%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [21]: /lookup/external-ref?access_num=10.1098/rspb.1947.0037&link_type=DOI [22]: #xref-ref-2-1 "View reference 2 in text" [23]: {openurl}?query=rft.jtitle%253DActa%2Bphysiologica%2BScandinavica%26rft.stitle%253DActa%2BPhysiol%2BScand%26rft.aulast%253DAndersson%26rft.auinit1%253DB.%26rft.volume%253D28%26rft.issue%253D2-3%26rft.spage%253D188%26rft.epage%253D201%26rft.atitle%253DThe%2Beffect%2Bof%2Binjections%2Bof%2Bhypertonic%2BNaCl-solutions%2Binto%2Bdifferent%2Bparts%2Bof%2Bthe%2Bhypothalamus%2Bof%2Bgoats.%26rft_id%253Dinfo%253Adoi%252F10.1111%252Fj.1748-1716.1953.tb00969.x%26rft_id%253Dinfo%253Apmid%252F13079904%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [24]: /lookup/external-ref?access_num=10.1111/j.1748-1716.1953.tb00969.x&link_type=DOI [25]: /lookup/external-ref?access_num=13079904&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [26]: /lookup/external-ref?access_num=A1953YC71800009&link_type=ISI [27]: #xref-ref-3-1 "View reference 3 in text" [28]: {openurl}?query=rft.jtitle%253DActa%2Bphysiologica%2BScandinavica%26rft.stitle%253DActa%2BPhysiol%2BScand%26rft.aulast%253DAndersson%26rft.auinit1%253DB.%26rft.volume%253D33%26rft.issue%253D4%26rft.spage%253D333%26rft.epage%253D346%26rft.atitle%253DA%2Bfurther%2Bstudy%2Bof%2Bpolydipsia%2Bevoked%2Bby%2Bhypothalamic%2Bstimulation%2Bin%2Bthe%2Bgoat.%26rft_id%253Dinfo%253Adoi%252F10.1111%252Fj.1748-1716.1955.tb01213.x%26rft_id%253Dinfo%253Apmid%252F13248609%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [29]: /lookup/external-ref?access_num=10.1111/j.1748-1716.1955.tb01213.x&link_type=DOI [30]: /lookup/external-ref?access_num=13248609&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [31]: /lookup/external-ref?access_num=A1955WP56200005&link_type=ISI [32]: #xref-ref-4-1 "View reference 4 in text" [33]: #xref-ref-5-1 "View reference 5 in text" [34]: {openurl}?query=rft.jtitle%253DAm.%2BJ.%2BPhysiol.%26rft.volume%253D125%26rft.spage%253D87%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [35]: #xref-ref-6-1 "View reference 6 in text" [36]: {openurl}?query=rft.jtitle%253DAmerican%2BJournal%2Bof%2BPhysiology%2B-%2BRegulatory%252C%2BIntegrative%2Band%2BComparative%2BPhysiology%26rft.stitle%253DAm.%2BJ.%2BPhysiol.%2BRegul.%2BIntegr.%2BComp.%2BPhysiol.%26rft.aulast%253DRolls%26rft.auinit1%253DB.%2BJ.%26rft.volume%253D239%26rft.issue%253D5%26rft.spage%253DR476%26rft.epage%253DR482%26rft.atitle%253DThirst%2Bfollowing%2Bwater%2Bdeprivation%2Bin%2Bhumans%26rft_id%253Dinfo%253Apmid%252F7001928%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [37]: /lookup/external-ref?access_num=7001928&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [38]: #xref-ref-7-1 "View reference 7 in text" [39]: {openurl}?query=rft.jtitle%253DJournal%2Bof%2Bcomparative%2Band%2Bphysiological%2Bpsychology%26rft.stitle%253DJ%2BComp%2BPhysiol%2BPsychol%26rft.aulast%253DFitzsimons%26rft.auinit1%253DT.%2BJ.%26rft.volume%253D67%26rft.issue%253D3%26rft.spage%253D273%26rft.epage%253D283%26rft.atitle%253DEating%2Bas%2Ba%2Bregulatory%2Bcontrol%2Bof%2Bdrinking%2Bin%2Bthe%2Brat.%26rft_id%253Dinfo%253Adoi%252F10.1037%252Fh0026772%26rft_id%253Dinfo%253Apmid%252F5787378%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [40]: /lookup/external-ref?access_num=10.1037/h0026772&link_type=DOI [41]: /lookup/external-ref?access_num=5787378&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [42]: /lookup/external-ref?access_num=A1969C796200001&link_type=ISI [43]: #xref-ref-8-1 "View reference 8 in text" [44]: {openurl}?query=rft.jtitle%253DPhysiology%2B%2526%2BBehavior%26rft.stitle%253DPhysiology%2B%2526%2BBehavior%26rft.aulast%253DBellisle%26rft.auinit1%253DF.%26rft.volume%253D27%26rft.issue%253D4%26rft.spage%253D649%26rft.epage%253D658%26rft.atitle%253DThe%2Bstructure%2Bof%2Bmeals%2Bin%2Bhumans%253A%2Beating%2Band%2Bdrinking%2Bpatterns%2Bin%2Blean%2Band%2Bobese%2Bsubjects.%26rft_id%253Dinfo%253Adoi%252F10.1016%252F0031-9384%252881%252990237-7%26rft_id%253Dinfo%253Apmid%252F7323168%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [45]: /lookup/external-ref?access_num=10.1016/0031-9384(81)90237-7&link_type=DOI [46]: /lookup/external-ref?access_num=7323168&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [47]: /lookup/external-ref?access_num=A1981MK37500014&link_type=ISI [48]: #xref-ref-9-1 "View reference 9 in text" [49]: {openurl}?query=rft.jtitle%253DNat.%2BRev.%2BNeurosci.%26rft.volume%253D18%26rft.spage%253D459%26rft_id%253Dinfo%253Adoi%252F10.1038%252Fnrn.2017.71%26rft_id%253Dinfo%253Apmid%252F28638120%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [50]: /lookup/external-ref?access_num=10.1038/nrn.2017.71&link_type=DOI [51]: /lookup/external-ref?access_num=28638120&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [52]: #xref-ref-10-1 "View reference 10 in text" [53]: {openurl}?query=rft.jtitle%253DNature%26rft.volume%253D537%26rft.spage%253D680%26rft_id%253Dinfo%253Adoi%252F10.1038%252Fnature18950%26rft_id%253Dinfo%253Apmid%252F27487211%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [54]: /lookup/external-ref?access_num=10.1038/nature18950&link_type=DOI [55]: /lookup/external-ref?access_num=27487211&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [56]: #xref-ref-11-1 "View reference 11 in text" [57]: {openurl}?query=rft.jtitle%253DNature%26rft.volume%253D568%26rft.spage%253D98%26rft_id%253Dinfo%253Apmid%252F30918408%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [58]: /lookup/external-ref?access_num=30918408&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [59]: #xref-ref-12-1 "View reference 12 in text" [60]: {openurl}?query=rft.jtitle%253DScience%26rft.stitle%253DScience%26rft.aulast%253DKapatos%26rft.auinit1%253DG.%26rft.volume%253D176%26rft.issue%253D4035%26rft.spage%253D685%26rft.epage%253D686%26rft.atitle%253DTongue%2BCooling%2Bduring%2BDrinking%253A%2BA%2BRegulator%2Bof%2BWater%2BIntake%2Bin%2BRats%26rft_id%253Dinfo%253Adoi%252F10.1126%252Fscience.176.4035.685%26rft_id%253Dinfo%253Apmid%252F17778173%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [61]: /lookup/ijlink/YTozOntzOjQ6InBhdGgiO3M6MTQ6Ii9sb29rdXAvaWpsaW5rIjtzOjU6InF1ZXJ5IjthOjQ6e3M6ODoibGlua1R5cGUiO3M6NDoiQUJTVCI7czoxMToiam91cm5hbENvZGUiO3M6Mzoic2NpIjtzOjU6InJlc2lkIjtzOjEyOiIxNzYvNDAzNS82ODUiO3M6NDoiYXRvbSI7czoyMToiL3NjaS8zNzAvNjUxMi80NS5hdG9tIjt9czo4OiJmcmFnbWVudCI7czowOiIiO30= [62]: #xref-ref-13-1 "View reference 13 in text" [63]: 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{openurl}?query=rft.jtitle%253DNeuron%26rft.volume%253D96%26rft.spage%253D1272%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.neuron.2017.11.041%26rft_id%253Dinfo%253Apmid%252F29268095%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [68]: /lookup/external-ref?access_num=10.1016/j.neuron.2017.11.041&link_type=DOI [69]: /lookup/external-ref?access_num=29268095&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [70]: #xref-ref-15-1 "View reference 15 in text" [71]: {openurl}?query=rft.jtitle%253DN.%2BEngl.%2BJ.%2BMed.%26rft.volume%253D380%26rft.spage%253D459%26rft_id%253Dinfo%253Adoi%252F10.1056%252FNEJMra1812053%26rft_id%253Dinfo%253Apmid%252F30699320%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [72]: /lookup/external-ref?access_num=10.1056/NEJMra1812053&link_type=DOI [73]: /lookup/external-ref?access_num=30699320&link_type=MED&atom=%2Fsci%2F370%2F6512%2F45.atom [74]: #xref-ref-16-1 "View reference 16 in text" [75]: {openurl}?query=rft.jtitle%253DCurr.%2BOpin.%2BNeurobiol.%26rft.volume%253D64%26rft.spage%253D79%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx