Prediction of protein content in paddy rice (Oryza sativa L.) combining near-infrared spectroscopy and deep-learning algorithm.

Rice is a staple crop in Asia, with more than 400 million tons consumed annually worldwide. The protein content of rice is a major determinant of its unique structural, physical, and nutritional properties. Chemical analysis, a traditional method for measuring rice's protein content, demands considerable manpower, time, and costs, including preprocessing such as removing the rice husk. Therefore, of the technology is needed to rapidly and nondestructively measure the protein content of paddy rice during harvest and storage stages. In this study, the nondestructive technique for predicting the protein content of rice with husks (paddy rice) was developed using near-infrared spectroscopy and deep learning techniques. The protein content prediction model based on partial least square regression, support vector regression, and deep neural network (DNN) were developed using the near-infrared spectrum in the range of 950 to 2200 nm. 1800 spectra of the paddy rice and 1200 spectra from the brown rice were obtained, and these were used for model development and performance evaluation of the developed model. Various spectral preprocessing techniques was applied. The DNN model showed the best results among three types of rice protein content prediction models. The optimal DNN model for paddy rice was the model with first-order derivative preprocessing and the accuracy was a coefficient of determination for prediction, Rp 2 = 0.972 and root mean squared error for prediction, RMSEP = 0.048%. The optimal DNN model for brown rice was the model applied first-order derivative preprocessing with Rp 2 = 0.987 and RMSEP = 0.033%. These results demonstrate the commercial feasibility of using near-infrared spectroscopy for the non-destructive prediction of protein content in both husked rice seeds and paddy rice.

Application of health technology assessment: a new need for an ethical neonatology.

New health technologies are constantly developing. However, their impacts on health and implications for health systems are not always clear. Faced with this situation, in the last 45 years, Health Technology Assessment (HTA) has taken an important role in the decision-making process related to the implementation of technologies in healthcare systems. According to the Core Model® EUnetHTA, a "full HTA" should cover nine domains: health problems and current use of technology, description and technical characteristics, safety, clinical effectiveness, costs and economic evaluation, ethical analysis, organizational aspects, patients and social aspects, legal aspects. In all domains of a HTA, the approach is evidence-based and uses epidemiological data, systematic reviews to gather the best level of proofs regarding clinical efficacy and safety of interventions and comparators and organizational and economic models. One exception is the ethical analysis, that uses value-based approach. Although in Neonatal Intensive Care Units (NICUs) there are highly advanced technological environments, HTA has not yet been widely used in this field for determining the "value" of the diagnostic and therapeutic procedures. An example of diagnostic tool used in NICUs is the near-infrared spectroscopy (NIRS), a noninvasive device that enables real-time monitoring of the condition of peripheral tissues in critically ill newborns. The availability of this diagnostic tool could improve the choice of the most appropriate treatment to the clinical situation of the newborn. The expected benefit of NIRS motivates the need of a full HTA. Conclusion: HTA is still little used in Neonatal Critical Care, but it may be the appropriate tool to determine the "value" of technologies used in this field. The implementation of clinical trials and HTA may help in an evidence-based evaluation of new technologies for the neonatal critical care. This could facilitate the rapid introduction of the best health technologies into clinical practice. What is Known: • Health Technology Assessment (HTA) has taken an important role in the decision-making process related to the implementation of technologies in healthcare systems • The centrality of ethics in HTA has been known. In fact, ethics is everywhere in HTA, and value judgments permeate all levels of HTA What is New: • HTA is still little used in Neonatal Critical Care, but it may be the appropriate tool to determine the "value" of technologies used in this field • The implementation of clinical trials and HTA may help in an evidence-based evaluation of new technologies for the neonatal critical care and in introduction of the best and ethically acceptable health technologies into clinical practice.

Prevalence of carotid artery stenosis and intra-cranial lesions in patients with aortic arch aneurysm and its association with intraoperative regional cerebral oxygen saturation and postoperative neurological outcomes.

Background: Although aortic aneurysm is associated with vascular aging and atherosclerosis, carotid and intracranial vascular disease prevalence in patients with aortic arch aneurysm remains unclear. Similarly, the effect of carotid and intracranial lesions on postoperative outcomes is unknown. This study aimed to investigate the prevalence of carotid artery stenosis and intracranial lesions in patients with aortic arch aneurysm and its association with intraoperative regional cerebral oxygen saturation (rScO2) and postoperative neurological outcomes, including delirium and cerebral infarction. Methods: This retrospective observational study included 133 patients with true aortic arch aneurysm who underwent preoperative magnetic resonance imaging (MRI). We evaluated the prevalence of carotid and intracranial arterial lesions. Symptomatic cerebral infarction and delirium, defined by the confusion assessment method for the intensive care unit, were evaluated for their association with preoperative cerebrovascular lesions. Additionally, changes in regional saturation of the cerebral tissue at different surgical phases were evaluated for patients with and without cerebrovascular lesions. Results: Fifteen (11.3%) patients experienced symptomatic cerebral infarction, and 64 (48.1%) had postoperative delirium. Preoperative MRI showed old infarction, microbleeds, significant carotid artery stenosis, and intracranial lesions in 21.1%, 14.3%, 10.5%, and 7.5% of the patients, respectively. White matter hyperintensities with Fazekas scale 2 were observed in 40.6% of the patients, while Fazekas scale 3 were observed in 18.8% of the patients. Preoperative MRI findings and postoperative neurological outcomes were not significantly different. Seventy-six patients underwent rScO2 monitoring intraoperatively. Changes in rScO2 in patients with and without carotid/cerebrovascular lesions were not significantly different. However, rScO2 was significantly lower in patients who developed cerebral infarction. Conclusions: Significant carotid artery stenosis and intracranial lesions were observed in 10.5% and 7.5% of the patients, respectively. Although preoperative MRI findings and changes in rScO2 or postoperative outcomes showed no significant association, patients with postoperative cerebral infarction showed significantly lower rScO2 intraoperatively.

[Evaluation of revascularization efficiency using near-infrared oximetry in patients with diabetic foot syndrome]. / Otsenka effektivnosti revaskulyarizatsii u patsientov s sindromom diabeticheskoi stopy metodom parainfrakrasnoi oksimetrii.

OBJECTIVE: To evaluate prognostic significance of tissue oximetry in healing of trophic defects in patients with diabetic foot syndrome (DFS) after endovascular revascularization. MATERIAL AND METHODS: In 42 patients with DFS, tissue oximetry was performed in angiosome projection with the FORE-SIGHT MC-2000 (CASMED) device before and the next day after revascularization of lower limb arteries. The 1st group included 30 patients with wound healing throughout 3 months, the 2nd group included 12 patients with amputation or no healing of trophic defects. RESULTS: Direct revascularization was more common in the 1st group (p=0.001). On the day after intervention, oxygen saturation (StO2) increased in all angiosomes in both groups (p<0.05). StO2 increment differed significantly between groups in all angiosomes except for point I (p<0.05). According to ROC analysis, StO2 increment by 4.5% in absolute values and 7.9% in percentage leads to trophic defect healing within 3 months (sensitivity and specificity were 76.7% and 66.7% for absolute values, 80% and 58.3% for percentage, respectively). CONCLUSION: Evaluation of StO2 in target angiosome may be valuable to predict trophic defect healing after endovascular surgery.

Mechanomyography reflects the changes in oxygenated hemoglobin during electrically evoked cycling in individuals with spinal cord injury.

BACKGROUND: Functional electrical stimulation (FES) cycling has been reported to enhance muscle strength and improve muscle fatigue resistance after spinal cord injury (SCI). Despite its proposed benefits, the quantification of muscle fatigue during FES cycling remains poorly documented. This study sought to quantify the relationship between the vibrational performance of electrically-evoked muscles measured through mechanomyography (MMG) and its oxidative metabolism through near-infrared spectroscopy (NIRS) characteristics during FES cycling in fatiguing paralyzed muscles in individuals with SCI. METHODS: Six individuals with SCI participated in the study. They performed 30 min of FES cycling with MMG and NIRS sensors on their quadriceps throughout the cycling, and the signals were analyzed. RESULTS: A moderate negative correlation was found between MMG root mean square (RMS) and oxyhaemoglobin (O2Hb) [r = -0.38, p = 0.003], and between MMG RMS and total hemoglobin (tHb) saturation [r = -0.31, p = 0.017]. Statistically significant differences in MMG RMS, O2Hb, and tHb saturation occurred during pre- and post-fatigue of FES cycling (p < 0.05). CONCLUSIONS: MMG RMS was negatively associated with O2Hb and muscle oxygen derived from NIRS. MMG and NIRS sensors showed good inter-correlations, suggesting a promising use of MMG for characterizing metabolic fatigue at the muscle oxygenation level during FES cycling in individuals with SCI.

Skeletal Anterior Open Bite Attenuates the Chewing-Related Increase in Brain Blood Flow.

The masticatory function of patients with skeletal anterior open bite (OPEN) is reported to be impaired compared with that of patients with normal occlusion (NORM). In this study, we compared brain blood flow (BBF) in patients with OPEN and NORM and investigated the factors related to BBF during mastication in patients with OPEN. The study included 17 individuals with NORM and 33 patients with OPEN. The following data were collected: number of occlusal contacts, jaw movement variables during mastication, and BBF measured with functional near-infrared spectroscopy during chewing. The number of occlusal contacts, maximum closing and opening speeds, closing angle, and vertical amplitude were smaller in the OPEN than in the NORM group. Interestingly, BBF increased less in the OPEN group. Correlation analysis revealed that several parameters, including number of occlusal contacts and closing angle, were correlated with changes in BBF during mastication. These results suggest that not only occlusion but also jaw movement variables and factors related to masticatory muscles contribute to the chewing-related increase in BBF. In conclusion, BBF increases less during mastication in patients with OPEN than in those with NORM. In addition, the higher increase in BBF is correlated with jaw movement. Together, we discovered that OPEN exhibits significant adverse effects not only on masticatory function but also on brain function.

Towards on-line cheese monitoring: Exploration of semi-hard cheeses using NIR and 1H NMR spectroscopy.

This study aims to investigate the potential of using advanced spectroscopies for cheese quality monitoring. For this purpose, six semi-hard cheeses manufactured using lactic acid bacteria (LAB) and/or propionic acid bacteria (PAB) were explored using near-infrared spectroscopy (NIRS) and Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy. The spectral data were analyzed using principal component analysis for extraction of possible discriminative patterns in quality parameters. The results show that the green analytical, but primarily bulk-sensitive, NIRS method was able to discriminate the cheese varieties primarily due to differences in the first overtone CH stretching region between 1650 and 1720 nm, in particular by the lactate methylene absorption at 1674 nm. A total of 25 metabolites were identified in the 1H NMR spectra of the cheese extracts, several of which were associated with the LAB and PAB metabolic pathways. PAB-associated metabolites include propionate, acetate, and glutamate, while LAB-associated metabolites include lactate and acetoin among others.

Bilateral Prefrontal Cortex Blood Flow Dynamics during Silent and Oral Reading Using Near-Infrared Spectroscopy.

This study aimed to investigate blood flow dynamics in the bilateral prefrontal cortex during silent and oral reading using near-infrared spectroscopy (NIRS). The subjects were 40 right-handed university students (20.5±1.8 years old, 20 men and 20 women). After completing the NIRS measurements, the subjects were asked to rate their level of proficiency in silent and oral reading, using a 5-point Likert scale. During oral reading, the left lateral prefrontal cortex (Broca's area) was significantly more active than the right side. During silent reading, prefrontal cortex activity was lower than that during oral reading, and there was no significant difference between both sides of the brain. A significant negative correlation was found between the change in oxy-hemoglobin (oxy-Hb) concentration in the left and right lateral prefrontal cortex during silent reading and silent reading speed. In addition, students with lower self-reported reading proficiency had significantly greater changes in oxy-Hb concentrations in the left and right lateral prefrontal cortex during silent/oral reading than did students with higher self-reported reading proficiency. Reading task assessment using NIRS may be useful for identifying language lateralization and Broca's area. The results demonstrate that NIRS is useful for assessing effortful reading and may be used to diagnose developmental dyslexia in children. J. Med. Invest. 71 : 92-101, February, 2024.

Advancing near-infrared spectroscopy: A synergistic approach through Bayesian optimization and model stacking.

Fourier transform near-infrared (FT-NIR) spectroscopy is a versatile and non-destructive analytical tool widely utilized in industries such as food, pharmaceuticals, and agriculture. While traditional FT-NIR instruments pose limitations in terms of cost and complexity, the advent of portable and affordable systems like NeoSpectra Scanners has broadened accessibility. Partial Least Squares Regression (PLSR) stands as an industry-standard method in Chemometrics for analyzing chemical compositions. This work addresses optimizing PLSR models in FT-NIR spectroscopy, focusing on enhancing accuracy and adaptability in material analysis. Unlike traditional PLSR models which often rely on grid searching a limited number of parameters, such as latent variables, the presented approach effectively expands the parameter space. A novel framework combining Bayesian search and stacking techniques is introduced to enable more customization while ensuring time and performance efficiency, along with automation in model development. Bayesian search efficiently explores hyperparameters space, enabling faster convergence to optimal model settings without exhaustive exploration. The proposed stacked model leverages learned knowledge from the top-performing PLSR models optimized through Bayesian methods, amalgamating a unified and potent body of knowledge. Bayesian-stacked models are compared with PLSR models that use grid search for a limited parameter set. Findings show a marked improvement in model performance: a 51.5% reduction in Root Mean Square Error (RMSE) for the training dataset and a 26.1% reduction for the testing dataset, alongside a 10.9% increase in the correlation coefficient square (R2) for the training dataset and a 10.4% increase for the testing dataset. Notably, Bayesian search reduces the model optimization time by approximately 90% compared with the grid search. Furthermore, when addressing instrumental variations, the models demonstrate an additional improvement, evident in the average reduction of 24.1% in the mean range of prediction. Overall, results demonstrate that the presented approach not only increases the prediction accuracy but also offers a more efficient, automated and robust solution for diverse spectroscopic applications.

Qualitative discrimination and quantitative prediction of microplastics in ash based on near-infrared spectroscopy.

Microplastics are recognized as a new environmental pollutant. Researchers have detected their presence in waste incineration ash. However, traditional testing methods take a very long testing period. There is a lack of research on detecting microplastics in waste incineration ash. In this paper, a portable near-infrared spectra (NIRS) spectrometer was used for qualitative discrimination and quantitative prediction of microplastics in ash. A total of 84 sets of simulated ash samples containing different types (PP, PS, PE, and PVC) and contents (2.4 wt% - 20 wt%) of microplastics were used in the model. The results show the qualitative discrimination model using support vector machines (SVM) method with multiplicative scatter correction (MSC) preprocessing could effectively identify the microplastic types in the ash with 100% detection accuracy. Furthermore, the partial least squares regression (PLSR) model was effective in quantitatively predicting the content of microplastics in ash. The Rp2 of the PP, PS, PE, and PVC models are 0.95, 0.93, 0.89, and 0.95, respectively. The RPD of the PP, PS, PE, and PVC models are 3.97, 3.96, 2.89 and 5.02, respectively. This study shows that microplastics in ash can be detected rapidly and accurately using portable near-infrared spectrometers.

The Effects of Neuromonitoring and Cerebrolysin Administration on Outcomes in Patients with Traumatic Brain Injury-An Interventional Pilot Study.

INTRODUCTION: Traumatic brain injury (TBI) is one of the most common causes of death and an important burden to the worldwide healthcare system and society. There is a lack of guidelines for types of monitoring or neuroprotective therapy. The aim of this pilot study was to assess its feasibility and, furthermore, to evaluate the impact of Cerebrolysin on the following clinical outcomes: length of stay, Glasgow Outcome Scale (GOS) and mortality. METHODS: A cohort of 56 patients was included in this non-randomised, real-time, pre-post-interventional study. The patients were assessed with the Glasgow Coma Scale (GCS) and divided into two groups: severe (GCS < 8) and non-severe (GCS > 8). After the radiological examination (CT scan), the patients were qualified for an immediate neurosurgical procedure if needed. The patients were admitted to the intensive care unit, where a standardised protocol for TBI treatment was implemented. Additional neuromonitoring was applied. RESULTS: There were 56 patients (19 females; 33.9%), of which 41 were considered severe cases; the patients were allocated to the Cerebrolysin (n = 25) or control groups (n = 31). In a generalised linear model (GLM) approach, the use of Cerebrolysin was associated with a decrease in the probability of death in non-severe patients (by 0.333 (standard error (SE) = 0.157, p = 0.034)) but not in severe patients (estimate (Est.) = -0.115, SE = 0.127, p = 0.364). Patients who received Cerebrolysin and who were neuromonitored had favourable outcomes and better survival rates. CONCLUSIONS: A multimodal treatment approach with monitoring and Cerebrolysin may have a beneficial effect on patients with less severe TBIs; however, the present study has multiple limitations, and further research is needed.

A Novel Variable Selection Method Based on Ordered Predictors Selection and Successive Projections Algorithm for Predicting Gastrodin Content in Fresh Gastrodia elata Using Fourier Transform Near-Infrared Spectroscopy and Chemometrics.

Gastrodin is one of the most important biologically active components of Gastrodia elata, which has many health benefits as a dietary and health food supplement. However, gastrodin measurement traditionally relies on laboratory and sophisticated instruments. This research was aimed at developing a rapid and non-destructive method based on Fourier transform near infrared (FT-NIR) to predict gastrodin content in fresh Gastrodia elata. Auto-ordered predictors selection (autoOPS) and successive projections algorithm (SPA) were applied to select the most informative variables related to gastrodin content. Based on that, partial least squares regression (PLSR) and multiple linear regression (MLR) models were compared. The autoOPS-SPA-MLR model showed the best prediction performances, with the determination coefficient of prediction (Rp2), ratio performance deviation (RPD) and range error ratio (RER) values of 0.9712, 5.83 and 27.65, respectively. Consequently, these results indicated that FT-NIRS technique combined with chemometrics could be an efficient tool to rapidly quantify gastrodin in Gastrodia elata and thus facilitate quality control of Gastrodia elata.

Identification of the human cerebral cortical hemodynamic response to passive whole-body movements using near-infrared spectroscopy.

The human vestibular system is crucial for motion perception, balance control, and various higher cognitive functions. Exploring how the cerebral cortex responds to vestibular signals is not only valuable for a better understanding of how the vestibular system participates in cognitive and motor functions but also clinically significant in diagnosing central vestibular disorders. Near-infrared spectroscopy (NIRS) provides a portable and non-invasive brain imaging technology to monitor cortical hemodynamics under physical motion. Objective: This study aimed to investigate the cerebral cortical response to naturalistic vestibular stimulation induced by real physical motion and to validate the vestibular cerebral cortex previously identified using alternative vestibular stimulation. Approach: Functional NIRS data were collected from 12 right-handed subjects when they were sitting in a motion platform that generated three types of whole-body passive translational motion (circular, lateral, and fore-and-aft). Main results: The study found that different cortical regions were activated by the three types of motion. The cortical response was more widespread under circular motion in two dimensions compared to lateral and fore-and-aft motions in one dimensions. Overall, the identified regions were consistent with the cortical areas found to be activated in previous brain imaging studies. Significance: The results provide new evidence of brain selectivity to different types of motion and validate previous findings on the vestibular cerebral cortex.

Multi-modality imaging of high-intensity plaques on non-contrast T1-weighted magnetic resonance imaging: a case report.

Background: Non-contrast T1-weighted imaging (T1WI) with cardiac magnetic resonance enables to evaluate the intensity of coronary plaque. Plaque-to-myocardial signal intensity ratio (PMR) has been shown to associate with an elevated risk of future coronary events. Of note, PMR >1.4 is a best cut-off value to identify high-risk plaque causing future coronary events. One recent study has reported intraluminal thrombus as a contributor to PMR. However, whether plaque material itself is associated with PMR has not been fully characterized yet. We present three cases with coronary artery stenosis evaluated by non-contrast T1WI-magnetic resonance imaging, optical coherence tomography (OCT) and near-infrared spectroscopy (NIRS)-intravascular ultrasound (IVUS) imaging. Case Description: Case 1 exhibited one lesion with high PMR (2.79) at the proximal segment of left anterior descending (LAD) artery. OCT imaging did not identify any obvious intra-luminal thrombus but the presence of lipid-rich plaque harboring cholesterol crystal at the corresponding lesion. In addition, an elevated maximum 4-mm lipid-core burden index (maxLCBI4mm) (=873) was observed at this lesion by NIRS/IVUS imaging. In case 2, PMR of coronary stenosis at the middle segment of LAD artery was 1.88. This lesion harboured lipidic materials without any thrombus on OCT imaging. NIRS-derived maxLCBI4mm was 725. Case 3 had a severe stenosis at the middle segment of LAD artery. This lesion exhibited a low PMR (0.90). On OCT and NIRS/IVUS imaging, this lesion was characterized as the presence of small lipid arc with a low maxLCBI4mm (=386). Conclusions: These cases showed the possible relationship of T1WI-derived PMR with the degree of lipidic plaque components.

Classifying Children with ADHD Based on Prefrontal Functional Near-infrared Spectroscopy Using Machine Learning.

Objective: : Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in children and adults characterized by cognitive and emotional self-control deficiencies. Previous functional near-infrared spectroscopy (fNIRS) studies found significant group differences between ADHD children and healthy controls during cognitive flexibility tasks in several brain regions. This study aims to apply a machine learning approach to identify medication-naive ADHD patients and healthy control (HC) groups using task-based fNIRS data. Methods: : fNIRS signals from 33 ADHD children and 39 HC during the Stroop task were analyzed. In addition, regularized linear discriminant analysis (RLDA) was used to identify ADHD individuals from healthy controls, and classification performance was evaluated. Results: : We found that participants can be correctly classified in RLDA leave-one-out cross validation, with a sensitivity of 0.67, specificity of 0.93, and accuracy of 0.82. Conclusion: : RLDA using only fNIRS data can effectively discriminate children with ADHD from HC. This study suggests the potential utility of the fNIRS signal as a diagnostic biomarker for ADHD children.

Do Vascular and Extracellular Measurements Consistently Reflect Intracellular pO2?

Oxygen measurements are routinely made either in the vasculature or in the extracellular fluid surrounding the cells of tissues. Yet, metabolic oxygen availability depends on the pO2 within the cells, as does the enhancing effect of oxygen on radiotherapy outcomes. This article reports quantitative modeling work examining the effect of cellular plasma membrane composition on tissue permeability, as a window into tissue oxygen gradients. Previous application of the model indicates that lipid-mediated diffusion pathways accelerate oxygen transfer from capillaries to intracellular compartments and that the extent of acceleration is modulated by membrane lipid and protein composition. Here, the effects of broken intercellular junctions and increased gap size between cells in the model are addressed. The conclusion is reached that the pO2 gradient will likely be consistent among similar, healthy tissues but may increase with increased interstitial fluid fraction and broken intercellular junctions. Therefore, tissue structural changes in tumors and other diseased or damaged tissues may lead to aberrations in permeability that confound interpretation of extracellular oxygen measurements.

Effects of Posture and Walking on Tibial Vascular Hemodynamics Before and After 14 Days of Head-Down Bed Rest.

Human skeletal hemodynamics remain understudied. Neither assessments in weight-bearing bones during walking nor following periods of immobility exist, despite knowledge of altered nutrient-artery characteristics after short-duration unloading in rodents. We studied 12 older adults (8 females, aged 59 ± 3 years) who participated in ambulatory near-infrared spectroscopy (NIRS) assessments of tibial hemodynamics before (PRE) and after (POST) 14 days of head-down bed rest (HDBR), with most performing daily resistance and aerobic exercise countermeasures during HDBR. Continual simultaneous NIRS recordings were acquired over the proximal anteromedial tibial prominence of the right lower leg and ipsilateral lateral head of the gastrocnemius muscle during supine rest, walking, and standing. During 10 minutes of walking, desaturation kinetics in the tibia were slower (time to 95% nadir values 125.4 ± 56.8 s versus 55.0 ± 30.1 s, p = 0.0014). Tibial tissue saturation index (TSI) immediately fell (-9.9 ± 4.55) and did not completely recover by the end of 10 minutes of walking (-7.4 ± 6.7%, p = 0.027). Upon standing, total hemoglobin (tHb) kinetics were faster in the tibia (p < 0.0001), whereas HDBR resulted in faster oxygenated hemoglogin (O2Hb) kinetics in both tissues (p = 0.039). After the walk-to-stand transition, changes in O2Hb (p = 0.0022) and tHb (p = 0.0047) were attenuated in the tibia alone after bed rest. Comparisons of NIRS-derived variables during ambulation and changes in posture revealed potentially deleterious adaptations of feed vessels after HDBR. We identify important and novel tibial hemodynamics in humans during ambulation before and after bed rest, necessitating further investigation. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.