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We present a comparative analysis of inertial-based odometry algorithms for the purpose of assisted return. An assisted return system facilitates backtracking of a path previously taken, and can be particularly useful for blind pedestrians. We present a new algorithm for path matching, and test it in simulated assisted return tasks with data from WeAllWalk, the only existing data set with inertial data recorded from blind walkers. We consider two odometry systems, one based on deep learning (RoNIN), and the second based on robust turn detection and step counting. Our results show that the best path matching results are obtained using the turns/steps odometry system.

Abstract Backgrounds Currently, family with sequence similarity 65 member A (FAM65A) is reported as a pivotal regulator in various cancers. However, the effect of FAM65A in lung squamous cell carcinoma (LSCC) is still unclear, the prime objective of this research is to explore the role of FAM65A in LSCC. Methods Gene expression data and correlated clinical information were downloaded from the public database and the expression of FAM65A was detected. The expression of FAM65A was also detected in our collected clinical samples and LSCC cell lines. Survival package of R language was used to determine the survival significance of FAM65A. Proteins expression level was determined via western blot assay. Cell function experiments and in vivo experiments were performed to explore the effect of FAM65A on LSCC cell biological behaviors. Results FAM65A expression was significantly increased in LSCC clinical samples and cell lines. High FAM65A expression predicted poor prognosis in LSCC patients. After silencing FAM65A, the ability of LSCC cell proliferation, invasion and migration was decreased, and LSCC cell cycle was blocked. Moreover, in vivo experiments revealed that silencing FAM65A could inhibit LSCC cell proliferation. Conclusions High FAM65A expression could enhance proliferative, invasive and migratory abilities of LSCC. FAM65A might be a novel biomarker of LSCC.

Abstract Objective Osteonecrosis of the femoral head (ONFH) is a severe disease that primarily affects the middle-aged population, imposing a significant economic and social burden. Recent research has linked the progression of non-traumatic osteonecrosis of the femoral head (NONFH) to the composition of the gut microbiota. Steroids and alcohol are considered major contributing factors. However, the relationship between NONFH caused by two etiologies and the microbiota remains unclear. In this study, we examined the gut microbiota and fecal metabolic phenotypes of two groups of patients, and analyzed potential differences in the pathogenic mechanisms from both the microbial and metabolic perspectives. Methods Utilizing fecal samples from 68 NONFH patients (32 steroid-induced, 36 alcohol-induced), high-throughput 16 S rDNA sequencing and liquid chromatography with tandem mass spectrometry (LC-MS/MS) metabolomics analyses were conducted. Univariate and multivariate analyses were applied to the omics data, employing linear discriminant analysis effect size to identify potential biomarkers. Additionally, functional annotation of differential metabolites and associated pathways was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Subsequently, Spearman correlation analysis was employed to assess the potential correlations between differential gut microbiota and metabolites. Results High-throughput 16 S rDNA sequencing revealed significant gut microbial differences. At the genus level, the alcohol group had higher Lactobacillus and Roseburia, while the steroid group had more Megasphaera and Akkermansia. LC-MS/MS metabolomic analysis indicates significant differences in fecal metabolites between steroid- and alcohol-induced ONFH patients. Alcohol-induced ONFH (AONFH) showed elevated levels of L-Lysine and Oxoglutaric acid, while steroid-induced ONFH(SONFH) had increased Gluconic acid and Phosphoric acid. KEGG annotation revealed 10 pathways with metabolite differences between AONFH and SONFH patients. Correlation analysis revealed the association between differential gut flora and differential metabolites. Conclusions Our results suggest that hormones and alcohol can induce changes in the gut microbiota, leading to alterations in fecal metabolites. These changes, driven by different pathways, contribute to the progression of the disease. The study opens new research directions for understanding the pathogenic mechanisms of hormone- or alcohol-induced NONFH, suggesting that differentiated preventive and therapeutic approaches may be needed for NONFH caused by different triggers.

Abstract Background For knee osteoarthritis patients, analyzing alignment of lower limbs is essential for therapy, which is currently measured from standing long-leg radiographs of anteroposterior X-ray (LLR) manually. To address the time wasting, poor reproducibility and inconvenience of use caused by existing methods, we present an automated measurement model in portable devices for assessing knee alignment from LLRs. Method We created a model and trained it with 837 conforming LLRs, and tested it using 204 LLRs without duplicates in a portable device. Both manual and model measurements were conducted independently, then we recorded knee alignment parameters such as Hip knee ankle angle (HKA), Joint line convergence angle (JCLA), Anatomical mechanical angle (AMA), mechanical Lateral distal femoral angle (mLDFA), mechanical Medial proximal tibial angle (mMPTA), and the time required. We evaluated the model’s performance compared with manual results in various metrics. Result In both the validation and test sets, the average mean radial errors were 2.778 and 2.447 (P0.05). Furthermore, the Bland-Altman 95% limits of agreement were less than ± 2° for HKA, JCLA, AMA, and mLDFA, and slightly more than ± 2 degrees for mMPTA. Conclusion The automatic measurement tool can assess the alignment of lower limbs in portable devices for knee osteoarthritis patients. The results are reliable, reproducible, and time-saving.

Abstract Creep is one of the typical mechanical properties of clay, and studying the creep mechanical properties of clay is of great significance to construction projects in clay sites. This study conducted creep tests on Chengdu clay and found that the soil mass underwent elastic deformation, decay creep deformation, steady-state creep deformation, and accelerated creep deformation. The isochronous stress ratio-logarithmic strain curves and their mathematical models were proposed to thoroughly analyze clay creep mechanical properties. Creep automatic feature points, such as linear elastic extreme point, initial yield point, long-term strength point, and plastic point, were identified on the curve. Considering the hardening and damage effects during creep loading, linear elastic and viscoelastic elements considering the time-dependent damage, a viscoplastic element considering the load hardening effect, and viscoplastic and plastic elements considering the load damage effect were established based on the element model and the Riemann–Liouville fractional derivative. Based on the mechanical properties of the whole clay creep process, the creep mechanical feature points, and the established element model, a clay creep model was proposed considering the hardening and damage effects. The rationality and regularity of the creep model were verified using the creep test data. This research accurately revealed the creep mechanical properties of clay and facilitated soil deformation prediction, thus providing technical guidance and references for construction projects in clay sites.

Background and purpose: GLP-1 receptor agonists are clinically utilized for type 2 diabetes and obesity. In vitro and in vivo preclinical studies were performed to assess the druggability of a novel small molecule GLP-1 receptor biased agonist SAL0112. Experimental approach: The HTRF assay, FLIPR assay, TR-FRET assay, and PathHunter assay were utilized for in vitro studies. Liver transporter tests were conducted using the HEK293-OATP1B1 and HEK293-OATP1B3 cell lines. In vitro stability assessments of various species and in vivo PK studies in rodents were performed. A model of type 2 diabetes and obesity induced by a high-energy diet in transgenic C57BL/6 mice expressing the human GLP-1 receptor gene was conducted. Principal results: SAL0112 demonstrated high potency and selectivity in activating the Gαs pathway of the GLP-1 receptor, with no observed desensitization. SAL0112 demonstrated greater stability in human and rat liver microsomes compared to Danuglipron. In vivo PK studies revealed higher absorption of SAL0112 in rats. SAL0112 displayed a significantly lower potential for DDI on liver transporters compared to Danuglipron. SAL0112 led to significant reductions in body weight (P

IntroductionVariability in microbial residues within soil aggregates are becoming progressively essential to the nutritive and sustainability of soils, and are therefore broadly regarded as an indispensable part of soil organic matter. It is unexplored how the widespread implementation of microbial fertilisers in agricultural production impacts soil organic nutrients, in particular the microbial residue fraction.MethodsWe performed a three-year field experiment to verify the distinct impacts of microbial and organic fertilizers on carbon accumulation in soil microbial leftovers among aggregate fractions.ResultsMicrobial residual carbon was shown to decrease insignificantly during the application of microbial fertilizer and to rise marginally afterwards with the utilization of organic fertilizer. However, the combined effects of the two fertilizers had substantial impacts on the accumulation of microbial residual carbon. Changes in the structure of the fungi and bacteria shown in this study have implications for the short-term potential of microbial fertilizer shortages to permanent soil carbon sequestration. Additionally, our findings revealed variations in microbial residue accumulation across the microbial fertilizers, with Azotobacter chroococcum fertilizer being preferable to Bacillus mucilaginosus fertilizer due to its higher efficiency. In this scenario of nutrient addition, fungal residues may serve as the primary binding component or focal point for the production of new microaggregates, since the quantity of SOC provided by fungal residues increased while that supplied by bacterial residues decreased.DiscussionOur findings collectively suggested that the mechanisms behind the observed bacterial and fungal MRC (microbial residue carbon) responses to microbial fertilizer or organic fertilizer in bamboo forest soils are likely to be distinct. The application of microbial fertilizers for a limited duration led to a decline soil stable carbon pool, potentially influencing the regulation of soil nutrients in such hilly bamboo forests.

Background: This study clarified the expression of cicrTLK1 in non-small cell lung cancer (NSCLC) and explored its role in cancer growth, metastasis and immune escape, providing a potential molecular target and theoretical basis for NSCLC treatment. Methods: The expression levels of circTLK1, miR-876-3p and SRSF7 were determined by RT-qPCR assay. The localization of circTLK1 in NSCLC cells was determined by FISH assay. EdU and cell plate clone formation assay were applied to explore cell proliferation. Wound healing test and Transwell assay were applied to measure the migration and invasion ability. Cell apoptosis rate was detected by FCM assay. Western blotting assay was adopted to measure the protein expression of SRSF7. Dual-luciferase reporter gene assay was applied to assess the interaction between miR-876-3p and circTLK1, and between miR-876-3p and SRSF7. The ability of cirTLK1 to regulate tumor formation in vivo was examined by tumor transplantation experiments in nude mice. Results: The relative expression of circTLK1 was increased in NSCLC cell lines. Knockdown of circTLK1 prohibited the proliferation, migration, and invasion, and promoted apoptosis rate, but miR-876-3p inhibitor reversed the effects of circTLK1 knockdown. In addition, silencing of circTLK1 overtly restrained the growth of transplanted tumors in vivo, and inhibited immune escape. In addition, circTLK1 interacted with miR-876-3p, and SRSF7 was concluded to be the target gene of miR-876-3p. Conclusion: In this study, we researched the inhibitory effect of circTLK1knockdown on NSCLC progression and immune escape, and further elucidated the potential regulatory mechanism of circTLK1/miR876-3p/SRSF7 axis.

Although more attention has been paid to microplastics (MPs) pollution in environment, research on the synthetic influence of microplastic and heavy metals remains limited. To help fill this information gap, we investigated the adsorption behavior of virgin polyvinyl chloride microplastics (PVCMPs) (≤450 µm white spherical powder) on cadmium (II). The effects on seed germination, seedling growth, photosynthetic system, oxidative stress indicators of lettuce, and changes in Cd bioavailability were evaluated under Cd2+ (25 μmol/L), PVCMPs (200 mg/L), and PVCMP-Cd combined (200 mg/L + 25 μmol/L) exposures in hydroponic system. The results demonstrated that the PVCMPs effectively adsorbed Cd ions, which validated by the pseudo-second-order kinetic and the Langmuir isotherm models, indicating the sorption of Cd2+ on the PVCMPs was primary chemisorption and approximates monomolecular layer sorption. Compared to MPs, Cd significantly inhibits plant seed germination and seedling growth and development. However, Surprising improvement in seed germination under PVCMPs-Cd exposure was observed. Moreover, Cd2+ and MPs alone or combined stress caused oxidative stress with reactive oxygen species (ROS) including H2O2, O2- and Malondialdehyde (MDA) accumulation in plants, and substantially damaged to photosynthesis. With the addition of PVCMPs, the content of Cd in the leaves significantly (P

The Sc@P10C12M2 catalysts were first constructed and utilized for methanol conversion reaction. In this work, DFT-D3 calculations were employed to investigate the conversion of CH3OH to CHOOCH3 on four different types of the Sc@P10C12M2 catalysts (M = Fe, Co, Ni, and Cu). The results indicate that the selectivity and formation activity of CHOOCH3 are influenced by the choice of metals. Specifically, the Sc@P10C12Ni2 catalyst demonstrates superior catalytic activity with an activation free energy and activity of 0.64 eV and 1.97 lgk/s−1 for the rate-limiting step at 298 K.This research reveals a structure–activity relationship for Sc@P10C12M2 catalysts, highlighting that catalytic performance is correlated with metal types, spin states, and charges. These insights provide theoretical guidance for the rational design of efficient methanol conversion catalysts.

Balance plays a crucial role in human life and social activities. Maintaining balance is a relatively complex process that requires the participation of various balance control subsystems (BCSes). However, previous studies have primarily focused on evaluating an individual’s overall balance ability or the ability of each BCS in isolation, without considering how they influence (or interact with) each other. The first study used clinical scales to evaluate the functions of the four BCSes, namely Reactive Postural Control (RPC), Anticipatory Postural Adjustment (APA), Dynamic Gait (DG), and Sensory Orientation (SO), and psychological factors such as fear of falling (FOF). A hierarchical structural equation modeling (SEM) was used to investigate the relationship between the BCSes and their association with FOF. The second study involved using posturography to measure and extract parameters from the center of pressure (COP) signal. SEM with sparsity constraint was used to analyze the relationship between vision, proprioception, and vestibular sense on balance based on the extracted COP parameters. The first study revealed that the RPC, APA, DG and SO indirectly influenced each other through their overall balance ability, and their association with FOF was not the same. APA has the strongest association with FOF, while RPC has the least association with FOF. The second study revealed that sensory inputs, such as vision, proprioception, and vestibular sensing, directly affected each other, but their associations were not identical. Among them, proprioception plays the most important role in the three sensory subsystems. This study provides the first numerical evidence that the BCSes are not independent of each other and exist in direct or indirect interplay. This approach has important implications for the diagnosis and management of balance-related disorders in clinical settings and improving our understanding of the underlying mechanisms of balance control.

The management of indoor humidity through equipment consumes massive energy, leading to the growing interest in passive regulation of indoor humidity via moisture buffering. Numerous factors may impact the performance of interior finishing material during moisture regulation, thus identifying the dominant parameters is critical for moisture buffering effect optimization. This study analyzes the influence of five moisture and surface parameters, which are directly related to the moisture transfer of the interior finishing layer, on the thermal loads in a typical office building under typical climates in China. The analysis employs scatter plots and sensitivity indices based on Sobol's method. The results show that the material thickness plays a decisive role under different climates. The importance of sorption isotherm varies with climates and load types. The vapor diffusion resistance factor of the material only affects the latent heat loads, while the effect of the surface vapor transfer resistance is negligible. Finally, this study puts forward suggestions for interior finishing material selection to achieve low-load performance based on the characteristics of parameter combinations.

Abstract Ubiquitin-specific protease 4 (USP4) represents a potential oncogene involved in various human cancers. Nevertheless, the biological roles and precise mechanism of USP4 in esophageal squamous cell carcinoma (ESCC) progression are not understood. Here, USP4 expression was found to be markedly upregulated in ESCC tumor tissues and cells. Loss- and gain-of-function assays suggested that USP4 silencing inhibited ESCC cell proliferation, migration, and invasion, while USP4 overexpression promoted these behaviors. Consistently, USP4 silencing repressed tumor growth and metastasis in an ESCC nude mouse model in vivo. As a target molecule of USP4, transforming growth factor-β-activated kinase 1 (TAK1) also showed high expression in ESCC. Moreover, we observed that USP4 specifically interacted with TAK1 and stabilized TAK1 protein levels via deubiquitination in ESCC cells. Importantly, USP4 promotes ESCC proliferation, migration, and invasion via the MEK/ERK signaling pathway and can be inhibited by U0126. Neutral red (NR), an inhibitor of USP4 can suppress ESCC progression in vitro and in vivo. Overall, this study revealed that USP4/TAK1 plays crucial roles in ESCC progression by modulating proliferation, migration, and invasion, and USP4 might be a potential therapeutic target in ESCC.

In order to utilize the advantage of the feature map in calculating efficiency and solve the problem that the traditional dynamic window approach is sensitive to global parameters, a path planning fusion algorithm based on feature map is proposed. A feature map expression applicable to path planning is given, and the detection of obstacles in the feature map is achieved by improving the calculation method of the distance between the robot and the obstacles. Combined with the basic principle of the Bug algorithm and the properties of line segment features, the searching and optimization algorithm is used to search the global feasible path first, and then the key nodes of the global optimal path are obtained by node optimization, and solutions are proposed for the problems of search direction selection at internal and external corner points and obstacle endpoint bypassing. To address the problem of high sensitivity of the traditional dynamic window approach to global parameters, the degree of influence of the parameters in the objective function on the planned path when the robot is at different positions is analyzed, and the original objective function is improved using the dynamic parameter approach. When the algorithms are fused, the calculation method of direction function in the objective function is improved in order to solve the problem that the robot may slow down in the intermediate nodes of the path. The simulation experiment verifies that the searching optimization algorithm is effective, the improved dynamic window approach reduces the sensitivity of parameters, and the fusion algorithm has a greater advantage in computational efficiency, with a maximum reduction of 79.27% and a minimum reduction of 43.16% in computational time consumption, and the robot moves more smoothly.

Abstract Background This meta-analysis compares the efficacy of unilateral biportal endoscopic transforaminal lumbar interbody fusion (UBE-TLIF) to conventional interbody fusion in lumbar degenerative diseases (LDD). Methods An extensive literature search was conducted in PubMed, Web of Science, and the Cochrane Library. Research related to UBE-TLIF published up to November 2022 was reviewed. The relevant articles were selected based on inclusion and exclusion criteria, as well as an evaluation of the quality of the data extraction literature. Meta-analysis was performed using Review Manager 5.3 software. Results This meta-analysis included six high-quality case–control trials (CCTs) involving 621 subjects. The clinical outcomes assessment showed no statistical differences in complication rates, fusion rates, leg pain VAS scores, or ODI scores. After UBE-TLIF, low back pain VAS scores were significantly improved with less intraoperative blood loss and a shorter hospital stay. A longer time was required for UBE-TLIF, however. Conclusion Despite the lack of sufficient high quality randomized controlled trials (RCTs) in this study, the results of this meta-analysis suggest that UBE-TLIF is more effective than open surgery in terms of length of stay, blood loss reduction during surgery, and improved low back pain after surgery. Nevertheless, the evidence will be supplemented in the future by more and better quality multicenter randomized controlled trials.

Abstract Background Acute coronary syndromes (ACS) are the leading cause of global death. Optimizing mortality risk prediction and early identification of high-risk patients is essential for developing targeted prevention strategies. Many researchers have built machine learning (ML) models to predict the mortality risk in ACS patients. Our meta-analysis aimed to evaluate the predictive value of various ML models in predicting death in ACS patients at different times. Methods PubMed, Embase, Web of Science, and Cochrane Library were searched systematically from database establishment to March 12, 2022 for studies developing or validating at least one ML predictive model for death in ACS patients. We used PROBAST to assess the risk of bias in the reported predictive models and a random-effects model to assess the pooled C-index and accuracy of these models. Results Fifty papers were included, involving 216 ML prediction models, 119 of which were externally validated. The combined C-index of the ML models in the validation cohort predicting the in-hospital mortality, 30-day mortality, 3- or 6-month mortality, and 1 year or above mortality in ACS patients were 0.8633 (95% CI 0.8467–0.8802), 0.8296 (95% CI 0.8134–0.8462), 0.8205 (95% CI 0.7881–0.8541), and 0.8197 (95% CI 0.8042–0.8354), respectively, with the corresponding combined accuracy of 0.8569 (95% CI 0.8411–0.8715), 0.8282 (95% CI 0.7922–0.8591), 0.7303 (95% CI 0.7184–0.7418), and 0.7837 (95% CI 0.7455–0.8175), indicating that the ML models were relatively excellent in predicting ACS mortality at different times. Furthermore, common predictors of death in ML models included age, sex, systolic blood pressure, serum creatinine, Killip class, heart rate, diastolic blood pressure, blood glucose, and hemoglobin. Conclusions The ML models had excellent predictive power for mortality in ACS, and the methodologies may need to be addressed before they can be used in clinical practice.

Background: Corn peptides, a novel food prepared from corn gluten meal (CGM) by enzymatic hydrolysis or microbial fermentation, have attracted considerable interest owing to their various bioactive properties. However, the underlying mechanism of corn peptides attenuate non-alcoholic fatty liver disease (NAFLD) remains unclear. Objective: This study aimed to investigate the effect of corn peptides in NAFLD and to decipher the underlying mechanisms. Design: NAFLD was induced by a high-fat diet (HFD) for 10 weeks. Corn peptides were administered during the period. Human hepatocellular carcinomas (HepG2) cells induced by free fatty acids were used for this mechanism study. Results: Corn peptides alleviated HFD-induced histopathological changes, disorders of lipid metabolism, and mitochondrial damage. Moreover, corn peptides blocked mitophagy suppression by HFD based on the increased LC3, ATG7 expressions, as well as decreased P62 levels. Corn peptides increased the expression of proteins involved in fatty acid β-oxidation, such as PPARα and PGC-1α. Corn peptides also improved the Ser/Thr kinase PINK1 (PINK1) and the E3 ubiquitin ligase Parkin (Parkin) translocation to mitochondria, which is confirmed by immunofluorescence. Furthermore, stable knockdown of PINK1 by PINK1 SiRNA in HepG2 inhibited PINK1-Parkin-associated mitophagy and resulted in lipid accumulation. Conclusion: Corn peptides improved cell injury and ameliorated mitochondrial dysfunction and lipid accumulation via PINK1/Parkin-mediated autophagy in NAFLD. Thus, corn peptides could be a promising nutritional molecule with natural functions for preventing NAFLD.

Abstract For the dual active bridge (DAB) DC‐DC converters, parameter uncertainty (circuit parameters, input and/or load perturbations) affect their performance, such as the dynamic performance and backflow power. Here, to deal with the uncertainties, a robust model predictive control (RMPC) for the DAB DC‐DC converter under extended‐phase‐shift (EPS) control is proposed to improve dynamic performance and reduce the backflow power of the DAB for the first time. First, a cost function consisting of backflow power and the output voltage is established. Second, considering the uncertainty of the circuit parameters, a robust term is added to the prediction model to increase the robustness. Finally, the effectiveness and superiority of the proposed method are verified by experiments and comparisons with existing methods. The proposed RMPC method shows superior performance in the sense of improved dynamic performance and reduced backflow power.

In the process of locating mixed far-field and near-field sources, sparse nonlinear arrays (SNAs) can achieve larger array apertures and higher degrees of freedom compared to traditional uniform linear arrays (ULAs) with the same number of sensors. This paper introduces a Modified Symmetric Nested Array (MSNA), which can automatically generate the optimal array structure with the maximum continuous lags for a given number of sensors. To effectively address mixed source localization, we designed an estimation algorithm based on high-order cumulants and the subarray partition method, applied to the MSNA. Firstly, a specialized fourth-order cumulant matrix, relevant only to Direction of Arrival (DOA) information, is constructed for the DOA estimation of mixed sources. Then, peak searching using the estimated DOA information enables the estimation of the distance parameters, effectively separating mixed sources. The algorithm has moderate computational complexity and provides high resolution and estimation accuracy. Numerical simulation results demonstrate that, with the same number of physical sensors, the proposed MSNA provides more continuous lags than existing arrays, offering higher degrees of freedom and estimation accuracy.

Introduction: The stress-strain relationship of clays characterized by strain hardening exhibits varying curves under different confining pressures and dry densities.Methods: Considering the viscoelastic properties of clays, a normalized viscoelastic model of strain-hardening clay was established based on fractional derivatives, and normalization factors were proposed.Results: The experimental results showed that the stress-strain relationship of the clay was strain hardening. It shows that Chengdu clay has better normalization conditions. Furthermore, the normalized analysis of this clay through the viscoelastic normalization model revealed that the straight line of normalized data displayed a goodness-of-fit of over 0.98. The obtained values were consistent with experimental results, suggesting the reasonability of the normalized strain-hardening parameters and elastic moduli.Discussion: In addition, the superiority of the developed model was verified by testing the strain-hardening clays in Wuhan, China and Bangkok, Thailand. After analyzing the strain-hardening parameters and normalization factors of our model, it was found that the slope of the normalized line can accurately reflect the strain-hardening ability of the clay. These findings demonstrated that the proposed normalization factor is preferred for a normalized viscoelastic model. It shows that the model proposed in this paper has clearer physical meaning and advancement.

The severity of the pandemic and its consequences on health and social care systems were quite diverse and devastating. COVID-19 was associated with an increased risk of neurological and neuropsychiatric disorders after SARS-CoV-2 infection. We did a cross-sectional study of 3 months post-COVID consequences of 178 Cuban subjects. Our study has a unique CUBAN COVID-19 cohort of hospitalized COVID-19 patients and healthy subjects. We constructed a latent variable for pre-health conditions (PHC) through Item Response Theory (IRT) and for post-COVID neuropsychiatric symptoms (Post-COVID-NPS) through Factor Analysis (FA). There seems to be a potential causal relationship between determinants of CIBD and post-COVID-NPS in hospitalized COVID-19 patients. The causal relationships accessed by Structural Equation Modeling (SEM) revealed that PHC (p < 0.001) and pre-COVID cognitive impairments (p < 0.001) affect the severity of COVID-19 patients. The severity of COVID-19 eventually results in enhanced post-COVID-NPS (p < 0.001), even after adjusting for confounders (age, sex, and pre-COVID-NPS). The highest loadings in PHC were for cardiovascular diseases, immunological disorders, high blood pressure, and diabetes. On the other hand, sex (p < 0.001) and pre-COVID-NPS including neuroticism (p < 0.001), psychosis (p = 0.005), cognition (p = 0.036), and addiction (p < 0.001) were significantly associated with post-COVID-NPS. The most common neuropsychiatric symptom with the highest loadings includes pain, fatigue syndrome, autonomic dysfunctionalities, cardiovascular disorders, and neurological symptoms. Compared to healthy people, COVID-19 patients with pre-health comorbidities or pre-neuropsychiatric conditions will have a high risk of getting severe COVID-19 and long-term post-COVID neuropsychiatric consequences. Our study provides substantial evidence to highlight the need for a complete neuropsychiatric follow-up on COVID-19 patients (with severe illness) and survivors (asymptomatic patients who recovered).