Prioritization of therapeutic targets for cancers using integrative multi-omics analysis.

BACKGROUND: The integration of transcriptomic, proteomic, druggable genetic and metabolomic association studies facilitated a comprehensive investigation of molecular features and shared pathways for cancers' development and progression. METHODS: Comprehensive approaches consisting of transcriptome-wide association studies (TWAS), proteome-wide association studies (PWAS), summary-data-based Mendelian randomization (SMR) and MR were performed to identify genes significantly associated with cancers. The results identified in above analyzes were subsequently involved in phenotype scanning and enrichment analyzes to explore the possible health effects and shared pathways. Additionally, we also conducted MR analysis   to investigate metabolic pathways related to cancers. RESULTS: Totally 24 genes (18 transcriptomic, 1 proteomic and 5 druggable genetic) showed significant associations with cancers risk. All genes identified in multiple methods were mainly enriched in nuclear factor erythroid 2-related factor 2 (NRF2) pathway. Additionally, biosynthesis of ubiquinol and urate were found to play an important role in gastrointestinal tumors. CONCLUSIONS: A set of putatively causal genes and pathways relevant to cancers were identified in this study, shedding light on the shared biological processes for tumorigenesis and providing compelling genetic evidence to prioritize anti-cancer drugs development.

Genetically evaluating the causal role of peripheral immune cells in colorectal cancer: a two-sample Mendelian randomization study.

BACKGROUND: Investigating novel therapeutic strategies for colorectal cancer (CRC) is imperative. However, there is limited research on the use of drugs to target peripheral blood immune cells in this context. To address this gap, we performed a two-sample Mendelian randomization (MR) analysis to identify potential therapeutic targets for CRC. METHODS: We applied two-sample MR to identify the causal relationship between peripheral blood immune cells and CRC. GWAS data were obtained from the IEU OPEN GWAS project. Based on the implications from the MR results, we conducted a comprehensive database search and genetic analysis to explore potential underlying mechanisms. We predicted miRNAs for each gene and employed extensive research for potential therapeutic applications. RESULTS: We have identified causal associations between two peripheral immune cells and colorectal cancer. Activated & resting Treg %CD4 + cell was positively associated with the risks of CRC, while DN (CD4-CD8-) %leukocyte cell exhibited a protective role in tumor progression. NEK7 (NIMA related kinase 7) and LHX9 (LIM homeobox 9) expressed in Treg cells were positively associated with CRC risks and may play a vital role in carcinogenesis. CONCLUSIONS: This study identified causal relationship between peripheral immune cell and CRC. Treg and DN T cells were implicated to own promoting and inhibiting effects on CRC progression respectively. NEK7 and LHX9 in Treg cells were identified as potential biotarget for antitumor therapies.

LncRNA-EWSAT1 promotes hepatocellular carcinoma metastasis via activation of the Src-YAP signaling axis.

Regardless of the improvements in diagnostic and therapeutic methods, the clinical outcomes of hepatocellular carcinoma (HCC) patients remain poor. Although accumulating evidence indicates that lncRNAs (long noncoding RNAs) are essential within the control of tumorigenesis and the metastasis of cancer, the underlying mechanisms remain largely unknown. This work explored the pattern of expression and functional significance of a newly found lncRNA, Ewing sarcoma-associated transcript 1 (EWSAT1), in HCC metastasis. The results indicated that EWSAT1 was upregulated significantly in HCC relative to that in normal tissues and was correlated with an aggressive phenotype and low patient survival. Functional experiments demonstrated that EWSAT1 could promote proliferation and HCC cell metastasis both in vitro and in vivo. Mechanistically, EWSAT1 binds directly to Yes-associated protein (YAP), promotes Sarcoma gene (Src)-induced phosphorylation of YAP, facilitates nuclear translocation of YAP, and consequently, activates the transcription of Hippo-YAP signaling target genes involved in cancer evolution. This study found that EWSAT1 plays a crucial role in HCC metastasis and that it has the potential to be a prognosis biomarker and a target for therapeutics.

para-Selective, Direct C(sp2)-H Alkylation of Electron-Deficient Arenes by the Electroreduction Process.

Direct para-selective C(sp2)-H alkylation of electron-deficient arenes based on the electroreduction-enabled radical addition of alkyl bromides has been developed under mild conditions. In the absence of any metals and redox agents, the simple electrolysis system tolerates a variety of primary, secondary, and tertiary alkyl bromides and behaves as an important complement to the directed alkylation of the C(sp2)-H bond and the classic Friedel-Crafts alkylation. This electroreduction process provides a more straightforward, environmentally benign, and effective alkylation method for electron-deficient arenes.

Machine learning accelerated search for the impact limit of the graphene/aluminum alloy whipple structure.

This paper proposes a Whipple structure to enhance the impact resistance of graphene/aluminum alloy composites by varying the interlayer spacing between graphene and aluminum alloy. The increased interlayer spacing provides more deformation space for the graphene to absorb more deformation energy, and enables the formation of a debris cloud from the bullet fragments and graphene fragments, significantly reducing the impact energy per unit area of the next material. The impact limit serves as a critical metric for assessing the impact resistance of the Whipple structure. Based on molecular dynamics simulations, we developed a machine learning model to predict the protection of aluminum alloy, and quickly determined the impact limits of velocity, bullet radius, and interlayer spacing by using the machine learning model. An empirical equation for the impact limit of interlayer spacing was established. The results showed that non-zero interlayer spacing can significantly improve the impact resistance of the hybrid structure; to fully exploit the superior impact resistance of this Whipple structure, the number of graphene layers should be at least 3. Furthermore, at high impact velocities and large bullet radii, the impact limit of the interlayer spacing exhibits a substantial correlation with the number of graphene layers. These results provide valuable information for the design of the impact resistance of the graphene/aluminum alloy composites.

Pharmacokinetic analysis of ceftazidime and cefazolin in the treatment of continuous ambulatory peritoneal dialysis-related peritonitis.

OBJECTIVE: Peritoneal dialysis-related peritonitis (PDRP) presents a significant challenge for nephrologists. Continuous intraperitoneal cefazolin and ceftazidime are recommended for the treatment of peritonitis. However, some pharmacokinetic studies have shown that doses of 15-20 mg/kg/d may not achieve sufficient therapeutic levels. In this study, we investigated the pharmacokinetics of ceftazidime and cefazolin in patients with continuous ambulatory peritoneal dialysis-related peritonitis and compared the pharmacokinetic characteristics between traditional and modified treatment groups. METHODS: From February 2017 to December 2019, 42 PDRP patients (17 males, 25 females; mean age: 50.7 ± 12.1 years; mean body weight: 60.9 ± 11.8 kg) were recruited for the study, all participants were anuric. Twenty patients were enrolled in the traditional group and treated with cefazolin (1.0 g) and ceftazidime (1.0 g) via intraperitoneal administration once daily for 14 days. Twenty-two patients were enrolled in the modified group and received the same dose of antibiotics twice daily for the initial five days, followed by once daily for the subsequent nine days. Serum and dialysate samples were collected after days 1, 2, 3, 5, 7, 10, and 14 and analyzed via liquid chromatography-mass spectrometry. RESULTS: In the traditional group, the highest and lowest serum concentrations of ceftazidime were 35.9 and 21.7 µg/mL, respectively. The highest concentration of cefazolin was 54.6 µg/mL on day 5 and the lowest concentration was 30.4 µg/mL on day 1. In the modified group, the highest and lowest serum concentrations of ceftazidime were 102.2 and 54.8 µg/mL, respectively. The highest concentration of cefazolin was 141.7 µg/mL and the lowest concentration was 79.8 µg/mL. All antibiotic concentrations were above the minimum inhibitory concentration (MIC) level (8 µg/mL of ceftazidime and 2 µg/mL of cefazolin) throughout the treatment period. However, on day 1, the concentration of ceftazidime in the third bag of dialysate effluent from the traditional group fell below the MIC level. Despite remaining above the MIC, cefazolin concentration was consistently lower in the third bag of dialysate effluent from the traditional group throughout the treatment period. CONCLUSIONS: Intraperitoneal administration of cefazolin and ceftazidime at a dose of 1 g twice daily for 5 days and then once daily for the rest of the treatment period ensured adequate therapeutic levels of antibiotics for treating anuric PDRP patients.

Glycopolymer Nanoparticles with On-Demand Glucose-Responsive Insulin Delivery and Low-Hypoglycemia Risks for Type 1 Diabetic Treatment.

Diabetic patients with type 1 or advanced type 2 stages need timely and precise insulin injection to regulate the daily blood glucose levels (BGLs). Otherwise, risks of serious or even deadly diabetes-associated complications occur. To achieve prolonged glucose regulation and low hypoglycemia risks, a novel on-demand glucose-responsive glycopolymer system was constructed for insulin delivery, which was self-assembled into nanoparticles by dynamic covalent bonds between two polymers: fluorophenylboronic acid-grafted polymer (poly-F) and polyol polymer (poly-G). Insulin was loaded during the assembly process. The nanoparticles showed excellent glucose responsiveness in vitro, with controlled insulin release at different glucose concentrations. In vivo treatment on type 1 diabetic mice showed prolonged BGL regulation and lower hypoglycemia risks. The mild preparation of the nanoparticles and outstanding glucose control shed light on the optional diabetic treatment for further clinical use.

NIR Activated Upper Critical Solution Temperature Polymeric Micelles for Trimodal Combinational Cancer Therapy.

The balance between drug efficiency and its side effects on normal tissues is still a challenging problem to be solved in current cancer therapies. Among different strategies, cancer therapeutic methods based on nanomedicine delivery systems have received extensive attention due to their unique advantages such as improved circulation and reduced toxicity of drugs in the body. Herein, we constructed dual-responsive polymeric micelles DOX&ALS@MFM based on an upper critical solution temperature (UCST) polymer to simultaneously combine chemotherapy, photothermal therapy (PTT), and photodynamic therapy (PDT). Amphiphilic block copolymer P(AAm-co-AN)-b-PEI-ss-PEG-FA with a critical point of 42 °C was able to self-assemble into polymeric micelles under physiological conditions, which further encapsulated anticancer drug doxorubicin (DOX) and photosensitizer ALS to obtain drug-loaded micelles DOX&ALS@MFM. Micelles aggregated at tumor sites due to folate targeting and an enhanced permeability retention (EPR) effect. After that, the high intracellular concentration of glutathione (GSH) and near-infrared (NIR) light prompted disassembly of the polymer to release DOX and ALS. ALS not only plays a role in PTT but also produces singlet oxygen, therefore killing tumor cells by PDT. Both in vitro and in vivo studies demonstrated the photothermal conversion and reactive oxygen species generation ability of DOX&ALS@MFM micelles, at the same time as the excellent inhibitory effect on tumor growth with NIR light irradiation. Thus, our research substantiated a new strategy for the biomedical application of UCST polymers in the cited triple modal tumor therapy.

An Endoplasmic Reticulum (ER)-Targeting DNA Nanodevice for Autophagy-Dependent Degradation of Proteins in Membrane-Bound Organelles.

Targeted protein degradation via proteasomal and lysosomal pathways is a promising therapeutic approach, and proteins in cytoplasm or on the cell membrane can be easily contacted and have become the major targets. However, degradation of disease-related proteins that exist in membrane-bound organelles (MBO) such as the endoplasmic reticulum (ER) remains unsolved due to the membrane limits. Here we describe a DNA nanodevice that shows ER targeting capacity and undergoes new intracellular degradation via the autophagy-dependent pathway. Then the DNA nanostructure functionalized with specific ligands is used to selectively catch ER-localized proteins and then transport them to the lysosome for degradation. Through this technique, the degradation of both exogenous ER-resident protein (ER-eGFP) and endogenous overexpressed molecular chaperone (glucose-regulated protein 78) in cancer cells has been successfully executed with high efficiency.

The effectiveness of active surveillance measures for COVID-19 cases in Pudong New Area Shanghai, China, 2020.

The aim of this study was to thoroughly document the effects of multiple intervention and control methods to mitigate the ongoing coronavirus disease 2019 (COVID-19) outbreak in Pudong New Area, Shanghai. After identification of the first confirmed case of COVID-19 in Pudong on January 21, 2020, the local Center for Disease Control and Prevention (CDC) launched a case investigation involving isolation, close-contact (CC) tracing and quarantine of persons with a potential exposure risk to prevent and control transmission. Epidemiological features of cases detected by three different strategies were compared to assess the impact of these active surveillance measures. As of February 16, 2020, a total of 108 confirmed COVID-19 cases had been identified in Pudong, Shanghai. Forty-five (41.67%) cases were identified through active surveillance measures, with 22 (20.37%) identified by CC tracing and 23 (21.30%) by quarantine of potential exposure populations (PEPs). The average interval from illness onset to the first medical visit was 1 day. Cases identified by CC tracing and PEPs were quarantined for 0.5 and 1 day before illness onset, respectively. The time intervals from illness onset to the first medical visit and isolation among actively screened cases were 2 days (p = .02) and 3 days (p = .00) shorter, respectively, than those among self-admission cases. Our study highlights the importance of active surveillance for potential COVID-19 cases, as demonstrated by shortened time intervals from illness onset to both the first medical visit and isolation. These measures contributed to the effective control of the COVID-19 outbreak in Pudong, Shanghai.

RNA sequencing analysis reveals the competing endogenous RNAs interplay in resected hepatocellular carcinoma patients who received interferon-alpha therapy.

BACKGROUND: Interferon-alpha (IFN-α) is a general therapeutic regimen to be utilized in hepatocellular carcinoma (HCC). However, regulatory mechanisms of IFN-α on competing endogenous RNAs (ceRNAs) level in anti-HCC relapse are rarely understood. METHODS: HCC patients with and without IFN-α treatment were calculated to analyze the expression profile of mRNA, long non-coding RNA (lncRNA), microRNA (miRNA), and circular RNA (circRNA) by RNA sequence, and significant differential expression (DE) of these types of RNAs were selected for further analysis. A ceRNA regulatory network was constructed to explore the potential mechanisms of IFN-α intervention on anti-HCC relapse. Finally, the potential prognostic associated genes among these DE RNAs were identified. RESULTS: Totally, 556 mRNAs, 120 circRNAs, 87 lncRNAs, and 96 miRNAs were differentially expressed in patients who received IFN-α treatment. A ceRNA regulatory network including a circRNA-miRNA-mRNA network which composed of 4 up- and 10 down-regulated circRNAs, 8 up- and 5 down-regulated miRNAs, 28 up- and 9 down-regulated mRNAs, and a lncRNA-miRNA-mRNA network which composed of 10 up- and 3 down-regulated lncRNAs, 11 up- and 5 down-regulated miRNAs, 28 up- and 10 down-regulated mRNAs was constructed. Gene enrichment and pathway analysis revealed that the ceRNA network was associated with immune-related pathway and corresponding molecular function in patients who accepted IFN-α treatment. Next, we identified 3 most relevant to IFN-α treatment to HCC among these DE RNAs, namely FAM20A, IGFBP4 and MARCH3, as the prognostic associated genes for HCC. Furthermore, MARCH3 expression correlated with infiltrating levels of tumor infiltrating immune cells (TICCs) in HCC. MARCH3 expression also showed strong correlations with the gene markers of diverse immune cells in HCC. CONCLUSION: Our data discovered a novel ceRNA network in HCC patients receiving IFN-α therapy, which might lay the foundation for better understand the regulatory mechanism of IFN-α treatment.

Short intrinsically disordered polypeptide-oligonucleotide conjugates for programmed self-assembly of nanospheres with temperature-dependent size controllability.

A series of short intrinsically disordered polypeptide conjugated oligonucleotides (IDPOCs) were rationally developed and assembled into well-defined nanospheres. The nanospheres exhibited excellent reversible thermoresponsive regulation of their contraction and expansion. Furthermore, the nanospheres showed biocompatibility, drug encapsulation and effective cellular uptake.

Comprehensive analysis of N6 -methyladenosine-related long non-coding RNAs for prognosis prediction in liver hepatocellular carcinoma.

BACKGROUND: Liver hepatocellular carcinoma (LIHC) is a lethal cancer. This study aimed to identify the N6 -methyladenosine (m6 A)-targeted long non-coding RNA (lncRNA) related to LIHC prognosis and to develop an m6 A-targeted lncRNA model for prognosis prediction in LIHC. METHODS: The expression matrix of mRNA and lncRNA was obtained, and differentially expressed (DE) mRNAs and lncRNAs between tumor and normal samples were identified. Univariate Cox and pathway enrichment analyses were performed on the m6 A-targeted lncRNAs and the LIHC prognosis-related m6 A-targeted lncRNAs. Prognostic analysis, immune infiltration, and gene DE analyses were performed on LIHC subgroups, which were obtained from unsupervised clustering analysis. Additionally, a multi-factor Cox analysis was used to construct a prognostic risk model based on the lncRNAs from the LASSO Cox model. Univariate and multivariate Cox analyses were used to assess prognostic independence. RESULTS: A total of 5031 significant DEmRNAs and 292 significant DElncRNAs were screened, and 72 LIHC-specific m6 A-targeted binding lncRNAs were screened. Moreover, a total of 29 LIHC prognosis-related m6 A-targeted lncRNAs were obtained and enriched in cytoskeletal, spliceosome, and cell cycle pathways. An 11-m6 A-lncRNA prognostic model was constructed and verified; the top 10 lncRNAs included LINC00152, RP6-65G23.3, RP11-620J15.3, RP11-290F5.1, RP11-147L13.13, RP11-923I11.6, AC092171.4, KB-1460A1.5, LINC00339, and RP11-119D9.1. Additionally, the two LIHC subgroups, Cluster 1 and Cluster 2, showed significant differences in the immune microenvironment, m6 A enzyme genes, and prognosis of LIHC. CONCLUSION: The m6 A-lncRNA prognostic model accurately and effectively predicted the prognostic survival of LIHC. Immune cells, immune checkpoints (ICs), and m6 A enzyme genes could act as novel therapeutic targets for LIHC.

Synchronized Data Collection for Human Group Recognition.

It is commonplace for people to perform various kinds of activities in groups. The recognition of human groups is of importance in many applications including crowd evacuation, teamwork coordination, and advertising. Existing group recognition approaches require snapshots of human trajectories, which is often impossible in the reality due to different data collection start time and frequency, and the inherent time deviations of devices. This study proposes an approach to synchronize the data of people for group recognition. All people's trajectory data are aligned by using data interpolating. The optimal interpolating points are computed based on our proposed error function. Moreover, the time deviations among devices are estimated and eliminated by message passing. A real-life data set is used to validate the effectiveness of the proposed approach. The results show that 97.7% accuracy of group recognition can be achieved. The approach proposed to deal with time deviations was also proven to lead to better performance compared to that of the existing approaches.

Comprehensive molecular profiling of intrahepatic cholangiocarcinoma in the Chinese population and therapeutic experience.

BACKGROUND: The genomic alterations of intrahepatic cholangiocarcinoma (ICC) in the Chinese population have not been fully revealed. Molecular profiling may provide a reference for clinical management, especially targeted therapy. METHODS: A retrospective study was conducted in 122 ICC patients. All patients' samples underwent next-generation sequencing (NGS), which analyzed 417 genes. The genetic characteristics, clinical management and therapeutic responses were analyzed. RESULTS: The most commonly mutated genes were TP53 (34%), KRAS (25%) and ARID1A (17%). Targeted agents were used referring to molecular profiling, in combination with chemotherapy. Twenty-two patients with wild-type KRAS/NRAS/BRAF were treated with cetuximab. The disease control and response rates were 78% and 47%, respectively, which were higher than those achieved with chemotherapy alone (72% and 11%, P = 0.16). Fifty-four patients underwent anti-VEGF treatment with bevacizumab. The disease control and response rates were 85% and 60%, respectively. Better therapeutic efficiency (P = 0.001) and longer progression-free survival (PFS) were observed in the bevacizumab-treated group compared to chemotherapy alone group (15.4 and 6.7 months, respectively; P = 0.04). The PFS of ten patients who underwent hepatectomy after combined treatment with chemotherapy and bevacizumab was longer than that of 139 patients who underwent surgical treatment (28.9 vs 18.0 months, P = 0.03). Two patients (1.6%) had signatures of microsatellite instability (MSI-H), and both benefited from immunotherapy. CONCLUSIONS: This study provides an overview of genetic alterations in Chinese ICC patients and indicates the potential clinical implications for NGS-based personalized therapies.

Buckling of cylindrical shells subjected to a finite number of lateral loads: application to single-walled carbon nanotubes.

The continuous loading assumption is adopted in most present studies on the buckling of thin shells subjected to lateral loads, while the relationship between the finite number of loads and the lateral buckling remains unclear. In this work, we derive an analytic formula for the dependence of the critical buckling stress on the number of loads, which shows that the critical stress increases significantly with the increase of the load number and reaches a saturation value in the limit of large load number. Furthermore, the analytic formula reveals the dependence of the critical stress on the deviation of the radius in an imperfect shell. To verify the validity of the analytic formula, we perform molecular dynamics simulations to investigate the buckling of both perfect and imperfect single-walled carbon nanotubes under a finite number of lateral loads, where the analytic formula agrees with the simulation results. These results shall be valuable for understanding mechanical stability of elastic thin shells or nanoscale tubal structures subjected to discrete lateral loads.

The Long Noncoding RNA ANRIL Promotes Cell Apoptosis in Lipopolysaccharide-Induced Acute Kidney Injury Mediated by the TLR4/Nuclear Factor-Kappa B Pathway.

BACKGROUND/AIMS: The purpose of this study is to analyze the expression and biological function of lncRNA ANRIL, microRNA-199a, TLR4, and nuclear factor-kappa B (NF-κB) in acute renal injury (AKI) induced by lipopolysaccharide (LPS). METHODS: The levels of ANRIL and microRNA-199a in mouse cells and kidneys were detected by quantitative-polymerase chain reaction. Western blot analysis was used for the NF-κB pathway protein. MTT assay was used for cell viability. Enzyme-linked immunosorbent assay was used for the secretion of inflammatory factors in mouse kidney tissue. Apoptosis was measured by flow cytometry and Western blotting. The potential binding region between ANRIL and miR-199a was verified by luciferase reporter assay. RESULTS: The upregulation of ANRIL can reduce the expression of microRNA-199a and increases the number of apoptotic cells. The expression levels of ANRIL in LPS-induced AKI mice and LPS-treated HK2 cells were upregulated compared with the control group. Overexpression of ANRIL increased apoptosis and promoted TLR4 (Toll-like receptor 4), NF-κB phosphorylation, and downstream transcription factor production. CONCLUSION: ANRIL/NF-κB pathway in LPS-induced apoptosis provided theoretical guidance for ANRIL in the treatment of AKI.

Edge4TSC: Binary Distribution Tree-Enabled Time Series Classification in Edge Environment.

In the past decade, time series data have been generated from various fields at a rapid speed, which offers a huge opportunity for mining valuable knowledge. As a typical task of time series mining, Time Series Classification (TSC) has attracted lots of attention from both researchers and domain experts due to its broad applications ranging from human activity recognition to smart city governance. Specifically, there is an increasing requirement for performing classification tasks on diverse types of time series data in a timely manner without costly hand-crafting feature engineering. Therefore, in this paper, we propose a framework named Edge4TSC that allows time series to be processed in the edge environment, so that the classification results can be instantly returned to the end-users. Meanwhile, to get rid of the costly hand-crafting feature engineering process, deep learning techniques are applied for automatic feature extraction, which shows competitive or even superior performance compared to state-of-the-art TSC solutions. However, because time series presents complex patterns, even deep learning models are not capable of achieving satisfactory classification accuracy, which motivated us to explore new time series representation methods to help classifiers further improve the classification accuracy. In the proposed framework Edge4TSC, by building the binary distribution tree, a new time series representation method was designed for addressing the classification accuracy concern in TSC tasks. By conducting comprehensive experiments on six challenging time series datasets in the edge environment, the potential of the proposed framework for its generalization ability and classification accuracy improvement is firmly validated with a number of helpful insights.

Diameter-dependent polygonal cross section for holey phenine nanotubes.

The cross-sectional shape of the nanotube is a key factor governing fundamental mechanical properties of the nanotube and the nanotube forest. In contrast to most circular nanotubes, in the present work, we demonstrate that the holey phenine nanotubes have polygonal cross sections with diameter-dependent number of sides. The non-circular cross section is attributed to the high twistability of the continuous C-C chains in the phenine nanotube. Consequently, the phenine nanotube forest has a square lattice structure rather than the regular hexagonal lattice of the carbon nanotube forest, resulting in a smooth buckling process under biaxial compression. The buckling pattern of the phenine nanotube forest is highly ordered with the orientation determined by the initial dislocation that frequently appears in the phenine nanotube forest.

The Path to Deliver the Most Realistic Follower Load for a Lumbar Spine in Standing Posture: A Finite Element Study.

A spine is proven to be subjected to a follower load which is a compressive load of physiologic magnitude acting on the whole spine. The path of the follower load approximates the tangent to the curve of the spine in in vivo neutral standing posture. However, the specific path location of the follower load is still unclear. The aim of this study is to find out the most realistic location of the follower load path (FLP) for a lumbar spine in standing. A three-dimensional (3D) nonlinear finite element model (FEM) of lumbosacral vertebrae (L1-S1) with consideration of the calibrated material properties was established and validated by comparing with the experimental data. We show that the shape of the lumbosacral spine is strongly affected by the location of FLP. An evident nonlinear relationship between the FLP location and the kinematic response of the L1-S1 lumbosacral spine exists. The FLP at about 4 and 3 mm posterior to the curve connecting the center of the vertebral bodies delivers the most realistic location in standing for healthy people and patients having low back pains (LPBs), respectively. Moreover, the "sweeping" method introduced in this study can be applicable to all individualized FEM to determine the location of FLP.