Analysis of spatial distribution and drivers of gaseous energy combustion pollution in China based on SDM.

Air pollution is an important part of ecological environment problems. Gaseous energy combustion pollution is a key part of air pollution. Analysis of its spatial distribution and drivers is important to effectively manage air quality and promote regional green development. This paper uses panel data of 30 provinces in China from 2006 to 2019 to analyze the spatial distribution and drivers of gaseous energy combustion pollution in each province of China through a combination of quantitative and qualitative analysis based on the spatial Durbin model, and further decompose the spatial effects of each influencing factor. The empirical results show, firstly, that inter-provincial gaseous energy combustion pollution in China shows significant spatial differences and cluster characteristics. Secondly, most areas are located in high-high aggregation area and low-low aggregation area. Finally, population, energy consumption and other independent variables have different impacts on gaseous energy combustion pollution in different regions. The changes of these variables will affect the adjacent areas through spatial transmission while affecting a region. According to the empirical results, this study proposes policy recommendations to balance the pollution degree of gaseous energy combustion in various regions and effectively reduce the emissions of various pollution sources. The research results are helpful to understand the spatial distribution of gaseous energy combustion pollution in various regions of China, provide reference for the future development of various regions, and have important practical significance for the reduction and balance of pollution levels.

Estrogen receptor signaling is reprogrammed during breast tumorigenesis.

Limited knowledge of the changes in estrogen receptor (ER) signaling during the transformation of the normal mammary gland to breast cancer hinders the development of effective prevention and treatment strategies. Differences in estrogen signaling between normal human primary breast epithelial cells and primary breast tumors obtained immediately following surgical excision were explored. Transcriptional profiling of normal ER+ mature luminal mammary epithelial cells and ER+ breast tumors revealed significant difference in the response to estrogen stimulation. Consistent with these differences in gene expression, the normal and tumor ER cistromes were distinct and sufficient to segregate normal breast tissues from breast tumors. The selective enrichment of the DNA binding motif GRHL2 in the breast cancer-specific ER cistrome suggests that it may play a role in the differential function of ER in breast cancer. Depletion of GRHL2 resulted in altered ER binding and differential transcriptional responses to estrogen stimulation. Furthermore, GRHL2 was demonstrated to be essential for estrogen-stimulated proliferation of ER+ breast cancer cells. DLC1 was also identified as an estrogen-induced tumor suppressor in the normal mammary gland with decreased expression in breast cancer. In clinical cohorts, loss of DLC1 and gain of GRHL2 expression are associated with ER+ breast cancer and are independently predictive for worse survival. This study suggests that normal ER signaling is lost and tumor-specific ER signaling is gained during breast tumorigenesis. Unraveling these changes in ER signaling during breast cancer progression should aid the development of more effective prevention strategies and targeted therapeutics.

Changing character of rainfall in eastern China, 1951-2007.

The topography and continental configuration of East Asia favor the year-round existence of storm tracks that extend thousands of kilometers from China into the northwestern Pacific Ocean, producing zonally elongated patterns of rainfall that we call "frontal rain events." In spring and early summer (known as "Meiyu Season"), frontal rainfall intensifies and shifts northward during a series of stages collectively known as the East Asian summer monsoon. Using a technique called the Frontal Rain Event Detection Algorithm, we create a daily catalog of all frontal rain events in east China during 1951-2007, quantify their attributes, and classify all rainfall on each day as either frontal, resulting from large-scale convergence, or nonfrontal, produced by local buoyancy, topography, or typhoons. Our climatology shows that the East Asian summer monsoon consists of a series of coupled changes in frontal rain event frequency, latitude, and daily accumulation. Furthermore, decadal changes in the amount and distribution of rainfall in east China are overwhelmingly due to changes in frontal rainfall. We attribute the "South Flood-North Drought" pattern observed beginning in the 1980s to changes in the frequency of frontal rain events, while the years 1994-2007 witnessed an uptick in event daily accumulation relative to the rest of the study years. This particular signature may reflect the relative impacts of global warming, aerosol loading, and natural variability on regional rainfall, potentially via shifting the East Asian jet stream.

Craniocervical posture in patients with skeletal malocclusion and its correlation with craniofacial morphology during different growth periods.

The association between craniocervical posture and craniofacial structures in the various sagittal skeletal malocclusion during different growth stages has been the focus of intense interest in fields of orthodontics, but it has not been conclusively demonstrated. Thus, this study aimed to investigate the association between craniofacial morphology and craniocervical posture in patients with sagittal skeletal malocclusion during different growth periods. A total of 150 from a large pool of cephalograms qualified for the inclusion and exclusion were evaluated and classified into three groups according to the Cervical Vertebral Maturation (CVM) by examining the morphological modifications of the second through fourth cervical vertebrae, each group consisted of 50 cephalograms. In each growth period, for the comparison of head and cervical posture differences among various skeletal classes, the radiographs were further subdivided into skeletal Class I (0° < ANB < 5°, n = 16), skeletal Class II (ANB ≥ 5°, n = 18), and skeletal Class III (0° ≤ ANB, n = 16) on the basis of their ANB angle. There was no significant difference in gender (P > 0.05). Some variables were found to be significant during pubertal growth and later in patients with sagittal skeletal malocclusion (P < 0.05). Most indicators describing craniocervical posture were largest in skeletal Class II and smallest in skeletal Class III during the peak growth periods and later. Cervical inclination variables were greater in skeletal Class III than in skeletal Class II. Variables of craniofacial morphology and craniocervical posture are more correlated during the pubertal growth period and later in patients with sagittal skeletal malocclusion. A tendency is an indication of the close interrelationship that a more extended head was in skeletal Class II while a flexed head was in skeletal Class III. Nevertheless, with the considerations of some limitations involved in this study, further longitudinal studies with large samples are required to elucidate the relationship clearly.

CUX1 regulates human hematopoietic stem cell chromatin accessibility via the BAF complex.

CUX1 is a homeodomain-containing transcription factor that is essential for the development and differentiation of multiple tissues. CUX1 is recurrently mutated or deleted in cancer, particularly in myeloid malignancies. However, the mechanism by which CUX1 regulates gene expression and differentiation remains poorly understood, creating a barrier to understanding the tumor-suppressive functions of CUX1. Here, we demonstrate that CUX1 directs the BAF chromatin remodeling complex to DNA to increase chromatin accessibility in hematopoietic cells. CUX1 preferentially regulates lineage-specific enhancers, and CUX1 target genes are predictive of cell fate in vivo. These data indicate that CUX1 regulates hematopoietic lineage commitment and homeostasis via pioneer factor activity, and CUX1 deficiency disrupts these processes in stem and progenitor cells, facilitating transformation.

Selective CDK7 Inhibition Suppresses Cell Cycle Progression and MYC Signaling While Enhancing Apoptosis in Therapy-resistant Estrogen Receptor-positive Breast Cancer.

PURPOSE: Resistance to endocrine therapy (ET) and CDK4/6 inhibitors (CDK4/6i) is a clinical challenge in estrogen receptor (ER)-positive (ER+) breast cancer. Cyclin-dependent kinase 7 (CDK7) is a candidate target in endocrine-resistant ER+ breast cancer models and selective CDK7 inhibitors (CDK7i) are in clinical development for the treatment of ER+ breast cancer. Nonetheless, the precise mechanisms responsible for the activity of CDK7i in ER+ breast cancer remain elusive. Herein, we sought to unravel these mechanisms. EXPERIMENTAL DESIGN: We conducted multi-omic analyses in ER+ breast cancer models in vitro and in vivo, including models with different genetic backgrounds. We also performed genome-wide CRISPR/Cas9 knockout screens to identify potential therapeutic vulnerabilities in CDK4/6i-resistant models. RESULTS: We found that the on-target antitumor effects of CDK7 inhibition in ER+ breast cancer are in part p53 dependent, and involve cell cycle inhibition and suppression of c-Myc. Moreover, CDK7 inhibition exhibited cytotoxic effects, distinctive from the cytostatic nature of ET and CDK4/6i. CDK7 inhibition resulted in suppression of ER phosphorylation at S118; however, long-term CDK7 inhibition resulted in increased ER signaling, supporting the combination of ET with a CDK7i. Finally, genome-wide CRISPR/Cas9 knockout screens identified CDK7 and MYC signaling as putative vulnerabilities in CDK4/6i resistance, and CDK7 inhibition effectively inhibited CDK4/6i-resistant models. CONCLUSIONS: Taken together, these findings support the clinical investigation of selective CDK7 inhibition combined with ET to overcome treatment resistance in ER+ breast cancer. In addition, our study highlights the potential of increased c-Myc activity and intact p53 as predictors of sensitivity to CDK7i-based treatments.

Black Phosphorus as a Targeting PPAR-γ Agonist to Reverse Chemoresistance in Patient-derived Organoids, Mice, and Pancreatic Tumor Cells.

Black phosphorus (BP) exhibits significant potential for clinical applications. However, further research is necessary to uncover the unknown biological functions of BP and broaden its applications across various fields. This study investigates the potential of BP as a targeting PPAR-γ agonist to overcome chemoresistance in the treatment of pancreatic adenocarcinoma (PAAD) using 2D and 3D cell lines, patient-derived organoids (PDOs), and mouse models. RNA-sequencing analysis shows that BP treatment enriches differentially expressed genes in the PPAR pathway, and molecular modeling predicts the potential docking site between BP and PPAR-γ. Transcriptional activity assays are further to verify the activation of PPAR-γ. BP-activated PPAR-γ inhibits cancer stem cell (CSC) properties and expression of biomarkers such as CD44 and c-Myc, which are involved in chemoresistance. Notably, CD44 overexpression in tumor cells renders them susceptible to BP while insensitive to gemcitabine. This indicates that BP preferentially targets stem-like cells, which exhibit heightened resistance to chemotherapeutic drugs. A combination treatment strategy involving BP and gemcitabine is developed, demonstrating enhanced treatment efficacy of PAAD in both in vitro and in vivo models. Thus, BP serves as a PPAR-γ agonist capable of reversing chemoresistance, establishing it as a potent anti-tumor approach for the treatment of PAAD.

The mental health impact of the COVID-19 pandemic on post-secondary students: A longitudinal study.

This prospective longitudinal study measured sex-specific changes in depression, anxiety, and stress scores using, validated Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and the Perceived Stress Scale (PSS) in a cohort of 1445 post-secondary students (500 males, 945 females) assessed at three time points from December 2020 to January 2022. Participants were ascertained from a population of 15,585 students with in-person activities on campus at baseline and recruited from December 2020 to January 2021. We also assessed how sociodemographic characteristics influenced students' mental health outcomes. Inverse probability weighting was used to account for missing data and attrition. Linear mixed effects models were used to analyze the relationship between the mental health scores in each questionnaire, demographic and academic data, and public health stringency measured by the local stringency index. No change was observed in questionnaire scores over time for males and females, but the stringency index was significantly associated with increased stress. Being in a non-health-related-field or being white affected males and females differently for stress and anxiety, but not depression. Demographics tended to be more influential on females' mental health than males. In conclusion, mental health resource allocation in time of emerging pandemic could benefit from targeted interventions.

Macrophage-organoid co-culture model for identifying treatment strategies against macrophage-related gemcitabine resistance.

BACKGROUND: Gemcitabine resistance (GR) is a significant clinical challenge in pancreatic adenocarcinoma (PAAD) treatment. Macrophages in the tumor immune-microenvironment are closely related to GR. Uncovering the macrophage-induced GR mechanism could help devise a novel strategy to improve gemcitabine treatment outcomes in PAAD. Therefore, preclinical models accurately replicating patient tumor properties are essential for cancer research and drug development. Patient-derived organoids (PDOs) represent a promising in vitro model for investigating tumor targets, accelerating drug development, and enabling personalized treatment strategies to improve patient outcomes. METHODS: To investigate the effects of macrophage stimulation on GR, co-cultures were set up using PDOs from three PAAD patients with macrophages. To identify signaling factors between macrophages and pancreatic cancer cells (PCCs), a 97-target cytokine array and the TCGA-GTEx database were utilized. The analysis revealed CCL5 and AREG as potential candidates. The role of CCL5 in inducing GR was further investigated using clinical data and tumor sections obtained from 48 PAAD patients over three years, inhibitors, and short hairpin RNA (shRNA). Furthermore, single-cell sequencing data from the GEO database were analyzed to explore the crosstalk between PCCs and macrophages. To overcome GR, inhibitors targeting the macrophage-CCL5-Sp1-AREG feedback loop were evaluated in cell lines, PDOs, and orthotopic mouse models of pancreatic carcinoma. RESULTS: The macrophage-CCL5-Sp1-AREG feedback loop between macrophages and PCCs is responsible for GR. Macrophage-derived CCL5 activates the CCR5/AKT/Sp1/CD44 axis to confer stemness and chemoresistance to PCCs. PCC-derived AREG promotes CCL5 secretion in macrophages through the Hippo-YAP pathway. By targeting the feedback loop, mithramycin improves the outcome of gemcitabine treatment in PAAD. The results from the PDO model were corroborated with cell lines, mouse models, and clinical data. CONCLUSIONS: Our study highlights that the PDO model is a superior choice for preclinical research and precision medicine. The macrophage-CCL5-Sp1-AREG feedback loop confers stemness to PCCs to facilitate gemcitabine resistance by activating the CCR5/AKT/SP1/CD44 pathway. The combination of gemcitabine and mithramycin shows potential as a therapeutic strategy for treating PAAD in cell lines, PDOs, and mouse models.

Mathematical Modeling Identifies Optimum Palbociclib-fulvestrant Dose Administration Schedules for the Treatment of Patients with Estrogen Receptor-positive Breast Cancer.

Cyclin-dependent kinases 4/6 (CDK4/6) inhibitors such as palbociclib are approved for the treatment of metastatic estrogen receptor-positive (ER+) breast cancer in combination with endocrine therapies and significantly improve outcomes in patients with this disease. However, given the large number of possible pairwise drug combinations and administration schedules, it remains unclear which clinical strategy would lead to best survival. Here, we developed a computational, cell cycle-explicit model to characterize the pharmacodynamic response to palbociclib-fulvestrant combination therapy. This pharmacodynamic model was parameterized, in a Bayesian statistical inference approach, using in vitro data from cells with wild-type estrogen receptor (WT-ER) and cells expressing the activating missense ER mutation, Y537S, which confers resistance to fulvestrant. We then incorporated pharmacokinetic models derived from clinical data into our computational modeling platform. To systematically compare dose administration schedules, we performed in silico clinical trials based on integrating our pharmacodynamic and pharmacokinetic models as well as considering clinical toxicity constraints. We found that continuous dosing of palbociclib is more effective for lowering overall tumor burden than the standard, pulsed-dose palbociclib treatment. Importantly, our mathematical modeling and statistical analysis platform provides a rational method for comparing treatment strategies in search of optimal combination dosing strategies of other cell-cycle inhibitors in ER+ breast cancer. SIGNIFICANCE: We created a computational modeling platform to predict the effects of fulvestrant/palbocilib treatment on WT-ER and Y537S-mutant breast cancer cells, and found that continuous treatment schedules are more effective than the standard, pulsed-dose palbociclib treatment schedule.

Does head and cervical posture correlate to malocclusion? A systematic review and meta-analysis.

BACKGROUND: The association of head and cervical posture with malocclusion has been studied for many years. Despite extensively encouraging researches, no conclusive evidence has been reached for clinical application. OBJECTIVE: To identify the question "Does head and cervical posture correlate to malocclusion?", a systematic review and meta-analysis based on the available studies were carried out (PROSPERO registration number: CRD42022319742). METHODS: A search of PubMed, Embase, Cochrane Library, and the grey literature was performed without language restrictions. The study screening, data extraction, risk-of-bias evaluation and methodological quality assessment were performed by two independent investigators. When a disagreement arose, a third author was consulted. RESULTS: 6 original cross-sectional studies involving 505 participants were included, which were of moderate methodological quality. NL/VER in Class Ⅱ group and NL/CVT in Class Ⅲ group showed significant differences compared to Class Ⅰ group, but no significant differences were observed in most of the variables like NSL/VER, OPT/CVT, OPT/HOR, CVT/HOR, NSL/OPT, NSL/CVT, NL/OPT in Class Ⅱ and Ⅲ groups. CONCLUSIONS: The results suggested that the current research evidence is not sound enough to prove the association of head and cervical posture with sagittal malocclusion. Better controlled design and a larger sample size are required for clarifying this question in future study.

A Nomogram to Accurately Identify Pancreatic Neuroendocrine Tumors Metastasizing to Distant Organs: A Study Based on Two National Population-Based Cohorts From the United States and China.

Background: Distant organ metastasis is the leading cause of death in pancreatic neuroendocrine tumor (pNET) patients. In the present study, we aimed to develop and validate a nomogram that could accurately identify pNET metastasizing to distant organs. Methods: The cases extracted from the Surveillance, Epidemiology, and End Results (SEER) program were assigned to the training cohort and validation cohort. The cases from the Chinese Gastrointestinal Neuroendocrine Tumors program were assigned to the external validation cohort. The strategy was developed with the support of a nomogram, and the predictive value of this strategy was evaluated by the receiver operating characteristic (ROC) curve analysis. Results: In total, 2024 American cases were involved in the present study. Besides, 1450 and 574 patients were allocated into training and internal validation cohorts, respectively. In addition, 122 Chinese patients were assigned to the external validation cohort. The results of the univariate logistic regression analysis suggested that tumor grade, tumor size, and the number of metastatic lymph nodes were the risk of metastasis to distant organs, and these 3 clinicopathological characteristics were used to develop the nomogram. We observed that the accuracy of the nomogram for predicting metastasis to distant organs was 0.797, 0.819, and 0.837 in the training cohort, internal validation cohort, and external validation cohort, respectively. Conclusions: A predictive nomogram was developed and validated, and it showed an acceptable performance in predicting metastasis to distant organs. The results will enable clinicians to identify pNETs, metastasizing to distant organs, and develop an effective individualized therapeutic strategy for these patients.

A Distinct Chromatin State Drives Therapeutic Resistance in Invasive Lobular Breast Cancer.

Most invasive lobular breast cancers (ILC) are of the luminal A subtype and are strongly hormone receptor-positive. Yet, ILC is relatively resistant to tamoxifen and associated with inferior long-term outcomes compared with invasive ductal cancers (IDC). In this study, we sought to gain mechanistic insights into these clinical findings that are not explained by the genetic landscape of ILC and to identify strategies to improve patient outcomes. A comprehensive analysis of the epigenome of ILC in preclinical models and clinical samples showed that, compared with IDC, ILC harbored a distinct chromatin state linked to gained recruitment of FOXA1, a lineage-defining pioneer transcription factor. This resulted in an ILC-unique FOXA1-estrogen receptor (ER) axis that promoted the transcription of genes associated with tumor progression and poor outcomes. The ILC-unique FOXA1-ER axis led to retained ER chromatin binding after tamoxifen treatment, which facilitated tamoxifen resistance while remaining strongly dependent on ER signaling. Mechanistically, gained FOXA1 binding was associated with the autoinduction of FOXA1 in ILC through an ILC-unique FOXA1 binding site. Targeted silencing of this regulatory site resulted in the disruption of the feed-forward loop and growth inhibition in ILC. In summary, ILC is characterized by a unique chromatin state and FOXA1-ER axis that is associated with tumor progression, offering a novel mechanism of tamoxifen resistance. These results underscore the importance of conducting clinical trials dedicated to patients with ILC in order to optimize treatments in this breast cancer subtype. SIGNIFICANCE: A unique FOXA1-ER axis in invasive lobular breast cancer promotes disease progression and tamoxifen resistance, highlighting a potential therapeutic avenue for clinical investigations dedicated to this disease. See related commentary by Blawski and Toska, p. 3668.

COVID-19 antibody therapeutics tracker: a global online database of antibody therapeutics for the prevention and treatment of COVID-19.

Facing the COVID-19 global healthcare crisis, scientists worldwide are collaborating to develop prophylactic and therapeutic interventions against the disease. Antibody therapeutics hold enormous promise for the treatment of COVID-19. In March 2020, the Chinese Antibody Society, in collaboration with The Antibody Society, initiated the "COVID-19 Antibody Therapeutics Tracker" ("Tracker") (https://chineseantibody.org/covid-19-track/) program to track the antibody-based COVID-19 interventions in preclinical and clinical development globally. The data are collected from the public domain and verified by volunteers on an ongoing basis. Here, we present exploratory data analyses and visualization to demonstrate the latest trends of COVID-19 antibody development, based on data for over 150 research and development programs and molecules included in the "Tracker" as of 8 August 2020. We categorized the data mainly by their targets, formats, development status, developers and country of origin. Although details are limited in some cases, all of the anti-SARS-CoV-2 antibody candidates appear to target the viral spike protein (S protein), and most are full-length monoclonal antibodies. Most of the current COVID-19 antibody therapeutic candidates in clinical trials are repurposed drugs aimed at targets other than virus-specific proteins, while most of these virus-specific therapeutic antibodies are in discovery or preclinical studies. As of 8 August 2020, eight antibody candidates targeting the SARS-CoV-2 S protein have entered clinical studies, including LY-CoV555, REGN-COV2, JS016, TY027, CT-P59, BRII-196, BRII-198 and SCTA01. Ongoing clinical trials of SARS-CoV-2 neutralizing antibodies will help define the utility of these antibodies as a new class of therapeutics for treating COVID-19 and future coronavirus infections.

[Monitoring and Analysis of the Spatio-temporal Change Characteristics of the PM2.5 Concentration Over Beijing-Tianjin-Hebei and Its Surrounding Regions Based on Remote Sensing].

To analyze the spatial and temporal variation characteristics of PM2.5 in Beijing-Tianjin-Hebei and its surrounding regions, a 1 km resolution AOT product was retrieved from MODIS data and the remote sensing inversion of the PM2.5 concentration in Beijing-Tianjin-Hebei and its surrounding regions was realized using the geographically weighted regression model. On this basis, the synthesis results of multi-timescale PM2.5 concentrations were verified and analyzed. Finally, the spatial and temporal variation characteristics of PM2.5 in Beijing-Tianjin-Hebei and its surrounding regions between 2016 and 2017 were compared and analyzed using different time scales. The results show that the verification of the PM2.5 concentration products of the average daily, monthly, and annual averages are in general good. The larger the time scale is, the better is the PM2.5 effect of the remote sensing estimation. The relative accuracy of the annual average PM2.5 products is higher than 80%. However, the precision of the PM2.5 remote sensing results for 2016 and 2017 is relatively close (at the same time scales). The PM2.5 distribution in Beijing-Tianjin-Hebei and its surrounding regions shows a seasonal variation (winter > autum ≈ spring > summer). The spatial distribution is high in the southern but low in the northern part. Compared with 2016, the average PM2.5 concentration decreased by~9.2% in 2017. The area with high values was significantly reduced. High PM2.5 concentrations occurred in November and December and low concentrations were observed in August. The PM2.5 concentration change between 2017 and 2016 is closely related to the comprehensive control crucial action and specific inspection activities of air pollution in 2017, which indirectly account for the effect of the reduction of the atmospheric pollution.

Allele-Specific Chromatin Recruitment and Therapeutic Vulnerabilities of ESR1 Activating Mutations.

Estrogen receptor α (ER) ligand-binding domain (LBD) mutations are found in a substantial number of endocrine treatment-resistant metastatic ER-positive (ER+) breast cancers. We investigated the chromatin recruitment, transcriptional network, and genetic vulnerabilities in breast cancer models harboring the clinically relevant ER mutations. These mutants exhibit both ligand-independent functions that mimic estradiol-bound wild-type ER as well as allele-specific neomorphic properties that promote a pro-metastatic phenotype. Analysis of the genome-wide ER binding sites identified mutant ER unique recruitment mediating the allele-specific transcriptional program. Genetic screens identified genes that are essential for the ligand-independent growth driven by the mutants. These studies provide insights into the mechanism of endocrine therapy resistance engendered by ER mutations and potential therapeutic targets.

Application of a two-dimensional model for predicting the pressure-flow and compression properties during column packing scale-up.

A two-dimensional model was formulated to describe the pressure-flow behavior of compressible stationary phases for protein chromatography at different temperatures and column scales. The model was based on the assumption of elastic deformation of the solid phase and steady-state Darcy flow. Using a single fitted value for the empirical modulus parameters, the model was applied to describe the pressure-flow behavior of several adsorbents packed using both fluid flow and mechanical compression. Simulations were in agreement with experimental data and accurately predicted the pressure-flow and compression behavior of three adsorbents over a range of column scales and operating temperatures. Use of the described theoretical model potentially improves the accuracy of the column scale-up process, allowing the use of limited laboratory scale data to predict column performance in large scale applications.

Robust speaker's location detection in a vehicle environment using GMM models.

Abstract-Human-computer interaction (HCI) using speech communication is becoming increasingly important, especially in driving where safety is the primary concern. Knowing the speaker's location (i.e., speaker localization) not only improves the enhancement results of a corrupted signal, but also provides assistance to speaker identification. Since conventional speech localization algorithms suffer from the uncertainties of environmental complexity and noise, as well as from the microphone mismatch problem, they are frequently not robust in practice. Without a high reliability, the acceptance of speech-based HCI would never be realized. This work presents a novel speaker's location detection method and demonstrates high accuracy within a vehicle cabinet using a single linear microphone array. The proposed approach utilize Gaussian mixture models (GMM) to model the distributions of the phase differences among the microphones caused by the complex characteristic of room acoustic and microphone mismatch. The model can be applied both in near-field and far-field situations in a noisy environment. The individual Gaussian component of a GMM represents some general location-dependent but content and speaker-independent phase difference distributions. Moreover, the scheme performs well not only in nonline-of-sight cases, but also when the speakers are aligned toward the microphone array but at difference distances from it. This strong performance can be achieved by exploiting the fact that the phase difference distributions at different locations are distinguishable in the environment of a car. The experimental results also show that the proposed method outperforms the conventional multiple signal classification method (MUSIC) technique at various SNRs.