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Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can lead to timely and effective medical treatment. The current conventional clinical methods have several limitations. Therefore, there is a need to develop faster and more reliable clinical detection, treatment, and monitoring methods to enhance their clinical applications. Raman spectroscopy is noninvasive and provides highly specific information about the molecular structure and biochemical composition of analytes in a rapid and accurate manner. It has a wide range of applications in biomedicine, materials, and clinical settings. This review primarily focuses on the application of Raman spectroscopy in clinical medicine. The advantages and limitations of Raman spectroscopy over traditional clinical methods are discussed. In addition, the advantages of combining Raman spectroscopy with machine learning, nanoparticles, and probes are demonstrated, thereby extending its applicability to different clinical phases. Examples of the clinical applications of Raman spectroscopy over the last 3 years are also integrated. Finally, various prospective approaches based on Raman spectroscopy in clinical studies are surveyed, and current challenges are discussed. [ABSTRACT FROM AUTHOR]

We report a case of drug‐induced lung injury treated with prior atezolizumab and subsequent sotorasib. The patient was a 62‐year‐old woman with lung adenocarcinoma harbouring a KRAS G12C mutation that was resistant to chemotherapy, including immune checkpoint inhibitors. Cough and dyspnea appeared on day 80 after sotorasib was administered as second‐line therapy, and chest computed tomography revealed ground glass opacities in all lung lobes. Bronchoalveolar lavage fluid showed an increased total cell count with lymphocyte predominance. The patient was considered to have lung injury caused by prior atezolizumab or sotorasib administration. Withdrawal of sotorasib did not improve symptoms and shadows in both lungs. We administered moderate‐dose prednisolone and the lung disorder quickly resolved. Prednisolone tapering was completed in 2 months, followed by several months without relapse. Definitive identification of the responsible drug for the drug‐induced lung injury proved challenging in the setting of exposure to multiple potential inciting agents. There is a need for high levels of clinical suspicion for timely evaluation and management.We report a case of drug‐induced lung injury treated with prior atezolizumab and subsequent sotorasib. Definitive identification of the responsible drug for the drug‐induced lung injury proved challenging in the setting of exposure to multiple potential inciting agents. There is a need for high levels of clinical suspicion for timely evaluation and management. [ABSTRACT FROM AUTHOR]

Nonobstructive azoospermia (NOA) is one of the most important causes of male infertility, accounting for 10–15% of infertile men worldwide. Among these, more than 70% of cases are idiopathic NOA (iNOA), whose pathogenesis and molecular basis remain unknown. This work profiles 3696 human testicular single‐cell transcriptomes from 17 iNOA patients, which are classified into four classes with different arrest periods and variable cell proportions based on the gene expression patterns and pathological features. Genes related to the cell cycle, energy production, and gamete generation show obvious abnormalities in iNOA germ cells. This work identifies several candidate causal genes for iNOA, including CD164, LELP1, and TEX38, which are significantly downregulated in iNOA germ cells. Notably, CD164 knockdown promotes apoptosis in spermatogonia. Cellular communications between spermatogonial stem cells and Sertoli cells are disturbed in iNOA patients. Moreover, BOD1L2, C1orf194, and KRTCAP2 are found to indicate testicular spermatogenic capacity in a variety of testicular diseases, such as Y‐chromosome microdeletions and Klinefelter syndrome. In general, this study analyzes the pathogenesis of iNOA from the perspective of germ cell development, transcription factor (TF) regulatory networks, as well as germ cell and somatic cell interactions, which provides new ideas for clinical diagnosis. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is one of the most common malignancies that is usually detected late in the clinic. The currently available diagnostic tools for CRC are either invasive or insensitive to early lesions due to the dearth of reliable biomarkers. In this study, we discovered that the extracellular vesicles (EVs) in the faeces of CRC patients can act as a potent biomarker for the non‐invasive diagnosis and prognosis of CRC. This finding is based on the identification of two transmembrane proteins—CD147 and A33—on faeces‐derived EVs (fEVs) that are intrinsically associated with CRC. The detection results show that the levels of CD147 and A33 on fEVs were upregulated in the CRC patients (n = 48), dramatically distinguishing them from the healthy donors (n = 16). The CD147/A33‐enriched EVs offer a clinical sensitivity of 89%, much higher than that (40%) of carcinoembryonic antigen (CEA), a clinically‐established serum biomarker for CRC diagnosis. In addition, the analysis of longitudinal faeces samples (n = 29) demonstrated that the CD147/A33‐enriched fEVs can be utilized to track the prognosis of CRC. Due to the high compliance of faeces‐based detection, the CD147/A33‐enriched fEVs could serve as new‐generation CRC biomarkers for large‐scale, non‐invasive CRC screening as well as real‐time monitoring of patient outcomes during clinical interventions. [ABSTRACT FROM AUTHOR]

Background: Female pattern hair loss (FPHL) is a non‐scarring hair disease characterized by progressive hair diminishment and decrease of its density. Although typical cases of FPHL are usually straightforward to diagnose, its initial forms can be unrecognized and often need the use of other diagnostic methods. Objective: To describe the accuracy of a diagnosis of FPHL based on clinical grounds and videodermoscopy compared with scalp biopsy. Methods: An observational diagnostic test study was performed. Scalp biopsies were read by the same dermatopathologist and processed horizontally to allow follicle's number and size evaluation. Digital videodermoscopy was also performed. Results: A total of 202 patients were enrolled, but only 35 women were assessed with digital videodermoscopy. When clinical diagnosis was compared to scalp biopsy, a sensitivity, specificity, positive predictive value (PPV), and a negative predictive value (NPV), of 77% %, 72.4%, 82.2%; and 65.5%, were respectively obtained. Videodermoscopy showed a sensitivity, specificity, PPV and NPV of 88.9%, 100%, 100%, and 72.7%, respectively. Conclusions: This study provided valuable information on the accuracy of clinical examination of FPHL, showed the usefulness of videodermoscopy as a method that in the future may replace scalp biopsy for its diagnosis, or also could aid patient´s follow‐up. [ABSTRACT FROM AUTHOR]

Purpose: To provides the clinical and genetic characteristics of a series of Chinese patients with X‐linked juvenile retinoschisis (XLRS) through multimodal imaging and next‐generation sequencing. Methods: Thirty patients (60 eyes) from 29 unrelated families of Chinese origin with XLRS were screened using multigene panel testing, and underwent a complete clinical evaluation. All variants identified in this study and reported in the Human Gene Mutation Database were analysed. Results: Twenty‐five distinct variants in the retinoschisin gene were identified, of which eight were novel, and one was de novo. Missense mutations were the most prevalent type, and mutation hot spot was localized in the discoidin domain. The mean Snellen best‐corrected visual acuity was 0.28 ± 0.17. Of all eyes presenting with schisis, 92.86% had lamellar schisis and 62.5% had peripheral schisis. Schisis changes mostly involved inner and outer nuclear layers. X‐linked juvenile retinoschisis (XLRS) patients had a high incidence of complications, and peripheral schisis was a risk factor for it. No obvious genotype–phenotype association was observed. Conclusion: This study provides comprehensive analyses of the genetic and clinical characteristics of XLRS in a cohort of Chinese patients. The fourth de novo mutation in RS1 was identified. And we show that XLRS has a wide spectrum of clinical characteristics; hence, molecular diagnosis is crucial for its diagnosis, differential diagnosis and genetic counselling. Peripheral schisis is a risk factor for the high incidence of complications, and no clear genotype–phenotype correlations were found. [ABSTRACT FROM AUTHOR]

Diagnostic medical imaging plays an imperative role in clinical assessment and treatment of medical abnormalities. The fusion of multimodal medical images merges complementary information present in the multi‐source images and provides a better interpretation with improved diagnostic accuracy. This paper presents a CT–MR neurological image fusion method using an optimised biologically inspired neural network in nonsubsampled shearlet (NSST) domain. NSST decomposed coefficients are utilised to activate the optimised neural model using particle swarm optimisation method and to generate the firing maps. Low and high‐frequency NSST subbands get fused using max‐rule based on firing maps. In the optimisation process, a fitness function is evaluated based on spatial frequency and edge index of the resultant fused image. To analyse the fusion performance, extensive experiments are conducted on the different CT–MR neurological image dataset. Objective performance is evaluated based on different metrics to highlight the clarity, contrast, correlation, visual quality, complementary information, salient information, and edge information present in the fused images. Experimental results show that the proposed method is able to provide better‐fused images and outperforms other existing methods in both visual and quantitative assessments. [ABSTRACT FROM AUTHOR]

Diagnostic medical imaging plays an imperative role in clinical assessment and treatment of medical abnormalities. The fusion of multimodal medical images merges complementary information present in the multi-source images and provides a better interpretation with improved diagnostic accuracy. This paper presents a CT–MR neurological image fusion method using an optimised biologically inspired neural network in nonsubsampled shearlet (NSST) domain. NSST decomposed coefficients are utilised to activate the optimised neural model using particle swarm optimisation method and to generate the firing maps. Low and high-frequency NSST subbands get fused using max-rule based on firing maps. In the optimisation process, a fitness function is evaluated based on spatial frequency and edge index of the resultant fused image. To analyse the fusion performance, extensive experiments are conducted on the different CT–MR neurological image dataset. Objective performance is evaluated based on different metrics to highlight the clarity, contrast, correlation, visual quality, complementary information, salient information, and edge information present in the fused images. Experimental results show that the proposed method is able to provide better-fused images and outperforms other existing methods in both visual and quantitative assessments. [ABSTRACT FROM AUTHOR]

Objective: COVID‐19 diagnosis is a critical problem, mainly due to the lack or delay in the test results. We aimed to obtain a model to predict SARS‐CoV‐2 infection in suspected patients reported to the Brazilian surveillance system. Methods: We analysed suspected patients reported to the National Surveillance System that corresponded to the following case definition: patients with respiratory symptoms and fever, who travelled to regions with local or community transmission or who had close contact with a suspected or confirmed case. Based on variables routinely collected, we obtained a multiple model using logistic regression. The area under the receiver operating characteristic curve (AUC) and accuracy indicators were used for validation. Results: We described 1468 COVID‐19 cases (confirmed by RT‐PCR) and 4271 patients with other illnesses. With a data subset including 80% of patients from Sao Paulo (SP) and Rio Janeiro (RJ), we obtained a function which reached an AUC of 95.54% (95% CI: 94.41–96.67%) for the diagnosis of COVID‐19 and accuracy of 90.1% (sensitivity 87.62% and specificity 92.02%). In a validation dataset including the other 20% of patients from SP and RJ, this model exhibited an AUC of 95.01% (92.51–97.5%) and accuracy of 89.47% (sensitivity 87.32% and specificity 91.36%). Conclusion: We obtained a model suitable for the clinical diagnosis of COVID‐19 based on routinely collected surveillance data. Applications of this tool include early identification for specific treatment and isolation, rational use of laboratory tests, and input for modelling epidemiological trends. [ABSTRACT FROM AUTHOR]

Fitz‐Hugh‐Curtis syndrome should be suspected in sexually active young women presenting with acute right upper quadrant pain even in the absence of lower abdominal pain. The risk of radiation exposure associated with computed tomography should also be considered while making a diagnosis of abdominal pain in young patients. [ABSTRACT FROM AUTHOR]

With the wide applications of biomedical images in the medical field, the segmentation of biomedical images plays an important role in clinical diagnosis, pathological analysis, and medical intervention. Full convolutional neural networks, especially U‐net, have improved the performance of segmentation greatly in recent years. However, due to their regular geometric structure, the standard convolutions that they use are inherently limited in dealing with geometric transformations while biomedical objects have huge variations in shape and size. In this study, the authors propose the DRU‐net, which is a novel U‐net with deformable encoder and reshaping upsampling convolution decoder, for biomedical image segmentation. First, deformable convolutional networks are applied and improved to enhance the learning ability of the encoder for geometric transformations. Second, a novel upsampling method named reshape upsampling convolution is proposed for better‐restoring resolution and fusion features. Furthermore, focal loss is used to address class imbalance and model overwhelmed problems in biomedical image segmentation tasks. Theoretic analysis and experimental results have shown that the proposed algorithm not only reduces the number of parameters of U‐Net, but also achieves produces competitive results compared with the state‐of‐the‐art algorithms in terms of various quantitative measures on Drosophila electron microscopy dataset and Warwick‐QU dataset. [ABSTRACT FROM AUTHOR]

Medical image quality requirements have been increasingly stringent with the recent developments of medical technology. To meet clinical diagnosis needs, an effective medical image enhancement method based on convolutional neural networks (CNNs) and frequency band broadening (FBB) is proposed. Curvelet transform is used to deal with medical data by obtaining the curvelet coefficient in each scale and direction, and the generalised cross‐validation is implemented to select the optimal threshold for performing denoising processing. Meanwhile, the cycle spinning scheme is used to wipe off the visible ringing effects along the edges of medical images. Then, FBB and a new CNN model based on the retinex model are used to improve the processed image resolution. Eventually, pixel‐level fusion is made between two enhanced medical images from CNN and FBB. In the authors' study, 50 groups of medical magnetic resonance imaging, X‐ray, and computed tomography images in total have been studied. The experimental results indicate that the final enhanced image using the proposed method outperforms other methods. The resolution and the edge details of the processed image are significantly enhanced, providing a more effective and accurate basis for medical workers to diagnose diseases. [ABSTRACT FROM AUTHOR]

Background: Appropriate depression care is a cancer‐care priority. However, many cancer survivors live with undiagnosed and untreated depression. Prostate cancer survivors may be particularly vulnerable, but little is known about their access to depression care. The goal of this study was to describe patterns and predictors of clinical diagnosis and treatment of depression in prostate cancer survivors. Methods: Generalized estimating equations were used to evaluate indicators of self‐reported clinical diagnosis and treatment depression as a function of individual‐level characteristics within a longitudinal dataset. The data were from a population‐based cohort of North Carolinian prostate cancer survivors who were enrolled from 2004 to 2007 on the North Carolina‐Louisiana Prostate Cancer Project (N = 1,031), and prospectively followed annually from 2008 to 2011 on the Health Care Access and Prostate Cancer Treatment in North Carolina (N = 805). Results: The average rate of self‐reported clinical diagnosis of depression was 44% (95% CI: 39%‐49%), which declined from 60% to 40% between prostate cancer diagnosis and 5‐7 years later. Factors associated with lower odds of self‐reported clinical diagnosis of depression include African‐American race, employment, age at enrollment, low education, infrequent primary care visits, and living with a prostate cancer diagnosis for more than 2 years. The average rate of self‐reported depression treatment was 62% (95% CI: 55%‐69%). Factors associated with lower odds of self‐reported depression treatment included employment and living with a prostate cancer diagnosis for 2 or more years. Conclusion: Prostate cancer survivors experience barriers when in need of depression care. [ABSTRACT FROM AUTHOR]

Aiming at the lack of signal preprocessing in current rectal signal research, a new 15th‐order Newton iterative fast independent component analysis (FastICA) algorithm is proposed to separate the signal. To solve the incomplete problem of the single channel rectal pressure signal, C‐C phase space reconstruction technology is used for multi‐dimensional signal reconstruction. In order to achieve the diagnosis of rectal dynamic after artificial anal sphincter implantation, the preprocessed rectal signal component is subjected to short‐time Fourier transforms for time–frequency analysis. This constitutes a complete rectal dynamic function diagnosis process. The non‐stationary simulation signal is constructed to verify the preprocessing method. A complete diagnostic experiment is performed on two rectal signals of different gut dynamic. Simulation results show that the proposed method can realise the preprocessing of non‐stationary signals. Through the rectal dynamic function experiment based FastICA‐STFT, two different rectal signals are distinguished, and the results are consistent with the clinical diagnosis, which has achieved the diagnosis of rectal motility. This study will provide support for the recovery of rectal dynamic function in patients with artificial anal sphincter implants. [ABSTRACT FROM AUTHOR]

Abstract: Doctors occasionally make diagnoses in strangers outside of formal medical settings by using the medical skill of visual inspection, such as noticing signs of melanoma or the symptoms of hyperthyroidism. This may cause considerable moral unease and doubts on the side of the diagnosing physician. Such encounters force physicians to consider whether or not to intervene by introducing themselves to the stranger and offering an unsolicited medical opinion despite the absence of a formal doctor‐patient relationship. A small body of literature has addressed the topic of the unsolicited medical opinion, often with a primary focus on practical advice. This article seeks to establish an ethical‐theoretical basis for physicians' ethical obligation to offer an unsolicited medical opinion when they make a diagnosis by visual inspection in a stranger outside of the formal medical context. Using a utilitarian approach, it is argued that, if it is in the physicians' power to prevent a possible loss of well‐being, without thereby sacrificing anything of equal value, physicians have an ethical obligation to intervene. [ABSTRACT FROM AUTHOR]

Congenital hyperinsulinism (CHI) has been mostly associated with mutations in seven major genes. We retrospectively reviewed a cohort of 32 patients with CHI. Extensive mutational analysis (ABCC8, KCNJ11, GCK, GLUD1, HADH, HNF4A, and UCP2) was performed on Ion torrent platform, which could analyze hundreds of genes simultaneously with ultrahigh-multiplex PCR using up to 6144 primer pairs in a single primer pool and address time-sensitive samples with single-day assays, from samples to annotated variants, to identify the genetic etiology of this disease. Thirty-seven sequence changes were identified, including in ABCC8/KCNJ11 (n = 25, 65.7%), GCK (n = 2), HNF4A (n = 3), GLUD1 (n = 2), HADH (n = 4), and UCP2 (n = 1); these mutations included 14 disease-causing mutations, eight rare SNPs, 14 common SNPs, and one novel mutation. Mutations were identified in 21 of 32 patients (65.6%). Among the patients with an identified mutation, 14 had mutations in ABCC8, one of which was combined with a GLUD1 mutation. Four patients had mutations in KCNJ11, 1 had a GCK mutation, 1 had a mutation in HADH, and two had a mutation in HNF4A. Among the 32 patients, the age at the onset of hyperinsulinemia ranged from the neonatal period to 1 year of age; five patients underwent a pancreatectomy due to intractable hyperinsulinemia. This study describes novel and previously identified mutations in patients with CHI. The spectrum of mutations in CHI patients represents an important tool for the diagnosis and prognosis of CHI patients in the Chinese population as well as for the genetic counseling of CHI families. [ABSTRACT FROM AUTHOR]

The most widely used clinical technique for estimating bone movements in knee joints with acceptable accuracy utilises implantation of heavy metallic beads into the bones. These small metallic objects become visible as highly contrasting features in captured radiographs, thus facilitating post kinematic assessment of bones in human joints with pinpoint accuracy. Although, this approach provides necessary precision for clinical diagnosis, pre‐ and post‐surgery planning for restoring joint function and locomotion, however, this approach also incurs high degree of invasiveness. In this study, a novel optical sensor is proposed for use in non‐invasive motion measurement of knee joints in three‐dimensional (3D) space. The approach is based on 3D angle‐of‐arrival (AoA) estimation using image processing procedures on the two‐dimensional images of sensor's aperture shadows. The novelty of the sensor in terms of design, operation and its potential applications for a wide range of possibilities including precise AoA estimation for unconstrained 3D motion analysis of knee joints is described. Finally, error analysis of the sensor's AoA measurement uncertainty is provided for different incident angles of optical beams, which demonstrates the potential of the sensor not only for high‐precision motion analysis of human joints; however, for other motion and position‐aware systems. [ABSTRACT FROM AUTHOR]

Background Several risk factors already have been determined for dogs with degenerative mitral valve disease ( DMVD). Risk factors often have been considered in isolation and have not always taken into account additional information provided by the history and physical examination ( PE). Hypothesis/Objectives Data obtained from history and PE of dogs with DMVD provide prognostic information and can be used for risk stratification. Animals Client-owned dogs (n = 244) with DMVD recruited from first opinion practice. Methods Prospective longitudinal follow-up of dogs with DMVD. History and PE data were obtained at 6-month intervals and analyzed with time-dependent Cox models to derive relative risk of cardiac death. Independent hazard ratios were used to derive a clinical severity score ( CSS), the prognostic value of which was evaluated by analyzing the median survival times for different risk groups and ROC analysis. Analysis of the progression of CSS over time also was undertaken. Results History of cough, exercise intolerance, decreased appetite, breathlessness (difficulty breathing) and syncope with PE findings of heart murmur intensity louder than III/VI and absence of respiratory sinus arrhythmia were independently associated with outcome and allowed development of the CSS. Clinical severity score distinguished groups of dogs with significantly different outcomes. Conclusions and Clinical Importance Routinely obtained clinical findings allow risk stratification of dogs with DMVD. Results of ancillary diagnostic tests may be complementary to history and PE findings and always should be interpreted in conjunction with these findings. [ABSTRACT FROM AUTHOR]

Tissue classification using computer aided diagnosis can help automated decision making to aid clinical diagnosis. Classification of breast tissue based on spectral features of impedance loci has frequently been done to classify malignant tissue with further requirement of more complex classification methodologies needed to improve the characterisation. In current study, tissue classification is done using in vivo electrical impedance data of 18 human subjects, from four quadrants of breast, palm, nail, arm, bicep and classified using algorithms involving machine learning methodologies, specifically support vector machines (SVMs) that are supervised learning models. They consist of learning algorithms based on the principal of structural risk minimisation. Two methodologies of SVM have been used in this study: with data binning and data pruning and without data binning and data pruning. Data binning and data pruning have improved the sensitivity of the SVM from 76.76 to 89.23%, but the specificity has decreased from 76.23 to 74.15%. This is a pilot study towards testing the reliability of the developed electrical impedance measuring system and developing a data mining‐based decision making system into an electrical impedance spectroscopy system, to help users (physicians) with tissue classification leading to reliable objective decision making. [ABSTRACT FROM AUTHOR]